bluuebunny/crossref_metadata_2025_split huggingface dataset:
Marine snow as a habitat for microbial mercury methylators in the Baltic Sea
Authors: Capo Eric , Bravo Andrea Garcia , Soerensen Anne L. , Bertilsson Stefan , Pinhassi Jarone , Feng Caiyan , Andersson Anders F. , Buck Moritz , Björn Erik 
Published: March 2020

AbstractMethylmercury (MeHg), a neurotoxic compound biomagnifying in aquatic food webs, can be a threat to human health via fish consumption. However, the composition and distribution of the microbial communities mediating the methylation of mercury (Hg) to MeHg in marine systems remain largely unknown. In order to fill this gap of knowledge, we used the Baltic Sea Reference Metagenome (BARM) dataset to study the distribution of the genes involved in Hg methylation (thehgcABgene cluster). We determined the relative abundance of thehgcABgenes and their taxonomic identity in 81 brackish metagenomes that cover spatial, seasonal and redox variability in the Baltic Sea water. ThehgcABgenes were predominantly detected in anoxic water, but somehgcABgenes were also detected in hypoxic and normoxic waters. Higher relative quantities ofhgcABgenes were found in metagenomes from marine snow compared to free-living communities in anoxic water, suggesting that marine snow are hotspot habitats for Hg methylators in oxygen-depleted seawater. Phylogenetic analysis identified well-characterized Hg methylators such as Deltaproteobacteria in oxygen-depleted water, but also uncovered Hg methylators within the Spirochaetes and Lentisphaerae phyla. Altogether, our work unveils the diversity of the microorganisms mediating MeHg production in the Baltic Sea and pinpoint the ecological niches of these microorganisms within the marine water column.
Optimized sgRNA design by deep learning to balance the off-target effects and on-target activity of CRISPR/Cas9
Authors: Lan Jie , Cui Yang , Wang Xiaowen , Song Guangtao , Lou Jizhong 
Published: March 2020

ABSTRACTThe CRISPR/Cas9 system derived from bacteria especiallyStreptococcus pyogenes(SpyCas9) is currently considered as the most advanced tool used for numerous areas of biological study in which it is useful to target or modify specific DNA sequences. However, low on-target cleavage efficiency and off-target effects impede its wide application. Several different sgRNA design tools forSpyCas9 by using various algorithms have been developed, including linear regression model, support vector machine (SVM) model and convolutional neuron network model. While the deep insight into the sgRNA features contributing for both on-target activity and off-target still remains to be determined. Here, with public large-scale CRISPR screen data, we evaluated contribution of different features influence sgRNA activity and off-target effects, and developed models for sgRNA off-target evaluation and on-target activity prediction. In addition, we combined both activity and off-target prediction models and packaged them as an online sgRNA design tool, OPT-sgRNA.
Stress priming affects fungal competition – evidence from a combined experimental and modeling study
Authors: Wesener Felix , Szymczak Aleksandra , Rillig Matthias C. , Tietjen Britta 
Published: March 2020

AbstractPriming, an inducible stress defense strategy that prepares an organism for an impending stress event, is common in microbes and has been studied mostly in isolated organisms or populations. How the benefits of priming change in the microbial community context and, vice versa, whether priming influences competition between organisms, remains largely unknown. In this combined experimental and modeling study, we developed a cellular automaton model based on dedicated data of different isolates of soil fungi in isolation and pairwise competition experiments. With the model, we simulated growth of the ascomyceteChaetomium elatumcompeting against other fungi to understand which species traits influence the benefit of priming and the effect of priming on competition. We showed that competition changes the priming benefit compared to isolated growth, and that it depends not only on the primeable species itself, but also on the competitors’ traits such as growth rate, primeability and stress susceptibility. In addition, we showed that priming benefits were not always reflected in the competitive outcome. With this study, we transferred insights on priming from studies in isolation to the community context. This is an important step towards understanding the role of inducible defenses in microbial community assembly and composition.
An Integrated Systems Biology Approach Identifies the Proteasome as a Critical Host Machinery for ZIKV and DENV Replication
Authors: Song Guang , Lee Emily M. , Pan Jianbo , Xu Miao , Rho Hee-Sool , Cheng Yichen , Whitt Nadia , Yang Shu , Kouznetsova Jennifer , Klumpp-Thomas Carleen , Michael Samuel G. , Moore Cedric , Yoon Ki-Jun , Christian Kimberly M. , Simeonov Anton , Huang Wenwei , Xia Menghang , Huang Ruili , Lal-Nag Madhu , Tang Hengli , Zheng Wei , Qian Jiang , Song Hongjun , Ming Guo-li , Zhu Heng 
Published: March 2020

AbstractThe Zika (ZIKV) and dengue (DENV) flaviviruses exhibit similar replicative processes but distinct clinical outcomes. A systematic understanding of virus-host protein-protein interaction networks can reveal cellular pathways critical to viral replication and disease pathogenesis. Here we employed three independent systems biology approaches toward this goal. First, protein array analysis of direct interactions between individual ZIKV/DENV viral proteins and 20,240 human proteins revealed multiple conserved cellular pathways and protein complexes, including proteasome complexes. Second, an RNAi screen of 10,415 druggable genes to identify host proteins required for ZIKV infection uncovered proteasome proteins. Third, a high-throughput screening of 6,016 bioactive compounds for ZIKV inhibitors yielded 134 effective compounds, including six proteasome inhibitors that suppress both ZIKV and DENV replication. Integrative analyses of these orthogonal datasets pinpoints proteasome as critical host machinery for ZIKV/DENV replication. Our study provides multi-omics datasets for further studies of flavivirus-host interactions, disease pathogenesis, and new drug targets.
Queuing models of gene expression: Analytical distributions and beyond
Authors: Shi C. , Jiang Y. , Zhou T. 
Published: March 2020

ABSTRACTActivation of a gene is a multistep biochemical process, involving recruitments of transcription factors and histone kinases as well as modification of histones. Many of these intermediate reaction steps would have been unspecified by experiments. Therefore, classical two-state models of gene expression established based on the memoryless (or Markovian) assumption would not well describe the reality in gene expression. In fact, recent experimental data have indicated that the inactive phases of gene promoters are differently distributed, showing strong memory. Here, we use a non-exponential waiting-time distribution to model the complex activation process of a gene, and analyze a queuing model of stochastic transcription. We successfully derive the analytical expression for the mRNA distribution, which provides insight into the effect of molecular memory created by complex activating events on the mRNA expression. We find that the reduction in the waiting-time noise may result in the increase in the mRNA noise, contrary to the previous conclusion. Based on the derived distribution, we also develop a method to infer the waiting-time distribution from a known mRNA distribution. Data analysis on a realistic example verifies the validity of this method.SIGNIFICANCEActivation of a gene is a complex biochemical process and involve several intermediate reaction steps, many of which have been unspecified by experiments. Stochastic models of gene expression that were previously established based on the constant reaction rates would not well reflect the reality in gene expression. To this end, we study a queuing model of stochastic transcription which assume that the reaction waiting time follows a general distribution and derive the analytical expression for mRNA distribution. Our results provide insight into the role of molecular memory in fine-tuning the gene expression noise, and can be used to infer the underlying molecular mechanism.
Converting networks to predictive logic models from perturbation signalling data with CellNOpt
Authors: Gjerga Enio , Trairatphisan Panuwat , Gabor Attila , Koch Hermann , Chevalier Celine , Ceccarelli Francesco , Dugourd Aurelien , Mitsos Alexander , Saez-Rodriguez Julio 
Published: March 2020

AbstractMotivationThe molecular changes induced by perturbations such as drugs and ligands are highly informative of the intracellular wiring. Our capacity to generate large data-sets is increasing steadily as new experimental approaches are developed. A useful way to extract mechanistic insight from the data is by integrating them with a prior knowledge network of signalling to obtain dynamic models. Logic models scale better with network size than alternative kinetic models, while keeping the interpretation of the model simple, making them particularly suitable for large datasets.ResultsCellNOpt is a collection of Bioconductor R packages for building logic models from perturbation data and prior knowledge of signalling networks. We have recently developed new components and refined the existing ones. These updates include (i) an Integer Linear Programming (ILP) formulation which guarantees efficient optimisation for Boolean models, (ii) a probabilistic logic implementation for semi-quantitative datasets and (iii) the integration of MaBoSS, a stochastic Boolean simulator. Furthermore, we introduce Dynamic-Feeder, a tool to identify missing links not present in the prior knowledge. We have also implemented systematicpost-hocanalyses to highlight the key components and parameters of our models. Finally, we provide an R-Shiny tool to run CellNOpt interactively.AvailabilityR-package(s):https://github.com/saezlab/cellnoptContactjulio.saez@bioquant.uni-heidelberg.deSupplementary informationSupplemental Text.
The total and active bacterial community of the chlorolichenCetraria islandicaand its response to long-term warming in sub-Arctic tundra
Authors: Klarenberg Ingeborg J. , Keuschnig Christoph , Warshan Denis , Jónsdóttir Ingibjörg Svala , Vilhelmsson Oddur 
Published: March 2020

AbstractLichens are traditionally defined as a symbiosis between a fungus and a green alga and or a cyanobacterium. This idea has been challenged by the discovery of bacterial communities inhabiting the lichen thalli. These bacteria are thought to contribute to the survival of lichens under extreme and changing environmental conditions. How these changing environmental conditions affect the lichen-associated bacterial community composition remains unclear.We describe the total (rDNA-based) and potentially metabolically active (rRNA-based) bacterial community of the lichenCetaria islandicaand its response to long-term warming using a 20-year warming experiment in an Icelandic sub-Arctic tundra. 16S rRNA and rDNA amplicon sequencing showed that the orders Acetobacterales (of the class Alphaproteobacteria) and Acidobacteriales (of the phylum Acidobacteria) dominated the bacterial community. Numerous ASVs (amplicon sequence variants) taxa could only be detected in the potentially active community but not in the total community. Long-term warming led to increases in relative abundance on class, order and ASV level. Warming altered the relative abundance of ASVs of the most common bacterial genera, such asGranulicellaandEndobacter. The potentially metabolically active bacterial community was also more responsive to warming than the total community.Our results suggest that the bacterial community of the lichenC. islandicais dominated by acidophilic taxa and harbors disproportionally active rare taxa. We also show for the first time that climate warming can lead to shifts in lichen-associated bacterial community composition.
Queen pheromone modulates the expression of epigenetic modifier genes in the brain of honeybee workers
Authors: Cardoso-Junior Carlos Antônio Mendes , Ronai Isobel , Hartfelder Klaus , Oldroyd Benjamin P. 
Published: March 2020

AbstractPheromones are used by many insects to mediate social interactions. In the highly eusocial honeybee (Apis mellifera) queen mandibular pheromone (QMP) is involved in the regulation of reproduction and behaviour of workers. The molecular mechanisms by which QMP acts are largely unknown. Here we investigate how genes responsible for epigenetic modifications to DNA, RNA and histones respond to the presence of QMP. We show that several of these genes are upregulated in the honeybee brain when workers are exposed to QMP. This provides a plausible mechanism by which pheromone signalling may influence gene expression in the brain of honeybee workers. We propose that pheromonal communication systems, such as those used by social insects, evolved to respond to environmental signals by making use of existing epigenomic machineries.
Bacteroides thetaiotaomicron-infecting bacteriophage isolates inform sequence-based host range predictions
Authors: Hryckowian Andrew J. , Merrill Bryan D. , Porter Nathan T. , Van Treuren William , Nelson Eric J. , Garlena Rebecca A. , Russell Daniel A. , Martens Eric C. , Sonnenburg Justin L. 
Published: March 2020

SummaryOur emerging view of the gut microbiome largely focuses on bacteria and less is known about other microbial components such as of bacteriophages (phages). Though phages are abundant in the gut, very few phages have been isolated from this ecosystem. Here, we report the genomes of 27 phages from the United States and Bangladesh that infect the prevalent human gut bacteriumBacteroides thetaiotaomicron. These phages are mostly distinct from previously sequenced phages with the exception of two, which are crAss-like phages. We compare these isolates to existing human gut metagenomes, revealing similarities to previously inferred phages and additional unexplored phage diversity. Finally, we use host tropisms of these phages to identify alleles of phage structural genes associated with infectivity. This work provides a detailed view of the gut’s “viral dark matter” and a framework for future efforts to further integrate isolation- and sequencing-focused efforts to understand gut-resident phages.
Rapid emergence of clonal interference during malaria parasite cultivation
Authors: Jett Catherine , Dia Aliou , Cheeseman Ian H. 
Published: March 2020

AbstractLaboratory cultivation of the malaria parasitePlasmodium falciparumhas underpinned nearly all advances in malariology in the past 30 years. When freshly isolated clinical isolates are adapted toin vitroculture mutations rapidly fix increasing the parasite growth rate and stability. While the dynamics of culture adaptation are increasingly well characterized, we know little about the extent of genomic variation that arises and spreads during long term culture. To address this we cloned the 3D7 reference strain and maintained a culture for ~84 asexual cycles (167 days). Growth rate of the culture population increased 1.14-fold over this timeframe. We used single cell genome sequencing of parasites at cycles 21 and 84 to measure the accumulation of diversityin vitro. This parasite population showed strong signals of adaptation across this time frame. By cycle 84 two dominant clades had arisen and were segregating with the dynamics of clonal interference. This highlights the continual process of adaptation in malaria parasites, even in parasites which have been extensively adapted to long term culture.
The anti-tubercular activity of simvastatin is mediated by cholesterol-dependent regulation of autophagy via the AMPK-mTORC1-TFEB axis
Authors: Bruiners Natalie , Dutta Noton K. , Guerrini Valentina , Salamon Hugh , Yamaguchi Ken D. , Karakousis Petros C. , Gennaro Maria L. 
Published: March 2020

ABSTRACTStatins, which inhibit both cholesterol biosynthesis and protein prenylation branches of the mevalonate pathway, increase anti-tubercular antibiotic efficacy in animal models. We investigated the mechanism of anti-tubercular action of simvastatin inMycobacterium tuberculosis-infected human monocytic cells. We found that the anti-tubercular activity of statins was phenocopied by cholesterol-branch but not prenylation-branch inhibitors. Moreover, statin treatment blocked activation of mechanistic target of rapamycin complex 1 (mTORC1), activated AMP-activated protein kinase (AMPK) through increased intracellular AMP:ATP ratios, and favored nuclear translocation of transcription factor EB (TFEB). These mechanisms all induce autophagy, which is anti-mycobacterial. The biological effects of simvastatin on the AMPK-mTORC1-TFEB-autophagy axis were reversed by adding exogenous cholesterol to the cells. Overall, our data demonstrate that the anti-tubercular activity of simvastatin requires inhibiting cholesterol biosynthesis, reveal novel links between cholesterol homeostasis, AMPK-mTORC1-TFEB axis, and intracellular infection control, and uncover new anti-tubercular therapy targets.
Molecular mechanism of regulation of the purine salvage enzyme XPRT by the alarmones pppGpp, ppGpp, and pGpp
Authors: Anderson Brent W. , Hao Aili , Satyshur Kenneth A. , Keck James L. , Wang Jue D. 
Published: March 2020

ABSTRACTThe alarmones pppGpp and ppGpp mediate starvation response and maintain purine homeostasis to protect bacterial species. Xanthine phosphoribosyltransferase (XPRT) is a purine salvage enzyme that produces the nucleotide XMP from PRPP and xanthine. Combining structural, biochemical and genetic analyses, we show that pppGpp and ppGpp, as well as a third putative alarmone pGpp, all directly interact with XPRT and inhibit XPRT activity by competing with its substrate PRPP. Structural analysis reveals that ppGpp binds the PRPP binding motif within the XPRT active site. This motif is present in another (p)ppGpp target, the purine salvage enzyme HPRT, suggesting evolutionary conservation in different enzymes. However, XPRT oligomeric interaction is distinct from HPRT in that XPRT forms a symmetric dimer with two (p)ppGpp binding sites at the dimer interface. This results in two distinct regulatory features. First, XPRT cooperatively binds (p)ppGpp with a Hill coefficient of 2. Also, XPRT displays differential regulation by the alarmones as it is potently inhibited by both ppGpp and pGpp, but only modestly by pppGpp. Lastly, we demonstrate that the alarmones are necessary for protecting GTP homeostasis against excess environmental xanthine inBacillus subtilis, suggesting that regulation of XPRT is key for regulating the purine salvage pathway.
Nrf2 represses ER stress-related ferroptosis in renal carcinoma cells via HO-1
Authors: Shen Yuanqing , Hu Zhiquan , Tian Jihua , Gan Jiahua , Ke Chunjin , Yang Chunguang , Zeng Xing , Shen Guanxin 
Published: March 2020

AbstractSelective-induction of regulated cell death is considered as a useful strategy for developing effective therapies against renal cell carcinoma (RCC). In this study, the role of nuclear factor-E2-related factor 2 (Nrf2) and its downstream genes in erastin-induced ferroptosis of renal carcinoma cells was investigated. Erastin induced endoplasmic reticulum (ER) stress and ferroptosis in renal carcinoma cells (786-0 and Caki-1), which was confirmed by morphological changes, increased lipid oxidation and ferroptosis inhibition. Data obtained from TCGA dataset showed that Nrf2 and heme oxygenase-1 (HO-1) were not only significantly differentially expressed between RCC and normal samples, but also associated with better survival in RCC patients. Moreover, the process of ferroptosis induced by erastin in renal carcinoma cells was accompanied by increased expression of Nrf2 and HO-1. Inhibition of Nrf2 or HO-1 expression enhanced lipid ROS accumulation and ferroptosis. Furthermore, pharmacological activation of HO-1 reversed ferroptosis-sensitizing effect of Nrf2 silencing, thereby clarifying the key role of Nrf2/HO-1 pathway in erastin-induced ferroptosis in renal carcinoma cells. In summary, we identified the role of Nrf2/HO-1 signaling pathway in the protection of renal carcinoma cells from ER stress-related ferroptosis, which indicated that targeting of Nrf2/HO-1 pathway as a viable treatment strategy for RCC.Abstract FigureGraphical abstract (supplementary figure):Nrf2 protects against ER stress-related ferroptosis via HO-1 in renal cancer cells. Cystine/glutamate antiporter (SLC7A11) abbreviated as xCT. Mitochondria abbreviated as Mito.
Predicting the Environmental Suitability and Population at Risk of Podoconiosis in Africa
Authors: Deribe Kebede , Simpson Hope , Pullan Rachel L. , Bosco Mbonigaba Jean , Wanji Samuel , Weaver Nicole Davis , Murray Christopher J. L. , Newport Melanie J. , Hay Simon I. , Davey Gail , Cano Jorge 
Published: March 2020

AbstractBackgroundPodoconiosis is a type of tropical lymphedema that causes massive swelling of the lower limbs. The disease is associated with both economic insecurity, due to long-term morbidity-related loss of productivity, and intense social stigma. The geographical distribution and burden of podoconiosis in Africa is uncertain.MethodsWe applied statistical modelling to the most comprehensive database compiled to date to predict the environmental suitability of podoconiosis in the African continent. By combining climate and environmental data and overlaying population figures, we predicted the suitability and human population at risk.ResultsIn Africa, environmental suitability for podoconiosis was predicted in 29 countries. By 2020, the total population in areas suitable for podoconiosis was estimated at 114.5 million people, (95% confidence interval: 109.4-123.9) with 16.9 million in areas suitable for both lymphatic filariasis and podoconiosis. Of the total 5,712 implementation units defined by WHO in Africa, 1,655 (29.0%) were found to be environmentally suitable for podoconiosis. The majority of IUs with high environmental suitability are located in Angola (80 IUs), Cameroon (170 IUs), the DRC (244 IUs), Ethiopia (495 IUs), Kenya (217 IUs), Uganda (116 IUs) and Tanzania (112 IUs). Of the 1,655 environmental suitable IUs, 960 (58.0%) require more detailed community-level mappingConclusionsOur estimates provide key evidence of the population at risk and geographical extent of podoconiosis in Africa, which will help decision-makers to better plan more integrated intervention programmes.