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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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

Evolution of resilience in protein interactomes across the tree of life

Phenotype robustness to environmental fluctuations is a common biological phenomenon. Although most phenotypes involve multiple proteins that interact with each other, the basic principles of how such interactome networks respond to environmental unpredictability and change during evolution are largely unknown. Here we study interactomes of 1,840 species across the tree of life involving a total of 8,762,166 protein-protein interactions. Our study focuses on the resilience of interactomes to network failures and finds that interactomes become more resilient during evolution, indicating that a species position in the tree of life is predictive of how robust its interactome is to network failures. In bacteria, we find that a more resilient interactome is in turn associated with the greater ability of the organism to survive in a more complex, variable and competitive environment. We find that at the protein family level, proteins exhibit a coordinated rewiring of interactions over time and that a resilient interactome arises through gradual change of the network topology. Our findings have implications for understanding molecular network structure both in the context of evolution and environment.\n\nSignificance StatementThe interactome network of protein-protein interactions captures the structure of molecular machinery that underlies organismal complexity. The resilience to network failures is a critical property of the interactome as the breakdown of interactions may lead to cell death or disease. By studying interactomes from 1,840 species across the tree of life, we find that evolution leads to more resilient interactomes, providing evidence for a longstanding hypothesis that interactomes evolve favoring robustness against network failures. We find that a highly resilient interactome has a beneficial impact on the organisms survival in complex, variable, and competitive habitats. Our findings reveal how interactomes change through evolution and how these changes affect their response to environmental unpredictability.

systems biology↗

bioRxiv2018

Exonuclease III (XthA) enforces in vivo DNA cloning of Escherichia coli to create cohesive ends

Escherichia coli has an ability to assemble DNA fragments with homologous overlapping sequences of 15-40 bp at each end. Several modified protocols have already been reported to improve this simple and useful DNA-cloning technology. However, the molecular mechanism by which E. coli accomplishes such cloning is still unknown. In this study, we provide evidence that the in vivo cloning of E. coli is independent of both RecA and RecET recombinase, but is dependent on XthA, a 3 to 5 exonuclease. Here, in vivo cloning of E. coli by XthA is referred to as iVEC (in vivo E. coli cloning). Next, we show that the iVEC activity is reduced by deletion of the C-terminal domain of DNA polymerase I (PolA). Collectively, these results suggest the following mechanism of iVEC. First, XthA resects the 3' ends of linear DNA fragments that are introduced into E. coli cells, resulting in exposure of the single-stranded 5' overhangs. Then, the complementary single-stranded DNA ends hybridize each other, and gaps are filled by DNA polymerase I. Elucidation of the iVEC mechanism at the molecular level would further advance the development of in vivo DNA-cloning technology. Already we have successfully demonstrated multiple-fragment assembly of up to seven fragments in combination with an effortless transformation procedure using a modified host strain for iVEC.\n\nImportanceCloning of a DNA fragment into a vector is one of the fundamental techniques in recombinant DNA technology. Recently, in vitro recombination of DNA fragments effectively joins multiple DNA fragments in place of the canonical method. Interestingly, E. coli can take up linear double-stranded vectors, insert DNA fragments and assemble them in vivo. The in vivo cloning have realized a high level of usability comparable to that by in vitro recombination reaction, since now it is only necessary to introduce PCR products into E. coli for the in vivo cloning. However, the mechanism of in vivo cloning is highly controversial. Here we clarified the fundamental mechanism underlying in vivo cloning of E. coli and also constructed an E. coli strain that was optimized for in vivo cloning.

bioengineering↗

bioRxiv2018

CTCF looping is established during gastrulation in medaka embryos

AbstractGenome architecture plays a critical role in gene regulation, but how the structures seen in mature cells emerge during embryonic development remains poorly understood. Here, we study early development in medaka (the Japanese killifish, Oryzias latipes) at 12 time points before, during, and after gastrulation which is the most dramatic event in early embryogenesis, and characterize transcription, protein binding, and genome architecture. We find that gastrulation is most associated with drastic changes in genome architecture, including the formation of the first loops between sites bound by the insulator protein CTCF and great increase in the size of contact domains. However, the position of CTCF is fixed throughout medaka embryogenesis. Interestingly, genome-wide transcription precedes the emergence of mature domains and CTCF-CTCF loops.

genomics↗

bioRxiv2018

Structural basis for prodrug recognition by the SLC15 family of proton coupled peptide transporters

A major challenge in drug development is the optimisation of intestinal absorption and cellular uptake. A successful strategy has been to develop prodrug molecules, which hijack solute carrier (SLC) transporters for active transport into the body. The proton coupled oligopeptide transporters, PepT1 and PepT2, have been successfully targeted using this approach. Peptide transporters display a remarkable capacity to recognise a diverse library of di- and tri-peptides, making them extremely promiscuous and major contributors to the pharmacokinetic profile of several important drug classes, including beta-lactam antibiotics, anti-viral and antineoplastic agents. Of particular interest has been their ability to recognise amino acid and peptide-based prodrug molecules, thereby providing a rational approach to improving drug transport into the body. However, the structural basis for prodrug recognition has remained elusive. Here we present crystal structures of a prokaryotic homologue of the mammalian transporters in complex with the antiviral prodrug valacyclovir and the peptide based photodynamic therapy agent, 5-aminolevulinic acid. The valacyclovir structure reveals that prodrug recognition is mediated through both the amino acid scaffold and the ester bond, which is commonly used to link drug molecules to the carriers physiological ligand, whereas 5-aminolevulinic acid makes far fewer interactions compared to physiological peptides. These structures provide a unique insight into how peptide transporters interact with xenobiotic molecules and provide a template for further prodrug development.

biochemistry↗

bioRxiv2018

Nearest-neighbor parameter for inosine-cytosine pairs through a combined experimental and computational approach

In RNA secondary structure prediction, nearest-neighbor parameters are used to determine the stability of a given structure. We derived the nearest-neighbor parameters for RNAs containing inosine-cytosine pairs. For parameter derivation, we developed a method that combines UV adsorption measurement experiments with free-energy calculations using molecular dynamics simulations. The method provides fast drop-in parameters for modified bases. Derived parameters were compared and found to be consistent with existing parameters for canonical RNAs. A duplex with an internal inosine-cytosine pair is 0.9 kcal/mol more unstable than the same duplex with an internal guanine-cytosine pair, and is as stable as the one with an internal adenine-uracil pair (only 0.1 kcal/mol more stable) on average.

bioinformatics↗

bioRxiv2018

Whatever You Want: Inconsistent Results Is The Rule, Not The Exception, In The Study Of Primate Brain Evolution

Primate brains differ in size and architecture. Hypotheses to explain this variation are numerous and many tests have been carried out. However, after body size has been accounted for there is little left to explain. The proposed explanatory variables for the residual variation are many and covary, both with each other and with body size. Further, the data sets used in analyses have been small, especially in light of the many proposed predictors. Here we report the complete list of models that results from exhaustively combining six commonly used predictors of brain and neocortex size. This provides an overview of how the output from standard statistical analyses changes when the inclusion of different predictors is altered. By using both the most commonly tested brain data set and a new, larger data set, we show that the choice of included variables fundamentally changes the conclusions as to what drives primate brain evolution. Our analyses thus reveal why studies have had troubles replicating earlier results and instead have come to such different conclusions. Although our results are somewhat disheartening, they highlight the importance of scientific rigor when trying to answer difficult questions. It is our position that there is currently no empirical justification to highlight any particular hypotheses, of those adaptive hypotheses we have examined here, as the main determinant of primate brain evolution.

evolutionary biology↗

bioRxiv2018

Probability cueing of singleton-distractor locations in visual search: priority-map- or dimension-based inhibition?

Observers can learn the likely locations of salient distractors in visual search, reducing their potential to capture attention (Ferrante et al., 2018; Sauter et al., 2018a; Wang & Theeuwes, 2018a). While there is agreement that this involves positional suppression of the likely distractor location(s), it is contentious at which stage of search guidance the suppression operates: the supra-dimensional priority map or feature-contrast signals within the distractor dimension. On the latter account, advocated by Sauter et al., target processing should be unaffected by distractor suppression when the target is defined in a different (non-suppressed) dimension to the target. At odds with this, Wang and Theeuwes found strong suppression not only of the (color) distractor, but also of the (shape) target when it appeared at the likely distractor location. Adopting their paradigm, the present study ruled out that increased cross-trial inhibition of the single frequent (frequently inhibited) as compared to any of the rare (rarely inhibited) distractor locations is responsible for this target-location effect. However, a reduced likelihood of the target appearing at the frequent vs. a rare distractor location contributes to this effect: removing this negative bias abolished the cost to target processing with increasing practice, indicative of a transition from priority-map- to dimension-based - and thus a flexible locus of - distractor suppression.\n\nPublic Significance StatementDistraction by a salient visual stimulus outside the focus of the task at hand occurs frequently. The present study examined whether and how knowledge of the likely location(s) where the distractors occur helps the observer to mitigate distraction. The results confirmed that observers can learn to suppress distracting stimuli at likely locations. Further, they showed that, the suppression may occur at different levels in the hierarchically organized visual system where the priorities of which objects to be attended in the environment are determined.

neuroscience↗

bioRxiv2018

Inductive determination of allele frequency spectrum probabilities in structured populations

We present a method for inductively determining exact allele frequency spectrum (AFS) probabilities for samples derived from a population comprising two demes under the infinite-allele model of mutation. This method builds on a labeled coalescent argument to extend the Ewens sampling formula (ESF) to structured populations. A key departure from the panmictic case is that the AFS conditioned on the number of alleles in the sample is no longer independent of the scaled mutation rate ({theta}). In particular, biallelic site frequency spectra, widely-used in explorations of genome-wide patterns of variation, depend on the mutation rate in structured populations. Variation in the rate of substitution across loci and through time may contribute to apparent distortions of site frequency spectra exhibited by samples derived from structured populations.

evolutionary biology↗

bioRxiv2018

Are protein-ligand complexes robust structures?

The predominant view in structure-based drug design is that small-molecule ligands, once bound to their target structures, display a well-defined binding mode. While this is convenient from a design perspective, it ignores the fact that structural stability (robustness) is not necessary for thermodynamic stability (binding affinity). In fact, any potential benefit of a rigid binding mode will have to be balanced against the entropic penalty that it entails. Surprisingly, little is known about the causes, consequences and real degree of robustness of protein-ligand complexes. Here we investigate two diverse sets of structures, comprising 79 drug-like and 27 fragment ligands, respectively. We focus on hydrogen bond interactions (469 in total), as they have been described as essential for structural stability. We find that 75% of complexes are anchored by at least one robust hydrogen bond, the remaining 25% either form loose complexes or are constrained by other interactions types. The first type of complexes generally combine a single anchoring point with looser regions, thus balancing order and disorder. Completely constricted protein-ligand complexes are rare and seem to fulfil a functional necessity. Structural stability analysis reveals a hidden layer of complexity in protein-ligand complexes that should be considered in ligand design.

biophysics↗

bioRxiv2018

Subthalamic nucleus local field potentials recordings reveal subtle effects of promised reward during conflict resolution in Parkinson’s disease

Cognitive action control depends on cortical-subcortical circuits, involving notably the subthalamic nucleus (STN), as evidenced by local field potentials recordings (LFPs) studies. The STN consistently shows an increase in theta oscillations power during conflict resolution. Some studies have shown that cognitive action control in Parkinsons disease (PD) could be influenced by the occurrence of monetary reward. In this study, we investigated whether incentive motivation could modulate STN activity, and notably STN theta activity, during response conflict resolution. To achieve this objective, we recorded STN LFPs during a motivated Simon task in PD patients who had undergone deep brain stimulation surgery. Behavioral results revealed that promised rewards increased the difficulty in resolving conflict situations, thus replicating previous findings. Signal analyses locked on the imperative stimulus onset revealed the typical pattern of increased theta power in a conflict situation. However, this conflict-related modulation of theta power was not influenced by the size of the reward cued. We nonetheless identified a significant effect of the reward size on local functional organization (indexed by inter-trial phase clustering) of theta oscillations, with higher organization associated with high rewards while resolving conflict. When focusing on the period following the onset of the reward cue, we unveiled a stronger beta power decrease in higher reward conditions. However, these LFPs results were not correlated to behavioral results. Our study suggests that the STN is involved in how reward information can influence computations during conflict resolution. However, considering recent studies as well as the present results, we suspect that these effects are subtle.

neuroscience↗

bioRxiv2018

Caribbean golden orbweaving spiders maintain gene flow with North America

The Caribbean archipelago offers one of the best natural arenas for testing biogeographic hypotheses. The intermediate dispersal model of biogeography (IDM) predicts variation in species richness among lineages on islands to relate to their dispersal potential. To test this model, one would need background knowledge of dispersal potential of lineages, which has been problematic as evidenced by our prior biogeographic work on the Caribbean tetragnathid spiders. In order to investigate the biogeographic imprint of an excellent disperser, we study the American Trichonephila, a nephilid genus that contains globally distributed species known to overcome long, overwater distances. Our results reveal that the American T. clavipes shows a phylogenetic and population genetic structure consistent with a single species over the Caribbean, but not over the entire Americas. Haplotype network suggests that populations maintain lively gene flow between the Caribbean and North America. Combined with prior evidence from spider genera of different dispersal ability, these patterns coming from an excellent disperser (Trichonephila) that is species poor and of a relatively homogenous genetic structure, support the IDM predictions.

evolutionary biology↗

bioRxiv2018

Computer vision and deep learning automates nocturnal rainforest ant tracking to provide insight into behavior and disease risk

Determining how ant colonies optimize foraging while mitigating disease risk provides insight into how the ants have achieved ecological success. Fungal infected cadavers surround the main foraging trails of the carpenter ant Camponotus rufipes, offering a system to study how foragers behave given the persistent occurrence of disease threats. Studies on social insect foraging behavior typically require many hours of human labor due to the high density of individuals. To overcome this, we developed deep learning based computer vision algorithms to track foraging ants, frame-by-frame, from video footage. We found foragers can be divided into behavioral categories based on how straight they walk across the trail. Eighty percent of ants walk directly across the trail, while 20% wander or circle when crossing the trail. Departure from the main trail encourages exploration of new areas and could enhance discovery of new food resources. Conversely, results from our agent-based model simulations suggest deviation from a straight path exposes foragers to more infectious fungal spores. Consistency in walking behavior may protect most ants from infection, while the foragers with increased exposure due to their mode of walking could be a sufficient number of new hosts to sustain disease in this environment.

animal behavior and cognition↗

bioRxiv2018

Dendritic spikes expand the range of well-tolerated population noise structures

The brain operates surprisingly well despite the noisy nature of individual neurons. The central mechanism for noise mitigation in the nervous system is thought to involve averaging over multiple noise-corrupted inputs. Subsequently, there has been considerable interest recently to identify noise structures that can be averaged out to preserve reliable signal encoding. By analyzing realistic synaptic integration in biophysically accurate neuronal models, I report a role for a complementary de-noising approach mediated by focal dendritic spikes. Dendritic spikes might seem unlikely candidates for noise reduction due to their miniscule integration compartments and poor averaging abilities. Nonetheless, the extra thresholding step introduced by dendritic spike generation could increase neuronal tolerance for a broad category of noise structures, some of which cannot be resolved well with averaging. Computations with multiple dendritic spikes compensate for compartment size constraints and expand the repertoire of conditions that can be reliably processed by neuronal populations.

neuroscience↗

bioRxiv2018

Destabilization of chromosome structure by histone H3 lysine 27 methylation

Chromosome and genome stability are important for normal cell function as instability often correlates with disease and dysfunction of DNA repair mechanisms. Many organisms maintain supernumerary or accessory chromosomes that deviate from standard chromosomes. The pathogenic fungus Zymoseptoria tritici has as many as eight accessory chromosomes, which are highly unstable during meiosis and mitosis, transcriptionally repressed, show enrichment of repetitive elements, and enrichment with heterochromatic histone methylation marks, e.g., trimethylation of H3 lysine 9 or lysine 27 (H3K9me3, H3K27me3). To elucidate the role of heterochromatin on genome stability in Z. tritici, we deleted the genes encoding the methyltransferases responsible for H3K9me3 and H3K27me3, kmt1 and kmt6, respectively, and generated a double mutant. We combined experimental evolution and genomic analyses to determine the impact of these deletions on chromosome and genome stability, both in vitro and in planta. We used whole genome sequencing, ChIP-seq, and RNA-seq to compare changes in genome and chromatin structure, and differences in gene expression between mutant and wildtype strains. Analyses of genome and ChIP-seq data in H3K9me3-deficient strains revealed dramatic chromatin reorganization, where H3K27me3 is mostly relocalized into regions that are enriched with H3K9me3 in wild type. Many genome rearrangements and formation of new chromosomes were found in the absence of H3K9me3, accompanied by activation of transposable elements. In stark contrast, loss of H3K27me3 actually increased the stability of accessory chromosomes under normal growth conditions in vitro, even without large scale changes in gene activity. We conclude that H3K9me3 is important for the maintenance of genome stability because it disallows H3K27me3 in these regions. In this system, H3K27me3 reduces the overall stability of accessory chromosomes, generating a \"metastable\" state for these quasi-essential regions of the genome.\n\nAuthor SummaryGenome and chromosome stability are essential to maintain normal cell function and viability. However, differences in genome and chromosome structure are frequently found in organisms that undergo rapid adaptation to changing environmental conditions, and in humans are often found in cancer cells. We study genome instability in a fungal pathogen that exhibits a high degree of genetic diversity. Regions that show extraordinary diversity in this pathogen are the transposon-rich accessory chromosomes, which contain few genes that are of unknown benefit to the organism but maintained in the population and thus considered \"quasi essential\". Accessory chromosomes in all fungi studied so far are enriched with markers for heterochromatin, namely trimethylation of H3 lysine 9 and 27 (H3K9me3, H3K27me3). We show that loss of these heterochromatin marks has strong but opposing effects on genome stability. While loss of the transposon-associated mark H3K9me3 destabilizes the entire genome, presence of H3K27me3 favors instability of accessory chromosomes. Our study provides insight into the relationship between chromatin and genome stability and why some regions are more susceptible to genetic diversity than others.

genetics↗

bioRxiv2018

Heritability and genetic variance of dementia with Lewy bodies

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinsons disease (PD) or Alzheimers disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.

neuroscience↗

bioRxiv2018

Stochastic models of the growth dynamics of some dendritic cells

Different models of tumor growth are considered. Some mathematical methods are developed to analyze the dynamics of mutations enabling cells in cancer patients to metas-tize. The mathematical models consist of some stochastic dynamical systems describing tumor cells and immune effectors. It is also considered a method to find the ideal outcome of some treatments. Some different types of dendritic cells are considered. The obtained results will help to find some suitable treatments,which can be successful in returning an aggressive tumor to its passive,non-immune evading state. The principle goal of this paper is to find ways to treat the cancer tumors before they can reach an advanced stage devel-opmen.\n\nAMS Subject Classifications92B05, 37C45.

bioengineering↗

bioRxiv2018

Increasing phylogenetic stochasticity at high elevations on summits across a remote North American wilderness

PREMISE OF THE STUDYAt the intersection of ecology and evolutionary biology, community phylogenetics can provide insights into overarching biodiversity patterns, particularly in remote and understudied ecosystems. To understand community assembly of the high-alpine flora of the Sawtooth National Forest, USA, we analyzed phylogenetic structure within and between nine summit communities.\n\nMETHODSWe used high-throughput sequencing to supplement existing data and infer a nearly completely sampled community phylogeny of the alpine vascular flora. We calculated mean nearest taxon distance (MNTD) and mean pairwise distance (MPD) to quantify phylogenetic divergence within summits, and assed how maximum elevation explains phylogenetic structure. To evaluate similarities between summits we quantified phylogenetic turnover, taking into consideration micro-habitats (talus vs. meadows).\n\nKEY RESULTSWe found different patterns of community phylogenetic structure within the six most species-rich orders, but across all vascular plants phylogenetic structure was largely no different from random. There was a significant negative correlation between elevation and tree-wide phylogenetic diversity (MPD) within summits: significant overdispersion degraded as elevation increased. Between summits we found high phylogenetic turnover, which was driven by greater niche heterogeneity on summits with alpine meadows.\n\nCONCLUSIONSThis study provides further evidence that stochastic processes shape the assembly of vascular plant communities in the high-alpine at regional scales. However, order-specific patterns suggest adaptations may be important for assembly of specific sectors of the plant tree of life. Further studies quantifying functional diversity will be important to disentangle the interplay of eco-evolutionary processes that likely shape broad community phylogenetic patterns in extreme environments.

evolutionary biology↗

bioRxiv2018

Fast Hierarchical Bayesian Analysis of Population Structure

We present fastbaps, a fast solution to the genetic clustering problem. Fastbaps rapidly identifies an approximate fit to a Dirichlet Process Mixture model (DPM) for clustering multilocus genotype data. Our efficient model-based clustering approach is able to cluster datasets 10-100 times larger than the existing model-based methods, which we demonstrate by analysing an alignment of over 110,000 sequences of HIV-1 pol genes. We also provide a method for rapidly partitioning an existing hierarchy in order to maximise the DPM model marginal likelihood, allowing us to split phylogenetic trees into clades and subclades using a population genomic model. Extensive tests on simulated data as well as a diverse set of real bacterial and viral datasets show that fastbaps provides comparable or improved solutions to previous model-based methods, while generally being significantly faster. The method is made freely available under an open source MIT licence as an easy to use R package at https://github.com/gtonkinhill/fastbaps.

genomics↗