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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Designing metabolic division of labor in microbial communities

Microbes face a tradeoff between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A \"gedanken experiment\" to investigate this tradeoff would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation, and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed integer linear programming to identify tradeoff solutions in communities of Escherichia coli strains. The strategies we found reveal a large space of nuanced and nonintuitive metabolic division of labor opportunities, including, for example, splitting the TCA cycle into two separate halves. The systematic computation of possible division of labor solutions for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displays a nonlinear boundary, indicating that the loss of an intracellular reaction is not necessarily compensated by a single imported metabolite. Different regions in this landscape are associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable, but outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor.

systems biology↗

bioRxiv2018

Cryo-EM structures of the DCPIB-inhibited volume-regulated anion channel LRRC8A in lipid nanodiscs

Hypoosmotic conditions activate volume-regulated anion channels in vertebrate cells. These channels are formed by leucine-rich repeat-containing protein 8 (LRRC8) family members and contain LRRC8A in homo- or hetero-hexameric assemblies. Here we present single-particle cryo-electron microscopy structures of LRRC8A in complex with the inhibitor DCPIB reconstituted in lipid nanodiscs. DCPIB plugs the channel like a cork in a bottle - binding in the extracellular selectivity filter and sterically occluding ion conduction. Constricted and expanded structures reveal coupled dilation of cytoplasmic LRRs and the channel pore, suggesting a mechanism for channel gating by internal stimuli. Conformational and symmetry differences between LRRC8A structures determined in detergent micelles and lipid bilayers related to reorganization of intersubunit lipid binding sites demonstrate a critical role for the membrane in determining channel structure. These results provide insight into LRRC8 gating and inhibition and the role of lipids in the structure of an ionic-strength sensing ion channel.

neuroscience↗

bioRxiv2018

Robust Estimation of the Phylogenetic Origin of Plastids Using a tRNA-Based Phyloclassifier

The trait of oxygenic photosynthesis was acquired by the last common ancestor of Archaeplastida through endosymbiosis of the cyanobacterial progenitor of modern-day plastids. Although a single origin of plastids by endosymbiosis is broadly supported, recent phylogenomic studies report contradictory evidence that plastids branch either early or late within the cyanobacterial Tree of Life. Here we describe CYANO-MLP, a general-purpose phyloclassifier of cyanobacterial genomes implemented using a Multi-Layer Perceptron. CYANO-MLP exploits consistent phylogenetic signals in bioinformatically estimated structure-function maps of tRNAs. CYANO-MLP accurately classifies cyanobacterial genomes into one of eight well-supported cyanobacterial clades in a manner that is robust to missing data, unbalanced data and variation in model specification. CYANO-MLP supports a late-branching origin of plastids: we classify 99.32% of 440 plastid genomes into one of two late-branching cyanobacterial clades with strong statistical support, and confidently assign 98.41% of plastid genomes to one late-branching clade containing unicellular starch-producing marine/freshwater diazotrophic Cyanobacteria. CYANO-MLP correctly classifies the chromatophore of Paulinella chromatophora and rejects a sister relationship between plastids and the early-branching cyanobacterium Gloeomargarita lithophora. We show that recently applied phylogenetic models and character recoding strategies fit cyanobacterial/plastid phylogenomic datasets poorly, because of heterogeneity both in substitution processes over sites and compositions over lineages.

evolutionary biology↗

bioRxiv2018

Metatranscriptome profiling of the dynamic transcription of mRNA and sRNA of a probiotic Lactobacillus strain in human gut

Metatranscriptomic sequencing has recently been applied to study how pathogens and probiotics affect human gastrointestinal (GI) tract microbiota, which provides new insights into their mechanisms of action. In this study, metatranscriptomic sequencing was applied to deduce the in vivo expression patterns of an ingested Lactobacillus casei strain, which was compared with its in vitro growth transcriptomes. Extraction of the strain-specific reads revealed that transcripts from the ingested L. casei were increased, while those from the resident L. paracasei strains remained unchanged. Mapping of all metatranscriptomic reads and transcriptomic reads to L. casei genome showed that gene expression in vitro and in vivo differed dramatically. About 39% (1163) mRNAs and 45% (93) sRNAs of L. casei well-expressed were repressed after ingested into human gut. Expression of ABC transporter genes and amino acid metabolism genes was induced at day-14 of ingestion; and genes for sugar and SCFA metabolisms were activated at day-28 of ingestion. Moreover, expression of sRNAs specific to the in vitro log phase was more likely to be activated in human gut. Expression of rli28c sRNA with peaked expression during the in vitro stationary phase was also activated in human gut; this sRNA repressed L. casei growth and lactic acid production in vitro. These findings implicate that the ingested L. casei might have to successfully change its transcription patterns to survive in human gut, and the time-dependent activation patterns indicate a highly dynamic cross-talk between the probiotic and human gut including its microbe community.\n\nImportanceProbiotic bacteria are important in food industry and as model microorganisms in understanding bacterial gene regulation. Although probiotic functions and mechanisms in human gastrointestinal tract are linked to the unique probiotic gene expression, it remains elusive how transcription of probiotic bacteria is dynamically regulated after being ingested. Previous study of probiotic gene expression in human fecal samples has been restricted due to its low abundance and the presence of of closely related species. In this study, we took the advantage of the good depth of metatranscriptomic sequencing reads and developed a strain-specific read analysis method to discriminate the transcription of the probiotic Lactobacillus casei and those of its resident relatives. This approach and additional bioinformatics analysis allowed the first study of the dynamic transcriptome profiles of probiotic L casei in vivo. The novel findings indicate a highly regulated repression and dynamic activation of probiotic genome in human GI tract.

microbiology↗

bioRxiv2018

The landscape of intrinsic and evolved fluoroquinolone resistance in Acinetobacter baumannii includes suppression of drug-induced prophage replication

The emergence of fluoroquinolone resistance in nosocomial pathogens has restricted the clinical efficacy of this antibiotic class. In Acinetobacter baumannii, the majority of clinical isolates now show high-level resistance due to mutations in gyrA (DNA gyrase) and parC (Topo IV). To investigate the molecular basis for fluoroquinolone resistance, an exhaustive mutation analysis was performed in both drug sensitive and resistant strains to identify loci that alter the sensitivity of the organism to ciprofloxacin. To this end, parallel fitness tests of over 60,000 unique insertion mutations were performed in strains with various alleles in genes encoding the drug targets. The spectrum of mutations that altered drug sensitivity was found to be similar in the drug sensitive and double mutant gyrAparC background having resistance alleles in both genes. In contrast, introduction of a single gyrA resistance allele, resulting in preferential poisoning of Topo IV by ciprofloxacin, led to extreme alterations in the insertion mutation fitness landscape. The distinguishing feature of preferential Topo IV poisoning was induction of DNA synthesis in the region of two endogenous prophages, which appeared to occur in situ. Induction of the selective DNA synthesis in the gyrA background was also linked to enhanced activation of SOS response and heightened transcription of prophage genes relative to that observed in either the WT or gyrAparC double mutants. Therefore, the accumulation of mutations that result in the stepwise evolution of high ciprofloxacin resistance is tightly connected to suppression of hyperactivation of the SOS response and endogenous prophage DNA synthesis.\n\nImportanceFluoroquinolones have been extremely successful antibiotics. Their clinical efficacy derives from the ability to target multiple bacterial enzymes critical to DNA replication, the topoisomerases DNA gyrase and Topo IV. Unfortunately, mutations lowering drug affinity for both enzymes are now widespread, rendering these drugs ineffective for many pathogens. To undermine this form of resistance, we sought to understand how bacteria with target alterations differentially cope with fluoroquinolone exposures. We studied this problem in the nosocomial pathogen A. baumannii, which causes resistant, life-threating infections. Employing genome-wide approaches, we uncovered numerous pathways that could be exploited to lower fluoroquinolone resistance independently of target alteration. Remarkably, fluoroquinolone targeting of Topo IV in specific mutants caused dramatic prophage hyperinduction, a response that was muted in strains with DNA gyrase as the primary target. This work demonstrates that resistance evolution via target modification can profoundly modulate the antibiotic stress response, revealing potential resistance-associated liabilities.

microbiology↗

bioRxiv2018

DNA damage dependent hypomethylation regulates the pro-angiogenic LncRNA MEG9

Changes in gene expression are key for the cells to adapt and response to intrinsic and extrinsic stimulus. It has been shown that genotoxic stress induces global hypomethylation as a result of decreased expression of DNA methyl transferases (DNMT). We hypothesized that DNA damage suppresses long non-coding RNA expression in the vasculature via DNA methylation leading to more robust DNA repair/survival or cellular senescence/death cell fate decisions. We show here that ionizing radiation reduces the expression of DNMTs in the vascular endothelium and this leads to increased expression of the anti-apoptotic lncRNA MEG9. MEG9 is a lncRNA from the DLK1-DIO3 ncRNA cluster. Loss-of-function studies using RNA gapmers indicate that MEG9 protects endothelial cells from DNA damage induced cell death. Consistent with this phenotype, knockdown of MEG9 decreases growth factor dependent angiogenesis in a 3D fibrin gel angiogenesis assay. Mechanistically, we observed that MEG9 knockdown decreased the expression of cell survival genes including survivin and induced the expression of pro-apoptotic genes such as Bad/Bax. Taken together, our findings illustrate how DNA methylation at selective lncRNA loci can regulate their expression and drive endothelial cell fate decisions.

cell biology↗

bioRxiv2018

Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight novel adipocyte biology

To characterize latent components of genetic associations, we applied truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identified key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits, and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across human phenotypes will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.

genetics↗

bioRxiv2018

Comparison between QST and ΦST indices in an endangered Boswellia serrata Roxb: Implications for conservation

Boswellia serrata, an economically important indigenous tree of dry deciduous forests, provides oleoresin gum of pharmaceutical significance and excellent pulp for paper industries, but faces threat to extinction due to poor natural regeneration and commercial exploitation. 240 individuals of the species representing 12 locations of its natural distribution in central India were investigated to compare the genetic differentiation indices, QST for GBH and wood fiber length and {phi}ST for neutral (RAPD+ISSR) markers. The comparison for paired locations was more informative than for metapopulation. The most paired locations were either under the stabilizing selection (QST (L) < {Phi}ST (L)) or in the genetic drift (QST(L) = {Phi}ST (L)) whereas a relatively small number of paired locations was under the divergent selection (QS T(L) > {Phi}ST (L)). The comparison for the metapopulation generating only a single trend of QST (P) > {Phi}ST (P) is, therefore, misleading. For conservation, the genetically deficit locations (QST (L) < {Phi}ST (L) and QST (L) = {Phi}ST (L)) of B. serrata warrant for reinforcement of their genetic diversity by introduction of genotypes from other genetically divergent locations (QST (L) > {Phi}ST (L)), which would check the fragmentation and genetic drift, resulting in reproductive vigour, natural regeneration and reverse the endangered status of the species.

genetics↗

bioRxiv2018

Novel Methods for Epistasis Detection in Genome-Wide Association Studies

More and more genome-wide association studies are being designed to uncover the full genetic basis of common diseases. Nonetheless, the resulting loci are often insufficient to fully recover the observed heritability. Epistasis, or gene-gene interaction, is one of many hypotheses put forward to explain this missing heritability. In the present work, we propose epiGWAS, a new approach for epistasis detection that identifies interactions between a target SNP and the rest of the genome. This contrasts with the classical strategy of epistasis detection through exhaustive pairwise SNP testing. We draw inspiration from causal inference in randomized clinical trials, which allows us to take into account linkage disequilibrium. EpiGWAS encompasses several methods, which we compare to state-of-the-art techniques for epistasis detection on simulated and real data. The promising results demonstrate empirically the benefits of EpiGWAS to identify pairwise interactions. Author summaryGenome-wide association studies are now a major tool for the discovery of biomarkers for complex diseases. However, the complexity of genetic architecture, in particular linkage disequilibrium, complicates that mission. Moreover, intergenic interactions, or epistasis, are often not correctly captured by the classical statistical methodologies. In our work, we propose a new framework to model linkage disequilibrium, which is based on propensity scores. Our goal is to detect epistatic interactions between a predetermined target locus and the rest of the genotype. The target may be identified from the literature, experiments, or top hits in previous genome-wide association studies. Recovering interactions with validated causal loci helps improve both interpretability and statistical power. Multi-targeting drug discovery can also benefit from our work through the combination of existing drugs with new ones for greater drug response.

bioinformatics↗

bioRxiv2018

Bursts and variability of beta oscillations mediate the effect of anxiety on motor exploration and motor learning

Anxiety results in sub-optimal motor performance and learning; yet, the precise mechanisms through which these modifications occur remain unknown. Using a reward-based motor sequence learning paradigm, we show that concurrent and prior anxiety states impair learning by biasing estimates about the hidden performance goal and the stability of such estimates over time (volatility). In an electroencephalography study, three groups of participants completed our motor task, which had separate phases for motor exploration (baseline) and reward-based learning. Anxiety was manipulated either during the initial baseline exploration phase or while learning. We show that anxiety induced at baseline reduced motor variability, undermining subsequent reward-based learning. Mechanistically, however, the most direct consequence of state anxiety was an underestimation of the hidden performance goal and a higher tendency to believe that the goal was unstable over time. Further, anxiety decreased uncertainty about volatility, which attenuated the update of beliefs about this quantity. Changes in the amplitude and burst distribution of sensorimotor and prefrontal beta oscillations were observed at baseline, which were primarily explained by the anxiety induction. These changes extended to the subsequent learning phase, where phasic increases in beta power and in the rate of long (> 500 ms) oscillation bursts following reward feedback were linked to smaller updates in predictions about volatility, with a higher anxiety-related increase explaining the biased volatility estimates. These data suggest that state anxiety alters the dynamics of beta oscillations during general performance, yet more prominently during reward processing, thereby impairing proper updating of motor predictions when learning in unstable environments.

neuroscience↗

bioRxiv2018

Tissue-specific genes as an underutilized resource in drug discovery

Tissue-specific genes are believed to be good drug targets due to improved safety. Here we show that this intuitive notion is not reflected in phase 1 and 2 clinical trials, despite the historic success of tissue-specific targets and their 2.3-fold overrepresentation among targets of marketed non-oncology drugs. We compare properties of tissue-specific genes and drug targets. We show that tissue-specificity of the target may also be related to efficacy of the drug. The relationship may be indirect (enrichment in Mendelian disease genes) or direct (elevated ability to spread perturbations in human protein-protein interactome for tissue-specifically produced enzymes and secreted proteins). Reduced evolutionary conservation of tissue-specific genes may represent a bottleneck for drug projects, prompting development of novel models with smaller evolutionary gap to humans. We highlight numerous open opportunities to use tissue-specific genes in drug research and hope that the current study will facilitate discovery efforts.

bioinformatics↗

bioRxiv2018

BitMapperBS: a fast and accurate read aligner for whole-genome bisulfite sequencing

As a gold-standard technique for DNA methylation analysis, whole-genome bisulfite sequencing (WGBS) helps researchers to study the genome-wide DNA methylation at single-base resolution. However, aligning WGBS reads to the large reference genome is a major computational bottleneck in DNA methylation analysis projects. Although several WGBS aligners have been developed in recent years, it is difficult for them to efficiently process the ever-increasing bisulfite sequencing data. Here we propose BitMapperBS, an ultrafast and memory-efficient aligner that is designed for WGBS reads. To improve the performance of BitMapperBS, we propose various strategies specifically for the challenges that are unique to the WGBS aligners, which are ignored in most existing methods. Our experiments on real and simulated datasets show that BitMapperBS is one order of magnitude faster than the state-of-the-art WGBS aligners, while achieves similar or better sensitivity and precision. BitMapperBS is freely available at https://github.com/chhylp123/BitMapperBS.

bioinformatics↗

bioRxiv2018

Rapid covalent-probe discovery by electrophile fragment screening

Covalent probes can display unmatched potency, selectivity and duration of action, however, their discovery is challenging. In principle, fragments that can irreversibly bind their target can overcome the low affinity that limits reversible fragment screening. Such electrophilic fragments were considered non-selective and were rarely screened. We hypothesized that mild electrophiles might overcome the selectivity challenge, and constructed a library of 993 mildly electrophilic fragments. We characterized this library by a new high-throughput thiol-reactivity assay and screened them against ten cysteine-containing proteins. Highly reactive and promiscuous fragments were rare and could be easily eliminated. By contrast, we found selective hits for most targets. Combination with high-throughput crystallography allowed rapid progression to potent and selective probes for two enzymes, the deubiquitinase OTUB2, and the pyrophosphatase NUDT7. No inhibitors were previously known for either. This study highlights the potential of electrophile fragment screening as a practical and efficient tool for covalent ligand discovery.

biochemistry↗

bioRxiv2018

I knew that! Confidence in outcome prediction and its impact on feedback processing and learning

Influential theories emphasize the importance of predictions in learning: we learn from feedback to the extent that it is surprising, and thus conveys new information. Here we explore the hypothesis that surprise depends not only on comparing current events to past experience, but also on online evaluation of performance via internal monitoring. Specifically, we propose that people leverage insights from response-based performance monitoring - outcome predictions and confidence - to control learning from feedback. In line with predictions from a Bayesian inference model, we find that people who are better at calibrating their confidence to the precision of their outcome predictions learn more quickly. Further in line with our proposal, EEG signatures of feedback processing are sensitive to the accuracy of, and confidence in, post-response outcome predictions. Taken together, our results suggest that online predictions and confidence serve to calibrate neural error signals to improve the efficiency of learning.

neuroscience↗

bioRxiv2018

Optimal evidence accumulation on social networks

A fundamental question in biology is how organisms integrate sensory and social evidence to make decisions. However, few models describe how both these streams of information can be combined to optimize choices. Here we develop a normative model for collective decision making in a network of agents performing a two-alternative forced choice task. We assume that rational (Bayesian) agents in this network make private measurements, and observe the decisions of their neighbors until they accumulate sufficient evidence to make an irreversible choice. As each agent communicates its decision to those observing it, the flow of social information is described by a directed graph. The decision-making process in this setting is intuitive, but can be complex. We describe when and how the absence of a decision of a neighboring agent communicates social information, and how an agent must marginalize over all unobserved decisions. We also show how decision thresholds and network connectivity affect group evidence accumulation, and describe the dynamics of decision making in social cliques. Our model provides a bridge between the abstractions used in the economics literature and the evidence accumulator models used widely in neuroscience and psychology.

neuroscience↗

bioRxiv2018

Differential generation of saccade, fixation and image onset event-related potentials in the human mesial temporal lobe

The electrophysiological signatures of encoding and retrieval recorded from mesial temporal lobe (MTL) structures are observed as event related potentials (ERPs) during visual memory tasks. The waveforms of the ERPs associated with the onset of visual stimuli (image-onset) and eye movements (saccades and fixations) provide insights into the mechanisms of their generation. We hypothesized that since eye movements and image-onset (common methods of stimulus presentation when testing memory) provide MTL structures with salient visual information, that perhaps they both engage similar neural mechanisms. To explore this question, we used intracranial electroencephalographic (iEEG) data from the MTLs of 11 patients with medically refractory epilepsy who participated in a visual search task. We sought to characterize electrophysiological responses of MTL structures to saccades, fixations and image onset. We demonstrate that the image-onset response is an evoked/additive response with a low-frequency power increase and post-stimulus phase clustering. In contrast, ERPs following eye movements appeared to arise from phase resetting of higher frequencies than the image onset ERP. Intriguingly, this reset was associated with saccade onset and not saccade termination (fixation), suggesting it is likely the MTL response to a corollary discharge, rather than a response to visual stimulation - in stark contrast to the image onset response. The distinct mechanistic underpinnings of these two ERP may help guide future development of visual memory tasks.

neuroscience↗

bioRxiv2018

Affectively-biased Competition Favoring Rewarding Expressions is Not Modulated by Common Variation in Norepinephrine Receptor Function

It is well established that emotionally salient stimuli evoke greater visual cortex activation than neutral ones, and can distract attention from competing tasks. Yet less is known about underlying neurobiological processes. As a proxy of population level biased competition, EEG steady-state visual evoked potentials are sensitive to competition effects from salient stimuli. Here we wished to examine whether individual differences in norepinephrine activity play a role in emotionally-biased competition.\n\nOur previous research has found robust effects of a common variation in the ADRA2B gene, coding for alpha2B norepinephrine (NE) receptors, on emotional modulation of attention and memory. In the present study, EEG was collected while 87 carriers of the ADRA2B deletion variant and 95 non-carriers (final sample) performed a change detection task in which target gratings (gabor patches) were superimposed directly over angry, happy, and neutral faces. Participants indicated the number of phase changes (0-3) in the target. Overlapping targets and distractors were flickered at a distinct driving frequencies. Relative EEG power for faces vs. targets at the driving frequency served as an index of cortical resources allocated to each of the competing stimuli. Deletion carriers and non-carriers were randomly assigned to Discovery and Replication samples and reliability of results across samples was assessed before the groups were combined for greater power.\n\nOverall happy faces evoked higher competition than angry or neutral faces; however, we observed no hypothesized effects of ADRA2B. Increased competition from happy faces was not due to the effect of low-level visual features or individuals low in social anxiety. Our results indicate that emotionally biased competition during sustained attention, while reliably observed in young adults, is not influenced by commonly observed individual differences linked to NE receptor function. They further indicate an overall pattern of affectively-biased competition for happy faces, which we interpret in relation to previously observed boundary conditions.

neuroscience↗

bioRxiv2018

CANDOCK: Chemical atomic network based hierarchical flexible docking algorithm using generalized statistical potentials

Small molecule docking has proven to be invaluable for drug design and discovery. However, existing docking methods have several limitations, such as, improper treatment of the interactions of essential components in the chemical environment of the binding pocket (e.g. cofactors, metal-ions, etc.), incomplete sampling of chemically relevant ligand conformational space, and the inability to consistently correlate docking scores of the best binding pose with experimental binding affinities. We present CANDOCK, a novel docking algorithm that utilizes a hierarchical approach to reconstruct ligands from an atomic grid using graph theory and generalized statistical potential functions to sample biologically relevant ligand conformations. Our algorithm accounts for protein flexibility, solvent, metal ions and cofactors interactions in the binding pocket that are traditionally ignored by current methods. We evaluate the algorithm on the PDBbind and Astex proteins to show its ability to reproduce the binding mode of the ligands that is independent of the initial ligand conformation in these benchmarks. Finally, we identify the best selector and ranker potential functions, such that, the statistical score of best selected docked pose correlates with the experimental binding affinities of the ligands for any given protein target. Our results indicate that CANDOCK is a generalized flexible docking method that addresses several limitations of current docking methods by considering all interactions in the chemical environment of a binding pocket for correlating the best docked pose with biological activity.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=28 SRC=\"FIGDIR/small/442897v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (16K):\norg.highwire.dtl.DTLVardef@1c1b2b0org.highwire.dtl.DTLVardef@1ba66a4org.highwire.dtl.DTLVardef@a8bfd3org.highwire.dtl.DTLVardef@c9d3bb_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗