bluuebunny/crossref_metadata_2025 huggingface dataset:
A kinesin-1 variant reveals motor-induced microtubule damage in cells
Authors: Budaitis Breane G. , Badieyan Somayesadat , Yue Yang , Blasius T. Lynne , Reinemann Dana N. , Lang Matthew J. , Cianfrocco Michael A. , Verhey Kristen J.
Published: October 2021

Kinesins drive the transport of cellular cargoes as they walk along microtubule tracks, however, recent work has suggested that the physical act of kinesins walking along microtubules can stress the microtubule lattice. Here, we describe a kinesin-1 KIF5C mutant with an increased ability to generate defects in the microtubule lattice as compared to the wild-type motor. Expression of the mutant motor in cultured cells resulted in microtubule breakage and fragmentation, suggesting that kinesin-1 variants with increased damage activity would have been selected against during evolution. The increased ability to damage microtubules is not due to the altered motility properties of the mutant motor as expression of the kinesin-3 motor KIF1A, which has similar single-motor motility properties, also caused increased microtubule pausing, bending, and buckling but not breakage. In cells, motor-induced microtubule breakage could not be prevented by increased a-tubulin K40 acetylation, a post-translational modification known to increase microtubule flexibility. In vitro, lattice damage induced by wild-type KIF5C was repaired by soluble tubulin and resulted in increased rescues and microtubule growth whereas lattice damage induced by the KIF5C mutant resulted in larger repair sites that made the microtubule vulnerable to breakage and fragmentation when under mechanical stress. These results demonstrate that kinesin-1 motility causes defects in and damage to the microtubule lattice in cells. While cells have the capacity to repair lattice damage, conditions that exceed this capacity result in microtubule breakage and fragmentation and may contribute to human disease.
In vitro experiments and kinetic models of pollen hydration show that MSL8 is not a simple tension-gated osmoregulator
Authors: Miller Kari , Strychalski Wanda , Nickaeen Masoud , Carlsson Anders , Haswell Elizabeth S.
Published: October 2021

Pollen, a neighbor-less cell that contains the male gametes, undergoes multiple mechanical challenges during plant sexual reproduction, including desiccation and rehydration. It was previously showed that the pollen-specific mechanosensitive ion channel MscS-Like (MSL)8 is essential for pollen survival during hydration and proposed that it functions as a tension-gated osmoregulator. Here we test this hypothesis with a combination of mathematical modeling and laboratory experiments. Time-lapse imaging revealed that wild-type pollen grains swell and then stabilize in volume rapidly during hydration.msl8mutant pollen grains, however, continue to expand and eventually burst. We found that a mathematical model wherein MSL8 acts as a simple tension-gated osmoregulator does not replicate this behavior. A better fit was obtained from variations of the model wherein MSL8 inactivation is independent of its membrane tension gating threshold or MSL8 strengthens the cell wall without osmotic regulation. Experimental and computational testing of several perturbations, including hydration in an osmolyte-rich solution, hyper-desiccation of the grains, and MSL8-YFP overexpression, indicated that the Cell Wall Strengthening Model best simulated experimental responses. Finally, expression of a non-conducting MSL8 variant did not complement themsl8overexpansion phenotype. These data indicate that, contrary to our hypothesis and to known MS ion channel function in single-cell systems, MSL8 does not act as a simple membrane tension-gated osmoregulator. Instead, they support a model wherein ion flux through MSL8 is required to alter pollen cell wall properties. These results demonstrate the utility of pollen as a cellular-scale model system and illustrate how mathematical models can correct intuitive hypotheses.
T cell receptor and IL-2 signaling strength control memory CD8+ T cell functional fitness via chromatin remodeling
Authors: Chin Shu Shien , Guillen Erik , Chorro Laurent , Achar Sooraj , Ng Karina , Oberle Susanne , Alfei Francesca , Zehn Dietmar , Altan-Bonnet Grégoire , Delahaye Fabien , Lauvau Grégoire
Published: October 2021

Cognate antigen signal controls CD8+ T cell priming, expansion size and effector versus memory cell fates, but it is not known if and how it modulates the functional features of memory CD8+ T cells. Here we show that the strength of T cell receptor (TCR) signaling determines the requirement for interleukin-2 (IL-2) signals to form a pool of memory CD8+ T cells that competitively re-expand upon secondary antigen encounter. Combining strong TCR and intact IL-2 signaling synergistically induces genome-wide chromatin accessibility in regions targeting a wide breadth of biological processes, consistent with their greater functional fitness. Chromatin accessibility in promoters of genes encoding for stem cell, cell cycle and calcium-related proteins correlated with faster intracellular calcium accumulation, initiation of cell cycle and more robust expansion. High-dimensional flow-cytometry analysis also highlights higher subset diversity and phenotypes. These results formally establish that epitope selection in vaccine design strongly impacts memory CD8+ T cell epigenetic programming and functions.

One Sentence Summary

The strength of antigenic and interleukin 2 signals received by CD8+ T cells during vaccination epigenetically programs their ability to form functional memory.
A within-host infection model to explore tolerance and resistance
Authors: Duneau David , Lafont Pierre D. M. , Lauzeral Christine , Parthuisot Nathalie , Faucher Christian , Jin Xuerong , Buchon Nicolas , Ferdy Jean-Baptiste
Published: October 2021

How are some individuals surviving infections while others die? The answer lies in how infected individuals invest into controlling pathogen proliferation and mitigating damage, two strategies respectively called resistance and disease tolerance. Pathogen within-host dynamics (WHD), influenced by resistance, and its connection to host survival, determined by tolerance, decide the infection outcome. To grasp these intricate effects of resistance and tolerance, we used a deterministic theoretical model where pathogens interact with the immune system of a host. The model describes the positive and negative regulation of the immune response, consider the way damage accumulate during the infection and predicts WHD. When chronic, infections stabilize at a Set-Point Pathogen Load (SPPL). Our model predicts that this situation can be transient, the SPPL being then a predictor of life span which depends on initial condition (e.g. inoculum). When stable, the SPPL is rather diagnostic of non lethal chronic infections. In lethal infections, hosts die at a Pathogen Load Upon Death (PLUD) which is almost independent from the initial conditions. As the SPPL, the PLUD is affected by both resistance and tolerance but we demonstrate that it can be used in conjunction with mortality measurement to distinguish the effect of disease tolerance from that of resistance. We validate empirically this new approach, usingDrosophila melanogasterand the pathogenProvidencia rettgeri. We found that, as predicted by the model, hosts that were wounded or deficient of key antimicrobial peptides had a higher PLUD, while Catalase mutant hosts, likely to have a default in disease tolerance, had a lower PLUD.
Interaction of human CRX and NRL in live HEK293T cells measured using fluorescence resonance energy transfer (FRET)
Authors: Zhuo Xinming , Knox Barry E.
Published: October 2021

CRX and NRL are retina-specific transcription factors that control rod photoreceptor differentiation and synergistically activate rod phototransduction gene expression. Previous experiments showed they interact in vitro and in yeast two-hybrid assays. Here, we examined CRX-NRL interaction in live HEK293T cells using two fluorescence resonance energy transfer (FRET) approaches: confocal microscopy and flow cytometry (FC-FRET). FC-FRET can provide measurements from many cells having wide donor-acceptor expression ranges. FRET efficiencies were calibrated with a series of donor (EGFP)-acceptor (mCherry) fusion proteins separated with linkers between 6-45 amino acids. CRX and NRL were fused at either terminus with EGFP or mCherry to create fluorescent proteins, and all combinations were tested in transiently transfected cells. FRET signals between CRX or NRL homo-pairs were highest with both fluorophores fused to the DNA binding domains (DBD), lower with both fused to the activation domains (AD), and not significant when fused on opposite termini. NRL had stronger FRET signals than CRX. A significant FRET signal between CRX and NRL hetero-pairs was detected when donor was fused to the CRX DNA binding domain and the acceptor fused to the NRL activation domain. FRET signals increased with CRX or NRL expression levels at a rate much higher than expected for collisional FRET alone. Together, our results show the formation of CRX-NRL complexes in live HEK293T cells that are close enough for FRET.
BioCompute Objects to communicate a viral detection pipeline with potential for use in a regulatory environment
Authors: Gulzar Naila , Keeney Jonathon , Baker Jack B. , Klempir Ondrej , Hannigan Geoffrey , Bitton Danny A. , Maritz Julia M , King Charles Hadley S. , Patel Janisha A. , Duncan Paul , Mazumder Raja
Published: October 2021

The volume of nucleic acid sequence data has exploded in recent years, and with it, the challenge of finding and transforming relevant data into meaningful information. Processing the abundance of data can require a dynamic ecosystem of customized tools. As analysis pipelines become more complex, there is an increased difficulty in communicating analysis details in a way that is understandable yet of sufficient detail to make informed decisions about results or repeat the analysis. This may be of particular interest to institutions and private companies that need to communicate complex computations in a regulatory environment. To meet this need for standard reporting, the open source BioCompute framework was developed as a standardized mechanism for communicating the details of an analysis in a concise and organized way, and other tools and interfaces were subsequently developed according to the standard. The goal of BioCompute is to streamline the process of communicating computational analyses. Reports that conform to the BioCompute standard are called BioCompute Objects (BCOs). Here, a comprehensive suite of BCOs is presented, representing interconnected elements of a computation that is modeled after those that might be found in a regulatory submission, but which can be shared publicly. Because BCOs are human and machine readable, they can be displayed in customized ways to further improve their utility, and an example of a collapsible format is shown. The work presented here serves as a real world implementation that imitates actual submissions, providing concrete examples. As an example, a pipeline designed to identify viral contaminants in biological manufacturing, such as for vaccines, is developed and rigorously tested to establish a rate of false positive detection, and is described in a BCO report. That pipeline relies on a specially curated database for alignment, and a set of synthetic reads for testing, both of which are also descriptively packaged in their own BCOs. All of the sufficiently complex processes associated with this analysis are therefore represented as BCOs that can be cross-referenced, demonstrating the modularity of BCOs, their ability to organize tremendous complexity, and their use in a lifelike regulatory environment.
KIMGENS: A novel method to estimate kinship in organisms with mixed haploid diploid genetic systems robust to population structure
Authors: Wang Yen-Wen , Ané Cécile
Published: October 2021

Motivation

Kinship estimation is necessary for evaluating violations of assumptions or testing certain hypotheses in many population genomic studies. However, kinship estimators are usually designed for diploid systems and cannot be used in populations with mixed haploid diploid genetic systems. The only estimators for different ploidies require datasets free of population structure, limiting their usage.

Results

We present KIMGENS, an estimator for kinship estimation among individuals of various ploidies, that is robust to population structure. This estimator is based on the popular KING-robust estimator but uses diploid relatives of the individuals of interest as references of heterozygosity and extends its use to haploid-diploid and haploid pairs of individuals. We demonstrate that KIMGENS estimates kinship more accurately than previously developed estimators in simulated panmictic, structured and admixed populations, but has lower accuracy when the individual of interest is inbred. KIMGENS also outperforms other estimators in a honeybee dataset. Therefore, KIMGENS is a valuable addition to a population geneticist’s toolbox.

Availability and Implementation

KIMGENS and its association simulation tool are implemented and available open-source at https://github.com/YenWenWang/HapDipKinship.

Contact

Yen-Wen Wang Email: ywang883@wisc.edu
Novel graph theoretic biological pathway network analytics methods for analyzing and discovering Alzheimer’s disease related genes
Authors: Saha Subrata , Soliman Ahmed , Rajasekaran Sanguthevar
Published: October 2021

Background

Alzheimer’s disease (AD) is the most common form of dementia among older people. It is a complex disease and the genetics and environmental factors behind it are not conclusive yet. Traditional statistical analyses are inadequate to identify variants, genes, or pathways capable of explaining AD as a unit. In this context, pathway network analysis based on a set of curated AD-specific genes identified in the literature can elucidate biological mechanisms underneath AD. Through the network, we can infer influential pathways that can together explain AD. Consequently, we can target those pathways and corresponding genes for further analysis to develop new drugs, discover novel AD-related genes, combine multiple hypotheses, and so forth.

Methods

We have developed a novel graph theoretic algorithm that can elucidate complex biology from a given set of disease-related genes. It constructs a weighted network of enriched pathways where similarity score between a pair of pathways is defined in a context-specific manner. To make the network robust, we employ topological overlap techniques on top of the raw similarity measure. We then provide the importance of each pathway with respect to the entire network, functional modules and importance of each pathway in a specific module, gene clusters, and so forth. We also provide a method to identify a set of novel genes that can further explain the disease-related genes and the disease itself.

Results

We have employed our algorithms onto a set of AD-specific genes. It identified three distinct functional modules that are related to metabolism, cancer, and infectious disease related pathways. These findings are matched with three recognized hypotheses in Alzheimer’s disease, e.g. “metabolism hypothesis,” “cell cycle hypothesis,” and “infectious disease hypothesis.” By analyzing the curated genes common among those functional modules, we can attain more understanding about this fateful disease. We have also identified 24 novel AD-related genes of which at least 14 genes are known to be involved in AD.

Conclusions

We developed a computational framework for analyzing biological pathways in a context-specific manner. It can be used in any sets of disease-related genes. We manifest its efficacy, reliability, and accuracy by employing a set of AD-specific genes.
Nanoscale organization of ryanodine receptor distribution and phosphorylation pattern determines the dynamics of calcium sparks
Authors: Hernández Mesa M. , van den Brink J. , Louch W.E. , McCabe K.J. , Rangamani P.
Published: October 2021

Super-resolution imaging techniques have provided a better understanding of the relationship between the nanoscale organization of function of ryanodine receptors (RyRs) in cardiomy-ocytes. Interestingly recent data have indicated that this relationship is disrupted in heart failure (HF), as RyRs are dispersed into smaller and more numerous clusters. However, RyRs are also hyperphosphorylated in this condition, and this is reported to occur preferentially within the cluster centre. Thus, the combined impact of RyR relocalization and sensitization on Ca2+ spark generation in failing cardiomyocytes is likely complex and these observations suggest that both the nanoscale organization of RyRs and the pattern of phosphorylated RyRs within clusters could be critical determinants of Ca2+ spark dynamics. To test this hypothesis, we used computational modeling to quantify the relationships between RyR cluster geometry, phosphorylation patterns, and sarcoplasmic reticulum (SR) Ca2+ release. We found that RyR cluster disruption results in a decrease in spark fidelity and longer sparks with a lower amplitude. Phosphorylation of some RyRs within the cluster can play a compensatory role, recovering healthy spark dynamics. Interestingly, our model predicts that such compensation is critically dependent on the phosphorylation pattern, as phosphorylation localized within the cluster center resulted in longer Ca2+ sparks and higher spark fidelity compared to a uniformly distributed phosphorylation pattern. Our results strongly suggest that both the phosphorylation pattern and nanoscale RyR reorganization are critical determinants of Ca2+ dynamics in HF.

Significance Statement

RyRs are ion channels located on the membrane of the sarcoplasmic reticulum that are responsible for an increase in cytosolic Ca2+ during cell excitation. Here, we investigate how the geometry of RyR clusters combined with spatial phosphorylation patterns impacts on Ca2+ spark generation and kinetics. The findings from our study show that both phosphorylation pattern and RyR cluster shape and dispersion have implications on Ca2+ spark activity and provide insights into altered Ca2+ dynamics during HF.
Survival of hatchery grown native oysters is associated with specific gut-associated bacteria at various locations within the Puget Sound
Authors: Kunselman Emily , Minich Jeremiah J , Horwith Micah , Gilbert Jack A , Allen Eric E
Published: October 2021

The Olympia oyster (Ostrea lurida) of the Puget Sound suffered a dramatic population crash, but restoration efforts hope to revive this native species. One overlooked variable in the process of assessing ecosystem health is association of bacteria with marine organisms and the environments they occupy. Oyster microbiomes are known to differ significantly between species, tissue type, and the habitat in which they are found. The goals of this study were to determine the impact of field site and habitat on the oyster microbiome and to identify core oyster-associated bacteria in the Puget Sound. Olympia oysters from one parental family were deployed at four sites in the Puget Sound both inside and outside of eelgrass (Zostera marina) beds. Using 16S rRNA gene amplicon sequencing of the oyster gut, shell, surrounding seawater and sediment, we demonstrate that gut-associated bacteria are distinct from the surrounding environment and vary by field site. Furthermore, regional differences in the gut microbiota are associated with the survival rates of oysters at each site after two months of field exposure. However, habitat type had no influence on microbiome diversity. Further work is needed to identify the specific bacterial dynamics that are associated with oyster physiology and survival rates.

Importance

The outcomes of this study demonstrate the need to monitor microbial ecology at potential oyster restoration sites, specifically for the native Olympia oyster in the Puget Sound. Some areas of Puget Sound may be less amenable to Olympia oyster restoration than others due to microbiome colonization trends. Furthermore, this study puts the oyster microbiome in the context of its surroundings, providing a holistic perspective on the factors that may influence oyster performance and microbial ecology.
HaHB11 transformed maize has improved yield under waterlogging and defoliation in control and field conditions
Authors: Raineri Jesica , Caraballo Luciano , Rigalli Nicolás , Portapila Margarita , Otegui María Elena , Chan Raquel Lía
Published: October 2021

HaHB11 is a sunflower transcription factor previously described as conferring improved yield to maize hybrids and lines. Here we report that transgenic HaHB11 maize lines exhibited a better performance funder waterlogging, both in greenhouse and field trials carried out during three growth cycles. One of these trials was particularly affected by a strong storm during flowering, causing severe defoliation. Controlled defoliation assays indicated that the transgenic genotypes were able to set more grains than controls. Hybrids were generated by crossing B73 HaHB11 lines with the contrasting Mo17 lines and tested in the field. These hybrids exhibited the same beneficial traits as the parental lines when compared with their respective controls. Waterlogging tolerance coursed via the root architecture improvement, including more xylem vessels, reduced tissue damage, less superoxide accumulation, and altered carbohydrate metabolism compared to controls. Multivariate analyses corroborated the robustness of the differential traits observed. Furthermore, canopy spectral reflectance data, computing 29 vegetation indices associated with biomass, chlorophyll, and abiotic stress, helped to identify genotypes as well as their growing conditions. Altogether the results reported here indicate that this sunflower gene constitutes a suitable tool to improve maize plants for environments prone to waterlogging and/or wind defoliation.

One sentence summary

Phenotyping and big data analyses indicate that the transcription factor HaHB11 confers waterlogging and defoliation tolerance, and increased yield to maize lines and hybrids in all tested conditions.
The anterior insular cortex associates temporally discontiguous stimuli during threat learning
Authors: Namkung Ho , Lockhart Sedona , de Chabot Josephine , Guttman Lauren , Isehak Imad , Kwon Hyung-Bae , Sawa Akira
Published: October 2021

Learning about potential threats in the environment is indispensable for survival. Deficits in threat learning constitute a key dimension of multiple brain disorders, which include posttraumatic stress disorder and anxiety disorder. While human brain imaging studies have highlighted a reliable engagement of the anterior insular cortex (AIC) in threat learning, its precise role remains elusive partly due to the lack of animal studies that can address causality and mechanistic questions. Filling in this gap, the present mouse study proposes a novel AIC-mediated mechanism underlying the association of temporally discontiguous stimuli during threat learning. We identified that activity of AIC layer 5 (L5) pyramidal neurons is required for associating temporally discontiguous stimuli, specifically during a time interval between them. Notably, the AIC is not required for associating temporally contiguous stimuli during threat learning. The AIC not only sends the essential information, via its L5 pyramidal neurons, to the basolateral amygdala (BLA) during the time interval, but also receives from the BLA. We also identified a modulatory role of AIC dopamine D1 receptor (D1R)-mediated dopamine signaling in associating temporally discontiguous stimuli during the time interval.
Cellular adhesion is a controlling factor in neutrophil extracellular trap formation induced by antineutrophil cytoplasmic antibodies
Authors: Lelliott Patrick M. , Nishide Masayuki , Pavillon Nicolas , Okita Yasutaka , Shibahara Takayuki , Mizuno Yumiko , Yoshimura Hanako , Obata Sho , Kumanogoh Atsushi , Smith Nicholas I.
Published: October 2021

Anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV) is a life-threatening condition characterized by improper activation of neutrophils and release of neutrophil extracellular traps (NETs) in small vessels. This study aimed to explain the role of NETs in AAV pathogenesis by investigating a link between neutrophil adhesion and NET release. We leveraged an imaging flow cytometry-based assay and three-dimensional culture to demonstrate that neutrophil adhesion is essential for ANCA induced NET formation. We confirmed this requirement for cell adhesion using standard microscopy on ultra-low attachment hydrogel surfaces and demonstrate that this depends on the focal adhesion kinase pathway as determined using inhibitors for multiple targets in this process. ANCA increased expression of β2 integrins on neutrophils, and we confirmed that these integrins were required for NET formation using blocking antibodies. Finally, inhibitors for oxidative burst prevented NET formation, and this oxidative burst was mediated by the focal adhesion pathway. Overall, our findings reveal a central role for neutrophil attachment in NET formation in response to ANCA, helping to explain the restricted localization pattern of vessel damage, and suggesting that targeting neutrophil adhesion factors may be beneficial in preventing pathological damage from NETs during AAV.
Identification of novel therapeutic targets for polyglutamine toxicity disorders that target mitochondrial fragmentation
Authors: Traa Annika , Machiela Emily , Rudich Paige D. , Soo Sonja K. , Senchuk Megan M. , Van Raamsdonk Jeremy M.
Published: October 2021

Huntington’s disease (HD) is one of at least nine polyglutamine toxicity disorders caused by a trinucleotide CAG repeat expansion, all of which lead to age-onset neurodegeneration. Mitochondrial dynamics and function are disrupted in HD and other polyglutamine toxicity disorders. While multiple studies have found beneficial effects from decreasing mitochondrial fragmentation in HD models by disrupting the mitochondrial fission protein DRP1, disrupting DRP1 can also have detrimental consequences in wild-type animals and HD models. In this work, we examine the effect of decreasing mitochondrial fragmentation in a neuronal C. elegans model of polyglutamine toxicity called Neur-67Q. We find that Neur-67Q worms have deficits in mitochondrial morphology in GABAergic neurons and decreased mitochondrial function. Disruption of drp-1 eliminates differences in mitochondrial morphology and rescues deficits in both movement and longevity in Neur-67Q worms. In testing twenty-four RNA interference (RNAi) clones that decrease mitochondrial fragmentation, we identified eleven clones that increase movement and extend lifespan in Neur-67Q worms. Overall, we show that decreasing mitochondrial fragmentation may be an effective approach to treat polyglutamine toxicity disorders and identify multiple novel genetic targets that circumvent the potential negative side effects of disrupting the primary mitochondrial fission gene drp-1.

Significance Statement

Polyglutamine toxicity disorders are caused by a trinucleotide CAG repeat expansion that leads to neurodegeneration. Both mitochondrial dynamics and function are disrupted in these disorders. In this work we use a simple genetic model organism, the worm C. elegans, to define the role of mitochondrial morphology in polyglutamine toxicity disorders. We show that CAG repeat expansion is sufficient to disrupt mitochondrial morphology and that genetic strategies that decrease mitochondrial fragmentation are beneficial in a neuronal model of polyglutamine toxicity. This work identifies multiple novel genes that are protective in worm models of polyglutamine toxicity, which may serve as potential therapeutic targets for Huntington’s disease and other polyglutamine toxicity disorders.
Ligand geometry dictates cellular and in vivo uptake of 3D DNA nanostructures
Authors: Gada Anjali Rajwar , RS Shravani , Vaswani Payal , Morya Vinod , Barai Amlan , Sen Shamik , Gupta Sharad , Sonawane Mahendra , Bhatia Dhiraj
Published: October 2021

Fabrication of nanoscale DNA devices to generate 3D nano-objects with precise control of shape, size, and presentation of ligands has shown tremendous potential for therapeutic applications. The interactions between different topologies of 3D DNA nanostructures and the cell membranes are crucial for designing efficient tools for interfacing DNA devices with biological systems. The practical applications of these DNA nanocages are still limited in cellular and biological systems owing to the limited understanding of interactions of different surface topologies of DNA nanodevices with cell membranes. The correlation between the geometry of DNA nanostructures and their internalization efficiency remains elusive. We investigated the influence of the shape and size of 3D DNA nanostructure on their cellular internalization efficiency. We found that of different geometries designed, one particular geometry, i.e., the tetrahedral shape, is more favoured over other geometries for their cellular uptake in 2D and 3D cell models. This is also replicable for cellular processes like 3D cell invasion assays in 3D spheroid models and passing the epithelial barriers in in-vivo zebrafish model systems. Our work establishes ground rules for the rational designing of DNA nanodevices for their upcoming biological and biomedical applications.
A Single-Cell Approach Reveals Variation in Cellular Phage-Producing Capacities
Authors: Kannoly Sherin , Oken Gabriella , Shadan Jon , Musheyev David , Singh Kevin , Singh Abhyudai , Dennehy John J.
Published: October 2021

Virus burst size, a component of viral fitness, is the average number of viral particles released from a single infected cell. In this study, we estimated bacteriophage lambda (λ) burst size mean and distribution at different lysis times. To estimate phage λ burst sizes at single-cell level, we employed a lysis-deficient E. coli lysogen, which allowed chemical lysis at desired times after the induction of lytic cycle. Induced cultures of E. coli lysogen were diluted and aliquoted into the wells of 96-well plates. A high dilution rate results in mostly empty wells and minimizes the probability of having multiple cells in wells that do receive cells. Burst size was estimated by titering single-cell lysates obtained after chemical lysis at desired times. Our data shows that the viral burst size initially increases exponentially with the lysis time, and then saturates at longer lysis times. We also demonstrate that cell-to-cell variation or “noise” in lysis timing does not significantly contribute to the burst size noise. The burst size noise remains constant with increasing mean burst size. The most likely explanation for the experimentally observed constant burst size noise is that cell-to-cell differences in burst size originate from differences in cellular capacity to produce phages. The mean burst size measured at different lysis times is positively correlated to cell volume, which may determine the cellular phage production capacity. However, experiments controlling for cell size indicates that there are other factors in addition to cell size that determine this cellular capacity.

ARTICLE IMPORTANCE

Phages produce offspring by hijacking a cell’s replicative machinery. Previously, it was noted that the variation in the number of phages produced by single infected cells far exceeded cell size variation. It has been hypothesized that this variation is a consequence of variation in the timing of host cell lysis. Here we show that cell-to-cell variation in lysis timing does not significantly contribute to the burst size variation. We suggest that the constant burst size variation across different host lysis times results from cell-to-cell differences in capacity to produce phages. We find that the mean burst size measured at different lysis times is positively correlated to cell volume, which may determine the cellular phage production capacity. However, experiments controlling for cell size indicates that there are other factors in addition to cell size that determine this cellular capacity.
Response to Tozinameran (BNT162b2) booster in twice-vaccinated kidney transplant and maintenance dialysis patients
Authors: Ben-Dov Iddo Z. , Tzukert Keren , Aharon Michal , Pri-Chen Hadas , Oster Yonatan , Oiknine-Djian Esther , Wolf Dana G. , Elhalel Michal Dranitzki
Published: October 2021

Background

Patients needing chronic RRT are at risk for severe COVID-19 and mount a lesser response to mRNA vaccination. We describe the impact of booster administration in these patients, amidst a third wave of infections and deaths.

Methods

In the setting of a prospective COVID-19-centred cohort study in dialysis and kidney transplant patients we examined humoral responses to booster vaccination, and subsequent infection risk.

Results

We quantified antibodies (DiaSorin) in 198 maintenance dialysis patients, 314 kidney transplant patients and 82 controls, without prior COVID-19 infection. Prior to boosting, 79% of controls, 35% of dialysis and 11% of transplant patients had levels ≥59 AU/ml (putatively protective), while 8-54 days after a third injection, respective rates were 100%, 93% and 58%. Risk factors for antibodies <60 AU/ml despite booster injection were transplant vs dialysis, OR=18.4 (p<0.0001), transitioning from dialysis to transplantation or vice versa, OR=15.7 (p<0.01) and days post injection, OR=0.953 (p<0.05). Antibody step-up after the booster inversely correlated with the second dose step-up (r=-0.33, p<0.01). In this surge, 2 controls, 2 dialysis and 9 transplant patients had COVID-19. Antibody level ≥59 AU/ml at any time point independently associated with reduced risk of infection during this surge, OR=0.264 (p=0.048).

Conclusions

We show that a third dose of tozinameran boosts antibody levels in patients receiving RRT, as it did in controls. Most patients have now reached antibody levels likely to protect from infection. Antibodies were higher after the third dose compared to previous peaks, which may hint that the latest immune response may be more robust and sustainable, even in immune-compromised patients. Kidney transplant recipients showed the most striking enhancement, exhibiting >5.5-fold increase in the percentage of patients with protective antibody levels. However, many transplant patients remain below threshold even after boost injection, necessitating further boosting strategies.
Evolutionary trade-offs between heat and cold tolerance limit responses to fluctuating climates
Authors: Schou Mads F. , Engelbrecht Anel , Brand Zanell , Svensson Erik I. , Cloete Schalk , Cornwallis Charlie K.
Published: October 2021

The evolutionary potential of species to cope with short-term temperature fluctuations during reproduction is critical to predicting responses to future climate change. Despite this, vertebrate research has focused on reproduction under high or low temperatures in relatively stable temperate climates. Here, we characterize the genetic basis of reproductive thermal tolerance to temperature fluctuations in the ostrich that lives in tropical and sub-tropical Africa. Both heat and cold tolerance are under selection and heritable, indicating that evolutionary responses to mean temperature change are possible. However, a negative, genetic correlation between heat and cold tolerance limits the potential for adaptation to fluctuating temperatures. Genetic constraints between heat and cold tolerance appears a crucial, yet underappreciated, factor influencing responses to climate change.

One-sentence summary

Reproductive success in fluctuating climates is constrained by a negative genetic correlation between heat and cold tolerance
OsMADS58 stabilizes gene regulatory circuits during rice stamen development
Authors: Shen Liping , Tian Feng , Cheng Zhukuan , Zhao Qiang , Feng Qi , Zhao Yan , Han Bin , Fang Yuhan , Lin Yanan , Chen Rui , Wang Donghui , Sun Wenfeng , Sun Jiaqi , Zeng Hongyun , Yao Nan , Gao Ge , Luo Jingchu , Xu Zhihong , Bai Shunong
Published: October 2021

Rice (Oryza sativa) OsMADS58 is a C-class MADS box protein, and characterization of a transposon insertion mutant osmads58 suggested that OsMADS58 plays a role in stamen development. However, as no null mutation has been obtained, its role has remained unclear. Here, we report that the CRISPR knockout mutant osmads58 exhibits complex altered phenotypes, including anomalous diploid germ cell differentiation, aberrant meiosis, and delayed tapetum degeneration. This CRISPR mutant line exhibited stronger changes in expression of OsMADS58 target genes compared with the osmads58 dSpm (transposon insertion) line, along with changes in multiple pathways related to early stamen development. Notably, transcriptional regulatory circuits in young panicles covering the stamen at stages 4–6 were substantially altered in the CRISPR line compared to the dSpm line. These findings strongly suggest that the pleiotropic effects of OsMADS58 on stamen development derive from a potential role in stabilizing gene regulatory circuits during early stamen development. Thus, this work opens new avenues for viewing and deciphering the regulatory mechanisms of early stamen development from a network perspective.
Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling
Authors: Alhazmi Fahd , Belkhatir Zehor , Bahloul Mohamed A. , Laleg-Kirati Taous-Meriem
Published: October 2021

Goal

Neurovascular coupling is a fundamental mechanism linking neural activity to cerebral blood flow (CBF) response. Modeling this coupling is very important to understand brain functions, yet challenging due to the complexity of the involved phenomena. One key feature that different studies have reported is the time delay that is inherently present between the neural activity and cerebral blood flow, which has been described by adding a delay parameter in standard models. An alternative approach was recently proposed where the framework of fractional-order modeling is employed to characterize the complex phenomena underlying the neurovascular. Thanks to its nonlocal property, a fractional derivative is suitable for modeling delayed and power-law phenomena.

Methods

In this study, we analyzed and validated an effective fractional-order for the effective modeling and characterization of the neurovascular coupling mechanism. To show the added value of the fractional order parameters of the proposed model, we perform a parameter sensitivity analysis of the fractional model compared to its integer counterpart. Moreover, the model was validated using neural activity-CBF data related to both event and block design experiments that were acquired using electrophysiology and laser Doppler flowmetry recordings, respectively.

Results

The validation results show the aptitude and flexibility of the fractional-order paradigm in fitting a more comprehensive range of well-shaped CBF response behaviors while maintaining a low model complexity. Comparison with the standard integer-order models shows the added value of the fractional-order parameters in capturing various key determinants of the cerebral hemodynamic response, e.g., post-stimulus undershoot.

Conclusions

This investigation authenticates the ability and adaptability of the fractional-order framework to characterize a wider range of well-shaped cerebral blood flow responses while preserving low model complexity through a series of unconstrained and constrained optimizations.

Impact Statement

The present study proposes a novel fractional-order framework for modeling neurovascular coupling. A parameter sensitivity analysis demonstrates the potential flexibility, and effectiveness of the fractional-order paradigm in reconstructing the cerebral hemodynamics with manageable complexity; and a real experimental validation analysis demonstrates the ability of the model in modeling a wider range of well-shaped CBF responses.
Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design
Authors: Ray Sourav , Thies Arne , Sunkara Vikram , Wulkow Hanna , Celik M. Özgür , Yergöz Fatih , Schütte Christof , Stein Christoph , Weber Marcus , Winkelmann Stefanie
Published: October 2021

We previously reported the successful design, synthesis and testing of the prototype opioid painkiller NFEPP that does not elicit adverse side effects. Uniquely, this design was based on mathematical modelling of extracellular interactions between G-protein coupled receptors (GPCRs) and ligands, recognizing that GPCRs function differently under pathological versus healthy conditions. We now present a novel stochastic model of GPCR function that includes intracellular dissociation of G-protein subunits and modulation of plasma membrane calcium channels associated with parameters of inflamed and healthy tissue (pH, radicals). The model is validated against in vitro experimental data for NFEPP and fentanyl ligands at different pH values. We found markedly reduced calcium channel inhibition induced by NFEPP at normal pH compared to lower pH, in contrast to the effect of fentanyl, and enhanced constitutive G-protein activation but lower probability of ligand binding with increasing radical concentrations. By means of molecular dynamics simulations, we also assessed qualitative changes of reaction rates due to additional disulfide bridges inside the GPCR binding pocket. The results suggest that, compared to radicals, low pH is a more important determinant of overall GPCR function in an inflamed environment. Future drug design efforts should take this into account.
Feature blindness: a challenge for understanding and modelling visual object recognition
Authors: Malhotra Gaurav , Dujmović Marin , Bowers Jeffrey S
Published: October 2021

Humans rely heavily on the shape of objects to recognise them. Recently, it has been argued that Convolutional Neural Networks (CNNs) can also show a shape-bias, provided their learning environment contains this bias. This has led to the proposal that CNNs provide good mechanistic models of shape-bias and, more generally, human visual processing. However, it is also possible that humans and CNNs show a shape-bias for very different reasons, namely, shape-bias in humans may be a consequence of architectural and cognitive constraints whereas CNNs show a shape-bias as a consequence of learning the statistics of the environment. We investigated this question by exploring shape-bias in humans and CNNs when they learn in a novel environment. We observed that, in this new environment, humans (i) focused on shape and overlooked many non-shape features, even when non-shape features were more diagnostic, (ii) learned based on only one out of multiple predictive features, and (iii) failed to learn when global features, such as shape, were absent. This behaviour contrasted with the predictions of a statistical inference model with no priors, showing the strong role that shape-bias plays in human feature selection. It also contrasted with CNNs that (i) preferred to categorise objects based on non-shape features, and (ii) increased reliance on these non-shape features as they became more predictive. This was the case even when the CNN was pre-trained to have a shape-bias and the convolutional backbone was frozen. These results suggest that shape-bias has a different source in humans and CNNs: while learning in CNNs is driven by the statistical properties of the environment, humans are highly constrained by their previous biases, which suggests that cognitive constraints play a key role in how humans learn to recognise novel objects.

Author summary

Any object consists of hundreds of visual features that can be used to recognise it. How do humans select which feature to use? Do we always choose features that are best at predicting the object? In a series of experiments using carefully designed stimuli, we find that humans frequently ignore many features that are clearly visible and highly predictive. This behaviour is statistically inefficient and we show that it contrasts with statistical inference models such as state-of-the-art neural networks. Unlike humans, these models learn to rely on the most predictive feature when trained on the same data. We argue that the reason underlying human behaviour may be a bias to look for features that are less hungry for cognitive resources and generalise better to novel instances. Models that incorporate cognitive constraints may not only allow us to better understand human vision but also help us develop machine learning models that are more robust to changes in incidental features of objects.
Limited specificity of molecular interactions incurs an environment-dependent fitness cost in bacteria
Authors: Igler Claudia , Fourcade Claire , Waldminghaus Torsten , Pauler Florian M. , Santhanam Balaji , Tkačik Gašper , Guet Călin C.
Published: October 2021

Reliable operation of cellular programs depends crucially on the specificity of biomolecular interactions. In gene regulatory networks, the appropriate expression of genes is determined through the specific binding of transcription factors (TFs) to their cognate DNA sequences. However, the large genomic background likely contains many DNA sequences showing similarity to TF target motifs, potentially allowing for substantial non-cognate TF binding with low specificity. Whether and how non-cognate TF binding impacts cellular function and fitness remains unclear. We show that increased expression of different transcriptional regulators in Escherichia coli and Salmonella enterica can significantly inhibit population growth across multiple environments. This effect depends upon (i) TF binding to a large number of DNA sequences with low specificity, (ii) TF cooperativity, and (iii) the ratio of TF to DNA. DNA binding due to the limited specificity of promiscuous or non-native TFs can thus severely impact fitness, giving rise to a fundamental biophysical constraint on gene regulatory design and evolution.
The Effects of Prenatal Nicotine and Thc E-Cigarette Exposure on Motor Development in Rats
Authors: Hussain S. , Breit K. R. , Thomas J. D.
Published: October 2021

In the United States, nicotine and cannabis are the most common licit and illicit drugs used among pregnant women. Importantly, nicotine and cannabis are now being combined for consumption via e-cigarettes, an increasingly popular route of administration. Both nicotine and tetrahydrocannabinol (THC), the primary psychoactive component of cannabis, cross the placenta barrier. However, the consequences of prenatal cannabis use are not well understood, and less is known about potential combination effects when consumed with nicotine, especially via e-cigarettes. The present study used a rodent model to examine how prenatal e-cigarette exposure to nicotine, THC, and the combination impacts motor development among offspring. Pregnant Sprague-Dawley rats were exposed to nicotine (36 mg/mL), THC (100 mg/mL), the combination, or vehicle via e-cigarette inhalation from gestational days (GD) 5-20. One sex pair per litter was tested on an early sensorimotor development task (postnatal days [PD] 12-20) and a parallel bar motor coordination task (PD 30-32). Combined prenatal exposure to nicotine and THC delayed sensorimotor development, even though neither drug produced impairments on their own. In contrast, prenatal exposure to either nicotine or THC impaired motor coordination, whereas combined exposure exacerbated these effects, particularly among females. These data illustrate that prenatal exposure to either nicotine or THC may alter motor development, and that the combination may produce more severe effects. These findings have important implications for pregnant women as we better understand the teratogenic effects of these drugs consumed via e-cigarettes.