pmid stringlengths 8 8 | pmcid stringlengths 8 11 ⌀ | source stringclasses 2
values | rank int64 1 9.78k | sections unknown | tokens int64 3 46.7k |
|---|---|---|---|---|---|
22092030 | null | s2 | 5,230 | {
"abstract": "Magnetotactic bacteria (MB) are remarkable organisms with the ability to exploit the earth's magnetic field for navigational purposes. To do this, they build specialized compartments called magnetosomes that consist of a lipid membrane and a crystalline magnetic mineral. These organisms have the potential to serve as models for the study of compartmentalization as well as biomineralization in bacteria. Additionally, they offer the opportunity to design applications that take advantage of the particular properties of magnetosomes. In recent years, a sustained effort to identify the molecular basis of this process has resulted in a clearer understanding of the magnetosome formation and biomineralization. Here, I present an overview of MB and explore the possible molecular mechanisms of membrane remodeling, protein sorting, cytoskeletal organization, iron transport, and biomineralization that lead to the formation of a functional magnetosome organelle."
} | 240 |
37440632 | null | s2 | 5,231 | {
"abstract": "The domestication of forest trees for a more sustainable fiber bioeconomy has long been hindered by the complexity and plasticity of lignin, a biopolymer in wood that is recalcitrant to chemical and enzymatic degradation. Here, we show that multiplex CRISPR editing enables precise woody feedstock design for combinatorial improvement of lignin composition and wood properties. By assessing every possible combination of 69,123 multigenic editing strategies for 21 lignin biosynthesis genes, we deduced seven different genome editing strategies targeting the concurrent alteration of up to six genes and produced 174 edited poplar variants. CRISPR editing increased the wood carbohydrate-to-lignin ratio up to 228% that of wild type, leading to more-efficient fiber pulping. The edited wood alleviates a major fiber-production bottleneck regardless of changes in tree growth rate and could bring unprecedented operational efficiencies, bioeconomic opportunities, and environmental benefits."
} | 247 |
35304743 | PMC9310579 | pmc | 5,232 | {
"abstract": "Abstract Reciprocal adaptation between hosts and symbionts can drive the maintenance of symbioses, resulting in coevolution and beneficial genotypic interactions. Consequently, hosts may experience decreased fitness when paired with nonsympatric partners compared to sympatric symbionts. However, coevolution does not preclude conflict—host and symbiont can act to advance their own fitness interests, which do not necessarily align with those of their partner. Despite coevolution's importance in extant symbioses, we know little about its role in shaping the origin of symbioses. Here, we tested the role of coevolution in establishing a novel association by experimentally (co)evolving a host with a protective bacterium under environmental stress. Although evolution in the presence of nonevolving bacteria facilitated host adaptation, co‐passaged hosts did not exhibit greater adaptation rates than hosts paired with nonevolving bacteria. Furthermore, co‐passaged hosts exhibited greater fecundity when paired with sympatric, co‐passaged bacteria compared to co‐passaged bacteria with which they did not share an evolutionary history. Thus, shared evolutionary history between the hosts and microbes actually reduced host fitness and has the potential to impede evolution of new beneficial associations.",
"discussion": "Discussion Coevolution has been shown to be a major contributing factor in shaping mutualistic interactions between hosts and their symbionts across a wide range of symbioses (Suen et al. 2011 ; Heath et al. 2012 ; Murfin et al. 2015 ; Wilson and Duncan 2015 ; Parker et al. 2017 ; Gabay et al. 2019 ; Rekret and Maherali 2019 ). However, the importance of coevolution in the early stages of nascent associations remains to be elucidated. In this study, we leveraged the amenability of C. elegans nematodes to evolution experiments and directly tested how co‐passaging of host and bacteria can impact host evolution. We hypothesized that specificity would evolve between partners sharing an evolutionary history, such that fitness gains could be obtained only when hosts were paired with their respective bacteria. Although we found that host–bacteria specificity did arise from co‐passaging, these bacteria conferred less fitness benefits toward their sympatric hosts. More specifically, our results suggest that co‐passaged hosts had the potential to exhibit greater fecundity after heat stress, but they were impeded from doing so due to association with their bacterial partners. Our selection regime during experimental evolution involved extracting bacteria from hosts that survived exposure to heat stress and then exposing the next generation of hosts to those bacterial genotypes. Co‐passaged bacteria benefitted if their hosts survived heat shock, providing opportunities for both horizontal and vertical transmission to the next generation of hosts. Our system may thus be representative of symbioses in nature where symbionts that are predominantly horizontally transmitted depend on host survival. For example, Steinernema nematodes form a mutualism with Xenorhabdus bacteria, where both partners depend on each other's survival to parasitize insect hosts. Multiple juvenile nematodes infect the same insect, and thus both vertical and horizontal transmission of Xenorhabdus can occur (Goodrich‐Blair 2007 ). Another example is arbuscular mycorrhizal fungi, which are horizontally transmitted and obligately dependent on their plant hosts (Raven 2010 ). In these symbioses, the fungus is reliant on the survival of its host for production of organic carbon. The dependency of these symbionts on the survival of their hosts may thus favor more robust hosts able to withstand environmental stressors, but, from the perspective of the symbiont, there is not necessarily a benefit for increased plant reproduction. Indeed, symbionts have been shown to improve one aspect of host fitness at the cost of another (Rudgers et al. 2012 ), and the evolution of mutualism may depend on the improved survival and decreased fecundity of interacting species (Fukui 2014 ). Within our experiment, co‐passaged bacteria improved host survival compared to the ancestral bacteria (Fig. 3a ), but there was little incentive for the bacteria to promote host reproduction because the bacteria was not always transmitted directly from mother to offspring. Our findings suggest that the co‐passaged bacteria were acting in their own selfish interests, potentially improving host survival at the cost of host reproduction. Singly passaged hosts, by contrast, did not necessarily need to survive for an extended period of time as much as they needed to reproduce to increase their fitness during our experiment. Previous work had indeed found that hosts adapted readily when the bacteria was not evolving (Hoang et al. 2021 ). If given the chance to evolve first and adapt to the bacteria, the host evolved to gain more benefit from its partner. Thus, coevolving with a new microbial partner in a stressful environment may actually limit the ability of hosts to expand their niche if fitness interests are not aligned. Previous work between C. elegans and its bacterial pathogen, Serratia marcescens , found classic patterns of host–parasite specificity, where host mortality was greater when hosts were paired with their sympatric parasite (Morran et al. 2014 ). We expected the reverse to be true for sympatric, beneficial microbes. Although host and bacteria exhibited specificity in our study, the results were contrary to expectations due to sympatric bacteria being the least beneficial in terms of host reproduction. Furthermore, there was no clear pattern in terms of host survival at the population level (Fig. 3c ), suggesting that co‐passaging did not have as large an impact on this fitness component. By contrast, two host populations produced significantly more offspring with allopatric bacteria than with sympatric bacteria (a third population was marginally significant), indicating that co‐passaged populations are diverging from one another with regard to reproduction (Table 1 ). Specifically, co‐passaged bacteria provided little reproductive benefits toward their sympatric hosts (Fig. 3d ), preventing hosts from reaching their evolutionary potential. Indeed, as hosts become trapped in interactions with their bacteria, it may be difficult for them to gain a significant benefit, constraining their ability to adapt to a stressful environment. Because reproduction is a critical component of an organism's fitness, we argue that co‐passaging led to detrimental effects for the host. In contrast, based on assays of bacterial abundance, we cannot identify a clear beneficial nor detrimental effect for the bacteria, though this measure was conducted at one point in evolutionary time and may not fully capture the dynamic process of coevolution between hosts and bacteria. Table 1 Fine‐scale sympatric versus allopatric test Measurement Sympatric Allopatric Chi‐square df \n P \n Greater survival/fecundity Survival B1 and H1 B1 and H2–H5 3.23 1 0.07 Sympatric (marginally) H1 and B2–B5 B2 and H2 B2 and H1, H3–H5 5.76 1 0.02* Allopatric H2 and B1, B3–B5 B3 and H3 B3 and H1, H2, H4, H5 0.89 1 0.35 Neither H3 and B1, B2, B4, B5 B4 and H4 B4 and H1–H3, H5 2.34 1 0.13 Neither H4 and B1–B3, B5 B5 and H5 B5 and H1–H4 0.12 1 0.73 Neither H5 and B1–B4 Fecundity B1 and H1 B1 and H2–H5 4.73 1 0.03 Allopatric H1 and B2–B5 B2 and H2 B2 and H1, H3–H5 2.02 1 0.15 Neither H2 and B1, B3–B5 B3 and H3 B3 and H1, H2, H4, H5 0.007 1 0.93 Neither H3 and B1, B2, B4, B5 B4 and H4 B4 and H1–H3, H5 3.72 1 0.05 Allopatric (marginally) H4 and B1–B3, B5 B5 and H5 B5 and H1–H4 7.35 1 0.007 Allopatric H5 and B1–B4 John Wiley & Sons, Ltd. We hypothesize that hosts did not maintain or had run out of genetic variation to combat their co‐passaged partners and may have reached their short‐term adaptative potential. Even though the ancestral host population started with standing genetic variation, it was composed of a low percentage of males. Because sperm is more heat sensitive than oocytes (Gouvêa et al. 2015 ), we observed little to no males by approximately generation 10 in most experimental evolution treatments. Combined with the bottleneck hosts underwent from repeated heat shock selection, these events would lead to a drastic decrease in host genetic diversity. An influx of genetic variation, such as through gene flow or genetic recombination, may help hosts keep up with their bacteria (Stoy et al. 2020 ). Although theory suggests that evolutionary rates can affect the evolution of beneficial associations, such that the slower evolving partner obtains more benefits (Bergstrom and Lachmann 2003 ), our study suggests that, at least for the evolution of a novel beneficial association, evolving quickly could be better for some hosts. Reciprocal selection between hosts and symbionts has allowed hosts to adapt to diverse conditions, maximizing the benefits that they can obtain from their symbionts (Murfin et al. 2015 ; Niepoth et al. 2018 ; Gabay et al. 2019 ; Rekret and Maherali 2019 ). From extant symbioses, we can infer that harboring protective microbes would facilitate host adaptation to stressful environments, thus establishing new associations between host and microbe. Previous work found that hosts can adapt to heat stress by being exposed to a nonevolving protective bacterium. Here, we demonstrate that co‐passaging of host and microbe does not accelerate host adaptation. Unexpectedly, co‐passaging resulted in reduced fitness for hosts paired with their sympatric bacteria, indicating that these bacteria evolved to provide the least benefits toward their partners. Our findings provide direct evidence that coevolution does not have to underlie beneficial associations (Moran and Sloan 2015 ), and highlight the potential for conflicts to arise between partners. Such conflicts can persist even after a long evolutionary history (Chong and Moran 2016 ). One way out of this conflict may be for hosts to acquire genetic variation, through sexual recombination or gene flow, for example, in order to respond to their quick evolving partner, allowing them to gain an advantage similar to that of hosts passaged with nonevolving bacteria. Overall, our study sheds light on the fitness consequences for hosts when they are tightly coupled to their bacteria in a nascent interaction, suggesting that reciprocal selection between partners may impede the establishment of novel beneficial associations despite the benefits it brings to established long‐term symbioses."
} | 2,659 |
34272801 | PMC8633507 | pmc | 5,234 | {
"abstract": "Summary Soil‐borne microbes can establish compatible relationships with host plants, providing a large variety of nutritive and protective compounds in exchange for photosynthesized sugars. However, the molecular mechanisms mediating the establishment of these beneficial relationships remain unclear. Our previous genetic mapping and whole‐genome resequencing studies identified a gene deletion event of a Populus trichocarpa lectin receptor‐like kinase gene PtLecRLK1 in Populus deltoides that was associated with poor‐root colonization by the ectomycorrhizal fungus Laccaria bicolor . By introducing PtLecRLK1 into a perennial grass known to be a non‐host of L. bicolor , switchgrass ( Panicum virgatum L.), we found that L. bicolor colonizes ZmUbipro‐PtLecRLK1 transgenic switchgrass roots, which illustrates that the introduction of PtLecRLK1 has the potential to convert a non‐host to a host of L. bicolor . Furthermore, transcriptomic and proteomic analyses on inoculated‐transgenic switchgrass roots revealed genes/proteins overrepresented in the compatible interaction and underrepresented in the pathogenic defence pathway, consistent with the view that pathogenic defence response is down‐regulated during compatible interaction. Metabolomic profiling revealed that root colonization in the transgenic switchgrass was associated with an increase in N‐containing metabolites and a decrease in organic acids, sugars, and aromatic hydroxycinnamate conjugates, which are often seen in the early steps of establishing compatible interactions. These studies illustrate that PtLecRLK1 is able to render a plant susceptible to colonization by the ectomycorrhizal fungus L. bicolor and shed light on engineering mycorrhizal symbiosis into a non‐host to enhance plant productivity and fitness on marginal lands.",
"conclusion": "Conclusion The data presented here provide a comprehensive picture of the dynamic changes in transcription, translation, and the concomitant alterations in the level of metabolites that occurred in L. bicolor colonization of switchgrass transgenic plant roots under the regulation of a poplar lectin receptor‐like kinase, PtLecRLK1. Specifically, our data indicated that introduction of PtLecRLK1 into a switchgrass plant alters its susceptibility to fungal colonization by up‐regulating the compatible interaction‐related genes/proteins and metabolites (i.e. nutrient assimilation, carbohydrate metabolism, cell cycle organization, and cell wall organization related molecules, and free amino acids) and by down‐regulating defence‐related genes/proteins and metabolites (i.e. jasmonic acid and ethylene synthesis molecules, organic acids) in response to L. bicolor inoculation. The down‐regulation of defence‐related genes/proteins and metabolites were also observed when poplar trees and PtLecRLK1 transgenic Arabidopsis are colonized by L. bicolor . Despite the down‐regulation, there is no evidence of compromising the plant’s ability to defend against pathogens. It is also worth investigating the influences of PtLecRLK1 and L. bicolor on both the compatible AMF colonization and the pathogenic interaction with switchgrass in future studies. The current results were obtained from greenhouse experiments and analyses of the molecular‐level regulation. It would be interesting to explore the long‐lasting compatible relationship between switchgrass and L. bicolor in field conditions by focussing on the symbiosis‐related physiological traits in the future studies. The present study also provides a basis for further in‐depth investigation of the signal transduction mechanisms underlying PtLecRLK1 ‐mediated L. bicolor colonization, and builds a foundation for fine‐tuning the engineering of a long‐lasting compatible relationship between the ectomycorrhizal fungus, L. bicolor, and a perennial C4 biofuel crop to improve sustainable switchgrass production on marginal lands.",
"introduction": "Introduction In natural ecosystems, ectomycorrhizal soil fungi can form symbiotic relationships with the roots of most temperate forest trees (Horan et al ., 1988 ). During the establishment of ectomycorrhizae (ECM), fungi colonize the plant root with the fungal hyphae penetrating the root from the root cap towards the epidermis and cortical tissue. The hyphal layer sheathes the root tip to form mantle structures, and the internal hyphae grow between the root epidermal and cortical cells to form a network called the Hartig net (Blasius et al ., 1986 ; Horan et al ., 1988 ). Through these physical structures, plants and fungi interact mutualistically; fungi provide water and a large variety of nutrients to host plants in exchange for photosynthesized sugars from the host (Smith and Read, 2010 ). Ectomycorrhizal fungi, Laccaria bicolor in particular, have attracted considerable attention over the past several years, because they are axenically cultivable, possess plant growth‐promoting characteristics, have a sequenced genome, and contribute several other benefits to their hosts (Felten et al ., 2009 ; Martin et al ., 2008 ; Smith and Read, 2010 ). For example, a previous report demonstrated that L . bicolor could stimulate lateral root growth in poplar ( Populus sp.) and Arabidopsis by regulating auxin signalling (Felten et al ., 2009 ). Furthermore, L. bicolor moderates the effects of phosphorus limitation in poplar by partitioning carbon between carbohydrates and secondary metabolites, whilst sustaining phosphorus uptake and translocation (Shinde et al ., 2018 ). In addition to modulating plant nutrition, ECMs activate stress‐related genes and signalling pathways that confer abiotic stress tolerance in poplar (Luo et al ., 2009 ). Given that the establishment of ECM requires the interchange of signals between both partners in the symbiosis, identification of the primary factors that regulate the establishment of symbiosis is essential for understanding the role of ECM in plant development and physiology. Previous studies have shown that effector‐type small secreted proteins (SSPs) were present in both L. bicolor and its host plant poplar and are important in establishing the ectomycorrhizal symbiosis (Martin et al ., 2008 ; Pellegrin et al ., 2019 ; Plett et al ., 2011 , 2017 ). Further genetic mapping and resequencing in poplar identified a whole gene deletion event of a lectin receptor‐like kinase encoding gene PtLecRLK1 that was associated with a decrease in colonization by L. bicolor (Labbé et al ., 2019 ). Lectin receptor‐like kinases (LecRLKs) are a group of cell‐surface receptors characterized by an extracellular lectin domain, a transmembrane domain, and an intracellular kinase domain (Bouwmeester and Govers, 2009 ; Herve et al ., 1996 ). LecRLKs are known to be involved in plant innate immunity (Singh and Zimmerli, 2013 ; Wang and Bouwmeester, 2017 ). The LecRLK from Arabidopsis, LecRK‐VI.2 was shown to be a mediator of the Arabidopsis pattern‐triggered immunity response (Singh et al ., 2012 ). Arabidopsis LecRK‐a1 was induced during senescence, wounding and in response to oligogalacturonic acid stress (Riou et al ., 2002 ). Arabidopsis LekRK‐I.9 was demonstrated to bind to the integrin ligand present in the oomycete effectors IPI‐O, thereby, contributing to disease resistance and maintaining robust cell wall‐plasma membrane integrations during Phytophthora infestans infection (Bouwmeester et al ., 2011 ). The expression of a poplar LecRLK, PnLPK , was induced by wounding, and the phosphorylation activity of PnLPK was increased in the presence of divalent metal cations (Nishiguchi et al ., 2002 ). Moreover, Nicotiana benthamiana NbLRK1 interacted with Phytophthora infestans INF1 elicitor and mediated INF1‐induced cell death (Kanzaki et al ., 2008 ). In Nicotiana attenuata , LecRK1 was reported to suppress insect‐mediated inhibition of defence responses during Manduca sexta herbivory (Gilardoni et al ., 2011 ). To date, most studies on RLKs have been performed in herbaceous model plants and focussed on their roles in plant responses to abiotic and biotic stresses, with only a few studies reported on the RLKs in perennial plants such as switchgrass ( Panicum virgatum L.). For example, Gill et al . ( 2018 ) reported that the expression of a switchgrass RLK gene was increased when using phosphite to inhibit diseases caused by oomycetes. Yongfeng et al . ( 2018 ) reported that a gene encoding cysteine‐rich RLK caused delayed flowering time in switchgrass. Unlike annual plants, which need tilling and replanting each year, perennial plants, such as poplar trees and switchgrass plants, retain their aboveground biomass, and their roots exhibit relatively higher soil microbe diversity and long‐lasting relationships with beneficial microbes (Glover et al ., 2010 ). Annual crops can lose five times as much water and 35 times more nitrate than perennial plants (Randall et al ., 1997 ). Therefore, perennial plants can improve soil nutrient and water conservation, creating more sustainable ecosystems (Vukicevich et al ., 2016 ). Due to such traits, perennial plants, including poplar and switchgrass, are being developed as major biomass feedstocks (Ma et al ., 2000 ). However, to improve economic viability, these bioenergy crops are expected to grow on marginal lands so that they do not compete with food crops growing on limited prime agricultural lands. There is a need to improve the fitness of bioenergy crops for growing conditions on marginal lands. A potential way to accomplish this is to engineer beneficial mycorrhization into bioenergy crops, given that increasing evidence has shown that the beneficial mycorrhization can promote plant nutrient acquisition and improve plant performance under abiotic stress. Switchgrass is known to be strongly dependent on arbuscular mycorrhizal fungi (AMF). Sun et al . ( 2018 ) reported that the inoculation of AMF increased switchgrass biomass and phosphorus (P) concentration in the cadmium‐contaminated soil. Schroeder‐Moreno et al . ( 2012 ) reported that AMF aided switchgrass nitrogen (N) assimilation in a high temperature and high N‐content environment. However, there are only a few studies reporting the relationship of switchgrass with ectomycorrhizal fungi. Ghimire et al . reported that ectomycorrhizal fungus Sebacina vermifera could enhance seed germination and biomass production in switchgrass under drought conditions (Ghimire et al ., 2009 ; Ghimire and Craven, 2011 ), but the underlying molecular mechanisms remain unclear. Our previous genomic and genetic studies reported that the lack of colonization of P . deltoides by ectomycorrhizal fungus L. bicolor was associated with a PtLecRLK1 locus deletion (Labbé et al ., 2019 ). PtLecRLK1 introduction into the non‐host, Arabidopsis, enabled the colonization of L. bicolor in the PtLecRLK1 transgenic Arabidopsis root, and was associated with the down‐regulation of plant defence‐related genes and metabolites, thus supporting the role of PtLecRLK1 in mediating plant‐ L. bicolor interactions (Labbé et al ., 2019 ). To explore the possibility of greater utilization of switchgrass in marginal environments via ectomycorrhization, and to better understand the role of PtLecRLK1 in mediating plant‐ L. bicolor interactions, we hypothesized that introducing PtLecRLK1 into non‐host switchgrass would enable colonization by L. bicolor . By characterizing the fungal colonization and molecular responses of L. bicolor ‐inoculated ZmUbipro‐PtLecRLK1 transgenic switchgrass roots, we demonstrated that the introduction of PtLecRLK1 allows the colonization of L. bicolor into switchgrass roots by altering the molecular responses at the transcriptional, translational, and metabolic levels. The initiative to engineer a long‐lasting beneficial relationship between switchgrass and the ectomycorrhizal fungus, L. bicolor , could maximize the utility and productivity of this important bioenergy crop for growth on marginal lands and in stressed environments.",
"discussion": "Results and Discussion In order to promote L. bicolor root colonization in a non‐host plant, we generated transgenic plants by heterologously expressing ZmUbipro‐PtLecRLK1 in switchgrass (a non‐host of L. bicolor ). Four switchgrass transgenic lines (i.e. 5007, 5012, 5016 and 5031) expressing ZmUbipro‐PtLecRLK1 were verified by RT‐PCR (Figure S1a ) and RNAseq (Figure S1b ) analyses and used in the present study. Ectomycorrhizal development in switchgrass As a non‐host of L . bicolor , the wild‐type (WT) switchgrass roots had only a thin layer of L. bicolor hyphae loosely attached to the surface with no penetration between the root epidermal cells (Figure 1a,c ). In contrast, the ZmUbipro‐PtLecRLK1 transgenic switchgrass roots developed typical ECM structures, including swelling in the root tip, and formation of the hyphal Hartig net between plant cells that extended beyond epidermal cells (Figure 1b,d ). These results support our hypothesis that introduction of PtLecRLK1 renders non‐host (switchgrass) receptive to colonization by L . bicolor . Figure 1 \n Laccaria bicolor colonization in roots of wild‐type switchgrass ( Panicum virgatum L., genotype ‘NFCX01’) and ZmUbipro‐PtLecRLK1 transgenic switchgrass. (a) Dual fluorescence‐stained transverse root section of WT switchgrass. (b) Dual fluorescence‐stained transverse root section of ZmUbipro‐PtLecRLK1 transgenic switchgrass. (c) and (d) Zoom‐ins from (a) and (b). Green colour represents the UVitex stained fungi cell; Purple colour shows the propidium iodide stained root cell. RC, Root cap; Co, Cortex; Ep, epidermis; HN, Hartig net. Images shown are representative images from three experiments. Bars = 5 μm. Performance of ZmUbipro‐PtLecRLK1 transgenic switchgrass under phosphorus limitation with L. bicolor inoculation Ray et al . ( 2020 ) reported that the AMF Serendipita vermifera ssp. Bescii promoted the growth of winter wheat under P‐limitation. Therefore, we aimed to investigate whether the transgene ZmUbipro‐PtLecRLK1 ‐induced colonization of L. bicolor would be beneficial to switchgrass growth under nutrient limitation. The plant height, tiller numbers, and tiller dry weight were measured after 2 months of co‐culturing with L. bicolor under the control condition and under the phosphorus (P) limitation condition. As the three‐way ANOVA analysis shows in Table S1 , the transgene, L. bicolor inoculation, P‐limitation treatment and the interactions amongst them did not impact plant dry weight. The transgene and P‐limitation treatment interaction caused significant differences in plant height. Under the control‐inoculation condition, WT plants were taller than transgenic plants. However, this difference disappeared under the P‐limitation inoculation condition (Figure S2a ). The P‐limitation condition suppressed the height of WT plants, but not the transgenic plants with L. bicolor inoculation. The transgene was also shown to be the main factor causing significantly more tiller numbers in one of the transgenic lines (line 5016) (Figure S2b ). Collectively, L. bicolor ‐inoculated‐transgenic plants tended to be more tolerant to P‐limitation than the WT plants. A comprehensive evaluation of the influence of L. bicolor inoculation on the performance of the transgenic plants would require field studies with larger sample size and longer inoculation time. Transcript profiling of switchgrass roots during early interaction with L. bicolor \n Given that switchgrass is a non‐host of L. bicolor , we wanted to explore the underlying molecular mechanisms mediating switchgrass‐ L. bicolor interaction, and identify molecular processes that are associated with L. bicolor colonization in the ZmUbipro‐PtLecRLK1 transgenic switchgrass. We aimed to uncover the molecular determinants of colonization towards the ultimate goal of mycorrhizal symbiosis engineering. The transcript profiles of WT and ZmUbipro‐PtLecRLK1 transgenic switchgrass roots with L. bicolor inoculation and mock inoculation at 2 months after inoculation (MAI) were generated. This time point corresponded to the penetration of L. bicolor fungal hyphae and formation of the Hartig net between the epidermal cells (Figure 1 ). Whole roots (containing a mixture of ECM and non‐ECM roots) were collected for RNA extraction. Principal component analysis, where PC1 and PC2 explained 80% of the variance, revealed genes from the different conditions forming distinct clusters (Figure 2a ). There was little variation between the two mock conditions in the WT and the transgenic clusters, whereas differences between the inoculated and the mock conditions and between inoculated‐WT and inoculated‐transgenics varied drastically. These differences were also revealed by the following pairwise comparisons amongst the four conditions. Pairwise comparisons between inoculated‐WT and mock‐WT, between inoculated‐transgenic and mock‐transgenic, between mock‐transgenic and mock‐WT, and between inoculated‐transgenic and inoculated‐WT showed 10,130, 6,506, 871, and 6,864 differentially expressed genes (DEGs), respectively, at an absolute fold change ≥2, FDR<0.05 (Figure 2b , Table S2 ). Laccaria bicolor inoculation in WT switchgrass caused the highest degree of gene regulation (10, 130), whilst the ZmUbipro‐PtLecRLK1 transgene caused the least gene regulation (871). These transcriptomic responses implied that the biotic stimulus (i.e. L. bicolor inoculation) impacted transcriptional regulation more during switchgrass‐microbe interaction than the introduction of an exogenous gene (i.e. PtLecRLK1 ). Figure 2 Transcriptomic analysis of switchgrass root samples in response to Laccaria bicolor inoculation. (a) Principal component analysis of gene expression patterns for four conditions of switchgrass samples. (b) Venn diagram showing the number of differentially expressed genes (DEGs) from pair comparisons between different conditions. (c) Overview of the enriched metabolic pathways of DEGs resulting from comparison between IN‐WT and M‐WT. (d) Overview of the enriched metabolic pathways of DEGs resulting from comparison between IN‐trans and IN‐WT. The red and blue colours indicate the log2 fold change of DEGs, showing up‐ or down‐regulated genes, respectively. The metabolic pathways were generated with MapMan software. IN‐trans, M‐trans, IN‐WT, and M‐WT are abbreviations for inoculated‐transgenic, mock‐transgenic, inoculated‐WT, and mock‐WT, respectively. Through analysing the DEGs from comparison between L. bicolor ‐inoculated WT and mock‐WT, we aimed to identify the transcriptional regulation of a typically non‐host plant, switchgrass, in response to the biotic stimulus‐ L. bicolor inoculation. There were 5,826 and 4,303 genes down‐ and up‐regulated, respectively. To explore the function of these DEGs, Gene Ontology (GO) enrichment analysis and MapMan analysis were performed to classify these DEGs. The GO enrichment analysis suggested these genes were overrepresented in transcriptional regulation, RNA biosynthesis, and metabolic and ammonium transportation processes, and underrepresented in photosynthesis, phosphorylation, phosphorous, glucan, polysaccharide, and carbohydrate metabolic processes (Figure S3a ). The MapMan analysis revealed that up‐regulated genes were involved in redox homeostasis and down‐regulated genes were involved in carbohydrate metabolism, cell wall organization, cell cycle organization, and nutrient uptake process (Figure 2c ). Having established the baseline transcriptomic responses to L . bicolor inoculation in the non‐host switchgrass, we wanted to further examine how introduction of PtLecRLK1 impacted these transcriptomic responses in the inoculated switchgrass transgenic plants. Thus, we compared the inoculated‐transgenic sample with the inoculated‐WT sample. With GO enrichment analysis, we found that 3,896 up‐regulated genes were enriched in reproductive processes, phosphorylation, phosphorus metabolic, and macromolecule modification. Those 2968 down‐regulated genes were overrepresented in response to water, abiotic stimuli, inorganic substance responses, and negative regulation of the mitotic cell cycle (Figure S3b ). The following MapMan analysis on these DEGs from the comparison between inoculated‐transgenic and inoculated‐WT indicated a trend contrary to that from the comparison between inoculated‐WT and mock‐WT plants. Redox homeostasis showed a decreasing trend, whereas carbohydrate metabolism, cell wall organization, secondary metabolites, cell cycle regulation, and nutrient uptake processes showed an increasing trend overall (Figure 2d ). It is well‐known that the life cycle of mycorrhizal fungi depends on the uptake of carbon from the host plant, and in return, they export nitrogen, phosphorus and minerals to plants (Bonfante and Genre, 2010 ). Compared to the inoculated‐WT, the genes of inoculated‐transgenic plants associated with nutrient uptake and carbohydrate metabolism were up‐regulated, suggestive of the plausibility of nutrient exchange between the two organisms. Felten et al . ( 2009 ) reported that the cell wall related and cell cycle related gene regulations increased in poplar— L. bicolor and Arabidopsis— L. bicolor interactions. The increased cell wall organization and cell cycle organization in inoculated‐transgenic switchgrass supported the feasibility of physical interaction between the two organisms. In summary, the transcriptomic analyses in switchgrass indicated that the introduction of PtLecRLK1 into switchgrass altered its compatibility with L. bicolor . To better understand the function of PtLecRLK1 in mediating the interaction between switchgrass and L. bicolor , DEGs related to the biotic stress pathway and the nutrient uptake process were analysed in switchgrass responding to L. bicolor‐ only (inoculated‐WT vs. mock‐WT), and that responding to L. bicolor + transgene (inoculated‐transgenics vs inoculated‐WT) (Tables S3 and S4 ). The major difference between DEGs related to biotic stress was the recognition between the two organisms (switchgrass and L. bicolor ), which was represented by the categories of cytoskeleton organization, cell wall organization, and external stimuli response (Figure 3a–d ). DEGs from plants responding to L. bicolor ‐only included 17 up‐ and 45 down‐DEGs belonging to cytoskeleton organization, 39 up‐ and 163 down‐DEGs belonging to cell wall organization, and 0 up‐ and 4 down‐DEGs involved in external stimuli response (Figure 3c ). DEGs from plants responding to L. bicolor + transgene included 14 up‐ and 13 down‐DEGs belonging to cytoskeleton organization, 45 up‐ and 30 down‐DEGs belonging to cell wall organization, and 7 up‐ and 1 down‐DEGs involved in external stimuli response (Figure 3d ). In terms of nutrient uptake related DEGs, there were 13 up‐ and 7 down‐ DEGs related to nitrogen assimilation, 5 up‐ and 2 down‐ DEGs related to sulphur assimilation, 1 up‐ and 7 down‐ DEGs related to phosphorus assimilation, 14 up‐ and 19 down‐ DEGs related to iron uptake, and 1 up‐ and 1 down‐ DEGs related to copper uptake in response to L. bicolor ‐only (Figure 3e ). DEGs from plants responding to L. bicolor + transgene showed 4 up‐ and 2 down‐ DEGs related to nitrogen assimilation, 5 up‐ and 2 down‐DEGs related to phosphorus assimilation, 9 up‐ and 6 down‐DEGs related to iron uptake, and 2 up‐ and 1 down‐DEGs related to copper uptake (Figure 3f ). There were 15 nutrient uptake related genes regulated in both of the comparisons (inoculated‐WT vs. mock‐WT and inoculated‐transgenics vs. inoculated‐WT), 9 out of 15 genes were up‐regulated in response to L . bicolor + transgene, and 5 genes were up‐regulated in response to L. bicolor ‐only (Figure S4 ). Overall, the data showed higher ratios of up‐ to down‐ DEGs related to biotic stress and nutrient uptake from plants responding to L . bicolor + transgene than those responding to L. bicolor ‐only. The data suggest that the introduction of transgene ZmUbipro‐PtLecRLK1 up‐regulated more genes involved in plant response to external stimuli, plant‐microbe recognition (cell wall organization and cytoskeleton organization), and plant nutrient uptake, and presumably allowing the establishment of a compatible interaction between switchgrass and L. bicolor . Figure 3 MapMan analyses of differentially expressed genes (DEGs) in biotic stress pathway and nutrient uptake process. (a) Biotic stress pathway analysis for DEGs from comparison between IN‐WT and M‐WT. (b) Biotic stress pathway analysis for DEGs from comparison between IN‐trans and IN‐WT. (c) The number of up‐ and down‐DEGs from comparison between IN‐WT and M‐WT in specific biotic stress categories. (d) The number of up‐ and down‐DEGs from comparison between IN‐trans and IN‐WT in specific biotic stress categories. (e) The number of up‐ and down‐DEGs from comparison between IN‐WT and M‐WT in specific nutrient assimilation categories. (f) The number of up‐ and down‐DEGs from comparison between IN‐trans and IN‐WT in specific nutrient assimilation categories. The red and blue colours indicate the log2 fold change of DEGs, showing up‐ or down‐regulated genes, respectively. The metabolic pathways were generated with MapMan software; IN‐trans, IN‐WT, and M‐WT are abbreviations for inoculated‐transgenic, inoculated‐WT, and mock‐WT, respectively. It is well known that the RLKs play important roles in plant innate immunity. To understand the role of native LecRLK during the transgenic switchgrass‐ L. bicolor interaction, 64 PtLecRLK1 sequence homolog genes ( PavirLecRLK ) in switchgrass were identified. The phylogenetic relationship amongst those genes is presented in Figure S5a . There were 16 out of 64 members that were differentially regulated in the four conditions (Figure S5b ). The regulated PavirLecRLK members included RDA2 that was shown to be involved in transducing immune responses in Arabidopsis (Park et al ., 2019 ), and ARK2, ARK 3 that were shown to be involved in immune‐triggered incompatibility in Arabidopsis (Alcázar et al ., 2010 ). Amongst the 16 PavirLecRLK, there was no PavirLecRLK member that was differentially regulated by the transgene PtLecRLK1 only, but more than 10 were regulated by the L. bicolor infection, and 6 genes were responding to L. bicolor + transgene (Figure S5b ). These results suggested that the PtLecRLK1 transgene did not impact endogenous PavirLecRLK expression, but the L. bicolor inoculation did. We also aligned the protein sequences of PtLecRLK1 and the 6 closest switchgrass sequence homologs, and analysed the 4 domains (D‐mannose binding lectin domain, S‐locus binding domain, PAN‐like domain and Protein kinase domain). As shown in Figure S5c–f , except that the protein kinase domain is highly conserved, the other three domains that are predicted to be involved in recognition are not highly conserved, suggestive of the possible distinct recognition mechanisms in poplar and switchgrass. Therefore, we speculate that a functional PtLecRLK1 orthologue, specifically recognizing the ligand secreted by L. bicolor may not be present in switchgrass. It would be interesting to compare the response of transgenic switchgrass to both EM fungi and native AM fungi and/or pathogenic microbes under similar conditions. Such a multiple interaction would more closely mimic the real‐world condition and reflect how the recognition and downstream signal cascade balance/conflict with different microbes to finally establish the symbiotic or defensive relationships. Co‐expression network analysis highlights transcriptional changes associated with L. bicolor inoculation and PtLecRLK1 introduction To better reveal the crucial shift of gene expression networks in the establishment of the switchgrass‐ L. bicolor interaction, weighted gene co‐expression network analysis (WGCNA) (Langfelder and Horvath, 2008 ) was used to extract the main patterns of gene co‐expression amongst the four conditions (i.e. mock‐WT, inoculated‐WT, mock‐transgenic, and inoculated‐transgenic). WGCNA resolved the 15, 606 differentially expressed genes into 16 modules, corresponding to branches labelled by colours indicated underneath the tree (Figure 4a , Table S2 ). Notably, 4 out of the 16 co‐expression modules: turquoise, yellow, black, and green colour modules exhibited condition‐specific (inoculated‐WT, inoculated‐transgenic, mock‐WT, and mock‐transgenic, respectively) expression values (Figure 4b,c ). That is, these modules were composed of genes that tended to be overexpressed in a single condition ( r > 0.71, P < 2.6e‐92, Figure S6 ). To compare the trends in gene expression of each group as a function of inoculation + transgenic condition, an overview of expression for each of the 4 groups was presented (Figure 4d ). Figure 4e is depicted graphically as the aggregate average expression value for each condition. The two mock groups indicated only a small difference. However, the two inoculated groups were drastically differentiated from each other, and from the two mock groups. In addition, there was an overlapping blue module between the inoculated‐WT and inoculated‐transgenic groups (Figure 4b–d ), leading to the similar average expression value amongst those two conditions in Figure 4e . Although the overlap contained fewer genes from the inoculated‐WT in the inoculated‐transgenic module, the average of those overlapped gene expressions was higher than that in the inoculated‐transgenic module. This analysis showed that the gene co‐expression network shifted as the result of the L. bicolor inoculation and the presence of PtLecRLK1 . Figure 4 Network analysis of switchgrass root genes. (a) Hierarchical cluster tree showing co‐expression modules identified using WGCNA. Modules correspond to branches and are labelled by colours as indicated underneath the tree. The average gene expression values of all the replicates from the respective condition were used to build the network. (b) Dendrogram tree showing the distance amongst conditions and different coloured‐modules. (c) Heatmap showing the correlation between modules and conditions. The green boxes highlight the correlated conditions and modules. The reported modules and conditions ( x ‐axis) are often highly correlated with distinct conditions and modules ( y ‐axis). Colour legend indicates the level of correlation module and condition. (d) Heatmap of co‐expression groups for differentially expressed genes across the four conditions. The vertical axis organizes genes according to replicates in conditions, and the horizontal axis shows individual gene in the conditions labelled on the y ‐axis. The colour codes from blue to red indicate the gene expression value from low to high. (e) Boxplots show the distribution of groups expression (mean RPKM of all genes within a given group) for different genotype and inoculation conditions. IN‐WT, inoculated‐WT; IN‐trans, inoculated‐transgenic; M‐WT, mock‐WT; M‐trans, mock‐transgenic; respectively. The WGCNA showed that PtLecRLK1 and its co‐expressed genes were in the yellow module representing the inoculated‐transgenic samples. We analysed its co‐expressed gene network (Figure S7 ) and found that there was one gene ( Pavir.5KG693600 ) that was directly connected with the expression of PtLecRLK1 . This gene encoded an Integrin‐Linked protein Kinase (ILK) family‐related protein. In mammalian cells, the ILK and its interactors play a key role in mediating the intracellular cytoskeletal and signalling proteins communicating with the extracellular matrix (Wu and Dedhar, 2001 ). The plant ILK was shown to be coupled with ion transporter function in plant cell development and immune response (Brauer et al ., 2016 ). In addition, the plant ILK with its upstream ILR (Integrin‐like receptor) has been shown to alter the cell wall and plasma membrane via response to multiple signals (Popescu et al ., 2017 ). Therefore, the plant ILK was proposed to be a signal integrator that assembles the transporter and receptor complex to generate the downstream signalling for plant cell growth and immune response (Popescu et al ., 2017 ). In our study, this ILK family‐related protein coding gene, Pavir.5KG693600, was co‐expressed with a hub gene Pavir.5KG551300 , encoding a lipid kinase‐phosphatidylinositol 4‐phosphate 5‐kinase MSS4‐like protein, which has been reported to be a cytoskeleton regulator in yeast (Desrivieres et al ., 1998 ) and membrane recycling modulator in Arabidopsis (Sousa et al ., 2008 ). The co‐expression network amongst PtLecRLK1, ILK and phosphatidylinositol 4‐phosphate 5‐kinase MSS4‐like protein suggests a potential role for PtLecRLK1 in switchgrass as an initial integrator for a ligand receptor and related receptor‐like kinase that subsequently triggers the signalling cascade leading to successful establishment of the interaction between switchgrass and L. bicolor . Collectively, our co‐expression network analysis revealed the distinct transcriptional reprogramming for L. bicolor inoculation and the effect of PtLecRLK1 , which could be summarized using modules and a co‐expression network with predicted functions. Functional classification and annotation of differential abundance proteins On the basis of the transcriptomic evidence showing the potential of PtLecRLK1 to establish a compatible relationship between the transgenic switchgrass and L. bicolor by up‐regulating genes benefiting plant‐microbe recognition and nutrient exchange, and down‐regulating the genes responsible for abiotic stresses, we wanted to extend our analysis to examine the impact of PtLecRLK1 on the translational level regulation. Using the same inoculated‐transgenic and inoculated‐WT plant materials, we generated proteomic profiles to identify proteins that were significantly up‐ or down‐regulated by the introduction of PtLecRLK1 during L. bicolor inoculation. Principal component analysis on proteins (transcripts were also incorporated into the same analysis) from the two different conditions formed distinct clusters (Figure 5a ). Differential abundance proteins were identified with a P < 0.05 and absolute log2 fold change ≥1 between the inoculated‐transgenic and inoculated‐WT. In brief, 1,422 differential abundance proteins (595 high abundance and 827 low abundance) were detected (Table S5 ). Differential abundance proteins were subjected to enrichment and clustering using functional analysis of GO and MapMan. In the GO function analysis, carbohydrate metabolic, tRNA aminoacylation, asparagine biosynthetic, nitrate assimilation, fatty acid metabolic, and anion transport were overrepresented in the high abundance proteins; for example, nitrate assimilation‐related proteins and nitrate transporter (Pavir.6NG072000, Pavir.6KG067100, Pavir.1NG011219), nitrate reductase (Pavir.6KG411506) and nitrite reductase (Pavir.1KG111021 and Pavir.1NG473400) were at high abundance in the inoculated‐transgenic switchgrass compared with the inoculated‐WT controls. Nitrate transporters are known to participate in nitrogen, phosphorus, and nutrient sensing in plants by regulating plant response to abiotic and biotic stresses (Hu et al ., 2019 ; Krouk et al ., 2010 ), possibly via the phytohormone and receptor‐like kinases (Liu et al ., 2020 ). Nitrogen transportation is known to play a key role in the compatible association during orchid mycorrhizal symbiosis (Dearnaley and Cameron, 2016 ). Increases in fatty lipid metabolism have also been reported in a compatible interaction between P. trichocarpa and L. bicolor (Tschaplinski et al ., 2014 ). In the low abundance proteins, photosynthesis, oxidation–reduction, nitrogen compound metabolic, phospholipid biosynthesis, and negative regulation of transcription were enriched (Figure 5b ). In addition, we observed that pathogen resistance proteins were decreased in the inoculated‐transgenic switchgrass, including WRKY40 (Pavir.1KG087300), WRKY4 (Pavir.3KG465900), LRR, and NB‐ARC domains containing disease resistance proteins: Pavir.6NG062400, Pavir.5NG342200, Pavir.6KG040500, Pavir.6KG045300, Pavir.6KG047205, and Pavir.6KG122900. Furthermore, proteins related to fungal Hartig net formation were altered in the inoculated‐transgenic switchgrass. Plett et al . reported that the application of the ethylene precursor, ACC (1‐aminocyclopropane‐1‐carboxylic acid), in poplar root systems inhibited Hartig net development (Plett et al ., 2014 ). We found that Pavir.5NG258500 and Pavir.5KG296000 encoding ACC oxidases, which synthesize ethylene from ACC, had lower abundance in the inoculated‐transgenic switchgrass than that in the inoculated‐WT control, suggestive of less negative regulation in Hartig net development in the transgenic plants compared to WT. On the other hand, ectomycorrhizal fungi have been reported to produce IAA from tryptophan with the nitrilase enzyme and to excrete IAA to enhance Hartig net formation in the host plant (Plett et al ., 2014 ). We observed that Pavir.1KG395705 and Pavir.1KG319400 encoding nitrilase‐related proteins showed higher abundance in the inoculated‐transgenic switchgrass, potentially increasing the IAA content to enhance Hartig net formation in the transgenic plant roots. To further explore the pathways in which the differential abundance proteins were involved, we analysed these proteins using the MapMan software. The metabolism pathway visualization is shown in Figure 5c . Most proteins involved in light reactions had low abundance. Interestingly, the high abundance proteins were enriched in carbohydrate metabolism, cell cycle organization, nutrient uptake, and phenolics pathways (Figure 5c ). Those pathways are similar to those of the up‐regulated DEGs (Figures 2d and 5c ). The biotic stress pathway analysis showed a decrease in the abundance of proteins that are related to jasmonic acid and ethylene signalling (Figure 5d ), which were reported to act as a negative modulator during the compatible symbiosis between poplar roots and L. bicolor (Plett et al ., 2014 ). Collectively, observation of the proteomic analysis showed that, in the inoculated‐transgenic plants, the high abundance proteins were involved in plant‐microbe compatible interactions, including carbohydrate metabolism, nutrient exchange and Hartig net formation, whereas the low abundance proteins were associated with changes in photosynthesis and plant defence, suggesting that the introduction of an exogenous gene, PtLecRLK1, regulates the switchgrass‐ L . bicolor interaction at the translational level, favouring compatible interactions. Figure 5 Proteomic analysis of switchgrass root samples in response to Laccaria bicolor inoculation. (a) PCA of inoculated transgenic and WT for transcripts and proteins. (b) GO enrichment analysis for differential abundance proteins from the comparison between inoculated‐transgenic and inoculated‐WT. The dot size reflects the number of genes included in the category. (c) Overview of the metabolic pathways that the differential abundance proteins are involved in. (d) Biotic stress pathway that the differential abundance proteins are involved in. The red and blue colours indicate the log2 fold change of differential abundance proteins, showing high or low abundance proteins, respectively. The metabolic pathways were generated with MapMan software. Earlier studies reported a weak correlation between transcript level and protein abundance (Greenbaum et al ., 2002 ; Nie et al ., 2007 ; Zhang et al ., 2006 ). Here, we compared 1,422 (high and low abundance: 595 and 827, respectively) differential abundance proteins with 6,864 (up‐ and down‐ regulated: 3,896 and 2968, respectively) DEGs. We found that 105 (up‐ and down‐regulated: 64 and 41, respectively) genes/proteins overlapped (Table S6 ). Nevertheless, functional enrichment analysis at both the transcriptional and the translational levels showed up‐regulated carbohydrate metabolism, cell cycle organization, and nutrient uptake and down‐regulated photosynthesis processes in the L. bicolor ‐inoculated‐transgenic roots. This dichotomy of up‐ and down‐regulated processes suggests concomitant regulation at the transcriptional and translational levels. Metabolomic profiling of switchgrass roots during early interaction with L. bicolor \n From transcriptomic and proteomic analyses, we observed the effect of PtLecRLK1 in switchgrass on up‐regulation of genes and proteins involved in plant‐microbe compatible interactions, such as carbohydrate metabolism, nutrient assimilation, and cell wall organization, and, conversely, down‐regulation of genes and proteins involved in responses to biotic and abiotic stresses. To further elucidate the underlying molecular mechanisms, we generated metabolite profiles of inoculated‐transgenic and WT plants to better understand the PtLecRLK1 regulation of switchgrass responses to L. bicolor inoculation. Gas chromatography‐mass spectrometry‐based metabolomics were conducted on the same L. bicolor ‐inoculated transgenic and WT root samples. PCA analysis demonstrated separation of the WT and transgenic samples (Figure 6a ). Figure 6b showed that metabolomic responses of the transgenics were associated with the accumulation of numerous nitrogenous metabolites, such as asparagine, tyrosine, leucine, isoleucine, valine, and other amino acids, and the decline in stearic acid, fumaric acid, malic acid, lactic acid, glucose, mannitol, and aromatic metabolites including hydroxycinnamate conjugates. The enrichment analysis showed that the high abundance metabolites were involved in amino acid biosynthesis and metabolism, and that the low abundance metabolites were involved in the biosynthesis of unsaturated fatty acids and fatty acid biosynthesis (Figure 6c–e and Table S7 ). Such metabolite changes have been observed in previous studies on plant‐microbe beneficial interactions. For example, the application of the beneficial fungus Trichoderma spp. biocontrol metabolite (6‐pentyl‐2H‐pyran‐2‐one) on tomato plant resulted in increased amino acids, such as tyrosine, valine, glutamine, leucine, arginine and threonine, and phenylalanine, whose high abundance was reported to enable massive enhancement of carbon flux (Mazzei et al ., 2016 ). Increases in asparagine, isoleucine, putrescine, and tryptophan, and decline in glucose were observed in the L. bicolor‐ inoculated 35S:PtLecRLK1 transgenic Arabidopsis and the L. bicolor compatible host, P. trichocarpa (Labbé et al ., 2019 ; Tschaplinski et al ., 2014 ). Decreases in glucose, malic and shikimic acid were vital for Panicillium expansum colonization in apple fruit (Žebeljan et al ., 2019 ). Besides sugars, fatty acids are another carbon source that the symbiont can obtain from the plant. For instance, the AM fungi Rhizophagus. irregularis cannot synthesize the fatty acids, and its host plant Medicago can transfer the fatty acid to fungi to build the symbiotic relationship (Jiang et al ., 2017 ; Luginbuehl et al ., 2017 ). A parasitic pathogen fungi , Golovinomyces cichoracearum , can also take up fatty acids from host plants and decrease the fatty acid biosynthesis in plants (Jiang et al ., 2017 ). However, the carbohydrate metabolism and the fatty acid metabolomic pathways were up‐regulated in the inoculated‐transgenic plants in the proteomic analysis. This led us to consider that those increased metabolic activities resulted in providing more available carbon, including fatty acids from transgenic plants to fungi, leading to the decreased fatty acid‐related metabolites in plants. The metabolomic results agreed with the transcriptomic analysis showing increased nitrogen‐containing metabolites associated with the up‐regulated genes enriched in the transmembrane transporter activity, protein metabolic activity, and the tryptophan catabolic process; and decreased carbon‐containing metabolites associated with the down‐regulated genes enriched in photosynthesis. Declines in fatty acids and organic acids were likely caused by increased carbon demands of the microbial symbiont (Larsen et al ., 2011 ). The increased free amino acid concentration in roots was putatively the result of exchanging nutrients for carbon by the fungus. Such metabolites change suggests that the steps including the nutrient exchange in a successful symbiosis occurred between the ZmUbipro‐PtLecRLK1 transgenic switchgrass and L . bicolor . Figure 6 Metabolite response in switchgrass roots inoculated with Laccaria bicolor . (a) PCA separation of switchgrass WT from the transgenic samples. (b) Heatmap showing regulated metabolites in WT and transgenic roots in response to L. bicolor inoculation. (c) High abundance metabolites pathway enrichment analyses. (d) Low abundance metabolites pathway enrichment analyses. The ball size indicates the pathway impact, calculated by the compound number observed divided by the total compound number in the pathway. (e) Overview of the metabolic pasthways that the differential abundance metabolites are involved in. The red and blue colours indicate the log2 fold change of differential abundance metabolites, showing high or low abundance metabolites, respectively. The metabolic pathways were generated with MapMan software. To gain insight on the L. bicolor transcriptomic response during its colonization in switchgrass roots, we also analysed the fungal genes in the RNAseq dataset. However, only 45 genes out of 23, 125 fungal genes had expression values in at least one of the 15 inoculated root samples. When we performed the pair comparison, we were only able to find one gene down‐regulated in comparison between inoculated‐WT and mock‐WT, and 4 genes up‐regulated in comparison between inoculated‐transgenic and mock‐transgenic plants. The possible reason for detecting a low number of fungal genes was that we focussed on host transcriptomic response and did not enrich fungal RNA for RNAseq, and that the ECM roots in the sample were relative low (as the RNA was extracted from the whole root whilst the ECM root normally occurs in the root tip section). To precisely determine the fungal transcriptomic response, a possible future study would require isolating the ECM root, separating fungal RNA from plant RNA, and measuring the transcriptomic response from both organisms to obtain a complete picture of gene regulation in mutualistic interaction."
} | 11,694 |
24086517 | PMC3784570 | pmc | 5,235 | {
"abstract": "Steady-state metabolite concentrations in a microorganism typically span several orders of magnitude. The underlying principles governing these concentrations remain poorly understood. Here, we hypothesize that observed variation can be explained in terms of a compromise between factors that favor minimizing metabolite pool sizes (e.g. limited solvent capacity) and the need to effectively utilize existing enzymes. The latter requires adequate thermodynamic driving force in metabolic reactions so that forward flux substantially exceeds reverse flux. To test this hypothesis, we developed a method, metabolic tug-of-war (mTOW), which computes steady-state metabolite concentrations in microorganisms on a genome-scale. mTOW is shown to explain up to 55% of the observed variation in measured metabolite concentrations in E. coli and C. acetobutylicum across various growth media. Our approach, based strictly on first thermodynamic principles, is the first method that successfully predicts high-throughput metabolite concentration data in bacteria across conditions.",
"introduction": "Introduction Cellular metabolism involves the joint activity of hundreds of enzyme-catalyzed biochemical reaction A system-wide understanding of cellular metabolism requires the quantification of both fluxes through these reactions and the concentrations of the corresponding metabolites. In recent years, mass spectrometry has become a popular tool for high-throughput measurements of metabolite concentrations. In combination with isotope tracing, mass spectrometry can also measure metabolic fluxes [ 1 - 3 ]. The application of this approach and others has revealed that both metabolite concentrations and fluxes span several orders of magnitude and significantly vary across microorganisms and growth conditions [ 4 - 6 ]. For steady-state systems, substantial insight into metabolic reaction rates can be achieved through constraints imposed by the law of mass balance under a steady-state assumption: for each internal metabolite, total influx must equal total efflux. Systems level application of this constraint, typically referred to as Flux Balance Analysis (FBA) [ 7 ], requires knowledge only of metabolic network stoichiometry, without requiring data on enzyme kinetic constants. Nevertheless, it has shown substantial predictive power for both fluxes and other phenotypes [ 2 , 8 , 9 ]. Accordingly, FBA has become a widely used tool in bioengineering [ 10 - 13 ]. In contrast to the success of FBA in predicting fluxes, there is no comparable tool for explaining and predicting metabolite concentrations in cell-wide setups. Explicitly modeling metabolite concentrations would require a systematic understanding of in vivo enzyme kinetics, which is currently lacking, despite ongoing progress on modeling metabolic systems using simplified rate equations and parameter estimation techniques [ 14 - 18 ]. An alternative approach involves extending FBA to genome-scale modeling of metabolite concentrations by accounting for thermodynamic considerations [ 19 - 24 ] (without modeling enzyme kinetic effects). These methods capitalized on the fact that the net flux direction depends on the thermodynamic driving force, − ΔG ', which is calculated according to the equation: Δ G ' = Δ G ' 0 + R T ln Q (1) Where Q is the ratio of the chemical activities of products and reactants within the compartment where the reaction is occurring, R is the gas constant, T is the temperature, and ΔG ' 0 is the standard reaction Gibbs energy (determined by the change in Gibbs energy of formation between products and substrates at standard concentrations). Throughout this work we assume the cytoplasm is a dilute aqueous solution (and therefore the metabolite chemical activities are equal to their absolute concentrations [ 25 ]). Extended FBA methods implementing thermodynamic constraints on reaction directionality were shown to improve flux predictions [ 19 , 20 ]. However, incorporating the second law of thermodynamics per-se into FBA (i.e. constraining ΔG '<0 for flux-carrying reactions) is insufficient for effectively predicting metabolite concentrations, as for most metabolites, a wide range of possible concentrations satisfies all network thermodynamic constraints [ 19 ]. Schuster and Heinrich [ 26 ] suggested the principle of minimization of intermediate concentrations to identify biologically plausible metabolite concentrations within the space of thermodynamically feasible solutions (see also 27 ). The maintenance of low metabolite concentrations is due to limitations on intracellular solvent capacity, osmotic pressure, and to facilitate rapid temporal responses to parameter changes [ 28 ]. It further serves to reduce cross-talk between metabolic pathways that may arise at high metabolite concentrations due to promiscuous activity of enzymes (i.e., enzymes acting non-specifically on substrates other than their natural ones) [ 29 , 30 ]. Indeed, recent studies have shown that the total intracellular levels of metabolites is limited to around 10 gr/L and 300 mM which amounts to 3% of the total cellular dry weight in E. coli [ 4 , 31 , 32 ] (see Supp. Material). Taking this optimality consideration into account, Schuster and Heinrich have analyzed the metabolite concentrations in key metabolic pathways in human erythrocytes, showing that their prediction corresponds qualitatively to experimental data [ 26 ]. Here, we suggest that steady-state metabolite concentrations reflect a compromise between limiting the total concentration of intermediate metabolites (“metabolite load”; as previously suggested by Schuster and Heinrich) and maintaining sufficient thermodynamic driving force such that enzymes are utilized efficiently, with most flux in the forward direction. By maintaining adequate forward driving force for all reactions, the enzyme concentrations required to support the necessary net metabolic flux is reduced. Thus, steady-state metabolite concentrations reflect a balance between minimizing metabolite levels and maximizing enzyme efficiency ( Figure 1 ). Minimizing enzyme levels is important, due to space restrictions in the cell and the costs of protein production and maintenance [33]. 10.1371/journal.pone.0075370.g001 Figure 1 Steady-state metabolite concentrations reflect a balance between minimizing metabolite levels versus maximizing enzyme efficiency. (a) The second law of thermodynamics alone is insufficient to uniquely determine metabolite concentrations, resulting in a space of possible metabolite levels. Two factors “pull” metabolite levels within this space in different directions: (I) a limitation of the solvent capacity and osmotic pressure that tends to drive metabolite concentrations down; (II) the cost associated with the production of enzymes that drives up ratios of reactant-to-product concentrations, and thereby total metabolite concentrations. (b) A toy example of a linear pathway. The chemical potential of each metabolite in the pathway depends on its concentration and intrinsic energy of formation. A drop in metabolite chemical potential at every step is a thermodynamic requirement for the pathway to carry flux. Considering only the objective of maximizing enzyme efficiency (i.e., forward flux per enzyme), it is desirable to achieve a large drop in chemical potential at each step, but this requires unrealistically high total metabolite concentrations (red line). On the other hand, solutions that minimize total metabolite concentrations result in small drops in chemical potential (with many reactions close to equilibrium), leading to inefficient enzyme utilization (most capacity lost to backwards flux) (green line). This in turn requires unrealistically high enzyme levels to produce the required metabolic flux. mTOW balances both factors (blue line.). We formalize the trade-off between metabolite and enzyme levels in a computational framework, which we term metabolic Tug-of-War (mTOW), in analogy to the concept of genetic tug-of-war for balancing other evolutionary constraints [ 34 ]. To facilitate mTOW’s genome-scale thermodynamic analysis, we implement a novel approach, Component Contribution Method (CCM) [ 35 ], for estimating reaction Gibbs energies. mTOW is applied to genome-scale metabolic network reconstructions of E. coli [ 36 ] and of C. acetobutylicum [ 37 ], and is shown to successfully explain measured metabolite concentrations in both species under various growth conditions [ 4 , 6 ].",
"discussion": "Discussion We demonstrated that under some growth media metabolite concentrations reflect a compromise between cellular adaptations towards minimizing the total metabolite vs. enzyme levels. Since metabolite and enzyme levels cannot be explicitly computed based on metabolic fluxes without extensive kinetic knowledge, we approximated enzyme levels for reactions based on their thermodynamic forces, as low thermodynamic forces result in substantial backward fluxes, and thus higher required enzyme levels. mTOW does not take into account how enzyme kinetic considerations influence metabolite concentrations, for example by changing an enzyme rate via increasing both its substrate and product concentrations proportionally (i.e. without changing its thermodynamic driving force). Furthermore, it does not account for allosteric regulation or for the effect of specific enzyme kinetic parameters on the enzyme levels required to catalyze a unit of flux. mTOW’s predictions also implicitly assume that enzymes are fully saturated, an assumption which is partially supported by experimental evidence [ 4 ]. While mTOW’s estimated enzyme levels should be regarded as a very crude approximation, we evaluate the plausibility of enzyme predicted concentrations under glucose medium with the proteomic data of Taniguchi et al [ 54 ] and Ishii et al [ 5 ]. We find a statistically significant correlation of 0.32 (p = 10-6 for 210 enzymes) between the predicted and measured enzyme levels using the recent proteomics data of Taniguchi et al, and a correlation of 0.44 (p = 0.02 for 26 enzymes) using the data of Ishii et al. ( File S1 ). To enable the prediction of metabolite concentrations via a genome-scale flux and thermodynamic analysis, mTOW is bound to make additional simplifying assumptions that may bias its predictions: First, it relies on estimated Gibbs energies for reactions via the CCM method rather than solely on experimental data which is lacking for most of the reactions in E. coli . Second, although the coverage of group contribution-based methods for estimating thermodynamic parameters (such as CCM) is much higher than what can be derived from experimental data, it is still not complete and covers an average of 90% of the active (i.e. flux carrying) reactions across the various growth media (and 75% of the entire reactions set in E. coli ). Third, the exact intracellular conditions (which include ionic strength, pH, and pMg) affect the energetics of reactions [ 55 ], and current thermodynamic models are lacking in their ability to model these changes precisely. Though CCM corrects for pH and ionic strength, accurate prediction of such changes across media and their effect on metabolism remains an open challenge. Fourth, current metabolic models do not encompass all relevant known reactions. Specifically, while the model accounts for the required biosynthetic rate of many essential biomass precursors, it does not include information on the thermodynamic requirements of the reactions that consume them as these are outside the scope of the model. For example, the employed E. coli model lacks information on the thermodynamics of aminoacyl tRNA synthetase that utilizes amino-acids, which is likely to limit mTOW’s ability to correctly predict amino-acid concentrations (and potentially that of their upstream intermediates; see Supp. Material). Fifth, as mTOW is formulated as a non-convex optimization problem, whose exact solution is computationally intractable for large-scale networks, we obtain only approximated solutions based on a combination of mixed-integer linear programing and quadratic programming optimizations (see Supp. Material). Identifying optimization criteria that would explain complex metabolic behaviors remains a major open challenge in systems biology [ 56 ]. The fact that mTOW successfully predicts metabolite concentrations based on a compromise between two objectives and without requiring a detailed kinetic model should provide further support for this line of research."
} | 3,139 |
38365247 | PMC10939377 | pmc | 5,237 | {
"abstract": "Abstract Bacterial communities are intricate ecosystems in which various members interact, compete for resources, and influence each other’s growth. Antibiotics intensify this complexity, posing challenges in maintaining biodiversity. In this study, we delved into the behavior of kin bacterial communities when subjected to antibiotic perturbations, with a particular focus on how interspecific interactions shape these responses. We hypothesized that social cheating—where resistant strains shield both themselves and neighboring cheaters—obstructed coexistence, especially when kin bacteria exhibited varied growth rates and antibiotic sensitivities. To explore potential pathways to coexistence, we incorporated a third bacterial member, anticipating a shift in the dynamics of community coexistence. Simulations and experimental bacterial communities confirmed our predictions, emphasizing the pivotal role of interspecific competition in promoting coexistence under antibiotic interference. These insights are crucial for understanding bacterial ecosystem stability, interpreting drug–microbiome interactions, and predicting bacterial community adaptations to environmental changes.",
"introduction": "Introduction Most habitats on earth are populated by diverse bacterial communities [ 1–3 ]. Within these complex assemblages, individual members engage in signaling [ 4 , 5 ] and resource competition [ 6–8 ] as well as the active production of substances that can benefit or harm others within the community [ 9 , 10 ]. Unraveling the mechanisms that maintain bacterial community biodiversity poses a considerable challenge for evolutionary ecology, as the competitive nature of interactions often results in the exclusion of competitively inferior community members, especially when communities are exposed to antibiotics. Such exposure introduces intricate social dilemmas, marked by the emergence of “cooperators”—those facilitating group benefits—and “cheaters” who exploit these benefits, altering the community structure [ 11 , 12 ]. To address these dilemmas and promote coexistence, several mechanisms, such as partial privatization and spatial structuring, have been proposed [ 13–15 ]. For instance, using individual-based modeling, a recent study suggested that bacteria have evolved coexistence maintenance mechanisms, which enforced cooperation through the costly synthesis of a harmful toxin that selectively targeted noncooperative cheaters [ 16 ]. Additionally, in toxin-mediated interference competition, spatial structure can support coexistence by offering weaker members sanctuaries from their more competitive counterparts [ 17 , 18 ]. These dynamics can give rise to cyclic dominance among species (e.g. “rock–paper–scissors” game), beyond the constraints imposed by competitive exclusion [ 19 , 20 ]. Much of these existing studies centered on addressing social dilemmas that arise among different bacterial species when faced with antibiotic interference [ 21–25 ]. Nevertheless, empirical evidence from natural ecosystems suggested that different genotypes (strains) of the same bacterial species also engaged in a broad spectrum of interactions [ 4 , 26–28 ]. These intraspecific interactions ranged from intense competitions, often due to vying for the same nutrients and space, to cheating and altruistic behaviors like the secretion of public goods such as extracellular enzymes or metabolites that benefit the entire community [ 28–32 ]. Moreover, kin bacteria frequently thrived in well-mixed, spatially unstructured environments, making cooperators easier for cheaters to exploit [ 33 , 34 ]. The intricacies of how these kin bacteria coexist under the perturbation of antibiotics remain largely unexplored. Here, we explored how increased interspecific interactions influenced the coexistence of kin bacteria within unstructured and well-mixed habitats in the presence of temporary antibiotic perturbations. We postulated that a prevalent form of intraspecific interaction among kin bacteria manifested as social cheating under antibiotic stress. In such circumstances, resistant strains effectively removed antibiotics from nearby locations, thereby protecting themselves and neighboring cheaters of the same species. Coexistence became challenging when there were significant differences in the inherent growth rates and competitive abilities between antibiotic-resistant (cooperator) and -sensitive (cheater) strains. By employing the Comamonas testosteroni KF-1 (cooperator)–CNB-2/Δ LuxR (cheater) experimental community exposed to sulfamethoxazole (SMX) perturbation, we validated these predictions. While consistent with the competitive exclusion principle, introducing a third member—termed the “regulator”—into the community was hypothesized to foster balance between cooperator and cheater strains. However, this addition could intensify inhibitory interactions, due to the potential production of multiple antibacterial agents [ 35 , 36 ]. Hence, we expanded our theoretical model to simulate this three-way interaction, identifying feasible conditions for coexistence between these kin bacteria in well-mixed environments. Our results demonstrated that this coexistence relied on three-way competitive interactions, rather than facilitation, with the involvement of an external species as a regulator. The emergence of interspecific competition mitigated intraspecific inhibitory interactions, allowing coexistence despite differences in the inherent growth rates and the exploitation of cooperators by cheaters. We validated our model by introducing Pseudomonas aeruginosa into the experimental community, revealing that interspecific competitive interactions exert a strong enough force to foster kin bacteria coexistence and biodiversity.",
"discussion": "Discussion Cheating, which refers to the behavior where individuals exploit the cooperative actions carried out by others [ 54 ], has been extensively studied in microbial laboratory systems in the context of toxin interference, biofilm formation [ 55 , 56 ], group defense strategies [ 56 , 57 ], swarming motility [ 58 , 59 ], and siderophore production [ 60–63 ]. The existence of cheaters imposes a cheating load, which can potentially lead to the erosion of diversity as more advantageous forms outcompete weaker ones [ 64 ]. This leads us to consider the specific mechanisms that maintain coexistence and diversity in environments characterized by social cheating. Previous research into coexistence within social cheating contexts predominantly delved into the interactions between distinct species. These investigations highlighted the pivotal role of spatial structures in promoting the coexistence of cooperator and cheater strains [ 17 , 22 , 65–67 ]. The spatial structure provided a stabilizing fitness effect by physically separating two species, thereby indirectly enhancing intraspecific competition [ 68 ]—a phenomenon consistent with ecological theory [ 69 , 70 ]. Recent research has proposed alternative mechanisms that can promote coexistence and maintain biodiversity in the absence of significant spatial structure. For instance, Kelsic et al. extended the classic models of toxin production, introducing the idea of cooperative toxin degradation outside the cell [ 71 ]. Their theoretical models proposed that the opposing actions between antibiotic production and degradation counter the invasion of cheating species that cease these activities. This balance supported long-term coexistence among species with varied production and degradation abilities, even in the absence of spatial structure. This mechanism was especially pertinent in environments that generate antibiotics endogenously rather than from external introductions. It’s crucial to recognize that social cheating is not restricted to interspecies dynamics but is also prevalent within species [ 72 , 73 ]. Some theories posited that intraspecific cheating can be viewed as a constructive force, where strains collaborate by spreading antibiotic resistance, sharing public goods, and providing cross-protection against antimicrobial agents for mutual benefit and coexistence [ 8 , 21 ]. In contrast to this cooperative perspective, our study revealed that, under the influence of antibiotics, intraspecific social cheating led to destructive consequences, resulting in a social dilemma characterized by intense negative interactions and the exclusion of kin members. Yet, our data indicated that the emergence of interspecific competition might alleviate these negative intraspecific inhibitions. Specifically, our findings emphasized that interspecific competition can counterbalance intraspecific exploitation and facilitate coexistence, even in scenarios where kin strains compete for limited resources within a well-mixed habitat. Based on the theoretical framework proposed by Chesson [ 70 ], we hypothesized that the presence of the regulator would exert both equalizing (convergence of fitness among competing strains with increasing species richness) and stabilizing (enhanced intraspecific competition) effects on fitness. In situations where the out-species exhibited greater competitiveness, they mitigated fitness disparities among strains through the presence of both strong damage cheaters and intermediate damage cooperators, exerting a similar “policing” effect. Such policing behaviors were widespread in the animal kingdom. For instance, insects engaged in policing to regulate worker reproduction and enhance colony reproductive efficiency [ 74 , 75 ]. Among primates, macaques had been observed displaying policing behaviors to reduce conflict and strengthen social networks [ 76 ]. Our study revealed an intriguing phenomenon: even simple organisms like bacteria can also exhibit similar policing behavior and promote the coexistence of kin bacteria. We also would like to emphasize the important role of perturbations in driving community shifts toward coexistence. While traditionally believed that disturbances lead to increased biodiversity through weakened competition [ 77 , 78 ], recent theoretical and experimental evidence has challenged this notion as incomplete, highlighting the profound impact of disturbance intensity [ 79 ]. A study found that within toxic metal working fluids, individual species could not survive, but together, they thrived and efficiently degraded the fluid. This was attributed to each species’ detoxification efforts bolstering the survival and proliferation of others [ 80 ]. However, as environments were permissive—marked by reduced toxicity or the introduction of additional species—the dominant interactions tipped from cooperation toward competition, leading to unpredictable community dynamics and unstable community structure. Such community-level evolutions underlined the intrinsic connection between the impact of disturbances on communities and their intensity. Our observations aligned with this perspective, indicating that a community can only achieve coexistence when perturbations do not severely damage any of the involved members. When the antibiotic perturbation duration was extended to 48 hours, cheaters could not dominate by exploiting cooperators ( Fig. S17A and S18A-B ), and the introduction of an additional member did not shift this outcome ( Figs S17B and S18C–E ). Conversely, in environments devoid of antibiotic disturbances, coexistence remained elusive ( Fig. S19 ). These observations highlighted a critical balance: both extended perturbations and their total absence were harmful to community coexistence. Through our study with simple bacterial communities, we provided evidence of the unexpected positive influence of subinhibitory antibiotic disturbances in shaping the coexistence of cheater and cooperator [ 81 ]. To sum up, the coexistence of cooperators and cheater strains is determined by several key conditions: (i) the emergence of perturbations during community development; (ii) competitive interactions, rather than facilitative interactions, play a crucial role in enabling community coexistence; (iii) the existence of a regulator with a growth rate similar to that of the cheater leads to reduced productivity (population size) of both the cheater and cooperator; and (iv) there are no limitations on the type of response exhibited by the regulator to antibiotics. Based on the experimental community dynamics, we hypothesized that P. aeruginosa , with intermediate growth characteristics, may effectively reduce the ecological niche overlap between the two C. testosteroni strains by controlling their population sizes, thereby alleviating negative intraspecific interactions, and suppressing cheating behavior ( Fig. 5G ). Therefore, to maintain biodiversity between cheaters and cooperators, it’s important to establish an equilibrium where neither group dominated completely, which can be achieved through an external species. This external species can help maintain an intermediate level of success for both cheaters and cooperators, preventing one from monopolizing resources or ecological niches. Considering the widespread occurrence of cross-protection under toxin interference within the natural microbial world [ 82–84 ], we proposed that interspecific competition plays a vital role in maintaining biodiversity in low spatial structure habitats, such as marine ecosystems. Of course, natural microbial ecosystems are extremely complex, containing orders of magnitude more species than modeled here, as well as additional interactions such as resource competition, metabolic cross-feeding, phage invasion, and predator–prey relationships. Our serial dilution protocol mimicked a chemostat where external nutrient were consistently replenished and unused nutrients or metabolic waste were systematically removed with each growth cycle. The model primarily investigated how antibiotic sensitivity, combined with species interactions, affected the community when the growth rates of the species were uninfluenced by external environments. Consequently, our model did not encompass external resource consumption and metabolite exchanges and assumed unvarying logistic growth along with linear per capita effects of species on one another. Additionally, beyond our current scope, there are interactions, both nonmonotonic and nonadditive, that significantly influence the establishment and sustenance of microbial communities. Despite these constraints, our model effectively predicted the effects of antibiotics on the microbial community, providing valuable insights. Future research should focus on specific microbial interactions, particularly those driven by chemicals such as consumable metabolites, signaling molecules, or a combination of factors."
} | 3,691 |
36605825 | PMC9642960 | pmc | 5,238 | {
"abstract": "Polymers of biological origin have become a topic of interest due to growing concerns about the environmental impact of the disposal of plastics. In recent years, the production of ecobenign microbial polymer polyhydroxyalkanoates (PHAs) using inexpensive and renewable resources has gained significant interest as these compounds are highly biodegradable, biocompatible, and sustainable. This study used leaf endophytic isolate Bacillus cereus RCL 02, obtained from the oil-yielding plant Ricinus communis L., to achieve statistical optimization of culture variables for the enhanced production of PHAs utilizing sugarcane molasses as the sole carbon source. A three-level and four-factor Box–Behnken design of response surface methodology was implemented to optimize the process variables, namely molasses (carbon substrate), ammonium sulfate (nitrogen source), initial pH, and incubation period, for improved biomass formation and PHA production. The highest growth (14.8 g/l) and PHA production (85.2%, dry cell weight) by the isolate were observed with 47 g/l molasses, 3 g/l ammonium sulfate, an initial pH of 6.7, and 62 h of incubation. Statistical optimization of the process allowed achieving a 1.6-fold increase in the PHA yield (7.8–12.6 g/l) compared with the conventional single-factor system of analysis. The biopolymer thus produced was confirmed as a copolymer of 3-hydroxybutyrate and 3-hydroxyvalerate [P(3HB-co-3HV)] using 1 H nuclear magnetic resonance spectroscopic analysis and was found to contain 7.8 mol% 3-hydroxyvalerate. These findings clearly indicate the efficacy of the B. cereus RCL 02 isolate in the biotransformation of raw sugarcane molasses to P(3HV-co-3HV), without the need for supplementation with high-cost precursors.",
"conclusion": "Conclusions The study investigated the direct conversion of an inexpensive and renewable AIBP, sugarcane molasses, to P(3HB-co-3HV) copolymer by the endophytic isolate B. cereus RCL 02 without supplementation of any expensive precursors in the growth medium. To the best of our knowledge, this is the first report on statistical methodology-based agro-waste conversion to PHA copolymer with the 3HV monomer composition by an endophytic strain of B. cereus under single-step batch cultivation conditions. The BBD of RSM has been successfully implemented to optimize the process variables, in order to achieve the maximum PHA production and delineate the role of each of the variables and their interactive effects. The statistically designed optimization ensued a 1.6-fold increase in the PHA yield (7.8–12.6 g/l) by the isolate RCL 02 compared with the classical OVAT methodology. Bioconversion of raw sugarcane molasses to a substantial amount of PHA copolymer (12.6 g/l) by an endophytic bacterial strain appears to be enticing both economically and ecologically, as it has integrated the biosynthesis of PHA with simultaneous utilization of an AIBP. Future studies will focus on developing a suitable and energy-efficient downstream process for the sustainable production of this biogenic polymer. In addition, detailed physicochemical characterization of this accumulated P(3HB-co-3HV) copolymer would be carried out to identify its potential applications, particularly in biomedicine.",
"introduction": "Introduction Polyhydroxyalkanoates (PHAs) are a heterogeneous family of polyesters of microbial origin. These compounds have gained significant interest due to their comprehensive green lifecycle and unique physicochemical properties resembling synthetic plastics (Akaraonye et al., 2010 ; Koller et al., 2017 ). Being biogenic, PHAs are nontoxic, biodegradable, and biocompatible and are considered eco-friendly alternatives for hazardous fossil fuel-derived recalcitrant thermoplastics, which lack effective recycling strategies and thus have adverse environmental consequences (Kumar et al., 2020 ). Under unbalanced growth conditions with an excess of carbon, diverse microbial systems, including bacteria and archaea derived from different ecological niches, can accumulate a substantial amount of PHAs as intracellular reserve polymers (Lu et al., 2009 ; Poli et al., 2011 ; Tan et al., 2014 ). Despite having huge potential, the production and commercialization of PHAs are still limited mainly due to the high cost of substrates and cosubstrates as well as insufficient infrastructure for industrial production (Kalia et al., 2021 ; Tan et al., 2021 ). The cost of feedstock is the major factor that influences the fermentation cost, which accounts for approximately 30–50% of the total PHA processing cost (Martínez-Avila et al., 2021 ). This cost can be effectively minimized using readily available feedstock such as industrial, agricultural, municipal, and food-based wastes (Li and Wilkins, 2020 ; Bhatia et al., 2021 ). Of these, agro-industrial by-products (AIBPs) are of particular interest as they are rich in carbon and can be efficiently transformed into valueadded biomaterials, including PHAs (Israni and Shivakumar, 2020 ; Kee et al., 2020). Recent studies have estimated that with the use of such by-products, the cost of PHA production can be eventually reduced by almost 50% (Kumar et al., 2018 ; Saratale et al., 2021 ). Generally, a single or an integrated pretreatment of AIBPs involving chemical (acid or alkali) or enzymatic hydrolysis is often required. From economic and ecological perspectives, bioconversion of AIBPs by a suitable bacterial strain is desirable to reduce the steps in PHA production, the use of harsh chemicals, and the release of toxic compounds and effluents to the environment (Koller et al., 2017 ; Adeleye et al., 2020 ). Nevertheless, industry-scale implementation also requires new and advanced technologies that facilitate the utilization of inexpensive raw materials such as AIBPs (Rodriguez-Perez et al., 2018 ). Sugarcane molasses is a complex viscous residue formed as a by-product in sugarcane industries and is widely used as a substrate in biotechnological processes (Dalsasso et al., 2019 ). Over the past few decades, an increasing number of biomaterials, such as polysaccharides, oligosaccharides, organic acids, and enzymes, have been produced through microbial fermentation using sugarcane molasses (Zhang et al., 2021 ). The key constituent of molasses, including sucrose, glucose, and fructose, as well as Fe, Mg, Ca, K, and vitamins (B7) in trace amounts, act as supplements for the growth of bacteria and archaea (Kumar et al., 2020 ). Sugarcane molasses has been validated as a competent substrate for the production of PHAs, especially poly(3-hydroxybutyrate) [P(3HB)], with the use of a wide variety of bacteria, including Acinetobacter nosocomialis (Reddy et al., 2018 ), Alcaligenes sp. (Tripathi et al., 2019 ), Cupriavidus necator (Dalsasso et al., 2019 ), Halomonas boliviensis (Ortiz Veizán et al., 2020 ), Parapedobacter sp. (Tyagi et al., 2021 ), Pseudomonas aeruginosa (Tripathi et al., 2012 ), Ralstonia eutropha (Acosta-Cárdenas et al., 2018 ), and Rhodopseudomonas sp. (Carlozzi et al., 2019 ). However, the utilization of sugarcane molasses alone or with additional cosubstrates has only recently been acknowledged for the production of PHA copolymers, namely poly(3-hydroxybutyrate-co-3-hydroxyvalerate) [P(3HB-co-3HV)] (de Paula et al., 2021 ; García et al., 2019 ; Morya et al., 2021 ), poly(3-hydroxyoctanoate-co-3-hydroxydecanoate) [P(3HO-co-3HD)] (Basnett et al., 2020 ), and poly(3-hydroxybutyrate-co-lactate) [P(3HB-co-LA)] (Jo et al., 2021 ). In particular, Bacillus sp. are recognized as ideal organisms for the use of molasses along with various other AIBPs for efficient production of P(3HB) (Sharma and Bajaj, 2015 ; Penkhrue et al., 2019; Evangeline and Sridharan, 2019 ; Suryawanshi et al., 2020 ). Besides less expensive feedstock, using an inexpensive fermentation technology is also an essential prerequisite for the large-scale production of PHA. The development of a suitable bioprocess is equally important to support the growth of the producer organisms and maximize the PHA titer and intracellular accumulation (Li and Wilkins, 2020 ). Moreover, PHA production is significantly influenced by various physical, chemical, and biological parameters, and optimization of these individual variables is crucial for PHA bioprocessing (Reddy et al., 2018 ). Classical optimization methods such as “one variable at a time” (OVAT) are time-consuming and inadequate to interpret the interactive effects of multiple factors that influence PHA production. Response surface methodology (RSM) has been established as an excellent and reliable statistical tool to assess the linear, quadratic, and interactive terms of process variables which is widely used to predict the optimal factor combination for achieving the maximum target response and has also been successfully implemented recently for PHA production (Evangeline and Sridharan, 2019 ; Tripathi et al., 2019 ). Bacillus cereus RCL 02, a bacterium endophytic to the leaves of the oil-yielding plant Ricinus communis L., has been reported to be able to synthesize and intracellularly accumulate P(3HB) (Das et al., 2017 ), as well as the copolyesters of 3-hydroxybutyrate (3HB) and 3-hydroxyvalerate (3HV), while growing in a mineral salt (MS) medium (Das et al., 2018 ). To meet the existing need for a cost-efficient method for PHA production, the isolate RCL 02 has also been exploited for the production of P(3HB-co-3HV)] using sugarcane molasses (Das et al., 2019 ). The present study aimed at the RSM-based statistical optimization of some process variables that influence the production of the PHA copolymer by B. cereus RCL 02 using untreated raw sugarcane molasses without supplementation of the fermentation medium with additional precursors or cosubstrates.",
"discussion": "Results and discussion Recently, Das et al. ( 2019 ) investigated the synthesis and accumulation of PHA copolymers (7.8 g/l) by the endophytic bacterium B. cereus RCL 02 grown under shake-flask culture in a modified MS medium supplemented with sugarcane molasses. The authors reported that carbon source (molasses), nitrogen source (ammonium sulfate), initial pH, and incubation time potentially influenced the production of both PHA homopolymer and copolymer, based on the OVAT methodology of optimization (Das et al., 2017 ; 2018 ; 2019 ). Therefore, in the present study, these four independent variables were chosen for statistical optimization, whereas the remaining variables were kept constant. RSM-based optimization of process variables for growth and PHA production Using the BBD of RSM, the optimal levels of the process variables and their interactive effect on maximum growth and PHA production by the endophytic isolate B. cereus RCL 02 were assessed. The following independent variables were assessed in the analysis: molasses ( X 1 ), ammonium sulfate ( X 2 ), initial pH ( X 3 ), and incubation time ( X 4 ) – Table 1 . Thirty randomized trials were designed based on the BBD with different concentrations and combinations of values of the independent variables at minimum (−1), central (0), and maximum (+1) levels. The matrix developed using the BBD and the experimental results obtained for the response variables growth ( Y 1 ) and PHA production ( Y 2 ) are shown in Table 2 . The experimental results indicated that the quadratic model was appropriate for navigating the design space. To predict the values of the response variables ( Y 1 and Y 2 ), the coeffcients of the polynomial equation were computed from the experimental data. The polynomial equations obtained using multiple regression analysis for both response variables were as follows: \n Y 1 = 13.55 + 2.008 X 1 − 0.383 X 2 + 1.733 X 3 + 1.275 X 4 + + 1.1 X 1 X 2 + 1.2 X 1 X 3 + 0.625 X 1 X 4 − 0.625 X 2 X 3 − 0.025 X 2 X 4 + − 1.575 X 3 X 4 − 3.662 X 1 2 − 3.125 X 3 2 − 1.213 X 4 2 \n (3) \n \n Y 1 = 81.417 + 9.758 X 1 − 2.117 X 2 + 5.991 X 3 + 8.633 X 4 + + 9.925 X 1 X 2 + 7.525 X 1 X 3 + 3.525 X 1 X 4 − 1.825 X 2 X 3 − + 2.55 X 2 X 4 − 5.125 X 3 X 4 − 18.8 X 1 2 − 10.263 X 2 2 − + 12.25 X 3 2 − 4.963 X 4 2 \n (4) \n Table 1 Coded levels of the independent variables used for the assessment of growth and PHA production by B . cereus RCL 02 based on BBD Independent variable Symbol Coded level −1 0 +1 Molasses [g/l] \n X \n 1 \n 20 40 60 Ammonium sulfate [g/l] \n X \n 2 \n 1 3 5 pH \n X \n 3 \n 6 6.5 7 Incubation time [h] \n X \n 4 \n 36 54 72 Table 2 Experimental design based on BBD and the observed values for growth and PHA production by B . cereus RCL 02 Run order Independent variable Response variable molasses [g/l] ammonium sulfate [g/l] pH incubation time [h] growth, DCW [g/l] PHA, DCW [%] 1 20 3 6.5 36 5.2 ± 0.2 44.7 ± 2.4 2 20 1 6.5 54 5.8 ± 0.2 55.1 ± 3.1 3 20 5 6.5 54 4.2 ± 0.1 36.8 ± 1.9 4 60 1 6.5 54 7.8 ± 0.3 54.2 ± 1.6 5 40 5 5.5 54 4.5 ± 0.2 42.7 ± 2.2 6 40 1 5.5 54 5.1 ± 0.2 53.8 ± 0.8 7 40 3 7.5 72 10.8 ± 0.3 77.5 ± 1.1 8 40 3 6.5 54 9.7 ± 0.4 80.4 ± 2.7 9 40 3 7.5 36 12.8 ± 0.5 69.2 ± 1.3 10 40 1 6.5 72 11.2 ± 0.2 80.4 ± 2.8 11 60 5 6.5 54 10.6 ± 0.2 75.6 ± 1.9 12 40 3 6.5 54 14.6 ± 0.1 85.8 ± 0.5 13 20 3 6.5 72 6.8 ± 0.3 50.5 ± 0.5 14 40 5 7.5 54 7.3 ± 0.2 65.4 ± 2.7 15 60 3 7.5 54 10.4 ± 0.2 69.2 ± 1.4 16 40 3 6.5 54 14.2 ± 0.2 84.1 ± 1.5 17 40 3 6.5 54 14.8 ± 0.3 82.4 ± 1.8 18 40 1 6.5 36 7.5 ± 0.1 54.9 ± 2.2 19 60 3 5.5 54 5.8 ± 0.1 49.4 ± 0.9 20 60 3 6.5 36 8.7 ± 0.1 55.5 ± 1.6 21 40 3 5.5 72 9.8 ± 0.2 75.6 ± 1.1 22 20 3 7.5 54 4.9 ± 0.1 32.4 ± 3.5 23 40 1 7.5 54 10.4 ± 0.1 69.2 ± 1.8 24 40 5 6.5 36 6.5 ± 0.3 53.2 ± 1.1 25 40 3 5.5 36 5.5 ± 0.4 46.8 ± 1.8 26 60 3 6.5 72 12.8 ± 0.1 75.4 ± 2.3 27 20 3 5.5 54 5.1 ± 0.3 42.7 ± 2.4 28 40 3 6.5 54 13.8 ± 0.1 75.4 ± 0.6 29 40 5 6.5 72 10.1 ± 0.1 68.5 ± 0.8 30 40 3 6.5 54 14.2 ± 0.1 80.4 ± 0.2 Each experimental value represents the mean of three replicates ± standard deviation; growth was determined by measuring the dry weight of cell mass, and production of PHA was quantified following chemical estimation (Law and Slepecky, 1961 ) and gravimetric methods Adequacy of the statistical models for growth and PHA production The aptness of the models for growth ( Y 1 ) and PHA production ( Y 2 ) was determined based on the plots of correlation between the predicted and the actual responses ( Fig. 1 ) and the normal probability plots of residuals ( Fig. 2 ). Aggregation of the points around the diagonal line, as shown in Fig. 1A and Fig. 1B , assured the reliable correlation between the actual and predicted values for growth ( Y 1 ) and PHA production ( Y 2 ). The predicted values of Y 1 and Y 2 calculated using the regression analysis revealed a high degree of correlation with the corresponding experimental data. These findings clearly indicate that the actual values of both the response variables were in good agreement with the predicted values and thus supported the adequacy of the proposed models. Similarly, normal probability plots for Y 1 ( Fig. 2A ) and Y 2 ( Fig. 2B ) revealed the accretion of residuals adjacent to the diagonal line, suggesting their independent normal distribution and the close proximity of the experimental values with the predicted ones. Fig. 1 Graphical representation of correlation between A) actual (straight line) and predicted (squared) responses for growth and B) PHA production using BBD Fig. 2 Normal probability plots of A) residuals for growth and B) PHA production The significance of the models for growth and PHA production was assessed using ANOVA. The ANOVA of the regression models for variables growth ( Table 3 ) and PHA production ( Table 4 ) confirmed that both models were statistically significant ( F model > 1, significant). The model F -values, estimated based on Fisher’s F -test, were 10.5 and 19.21 for growth and PHA production, respectively. It should be noted that the F -value is a statistical measure of how well the factors describe the variation in the data around their mean (Tripathi et al., 2019 ). The greater the F -value is from unity, the more certain it is that the factors adequately explain the variation in the data and that the estimated coefficients of the factors are real. In the present study, the model F -values of 10.5 and 19.21 estimated for Y 1 and Y 2 , respectively, and their very low corresponding probability values ( P < 0.0001) clearly indicated that both the constructed models were significant for understanding the interactive effect of independent variables. In addition, LOF measures the inability of the model to represent the data at points that are excluded from the regression (Adetunji and Olaniran, 2020 ). The LOF values of 0.3639 and 2.34 determined for Y 1 and Y 2 , respectively, implied that they were not significant relative to the pure error. The insignificant LOF indicated the statistical accuracy and robustness of the models, which were sufficient enough to predict the response variables under any combination of the variable values. Table 3 ANOVA based on the quadratic polynomial model for the growth of the endophytic bacterium B . cereus RCL 02 Source Sum of squares Degree of freedom Mean square F -value P -value Model 311.54 14 22.25 10.50 < 0.0001 *** \n X \n 1 \n 48.40 1 48.40 22.84 0.0002 *** \n X \n 2 \n 1.76 1 1.76 0.8322 0.3761 \n X \n 3 \n 36.05 1 36.05 17.02 0.0009 *** \n X \n 4 \n 19.51 1 19.51 9.21 0.0084 *** \n X \n 1 \n X \n 2 \n 4.84 1 4.84 2.28 0.1515 \n X \n 1 \n X \n 3 \n 5.76 1 5.76 2.72 0.1200 \n X \n 1 \n X \n 4 \n 1.56 1 1.56 0.7374 0.4040 \n X \n 2 \n X \n 3 \n 1.56 1 1.56 0.7374 0.4040 \n X \n 2 \n X \n 4 \n 0.0025 1 0.0025 0.0012 0.9731 \n X \n 3 \n X \n 4 \n 9.92 1 9.92 4.68 0.0470 ** \n \n X 1 2 \n \n 91.98 1 91.98 43.41 < 0.0001 *** \n \n X 2 2 \n \n 74.67 1 74.67 35.24 < 0.0001 *** \n \n X 3 2 \n \n 66.96 1 66.96 31.60 < 0.0001 *** \n \n X 4 2 \n \n 10.08 1 10.08 4.76 0.0455 ** Residual 31.78 15 2.12 Lack of fit 13.39 10 1.34 0.3639 0.9184 Pure error 18.40 5 3.68 Cor total 343.32 29 (***) – highly significant, (**) – significant at the 95% probability level; X 1 , X 2 , X 3 , and X 4 are the four independent variables—molasses, ammonium sulfate, pH, and incubation time, respectively; the lack-of-fit F -value of 0.36 implies the lack of fit is not significant relative to the pure error Table 4 ANOVA based on the quadratic polynomial model for PHA production by the endophytic bacterium B . cereus RCL 02 Source Sum of squares Degree of freedom Mean square F -value P -value Model 6690.78 14 477.91 19.21 < 0.0001 *** \n X \n 1 \n 1142.70 1 1142.70 45.93 < 0.0001 *** \n X \n 2 \n 53.76 1 53.76 2.16 0.1622 \n X \n 3 \n 430.80 1 430.80 17.32 0.0008 *** \n X \n 4 \n 894.41 1 894.41 35.95 < 0.0001 *** \n X \n 1 \n X \n 2 \n 394.02 1 394.02 15.84 0.0012 *** \n X \n 1 \n X \n 3 \n 226.50 1 226.50 9.10 0.0087 *** \n X \n 1 \n X \n 4 \n 49.70 1 49.70 2.00 0.1779 \n X \n 2 \n X \n 3 \n 13.32 1 13.32 0.5355 0.4756 \n X \n 2 \n X \n 4 \n 26.01 1 26.01 1.05 0.3228 \n X \n 3 \n X \n 4 \n 105.06 1 105.06 4.22 0.0577 \n \n X 1 2 \n \n 2423.59 1 2423.59 97.42 < 0.0001 *** \n \n X 2 2 \n \n 722.19 1 722.19 29.03 < 0.0001 *** \n \n X 3 2 \n \n 1029.00 1 1029.00 41.36 < 0.0001 *** \n \n X 4 2 \n \n 168.87 1 168.87 6.79 0.0199 *** Residual 373.18 15 24.88 Lack of fit 307.53 10 30.75 2.34 0.1800 Pure error 65.65 5 13.13 Cor total 7063.96 29 (***) – highly significant (significant at the 95% probability level); X 1 , X 2 , X 3 , and X 4 are the four independent variables—molasses, ammonium sulfate, pH, and incubation time, respectively; the lack-of-fit F -value of 2.34 implies the lack of fit is not significant relative to the pure error The coefficient of determination ( R \n 2 ) values for Y 1 and Y 2 were recorded at 0.9074 and 0.9472, respectively, which implied the accuracy of both models with appreciable predictability ( Table 5 ). The R \n 2 value measures the “goodness of fit”, and its proximity to 1 denotes a better correlation between the observed and predicted responses (Sharma and Bajaj, 2017 ). However, lower R \n 2 values indicate that the response variables are not appropriate to explain the variation. In the present study, the R \n 2 values obtained for growth ( Y ) and PHA production ( Y 2 ) indicated that approximately 91% and 95% variability could be explained by the respective models. The adjusted R \n 2 values, which corrects the R \n 2 value for the sample size and number of terms, were recorded at 0.8210 and 0.8979 for Y 1 and Y 2 , respectively. The predicted R \n 2 for Y 1 was 0.6982 and for Y 2 was 0.7395. The difference between the adjusted and the predicted R \n 2 was less than 0.2 for both response variables ( Y 1 and Y 2 ), and hence, a reasonable agreement was found. The adequate precision measures the signal (response) to noise (deviation) ratio. As reported in a previous study, a ratio greater than 4 (S/N > 4) is desirable (Sharma and Bajaj, 2015 ). In the present study, ratios of 10.157 and 14.421 for Y 1 and Y 2 , respectively, indicated adequate signal, and thus, these models could be suitably used to navigate the design space. The percent coefficient of variation (C.V. %) is a statistical parameter that indicates the reliability of the experiment and provides information regarding the degree of precision with which the experiments were performed (Adetunji and Olaniran, 2020 ). In this case, the C.V. % of 16.12% and 7.93% determined for Y 1 and Y 2 , respectively, indicated the accuracy and consistency of the generated models. Table 5 Statistical parameters of the polynomial model designed for growth and PHA production by the endophytic bacterium B . cereus RCL 02 Statistical parameter Value growth, DCW [g/l] PHA, DCW [%] \n \n R \n \n 2 \n 0.9074 0.9472 Adjusted R \n 2 0.8210 0.8979 Predicted R \n 2 0.6982 0.7359 Adequate precession 10.1568 14.4212 Standard deviation 1.46 4.99 Mean 9.03 62.91 C.V. % 16.12 7.93 R 2 – denotes the coeffcient of determination, C.V. % – denotes the percent coefficient of variation Interactive effect of independent variables The linear terms of independent variables, namely molasses ( X \n 1 ), initial pH ( X \n 3 ), and incubation time ( X \n 4 ), were found to be significant ( P < 0.05) – Table 3 – for growth ( Y \n 1 ). When quadratic terms were considered, all the four variables ( X 1 2 , X 2 2 , X 3 2 , and X 4 2 ) showed significant effects. However, the interactive effect of initial pH ( X \n 3 ) and incubation time( X \n 4 ) most significantly influenced the biomass formation by the isolate B. cereus RCL 02. Similarly, the linear terms X \n 1 , X \n 3 , and X \n 4 , as well as all four quadratic terms X 1 2 , X 2 2 , X 3 2 , and X 4 2 , exhibited a substantial influence on polymer production ( Y 2 ) – Table 4 . The interactive effect of molasses (X 1 ) and ammonium sulfate (X 2 ), as well as that of molasses (X 1 ) and initial pH (X 3 ), also had a positive impact on PHA accumulation by the endophytic isolate B. cereus RCL 02. Furthermore, the 2D contour and 3D response surface plots were analyzed to better comprehend the combinational effects among the interacting variables for growth and biopolymer production. An elliptical contour plot is designated for a significant interactive effect between the variables, whereas a circular contour plot is designated for nonsignificant interactions between the corresponding variables (Suryawanshi et al., 2020 ). In the present study, the elliptical contour plot, as shown in Fig. 3F , clearly indicated that the interactive effect of initial pH ( X \n 3 ) and incubation time ( X \n 4 ) most significantly influenced biomass formation ( Y \n 1 ) as compared to the interactive effect of molasses ( X \n 1 ) and ammonium sulfate ( X \n 2 ) ( Fig. 3B ) and that of molasses ( X \n 1 ) and initial pH ( X \n 3 ) ( Fig. 3D ). The response surface plot ( Fig. 3E ) clearly showed that an initial pH ( X \n 3 ) of 6.7 and incubation time ( X \n 4 ) of 62 h supported the maximum biomass formation by B. cereus RCL 02. However, a further increase in these two variables inhibited the growth. The molasses ( X \n 1 ) and ammonium sulfate ( X \n 2 ) response surface interaction plot ( Fig. 3A ) showed a concomitant increase in biomass formation with an increasing concentration of molasses beyond the center points nearly reaching the periphery. In contrast, the curvature of the 3D response plot ( Fig. 3C ) corresponding to the interaction between molasses ( X 1 ) and initial pH ( X 3 ) indicated a decreasing growth of the isolate B. cereus RCL 02 with an increasing pH toward the periphery. Fig. 3 Response surface and contour plots showing the interactive effect of molasses and ammonium sulfate (A and B), molasses and pH (C and D), and pH and incubation time (E and F) for the growth of the endophytic isolate B. cereus RCL 02 The interaction between molasses ( X 1 ) and ammonium sulfate ( X 2 ) had a remarkable influence on polymer production, which was clearly evident from both the response ( Fig. 4A ) and the contour plots ( Fig. 4B ). A gradual increase in polymer accumulation was observed with an increasing concentration of molasses. These results thus are in line with the previously reported growth-associated polymer biosynthesis by the endophytic isolate B. cereus RCL 02 (Das et al., 2017 , 2019 ). Increasing the molasses concentration beyond 47 g/l reduced polymer accumulation, which might be due to substrate inhibition, changes in the osmoticum, and/or the interference of other impurities present in molasses. Reddy et al. ( 2018 ) have previously reported a similar observation of mutual interaction between these two variables, where the maximum production of P(3HB) (7.82 g/l) by A. nosocomialis RR20 was attained with 28 g/l of molasses and 3.2 g/l of ammonium sulfate. Moreover, Suryawanshi et al. ( 2020 ) indicated that the carbon (molasses) and nitrogen (urea) sources were the most critical control factors influencing the production of P(3HB) by B. cereus 2156. On the contrary, the interactive effect between molasses, ammonium sulfate, and initial pH was found insignificant and failed to affect PHA production by B. cereus VIT-SSR1 (Evangeline and Sridharan, 2019 ). The response surface ( Fig. 4C ) and contour plots ( Fig. 4D ) representing the interactive effect of molasses ( X \n 1 ) and initial pH ( X \n 3 ) also showed a positive impact on PHA accumulation by the endophytic isolate B. cereus RCL 02. However, the interactive effect of initial pH ( X \n 3 ) and incubation time ( X \n 4 ) ( Fig. 4E and Fig. 4F ) did not have much influence on PHA production by this species. In contrast, Hassan et al. ( 2019 ) well described the influence of pH and incubation time on the production of P(3HB) by Bacillus subtilis . Fig. 4 Response surface and contour plots showing the interactive effect of molasses and ammonium sulfate (A and B), molasses and pH (C and D), and pH and incubation time (E and F) for PHA production by the endophytic isolate B. cereus RCL 02 Validation of the statistical model The model used was verified by conducting the experiments in triplicate under optimal conditions as predicted by the point prediction tool of RSM. The most favorable conditions predicted for the maximum growth of biomass and PHA production were as follows: molasses 47 g/l, ammonium sulfate 3 g/l, initial pH 6.7, and incubation time 62 h. Under such optimal conditions, the biomass and PHA production were recorded to be 14.8 g/l and 85.2% dry cell weight (DCW), respectively, which were almost equivalent to the predicted values (14.4 g/l and 86.8% DCW, respectively) ( Table 6 ). Therefore, it was clear that the predicted and experimental values were in good agreement, manifesting the validity of both the models. Table 6 Optimum values of the independent variables and confirmatory trials for the predicted responses under optimal conditions Independent variable Optimum condition coded level actual level Molasses [g/l] 0.35 47 Ammonium sulfate [g/l] 0 3 pH 0.40 6.7 Incubation time [h] 0.44 62 Response predicted value experimental value Growth, DCW [g/l] 14.4 14.8 ± 0.1 PHA, [% DCW] 86.8 85.2 ± 1.4 Each experimental value represents the mean of three replicates ± SD; the coded levels of the independent variables were calculated as follows: Z = ( Z i – Z 0 )/Δ Z , where Z is the coded value and Z i is the real value; Z 0 indicates the value of the independent variable at the central point; and Δ Z represents the step change value In the literature, the endophytic isolate B. cereus RCL 02 has already been reported to produce biomass of 9.4 g/l with a PHA content of 83.5% using sugarcane molasses, based on the OVAT methodology of optimization (Das et al., 2019 ). It is therefore apparent from the present study that the RSM-based optimization effectively enhanced the PHA yield by 1.6-fold (7.8–12.6 g/l) as compared to the conventional OVAT methodology. Moreover, the PHA production (12.6 g/l) efficiency of the endophytic isolate B. cereus RCL 02 was found to be quite satisfactory compared with the efficiency of other nonendophytic bacterial strains, with the use of sugarcane molasses ( Table 7 ). Table 7 Fermentative utilization of molasses as the carbon source for the production of PHA copolymers by different natural and recombinant bacterial strains Organism Carbon substrate utilized Type of PHA copolymer produced PHA content [%, DCW] Reference Bacillus cereus RCL 02 sugarcane molasses P(3HB-co-3HV) 85.2 this study Burkholderia glumae MA13 sugarcane molasses P(3HB-co-3HV) 46.6 de Paula et al., 2021 Burkholderia sp. ISTR5 p-coumaric acid and molasses P(3HB-co-3HV) 83 Morya et al., 2021 Cupriavidus necator ATCC 17699 vinasses–molasses mixture P(3HB-co-3HV) 78 García et al., 2019 Cupriavidus necator H16 (Re 2058/pCB113) date seed oil and date molasses P(3HB-co-3HHx) 51 Purama et al., 2018 Pseudomonas mendocina CH50 sugarcane molasses P(3HO-co-3HD) 14.2 Basnett et al., 2020 Recombinant Ralstonia eutropha sugarcane molasses P(3HB-co-LA) 29.1 Jo et al., 2021 DCW – dry cell weight, P(3HB-co-3HV) – poly(3-hydroxybutyrate-co-3-hydroxyvalerate), P(3HB-co-3HHx) – poly(3-hydroxybutyrate-co-3-hydroxyhexanoate), P(3HO-co-3HD) – poly(3-hydroxyoctanoate-co-3-hydroxydecanoate), P(3HB-co-LA) – poly(3-hydroxybutyrate-co-lactate) Although PHA accumulation by endophytic B. cereus strains was not previously analyzed in detail, the potential of nonendophytic strains of B. cereus to produce the biopolymer has been extensively documented (Valappil et al., 2007 ; Akaraonye et al., 2011; Sharma and Bajaj, 2015 ; Mohandas et al. 2018 ; Evangeline and Sridharan, 2019 ; Suryawanshi et al., 2020 ). The bacterium B. cereus SPV was found to produce the homopolymer P(3HB), accounting for 38% of its DCW, using glucose as the main source of carbon (Valappil et al., 2007 ). However, P(3HB) production by the strain SPV was enhanced up to 61.07% DCW when the growth medium was supplemented with sugarcane molasses (Akaraonye et al., 2011). Similarly, Sharma and Bajaj ( 2015 ) isolated the bacterium B. cereus PS 10 from a domestic waste landfill, which exhibited a substantial P(3HB)-producing potential (57.5% DCW) with the use of sugarcane molasses. In the study by Mohandas et al. ( 2018 ), the marine water isolate B. cereus MCCB 281 and glycerol were used for the production of copolymers of PHA. In the present study, the central composite design-based statistical optimization enhanced the MCCB 281-mediated PHA production [68.27% (w/w)] by 1.5-fold. Likewise, Plackett–Burman and central composite design of RSM were used for the optimization of the process parameters, viz. molasses, ammonium sulfate, and initial pH, with the maximum production of P(3HB) accounting for 40.3% DCW achieved from B. cereus strain VIT-SSR1 (Evangeline and Sridharan, 2019 ). Recently, Suryawanshi et al. ( 2020 ) also used BBD for enhancing the production of P(3HB) (59.30% DCW) by B. cereus 2156, using molasses and urea as carbon and nitrogen sources, respectively. Therefore, it is apparent that the production of PHA (85.2% DCW) by the endophytic isolate B. cereus RCL 02 was higher compared with other PHAproducing B. cereus strains so far reported. NMR spectroscopic analysis 1 H NMR was used to determine the monomeric composition of the purified PHA polymer isolated from the endophytic B. cereus RCL 02. The 1 H NMR spectrum ( Fig. 5 ) showed resonances at 1.25, 2.45–2.64, and 5.22–5.27 ppm representing the methyl (−CH 3 ), methylene (−CH 2 −), and methine groups (−CH−), respectively, from the 3HB monomer. Likewise, the resonances at 0.89, 1.62, and 5.15–5.17 ppm represented the methyl group (−CH 3 ), methylene group (−CH 2 −), and methine group (−CH−), respectively, corresponding to the 3HV monomer. The chemical shifts observed were consistent with the previous findings of Pillai et al. ( 2020 ) and confirmed that the polymer obtained from the endophytic isolate B. cereus RCL 02 was P(3HB-co-3HV). Fig. 5 \n 1 H NMR spectra of purified P(3HB-co-3HV) copolymer produced by the endophytic isolate B. cereus RCL 02 The characteristic peaks at 0.9 and 1.25 ppm in the 1 H NMR spectrum are commonly used to determine the composition of 3HV in P(3HB-co-3HV), according to the following equation: \n 3HV(%)= AreaCH 3 (3HV) AreaCH 3 (3HV)+AreaCH 3 (3HB) × 100 % \n (5) \n By integrating the area under the peaks at 0.89 and 1.25 ppm in the 1 H NMR spectra, it was found that P(3HB-co-3HV) produced by B. cereus RCL 02 under optimized cultural conditions had 7.8 mol% 3HV. Incorporation of the 3HV monomer (7.8 mol%) in P(3HB-co-3HV) by the endophytic strain RCL 02 was fairly notable when compared with other PHA copolymers accumulated by different bacterial strains after fermentation using molasses and related agro-industrial waste-based products as the carbon source. On the other hand, PHA accumulated by Burkholderia glumae MA13 had only 1.5 mol% 3HV using sugarcane molasses (de Paula et al., 2021 ), while the halophilic archeal strains, viz. Haloferax mediterranei and Halogeometricum borinquense , have been reported to accumulate P(3HB-co-3HV) with 12.36 mol% 3HV using pretreated vinasse (Bhattacharyya et al., 2012 ) and 13.29 mol% 3HV using pretreated sugarcane bagasse (Salgaonkar and Braganca, 2017 ), respectively. Furthermore, the bacterium B. cereus YB-4 isolated from ammunition-polluted soil accumulated PHAs with 3HV fraction up to 2 mol% using glucose as the sole source of carbon (Mizuno et al., 2010 ). Feedstock plays an important role in determining the economic feasibility and sustainability of PHA bioprocessing (Sirohi et al., 2020 ). Previous reports have documented the exploitation of inexpensive and readily available sugarcane molasses as the carbon substrate for the production of the intracellular PHA polymer using a number of bacterial strains. The majority of these studies have reported the production of P(3HB) using molasses. Despite the biodegradability and biocompatibility of P(3HB), its widespread application is still limited due to its high crystallinity and brittleness (Raza et al., 2020 ). However, P(3HB-co-3HV) is considered more promising due to higher elasticity with lesser crystallinity and tensile strength and hence comparatively more flexible (Grigore et al., 2019 ). Supplementation of propionic acid, p-coumaric acid, and vinasses in sugarcane molasses has led to the production of P(3HB-co-3HV) copolymer by microbial cultures such as Azohydromonas lata (Zafar et al., 2012 ), Burkholderia sp. (Morya et al., 2021 ), and Cupriavidus necator (García et al., 2019 ). However, reports on the production of copolymers such as poly(3-hydroxybutyrate-co-3-hydroxyhexanoate), P(3HO-co-3HD), and P(3HB-co-LA) from sugarcane molasses by naturally occurring bacteria and recombinant strains are not uncommon (Purama et al., 2018 ; Basnett et al., 2020 ; Jo et al., 2021 ) ( Table 7 ). The endophytic B. cereus RCL 02 could accumulate P(3HB-co-3HV) using molasses, without any pretreatment and supplementation of the fermentation medium with precursors. In general, the alkanoic acids used as precursors in the fermentation medium for the production of various heteropolymers are expensive and often exert an inhibitory effect on the growth of the producer organisms (Das et al., 2018 ). On the contrary, using agro-industrial wastes such as molasses as the carbon feedstock instead of a pure carbon source and expensive precursors for PHA production is not only a sustainable alternative in the disposal of industrial by-products but also favors the bioconversion of waste into an economically valuable product (Akaraonye et al., 2010 ). It is apparent that different acidic compounds produced as metabolic intermediates during the growth-associated utilization and fermentation of molasses by the strain RCL 02 might contribute to the incorporation of 3HV monomers into the accumulated PHA (Das et al., 2019 ). Furthermore, sugarcane molasses could not only serve as the potential source of carbon but also provide vitamins and other essential growth factors for the effective growth and sustainable production of P(3HB-co-3HV) copolymer by the bacterium B. cereus RCL 02. A literature survey regarding the production of PHA by Bacillus spp. has clearly revealed that the accumulation of PHA, particularly by B. cereus strains, has been widely reported. However, the majority of the studies reported the production of the homopolymer P(3HB) (Evangeline and Sridharan, 2019 ; Suryawanshi et al., 2020 ), and only a few have documented the production of PHA copolymer with pretreatments of the carbon feedstock and/or supplementation with pure carbon sources and expensive precursors (Mizuno et al. 2010 ; Mohandas et al., 2018 ). The present study indicated the direct bioconversion of untreated AIBP to the PHA copolymer by an endophytic strain of B. cereus without any addition of precursor or cosubstrates to the fermentation medium, thus making the process environmentally and economically viable."
} | 9,533 |
34122359 | PMC8193672 | pmc | 5,239 | {
"abstract": "Dynamic consortium of microbial communities (bacteria, fungi, protists, viruses, and nematodes) colonizing multiple tissue types and coevolving conclusively with the host plant is designated as a plant microbiome. The interplay between plant and its microbial mutualists supports several agronomic functions, establishing its crucial role in plant beneficial activities. Deeper functional and mechanistic understanding of plant-microbial ecosystems will render many “ecosystem services” by emulating symbiotic interactions between plants, soil, and microbes for enhanced productivity and sustainability. Therefore, microbiome engineering represents an emerging biotechnological tool to directly add, remove, or modify properties of microbial communities for higher specificity and efficacy. The main goal of microbiome engineering is enhancement of plant functions such as biotic/abiotic stresses, plant fitness and productivities, etc. Various ecological-, biochemical-, and molecular-based approaches have come up as a new paradigm for disentangling many microbiome-based agromanagement hurdles. Furthermore, multidisciplinary approaches provide a predictive framework in achieving a reliable and sustainably engineered plant-microbiome for stress physiology, nutrient recycling, and high-yielding disease-resistant genotypes.",
"conclusion": "Concluding Remarks In view of the complexities of microbial interactions, “microbe-friendly” plants or genetically engineered/edited plant genome will lead to field success by strengthening plant health and preparedness against environmental fluctuations. This microbial fortification will enhance gene expression, enzymatic parameters, nutrient uptake, and biocontrol response. Thus, strategic manipulation and inoculation of microbial multispecies will have more impactful response on plant growth performance by minimizing chemical farm inputs. In this scenario, microbiome engineering offers exciting opportunities for understanding and engineering individual organisms to the entire ecosystems. This envisioned technology will reveal a vast diversity and elegance underlying natural microbial ecosystems at the frontier of nutritional and ecological demands. The transcendental role of microbes in the field of basic sciences, human health, and agriculture is worth mentioning at the frontier of synthetic biology strategies. However, many of the associated technologies of bioengineering are still in its infancy and require a regulated framework for examining its future in crop improvement programs.",
"introduction": "Introduction Scientific research advances over the eons of time have propelled microbial coevolution and diversification as important forces in sculpturing and carving every accessible part of nature ( Saleem et al., 2017 ). The taxonomically diverse microbial communities interacting with different components of ecosystem are acknowledged to be a major trait in terrestrialization of plants. Therefore, this multiorganismal assemblage and its synergistic relationships with the host shape the “holobiont” framework ( Cooke et al., 2019 ). The holistic and interactive colonization of plants by ecologically diverse microbial communities is designated as plant microbiome ( Foo et al., 2017 ). The microbiota can exist persistently in, on, and around different tissues during plant life cycle ( Nelson, 2018 ). Bacteria, fungi, protozoa, archaea, and viruses comprise diverse microbiota teaming with the plant. The study of multitrophic interactions between the two has greatly elaborated ecoevolutionary and functional understanding of host-microbe interactions. Rhizosphere, endosphere, and phyllosphere are the major microecosystems where bidirectional chemical dialog directly contributes to plant development, physiology, and systemic defenses and indirectly produce root exudates and other metabolites acting as nutrient sources and signals for modulating microbial composition ( Mueller and Sachs, 2015 ). Host genotypic traits, developmental stage, soil properties, and environmental conditions harmonize the structural and functional dynamics of microbiome ( Rossmann et al., 2017 ). This symbiotic interactome confers many adaptive advantages to plant growth and development viz. nutrient acquisition, stress resilience, modulation of hormone levels, disease resistance, enable toxin production, and increased root exudation ( Singh et al., 2020 ). Opening up of new high-throughput community analyses methods, next-generation sequencing techniques and meta-“omics” tools have greatly unraveled the multitrophic interactions present in the black box of plant microbiome ( Ahmad et al., 2019 ). With the advent of these high-throughput technologies, plant beneficial microbes can be manipulated. In this scenario, microbiome engineering may be an alternative way to understand, manipulate, and develop corresponding technologies for developing microbial communities crucial to plant health and productivity ( Prasad et al., 2018 ). The present review fosters various practical ways by which plant-microbial mutualism can be manipulated to enhance plant performance and agricultural productivity."
} | 1,284 |
36426121 | PMC9679247 | pmc | 5,242 | {
"abstract": "Abstract Our experimental work illustrates how microbial ecosystems can be shaped by selective pressures over long‐term ecological time scales. Natural microbial ecosystems generally consist of various co‐existing species, where community composition describes the frequency at which species or types are present. Overall functionality of the system is achieved by interacting species. Upon short‐term selection, for instance by transfer to a novel environment, community composition and functionality may change in a process referred to as species sorting. Various factors, such as initial community composition and selective pressures from the environment, may influence this change. Mabisi is a traditional fermented food from Zambia that naturally contains a bacterial community of around twenty unique bacterial types. We used six comparable but different natural bacterial Mabisi communities, each split into five identical replicates, for 16 propagation cycles in a novel, common laboratory environment. Composition of the bacterial communities changed upon propagation. The influence of four main factors on community composition, i.e. initial composition (history), impact of the environment (adaptation), changes due to interaction between species and random processes (chance) in species dynamics, was tested using maximum likelihood ratios. Initial community composition seemed to determine the change in community composition, followed by random processes. Interestingly, we observed convergence at the level of ecosystem functionality, which was measured as profiles of metabolic output. This suggests different combinations of species or types can achieve similar eco‐system functionality.",
"conclusion": "5 CONCLUSION When placed in a new (laboratory) environment, different natural bacterial communities from Mabisi maintain their diversity and did not show simple convergent change towards an eroded microbial community with only a few species. Even though the bacterial community composition from the original Mabisi communities seem very similar, small differences made that the final community composition differed between samples from different origin. These changes were parallel in all 5 replicates of the same original Mabisi community. Initial diversity and interactions were determining factors in community composition. However, final composition could not be predicted by initial composition. Despite the changes in community composition, a directed change in function was not found. This suggests that different groups of bacteria might have the same function in this system. We observed that upon repeated cycles of propagation bacterial community composition was highly dependent on initial composition and to a lesser extent depended on changes caused by the new environment—clean bottles in the laboratory rather than a calabash used by traditional processors. The reproducibility in the way the composition of these communities changed in their new environment opens a door for further research towards finding specific causes within the initial community for the specific compositional dynamics we observed. This would be an important step towards predicting community structure and function in novel environments. Finally, our work illustrates that (traditional) fermented foods are very suitable as tractable systems to study general ecological principles (Alekseeva et al., 2021 ; Wolfe & Dutton, 2015 ).",
"introduction": "1 INTRODUCTION In many ecosystems various species co‐exist forming species communities. Community composition is defined as the identity and relative abundances of all taxa in the community (Gill et al., 2020 ). Similar ecosystems have similar species diversities and community composition, for instance in the communities of Darwin's finches on similar islands and communities of cichlid fish in similar African lakes (Grant et al., 1976 ; Seehausen & Bouton, 1997 ), showing that similar eco‐systems have similar community composition with regard to species present. Biotic and abiotic factors are thought to generate ecological niches that support multiple species to co‐exist and stabilise eco‐systems (Hardin, 1960 ). Community composition can change due to selection pressures (Fiegna et al., 2015 ; Freilich et al., 2011 ; Gravel et al., 2010 ; Zaret & Rand, 1971 ). Selection pressures may shift the balance among the co‐existing species favouring the species which are best adapted to the selection pressure (Lawrence et al., 2012 ), leading to a process of species sorting (Langenheder & Székely, 2011 ; Székely & Langenheder, 2014 ). Key questions include whether species sorting would lead to parallel or divergent change when species communities encounter the same change in environment, when similar species or types are present in ancestral communities, and to what level species sorting is repeatable. Functionality of the eco‐system, which could be defined as the overall output of the system in terms of metabolites, is linked to community composition and may also change upon selection (Eisenhauer et al., 2019 ; Waldrop et al., 2000 ; Wolfe & Dutton, 2015 ). Here we study how a change of environment can change the community composition of fermenting bacteria in a natural microbial eco‐system derived from Mabisi. Mabisi is traditionally produced in Zambia through spontaneous fermentation of raw milk, resulting in a sour non‐alcoholic product consumed by all age groups. The bacterial community consists of six to ten main species of lactic acid and acetic acid bacteria (Groenenboom et al., 2020 ; Moonga et al., 2020 ; Schoustra et al., 2013 ). Production methods of Mabisi differ per region (Moonga et al., 2019 ). In most cases, raw milk is filled in a container, either a calabash, bucket or milk can, and left undisturbed for 24–48 h after which it is stirred and consumed. The resulting community is re‐used for the production of the next Mabisi by addition raw cow milk to the containers in which the community is present. These bacterial communities have been co‐cultured up to tens of years or maybe even more. In a food technology context the serial transfer of material is referred to as backslopping (Nout et al., 2005 ). Mabisi, like other traditional fermented foods, is a means for many small scale processors and entrepreneurs to promote livelihoods and nutrition within a local context (Materia et al., 2021b ). In this experiment, six different original Mabisi samples were used, each split in five replicates and propagated over 16 serial transfers in a common environment. We characterized the samples in terms of the bacterial community composition, i.e. the identity and relative abundances of all operational taxonomic units (OTUs) or bacterial types and functionality (metabolic output) at the start of the experiment and after the repeated transfers. The central question we address is whether initially similar communities will either become more alike (convergence) or less alike (divergence) with respect to the bacterial community composition. Final community composition could be affected by the initial composition (history—OTUs present and their relative abundance) and the selective pressures during the repeated transfers imposed by the environment (change; Travisano et al., 1995 ). If a new slightly different from the original environment is the main driver of change in community composition, we expect the communities to become more alike. However, should the slight differences in community composition between the six original Mabisi samples be the main driver, we expect community composition to diverge. By using five replicates of each of the six original Mabisi samples for the repeated transfers, we will assess how repeatable the changes in bacterial community composition and functionality are when starting with communities with slight initial differences in bacterial community composition. This will show whether there would be an optimum community composition in a given environment. Two traits related to community dynamics, metabolic profile and community composition, are measured at the beginning and end of the experiment. We used a custom statistical model to test whether initial community composition and environment were significantly affecting community dynamics and if so, whether this happened according to an additive or interactive scenario. For this we used a log‐likelihood ratio test with multinomial probabilities distributions.",
"discussion": "4 DISCUSSION We used natural microbial communities from six Mabisi samples from Zambia as starting points for 16 propagation cycles into a novel environment, splitting each original sample into five replicates. At the start and end of the propagations, we measured bacterial community composition and metabolic profiles, asking whether the composition of these microbial communities would diverge or converge upon propagation in a common environment. At the genus level, the six original microbial communities show much similarity, however, when comparing the communities at the level of OTUs and corresponding species as which then are blasted, differences between the communities can be observed (Appendix S2 : Figure S2b ). The level of similarity at the genus level, in combination with a variation in OTUs, made the different bacterial communities a suitable starting point to study potential change in bacterial community composition upon repeated propagation cycles. The original communities harboured similar species (although each species could be present at a different frequency) and thus contained the potential for community composition to converge. The environment used for the repeated propagation cycles—full fat milk in the laboratory—is simpler than the Mabisi environment the bacterial communities originated from. The new environment might have been favorable for only those bacteria that were most fit for this specific environment. This potentially caused a loss in the number of species/OTUs towards retaining only a few OTUs in the microbial community. This is, however, not what we observed. The laboratory milk environment appeared to provide enough niches to the bacterial species to maintain diversity in OTUs. Our results show that upon propagation in the new environment, the bacterial community composition changed. After 16 repeated propagation cycles two clusters emerged among our propagated communities (Figure 2 ). The two ecological clusters were characterized by the fact that OTUs classified as either Lactobacillus delbrueckii or Lactobacillus helveticus was the most abundant species. This implies these two types share the same ecological niche and seem to be interchanging their functionality. What functional properties underlie this interchanging of functionality is subject of further study, which could be implemented using metagenomic sequencing. The present study used 16S amplicon sequencing of the V3–V4 region to characterize the bacterial communities at the level of differences in OTUs. While we blasted these to a database to show to what species these OTUs could belong, our analysis does not allow to fully nor reliably identify at species level. As subspecies are substantially different in their biology and functionality, grouping bacteria by their species level is not detailed enough to determine their function in a certain environment, let alone to detect variations that exist within the same species with respect to their functional properties (Salvetti et al., 2018 ; Wittouck et al., 2019 ). Therefore, based on this study, we are unable to elaborate on what functional differences between Lactobacillus delbruecki and Lactobacillus helveticus may drive the ecological clustering. Further, the natural community used in this experiment very likely contained taxa from other domains (Moonga et al., 2019 ). The possible interactions between taxa, such as with yeasts, fungi, or bacteriophages, can also give more insight in the microorganisms present to a subspecies or perhaps even lineage level. Our results suggest that the change in bacterial community composition towards one of the two ecological states is dependent on the original Mabisi bacterial community. Predicting which cluster the community would belong to after repeated propagation cycles does not seem straightforward. For example, original Mabisi 4 and original Mabisi 5 show clear similarities (Figure 2 and Appendix S2 : Figure S2a ), while the bacterial communities after 16 propagation cycles belong to different clusters. This dependence on the composition of the original bacterial community was apparent from our maximum likelihood based tests on what factors shape the community composition of propagated communities. The environment was found to have the least influence on the change in community composition of the four tested mechanisms. It is interesting to see that allowing interactions between initial community composition and time explained an extra 18.6% of the variation, compared to the additive effect of initial community composition and time. This indicates that in one propagated lineage a certain OTU increased, while in another the same OTU decreased. We therefore hypothesise that biotic interactions within the community have a bigger influence on the fitness of a certain OTU than the selection of the abiotic environment (Dunson & Travis, 1991 ). We had expected that the increased differences in the bacterial community composition would translate into increased differences in metabolic activity (Lawrence et al., 2012 ; Waldrop & Firestone, 2006 ). However, in contrast to community composition, the metabolic profiles of the propagated communities did not show two clusters representing the two ecological states. The metabolites produced in a microbial community might thus be more dependent on the environment than on initial and current community composition. The metabolic pathways resulting in the formation of the volatiles measured might be either present in species/OTUs which are represented in both ecological states or be carried by different species but expressed in a similar way. Also, in pH, phase separation and product thickness no directed change during the repeated propagation cycles were found (Appendix S5 ). We conclude that despite clear differences between the community composition after repeated propagation cycles, the metabolic functionality, and potentially the transcriptomic profile, of the communities as a whole remained similar. This makes that community metabolism and community composition at the level of species are not directly linked. New environments can cause communities to change in composition and function. These changes are influenced by adaptation, chance, and evolutionary history (Travisano et al., 1995 ). Trait that are strongly related to fitness (such as bacterial growth rate) are more influenced by history, while traits that are weakly related to fitness (such as cell size) are more influenced by environment and chance (Travisano et al., 1995 ). Community composition was more influenced by the initial community composition (evolutionary history), while for metabolic profile this was not the case. This experiment can also be seen as an analogy to an experimental evolution with one species starting with standing variation (Prezeworski et al., 2005 ; Teotónio et al., 2009 ). In our case, however, we study the sorting of species rather than the sorting of genotypes. Due to selection pressures, one or a few individuals with the highest fitness can be selected in an experiment with standing genetic variation. In case of communities, we cannot speak about fitness of the individual, as the community does not reproduce as one organism, but rather consists of multiple organisms which all reproduce on their own and therefore have their own fitness (de Vos et al., 2018 ). However, although we cannot use fitness as defined for individual genotypes within a species, we can study how whole communities may adapt to a new environment. Although species are often studied in isolation, in nature they interact with many other organisms. Therefore, this study is focussed on the dynamics of whole communities to complement findings of studies focussing on individuals. The propagation of bacterial communities into fresh medium was repeated 16 times, amounting to around 100 cell divisions or generations. While novel mutations could arise during our experiment, these are not expected to be frequent nor to have a large impact on community composition due to the limited number of generations. A much longer selection experiment may combine factors of species sorting, which occurs at an ecological time‐scale, with effects of novel mutations that may lead to increase in abundance of some species (Kato & Watanabe, 2010 )."
} | 4,213 |
36336802 | PMC9733649 | pmc | 5,243 | {
"abstract": "Abstract Plant roots significantly influence soil microbial diversity, and soil microorganisms play significant roles in both natural and agricultural ecosystems. Although the genetically modified (GM) crops with enhanced insect and herbicide resistance are thought to have unmatched yield and stress resistance advantages, thorough and in‐depth case studies still need to be carried out in a real‐world setting due to the potential effects of GM plants on soil microbial communities. In this study, three treatments were used: a recipient soybean variety Jack, a triple transgenic soybean line JD321, and the glyphosate‐treated JD321 (JD321G). Three sampling stages (flowering, seed filling and maturing), as well as three host niches of soybean rhizosphere [intact roots (RT), rhizospheric soil (RS) and surrounding soil (SS)] were established. In comparison to Jack, the rhizospheric soil of JD321G had higher urease activity and lower nitrite reductase at the flowering stage. Different treatments and different sampling stages existed no significant effects on the compositions of microbial communities at different taxonomic levels. However, at the genus level, the relative abundance of three plant growth‐promoting fungal genera (i.e. Mortierella , Chaetomium and Pseudombrophila ) increased while endophytic bacteria Chryseobacterium and pathogenic bacteria Streptomyces decreased from the inside to the outside of the roots (i.e. RT → RS → SS). Moreover, two bacterial genera, Bradyrhizobium and Ensifer were more abundant in RT than in RS and SS, as well as three species, Agrobacterium radiobacter , Ensifer fredii and Ensifer meliloti , which are closely related to nitrogen‐fixation. Furthermore, five clusters of orthologous groups (COGs) associated to nitrogen‐fixation genes were higher in RT than in RS, whereas only one COG annotated as dinitrogenase iron‐molybdenum cofactor biosynthesis protein was lower. Overall, the results imply that the rhizosphere host niches throughout the soil–plant continuum largely control the composition and function of the root‐associated microbiome of triple transgenic soybean.",
"conclusion": "CONCLUSIONS The results showed that the transgenic soybean line treated with glyphosate altered soil nutrient dynamics by increasing soil N nutrient availability and decreasing soil P nutrient availability, but had no significant effect on root‐associated microbial communities. Moreover, the host niches and soybean growth stages had greater influence on the assembly and shift of microbial communities than novel gene insertion and glyphosate application. Thus, the use of GM soybean and glyphosate application can be deemed as safe for the composition and function of root‐associated microbial communities in the present study. These studies will be useful for precise and safe control of GM crops and glyphosate in ecological agriculture.",
"introduction": "INTRODUCTION The safety of genetically modified (GM) crops is one of the hot issues around the world. According to the report of the International Service for the Acquisition of Agri‐biotech Applications (ISAAA), the planting area of GM crops has increased from 1.7 million hectares to 190.4 million hectares in the past two decades, since GM crops provide food, feed and shelter for the 7.7 billion global population (ISAAA, 2019 ). Unfortunately, despite the incomparable advantages of GM crops, since their introduction, widespread applications have sparked persistent public concerns across the globe. Evaluating the possible negative effects of alien genes expressed in transgenic plants is critical in determining environmental safety. Microbial community analysis of the rhizosphere is a vital approach for evaluating the environmental impact of GM crops (Oh et al., 2021 ). Many prior studies have revealed the varied impacts of GM crops on the environment, particularly on the root‐associated microbial communities (Dunfield & Germida, 2004 ; Guan et al., 2016 ; Liu et al., 2005 ; Wen et al., 2019 ; Yang et al., 2020 ). The two most common target genes for GM crops are the 5‐enolpyruvylshikimate‐3‐phosphate synthase ( EPSPS ) gene and cry1c gene. The EPSPS gene can improve glyphosate tolerance, while the cry1c gene can increase insect resistance (de Maagd et al., 2001 ; Duke & Powles, 2008 ; Guo et al., 2016 ; Yang et al., 2020 ). According to several reports, glyphosate‐tolerant transgenic crops may have a significant impact on the rhizosphere's microbial communities, particularly by reducing diversity and influencing the composition of the culturable root‐endophytic bacterial community (Dunfield & Germida, 2001 ; Lee et al., 2011 ; Lopes et al., 2016 ). On the contrary, certain other EPSPS ‐transgenic crops had little to no impact on the overall bacterial community in the rhizosphere (Wen et al., 2019 ; Yang et al., 2021 , 2020 ). For insect‐resistance transgenic crops, the adsorption and binding of Bt toxin proteins to clay could result in toxin accumulation and may further affect soil microbes (Li et al., 2018 ; Strain & Lydy, 2015 ). In previous studies, Bt crops were found to dramatically impact the microbial properties and enzymatic activities in rhizosphere soil, as well as to reduce the gram‐positive to gram‐negative bacteria ratio in rhizosphere soil (Chen et al., 2012 ; Xue et al., 2005 ). In contrast, some Bt crops were shown to have no impact on the soil archaeal community or enzyme activity when compared to their parental crops (Coz et al., 2008 ; Wang, Wang, et al., 2017 ). The inconsistent effects of GM crops on the rhizosphere community could possibly be attributed to soil heterogeneity and a lack of effective control (Mandal et al., 2020 ). In fact, there is also a lack of evaluation of the practical effects of GM crops with insect‐resistance and glyphosate‐tolerance on rhizosphere microorganisms and nutrient dynamics under glyphosate application. Glyphosate has been well known for being environmentally friendly and toxicologically safe (Duke & Powles, 2008 ). However, the potential effects of glyphosate on plant mineral nutrition, diseases and soil microorganisms have attracted increasing attention (Duke & Powles, 2008 ; Johal & Huber, 2009 ; Sihtmäe et al., 2013 ). Through the analysis of more than 8000 citations, Duke et al. ( 2012 ) believed that whether the glyphosate application has a significant impact on mineral nutrition on crops is still controversial. The impact of glyphosate on soil microbiome may be masked by the redundant function of microbial community, and glyphosate treatment would further alter the composition of soil microbial community and influence several critical processes mediated by particular microbial groups (Imfeld & Vuilleumier, 2012 ). Plant host can make primary resources available, such as sugars and other chemicals, via root exudates, and hence strongly select specific microbial groups surrounding the roots (Kroll et al., 2017 ). Different crop microbiomes were dominated by different dominant taxa (e.g. Bacilli for wheat and barley and Methylobacteriaceae for maize) (Xiong et al., 2020 ). Soybean is the most widely grown oil‐bearing crop in the world, accounting for more than 50% of the world's edible oil production, and GM soybean occupies about 74% of the soybeans planted in the world (ISAAA, 2019 ). Some plant growth‐promoting rhizobacteria (PGPR) such as Rhizobium , Novosphingobium and Streptomyces have been found to be abundant in soybean rhizosphere (Liu et al., 2019 ). A recent study also demonstrated that the compartment niche and the host species have a major influence on the microbiome assembly along the soil–plant continuum as a result of the enhanced host selection pressure from soils to epiphytes to endophytes (Xiong et al., 2020 ). Although triple transgenic insect‐resistant and glyphosate‐tolerant soybeans offer more promising and superior agronomic and resistance traits, their impacts on the composition and function of root‐associated microbiomes in rhizosphere host niches throughout the soil–plant continuum remain unknown. To address these issues, a triple transgenic ( g2m‐epsps & gr79m‐epsps & cry1c ) soybean line JD321, its recipient soybean variety Jack and JD321 treated with glyphosate (JD321G), were all used to assess the alterations in the root‐associated microorganism and nutrient dynamics in response to both genetic modification and glyphosate application. Soil samples were collected at the flowering, seed filling and maturing stages, as well as three rhizosphere host niches from the interior to the outside of the roots, including intact roots (RT), rhizospheric soil (RS) and surrounding soil (SS). We aimed to test the following hypotheses: (i) the GM soybean with insect‐resistance and glyphosate‐tolerance, as well as glyphosate application would alter the rhizosphere microbial communities and nutrient dynamics; (ii) host niches would determine the differentiation of root‐associated microbial communities in response to newly introduced genes and glyphosate application.",
"discussion": "DISCUSSION Host niches determine the differentiation of root‐associated microbial communities Our results showed that the differentiation of root‐associated microbial communities was predominantly determined by the host niche, rather than newly imported genes or glyphosate application. These findings supported our second hypothesis that the sampling compartment (i.e. host niches) has a major impact on the assembly and the shift of bacterial and fungal communities, which was consistent with earlier findings (Anzalone et al., 2021 ; Loganathachetti et al., 2017 ; Wen et al., 2019 ; Yang et al., 2020 ). Different physical structures, biotic components and abiotic conditions create different potential niches for microbes (Aas et al., 2019 ). In this study, the abundance of PGPR and plant growth‐promoting fungi (PGPF) was changed gradually in the host rhizosphere niches from the inside to the outside of the soybean roots. Rhizobacteria related to nitrogen fixation represents the most important group of PGPR in soybean. Bradyrhizobium and Ensifer , two major nitrogen‐fixing genera, were more abundant in the host niche RT than RS (Figure 4A ). The result implied that the soybean root had an enrichment effect on the nitrogen‐fixing genera, which was consistent with our previous findings (Wen et al., 2020 ). However, only two species, E. fredii and E. meliloti (Bellato et al., 1997 ; Galardini et al., 2013 ), were found to be enriched in RT, whereas no changes in abundance of Bradyrhizobium species were detected. Although the relative abundance of nitrogen‐fixating bacteria Agrobacterium radiobacter (Yablunenko et al., 1995 ) was higher in RT, the ternary diagram did not show the same trend of the genus Agrobacterium among different host niches. Such discrepancies might be due to insufficient sequencing depth or improper annotation (Zhang, Bai, et al., 2020 ). Furthermore, the absence of the genus Agrobacterium may be due to the reason that Agrobacterium in the 16 S SILVA taxonomy, Agrobacterium is combined into a single genus ‘ Allorhizobium ‐ Neorhizbium ‐ Pararhizobium ‐ Rhizobium ’ with genera Burkholderia and Rhizobium (Lu & Salzberg, 2020 ), as shown in Figure S12A , thus, the limitation of existing database may affect the analysis of specific functional species. Lastly, the relative abundance of only one function classification gene, COG1433 increased from the inside to the outside of the soybean roots. This COG was defined as dinitrogenase iron‐molybdenum cofactor biosynthesis protein and was closely related to nif gene cluster (Stoeckel et al., 2008 ; Toepel et al., 2008 ). On the contrary, five of the seven COGs directly associated with nitrogen fixation were enriched in the niche RT (Figure 5 ). These results also suggest that host niches significantly affect the relative abundance of nitrogen‐fixing functional genes by enriching the aforementioned nitrogen‐fixing genera and species. Plants can improve their health or enhance their resistance against biotic and abiotic stresses by affecting the assembly of rhizosphere microorganisms, especially by enriching plant growth‐promoting bacteria and fungi (Pieterse et al., 2014 ). Three PGPF genera (Hansen et al., 2013 ; Ozimek & Hanaka, 2020 ; Wang, Zhang, et al., 2017 ), Mortierella , Chaetomium and Pseudombrophila were found to be increased gradually from the inside to the outside of the roots (Figure S10 ), implying that soybean prefer to accumulate such fungi far from their roots. Mortierella elongata has the potential to symbiotically interact with PGPRs like Burkholderia in the rhizosphere soil (Uehling et al., 2019 ). Furthermore, some symbiotic PGPF, such as mycorrhizal fungi, have been shown to develop optimal dispersal networks in the legume rhizosphere soil to aid rhizobia enrichment (Pieterse et al., 2014 ; Zhang, Li, et al., 2020 ). These findings may help to explain the enrichment trends of the three PGPF genera in RS and SS as compared to RT. Additionally, it was discovered in the current investigation that the relative abundance of one PGPR genus Chryseobacterium increased from the outside to the inside of the roots (Figure S10 ), indicating that the root had an enrichment effect on this PGPF (Zhang et al., 2021 ). According to (Pieterse et al., 2014 ; Rudrappa et al., 2008 ), PGPR epiphytes have a tendency to form biofilms, which are multicellular communities encased inside an extracellular matrix. This may be what causes PGPR genera like Chryseobacterium to be more abundant in the niche RT. Therefore, the differentiation of root‐associated microbial communities was determined by the host niches, which may have been primarily influenced by the root barrier or root exudates (Salas‐Gonzalez et al., 2021 ; Sasse et al., 2018 ; Zhalnina et al., 2018 ). Effects of plant growth stage on the nutrient dynamics and microbial communities One of the interesting findings of this study was that, in addition to host niches, soybean growth stages also played a more significant role in determining the assembly and shift of microbial communities than newly introduced gene and glyphosate application. The present investigation found significantly increased nitrate reductase and urease activities at the flowering stage (Figure 1 and Figure S1–S12 ), suggesting that the growth stages of soybean also affected the nutrient dynamics in soil. Previous research found seasonal patterns of nitrate reductase and nitrogen fixation in peanut ( Arachis hypogaea L.), that is, leaf nitrate reductase activity declined rapidly while N fixation activity of root nodules increased post‐flowering (Sung & Sun, 1990 ), which was consistent with our findings. Nitrate is an important factor affecting symbiotic nitrogen fixation of leguminous crops. Increased nitrate content causes a decrease in root nodule respiration rate and nitrogenase activity (Vadez et al., 1996 ). Therefore, higher enzyme activity of nitrate reductase is beneficial to root nodule development and nitrogen fixation at the flowering stage. In our study, it was observed that the relative abundance of genus Arthrobacter was higher at flowering stage than any other sampling stages (Figure 4 ). According to certain reports, the Arthrobacter bacteria can assist eliminate biological nitrogen, such as nitrate nitrogen (He et al., 2017 , 2020 ). Therefore, greater nitrate reductase activities may result from the enrichment effect of Arthrobacter in soybean rhizospheric soil at flowering stage, may lead to the higher nitrate reductase activities, which is beneficial to root nodule respiration and boosts the effectiveness of nitrogen fixation. GM soybean with glyphosate application altered the nutrient dynamics Our results showed that GM soybean with insect‐resistance and glyphosate‐tolerance, as well as glyphosate application, only altered the rhizosphere nutrient dynamics, not the assembly and shift of microbial communities in the real scenario. In this study, the growth of Bt‐soybeans had a major impact on soil enzyme activities involved in nutrient cycling, which was in line with earlier research (Li et al., 2019 ; Mandal et al., 2020 ). First, we found that GM soybean JD321 with glyphosate treatment (JD321G) had lower nitrite reductase and higher urease activities than the control recipient soybean cultivar Jack at the flowering stage (Figure 1 ), suggesting that the GM soybean with glyphosate application decreased nitrogen loss and increased the inorganic nitrogen supply in soil. The nitrite reductase is one of the intracellular enzymes that participates in denitrification and can reduce the accumulation of nitrite nitrogen in the environment (Meakin et al., 2007 ). According to some previous studies, denitrification may sometimes accelerate under Bt crops by promoting nitrite reductase activities along with an increase in denitrifying bacteria (Li et al., 2019 ; Wu et al., 2004 ). However, other studies claimed that Bt crops had little to no impact on bacterial nitrite reductases (Szoboszlay et al., 2019 ). These results were inconsistent with our findings, and the possible explanation can be that we applied glyphosate in the planting of GM soybean in the real scenario, which was not completely consistent with the treatments in the previous studies. Urease enzymes can help with nitrogen mineralization by converting urea into inorganic nitrogen (Li et al., 2019 ). Higher urease activity may result in enhanced nitrogen cycling, which is consistent with recent research that demonstrated increased nitrogen mineralization under Bt crops (Li et al., 2019 ; Sarkar et al., 2009 ). The higher nitrogen cycling in soil cause the plants grow bigger and retain more N and take up more N, while their roots release more exudates to stimulate saprophytic microbes for mineralization at the same time. Soil enzymes are a sensitive indication of soil metabolic processes and fertility, and their activities are affected by soil chemical properties and microbial compositions under GM plants (Bennicelli et al., 2009 ; Bila et al., 2020 ; Li et al., 2019 ). However, utilizing high‐throughput sequencing analysis in this study, the nitrogen‐fixing endosymbiont genus Bradyrhizobium , which was closely related to rhizobial denitrification (Lopez et al., 2017 ), along with some copiotrophic ureolyric microbes such as Betaproteobacteria, Alphaproteobacteria, and Gammaproteobacteria which were associated with soil urease activity (Wang et al., 2019 ), showed no significant difference in abundance among Jack, JD321 and JD321G. The glyphosate application accelerated soil nitrogen cycling. When comparing JD321G with JD321 in this study, we discovered that the use of glyphosate increased the urease activity at the flowering stage (Figure 1 ), which was consistent with previous studies (Kunanbayev et al., 2019 ; Sannino & Gianfreda, 2001 ). Glyphosate is moderately persistent in soil, and the decomposition rate should be closely related to the enzymatic activities of soil microorganisms (Gimsing et al., 2004 ; Veiga et al., 2001 ). But as of now, there are no changes between JD321 and JD321G in the relative abundance of the related microorganisms. The rhizospheric soils of JD321G were discovered to have less alkaline phosphatase and acid phosphatase activity than Jack (Figure 1 ), which suggests that GM soybean cultivation with glyphosate application may limit phosphorus mineralization. Although several investigations discovered that enzyme activities remained unchanged in Bt crops (Mina & Chaudhary, 2012 ), numerous studies have shown that the response rates of phosphatase are often lower in Bt crops than in non‐Bt crops in field experiments, which may be due to Bt protein secretion (Li et al., 2019 ; Sarkar et al., 2009 ). Acid phosphatase and alkaline phosphatase are strongly associated with rhizosphere phosphorus (P) content and P cycle efficiency, hence promoting the mineralization of soil organic P (Wang et al., 2022 ). Additionally, the nutritive usage of glyphosate was associated with the absorption of phosphate, which means that glyphosate application increased the amount of nutritive phosphorus in soil (Drzyzga & Lipok, 2018 ; Ortiz et al., 2017 ). This excess supply of phosphorus brought on by glyphosate application may also be the cause of the inhibitory activity of phosphatase under JD321G. Furthermore, root‐associated microbial communities play a major role in controlling the amount of available soil P, in particular, arbuscular mycorrhizal fungi (AMF) improved the mineralization of soil organic P and have a positive impact on root phosphatase activities (Cordero & Datta, 2016 ; Ortiz et al., 2015 ; Wu et al., 2021 ). However, there were no significant differences in the relative abundance of AMF or other P‐solubilizing microorganism among Jack, JD321 and JD321G. As a result, we found that GM soybean showed a considerable response to glyphosate application in rhizosphere nutrient dynamics, despite having no influence on the root‐associated microbial communities. Realities and hopes of agricultural microbiome Microbiota are essential components of the soil, driving biogeochemical cycles and promote plant growth and productivity, and contribute to the end of hunger (Hu et al., 2022 ; Zhu et al., 2021 ). Application of agricultural microbiome could make the food and agricultural system more efficient, resilient and sustainable than rely on synthetic chemical fertilizer technology (Hu et al., 2022 ). Over the past decade, due to the risk of biotic and abiotic stresses and agrochemicals, and the loss of efficacy of some agrochemicals and plant breeding programmes, the use of agricultural microbiome to sustainably increase agricultural production has received more and more attention from researchers to practitioners (Batista & Singh, 2021 ). By integrating recent advances in plant‐associated microbiome science methods including genomic, metabolic techniques, bioinformatics and synthetic community with classical microbiology, researchers can better explore the mechanism of soil microbiota (including many species that have yet to be cultured and characterized) (van der Voort et al., 2016 ; Vorholt et al., 2017 ). Furthermore, the long‐term experiments of the complex interactions among microorganisms (e.g. quorum sensing) in depth and connecting environmental and evolutionary microbiology will also be necessary for fully understand the potential the potential efficacy and mechanism of the application of agricultural microbiome (Corral‐Lugo et al., 2016 ; Espinosa‐Urgel, 2022 ). Thus, the agricultural microbiome will not only play an important role in ecological agricultural production but also contribute towards basic study, job creation and mitigation of the impacts of climate change (Batista & Singh, 2021 ). There are several important limitations to the study as well. Both the soybean yield traits and the Bt protein residues secreted by GM soybean in soil were not studied in this investigation. The present study is expected to provide a first‐hand data and scientific basis of the selection and application of plant growth promoting bacteria/fungi in soybean rhizosphere in the future work. Due to the complex network of root‐soil‐microbe interactions, it is necessary to conduct long‐term studies to analyse the effects of GM soybean with insect‐resistance, glyphosate‐tolerance and glyphosate application on rhizosphere interactions and functional groups of microbes in order to obtain comprehensive data for evaluating the bio‐safety of GM crops on the soil environment in ecological agriculture."
} | 5,958 |
38547104 | PMC10977701 | pmc | 5,244 | {
"abstract": "In spatially structured microbial communities, clonal growth of stationary cells passively generates clusters of related individuals. This can lead to stable cooperation without the need for recognition mechanisms. However, recent research suggests that some biofilm-forming microbes may have mechanisms of kin recognition. To explore this unexpected observation, we studied the effects of different types of cooperation in a microbial colony using spatially explicit, agent-based simulations of two interacting strains. We found scenarios that favor a form of kin recognition in spatially structured microbial communities. In the presence of a “cheater” strain, a strain with greenbeard cooperation was able to increase in frequency more than a strain with obligate cooperation. This effect was most noticeable in high density colonies and when the cooperators were not as abundant as the cheaters. We also studied whether a polychromatic greenbeard, in which cells only cooperate with their own type, could provide a numerical benefit beyond a simple, binary greenbeard. We found the greatest benefit to a polychromatic greenbeard when cooperation is highly effective. These results suggest that in some ecological scenarios, recognition mechanisms may be beneficial even in spatially structured communities.",
"introduction": "Introduction Microbial life is rife with complex interactions between and within species. As a necessary part of existence, microbial social interactions can vary from chemical warfare, to competition, to synchronization, to cooperation [ 1 , 2 ]. Like all cooperative communities, microbes are susceptible to invasion by selfish individuals who benefit from cooperation [ 3 ], but do not contribute [ 4 – 10 ]. Despite the potential for invasion, cooperative behaviors are prevalent in natural systems. Such behaviors can often be explained through kin selection: individuals cooperate with relatives that likely share genes for the behavior. If the fitness benefits of the behavior are large enough, the frequency of the cooperative allele(s) will increase in the population, such that cooperation will outcompete other strategies [ 11 , 12 ]. One way to ensure the stability of kin-selected cooperation is through kin recognition in which individuals recognize and preferentially cooperate with related individuals [ 13 ]. While recognition of relatives has been documented in animals, it is uncommon in microbial systems. Instead, there is “kind” recognition where cooperators recognize each other through a particular signal; this system is known as a greenbeard. A greenbeard locus encodes a cooperative behavior (a single or multiple, tightly linked genes), a signal of cooperation, and the ability to recognize the signal in others [ 14 , 15 ]. For a greenbeard system to function, there must be relatedness at the locus, but not necessarily across the entire genome. Microbial examples include cell adhesion proteins that allow cells to attach to one another, as has been reported in yeast and social amoebae [ 16 – 19 ]. In aggregative cooperative behaviors that require motile microbes to locate one another before adhering, such as the formation of foraging slugs, fruiting bodies, or swarms, rare instances of kin- and self-recognition have been reported [ 9 , 20 , 21 ]. Rather than a binary system of cooperation or non-cooperation, as is expected for a greenbeard locus, the proteins responsible for cellular adhesion exhibit a spectrum of cooperation (e.g., strength of cell-to-cell interaction) related to allelic variation, thus creating a “polychromatic greenbeard” [ 22 , 23 ]. A polychromatic greenbeard is more similar to traditional kin recognition, as individuals with identical “shades” of green tend to be more closely related across the genome, as long as rates of recombination are low [ 24 , 25 ]. In contrast to motile microbes, many microbes live and interact in stationary, spatially-structured communities known as biofilms. These communities are characterized by attachment to a surface, an extracellular matrix produced by the microbes, cellular differentiation, and increased resistance to environmental stressors [ 26 ]. Biofilms exist in nearly every environment in which microbes can be found, including medical settings where their presence is a particular risk due to their increased resistance to antimicrobials [ 27 , 28 ]. Biofilms require individuals to cooperate and produce goods that will be used by other members of the community (i.e., extracellular matrix, drug efflux pumps, diffusible enzymes, quorum sensing molecules) [ 2 ]. Mathematical modeling, simulations, and microbial experiments have demonstrated that unlike in aggregative and motile phenotypes, biofilms do not require a recognition system for cooperation to be stable (reviewed in [ 29 ]). Clonal growth generates local patches of high-relatedness and leads to lineage sorting [ 30 – 32 ]. In this way, passive spatial assortment leads to kin selection without the need for kin recognition. Despite the body of work suggesting recognition systems are not required for stable cooperation in biofilms, recent research has provided evidence that a cell adhesion protein may actually act in recognition in the budding yeast Saccharomyces cerevisiae , a stationary, biofilm-forming eukaryotic microbe [ 33 , 34 ]. Given this unexpected observation, here we ask whether greenbeard and polychromatic greenbeard systems could provide a benefit to cooperators in stationary microbial communities. While such recognition systems may not be required for stable cooperation, it is possible they provide enough of a fitness benefit to explain the presence of recognition systems in species whose characteristics preclude motility. We hypothesize that even with the passive emergence of clusters of direct kin, the ability to restrict cooperative benefits will lead to increased representation of cooperators in a growing spatially-structured community. Our approach to addressing this question uses spatially-explicit, agent-based simulations of a growing microbial community containing two cell types. The simulations represent a simplified microbial community in which cells interact under different scenarios (with different sets of rules). Briefly, in our simulations, cooperators have a slower basal growth rate than non-cooperators, which represents the cost of producing non-diffusible/locally diffused public goods and other traits associated with biofilm formation. Cells that are adjacent to cooperators have an increased growth rate due to the benefit provided by the cooperative goods. A greenbeard recognition system is implemented by allowing cooperator cells to only increase the growth rate of cooperator neighbors. Finally, we investigate the effect of a polychromatic greenbeard by simulating microbial communities with two cooperator cell types that have different basal growth rates and can restrict growth benefit to their own cell type. We simulate different scenarios over a range of starting ratios of each cell type and of the strength of cooperation.",
"discussion": "Discussion The goal of the simulations presented here was to investigate the effects of different types of cooperation on the frequency and arrangement of cells in spatially structured microbial communities, and in particular, determine whether a polychromatic greenbeard (i.e., microbial kin recognition) could provide a fitness or growth benefit in such a community. Our simulations began with a small inoculum of different starting frequencies of two cell types. This could represent an experimental situation, such as starting a colony on a petri dish, or a more natural situation, such as a migration via an insect to a new environment or resource patch. The probability of growth for each cell depended on its type and neighborhood. We tracked the colony growth over time and monitored the change in frequency of the cell types. The simulations were fitness-based models that altered growth rates based on different types of cell-cell interactions. The model did not consider biological mechanisms, such as nutrient flux or enzyme diffusion, as the goal was to determine whether certain types of interactions could provide a fitness benefit, not to model the specific dynamics of an experimental system [ 29 , 38 ]. Despite not including explicit mechanisms in our model, the scenarios we simulated are rooted in biological phenomena that exist in spatially structured communities. The obligate cooperators growing with non-cooperators captures the idea of a locally diffusible enzyme that can be used by producers and non-producers alike (e.g., [ 39 – 43 ]), or floating aggregates that can contain non-producing cells that ultimately lead to the collapse of the community [ 44 ]. It is within this context that it is possible to ask whether a recognition mechanism in which cooperators only provide growth benefits to other cooperators might provide a fitness advantage, which was tested in our greenbeard and non-cooperator simulations. For biofilms, these simulations capture the idea of only adhering to cells also expressing adhesins [ 17 , 19 ]. And finally, we ask if restrictive cooperation in which cooperators provide growth benefits exclusively to specific cooperator types might provide a further fitness advantage, tested in our polychromatic greenbeard simulations. In the case of diffusible enzymes, this could be the advantage of enzyme-receptor specificity [ 45 ], while in the case of biofilms, it could be adhering to cells with the same adhesin alleles [ 34 ]. In the first set of simulations, our results confirmed that obligate cooperation can increase in frequency in spatially structured communities, even when “cheating” [ 3 , 46 ] is possible, as long as the growth benefit provided by cooperative cells is only local. This has been studied most extensively as diffusible public goods using experimental, computational, and theoretical approaches (reviewed in [ 29 ]). Our simulation model results qualitatively agree with the conclusions of those studies: when growth promotes clonal clusters, the benefit to the cooperative behavior is mostly shared with clonemates, and can therefore resolve the public goods cheating dilemma. In this first set of simulations, we also investigated greenbeard cooperation in a community with non-cooperators. In microbes, this kind of cooperation is usually in the form of cell-cell adherence, and has been investigated experimentally and computationally [ 17 , 19 , 30 , 32 , 37 , 47 ]. Once again, our simulations qualitatively confirm findings from these studies: the ability to adhere selectively promotes spatial segregation and can even be used as a weapon against non-adhering strains. In our simulations, we were able to compare the increase in frequency of cooperators under the different types of cooperation, and found that greenbeard cooperation is able to increase in frequency more than obligate cooperation, a somewhat surprising result for spatially structured communities. The clonal growth of stationary cells passively generates local clusters, so it was unclear in advance whether a greenbeard cooperator would provide much of a growth advantage compared to an obligate cooperator that is able to interact within a cluster of like types. Finally, we found that the benefit to both obligate and greenbeard cooperation when grown with non-cooperators was realized as communities became denser at the end of the community expansion. The increase in density allowed the growth benefits of cooperators to have an effect as cells were in contact more [ 48 ]. Our second set of simulations investigated whether a polychromatic greenbeard, in which the cells only cooperate with their own type, could provide a numerical benefit beyond a simple, binary greenbeard. The results showed that a more fit, faster-growing lineage will be hampered by the presence of a less fit, slower-growing lineage because the slower lineage will gain a growth benefit from being near the more abundant, faster one. The results also show that if one of the strains were able to restrict their cooperation (the asymmetric case of one polychromatic greenbeard and one simple greenbeard), such a strategy would be favored over the symmetric greenbeard case (i.e., the faster strain increases its relative frequency when it is selectively cooperative, and the slower strain increases its relative frequency when it is selectively cooperative). Finally, we also see that restoring the symmetry, by both strains only cooperating with their own type, would be favored. That is, when one strain has the advantage of restricting cooperation (i.e., a form of “cheating”), if other strain also becomes selectively cooperative, its frequency will increase. This suggests that if one lineage were to evolve a mechanism for selective recognition, selection would favor a similar mechanism in the other. This could lead to a polychromatic greenbeard cooperative system in a spatially structured community. The question of the general conditions that favor the evolution and stability of kin recognition is different than that which is addressed here (reviewed in [ 49 ]). We simply show that there are conditions under which a recognition system could provide a numerical fitness benefit. The simulation model used for this research was inspired by an investigation into the spatial arrangement of microbial communities with different types of ecological interactions [ 35 ]. While the goal of our work was to compare the effects of obligate and restrictive cooperation on population growth, and not to measure spatial characteristics per se, it is worth noting the similarities and differences between the sets of simulated communities from the two research endeavors. Briefly, Momeni et al. described the effect of one cell type on the other as either neutral (∼), positive (↑), or negative (↓), but assumed the effect of a cell on its own type was neutral. For example: (∼, ∼) was baseline cooperation in which cell types simply competed for resources; (∼, ↓) was amensalism in which one cell type harmed the other; and (↑, ↑) was cooperation in which each cell type benefitted from the other. A main conclusion from Momeni et al.’s research was that cooperation (↑, ↑) led to spatial “intermixing” of lineages, while other ecological interactions led to spatial segregation. In their conceptual framework, cooperation was defined as a relationship between lineages and was inspired by the biological phenomenon of two auxotrophic cell types secreting products that complement the other’s needs. It therefore makes intuitive sense for the cell lineages to mix as they enhance each other’s growth. In our simulations, cooperation was defined within a lineage and was inspired by a different biological phenomenon, one in which a single lineage produces goods that enhance its own growth, but goods that can possibly be utilized by others, unless restricted. Comparing the models, our “obligate cooperation” (with the potential for non-cooperators to be considered cheaters) is the same as their commensal (∼, ↑), except in our case, the lineage providing the growth benefit also helps its own growth. Similarly, our “two simple greenbeards” is the same as their (↑, ↑) cooperation, except again, our lineages also enhance their own growth. We did not calculate an intermixing index, but we can ask qualitatively, what kind of spatial arrangements were generated by the cooperative interactions in our simulations? Most of our simulated colonies showed strong spatial segregation. The two scenarios that showed the most intermixing between lineages were: (1) an obligate cooperator with a non-cooperator ( Fig 2B ), and (2) two simple greenbeards ( Fig 5A ); however, neither of these scenarios appeared to show as much mixing as the (↑, ↑) cooperation in the Momeni et al. simulations. Notably, these are the only two cases in which none of the lineages can restrict the growth benefits of cooperation. Using their definitions, restricting cooperation simply reverts a lineage to neutral (∼) in its effect on the other strain. Thus, most of our simulations fall within the “non-cooperation” designation of their framework and have the spatial assortment associated with it. It thus appears that the amount of intermixing expected in a cooperative microbial community depends strongly on the type of cooperation: restricting the benefits of cooperation to like kinds can lead to enhanced segregation, rather than the cooperative intermixing previously reported. While the details of the simulations and the parameter values used here may not be representative of all, or even most, microbial communities, the qualitative result, that there are possible scenarios that favor a form of “kin recognition” in spatially structured microbial communities, may be more general. They may also shed light on recent observations in yeast and bacteria that suggest specificity in social traits may exist in natural microbial populations [ 34 , 45 ]. In a study of Pseudomonas bacteria, producers and non-producers of pyoverdine (an iron-scavenging compound considered to be a local public good) were isolated within soil communities, suggesting cooperators and cheaters exist together in nature in a spatially structured environment [ 45 ]. Furthermore, the ability of non-producers to use the pyoverdine of producers was affected by relatedness. In the Saccharomyces yeasts that inspired this research, different genotypes can be found as close as on the same tree [ 50 , 51 ] and research with Drosophila has shown that yeast spores can traverse the digestive tract with viable spores deposited post-digestion [ 52 ]. Cellular adhesins required for yeast biofilm formation show different adherence properties in self and non-self combinations [ 34 ]. Thus, there are plausible ecological scenarios in which multiple genotypes may inoculate and compete in a new environment. More broadly, in many natural microbial populations, diverse lineages are isolated from the environment, and the diversity is often related to the ecological function and evolutionary history of the species [ 53 ]. Thus, the potential exists for the type of interactions studied here to exist in natural settings."
} | 4,585 |
34231559 | PMC8294043 | pmc | 5,248 | {
"abstract": "Natural and artificial proteins with designer properties and functionalities offer unparalleled opportunity for functional nanoarchitectures formed through self-assembly. However, to exploit this potential we need to design the system such that assembly results in desired architecture forms while avoiding denaturation and therefore retaining protein functionality. Here we address this challenge with a model system of fluorescent proteins. By manipulating self-assembly using techniques inspired by soft matter where interactions between the components are controlled to yield the desired structure, we have developed a methodology to assemble networks of proteins of one species which we can decorate with another, whose coverage we can tune. Consequently, the interfaces between domains of each component can also be tuned, with potential applications for example in energy – or electron – transfer. Our model system of eGFP and mCherry with tuneable interactions reveals control over domain sizes in the resulting networks.",
"conclusion": "4 Conclusions By carefully controlling interactions in a binary protein system, we have assembled a nanoarchitecture with tunable domain sizes. In particular we have used specific interactions between a trivalent ion (Y 3+ ) to assemble a backbone network of eGFP. In the second step of assembly, we add another protein mCherry, which has been cationised such that it does not interact with the trivalent ion. In order that the mCherry binds to the eGFP network, we use a nonspecific salt, ammonium sulphate. Our assembly approach leads to mesoscopic domains of mCherry on the eGFP network. By tuning the composition of the two proteins, we find that the domain size can be tuned, and we deduce that this is due to competing assembly mechanisms of the mCherry onto the network: at low mCherry concentrations, mCherry–eGFP encounters dominate, leading to more protein mixing and smaller domain sizes. Increasing the mCherry concentration leads to mCherry–mCherry encounters dominating instead, such that aggregates of mCherry form prior to decorating the eGFP network and decreasing mixing. An interesting possibility for the future would be to develop computational approaches similar to the ground breaking work on the crystallisation of rubredoxin by Fusco et al. 57 This would help to shed further light into the protein–salt interactions as well as the self-assembly and network decoration mechanisms at play. However, in making analogy with colloidal systems, we believe that the networks formed here are consistent with spinodal gelation, 53,58 pertaining to systems where strong attractions, without significant directional dependence drive gelation, as has been observed previously in lyzozyme gels. 59 In this sense, these are non-equilibrium structures and on long timescales could perhaps condense further. 54 Our work emphasises the complexity of protein–salt interactions and highlights the need for further studies to understand better the specific interactions involved to obtain the desired structures. To this end, we have investigated selective control of protein–protein interactions, fundamental to realising the goal of tunable multi-protein architectures at mesoscopic lengthscales. Additionally, we have shown the structures formed are networks and determined the protein–protein interactions with small angle X-ray scattering and found behaviour consistent with theory. 18 By using fluorescent proteins to monitor the protein stability, we provide some evidence that the structure may be preserved during the self-assembly process, since only folded proteins will contribute to the fluorescence corresponding to their fluorophore observed in the gels. As such, binary mixtures of proteins with enzymatic, charge-carrying, antibiotic and light-harvesting abilities can be designed de novo and assembled into micron-sized porous networks through the methodology developed herein. Compartmentalisation and/or immobilisation of enzymes allows for the combination of complex multi-step reactions and mimics the cascade metabolic pathways found in nature. Additionally, the enzyme close proximity resulting from it, might improve synergistic interactions between enzymes involved in sequential reactions. 60,61 For applications, immobilisation also improves enzyme operational, thermal, mechanical and storage stability. 62 Efforts to immobilise single or mixtures of enzymes have been obtained before in so called cross-linked enzyme aggregates (CLEAs), where the proteins are mixed together in solution, precipitated and crosslinked. 60–62 In these aggregates the protein catalytic activity is comparable with their counterparts in solution. 60 In contrast to CLEAs, our approach offers a better control over the assembly and the interactions of binary protein structures. In addition, the porous structure on our gels, might also facilitate the flux of substrates and products, and might help with the recovery of the final compounds of interest. Moreover, the proteins involved in our decorated networks do not require compatibility or specificity on their mutual interactions. Additionally, group-specific cross-linking of the decorated networks can provide further stability and will allow the elimination of the precipitating salts for future applications. Finally our methodology is straightforward, cheap, versatile and scalable, and hence, it opens the door for new strategies to produce a novel class of innovative functional biomaterials beyond the fluorescent proteins we have used here to demonstrate the method. For instance, a similar approach with enzymes can yield advanced materials where sequential multi-enzyme catalysis can be incorporated; light harvesting arrays can be obtained for energy transduction; and electron transfer proteins can form small scale electronics.",
"introduction": "1 Introduction Complex, hierarchical, materials with long-range ordering, comprised from building blocks at the nano- and micro-scale can be obtained by controlling self-assembly, through careful manipulation of the interactions between the assembling components. 1–3 If the constituents of such structures exhibit useful optical, magnetic, electric, chemical or biological properties, then the assemblies formed hold great potential for a myriad of applications including photonics, energy transfer and storage, catalysis, drug delivery and tissue scaffolding. 4–9 Perhaps the greatest source of inspiration for design and construction at the nanoscale is nature itself. The exquisite level of complexity, specificity, efficiency and sophistication of systems found in nature makes their building blocks (proteins, nucleic acids, carbohydrates and lipids) an attractive possibility to be exploited for new materials. Of these building blocks, proteins exhibit the largest diversity of structure and function and thus have the greatest potential to be exploited as the functional components for novel nanostructured materials. 5–8,10–13 They are capable of carrying out structural, catalytic, transport, packaging, optical, specific recognition, electrical, information storage and metabolic functions. 5,6 Among synthetic materials, dispersions of colloids and nanoparticles self-assemble to a very wide variety of structures, which can be controlled by tuning the interactions between the particles. 14 Similarly interactions between proteins determine the structures into which they assemble. 15–20 Here we take inspiration from self-assembly of soft matter systems such as colloids in the context of protein assembly to form a 3d network of a binary protein system. In nature, assembly of proteins into networks is often avoided, so that a condensed phase is formed only if (i) they have evolved to do so ( i.e. compartmentalised structures like carboxysomes or viral capsids), if (ii) mutations lead to mis-folding or to interactions that produce aggregation, or if (iii) changes in the medium ( i.e. ionic strength or significant changes in temperature or pH) occur. 16,19,21,22 In the latter two scenarios, the proteins may lose their functionality. Furthermore, unlike most gel networks found in nature, here we aim to produce an architecture with a binary system in which the domain size of each species can be controlled. By incorporating multi-enzyme cascades, light harvesting arrays and electron transfer proteins, such multicomponent networks hold great potential as advanced materials for catalysis, energy transduction and small scale electronics. While so-called bigels of two distinct unconnected, mixed or bicontinuous networks have been produced with colloids, 23 (denatured) proteins 24 and in simulations with patchy particles, 25 here our focus is on a single network of two components, where we can control the assembly such that the domain size and hence the interfaces between domains can be tuned. In particular, we aim to self-assemble decorated protein networks formed by distinguishable protein domains, where these preserve their native structure. The fluorescent proteins enhanced green fluorescent protein (eGFP) and mCherry were chosen as the model system due to the ease of monitoring the assembly process with fluorescent microscopy. To assemble these structures, we develop a strategy to control the interactions of each species independently, similar to Immink and collaborators. 26 Here, we exploit the effects of salts on protein solutions, 18,27–29 based on specific salt–protein interactions. Trivalent ions have been shown to selectively interact with the surface-exposed carboxylic groups of the acidic residues of the proteins, which in turn, leads to gelation or crystallisation. 30–32 Thus, by effectively modifying the surface of the proteins, we provide the specificity required to gain control over their self-assembly at mesoscopic lengths of tens of nanometers and upwards. We also use nonspecific interactions via the addition of ammonium sulphate so that we have two methods to control the interactions between the proteins. Since the specific interactions are controlled by trivalent ions (here Y 3+ ) which interact with a negatively charged protein (eGFP), the non-specific protein (mCherry) is cationised such that it should be independent of the yttrium. This leads to a binary protein system with opposite charges which can then weakly associate. Therefore our strategy to assemble the binary network is to first assemble the eGFP into a backbone of the network and then to decorate this backbone with mCherry, which we assemble by addition of ammonium sulphate. Depending on the concentration of mCherry, we find different mechanisms of assembly of the mCherry which provides a means to tune the coverage of the eGFP network. As such, the strategies proposed herein represent a promising route to yield a new type of functional biomaterial, a multicomponent 3d network whose domains could have enzymatic, electron or energy transfer properties for example. Our work is organised as follows. In Section 2 we describe the methods followed. In Section 3 we present and discuss our results. We start by showing the increment in the specificity of protein–salt interactions to gain sufficient control over the gelation process. This is followed by studying the nature and strength of the protein–salt interactions in the presence of different salt concentrations using small-angle X-ray scattering (SAXS). Once we stablished the interactions, we then proceed to assemble the desired structures, following the proposed two-step addition of native and modified proteins to different salts, along with the structure characterisation using confocal laser scanner microscopy. We then implement our strategy for different protein compositions to tune the protein domain sizes within the network and propose a mechanism for our findings. Finally, we study quantify the structure of our decorated networks via their fractal dimension. In Section 4 we summarise our conclusions.",
"discussion": "3 Results and discussion We present our results and discussion in four main sections. The first section corresponds to tuning the protein–protein interactions to gain sufficient control over the assembly process using small-angle X-ray scattering (SAXS). We then proceed to assemble the desired structures following the two-step process of assembling a network of eGFP which is subsequently decorated with mCherry. In the third section, we demonstrate tuning of the protein domain sizes within the network. Finally, we obtained the fractal dimension of the decorated networks to characterise their structure. 3.1 Controlling specificity of protein interactions To suppress non-specific interactions between the salts and the proteins, we require high protein–salt specificity. To achieve this, we focus on yttrium chloride (YCl 3 ). 31 While iron chloride would in principle be an alternative, precise control over the pH during the assembly process is important and we are more confident of this with YCl 3 . The results are illustrated in Fig. 3a and Fig. S1a (ESI † ) where eGFP forms a network readily upon the addition of Yttrium Chloride. So that the yttrium chloride only interacts with the eGFP, we cationise the mCherry, which suppresses its interaction with the metal cation due to the positive charge on the protein resulting from the cationisation. We determined the cationised mCherry (c-mCherry) ζ -potential at pH = 7.4 and calculated its effective surface charge Q 31 (see Methods section for further details). We observed a charge inversion for the cationised mCherry ( ζ c-mCherry = +9.3 mV and Q c-mCherry = +7.51 e ) from its native negative counterpart ( ζ mCherry = −7.0 mV and Q mCherry = −5.90 e ). To test if we have effectively “blocked” the interaction between YCl 3 and c-mCherry, we mixed solutions of c-mCherry against the same concentrations of salts as for the eGFP. We did not observe any assembling for the c-mCherry at any concentration of YCl 3 up to 50 mM as shown in Fig. S2a (ESI † ). Finally, we demonstrated assembly through non-specific interactions using ammonium sulphate, 29 (NH 4 ) 2 SO 4 . To destabilise c-mCherry, we added 3 M of ammonium sulphate to a 7 mg mL −1 solution of the protein. Images of the results obtained are shown in Fig. 3b and Fig. S2b (ESI † ) where the cationised protein formed networks whilst retaining its fluorescent properties. We thus obtained a system where eGFP forms a network through specific interactions with YCl 3 , whereas the cationisation of mCherry successfully modified the net charge of the protein from negative to positive and the assembly of the cationised protein with said salt was effectively avoided. However, the non-specific interactions with ammonium sulphate were not affected and c-mCherry assembled readily with this salt. We used these specific and differential interactions to yield the decorated networks. 3.2 Determination of protein–protein interactions In order to determine the interactions in our system, we conducted small-angle X-ray scattering (SAXS) studies on protein solutions (10 mg mL −1 ) with different salt concentrations: eGFP with YCl 3 and c-mCherry with (NH 4 ) 2 SO 4 , all below the precipitation concentration. We chose to consider solutions below the precipitation concentration because under these conditions it is possible to relate the protein–protein interactions to the static structure factor S ( q ). 14 Additionally, we further purified the proteins through size exclusion chromatography to eliminate any impurities that might interfere with the measurements. However, we did not filter the samples after salt addition and thus they were studied as prepared. We consider solutions of one species only for simplicity and also because each species is in solution at different stage of the assembly sequence ( Fig. 1 ). Further details are given in the Methods section. The scattering intensity, I ( q ) is related to the product of the form factor P ( q ) and the static structure factor S ( q ). I ( q ) = ϕV protein (Δ ρ ) 2 P ( q ) S ( q ) where ϕ is the volume fraction of the proteins, V protein is the volume of the protein, Δ ρ is the difference in scattering length density between the proteins and its supporting solvent. Under certain assumptions, the structure factor is uniquely determined by the pair interaction potential between the proteins. 18,40,41 Fig. 1 Strategy to yield decorated protein networks. (a) Specific interactions of trivalent Y 3+ ions and eGFP and protein surface modification (cationisation) of mCherry are exploited to provide and control the specificity of protein–salt interactions to yield a decorated network with distinguishable protein domains. (b) Two-step design methodology, where a backbone network of eGFP is formed first, followed by its decoration with cationised mCherry domains. The scattering intensities for eGFP and c-mCherry are shown in Fig. 2a and c , respectively. It has been previously found that interactions in globular protein solutions in the presence of salts resemble those of charged particles with short-range attractive potentials. 30–32,42–44 In our system, in the absence of added salt we obtain a system with electrostatic repulsions. When the salt concentration is increased, we find a reduction of the strength of the repulsive interactions due to attractions between the proteins by either forming bridges (YCl 3 ) 30–32,43 or by decreasing their solubility through non-specific interactions ((NH 4 ) 2 SO 4 ). 29,45 Fig. 2 Determining protein–protein interactions with small angle X-ray scattering (SAXS). (a) and (c) SAXS scattering intensity with a cylinder and a Ornstein–Zernike model fitting for 10 mg mL −1 protein solutions of eGFP with different YCl 3 concentrations and a cylinder fitting of cationised mCherry with various (NH 4 ) 2 SO 4 concentrations, respectively. (b) Evolution of the lengths of the protein dimers and small aggregates and correlation lengths, ξ of eGFP at different YCl 3 concentrations. (d) Evolution of the length of cationised mCherry as (NH 4 ) 2 SO 4 concentration is increased. In order to determine these interactions we first fitted our SAXS data with a cylindrical form factor 46 to obtain information on the dimerisation and aggregation of small numbers of proteins. The results obtained are shown in Fig. 2a and c and in Tables SI and SII (ESI † ), where we found different behaviour for each protein. It is worth noting that we sought to describe the protein–salt behaviour in our gel formation strategy, thus, we did not filter any of the samples to eliminate small aggregates, nor did we perform any concentration corrections in the data to account for the possible formation and precipitation of the former. Previous work on eGFP revealed that the protein exists in dimers. 46 When no YCl 3 is present, SAXS data indicates the presence of cylinders with a diameter of 30 Å and lengths of ∼80 Å, consistent with dimers as illustrated in the inset in Fig. 2a (Table SI, ESI † and Fig. 2b ). As the concentration of YCl 3 is increased, the length of the cylinders we fit also increases, indicating protein association. This is also shown as an upturn in S ( q ) at low wavevector q in Fig. 2a . To fit this q range we used the product of the cylinder form factor and the Ornstein–Zernike (OZ) form for the structure factor. We obtained the correlation length, ξ , of the density fluctuations, which we interpret as transient clusters, using S ( q ) ∼ [1 + ( qξ ) 2 ] −1 . 47 The results are shown in Fig. 2b , where we found an increase in the correlation length ξ as the salt concentration is increased. However, we do obtain large errors for these fittings. We then can only interpret these results as an indication of sequential protein association, following yttrium ions bridging. 30 The fitted parameter for the form factor and structure factor indicate we have charge-stabilised eGFP dimers between which the repulsion is decreased as YCl 3 is added to the system as illustrated in the inset in Fig. 2a . On the other hand, c-mCherry presents a completely different behaviour upon addition of ammonium sulphate. Our form factor fitting where no salt is present in the protein solution indicates the presence of monomers of ∼32 Å diameter and length of ∼50 Å, consistent with monomers of mCherry 48 (see Table SII, ESI † and inset in Fig. 2c ). The small size increase is likely due to the cationisation. For c-mCherry, blue we only observe a change of the form factor when a high salt concentration (close to the gel formation concentration of 1.6 M) is added to the system, as shown in Fig. 2d . Moreover, there is a lack of an increase in intensity at low q as observed for eGFP and the cylinder form factor alone is enough to describe c-mCherry. The upturn observed is independent of the salt concentration and is likely due to aggregates formed during sample manipulation. It is worth highlighting the big difference on the background signal at high q for salt concentrations above 0.75 M ( Fig. 2c ). Further investigation in this respect, showed this signal came from some protein denaturation. However, we still observed significant chromophore fluorescence of this protein even at much higher salt concentrations, as shown in the previous section. Due to the presence of salts and the formation of aggregates, we faced limitations to assess protein stability via conventional techniques such as circular dichroism, for example. Thus, to further investigate the level of protein folding of cationised mCherry, we measured its the emission fluorescence at different temperatures. This represents a sensitive metric of structural integrity as the chromophore hydrolyses when exposed to water. 49 The results are shown in Fig. S3 in the ESI, † where a clear decrease of emission signal is observed as the temperature is increased, and it is lost above 80 °C. From these results we can conclude that the unfolded protein looses its fluorescence and will not contribute to the signal observed in the gels. Thus, unlike eGFP where association and dimerisation is controlled continuously by adding YCl 3 , in the case of c-mCherry, we have charge-stabilised c-mCherry monomers whose attraction is only abruptly increased when a sufficiently large amount of (NH 4 ) 2 SO 4 is added to the solution, as illustrated in the sketch in Fig. 2b . 3.3 Two-step formation of decorated protein networks As outlined in the introduction, we first assemble a network of eGFP via the specific interactions of the trivalent salt, and then decorate with c-mCherry via the addition of the nonspecific ammonium sulphate interactions. Building on our investigation of the interactions between the proteins discussed above, to assemble a robust eGFP backbone network, we prepared a system of eGFP at 4 mg mL −1 with a trivalent salt concentration of YCl 3 at 5 mM. The resulting network is shown in Fig. 3a . We also tested the stability of this network in the presence of ammonium sulphate. The structure is shown in Fig. S4 (ESI † ), where we do not observe major changes in the gel structure in comparison with the gels shown in the figure mentioned before. We proceeded to prepare an c-mCherry solution at 4 mg mL −1 and tested its assembly first in the absence of the eGFP, using a saturated ammonium sulphate concentration of 3 M to ensure full aggregation, as shown in Fig. 3b . Fig. 3 Deconvolved confocal images of individual and decorated eGFP and cationised mCherry networks. (a) eGFP network formed through the addition of yttrium chloride. (b) Cationised mCherry network formed by adding ammonium sulphate. (c and d) Confocal images of the expected decorated gel networks with distinctive eGFP (green) and cationised mCherry (red) domains. 4 mg mL −1 of eGFP were mixed on their own with 5 mM of yttrium chloride to form a gel. 3 M of ammonium sulphate is added followed by 4 mg mL −1 of cationised mCherry at pH = 7. Inset in (c) rendering of a binary network from confocal microscopy images showing a percolating structure in 3d. Scale bars = 10 μm. We assemble the decorated network, as follows. To the eGFP network (volume 15 μl), we added ammonium sulphate and then c-mCherry solution (volume 5 μl), such that the concentrations in the final solution of (volume 20 μl), was 4 mg mL −1 for both the eGFP and mCherry, 5 mM for the YCl 3 and 3 M for the (NH 4 ) 2 SO 4 . The results of this approach are shown in Fig. 3c and d , where we can observe a backbone eGFP network decorated with c-mCherry. 3.4 Tuning the coverage of the backbone eGFP network with cationised mCherry The eGFP network coverage exhibits clearly identifiable domains of both eGFP and c-mCherry. This indicates that they are at least predominantly composed of one of the proteins. To confirm that the structures found are indeed 3d networks in Fig. 3c inset we show a 3d rendering of confocal microscopy image data where we see percolation in all three dimensions. It is worth highlighting that the elongation in the z plane is related to the limited optical resolution. Thus, the strategy proposed successfully produced decorated networks with distinctive protein domains. However, there are still large yellow areas (overlay of green and red channels), indicating that c-mCherry deposited directly on the surface of the preexisting eGFP network which we will refer as “mixture” below. Both observations are clearer at higher magnifications ( Fig. 3d ). We further confirmed that the strategy followed above to increase salt–protein specificity is indeed required to yield the decorated structures. Rather than the two-step approach of decorating a gel of eGFP and then adding mCherry, we mixed solutions of eGFP and mCherry and added several (NH 4 ) 2 SO 4 salt concentrations. The results are shown in Fig. S5 in the ESI. † No assembly occurs before 1 M of (NH 4 ) 2 SO 4 , and we only start to find clusters of ∼5 μm formed solely by eGFP up to 1.5 M of (NH 4 ) 2 SO 4 . However, we start observing co-precipitation of the proteins at a salt concentration of 1.6 M (NH 4 ) 2 SO 4 , where the proteins are indistinguishably mixed on the lengthscales we access. This is more evident as the salt concentration increases. Full co-precipitation is observed at 3 M of (NH 4 ) 2 SO 4 . This coprecipitation is due to non-specific interactions between the proteins due to the addition of (NH 4 ) 2 SO 4 . Indeed, the isoelectric point and acidic surface residues of the two proteins are similar and only a few salt (Ca 2+ and SO 4 2− ) specific sites are present in eGFP, as shown in Table SIII (ESI † ). 50,51 One of these is a site for a sulphate group for eGFP. ‡ ‡ However the observation of the presence of these specific sites is related to the crystallisation process followed to determine the crystal structure in the PDB, 50 and there may well be similar sites on mCherry. Therefore, choosing salts with specific protein interactions and the modification of the surface of the proteins carried out above are essential for the successful decorated network formation. Having assembled the desired architecture, we then investigated whether we could control the coverage of the eGFP network and the domain sizes of eGFP and c-mCherry. To do this, we decreased the concentration of c-mCherry to 0.5, 0.2, and 0.1 of the eGFP concentration, which was kept at 4 mg mL −1 , similar to the strategy proposed by de las Heras et al. on simulations of binary mixtures of patchy spheres. 25 Fig. 4a shows the percentages of protein domains identified as eGFP (green), c-mCherry (red) and mixture (yellow) according to the different eGFP:c-mCherry composition. Unexpectedly, as we decreased the amount of c-mCherry, the percentage of domains identified as eGFP also decreased slightly, whereas the percentage of mixed network increased ( Fig. 4a ), making almost half of the network composition when the eGFP : c-mCherry ratio is 10 : 1. The small decrease of eGFP coverage suggests that the increase in mixing occurs mainly at expense of individual domains of c-mCherry, however, we would expect to see a more significant reduction of the regions identified as eGFP domains. Fig. 4 Control over eGFP gel coverage with cationised mCherry. (a) Comparison of individual regions of eGFP (green), cationised mCherry (red) and mixture (yellow) in the binary network when the eGFP : cationised mCherry concentration ratio of the proteins is varied from 1 : 1, 2 : 1, 5 : 1, 10 : 1. (b) Comparison of the distribution of the domain volume size of individual regions of eGFP (left), cationised mCherry (centre) and mixture (right) in the decorated networks. The eGFP : cationised mCherry concentration ratio is varied from 1 : 1 (pink), 2 : 1 (purple), 5 : 1 (blue) and 10 : 1 (turquoise). (c) and (d) Cationised mCherry competition between forming clusters before their deposition (c: c-mCherry rich) or depositing directly on the pre-existing eGFP backbone (d: c-mCherrry poor). Finally we measured the sizes of the eGFP, c-mCherry and mixture domains to see if their distribution also changed with the different ratios of protein concentration tested. To carry out this analysis, the neighbours of pixels identified as a particular domain type were counted and the number of pixels per domain was obtained. The resulting probability distribution functions are shown in Fig. 4b , where the left panel shows the size distribution of eGFP domains, the centre one corresponds to c-mCherry and the right panel pertains to the domains of mixed proteins. The plots show that as the concentration of c-mCherry is decreased, the amount of small domain sizes also decreases for eGFP and mixed protein regions. Such reduction in domain sizes is more evident at 5 : 1 and 10 : 1 protein ratios (pink and turquoise colours, respectively in Fig. 4b ). However, c-mCherry shows a different behaviour, with a general reduction of the amount of protein domains consistent with the previous analysis. A reduction of the sizes of eGFP and mixed protein domains, but not of eGFP gel coverage, might be a consequence of non-homogenous and more scattered deposition and mixing of c-mCherry as its concentration is reduced. Thus, the sizes of protein domains and the protein mixing can be manipulated by modifying the composition of the system. 3.5 Two mechanisms for network decoration This unexpected behaviour of increasing protein mixing by c-mCherry upon decreasing the concentration suggests that more than one mechanism of c-mCherry assembly onto the network is at play. We propose the following. • If the amount of regions identified as c-mCherry increases or remains the same as the quantity of this protein is reduced, there may be a preference for aggregation between like proteins (eGFP–eGFP and c-mCherry–c-mCherry). This might occur because at high concentrations c-mCherry is more likely to encounter more protein of its kind in solution. As a result, before depositing on the surface of the pre-existing eGFP gel, c-mCherry will aggregate with itself, forming small clusters, as illustrated in Fig. 4c (c-mCherry rich). • On the other hand if the protein mixing increases as less c-mCherry is added, then the likelihood of c-mCherry to come in contact with eGFP increases since there is now less c-mCherry available in solution, and thus the precipitating c-mCherry will deposit directly on the surface of the pre-existing eGFP gel. This mixing and deposition is non-homogenous, leading to small domain sizes of both eGFP and mixed protein [ Fig. 4d (c-mCherry poor)]. We believe that the c-mCherry coverage as a function of reducing the quantity added may be due to a competition between these two different extreme scenarios arising from varying the concentration of c-mCherry solely. At high c-mCherry concentrations, like-protein encounters dominate with individual domains of c-mCherry forming, prior to decorating the eGFP network. However, as we decrease the concentration of c-mCherry, then eGFP–c-mCherry encounters seem to dominate and the latter preferentially mixes with the eGFP gel, leading to smaller domain sizes of individual proteins. 3.6 Gel fractal dimensions Since our gels are constituted by individual and mixed domains of two proteins, we can describe their structure through the connectivity of the eGFP, c-mCherry and mixed clusters via their fractal dimension, d f . 52–54 As discussed in the previous section, the size distribution of domains changes according to the different protein concentrations used, thus, d f can also give information about how the overall gel structure might be altered by changing the amount of protein. The values obtained for the d f of each domain are plotted in Fig. 5b according to the eGFP : c-mCherry ratio tested. All the values obtained lay within a range of 2.2–2.6, consisting with d f ∼ 2.5 characteristic of percolating clusters, where the structure expands in 3d without filling all the available space. 52,53,55 Additionally, this value of d f is closer to gels pertaining to the reaction-limited cluster aggregation (RLCA) regime ( d f ∼ 2). This classification is based on the kinetics of cluster aggregation, and for the case of RLCA, the formation rate is limited by the probability of particles bonding upon collision. 56 These results further support our picture of the two mechanisms at play for the network decoration, where the preferential aggregation of c-mCherry with other c-mCherry in solution or with the pre-existing eGFP gel depends on the likelihood of the protein finding one or the other first. Despite of the changes in gel composition, we do not observe significant variation on the d f for any of the different protein ratios. This might be due to the fact that the initial gel consisted of only eGFP and the deposition of c-mCherry and/or protein mixing occurred on top of it. Since the concentration of eGFP remained constant, so did the overall structure of the gel. Fig. 5 Gel structural analysis. (a) Radius of gyration of eGFP clusters as a function of the number of eGFP domains shown to illustrate the calculation of the fractal dimension, d f (b) d f of eGFP (green), cationised mCherry (red) and mixture (yellow) domains according to the different eGFP–cationised mCherry gel compositions. Note: for eGFP–cationised mCherry ratios 5 : 1 and 10 : 1, eGFP and cationised mCherry domains have the same d f = 2.5. The latter have been plotted in a smaller size for clarity."
} | 8,652 |
39927799 | PMC11967871 | pmc | 5,250 | {
"abstract": "Abstract The atmosphere contains ≈1.3 billion tons vapor that can be condensed to obtain water, which has the promise of alleviating the water crisis. However, condensed droplets are difficult to shed from the condensation surface that means a low surface refreshing frequency, showing the low water collection rate and efficiency. Here, this limitation is successfully overcome by proposing a novel superhydrophobic condensation absorber (SCA). All surfaces of the SCA are superhydrophobic but covered with a series of superhydrophilic through pores and superhydrophilic points which enabled the SCA with a rapid droplet nucleation capability. The whole condensation processes exhibit that the SCA has the extremely small droplet shedding volume and the highly frequent surface refreshing, which are 0.00003 and 1.1× 10 6 times that of the existing water collection method, respectively. The water collection rate of SCA is superior than that of the existing water collection methods, reaching to 80 mg cm −2 h −1 at the subcooling temperature of only 10 °C. In addition, the collected water by this SCA is clean without any contaminant. This high‐efficiency and eco‐friendly water collection method will maximize the acquisition of clean water from atmosphere, which has a strong implication for the people suffering from the freshwater crisis.",
"conclusion": "3 Conclusion In summary, we proposed a novel SCA based on a droplet jetting phenomenon which was inspired by the quick shedding of water droplets from the lotus leaf surface. All surfaces of the SCA were superhydrophobic but covered with a series of superhydrophilic through pores and superhydrophilic points. The dynamic behaviors of the condensed droplets on the SCA showed that a higher relative ambient humidity and a larger subcooling temperature were beneficial to improve the droplet shedding frequency. The whole condensation processes of the SCA could be divided into three stages which were the condensed droplet nucleation stage, condensed droplet growth stage, and condensed droplet absorption stage. In these three stages, the condensed droplet size and the droplet coverage ratio on the SCA were always less than 350 µm and 35%. We compared the water collection performance of the SCA with the existing other water collection methods and found that the SCA had the superior water collection rate of 80 mg cm −2 h −1 at the subcooling temperatures of 10 °C. The superior water collection rate was due to the high‐frequency droplet shedding and high‐frequency surface refreshing, which resulted from the low droplet coverage ratio and the small droplet shedding size. In addition, the collected water by the SCA was clean. Since the water collection mass can be easily improved by increasing the size of the SCA, this water collection method based on the ultra‐rapid droplet jetting phenomenon is very meaningful to the world.",
"introduction": "1 Introduction As the rapid increasing of global population, the 193 member states of the United Nations adopted 17 Sustainable Development Goals (SDGs), where the Goal 6 of SDGs stated that water scarcity seriously restricted the human sustainable development. [ \n \n 1 \n , \n 2 \n \n ] The main reason that the existing methods for obtaining the clean water, such as inter‐basin water diversion, seawater desalination, and sewage purification, are difficult to popularize which results from the high‐cost and the high energy consumption. [ \n \n 3 \n , \n 4 \n , \n 5 \n \n ] Therefore, people urgently need a low‐cost and energy‐saving method to obtain the clean water. In nature, the atmosphere stores a large amount of sustainably regenerated water resources in the form of vapor or fog, which is ≈1.3 × 10 9 tons, accounting for 10% of all other freshwater resources. [ \n \n 6 \n , \n 7 \n \n ] If these water vapor can be collected and utilized, it can alleviate the water crisis. [ \n \n 8 \n \n ] The organism and phenomena in nature have inspired people to collect vapor from the atmosphere, e.g., the leaves of plant generate the dew on a damp night or morning. This means that when an object is located in a damp environment and its surface temperature is lower than the dew temperature, the vapor in the atmosphere will condense on the object surface and form the condensation water. [ \n \n 9 \n \n ] Researchers found that the dropwise condensation usually exhibited a better water collection rate than the filmwise condensation. This was because the filmwise condensation form had a thicker insulation layer which led to a lower heat transfer performance and a lower surface refreshing frequency. [ \n \n 10 \n , \n 11 \n , \n 12 \n \n ] However, even though the condensation surface is dropwise condensation, its surface refreshing frequency is still not high enough because the condensed droplets need to grow to a certain size with ≈2.7 mm to overcome the capillary force and shed from the condensation surface by the gravity. [ \n \n 13 \n , \n 14 \n \n ] To increase the surface refreshing frequency, the micro‐/nano‐structured superhydrophobic surface with the droplet jumping phenomenon and the slippery liquid‐infused porous surface (SLIPS) were proposed. [ \n \n 15 \n , \n 16 \n , \n 17 \n , \n 18 \n , \n 19 \n \n ] Nevertheless, the landing position of the shedding droplets on the micro‐/nano‐structured superhydrophobic surface was random, resulting in a significant loss of the shedding droplets. [ \n \n 20 \n \n ] In addition, the shedding droplets would take away a lot of lubricant on the SLIPS, which caused a contamination of the collected water. [ \n \n 21 \n , \n 22 \n \n ] Therefore, if we can develop a novel water collection method with high‐frequency surface refreshing and high‐efficiency collection of the shedding droplet but without any contamination will be very meaningful to the world, especially for the people suffering from the freshwater crisis. In this work, we designed a novel superhydrophobic condensation absorber (SCA) which was filled with water and inspired by the quick shedding phenomenon of water droplets from the lotus leaf surface. All surfaces of the SCA were superhydrophobicity but covered with a series of superhydrophilic through pores and superhydrophilic points. Then, the dynamic behavior of the condensed droplets on the SCA and their influencing factors including the relative ambient humidity and surface temperature were investigated by an environmental scanning electron microscope and a camera, respectively. The condensed droplets could quickly and frequently shed from the SCA, greatly increasing its surface refreshing frequency, which made it possible to collect a large amount of water from the atmosphere even under a lower subcooling. More interesting is that this high‐efficiency and environment‐friendly water collection method can generate the abundant freshwater resources and promote the human sustainable development.",
"discussion": "2 Results and Discussion 2.1 Ultra‐Rapid Droplet Jetting Enabled High‐Frequency Surface Refreshing Lotus leaf is a common superhydrophobic surface in nature, where a water droplet has a contact angle greater than 150 ° and is easily shed from this surface ( Figure \n \n 1 a ). [ \n \n 23 \n \n ] When the lotus leaf was subjected to the insect infestation or mechanical damage, a through pore will form on its surface (Figure 1b ; Figure S3 , Supporting Information). Once a water droplet on the lotus leaf contacted this pore, it would be absorbed in the pore and entered the water in a form of droplet jetting within 140 ms, keeping the surface cleaning (Figure 1c ; Video S1 , Supporting Information). Inspired by this phenomenon, we guessed that if the condensed droplet on the surface could spontaneously shed from the condensation surface in the form of this ultra‐rapid droplet jetting, it will facilitate the shedding of condensed droplets. Therefore, we first investigated whether a superhydrophobic surface with superhydrophilic pore could generate the condensed droplets and these condensed droplets whether could be easily and rapidly shed from the condensation surface by superhydrophilic pore in the form of droplet jetting. To verify this hypothesis, we made a condensation platform and fabricated a superhydrophobic Al sheet with a superhydrophilic through pore with 300 µm diameter via the combination of the laser processing and the FAS modification (Figures S4 and S5 , Supporting Information). [ \n \n 24 \n , \n 25 \n , \n 26 \n \n ] In order to facilitate the observation of the droplet jetting, we fabricated four superhydrophilic points with 100 µm diameter around superhydrophilic through pore via the laser and placed a 1.5 µL dye droplet on one of these superhydrophilic points. After 30 min condensation, the condensed droplets could be clearly observed on superhydrophobic surface and four superhydrophilic points. These droplets gradually grew and coalesced with the surrounding other condensed droplets with the increasing time (Figures S6 and S7 , Supporting Information). After 90 min, the droplet ⑤ on superhydrophobic surface coalesced with the droplet ③ on superhydrophilic point. During the coalescence process, the coalesced droplets generated the droplet oscillation because of the surface energy releasing, which caused the coalesced droplet contacted the droplet ①, droplet ②, and droplet ④ on superhydrophilic points and ultimately coalesced to form a large droplet ⑥ (Figure S8 , Supporting Information). Once this droplet ⑥ contacted superhydrophilic pore, it was easily and rapidly entered the water through the pore in the form of droplet jetting within 340 ms, as shown in Figure 1d,e , and Video S2 (Supporting Information). Therefore, superhydrophobic surface with superhydrophilic pore could generate the condensed droplets. The generated condensed droplets can easily and rapidly shed from the condensation surface by superhydrophilic pore in the form of droplet jetting, which has the potential to be used for collecting water from the atmosphere. Figure 1 Droplet jetting phenomena on the lotus leaf and a superhydrophobic Al sheet with superhydrophilic pore. a) A lotus leaf in the pond. b) Schematic of fabricating through pore on the lotus leaf using a needle. c) When a dyed 15 µL droplet contacted the pore on the lotus leaf, it was quickly absorbed into this pore and generated a droplet jetting phenomenon. The entire droplet jetting process was ≈140 ms. d) Top view of the condensed droplets on a superhydrophobic Al sheet with superhydrophilic through pore. e) Side view of the condensed droplets on a superhydrophobic Al sheet with superhydrophilic through pore. The diameters of superhydrophilic through pore and superhydrophilic point were 300 µm and 100 µm, respectively. The ambient temperature, relative ambient humidity, and condensation surface temperature for this experiment were 26 °C ± 1 °C, 70% ± 2.5%, and 10 °C ± 1 °C, respectively. We then established a condensation experiment system to investigate the condensation performance of our proposed method that inspired by the ultra‐rapid droplet jetting phenomenon, as shown in Figure \n \n 2 a . The SCA was the core part of the condensation experiment system Figure S9 (Supporting Information). In the droplet jetting experiment shown in Figure 1e , we found that the droplet nucleation rate on superhydrophilic point was much faster than that on superhydrophobic surface. Therefore, we proposed that if superhydrophilic points were fabricated at the incenter of triangle of superhydrophilic staggered arrangement pore array, it will be beneficial to increase the water collection rate because of the increased droplet nucleation rate during the condensation processes (Figure 2b ). The influence of the SCA type1 without superhydrophilic points and the SCA type2 with superhydrophilic points on the water collection rate was studied. The results showed that the water collection rates of SCA type1 and SCA type2 were 69.5 mg cm −2 h −1 and 80.0 mg cm −2 h −1 , respectively, for the same pore diameter d \n p of 300 µm and the same space S \n e of 300 µm between superhydrophilic region edges, as shown in Figure 2c . It indicated that the superhydrophilic points indeed could increase the water collection rate. Then, the SCA type2 was used as the SCA in the following work. Figure 2 The SCA had the high‐frequency surface refreshing which resulted from the ultra‐rapid droplet jetting. a) A closed chamber was used to observe condensation processes on the SCA and conduct water collection experiments. b) Schematic of the SCA type1 without superhydrophilic points and the SCA type2 with superhydrophilic points. Superhydrophilic point diameter d \n sp of 50 µm. c) The water collection rate of the SCA type1 and the SCA type2 . d) The variation of water collection rate with the pore diameter and the space between superhydrophilic region edges. e) The variation of water collection rate with superhydrophilic point diameter. In these water collection experiments, the ambient temperature, relative ambient humidity, and sample surface temperature were 26 °C ± 1 °C, 70% ± 2.5%, and 10 °C ± 1 °C, respectively. f) Schematic of three surface refreshing types on the SCA. g) ESEM images of three surface refreshing types on the SCA. We further investigated the influence of the SCA structure parameters on the water collection rate and found that the increasing S \n e made the condensed droplets difficult to be captured by superhydrophilic pores, resulting in the loss of the shedding droplet. Differently, the d \n p from 100 µm to 500 µm had almost no effect on the water collection rate (Figure 2d ; Figure S10 , Supporting Information). This was because that the shedding size of the condensed droplets on the SCA was small and the shedding droplets could be completely absorbed by superhydrophilic pores with d \n p of 100 µm‐500 µm. In addition, it can be seen that if the pore area was constant, the pore shape was also insignificant for the droplet jetting process and the water collection rate (Figures S11 and S12 and Video S3 , Supporting Information). However, the diameter d \n sp of superhydrophilic point had a significant influence on the water collection rate. The water collection rate decreased with the increasing d \n sp , which resulted from that the increasing d \n sp would decrease the area of superhydrophobic region, as shown in Figure 2e . When the d \n sp was larger than 150 µm, the condensed droplet on superhydrophilic point easily formed the liquid bridge with the water on superhydrophilic area around superhydrophilic pore, resulting in the loss of water collection capability. Therefore, we chose the d \n p of 100 µm, the S \n e of 300 µm, and the d \n sp of 50 µm as the structure parameters of the SCA (Figure S13 , Supporting Information). We then carefully observed the condensation processes on the SCA by an environmental scanning electron microscope (ESEM) and found that the surface refreshing of the SCA was very frequent and could be summarized into three types, as shown in Figure 2f,g , Figure S14 and Videos S4–S6 (Supporting Information). For the surface refreshing I, once the condensed droplets on superhydrophobic surface contacted the condensed droplet on superhydrophilic point, the condensed droplets on superhydrophobic surface would rapidly coalesce with the condensed droplet on superhydrophilic point under the Laplace force, refreshing the SCA surface. For the surface refreshing II, once the condensed droplets around superhydrophilic pore contacted superhydrophilic region around superhydrophilic pore, they would be quickly absorbed into superhydrophilic pore, refreshing the SCA surface. For the surface refreshing III, once grown condensed droplet on superhydrophilic point contacted superhydrophilic region around superhydrophilic pore, it would rapidly shed from the SCA surface and be absorbed into superhydrophilic pore, refreshing the SCA surface. In addition, we also calculated the maximum droplet shedding sizes of three surface refreshing types, which could be expressed as,\n \n (1) \n D max − I = D max − II = S e + d r 2 + 3 S e 2 − 3 d spr 2 6 S e + d spr \n \n \n (2) \n D max − III = 2 3 − 3 d r + 2 3 S e 3 \n where D \n max‐I , D \n max‐II , and D \n max‐III are the maximum droplet shedding sizes of the surface refreshing I, surface refreshing II, and surface refreshing III, respectively (Figure S15 , Supporting Information). d \n r and d \n spr are the diameter of superhydrophilic region around superhydrophilic pore and the diameter of superhydrophilic region around superhydrophilic point, which are 300 µm and 150 µm, respectively. Combined with Equations ( 1 ) and ( 2 ), the D \n max‐I , D \n max‐II , and D \n max‐III could be calculated by MATLAB, which were 208 µm, 208 µm, and 393 µm, respectively. Therefore, the extremely small droplet shedding size resulted in the high‐frequency droplet shedding and high‐frequency surface refreshing, which meant that this method could timely phase‐separate by separating the condensed droplets, vapor, and condensation surface. [ \n \n 15 \n , \n 27 \n \n ] \n 2.2 Dynamic Analysis of Condensed Droplets on the SCA To investigate the influence of different conditions on the condensation performance of SCA, we then studied the dynamic behaviors of the condensed droplets on the SCA under the different relative ambient humidities and sample surface temperatures, respectively. We first adjusted the temperature of the cold plate to achieve different sample surface temperatures (Table S1 and Video S7 , Supporting Information). Under the different sample surface temperatures, the dynamic behaviors of the condensed droplets were different, as shown in Figure \n \n 3 a . When the sample surface temperature was 17 °C, the surface subcooling temperature was only ≈3 °C. The condensed droplets could be observed on the SCA surface after ≈30 min. However, the condensed droplets on the SCA surface could be observed about only 15 min at the 15 °C sample surface temperature. The time to observe the condensed droplets was decreased with the decreasing sample surface temperature. In addition, we found that when the sample surface temperature was 10 °C, the condensed droplets on superhydrophilic point would quickly shed from the SCA surface and enter the pore after 30 min, leaving a refreshed surrounding region around this pore (Figure 3a ). We chose a 2 mm × 2 mm area as the observation region to carefully observe and measure the maximum size of the condensed droplets on the SCA with the different sample surface temperatures. The results indicated that the maximum droplet size was less than 350 µm, which was consistent with the theoretical calculation value in the section 3.1, as shown in Figure 3b . We also calculated the droplet coverage ratio which was the ratio of the area of the condensed droplets to the total area of SCA in the observation region. It was exciting that the droplet coverage ratio on the SCA was always less than 35% at the different sample temperatures (Figure 3c ; Figure S16 , Supporting Information). Moreover, we also studied and observed the dynamic behaviors of the condensed droplets on the SCA at different relative ambient humidities, where the ambient temperature and the sample temperature were 26 °C ± 1 °C and 10 °C ± 1 °C (Figure S17 , Supporting Information). When the relative ambient humidity was higher than 40%, the condensed droplets could be observed within 60 min with the maximum droplet size less than 350 µm and the droplet coverage ratio less than 35% (Figure 3d,e ; Figure S18 and Video S8 , Supporting Information). However, when the relative ambient humidity was 40%, there were no condensed droplets observed on the SCA within 60 min due to the too low subcooling temperature (Table S2 , Supporting Information). Figure 3 Dynamic behaviors of condensed droplets on the SCA. a) The condensation processes on the SCA at different sample surface temperatures, where the ambient temperature and the relative ambient humidity were 26 °C ± 1 °C and 70% ± 2.5%. b) The variation of the maximum droplet size on the SCA with the time at different sample surface temperatures. c) The variation of the droplet coverage ratio on the SCA with the time at different sample surface temperatures. d) The variation of the maximum droplet size on the SCA with the time at different relative ambient humidities. e) The variation of the droplet coverage ratio on the SCA with the time at different relative ambient humidities. In the condensation experiments with different relative ambient humidities, the ambient temperature and the sample surface temperature were 26 °C ± 1 °C and 10 °C ± 1 °C. According to the dynamic analysis of the condensed droplets, we divided the condensation processes of the SCA into three stages: condensed droplet nucleation stage (Stage I), condensed droplet growth stage (Stage II), and condensed droplet absorption stage (Stage III). We chose the experiment condition of the ambient temperature of 26 °C, relative ambient humidity of 70%, and sample temperature of 10 °C to further analyze the dynamic processes of the condensed droplets on the SCA, as shown in Figure \n \n 4 a . In the Stage I, since the nucleation barrier was much lower on superhydrophilic point than on superhydrophobic region, the condensed droplets first nucleated and were observed on superhydrophilic points. During this process, the condensed droplet size was very small less than 50 µm, but the condensed droplet number was large and rapidly reached 2000 within 10 min (Figure 4b ). In addition, there was almost no visible surface refreshing in the stage I. After 10 min, the condensation process reached the Stage II. Once the gradually growth droplets on superhydrophobic region contacted the droplet on superhydrophilic point, they would quickly coalesce with the droplet on superhydrophilic point, refreshing the region around this point. During this stage, we would observe the significant surface refreshing phenomena in the form of surface refreshing I, which caused that the droplet number and the droplet size significantly decreased and increased, respectively (Figure 4c ). As the droplets on superhydrophilic point gradually grew, they would contact superhydrophilic pores, which reached the Stage III. Once these droplets contacted superhydrophilic pores, they would be quickly absorbed into the SCA, refreshing the region around the pores and starting a new condensation cycle, as shown in Figure 4d . During this stage, the phenomena of the surface refreshing II and surface refreshing III could be frequently observed on SCA. In addition, we also investigated the variations of the droplet number on the SCA with the condensation time at different sample surface temperatures and different relative ambient humidities (Figure S19 , Supporting Information). The results showed that the time to reach the Stage II and Stage III increased from 11 min to 35 min and from 30 min to 83 min with the sample surface temperature increased from 10 to 17 °C, and decreased from 90 min to 11 min and from 260 min to 30 min with the relative ambient humidity increased from 40% to 70%, as shown in Figure 4e,f . Therefore, it can be seen that the difference between the sample surface temperature and ambient temperature and the relative ambient humidity are important factors that affect the condensation processes of the SCA. When the SCA was placed in a humid environment, it can quickly generate condensed droplets on the surface and frequently shed these condensed droplets from the surface in the form of the droplet jetting, which is beneficial for improving the water collection rate. [ \n \n 27 \n \n ] \n Figure 4 The three stages of condensation processes on the SCA. a) The variation of the droplet number on the SCA with the time within a 2 mm × 2 mm area. According to the droplet size and the droplet number, the condensation process was divided into three stages: condensed droplet nucleation stage (Stage I), condensed droplet growth stage (Stage II), and condensed droplet absorption stage (Stage III). The ambient temperature, relative ambient humidity, and sample surface temperature were 26 °C ± 1 °C, 70% ± 2.5%, and 10 °C ± 1 °C, respectively. b) The droplet size and the droplet number on the SCA during the Stage I. c) The droplet size and the droplet number on the SCA during the Stage II. d) The droplet size and the droplet number on the SCA during the Stage III. e) The variation of the time to reach the Stage I and Stage II with the increasing sample surface temperature, where the ambient temperature and the relative ambient humidity were 26 °C ± 1 °C and 70% ± 2.5%. f) The variation of the time to reach the Stage I and Stage II with the increasing relative ambient humidity, where the ambient temperature and the sample surface temperature were 26 °C ± 1 °C and 10 °C ± 1 °C. 2.3 High‐Efficiency Water Collection Previous researches showed that superhydrophilic surface (SHI), superhydrophobic surface (SHP), superhydrophobic/superhydrophilic hybrid pattern surface (SSHP), and SLIPS had a good water collection capability. [ \n \n 28 \n , \n 29 \n , \n 30 \n , \n 31 \n , \n 32 \n , \n 33 \n , \n 34 \n , \n 35 \n , \n 36 \n , \n 37 \n , \n 38 \n , \n 39 \n , \n 40 \n , \n 41 \n , \n 42 \n , \n 43 \n , \n 44 \n , \n 45 \n , \n 46 \n \n ] Almost all researches placed the water collection surface perpendicular to the horizontal plane, relying on gravity to make the condensed droplets shed. However, in the practical application, an object is usually composed of the top wall, side wall, and bottom wall. If only the side wall is considered to collect water which means the top wall and side wall are ignored, seriously reducing the water collection capability. We fabricated four surfaces as the control group and conducted the water collection experiments of the SHI, SHP, SSHP, SLIPS, and SCA on the top wall, side wall, and bottom wall ( Figure \n \n 5 a ; Figures S20–S23 and Videos S9–S11 , Supporting Information). Figure 5 The SCA had a high‐efficiency water collection capability. a) The water collection processes of the SHI, SHP, SSHP, SLIPS, and SCA at the top wall. In these water collection experiments, the ambient temperature, relative ambient humidity, and sample surface temperature were 26 °C ± 1 °C, 70% ± 2.5%, and 10 °C ± 1 °C, respectively. b) Droplet shedding size of the different samples on the top wall/side wall/bottom wall. c) Surface refreshing frequency of the different samples on the top wall/side wall/bottom wall. d) Performance comparison of the water collection efficiency of the top wall/ side wall/ bottom wall, the average droplet shedding volume, the average surface refreshing frequency, and the average droplet coverage ratio after 60 min condensation of these five surfaces. e) Water collection rate of the different water collection methods. The detailed data of these literatures is included in Table S8 (Supporting Information). f) FTIR spectrum of the clean water, the silicone oil, the collected water from the SLIPS, the collected water from the SCA. In these five surfaces, the condensed droplets were the most difficult to shed from the SHI but easily shed from the SHP and the SCA because of different surface wettability. By measuring the shedding droplet volume, we found that the droplet shedding volume of the SCA on the top wall/side wall/bottom wall was only 0.03 µL/0.03 µL/0.03 µL, which was 0.00005/0.0004/0.00023, 0.0375/0.15/0.15, 0.00004/0.00012/0.0002, and 0.00003/0.003/0.00177 times of that of SHI, SHP, SSHP, and SLIPS, (Figure 5b ; Figure S24 , Supporting Information). We then counted the surface refreshing frequency of these five surfaces and found that the surface refreshing frequency of this SCA was as high as 20000 h −1 /25000 h −1 /15000 h −1 on the top wall/side wall/bottom wall, which was 1 × 10 6 /3.1 × 10 5 /3 × 10 5 , 333/25/19, 6 × 10 5 /1.7 × 10 4 /6000, and 1.1 × 10 6 /2.5 × 10 5 /1.1 × 10 5 times of that of SHI, SHP, SSHP, and SLIPS (Figure 5c ). The high surface refreshing frequency of the SCA was due to the extremely small droplet shedding size and rapidly phase‐separation form. In addition, we also calculated the droplet coverage ratio of these five surfaces at the top wall/side wall/bottom wall and found that the droplet coverage ratio of the SCA was always less than 35% that originated from the high‐frequency droplet shedding and high‐frequency surface refreshing, which would decrease the influence of thermal resistance generated by the condensed droplets on the surface, as shown in Figure S25 (Supporting Information). Although the SHP also exhibited a high surface refreshing frequency and a low droplet coverage ratio, since the droplet shedding form of the SHP was the droplet jumping that originated from the surface energy releasing, resulting in a significant loss of the shedding droplets. To objectively evaluate the water collection capability of these different surfaces, we developed a performance figure of merit for this condensation experiment system, as shown in Figure S26 and Tables S3–S7 (Supporting Information). The water collection efficiency η was used to appraise the water collection capability from the atmosphere, which could be described as follows,\n \n (3) \n η = W e W t × 100 % \n where W \n e and W \n t are the experimental water collection rate and the theoretical water collection rate of the sample surface. [ \n \n 34 \n \n ] The experimental water collection rate was calculated as follows:\n \n (4) \n W e = m e A e × t e \n where m \n e , A \n e , and t \n e are the water collection mass, the collection area, and the collection time. [ \n \n 7 \n \n ] The theoretical water collection rate of the sample surface can be expressed as follows:\n \n (5) \n W t = W m , air × Δ k vapor \n where W \n m, air and Δ k \n vapor were the mass transfer coefficient of air and the difference in the mass fraction of vapor and air between the air and the sample surface. [ \n \n 34 \n \n ] The model and detailed calculation process are shown in Figure S26 (Supporting Information). After calculation, we comprehensively compared the water collection efficiency of the top wall ( η \n top )/ side wall ( η \n side )/ bottom wall ( η \n bottom ), the average droplet shedding volume V \n as , the average surface refreshing frequency f \n as , and the average ratio λ \n ac‐60 of droplet coverage after 60 min condensation of these five surfaces. It could be seen that these performances of the SCA were superior than that of the other water collection methods (Figure 5d ). Moreover, we also calculated the subcooling temperature and water collection rate on the SHP, SSHP, and SLIPS used in the reported literatures and compared their water collection performance with that of the SCA. [ \n \n 32 \n , \n 33 \n , \n 34 \n , \n 35 \n , \n 36 \n , \n 37 \n , \n 38 \n , \n 39 \n , \n 40 \n , \n 41 \n , \n 42 \n , \n 43 \n , \n 44 \n , \n 45 \n \n ] As everyone knows, a larger subcooling temperature can increase the water collection rate. The SCA had a water collection rate of 80 mg cm −2 h −1 at a subcooling temperature of 10 °C, while the SHP required the subcooling temperatures of 27 °C to achieve the almost equiv. water collection rate (Figure 5e ). In addition, we found that the collected water from the SLIPS was seriously contaminated by the lubricant oil (Figure 5f ; Figures S27 and S28 and Table S9 , Supporting Information). However, the collected water from the SCA was very clean and could be directly used for actual production or daily life (Table S10 , Supporting Information). In this work, we focused on the atmospheric water collection to show the timely phase‐separation of the condensed droplets, vapor, and condensation surface. In the southern China, the high‐temperature and high‐humidity environments are an ideal atmospheric water collection environment. Therefore, we believe that this fundamental research will be conducive to human efficiently and environmentally obtain freshwater resources in the future. [ \n \n 46 \n \n ]"
} | 8,036 |
26776731 | null | s2 | 5,251 | {
"abstract": "Bacterial programmed cell death and quorum sensing are direct examples of prokaryote group behaviors, wherein cells coordinate their actions to function cooperatively like one organism for the benefit of the whole culture. We demonstrate here that 2-n-heptyl-4-hydroxyquinoline-N-oxide (HQNO), a Pseudomonas aeruginosa quorum-sensing-regulated low-molecular-weight excreted molecule, triggers autolysis by self-perturbing the electron transfer reactions of the cytochrome bc1 complex. HQNO induces specific self-poisoning by disrupting the flow of electrons through the respiratory chain at the cytochrome bc1 complex, causing a leak of reducing equivalents to O2 whereby electrons that would normally be passed to cytochrome c are donated directly to O2. The subsequent mass production of reactive oxygen species (ROS) reduces membrane potential and disrupts membrane integrity, causing bacterial cell autolysis and DNA release. DNA subsequently promotes biofilm formation and increases antibiotic tolerance to beta-lactams, suggesting that HQNO-dependent cell autolysis is advantageous to the bacterial populations. These data identify both a new programmed cell death system and a novel role for HQNO as a critical inducer of biofilm formation and antibiotic tolerance. This newly identified pathway suggests intriguing mechanistic similarities with the initial mitochondrial-mediated steps of eukaryotic apoptosis."
} | 354 |
26029236 | PMC4429567 | pmc | 5,254 | {
"abstract": "The tripartite symbiosis between legumes, rhizobia and mycorrhizal fungi are generally considered to be beneficial for the nitrogen (N) uptake of legumes, but the facilitation of symbiosis in legume/non-legume intercropping systems is not clear. Therefore, the aims of the research are as follows: (1) to verify if the dual inoculation can facilitate the N uptake and N transfer in maize/soybean intercropping systems and (2) to calculate how much N will be transferred from soybean to maize. A pot experiment with different root separations [solid barrier, mesh (30 μm) barrier and no barrier] was conducted, and the 15 N isotopic tracing method was used to calculate how much N transferred from soybean to maize inoculated with arbuscular mycorrhizal fungi (AMF) and rhizobium in a soybean ( Glycine max L.cv. Dongnong No. 42)/maize ( Zea mays L.cv. Dongnong No. 48) intercropping system. Compared with the Glomus mosseae inoculation ( G.m. ), Rhizobium SH212 inoculation (SH212), no inoculation (NI), the dual inoculation (SH212+ G.m. ) increased the N uptake of soybean by 28.69, 39.58, and 93.07% in a solid barrier system. N uptake of maize inoculated with both G. mosseae and rhizobium was 1.20, 1.28, and 1.68 times more than that of G.m. , SH212 and NI, respectively, in solid barrier treatments. In addition, the amount of N transferred from soybean to maize in a dual inoculation system with a mesh barrier was 7.25, 7.01, and 11.45 mg more than that of G.m. , SH212 and NI and similarly, 6.40, 7.58, and 12.46 mg increased in no barrier treatments. Inoculating with both AMF and rhizobium in the soybean/maize intercropping system improved the N fixation efficiency of soybean and promoted N transfer from soybean to maize, resulting in the improvement of yield advantages of legume/non-legume intercropping.",
"introduction": "Introduction Legume and non-legume intercropping cultivation has been widely encouraged in sustainable agriculture because it has the potential to improve the yield significantly and allow plants to use soil N more efficiently ( Eaglesham et al., 1981 ; Li et al., 2001 , 2011 ; Hauggaard-Nielsen et al., 2009 ; Gao et al., 2014 ), which is beneficial for reducing the amount of chemical fertilizer supplies and has positive consequences on the environment ( Lekberg and Koide, 2005 ; Pelzer et al., 2012 ). N could be used efficiently in the intercropping system because the N fixed by legumes can be transferred to companion species, and this part of N is a crucial source for the non-nodulated crop’s growth and development ( Moyer-Henry et al., 2006 ). For example, Fujiu et al. (1990) have found that the amount of N transferred to sorghum ( Sorghum bicolor Moench cv. Yuldjirushi) accounted for 32–58% of its N uptake in a soybean ( Glycine max L. cv. Kurosengoku)/sorghum intercropping system. A substantial amount of N is transferred in different communities including N 2 -fixed and non-N 2 fixed plants ( Chu et al., 2004 ; Sierra and Daudin, 2010 ; Isaac et al., 2012 ; Frankow-Lindberg and Dahlin, 2013 ; Jamont et al., 2013 ; Chapagain and Riseman, 2014 ). In addition, inoculating rhizobium can significantly increase the yield and N uptake of wheat ( Triticum aestivum L. cv. Long 17) and faba bean ( Vicia faba L. cv. Linxia Dacandou) and further improve the intercropping advantages. This has been confirmed by Xiao et al. (2006) , who inoculated rhizobia strain NM353 for faba bean in faba bean/wheat intercropping system. Fang et al. (2009) showed that the biomass and grain yield of faba bean ( V. faba L. cv. Lincan No. 2) and maize ( Zea mays L. cv. Zhongdan No. 2) and the number of faba bean nodules were increased similarly when inoculated with rhizobia strain GS374 in the faba bean/maize intercropping system. Several studies also indicated that inoculating both AMF and rhizobium can promote the growth of crops and improve the yield and nutrient uptake of crops ( Lekberg and Koide, 2005 ; Antunes et al., 2006 ; Varennesa and Goss, 2007 ; Tajini et al., 2011 ; Abd-Alla et al., 2014 ). AMF is considered to be of great importance in plant symbiosis and promoting nutrient uptake, especially P ( Li et al., 2004 ; Pasqualini et al., 2007 ; Xiao et al., 2010 ; Tajini et al., 2011 ; Abd-Alla et al., 2014 ). The mycelium can extend to the area outside the rhizosphere, connect roots with the surrounding soil microhabitats and enlarge the area that roots have to absorb nutrients ( He et al., 2003 ). Thus, water and nutrients can be transported by the huge hyphae network to be finally absorbed by plants ( Tobar et al., 1994 ; Vassilev et al., 2001 ; Yao et al., 2001 ; He et al., 2003 ). The N transfer in intercropping systems is assumed to be enhanced if N fixation by legumes can be improved by inoculation with AMF and rhizobium, which have the potential to enhance plant productivity. However, the effects of inoculating both rhizobium and AMF in legume/non-legume intercropping systems on N transfer are currently uncertain. Therefore, the objectives of our study are as follows: (1) to verify if the dual inoculation can facilitate N uptake and N transfer in a maize/soybean intercropping system, (2) to use the 15 N isotopic tracing method to calculate how much N will be transferred between maize and soybean intercropping under the inoculation of both rhizobium and AMF.",
"discussion": "Discussion The growth of maize plants in a no barrier system was facilitated greatly over those with a mesh barrier or solid barrier, regardless of the status of inoculation, confirming the yield advantage in maize/soybean intercropping systems in agreement with previous reports ( Hauggaard-Nielsen and Jensen, 2005 ; Chapagain and Riseman, 2014 ). The biomass of soybean and maize inoculated with both AMF and rhizobium were more than that of NI in all root separation patterns, which illustrates that inoculating rhizobium and AMF can enhance the biological yield advantages of soybean and maize. This is consistent with our former research results that the biomass of soybean supplied with different phosphorus sources was improved significantly when inoculated AMF and rhizobium ( Tong et al., 2009 ). Xiao et al. (2010) have found that inoculating AMF in upland rice ( Oryza sativa ssp. Japonica Nipponbare) and mungbean ( Vigna radiata L. cv. Chuanyuan) intercropping systems increased the biomass of mungbean by 288.8%. In addition, Mei et al. (2012) found that the average grain yields of faba bean ( V. faba L.) and maize ( Z. mays L.) increased by 30–197% and 0–31%, respectively, after inoculating with rhizobium in maize and faba bean intercropping systems in reclaimed desert soil. In our study, we inoculated both rhizobium and AMF in a soybean/maize intercropping system. The soybean and maize biomass was 21.66 and 16.32% higher than that of SH212 alone and 22.31 and 15.67% higher than that of G.m. alone in a no barrier pattern ( Table 1 ). That suggested synergistic facilitation for yield advantage was observed in maize/soybean intercropping because of inoculating both AMF and rhizobium. Why Did Inoculating Rhizobium and AMF in Soybean/Maize Intercropping System Improve Growth of Maize and Soybean? In our experiment, both AMF and rhizobium colonization independently increased the total biomass of soybean in solid barrier patterns compared with their respective controls, and the total biomass of soybean with dual inoculation was 1.68 times as much as that of NI ( Table 1 ). We found synergistic effects of AMF and rhizobium on soybean growth, which was consistent with the results of Abd-Alla et al. (2014) , who found that dual inoculation with rhizobium and AMF was more efficient for promoting growth of faba beans ( V. faba L.). Rhizobium symbiosis is involved in the fixation of atmospheric N, whereas AMF improves the ability of a plant to absorb P and other nutrients ( Li et al., 2006 ; Erman et al., 2011 ; Tajini et al., 2012 ; Pellegrino and Bedini, 2014 ). Our previous study found that maize overyielding in maize/faba bean or soybean intercropping resulted from its uptake of phosphorus mobilized by the acidification of the rhizosphere via fababean root by using mesh (permeable) and solid (impermeable) root barriers. The level of soybean to acidify rhizosphere is lower than faba bean ( Li et al., 2007 ). The present study showed that N uptake by soybean inoculated with both AMF and rhizobium with no barriers was 1.98 times as much as that of the NI group ( Figure 3A ). Therefore, the increase in dry matter accumulation could be attributed to the incremental increase on nodulation, N fixation and nutrient acquisition. In this experiment, we found that the N uptake of maize with no barriers was 8.63 and 12.01% more than that with mesh barriers or solid barriers under non-inoculated conditions, and 9.08 and 17.94% more under dual inoculated conditions ( Figure 3B ). In addition, the results showed that N transfer from soybean inoculated with both AMF and rhizobium to maize in no barrier and mesh barrier patterns increased 12.46 and 11.45 mg/pot compared with the NI group ( Table 3 ), which means that the N transfer was improved due to the dual inoculation. Therefore, the biomass of maize was improved due to the increase of N uptake after intercropping with soybean and inoculating with AMF and rhizobium. This is in agreement with the results of Zarea et al. (2011) , Larimer et al. (2014) , and Pellegrino and Bedini (2014) . AM Fungal Hyphae Contribute to N Transfer in Soybean/Maize Intercropping Systems Arbuscular mycorrhizal fungi are important components in intercropping agrosystems ( Li et al., 2009 ; Yan et al., 2014 ). In our study, N was transferred under non-inoculation conditions in mesh barrier patterns, but the rate and amount of N transferred in SH212+ G.m. inoculations were 1.56 and 3.07 times more than that of the NI group ( Table 3 ), which resulted from the improved AMF colonization rate of soybean and maize by inoculating with both rhizobium and AMF. The 30-μm nylon-net prevented the direct contact of the roots of soybean and maize but allowed hyphae to penetrate and link, and the hyphae enhanced the degree of contact of soybean and maize and the degree of contact of roots affected N transfer significantly, in agreement with Chu et al. (2004) . Many researchers suggested that there were two pathways for N transfer. One is a direct transfer that N fixed by legumes is transferred to associated non-N 2 fixed plants via a mycorrhizal fungal hyphae network ( Cardoso and Kuyper, 2006 ; Sierra and Nygren, 2006 ). The N concentration of legumes is generally higher than graminaceous; therefore, N could transfer to intercropped graminaceous along the gradient of concentration via hyphae ( Chu et al., 2004 ). The other pathway is an indirect transfer, in which the residual and root exudates ( Jalonen et al., 2009 ) of legumes release N to the rhizosphere when they decompose, and the mineralized inorganic N can then be absorbed by the intercropped graminaceous or mycorrhizal hyphae ( Tomm et al., 1994 ; Johansen and Jensen, 1996 ; He et al., 2003 ). In our experiment, the rate and the amount of N transferred from soybean to maize were improved by microbial inoculations. Hence, no matter which way the N is transferred, the hyphae play an important role in N transfer from soybean to associated maize. In addition, we found that inoculating rhizobium also promoted the growth of maize. Some studies have confirmed that PGPR were beneficial for plant growth, yield and crop quality ( Zafar et al., 2012 ; Stefan et al., 2013 ; Güneş et al., 2014 ; Yadav and Verma, 2014 ). PGPRs could enhance asymbiotic N 2 fixation and nutrient uptake and compete against detrimental microorganisms ( Dey et al., 2004 ; Lucy et al., 2004 ; Khan, 2005 ; Yadav and Verma, 2014 ), which would be the reason that the growth of maize increased with rhizobium inoculation in our experiment. Arbuscular mycorrhizal fungi and rhizobium establish beneficial symbiosis with legumes and enhance the advantage of intercropping, and the nutrient uptake and biomass of intercropped crops were significantly increased. Therefore, co-inoculation with both AMF and rhizobium should be considered for the sustainable development of the legume/graminaceous intercropping pattern."
} | 3,090 |
28694942 | PMC5485398 | pmc | 5,256 | {
"abstract": "Self-repairing biohybrid nanoshells provide living cells with high activity and extended viability in harsh micro-environments.",
"conclusion": "Conclusions To conclude, we have described an experimental success of the use of biohybrid nanoshells in cell-in-shell encapsulation to endow the encapsulated cells with self-repairing behaviour. These self-repairing shells present structural superiority of nanopores and nanolayers, and provide the cells with excellent protection. The interaction mechanism has been investigated in detail, and guided the synthesis of the self-repairing biohybrid shells using different bioactive molecules. It is believed that our strategy is not limited to yeast and cyanobacteria, and should be applicable to higher eukaryotes, such as human cells, even multicellular organisms. 25 Furthermore, other functional matter can also be used to enhance cell activity and introduce various functionalities. For example, bioactive proteins can be used to improve the selective activity; polymers can be used to design smart interfaces; oxides can be used to introduce magnetic, electronic, optical, and thermal properties. The self-repairing strategy developed here therefore offers a general, facile, and unique approach for the encapsulation of cells with long-term viability, extraordinary stability, high activity and multiple functionalization.",
"introduction": "Introduction Self-repair is a common and wonderful phenomenon of living organisms to allow them to adapt to constantly changing environments through long term evolution. 1 However, it is rarely seen in single cells, which might be a result of evolution of unicellular organisms to multicellular organisms having more advanced environmental adaption and self-protection capability. It is therefore of great interest to endow the single cell with self-repair behaviour. A cell-in-shell structure without complicated genetic manipulation is currently regarded as the most efficient non-biogenic route to cell protection and functionalization. 2 – 12 The nanostructured shell materials with tunable physico-chemical properties provide an indispensible platform to endow cells with new functionalities, 13 – 25 such as magnetic cell-in-Fe 3 O 4 shell, 15 , 16 thermally durable cell-in-SiO 2 shell 17 and cell-in-SiO 2 /TiO 2 shell, 18 electrically conductive cell-in-Au/Ca/graphene shell, 19 UV-resistant cell-in-LnPO 4 shell 20 and pH-responsive cell-in-poly(methacrylic acid)-co-NH 2 shell. 21 However, traditional nanostructured shells do not satisfy the increasing demands of modern applications because these synthetic shells not only disturb cell proliferation and life cycle, but also are unable to re-assemble onto the cell surface after the process of encapsulation. 26 Once shell structures are broken, which is often caused by cell division, the decrease of stability and loss of functionalities of encapsulated cells and/or daughter cells will occur. 27 A path to self-repair of the functional nano-scale shell is mostly preferred, whereby the preformed precursor could self-assemble onto the cell surface during cell division. Natural amino acids can non-covalently bind with the cell surface due to their bioactive groups ( e.g. amino group, carboxyl group and/or thiol group etc. ). They could, therefore, readily self-assemble onto the cell surface to form a nanothin meso-scaled layer. Also as the most basic biomolecules that do not require complicated synthetic procedure, amino acids possess similar physico-chemical properties to small biomolecules of cell, and therefore can be good candidates to form nanoshells. However, amino acid molecules alone may be transported through cell membrane/walls, suggesting that the amino acid molecules are not stable onto the cell surface as shell materials. 28 As is known, amino acid molecules can interact with gold nanoparticles which have been successfully introduced to shell materials. 29 – 31 In this study, biohybrid aggregates composed of Au nanoparticles and l -cysteine molecules have been successfully developed to fabricate the nanoshell around the cell surface and endow the encapsulated cell with the self-repairing property. This self-assembled Au@ l -cysteine biohybrid nanothin shell presents a worm-like porous structure due to the properties and nano-effect of Au nanoparticles. Interestingly, the nanoporous biohybrid shell would not only allow fast mass exchange, and increase cell activity and stability in synthetic environments, but also offer the encapsulated cells more functionalities to expand their applicability, such as protecting the cells against strong UV radiation, natural toxins, high light radiation, and abrupt pH changes. Most importantly, the self-assembled Au@ l -cysteine hybrid aggregates dispersed in the culture solution can act as sol precursors to self-repair broken shells and form integrated shells. The formation of the biohybrid aggregates was first investigated. l -cysteine was added to an Au colloid (2–3 nm in diameter from the transmission electron microscopy (TEM) micrograph in Fig. S1a † ) at room temperature. Precipitates were characterized after collection by centrifugation–washing steps. The TEM micrograph depicts that the biohybrid aggregates present nanoporous structure with 4–8 nm pore size (Fig. S1b † ). The Fourier transform infrared spectroscopy (FTIR) and the X-ray photoelectron spectroscopy (XPS) spectra confirm the formation of Au–S bonds (Fig. S2a and b † ), 32 , 33 indicating that the interaction and structure of biohybrids are stable. The UV-vis spectrum shows that the Au@ l -cysteine biohybrids not only can absorb excess high light (Fig. S2c † ), but are also stable in solution (Fig. S2d † ). It is safe to conclude that the nanosized Au@ l -cysteine biohybrids are stable in solution and present a nanoporous structure. These properties not only enable self-assembly and self-repairing of shells, but also facilitates mass communication. Yeast cells Saccharomyces cerevisiae have been selected as our model eukaryotic cells to study self-repairing behaviours. In a typical preparation of self-repairing yeast cell-in-shell structures (Fig. S1 † ), the biohybrid aggregates are firstly dispersed in phosphate buffer solution (PBS). Subsequently, the aggregates are added to the clean cell solution under gentle shaking at room temperature. During the interaction between the native yeast cells (Fig. S1c † ) and the preformed precursors, native cells are gradually entrapped in the biohybrid shell formed by the condensation of the meso-structured Au@ l -cysteine aggregates (Fig. S1d † ). The entrapped cells and excess biohybrid aggregates are collected and re-dispersed into fresh medium for further incubation under ambient conditions. SEM (scanning electron microscopy), OM (optical microscopy) and TEM micrographs ( Fig. 1 ) clearly depict that the yeast cells are individually and separately entrapped in dense shells and maintain their original morphologies, which strongly argues that such a self-assembly has no negative effect on the biological morphologies of the cells. Biohybrid aggregates on the cell surface form a worm-like nanoporous structure (inset in Fig. 1b ), and the nanopore size is 2–6 nm, which is slightly smaller than the TEM data of preformed precursors (Fig. S1b † ). Probably a little deformation of nanochannels occurs due to the interaction between the soft structured biohybrid aggregates and cell surface. The microtome-sliced TEM micrograph ( Fig. 1c ) shows that the cell is entrapped in the uniformly nanothin shell with 160 nm of thickness, and cell integrity is maintained. The EDX line profile of cell@biohybrid shell confirms that biohybrid aggregates containing Au element are uniformly coated on the cell surface ( Fig. 1d and inset). Furthermore, cell culture experiments show that the growth curve of encapsulated cells is similar to that of native cells, which indicates that the nanoshell has no obvious effect on cell division (Fig. S3 † ). All together it can be concluded that (1) our procedure is facile and does not need numerous cycles of multilayer deposition in comparison with traditional layer-by-layer methods, meaning that cell activity could be well maintained after encapsulation; (2) the biocompatible biohybrid aggregates can effectively and easily coat onto the cell surface by self-assembly, which is beneficial for self-repair when the shell is broken; (3) nanothin and nanoporous structures of shells have been developed which would facilitate mass and energy transportation and cell division. Fig. 1 Characterization of yeast cell-in-shell structure. (a) SEM and OM in a visible light mode (inset) micrographs of yeast cells@biohybrid shells; (b) TEM micrographs of yeast@biohybrid shell and the corresponding magnified micrograph of black square area (inset) show that the single cell is coated with nanoporous-structured biohybrid shell; (c) ultrathin section TEM micrograph of yeast@biohybrid shell; (d) EDX line profile for Au encapsulated yeast cells confirms the presence of biohybrid shells.",
"discussion": "Results and discussion To test whether the biohybrid shells protect cells in harsh conditions during cell proliferation, relative activities of encapsulated yeast cells have been carried out with native yeast cells as a comparison. It has been proven that cells keep their ability to proliferate in fresh media (Fig. S4 † ). Therefore, the encapsulated yeast cells are cultivated in fresh liquid media and in normal solution (without fresh medium) under short wave ultraviolet radiation (UVC, strongest ultraviolet band of sunlight for destroying genetic structure of cells 34 ) ( Fig. 2 ). Encapsulated yeast cells maintain higher activity under UVC radiation. For example, even after 5 hours radiation, 98% (±6%) of the initial activity of encapsulated cells in fresh medium remain ( Fig. 2a ), while native cells in medium ( Fig. 2c ) quickly lose their activity within 5 hours. When in normal solution without medium, yeast cell@biohybrid shell ( Fig. 2b ) also shows higher activity than yeast cell within silica (Fig. S5 † ) and native yeast cells ( Fig. 2d ) in normal solution. Their lower activity, compared with the encapsulated cells in fresh medium, should be attributed to the cells’ ability to divide being inhibited in the absence of the fresh medium. Furthermore, the test of nanosized natural toxin (lyticase) 35 invasion shown in Fig. S6 † can also prove that the shells can protect the cells against natural toxin invasion. Fig. 2 Relative activities of yeast@biohybrid shell exposed under UVC radiation. Relative activities by yeast@biohybrid shell and native yeast exposed under UVC radiation in (a) and (c) fresh cultural medium, and (b) and (d) solution without cultural medium. It is also necessary to point out that encapsulated cells can easily break their shells during cell division since the shell is very thin and soft. That seems to easily cause loss of functionalities and a decrease in stability. However, the encapsulated yeast cells mentioned above still show high stability in proliferation. Therefore, there should be a presence of other protection mechanism. The surfaces and morphologies of the yeast cells during division are shown in the SEM micrographs in Fig. 3(a–e) and Fig. S7A. † The micrographs show that the generation of a yeast cell is typical budding reproduction, and the morphologies of cells during the budding are normal and do not shrink. Notably, nanoparticles aggregated on the cell surfaces do not show significant decreases in the 5 stages of the life cycle (G0, S, G2, M and G1 phases, see Fig. 3 and Fig. S7A † ). The shell thickness of the dividing cell (around 140 nm, Fig. 3f ) becomes slightly thinner, compared with that of the single cell (around 160 nm, Fig. 1C ) because the enlarged surface area during cell division will make the shell become thinner. It is surely impossible to cover both mother cell and daughter cell only by the original biohybrid shell, despite the shells being soft and allowing deformation. The excess biohybrid aggregates could play an important role in self-assembly onto the naked buds and/or daughter cells because the only possibility is that the excess biohybrid aggregates in solution self-repair the thinner shells and/or broken shells. Fig. 3 Process of self-repairing biohybrid nanoshells in yeast cell division (a–e), (scale bar: 1 μm). (a) Encapsulated mother yeast cell (G0 phase); (b) encapsulated mother cell and bud (S phase); (c) encapsulated mother cell and growing bud (G2 phase); (d) encapsulated mother cell and bud of the same size as the mother cell (M phase); (e) encapsulated mother and daughter cells (G1 phase). (f) Merged magnified ultrathin section TEM micrograph of encapsulated dividing cell (scale bar: 250 nm). All original details are shown in Fig. S7. † \n Direct evidence of self-repair is observed in the marked square and circle areas in Fig. 3f and Fig. S7B. † There is no difference in shell thickness between the mother cell and the bud (circle area in Fig. S7B (b) † ). This means that the biohybrid aggregates can self-assemble onto the naked surfaces of both the mother cell and the bud. More interestingly, biohybrid aggregates have been found in the newly generated interface between mother cell and the bud (square area in Fig. S7B(a) † ). This suggests that the generated interface is subsequently filled by original biohybrid shell aggregates or excessive nano-aggregates after cell division. It is a unique phenomenon, where it seems that the broken shell can be self-repaired by self-assembled biohybrid aggregates, and also an excellent advantage, indicating that cells are protected and functionalized by biohybrid shells in the life cycle. In contrast, the self-assembling phenomenon can hardly be found in yeast cell@polymer matter (Fig. S8a and b † ) and cells within inorganic matter (Fig. S8c and d † ) in the presence of excess shell materials. The results confirm that traditional polymeric or inorganic shells are not self-repair, even in the presence of excess shell precursors, directly attributed to easily polymerization of the traditional bulky polymeric precursors during the cell encapsulation procedure. The aggregation behaviours of typical polymeric nanocomposites are also evidenced (Fig. S9a and b † ). TEM images clearly evidence that Au@PAH (poly allyamine hydrochloride) (Fig. S9a † ) and Au@PLL (poly l -lysine) (Fig. S9b † ) nanocomposites are easily polymerized to very large particle aggregates or large scale net-like aggregates. As is well known, these large aggregates or precipitates are difficult to self-assemble onto the cell surface or self-repair the broken shell. In contrast, small amino acid molecule-based nano-aggregates (Au@ l -cysteine biohybrids) (Fig. S9c † ) could easily achieve the goal of self-repairing property due to the nano-effect and their surface bound functional groups. This is a big advantage of small amino acid molecules in the self-repairing of shells. Such a self-repairing phenomenon is not only limited to eukaryotic cells. It could also be extended to prokaryotic cell systems. Cyanobacteria, which play a major role in the global carbon cycle, 36 have been picked as a typical example of prokaryotic cells. The self-repairing process of encapsulated cyanobacteria is also observed by SEM and TEM images ( Fig. 4A and B ). Fig. 4A shows that the reproduction of cyanobacteria is a typical binary fission, and morphologies of cells are normal and do not shrink, implying that the shells do not limit the encapsulated cells’ division. The nanoparticles are clearly observed to aggregate on cell surfaces in the whole division cycle. Compared with yeast cells, the shells of the encapsulated cyanobacteria cells show a thinner thickness (around 100 nm, Fig. 4B ). This indicates that the interaction between the biohybrid aggregates and the cyanobacterium is possible weaker than the yeast cell, attributed to the different bio- and physicochemical properties of the cells’ surfaces. Furthermore, the self-repairing biohybrid shell could also act as a safeguard to protect cyanobacteria from harsh conditions, such as high light and strong UV radiation, and abrupt pH changes (Fig. S10 † ). Fig. 4 (A) Process of self-repairing biohybrid nanoshell in cyanobacteria division (a–e); (B) microtome-sliced TEM micrograph and magnified micrograph (inset) of encapsulated cyanobacteria (scale bar: 0.5 μm). All the protection to UVC and high-light radiation, natural toxin invasion and abrupt pH change should be attributed to the biohybrid shell, for example, the strong absorption of UVC and high-light (in wavelength of 190–280 nm (Fig. S11 † ), and 450–700 nm (Fig.S2d)), strong interaction between the amino acid and nature toxin (Table S1 † ), and good buffering capacity of amino acid molecules. It is notable that the cell protection during proliferation would be due to the self-repairing behaviour of the encapsulated cells. Self-assembly between nano-aggregates and cell surface is the critical factor of this self-repair. It is reasonable to consider self-repairing behaviours caused by self-assembly. We cultivated yeast cells in biohybrid solution ( Fig. 5a ) and on a biohybrid-coated silicon substrate ( Fig. 5b ), respectively. SEM images clearly show that with the time being prolonged, the biohybrid aggregates on cell surfaces gradually increase from a loose structure to a dense structure under both sets of conditions. There is no obvious difference in the cell surface after 10 hours compared with that after 8 hours in the case of the cells in the biohybrid solution (Fig. S12 † ), indicating that the thickness of shell cannot increase unlimitedly with time being prolonged. Similarly, in the case of the cells on the biohybrid coated silicon substrate, the shell grows uniformly from bottom to top. These results point to a clear demonstration that the biohybrid aggregates could actively self-assemble onto a cell surface to form a dense shell, even by cultivating the cells on a biohybrid coated silicon substrate, which is the direct reason why the nano-aggregates can self-repair the shells. Fig. 5 SEM images of yeast cells (a) in biohybrid solution, and (b) on silicon substrate surfaces coated by biohybrid aggregates for various times. Insets are magnified images, scale bar: 200 nm. The formation of a uniform nanoshell and shell thickness are possibly related to the surface charges and potentials of cells and biohybrids. Surface charges and potentials of cells and biohybrids have been measured by zeta potentials ( ζ ), where ζ (yeast cell) is –17.1 ± 1.2 mV, ζ (cyanobacteria) is –14.2 ± 0.8 mV, ζ (biohybrid) is –19.3 ± 0.7 mV (Table S2 † ). After encapsulation, zeta potentials of encapsulated cells are higher than native cells ( ζ (yeast cell@biohybrid shell) is –18.5 ± 1.5 mV, ζ (cyanobacteria@biohybrid shell) is –16.4 ± 1.4 mV) (Table S2 † ). This means that the encapsulated cells provide better dispersion than native cells because the charged encapsulated cells repel one another and therefore overcome the natural tendency of cells to aggregate. 37 According to the simplified Grahame equation for low zeta potential ( σ = εε \n 0 \n ζ / λ \n D , where ε is dielectric permittivity and λ \n D is the Debye length), 38 surface charge ( σ ) is positive proportional to zeta potential. In our proposed model, the negatively charged cell surfaces are possibly attracted electrostatically to the ion pair (negatively charged biohybrid aggregates with cationic ions (M + )) forming an electrical triple layer ( Fig. 6a ). 39 , 40 After self-assembling onto the cell surface, the biohybrid aggregates intimately coat the cell surface via hydrogen-bonds between amino groups/carboxyl groups of the cysteine molecules in the biohybrid aggregates and the functional groups (such as amino groups and carboxyl groups of proteins and hydroxyl groups of polysaccharide) of the cell surface ( Fig. 6b ). It is evidenced that pure cysteine molecules can also form a net-like aggregation on the cell surface (Fig. S13a, † the smooth native cell surface is the comparison in Fig. S13b † ), in spite of its instability. These interactions might cause the deformation of nanopores of nanoaggregates, corresponding with the previous results shown in Fig. 1b and S1b. † After encapsulation, moreover, yeast cells can attract more charged biohybrid aggregates due to their higher surface charge, compared with cyanobacteria surface, which gives a reason for the biohybrid shell on yeast cell surfaces being thicker than the shell on cyanobacteria surfaces. This is also in very good agreement with the TEM results ( Fig. 1c and 4B ). With the increased thickness of shell, the surface charge of encapsulated cells would reach a balance where the biohybrid aggregates in solutions could not continue to assemble onto the original biohybrid shell ( Fig. 6a ). When the shell is broken during the cell proliferation, this balance is broken and the encapsulated yeast cell would absorb and re-assemble the nano-aggregates to self-repair the shell. Such a self-repairing behaviour is analogous to a certain self-repairing method in living organisms, where the broken area is self-repaired by the uptake of external precursors. For example, diatoms absorb silicon sources from their living environment to re-build their silica shell during cell division. 41 , 42 These proposed models are in good agreement with the experimental results, which are helpful to understand the self-repairing behaviour of encapsulated cells. Fig. 6 Formation mechanism of self-repairing biohybrid shell on yeast cell surface. (a) Ionic interactions proposed between cell and nanoaggregates during forming process, where M + is cationic ions in solution; (b) interaction between the cell surface and biohybrid shell after formation. Furthermore, in our case, negative charges encapsulated around the cells do not affect the intrinsic characteristics of cell surface charge, 43 which avoid cell surface damage caused by traditional positively charged polyelectrolyte shell. 44 Different bioactive molecules can be therefore easily introduced to form self-repairing biohybrid shells, such as different amino acids and peptides. These shells can also be engineered onto the cell surface to protect cells. For example, cyanobacteria within Au@ l -lysine hybrid shells show higher photosynthetic activity under high light radiation (Fig. S14a † ). Cyanobacteria cells within Au@glutathione shells have been clearly confirmed by the microtome-sliced TEM image (Fig. S14b † )."
} | 5,676 |
36771084 | PMC9919917 | pmc | 5,257 | {
"abstract": "Pyruvate is a hub of various endogenous metabolic pathways, including glycolysis, TCA cycle, amino acid, and fatty acid biosynthesis. It has also been used as a precursor for pyruvate-derived compounds such as acetoin, 2,3-butanediol (2,3-BD), butanol, butyrate, and L-alanine biosynthesis. Pyruvate and derivatives are widely utilized in food, pharmaceuticals, pesticides, feed additives, and bioenergy industries. However, compounds such as pyruvate, acetoin, and butanol are often chemically synthesized from fossil feedstocks, resulting in declining fossil fuels and increasing environmental pollution. Metabolic engineering is a powerful tool for producing eco-friendly chemicals from renewable biomass resources through microbial fermentation. Here, we review and systematically summarize recent advances in the biosynthesis pathways, regulatory mechanisms, and metabolic engineering strategies for pyruvate and derivatives. Furthermore, the establishment of sustainable industrial synthesis platforms based on alternative substrates and new tools to produce these compounds is elaborated. Finally, we discuss the potential difficulties in the current metabolic engineering of pyruvate and derivatives and promising strategies for constructing efficient producers.",
"conclusion": "5. Conclusions and Prospects This review aimed to present the progress of research on pyruvate and derived compounds based on metabolic engineering. Detailed pyruvate and derived compounds production and engineering strategies are described in Table 1 . We found a long history of microbial production of these compounds. As shown in Table 1 , E. coli , C. glutamicum , C. glabrata, K. pneumoniae , and S. cerevisiae are commonly used, producing strains, among which C. glutamicum is a food-grade microorganism with high safety and more suitable for industrial production. These microorganisms usually generate specific products by establishing synthetic metabolic pathways. Traditionally, microorganisms establish synthetic metabolic pathways mainly by gene overexpression or knockout to maximize production. However, improper gene expression or certain metabolic defects may cause problems such as cell growth inhibition, metabolic flux imbalance, and capacity reduction due to the inability to provide precise regulation. Therefore, metabolic engineering should shift from stepwise static regulation to dynamic regulation development, which helps maintain metabolic balance and cell growth. For example, switches in elements such as promoters can be induced upon exogenous signaling stimuli to regulate the expression of downstream genes, or dynamic regulation can be achieved by metabolite response elements such as promoters and transcription factors to regulate the expression levels of key enzymes of the pyruvate synthesis pathway, enabling cells to induce pyruvate spontaneously [ 70 , 121 , 122 , 123 ]. In addition, RNA-based engineering of cis -repressors has been successfully applied in metabolic engineering and synthetic biology to control specific proteins in a modifiable manner and alter metabolic fluxes to produce valuable chemicals [ 124 , 125 ]. The cis -repressors have the advantage of being portable and do not require an inducer due to the built-in set threshold for protein synthesis [ 125 ]. The complexity of regulation and metabolite crosstalk in metabolic pathways is also a major difficulty in the development of metabolic engineering. The recent advance of bacterial microcompartments has reduced the complexity by compartmentalizing intracellular enzymes using selective permeation of the protein shell [ 126 , 127 ]. The locus of bacterial microcompartments has been identified in 23 bacterial phyla [ 128 ], and will provide the basis for the next generation of metabolic engineering. The increase in the number of omics datasets, coupled with advances in ML, has also created tremendous opportunities for metabolic engineering. The increase in the number of omics datasets coupled with advances in ML have allowed insight into intracellular metabolic pathways, thus creating tremendous opportunities for scientists to explore cell-free biosynthesis systems in vitro [ 129 ]. Cell-free biosynthesis includes steps such as pathway design, enzyme mining, enzyme modification, multi-enzyme assembly, and pathway optimization, which will rely on metabolic pathway databases and applications of ML to design components and modules [ 130 ]. In addition, low-cost chemical methods allow the synthesis of high-purity pyruvate and derivatives [ 131 ], making them more economically attractive, which has led to limitations in the development of industrial fermentation. Therefore, reducing the cost of raw materials is an effective way to improve microbial metabolic engineering technology applications. For example, common agricultural waste lignocellulosic is used as a fermentation substrate [ 132 ]. However, other issues need to be considered to increase its industrial value: (1) developing more efficient technologies for saccharifying lignocellulose including the search for more efficient cellulose hydrolases; (2) developing pretreatment technologies to eliminate inhibitors and toxic substances from lignocellulose hydrolysates; (3) improving the tolerance of engineered bacteria to inhibitors and toxic substances to improve the efficiency of lignocellulose utilization; and (4) developing product recovery technologies to improve the efficiency of product recovery. In addition, some techniques are also under development for directly converting CO 2 to acetoin, 2,3-BD, and butanol by some carbon-fixing microorganisms [ 106 , 133 ]. Although a suitable production route was successfully constructed, the cyanobacteria yield was too low to meet the needs of industrial production [ 134 ]. Therefore, we anticipate higher productivity if we develop methods to produce pyruvate and its derivatives from mixed substrates, combined with fermentation process optimization and downstream recovery operations.",
"introduction": "1. Introduction Many chemicals and fuels are currently produced from fossil fuels, which will cause a worldwide decrease in fossil materials and many environmental problems. The emergence of metabolic engineering in the early 1990s provided ideas to solve the problems [ 1 ]. The establishment of the new discipline has significantly accelerated cell construction for chemical production. As a rapidly developing field, it uses genetic recombination technologies to change cell characteristics and combine with other technologies, such as biochemical engineering and microbial gene regulation, to construct new metabolic pathways for the synthesis of specific products [ 2 ]. To this end, a wide range of engineering strategies has been developed in various microorganisms, including the evolution of genome editing [ 3 ], tolerance engineering [ 4 ], rewiring of metabolic fluxes [ 5 ], and adaptive evolution [ 6 ]. Pyruvate is the hub of various endogenous metabolic pathways, which not only plays a crucial role in bioenergetic metabolism but also serves as a precursor for synthesizing a wide range of compounds. Compounds whose starting substance is sugar and whose target substance is pyruvate or are biosynthesized via pyruvate as an intermediate metabolite are called pyruvate-derived compounds such as acetoin, 2,3-BD, butanol, butyrate, and L-alanine. These derived chemicals are widely used in various fields. Acetoin and 2,3-BD have high potential applications as plasticizers, softeners, drug fumigants, and foods [ 7 ]. Butanol is used as a substitute for gasoline to alleviate the pressure of petroleum resources [ 8 ]. Butyrate mainly serves as animal feed additives, flavors, and pharmaceuticals while being a vital precursor for biofuel production [ 9 ]. L-alanine is a precursor of methyl glycine diacetate [ 10 ], which can be used as a novel synthetic green chelator. Pyruvate is currently produced by chemical conversion or microbial fermentation to meet the fast-growing market demand. In terms of chemical conversion, pyruvate is mainly synthesized via dehydration and decarboxylation of tartaric acid [ 11 ]. In this process, pyruvate is distilled from the mixture of tartaric acid and potassium bisulfate at 220 °C. Then, the resulting crude acid is further distilled under a vacuum, which is unsustainable and depends on the extensive use of energy and dangerous solvents. In addition, using food crops like maize, potato, and cassava as raw materials for specific product fermentation will lead to the dilemma of competing with humans for food. The development of metabolic engineering can redesign microorganisms and engineer their metabolic ability to produce specific product production from renewable feedstocks. In this review, we outline the existing biosynthesis routes of pyruvate and derivatives and describe the metabolic engineering strategies in microorganisms to enhance productivity. We also propose a system-wide metabolic engineering strategy that combines systems biology and synthetic biology with molecular modification as a novel method for improving the production level, yield, and productivity of these compounds in the future. Detailed pyruvate and derived compounds production and engineering strategies are described in Table 1 ."
} | 2,327 |
33833414 | PMC8443676 | pmc | 5,258 | {
"abstract": "Plasmids are autonomous genetic elements that can be exchanged between microorganisms via horizontal gene transfer (HGT). Despite the central role they play in antibiotic resistance and modern biotechnology, our understanding of plasmids’ natural ecology is limited. Recent experiments have shown that plasmids can spread even when they are a burden to the cell, suggesting that natural plasmids may exist as parasites. Here, we use mathematical modeling to explore the ecology of such parasitic plasmids. We first develop models of single plasmids and find that a plasmid’s population dynamics and optimal infection strategy are strongly determined by the plasmid’s HGT mechanism. We then analyze models of co-infecting plasmids and show that parasitic plasmids are prone to a “tragedy of the commons” in which runaway plasmid invasion severely reduces host fitness. We propose that this tragedy of the commons is averted by selection between competing populations and demonstrate this effect in a metapopulation model. We derive predicted distributions of unique plasmid types in genomes—comparison to the distribution of plasmids in a collection of 17,725 genomes supports a model of parasitic plasmids with positive plasmid–plasmid interactions that ameliorate plasmid fitness costs or promote the invasion of new plasmids.",
"introduction": "Introduction Plasmids are autonomous genetic elements that utilize the replication machinery of a host to replicate. They come in a variety of forms, ranging from plasmids of only a few kilobases that contain no discernible genes [ 1 ], to large, chromosome-like plasmids that encode genes essential to host survival [ 2 ]. Plasmids can transfer between hosts by a variety of mechanisms, including conjugation, by which cells directly exchange plasmids [ 3 ], and transformation, in which free plasmids infect cells [ 4 ]. Plasmids are important vehicles of horizontal gene transfer (HGT) in bacteria and archaea, being one of the mechanisms that allow these clonally reproducing organisms to share genetic information [ 5 ]. As such, plasmids play a key role in the dissemination of antibiotic resistance genes among pathogens [ 6 , 7 ]. For example, one survey of Salmonella enterica genomes found that over 80% of the identified antibiotic resistance genes were contained within plasmids [ 8 ]. In addition to carrying and transmitting these genes, plasmids can influence gene persistence and evolution in subtle ways. Plasmids physically link different genes in a manner that promotes co-selection, potentially increasing the persistence of these genes [ 9 ]. Plasmids with multiple copies have been shown to accelerate the evolution of novel antibiotic resistance variants, allowing populations to survive environmental changes that would drive populations with only chromosomally-encoded resistance genes to extinction [ 10 ]. The impact of a plasmid on its host’s ability to respond to environmental factors is an important aspect of plasmid ecology, but plasmids are not simply genetic accessories. Plasmids have a complex ecology that is also influenced by different routes of plasmid transfer and by a plethora of plasmid–plasmid interactions [ 11 , 12 ]. Despite the significant role plasmids play in evolution and public health, many aspects of their natural ecology are not well understood. Most notably, it has not yet been definitively established how plasmids are able to persist over evolutionary timescales and not simply be integrated into the chromosome to minimize replication costs. In addition to this existential question, the factors governing the distribution of plasmids in nature have yet to be elucidated. Within a single species, there can be a wide variation of plasmid numbers and it is not understood why some strains contain large numbers of plasmids while others contain none. There are two major mechanisms that could allow plasmids to be maintained: (1) Positive selection—plasmids are beneficial such that plasmid-containing cells out-compete plasmid-free cells. Scenarios based on positive selection also often include additional mechanisms to explain why beneficial plasmids are not eventually integrated into the chromosome. (2) Infectious transfer—costly plasmids could be maintained if they spread fast enough to compensate for reduced host growth. We refer to a plasmid that requires infectious transfer to persist as an “infectious plasmid”. Hypotheses invoking positive selection have historically been dominant in the literature with many works, primarily relying on early measurements of conjugation rates [ 13 , 14 ], asserting that natural HGT rates are too slow for infectious spread of plasmids [ 12 , 15 – 17 ]. There is also some recent experimental evidence for positive selection being required for plasmid persistence in laboratory strains [ 18 ]. However, there is now a growing body of experimental evidence that HGT can indeed be fast enough to maintain costly plasmids. Early work by Lundquist demonstrated costly plasmids successfully invading plasmid-free populations [ 19 ], and recent work has shown plasmids spreading in the absence of positive selection in laboratory strains and natural hosts [ 20 – 22 ]. In many cases it is still difficult to determine whether a given natural plasmid is truly an infectious plasmid, owing to the fact that the functions of many plasmid-borne genes have yet to be understood. However, the aforementioned experimental results demonstrate that parasitism is a viable plasmid lifestyle. What are the ramifications of these findings for plasmid ecology? Mathematical models have played an important role in understanding the results of plasmid experiments. Analysis of early models of conjugative plasmids yielded conditions for persistence that are widely utilized in interpreting experimental results [ 23 ]. Since this early work, mathematical models have been extended to study plasmid ecosystems beyond those that can be created in the laboratory. These ecological models of plasmids have primarily focused on the case of beneficial plasmids, in particular those carrying antibiotic resistance genes and genes enabling cooperative behaviors [ 16 , 24 – 26 ]. There has been comparatively little theoretical work on parasitic infectious plasmids, with only a handful of papers exploring this scenario. These papers have generally focused on conjugative plasmids in single well-mixed environments [ 20 , 27 , 28 ], with exploration of more complex scenarios limited to generalized models of mobile genetic elements [ 29 , 30 ]. Motivated by experimental evidence that natural plasmids can exist as infectious parasites, we ask: what are the implications for plasmid ecology? We begin with single plasmid, single species models and find that different modes of HGT can lead to qualitatively different infection strategies and population dynamics. We then model plasmid co-infection and find a plasmid “tragedy of the commons” in which runaway invasions by plasmids reduce the fitness of the host to arbitrarily low levels. We propose that the resolution of this plasmid runaway lies on a higher level of selection: in metapopulation models, plasmid invasions are limited by HGT barriers between populations. From a Wright–Fisher type model, we derive the predicted distribution of the number of unique plasmid types per genome and show that the form of the distribution varies depending on plasmid epistasis (i.e. plasmid–plasmid interactions that influence plasmid fitness costs or the invasion rate of new plasmids). We find that the observed distribution in a collection of 17,725 genomes is consistent with a model of parasitic plasmids with positive epistasis.",
"discussion": "Discussion Plasmids play a significant role in bacterial evolution and the spread of antibiotic resistance, but their ecology is not well understood. Inspired by experiments demonstrating that plasmids can exist parasitically, we used simple mathematical models to explore the implications of these findings for the distribution of plasmids in nature. By analyzing models across multiple population scales, we developed a mechanistic framework to provide insight into the forces shaping the natural ecology of plasmids. Our single-plasmid models revealed that plasmid ecology is strongly dependent on the mechanism of HGT. Our analysis predicts that a conjugative plasmid maximizes its ability to invade populations by having moderate copy number and consuming only a modest fraction of the host’s budget, in-line with previous explorations of the trade-off between segregation loss and host burden [ 34 ]. This appears to reflect the reality of conjugative plasmids as they typically have low copy numbers [ 5 ] and a moderate fitness cost \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\Delta}$$\\end{document} Δ [ 15 , 35 ]. While we specifically considered the case of plasmids that rely on random segregation, this conclusion should hold for other segregation mechanisms as well. If a plasmid uses an active segregation mechanism, its optimal copy number will likely be lower than a plasmid that relies on random segregation. Interestingly, our model of transformative plasmids leads to a very different outcome. Unlike a conjugative plasmid, a plasmid relying on transformation can enhance its transmission by increasing its copy number. This means that a transformative plasmid’s optimal infection strategy is to behave in a phage-like manner and produce as many copies as possible. Thus far, there is no direct experimental evidence for the existence of parasitic transformative plasmids, though there are natural plasmids with high copy numbers in-line with those expected from our model ( \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$n_{\\mathrm{p}} \\,\\sim\\, 10^2$$\\end{document} n p ~ 1 0 2 ) [ 36 ]. Presently, the possibility of transformative parasitic plasmids cannot be ruled out as there has been relatively little experimental work studying the ecology of plasmids spread by natural transformation. While we explicitly modeled conjugative and transformative plasmids, our framework is useful for understanding the ecological and evolutionary implications of other transfer mechanisms. We predict that HGT mechanisms that are enhanced by copy number promote phage-like behavior, while those not enhanced by copy number will lead to more restrained parasites. For example, it was recently shown that plasmids can use specialized vesicles to spread between cells [ 37 ]. If higher copy number allows for the production of more plasmid vesicles, the plasmid’s optimal behavior will likely be phage-like, similar to a transformative plasmid. Interestingly, plasmids can also use phage to transfer between cells via a mechanism known as transduction [ 38 ]. Since this mechanism involves extracellular vectors, our results indicate that the large burst sizes phage use to propagate are also optimal for plasmid spread. Our single-plasmid results can also be useful in understanding the behavior of non-plasmid parasitic genetic elements. For example, viroids are pathogenic circular RNA elements encoding no known protein. They are plant pathogens transmitted by leaf-to-leaf contact or contaminated tools [ 39 ], a mechanism that likely benefits from an increased number of copies. As expected from our framework, viroids place a severe, sometimes lethal, burden on their hosts [ 39 ]. Our analyses of multiple plasmids in a single-population highlight the broader ecological pressures faced by parasitic plasmids. Without additional limiting mechanisms, plasmids in our model are prone to a “tragedy of the commons” within a single population. Due to the relative nature of fitness, existing plasmids do not prevent the spread of new plasmids, leading to runaway invasions. We find that the distribution of plasmid types within a population depends on the strength of the transfer mechanism and the cost of the plasmids, with the most extreme scenario being one in which all cells contain all plasmids. While we limited our multiplasmid analyses to plasmids from different incompatibility groups, competition of plasmids in the same incompatibility group can lead to additional forms of selection pressure. If two incompatible plasmids share a copy-control mechanism, it may be beneficial for a plasmid to increase its copy number to out-compete the other plasmid [ 34 ]. Even in this case, there will be substantial differences between plasmids with different transfer mechanisms. For a conjugative plasmid, this intra-host pressure will conflict with inter-host pressure to maintain a moderate copy number, while for a transformative plasmid the intra-host pressure will align with the inter-host pressure to increase copy number. This additional pressure towards higher copy numbers will likely worsen the tragedy of the commons. Indeed, a tragedy of the commons between incompatible plasmids has been observed in experiments [ 40 ]. We suggest that the tragedy of the commons between parasitic plasmids is counteracted by competition between populations isolated by HGT barriers. Correspondingly, within a Wright–Fisher model, we are able to provide a dynamic explanation for the distribution of plasmids in nature. We find that real distributions are consistent with strong positive epistasis between plasmids, a phenomenon that has been observed in experiments [ 12 ]. Interestingly, while our model is able to fit the plasmid distributions within many genera, some distributions contained sharp variations that our model cannot account for. This suggests the presence of additional factors governing plasmid acquisition and loss, such as environment-specific parameters. Our model of a balance between parasite invasion and selection is conceptually similar to those developed for transposons [ 41 ], and there are generalized models of mobile genetic elements that rely on a similar mechanism [ 30 ]. However, a major difference is that these models are concerned with the distribution of copy numbers, while we model the distribution of plasmid types. In addition to HGT barriers, we explored CRISPR-Cas as a possible mechanism limiting plasmid transfer. Somewhat surprisingly, we found no substantial difference in the distribution of unique plasmid types for cells harboring cas genes and those not harboring cas genes. This is counterintuitive, as it has been shown experimentally that a CRISPR-Cas system can prevent plasmid invasion [ 32 ]. However, our findings are consistent with a recent bioinformatics study finding no negative relationship between the rate of HGT and CRISPR-Cas activity [ 42 ]. A potential explanation for these results is that the presence or absence of CRISPR-Cas systems may change on a rapid timescale, such that genomes are intermittently protected by CRISPR-Cas, but not all genomes have them at a given time. This discrepancy may also be partially explained by limitations of our bioinformatic analyses. We focused on CRISPR-Cas systems as they are well-studied and widespread, but other, possibly undiscovered, defense systems may also play a role in limiting plasmid invasion. That said, a previous study found results similar to ours for RM systems, another major bacterial defense system [ 33 ]. We took a primarily ecological view in this work, but understanding plasmid evolution is equally important. Parasitic plasmids are now known to exist, but what drives their evolution? Our multiplasmid models raise interesting questions about the evolution of plasmid interactions. For example, our analysis of natural plasmid distributions suggests that plasmids generally mitigate each other’s fitness costs, but why would parasites competing for a host cooperate? We hope that our modeling can serve as a foundation for further theory and experiments characterizing plasmid ecology and evolution."
} | 4,077 |
30076360 | PMC6076286 | pmc | 5,259 | {
"abstract": "Macro-fungi play important roles in the soil elemental cycle in terrestrial ecosystems. Many researchers have focused on the interactions between mycorrhizal fungi and host plants, whilst comparatively few studies aim to characterise the relationships between macro-fungi and bacteria in situ . In this study, we detected endophytic bacteria within fruit bodies of ectomycorrhizal and saprophytic fungi (SAF) using high-throughput sequencing technology, as well as bacterial diversity in the corresponding hyphosphere soils below the fruit bodies. Bacteria such as Helicobacter , Escherichia-Shigella , and Bacillus were found to dominate within fruit bodies, indicating that they were crucial in the development of macro-fungi. The bacterial richness in the hyphosphere soils of ectomycorrhizal fungi (EcMF) was higher than that of SAF and significant difference in the composition of bacterial communities was observed. There were more Verrucomicrobia and Bacteroides in the hyphosphere soils of EcMF, and comparatively more Actinobacteria and Chloroflexi in the hyphosphere of SAF. The results indicated that the two types of macro-fungi can enrich, and shape the bacteria compatible with their respective ecological functions. This study will be beneficial to the further understanding of interactions between macro-fungi and relevant bacteria.",
"introduction": "Introduction Macro-fungi, also known as mushrooms, are a type of chlorophyll-free heterotrophic organism 1 . Ectomycorrhizal fungi (EcMF) and saprophytic fungi (SAF) represent two major fungal guilds in terrestrial ecosystems and both play crucial roles in material conversion and elemental cycles 2 – 4 . EcMF are able to establish mutualistic interactions with host plants and form ectomycorrhizae in the natural environment 5 . They provide mineral elements for host plants by weathering minerals or decomposing organic matter 6 , 7 , or/and take-up mineral nutrients directly from soils to obtain valuable photosynthetic carbon in return 8 , 9 . The photosynthetic carbon is transferred to extramatrical mycelia and becomes a nutrient supply for underground heterotrophic organisms 10 . SAF are mainly responsible for decomposing litter and complex organic carbon in soils for nutrients 11 , 12 . Therefore, there are noteworthy differences in the ecological functions of the two types of macro-fungi in the terrestrial ecosystem. The evolution of fungi in terrestrial ecosystems has exerted a strong impact on bacterial niche development 13 . Bacteria had developed competitive strategies for plant-derived substrates in their long-term evolution, and the utilisation of fungal-derived substrates has also led to different ecological strategies ranging from mutualist, endosymbiotic, and mycophagous bacteria 14 . In boreal forests, extramatrical mycelia of EcMF are important parts of underground biomass 15 . Compared to the root tips of plants, EcMF have a complex hyphal network and larger surface area which may provide a sufficient niche for relevant varied bacteria. Bacteria in ectomycorrhizosphere are not only influenced by the local soil environment, but strongly selected by particular fungal symbionts, namely, specific EcMF harboured distinct bacteria and ascomycete communities 16 . Tornberg and Olsson 17 proposed that wood-decomposing fungi could influence bacterial community structure by using phospholipid fatty acid profiles to characterise bacterial communities. Furthermore, the bacteria may also be responsible for the changes in the structure of fungal communities demonstrated by the results from the study by Höppener-Ogawa 18 , who inoculated the genus Collimonas to soils and examined fungal diversity in soils and rhizosphere soils of arbuscular mycorrhizal fungi by PCR-DGGE. Therefore, fungal hyphae, to some extent, may affect the bacterial compositions of the underlying soils and a stable community structure in hyphosphere soils by mutual selection and adaptation processes. Endophytic bacteria in fruit bodies have attracted more attention to the study of the microbiome of bacteria associated with macro-fungi. Pent and Bahram 19 investigated and sequenced the endophytic bacteria from the fruit bodies of Agaricomycetes and found that both the soils, and the fungal species, contributed to the bacterial communities in fruit bodies. They hypothesised that the bacteria in fungal fruit bodies may be selected based on their symbiotic functions or environmental requirements. Benucci and Bonito 20 also drew a similar conclusion, namely that fungal species, and their regional distribution may contribute to bacterial diversity associated with fruit bodies of Pezizales. Therefore, the bacteria living in the fruit bodies of macro-fungi may play an important role in the development of the fruit bodies. Based on the aforementioned analysis, we proposed that the hyphae of EcMF and SAF are capable of maintaining, or regulating, some special bacterial populations in their fruit bodies and hyphosphere soils. Therefore, an experiment was conducted to reveal the ecological relationship between macro-fungi and bacteria in situ , which is conducive to understanding of their ecological roles.",
"discussion": "Discussion The bacteria inhabiting the macro-fungi are correlated with their hosts probably due to favourable growth environment and the selection of the fungi 22 . Rangel-Castro et al . 23 analysed the growth media of Cantharellus cibarius by 13 C-NMR and found exudation of trehalose and mannitol which may explain how millions of bacteria can reproduce inside long-lasting fruit bodies of chanterelles without damaging the hyphae thereof. The dominant bacteria may occupy the niche quickly and play a role in inhibiting the entry of other bacteria or pathogens, which has been confirmed in isolation experiments of endophytic bacteria in fruit bodies 24 . The common endophytic bacteria of the two types of macro-fungi comprised the main bacteria groups, which was similar to the results found in a study by Dahm et al . 25 , who observed that the majority of bacteria derived from the fruiting bodies of EcMF were Gram-positive cocci. The similar physical environment and nutrients may account for the high abundance of common bacteria 23 . Furthermore, the high relative abundance of common bacteria may also be important for the growth of macro-fungi 22 . Tsukamoto et al . 26 found that bacteria, such as Acinetobacter sp., Bacillus pumilus , and Sphingobacterium multivorum , isolated from wild Agaricales, are capable of detoxifying tolaasin produced by Pseudomonas tolaasiithe . Associated bacteria inhabit spores, the hyphal surface, and internal structures of arbuscular mycorrhizal fungi can promote growth of hyphae 24 , and accelerate the sporulation of arbuscular mycorrhizal fungi 27 . Similarily, bacteria associated with EcMF could play an important role in sporocarp formation 28 and in promotion of mycorrhizal symbiosis 29 – 32 . Furthermore, some endophytic bacteria within plants exhibit a vertical transmission phenomenon in which endophytic bacteria are passed from parent to offspring through seeds conducive to the survival of the offspring 33 . In particular, fruit bodies of different fungal taxa create various specific conditions that filter certain bacteria from the surrounding bulk soil 34 , 35 . The endophytic bacteria within fruit bodies may be important to the growth of fruit bodies and the development of their spores. Our results showed that the bacterial richness in EMFs was significantly higher than that in SAFs ( t = 2.48, p = 0.03, Fig. 3a ), which may be related to the fungus-derived carbon sources. Ectomycorrhizal symbiont can serve as a two-way channel to achieve transfer of the nutrition between plants and EcMF. EcMF provide a large number of mineral elements for plants and acquired valuable plant photosynthetic products in return 36 , 37 . The carbohydrates are an important carbon source of certain bacteria inhabiting the mycorrhizosphere 38 . So the hyphosphere soils of EcMF were able to support more types of bacteria. We analysed the bacteria with significant differences of the hyphosphere soils between two ecological types of macro-fungi based on the phylum level of classification (Fig. 7 ). The results showed that the growth of different fungal hyphae had a directional selection effect on the surrounding bacteria and tended to shape the microbial community to serve their respective ecological functions. It is interesting to note that Actinobacteria were dominant in SAFs, which may be associated with their producing rich antibiotics and inhibiting growth of pathogenic bacteria 39 , which were beneficial to the growth of hyphae of SAF and contribute to the formation of their fruit bodies. In contrast, EcMF were capable of secreting antibacterial substances which inhibit pathogenic microorganism, such as Fusarium oxysporum 40 , 41 . Thus the relative abundance of Actinobacteria in EMFs was markedly lower than that in SAFs. The microbial communities of the hyphosphere soils of EcMF were more conducive to the establishment of cooperative relationships between mycorrhizal fungi and specific plants. The measured pH of the soil samples showed the hyphosphere soils of the EcMF were generally acidic (Table 3 ). The acidic environment was beneficial to the release of insoluble mineral elements (such as K and P) and improved the efficiency with which the plant could use these mineral elements 42 – 44 . EcMF were likely to enrich the bacteria which were capable of producing acidic matter and weathering minerals 36 , 45 , and Taylor et al . 46 found that EcMF secrete organic acids and decrease the pH of the surrounding soil to increase the content of mineral elements in the mycorrhizosphere. This might be a possible explanation to why Acidobacteria ( t = 1.88, p = 0.09) and Bacteroides ( t = 2.22, p = 0.05) were present in greater number in EMFs than that in SAF in this experiment. The EcMF also provided nitrogen to the plants 27 which was consistent with the presence of a considerable portion of the Nitrospirae and Planctomycetes. Nitrospirae bacteria converted ammonium nitrogen into nitrate 28 which was more easily absorbed and utilised by plants. These bacteria were involved in the cycle of nitrogen in the rhizosphere region. There were also some bacterial species with a special biological function in the hyphosphere soils of EcMF, mycorrhiza helper bacteria, which play an irreplaceable role in the formation of mycorrhizae, included Bacillus sp. 29 , Pseudomonas sp. 30 , and Burkholderia sp. 31 . The results of this study also proved that the relative abundance of these bacteria in the hyphosphere soils of EcMF was higher than that in SAF. Figure 7 Differential analyses of bacteria in the hyphosphere soils of ectomycorrhizal fungi (EMFs) and saprophytic fungi (SAFs) at the level of phylum, and the phyla with significant differences between EMFs and SAFs were listed. p -values are derived from use of the T- test. * p < 0.05; ** p < 0.01. Table 3 The chemical properties of the hyphosphere soils below different types of macro-fungi. Sample pH TOC TN Cu Al Ca Fe K Mg Mn Ni P Zn mg/g mg/kg APs 4.68 ± 0.15 4.61 ± 1.27 1.80 ± 0.11 0.40 ± 0.21 2.00 ± 0.33 378.17 ± 8.60 67.95 ± 16.55 54.43 ± 1.49 84.06 ± 7.46 15.17 ± 2.83 0.08 ± 0.10 0.41 ± 0.33 0.78 ± 0.55 SPs 6.00 ± 0.03 4.02 ± 2.91 1.53 ± 0.29 0.71 ± 0.41 1.43 ± 0.30 389.36 ± 4.71 50.14 ± 9.39 40.14 ± 7.33 57.28 ± 5.23 4.62 ± 1.20 0.00 ± 0.00 0.00 ± 0.00 0.64 ± 0.48 TFs 5.40 ± 0.07 4.71 ± 0.19 1.66 ± 0.05 0.84 ± 0.40 1.41 ± 0.41 367.31 ± 12.33 86.48 ± 23.19 88.39 ± 6.22 116.12 ± 3.26 7.04 ± 1.73 0.18 ± 0.17 0.00 ± 0.00 1.08 ± 0.77 AFs 4.61 ± 0.38 17.71 ± 7.60 2.99 ± 0.50 1.67 ± 0.92 11.28 ± 2.89 310.84 ± 46.64 122.02 ± 8.88 52.64 ± 28.27 16.95 ± 9.57 15.60 ± 3.29 0.00 ± 0.00 1.49 ± 0.99 6.85 ± 5.35 CMs 7.50 ± 0.14 10.62 ± 0.45 2.20 ± 0.01 1.53 ± 0.05 0.30 ± 0.04 389.72 ± 5.41 30.37 ± 0.14 104.81 ± 1.40 39.11 ± 0.52 5.32 ± 0.04 0.00 ± 0.00 0.55 ± 0.29 1.75 ± 0.05 TAs 7.69 ± 0.05 0.00 ± 0.00 1.14 ± 0.04 0.47 ± 0.02 0.38 ± 0.03 333.28 ± 3.37 25.15 ± 0.21 89.34 ± 1.61 159.12 ± 3.08 2.75 ± 0.03 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 TOC, total organic carbon; TN, total nitrogen; Cu, exchangeable copper; Al, exchangeable aluminum; Ca, exchangeable calcium; Fe, exchangeable iron; K, exchangeable potassium; Mg, exchangeable magnesium; Mn, exchangeable manganese; P, exchangeable phosphorus; Zn, exchangeable zinc. Values are mean ± standard deviation."
} | 3,138 |
35814682 | PMC9263704 | pmc | 5,261 | {
"abstract": "The complex gut microbiome is a malleable microbial community that can undergo remodeling in response to many factors, including the gut environment and microbial properties. Enterococcus has emerged as one of the predominant gut commensal bacterial and plays a fundamental role in the host physiology and health of the major economic agricultural insect, Bombyx mori. Although extensive research on gut structure and microbiome diversity has been carried out, how these microbial consortia are established in multifarious niches within the gut has not been well characterized to date. Here, an Enterococcus species that was stably associated with its host, the model organism B. mori , was identified in the larval gut. GFP–tagged E. faecalis LX10 was constructed as a model bacterium to track the colonization mechanism in the intestine of B. mori . The results revealed that the minimum and optimum colonization results were obtained by feeding at doses of 10 5 CFU/silkworm and 10 7 CFU/silkworm, respectively, as confirmed by bioassays and fluorescence-activated cell sorting analyses (FACS). Furthermore, a comprehensive genome-wide exploration of signal sequences provided insight into the relevant colonization properties of E. faecalis LX10. E. faecalis LX10 grew well under alkaline conditions and stably reduced the intestinal pH through lactic acid production. Additionally, the genomic features responsible for lactic acid fermentation were characterized. We further expressed and purified E. faecalis bacteriocin and found that it was particularly effective against other gut bacteria, including Enterococcus casselifavus , Enterococcus mundtii , Serratia marcescens , Bacillus amyloliquefaciens, and Escherichia coli. In addition, the successful colonization of E. faecalis LX10 led to drastically increased expression of all adhesion genes ( znuA , lepB , hssA , adhE , EbpA , and Lap ), defense genes ( cspp, tagF , and esp ), regulation gene ( BfmRS ), secretion gene ( prkC ) and immune evasion genes ( patA and patB ), while the expression of iron acquisition genes ( ddpD and metN ) was largely unchanged or decreased. This work establishes an unprecedented conceptual model for understanding B. mori –gut microbiota interactions in an ecological context. Moreover, these results shed light on the molecular mechanisms of gut microbiota proliferation and colonization in the intestinal tract of this insect.",
"conclusion": "Conclusion In conclusion, we identified a stable interaction between B. mori and E. faecalis , which will be useful for addressing important questions in the gut microbiota field that will lead to agricultural, economic, and environmental benefits. Moreover, the release of insects with stable symbionts in interventions may be effective against both pests (e.g., by improving the survival of sterile males) and pathogen vectors (e.g., by enhancing resistance to pathogens). Understanding what regulates gut colonization may be critical for the success of these approaches. Therefore, this new framework and concept for studying specific gut bacteria will contribute to the growing field of research on silkworm-microbe interactions.",
"introduction": "Introduction The insect gut is colonized by a complex bacterial community that governs a wide range of functions contributing to the host’s physiology, pathogen defense, development, and immune protection ( Engel and Moran, 2013 ; Xiao et al., 2017 ). Thus, the gut microbiota may be recognized as a virtual “bacterial organ” that is integrated into the host’s biological system and fundamental to its health ( Aksoy, 2018 ; Schretter, 2020 ). For instance, a comparison between aposymbiotic and symbiotic insects showed that the Burkholderia symbiont dramatically increases the fecundity, growth rate, and body size of stinkbugs by providing essential metabolites, and the insect host can also develop resistance against the insecticide fenitrothion ( Kikuchi et al., 2007 ; Kikuchi and Fukatsu, 2014 ). The phytophagous leafminer Phyllonorycter blancardella (Lepidoptera) co-opts the bacterial endosymbiont Wolbachia to improve its nutritional and physiological environment ( Kaiser et al., 2010 ). Furthermore, associations with specific microorganisms may improve environmental fitness or provide new opportunities for exploring new niches ( Robinson et al., 2018 ). Although myriad microorganisms inhabit the guts of insects, many gut community members are transient, and it is sometimes difficult to create a resident microbiota due to various intrinsic factors (developmental stage, sex, genetics, gut pH, digestive enzymes, etc.) ( Engel and Moran, 2013 ; Hammer et al., 2017 ). The silkworm, Bombyx mori , is a powerful model organism for studying the bacterial colonization of the invertebrate intestine and for deciphering the interactions between the host and its gut microbiota ( Chen et al., 2018 , 2020 ). The midguts of silkworm larvae exhibit extremely high alkalinity, with pH levels of 10–11, and their digestive enzymes are adapted to the alkaline environment ( Liang et al., 2018 ). Recent extensive surveys have revealed that these adverse conditions may support the growth of alkaline-resistant and facultative anaerobic microorganisms, such as Firmicutes, Planctomycetes, and Clostridium ( Bignell et al., 2011 ; Yeruva et al., 2020 ). For example, Enterococcus (Firmicutes), which plays a crucial role in metabolic adaptability against pathogenic or plant toxins and anti-herbivore defense, was found to be one of the predominant gut microorganism of lepidopteran insects, including B. mori , Helicoverpa zea , and Porthetria dispar ( Paniagua Voirol et al., 2018 ; Zhang et al., 2022 ). Some other insects harbor similar bacterial lineages in their alkaline guts ( Egert et al., 2003 ; Broderick et al., 2004 ). Several physiological and biochemical characteristics of the gut environment influence the colonization of such symbionts, including the constant expulsion of intestinal contents via peristalsis, pH levels, reactive oxygen species, nutrient availability, digestive enzymes, and possibly antimicrobial agents ( Siegel and Weiser, 2015 ). Thus, it appears likely that bacteria stably inhabiting the gut would have developed sophisticated mechanisms to resist these challenges. The green fluorescent protein (GFP) of the jellyfish Aequorea victoria , first described in the 1970s, is a bright, stable molecular marker used in live-cell imaging to facilitate bacterial localization, isolation, and tracking in biological studies of several host species ( Rizzo et al., 2009 ; Viswanathan et al., 2015 ). Genetically modified bacteria labeled with GFP or other fluorescent proteins have provided a unique and powerful tool for understanding the spatiotemporal dynamics and ecological interactions of the gut microbiota ( Wang S. et al., 2017 ). Recently, similar research has been performed in Pseudomonas -zebrafish, Photorhabdus -nematode, Burkholderia -bean bug, and other model symbiotic systems ( Rawls et al., 2007 ; Ciche et al., 2008 ; Kikuchi and Fukatsu, 2014 ). For example, the Pseudomonas aeruginosa : GFP transcriptional reporter strain is detectable in the Caenorhabditis elegans head and intestine regions using fluorescence microscopy ( Sellegounder et al., 2019 ). Despite the recognized importance of gut-associated bacteria to B. mori , how and where its gut microbiota achieves colonization and the genetic and molecular bases of colonization are still open questions. In the current study, we constructed a genetically engineered strain of E. faecalis LX10 expressing GFP to visualize how the test organism adapted to the gut environment of silkworms. E. faecalis LX10 grew well under alkaline conditions and showed efficient lactic acid production. We further analyzed bacteriocin production and bacterial competition based on whole-genome sequencing. In addition, we quantified colonization-related genes following the growth of the bacterium in the gut using quantitative real-time PCR (RT–qPCR). The present study enhances our understanding of gut colonization by an indigenous bacterium and may promote the application of probiotic targeting regulation in agricultural and economic insects or for pest control of lepidopterans.",
"discussion": "Discussion The successful colonization of the insect gut by symbiotic bacteria is an essential step in controlling beneficial microbe systems and the health status of the host ( Paniagua Voirol et al., 2018 ; Sauers and Sadd, 2019 ). In this paper, we report that the level of E. faecalis is as high as 10 8 copies in a normal 5th-instar larva gut, as confirmed by FISH analysis. In agreement with our results, previous studies have also found that Enterococcus is the most dominant bacterial genus in the gut microflora of silkworms ( Xiang et al., 2007 ; Sun et al., 2016 ). Therefore, the dominant species, E. faecalis , is particularly likely to play a major role in facilitating the survival of its host in a changing environment during development. Our results showed that the expression of GFP does not affect the physiology and fitness of E. faecalis , as strong fluorescence of recombinant GFP– E. faecalis was observed upon CLSM and FACS analyses. Similar results have been observed for Lactobacillus reuteri ( Lizier et al., 2010 ) and E. mundtii ( Teh et al., 2016 ). A recent study also showed that GFP expression did not negatively affect the bacterial function or survival of E. coli and S. marcescens ( Wang S. et al., 2017 ; Chiapponi et al., 2020 ). In this study, GFP-tagged E. faecalis was introduced into the gut of B. mori , and it could stably persist and proliferate. Our recent study suggested that the minimum and optimum doses for colonization are 10 5 CFU/mL to 10 7 CFU/mL. Similarly, the minimum threshold for successful colonization for Burkholderia was shown to be 1.9 × 10 6 symbionts in the stinkbug Megacopta punctatissima ( Hosokawa et al., 2007 ; Kikuchi and Yumoto, 2013 ). In Spodoptera littoralis , the midgut CFU count was observed to range from 1.0 × 10 5 during the fourth instar to 2.7 × 10 7 in the fifth instar after feeding on fluorescent E. mundtii ( Teh et al., 2016 ). This suggests that different host species may influence bacterial colonization. Haoyue × Jingsong strain was used in this study, which is the most widely used and popularized multifilament bivoltine B. mori strain in China. The stable colonization of the gut by E. faecalis requires introduction within a certain threshold range. This is probably because the food intake rates of silkworms affect the speed of microbe passage through the gut and, thus, the colonization efficiency via excretion ( Smith et al., 2015 ; Zhang et al., 2022 ). In addition, we found that attachment to the gut appears to be required for E. faecalis to successfully colonize the PM. The PM of insects is composed of chitinous and glycoprotein structures that form a protective barrier against intestinal bacterial infection, abrasive food particles, digestive enzymes, and oral pathogens ( Nakashima et al., 2018 ). Additionally, the PM compartmentalizes digestive processes, allowing efficient nutrient absorption and the reutilization of hydrolytic enzymes ( Hegedus et al., 2009 ; Kuraishi et al., 2011 ; Rose et al., 2020 ). GFP bacteria accumulated around the PM, suggesting that there may be specific, stable cell attachment sites. Interestingly, GFP– E. faecalis may switch from diplococcus to chain form under treatment with intestinal juice. Previous work sowed that certain common intestinal molecules, bile acids, and lysozyme also increase chaining and biofilm formation in E. faecalis , thereby increasing the colonized surface area ( Varahan et al., 2013 ; McKenney et al., 2019 ). In brief, the increased surface area of longer chains may advantageously increase adherence to the host, as bacteria must prevent themselves from being flushed off of system surfaces to achieve successful colonization ( Weiser, 2013 ). In addition, E. faecalis LX10 actively secretes the antimicrobial peptide bacteriocin, which may enhance its competitive fitness by inhibiting other competing gut bacteria. Bacteriocin production is a powerful means of shaping gut communities, and the interactions and transmission between a host and its gut microbiota determine colonization success ( Stephens et al., 2015 ). Many factors, such as the gut environment (pH and osmotic pressure) ( Kikuchi and Yumoto, 2013 ), host-species specificity ( La Rivière et al., 2015 ), antimicrobial agents, and host or symbiont genotypes ( Wang Q. et al., 2017 ), may determine colonization success. We speculate that the high competitiveness of E. faecalis in the gut may also be attributed to its ability to produce bacteriocins strengthening the competitive ability of Enterococcus against other bacteria ( Cebrian et al., 2012 ). It has been reported that the pathogen Helicobacter pylori can be eradicated by autolysins secreted from Lactobacillus acidophilus and that E. coli O157:H7 can be inhibited by Saccharomyces cerevisiae in ruminal fluid ( Lorca et al., 2001 ; Bach et al., 2003 ). In addition, the gut bacterium E. mundtii of Spodoptera littoralis can secrete stable class IIa bacteriocin, which facilitates the normal development of the gut microbiota over harmful gut invading bacteria ( Shao et al., 2017 ). Bacteriocin exerts its activity against microbes by inhibiting the formation of cell walls or causing holes to form in the cell membrane, leading to the release of cytoplasm and the death of target bacteria ( Scholl, 2017 ; Kranjec et al., 2020 ). Bacteriocin protects the bacterium against its own bacteriocin activity through the action of immune-related proteins, such as ABC transporter, LanI, and LanFEG proteins, which increase the colonization of probiotic bacteria vis cell–cell interactions in the digestive tract ( McAuliffe et al., 2001 ). E. faecalis LX10 can grow well under alkaline conditions and can decrease the pH of the gut by producing high levels of lactic acid. Many Enterococcus species are highly competitive due to their tolerance of a wide range of temperatures and pH levels ( Abdel-Rahman et al., 2015 ; Kridsada et al., 2022 ). E. faecalis LX10 produces significantly higher levels of lactic acid (18.74–28.79 g/L) at different pH levels relative to species reported in other studies. For example, 9 Enterococcus spp. were selected from various sources, and their lactic acid production at 30°C and pH 10 ranged from 11.3 to 18.3 g/L ( Yokaryo and Tokiwa, 2014 ). One reason that bacteria produce different amounts of acid may be their different isolation sources. Lactic acid may break down membrane-bound enzymes and lead to their metabolic assimilation through the lactic acid fermentation pathway to improve food digestibility ( Kridsada et al., 2022 ). We speculate that lactic acid plays an important role in modulating the gut environment, which is conducive to maintaining the dynamic balance of the gut microbiota under alkaline conditions ( Yuksekdag et al., 2021 ). Furthermore, genomic analysis revealed that the sugar uptake gene responsible for lactate production was dispersed across the chromosome and plasmid of E. faecalis LX10, reflecting its metabolic flexibility in efficient lactic acid production. For instance, the pentose phosphate pathway (PP pathway) and the phosphoketolase pathway (PK pathway) were previously reported to be the two main pathways for lactic acid fermentation ( Okano et al., 2009 ; Shinkawa et al., 2011 ). Key enzymes involved in the PP and PK pathways, including ABC transporter permease and transketolase, were detected in E. faecalis LX10. Therefore, we speculated that the activity of related enzymes involved in lactic acid fermentation was quite stable under high-pH conditions, which might be one of the colonization mechanisms underlying specialized adaptation to the silkworm gut niche. The successful colonization of E. faecalis LX10 led to drastically increased expression of most adhesin genes ( znuA , lepB , hssA , adhE , EbpA , and Lap ), defense-related genes ( cspp, tagF and esp ), regulation gene ( BfmRS ), secretion gene ( prkC ) and immune evasion-related genes ( patA and patB ), while the expression of iron acquisition protein-encoding genes ( ddpD and metN ) was largely unchanged or decreased relative to the expression levels in the gut on a genome-wide scale. Enterococcus species have been found to adhere to various extracellular matrix components or host cells using adhesins such as aggregation substances, hemagglutinin, MSCRAMM, and other virulence factors that contribute to the colonization of host tissues ( Nallapareddy and Murray, 2008 ; Somarajan et al., 2015 ; Deng et al., 2019 ; Phillips et al., 2019 ). For example, adhE have been reported to play a role in adherence to host tissue cells for biofilm formation ( Cobo Molinos et al., 2008 ; Crosby et al., 2020 ). In vivo , it has been shown that the adhE mutant shows a significantly attenuated biofilm formation ability in a rat endocarditis model and a murine urinary tract infection model ( Nallapareddy et al., 2006 ; Singh et al., 2007 ). Another study showed that cell surface proteins ( cspp and esp ) contribute to cell colonization by significantly enhancing biofilm formation in the presence of and by attachment to tissue-based surfaces ( Tendolkar et al., 2004 ). The PASTA kinase protein family contains a transmembrane Ser/Thr kinase ( prkC ) that is crucial for cell envelope integrity, adaptation to available nutrient sources, and resistance to antimicrobial agents that target the cell wall of E. faecalis ( Hall et al., 2017 ). The deletion of prkC in E. faecalis results in a profound gastrointestinal tract colonization defect in antibiotic–naïve mice ( Banla et al., 2018 ). Genes involved in core enterococcal and genome plasticity are key drivers of gut colonization."
} | 4,525 |
34917993 | PMC8645841 | pmc | 5,262 | {
"abstract": "Highlights • Fluorescent and non-fluorescent species of Pseudomonas are important for plant growth promotion, phytopathogenic control and plant disease management. • Pseudomonas belong to Pseudomonadaceae family (10 groups on the basis of rRNA-DNA hybridization) classified into 6-subgroups of rRNA gene homology and RFLP. • Pseudomonas species produce antagonistic mechanism such as ISR and compounds like cell wall degradation enzymes, and antibiotics to maintain a mutualistic relationship with the associated plant. • Pseudomonas sp. synthesize auxins having properties similar to phytohormones like IAA, which act as signaling molecules for regulating plant growth.",
"conclusion": "4 Conclusion Pseudomonas species are notable colonizers residing either as a part of local or exotic microflora within the rhizosphere holding an extensive significance in soil health improvement, sustainable agricultural practices, and maintenance of rhizospheric microbial diversity. Various factors such as soil pH, temperature, water holding capacity, nutrient availability, oxygenic conditions, and soil type determine the growth of this essential rhizospheric Pseudomonas ( Lami et al., 2020 ). Various fluorescent and non-fluorescent strains of the genus Pseudomonas have been rearranged by modern molecular classification and are kept in the RNA homology group-I. Applications of the Pseudomonas species are extensively used in numerous industrial sectors such as food, pharmaceutical, ecological. Several species of fluorescent Pseudomonas acts as PGPR possess properties as both provide plant growth regulation and disease resistance. Properties of Pseudomonas in providing plant growth include nitrogen fixation, siderophore production, and phosphate solubilization while in disease resistance includes induced systemic resistance (ISR), phenazine production, and antibiotic production ( Desnoues et al., 2003 ). The increase in siderophore and secondary metabolite production, phosphate solubilization and chemotactic responses between the host plant crop and the Pseudomonas species triggers the colonization process leading to enhanced growth in the host plant. Various chemically mediated feedback mechanisms are also involved in proper growth regulation of plant by Pseudomonas sp. ( Rodríguez et al., 2020 ). The overall vision of this review is based on the importance of Pseudomonas in food security and safe agricultural practices. Prospects supporting the transgenic crop production and technologies based on their generation are yet to be optimized, until now bioavailability of minerals in crops via microbial intervention are giving positive results.",
"introduction": "1 Introduction Soil ecosystem possesses rich diversity than any other ecosystem with complex interactions between living and non-living entities. These living forms habituated in soil are crucial for supporting qualitative plant growth ( Uppal et al., 2017 ). Plants get their nourishment by absorbing nutrients from various sources such as (i) decayed plants and animals composed of organic matter; (ii) soil that occurs as silt, sand, and clay of different particle sizes and water holding capacities. Over utilization of chemical fertilizers and insecticides throughout the years had shown adverse effect on soil quality, fertility and ecology ( Garrido-Sanz et al., 2017 ). Other than this, several competitive agricultural practices like overgrazing and traditional tilling are responsible for the deterioration of cultivable topsoil. So as to combat this situation, various biotechnological methods manage the fusion of conventional organic harvest techniques to chief elements required for promoting rhizobial competency. Plant promotional rhizobial modification methods (like sustainable, active rhizobia and self-regulation) are called biocontrol, bioaugmentation, and biostimulation ( Bhadauria et al., 2010 ). The additional microbial strains present in the rhizobial regions may interact positively or negatively with local microbes to raise active metabolism and colonization by decreasing various microbial infections caused by parasites ( Garcia-Seco et al., 2013 ). Approximately 1 billion species of bacteria exist on Earth. Out of them, 5000 species identified yet ( Sah and Singh, 2016 ). Moreover, surface soil microbes present on the Earth consider around 10 billion microbes per gram. One gram of that soil contains approximately 4000 distinct bacterial genomes. These units estimate an enormous mass diversity significance while showing the progressive competition in the rhizospheric complement ( Sah and Singh, 2016 ). The total percentage value of the microbes present in the soil constituents is <0.4–0.5% w/w. This microflora defines the rhizobial interactions by forming a vibrant assembly of various beneficial microbes interacting: (i) with each other and (ii) with plants, forming positive interactions to promote their growth in order to get protection (Kumar et al., 2016b). Pseudomonadales , on the basis of physiological and biological characteristics (1973), are most abundantly reported among all the other classified orders such as Enterobactera, Xanthomonadales, Gammaproterbacteria, Alteromonadales , and Legionellale ( Chu et al., 2019 ). Several strains of Pseudomonas veronii abundantly found, approx 38%, with a proportion of all bacterial communities present in the rhizosphere ( Qessaoui et al., 2019 ). 1.1 Pseudomonas and its classification The widespread occurrence of Pseudomonas indicates its adaptability through molecular, environmental, and physiological diversity ( Sah and Singh, 2016 ). The classification of Pseudomonas covered as a part of Bergy's Manual (in 1923), based on its phenotypic characteristics, described various media presenting comparable plate counts select different bacterial types reaching several diversity estimates within the same soil. Pseudomonas taxonomy has always been questionable for decades since numerous bacterial taxa were primarily classified into the genus, later incorporated within various other genus of diverse classes of proteobacteria. That was due to advancements in phylogenetic, molecular characterization and distribution procedures for classification of microbes ( Chu et al., 2019 ). Pseudomonadaceae family includes genera like Pseudomonas, Zoogloea, Frateuria , and Xanthomonas . The genus Pseudomonas holds gram-negative, rod-shaped straight or slightly curved cells with polar flagella. The taxonomic situation of Pseudomonas has been changed drastically since its first classification report. On the basis of genomic data, Pseudomonas sensu stricto has been segregated from proteobacteria subclass Beta and reclassified as Proteobacterial subclass Gamma ( Chu et al., 2019 ). Blagodatskaya and Kuzyakov (2008) summarized the dietary properties of >200 strains approximately on >100 various organic composites, along with an extensive modification of components for simplifying Pseudomonas taxonomy. Although the classification of this genera never got mentioned in Bergey's manual because Pseudomonas distribution, solely based on phenotype with% GC content as only molecular information mentioned during species description. The most significant contribution in the characterization of Pseudomonas genetically was stretched in the 1970s. The classification of the various groups of bacteria into 5-subgroups of rRNA and the relative DNA to RNA quantities separated based on their phylogeny describing the remains of the Pseudomonas genera ( Chu et al., 2019 ). In a genotypic strategy known as the ribosomal RNA cataloging method initially, the rRNA partial sequence leads to the pseudomonads classification and its grouping based on phylogeny coinciding with 5-subgroups of rRNA ( Sundar et al., 2021 ). Bacterial phylogenetic classification carried out on the basis of its 16S rRNA sequencing technique directed three subdivisions known as Proteobacteria, α, β, and γ. Currently, there are >10 classified genera in Pseudomonadales, including Stenotrophomonas, Burkholderia, Sphingomonas, Caulobacter, Xanthomonas, and Ralstonia ( Chu et al., 2019 ) ( Fig. 1 ). Fig. 1 An overall classification of Pseudomonas showing >10 classified genera in Pseudomonadales and their further classified species representing different clusters on the basis of multiple enzyme RFLP. Fig. 1 Pseudomonas fluorescent species, subdivided into seven biotypes as A to F, later known as biovars bv., I, II, III, IV, and V. Biovar D and E shifted to P. chlororaphis and P. aureofaciens , clustered as the P. chlororaphis sp. Although this approach introduces flaws like (i) associates significance of some characteristics and (ii) quantitative analysis of characteristics is less. Pseudomonas has simple nutritional requirements due to their properties in the degradation of distinct substrates, aromatic chemicals, halogenated derivatives, and recalcitrant organic residues.( Sah and Singh, 2016 ) studied the growth of various Pseudomonas strains on several different organic substrates, reporting great diversity in genus Pseudomonas . Taxonomic characterization of the Pseudomonas with the advancement in the DNA fingerprinting techniques like RFLP, 16S rDNA, and ARDRA of different groups with monophyla and several before included Pseudomonas species moved to distinct another genus yet, Pseudomonas sensu-stricto persists influential diversity, for example, P. plecoglossicida, P. simiae, P. salomonii, P. palleroniana and P. costantinii ( Verma et al., 2019 a). Pseudomonas brassicacearum and Pseudomonas thivervalensis isolated from rice and garlic, Pseudomonas rhizosphaerae, P. lutea and P. argentinensis isolated from rhizosphere of grass, P. lurida isolated from grass phyllosphere, P. duriflava from desert soil, P. guinea isolated from Antarctic soil, P. psychrotolerans from the veterinary clinic, and P. thermotolerans isolated from clinical samples of animals ( Chu et al., 2019 )."
} | 2,507 |
38997772 | PMC11241880 | pmc | 5,263 | {
"abstract": "Background The rhizosphere microbiome displays structural and functional dynamism driven by plant, microbial, and environmental factors. While such plasticity is a well-evidenced determinant of host health, individual and community-level microbial activity within the rhizosphere remain poorly understood, due in part to the insufficient taxonomic resolution achieved through traditional marker gene amplicon sequencing. This limitation necessitates more advanced approaches (e.g., long-read sequencing) to derive ecological inferences with practical application. To this end, the present study coupled synthetic long-read technology with avidity sequencing to investigate eukaryotic and prokaryotic microbiome dynamics within the soybean ( Glycine max ) rhizosphere under field conditions. Results Synthetic long-read sequencing permitted de novo reconstruction of the entire 18S-ITS1-ITS2 region of the eukaryotic rRNA operon as well as all nine hypervariable regions of the 16S rRNA gene. All full-length, mapped eukaryotic amplicon sequence variants displayed genus-level classification, and 44.77% achieved species-level classification. The resultant eukaryotic microbiome encompassed five kingdoms (19 genera) of protists in addition to fungi – a depth unattainable with conventional short-read methods. In the prokaryotic fraction, every full-length, mapped amplicon sequence variant was resolved at the species level, and 23.13% at the strain level. Thirteen species of Bradyrhizobium were thereby distinguished in the prokaryotic microbiome, with strain-level identification of the two Bradyrhizobium species most reported to nodulate soybean. Moreover, the applied methodology delineated structural and compositional dynamism in response to experimental parameters (i.e., growth stage, cultivar, and biostimulant application), unveiled a saprotroph-rich core microbiome, provided empirical evidence for host selection of mutualistic taxa, and identified key microbial co-occurrence network members likely associated with edaphic and agronomic properties. Conclusions This study is the first to combine synthetic long-read technology and avidity sequencing to profile both eukaryotic and prokaryotic fractions of a plant-associated microbiome. Findings herein provide an unparalleled taxonomic resolution of the soybean rhizosphere microbiota and represent significant biological and technological advancements in crop microbiome research. Supplementary Information The online version contains supplementary material available at 10.1186/s40793-024-00590-5.",
"conclusion": "Conclusions The defined study provides a taxonomically resolved view of the soybean rhizosphere microbiome. Unique in its design, this research was carried out in situ, circumventing the often-observed discrepancy where taxa linked to host fitness in controlled settings fail to replicate symbiont status under field conditions [ 136 ]. This study revealed that both eukaryotic and prokaryotic rhizosphere microbiomes display structural and compositional variation in response to treatment, cultivar, and growth stage, consistent with earlier studies primarily leveraging short-read sequencing. Furthermore, the novelty of the present work was well-accentuated through community membership analysis, where taxonomic resolution permitted taxonomy-based functional annotation, identifying an ecologically relevant, saprotroph-rich core microbiome and demonstrating empirical evidence for host selection of mutualistic taxa and concomitant pathogen restriction. The use of multiple association methods for microbial co-occurrence network construction and the comprehensive assessment of network topology underscored the influence of experimental conditions (biostimulant application and cultivar) on co-occurrence network structure. Moreover, the augmentation of such networks with edaphic and agronomic data, complemented by regularized linear regression and a novel node prioritization criterion, identified microbial genera which may be leveraged for sustainable agriculture, many of which are known for their ecological significance. In conclusion, the application of synthetic long-read technology and an in situ experimental design yielded an unparalleled understanding of the soybean rhizosphere microbiome, signifying a considerable advancement in crop microbiome research with practical implications for microbiome-based agriculture.",
"discussion": "Discussion Soil is the most biodiverse habitat on Earth, harboring an estimated 59% of all living organisms [ 130 ]. Yet, relatively little is known about the inhabitants of this dynamic ecosystem, their interaction, their collective influence on environmental (and thereby human) health, and the interplay of stochastic and deterministic processes shaping such communities [ 131 – 133 ]. Single-molecule-based sequencing stands at the forefront of technologies predicted to clarify these ambiguities inherent in complex microbial systems [ 134 ]. To this end, the current study paired the commercial LoopSeq SLR platform with avidity sequencing to profile both eukaryotic and prokaryotic fractions of the soybean rhizosphere microbiome. An in situ experimental design reflected potential environmental dependencies in microbiome structure, which are likely missed in greenhouse/growth chamber experiments [ 135 , 136 ], yet remain indispensable for practical application of derived inferences [ 137 ]. Multiple growth stages, commercial cultivars (genotypes), and biostimulants were also incorporated given their reported effect on rhizosphere microbiome assembly in soybean [ 13 , 17 , 18 ] and other plant systems [ 138 – 140 ]. The aim of this approach was to generate a well-resolved depiction of soybean rhizosphere microbiome structure and composition, laying groundwork for future applications in microbiome-based agriculture. Perhaps the most significant outcome of this study was the taxonomic resolution achieved with both 16S and 18S-ITS SLRs. Traditional short-read amplicon sequencing rarely classifies ASVs beyond genus level, constraining biological inference [ 29 ]. For instance, Sugiyama et al. [ 141 ] suggested that soybean demonstrates species- and even strain-level selection of Bradyrhizobia based upon stark abundance patterns of ASVs/OTUs with Bradyrhizobium annotation; yet, this notion could not be verified given the limited resolution discerned with pyrosequencing. In the present work, assembling all 9 hypervariable regions of the 16S rRNA gene assigned prokaryotes to at least species level, with nearly one-fourth of mapped, full-length ASVs obtaining strain-level classification. This included the identification of 13 Bradyrhizobium species, some of which demonstrated exclusivity and/or differential abundance (i.e., putative selection) across experimental conditions. Furthermore, a subset of ASVs corresponding to Bradyrhizobium elkanii and Bradyrhizobium japonicum (genus members with the greatest absolute abundance) were resolved at strain level (one and four strains, respectively). This result further coincides with prior studies wherein Bradyrhizobium elkanii and Bradyrhizobium japonicum were the predominant species to nodulate soybean [ 142 ]. In eukaryotic microbial community analysis, the de novo-assembled 18S-ITS1-ITS2 molecules facilitated genus-level taxonomic assignment for all mapped ASVs, and species level assignment for approximately 45%. This strategy effectively captured diverse fungal taxa with agricultural importance, such as soybean-parasitizing genera. Beyond fungi, the analysis identified five kingdoms encompassing 19 genera of protists, including Phytophthora and Pythium [ 143 ]. Assessing soil-dwelling prokaryotic, fungal, and protist communities in tandem bears significance given that general primers do not exist for short-read amplicon profiling of protists [ 19 , 144 ] and the understated yet significant role of protists in the soil microbiome [ 145 ]. Furthermore, the resolution achieved here permitted the automated retrieval of taxonomy-based functional annotations, allowing for highly reproducible biological inference without the need for sequence-based functional prediction. Measures of α and β diversity suggested an overarching temporal effect on microbiome structure and composition, with more subtle trends attributed to treatment, cultivar, and fixed effect interaction. These findings were consistent with Moroenyane et al. [ 146 ], wherein spatial and temporal dynamics were key modulators of α and β diversity in the soybean rhizosphere microbiome. Further, α diversity aligned explicitly with the work of Longley et al. [ 13 ]. In both studies, eukaryotic and prokaryotic richness were decreased at the R2 growth stage and increased by R6 [ 13 ]. Shannon diversity trends matched the no-till soil findings of Longley et al. [ 13 ], showing reduced eukaryotic diversity at R6 compared to R2, with prokaryotes exhibiting the inverse trend. The authors of the compared study noted that their results deviated from prior research, postulating that management could account for the discrepancy [ 13 ]. In this regard, the accordance between the current and prior work may be attributed to the absence of tillage in both experimental designs. Agreeance may also reflect growth stage selection, as bacterial diversity in the soybean rhizosphere has been evidenced to increase between R1 and R5 and then decrease from R5 to R8 [ 147 ]. Moreover, the sole use of full-length contigs for analysis may have impacted diversity estimates, potentially excluding shorter sequences that contribute to overall α and β diversity. Consistent with previous studies, the eukaryotic microbiome composition was predominantly Ascomycota [ 9 , 13 ], while the prokaryotic fraction was largely represented by Proteobacteria [ 9 , 18 ], as evidenced by taxonomic classification of mapped ASVs. The β diversity patterns echoed findings from Moroenyane et al. [ 146 ] in which growth stage (and interactions comprised thereof) best explained compositional dissimilarity, yet also displayed significant heterogeneous dispersion, across both eukaryotic and prokaryotic communities. In the current study, a spatial effect was evident in the eukaryotic microbiome composition, with samples clustering by field location. Given the experimental setup replicated a conventional row crop system, this may reflect an \"edge-of-field\" effect, with plots near turnrows receiving varied moisture or amendment applications. Comparable findings were reported by Longley et al. [ 13 ] wherein management strategy (i.e., conventional, no-till, organic) rendered distinct clustering of eukaryotic rhizosphere communities, with such trends absent for prokaryotic communities [ 13 ]. Notably, heterogeneity arising from field location was controlled statistically in all analyses. Community membership revealed core, unique, and differentially abundant taxa across fixed effect levels. The core microbiome is a crucial element for rhizosphere microbiome assembly and consequent plant growth promotion [ 148 , 149 ]. Thus, it is unsurprising that the core microbiome in this study was enriched with saprotrophic fungi, which decompose organic matter, contribute to nutrient cycling, and support soil structure [ 150 ]. Unique taxon identification reinforced the supposition of Sugiyama et al. [ 141 ] that Bradyrhizobia are subject to species-level selection, and implicated strong host selectivity of parasites/pathogens and mutualists. With regard to the latter, numerous plant pathogens were exclusive to the rhizosphere of the SDS-susceptible soybean cultivar, particularly at later growth stages. This could be attributed to compromised defense mechanisms of the susceptible cultivar, allowing opportunistic pathogens to colonize and proliferate, or possibly due to specific root exudates from this cultivar that inadvertently promote the growth of these pathogens. The exclusivity of Streptomyces panaciradicis , Pseudomonas fluorescens , and Streptomyces griseoplanus in the SDS-tolerant rhizosphere may also reflect host selection, as the two former have been leveraged as biocontrol agents against Fusarium pathogens [ 151 , 152 ] and the latter as a biocontrol agent against Macrophomina [ 153 ]. The Pseudomonas genus has also been associated with SDS-suppressive soils spanning 45 soybean fields [ 10 ]. Lastly, the enrichment of Bradyrhizobia in CZ4979X vs CZ4810X and in Biostimulant vs Control further supports the exclusivity of Pseudomonas fluorescens , which is well-evidenced to interact synergistically with Bradyrhizobium japonicum [ 154 , 155 ]. These microbial dynamics in the soybean rhizosphere highlight potential avenues for targeted crop protection, improved soil health, and optimized disease-resistant breeding. Putative co-occurrences between prokaryotic, fungal, and protist genera were determined using Spearman and Pearson association methods. The Pearson networks exhibited greater complexity and more pronounced variability in node relative abundance compared to the Spearman networks. This disparity could be influenced by Spearman's method of assigning similar rank values to taxa with minimal or zero abundances, leading to simpler network structure and a reduced representation of high-abundance taxa [ 156 ]. Conversely, Pearson's sensitivity to actual data magnitudes may amplify the presence of notably abundant taxa, resulting in networks with a broader range of densities and node abundances [ 156 ]. Nonetheless, the dominant effect of treatment-cultivar interaction on condition-specific network structure was persistent across the association methods. In like manner, Liu et al. [ 18 ] noted a subtle genotype effect on soybean rhizosphere microbial co-occurrence network structure. Due to the reported effects of biostimulant application on soybean agronomic performance [ 157 ] and microbial network structure in other environments [ 158 ], it is also logical to presume its influence on network structure in the present work. Still, one must consider such findings as preliminary, given the shortcomings in inferring ecological interaction from co-occurrence [ 159 ] and that mapped ASVs were used exclusively for co-occurrence network construction, the latter of which could influence network structure and node prioritization. It is therefore recommended to complement network analysis with additional measurements for more robust hypothesis-driven research [ 160 ]. In this manner, 24 edaphic measurements were collected for each soil sample, evaluated with GLMMs and rank-based associations, and incorporated into phenotype-taxon networks. Soil organic matter (SOM) was among the most dynamic parameters assessed, displaying significant variation between five fixed effect level comparisons. This may reflect robust organic macromolecule depolymerization given the observed enrichment of saprotrophs in the eukaryotic rhizosphere microbiome [ 161 ] and Proteobacteria in the prokaryotic fraction [ 162 ], and perhaps coincides with the establishment of nodulation [ 163 ]. The edaphic data were used independently to construct phenotype-taxon networks based on the framework of Poudel et al. [ 89 ]. A more exhaustive approach was used to prioritize nodes by modularity and centrality, accentuating microbial taxa with both module-specific and network-wide influence. As expected, the prioritized nodes for edaphic networks were mostly saprotrophic eukaryotes. Moreover, the core rhizosphere microbiome has been shown to interact with more transient taxa via competition and cooperation, being central for microbial network structure and functional stability [ 149 , 164 ]. In line with this, nearly one-third of the prioritized nodes for edaphic networks were members of the core microbiome. Other identified nodes reinforced trends in edaphic measures (e.g., the β-Proteobacteria genus Burkholderia and the α-Proteobacteria genus Bradyrhizobium are prominent lignin decomposers that can nodulate soybean [ 162 , 165 ]). The microbiome dataset was further contextualized by taking agronomic measurements at the end of the growing season. The most apparent trend was that biostimulant application increased every measured trait, with variation in 100-seed weight and theoretical yield being statistically significant. Additionally, the SDS-susceptible variety had heightened 100-seed weight and theoretical yield in comparison to the tolerant cultivar despite having reduced pods/plant, aboveground biomass, and increased pathogens in the rhizosphere, implicating a putative fitness cost associated with genetic resistance/tolerance in the absence of disease [ 166 ]. Notably, each replicate for 100-seed weight and theoretical yield encompassed approximately 40 plants in a manner aligned with yield plot trials. Network analysis and node prioritization were consistent with that for edaphic properties, highlighting saprotrophic eukaryotes, SOM-decomposing/nitrogen-fixing bacteria, and members of the core microbiome. As evidenced, complementing co-occurrence networks with phenotypic data provides improved ecological context that can guide the practical application of derived inferences (e.g., through the design and implementation of synthetic microbial communities) [ 89 ]."
} | 4,335 |
31758041 | PMC6874649 | pmc | 5,264 | {
"abstract": "The alarming rate of global pollinator decline has made habitat restoration for pollinators a conservation priority. At the same time, empirical and theoretical studies on plant-pollinator networks have demonstrated that plant species are not equally important for pollinator community persistence and restoration. However, the scarcity of comprehensive datasets on plant-pollinator networks in tropical ecosystems constrains their practical value for pollinator restoration. As closely-related species often share traits that determine ecological interactions, phylogenetic relationships could inform restoration programs in data-scarce regions. Here, we use quantitative bee-plant networks from Brazilian ecosystems to test if priority plant species for different restoration criteria (bee species richness and visitation rates) can be identified using interaction networks; if phylogenetic relationships alone can guide plant species selection; and how restoration criteria influence restored network properties and function. We found plant species that maximised the benefits of habitat restoration for bees (i.e., generalists and those with distinct flower-visitor species) were clustered in a small number of phylogenetically-diverse plant families, and that prioritising the recovery of bee visitation rates improved both stability and function of restored plant-pollinator networks. Our approach can help guide restoration of pollinator communities, even where information on local ecosystems is limited.",
"introduction": "Introduction Growing concern over the negative environmental impacts of human activities has put ecological restoration at the forefront of the fight to reverse biodiversity loss and to recover ecosystem functions and services 1 . Historically, restoration programs have focused on structural indicators, such as the recovery of plant communities relative to a reference ‘pristine’ state (e.g., pre-European settlement) 2 , with the assumption that fauna and ecosystem processes (e.g., pollination, seed dispersal, nutrient cycling) recover in tandem 3 . However, more recent evidence has demonstrated that selecting plant species to restore biotic interactions, rather than habitats, is critical to maintain ecosystem functions and health 4 – 7 . Animal-mediated pollination is an essential ecological function in most terrestrial ecosystems 8 . Among pollinator taxa, bees are considered to be the most important group in both natural and agricultural ecosystems 9 , 10 . Unfortunately, many species are sensitive to anthropogenic disturbance, particularly the loss and fragmentation of natural habitats, and are globally in decline 10 , 11 . Outside of agricultural systems, for which there is considerable evidence on the benefits of habitat restoration for wild bees and crop pollination services (e.g. wildflower strips, hedgerows) 12 – 14 , bees are rarely considered as an explicit restoration target in natural lands 3 , 15 . Given that one of the key aims put forward by the International Union for Conservation of Nature’s (IUCN) Bonn Challenge ( www.bonnchallenge.org ) is to restore 350 million hectares of degraded land by 2030, a failure to target bees could lead to reproductive failure and even collapse of plant communities in restored habitats 15 . To investigate the impacts of habitat restoration on bees, many studies adopt network-based approaches, as they provide quantitative and comprehensive information on how environmental changes spread through ecological communities and influence their stability and function 4 , 16 . Studies on plant-bee networks (and more broadly “plant-pollinator networks”) reveal that network generalists, species with many interaction partners, form the core of these networks, and are essential for their dynamic and structural stability 17 , 18 . These findings have important implications for ecological restoration, and several network-based measures of species-level generalisation, alongside modularity (i.e. ‘hubs’ and ‘connectors’), and ecological distinctiveness indices (i.e. functional complementarity), have been put forward to select plant species for bees 18 – 23 . In recent years, conservation scientists have also adopted machine-learning techniques (e.g. genetic algorithms) to inform plant species selection in regional bee restoration programs 24 . However, together with uncertainty over which approach provides the best outcome for bees and pollination, a major drawback of network-based restoration is the need for accurate and meaningful data on interspecific interactions 7 . At present, plant-pollinator networks in countries in tropical regions, such as Brazil, remain limited in number, and overrepresented by vertebrate pollinators (e.g. hummingbirds, bats) 25 , 26 . This data-deficiency is compounded by accelerating impacts of human activities in the tropics relative to other global regions 27 , 28 . In data-scarce regions, restoration managers could use phylogenetic relationships among plant species as proxies of ecological function 29 . Phenotypic complementarity between interaction partners (e.g. long-tonged bees visit deep corolla flowers) has been found to be an important predictor of ecological network structure and function (e.g. pollination) 30 – 32 , although much of the existing data comes from temperate rather than tropical ecosystems. Because closely-related species tend to have similar functional traits, due to shared ancestry 33 – 35 , they often occupy similar positions in networks, both in terms of number of interaction partners and their partner species’ functional attributes 34 , 36 . This trait conservation within evolutionary lineages has great potential for use in bee restoration 37 . For example, if priority plant species (i.e. those that support high diversity/abundance of bees) occupy defined positions within the phylogeny, land managers could adapt findings from existing networks to habitats with slightly different species compositions 38 . Such an approach could facilitate the recovery of bee communities in degraded habitats at large spatial scales and across heterogeneous environments. Here, we use bee-plant networks from across Brazil to test if priority plant species for different restoration criteria (bee species richness and bee visitation rates) can be identified using species-level metrics (for details on chosen network metrics, see Table 1 ). We compare bee community recovery (i.e. restoration success) under different metrics to outcomes using random plant species selection and machine-learning techniques (genetic algorithms), for quantitative networks sampled in two distinct physiognomies (forest or savannah-like biomes). We then use null models to test if phylogenetic relationships can identify priority plant species in regions for which no information on interaction patterns is available. To provide practical information for bee restoration managers, we additionally investigate whether these plant species are clustered within specific families. Finally, we evaluate if specific restoration criteria influence the structural properties of restored bee-plant networks, and the potential of restored bee species to pollinate wider plant communities using a proxy measure of pollination function (shared flower visitor index). Table 1 Network metrics used to describe species-level generalisation and compositional differences in supported pollinator communities among plant species. Species-level metric Description Citing references i) Normalised Degree (ND) The number of interaction partner species divided by total number of species in other trophic level 17 , 19 ii) Interaction Strength (ST) Sum of partner species’ dependencies (proportion of visits to given plant species) 39 iii) Closeness Centrality (CC) The proximity of individual nodes (species) to all other nodes within a network; species with high scores are important to many other species 18 , 19 iv) Betweenness Centrality (BC) How individual nodes act as ‘connectors’, linking otherwise unconnected subsets (modules) of species 18 , 19 v) Functional Complementarity (FC) The ecological distance between plant species’ pollinator assemblages 22 Cited references include studies that previously highlighted importance of metrics for restoration of mutualistic interaction networks.",
"discussion": "Discussion Our results show that previous information on plant-bee interactions can be used to optimise restoration programs by the selection of plant species that maximise benefits to bee communities, and that priority species are clustered in a small number of phylogenetically-diverse plant families. We also found that prioritising the recovery of bee visitation rates over bee species richness, may be the most effective means of restoring ecosystem function in degraded Brazilian landscapes. Given the widespread impacts of human activities on tropical biodiversity, our results can help restoration practitioners to recover pollinator communities and ecosystem function in heterogeneous landscapes such as those found in Brazil, even where little is known beyond inventories of local plant communities. Independent of which component of bee communities was targeted (species richness, bee visitation rates), the genetic algorithm tool developed by M’Gonigle et al . 24 was consistently the most effective means of selecting plant species. Only in the case of bee species richness did a network metric (interaction strength) come close to matching results provided by the algorithms, reinforcing that generalist plant species, which are visited by disproportionately high numbers of bee species relative to other plant species, are essential for restoring bee diversity 17 , 39 . Despite the primacy of the algorithms, network indices may provide a better indication of the actual ecological drivers underpinning bee-plant network structure, and bee community recovery. For example, plant species selected by functional complementarity (FC) 22 , the best-performing metric for bee visitation rates, may reflect important functional differences between plant species (e.g. floral traits, resource type, phenology). As a consequence, this metric probably recovered discrete subsets of closely-interacting species (modules) faster than species-level generalisation metrics (e.g. degree, strength, centrality), that most likely selected plants with a high degree of overlap in their floral traits (e.g. short, open corollae) and visitor communities. However, plant species with high FC scores (i.e. distinct flower-visitor communities) could also include rare species that contributed little to overall bee visitation rates. In contrast, algorithms exclusively-selected plant species based on sum totals of visits recovered, a factor likely to be strongly influenced by an individual plant species’ relative abundance in sampled habitats 40 . This highlights the importance of standardising species’ abundances (e.g. visits/flowers) to disentangle the relative importance of functional traits and local abundance in structuring plant-pollinator networks, something that many existing plant-pollinator networks (but with some important exceptions 4 , 41 , 42 ), do not account for. An important caveat to our results is that aggregated topological models (>1 yr of repeat surveys) used to simulate the bee community recovery did not account for inherent temporal dynamics of plant-pollinator networks (i.e. temporal overlap in bloom/insect activity periods), nor the plastic behavioural responses of bees to the gain or loss of plant species (i.e. ‘rewiring’) 39 . Thus, it is unclear to what extent these aggregate networks can be used to predict flower-visitor communities in restored (i.e. partial) habitats. However, our aim was to identify plant species that provide the greatest benefit to bee communities (i.e. maximum number of species/visits), including potential rewiring species (e.g. bee species A only visits plant species B in the absence of plant species C), which can be largely determined using aggregated networks. Across networks, phylogenetic clustering of priority species was strongest under the nearest taxon index (NTI), indicating that priority species were found in several clusters (i.e. families), rather than one large cluster of closely-related taxa, which would cause the net relatedness index (NRI) to indicate stronger clustering as well 43 . This demonstrates firstly, that phylogenetic relationships can be used to detect priority plant species for bee restoration, and secondly, by increasing phylogenetic diversity among selected species, we can likely reduce the number of plant species required (and hence costs) in restoration programs. This was supported by the lack of phylogenetic clustering among priority species in individual networks, which given that functional traits are expected to be conserved among closely-related species 34 , 35 , would lead to reduced levels of functional complementarity among selected plant species, a key driver of bee diversity in natural and agricultural habitats 44 . Furthermore, elevated competition among closely-related species may preclude co-occurrence at individual sites 45 , although this will depend on the relative importance of abiotic (i.e., environmental filtering) and biotic factors (e.g., interspecific interactions) in community assembly processes 35 . Finally, although biome type was an important factor in determining the relative number of plant species required to meet our restoration targets (higher in forested biomes), we found no evidence of significant phylogenetic turnover between biomes. Therefore, whilst species composition varied between networks in different biomes, overall phylogenetic composition and structure of plant communities did not, allowing our recommendations to be applicable to distinct Brazilian biomes. Nonetheless, many of the evaluated networks were from south-eastern Brazil, and further research is required in underrepresented regions, particularly Amazonia, which was represented by a single network (24 in total), to ensure findings are relevant for the restoration of Brazilian bees. Considering only native bee taxa, assessments at family level revealed that members of the Malpighiaceae family were clear priorities for bee restoration in studied regions. Malpighiaceae species are well known for their importance to oil-collecting solitary bees 46 , that together represented 15% of bee species in networks. Collected oil is used as both adult and larval food, and in nest construction 46 . As well as their importance for oil-collecting taxa, several studies examining pollen stores of native eusocial bees have highlighted the importance of Malpighiaceae pollen, among other families, as larval food 47 – 49 . Thus, not only do Malpighiaceae flowers form highly specialised interactions with oil-collecting bees, they provide protein-rich pollen for generalist eusocial taxa, underlining their importance for Brazilian bee restoration. Alongside the Malpighiaceae, several other families were selected more often than expected by chance (e.g. Convolvulaceae, Sapindaceae), and likely to be important priorities for bee restoration in Brazilian ecosystems, although they fell above the significance threshold ( α = 0.05). Likewise, families which were selected less often (e.g. Anacardiaceae, Asteraceae), whilst still providing resources for flower-visiting bees, are considered low priorities for bee restoration programs. However, reasons why these families promote (or hinder) the recovery of bee communities, and the extent to which these differences are determined by specific functional traits shared among family members (e.g. elaiophores in Neotropical Malpighiaceae), or multiple traits working in chorus, and the relative importance of different traits across geographic regions, remains unresolved. Thus, future studies should aim to incorporate trait-based approaches to identify functional drivers of patterns observed here and test the validity of ‘trait-matching’ hypotheses in diverse tropical plant-pollinator networks. Despite these drawbacks, our results do provide an initial guide (i.e. key plant families) for Brazilian restoration managers, although, given the limited number of families positively or negative selected, further work is required to translate our findings into actual restoration practices. Eventually, this approach could also be adapted to agricultural settings with the aim of improving crop pollination services through the establishment of ‘bee-friendly’ habitats in croplands (e.g., hedgerows, wildflower plantings) 12 , 50 . Overall bee community recovery and restoration of pollination function were dependent on the specific criteria being targeted in simulations (i.e., bee species richness or visitation rates). Simulations that prioritised the recovery of bee visitation rates over species richness tended to produce more generalised networks and had higher values for a proxy measure of pollination function (i.e., export of shared flower-visitor species to adjacent habitats). High levels of generalisation imply greater functional redundancy among interacting species, a positive driver of stability and function in mutualistic networks, and a key priority for ecological restoration 4 . However, given that we defined restoration success as the minimum number of plant species required to meet our a priori restoration criteria (80% of bee species/visits restored), further work is required to make sure that levels of functional redundancy among selected plant species are sufficient to ensure that restored bee communities and pollination services are resilient to future disturbances 4 . Improved pollination function in simulations that targeted visitation rates may have been because plant species predominantly targeted hyper-abundant ‘supergeneralists’ (i.e., species that interact with disproportionately high numbers of plant species), such as the eusocial bee species A. mellifera and Trigona spinipes , that together represented 46.3% of total visits. Previous research has highlighted the importance of generalist species for network stability and function 17 , and more specifically, the contributions of the above mentioned bee species in Brazilian ecosystems 51 . Assuming recovered bee populations move between restored and adjacent habitats, restoration programs benefiting supergeneralists probably have the greatest potential to quickly recover ecosystem functions across large spatial scales. On the other hand, promoting supergeneralists over the recovery of bee species diversity may exacerbate growing problems of biotic homogenisation in tropical ecosystems 52 . Furthermore, caution is required in assuming that the Müller (‘shared pollinators’) index is a useful proxy of pollination function in wider plant communities. Firstly, it remains unclear the degree to which bees move between restored and adjacent habitats, a factor likely to be greatly influenced by bee foraging range, behaviour, nesting habit, and surrounding landscape structure 1 . Secondly, our models do not include information on pollinator effectiveness, or the dependence of plant species on biotic pollination 39 , and evidence from pollen deposition networks suggests that plant-pollinator interactions may be more specialised than they first appear in flower-visitor networks 53 . Therefore, just because restored plant species sustain bee species that also visit many other plant species does not necessarily imply that those insects are effective pollinators of all visited plant species. And finally, because bee-plant networks ignore the contributions of other insect flower visitors (e.g. flies, beetles, butterflies/moths), of which many are effective pollinators in tropical plant communities. Thus, enhancing native pollinator species diversity, as well as improving the overall conservation value ( A. mellifera is an invasive species in Brazil), is likely to be an essential component in the recovery of pollination function in degraded Brazilian landscapes. In this study we demonstrate that priority plant species for the restoration of Brazilian bee communities can be selected based on prior information on their interaction patterns. Not only are they largely generalist species that form many interactions with flower-visiting bees but are also non-randomly distributed across the angiosperm phylogenetic tree. This information, along with the identity of key plant families, can provide restoration practitioners with the means to select priority plant species for bee community recovery in degraded lands, even where ecological information on the target ecosystem is limited. Further studies evaluating restoration success in areas where these selection practices are applied in loco will be important to validate our model-based predictions."
} | 5,224 |
25369743 | PMC4187134 | pmc | 5,265 | {
"abstract": "Hot springs have been investigated since the XIX century, but isolation and examination of their thermophilic microbial inhabitants did not start until the 1950s. Many thermophilic microorganisms and their viruses have since been discovered, although the real complexity of thermal communities was envisaged when research based on PCR amplification of the 16S rRNA genes arose. Thereafter, the possibility of cloning and sequencing the total environmental DNA, defined as metagenome, and the study of the genes rescued in the metagenomic libraries and assemblies made it possible to gain a more comprehensive understanding of microbial communities—their diversity, structure, the interactions existing between their components, and the factors shaping the nature of these communities. In the last decade, hot springs have been a source of thermophilic enzymes of industrial interest, encouraging further study of the poorly understood diversity of microbial life in these habitats.",
"conclusion": "5. Conclusions Less diversity and richness in hot springs than in other aquatic environments have been reported [ 12 , 33 , 48 ]. Analysis of thermal communities from all over the world has found the recurrent presence of certain groups, although in some hot springs there are specific strains that contribute significantly to the composition of the microbial community, and whose presence is correlated to the geochemical properties of hot springs. Apart from microbial community profiles, metagenomics assesses the effect of physicochemical conditions in community diversity from hot springs; although temperature seems to be the major factor, geochemical compositions and geographical distances are significant in some cases. Discoveries in thermal environments have increased the knowledge about the evolution not only of bacteria and archaea, but also of viruses. As far as metagenomic studies are to be expanded, a more complete phylogeny of these groups could be drawn. Hot springs are also a vast source of new and diverse thermophilic enzymes, many with potential uses in industry. Metagenomics is a powerful tool to identify yet unknown enzymes and provide industry with more cost-effective biocatalysts for specific purposes. The reports summarized in this review and others not covered for brevity, but equally valuable, demonstrate the unequalled potential of metagenomics in the study of hot springs as well as the importance of continuing research in this field. We might expect that the findings already made probably represent only the tip of the iceberg.",
"introduction": "1. Introduction Currently there is a great interest in hot springs, which are the natural habitat of thermophilic and hyperthermophilic microorganisms with optimal growth temperatures of >55 °C and >80 °C, respectively. Enzymes obtained from them have been proved to be extremely valuable as biocatalysts for industrial and biotechnological purposes. A paradigm is Taq polymerase from Thermus aquaticus that led to the development of the polymerase chain reaction (PCR) technique [ 1 ]. The initial studies on hot springs focused only on their physicochemical properties and geological features, and it was not until the mid-XX century that the study of the microbiology of these ecosystems began [ 2 ]. The temperature in hot springs is usually over the limit of eukaryotic life (near to 60 °C), which limits the microbial life to Bacteria and Archaea (and their viruses). The earliest microbiological work was based on the isolation and identification of thermophilic microbial strains. 16S rRNA-based studies subsequently revealed that microbial diversity was much broader than suggested by culture-dependent techniques. In combination with the construction of metagenomic libraries, research on total environmental DNA produced a vast amount of information, providing detailed pictures of the microbial communities present in diverse thermal environments. Each hot spring differs from others in temperature, chemical composition and its gradients of temperature or light. Hot springs comprise several habitats, such as thermal fluids, microbial mats and sediments. This diversity of habitats provides a vast number of sites to sample, all with potential interest for metagenomic analysis. The increasing number of reports makes it easier to understand how physicochemical conditions and biological interactions have shaped these microbial communities within their specific environments. In this review, we will illustrate with several examples the usefulness of metagenomic techniques in expanding our knowledge about microbial communities in hot springs."
} | 1,153 |
35621390 | null | s2 | 5,267 | {
"abstract": "Host genetic variation can shape the diversity and composition of associated microbiomes, which may reciprocally influence host traits and performance. While the genetic basis of phenotypic diversity of plant populations in nature has been studied, comparatively little research has investigated the genetics of host effects on their associated microbiomes. Switchgrass (Panicum virgatum) is a highly outcrossing, perennial, grass species with substantial locally adaptive diversity across its native North American range. Here, we compared 383 switchgrass accessions in a common garden to determine the host genotypic influence on rhizosphere bacterial composition. We hypothesized that the composition and diversity of rhizosphere bacterial assemblages would differentiate due to genotypic differences between hosts (potentially due to root phenotypes and associated life history variation). We observed higher alpha diversity of bacteria associated with upland ecotypes and tetraploids, compared to lowland ecotypes and octoploids, respectively. Alpha diversity correlated negatively with flowering time and plant height, indicating that bacterial composition varies along switchgrass life history axes. Narrow-sense heritability (h"
} | 308 |
27350364 | PMC5043000 | pmc | 5,268 | {
"abstract": "Abiotic stress is a widespread threat to both plant and soil communities. Arbuscular mycorrhizal (AM) fungi can alleviate effects of abiotic stress by improving host plant stress tolerance, but the direct effects of abiotic stress on AM fungi are less well understood. We propose two hypotheses predicting how AM fungi will respond to abiotic stress. The stress exclusion hypothesis predicts that AM fungal abundance and diversity will decrease with persistent abiotic stress. The mycorrhizal stress adaptation hypothesis predicts that AM fungi will evolve in response to abiotic stress to maintain their fitness. We conclude that abiotic stress can have effects on AM fungi independent of the effects on the host plant. AM fungal communities will change in composition in response to abiotic stress, which may mean the loss of important individual species. This could alter feedbacks to the plant community and beyond. AM fungi will adapt to abiotic stress independent of their host plant. The adaptation of AM fungi to abiotic stress should allow the maintenance of the plant-AM fungal mutualism in the face of changing climates. Electronic supplementary material The online version of this article (doi:10.1007/s00442-016-3673-7) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions We conclude that AM fungi are important for improving plant tolerance to abiotic stress, but also respond to abiotic stress independently of their host plant. Abiotic stresses affect the abundance and community composition of AM fungi. Changes in the diversity of AM fungi will feed back into the plant community and cause corresponding changes in diversity and dominant plant species, and these feedbacks will become stronger with climate changes, agriculture, and plant invasions. AM fungi are capable of adapting to the abiotic environment which may or may not improve their mutualistic function. The impact of the ecological and evolutionary responses of AM fungi to abiotic stresses is likely to become even more important for both natural and agricultural systems in the face of climate changes and biotic stresses, such as invasion by non-native species.",
"introduction": "Introduction Abiotic stress is widespread. While abiotic stress is common in all environments, its effects are best documented in agricultural systems where abiotic stresses can cause losses in yield of food crops of up to 70 % (Mantri et al. 2011 ). Drought (Pardo 2010 ; Cramer et al. 2011 ), temperature (Weis and Berry 1988 ), salinity (Munns and Tester 2008 ), pH (Yokota and Ojima 1995 ; Koyama et al. 2001 ; Hinsinger et al. 2003 ), and nutrient deficiency or excess all negatively impact plant fitness. Arbuscular mycorrhizal (AM) fungi can often help alleviate the negative consequences of these stresses. The arbuscular mycorrhizal symbiosis is an important relationship formed between the members of the phylum Glomeromycota and ~ 80 % of all land plants (Smith and Read 2008 ). AM fungi are obligate symbionts that colonise plant roots. The fungi gain carbohydrates from the plant host, while the fungi improve plant nutrient and water uptake. The benefits to plant partners can vary depending on the AM fungal species, plant species, and abiotic context (Hoeksema et al. 2010 ). AM fungal community composition and diversity are influenced by plant community composition and diversity (Johnson et al. 2004 ; Hausmann and Hawkes 2009 ; De Deyn et al. 2011 ; Koch et al. 2012 ; López-García et al. 2014 ; Chagnon et al. 2015 ; Reininger et al. 2015 ), biotic stress (Eom et al. 2001 ; Gehring and Bennett 2009 ), and abiotic factors (Johnson et al. 1992 ; Zobel and Öpik 2014 ; Antoninka et al. 2015 ; Borriello et al. 2015 ; Klabi et al. 2015 ). In addition, these factors often interact to influence AM fungal community structure and diversity (e.g., Johnson et al. 1992 ; Klabi et al. 2015 ). Despite our awareness of the influence of these factors on AM fungal community structure and diversity, predominantly only the evolutionary influence of plant community composition on AM fungi has been explored (Kiers and Van Der Heijden 2006 ; Wyatt et al. 2014 ; but see Behm and Kiers 2014 ; Johnson 1993 ). The AM symbiosis has been shown to reduce the negative effects of abiotic stresses. In this study, we define abiotic stress as a shift in any non-living factor within the environment away from the optimal condition or away from the condition to which most organisms in that environment have become adapted. While abiotic stress is context dependent, there are a number of examples demonstrating the impact of AM fungi in improving abiotic stress tolerance in plants. AM fungi improve plant fitness during drought (Smith and Read 2008 ) possibly due to the increased surface area for water absorption provided by AM hyphae (Auge 2001 ), increased access to small soil pores (Smith and Read 2008 ), or improved apoplastic water flow (Bárzana et al. 2012 ). Improved phosphorus nutrition is a common benefit of the AM symbiosis, and particularly during drought conditions, AM fungi improve P uptake from dry soil (Neumann and George 2004 ). AM fungal-improved salinity tolerance (Al-Karaki 2000 ; Evelin et al. 2009 ) has been hypothesised to be due to improved P nutrition, improved ion homeostasis, maintaining photochemical capacity, and higher activity of antioxidant enzymes (Hajiboland et al. 2009 ). Heavy metal toxicity for plants can be reduced by AM fungi, through hyphal ‘metal binding’ which reduces the bioavailability of elements, such as Cu, Pb, Co, Cd, and Zn (Audet and Charest 2007 ). AM fungi may also be more tolerant than plant roots of high temperatures (Bunn et al. 2009 ), and induce higher enzymatic activity and secondary metabolite content in plants (Chen et al. 2013 ) leading to greater cold tolerance in host plants. As a result, AM fungi can clearly benefit host plants exposed to abiotic stress. As mentioned above, less attention has been paid to the direct selective effects of abiotic stress on AM fungi themselves, independent from the effect on their host. Abiotic stress also impacts host plants, and therefore, abiotic stress will indirectly influence AM fungi via host plants, although this influence is likely to follow patterns similar to those identified for the influence of plants on AM fungi under ambient conditions (Kiers and Van Der Heijden 2006 ; Wyatt et al. 2014 ). As a result, in this study, we address the possible direct effects of abiotic stress on the fitness, diversity, evolution, community composition, and symbiotic functioning of AM fungi. Studying the effects of abiotic stress on AM fungi separately from plants will help to provide a better understanding of the strengths and weaknesses of their ubiquitous relationship. Like in all organisms, environmental variation causes selection for different traits in AM fungi. This leads to individuals differing in their symbiotic function based on the contrasting climates or soil conditions of the areas they originated from (Mena-Violante et al. 2006 ; Antunes et al. 2011 ; Sochacki et al. 2013 ). It has been suggested that local adaptation to varying environmental conditions produce more important differences in AM fungi than the basic functional differences between coexisting AM fungal taxa (Sanders 2002 ). Adaptation to environmental conditions can even be seen in highly localised areas, for example, within a natural CO 2 spring, where hypoxia has driven the selection of AM fungal species capable of surviving high concentrations of CO 2 resulting in AM fungi with reduced extra-radical mycelia and enhanced uptake of oxygen from the roots of the plant (Maček et al. 2011 ). Similarly, the ability of three AM fungal phylotypes from Yellowstone National Park to survive in geothermal soils is likely due to tolerance of low pH conditions (Appoloni et al. 2008 ). Evolutionary responses to abiotic stress not only improve the ability of an AM fungus to survive, but may also benefit the host plants exposed to the same stress (Mena-Violante et al. 2006 ; Sochacki et al. 2013 ). This may not be equally true for all stresses, however. For example, increased nutrient loads have been suggested to reduce the benefit AM fungi deliver to host plants (Johnson 1993 ; Antunes et al. 2012 ). Only in extreme cases are nutrients present in such excess as to directly damage plants (Scheirs and De Bruyn 2004 ), but many changes in nutrient availability away from the level plants and fungi are adapted to can be considered an abiotic stress, and, in addition, nutrient availability can undermine the benefits that plants receive from the mycorrhizal symbiosis (Johnson 1993 ). The potential for AM fungi to adapt to novel conditions may be a particularly important characteristic for an organism with limited dispersal capabilities. The benefits provided to plants by AM fungi will become even more important, due to increasing abiotic stresses caused by climate change (Hanson and Weltzin 2000 ; Compant et al. 2010 ). This is demonstrated by the knock-on effects on plant communities that can occur when AM fungal diversity or community composition is changed (van der Heijden et al. 1998 ; Antoninka et al. 2009 ; Sun et al. 2013 ). Knock-on effects occur if plants differ in their response to specific AM fungal species, or if they have varying levels of general dependence on the symbiosis. In this case, a change in AM fungal community composition could, for example, make a species of plant dependent on the AM symbiosis (or a particular AM fungal species) less fit. It could then be out-competed by plant species less dependent on AM fungi (Mariotte et al. 2013 ). Given the potential influence of AM fungi on plant responses to climate change, the direct effects of abiotic stress on the fungi themselves and the consequences for the symbiosis cannot be ignored. In this study, we present two hypotheses for how abiotic stress influences the ecology and evolution of AM fungi (Table 1 ). The stress exclusion hypothesis addresses the ecological consequences for an AM fungal community of a relatively short-term abiotic stress, whereas the stress adaptation hypothesis examines the long-term evolutionary consequences of selection by abiotic stress on AM fungi. Table 1 Summary of the stress exclusion and mycorrhizal stress adaptation hypotheses including assumptions, possible experiments to test assumptions currently lacking evidence, and predictions Hypothesis Assumptions Possible experiments Predictions Stress exclusion: abiotic stress will cause changes in AMF community composition. 1. AMF communities are diverse 1. Applying an abiotic stress to a soil with a diverse AMF community will change the AMF community composition. Species that cannot tolerate adverse conditions will be the first to become less prevalent, leaving the soil system with a higher proportion of species tolerant to that stress. This will result in an overall change in composition in the AMF community 2. Abiotic stresses affect AMF directly 3. AMF species can differ in their response to the same abiotic stress, some having a negative reaction that reduces their abundance 4. Abiotic stress response of AMF is not dependent on/controlled by host plant response Mycorrhizal stress adaptation: abiotic stress will lead to adaption among AMF species within communities from areas that are repeatedly exposed to abiotic stress. 1. AMF and plants are equally likely to interact under ambient or abiotic stress conditions 1. Abiotic stress adapted AMF will have greater nutrient delivery function under the specific abiotic stress to which they have adapted than AMF that have not adapted to the same abiotic stress 2. Host plant fitness will improve under abiotic stress conditions in the presence of AMF adapted to that abiotic stress condition versus no AMF 3. Host plant fitness will improve under abiotic stress conditions in the presence of AMF adapted to that abiotic stress condition versus AMF that are not adapted to that abiotic stress condition 2. AMF benefit host plants under abiotic stress 3. AMF adapt directly to abiotic stress conditions 4. Plant adaptations to abiotic stress conditions do not influence AMF adaptation to abiotic stress 4. Grow two genotypes of a plant species with varying tolerance to an abiotic stress with AMF under the abiotic stress or ambient conditions. After multiple generations, inoculate unadapted plant genotype, grow with and without the stress, and compare AM fungal fitness 5. AMF adaptation to abiotic stress conditions improves AMF fitness 6. AMF adaptation to abiotic stress conditions will influence different plant species and communities equally 7. AMF adaptation to one abiotic stress will not result in adaptation to all abiotic stresses 7. Inoculate plants with AMF and grow under one abiotic stress. After multiple generations, inoculate plants with selected AMF, grow under different abiotic stresses, and compare AMF fitness \n AMF arbuscular mycorrhizal fungi"
} | 3,271 |
33108605 | PMC7591656 | pmc | 5,269 | {
"abstract": "The algal biotechnology together with the wastewater treatment can contribute to the production of renewable energies such as bioethanol, biodiesel and biohydrogen and solve many of the challenges currently facing the shortage of fossil fuels and environmental impacts. Hydrogen as the cleanest source of energy is a promising alternative to conventional fossil fuels. Among different technologies for hydrogen production, photosynthetic microorganism, such as microalgae, has a great potential to produce hydrogen, by using only water and sunlight. One of the great opportunities is that microalgae can be cultivated in urban wastewater, which contains sources of carbon and nutrients, helping to reduce the cost of biomass and energy production. Microalgae C. vulgaris and S. obliquus immobilized grown in urban wastewater was proposed for the production of biohydrogen by sulfur deprivation and two light quality prior to anaerobic condition at pH 7.5 and 30 °C and 140 µE/m 2 /s of light intensity. The results indicate that blue light induces greater algal growth than under Purple light, while the maximum hydrogen production was for cultures under purple light of 128 mL H 2 /L (productivity 204.8 mL H 2 /L/day) and 60.4 mL H 2 /L (productivity 39.18 mL H 2 /L/day) for S. obliquus and C. vulgaris , respectively. An additional advantage is the high removal of organic carbon by S. obliquus cultures under purple incident light compared to C. vulgaris , being a double benefit; energy production and wastewater treatment.",
"introduction": "Introduction One of the great challenges for the coming decades is to obtain renewable sources that are friendly to the environment and to be able to replace the high dependence on fossil fuels. Much of the available energy is obtained from fossil energy sources; however, these are a non-renewable energy source and cause many negative impacts on the environment (Azwar et al. 2014 ). Therefore, several studies have been conducted to explore new sources of sustainable energy that can replace fossil fuels, and which do not have negative impacts on the environment. One of the biofuels that has caught interest is the biodiesel obtained from microalgal culture; this can play a role as primary producer of polyunsaturated and saturated fatty acids, which can be used for biodiesel production. On the other hand, the microalgae cultures offer several additional advantages as carbon dioxide capture and fixation during photosynthesis process, as well as, the removal of nitrogen and phosphorous from wastewaters. For these reasons, the microalgae show high potential in algal biotechnology (Ruiz-Marín et al. 2010 ; Lim et al. 2010 ; De Godos et al. 2010 ; Wang et al. 2010 ; Chinnasamy et al. 2010 ). Another source of renewable energy produced by photosynthetic organisms is hydrogen, which contains a higher energy content of 122 kJ/g, which is 2.75 time greater than hydrocarbon fuels (Argun et al. 2008 ); for this reason has been investigated as a substitute for fossil fuels with a promising future, considered as an energy carrier. The first scientific investigation of H 2 evolution by microalgae was conducted by Gaffron and Rubin ( 1942 ) who reported that microalgae Scenedesmus obliquus produces H 2 in the dark at low rates and by replacing the atmosphere of the culture with nitrogen gas. Kessler ( 1974 ) concluded that hydrogen production depends on the adaptive capacity of microalgae during the transition from dark anaerobic conditions to oxygenic photosynthesis, as a means to re-oxidize the electron transport pathway. Microalgae produces hydrogen by adopting a two-stage process (indirect biophotolysis). In stage 1, CO 2 is fixed in the presence of sunlight through photosynthesis; that is, the microalgae produce O 2 and accumulate carbon in the form of biomass. In stage 2, the hydrogen produced by the degradation of stored organic compounds via anaerobic takes place in the absence of oxygen using multi-enzyme systems under a series of complex biochemical reactions (Argun et al. 2009 ; Kapdan and Kargi 2006 ). Studies have reported that the use of immobilized cells for hydrogen production is more attractive than free cells. The immobilized cells systems have advantages such as an increase in the cell retention time within bioreactors and higher metabolic activity than free cells (Tam and Wong 2000 ). Additional, immobilized cells help to avoid the settling during growth, phenomenon that inhibits growth due to limited gas diffusion and light penetration: therefore, immobilized cells show greater hydrogen production than free cell cultures (Rashid et al. 2013 ). Several strategies have been implemented to improve hydrogen production such as the variation of light intensity, carbon source, pH, temperature and sulfur deprivation (Azwar et al. 2014 ; Rashid et al. 2013 ). The sulfur deprivation in microalgae cultures is a key factor since it inhibits protein synthesis and consequently the production of oxygen declines which is hydrogenase enzyme inhibitor (Antal and Lindblad 2005 ). Hydrogen production by green microalgae take place in anaerobic conditions in the dark to induce activation of enzymes involved in hydrogen metabolism. Hydrogenase sensitivity to oxygen is a big challenge for this method, so that further research is needed to develop engineered hydrogenase so that it is not sensitive to oxygen inactivation. Sulfure deprivation and anaerobic condition induce expression of hydrogenases [Fe]- in algal cells, so that continuous hydrogen production can be achieved (Ghirardi et al. 2000 ). [FeFe]-hydrogenase is an enzyme which plays a vital role in anaerobic metabolism, which is produce by green algae and become more efficient catalyst hydrogenases. [FeFe]-hydrogenase is able to catalysis the reversible oxidation of molecular hydrogen (Florin et al. 2001 ; Azwar et al. 2014 ). On the other hand, hydrogen production is achieved by the degradation of internal stored compounds and can be increased by the addition of external carbon source. The nature of the carbon source and their concentration determine the economic feasibility of hydrogen production process; the use of cheaper carbon source can bring down the cost of hydrogen production significantly and an alternative is the use of urban wastewater as carbon source and nutrients (N and P) with the additional advantage that the algae culture system contributes to wastewater treatment (Ruiz-Marín et al. 2010 ). According to Brennan and Owende ( 2010 ), the combination of these processes will be the most plausible commercial application in the short term and a sustainable way to produce bioenergy and bio-products (Batista et al. 2015 ). In general, the investigations carried out have shown that these strategies contribute to improve the hydrogen production but the method of culture using different sources of energy (light quality) and carbon source is always acknowledged to be a key factor having strong influence, however, scarce studies have been reported on the influence of the light quality (wavelength) on the hydrogen production. Chavez-Fuentes et al. ( 2018 ) reported that the light source is a variable that influences the biochemical composition, suggesting that blue light contributes to growth and purple light to lipid accumulation, so that, it is possible to regulate photosynthesis and biochemical composition by manipulating the wavelength in algal culture. The present study explores the production of hydrogen by Chlorella vulgaris and Scenedesmus obliquus immobilized cells in alginate beads as a renewable energy source, cultivated in artificial wastewater combining the effect of blue and purple light and dark anaerobic condition.",
"discussion": "Discussion In the present study, the maximum increase in cell density for the cultures under blue light for both immobilized microalgae were similar to the reported by Chavez-Fuentes et al. ( 2018 ) concluding that free cells cultures of C. vulgaris and S. obliquus exposed to blue light favored growth, while purple light induces lipid accumulation (% w/w). Other studies suggest that blue light contains energy more efficient for carrying out photosynthesis (Das et al. 2011 ; Korbee et al. 2005 ). While the purple light due to high energy that can emit, cause effects on the growth of C. vulgaris and S. obliquus (Mohsenpour et al. 2012 ). Although the available information is scarce on growth in immobilized systems under different light sources, it has been documented that in free cell cultures growth changes can occur when going from a phototrophic to a mixotrophic culture system in microalgae, as reported by Canedo-López et al. ( 2016 ) in mixotrophic cultures (white light/dark) of Chlorella vulgaris showed a low cell density in artificial wastewater medium and urban wastewater of 11.65 × 10 6 cells/mL and 10.76 × 10 6 cells/mL, respectively; compared with phototrophic culture of 17.66 × 10 6 cells/mL and 15.26 × 10 6 cells/mL, respectively. Concluding that lighting conditions (continuous light/photoperiods) influence algal growth. On the other hand, Papazi et al. ( 2012 ) reported a lower mixotrophic growth of Scenedesmus obliquus for 5 days with dichlorophenol from 4.5 × 10 5 cells/mL to 11.9–16.1 × 10 5 cells/mL; with the aim of increasing the rate of hydrogen production. Although the comparison is not absolutely correct between free and immobilized cells, because the conditions and the parameters used in the literature are totally different, it is a fact that mixotropic conditions tend to decrease cell density compared to phototrophic cultures. In addition to the above, the mixotrophic culture under different light sources could also cause changes in algal growth such as those reported by Chavez-Fuentes et al. ( 2018 ) suggesting that the intensity and light source modifies the growth and biochemical composition, reporting the highest concentrations of biomass dry weight (g/L) and cellular density (cells/mL) for a white light source (140 µE/m 2 /s) of 0.3 g/L and 4.9 × 10 6 cells/mL, respectively and, for blue light of 0.4 g/L and 4.5 × 106 cells/mL, respectively; in contrast to the observed for purple light (0.23 g/L and 2.97 × 10 6 cells/mL, respectively) and yellow light (0.12 g/L and 3.13 × 10 6 cells/mL, respectively). This is congruent with the reported in the present study, cultivation of immobilized cells showed a low cell density (cell/beads) under purple light with respect to blue light, suggesting the light quality is a factor key that can modify the growth and, consequently, algal biochemical composition in cultures with artificial wastewater. In a fact that the immobilization of cells on substrates offers a greater advantage over free cells in suspension, since the immobilized cellular matter occupies less space, requires a smaller volume of growth medium, is easier to handle, and can be used repeatedly for products generation. In addition to photosynthetic bacteria, immobilized green algal cultures has also been employed to increase the yield and efficiency of H 2 production in these eukaryotic oxygenic photosynthesis systems. Immobilized systems have been found to be more efficient at switching between the oxygenic photosynthesis (growth) and the hydrogen production modes. Kosourov and Seibert ( 2009 ) reported for C. reinhardtii immobilized on alginate films in sulfur/phosphorus-deprived cultures, a high cell density (2000 µg Chl/mL) and hydrogen production rates (12.5 µmol/mg Chl/h). It is a fact that immobilization helps to improve the hypoxic environment in the vicinity of the cells, thus promoting conditions for H 2 -production and making more efficient use of the carbon sources contained in the culture media. During the second stage, hydrogen production by C. vulgaris and S. obliquus immobilized cells was proportional to the glucose consumption (Table 2 ). These suggested that the maximum glucose uptake for the cultures of C. vulgaris and S. obliquus (70% and 90%, respectively) under purple light (Table 2 ) were related with the maximum production of H 2 . The ability to remove organic carbon has been reported in numerous microalgae in mixotrophic culture systems making this attractive for use in wastewater treatment systems. Canedo-López et al. ( 2016 ) reported a similar removal of total organic carbon (TOC) for Chlorella vulgaris in mixotrophic free culture in artificial wastewater (70.5−86.0%) and urban wastewater (43.7−56.2%). Other studies in free cell culture suggest a high removal of chemical oxygen demand (COD) for Chlorella sp. and Scenedesmus obliquus from 63 to 88% (Lu et al. 2016 ; Gupta and Pawar 2018 ). This suggests that both microalgae can change its metabolism from autotrophic to mixotrophic according to prevailing conditions, and continue to use inorganic and organic carbon (Ogbonna and Tanaka 2000 ; Liang et al. 2009 ; Mandal and Mallick 2011 ). The high hydrogen production obtained for S. obliquus of 128 mL H 2 /L (productivity of 204.8 mL H 2 /L/day) and for C. vulgaris of 60.4 mL H 2 /L (productivity of 39.18 mL H 2 /L/day) (Fig. 1 ; Table 2 ) were high to the reported by Chader et al. ( 2009 ) for Chlorella sorokiniana of 1.35 mL H 2 /L/h in free cell cultures, containing acetate as the only carbon source under optimal conditions of pH: 7.2 and light intensity of 120 µE/m 2 /s at 30 °C. Rashid et al. ( 2013 ) evaluated the production of hydrogen by immobilized C. vulgaris optimizing parameters such as: pH, carbon source (glucose, fructose, sucrose and malt extract) and light intensity. The authors reported a maximum production of 812, 874, 1315 and 1144 mL/L for the different carbon sources at pH 8, respectively. These values were high compared to that obtained in the present study, but other factors could intervene in the production of H 2 when microalgae are cultivated in wastewater, such as organic load, carbon sources and competition and predation by other microorganisms. According to Das and Veziroglu ( 2001 ) the high concentration of carbon source modifies the metabolic pathway and leads to production of unwanted by-products and, because of this, it is important to consider each of these factors during hydrogen production. In cultures of C. vulgaris under white, purple and blue light a prolonged lag phase was observed before hydrogen production of 70 h, 35 h and 10 h, respectively, suggesting this time as required to change the metabolism from autotrophic to heterotrophic to use the available carbon sources in the wastewater and be able to express the hydrogenase enzyme for subsequent hydrogen production. In contrast, S. obliquus only presented a lag phase in cultures under white light (Fig. 1 ), compared with the cultures under purple and blue light suggesting a high capacity of the microalgae to adapt under these cultivation conditions and, to activate the enzyme hydrogenase for production of hydrogen in the first hours of dark anaerobic condition. In fact, microalgae C. vulgaris showed an insufficient ability to degrade glucose into protons, and consequently, during this period of prolong time lag, the hydrogenase enzyme was not active sufficiently to convert them into hydrogen. Although the biochemistry of immobilized cells was not determined in the present study, some considerations may be mentioned. It is likely that a light source with a high level of energy (purple light) induces lower growth but with a high uptake of organic carbon and potentiate the production of hydrogen, while in the case of blue light (low energy level) induces growth but lower hydrogen production during the anaerobic stage. In this context, the results could suggest that the accumulation of lipids which is induced by light quality (purple light) contributes to a better the use of external carbon sources, since microalgal cells under these conditions will have a lower growth, content of chlorophyll and carbohydrates-proteins, so it forces a metabolic change for a better use of external carbon sources and quickly activates the hydrogenase enzyme under anaerobic conditions, which could be related to low energy uptake from purple light for the phtosynthesis, compared to those cultures under white and blue light where the carbohydrate and protein content assumes that are high. However, more studies should be carried out to know which of these two conditions during anaerobic dark phase cultivation contributes to increased hydrogen production. In fact, microalgae S. obliquus represents a better proposal for the hydrogen production than C. vulgaris and is a candidate for the wastewater treatment with the ability to efficiently remove the carbon source from urban wastewater and obtain bio-hydrogen as an energy source."
} | 4,209 |
24145501 | PMC3804853 | pmc | 5,270 | {
"abstract": "The search for optimization principles in microbial metabolism, such as biomass or ATP yields or growth rate optimization, has attracted substantial research efforts in the recent years. Here we use the results of C13 labeling experiments together with genome scale metabolic networks of S cerevisiae and E coli in order to assess if there are relationships between systemic variables that are present in both organisms. Strong correlations between the total flux per unit of substrate and the ATP turnover rate per unit of substrate and between the growth rate divided by the total flux and the total flux per unit of substrate were observed for both organisms. We also observed that the common assumption of biomass yield optimization is not consistent with the experiments.",
"discussion": "Discussion In summary, using two genome scale metabolic models of high quality, for a prokaryotic and a eukaryotic organism, and high quality C13 labeling experimental data 16 19 ; we have identified three strongly conserved correlations between systemic variables. The correlation between ATP and NADH turnover rates appears to be trivial to some extent, due to the fact that both processes are highly coupled through respiration, and also fermentation. The two other correlations are non-trivial and are surprisingly well conserved for two very different microbial organisms. This points to the existence of global operation principles (involving relationships between systemic variables) of microbial metabolism that are common to eukaryotic and prokaryotic species. We also showed that if an objective function exists this is not likely to be the growth yield. Based on our results, we suggest the utilization of the identified relationships as extra constrains in the genome-scale metabolic models. This is likely to lead to more realistic predictions of the metabolic flux distribution, at least in the two organisms we have analyzed. Using objective functions such as biomass yield does not seem to be a good option, and other objective functions ( figure 2 ), such as total turnover of redox cofactors, are likely to be closer to reality. It has also been shown that the allocation of ATP to biosynthetic processes is clearly non-optimal in the studied strains."
} | 562 |
29146872 | PMC5688466 | pmc | 5,271 | {
"abstract": "What does it take to convert a living organism into a truly productive biofactory? Apart from optimizing biosynthesis pathways as standalone units, a successful bioengineering approach must bend the endogenous metabolic network of the host, and especially its central metabolism, to support the bioproduction process. In practice, this usually involves three complementary strategies which include tuning-down or abolishing competing metabolic pathways, increasing the availability of precursors of the desired biosynthesis pathway, and ensuring high availability of energetic resources such as ATP and NADPH. In this review, we explore these strategies, focusing on key metabolic pathways and processes, such as glycolysis, anaplerosis, the TCA (tricarboxylic acid) cycle, and NADPH production. We show that only a holistic approach for bioengineering — considering the metabolic network of the host organism as a whole, rather than focusing on the production pathway alone — can truly mold microorganisms into efficient biofactories.",
"conclusion": "Concluding remarks This review explores and exemplifies the importance of considering the entire metabolic network, and especially central metabolism, when optimizing the biosynthesis of a product of interest. Through the examples presented in this review, several general principles of holistic bioengineering emerge. First and foremost, regardless of the exact pathway or process in question, the manipulation of cellular metabolism is mostly aimed at one of three key goals: (i) deleting endogenous pathways that compete with the biosynthesis of a desired product. These include fermentation pathways in which carbons leak out of the cell, oxidative pathways — such as the TCA cycle — that release carbon as CO 2 , or simply metabolic highways that channel flux away from the required biosynthetic route. (ii) Increasing flux toward a key precursor of the biosynthesis route. This can be performed by the overexpression of endogenous enzymes or the introduction of foreign enzymes and pathways that directly convert feedstock to precursor. The most commonly pursued biosynthetic precursor is acetyl-CoA; numerous studies have developed innovative strategies to increase the level of this central metabolite toward enhancing the production of a myriad of downstream products. Other metabolic precursors, such as pyruvate or 2-ketoglutarate, have received less attention; however, considering their importance for the biosynthesis of multiple chemicals, we can expect more efforts to be directed toward their enhanced synthesis. (iii) Manipulating the energy and redox state of the cell to rewire cellular fluxes toward bioproduction. Here, we differentiate between two complementary approaches. A general strategy is to increase the ATP levels in the cell — e.g. via ATP-generating anaplerosis or more efficient glycolysis — such that less of the carbon feedstock is directed toward energy production and more toward biosynthesis. A more focused approach is to increase the availability of an energy carrier that is required in high amounts for a specific biosynthetic process. The most common example is NADPH, a high supply of which is essential for the production of numerous chemicals. Another important principle is the inherent trade-off between rate and yield, especially from a thermodynamic point of view. That is, ATP-efficient pathways tend to operate under a low thermodynamic driving force. This leads to one of two outcomes: low pathway rate or high investment in pathway enzymes, leading to protein burden [ 114 ]. One of the most illuminating examples of this phenomenon is the prevalence of the ED pathway. While this pathway generates only half the ATP molecules the EMP glycolysis does, its higher thermodynamic driving force enables high flux at low protein investment and hence, it is the preferred pathway in many microorganisms that can produce ATP via means other than glycolysis, e.g. respiration or photosynthesis [ 82 ]. An additional fundamental lesson relates to harnessing natural selection for increased bioproduction. In most cases, sustaining high flux via a biosynthetic route does not benefit the microbe, but rather consumes resources that could otherwise be used to sustain growth, i.e. the activity of the pathway has a negative impact on fitness. As such, strain instability, where short-term cultivation results in the rise of mutations that abolish the activity of a biosynthetic route, is a common hurdle that limits many bioproduction projects (e.g. [ 133 , 134 ]). Yet, in some cases, it is possible to engineer the bioproduction strain such that the activity of the biosynthetic route will be beneficial, or even essential for microbial growth. As growth is coupled to pathway activity, strain evolution is highly unlikely to disrupt it. As discussed above, a common example for this is the deletion of competing fermentation pathways, such that ATP-producing, redox-balanced fermentation can proceed only via a specific pathway leading to a desired product. Another interesting example, discussed in the TCA cycle section, is the use of 2-ketoglutarate-dependent dioxygenase as sole way to recycle 2-ketoglutarate, thus coupling growth to a required biocatalysis. Harnessing natural selection in such a way can serve more than to just ensure the stability of a biosynthetic route: it can also be used to enhance its activity. While most metabolic engineering efforts require multiple design-test cycles — tweaking gene expression levels and monitoring the effect on production — these can be avoided if direct selection for high pathway activity is possible, thus saving time and labor. In most cases, the rewiring of cellular metabolism was rationally designed based on the knowledge and experience of the authors. In other cases, a computational strategy was taken to systematically explore all possible alternations of central metabolism that could lead to beneficial results (e.g. [ 135 – 141 ]). While both approaches are valid, it is fair to say that in the long run, precise fine-tuning of the endogenous cellular metabolism will vastly benefit from specialized software and computational tools. Yet, for such tools to truly reinvent the field of metabolic engineering, they should involve much more than a stoichiometric analysis, as is commonly the case now. Instead, thermodynamics and kinetics of reactions should be considered [ 142 – 145 ], alongside known regulatory effects, such as allosteric inhibition or activation, as well as measured ranges of enzyme and metabolite concentrations (e.g. [ 113 ]). While obtaining sufficient data on these parameters is a not an easy task, the availability of -omics tools and databases can considerably assist in addressing this challenge. We emphasize that while we focused on central metabolism in this review, a truly holistic bioengineering encompasses other aspects of cellular physiology, including amino acid, nucleotide and fatty acid metabolism, assimilation of inorganic elements such as nitrogen and sulfur, passive and active cellular transport, as well as transcription and translation. Each of these cellular processes can be — and should be — modified or rewired as to support the most efficient conversion of feedstock into product. We would like to finish by noting that even if we keep focusing on central metabolism, the challenge of wholly redrawing it — as opposed to mildly rewiring it, as is commonly done — is still open. To what extent can we reinvent key metabolic pathways? Can such dramatic changes be useful for biotechnological applications? Some pioneering studies, e.g. engineering an active Calvin Cycle in E. coli [ 146 ] — may start providing answers to these questions soon.",
"introduction": "Introduction The bioproduction of value-added chemicals is gaining momentum, slowly but surely replacing environmentally unsustainable fossil-carbon-based chemical processes. Metabolic engineering of microbes now supports the production of food additives [ 1 ], plastic monomers [ 2 ] and polymers [ 3 ], solvents [ 4 ], aromatics [ 5 ], pharmaceuticals [ 6 ], pigments [ 7 ], hydrocarbons [ 8 ], fuels [ 9 ], and chemical building blocks [ 10 ]. Successful engineering of a microbe for the efficient bioproduction of a compound requires more than just the introduction of the biosynthesis enzymes. For instance, adaptation of foreign genes into the host organism, in terms of GC content or codon utilization, plays an important role in obtaining high protein expression efficiency and enzymatic activity [ 11 ]. Fine-tuning of enzyme levels using different plasmid backbones [ 12 ], promoters [ 13 ], and ribosome-binding sites [ 14 ] is also vital to ensure sufficient flux via the biosynthetic route, while minimizing protein burden and accumulation of toxic or wasteful intermediates [ 14 ]. Yet, apart from the properties of the bioproduction pathway itself, as a standalone unit, the endogenous metabolic network of the host organism plays a key role in determining biosynthesis efficiency. There are three primary means by which central metabolism can be modified to enhance a bioproduction process: decreasing and abolishing metabolic flux toward competing pathways that lead to waste byproducts, increasing the availability of the direct precursors of the desired biosynthesis routes, and ensuring high availability of cellular energetic resources, mainly ATP and NADPH. These metabolic strategies are the focus of this review. We argue that engineering of the cell as a whole is crucial for the optimization of any metabolic process. We find the term holistic bioengineering most appropriate to describe this approach. Figure 1 presents the canonical central metabolism, on which the networks of several model biotechnological organisms — mainly Escherichia coli , Corynebacterium glutamicum , and Saccharomyces cerevisiae — are overlaid (ignoring compartmental localization). Key pathways are marked by specific colors. Enzymes to which we directly refer below are marked with a yellow background. We divide this review into several sections, each discussing the modifications made to a different central pathway or process with the aim of enhancing a particular biosynthetic flux. As the topic is quite extensive, our review focuses on several primary examples which, we believe, demonstrate the key aspects.\n Figure 1. An overview of the structure of central metabolism in model organisms, such as E. coli , C. glutamicum , and S. cerevisiae , as discussed in the present paper. Each organism possesses only a subset of the enzymes shown in the figure. Compartmental separation (in case of eukaryotic organisms) is not shown. Glucose and glycerol are shown as representative carbon feedstocks. We have divided central metabolism into different generalized pathways, as indicated by the colors of the arrows. Enzymes mentioned in the text are shown with a yellow background. Some anaplerotic reactions use bicarbonate instead of CO 2 ; for the sake of simplicity, we write CO 2 as the substrate of all of them. Abbreviations: ACK, acetate kinase; ACS, acetyl-CoA synthetase; ADH, alcohol dehydrogenase; AADH, acetaldehyde dehydrogenase; EDA, 2-keto-3-deoxygluconate 6-phosphate aldolase; EDD, phosphogluconate dehydratase; FBA, fructose-bisphosphate aldolase; FHD, fumarate hydratase; FRT, fumarate reductase; GAPDH, glyceraldehyde 3-phosphate dehydrogenase (phosphorylating); GAPN, non-phosphorylating glyceraldehyde 3-phosphate dehydrogenase; GND, 6-phosphogluconate dehydrogenase (decarboxylating); ICDH, isocitrate dehydrogenase; ICL, isocitrate lyase; KGDH, 2-ketoglutarate dehydrogenase; LDH, lactate dehydrogenase; MAE, malic enzyme; PKF, 6-phosphofructokinase; PGI, glucose-6-phosphate isomerase; PGK, phosphoglycerate kinase; PCK, phosphoenolpyruvate carboxykinase; PDC, pyruvate decarboxylase; PDH, pyruvate dehydrogenase; PFL, pyruvate formate-lyase; PPC, phosphoenolpyruvate carboxylase; PTA, phosphate acetyltransferase; PYC, pyruvate carboxylase; SDH, succinate dehydrogenase; TPI, triose-phosphate isomerase; ZWF, NADP + -dependent glucose-6-phosphate dehydrogenase."
} | 3,036 |
28544434 | PMC5519929 | pmc | 5,272 | {
"abstract": "Abstract Biomimetic, strain‐stiffening materials are reported, made through self‐assembly and covalent fixation of small building blocks to form fibrous hydrogels that are able to stiffen by an order of magnitude in response to applied stress. The gels consist of semi‐flexible rodlike micelles of bisurea bolaamphiphiles with oligo(ethylene oxide) (EO) outer blocks and a polydiacetylene (PDA) backbone. The micelles are fibers, composed of 9–10 ribbons. A gelation method based on Cu‐catalyzed azide–alkyne cycloaddition (CuAAC), was developed and shown to lead to strain‐stiffening hydrogels with unusual, yet universal, linear and nonlinear stress–strain response. Upon gelation, the X‐ray scattering profile is unchanged, suggesting that crosslinks are formed at random positions along the fiber contour without fiber bundling. The work expands current knowledge about the design principles and chemistries needed to achieve fully synthetic, biomimetic soft matter with on‐demand, targeted mechanical properties."
} | 254 |
25330991 | PMC4204047 | pmc | 5,273 | {
"abstract": "The metatranscriptomic recharacterization in the present study captured microbial enzymes at the unprecedented scale of 40,000 active genes belonged to 2,269 KEGG functions were identified. The novel information obtained herein revealed interesting patterns and provides an initial transcriptional insight into the thermophilic cellulose methanization process. Synergistic beta-sugar consumption by Thermotogales is crucial for cellulose hydrolysis in the thermophilic cellulose-degrading consortium because the primary cellulose degraders Clostridiales showed metabolic incompetence in subsequent beta-sugar pathways. Additionally, comparable transcription of putative Sus-like polysaccharide utilization loci (PULs) was observed in an unclassified order of Bacteroidetes suggesting the importance of PULs mechanism for polysaccharides breakdown in thermophilic systems. Despite the abundance of acetate as a fermentation product, the acetate-utilizing Methanosarcinales were less prevalent by 60% than the hydrogenotrophic Methanobacteriales . Whereas the aceticlastic methanogenesis pathway was markedly more active in terms of transcriptional activities in key genes, indicating that the less dominant Methanosarcinales are more active than their hydrogenotrophic counterparts in methane metabolism. These findings suggest that the minority of aceticlastic methanogens are not necessarily associated with repressed metabolism, in a pattern that was commonly observed in the cellulose-based methanization consortium, and thus challenge the causal likelihood proposed by previous studies.",
"discussion": "Discussion The technical reproducibility of NGS-based metatranscriptomic sequencing is a topic lacking wide recognition. At this early stage of applying RNA-seq to metatranscriptomes, it is common to see frontier research without an emphasis on replication, especially for technical replicates 17 18 19 . After an extensive literature survey, we found only one previous work that addressed the issue of technical replicates. Tsementzi, D. et al . 20 noticed that the variability in technical replicates was almost as large as it was in the biological replicates. Their findings highlighted the presence of noticeable variation between mRNA technical replicates. In contrast, extensive studies have shown that the NGS-based transcriptome of a single organ (stem cells 21 , liver and kidneys 22 ) or single species (yeast 23 ) is highly replicable with little technical variation. Therefore, we speculate that inadequate sequencing coverage other than RNA extraction contributes primarily to the variation between metatranscriptomic technical replicates as observed in this study ( Table S1 ), and the enormous amount of mRNA molecules, at approximately 8 × 10 23 microbial mRNA molecules per liter of reactor sludge with volatile suspended solids of 800 mg/L (~200 mRNA molecules per bacterial cell 24 ) makes it economically difficult to obtain the sequencing depth required to ensure the representation of the entire metatranscriptional profile 25 . The scale of variation observed in this study was comparable to that reported by Tsementzi, D. et al. 20 . Therefore even the large NGS-based metatranscriptional libraries constructed here (3.8 million mRNA sequences after filtering ribosomal and small RNA content out of 29.5 million Illumina reads for each replicated RNA library, Figure S2 ) could at best provide a snapshot of the major activities of the community at a particular time point. Additionally, we picked the peak of biogas production to ensure active microbial metabolism in the microbiota because based on the long-term monitoring the peak biogas formation occurred almost simultaneously with the highest cellulose uptake rate in the sequencing batch reactor (SBR) cycle. Because of the annotation difficulty caused by the short reads of Illumina sequencing, we compared the distribution and function of different phylotypes within the community at the order level. The adaptation of the thermophilic microbial consortium to cellulose yielded simplified communities in which members of Anaerolineas , Clostridiales , Bacteroidales and Thermotogales (listed in order of dominance) were the most prevalent populations. The consortium showed notable microbial diversity with 700 species (Shannon Index of 6.7) ( Figure S6 ), which was comparable to that of the cow rumen (approximately 1000 OTUs 5 ) and the termite hindgut (800 OTUs and Shannon Index of 5.05 11 ). Compared to our previous community analysis at 120 days 26 , a significant decline in the Clostridiales population and the consequent increase in Bacteroidales and Anaerolineas was noted in the SBR long-term operation at 545 days (this study). Eichorst, M. et al. 27 observed a similar community shift from Firmicutes to a novel Bacteroidetes population in an aerobic thermophilic microbiome that was adapted to microcrystalline cellulose, and they argued that the gradual accumulation of solubilized cellulose after initial hydrolysis was the reason for this trend. In contrast, our annotation-based comprehensive protein database (NCBI nr database) did not disclose the direct metabolism advantage of Bacteroidales or Anaerolineas growing on soluble oligosaccharides ( Figure 4 ). However, since unknown proteins (proteins that cannot be taxonomically classified), especially the beta-glycosidase of GH02 and GH03, played important roles in the oligosaccharide metabolism of the community, we cannot conclude that Bacteroidales or Anaerolineas are unimportant to oligosaccharide consumption. Instead, we observed the strong transcription of putative Sus-like polysaccharide utilization loci (PULs) (with RPKM-RNA comparable to GH09 observed in Clostridiales ) in an unclassified order of the Bacteroidetes phylum following the identification protocol proposed by Rosewarne, C. et al. 28 . This phenomenon not only consolidated the involvement of Sus-like PULs from Bacteroidetes in cellulose-hydrolysis 28 29 but also helped, in part, to reveal that the accumulation of the Bacteroidetes population in this cellulolytic consortia may actually be related to its special cellulose hydrolysis capability. Additionally, we noticed the strong transcription of genes involved in cell protection against oxygen species in Bacteroidales ( Figure 3 ), indicating the ability of this population to grow in a facultative manner. We speculate that temporary oxygen exposure during sample preparation might cause the strong oxidative stress resistance observed in Bacteroidetes . Clostridiales play vital roles in cellulose hydrolysis via cellulosome complexes. The proximity of endocellulases to heat shock protein explains the transcriptional advantage of these cellulases in response to high temperatures ( Figure S4 ). The consistency of this genetic arrangement with that of Clostridium clariflavum DSM 19732 circumscribed the phylogenetic origin of the active Clostridiales as a branching strain of this species. Thermotogales only exhibited an exo-cutting capacity towards the exposed chains produced by endocellulases of Clostridiale s, suggesting their dependency on Clostridiales for carbohydrate metabolism. In return, by expressing beta-glycosidases, both Spirochaetales and Thermotogales could facilitate the microbial uptake of tetrasaccharides and cellobiose, the accumulation of which will otherwise cause strong inhibition on Clostridiales cellulases such as GH48. This synergistic mechanism could explain the earlier observed cellulose degradation enhancement in Clostridium thermocellum when the Spirochaeta phylotypes were present within its environment 30 and help to shed light on the ubiquitous presence of symbiotic Spirochetes in the gut of diverse termites 11 31 . Because the consortium was absolutely predominated by Clostridiales at 120 days of enrichment, which constituted up to 70% of the community, it is reasonable to speculate that the Clostridiales populations contributed the majority of both the hydrolysis and beta-sugar metabolism of the community at this earlier time point. In contrast, a major contribution of beta-glycosidase activity was observed in Thermotogales and Spirochaetales populations within 545 days in the metatranscriptome, suggesting that synergistic effects between cellulose-hydrolyzing Clostridiales and beta-sugar-consuming Thermotogales and Spirochaetales play a critical role over the long-term in the SBR. However, further validation of this hypothesis is required to reveal the dynamics of population involvement in cellulose bioconversion. Additionally, we observed a strong mobility via bacterial flagella in Thermotogales that was consistent with the general cell motility reported in the cellulolytic members of this order 32 33 34 . This increase in the transcription of genes involved in cell motility highlights the importance of physical cell movement in facilitating the capture and breakdown of beta-sugars in Thermotogales . Despite the general absence of hemicellulose substrate, a moderate transcription level of hemicellulases (labeled red in Figure 4 ) in Clostridiales and Spirochaetales was observed. Aside from the rare possibility of being housekeeping genes with expressions that are unaffected by experimental conditions, co-transcription with cellulases was more likely to be the machinery coordinating the hemicellulase regulation of Clostridiales and Spirochaetales populations. The lack of gene clusters for cellulases and hemicellulases 35 had long been regarded as the genetic barrier for these two enzymes to co-transcribe in Clostridiales until the recent discovery of celC–glyR3–licA co-transcription in Clostridium thermocellum 36 . However, this co-transcriptional regulation has never been observed for strains in Spirochaetales before. In the present study, we did not observe genetic clusters consisting of cellulase and hemicellulase on the scaffolds of either Clostridiales or Spirochaetales . Thus, the observed co-transcription pattern of hemicellulases and cellulases in these two populations could serve to consolidate the co-transcription machinery that coordinates hemicellulase activities in these populations. Despite the fact that acetate is always the major intermediate product, the prevalence of exclusively hydrogenotrophic Methanobacteriales over aceticlastic methanogens (primarily Methanosarcinales ) is common in the cellulose-based methanization system 6 37 38 . Previously, the presence of over-competing hydrogenotrophic populations was interpreted as the influence of the inhibitory effect of environmental factors on the activity of the aceticlastic methanogens. Such factors include a high level of ammonia or volatile fatty acids (VFAs), extreme pH values or elevated temperatures 39 40 41 42 . However, our results may overturn this hypothesis because the less prevalent aceticlastic population showed significantly higher overall transcriptional activity in methanogenesis than its hydrogenotrophic counterpart. These findings suggested that the minority of aceticlastic methanogens is not necessarily associated with a repressed metabolism. Instead, we speculate that other overlooked factors, such as a slower growth rate of aceticlastic methanogens, may actually shape the Methanobacteriales -dominated distribution of methanogens in the thermophilic cellulose methanization consortium. This finding also indicates the weakness of studying methanogenesis pathways based on the phylogenetic prevalence of representative methanogens. Hydrogenotrophic Methanobacteriales often co-exist with syntrophic acetate-oxidizing bacteria (SAOB), which facilitate the fermentation of acetate to hydrogen and carbon dioxide. Some researchers claimed that enhanced acetate oxidation by SAOB is crucial for maintaining the effectiveness of this hydrogen-utilizing methanogenesis pathway 43 44 45 ; however, the attempt to enhance hydrogenotrophic methanogenesis via the bio-augmentation of the SAOB population was unsuccessful 43 . Therefore, the synergistic mechanism between Methanobacteriales and syntrophic bacteria remains unclear. Unfortunately, owing to the limited identification of thermophilic SAOB and the lack of known enzymes that are specific to its acetate oxidizing pathway, active SAOB populations could not be clearly identified. However, the active symbiotic involvement of Nitrospirales in methanogenesis suggested that the population actively transcribed CoM-S-S-CoB heterodisulfide reductase, which regenerated coenzyme M and coenzyme B after the final methanogenesis reaction (Step 4 in Figure 5 ). This population also exhibited visible activity towards sulfate reduction, which consumes hydrogen for electrons and thus provides a thermodynamically favorable environment for acetate oxidation to take place 44 45 . By combining NGS-based metatranscriptomics and metagenomics, the present study provides initial transcriptional insights into the expressed biological functions during thermophilic cellulosic biomass methanization. Novel information on phylogeny and the functions of the 40,000 active genes identified in the metatranscriptome highlight the importance of complementary interactions between microbial groups ( Thermotogales, Spirochaetales , and unclassified order of Bacteroidetes and Clostridiales ) for efficient cellulose hydrolysis. More importantly, we observed stronger transcriptional activities in genes that were involved in aceticlastic methanogenesis pathways when the aceticlastic Methanosarcinales are less dominant than their hydrogenotrophic counterparts, Methanobacteriales . This finding contradicts the earlier hypothesis on the repressed activity of aceticlastic methanogens and suggests that the less prevalent aceticlastic populations could play more important roles in cellulose methanogenesis than previously expected. More intensive biological and technical replication is required to reveal whether this is a general pattern in similar systems. Further metatranscriptomic investigation of aceticlastic methanogenesis activity in lignocellulosic biomass methanogenesis systems, especially in the large-scale digesters, could help to better explain the ecological contributions of different methanogens during these processes and eventually provide practical guidelines for microbial manipulation in cellulose decomposition."
} | 3,623 |
25384058 | PMC4226610 | pmc | 5,274 | {
"abstract": "Interactions between species form complex networks that vary across space and time. Even without spatial or temporal constraints mutualistic pairwise interactions may vary, or rewire, across space but this variability is not well understood. Here, we quantify the beta diversity of species and interactions and test factors influencing the probability of turnover of pairwise interactions across space. We ask: 1) whether beta diversity of plants, pollinators, and interactions follow a similar trend across space, and 2) which interaction properties and site characteristics are related to the probability of turnover of pairwise interactions. Geographical distance was positively correlated with plant and interaction beta diversity. We find that locally frequent interactions are more consistent across space and that local flower abundance is important for the realization of pairwise interactions. While the identity of pairwise interactions is highly variable across space, some species-pairs form interactions that are locally frequent and spatially consistent. Such interactions represent cornerstones of interacting communities and deserve special attention from ecologists and conservation planners alike.",
"introduction": "Introduction Spatial turnover of diversity, or beta diversity, has long been recognized as an important part of species diversity [1] – [3] . The beta diversity of a region is high if local sites within the region have unique species compositions so that no single site samples the majority of the total regional diversity. Beta diversity is fundamental to many aspects of diversity in ecological communities and in conservation planning, e.g. when determining the number of protected areas required to achieve biodiversity representation [4] – [6] . Interactions between species are an important, but often ignored, part of biodiversity [7] . Complete diversity assessments, and questions on drivers of diversity, should refer to both species and interactions, but this is still rarely done. Recent studies indicate that we cannot make solid inferences about regional interaction diversity solely from information about species diversity. For instance, Burkle and Alarcón [8] showed that community dissimilarity of plant and pollinator species was highly predictable along an environmental gradient whereas the dissimilarity of the interactions between them was poorly explained. Poisot et al. [9] similarly found no correlation between beta diversity of species and interactions for host-parasite networks indicating that species and interactions are sorted through different mechanisms. Sabatino et al. [10] demonstrated that interaction richness increases twice as fast as species richness with increasing area. Furthermore, interactions between specialists have been shown to be the most vulnerable to habitat fragmentation, while interactions between the core of generalists are more robust [11] . Still, our knowledge of the regional dynamics of interaction diversity, and the relationship between diversity of interactions and species, is in its infancy. Increased knowledge of the drivers of beta diversity of interactions is important to community ecology as it may illuminate what determines the identity of pairwise interactions and whether they are predictable from the composition of species, but it may also guide conservation planning by aiding the understanding of ecosystem functioning and interaction-based ecosystem services [12] . Mutualistic networks consist of two interacting communities and, consequently, their interactions are often analysed using a bipartite network approach [13] . Such networks consist of two types of nodes, e.g. plants and pollinators, connected by links. Detailed structures of pollination networks, such as species degree, core composition, and the identity of pairwise interactions, are highly dynamic over time [8] , [14] – [20] . This variation is caused by temporal differences in species composition and phenology [15] – [18] , [21] but also by a strong lability in the identity of pairwise species interactions, i.e. interaction rewiring [18] , [22] . Interactions are temporally constrained if phenologies of potentially interacting species are decoupled, but they may also be spatially constrained [23] . One obvious reason is the turnover in species composition, i.e. spatial species-driven interaction turnover. However, a pair of species interacting in one area might be present in another area without interacting, i.e. spatial interaction rewiring (see [19] for a similar distinction in studies of temporal interaction turnover). Poisot et al. [9] propose that the overall dissimilarity in interactions between networks is the sum of the dissimilarities caused by species turnover and interaction turnover (i.e. interaction rewiring). In the current study, we focus on the interaction turnover component. This variability in species interactions is not well studied but recent progress has identified potential drivers. First, species abundance affects the probability of interactions [24] . Neutral theory states that individuals interact randomly and that species interact with a probability determined by their abundance product [25] . Because population densities determine the probabililty of pairwise species encounters, relative abundances ultimately determine the realization of pairwise interactions. Second, when species meet, trait matching will constrain or promote the realization of pairwise interactions [23] , [26] . Compatibility of traits between species can be viewed quantitatively rather than purely qualitatively, and species with highly matching traits will likely interact with higher probability than species with poorly matching traits. Traits may also vary within-species across populations, increasing interaction turnover across space [27] . Finally, the local realization of pairwise interactions might be affected by competitive or facilitative effects from other species or interactions. Such mechanisms will potentially create complex community effects which are not easily tested. Network structure is determined by the combined effects of neutrality and trait matching [21] , [28] but as drivers of interaction turnover they have not been properly tested. Here, we quantify the spatial turnover in plant-pollinator interaction networks by examining the beta diversity of species and interactions between network pairs across seven sites. Then, we restrict the analysis to the shared networks between sites (i.e. only including shared species, see Figure 1A ) and test the effect of interaction properties and site characteristics upon interaction turnover. Specifically we ask: 1) to what extent beta diversity of plant species, pollinator species, and interactions follow similar trends across space, and 2) which interaction properties and site characteristics are related to the probability of turnover of pairwise interactions across space. That is, when looking at each specific interaction between species pairs shared between two or more sites, can we then determine which interactions are more likely to turn over and under which conditions? 10.1371/journal.pone.0112903.g001 Figure 1 Site-pair comparison and interaction specific site-pair combinations. A) Site-pair comparison. Site 1 and 2 each have unique plants and pollinators. The central square represents the interaction-matrix between shared species. Here, six interactions are present in both sites (interaction consistency, filled squares) and six interactions are only observed in one of the two sites (interaction turnover, open squares). Unique species to either site 1 or 2 were discarded and only the central matrix was used for analysing the turnover of pairwise interactions. B) Interaction specific site-pair combinations. This (hypothetical) interaction is observed at sites 1 and 6 (filled squares) while the species pair is also present at site 3, however without interacting (open square). One or both species are absent from the remaining sites (in grey) and they are excluded from the analysis for this particular interaction. Three site-pair combinations are possible in this case; 1↔3 and 6↔3: interaction turnover and 1↔6: no interaction turnover (interaction consistency). On larger spatial scales, increasing dissimilarity between communities with increasing geographical distance, i.e. distance decay, is a well-documented pattern with respect to species composition [29] and has been shown once also for food webs [30] . The pattern, however, seems to become less clear at smaller spatial scales (1–3 km) and is thus far poorly explored with respect to interactions (but see [8] ). Although Burkle and Alarcón [8] found no correlation between distance and species and interaction similarity across pollination networks, Dáttilo et al. [31] found a decreasing similarity in ant and plant composition with increasing distance. Thus, we expect a positive correlation between geographical distance and turnover of species. While species and interactions could be sorted through different mechanism [9] we also expect a positive correlation between geographical distance and interaction turnover, although the predictability may be lower. For our second question we focus on two interaction properties: average interaction frequency and interaction generalization, and three site characteristics: local flower abundance, local network species richness, and geographical distance between sites. Average interaction frequency measures the average frequency of a given pairwise interaction when both species are present. We argue that this is a good proxy for trait complementarity and behavioural preferences between species pairs. Lacking detailed information on species-specific traits, and how they would combine in the given system, interaction frequency is likely an outcome of such mechanisms [27] . We expect average interaction frequency to be negatively correlated with the probability of turnover. Interaction generalization is a measure of the generalization level of the species pair forming the interaction in question. Ecological specialization, i.e. the use of a relatively small proportion of the available interaction partners [32] , [33] , is likely connected to less promiscuity, and thus a higher consistency of interactions between more specialized species can be expected [34] , [35] . Flower abundance has repeatedly been shown to be important to determine network structure [21] , [24] , [36] – [40] , and we expect a change in local flower abundance between sites to influence interaction turnover so that a decrease in flower abundance of a given plant species will lower the probability that pairwise interactions, involving the same plant species, are realized. Finally, as explained above, different mechanisms of interference from other species might promote interaction turnover. We therefore expect that species richness of a given site can affect the realization of pairwise interactions by altering the competitive or facilitative context. Predicting the direction of such an effect is problematic as it is likely highly system-specific. However, recent experimental work on plant-pollinator systems indicates that an increase in species richness could increase the probability of turnover of interactions [41] . We show a positive correlation between geographical distance and beta diversity of species and interactions. Our findings indicate that the identity of pairwise interactions is highly variable across space, but that local flower abundance is important for the realization of interactions. Furthermore, those pairwise interactions that are locally frequent will also tend to be consistent across space if no temporal or spatial constraints are imposed on the species. These interactions could be of key importance for species in obligate or facultative mutualisms and form consistent elements in otherwise highly variable interaction networks.",
"discussion": "Discussion Pairwise interactions, the fundamental component of complex ecological networks, have proven difficult to predict [8] , [50] . We find that pairwise interactions are indeed highly variable across space, but that some types of interactions are more predictable than others. Pairwise interactions that are locally frequent are more consistent across space. We further show that the probability, for a pairwise interaction to be realized, is increased with the local abundance of the plant species forming the interaction. Finally, increased geographical distance between sites significantly increase beta diversity of plant species and interactions and the probability of turnover of pairwise interactions. As expected, interactions that were locally more frequent showed a lower turnover across sites. Such interactions can be interpreted as linking species of high mutual affinity; if no spatial or temporal constraints are imposed, these species pairs will likely interact, and likely with a high frequency. Such strong interactions are of principal importance in plant reproduction locally [38] . Our results demonstrate their regional importance as interactions that link sites across campos rupestres landscape. These interactions represent spatially consistent elements across interaction networks. Hyperdominant species represent a defining set for a biome or a region and will account for a large proportion of the processes within a given system [51] . Understanding this small fragment of the existing diversity will thus greatly increase the understanding of the system. We have here taken a first step towards identifying a set of interactions that in a similar manner is defining for a region. While the effect of abundance on nestedness, asymmetry, species degree, and other network properties in plant-pollinator networks is well documented [21] , [28] , [37] , [38] , the effect of flower abundance on the realization of pairwise interactions is hitherto poorly tested. We show that the probability for a given pollinator to interact with a given plant species depends upon the resource level that the plant is offering at a given site. Flower abundance affects pairwise interactions by increasing the attractiveness of plants with many flowers (i.e. increased resource levels), and hereby influencing behavioural decisions by pollinators. Additionally, abundance affects species' encounter probabilities and such neutral factors have earlier been shown to influence interaction patterns [24] , [39] . Interaction strength is directly affected by relative abundances [24] but as we have shown here, interactions may also be entirely lost or gained over space as a function of varying abundances. Negative difference in abundance increases the probability of interaction loss by introducing “neutral forbidden links” [52] . That is, because of low abundances, co-occurring rare species might be constrained from interacting, in spite of otherwise complementing traits. In a strict neutral approach, species identities do not matter – relative abundances alone determine interaction probability [25] . In reality, encounters may be stochastic, but certain species will be more likely to interact if they meet. The strong affinities between certain pairs of species, here indicated by the negative relationship between average interaction frequency and turnover probability, are likely a function of trait complementarity. Beta diversity of interactions and species were related to geographical distance in a similar positive manner. Plant species not only showed overall higher beta diversity than pollinators; plant beta diversity, contrary to that of pollinators, was significantly correlated with geographical distance. Pollinators are mobile and, all else being equal, will show higher dispersal capabilities in ecological time possibly explaining the lower, and less distance-dependent, beta diversity of pollinator species compared to plants. A similar pattern has been shown for herbivores and their plant hosts [30] . Beta diversity of interactions between shared species (β OS ) also showed a significant correlation with geographical distance, suggesting that species in neighboring sites are more likely to display similar interaction behaviors compared to species from distant sites. Such a significant relationship has, to our knowledge, not been found earlier. Geographical distance also had a significant effect on the probability of turnover in our model, reaffirming the correlation between β OS and geographical distance. It should be noted, however, that in both cases correlations were significant, but not strongly so. Thus, geographical distance alone explains little of the variation in interactions across space. A combination of subtle variation in community and landscape properties which are spatially autocorrelated could be the cause of the distance effect on interaction turnover. Interaction generalization (i.e. the mean generalization level of the species involved in a particular interaction) showed no significant effect on the probability of turnover of pairwise interactions. Species with few local interaction partners might indeed appear as specialists, however, interactions between these species were not more consistent across space. Thus specialized interactions (least generalized) might not actually be between specialist species per se , but simply between species with few local interaction partners which might change across sites. Network species richness neither had any significant effect on the turnover of pairwise interactions. Instead, complex synergistic effects of different community and landscape properties will have to be included in order to discover more deeply the mechanisms behind the detailed patterns of pairwise interactions. High levels of endemism and extremely narrow distributional ranges of some species [42] make campos rupestres a unique but also fragile habitat. Campos rupestres are under threat from several human activities such as mining, cattle ranching, wood extraction, cultivation, and road construction [43] . Here we confirm the high heterogeneity of species composition across campo rupestre habitat and further show an equally high turnover of plant-pollinator interactions. While plants in campos rupestres are spatially constrained and distributed in local patches, pollinators disperse freely between these patches. Pollinators could thus function as spatial couplers of otherwise disjunct plant populations and be very important to gene flow between local plant populations; a subject worthy of further study. These findings indicate that conservation management in campos rupestres will likely need to consider the protection of a large network of reserves, i.e. a metanetwork [7] , in order to maximize representation of species and processes [6] . Future work on interactions could focus on the turnover of functional groups instead of taxonomic species. Perhaps species traits are better predictors of pairwise interactions than actual species identities (e.g. [53] ). Trait information could increase our knowledge on which interactions are the most consistent and why, and reveal which, if any, interactions are truly obligatory [28] , [36] . We have quantified the beta diversity of interactions across space and investigated the turnover of each pairwise interaction. Beta diversity of interactions is generally high and the identity of pairwise interactions is highly variable across space. A large part of the pairwise interactions constituting plant-pollinator networks seems to be partly random encounters and/or opportunistic interactions whose identity is largely determined by local species abundances. However, pairwise interactions that are locally frequent will tend to be consistent across space if no temporal or spatial constraints are imposed on the species. Thus, beneath the large variation and diversity across space, some species form interactions that are more consistent and predictable. Such interactions represent cornerstones of interacting communities and deserve special attention from ecologists and conservation planners alike."
} | 5,063 |
34276632 | PMC8281973 | pmc | 5,275 | {
"abstract": "There are still many challenges to overcome for human space exploration beyond low Earth orbit (LEO) (e.g., to the Moon) and for long-term missions (e.g., to Mars). One of the biggest problems is the reliable air, water and food supply for the crew. Bioregenerative life support systems (BLSS) aim to overcome these challenges using bioreactors for waste treatment, air and water revitalization as well as food production. In this review we focus on the microbial photosynthetic bioprocess and photobioreactors in space, which allow removal of toxic carbon dioxide (CO 2 ) and production of oxygen (O 2 ) and edible biomass. This paper gives an overview of the conducted space experiments in LEO with photobioreactors and the precursor work (on ground and in space) for BLSS projects over the last 30 years. We discuss the different hardware approaches as well as the organisms tested for these bioreactors. Even though a lot of experiments showed successful biological air revitalization on ground, the transfer to the space environment is far from trivial. For example, gas-liquid transfer phenomena are different under microgravity conditions which inevitably can affect the cultivation process and the oxygen production. In this review, we also highlight the missing expertise in this research field to pave the way for future space photobioreactor development and we point to future experiments needed to master the challenge of a fully functional BLSS.",
"conclusion": "Conclusion Bioregenerative life support systems are complex networks of biological and physicochemical transformations, including bioreactors, whose functioning are influenced by space environment like reduced gravity levels and increased doses of ionizing radiation. As a consequence, several biological and physical key bioreactor processes have to be controlled and adapted to these altered conditions by, for example, the usage of membrane-aerated PBRs. In practice, recent flown experiments have shown the challenge linked to the deployment of a successful PBR in space. Further knowledge is therefore needed to improve the necessary success rate that will allow continuous operation at a larger scale. In general, more long-term continuous experiments should be conducted and all important parameters (temperature, gas exchange rates, light intensity, concentration of nutrients and biomass production) have to be monitored online, allowing remote bioreactor control from Earth, to reduce the dependence on the crew. Even though many promising experiments on photobioreactors for space applications were conducted, the development of a sufficient life support system still depends on an interconnected, continuously running loop system with a maximum closure.",
"introduction": "Introduction Human space exploration aims to go farther into space and crewed missions are planned to Moon and Mars. The European Space Agency (ESA) as well as the National Aeronautics and Space Administration (NASA) plan human missions to Mars in the coming decades ( Hufenbach et al., 2014 ; Anderson et al., 2019 ). The space travelers need oxygen, fresh water and nutritional food to survive on such space missions ( MacElroy and Bredt, 1984 ) and the supply has to become independent from Earth. In order to minimize the resupply needs and the embarked mass, the recycling process will have to include food production coupled to oxygen (O 2 ) and water (H 2 O) recovery that entails the use of at least one biological compartment for producing edible biomass. This challenge can be solved by the development of a bioregenerative life support system (BLSS), that meets the needs at least for a part of food supply to the crew and secures air, water as well as safe waste recycling ( Gitelson et al., 1976 ). This review will focus on the bioprocess of microbial photosynthesis and, in particular, on photobioreactors (PBRs) used in space for BLSS. Moreover, we focus on the process of air revitalization, meaning the efficient removal of carbon dioxide (CO 2 ) and production of O 2 . The goal of this study is to give an overview of the experiments that have been conducted with liquid cultures of photosynthetic microbes and PBRs for application in space, and to highlight similarities and common challenges. Hereby, the last 30 years will be focused. Additionally, missing data and suggestions on future experiments will be discussed. The following sections describe the general requirements for life support systems and the current state of the art to how a BLSS can be developed using different techniques and organisms.",
"discussion": "Discussion In this section, we highlight the different challenges in context of PBR for space applications in order to give an overview of knowledge gaps and problems that already occurred or might arise in the future of BLSS research. Safety and Reliability – Robustness, Resilience, and Redundancy The safety and reliability of a life support system is of utmost importance. In order to avert fatal incidents, several back-up facilities and control mechanisms have to be installed and the system has to be monitored consistently. All possible scenarios have to be calculated and evaluated beforehand to avoid failure, because failure can be fatal for the crew ( Bartsev et al., 1996 ). For example, a failure in O 2 production has to be intercepted by an emergency system before a drop in the O 2 concentration of the cabin occurs. A high degree of redundancy has to be achieved. Physicochemical emergency back-up systems, plant compartments and different PBRs could be put in parallel that can be uncoupled from each other. And not all bioreactors need to be operated in long duration continuous production, but a regime of alternating batches or operation and downtime of bioreactors could be implemented, if shown to be advantageous for operation, harvesting or maintenance. In addition, reliable mathematical models for the bioreactors are essential to keep all processes predictable ( Vernerey et al., 2001 ). This is a highly strategic point when the recycling efficiencies of different elements and compounds are coupled and intertwined as it is the case for BLSS, such as MELiSSA. In this case, the action on an operational variable has distributed consequences at several points of the recycling system, calling for an intelligent control strategy based on knowledge models taking into account the dynamic exchanges between the different parts of the recycling system. The other important point for life support systems for space is that the buffer tanks generally have a minimal capacity entailing an online control strategy. The criteria for reliability, availability, maintainability and supportability (RAMS) engineering have to be applied in the BLSS research. Gas Exchange and O 2 /CO 2 Balance Between Consumer and Producer As mentioned, on average, one human needs ∼0.82 kg of O 2 and produces ∼1.04 kg of CO 2 per day. Depending on the activity level, the ratio of exhaled CO 2 to consumed O 2 , i.e., the respiratory coefficient, can vary ( Anderson et al., 2018 ). On the other hand, the O 2 production of algae and cyanobacteria can be characterized by a photosynthetic coefficient, describing the ratio of produced moles of O 2 per consumed moles of CO 2 . This ratio is dependent on the organism (and its biochemical composition) and the nutrient substrate (e.g., the nitrogen source). The stoichiometric eqs. 3, 4 [simplified from Cornet et al. (1998) ] show this dependence for Limnospira indica on the examples ammonium (NH 3 ) and nitrate (NO 3 – or here: HNO 3 ) as nitrogen sources. Solving the stoichiometric equations reveals that the photosynthetic coefficient for ammonium is ∼1.0 and for nitrate ∼1.4. (3) C O + 2 0.528 H O 2 + 0.173 N H + 3 n h ν → C H O 1.575 N 0.459 0.173 \n + 1.034 O 2 (4) C O + 2 0.701 H O 2 + 0.173 H N O + 3 n h ν → C H O 1.575 N 0.459 0.173 \n + 1.381 O 2 Importantly, it must be outlined that photosynthetic growth stoichiometry has no degree of freedom when the composition of nitrogen source (or its degree of reduction) is fixed so that the photosynthetic coefficient is only depending and linked to the culture conditions. The number of photons required to fix 1 mol of carbon is depending on the culture conditions. Away from photo inhibition conditions, a typical value is n = 20 mol photons per mol of carbon fixed ( Cornet and Dussap, 2009 ; Poulet et al., 2020 ). In order to avoid an imbalance in gas composition, a system has to be developed to combine the respiratory quotient of the crew members and the photosynthetic coefficient of the microalgae. In some experiments, successes were achieved (see section “Photosynthetic Microorganisms as Catalysers for Air Revitalization in Space”). However, gas exchange in space is much more complex, due to the lower or lack of gravity. There is still very little information about the gas, water and solute transport in microgravity in living organisms. Moreover, microgravity conditions strongly modify the environment of the chemical and biochemical processes, e.g., implying lack of sedimentation and impaired gas and liquid phase separation. Consequently, transport is limited to diffusion causing an increase of boundary layer thickness and therefore a significant decrease of mass and heat transfer coefficients. This can cause problems with pumping and the mineral availability for the cultures and has to be elucidated more thoroughly ( Klaus et al., 1997 ). In situ Resource Utilization and Light as an Energy Source Another challenge is the complete closure of a BLSS. So far, no loop has an efficiency of 100%, which means that all tested life support systems still rely on external addition of different substances like carbonate or trace elements, etc. For example, the 105 days long Lunar Palace 1 experiment (plants, insects, and three crew members) reached a full oxygen and water recycling but only 20.5% nitrogen recovery from urine and 55% of the food was regenerated. In this approach, physico-chemical and biological processes were combined ( Fu et al., 2016 ). Some substances are either difficult to find in the space environment or it is very costly and time consuming to convert them into a usable form. Therefore, space habitats for humans have to be fully functional under the specific conditions and have to rely on the materials available around and only a small amount of material brought from Earth. For example, lunar regolith, mars soil and CO 2 in the Martian atmosphere are promising substances to be used for in situ resource utilization (ISRU) ( Montague et al., 2012 ; Muscatello and Santiago-Maldonado, 2012 ). The usage of photoautotrophic organisms helps to overcome parts of the material problems because their main energy source is light. But so far, only experiments using artificial light (e.g., halogen lamps or LEDs) have been flown ( Table 4 ) which means that the naturally available solar energy is not used directly so far. One of the main reasons is that the natural light intensities and spectral energy distributions available in space are not compatible with the needs of the photosynthetic organisms. The intensity of sun light depends on the distance from the sun and the irradiation spectrum in deep space consists of a different wavelength composition than the irradiation we experience on ground due to absorption of light in the Earth’s atmosphere ( Cockell and Horneck, 2001 ). Besides that, the ISS, Moon and Mars surface are eclipsed for 50% of the time and the day and night cycles, e.g., on the moon are very different from Earth. For example, one lunar night is as long as 18 Earth days ( Alvarado et al., 2021 ; Xie et al., submitted) 1 . Also, the intensity of natural light sources is much more difficult to be controlled than artificial light sources. Therefore, approaches where solar power is used to store energy in batteries as fuel for LEDs with suitable light characteristics, that can be used in PBRs and greenhouses, are desired. Scaling Up So far, the research on the PBR part of the BLSS is the most sophisticated area. But also in the PBR research, most experiments were done in lab up to pilot scale (100 mL up to 83 L, Tables 1 – 4 ) and these volumes were not sufficient to provide 100% of the O 2 need of a crew member ( Javanmardian and Palsson, 1992 ; Alemany et al., 2019 ). So even if a small lab scale bioreactor is successful, scaling-up procedures have to follow to achieve the needed production rates for a BLSS, which vary strongly depending on the used organisms ( Vernerey et al., 2001 ). In order to develop a reliable system, the PBR needs to represent a well-balanced combination of a relatively small, but sufficient volume and high productivity via usage of proper illumination in high cell density cultures. Connecting Multiple Bioreactors and Closing the Loop Only a few experiments involve bioreactors that are connected to other life support compartments like the crew or a waste recycling compartment. Consequently, many challenges remain in this research area and the connection between the different systems has to be elucidated more. Additional experiments on the nitrifying community and the other parts of the waste treatment (e.g., thermophilic anaerobic bacteria to produce volatile fatty acids out of waste) have to be conducted in space and further developed on ground ( Lasseur et al., 2010 ). Some unidentified problems might arise in connected bioreactors. Cross-contamination and cross-talking of the organisms by quorum sensing molecules between the different compartments might disturb the system on a long-term scale ( Mastroleo et al., 2013 ). However, also in axenic bioreactors, there is missing knowledge about cell-cell communication and biofilm formation in space. Long Duration Cultivation in Engineered Bioreactors and Space Conditions The following question has to be answered: does a long-term cultivation in engineered bioreactors under space conditions have an effect on the microorganisms? A predictable and stable growth rate of the culture is essential for the performance of a PBR. Early stress signals have to be monitored to avoid culture failure in space and adequate countermeasures have to be developed. For this, low-dose prolonged irradiation and (simulated) microgravity experiments are needed. The genetic stability over multiple generations has to be addressed, e.g., the mutation rates, differences in gene expression and epigenetic effects like changes in DNA methylation patterns. So far, not enough experiments on long term conduction of photobioreactors were done, to answer that question. The effect of cosmic irradiation and reduced gravity on the oxygen production rate and nutritive value of the photosynthetic microorganisms has to be investigated. In plant experiments, it was reported that low doses of ionizing irradiation can cause an increase in growth rate ( Sax, 1963 ; Upton, 2001 ), but for algae and cyanobacteria very limited data are available so far. Planel et al. (1987) presented a hormesis effect for the cyanobacterium Synechococcus lividus when irradiated with 1.49 mGy per year. If proven for BLSS relevant organisms, such hormesis effects might even be useful for the BLSS productivity. Most space experiments with living organisms have only been done in LEO so far. There are very few reports of microbial experiments that went out of LEO ( Horneck et al., 2010 ). One of the rare examples is the Chinese lunar chang’e 4 lander that brought organisms (plants, yeast and fruit fly eggs) farther into Space (Xie et al., submitted, see text footnote 1). Therefore, future investigations need to be beyond LEO, and e.g., in Moon orbit or on the Moon surface. Also, insightful investigations remain to be systematically done in order to detail and understand the mechanisms of interaction of zero-gravity conditions and different levels of intracellular organization and metabolic regulation. By example, it is well-known that gravitropism is an important phenomenon for higher plants growth and roots development. Similar effects are likely to occur even in simpler prokaryotic organisms linked to dissolved gas exchanges (namely O 2 and CO 2 ) between intracellular level and the culture environment. Remote Commanding, Monitoring, Reporting, and Data Exploitation During literature research, it became apparent, that the published data often do not include all needed information. Especially the light intensity inside the culture, temperature and pH data are often missing. Furthermore, the data of space experiments are deficient and often difficult to compare. For example, different sizes for different missions were used ( Table 4 ) and the space experiments were mainly to investigate on exposure, survival and simplified processes. Also, only very few experiments with on-board monitoring can be found in the literature [e.g., ArtEMISS-B described in Poughon et al. (2020) ]. Real-time bioprocess monitoring has to be achieved to obtain reproducible and reliable results."
} | 4,262 |
28913428 | PMC5590788 | pmc | 5,276 | {
"abstract": "Stretchable rubber-like electronics from intrinsically stretchable semiconductors and conductors are demonstrated.",
"introduction": "INTRODUCTION The past decade has witnessed significant advancements in stretchable electronics. Owing to its superior mechanical characteristics (that is, soft, bendable, stretchable, and twistable), stretchable electronics hold promise in health monitors ( 1 , 2 ), medical implants ( 3 – 5 ), artificial skins ( 6 – 8 ), and human-machine interfaces ( 9 , 10 ). To date, most electronic materials, especially semiconductors, including inorganics (such as Si and GaAs) and organics [such as poly(3-hexylthiophene-2,5-diyl) (P3HT) and pentacene], are mechanically nonstretchable ( 11 , 12 ). To enable mechanical stretchability in electronic devices, special mechanical structures or architectures have generally been used to accommodate or eliminate mechanical strain in nonstretchable materials while stretched. Examples of these structures include out-of-plane wrinkles ( 13 ), in-plane serpentines ( 14 ), rigid islands with deformable interconnects ( 15 , 16 ), and kirigami architectures ( 17 – 19 ). An alternative route to eliminating the burden of constructing dedicated architectures and the associated sophisticated fabrication processes is to build stretchable electronics from intrinsically stretchable electronic materials, which have potential toward scalable manufacturing, high-density device integration, large strain tolerance, and low cost ( 11 , 20 ). Although conductors that are intrinsically stretchable have been reported extensively ( 21 ), semiconductors that are intrinsically stretchable have been a general challenge. Existing ways of improving stretchability in semiconductors include using conjugated polymer nanowire and nanofibril networks ( 22 – 24 ) and microcracked films ( 25 ). However, their mobilities are generally very low. Recently, stretchable polymer semiconductors with relatively high mobilities and the associated thin-film transistors (TFTs) have been successfully demonstrated from dedicated polymer and nanostructure designs ( 26 , 27 ). Here, we report highly stretchable electronics and sensors that are made of intrinsically stretchable composite semiconductors and conductors. Specifically, we exploit P3HT nanofibril (P3HT-NF) percolated polydimethylsiloxane (PDMS) rubber composite as a stretchable semiconductor, Au nanoparticles with conformally coated silver nanowires (AuNP-AgNW) dispersed within PDMS as a stretchable conductor, and ion gel as a gate dielectric. In particular, instead of creating novel polymers for stretchable semiconductors, which heavily require sophisticated molecular design and synthesis, we use all commercially available materials as precursors to achieve highly stretchable semiconductors that can be manufactured in a repeatable and scalable manner and have stable performances. The P3HT-NF percolated PDMS rubber composite maintains semiconductor characteristics under 50% mechanical stretching along and perpendicular to the channel length directions. Simple solution processes are used to form thin films to construct stretchable devices, including TFTs and sensors, without any additional structural design to achieve large mechanical stretchability. Examples of intrinsically stretchable electronics that have been exploited include stretchable ion gel–gated TFTs and strain, pressure, and temperature sensors. The ion gel–gated TFTs exhibited a field-effect mobility (μ FE ) and an on/off ratio ( I ON/OFF ) of 1.4 cm 2 /V∙s and 5.6 × 10 3 , respectively. While the mobility achieved a high value for the stretchable organic format of semiconductors, it only has a moderate decrease of less than 45% under 50% mechanical stretching. We demonstrate the application of these intrinsically stretchable electronics as multifunctional artificial robotic skins that can translate hand motions and gestures to provide haptic sensing capabilities.",
"discussion": "DISCUSSION The elastomeric composite semiconductors and conductors in this work enable a class of stretchable electronics and sensors that are intrinsically highly stretchable without any requirement for additional mechanical structure designs for traditional nonstretchable semiconductors. The elastomeric composite semiconductor of P3HT-NF/PDMS can all be created from common and commercially available materials. We demonstrate that stretchable electronics and sensors can also be created with simple fabrication steps by using these stretchable electronic materials. Our results show that intrinsically stretchable transistors remain functional while stretched by 50% and the elastomeric composite semiconductor achieves very high mobility while moderate mobility decrease is observed, that the strain sensors operate in a stable manner while achieving the highest GF for large level strains, that the pressure and temperature sensors show reliable performances, and that the intrinsically stretchable electronics and sensors can be used as smart skins for robotics. We foresee that this strategy of enabling elastomeric semiconductors by percolating semiconductor nanofibrils into a rubber will advance the development of stretchable semiconductors, and the approach to constructing electronics and sensors all from elastomeric electronic materials will move forward the advancement of stretchable electronics for a wide range of applications, such as artificial skins, biomedical implants, and surgical gloves."
} | 1,367 |
34777926 | PMC8579420 | pmc | 5,278 | {
"abstract": "Increasing energy\nautonomy and lowering dependence on lithium-based\nbatteries are more and more appealing to meet our current and future\nneeds of energy-demanding applications such as data acquisition, storage,\nand communication. In this respect, energy harvesting solutions from\nambient sources represent a relevant solution by unravelling these\nchallenges and giving access to an unlimited source of portable/renewable\nenergy. Despite more than five decades of intensive study, most of\nthese energy harvesting solutions are exclusively designed from ferroelectric\nceramics such as Pb(Zr,Ti)O 3 and/or ferroelectric polymers\nsuch as polyvinylidene fluoride and its related copolymers, but the\nlarge implementation of these piezoelectric materials into these technologies\nis environmentally problematic, related with elevated toxicity and\npoor recyclability. In this work, we reveal that fully biobased non-isocyanate\npolyurethane-based materials could afford a sustainable platform to\nproduce piezoelectric materials of high interest. Interestingly, these\nnon-isocyanate polyurethanes (NIPUs) with ferroelectric properties\ncould be successfully synthesized using a solvent-free reactive extrusion\nprocess on the basis of an aminolysis reaction between resorcinol\nbis-carbonate and different diamine extension agents. Structure–property\nrelationships were established, indicating that the ferroelectric\nbehavior of these NIPUs depends on the nanophase separation inside\nthese materials. These promising results indicate a significant potential\nfor fulfilling the requirements of basic connected sensors equipped\nwith low-power communication technologies.",
"conclusion": "Conclusions Fully biobased NIPUs\nhave been successfully synthesized using a\nsolvent-free process. REX allowed to synthetize NIPUs by avoiding\nthe difficulties related with heat and mass transport due to the high\nviscosity, typically observed in their batch-type syntheses. The molecular\narchitecture of the obtained NIPUs has been designed to show a final\npolar structure and consequently to get the ferroelectric-like behavior.\nUsing resorcinol bis-carbonate and cadaverine as monomers, a NIPU\ncharacterized by high T g and a permanent\ndipolar moment has been obtained. Although the obtained NIPUs were\ntotally amorphous, AFM characterization showed their phase-separated\nnanostructurations. Depending on the processing method, RBC–CAD\nshowed different nanostructuration, as ordered needle and lamellar\nnanostructure, when it was processed by drop casting method and by\ncompression molding, respectively. The nanophase separation has been\nascribed to the high level of interurethane hydroxy hydrogen bonding\npresent in the hard segment of NIPUs as it was evidenced by performing\nAFM as a function of temperature. Adding a biobased diamine oligomer\nas a chain extender, the flexibility of the molecular architecture\nwas increased and the phase compatibility as well, maintaining the\npolar structure. Macroscopic ferroelectric switching was achieved\nfor sample RBC–CAD-bioATO, and piezoelectric activity demonstrated\nto be a behavior that can be tuned by changing the NIPU molecular\narchitectures, being potential candidates for emerging applications\nlike in energy harvesting and can enable the design of self-powered\ndevices such as follow-up medical devices, despite the low piezoresponse\nobtained (2 pC N –1 ). We believe that these materials\nafford a real response to the large demand to implement sustainable\nenergy harvesters, while affording environmentally friendly materials.\nMoreover, RBC–CAD and RBC–CAD-bioATO are promising materials\nfor the processing of biobased polymer–ceramic composites with\nenhanced piezoelectric response, being a greener and sustainable alternative\nto piezoceramics.",
"introduction": "Introduction Our\nlast decades were being driven for the continuous search of\nmore sustainable alternatives to reduce the overconsumption of fossil\nfuels, relating to the global warming. Renewable energy sources such\nas wind and solar energies can represent a relevant option to overcome\nthis issue but are not sufficient to fully support the global energy\ndemand in the upcoming decades. Considering these factors, academic\nand industrial researchers are now pushing to develop advanced energy\nharvesting technologies from wasted energy sources as an alternative\nto the aforementioned issues. 1 In\nthis context, piezoelectric materials are expected to emerge\nas one of the most important functional materials for the energy harvesting\nsector. 2 , 3 Piezoelectric materials are able to convert\nthe mechanical energy to electrical signals, named the direct piezoelectric\neffect also known as generator or transducer effects, as well as the\nopposite, called the converse piezoelectric effect also known as motor/actuator\neffects. 1 , 4 Interestingly, the energy harvesting with\nsuch materials represents the most suited solution to power electronic\ndevices of low voltage such as wireless sensors, portable devices,\nand medical implants, particularly in Internet of things (IoT). 4 They can even represent a unique solution in\nmany applications like sensors installed in remote locations or inside\nthe human body in which external intervention to replace these devices\nafter their service remains difficult or even impossible. 5 In this respect, piezoelectric energy harvesters\nprovide the best promises because they can generate elevated electrical\nenergy density that can be readily stored in any battery-related system.\nIn addition, the high flexibility of some piezoelectric materials\nallows them to be readily downsized into miniaturized devices. 6 In general, piezoelectric materials can be divided\ninto four main categories depending upon their microstructural characteristics:\nceramics, single crystals, polymers, and composites. 7 Among them and related with economic and environmental\nissues, 8 piezoelectric polymers afford\nseveral advantages\nbecause they are easily processable on a large scale and can be readily\ndesigned in different shapes and useful objects like thin films. Moreover,\nthey are flexible, lightweight, and show interesting mechanical properties\nwhen compared to extremely fragile ceramic materials. Even though\nthe piezoelectric performance of polymers remains lower than that\nof ceramics, they have much higher piezoelectric voltage coefficients,\nbeing very interesting in the case of sensing applications. 5 , 9 The piezoelectric effect in these polymers is mainly due to\ntheir\nspecific (macro)molecular structure that can be achieved in amorphous\nand semi-crystalline materials. 10 Even\nif they are characterized by different mechanisms, giving rise to\npiezoelectricity, four critical features must be present within all\nthese piezoelectric polymers. These are (1) the presence of permanent\nmolecular dipoles, (2) the ability to orient or align the molecular\ndipoles, (3) the ability to fix this dipole alignment once it is achieved,\nand (4) the ability of the material to undergo large strains when\nmechanically stressed. 11 Semi-crystalline\npolymers contain a polar polymorphic crystalline\nphase that can be readily orientated by poling treatments, leading\nto the piezoelectric effect. In the case of amorphous polymers, they\nhave to be of vitreous nature and contain within their macromolecular\nstructure an elevated number of molecular dipoles, which might be\naligned and fixed to give rise to piezoelectricity. 12 Polyvinylidene fluoride (PDVF) and its copolymers\nrepresent the\nbest examples of ferroelectric semi-crystalline polymers with excellent\npiezoelectric and pyroelectric properties, 13 − 16 but they are not considered as\ngreen as their sourcing and production are both impactful. 17 Therefore, other types of polymers have been\nextensively investigated in the last decade and significant efforts\nare more and more being focused on sustainable and environmentally\nfriendly ferroelectric polymers. Among them, polyurethanes (PUs) represent\nthe most versatile polymers nowadays. 2 , 18 − 21 They are the sixth most widely used polymers being applied in many\nindustrial fields with a variety of physical, chemical, and interesting\nelectroactive properties. The structural and ferroelectric properties\nof aliphatic PUs were first reported by Tasaka et al., 22 and it was suggested that ferroelectricity was\noriginated from the hydrogen-bonded crystalline regions. On the other\nhand, amorphous aromatic PUs have also been claimed to be ferroelectrics,\nwhose origin was attributed to dipole motions in the hydrogen-bonded\namorphous phase, that can be frozen below T g . 12 , 23 , 24 This is even\nhigher compared that of aliphatic PUs due to the chain stiffening\nwith bulky phenyl groups. Despite the large number of applications\nof PUs, increasing concerns related to the toxicity of isocyanate\nmonomers currently used for their synthesis, moisture sensitivity,\nand sustainability have stimulated the search for sustainable and\nalternative synthetic strategies for these materials. 25 Non-isocyanate PUs (NIPUs) produced from cyclic carbonate\naminolysis\nare materials with high potential to replace traditional PUs. 26 , 27 Despite being promising, NIPUs suffer from some limitations even\nif a catalyst is used, such as conversion limitations that prevent\nobtaining high-molecular mass materials. Indeed, during the NIPU formation,\nextra hydrogen bonds are steadily created between reactive species\nand hydroxyl and carbamate groups, leading to an increase in the viscosity\nof the system and consequently limiting the reactivity and thus the\nfinal molecular weight of NIPUs. 28 , 29 The production\nof these promising functional materials using efficient processes\nrepresents a significant challenge. Compared with traditional PUs,\nNIPUs exhibit improved thermal stability, higher resistance to nonpolar\nchemical solvents, increased adhesion and wear resistance. 25 , 30 In addition, sustainability will be essential for future technologies,\nbeing the main core to harmonize our living environment with nature. 8 In this direction, researchers and industries\nare directing many efforts toward the synthesis of biobased active\npolymers using environmentally friendly and solvent-free methods in\nthe last decades. 31 − 33 Interestingly, the main biobased cyclic bis-carbonates\nthat are used for the production of NIPUs by aminolysis can be derived\nfrom CO 2 -sourced carbonated vegetable oils 34 − 36 and more recently by the use of some biobased aliphatic, cyclic,\nand aromatic amines in the field. 37 In this work, fully biobased NIPUs with ferroelectric properties\nhave been successfully synthesized using a solvent-free process. For\nthe best of our knowledge, ferroelectric properties of NIPUs have\nnever been reported in the literature. In order to achieve these ferroelectric\nproperties, the structure of the NIPUs has been finely tuned up to\nget a high T g by using a biobased aromatic\nbis-cyclic carbonate monomer such as resorcinol bis-carbonate in the\npresence of two short biobased diamines, that is, putrescine (or 1,4-diaminobutane)\nand cadaverine (or 1,5-diaminopentane). To increase the flexibility\nof these NIPUs, the as-synthesized biobased diamine oligomer was also\ninvestigated as a chain extender in order to study how the molecular\narchitecture and the flexibility can affect the final polar structure\nand consequently the ferroelectric behavior. To design these NIPU\nmaterials in a sustainable manner, reactive extrusion (REX) was employed,\nrepresenting an attractive and sustainable solvent-free polymer processing\nroute. 36 , 38 − 40 The benefits of the\nREX process were studied, and the (nano)morphology of the NIPUs obtained\nwas characterized deeply by atomic force microscopy (AFM).",
"discussion": "Results\nand Discussion Solvent-Free Production of NIPUs and Chemical\nCharacterization NIPUs were first synthesized from resorcinol\nbis-cyclic carbonate\n(RBC) and two aliphatic diamines, respectively, cadaverine (CAD, RBC–CAD\nbeing the resulting NIPU) and putrescine (PUTR, RBC–PUTR being\nthe resulting NIPU), as reported in Figure 1 . Figure 1 Synthesis of RBC-based NIPUs ( x = 2 for PUTR or x = 3 for CAD). The reactions were performed at 100 °C for 1 h, while\nthe\nscrew speed was maintained constant at 100 rpm (see Supporting Information ). With the aim to increase the flexibility\nof the NIPU structure and study how the architecture can affect its\nthermal, morphological, and ferroelectric properties, a NIPU based\non the RBC–CAD system was synthesized in the presence of an\namino-telechelic oligoamide (bioATO) as a chain extender. In fact,\nthanks to its oligomeric aliphatic structure and chain length, bioATO\ncould increase the flexibility of the rigid RBC–CAD-type system\noriginating from the aromatic ring of RBC. Several authors have\nreported that reaction temperatures higher\nthan 120 °C can lead to the undesirable formation of different\nside products such as ureas and oxazolidinones that can affect negatively\nthe conversion rate and the NIPU molecular weight. 41 , 42 Therefore, in our case, the polymerization temperature inside the\nextruder was chosen as a balance between the melting flow of the monomers\nand the polymer already formed and the maximum temperature to avoid\nthese side reactions. As mentioned in the synthesis procedure, the\nliquid monomers were premixed before being injected into the extruder\nin order to facilitate their introduction. Based on this strategy,\nwe ensured that the pressure induced by the screws is efficient enough\nto provide the correct flow of the material within the extruder and\ntherefore to achieve the successful synthesis of these NIPUs. The reaction extent was followed by monitoring uniaxial force recorded\nover time 39 ( Figure S1 ). More specifically, the uniaxial force is expected to increase\nwith the melt viscosity as a result of the molar mass increase of\nNIPUs. Figure S1a shows that after 1 h,\nthe melt viscosity of RBC–CAD was no longer increasing and\neven reached a plateau. In contrast, the melt viscosity of even RBC–PUTR\nreached higher values and the plateau of the curve was not still observed\nafter 1 h, indicating that the polymerization was still not completed.\nAfter this reaction time, even if the reaction was not complete, RBC–PUTR\nwas recovered back in order to avoid any possible thermal degradation.\nThe same behavior was observed in the case of RBC–CAD-bioATO\neven after 90 min in which no plateau was observed, suggesting that\nthe polymerization was almost uncompleted ( Figure S1b ). However, in both cases, the increase in uniaxial force\nwas more elevated and occurred in shorter residence time, about 10\nand 15 min for RBC–PUTR and RBC–CAD-bioATO, respectively.\nSimilar results were obtained by Poussard et al., 43 and this behavior was justified by the reduced accessibility\nof amine moieties present in the end groups of the oligoamide derivatives\ntoward the ring-opening reaction of our cyclic carbonate derivative,\nas ascribed to the steric hindrances commonly reported for this kind\nof diamine. After extrusion, RBC–CAD and RBC–PUTR\nwere analyzed\nby infrared spectroscopy [Fourier-transform infrared (FTIR)] and proton\nNMR techniques. In Figure S2 , the FTIR\nspectra of the monomers and the obtained biobased NIPUs are shown.\nFTIR spectra confirmed the NIPU synthesis by REX. In fact, it is easy\nto notice that the intensity of the signal characteristic of the carbonyl\ngroup of RBC 44 at 1782 cm –1 decreased for all the NIPUs processed, totally disappearing in the\ncase of RBC–CAD and RBC–PUTR. Contrary to what was observed\nfollowing the reaction extent during the REX, RBC–PUTR spectra\nshowed a complete conversion probably because the residual amount\nof RBC is so low, and no change was noticed in the IR spectra. Furthermore,\nthe band related to the urethane bond was observed at 1692 cm –1 , demonstrating that the reaction took place and the\nhydroxyurethane functionality was formed. Compared with traditional\nPUs, this band is shifted toward lower wavenumber, indicating that\nthese hydroxyurethane bonds are hydrogen bonded in all NIPUs. 44 − 46 Moreover, it was possible to observe the presence of a broad band\nat 3330 cm –1 related to the −OH groups characteristic\nof NIPUs. 44 − 47 The 1 H NMR spectra of NIPUs demonstrate their successful\nformation, confirming the high conversion reached during REX ( Figures S6 and S7 ). In fact, in the case of RBC–CAD\nand RBC–PUTR, no characteristic signal of the RBC ring was\nobserved after 1 h extrusion, demonstrating that the carbonate conversion\nwas over 99%. In addition, 1 H NMR spectra show that no\nurea was formed during the reactive compounding of the NIPUs at 100\n°C. Furthermore, no signal was observed at 5.7 ppm that could\nbe clearly attributed to this kind of functionality. 48 In the case of RBC–CAD-bioATO, the resulting NIPU\nwas insoluble in current deuterated solvent, making difficult to deeply\nstudy its chemical structure by NMR analysis, including its macromolecular\ncharacterization using GPC. However, the samples RBC–CAD and\nRBC–PUTR result in partially soluble NIPUs due to the presence\nof high hydrogen bonding, not enabling an accurate determination of\ntheir molecular weight. Thermal Properties and Stability Thermal properties\nof the synthesized NIPUs were then studied by differential scanning\ncalorimetry (DSC) and thermogravimetric analysis (TGA). The thermal\ndecomposition of NIPUs was assessed by TGA under nitrogen ( Figure S8 ) while Figure S9 shows the second heating scan of DSC analysis. Table 1 summarize all thermal properties. Table 1 Thermal Properties of the NIPUs Obtained\nby REX DSC TGA T g [°C] T m [°C] T c [°C] T 5% [°C] T max [°C] RBC 7/15 174 239/331 RBC–CAD 39 204 289/320 RBC–PUTR 50 223 275/312 bioATO –11 94 84 364 427 RBC–CAD-bioATO 20/42 96 83 237 442 The thermal properties are\naffected by the diamine chain length;\nthe longer the diamine, the lower the glass transition temperature,\nas it was previously demonstrated by other authors. 39 , 47 From Figure S9a , NIPUs synthesized from\nRBC and CAD or PUTR were amorphous materials with a T g of 39 and 50 °C, respectively. Similar results\nhave been obtained for other NIPUs based on RBC. Schimpf et al. 30 synthesized an amorphous NIPU based on RBC and\n1,12-diaminododecane with a T g of 35 °C.\nWhen our biosourced diamine oligoamide was used as a chain extender,\na semi-crystalline NIPU was obtained, with double T g and a T m at 96 °C.\nAs it is easy to notice in Figure S9b ,\nthe T m observed was closely related to\nthe semicrystalline character of the neat bioATO. On the other\nhand, the thermal stability of the resulting NIPU\nhas the opposite tendency, compared with the T g results, that is, the longer the aliphatic diamine, the higher\nthe NIPU thermal stability. 39 The thermal\nstability of the NIPUs based on CAD or PUTR as diamine was considerably\nlower than that of RBC–CAD-bioATO, in which RBC–PUTR\nwas the less thermally stable NIPU, as seen from the T max values. In particular, RBC–CAD-bioATO exhibited\na jump higher than 100 °C compared to the other NIPUs obtained. Indeed, the higher thermal stability is related to the increase\nin the length along the adjacent hydroxyurethane bonds as previously\nreported. 49 Interestingly, the thermal\nstability of RBC–CAD-bioATO was demonstrated being higher than\nthat of traditional PUs that degrade at around 310 °C as reported\nin the literature. 50 , 51 Regarding the degradation pathway,\nRBC–CAD and RBC–PUTR showed two T max , indicating that two degradation steps occur. The first\nstep corresponds to the degradation of urethane links, while the second\none corresponds to the degradation of the main hydrocarbon chain. 52 In the case of RBC–CAD-bioATO, a major\nsingle degradation step was noticed probably due to the % amount of\nbioATO used. Microstructure Characterization by AFM The microstructure\nof the obtained NIPUs was studied by AFM. This technique is widely\naccepted as a versatile method for studying microstructures of both\nconventional PUs and NIPUs. 53 − 55 The AFM samples of the NIPUs\nobtained by polyaddition of RBC to PUTR or CAD were prepared by drop\ncasting and by compression molding. For drop-cast samples, there is\na significant difference in surface morphologies between RBC–CAD\nand RBC–PUTR in which RBC–CAD showed needle-like structures.\nBy contrast, RBC–PUTR exhibited a nanophase-mixing surface\ntopography as observed in Figures S10 and S11 . On the other hand, samples prepared by compression molding of both\nRBC–CAD and RBC–PUTR showed phase-separated nanostructurations\nalthough they are totally amorphous ( Figure 2 a–d). Figure 2 Comparison of the morphology of (a,b)\nRBC–CAD, (c,d) RBC–PUTR,\nand (e,f) RBC–CAD-bioATO, prepared by compression molding. When RBC–CAD was processed by drop casting\nmethod, the mobility\nof the polymer chain was more increased, having more time to form\na nanostructuration into longer and ordered needle ( Figure S11 ). On the other hand, when RBC–CAD was processed\nby compression molding, a lamellar nanostructuration was observed\n( Figure 2 ). Nevertheless,\nthe following AFM analysis was performed only for the compression-molded\nsamples because they are synthesized by solvent-free method and to\nstudy the microstructure of the samples as they are used for the proposed\napplication. As previously reported, phase images in tapping\nAFM are well-suited\nfor displaying domains of different mechanical properties inside PU-based\nsamples. 54 , 56 In our case, the contrast between the nanostructures\nand the matrix is apparent. Especially, for the RBC–CAD-bioATO\nsample, fiber-like domains, which were obscured in the height images,\nwere revealed in phase images ( Figure S12 ). It should be noted that the degree of nanophase separation using\nthe oligoamide (RBC–CAD-bioATO) was less prominent with respect\nto the other two samples. The nanophase separation could be ascribed\nto the high level of interurethane hydroxy hydrogen bonding present\nin the hard or soft domains of NIPUs. Some previous studies of nanophase\nseparation due to hydrogen bonding in PUs and NIPUs monitor the peak\nassociated with urethane carbonyl, concluding that shifts at ∼1690\nand ∼1720 cm –1 are associated with hydrogen-bonded\ncarbonyl and free carbonyl, respectively. 35 , 44 , 57 As shown in Figure S13a , both RBC–CAD and RBC–PUTR showed a high level of\nhydrogen-bonded carbonyl (∼1690 cm –1 ), whereas\na high level of free carbonyl (∼1720 cm –1 ) was much more evident in the spectrum of RBC–CAD-bioATO.\nIt should be noted that, besides the hydrogen bonds between hard domains\nof soft domains, hydrogen bonding can also be formed between hard\nand soft domains, which in turn results in phase mixing. When −O–\ngroups in soft domains form hydrogen bonds with −NH groups\nin hard domains, a part of carbonyl in the hard domain will be dissociated.\nTherefore, the FTIR results indicated that the RBC–CAD-bioATO\nsample had a large portion of hard segments dissolved in soft segments,\nresulting in a reduction in the nanophase separation. Moreover,\nwhen bioATO had been added as a chain extender in RBC–CAD-based\nNIPU, the nanostructure was increasingly well-distributed compared\nto that in RBC–CAD. This suggests that the compatibility between\ncomponents was enhanced. It should be noted that due to the semicrystalline\ncharacter of bioATO, the morphology of NIPU can be frozen in its crystalline\nphase, leading to a reduction in the phase-separation, as previously\nreported. 58 In order to prove that the\nnanostructuration depends on the inter-urethane hydrogen bonding,\nthe morphological study by AFM was assessed as a function of the increased\ntemperature. As seen in Figure S14 , the\nRBC–CAD nanostructure observed at 25 °C was still stable\nup to 35 °C. At these temperatures, the nanostructures composed\nof chains packed tightly together with a slight organization order.\nAt 40 °C, the nanostructure started to change dramatically. All\nchains were relaxing, and the orderliness started to fade down. Furthermore,\nat 70 and 75 °C, the height at the middle of the image was lower\nthan that at the edge. This can be explained by the fact that the\nhardness of the surface was reduced to a point that the tip could\nsweep the material from the center to both sides (the force was kept\nconstant all the time). It is worth to notice that when the sample\nwas cooled down to room temperature, the nanostructure appeared again\nbut with different organization. Thus, we can conclude that the nanostructures\nare likely stable below glass transition temperature while they are\nsignificantly altered above this temperature. Moreover, the\nimpact of nanophase separation on the local nanomechanical\nproperties was also investigated by using an AFM-based method, peakforce\nQNM. This well-known technique can reveal useful information such\nas elastic modulus, adhesion force and deformation values at the nano-scale\nlevel. 59 Figure 3 shows the peakforce QNM topography, DMT\nmodulus, and adhesion images for each NIPU sample. Figure 3 Peakforce QNM height\nimages (top row), DMT modulus (middle row),\nand adhesion (bottom row) surface maps of RBC–CAD (first column),\nRBC–PUTR (second column), and RBC–CAD-bioATO (third\ncolumn). Even if they were totally amorphous,\nRBC–CAD and RBC–PUTR\nexhibited phase-separated morphologies composed of both hard and soft\ndomains. In the contact modulus images of these two samples (second\nrow images of Figure 3 ), the nanostructures appear as bright colors. This indicates that\nthey have lower elastic modulus (soft domains) whereas the matrix\nin both cases have dark colors, in line with higher modulus values\n(hard domains). Besides, these hard and soft domains corresponded\nto high- and low-adhesive regions, respectively ( Figure 3 ). This emphasizes that the\nnanostructures in the case of our amorphous NIPUs are likely formed\ndue to the hydrogen bonding between isolated soft domains. They present\nhigher mobility leading to a more ordered structure, whereas the matrix\nconsisted of more rigid disordered domains. Furthermore, the nanostructures\nin RBC–CAD show needle-like shapes, which were coherent with\nwhat was observed in the drop-cast sample but smaller in size and\nless connected. Like for RBC–PUTR, the soft domains are more\nconcentrated and greater in size. On the other hand, the RBC–CAD-bioATO\ndisplays a better homogeneity in terms of mechanical distribution,\nresulting from the nanophase mixing behavior. This homogeneous distribution\ncan prove that the addition of bioATO as a chain extender can improve\nthe compatibility of separated nanophases compared to RBC–CAD. Peakforce QNM not only provide qualitative information but can\nalso evaluate the local mechanical properties quantitatively. In the\nspectroscopy mode, force–deformation curves (FCs) are acquired\nat each pixel of the images. Figure 4 shows three representative FCs corresponding to each\nsample. Figure 4 Representative force curves of the NIPU sample, (a) RBC–CAD,\n(b) RBC–PUTR, and (c) RBC–CAD-bioATO. When the tip is far from the surface samples, the FCs display\nhorizontal,\nflat lines, which means that there is no interaction between the tip\nand the sample. As soon as the tip moves close enough to the samples,\nattractive Van der Waals force pulls the tip toward the surface, leading\nto negative forces in the FCs. The AFM tip then contacts and indents\nthe surface, causing the force to rise linearly to a positive value.\nThis part of the FCs is called the extend part (indicated by blue\ncolor in the figure). After reaching to pre-set force values (peakforce\nvalues), the tip starts to retract from the sample and the force slowly\ndecreases again, reaching the lowest negative value (adhesion force).\nAs the interaction between the tip and the sample is lost completely,\nthe force returns to zero. This part of the force curve is called\nthe retract part (indicated by red color). It should be noted that\nthere was no hysteresis loop occurring in the contact part for all\nsamples. This indicates that the tip–sample interactions in\nall cases are purely elastic, and no plastic deformation has occurred.\nTherefore, suitable contact mechanic models can be applied to calculate\nthe contact modulus of the samples. The choice of model depends on\ncertain parameters such as the tip shape used to conduct the experiment,\nthe effect of adhesion force, and the deformation types of the materials\n(plastic or elastic). In our case, the AFM tip used was RTESPA 300-30.\nThis type of AFM probe has a spherical shape with a controlled tip\nradius of approximately 30 nm and was verified by SEM measurement\nas shown in Figure S15 . Furthermore, the\ncontribution of adhesion forces in each sample was significantly large\n(20–30 nN). Therefore, the Derjaguin–Muller–Toporove\n(DMT) model was chosen for the final calculation. 60 Figure S16 shows the boxplot\nanalysis of DMT modulus of RBC–CAD, RBC–PUTR, and RBC-bioATO.\nThe mean values and standard deviation values ( N =\n30) of nanostructures and the matrices were reported. As shown in\nthe corresponding figure, the calculated DMT modulus of the nanostructures\nand matrix of RBC–CAD are slightly higher than those corresponding\nto RBC–PUTR. This indicates that changing from CAD to PUTR\naltered the topological features and had an impact on the local mechanical\nproperties of the NIPU. On the other hand, a homogeneous modulus distribution\nwas obtained in the case of RBC-bioATO, as expected with its nanophase\nmixing behavior. In addition, the high level of interdomain hydrogen\nbonding in RBC–CAD-bioATO lowers its local nano-mechanical\nproperties, as previously reported for NIPUs of microphase-separated\nstructure. They show better mechanical properties than phase-mixed\nones. 45 , 61 This result was confirmed by the DMA (Figure\nS17, Supporting Information ), which demonstrates\nthat RBC–CAD showed higher storage modulus than RBC–CAD-bioATO.\nIt means that the introduction of the chain extender in NIPU architecture\nincreases the flexibility of the system, promoting the chain mobility\nat room temperature. Ferroelectric-like Behavior and Its Origin Dielectric\nproperties of the NIPUs synthesized from RBC with CAD or PUTR were\ncharacterized by measuring their complex dielectric permittivity as\na function of temperature. Figure 5 shows the temperature dependence of real (ε′)\nand imaginary (ε″) components of permittivity at different\nfrequencies for RBC–CAD and RBC–CAD-bioATO samples.\nA similar dielectric behavior was found for samples RBC–CAD\n( Figure 5 a) and RBC–PUTR\n(included in Supporting Information , Figure\nS18). Figure 5 Temperature dependence of the real (ε′) and imaginary\n(ε″) components of dielectric permittivity during heating\nat different frequencies for the samples (a) RBC–CAD and (b)\nRBC–CAD-bioATO. The T g region is\nindicated in both bases. Correspondingly, the\nimaginary permittivity, related with dielectric\nlosses, shows a distinctive peak/step, more visible in the low-frequency\ndata (<10 kHz) at a temperature that shifts with increasing frequency.\nThis is the typical behavior of the weak dielectric relaxation associated\nwith the glass transition. Note that, above T g , both permittivity and losses increase sharply, along with\nhigher-frequency dispersion (see also Supporting Information , Figure S19), resulting from the activation of\nionic conduction mechanisms. Indeed, low-frequency ac conductivity\nincreases on 1 order of magnitude by only 20 °C, from room temperature\nto T g ( Figure S19 ). Nevertheless, room-temperature conductivity was rather low\nin all\nsamples and dielectric losses tan δ were below 0.1, so that\nhigh electric fields can be endured. Similar results have been reported\nfor some linear aromatic PUs and polyureas. 24 , 62 This dielectric relaxation that takes place at the glass transition\nis likely associated with the freezing of the hydrogen-bonded dipoles\nin the amorphous phase below T g , in agreement\nwith previous reports. 23 , 24 , 63 Note that the low permittivity of these NIPUs (ε′ about\n2.4) can be considered advantageous for certain applications such\nas energy harvesting because high voltage coefficients (g 33 ) can result even from low ( d 33 ) piezoelectric\ncoefficients. 2 , 7 Despite the apparent similar\ndielectric behavior of sample RBC–CAD-bioATO\n( Figure 5 b), a couple\nof differences are worth to be highlighted. First, the permittivity\nshows negligible temperature dependence and frequency dispersion from\n−70 °C to room temperature, while dielectric losses were\nmuch lower than those of RBC–CAD. Besides, the abrupt increase\nin permittivity and losses above T g were\nmore pronounced for sample RBC–CAD-bioATO. These differences\ncould be associated to the incorporation of the semi-crystalline chain\nextender, which not only results in lower ionic conduction within\nthe glassy state but also increases mobility of charge carriers above T g ( Supporting Information , Figure S19). Note also that the dielectric relaxation takes place\nbelow room temperature and could be affected by the presence of a\nsecond T g in this material related to\nthe bioATO chain extender, as shown in DSC analysis ( Table 1 ). Ferroelectric hysteresis\nloops were measured to set parameters\nlike polarization switching and coercivity; the latter stands for\nthe electric field required to reverse the direction of polar domains/dipoles. Figure 6 a,b shows the polarization\nversus electric field (P–E) hysteresis loops at room temperature\nfor the RBC–CAD and RBC–PUTR samples, for a maximum\nelectric field of 20 kV mm –1 . Red loops are obtained\nafter compensation by subtracting the linear polarization and conduction\ncontributions, as described in the Experimental section. Figure 6 Comparison\nof P–E hysteresis loops and current density curves\nas a function of the electric field (I–E) measured at room\ntemperature and 0.01 Hz for RBC–CAD (a,c) and RBC–PUTR\n(b,d). Red loops are obtained after compensation by subtracting linear\npolarization and conduction contributions. A nonlinear behavior of the polarization is clearly shown for sample\nRBC–CAD with an apparent remanent polarization ( P r ) of 0.05 μC cm –2 . For the RBC–PUTR\nsample, however, only a linear dielectric-like behavior was found\nup to 20 kV mm –1 , and higher electric fields resulted\nin the sample electrical breakdown. The ferroelectric-like behavior\ncould be better visualized by analyzing\nthe corresponding current density curves (I–E loops), in which\nthe evolution of the polarization switching can be followed ( Figure 6 c,d). Note that switching\ncurrent remains after compensation of I–E loops for sample\nRBC–CAD (red loop), while no switching current resulted for\nsample RBC–PUTR. A macroscopic switching seems to take place\nonly in the RBC–CAD sample. It should be mentioned that NIPUs\nsynthesized from RBC with either CAD or PUTR were both amorphous and\npresented a T g slightly above room temperature,\nso that hysteresis measurements were carried out within the glassy\nstate. This is not the typical case of most known ferroelectric polymers,\nlike PVDF-based ones, which are rather semi-crystalline and typically\nmeasured above the glass transition temperature, where polarization\nswitching is favored. 17 A strategy was\nalso used to obtain ferroelectric switching in some amorphous aromatic\nPUs, for which P–E hysteresis loops similar to those reported\nhere were found. 20 , 23 Therefore, it is important to\ndiscuss about the shape and the possible origin of the switching observed\nin the current loops of these samples to discard the artificial polarizations\ncoming from charge accumulation at interfaces. The current loops\nfor the RBC–CAD sample are composed of\na series of current sparks, which can be even more abrupt as they\nappear, producing a smoothening of the current due to the large constant\ntime employed in the measurement system. These sparks might come from\nnon-homogeneous switching of polar entities, which can reflect the\nphase heterogeneity observed in the AFM study of samples (parallel\ndipole arrangements related to the lamellar-like nanostructuration\ngiving rise to non-cooperative switching). The phenomenon can be observed\nin amorphous or glassy systems that contain molecular polar dipoles\nwith enough rotational mobility above T g but whose mobility is greatly reduced in the frozen glassy state.\nThese systems might suffer from slow switching times due to their\nhigh rotational viscosity below T g . 64 This behavior is, therefore, different\nfrom that of the typical\nferroelectrics, which require cooperative switching of the ferroelectric\ndomains/dipoles. Indeed, the loops achieved in sample RBC–CAD\nresemble rather those typically reported in electrets, where switching\ncomes from mobile charged defects. 64 , 65 In ferro-electrets\n(voided charged polymers), instead, internal charging processes within\nthe cavities of non-polar cellular polymers take place, which can\nbe “switched” or re-charged in the opposite direction\nvia dielectric barrier microdischarges. 66 Although, NIPUs synthesized from RBC with either CAD or PUTR do\nnot present the typical void structure of cellular polymers but rather\na nanophase separation due to hydrogen bonding. On the other\nhand, no switching was found in the case of the RBC–PUTR\nsample, that is, using an even carbon number diamine as a monomer\nduring the NIPU synthesis. This could be explained considering that\npolar dipoles are disposed symmetrically, resulting in a permanent\ndipolar moment to be equal to zero. Note also that T g of the RBC–PUTR sample is higher than that of\nthe RBC–CAD samples, so that this higher T g may result in a worst switching, if any, at room temperature.\nP–E hysteresis measurements were also carried out at different\ntemperatures for the RBC–CAD sample, as shown in Figure S20 (only loops compensated are given).\nA similar polar switching behavior was found with decreasing temperature,\neven at 10 °C, far below the T g of\nthe RBC–CAD sample (39 °C), while both P r and E c apparent values increase\nwith temperature. This seems to indicate better switching performance\nof the RBC–CAD sample and the role of material’s hardening\nbelow T g , in which the mobility of the\npolar entities is strongly reduced. In order to shed further\nlight on these results, a computational\nstudy based on a molecular modeling method was performed to investigate\nthe different chain conformations that can be adopted by our polymers\nand the interchain hydrogen bonding interactions as a function of\nthe diamine used for the NIPU synthesis. We selected the DREIDING\nforce field61, which describes explicitly the hydrogen bond interactions,\nfor the simulations, as implemented in Materials Studio 18.0.62. First,\nwe have considered the shortest planarized segments of both derivatives.\nWe systematically changed the value of the dihedral angles around\nthe urethane moieties and optimized in each case the backbone with\nthese fixed values. The most stable structures and the linearized\nchains were finally retained in Figure 7 . We adopted a similar strategy for the longer chains\nin Figure S21 . Figure 7 Energetic comparison\nof the more stable linearized segments in\nboth RBC–PUTR and RBC–CAD. It is not straightforward to fully address the difference in the\nlevel of interactions between chains because the systems are very\nflexible and are characterized by the presence of stereogenic carbons.\nInterestingly, when we impose a planarized structure likely imposed\nby solid-state packing effects, we can distinguish a structural difference\nbetween RBC–PUTR and RBC–CAD specimens. In the most\nstable structure, the chain containing the putrescine as diamine displays\nthe carbonyl groups oriented in opposite directions, while they point\nin the same direction in RBC–CAD as illustrated in Figure S21 . This difference in orientation can\npotentially influence the pattern of hydrogen bonding between chains,\nalthough this pattern can also be influenced by other possible side\nproducts obtained during the polymerization. However, these chain\nconformations are not totally linear but are rather bent, thus representing\na non-ideal configuration for the nanostructuration. Accordingly,\nthe more stable linear segments in both NIPUs were also studied ( Figure 7 ). This result confirms\nthat one of the factors that could explain the polar switching response\nof RBC–CAD is the presence of a net dipole moment due to the\nparallel dipoles formed by the carbonyl groups throughout the polymeric\nNIPU chain. Similar results were already reported in the case of polyureas,\npolyamides, and more recently some PUs. Indeed, it was reported that\ndipoles in odd nylons such as nylon 11 and nylon 9 are oriented in\nthe same direction, whereas in even nylons, the net dipole moment\nbecomes zero because dipoles are arranged in an antiparallel fashion. 67 , 68 Similarly, it was reported that even linear aromatic PUs have antiparallel\ndipoles, resulting in a non-polar state, while odd linear aromatic\nPUs have parallel dipoles and are thus polar. 24 Therefore, it is possible to conclude that the RBC–CAD obtained\nfrom an odd carbon number diamine is in a polar state with a net dipole\nmoment. Nevertheless, having dipole moments does not necessarily\nmean having\nthe ferroelectric-like behavior, for which cooperative switching of\npolar entities/dipoles is required. We then study the ferroelectric\nswitching behavior of RBC–CAD-bioATO to determine the effect\nof the greater flexibility and mobility of the chains due to the presence\nof the semicrystalline chain extender. Figure 8 shows the room-temperature P–E hysteresis\nand current density loops for RBC–CAD-bioATO. In this case,\nred loops are obtained after compensation by subtracting not only\nthe linear polarization and conduction contributions but non-linear\nleakage currents were also considered. Figure 8 Room-temperature P–E\nhysteresis loop (a) and current density\ncurve for RBC–CAD-bioATO (b) measured at 0.01 Hz. Red loops\nare obtained after compensation by subtracting linear polarization\nand conduction contributions. It should be noted that, contrary to the RBC–CAD sample,\nboth polarization and current density curves for the RBC–CAD-bioATO\nsample clearly indicate cooperative switching, reminiscent of the\ntypical response of ferroelectric material. A P r of 0.05 μC cm –2 resulted in this\ncase in an E c of 11 kV mm –1 , figures lower than those found for, for example, PVDF-based polymers. 13 , 17 The lower coercive fields are advantageous for practical applications. Note that bioATO introduces some semi-crystallinity into the NIPU\nand that a second T g was found at room\ntemperature associated with it in sample RBC–CAD-bioATO ( Figure S9 ), so that ferroelectric switching would\ntake place in a softened environment. Ferroelectric switching performance\nobserved when bioATO is added to RBC–CAD-based NIPU could be\nrelated to the enhanced compatibility of the soft and hard phases\nobserved by AFM, which indicated a more homogeneous morphology and\na better mechanical coupling between them. These results evidence\nthe ferroelectric-like behavior of this fully biobased NIPUs produced\nby the solvent-free process. The Berlincourt piezoelectric coefficient d 33 was evaluated after hysteresis measurement,\nin which poling\nof the samples was attained by turning off the electric field right\nbefore completing the loop at a low measuring frequency. NIPUs synthesized\nfrom RBC with CAD do not show d 33 activity\nin Berlincourt, but a meaningful d 33 value\nof 2 pC N –1 resulted for the poled RBC–CAD-bioATO\nsample, the one that showed loops with clear indications of ferroelectricity.\nThis value must be compared with those reported for (non-PVDF) polymers,\nsuch as nylons, polyamides, cellulose, and their derivatives or PUs,\nfor which effective piezoelectric responses between 2 and 5 pC N –1 are typically reported. 2 , 69 Note that,\ndespite the low d 33 achieved, high voltage\ncoefficients g 33 (above 0.1 V m N –1 )\nare anticipated due to the very low permittivity of NIPUs, although\ncorresponding figures of merit for energy harvesting applications\nare less than desired. 70 Nevertheless,\nthese materials can be processed in large areas to\nproduce enough power for applications. A more efficient poling is\nneedful, which requires tailored conditions like poling above T g and/or higher electric fields, where electrical\nbreakdowns are a drawback. Conductivity values would need to be thus\noptimized. To improve the rotational mobility within the highly viscous\nglassy state is necessary for a better stability of the aligned polar\nentities, a critical challenge for functionality in energy harvesting\napplications."
} | 11,199 |
22310174 | null | s2 | 5,280 | {
"abstract": "A major goal of biological research is to provide a mechanistic understanding of diverse biological processes. To this end, synthetic biology offers a powerful approach, whereby biological questions can be addressed in a well-defined framework. By constructing simple gene circuits, such studies have generated new insights into the design principles of gene regulatory networks. Recently, this strategy has been applied to analyze ecological and evolutionary questions, where population-level interactions are critical. Here, we highlight recent development of such systems and discuss how they were used to address problems in ecology and evolutionary biology. As illustrated by these examples, synthetic ecosystems provide a unique platform to study ecological and evolutionary phenomena that are challenging to study in their natural contexts."
} | 211 |
22225547 | PMC3491685 | pmc | 5,281 | {
"abstract": "System approaches to elucidate ecosystem functioning constitute an emerging area of research within microbial ecology. Such approaches aim at investigating all levels of biological information (DNA, RNA, proteins and metabolites) to capture the functional interactions occurring in a given ecosystem and track down characteristics that could not be accessed by the study of isolated components. In this context, the study of the proteins collectively expressed by all the microorganisms present within an ecosystem (metaproteomics) is not only crucial but can also provide insights into microbial functionality. Overall, the success of metaproteomics is closely linked to metagenomics, and with the exponential increase in the availability of metagenome sequences, this field of research is starting to experience generation of an overwhelming amount of data, which requires systematic analysis. Metaproteomics has been employed in very diverse environments, and this review discusses the recent advances achieved in the context of human biology, soil, marine and freshwater environments as well as natural and bioengineered systems.",
"conclusion": "Conclusions Overall, the field of metaproteomics is gaining momentum at an exponential rate within very diverse environments. An overview of selected studies from the ecosystems discussed in this review is shown in Table 1 . Advances in metaproteomics finally allow for the consideration of the integration of such data in system approaches ( Fig. 1 ). This was partly achieved in the aquatic environment where Lauro et al . (2011) combined metagenomic, metaproteomic and physicochemical data to describe the interaction between the microbial populations defining the biogeochemical cycles throughout a water column. Such an approach could feasibly be transferred to other environmental ecosystems. To date, the application of complex system approaches is still scarce and requires a coordinated experimental design that brings together expertise from each of the many technologies involved. Table 1 Overview of selected metaproteomics studies Environment Number of peptides/proteins identified Method Databases References Human gut NA/2214 proteins LC-MS/MS 2 unmatched human gut metagenomes, several genomes from gut inhabitants and several nonhuman gut genome Verberkmoes et al . (2009a) Human gut 5010 peptides/NA 1D-PAGE, LC-MS/MS Synthetic human gut metagenome (216 genomes from gut inhabitant) and 124 human gut unassembled nonannotated metagenomes Rooijers et al . (2011) Soil NA/716 proteins LC-MS/MS Unmatched soil metagenome supplemented with 1606 genomes Chourey et al . (2010) Soil NA/122 2D-PAGE, MALDI TOF/TOF MS/MS Complete NCBInr, bacterial entries NCBInr and fungal entries NCBInr Wang et al . (2011) Marine 6533 peptides/1042 proteins LC-MS/MS SAR11 clade and specific microorganisms from Sargasso Sea metagenome as well as genomes from sequenced isolates Sowell et al . (2009) Marine 5389 peptides/2273 proteins LC-MS/MS Global Ocean Sampling combined metagenomes Morris et al . (2010) Freshwater NA/1824 proteins 1D-PAGE, LC-MS/MS Matched metagenomes Lauro et al . (2011) Acid mine drainage biofilm NA/4107 proteins LC-MS/MS Biofilm_AMD_CoreDB database Mueller et al . (2011) Activated sludge NA/5029 proteins LC-MS/MS Three distinct unmatched activated sludge metagenomes Wilmes et al . (2008b) Anaerobic digestion NA/202 proteins 2D-PAGE, LC-ESI-MS/MS Bacterial entries of the NCBI nonredundant database Jehmlich et al . (2010) 1/2D-PAGE, one/two-dimensional polyacrylamide gel electrophoresis; LC-MS/MS, liquid chromatography-tandem mass spectrometry; MALDI-TOF, matrix-assisted laser desorption ionization-time of flight; ESI, electrospray ionization. The technical limitations encountered throughout the metaproteomic workflow ( Fig. 2 ) have, for the most part, been addressed in the ecosystems discussed in this review. However, it should be kept in mind that an exhaustive investigation of the entire metaproteome is unlikely due to the unfeasibility of developing a universal protein analysis protocol. Furthermore, it must be considered that a metaproteome may include intracellular, extracellular and membrane-bound proteins, and ideally, the three protein fractions should be analysed for each sample. When possible, opting for gel-free protein fractionation seems to lead to a higher level of protein identification when compared with gel-based methods. For example, when analysing the metaproteome of activated sludge, the use of 2-DGE resulted in the identification of 38 proteins ( Wilmes et al ., 2008a ), while the 2D-nano-LC method led to the identification of 5029 proteins ( Wilmes et al ., 2008b ). In addition, it is now apparent that metaproteomic approaches benefit from the availability of relevant metagenomic data, either matched or unmatched. As a result of this combined protocol, a new difficulty is encountered regarding the analysis and interpretation of the vast quantity of data generated. A major hurdle in the utilization of metagenomic data, impacting directly on metaproteomics, has been recognized as the assembly and the annotation of the collected genomic fragments. Rooijers et al . (2011) proposed an iterative workflow using nonannotated, unassembled metagenome sequences, which could be systematically used in metaproteomic investigations whenever relevant metagenomic data are available. Future metaproteomic studies should aim to progress from proof of concept approaches to experimental designs leading to practical applications. For example, metaproteomic comparisons between healthy and diseased states within the human microbiome have yet to be carried out. Additionally, comparative in situ bioremediation investigations will need to be conducted to access the functional response of the natural mixed microbial communities to common pollutants. Furthermore, when investigating bioremediation processes, pollutants should be systematically monitored throughout the trials, to clarify the contaminant degradation status as a function of time. This in turn should allow for the proper assessment of the degrading abilities of the microbial communities investigated. To conclude, the feasibility of metaproteomic studies has been successfully demonstrated in very diverse natural and engineered environments. However, only few studies to date employed this strategy to answer specific biological questions such as how complex communities define the biology of a given ecosystem (Ng et al ., 2010; Wilmes et al ., 2008b ; Denef et al ., 2010 ; Mueller et al ., 2010 ; Lauro et al ., 2011 ), and it is now critical to move metaproteomics forward in order for this technology to achieve its full potential. To this end, future studies must be designed with an aim towards gaining some understanding of ecological concepts, and the data generated must be adequately analysed. In addition, attempts should be made to integrate such data in the context of system approaches to allow for the prediction of functional responses to environmental stimuli.",
"introduction": "Introduction Microorganisms occupy virtually every habitat on our planet, and their activities largely determine the environmental conditions of today's world. Indeed, microorganisms are heavily involved in biogeochemistry, ensuring the recycling of elements such as carbon and nitrogen ( Madsen, 2011 ). In addition, microorganisms are extensively used to degrade anthropogenic waste prior to release into the environment ( Hussain et al ., 2010 ; Park et al ., 2008b ). In their natural habitat, microorganisms coexist in mixed communities, the complexity of which is specific to each environment, for example from six estimated individual taxa for an acid mine drainage biofilm ( Ram et al ., 2005 ), up to 10 6 estimated taxa per gram of soil ( Wilmes & Bond, 2006 ). As most of the microorganisms present in the environment have not been cultured, their investigation requires the use of molecular techniques that bypass the traditional isolation and cultivation of individual species ( Amann et al ., 1995 ). Moreover, even when isolation is possible, a single species removed from its natural environment might not necessarily display the same characteristics under laboratory conditions as it does within its ecological niche. Therefore, the study of mixed microbial communities within their natural environment is key to the investigation of the diverse roles played by microorganisms, and to the identification of the microbial potential for biotechnological application, including but not limited to: pharmaceutical, diagnostics, waste treatment, bioremediation and renewable energy generation. An emerging field of research in microbial ecology encompasses system approaches ( Fig. 1 ), whereby all levels of biological information are investigated (DNA, RNA, proteins and metabolites) to capture the functional interactions occurring in a given ecosystem and identify characteristics that could not be accessed by the study of isolated components ( Raes & Bork, 2008 ; Röling et al ., 2010 ). Recent technological advances, including the development of high-throughput ‘omics’ methods, make such system approaches possible, where mixed microbial communities are viewed as one meta-organism. Metagenomics, metatranscriptomics, metaproteomics and metametabolomics are employed to determine respectively the DNA sequences of the meta-organism under study, the collectively transcribed RNA, the translated proteins and the metabolites resulting from cellular processes. All of the generated data can then be used to identify the metabolic pathways and cellular processes at work within an ecosystem. Yet another level of information is required to access the molecular interactions occurring within the ecological niche under investigation, and this is achieved by the application of metainteractomics ( Fig. 1 ; Lievens et al ., 2010 ; Medina & Sachs, 2010 ; Janga et al ., 2011 ). Ultimately, system approaches aim to develop mathematical models that can be used to predict the behaviour of a biological system in response to environmental stimuli ( Fig. 1 ; Raes & Bork, 2008 ; Röling et al ., 2010 ). Fig 1 System approach for the characterization of microbial ecosystems. Metagenomics (DNA sequencing of all the microorganisms from an ecosystem), metatranscriptomics (analysis of RNA collectively transcribed by all the microorganisms from an ecosystem), metaproteomics (analysis of proteins collectively expressed by all the microorganisms from an ecosystem) and metametabolomics (analysis of metabolites collectively produced by all the microorganisms from an ecosystem) are employed to access the metabolic pathways and cellular processes at work in an ecosystem. Metainteractomics (analysis of the molecular interactions between all the microorganisms from an ecosystem) is used to investigate the cellular network in an ecosystem. All the resulting data provide insights into ecosystem functioning and are used to generate a model, which in turn can allow the prediction of the behaviour of an ecosystem in response to environmental changes. Metaproteomics, which is the identification of all the proteins expressed at a given time within an ecosystem (as defined by Wilmes & Bond, 2004 ), is an indispensable element of system approaches and plays a key role in the determination of microbial functionality. Microbial metaproteomics has been applied in the context of diverse environments such as soil ( Benndorf et al ., 2007 ; Williams et al ., 2010 ; Wang et al ., 2011 ), sediments ( Benndorf et al ., 2009 ; Bruneel et al ., 2011 ), marine ( Morris et al ., 2010 ; Sowell et al ., 2011 ), freshwater ( Ng et al ., 2010 ; Habicht et al ., 2011 ; Lauro et al ., 2011 ), human intestinal tract ( Verberkmoes et al ., 2009a ; Rooijers et al ., 2011 ), human oral cavity ( Rudney et al ., 2010 ), animal guts ( Toyoda et al ., 2009 ; Burnum et al ., 2011 ) and natural and bioengineered systems ( Ram et al ., 2005 ; Wilmes et al ., 2008a ; Jehmlich et al ., 2010 ). Typically, metaproteomic approaches involve up to seven main steps ( Fig. 2 ), namely sample collection, recovery of the targeted fraction, protein extraction, protein separation and/or fractionation, mass spectrometry analysis, databases searches and finally data interpretation, whereby the expressed proteins and pathways identified are used to access information about system functioning (for detailed descriptions of the methodologies involved, see Wilmes & Bond, 2006 and Verberkmoes et al ., 2009b ). Each environment offers specific challenges and limitations within this workflow. Typically, sample collection and recovery of the targeted fraction ( Fig. 2 ) can be problematic in the marine and freshwater context, where microorganisms can be recovered from hundreds of litres of water away from laboratory facilities. The protein extraction step ( Fig. 2 ) has proven specifically difficult when dealing with soil samples, which naturally contain interfering humic acids. Such compounds are usually co-extracted together with proteins and are known to interfere with protein quantification, separation and identification ( Bastida et al ., 2009 ). The use of gel-based methods for protein separation presents some disadvantages regardless of the origin of the sample. Such drawbacks are typically those associated with two-dimensional gel electrophoresis (2-DGE): proteins with extreme isoelectric points (basic or acidic) or extreme molecular weight (very large or very small), lipophilic proteins and low abundance proteins are typically excluded ( Gygi et al ., 2000 ; Ong & Pandey, 2001 ). Finally, the limitations encountered in the last three steps of the metaproteomic workflow ( Fig. 2 ), namely mass spectrometry analysis, databases searches and data interpretation are intrinsically linked to the success of the previous steps with a disadvantage in fields where no metagenome sequences are available. Overall, metaproteomics relies on the availability of relevant genome and metagenome sequences when searching generated mass spectra against existing databases for protein identification. As such, this approach cannot be viewed as an isolated method because it benefits from genome/metagenome sequencing for protein identification. However, when no relevant sequences are available, de novo peptide sequencing can be used for protein identification ( Lacerda et al ., 2007 ; Fig. 2 ). In addition to being an integrative component of system approaches ( Fig. 1 ), metaproteomics presents some valuable advantages over other ‘omics’ technologies for functional analyses. Primarily, metagenomic data only account for the microbial potential of a system and do not provide any insights into microbial activity. On the other hand, metatranscriptomics is one step closer to the identification of active metabolic pathways but does not allow for translational regulation to be taken into consideration; indeed, a lack of correlation between mRNA levels and proteins levels has been previously documented ( Gygi et al ., 1999 ; Pradet-Balade et al ., 2001 ). Finally, metaproteomics provides significant insights into microbial activity together with metametabolomics, which is the study of the intermediate and end-products of cellular processes. Metagenomic data typically include numerous genes of unknown function ( Ram et al ., 2005 ), most likely involved in novel functional systems. Metaproteomics may be useful to identify the circumstances under which these unknown functions are required and might therefore help to elucidate which systems hold the most potential for further investigation. Metaproteomics might also prove to be valuable for the identification of key microbial activities occurring in natural environments that could be exploited in a bioengineered context. For example, the investigation of the proteins expressed within the wood termite gut ( Burnum et al ., 2011 ) or the sheep gut ( Toyoda et al ., 2009 ) aimed at identifying natural microbial processes involved in the degradation of wood and cellulose. Such microbial processes could be harnessed for the production of renewable energy from wood or grass. For the purpose of this review, we discuss the advancement of metaproteomics in the context of human biology, soil, marine and freshwater environments as well as natural and bioengineered systems. Fig 2 Typical workflow for metaproteomics analysis."
} | 4,132 |
39012392 | PMC11252210 | pmc | 5,282 | {
"abstract": "Abstract Waste glycerol is produced in excess by several industries, such as during biodiesel production. In this work, the metabolic versatility of anaerobic sludge was explored towards waste glycerol valorization. By applying different environmental (methanogenic and sulfate-reducing) conditions, three distinct microbial cultures were obtained from the same inoculum (anaerobic granular sludge), with high microbial specialization, within three different phyla ( Thermodesulfobacteriota , Euryarchaeota and Pseudomonadota ). The cultures are capable of glycerol conversion through different pathways: (i) glycerol conversion to methane by a bacterium closely related to Solidesulfovibrio alcoholivorans (99.8% 16S rRNA gene identity), in syntrophic relationship with Methanofollis liminatans (98.8% identity), (ii) fermentation to propionate by Propionivibrio pelophilus strain asp66 (98.6% identity), with a propionate yield of 0.88 mmol mmol −1 (0.71 mg mg −1 ) and a propionate purity of 80–97% and (iii) acetate production coupled to sulfate reduction by Desulfolutivibrio sulfoxidireducens (98.3% identity). In conclusion, starting from the same inoculum, we could drive the metabolic and functional potential of the microbiota towards the formation of several valuable products that can be used in industrial applications or as energy carriers. Key points \n Versatility of anaerobic cultures was explored for waste glycerol valorization Different environmental conditions lead to metabolic specialization Biocommodities such as propionate, acetate and methane were produced Supplementary Information The online version contains supplementary material available at 10.1007/s00253-024-13248-6.",
"introduction": "Introduction Biodiesel production and ethanol production by yeast or the oleochemical industry generate glycerol as a by-product (Clomburg and Gonzalez 2013 ; Monteiro et al. 2018 ; Navarrete et al. 2014 ). Largely exceeding its demand, glycerol changed from a commodity chemical to a surplus by-product and even to a waste product, creating environmental and economic losses (Clomburg and Gonzalez 2013 ; Monteiro et al. 2018 ; Viana et al. 2012 ). Within this framework, anaerobic bioconversion of glycerol to valuable chemical compounds can be a sustainable treatment strategy, adding value to waste glycerol and to the biodiesel industry (Holm-Nielsen et al. 2009 ; Viana et al. 2012 ; Yazdani and Gonzalez 2007 ). Under anaerobic conditions, the high reduction state of glycerol is an advantage, as glycerol fermentation results in the production of more reduced compounds than with sugars as glucose (Yazdani and Gonzalez 2007 ). Nevertheless, the high reduction state of glycerol also presents considerable challenges, since only a few fermentative bacteria are capable of easily disposing off the excess of reducing equivalents generated from glycerol. Other bacteria can oxidize glycerol coupled to the reduction of external electron acceptors, such as sulfate (Clomburg and Gonzalez 2013 ), or in syntrophy with hydrogenotrophic methanogens (Qatibi et al. 1991a , b ). Syntrophic collaboration was even shown to accelerate glycerol degradation (Magalhães et al. 2020 ; Richter and Gescher 2014 ), possibly because it facilitates the maintenance of the proper intracellular redox balance. Zhang et al. ( 2015 ) suggested that the use of mixed cultures for glycerol degradation may present economic and process advantages. The objective of this work was to drive the naturally occurring microbiome of anaerobic sludge towards glycerol consumption and valorization and to study the diversity and physiology of the obtained microorganisms and/or communities. Starting from the same inoculum (anaerobic sludge), three distinct specialized glycerol degrading cultures were obtained, and their physiology was studied. The obtained cultures are capable of metabolizing glycerol through different pathways, proving the metabolic versatility of using anaerobic mixed cultures, as well as proving the concept of the ability to shape mixed microbial communities towards specific needs (Oleskowicz-Popiel 2018 ).",
"discussion": "Discussion Although starting from the same inoculum, microbial specialization was evidenced for glycerol conversion, with organisms from three different phyla— Euryarchaeota , Thermodesulfobacteriota and Pseudomonadota —being found in the three distinct glycerol-degrading cultures. The use of anaerobic granular sludge proved to be an efficient microbial platform for the production of biocommodities, such as propionate, methane and/or acetate. The different products generated by the stable cultures suggest metabolic specialization, with glycerol being degraded through different pathways (Fig. S2 ). In the Gly-M co-culture, glycerol was converted to acetate and H 2 (Eq. 2 ), with subsequent conversion of hydrogen to methane by the hydrogenotrophic methanogen (Eq. 3 ). The conversion stoichiometry is shown in Eq. 4 , and the possible metabolic pathway is illustrated in Fig. S2 a. The absence of aceticlastic methanogens allows acetate production, for potential use as commodity chemical. The activity of the hydrogenotrophic methanogen mitigates the thermodynamic constraints associated with high hydrogen partial pressure, contributing to the redox balance by removing the excess reducing power (Fig. S2 a). 2 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${ \\text{C}}_{3}{\\text{H}}_{8}{\\text{O}}_{3}+2 {\\text{H}}_{2}\\text{O}{\\to \\text{C}}_{2}{\\text{H}}_{3}{{\\text{O}}_{2}}^{-}+{{\\text{HCO}}_{3}}^{-}+3{\\text{ H}}_{2}+2{\\text{ H}}^{+}$$\\end{document} C 3 H 8 O 3 + 2 H 2 O → C 2 H 3 O 2 - + HCO 3 - + 3 H 2 + 2 H + 3 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$4 {\\text{H}}_{2}+{{\\text{HCO}}_{3}}^{-}+{\\text{H}}^{+}\\to {\\text{CH}}_{4}+3{\\text{ H}}_{2}\\text{O }$$\\end{document} 4 H 2 + HCO 3 - + H + → CH 4 + 3 H 2 O 4 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\text{C}}_{3}{\\text{H}}_{8}{\\text{O}}_{3}\\to {\\text{C}}_{2}{\\text{H}}_{3}{{\\text{O}}_{2}}^{-}+0.75\\text{ C}{\\text{H}}_{4}+0.25\\text{ HC}{{\\text{O}}_{3}}^{-}+0.25 {\\text{H}}_{2}\\text{O}+1.25{\\text{ H}}^{+}$$\\end{document} C 3 H 8 O 3 → C 2 H 3 O 2 - + 0.75 C H 4 + 0.25 HC O 3 - + 0.25 H 2 O + 1.25 H + Syntrophic relationships between fermentative bacteria (e.g., Thermoanaerobacter species, Escherichia coli ) and methanogens were reported to facilitate glycerol fermentation (Magalhães et al. 2020 ; Richter and Gescher 2014 ; Zhang et al. 2015 ). However, co-culture Gly-M incubated with BrES was not able to degrade glycerol, nor to produce methane (Fig. 2 b), highlighting that the presence of the methanogen is essential for glycerol conversion, and pointing to the occurrence of an obligatory syntrophic relationship. Association between sulfate-reducing bacteria, such as Desulfovibrio species and methanogens, has been reported in the absence of sulfate, mostly regarding ethanol and lactate degradation (Rabus et al. 2006 ). Still, Solidesulfovibrio alcoholivorans , S. fructosovorans and S. carbinolicus were reported to degrade glycerol without sulfate in the presence of Methanospirillum hungatei (Qatibi et al. 1998 ; Qatibi et al. 1991a , b ). From the known Solidesulfovibrio strains (former Desulfovibrio sp.), only S. fructosovorans DSM 3604 (Qatibi et al. 1998 ) and S. carbinolicus strain EDK82 (Nanning and Gottschal 1986) are able to perform glycerol fermentation. All the other strains that are known to degrade glycerol can only do it in the presence of sulfate as an external electron acceptor or in syntrophy with a methanogen. After several transfers of Gly-M culture, propionate production was observed, leading to a new line of enrichments—Gly-P. Propionate production has attracted significant attention due to its importance as a chemical building block widely used in various industries, including feed and food preservatives, herbicides, cosmetics, plastics and pharmaceuticals (Ahmadi et al. 2017 ; Gonzalez-Garcia et al. 2017 ). Glycerol conversion to propionate results in higher production yields and less by-products compared to other substrates (Barbirato et al. 1997 ; Chen et al. 2016 ; Coral et al. 2008 ; Dishisha et al. 2015 ), mainly due to the high reduction state of glycerol. Moreover, this conversion is redox-neutral (Fig. S2 b) and yields more energy (Barbirato et al. 1997 ). The closest cultured relative of strain Gly-P, P. pelophilus strain asp66, was reported to be not able to degrade glycerol. The same is the case for all the other Propionivibrio species described (Brune et al. 2002 ; Hansen et al. 1990 ; Tanaka et al. 1990 ; Thrash et al. 2010 ). In fact, by analyzing the genome of P. pelophilus strain asp66 (DSM 12018 T ), at the Integrated Microbial Genomes (IMG) ( https://img.jgi.doe.gov/ ) and at The National Center for Biotechnology Information (NCBI) ( https://www.ncbi.nlm.nih.gov/ ) genomic platforms, it was possible to confirm that this bacterium lacks the genes encoding for the enzymes that are directly linked to glycerol utilization, such as glycerol dehydratase, glycerol dehydrogenase or glycerol kinase (Clomburg and Gonzalez 2013 ). This fact, together with a lower 16S rRNA gene identity than 98.7% (which is the threshold for the same species), points out that strain Gly-P could potentially represent a novel Propionivibrio species. Both Gly-P and Propionivibrio pelophilus strain asp66 (Hansen et al. 1990 ), its closest relative, were unable to grow with ethanol, propanol, butanol and succinate. For all glycerol concentrations tested, propionate yield remained relatively constant (Table 3 ), corroborating the findings of Chen et al. ( 2016 ), who showed a minimal impact on propionate yield with increasing glycerol concentrations. Barbirato et al. ( 1997 ) also reported similar or lower propionate yields for Acidipropionibacterium acidipropionici (Nouioui et al. 2018 ), Cutibacterium acnes (Nouioui et al. 2018 ) and Anaerotignum propionicum (Ueki et al. 2017 ). Additionally, Zhang and Yang ( 2009 ) reported propionate yields from glycerol of 0.67–0.88 mmol mmol −1 (0.54–0.71 g g −1 ) by metabolically engineered Propionibacterium acidipropionici . With the increase in glycerol concentrations, succinate and acetate yields started to increase (Table 3 ), most probably due to inhibition by propionate accumulation. Succinate is a precursor to propionate (Fig. S2 b), and its accumulation in the assays (although at low concentrations) suggests inhibition of the succinate pathway of propionate formation. At the same time, the metabolic flux is also being redirected towards acetate production. End-product inhibition typically constrains propionic acid fermentation processes (Zhang and Yang 2009 ). Among volatile fatty acids, propionate concentrations can have the most significant inhibitory effect on glycerol degradation (Chen et al. 2016 ; Zhang et al. 2015 ), due to product-mediated inhibition on cell growth and metabolic activity (Blanc and Goma 1987 ). Regarding to Gly-S culture (Fig. S2 c), and considering the stoichiometry of the reaction shown in Eq. 5 , electron recovery between 79.4 and 96.8% was calculated for the different glycerol concentrations studied (Table 4 ). 5 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\text{C}}_{3}{\\text{H}}_{8}{\\text{O}}_{3}+0.75\\text{ S}{{\\text{O}}_{4}}^{2-}\\to {\\text{C}}_{2}{\\text{H}}_{3}{{\\text{O}}_{2}}^{-}+{{\\text{HCO}}_{3}}^{-}+0.75\\text{ H}{\\text{S}}^{-}+1.25 {\\text{H}}^{+} +{\\text{H}}_{2}\\text{O}$$\\end{document} C 3 H 8 O 3 + 0.75 S O 4 2 - → C 2 H 3 O 2 - + HCO 3 - + 0.75 H S - + 1.25 H + + H 2 O For glycerol concentrations higher than 30 mmol L −1 , substrate inhibition strongly constrained the activity of this culture (Table 4 ). The capacity of its closest relative, Desulfolutivibrio sulfoxidireducens , to utilize glycerol was previously reported by Bak and Pfennig ( 1987 ), although showing very slow glycerol consumption and very poor growth. Chen et al. ( 2019 ) compared synthetic communities comprising a sulfate reducer ( D. vulgaris strain Hildenborough) and two methanogens, assembled as syntrophic co- or tri-cultures. When the cultures were placed with sulfate, the methane production was highly diminished, which was attributed to a metabolic shift in bacteria towards respiration with sulfate, leading to a disruption in the methanogenic population (Chen et al. 2019 ). A similar biochemical conflict between the different metabolic processes (sulfate reduction and methanogenesis as biological electron acceptor) most probably shaped the microbial specialization observed in Gly-S culture. When Gly-S culture was incubated without sulfate, no growth occurred, but when co-incubated with a methanogenic partner, such as Methanobacterium formicicum , glycerol was slowly converted to acetate and methane, showing that the methanogen was consuming the hydrogen/formate generated from glycerol and working as biological electron acceptor. It is worth recalling that Gly-S culture was enriched from a methanogenic granular sludge, which most probably influenced its metabolic traits. In summary, this work explores the microbial diversity and metabolic specialization of anaerobic microorganisms involved in glycerol conversion and valorization. Three distinct stable cultures were developed, under different environmental conditions, using microbial mixed cultures as biocatalysts. These cultures have the ability to grow and convert glycerol into biocommodities that can be used in industrial applications or as energy carriers. Syntrophic (Gly-M), fermentative (Gly-P) and sulfate-reducing (Gly-S) cultures were obtained, allowing the sustainable treatment and valorization of glycerol. This work contributes to tackle the bottleneck of biodiesel production, caused by the surplus of glycerol. The specialization of cultures that was observed led to product diversification, also contributing to anaerobic process valorization. It was indicated that the top-down design of the microbiome is a promising strategy for not only utilization of troublesome waste but also suitable for dedicated platform chemical production (Lawson et al. 2019 ). The investment in biological methods of environmental-friendly nature is a demand for application at an industrial level and the development of novel bio-based technologies."
} | 3,825 |
36362966 | PMC9693385 | pmc | 5,284 | {
"abstract": "Interactions between metals and microbes are critical in geomicrobiology and vital in microbial ecophysiological processes. Methane-oxidizing bacteria (MOB) and ammonia-oxidizing microorganisms (AOM) are key members in aerobic environments to start the C and N cycles. Ammonia and methane are firstly oxidized by copper-binding metalloproteins, monooxygenases, and diverse iron and copper-containing enzymes that contribute to electron transportation in the energy gain pathway, which is evolutionally connected between MOB and AOM. In this review, we summarized recently updated insight into the diverse physiological pathway of aerobic ammonia and methane oxidation of different MOB and AOM groups and compared the metabolic diversity mediated by different metalloenzymes. The elevation of iron and copper concentrations in ecosystems would be critical in the activity and growth of MOB and AOM, the outcome of which can eventually influence the global C and N cycles. Therefore, we also described the impact of various concentrations of metal compounds on the physiology of MOB and AOM. This review study could give a fundamental strategy to control MOB and AOM in diverse ecosystems because they are significantly related to climate change, eutrophication, and the remediation of contaminated sites for detoxifying pollutants.",
"conclusion": "5. Conclusions and Future Study High concentrations of metals in the environment are introduced from metal-containing inorganic pollutions produced by anthropogenic activity, which has a substantial impact on microbial communities and alters their activity. Understanding carbon and nitrogen cycling at the molecular level may also allow insight into how microorganisms are adapting and benefiting from various metal concentrations at the ecosystem level. This is an important step toward mitigating the further release of greenhouse gases containing carbon and nitrogen into the atmosphere. Aerobic methane and ammonia oxidizers (MOB and AOM) are critical members of the carbon and nitrogen cycle in aerobic environments. Their metabolic capacity is significantly affected by metal compounds. Our review concluded that copper and iron metals are essential for various fundamental and specialized physiological processes in MOB and AOM. They are vital in the functioning of enzymes involved in the oxidation processes, which facilitate the growth and activity of microbes in various environments. On the other hand, high metal concentrations are considered toxic for microbial communities. However, further studies are still needed to address the unsolved question in our knowledge of trace metal physiology. For example, (i) comprehending the uptake system of metal or complex of metal-ligands by AOM, (ii) the ammonia oxidation activity affected by methanobactin on AOM growing culture in limited or excess metal conditions, (iii) co-metabolism of methane oxidation by AOA and comammcox with different metal concentrations, and (iv) relationships between metal bioavailability and fluxes of greenhouse gases produced by MOB and AOM. This review study could provide essential information for future works, not only to answer these fundamental questions regarding the ecology and physiology of MOB and AOM in diverse ecosystems but also for comprehending and managing C and N cycles in nature.",
"introduction": "1. Introduction Nitrogen is an essential element for all living life on our planet, as it is a component of nucleic acids and proteins and constitutes most of the atmosphere, around 80%. The nitrogen in the ecosystem is cycled by various biological processes such as nitrogen fixation, nitrification, denitrification, assimilation, and ammonification. These processes include anaerobic nitrate reduction to ammonium (DNRA), denitrification of anaerobic methane oxidation (DAMO), and dissimilatory nitrate reduction to ammonium (DNRA) [ 1 ]. Nitrification is a vital process of the global biogeochemical nitrogen cycle. It plays a significant role in fertilizer loss in industrial agriculture, eutrophication, and the production of greenhouse gas N 2 O, which has a very long residence time in the atmosphere (120 years). Furthermore, it contributes to ozone destruction by reacting with the atomic oxygen to form nitric oxide (NO) in the atmosphere [ 2 ]. On the other hand, nitrification is essential for efficient sewage treatment. The aerobic oxidation of ammonia initiates nitrification by ammonia-oxidizing microorganisms (AOM), which is mediated by three distinct groups of aerobic autotrophic ammonia oxidizers: (i) ammonia-oxidizing bacteria (AOB), (ii) ammonia oxidizing-archaea (AOA), and (iii) complete ammonia-oxidizing bacteria (Comammox) [ 1 ]. Ammonia is also oxidized by the anammox (anaerobic ammonium oxidation) process in the anaerobic system [ 3 ] and also oxidized by the heterotrophic and fungal nitrification process [ 4 ]. However, these oxidation processes involve completely different physiological pathways compared to the canonical aerobic oxidation in AOM (see details below). Hence, in this review, we focused on canonical aerobic ammonia oxidation, which is physiologically comparable to the aerobic methane oxidation pathway. Carbon dioxide (CO 2 ) is the most prevalent greenhouse gas accounting for 95% of all emissions. The following two gases are methane (CH 4 ) and nitrous oxide (N 2 O), which have a substantial impact on the climate [ 2 ]. Despite having atmospheric concentrations of ~1800 parts per billion (ppb) for CH 4 and ~330 ppb for N 2 O [ 5 ], respectively, they are 25 and 300 times more effective at absorbing infrared light than CO 2 . Anaerobic decomposition of organic matter produces CH 4 and later transforms it into CO 2 , increasing total atmospheric CO 2 concentration. As a source of energy, methanotrophs (MOB; aerobic methane-oxidizing bacteria) are primarily responsible for the enzymatic oxidation of CH 4 . The aerobic and anaerobic methanotrophic reactions consume about 35% (0.6 Gt, gigatonne), and 18% (0.3 Gt) of the global CH 4 production per year, respectively [ 6 ]. Canonical aerobic methane oxidation is performed by certain bacteria that combine molecular oxygen with CH 4 to produce methanol (CH 3 OH), then the methanol is oxidized into formaldehyde (CH 2 O), and then finally oxidized to CO 2 via formate (CH 2 O 2 ) using either the serine or ribulose monophosphate pathway ( Figure 1 and details see below) [ 7 ]. An anaerobic pathway of reverse methanogenesis is believed to oxidize methane by the ANME group of archaea [ 6 , 8 ], Methanosarcinales and Methanomicrobiales , which are closely associated with sulfate-reducing gamma-proteobacteria [ 9 ]. Interactions between microbes and trace metals such as copper (Cu), zinc (Zn), cobalt (Co), molybdenum (Mo), selenium (Se), manganese (Mn), and iron (Fe) are important in nature. Metals can influence microbial growth, activity, and survival directly (such as making metalloenzyme; see below) or indirectly [ 10 ]; thus, it is not unusual that they deal with them, sometimes to their use (bioavailable), often to their harm (toxic), when present at high enough concentrations [ 11 ]. Microorganisms can bind metal ions and transport them into the cells for various purposes, such as electron donors or acceptors in metabolic activities [ 12 ]. Most enzyme classes contain metalloenzymes, which are metal-bound proteins having a labile coordination site. The metal ion with a substrate-compatible shape is usually located in the active site of metalloenzymes. Therefore, as with all enzymes, the shape of the active site is crucial. Despite the intricacy of organic chemistry reactions, metal ions can execute such reactions that are challenging to achieve. The Irving-Williams stability series defines the order of affinity for essential divalent cations. In addition, the required concentration of trace metal can be calculated by the speciation of metals in solution, based on equilibrium stability constants ( K ) which is the strength of the interaction between metals and the ligands that come together to form the complex [ 13 ]. Therefore, the microbes must deal with enough metal atoms to satisfy the protein requirements; however, not all metals are bioavailable. In the environmental system, metals are found in various forms, including the hydrated free ion, inorganic complexes (with ligands such as Cl − , OH − , CO 3 2− ), organic complexes (with simple organic molecules of biogenic or anthropogenic origin, and with natural organic matter, NOM), as well as in colloidal and other solid phase forms. It is well known that ligand concentration, temperature, pH, and redox state determine the partitioning (bioavailability and toxicity) of metals among the different forms [ 14 , 15 ]. In the natural environment, metals are usually present in complex and colloidal forms and are rarely found in free form [ 16 ]. The concentration of free metal ions can be decreased in the presence of chelating agents such as various organics and ethylenediaminetetraacetic acid (EDTA) or due to pH fluctuations. In addition, the stability of metalloenzymes can be affected by buffer complexations with metals. The free metal ion concentration in environmental systems is the best predictor of both bioaccumulation and toxicity of cationic metals [ 17 , 18 ]. Therefore, the bioavailability and toxicity of metals for microbes are dependent on (i) the ionic strength of a medium, (ii) the presence of organic matter, (iii) pH, (iv) redox potential, and (v) valence state. All these factors may favor the formation of different metal species with high or low bioavailability and toxicity [ 19 ]. Although MOB and AOM are substrate-specific, preferring CH 4 and NH 3 , respectively, they can interact with one another in various ways [ 20 ]. Such interactions include the influence of ammonium on methane oxidation and MOB growth [ 21 ]. Moreover, MOB and AOB also share many physiological, structural, and ecological characteristics, including reliance on monooxygenase reactions catalyzed by the copper-containing membrane-bound monooxygenase superfamily ( Figure 1 and see details below) [ 22 ], intracellular membrane systems, sensitivity to the same inhibitors, possession of hydroxylamine oxidoreductase systems, and the ability to grow in oxic environments [ 23 ]. Methane monooxygenase (MMO) in methanotrophs and ammonia monooxygenase (AMO) in ammonia oxidizers have evolved to be functionally identical, and they are capable of oxidizing both methane and ammonia [ 24 ]. Furthermore, interactions between methanotrophs and AOM and the effects of carbon and nitrogen cycles have rarely been studied in complex natural ecosystems because they are the critical member of global carbon and nitrogen cycles, respectively [ 23 ]. Copper is one of the important trace metals involved in various fundamental and specialized physiological processes, including electron transfer, oxygen transport, superoxide detoxification, denitrification, and ammonia and methane oxidation. Similar to other critical trace metals such as iron, copper is found in small amounts in the ocean, and is heavily complexed by organic ligands, which reduce the inorganic dissolved free metal [ 25 ]. It is suggested that Fe promotes the growth of various marine N-cycling microorganisms in a substantial section of oceans [ 26 ]. However, it is yet to be determined if metal availability influences the biological niche separation of AOM and MOB in the environmental systems. Therefore, it is crucial to know how AOM and MOB are affected by the fluctuations in metal concentrations, especially Cu and Fe, which will be covered in this review paper. Collectively, since they are necessary for the enzymes involved in ammonia and methane oxidation, Cu and Fe are critically important for the growth and activity of microbes. However, high metal concentrations above the cell capacity could be toxic for microbes. In this review, we focused on aerobic ammonia and methane oxidation pathways mediated by metals and the impact of various metal concentrations. Especially Cu and Fe, on ammonia and methane oxidizers in in vitro and in situ systems, and different metal uptake strategies."
} | 3,055 |
33288773 | PMC7721750 | pmc | 5,285 | {
"abstract": "Understanding the inner behaviour of multilayer perceptrons during and after training is a goal of paramount importance for many researchers worldwide. This article experimentally shows that relevant patterns emerge upon training, which are typically related to the underlying problem difficulty. The occurrence of these patterns is highlighted by means of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams, a 2D graphical tool originally devised to support the work of researchers on classifier performance evaluation and on feature assessment. The underlying assumption being that multilayer perceptrons are powerful engines for feature encoding, hidden layers have been inspected as they were in fact hosting new input features. Interestingly, there are problems that appear difficult if dealt with using a single hidden layer, whereas they turn out to be easier upon the addition of further layers. The experimental findings reported in this article give further support to the standpoint according to which implementing neural architectures with multiple layers may help to boost their generalisation ability. A generic training strategy inspired by some relevant recommendations of deep learning has also been devised. A basic implementation of this strategy has been thoroughly used during the experiments aimed at identifying relevant patterns inside multilayer perceptrons. Further experiments performed in a comparative setting have shown that it could be adopted as viable alternative to the classical backpropagation algorithm.",
"conclusion": "Conclusion This article has shown that relevant patterns arise inside MLPs upon training, as clearly highlighted by the \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ signatures of their hidden layers. In particular, the analysis has experimentally demonstrated that, upon training, clear patterns representing success or failure typically hold. The existence of patterns that lay half-way between success and failure has also been highlighted. To facilitate the analysis on MLPs equipped with more than one hidden layer, a layer-wise training strategy has been devised and implemented, called progressive training. In this strategy, layers are individually trained starting from the one in charge of processing the given inputs. Despite the fact that this is a methodological article, experimental results show that progressive training appears a viable alternative to the backpropagation algorithm. As for future work, several research activities are under way, including (i) getting a better understanding of the connection between MLP relevant patterns and training parameters, (ii) devising a general criterion for stopping the training as soon as a success pattern is found, (iii) devising proper pruning strategies, entrusted with the deletion of neurons deemed useless; (iv) investigating the causes that generate half-way patterns; and (v) characterising progressive training from an information theory perspective. Notably, after reaching theoretical and/or experimental findings on the cited issues, setting up an adaptive training strategy in which the final shape of a neural architecture is not known in advance should no longer be an unattainable goal.",
"introduction": "Introduction Artificial Neural Networks (ANNs), and in particular multilayer perceptrons (MLPs), are a tool of paramount importance for machine learning and pattern recognition, thanks to their effectiveness and flexibility. As the classical formulation of the backpropagation algorithm (see for example Rumelhart et al. 1 ) follows the guidelines of gradient descent, the mainstream in the research on ANNs has been focusing on how to escape from local minima (see for example Lo et al. 2 and Atakulreka and Sutivong 3 ). Related works explore the hypothesis that local minima lead to performances that are similar to the one obtained by reaching the global minimum (see for example Choromanska et al. 4 ). The problem of saddle points has also been investigated, trying to verify the assumption that finding local minima is actually not a problem (see for instance Pascanu et al. 5 and Dauphin et al. 6 on this matter). Further studies have been performed by relaxing the classical training strategy in various ways. Let us recall only the proposals that fall under the umbrella of stochastic gradient descent (SGD), as they have become a de facto standard for training modern MLP architectures. These proposals share a common ancestor, i.e., the pioneering work of Robbins and Monro 7 . Recent variations of this motif include in particular Adagrad 8 RMSProp (by Tieleman and Hinton, 2012—unpublished), Momentum 9 Adam 10 and kSGD 11 . Without claiming to be exhaustive, other proposals made in recent years that go beyond the cited SGD strategy are briefly recalled hereinafter. Lee et al. 12 explore a novel approach to credit assignment in deep neural networks (DNNs), called target propagation. The underlying idea is to compute, at each layer, targets rather than gradients. Like gradients, targets are propagated backwards; however, this process relies on autoencoders (see Hinton and Salakhutdinov 13 ). Lillicrap et al. 14 propose a mechanism, called feedback alignment, which assigns blame by multiplying errors even by random synaptic weights. The authors show that this mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Following the work on feedback alignment, Nøkland 15 shows that the error can also be propagated, through fixed random connections, directly from the output layer to each hidden layer. Moreover, Frerix et al. 16 propose an algorithm that takes implicit rather than explicit gradient steps to update the network parameters during training. With the advent of DNNs, a renewed interest has been shown in the problem of how to get insights about the inner behaviour of neural architectures. Alain and Bengio 17 propose to measure how suitable are for classification the features that occur at every layer of a model. To this end, the authors use linear classifiers (named probes), which are trained independently of the model itself. Information theory has also been used as prominent formal tool in the attempt of unveiling relevant properties of ANNs equipped with multiple layers. According to this grounded view, entropy and related concepts (in particular, mutual information) have been used to capture the flow of the information throughout the layers of neural architectures. Achille and Soatto 18 show that invariance to nuisance factors in a DNN is equivalent to information minimality of the learned representation, and that stacking layers and injecting noise during training naturally bias the network towards learning invariant representations. Following the work of Tishby et. al 19 and of Tishby and Zaslavsky 20 , Shwartz-Ziv and Tishby 21 point out that any internal representation of a DNN can be seen as the combination of an encoder and a decoder. Starting from this concept, the authors show that this combination can be quantified by its information plane coordinates and that the optimal representations are constrained by the Information Bottleneck bound. Moreover, they show that most of the training epochs in standard deep learning are spent on input compression rather than on fitting the training labels. The authors emphasize that this generalization mechanism is unique to DNNs and absent in classical networks equipped with one hidden layer. Moreover, they show that the training time is dramatically reduced when adding more hidden layers. Wickstrøm et al. 22 suggest that the goal of a network is to optimize, for each layer, the trade-off between compression and prediction. They propose a framework for information plane analysis able to shed new light on small-scale DNNs, with the final goal of analysing contemporary large-scale DNNs. According to Yang et al. 23 , performance and model explainability are the two most important objectives when developing machine learning algorithms to solve real-world problems. More recently, Yu and Principe 24 point out that, despite their great success in practical applications, there is still room for analysing DNNs from a theoretical (and systematic) perspective. These concerns also originated a DARPA program launched in 2016, aimed at improving eXplainability in AI systems 25 . The goal of this program is to enact the definition or modification of machine learning techniques aimed at producing explainable models. Relevant issues along this perspective are (i) the types of measures to be adopted, being aware that accuracy, in its standard definition, may not be a proper tool for revealing the quality of a learned model; and (ii) the need for suitable tools aimed at investigating and visually inspecting the inner behaviour of MLPs. In a 2010 article, Valverde-Albacete and Peláez-Moreno 26 propose the adoption of entropic measures based on the confusion matrices that characterize the behaviour of multi-class classifiers. The authors end up with a measure reported in a three-dimensional entropy space, which can be further projected in a two-dimensional space as De Finetti entropy diagram. In a subsequent article 27 the same authors point out that the most widely acknowledged measure of performance, i.e., accuracy, may fail to capture crucial information transfer in the classification task. To show evidence of this unwanted behaviour, the authors use the entropy triangle to perform a combinatorial analysis on variously sized confusion matrices. In fact, it is well known that accuracy can give information about the actual discrimination capability of a classifier only when negative and positive data are perfectly balanced. To deal with the difficulties of applying accuracy in its classical definition, the authors propose another measure, called “entropy-modulated accuracy”, in which the influence of the input distribution is factored out. According to the author claims, this is a more natural measure of classification performance than accuracy when the heuristic to maximize is the transfer of information through the classifier instead of classification error count. In 2015, Armano 28 proposed \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ measures and diagrams, the latter being a diamond-shaped 2D graphical tool devised to support the work of researchers on binary classifier performance evaluation and on feature assessment. This proposal is rooted on specificity and sensitivity, as done for ROC curves 29 . Hence, the visual inspection proceeds by pretending that the underlying data are in fact balanced. When used for feature assessment, these diagrams allow to depict the so-called class signature (or signature , for short), which is obtained by reporting the behaviour of each feature, seen as an elementary classifier, with respect to the positive category. Being aimed at at shedding new light on the inner behaviour of MLPs, this article falls in the the frame of eXplainable AI. The underlying conjecture is that specific patterns are expected to arise at the hidden layers of an MLP upon training. In turn, this conjecture is supported by the assumption that MLPs are very effective feature encoders. Not incidentally, this assumption is in full accordance with the cited analysis of Swhartz-Ziv and Tishby 21 , who observe that—fixing any hidden layer—the part of the MLP that originates from the inputs plays the role of encoder, whereas the part headed to the output(s) plays the role of decoder. According to this view, the neurons of a hidden layer can always be seen as an alternative representation of the given inputs, as they are in fact projected onto another feature space. Beyond the close connection between this interpretation and entropy-based measures (in particular, mutual information), the assumption is apparently sound also thinking of the MLP as a device that progressively tries to make its embedded features, represented by the neurons of the hidden layers, covariant with one of the given categories. Given that the hidden layers of any MLP can be seen as alternative input sources, they have been investigated by means of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams, with the goal of highlighting the occurrence of relevant patterns able to give information about the generalisation ability of the MLP over the problems at hand. To better investigate the occurrence of these patterns, a training strategy inspired by some relevant recommendations of deep learning (see in particular Bengio et al. 30 , Nøkland 15 and Juefei-Xu et al. 31 ) has also been devised and implemented. In this strategy (called progressive training ) each layer is trained in isolation, starting with the one in charge of processing the given inputs and going forward until the output layer is reached. After this clarification, the reader should be aware that this proposal is mainly framed around a methodological perspective , aimed at showing that relevant patterns can be found at the hidden layers of an MLP upon training. The remainder of this article is organised as follows: starting with a brief and informal introduction to \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams, “ Results ” reports experimental results, pointing in particular to the rise of relevant patterns inside MLPs able to account for the generalisation process. This section also reports information about the effectiveness of the proposed progressive training algorithm (PT for short, hereinafter), in comparison with the classical backpropagation algorithm (BP for short, hereinafter). “ Discussion ” makes further comments on the ability of MLPs to act as feature encoders and on the occurrence of relevant patterns inside MLPs. The role of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams in the task of devising more effective training strategies and the possibility of using MLPs and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams in combination to perform multivariate analysis are also discussed. “ Methods ” illustrates the main characteristics of PT, also focusing on its pragmatic and theoretical roots. “ Conclusion ” draws conclusions and outlines future work.\n\nInformal introduction to \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams Although in this article \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams play a gregarious role, their main concepts are summarized hereinafter for the sake of clarity. Further details on this matter are reported in the Supplementary Information (Supplementary section S1 ) available online. The interested reader may also find an extensive study on their semantics in Armano and Giuliani 32 . Figure 1 Class signature of the dataset optdigits, downloaded from the UC Irvine machine learning repository (UCI, hereinafter). Each sample is encoded with an image of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$32 \\times 32$$\\end{document} 32 × 32 B/W pixels, for a total of 1024 binary features. The multiclass problem has been binarized considering the digit 0 as positive category and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$1, 2, \\ldots , 9$$\\end{document} 1 , 2 , … , 9 as negative category. Each point in the diagram represents the “performance” of a feature, considered as an elementary classifier. Feature importance is highlighted by a scale of colours: from red (not relevant) to blue (highly relevant). Intermediate values are represented with yellow, green and light blue, depending on the corresponding feature importance (from lower to higher). Due to the presence of several points with high value of |δ|, the problem is expected to be easy. The measures that give rise to the \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ space are defined as: \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\varphi = \\rho - \\overline{\\rho }$$\\end{document} φ = ρ - ρ ¯ and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\delta = \\rho + \\overline{\\rho }- 1$$\\end{document} δ = ρ + ρ ¯ - 1 , where \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\overline{\\rho }$$\\end{document} ρ ¯ and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\rho$$\\end{document} ρ denote specificity and sensitivity. Upon normalisation, the values of any feature that occurs in the given dataset --as found in the available training samples--can always be seen as the outputs of an elementary (single-feature) classifier. Hence, to draw the class signature of the dataset, first the \"performance\" of each feature with respect to the positive category is evaluated, and then all corresponding values (in terms of φ and δ) are reported in a diagram. Figure 1 shows an example of how \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams can be used for feature assessment, by depicting the signature of the dataset optdigits . It is worth to highlight that φ coincides with the horizontal axis, whereas δ with the vertical one. In the cited figure, points have different colours, which account for their importance; in particular, blue points are assumed to be highly useful for the classification process and vice versa for red points. However, note that hereinafter the colour map will be automatically rescaled according to the difference between minimum and maximum value of |δ|. This choice has been taken to facilitate the reader at visually ranking points even when the values of |δ| have low dynamics. According to the given definitions, both measures range in the interval [− 1, + 1], and their underlying semantics is the following: \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\varphi$$\\end{document} φ estimates the bias of a feature with respect to the positive (and negative) category on the given dataset, whereas (though stretched in \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$[-1,+1]$$\\end{document} [ - 1 , + 1 ] ) \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\delta$$\\end{document} δ gives the accuracy of a feature with respect to the positive category. Note that, being given in terms of specificity and sensitivity, φ and δ are both independent of the actual balancing between negative and positive samples. It can be easily shown that \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\varphi$$\\end{document} φ is the locus of points such that the mutual information between a feature and the positive or negative category drops to zero. Hence, features laying close to this axis (i.e., such that \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\vert \\delta \\vert \\approx 0$$\\end{document} | δ | ≈ 0 ) are expected to provide limited or negligible support to the classification process. This is true for the whole axis, although with different semantics (in particular, features independent of either class label lay at the crossing of the \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\varphi$$\\end{document} φ and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\delta$$\\end{document} δ axes). As for \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\delta$$\\end{document} δ , by construction, it gives information about the degree of agreement (or disagreement) between a feature and the positive category. In case of agreement (upper corner), the feature is said to be covariant with the positive category, whereas in case of disagreement (lower corner) it is said to be contravariant. Features whose \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\delta$$\\end{document} δ value is close to the upper or lower corner are expected to give strong support to the classification process. The fact that both highly covariant and highly contravariant features are equally important should not be surprising, as selecting a class as positive or negative is just an arbitrary choice.",
"discussion": "Discussion In this section, further comments are given on the following aspects: (i) the capability of MLPs to act as feature encoders when trained with PT; (ii) the occurrence of relevant patterns inside MLPs; (iii) the role of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams in the task of devising more effective training strategies; and (iv) the possibility of using MLPs and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams in combination to perform multivariate analysis. The insight that lays behind the work described in this article is that MLPs are very effective feature encoders and that relevant patterns arise upon training. The soundness of this insight is also supported by the ongoing research on deep learning, which has fully adopted autoencoders (see Bourlard and Kamp 41 and Hinton and Zemel 42 ) as a mean for implementing feature extraction according to an unsupervised perspective. However, the process of encoding features is not necessarily unsupervised. In fact, applying backpropagation allows to generate different encodings of the input features at each hidden layer, driven by the errors evidenced at the output layer. This process of feature encoding is particularly effective for PT, in which hidden layers are trained one at a time, using mean square error as loss function. In so doing, the transformation of inputs from a layer to another is progressively driven by a generative thrust aimed at making the new encodings more covariant or contravariant with the positive category. Besides, many comments reported in Shwartz-Ziv and Tishby 21 have been experimentally assessed while checking the soundness of PT. In fact, on average, the proposed strategy appears as least as effective as BP, allows to better highlight the input compression mechanism, and typically shows a shorter training time. As for the occurrence of relevant patterns inside MLPs, experimental assessments made over a great number of datasets, have shown that the following significant kinds of pattern hold: failure, success and partial success. Failure patterns point to the inability of the MLP to come up with new feature spaces laying as far as possible from the \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\varphi$$\\end{document} φ -axis. This kind of patterns has been extensively studied, and the difference between a failure due to the inability of the network to come up with a suitable generalisation has been distinguished from other causes related to algorithmic issues. In particular, the former case is typically evidenced by neurons located close to the centre of the \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagram, whereas the latter (which highlights the occurrence of saturation) is typically evidenced by neurons that lay in proximity of the left and/or right corner(s). Needless to say that these two cases can occur jointly. As for success patterns, they hold when the training activity has generated neurons that are highly covariant or highly contravariant with the positive category. Typically, one cluster is found in proximity of the upper corner and another in proximity of the lower; however, also a single cluster may occur. Experimental results demonstrated that, once achieved, any such pattern tends to be steady. In particular, assuming that a researcher has decided that the MLP at hand should have a shape of length N and that a success pattern has been found at a layer \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$k^{*} < N$$\\end{document} k ∗ < N , the point here is whether training the remaining layers may improve or not the final performance. Experiments performed on many different problems highlight that negligible improvement can be obtained after \n \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$k^{*}$$\\end{document} k ∗ , as at all layers \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$k > k^{*}$$\\end{document} k > k ∗ similar patterns of generalisation success would be reproduced. Figure 10 reports the signatures of an MLP equipped with four hidden layers (all with the same number of neurons) and trained on the WBC dataset. The figure shows that only marginal changes characterize a hidden layer with respect to the others, highlighting that a pattern of success holds on all layers. The lack of relevance regarding these variations has been assessed by removing all hidden layers but the first. In fact, as expected, the classification performance was not affected by the removal. Notably, the steadiness of success patterns appears very important for devising adaptive training strategies in which the shape of an MLP is not a priori defined. Patterns of partial success occur when clusters of neurons tend to attain the upper and/or the lower corner, but with limited success (in other words, these clusters typically stand half-way between the \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\varphi$$\\end{document} φ -axis and the upper and/or lower corners). One reasonable hypothesis that may explain their occurrence consists of assuming that they originate from the intrinsic difficulty of the dataset at hand. A more interesting hypothesis, which however does not rule out the previous one, is that this kind of pattern accounts for the limitations of BP. In the event that at least part of the responsibility for the occurrence of half-way patterns is due to the gradient descent enforced by backpropagation, there is room for experimenting alternative training strategies (e.g., SGD) able to inject the pseudo-random behaviour required to escape from local minima. Also these patterns tend to be steady, thus highlighting that there is no guarantee for PT to come up with a better generalization just adding further layers. Notably, the presence of half-way patterns is consistent with the findings of Salakhutdinov and Murray 43 and of Larochelle and Bengio 44 , who point out that deep architectures cannot be considered better than shallow ones on every problem. This proposal also highlights the role of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams in the task of devising more effective training strategies. In particular, the fact that the inner behaviour of MLPs can be investigated with proper visual and computational tools (i.e., \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams and measures) promotes the opening of new scenarios, in which further relevant techniques could be borrowed from the machine learning and pattern recognition communities and adapted to this research topic. For instance, assuming that PT is used, one may focus on the advantage of pruning the current layer before training the next. The benefit of applying pruning should not be surprising, as the \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ analysis performed on hidden layers allowed to verify that they may contain neurons which are apparently not useful for the classification task (e.g., those that lay in proximity of the left or right corner). A simple pruning strategy would consist of devising a proper cost function and use it for ranking neurons with the goal of identifying candidates for deletion. Rather than adopting entropy or Gini index, which appear more convenient for identifying neurons characterised by low accuracy in a MAP setting 45 , one may be interested at minimising the bias as well (i.e., at trying to make specificity and sensitivity as equal as possible while maximising the accuracy). Which cost functions appear more appropriate for enforcing bias minimisation is still a matter of investigation. In any case, the opportunity of visually inspecting hidden layers by means of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagram should greatly help rapid advances in this research topic. The reader interested in pruning and compression techniques may also consult –for instance– the review articles of Augasta and Kathirvalavakumar 46 and of Cheng et al. 47 . Alternative pruning strategies may be devised also considering that, at least in principle, any layer of an MLP could be seen as an ensemble—the role of individual classifiers being played by the corresponding neurons. According to this view, an appropriate pruning strategy might be devised in accordance with the proposals concerning the trade-off between diversity and accuracy, as investigated by the community of classifier ensembles (see for example Kuncheva and Whitaker 48 and Bhatnagar et al. 49 ). Notably, this view is indirectly confirmed by the adoption of softmax 50 in two relevant scenarios: (i) as output blender for classifier ensembles, e.g., Memisevic et al. 51 , and (ii) as output combiner for CNNs, e.g., Krizhevsky et al. 52 and Liu et al. 53 . The last comments of this section are devoted to highlight the potential of using MLPs and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams in combination to perform multivariate analysis. In 28 the author points to the ability of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams to make feature-importance analysis by calculating the class signature on the given dataset (recall that class signatures fall into the broad category of univariate analysis, as they concentrate on each feature taken in isolation). Class signatures are in fact “semi-decidable”, meaning that when at least one feature highly covariant or contravariant with the positive category is found, then the problem at hand is certainly easy. Unfortunately, the converse is not true. In other words, when no good features are found, one may conjecture that the problem is difficult, but further supporting information is needed to complete the assessment. Fortunately, training an MLP on the given dataset can shed more light on its actual difficulty. Again, a failure (i.e., an MLP with limited generalisation capability) would not necessarily mean that the problem is in fact hard to solve. However, the identification of a success pattern at any hidden layer would turn the appraisal from potentially-difficult to easy. This support for decision making is obtained by providing the researcher with manifold class signatures, one for each layer (including the one evaluated on inputs.) Although each signature is made according to a univariate perspective, those evaluated at the hidden layers can give strong support to multivariate analyses, as the neurons therein may provide useful combinations of input features (depending on the work done by the adopted training algorithm). An evidence about the shortcomings of univariate analysis has been given before with the synthetic xor problem. This is a characteristic example of how univariate analysis may fail while multivariate analysis (obtained by the combined use of MLPs and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\langle \\varphi ,\\delta \\rangle$$\\end{document} ⟨ φ , δ ⟩ diagrams) may succeed. Figure 10 Hidden layers of an MLP trained on the dataset WBC (Wisconsin Breast Cancer) from UCI. To give a flavour of the underlying process, PT has been performed on an MLP architecture equipped with four hidden layers, all with the same number of neurons (i.e., 10). The corresponding signatures highlight that the same pattern of generalisation success is duplicated along the hidden layers."
} | 10,333 |
21972240 | PMC3187577 | pmc | 5,286 | {
"abstract": "ABSTRACT The genus Cyanothece comprises unicellular cyanobacteria that are morphologically diverse and ecologically versatile. Studies over the last decade have established members of this genus to be important components of the marine ecosystem, contributing significantly to the nitrogen and carbon cycle. System-level studies of Cyanothece sp. ATCC 51142, a prototypic member of this group, revealed many interesting metabolic attributes. To identify the metabolic traits that define this class of cyanobacteria, five additional Cyanothece strains were sequenced to completion. The presence of a large, contiguous nitrogenase gene cluster and the ability to carry out aerobic nitrogen fixation distinguish Cyanothece as a genus of unicellular, aerobic nitrogen-fixing cyanobacteria. Cyanothece cells can create an anoxic intracellular environment at night, allowing oxygen-sensitive processes to take place in these oxygenic organisms. Large carbohydrate reserves accumulate in the cells during the day, ensuring sufficient energy for the processes that require the anoxic phase of the cells. Our study indicates that this genus maintains a plastic genome, incorporating new metabolic capabilities while simultaneously retaining archaic metabolic traits, a unique combination which provides the flexibility to adapt to various ecological and environmental conditions. Rearrangement of the nitrogenase cluster in Cyanothece sp. strain 7425 and the concomitant loss of its aerobic nitrogen-fixing ability suggest that a similar mechanism might have been at play in cyanobacterial strains that eventually lost their nitrogen-fixing ability.",
"introduction": "Introduction Cyanobacteria constitute a fascinating group of photosynthetic prokaryotes that have inhabited almost every sunlit ecosystem of the earth for ~3 billion years. The remarkable success of this group of microbes in adapting to a wide range of environmental and ecological conditions has largely been attributed to the presence of an extraordinarily flexible repertoire of metabolic pathways ( 1 , 2 ). Cyanobacteria possessed an efficient cellular machinery to function in anaerobic environments that prevailed during the mid-/late Archaean era, and their metabolic activities are credited for the transitioning of the earth into the present-day oxygen-rich environment ( 3 ). In fact, many of the archaic metabolic traits have been retained in extant cyanobacterial species, enabling them to thrive in many diverse ecological niches. The metabolic feats of cyanobacteria are exemplified by the ability of some strains to fix molecular nitrogen, a process sensitive to oxygen ( 4 ) and not found in any other known oxygenic organism ( 5 , 6 ). Cyanobacteria have adapted various strategies to meet the cellular demands of nitrogen fixation, the most critical being the protection of the oxygen-sensitive nitrogenase enzyme ( 7 ). While some filamentous strains have developed specialized cells, called heterocysts, to accommodate this process, unicellular strains make use of the diurnal cycle to separate oxygen-evolving photosynthesis from oxygen-sensitive nitrogen fixation ( 8 , 9 ). Recent studies have demonstrated the importance of unicellular nitrogen-fixing cyanobacteria in the marine nitrogen and carbon cycle ( 10 , 11 ). The efficiency of nitrogen fixation exhibited by these microbes during the dark period of a day/night cycle suggests that they must have the ability to harvest and store sufficient solar energy during the day, which in turn fuels the energy-intensive nitrogen-fixing process at night. The suboxic intracellular conditions that are maintained during the nitrogen fixation period also facilitate various fermentative processes that are commonly observed in many facultative and obligate anaerobes ( 12 , 13 ). Cyanothece is a genus of morphologically diverse, unicellular cyanobacteria that are known to inhabit a variety of ecological niches. This genus was created by Komárek ( 14 ) to include unicellular cyanobacteria with distinct morphological, ultrastructural, and genomic features ( 15 – 17 ). Cyanothece strains from various ecotypes have been studied in the past for their robust circadian rhythm, fermentative capabilities, and other biotechnological applications ( 12 , 18 , 19 ). Cyanothece sp. ATCC 51142 [hereinafter referred to as Cyanothece 51142], a prototypic member of this genus, was isolated from the Texas Gulf Coast and is one of the most potent diazotrophic strains yet characterized ( 20 ). System-level studies with Cyanothece 51142 revealed many novel metabolic traits of this unicellular cyanobacterium which led to the determination of its genome sequence at the Washington University sequencing center ( 21 ). The studies revealed robust diurnal and circadian cycling of central metabolic processes in this strain, as well as a strong coordination of correlated processes at the transcriptional level ( 22 ). Interestingly, genome analysis of Cyanothece 51142 uncovered the presence of a 430-kb functional linear chromosomal element, the first such element to be identified in any photosynthetic bacterium. The arrangement of genes on this chromosome suggested a specific role for it in energy metabolism, and it was hypothesized that such linear elements with regulatory functions might be a distinctive trait of the genus Cyanothece ( 21 ). Also interesting from the genomic perspective is the finding that some atypical nitrogen-fixing strains, such as the endosymbiont spheroid body of the eukaryotic diatom Rhopalodia gibba and the unicellular marine cyanobacterium UCYN-A, which lacks photosystem II, have genomes closely related to those of Cyanothece spp. ( 23 , 24 ). In particular, the nitrogenase gene clusters in both of these organisms is highly similar to that in Cyanothece 51142. It has been hypothesized that these organisms may have evolved as a result of targeted gene loss (loss of genes involved in photosynthesis while maintaining an elaborate gene cluster involved in nitrogen fixation) from a Cyanothece -like ancestor ( 23 ), thus suggesting a highly plastic nature of Cyanothece genomes as well as the robustness of their nitrogen-fixing machinery. The most striking of the unique metabolic capabilities of Cyanothece 51142 is that cells can exhibit high rates of nitrogenase-mediated H 2 production under aerobic conditions, an unusual metabolic trait in oxygenic phototrophs ( 25 ). Furthermore, the metabolic versatility of this strain was demonstrated by its ability to switch between photoautotrophic and photoheterotrophic modes of metabolism depending on the availability of external carbon sources and the presence of an atypical alternative citramalate pathway for isoleucine biosynthesis ( 26 ). In an effort to unravel the genomic basis of the observed metabolic traits of unicellular diazotrophic cyanobacteria, the genomes of five additional members of the genus Cyanothece ( Cyanothece sp. strains PCC 7424, PCC 7425, PCC 7822, PCC 8801, and PCC 8802 [hereinafter referred to as Cyanothece 7424, 7425, 7822, 8801, and 8802]) were sequenced at the Joint Genome Institute, U.S. Department of Energy. The strains were collected from different geographical locations and exhibit considerable diversity with respect to cell size and pigment composition. A comparison of the genomes of the different Cyanothece strains revealed that members of this genus are metabolically versatile, each member having acquired unique metabolic capabilities. The capability of aerobic nitrogen fixation and the presence of a large, contiguous nif gene cluster distinguish this group of unicellular photosynthetic microbes. Analysis of the genes common and unique to five of the six Cyanothece strains revealed that the core Cyanothece genomes is an amalgamation of genes from strains associated with fermentative capabilities, such as Microcystis and Microcoleus strains, and from aerobic nitrogen-fixing filamentous strains. The key to the success of this group of organisms appears to lie in their ability to retain such useful metabolic traits as nitrogen fixation and anaerobic fermentation while simultaneously adapting and accommodating advanced cellular features of contemporary photosynthetic organisms.",
"discussion": "DISCUSSION Our analyses of the six completely sequenced Cyanothece genomes revealed that many key metabolic features were conserved during evolution, while considerable diversity was also gained ( Fig. 2 ). The metabolic traits common to the six Cyanothece strains are shared by many other cyanobacteria, suggesting that they must have been acquired from an ancient ancestor and retained in the extant strains. The plasticity of the Cyanothece genomes is evident from the fact that the strains have acquired many novel metabolic capabilities, which is reflected in their diverse genotypes and phenotypes (such as cell size, shape, and pigment composition). Two of the Cyanothece strains possess linear chromosomal elements, a feature not observed in any other photosynthetic bacteria studied to date. These chromosomal elements seem to accommodate specific adaptive features that might impart niche-specific advantages to the strains, as is suggested by the presence of a large number of genes encoding transposons and CRISP-R-associated proteins. The significant difference observed in the numbers of predicted coding sequences between the Cyanothece strains suggests a substantial amount of loss or gain of genetic material over evolutionary time. Cyanothece 8801 and 8802 possess the smallest genomes and have a high percentage of pseudogenes, indicating that they might be undergoing a reductive genome evolution. A high percentage of pseudogenes is also observed in the genome of N. azollae , a strain that has undergone significant gene loss to adapt to a symbiotic lifestyle ( 38 ). Despite their small genomes, Cyanothece 8801 and 8802 possess many novel genes that are missing in the other Cyanothece strains and in most sequenced cyanobacteria, suggesting that they must have been acquired in response to some selective pressure. An outstanding example is the presence of the V-type ATPases, involved in numerous energy transduction pathways and known to be indispensable for plant growth, especially under different stress conditions ( 39 , 40 ). Another plant-like feature in Cyanothece is the presence of a two-gene operon in Cyanothece 7424 and 7822 encoding enzymes involved in the glyoxylate cycle. In plants this cycle is implicated in the conversion of storage lipids into carbohydrates ( 41 ). This cycle is also known to impart metabolic versatility to some bacterial strains. However, no other cyanobacterial strain sequenced to date is known to possess the glyoxylate cycle. Our phylogenetic analysis showed that Cyanothece 7425 separated from the other Cyanothece strains at an early stage of evolution. Cyanothece 7425 cells are smaller than those of the other Cyanothece strains and are more cylindrical. A GC content of ~40% is characteristic of the genus Cyanothece , and Cyanothece 7425 is an anomaly in this regard as well, with a GC content of ~50%. In contrast to the other five Cyanothece strains, Cyanothece 7425 fixes nitrogen only under anaerobic conditions and appears to share a common ancestor with three other anaerobic nitrogen-fixing Synechococcus strains. In contrast to the nif gene cluster in the five Cyanothece strains, the cluster in Cyanothece 7425 is disrupted by the insertion of a large fragment and exhibits inversions similar to those of the clusters in the Synechococcus strains. However, our protein BLAST analysis did not show significant homology of the Cyanothece 7425 genes with those of any Synechococcus strain. Also, unlike the other Cyanothece strains, very few of the Cyanothece 7425 genes had homologs in Microcystis and Microcoleus . These results indicate that Cyanothece sp. PCC 7425 represents a cyanobacterial strain that is losing its nitrogen-fixing ability and evolving independently of the other Cyanothece strains. Another interesting observation in this study is the absence of an uptake hydrogenase in all the sequenced anaerobic nitrogen-fixing cyanobacteria, which suggests that this enzyme must be associated with aerobic nitrogen fixation in nonheterocystous cyanobacterial strains. Raphidiopsis brookii , a strain that has lost the ability to fix nitrogen and has eliminated most of the nitrogen fixation related genes ( 42 ), also does not have genes encoding the uptake hydrogenase. Cyanothece 7425 is phylogenetically closest to A. marina and shares a common ancestor with this strain, indicating that the latter lost its nitrogen-fixing ability in the course of evolution. Similarly, T. elongatus , a unicellular nitrogen-fixing strain, located between two anaerobic nitrogen fixers, appears to have lost its nitrogen-fixing ability. These evolutionary trends suggest that strains that have not adapted for functioning under aerobic conditions may not succeed in a predominantly oxygen-rich environment and therefore lose this ability with the simultaneous elimination of the nitrogenase cluster. Therefore, the nitrogenase cluster of Cyanothece , which appears to have evolved to function efficiently under ambient conditions, is evolutionarily selected for, as is seen in strains like UCYNA and the endosymbiont of R. gibba . \n Cyanothece cells are unique in their ability to provide a platform for both aerobic and anaerobic metabolic processes at alternate phases of the diurnal cycle. While the unicellular Microcystis cells also have the capability to create an anoxic intracellular environment, they do not have genes required for nitrogen fixation. Five Cyanothece strains exhibit high rates of nitrogenase-mediated hydrogen production under aerobic conditions, indicating that an anaerobic intracellular environment is created to protect the oxygen-sensitive nitrogenase enzyme. The Cyanothece genomes also contain many genes for catalases and peroxidases, enzymes which protect oxygen-sensitive cellular constituents required for anaerobic metabolism. A large, contiguous nif gene cluster and the ability to perform aerobic nitrogen fixation distinguish the unicellular Cyanothece cells from all other cyanobacteria. The presence of versatile metabolic pathways, such as nitrogen fixation and oxygenic photosynthesis, and the ability to generate anoxic cellular environments under diazotrophic growth conditions make members of the genus Cyanothece attractive model systems for studying various sunlight-driven biofuel-yielding pathways which entail microaerobic conditions."
} | 3,689 |
31922143 | PMC6946277 | pmc | 5,287 | {
"abstract": "Directional manipulation of underwater bubbles on a solid surface has attracted much attention due to its large-scale applications such as electrocatalytic gas evolution reactions, wastewater remediation, and solar energy harvesting. In this work, the patterned slippery surface (PSS) is fabricated via a facile method where the patterned pathways are fabricated by means of etching the pristine copper sheet. These patterned surfaces consisted of pristine copper and modified oxide copper which exhibit different wettability for bubble and water. The superhydrophobic and aerophilic surface can efficiently capture bubbles, and the infused oil layer is beneficial for reducing the resistance during transportation. Furthermore, the bubble can move upward, downward, and horizontally. Hence, it is easy to realize the bubble's transportation and collection on the functional surfaces.",
"conclusion": "3. Conclusion In summary, the directional transportation and collection of bubbles underwater were realized on the patterned slippery surfaces which were fabricated via a facile method. These samples of PSS were combined by two regions, the treated superhydrophobic part with lubricant infused and the untreated part of the pristine copper. The superhydrophobic and aerophilic surface can efficiently capture bubbles, and the infused oil layer was beneficial for reducing the resistance for bubble transportation. Hence, the samples were capable of capturing and transporting bubbles on the treated part. Further, with a well-designed path on the surface such as PSS-C, PSS-M, and PSS-wedge, the directional transportation of bubbles can be organized precisely. Furthermore, the PSS-Y can realize the bubble's collection. This facile method demonstrated promising prospective in fabricating substrates for directional transportation and collection of bubbles.",
"introduction": "1. Introduction The manipulation of underwater bubbles is significant in a fluid system due to its large-scale applications, such as electrocatalytic gas evolution reactions, wastewater remediation, and solar energy harvesting [ 1 – 11 ]. Meanwhile, the bubbles play an important role in nature. For instance, the superhydrophobic abdomen of diving bell spiders can capture bubbles for its further living in the water [ 12 , 13 ]. However, the underwater bubbles also have some negative effects in industries, such as corrosion of pipes, air locks, and clogging of bubbles in intravenous tubing [ 14 – 18 ]. Thus, it is urgent to spend further time in research for bubble's capture and removal. In addition, there are significant correlations between liquid wettability and bubble wettability which have been reported in recent years [ 19 – 21 ]. The three-phase (gas-liquid-solid) contact line of bubble on a solid surface in an aqueous environment is the same as water droplet on the solid surface in air. For an ideal surface, the bubble contact angle is complementary to water contact angle. Therefore, the superhydrophobic surface presents as aerophilic while the hydrophilic surface is aerophobic. Bubbles can be captured more easily on the superhydrophobic surface than on the superhydrophilic surface. Thus, surfaces with the super wetting ability can be applied in bubble manipulation. Tian et al. [ 22 ] have fabricated superhydrophobic PE plates with modified nanoparticles coated on it. Releasing continuous bubbles on the plate underwater, it can float and dive with bubble capture and breakage. It manifested that the superhydrophobic layer could capture bubbles efficiently, and bubbles could merge into a larger one. Yu et al. [ 23 ] realized the directional manipulation of bubbles on a superhydrophobic helix. The bubble stayed on the climax of the helix under the coeffect of buoyancy and adherence and moved directionally along the helix when it rotated. In addition, they also realized the spontaneous directional transportation of bubbles on a superhydrophobic cone [ 24 ]. In general, there is a high adhesive force between the superhydrophobic substrate and bubbles. Bubbles tend to spread rapidly and adhere to the surface due to the interaction of air and substrates [ 25 – 27 ]. Inspired by the movement of water droplets or insects on Pitcher plant, spider silk, and cactus spine [ 28 – 33 ], the slippery surfaces with a lubricant layer and the substrates with a geometrical gradient have been applied largely in the directional manipulation of underwater bubbles [ 7 , 10 , 34 – 41 ]. Zhang et al. [ 34 ] designed a wedge-shaped superhydrophobic surface with a lubricant layer via laser cutting for this directional movement. This movement occurred in a horizontal direction in which bubbles suffered unbalanced Laplace pressure, and the bubble moves entirely rather than pinned on the surface. Additionally, Tang et al. [ 39 ] used photolithograph to manufacture bioinspired patterned slippery surface which achieved upward directional transportation of buoyancy-driven bubbles. Furthermore, the directional transportation of bubbles can also be realized on the Janus membrane where bubbles can only penetrate from the hydrophilic side to the hydrophobic side [ 42 – 44 ]. Yin et al. [ 42 ] realized the bubble transportation through a Janus PFTE mesh which was created via a femtosecond laser. As mentioned above, the driving force for this transportation mainly depends on buoyancy and unbalanced Laplace pressure. Though there are many surfaces which are served for bubble directional transportation, the most fabricated methods are complex and time-consuming, such as laser cutting and photolithograph [ 24 , 34 , 39 , 42 , 43 ]. Thus, it is significant to explore a facile method to fabricate a functional surface for directional transportation. Herein, a facile method has been presented in this work for fabricating the patterned slippery surfaces (PSS) for bubble manipulation. Patterns were fabricated by covering a part of the copper substrate with tape when etching. Besides, the pattern can be designed by adjusting the shape of the tape. With different shapes on the slippery surface, the manipulations of bubble can be controlled. Furthermore, bubbles can move upward with different paths by buoyancy, horizontal and downward on PSS with geometrical gradient under unbalanced Laplace pressure. This facile method is beneficial for further study of bubble manipulation.",
"discussion": "2. Result and Discussion 2.1. Preparation of Patterned Slippery Surface and Characterization The etching process was expressed as previous work [ 45 ]. The whole fabrication process of this patterned slippery surface was shown in Figure 1 . The transparent tape was functional for the protection to avoid pristine copper to be etched which resulted in a patterned surface, the yellow part reflected the pristine copper, and the black part meant the oxide copper after being etched. Figures 1(a) – 1(c) show the detailed morphologies of the modified oxide copper and the section view of the patterned surface. The oxide copper showed a spherical shape, and the section view displayed a concave-convex shape. The oxide copper was in the lower part. Besides, the width ratio between the yellow and black parts is 1 : 1. Furthermore, the images of bubble and water contact angles on different types of surfaces (superhydrophobic surfaces, slippery surfaces, original surfaces, and PSS) were shown in Figure 2 , , and . In addition, the black part was modified to be superhydrophobic and aerophilic with the water and bubble contact angles of 155 ± 2° and 60 ± 2°; the pristine copper is hydrophilic and aerophobic of water and bubble contact angles of 80 ± 2° and 130 ± 2°. For the ideal surface, the water contact angle ( θ w ) in air and the bubble contact angle ( θ b ) in water complementary resulted from almost the same three-phase contact line. Additionally, the effect of buoyancy for bubble was analogous of gravity for water droplet. According to Young's equation, the values of θ w and θ b can be calculated as\n (1) cos θ w = γ SV − γ SL γ LV , (2) cos θ b = γ SL − γ SV γ LV , where γ SV , γ LV , and γ SL represented the surface energy of solid-vapor interface, liquid-vapor interface, and solid-liquid interface, respectively. Based on equation ( 1 ) and ( 2 ), it is easy to derive θ b = 180° − θ w . After lubricant PFPE was infused, the oil layer had substituted the solid substrate which resulted in the change of three phases. Therefore, the water ( θ wo ) and bubble ( θ bo ) contact angles were 110 ± 2° and 53 ± 2° with oil layer, which can be expressed as\n (3) cos θ w o = γ OV − γ OL γ LV , cos θ b o = γ OL − γ OV γ LV , where γ OV and γ OL are the surface energy of oil-vapor interface and oil-liquid phase. Besides, θ wo and θ wb were still complementary, θ wo + θ wb = 180°. In addition, the patterned surface displays anisotropic wettability that resulted from the wettability difference between the yellow and black parts; the bubble contact angle is 126 ± 2° and 70 ± 2° in the x and y directions on the treated part with 1 mm width. From these results, it can be concluded that the treated part remains aerophilic for better bubble capture and transportation. 2.2. Directional Manipulation of Bubble on PSS with Straight Stripes As for the whole process of bubble directional manipulation, the first step is capturing the bubbles. As shown in Figure 3(a) , the pristine copper sheet cannot capture bubbles. Bubbles bounced to the upper position continuously to escape after it contacted with the inclined samples since the pristine copper is aerophobic. Moreover, the directional manipulation of underwater bubbles cannot be realized on the superhydrophobic oxide copper. From Figure 3(b) , the silver mirror-like phenomenon was observed immediately on the superhydrophobic sample after being immersed in water; there was a bubble layer on the sample. Additionally, although the substrate can capture bubbles efficiently, bubbles stay in the original position to expand the air layer instead of moving upward, which was shown in Figure 3(b) . Thus, it is hard to realize the directional transportation of underwater bubbles on superhydrophobic substrates, while in previous work the directional transportation of bubbles has been accomplished by a slippery surface with shape gradient structure [ 25 ]. Therefore, based on those researches, the slippery surface fabricated by the superhydrophobic substrate with infused oil layer was conducive to capture and transport bubbles [ 25 , 34 – 37 , 39 ]. In this work, we have fabricated patterned slippery surface (PSS) with different widths to achieve the goal of directional manipulation. As shown in Figure 4 and , the PSS-2 was inclined in water to observe the bubble movement. Then, releasing a single bubble with the volume of about 15 μ L in the slippery stripe, it was restricted by the boundary on the treated stripes and moved from the bottom up with the shape of ellipse ( Figure 4(a) ). Besides, releasing a single bubble with the same volume in the untreated stripe, the bubble bounced on the stripe to the upper location firstly, then it moved horizontally to the slippery area that resulted from the touch between the bubble and the slippery stripe. Then, the bubble transported to the top on the slippery stripe after horizontal movement ( Figure 4(b) ). From the single bubble motion on the PSS-2, it can be concluded that the combined surface can realize the directional manipulation of underwater bubbles on the treated stripes. Further, the same phenomenon had been observed in samples of PSS-1 and PSS-3 as shown in Fig. and with the same volume of bubble. Bubbles appeared in different shapes in treated stripes with different widths that resulted from the tendency that bubble would cover more area on the treated stripes. The transportations were also shown in and . However, there were some special phenomena in the directional manipulation in the samples PSS-1 and PSS-3 with the single bubble with the volume of 15 μ L. As shown in Figure 4(c) , the bubble covered three stripes (treated, untreated, and treated) during the whole upward transportation with the first contacted position of the untreated stripe, while in the sample of PSS-3 the bubble moved from the bottom up in the untreated part instead of a horizontal movement to the treated stripe to the top, which was shown in Figure 4(d) . The special transportations were also shown in . It can be ascribed to the relationship of bubble volume and stripe width. In PSS-1, the bubble tended to move horizontally to the treated part after being released on the untreated part, but the stripe width was much narrower compared to the bubble diameter that resulted in the touch between the bubble and two treated stripes. Then, the bubble and three stripes achieve a balance for directional movement. Nevertheless, the sample width of PSS-3 was too large for this bubble which resulted in the bouncing of the bubble from bottom up on the untreated stripe. From those movements of 15 μ L bubble on the PSS samples, it could be concluded that the directional movement was mainly decided by the treated stripe which offered the capacity of capturing bubbles and the transport area. Furthermore, the horizontal movement depended on the contact of the bubble and the treated part. The treated part is also aerophilic with the oil layer for bubbles containing lower free energy than the pristine copper part that resulted in better capturing of the bubbles. Moreover, the added oil layer can make the substrate more regular and polisher to cover defects of this substrate. Based on this oil layer, bubbles can move entirely instead of bulk of movement with part of it remaining in the initial position under the driving force of buoyancy. In addition, the driving force for the bubble directional transportation included buoyancy ( F BP ) and Laplace force difference ( F LP ), and the resistance was mainly generated by the adhesive force ( F AD ) and the sample defects ( F DE ), which was shown in Figure 5 . Furthermore, the buoyancy was generated by a part of the bubble which was the unbounded region, F BP can be calculated as [ 46 , 47 ]\n (4) F BP = ρ g V P , where ρ is the density of water, g is the gravitational acceleration, and V P is the effective volume of the bubble (the left part of bubble in Figure 5(b) ). Moreover, there is a Laplace force difference ( F LP ) generated by the curved bubble surface; it can be calculated as [ 47 ]\n (5) F LP = 2 γ water R 1 A 1 − 2 γ water R 2 A 2 , where γ water is the surface tension of water, R 1 and R 2 are the radii of bubble in the front and back sides, and A 1 and A 2 are the projected area of the bubble at the front and back sides. In addition, in those inclined samples, the adhesion belonged to the lateral adhesion ( F LA ) which its direction is against the directional transportation of bubbles on a solid substrate [ 46 – 49 ]. Thus, the resultant force ( F RT ) in the moving direction can be calculated as\n (6) F RT = F BP cos θ + F LP sin θ − F LA − F DE , where θ is the inclined angle of the surface in water. Based on equation ( 6 ), the movement was affected by several factors. F BP and F LP mainly depended on the inclined angle; F LA had been reduced by the oil layer that resulted in the directional transportation. From above experiments, it can be confirmed that the PSS samples with straight treated stripes can realize efficiently the directional transportation of bubbles. Further, the samples also reduced the modified area in the total surface but with the same capacity of capturing bubbles compared to the whole modified surface which was beneficial for the environment. Hence, the patterned surface with the oil layer is an ideal candidate for capturing and transporting bubbles underwater. 2.3. Directional Transportation of Bubbles on PSS Samples with Special Shapes Based on the fabricated method of the above samples with straight pathway, we also had fabricated the patterned slippery surface with the treated part displayed letter “C” (PSS-C). The width of the treated path was 4 mm. As shown in Figure 6(a) , the bubble with a volume of 15 μ L moved from the bottom up in a curve track which was the same as the treated path. The boundary line had played an important role in preventing the bubble escape from the treated path. Thus, the treated path on PSS samples offered the transported tracks for bubbles after bubble releasing. We also fabricated the patterned slippery surface with the treated part displayed letter “M” (PSS-M). There were some turning points in this sample. Therefore, the single bubble with the volume of about 15 μ L was released on the PSS-M to detect the ability of directional transportation on this sample, which was shown in Figure 6(b) and . The width of “M” was 3 mm, and the boundary lines were parallel and straight. The single bubble displayed a circular shape and moved along the treated path. Then, the bubble turned right and left when it reached the turning point of letter “M” in order to remain on the treated part all the time. Moreover, the shape of the bubble changed largely when going through the turning point. The transported track was also the same as the treated path, the letter “M.” With the letters “M” and “C” on the substrate, we can control the directional transportation of bubbles underwater more precisely in ideal directions and paths. Although those PSS samples (PSS-1, PSS-2, PSS-3, PSS-C, and PSS-M) could realize the directional transportations, bubbles could only move vertically from the lower position to the higher position driven by buoyancy force. Nonetheless, this facile method of fabricating the PSS samples offered the opportunity for spontaneous directional transportation of bubbles underwater. Thus, we fabricated the PSS samples with wedge shapes for spontaneous directional transportation of bubbles. There were four equal wedges on the copper sheet with the apex angle of 7°. As shown in Figure 7(a) and , the bubble moved from the narrow tip to the wide end after being released on the wedge spontaneously. Besides, the bubble moved faster in the early time and slowed down to stagnation. Moreover, this PSS-wedge sample could also realize antibuoyancy movement. As shown in Figure 7(b) and , the bubble moved downward spontaneously after being released on the inclined sample. The driving force on this sample of the PSS-wedge was the Laplace force difference ( F LP ′) no matter how the bubble moved. As shown in Figure 7(c) , F LP ′ can be calculated as [ 34 , 50 ]\n (7) F ′ LP = γ water − γ oil 1 r 1 − 1 r 2 sin α r 2 − r 1 V , where γ oil is the surface tension of the oil layer, α is the apex angle, V is the bubble volume, and r 1 and r 2 are the radii of the bubble in the tip and end positions. For the movement in Figure 7(b) , the buoyancy became the resistance. Thus, the transported distance was much shorter than that in the inclined PSS-wedge sample. Hence, the patterned slippery surface can be designed with serval special shapes on it by covering the pristine copper sheet for further directional transportation of bubbles. 2.4. Bubble Transportation and Collection on PSS-Y Bubble capture and collection have attracted much attention in recent years. Though there were many materials investigated for bubble collection, simplifying the fabrication methods for those materials was still a challenge. However, the PSS samples were fabricated via a facile etching method and it could efficiently capture bubbles and transport them along the treated area. Therefore, we designed a sample (PSS-Y) based on this method to achieve the goal of bubble collection. This sample also included two parts, the treated and untreated parts. As shown in Figure 8(a) , the treated part was combined by two areas, the collect area and the transport area. Moreover, the transport area was 4 mm wide and 20 mm long which showed a rectangle, while another area showed a trapezoid with the upper and lower widths of 4 mm and 20 mm, respectively, and the height was 20 mm. The total process of bubble collection could be divided into three steps: attach on the collect area, move on to the transport area, and escape from this sample. We first examined the movement of two individual bubbles on this PSS-Y sample. As shown in Figure 8(b) and , two bubbles with the volume of about 15 μ L moved upward along the boundary line in the lower part. Then, the two bubbles merged into one when they moved to the joint between the straight and lower part. Finally, the merged bubble transported on the stripe to the end along the treated straight path. From the transportation of bubbles on the sample of PSS-Y, this special PSS samples could collect bubbles by the two parts. Based on the phenomenon of two bubbles on PSS-Y, we have released multiple bubbles on PSS-Y in different positions. From Figure 8(c) and , all bubbles were captured by the collect area and moved along the treated part. Furthermore, bubbles might coalesce in the joint and move upward to escape this sample in the straight treated path. In this sample of PSS-Y, the trapezoid part had amplified the contact area between bubbles and sample which resulted in larger collect area, and the straight part restricted the leaving position of bubbles for bubble collection."
} | 5,359 |
39163267 | PMC11375855 | pmc | 5,289 | {
"abstract": "Abstract Horizontal gene transfer (HGT) is fundamental to microbial evolution and adaptation. When a gene is horizontally transferred, it may either add itself as a new gene to the recipient genome (possibly displacing nonhomologous genes) or replace an existing homologous gene. Currently, studies do not usually distinguish between “additive” and “replacing” HGTs, and their relative frequencies, integration mechanisms, and specific roles in microbial evolution are poorly understood. In this work, we develop a novel computational framework for large-scale classification of HGTs as either additive or replacing. Our framework leverages recently developed phylogenetic approaches for HGT detection and classifies HGTs inferred between terminal edges based on gene orderings along genomes and phylogenetic relationships between the microbial species under consideration. The resulting method, called DART , is highly customizable and scalable and can classify a large fraction of inferred HGTs with high confidence and statistical support. Our application of DART to a large dataset of thousands of gene families from 103 Aeromonas genomes provides insights into the relative frequencies, functional biases, and integration mechanisms of additive and replacing HGTs. Among other results, we find that (i) the relative frequency of additive HGT increases with increasing phylogenetic distance, (ii) replacing HGT dominates at shorter phylogenetic distances, (iii) additive and replacing HGTs have strikingly different functional profiles, (iv) homologous recombination in flanking regions of a novel gene may be a frequent integration mechanism for additive HGT, and (v) phages and mobile genetic elements likely play an important role in facilitating additive HGT.",
"introduction": "Introduction \n Horizontal gene transfer (HGT) refers to the transfer of genetic material between two organisms that do not have a parent–offspring relationship. HGT can occur both intra- and inter-species, and is well-understood to be a major driver of microbial evolution. Transferred genes may be selfish genetic elements, or be associated with selfish genetic elements that facilitate integration into the recipient genome, and/or they may integrate into the recipient genome through homologous recombination. At a fundamental level, one can distinguish between replacing HGTs, where the transferred gene replaces an existing homologous gene in the recipient genome, and additive HGTs, where the transferred gene is added as a new gene to the recipient genome, possibly displacing one or more existing nonhomologous genes ( Choi et al. 2012 ). However, classification of HGTs as being additive or replacing is nontrivial and there are currently no reliable, high-throughput computational solutions for this task. We note that the distinction between additive and replacing transfers does not necessarily correspond to their integration mechanisms as additive transfers can occur through homologous recombination in the flanking regions of the added gene ( Polz et al. 2013 ). We also note that an additive transfer need not necessarily increase the number of genes in the recipient genome since the transferred gene may overwrite one or more nonhomologous genes, resulting in their immediate loss ( Ely 2020 ). \n Choi et al. (2012) studied the role of additive and replacing HGTs in the evolution of Streptococcus . That study was among the first to distinguish between the two types of HGTs, and adapted existing methods based on phylogenetic reconciliation and whole-genome alignments to do so ( Didelot et al. 2010 ; Doyon et al. 2010 ). A key finding of the study was that replacing and additive HGTs appear to have played markedly different roles in the evolution of Streptococcus ( Choi et al. 2012 ), with putative virulence genes being correlated with additive, not replacing, HGTs. Khayi et al. (2015) used phylogenetic discordance and gene order information to study additive and replacing HGTs in the pathogen Dickeya solani and suggested that inter-species HGT may have caused substantial variability in Dickeya solani genomes. More recently, there have been attempts at designing heuristics for distinguishing between additive and replacing HGTs using phylogenetic reconciliation ( Kordi et al. 2019 ; Mondal et al. 2020 ), but such approaches do not make use of gene order information and currently have a high error rate even on simulated data. Thus, there do not yet exist any systematic, broadly applicable, rigorously tested approaches that can be used to reliably classify HGTs as additive or replacing. As a result, existing research on HGTs does not usually distinguish between additive and replacing HGTs, leaving their relative frequencies and specific roles in microbial evolution poorly understood. In this work, we develop a novel computational framework that can classify a large fraction of HGTs inferred between the terminal edges of the phylogeny as being either additive or replacing with high confidence. Our framework leverages recent advances in HGT detection methods to identify high-confidence “terminal-edge” HGTs (i.e. HGTs occurring between branches leading to terminal taxa) and uses gene order information and phylogenetic relationships to classify a large fraction of the HGTs with high confidence. The resulting method, called DART (short for “Detection of Additive and Replacing Transfers”), is highly customizable, statistically supported, and scalable to hundreds of genomes and thousands of gene families. We applied DART to a large dataset of over 7,500 gene families (homologous groups) from 103 Aeromonas strains representing 28 different species ( Rangel et al. 2019 ; Kloub et al. 2021 ) and were able to classify a large fraction of the inferred terminal-edge HGTs with high confidence. Members of Aeromonas are found in water and sediments, live in symbiosis with fish, insects and leeches, and cause disease in humans and other animals ( Janda and Abbott 2010 ; Milligan-Myhre et al. 2011 ; Marden et al. 2016 ; Fernandez-Bravo and Figueras 2020 ). The comprehensive Aeromonas dataset used in the current study ( Kloub et al. 2021 ) has sufficient breadth and depth to assess both inter-species and intra-species HGTs. Moreover, HGT and recombination between members of Aeromonas occur frequently, making this an excellent test case ( Morandi et al. 2005 ; Silver et al. 2011 ; Colston et al. 2014 ; Kloub et al. 2021 ). Initial analysis of this dataset yielded a total of 31,187 high-confidence terminal-edge intra-species HGTs and 9,334 high-confidence terminal-edge inter-species HGTs. Among these, DART was able to classify 89% of the intra-species HGTs and 75% of the inter-species HGTs. Analysis of these classified HGTs provides insights into the relative frequencies, functional biases, and integration mechanisms of additive and replacing HGTs. Among other results, we find that (i) the relative frequency of additive HGT increases with increasing phylogenetic distance, (ii) replacing HGT dominates at shorter phylogenetic distances (e.g. between strains belonging to the same species), (iii) additive and replacing HGTs have strikingly different functional profiles, (iv) additive HGTs often, but not always, integrate themselves within gene neighborhoods similar to the original gene neighborhood in the donor genome, suggesting homologous recombination in flanking regions as a possible insertion mechanism, and (v) phages and mobile genetic elements likely play an important role in facilitating additive HGT, especially at larger phylogenetic distances. We also analyze two specific HGTs in detail and demonstrate how HGTs can sometimes have complex characteristics, simultaneously having additive, homologous replacement, and nonhomologous displacement components. Overall, the ability to easily classify HGTs as either additive or replacing, as enabled by DART, has many potential benefits for microbial evolutionary studies. For example, it can provide insight into possible functions of transferred genes, improve our understanding of the evolutionary and functional implications of HGT (e.g. how often and under which conditions does HGT enable the acquisition of new abilities or functions versus refining existing abilities or functions?), and help refine our understanding of HGT integration mechanisms, particularly for additive HGTs. DART is open-source and freely available from https://compbio.engr.uconn.edu/software/dart/ . The Aeromonas dataset and a complete list of classified HGTs are also freely available from the same URL.",
"discussion": "Discussion In this work, we introduced a new, high-throughput approach, called DART, for classifying inferred HGTs as additive or replacing. Our analysis of the Aeromonas data shows that DART can confidently classify a large fraction of terminal-edge HGTs as either additive or replacing, and reveals several important insights into the prevalence, functional characteristics, and integration mechanisms of additive and replacing HGTs. For instance, we find that the fraction of HGTs acquired additively increases with increasing phylogenetic distance, and that replacing HGTs greatly dominate among strains or genomes from the same or closely related species. We also find clear functional preferences among replacing HGTs and additive HGTs, with enrichment in one or the other across several different COG categories. Interestingly, we find that a much larger fraction of additively acquired genes have poorly characterized or unknown functions. Our analysis also suggests that, not necessarily surprisingly, even additively acquired genes often integrate themselves within gene neighborhoods that are similar to their gene neighborhoods in donor genomes, pointing to homologous recombination in flanking regions as a possible insertion mechanism. We also find that phages and mobile genetic elements likely play an important role in facilitating additive HGTs, especially at larger phylogenetic distances. Moreover, our case studies highlight how some HGTs can have complex characteristics, simultaneously having additive, homologous replacement, and nonhomologous displacement components ( supplementary Figures S7 through S11, Supplementary Material online ). The resulting software is easy to use and highly customizable and simplifies the inference of additive and replacing HGTs; we expect that its application will lead to improved understanding of the functional potential, integration mechanisms, and evolutionary impacts of HGT. In particular, analysis of additional microbial datasets from other genera could further refine the insights from our Aeromonas analysis and help identify general biological principles concerning additive and replacing HGTs. Biological implications The dominance of replacing HGT within species boundaries agrees with the proposal of Dykhuizen and Green (1991) that replacing HGT followed by recombination can be used to define species similar to the biological species concept. However, integration into a genome through homologous recombination requires only short stretches of similar sequences flanking the recombining DNA ( Lorenz and Wackernagel 1994 ). Consequently, in bacteria and archaea, replacing HGT is not limited by a well-defined species boundary, rather a steep gradient for the successful integration of transferred genetic material exists ( Roberts and Cohan 1993 ; Vulic et al. 1997 ; Williams et al. 2012 ). HGT between close relatives followed by homologous recombination, similar to eukaryotic sex, counteracts the accumulation of slightly deleterious mutations; however, replacing HGT also prevents or at least slows down the co-evolution of genes. The complexity hypothesis ( Jain et al. 1999 ) suggests that genes, whose products are part of large structurally integrated complexes, are only infrequently transferred. Our findings, and previous findings on the transfer of ribosomal RNAs and proteins ( Mylvaganam and Dennis 1992 ; Ho et al. 1999 ; Gogarten et al. 2002 ; Zhaxybayeva et al. 2009 ) suggest that this might not always be the case. Further analyses based on larger data sets will be necessary to determine if the disruption of co-evolution slows down replacing transfers of genes encoding parts of a complex machinery. The finding that additive HGTs generally occur across species boundaries agrees with the understanding of genomic islands as providing adaptation to a particular ecological niche ( Dobrindt et al. 2004 ). This interpretation is also supported by many genes in the additive HGT category encoding proteins involved in the uptake and metabolism of substrates, which may help the recipient to adapt to a particular niche in which these substrates are available ( Juhas et al. 2009 ), or rather these islands are adapted to an ecological niche and are transferred into organisms occupying or invading this niche ( Papke and Gogarten 2012 ). The other large additive transfer category is, unsurprisingly, prophages and selfish genetic elements. Short deletions ( Mira et al. 2001 ; Bobay and Ochman 2017 ) and recombination events that separate deleterious from advantageous genes ( Nguyen et al. 2022 ) are ways that selfish genetic elements can be inactivated and lost from genomes. Finally, analysis of the divergence between Escherichia and Salmonella ( Retchless and Lawrence 2007 ) suggests that additive transfers locally impact replacing transfers. An adaptive gene integrated into a genome through additive HGT can prevent replacing HGT from donors that do not harbor this gene because homologous recombination usually requires homologous flanking regions on both ends of integrated gene. Thus, in the immediate genome neighborhood of the added gene, a slowly expanding island is created in which polymorphisms accumulate preventing further homologous recombination. Impact of dataset construction choices on classification Our analysis of the Aeromonas dataset identifies unrecognized homology as a key reason for potential misclassification by DART. Such unrecognized homology can result from incomplete gene calling during the annotation or over-splitting of gene families during the classification of homologous groups. Any high-throughput, automated pipeline for gene annotation and gene family clustering, such as RAST ( Aziz et al. 2008 ) and OrthoMCL ( Li et al. 2003 ) (plus single linkage clustering) as used in the construction of the Aeromonas dataset, is likely to be affected by this problem to at least some degree (see, e.g. Bakke et al. 2009 ). Thus, additional filtering of classification results using BLAST, as we demonstrate, may be necessary to validate the results when analyzing large datasets created using automated computational pipelines. In addition, as our case study of cHG 21,480 shows ( supplementary Figure S12, Supplementary Material online ), it may be beneficial to use multiple different annotation software when studying and interpreting specific HGTs, or even as a way to identify potential false-positive and/or false-negative classifications. Methodological limitations The classification approach implemented in DART has two key limitations. First, DART can only classify HGTs that are between terminal edges, i.e. whose donor and recipient are along terminal edges on the species tree. This is because DART relies critically on gene ordering information for the recipient species, which is not directly available for ancestral species. The resulting focus on only HGTs between terminal edges can bias the study of replacing versus additive HGTs since the effect of selective pressures on recently horizontally acquired genetic material may not be fully accounted for. Thus, results related to relative frequencies of additive and replacing HGTs and to their functional biases should be interpreted with caution. Second, DART only classifies single-gene HGTs or HGTs that may be part of small HMGTs, not large HMGTs. This is due to DART’s reliance on assessing the similarities of the gene neighborhoods of the transferred gene on the recipient genome and its homologs on the closest phylogenetic neighbors, which can be misled by large HMGTs. In addition, as discussed above, DART’s classifications can be sensitive to incomplete gene calling or under-clustering of gene families. As we show in this work, it is possible to detect and filter out many potentially misclassified HGTs, but this reduces the number of HGTs ultimately classified. Such filtering also affects additive HGTs more than it affects replacing HGTs, which can artificially lower the fraction of HGTs classified as additive post filtering. At a more fundamental level, the accuracy of any HGT classification framework depends on the accuracy of HGT detection itself. While DART uses state-of-the-art phylogenetic approaches for HGT detection, these methods still suffer from relatively high false-positive and false-negative inference rates ( Nguyen et al. 2013 ; Bansal et al. 2015 , 2018 ). DART’s focus on classifying only terminal-edge HGTs, along with its use of conservative HGT inference parameters, helps minimize the impact of false-positive inferences, but still, at least some of the classified “HGTs” are likely to either not be true HGTs or have their donors and/or recipients incorrectly inferred. The potentially large false-negative rate for the conservative HGT inference pipeline used by DART can also be problematic in that it can lead to biases in the kinds of HGTs that are detected, potentially leading to biased down-stream inferences when analyzing the classified additive and replacing HGTs. Moreover, it can be very difficult, or even impossible, to detect many HGTs between closely related species or strains due to insufficient sequence divergence, which can again potentially bias downstream inferences. Future directions Several aspects of the classification approach implemented in DART can be further improved. For instance, it may be possible to overcome the restriction to classifying only terminal-edge HGTs by combining DART with methods that can infer ancestral gene content and ordering ( Duchemin et al. 2017 ; Feng et al. 2017 ). DART could then be applied to all HGTs for which gene contents and orderings of their recipients can be inferred with reasonable certainty. It would also be worth extending DART to classify inferred HMGTs ( Kloub et al. 2021 ). The existing algorithms implemented in DART can easily be used to classify HMGTs if the boundaries of an HMGT are inferred accurately, However, due to HGT inference error and uncertainty, it is often difficult to infer the precise breakpoints for an HMGT. Nonetheless, by using sequence-based features such as GC content or codon usage bias to identify HMGT breakpoints, together with better accounting for breakpoint uncertainty in GNC calculations, it may be possible to reliably classify recent HMGTs as being additive or replacing. Finally, it would be very interesting to combine recently developed, but as yet unreliable, reconciliation-based approaches for classifying additive and replacing HGTs ( Kordi et al. 2019 ; Mondal et al. 2020 ). By combining DART with such reconciliation-based approaches, it may be possible to both improve classification accuracy and classify a larger fraction of HGTs."
} | 4,840 |
25923203 | PMC4414556 | pmc | 5,291 | {
"abstract": "Symbiotic associations can be disrupted by disturbance or by changing environmental conditions. Endophytes are fungal and bacterial symbionts of plants that can affect performance. As in more widely known symbioses, acute or chronic stressor exposure might trigger disassociation of endophytes from host plants. We tested this hypothesis by examining the effects of oil exposure following the Deepwater Horizon (DWH) oil spill on endophyte diversity and abundance in Spartina alterniflora – the foundational plant in northern Gulf coast salt marshes affected by the spill. We compared bacterial and fungal endophytes isolated from plants in reference areas to isolates from plants collected in areas with residual oil that has persisted for more than three years after the DWH spill. DNA sequence-based estimates showed that oil exposure shifted endophyte diversity and community structure. Plants from oiled areas exhibited near total loss of leaf fungal endophytes. Root fungal endophytes exhibited a more modest decline and little change was observed in endophytic bacterial diversity or abundance, though a shift towards hydrocarbon metabolizers was found in plants from oiled sites. These results show that plant-endophyte symbioses can be disrupted by stressor exposure, and indicate that symbiont community disassembly in marsh plants is an enduring outcome of the DWH spill.",
"conclusion": "Conclusions Our findings indicate that stressor exposure can result in sustained loss of endophytes in a system where elevated vulnerability of plant hosts could cascade into functional deficits that reshape whole ecosystems. Reduced integrity of S . alterniflora hosts could, for example, translate to lower growth and productivity, which in turn could reduce accretion and increase erosion [ 50 ]. Further work will be necessary to determine organismal and ecosystem outcomes of endophyte loss in S . alterniflora . Additionally, further work will be necessary to determine the pace and trajectory of endophyte community reassembly following stressor exposure. Our findings suggest that the presence of oil impedes the reassembly of endophyte communities in S . alterniflora , with rates of reassembly contingent on composition ( i . e ., bacterial versus fungi), and tissue type ( i . e ., leaf versus root). It is also likely that the duration of stressor exposure ( i . e ., acute versus chronic) also drives reassembly rates. Identifying the conditions that control reassembly would not only aid in rapid assessment of stressor exposure and ecological integrity [ 57 ], it would also promote the development of methods to facilitate reconstitution of symbioses and novel approaches to accelerate recovery of at-risk ecosystems. For example, resilience might be enhanced by inoculating host plants with indigenous endophytes [ 22 ] or protective benefits might be conferred with targeted endophytes known to metabolize contaminants [ 75 ] which could lead to more effective remediation and ecosystem restoration.",
"introduction": "Introduction Disturbance or shifts in environmental conditions can disrupt widespread and often obligate symbiotic associations. Many symbionts confer benefits to hosts, such as nutrient acquisition ( e . g ., mycorrhizae and nitrogen-fixing bacteria), protection through production of toxins ( e . g ., cyanobacteria in cycads), and production of photosynthate ( e . g ., algae in lichens and zooxanthellae in corals). Although these relationships are often beneficial to both partners, changes in environmental conditions, such as those brought on by climate change or acute disturbances, may result in disassociation. For example, corals expel zooxanthellae when ocean temperature spikes [ 1 , 2 ], pH drops [ 3 , 4 ], or when salinity increases [ 5 ]. Disruption of symbiotic associations may place a temporary strain on the host, or in some cases lead to host death. Consequently, the loss of symbionts can propagate to population and community-wide mortality, which in turn can result in sustained loss of biodiversity and ecosystem services [ 6 – 9 ]. Endophytes are microorganisms that live asymptomatically within plant tissue [ 10 ]. These symbionts have been found throughout the plant kingdom and have been described as “hyperdiverse” [ 11 ]. Endophytes are increasingly becoming recognized as contributors to plant performance. Some endophytic bacteria are known to directly and indirectly protect host plants against pathogens [ 12 – 15 ] and others increase nutrient acquisition [ 16 ]. Fungal endophytes have been shown to increase host tolerance to biotic stress, including pathogen and herbivore damage [ 17 – 19 ], but also to abiotic stress, such as drought, high salinity, and extreme temperatures [ 20 , 21 ]. For example, Redman et al . [ 22 ] were able confer salt and drought tolerance to rice plants through inoculation with specific salt- and temperature-adapted endophytes. Additionally, endophytes have been shown to increase plant growth, water retention, and chlorophyll concentration, as well as protect hosts against oxidative stress [ 23 ]. Though the influence of endophytes can drive host plant demography [ 24 ] and shape plant communities [ 25 – 27 ], and though several studies have demonstrated mutualistic relationships between endophytes and plants, little is known about endophyte responses and subsequent effects on plant hosts following stressor exposure [ 28 ]. Prior studies suggest that endophyte community structure shifts in response to stressor exposure. Some specialized endophyte species have been shown to thrive under extreme stress, such as hypersaline coastal ecosystems and high temperatures from hydrothermal vents [ 20 ]. Symbioses with plants in these cases have been described as “habitat-adapted symbiosis,” indicating that each partner in the symbiosis requires the presence of the other to survive under such conditions [ 22 ]. Kandalepas [ 29 ] showed, however, that endophyte diversity in the obligate marsh plant Sagittaria lancifolia decreases and that endophyte composition changes with chronic salt and flood stress. This suggests that exposure to stress may lead to sustained loss of endophytes and disassociation of endophyte-host plant symbioses. Greater understanding of endophyte responses to stress could shed light on fundamental ecological processes and offer novel perspective on how symbioses can sustain at-risk ecosystems. In this study, we examine the effects of oil exposure on endophytes of Spartina alterniflora (smooth cordgrass)—a foundational species of salt marshes across the Atlantic and Gulf coasts of North America. Smooth cordgrass inhabits high saline environments that are frequently flooded—stressful conditions that exceed the tolerance limits of nearly all plant species [ 30 ]. Prior studies suggest that other salt marsh plants harbor a high diversity and abundance of endophytes that shift following exposure to recurring natural abiotic stress [ 31 , 29 ]. Here we examined endophytes from S . alterniflora plants in marshes that were oiled by the Deepwater Horizon (DWH) oil spill in 2010, as well as from plants in nearby reference areas that were not oiled ( Fig 1 ). Our objective was to determine whether stressor exposure can result in sustained loss of endophytes in a system where elevated susceptibility of plant hosts to stress or injury could cascade into further reinforcing loss of endophyte diversity, host plant integrity, and ecosystem function [ 32 ]. We hypothesized that exposure to novel stress might result in pronounced shifts in endophyte community composition, including sustained loss from plant hosts. Fungal and bacterial endophytes isolated from roots and leaves were examined to determine whether common endophytes disassociate from plant hosts following oil exposure, while hydrocarbon-metabolizing fungi and bacteria persist [ 33 ]. Evidence of either outcome would suggest that the structure and composition of endophyte communities could serve as a new class of biological indicators of stressor exposure, including hydrocarbon contamination, in coastal marshes and other at-risk ecosystems. 10.1371/journal.pone.0122378.g001 Fig 1 Map of study area. (A) The location of S . alterniflora collections for oiled (yellow circles) and unoiled reference (red circles) areas at Bay Jimmy; and (B) the location of S . alterniflora collections for oiled and unoiled reference areas at Fourchon. Specific GPS coordinates for each area at both sites are provided in Table A in S1 File . Images were obtained from the Louisiana Oil Spill Coordinator's Office (LOSCO), 20000120, Louisiana Land and Water Interface, Geographic NAD83, LOSCO (2000) (landwater_interface_LOSCO_1992). Metadata for these maps are available at http://lagic.lsu.edu/data/losco/landwater_interface_losco_1992.html .",
"discussion": "Discussion Like other widespread symbionts, endophyte communities can be disrupted by stressor exposure. Our finding that oil contamination altered root and foliar endophyte communities within a foundational salt marsh plant demonstrates that the principle of anthropogenic disruption of host-symbiont interactions [ 3 , 4 ] extends to plant-endophyte systems. Our results also illustrate that the DWH spill has left a lasting imprint on the ecology of northern Gulf of Mexico shorelines. We detected pronounced shifts in fungal and bacterial endophyte communities within S . alterniflora from oiled shorelines sampled three years after the spill. The diversity and abundance of endophytes were markedly lower in plants from oiled areas, largely reflecting the loss of foliar endophytic fungi. The composition of remnant communities also reflected shifts toward oil-philic OTUs, which mostly consisted of oil-philic bacteria. Though the role of endophytes in S . alterniflora remains undetermined, the disruption of endophyte community structure could debilitate host plants through the loss of stress tolerance or other key physiological functions [ 20 , 22 , 46 , 47 ]. Spartina alterniflora can achieve full vegetative recovery in as little as seven months after 100% oil cover [ 48 ], but our findings indicate that full ecological and physiological function may not be recovered years after initial exposure. Thus, even if vegetative regrowth is achieved following an oiling event, S . alterniflora may be more susceptible to other stressors, such as inundation and nutrient loading, which are linked to marsh loss [ 49 – 52 ]. If so, then the duration and magnitude of direct impacts attributable to the DWH spill may be amplified by cascading vulnerability arising from the disruption of ecological interactions. Endophyte abundance and diversity Foliar fungal endophytes were nearly absent in plants from oiled areas. This contrasts sharply with evidence that fungi became dominant constituents of metazoan communities in beach sediments oiled during the DWH spill [ 33 ]. Our growth experiments demonstrated that the observed loss could be an outcome of oil toxicity, but oiling may also indirectly shape foliar fungal endophyte communities. The foliar endophytes examined in this study are horizontally transmitted via spores dispersed via air currents. While outside of the host plant tissue, endophyte spores are susceptible to environmental influences that may decrease inoculum potential. Spore density or viability on plant surfaces or other substrates could be reduced if oiling prevents endophytes from penetrating leaf surfaces or extending hyphal growth within tissues of oiled plants. Physiological responses of host plants to oil exposure also may shape endophyte community structure. For example, plant uptake of PAHs [ 53 ] might select for endophytes that are able to metabolize hydrocarbons and derivative by-products inside of plant tissues [ 54 ]. Though further work will be necessary to test this hypothesis, our survey results support the possibility of functional retention of select endophytes in stressed host plants. Additional support for this comes from evidence of elevated concentrations of PAHs on leaf surfaces, in the cuticle, as well as within the leaf tissue of S . alterniflora concurrently sampled from oiled areas at Bay Jimmy [ 55 ]. More modest responses were detected for root fungal endophytes and bacterial endophytes. We observed lower fungal endophyte diversity in roots from plants sampled in oiled areas, but in contrast to foliar fungal endophytes, oiling did not influence the abundance of root fungal endophytes. No differences in bacterial endophyte diversity or abundance were detected. Evidence of reduced root fungal endophyte diversity is consistent with evidence of lower fungal diversity in beach sediments oiled by the DWH spill [ 33 ]. The loss of fungal diversity in beach sediments has been attributed to oil-induced environmental stress favoring resilient, opportunistic species able to capitalize on the availability of new resources [ 33 ]. Our findings suggest that the observed shifts in fungal endophyte communities may be attributable to a similar process, though oiling can also influence the availability of host-derived carbon and nutrients, reduce inoculum potential, and prevent penetration of root tissue. Discriminating among these possibilities will require examining the S . alterniflora rhizosphere to determine the prevalence of fungal spores typical of an endophytic lifestyle. Bacterial endophytes appear to be less sensitive to oiling than fungal endophytes, but it is also possible that bacterial endophyte responses are more transient than fungal responses. Oiling can elicit punctuated and temporary shifts in bacterial communities. Beazley et al . [ 56 ] found, for example, that the relative abundance and number of bacterial OTUs increased sharply in oiled salt marsh sediments during the DWH spill, reflecting a spike in the abundance of hydrocarbon-degrading microbial populations. Our findings do not exclude the possibility that bacterial endophyte communities underwent rapid succession, possibly related to the use of different hydrocarbon compound classes [ 57 ]. Indeed, our surveys and growth assays suggest that oil exposure elicited the rise of hydrocarbon-degrading OTUs, resulting in lasting shifts in the composition of bacterial endophyte communities. Community structure Oil exposure altered endophyte community structure in S . alterniflora , with contrasting pathways of response in foliar versus root communities. Oiling resulted in the divergence of foliar communities and the convergence of root communities. The observed response trajectories are likely a reflection of selective retention acting in conjunction with dispersal pathways through aerial and subsurface environments. Foliar endophytes tend to be wind dispersed as spores, while root endophytes are largely transported by water in soil [ 58 ]. Therefore greater similarity would be expected for foliar communities among our unoiled reference areas, as dispersal is likely not limiting across the spatial scale of this study. Stressor exposure, however, may limit the potential of spore inoculum potential, thereby increasing the possibility that the community structure of foliar endophytes reflects the intensity and persistence of oil within the local environment. Conversely, root endophytes would be expected to be less similar in unoiled reference areas, as heterogeneous soil conditions and dispersal limitation are known to affect subsurface microbial community structure [ 58 ]. Thus community dissimilarity is likely a reflection of stochastic and limited dispersal promoting ecological drift [ 59 ]. Convergence may subsequently result from oiling acting as a selective filter via toxicity, effects on inoculum potential, penetration of root tissue, or resource availability. The composition of bacterial endophyte communities in plants sampled from oiled areas was similar to bacterial communities found in salt marsh sediments and beach sands oiled during the DWH spill [ 56 , 57 , 60 , 61 ]. Nearly 40% of the bacterial endophytes found in plants from oiled areas belonged to the phylum Proteobacteria , with most Proteobacteria OTUs identified as Alpha - and Gammaproteobacteria . Many of these bacteria have been linked to degradation of recalcitrant hydrocarbons, including PAHs, in contaminated sediments [ 62 – 64 ]. The most common bacterial endophyte in our study, however, was Bacillus pumilus (Phylum: Firmicutes ), a nitrogen fixing bacterium [ 65 ] prevalent in high salinity environments [ 66 ] known to promote plant growth and protect roots and leaves from fungal pathogens [ 66 – 69 ]. Firmicutes are known to contain several hydrocarbon-metabolizing families, including Bacillaceae [ 56 ]. Bacillus pumilus was equally or more abundant in samples from oiled versus unoiled reference areas, except in leaf tissues taken from oiled areas at Fourchon, in which it was altogether absent. Beazley et al . [ 56 ] similarly found that abundance of Firmicutes in oiled salt marsh sediments steadily increased during and after the oil spill, even when oil was no longer detectable. As community enrichment of Firmicutes has also been observed in other affected coastal environments, including oiled beaches [ 70 ], the group could serve as an indicator of hydrocarbon degradation, particularly when more recalcitrant compounds like PAHs are present. Though comparably little is known about the function of constituent members of fungal communities, our findings indicate that the observed shifts are attributable to differential responses of indigenous taxa to the presence of oil. The most common fungal strain found in our study was a species of Phaeosphaeria . We found that this strain was more prevalent in roots and leaves from plants sampled in Fourchon, as well as in leaves from plants sampled in Bay Jimmy, but it was absent in roots from plants collected in Bay Jimmy. This discrepancy could reflect functional variation among Phaeosphaeria lineages, variation in length of time since oil exposure, or under sampling. Phaeosphaeria are known to be one of the primary decomposers in salt marshes dominated by S . alterniflora [ 71 ]. Phaeosphaeria fungi also are being explored as potential agents for bioremediation of oil contamination [ 72 ]. Members of this group are known to contain lignolytic laccase enzymes, which have been shown to aid in the detoxification of organic pollutants within the rhizosphere [ 73 ]. Evidence of elevated production of these enzymes in oiled marsh sediments also has been attributed to hydrocarbon degradation arising from plant-microbe interactions [ 56 ]. The observed shifts in endophyte structure may reflect underlying responses to stressor exposure. Many of the families found in our study are known to promote the integrity of host plants through other mechanisms. For example, Bacillus cereus —which was found in roots from plants in oiled areas of Bay Jimmy—can promote root and shoot growth as well as higher chlorophyll concentrations [ 74 , 23 ]. Bacillus taquilensis can protect plants from oxidative stress [ 23 ]. Bacillus cereus and B . taquilensis also can increase water retention, thereby ameliorating salt stress in host plants [ 23 ]. Though Phaeosphaeria is a promising tool for bioremediation [ 72 ], our findings suggest that these fungi may influence a range of functions. The dominant strain detected within S . alterniflora appears to be systemic, as it was isolated from leaves and roots. Thus endophytes may serve dual or multiple purposes, and some may exhibit different functions when host plants are exposed to novel conditions like oil contamination. Further study is warranted to determine the functional plasticity of endophytes and to better understand the importance of individual versus community-level contributions to host plant survival and fitness. More intensive sampling and a wider range of assays could offer further understanding of in vitro responses to exposure, and in planta experiments could clarify how in vitro assays reflect in planta conditions. Because a great majority of bacteria and fungal endophytes are not culturable, use of culture independent approaches (e.g., genomic assays) could also enrich understanding of taxonomic and functional responses of endophyte communities to stress and disturbance."
} | 5,108 |
23086573 | null | s2 | 5,293 | {
"abstract": "Cell-free protein synthesis harnesses the synthetic power of biology, programming the ribosomal translational machinery of the cell to create macromolecular products. Like PCR, which uses cellular replication machinery to create a DNA amplifier, cell-free protein synthesis is emerging as a transformative technology with broad applications in protein engineering, biopharmaceutical development, and post-genomic research. By breaking free from the constraints of cell-based systems, it takes the next step towards synthetic biology. Recent advances in reconstituted cell-free protein synthesis (Protein synthesis Using Recombinant Elements expression systems) are creating new opportunities to tailor the reactions for specialized applications including in vitro protein evolution, printing protein microarrays, isotopic labeling, and incorporating nonnatural amino acids."
} | 218 |
33228110 | PMC7699398 | pmc | 5,294 | {
"abstract": "Biofilms are aggregates of microbial cells encased in a highly hydrated matrix made up of self-produced extracellular polymeric substances (EPS) which consist of polysaccharides, proteins, nucleic acids, and lipids. While biofilm matrix polysaccharides are unraveled, there is still poor knowledge about the identity and function of matrix-associated proteins. With this work, we performed a comprehensive proteomic approach to disclose the identity of proteins associated with the matrix of biofilm-growing Burkholderia multivorans C1576 reference strain, a cystic fibrosis clinical isolate. Transmission electron microscopy showed that B. multivorans C1576 also releases outer membrane vesicles (OMVs) in the biofilm matrix, as already demonstrated for other Gram-negative species. The proteomic analysis revealed that cytoplasmic and membrane-bound proteins are widely represented in the matrix, while OMVs are highly enriched in outer membrane proteins and siderophores. Our data suggest that cell lysis and OMVs production are the most important sources of proteins for the B. multivorans C1576 biofilm matrix. Of note, some of the identified proteins are lytic enzymes, siderophores, and proteins involved in reactive oxygen species (ROS) scavenging. These proteins might help B. multivorans C1576 in host tissue invasion and defense towards immune system assaults.",
"conclusion": "5. Conclusions In conclusion, we have shown that biofilm-growing B. multivorans C1576 produces OMVs and that these spherical bilayered structures represent a source of proteins for the biofilm matrix together with cell lysis. Our results also elucidate the proteome from a functional perspective of the biofilm matrix and OMVs of B. multivorans C1576. This work opens perspectives to disclose the role played by the OMVs within biofilms produced by B. multivorans C1576.",
"introduction": "1. Introduction In natural settings and in man-made environments, many bacteria are generally found to live in highly complex communities referred to as biofilms, which are surface-associated aggregates of microbial cells embedded in a matrix consisting of extracellular polymeric substances (EPS) [ 1 , 2 , 3 , 4 ]. Although the composition of the biofilm matrix varies with the bacterial species and the growth conditions under which biofilms develop, EPS generally include polysaccharides, proteins, nucleic acids, and lipids [ 5 ]. The biofilm lifestyle allows bacterial cells to experience a physical closeness which is the base for phenomena such as quorum sensing (QS) and horizontal gene transfer (HGT) [ 6 ]. Moreover, the biofilm matrix provides bacteria with protection towards dehydration, UV light, disinfectants, and toxic metal ions, some antimicrobial compounds, many protozoa, and attacks by the immune system of the host [ 6 ]. As a generality, the composition of the biofilm matrix consists of exopolysaccharides, proteins, and nucleic acids, although the components and their proportions are dependent on the microorganism and the conditions of their growth [ 5 ]. In floating activated sludge, the protein content can even exceed that of polysaccharides [ 7 , 8 , 9 ]. Matrix-associated proteins are represented by membrane surface adhesins, proteins building up extracellular appendages (flagella, pili, and fimbriae), proteins actively secreted, and proteins transported by outer membrane vesicles (OMVs) [ 5 ]. OMVs are recognized as biofilm matrix components [ 10 ] and their biological role has been related to protective mechanisms [ 11 ], as they are involved in a wide range of phenomena like pathogenesis, bacterial communication, bacteria-host interactions, nutrient capture, HGT, and competition [ 12 , 13 ]. OMVs are bi-layered structures with a diameter ranging from 20 to 200 nm, which gemmate from the outer membrane (OM) of many Gram-negative bacteria [ 14 , 15 ]. OMVs generally carry OM lipids, lipopolysaccharide, proteins, and nucleic acids [ 16 ]. Burkholderia multivorans is a Gram-negative opportunistic pathogen that can cause severe lung infections in cystic fibrosis (CF) patients [ 17 ]. It belongs to the so-called Burkholderia cepacia complex (Bcc), a group of at least 22 closely-related species widely distributed in natural environments and with the ability to infect plants, animals, and humans [ 18 , 19 , 20 , 21 , 22 ]. When grown in Petri dishes containing different solid culture media, Bcc species have been shown to produce various biofilm polysaccharides or exopolysaccharide (Epols), most often in mixtures [ 23 ]. Furthermore, the specific biofilm mode of growth may influence the production of distinct Epols [ 24 ]. In this work, we used B. multivorans strain C1576, a CF clinical isolate biofilm-growing species which was thoroughly investigated for Epol production in our laboratory. It produces cepacian, the most common Epol among both Bcc and non-Bcc species when grown on semipermeable nitrocellulose membranes deposited on solid yeast extract–mannitol culture medium [ 25 ]. When grown in the same way but using Mueller–Hinton medium, it synthesizes a different exopolysaccharide which has been named EpolC1576. The latter consists of a tetrasaccharide repeating unit containing equimolar amounts of D-mannose and D-rhamnose [ 25 ]; this polymer might be involved not only in biofilm formation and maintenance, but also in the diffusion of small nonpolar compounds like quorum sensing molecules, through the highly hydrated environment of the biofilm matrix [ 26 ]. The presence of proteins has been recognized in biofilms of many bacterial species, but their identification and functional characterization have been addressed only for a limited number of bacteria [ 27 ], including some Burkholderia species [ 28 , 29 , 30 ]. At the same time, Burkholderia OMVs have been investigated mainly in the frame of vaccine development [ 31 , 32 , 33 ], while there is little information about their proteome [ 34 ]. Therefore, the aim of this work was to elucidate the proteins associated with the biofilm matrix of B. multivorans C1576.",
"discussion": "4. Discussion Even though extracellular proteins have been proposed to be of primary importance for the function of the biofilm matrix, there is still a lack of knowledge about the identity of many of them. In this work, matrix-associated proteins of biofilm-growing B. multivorans C1576 have been identified. It has not been surprising to find that a large fraction of the matrix proteome of B. multivorans C1576 is made up of membrane-bound and cytoplasmic proteins. Membrane and cytoplasmic proteins have been recognized in the biofilm matrix of various bacterial species [ 42 , 43 , 44 , 45 ], even in those characterizing microbial communities of activated sludges and acid mine drainage [ 46 , 47 ]. Despite this, the reason why these proteins localize in the biofilm matrix is still elusive. Biofilm production involves bacterial cell death, an event that is thought to be characteristic of developing biofilms [ 42 ], thus suggesting that cell lysis could explain the presence of membrane-bound and cytoplasmic proteins in the matrix. Another source of intracellular proteins for the matrix could be represented by spherical bilayered structures from the outer membrane, the OMVs, that planktonic and biofilm-growing Gram-negative bacteria have been shown to release [ 12 ]. Burkholderia thailandensis OMVs range in size from 20 to 100 nm and contain antimicrobials [ 34 ], while Burkholderia cepacia releases OMVs that range from 30–220 nm in diameter and contain virulence factors [ 48 ]. Similarly, our results showed that most of the OMVs of B. multivorans C1576 have a diameter that ranges between 25 and 70 nm and some of them reached 150 nm ( Figure 2 ). These spherical bilayered structures that gemmate from the outer membrane have been recognized to be a relevant component of the biofilm matrix of other Gram-negative bacteria such as P. aeruginosa [ 12 ]. The proteome of OMVs produced by biofilm-growing B. multivorans C1576 consisted of 64 proteins. Many of them are outer membrane proteins and this is in good agreement with previous findings [ 16 , 49 ]. OMVs contain porins, siderophores, and enzymes scavenging reactive oxygen species. Proteomic data reveal that about 29% of OMV-associated proteins (19 out of 64) are in common with the matrix proteome ( Figure 3 ), thus indicating that OMVs could represent a source of both membrane-bound and cytoplasmic proteins for the biofilm matrix of B. multivorans C1576. As observed for other Gram-negative species [ 49 , 50 ], OMVs are greatly enriched in outer membrane proteins including porins ( opcP ; Bmul_4327; Bmul_4600), receptors (Bmul_1594; Bmul_3338; Bmul_4173) and lipoproteins ( slyB ). However, only 5 proteins out of the 20 most abundant matrix-associated proteins are found in OMVs. Our data suggest that cell death and release of OMVs are mainly responsible for the composition of the extracellular proteome of biofilm-growing B. multivorans C1576. It would be interesting to know whether some of these proteins possess enzymatic activity and/or a structural role that is crucial for the biofilm physiology. Not surprisingly, various lytic proteins that could be involved in the enzymatic degradation of different molecules have been identified, such as the peptidase S1 (Bmul_3442), the proteolytic subunit of the ATP-dependent Clp protease (Bmul_1349— clpP ), and an endoribonuclease (Bmul_1781). Even though some of these proteins have not been characterized as virulence factors yet, it cannot be ruled out that they could support B. multivorans C1576 infections via the degradation of host tissues. These enzymes could also help B. multivorans C1576 to resist attacks perpetrated by phagocytic cells and other microorganisms. It is interesting to note that a bacteriocin (Bmul_5413— lin ) has also been found. Bacteriocins are powerful toxins with an antibacterial activity that mediate competition between different bacterial species [ 51 ]. Since P. aeruginosa and Bcc species can co-infect CF patients [ 52 ], it can be speculated that bacteriocins could help B. multivorans C1576 in shaping and defining the relationship with P. aeruginosa within CF lungs. Among the matrix-associated proteins, the well-characterized virulence factor named ecotin ( ecoT -WP_006405712.1) has been detected. The one produced by P. aeruginosa has been shown to inhibit the serine protease elastase synthesized by neutrophils [ 53 ], thus severely compromising the bactericidal efficiency of this enzyme. In the same way, ecotin produced by B . multivorans C1576 can protect the bacteria from killing activity of elastase secreted by neutrophils, thus enhancing bacterial tolerance towards the innate immune system. Proteins responsible for detoxification of reactive oxygen species (ROS) are a relevant fraction of both matrix- and OMVs-associated proteins. Proteins found to be involved in oxidative stress are four thiol peroxidases tpx (SMG02352.1, WP_006400399.1, WP_057926826.1, and WP_059465341.1), a superoxide dismutase sod (EGD01013.1), catalase HPII ( katE , CATE_ECOLI), a peroxidase (Bmul_2571, OJD07310.1), and a thioredoxin (Bmul_1445, ABC39250.1). Since some of these detoxifying enzymes have been found associated with OMVs, it may be speculated that B. multivorans C1576 releases them via OMVs to cope with oxidative stresses. The presence of matrix-associated enzymes that inactivate ROS would allow bacteria to resist to those attacks from phagocytes based on hydrogen peroxide production [ 54 ]. It has been interesting to find that OMVs carry various proteins involved in iron acquisition, also referred to as siderophores. Acquisition of iron is crucial for bacterial survival and siderophores have been recognized as relevant virulence factors for many pathogens affecting CF patients [ 55 , 56 ]. Since, in body fluids iron is tightly bound to proteins such as transferrin, lactoferrin, and ferritin [ 57 ], bacterial pathogens have developed strategies to utilize these proteins as sources of iron. For example, in CF lungs B. cenocepacia can acquire iron after proteolytic degradation of ferritin [ 58 ]. In the same way, siderophores identified in B. multivorans C1576 could help this opportunistic pathogen to survive within the host environment where availability of free iron is strictly limited. The biological role of the intracellular proteins associated with both the biofilm matrix and OMVs of B. multivorans C1576 is not known. There is experimental evidence that some intracellular proteins may have a function also outside the cell and for this reason they have been named moonlighting proteins [ 59 ]. Among these proteins, there is the elongation factor Tu which has been localized on the surface of P. aeruginosa where it helps bacteria to evade the human complement attack via interactions with host regulatory proteins [ 60 ]. The matrix proteome of B. multivorans C1576 has been found to contain various elongation factors (G, Ts, GreAB), but not the elongation factor Tu. The latter, together with chaperonin GroEL, has been also shown to enable lactobacilli to bind to mucin and epithelial cells of the human gastrointestinal tract [ 61 , 62 ]. Since some of these intracellular proteins have been demonstrated to be involved in host-pathogen interactions for other bacterial species, it can be speculated that one or more intracellular proteins localized in the biofilm matrix of B. multivorans C1576 could play a role in bacterial pathogenesis. Moreover, the presence of the mentioned chaperons and elongation factors, plus ribosomal proteins (A9ADI4) of cytoplasmic origin in OMVs was also described for E. coli , suggesting that, as the translation of outer membrane proteins occurs simultaneously with the integration into the membrane, transcriptional and ribosomal proteins can be included into OMVs [ 49 , 63 , 64 ]. Many of the identified proteins are membrane-bound proteins and of cytoplasm origin, thus suggesting that cell lysis could represent a relevant source of proteins for the biofilm matrix. They are porins, ATP binding-cassette transporters (ABC), enzymes of the tricarboxylic acid cycles (TCA), proteins involved in fatty acids biosynthesis, cell redox homeostasis, and translation. Moreover, the presence of the bacterial DNA-binding proteins indicates that DNA molecules are components of the biofilm matrix of B. multivorans C1576, as already seen for other bacterial species [ 65 , 66 , 67 , 68 , 69 ]. Extracellular DNA molecules (eDNA) have been recognized as a prominent constituent of the bacterial biofilm matrix [ 65 , 70 ]. For this reason, it has not been unexpected to find DNA-binding proteins in the proteome of the biofilm matrix of B. multivorans C1576. The DNA-binding protein HU-alpha hupA (DBHA_BURPS), which is a histone-like protein involved in DNA wrapping, has been found associated with OMVs, whereas the DNA-binding protein Bv3F (Bmul_0190, POM19719.1) and a single-stranded DNA-binding protein (Bmul_0538, SMG01792.1) have been localized in the biofilm matrix. Even though DNA-binding proteins affect DNA compactness and transcription [ 71 ], it is unknown whether they influence the structural and functional properties of eDNA in the context of the biofilm matrix. Beyond exoenzymes, membrane-bound and DNA-binding proteins, the biofilm matrix of bacteria also contains lectins, proteins with no enzymatic activity, but showing specific carbohydrate-binding ability. Lectins are thought to take part in biofilm formation and development, but also to be responsible for its architecture and mechanical stability. Transcriptomic and proteomic analysis of mutants of B. cenocepacia H111 led to the identification of the quorum sensing-regulated operon bclACB which codes three lectins: BclA, BclC, and BclB [ 72 ]. B. cenocepacia H111- bclACB mutants produce biofilms with altered architecture with respect to the wild-type, thus suggesting that these three lectins are necessary for biofilm proper development [ 72 ]. In the search for proteins of B. multivorans C1576 that may interact with EpolC1576, no known carbohydrate-binding protein has been found."
} | 4,066 |
38091402 | PMC10848725 | pmc | 5,295 | {
"abstract": "Strain-induced crystallization (SIC) prevalently strengthens, toughens, and enables an elastocaloric effect in elastomers. However, the crystallinity induced by mechanical stretching in common elastomers (e.g., natural rubber) is typically below 20%, and the stretchability plateaus due to trapped entanglements. We report a class of elastomers formed by end-linking and then deswelling star polymers with low defects and no trapped entanglements, which achieve strain-induced crystallinity of up to 50%. The deswollen end-linked star elastomer (DELSE) reaches an ultrahigh stretchability of 12.4 to 33.3, scaling beyond the saturated limit of common elastomers. The DELSE also exhibits a high fracture energy of 4.2 to 4.5 kJ m −2 while maintaining low hysteresis. The heightened SIC and stretchability synergistically promote a high elastocaloric effect with an adiabatic temperature change of 9.3°C.",
"introduction": "INTRODUCTION Strain-induced crystallization (SIC) is a prevalent phenomenon in elastomers and gels where amorphous polymer chains transform into highly oriented and aligned crystalline domains due to an applied mechanical strain ( 1 ). Since these oriented and aligned crystalline domains can resist crack extension, promote crack blunting, and facilitate crack deflection ( 2 , 3 ), SIC remarkably reinforces elastomers and gels, giving increased strength and toughness ( 4 ). Soft materials are typically reinforced with dissipation mechanisms ( 5 – 11 ) by inducing viscoelasticity or the Mullins effect, which require substantial recovery time and cause internal damage. In contrast, SIC—as a rapid reinforcement strategy—can preserve network integrity and achieve close to 100% recovery in seconds ( 12 , 13 ). In addition to its impacts on material reinforcement, SIC plays a vital role in various applications, including elastocaloric cooling ( 14 – 16 ) and strain-programmable actuation ( 17 ). The strain-induced crystallinity in common elastomers is typically below 20%. For instance, natural rubber (NR) only achieves about 15% crystallinity when stretched six times its initial length at room temperature ( 18 ). Mechanical training ( 19 ) or freeze-assisted salting out ( 20 ) of polyvinyl alcohol (PVA) hydrogels can increase the crystallinity to about 40%, but these processes create permanent structural changes. Similarly, the crystallinity of plastics ( 21 ), fibers ( 22 ), and polymer solutions ( 23 ) can irreversibly rise due to mechanical loading. In these cases, the newly formed crystalline domains do not revert to amorphous chains when unloaded. Recent studies report that poly(ethylene glycol) (PEG) hydrogels with slide-ring or tri-branched architectures achieve reversible SIC under large deformations but rely on the presence of a solvent ( 12 , 13 ). The irreversibility, low magnitude of strain-induced crystallinity, or solvent dependency in soft materials substantially limits their performance for diverse applications. For example, although elastocaloric cooling by SIC in NR was first studied as early as 1805 ( 24 ), commercialization of elastomer-based elastocaloric refrigeration has been hampered by deficient SIC. It remains technologically challenging yet highly desirable to design soft materials with high, elastically reversible SIC. Here, we report a class of deswollen end-linked star elastomers (DELSEs) that achieve up to 50% strain-induced crystallinity. We attribute the ultrahigh SIC in the DELSE to two characteristics that differ for conventional elastomers: a uniform network structure and a high stretchability due to the lack of trapped entanglements ( 25 , 26 ). We take advantage of tetra-PEG gels pioneered by Sakai and colleagues because the network contains a regular structure with fewer defects than common networks and attains elasticity consistent with the phantom network model ( Fig. 1A ) ( 25 – 28 ). We show here that a DELSE can, unlike the tetra-PEG gel or common elastomers, achieve ultrahigh SIC. In contrast to the DELSE, common elastomers contain a widely dispersed chain length distribution, substantial molecular defects, and considerable trapped chain entanglements because they are synthesized by either vulcanization or gelation at relatively high concentrations ( Fig. 1B ). Second, we find that the root mean square (RMS) end-to-end distance of polymer chains in the DELSE when fully deswollen from the overlap concentration is R (Φ = 1) ≈ ν mon 1/3 \n N 1/3 , where ν mon is the Kuhn monomer volume and N is the number of Kuhn monomers per chain ( Fig. 1E ) (see the Supplementary Materials for derivation) ( 29 ); common elastomers typically have R (Φ = 1) ≈ N 1/2 b , namely, that of unperturbed Gaussian chains ( Fig. 1G ), where b is the Kuhn length ( 30 , 31 ). We used molecular dynamics to calculate the average end-to-end distance of polymer chains in the DELSE compared with conventional polymer melts, validating the scaling of R (Φ = 1) ~ N 1/3 ( Fig. 1, F and H ). Because of this scaling and the lack of trapped entanglements, the bulk stretchability is much higher in the DELSE than in common elastomers. The former scales as N 2/3 without an upper limit, while the latter scales as \n N 1/2 and saturates at N e 1/2 when N > N e , where N e is the entanglement molecular weight. We propose that these features of the DELSE above T m effectively promote uniform polymer chain orientation and alignment under an applied bulk strain, causing the ultrahigh SIC ( Fig. 1, C and D ). Fig. 1. Deswollen end-linked star elastomers. ( A ) The DELSE forms through controlled crosslinking of star macromers followed by solvent evaporation to form a homogeneous crosslinked polymer network (illustrations are exaggerated to highlight architectural differences). ( B ) Conventional elastomers form through random crosslinking processes such as vulcanization of long polymer chains or gelation from monomers. ( C ) The more homogeneous architecture supports chain alignment during stretching causing crystalline domain formation in the DELSE. ( D ) In contrast, physical barriers like trapped entanglements and inhomogeneities limit the effect of SIC in common elastomers. ( E ) The RMS end-to-end distance of polymers chains in a DELSE in the undeformed state scales as N 1/3 , as validated by ( F ) molecular dynamics simulation (representative simulated chain conformation inset). ( G ) The RMS end-to-end distance of polymers chains in a conventional elastomer in the undeformed state scales as N 1/2 , as validated by ( H ) molecular dynamics simulation (representative simulated chain conformation inset).",
"discussion": "DISCUSSION Comparisons between the DELSE and NR show how increased stretchability, different polymer chemistry, and a more well-formed structure combinatorially increase the SIC and elastocaloric effect in elastomeric materials. The additional comparison with the DELE, whose stretchability and chemistry parallel those of the DELSE, specifically demonstrates the importance of the relatively homogeneous structure. The DELE also exhibits higher SIC than NR due to its stretchability and chemistry; however, the DELSE outperforms the DELE because it is more homogeneous and contains fewer defects. Since Katz first noticed a rubber band become opaque due to SIC during stretching in 1924 ( 1 ), rubbers have been harnessed throughout society for everything from household goods to car tires, etc. Although applications for rubber have progressed in the modern era, the synthesis strategy has remained almost the same. Here, we report the next generation of elastomers that demonstrate profound SIC, far exceeding that of NR and other common elastomers. The DELSEs also warrant further fundamental investigation due to the abnormal scaling of their elastic stretchability limit. Generally, the elastomer fabrication approach harnessed here—end-linking a highly regular gel and then fully deswelling the network—provides a platform with promise across a breadth of polymer chemistries. As shown here in the DELSE, elastomers fabricated in this manner exhibit the capacity to outperform conventional counterparts. These results also suggest the potential for precisely engineering SIC in soft materials by controlling their network architecture. This class of deswollen elastomers can play a key role in the future of aerospace structures, medical devices, and elastocaloric refrigeration design."
} | 2,104 |
36160001 | PMC9500204 | pmc | 5,296 | {
"abstract": "Lignin contributes to plant resistance to biotic and abiotic stresses and is dominantly regulated by enzymes which catalyze the generation of metabolites intermediates in lignin synthesis. However, the response of lignin and its key regulatory factors to high temperature stress are poorly understood. Here, this finding revealed that the content of lignin in poplar ( Populu s spp) stem increased after 3 days of high temperature stress treatment. In fourteen metabolic intermediates of lignin biosynthetic pathway with targeted metabolomics analysis, caffeate and coniferaldehyde increased evidently upon heat stress. C3’H ( p -Coumaroylshikimate 3-hydroxylase) and CCR (Cinnamoyl-CoA reductase) are recognized to catalyze the formation of caffeate and coniferaldehyde, respectively. Transcriptome data and RT-qPCR (reverse transcription-quantitative real-time polymerase chain reaction) analysis uncovered the high transcriptional level of PtrMYBs ( PtrMYB021 , PtrMYB074 , PtrMYB85 , PtrMYB46 ), PtrC3’H1 (Potri.006G033300) and PtrCCR2 (Potri.003G181400), suggesting that they played the vital role in the increase of lignin and its metabolic intermediates were induced by high temperature. The discovery of key regulators and metabolic intermediates in lignin pathway that respond to high temperature provides a theoretical basis for quality improvement of lignin and the application of forest resources.",
"conclusion": "Conclusion In general, when subjected to high temperature stress, poplar produces lignin through secondary metabolic pathways to resist adverse abiotic stresses. Several TFs (NAC, MYB) and structural genes ( PAL , C4H , C3'H , 4CL , HCT , CCR , COMT , F5H , CCoAOMT , CAD , LAC , and POD ) in lignin synthesis pathway participated in the high temperature response of poplar ( Figure 7 ; Zhang et al., 2020 ). In addition, the intermediates of lignin metabolic pathway (caffeate and coniferaldehyde) were also affected by high temperature and thus regulated lignin content. High temperature increases lignin contents of poplar stem may via inducing the PtrCCR2-participated biosynthesis caffeate and coniferaldehyde possibly under the regulation of PtrMYB021 and PtrMYB074 or some other MYB TFs. The related molecular mechanism needs further analysis and verification. Besides, the changes of H, G and S types of lignins and the changes of lignin ratios/proportions will be research emphases on molecular mechanism analysis. Identification of the key substances and genes in the lignin pathway in response to high temperature is of great significance to explore the high temperature resistance of poplar. FIGURE 7 Regulatory mechanism between high temperature and lignin content. High temperature brings about the increased lignin content. Transcriptome analysis indicated that some vital transcription factors such as PtrMYBs, others lignin related transcription factors and lignin-related structural gene such as PtrC3’H1 , PtrCCR2 were induced by high temperature. PtrC3’H1 may be a possible factor leading to the decrease of caffeate content, while PtrCCR2 may bring about the lessen of coniferaldehyde. caffeate, coniferaldehyde represents the different lignin precursors.",
"introduction": "Introduction Forest resources not only have great application value for vegetation restoration, soil erosion prevention and saline-alkali land restoration, but also can be used for the development of biomass and fiber energy ( Nakahara et al., 2019 ). Lignin plays a vital role in cell wall formation, especially in wood and bark, and it permits the xylem to maintain a certain amount of water transport, mechanical support, growth and development for plants ( Zhao and Dixon, 2011 ). However, lignin is also a major obstacle to the utilization of forest resources ( Van Acker et al., 2013 ; Behr et al., 2019 ). Therefore, the study of lignin is of great significance to the utilization of forest resources. High temperature stress is an important factor affecting plant growth and development ( Zhu, 2016 ). And lignin is essential in plant response to stresses such as high temperature stimuli ( Cesarino, 2019 ). Plant stems are subjected to rapid lignification of cell walls with high temperatures treatment ( Crivellaro and Büntgen, 2020 ). During lignification, lignin accumulation is deposited in the cell wall, which enhances the stiffness of the cell wall and makes the xylem cell wall less permeable to water, facilitating the long-distance transport of water, minerals, and organic matter in the plant ( Zhao, 2016 ). Plants tend to synthesize more lignin so as to enhance their resistance to high temperature stress. Lignin synthesis is a complex network, including the lignin monomers biosynthesis, transport and polymerization process ( Vanholme et al., 2019 ). Lignin monomers are synthesized in the cytoplasm through a series of reactions including hydroxylation, deamination, reduction, methylation and transportation to the apoplast ( Vanholme et al., 2019 ). Seconldly, lignin is produced by the polymerization of lignin monomers in the secondary cell wall ( Vanholme et al., 2008 ; Bonawitz and Chapple, 2010 ; Miao and Liu, 2010 ; Vanholme et al., 2019 ). According to the differences in lignin monomers and crosslinking methods, lignin monomers can be classified as three main forms, including p-hydroxyphenyl (H), guaiacyl (G), and syringyl (S) ( Vanholme et al., 2008 ; Vanholme et al., 2019 ). Many enzymes are involved in formation of lignin monomer, and the expression level of the genes encoding these enzymes directly affects the content and deposition of lignin ( Vanholme et al., 2008 ; Vanholme et al., 2019 ). Lignin is polymerized from the monomers of phenylpropane derivatives. Recently, researches showed that the change of phenylpropanoid biosynthetic enzymes in transgenic poplar had great influence on lignin content ( Wang et al., 2018 ). Phenylalanine ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H), and 4-coumarate CoA ligase (4CL) are three enzymes which are related with the first three catalytic reactions of the traditional phenylpropane pathway, respectively ( Rohde et al., 2004 ; Chen et al., 2006 ; Vanholme et al., 2008 ; Wang et al., 2018 ). The decline of PAL, C4H and 4CL expression reduced the lignin content ( Rohde et al., 2004 ; Chen et al., 2006 ; Vanholme et al., 2008 ; Wang et al., 2018 ). Many other enzymes such as quinate/shikimate p-hydroxycinnamoyltransferase (HCT), p-coumaroylshikimate 3-hydroxylase (C3’H), caffeoyl shikimate esterase (CSE), caffeic acid O-methyltransferase (COMT), caffeoyl-CoA O-methyltransferase (CCoAOMT), cinnamoyl-CoA reductase (CCR), ferulate 5-hydroxylase (F5H), and cinnamyl alcohol dehydrogenase (CAD), are essential to maintain a normal level of lignin content ( Barros et al., 2015 ; Xie et al., 2018 ). The absence of any enzyme more or less affects the synthesis of lignin ( Barros et al., 2015 ; Xie et al., 2018 ). C3’H is a phenolic enzyme that catalyzes the production of p-coumaric acid to caffeic acid and p-coumaryl shikimic acid to catechylshikimic acid. The expression level of C3’H directly affects the lignin content and S/G ratio ( Coleman et al., 2008 ; Bryant et al., 2020 ). CYP98A3 gene was isolated in early bioinformatics experiments, which may encode C3’H enzyme in Arabidopsis ( Schoch et al., 2001 ). In alfalfa, the content of lignin in transgenic plants with increased C3’H expression was 5% higher than that in wild-type plants ( Reddy et al., 2005 ; Pu et al., 2009 ). The lignin content in P. alba × P. grandidentata reduced significantly when the expression of C3’H was inhibited ( Coleman et al., 2008 ; Peng et al., 2021 ). Although the reduction of C3’H expression will lead to dwarfed phenotype, relevant studies have shown that the specific components in mediator complex can contribute to the normal growth of plants and the increase of H-type lignin, which is conducive to the conversion of bioenergy ( Bonawitz et al., 2014 ). CCR catalyzes the generation of hydroxycinnamaldehydes from hydroxycinnamoyl-CoA esters, and its down-regulation causes the decline of lignin content ( Ruel et al., 2009 ; Van Acker et al., 2014 ). ccr1 mutant in maize changed the lignin deposition in the walls of the sclerenchymatic fibre cells surrounding the vascular bundles and lignin content ( Tamasloukht et al., 2011 ). Besides, reduction of lignin caused by decreased CCR expression brings about lower ferulic acid resulting in a decrease in polymers ( Leplé et al., 2007 ; Ralph et al., 2008 ). Down-regulation of CCR gene expression can reduce the conversion of poplar into ethanol and even the biomass of poplar ( Van Acker et al., 2014 ). A recent study found that CCR2 knockdown can reduce lignin content in poplar trees without affecting their normal growth ( De Meester et al., 2020 ). Besides, the overexpression of OsCCR can increase the lignin content and enhance the resistance to pathogenic bacteria in rice ( Kawasaki et al., 2006 ). COMT is the methylation enzyme of lignin biosynthesis, which is responsible for the methylation of lignin precursor ( Daly et al., 2019 ). It catalyzes the methylation of a number of substances such as 5-hydroxy coniferyl alcohols, caffeoyl, free acids and aldehydes ( Daly et al., 2019 ). Inhibition of COMT transcription level in tobacco and poplar decreased lignin content ( Dwivedi et al., 1994 ; Jouanin et al., 2000 ). In ryegrass, the biomass and phenotype unchanged with COMT1 expression disturbed ( Tu et al., 2010 ). Significantly, the economic value of ryegrass was increased by the reduction of lignin and its components ( Tu et al., 2010 ). The transcriptional level and enzyme activity of COMT can directly or indirectly affect the production of lignin, coumarin, flavonoids, organic acids and other metabolites ( Saluja et al., 2021 ). Therefore, COMT may play a key role in promoting the growth and development of plant and its adaptation to the environment, as well as in the synthesis of ferulic acid. NAC and MYB transcription factors (TFs) are the two most important classes of TFs that regulate lignin ( Ohtani and Demura, 2019 ). NAC TFs PtrVND6 and PtrSND1 regulate lignin synthesis involved in poplar growth and development ( Lin et al., 2017 ). Downstream of NAC TFs, MYB TFs such as AtMYB46 and AtMYB83 are involved in lignin synthesis by regulating the expression of some structural genes in the lignin synthesis pathway ( Ohtani and Demura, 2019 ). Thus, it is crucial to explore the involvement of environmental factors in lignin synthesis through NAC and MYB TF. Poplar ( Populu s spp), which is an important forest resource, is served as a model material to study the basic biological characters of trees except for shelter forest, road greening and papermaking ( Taylor, 2002 ). With the intensification of human activities, the occurrence of extreme weather is increasingly frequent. Therefore, it is of great significance for the utilization of bioenergy to understand the molecular mechanism of lignin response to extreme weather such as high temperature and explore candidate genes related to lignin synthesis and metabolism in response to high temperature stress in poplar.",
"discussion": "Discussion The lignin content increased under high temperature stress High temperature stress is one of the major environmental factors that affect plant distribution and development and limit plant resource utilization ( Zhu, 2016 ). Because of a series of advantages such as small genome, rapid growth and high economic value, poplar is a model for studying forest plants and also suitable for transcriptome study ( Taylor, 2002 ). In this study, poplar tissue culture plantlets “84K” was used as the research material, and treated at 35°C for 6, 12, 24, 48, and 72 h, it was found that the lignin content in the stem of poplar tissue culture seedlings increased significantly after high temperature treatment ( Figure 1 ). Lignin, a class of phenylpropane polymers, is essential for plant growth and development and in response to biotic and abiotic stress stimuli ( Cesarino, 2019 ). Once the stem of a plant is exposed to high temperatures, the cell walls rapidly lignify ( Crivellaro and Büntgen, 2020 ). Lignin accumulates and is deposited in the cell wall, strengthening the stiffness of the cell wall, making the xylem cell wall less permeable to water and which facilitates the long-distance transport of water, minerals and organic matter in plants ( Zhao, 2016 ). When plants are subjected to high temperature stress, they will enhance their resistance to stress by synthesizing more lignin. The caffeate and coniferaldehyde may be the key factor for the increase of lignin content of poplar stem responding to high temperature Lignin synthesis involves the production of many intermediate metabolites ( Boerjan et al., 2003 ; Pu et al., 2009 ; Barros et al., 2015 ). It was found that intermediates and their secondary metabolites produced by phenylpropanoid metabolic pathway not only improved disease resistance but also regulated and promoted plant resistance to abiotic adversities such as low temperature, high temperature, and UV radiation ( Dixon and Paiva, 1995 ). Under abiotic stresses such as ozone and drought, the content of phenylpropanoid metabolic secondary organisms including gallic acid, caffeic acid, and coumaric acid increased ( Dixon and Paiva, 1995 ; Sgarbi et al., 2003 ; Xu et al., 2022 ). Similarly, our study found that high temperature promoted the accumulation of caffeic acid. Caffeic acid is a key intermediate in the lignin metabolic pathway and is ubiquitous in the plant kingdom ( Deng and Lu, 2017 ; Reuter et al., 2020 ). In addition, mechanical injury, ethylene and methyl jasmonate treatment caused changes of caffeic acid ( Reuter et al., 2020 ). The increase of caffeic acid content caused an increase of lignin content ( Bubna et al., 2011 ). Therefore, it is possible that the elevation of caffeic acid stressed by high temperature is the cause of lignin elevation. In addition to the elevated caffeic acid content, the coniferaldehyde content also increased after high temperature treatment. Coniferaldehyde is a key intermediate metabolite in lignin synthesis and sometimes functions as a lignin monomer to influence lignin synthesis ( Lapierre et al., 2004 ; Anderson et al., 2015 ). Coniferaldehyde also modulates the lignin metabolic pathway by altering the content and composition of lignin, including through the conversion to ferulic acid and its derivatives ( Van Acker et al., 2017 ). Coniferaldehyde content of lignin and other components filled in the cell wall can effectively inhibit the degradation of the maize cell wall ( Grabber et al., 1998 ). In addition, physical, biochemical and mechanical properties of lignin altered because of the amount of coniferaldehyde residues ( Fornalé et al., 2012 ; Van Acker et al., 2013 ; Wang et al., 2018 ; Blaschek et al., 2020 ). In a word, the synthesis of these substances may be an important reason for the elevated lignin content caused by high temperature. The possible genes involved in lignin synthesis of poplar stem responding to high temperature stress The synthesis of caffeic acid is regulated by several genes. P-coumarate to caffeate reactions are mainly catalyzed by C3'H ( Mottiar et al., 2016 ). C3'H belongs to cytochrome P450 class. Schoch et al. cloned and isolated the C3'H gene from cytochrome P450 of Arabidopsis genome ( Schoch et al., 2001 ). Numerous studies have shown that C3'H is the rate-limiting enzyme of phenylpropanoid pathway in the lignin biosynthetic pathway, which can catalyze the C3 hydroxylation reaction on the benzene ring of the phenylpropanoid structure and can determine the carbon source flow of lignin monomers. Down-regulation of C3'H expression can both reduce lignin content and change monomer composition, which can reduce the cost of plant papermaking ( Abdulrazzak et al., 2006 ). In hybrid poplar ( Populus grandidentataalba ), lignin monomer composition and lignin content were significantly reduced in C3'H RNAi strains ( Coleman et al., 2008 ). Among the two C3'H genes subjected to high temperature-stimulated expression changes in this study, PtrC3'H1 (Potri.006G033300) had a very high similarity with C3'H (GenBank accession no. EU391631) and its transcript levels were significantly elevated by high temperature stress. This suggested that PtrC3'H1 (Potri.006G033300) may be involved in caffeic acid production and thus affect lignin content after high temperature induction. There are two directions regarding the destination of caffeic acid, one is the synthesis of ferulic acid in the presence of COMT (caffeic acid O-methyltransferase); the other is the generation of caffeoyl-CoA in the presence of 4CL (4-coumarate: CoA ligase) ( Mottiar et al., 2016 ). In hybrid poplar ( Populus trichocarpa and Populus deltoides ), overexpression of Pto4CL gene was effective in increasing lignin content ( Allina et al., 1998 ). The Pt4CL1 gene was specifically expressed in organs with high lignin content such as xylem and was involved in the lignin synthesis process in aspen ( Hu et al., 1998 ; Naik et al., 2018 ). Among the 16 high temperature-induced 4CLs , the transcript expression levels of two genes, (Potri.004G102000) and (Potri.017G112800), were consistently reduced by high temperature stimulation, suggesting that the reduction in their transcript levels may have influenced the elevation of caffeic acid. In this study, it was found that only one PtrCOMT (Potri.006G120000) altered with high temperature treatment and its transcript level was reduced only at 6 h. This may also be one of the reasons for the elevated caffeic acid content. Coniferaldehyde synthesis is influenced by several genes. Among them, CCR and COMT have the ability to promote the production of coniferaldehyde, while F5H and CAD make coniferaldehyde to produce other substances. It was found that 32 CCRs , 1 COMT , 3 F5Hs and 42 CADs were induced by high temperature in this study. Among them, PtrCOMT (Potri.006G120000), whose expression was reduced by high temperature induction, was not responsible for the elevation of coniferaldehyde. Lignin contents in down-regulated transgenic strains of CCR1 gene were significantly lower compared to wild type ( Van Acker et al., 2014 ). 12 of 32 CCRs induced by high temperature significantly elevated genes may be involved in high temperature-induced coniferaldehyde and lignin synthesis. PtrCCR2 (Potri.003G181400) was related with lignin content ( De Meester et al., 2020 ). With our results, PtrCCR2 (Potri.003G181400) exhibited evidently high expression after heat induction. Besides, two genes (Potri.005G117500, Potri.007G016400) were up-regulated by high temperature induction in three F5Hs , indicating that they are not factors in coniferaldehyde elevation. However, there was no significant reduction in PtrCADs transcription levels among the numerous heat-induced PtrCADs , suggesting that PtrCADs may be not responsible for the elevation of coniferaldehyde. Analysis of TFs that may affect lignin synthesis in response to high temperatures Lignin synthesis is also regulated by TFs. The NAC MYB-based gene regulatory network (NAC-MYB-GRN) is widely considered to be the main pathway regulating lignin synthesis ( Ohtani and Demura, 2019 ). NAC is the primary network controlling lignin synthesis ( Ohtani and Demura, 2019 ). The secondary regulatory network are some MYB TFs such as AtMYB46 and AtMYB83 which are the downstream of NAC TFs ( Ohtani and Demura, 2019 ). NAC and MYB affect lignin synthesis by regulating the transcription levels of some structural genes that are critical in the process of lignin synthesis. NAC TFs, especially VND6 and SND1, are thought to be the master regulators of SCWs ( Zhong et al., 2007 ; Lin et al., 2017 ). In poplar, PtrVND6 and PtrSND1 can participate in the synthesis of lignin as well as cellulose, hemicelluloses by affecting the differentiation of secondary cell walls (SCWs) ( Lin et al., 2017 ). Overexpression of VND6 and SND1 caused impaired lignin content and unhealthy plant development ( Lin et al., 2017 ). However, among the nine NACs identified that were induced by high temperature in this study, the changes were not obvious, and none of them were reported to be involved in lignin synthesis or SCWs formation. Some MYB TFs acted as the downstream of NAC TFs and are involved in lignin synthesis by directly binding to the promoters of lignin structural genes ( Behr et al., 2019 ). PtrMYB021 and PtrMYB074 regulated the growth and development of poplar by participating in lignin production ( Chen et al., 2019 ). In addition, several other MYB TFs were found to be involved in the lignin metabolic pathway ( Chen et al., 2019 ). By analyzing 558 MYB TFs induced by high temperature, it was found that the transcript levels of PtrMYB021 and PtrMYB074 were significantly elevated by high temperature induction. MYB46 and MYB83 were considered to be a secondary master switch of SND1 involved in lignin synthesis ( Zhong et al., 2007 ; Ko et al., 2014 ). PtrMYB103/46 (Potri.003G132000), a homolog of AtMYB46, was also induced by high temperature although weakly. Some other MYB TFs such as PtrMYB002, PtrMYB003, PtrMYB020, PtrMYB161, PtrMYB90, PtrMYB152, PtrMYB189, etc. have also been reported to be involved in lignin synthesis ( Ko et al., 2014 ; Chen et al., 2019 ). Transcriptome data showed that PtrMYB090 (Potri.015G033600), PtrMYB161 (Potri.007G134500), PtrMYB3 (Potri.001G267300), PtrMYB125/85 (Potri.003G114100), PtrMYB093 (Potri.004G138000) transcript expression levels were elevated by high temperature induction. These PtrMYBs may play an important role in lignin accumulation of poplar stem in response to high temperature."
} | 5,480 |
32937884 | PMC7565417 | pmc | 5,297 | {
"abstract": "Mechanisms used by plants to respond to water limitation have been extensively studied. However, even though the inoculation of beneficial microbes has been shown to improve plant performance under drought stress, the inherent role of soil microbes on plant response has been less considered. In the present work, we assessed the importance of the soil microbiome for the growth of barley plants under drought stress. Plant growth was not significantly affected by the disturbance of the soil microbiome under regular watering. However, after drought stress, we observed a significant reduction in plant biomass, particularly of the root system. Plants grown in the soil with disturbed microbiome were significantly more affected by drought and did not recover two weeks after re-watering. These effects were accompanied by changes in the composition of endophytic fungal and bacterial communities. Under natural conditions, soil-derived plant endophytes were major colonizers of plant roots, such as Glycomyces and Fusarium, whereas, for plants grown in the soil with disturbed microbiome seed-born bacterial endophytes, e.g., Pantoea, Erwinia, and unclassified Pseudomonaceae and fungal genera normally associated with pathogenesis, such as Gibberella and Gaeumannomyces were observed. Therefore, the role of the composition of the indigenous soil microbiota should be considered in future approaches to develop management strategies to make plants more resistant towards abiotic stress, such as drought.",
"conclusion": "5. Conclusion Soil holds an extremely high diversity of microorganisms, taxonomic and functional, which might be essential for the plants to cope with a continuously changing environment (flooding, drought, different types of pathogens, heat, etc.). In the present study, we have demonstrated the relevance of soil microorganisms for the response of plants to drought stress. Moreover, we identified many microbial groups with potential beneficial effects for the growth of barley plants when submitted to stress. Knowledge on the mechanisms by which soil microbes interfere with the response of plants to abiotic stressors is essential and should be implemented in future studies. This could benefit future breeding approaches, for example, by the selection of plants with higher phenotypic plasticity due to the interaction with the soil microbiome.",
"introduction": "1. Introduction Due to their sessile lifestyle, plants are directly exposed to changing environmental conditions, which could have a strong impact on their survival. In agricultural systems, this could lead to losses in productivity, representing a major constraint for food security. In fact, the increase of extreme weather events, including drought, heat, and flooding, is already affecting food production on a global scale. For cereal crops, yield reductions of 9 to 10% have been documented in the last decades [ 1 ]. Water limitation affects seed germination, establishment of seedlings and subsequent vegetative growth. The influence on later plant performance and yield depends both on the exact time point of the drought during plant development and the duration. Drought stress can lead to poor germination rates due to reduced water uptake during the imbibition phase, reduced energy supply, and impaired enzyme activity [ 2 ]. Furthermore, water stress might interfere with the vegetative growth, nutrient acquisition, photosynthesis rates and assimilate partitioning of growing plants [ 3 ]. Plants developed different strategies to handle drought stress during evolution [ 2 ]. To avoid dehydration, plants can reduce water losses via transpiration and increase water uptake by the roots. Stomatal closure is one of the first responses of plants to drought [ 4 ], which leads to a decline of leaf internal CO 2 and, hence, photosynthesis [ 5 ]. On the other hand, plants with better ability to extract water from the soil are more resistant to drought. This is achieved via changes in root morphology [ 6 ]. In addition, tolerance to drought stress can be also accomplished by physiological adaptations. For example, plants can regulate their turgor pressure under drought stress by increasing the concentration of compatible solutes, such as sugars, sugar alcohols, proline, and glycinebetain [ 7 ]. Besides, the enhanced production of antioxidative enzymes is also a crucial response to drought stress, as under limited water availability reactive oxygen species are produced, which can affect cell metabolism [ 8 ]. Even though microbes have been shown to improve plant performance under drought stress [ 9 ], bacteria, fungi, and archaea have been scarcely considered in theories about mechanisms by which plants respond or even adapt to water limitation. Inoculation of plant seeds with probiotic microbiota has increased germination rates, changed plant root architecture, improved reactive oxygen species (ROS)response, and raised the concentration of proteins and sugars as well as enhanced proline contents in leaves [ 10 , 11 , 12 ]. Moreover, as shown by Castillo et al. [ 13 ] the inoculation of seedlings with selected bacterial strains modifies plant hormone balance, for example, by increasing the salicylic acid concentrations in shoots. In addition, the improved performance of pea plants under drought stress due to the inoculation with a Pseudomonas sp. strain producing 1-aminocyclopropane-1-carboxylic acid (ACC)-deaminase was explained by a reduction of ethylene levels in the plant tissue [ 14 ]. The inoculation of plants with microbes may induce several changes in the plant phenotype. For example, Pandey et al. [ 15 ] demonstrated the role of Trichoderma harzianum on the mitigation of drought stress in rice plants due to the upregulation of aquaporin, dehydrin and malonialdehyde. Yet most studies, showing the importance of microorganisms for improved stress responses of plants, are based on inoculation experiments using single bacterial or fungal strains and do not take into account the role of the soil microbiome in the mitigation of drought stress in plants. A study of Lau and Lennon [ 16 ] gave first evidence for the important role of the soil microbiome for the fast adaptation of plants to drought. The authors demonstrated that plants grown in soils, which harbor microbial communities pre-conditioned to drought, performed better when facing drought than those grown in soils with a non-adapted microbiome. Likewise, it was shown recently that plant–soil feedbacks can be affected by legacy effects of drought on soil microbes [ 17 ]. However, the inherent role of the soil microbiome on the response of plants to drought stress still needs to be addressed. Therefore, in the present study, we carried out a pot experiment where the fitness of barley plants under optimal growth conditions and drought stress was compared when plants were grown in an arable soil in its natural status or with a disturbed microbiome as a result of repeated autoclaving. We investigated plant responses directly after a drought setting and after a regeneration period under normal water conditions. We linked plant responses to the diversity of root endophytes, which are considered as an important group of microbes driving plant stress response [ 18 ]. In the respective treatments, we assessed how the composition of root endophytes was affected by drought in both soils using a molecular barcoding approach for bacteria and fungi. We postulated that plants have a comparable performance in both soils under optimal growth conditions. However, once subjected to drought stress, plants grown in soil with natural microbial communities will perform better compared to plants grown in soil with a disturbed microbiome, which indicates the importance of soil born microbes as part of the endophytic microbiome.",
"discussion": "4. Discussion 4.1. Drought Stress Differently Affect Plant Growth in Soils with Natural and Disturbed Microbiome As expected, plants submitted to drought stress exhibited visible signs of water deficit, including lower dry mass, particularly for the roots. However, dry mass values were higher for plants grown in NSM compared to DSM. This might be linked to root microbiome composition, as the overall composition of both bacterial and fungal communities was clearly influenced by soil status. Differences in β-diversity were expected, as the soil microbiota is considered the major driver of root associated microbial communities [ 36 , 37 ]. Hence, it is expected that differences in the composition of the soil microbiome will be reflected in the root microbiome. However, we did not observe effects of soil pretreatment and diversity of root endophytes. This was unexpected, as we observed a clear reduction of the microbial biomass, as assessed by DAPI staining. Although we were aware that soil sterilization process is not 100% efficient, as also discussed elsewhere [ 38 ], it is well known that soil microbial communities are strongly disturbed during this process [ 39 , 40 ]. However, barley seeds possess a very diverse microbiome [ 22 , 41 , 42 ]. Therefore, even though the soil microbiome was affected, seed-borne endophytes might have occupied the free niche in root tissue and, hence, no significant differences were observed when α-diversity was considered. After 11 days of water limitation, we detected high POX activity levels for plants grown in both soils. Increases in activity of ROS scavenging enzymes as a response to drought stress in cereals have been extensively documented [ 43 , 44 ]. POX levels remained high in plants grown in DSM two weeks after re-watering, whereas a trend to lower POX activity for plants grown in NSM was observed. This would suggest reduced ROS stress as a possible mechanism for better response in NSM. We assume that soil microbes helped the plants to cope with the stress, by modifying its physiological response. For example, it was shown that the fungus Piriformospora indica can modulate metabolic response of barley plants to water deficit, mainly by inducing changes in the abundance of proteins which are involved in the plant’s primary metabolism, in particular, acting to mitigate the damage caused by oxidative stress [ 45 ]. 4.2. The Diversity of the Root-Associated Microbiome Did Not Change Directly After Drought Stress Drought did not significantly affect the diversity and richness of bacterial and fungal endophytes, though plants showed clear signs of water stress. Yet the richness and diversity of soil microbial communities can be strongly affected by drought, as shown by de Vries et al. [ 46 ]. This probably reflects the differences in the habitats, as microorganisms living inside or tightly associated with plants benefit from mechanisms used by the host to respond to water deficit, whereas those in living in the soil are more directly affected by the stress. Therefore, microbial communities might change more rapidly in the soil than inside the plant. 4.3. Enrichment of Soil Microbes in the Roots of Drought Stressed Plants We predicted a higher relative abundance of Actinobacteria in the roots of drought-affected plants, as shown in different studies assessing the effects of drought on the composition of bacterial communities associated with the roots of grasses [ 47 , 48 ]. In our study, we did evaluate changes in relative abundance and, hence, cannot discard the possibility that the absolute numbers of total Actinobacteria increases, even though those are not reflected in relative abundances. Nevertheless, we detected a significant increase in the abundance many Actinomycetes taxa in the roots of drought-stressed plants grown in NSM soil. Moreover, many OTUs assigned to Actinobacteria were identified as indicators of drought stress for NSM but not for DSM the disturbed soil. As shown by Yang et al. (2017), Actinobacteria that colonize the roots of different barley cultivars are mostly derived from the soil and are not a major part of the seed-derived microbiome. This was likewise the case for Deltaproteobacteria and Bacteroidetes, for which we also detected higher abundances in plants grown in natural soils but not for those grown in the soils with disturbed microbiome. Whether the bacteria enriched in drought-stressed plants do positively affect their hosts or just benefit from free niches usually occupied by other organisms when plants are not water limited, still needs to be investigated. Furthermore, many taxa from the phylum Saccharibacteria (former candidate division TM7) were identified as biomarkers for NSM soils. This result was intriguing, as Saccharibacteria were described as ultra-small parasitic bacteria that live in tight association with Actinobacteria [ 49 , 50 ] and was also reported to be enriched in drought-affected maize plants [ 51 ]. Besides, Saccharibacteria were shown to degrade salicylic acid [ 50 ], a phytohormone involved in the regulation of drought stress response [ 52 ], which also modulates the root microbiome assembly [ 53 ]. Soil fungi are in general considered to be more resistant to drought than bacteria, at least in short term periods such as in the present study [ 46 ]. In fact, our data indicates that endophytic fungal communities were less affected directly after drought. Only one Fusarium and an unclassified Hypocreales fam incertae sedis were identified as characteristic biomarker for the plants grown in NSM and DSM soils and submitted to drought stress, respectively. It is hard to make any conclusion at this taxonomic level, particularly in the case of barley, for which functional traits rather phylogenetic affiliation seems to be determinant for colonization [ 54 ]. 4.4. Seed-Borne Organisms Were the Major Drought Responders in Soils with Disturbed Microbiome Many bacterial OTUs shown to be differentially abundant in the roots of plants submitted to drought stress were assigned to genera, frequently detected in barley seeds, namely Pantoea, Erwinia, and Pseudomonas (Rahman et al., 2018; Yang et al., 2017). This holds particularly true for plants grown in the soil with disturbed microbiome, reinforcing the idea that under these conditions a higher proportion of the root microbiome is originated from the seed-borne microbiome. Many of these bacterial strains from these genera were shown to improve the response of plants to stress. This is the case for seed-borne Pantoea strains that primed barley immune response to the pathogen Blumeria graminis (Rahman et al., 2018) and promoted considerable growth of wheat seedlings under saline stress [ 55 ]. Besides, Pantoea strains might also improve plant fitness under drought stress [ 56 ]. For the fungal communities, we observed an increase in the abundance of genera normally associated with pathogenesis in barley plants, such as Gibberella and Gaeumannomyces. This result was intriguing as there were no signs of pathogenesis throughout the experiment. Even though we cannot discard that these were truly fungal pathogens, which colonized the host without causing symptoms, it is also possible that they are seed-borne endophytes. Geisen et al. (2017) have shown that most seed endophytes mostly resembled pathogens. Interestingly, in this study, they observed no overlap between the root and seed endophytes, mainly when plants were grown in non-sterile soil. Anyhow, differentiation between pathogenic and non-pathogenic strains from the same fungal species is difficult and relies on other markers than ITS sequences (Lievens et al., 2008), used in the present study. Furthermore, according to Redman [ 57 ] the host physiology is likely to control the lifestyle of the colonizing fungus. 4.5. Changes in the Composition of Root-Associated Endophytes from Drought Alleviated Plants There is evidence for a different allocation of plant carbon to soil fungi and bacteria during drought and at the recovery phase [ 58 ], which could have influenced the recruiting of soil microorganisms. According to Fuchslueger, drought might weaken the link between plant and bacterial, but not fungal, carbon turnover, and facilitate the growth of potentially slow-growing, drought-adapted soil microbes, such as Gram-positive bacteria. This corroborates our findings, in which many taxa of the phylum Firmicutes were identified as biomarkers for the drought settings in both NSM (Clostridium) and DSM soils (Brevibacillus). Moreover, we detected a general increase in diversity for fungi, particularly in DSM soil. Interestingly, we only identified fungal biomarkers for DSM soils, namely Curvularia and Coniochaeta. The first was described to form symbiotic associations with Dichanthelium lanuginosum, thereby increasing plant host tolerance to high soil temperatures [ 59 ]. High abundances of Curvularia were also observed in grassland soils under to water deficit [ 60 ]. Coniochaeta sp. were classified according to their origin, namely as soil, dung or wood originated, with a few cosmopolite species. Among the soil forms, several are common in post-fire soils [ 61 ]. These fungal taxa could better survive the harsh treatment to which the DSM soil was submitted. Effects of Curvularia and Coniochaeta on the barley plant performance under drought stress should be addressed in future experiments."
} | 4,315 |
22050007 | null | s2 | 5,298 | {
"abstract": "We demonstrate the assembly of extremely robust and pH-responsive thin shell LbL microcapsules from silk fibroin counterparts modified with poly(lysine) and poly(glutamic) acid, which are based on biocompatible silk ionomer materials in contrast with usually exploited synthetic polyelectrolytes. The microcapsules are extremely stable in an unusually wide pH range from 1.5 to 12.0 and show a remarkable degree of reversible swelling/deswelling response in dimensions, as exposed to extreme acidic and basic conditions. These changes are accompanied by reversible variations in shell permeability that can be utilized for pH-controlled loading and unloading of large macromolecules. Finally, we confirmed that these shells can be utilized to encapsulate yeast cells with a viability rate much higher than that for traditional synthetic polyelectrolytes."
} | 213 |
27547485 | null | s2 | 5,299 | {
"abstract": "Stretchable electronics enables lots of novel applications ranging from wearable electronics, curvilinear electronics to bio-integrated therapeutic devices that are not possible through conventional electronics that is rigid and flat in nature. One effective strategy to realize stretchable electronics exploits the design of inorganic semiconductor material in a stretchable format on an elastomeric substrate. In this review, we summarize the advances in mechanics and thermal management of stretchable electronics based on inorganic semiconductor materials. The mechanics and thermal models are very helpful in understanding the underlying physics associated with these systems, and they also provide design guidelines for the development of stretchable inorganic electronics."
} | 194 |
26812942 | PMC4728488 | pmc | 5,300 | {
"abstract": "Smart water-collecting functions are naturally endowed on biological surfaces with unique wettable microstructures, e.g., beetle back with “alternate hydrophobic, hydrophilic micro-regions”, and spider silk with wet-rebuilt “spindle-knot, joint” structures. Enlightened by the creature features, design of bio-inspired surfaces becomes the active issue in need of human beings for fresh water resource. Recently, as observed from spider web in nature, the net of spider silk is usually set in different situations and slopes in air, thus spider silks can be placed in all kinds of orientations as capturing water. Here, we show the styles and orientations of hump-on-string to control the ability of water collection as bioinspired silks are fabricated successfully. As different strings, sizes (height, length, pitch) of humps can become the controlling on volumes of extreme water drops. It is related to the different solid/liquid contact regions resulting in the as-modulated wet adhesion due to orientations of humps-on-strings. The conversion of high-low adhesion can be achieved to rely on orientations for the effect of capturing water drops. These studies offer an insight into enhancement of water collection efficiency and are helpful to design smart materials for controlled water drop capture and release via conversions of high-low adhesion."
} | 338 |
22154858 | null | s2 | 5,301 | {
"abstract": "Biosynthetic strategies for the production of recombinant elastin-like protein (ELP) triblock copolymers have resulted in elastomeric protein hydrogels, formed through rapid physical crosslinking upon warming of concentrated solutions. However, the strength of physically crosslinked networks can be limited, and options for non-toxic chemical crosslinking of these networks are not optimal. In this report, we modify two recombinant elastin-like proteins with aldehyde and hydrazide functionalities. When combined, these modified recombinant proteins self-crosslink through hydrazone bonding without requiring initiators or producing by-products. Crosslinked materials are evaluated for water content and swelling upon hydration, and subject to tensile and compressive mechanical tests. Hydrazone crosslinking is a viable method for increasing the mechanical strength of elastin-like protein polymers, in a manner that is likely to lend itself to the biocompatible in situ formation of chemically and physically crosslinked ELP hydrogels."
} | 259 |
36563147 | PMC9788767 | pmc | 5,303 | {
"abstract": "Improving the precision and function of encapsulating three-dimensional (3D) DNA nanostructures via curved geometries could have transformative impacts on areas such as molecular transport, drug delivery, and nanofabrication. However, the addition of non-rasterized curvature escalates design complexity without algorithmic regularity, and these challenges have limited the ad hoc development and usage of previously unknown shapes. In this work, we develop and automate the application of a set of previously unknown design principles that now includes a multilayer design for closed and curved DNA nanostructures to resolve past obstacles in shape selection, yield, mechanical rigidity, and accessibility. We design, analyze, and experimentally demonstrate a set of diverse 3D curved nanoarchitectures, showing planar asymmetry and examining partial multilayer designs. Our automated design tool implements a combined algorithmic and numerical approximation strategy for scaffold routing and crossover placement, which may enable wider applications of general DNA nanostructure design for nonregular or oblique shapes.",
"introduction": "INTRODUCTION DNA origami ( 1 ) is an enticing technique for nanoscale design because of its simple and consistent design principles ( 2 – 7 ), from which it can produce self-assembling ( 8 – 14 ), spatially organized nanomaterials ( 15 – 17 ) to study nanoscale phenomena ( 18 – 31 ). The catalog of DNA origami shapes and their respective underlying design strategies has become increasingly varied by exploitation of algorithmic principles and optimization of synthesis conditions ( 32 – 36 ). Many three-dimensional (3D) DNA origami shapes can also be designed in such a way as to serve as a separating barrier between encapsulated internal moieties and an external environment. Emerging applications using encapsulating 3D DNA nanostructures have affected areas such as nanoparticle synthesis ( 37 , 38 ), low-volume reactors ( 39 , 40 ), templated assembly ( 41 – 43 ), molecular transport ( 44 – 48 ), or drug delivery ( 49 – 53 ). These applications often demand rigid, hollowed structures or, in other words, capsule-like functionality. Thus far, DNA nanostructures tailored toward interdisciplinary applications remain constrained to a relatively limited variety of forms; most are still based on designs arising from strategies that are founded upon a traditional strategy where helices are straight and parallel to a common vector ( 2 ). Earlier work proposed a contrasting strategy based on curved DNA helices, which were better suited for developing a wide variety of capsule-like structures ( 3 , 4 ). Curvature can provide a finer-grained discretization of addressable locations and geometries ( 31 , 38 , 42 ) and create enclosed shapes with larger compartments more economically than block-based designs ( 39 , 52 ). Curved motifs also align more closely with naturally occurring or globular molecules ( 43 ) while still maintaining an enclosed space that is suitable for consolidating molecular activity. However, while the benefits of novel DNA nanostructures that are stable, curved, and fully enclosed and that achieve practical yields are evident, the high complexity of designing these structures has hindered its accessibility to researchers. Furthermore, current design principles for enclosed, curved DNA nanostructures have mostly been demonstrated for single-layer nanostructures, which limit the achievable rigidity and applications. This work expands the design space of enclosed, curved DNA nanostructures and introduces the DNAxiS [Computer-aided design (CAD)] for DNA nanostructures with axial symmetry) software tool to automate the corresponding escalation in design tedium. We introduce -previously unknown, multilayer design strategies ( 33 – 36 ) specifically for curved DNA nanostructures under the term reinforcement, which leads to increasing the overall yield and stability by only targeted application of multilayer design principles to segments in the structure. DNAxiS is the first CAD software tool implementing probabilistic algorithms to perform crossover selection and the first for the design of capsule-like curved DNA nanostructures, with a specific focus on those with axial symmetry (DNAxiS is standalone, open-source software with more information and an online version available at http://caddna.cs.duke.edu ).",
"discussion": "DISCUSSION DNAxiS is uniquely the first software tool to apply automated routing techniques based on heuristic optimization algorithms. As DNA nanostructures increase in scale, with less regularity and more independently designed components, designs may move into a space that becomes intractable for human designers while also lacking sufficient algorithmic regularity. Our work presents an approach for novel DNA origami designs as oblique, freeform structures, which may enable the design of novel geometries, thus enabling wider accessibility to the field for the larger scientific community. We demonstrated how this strategy can succeed for curved DNA origami designs, forming enclosed shapes that do not have any apparent algorithmic regularity to exploit. We described the design complexity that arises from structures that have nonhomogeneous helical twist, notably of which is skewing the periodicity of crossover positions to a point where it becomes tedious for a human designer to arrange a stable crossover network. Having to repeat this for each unique crossover pattern between adjacent helices can quickly become overwhelming for a human designer and can become a barrier for applying DNA nanotechnologies across interdisciplinary applications. This work introduced design principles that include multilayer design of curved and enclosed shapes and characterized the effect of reinforcement on the yield and shape accuracy of structures. Furthermore, the benefits of automation and software modeling were demonstrated in axially asymmetric shapes that took advantage of the ability to rapidly edit geometries and calculate crossover networks. These functionalities can continue to be developed for the future to investigate and generalize methods for DNA origami design for optimization and shape complexity (figs. S37 to S39). A potential impact of our work is to motivate wider consideration of the design and manipulation of globular and more biomimetic DNA nanostructure."
} | 1,596 |
21287166 | PMC3076579 | pmc | 5,305 | {
"abstract": "The key precursors for p -hydroxybenzoate production by engineered Pseudomonas putida S12 are phosphoenolpyruvate (PEP) and erythrose-4-phosphate (E4P), for which the pentose phosphate (PP) pathway is an important source. Since PP pathway fluxes are typically low in pseudomonads, E4P and PEP availability is a likely bottleneck for aromatics production which may be alleviated by stimulating PP pathway fluxes via co-feeding of pentoses in addition to glucose or glycerol. As P. putida S12 lacks the natural ability to utilize xylose, the xylose isomerase pathway from E. coli was introduced into the p -hydroxybenzoate producing strain P. putida S12palB2. The initially inefficient xylose utilization was improved by evolutionary selection after which the p -hydroxybenzoate production was evaluated. Even without xylose-co-feeding, p -hydroxybenzoate production was improved in the evolved xylose-utilizing strain, which may indicate an intrinsically elevated PP pathway activity. Xylose co-feeding further improved the p -hydroxybenzoate yield when co-fed with either glucose or glycerol, up to 16.3 Cmol% (0.1 g p -hydroxybenzoate/g substrate). The yield improvements were most pronounced with glycerol, which probably related to the availability of the PEP precursor glyceraldehyde-3-phosphate (GAP). Thus, it was demonstrated that the production of aromatics such as p -hydroxybenzoate can be improved by co-feeding different carbon sources via different and partially artificial pathways. Moreover, this approach opens new perspectives for the efficient production of (fine) chemicals from renewable feedstocks such as lignocellulose that typically has a high content of both glucose and xylose and (crude) glycerol.",
"introduction": "Introduction Pseudomonas putida S12 is a solvent-tolerant bacterium that has been developed as a platform host for the production of a range of substituted aromatic compounds such as phenol, t -cinnamate, p -coumarate, p -hydroxybenzoate, and p -hydroxy-styrene (Nijkamp et al. 2005 ; Nijkamp et al. 2007 ; Verhoef et al. 2007 ; Verhoef et al. 2009 ; Wierckx et al. 2005 ). Its solvent tolerance properties enable P. putida S12 to produce these toxic hydrophobic compounds to high titres without provoking harmful effects (de Bont 1998 ). Furthermore, in situ product extraction can be applied in fermentations by adding a second phase of a water-immiscible solvent, preventing the accumulation of product to concentrations that are inhibitory even to solvent-tolerant microorganisms (Heipieper et al. 2007 ; Verhoef et al. 2009 ). The production of aromatic compounds by engineered P. putida S12 is based on the conversion of endogenously formed tyrosine or phenylalanine. The key precursors of these aromatic amino acids are phosphoenolpyruvate (PEP) and erythrose-4-phosphate (E4P) (Fig. 1 ). PEP is produced in the lower glycolysis from glyceraldehyde-3-phosphate (GAP). GAP is formed from glucose, either via the Entner–Doudoroff pathway or via the pentose phosphate (PP) pathway, whereas E4P is derived exclusively from the PP pathway. In view of the typically low activity of the PP pathway in P. putida (del Castillo et al. 2007 ; Fuhrer et al. 2005 ; Wierckx et al. 2009 ), the availability of E4P and PEP may present a bottleneck for efficient aromatics production. Increasing the availability of E4P and PEP was therefore expected to enhance the production of aromatic compounds by engineered P. putida S12, as previously demonstrated for the pre-aromatic compounds chorismate and shikimate in Escherichia coli (Martinez et al. 2008 ).\n Fig. 1 Schematic representation of the biosynthetic pathways for p -hydroxybenzoate production from glycerol, glucose, and xylose. The scheme shows only the relevant routes. Heterologous genes are indicated in italics and underlined . Xylose isomerase ( xylA ); xylulokinase ( xylB ); phenylalanine/tyrosine ammonia lyase ( pal/tal ). Glucose-6-phosphate ( G6P ); fructose-6-phosphate ( F6P ); fructose-1,6-bisphosphate ( F1,6BP ); triose-3-phosphate ( T3P ); phosphoenolpyruvate ( PEP ); pyruvate ( PYR ); glycerol-3-phosphate ( Gly3P ); ribulose-5-phosphate ( RU5P ); xylulose-5-phosphate ( Xu5P ); ribose-5-phosphate ( R5P ); glyceraldehyde-3-phosphate ( GAP ); sedoheptulose-7-phosphate ( S7P ); erythrose-4-phosphate ( E4P ); 3-deoxy- d -arabino-heptulosonate-7-phosphate ( DAHP ); chorismate ( CHO ); phenylalanine ( PHE ); cinnamate ( CIN ); tyrosine ( TYR ); p -coumarate ( COUM ); 4-hydroxyphenylpyruvate degradation pathway ( HD pathway ); protocatechuate degradation pathway ( PD Pathway ) \n The availability of PEP and E4P may be improved by stimulating PP pathway fluxes through pentose (co-)feeding, as was demonstrated previously in E. coli (Gonzalez et al. 2002 ). Unfortunately, this strategy cannot be applied to P. putida S12 as this strain lacks the natural ability to utilize pentoses. However, in previous work, we successfully introduced xylose utilization, via the xylose isomerase and PP pathway, into wild-type P. putida S12 (Meijnen et al. 2008 ). In the present study, a similar approach was employed to introduce xylose catabolism into P. putida S12palB2. This P. putida S12-derived strain produces p -hydroxybenzoate, which was selected as a model value-added aromatic compound derived from the aromatic amino acid biosynthesis pathway (Verhoef et al. 2010 ). The effect of xylose co-feeding on p -hydroxybenzoate production was assessed using glucose as the primary carbon source, mimicking lignocellulosic hydrolysate that typically contains high levels of both glucose and xylose. Alternatively, glycerol was employed as primary carbon source, being a good source for PEP as well as being a model for raw glycerol waste from biodiesel production.",
"discussion": "Discussion A mixed-substrate feeding strategy was devised to improve aromatics production by engineered P. putida S12. The approach was based on the assumption that the precursors E4P and PEP were limiting factors for aromatic biosynthesis and that their availability could be improved by stimulating the PP pathway fluxes through pentose co-feeding. A p -hydroxybenzoate producing strain, P. putida S12palB2, was selected as an aromatics-producing model system. As this strain does not have the natural ability to utilize pentoses, a xylose isomerase pathway was introduced, and the initially low growth rate on xylose was improved via an evolutionary selection procedure. Surprisingly, tenfold less transfers were required to achieve growth characteristics similar to those of the previously evolved xylose-utilizing strain P. putida S12xylAB2 (Meijnen et al. 2008 ). In part, this can be attributed to the targeted disruption of gcd , since more than ten transfers had been required for strain S12xylAB2 to acquire a gcd negative phenotype. In addition to the xylose utilization efficiency, also the p -hydroxybenzoate yield was improved after the evolutionary selection. This phenomenon may be explained by the increased PP pathway activity associated with the improved xylose utilization phenotype, leading to an intrinsically improved E4P and PEP availability, independently from xylose co-feeding. As anticipated, xylose co-feeding considerably improved the p -hydroxybenzoate yield. The increased product yield was observed with both glucose and glycerol as the primary substrate and was shown not to be caused by xylose consumption per se. Remarkably, both the product and biomass yield on glycerol were consistently higher compared to glucose, either with or without xylose co-feeding. This may be attributed to regulatory effects (e.g., carbon catabolite repression) but could also indicate that PEP availability is more critical for efficient p -hydroxybenzoate production than E4P availability. If it is assumed that pyruvate dikinase (PEP synthase) is active only under gluconeogenic conditions (Sauer and Eikmanns 2005 ), twice the amount of GAP (and, thus, PEP) can be obtained from glycerol compared to glucose, which is metabolized via the Entner–Doudoroff pathway in pseudomonads (del Castillo et al. 2007 ; Fuhrer et al. 2005 ). In addition, the glycerol-associated yield improvement appears to be connected to the evolutionary selection, since no such effect has been observed with the parent strains of P. putida S12pal_xylB7 (Verhoef et al. 2010 ). Presumably, the increased PP pathway activity associated with the efficient xylose-utilizing phenotype may allow for a more efficient equilibration of PEP and E4P levels, resulting in more efficient p -hydroxybenzoate production. It should be noted that the applied proportion of xylose in the feed showed little effect within the range tested, whether the primary substrate was glucose or glycerol. Apparently, the p -hydroxybenzoate production is not very sensitive to variations in relative xylose concentrations above a certain threshold value. Unexpectedly, the capacity to transport and/or utilize xylose appeared to be dependent on the primary carbon source. With glycerol, a low concentration of residual xylose was observed that is presumably close to the K \n m of the—yet unidentified—xylose transporter in P. putida S12pal_xylB7. With glucose as the primary substrate, however, the residual xylose concentrations were higher and furthermore increased more than proportionally with increasing amounts of xylose in the feed. Although this phenomenon is still subject to further study, it may be hypothesized that xylose transport in P. putida S12pal_xylB7 is PEP dependent. This would be consistent with the observed increase in residual xylose concentrations with decreasing glucose feed (an already relatively inefficient source of PEP), the relative independency between residual xylose concentration and glycerol feed (a good source of PEP), and the decreased growth rate on xylose when Pal/Tal was introduced (drain on PEP for p -hydroxybenzoate production). In that case, replacing any PEP-dependent transport systems would be an obvious target for further strain improvement. The GAP/PEP availability may furthermore be improved by constructing an ED-negative, glycolytic P. putida S12 strain. The contribution of the (ATP-driven) E. coli xylose transporter XylFGH to xylose import was presumably limited as observed previously (Meijnen et al. 2008 ). We have demonstrated that p -hydroxybenzoate production in P. putida can be considerably improved by co-feeding different carbon sources that are metabolized via different, (partly artificial) pathways. Thus, the availability of the key aromatics precursors, PEP and E4P, is improved. In addition to p -hydroxybenzoate, the production of other aromatic compounds derived from aromatic amino acids may be stimulated via this strategy. Moreover, lignocellulosic hydrolysate, the expected major feedstock for future production of biobased fuels and chemicals (Himmel and Bayer 2009 ; Kumar et al. 2008 ; Lange 2007 ), seems to be ideally suited for aromatics production since glucose and xylose are the predominant constituents. Also the improved production on glycerol presents an additional possibility to deploy a cheap and abundant waste substrate for biocatalytic production of (fine) chemicals."
} | 2,821 |
36727426 | PMC9933455 | pmc | 5,306 | {
"abstract": "Control over synthetic DNA-based nanodevices can be achieved with a variety of physical and chemical stimuli. Actuation with light, however, is as advantageous as difficult to implement without modifying DNA strands with photo-switchable groups. Herein, we show that DNA nanodevices can be controlled using visible light in photo-switchable aqueous buffer solutions in a reversible and highly programmable fashion. The strategy presented here is non-invasive and allows the remote control with visible light of complex operations of DNA-based nanodevices such as the reversible release/loading of cargo molecules."
} | 153 |
33447799 | PMC7798458 | pmc | 5,307 | {
"abstract": "In May 2019, 29 scientists with expertise in various subdisciplines of biofilm research got together in Leavenworth (WA, USA) at an event designated as the ‘2019 Biofilm Bash’. The goal of this informal two-day meeting was first to identify gaps in our knowledge, and then to come up with ways how the biofilm community can fill these gaps. The meeting was organized around six questions that covered the most important items brought forward by the organizers and participants. The outcome of these discussions is summarized in the present paper. We are aware that these views represent a small subset of our field, and that inevitably we will have inadvertently overlooked important developing research areas and ideas. We are nevertheless hopeful that this report will stimulate discussions and help create new ways of how we can advance our field.",
"conclusion": "Concluding statements It is very difficult to capture everything that was discussed between 29 people during two days of engaged and animated discussions. Nevertheless, we are convinced that the most important issues are covered in the summary above. In addition, during the plenary sessions, several action items were identified. These are often transversal (i.e. cut across the different questions) and are summarized in Box 1 . With the support of the wider biofilm community, we will start addressing those action items in the near future. Progress updates will be presented at the various biofilm conferences and other meetings as well as in writing. Box 1 Action items identified during the plenary discussions. • Techniques used to study the microenvironment of solid tumor cancers and for in situ research of microbial communities in the natural environment have great potential for application to laboratory biofilm experiments, and should be translated to other fields such as industrial, medical or dental biofilms. One way to achieve this would be for biofilm researchers to attend methods intensive conferences outside the biofilm field. The International Society for Microbial Ecology (ISME) conference was cited as an excellent example. • A second path would be to bring in speakers from other fields to future biofilm conferences whom were developing methods in their own fields which may be translatable. • Workshops dedicated to specific techniques which might have biofilm applications could help advance the field. • A better overview of what is available (worldwide) in terms of training opportunities is desirable and it needs to be explored how different initiatives can be connected. • A well-documented study demonstrating that a biofilm specific therapeutic has clinical efficacy, where conventional surgical or antibiotic interventions had failed, would advance the medical biofilm field. If a biofilm approach could be demonstrated in one type of infection, then the doors might open to spark innovation in treating other types of biofilm infections. • In terms of surface modifications, silver alloy in the coating of a urinary catheter has demonstrated a reduction in infections [ 43 ]. However, the mechanism of action, whether it reduced adhesion or influenced biofilm development is un known. More fundamental knowledge on the mode of action of successful surface modifications beyond silver alloys is needed. • The lack of a definitive biofilm biomarker and medical imaging modality for detecting biofilms makes it difficult to assess the impact of anti-biofilm therapeutics. Thus work towards a suite of biofilm markers is needed. • There is need for a position paper on the applicability and limitations of biofilm and host/environmental models. Topics such as the ones listed below could be discussed in this paper: (i) Define constraining parameters in model systems with respect to spatial and temporally relevant scales. This in an engineering approach, where the goal is to define the principal features that we need in a model given that the complexity prohibits all variables. (ii) Development of enhanced tools for accurate evaluation of the applied model. (iii) Application of computer models to aid in evaluation. (iv) Assess the utility of artificial intelligence in biofilm control evaluation. • Wikipedia is often the first source of information (lay) people find, so we need to make sure the ‘Biofilm’ Wikipedia page is current and updated. • To deliver a clear and consistent message about what a biofilm is, a set of slides (1–3 slides) will be developed that can be shared by all interested. • There is an urgent need to bring a clear message to stakeholders about the importance of biofilms. No reliable estimates of the overall burden of biofilm infections have been published since 2010 [ 44 ] and an updated estimate of the human, financial, and social burden of clinical and industrial biofilms is needed. What are the benefits of biofilms in certain systems? What costs are associated with biofilm-related fouling? Different target audiences will need different clear messages. An essential aspect of this is bringing the biofilm concept to the attention of funding organizations. Antimicrobial resistance and microbiome management are now accepted areas of concern and targets for therapeutics but we need to better incorporate the concept of biofilms into these discussions to highlight issues with controlling biofilms. In parallel, the benefits of biofilms should also be estimated and delivered to stakeholders interested in promoting biofilm. • Development of a Biofilm Text Book could help reach a wider audience. The current version hosted by the CBE could be further developed. • We need to ‘push’ the biofilm concept with scientific and professional organizations so it is included in recommended training programs, continued education activities and curricula. • There are several misconceptions in the field, including that biofilms always take the form of mushroom-shaped structures, that the process of biofilm formation follows a fixed developmental cycle, and that all biofilms are surface-attached. These misconceptions need to be corrected and the message delivered to a wide target audience. • We need to discuss to what extent we expect biofilm experiments to be standardized and if so in what aspects of the workflow standardization is most important. Guidelines that reflect this should be developed. ‘Minimum information’ guidelines [ 30 ] can support researchers, reviewers and editors to determine whether the information required to successfully reproduce an experiment is available. In addition, we need to make sure these guidelines are disseminated widely to ensure that they are adopted by all stakeholders. • There was a consensus that there is currently no need for a separate biofilm society. However, if we want to further integrate the field at an international level, we need to explore funding opportunities and talk to funding organizations and program officers. Alt-text: Box 1",
"introduction": "Introduction In October 2005 Bill Costerton invited a small group of established and junior biofilm researchers to a ‘Biofilm Bash’ in Los Angeles (CA, USA) to discuss the rapid advances that had developed in the field over the preceding decade, to think about how new and exciting technologies could be applied to biofilm research and to identify directions that the field might develop in the future. A decade later in 2015 discussions started about having a second ‘Biofilm Bash’ to again take stock of the field and discuss both old and new challenges as well as new opportunities in biofilm research and education; this second ‘Biofilm Bash’ materialized in 2019. From May 7 to 9, 2019, the Ponderosa Lodge in Leavenworth (WA, USA) was the scene of this ‘2019 Biofilm Bash’, organized by the late Mark Shirtliff, Paul Stoodley, Birthe Kjellerup, Tom Coenye and Thomas Bjarnsholt. The main goals were to identify the gaps in our biofilm knowledge, identify ways how we can fill those gaps, and determine how we can increase our impact related to biofilms with various stakeholders. The ‘Biofilm Bash’ was organized as a result of informal discussions between the organizers (and others) at major scientific meetings in the preceding months and years. The underlying thought that brought about the ‘Biofilm Bash’ was that the biofilm community is scattered as a subdiscipline within many other fields. For example, dental plaque, activated sludge, oil field souring, native valve endocarditis, respiratory tract infections in cystic fibrosis, microbial corrosion, indwelling medical device infections, microbial fuel cells, endophthalmitis, osteomyelitis, and prosthetic joint infections are all biofilm-related – i.e. the mechanisms behind them have many commonalities, yet we lack the unity that can be found in other research topics (e.g. cancer). An integral part of the meeting preparation included invitation of participants that would reflect the overall diversity of the biofilm field and at the same time created a balance between more established biofilm researchers and people that are new to the field and/or come in from a different angle. To allow fruitful participation, manageable and productive small group discussions (with max. six people in each group), and because of logistical reasons, the target number of attendees was set at approx. 30. Potential participants were identified in a decentralized way, where Birthe Kjellerup, Darla Goeres, Kendra Rumbaugh, Matthew Parsek, Paul Stoodley, Thomas Bjarnsholt, Tom Coenye, and Trine Rolighed Thomsen (all involved in an informal ‘pre-meeting’ on 9 October 2018, in Washington DC, during the American Society for Microbiology (ASM) Biofilm Conference) were asked to each propose up to six names, and all these people were pre-invited. Ultimately 29 researchers from Portugal, USA, Denmark, Belgium, The Netherlands, UK, and Australia were present ( Table 1 , Fig. 1 ). Table 1 Overview of participants and their affiliation. Table 1 Name Affiliation City, country Nuno Azevedo University of Porto Porto, Portugal Haluk Beyenal Washington State University Pullman, WA, USA Thomas Bjarnsholt Costerton Biofilm Center Copenhagen, Denmark Mette Burmølle University of Copenhagen Copenhagen, Denmark Tom Coenye Ghent University Ghent, Belgium Vaughn Cooper University of Pittsburgh Pittsburgh, PA, USA Matthew Fields Center for Biofilm Engineering Bozeman, MT, USA Darla Goeres Center for Biofilm Engineering Bozeman, MT, USA Luanne Hall-Stoodley The Ohio State University Columbus, OH, USA Birthe V. Kjellerup University of Maryland College Park, MD, USA Michel Koo University of Pennsylvania Philadelphia, PA, USA Kasper Kragh Costerton Biofilm Center Copenhagen, Denmark Bastiaan Krom Academic Centre for Dentistry Amsterdam, The Netherlands Tagbo Niepa University of Pittsburgh Pittsburgh, PA, USA Matthew Parsek University of Washington Seattle, WA, USA Gordon Ramage University of Glasgow Glasgow, UK Courtney Reichhardt University of Washington Seattle, WA, USA Alex Rickard University of Michigan Ann Arbor, MI, USA Katharina Richter University of Adelaide Adelaide, Australia Trine Rolighed Thomsen Aalborg University and Danish Technological Institute Aalborg and Aarhus, Denmark Kendra Rumbaugh Texas Tech University Health Sciences Center Lubbock, TX, USA Karin Sauer Binghamton University Binghamton, NY, USA Pradeep Singh University of Washington Seattle, WA, USA Phil Stewart Center for Biofilm Engineering Bozeman, MT, USA Paul Stoodley The Ohio State University, and National Biofilms Innovation Centre (NBIC), University of Southampton Columbus, OH, USA Jeremy Webb National Biofilms Innovation Centre (NBIC), University of Southampton Southampton, UK Marvin Whiteley Georgia Institute of Technology Atlanta, GA, USA Craig Williams University of West Scotland Paisley, UK Dan Wozniak The Ohio State University Columbus, OH, USA Fig. 1 Selection of pictures taken during the 2019 Biofilm Bash. Top: plenary session inside the Ponderosa Lodge. Middle: Group picture with all participants in front of Beaver Creek Lodge. Bottom left: Dinner on the first night. Bottom right: discussions on the meadow. Fig. 1 To allow maximal input and involvement from all participants, the ‘2019 Biofilm Bash’ was organized as a series of small-group brainstorming sessions during which six questions were addressed. There were no research presentations. These six questions were proposed by the organizing committee but were fine-tuned based on the input from the majority of participants. Each question/topic was discussed by at least four groups of four to six participants. In addition, to maintain the dynamics, groups were re-organized after every session to mix participants. In every group a person was designated as discussion leader; this discussion leader was also responsible for reporting back to the entire group during two plenary sessions. The outcome of these discussions is summarized below. Question 1 What will be the technologies of the future in biofilm research? Which are the developing technologies in this field and what technologies from outside the biofilm field could have a major added value? How can we ensure that methods commonly used in environmental research find their way to clinical research and vice versa? The three main themes that emerged were the need to incorporate techniques which can a) combine microscopic imaging with label free chemical profiling, b) sense the biofilm environment and c) process large and complex data sets (such as omics data) with machine learning and artificial intelligence to reveal patterns in multi-scalar relationships and interactions between the biofilm and its environment. Biofilm imaging. Imaging has been the mainstay of biofilm research and provided the first direct proof of these communities on surfaces in the early 1980s [ 1 , 2 ]. Initially scanning electron microscopy (SEM) was used to provide high resolution images of the surfaces and transmission electron microscopy (TEM) was required to resolve the ultrastructure between the cells and the EPS (extracellular polymeric substance) but these techniques require dehydration and labelling of specific components is difficult. Biofilm imaging was revolutionized in the early 1990’s by confocal microscopy which allowed live cell imaging in 3D in real time [ 3 , 4 ]. However for most purposes labelling is limited to a few compounds and the visualization of individual EPS polymers and other components such as vesicles and determining how they structurally interact among themselves and with the bacterial cells is beyond the limit of resolution of this technology. Super high resolution (beyond the diffraction limit of light) live cell imaging is now becoming increasingly available with resolutions from 100 nm to 20 nm (in the XY plane), which will allow us to probe these interactions [ 5 ]. Another exciting area is that of label free imaging techniques such as Coherent Anti-Stokes Raman Spectroscopy (CARS), which can be coupled with confocal microscopy or matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) and other MS imaging techniques to provide high resolution chemical mapping of a specimen [ 6 ]. Imaging the EPS has been difficult not only due to limitations in microscope resolution but also because there are no universal stains and so only targeted components can be detected. Chemical imaging has great potential to investigate EPS chemistry and can also be used to identify components such as antibiotics or signals within biofilms. There was some discussion on the need for more sophisticated image analysis techniques for quantifying biofilms, which are less subjective than those used today. They largely rely on semi-subjective thresholding and are also limited by the stains and concentrations that the microscope can detect [ 7 ]. Sensors. Monitoring heterogeneity in the biofilm microenvironment can sometimes be achieved with specific stains. However, in many cases, particularly in the presence of dissolved components such as nutrients or metabolites, there are no stains available or the time scale is too slow. In addition, direct microscopic examination might not be feasible outside the lab (i.e. in situ such as in a wound or an industrial pipeline). Currently microelectrodes and planar optodes can be used but these can be fiddly and require direct access and sophisticated equipment thus they are most used in the controlled environment of the laboratory. Nanobots and nanorobotics is an area that is being developed in the field of medicine to send wireless signals to report on the local environment [ 8 ]. It was discussed that such technology would have great application in basic and applied biofilm research. Artificial intelligence (AI)/machine learning (ML). We are currently living in the age of ‘omics’, and although various ‘omics’ approaches are being applied to biofilm communities, relating these large and usually complex data sets to biofilm function still often relies on manually cherry picking a handful of familiar or likely candidate genes or proteins, or using principal component analysis to differentiate between overall patterns. We are still playing catch-up with providing the infrastructure for interpreting such data sets and bioinformaticians are still in high demand. It was predicted that AI/ML will develop in a similar way and offer great potential in recognizing complex patterns in biofilm data sets (see for example reference [ 9 ]), integrating disparate data sets such as 4D imaging data with multidimensional chemical data and ‘omics’ data sets. Others. In addition, many other biofilm related techniques were brought up including mechanical and rheological testing, flow cytometry, cryo-EM and more sophisticated computational modeling software for integrating biofilm processes with fluids interactions. Some techniques such as microfluidic platforms for high throughput experiments and the integration of multi-scalar correlative imaging techniques, i.e. Confocal Raman Microspectroscopy (alone or combined with stable isotopic probing) [ 10 ], live cell imaging, small animal imaging with in vivo imaging systems (IVIS) [ 11 ] and medical imaging techniques such as Micro Computed Tomography (micro-CT) [ 12 ] or Magnetic Resonance Imaging (MRI) [ 13 ] with resolutions ranging from the sub-cellular level to the system level, are clearly promising but were not discussed in detail. In the medical field, medical imaging techniques which could show the location of biofilm pre- or intra-operatively would present a major breakthrough for surgical management as well as allowing the progress of treatments to be tracked as they are for tumor treatments. Currently there are no biofilm specific probes and the spatial resolution of medical imaging modalities is not sufficient. Question 2 What innovative approaches to tackle unwanted biofilms are needed? What can be expected from them? The discussion focused primarily on non-antibiotic or antibiotic adjuvant prevention and treatment strategies . These included targeting the EPS matrix to break up the biofilm either enzymatically or through activating natural dispersion mechanisms [ 14 ], adding ‘potentiators’ such as metabolites or nutrients which may activate persister and stationary cells, rendering them susceptible to antibiotics [ 15 , 16 ], and vaccines against biofilm specific antigens [ 17 ]. Based on developments in tumor cancer medicine, a suggestion was to use immunomodulation therapy to disrupt the pathogenic microenvironment. It was suggested that a solution for prevention was a surface that was inherently repulsive to bacteria, yet was biocompatible in the clinical setting and mechanically functional in engineered systems. However, as bacteria are not always attached to the surface of the implant but maybe present as aggregates close to the surface, this may not be the perfect solution and more studies are needed to address this. There are interesting developments in biomimicry approaches based largely on physical patterning [ 18 ], although these tend to be expensive and there are questions on whether patterning alone can fully explain the biological function. In addition to discussing novel therapies it was recognized that we are still lacking a basic understanding of how antibiotics interact with biofilms . It is well established that cells in biofilms are orders of magnitude less sensitive to antibiotics and antimicrobial agents than rapidly growing planktonic and early solid agar plate cultures. These data are largely based on 24 h exposure times or less. For medical biofilms anecdotal clinical evidence suggests that biofilms can survive long term exposure to systemic antibiotics but in this case the concentration is limited by the threshold of the therapeutic window, beyond which toxicity is a concern. Basic research is needed to define the pharmacokinetics with respect to high concentrations, which might be achieved through local targeted delivery and over longer time scales. Another important factor is to determine how the age of the biofilm influences susceptibility and how translational in vitro tests are to the real world environment. The need for better models was discussed in more depth in Question 3 (see below). Along the same lines, the question was asked with any therapeutic how low is low enough ? It is not clear how many percent or log reductions in biofilm bacteria is enough, or how the absolute magnitude of numbers which might remain, relate to clinical or industrial relevance. Each system will have a specific tolerance and in some cases (such as certain infections) complete eradication is required (according to conventional thinking), whereas in some industrial systems (e.g. ship hull fouling) a limited amount of biofilm may be tolerated as long as it does not cause negative effects (e.g. drag) beyond a critical operational level. Interestingly, there was some discussion of whether the body could tolerate a certain amount of pathogenic biofilm bacteria and if therapeutics might still have utility if they keep the biofilm in check, such as is the case with routine oral hygiene or the use of suppressive antibiotic therapy in patients, where surgery is contraindicated and the infecting bacteria are susceptible to well-tolerated antibiotics. A different approach to control medical biofilms was to use approaches to reduce bacterial adhesion and biofilm build up that are commonly used in the natural environment and in industry. In pipelines for example, dead ends where water stagnates, lags, sudden expansions and contractions, sharp bends and surface protrusions are reduced, since it is known that turbulent eddies associated with these features can trap and promote bacterial attachment to surfaces. Eddies and back current locations might furthermore form protective niches. A similar phenomenon occurs in infective endocarditis, where damage to the heart valve allows bacteria to accumulate and proliferate in biofilm vegetations [ 19 ]. Thus some of these design concepts, along with the use of materials that can be more easily cleaned, might be applied to medical devices and the hospital environment as infection control measures. Probiotic approaches were also discussed. The use of probiotics is now accepted with respect to gut microbiology but increasingly there is discussion among surgeons, at least in orthopedics, that probiotics might be used to prevent or manage deep surgical site infections. A few years ago discussion of introducing bacteria to a deep tissue site would have been unthinkable; now there is discussion of native joint microbiomes [ 20 , 21 ] and the role of a healthy lung microbiome in infectious diseases [ 22 , 23 ], opening up the door to thinking about novel therapeutics. Question 3 How good are our \n experimental \n models? There is no framework for biofilm model evaluation in regard to how well it recapitulates the natural environment it is meant to mimic. How can we approach this question as a field? Models are essential to science and a variety of models are used in biofilm science ranging from simple in vitro models to more complex invertebrate and vertebrate in vivo models [ 24 , 25 ]. The discussion showed that there is a lack of standardization for experimental protocols and data analysis (see also below, Question 5 ). A publicly accessible database hosting currently-used methods with protocols and standards was proposed. This would be followed up by workshops at general and more specific conferences and meetings during, which (starting) biofilm researchers could be trained in these methods. The workshops would utilize material from the database and over time this repository could become interactive. To make it easier to perform comparable experiments with selected models, it was suggested that lists of preferred vendors would also be present in the database. An important part of the discussion was related to “ How do you select an appropriate model? ” It was suggested to develop a Decision Tree for model selection that would include criteria for choice of models as well as parameters that should be discussed during the experimental phase and subsequently for data analyses. This would make it possible to compare and evaluate results from similar models but from different research groups. It was also suggested to develop a list of parameters that should be included in manuscripts and proposals to ensure a more informed and fair evaluation. It was discussed what would be sufficient and what will be necessary if guidelines would be developed and enforced. When is a simple model sufficient to answer the specific research question, when should one move to a more complex model and which types of parameters should be evaluated at each step? It was also discussed how it can be ensured that researchers in more resource limited settings (such as many undergraduate colleges and/or less resource rich countries) could still be included if such guidelines were implemented. An important aspect of model selection is to ask the right question before making a decision about a model. In this consideration, the presence of spatial and physiological heterogeneity needs to be accounted for. The in situ relevance of the biofilm model must also be evaluated prior to selection, for example, prior to using a particular model, it should be evaluated whether the inoculum, the flow regime (if any) and the surfaces/interfaces are matching the environment in the system that is being modelled. The key drivers and parameters in the system and environment must be identified to obtain in situ relevance. Tools should be developed that can be used for evaluation of how the model and results can be transferred to practice and the practitioners (including clinicians and engineers) should be involved in evaluation of the model to ensure in situ relevance. Subsequently validation studies should be performed (e.g. can a toilet bowl as a system be modelled in a Rotating Disk Biofilm Reactor?). The host response is also an important factor for consideration of medical/clinical biofilm models. An alternative to conventional vertebrate models (mouse, rat, rabbit) are zebrafish, and invertebrate models such as Galleria mellonella or Caenorhabditis elegans in cases where only the innate immune response is investigated [ 26 ]. Organ-on-a-chip options are increasingly being applied and benefits from the opportunities of 3D-printing and micro-hydraulic systems [ 27 ]. A discussion point was raised that more knowledge is needed about the environment that is being investigated prior to the selection of a model , since the environment often determines the organization of a biofilm. This will enhance knowledge about complexity while simultaneously dealing with reproducibility and the pragmatic issue of finances for repeated experiments. Also, while bad models do not exist, a particular model can be poorly suited for answering a particular research question and/or the interpretation of the obtained data can be bad. Appropriate quality assurance (QA)/quality control (QC) procedures must be in place as with all experiments and must include the quality of the microbial inoculum as well as the rest of the model system. This will ensure a higher degree of reproducibility. The details of the applied methods must be outlined as a part of the QA/QC. The need to develop relevant models for polymicrobial interactions such as infections as well as environmental systems and many industrial problems was raised. Stable and maybe even self-sustaining model systems are also needed. The complexity of existing in vitro and in vivo models was discussed. Can we -based on existing data-evaluate how good these models are? Better approaches for evaluation of biofilm models must be developed so they accurately recapitulate the in vivo setting. Is it necessary to apply transcriptomic, proteomic and/or phylogenetic techniques to document that the applied model is accurate and can this be utilized in complex environments? Biofilm communities per definition are complex and heterogeneous and we need to ensure that the complexity is modelled appropriately. However, it is currently unclear whether all systems can be modelled. Computer modeling can potentially solve some of the gaps that arise from experimental approaches. Finally, there was interest in identifying a medium, where negative data can be published, since these are often showing the limitations and negative sides of models that are otherwise neglected. Question 4 How can we make other stakeholders (e.g. medical doctors, engineers, other professionals) aware that biofilms are important? What can we do to make sure that the biofilm concept is actually included in curricula and standardized tests? Can something like the biofilm ‘hypertextbook’ developed at the Center for Biofilm Engineering (CBE) play a role in this? What about developing workshops that can ‘travel’ to the different biofilm conferences and be renewed as needed? Increased visibility to ‘biofilm’ as an integrated part of other scientific fields was requested. This can be done by publishing reviews in relevant journals as well as by interacting with the lay press (e.g. informing newspapers and local media about new discoveries and overall information about biofilms). Increased use of social media as a platform should also be considered to reach younger demographics. Informative YouTube videos and TED-style talks by high-profile scientists and other thought leaders could also be a part of ‘marketing’ the biofilm concept. We can increase the visibility of ‘biofilm’ by always including it as a keyword, use social media (Twitter, ResearchGate, LinkedIn etc.) to highlight biofilm-related publications but also by writing position papers to be published in journals that typically do not have a biofilm focus. Publication of case reports involving biofilms will increase the awareness about biofilms in the clinical and industrial fields and can be delivered in a way that will promote appreciation of biofilms when they occur in the these settings. Furthermore, a correction of decades of misconception in the field that a biofilm is a surface-attached mushroom-shaped structure, must take place. This will likely increase the general awareness, since people will be able to associate and identify their findings as a biofilm even though it is not a mushroom-like structure. For the biofilm message to be received, the message must be defined and refined so it will hit the target audience. The American Cancer Society has been very successful in delivering their message (supported by effective fundraising) and it was suggested that this could serve as a model. In this way biofilms can be linked to important societal issues such as antimicrobial resistance, microbial corrosion and chronic infectious diseases, but also to the positive aspects related to for instance wastewater treatment, food production and bioremediation. An important aspect for this part to move forward is to identify existing data on the burden and benefits of biofilms, respectively. It is also imperative to link biofilm to other recognized concepts such as cancer, global warming (including coral bleaching), and food production, and to estimate the financial and human global burden. Primary and secondary education (K-12 in the US) as well as education at the university level are important gateways to increasing the awareness and knowledge about biofilms. More focus on providing information and materials for teachers at all levels will increase the general awareness. This could be done by providing examples of harmful and beneficial biofilms for different levels that educators can include directly in their lesson plans and in the classroom. Experimental biofilm instruction can also be facilitated by examples and protocols that high school and university students can benefit from. Establishment of a database with protocols and vendor information (cfr. Question 3 ) would also be a part of improved outreach to educators. Wikipedia and other links could add to the knowledgebase for middle and high school students. Resources already exist such as ‘Evolving STEM’ ( https://evolvingstem.org/ ) that can be included right away. Continuing education of professionals at major conferences and other venues will also be an important aspect. Several medical organizations offer courses, workshops etc. to obtain CME (Continuing Medical Education) and CE (Continuing Education) credits. The topic of biofilm should become a part of CME/CE and other types of continued education for other organizations. To get biofilm to be a part of CME/CE, increased impact of biofilm must be pushed at the general microbiology meetings that take place at an annual basis such as ASM Microbe, the Federation of European Microbiological Societies (FEMS) Congress of European Microbiology, The Microbiology Society Annual Meeting (UK) and the European Congress of Clinical Microbiology & Infectious Diseases (ECCMID). This could also provide an avenue for making ‘biofilm’ a topic for the Medical Board Exam, Dental Board Exam, and the Fundamentals of Engineering Exam (the Engineering Board exam). The push for inclusion on the Board Exams has a straightforward path in the US. However, in Europe and globally, this must be individually targeted for each country. Question 5 Standardization/databases/data sharing. Should there be a biofilm database in which large datasets relevant to the field are uploaded to prevent the need for each group to scour existing databases. If so, where should it be maintained and who can curate it? Maybe crowdsource? This is an issue for labs that don’t have the expertise to analyze large datasets and for labs that focus on large datasets. Should we standardize our models? When is standardization required? The question about ‘standardization’ is not new (see also Question 3 , above), but remains relevant in the biofilm research field and is frequently the subject of debate. Standardization of methods is often driven by regulatory authorities (e.g. the US Food and Drug Administration [FDA], the US Environmental Protection Agency [EPA], and the European Medicines Agency [EMA]) and industry, and this is also the case in the biofilm field [ [28] , [29] , [30] , [31] , [32] ]. Standard methods allow for comparison across treatments and devices, enable regulatory agencies to make informed decisions, and provide insights into the Type 1 and Type 2 error rates that can be expected, when the treatment or device is tested in a clinical or industrial trial. Standard methods used for applications beyond their intended ‘significance and use’ may provide misleading results, but the error is the result of misuse of the method, not due to the inadequacies of the standardization. Finally, standard methods are living documents that require constant review and updating. As science and technology evolve, so should the standard methods. Standardized methods can also play an important role in increasing our understanding of the basic biology of biofilms, including insights into the mechanisms involved in biofilm tolerance. Comparison of results obtained in absence of some form of standardization is at best difficult [ 33 ]. Standardized methods are important tools for screening of large libraries for potential compounds with anti-biofilm activity [ 32 ]. However, regardless of standardization, in vitro biofilm susceptibility tests will frequently (but not always, [ [34] , [35] , [36] ]) yield results that are poorly representative of the actual activity of the antibiotic against the biofilm in vivo , because of profound difference between different types of biofilms. This is an important point, because it illustrates that even the best in vitro model does not fully mimic the in vivo situation. Progress has been made in developing laboratory biofilm models that are more representative of the situation in a patient (e.g. in the context of chronic wound infections and CF) [ 37 , 38 ] and industrial environments [ 39 ], but studies establishing the validity of these models are still largely lacking. Finally, in some contexts it may be more readily achievable and useful to standardize specific key parts of workflows and procedures, rather than the entire method. For example, it may be difficult to standardize the entire workflow of biofilm formation, antimicrobial treatment and crystal violet staining in a 96-well microtiter plate, but the staining procedure as such could be standardized. Do we need biofilm-specific repositories? What about sharing and re-use of data? Standardization would also improve the content of databases, and the other way around, databases can promote the standardization efforts. Databases in the context of biofilm research could refer to physical databases for microbial strains, and to computer databases for a wide range of different data types (images, genomics, transcriptomics etc.). For the deposit of (mutant) strains no additional initiatives are necessary. Strains can be deposited in a number of international culture collections (including ATCC in the US and BCCM/LMG Bacteria Collection in Belgium). This deposit guarantees that a particular strain is not lost and allows other researchers to easily obtain it. In addition, special panels of microorganisms can be assembled and deposited in these collections. A recent example of this includes the international Pseudomonas aeruginosa reference panel [ 40 ]. The deposition of (sets of) strains in international culture collection will allow researchers from different laboratories to work on the same strain, which will facilitate comparison of results obtained with different experimental approaches in different laboratories. Making sure that biological material included in published biofilm studies is available to other researchers is a shared responsibility of authors and journals/publishers; with the need for the latter to be stricter about this. There is less consensus about the deposition of data, although overall the feeling was that one or more repositories dedicated to biofilm data could be useful. As an example, the WormBase repository for data concerning Caenorhabditis elegans and related organisms was mentioned [ 41 ]. However, the added value of depositing biofilm-derived ‘omics’ data in a second database (besides e.g. GenBank and ArrayExpress) was questioned. The experience with the BiofOmics web platform aimed at the systematic and large-scale compilation, processing and analysis of biofilm data from high-throughput experiments [ 31 ] shows that it is difficult to convince researchers to deposit their data and the curation of such database(s) is time-consuming. A possible solution to that is crowdsourcing of curation, but that solution carries the risk of introducing bias and variability. In addition, the main goal of data deposition is re-use of data and this has several implications. Besides the issue of standardization outlined above, there is also the issue concerning metadata – i.e. what information about a dataset is required before data can be re-used? In 2014, standards for reporting experiments and data on biofilms were published (minimum information about a biofilm experiment, MIABiE) [ 30 ] but the uptake of these guidelines has been slow, both on the side of the scientific community (i.e. biofilm researchers) and on the side of journals/publishers. Regardless, there seems to be a consensus that more efforts are needed to make raw data and the associated relevant metadata available as soon as possible, at the latest when the research results are published. This is a shared responsibility of authors and editors. A final added value of a biofilm data repository is that it would force researchers to upload their data and metadata in a certain way, opening up the possibilities of performing meta-analyses on these data. Can we provide guidance to (starting) biofilm researchers? With the ever-growing number of biofilm-related papers published and the wide range of different methods available, it is not easy for researchers new in the field (or new to a particular subdiscipline in the field) to choose the most appropriate model system (see also Question 3 ). While there are several review papers on various aspects of biofilm model systems and biofilm methods in general [ 24 , 25 , 38 , 42 ], it seems that this information is not easily available for researchers. An example of this is the widespread use of crystal violet staining. While this can be a valuable tool, it is often used in experiments that would be better served by other output parameters. In addition, some guidance towards data interpretation may also be needed (e.g. how much biofilm reduction is needed in a particular model before considering it biologically meaningful?). A comprehensive decision making algorithm (cfr. Decision Tree for model selection in Question 3 , above) for choosing the most optimal approach for a particular biofilm experiment would be considered useful and detailed information about biofilm methods (principles, protocols, examples of studies using these protocols) should ideally be available online, e.g. as part of the ‘Biofilms: The Hypertextbook’ website ( http://www.hypertextbookshop.com/biofilmbook/v004/r003/ ) maintained by the Center for Biofilm Engineering. Question 6 What do we see in the future of the field in terms of journals, conferences, organization, training schools? Is there a way to (re-)unite the field in terms of conferences - is this necessary or are we happy the way it is? What model(s) do we see in the future for biofilm research? Is there need for more and/or larger (virtual) centers like \n the \n CBE (Center for Biofilm Engineering), NBIC (National Biofilms Innovation Centre) and SCELSE (Singapore Centre for Environmental Life Sciences Engineering)? Is there a need for an independent biofilm society focusing on biofilms in health, environment and energy? Although biofilms impact all aspects of life and biological sciences, it is viewed as a separate field. Is this due to historical reasons, with bacteriology historically involving shaken cultures and mostly planktonic bacteria or is it because we as a field have isolated ourselves on purpose (e.g. by organizing dedicated biofilm conferences)? Biofilms are likely involved in most (if not all) aspects of microbiology, but this is often overlooked. Organization within the field and outreach. One of the key points of the ‘Biofilm Bash’ was to discuss whether an International Biofilm Society should or could be formed. This was welcomed as an intriguing idea, and would give visibility to the field, but there were also many questions about its goals, the practical organization and financial aspects. Several societies for microbiology already exist and it was argued that forming an International Biofilm Society would tap into the energy and passion that people have for the field and may dilute and financially damage the existing societies. The general feeling was that it would be better to use the existing microbiology societies (including ASM, FEMS and the European Society for Clinical Microbiology and Infectious Diseases [ESCMID]) to ‘push the biofilm agenda’ while at the same time opening up the field to others (including bioengineers, mathematicians etc.). Successful global outreach and public engagement will likely require more educational material, position papers, and text books (see also Question 4 ). A list of future stakeholders include -but is not limited too-schools, universities, industry, regulatory agencies and governments. Conferences. Another point for discussion was biofilm conferences: do we need more or less? There was a general consensus that we should not have more conferences on biofilms, the field is saturated. Rather we should aim to have more joint meetings as too many meetings dilute the impact and attendance. A preferred scenario is to have one biofilm conference every year with large joint conferences every 3rd or 6th year. It has been proposed before to combine the different biofilms conferences but so far attempts have been unsuccessful. However maybe in the light of the ‘Biofilms Bash’, we could approach the different biofilm conference organizers to discuss a united approach. The consensus was that we need to rely more on existing microbiological societies and their (general) meetings to organize these conferences. It was also proposed to setup a Gordon or Keystone conference on biofilms. Strategies for future meetings should be directed towards reaching people who are new to the field: we need people to understand that biofilms are not a special thing but rather the common mode of growth of microorganisms! Journals. As for biofilm specific journals, it was thought that the market is already saturated. With the new journal ‘Biofilm’ we have enough specific journals and biofilm research can also be published in the existing more general journals. Training schools and courses. It was discussed how we can educate researchers about biofilm and use existing knowledge and resources better. Training schools and workshops, such as Summer Schools, to learn the basics of biofilm models are still needed but it is worth investigating whether this can be organized at a larger international scale (Woods Hole and Cold Spring Harbor course programs were mentioned as examples) as such courses would benefit from a more interdisciplinary approach. There also seems to be a need for shorter/more dedicated courses also offering data analysis, including statistics. Other suggestions for workshops and short courses/training schools include image analysis, flow cells, microscopy, industrial biofilms, regulatory aspects of biofilms, hands-on techniques, clinical/medical biofilms, dental biofilms, environmental biofilms, and biofilms in engineering. These courses/workshops could also be part of conferences as is already happening with Eurobiofilms, ASM Conference on Biofilms and ChinaBiofilms. It is proposed to make a list of available hands-on courses as well as online courses (e.g. https://biofilmcourse.ku.dk/ , https://www.coursera.org/learn/bacterial-infections ). Networking. The biofilm field would benefit from a map of available infrastructure, resources, societies, as well as integrative conferences and courses. Increased interdisciplinary and international networking would also be beneficial and the larger centers (e.g. NBIC, CBE, SCELSE) can and should play a role in catalyzing these interactions. This was discussed extensively and although the value of this (e.g. in leveraging international funding initiatives) was clear to all, organizing this on an international level is challenging. Funding agencies that could be contacted for this include the National Science Foundation (NSF, US), National Institutes of Health (NIH, US) and the European Cooperation in Science and Technology (COST) intergovernmental framework. Regardless of which partnerships/networks will develop in the future, these should be inclusive. We will need to act as a connected community to successfully develop platforms that fuel innovation!"
} | 12,099 |
28324544 | PMC4522733 | pmc | 5,308 | {
"abstract": "Modern agriculture faces challenges, such as loss of soil fertility, fluctuating climatic factors and increasing pathogen and pest attacks. Sustainability and environmental safety of agricultural production relies on eco-friendly approaches like biofertilizers, biopesticides and crop residue return. The multiplicity of beneficial effects of microbial inoculants, particularly plant growth promoters (PGP), emphasizes the need for further strengthening the research and their use in modern agriculture. PGP inhabit the rhizosphere for nutrients from plant root exudates. By reaction, they help in (1) increased plant growth through soil nutrient enrichment by nitrogen fixation, phosphate solubilization, siderophore production and phytohormones production (2) increased plant protection by influencing cellulase, protease, lipase and β-1,3 glucanase productions and enhance plant defense by triggering induced systemic resistance through lipopolysaccharides, flagella, homoserine lactones, acetoin and butanediol against pests and pathogens. In addition, the PGP microbes contain useful variation for tolerating abiotic stresses like extremes of temperature, pH, salinity and drought; heavy metal and pesticide pollution. Seeking such tolerant PGP microbes is expected to offer enhanced plant growth and yield even under a combination of stresses. This review summarizes the PGP related research and its benefits, and highlights the benefits of PGP rhizobia belonging to the family Rhizobiaceae, Phyllobacteriaceae and Bradyrhizobiaceae.",
"conclusion": "Conclusion Rhizosphere is a unique niche that provides habitation and nutrition to PGP microorganisms. In turn, these microorganisms produce multiple benefits of induced plant growth, defense against diseases and survival under stress with many other unknown benefits. The present review documents the potential of PGP rhizobia and highlights the unique properties of plant growth induction, defense pathways and the resistance spectrum available against various abiotic stresses on a variety of agricultural crops. However, the extent of success in realizing the benefits of PGP tends to diminish as it moves from laboratory to greenhouse and to fields, which reflects the scarcity of research on the beneficial effects of PGP microbes under field conditions. Therefore, generation of comprehensive knowledge on screening strategies and intense selection of best rhizobacterial strain for rhizosphere competence and survival is the current need to enhance the field level successes. Identification of such potential rhizobial strains and developing a robust technology for the use by smallholder farmers is still in its infancy. Thus, additional comprehensive research to exploit the potential of PGP rhizobia would provide for expansion of this research area, commercialization and improve sustainability in agricultural production.",
"introduction": "Introduction Imbalance in nitrogen (N) cycling, nutritional status, physical and biological properties of soil, incidence of pests and diseases, fluctuating climatic factors and abiotic stresses are the interlinked contributing factors for reduced agricultural productivity. Agricultural sustainability, food security and energy renewability depends on a healthy and fertile soil. However, rapid acceleration of desertification and land degradation by numerous anthropogenic activities leads to an estimated loss of 24 billion tons of fertile soil from the world’s crop lands (FAO 2011 ). The intensity of such degradation can be realized by the extent of highly degraded (25 %) and slightly/moderately degraded (36 %) lands, while only 10 % of land is listed to be improving all though high level use of agricultural chemicals have increased the productivity of available limited lands, high energy and environmental costs associated with their use necessitate the search for alternative methods of soil fertility and pest management. Recent estimations indicate that by 2030, the increasing population growth and changing consumption patterns would increase the demand for food by at least 50 %, energy by 45 % and water by 30 % (IFPRI 2012 ). These expectations cannot be met sustainably unless the soil fertility and productivity has been restored in the already degraded lands. A reversal of the decline in soil health is a possibility through the use of green and farm yard manures, composts and crop residues and by crop management options, such as natural fallow, intercropping, relay cropping, cover crops, crop rotations and dual purpose legumes. Among these practices, legumes are the well-acknowledged builders and restorers of soil fertility, primarily through their association with symbiotic nitrogen fixation. Use of microbial agents for improving agricultural productions, soil and plant health had been practiced for centuries. By the end of the ninenteenth century, the practice of mixing natural soil with seeds became a recommended method of legume inoculation. Rhizospheric soil, inhabited and influenced by the plant roots, is usually rich in nutrients when compared to the bulk soil, due to the accumulation of numerous amino acids, fatty acids, nucleotides, organic acids, phenols, plant growth regulators/promoters, putrescine, sterols, sugars and vitamins released from the roots by exudation, secretion and deposition. This results in enrichment of microorganisms (10- to 100-folds than the bulk soil) such as bacteria, fungus, algae and protozoa, among which bacteria influence the plant growth in a most significant manner (Uren 2007 ). Such rhizobacteria were categorized depending on their proximity to the roots as (1) bacteria living in soil near the roots (rhizosphere) (2) bacteria colonizing the root surface (rhizoplane) (3) bacteria residing in root tissue (endophytes), inhabiting spaces between cortical cells and (4) bacteria living inside cells in specialized root structures, or nodules, which includes two groups—the legume associated rhizobia and the woody plant associated Frankia sp. (Glick 1995 ). Bacteria that belong to any of these categories and promote plant growth either directly (nitrogen fixation, phosphate solubilization, iron chelation and phytohormone production) or indirectly (suppression of plant pathogenic organisms, induction of resistance in host plants against plant pathogens and abiotic stresses), are referred as plant growth promoting rhizobacteria (PGPR). Vessey ( 2003 ) preferred to categorize the bacteria that belong to the above mentioned first three groups as extracellular PGPR (ePGPR) and the fourth group as intracellular PGPR (iPGPR). This ePGPR includes the genera Bacillus, Pseudomonas, Erwinia, Caulobacter, Serratia, Arthrobacter, Micrococcus, Flavobacterium, Chromobacterium, Agrobacterium, Hyphomycrobium and iPGPR includes the genera Rhizobium, Bradyrhizobium, Sinorhizobium, Azorhizobium, Mesorhizobium and Allorhizobium. \n Research on exploring the potential of such PGPR has been reviewed periodically by many researchers (Bhattacharyya and Jha 2012 ; Gray and Smith 2005 ; Johri et al. 2003 ; Lugtenberg and Kamilova 2009 ). There are many reviews focusing on both ePGPR and iPGPR. However, we intend to provide a detailed review on iPGPR, the rhizobia that belong to the families Rhizobiaceae (excluding the Frankia sp.), Bradirhizobiaceae and Phyllobacteriaceae, having unique association with root nodules of legumes and induce plant growth in many ways and improving sustainability in agriculture. Similar review on the capacity of rhizobia in inducing the plant growth of nonleguminous plants has been published by Mehboob et al. ( 2012 ). In Rhizobiaceae family, the constituents increased considerably from 8 in the year 1980 to 53 in 2006 (Willems 2006 ). Dispersion of host plants to new geographical locations might serve as a major source for these new rhizobia species. Still, increasing number of rhizobial species is expected because of following reasons. Only 57 % of 650 genera of leguminous plants have been studied for nodulation. Exploration of large number of legume species can potentially lead to the identification of many more rhizobial species. Recent advancements in the taxonomic research with the aid of specific molecular tools are another reason. So, identification and exploration of such potential rhizobia with plant growth promoting properties will be useful for sustainable agriculture."
} | 2,100 |
25642283 | PMC4311453 | pmc | 5,310 | {
"abstract": "Background The fermentation inhibition of yeast or bacteria by lignocellulose-derived degradation products, during hexose/pentose co-fermentation, is a major bottleneck for cost-effective lignocellulosic biorefineries. To engineer microbial strains for improved performance, it is critical to understand the mechanisms of inhibition that affect fermentative organisms in the presence of major components of a lignocellulosic hydrolysate. The development of a synthetic lignocellulosic hydrolysate (SH) media with a composition similar to the actual biomass hydrolysate will be an important advancement to facilitate these studies. In this work, we characterized the nutrients and plant-derived decomposition products present in AFEX™ pretreated corn stover hydrolysate (ACH). The SH was formulated based on the ACH composition and was further used to evaluate the inhibitory effects of various families of decomposition products during Saccharomyces cerevisiae 424A (LNH-ST) fermentation. Results The ACH contained high levels of nitrogenous compounds, notably amides, pyrazines, and imidazoles. In contrast, a relatively low content of furans and aromatic and aliphatic acids were found in the ACH. Though most of the families of decomposition products were inhibitory to xylose fermentation, due to their abundance, the nitrogenous compounds showed the most inhibition. From these compounds, amides (products of the ammonolysis reaction) contributed the most to the reduction of the fermentation performance. However, this result is associated to a concentration effect, as the corresponding carboxylic acids (products of hydrolysis) promoted greater inhibition when present at the same molar concentration as the amides. Due to its complexity, the formulated SH did not perfectly match the fermentation profile of the actual hydrolysate, especially the growth curve. However, the SH formulation was effective for studying the inhibitory effect of various compounds on yeast fermentation. Conclusions The formulation of SHs is an important advancement for future multi-omics studies and for better understanding the mechanisms of fermentation inhibition in lignocellulosic hydrolysates. The SH formulated in this work was instrumental for defining the most important inhibitors in the ACH. Major AFEX decomposition products are less inhibitory to yeast fermentation than the products of dilute acid or steam explosion pretreatments; thus, ACH is readily fermentable by yeast without any detoxification. Electronic supplementary material The online version of this article (doi:10.1186/s13068-014-0179-6) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusion In this work, nutrients and decomposition products present in ACH were characterized with the goal of formulating a synthetic hydrolysate, which will be used in multi-omics analysis for understanding the inhibition mechanisms of the lignocellulosic hydrolysate. This work also provides an example showing how synthetic lignocellulosic hydrolysates derived from other pretreatment technologies (such as dilute acid and steam explosion) can be formulated. The ACH contained high levels of nitrogenous compounds, notably phenolic amides and acetamide. Due to their presence at high concentrations, their observed inhibitory effect on xylose consumption and ethanol production was the most significant among all the families of compounds tested herein, which included aliphatic acids, furans, lignin-derived phenolic compounds, and oligomeric carbohydrates. However, when comparing the inhibition due to amides at the same molar concentrations as their acid counterparts, we observed that amides are significantly less inhibitory to both glucose and xylose fermentation than the acids. The reduced inhibitory effect of amides is a major advantage of AFEX- and ammonia-based pretreatments over other pretreatment technologies that mainly produce carboxylic acids as decomposition products. Because of the reduced production of carboxylic acids and furans, notably furfural and 5-HMF, the ACH is easily fermentable without any detoxification. Although we were able to identify the major groups of inhibitory compounds present in the ACH, the SH did not exactly match the performance of the actual hydrolysate. The cell density in SH was considerably lower than in the actual hydrolysate and, as a consequence, the xylose consumption rate was also slightly reduced. However, the proposed SH was instrumental in identifying the inhibitory effect of various classes of compounds present in the hydrolysate and their relative contribution to the overall inhibition. Due to the complexity of the lignocellulosic hydrolysate composition, we will likely develop more representative versions of the SH as we learn more about the composition of actual hydrolysates. The SH formulation will be instrumental in future multi-omics studies to understand the nature of AFEX pretreatment-specific decomposition products and how they inhibit yeast and bacteria, so that we can engineer better strains to maximize biofuel yields and productivity. Endnote a TM - AFEX is a trademark of MBI International, Lansing, Michigan.",
"discussion": "Results and discussion The major objective of this work is the formulation of a synthetic lignocellulosic hydrolysate (SH), as a tool to understand the effect of various components from pretreated biomass on microbial fermentation. This work provides guidelines and a methodology to formulate a detailed SH, based on the composition of industrially relevant lignocellulosic hydrolysates. The SH described in this work was designed based on the composition of ACH and was used to determine the impact of various major biomass-derived products on the performance of S. cerevisiae 424A (LNH-ST) fermentation. The details concerning 1) characterization of the AFEX-CS hydrolysate, 2) formulation of an SH, and 3) the impact of major hydrolysate components on yeast fermentation will be discussed here. Characterization of the ACH Characterization of the ACH involves identification and quantification of 1) natively available microbial nutrients, 2) plant-derived chemicals, and 3) pretreatment-specific decomposition products. The nutrients available in the ACH are listed in Table 2 and comprise various forms of carbohydrates, nitrogenous compounds, vitamins, and minerals. The carbohydrates which could be consumed by S. cerevisiae 424A (LNH-ST) as a carbon source were glucose (60 g/L) and xylose (26 g/L). Other carbohydrates were found in ACH at lower abundances, including arabinose (5 g/L), glucan-derived oligomers (12 g/L), and xylan-derived oligomers (18 g/L). However, these were not categorized as nutrients, as S. cerevisiae 424A (LNH-ST) is not capable of using these sugars as a primary carbon source [ 21 ]. A total of 1.44 g/L of protein was estimated by LC-MS during the amino acid analysis of the ACH. Individual amino acid concentrations are shown in Additional file 1 : Table S1. While the total protein concentration is fairly similar to the results of a previous study [ 18 ], the relative proportions of individual amino acids were significantly different. In this work, aspartate, valine, and proline were the most abundant amino acids, as opposed to glutamate, glycine, and alanine reported by Lau et al. [ 18 ]. These differences are likely related to the fact that, in this study, enzymatic hydrolysis was performed on a different source of corn stover, using different commercial enzymes. However, these changes in amino acid proportions, due to differences in feedstock and enzyme sources, did not affect the overall fermentation profiles of S. cerevisiae 424A (LNH-ST) grown on the hydrolysate, as the results obtained in this study are comparable to those of our previous work [ 10 ]. The free ammonium concentration found in the hydrolysate was the same as the total protein (1.44 g/L) and significantly different from the value reported previously (0.75 g/L) [ 18 ]. The concentration of free ammonium in the hydrolysate is dependent on the levels of residual ammonia left adsorbed on the biomass after AFEX pretreatment, which may vary due to differences in the relative organic acid content of the feedstock and the efficiency of ammonia removal by evaporation in the fume hood following pretreatment. However, these variations in ammonium concentration between pretreatment batches did not have significant effects on the fermentation profiles of S. cerevisiae 424A (LNH-ST) compared to previous studies [ 10 , 13 ]. This observation suggests that nitrogen is not a limiting factor for efficient fermentation of ACH. Vitamin concentrations reported in this manuscript (Table 2 ) were based on results previously reported by our laboratory [ 18 ]. A sensitivity analysis was carried out to evaluate the impact of vitamin concentrations on the fermentability of SH and verify if using previously reported values is a reasonable assumption for this work. For this purpose, experiments using ACH with and without 50% vitamin supplementation (based on values from Table 2 ) were performed. As no significant differences were observed on the fermentation profiles (data not shown) during this sensitivity analysis, it was reasonable to assume that the values obtained in the previous study could be used to estimate the vitamin composition of the SH (Table 2 ). It is also important to note that the goal of this study is to formulate a SH based on a typical composition of an industrially relevant biomass hydrolysate, which can vary significantly depending on the origin of the feedstock and enzymes used. Therefore, using values from our previous study was a reasonable assumption for achieving the aforementioned goals of the current study. The mineral content of ACH was quantified by ICP-MS. Macro-elements such as P, K, and Mg were present in concentrations above the optimum range required for yeast growth defined by Jones and Greenfield (1984) [ 22 ]. These minerals are essential to all yeast and must be present in millimolar concentrations for optimal cell growth [ 22 ]. From Table 2 , it is possible to observe an extremely high level of K (3886.50 mg/L), which resulted from the utilization of KOH for pH adjustment to 4.8 during enzymatic hydrolysis. Unfortunately, pH maintenance is essential to maximize enzymatic hydrolysis conversions; therefore, little could be done to avoid the accumulation of this macro-element. Elements such as Na, Ca, and Mn are also available in concentrations above the optimum for yeast growth [ 22 ]. However, the effect of high levels of trace elements in combination with other components found in ACHs is not yet understood. Chelation effects and ionic interactions with hydrolysate components may affect the optimum range of these minerals for yeast growth [ 23 ]. Characterization of pretreatment-derived decomposition products and potential plant- derived inhibitory compounds present in the hydrolysate was performed using targeted LC- and GC-MS analysis. In our previous work, the most abundant compounds produced during AFEX pretreatment of CS were identified and quantified [ 15 ]. That work served as the platform to characterize the hydrolysate composition described here. In Table 4 , these products were categorized into nitrogenous compounds, furans, aliphatic acids, aromatic compounds, and carbohydrates. The concentration of nitrogenous compounds and furans was calculated based on the amounts present in AFEX-CS, as previously reported by Chundawat et al. [ 15 ]. High levels of sugars in the hydrolysate interfered with the direct quantification of these products by GC-MS, including acetamide, pyrazines, imidazoles, and furans. We considered removing those monomeric sugars from the hydrolysate prior to GC-MS analysis; however, this would have required extensive sample preparation and would thus affect the accuracy of absolute quantification of each target compound (without extensive method development, see previous study for issues encountered during typical GC-MS analysis in presence of high soluble sugar background [ 24 ]). For achieving the major goals of our current study, we have assumed that all nitrogenous compounds and furans found in AFEX-CS were totally solubilized (with 100% recovery) in the supernatant during enzymatic hydrolysis, as they are highly soluble at those concentration levels (see Table 4 for details). All other compounds presented in Table 4 were directly quantified in the hydrolysate using HPLC and LC-MS analysis. Carbohydrates are by far the most abundant compounds in the hydrolysate, where 60 g/L glucose, 26 g/L xylose, and 5 g/L arabinose were quantified as the major carbohydrate monomers (Table 4 ). The concentration of carbohydrates (and other compounds) depends on the solids loading used during enzymatic hydrolysis of the pretreated biomass. In this work, 18% solids loading enzymatic hydrolysis was performed to create the ACH, giving a sufficient concentration of sugars to produce approximately 4 wt% ethanol after fermentation. This enzymatic hydrolysis condition is considered to be industrially relevant; therefore, results from this study have practical industrial relevance. However, typically under such high solids loadings, the enzymes are inhibited by high concentrations of soluble sugars [ 25 , 26 ], leading to the progressive accumulation of sugar oligomers derived from xylan and glucan. This likely explains the presence of 12 g/L and 18 g/L of gluco- and xylo-oligomers, respectively, in the ACH. From Table 4 , it is clear that, besides carbohydrates, the major water soluble plant-derived compounds present in ACH are feruloyl amide, p -coumaroyl amide, acetamide, acetic acid, trans -aconitic acid, formic acid, and p -coumaric acid. All these components are present in the hydrolysate in concentrations above 300 mg/L and, therefore, their presence at such levels can potentially impact the performance of yeast fermentation during biofuel production. The nitrogenous compounds presented in Table 4 are products of reactions between plant cell wall components and ammonia, which are produced during AFEX pretreatment [ 15 ]. For example, acetamide, feruloyl amide, and p -coumaroyl amide are products of ammonolysis reactions that cleave ester-bound acetates, coumarates, and ferulates, which are abundantly present in the plant cell wall of CS [ 27 , 28 ]. These reactions are thought to be important for the efficacy of the pretreatment, by disrupting the ester cross-links between carbohydrates and lignin, or by deacetylating the xylan backbone of hemicellulose [ 15 , 28 , 29 ]. The acid counterparts of these amides, that is, acetic acid, ferulic acid, and p -coumaric acid, are products of hydrolysis of the same esters, which also occur during AFEX due to the presence of hydroxyl ions in the pretreatment media [ 15 ]. Similarly to dilute acid pretreatment, formic acid is also widely produced during AFEX; however, it is formed by a different mechanism, likely via alkaline peeling reactions of polysaccharides [ 15 , 30 , 31 ]. On the other hand, trans -aconitic acid is not regarded as a typical AFEX pretreatment-derived decomposition product, but it is a well-known plant metabolite that is particularly abundant in grasses, including maize [ 15 , 32 , 33 ]. Therefore, its presence in a CS-derived hydrolysate at these levels is expected. Other less abundant products present in the hydrolysate, also listed in Table 4 , are included in various categories such as nitrogenous compounds, furans, aliphatic acids, and aromatic compounds. Though they are present in lower amounts in the hydrolysate, their inclusion in the SH is important because their cumulative and synergistic inhibitory effects may be significant during microbial fermentation [ 34 ]. Formulation of a control synthetic medium As mentioned above, ACH contains nutrients, as well as plant-derived compounds that are potentially inhibitory to microorganisms. The control synthetic medium was formulated to contain a similar level of nutrients as the biomass-derived hydrolysate, without the plant-derived inhibitory components. Table 3 summarizes the nutrient formulation of the control synthetic medium used in this work. Specifically, (NH 4 ) 2 SO 4, peptone, and vitamins were used to match the concentrations of ammonia, protein, and vitamins, respectively, present in the hydrolysate. The concentrations of mineral elements added to the control synthetic medium were largely matched by adding a selection of salts as described in Table 3 . The salts were carefully selected to avoid solubility problems during media preparation. In general, chlorine-based salts showed higher solubility in the synthetic hydrolysate than the sulfate, phosphate, or carbonate counterparts. However, a recent study by Casey et al. [ 35 ] revealed that chloride salts can be more detrimental to the specific xylose consumption rate of S. cerevisiae 424 A (LNH-ST) compared to their sulfate counterparts, for example. Therefore, high concentrations of chlorine anions in solution could negatively affect xylose fermentation. To avoid the presence of high levels of chlorine-based salts in the synthetic medium, we selected potassium salts with three different anion pairs and sodium salts with two different anion pairs (Table 3 ). For the same reason, we also chose to use Ca(NO 3 ) 2 instead of CaCl 2 . In this synthetic control medium, S. cerevisiae 424A completely consumed glucose and xylose in 18 and 72 h, respectively, generating ethanol at a concentration of around 35 g/L (about 80% metabolic yield) and a cell density (OD 600 nm) of approximately 12 (Figure 1 ). These results suggest that ACH is not limited by nitrogen, protein, or micronutrients for consuming glucose and xylose during ethanol production (though the rate of xylose uptake is significantly slower than that of glucose). However, determining the nutrient composition of AFEX pretreated biomass hydrolysates and formulating a control synthetic medium is critical to further improving microbial co-fermentations for more efficient and rapid conversion of lignocellulosic hydrolysates in the presence of inhibitory compounds. This is highlighted by the fact that xylose fermentation is affected by the nutrients level in the medium and that individual decomposition products in ACH are not very inhibitory for robust yeast species such as S. cerevisiae [ 10 ]. Thus, it is likely that the inhibitory effect of many of the plant-derived compounds present in the hydrolysate would not be observed in nutrient-rich media (such as Yeast Extract Peptone, YEP medium). Though the control synthetic medium formulated in this work is not exactly comparable with the actual biomass hydrolysate due to experimental limitations, the nutrient value is close enough to be considered acceptable for studying the effect of different inhibitors on strain performance. A sensitivity analysis was performed to determine how the concentration of amino acids affects cell growth and the fermentation performance. It was found that a variation of the amino acid concentration by up to two times the amount detected in the hydrolysate did not affect cell growth; however, it did improve the xylose consumption rate (data not shown). Figure 1 \n Fermentation profile of the control synthetic medium (blank) without addition of nutrients. \n Inhibitory effect of different classes of compounds from ACH on S. cerevisiae 424A fermentation As previously mentioned, the plant-derived compounds and pretreatment decomposition products present in ACH were divided into five groups: nitrogenous compounds, organic acids, aromatic compounds, carbohydrates, and furans (Table 4 ). The effect of the different groups of lignocellulose decomposition products on S. cerevisiae 424A fermentation was investigated and compared with the control synthetic medium (blank) formulated in this work (Table 5 ). The various classes of compounds identified in ACH were added to the blank medium at an abundance comparable to that in the actual hydrolysate to determine their individual and combinatorial inhibitory contribution to yeast fermentation. Table 5 \n Fermentation parameters for synthetic media (SM) in presence of various groups of lignocellulose decomposition products (DP) \n e \n \n Biomass yield \n b \n (g/g) \n \n Xylose consumption (%) \n \n Ethanol productivity (g/L/h) \n \n Ethanol yield \n c \n (g/g) \n \n Glycerol yield (g/g) \n \n Xylitol yield (g/g) \n \n Acetate yield (g/g) \n \n Carbon balance closure \n \n 18 h \n \n 24 h \n \n 48 h \n \n 24 h \n \n 48 h \n \n 48 h \n \n 48 h \n \n 48 h \n \n 48 h \n Blank SM a \n 0.078 ± 0.002 66.92 ± 0.18 97.08 ± 0.04 1.29 ± 0.01 0.71 ± 0.01 0.406 ± 0.001 0.058 ± 0.000 0.053 ± 0.002 0.007 ± 0.000 1.00 Blank + Nitrogenous compounds 0.067 ± 0.003 44.69 ± 0.68 86.92 ± 0.61 1.21 ± 0.00 0.69 ± 0.01 0.402 ± 0.007 0.060 ± 0.001 0.055 ± 0.003 0.007 ± 0.000 0.98 Blank + Aliphatic acids d \n 0.068 ± 0.002 58.95 ± 0.16 94.17 ± 0.04 1.23 ± 0.01 0.73 ± 0.01 0.427 ± 0.001 0.051 ± 0.000 0.042 ± 0.001 0.002 ± 0.000 1.01 Blank + Aromatic compounds 0.072 ± 0.002 68.70 ± 0.19 88.34 ± 0.04 1.29 ± 0.00 0.72 ± 0.01 0.421 ± 0.001 0.051 ± 0.000 0.032 ± 0.001 0.007 ± 0.000 1.00 Blank + Carbohydrates (oligos) 0.074 ± 0.002 54.68 ± 0.98 94.49 ± 0.50 1.28 ± 0.00 0.73 ± 0.00 0.416 ± 0.001 0.059 ± 0.000 0.043 ± 0.000 0.007 ± 0.000 1.01 Blank + Furans 0.078 ± 0.002 69.25 ± 0.19 96.90 ± 0.04 1.29 ± 0.00 0.72 ± 0.01 0.410 ± 0.001 0.059 ± 0.000 0.052 ± 0.002 0.007 ± 0.000 1.01 Blank + DP in combination d \n 0.059 ± 0.002 21.17 ± 0.09 40.05 ± 1.28 1.20 ± 0.01 0.64 ± 0.00 0.440 ± 0.000 0.045 ± 0.000 0.024 ± 0.000 −0.002 ± 0.000 0.99 Actual Hydrolysate d \n 0.065 ± 0.001 14.91 ± 0.53 43.31 ± 0.47 1.26 ± 0.01 0.73 ± 0.00 0.474 ± 0.002 0.048 ± 0.001 0.018 ± 0.000 −0.003 ± 0.001 1.06 \n a The blank was the synthetic medium without the addition of decomposition products (DP). \n b Biomass yield was based on both glucose and xylose consumed at 18 h fermentation, when the cell density reached the maximum. One unit of absorbance at 600 nm is approximately equal to 0.48 g dry cell wt/L. \n c Theoretical metabolic yield of ethanol for both sugars was 0.51 g EtOH/g consumed sugar. \n d The initial concentration of acetate in the hydrolysate and synthetic medium with the addition of aliphatic acids and DP in combination was 1.9 g/L. \n e The t -test results for determining statistically significant differences between the different results are presented in Additional file 1 , S2, Tables S2-1 - S2-9. From the results presented in Table 5 , the nitrogenous compounds caused a significant decrease in cell biomass yield, xylose consumption rate, and 24 h ethanol productivity compared to the blank control SM (Additional file 1 : Table S2-1, S2-2, and S2-4). Though this class of compounds is not usually found in most lignocellulosic hydrolysates, certain amides are produced by a variety of plants and are known to have anti-fungal effects [ 36 ]. As nitrogenous compounds are quite abundant in AFEX biomass-derived hydrolysates and limited information about their inhibitory effect on microbes is currently available in the literature, we will discuss this in more detail in the subsequent section. Similarly to the effect of nitrogenous compounds, the xylose consumption rate and cell biomass yields were also negatively affected by the addition of aliphatic acids and aromatic compounds (Table 5 ). On the other hand, the ethanol metabolic yield was enhanced by the presence of these two classes of compounds, which is consistent with earlier findings in the literature [ 37 ]. As these weak acids will be present in the hydrolysate solution predominantly in their non-dissociated form, they will be permeable through the yeast cell membrane [ 38 ]. Once they enter the cytosol, the acids will dissociate and the cell will be forced to pump excess protons through the membrane to maintain homeostasis. Though low concentrations of organic acid have been observed to increase ethanol yields and fermentation rates, this benefit is lost at higher acid concentrations [ 39 - 42 ]. High levels of anionic acid species are also toxic to the cell and can result in cessation of growth or cell death [ 41 , 43 ], which does not seem to be the case for ACH. Lignin-derived aromatic compounds, such as phenols, are also known to inhibit S. cerevisiae growth, especially lower molecular weight phenolics. The toxicity of these compounds is dependent on the relative position (ortho, meta, or para) of the functional group in the benzene ring [ 44 ] and also on the type of functional group (for example, aldehydes, ketones, or acids). The phenolic compounds may interact with biological membranes, interfering with their function. However, the inhibition mechanism of this family of compounds is not well understood [ 45 ]. The oligomeric carbohydrates (particularly xylo-oligomers) also negatively affected xylose consumption rate in the first 24 h (18% of the control xylose consumption was reduced in the first 24 h). However, at the 48 h time point this difference was reduced to 2.7% of the control xylose consumption. As a result, the 48 h ethanol metabolic yield was only reduced by 2.5% of the control in the first 48 h. To our knowledge, xylose consumption inhibition by oligomeric carbohydrates has never been reported in the literature, and it would be interesting to determine the possible reason for this observation in a future study. Addition of furans did not affect fermentation kinetics in great extent compared to the control (blank). The results from Table 5 show that there were no significant differences in biomass yield, 24 h ethanol productivity, and 48 h acetate yields compared to the blank SM (see Additional file 1 : S2). Although the other parameters shown in Table 5 related to furan addition were statistically different from those of the blank SM, the observed difference was not very pronounced. The inhibitory effects of furans (such as furfural and hydroxymethyl furfural) on cellular metabolism have been thoroughly studied by several researchers [ 37 , 46 ]. These effects include oxidative damage of yeast cells by lower abundance of reducing agent concentrations (such as NADPH and NADH) and reduced activities of enzymes involved in the glycolysis pathway. From the most common furans found in lignocellulosic hydrolysates, furfural seems to be more inhibitory when compared to 5-HMF, at equivalent concentrations [ 47 ]. As AFEX pretreatment produces a low level of 5-HMF (Table 4 ) and practically no furfural, the concentration of this class of compounds in the hydrolysate appears to be low enough to avoid oxidative damage during yeast fermentation. The synergistic inhibitory effect of the various classes of decomposition products (DP) was observed on xylose fermentation. The combination of all compounds (blank + DP in combination) showed a higher inhibitory effect than the aggregate value of individually added products (48 h data). This result agrees with previous reports that also observed synergies on the inhibitory effect of different compounds during yeast fermentation [ 47 ]. Among all the classes of decomposition products tested herein, nitrogenous compounds were the most inhibitory to xylose fermentation (Table 5 ), which could potentially be explained by their relatively higher concentration in the hydrolysate. In the presence of aliphatic acids, about 70% decrease in acetate production was observed compared to the blank SM (Table 5 ). This result may be related to end-product (acetate) inhibition of the acetate synthesis pathway in yeast. Moreover, when all the decomposition products were added together, acetate was consumed by the yeast after 48 h fermentation, instead of being produced. It is possible that the yeast cells consume acetate to equilibrate the redox imbalance caused by the xylose metabolic pathway and due to the presence of high concentrations of other inhibitory compounds [ 48 ]. However, to better understand this finding, more detailed metabolomic experiments will need to be carried out in the future using SHs. The carbon mass balance closures for the various synthetic media evaluated in Table 5 are approximately equal to 1. However, for the actual hydrolysate the carbon mass balance closes at 1.06, which means that there is 6% more carbon being formed than the carbon consumed. This observation may suggest that there are other carbon sources present in small quantities in the actual hydrolysate, which were not detected or analyzed in this study. More in-depth characterization is required to determine the minor carbon sources that contribute to this carbon mass balance closure. Inhibitory effect of individual families of nitrogenous compounds Since the effects of nitrogenous products on fermentation are particularly less well understood than the remaining categories of compounds, and because these products are specifically linked to ammonia-based pretreatment, we decided to further investigate their individual effect on the fermentation profile of S. cerevisiae 424A. Here, we evaluated in more detail the effect of various 1) pyrazines, 2) imidazoles, and 3) amides on xylose consumption and ethanol production rates (Table 6 and Figure 2 ). The results show that the addition of pyrazines or imidazoles to a well-defined SM did not significantly affect the kinetics of xylose consumption and ethanol production ( P -value ≥ 0.05, see Additional file 1 , S3, Tables S3-2 - S3-4). These two families of compounds are not present in the hydrolysate at high concentrations and therefore are likely not to have any major inhibitory effect on yeast fermentation. However, amides are present at much higher concentration in the hydrolysate, and their addition to the blank media resulted in decrease of biomass yield, xylose consumption rate, and ethanol productivity. Specifically, with the addition of amides the biomass yield, xylose consumption, and ethanol productivity were reduced from 0.068 g/g, 95%, and 0.71 g/L/h to 0.061 g/g, 80%, and 0.65 g/L/h, respectively. Though we see some level of inhibition on xylose consumption and ethanol production, the mechanisms of amide inhibition are not well understood. It is possible that phenolic amides have a similar mechanism of inhibition to the lignin-derived phenolic compounds, which tend to impact the integrity of the cell membranes when present at high concentrations [ 44 , 45 ]. Table 6 \n Fermentation parameters of synthetic media (SM) with/without the addition of various nitrogenous compounds commonly found in AFEX-CS hydrolysates (ACHs) \n \n Biomass yield (g/g) \n \n Xylose consumption \n a \n (%) \n \n Ethanol productivity \n a \n (g/L/h) \n \n Ethanol yield (g/g) \n \n Glycerol yield (g/g) \n \n Xylitol yield (g/g) \n \n Acetate yield (g/g) \n Blank (SM) b \n 0.068 ± 0.001 95 ± 1 0.71 ± 0.01 0.411 ± 0.005 0.059 ± 0.001 0.060 ± 0.004 0.010 ± 0.001 Blank + pyrazines 0.070 ± 0.002 95 ± 0 0.72 ± 0.00 0.416 ± 0.002 0.062 ± 0.003 0.061 ± 0.001 0.010 ± 0.004 Blank + imidazoles 0.070 ± 0.002 95 ± 0 0.72 ± 0.00 0.414 ± 0.001 0.062 ± 0.003 0.060 ± 0.003 0.012 ± 0.000 Blank + amides 0.061 ± 0.000 80 ± 1 0.65 ± 0.01 0.390 ± 0.005 0.069 ± 0.001 0.056 ± 0.003 0.013 ± 0.001 \n a Both xylose consumption and ethanol volumetric productivity are shown at 48 h. \n b Except for biomass yield, the differences between all other blank (SM) results from Tables 5 and 6 are not statistically significant ( P > 0.05). Figure 2 \n Time course profile for xylose uptake (A) and ethanol production (B) during fermentation by \n Saccharomyces cerevisiae \n 424A (LNH-ST) in a defined minimal synthetic medium (or blank) with addition of pyrazines, imidazoles, and amides. \n Comparison between the inhibitory effects of amides and the corresponding carboxylic acids Three amides (feruloyl amide, coumaroyl amide, and acetamide) present in the hydrolysate were further studied individually and their inhibition profiles were compared to their corresponding acid forms (ferulic acid, coumaric acid, and acetic acid) in the blank synthetic medium (Figure 3 ). Unlike the previous experiments reported herein, the concentration of amides and acids chosen for this study was not based on their actual amount in the ACH. In this case, it was assumed that all the reacting esters present in the biomass were cleaved by ammonolysis or hydrolysis reactions, respectively. As a result, the same exact molar concentrations of the acid and amide counterparts were used for each comparative inhibition experiment. Figure 3 \n Time course profile of co-fermentation in a minimal synthetic medium without the addition of pretreatment-based decomposition products (blank) (A) and with the addition of 6.2 mM feruloyl amide and ferulic acid (B), 7.5 mM coumaroyl amide and coumaric acid (C), and 28.8 mM acetamide and acetic acid (D) mimicking a dilute acid or ammonia pretreated lignocellulosic hydrolysate. Solid lines depict acids; dashed lines depict amides. In contrast to our previous results for when the amides were added together, the individual amides did not show a substantial inhibitory effect on fermentation compared to the control. Xylose was completely consumed to undetectable levels within 72 h with maximum OD 600 of around 12 for all the amides tested in this work (Figure 3 ). Therefore, the inhibitory behavior of amides is likely a synergistic effect, coupled with the fact that the total concentration of amides was higher than when present individually. The corresponding acid forms of those amide compounds, however, all showed substantial inhibition on cell growth and xylose fermentation. Among all acids, ferulic acid showed the highest inhibitory effect followed by acetic acid and coumaric acid, which was consistent with their relative abundance in the ACH (Table 4 ). Furthermore, ferulic acid is known to be a more potent inhibitor of yeast growth than coumaric acid, when present at similar concentrations. From the results presented in Figure 3 B, the presence of ferulic acid in the fermentation media reduced the cell density by 45%. The average xylose consumption rate decreased to a very low 0.09 g/L/h (0 to 24 h), a much larger decrease than that caused by feruloyl amide (reduced to 0.55 g/L/h). Ferulic acid even affected the glucose consumption rate, which was not observed for any other decomposition product tested herein. Complete glucose consumption was only achieved after 48 h fermentation instead of 18 h, as it was in the case of the control blank medium. From these results, it is evident that amides are less inhibitory than their corresponding acid forms, based on the same molar concentration, on yeast fermentations. Carboxylic acids permeate into the cytosol in their undissociated form when performing fermentations at pH 5.5. While in the cytosol, the acids dissociate due to the near-neutral conditions of the cytosol, decreasing the intracellular pH [ 38 ]. This effect will not be observed for amides, which typically have pKa values greater than 10. This could partially explain why AFEX pretreated biomass has greater fermentability compared to dilute acid pretreated biomass [ 9 ]. Ester hydrolysis reactions that occur during dilute acid and steam explosion pretreatments result in the formation of the organic acids studied herein, probably at similar concentrations to the ones used in this study. However, in the case of AFEX pretreatment (under the presently employed conditions) only about one third of the total available esters are hydrolyzed to yield acids, while the remaining are ammonolyzed to the less inhibitory amides. One possible way to enhance the fermentability of AFEX pretreated biomass is to further reduce the hydrolysis reaction products during pretreatment and promote conditions that improve the selectivity toward the less inhibitory ammonolysis reaction-derived products. Comparison between SH and ACH The fermentation profile of S. cerevisiae 424A in SH was compared side by side to the actual ACH as shown in Figure 4 . The cell growth during fermentation in the control synthetic medium (blank) was comparable to that of the actual hydrolysate, achieving a cell density of OD 600 11.5 after 18 h (Figure 4 D). However, cell growth in the SH, in the presence of all the decomposition products from Table 4 , was greatly reduced, showing a cell density of around OD 600 8 after 18 h fermentation. This value represents just 68% of the cell density obtained using the blank medium. Figure 4 \n Time course profile of co-fermentation in minimal synthetic medium (SM) with or without the addition of plant cell wall decomposition products (DP) compared to hydrolysate (ACH). (A) and (B) depict glucose and xylose uptake, respectively; (C) depicts ethanol concentration produced; and (D) depicts cell density as OD 600 nm. As expected, xylose was almost completely consumed after 48 h fermentation in the control synthetic medium. The average xylose consumption rate was 0.70 g/L/h (0 to 24 h). However, the xylose consumption rates in the SH and ACH were 0.23 g/L/h and 0.28 g/L/h, respectively, which were much lower than the control rate. The lower cell density in the SH was one of the possible causes of the decreased xylose consumption rates. DP inhibition of specific xylose consumption rate and decreasing viable cell density were probably the other two reasons for the slow xylose fermentation [ 13 ]. Regarding the ethanol yield, SH and ACH results were statistically different (0.439 g/g and 0.486 g/g, respectively) and this difference represents about 10% of the ACH ethanol yield. In both these cases, the ethanol yields were significantly higher than the control (0.405 g/g). This increased ethanol metabolic yield in the presence of AFEX pretreatment-derived decomposition products is consistent with our previous observations and other reports [ 10 , 13 , 49 ]. The final ethanol concentrations achieved in the ACH, control synthetic medium, and SH were 38 g/L, 35 g/L, and 32 g/L, respectively. During the first 18 h period, glucose and xylose consumption were equivalent for both media, and only after 18 h fermentation was it possible to observe significant differences in xylose consumption and, consequently, in ethanol production. Therefore, the higher ethanol yields observed for the actual biomass hydrolysate seem to be related to better xylose fermentation. For an ideal SH, one would expect identical cell growth behavior, sugar consumption rates and ethanol yields to those observed for the actual hydrolysate. The differences in cell growth profile between the SH and the ACH may be due to incomplete evaluation of the composition of the actual hydrolysate, which is very complex and presents various analytical challenges. Possible improvements for future versions of the SH may include the analysis of redox co-factors present in plant biomass (for example, NAD(P)H), which could potentially help the yeast cells to improve their fermentation performance. Also, the higher concentration of chlorine-containing salts in the SH might be another possible factor that could have caused such a negative impact (Tables 2 and 3 ). Therefore, optimizing the choice of salts to closely match the mineral content of the ACH would help improve the performance of the SH. Nevertheless, the SH presented in this study was successfully used to evaluate the relative levels of inhibition associated with the various classes of compounds that are present in the actual ACH. Moreover, as we performed a detailed characterization of the amino acids present in the ACH (Additional file 1 : Table S1), it is possible to formulate a well-defined synthetic medium by the addition of individual amino acids, at the respective concentrations, in contrast to peptone. The utilization of defined synthetic media will be important for future multi-omics studies that will help us understand the mechanisms of inhibition under well-controlled experimental conditions."
} | 10,041 |
38344288 | PMC10853475 | pmc | 5,311 | {
"abstract": "Advances in synthetic biology have enabled the incorporation of novel biochemical pathways for the production of high-value products into industrially important bacterial hosts. However, attempts to redirect metabolic fluxes towards desired products often lead to the buildup of toxic or undesirable intermediates or, more generally, unwanted metabolic cross-talk. The use of shells derived from self-assembling protein-based prokaryotic organelles, referred to as bacterial microcompartments (BMCs), as a scaffold for metabolic enzymes represents a sophisticated approach that can both insulate and integrate the incorporation of challenging metabolic pathways into industrially important bacterial hosts. Here we took a synthetic biology approach and introduced the model shell system derived from the myxobacterium Haliangium ochraceum (HO shell) into the industrially relevant organism Zymomonas mobilis with the aim of constructing a BMC-based spatial scaffolding platform. SDS-PAGE, transmission electron microscopy, and dynamic light scattering analyses collectively demonstrated the ability to express and purify empty capped and uncapped HO shells from Z. mobilis . As a proof of concept to internally load or externally decorate the shell surface with enzyme cargo, we have successfully targeted fluorophores to the surfaces of the BMC shells. Overall, our results provide the foundation for incorporating enzymes and constructing BMCs with synthetic biochemical pathways for the future production of high-value products in Z. mobilis .",
"introduction": "1 Introduction The use of microorganisms in the production of commercial products is emerging as a valuable strategy because it reduces the production of toxic waste and is considered sustainable, clean, natural, and inexpensive ( Adesina et al., 2017 ). In many cases, the bacterial chassis that is selected to execute the synthetic metabolic function, typically Escherichia coli or Bacillus subtilis , is chosen because of certain characteristics such as fast growth rate, the ability to survive in a range of different growth conditions, and the availability of genetic modification tools. However, in some cases, these bacterial chassis are not fitted to execute the functions needed for efficient bioproduction ( Calero and Nikel, 2018 ). The integration of synthetic biology and advanced metabolic engineering has enabled the incorporation of non-model organisms as hosts for developing efficient microbial cell factories. These non-traditional organisms typically possess unique enzymatic or fitness advantages, such as increased robustness or efficient metabolism that make them better suited for industrial processes. \n Zymomonas mobilis ( Z. mobilis) is an obligatory fermentative alpha-proteobacterium that has attracted significant interest as a platform for the biosynthesis of biofuels due to of its native ability to efficiently metabolize glucose to ethanol rather than to biomass ( Xia et al., 2019 ; Zhang et al., 2019 ). It possesses several desirable industrial biocatalyst characteristics, such as high productivity, high alcohol tolerance, and a broad pH range for production (pH 3.5–7.5), that make it an ideal platform for industrial-scale production of biofuels and other valuable bioproducts ( Yang et al., 2016 ). Although diverse metabolic engineering approaches have expanded the potential of Z. mobilis , for example, by broadening its substrate range to include xylose and arabinose, or by enhancing Z. mobilis tolerance to ethanol and lignocellulosic hydrolysate inhibitors ( Wang et al., 2018 ; Zhang et al., 2019 ), many attempts to redirect metabolic fluxes towards desired products by enhancing native pathways or introducing new heterologous pathways in Z. mobilis resulted in the accumulation of toxic or unwanted intermediates ( Chen et al., 2013 ; Yang et al., 2016 ; Felczak et al., 2019 ). Therefore, in addition to the linear design of metabolic pathways in Z. mobilis , successful engineering must consider the spatial separation of introduced biosynthetic pathway enzymes to cope with challenges such as unproductive or harmful crosstalk ( Heinig et al., 2013 ). The co-localization of pathway enzymes and their substrates is an attractive approach for multi-enzymatic synthesis in engineered cells. The use of compartmentalization in metabolic engineering has been demonstrated to increase the production efficiency of different metabolites by taking advantage of the endogenous substrate pool in various organelles such as mitochondria ( Lv et al., 2016 ; Sheng et al., 2016 ), peroxisomes ( Gassler et al., 2020 ), and chloroplasts ( Wu et al., 2006 ). However, with the increasing use of industrial microorganisms to produce high value bioproducts, there is also a requirement to achieve a spatial organization within prokaryotic cells. Bacterial microcompartments ( Kerfeld et al., 2018 ; Sutter et al., 2021 ) provide a natural model for compartmentalization inside a prokaryotic cell. The utilization of these self-assembling organelles as scaffolds for metabolic enzymes is a sophisticated approach that is becoming widely useful ( Kirst and Kerfeld, 2019 ; Kerfeld and Sutter, 2020 ; Raba and Kerfeld, 2022 ). BMC shells natively sequester an enzymatic core that carries out a metabolic pathway. The shell is selectively permeable, functioning as a barrier between the encapsulated enzymes and the cytosol. They have been bioinformatically identified in the majority of bacterial phyla ( Sutter et al., 2021 ) and are known to be involved in CO 2 fixation in autotrophs (reviewed in Rae et al., 2013 ; Kerfeld and Melnicki, 2016 ; Liu, 2022 ) and in the catabolism of organic substrates such as 1,2-propanediol ( Bobik et al., 1999 ), ethanolamine ( Kofoid et al., 1999 ), small saccharides ( Petit et al., 2013 ; Erbilgin et al., 2014 ), taurine ( Burrichter et al., 2021 ), and aromatic compounds ( Doron et al., 2023 ). The shell of most BMCs is composed of three types of protein building blocks, which assemble into icosahedral bodies. These include a BMC-H monomer (pfam00936) that assembles into hexamers, BMC-T (2x pfam00936), a pseudohexamer formed from trimers, and BMC-P that assembles into pentamers and cap the vertices (pfam03319). A pore, typically formed at the cyclic symmetry axis of hexamers and pseudohexamers, and can vary in their size or charge, serves as a channel for metabolites to traverse the shell ( Kerfeld et al., 2018 ). The ability to encapsulate many enzymes within a selectively permeable, tunable shell has made the idea of repurposing BMC shells to encapsulate non-native enzymes highly attractive. The development of the synthetic model shell systems derived from the Pdu BMC ( Parsons et al., 2010 ; Nichols et al., 2020 ), carboxysome ( Cai et al., 2016 ; Sutter et al., 2019 ; Li et al., 2020 ), the metabolosome of Haliangium ochraceum (HO shells) ( Lassila et al., 2014 ; Sutter et al., 2017 ), or the GRM BMC ( Kalnins et al., 2020 ), as well as the ability to target non-native cargo into their lumen has paved the way towards designing novel nano bioreactors. Furthermore, in an effort to facilitate the encapsulation efficiency, which was relatively low when native encapsulation methods were used (reviewed in Aussignargues et al., 2015 ), various synthetic encapsulation methods were developed. One method involves the design of synthetic circularly permuted hexamer (CPH) with an inverted sidedness of its N- and C-terminal residues relative to wild type hexamer (WTH). The direct fusion of protein cargo to WTH from HO (BMC-H) or Pdu (PduA) systems or to their permuted versions, resulted in the displaying of the cargo on the external shell surface or the encapsulation of the cargo within the lumen, respectively ( Lee et al., 2018 ; Ferlez et al., 2019 ). Another method employs the incorporation of split bacterial adhesion domains, specifically SpyTag ( Zakeri et al., 2012 ) and SnoopTag ( Veggiani et al., 2016 ), into a luminal loop of the HO BMC-T shell protein, and its counterpart domain (SpyCatcher and SnoopCatcher) to a heterologous protein cargo. The interaction between the two domains results in a covalent link between the two proteins and was shown to improve the encapsulation efficiency of various fluorophores and enzymes ( Hagen et al., 2018 ; Kirst et al., 2022 ). Furthermore, the SnoopTag/SnoopCatcher system does not exhibit cross-reactivity with the SpyTag/SpyCatcher system, making it possible to simultaneously encapsulate multiple enzymes. In addition, fusing protein elements such as affinity tags to the C-terminus of shell proteins, such as BMC-H and BMC-P facilitated the purification of empty or loaded shells ( Hagen et al., 2018 ). Altogether, these features ( Figure 1 ) make the shells of BMCs to be an ideal platform for “bottom-up” approaches to construct synthetic BMCs carrying out entirely novel functions ( Kirst and Kerfeld, 2019 ; Kerfeld and Sutter, 2020 ). These include the construction of synthetic BMCs that encapsulate pyruvate decarboxylase and an alcohol dehydrogenase from Z. mobilis within Pdu shells for the production of ethanol ( Lawrence et al., 2014 ), the encapsulation of HydA, an [FeFe]-hydrogenase and ferrodoxin from the green alga Chlamydomonas reinhardtii , within α-carboxysome shells for the production of hydrogen ( Li et al., 2020 ), and the encapsulation of pyruvate formate lyase (PFL) and the acetyl-CoA producing enzyme phosphotransacetylase within HO shells for the production of pyruvate ( Kirst et al., 2022 ). FIGURE 1 Model of the HO synthetic shell with the functionalized building blocks that were engineered in E. coli and applied to Z. mobilis . Overview of the modifications of HO shell proteins. SpyTag and SnoopTag split adhesion domains were introduced into a loop within BMC-T 1 shell proteins to facilitate the encapsulation of cargo proteins. A Strep tag was added to the C-terminus of BMC-P or BMC-H to allow the rapid purification of the loaded shells. Protein cargo can be genetically fused to the C-terminus of WTH (cargo will be displayed on exterior surface of shell) or CPH (cargo will be encapsulated within the lumen of the shell). In this study, we applied tools for constructing and programming shells inside Z. mobilis . We show here that the expression of synthetic operons encoding for HO shell proteins in Z. mobilis enabled the purification of fully assembled shells and shells that lack pentamers (“uncapped”) at their vertices, which we refer to as wiffle balls. Furthermore, we demonstrated the potential of the Z. mobilis shells to encapsulate or display fluorophores as cargo. These results provide the proof-of-concept required to show that the BMC shell system can be a sophisticated compartmentalization strategy for improving bioproduct synthesis in the industrially relevant microorganism Z. mobilis .",
"discussion": "4 Discussion The potential for encapsulating synthetic biochemical pathways into BMC shells in industrially important bacterial hosts has many applications in metabolic engineering ( Kerfeld and Sutter, 2020 ; Stewart et al., 2021 ; Liu, 2022 ; Abrahamson et al., 2023 ). It is especially relevant to pathways with poor enzyme kinetics, or prone to crosstalk with endogenous host pathways or those that generate volatile or toxic intermediates that might disrupt the metabolism of the cell. Although the encapsulation of metabolic enzymes in BMC shells in non-native organisms has mostly been confined to E. coli including the construction of shell-based nano bioreactors for production of ethanol ( Lawrence et al., 2014 ), 1,2-propanediol ( Lee et al., 2016 ), hydrogen ( Li et al., 2020 ), and pyruvate ( Kirst et al., 2022 ), several recent studies have introduced BMC gene clusters or synthetic operons encoding BMC shell proteins also into various industrial bacterial hosts. These include the established industrial workhorse for the production of amino acids, Corynebacterium glutamicum ( Baumgart et al., 2017 ; Huber et al., 2017 ), the Gram-positive model organism Bacillus subtilis ( Wade et al., 2019 ), and several Pseudomonas species ( Graf et al., 2018 ). These studies demonstrated the assembly of shells or BMCs of either the Pdu system from Citrobacter freundii ( Huber et al., 2017 ), Salmonella enterica ( Graf et al., 2018 ), and the thermophile Parageobacillus thermoglucosidasius ( Wade et al., 2019 ), or the α-carboxysome shell from Halothiobacillus neapolitanus ( Baumgart et al., 2017 ). In this study, we took a synthetic biology approach and introduced the HO shell system into Z. mobilis . Our ultimate objective is to establish BMC-based spatial organization, with the long-term aim of minimizing the loss of intermediate metabolites and enhancing pathway flux in Z. mobilis . This can be done by localizing metabolic enzymes that catalyze sequential steps on the HO BMC shell and wiffle ball scaffolds. To utilize the HO shells and wiffle balls in Z. mobilis , it was first necessary to demonstrate the ability to express the different shell proteins in Z. mobilis and to subsequently purify the assembled shells using the CAP method ( Hagen et al., 2018 ). Our ability to identify the different shell components on SDS-PAGE following their purification on a StrepTrap affinity column, after adding a sucrose cushion step to get rid of unbound shell proteins ( Figure 2B ), as well as to visualize intact assembled shells on negatively stained grids ( Figure 2C ), confirm the successful assembly of HO shells in Z. mobilis . Furthermore, our results demonstrate the advantage of using the CAP method in purifying shells in a rapid and simple way from crude Zymomonas cell extract and offer an advantage over other shell systems that require tedious and long purification processes. By adding affinity tags to the C-terminus of HO-BMC-P or BMC-H, shells and wiffle balls can be efficiently purified and bioproducts that were produced within the shells can be rapidly extracted. This is especially valuable for bioproducts that are prone to degradation or oxidation. In addition to our ability to purify assembled shells or wiffle balls, it was also essential to validate the functionality of various scaffolding strategies that were developed for the HO shell system in E. coli over the years for targeting cargo proteins to the interior and exterior parts of the shells. These include the direct fusion of cargo to WTH or CPH proteins and the exploitation of the SpyTag-SpyCatcher/SnoopTag-SnoopCatcher split adhesion bacterial systems that were elegantly and uniquely incorporated into HO shells and wiffle balls. The HO shells are structurally characterized ( Sutter et al., 2017 ) showing that the N and C-termini of the HO hexamer are surface exposed. Additionally, previous studies confirmed the orientation of WTH and CPH-fused fluorophores as external and luminal-targeted cargo, respectively, using a proteolysis analysis ( Ferlez et al., 2019 ), and the orientation of the SpyCatcher-fused fluorophore as luminal using FRET analysis ( Kirst et al., 2022 ). The formation of small circular bodies in Z. mobilis cells expressing sc_sfGFP and shell proteins ( Figure 3E ) and the identification of additional protein bands with intrinsic sfGFP or mScarlet fluorescence signal on SDS-PAGE ( Figures 3F , 4 right panels) following purification from StrepTrap affinity column, demonstrate the targeting of fluorophores to shells. These findings serve as a proof-of-concept for our ability to assemble and purify shells with cargo on the exterior and interior surfaces of the shell in Z. mobilis . Furthermore, our ability to simultaneously encapsulate and decorate the external surface of the shells and wiffle balls with proteins of choice shows that the external surface of a shell can be functionalized with an enzyme that could potentially create a high local concentration of substrate proximal to the shell, which would enhance the enzymatic reactions of the encapsulated enzymes via increased diffusion of substrates into the shell. By achieving BMC shell-based compartmentalization in Z. mobilis and validating the functionality of the different scaffolding strategies, we are providing evidence for the feasibility of future design and construction of synthetic shell-insulated metabolic pathways of up to four enzymes (three encapsulated and one displayed) in Z. mobilis . This will further advance the use of biocatalyst unique characteristics that Z. mobilis has to offer for the industrial-scale production of biofuels and other valuable bioproducts. It is still debatable whether the uncapped shells should be defined as a separate compartment. At the very least, wiffle balls can be considered three-dimensional scaffolds for the immobilization and co-localization of cargo. In terms of a defined compartment, on the one hand, the absence of the pentamer in the shell vertices leaves a 5 nm hole that allows the crossing of oxygen, enzymes, or other metabolites into the shells. On the other hand, the encapsulation of the metabolic enzymes in close proximity to each other ensures a quick conversion of the intermediates and prevents their diffusion to competing off-branching pathways in the cytosol. This facilitates the continuation of the pathway and increases final product yield. Theoretically, an isolated wiffle ball can be constructed if the regeneration of co-factors occurs within the compartment by the encapsulated enzymes. This was demonstrated with the activity of the sFUT module, where the acetyl-CoA, which is condensed with formate to make pyruvate by PFL activity, is regenerated by the activity of the encapsulated phosphotransacetylase ( Kirst et al., 2022 )."
} | 4,449 |
23833703 | null | s2 | 5,312 | {
"abstract": "A spider's ability to store silk protein solutions at high concentration is believed to be related to the protein's terminal domains. It has been suggested that a shift in salt concentration and pH can have a significant influence on the assembly process. Based on experimental data, a model has been proposed in which the N-terminal domain exists as a monomer during storage and assembles into a homodimer upon spinning. Here we perform a systematic computational study using atomistic, coarse-grained and well-tempered metadynamics simulation to understand how the NaCl concentration in the solution affects the N-terminal domain of the silk protein. Our results show that a high salt concentration, as found during storage, weakens key salt bridges between the monomers, inducing a loss in bond energy by 28.6% in a single salt bridge. As a result dimer formation is less likely as 35.5% less energy is required to unfold the dimer by mechanical force. Conversely, homodimer formation appears to be more likely at low salt concentrations as the salt bridge stays at the lower energy state. The link between salt concentration, structure and stability of the N-terminal domain provides a possible mechanism that prevents premature fiber formation during storage."
} | 316 |
19874919 | null | s2 | 5,313 | {
"abstract": "Water-insoluble regenerated silk materials are normally produced by increasing the beta-sheet content (silk II). In the present study water-insoluble silk films were prepared by controlling the very slow drying of Bombyx mori silk solutions, resulting in the formation of stable films with a predominant silk I instead of silk II structure. Wide angle X-ray scattering indicated that the silk films stabilized by slow drying were mainly composed of silk I rather than silk II, while water- and methanol-annealed silk films had a higher silk II content. The silk films prepared by slow drying had a globule-like structure at the core surrounded by nano-filaments. The core region was composed of silk I and silk II, surrounded by hydrophilic nano-filaments containing random turns and alpha-helix secondary structures. The insoluble silk films prepared by slow drying had unique thermal, mechanical and degradative properties. Differential scanning calorimetry results revealed that silk I crystals had stable thermal properties up to 250 degrees C, without crystallization above the T(g), but degraded at lower temperatures than silk II structure. Compared with water- and methanol-annealed films the films prepared by slow drying had better mechanical ductility and were more rapidly enzymatically degraded, reflecting the differences in secondary structure achieved via differences in post processing of the cast silk films. Importantly, the silk I structure, a key intermediate secondary structure for the formation of mechanically robust natural silk fibers, was successfully generated by the present approach of very slow drying, mimicking the natural process. The results also point to a new mode of generating new types of silk biomaterials with enhanced mechanical properties and increased degradation rates, while maintaining water insolubility, along with a low beta-sheet content."
} | 472 |
29142825 | PMC5678820 | pmc | 5,314 | {
"abstract": "Metabolic engineering of microbial cell factories for the production of heterologous secondary metabolites implicitly relies on the intensification of intracellular flux directed toward the product of choice. Apart from reactions following peripheral pathways, enzymes of the central carbon metabolism are usually targeted for the enhancement of precursor supply. In Pseudomonas putida , a Gram-negative soil bacterium, central carbon metabolism, i.e., the reactions required for the synthesis of all 12 biomass precursors, was shown to be regulated at the metabolic level and not at the transcriptional level. The bacterium's central carbon metabolism appears to be driven by demand to react rapidly to ever-changing environmental conditions. In contrast, peripheral pathways that are only required for growth under certain conditions are regulated transcriptionally. In this work, we show that this regulation regime can be exploited for metabolic engineering. We tested this driven-by-demand metabolic engineering strategy using rhamnolipid production as an example. Rhamnolipid synthesis relies on two pathways, i.e., fatty acid de novo synthesis and the rhamnose pathway, providing the required precursors hydroxyalkanoyloxy-alkanoic acid (HAA) and activated (dTDP-)rhamnose, respectively. In contrast to single-pathway molecules, rhamnolipid synthesis causes demand for two central carbon metabolism intermediates, i.e., acetyl-CoA for HAA and glucose-6-phosphate for rhamnose synthesis. Following the above-outlined strategy of driven by demand, a synthetic promoter library was developed to identify the optimal expression of the two essential genes ( rhlAB ) for rhamnolipid synthesis. The best rhamnolipid-synthesizing strain had a yield of 40% rhamnolipids on sugar [Cmol RL /Cmol Glc ], which is approximately 55% of the theoretical yield. The rate of rhamnolipid synthesis of this strain was also high. Compared to an exponentially growing wild type, the rhamnose pathway increased its flux by 300%, whereas the flux through de novo fatty acid synthesis increased by 50%. We show that the central carbon metabolism of P. putida is capable of meeting the metabolic demand generated by engineering transcription in peripheral pathways, thereby enabling a significant rerouting of carbon flux toward the product of interest, in this case, rhamnolipids of industrial interest.",
"conclusion": "4 Conclusion In this work, we showed that the concept of “driven by demand” described for E. coli by Koebmann et al. (2002) could also be exploited for flux rerouting in P. putida . To rapidly implement heterologous pathways, tools for creating the required demand are becoming important ( Zobel et al., 2015 , Nikel et al., 2014 ). Interestingly, in the engineered microorganism, the production of the product of choice is uncoupled from growth, which might be caused by overcoming the host's intrinsic regulation cascades by introducing the target genes under the control of a synthetic promoter. The results suggest that P. putida is a suitable host for biotechnological applications. Its versatile metabolism, which responds to the demand created by heterologous pathways, is well suited for metabolic engineering. Metabolic engineering of bacteria yielding a production strain, which is competitive on an industrial scale, is a complex task. Even for scientific groups with both the equipment and the required expertise, this process requires considerable time and effort, as demonstrated by the excellent extant examples ( Becker et al., 2011 , Becker and Wittmann, 2012a , Becker and Wittmann, 2012b , Buschke et al., 2013 ). P. putida might provide a good starting point for establishing novel synthesis pathways via classic metabolic engineering strategies.",
"introduction": "1 Introduction Our society relies heavily on crude oil and the products derived thereof. To reduce this dependence, sustainable processes based on renewable resources must be established. One such method is whole-cell biocatalysis using sugars as a substrate. A bacterial species with excellent characteristics for this technique is Pseudomonas putida , a Gram-negative, saprotrophic soil bacterium with a very versatile metabolism and high tolerance to organic solvents ( Ramos et al., 1995 ). These characteristics have made P. putida a much discussed host for industrial applications ( Tiso et al., 2015 ), although only a few examples exist thus far. Metabolic engineering of secondary metabolite producers implicitly relies on high flux through central carbon metabolism (CCM). This high flux caused by the demand for carbon and energy for the synthesis of the molecule of interest, however, is rarely matched, requiring substantial improvements in CCM operation. The reactions of the CCM are providing the twelve precursors for biomass, i.e., for proteins, nucleic acids, polysaccharides, and lipids ( Noor et al., 2010 ). An excellent example of rational strain engineering by optimizing the flux distribution and channeling it to the product of choice was reported by Becker et al. (2011) . The authors introduced 12 genome-based changes, including the overexpression of five genes encoding for enzymes fueling precursor-synthesizing pathways. In addition, the deletion or down-regulation of two genes encoding enzymes catalyzing competing reactions were introduced, yielding an l -lysine-overproducing strain of Corynebacterium glutamicum . In contrast with this example, we here propose an approach that does not require substantial modifications of the host strain but, rather, relies on the capability of the organism to reroute flux driven by a given (in our case, engineered) demand. The strategy used here exploits the findings of Koebmann et al., (2002) , who observed a strong increase in flux through glycolysis in Escherichia coli after introducing an ATP sink, thus discovering the concept of “driven by demand.” It was recently shown that the CCM in P. putida is not transcriptionally regulated but, rather, is metabolically regulated ( Sudarsan et al., 2014 ). Despite substantial rerouting of flux during growth on glucose, fructose, and benzoate, the transcription levels of the genes for CCM remain constant. Notably, the carbon substrate degradation pathways beta-ketoadipate and Entner-Doudoroff are transcriptionally regulated ( Koebmann et al., 2002 ). Indeed, there is also evidence from extreme growth conditions (e.g., growth in the presence of a second phase of octanol) that P. putida can match metabolic demand by tripling the glucose uptake rate without producing any side products; thus, only biomass and CO 2 are formed by this bacterium ( Blank et al., 2008 ). An example of this strategy is an engineered P. putida that hyper-produces polyhydroxyalkanoate (PHA) ( Poblete-Castro et al., 2013 ). The authors deleted one gene ( gcd , encoding for glucose dehydrogenase), which led to the rerouting of fluxes to the desired product. They were able to increase PHA accumulation by 100%. In contrast to these results, peripheral pathways, which are not part of the CCM, are not as easily modified. Establishing a high production rate of aromatics from sugars in P. putida again entails substantial modifications to reroute intracellular flux resulting from the regulation of the synthesis pathways of aromatics. This regulation relies on the biosynthesis pathways of specific amino acids, which are regulated allosterically ( Wierckx et al., 2005 ). To verify the engineering-by-demand approach, we chose rhamnolipid synthesis as an example. It was earlier shown that P. putida is able to produce rhamnolipids after introducing two genes of the rhamnolipid synthesis pathway from P. aeruginosa, encoding RhlA and RhlB ( Wittgens et al., 2011 , Ochsner et al., 1994 ). The demand for precursors (i.e., increased flux through the rhamnose activation pathway and de novo lipid synthesis) varied according to the different promoter strengths of the rhlAB operon. The flux redistribution is estimated and the results are discussed in the context of the implications of the driven-by-demand concept for constructing superior production strains based on P. putida .",
"discussion": "3 Results and discussion 3.1 Synthetic promoter library The expression vector used previously was pVLT31 ( de Lorenzo et al., 1993 ) featuring the ori RSF1010 and the inducible tac promoter ( de Boer et al., 1983 ). This vector was used here as a reference. The newly constructed plasmid is based on pBBR1-MSC3 ( Kovach et al., 1995 ), containing the pBBR1 ori. The native RBS of the genes were kept. With P. putida carrying the synthesis pathway under the control of a synthetic promoter library indeed high rhamnolipid producing mutants were identified. From the first screening of a couple of thousand mutants using the blood agar assay, only 75 transformants were found to produce rhamnolipids (these results have partly been published in Beuker et al. (2016 ). 23 of these were characterized in more detail. Shake flask experiments were carried out with these strains to determine physiological data on rhamnolipid production. Surprisingly nine strains did not produce detectable amounts of rhamnolipids. The remaining 14 transformants covered a rhamnolipid titer range from 0.05 g/L to 2.8 g/L ( Fig. 2 ). While the transformant with the reference expression system, featuring a tac promoter, only produced 0.31 g/L rhamnolipids ( Wittgens et al., 2011 ), the best producing transformant carrying the variant no. eight of the synthetic promoter library produced up to 2.8 g/L and was called P. putida KT2440 pSynPro8. This microbial cell factory, with its constitutive expression system features simplified handling, as induction is no longer required. Fig. 2 Final rhamnolipid titers of P. putida with different synthetic promoters. The previously used tac promoter based system served as reference. The error bars represent the deviation from the mean of two biological replicates. Fig. 2. Seven promoters were chosen for sequencing, covering the whole range of rhamnolipid titers. The data shows, that indeed the −35 and −10 box remained unchanged, while the randomized regions featured great variations in nucleotides. As all these promoters showed rhamnolipid production during the first screening, one might conclude that only intact promoters lead to the production of rhamnolipids. Table SynPro8: AGCTC TTGACA AGGTCGGAAAATTGAAG TATAAT ATCAGT SynPro5: TTTCC TTGACA AGCCTAGTTTCGCCATT TATAAT GACTCG SynPro16: GTTGA TTGACA AAGCGCTTACCTCTTTC TATAAT ATAGAG SynPro1: GGTGG TTGACA TTGGCATTACAACGTAT TATAAT TTAGCG SynPro11: TAGAG TTGACA CACCTTCGGGTGGGCCT TATAAT ACTCGC SynPro7: TATAT TTGACA GAACCCCTGCAGACGTA TATAAT ATGGTG SynPro15: TACGC TTGACA TCGTGCGCCGGGCTGGT TATAAT GCCGAA 3.2 Rhamnolipid-producing P. putida With the best performing expression system pSynPro8, P. putida produced under reference conditions (10 g/L glucose in LB medium) approximately 3 g/L rhamnolipids ( Fig. 3 ), corresponding to a carbon yield of 40% [Cmol RL /Cmol Glc ], which is approximately 55% of the theoretical yield. Whereas the titers obtained with the native producer were higher with plant oils as carbon sources (>100 g/L), the carbon yield of P. aeruginosa was 7% [Cmol RL /Cmol Glc ], less than the 10% of the stoichiometric theoretical yield ( Müller et al., 2010 ). Fig. 3 Rhamnolipid production with P. putida KT2440 pSynPro8. Development of biomass (rectangles, ■), rhamnolipid (triangles, ▲), and glucose (diamonds, ♦) concentrations. The experimental data are depicted as symbols, and the lines present the fitted courses. The CDW trend was determined using a logistic growth model. A multivariable least squares fit was used to illustrate the development of all three fermentation parameters depending on each other, according to Wittgens et al. (2011) . The error bars represent the deviation from the mean of two biological replicates. CDW, cell dry weight. Fig. 3. The titer achieved here was the highest reported using a recombinant rhamnolipid producer with glucose as a carbon source. Compared to our first strain P. putida KT42C1 pVLT31_ rhlAB ( Wittgens et al., 2011 ), a doubling in titers could be achieved (3 g/L instead of 1.5 g/L). As a result of the high titer and the short fermentation time, this new microbial cell factory featured a specific rhamnolipid production rate, which was approximately three times higher than it was with the first strain (47 mg/(g CDW h) instead of 18 mg/(g CDW h)). Strikingly, this rate was also approximately 75% higher than the rate that the wild-type producer features (27 mg/(g CDW h)) ( Table 3 ). We would like to emphasize that the only alteration of the organism was the overexpression of the two dedicated genes rhlA and rhlB , resulting in the substantial production of a secondary metabolite in a host that generally produces biomass and CO 2 . Apparently, cell growth was limited after approximately 5 h. This behavior is often exhibited in cultivations with complex media, as shifting between carbon sources occurs. Once the preferred carbon source is depleted, the catabolism switches to the next carbon source, which is reflected in the growth curve. Consequences in the context of the described experiment could be reduced rhamnolipid production. On the contrary, an alternative effect could be enhanced rhamnolipid production, as limited growth frees more resources for rhamnolipid synthesis. Indeed an increase in the rhamnolipid production rate, indicated by a deviation of the experimental data above the fitted line can be inferred. 3.3 Meeting metabolic demands We observed in the above experiments an increased glucose uptake rate of 1.2 mmol/(g CDW h) for pPS05 and 3.2 mmol/(g CDW h) for pSynPro8, which we here investigate conceptually. Can the metabolic network operation in P. putida be hijacked by creating demand for central carbon metabolism (CCM) intermediates? We previously showed that energetic demand could be met by P. putida by increasing the glucose uptake rate dramatically, for example, in response to a second phase of octanol ( Blank et al., 2008 ) or the uncoupler 2,4-dinitrophenol (DNP) ( Ebert et al., 2011 ). To evaluate whether the metabolism of the P. putida used here, grown on a complex medium (e.g., amino acids available) and complemented with glucose, responds comparably, we added alternating DNP concentrations. When adding 700 mg/L DNP to P. putida KT2440 growing in LB medium supplemented with 10 g/L glucose, the strain had a glucose uptake rate of 2.0 mmol/(g CDW h) instead of 1.1 mmol/(g CDW h) without DNP. At a concentration of 1,100 mg/L DNP, the glucose uptake rate reached 2.2 mmol/(g CDW h). This increase in glucose uptake rate did not affect the growth rates, which were 0.86 h −1 (no DNP), 0.88 h −1 (700 mg/L DNP), and 0.79 h −1 (1,100 mg/L DNP) ( Fig. 4 ). Importantly, no byproduct formation was observed, consistent with Blank et al. (2008 ) and Ebert Ebert et al. (2011 ). Hence, creating a sink for NADH by the addition of an uncoupler resulted in a doubling of the glucose uptake rate. This finding provides strong support that the metabolic network operation of P. putida can be substantially altered by the here-exploited concept of driven by demand. Fig. 4 2,4-Dinitrophenol (DNP) addition leads to enhanced glucose uptake rates. The specific glucose uptake rate is shown in white, and the growth rate is depicted by the black-filled columns. P. putida KT2440 pPS05 was cultivated without DNP as a reference and with 700 and 1,100 mg/L DNP, according to Ebert et al. (2011) . The error bars represent the deviation from the mean of two biological replicates. Fig. 4. 3.4 Hijacking central carbon metabolism operation Can the observed increase in glucose uptake rate be exploited for the production of valuable chemicals? We previously reported that the CCM in P. putida is, under many conditions, not regulated transcriptionally but, rather, at the metabolic (and potentially posttranslational) level. In contrast, peripheral anabolic and catabolic pathways are transcriptionally regulated ( Sudarsan et al., 2014 ). This organization of the metabolic network allows for rapid flux rerouting to adapt to ever-changing growth conditions. We here argue again that these flux changes are the result of changing metabolic demands ( Table 2 ). Table 2 Changing flux through CCM during growth (µ=0.1 1/h) on different carbon sources in P. putida KT2440 ( Sudarsan et al., 2014 ). PP – pentose phosphate, TCA – tricarboxylic acid. Table 2. Substrate Flux through pathway [mmol/(g CDW h)] PP pathway Lower glycolysis TCA cycle Glucose 0.01 2.13 2.98 Fructose 0.03 1.53 1.87 Benzoate 0.00 0.18 0.57 Consequently, we examined whether this structural organization of the metabolic network explained the high performance of the rhamnolipid-synthesizing strain ( Fig. 3 ). We introduced the genes for mono-rhamnolipid synthesis into P. putida ( rhlA and rhlB ), thereby creating additional demand in the CCM for glucose-6-phosphate (for rhamnose synthesis) and acetyl-CoA (for hydroxy-fatty acid production via de novo lipid synthesis) ( Fig. 5 ). Fig. 5 Rhamnolipid biosynthesis pathway. The blue lines depict the CCM after Sudarsan et al. (2014) , including the pentose phosphate (PP) pathway and tricarboxylic acid (TCA) cycle, and the brown lines represent the Entner-Doudoroff (ED) pathway. The green and the purple lines indicate the rhamnolipid precursor-providing pathways: the rhamnose pathway, and fatty acid biosynthesis, respectively. The red lines show the competing polyhydroxyalkanoate (PHA) production, and the orange lines symbolize the introduced rhamnolipid (RL) synthesis pathway. The recombinant enzymes (RhlA and RhlB) originating from P. aeruginosa and introduced in P. putida by the encoding genes are indicated in orange. These were the only genetic modifications implemented. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Fig. 5. To examine different demands, i.e., different rhamnolipid production rates, we used the two plasmids pSynPro8 and pPS05 and two strains, namely, the reference P. putida KT2440 and the derivative P. putida KT40CZC. In P. putida KT40CZC, the PHA synthesis operon is deleted ( Escapa et al., 2012 ). PHA synthesis starts from activated hydroxy-fatty acids competing directly with rhamnolipid synthesis for the common precursor. Quantitative physiology experiments allowed for the estimation of flux via the precursor-supplying pathways, the glucose uptake rate, and the growth rate. For comparison, the physiology of the reference strain P. putida KT2440 not producing rhamnolipids was examined. It was discovered that P. putida KT40CZC was better suited for rhamnolipid synthesis with the new expression plasmid pPS05 than the wild-type strain ( Table 3 ). This recombinant strain has a higher specific production rate and also reaches a higher titer. Table 3 Growth and production parameters of rhamnolipid synthesis. For comparison, wild-type P. aeruginosa PA01 is listed in line 1. Table 3. Organism Medium Substrates Cell Dry Weight Maximal Titer Carbon Yield a Process Time Space-Time Yield Specific RL-Prod. Rate b Reference Substance [g/L] [g CDW /L] [g RL /L] [Cmol RL /Cmol subs ] [h] [mg RL /(L h)] [g/(g CDW h)] P. aeruginosa PA01 MS Sunflower Oil 250 16.3 39.0 0.07 (8%) 90 433.3 0.027 Müller et al. (2010 ) P. putida KT2440 pSynPro8 LB Glucose 12 3.1 3.2 0.40 (55%) 22 146.4 0.047 Wittgens (2013 ) P. putida KT40CZC pPS05 LB Glucose 11 3.4 2.4 0.35 (48%) 23 104.3 0.031 This study P. putida KT2440 pPS05 LB Glucose 11 4.5 2.2 0.32 (44%) 22 100.0 0.022 This study LB – Lysogeny broth, MS – Mineral salts. a For the calculation of yields during production on complex media, it was assumed that rhamnolipids were synthesized from glucose, whereas other medium components were utilized for cell growth. The numbers in parentheses show the percentages of the theoretical maximum. b The specific rhamnolipid production rate was calculated as the average over the entire fermentation time using the maximal rhamnolipid titer and the maximal cell dry weight determined. With an increasing rhamnolipid production rate, the glucose uptake increased while the growth rate remained constant ( Fig. 6 ). In the best producing strain with a rhamnolipid production rate of 0.1 mmol/(g CDW h), the glucose uptake increased by 24% to 1.3 mmol/(g CDW h) compared to the non-producing strain. P. putida KT2440 pPS05 produced rhamnolipids with a glucose uptake rate of 1.2 mmol/(g CDW h), which is 12% more than the wild-type strain. These findings are a strong indication that flux through the CCM is indeed increased. The additional glucose is used to satisfy the increased demand created by the production of the rhamnolipids. Fig. 6 Performance parameters of rhamnolipid producers compared to the wild-type strain. The black-filled columns represent the growth rate, and the unfilled columns indicate the glucose uptake rate. On the second y-axis, specific rhamnolipid production is plotted. The respective columns are filled in gray. For better comprehension, the second y-axis is also drawn in gray. The error bars represent the deviation from the mean of two biological replicates. Fig. 6. To assess whether the extra glucose, which is taken up is directed to rhamnolipid synthesis or just burned and oxidized to carbon dioxide, CO 2 production was measured in a separate experiment. As can be seen, carbon dioxide production of the reference P. putida KT2440 is higher compared to the rhamnolipid producer ( Fig. 7 ). The reduction in CO 2 formation might be a response of P. putida to the availability of an additional redox sink, namely rhamnolipid synthesis. The reference strain oxidizes glucose to CO 2 via the tricarboxylic acid (TCA) cycle. To regenerate the reduced redox cofactors and thereby balance the electrons, the electron transport chain is employed by P. putida using oxygen as terminal electron acceptor. The rhamnolipid-producing strain can use the rhamnolipids as electron acceptors as the carbons in the fatty acid moieties are higher reduced than glucose. Thus, we assume that this strain under the given conditions does not need the electron transport chain to the same extend as the reference strain, with the result of lower CO 2 formation. Fig. 7 Carbon dioxide produced during cultivation by P. putida KT2440 (gray line) and P. putida KT2440 pPS05, which is capable of rhamnolipid synthesis (black line). The deviation shown in light gray originates from the mean of two biological replicates. Fig. 7. As less glucose is wasted for the generation of CO 2 , the rhamnolipid production strain should be able to allocate more carbon to the synthesis of rhamnolipids. These considerations again hint to the conclusion that via reorganization of metabolic fluxes the cell is able to meet the opposed demand. Based on the physiological data, we estimated the flux through the pathways providing the precursors for rhamnolipid production, i.e., activated dTDP-rhamnose, and the hydroxy-fatty acids for HAA synthesis ( Fig. 8 ). The P. putida wild type not producing rhamnolipids still synthesizes rhamnose as part of the lipopolysaccharides on the outer cell wall. A constant synthesis rate was estimated based on the growth rate and on the approximate rhamnose content in the lipopolysaccharides. For de novo synthesis, basic activity was calculated via the fatty acid share in the biomass. When introducing the enzymes for rhamnolipid production, the particular flux via the activated rhamnose pathway was dramatically enhanced. Moreover, de novo fatty acid synthesis increased by 50% in the best producing strain. Fig. 8 Estimated intracellular fluxes in P. putida strains with different activity levels of rhamnolipid production. The black-filled columns represent the rate via the rhamnose pathway, and the gray-filled columns indicate the de novo fatty acid synthesis rate (second y-axis). For better comprehension, the second y-axis is also shown in gray. The error bars represent the deviation from the mean of two biological replicates. Fig. 8. Again, these enhancements of flux in the metabolic network occurred without any engineering of the CCM. Rather, the metabolism met the demand created, which was possible because P. putida is capable of up-regulating its CCM on a metabolic level without altering gene expression levels ( Sudarsan et al., 2014 ). Because rhamnose is synthesized from glucose-6-phosphate and fatty acid de novo synthesis also draws carbon from CCM, and furthermore, growth remains constant, the flux distribution in the CCM is clearly altered to meet the RL synthesis demand. Metabolic engineering strategies often involve the increase of flux in precursor-providing pathways. To identify valuable targets for overexpression, metabolic control analysis is frequently performed. Metabolic control analysis examines the underlying reaction network of a given pathway to distinguish the enzymatic step that controls the overall production rate. This specific reaction rate can then be enhanced, which should lead to a higher production rate toward the product of choice. This process is continued iteratively until no further enhancement can be achieved ( Stephanopoulos et al., 1998 ). To increase rhamnolipid production, it would thus be advisable to overexpress the entire rml operon harboring the genes responsible for the synthesis of the activated dTDP-rhamnose from glucose-1-phosphate or the pyruvate dehydrogenase, which is the first step from pyruvate toward de novo lipid synthesis ( Scriba and Holzer, 1961 ). A substantial enhancement of flux in glucose-6-phosphate- and pyruvate-supplying pathways via CCM is required to sustain an unchanged rate of growth and to generate the resources for the heterologous production of rhamnolipids ( Fig. 5 ). We hence conclude that CCM operation in P. putida is driven by the demand created. Again, the mechanistic explanation might be that the CCM in this organism is regulated at the metabolic level ( Sudarsan et al., 2014 ). Hence, generating additional demand by introducing enzymes deriving metabolites from CCM causes P. putida to increase metabolic flux. In the presented example, we overexpressed two enzymes producing rhamnolipids, which burdened CCM at glucose-6-phosphate and acetyl-CoA, resulting in flux increases by 300% and 50%, respectively. There is however one major difference to the experiment carried out by Sudarsan et al., (2014) . While they were working in a chemostat environment at constant growth rate, the experiments described here were carried out in batch cultures, featuring different growth phases. In the previous study, the putative impact of growth rate on transcriptional regulation was thus excluded by the experimental setup, while this has not been done in the experiments carried out in this study. Differences in growth could thus be partly responsible for the observed phenomena. The conditions under which an organism responds to being driven by demand is not generally known. Pseudomonas, as a soil bacterium, lives in environments where nutrients are scarce and must compete for these resources. Other industrial microorganisms, such as E. coli , Lactobacillus , and Saccharomyces cerevisiae, have been isolated from nutrient-rich environments, such as the lower intestines of mammals, milk, and crops, respectively. With many resources in abundance, these organisms might have been selected for rate rather than for efficiency (yield) ( Novak et al., 2006 , Jessup and Bohannan, 2008 ). A good example for the high efficiency of P. putida is its glucose uptake system. Whereas E. coli and other microorganisms absorb glucose at high rate, P. putida converts part of the glucose into gluconate and further into ketogluconate ( del Castillo et al., 2007 ). This process has two advantages in a competitive environment. First, while growing on a preferred carbon source, the bacterium renders this carbon source useless for competitors not able to absorb gluconate or ketogluconate. Second, gluconate and ketogluconate are organic acids and thus greatly lower the pH. A low pH not only stops the growth of some organisms but also frees some of the scarce resources, such as iron and phosphate ( Rodriguez and Fraga, 1999 ). Another interesting feature of the glucose uptake system of P. putida is its superior glucose affinity. Glucose uptake in P. putida into the periplasmic space occurs through outer membrane porins encoded by oprB1 and oprB2 . The importation into the cytosol is mediated through an ABC uptake system encoded by the open reading frames PP1015 to PP1018 ( del Castillo et al., 2007 ). ABC transporters in Gram-negative bacteria often feature a binding protein that is located in the periplasm. This binding protein has high affinity for the specific substrate ( Boos et al., 1996 ). The transport system of Thermococcus litoralis, featuring a similar binding protein, for example, has a K m of approximately 20 nM, whereas the K m of the glucose uptake system of E. coli exhibits 1 µM ( Xavier et al., 1996 ). After binding the substrate, the actual transport is driven by the hydrolysis of ATP molecules ( Davidson and Chen, 2004 ). This biochemical investment allows for glucose uptake when concentrations are very low. These two examples show the adaptation of P. putida to environments where nutrients are scarce. Under such conditions, changes in carbon sources are frequent. Whenever a change in the environment occurs, P. putida is able to reconfigure its CCM rapidly without relying on transcriptional regulation. In the context of heterologous rhamnolipid production, which is an engineered demand, P. putida increases carbon uptake while maintaining a high growth rate. The metabolism simply reacts to the “theft” of precursors needed for growth by increasing the flux through the essential precursor pathways. 3.5 Glucose satisfies the enhanced carbon demand As described above, the rate of glucose uptake increases when an additional demand is created. Is this glucose directed toward rhamnolipid synthesis and hence to the created demand, or is it simply distributed throughout the bacterium's metabolism? Via stable isotope-labeling experiments and the analysis of the resulting labeling patterns in the rhamnolipid molecules, the carbon source used for rhamnolipid synthesis was determined. For the corresponding experiments, on the one hand, minimal medium supplemented with unlabeled glucose and, on the other hand, LB medium with uniformly 13 C-labeled glucose were used. Two samples were obtained: one in the exponential phase and the other in the stationary phase. At the latter time point, the glucose was completely consumed. The synthesized rhamnolipids were analyzed by HPLC coupled to mass spectrometric detection (LC–MS). The produced biomass was investigated by gas chromatography coupled to mass spectrometry (GC–MS) measurement. Sections of the LC-MS mass spectra at the retention time of Rha-C 10 -C 10 (11.8 min) are depicted in Fig. 9 . Fig. 9 Mass spectra of LC–MS measurements of the rhamnolipid Rha-C 10 -C 10 . The mass spectra show data for the rhamnolipid Rha-C 10 -C 10 synthesized by P. putida KT2440 pPS05 grown in LB or minimal medium with unlabeled or 13 C-labeled glucose in two distinct growth phases: a) minimal medium and 12 C-glucose, exponential phase; b) minimal medium and 13 C-glucose, exponential phase; c) LB medium and 13 C-glucose, exponential phase; d) minimal medium and 12 C-glucose, stationary phase; e) minimal medium and 13 C-glucose; stationary phase; and f) LB medium and 13 C-glucose, stationary phase. Isotope distribution in a) and d) reflects the natural abundance of 13 C (1.1%), which corresponds to approximately 29% for 26 carbon atoms of m / z 504. cps – counts per second. Fig. 9. The molecular weight of the Rha-C 10 -C 10 rhamnolipid molecule is 504 u. It is detected as a deprotonated molecule (mass to charge ratio [ m/z ] of 503) during LC-MS analysis with electrospray ionization. In the mass spectra shown in Fig. 9 , the measured signals are higher than m/z 503 caused by 13 C-incorporation from the labeled glucose precursor. The examined rhamnolipid Rha-C 10 -C 10 contains 26 carbon atoms; thus, signals from m/z 503 to m/z 529 can occur. A fully labeled rhamnolipid would give rise to m/z 529. Mass spectra a and d show the rhamnolipid Rha-C 10 -C 10 synthesized from unlabeled glucose in different growth phases as a reference. The highest peak is at m/z 503. Mass spectrum b, obtained from cultivation in minimal medium with fully labeled glucose, should show only the m/z 529 signal. However, as shown in Fig. 9 b, the measured rhamnolipids show a distribution with its maximum at m/z 517. The explanation for this distribution in partially labeled rhamnolipid is the presence of unlabeled biomass from the preculture and the percentage of unlabeled glucose, which is contained in the 13 C-labeled glucose. The enrichment of 13 C-labeled glucose is 99% for each carbon atom, resulting in 94% (0.99 6 ) completely labeled glucose molecules. Interestingly, the mass spectra for the rhamnolipid derived from the cultivation with 13 C-labeled glucose with minimal medium ( Fig. 9 b) and LB medium ( Fig. 9 c) are very similar, indicating that during the exponential phase, the main source for rhamnolipid production is glucose, whereas the components of the LB medium are consumed for cell growth. Spectrum e shows the expected distribution: almost exclusively fully labeled rhamnolipid Rha-C 10 -C 10 . The distribution in spectrum f is also shifted toward higher masses, again showing that the main carbon source for rhamnolipid synthesis is glucose. During the exponential phase ( Fig. 9 c), this leads to a spectrum similar to the spectrum of the rhamnolipid when using isotopically labeled glucose as sole carbon source ( Fig. 9 b). Later, when the unlabeled compounds are further attenuated by the depletion of media components and the comparatively higher influx of labeled carbon atoms, the labeling pattern of the rhamnolipid shifts to higher masses ( Fig. 9 f). An interesting observation is that, in the mass spectra, the m/z values with even numbers also appear, despite de novo fatty acid synthesis assembling fatty acids using C 2 molecules as basic modules. In theory, the labeling of the rhamnolipid molecules should thus increase in steps of two. The unlabeled carbon that is incorporated into the rhamnolipid molecule, however, also contains natural 13 C-isotopes. The natural abundance of 13 C is 1.08. In the rhamnolipid molecule, which contains 26 carbon atoms, this results in almost 29% of the molecules having one 13 C-isotope and approximately 4% of the total rhamnolipid molecules carrying two 13 C-isotopes. Furthermore, isotope ratios of O ( 16 O=100%; 17 O=0.04%; 18 O=0.21%;) and H ( 1 H=100%; 2 H=0.01%) contribute to the signals. This naturally occurring isotope distribution is reflected in mass spectra a and d. We also performed the reverse test, measuring the labeling in the proteinogenic amino acids. The fractional labeling of the examined amino acids showed that most amino acids were absorbed from the medium, whereas only a minor fraction was synthesized de novo from glucose ( Fig. 10 ). Whereas some amino acids showed a fractional labeling of more than 0.2, at least half of the analyzed amino acids featured a fractional labeling less than 0.1; hence, more than 90% of these amino acids were absorbed from the medium. Fig. 10 Fractional labeling of amino acids during growth on LB medium with 13 C-labeled glucose. The fractional labeling indicates the fraction of carbon atoms in the respective molecule that are 13 C-labeled. The error bars represent the deviation from the mean of two biological replicates. Fig. 10. To conclude, we showed that the synthesized rhamnolipids mainly originated from the 13 C-labeled glucose, whereas the biomass predominantly originated from unlabeled medium compounds. Hence, the increased glucose uptake caused by the created demand was most likely used by the cell to satisfy this demand. The sugars were directed by the metabolism of P. putida toward the reactions providing precursors for rhamnolipid synthesis. Only a minor fraction of the sugar was used for biomass production. In addition, the carbon dioxide production experiments point to the conclusion that rhamnolipid synthesis offers a possibility for the cell to use the offered carbon source more efficiently. Thus, the production strain is able to invest more glucose for the synthesis of rhamnolipids. The yield of product on substrate is an important parameter in biocatalysis. One challenge is the reduction of yield caused by the growth of the whole-cell catalyst. Hence, production under reduced- or non-growth conditions is an engineering goal. We reported previously that engineered P. putida KT2440, under reference conditions, produced rhamnolipids independently of growth ( Wittgens et al., 2011 ). The carbon source used (LB or glucose) was inferred from CO 2 evolution. Here, we report the direct measurements of the 12 C/ 13 C-labeling of rhamnolipids and the produced biomass. The detected labeling patterns supported the hypothesis that rhamnolipid synthesis occurred independently of growth. When supplying LB medium and 13 C-labeled glucose, the majority of the rhamnolipid molecules contained labeled 13 C-carbon atoms emanating from the labeled glucose. The fractional labeling in the exponential growth phase of the C 10 -C 10 rhamnolipids was 0.63. Only a small part (approximately 15%) of the rhamnolipid molecules carried ten or fewer labeled carbon atoms. Hence, the compounds from the LB medium contributed only a small fraction to rhamnolipid synthesis. In contrast, only 16% of the carbon atoms in the biogenic amino acids were labeled. The majority of the biomass is thus derived from unlabeled compounds of the medium and not from glucose. The assumption that medium compounds are used for growth while glucose is utilized in rhamnolipid synthesis is thus strengthened. A possible explanation for the uncoupling of growth and rhamnolipid production might be found in the lipidic precursor, i.e., the activated hydroxy-fatty acids. These molecules are also used for the synthesis of the internal storage polymer PHA, which P. putida produces during secondary substrate-limiting conditions when the carbon source is still abundant ( Prieto et al., 2007 )."
} | 9,714 |
39919188 | PMC11804925 | pmc | 5,315 | {
"abstract": "Material properties gradually degrade under cyclic loading, leading to catastrophic failure. It results in large costs for inspection, maintenance, and downtime. Besides, materials require combinations of performance such as load bearing and energy dissipation. However, improving one performance of a material often sacrifices another performance, making it difficult to create materials with optimal performance profiles. Here we report a liquid-infused porous piezoelectric scaffold (LIPPS) that simultaneously enhances its load-bearing and energy dissipation capability under cyclic loading. For example, after 12 million loading cycles, LIPPS increases its modulus by 3600% and hysteresis by 3000%. From a CT study, this behavior is attributed to the self-recoverable mineralization under mechanical loading. Moreover, LIPPS shows a reprogrammable stiffness distribution based on the loading distribution, which enables the material to generate multiple shapes by self-folding. Our findings can contribute toward unprecedented opportunities in soft robotics, vehicles, infrastructure, and tissue engineering and contribute to the new paradigm of material selection with improved resilience and sustainability.",
"introduction": "INTRODUCTION Similar to the aging process of our body, repeated mechanical loading on structures, devices, and vehicles leads to the generation and propagation of defects in the materials. Over time, these defects accumulate and lead to deterioration of mechanical performance and the premature failure of components ( 1 , 2 ). As a result, periodic inspection and maintenance are conducted to find defects, make repairs, and estimate the remaining lifetime to prevent catastrophic failure, incurring large costs and downtime. Among many material properties that degrade under cyclic loading, load-bearing and energy dissipation capabilities are crucial properties for the structural performance of materials across various applications, from soft robotics to aircraft ( 3 ). The elastic modulus of a material is vital for load-bearing components, as it determines the deformation of a material under a load and the ability to withstand multiple loading cycles, making it a primary material property considered in engineering applications. In addition, hysteresis is essential for energy-dissipating components, as it allows materials to effectively dissipate the loading energy and maintain structural integrity. However, these material properties tend to be mutually exclusive, resulting in trade-offs between improving stiffness and energy dissipation that hinder the creation of materials with optimal combinations of these properties ( 4 ). For example, materials with high stiffness do not typically have high damping such as metals, while materials with high damping such as rubbers do not exhibit high stiffness ( 3 , 5 , 6 ). Related current efforts to address this trade-off challenge primarily focus on improving one property, such as the toughness of a material, while minimizing the reduction of other properties, such as stiffness under static loading ( 5 – 7 ). Nevertheless, even if properties are initially optimized, cyclic loading will lead to defects and accumulating degradation of both stiffness and toughness over time, shortening the lifetime of materials. To extend material lifetime, an ideal material would have the ability to improve both stiffness and dissipation properties as well as repair defects and damage that arise over time. In this regard, there are salient examples in nature that strike a balance between both properties without sacrificing the other, with bones addressing these challenges in an elegant way ( 8 – 10 ). Through a process known as mechanotransduction, bone converts fluid motion from structural deformation into a signal to induce mineralization ( 8 – 10 ). This allows the mechanical properties of bone to be enhanced in response to applied loading by synthesizing reinforcing materials using local resources contained within surrounding body fluids ( 11 ). The porous network structure of bone is advantageous in this process as it enables easy storage and transport of body fluids that contain resources for mineral formation ( 8 , 10 , 12 ). These dynamically adaptive behaviors make these natural mechanisms an intriguing source of inspiration for developing transformative synthetic materials that mimic existing solutions in nature. Recently, there have been seminal works to develop materials that use mechanical cues to enhance their mechanical properties through the formation of stronger bonds and crosslinking (by polymerization) within the material ( 1 , 13 – 16 ). However, most of these materials (i) do not simultaneously enhance both load-bearing and energy dissipation capabilities upon cyclic mechanical loading, (ii) have limited load-bearing capability ( 17 ), (iii) require additional energy to enhance the material ( 18 ), (iv) are difficult to synthesize ( 18 ), (v) need to be used in a liquid environment ( 19 ), and (vi) are constrained by a specific material system. These limitations restrict the utility of existing mechanically adaptive materials. In addition to creating materials capable of improving their mechanical properties, the ability to control the stiffness distribution in a structure has been actively studied to make self-folding structures ( 20 , 21 ). However, stiffness changes are usually imparted through irreversible processes and require multiple materials with varying stiffness combinations. These restrictions limit the range of shape transformations that are possible after fabrication and tend to require multistep fabrication procedures or dedicated equipment. Instead, reversible stiffness distribution control over a single material for reconfiguration into various distinct shapes would be desirable. To address these challenges, we are inspired by the ability of bone to strengthen in response to mechanical loading, its good stiffness and toughness, and its ability to dynamically control the stiffness distribution in response to the location and magnitude of loading. Unlike natural materials like bone, engineering applications often require noncellular materials. We leverage the piezoelectric effect as an alternative of cellular mechanisms of bone, enabling the creation of materials that adapt to external loading without cells. Moreover, while bone operates within a liquid environment, engineering solutions often require a nonliquid environment. We report a liquid-infused material, inspired by Nepenthes pitcher plants that can form a liquid-infused surface in air due to microstructures made of hydrophilic material that can trap water within its structure ( 22 ). Built upon our previous study on piezo charge–induced mineralization ( 19 ), we report a liquid-infused porous piezoelectric scaffold (LIPPS) that simultaneously enhances both its load-bearing and energy dissipation capabilities in response to cyclic loading (e.g., an increase of 3600% and 3000%, respectively, after 12 million loading cycles) and its application to force-based reprogrammable self-folding materials (see Fig. 1 for overview). Furthermore, the LIPPS can be synthesized with various matrix materials including polydimethylsiloxane (PDMS) and hydrogel, making LIPPS not bound to a specific material system. Fig. 1. Overview of LIPPS and characterizations of liquid infusion and pores. ( A ) Overview of LIPPS, highlighting the bioinspiration from bone and the pitcher plant, the reversible reinforcement mechanism, the fabrication process to create the porous composite, mechanical property changes showing increasing stiffness and dissipation after cyclic loading, and the reprogrammable self-folding mechanism and example applications. [Pitcher plant morphology image ( 22 ): copyright 2004, The National Academy of Sciences] ( B ) Effects of surface functionalization: initial hydrophobic surface without PAA coating and high contact angle versus hydrophilic surface with PAA coating and decreased contact angle due to PAA coating. ( C ) Liquid infusion capability of the porous composite scaffold with PAA coating showing the ability to store mineral ion solution within the composite. ( D ) Pore radius distribution analyzed from micro-CT showing that pore sizes are below the capillary length of water. ( E ) Mineralization characterization from micro-CT comparing porosity changes after mineralization, with porosity decreasing due to mineral filling of the pore space. To realize such a material, we derived inspiration from bone and pitcher plants ( Fig. 1A , top) and rationalized the synthesis approach based on our previous work on a pitcher plant–inspired slippery liquid-infused porous surfaces ( 23 ) as follows: (i) An open-cell porous microstructure is preferred for fluid transport within a material ( 24 , 25 ), (ii) the pore size should be below the capillary length of the liquid ( 26 ), (iii) a smaller pore size is preferred as capillary force is inversely proportional to pore size ( 26 ), and (iv) a surface property that promotes spontaneous wicking of a liquid is preferred ( 27 ) (also known as hydrophilic for a water-based solution). We aimed to synthesize a porous piezoelectric material where a mineral solution is infused to allow the material system to respond to the cyclic loading by synthesizing minerals within the porous structure.",
"discussion": "DISCUSSION The LIPPS not only has intriguing spatial and temporal behaviors in response to cyclic mechanical loading but also provides opportunities to study unprecedented phenomena that occur from coupling mechanical stress with material synthesis. The LIPPS also validates the bioinspired approach to overcome a previously accepted paradigm of mutual exclusivity in mechanical property trade-offs. While we have used either PDMS or hydrogels as matrix materials and an SBF as a liquid mineral ion electrolyte, one can incorporate combinations of various matrix materials and compositions of electrolytes. For example, for higher load-bearing capability, materials such as an epoxy or a cement can be adopted as a matrix material to increase the initial modulus of the material, while metal-based ionic solutions can be used to compose an electrolyte to allow for stronger materials to further enhance the mechanical properties of the reinforced composite. One can also consider adding additives for controlling crystallinity ( 31 ) or various functional particles in an infused liquid to autonomously change, for example, optical, electrical, magnetic, or thermal properties upon mechanical loading. In our example, BTO was used to impart piezoelectric properties, and CNTs were added to improve electrical conductivity, but silver or gold particles could be added to improve thermal conductivity and heat dispersion as well as transparency or reflectivity ( 32 ). The liquid electrolyte composition can be also selected or modified on the basis of the operation environment to consider factors such as freezing temperature, boiling temperature, and humidity. We envision that our findings can provide stepping stones toward unprecedented opportunities in various fields including soft robotics ( 33 – 36 ), vehicles ( 37 ), infrastructure ( 38 ), and tissue engineering/medical devices ( 39 ) and can contribute to changing the paradigm ( 40 ) of material selection to create more resilient materials and improve safety and sustainability. For example, in soft robotics, compliance is ideal for increasing flexibility and safety, particularly in situations involving close contact with humans. However, soft materials are exposed to risk from damage that is not easily repairable. A material that can locally adapt its mechanical properties under higher stress environments may be desirable to optimize material integrity. Given the range of achievable modulus, the LIPPS could provide mechanisms to prevent damage without sacrificing flexibility. For vehicles and infrastructures, they undergo varying cyclic loadings which degrade material properties and can result in sudden premature failure. Materials that can adapt to varying loading conditions and improve their properties under cyclic loading can contribute to addressing such challenges with more development of stiffer material systems. Similarly, medical devices implanted into the body such as orthopedic implants not only carry risks of damage and fracture under extended use but also can lead to stress shielding due to mismatches in stiffness with surrounding tissues. A material that could adapt its mechanical properties to match the environment could provide a mechanism to minimize stress shielding. Furthermore, the ability to regenerate the material with minerals similar to bone material could further reduce the failure risk while improving osseointegration, potentially improving patient outcomes. Overall, the LIPPS shows the ability to increase both load-bearing and energy dissipation capabilities under cyclic loadings due to piezoelectric charge–induced mineralization. This characteristic can help overcome the trade-off between stiffness and hysteresis of current materials. Furthermore, the ability of LIPPS to not only stiffen upon mechanical loading but also recover after mineral damage allows the material to have a mechanism for reversible control over the stiffness distribution within a single material. These characteristics lend the material to be able to create reprogrammable self-folding structures as well as provide utility for environments with load-bearing and energy dissipation demands. Such materials could be notably advantageous in a range of applications including soft robotics where preventing failure without compromising flexibility through localized enhancement is ideal, in vehicular and infrastructure materials to mitigate damage and prevent premature failure under extended loading and in medical devices where the ability to reducing fracture risk while minimizing stiffness mismatches between implants and tissues through the generation of biocompatible mineral structures could improve patient outcomes."
} | 3,532 |
39919188 | PMC11804925 | pmc | 5,315 | {
"abstract": "Material properties gradually degrade under cyclic loading, leading to catastrophic failure. It results in large costs for inspection, maintenance, and downtime. Besides, materials require combinations of performance such as load bearing and energy dissipation. However, improving one performance of a material often sacrifices another performance, making it difficult to create materials with optimal performance profiles. Here we report a liquid-infused porous piezoelectric scaffold (LIPPS) that simultaneously enhances its load-bearing and energy dissipation capability under cyclic loading. For example, after 12 million loading cycles, LIPPS increases its modulus by 3600% and hysteresis by 3000%. From a CT study, this behavior is attributed to the self-recoverable mineralization under mechanical loading. Moreover, LIPPS shows a reprogrammable stiffness distribution based on the loading distribution, which enables the material to generate multiple shapes by self-folding. Our findings can contribute toward unprecedented opportunities in soft robotics, vehicles, infrastructure, and tissue engineering and contribute to the new paradigm of material selection with improved resilience and sustainability.",
"introduction": "INTRODUCTION Similar to the aging process of our body, repeated mechanical loading on structures, devices, and vehicles leads to the generation and propagation of defects in the materials. Over time, these defects accumulate and lead to deterioration of mechanical performance and the premature failure of components ( 1 , 2 ). As a result, periodic inspection and maintenance are conducted to find defects, make repairs, and estimate the remaining lifetime to prevent catastrophic failure, incurring large costs and downtime. Among many material properties that degrade under cyclic loading, load-bearing and energy dissipation capabilities are crucial properties for the structural performance of materials across various applications, from soft robotics to aircraft ( 3 ). The elastic modulus of a material is vital for load-bearing components, as it determines the deformation of a material under a load and the ability to withstand multiple loading cycles, making it a primary material property considered in engineering applications. In addition, hysteresis is essential for energy-dissipating components, as it allows materials to effectively dissipate the loading energy and maintain structural integrity. However, these material properties tend to be mutually exclusive, resulting in trade-offs between improving stiffness and energy dissipation that hinder the creation of materials with optimal combinations of these properties ( 4 ). For example, materials with high stiffness do not typically have high damping such as metals, while materials with high damping such as rubbers do not exhibit high stiffness ( 3 , 5 , 6 ). Related current efforts to address this trade-off challenge primarily focus on improving one property, such as the toughness of a material, while minimizing the reduction of other properties, such as stiffness under static loading ( 5 – 7 ). Nevertheless, even if properties are initially optimized, cyclic loading will lead to defects and accumulating degradation of both stiffness and toughness over time, shortening the lifetime of materials. To extend material lifetime, an ideal material would have the ability to improve both stiffness and dissipation properties as well as repair defects and damage that arise over time. In this regard, there are salient examples in nature that strike a balance between both properties without sacrificing the other, with bones addressing these challenges in an elegant way ( 8 – 10 ). Through a process known as mechanotransduction, bone converts fluid motion from structural deformation into a signal to induce mineralization ( 8 – 10 ). This allows the mechanical properties of bone to be enhanced in response to applied loading by synthesizing reinforcing materials using local resources contained within surrounding body fluids ( 11 ). The porous network structure of bone is advantageous in this process as it enables easy storage and transport of body fluids that contain resources for mineral formation ( 8 , 10 , 12 ). These dynamically adaptive behaviors make these natural mechanisms an intriguing source of inspiration for developing transformative synthetic materials that mimic existing solutions in nature. Recently, there have been seminal works to develop materials that use mechanical cues to enhance their mechanical properties through the formation of stronger bonds and crosslinking (by polymerization) within the material ( 1 , 13 – 16 ). However, most of these materials (i) do not simultaneously enhance both load-bearing and energy dissipation capabilities upon cyclic mechanical loading, (ii) have limited load-bearing capability ( 17 ), (iii) require additional energy to enhance the material ( 18 ), (iv) are difficult to synthesize ( 18 ), (v) need to be used in a liquid environment ( 19 ), and (vi) are constrained by a specific material system. These limitations restrict the utility of existing mechanically adaptive materials. In addition to creating materials capable of improving their mechanical properties, the ability to control the stiffness distribution in a structure has been actively studied to make self-folding structures ( 20 , 21 ). However, stiffness changes are usually imparted through irreversible processes and require multiple materials with varying stiffness combinations. These restrictions limit the range of shape transformations that are possible after fabrication and tend to require multistep fabrication procedures or dedicated equipment. Instead, reversible stiffness distribution control over a single material for reconfiguration into various distinct shapes would be desirable. To address these challenges, we are inspired by the ability of bone to strengthen in response to mechanical loading, its good stiffness and toughness, and its ability to dynamically control the stiffness distribution in response to the location and magnitude of loading. Unlike natural materials like bone, engineering applications often require noncellular materials. We leverage the piezoelectric effect as an alternative of cellular mechanisms of bone, enabling the creation of materials that adapt to external loading without cells. Moreover, while bone operates within a liquid environment, engineering solutions often require a nonliquid environment. We report a liquid-infused material, inspired by Nepenthes pitcher plants that can form a liquid-infused surface in air due to microstructures made of hydrophilic material that can trap water within its structure ( 22 ). Built upon our previous study on piezo charge–induced mineralization ( 19 ), we report a liquid-infused porous piezoelectric scaffold (LIPPS) that simultaneously enhances both its load-bearing and energy dissipation capabilities in response to cyclic loading (e.g., an increase of 3600% and 3000%, respectively, after 12 million loading cycles) and its application to force-based reprogrammable self-folding materials (see Fig. 1 for overview). Furthermore, the LIPPS can be synthesized with various matrix materials including polydimethylsiloxane (PDMS) and hydrogel, making LIPPS not bound to a specific material system. Fig. 1. Overview of LIPPS and characterizations of liquid infusion and pores. ( A ) Overview of LIPPS, highlighting the bioinspiration from bone and the pitcher plant, the reversible reinforcement mechanism, the fabrication process to create the porous composite, mechanical property changes showing increasing stiffness and dissipation after cyclic loading, and the reprogrammable self-folding mechanism and example applications. [Pitcher plant morphology image ( 22 ): copyright 2004, The National Academy of Sciences] ( B ) Effects of surface functionalization: initial hydrophobic surface without PAA coating and high contact angle versus hydrophilic surface with PAA coating and decreased contact angle due to PAA coating. ( C ) Liquid infusion capability of the porous composite scaffold with PAA coating showing the ability to store mineral ion solution within the composite. ( D ) Pore radius distribution analyzed from micro-CT showing that pore sizes are below the capillary length of water. ( E ) Mineralization characterization from micro-CT comparing porosity changes after mineralization, with porosity decreasing due to mineral filling of the pore space. To realize such a material, we derived inspiration from bone and pitcher plants ( Fig. 1A , top) and rationalized the synthesis approach based on our previous work on a pitcher plant–inspired slippery liquid-infused porous surfaces ( 23 ) as follows: (i) An open-cell porous microstructure is preferred for fluid transport within a material ( 24 , 25 ), (ii) the pore size should be below the capillary length of the liquid ( 26 ), (iii) a smaller pore size is preferred as capillary force is inversely proportional to pore size ( 26 ), and (iv) a surface property that promotes spontaneous wicking of a liquid is preferred ( 27 ) (also known as hydrophilic for a water-based solution). We aimed to synthesize a porous piezoelectric material where a mineral solution is infused to allow the material system to respond to the cyclic loading by synthesizing minerals within the porous structure.",
"discussion": "DISCUSSION The LIPPS not only has intriguing spatial and temporal behaviors in response to cyclic mechanical loading but also provides opportunities to study unprecedented phenomena that occur from coupling mechanical stress with material synthesis. The LIPPS also validates the bioinspired approach to overcome a previously accepted paradigm of mutual exclusivity in mechanical property trade-offs. While we have used either PDMS or hydrogels as matrix materials and an SBF as a liquid mineral ion electrolyte, one can incorporate combinations of various matrix materials and compositions of electrolytes. For example, for higher load-bearing capability, materials such as an epoxy or a cement can be adopted as a matrix material to increase the initial modulus of the material, while metal-based ionic solutions can be used to compose an electrolyte to allow for stronger materials to further enhance the mechanical properties of the reinforced composite. One can also consider adding additives for controlling crystallinity ( 31 ) or various functional particles in an infused liquid to autonomously change, for example, optical, electrical, magnetic, or thermal properties upon mechanical loading. In our example, BTO was used to impart piezoelectric properties, and CNTs were added to improve electrical conductivity, but silver or gold particles could be added to improve thermal conductivity and heat dispersion as well as transparency or reflectivity ( 32 ). The liquid electrolyte composition can be also selected or modified on the basis of the operation environment to consider factors such as freezing temperature, boiling temperature, and humidity. We envision that our findings can provide stepping stones toward unprecedented opportunities in various fields including soft robotics ( 33 – 36 ), vehicles ( 37 ), infrastructure ( 38 ), and tissue engineering/medical devices ( 39 ) and can contribute to changing the paradigm ( 40 ) of material selection to create more resilient materials and improve safety and sustainability. For example, in soft robotics, compliance is ideal for increasing flexibility and safety, particularly in situations involving close contact with humans. However, soft materials are exposed to risk from damage that is not easily repairable. A material that can locally adapt its mechanical properties under higher stress environments may be desirable to optimize material integrity. Given the range of achievable modulus, the LIPPS could provide mechanisms to prevent damage without sacrificing flexibility. For vehicles and infrastructures, they undergo varying cyclic loadings which degrade material properties and can result in sudden premature failure. Materials that can adapt to varying loading conditions and improve their properties under cyclic loading can contribute to addressing such challenges with more development of stiffer material systems. Similarly, medical devices implanted into the body such as orthopedic implants not only carry risks of damage and fracture under extended use but also can lead to stress shielding due to mismatches in stiffness with surrounding tissues. A material that could adapt its mechanical properties to match the environment could provide a mechanism to minimize stress shielding. Furthermore, the ability to regenerate the material with minerals similar to bone material could further reduce the failure risk while improving osseointegration, potentially improving patient outcomes. Overall, the LIPPS shows the ability to increase both load-bearing and energy dissipation capabilities under cyclic loadings due to piezoelectric charge–induced mineralization. This characteristic can help overcome the trade-off between stiffness and hysteresis of current materials. Furthermore, the ability of LIPPS to not only stiffen upon mechanical loading but also recover after mineral damage allows the material to have a mechanism for reversible control over the stiffness distribution within a single material. These characteristics lend the material to be able to create reprogrammable self-folding structures as well as provide utility for environments with load-bearing and energy dissipation demands. Such materials could be notably advantageous in a range of applications including soft robotics where preventing failure without compromising flexibility through localized enhancement is ideal, in vehicular and infrastructure materials to mitigate damage and prevent premature failure under extended loading and in medical devices where the ability to reducing fracture risk while minimizing stiffness mismatches between implants and tissues through the generation of biocompatible mineral structures could improve patient outcomes."
} | 3,532 |
39919188 | PMC11804925 | pmc | 5,316 | {
"abstract": "Material properties gradually degrade under cyclic loading, leading to catastrophic failure. It results in large costs for inspection, maintenance, and downtime. Besides, materials require combinations of performance such as load bearing and energy dissipation. However, improving one performance of a material often sacrifices another performance, making it difficult to create materials with optimal performance profiles. Here we report a liquid-infused porous piezoelectric scaffold (LIPPS) that simultaneously enhances its load-bearing and energy dissipation capability under cyclic loading. For example, after 12 million loading cycles, LIPPS increases its modulus by 3600% and hysteresis by 3000%. From a CT study, this behavior is attributed to the self-recoverable mineralization under mechanical loading. Moreover, LIPPS shows a reprogrammable stiffness distribution based on the loading distribution, which enables the material to generate multiple shapes by self-folding. Our findings can contribute toward unprecedented opportunities in soft robotics, vehicles, infrastructure, and tissue engineering and contribute to the new paradigm of material selection with improved resilience and sustainability.",
"introduction": "INTRODUCTION Similar to the aging process of our body, repeated mechanical loading on structures, devices, and vehicles leads to the generation and propagation of defects in the materials. Over time, these defects accumulate and lead to deterioration of mechanical performance and the premature failure of components ( 1 , 2 ). As a result, periodic inspection and maintenance are conducted to find defects, make repairs, and estimate the remaining lifetime to prevent catastrophic failure, incurring large costs and downtime. Among many material properties that degrade under cyclic loading, load-bearing and energy dissipation capabilities are crucial properties for the structural performance of materials across various applications, from soft robotics to aircraft ( 3 ). The elastic modulus of a material is vital for load-bearing components, as it determines the deformation of a material under a load and the ability to withstand multiple loading cycles, making it a primary material property considered in engineering applications. In addition, hysteresis is essential for energy-dissipating components, as it allows materials to effectively dissipate the loading energy and maintain structural integrity. However, these material properties tend to be mutually exclusive, resulting in trade-offs between improving stiffness and energy dissipation that hinder the creation of materials with optimal combinations of these properties ( 4 ). For example, materials with high stiffness do not typically have high damping such as metals, while materials with high damping such as rubbers do not exhibit high stiffness ( 3 , 5 , 6 ). Related current efforts to address this trade-off challenge primarily focus on improving one property, such as the toughness of a material, while minimizing the reduction of other properties, such as stiffness under static loading ( 5 – 7 ). Nevertheless, even if properties are initially optimized, cyclic loading will lead to defects and accumulating degradation of both stiffness and toughness over time, shortening the lifetime of materials. To extend material lifetime, an ideal material would have the ability to improve both stiffness and dissipation properties as well as repair defects and damage that arise over time. In this regard, there are salient examples in nature that strike a balance between both properties without sacrificing the other, with bones addressing these challenges in an elegant way ( 8 – 10 ). Through a process known as mechanotransduction, bone converts fluid motion from structural deformation into a signal to induce mineralization ( 8 – 10 ). This allows the mechanical properties of bone to be enhanced in response to applied loading by synthesizing reinforcing materials using local resources contained within surrounding body fluids ( 11 ). The porous network structure of bone is advantageous in this process as it enables easy storage and transport of body fluids that contain resources for mineral formation ( 8 , 10 , 12 ). These dynamically adaptive behaviors make these natural mechanisms an intriguing source of inspiration for developing transformative synthetic materials that mimic existing solutions in nature. Recently, there have been seminal works to develop materials that use mechanical cues to enhance their mechanical properties through the formation of stronger bonds and crosslinking (by polymerization) within the material ( 1 , 13 – 16 ). However, most of these materials (i) do not simultaneously enhance both load-bearing and energy dissipation capabilities upon cyclic mechanical loading, (ii) have limited load-bearing capability ( 17 ), (iii) require additional energy to enhance the material ( 18 ), (iv) are difficult to synthesize ( 18 ), (v) need to be used in a liquid environment ( 19 ), and (vi) are constrained by a specific material system. These limitations restrict the utility of existing mechanically adaptive materials. In addition to creating materials capable of improving their mechanical properties, the ability to control the stiffness distribution in a structure has been actively studied to make self-folding structures ( 20 , 21 ). However, stiffness changes are usually imparted through irreversible processes and require multiple materials with varying stiffness combinations. These restrictions limit the range of shape transformations that are possible after fabrication and tend to require multistep fabrication procedures or dedicated equipment. Instead, reversible stiffness distribution control over a single material for reconfiguration into various distinct shapes would be desirable. To address these challenges, we are inspired by the ability of bone to strengthen in response to mechanical loading, its good stiffness and toughness, and its ability to dynamically control the stiffness distribution in response to the location and magnitude of loading. Unlike natural materials like bone, engineering applications often require noncellular materials. We leverage the piezoelectric effect as an alternative of cellular mechanisms of bone, enabling the creation of materials that adapt to external loading without cells. Moreover, while bone operates within a liquid environment, engineering solutions often require a nonliquid environment. We report a liquid-infused material, inspired by Nepenthes pitcher plants that can form a liquid-infused surface in air due to microstructures made of hydrophilic material that can trap water within its structure ( 22 ). Built upon our previous study on piezo charge–induced mineralization ( 19 ), we report a liquid-infused porous piezoelectric scaffold (LIPPS) that simultaneously enhances both its load-bearing and energy dissipation capabilities in response to cyclic loading (e.g., an increase of 3600% and 3000%, respectively, after 12 million loading cycles) and its application to force-based reprogrammable self-folding materials (see Fig. 1 for overview). Furthermore, the LIPPS can be synthesized with various matrix materials including polydimethylsiloxane (PDMS) and hydrogel, making LIPPS not bound to a specific material system. Fig. 1. Overview of LIPPS and characterizations of liquid infusion and pores. ( A ) Overview of LIPPS, highlighting the bioinspiration from bone and the pitcher plant, the reversible reinforcement mechanism, the fabrication process to create the porous composite, mechanical property changes showing increasing stiffness and dissipation after cyclic loading, and the reprogrammable self-folding mechanism and example applications. [Pitcher plant morphology image ( 22 ): copyright 2004, The National Academy of Sciences] ( B ) Effects of surface functionalization: initial hydrophobic surface without PAA coating and high contact angle versus hydrophilic surface with PAA coating and decreased contact angle due to PAA coating. ( C ) Liquid infusion capability of the porous composite scaffold with PAA coating showing the ability to store mineral ion solution within the composite. ( D ) Pore radius distribution analyzed from micro-CT showing that pore sizes are below the capillary length of water. ( E ) Mineralization characterization from micro-CT comparing porosity changes after mineralization, with porosity decreasing due to mineral filling of the pore space. To realize such a material, we derived inspiration from bone and pitcher plants ( Fig. 1A , top) and rationalized the synthesis approach based on our previous work on a pitcher plant–inspired slippery liquid-infused porous surfaces ( 23 ) as follows: (i) An open-cell porous microstructure is preferred for fluid transport within a material ( 24 , 25 ), (ii) the pore size should be below the capillary length of the liquid ( 26 ), (iii) a smaller pore size is preferred as capillary force is inversely proportional to pore size ( 26 ), and (iv) a surface property that promotes spontaneous wicking of a liquid is preferred ( 27 ) (also known as hydrophilic for a water-based solution). We aimed to synthesize a porous piezoelectric material where a mineral solution is infused to allow the material system to respond to the cyclic loading by synthesizing minerals within the porous structure.",
"discussion": "DISCUSSION The LIPPS not only has intriguing spatial and temporal behaviors in response to cyclic mechanical loading but also provides opportunities to study unprecedented phenomena that occur from coupling mechanical stress with material synthesis. The LIPPS also validates the bioinspired approach to overcome a previously accepted paradigm of mutual exclusivity in mechanical property trade-offs. While we have used either PDMS or hydrogels as matrix materials and an SBF as a liquid mineral ion electrolyte, one can incorporate combinations of various matrix materials and compositions of electrolytes. For example, for higher load-bearing capability, materials such as an epoxy or a cement can be adopted as a matrix material to increase the initial modulus of the material, while metal-based ionic solutions can be used to compose an electrolyte to allow for stronger materials to further enhance the mechanical properties of the reinforced composite. One can also consider adding additives for controlling crystallinity ( 31 ) or various functional particles in an infused liquid to autonomously change, for example, optical, electrical, magnetic, or thermal properties upon mechanical loading. In our example, BTO was used to impart piezoelectric properties, and CNTs were added to improve electrical conductivity, but silver or gold particles could be added to improve thermal conductivity and heat dispersion as well as transparency or reflectivity ( 32 ). The liquid electrolyte composition can be also selected or modified on the basis of the operation environment to consider factors such as freezing temperature, boiling temperature, and humidity. We envision that our findings can provide stepping stones toward unprecedented opportunities in various fields including soft robotics ( 33 – 36 ), vehicles ( 37 ), infrastructure ( 38 ), and tissue engineering/medical devices ( 39 ) and can contribute to changing the paradigm ( 40 ) of material selection to create more resilient materials and improve safety and sustainability. For example, in soft robotics, compliance is ideal for increasing flexibility and safety, particularly in situations involving close contact with humans. However, soft materials are exposed to risk from damage that is not easily repairable. A material that can locally adapt its mechanical properties under higher stress environments may be desirable to optimize material integrity. Given the range of achievable modulus, the LIPPS could provide mechanisms to prevent damage without sacrificing flexibility. For vehicles and infrastructures, they undergo varying cyclic loadings which degrade material properties and can result in sudden premature failure. Materials that can adapt to varying loading conditions and improve their properties under cyclic loading can contribute to addressing such challenges with more development of stiffer material systems. Similarly, medical devices implanted into the body such as orthopedic implants not only carry risks of damage and fracture under extended use but also can lead to stress shielding due to mismatches in stiffness with surrounding tissues. A material that could adapt its mechanical properties to match the environment could provide a mechanism to minimize stress shielding. Furthermore, the ability to regenerate the material with minerals similar to bone material could further reduce the failure risk while improving osseointegration, potentially improving patient outcomes. Overall, the LIPPS shows the ability to increase both load-bearing and energy dissipation capabilities under cyclic loadings due to piezoelectric charge–induced mineralization. This characteristic can help overcome the trade-off between stiffness and hysteresis of current materials. Furthermore, the ability of LIPPS to not only stiffen upon mechanical loading but also recover after mineral damage allows the material to have a mechanism for reversible control over the stiffness distribution within a single material. These characteristics lend the material to be able to create reprogrammable self-folding structures as well as provide utility for environments with load-bearing and energy dissipation demands. Such materials could be notably advantageous in a range of applications including soft robotics where preventing failure without compromising flexibility through localized enhancement is ideal, in vehicular and infrastructure materials to mitigate damage and prevent premature failure under extended loading and in medical devices where the ability to reducing fracture risk while minimizing stiffness mismatches between implants and tissues through the generation of biocompatible mineral structures could improve patient outcomes."
} | 3,532 |
39919188 | PMC11804925 | pmc | 5,316 | {
"abstract": "Material properties gradually degrade under cyclic loading, leading to catastrophic failure. It results in large costs for inspection, maintenance, and downtime. Besides, materials require combinations of performance such as load bearing and energy dissipation. However, improving one performance of a material often sacrifices another performance, making it difficult to create materials with optimal performance profiles. Here we report a liquid-infused porous piezoelectric scaffold (LIPPS) that simultaneously enhances its load-bearing and energy dissipation capability under cyclic loading. For example, after 12 million loading cycles, LIPPS increases its modulus by 3600% and hysteresis by 3000%. From a CT study, this behavior is attributed to the self-recoverable mineralization under mechanical loading. Moreover, LIPPS shows a reprogrammable stiffness distribution based on the loading distribution, which enables the material to generate multiple shapes by self-folding. Our findings can contribute toward unprecedented opportunities in soft robotics, vehicles, infrastructure, and tissue engineering and contribute to the new paradigm of material selection with improved resilience and sustainability.",
"introduction": "INTRODUCTION Similar to the aging process of our body, repeated mechanical loading on structures, devices, and vehicles leads to the generation and propagation of defects in the materials. Over time, these defects accumulate and lead to deterioration of mechanical performance and the premature failure of components ( 1 , 2 ). As a result, periodic inspection and maintenance are conducted to find defects, make repairs, and estimate the remaining lifetime to prevent catastrophic failure, incurring large costs and downtime. Among many material properties that degrade under cyclic loading, load-bearing and energy dissipation capabilities are crucial properties for the structural performance of materials across various applications, from soft robotics to aircraft ( 3 ). The elastic modulus of a material is vital for load-bearing components, as it determines the deformation of a material under a load and the ability to withstand multiple loading cycles, making it a primary material property considered in engineering applications. In addition, hysteresis is essential for energy-dissipating components, as it allows materials to effectively dissipate the loading energy and maintain structural integrity. However, these material properties tend to be mutually exclusive, resulting in trade-offs between improving stiffness and energy dissipation that hinder the creation of materials with optimal combinations of these properties ( 4 ). For example, materials with high stiffness do not typically have high damping such as metals, while materials with high damping such as rubbers do not exhibit high stiffness ( 3 , 5 , 6 ). Related current efforts to address this trade-off challenge primarily focus on improving one property, such as the toughness of a material, while minimizing the reduction of other properties, such as stiffness under static loading ( 5 – 7 ). Nevertheless, even if properties are initially optimized, cyclic loading will lead to defects and accumulating degradation of both stiffness and toughness over time, shortening the lifetime of materials. To extend material lifetime, an ideal material would have the ability to improve both stiffness and dissipation properties as well as repair defects and damage that arise over time. In this regard, there are salient examples in nature that strike a balance between both properties without sacrificing the other, with bones addressing these challenges in an elegant way ( 8 – 10 ). Through a process known as mechanotransduction, bone converts fluid motion from structural deformation into a signal to induce mineralization ( 8 – 10 ). This allows the mechanical properties of bone to be enhanced in response to applied loading by synthesizing reinforcing materials using local resources contained within surrounding body fluids ( 11 ). The porous network structure of bone is advantageous in this process as it enables easy storage and transport of body fluids that contain resources for mineral formation ( 8 , 10 , 12 ). These dynamically adaptive behaviors make these natural mechanisms an intriguing source of inspiration for developing transformative synthetic materials that mimic existing solutions in nature. Recently, there have been seminal works to develop materials that use mechanical cues to enhance their mechanical properties through the formation of stronger bonds and crosslinking (by polymerization) within the material ( 1 , 13 – 16 ). However, most of these materials (i) do not simultaneously enhance both load-bearing and energy dissipation capabilities upon cyclic mechanical loading, (ii) have limited load-bearing capability ( 17 ), (iii) require additional energy to enhance the material ( 18 ), (iv) are difficult to synthesize ( 18 ), (v) need to be used in a liquid environment ( 19 ), and (vi) are constrained by a specific material system. These limitations restrict the utility of existing mechanically adaptive materials. In addition to creating materials capable of improving their mechanical properties, the ability to control the stiffness distribution in a structure has been actively studied to make self-folding structures ( 20 , 21 ). However, stiffness changes are usually imparted through irreversible processes and require multiple materials with varying stiffness combinations. These restrictions limit the range of shape transformations that are possible after fabrication and tend to require multistep fabrication procedures or dedicated equipment. Instead, reversible stiffness distribution control over a single material for reconfiguration into various distinct shapes would be desirable. To address these challenges, we are inspired by the ability of bone to strengthen in response to mechanical loading, its good stiffness and toughness, and its ability to dynamically control the stiffness distribution in response to the location and magnitude of loading. Unlike natural materials like bone, engineering applications often require noncellular materials. We leverage the piezoelectric effect as an alternative of cellular mechanisms of bone, enabling the creation of materials that adapt to external loading without cells. Moreover, while bone operates within a liquid environment, engineering solutions often require a nonliquid environment. We report a liquid-infused material, inspired by Nepenthes pitcher plants that can form a liquid-infused surface in air due to microstructures made of hydrophilic material that can trap water within its structure ( 22 ). Built upon our previous study on piezo charge–induced mineralization ( 19 ), we report a liquid-infused porous piezoelectric scaffold (LIPPS) that simultaneously enhances both its load-bearing and energy dissipation capabilities in response to cyclic loading (e.g., an increase of 3600% and 3000%, respectively, after 12 million loading cycles) and its application to force-based reprogrammable self-folding materials (see Fig. 1 for overview). Furthermore, the LIPPS can be synthesized with various matrix materials including polydimethylsiloxane (PDMS) and hydrogel, making LIPPS not bound to a specific material system. Fig. 1. Overview of LIPPS and characterizations of liquid infusion and pores. ( A ) Overview of LIPPS, highlighting the bioinspiration from bone and the pitcher plant, the reversible reinforcement mechanism, the fabrication process to create the porous composite, mechanical property changes showing increasing stiffness and dissipation after cyclic loading, and the reprogrammable self-folding mechanism and example applications. [Pitcher plant morphology image ( 22 ): copyright 2004, The National Academy of Sciences] ( B ) Effects of surface functionalization: initial hydrophobic surface without PAA coating and high contact angle versus hydrophilic surface with PAA coating and decreased contact angle due to PAA coating. ( C ) Liquid infusion capability of the porous composite scaffold with PAA coating showing the ability to store mineral ion solution within the composite. ( D ) Pore radius distribution analyzed from micro-CT showing that pore sizes are below the capillary length of water. ( E ) Mineralization characterization from micro-CT comparing porosity changes after mineralization, with porosity decreasing due to mineral filling of the pore space. To realize such a material, we derived inspiration from bone and pitcher plants ( Fig. 1A , top) and rationalized the synthesis approach based on our previous work on a pitcher plant–inspired slippery liquid-infused porous surfaces ( 23 ) as follows: (i) An open-cell porous microstructure is preferred for fluid transport within a material ( 24 , 25 ), (ii) the pore size should be below the capillary length of the liquid ( 26 ), (iii) a smaller pore size is preferred as capillary force is inversely proportional to pore size ( 26 ), and (iv) a surface property that promotes spontaneous wicking of a liquid is preferred ( 27 ) (also known as hydrophilic for a water-based solution). We aimed to synthesize a porous piezoelectric material where a mineral solution is infused to allow the material system to respond to the cyclic loading by synthesizing minerals within the porous structure.",
"discussion": "DISCUSSION The LIPPS not only has intriguing spatial and temporal behaviors in response to cyclic mechanical loading but also provides opportunities to study unprecedented phenomena that occur from coupling mechanical stress with material synthesis. The LIPPS also validates the bioinspired approach to overcome a previously accepted paradigm of mutual exclusivity in mechanical property trade-offs. While we have used either PDMS or hydrogels as matrix materials and an SBF as a liquid mineral ion electrolyte, one can incorporate combinations of various matrix materials and compositions of electrolytes. For example, for higher load-bearing capability, materials such as an epoxy or a cement can be adopted as a matrix material to increase the initial modulus of the material, while metal-based ionic solutions can be used to compose an electrolyte to allow for stronger materials to further enhance the mechanical properties of the reinforced composite. One can also consider adding additives for controlling crystallinity ( 31 ) or various functional particles in an infused liquid to autonomously change, for example, optical, electrical, magnetic, or thermal properties upon mechanical loading. In our example, BTO was used to impart piezoelectric properties, and CNTs were added to improve electrical conductivity, but silver or gold particles could be added to improve thermal conductivity and heat dispersion as well as transparency or reflectivity ( 32 ). The liquid electrolyte composition can be also selected or modified on the basis of the operation environment to consider factors such as freezing temperature, boiling temperature, and humidity. We envision that our findings can provide stepping stones toward unprecedented opportunities in various fields including soft robotics ( 33 – 36 ), vehicles ( 37 ), infrastructure ( 38 ), and tissue engineering/medical devices ( 39 ) and can contribute to changing the paradigm ( 40 ) of material selection to create more resilient materials and improve safety and sustainability. For example, in soft robotics, compliance is ideal for increasing flexibility and safety, particularly in situations involving close contact with humans. However, soft materials are exposed to risk from damage that is not easily repairable. A material that can locally adapt its mechanical properties under higher stress environments may be desirable to optimize material integrity. Given the range of achievable modulus, the LIPPS could provide mechanisms to prevent damage without sacrificing flexibility. For vehicles and infrastructures, they undergo varying cyclic loadings which degrade material properties and can result in sudden premature failure. Materials that can adapt to varying loading conditions and improve their properties under cyclic loading can contribute to addressing such challenges with more development of stiffer material systems. Similarly, medical devices implanted into the body such as orthopedic implants not only carry risks of damage and fracture under extended use but also can lead to stress shielding due to mismatches in stiffness with surrounding tissues. A material that could adapt its mechanical properties to match the environment could provide a mechanism to minimize stress shielding. Furthermore, the ability to regenerate the material with minerals similar to bone material could further reduce the failure risk while improving osseointegration, potentially improving patient outcomes. Overall, the LIPPS shows the ability to increase both load-bearing and energy dissipation capabilities under cyclic loadings due to piezoelectric charge–induced mineralization. This characteristic can help overcome the trade-off between stiffness and hysteresis of current materials. Furthermore, the ability of LIPPS to not only stiffen upon mechanical loading but also recover after mineral damage allows the material to have a mechanism for reversible control over the stiffness distribution within a single material. These characteristics lend the material to be able to create reprogrammable self-folding structures as well as provide utility for environments with load-bearing and energy dissipation demands. Such materials could be notably advantageous in a range of applications including soft robotics where preventing failure without compromising flexibility through localized enhancement is ideal, in vehicular and infrastructure materials to mitigate damage and prevent premature failure under extended loading and in medical devices where the ability to reducing fracture risk while minimizing stiffness mismatches between implants and tissues through the generation of biocompatible mineral structures could improve patient outcomes."
} | 3,532 |
19769971 | null | s2 | 5,317 | {
"abstract": "The first full genome sequences were established in the mid-1990s. Shortly thereafter, genome-scale metabolic network reconstructions appeared. Since that time, we have witnessed an exponential growth in their number and uses. Here I discuss, from a personal point of view, four topics: (1) the placement of metabolic systems biology in the context of broader scientific developments, (2) its foundational concepts, (3) some of its current uses, and (4) some of the expected future developments in the field."
} | 127 |
35857216 | PMC9300530 | pmc | 5,319 | {
"abstract": "Introduction Glycerol is a byproduct from the biodiesel industry that can be biotransformed by Escherichia coli to high added-value products such as succinate under aerobic conditions. The main genetic engineering strategies to achieve this aim involve the mutation of succinate dehydrogenase ( sdhA ) gene and also those responsible for acetate synthesis including acetate kinase, phosphate acetyl transferase and pyruvate oxidase encoded by ackA , pta and pox genes respectively in the ΔsdhAΔack-ptaΔpox (M4) mutant. Other genetic manipulations to rewire the metabolism toward succinate consist on the activation of the glyoxylate shunt or blockage the pentose phosphate pathway (PPP) by deletion of isocitrate lyase repressor ( iclR ) or gluconate dehydrogenase ( gnd ) genes on M4- ΔiclR and M4- Δgnd mutants respectively. Objective To deeply understand the effect of the blocking of the pentose phosphate pathway (PPP) or the activation of the glyoxylate shunt , metabolite profiles were analyzed on M4- Δgnd , M4- ΔiclR and M4 mutants. Methods Metabolomics was performed by FT-IR and GC–MS for metabolite fingerprinting and HPLC for quantification of succinate and glycerol. Results Most of the 65 identified metabolites showed lower relative levels in the M4- ΔiclR and M4- Δgnd mutants than those of the M4. However, fructose 1,6-biphosphate, trehalose, isovaleric acid and mannitol relative concentrations were increased in M4- ΔiclR and M4- Δgnd mutants. To further improve succinate production, the synthesis of mannitol was suppressed by deletion of mannitol dehydrogenase ( mtlD ) on M4- ΔgndΔmtlD mutant that increase ~ 20% respect to M4- Δgnd . Conclusion Metabolomics can serve as a holistic tool to identify bottlenecks in metabolic pathways by a non-rational design. Genetic manipulation to release these restrictions could increase the production of succinate. Supplementary Information The online version contains supplementary material available at 10.1007/s11306-022-01912-9.",
"conclusion": "Conclusions The results obtained in this study evidence that the deletion of mannitol synthesis is a successful metabolic engineering strategy to improve succinic acid production of the M4- Δgnd mutant, although nitrogen metabolism was depleted as observed with FT-IR and GC–MS. However, the depletion of trehalose synthesis did not have a synergistic effect using M4- ΔiclR as genetic background, which evidence the complexity of the metabolic pathways and regulatory networks and their application to metabolic engineering.",
"introduction": "Introduction The biological synthesis of high value chemicals has recently attracted lots of interests, as new feedstocks become available and in order to reduce the environmental impact of petrochemical derivatives production. Thus, the United States Department of Energy has declared 12 compounds as building blocks, including the C4-dicarboxylic acids such as succinic, malic and fumaric acids. For instance, the succinic acid market is approximately 20,000–30,000 tons a year, being used principally in four industrial sectors that require high cost raw materials including: (1) detergents and surfactants, (2) ion chelators, (3) food (acidulants and antimicrobial) and (4) pharmaceutical industry (Ahn et al., 2016 ; Beauprez et al., 2010 ; Song & Lee, 2006 ; Zhu et al., 2014 ). These metabolites can be produced by biological means (Werpy & Petersen, 2004 ). Succinic acid can be produced through microbial fermentation processes with glycerol which is an interesting and relatively cheap alternative substrate since it is produced as waste from the biodiesel industry and also it has a high carbon content (58.4%) and reduction power (da Silva et al., 2009 ; Gholami et al., 2014 ; Samul et al., 2014 ). Glycerol can be metabolized by several bacterial species (Agarwal et al., 2007 ; Barros et al., 2013 ; Lee et al., 2010 ; Nikel et al., 2008 ; Scholten et al., 2009 ) Among them, Escherichia coli is an interesting option, because it is one of the best characterized microorganisms for biotechnological applications. Indeed, this bacterium, consumes glycerol and produces succinic acid under anaerobic conditions, when the Tricarboxylic Acid (TCA) cycle splits in two linear pathways, one of which has succinic acid as an end product that is exported out of the cell. For this reason, most of the work related to succinic acid production in E. coli , has been carried out under anaerobic conditions. This production has been implemented by using diverse metabolic engineering strategies such as inactivation of fermentative pathways of co-products (lactate, acetate, formate and ethanol) as well as the overexpression of anaplerotic and cataplerotic enzymes. Using these strategies it is possible to obtain biotransformation yields of up to 0.80 mol/mol using glycerol as a carbon source (Blankschien et al., 2010 ; Liang et al., 2011 ; Zhang et al., 2010 ). However, the anaerobic production of succinic acid becomes difficult and slow due to the low growth and substrate consumption rate. Nevertheless , in silico models show that the aerobic production of succinic acid is more favorable considering that succinic acid production is associated with growth, in which the maximum molar yield of biomass under aerobic conditions is 0.725 mol/mol which is considerably higher respect to anaerobic condition that is 0.187 mol/mol (Liu et al., 2010 ; Steinsiek et al., 2011 ). The main genetic engineering strategies previously tested for succinic acid production under strictly aerobic conditions involved the linearization of the TCA cycle by deletion of succinic acid dehydrogenase subunits A and B ( sdhAB ) in which succinic acid is exported out of the cell. To improve the biotransformation yield, the glyoxylate shunt has also been activated in this genetic background by deletion of the iclR gene (isocitrate lyase regulator), a negative regulator of this pathway’s genes ( aceA; isocitrate lyase and aceB ; malate synthase A). This activation has been implemented by deletion of the genes for the enzymes of competitive pathways such as pyruvate oxidase ( poxB ), acetate kinase ( ackA ) and phosphate acetyltransferase ( pta ) (Lin et al., 2005a ). For instance using the multiple mutant ΔsdhABΔpoxBΔackA-ptaΔiclR 0.67 mol succinic acid/mol glycerol was obtained (Lin et al., 2005b ). Other strategies using at least one of these gene deletions have been used by Li et al. ( 2013 ). Another strategy previously reported consisted on the mutation of gluconate dehydrogenase ( gnd) gene involved in the reductive pentose phosphate pathway (PPP), which increased the succinic acid production under anaerobic conditions using glucose or glycerol as the carbon source (Mienda et al., 2016 ; Zhao et al., 2004 ). Regardless of such successful strategies, in silico analysis suggest that succinic acid production could achieve higher rates in aerobiosis (Chong et al., 2014 ). It is therefore necessary to optimize succinic acid precursors through metabolic strategies that prevent carbon leakages and maintain energy and redox balance for cell survival and growth (Zhu et al. 2014 ), although these carbon leakages are difficult to predict due to the complexity of the biochemical pathways. In the past two decades, the application of metabolomics has proven itself as a helpful approach for a better understanding of the metabolic processes in different biological systems (Martien & Amador-Noguez, 2017 ). The profiling of metabolites in biological systems has been of interest for many years since the work of Williams et al. ( 1951 ) as an early demonstration of “metabolic pattern” unique to individuals (Williams et al., 1951 ). The analytical platforms most commonly used in this field are gas or liquid chromatography–mass spectrometry (GC–MS or LC–MS) and nuclear magnetic resonance (NMR) spectroscopy (Begley et al., 2009 ). Other hand, spectroscopic methods have also been used in metabolomic platforms; for instance, Fourier transform infra-red (FT-IR) spectroscopy can be applied as an automated and very rapid holistic approach (Winson et al., 1997 ) providing biomolecular “fingerprints” made up of the vibrational features of microbial cell components (Naumann et al., 1991 ) and the chemically-based discrimination of intact microbial cells, which may allow for the detection and identification of the most significant groups of biomolecules in a biological system. Such findings may direct the study towards the appropriate omics platforms and analytical methods (Goodacre et al., 1998 ). In the absence of a universally applicable analytical platform, complementary data can be compiled using several platforms, to allow for better understanding of a biological process and a more informative conclusion to be made (Begley et al., 2009 ). Taking into account the robustness and the advantages of metabolomic platforms, the aim of the present work is to perform a metabolomics analysis of three aerobic succinic acid producer strains with different genetic backgrounds: the base mutant ( ΔsdhAΔack-ptaΔpox ) (Lin et al., 2005a ) was used to generate two quintuple strains: (i) with an additional mutation of the iclR gene ( ΔsdhAΔack-ptaΔpoxΔiclR ) or (ii) the gnd gene ( ΔsdhAΔack-ptaΔpoxΔgnd ). The findings of this study provide a better understanding of the metabolic rewiring processes in these mutants, which may assist the metabolic design and engineering strategies for improving succinic acid production.",
"discussion": "Discussion This study aim was to use metabolomics tools to identify key metabolites as targets for potential genetic modifications of E. coli strains to improve succinic acid production under aerobic conditions. To this end, three mutant strains, previously described as capable of producing succinic acid under aerobic conditions (Lin et al. 2005b ), were constructed: M4, M4- ΔiclR , M4- Δgnd mutant strains (Soto-Varela et al., 2021 ). Comparative analysis of the metabolome using complementary techniques such as FT-IR spectroscopy, GC–MS and targeted HPLC, revealed interesting differences in the behavior and phenotypic profiles of these three mutants. The FT-IR analysis indicated that the metabolic fingerprint of M4- ΔiclR was significantly different from the rest of the samples from M4 and M4- Δgnd strains (Supplementary Information Fig. 2 a and c). This distinctive profile is consistent with the differences in the growth from 31 up to 55 h (Fig. 1 a) and the growth rate (Table 1 ), which were higher respect to the M4 mutant, and the glycerol consumption rate (since 10 up to 31 h) that was also higher (Fig. 1 c). However, after the first 31 h, a decrease of glycerol consumption rate was observed in all three strains, which agree with (Lin et al. 2005b ) findings, who reported a decrease in the carbon source consumption (glucose in that case) after 24 h. For this reason, a strategy to increase growth and productivity could be focused in improving glycerol assimilation in both quintuple mutants after 24 h, taking into account what was described by Jiang et al. ( 2016 ). Our results also confirm that glycerol is a more favorable carbon source than glucose for the M4 genetic background, since feeding with glucose (10 g/L [55.51 mM]) produced 4 mM of succinic acid (Lin et al., 2005a ) resulting in 3.5% of theoretical molar yield, while the same strain produces 8 mM after 24 h using glycerol (11.5 g/L [125 mM]) as this work describes, which is 6% of theoretical molar yield. This evidence is in agreement with the GC–MS analysis, which indicates that glycerol 3-P values in both quintuple mutants had decreased compared to the M4 strain values. On the other hand, the mutation of iclR gene in the M4 mutant slightly increased succinic acid production at 48 h (Fig. 1 b) using glycerol and in a lesser extent to that obtained using glucose (Lin et al. 2005b ). Additionally, in this study, a similar slight increase in extracellular succinic acid was observed in the M4- Δgnd strain. The finding of differences in the relative concentration of these metabolites may also suggest the presence of key regulation points, and possible competitive metabolites and pathways that can be considered carbon leakages. The GC–MS results also implied that carbon metabolism seems to be more active in the M4 strain. In fact, the differences detected between the strains by PCA could be explained mainly by changes in various sugars levels such as fructose and glucose in the M4 mutant. These results are also agree with the FT-IR findings, which suggested major changes in polysaccharide vibrational regions (900–1200 cm −1 ), as well as changes in the protein and peptide levels which could also be linked to the expression of different enzymes, contributing to the upregulation of various pathways. The PCA shows how nitrogen metabolism is more active in M4 and M4- ΔiclR mutant, not only in terms of amino acids metabolism, but also in precursors of nitrogenous bases such as uracil and xanthine (Fig. 2 , Fig. 4 and Table S4), reflecting the higher growth rate of both strains respect to M4- Δgnd (Table 1 ). Nitrogen catabolism at 48 h seems to be also more active, which may explain the diauxic shift in the growth curves (Fig. 1 a) as products such as putrescine and urea were detected in M4. Remarkably, urea and serine were key metabolites for separation between M4- Δgnd , M4- ΔiclR and M4 samples in PCA (Fig. 2 , Table S4) and the separation of M4- ΔiclR is also shown by FT-IR analysis that can explain by the possible abundance, in agreement to amine or amides (C = O, N–H, C-N) functional groups (Supplementary Information Fig. S2) of asparagine but not in glutamine because similar level of glutamine was detected in the three mutants at the two time points (Fig. 3 ). Additional analysis by heatmap performed with 26 identified compounds related to N metabolism (Fig. 4 and Table S6), and a metabolite-based dendrogram showed two main clusters. The dendrogram revealed that relative quantification of hydroxylamine and urea at two time points are very different to the rest of the detected metabolites. Urea is higher in M4 and the hydroxylamine in M4- Δgnd at 48 h. Urea is involved in amino acid catabolism as the main nitrogen waste product, whereas hydroxylamine is involved in ammonium generation from a reduced electron acceptor, or can be also generated from glutathione. This effect could probably be due to its important role in the regulation of the nitrogen assimilation. Glutamine synthetase, which catalyze the amination of the glutamate to glutamine is a key enzyme in ammonia assimilation and it has a feedback regulation (Goss et al., 2001 ; Stadtman, 2001 ). This enzyme may also be used to control the carbon flux to α-ketoglutarate and therefore to succinic acid. This metabolic redirection may be modulated by addition of different NH 4 concentrations to the culture medium. In the M4- Δgnd strain most of the nitrogen compounds levels were lower than those obtained in M4 and M4- ΔiclR strains, probably due to the blocking of the oxidative phase of the PPP (through gnd gene deletion) and the theoretical NADPH depletion. This lower NADPH/NADP + balance should affect many anabolic reactions (Giraud & Naismith, 2000 ; McCourt et al., 2004 ; Yu et al., 2011 ) and may be a bottleneck in the metabolism of this mutant. This effect was also reported by Zhao et al. ( 2004 ), who mutated the zwf gene, that encode the glucose 6-P dehydrogenase, although in this case only acetate was used as carbon source. On the other hand, it seems that a key point affected by iclR mutation is the control of the gluconeogenesis and glycolysis pathways, evidenced by the accumulation of fructose-1,6-BP in this strain at 24 h (Fig. 3 ). Furthermore, glycerol is a substrate that promotes gluconeogenesis due to the need of sugars synthesis (Peng & Shimizu, 2003 ) since glycerol and bicarbonate are the unique carbon sources. In the M4- ΔiclR , carbon leakage is attenuated due to the fact that in this mutant the activation of the glyoxylate shunt lead to a drop of the two decarboxylation steps of the TCA cycle, allowing the formation of metabolic intermediates from Acetyl-CoA without carbon lost (Mainguet et al., 2013 ). This could explain the increment in the synthesis of sugars like trehalose and mannitol (Fig. 3 ) . Therefore, the regulation of this step, mainly in the M4- ΔiclR , is key point to redirect the carbon flux through glycolysis to the TCA cycle to promote the production of metabolites of interest. This unbalance of the central carbon pathways leads to an increment of trehalose in M4- ΔiclR at 48 h, probably caused by an up-regulation of the otsA and otsB genes which encode the trehalose 6-P synthetase and trehalose-6-P phosphatase enzymes, respectively which are responsible for synthesis of high concentrations of internal trehalose during the transition to stationary phase (Hengge-Aronis et al., 1991 ), or particularly osmotic stress conditions (Giaever et al., 1988 ). Trehalose could be considered as a carbon leakage, because it is not a product of biotechnological interest, but it has an important role as osmoprotectant compound in physiological stress of the bacteria. For this, the deletion of otsA gene in the M4- ΔiclR may improve succinic acid synthesis. In the case of mannitol, it is worth noting that there was an increase in production in both quintuple mutants at 24 h (Fig. 3 ) \ncompared to that of the M4 strain, being this one of the \nmetabolites that explains the differences between the three strains in the PCA (Fig. 2 ). In order to \nvalidate these hypotheses, the deletion of otsA gene on M4- ΔiclR and the deletion of mtlD gene on both quintuple mutants were carried out. The mtlD deletion in M4- Δgnd increased succinic acid production around 20% respect to the reference at 48 h (Fig. 5 a) and specific production (Table 1 ) at both time points, without altering the growth curve along 48 h, growth rate of log phase (Fig. 5 b and Table 1 ) and glycerol consumption (Fig. 5 c). Mannitol is the most common natural hexitol and can be used as a carbon source in E. coli in a reaction catalyzed by MtlD enzyme, which is involved in the reversible conversion of: D-mannitol 1-P + NAD + ←→ Fructose 6-P + NADH + H + (Reshamwala et al., 2014 ). Therefore, the blockage of mannitol synthesis in gluconeogenesis may avoid C leakage and increase C-flux towards succinic acid. We found that, although the deletion of mtlD on the M4- ΔiclR mutant, does not have a significant effect on succinic acid production, glycerol consumption rate increased at 31 h, so this increment of C-flux is probably diverted to growth but not to succinic acid net production because no differences were observed respect to the reference strain (Fig. 5 b, d and f). On the other hand, the other possible C leakage identified in this study is the synthesis and accumulation of trehalose, a disaccharide which is synthesized from Glucose and Glucose 6-P by trehalose 6-P synthase (OtsA) enzyme under conditions of high osmolarity (Giaever et al., 1988 ). Although trehalose accumulation is observed in the M4- ΔiclR mutant at 48 h (Fig. 3 ), the deletion of otsA enzyme gene, not only did not enhance succinic acid production but also diminish this production as well as the glycerol consumption and affected to the growth curve (Fig. 5 b, d and f) and the growth rate (Table 1 ). As described above, endogenous trehalose is synthesized in stationary phase under physiological stress conditions. As described above, the deletion of otsA gene affects significantly to the growth and consequently to succinic acid production. It has been reported before that otsA mutants are viable but osmotically sensitive in minimal medium (Giaever et al., 1988 ), which is the same medium used in this work. The M4- ΔiclRΔotsA mutant strain is probably also more sensitive to extracellular succinic acid, and this idea is supported by the fact that overexpression of otsA gene improves ethanol tolerance in an engineered strain (Woodruff et al., 2013 ). Therefore, the hypothesis of blocking trehalose synthesis as a C-leakage to increase C-flux towards succinic acid is not supported by the results obtained in the M4- ΔiclRΔotsA mutant since trehalose is performing a significant role in the tolerance to succinic acid. In this sense, it is important to highlight how metabolomics can evidence new targets or phenotypes that the rational metabolic engineering design cannot predict, contributing therefore the implementation of new enhanced producer strains. Table 1 Comparison of the parameters of: growth rate, molar yields, and specific succinic acid production in M4, M4-∆ gnd , M4-∆ iclR, M4-∆ gnd ∆ mtlD (in bold), M4-∆ iclR ∆ mtlD , and M4-∆ iclR ∆ otsA mutant strains . Means and standard deviations were calculated using between four and nine replicates Bicarbonate in M9 medium (HNaCO 3 ) Mutant strains Growth rate (µ) Molar yield (mol succinic acid /mol glycerol consumed) Specific succinic acid production (mmol × g CDW −1 ) 24 h 48 h 24 h 48 h 2 g/L M4 0.12 ± 0.01 0.12 ± 0.00 0.12 ± 0.01 3.05 ± 0.10 3.89 ± 0.24 M4-∆ gnd 0.13 ± 0.01 0.14 ± 0.01 0.14 ± 0.02 3.48 ± 0.23 3.80 ± 0.81 M4-∆ iclR 0.14 ± 0.01 0.13 ± 0.01 0.14 ± 0.01 3.16 ± 0.18 3.72 ± 0.18 4 g/L M4-∆ gnd 0.15 ± 0.02 0.14 ± 0.03 0.13 ± 0.02 4.03 ± 1.23 4.71 ± 1.07 M4-∆ gnd ∆ mtlD 0.15 ± 0.03 0.15 ± 0.03 0.16 ± 0.02 4.55 ± 1.65 5.93 ± 1.20 M4-∆ iclR 0.14 ± 0.02 0.15 ± 0.03 0.15 ± 0.01 5.69 ± 1.65 5.94 ± 0.20 M4-∆ iclR ∆ mtlD 0.16 ± 0.01 0.13 ± 0.01 0.14 ± 0.01 4.26 ± 0.46 5.45 ± 0.43 M4-∆ iclR ∆ otsA 0.11 ± 0.02 0.14 ± 0.05 0.13 ± 0.03 4.75 ± 1.55 5.88 ± 1.48"
} | 5,456 |
36459548 | PMC10936060 | pmc | 5,320 | {
"abstract": "Human-like tactile perception is critical for promoting robotic intelligence. However, reproducing tangential “sliding” perception of human skin is still struggling. Inspired by the lateral gating mechanosensing mechanism of mechanosensory cells, which perceives mechanical stimuli by lateral tension–induced opening-closing of ion channels, we report a robot skin (R-skin) with mechanically gated electron channels, achieving ultrasensitive and fast-response sliding tactile perception via pyramidal artificial fingerprint-triggered opening-closing of electron gates (E-gates, namely, customized V-shaped cracks within embedded mesh electron channels). By imitating cytomembrane to modulate membrane mechanics, local strain is enhanced at E-gates to effectively regulate electron pathways for high sensitivity while weakened at other positions to suppress random cracks for robust stability. The R-skin can directly recognize ultrafine surface microstructure (5 μm) at a response frequency (485 Hz) outshining humans and achieve human-like sliding perception functions, including dexterously distinguishing texture of complex-shaped objects and providing real-time feedback for grasping.",
"introduction": "INTRODUCTION Robot skins (R-skins) have long been anticipated in intelligent robots and prosthetics for reproducing or surpassing human sensing capabilities of external environment ( 1 – 4 ). Many R-skins have been able to mimic human skin well to perceive pressure ( 5 – 7 ), pressure distribution ( 8 – 10 ), shape ( 11 , 12 ), hardness ( 13 ), and compliance ( 14 ) based on diverse pressure sensing mechanisms, and representative applications have been demonstrated for preventing crushing fragile objects in robotic manipulation ( 15 ) or providing neuromorphic information to amputees for perceiving touch and pain ( 16 ). Despite extensive progress in artificial skins, current research primarily focuses on the imitation of vertical “compressing” perception functions of human skin, that is, by squeezing the object surface to acquire physical information, such as object properties or interaction forces ( 17 ). However, another crucial perception function, tangential “sliding” perception of human skin is still struggling to be reproduced by R-skins due to the lack of tangential tactile sensing mechanism, which hinders the full acquisition of dynamic sliding interaction information (e.g., surface texture information, instantaneous slippage, and sliding state) ( 18 , 19 ). Such dynamic interaction information is valuable for robotic intelligent identification, response to transient events, and interactive feedback ( 20 ). Hence, R-skins for sliding tactile perception are urgently desired for providing more comprehensive tactile information and perfecting tactile functions of robots. Human skin has long been the inspiration and reference for various tactile sensors. At present, although some attempts have been made to imitate the sliding tactile functions of human skin by using common sensitization microstructures [porous structures ( 21 , 22 ) and micropillars ( 23 )] or mimicking the epidermis-dermis interlocked microstructures ( 24 – 26 ) of human skin to amplify the tactile stimuli, they essentially rely on the existing vertical compressing sensing mechanism of flexible pressure sensors to convert mechanical stimuli into electrical signals. The underlying mechanoelectrical transduction mechanism and corresponding sensitivity-enhancing mechanism of human tactile sensory cells have not yet been imitated. Besides, typical sliding tactile functions of human skin (such as dexterously distinguishing the surface roughness of complex-shaped objects with narrow space, accurately identifying orientation of textures, perceiving slipping state, and providing real-time tactile feedback) have not been reproduced by these sensors limited by the detection resolution and response frequency, which hinders the development of robotic sliding tactility toward human-like haptics. Tactile sensation of human fingertip skin is achieved by fingerprints (for transmitting mechanical stimuli to mechanosensory cells) ( 24 , 25 ) and mechanically gated ion channels (for converting mechanical stimuli into electrical signals) ( 27 – 30 ) in the cytomembrane of mechanosensory cells ( Fig. 1A ). Many cell experiments in vitro have demonstrated that different mechanical stimuli (compressing, stretching, or fluid shear force) applied to mechanosensory cells are all ultimately translated into membrane deformation-induced lateral tension to pull the ion channels to be opened, allowing the influx of extracellular cations into cells, thus forming physiological electrical signals ( 30 – 33 ) ( Fig. 1B ). Note that even a displacement stimulation of about 10 nm is sufficient to open ion channels and activate ion currents for some cells ( 34 ). Such high sensitivity is related to modulating the mechanical state of cell membrane (e.g., increasing the membrane stiffness) via regulating the membrane components (e.g., binding more cholesterol), which can enhance the local deformation of ion channels to open them efficiently ( 35 ). Conversely, depletion of cholesterol will attenuate the membrane stiffness and the mechanosensitivity ( 35 ), and knockout of the ion channel–related genes will abolish the mechanosensitivity of cells ( 29 ). Therefore, the lateral tension–induced gating sensing mode is the key mechanoelectrical transduction mechanism of human tactile sensory system, and efficient opening of ion channels caused by the modulation of membrane mechanics plays a critical role in enhancing the sensitivity ( 32 , 35 ), but such valuable physiological mechanisms have not yet been imitated and reproduced by R-skins. Fig. 1. Inspiration and design of R-skin for sliding tactile perception. ( A ) Schematic illustration of the tactile sensory system of fingertip skin. ( B ) Sensing mechanism of mechanically gated ion channels. Cholesterol can modulate the membrane mechanical state to facilitate the efficient opening of ion channels. ( C ) Schematic diagram of the R-skin with MGEC and micropyramid-shaped artificial fingerprint. ( D ) Sliding sensing mechanism of the R-skin. The dynamic tension caused by the sliding interaction can induce the opening-closing of E-gates and the consequent tactile electrical signals (top). E-gates opened in an approximate V shape with the increase of strain (bottom). Scale bars, 5 μm. ( E ) Conceptual diagram of surface roughness recognition of complex-shaped objects by a robot equipped with R-skin. ( F ) Photographs of a complex-shaped machined part (top; scale bar, 100 mm) and its four surfaces with different roughness values (bottom; scale bars, 5 mm). ( G ) Recognition signals of the four surfaces with different roughness values of the complex-shaped machined part. Here, inspired by the lateral gating sensing mechanism of human skin, we report an R-skin with mechanically gated electron channels (MGECs), achieving ultrasensitive and fast-response sliding tactile perception. The R-skin is a stably bonded monolithic structure consisting of inner MGEC and outer micropyramid-shaped artificial fingerprint. External mechanical stimuli transmitted from the artificial fingerprint can induce dynamic membrane tension, which can trigger the opening-closing of electron gates (E-gates) in MGEC to regulate the number of electron pathways, thereby encoding mechanical stimuli into tactile electrical signals. Specifically, carbon nanotube (CNT) conductive networks embedded in polydimethylsiloxane (PDMS) mesh channels act as electron channels, within which position-customizable V-shaped cracks were induced to serve as E-gates for gating electron flow. Furthermore, inspired by the membrane mechanical state–controlled sensitivity-enhancing mechanism of mechanically gated ion channels, we can design the mesh channels to modulate the membrane mechanical state under tension, significantly enhancing the local strain at E-gates and weakening that at other positions. Such programmable strain distribution not only can enhance the opening width of E-gates but also can suppress random cracks in CNT electron channels, thus synchronously achieving high sensitivity, robust stability, and regulable performance. On the basis of this modulation strategy, the sensitivity to subtle strain is enhanced by 74 times than the counterpart flat film sensor, enabling a robot to accurately recognize ultrafine surface microstructure with ultrafine sliding detection resolution (linewidth of 5 μm) at a rapid response frequency (485 Hz), surpassing human rapid-adapting (RA) mechanoreceptors (400 Hz). The R-skin can also achieve typical sliding perception functions of human skin, such as dexterously perceiving roughness of complex-shaped objects, accurately identifying texture orientation, detecting slipping state, and providing real-time feedback for grasping, showing promising applications in robotic intelligent recognition and feedback. This work opens up new scientific fields for R-skins by proposing a lateral gating sensing mechanism and a membrane mechanical state–controlled sensitivity-enhancing mechanism.",
"discussion": "DISCUSSION We have developed a bioinspired R-skin for sliding tactile perception based on a lateral gating sensing mechanism inspired by the tactile sensory system of human skin. The proposed R-skin enables the robot to recognize both coarse and fine surface textures just like human skin, endowing the robot with ultrafine sliding detection resolution (linewidth of 5 μm) and rapid response frequency (485 Hz), surpassing that of human RA mechanoreceptors (400 Hz), which are also superior to existing sensors to the best of our knowledge. Such ultrasensitive and fast-response perception capability helps advance the practical application of R-skin for sliding tactile perception, as it addresses the trade-off between the recognition accuracy and efficiency caused by the limited detection resolution and response frequency of existing sensors. Moreover, the R-skin can be attached to the finger to achieve typical sliding perception functions of human skin, such as dexterously distinguishing the roughness of a complex-shaped part with narrow space, accurately identifying texture orientation, perceiving slipping state, and providing real-time feedback for grasping. Such capabilities broaden the applications of the R-skin and cover the shortage of tangential sliding sensing functions of existing artificial skins, showing promising applications in robotic intelligent recognition and interactive feedback. The aforementioned ultrasensitive sensing capability is attributed to the proposed bioinspired lateral gating sensing mechanism. As shown in Fig. 3C , it is the lateral tension–induced opening-closing of E-gates that plays the key role in converting subtle mechanical stimuli into distinguishable tactile electrical signals during the sliding tactile perception. Although some previously reported sliding tactile skins are also constructed by mimicking the structure of human skin, they all imitate the interlocked microstructure between the epidermal and dermal layers for amplifying the tactile stimuli. In essence, they still rely on the traditional compressing sensing mechanism of flexible pressure sensors, which converts mechanical stimuli into electrical signals by compressing the laminated sensing layers. The underlying lateral gating mechanosensing mechanism of tactile sensory cells has not yet been imitated. However, a common phenomenon of the compressing sensing mechanism is that the sensitivity generally decreases significantly with increasing pressure due to the gradually increased compression resistance. During sliding tactile perception, their most sensitive range (small pressure range) will be occupied by the pre-pressure (applied for making the fingerprint of the artificial skin in close contact with objects) in advance, rather than effectively contributing to sliding perception, which inherently limits their sliding perception sensitivity. Besides, for the unique sensing process (dynamic tangential sliding), typically used laminated structures may face challenges in stability due to dislocations or wrinkles between layers. Therefore, we believe that the proposed lateral gating sensing mechanism opens new scientific fields for robotic tactile skins. In addition to the bioinspired lateral gating sensing mechanism of tactile sensory cells, we can also mimic membrane mechanical state–controlled sensitivity-enhancing mechanism of the mechanically gated ion channels in cell membrane to modulate the performance of our R-skin, which is also an innovative bioinspired strategy not reported in previous works. A common phenomenon of many previously reported crack-based sensors is that they achieved high sensitivity at large stretching ( 36 , 40 , 41 ), but their sensitivity in the small strain range is low because of the fact that cracks are not easy to open in the small strain range. However, a high sensitivity in small range is vital and desired for detecting tiny strain. Compared to these sensors, by designing the mesh channels to customize the strain distribution of the sensing membrane, the local strain of MGEC can be enhanced at E-gates to effectively enhance the width of E-gates to improve the sensitivity in small strain range and the detection limit. Compared to the previously reported work ( 44 ), the position of cracks in the CNT network can be precisely customized in our work by designing the parameters of the mesh structure, so better stability was achieved by MGEC because of its unique customizability of crack locations and stable interface, which avoid random crack propagation and interfacial debonding. Such good comprehensive performance of sensitivity in small strain range and stability is exactly what our R-skin requires for amplifying tiny strain during dynamic sliding tactile perception. Moreover, the customized positions of E-gates also endow great convenience for regulating the sensing performance by directly adjusting the distribution of E-gates. We believe that this modulation strategy is universal for other stretchable electronics for modulating membrane mechanical state and controlling crack propagation."
} | 3,574 |
23139811 | PMC3490862 | pmc | 5,322 | {
"abstract": "Some plants can tolerate and even detoxify soils contaminated with heavy metals. This detoxification ability may depend on what chemical forms of metals are taken up by plants and how the plants distribute the toxins in their tissues. This, in turn, may have an important impact on phytoremediation. We investigated the impact of arbuscular mycorrhizal (AM) fungus, Glomus intraradices , on the subcellular distribution and chemical forms of cadmium (Cd) in alfalfa ( Medicago sativa L.) that were grown in Cd-added soils. The fungus significantly colonized alfalfa roots by day 25 after planting. Colonization of alfalfa by G. intraradices in soils contaminated with Cd ranged from 17% to 69% after 25–60 days and then decreased to 43%. The biomass of plant shoots with AM fungi showed significant 1.7-fold increases compared to no AM fungi addition under the treatment of 20 mg·kg −1 Cd. Concentrations of Cd in the shoots of alfalfa under 0.5, 5, and 20 mg·kg −1 Cd without AM fungal inoculation are 1.87, 2.92, and 2.38 times higher, respectively, than those of fungi-inoculated plants. Fungal inoculation increased Cd (37.2–80.5%) in the cell walls of roots and shoots and decreased in membranes after 80 days of incubation compared to untreated plants. The proportion of the inactive forms of Cd in roots was higher in fungi-treated plants than in controls. Furthermore, although fungi-treated plants had less overall Cd in subcellular fragments in shoots, they had more inactive Cd in shoots than did control plants. These results provide a basis for further research on plant-microbe symbioses in soils contaminated with heavy metals, which may potentially help us develop management regimes for phytoremediation.",
"introduction": "Introduction Cadmium (Cd) is a widespread hazardous heavy metal. Many agricultural soils have elevated concentrations of Cd resulting from management practices such the application of sewage sludge or animal manure. Mining activities can also lead to high concentrations of Cd in surrounding lands. These and other practices may threaten environmental quality and sustainable food production [1] , [2] . Excessive concentrations of Cd are toxic to plants and profoundly interfere with a series of physiological processes such as enzyme activity, respiration, photosynthesis, and nutrient assimilation [3] . However, some plants that can grow in Cd-contaminated soils have evolved mechanisms for tolerating heavy metals inside plant cells [4] . There is some evidence that metal tolerance and detoxification in plants can be achieved by confining toxins to a subcellular distribution or by changing their chemical structure. For example, zinc (Zn) and Cd are preferentially stored in vacuoles of the epidermal and mesophyll cells of the Zn/Cd hyperaccumulator Thlaspi caerulescens \n [5] , [6] . Similarly, in Brassica juncea and Arabidopsis thaliana , leaf trichomes appear to be preferential storage and detoxification sites for Cd [7] . In Cd-tolerant Salix viminalis , pectin-rich layers of the collenchyma cell walls of leaf veins are an important Cd sink [8] . Although some recent studies have shown that several plants can tolerate and detoxify Cd, few studies have examined the effects of soil microbes that form associations with these plants, especially arbuscular mycorrhizal (AM) fungi. AM fungi play significant roles in the recycling of plant nutrients, maintenance of soil structure, detoxification of noxious chemicals, control of plant pests, and regulation of plant growth and its interactions with the soil environment [9] , [10] . Plant-microbe symbioses are ubiquitous in both natural and most anthropogenically influenced soils [11] – [13] . In addition, AM fungi have been shown to transport and immobilize Cd in the root system, which reduces the detrimental effects of the metal on plant physiology [14] . Therefore, the use of mycorrhizal plants for land remediation has been proposed. However, how AM fungi might affect other aspects of heavy metal accumulation and distribution in plants remains uncertain. 10.1371/journal.pone.0048669.g001 Figure 1 Arbuscular mycorrhizal colonization (%) of alfalfa ( Medicago sativa L.) exposed to 20 mg kg −1 Cd in soil. Alfalfa ( Medicago sativa L.) is a deep-rooting perennial plant with high biomass production. It grows quickly, is tolerant to drought, and does not have any reported environmental hazards. In this sense, it is an ideal natural resource for the remediation of contaminated soils [15] , [16] . Batch laboratory experiments have determined that alfalfa can bind various heavy metal ions [17] . In addition, alfalfa has been shown to tolerate and take up heavy metals from soil; however, relatively few studies have investigated the effects of AM fungi on the uptake and distribution of metals (and the forms of metals) in alfalfa [18] , [19] . In the present study, we investigated the effects of AM fungi on the growth and subcellular uptake of Cd of alfalfa planted in soil contaminated with Cd. We also examined forms of Cd taken up by the plants and quantified the amounts of each form of Cd in plant tissues. Our results elucidate the interaction among AM fungi, alfalfa, and Cd-contaminated soil, and provide new insights into how AM fungi may affect plant uptake and distribution of heavy metals. 10.1371/journal.pone.0048669.g002 Figure 2 Effect of Cd 2+ toxicity on plant growth in plants inoculated with the AM fungus after 80 days (a: 0.5 mg kg −1 Cd treatment; b: 5 mg kg −1 treatment; c: 20 mg kg −1 treatment) and the biomass of alfalfa for untreated plants (No AMF) and treated plants (AMF) after 25–80 days of growth in 0.5, 5 and 20 mg kg −1 Cd soil (d) (0.5-M means 0.5 mg kg −1 Cd treatment without AM fungal inoculation; 0.5+M means 0.5 mg kg −1 Cd treatment with AM fungal inoculation).",
"discussion": "Discussion Certain plants can be used to clean up contaminated soils and waters. This detoxification ability may depend on what chemical forms of metals are taken up by plants and how the plants distribute the toxins in their tissues, and hence these factors may impact phytoremediation efforts [25] – [27] . One such plant is alfalfa, which is widely distributed in both contaminated and uncontaminated areas of China [15] . We investigated the subcellular distribution and chemical forms of Cd in alfalfa ( Medicago sativa L.) inoculated with the arbuscular mycorrhizal (AM) fungi Glomus intraradices and planted in contaminated soil. Our results indicate that AM fungi have the potential ability of reducing Cd accumulation and beneficial consequences of mycorrhizal associations on plant growth in heavy metals contaminated soil. High concentrations of Cd were toxic to alfalfa plants lacking AM fungi, which significantly decreased biomass. However, AM fungal inoculation significantly increased the biomass of roots and shoots compared to untreated plants and there were no significant differences on the biomass with AM fungal inoculation under 0.5 mg kg −1 and 5 mg kg −1 Cd treatments ( Fig. 2 ). In present study, AM fungi alter Cd transformation in alfalfa and resist Cd toxicity by reducing Cd uptake from roots to shoots, distributing Cd in the subcellular fractions of cell walls, restricting Cd accumulation in membranes, and isolating Cd in an inactive state in roots and shoots. Plants that accumulate and/or tolerate Cd have evolved mechanisms to resist taking up metals in the soil and/or to tolerate metals inside cells [28] . Some mycorrhizal fungi that grow in association with plants have been shown to reduce the accumulation of certain heavy metals in the shoots of host plants, presumably by increasing metal retention within roots [11] , [29] . Indeed, in the present study, plants inoculated with AM fungi had larger amounts of Cd in their roots and smaller amounts in their shoots ( Fig. 3 ), improving the plants’ resistance to Cd toxicity compared to controls. In addition, AM-treated plants distributed more Cd in subcellular fractions of tissues, further reducing Cd accumulation in membranes ( Table 1 , Fig 4 ). Excessive accumulation in plant membranes would destroy cell activity and thus inhibit plant growth [25] , [26] . Hence, selective distribution of toxins might be an important strategy for heavy metal tolerance and detoxification in plants. The fungi-treated plants also sequestered more Cd in cell walls. Cell walls are mainly composed of cellulose, hemicellulose, pectin, and protein, whose surfaces tend to be negatively charged [30] , serving as efficient sites for sequestering toxins. Heavy metals that crossed cell walls eventually dissolved and became incorporated into organelles. However, we found that plants with AM fungal inoculation accumulated more Cd in the soluble fractions of roots and shoots. That is, more Cd remained in solution and never entered organelles, suggesting that the soluble fraction serves as another storage compartment for toxins in both roots and shoots. Therefore, the cell matrix between cells and organelles could be considered an intracellular buffer [31] . Soluble cellular components not only store heavy metals but also contain organo-ligands, which are mainly sulfur-rich peptides, organic alkali, and organic acids. Complexation of metals with organo-ligands within such storage sites decreases free ion activity and thus reduces toxicity [32] . Finally, AM fungi also improved tolerance to Cd by seemingly converting Cd into inactive forms, as treated plants had significantly more inactive forms of Cd in roots and shoots than did untreated plants. Different chemical species of heavy metals have different biological functions, with distinct toxicities and migration patterns [4] , [33] . For example, water-soluble Cd has a high capacity to migrate and is more deleterious to plant cells, whereas Cd in forms such as metal-phosphate complexes shows no or little toxicity to plants. In the present study, there was a significant increase in the proportion of inactive forms of Cd in the subcellular fractions of both roots and shoots of fungi-treated plants compared to controls ( Fig. 5 ). Among these fractions, a large proportion of Cd was integrated with pectates and protein, suggesting that Cd may have been chelated by a polar material such as a hydroxyl or carboxyl group, forming a non-toxic complex. Although heavy metal pollutants had significant effects on AM fungi in soil [34] , [35] , numerous studies have demonstrated that symbiotic interactions between plants and AM fungi may improve plant tolerance to and uptake of heavy metals [36] – [38] . So inoculation of AM fungi would be important in phytoremediation of soils contaminated with heavy metals. Even some propagules of indigenous fungi already exist in soil, there may be competition among AM fungi with different ability of colonization. Therefore, inoculation of target AM fungal species that have been demonstrated to be effective in detoxification would be helpful to improve the efficiency of phytoremediation. In summary, inoculation of AM fungi significantly enhanced the growth of alfalfa plants in a Cd-contaminated soil, increased total Cd in roots but decreased Cd concentrations in shoots. Our results also showed that AM fungi increased the proportion of Cd in cell wall while reducing the proportion in organelles and membranes. Moreover, AM fungi increased the proportion of inactive forms of Cd in roots and shoots. Together, our results illustrate that AM fungi enhanced plant resistance or tolerance to Cd through altering both the forms of Cd and the distribution of Cd among different plant tissues. These findings provide new insights into the roles of plant-microbe symbioses in mediating the impact of heavy metals on plants and highlight the need of further research on the contribution of AMF to phytoremediation."
} | 2,968 |
37110287 | PMC10145494 | pmc | 5,323 | {
"abstract": "Heavy-metal contaminants are one of the most relevant problems of contemporary agriculture. High toxicity and the ability to accumulate in soils and crops pose a serious threat to food security. To solve this problem, it is necessary to accelerate the pace of restoration of disturbed agricultural lands. Bioremediation is an effective treatment for agricultural soil pollution. It relies on the ability of microorganisms to remove pollutants. The purpose of this study is to create a consortium based on microorganisms isolated from technogenic sites for further development in the field of soil restoration in agriculture. In the study, promising strains that can remove heavy metals from experimental media were selected: Pantoea sp., Achromobacter denitrificans , Klebsiella oxytoca , Rhizobium radiobacter , and Pseudomonas fluorescens . On their basis, consortiums were compiled, which were investigated for the ability to remove heavy metals from nutrient media, as well as to produce phytohormones. The most effective was Consortium D, which included Achromobacter denitrificans , Klebsiella oxytoca , and Rhizobium radiobacter in a ratio of 1:1:2, respectively. The ability of this consortium to produce indole-3-acetic acid and indole-3-butyric acid was 18.03 μg/L and 2.02 μg/L, respectively; the absorption capacity for heavy metals from the experimental media was Cd (56.39 mg/L), Hg (58.03 mg/L), As (61.17 mg/L), Pb (91.13 mg/L), and Ni (98.22 mg/L). Consortium D has also been found to be effective in conditions of mixed heavy-metal contamination. Due to the fact that the further use of the consortium will be focused on the soil of agricultural land cleanup, its ability to intensify the process of phytoremediation has been studied. The combined use of Trifolium pratense L. and the developed consortium ensured the removal of about 32% Pb, 15% As, 13% Hg, 31% Ni, and 25% Cd from the soil. Further research will be aimed at developing a biological product to improve the efficiency of remediation of lands withdrawn from agricultural use.",
"conclusion": "5. Conclusions This study featured ten pure microbial strains isolated from technogenically disturbed soils. Achromobacter denitrificans , Klebsiella oxytoca , and Rhizobium radiobacter proved suitable for a consortium. Achromobacter denitrificans utilized 40.03 mg/L As from the nutrient medium. It also was effective in removing Hg (73.08 mg/L), Pb (71.10 mg/L), and Cd (62.41 mg/L). Klebsiella oxytoca utilized 51.14 mg/L Pb, 51.33 mg/L Hg, and 78.02 mg/L Cd. Rhizobium radiobacter had the best results for Ni (56.94 mg/L), Hg (61.57 mg/L), and Pb (74.26 mg/L). These microorganisms proved to be biocompatible and did not inhibit each other’s growth. We united the microorganisms into microbial consortiums and tested their ability to synthesize phytohormones. Consortiums D and C synthesized the largest number of phytohormones. They had good prospects for the phytoremediation method, but this fact needs additional investigation. Consortium D had the optimal ratio of Achromobacter denitrificans , Klebsiella oxytoca , and Rhizobium radiobacter as 1:1:2. This consortium removed 56.39 mg/L Cd, 58.03 mg/L Hg, 61.17 mg/L As, 91.13 mg/L Pb, and 98.22 mg/L Ni from the medium with individual heavy metals. The same consortium also utilized 47.33–83.26 mg/L of composite pollutants, which included Pb, As, Hg, Ni, and Cd. Consortium D spotted no significant decrease in biomass accumulation during cultivation in environments with separate and composite heavy-metal-contaminated media. The optimal pH for Consortium D was pH = 7, while the greatest biomass accumulation was observed at 25–30 °C. The resulting consortium is effective against mixed pollution with heavy metals, increasing the phytoremediation ability of plants. It is assumed that Consortium D is also able to increase the establishment of plants in disturbed areas, however, additional experiments are needed to confirm the data. Further research will be aimed at developing a biological product to improve the efficiency of remediation of lands withdrawn from agricultural use.",
"introduction": "1. Introduction Rapid population growth and industrialization increase human demand for food. Only larger and more productive agricultural areas can provide food security [ 1 , 2 ]. Unfortunately, the ever-growing anthropogenic load affects the productive properties of agricultural soils and their fertility by causing organic matter reduction, nutrient depletion, pollution with heavy metals, pesticides, mineral fertilizers, polycyclic aromatic hydrocarbons, etc. [ 3 , 4 ]. Poor agricultural practices and management of water and land resources cause a drastic decline in agricultural soil quality and induce disastrous economic losses [ 5 , 6 , 7 ]. This situation poses an urgent task of reducing the degradation rate of disturbed farming lands and increasing its restoration rate. This task is one of the 17 main goals of sustainable development defined by the United Nations through 2030 [ 8 ]. Global agricultural communities are particularly concerned with the current heavy-metal contamination of agricultural lands. Heavy metals are highly toxic compounds that can persist in soils for a long time. Cd, Pb, Zn, and Cu enter agricultural soil with fertilizers, including organic ones. However, arsenic and mercury can also mix with agricultural soil if the field is located near industrial enterprises [ 9 , 10 , 11 ]. Moreover, heavy metals are prone to bioaccumulation. They are known to accumulate in agricultural crops, thus changing their biochemical and physiological processes [ 12 ]. Not only do they reduce plant productivity, but they also lead to necrosis of plant tissues, if allowed to reach high concentrations [ 13 , 14 ]. Heavy metals enter living organisms with agricultural products. As a result of biomagnification, they accumulate until they become a serious threat to the health of animals and people [ 15 , 16 ]. Anthropogenic, or technogenic, soil contamination with metals occurs as a result of the activities of mining enterprises, the burning of enterprise waste, oil and oil product spills, transport emissions, industrial and domestic waste dumps, etc. [ 17 , 18 ]. Left unattended, industrial waste causes heavy metals to migrate to agricultural areas as a result of heavy rains, natural erosion, or microbial activity [ 19 , 20 ]. Agriculture is another source of heavy-metal contamination of soil. For example, excessive Cd, Cu, and As can be associated with a severe overuse of chemical fertilizers. Cd is an important metal component of phosphate ore, which is used in phosphate fertilizers, and may also contain As [ 21 ]. Herbicides and pesticides also contribute to the pollution of agricultural soils. For instance, Defarge et al. proved that pesticides contain Cr, Co, Pb, and Ni [ 22 ]. Bai et al. reported that the content of Co, Zn, and Cu in greenhouse soils correlates with the cultivation time. These pollutants probably accumulated due to fertilizers [ 23 ]. Heavy metals can be removed from soil by physicochemical or biological methods. Physical and chemical methods include replacement of the soil layer, electrokinetic removal, thermal treatment, soil washing, vitrification, and chemical treatment with lime, phosphate compounds, or organic compounds [ 15 ]. Each group of methods has its own advantages and disadvantages. Physicochemical methods are efficient and fast while being expensive and labor-consuming. Eventually, they can cause drastic changes in soil quality indicators. Therefore, physicochemical methods provide no optimal solution in agriculture [ 15 ]. Biological treatment is a good alternative because it is economical and environmentally friendly. Biological methods rely on plants (phytoremediation) and microorganisms (bioremediation) [ 24 ]. Bioremediation has attracted a lot of scientific attention in recent years. Its mechanisms are based on redox transformations, absorption, and changes in the reaction of the medium. Currently, the most common methods of microbial removal of heavy metals are biosorption–bioaccumulation, production of biosurfactants, bioleaching, oxidation–reduction, biovolatilization, biomineralization, etc. [ 25 ]. Microorganisms are able to develop protective systems to avoid negative effects; however, most heavy metals destroy the membranes of microbial cells. Therefore, the ability of microorganisms to remain viable under the influence of heavy metals in the restoration of disturbed areas is of decisive importance [ 26 ]. According to literature data, it is possible to use Bacteroidetes and Firmicutes for As-contaminated areas. Their abundance positively correlates with this pollutant in contaminated areas. It is also noted that proteobacteria are resistant to high concentrations of Zn, as well as Pb [ 27 ]. The toxicity and mobility of most heavy metals, e.g., Cu, Se, Pb, Cr As, or Ni, depend on the oxidation degree [ 28 ]. Using these pollutants as food sources, microorganisms change their redox potential [ 29 ]. Yang et al. showed that stimulation of native microorganisms reduced Cr (VI) to Cr (III). Its carcinogenic and mutagenic properties make hexavalent Cr more toxic than trivalent. When ingested with food, it causes respiratory problems and allergies [ 30 ]. Under the stress caused by heavy metals, some microorganisms are able to secrete extracellular polymeric substances, such as polysaccharides, proteins, and lipids containing numerous binding sites that can bind heavy-metal ions. As a result, heavy metals are adsorbed on the surface of the cell wall. For example, Klebsiella pneumoniae Kpn555 isolated from coffee waste was found capable of Pb bioaccumulation, and its maximal biosorption capacity was 475 mg/g. In some cases, metals accumulate intracellularly in the cytoplasm, where they are transformed under the action of enzymes [ 31 ]. The biosorption abilities of microorganisms can accelerate ex-situ remediation. Soil microbial communities are stable and maintain various ecological processes, e.g.,: Nutrient cycle [ 32 ]; Organic carbon balance and degradation [ 33 ]; Prevention and treatment of plant diseases [ 34 ]. Some native microbial strains can reduce the concentrations of heavy metals in soil. For example, Aspergillus niger M1DGR, which was isolated from the industrial soil of Hattar, Pakistan, demonstrated extremely high bioaccumulation; it was able to extract 98% Cd and 43% Cr [ 35 ]. Stenotrophomonas rhizophila JC, isolated from the contaminated soil of Jinchang (China), was able to remove 76.9% Pb and 83.4% Cu [ 36 ]. It should be noted that the most promising is the isolation of microorganisms from technogenically disturbed soils that are subjected to heavy-metal contamination for a long time. Such microorganisms are resistant to aggressive environmental conditions and in the process of adaptation are able to acquire the necessary destructive properties. The joint use of microorganisms and plants is also promising. It is well known that soil microorganisms can affect the mobility and bioavailability of heavy metals by dissolving metal phosphates, releasing chelating agents, and causing redox changes [ 37 ]. In addition, some bacteria are able to synthesize phytohormones, having a positive effect on plant growth and development. For example, Rhizobium pusense KG2 is reported to be able to immobilize Cd 2+ in soil, stimulate plant growth, and improve plant resistance to Cd [ 38 ]. The most promising for the restoration of agricultural soils was the use of meadow clover ( Trifolium pratense L.). It is widely used as a high-quality fodder, green manure plant, and soil and water conservation plant. Literature evidence suggests that T. pratense has high photosynthetic and antioxidant activity. In addition, most of the heavy metals are concentrated in the root system, indicating that it may have a good potential to resist heavy-metal toxicity and promote effective detoxification of contaminated sites [ 39 ]. The purpose of this study is to create a consortium based on microorganisms isolated from technogenic sites for further development in the field of soil restoration in agriculture.",
"discussion": "4. Discussion The data obtained were consistent with the results obtained by other scientists. For example, Achromobacter has been used to bioremediate soils contaminated with heavy metals. Achromobacter sp. L3 can immobilize and remove divalent cadmium [ 60 ]. Ni et al. showed that K. Oxytoca isolates are resistant to such heavy metals as Cu 2+ (84.8%), Pb 2+ (80.8%), Cr 3+ (66.4%), Zn 2+ (66.4%), and Hg 2+ (49.6%) [ 61 ]. According to Alboghobeish et al., some strains of K. oxytoca isolated from industrial wastewater were resistant to Ni 2+ [ 62 ]. Some representatives of Rhizobium were resistant to high concentrations of heavy metals. They also had good nitrogen-fixing capacity and thus improved plant growth, allowing them to be used as biofertilizers [ 63 , 64 ]. The ability of microorganisms to intensify plant growth and produce growth-stimulating substances is widely covered in the scientific literature. Thus, in a study by Mogal et al., leguminous plants treated with Rhizobium spp. observed an increase in the content of indoleacetic, indolebutyric, gibberellic, and other acids in the roots [ 65 ]. The ability to produce phytohormones in Achromobacter denitrificans is also confirmed. In a study by Singh et al., this microorganism showed the ability to synthesize indoleacetic acid. In addition, the ability of this microorganism to produce siderophores, ammonia, and organic acids was noted [ 66 ]. Phytostimulating activity was also noted in bacteria of the genus Klebsiella . For example, Mitra et al. reported that Klebsiella michiganensis produced indole-3-acetic acid and also carried out phosphate solubilization and nitrogen fixation [ 67 ]. Thus, a consortium including Achromobacter , Rhizobium , and Klebsiella may have prospects for application in agriculture, not only contributing to the removal of heavy metals from contaminated soils, but also stimulating the growth of plants in the disturbed area. Consortium D (presented in this paper) is designed to be effective in heavy-metal removal due to its ability to operate under mixed contamination conditions. Currently, most of the developed microbial preparations are aimed at removing one or two, and less often three, metals [ 68 , 69 , 70 ]. Consortium D is active against five heavy metals at once, which include Pb, As, Hg, Ni, and Cd. The elimination of mixed pollution by heavy metals is an urgent problem that is widely reported in the scientific community. For example, Liu et al. have established the effectiveness of manganese-oxidizing bacteria against mixed pollution of As, Pb, and Cd. According to the presented data, the removal of As, Pb, and Cd in the composite phase of polluted water varied from 22 to 35% [ 59 ]. This is less efficient than the use of the Consortium D developed in this study. The absorption of metals from the aquatic environment for it ranged from 47 to 83%. In addition, the microorganisms included in the consortium are native, isolated from the technogenically disturbed territories of the region. Accordingly, they are adapted to the soil and climatic conditions of the restored areas. Due to the ability of microorganisms to remove heavy metals from the environment, as well as to intensify the growth and development of plants, it is promising to use a combination of phyto- and bioremediation methods. This is confirmed by the data of modern scientific literature. It is reported that the inoculation of Miscanthus sinensis A. with the Pseudomonas koreensis AGB-1 strain increased the solubilization of heavy metals, as well as their availability in the plant rhizosphere. In addition, a decrease in oxidative stress from heavy metals was observed, as well as an increased increase in biomass in Miscanthus sinensis A [ 71 ]. Durand et al. found that plant inoculation with PGPR Variovorax NB24 resulted in increased nickel accumulation in roots and aerial parts [ 72 ]. Further research in the field of bioremediation of heavy metals will explore the mechanisms of removal of pollutants from the environment. A better understanding of the processes will improve cleaning efficiency. The consortium created within the framework of this work has great prospects not only in soil cleanup. His further research can be directed to the development of sorption systems by the method of immobilization on a solid support, which is currently a promising direction [ 56 ]. Adsorption systems obtained by this method can be used to treat industrial wastewater, as well as industrial water contaminated with heavy metals. However, further research is required in this area in order to select a carrier that allows reaching the maximum degree of purification and is easily removed from the treated areas."
} | 4,248 |
24387194 | PMC3890548 | pmc | 5,324 | {
"abstract": "Background Comparative genomics is a powerful approach for studying variation in physiological traits as well as the evolution and ecology of microorganisms. Recent technological advances have enabled sequencing large numbers of related genomes in a single project, requiring computational tools for their integrated analysis. In particular, accurate annotations and identification of gene presence and absence are critical for understanding and modeling the cellular physiology of newly sequenced genomes. Although many tools are available to compare the gene contents of related genomes, new tools are necessary to enable close examination and curation of protein families from large numbers of closely related organisms, to integrate curation with the analysis of gain and loss, and to generate metabolic networks linking the annotations to observed phenotypes. Results We have developed ITEP, an Integrated Toolkit for Exploration of microbial Pan-genomes, to curate protein families, compute similarities to externally-defined domains, analyze gene gain and loss, and generate draft metabolic networks from one or more curated reference network reconstructions in groups of related microbial species among which the combination of core and variable genes constitute the their \"pan-genomes\". The ITEP toolkit consists of: (1) a series of modular command-line scripts for identification, comparison, curation, and analysis of protein families and their distribution across many genomes; (2) a set of Python libraries for programmatic access to the same data; and (3) pre-packaged scripts to perform common analysis workflows on a collection of genomes. ITEP’s capabilities include de novo protein family prediction, ortholog detection, analysis of functional domains, identification of core and variable genes and gene regions, sequence alignments and tree generation, annotation curation, and the integration of cross-genome analysis and metabolic networks for study of metabolic network evolution. Conclusions ITEP is a powerful, flexible toolkit for generation and curation of protein families. ITEP's modular design allows for straightforward extension as analysis methods and tools evolve. By integrating comparative genomics with the development of draft metabolic networks, ITEP harnesses the power of comparative genomics to build confidence in links between genotype and phenotype and helps disambiguate gene annotations when they are evaluated in both evolutionary and metabolic network contexts.",
"conclusion": "Conclusions The ITEP toolkit integrates a large number of existing bioinformatics tools into a single cohesive, flexible framework for comparative analysis of physiological variation in microbial pan-genomes. The modular design of the toolkit makes it straightforward to add additional functionality to the toolkit, as illustrated by our implementation of novel tools for generation of draft metabolic reconstructions from a curated reference network. It also makes the analysis very flexible, empowering researchers to quickly develop analysis workflows while also providing a wide array of tools for curation of annotations and gene calls. The ability to rapidly curate protein families and propagate metabolic networks from reference organisms to related strains will streamline the process of generating high-quality physiological and evolutionary hypotheses and ultimately lead to an improvement in the inter-genome consistency of metabolic models of microbes.",
"discussion": "Results and Discussion Test data set We chose to use the Group 1 Clostridia as a test case to illustrate capabilities of the ITEP toolkit. This metabolically diverse phylogenetic clade includes industrially important organisms such as the solventogenic organisms Clostridium acetobutylicum and C. beijerinckii , as well as several medically important strains such as C. perfringes and C. botulinum [ 49 ]. C. botulinum and C. perfringes genomes have both been heavily sampled, therefore providing the opportunity to study genetic differences at both species and at the genus-scale. In addition, manually-curated metabolic models are available for C. acetobutylicum ATCC 824 [ 50 , 51 ] and C. beijerinckii NCIMB 8052 [ 52 ], affording an opportunity to use ITEP to examine metabolic differences between these and the other Clostridium species in the clade. The species belonging to the Group 1 Clostridia were determined based on the PATRIC database [ 53 ] and the ARB Living Tree 16S rRNA tree [ 54 ]. All complete and draft genomes from this group were downloaded from RefSeq in March 2013 (including plasmids) along with the genome of an outgroup organism, Acetobacterium woodii . Overall, 26 complete and 26 incomplete Clostridia genomes were downloaded and analyzed (see Additional file 3 for complete strain names and RefSeq accession numbers). The test dataset was chosen to be relatively small for purposes of illustration. ITEP currently supports creation of databases containing up to about 200 genomes on a modern workstation with 1 TB of hard drive space, 16 GB of RAM, and 12 processors (using which all vs. all BLAST, MCL, and RPSBlast would take about 6 days altogether). Disk space and time requirements grow as O(N 2 ) where N is the number of genomes. In this example, MCL was used to perform clustering and predict protein families. The relative strengths of this and other methods for predicting protein function have been reviewed at length [ 13 , 55 - 57 ]. Importantly, if the user desires to use different algorithms for clustering, ITEP supports exporting subsets of BLAST data in formats convenient for import into clustering tools, importing the clustering results back into the SQLite database, and applying the same workflows as described here to interpret and curate them. Complete tutorials for performing the analyses described in this section and many others are available in the package documentation (included as Additional file 4 , matching the version of ITEP code provided as Additional file 5 ). A link to an up-to-date web version of this documentation and code is linked to from the project website ( https://price.systemsbiology.net/itep ). Analysis of gene gain and loss patterns across phylogeny As a starting point for the analysis of the Group 1 Clostridia pan-genome, we used ITEP to compute the number of conserved gene families (one member or more in every organism) in each clade in the Group 1 Clostridia and in A. woodii (Figure 2 ). The results indicate that a large number of genes are conserved between closely related strains (such as C. sporogenes and C. botulinum A, B and F subtypes) but the number of conserved genes drops off rapidly as more diverse strains are added. The identities of the conserved genes can easily be extracted from ITEP and used to examine physiological differences between the clades of organisms and at what point a particular function was lost. In the same manner, ITEP can be used to identify gene families unique to each clade or those that are found in exactly one copy in each member. Importantly, the curation tools in ITEP can be used to verify conclusions drawn from analyzing these gain and loss patterns (see later sections for some examples). Comparison of draft and complete genomes and curation of protein families Draft genomes are prevalent in many environmental studies, but because they are incomplete, presence and especially absence calls are inherently less certain for them than they are for complete genomes. The grouping capabilities of ITEP are useful for evaluating the quality of draft genomes by comparing their gene content with closely related closed genomes. To illustrate this, we have generated MCL clusters including two different groups of organisms with identical clustering parameters: one group contained only the completely sequenced Group 1 Clostridia species (blue genomes in Figure 3 ), while the other contained both the completely-sequenced genomes and the draft genomes for strains in the same phylogenetic clades as the completely-sequenced species (green genomes in Figure 3 - only those genomes in the same clade were used to minimize differences due to species divergence). By comparing the protein content in these two groups, we found that 561 protein families were conserved in all of the completely sequenced genomes, but that 270 of them (48%) were missing in at least one of the draft genomes in the same clades (see Additional file 3 for a complete list). The protein families that appeared to be missing in some of the draft Group 1 Clostridia genomes but not the complete ones covered many cellular subsystems, including 17 ribosomal protein families (Figure 3 ) and other widely conserved proteins such as the cell division protein FtsZ. When a highly conserved gene appears to be absent in a particular genome but does not have a congruent loss pattern on the phylogenetic tree, these are candidates for missing or wrong annotations or gene calls. Importantly, ITEP includes ways to search for apparently missing genes in the incomplete genomes, making it possible to identify and correct certain types of gene calling and annotation errors. As an example, we have used the tBLASTn wrapper script in ITEP to search for copies of the L20 ribosomal protein in all of the Group 1 Clostridia and in Acetobacterium woodii . The search revealed a complete, uncalled copy of the L20 protein in A. woodii and an uncalled fragment (on the end of a contig) of a L20 protein in C. perfringens CPE F4969. To find evidence that these were real L20 proteins, we used ITEP scripts to pull the homologous sequences suggested by tBLASTn out of the database, align them, and build a maximum-likelihood tree containing these proteins with neighborhoods mapped onto the tree. The multiple alignment confirmed that the newly identified L20 homologs are very similar to called ribosomal proteins in closely-related complete genomes (Figure 4 A and Additional file 6 ), while mapping the neighborhoods of the uncalled genes revealed significant conservation of gene neighborhoods (Figure 4 B), supporting the hypothesis that the identified proteins are really L20 ribosomal proteins and should be included in the gene annotation. The same methodology can also be applied to search for apparently missing metabolic or regulatory genes, which would help fill in gaps that appear when generating models of cellular physiology. In this way, the challenge of accurate gene annotation can be approached both from the bottom up (gene orthology) and top down (relationship to physiological functions), tying together microbial phylogeny and physiology. Draft metabolic reconstruction and curation of metabolic protein families The comparative analysis capabilities of ITEP can be used to generate draft metabolic networks as a starting point for generating high-quality metabolic models of organisms based on their similarity (or lack of similarity) to related genomes. To illustrate this capability, we have generated draft metabolic networks of each completely-sequenced Group 1 Clostridia strain using the published C. beijerinckii model [ 52 ] as a reference. This model was chosen as a reference because it is the most recent and most complete model of a member of the Group 1 Clostridia that has been published. We found that the presence and absence calls for metabolic functions in the other Clostridia were strongly dependent on the chosen homology cutoff: with a relatively stringent cutoff of 0.5, some organisms (such as C. tetani ) appeared to be missing more than half of the 874 gene-associated metabolic reactions in the C. beijerinckii metabolic reconstruction, and even with a very lenient cutoff of 0.1, at least 100 of them were missing in each other organism (see Additional file 3 ). These missing reactions create gaps in the metabolic network that represent either real differences in physiology or incorrect absence calls due to methodological issues such as incorrect clustering, mis-annotation, or missing gene calls. The presence of gaps in reconstructed networks makes it difficult to turn them into functional metabolic models [ 58 ]. The comparative genomics capabilities of ITEP can be used to help identify genes that fix gaps in metabolic pathways (either those generated by using ITEP's clustering capabilities or those built using other tools). For example, the draft metabolic reconstructions for Clostridium botulinum BKT105925 and C. novyi NT based on MCL clustering were predicted to lack the purD enzyme necessary for purine synthesis (down to a homology cutoff of 0.1 maxbit score). No genes were annotated to perform this function in the source GenBank files for these genomes. In an attempt to fill this gap, we used ITEP to perform a tBLASTn search against these two organisms using the copy of purD from C. beijerinckii (Cbei_1060) as a reference. Interestingly, we found a very strong homology between the C. beijerinckii purD and the N-terminal end of much larger proteins in C. botulinum BKT105925 and C. novyi NT (CbC4_1757 and NT01CX_2418, respectively). Searching these genes against the RPSBLAST results that were stored in the ITEP database revealed that the large proteins from C. botulinum BKT105925 and C. novyi NT are in fact fusions of purD and purL (Figure 5 ), in agreement with the assignments based on MetaCyc [ 59 ], RAST [ 26 ], and the SEED [ 60 ]. Therefore, the gap in the metabolic network can be fixed by assigning the same function to both of these genes, making simulations performed using other tools [ 61 - 63 ] more accurate. Figure 5 Curation of a metabolic protein family by comparison with conserved domains. Left side: a portion of the purine synthesis pathway in the group 1 Clostridia. Right side: conserved domain architecture of two purD-purL fusions in the group 1 Clostridia as computed and displayed by ITEP tools (with minor formatting changes). The comparison makes it clear that these two proteins are fusions of purD and purL . See list of abbreviations for full compound names. Only hits to conserved domains with E-values better than 1E-100 are shown."
} | 3,553 |
36532459 | PMC9751014 | pmc | 5,325 | {
"abstract": "Coastal ecosystems deteriorate globally due to human-induced stress factors, like nutrient loading and pollution. Bacteria are critical to marine ecosystems, e.g., by regulating nutrient cycles, synthesizing vitamins, or degrading pollutants, thereby providing essential ecosystem services ultimately affecting economic activities. Yet, until now bacteria are overlooked both as mediators and indicators of ecosystem health, mainly due to methodological limitations in assessing bacterial ecosystem functions. However, these limitations are largely overcome by the advances in molecular biology and bioinformatics methods for characterizing the genetics that underlie functional traits of key bacterial populations – “key” in providing important ecosystem services, being abundant, or by possessing high metabolic rates. It is therefore timely to analyze and define the functional responses of bacteria to human-induced effects on coastal ecosystem health. We posit that categorizing the responses of key marine bacterial populations to changes in environmental conditions through modern microbial oceanography methods will allow establishing the nascent field of genetic counselling for our coastal waters. This requires systematic field studies of linkages between functional traits of key bacterial populations and their ecosystem functions in coastal seas, complemented with systematic experimental analyses of the responses to different stressors. Research and training in environmental management along with dissemination of results and dialogue with societal actors are equally important to ensure the role of bacteria is understood as fundamentally important for coastal ecosystems. Using the responses of microorganisms as a tool to develop genetic counselling for coastal ecosystems can ultimately allow for integrating bacteria as indicators of environmental change.",
"conclusion": "Conclusion We envision that microbes are sensitive sentinels (allowing detection of for example pathogens, nutrient loadings, pollution, and also in the long run as indicators of changes in food web structure in response to, e.g., over fishing) for the identification of undesired changes in the environment. With this view, the use of coastal microorganisms in genetic counselling for the environment could provide guidance for actions to reduce anthropogenic impact on the environment, which involves, e.g., the creation of marine reserves/protected areas or actual changes in legislation for the use of, e.g., fertilizers and pesticides. We posit that the actions presented in our road map for systematically exploring the responsiveness of key bacterial populations to environmental change – in time and space – will become critically important for laying the foundations for future assessment of environmental quality, optimization of coastal management, and policy. This is an urgent issue given the very rapid conceptual and methodological developments in using genetic and genomic analyses to obtain mechanistic understanding of ecological processes – paralleling and interacting with the corresponding developments in, e.g., medical sciences, forensics, biotechnology, and other industries. We believe that informed decisions based on environmental genetic counselling will ultimately aid mitigation of threats to coastal ecosystems posed by human activity, such as global change.",
"introduction": "Introduction Earth is under tremendous pressure from human activities and the resulting global change. Coastal waters are productive ecosystems of high importance to society that suffer greatly from human activities causing water pollution, eutrophication, disrupted nutrient cycles, and loss of biodiversity ( Rockström et al., 2009 ; Nash et al., 2017 ; Halpern et al., 2019 ). Legislative regulations for coastal management differ substantially between countries and continents, which represents a challenge for international agreements to promote coastal ecosystem health. As an example from the continent where we have our affiliations, it can be noted that the overarching aim of the Marine Strategy Framework Directive developed by the European Commission is to attain good environmental status across Europe’s marine environment. We think that achieving good environmental status in coastal marine waters requires actions based on due knowledge of the major ecosystem components – and an essential organism group that is left out of the equation is the bacteria (here denoting prokaryotes; Bacteria and Archaea). So, why consider bacteria? Following the ground-breaking discovery in the early 1980s that planktonic bacteria in the oceans are actively growing and extremely abundant (10 9 cells/L), blossoming research on the metabolism, biodiversity and ecology of marine bacteria rapidly established their paramount role in the degradation of dissolved organic carbon (DOC). Moreover, bacteria regulate biogeochemical element cycles and influence overall marine productivity, processing more than 50% of the carbon fixed by photosynthesis and mediating most transformations of, e.g., nitrogen, phosphorus, and trace metals ( Cole et al., 1988 ; Azam, 1998 ; Falkowski et al., 2008 ; Figure 1A ). Recent advances in microbial oceanography have revealed that bacteria also provide a number of unexpected goods and services that influence ecosystem dynamics and productivity up to the level of fish, including the degradation of pollutants, production of vitamins, degradation of reactive oxygen species and the production of growth hormones ( Amin et al., 2015 ; Durham et al., 2015 ; Cavicchioli et al., 2019 ). Moreover, because of their fast growth rates, bacteria react sensitively and rapidly to changes in environmental conditions. Nevertheless, bacteria have so far essentially been overlooked as indicators of ecosystem health, which has recently been highlighted ( Zhang et al., 2020 ; Cordier et al., 2021 ; Alonso et al., 2022 ; Orel et al., 2022 ), and are currently not integrated in the development of policy making and management strategies to meet and mitigate the challenges imposed by human activity and global change on coastal waters. Figure 1 Illustration of the marine food web and proposed analysis workflow for disentangling linkages between environmental stressors and genomic structure and content of key marine bacteria. (A) Bacteria are fundamental in recycling of nutrients including dissolved organic carbon (black arrows to bacteria) and in providing ecosystem-wide services to higher trophic levels (yellow arrows). (B) Current state of the art methodology is based on sampling of the total nucleic acid (DNA and/or RNA) content of marine environments. (C) Computational analyses provide metagenome-assembled genomes (MAGs) that give unprecedented insights into both the identity of key bacterial populations and the genes underlying their different functional traits. Doughnut shapes represent genomes of such key bacterial populations and the colored doughnut sections denote traits. Co-occurrence network analysis of bacterial populations and their traits (black arrows between genomes) allows for identification of traits responsive to global change variables (blue arrows) and ultimately the ecosystem services supplied by key bacteria. An analogy between human health and ecosystem health is warranted to grasp the potential of the mapping of the genetic basis for bacterial responses to environmental change. In medical practice, obtaining information about genetic disorders to make individually informed choices on medication and risk management – based on advice from genetics counsellors and medical doctors – is a rapidly spreading practice at hospitals worldwide, thanks to the large amount of affordable information gained by genome sequencing of patient material (be it cancer cells or gut microbiomes). In medicine, knowledge sources ranging from patient records to results from animal disease-model experiments (just to mention a few) have been essential to develop the understanding necessary to develop efficient treatments. In marine research, knowledge from time series measurements in the sea and controlled experiments with bacterial assemblages and isolates constitute a corresponding knowledge base ( McCarren et al., 2010 ; Palovaara et al., 2014 ; Fuhrman et al., 2015 ; Bunse and Pinhassi, 2017 ; Landa et al., 2017 ). We find that it is now feasible and pertinent to build the knowledge for genetic counselling for the environment – effectively to interpret and predict alterations in microbial ecosystem functions in response to global change ( Figure 1 ). This is the background against which we call for systematically deploying state-of-the-art methods for genetic and genomic analyses of coastal ecosystems. This would permit identifying and characterizing functional traits of key bacterial populations, so that ultimately – through a dialogue between researchers and policy makers – bacteria can be implemented in environmental monitoring and used to improve the management of our world’s coastal waters. Interrogating linkages between bacterial traits and ecosystem functions Why are bacteria not yet explicitly considered in policy making, marine management practices, or ecosystem models? One central explanation is the lack of morphological traits that distinguish components of marine bacterioplankton – e.g. families, species or populations – which in turn severely complicates the study of their ecology. In this context, it is enlightening to make a comparison with another central plankton group, the photosynthetic eukaryotic and prokaryotic microorganisms referred to as phytoplankton. Importantly, the pronounced (and captivating) morphological differences between several phytoplankton groups allowed aquatic ecologists already in the early 1900s to establish a thorough understanding of functional traits of key taxa in a quantitative manner. Further, the spatiotemporal distribution of key phytoplankton taxa could be shown to vary predictably in relation to environmental conditions ( Falkowski and Oliver, 2007 ). Therefore, major phytoplankton taxa, differing for example in size, motility or pigmentation, are represented in contemporary ecosystem models used for providing guidelines on sustainable management practices of aquatic environments around the globe (e.g., the BALTSEM model for the Baltic Sea). Conceptual and methodological advances in microbial ecology now allow for genetic and genomic characterization of the molecular mechanisms that determine the ecological niches of bacterial taxa ( Figures 1B , C ). We therefore posit that it is now both feasible and pertinent to develop corresponding knowledge of the metabolic and physiological characteristics representing functional traits that distinguish key bacterial taxa ( Martiny et al., 2015 ; Coles et al., 2017 ; Baltar et al., 2019 ). Identification of such functional traits will be the first step to allow for a future inclusion of bacteria in ecosystem models. Bacterial traits and ecosystem function To obtain a thorough and mechanistic understanding of ecosystem functioning we reason that it is important to maneuver aquatic microbial ecology into the territory of trait-based ecology ( Raes et al., 2011 ; Wallenstein and Hall, 2012 ; Brown et al., 2014 ; Krause et al., 2014 ). This includes defining what traits are and how they can be understood. One such example relates to microbial vitamin metabolism. The entire traditional food chain up to fish and birds depends on vitamin B1 produced by microbes. For this, it is possible to determine which bacteria contain the genes encoding vitamin B1 synthesis pathways and assign them to the trait “vitamin B1 synthesis,” and thus identifying the main providers of the ecosystem service “vitamin provision” ( Paerl et al., 2018 ). In a similar manner, one can explore the role of bacteria in carbon cycling through analysis of traits like polysaccharide metabolism (conferred by, e.g., glycosyl hydrolases) and hydrocarbon metabolism (conferred by, e.g., aromatic-ring- hydroxylating dioxygenase genes; this at the same time addresses pollutant degradation traits ( González-Gaya et al., 2019 )). Also a variety of nitrogen and phosphorus cycling-related traits are pertinent to characterize, such as those for uptake or metabolism of different classes of dissolved organic or inorganic nitrogen or phosphorus. This could include genes for aminopeptidases versus phosphatases, which cross talk with the carbon cycle, or more specific traits like polyphosphate metabolism (conferred by purine nucleoside phosphorylases, PNPs), and genes involved in nitrification, denitrification or nitrogen fixation ( Happel et al., 2019 ; Sosa et al., 2019 ). We recognize the challenge associated with defining traits, at an appropriately specific level, to obtain ecologically meaningful interpretations of patterns of trait distribution in nature. Nevertheless, we find that even traits carried by diverse taxa, e.g., nitrogen fixation ( Zehr et al., 2003 ; Hallstrøm et al., 2022 ), provide pivotal insights into the interactions between microbes and the surrounding environment. The potential to characterize linkages between bacteria and ecosystem services A primary requisite to identify the genetics underlying particular traits is the access to detailed data on the genomes of key bacterial populations, which circumvents the dependence on difficult-to-assess differences in morphological or other phenotypic distinctions between taxa. In fact, standards are being developed so that new taxa and their names can be proposed based entirely on genomic information ( Hedlund et al., 2022 ). Due to increasingly high-throughput and cost-effective sequencing methodologies, knowledge is accumulating on the spatiotemporal distribution of microbial groups and populations. In recent years, amplicon sequencing of phylogenetic marker genes (e.g., 16S rRNA) has been complemented by metagenomic and metatranscriptomic (−omics) studies of natural marine communities. Long-term field sampling provides important knowledge on the seasonal dynamics of key bacterial populations ( Fuhrman et al., 2006 ; Teeling et al., 2012 ; Cram et al., 2015 ; Lambert et al., 2019 , 2021 ; Auladell et al., 2022 ), and it has become evident that several ecosystem services are directly dependent on the diversity of bacterial communities ( Galand et al., 2015 , 2018 ; Garcia-Garcia et al., 2019 ). This complements theoretical considerations showing that biodiversity is fundamental for the capacity of natural communities to adapt to environmental change, i.e., the insurance effects of biodiversity ( Yachi and Loreau, 1999 ). However, there is a critical lack of knowledge as to why different bacterial populations become dominant at different times and places or, even more importantly, how different populations influence their environment (i.e., what ecosystem functions they carry out). The answers to these questions are now tractable through molecular studies of the regulation of functional traits encoded in the genomes of key bacterial populations in response to environmental factors ( Krause et al., 2014 ). Hereby we emphasize the use of -omics analyses in combination with the study of physiological and ecological responses. Moreover, the -omics approaches have the potential to resolve evolutionary long term adjustments in microbial communities. The potential of linking -omics and environmental/ecological data has only recently been explored ( Garcia et al., 2020 ; VanInsberghe et al., 2020 ), in part due to a lack of adequate computational methods (bioinformatics). Pioneering advances forming the basis for genetic counselling for the environment span from: 1) mapping bacterial taxa and their dynamics through 16S rRNA gene amplicon sequencing ( Andersson et al., 2010 ; Edgar et al., 2011 ; Herlemann et al., 2011 ), via 2) the development of in situ instrumentation as a basis for non-biased -omics analyses ( Ottesen et al., 2011 ; Bochdansky et al., 2017 ; Charvet et al., 2019 ), and 3) metagenomics and metatranscriptomics whereby functional genes are identified and their expression quantified ( Gifford et al., 2013 ; Bunse et al., 2016 ; Rognes et al., 2016 ; Markussen et al., 2018 ; Alneberg et al., 2018b ; Oberbeckmann et al., 2021 ), to 4) the present frontier, where it is possible to define bacterial populations and obtain genomes for key populations from metagenomic datasets, i.e., metagenome-assembled genomes (MAGs; Albertsen et al., 2013 ; Alneberg et al., 2014 ; Hugerth et al., 2015 ; Alneberg et al., 2018a ; Figure 1C \n ) . Moreover, from the content of functional genes in MAGs, their ecological niches across gradients of environmental conditions can be predicted, e.g., temperature, salinity, (in) organic nutrients and pollutants ( Delmont et al., 2019 ; Alneberg et al., 2020 ; Cerro-Galvez et al., 2021 ; Pereira et al., 2021 ; Sjöqvist et al., 2021 ; Sun et al., 2021 ). Ultimately, this will move the field forward by determining how ecosystem services are distributed among key bacterial populations, rather than at community level as done before. Adoption of MAG-assembly combined with long read sequencing approaches have recently given insights into the distribution of bacterial populations and their traits across the vastness of the open ocean ( Ibarbalz et al., 2019 ), while leaving major blank spaces for the coastal seas. MAGs combined with metagenomic data sampled across environmental gradients can even reveal intra-species population structures and genes under environment-specific selection ( Delmont et al., 2019 ; Sjöqvist et al., 2021 ). The finding of such strong links between bacterial genomes and the ecological niche provides a solid conceptual framework for predictive ecology based on genomic data from the environment. This allows, for the first time, to resolve some long standing yet urgent tasks: to determine how ecosystem services are distributed among marine bacteria ( Ducklow, 2008 ), how key bacterial populations are affected by human impacts on coastal waters ( Hutchins and Fu, 2017 ), and, in turn, how changes in bacterial abundances and activities influence the ecosystem, and vice versa ( Azam and Malfatti, 2007 ). Now it is time to apply this knowledge to assess how human pressures on coastal waters influence bacterial communities and their ecosystem services. This has the potential to contribute evidence-based knowledge in both academic and non-academic settings where policies are shaped. Research strategy into the future We propose that systematic study of the microbial oceanography in coastal seas through the lenses of molecular biosciences could pave the way for the integration of bacteria into environmental management. In practice, we envision the following “road map”: Compilation of prokaryotic biodiversity data (16S rRNA gene amplicons) from coastal locations, i.e., compilation and meta-analysis of existing data sets by taking advantage of existing projects and tools. Establishment of MAG libraries from metagenomes across coastal locations of interest; through field sampling to identify key bacterial populations and their functional potentials; i.e. putative traits. Identification of expressed traits from metatranscriptomes; field study catalogue of expressed genes from prokaryotic communities in general, and key bacterial populations (MAGs) in particular, from coastal locations. Experimental testing of the regulation of key traits; environmental factors and anthropogenic stressors as determinants of trait responses of bacterial assemblages and key bacterial populations (MAGs). Experimental testing of anthropogenic stressor effects on functional responses and traits in single isolates or mixtures of isolates representative of the major taxa of coastal marine bacterial communities. Cross validation of trait responses to individual stressors in key bacterial populations of different coastal seas (international meta-analysis of linkages between environmental stressors and particular bacterial functional traits and taxa). Establishment of national or regional “meeting points” for dialogue and collaborations with society – national environmental protection agencies, and local and regional authorities and industry. Establishment of an international collaborative group to generate efficient layman descriptions/summaries of research findings – aimed at general public/education and authorities – to outline the utility of genetic counselling for the environment. We think that systematically following such a road map would decipher the functionality and regulation of key bacterial populations in coastal waters. To reach this goal, it would be necessary to consolidate and develop existing computational methods for linking genes and populations to ecosystem services ( Figures 1B , C , 2 , “Bioinformatics”). An ambitious goal is then to delineate and ultimately predict the functionality of key bacterioplankton organisms via approaches ranging in complexity from time-resolved in situ studies ( Figure 2 , “Field studies”) to hypothesis-driven experiments with natural assemblages and/or experiments with single and multiple bacterial strains ( Figure 2 , “Experiments”). Such experiments could be done in both microcosms (up to some liters) and mesocosms (hundreds of liters) to address scale-dependent ecological processes. Together, these approaches are suited to address the overarching aim of resolving how traits and ecosystem functions are distributed among key bacterial populations present in coastal ecosystems, and how the abundance and activity of these bacteria – and thus their ecological traits – are affected by environmental factors in general, and environmental factors directly affected by global change in particular. In this framework, marine stations along the coasts of Europe are used as an example ( Figure 2 ), but it can be applied and implemented globally. In parallel with these advances, it is necessary to engage in outreach and dissemination of research findings to a broad public along with training to bridge knowledge of microbial ecology and microbiome research with understanding of practices in management and governance ( Figure 2 , “Coastal Management”). Figure 2 Research strategy to obtain comprehensive understanding of the genetic responses of key marine bacteria to environmental stressors in coastal waters, using European waters as an example. Bioinformatics for developing computational tools and workflows to effectively interpret linkages between functional traits and environmental factors. Field studies to generate and evaluate data on traits of key bacterial populations (from genomes and transcriptomes) and their distributions in time and space in relation to variability in environmental conditions. Experiments to identify and confirm relationships between environmental factors and specific traits and bacterial populations. Synergies between computational analyses of genomics, distributions and measured variability in environmental variables from field studies and experiments are essential to identify how bacterial functional traits can form the basis for genetic counselling of coastal seas. Dialogs with societal actors through all steps in the research strategy will be needed for reaching the goal of using bacteria to improve the quality of actions in coastal management.",
"discussion": "Discussion A fundamental incentive for this Perspective is the unifying framework of molecular biosciences, which daily brings important new knowledge to humanity, be it on human evolution, history, forensics, or medical sciences. Microbial oceanography pioneered the study of bacterial ecology and diversity using molecular methods ( Giovannoni et al., 1990 ; Fuhrman et al., 1992 ; Béjà et al., 2000 ; Venter et al., 2004 ), setting the stage for the ongoing quest in environmental and medical sciences alike, to understand the interdependencies between microbiomes (i.e., microbial community composition and dynamics) and their “environment,” using the “omics” approaches (genomics, transcriptomics and proteomics; applied to tissues, cell lines, model bacteria and natural communities [termed “meta-omics” when applied to the latter]). Coastal waters are highly valuable ecosystems with regard to the services they provide; e.g. fish and shellfish production, recreation, and waste assimilation. Understanding the factors that influence the productivity and stability of coastal ecosystems is therefore of utmost importance for a sustainable management of these regions. Working toward implementing genetic counselling for the marine environment is pertinent because increasing anthropogenically induced environmental disturbances, such as eutrophication and climate change, are placing numerous stressors on life in the oceans. It is also timely because, for the first time, we can decipher the functional role of key bacterial populations. Via advanced molecular techniques, the genes maintained and expressed by microbes can now be identified – revealing the functionality of these organisms and their linkages to prevailing environmental conditions and nutrient biogeochemistry. This facilitates the prediction of ecosystem services provided by global coastal waters in the future – a prerequisite for early mitigation of human impact and a critical step for identifying the societal actions required to ensure sustainable management of these sensitive regions in the face of global change. We think it is timely to incorporate the emerging knowledge of genetics and ecology of bacteria – understood as genetics counselling for the environment – into developing increasingly sustainable management strategies and evaluation processes ( Cordier et al., 2021 ). Beyond the systematic exploration of the relation between functional traits of key bacterial populations and environmental conditions, this requires education of the next generation of researchers with special emphasis on bridging bioinformatics, molecular biology, marine ecology, and ecosystem management. A prerequisite for success in this direction is interdisciplinary research involving modern environmental microbiology – computational and molecular biology, physiology, microbial oceanography and ecology – along with involvement of stakeholders in coastal management. Dissemination of results is an important component, as nicely exemplified through the TARA oceans project. 1 In the outlined research strategy, continued use of and design of new coastal time-series stations will be critical for cross-system identification of environmental drivers of bacterial functionality – linkages between the environment and the processes carried out by bacteria. Time-series meta-omics datasets of at least 5–10 years are important because nutrient levels and biological activities are dynamic and seasonal features of temperate coastal ecosystems are expected to be affected by climate change. In turn, the established links furnish an ecophysiological understanding of key bacterial populations in natural waters, and this will be a precondition for the successful accomplishment of points 6 to 8 above. Research communication and dialogue with society has recently been emphasized in policy documents from, e.g., UNESCO, Global Research Council and Science Europe. Such closer collaboration between researchers and societal actors can be partially supported by national funding sources, but for example the efforts to reach a shared understanding across borders (emphasized in the last three points) would benefit from international funding. Certainly, researcher engagement in defining future (inter)national funding schemes would be warranted for this. The proposed actions have the potential to ensure that the role of bacteria is recognized as being of fundamental importance for the coastal marine ecosystem, and that this knowledge reaches decision makers involved in marine management. This will be invaluable for the continued refinement of sustainable management strategies for coastal zones."
} | 7,047 |
30417874 | PMC6235589 | pmc | 5,327 | {
"abstract": "Spatial structure and patterning play an important role in bacterial biofilms. Here we demonstrate an accessible method for culturing E. coli biofilms into arbitrary spatial patterns at high spatial resolution. The technique uses a genetically encoded optogenetic construct—pDawn-Ag43—that couples biofilm formation in E. coli to optical stimulation by blue light. We detail the process for transforming E. coli with pDawn-Ag43, preparing the required optical set-up, and the protocol for culturing patterned biofilms using pDawn-Ag43 bacteria. Using this protocol, biofilms with a spatial resolution below 25 μm can be patterned on various surfaces and environments, including enclosed chambers, without requiring microfabrication, clean-room facilities, or surface pretreatment. The technique is convenient and appropriate for use in applications that investigate the effect of biofilm structure, providing tunable control over biofilm patterning. More broadly, it also has potential applications in biomaterials, education, and bio-art.",
"introduction": "Introduction Biofilms are surface-attached communities of microbes, and are well-known for their strong structure-function coupling. Spatial geometry and patterning of biofilms play an important role in overall community function (and vice versa) 1 . The small length scales involved in biofilm structure—on the order of tens of microns 2 —make tunable and convenient control of biofilm patterning a challenging problem. Here we demonstrate a protocol that allows for biofilms to be precisely patterned in arbitrary geometries, based on optical illumination. The protocol presented here uses pDawn-Ag43 3 , an optogenetic construct that couples biofilm formation in E. coli bacteria to optical illumination by driving the expression of Ag43 (an adhesin gene responsible for surface adhesion and biofilm formation) under the control of pDawn 4 (a transcriptional regulator controlled by optical illumination). The method is convenient to use and can pattern biofilms on various surface environments, including enclosed (transparent) culture chambers. Compared to existing cell deposition methods, such as droplet-based deposition 5 or surface prepatterning/treatment 6 , pDawn-Ag43 does not require microfabrication or clean-room facilities and does not require materials beyond those available to a typical microbiology laboratory. It is able to pattern with a spatial resolution below 25 μm, approaching the spatial dimensions of microcolonies in naturally existing biofilms 2 . Overall, this technique provides the ability to manipulate biofilm structure, which then opens many avenues to study microecology in bacterial communities 7 . Additionally, patterned biofilms may provide a convenient platform upon which to engineer useful biomaterials 8 9 . In this paper, we discuss the basic protocol required for patterning biofilms using pDawn-Ag43 and address potential modifications and troubleshooting related to the method.",
"discussion": "Discussion In light of the need for research tools that allow for biofilm structure control, we have presented an easy-to-use protocol for patterning bacterial biofilms using the pDawn-Ag43 optogenetic construct. With this technique, E. coli biofilms can be optically patterned on various surface environments, including enclosed chambers, with a spatial resolution below 25 μm. Overall, this protocol can be broken down into four main sections: (1) the preparation of the pDawn-Ag43 bacteria, (2) the preparation of the optical and culture set-up hardware, (3) the pre-illumination bacterial growth steps, and (4) the post-illumination rinses and imaging. The critical part of section 1 is the successful transformation of pDawn-Ag43 plasmid into the E. coli strain of interest. This is facilitated by isolating high-quality purified plasmid and generating high-quality competent cells for transformation ( Table 1 , troubleshooting). The critical part of section 2 is the optimization of the projector set-up so that the illumination intensity is adjusted to 50 μW/cm 2 at the 460-nm wavelength, and the projector is properly focused at the biofilm sample height. Note that in this protocol, we describe an inverted illumination set-up where the projector shines light from below, upward toward the biofilm sample. The advantage of this set-up is that the light only needs to travel through the bottom of the culture dish before reaching the biofilm formation surface. Illumination from above means that the light would have to travel through the liquid media above the biofilm surface, which, during the course of the growth, gets cloudy with planktonic cells. In addition to these concerns, it is also important to minimize stray light in the optical set-up as much as possible, for example, by covering up reflective surfaces on the interior of the incubator—this helps to obtain sharper patterned biofilms. On a related note, sharper biofilm patterns can also be obtained by using a photomask to control illumination patterning ( Figure 3D , Figure 4C ). Common issues requiring troubleshooting include projector reliability issues at higher temperatures ( e.g. , 37 °C), which can be minimized by incubating the biofilm growth at lower temperatures ( e.g. , 30 °C), as well as computer software that causes operating system updates or blue light filtering during overnight growth ( Table 1 ). It is also important to note that, depending on the projector and incubator model used, it is also possible that heat generated from the projector will result in a higher interior temperature than the incubator set temperature, which may need to be corrected. The critical part of section 3 is obtaining reliable and repeatable bacterial samples before they are induced by illumination. For this reason, it is recommended to obtain clonal colonies of pDawn-Ag43 bacteria by streaking them out on an agar plate and then using the liquid culture steps to ensure that the bacteria are illuminated/induced at the late exponential growth phase in a repeatable manner. Finally, the critical part of section 4 is to thoroughly, but also gently, wash away the planktonic cells remaining after the biofilm patterning protocol; thus, it is recommended to perform multiple gentle rinse steps with PBS. Compared to existing techniques for cell patterning 5 6 , optical biofilm patterning based on pDawn-Ag43 has a reasonably low barrier of entry to use, in that it does not require microfabrication, clean-room facilities, complex chemistry, or surface pretreatment, yet is still able to pattern with the high resolution (25 μm) typically associated with microfabrication techniques. The method extends previous work on bacterial photolithography for controlling gene expression 17 . Currently, pDawn-Ag43 plasmid is limited to E. coli , as it uses a pUC-based origin of replication, but pDawn and Ag43 are both compatible in other (Gram-negative) bacterial species. Genetic techniques are available for potentially introducing light-regulated biofilm formation to different bacterial species and represents a possible direction for future research. Another potential limitation of the technique is that it works by increasing biofilm formation in strains with weak native biofilm formation ( e.g. , MG1655 E. coli ). However, strains with strong native biofilm formation have biofilms form regardless of illumination conditions, precluding patterned biofilm formation using pDawn-Ag43 as described here; yet optogenetic techniques may still prove applicable in regulating biofilm formation. We note that in other contexts, alternative methods of biofilm patterning may be available, such as via optical c-di-GMP modulation 18 . Overall, pDawn-Ag43 based patterning will be appropriate for use in applications that investigate the effect of biofilm structure on function 1 and, therefore, could benefit from tunable control over biofilm patterning—a particularly relevant example to highlight is the study of microbial ecology in biofilms 2 . Future directions include making patterned biomaterials 8 9 and/or structured bacterial communities. Alternative applications of this accessible protocol also include bio-art 19 , given the clear aesthetic potential, as well as formal and informal life science education 20 21 22 . From an educational perspective, the protocol described here combines many relevant techniques (bacterial culture, transformation, optics/optogenetics) and is also modularly extendable ( e.g. , include microfluidics)."
} | 2,129 |
37310347 | PMC10370314 | pmc | 5,328 | {
"abstract": "ABSTRACT This study is a continuation by the Environmental Biotechnology Group of the University of Tübingen in memoriam to Reinhard Wirth, who initiated the work on Mth60 fimbriae at the University of Regensburg. Growth in biofilms or biofilm-like structures is the prevailing lifestyle for most microbes in nature. The first crucial step to initiate biofilms is the adherence of microbes to biotic and abiotic surfaces. Therefore, it is crucial to elucidate the initial step of biofilm formation, which is generally established through cell-surface structures (i.e., cell appendages), such as fimbriae or pili, that adhere to biotic and abiotic surfaces. The Mth60 fimbriae of Methanothermobacter thermautotrophicus ΔH are one of only a few known archaeal cell appendages that do not assemble via the type IV pili assembly mechanism. Here, we report the constitutive expression of Mth60 fimbria-encoding genes from a shuttle-vector construct and the deletion of the Mth60 fimbria-encoding genes from the genomic DNA of M. thermautotrophicus ΔH. For this, we expanded our system for genetic modification of M. thermautotrophicus ΔH using an allelic-exchange method. While overexpression of the respective genes increased the number of Mth60 fimbriae, deletion of the Mth60 fimbria-encoding genes led to a loss of Mth60 fimbriae in planktonic cells of M. thermautotrophicus ΔH compared to the wild-type strain. This, either increased or decreased, number of Mth60 fimbriae correlated with a significant increase or decrease of biotic cell-cell connections in the respective M. thermautotrophicus ΔH strains compared to the wild-type strain. IMPORTANCE \n Methanothermobacter spp. have been studied for the biochemistry of hydrogenotrophic methanogenesis for many years. However, a detailed investigation of certain aspects, such as regulatory processes, was impossible due to the lack of genetic tools. Here, we amend our genetic toolbox for M. thermautotrophicus ΔH with an allelic exchange method. We report the deletion of genes that encode the Mth60 fimbriae. Our findings provide the first genetic evidence of whether the expression of these genes underlies regulation and reveal a role of the Mth60 fimbriae in the formation of cell-cell connections of M. thermautotrophicus ΔH.",
"introduction": "INTRODUCTION Microbial biofilm formation, maintenance, and dispersion in various habitats have been investigated in numerous studies ( 1 – 3 ). Many studies elucidated biofilm formation for bacteria, especially for clinically relevant pathogenic species ( 3 – 6 ). However, knowledge about archaeal biofilm formation remains in an early stage ( 7 , 8 ). Archaea are found in extreme habitats with respect to pH, temperature, or salinity, as well as under moderate conditions such as seawater, the human gut, and rice paddy fields. Thus, archaea have evolved a wide range of strategies to colonize this extensive variety of habitats ( 9 ). In general, forming a biofilm in new habitats is performed through cell-surface molecules and structures, enabling microbes to attach and adhere to a surface ( 10 , 11 ). One possibility is adherence via extracellular polymeric substances ( 12 ). However, this was more frequently described to be important in a later stage of colonization and not for the initial attachment ( 3 , 12 ). For archaea, this initial attachment to surfaces mostly relies on archaeal cell appendages, such as archaella, pili, fimbriae, and other specialized archaeal cell appendages ( 13 , 14 ). Typically, archaella differ from all other cell appendages in two ways: (i) the diameter, which is 10 to 15 nm, compared to ~5 nm for fimbriae and pili, and (ii) the ability to rotate, and therefore enable directed motility of the microbe ( 13 ). It was shown that several archaellum structures allow for adherence to surfaces ( 14 – 16 ). Archaella and most cell appendages described for archaea, so far, are assembled via the type IV pili assembly mechanism ( 17 , 18 ). However, some archaeal cell appendages most likely assemble by mechanisms different from the type IV pili assembly mechanism, such as bundling pili of Pyrobaculum calidifontis , archaeal cannulae of Pyrodictium abysi , hami from Altiarchaeum hamiconexum , threads of Sulfolobus acidocaldarius , conjugative pili of Aeropyrum pernix and P. calidifontis , and Mth60 fimbriae from M. thermautotrophicus ΔH ( 19 – 25 ). These archaeal cell appendages allow adherence to abiotic surfaces and biotic adherence between microbes but do not confer motility to the microbe. Here, we focused on the Mth60 fimbriae from M. thermautotrophicus ΔH. The Mth60 fimbriae were first described by Doddema et al. ( 26 ). They differ from archaella by their diameter and a length of up to 5 μm ( 13 , 26 ). Planktonic wild-type M. thermautotrophicus ΔH cells contain between one and three Mth60 fimbriae. In contrast, cells that adhered to surfaces contained significantly higher numbers of Mth60 fimbriae per cell ( 20 ). M. thermautotrophicus ΔH was shown to adhere to several distinct surfaces, such as glass, carbon-coated gold, copper grids, and silicium wafers, via the Mth60 fimbriae ( 20 ). In addition to abiotic surfaces, biotic cell-cell connections with surface-adhered M. thermautotrophicus ΔH have been demonstrated ( 20 ). The Mth60 fimbriae mainly consist of the major fimbrin protein Mth60, which is eponymous for the Mth60 fimbriae. The corresponding gene, mth60 , is transcribed in two transcriptional units (i.e., operons), mth58-mth60 and mth60-mth61 (MTH_RS00275 to MTH_RS00285, MTH_RS00285 to MTH_RS00290). Therefore, the transcription levels of mth60 are much higher than those of the surrounding genes in the two operons ( 27 ). Recombinant Mth60 protein, produced in Escherichia coli , led to auto-assembly of filamentous fimbria structures when incubated at 65°C in M. thermautotrophicus ΔH growth medium ( 20 , 27 , 28 ). This auto-assembly feature of recombinant Mth60 protein was patented for a potential application as heat-induced glue through the solidification of the Mth60 protein at elevated temperatures ( 28 ). Furthermore, the auto-assembly feature indicated a unique pilus assembly mechanism of Mth60 fimbriae, which is distinct from the type IV pilus assembly mechanism that was described for the majority of cell appendages studied to date in archaea ( 13 ). The functions of mth58 , mth59 , and mth61 , which are the three genes that are cotranscribed with mth60 , remain largely unknown. Auto-assembly tests of Mth59 together with Mth60 failed in assembling filamentous structures. However, additional bioinformatics modeling of the Mth59 protein structure indicated a potential chaperone function of Mth59 for Mth60 ( 27 ). Biofilm formation of methanogenic archaea has been demonstrated in different habitats with various methanogenic species involved, such as (i) biofilm formation of Methanosphaera stadtmanae and Methanobrevibacter smithii in the human gut ( 29 ), (ii) syntrophic relationships of the sulfate-reducing bacteria Desulfovibrio vulgaris Hildenborough and Methanococcus maripaludis ( 30 ), and (iii) putative colonization of black smokers by Methanocaldococcus villosus ( 31 ). To further investigate the relevance of Mth60 fimbriae of the thermophilic methanogenic archaeon M. thermautotrophicus ΔH for biotic cell-cell connections ( 20 ), we expanded our genetic toolbox for M. thermautotrophicus ΔH ( 32 ) with suicide vectors for targeted gene deletion. This enabled us to delete the Mth60 fimbria-encoding operons ( mth58 - mth60 and mth60 - mth61 ) from the genomic DNA of M. thermautotrophicus ΔH using an allelic-exchange method. We further generated a strain of M. thermautotrophicus ΔH that contained a shuttle-vector construct for the constitutive expression of the Mth60 fimbria-encoding operons. We observed various phenotypes and significantly different numbers of Mth60 fimbriae per cell for the different strains. Thus, we could elucidate the intraspecies adherence ability of M. thermautotrophicus ΔH.",
"discussion": "DISCUSSION In this study, we reported the implementation of suicide-vector constructs for homologous recombination in M. thermautotrophicus ΔH to generate site-specific gene deletion mutants via allelic exchange with a positive selectable marker. With our expanded genetic tools, we elucidated the positive and negative influence of constitutive expression and deletion of the Mth60 fimbria-encoding operons on the in-vivo production of Mth60 fimbriae in M. thermautotrophicus ΔH. We demonstrated a correlation between the number of Mth60 fimbriae and the number of cell-cell connections with a constitutive Mth60-fimbria expression strain, wild-type strain, and Mth60-fimbria deletion strain of M. thermautotrophicus ΔH. We measured significantly lower numbers of cell-cell connections in M. thermautotrophicus ΔH strains with lower numbers of Mth60 fimbriae. Therefore, we demonstrated the importance of Mth60 fimbriae for establishing cell-cell connections, which is essential for initial biofilm formation. The DNA-transfer protocol, and therefore the generation of deletion mutants of M. thermautotrophicus ΔH, was performed with the same procedure we had established before for shuttle-vector constructs ( 32 ). However, for the successful isolation of mutant strains, the concentration of neomycin as the antibiotic substance had to be lowered to 100 μg/mL instead of 250 μg/mL for the initial liquid enrichment and on solidified medium plates when a genomic alteration was introduced. It is known that cells can adapt the copy number of plasmids in response to higher antibiotic substance concentrations, which leads to higher resistance levels toward these antibiotic substances ( 37 ). It is further known that M. thermautotrophicus ΔH is always diploidic ( 38 ). Thus, we argue that the copy number of our shuttle vector is likely higher than two (as for the genome copies) or potentially can be increased with higher antibiotic substance concentrations. This would explain the higher neomycin resistance levels of shuttle-vector-containing M. thermautotrophicus ΔH compared to genome-altered M. thermautotrophicus ΔH mutant strains. While isolating a clean M. thermautotrophicus ΔH strain with a deletion of the Mth60 fimbria-encoding operons, we obtained PCR signals and Nanopore sequencing reads for wild-type M. thermautotrophicus ΔH, single-homologous recombined, and double-homologous recombined mutant strains from the same colony sample. This was the case even after two steps that included isolating an individual clonal population and transferring it to liquid growth medium (Fig. S2). One possible explanation is the diploid character of M. thermautotrophicus ΔH, which might result in residual wild-type or single-homologous recombined alleles on the second chromosome ( 38 ). This could result in a heterozygous culture of M. thermautotrophicus ΔH, as it was shown to appear in heterozygous and many genome copy-containing Methanococcus maripaludis cultures ( 39 ). Another possible explanation is the characteristic of M. thermautotrophicus ΔH of forming multicellular filaments. This could result in different genotypes in one filament of multiple individual M. thermautotrophicus ΔH cells ( 36 , 38 ). These observations of various genotypical PCR signals make it more laborious, but not impossible, to isolate clean deletion strains of M. thermautotrophicus ΔH with a homologous recombination-based methodology ( Fig. 1B ). To reduce the required screening efforts, tools for markerless mutagenesis or CRISPR/Cas should be implemented in the future, because they were shown to work in other methanogenic archaea already ( 40 – 43 ). We performed immunofluorescence staining to visualize the Mth60 fimbriae with the Mth60-fimbria-deletion, the constitutive Mth60-fimbria-producing, and wild-type M. thermautotrophicus strains. The Mth60-fimbria antibodies that we used for immunofluorescence staining were generated from a native Mth60-fimbria preparation, which was purified through density gradient centrifugation. After our staining approach, we demonstrated that the entire cell wall was also stained, in addition to the Mth60 fimbriae, which resulted in the staining of the entire cell ( Fig. 2A to C ). One possible explanation is that cell wall components were purified in the same fraction of the density gradient centrifugation, resulting in a mixture of the polyclonal antibodies against several antigens. Another explanation is that the Mth60 fimbria antibody recognizes glycosylated epitopes of the major fimbrin Mth60 of the Mth60 fimbriae ( 20 ). In that case, the Mth60-fimbria antibody might also bind glycosylated cell wall components on the envelope of M. thermautotrophicus ΔH cells ( 44 ). Thoma et al. ( 20 ) mentioned a difference in the number of Mth60 fimbriae in planktonic M. thermautotrophicus ΔH cells versus cells that were actively grown in the presence of a surface to which the cells adhered. While only 50% of planktonic cells contained few Mth60 fimbriae, cells that were adhered to surfaces contained large numbers of Mth60 fimbriae per microbial cell ( 20 ). This finding indicated regulation of the expression of the Mth60 fimbria-encoding operons. When we exchanged the putatively regulated promoter for the constitutive P hmtB promoter, fimbriae were identified in higher numbers for each planktonic M. thermautotrophicus ΔH cell ( Fig. 2 and 3 ) ( 32 ). However, the regulatory mechanism of putative promoter regions of the Mth60 fimbria-encoding operons will need to be investigated further. The Mth60-fimbria deletion mutant of M. thermautotrophicus ΔH contains no Mth60 fimbriae ( Fig. 2C and 3C ). This loss of Mth60 fimbriae did not appear to influence the generation of individual multicellular filaments. However, the connections to other multicellular filaments were significantly reduced. From this, we concluded that Mth60 fimbriae play a significant role in M. thermautotrophicus ΔH biotic cell-cell connections under the conditions we investigated. However, another mechanism seems essential for forming multicellular filaments, which could include a putative influence of additional cell appendages or surface structures. Thus, we argue that Mth60 fimbriae cannot be the only factor essential for forming multicellular filaments, as these multicellular filaments were present in all M. thermautotrophicus ΔH strains we analyzed. It was shown that adding Mth60-fimbria antibodies to surface-adhered M. thermautotrophicus ΔH cells led to the detachment of the cells, potentially by blocking the Mth60 fimbria adhesion mechanism ( 20 ). With the deletion of the Mth60-fimbria operons, and therefore the loss of Mth60 fimbriae, we could now support these results on a genetic level by demonstrating reduced cell-cell connections in vivo . Because the raised antibodies against Mth60-fimbriae potentially bound mostly glycosylated proteins, we hypothesized that attachment of the anti-Mth60-fimbria antibody had an effect similar to that of the deletion of oligosaccharyltransferase AglB in M. maripaludis . This deletion led to the loss of glycosylation of M. maripaludis pilus structures, and therefore the deletion strain was deficient in surface attachment ( 45 ). Further investigations of the glycosylation of Mth60 fimbriae will be required in M. thermautotrophicus ΔH. We demonstrated that deletion of all four genes that are cotranscribed with mth60 , including mth60 , led to the loss of Mth60 fimbriae. In addition, we provided further evidence for the regulation of the Mth60 fimbria-encoding operons. Based on these findings, the functions of the individual genes in the Mth60 fimbria-encoding operons can be studied in more detail. Understanding the putatively regulated promoters of the Mth60 fimbria-encoding operons is the first step in identifying a sensory system in M. thermautotrophicus ΔH that allows adherence to biotic and abiotic surfaces for initial biofilm formation. The reduced ability to form cell-cell connections might impact the rheology of a high-density microbial culture, and thus for biotechnological applications with M. thermautotrophicus , such as for power-to-gas processes in large-scale fermentation to convert carbon dioxide and hydrogen to renewable methane ( 46 ). A possible effect of the rheology on parameters, such as mixing, gas solubility, and gas conversion efficiency, with the pilus-deficient strain of M. thermautotrophicus ΔH will have to be addressed in future research."
} | 4,168 |
33370327 | PMC7769462 | pmc | 5,329 | {
"abstract": "Marine phytoplankton, and in particular diatoms, are responsible for almost half of all primary production on Earth. Diatom species thrive from polar to tropical waters and across light environments that are highly complex to relatively benign, and so have evolved highly divergent strategies for regulating light capture and utilization. It is increasingly well established that diatoms have achieved such successful ecosystem dominance by regulating excitation energy available for generating photosynthetic energy via highly flexible light harvesting strategies. However, how different light harvesting strategies and downstream pathways for oxygen production and consumption interact to balance excitation pressure remains unknown. We therefore examined the responses of three diatom taxa adapted to inherently different light climates (estuarine Thalassioisira weissflogii , coastal Thalassiosira pseudonana and oceanic Thalassiosira oceanica ) during transient shifts from a moderate to high growth irradiance (85 to 1200 μmol photons m -2 s -1 ). Transient high light exposure caused T . weissflogii to rapidly downregulate PSII with substantial nonphotochemical quenching, protecting PSII from inactivation or damage, and obviating the need for induction of O 2 consuming (light-dependent respiration, LDR) pathways. In contrast, T . oceanica retained high excitation pressure on PSII, but with little change in RCII photochemical turnover, thereby requiring moderate repair activity and greater reliance on LDR. T . pseudonana exhibited an intermediate response compared to the other two diatom species, exhibiting some downregulation and inactivation of PSII, but high repair of PSII and induction of reversible PSII nonphotochemical quenching, with some LDR. Together, these data demonstrate a range of strategies for balancing light harvesting and utilization across diatom species, which reflect their adaptation to sustain photosynthesis under environments with inherently different light regimes.",
"conclusion": "Conclusions In summary, we have built on previous studies demonstrating differences in nonphotochemical quenching amongst diatom species, and strategies in dealing with transient high light exposure (e.g. [ 8 ]) to elucidate the trade-offs amongst varying energy dissipating strategies from ecologically distinct diatoms. We found that T . weissflogii and T . pseudonana exhibited capacity to rapidly initiate nonphotochemical quenching at lower light, which corresponded to lower light dependent respiration (LDR) at HL and lower k PI . T . oceanica , on the other hand, does not initiate nonphotochemical quenching as a rapid primary response mechanism to dissipate excess light energy and therefore had an accumulation of photochemical energy resulting in higher rates of LDR but also higher k PI . This supports the idea that photo-protective strategies are evolutionarily conserved based on ecological niche for diatoms. These diatoms possess similar core machinery to dissipate excess light energy but have balanced the mechanistic dissipation strategies employed to best suit their respective niche.",
"introduction": "Introduction Diatoms account for the majority of marine primary production [ 1 , 2 ] and are ubiquitous across aquatic environments [ 3 ], from tropical to polar regions, and from highly dynamic coastal and upwelling habitats to more stable oceanic waters. Adaptation of diatoms to these environments has resulted in their evolution of photosynthetic machinery optimized to very different light regimes caused by short-term (e.g. clouds, sun flecks, diel cycle) and long-term (e.g. seasonal) processes, as well as positioning relative to water column thermal and nutrient gradients [ 4 , 5 ]. Whilst the overall success of diatoms appears driven by complex acclimation processes trending towards a light level that is close to an average irradiance within the mixed layer of a given water body [ 6 , 7 ], routine exposure to stochastic high light episodes requires dynamic photoprotective capacity [ 8 – 11 ]. Diatoms use multiple processes to regulate photosynthesis, including modifying the ultrastructure (and thus the excitonic connectivity) of pigments and proteins, which together regulate the flow of excitation energy reaching the electron carrier system [ 8 , 12 ]. Failure to regulate excess excitation energy either as photons reaching the reaction centre or as harvested energy (i.e. electrons) within the electron transport chain can increase the probability of photo-inactivation of photosystem II (PSII, [ 13 ]), likely from the generation of reactive oxygen species [ 14 ], ultimately leading to a decrease in net primary productivity and growth. It is therefore paramount that photoautotrophs have mechanisms to dissipate excess light energy and photo-protect the photosystems, and associated metabolism, while maintaining photosynthesis to support growth. One of the most important mechanisms for rapid (on the order of seconds to minutes) regulation of photochemistry under high light is non-photochemical quenching (see [ 15 ] review), parameterized herein as a yield, YNPQ (equivalent to ΦNPQ [ 16 ] and conceptually similar to [1-Q] [ 17 ]), whereby excitation energy in excess of the photosynthetic capacity, is safely dissipated as heat by light harvesting pigment complexes associated with PSII (LHCII, [ 18 , 19 ]). YNPQ is a regulated process and contrasts with unregulated non-photochemical quenching, parameterized by YNO (equivalent to ΦNO, [ 16 ]). YNO comprises constitutive thermal losses [ 16 ] as well as intrinsic losses ( sensu [ 20 ]). As with all algae, light harvesting pigments in diatoms are connected to the PSII reaction centres (RCIIs) with an embedded oxygen evolving complex (OEC) that splits water to release electrons for use in photochemistry. Alterations in carotenoid pigment composition are regulated through the xanthophyll cycle (XC) and interact with particular photo-protective light harvesting complex protein isoforms (LHCXs) to lower the energetic transfer efficiency from antennae pigments to RCII [ 21 – 24 ]. When light is transiently in excess, induction of nonphotochemical quenching occurs whereby the accumulation of a proton gradient, and consequently ΔpH, across the thylakoid membrane drives the de-epoxidation of XC pigments, via two evolutionarily divergent protection pathways, diadinoxanthin (Dd, light harvesting) to diatoxanthin (Dt, photo-protective) [ 25 ] which dominates in diatoms and/or violaxanthin to zeaxanthin [ 26 – 28 ] which dominates in green lineages. Exposure to high light triggers synthesis of LHCX isoforms that localize closely to the RCII core, resulting in core complex associated non-photochemical quenching [ 21 , 24 , 29 ]. Sustained high light exposure, in turn, drives accumulation of accessory pigments [ 24 ], which may also result from the continued accumulation of LHCXs [ 12 , 23 , 30 ] generating longer-lived, more slowly reversible, forms of nonphotochemical quenching. Nevertheless, diatoms typically maintain a constitutive capacity to build substantial but reversible nonphotochemical quenching through the XC [ 12 ]. Recent work using mutants of the pennate diatom P . tricornutum [ 31 ] showed that all capacity for rapidly reversible nonphotochemical quenching can be explained by LHCXs and the XC operating in concert and that, at least for P . tricornutum , longer-lived nonphotochemical quenching generally signifies the build-up of photo-inhibition that can only be reversed through turnover of PSII protein subunits [ 32 ]. An additional process—detachment of LHCXs from the RCIIs to invoke “super quenching”–appears to be a relatively minor process in P . tricornutum , suggesting that the energy trapping efficiency of the antenna does not out-compete that of the RCIIs [ 33 , 34 ]. In other diatoms, however, antennae detachment appears to sustain nonphotochemical quenching [ 35 – 37 ], that in turn overlaps kinetically with photoinactivation and repair [ 13 , 38 ]. Dynamic light regimes appear to select for phytoplankton taxa with different strategies of nonphotochemical quenching to optimize cell growth and survival, as demonstrated in a recent comparative assessment of various microalgal species and ecotypes [ 39 ]. Environments characterized by particularly large light fluctuations include shallow waters that are inhabited by both benthic diatoms and pelagic estuarine/coastal diatoms. Interestingly, the strategies used to deal with dynamic high light are quite different within niche-specific diatom groups, whereby non-motile benthic diatoms employ rapidly reversible nonphotochemical quenching through XC—presumably to cope with more variable light fields [ 8 , 40 ]–whereas motile benthic diatoms preferentially employ slower, sustained non-photochemical quenching [ 21 , 29 ]. This pattern has been further confirmed comparing Artic diatoms [ 41 ]. Within pelagic species, the coastal taxon Skeletonema costatum exhibits inherently less capacity for sustained non-photochemical quenching than the estuarine taxon Phaeodactylum tricornutum , but these alternate managements of excitation pressures are compensated by different capacities for PSII repair [ 42 ]. Here, maintaining a greater proportion of “active” PSIIs but lower capacity for non-photochemical quenching, presumably, places more pressure on electron carriers downstream of PSII to dissipate the transient accumulation of excessive excitation energy within the photosynthetic electron transport chain. Microalgae exposed to supra-optimal light can further deal with excessive excitation energy through “alternative electron flows” downstream of PSII (e.g. [ 25 , 43 – 45 ]). Numerous alternative electron pathways have been described, including electron cycles around PSII [ 46 – 48 ] and PSI [ 49 ] that do not consume O 2 , or alternative midstream terminal oxidase (MOX, [ 50 ]) pathways downstream of PSII (e.g. plastid terminal oxidase, PTOX, [ 51 , 52 ]) or of PSI (Mehler-Ascorbate-Peroxidase, [ 53 , 54 ]; Flavodiiron proteins, [ 55 ]) that consume electrons and O 2 . It has been suggested that such up-regulation of alternative electron flow directly feeds back to non-photochemical quenching generation at PSII by generating ΔpH—a key trigger of antennae-based non-photochemical quenching processes [ 52 ]. In spite of the potential importance of these electron pathways, relatively little is known as to whether they operate to sustain photo-protective capacity in diatoms. Mehler Ascorbate Peroxidase activity (Mehler for brevity) is an alternative electron sink following PSI, consuming O 2 to ultimately re-generate H 2 O (e.g. [ 54 , 56 ]) and appears to be a significant route of total O 2 uptake in the light amongst diatoms [ 57 ]. For example, 60% oxygen uptake via Mehler activity was observed for Thalassiosira pseudonana [ 58 ] and Cylindrotheca [ 59 ]. However, other reports have suggested a significant role for mitochondrial alternative oxidase (AOX; e.g. Thalassiosira weissflogii , [ 54 ]), which can, in turn, supply energy to chloroplast-protective processes [ 60 ]. Photorespiration related to RUBISCO oxidase function is often considered a negligible source of energy dissipation in diatoms as they have evolved carbon concentrating mechanisms [ 61 , 62 ]. Importantly, Mehler, but not AOX, directly supports chloroplast proton motive force pathways that directly contribute to signalling photo-protection through the light harvesting apparatus (see [ 45 ]). At present, it remains unexplored whether and how the modulation of O 2 consumption, as a means to balance excess excitation pressure, can be reconciled with differential capacities for non-photochemical protection amongst diatoms. Here we initially examined allocation of excitation energy to non-photochemical vs. photochemical pathways across a broad panel of diatoms to uncover divergent strategies. We then analyzed three representative diatom taxa ( Thalassioisira weissflogii , Thalassiosira pseudonana , Thalassiosira oceanica ) from ecologically distinct light environments (estuarine, coastal, open ocean, respectively) to determine their balance of photo-protective strategies through XC versus PSII repair capacity, and whether species with higher capacities for non-photochemical quenching exhibited lower reliance on induction of light-dependent O 2 consumption (light-dependent respiration, LDR). We therefore screened T . weissflogii , T . pseudonana and T . oceanica for (i) pigment content and de-epoxidation activity, (ii) PSII photo-inactivation and repair rate constants, and (iii) LDR upon transient exposure to high light, relative to the growth irradiance. Together these data demonstrate that diatom species from different ecological niches have highly divergent energy allocation strategies to cope with high light exposure.",
"discussion": "Discussion Diatoms exhibit varying responses to light to thrive across diverse environmental niches [ 40 , 41 , 101 , 104 – 106 ]. Estuarine diatoms (e.g. T . weissflogii ), exhibit a high capacity to rapidly initiate nonphotochemical quenching whereas oceanic diatoms (e.g. T . oceanica ) have slower initiation of nonphotochemical quenching as light intensifies, with coastal diatoms (e.g. T . pseudonana ), exhibiting an intermediate response [ 8 , 107 ]. Our data confirmed these trends, despite similar rates of NPP across the three diatom representatives when grown under the same conditions of moderate, steady light ( Table 1 ). Here, we add to the understanding of adaptive differences in photophysiological trade-offs employed by diatoms shifted to high light through (i) nonphotochemical quenching induction, (ii) reliance on energy consumption downstream of PSII and (iii) utilization of energetically expensive repair processes to counter damage to the photosynthetic machinery ( Fig 8 ). Faster induction of nonphotochemical quenching was accompanied by lower susceptibility to PSII inactivation, while faster relaxation of nonphotochemical quenching corresponded with faster repair, across the three species. The faster nonphotochemical quenching relaxation and PSII repair for T . pseudonana was accompanied by greatest change in DPS capacity from Ig to HL. For T . oceanica , slower nonphotochemical quenching induction, and greatest susceptibility to PSII inactivation, was in turn accompanied by greater proportion of O 2 evolved from PSII (GP O2 ) flowing to LDR, and less to R DARK . Thus, under transient high light exposure T . weissflogii adopts a strategy of rapid and sustained PSII downregulation, thereby requiring relatively little RCII inactivation/repair, or the need to induce O 2 and electron consuming (LDR) pathways. In contrast, T . oceanica appears to not initiate protective mechanisms to alleviate excess excitation pressure on PSII, as evident by relatively little downregulation, inactivation and only moderate repair, but, instead, places greater reliance on LDR to dissipate excess excited energy downstream of PSII. Although these experiments were conducted under nutrient repletion, T . oceanica is evolved for low nutrient growth. Limiting reliance upon PSII repair thereby lowers the requirement for mineral nutrient investment into metabolically expensive systems for protein turnover [ 32 , 108 ]. The response for coastal T . pseudonana is intermediate, with moderate downregulation and inactivation of PSII, but high repair of PSII and relaxation of nonphotochemical quenching, and some LDR. These trends show inherent trade-offs in how these different species deploy downregulation and repair of PSII, versus modulating subsequent re-consumption of oxygen and electrons ( Fig 8 ). 10.1371/journal.pone.0244252.g008 Fig 8 Summary of relative reliance (low to high; light grey to black) on various energy dissipation strategies when subject to transient HL including (i) de-epoxidation state (DPS) of xanthophyll cycle pigments, (ii) induction/relaxation of nonphotochemical quenching (parameterized as YNPQ), (iii) inactivation/repair of PSII and (iv) O 2 consuming pathways (LDR/R DARK ) for the three Thalassiosira diatom species examined here. In diatoms, activation of nonphotochemical quenching requires both the proton (H + ) gradient across the thylakoid membrane (ΔpH) and xanthophyll cycling (XC), involving the de-epoxidation state (DPS) of diadinoxanthin (Dd, light harvesting pigment) to diatoxanthin (Dt, photo-protective pigment) [ 109 ]. Dt epoxidation to Dd in T . pseudonana was shown to be inhibited at HL due to the presence of a proton gradient, which maintains high concentrations of this photo-protective pigment. Dt epoxidation is also inhibited by complete darkness after HL exposure [ 85 ]. Such inhibition of Dt epoxidation allows diatoms to re-activate nonphotochemical quenching rapidly if needed, thus avoiding over-reliance on a single photo-protective mechanism [ 109 ]. Diatoms also benefit from rapid pigment conversion by Dt epoxidase during subsequent transition to low light that is evident through rapid relaxation/reversibility (within 5 min) of a component of nonphotochemical quenching [ 85 , 110 ]. Such patterns were consistent with those we observed, with all species increasing Dt concentrations under HL [ 39 ], however this was not always consistent with a rapidly reversible nonphotochemical quenching. While T . pseudonana showed rapidly reversible nonphotochemical quenching, T . weissflogii appeared to sustain nonphotochemical quenching upon transition to low light, in parallel with its low capacity for PSII repair (k REC ; Table 3 ). Sustained nonphotochemical quenching has been observed to have a linear relationship with Dt whereby at lower acclimated growth irradiances sustained nonphotochemical quenching at the initial dark fluorescence measure was around 5-fold lower than in high-light acclimated T . gravida [ 38 ]. However, recent studies have observed a deviation from this linearity [ 41 ], supporting the hypothesis that some portion of Dt is not directly related to nonphotochemical quenching and prevents full relaxation of nonphotochemical quenching [ 15 ]. While our study only obtained Dt concentrations at Ig and a brief (10 min) transient shift to HL, we cannot rule out the effect of Dt on sustained nonphotochemical quenching, and thus fluorescence signals retrieved. However, there was no significant difference in Dt among species at Ig ( p = 0.323), therefore the trends observed appear robust. Interestingly, T . oceanica had slow initiation of nonphotochemical quenching under HL ( Fig 1A ) suggesting that a high content of Dt could be present but disconnected from RCII as was observed by Zhu & Green [ 10 ]. T . oceanica does not rapidly initiate nonphotochemical quenching to dissipate excess incident light energy in the antennae bed and, subsequently, suffers high excitation pressure on the RCIIs that split water and, potentially, higher excitation pressure through the subsequent electron carrier network. Increased ‘traffic’ of excitation energy was clear from the higher photo-inactivation rates (k PI ) for T . oceanica compared to the other two species. Previous studies on diatoms have established a link between diatom cell size and susceptibility to photo-inactivation, whereby cell size is inversely proportional to photo-inactivation [ 73 ] and thus larger cells require lower PSII protein turnover [ 108 ]. This complements our data of higher PSII repair rates (k REC ) for the smaller T . pseudonana than the larger T . weissflogii . Importantly, cell size may explain some photo-inactivation trends, but protein synthesis and regeneration, that alters in accordance with photosynthetic architecture also needs to be considered [ 32 , 73 ]. It is technically difficult to discriminate between photoinactivation of PSII and sustained downregulation of PSII, but ecophysiologically [ 86 ] a sustained suppression of PSII activity imposes opportunity costs on subsequent productivity, whatever the mechanism. PSII repair comes at a significant cost to the cell where the (re)synthesis of photosynthetic machinery comes at the expense of photosynthetic production [ 86 ]. Chloroplastic protein metabolism for PSII repair saturates at low light and continues during dark periods thus competing with growth for energy generated by photosynthesis [ 108 , 111 ]. For T . oceanica with the highest k PI ( Table 3 ), alternative mechanisms may be employed to obtain additional metabolic energy at the expense of biosynthetic reductant. One source of energy could be PSII-MOX [ 50 , 112 ] or PSI-Mehler [ 113 ] that consume O 2 and generate a trans-membrane proton gradient to power ATP generation. While specific O 2 -consuming pathways were not distinguished in this study, there was evidence to support a higher reliance on energy sourced from O 2 -consuming pathways by T . oceanica evidenced by higher LDR at HL compared to all other species ( S2 Table , Fig 5 ). The corresponding slower induction of nonphotochemical quenching exhibited by T . oceanica confirms previous studies showing a higher dependence on MOX processes. Importantly, such LDR pathways also act to consume excessive oxygen, which in the presence of high excitation pressure increases the chance of reactive oxygen species generation and further PSII—and indeed cellular—damage. Interestingly, T . weissflogii exhibited the highest dark respiration ( S1 Table ). A recent energetic coupling was found in diatoms between mitochondria and chloroplasts whereby ATP is supplied to the plastid by the mitochondria in the dark via upregulation of mitochondrial alternative oxidase (AOX) [ 60 , 114 , 115 ]. ATPase in the chloroplast hydrolyses this ATP to ADP which increases H + concentration in the lumen that ultimately activates de-epoxidation of Dd to Dt [ 15 ]. Thus, in contrast to T . oceanica that is slower to initiate nonphotochemical quenching, our data would suggest T . weissflogii relies on “front loading”, or priming the photosynthetic apparatus, for rapid HL exposure at any time and in the absence of a light-driven proton motive force by keeping pH and Dt concentrations optimal for photo-protection. Diatoms exhibit distinct alterations in photosynthetic architecture based on ecological niche, where oceanic diatoms ( T . oceanica ) have been found to have up to 10 PSII:PSI while coastal diatoms generally have 2 PSII:PSI [ 107 ]. These differences are primarily attributed to iron (Fe) availability, as the requirement for synthesis of PSII, Cyt b 6 f, and PSI are 3, 6, and 12 Fe atoms, respectively, but also provide insight into potential evolutionarily conserved species-specific photo-protective strategies amongst diatoms. Fe availability greatly influences growth rates of diatoms from various habitats whereby T . pseudonana and T . weissflogii growth rates were lowered by approximately 75% under Fe limitation while T . oceanica showed no significant change in growth rate [ 116 ] suggesting an evolutionary predisposition for the Fe-depleted open ocean. Different diatoms are equipped (genetically) to exploit many environments [ 2 , 60 , 117 ]. When light is stable and nutrients are limiting, typical of oceanic waters, diatoms appear to focus on upregulating light harvesting to produce more photochemical energy for cellular maintenance as nutrients are the limiting factor for division in these environments [ 101 ]. This pattern is consistent with the reliance of T . oceanica upon recycling electrons back to O 2 under excess light. This cyclic flux of electrons trades biosynthetic reductant for ATP generation. If inorganic nutrients are limiting, the requirement for ATP for maintenance and nutrient uptake increases relative to the requirement for actual reductive biosynthesis. Conversely, for coastal/estuarine waters, where light is dynamic and nutrients plentiful, diatoms can afford to invest more energy in biosynthesis of macromolecules and division as well as energetically expensive photosynthetic machinery, such as PSI, that are more efficient trapping excitation energy than PSII [ 118 ]. Also, PSI photochemistry incurs a higher Fe requirement compared to ATP generation through MOX pathways [ 50 ]. The most studied MOX, plastid terminal oxidase (PTOX), was found to be a significant contributor to electron flow in marine Synechococcus [ 51 ] but absent for several coastal phytoplankton species compared to oceanic species [ 119 , 120 ]. Based on our observations, we propose that T . oceanica cannot “afford” to synthesize new photosynthetic machinery and instead evolved strategies to allocate harvested light energy towards chemical energy for maintenance and growth while the slowly induced nonphotochemical quenching provides a fail-safe in the event of prolonged light stress."
} | 6,249 |
27645425 | PMC5028755 | pmc | 5,330 | {
"abstract": "Organic neuromorphic devices hold great promise for unconventional signal processing and efficient human-machine interfaces. Herein, we propose novel synaptic organic transistors devised to overcome the traditional trade-off between channel conductance and memory performance. A vacuum-processed, nanoscale metallic interlayer provides an ultra-flat surface for a high-mobility molecular film as well as a desirable degree of charge trapping, allowing for low-temperature fabrication of uniform device arrays on plastic. The device architecture is implemented by widely available electronic materials in combination with conventional deposition methods. Therefore, our results are expected to generate broader interests in incorporation of organic electronics into large-area neuromorphic systems, with potential in gate-addressable complex logic circuits and transparent multifunctional interfaces receiving direct optical and cellular stimulation."
} | 237 |
39703569 | PMC11655697 | pmc | 5,331 | {
"abstract": "Microbial electrochemical technologies (MET) can remove a variety of organic and inorganic pollutants from contaminated groundwater. However, despite significant laboratory-scale successes over the past decade, field-scale applications remain limited. We hypothesize that enhancing the electrochemical conductivity of the soil surrounding electrodes could be a groundbreaking and cost-effective alternative to deploying numerous high-surface-area electrodes in short distances. This could be achieved by injecting environmentally safe iron- or carbon-based conductive (nano)particles into the aquifer. Upon transport and deposition onto soil grains, these particles create an electrically conductive zone that can be exploited to control and fine-tune the delivery of electron donors or acceptors over large distances, thereby driving the process more efficiently. Beyond extending the radius of influence of electrodes, these diffuse electro-conductive zones (DECZ) could also promote the development of syntrophic anaerobic communities that degrade contaminants via direct interspecies electron transfer (DIET). In this review, we present the state-of-the-art in applying conductive materials for MET and DIET-based applications. We also provide a comprehensive overview of the physicochemical properties of candidate electrochemically conductive materials and related injection strategies suitable for field-scale implementation. Finally, we illustrate and critically discuss current and prospective electrochemical and geophysical methods for measuring soil electronic conductivity—both in the laboratory and in the field—before and after injection practices, which are crucial for determining the extent of DECZ. This review article provides critical information for a robust design and in situ implementation of groundwater electro-bioremediation processes.",
"conclusion": "6 Concluding remarks Electro-bioremediation is increasingly recognized as a flexible and sustainable strategy to tackle the problem of groundwater contamination. A decisive milestone towards the market deployment of this technology will be the development of viable field implementation strategies. In this context, we have presented and critically analyzed the approach known as the \"diffuse electro-conductive zone (DECZ).\" This method, which involves the subsurface injection of electrically conductive materials, has the potential to address one of the most significant challenges associated with subsurface electro-bioremediation processes, namely, the small radius of influence of electrodes. Based on laboratory studies, carbon- and iron-based materials, with dimensions spanning from nanometer-to millimeter-scale, appear to be the most effective ones. However, field applications remain extremely limited, and ad hoc protocols and methodologies for injection of selected particles within the aquifers still need to be developed and validated. Analogously, the analytical protocols currently employed to measure soil electrical conductivity for agronomic practices appear inadequate to track the efficiency of injection or to size the extension of DECZ, as these protocols predominantly measure ionic conductivity instead of electronic conductivity. Electrochemical impedance spectroscopy holds some potential to overcome this problem since, at least in principle, it would allow discriminating among the two different types of conductivities. However, geophysical methods and techniques appear more appropriate and have a greater potential for field application.",
"introduction": "1 Introduction Anthropogenic pollution of groundwater by organic and inorganic contaminants (e.g., petroleum hydrocarbons, pharmaceuticals, brominated flame retardants, per- and poly-fluoroalkyl substances (PFAS), heavy metals, and nitrate) is an issue of ever-increasing relevance, particularly considering that more than half of the global freshwater supply for drinking, industrial uses, and irrigation comes from groundwater [ [1] , [2] , [3] , [4] , [5] ]. These contaminants' persistent threats to human, animal, and ecosystem health call for urgent remedies [ [6] , [7] , [8] ]. In the last decades, the expanding knowledge gathered on the ability of microorganisms to degrade or transform pollutants into harmless end-products and their degradative metabolic pathways has strikingly boosted the interest in bioremediation technologies for the cleanup of contaminated sites [ [9] , [10] , [11] ]. These are typically based on the possibility of manipulating environmental conditions by controlling the redox potential and/or by supplying nutrients, electron donors, or acceptors. However, the promise of bioremediation as a lower-cost, simpler, and more environmentally friendly alternative to conventional physical-chemical approaches is yet to be fully realized. Indeed, bioremediation is often associated with limited performance regarding process robustness and rates [ 12 ]. This is largely due to the limited availability of tools for domesticating the biological activity of the pollutant-degrading microbes in the contaminated matrix in time and space. Approximately twenty years ago, research on microbial extracellular electron transfer started to gain significant traction [ 13 , 14 ]. The initial breakthrough technology was the microbial fuel cell, generating power from organic waste or sediments [ [15] , [16] , [17] ]. However, it soon became apparent that the influence of microbial electrochemical technologies (METs) extends far beyond this, impacting numerous other domains of industrial and environmental biotechnology, for example, allowing processes such as groundwater bioremediation to be driven by solid-state electron donors and acceptors in a highly flexible and controllable manner [ [18] , [19] , [20] , [21] , [22] ]. Unlike conventional bioremediation approaches that only provide one redox condition, METs can simultaneously establish reducing (at the cathode) and oxidizing (at the anode) conditions. This process can even be integrated within a single treatment sequence, thus enabling the complete degradation (and detoxification) of contaminants with specific characteristics and complex mixtures [ [23] , [24] , [25] , [26] ]. The most noticeable feature of METs for in situ bioremediation is that the electrodes can be deployed within the contaminated matrix (i.e., soil, sediment, or groundwater). The electrodes can serve as virtually inexhaustible electron acceptors or donors for contaminants degradation (or removal via precipitation as in the case of metals), thus eliminating the need for the external, continual injection of chemical amendments. Another key feature of MET is that the “energy level” of the electron donor/acceptor can be regulated, at least partially, using a power source, hence providing a unique tool for increasing, manipulating, and/or fine-tuning the rate and/or the selectivity of the target reaction(s) [ 19 , 20 ]. Furthermore, it is worth noting that since the electrode(s) may also support microbial growth, METs facilitate the co-localization of the electron donor/acceptor and the degrading microorganisms. Since many organic contaminants (e.g., petroleum hydrocarbons, emerging organic pollutants like pharmaceuticals) can be adsorbed on the surface of carbon-based electrodes, they tend to concentrate in a highly reactive zone where also the biocatalysts occur, and the electron donor/acceptor are simultaneously present [ 27 ]. Over the past few years, electro-bioremediation has attracted considerable interest in the scientific community, and several lab-scale studies have been published which have provided robust indications that MET can be employed for enhancing the biodegradation of a wide range of organic and inorganic soil and groundwater pollutants [ 19 , 28 , 29 ]. Despite this increasingly recognized potential, several hurdles still limit the transition of electro-bioremediation techniques from the laboratory to the field. The most striking is the lack of effective system configurations suitable for in situ applications. Indeed, being surface-based technologies, METs typically require high surface area electrodes to attain sufficiently high contaminants biodegradation rates and treat large, contaminated areas. In the case of large contamination plumes, this would ultimately result in unacceptably high costs of electrodes and consequent prohibitive capital expenditures (CAPEX) [ 28 , 30 ]. This review paper brings forward the intriguing hypothesis that making the surrounding of an electrode electrochemically conductive through the injection into the aquifer of low-cost and environmentally safe (metal- or carbon-based) conductive (nano)particles ( Fig. 1 a) could potentially represent a groundbreaking and cost-effective alternative to the use of multiple, high surface-area electrodes posted at a short distance one from each other. In other words, this approach would result in the creation within the aquifer of a so-called “diffuse electro-conductive zone (DECZ),” serving itself as a sink or source of electrons over high depths and long-distances and thus prompting the in situ bioremediation process more efficiently ( Fig. 1 b). Further to extending the radius-of-influence of electrodes, DECZ could also promote the development of syntrophic communities exploiting direct interspecies electron transfer process (DIET) [ [31] , [32] , [33] , [34] , [35] , [36] ] to anaerobically degrade organic contaminants under for instance, nitrate-reducing, sulfate-reducing, or methanogenic conditions ( Fig. 1 c) [ 37 ]. Fig. 1 a , The creation of a “diffuse electro-conductive zone (DECZ)” within a contaminated aquifer through the injection of iron- or carbon-based materials. b , Extending the radius of influence (ROI) of anodes and cathodes exploiting the DECZ concept. c , Promoting the anaerobic, direct interspecies electron transfer (DIET)-based, cooperative degradation of reduced pollutants under methanogenic or sulfate-reducing conditions by exploiting the DECZ concept. Fig. 1 In the past few years, some review papers dealing with the application of electro-bioremediation or DIET-based bioremediation approaches have been published in the scientific literature [ 19 , 20 , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] ]. Most of these articles, however, have revolved around descriptions of the classes of treated contaminants, the involved (reductive or oxidative) biotransformation pathways, the key microorganisms, and related microbe-electrode extracellular electron transfer mechanisms, as well as the impact of key process parameters on treatment efficiency. To the best of our knowledge, none of these published documents has presented and discussed in a systematic manner practical strategies for in situ implementation of electro-bioremediation or DIET-based technologies. In this specific context, the scope of the present review paper is to: (i) recall briefly fundamental aspects of cathodic, anodic, and DIET-based electro-bioremediation processes; (ii) identify key factors which presently limit treatment efficacy, with specific reference to the radius of influence (ROI) of electrodes; (iii) review strategies to create DECZ; (iv) review state-of-the-art methods to measure soil electronic conductivity at field- and laboratory-scale; (v) identify challenges and research needs for the future application of the DECZ concept in electro-bioremediation processes."
} | 2,872 |
40277608 | PMC12025070 | pmc | 5,333 | {
"abstract": "Honeycomb-structured, mixed-wettability surfaces have attracted significant attention due to their potential for tailoring surface properties and controlling fluid dynamics at the nanoscale. However, the underlying mechanisms governing droplet spreading and wettability modulation remain insufficiently understood. This study, using molecular dynamics simulations, reveals that periodic hydrophilic–hydrophobic areas within honeycomb structures induce unique oscillatory spreading behaviors and allow the precise modulation of equilibrium contact angles. The findings demonstrate that honeycomb designs can effectively transition surfaces between hydrophilic and hydrophobic states, with practical applications in boiling heat transfer, thermal management, and advanced materials development.",
"conclusion": "4. Conclusions and Further Work 4.1. Conclusions In this study, the influence of honeycomb-structured, mixed-wettability surfaces on droplet spreading dynamics and surface wettability modulation was comprehensively investigated through molecular dynamics simulations. The results reveal that a honeycomb structure provides a versatile platform for tailoring surface properties, enabling precise control over the spreading process and equilibrium contact angle. The etched honeycomb areas, with their periodic alternation of hydrophilic and hydrophobic areas, introduce unique oscillatory behaviors during droplet spreading, which are absent on smooth surfaces. These findings underscore the critical role of surface morphology and wettability in determining droplet dynamics at the nanoscale. The adoption of molecular dynamics simulation enabled the detailed analysis of atomic-level interactions, providing insights that are challenging to achieve through the use of experimental or macroscale numerical approaches. By simulating water droplets on honeycomb-etched surfaces, this study highlights how differences in wettability between etched and smooth areas influence the spreading rate, contact line velocity, and final equilibrium state of the droplet. This work further demonstrates that honeycomb structures can effectively modulate surface wettability, transitioning surfaces from hydrophilic to hydrophobic or vice versa, depending on the design parameters. In conclusion, this research establishes a strong foundation for the design and application of honeycomb-structured, mixed-wettability surfaces. By enhancing our understanding of nanoscale droplet dynamics and surface interactions, it paves the way for the development of next-generation materials and technologies that leverage the interplay between structure and wettability. Through continued exploration, honeycomb-inspired surfaces hold promise for addressing critical challenges in thermal management, surface engineering, and beyond. 4.2. Discussion on Future Work In the present research, this paper mainly discusses and analyzes water droplet spreading on honeycomb-structured mixed-wettability surfaces through molecular simulation studies. In the future, further experimental validation is required to confirm the accuracy of the model and the applicability of the related surfaces. Although experiments at the nanoscale are currently challenging to achieve, it is planned that the scale of the experimental validation will be extended to the microscale, utilizing surface roughness to create distinct wettability differences between honeycomb-etched and smooth surfaces on certain copper materials to ensure that the experimental conditions are consistent, as much as possible, with the simulation settings. In addition, the droplets should be stably placed through the use of a pipette on the surface. During the spreading process of the droplet, the droplet profile, such as the change in its contact angle and height, needs to be measured in real time. Thus, a comparison of the simulation results and the experimental results can be used to judge whether the simulation model is accurate.\n\n4.1. Conclusions In this study, the influence of honeycomb-structured, mixed-wettability surfaces on droplet spreading dynamics and surface wettability modulation was comprehensively investigated through molecular dynamics simulations. The results reveal that a honeycomb structure provides a versatile platform for tailoring surface properties, enabling precise control over the spreading process and equilibrium contact angle. The etched honeycomb areas, with their periodic alternation of hydrophilic and hydrophobic areas, introduce unique oscillatory behaviors during droplet spreading, which are absent on smooth surfaces. These findings underscore the critical role of surface morphology and wettability in determining droplet dynamics at the nanoscale. The adoption of molecular dynamics simulation enabled the detailed analysis of atomic-level interactions, providing insights that are challenging to achieve through the use of experimental or macroscale numerical approaches. By simulating water droplets on honeycomb-etched surfaces, this study highlights how differences in wettability between etched and smooth areas influence the spreading rate, contact line velocity, and final equilibrium state of the droplet. This work further demonstrates that honeycomb structures can effectively modulate surface wettability, transitioning surfaces from hydrophilic to hydrophobic or vice versa, depending on the design parameters. In conclusion, this research establishes a strong foundation for the design and application of honeycomb-structured, mixed-wettability surfaces. By enhancing our understanding of nanoscale droplet dynamics and surface interactions, it paves the way for the development of next-generation materials and technologies that leverage the interplay between structure and wettability. Through continued exploration, honeycomb-inspired surfaces hold promise for addressing critical challenges in thermal management, surface engineering, and beyond.",
"introduction": "1. Introduction The spreading of liquid droplets on a solid substrate is critical in nature and in various industries, with extensive applications in lubrication, painting, surface coating, oil recovery, and so forth. In the 1970s, researchers from the US and Japan began to process micro/nano-structured patterns on boiling surfaces to improve the boiling heat transfer performance of electronic device liquid cooling technology [ 1 ]. Emerging techniques by micro/nano-fabrication technology to form surfaces have gradually shifted from the conventional scale to the micro/nanoscale. With the development of MEMS and NEMS devices, this reduction in scale has continued, while the power density of such technology has increased [ 2 ]. This trend has led to a significant rise in the heat generated per unit area, making effective thermal management increasingly challenging. Boiling heat transfer is a highly efficient method, acting as a heat exchange mechanism, which has been proven by previous key experimental research. It has been demonstrated that a mixed-wettability surface can effectively enhance boiling heat transfer. Hu et al. [ 3 ] observed that hydrophobic surfaces exhibit better boiling heat transfer coefficients compared to hydrophilic surfaces, although the critical heat flux (CHF) is lower. Zhang et al. [ 4 ] found that under low superheat conditions, hydrophobic surfaces have a lower boiling onset temperature and higher heat transfer coefficients than hydrophilic surfaces. In addition, researchers have employed the lattice Boltzmann method to investigate the impact of surface wettability on boiling at the microscale [ 5 ]. Lee et al. [ 6 ] demonstrated that reducing the wettability can increase the heat transfer coefficients, but decreases the CHF. Jo et al. [ 7 ] studied bubble nucleation sites, detachment frequency, and other factors of hydrophobic and hydrophilic surfaces in regard to nucleate boiling. Experimental work underpins nature-inspired structures that have resulted in enhanced thermal exchange of the surface in comparison to traditional surfaces. The unique wettability properties found in nature have been used with multi-scale morphological structures found on the surfaces of various plants and animals to analyze aspects such as the “lotus effect” [ 8 ]. In 1997, German botanists Barthlott and Neinhuis discovered that the surface of lotus leaves exhibits distinctive micron-scale papillae structures, allowing water droplets to roll freely across the surface and carry away surface contaminants, thereby achieving a self-cleaning effect. A similar phenomenon of unidirectional liquid transport has been observed on the surface of rice leaves. The surface of rice leaves features micro–nano composite protrusions like those of lotus leaves. These unevenly arranged protrusions are the primary cause of the isotropic rolling behavior of water droplets on the surface of the leaves [ 9 ]. In addition to lotus leaves, the wettability phenomenon of rice leaves and roses [ 10 , 11 ] can also be observed in other plants. Moreover, the wettability of insect wing surfaces has garnered significant attention in recent studies. The investigation into honeycomb structures generated by nature as a thermal exchange surface is limited. Honeycomb structure refers to highly ordered micro/nanoscale structures arranged in a hexagonal pattern. This geometry of highly uniform and regular hierarchical structures can theoretically serve as model for studying thermal properties to generate a surface pattern [ 12 , 13 , 14 ]. The arrangement of structured formations in regard to a specific surface area can be used to form unique optical properties, making them promising candidates for applications in various fields, including tissue engineering, life sciences, superhydrophobic materials, optoelectronic materials, templates, sensors, and micro/nanoparticle separation [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. As a result, in this research, we employ the honeycomb structure to create a new mixed hydrophilic and hydrophobic surface to observe how a mixed-wettability structure with a honeycomb structure effects the wettability of the surface and how droplets spread on these surfaces to add further insight into the enhancement of boiling heat transfer. However, at the nanoscale, it is challenging to observe bubble nucleation or measure the heat flux density through the use of experimental methods or traditional macroscale numerical simulation approaches. Due to the limitations in terms of scale, traditional experimental and numerical simulation methods are unable to effectively reveal the mechanisms of phase change. Molecular dynamics (MD) has emerged in recent years as a powerful microscale numerical simulation method. This method is based on Newton’s second law to simulate molecular motion, enabling the analysis of the microscopic evolution of molecular systems. By applying statistical methods, the macroscopic thermodynamic properties of the molecular system can be calculated. With advancements in computational modeling, MD has been widely adopted and promoted, becoming a robust tool for exploring the mechanisms of boiling heat transfer. Zhang et al. [ 30 ] demonstrated through molecular dynamics (MD) simulations that surface wettability is one of the primary factors influencing boiling heat transfer. A study by Wang et al. [ 31 ] concludes that enhanced surface wettability reduces interfacial thermal resistance, thereby promoting boiling heat transfer. Similarly, Cao and Cui [ 32 ] found that the lower vibrational density of states (VDOS) mismatch between hydrophilic solid walls and liquids results in better heat transfer performance of the liquid film on hydrophilic surfaces. In addition, Hens et al. [ 33 ] showed that hydrophilic surfaces, due to their stronger solid–liquid interfacial potential, can significantly improve boiling heat transfer performance. Chen et al. [ 34 ] observed that during boiling, a layer of argon atoms consistently adheres to hydrophilic triangular nanochannels. This work concludes that hydrophilic nanochannels have greater capacity to transfer thermal energy than hydrophobic surfaces, thus promoting bubble nucleation. Yin et al. [ 35 ], by analyzing the potential energy distribution of liquid films, demonstrated that enhanced surface wettability increases bubble nucleation rates. Wang and Li [ 36 ] revealed that hydrophilic–hydrophobic mixed surfaces with a high hydrophilic area ratio exhibit lower interfacial thermal resistance and superior boiling heat transfer performance. In this study, molecular dynamics simulation is employed to further investigate the role of the honeycomb structure in modifying surface wettability. Specifically, the spreading process of liquid water molecules at room temperature on a honeycomb-etched mixed-wettability surface is simulated. We adjust the wettability of both the honeycomb-etched surface and the smooth surface by tuning the solid–liquid interactions to create a mixed hydrophilic–hydrophobic surface. This study examines the effects of the honeycomb-etched structure on surface wettability, the evolution of the water droplet spreading radius R, and how the honeycomb structure influences the motion of water molecules. Additionally, the effect of the etched honeycomb structure on surfaces with different wettability is also investigated. Figure 1 a illustrates a natural honeycomb structure with a highly uniform hexagonal array pattern. Figure 1 b shows the hydrophobic state of water droplets on the cell walls of the natural honeycomb surface under a microscope. Guo et al. [ 37 ] discovered that the wettability and adhesion properties of natural honeycomb walls in regard to water and honey droplets can be utilized as a “mechanical hand” for micro-droplet transfers. Zhang et al. [ 2 ] progressed this work through the analysis of transported micro/nano droplets by modifying the surface wettability through stretching the honeycomb structure pores. To gain deeper insights into the role of honeycomb walls in regard to surface wettability for micro-droplet transfers, we created a honeycomb form by etching this structure onto a smooth surface, as highlighted in Figure 1 c. The molecular simulation effects of the applied honeycomb-structured pattern was assessed by modelling the surface geometry roughness effects, as illustrated in Figure 1 d, to understand its influence on surface wettability.",
"discussion": "4.2. Discussion on Future Work In the present research, this paper mainly discusses and analyzes water droplet spreading on honeycomb-structured mixed-wettability surfaces through molecular simulation studies. In the future, further experimental validation is required to confirm the accuracy of the model and the applicability of the related surfaces. Although experiments at the nanoscale are currently challenging to achieve, it is planned that the scale of the experimental validation will be extended to the microscale, utilizing surface roughness to create distinct wettability differences between honeycomb-etched and smooth surfaces on certain copper materials to ensure that the experimental conditions are consistent, as much as possible, with the simulation settings. In addition, the droplets should be stably placed through the use of a pipette on the surface. During the spreading process of the droplet, the droplet profile, such as the change in its contact angle and height, needs to be measured in real time. Thus, a comparison of the simulation results and the experimental results can be used to judge whether the simulation model is accurate."
} | 3,905 |
25564461 | PMC4285725 | pmc | 5,334 | {
"abstract": "The composition, ecology and environmental conditions of mesophotic coral ecosystems near the lower limits of their bathymetric distributions remain poorly understood. Here we provide the first in-depth assessment of a lower mesophotic coral community (60–100 m) in the Southern Caribbean through visual submersible surveys, genotyping of coral host-endosymbiont assemblages, temperature monitoring and a growth experiment. The lower mesophotic zone harbored a specialized coral community consisting of predominantly Agaricia grahamae , Agaricia undata and a “deep-water” lineage of Madracis pharensis , with large colonies of these species observed close to their lower distribution limit of ~90 m depth. All three species associated with “deep-specialist” photosynthetic endosymbionts ( Symbiodinium ). Fragments of A. grahamae exhibited growth rates at 60 m similar to those observed for shallow Agaricia colonies (~2–3 cm yr −1 ), but showed bleaching and (partial) mortality when transplanted to 100 m. We propose that the strong reduction of temperature over depth (Δ5°C from 40 to 100 m depth) may play an important contributing role in determining lower depth limits of mesophotic coral communities in this region. Rather than a marginal extension of the reef slope, the lower mesophotic represents a specialized community, and as such warrants specific consideration from science and management.",
"discussion": "Discussion The lower mesophotic community at our study site was dominated by Agaricia grahamae and Madracis pharensis , and to a lesser extent Agaricia undata , confirming previous observations in the Western Atlantic reporting Agaricia and Madracis spp. as the dominant members of the lower mesophotic 5 8 9 20 31 32 33 . Although A. undata is considered rare in Curaçao 17 34 , we can confirm early observations by Bak 15 21 that A. undata does regularly occur at lower mesophotic depths, accounting for about a quarter of our collected Agaricia specimens (8 out of 29) between 80–90 m. Helioseris cucullata and Montastraea cavernosa are two other species that have been regularly reported at depths in excess of 70 m at other locations in the Caribbean 4 , but we observed only one colony of M. cavernosa at these depths. H. cucullata was only observed in this study at depths shallower than 60 m, and in small numbers, which may be related to the reported strong decline of this species in Curaçao over the past several decades 35 36 . Both M. cavernosa and Stephanocoenia intersepta are normally relatively abundant at ~60 m depth at other sites around Curaçao, with species such as Madracis formosa , Agaricia lamarcki and Scolymia cubensis occurring at lower densities (Bongaerts and Vermeij, personal observations). The (relative) absence of these species at lower mesophotic depths (≥60 m) at our study site is therefore not necessarily representative for other reefs around Curaçao. Nonetheless, the observations here confirm that deep-water specialist Agaricia species (i.e. A. grahamae and A. undata ) dominate the lower mesophotic communities beyond 70 m in Curaçao, with M. pharensis occupying the lowest reaches of the mesophotic. Our molecular data provides further insights into whether the lower mesophotic zone represents a unique, specialized community or a “marginal” extension of upper mesophotic reef communities (30–60 m). While the upper mesophotic zone still hosts many “depth-generalist” coral species (~25–40%) that are also found in shallow-water habitats 21 24 , the lower mesophotic community (at the study site) consists mainly of deep-water specialists (i.e. Agaricia grahamae and Agaricia undata ). An exception is the species M. pharensis , which is also commonly found in shallow-water 16 . However, the host phylogeny for this species confirms previous work reporting the presence of two divergent lineages 18 ( Fig. 7 ), that likely represent distinct (cryptic) species. These two M. pharensis lineages each associate with a distinct Symbiodinium type (“Clade 1” with Symbiodinium B15 and “Clade 2” with Symbiodinium B7) and exhibit distinct depth distributions, with the B15-associated lineage found predominantly at mesophotic depths 18 19 ( Fig. 7 ). Interestingly, a further genetic subdivision was found within this clade, between M. pharensis hosts collected from upper mesophotic (40–60 m) and lower mesophotic depths (80–90 m), with depth zones explaining 37% of molecular variance. However, the extent of genetic divergence between these mesophotic populations remains unclear as only a single mitochondrial marker was used. No genetic subdivision was found between A. grahamae specimens from upper mesophotic and lower mesophotic depths (nor between the species A. grahamae and A. lamarcki ) using conserved mitochondrial markers, with all individuals also hosting the same Symbiodinium subtype (assessed for both the ITS2 and cox1 region). The two Symbiodinium types found in association with mesophotic Agaricia and Madracis spp. are rare in shallow reef communities 17 19 and may represent Symbiodinium types specialized to deep-water conditions (e.g. low irradiance) 17 19 37 . These findings corroborate that the upper mesophotic is a transition zone hosting coral-endosymbiont associations that are shared with both the shallow and lower mesophotic reef 2 24 , whereas the lower mesophotic reef hosts a specialized “deep-water” coral and endosymbiont community. Fragments of Agaricia colonies were transplanted from their original depth at ~80 m to a shallower depth (60 m), back to their original depth (80 m), and a depth exceeding their natural distribution range at this site (100 m). Surprisingly, survival rates were extremely low on the “control” rack (80 m) compared to the shallower and deeper rack, despite the fact that fragments were transplanted back to their original depth in the direct vicinity of existing Agaricia colonies. Factors explaining this high mortality may be due to unnoted differential handling or positioning of the rack at a location unfavorable to coral growth (e.g. with increased sedimentation), however an obvious cause could not be identified. The high mortality overall might reflect a lowered ability of corals at these depths (due to physiological limitations) to cope with the stress associated with these manipulations. Although no noticeable growth was observed on the 80 and 100 m racks (linear increases of <4 mm), “healthy” A. grahamae fragments left on the 60 m rack (n = 6) grew at an average (extrapolated) rate of 22.0 mm yr −1 , with a maximum (extrapolated) rate of 30.8 mm yr −1 ( Supplement Table 4 ). These represent some of the first growth estimates measured at lower mesophotic depths (60–100 m), with other records being those from Leptoseris fragilis in the Red Sea (radial growth of 5–8 mm yr −1 ) 30 and that from a single Leptoseris hawaiiensis colony in Hawaii (radial growth of 11 ± 3 mm yr −1 ) 29 . Interestingly, the growth rates we observed at 60 m are similar to the maximum diameter growth rates (24.8–33.6 mm yr −1 ) previously measured for juvenile and adult A. \n humilis and A. agaricites colonies at shallow and intermediate depths (5–30 m) in Curaçao 38 39 40 . Calcification rates are however likely to be lower, as the skeletons of agariciids at lower mesophotic depths are usually much thinner compared to shallow depths 29 30 . The minimal growth of the few “healthy” fragments left on the 80 and 100 m racks (n = 2 on each rack) could indicate that growth rates may decline rapidly at depths beyond 60 m, but given the low sample sizes this should be assessed further. Nonetheless, this initial assessment demonstrates that the growth rates of corals at mesophotic depths (i.e. 60 m) are not necessarily stunted and can be similar to that observed in shallow water, which implies that the coral communities in this depth zone have some ability to recover from physical disturbances. At the study site, zooxanthellate corals were observed down to a maximum depth of ~90 m. The extrapolated proportion of surface PAR irradiance reaching these depths (assuming a constant K d(PAR) ) would be 0.13 or 0.30% depending on which reported K d(PAR) value for Curaçaoan waters is used (0.072 19 or 0.063 41 ). Although these values match extrapolated values reported for other parts of the Caribbean (0.15–0.29%), corals have been observed growing at even lower extrapolated values such as 0.007% in Hawaii (reviewed in Kahng et al. 4 ). Extrapolated values only provide very rough estimates, as optical transparency of the water column is often greater in deeper water and irradiance values at depth are strongly influenced by local bathymetric features 22 . Usually, in the lower mesophotic, a marked decrease in colony size over depth is observed 30 , or exclusively small colonies are found close to the lower depth distribution 42 43 44 , which has been attributed to light gradually becoming a limiting factor to coral growth 4 . At the study site no such pattern was identified for either Agaricia or Madracis , with large colonies of both genera present close to the rather abrupt lower depth limit ( Fig. 2 ). As such, it may be that other environmental factors play a contributing role in determining lower depth distributions of zooxanthellate corals at the study site. Lack of suitable substrate at depth can be an important factor in determining lower depth limits 21 22 , particularly in the presence of sandy terraces, steep walls or undercut ridges, and can prevent the development of coral communities at depths where irradiance levels should still be able to sustain coral growth. Although the slope angle at our study site was mostly very steep at depths beyond 90–100 m, there were several deeper outcrops and ledges consisting of “suitable” hard substrate. Thus, despite the important role of substrate availability and sedimentation in driving the spatial patchiness of mesophotic communities, they cannot explain the observed abrupt depth limit at the study site. Temperatures do not appear to decrease dramatically across the shallow-mesophotic depth gradient in many regions that support coral reefs, and are therefore not considered to play a role in determining depth limits of zooxanthellate corals at tropical locations 4 . Similar conclusions might have been drawn for our study site if temperatures were only measured episodically (e.g. at certain times in July 2013 temperatures were identical from 10 to 80 m depth) ( Fig. 4 ), however over longer time intervals it becomes apparent that thermal conditions are in fact very distinct between shallow and mesophotic depths on Curaçao. A steep decrease in temperatures and increased variability was observed at depths below 40 m 16 45 . Just below the observed depth limit of zooxanthellate corals (100 m depth), temperatures were on average ~5°C lower than at shallow depths (i.e. 22.8°C at 100 m versus 27.6–26.9°C at 10–40 m) and exposures to temperatures <22°C occurred regularly ( Fig. 5 ). Although these temperatures are still well above the known lower temperature limits observed for zooxanthellate corals globally (15–18°C) 46 , they are much lower than seawater temperatures recorded in shallow waters around Curaçao 45 47 and Bonaire 48 . The last month of our transplantation experiment was also the coldest (minimum temperature recorded at 100 m was 19.8°C) ( Fig. 4 ), and the observed bleaching and partial mortality observed on the 100 m transplant rack ( Fig. 8 ) could be the result of long- or short-term exposure to these colder temperature conditions. Although other causes such as long-term exposure to suboptimal light conditions cannot be ruled out, deep-water bleaching (≥30 m) of Agaricia colonies has previously been observed in Curaçao 45 and Bonaire 48 . This bleaching could be attributed to cold-water influxes likely due to the shallowing of a deep-water thermocline. The bleaching in Curaçao was followed by substantial mortality of Agaricia on the deep reef (Bak, unpublished results), demonstrating that episodic cold-water exposure can be an important selective force for deep reef communities. As such, we hypothesize that temperature is a contributing factor in determining lower depth limits at the study site, and may be limiting the development of coral communities at depth through long-term exposure to colder temperatures or short-term exposure to episodic cold-water anomalies 49 . As cold-water influxes on deep reefs can be dependent on bathymetry 50 , it could well be that lower depth limits also vary around the island depending on the reef profile. Overall, this study demonstrates that the lower mesophotic represents a specialized coral community, rather than a marginal extension of the reef slope, and should be regarded as a distinct entity within the coral reef ecosystem. Only a few dominant zooxanthellate coral species were found at these depths, but all of them represented deep-specialists, hosting specialist Symbiodinium types, that only rarely occur on the shallow reef. Although our initial findings on growth rates at the transition of the upper and lower mesophotic zone (i.e. 60 m depth) indicate a certain potential for recovery, the dominant flat and plate-like morphologies at lower mesophotic depths make these coral communities susceptible to sedimentation from e.g. coastal development 45 and their thin skeletons make them more prone to direct physical disturbances. Indirect effects of artisanal and recreational fisheries can be substantial, and we observed a lot of human debris ranging from discarded glass bottles to small “disposable” fishing anchors. Currently, lower mesophotic coral ecosystems in this region do not receive any form of protection as they fall outside of the “Marine Park” boundaries in both Curaçao and Bonaire, which are defined by the 60 m isobaths. We argue that these ecosystems deserve separate consideration during marine conservation planning, taking into account their distinct set of stressors and to provide them with adequate protection despite being located “out-of-sight”."
} | 3,552 |
21983651 | PMC3210952 | pmc | 5,336 | {
"abstract": "The microbial electrolysis cell (MEC) is a promising system for hydrogen production. Still, expensive catalysts such as platinum are needed for efficient hydrogen evolution at the cathode. Recently, the possibility to use a biocathode as an alternative for platinum was shown. The microorganisms involved in hydrogen evolution in such systems are not yet identified. We analyzed the microbial community of a mixed culture biocathode that was enriched in an MEC bioanode. This biocathode produced 1.1 A m −2 and 0.63 m 3 H 2 m −3 cathode liquid volume per day. The bacterial population consisted of 46% Proteobacteria , 25% Firmicutes , 17% Bacteroidetes , and 12% related to other phyla. The dominant ribotype belonged to the species Desulfovibrio vulgaris . The second major ribotype cluster constituted a novel taxonomic group at the genus level, clustering within uncultured Firmicutes . The third cluster belonged to uncultured Bacteroidetes and grouped in a taxonomic group from which only clones were described before; most of these clones originated from soil samples. The identified novel taxonomic groups developed under environmentally unusual conditions, and this may point to properties that have not been considered before. A pure culture of Desulfovibrio strain G11 inoculated in a cathode of an MEC led to a current development from 0.17 to 0.76 A m −2 in 9 days, and hydrogen gas formation was observed. On the basis of the known characteristics of Desulfovibrio spp., including its ability to produce hydrogen, we propose a mechanism for hydrogen evolution through Desulfovibrio spp. in a biocathode system.",
"introduction": "Introduction The high-energy demands of our modern society in combination with the foreseeable depletion of fossil fuels call for the development of sustainable, green forms of energy. Biomass or the organic waste from wastewaters is a source of renewable energy. Recent advances in the use of organic matter for energy production include electricity generation in a microbial fuel cell (MFC) (Logan et al. 2006 ) and the production of hydrogen in a microbial electrolysis cell (MEC) (Liu et al. 2005 ; Rozendal et al. 2006 ; Logan et al. 2008 ). These kinds of systems are still under development, but they show great potential for green energy production. Both MFC and MEC usually consist of two compartments containing an anode and a cathode separated by an ion exchange membrane (Rozendal et al. 2007 ). The two electrodes are connected through an electrical circuit. At the anode, electrochemically active microorganisms are present that consume organic matter and transfer the electrons derived from metabolic processes to the electrode, either by direct or indirect extracellular electron transfer (Ieropoulos 2005 ; Lovley 2006 ; Stams et al. 2006 ; Torres et al. 2009 ; Lovley and Nevin 2011 ). An electron acceptor in the cathode liquid enables a current flow from anode to cathode. Typically, oxygen or Fe(III) is used as the electron acceptor in the MFC (Rabaey and Verstraete 2005 ; Logan and Regan 2006 ), while in the MEC, protons act as the sole electron acceptor to form hydrogen. For the MEC, a supply of electrical energy is required to make hydrogen gas production possible (Liu et al. 2005 ; Rozendal et al. 2006 ). Acetate is often used as model substrate in MEC systems because it is an end product of fermentation. Theoretically, acetate oxidation yields a potential of −0.29 V (vs. standard hydrogen electrode (SHE), at pH 7, pH 2 = 1 bar), while for hydrogen production from protons, a potential of −0.41 V (vs. SHE, at pH 7, pH 2 = 1 bar) is required (Liu et al. 2005 ). Energy is added by applying enough voltage to render an exergonic reaction. Hence, the theoretically applied voltage required for hydrogen gas production in an MEC fed with acetate is 0.12 V. In comparison, for conventional water electrolysis, the theoretically applied voltage needed is 1.2 V at pH 7 (Liu et al. 2005 ). The lower energy requirement of the MEC makes it an attractive system for hydrogen gas production. In practice, however, a minimum applied voltage of 0.25 V is needed because of several potential losses in the system (Rozendal et al. 2006 ; Sleutels et al. 2009a , b ). The total applied voltage demand in practice is for a great part dependent on the overpotential at the electrodes. The use of a good catalyst can decrease the overpotential significantly (Jeremiasse et al. 2009b ). Conventionally, platinum is used as a catalyst for hydrogen gas production (Vetter 1967 ) and is therefore also applied at MEC cathodes (Rozendal et al. 2006 ). Because of the high costs and scarcity of platinum, alternative catalysts for hydrogen production are desirable. Microbial cathodes (biocathodes) form an alternative with great prospectives since they are low cost (both electrode material and catalyst) and self-generating. A biocathode can be defined as an electrode from cheap material (e.g., carbon) with a microbial population present at the electrode or in the electrolyte that catalyzes the cathodic reaction. To act as a biocathode in an MEC, microorganisms need to be able to take up electrons from the electrode material and use these electrons to produce hydrogen. The uptake of electrons from a solid surface or cathode is known from corrosion studies, where metals (e.g., iron) are oxidized by microorganisms that use the electrons from this reaction for metabolic processes (Dinh et al. 2004 ; Mehanna et al. 2009 ). Furthermore, in MFCs, biocathodes have been successfully applied to reduce oxygen, fumarate, nitrate, perchlorate, or chlorinated compounds (Huang et al. 2011 ). Microorganisms that can produce hydrogen are found in a large variety of environments (Schwartz and Friedrich 2006 ) and contain hydrogenases that catalyze the reversible reaction 2H + + 2e − ↔ H 2 . Purified hydrogenases have been successfully used on carbon electrodes as a catalyst for hydrogen production (Vignais et al. 2001 ; Lojou and Bianco 2004 ; Lojou 2011 ; Vincent et al. 2007 ). The drawback for these systems is that the enzymes are relatively unstable and lose catalytic activity over time. The use of whole cells can help in maintaining enzyme stability. Immobilization of whole Desulfovibrio vulgaris cells (well known to contain hydrogenases) on an electrode was successful for hydrogen production, and the process was more stable than with enzymes only (Guiral-Brugna et al. 2001 ; Lojou et al. 2002 ). For continuous hydrogen production, the challenge is to generate a biocathode with living cells, able to survive and grow. The microbial uptake of electrons from a cathode for the production of hydrogen in an MEC was shown for the first time by Rozendal et al. ( 2008 ). In their study, an MEC half cell with carbon felt electrodes was started up with a biological anode that was initially fed with acetate and hydrogen. Hexacyanoferrate(III) was reduced at the cathode. When stable anodic current was reached, the acetate and hydrogen supply was stopped, and the polarities of anode and cathode were reversed, resulting in a biocathode and chemical anode. The cathode potential was poised at −0.7 V vs. SHE resulting in an average current of 1.1 A m −2 and production of 0.63 m 3 H 2 m −3 cathode liquid volume per day. A similar setup that was not inoculated served as negative control and produced a current of 0.3 A m −2 and 0.08 m 3 H 2 m −3 cathode liquid volume per day. In the present study, we describe the microbial population present on the graphite felt cathode using scanning electron microscopy, denaturing gradient gel electrophoresis (DGGE), and cloning and sequencing of 16S ribosomal RNA genes.",
"discussion": "Discussion In previous research, hydrogen production in an MEC with a biocathode has been shown (Rozendal et al. 2008 ; Jeremiasse et al. 2009a ). Our research gives the first description of a microbial community of a hydrogen-producing biocathode in an MEC. The results showed high bacterial 16S rRNA gene diversity, with the dominant species belonging to the genus Desulfovibrio . Two other predominant clusters were found that were related to uncultured Firmicutes and uncultured Bacteroidetes . In addition to being the dominant ribotype in the MEC biocathode, progression of current was shown after inoculation of an MEC cathode with pure cultures of Desulfovibrio G11. The dominance of Desulfovibrio spp. in the biocathode can be reasoned because Desulfovibrio species are well known for their ability to produce and consume hydrogen gas (Carepo et al. 2002 ). Coating of an electrode with immobilized D. vulgaris cells has been reported to catalyze the evolution of hydrogen at a cathode (Lojou et al. 2002 ). However, this catalytic effect occurred only in the presence of the electron shuttle methyl viologen. The application of living Desulfovibrio as hydrogen catalyst at a cathode without an added mediator, as in our system, was not shown before. This is not only fundamentally, but also practically, of great interest because it will allow low-cost and self-maintaining cathode systems for hydrogen production. The second major group of bacteria found in this study, the uncultured Firmicutes , does not belong to any earlier described genus. Apparently, the conditions in the MEC created an environment in which bacteria belonging to a new taxonomic group were able to develop predominantly. Moreover, it is interesting to note that the closest related genus is Desulfitobacterium , of which at least one member, D. hafniense strain DCB2, was electrochemically active in an anode from an MFC (Milliken and May 2007 ). Furthermore, Desulfitobacterium spp. were found as the dominant population in a mixed culture that was producing hydrogen gas in a dechlorinating cathode system (Aulenta et al. 2008 ). Similar to the experiment with immobilized D. vulgaris , no hydrogen was produced in the absence of methyl viologen as a mediator. The third major group of bacteria in the MEC biocathode belonged to the uncultured Bacteroidetes and also constitutes a novel group without cultured relatives at genus level (92% identity). Members of the Bacteroidetes phylum are found in a large variety of environments such as soil, sediments, human and animal gut, and seawater. The group of uncultured Bacteroidetes clones in our study was most closely related to clones from various environmental samples that presumably all originated from anaerobic sources. The closest related cultured bacterium, R. microfusus , grows fermentatively on carbohydrates (Kaneuchi and Mitsuoka 1978 ), but no other information about its metabolism is available. The principle of electron uptake from a solid surface has been shown before, but the mechanisms are poorly understood. The reverse process of electron transfer to an anode has been studied in more detail, and those studies provided information on which mechanisms are possible (Rabaey et al. 2004 ; Lovley 2008 ; Nevin et al. 2009 ). Extracellular electron transfer can take place indirectly using electron shuttles such as methyl viologen, humic acid, sulfide, cysteine, riboflavin, phenazine, and quinones (Stams et al. 2006 ; Logan 2009 ). Membrane-associated proteins such as cytochromes and cell appendages or nanowires have been suggested to be involved in direct electron transfer (Kim 2002 ; Mehta et al. 2005 ; Reguera et al. 2005 ). For the most extensively studied species G. sulfurreducens , expression and deletion studies have shown that direct extracellular electron transfer to an electrode involves multicopper proteins (Holmes et al. 2008 ), several c -type cytochromes, (Holmes et al. 2006 ) and pillin structures which most likely are involved in the physical association with the electrode (Nevin et al. 2009 ). Furthermore, G. sulfurreducens can change from electron donating to electron uptake for hydrogen production after reversing the potential from anodic to cathodic (Geelhoed and Stams 2011 ). For extracellular electron uptake from an electrode, several mechanisms have been suggested (Geelhoed et al. 2010 ; Rosenbaum et al. 2011 ). Recent findings suggest that G. sulfurreducens uses different cytochromes in the pathways for electron donating than for electron uptake (Strycharz et al. 2011 ). These authors suggest that this might reflect the optimal potential at which specific proteins can accept or donate electrons. With our findings that Desulfovibrio spp. are dominant microorganisms at the cathode together with our findings that Desulfovibrio G11 is electrochemically active at the cathode, the possible mechanisms of electron transfer and hydrogen production for this species can be inferred, as discussed below. The genomes of Desulfovibrio species show several c -type cytochromes and multicopper proteins with homology to the proteins involved in electron donation in Geobacter species (NCBI search). Similar to the pillin structures in Geobacter spp., D. vulgaris flagellar appendages (genes flgC , flgB , and flgL ) have been associated with physical association during syntrophic growth (Walker et al. 2009 ) and might also be involved in adherence to electrodes. These similarities suggest that the mechanism of extracellular electron transfer by Desulfovibrio spp. could be similar to previously described mechanisms of electron transfer involving extracellular appendage (pili or flagella)-like structures, cytochromes, or shuttle compounds. The electron transfer from an electrode to the microorganisms can possibly take place by reversed reaction of those previously described mechanisms. More research is needed to understand how electron transfer in cathode systems takes place. Hydrogen production from protons is energetically costly. For microbial hydrogen production, energy needs to be added in the form of an electron donor with high energy (e.g., glucose or light) or in the MEC biocathode by the applied voltage. A putative mechanism for the conservation of energy from hydrogen production at the cathode may be comparable to hydrogen production from formate in methanogenic co-cultures (Dolfing et al. 2008 ; Stams and Plugge 2009 ). Energy gain and growth from production of hydrogen have been shown for Desulfovibrio G11 grown on formate in coculture with Methanobrevibacter arboriphilus AZ (Dolfing et al. 2008 ). Conservation of energy by Desulfovibrio spp. was proposed to involve an energy-conserving hydrogenase or a hydrogenase present at the cytoplasmic side of the membrane. In the genome of D. vulgaris , genes coding for both types of hydrogenases are present. The release of protons from formate by a formate dehydrogenase located at the periplasmic side of the membrane combined with proton consumption at the cytoplasmic side results in the generation of a proton gradient over the membrane that can be utilized by a membrane-bound ATPase. It has been suggested that in a similar way energy, could be gained from the production of hydrogen from electrons derived from a cathode (Geelhoed et al. 2010 ). Our findings that Desulfovibrio species dominate the microbial community of the MEC support the idea that the mechanism of electron transfer from an electrode to the bacterium can take place like suggested before by Dolfing et al. ( 2008 ) and Geelhoed et al. ( 2010 ). Comparing MEC experiments to syntrophic growth, Geelhoed et al. ( 2010 ) calculated that the energy applied to MEC systems is enough to allow energy conservation and growth. However, in those calculations, no energy losses in the system were taken into account. The actual energy available at the cathode can be estimated from the potential of the cathode (−0.7 V vs. SHE) minus the energy needed to form hydrogen (−0.41 V vs. SHE) which gives the maximum theoretical energy available for the microorganisms (−0.29 V). The cathode losses, expressed as the concentration overpotential, can be calculated as described by Jeremiasse et al. ( 2009b ). Under the conditions prevailing in the biocathode system studied here (Rozendal et al. 2008 ), using a p K a 2 of 7.21 for phosphate buffer, the concentration overpotential can be estimated at −0.019 V. Hence, the actual energy available for the microorganisms is −0.29 + 0.019 = −0.27 V or −52 kJ per mole H 2 produced (at pH 7 and pH 2 = 1 bar). In comparison, the Gibbs free energy change associated with conversion of formate to hydrogen and carbon dioxide is −17 to −19 kJ per mole H 2 (Dolfing et al. 2008 ). This shows that for the studied biocathode system, even if the overpotential is taken into account, there is sufficient energy available for the microorganisms to grow. The energetic limits for microbial hydrogen production and growth in an MEC biocathode still need to be explored. Our findings that the dominant microorganism in the MEC biocathode is a Desulfovibrio sp., together with the knowledge about the hydrogen metabolism and potential for exocellular electron transfer of Desulfovibrio spp., give very strong indications that they are actively involved in the hydrogen production at the biocathode of the MEC. Since Desulfovibrio spp. are also able to consume hydrogen, it can be reasoned that the microbial community on the electrode developed during the anodic phase, in which acetate and hydrogen were the substrates. However, after switching the polarity, the production of hydrogen gas commenced only after several days, suggesting that microbial adaptation and possibly growth were necessary to start hydrogen production at the cathode. In addition, the potential electroactivity of Desulfovibrio in a cathode was supported by the observed current production and hydrogen production after inoculation of an MEC cathode with Desulfovibrio G11. Besides Desulfovibrio , two novel and abundantly present groups of bacteria were present. These bacteria need to be characterized further before their role in an MEC can be inferred."
} | 4,510 |
28961177 | PMC5664097 | pmc | 5,337 | {
"abstract": "Many insect species maintain mutualistic relationships with endosymbiotic bacteria. In contrast to their free-living relatives, horizontal gene transfer (HGT) has traditionally been considered rare in long-term endosymbionts. Nevertheless, meta-omics exploration of certain symbiotic models has unveiled an increasing number of bacteria-bacteria and bacteria-host genetic transfers. The abundance and function of transferred loci suggest that HGT might play a major role in the evolution of the corresponding consortia, enhancing their adaptive value or buffering detrimental effects derived from the reductive evolution of endosymbionts’ genomes. Here, we comprehensively review the HGT cases recorded to date in insect-bacteria mutualistic consortia, and discuss their impact on the evolutionary success of these associations.",
"conclusion": "4. Conclusions Close association with microorganisms allowed animals to colonize highly specialized niches. This is the case of insects, whose facultative/obligatory association with mutualistic intracellular bacteria is considered essential for their evolutionary success. The ever-increasing availability of genomic data has highlighted the high impact of inter-domain associations on the horizontal acquisition of exogenous DNA by insects. Although most of the cases appear to represent transient transfers of genes, lacking an effective integration in the biology of the recipient species, recent findings strongly suggest that HGT might play a key role in the fine-tuning of mechanisms allowing for the maintenance and regulation of insect-bacteria nutritional symbioses. In the holobiont era, further analyses of available genomic/transcriptomic data, exploration of additional symbiotic models, and empirical assessment of the adaptive value of transferred loci are expected to enhance this new paradigm.",
"introduction": "1. Introduction 1.1. Horizontal Gene Transfer: Molecular Signatures and Mechanisms Vertical inheritance between generations, via sexual or asexual reproduction, represents the main mechanism for the transmission of genetic material in nature [ 1 ]. Nevertheless, genetic information can also be transmitted between reproductively isolated species via Horizontal Gene Transfer (HGT). This phenomenon is governed by three major mechanisms in prokaryotes: transformation (i.e., direct uptake of exogenous DNA), conjugation (i.e., plasmid-mediated uptake of exogenous DNA), and transduction (i.e., virus-mediated uptake of exogenous DNA). More recently, genetic transfer through prophages-derived gene transfer agents (GTAs) and cell fusion have been described [ 2 ]. On the other hand, the mechanisms allowing for HGT in eukaryotes remain unclear. Evidences suggest the key involvement of transposable elements [ 3 , 4 , 5 , 6 , 7 ], bacteriophages [ 8 ], giant viruses [ 9 ], and extracellular vesicles such as exosomes [ 10 ] in bacteria-to-animals transfer of genetic material. Mutational change and subsequent selection might lead to the appearance of novel genes after the duplication of pre-existing loci. Alternatively, genes that have already undergone selective pressures can be directly transferred between different species via HGT [ 11 ]. Despite the evident evolutionary advantages of HGT (see Section 1.2 ), newly acquired loci often function inefficiently within their new genomic background [ 12 , 13 ] and/or generate detrimental side effects [ 14 ]. HGT-associated costs are related to several non-mutually exclusive phenomena. These include genetic/genomic features disruption [ 15 , 16 ]; sequence-specific signatures of the horizontally acquired loci [ 17 ]; sequestration of cell limited resources due to transcription and translation of gene products encoded by the foreign DNA [ 18 ]; cytotoxic effects due to misfolded proteins [ 19 , 20 ]; disruption of fine-tuning of cellular networks caused by changes in protein dosage [ 13 , 21 ] or inefficient interaction with local proteins due to the lack of molecular co-evolution [ 22 , 23 ]; and system-level effects derived from direct or indirect impact of acquired loci on the regulation of transcriptional patterns or the concentration of signaling metabolites [ 24 , 25 ]. Due to the HGT-associated costs, the kind of genes and pathways maintained over extended timescales after being transferred are highly biased. When present, horizontally acquired sequences are detected by using probabilistic methods, including molecular phylogenetics, codon usage, and oligonucleotide composition analyses [ 2 ]. In addition, synteny-based evidences or shared ecological niches between donor and recipient species can be used to further support the HGT-hypothesis. 1.2. Horizontal Gene Transfer as an Evolutionary Force Horizontal transfer of genetic material plays a major evolutionary role among prokaryotes [ 26 , 27 ], explaining their extensive ecological diversification [ 28 , 29 , 30 ], and being relevant for bacterial evolution at least since the origins of the bacterial divisions [ 31 ]. Eukaryotes, however, present several barriers to HGT, including the selective double membrane of the cellular nucleus, the required adjustment of acquired genetic elements to the eukaryotic transcription machinery, and the need to affect the germ cell line in order to ensure intergenerational transmission in multicellular organisms [ 11 , 32 ]. In spite of this, prokaryotes-to-eukaryotes HGT events have drastically influenced eukaryotes early evolution. According to the Serial Endosymbiosis Theory (SET), free-living alphaproteobacteria and cyanobacteria were the ancestors of mitochondria and chloroplast, respectively. Their functional integration with early eukaryotes led to the organelles drastic genome reduction and horizontal transfer of both RNA- and protein-coding genes to the eukaryotic nuclear genome [ 1 , 33 , 34 ]. This phenomenon apparently keeps playing an important role in eukaryotes adaptive evolution [ 35 ]. Thus, many HGT events detected in fungi [ 36 , 37 , 38 ], plants [ 9 , 39 ], and animal genomes (see next sections for further details) involve bacteria as donor species. In general, bacteria possessing the ability to transfer DNA to eukaryotes closely interact with eukaryotic hosts (i.e., they maintain symbiotic associations of parasitic or mutualistic nature), and show high levels of genome plasticity and gene motility by means of a relevant mobilome. In addition, certain bacterial structures such as Type IV Secretion System (T4SS), the only natural bacterium-to-eukaryote DNA transfer system known so far [ 40 ], might facilitate this kind of transfer. Next-generation sequencing technologies are yielding a growing body of evidence on HGT signatures in animal genomes [ 41 ]. Most HGT events affect invertebrates that display close associations with a broad range of microorganisms [ 42 , 43 ], and whose simpler structural organization is expected to increase the accessibility of their germline to exogenous DNA. In some cases, HGT drastically impacts animals’ biology. For instance, the human parasitic nematode Brugia malayi encodes an essential ferrochelatase gene of prokaryotic origin [ 44 ], and the transfer of a nearly complete Wolbachia pipientis genome has triggered the evolution of a new sex chromosome in pill bugs [ 45 ]. Furthermore, HGT have apparently allowed for the colonization of novel ecological niches. Thus, a number of genes encoding plant cell-wall degrading enzymes such as cellulases, xylanases, pectate lyases, and polygalacturonases have been found in plant–parasitic nematodes [ 4 , 46 ]. In the same line, the adaptation to the herbivorous lifestyle of the coffee berry borer beetle Hypothenemus hampei and the mustard leaf beetle Phaedon cochleariae has been facilitated by horizontally acquired genes (i.e., mannanase and xylanase, respectively), likely coming from the gut microbiota [ 3 , 6 ]. In some cases, selective advantages supplied by horizontally transferred loci might not be so obvious. For example, the genetic diversity of bdelloid rotifers provided by massive HGT from bacteria, fungi and plants might both compensate for their unisexual reproductive strategy and enable tolerance against desiccation [ 47 ]."
} | 2,053 |
30889870 | PMC6471067 | pmc | 5,339 | {
"abstract": "Polyurethane (PU) is a versatile polymer used in a wide range of applications. Recently, imparting PU with self-healing properties has attracted much interest to improve the product durability. The self-healing mechanism conceivably occurs through the existence of dynamic reversible bonds over a specific temperature range. The present study investigates the self-healing properties of 1,4:3,6-dianhydrohexitol-based PUs prepared from a prepolymer of poly(tetra-methylene ether glycol) and 4,4′-methylenebis(phenyl isocyanate) with different chain extenders (isosorbide or isomannide). PU with the conventional chain extender 1,4-butanediol was prepared for comparison. The urethane bonds in 1,4:3,6-dianhydrohexitol-based PUs were thermally reversible (as confirmed by the generation of isocyanate peaks observed by Fourier transform infrared spectroscopy) at mildly elevated temperatures and the PUs showed good mechanical properties. Especially the isosorbide-based polyurethane showed potential self-healing ability under mild heat treatment, as observed in reprocessing tests. It is inferred that isosorbide, bio-based bicyclic diol, can be employed as an efficient chain extender of polyurethane prepolymers to improve self-healing properties of polyurethane elastomers via reversible features of the urethane bonds.",
"conclusion": "3. Conclusions We have synthesized PUEs with biobased isosorbide and isomannide as chain extenders and compared their properties with those of PUE synthesized with a BD chain extender. The anhydrohexitol-extended PUEs exhibited higher mechanical properties than the BD-extended PUE. The morphologies of the synthesized PUEs depends on the chemical structure and microphase separations of hard segments composed of chain extender molecules. As confirmed by the FT-IR spectra and TGA results, the anhydrohexitol-based PUs exhibited thermal reversibility with their constituents; moreover, a fractured ISB–PU film reformed after hot pressing at 150 °C. It is inferred that the anhydrohexitols due to the rigid, bulky structure of ISB and IMN as chain extenders conferred more thermal reversibility to PUE than BD, the conventional chain extender. It was found that ISB-PU showed superior mechanical properties compared with BD-PU and IMN-PU. Owing to its reversibility and excellent mechanical properties, ISB-based PU is a promising candidate for hot melt adhesives, powder coatings, and self-healing polymers.",
"introduction": "1. Introduction Polyurethane (PU) is a very versatile material with a wide range of physical and chemical properties. Consequently, it is widely applied in the automotive, construction, furniture, insulation, and textile industries [ 1 ]. Polyurethane elastomer (PUE), a linear block copolymer composed of a soft and a hard segment, is especially versatile. The soft segment (polyol) imparts the elastic properties of the polymer, and the hard segment (diisocyanate with a chain extender) acts like a physical crosslinker [ 2 ]. The strength and stiffness of the segmented structure can be controlled by varying the constituents of these three materials (polyol, diisocyanate, and chain extender) [ 3 , 4 , 5 ]. From an economic viability and safety perspective, other researchers have attempted to increase the lifetime of PU products [ 6 , 7 ]. Recently, the introduction of dynamic covalent bonds for self-healing polymers has attracted increasing interest. One self-healing mechanism involves reversible covalent bonding between the isocyanate and active hydrogens in PUs [ 8 , 9 ]. As the bond between isocyanate and aromatic hydroxyl compounds is relatively weak, it dissociates at a certain temperature, releasing free isocyanate and an aromatic hydroxyl. The dissociation temperature of thermo-reversible urethane bonds depends on the structures of the isocyanate and active hydrogen compound [ 10 , 11 ]. The reversible properties were utilized for the development of blocked isocyanates. Under appropriate temperature control, these covalent bonds can be repeatedly formed and dissociated, enabling self-healing in even thermosetting PUs [ 12 , 13 , 14 ]. In recent years, the replacement of petroleum-based materials with greener alternatives has become an urgent topic in both academia and industry, as petroleum resources are depleting and their disposal causes environmental problems [ 15 , 16 , 17 ]. As candidates among renewable resources, carbohydrate derivatives are highly suitable because they are biodegradable, biocompatible, low cost, and naturally abundant [ 18 , 19 ]. 1,4:3,6-Dianhydrohexitol exists in three isomeric forms with different chiralities: isosorbide (1,4:3,6-dianhydro- d -glucitol), isomannide (1,4:3,6-dianhydro- d -mannitol), and isoidide (1,4:3,6-dianhydro- l -idotol) [ 20 ]. 1,4:3,6-Dianhydrohexitol is a biobased bicyclic diol consisting of two cis -shaped tetrahydrofuran rings and two hydroxyl groups, with an internal angle of approximately 120°. Isosorbide has one highly reactive hydroxyl group at the exo-position (OH-2) and one relatively less reactive hydroxyl group at the endo-position (OH-5). At the endo-position, the reactivity is hindered by steric effects and hydrogen bonds with nearby ether groups. Isomannide has two endo-hydroxyl groups, whereas isoidide has two exo-hydroxyl groups [ 21 , 22 ]. Polymers based on 1,4:3,6-dianhydrohexitol have high glass transition temperatures [ 23 , 24 ] and special optical properties [ 25 ], and are applied as food packaging materials [ 26 ] and medical fields [ 27 , 28 , 29 ]. An PU based on isosorbide was first reported in 1984 [ 30 ]. More recently, isosorbide [ 31 , 32 , 33 , 34 ] and isomannide [ 35 ] have been studied to replace the petrochemical-based chain extender (1,4-butanediol) being used in conventional PU manufacture. To the best of our knowledge, the thermally reversible nature of urethane bonds formed by the chemical reactions between 1,4:3,6-dianhydrohexitol and aromatic diisocyanates was not investigated up to now. In this paper, we investigated PUEs based on isosorbide and isomannide, and study the applicability of the reversible properties of the urethane bonds to self-healing polymers using the structural features of 1,4:3,6-dianhydrohexitol. We prepared a prepolymer by reacting polyol with an aromatic diisocyanate. We then produced PUEs using butane diol, isosorbide, or isomannide as the chain extender. The urethane groups formed from isosorbide and isomannide display reversible properties at lower temperature than 1,4-butanediol based urethane groups, allowing reprocessing and thermally self-healing properties at mild temperatures.",
"discussion": "2. Results and Discussion 2.1. Synthesis and Characterization of PUEs The process to prepare PUEs is described in Scheme 1 . The successful synthesis of the prepared PUEs was confirmed by FT-IR spectroscopy. Figure 1 shows the FT-IR spectra of BD–PU, ISB–PU, and IMN–PU. The characteristic peaks of PUE appear in Figure 1 A. The –N=C=O stretching peak at 2270 cm −1 is absent, confirming that the isocyanate of the prepolymer has completely reacted with the hydroxyl group of the chain extender, forming the urethane group ( Figure S1 ) [ 36 , 37 ]. The characteristic N–H stretching peak and carbonyl –C=O stretching peak of urethane appear in the regions 3500–3200 and 1733–1700 cm −1 , respectively. The urethane linkage was confirmed by the –CN peak of carbamate at 1536 cm −1 and the amide peak at 1223 cm −1 [ 38 , 39 ]. The N–H stretching peaks of the PUEs are compared in Figure 1 B. The absence of the free N–H stretching peak at 3480 cm −1 clarifies that almost all the N–H groups were hydrogen bonded. The absorbances in the 3300–3350 and 3290–3310 cm −1 regions are attributed to N–H groups hydrogen bonded to the carbonyl oxygen of urethane and to the oxygen of ether respectively. The absorbance peak of N–H at a higher wavenumber in IMN–PU than those in BD–PU and ISB–PU indicates stronger bonding of the hard segment in IMN–PU than in BD–PU and ISB–PU. Figure 1 C compares the FT-IR spectra of the C=O stretching peaks at 1500–1800 cm −1 for the three PUs. Hydrogen-bond formations of the carbonyl groups of PU are well known and reflect microphase separation of the soft and hard segment domains of the PU. Hydrogen bonding shifts the peak of the carbonyl group to lower wavenumbers (ca. 1710 cm −1 , versus 1730 cm −1 for free carbonyl groups). The ratio of the absorbances at 1730 and 1710 cm −1 can assay the number of hydrogen bonds in the hard segments of PU. The absorbance ratios of BD–PU, ISB–PU, and IMN–PU were 0.89, 0.81, and 1.18, respectively, verifying that the hard segments of IMN–PU formed a higher proportion of strong hydrogen bonds than those of BD–PU and ISB–PU [ 40 ]. The strong hydrogen bonds in IMN–PU are attributable to the conformation of IMN (endo-positioned hydroxyl groups), which favors hydrogen bonding and microphase separation as shown in Figure 1 C. The molecular weights of the PUEs determined by GPC are summarized in Table 1 . The molecular weight of BD–PU was the highest among the three PUs, because the secondary hydroxyl groups of ISB and IMN react less readily with the isocyanate group than the primary hydroxyl group of BD [ 41 ]. In the ISB- and IMN-based PUs, the final molecular weight depends on the position of the secondary hydroxyl group. IMN–PU has a lower molecular weight than ISB–PU because its reactivity is impeded by the steric hindrance of the endo-hydroxyl groups (the exo-hydroxyl groups are comparatively free) [ 20 ]. 2.2. Thermal and Mechanical Properties of PUEs The microphase separation of PUEs can be also studied by DSC and DMA. Figure 2 shows the DSC thermograms of the PUEs prepared in this study. The enthalpy changes at low temperatures (−60 to −50°C) are related to glass transitions of the soft segment domain. It is worthwhile noting that the glass transition temperature of the soft segments ( T gs ) of IMN–PU is lower than those of BD–PU and ISB–PU. The low T gs of polyol in the soft segment of IMN–PU is attributable to better microphase separation than in the other PUEs [ 42 ]. The hard segments of the three PUEs melted in similar temperature ranges (150 °C to 200 °C), although the enthalpy change (∆ H mh ) of the hard segment melt was larger in IMN–PU than in BD–PU and ISB–PU, again indicating the superior microphase separation, strong hydrogen bonds, and high crystallinity of IMN–PU [ 43 , 44 ]. Glass transition temperatures of hard segments of PUE ( T gh ) were observed between T gs and T mh at 30~60 °C. Figure 3 displays the dynamic mechanical properties of the investigated PUEs. The rubbery plateau modulus of IMN–PU was higher than those of BD–PU and ISB–PU in (A) of Figure 3 . This high rubbery plateau modulus reflects the structural features and physical crosslinking effects of the hard segment domain. The flow temperature ( T flow ) defined as the intersection of the rubbery plateau region and flow region was also higher in IMN–PU than in the other PUs. The stronger the hydrogen bond of PUEs, the higher the flow temperature of PUEs. Figure 3 B compares the loss moduli in the three PUEs. T gs (indicated by the temperature of the highest loss modulus) was lower in IMN–PU than in BD–PU and ISB–PU. Again, this reflects the better microphase separation in IMN–PU. The thermal properties determined by DSC and DMA are summarized in Table 2 . Figure 4 shows the stress–strain behaviors of the PUs. The tensile properties of PUEs determined by UTM are summarized in Table 3 . The Young’s moduli of ISB–PU and IMN–PU were higher than that of BD–PU, owing to the rigid structure of the anhydrohexitols [ 45 ]. Interestingly, ISB–PU and BD–PU showed strain hardening (i.e., high tensile strength), whereas IMN–PU did not due to strong hydrogen bonds. According to Torkelson and coworkers, strain hardening in PUs with high microphase separation is hindered by the sharp boundary between the microphases [ 46 ]. Efficient strain hardening of ISB–PU is attributable to the interdiffusion of the interfacial properties of the microphase-separated domains. 2.3. Morphologies of PUEs The microstructure and phase separation of the PUEs were confirmed by tapping-mode AFM and SAXS. Figure 5 displays AFM images of the PUEs. The darker and brighter regions correspond to the soft and hard segment domains, respectively [ 47 , 48 ]. In BD–PU ( Figure 5 a), the bright regions of sphere or cylinder like shapes are isolated and surrounded by the dark regions. This apparent phase difference evidences the contrast between the hard and soft segment domains. In ISB–PU and IMN-PU, the bright portions are smaller than in BD–PU slightly, but the striking differences between PUEs in this study were not observed. Figure 6 shows the SAXS profiles of the PUEs investigated in this study. In the SAXS profile, the scattering intensity indicates crystallinity, which was related to the microphase separation of PUEs [ 45 , 49 , 50 ]. The scattering intensities of IMN–PU and ISB-PU were higher that of BD–PU, which contributed to the chemical structure of anhydrohexitol. The interdomain distances of PUEs were calculated by Bragg’s equation, d = 2π/q, using the value of q at the peak. The scattering widths of IMN–PU and ISB–PU were bigger than that of BD–PU, which indicate that the sizes of hard domain in IMN–PU and ISB–PU were smaller than that of BD–PU. On the other hand, the calculated average interdomain distances of BD–PU, IMD–PU and ISB–PU were 20 nm, 12 nm and 12 nm, respectively, indicating better microphase separation of BD–PU. These results showed that strong hard segment bonding of IMN–PU despite the small size of domain. This is consistent with the previous results of DSC, DMA and AFM. 2.4. Reversibility of PUEs ISB–PU and IMN–PU contains urethane bonds from anhydrohexitol and MDI (an aromatic isocyanate). As is well known, urethane bonds formed by aromatic hydroxyl groups and aromatic isocyanates undergo reversible reactions at elevated temperatures [ 51 ]. Such reversibility is used to prepare blocked isocyanates. Anhydrohexitol possesses a hydroxyl group with a cycloaliphatic ring structure similar to the aromatic hydroxyl group, and a very bulky structure. For this reason, we were interested in the reversible features of anhydrohexitol-based urethanes for the self-healing PUEs. The reversible properties of the carbamates in ISB–PU and IMN–PU were investigated by FT-IR at elevated temperatures. The FT-IR spectra of ISB–PU and IMN–PU exhibited an –N=C=O peak at elevated temperatures ( Figure S2 ), confirming the reversible feature of these PUs. In contrast, the –N=C=O peak was absent in the BD–PU spectrum at the same temperatures. Figure 7 plots the relative absorbances of the isocyanates and the carbamate C–N group in the three PUs as a function of temperature. The peak intensities of ISB–PU and IMN–PU in Figure 7 A increased with temperature, whereas those of BD–PU were almost constant. The significant decline in the carbamate C–N peaks of ISB–PU and IMN–PU in Figure 7 B was attributable to the reverse reaction of urethane. Moreover, as the reversible reaction progressed, the increase in the isocyanate peak and the corresponding decrease in the carbamate peak were greater in IMN–PU than in ISB–PU. The urethane group formed by the hydroxyl group at the endo-position of anhydrohexitol is destabilized by the steric hindrance caused by intramolecular hydrogen bonding. These unstable urethanes favor reversible reactions as shown in Scheme 2 . To check whether volatile anhydrohexitols are liberated by the reversible properties of carbamates in the PUs, we carried out an isothermal TGA at 180 °C on very thin PUE films. In isothermal runs, the weight loss is attributable to the volatilizations of ISB and IMN dissociated by reversible reaction of urethanes. These results are due to the isothermal condition exceed the boiling points of both ISB and IMN (150 °C and 160 °C, respectively). Figure 8 plots the weight losses at 180 °C in BD–PU, ISB–PU, and IMN–PU over time. After 120 min, the weight of BD–PU was only marginally reduced, whereas those of ISB–PU and IMN–PU had noticeably declined. We thus postulated that the carbamates of ISB–PU and IMN–PU chemically reverse at lower temperature than those of BD–PU, conventional PU comparatively. TGA data of PUEs are given in Figure S3 . The initial weight loss of ISB-PU and IMN-PU was observed at lower temperatures than that of BD-PU due to the reversible features anhydrohexitol-based PU as discussed above. 2.5. Reprocessability of ISB-Based PU The reprocessing tests demonstrate whether ISB-based PU exhibits self-healing properties. When the ISB–PU film is damaged, the fractured pieces can be reprocessed into integrated film via the thermoreversible behavior of the PU. In the reprocessing analysis, the ISB–PU and BD–PU test pieces were placed between two metal plates and hot pressed at 150 °C for 10 min. Photo images of fractured BD–PU and ISB–PU films before and after heating are shown in Figure 9 . After remolding, the ISB–PU film was reintegrated through reversible covalent bonding and physical melting. In contrast, the BD–PU test pieces remained nonintegrated and adhered only through partial melting, retaining a fractured appearance. IMN–PU also did not recover its shape after hot pressing. IMN-PU exhibited high reversibility than ISB–PU, but the flow temperature of IMN-PU was increased by the improved microphase separation."
} | 4,380 |
23976882 | PMC3747994 | pmc | 5,341 | {
"abstract": "Artificial human gut microbial communities implanted into germ-free mice provide insights into how species-level responses to changes in diet give rise to community-level structural and functional reconfiguration and how types of bacteria prioritize use of available nutrients in vivo .",
"introduction": "Introduction A growing body of evidence indicates that the tens of trillions of microbial cells that inhabit our gastrointestinal tracts extend our biological capabilities in important ways. Microbial enzymes process many compounds that would otherwise pass through our intestines unaltered [1] , and cases of particular nutrient substrates favoring the growth of particular taxa are being reported [2] – [5] . Changes in diet are therefore expected to lead to changes in the composition and function of the microbiota [6] – [10] . However, our understanding of diet–microbiota interactions at a mechanistic level is still in its infancy. The absence of a complete catalog of the microbial strains and associated genome sequences that comprise a given microbiota complicates efforts to describe how particular dietary substrates influence individual taxa, how taxa cooperate/compete to utilize nutrients, and how these many interactions in aggregate lead to emergent host phenotypes. Gnotobiotic mice colonized with defined consortia of sequenced human gut microbes, on the other hand, provide an in vivo model of the microbiota in which the identity of all taxa and genes comprising the system are known. Within these assemblages, expressed mRNAs and proteins can be attributed to their genome, gene, and species of origin, and findings of interest can be pursued in follow-up in vitro or in vivo experiments. These systems also afford an opportunity to tightly control experimental variables to a degree not possible in human studies and have proven useful in studying microbial invasion, microbe–microbe interactions, and the metabolic roles of key ecological guilds [11] – [15] . Studies aiming to better understand community-level assembly, resilience, and adaptation are therefore likely to benefit from a focus on such defined systems. However, the limited taxonomic and functional representation within artificial communities of modest complexity requires that caution be exercised when extrapolating results to more complex, naturally occurring gut communities (see Prospectus ). Culture-independent surveys of the healthy adult gut microbiota consistently conclude that it is composed primarily of members of two bacterial phyla, the Bacteroidetes and Firmicutes [16] – [21] . The dominance of these two bacterial phyla suggests that their representatives in the human gut are exquisitely adapted to its dynamic conditions, which include a constantly evolving nutrient environment. Members of the genus Bacteroides are known to be adept at utilizing both plant- and host-derived polysaccharides [22] . Comparisons of available Bacteroides genomes with those from other gut species indicate that the former are enriched in genes involved in the acquisition and metabolism of various glycans, including glycoside hydrolases (GHs) and polysaccharide lyases (PLs), as well as linked environmental sensors that control their expression (e.g., hybrid two-component systems, extracytoplasmic function (ECF) sigma factors and anti-sigma factors). Many of these genes are organized into polysaccharide utilization loci (PULs) that are distributed throughout the genome [23] , [24] . Recent studies have focused on better understanding the evolution, specificity, and regulation of PULs in the genomes of species like Bacteroides thetaiotaomicron and Bacteroides ovatus \n [25] , [26] . Little is known, however, about the metabolic strategies adopted by multiple competing species in more complex communities, how dietary changes lead to reconfigurations in community structure through changes in individual species, or whether dietary context influences which genes dominant species rely on to remain competitive with other microbes, including those genes that are components of PULs. Here, we adopt a multifaceted approach to study an artificial community in gnotobiotic mice fed changing diets in order to better understand (i) the process by which such a community reconfigures itself structurally in response to changes in host diet; (ii) how aggregate community function, as judged by the metatranscriptome and metaproteome, is impacted when host diet is altered; (iii) how the metabolic strategies of its individual component microbes change, if at all, when the nutrient milieu is dramatically altered, with an emphasis on one prominent but understudied member of the human gut Bacteroides ; and (iv) whether a microbe's metabolic versatility/flexibility correlates with competitive advantage in an assemblage containing related and unrelated species.",
"discussion": "Results and Discussion Sequencing the Bacteroides cellulosilyticus WH2 Genome Though at least eight complete and 68 draft genomes of Bacteroides spp. are currently available [27] , there are numerous examples of distinct clades within this genus where little genomic information exists. To further explore the genome space of one such clade, we obtained a human fecal isolate whose four 16S rRNA gene sequences indicate a close relationship to Bacteroides cellulosilyticus ( Figure S1A,B ). The genome of this isolate, which we have designated B. cellulosilyticus WH2, was sequenced deeply, yielding a high-quality draft assembly (23 contigs with an N50 value of 798,728 bp; total length of all contigs in the assembly, 7.1 Mb; Table S1 ). Annotation of its 5,244 predicted protein-coding genes using the carbohydrate active enzyme (CAZy) database [28] revealed an extraordinary complement of 503 CAZymes comprising 373 GHs, 23 PLs, 28 carbohydrate esterases (CEs), and 84 glycosyltransferases (GTs) (see Table S2 for all annotated genes in the B. cellulosilyticus WH2 genome predicted to have relevance to carbohydrate metabolism). One distinguishing feature of gut Bacteroides genomes is the substantial number of CAZymes they encode relative to those of other intestinal bacteria [29] . The B. cellulosilyticus WH2 CAZome is enriched in a number of GH families even when compared with prominent representatives of the gut Bacteroidetes ( Figure S2A ). When we expanded this comparison to include all 86 Bacteroidetes in the CAZy database, we found that the B. cellulosilyticus WH2 genome had the greatest number of genes for 19 different GH families, as well as genes from two GH families that had not previously been observed within a Bacteroidetes genome ( Figure S2B ). Altogether, B. cellulosilyticus WH2 has more GH genes at its disposal than any other Bacteroidetes species analyzed to date. In Bacteroides spp., CAZymes are often located within PULs [30] . At a minimum, a typical PUL harbors a pair of genes with significant homology to the susC and susD genes of the starch utilization system (Sus) in B. thetaiotaomicron \n [30] – [32] . Other genes encoding enzymes capable of liberating oligo- and monosaccharides from a larger polysaccharide are also frequently present. The susC - and susD -like genes of these loci encode the proteins that comprise the main outer membrane binding and transport apparatus and thus represent key elements of these systems. A search of the B. cellulosilyticus WH2 genome for genes with strong homology to the susC - and susD -like genes in B. thetaiotaomicron VPI-5482 revealed an unprecedented number of susC / D pairs (a total of 118). Studies of other prominent Bacteroides spp. have found that the evolutionary expansion of these genes has played an important role in endowing the Bacteroides with the ability to degrade a wide range of host- and plant-derived polysaccharides [25] , [33] . Analysis of deeply sampled adult human gut microbiota datasets indicates that B. cellulosilyticus strains are common, colonizing approximately 77% of 124 adult Europeans characterized in one study [18] and 62% of 139 individuals living in the United States examined in another survey [20] . We hypothesized that the apparent success of B. cellulosilyticus in the gut is derived in part from its substantial arsenal of genes involved in carbohydrate utilization. Measuring Changes in the Structural Configuration of a 12-Member Model Microbiota in Response to a Dietary Perturbation To test the fitness of B. cellulosilyticus WH2 in relation to other prominent gut symbionts, and the importance of diet on its fitness, we carried out an experiment in gnotobiotic mice (experiment 1, “E 1 ,” Figure S3 ). Two groups of 10–12-wk-old male germ-free C57BL/6J animals were moved to individual cages within gnotobiotic isolators ( n = 7 animals/group). At day zero, each animal was colonized by oral gavage with an artificial community comprising 12 human gut bacterial species ( Figure 1A , Table S3 ). Each species chosen for inclusion in this microbial assemblage met four criteria: (i) it was a member of one of three bacterial phyla routinely found in the human gut (i.e., Bacteroidetes, Firmicutes, or Actinobacteria), (ii) it was identified as a prominent member of the human gut microbiota in previous culture-independent surveys, (iii) it could be grown in the laboratory, and (iv) its genome had been sequenced to at least a high-quality draft level. Species were also selected for their functional attributes (as judged by their annotated gene content) in an effort to create an artificial community that was somewhat representative of a more complex human microbiota. For example, although more than half of the species in the assemblage were Bacteroidetes predicted to excel at the breakdown of polysaccharides, several were also prominent inhabitants of the human gut that are thought to have limited carbohydrate utilization capabilities (e.g., Firmicutes from Clostridium cluster XIVa). Some attributes for the 12 strains included in the artificial community are provided in Table S4 . 10.1371/journal.pbio.1001637.g001 Figure 1 COPRO-Seq analysis of the structure of a 12-member artificial human gut microbial community as a function of diet and time. (A) The 12 bacterial species comprising the artificial community. (B) Principal coordinates analysis (PCoA) was applied to relative abundance data generated by COPRO-Seq from two experiments (E 1 , E 2 ), each spanning 6 wk. Following colonization (day 0), mice were switched between two different diets at 2-wk intervals as described in Figure S3 . COPRO-Seq data from E 1 and E 2 were ordinated in the same multidimensional space. For clarity, only data from E 2 are shown here (for the E 1 PCoA plot, see Figure S5A ). Red/blue, feces; pink/cyan, cecal contents. (C) Proportional abundance data from E 1 illustrating the impact of diet on fecal levels of a diet-sensitive strain with higher representation on HF/HS chow ( B. caccae ), a diet-sensitive strain with higher representation on LF/HPP chow ( B. ovatus ), a diet-insensitive strain with no obvious diet preference ( B. thetaiotaomicron ), and a diet-sensitive strain with a preference for the LF/HPP diet that also achieves a high level of representation on the HF/HS diet ( B. cellulosilyticus WH2). Mean values ± SEM are shown. Plots illustrating changes in abundance over time for all species in both experiments are provided in Figure S4C . For 2 wk, each treatment group was fed a standard low-fat/high-plant polysaccharide (LF/HPP) mouse chow, or a “Western”-like diet where calories are largely derived from fat, starch, and simple sugars (high-fat/high-sugar (HF/HS)) [12] . Over the course of 6 wk, diets were changed twice at 2-wk intervals, such that each group began and ended on the same diet, with an intervening 2-wk period during which the other diet was administered ( Figure S3 ). Using fecal DNA as a proxy for microbial biomass, the plant polysaccharide-rich LF/HPP diet supported 2- to 3-fold more total bacterial growth (primary productivity) despite its lower caloric density (3.7 kcal/g versus 4.5 kcal/g for the HF/HS diet; Figure S4A ). The HF/HS diet contains carbohydrates that are easily metabolized and absorbed in the proximal intestine (sucrose, corn starch, and maltodextrin), with cellulose being the one exception (4% of the diet by weight versus 46.3% for the other carbohydrate sources). Thus, in mice fed the HF/HS diet, diet-derived simple sugars are likely to be rare in the distal gut where the vast majority of gut microbes reside; this may provide an advantage to those bacteria capable of utilizing other carbon sources (e.g., proteins/oligopeptides, host glycans). In mice fed the LF/HPP diet, on the other hand, plant polysaccharides that are indigestible by the host should provide a plentiful source of energy for saccharolytic members of the artificial community. To evaluate the impact of each initial diet and subsequent diet switch on the structural configuration of the artificial community, we performed shotgun sequencing (community profiling by sequencing; COPRO-Seq) [11] of DNA isolated from fecal samples collected throughout the course of the experiment, as well as cecal contents collected at sacrifice. The relative abundances of the species in each sample (defined by the number of sequencing reads that could be unambiguously assigned to each microbial genome after adjusting for genome uniqueness) were subjected to ordination by principal coordinates analysis (PCoA) ( Figure S5A ). As expected, diet was found to be the predominant explanatory variable for observed variance (see separation along principal coordinate 1, “PC1,” which accounts for 52% of variance). The overall structure of the artificial community achieved quasi-equilibrium before the midpoint of the first diet phase, as evidenced by the lack of any significant movement along PC1 after day five. A structural reconfiguration also took place over the course of ∼5 d following transition to the second diet phase. Notably, the two treatment groups underwent a near-perfect inversion in their positions along PC1 after the first diet switch; the artificial community in animals switched from a LF/HPP to HF/HS diet took on a structure like that which arose by the end of the first diet phase in animals consuming the HF/HS diet, and vice versa. The second diet switch from phase 2 to 3 resulted in a similar movement along PC1 in the opposite direction, indicating a reversion of the artificial community's configuration to its originally assembled structure in each treatment group. These results, in addition to demonstrating the significant impact of these two diets on the structure of this 12-member artificial human gut community, also suggest that an assemblage of this size is capable of demonstrating resilience in the face of substantial diet perturbations. The assembly process and observed diet-induced reconfigurations also proved to be highly reproducible as evidenced by COPRO-Seq results from a replication of E 1 (experiment 2, “E 2 ”). In this follow-up experiment, fecal samples were collected more frequently than in E 1 , providing a dataset with improved temporal resolution. Ordination of E 2 COPRO-Seq data by PCoA showed that (i) for each treatment group in E 2 , the artificial community assembles in a manner similar to its counterpart in E 1 ; (ii) structural reconfigurations in response to diet occur with the same timing as in E 1 ; and (iii) the quasi-equilibria achieved during each diet phase are highly similar between experiments for each treatment group (compare Figures 1B and S5A ). As in E 1 , cecal data for each E 2 treatment group overlap with their corresponding fecal samples, and DNA yields from E 2 fecal samples vary substantially as a function of host diet ( Figure S4B ). COPRO-Seq provides precise measurements of the proportional abundance of each member species present in the artificial community. Data collected in both E 1 and E 2 ( Table S5 ) revealed significant differences between members in terms of the maximum abundance levels they achieved, the rates at which their abundance levels were impacted by diet shifts, and the degree to which each species demonstrated a preference for one diet over another ( Figure S4C ). Changes in each species' abundance over time replicated well across animals in each treatment group, suggesting the assembly process and diet-induced reconfigurations occur in an orderly, rules-based fashion and with minimal stochasticity in this artificial community. A species' relative abundance immediately after colonization (i.e., 24 h after gavage/day 1) was, in general, a poor predictor of its abundance at the end of the first diet phase (i.e., day 13) (E 1 \n R \n 2 = 0.23; E 2 \n R \n 2 = 0.27), suggesting that early dominance of the founder population was not strongly tied to relative success in the assembly process. In mice initially fed a HF/HS diet, four Bacteroides spp. ( Bacteroides caccae , B. cellulosilyticus WH2, B. thetaiotaomicron , and Bacteroides vulgatus ) each achieved a relative abundance of ≥10% by the end of the first diet phase (day 13 postgavage), with B. caccae attaining the highest levels (37.1±4.9% and 34.2±5.5%; group mean ± SD in E 1 and E 2 , respectively). In animals fed the plant polysaccharide-rich LF/HPP chow during the first diet phase, B. cellulosilyticus WH2 was dominant, achieving levels of 37.1±2.0% (E 1 ) and 41.6±3.9% (E 2 ) by day 13. B. thetaiotaomicron and B. vulgatus also attained relative abundances of >10%. Changes in diet often resulted in rapid, dramatic changes in a species' proportional representation. Because the dynamic range of abundance values observed when comparing multiple species was substantial (lowest, Dorea longicatena (<0.003%); highest, B. caccae (55.0%)), comparing diet responses on a common scale using raw abundance values was challenging. To represent these changes in a way that scaled absolute increases/decreases in relative abundance to the range observed for each strain, we also normalized each species' representation within the artificial community at each time-point to the maximum proportional abundance each microbe achieved across all time-points within each mouse. Plotting the resulting measure of abundance (percentage of maximum achieved; PoMA) over time demonstrates which microbes are strongly responsive to diet (experience significant swings in PoMA value following a diet switch) and which are relatively diet-insensitive (experience only modest or no significant change in PoMA value following a diet switch). Heatmap visualization of E 1 PoMA values ( Figure S5B ) indicated that those microbes with a preference for a particular diet in one animal treatment group also tended to demonstrate the same diet preference in the other. Likewise, diet insensitivity was also consistent across treatment groups; diet-insensitive microbes were insensitive regardless of the order in which diets were introduced. Of the diet-sensitive taxa, those showing the most striking responses were B. caccae and B. ovatus , which strongly preferred the “Western”-like HF/HS diet and the polysaccharide-rich LF/HPP diet, respectively ( Figures 1C and S4C ). Among the diet-insensitive taxa, B. thetaiotaomicron showed the most stability in its representation ( Figures 1C and S4C ), consistent with its reputation as a versatile forager. Paradoxically, B. cellulosilyticus WH2 was both diet-sensitive and highly fit on its less-preferred diet; although this strain clearly achieved higher levels of representation in animals fed the LF/HPP diet, it also maintained strong levels of representation in animals fed the HF/HS diet ( Figures 1C and S4C ). When taking into account the abundance data for all 12 artificial community members, proportional representation at the end of the first diet phase (i.e., day 13) was a good predictor of representation at the end of the third diet phase (i.e., day 42) (E 1 \n R \n 2 = 0.77; E 2 \n R \n 2 = 0.84), suggesting that the intervening dietary perturbation had little effect on the ultimate outcomes for most species within this assemblage. However, one very low-abundance strain ( D. longicatena ) achieved significantly different maximum percentage abundances across the two treatment groups in each experiment, suggesting that steady-state levels of this strain may have been impacted by diet history. In mice initially fed the LF/HPP diet, D. longicatena was found to persist throughout the experiment at low levels on both diet regimens. In mice initially fed the HF/HS diet, D. longicatena dropped below the limit of detection before the end of the first diet phase, was undetectable by the end of the second diet phase, and remained undetectable throughout the rest of the time course. This interesting example raises the possibility that for some species, irreversible hysteresis effects may play a significant role in determining the likelihood that they will persist within a gut over long periods of time. The Cecal Metatranscriptome Sampled at the Time of Sacrifice These diet-induced reconfigurations in the structure of the artificial community led us to examine the degree to which its members were modifying their metabolic strategies. To establish an initial baseline static view of expression data for each microbe on each diet, we developed a custom GeneChip whose probe sets were designed to target 46,851 of the 48,023 known or predicted protein-coding genes within our artificial human gut microbiome (see \n Materials and Methods \n ). Total RNA was collected from the cecal contents of each animal in E 1 at the time of sacrifice and hybridized to this GeneChip. The total number of genes whose expression was detectable on each diet was remarkably similar (14,929 and 14,594 detected in the LF/HPP→HF/HS→LF/HPP and HF/HS→LF/HPP→HF/HS treatment groups, respectively). A total of 11,373 genes (24.3%) were expressed on both diets ( Figure S6A ), while 2,003 (4.3%) were differentially expressed to a statistically significant degree, including 161 (6.1%) of the 2,640 genes in the microbiome encoding proteins with CAZy-recognized domains. Figure S6B illustrates the fraction of the community-level CAZome and several species-level CAZomes expressed on each diet (see Table S6 for a comprehensive list of all genes, organized by species and fold-change in expression, whose cecal expression was detectable on each diet and all genes whose expression was significantly different when comparing data from each treatment group). Among taxa demonstrating obvious diet preferences (as judged by relative abundance data), B. caccae and B. cellulosilyticus WH2 provided examples of CAZy-level responses to diet change that were different in several respects. Our observations regarding the carbohydrate utilization capabilities and preferences of B. caccae are summarized in Text S1 . However, our ability to evaluate shifts in B. caccae 's metabolic strategy in the gut was limited by its very low abundance in animals fed LF/HPP chow (i.e., our mRNA and subsequent protein assays were often not sensitive enough to exhaustively sample B. caccae 's metatranscriptome and metaproteome). In contrast, the abundance of B. cellulosilyticus WH2, which favored the LF/HPP diet, remained high enough on both diets to allow for a comprehensive analysis of its expressed genes and proteins. This advantage, along with the exceptional carbohydrate utilization machinery encoded within the genome of this organism, encouraged us to focus on further dissecting the responses of B. cellulosilyticus WH2 to diet changes. Detailed inspection of the expressed B. cellulosilyticus WH2 CAZome (503 CAZymes in total) provided an initial view of this microbe's sophisticated carbohydrate utilization strategy. A comparison of the top decile of expressed CAZymes on each diet disclosed many shared elements between the two lists, spanning many different CAZy families, with just over half of the 50 most expressed enzymes on the plant polysaccharide-rich LF/HPP chow also occurring in the list of most highly expressed enzymes on the sucrose-, corn starch-, and maltodextrin-rich HF/HS diet ( Figure 2A ). Twenty-five of the 50 most expressed CAZymes on the LF/HPP diet were significantly up-regulated compared to the HF/HS diet; of these, seven were members of the GH43 family ( Figure 2B ). The GH43 family consists of enzymes with activities required for the breakdown of plant-derived polysaccharides such as hemicellulose and pectin. Inspection of the enzyme commission (EC) annotations for the most up-regulated GH43 genes shows that they encode xylan 1,4-β-xylosidases (EC 3.2.1.37), arabinan endo-1,5-α-L-arabinosidases (EC 3.2.1.99), and α-L-arabinofuranosidases (EC 3.2.1.55). The GH10 family, which is currently comprised exclusively of endo-xylanases (EC 3.2.1.8, EC 3.2.1.32), was also well represented among this set of 25 genes, with four of the seven putative GH10 genes in the B. cellulosilyticus WH2 genome making the list. Strikingly, of the 45 predicted genes with putative GH43 domains in the B. cellulosilyticus WH2 genome, none were up-regulated on the “Western”-style HF/HS diet. 10.1371/journal.pbio.1001637.g002 Figure 2 \n B. cellulosilyticus WH2 CAZyme expression in mice fed different diets. (A) Overview of the 50 most highly expressed B. cellulosilyticus WH2 CAZymes (GHs, GTs, PLs, and CEs) for samples from each diet treatment group. List position denotes the rank order of gene expression for each treatment group, with higher expression levels situated at the top of each list. Genes common to both lists are identified by a connecting line, with the slope of the line indicating the degree to which a CAZyme's prioritized expression is increased/decreased from one diet to the other. CAZy families in bold, colored letters highlight those list entries found to be significantly up-regulated relative to the alternative diet (i.e., a CAZyme with a bold green family designation was up-regulated on the LF/HPP diet; a bold orange family name implies a gene was up-regulated significantly on the HF/HS diet). Statistically significant fold-changes between diets are denoted in the “F.C.” column (nonsignificant fold-changes are omitted for clarity). (B) Breakdown by CAZy family of the top 10% most expressed CAZymes on each diet whose expression was also found to be significantly higher on one diet than the other. Note that for each diet, the family with the greatest number of up-regulated genes was also exclusively up-regulated on that diet (LF/HPP, GH43; HF/HS, GH13). In total, 25 genes representative of 27 families and 12 genes representative of 13 families are shown for the LF/HPP and HF/HS diets, respectively. The most highly expressed B. cellulosilyticus WH2 CAZyme on the plant polysaccharide-rich chow (which was also highly-expressed on the HF/HS chow) was BWH2_1228, a putative α-galactosidase from the GH36 family. These enzymes, which are not expressed by humans in the stomach or intestine, cleave terminal galactose residues from the nonreducing ends of raffinose family oligosaccharides (RFOs, including raffinose, stachyose, and verbascose), galacto(gluco)mannans, galactolipids, and glycoproteins. RFOs, which are well represented in cereal grains consumed by humans, are expected to be abundant in the LF/HPP diet given its ingredients (e.g., soybean meal), but potential substrates in the HF/HS diet are less obvious, possibly implicating a host glycolipid or glycoprotein target. Surface glycans in the intestinal epithelium of rodents are decorated with terminal fucose residues [34] as well as terminal sialic acid and sulfate [35] . Hydrolysis of the α-2 linkage connecting terminal fucose residues to the galactose-rich extended core is thought to be catalyzed in large part by GH95 and GH29 enzymes [36] . The B. cellulosilyticus WH2 genome is replete with putative GH95 and GH29 genes (total of 12 and 9, respectively), but only a few ( BWH2_1350 / 2142 / 3154 / 3818 ) were expressed in vivo on at least one diet, and their expression was low relative to many other CAZymes (see Table S6 ). Cleavage of terminal sialic acids present in host mucins by bacteria is usually carried out by GH33 family enzymes. B. cellulosilyticus WH2 has two GH33 genes that are expressed on either one diet ( BWH2_3822 , HF/HS) or both diets ( BWH2_4650 ), but neither is highly expressed relative to other B. cellulosilyticus WH2 CAZymes. Therefore, utilization of host glycans by B. cellulosilyticus WH2, if it occurs, likely requires partnerships with other members of the artificial community that express GH29/95/33 enzymes (see Table S6 for a list of members that express these enzymes in a diet-independent and/or diet-specific fashion). Among the 50 most highly expressed B. cellulosilyticus WH2 CAZymes, 12 were significantly up-regulated on the HF/HS diet compared to the LF/HPP diet, with members of family GH13 being most prevalent. While the enzymatic activities and substrate specificities of GH13 family members are varied, most relate to the hydrolysis of substrates comprising chains of glucose subunits, including amylose (one of the two components of starch) and maltodextrin, both prominent ingredients in the HF/HS diet. GeneChip-based profiling of the E 1 cecal communities provided a snapshot of the metatranscriptome on the final day of the final diet phase in each treatment group. The analysis of B. cellulosilyticus WH2 CAZyme expression suggested that this strain achieves a “generalist” lifestyle not by relying on substrates that are present at all times (e.g., host mucins), but rather by modifying its resource utilization strategy to effectively compete with other microbes for diet-derived polysaccharides that are not metabolized by the host. Community-Level Analysis of Diet-Induced Changes in Microbial Gene Expression To develop a more complete understanding of the dynamic changes that occur in gene expression over time and throughout the artificial community following diet perturbations, we performed microbial RNA-Seq analyses using feces obtained at select time-points from mice in the LF/HPP→HF/HS→LF/HPP treatment group of E 2 ( Figure S3 ). We began with a “top-down” analysis in which every RNA-Seq read count from every gene in the artificial microbiome was binned based on the functional annotation of the gene from which it was derived, regardless of its species of origin. In this case, the functional annotation used as the binning variable was the predicted EC number for a gene's encoded protein product. Expecting that some changes might occur rapidly, while others might require days or weeks, we searched for significant differences between the terminal time-points of the first two diet phases (i.e., points at which the model human gut microbiota had been allowed 13 d to acclimate to each diet). The 157 significant changes we identified were subjected to hierarchical clustering by EC number to determine which functional responses occurred with similar kinetics. The results revealed that in contrast to the rapid, diet-induced structural reconfigurations observed in this artificial community, community-level changes in microbial gene expression occurred with highly variable timing that differed from function to function. These changes were dominated by EC numbers associated with enzymatic reactions relevant to carbohydrate and amino acid metabolism (see Table S7 for a summary of all significant changes observed, including aggregate expression values for each functional bin (EC number) at each time-point). Significant responses could be divided into one of three groups: “rapid” responses were those where the representation of EC numbers in the transcriptome increased/decreased dramatically within 1–2 d of a diet switch; “gradual” responses were those where the representation of EC numbers changed notably, but slowly, between the two diet transition points; and “delayed” responses were those where significant change did not occur until the end of a diet phase ( Figure 3 , Table S7 ). EC numbers associated with reactions important in carbohydrate metabolism and transport were distributed across all three of these response types for each of the two diets. Nearly all genes encoding proteins with EC numbers related to amino acid metabolism that were significantly up-regulated on HF/HS chow binned into the “rapid” or “gradual” groups, suggesting this diet put immediate pressure on the artificial microbial community to increase its repertoire of expressed amino acid biosynthesis and degradation genes. Genes with assigned EC numbers involved in amino acid metabolism that were significantly up-regulated on the other, polysaccharide-rich, LF/HPP diet were spread more evenly across these three response types ( Figure 3 ). 10.1371/journal.pbio.1001637.g003 Figure 3 Top-down analysis of fecal microbiome RNA expression in mice receiving oscillating diets. The fecal metatranscriptomes of four animals in the LF/HPP→HF/HS→LF/HPP treatment group of E 2 were analyzed using microbial RNA-Seq at seven time-points to evaluate the temporal progression of changes in expressed microbial community functions triggered by a change in diet. After aligning reads to genes in the defined artificial human gut microbiome, raw counts were collapsed by the functional annotation (EC number) of the gene from which the corresponding reads originated. Total counts for each EC number in each sample were normalized, and any EC numbers demonstrating a statistically significant difference in their representation in the metatranscriptome between the final days of the first two diet phases were identified using a model based on the negative binomial distribution [57] . Normalized expression values for 157 significant EC numbers (out of 1,021 total tested) were log-transformed, mean-centered, and subjected to hierarchical clustering, followed by heatmap visualization. “Rapid” responses are those where expression increased/decreased dramatically within 1–2 d of a diet switch. “Gradual” responses are those where expression changed notably, but slowly, between the two diet transition points. “Delayed” responses are those where significant expression changes did not occur until the end of a diet phase. EC numbers specifying enzymatic reactions relevant to carbohydrate metabolism and/or transport are denoted by purple markers, while those with relevance to amino acid metabolism are indicated using orange markers. A full breakdown of all significant responses over time and the outputs of the statistical tests performed are provided in Table S7 . Careful inspection of our top-down analysis results and a complementary “bottom-up” analysis in which normalization was performed at the level of individual species, rather than at the community level, allowed us to identify other important responses that would have gone undetected were it not for the fact that we were dealing with a defined assemblage of microbes where all of the genes in component members' genomes were known. For example, an assessment of the representation of EC 3.2.1.8 (endo-1,4-β-xylanase) within the metatranscriptome before and after the first diet switch (LF/HPP→HF/HS) initially suggested that this activity was reduced to a statistically significant degree as a result of the first diet perturbation (day 13 versus day 27; Mann–Whitney U test, p = 0.03; Figure S7A ). Aggregation by species of all sequencing read counts assignable to mRNAs encoding proteins with this EC number revealed that over 99% of the contributions to this functional bin originated from B. cellulosilyticus WH2 (note the similarity in a comparison of Figure S7A and Figure S7B ), implying that the community-level response and the response of this Bacteroides species were virtually one and the same. A tally of all sequencing reads assignable to B. cellulosilyticus WH2 at each time-point disclosed that although this strain maintains high proportional representation in the artificial community throughout each diet oscillation period (range, 10.3–42.5% and 11.6–43.3% for E 1 and E 2 , respectively), its contribution to the metatranscriptome is substantially decreased during the HF/HS diet phase ( Figure S7C ). This dramatic reduction in the extent to which B. cellulosilyticus WH2 contributes to the metatranscriptome in HF/HS-fed mice “masks” the significant up-regulation of EC 3.2.1.8 that occurs within the B. cellulosilyticus WH2 transcriptome following the first diet shift (day 13 versus day 27; Mann–Whitney U test, p = 0.03; Figure S7D ). A further breakdown of endo-1,4-β-xylanase up-regulation in B. cellulosilyticus WH2 when mice are switched to the HF/HS diet reveals that most of this response is driven by two genes, BWH2_4068 and BWH2_4072 ( Figure S7E ). Our realization that we were unable to correctly infer the direction of one of the most significant diet-induced gene expression changes in the second most abundant strain in the artificial community when inspecting functional responses at the community level provides a strong argument for expanding the use of microbial assemblages comprised exclusively of sequenced species in studies of the gut microbiota. This should allow the contributions of individual species to community activity to be evaluated in a rigorous way that is not possible with microbial communities of unknown or poorly defined gene composition. High-Resolution Profiling of the Cecal Metaproteome Sampled at the Time of Sacrifice In principle, protein measurements can provide a more direct readout of expressed community functions than an RNA-level analysis, and thus a deeper understanding of community members' interactions with one another and with their habitat [37] , [38] . For these reasons and others, much work has been dedicated to applying shotgun proteomics techniques to microbial ecosystems in various environments [39] , [40] . Though these efforts have provided illustrations of significant methodological advances, they have been limited by the complexity of the metaproteomes studied and by the difficulties this complexity creates when attempting to assign peptide identities uniquely to proteins of specific taxa. Recognizing that a metaproteomics analysis of our artificial community would not be subject to such uncertainty given its fully defined microbiome and thus fully defined theoretical proteome, we subjected cecal samples from two mice from each diet treatment group in E 1 ( n = 4 total) to high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS; see \n Materials and Methods \n ). We had three goals: (i) to evaluate how our ability to assign peptide-spectrum matches (PSMs) to particular proteins within a theoretical metaproteome is affected by the presence of close homologs within the same species and within other, closely related species; (ii) to test the limits of our ability to characterize protein expression across different species given the substantial dynamic range we documented in microbial species abundance; and (iii) to collect semiquantitative peptide/protein data that might validate and enrich our understanding of functional responses identified at the mRNA level, particularly with respect to the niche (profession) of CAZyme-rich B. cellulosilyticus WH2. Given the evolutionary relatedness of the strains involved, we expected that some fraction of observed PSMs from each sample would be of ambiguous origin due to nonunique peptides shared between species' proteomes. To assess which species might be most affected by this phenomenon when characterizing the metaproteome on different diets, we catalogued each strain's theoretical peptidome using an in silico tryptic digest. This simulated digest took into account both the potential for missed trypic cleavages and the peptide mass range that could be detected using our methods. The results ( Figure S8A , Table S8 ) demonstrated that for an artificial community of modest complexity, the proportion of peptides within each strain's theoretical peptidome that are “unique” (i.e., assignable to a single protein within the theoretical metaproteome) varies substantially from species to species, even among those that are closely related. We found the lone representative of the Actinobacteria in the artificial community, Collinsella aerofaciens , to have the highest proportion of unique peptides (94.2%), while B. caccae had the lowest (63.0%). Interestingly, there was not a strong correlation between the fraction of a species' peptides that were unique and the total number of unique peptides that species contributed to the theoretical peptidome. For example, C. aerofaciens (2,367 predicted protein-coding genes) contributed only 81,894 (1.5%) unique peptides, the lowest of any artificial community member evaluated, despite having a proteome composed of mostly unique peptides. On the other hand, B. cellulosilyticus WH2 (5,244 predicted protein-coding genes) contributed 241,473 (4.5%) unique peptides, the highest of any member despite a high fraction of nonunique peptides (18.4%) within its theoretical peptidome. The evolutionary relatedness of the Bacteroides components of the artificial community appeared to negatively affect our ability to assign their peptides to specific proteins; their six theoretical peptidomes had the six lowest uniqueness levels. However, their greater number of proteins and peptides relative to the Firmicutes and Actinobacteria more than compensated for this deficiency; over 60% of unique peptides within the unique theoretical metaproteome were contributed by the Bacteroides . We also found that the proportion of PSMs uniquely assignable to a single protein within the metaproteome varied significantly by function, suggesting that some classes of proteins can be traced back to specific microbes more readily than others. For example, when considering all theoretical peptides that could be derived from the proteome of a particular bacterial species, those from proteins with roles in categories with high expected levels of functional conservation (e.g., translation and nucleotide metabolism) were on average deemed unique more often than those from proteins with roles in functions we might expect to be less conserved (e.g., glycan biosynthesis and metabolism) (see Table S8 for a summary of how peptide uniqueness varied across different KEGG categories and pathways, and across different species in the experiment). However, even in KEGG categories and pathways with high expected levels of functional conservation, the vast majority of peptides were found to be unique when a particular species was not closely related to other members of the artificial community. Next, we determined the average number of proteins that could be experimentally identified in our samples for each microbial species within each treatment group in E 1 . The results ( Figure S8B , Table S9 ) illustrate two important conclusions. First, although equal concentrations of total protein were evaluated for each sample, slightly less than twice as many total microbial proteins were identified in samples from the LF/HPP-fed mice as those from mice fed the HF/HS diet (4,659 versus 2,777, respectively). While there are a number of possible explanations, both this finding and the higher number of mouse proteins detected in samples from HF/HS-fed animals are consistent with the results of our fecal DNA analysis, which indicated that the HF/HS diet supports lower levels of gut microbial biomass than the LF/HPP diet ( Figure S4A,B ). Second, a breakdown of all detected microbial proteins by species of origin ( Figure S8B ) revealed that the degree to which we could inspect protein expression for a given species was dictated largely by its relative abundance and the diet to which it was exposed. Our ability to detect many of B. cellulosilyticus WH2's expressed transcripts and proteins in samples from both diet treatment groups allowed us to determine how well RNA and protein data for an abundant, active member of the artificial community might correlate. These data also allowed us to evaluate whether or not the types of genes considered might influence the degree of correlation between these two datasets. We first performed a spectral count-based correlation analysis on the diet-induced, log-transformed, average fold-differences in expression for all B. cellulosilyticus WH2 genes that were detectable at both the RNA and protein level for both diets. The results revealed a moderate degree of linear correlation between RNA and protein observations ( Figure S8C , black plot; r = 0.53). However, subsequent division of these genes into functionally related subsets, which were each subjected to their own correlation analysis, revealed striking differences in the degree to which RNA-level and protein-level expression changes agreed with one another. For example, diet-induced changes in mRNA expression for genes involved in translation showed virtually no correlation with changes measured at the protein level ( Figure S8C , red plot; r = 0.03). Correlations for other categories of B. cellulosilyticus WH2 genes, such as those involved in energy metabolism ( Figure S8C , green plot; r = 0.36) and amino acid metabolism ( Figure S8C , orange plot; r = 0.48), were also poorer than the correlation for the complete set of detectable genes. In contrast, the correlation for the 110 genes with predicted involvement in carbohydrate metabolism was quite strong ( Figure S8C , blue plot; r = 0.69), and was in fact the best correlation identified for any functional category of genes considered. The significant range of correlations observed in different categories of genes suggests that the degree to which RNA-based analyses provide an accurate picture of microbial adaptation to environmental perturbation may be strongly impacted by the functional classification of the genes involved. Additionally, these data further emphasize the need for enhanced dynamic range metaproteome measurements and better bioinformatic methods to assign/bin unique and nonunique peptides so that deeper and more thorough surveys of the microbial protein landscape can be performed and evaluated alongside more robust transcriptional datasets. Identifying Two Diet-Inducible, Xylanase-Containing PULs Whose Genetic Disruption Results in Diet-Specific Loss of Fitness Several of the most highly expressed and diet-sensitive B. cellulosilyticus WH2 genes in this study fell within two putative PULs. One PUL ( BWH2_4044–55 ) contains 12 ORFs that include a dual susC / D cassette, three putative xylanases assigned to CAZy families GH8 and GH10, a putative multifunctional acetyl xylan esterase/α-L-fucosidase, and a putative hybrid two-component system regulator ( Figure 4A ). Gene expression within this PUL was markedly higher in mice consuming the plant polysaccharide-rich LF/HPP diet at both the mRNA and protein level. Our mRNA-level analysis disclosed that BWH2_4047 was the most highly expressed B. cellulosilyticus WH2 susD homolog on this diet. Likewise, BWH2_4046 / 4 , the two susC -like genes within this PUL, were the 2nd and 4th most highly expressed B. cellulosilyticus WH2 susC -like genes in LF/HPP-fed animals, and exhibited expression level reductions of 99.5% and 93% in animals consuming the HF/HS diet. The same LF/HPP diet bias was observed for other genes within this PUL ( Figures 2A and 4B ) but not for neighboring genes. The same trends were obvious and amplified when we quantified protein expression ( Figure 4C ). In mice fed LF/HPP chow, only three B. cellulosilyticus WH2 SusC-like proteins had higher protein levels than BWH2_4044/6, and only two SusD-like proteins had higher levels than BWH2_4045/7. Strikingly, we were unable to detect a single peptide from 9 of the 12 proteins in this PUL in samples obtained from mice fed the HF/HS diet, emphasizing the strong diet specificity of this locus. 10.1371/journal.pbio.1001637.g004 Figure 4 Two xylanase-containing B. cellulosilyticus WH2 PULs demonstrating strong diet-specific expression patterns in vivo . (A) The PUL spanning BWH2_4044 – 55 includes a four-gene cassette comprising two consecutive susC / D pairs, multiple genes encoding GHs and CEs, and a gene encoding a putative hybrid two-component system (HTCS) presumed to play a role in the regulation of this locus. GH10 enzymes are endo-xylanases (most often endo-β-1,4-xylanases), while some GH5 and GH8 enzymes are also known to have endo- or exo-xylanase activity. CE6 enzymes are acetyl xylan esterases, as are some members of the CE1 family. A second PUL spanning BWH2_4072 – 6 contains a susC / D cassette, an endo-xylanase with dual GH10 modules as well as dual carbohydrate (xylan) binding modules (CBM22), a hypothetical protein of unknown function, and a putative HTCS. (B) Heatmap visualization of GeneChip expression data for BWH2_4044 – 55 and BWH2_4072 – 6 showing marked up-regulation of these putative PULs when mice are fed either a plant polysaccharide-rich LF/HPP diet or a diet high in fat and simple sugar (HF/HS), respectively. Data are from cecal contents harvested from mice at the endpoint of experiment E 1 . (C) Mass spectrometry-based quantitation of the abundance of all cecal proteins from the BWH2_4044 – 55 and BWH2_4072 – 6 PULs that were detectable in the same material used for GeneChip quantitation in panel (B). Bars represent results (mean ± SEM) from two technical runs per sample. For each MS run, the spectral counts for each protein were normalized against the total number of B. cellulosilyticus WH2 spectra acquired. (D) Comparison of in vivo PUL gene expression as measured by RNA-Seq (top) and the degree to which disruption of each gene within each PUL by a transposon impacts the fitness of B. cellulosilyticus WH2 on each diet, as measured by insertion sequencing (INSeq, bottom). For the lower plots, fitness measurements were calculated by dividing a mutant's representation (normalized sequencing counts) within the fecal output population by its representation within an input population that was introduced into germ-free animals via a single oral gavage along with other members of the artificial community. For cases in which no instances of a particular mutant could be measured in the fecal output (resulting in a fitness calculation denominator of zero), data are plotted as “<0.01” and are drawn without error bars. A second PUL in the B. cellulosilyticus WH2 genome composed of a susC / D -like pair ( BWH2_4074 / 5 ), a putative hybrid two-component system regulator ( BWH2_4076 ), and a xylanase (GH10) with dual carbohydrate binding module domains (CBM22) ( BWH2_4072 ) ( Figure 4A ) demonstrated a strong but opposite diet bias, in this case exhibiting significantly higher expression in animals consuming the HF/HS “Western”-like diet. Our mRNA-level analysis showed that this xylanase was the second most highly expressed B. cellulosilyticus WH2 CAZyme in animals consuming this diet ( Figure 2A ). As with the previously described PUL, shotgun metaproteomics validated the transcriptional analysis ( Figure 4B,C ); with the exception of the gene encoding the PUL's presumed transcriptional regulator ( BWH2_4076 ), diet specificity was substantial, with protein-level fold changes ranging from 10–33 across the locus ( Table S10 ). Recent work by Cann and co-workers has done much to advance our understanding of the regulation and metabolic role of xylan utilization system gene clusters in xylanolytic members of the Bacteroidetes, particularly within the genus Prevotella \n [41] . The “core” gene cluster of the prototypical xylan utilization system they described consists of two tandem repeats of susC / susD homologs ( xusA / B / C / D ), a downstream hypothetical gene ( xusE ) and a GH10 endoxylanase ( xyn10C ). The 12-gene PUL identified in our study ( BWH2_4044 – 55 ) appears to contain the only instance of this core gene cluster within the B. cellulosilyticus WH2 genome, suggesting that this PUL, induced during consumption of a plant polysaccharide-rich diet, is likely to be the primary xylan utilization system within this organism. A recent study characterizing the carbohydrate utilization capabilities of B. ovatus ATCC 8483 also identified two PULs involved in xylan utilization ( BACOVA_04385 – 94 , BACOVA_03417 – 50 ) whose gene configurations differ from those described in Prevotella spp. [25] . Interestingly, the five proteins encoded by the smaller xylanase-containing PUL described above ( BWH2_4072 – 6 ) are homologous to the products of the last five genes in BACOVA_4385 – 94 (i.e., BACOVA_4390 – 4 ). The order of these five genes in these two loci is also identical. The similarities and differences observed when comparing the putative xylan utilization systems encoded within the genomes of different Bacteroidetes illustrate how its members may have evolved differentiated strategies for utilizing hemicelluloses like xylan. Having established that expression of BWH2_4044 – 55 and BWH2_4072 – 6 is strongly dictated by diet, we next sought to determine if these PULs are required by B. cellulosilyticus WH2 for fitness in vivo . A follow-up study was performed in which mice were fed either a LF/HPP or HF/HS diet after being colonized with an artificial community similar to the one used in E 1 and E 2 (see \n Materials and Methods \n ). The wild-type B. cellulosilyticus WH2 strain used in our previous experiments was replaced with a transposon mutant library consisting of over 90,000 distinct transposon insertion mutants in 91.5% of all predicted ORFs (average of 13.9 distinct insertion mutants per ORF). The library was constructed using methods similar to those reported by Goodman et al. ( [42] ; see \n Materials and Methods \n ) so that the relative proportion of each insertion mutant in both the input (orally gavaged) and output (fecal) populations could be determined using insertion sequencing (INSeq). The INSeq results revealed clear, diet-specific losses of fitness when components of these loci were disrupted ( Figure 4D ). Additionally, as observed in E 1 and E 2 , expression of each PUL was strongly biased by diet, with genes BWH2_4072 – 5 demonstrating up-regulation on the HF/HS diet and BWH2_4044 – 55 on the LF/HPP diet. The extent to which a gene's disruption impacted the fitness of B. cellulosilyticus WH2 on one diet or the other correlated well with whether or not that gene was highly expressed on a given diet. For example, four of the five most highly expressed genes in the BWH2_4044 – 55 locus were the four genes shown to be most crucial for fitness on the LF/HPP diet. Of these four genes, three were susC or susD homologs (the fourth was the putative endo-1,4-β-xylanase thought to constitute the last element of the xylan utilization system core). Though the fitness cost of disrupting genes within BWH2_4044 – 55 varied from gene to gene, disruption of any one component of the BWH2_4072 – 6 PUL had serious consequences for B. cellulosilyticus WH2 in animals fed the HF/HS diet. This could suggest that while disruption of some components of the BWH2_4044 – 55 locus can be rescued by similar or redundant functions elsewhere in the genome, the same is not true for BWH2_4072 – 5 . Notably, disruption of BWH2_4076 , which is predicted to encode a hybrid two-component regulatory system, had negative consequences on either diet tested, indicating that regulation of this locus is crucial even when the PUL is not actively expressed. While many genes outside of these two PULs were also found to be important for the in vivo fitness of B. cellulosilyticus WH2, those within these PULs were among the most essential to diet-specific fitness, suggesting that these loci are central to the metabolic lifestyle of B. cellulosilyticus WH2 in the gut. Characterizing the Carbohydrate Utilization Capabilities of B. cellulosilyticus WH2 and B. caccae \n The results described in the preceding section indicate that B. cellulosilyticus WH2 prioritizes xylan as a nutrient source in the gut and that it tightly regulates the expression of its xylan utilization machinery. Moreover, the extraordinary number of putative CAZymes and PULs within the B. cellulosilyticus WH2 genome suggests that it is capable of growing on carbohydrates with diverse structures and varying degrees of polymerization. To characterize its carbohydrate utilization capabilities, we defined its growth in minimal medium (MM) supplemented with one of 46 different carbohydrates [25] . Three independent growths, each consisting of two technical replications, yielded a total of six growth curves for each substrate. Of the 46 substrates tested, B. cellulosilyticus WH2 grew on 39 ( Table S11 ); they encompassed numerous pectins (6 of 6), hemicelluloses/β-glucans (8 of 8), starches/fructans/α-glucans (6 of 6), and simple sugars (14 of 15), as well as host-derived glycans (4 of 7) and one cellooligosaccharide (cellobiose). The seven substrates that did not support growth included three esoteric carbohydrates (carrageenan, porphyran, and alginic acid), the simple sugar N-acetylneuraminic acid, two host glyans (keratan sulfate and mucin O-glycans), and fungal cell wall-derived α-mannan. B. cellulosilyticus WH2 clearly grew more robustly on some carbohydrates than others. Excluding simple sugars, fastest growth was achieved on dextran (0.099±0.048 OD 600 units/h), laminarin (0.095±0.014), pectic galactan (0.088±0.018), pullulan (0.088±0.026), and amylopectin (0.085±0.003). Although one study has reported that the type strain of B. cellulosilyticus degrades cellulose [43] , the WH2 strain failed to demonstrate any growth on MM plus cellulose (specifically, Solka-Floc 200 FCC from International Fiber Corp.) after 5 d. Maximum cell density was achieved with amylopectin (1.17±0.02 OD 600 units), dextran (1.12±0.20), cellobiose (1.09±0.08), laminarin (1.08±0.08), and xyloglucan (0.99±0.04). Total B. cellulosilyticus WH2 growth (i.e., maximum cell density achieved) on host-derived glycans was typically very poor, with only two substrates achieving total growth above 0.2 OD 600 units (chondroitin sulfate, 0.50±0.04; glycogen, 0.99±0.02). The disparity between total growth on plant polysaccharides versus host-derived glycans, including O-glycans that are prevalent in host mucin, indicates a preference for diet-derived saccharides, consistent with our in vivo mRNA and protein expression data. We also determined how the growth rate of B. cellulosilyticus WH2 on these substrates compared to the growth rates for other prominent gut Bacteroides spp. After subjecting B. caccae to the same phenotypic characterization as B. cellulosilyticus WH2, we combined our measurements for these two strains with previously published measurements for B. thetaiotaomicron and B. ovatus \n [25] . The results underscored the competitive growth advantage B. cellulosilyticus WH2 likely enjoys when foraging for polysaccharides in the intestinal lumen. For example, of the eight hemicelluloses and β-glucans tested in our carbohydrate panel, B. cellulosilyticus WH2 grew fastest on six while B. ovatus grew fastest on two ( Table S11 ). B. caccae and B. thetaiotaomicron , on the other hand, failed to grow on any of these substrates. Across all the carbohydrates for which data are available for all four species, B. cellulosilyticus WH2 grew fastest on the greatest number of polysaccharides (11 of 26) and tied with B. caccae for the greatest number of monosaccharides (6 of 15). B. thetaiotaomicron and B. caccae did, however, outperform the other two Bacteroides tested with respect to utilization of host glycans in vitro , demonstrating superior growth rates on four of five substrates tested ( Table S11 ). \n B. cellulosilyticus WH2's rapid growth to high densities on xylan, arabinoxylan, and xyloglucan, as well as xylose, arabinose, and galactose, is noteworthy given our prediction that two of its most tightly regulated, highly expressed PULs appear to be involved in the utilization of xylan, arabinoxylan, or some closely related polysaccharide. To identify specific mono- and/or polysaccharides capable of triggering the activation of these two PULs, as well as the 111 other putative PULs within the B. cellulosilyticus WH2 genome, we used RNA-Seq to characterize its transcriptional profile at mid-log phase in MM ( Table S12 ) plus one of 16 simple sugars or one of 15 complex sugars ( Table S13 ) (see \n Materials and Methods \n ; n = 2–3 cultures/substrate; 5.2–14.0 million raw Illumina HiSeq reads generated for each of the 90 transcriptomes). After mapping each read to the B. cellulosilyticus WH2 reference gene set, counts were normalized using DESeq to allow for direct comparisons across samples and conditions. Hierarchical clustering of the normalized dataset resulted in a well-ordered dendrogram in which samples clustered almost perfectly by the carbohydrate on which B. cellulosilyticus WH2 was grown ( Figure 5A ). The consistency of this clustering illustrates that (i) technical replicates within each condition exhibit strong correlations with one another, suggesting any differences between cultures in a treatment group (e.g., small differences in density or growth phase) had at best minor effects on aggregate gene expression, and (ii) growth on different carbohydrates results in distinct, substrate-specific gene expression signals capable of driving highly discriminatory differences between treatment groups. The application of rigorous bootstrapping to our hierarchical clustering results also revealed several cases of higher level clusters in which strong confidence was achieved. These dendrogram nodes (illustrated as white circles) indicate sets of growth conditions that yield gene expression patterns more like each other than like the patterns observed for other substrates. Two notable examples were xylan/arabinoxylan (which are structurally related and share the same xylan backbone) and L-fucose/L-rhamnose (which are known to be metabolized via parallel pathways in E. coli \n [44] ). 10.1371/journal.pbio.1001637.g005 Figure 5 \n In vitro microbial RNA-Seq profiling of B. cellulosilyticus WH2 during growth on different carbohydrates. (A) Hierarchical clustering of the gene expression profiles of 90 cultures grown in minimal medium supplemented with one of 31 simple or complex sugars ( n = 2–3 replicates per condition). Circles at dendrogram branch points identify clusters with strong bootstrapping support (>95%; 10,000 repetitions). Solid circles denote clusters comprising only replicates from a single treatment group/carbohydrate, while open circles denote higher level clusters comprising samples from multiple treatment groups. Colored rectangles indicate the type of carbohydrate on which the samples within each cluster were grown. (B) Unclustered heatmap representation of fold-changes in gene expression relative to growth on minimal medium plus glucose (MM-Glc) for 60 of the 236 paired susC - and susD -like genes identified within the B. cellulosilyticus WH2 genome (for a full list of all paired and unpaired susC and susD homologs, see Table S2 ). Data shown are limited to those genes whose expression on at least one of the 31 carbohydrates tested demonstrated a >100-fold increase relative to growth on MM-Glc for at least one of the replicates within the treatment group. Yellow boxes denote areas of the map where both genes in a susC / D pair were up-regulated >100-fold for at least two of the replicates in a treatment group and where the average up-regulation for each gene in the pair was >100-fold across all replicates of the treatment group. Two sets of columns to the right of the heatmap indicate PULs that were detectably expressed at the mRNA level (left set of columns) and/or protein level (right set of columns) in experiment 1 (E 1 ). Red and black circles indicate that both genes in a susC / D pair were consistently expressed on a particular diet, as determined by GeneChip analysis of cecal RNA (≥5 of 7 animals assayed) or LC-MS/MS analysis of cecal protein (2 of 2 animals assayed). In both cases, a red circle denotes significantly higher expression on one diet compared to the other. Importantly, these findings suggested that by considering in vitro profiling data alongside in vivo expression data from the artificial community, it might be possible to identify the particular carbohydrates to which B. cellulosilyticus WH2 is exposed and responding within its gut environment. To explore this concept further, we compared expression of each gene in each condition to its expression on our control treatment, MM plus glucose (MM-Glc). The results revealed a dynamic PUL activation network in which some PULs were activated by a single substrate, some were activated by multiple substrates, and some were transcriptionally silent across all conditions tested. Of the 118 putative susC / D pairs in B. cellulosilyticus WH2 that we have used as markers of PULs, 30 were dramatically activated on one or more of the substrates tested; in these cases, both the susC - and susD -like genes in the cassette were up-regulated an average of >100-fold relative to MM-Glc across all technical replicates ( Figure 5B ). At least one susC / D activation signature was identified for every one of the 17 oligosaccharides and polysaccharides and for six of the 13 monosaccharides tested ( Table S14 ). The lack of carbohydrate-specific PUL activation events for some monosaccharides (fructose, galactose, glucuronic acid, sucrose, and xylose) was expected, given that these loci are primarily dedicated to polysaccharide acquisition. Further inspection of gene expression outside of PULs disclosed that B. cellulosilyticus WH2 prioritizes use of its non-PUL-associated carbohydrate machinery, such as putative phosphotransferase system (PTS) components and monosaccharide permeases, when grown on these monosaccharides ( Table S14 ). Several carbohydrates activated the expression of multiple PULs. Growth on water-soluble xylan and wheat arabinoxylan produced significant up-regulation of five susC / D -like pairs ( BWH2_0865 / 6 , 0867 / 8 , 4044 / 5 , 4046 / 7 , and 4074 / 5 ). No other substrate tested activated as many loci within the genome, again hinting at the importance of xylan and arabinoxylan to this strain's metabolic strategy in vivo . Cecal expression data from E 1 showed that 15 of these activated PULs were expressed in vivo on one or both of the diets tested (see circles to the right of the heatmap in Figure 5B ). In mice fed the polysaccharide-rich LF/HPP chow, B. cellulosilyticus WH2 up-regulates three susC / D pairs ( BWH2_2717 / 8 , 4044 / 5 , 4046 / 7 ) whose expression is activated in vitro by arabinan and xylan/arabinoxylan. The three most significantly up-regulated susC / D pairs ( BWH2_1736 / 7 , 2514 / 5 , 4074 / 5 ) in mice fed the HF/HS diet rich in sugar, corn starch, and maltodextrin are activated in vitro by amylopectin, ribose, and xylan/arabinoxylan, respectively. All three PULs identified as being up-regulated at the RNA level in LF/HPP-fed mice were also found to be up-regulated at the protein level ( Figure 5B ). Two of the three PULs up-regulated at the mRNA level in HF/HS-fed mice were up-regulated at the protein level as well. The presence of an amylopectin-activated PUL among these two loci is noteworthy, given the significant amount of starch present in the HF/HS diet. The up-regulation of four other PULs in HF/HS-fed animals was only evident in our LC-MS/MS data, reinforcing the notion that protein data both complement and supplement mRNA data when profiling microbes of interest. Two of the five susC / D pairs activated by xylan/arabinoxylan form the four-gene cassette in the previously discussed PUL comprising BWH2_4044 – 55 that is activated in mice fed the plant polysaccharide-rich chow (see Figure 4A ). Another one of the five is the susC / D pair found in the PUL comprising BWH2_4072 – 6 that is activated in mice fed the HF/HS “Western”-like chow (see Figure 4A ). Thus, we have identified a pair of putative PULs in close proximity to one another on the B. cellulosilyticus WH2 genome that encode CAZymes with similar predicted functions, are subject to near-identical levels of specific activation by the same two polysaccharides (i.e., xylan, arabinoxylan) in vitro , but are discordantly regulated in vivo in a diet-specific manner. The highly expressed nature of these PULs in the diet environment where they are active, their shared emphasis on xylan/arabinoxylan utilization, and their tight regulation indicate that they are likely to be important for the in vivo success of this organism in the two nutrient environments tested. However, the reasons for their discordant regulation are unclear. One possibility is that in addition to being activated by xylan/arabinoxylan and related polysaccharides, these loci are also subject to repression by other substrates present in the lumen of the gut, and this repression is sufficient to block activation. Alternatively, the specific activators of each PUL may be molecular moieties shared by both xylan and arabinoxylan that do not co-occur in the lumenal environment when mice are fed the diets tested in this study. Prospectus Elucidating generalizable “rules” for how microbiota operate under different environmental conditions is a substantial challenge. As our appreciation for the importance of the gut microbiota in human health and well-being grows, so too does our need to develop such rules using tractable experimental models of the gut ecosystem that allow us to move back and forth between in vivo and ex vivo analyses, using one to inform the other. Here, we have demonstrated the extent to which high-resolution DNA-, mRNA-, and protein-level analyses can be applied (and integrated) to study an artificial community of sequenced human gut microbes colonizing gnotobiotic mice. Our efforts have focused on characterizing community-level and species-level adaptation to dietary change over time and “leveraging” results obtained from in vitro assessments of individual species' responses to a panel of purified carbohydrates to deduce glycan exposures and consumption strategies in vivo . This experimental paradigm could be applied to any number of questions related to microbe–microbe, environment–microbe, and host–microbe interactions, including, for example, the metabolic fate of particular nutrients of interest (metabolic flux experiments), microbial succession, and biotransformations of xenobiotics. Studying artificial human gut microbial communities in gnotobiotic mice also allows us to evaluate the technical limitations of current molecular approaches for characterizing native communities. For example, the structure of an artificial community can be evaluated over time at low cost using short read shotgun DNA sequencing data mapped to all microbial genomes within the community (COPRO-Seq). This allows for a much greater depth of sequencing coverage (i.e., more sensitivity) and much less ambiguity in the assignment of reads to particular taxa than traditional 16S rRNA gene-based sequencing. Short read cDNA sequences transcribed from total microbial community RNA can also often be assigned to the exact species and gene from which they were derived, and the same is also often true for peptides derived from particular bacterial proteins. However, substantial dynamic range in species/transcript/protein abundance within any microbiota, defined or otherwise, imposes limits on our ability to characterize the least abundant elements of these systems. The effort to obtain a more complete understanding of the operations and behaviors of minor components of the microbiota is an area deserving of significant attention, given known examples of low-abundance taxa that play key roles within their larger communities and in host physiology [2] , [45] . Developing such an understanding requires methods and assays that are collectively capable of assessing the structure and function of a microbiota at multiple levels of resolution. The need for high sensitivity and specificity in these approaches will become increasingly relevant as we transition towards experiments involving defined communities of even greater complexity, including bacterial culture collections prepared from the fecal microbiota of humans [46] . We anticipate that the study of sequenced culture collections transplanted to gnotobiotic mice will be instrumental in determining the degree to which physiologic or pathologic host phenotypes can be ascribed to the microbiota as well as specific constituent taxa. The recent development of a low-error 16S ribosomal RNA amplicon sequencing method (LEA-Seq) and the application of this method to the fecal microbiota of 37 healthy adults followed for up to 5 years indicated that individuals in this cohort contained 195±48 bacterial strains representing 101±27 species [47] . Furthermore, stability follows a power-law function, suggesting that once acquired, most gut strains in a person are present for decades. New advances in the culturing of fastidious gut microbes may one day allow us to capture most (or all) of the taxonomic and functional diversity present within an individual's fecal microbiota as a clonally arrayed, sequenced culture collection, providing a perfectly representative and defined experimental model of their gut community. In the meantime, first-generation artificial communities of modest complexity such as the one described here offer a way of studying many questions related to the microbiota. However, the limited complexity and composition of our 12-species artificial community, and the way in which it was assembled in germ-free mice, make it an imperfect model of more complex human microbiota. Native microbial communities, for example, are subject to the influence of variables that are notably absent from this system, such as intraspecies genetic variability and exogenous microbial inputs. There are also taxa (e.g., Proteobacteria, Bifidobacteria) and microbial guilds (e.g., butyrate producers) typical of human gut communities that are absent from our defined assemblage that could be used to augment this system in order to improve our understanding of how their presence/absence influences a microbiota's response to diet and a spectrum of other variables of interest. These future attempts to systematically increase complexity should reveal what trends, patterns, and trajectories observed in artificial assemblages such as the one reported here map or do not map onto natural communities. Finally, one of the greatest advantages of studying defined assemblages in mice is that they afford us the ability to interrogate the biology of key bacterial species in a focused manner. The artificial community we used in our experiments included B. cellulosilyticus WH2, a species that warrants further study as a model gut symbiont given its exceptional carbohydrate utilization capabilities, its apparent fitness advantage over many other previously characterized gut symbionts, and its genetic tractability. This genetic tractability should facilitate future experiments in which transposon mutant libraries are screened in vivo as one component of a larger artificial community in order to identify this strain's most important fitness determinants under a wide variety of dietary conditions. Identifying the genetic elements that allow B. cellulosilyticus to persist at the relatively high levels observed, regardless of diet, should provide microbiologists and synthetic biologists with new “standard biological parts” that will aid them in developing the next generation of prebiotics, probiotics, and synbiotics."
} | 19,106 |
38577582 | PMC10993476 | pmc | 5,343 | {
"abstract": "Abstract Nitrate leaching from agricultural soils is increasingly found in groundwater, a primary source of drinking water worldwide. This nitrate influx can potentially stimulate the biological oxidation of iron in anoxic groundwater reservoirs. Nitrate-dependent iron-oxidizing (NDFO) bacteria have been extensively studied in laboratory settings, yet their ecophysiology in natural environments remains largely unknown. To this end, we established a pilot-scale filter on nitrate-rich groundwater to elucidate the structure and metabolism of nitrate-reducing iron-oxidizing microbiomes under oligotrophic conditions mimicking natural groundwaters. The enriched community stoichiometrically removed iron and nitrate consistently with the NDFO metabolism. Genome-resolved metagenomics revealed the underlying metabolic network between the dominant iron-dependent denitrifying autotrophs and the less abundant organoheterotrophs. The most abundant genome belonged to a new Candidate order, named Siderophiliales. This new species, “ Candidatus Siderophilus nitratireducens,” carries genes central genes to iron oxidation (cytochrome c cyc2 ), carbon fixation ( rbc ), and for the sole periplasmic nitrate reductase ( nap ). Using thermodynamics, we demonstrate that iron oxidation coupled to nap based dissimilatory reduction of nitrate to nitrite is energetically favorable under realistic Fe 3+ /Fe 2+ and NO 3 − /NO 2 − concentration ratios. Ultimately, by bridging the gap between laboratory investigations and nitrate real-world conditions, this study provides insights into the intricate interplay between nitrate and iron in groundwater ecosystems, and expands our understanding of NDFOs taxonomic diversity and ecological role.",
"introduction": "Introduction Globally, approximately one-third of the nitrogen applied to agricultural soils is lost via leaching to the surrounding waterbodies [ 1 ]. This has led to elevated nitrate (NO 3 − ) levels in anoxic groundwaters, a primary source of drinking water worldwide [ 2 ]. Owing to population growth and agriculture intensification, nitrate concentrations in subsurface waters are expected to continue increasing [ 3 ]. Besides its direct impact on human health [ 4 ], nitrate can significantly alter the biogeochemistry of groundwater reservoirs [ 5 ]. Nitrate promotes the oxidation of sulfide and in particular of iron (Fe) – the most prevalent groundwater contaminant – leading to the formation of oxides with high adsorption capacity and the emission of greenhouse gases [ 6 ]. Despite these implications, the consequences of nitrate–iron interactions on ecosystems and drinking water production systems remain largely unexplored. A detailed understanding of the underlying principles is paramount for anticipating and mitigating current and future challenges, as well as for exploring potential synergies and biotechnological opportunities. Nitrate-dependent iron-oxidizing (NDFO) bacteria, also referred to as nitrate-reducing iron-oxidizers (NRFO) [ 7 , 8 ], couple the anoxic reduction of nitrate to the oxidation of Fe 2+ (eq. 1 ). Since their discovery in 1996 by Straub et al . [ 9 ], NDFO microorganisms have been the focus of extensive research both in pure and mixed cultures (reviewed in [ 10 ]), and several complete genomes are already publicly available [ 11 , 12 ]. The metabolic versatility of NDFO bacteria spans from lithoautotrophic to mixotrophic growth [ 10 ], to partial denitrification using nitric oxide (NO) [ 13 ] and nitrous oxide (N 2 O) [ 11 ] as terminal electron acceptors. At the same time, due to the inherently low energetic yield of iron oxidation, NDFO bacteria live close to the thermodynamic edge [ 14 ]. Their fitness is highly dependent on environmental factors such as substrate and product availability, pH and temperature [ 15 ]. Chemical reactions – such as the quasi-instantaneous precipitation of the biologically formed Fe 3+ − can play a pivotal role by modulating iron and nitrogen concentrations [ 16 ]. However, our current understanding is largely based on laboratory settings, and does not necessarily reflect the complexity of natural and engineered ecosystems where several (a)biotic reactions occur simultaneously at temperatures significantly lower than tested to date [ 17 ]. \n (1) \n \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n\\begin{equation*} 10\\mathrm{F}{\\mathrm{e}}^{2+}+2\\mathrm{N}{\\mathrm{O}}_3^{-}+24\\ {\\mathrm{H}}_2\\mathrm{O}\\to 10\\mathrm{F}\\mathrm{e}{\\left(\\mathrm{OH}\\right)}_3+{\\mathrm{N}}_2+18{\\mathrm{H}}^{+} \\end{equation*}\\end{document} \n To address these knowledge gaps, we established a pilot-scale filter on anoxic groundwater containing both Fe 2+ and NO 3 − . The emulated groundwater conditions allowed for the establishment of a microbial enrichment that simultaneously removed Fe 2+ and NO 3 − . In depth metagenomic analysis of the steady-state community revealed a new order-level NDFO lineage, deepening our understanding of their taxonomic diversity and ecological roles. Overall, our study bridges the gap between laboratory studies and real-world conditions, and offers a nuanced view on the intricate interplay between nitrate and iron in groundwater ecosystems.",
"discussion": "Discussion We established a pilot-scale filter on nitrate-rich anoxic groundwater to elucidate the structure and metabolism of nitrate-reducing iron-oxidizing microbial communities under oligotrophic conditions mimicking natural groundwater. The enriched microbial community stoichiometrically removed iron and nitrate during more than 4 months, and was dominated by a genome belonging to a new Candidate order, named Siderophiliales. The genome of this new species, “ Ca . Siderophilus nitratireducens,” encoded the genes for iron oxidation (cytochrome c cyc2 ) and, within the denitrification pathway, the periplasmic nitrate reductase ( nap ). The absence of other denitrification genes suggests a short catabolic path, which may offer a kinetic advantage in terms of higher iron oxidation rates [ 29 ] especially under nitrogen limiting conditions [ 30 ]. In contrast, the majority of NDFO genomes reported so far encode the membrane-bound nitrate reductase ( nar ) along with other downstream denitrification genes [ 11 , 31–34 ]. Nar actively translocates protons, whereas nap conserves energy only indirectly by accepting electrons from the quinol pool on the periplasmic side of the membrane, effectively consuming cytoplasmic protons [ 35 ]. Recently, novel Zetaproteobacteria genomes possessing nap have been recovered from a complex community, yet they also possessed at least another energy conserving nitrogen oxide [ 5 , 36 ]. The presence of a cbb 3 -type cytochrome c oxidase suggests that “ Ca . Siderophilus nitratireducens” may also be capable of oxygen respiration. This is consistent with the fact that all reported genomes of anaerobic iron-oxidizing bacteria contain oxygen reductases [ 31 , 34 , 37 ], including the well-studied KS [ 13 ] and AG [ 38 ] cultures. However, to the best of our knowledge, NDFO growth under (micro)aerophilic conditions has not been reported to date [ 11 ]. Although the sporadic detection of traces of oxygen (<3 μM) in our filter does not allow to fully exclude aerobic activity, and in the absence of cultured representatives to confirm it, we posit that nap -driven iron oxidation was the primary catabolic route of “ Ca . Siderophilus nitratireducens” under the in-situ restricted availability of alternative substrates. Furthermore, “ Ca . Siderophilus nitratireducens” was also identified as a putative autotroph, adding the additional challenge of energy and electrons needs for anabolic CO 2 fixation to the growth on iron, a weak electron-donor at standard conditions [ 15 ]. Thermodynamic evaluations indicate that nap -dependent iron oxidation can sustain growth at realistic Fe 3+ /Fe 2+ and NO 3 − /NO 2 − concentrations ratios. To this end, the quasi-instantaneous precipitation of the biologically formed Fe 3+ as iron oxides under circum-neutral pH plays a central role as thermodynamic driving force [ 39 ]. The specific mechanisms by which this thermodynamic potential is harnessed for carbon fixation remain to be fully elucidated. The subsequent reduction of the produced nitrite resulted from the concerted activity of putative autotrophic iron-oxidizers and organoheterotrophs. Within the microbial community, the second most abundant genome, MAG.26 (f_ Gallionellaceaea ), featured the genetic potential for iron oxidation and most denitrification steps, with the exception of nitrous oxide reductase ( nor ). MAG.26 also possessed the cytochrome c oxidase cbb 3 -type cco NOP for aerobic respiration. Interestingly, this genome contained genes for CO 2 fixation, a trait mirrored in all other less abundant genomes with the ability to oxidize iron. This suggests that autotrophy may represent an essential trait for NDFOs in anoxic groundwaters where the dissolved organic carbon is largely non-biodegradable [ 40 ]. The three second most abundant genomes, MAG.18 (f_ Anaeromyxobacteraceae ), MAG.19 (g_ Devosia ) and MAG.10 (f_ Chitinophagaceae ) were found to lack the genes for iron oxidation and CO 2 assimilation. Yet, these genomes encompassed the full denitrification pathway starting from nitrite. Besides the likely occurrence of chemical reduction of NO to N 2 O [ 41 ], we speculate that these heterotrophs complemented the NDFOs for at least the reduction of NO using autotrophically fixed organic carbon as substrate. A similar metabolic network was also recently observed in mesophilic NDFO communities [ 13 ]. Overall, the measured iron and nitrate consumption yield of 7.1 mol Fe 2+ : mol NO 3 − is consistent with the expected 5.6, i.e. considering the theoretical catabolism (eq. 1 ) and the recently estimated 12% of electrons used for growth [ 7 ], but higher than the experimentally observed range of 3.8–4.7 [ 9 , 31 , 42 ]. At first, we hypothesized nitrate ammonification to be the reason for the slight excess in iron oxidation, yet none of the putative iron-oxidizing genomes encoded for the common nrf nor for the newly reported octaheme complex [ 43 ]. Also, the oxygen sporadically detected in the influent was always below the quantification limit of 3 μM, a conservative concentration that alone would explain less than 15% of the total iron consumption via chemical oxidation. As no Fe 3+ was detected in the reactor effluent, all iron necessarily accumulated inside the reactor either as Fe 2+ or Fe 3+ precipitates. X-ray diffraction and Mössbauer spectroscopy identified over 94% of the Fe in solids as amorphous ferrihydrite, an Fe 3+ oxide, with <6% of the solids attributed to magnetite, an Fe 2+ –Fe 3+ oxide typically formed under anaerobic conditions ( Figure S4 , Table S2 and SI 5 ). Consequently, the Fe 2+ unaccounted for was likely continuously adsorbed onto the newly-formed Fe 3+ oxides, a well-studied phenomenon [ 44 ], yet the extent to which this occurred was not investigated. In conclusion, pending experimental validation, we surmise that NDFO microorganisms may not only contribute to iron removal by direct oxidation but also by continuously providing newly-formed iron oxides for its adsorption. Description of “ Ca. Siderophilus nitratireducens” gen. nov., sp. nov. \n Siderophilus ( Si.de.ro ’phi.lus Gr. masc.n. sidêros iron; Gr. masc. adj. philos loving; N.L. masc. n. Siderophilus , loving iron). \n ni.tra.ti.re .du’.cens (N.L. masc. n. nitras (gen. nitratis) , nitrate; L. pres. part. reducens , converting to a different state; N.L. part. adj. nitratireducens , reducing nitrate). Autotrophic nitrate-reducing iron-oxidizing bacterium isolated from a filtration unit fed with anaerobic groundwater with iron(II) and nitrate. Harbors also have the genetic potential to aerobically oxidize iron."
} | 3,020 |
39812922 | PMC12065754 | pmc | 5,350 | {
"abstract": "Cyanobacteria are advantageous hosts for industrial applications toward achieving sustainable society due to their unique and superior properties such as atmospheric CO 2 fixation via photosynthesis. However, cyanobacterial productivities tend to be weak compared to heterotrophic microbes. To enhance them, it is necessary to understand the fundamental metabolic mechanisms unique to cyanobacteria. In cyanobacteria, NADPH and ATP regenerated by linear and cyclic electron transfers using light energy are consumed by CO 2 fixation in a central metabolic pathway. The previous study demonstrated that the strain deleted a part of respiratory chain complex (Δ ndhF1 ) perturbed NADPH levels and photosynthetic activity in Synechocystis sp. PCC 6803. It is expected that disruption of ndhF1 would result in a decrease in the function of cyclic electron transfer, which controls the ATP/NAD(P)H production ratio properly. In this study, we evaluated the effects of ndhF1 deletion on central metabolism and photosynthesis by 13 C-metabolic flux analysis. As results of culturing the control and Δ ndhF1 strains in a medium containing [1,2- 13 C] glucose and estimating the flux distribution, CO 2 fixation rate by RuBisCO was decreased to be less than half in the Δ ndhF1 strain. In addition, the regeneration rate of NAD(P)H and ATP by the photosystem, which can be estimated from the flux distribution, also decreased to be less than half in the Δ ndhF1 strain, whereas no significant difference was observed in ATP/NAD(P)H production ratio between the control and the Δ ndhF1 strains. Our result suggests that the ratio of utilization of cyclic electron transfer is not reduced in the Δ ndhF1 strain unexpectedly. Supplementary Information The online version contains supplementary material available at 10.1007/s12010-024-05138-4.",
"introduction": "Introduction Since cyanobacteria can grow using light energy and atmospheric CO 2 , it is attracting attention as a host for producing chemicals from CO 2 toward achieving a sustainable society [ 1 ]. Cyanobacteria possess several advantageous properties for industrial applications: (i) atmospheric CO 2 fixation as a sole carbon source by RuBisCO, (ii) low contamination risks due to quick growth on simple media, and (iii) higher photosynthetic efficiency than land plant [ 2 ]. Previous studies successfully produced various valuable compounds, including polyhydroxyalkanoates [ 3 ], alcohols [ 4 , 5 ], carbohydrates [ 6 – 8 ], organic acids [ 9 , 10 ], and isoprene derivatives [ 11 – 13 ], using genetically engineered cyanobacterial strains. However, productivities tend to be weak compared to other microbes that can utilize higher energy contents such as sugars and oils. To enhance the cyanobacterial productions, it is necessary to understand the cyanobacteria-specific functional connection between photosystem producing the energy required to fix CO 2 and central metabolic pathway responsible for the conversion from the CO 2 to the target products. In case of cyanobacterial photosynthesis, the photosystem produces NADPH and ATP, which are used in a sequence of reactions involving CO 2 fixation by the RuBisCO, as known as Calvin-Benson-Bessham (CBB) cycle. The relationship between linear electron transfer (LET) and cyclic electron transfer (CET), which are typical electron flows in photosystems [ 14 ], and the CBB cycle is shown in Fig. 1 . In the LET, electrons extracted from water in photosystem II (PSII) are transferred to NADP + via plastoquinone (PQ) followed by the cytochrome b 6 f complex (Cyt b 6 f ), plastocyanin (PC), and photosystem I (PSI). Transhydrogenase (TH) converts NADPH with NAD + to NADP + with NADH and vice versa. The LET produces NADPH and ATP in a molar ratio 2:2.57, whereas the molar ratio of NADPH and ATP consumed in the CBB cycle is 2:3. To address this ATP shortage in the LET, cyanobacteria utilize another electron transfer system, CET. The CET produce ATP without NADPH production by transferring electron from ferredoxin (Fd) to PQ for reacting to fluctuating environmental conditions [ 15 , 16 ]. One of the electron acceptors in CET is NAD(P)H-dehydrogenase I (NDH-1) as respiratory chain complex. Toyoshima et al. revealed that NDH-1 was utilized under favorable growth conditions [ 17 ]. Battchikova et al. revealed that deletion of ndhS , which constitutes a new subunit of NDH-1, triggered reduction of growth rate and CET activity mediated by the NDH-1 [ 18 ]. These results suggest that the NDH-1 is a pivotal electron acceptor in CET. Hence, it is considered that NDH-1 dysfunction can perturb the link between photosystem and central metabolic pathway via NAD(P)H. Fig. 1 Relationship between photosystem and central metabolic pathway in cyanobacteria connected by NAD(P)H and ATP. In linear electron transfer, electrons extracted from water in photosystem II (PSII) are transferred to photosystem I (PSI) via cytochrome (Cyt b 6 f ) and used for NAD(P)H regeneration. ATP is also regenerated using protons (H + ) pumped out during the electron transfer process. In cyclic electron transfer, electrons from ferredoxin (Fd) or NAD(P)H are transferred to plastoquinone (PQ), thereby regenerating ATP without regenerating NAD(P)H. Transhydrogenase (TH) easily converted electron transfer between NADH and NADPH. CO 2 is fixed by RuBisCO in central metabolic pathway using NAD(P)H and ATP produced by the photosystem According to updated-Fluorome summarizing the chlorophyll fluorescence of 750 gene-disruptant from Synechocystis sp. PCC 6803, the strain disrupted ndhF1 encoding NAD(P)H-quinone oxidoreductase subunit 5 in NDH-1 (Δ ndhF1 ) showed the largest change in the Kautsky curve [ 19 ]. Although it has been shown that the photosynthetic activity estimated from chlorophyll fluorescence in mutants with defective respiration, including the Δ ndhF1 strain, may be increased [ 20 ], the NADPH accumulated in the dark [ 21 ]. Since deletion of genes regarding NDH-1 resulted in the accumulation of excess NAD(P)H available for biosynthesis of target products, NDH-1 dysfunction may be effective for productions of valuable compounds in cyanobacteria. In facts, deletion of ndhF1 in engineered-cyanobacterial strains triggered increase of the production of ethanol and 1,3-propandiol, which consumed NAD(P)H for biosynthesis, via expansion of NAD(P)H sink [ 22 , 23 ]. Therefore, it is expected that the analysis of the Δ ndhF1 strain without producing the NAD(P)H-consuming chemical productions is useful for understanding the fundamental metabolism of cyanobacteria about NAD(P)H perturbation. Although the regenerative fluxes of NAPDH and ATP by photosystem cannot be measured directly, the balance between regeneration and consumption rates of them in cyanobacteria is maintained homeostasis by the photosystem and central metabolism. Therefore, by determining the regeneration and consumption rates of them by the central metabolic pathway, it is possible to estimate those by photosynthesis. 13 C-metabolic flux analysis ( 13 C-MFA) is a method that accurately predicts the flux distribution of metabolic pathway, including the CO 2 fixation rate, using isotope labeling information [ 24 ]. One of the insights from 13 C-MFA is an estimation of the intracellular state based on cumulation of the regeneration and consumption rates of NAD(P)H and ATP accompanying metabolic reactions [ 15 , 25 ]. In this study, we aimed to investigate how the metabolic state changes in the Δ ndhF1 strain by 13 C-MFA. We cultivated the Δ ndhF1 strain in medium containing glucose and carbonate, estimated the flux distribution on the central metabolic pathway during the exponential growth phase, and evaluated the effects of NDH-1 dysfunction on the overall metabolism of cyanobacteria.",
"discussion": "Discussion In this study, we evaluated metabolic states of the Δ ndhF1 and Ctrl strains by 13 C-MFA. The specific rates of growth and glucose consumption, and contents of photosynthetic pigments in the Δ ndhF1 were decreased compared to the Ctrl strain (Fig. 2 , Table 1 , Supplementary Fig. 1). Accompanied with the reduction of them, the CO 2 fixation rate by RuBisCO in the Δ ndhF1 also decreased compared to the Ctrl strain, whereas no obvious change of flux ratio at the branch points in metabolic pathway was observed (Fig. 4 ). Although the total specific NAD(P)H and ATP regeneration/consumption rates were decreased in the Δ ndhF1 , regenerative NAD(P)H/ATP ratio by photosynthesis was comparable between the Ctrl and Δ ndhF1 strains (Fig. 5 ). The previous study demonstrated that the change of ATP/NAD(P)H production ratio reflected utilization ratio of CET/LET ratio [ 15 ]. These results suggest that the total photosynthetic activities estimated from 13 C-MFA decrease under NDH-1 dysfunction, but the utilization ratio of CET remains unchanged against expectations. Despite the disruption of ndhF1 , which constituted a main electron acceptor NDH-1 in CET, no obvious change was observed in the utilization ratio of CET. The fact that the CET utilization ratio was stably maintained may indicate that this level of CET utilization ratio was necessary under the culture conditions used in this study. According to the previous study [ 15 ], the CET/LET ration in Synechocystis sp. PCC 6803 under mixotrophic condition under 3 kinds of single wavelength lights was estimated to 0.2–2.2. Of these, the growth rate, flux distribution, and ATP/NADPH ratio in this study were middle level between R630 and R680, which have CET/LET rations of 0.2–0.5 and 0.5–1.0, respectively. Hence, it is expected that CET/LET rations of 0.2–0.5 were required for growth of Synechocystis sp. PCC 6803 under mixotrophic conditions. Since CET is a pivotal system to produce ATP without NADPH regeneration for responding flexibly to changing environments, there are some alternative pathways [ 37 ]. NAD(P)H dehydrogenase II (NDH-2) is a one of the candidates for alternative electron acceptors. NDH-2, unlike NDH-1, reduces PQ without formation of proton gradient during the electron transfer via itself [ 38 ]. Although the efficiency of ATP production via the oxidation of NAD(P)H by NDH-2 is smaller than that by NDH-1, its function may be advantageous under NAD(P)H-rich conditions such as ndhF1 deletion, since excess NAD(P)H can be consumed without futile ATP production. Although a few reports showed the functionality of NDH-2 in Synechocystis sp. PCC 6803 [ 39 , 40 ], these were insufficient to estimate the degree of contribution to CET by NDH-2. Another candidate for electron acceptors in CET is a proton gradient regulation 5 (PGR5) coupled with PGR5-like photosynthetic phenotype 1 (PGRL1). PGR5/PGRL1 transfers electron from Fd to PQ directly or indirectly [ 41 ]. The previous studies reported that their analogs were found in Synechocystis sp. PCC 6803 genome and stimulated CET as electron acceptors [ 42 , 43 ]. However, the CET efficiency using alternative electron acceptors seemed to be much lower than that using NDH-1, since parameters related to cyanobacterial growth decreased across the board in this study, especially photosynthetic pigments. PC localizes in phycobilisome for harvesting light energy, while chlorophyll localizes in PSII and PSI for transferring light energy. Since these pigments contributes to efficient photosynthetic activities, decrease of these pigments should be effective to avoid production of the excess NAD(P)H in absence of ndhF1 in exchange for well-growth. As shown in the previous studies for enhancing productivities of target products which required NAD(P)H for biosynthesis, it is certainly a great idea in which ndhF1 disruption for making excess available NAD(P)H pool in engineered-cyanobacterial strains [ 22 , 23 ]. However, this study revealed that ndhF1 disruption also triggered some unfavorable decreases in cyanobacterial metabolism, including growth rate, photosynthetic pigment contents, and CO 2 fixation rate. It may be caused by the excess NAD(P)H pool. One solution is to consume excess NAD(P)H accumulated by the disruption of ndhF1 to an appropriate level by enhancing the productions of target compounds requiring NAD(P)H for their biosynthesis using genetic engineering techniques. Although this strategy is expected to improve cyanobacterial growth to some extent, the carbon shortage will limit whole cyanobacterial metabolism because of current state that ca. 70% of CO 2 fixation rate must be redistributed into the CBB cycle to maintain the current CO 2 fixation rate. Hence, most important improvement for cyanobacterial metabolism is enhancement of efficiency of CO 2 fixation by RuBisCO via CBB cycle. Although it is a challenging issue, success for improvement will open up a new frontier for cyanobacterial production."
} | 3,217 |
34135337 | PMC8209157 | pmc | 5,351 | {
"abstract": "Photoreceptors are conserved in green algae to land plants and regulate various developmental stages. In the ocean, blue light penetrates deeper than red light, and blue-light sensing is key to adapting to marine environments. Here, a search for blue-light photoreceptors in the marine metagenome uncover a chimeric gene composed of a phytochrome and a cryptochrome ( Dualchrome1 , DUC1 ) in a prasinophyte, Pycnococcus provasolii . DUC1 detects light within the orange/far-red and blue spectra, and acts as a dual photoreceptor. Analyses of its genome reveal the possible mechanisms of light adaptation. Genes for the light-harvesting complex (LHC) are duplicated and transcriptionally regulated under monochromatic orange/blue light, suggesting P. provasolii has acquired environmental adaptability to a wide range of light spectra and intensities.",
"introduction": "Introduction Photosynthetic organisms utilize various wavelengths of light, not only as sources of energy but also as clues to assess their environmental conditions. Blue light penetrates deeper into the ocean, whereas red light is absorbed and immediately decreases at the surface. Oceanic red algae possess blue-light receptor cryptochromes (CRYs) but not red-light receptor phytochromes (PHYs) 1 . Similarly, most chlorophytes have CRYs but fewer have PHYs. PHYs are bilin-containing photoreceptors for the red/far-red-light response. Interestingly, algal PHYs are not limited to red and far-red responses. Instead, different algal PHYs can sense orange, green, and even blue light 2 . They have the ability to photosense between red-absorbing Pr and far-red-absorbing Pfr, and this conformational change enables interactions with signaling partners 3 . CRY is a photolyase-like flavoprotein and widely distributed in bacteria, fungi, animals and plants. In 2012–2014, large-scale metagenome analyses were performed in Sendai Bay, Japan, and the western subarctic Pacific Ocean after the Great East Japan Earthquake to monitor its effects on the ocean ( http://marine-meta.healthscience.sci.waseda.ac.jp/crest/metacrest/graphs/ ). These metagenome analyses targeted eukaryotic marine microorganisms as well as bacteria. Blue-light sensing is key to adapting to marine environments. From a search for CRYs in the marine metagenomic data, we found a chimeric photoreceptor, designated as Dualchrome1 (DUC1), consisting of a two-domain fusion of PHY and CRY. We found that DUC1 originated from a prasinophyte alga, Pycnococcus provasolii . P. provasolii is a marine coccoid alga in Pseudoscourfieldiales, Pycnococcaceae (or prasinophyte clade V 4 ) and was originally discovered in the pycnocline 5 . P. provasolii is classified in Chlorophyta, which is a sister group of the Streptophyta in Viridiplantae. Chlorophyta contain three major algal groups, Ulvophyceae, Trebouxiophyceae and Chlorophyceae (UTC clade), and “prasinophytes”, which have several characteristics considered to represent the last common ancestor of Viridiplantae. Prasinophytes mainly inhabit marine environments and are dominant algae under various light qualities and intensities 6 . Thus, prasinophytes are key to understanding the diversity and evolutionary history of the light response system in the Viridiplantae. Environmental DNA research shows P. provasolii lives at depths in the range of 0–100 m and in varying regions of the marine environment 6 , 7 . It also has a unique pigment composition (prasinoxanthin and Magnesium 2,4-divinylpheoporphyrin a 5 monomethyl ester) and an ability to adapt to the spectral quality (blue and blue-violet) and low fluxes of light found in the deep euphotic zone of the open sea 5 , 8 . We unveil here with DUC’s ability to detect a wide range of the light spectrum (orange to far-red for PHY and UV to blue for CRY) and undergo dual photoconversions at both the PHY and CRY regions. We sequence the genome of P. provasolii and examine its light-associated features. These findings will help to understand the evolutionary diversity of photoreceptors in algae and explain the environmental adaptation and success of P. provasolii .",
"discussion": "Discussion In this research, we have found a bifunctional photoreceptor, PpDUC1, composed of a fusion of PHY and CRY. In terms of evolution, it is often speculated that different domains of one organism’s protein are encoded by separate genes in another and this has been used successfully to speculate about direct physical interaction or indirect functional association 22 . It is reported that phyB and cry2 physically interact to transduce light signals for controlling flowering time in Arabidopsis 23 . Our discovery of PpDUC1 indicates that PHY and CRY interact actively to enable proper perception of light signals. Another example is Neochrome, which is found in ferns 24 , that is composed of a PHY domain and a PHOT domain. This chimeric protein also supports the idea that there is dynamic interaction of photoreceptors 25 . From RNA-Seq analysis we found P. provasolii responds to orange, blue and far-red light and that 1,964 genes are expressed under orange and blue light. DCMU treatment reduced the number of DEGs to 1,094, orange DEGs being reduced from 1,503 to 471. Most of the genes whose expression was canceled by DCMU are genes involved in photosynthesis (Supplementary Fig. 11 ). Since DUC1 can sense orange, blue and far-red lights, some of the 119 DEGs of OBF light may be controlled by DUC1(Fig. 5b ). Interestingly 45 out of these 119 genes showed higher expression in blue compared to orange light. On the other hand, among 155 DEGs of orange and blue lights only 6 genes showed higher expression in blue compared to orange light (Fig. 5b ). These 45 genes may be controlled by other cryptochromes enabling them to achieve their higher expression. DUC1 , Plant-like CRY , CRY-dash and HY5 were all induced by blue light with DCMU treatment. Inhibition of photosynthesis may control expression of these genes (Fig. 5d ). In tobacco cells, PpDUC1 mostly localizes in the nucleus under white light (Fig. 3f ) while the PpPHY domain is mainly localized in the cytoplasm. Although this investigation was done in a heterologous system, PpPHY’s intracellular localization did not change under different light conditions. This may explain the results of the complementation assay that shows PpDUC1 does not complement phyB in respect of hypocotyl length (Supplementary Figs. 13 and 14 , Supplementary Method 8 and 9 ). Plant and M. pusilla phytochromes translocate from the cytoplasm to the nucleus under light irradiation 17 . Plant phytochrome is known to transduce its photoactivated signals through interaction with PIF protein in the nucleus and finally HY5 controls light-inducible gene expression 26 . We did not observe light-dependent intracellular PpDUC1 translocation nor its enrichment in the nucleus by light in tobacco cells (Supplementary Fig. 8 ). Also, there is no PIF homolog in the P. provasolii genome (Table 1 ). Further analysis is needed to understand how DUC1 transduces light signals to control gene expression in P. provasolii . In this study, we have revealed that PpPHY shows Po/Pfr photocycle, which is similar to the PHY molecules derived from other prasinophyte species, indicative of the same origin 2 . It is well known in cyanobacteriochrome photoreceptors, distant relatives of the PHYs, that the trapped geometry of the rotating ring D is crucial for blue-shifted absorption 27 . Residues unique to prasinophyte PHY molecules would be crucial for such a twist of ring D. Notably, two Tyr residues conserved among the plant and cyanobacterial PHYs that hold ring D are replaced with Phe, Met or Trp residues in the prasinophyte PHYs (Supplementary Fig. 15 and Supplementary Method 10 ) 28 , which may contribute to holding ring D in the trapped geometry, resulting in the absorption of blue-shifted orange light in the dark state Po form. Many green algae share genes for PHY 9 and pCRY 29 . Of the prasinophytes, Tetraselmis , Nephroselmis , Micromonas , Dolichomactix , and Prasinoderma possess genes for functional PHY 1 , 2 . However, the genomes of Chloropicon , Ostreococcus , Bathycoccus , and M. commoda lack any PHY genes (Table 1 and Fig. 4 ). These PHYs are monophyletic and the tree topology coincides with the species tree (Fig. 1c and Supplementary Fig. 4 ), suggesting that PHY may have disappeared multiple times, independently 9 . Our phylogenetic analysis inclusive of DUC1 supports the idea that the last common ancestor of the Archaeplastida had a phytochrome 17 . In contrast, pCRY is widely shared in chlorophytes and streptophytes 15 , and only the genomes of Mamiellales and Chlorella variabilis lack pCRY (Supplementary Fig. 3 ). In evolutionary terms, PpDUC1 was not found in other green algae except for P. provasolii and Pseudoscourfieldia , and P. provasolii is sister to N. pyriformis , which possesses PHY and pCRY , which suggest that PpDUC1 may have been acquired in an ancestor of Pycnococcus (and Pseudoscourfieldia ). As the domain structure of PpDUC1 is similar to the Phy and Cry of N. pyriformis (Fig. 4 ), PpDUC1 may have been generated via the fusion of these genes. Recent fusion is suggested by the remaining original GC%, i.e., the PHY region has higher GC% than the pCRY region in PpDUC1 (PpPHY: 62.2% and PpCRY: 59.5%). Sensitivity to weak light is essential for marine algae. P. provasolii also has a unique pigment composition (prasinoxanthin and Magnesium 2,4-divinylpheoporphyrin a 5 monomethyl ester) and an ability to adapt to spectral quality (blue and blue-violet) and low-light intensity 5 , 8 . Under high-light radiation, algae and land plants degenerate antenna complexes (LHCs and pigments) to decrease the absorbance of excess energy and prevent photodamage 30 . The degradation of Chl triggers degradation of LHCs 31 . Interestingly, LHC induction by orange and blue light is strongly reduced by DCMU treatment but ELIP expression is induced by DCMU treatment. ELIPs are members of LHCs that protect photosynthesis from high-light irradiation. Therefore, P. provasolii may adjust the amount of antenna complex by Chl degradation under strong light at the surface of the sea. For photosynthesis in marine environments, Chl b is suitable because its absorption peak is shifted to blue-green compared with Chl a . This use of Chl b is different to land plants. Marine prasinophytes possess Chl b , not only in LHCs but also in PSI core antennae 5 , 32 . P. provasolii possesses LHCA, LHCB and a number of prasinophyte-specific LHCs (Lhcp) (Fig. 5 ). The Lhcps make complexes with Chl a / b and carotenoids 33 . Our transcriptome data showed that all LHC genes were upregulated and some Lhcps were strongly upregulated under orange- and blue-light irradiation (Fig. 5 ). This result is consistent with LHC regulation in land plants. Our studies show the possible dynamic adaptation mechanisms to light spectra and intensities in P. provasolii , through the blue-, orange- and far-red-sensing DUC1. Acquisition of the dual functional photoreceptor, DUC1, has opened up a way for P. provasolii to widen its spectral utilization."
} | 2,818 |
36961890 | PMC11817482 | pmc | 5,352 | {
"abstract": "Biofilms are multicellular communities with a spatial structure. Different from single-cell scale diffusion in planktonic systems, the diffusion distance becomes the dimension of multicellular clusters in a biofilm. Such differences in diffusion behavior affect the tolerance and response to exogenous stress. Here, we found that at the same doses of exogenous hydrogen peroxide (H 2 O 2 ), planktonic Escherichia coli were completely killed within two hours, whereas the biofilm resumed growth in six hours by building a catalase barrier to block H 2 O 2 penetration, despite the growth burden. Unexpectedly, when we changed the carbon source from glucose to glycerol, H 2 O 2 instantly counterintuitively boosted biofilm growth due to supplemental oxygen, which was the growth-limiting factor. We further demonstrated that the energy metabolism modes determined the growth-limiting factor, which then determined the two patterns of biofilms resistances to H 2 O 2 .",
"introduction": "INTRODUCTION In addition to the well-known planktonic bacteria commonly found in laboratory shakers, community living accounts for the majority of bacteria in nature ( 1 , 2 ). Especially on surfaces, bacteria secrete extracellular polymeric substances, such as proteins, polysaccharides, and extracellular DNA, which enable the formation of dense aggregates that are termed biofilms ( 3 – 5 ). The dense and packed structure of multicellular communities determines the spatial gradient of nutrients, oxygen, pH, and metabolites in biofilms ( 6 – 9 ). Taking biofilms in fluid environments as an example, we found that nutrients and oxygen originated mainly from external fluids, resulting in a nutrient- and oxygen-rich environment at the periphery of biofilms ( 10 ). However, nutrients and oxygen can only diffuse to a certain depth because of their consumption by peripheral bacteria, resulting in hypoxia, lack of nutrients, and accumulation of metabolite waste in the biofilm interior ( 6 – 10 ). The spatial gradient of nutrients and metabolites determines the spatial differences in the microenvironment ( 11 – 16 ) and further determines the high spatial heterogeneity of growth and metabolism, as well as specific collective behaviors of the biofilms, such as division of labor and spatial cross-feeding ( 17 – 19 ). Much of what makes life in a microbial biofilm different from life in a free aqueous suspension can be explained by the phenomenon of diffusion. In planktonic systems, small molecules almost simultaneously and isotropically diffuse into cells, especially under agitation ( 20 , 21 ). In multicellular biofilm communities, exogenous molecules diffuse unilaterally from the periphery of the biofilm to the interior ( 20 , 22 , 23 ). Diffusion is the predominant transport process within the cell aggregates ( 21 , 24 , 25 ). Although the diffusion distance for a freely suspended microorganism is of the order of magnitude of the dimension of an individual cell, the diffusion distance in a biofilm becomes the dimension of multicellular clusters. This can easily represent an increase of two to three orders of magnitude in the diffusion distance, compared to a single cell ( 20 , 21 ). Thus, when encountering antimicrobial agents, planktonic bacteria have no opportunity to respond when the stress exceeds a certain threshold; however, unilateral diffusion may allow a time window for the adaptation and active regulation of bacteria in the biofilm ( 26 – 29 ). On the basis of the microfluidic method developed in our laboratory ( 10 ), this work focuses on the responses of biofilm and planktonic bacteria to oxidative stress caused by exogenous hydrogen peroxide (H 2 O 2 ) from the perspective of diffusion behaviors. Our findings provide references and warnings for current epidemic prevention and environmental disinfection work. Moreover, this study provides a perspective for studying the mechanisms of biofilm resistance to exogenous stress.",
"discussion": "DISCUSSION The multicellular community of the biofilm determines the spatial structure and unidirectional diffusion behavior of exogenous molecules ( 20 – 23 , 27 ). In contrast to isotropic diffusion with single-cell dimensions in the planktonic system, this unidirectional and long-range diffusion may create opportunities and provide a time window for biofilms to respond to exogenous stress. In this study, we found that planktonic bacteria were not resistant to exogenous H 2 O 2 , whereas the biofilm community exhibited two patterns of resistance behavior. The first involves building a catalase barrier to block further penetration of H 2 O 2 but at the cost of a reduced growth rate. This is because maintaining the catalase barrier consumes energy, and the carbon source is the growth-limiting factor. In the second pattern, under the premise that oxygen is a growth-limiting factor (the oxygen in the medium is not enough for biofilm growth; fig. S11), exogenous H 2 O 2 can accelerate biofilm growth. As the catalytic product of H 2 O 2 , oxygen alleviates growth restriction (the oxygen generated from H 2 O 2 meets its growth demands; fig. S11), and the cross membrane rate of oxygen is faster than that of H 2 O 2 ( 40 ), resulting in a growth rate greater than the killing rate and the net growth of biofilms. In the planktonic system, even if oxygen is the growth-limiting factor in a low-oxygen environment and the addition of H 2 O 2 may also produce oxygen, owing to the isotropic diffusion of H 2 O 2 , bacteria were synchronously subjected to oxidative stress or killed (fig. S12) and could no longer use the generated oxygen. Biofilms exhibited these two patterns of resistance behavior because bacteria have different energy metabolism modes. The OCR is different for different carbon sources, resulting in different penetration depths of oxygen in biofilms. Factors that affect biofilm growth include carbon, nitrogen, phosphate, and oxygen. However, owing to the unidirectional diffusion of nutrients from the biofilm periphery to the interior, the nutrient with the shallowest diffusion depth becomes the limiting factor for biofilm growth. In our defined medium, the main factors affecting biofilm growth were the carbon source and oxygen. Therefore, in the first case, when the carbon source is limited, maintenance of the catalase barrier consumes energy, resulting in the reduction of energy allocated to growth. This resistance is maintained at the cost of a growth reduction. However, in the second case, because oxygen is the growth-limiting factor and H 2 O 2 is catalyzed to oxygen by catalase, supplemental oxygen relieves the growth restriction to a certain extent, resulting in net growth, as described above. In addition, in general, H 2 O 2 boosts biofilm growth under various conditions. This work suggests that community-specific diffusion characteristics may be an important entry point for studying the resistance mechanism of biofilms to exogenous stresses."
} | 1,740 |
26379769 | PMC4571542 | pmc | 5,353 | {
"abstract": "Background Synechocystis sp. PCC 6803, a model organism used for bioenergy and bioplastic production, was grown in continuous culture to assess its most important bioenergetic parameters. Results Biomass yield on light energy of 1.237 g mol photons −1 and maintenance energy requirement of 0.00312 mol photons g −1 h −1 were calculated. This corresponded to a light conversion efficiency of 12.5 %, based on the model of Pirt which was about 35 % lower than the theoretical one based on the stoichiometric equation for the formation of biomass on carbon dioxide, water, and nitrate. The maximum F v / F m ratio recorded in the Synechocystis cultures was 0.57; it progressively declined to 0.45 as the dilution rate increased. An over-reduction of reaction centers at a high dilution rate was also recorded, together with an increased V J phase for the chlorophyll fluorescence transient. In contrast, the chlorophyll optical cross section increased by about 40 % at the fastest dilution rate, and compensated for the decline in F v / F m , thus resulting in a constant total photosynthesis rate (photosynthesis plus respiration). Chlorophyll content was maximum at the lowest dilution rate and was 48 % lower at the highest one, while phycocyanin, and total carotenoids decreased by about 42 % and 37 %, respectively. Carotenoid analysis revealed increased echinenone, zeaxanthin, and myxoxanthophyll contents as the dilution rate increased (40.6, 63.8 and 35.5 %, respectively, at the fastest dilution rate). A biochemical analysis of the biomass harvested at each different dilution rates showed no changes in the lipid content (averaging 11.2 ± 0.6 % of the dry weight), while the protein content decreased as the dilution rate increased, ranging between 60.7 ± 1.1 and 72.6 ± 0.6 %. Amino acids pattern did not vary with the dilution rate. Carbohydrate content ranged from 9.4 to 16.2 % with a mean value of 11.2 ± 1.4 %. Conclusions The present work provides useful information on the threshold of light conversion efficiency in Synechocystis , as well as basic bioenergetic parameters that will be helpful for future studies related to its genetic transformation and metabolic network reconstruction. Electronic supplementary material The online version of this article (doi:10.1186/s13068-015-0319-7) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions The limited amount of available fossil energy on the one hand and the necessity: of gearing the economy towards low carbon emissions on the other, intensify the demand for clean energy sources for the near future. Synechocystis is a model system: thanks to its available genomic sequence and to its ability to be naturally transformable. It could provide renewable energy in the form of hydrogen, which is considered to be the most important energy carrier [ 3 , 28 ]. Moreover, its use has been proposed for photosynthetic production of isoprene for various applications, such as the production of rubber, adhesives, plastics, and perfumes [ 5 – 7 ]. This study provides a significant data set analyzing the maximum threshold of LCE as well as basic bioenergetic parameters of high-density cultures of Synechocystis , a microorganism of immense biotechnological potential. Our experiments will help future attempts of genetic transformation of this organism and improve in silico analysis of cyanobacterial photosynthetic models. We would like to emphasize that the mean effective LCE attained by Synechocystis in this study (11.32 ± 0.41 %) was under strictly controlled laboratory conditions (refers to PAR from 400 to 700 nm). Under more natural outdoor conditions with variable environmental factors (e.g., temperature, mixing, nutrients), the LCE, typically drops to 5–6 % of total solar radiation, of which PAR is assumed to account for 45 %. Similar LCE was also found by Zhu et al. for higher plants [ 29 ]. The culture studied in our lab was exposed to a light intensity which was roughly 1/10th of that recorded outdoors on a typical day in summer. Therefore, it would be unrealistic to compare laboratory performance of Synechocystis to outdoor culture scenarios.",
"discussion": "Discussion Since there is considerable interest throughout the world in exploring Synechocystis as both an organism suitable for producing hydrogen and as a source of bioplastic material, an assessment of its photosynthetic efficiency is important. To determine the optimum growth conditions of Synechocystis , continuous culture experiments were carried out. Different dilution rates were applied to establish the optimal cell concentration and the maximal light conversion attainable by this organism. A constant biomass yield on the absorbed light energy of 1.237 g mol photons −1 was calculated for Synechocystis which was considerably higher than the ones reported by Zijffers [ 13 ] for Chlorella sorokiniana (0.78 g mol photons −1 ) and Dunaliella tertiolecta (0.75 g mol photons −1 ). This discrepancy can be explained by the fact that absorbed light was used in our calculation, instead of total incident light. Another important difference was that, in our experiment, the incident light intensity was 1/6 of the amount used by the said authors, and therefore our culture might have dissipated a very small amount of energy via NPQ. Based on Pirt’s model, LCE (PAR basis) yielded a maximum value of 12.5 %. This value was around 40 % lower than the theoretical one (i.e., 18.95 %, Additional file 5 : Text S1). The discrepancy between actual and theoretical LCE was very close to that calculated for the quantum yield of photosynthesis, Φ CO2 and to the maximum quantum yield of PSII ( F v / F m ). This ratio was in fact lower than the one normally reported in higher plants and microalgae (0.75–0.85). It is conceivable that the photosynthetic apparatus of Synechocystis cells it normally stays in state 2, which is characterized by lower fluorescence and photosynthesis rates and high energy dissipation via state transition quenching (qT) [ 14 ]. qT is attributed to the decoupling of phycobilisomes from PSII [ 14 ]. It has been reported that phycobilisome decoupling is seemingly important not only under strong irradiation [ 15 ], but also at physiological conditions of irradiance, provided that the exposure time is sufficiently long. It has been suggested that the dissipation of light energy in Synechocystis may occur via both the orange carotenoid protein (OCP) [ 16 ] in blue actinic light and a rise in orange light-induced S, M fluorescence [ 14 ]. The actual biomass yield ( Y , g mol photons −1 ) was relatively constant at most of the high D (Table 1 ). Between minimum and maximum D values, an increase in Y of about 20 % was observed. This could be attributed to the greater availability of light and to the higher growth yield Y . The highest biomass yield on light energy (1.22 ± 0.05 g mol photons −1 ) was attained at D = 0.0725 h −1 . LCE values at different D were fairly constant (mean 11.3 ± 0.41 %). Most likely, the efficient mixing system, consisting of a specially designed rotating impeller [ 17 ], and the absence of any dark zones in the reactor, prevented cells from becoming acclimated to low light even when they were grown at low D (dense cultures). On the other hand, cells grown at a high D reacted by reducing the chlorophyll antenna and increasing their optical absorption cross section, thus making better use of light per chlorophyll unit. In our culture system the photon flux uptake ranged from 16 to 95 mmol photons g −1 h −1 , with optimum value close to 50 mmol photons g −1 h −1 , that is, in correspondence to the highest LCE attained. These findings agree with the metabolic model proposed by Nogales et al. [ 18 ]. Both the maximum photochemical quantum yield ( F v / F m ) and the effective quantum yield of PSII ( ∆F /F m ′ ) declined by about 20 % between minimum and maximum D . This occurrence was also accompanied by a slight increase in V J of the chlorophyll fluorescence transient. A lower decrease in the ETR max was recorded (about 10 % at the extreme D ). This lower difference compared to that observed in the effective quantum yield of PSII (∆ F / F m ′ ) could be explained by the fact that with the increase of D the cells reacted with a 40 % increase in the chlorophyll optical absorption cross section. Despite the reduction in the F v / F m ratio, gross photosynthesis (i.e. net photosynthesis plus respiration) did not show important changes and was found to be almost independent of D . Reductions in the net photosynthesis rate was compensated by a proportional increase in the respiration rate, which increased with increasing D . The apparent paradox of a reduction in the F v / F m ratio without a parallel reduction in the maximum photosynthesis rate had already been reported by Behrenfeld et al. [ 19 ]. Quantum yield Φ CO2 determined in this study resulted higher (close to 0.06 mol CO 2 mol photons −1 ) in cells grown at lower D (between 0.0173 and 0.0282 h −1 ). This value was close to that reported by Skillman [ 20 ] for C4 plants and that calculated by Nogales et al. using cyanobacteria system analysis [ 21 ]. The value slightly declined with the increase of D , which reduced the cell concentration and therefore led to a higher exposure of cells to light and consequently to a reduction in the effective quantum yield of PSII. Yet, these changes were not detected by changes in NPQ which was most likely underestimated due to the difficulty of correctly measuring F m in dark adapted cultures of cyanobacteria. Moreover, in our calculation we assumed that PSII/PSI ratio was constant and equal to 1. This ratio is close to the value reported by Fujimori et al. [ 22 ], who used Synechocystis cultures exposed to a constant light intensity similar to our experiments. However, PSII/PSI may range from 0.4 to 1.0 from low light-adapted to high light-adapted cultures [ 22 , 23 ]. Much higher changes in the PSII/PSI ratio can be expected in carbon limited Synechocystis cultures as reported by Nogales [ 21 ]. PSII/PSI as low as 0.2 has been reported [ 24 ]. This unusual stoichiometry in cyanobacteria has been explained with the involvement of PSI in a significant amount of cyclic electron flow around this photosystem. Alternatively, high PSI amount in cyanobacteria may serve to balance the abundance of the respiratory electron transfer pathways into the PQ pool [ 25 ]. Both hypothesis are suggested to act as photoenergy-dissipation pathways [ 21 , 25 ]. About 20 % of electrons originated from water was targeted to O 2 via Mehler reaction (water–water cycle) in wild type Synechocystis grown under atmospheric CO 2 levels [ 26 , 27 ]."
} | 2,698 |
38786783 | PMC11124044 | pmc | 5,354 | {
"abstract": "Nowadays, magnetic materials are also drawing considerable attention in the development of innovative energy converters such as triboelectric nanogenerators (TENGs), where the introduction of magnetic materials at the triboelectric interface not only significantly enhances the energy harvesting efficiency but also promotes TENG entry into the era of intelligence and multifunction. In this review, we begin from the basic operating principle of TENGs and then summarize the recent progress in applications of magnetic materials in the design of TENG magnetic materials by categorizing them into soft ferrites and amorphous and nanocrystalline alloys. While highlighting key role of magnetic materials in and future opportunities for improving their performance in energy conversion, we also discuss the most promising choices available today and describe emerging approaches to create even better magnetic TENGs and TENG-based sensors as far as intelligence and multifunctionality are concerned. In addition, the paper also discusses the integration of magnetic TENGs as a power source for third-party sensors and briefly explains the self-powered applications in a wide range of related fields. Finally, the paper discusses the challenges and prospects of magnetic TENGs.",
"conclusion": "5. Conclusions and Outlook This paper summarizes the applications of magnetic materials in TENGs and their applications in HNGs and self-powered sensors. It can be found that magnetic materials have shown great potential for developing high-performance and multifunctional TENGs for flexible wearables and robotics. Furthermore, composite films formed by magnetic particles and other materials, combined with magnets, enable non-contact energy harvesting, thereby improving the stability and durability of TENGs in extreme environments. Additionally, mechanical information in the environment can be converted into output signals of TENGs, allowing TENGs to operate as independent sensing systems and aid in the quick advancement of the Internet of Things era. While magnetic material-based self-powered sensors offer many advantages, there are certain limitations in terms of integration and practical applications. 5.1. Power Output Enhancement The methods to boost the output performance of TENGs mainly include material selection, surface optimization, and structural design. In this review, magnetic materials are chosen, which can be added as tiny magnetic particles to the electrode materials (with an excellent surface charge density, electronegativity, dielectric constant, etc.) or applied as thin films in the devices to increase the output performance of TENG through electrostatic induction and electromagnetic induction. Surface optimization is mainly achieved by physical or chemical treatments on the material surface. For example, changing the texture and roughness of the surface through physical methods such as electrospinning, 3D printing, and plasma treatment can improve the energy conversion efficiency. Chemical methods, such as surface corrosion or functionalization, can promote the transfer of electrons during the friction process to enhance the TENG’s output performance. Optimizing the structural design can also improve the output performance of soft or hard magnetic TENGs in different environments. By designing hybrid generators of different magnetic TENG structures (EMGs and TENGs), the coupling effect between triboelectrification and electromagnetic induction can be enhanced, enabling more efficient energy collection and conversion into electricity in a magnetic field. In addition, based on Maxwell’s equations, the addition of magnetic materials enhances the output current in TENGs. In the absence of an external magnetic field, the magnetic material undergoes magnetization due to the electric current generated after periodic friction with dielectric materials, thereby producing a magnetization current to enhance the output performance of the TENG. Upon the application of an external magnetic field, the magnetic material exhibits ordered magnetic domains, leading to a stronger magnetization current, while the magnetic field’s intensity directly impacts the magnitude of this current. Currently, there is relatively limited research on the enhancement of TENG performance through the magnetization current. While all of these techniques can enhance a magnetic TENGs’ output performance, there is still potential to maximize output performance through structural design. 5.2. Durability Enhancement Magnetic materials possess strength and wear resistance, allowing them to maintain their magnetic properties and structural stability even after multiple stress and friction cycles, thereby improving the reliability and lifespan of TENGs. Durability is an important parameter in practical applications of TENGs. Frictional materials may experience certain wear during long-term bending and stretching, so improving the stability of TENGs requires considering the material’s wear resistance. The repulsion between magnets can also enhance the material’s fatigue resistance. Additionally, in different environments, temperature, humidity, ion concentration, and physical fields can reduce the durability of TENGs. Therefore, materials with certain resistance capabilities and non-contact encapsulation of TENGs can be considered. Magnetic materials can be used to control enclosed TENGs through a magnetic field, converting mechanical energy into electrical energy. Enclosed TENGs operate under constant humidity and ion concentrations, allowing non-contact TENGs to provide a stable output of electrical energy. 5.3. Multifunctionality Multifunctionality holds significant value in practical applications, as it can boost the output performance of TENGs in various ways. TENG sensors with multifunctionality can also analyze complex environments and obtain multiple sets of data. Magnetic materials not only serve as critical components of TENGs but also can be used to secure and guide non-magnetic materials, thereby increasing the efficiency of mechanical energy conversion. Furthermore, magnetic materials can regulate the output voltage and frequency of the generator by altering their physical properties, thereby controlling the power generation performance. The self-powered multifunctional sensor (MS) indicated above has the ability to sense acceleration, rotational parameters, and force. This TENG consists of a low-damping magnetic column and a PTFE film. The mechanism drives the electrodes to produce voltage output by converting translational motion into multiturn or swinging rotational movement of the magnetic column surrounding the PTFE film. Parameters of force and acceleration can be determined by extracting the amplitude, frequency, and some time characteristics from the output waveform. In the sliding mode, these miniature devices can be applied to equipment such as robots, drones, and aircraft that require motion parameters, thereby enhancing the sensitivity of the devices. This represents a significant advancement in this field. 5.4. Expansion of Application Scenarios Magnetic materials possess magnetic properties that are not found in other materials, and there is a close relationship between magnetism and electricity. Therefore, by employing rational structural design, magnetic materials can not only enhance the output performance of TENGs but also boost their ability to sense magnetic fields. This has led to the development of self-powered sensors capable of sensing magnetic fields and magnetic minerals. Additionally, different magnetic materials can provide further assistance to TENGs and sensors in a variety of domains, such as energy, biology, medicine, flexible electronics, and the IoT, offering significant research opportunities. It is hoped that this summary will offer readers a thorough grasp of the present magnetic TENGs and act as a source of inspiration for robotics and internet research in the future.",
"introduction": "1. Introduction Given the continuous growth of the global energy demand, people are increasingly concerned about the sustainability and renewability of energy [ 1 , 2 ]. The limited nature of traditional energy sources and their impacts on the environment make the development of new energy sources a top priority [ 3 ]. In the pursuit of new energy sources, TENGs have emerged as one of the highly anticipated energy-converting technologies on the basis of the coupled effects of triboelectric charging and electrostatic induction [ 4 , 5 ]. An interaction between two distinct frictional electrode materials results in the generation of frictional charges on their surfaces, as well as the conversion of mechanical energy into electrical potential in the event of additional electrostatic induction. TENGs can convert small mechanical energies from human body movements [ 6 , 7 , 8 , 9 , 10 , 11 , 12 ], breezes [ 13 , 14 , 15 ], rotations [ 16 ], sound waves [ 17 , 18 , 19 ], water waves [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ], and other sources into electrical energy for various wearable electronics [ 29 ]. TENGs possess high flexibility and portability, allowing them to be embedded into various devices and systems, and providing them with self-sustaining power sources. This technology holds great potential for applications in precision instruments [ 30 , 31 , 32 , 33 ], wearable devices [ 34 , 35 , 36 ], chemical reactions [ 37 , 38 , 39 ], sensors [ 40 , 41 , 42 , 43 ], and other portable personal electronic products [ 44 , 45 , 46 ]. It not only provides continuous and stable energy for these devices but also has the potential to reduce reliance on traditional batteries to some extent, thereby minimizing electronic waste generation and promoting environmental friendliness [ 47 , 48 ]. Therefore, as an innovative energy technology, TENGs offer a more sustainable and eco-friendly energy solution for humanity [ 49 , 50 , 51 ]. Science and technology are thought to have the potential to play a significant role in the future energy sector, providing our intelligent society with more convenience and sustainability as a result of ongoing advancements and the growth of their applications. At present, magnetic materials are showing their potential for the design of high-performance TENGs due to their high magnetic conductivity, stability, adjustable magnetism, and controllable magnetic fluid properties [ 52 , 53 , 54 ]. Adding magnetic materials to TENGs improves their energy conversion effectiveness, stability, and longevity while also expanding their controllability and adaptability [ 55 , 56 , 57 , 58 , 59 ]. Currently, magnetic materials, including neodymium iron boron (NdFeB), nickel ferrite (NiFe 2 O 4 ), and iron oxide, can be used in TENGs to harness mechanical energy from sources such as wind [ 55 , 56 ], magnetic fields [ 57 ], finger bending [ 58 ], water flow [ 59 ], and compression [ 57 ]. These TENGs have been extensively studied in various applications, including self-powered sensors [ 60 ], robots [ 61 ], flexible wearable devices [ 62 ], and self-powered integrated systems [ 63 ]. Moreover, the variation in frictional electric output induced by mechanical or magnetic stimulation can be directly utilized as sensing signals, thereby introducing self-powered sensors based on TENGs. Therefore, self-powered intelligent systems can be developed in various fields, including the Internet of Things [ 64 , 65 ], flexible devices [ 66 ], drug delivery [ 67 ], and self-propelled robots [ 61 ]. On the basis of predecessors, this paper more fully summarizes the application of magnetic materials in TENGs and self-powered sensors. The investigated magnetic materials include a variety of soft ferrites, hard magnetic materials, and composite magnetic materials. In addition to discussing the most promising options at the moment and outlining new strategies to build more intelligent and multifunctional magnetic TENGs, we also review the current state of development of magnetic TENGs and prospects for enhancing their energy conversion performance. Additionally, this article explores the incorporation of TENGs as power sources for external sensors and provides a brief overview of the self-powering applications in various related fields, as depicted in Figure 1 . Finally, the challenges and prospects of applying magnetic materials in TENGs are discussed.\n\n3.2.1. Introduction to Soft Magnetic Materials Soft magnetic materials refer to materials that cannot maintain magnetism for a long time after magnetization. Soft magnetic materials have very small residual magnetism and coercivity (less than 1000 A/m), and ferrite is the main soft magnetic material used in TENGs ( Table 2 ). Soft magnetic materials have a wide range of applications in sensors [ 98 , 99 ], transformers [ 100 ], relays [ 101 ], and motors [ 102 ]."
} | 3,219 |
39731138 | PMC11681767 | pmc | 5,356 | {
"abstract": "The biological production of lipids presents a sustainable method for generating fuels and chemicals. Recognized as safe and enhanced by advanced synthetic biology and metabolic engineering tools, yeasts are becoming versatile hosts for industrial applications. However, lipids accumulate predominantly as triacylglycerides in yeasts, which are suboptimal for industrial uses. Thus, there have been efforts to directly produce free fatty acids and their derivatives in yeast, such as fatty alcohols, fatty aldehydes, and fatty acid ethyl esters. This review offers a comprehensive overview of yeast metabolic engineering strategies to produce free fatty acids and their derivatives. This study also explores current challenges and future perspectives for sustainable industrial lipid production, particularly focusing on engineering strategies that enable yeast to utilize alternative carbon sources such as CO 2 , methanol, and acetate, moving beyond traditional sugars. This review will guide further advancements in employing yeasts for environmentally friendly and economically viable lipid production technologies.",
"conclusion": "Conclusion The biological production of FFAs and their derivatives, such as fatty alcohols and alkanes, is essential for sustainable industrial processes. Metabolic engineering of yeasts has already achieved notable successes in producing FFAs, highlighting the importance of tailored metabolic engineering strategies for each yeast strain. Additionally, the utilization of low-carbon compounds such as CO 2 and methanol is increasingly vital for sustainable industrial production. Therefore, refining metabolic pathways to convert these compounds into FFAs is crucial. Ongoing advancements in synthetic biology, omics analysis, and systems metabolic engineering will enable sustainable and large-scale industrial production of FFAs and their derivatives.",
"introduction": "Introduction The relentless expansion of petroleum-based industries has exacerbated greenhouse gas emissions, contributing significantly to environmental issues such as climate change. This ongoing environmental degradation highlights the urgent necessity for a shift toward more sustainable industrial practices to mitigate their adverse effects on our lives. Advancements in metabolic engineering and synthetic biology have led to the rise of microorganism-based industries as practical alternatives. These technologies have led to the inception of the production of diverse industrial products by converting greenhouse gases and C1 compounds such as CO 2 , CH 4 , and green methanol. This approach not only leverages bioconversion technologies but also plays a crucial role in mitigating environmental greenhouse gas emissions, addressing key challenges in sustainability [ 1 , 2 ]. Free fatty acids (FFAs) are critically important across various industries, serving as the preferred precursors for synthesizing a range of fatty acid derivatives. A notable characteristic of FFA is their straightforward conversion into a diverse spectrum of biofuels, which further underscores the role of FFA in advancing sustainable energy solutions. Biodiesel, the most well-known and commercially produced biomass-derived diesel fuel, consists of mono-alkyl esters of long-chain fatty acids. Traditionally, biodiesel is synthesized from plant oils via chemical transesterification—a process that is becoming problematic for large-scale commercial viability due to the cost and availability of feedstocks. Moreover, a surplus of alcohol is frequently necessary to drive the reaction towards near completion, further increasing production costs. In response, recent efforts have focused on directly producing fatty acid ethyl esters (FAEEs) in vivo to create more sustainable forms of biodiesel [ 3 – 5 ]. Yeast engineering has extended efforts to produce other FFA-based products, such as fatty alcohols (FAs) and fatty alkanes (FALKs) directly in vivo. FAs, long-chain hydrocarbons with over ten carbon atoms and a terminal –OH group, are utilized in various applications, including lubricants, surfactants, cosmetics, pharmaceuticals, agricultural chemicals, plastic polymerization agents, textile coatings, personal care commodities, mineral processing substances, and fuels [ 6 ]. Another vital class of hydrocarbons is FALKs, which are utilized as primary liquid fuels for transportation and in the manufacturing of plastics, being key components of petrol, diesel, and jet fuel. Terminal alkenes, also known as olefins, possess a high energy density and exhibit comparable storage, transportation, and combustion properties to current liquid transportation fuels, rendering them advantageous for synthesizing polyethylene, lubricants, and detergents [ 7 ]. Yeast-based platforms have attracted significant attention due to progress in metabolic engineering and synthetic biology, along with the designation of several yeast species under the Generally Recognized as Safe (GRAS) status. Among various yeast species, Saccharomyces cerevisiae and Yarrowia lipolytica have been widely studied for producing fatty acid-derived hydrocarbons. S. cerevisiae is valued for its robustness, capable of thriving in low pH and challenging environmental conditions, and is well-equipped with genetic tools that facilitate metabolic engineering [ 8 , 9 ]. Numerous studies with S. cerevisiae engineering have been conducted to produce biofuels such as bio-ethanol. Y. lipolytica , known for oleaginous yeast, has attracted significant interest due to its ability to accumulate high lipid content [ 10 ]. Recently, Rhodosporidium toruloides , another oleaginous yeast, has shown promising results in the production of FFA and FAEE [ 11 , 12 ]. Additionally, the ability of methylotrophic yeasts to metabolize methanol has opened new avenues for research, with multiple studies exploring the potential of engineered yeasts to transform methanol and CO 2 into lipids [ 13 , 14 ]. Pichia pastoris and Ogataea polymorpha , methylotrophic yeasts, have demonstrated their efficacy in producing fatty acid-derived hydrocarbons from sustainable one-carbon (C1) feedstock methanol [ 15 – 17 ]. The use of yeast platforms for synthesizing fatty acids and their derivatives thus holds significant promise for advancing sustainable industrial processes. This review comprehensively examines the recent advancements in metabolic engineering strategies designed to enhance the biosynthesis of fatty acids and their derivatives (FA, FAEE, and FALK) in yeast. Additionally, this review aims to introduce strategies for metabolizing CO 2 and methanol in yeast and to discuss lipid metabolism approaches. It will also present effective strategies for future research on lipid production based on C1 compounds, illustrating the potential advancements in yeast-based biotechnological applications contributing to an environmentally friendly and renewable energy future. Metabolic engineering strategies for free fatty acid (FFA) production In microbial systems, lipids are typically stored as triacylglycerides (TAGs), which limits their direct usability. However, compared to TAGs, FFAs are critical precursors for the synthesis of a wide variety of compounds for extensive industrial applications. Therefore, biologically deriving FFAs presents a highly feasible and economically viable method. This chapter summarizes the metabolic engineering strategies for producing FFAs in yeast (Fig. 1 ; Table 1 ). \n Fig. 1 A schematic overview of metabolic engineering strategies for producing FFAs in yeasts. Glucose, methanol, CO 2, and its derivative formate represent the initial carbon source. Overexpressed genes and knocked-out genes are shown in blue and red, respectively. Abbreviations: ACC1, acetyl-CoA carboxylase; ACL, ATP: citrate lyase; ACS, acetyl-CoA synthetase; ARE, sterol acyltransferases; CBB cycle, Calvin-Benson-Bassham cycle; CTP, citrate transporter; DAG, diacylglycerol; DAS, dihydroxyacetone synthase; DGA, diacylglycerol acyltransferases; DHA, dihydroxyacetone; FAA/FAT, fatty acyl-CoA synthetases; FAS, fatty acid synthetases; FDH, formate dehydrogenase; G3P, glyceraldehyde 3-phosphate; GapN, glyceraldehyde-3-phosphate dehydrogenase; GPD, glycerol-3-phosphates; LRO, diacylglycerol acyltransferase; MDH, malate dehydrogenase; ME, malic enzyme; MFE, multifunctional enzymes; 3PG, 3-phospho-glycerate; PAH/LPP/DPP/APP, phosphatidate phosphatases; PDH, pyruvate dehydrogenase; PEX10, peroxisome synthetase; PL, phospholipid; POX, peroxisomal acyl-CoA oxidase; PRK, phosphoribulokinase; PXA, peroxisomal acyl-CoA transporter; Pyr, pyruvate; SE, sterol esters; RuBisCO, ribulose 1,5-bisphosphate carboxylase/oxygenase; RuBP, ribulose 1,5-bisphosphate; TAG, triacylglycerol; TE/ACOT5/RnTEII/‘TesA, thioesterases; TGL, triacylglycerol lipases; Xu5P, xylulose 5-phosphate; XuMP cycle, xylulose monophosphate cycle \n \n Table 1 Summary of metabolic engineering strategies for free fatty acid production in yeasts Strain Metabolic engineering strategies Medium and carbon sources Results Fatty acid composition (%) References \n Yarrowia lipolytica \n Overexpression of DGA2 , TGL4 and KlTGL3 ; deletion of FAA1 and MFE1 YNB, glucose 2.8 g/L (batch), 10.4 g/L (fed-batch) C16:0, C16:1, C18:0, C18:1, C18:2 [ 27 ] Overexpression of RnTEII ; deletion of DGA1 , DGA2 , LRO1 , ARE1 , FAA1 and MFE1 YNB, glucose 3 g/L (batch) C16:0, C16:1, C18:0, C18:1, C18:2 [ 27 ] Overexpression of truncated hFAS-EcTesA ′ YNB, glucose 1.3 g/L (batch), 9.67 g/L (fed-batch) C12:0 (7.5%), C14:0 (29.2%), C16:0, C16:1, C18:0, C18:1, C18:2 [ 24 ] Overexpression of ACC1 ; deletion of GPD1 , GUT2 and PEX10 YNB, glycerol and glucose 2 g/L (batch) C16:0 (9.6%), C16:1 (9.8%), C18:0 (6.9%), C18:1 (46.7%), C18:2 (20.4%), C20:0 (0.7%), C22:0 (0.7%), C24:0 (4.1%) [ 23 ] Overexpression of MaC16E , CDS1 , PSD1 , CHO2 , OPI3 , and CpFAH12 ; deletion of MEF1 , PEX10 , FAD2 , PAH1 , APP1 , MHY1 , and DGA1 YNBR, glucose 2 g/L (batch) C18:1-OH, (74%), C18:2 (11%), C16:0, C16:1, C18:0, C18:1 (15%) [ 28 ] \n Saccharomyces cerevisiae \n Overexpression of ACC1 , FAS1 , FAS2 and ‘TesA ; deletion of PXA2 , POX1 , FAA1 and FAA4 MM, glucose 400 mg/L (batch) C12:0 (2.7%), C14:0 (9.4%), C16:0 (47.0%), C16:1 (19.3%), C18:0 (10.4%), C18:1 (10.7%) [ 25 ] Overexpression of ACOT5 ; deletion of FAA1 and FAA4 YNBD, glucose 500 µg/ml (batch) C16:0, C16:1, C18:0, C18:1 [ 21 ] Overexpression of DGA1 and TGL3 ; deletion of FAA1 , FAA2 , FAA4 , FAT1 , PXA1 and POX1 YPD, glucose 2.2 g/L (batch) C16:0, C16:1, C18:0, C18:1 [ 29 ] Overexpression of CTP1 , RtME , MDH3 , MmACL , RtFAS , ACC1 and ‘ TesA ; deletion of HFD1 , FAA1 , FAA4 and POX1 MM, glucose 1 g/l (batch), 10.4 g/l (fed-batch) C16:0, C16:1, C18:0, C18:1 [ 22 ] Overexpression of the cPDH and GapN ; and deletion of GPD1 , GPD2 , PAH1 , LPP1 , DPP1 and ARE1 MM, glucose 840.5 mg/L (batch) C16:0, C16:1, C18:0, C18:1 [ 20 ] Overexpression of FDH and CBBm MM, CO 2 , formate, and glucose 10.1 g/L (fed-batch) C16:0, C16:1, C18:0, C18:1 [ 30 ] Overexpression of ACS and FDH MM, acetate, glucose and formate 6.6 g/l (fed-batch) C16:0, C16:1, C18:0, C18:1 [ 31 ] \n Starmerella bombicola \n Deletion of FAA1 and MFE2 Lang production media, glucose 0.933 g/L (batch) C16:0 (13.2%), C18:0 (40%), C18:1 (43.8%) [ 32 ] \n Pichia pastoris \n Overexpression of MmACL , DAS2 , XFPK , ScIDP2 and PTA ; deletion of FAA1 and FAA2 MM, methanol 5.1 g/L (batch), 23.4 g/L (fed-batch) C16:0, C16:1, C18:0, C18:1, C18:2 [ 15 ] \n Ogataea polymorpha \n Overexpression of FBP1 , RPE , MmACL , ZWF1 , ScIDP2 , AOX1 , DAS and DAK ; deletion of FAA1 , LPL1 and IZH3 MM, methanol 15.9 g/L (fed-batch) C16:0 (30–40%), C16:1 (< 5%), C18:0 (< 5%), C18:1 (20–30%), C18:2 (30–40%) [ 16 ] \n Enhancement of acetyl-CoA and malonyl-CoA pools Acetyl-CoA and malonyl-CoA are crucial intermediates in the biosynthetic pathway of fatty acids (Fig. 1 ). A pyruvate dehydrogenase (PDH) complex plays a role in converting pyruvate to acetyl-CoA [ 18 , 19 ]. The conversion of acetyl-CoA to malonyl-CoA, catalyzed by acetyl-CoA carboxylase ( ACC), marks the beginning of fatty acid synthesis. Malonyl-CoA acts as the two-carbon donor in the chain-elongation process of fatty acid synthesis, which continues until the desired chain length is achieved. Zhang et al. (2020) demonstrated that introducing the cytosolic pyruvate dehydrogenase ( cPDH ) complex from Enterococcus faecalis into S. cerevisiae significantly enhanced the cytosolic acetyl-CoA pool, resulting in an enhanced FFA production. In this study, while a parental strain of S. cerevisiae (Δ FAA1/4 , Δ POX1 , Δ HFD1 ) produced FFA at 458.9 mg/L, the introduction of the PDH protein complex increased the FFA titer to 512.7 mg/L [ 20 ]. Additionally, ACC1 overexpression can enhance malonyl-CoA pools and subsequently increase FFA titers in yeast [ 21 – 24 ]. In an engineered strain of Y. lipolytica (Δ GPD1 , Δ GUT2 , Δ PEX10 ), the initial FFA production was quantified at a level of 382.8 mg/L. However, the overexpression of ACC1 significantly increased the titer to 1436.7 mg/L, representing a 3.7-fold enhancement in comparison to the parental strain [ 23 ]. Zhou et al. (2016b) replaced the native promoter of the ACC1 gene with the strong TEF1 promoter in S. cerevisiae , resulting in the production of 10.4 g/L of FFAs, while the parental strain (Δ POX1 , Δ Faa1/4 , Δ HFD1 , ‘ TesA ↑, RtFAS ↑) produced only 7.0 g/L [ 22 ]. Directing fatty acyl-CoA to FFAs production with the inhibition of TAG, SE, and phospholipid synthesis The conversion of malonyl-CoA to fatty acyl-CoA is a critical step in fatty acid synthesis, where each elongation cycle adds two carbons to the growing fatty acyl chain (Fig. 1 ). The fatty acid synthetase ( FAS1 and FAS2 ) elongates this carbon chain, ultimately forming fatty acyl-CoA, a direct precursor for FFAs. Heterologous type-I FAS from Brevibacterium ammoniagenes ( baFAS ) (Eriksen et al., 2015), Rhodosporidium toruloides FAS ( RtFAS1 and RtFAS1 ) [ 22 ] or endogenous FAS1 / FAS2 from S. cerevisiae [ 25 ] were employed to enhance fatty acyl-CoA production. For instance, the expression of baFAS in the ΔFAS1 S. cerevisiae strain resulted in a 2.75-fold increase in palmitic acid production compared to the parental strain [ 26 ]. Thioesterases play a pivotal role by converting fatty acyl-CoA into FFAs, thereby inhibiting their storage as TAGs or sterol esters (SEs). A truncated version of acyl-CoA thioesterase ( Acot5s ) from Mus musculus was expressed in the cytoplasm of S. cerevisiae , resulting in improved FFA synthesis, achieving up to 500 µg/mL in batch cultivation [ 21 ]. The overexpression of E. coli acyl-ACP thioesterase ‘TesA in S. cerevisiae resulted in the production of 5 mg/L of FFAs, an 8-fold increase in comparison to the background strain [ 25 ]. Zhou et al., (2016b) also overexpressed ‘tesA in S. cerevisiae , which resulted in the production of 0.67 g/L FFA [ 22 ]. In Y. lipolytica , coupling the overexpression of FAS1 with thioesterase from E. coli led to production levels reaching 1.3 g/L in shake flasks and up to 9 g/L in bioreactors [ 24 ]. An engineered strain of Y. lipolytica (Δ ARE1 , Δ DGA1 / 2 , Δ LRO1 , Δ FAA , Δ MFE1 ), lacking neutral lipid synthesis pathways (TAG/SE), significantly increased FFA production from 730 mg/L to 3 g/L upon overexpressing a cytosolic thioesterase from Rattus norvegicus ( RnTEII ) [ 27 ]. In Y. lipolytica , the production of ricinoleic acid (RA) via the cytidine diphosphate diacylglycerol (CDP-DAG) pathway was achieved by regulating lipid flux towards the phosphatidylcholine (PC) and oleic acid (OA) pool. This enhancement began with the overexpression of the CpFAH12 encoding fungal Δ12 oleate hydroxylase from Claviceps purpurea , combined with the deletion of the TAG synthesis pathway (Δ DGA1 ). Further amplification of the phospholipid pool was achieved by overexpressing several key genes: CDS1 (phosphatidate cytidylyltransferase), PSD1 (phosphatidylserine decarboxylase), CHO2 (phosphatidylethanolamine N-methyltransferase), and OPI3 (phosphatidyl-N-methylethanolamine N-methyltransferase). Finally, the overexpression of fatty acid elongase from Mortierella alpine ( MaC16E ) led to 2.061 g/L RA acid production [ 28 ]. FFAs can also be generated by remodeling TAGs, where triacylglycerol lipases ( TGL ) break down TAGs into FFAs. In S. cerevisiae , a genetically modified strain co-overexpressing TGL3 and DGA1 produced up to 2.2 g/L of extracellular FFAs [ 29 ]. Similarly, in Y. lipolytica , employing a comparable engineering strategy involving the overexpression of TGL3 , TGL4 , and DGA2 achieved a FFAs production level of 2.8 g/L [ 27 ]. Additionally, the complete elimination of phospholipid synthesis from FFAs through the deletion of phosphatidate phosphatase genes ( PAH1 , APP1 , DPP1 , LPP1 ) further enhanced FFA production [ 20 , 28 ]. Inhibition of beta-oxidation Blocking competing metabolic pathways is a general approach to direct and enhance the carbon flux towards desired products. Thus, one of the critical strategies for FFA production involves eliminating the β-oxidation pathway, which naturally degrades fatty acids into acetyl-CoA in the peroxisome, thereby preventing the potential recycling of FFAs into unwanted metabolic products (Fig. 1 ). In the β-oxidation cycle, the peroxisomal acyl-CoA transporter ( PXA1 ), POX1 , and multifunctional enzymes (encoded by MFE1 , MFE 2) have been mainly targeted for deletion. Additionally, inhibiting peroxisome synthesis through the deletion of peroxisome synthetase ( PEX10) , which is crucial for peroxisome biogenesis, prevents FFAs from being converted into β-oxidation products [ 23 , 28 ]. Further measures include disrupting fatty acyl-CoA synthetases, namely FAA1 , FAA2 , FAA4 , and FAT1 . These genes are responsible for converting FFAs back into fatty acyl-CoA, and their inhibition is vital for ensuring that fatty acids are not recycled in the β-oxidation cycle but instead accumulate as FFAs [ 20 – 22 , 24 , 27 , 29 – 32 ]. Deleting these enzymes makes it possible to prevent the reconversion process of fatty acid, thus promoting the accumulation of FFAs instead of their re-utilization as fatty acyl-CoA. However, the reduction of the β-oxidation was synergetic when it was applied to other FFA enhancement strategies. Thus, this strategy is not usually used solely. Enhancing cofactor (NADPH) supply The synthesis of fatty acids in yeast critically relies on an adequate supply of NADPH, which acts as a reducing equivalent. This cofactor is pivotal for the reductive steps that transform acetyl-CoA and malonyl-CoA into longer-chain fatty acids. Specifically, NADPH supplies the necessary electrons for the reduction reactions catalyzed by the fatty acid synthase complex (FAS). This complex condenses acetyl-CoA and malonyl-CoA into acyl-CoA. Each step in this elongation process requires two molecules of NADPH to reduce the carbonyl group of the acyl intermediates, thereby enabling further chain extension. Consequently, a deficiency in NADPH can significantly hinder the production of fatty acids [ 10 , 33 , 34 ]. Thus, various NADPH-dependent enzymes involved in lipid synthesis have been employed for metabolic engineering. Chen et al. (2016) overexpressed NADP + -dependent aldehyde dehydrogenase to enhance the cellular pool of NADPH. Indeed, this augmentation supports fatty acid synthesis by providing a robust supply of reducing equivalents [ 9 ]. The introduction of NADP + -dependent glyceraldehyde-3-phosphate dehydrogenase ( GapN ) from Streptococcus mutans enabled the irreversible conversion of glyceraldehyde-3-phosphate to 3-phosphoglycerate, thereby producing NADPH. This modification enhanced the production of FFA and FAEE while reducing glycerol synthesis [ 20 , 35 ]. Another strategic modification in S. cerevisiae involved redirecting carbon flux towards glutamate biosynthesis by deleting the NADPH-dependent glutamate dehydrogenase ( GDH1 ). This change significantly improves NADPH availability, increasing the FFA pool for FA synthesis [ 36 ]. In Y. lipolytica , the use of a microbial electrosynthesis (MES) system proved effective in converting electrons directly into NADPH, resulting in a 2.79-fold increase in the NADPH/NADP + ratio and enhancing the production of FAs from acetate [ 37 ]."
} | 5,145 |
28555623 | PMC5459945 | pmc | 5,358 | {
"abstract": "Modifications made during metabolic engineering for overproduction of chemicals have network-wide effects on cellular function due to ubiquitous metabolic interactions. These interactions, that make metabolic network structures robust and optimized for cell growth, act to constrain the capability of the cell factory. To overcome these challenges, we explore the idea of an orthogonal network structure that is designed to operate with minimal interaction between chemical production pathways and the components of the network that produce biomass. We show that this orthogonal pathway design approach has significant advantages over contemporary growth-coupled approaches using a case study on succinate production. We find that natural pathways, fundamentally linked to biomass synthesis, are less orthogonal in comparison to synthetic pathways. We suggest that the use of such orthogonal pathways can be highly amenable for dynamic control of metabolism and have other implications for metabolic engineering.",
"discussion": "Discussion In this paper, we provide an alternative perspective to the problem of designing pathways and strains for metabolic engineering. In contrast to the prevalent approach of growth-coupled designs, we suggest that orthogonal pathway design coupled with DME might be effective for de novo strain design. This idea of orthogonality is closely related to modularity, which has been well studied for metabolic networks 21 22 23 , and used for metabolic engineering 24 25 26 . While, the central metabolism of E . coli is highly connected and robust, elements of it do behave as modular subsystems. Amino-acid biosynthesis control is one such example that allows the cells to be stable in the presence of varying environmental conditions 27 . Regulation at the beginning and end of these subsystems allows cells a control mechanism well suited for robust growth. Orthogonality principles can be thought of as modular subsystems for chemical production that minimize total interactions with the natural cellular metabolism, and that can be achieved through synthetic pathways for substrate utilization. When traditional metabolic engineering aims to repurpose cellular metabolism for chemical production, it does so within the evolutionary disposition for growth known as growth coupling. However, the organization of this network structure follows principles of optimality different from those that metabolic engineers would attribute to be optimal for chemical production. We have shown efficient chemical production requires an optimality principle outside the scope of a cellular growth objective, which, akin to elements of metabolism such as amino-acid biosynthesis, require modular and independent subsystems in the cell, and a robust control mechanism over them. In this work, these subsystems can be measured by the ability of the metabolic network to perform two separate tasks (growth and chemical production). The orthogonality score measures this ability by calculating a ‘distance' metric in the metabolic flux space for these two tasks. A determinant of orthogonality is the overlap of the reactions that support biomass production and the chemical production pathways. A key finding of our work is that native glucose utilization pathways are not orthogonal for succinate and several other products (for example, 1,4-butanediol) due to this overlap. Further analysis reveals that this non-orthogonality is largely due to the generation of phosphorylated metabolites and the individual biomass precursor metabolites in these native pathways that are valuable for biomass production, but are not essential for substrate utilization in the chemical production modes. In the Supplementary Note 2 , we expand on several additional case studies that support these findings. We found that, by contrast, the catabolism of most orthogonal pathways lacked phosphorylation reactions. We found both glucose and xylose to be structurally more efficient for product formation when they were not phosphorylated. These types of non-phosphorylated pathways are sometimes observed naturally in microbes, although they are not common. These pathways typically do not involve substrate-level phosphorylation, are less energy-efficient and dissipate more free energy, thereby providing a higher thermodynamic driving force than conventional pathways. This is an important aspect of the flux capacity of metabolic pathways. There are two significant benefits for bypassing biomass precursors: (1) Pathways produce higher yields because they avoid carbon losses associated with precursor synthesis. For example, the generation of metabolites of the pentose phosphate pathway results in carbon loss through zwf . (2) Orthogonal pathways implicitly bypass regulation as the biomass precursors tend to be highly regulated. For example, fructose-1-6-bisphosphate has been demonstrated to be a metabolic ‘flux sensor' important to the control of glycolytic flux 28 . Other such metabolites also act to regulate the cell, and changes in their concentration have ripple effects through several metabolic pathways. Hence, synthetic orthogonal pathways offer a metabolic solution to a complicated regulatory problem. The significance of a flux sensor in natural metabolism is an important consequence for metabolic engineering. Glycolytic flux during stationary phase often ceases due to the accumulation or draining of intracellular metabolites, which are recognized by these flux sensors, and play a role in reducing glycolytic flux 28 . Hence, most chemical production in industry is carried out using a fed-batch process, where the goal is to engineer a high glycolytic flux during stationary phase by targeting the regulatory network 29 . Orthogonal pathways rely on these same principles of using a thermodynamic driving force for conversion, but avoid the necessary challenges of targeting regulatory networks. We also uncovered that orthogonality principles rest on the pairing of an input substrate and the product. Accordingly, engineering pathways de novo for a given substrate–product pair is a better approach to metabolic engineering than depending on pathways that consume glucose for any and all biochemical products. The diversification of feedstocks away from glucose, syngas, methane, methanol and glycerol, supports our idea 30 31 32 33 34 . Our framework applies principles of orthogonality to design metabolic processes that are tailored for the conversion of a specific substrate to a product in the most efficient way possible. Our work also has important applications for DME. Conceptually, DME has gained quite a bit of attention 35 36 , and shown early promise 37 38 39 40 41 42 43 44 . Several studies have utilized strategies for controlling pathway flux to improve yields using inducible systems and circuits, as well as metabolic sensors connected to synthetic cell circuits 39 45 . However, adapting these early successes to high yielding industrial strains has yet to be shown. The balancing of gene expression in DME, through multi-gene control, is among the many challenges. In a typical highly regulated network, this requires global coordination of metabolism. Studies employing the use of synthetic circuits to control several genes seem to be limited over the number of genes they are capable of accurately controlling. Our analysis suggests that orthogonal pathway design may be a key to experimentally realizing this in industrial strains. The orthogonal design proposed here reduces the number of interactions within metabolism and facilitates a two-stage fermentation strategy. It achieves the goal of circumventing the complex regulatory, enzymatic and metabolomic changes by controlling the flux towards biomass precursors via a metabolic control valve. Importantly, two-stage fermentation (or growth-uncoupled production) is typically used in commercial bioprocesses for large-scale chemical production despite the fact that so many strain design algorithms are focused on growth coupling. In this regard, our framework provides a direct route to translate lab-scale designs to commercial strains without first developing growth-coupled strains that are not suited for two-stage industrial production. It is worthwhile noting that nutrient-based valves can exist, and there have been demonstrations of such valves including the use of oxygen 46 , nitrogen 47 and phosphate 48 limitations. For instance, oxygen-based nutrient valves have been observed in two-stage fermentation for succinic acid production, and nitrogen limitation has been used to produce citrate. However, computational strain design and early strain development has conventionally been guided by a growth-coupled approach. Hence, we have proposed a computational approach to design valves for DME and suggest that future research could focus on even more efficient methods for the design of metabolic control valves based on orthogonal pathways. The recent focus in metabolic engineering has been the design and use of complex synthetic circuits to control gene expression (for example, via a synthetic toggle switch 42 49 ). In light of these approaches, our work has been to understand how reworking the design of the central metabolism may allow the simplification of these circuits, so that rather than employing a multi-gene control, it may be possible to achieve the desired production target(s) by manipulating a single gene. Of course, it is conceivable that these gene-level valves could be combined with the valves related to nutrient uptake to provide an additional layer of flexibility in controlling metabolism. Finally, implementation of synthetic substrate utilization pathways is not common. However, a growing body of successful experimental studies supports the value of such synthetic pathways 50 51 52 . This strategy has been recently applied for the design of a synthetic ED pathway in E. coli 12 . Our approach formalizes the advantages of such synthetic pathways, and provides a systematic framework for introducing synthetic orthogonal pathways for metabolic engineering. One of the many challenges that we do not explicitly consider in our current analysis are protein-level interactions of orthogonal pathways. These include enzyme-level inhibition by cofactors or cellular metabolites. The issue of promiscuity of enzymes within metabolism is also another issue that needs consideration. Nevertheless, these are issues that are currently confronted and addressed by almost any metabolic engineering design approach during the scale-up of high-yield strains. Hence, these issues are not a new task for metabolic engineers. Most importantly, to our knowledge, this work represents the first time that the role that substrate utilization has on metabolic engineering and chemical production has been evaluated, outside of pathway yield. In the introduction, we had noted that cellular metabolism has been shaped by evolutionary forces for cell growth and survival, objectives which are at odds with chemical production. To understand how ‘far' apart metabolism is between growth and chemical production, we have proposed a mathematical framework for systematically evaluating this distance. In some cases, chemical production can be satisfactorily obtained by natural pathways, but more often it is useful to engineer synthetic pathways for substrate utilization. In conclusion, we derive principles for metabolite production using pathways that interact as little as possible with the cell's natural metabolism. Taken together, we believe our work bridges the current methodologies of strain design at the lab scale to the design of industrial growth-independent production strains that are necessary to satisfy key fermentation metrics that make bio-production a financially viable process 53 54 . The development of industrial microbial strains typically focuses on improving flux through the central metabolism under the assumption that efficient growth pathways are also valid for product synthesis. Studies have shown that more efficient chemical production can be achieved when heterologous enzymes are engineered into the cell to bypass certain biomass precursors. Our work extends these circumstantial observations into a formal mathematical framework and shows that full pathways that avoid many biomass precursors can produce chemicals through optimal network structures."
} | 3,107 |
38187193 | PMC10767161 | pmc | 5,361 | {
"abstract": "Summary Cephalopods are remarkable creatures, captivating scientists with their advanced neurophysiology, complex behavior, and miraculously effective camouflage. Research into cephalopods has led to many discoveries in neuroscience, cell biology, and materials science. Specifically, squids provide us with remarkable self-healing Squid Ring Teeth protein, which is applied herein to extend the life span of foams. Despite the advantages of porosity in surface science applications, porosity impairs mechanical properties by making materials more prone to structural damage –which traditional polymeric foams also suffer from. Drawing inspiration from Squid Ring Teeth, we developed self-healing tandem repeat proteins to overcome these challenges. By leveraging porosity and self-healing properties inspired by Squid Ring Teeth, we created bioengineered protein foams with high separation capacity (5.1 g g −1 ) and efficiency (≈94%). The foams healed entirely within minutes which regained over 100% strength after repair. These advances promise applications for efficient continuous water treatment through durable filter cartridges.",
"introduction": "Introduction Self-healing is a remarkable natural phenomenon that allows organisms to repair internal or external damages and prolong their lives. The adaptive capabilities of organisms have enabled them to survive and thrive despite obstacles, such as external physical damage. 1 Yet, at the cellular level, lies a prowess empowering life for millennia – self-healing. With this intrinsic and involuntary cellular process, living things can cope with their environment while maintaining sustainability. Scientists from many disciplines seek ways to harness this desirable capability by promising cost-effectiveness through longer product lifespans and greater environmental resilience. 2 , 3 Despite significant attention toward developing self-healing polymers in recent years, many of these materials still suffer from low repair strength or slow healing times. However, diverse strategies to create advanced polymeric systems with enhanced qualities are still under development. 3 While scientists have focused primarily on analyzing such creations with synthetic polymers, there is much room for innovation in bioengineered proteins that could revolutionize material engineering as we know it today. Nature has an incredible ability to heal itself, even in the smallest of pores. We see this with bones and exoskeletons in animals and wood in plants - all have remarkable self-healing capabilities that surpass human engineering efforts. 4 Hence, achieving self-healing in porous structures is challenging compared to bulk matrices. Yet, nature can still manage repairs without sacrificing the porous morphology. These fascinating capabilities of Nature motivated this research to create biosynthetic materials with similar resilience. Porous materials are common in the industry, but their unique porosity can drastically reduce mechanical strength. This problem is further exacerbated by the random pore distributions that create stress concentrations that propagate failure upon an external load being applied. To counteract this effect, we looked to Nature for a self-healing material solution, namely squid ring teeth (SRT). 5 Amazingly, SRTs contain pores - essential for our desired structure – and feature excellent healing capabilities without needing complex biological pathways. With SRT’s help, we could create repairable porous structures. 6 We have achieved facility-scale production of bioengineered SRT proteins. These materials exhibit rapid self-healing and impressive strength recovery, repairing themselves in less than 1 min with tensile strengths ranging from 10 to 100 MPa. 7 These proteins are classified as thermoplastic elastomers with hydrogen bonds that rapidly restructure protein chains at damaged interfaces into nanocrystal β-sheets, requiring only brief exposure to a plasticizer for activation. 8 Here, we synthesized porous SRT protein foams using the salt-leaching method. Besides the rapid self-healing ability, we demonstrate how these bioengineered proteins can tune the mechanics of foams by their molecular weights. Additionally, SRT proteins' hydrophobic properties make them ideal for creating highly selective and efficient oil-absorbing foams. We show that the total oil absorption capacity and separation efficiency are 5.1 g g −1 and 94%, respectively. These self-healing foams are promising for several applications beyond solely structural, such as tissue scaffolding, acoustics, energy storage, and so forth. Combined with their wetting behavior, tandem repeat protein foams are an excellent choice as durable filter cartridges for water treatment. Moreover, our approach supports a sustainable circular economy, which can recover, reuse, and recycle protein foam materials.",
"discussion": "Results and discussions Tandem repeat proteins Over a century ago, Williams' \"Anatomy of Squid\" described a principal evolutionary aspect of squid, i.e., teeth-containing suckers. 9 Nixon and Dilly published an article in 1977 after studying squid suckers. 10 They concluded that the suckers have a porous protein structure called squid ring teeth (SRT). Demirel et al. showed that SRT have self-healing abilities to repair themselves under pressure. 6 We further studied the features of SRT and re-confirmed nanopores through scanning electron microscopy (SEM), as shown in Figure 1 . Figure 1 Scanning electron micrographs illustrating nano-pores in squid ring teeth cross-section at three different resolutions Self-repairing materials can be engineered by manipulating protein structures at a molecular level. By varying amino acid sequences in tandem repeat (TR) proteins, inspired by the hierarchical assembly found naturally within SRT proteins, it is possible to design biomaterials with mechanically superior properties and self-healing capabilities. Specific alanine-rich segments (i.e., PAAASVSTVHHP) create physical crosslinks, while glycine regions (i.e., YGYGGLYGGLYGGLGYG) add flexibility to the polymer matrix making up these TR proteins. Furthermore, this segmented copolymer design approach enables us to adjust chain length, resulting in three distinct varieties: TR-n4, TR-n7, and TR-n11, where “n” denotes the number of repeat units. The resulting variations of 4-, 7-, and 11-repeat units were synthesized via microbial fermentation technique, as depicted in Figure 2 A. Figure 2 Biomimetic Tandem Repeat protein synthesis (A) Tandem repeat protein sequence design was inspired by squid ring teeth protein. Shown is the production process, including protein sequencing, expression in E. Coli followed by bio-fermentation, and downstream processes to yield protein powder. (B) Images showing production steps post-sequencing. (C) MALDI-TOF validation of molecular weight for purified TR proteins for TR-n4, n7, and n11. As reported in our earlier work, we used the E. coli strain BL21(DE3) to produce the TR proteins. 11 Our organic extraction method enabled us to efficiently separate TR proteins, which are insoluble under cellular physiological conditions. By dissolving the inclusion body pellets in dimethyl sulfoxide (DMSO) and precipitating them with ultra-purified water as a counter solvent, we achieved a high yield of 1.5 g/L dry protein on both small and large scales (100 L fermenter). The process of synthesis is shown in Figure 2 B. The molecular weight assessment was performed via mass spectroscopy (Matrix-Assisted Laser Ionization-Time of Flight spectroscopy, MALDI-TOF) because these proteins are insoluble in conventional buffers. More importantly, the protein electrophoresis gels are difficult to obtain and do not provide accurate results; MALDI-TOF provides accurate quantitative data ( Figure 2 C). Tandem repeat protein foams synthesis and structure We prepared highly porous TR protein foams with open-cell morphology using the salt-leaching approach, as shown in Figure 3 A. Our salt leaching process involves the use of an organic solvent and solid salt granules as porogen in an organic solvent (HFIP) that can dissolve our protein at high concentrations (i.e., >150 g/L). As HFIP evaporates, protein aggregates in the gaps between adjacent salt particles. Our study uses NaCl because it does not mix with the organic solvent (HFIP). To remove the salt, we utilize water, which eliminates the NaCl granules quickly but cannot dissolve the TR protein. We achieved an interconnected network of large pores formed upon the solidification of protein surrounding NaCl granules upon the evaporation of the volatile solvent. This method was chosen over gas-foaming as it yields homogeneous porosity distribution and an interconnected network of open cells throughout the material. Upon closer inspection through SEM ( Figure 3 B) and X-ray tomography ( Figure 3 C), the large pores encase smaller micro-pores, likely increasing fluid take up and saturation. The inter-spacing between NaCl crystals decides the thickness of the solidified protein segments and, thus, the formation of either the macro- or micro-pores. The calculated average porosities were 87.6 ± 1.8%, confirming the low densities of this bioengineered foam structure; a dandelion spore supporting a representative foam is shown ( Figure 3 D). Figure 3 Morphology of TR protein foams (A.) TR protein foam synthesis by salt leaching method. (B) Interconnected pore network as seen in TR protein foam micrographs. The protein segments forming the foam structure further have micro-pores. (C) The process of estimation of foam porosity. Image analysis identifies protein segments in the 2D tomography scans. The fraction of black pixels in the final image represents porosity. (D) Ultralight TR protein foam supported by a Dandelion flower. Mechanical properties and self-healing TR protein foams exhibit self-healing capabilities, which we validated through three-point flexural tests. The flexural stress-strain plots of the foams are depicted in Figure 4 A, and the progression of a representative flexural test is shown in Figure 4 A i, ii, and iii. As the molecular weight of TR protein increases, the ultimate stress and stiffness increase. The ultimate flexural stress for TR-n4, n7, and n11 are 62.2 ± 17.1 kPa, 167.2 ± 19.2 kPa, and 336.4 ± 23.8 kPa, resp. This behavior is expected because a higher degree of polymerization promotes chain entanglements and the formation of β-sheet structures. This favors the reduction of the density of network defects within the bulk of the protein matrix. 12 The foams were self-healed after mechanical testing, and the regenerated strength was measured. After these rigorous experiments, a full-strength recovery after self-healing was confirmed. Figure 4 Mechanical and self-healing properties of TR protein foams (A) The strength and stiffness of pristine TR protein foams are tunable depending on the molecular weight of the protein chain. Representative stress-strain plots are shown, and a three-point bending test of a representative foam is depicted in chronological order (i, ii, and iii). Scale bars = 10 mm. (B) Description of self-healing protocol for foams after sustaining mechanical damage. Scale bars = 10 mm. (C) Norm. force-deflection curves of self-healed TR protein foams. The force-deflection curves of self-healed foams were normalized with respect to the max force and displacements of pristine foams. The data for TR-n4 represent lyophilized foams. The threshold line marks max flexural forces for the foams. (D) The figure-of-merit depicts the superior self-healing capabilities of TR protein foams as opposed to porous structures reported in the literature. 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 While most studies used mechanical tests to validate self-healing, some used other functional characterization. Figure 4 B showcases the self-healing protocol requiring no additional chemical treatment for repair. The mechanism of self-healing has been discussed earlier. 7 Rapid chain diffusion occurs across fractured surfaces to form new secondary structures (e.g., β-sheets), speeding up the repair time. Hot water treatment lowers glass transition temperatures while external pressures (minimal in magnitude) ensure that the contact between damaged surfaces is maintained without compromising integrity. Figure 4 C shows normalized deflection curves, confirming complete strength regeneration in reference to pristine foams (raw data are plotted in Figure S1 ). The strength regeneration was over 100% for all foams as indicated by max flexural force lying over the threshold (norm. force = 1) set by pristine foams. Additionally, the slopes of the initial linear region of force-deflection curves of self-healed foams were higher than that of pristine foams, indicating greater stiffness. A decrease in cross-sectional areas was expected during self-healing due to the shrinkage of soft protein matrices upon exposure to hot water. However, this decrease was significant only in the low molecular weight TR-n4 variant. We also analyzed a less porous TR-n4 foam that was air-dried instead of lyophilized to confirm complete damage reversal, as shown in Figure S1 . This foam showed no shrinkage at the interface but still had over 100% strength regeneration. In our earlier report on self-healing TR protein films, 7 we identified a shift of protein microstructure toward higher crystallinity (increased β-sheet fraction) due to hot water treatment. We posit that this increment in crystallinity at the self-healed interface is the reason behind improved mechanical properties. Self-healing chemical-based protocols are not appropriate for oil-separating foams as they are effective with foams of lower porosities and closed-cell structures. Moreover, such methods do not conserve the porous morphology after repair. Traditional foams need conditioning (e.g., near-IR 13 and sunlight 14 irradiation), high-temperature and pressure annealing (vs. short treatment), or unique blends of chemicals, which take days to achieve self-healing. However, TR-n4, n7, and n11 foams can self-heal within 3–8 min. TR protein foams perform better self-healing than previously reported ones, as shown in Figure 4 D. They can quickly and easily self-heal, allowing for the shaping of the foam as desired. Wetting properties of tandem repeat protein films We conducted experiments to investigate how TR protein films interact with liquids, specifically water and oil, and how porosity affects these interactions. We measured the contact angles of both liquids on the films and found that water had an average contact angle of 78.43 ± 8.48°, while oil had an average contact angle of 22.86 ± 3.73°. The results indicate that TR proteins are not very hydrophilic but are highly oleophilic. Figure 5 A shows each liquid’s corresponding average contact angles (see Supplemental information , Figure S2 ). TR proteins are more hydrophobic than natural biopolymers, including silk, 26 , 27 , 28 zein, 29 , 30 soy protein, 31 keratin, 32 , 33 and cellulose. 34 , 35 , 36 We further demonstrate the oleophilic nature of TR proteins using the capillary rise experiment ( Figure 5 B). The difference in water column height between the protein-coated capillary and the control is over five times higher than the oil column. This selective-absorption behavior is crucial in foams, as will be discussed later. The wetting properties of the protein also depend on its degree of crystallinity. Thermal (hot water) and chemical (methanol) treatment of protein films induces higher crystallinity due to the formation of additional β-sheets. This can be quantified by the deconvolution of the Amide-I band of the FTIR spectra, as shown in Figure S3 . The methanol-treated film had a higher fraction of β-sheet crystallites (39.97%) than the untreated film (30.13%). With the increase in crystallinity, the average contact angle of oil on TR-n11 decreased by 12.64° (as seen in Figure 5 C). We note that the film could not be tested with higher oil droplet volumes due to the droplets' span exceeding the camera lens’s aperture ( Figure S4 ). Figure 5 Wetting properties of TR proteins (A) TR proteins are hydrophobic and oleophilic compared to the glass substrate, as depicted in the plot and the contact angle images for respective cases. (B) Capillary rise experiment with glass and TR-n11 protein-coated capillaries with oil and water. The difference in column heights of liquids confirms TR proteins’ oleophilic and hydrophobic properties. (C) The contact angle of oil on washed and methanol-treated films. (D) The water droplet image on a representative TR protein foam sample and the respective plot of contact angle vs. droplet volume. (E) Theoretical estimate of total oil-absorption capacities (with 0.915 g cm −3 oil density and 1.35 g cm −3 material density) as a function of foam porosity at various selective oil-absorption efficiencies ( f ). (F) Fraction of oil and water absorbed by TR protein foams corroborates the selective oil absorption behavior. (G) Classification of foams reported in the literature (circles) according to the materials used and their selective oil-separation efficiencies. 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 Selective oil-absorption On porous foam surfaces, the contact angles of water and oil differ from those on thin films of proteins ( Figure S5 ). Figure 5 D depicts an image of the sessile drop experiment with water and TR protein foam. The contact angle of water rises to a maximum of 143.0 ° (with an average of 137.2 ° ), while the contact angle of oil could not be measured due to instant absorption. The experimental contact angle of water on foam is close to the theoretical estimate of 147.6 ° (see method details for derivation). These results demonstrate how porous surfaces amplify the hydrophobic behavior of TR proteins, which is comparable to other biopolymer aerogels 37 , 88 of significantly higher porosities. Numerous studies have been reported on oil-water separation in the literature. 89 The most commonly used parameters to measure the performance of foams are total oil absorption capacity (g/g) and separation efficiency (the fraction of oil absorbed or separated). On average, the total oil-absorption capacity and separation efficiency are 5.07 ± 0.5 g g −1 and 93.9 ± 0.9%, respectively ( Figure 5 ). The total absorption capacity can theoretically be estimated ( Figure 5 E), and the theoretical estimate for our foams (4.5 g/g) agrees with the experimental data. Our model indicates that it is necessary to normalize total oil-absorption capacity with porosity when using it as a figure of merit for wetting properties of porous materials (see method details and Figure S6 ). If fabricated with greater porosity, TR protein foams would exhibit high capacity (due to increased pore volume) while the protein’s wetting properties remain virtually unchanged. Hence, separation efficiency is a valuable metric for collectively comparing all porous materials' wetting behavior. TR protein foams have a strong affinity for oil, which explains their selective oil-absorption behavior. Oil is quickly absorbed when the foam is placed at the liquid interface due to the capillary effect (see Figure S7 ). However, water is not absorbed because the surface is superhydrophobic. The material’s wetting characteristics and the liquid’s surface tension generate a pressure difference at the liquid-air interface within capillaries. This intrusion pressure promotes oil transport through capillaries while restricting water transport. 90 , 91 When the contact angle inside capillaries is less than 90°, liquid transport is preferred, but not when it exceeds 90° (i.e., the lower the contact angle of liquid in capillaries, the faster the absorption kinetics). Our foams achieved saturation in under 40 s, indicating a fast oil absorption rate. Additionally, we observed that water did not displace the oil when an oil-soaked foam was immersed in water for extended periods. In Figure 5 G, we depict the separation efficiencies of different types of foams. This figure categorizes foams into four groups: polymeric, biopolymeric, non-polymeric, and metallic. Almost all foams mentioned in the literature are chemically modified. After the foam is produced, these modifications are done using agents such as silanes, siloxanes, metal oxides, and fluorinated polymers. 92 The substrate is treated with these agents using dip-coating, chemical vapor deposition, polymer grafting, spray-coating, or nanoparticle deposition. 93 On the other hand, our TR protein foams display high oleophilic behavior and comparable separation efficiencies even without any chemical enhancement of the surface. This highlights the uniqueness of TR protein foams as sustainable biomaterials, making them stand out from traditional sorbents. Figures S8 and S9 show the entire process flow of TR protein materials, highlighting their sustainability through reusability and recyclability after oil absorption.\n\nDiscussion Hydrophobic TR protein foams have unique properties that make them ideal for separating oil and water in water treatment processes. They can self-heal rapidly, a feature not reported in other open-celled foams. In addition to their use in industrial filtration processes, these foams are an excellent option for traditional porous sorbents of oil impurities. One of the benefits of TR proteins over synthetic polymeric systems is their sustainability. TR proteins are biodegradable and renewable, eliminating the need for petroleum-based everlasting polymers. The non-covalent nature of supramolecular interactions allows for easy repurposing of TR protein foams. Biomanufactured TR proteins yield functional properties with high efficiency and sustainability. Remarkably, this replication of self-healing mechanisms allows for incorporating porosity into these proteins, thereby boosting their selectivity in oil absorption from aqueous media. This opens up exciting avenues, such as utilizing SRT foams to cleanse water or as efficient sorbents for oils without compromising performance due to deterioration. Limitations of the study This study demonstrates that bioengineered protein foams, inspired by nature, can be sustainably utilized as absorbent materials. We showed that these foams have self-healing abilities to repair themselves under pressure. There is still a lack of understanding regarding the relationship between self-healing and porosity. Our research will focus on this topic in the future."
} | 5,721 |
33803653 | PMC8003077 | pmc | 5,362 | {
"abstract": "Plastic pollution is a worldwide concern causing the death of animals (mainly aquatic fauna) and environmental deterioration. Plastic recycling is, in most cases, difficult or even impossible. For this reason, new research lines are emerging to identify highly biodegradable bioplastics or plastic formulations that are more environmentally friendly than current ones. In this context, microbes, capable of synthesizing bioplastics, were revealed to be good models to design strategies in which microorganisms can be used as cell factories. Recently, special interest has been paid to haloarchaea due to the capability of some species to produce significant concentrations of polyhydroxyalkanoate (PHA), polyhydroxybutyrate (PHB), and polyhydroxyvalerate (PHV) when growing under a specific nutritional status. The growth of those microorganisms at the pilot or industrial scale offers several advantages compared to that of other microbes that are bioplastic producers. This review summarizes the state of the art of bioplastic production and the most recent findings regarding the production of bioplastics by halophilic microorganisms with special emphasis on haloarchaea. Some protocols to produce/analyze bioplastics are highlighted here to shed light on the potential use of haloarchaea at the industrial scale to produce valuable products, thus minimizing environmental pollution by plastics made from petroleum.",
"conclusion": "7. Conclusions Microbiologically produced PHAs are viable candidates to replace conventional oil-based plastics. However, the production costs of this biopolymer are still considerably higher in comparison to those of traditional polymers. Important challenges should be overcome, including the costs of the carbon source as well as enhancing the production and extraction efficiency. In these terms, haloarchaea species provide the advantage of utilizing inexpensive carbon sources of industrial origin, lower energy requirements due to negligible sterility precautions, downstream processing without the use of any chemical solvent for cell lysis, the recyclability of process side-streams (spent fermentation broth and cell debris), and the production of 3HV-containing copolyesters from unrelated carbon sources. Promising findings regarding haloarchaea-related PHA production have been reported in recent years at the laboratory scale. However, very few works have provided an in-depth characterization at the pilot or semi-industrial scale, and marketable prototypes from haloarchaeal PHA and techno-economic assessments are scarce. What is needed now is to drive the upscaling of those promising processes at the lab-scale to boost the development of archaeal cell factories and illustrate their potential in the future of sustainable biotechnology.",
"introduction": "1. Introduction Plastic pollution is distributed across the globe, and it is a problem of growing environmental concern, which is aggravated by the great durability of polymers and their inaccurate management [ 1 ]. Global production of resins and fibers increased from 2 metric tons (Mt) in 1950 to 380 Mt in 2015. From that date, approximately 6300 Mt of plastic waste has been generated, around 9% of which was recycled, 12% was incinerated, and 79% ended up in landfills or the natural environment, with its consequent accumulation [ 2 ]. More than 80% of the plastics produced are obtained through polymerization of monomers into high-molecular-weight chains, receiving the name of thermoplastics [ 3 , 4 ]. The physical (e.g., melting, extrusion, and pelletization) and chemical (mixture with antioxidants, plasticizers, clarifiers, bisphenol A-based polycarbonate, copolymers, colorants, etc.) properties of these polymer matrixes are modified, thus obtaining a complex chemical composition in their physical structure [ 4 ]. In general, these materials show high malleability which, together with their low cost and versatility, have contributed to an increase in their use worldwide. It is estimated that plastics now flow through major food-webs across the Earth, with potential implications for populations and ecosystems as well as human health [ 5 ]. Plastic waste has affected over 690 marine species with small plastic particles ending up in the digestive tract of organisms from different trophic levels [ 6 ]. Under different conditions, such as mechanic abrasion, temperature fluctuations, or the influence of light or sea waves, plastics go through a fragmentation process into smaller particles named microplastics, whose size is below 5 mm [ 7 ]. Microplastics are ubiquitous in water, soil, and atmospheric environments and come from different sources. The discharge of microplastic-containing wastewater is a major source of microplastic pollution in water [ 8 ]. Carr and co-workers stated that although sewage treatment systems present a removal rate of microplastics as high as 98%, 65 million microplastics still enter water through these facilities every day [ 9 ]. The abundance of microplastics ranged from 741 to 7707 items·kg −1 , with the minimum value corresponding to 1971 and the maximum value to 2018. The outer layer of microplastics is ideal for harboring bacteria, viruses, and algae, and abiotic substances [ 10 ]. These abiotic substances include organic pollutants, perfluorinated compounds (PFCs), heavy metals, and pharmaceuticals and personal care products (PPCPs). Consequently, the adhesion of pollutants makes microplastics a source of pollution [ 8 ]. The long-distance microplastic migration also increases the risk of biological invasion, as attached microorganisms follow the same route [ 11 ]. A major problem about microplastics is their capacity to release absorbed contaminants and chemical additives into an organism, compromising its health [ 12 ]. Due to their small size, microplastics are ingested by filter, suspension, and detritus feeders living in the water column and bottom sediments, and they are present in the guts of invertebrates, fish, turtles, and a range of species intended for human consumption or involved in critical ecological roles [ 13 ]. Microplastics can potentially harm animal species, since many plastic additives and persistent chemicals are endocrine disruptors, altering metabolic and reproductive endpoints [ 14 ]. These substances are known as endocrine disrupting chemicals (EDCs), which affect all hormonal systems controlling the development and function of reproductive organs, regulation of metabolism, and satiety [ 15 ]. Bisphenol A (BPA) and bis(2-ethylhexyl)phthalate (DEHP) are EDCs used as plastic components or additives, which can cause chronic adverse effects on several organisms [ 16 ]. It is also known that floating microplastic fibers and their adsorbed pollutants enter the human body via the respiratory system, causing a lasting physiological impact on the body [ 8 ]. Due to the considerable negative impact of the production, use, and disposal of plastics, not only the scientific community but also political sectors are stressing the need to look for alternatives that allow the use of biodegradable plastics and their production following environmentally friendly procedures. Unlike fossil-fuel plastics, which are derived from petroleum, bioplastics are a form of plastics derived from renewable biomass sources. Biodegradability is a property that enables certain bioplastics, but not all, to be chemically broken down by the action of microorganisms, such as bacteria, fungi, and algae. Therefore, bioplastics are an alternative to synthetic plastics to reduce their environmental impact. They are produced by several microorganisms when there is availability of excess substrates (carbon source) under conditions of limited oxygen, nitrogen, phosphorus, or pH fluctuations [ 17 ]. As an example, polyhydroxyalkanoates (PHAs) are biological polyesters mainly produced by microbial fermentation processes. They are recognized because of their 100% biodegradability, biocompatibility, and sustainability [ 18 ]. The first identified PHA was polyhydroxybutyrate (PHB), which is utilized as a reserve material in bacteria, amounting up to 80% of the dry bacterial biomass [ 19 , 20 ]. The interest in identifying the molecular machinery sustaining the microbial production of bioplastics is such that the number of scientific publications on this topic has increased significantly over the last decade (more than 9000 research articles and reviews focused on plastics pollution and potential solutions have been published over the last 10 years) [ 21 ]. In this context, microbes able to synthesize bioplastics are considered good models to develop biotechnological-based processes in which microorganisms can be used as cell factories for bioplastic production at a large scale. Extremophilic microbes in general, and particularly the haloarchaea group (Archaea domain), have received considerable attention from the scientific community due to their peculiar metabolic capabilities, including the capacity of bioplastic production shown by some species. Thus, some haloarchaea can produce significant concentrations of marketed bioplastics, such as polyhydroxyalkanoate (PHA), polyhydroxybutyrate (PHB), and polyhydroxyvalerate (PHV). The growth of those microorganisms at the pilot or industrial scale offers several advantages compared to other microbes that are bioplastic producers in terms of sterilization of the cultures, growth rate, etc. This review summarizes the most recent findings regarding the production of bioplastics by microorganisms, with special emphasis on haloarchaea as promising organisms, to reduce the negative effect of plastics contamination in the future. Discussions about protocols already used to produce and analyze bioplastics are also highlighted to shed light on the potential use of haloarchaea at the industrial scale in order to produce those valuable products."
} | 2,473 |
34841352 | PMC8610360 | pmc | 5,363 | {
"abstract": "Highlights • Biofertilizers have a potential to direct a sustainable agriculture. • Consortia biofertilizers extend soil biodiversity and thus, impact with effect beneficial. • Omics allow a global vision of uncultured and rare microorganism (\"dark matter\"). • Omics will help determine the functional ecology of microbial communities. • Functional and metabolic networks and omics will determine biofertilizers selection."
} | 105 |
37148247 | PMC10193292 | pmc | 5,364 | {
"abstract": "Summary Here, we present a protocol to analyze the inhibition of self-generated extracellular free organic carbon (EFOC) on CO 2 fixation by chemoautotrophic bacteria. We detail the construction and operation of membrane reactor, followed by a simulation experiment to verify the inhibition of EFOC on CO 2 fixation. We further describe the analysis of main inhibitory components in EFOC and measurement of abundance and transcription level of ribulose bisphosphate carboxylase/oxygenase (RuBisCO) gene to clarify the mechanism of the main inhibition components on CO 2 fixation. For complete details on the use and execution of this protocol, please refer to Zhang et al. (2022). 1"
} | 171 |
28486499 | PMC5423606 | pmc | 5,365 | {
"abstract": "Many ecosystems experience strong temporal variability in environmental conditions; yet, a clear picture of how niche and neutral processes operate to determine community assembly in temporally variable systems remains elusive. In this study, we constructed neutral metacommunity models to assess the relative importance of neutral processes in a spatially and temporally variable ecosystem. We analyzed macroinvertebrate community data spanning multiple seasons and years from 20 sites in a Sonoran Desert river network in Arizona. The model goodness-of-fit was used to infer the importance of neutral processes. Averaging over eight stream flow conditions across three years, we found that neutral processes were more important in perennial streams than in non-perennial streams (intermittent and ephemeral streams). Averaging across perennial and non-perennial streams, we found that neutral processes were more important during very high flow and in low flow periods; whereas, at very low flows, the relative importance of neutral processes varied greatly. These findings were robust to the choice of model parameter values. Our study suggested that the net effect of disturbance on the relative importance of niche and neutral processes in community assembly varies non-monotonically with the severity of disturbance. In contrast to the prevailing view that disturbance promotes niche processes, we found that neutral processes could become more important when the severity of disturbance is beyond a certain threshold such that all organisms are adversely affected regardless of their biological traits and strategies.",
"introduction": "Introduction Understanding community assembly—the processes responsible for observed spatiotemporal patterns of biodiversity—is a long-standing challenge in community ecology [ 1 ]. In recent years, a rich body of literature exploring the relative importance of niche vs . neutral processes has often resulted in polarizing outcomes [ 2 – 3 ]. According to the niche perspective, all species differ from each other, and their distribution and abundance are limited by environmental factors that select for particular biological traits expressed by species in the regional species pool [ 4 ]. The neutral perspective, in contrast, operates on the assumption that these interspecific differences are immaterial for explaining certain biodiversity patterns [ 5 ]. Both neutral and niche processes are important in community assembly; the challenge is to understand where, when, and how each affects community structure [ 6 ]. Now, it is also well recognized that environmental disturbance is an important force driving community structure and dynamics [ 7 – 9 ]. Both experimental evidence and theoretical models have suggested that disturbance can influence community assembly [ 10 – 13 ], including the relative importance of niche and neutral processes. The exact mechanisms by which the influence of disturbance operates, however, remains unresolved. Several studies, for example, support the hypothesis that neutral processes dominate in places characterized by more benign environments, whereas in harsher environments niche selection plays a more predominant role by filtering out species lacking disturbance resistance traits [ 14 – 17 ]. Other studies, however, suggest a more complex, non-monotonic relationship. In Sweden, Lepori & Malmqvist [ 11 ] reported that the strength of niche processes shaping macroinvertebrate communities increased with the severity of flood disturbance initially, but weakened once flood severity exceeded intermediate levels. These findings lend support to the notion that neutral processes may be important under severe disturbances, presumably because these disturbances promote random extinction and recolonization even for those organisms most resistant to disturbance. In short, considerable uncertainty regarding the roles of niche and neutral processes in community assembly remains. Dryland streams are known for extreme hydrologic variability, where aquatic organisms face both severe drying events and massive flooding [ 18 ]. Hydrologic regimes are also heterogeneous across the landscape, consisting of a mosaic of perennial, intermittent, and ephemeral streams that vary greatly in flow permanence over the year [ 19 ]. Although all of these stream types experience flood disturbance, aquatic organisms must also cope with drought conditions in intermittent and ephemeral streams (hereafter “non-perennial”) that seasonally dry. For these reasons, dryland streams are an appropriate study system to evaluate the effects of disturbance on the relative strength of niche and neutral processes in community assembly. Indeed, a considerable amount of literature has shown that aquatic invertebrate assemblages in dryland streams are strongly influenced by hydrological variability in space and time [ 20 – 22 ]. In these systems, support for the role of niche processes (environmental filtering imposed by hydrological regime) has been well documented (e.g., [ 22 – 25 ]), yet the potential role of neutral processes and whether it might vary in space (i.e., different degrees of harshness: perennial vs. non-perennial streams) and time (i.e., different sequences of drying and flooding) has been notably overlooked. The present study aims to address this knowledge gap by answering the following questions. First, are neutral processes more important for shaping community assembly in perennial versus non-perennial streams? Second, does hydrologic variability related to differing intensities of disturbance (i.e., drying and flooding) influence the contribution of neutral processes to community assembly? We analyzed macroinvertebrate community data spanning multiple seasons and years from 20 locations across a Sonoran Desert river network in Arizona, U.S.A., and built spatially- and temporally-explicit neutral metacommunity models to assess the changes of relative importance of neutral processes in space and in time.",
"discussion": "Discussion In this study, we developed a spatiotemporal neutral model for aquatic invertebrate communities in dryland streams to investigate whether and how the relative importance of neutral processes varies across space and time. Despite some non-ideal conditions for neutrality [ 37 ], namely relatively low richness compared to streams in other biomes [ 38 ] and generally strong dispersal limitation among freshwater invertebrates [ 39 ], dryland streams offer great natural laboratories for investigating the effects of temporal variability on the relative strength of niche and neutral processes in community assembly. This is because these streams are highly variable in time, strongly heterogeneous in space, and harbor ecological communities that have historically experienced such environmental variability. We used the goodness of fit of the neutral metacommunity model to evaluate the relative importance of neutral processes in perennial and non-perennial streams and under different hydrological conditions. Even though we only had eight sampling events—which limited the range of hydrological conditions represented and the strength of statistical inference—our results were informative. We found greater relative importance of neutral processes in perennial streams and during relatively low flow periods and periods of very high flow that represented times of hydrologic disturbance. However, when flow was very low (mean daily discharge < 0.1 m 3 s -1 ), the model performance exhibited large variability, with TE ranging from -1.6 to 0.5 ( Fig 2b ); the negative TE values hinted at the possibility of strong non-neutral processes. These results suggested that the importance of neutral assembly processes vary both in space and time for the aquatic invertebrate community in this dryland stream network. The neutral model provided consistently better model fits for invertebrate communities of perennial streams than for non-perennial streams: neutral processes explained 20%-30% of species assembly in perennial streams, but the low (or negative) TE indicated that neutral processes play much weaker roles in non-perennial streams ( Table 1 ). Although both perennial and non-perennial streams experience disturbances in the form of floods, droughts in non-perennial streams are likely stronger disturbances for aquatic macroinvertebrates. Leigh & Datry [ 25 ] recently assessed the influence of drying on macroinvertebrate communities in Australia and Europe over broad spatial and temporal scales, and found that drying is more important to species diversity compared to other flow-related determinants. Fritz & Dodds [ 40 ] showed that stream macroinvertebrates are typically more resistant and resilient to flooding than to drying. In our own study system, Bogan & Lytle [ 21 ] monitored two stream pools for eight years, and found that invertebrate communities underwent a shift in species composition in response to a transition from perennial flow to intermittent. In this sense, perennial streams, despite their frequent flood disturbances, are relatively more benign habitats for macroinvertebrate communities than non-perennial streams that experience drying. This agrees with the theoretical prediction that neutral processes are more important in systems that have less environmental fluctuation (more benign habitats) [ 17 ]. In contrast, flow intermittency serves as a stronger environmental filter to select for species with biological traits and behavioral strategies to survive drying phases, leading to greater effects of niche processes and weaker roles of neutral processes in non-perennial. Across the entire dryland stream network, the model performance varied with stream discharge in the sampling period: when mean daily discharge was greater than 0.1 m 3 s -1 , model goodness-of-fit decreased with discharge, and increased again when the discharge was very high ( Fig 2b ). A decrease in model performance with discharge indicated that neutral processes became less important as the stream became wetter (often associated with floods). This is consistent with the current understanding that as the habitat is more disturbed, niche processes become more important [ 14 – 17 ]. However, at the very high flow end (daily discharge at about 5 m 3 s -1 ), with their large flood disturbances, neutral processes explained up to ~50% of the variance ( Fig 2b ). This is contradictory to the prevailing view that disturbances promote niche processes [ 14 – 17 ]. A potential explanation is that the severe disturbances cause random recolonization and extinction even among the regional taxa that are most resistant to disturbance [ 11 ]. The summer 2010 sampling took place two weeks after a 5-year flood (i.e., 20-percent annual exceedance probability) ( Fig 2a ). Faced with severe floods, the protection against flood scour provided by biological traits (e.g., streamlined body shape, small body size, and ability for attachment to the substratum [ 7 ]) is probably very limited, and community assembly may be driven more by neutral processes. At the other end of hydrological spectrum—the very low flow conditions (mean discharge lower than 0.1 m 3 s -1 )—the roles of neutral processes in community assembly were mixed: ranging from moderate importance of neutral processes to likely dominance of non-neutral processes. The variable relative importance of neutrality could be because our measure of discharge was calculated for the entire sampling period, and thus did not isolate the flow conditions immediately prior to sampling nor capture the long-term flow patterns at the site. For example, although 2009 (summer and fall) and 2011 (fall) had similar low discharge during the sampling periods, the duration of low flow periods varied greatly: the very low flow period lasted for 15 months prior to 2009 fall sampling, 12 months prior to 2009 summer sampling, and just two months prior to 2011 fall sampling. Water-retaining refuges could provide effective protection against drought for most populations for a certain period of time; however, confronted with prolonged severe drought, these refuges would be compromised by reductions in size and worsening water quality [ 41 ]. These results suggest that when disturbances are sufficiently severe—large flood or prolonged and severe drought—the risk of mortality may be decoupled from the species’ traits and identity, resulting in more neutral process-dominated biodiversity patterns. Lepori & Malmqvist [ 11 ] showed similar results, where extreme disturbances triggered neutral processes for an aquatic invertebrate community in streams in North Sweden. There are also alternative explanations for greater importance of neutral processes during very high flow periods. For example, when stream flow is very low or very high, the whole landscape is more homogeneous (uniformly connected high stream flow), while intermediate and low flow promotes higher flow heterogeneity across landscapes by creating higher degrees of habitat patchiness. Theoretical models [ 37 , 42 ] suggest that the validity of the neutrality assumptions increases as a more homogeneous environment enables higher niche overlap. This explanation is somewhat speculative at this point, as one needs quantification of landscape heterogeneity to support it—a worthwhile future research direction. Taken together, these findings suggest that the theoretical framework needs to be modified to recognize that the net effect of disturbance on the relative importance of community assembly forces could be non-monotonic and severity-dependent. Additionally, the relative contribution by neutral processes to community assembly could vary both in space and in time, as demonstrated in our study."
} | 3,442 |
25741356 | PMC4332284 | pmc | 5,366 | {
"abstract": "A greenhouse pot experiment was carried out to evaluate the efficiency of arsenic phytoextraction by the fern Pteris vittata growing in arsenic-contaminated soil, with or without the addition of selected rhizobacteria isolated from the polluted site. The bacterial strains were selected for arsenic resistance, the ability to reduce arsenate to arsenite, and the ability to promote plant growth. P. vittata plants were cultivated for 4 months in a contaminated substrate consisting of arsenopyrite cinders and mature compost. Four different experimental conditions were tested: (i) non-inoculated plants; (ii) plants inoculated with the siderophore-producing and arsenate-reducing bacteria Pseudomonas sp. P1III2 and Delftia sp. P2III5 (A); (iii) plants inoculated with the siderophore and indoleacetic acid-producing bacteria Bacillus sp. MPV12, Variovorax sp. P4III4, and Pseudoxanthomonas sp. P4V6 (B), and (iv) plants inoculated with all five bacterial strains (AB). The presence of growth-promoting rhizobacteria increased plant biomass by up to 45% and increased As removal efficiency from 13% without bacteria to 35% in the presence of the mixed inoculum. Molecular analysis confirmed the persistence of the introduced bacterial strains in the soil and resulted in a significant impact on the structure of the bacterial community.",
"introduction": "INTRODUCTION Arsenic is widely dispersed in the Earth’s crust with an average concentration of ∼5 mg kg -1 . It is a component of more than 200 minerals, although it primarily exists as arsenopyrite and other sulfides. Rocks can release arsenic compounds during weathering, allowing dispersion by wind and water. The natural arsenic content of soils ranges from 0.01 to more than 600 mg kg -1 ( Yan-Chu, 1994 ). Approximately one third of the arsenic in the atmosphere is also from natural sources, such as volcanoes and forest wildfires (United States Environmental Protection Agency [ US-EPA ], 1998 ). The remaining arsenic in the environment is anthropogenic in origin. Arsenic is used in the pharmaceutical, glass, timber, and leather industries, and for the production of pigments, metal alloys, semiconductors, and optoelectronics. Uncontaminated soils usually contain 0.2–40 mg kg -1 arsenic but concentrations of 100–2500 mg kg -1 can be found in the vicinities of copper-smelting plants and in heavily pesticide-contaminated agricultural soils, which are the greatest sources of arsenic pollution (World Health Organization [ WHO ], 2000 ). The diverse industrial uses of arsenic provide many opportunities for human exposure to the element ( Garelick et al., 2008 ). Arsenic in soils exists predominantly as arsenate (AsV), which includes HAsO 4 2- and H 2 AsO 4 - . However, arsenite (AsIII), arsine (AsH 3 ), and several organoarsenic compounds are also found ( Roy et al., 2015 ). Arsenic is acutely toxic to humans and also has a chronic impact on health, as well as genotoxic and carcinogenic effects ( Léonard and Lauwerys, 1980 ; Ratnaike, 2003 ; Hughes et al., 2011 ). It is considered to be five times as dangerous as lead ( United States Department of Health and Human Services [US-DHHS], 2007 ). The chronic effects of arsenic include gastrointestinal disorders, anemia, peripheral neuropathy, skin lesions, hyperpigmentation, gangrene of the extremities, vascular lesions, liver and kidney damage, and spontaneous abortions ( Szymañska-Chabowska et al., 2002 ; Fernández et al., 2012 ). The inhalation of arsenic-containing compounds is a minor exposure route with the exception of workers in the copper-smelting and pesticide-manufacturing industries, and in power plants burning arsenic-rich coal ( Naujokas et al., 2013 ). Arsenic exposure through contaminated drinking water is common in mine drainage areas and where the bedrock has a high arsenic content ( Nordstrom, 2002 ; Rahman et al., 2009 ) exceeding the 10 μg l -1 safety limit established by the United States Environmental Protection Agency ( US-EPA, 1998 ) and the World Health Organization ( WHO, 2000 ). Arsenic may also be present in the diet, particularly in seafood, e.g., marine fish, mussels, and certain crustaceans ( European Food Safety Authority [EFSA], 2009 ). The presence of arsenic in the environment and its associated health risks have led to the deployment of conventional remediation strategies for the cleanup of contaminated sites including removal (excavation and landfilling) and containment (capping). Because both these approaches are expensive, plant-assisted bioremediation (phytoremediation) has been considered as an inexpensive and environmentally beneficial in situ treatment for polluted soils ( Pilon-Smits, 2005 ). This is based on the ability of hyperaccumulator plants to extract metals (including metalloids such as arsenic) from contaminated soils and sequester the minerals in their aboveground biomass ( Lasat, 2002 ). However, effective phytoremediation in metal/metalloid-contaminated soils requires a detailed understanding of the complex interactions in the rhizosphere, because soil microbes influence metal bioavailability ( Rani and Juwarkar, 2013 ). For example, microbes catalyze redox reactions leading to changes in the mobility of metals and their ions, and thus the efficiency with which they are taken up by roots ( Sessitsch et al., 2013 ). Microbes therefore play a crucial role in arsenic geochemical cycling through biochemical transformation, e.g. reduction, oxidation, and methylation ( Smedley and Kinniburgh, 2002 ; Lloyd and Oremland, 2006 ; Páez-Espino et al., 2009 ). Here we focus on a severe case of arsenic contamination in the Scarlino industrial area (south–west Tuscany, GR, Italy) caused by the dumping of 1.5 million tons of arsenopyrite cinders generated during the manufacture of sulfuric acid. The cinder layer covering the soil is currently being removed as the first step toward restoring the site, but a more refined strategy is required to regenerate the underlying soil, which is now heavily contaminated with arsenic minerals. We tested a remediation strategy for soil mixed with arsenopyrite cinders based on microbially enhanced phytoextraction using the arsenic hyperaccumulator fern species Pteris vittata . We carried out a mesocosm experiment under glasshouse conditions as a preliminary test to evaluate the efficiency of arsenic phytoextraction by P. vittata with or without the help of bacterial inoculums comprising species isolated from the rhizosphere of autochthonous plants grown on surrounding soil. The bacteria were enriched by selection with arsenite As(III) or arsenate As(V) to identify species that are arsenic resistant, able to reduce arsenate to arsenite, and able to promote plant growth by producing indoleacetic acid (IAA) or siderophores. The overall aim was to identify bacterial strains that promote the translocation of arsenic from contaminated environmental matrices into plant tissues, especially the epigeal portion of P. vittata .",
"discussion": "DISCUSSION We have demonstrated that the inoculation of soil with a mixture of bacteria selected for their ability to promote plant growth and the mobility of arsenic compounds can enhance arsenic phytoextraction from highly contaminated environmental matrices by the hyperaccumulator fern species P. vittata . Even extreme contamination, such as soil predominantly comprising arsenopyrite cinders from the Scarlino industrial area in Tuscany, can be substantially remediated using this approach. The bacteria were selected for multiple beneficial traits including the production of IAA and siderophores, and the ability to reduce arsenate to arsenite. The inoculation of contaminated soil with five of the best-performing strains achieved an eightfold increase in the arsenic BCF and a threefold increase in PE compared to non-inoculated plants. The PE increased from 13% in the absence of the selected bacteria to 35% when P. vittata plants were augmented with inoculum AB, comprising all five selected bacterial strains. This can be attributed to the ability of the bacteria to withstand particularly adverse experimental conditions. All five strains are indigenous to the contaminated site and have therefore evolved to prosper in an arsenic-rich environment. Our data indicate that the species in inoculums A and B confer overlapping beneficial properties, with inoculum A containing bacteria with the ability to reduce As(V) and inoculum B containing bacteria that produce IAA. The combination of both abilities therefore creates additive benefits to enhance the growth and remediation capacity of the P. vittata plants. The presence of the five selected bacterial strains also had a profound impact on the functional equilibrium of the P. vittata rhizobacterial community, as shown by the similarity indices and DGGE molecular fingerprints of soil samples from non-inoculated plants and those treated with inoculums A, B, and AB. The potential of specific bacterial inoculums to promote arsenic accumulation by plants has been described in previous studies. For example, Yang et al. (2012) inoculated P. vittata plants with five different allochthonous bacterial strains from the genera Delftia , Comamonas, and Streptomyces that were able to reduce arsenate to arsenite. This resulted in a 50% increase in biomass after 4 months, and an increase in phytoextraction efficiency from 7% without inoculation to 15% with the addition of different bacterial strains. Similarly, we found that inoculation with the arsenate-reducing strains Pseudomonas sp. P1III2 and Delftia sp. P2III5 (inoculum A) increased the phytoextraction efficiency from 13.6 to 21%. It is well known that rhizosphere microbes influence the mobility of heavy metals in soil by regulating absorption/desorption equilibria, oxidation/reduction reactions, and other mechanisms ( Robert and Berthelin, 1986 ). The bioavailability of heavy metals in soil is known to be influenced by the rhizosphere microbial community, the interaction between microbes and plant roots, and exudates of microbial origin ( Tang et al., 2001 ). Finally, hydroponically grown P. vittata has been shown to utilize both arsenite and arsenate, although arsenate is taken up more efficiently because it competes with phosphate ( Wang et al., 2002 ; Tu et al., 2004 ). The IAA-producing strains Variovorax sp. P4III4, Pseudoxanthomonas sp. P4V6, and Bacillus sp. MPV12 (inoculum B) elicited a significant increase in both the BCF and the accumulation of arsenic in the fronds, but the TF fell significantly compared to non-inoculated plants and those treated with inoculums A and AB. This probably reflects the ability of the bacteria to accumulate large amounts of intracellular arsenic and thus prevent its uptake into the roots, as previously reported for the arsenic hypertolerant bacterial strain Bacillus sp. DJ-1 (isolated from a treatment plant for industrial effluents in India) which can accumulate arsenic at concentrations of up to 9.8 ± 0.5 mg g -1 dry weight ( Joshi et al., 2009 ). All three inoculums we tested also boosted epigeal plant biomass by an average of 45%. Bacteria that promote plant growth do so by synthesizing beneficial compounds or facilitating the uptake of certain nutrients from the soil ( Burd et al., 2000 ; Çakmakçi et al., 2006 ). They can also prevent or ameliorate plant diseases ( Jetiyanon and Kloepper, 2002 ; Guo et al., 2004 ). The inoculation of P. vittata with arbuscular mycorrhizal fungi can also boost plant growth, e.g., Leung et al. (2013) infected P. vittata roots with Glomus mosseae and G. intraradices strains that are indigenous to soil contaminated with mining waste, not only achieving a higher biomass but also an increase in the TF from 3 to 10. Similar results were obtained by Trotta et al. (2006) . Our bacterial inoculums produced IAA, which is a plant growth hormone ( Patten and Glick, 2002 ) and/or siderophores, which facilitate the uptake of nutrients in the presence of competing metals ( Burd et al., 2000 ). A recent study by Jeong et al. (2014) showed that Pseudomonas aeruginosa siderophores can effectively form siderophore–arsenic complexes in aqueous solutions. A series of pot experiments was then carried out to investigate the effect of microbial siderophores as iron-chelators on the phytoextraction of arsenic by P. cretica . Plants grown in soil supplemented with siderophores accumulated 3.7-fold more arsenic than control plants growing in normal soil ( Jeong et al., 2014 ). Several experiments have shown that P. vittata can phytovolatilize arsenic and this may also contribute to the overall PE because the vapor released from P. vittata fronds contains both As(III) and As(V) ( Roy et al., 2015 ). Furthermore, numerous soil bacteria can volatilize arsenic by reducing arsenate and arsenite to arsine and other organoarsenic compounds. For example, a genetically engineered Pseudomonas putida strain was shown to volatilize almost completely the initial arsenite component of the soil into organoarsenic compounds ( Chen et al., 2014 ). We conclude that the inoculation of plants with arsenic-resistant, growth-promoting bacteria that can reduce As(V) to As(III), particularly bacteria that are indigenous to contaminated sites earmarked for remediation, can improve the efficiency of arsenic phytoextraction even by hyperaccumulator plant species such as P. vittata . This approach appears to be particularly useful for heavily contaminated sites such as the landfill for arsenopyrite cinders at the Scarlino industrial site considered in this investigation."
} | 3,414 |
34598726 | PMC8487115 | pmc | 5,367 | {
"abstract": "Background Ethyl acetate (C 4 H 8 O 2 ) and hydrogen (H 2 ) are industrially relevant compounds that preferably are produced via sustainable, non-petrochemical production processes. Both compounds are volatile and can be produced by Escherichia coli before. However, relatively low yields for hydrogen are obtained and a mix of by-products renders the sole production of hydrogen by micro-organisms unfeasible. High yields for ethyl acetate have been achieved, but accumulation of formate remained an undesired but inevitable obstacle. Coupling ethyl acetate production to the conversion of formate into H 2 may offer an interesting solution to both drawbacks. Ethyl acetate production requires equimolar amounts of ethanol and acetyl-CoA, which enables a redox neutral fermentation, without the need for production of by-products, other than hydrogen and CO 2 . Results We engineered Escherichia coli towards improved conversion of formate into H 2 and CO 2 by inactivating the formate hydrogen lyase repressor ( hycA ), both uptake hydrogenases ( hyaAB , hybBC ) and/or overexpressing the hydrogen formate lyase activator ( fhlA ), in an acetate kinase ( ackA ) and lactate dehydrogenase ( ldhA )-deficient background strain. Initially 10 strains, with increasing number of modifications were evaluated in anaerobic serum bottles with respect to growth. Four reference strains ΔldhAΔackA , ΔldhAΔackA p3-fhlA, ΔldhAΔackAΔhycAΔhyaABΔhybBC and ΔldhAΔackAΔhycAΔhyaABΔhybBC p3-fhlA were further equipped with a plasmid carrying the heterologous ethanol acyltransferase (Eat1) from Wickerhamomyces anomalus and analyzed with respect to their ethyl acetate and hydrogen co-production capacity. Anaerobic co-production of hydrogen and ethyl acetate via Eat1 was achieved in 1.5-L pH-controlled bioreactors. The cultivation was performed at 30 °C in modified M9 medium with glucose as the sole carbon source. Anaerobic conditions and gas stripping were established by supplying N 2 gas. Conclusions We showed that the engineered strains co-produced ethyl acetate and hydrogen to yields exceeding 70% of the pathway maximum for ethyl acetate and hydrogen, and propose in situ product removal via gas stripping as efficient technique to isolate the products of interest. Supplementary Information The online version contains supplementary material available at 10.1186/s13068-021-02036-3.",
"conclusion": "Conclusion Modification of the Fhl regulation system is an effective way to improve hydrogen production in E. coli . Overexpression of the Fhl activator fhlA , but also the inactivation of the Fhl repressor hycA and hydrogenases 1 and 2 by knocking out hyaAB and hybBC improved hydrogen production fourfold. During anaerobic fermentation of BW25113 Δldh Δack p3-fhlA pET26b: T7/LacI-trEat1 Wan N-13 on glucose 70% of the pathway yields for ethyl acetate and hydrogen, 0.695 mol ethyl acetate /mol glucose and 1.44 mol hydrogen /mol glucose , respectively, were obtained. Cultivation of BW25113 Δldh Δack ΔhycA ΔhyaAB ΔhybBC pET26b: T7/LacI-trEat1 Wan N-13 led to highest ethyl acetate and hydrogen production rates, being 1.41- and 4-fold higher than the parental strain that mainly accumulated formate. Coupled to in situ product removal by gas stripping both products can efficiently be produced and recovered, offering attractive downstream processing opportunities for co-production of bio-based ethyl acetate and green hydrogen by E. coli .",
"discussion": "Discussion The current study demonstrates how anaerobic ethyl acetate production can be coupled to efficient hydrogen co-production, thereby improving overall fermentation performance of the system. With an ethyl acetate yield on glucose close to 70% of the pathway yield E. coli can compete with natural producers, like K. marxianus [ 13 ] and performs close to earlier reported values using a truncated version of W. anomalus Eat1 [ 3 ]. Inactivation of the uptake hydrogenases ( hyaAB and hybBC ) and the Fhl repressor ( hycA ) led to 4-times higher hydrogen production rates relative to the control strain. While other studies found that those modifications did not negatively affect growth rates, here, the strain performance was even slightly improved during batch reactor fermentations [ 17 ]. This is likely a consequence of reduced formate concentrations, that may impose inhibitory effects to the cells [ 37 ]. Hydrogen yields realized by modified strains ranged from 1–1.47 mol hydrogen /mol glucose , thus the improvements are comparable to earlier reported values around 1.15–1.8 mol hydrogen /mol glucose [ 6 , 16 , 19 , 29 , 36 ]. Overexpression of the Fhl activator fhlA using the p3 promoter led to the highest hydrogen yields on glucose in BW25113 ΔΔ p3-fhlA trEat1, with a product yield of 1.47 mol hydrogen /mol glucose , respectively. However, for this strain also reduced biomass formation and reduced production rates of hydrogen and ethyl acetate were observed. In previous research, overexpression of fhl from a low copy number plasmid improved growth rates and hydrogen production from formate [ 35 ]. Also on glucose no impact of overexpression was noted using an IPTG-inducible expression system while the plasmid insertion itself did reduce the growth rate of the strain and also impacted growth rates during aerobic cultivation on formate [ 16 , 17 ]. Therefore, fine-tuning the overexpression with different promoters or inducible expression systems, combined with adaptation seems necessary to keep the hydrogen overexpression strains competitive. While the applied modifications reportedly improve hydrogen (co-)production, there are still options to inactivate formate exporters (focA) or other formate-consuming enzymes including formate dehydrogenase- N (FdnG), dehydrogenase-O (FdoG), or nitrate reductase A (NarG) that positively impacted hydrogen production [ 16 ]. In the mentioned studies, efficient hydrogen-producing strains also carried an frdAB inactivation to eliminate succinate formation, which should be considered when optimizing further towards the maximum pathway yield of 2 mol hydrogen /mol glucose . Especially for strain BW25113 ΔΔΔΔΔ trEat1 the succinate yield was 2-times higher than the parental strain and may have masked the positive effects of hydrogen production as carbons were diverted from the intended co-product ethyl acetate. Complete suppression of acetate formation is challenging and inactivation of ackA or pta often leads to a reduction in acetate accumulation only [ 11 , 32 ]. Inactivation of the full ackA-pta operon, could help to lower acetate accumulation to negligible amounts [ 27 , 30 ]. Additionally, acetate may originate from Eat1 thiolysis or esterase side-activities converting ethyl acetate or acetyl-CoA into acetate [ 3 , 23 ]. Eliminating side-activities by protein engineering may be one way to overcome this drawback of Eat1. Here, we applied gas stripping to remove ethyl acetate more efficiently and reduce the residence time in the fermentation broth. Next to product degradation, product toxicity is another factor tackled with this strategy [ 8 , 14 ]. Like most products, ethyl acetate can accumulate to toxic concentrations, thereby imposing inhibitory effects on the cells. For E. coli the threshold is estimated for ethyl acetate titers above 110 mM [ 34 ]. While this concentration was not and could not be reached under the tested conditions, gas stripping will become more important once the process is further upscaled. Moreover, the production of H 2 and CO 2 instead of formate, also benefits from gas stripping and enables continuous removal of both products of interest. Low hydrogen yields during fermentation in expression hosts like E. coli combined with a mix of other fermentation products is a major drawback in microbial hydrogen production [ 18 , 28 ]. Besides efficient production of hydrogen, production of only one other main fermentation product remains challenging Especially high-yield production of ethanol is often limited by NAD(P)H availability. Since NAD(P)H is only produced during the EMP pathway (GAP oxidation), ethanol formation can only amount to 1 mol ethanol /mol glucose , with the concomitant formation of 1 mol acetate /mol glucose . Higher ethanol yields requires additional NAD(P)H. Various engineering approaches have been used to generate extra NAD(P)H; Sundara Sekar et al. [ 29 ] employed a partial pentose phosphate pathway, which resulted in co-production of ethanol and hydrogen, with limited by-products formation or loss of growth, reaching yields for ethanol and hydrogen on glucose of 1.4 mol ethanol /mol glucose and 1.88 mol hydrogen /mol glucose , respectively. Others made use of a pyruvate dehydrogenase instead of the pyruvate formate lyase yielding more NAD(P)H and reaching ethanol yields of 1.8 mol ethanol /mol glucose [ 38 ]. The latter obviously occurs at the expense of formate or hydrogen. Thus, optimal co-production of hydrogen and one other product requires a redox-balanced acetyl-CoA conversion. The production of ethyl acetate as demonstrated here enables such redox neutral acetyl-CoA conversion and simultaneously co-production of hydrogen at its theoretical maximum of 2 mol hydrogen /mol glucose . With the co-production of ethyl acetate and hydrogen from glucose of 0.71 mol ethyl acetate /mol glucose and 1.47 mol hydrogen /mol glucose for strain BW25113 Δldh Δack p3-fhlA pET26b:Eat Wan N13, we successfully provide a first outlook on the applicability of this strategy towards another industrially relevant compound. Especially with respect to green hydrogen, co-production strategies offer an elegant way to improve the economic feasibility of a microbial production route and should be further pursued."
} | 2,446 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.