Biology subjects

Martin, D. P.

Publications and source records attributed to Martin, D. P..

18 recordsLinked to original sources

bioRxiv2026

Auditing Biomedical Literature with Blinded AI Peer Review: Where Peer Review Works, Where It Fails, and How to Strengthen It

Biomedical publishing has grown more than elevenfold since 1991, outstripping human peer review. Unblinded language models cannot audit this literature objectively because they recognize famous authors and journals from training memory. We built BARS (Blinded AI Review System), an automated referee that strips titles, author names, institutions, journal headers, and dates before grading full-text manuscripts on a 10-point scale covering methods, evidence, biology, and reproducibility. We used BARS to generate 1,874 blind reviews across 1,714 unique papers. BARS passed 100% of verified sound controls, caught 77% to 91% of internally flawed papers, eliminated a +0.35-point prestige boost, and more than doubled human referee consistency. Across 320 recent open-access articles (2020-2025) from eight fields, 54% failed on core scientific rigor (<5.0/10; 41% excluding megajournals). Revision at selective journals improved preprints more than twice as much as revision at commercial megajournals (+0.62 vs. +0.30 points; baseline-adjusted p = 0.033), and BARS recalled 98% of unresolved human referee critiques across 100 open-review papers. Across 915 date-blinded papers from 1991 to 2025, average scores fell from 7.6/10 to 5.8/10 as megajournals and template database studies expanded. Blinded self-audits of 238 papers by two senior authors -- and of this manuscript itself -- caught real statistical, control, and table errors in our own work. At four cents per paper, BARS offers a practical quality check for authors, journals, and readers (https://veg.github.io/BARS/).

scientific communication and education↗

bioRxiv2026

Clean Breaks: Attention Force Field Deconvolution of Recombination Across Sequence Manifolds

Homologous recombination and horizontal gene transfer assemble mosaic chromosomes across divergent lineages. Reticulate evolution violates bifurcating trees, yet existing detectors enforce a stark trade-off: phylogenetic changepoint models optimize partitioned topologies at exponential computational cost, whereas sequence triplet heuristics evaluate rapidly but suffer from severe combinatorial event overcounting. We introduce RhizAeon, an open-source platform that deconvolves reticulate evolution through continuous trajectory mechanics across metric embeddings in linear time (O(N K L)). Projecting aligned sequences into canonical metric coordinates and routing lineage-specific rate variation into an unpolarized root sink, the engine iteratively scrubs mosaic tracts and verifies breakpoints through Brownian-bridge statistics, dyadic matched filters, and maximum-likelihood polishing. Across canonical coalescent benchmarks and a continuous parameter sweep of 1,000,000 whole genomes, RhizAeon bounds false-positive rates well below the 5.0% nominal ceiling (0.58% on 1,200 rate-variation nulls and 1.01% across 333,334 continuous sweep nulls). Leave-one-in verification and bidirectional overlap clustering collapse co-recombinant clades into single ancestral reticulations. Empirical analyses across wildlife sarbecovirus Spike chimeras, multidrug-resistant Streptococcus pneumoniae chromosomes (2.22 Mb), and 379 primate HLA Class I alleles reconstruct complex whole-genome mosaicism, cassette exchanges, and micro-conversions in seconds. The core engine compiles to WebAssembly for interactive execution within standard web browsers.

evolutionary biology↗

bioRxiv2026

HyphAeon: Attention on Evolution Across Deep Time Transforms Comparative Genomics

Detecting Darwinian natural selection is fundamental to evolutionary biology and functional genomics, yet standard methods based on phylogenetic models that estimate the ratio of non-synonymous to synonymous substitution rates (dN/dS) fail to scale with modern genomic volumes. Fitting continuous-time Markov substitution matrices across dense trees with hundreds of species requires extensive compute, forcing comparative genomics to rely on aggressive taxon subsampling or static whole-tree summaries that dilute transient adaptive bursts. Here we present HyphAeon, a lightweight (~1.91M parameter backbone, 2.46M across the full multi-task suite) phylogeny-informed foundation transformer trained to amortize the detection of episodic diversifying selection across 742-species mammalian coding alignments (17,186 genes, 9.77 x 10^6 codons). HyphAeon approaches the discriminative accuracy of numerical maximum-likelihood selection tests (MEME) across episodic burst regimes (ROC-AUC up to 0.942, mean 0.659; empirical Precision-Recall lift up to 25.8x, mean 7.7x; rank concordance up to rho = 0.983) while executing >1,000x faster per locus (averaging <1 ms per site across genome-wide scans) and >10,000x faster at proteome scale, generalizing outside its mammalian training distribution without retraining. Beyond accelerating classical tests, embedding molecular evolution into a differentiable geometric latent space enables analytical capabilities inaccessible to static dN/dS models: (1) targeted alignment artifact correction via counterfactual attribution; (2) macromolecular contact recovery and multi-site epistatic sectors (CESI); (3) directional phenotype-to-genotype attribution in lineage space (PARS); and (4) continuous temporal surveillance regression that tracks positive sweep velocities across longitudinal cohorts (evaluated across 12,167 timestamped genomes and benchmarked against external frequencies from >9.34 million genomes), rescuing adaptive substitutions obscured by post-fixation dilution. By bridging statistical phylogenetics with geometric representation learning, HyphAeon establishes comparative genomics as an interactive, high-throughput computational framework for evolutionary discovery.

bioinformatics↗

bioRxiv2026

SRARec: A program for detecting recombination in sequencing reads and its application to uncover recombination patterns in SARS-CoV-2 and HIV-1

The detection of recombination using consensus genome sequences has key limitations including failure to consider rare genetic variants and misidentification of artifactually assembled genome chimaeras as biological recombinants. However, commonly used recombination detection tools are not designed to directly analyse sequencing read data. Here, we present SRARec, a recombination detection tool that operates directly on raw reads. SRARec identifies polymorphic sites and applies the four-gamete test to detect recombination at the read level. The software incorporates mapping and quality filters and can analyse large repositories of raw sequencing data. Simulation validations showed that, given sufficient sequence diversity, SRARec can accurately detect recombination breakpoints. The consideration of rare variants makes SRARec particularly useful for detecting recombination in intra-host viral populations. Therefore, we applied the tool to 601,045 SARS-CoV-2 and 4,999 HIV-1 read datasets from the Sequence Read Archive (SRA, NCBI), enabling unprecedented genome-wide screening of intra-host recombination breakpoint signals at read-level resolution. Aggregating across all analysed datasets, the distribution of detected recombination breakpoint counts along genomes differed between these viruses, with pervasive breakpoint signals detectable in HIV-1 and sporadic clustered breakpoint hotspots in SARS-CoV-2. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/741747v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@aa58fforg.highwire.dtl.DTLVardef@1b9061borg.highwire.dtl.DTLVardef@4010f1org.highwire.dtl.DTLVardef@1853e2_HPS_FORMAT_FIGEXP M_FIG C_FIG

evolutionary biology↗

bioRxiv2026

Beyond Invariable Sites: Using Evolutionary Stasis to Map Multi-Layered Constraints on the Evolution of Viral and Mammalian Genomes

The quantification of genomic conservation has progressed from foundational statistical modeling of evolutionary rates to state-of-the-art phylogeny-aware deep learning architectures. Yet, a fundamental resolution gap remains whenever evolutionary rates closely approach the "zero-rate origin," where standard selection inference tools will essentially ignore signals of extreme purifying section at invariant genome sites. We present B-STILL (Bayesian Significance Test of Invariant Low Likelihoods), a hierarchical Bayesian framework designed to resolve the selective landscape of protein-coding data by leveraging gene-level calibration and codon-site specific evolutionary opportunity. This framework is based on computationally efficient approximations using codon-substitution models which are scalable to alignments with thousands of sequences. By explicitly tuning the stasis radius around the near-zero evolutionary-rate regime, B-STILL distinguishes between stochastic invariance and functional constraint, identifying Evolutionary Stasis Anchors (ESAs) where the upper bound on permitted evolutionary change is statistically anomalous relative to the background of the gene. This hierarchical approach provides a signature of functional or structural constraint that is often difficult to detect using other tools. Validation against extensive pathogen and clinical databases confirms that ESAs are predictors of biological fitness and disease potential. Collectively, we identified thousands of significantly clustered ESAs that precisely footprint both known functional domains and currently uncharacterized structural motifs in mammalian and viral genomes. These findings establish B-STILL as a scalable statistical framework for high-resolution genomic annotation, transforming formerly ignored invariant genome and protein sites into informative markers of extreme purifying selection across both well-characterized and uncharacterized protein-coding genes from different domains of life.

evolutionary biology↗

bioRxiv2026

Genetic Evidence Indicates the Evolutionary Importance of the SARS-CoV-2 ORF9b protein

All known betacoronaviruses possess an overlapping alternate-frame gene within the nucleocapsid gene. In SARS-CoV-2, the gene for this "internal protein" is ORF9b. The WHO Variants of Concern (VOC) Alpha, Delta, and Omicron all possess noncoding mutations that increase ORF9b expression. We show that with two exceptions, every major variant of the VOC era has had similar noncoding mutations to increase ORF9b expression and that these mutations are also frequently seen in long-branch, anachronistic, posited chronic-infection (PCI) sequences. Furthermore, we show that the amino acid substitution rate in ORF9b is higher than for any other SARS-CoV-2 gene, both in high-quality circulating sequences and in PCI sequences. This suggests that, as immunity to SARS-CoV-2 has grown in the population, increased ORF9b expression has conferred an evolutionary advantage, likely due to its ability to antagonize the antiviral type-I interferon response. We also show that PCI sequences are marked by distinct mutational patterns in ORF9b, some of which later became prominent in major variants. This evidence points to the importance of ORF9b for both viral transmission and within-host persistence.

microbiology↗

bioRxiv2025

scoup: Simulate Codon Sequences with Darwinian Selection Incorporated as an Ornstein-Uhlenbeck Process

Genetic analyses of natural selection within and between populations have increasingly developed along separate paths. The two important genres of evolutionary biology (i.e. phylogenetics and population genetics) borne from the split can only benefit from research that seeks to bridge the gap. Simulation algorithms that combine fundamental concepts from both genres are important to achieve such unifying objective. We introduce scoup, a codon sequence simulator that is implemented in R and hosted on the Bioconductor platform. There is hardly any other simulator dedicated to genetic sequence generation for natural selection analyses on the platform. Concepts from the Halpern-Bruno mutation-selection model and the Ornstein-Uhlenbeck (OU) evolutionary algorithm were creatively fused such that the end-product is a novelty with respect to computational genetic simulation. Users are able to seamlessly adjust the model parameters to mimic complex evolutionary procedures that may have been otherwise infeasible. For example, it is possible to explicitly interrogate the concepts of static and changing fitness landscapes with regards to Darwinian natural selection in the context of codon sequences from multiple populations.

evolutionary biology↗

bioRxiv2025

difFUBAR: Scalable Bayesian comparison of adaptive evolution

While many phylogenetic methods exist to characterize evolutionary pressure at individual codon sites, relatively few allow direct comparison between different a priori selected sets of branches. Such comparisons may be useful for pinpointing precisely the codon sites that are under differing selective pressures due to differing environmental contexts, or differing genomic contexts via epistatic interactions. Indeed, this was only recently addressed by an approach, developed in the frequentist framework, that proposes a site-wise likelihood ratio hypothesis test. Previously, we have demonstrated that approximate grid-based Bayesian approaches to characterizing site-wise variation in selection parameters can outperform individual site-wise likelihood ratio tests. Such grid-based approaches can exhibit poor computational scaling when the number of site-wise parameters expands, but here we show that this is still tractable up to four parameters, and that a simple subtree-likelihood caching strategy can provide efficiency improvements in some cases. We propose difFUBAR, which allows the demarcation of two branch sets of interest and, optionally, a background set, and estimates joint site-specific posterior distributions over , {omega}1,{omega} 2, and{omega} BG using a Gibbs sampler. Evidence for hypotheses of interest can then be quantified directly from the posterior distribution, and we standardly report P ({omega}1 > {omega}2), P ({omega}2 > {omega}1), P ({omega}1 > 1), and P ({omega}2 > 1). We characterize the computational and statistical performance of this approach on previous simulations, comparing it to the site-wise likelihood ratio test approach, where it shows moderate statistical benefits, and substantial computational gains, typically being more than two orders of magnitude faster on the same datasets. We also demonstrate that it can scale to datasets of over ten thousand taxa, on a laptop in under ten minutes. difFUBAR is implemented in MolecularEvolution.jl - a Julia framework for phylogenetic model development - and can be run locally, or online via a Colab notebook.

bioinformatics↗

bioRxiv2024

Nasopharyngeal specific selection and emergence of SARS-CoV-2 spike fusion peptide mutation P812S during chronic infection

Omicron emergence represented a seismic event in the COVID-19 pandemic, demonstrating what was essentially antigenic shift in a virus that cannot reassort its genome as influenza can. Understanding the success of Omicron is essential, and yet we have little understanding of the biological underpinnings of its ability to accommodate diverse mutations and bring together deleterious mutations to generate a highly successful new serotype. Persistent SARS-CoV-2 infections are a likely source of new variants and may provide valuable insight into past and future evolutionary trajectories, in particular those involving allosteric interactions that defy genotype to phenotype prediction. Here we observe upper airway specific evolution of SARS-CoV-2 demonstrating fusion peptide (FP) domain mutation S:P812S adjacent to the S2 cleavage site that emerged during a chronic infection in an immunocompromised individual. Indeed, this mutation had previously emerged in an ancestral B lineage as well as the delta variant lineage and transmitted successfully in populations globally, though remains uncharacterised. P812S in spike pseudotyped virus particles did not impact entry efficiency across cell lines expressing endogenous ACE2 and TMPRSS2. However, efficiency of spike cleavage at S1/S2 was reduced and molecular dynamics simulation demonstrated altered S1/S2 loop conformations that possibly impacted furin mediated cleavage. Consistent with impaired S1/S2 cleavage, and reminiscent of Omicron BA.1, cell-cell fusogenicity was severely impaired by introduction of P812S. The mutation also introduced significant perturbations to the FP region and also affected protomer-protomer packing. P812S conferred evasion of a neutralising monoclonal antibody targeting the fusion peptide, consistent with significant structural rearrangements in the FP region. Finally, P812S bearing viruses showed evasion of polyclonal neutralising antibodies in sera from vaccinated individuals at 32{degrees}C (simulating upper respiratory tract) and to a lesser extent at 37{degrees}C. Thus we report a novel mutational adaptation to the upper airway allowing enhanced immune evasion to fusion peptide targeting neutralising antibodies that also incurs a defect in ability to induce syncytia. These data shed light on the balance between upper airway adaptation/immune evasion by SARS-CoV-2, ability to induce syncytia formation, and disease severity given the established link between syncytia and severe COVID-19.

immunology↗

bioRxiv2023

Network-based integrative multi-omics approach reveals biosignatures specific to COVID-19 disease phases.

BackgroundCOVID-19 disease is characterized by a spectrum of disease phases (mild, moderate, and severe). Each disease phase is marked by changes in omics profiles with corresponding changes in the expression of features (biosignatures). However, integrative analysis of multiple omics data from different experiments across studies to investigate biosignatures at various disease phases is limited. Exploring an integrative multi-omics profile analysis through a network approach could be used to determine biosignatures associated with specific disease phases and enable the examination of the relationships between the biosignatures. AimTo identify and characterize biosignatures underlying various COVID-19 disease phases in an integrative multi-omics data analysis. MethodWe leveraged the correlation network approach to integrate transcriptomics, metabolomics, proteomics, and lipidomics data. The World Health Organization (WHO) Ordinal Scale (WOS) was used as a disease severity reference to harmonize COVID-19 patient metadata across two studies with independent data. A unified COVID-19 knowledge graph was constructed by assembling a disease-specific interactome from the literature and databases. Disease-state omics-specific graphs were constructed by integrating multi-omics data with the unified COVID-19 knowledge graph. We expanded on the network layers of multiXrank, a random walk with restart on multilayer network algorithm, to explore disease state omics-specific graphs and perform enrichment analysis. ResultsNetwork analysis revealed the biosignatures involved in inducing chemokines and inflammatory responses as hubs in the severe and moderate disease phases. We observed more shared biosignatures between severe and moderate disease phases as compared to mild-moderate and mild-severe disease phases. We further identified both biosignatures that discriminate between the disease states and interactions between biosignatures that are either common between or associated with COVID-19 disease phases. Interestingly, cross-layer interactions between different omics profiles increased with disease severity. ConclusionThis study identified both biosignatures of different omics types enriched in disease-related pathways and their associated interactions that are either common between or unique to mild, moderate, and severe COVID-19. These biosignatures include molecular features that underlie the observed clinical heterogeneity of COVID-19 and emphasize the need for disease-phase-specific treatment strategies. In addition, the approach implemented here can be used for other diseases. Key findings Integrative multi-omics analysis revealed biosignatures and biosignature interactions associated with COVID-19 disease states. Disease severity increases with biosignature interactions across different multi-omics data. The harmonization approach proposed and implemented here can be applied to other diseases

bioinformatics↗

bioRxiv2023

Primary Ciliary Dyskinesia patient specific hiPSC-derived airway epithelium in Air Liquid Interface culture recapitulates disease specific phenotypes in vitro

Primary ciliary dyskinesia (PCD) is a rare heterogenic genetic disorder associated with perturbed biogenesis or function of motile cilia. Motile cilia dysfunction results in diminished mucociliary clearance (MCC) of pathogens in the respiratory tract and chronic airway inflammation and infections successively causing progressive lung damage. Current approaches to treat PCD are symptomatic, only, indicating an urgent need for curative therapeutic options. Here, we developed an in vitro model for PCD based on human induced pluripotent stem cell (hiPSC)-derived airway epithelium in Air-Liquid-Interface cultures. Applying transmission electron microscopy, immunofluorescence staining, ciliary beat frequency and mucociliary transport measurements, we could demonstrate that ciliated respiratory epithelia cells derived from two PCD patient specific hiPSC lines carrying mutations in DNAH5 and NME5, respectively, recapitulate the respective diseased phenotype on a molecular, structural and functional level.

bioengineering↗

bioRxiv2022

Selection analysis identifies unusual clustered mutational changes in Omicron lineage BA.1 that likely impact Spike function

Among the 30 non-synonymous nucleotide substitutions in the Omicron S-gene are 13 that have only rarely been seen in other SARS-CoV-2 sequences. These mutations cluster within three functionally important regions of the S-gene at sites that will likely impact (i) interactions between subunits of the Spike trimer and the predisposition of subunits to shift from down to up configurations, (ii) interactions of Spike with ACE2 receptors, and (iii) the priming of Spike for membrane fusion. We show here that, based on both the rarity of these 13 mutations in intrapatient sequencing reads and patterns of selection at the codon sites where the mutations occur in SARS-CoV-2 and related sarbecoviruses, prior to the emergence of Omicron the mutations would have been predicted to decrease the fitness of any genomes within which they occurred. We further propose that the mutations in each of the three clusters therefore cooperatively interact to both mitigate their individual fitness costs, and adaptively alter the function of Spike. Given the evident epidemic growth advantages of Omicron over all previously known SARS-CoV-2 lineages, it is crucial to determine both how such complex and highly adaptive mutation constellations were assembled within the Omicron S-gene, and why, despite unprecedented global genomic surveillance efforts, the early stages of this assembly process went completely undetected.

evolutionary biology↗

bioRxiv2022

RASCL: Rapid Assessment Of SARS-CoV-2 Clades Through Molecular Sequence Analysis

An important component of efforts to manage the ongoing COVID19 pandemic is the Rapid Assessment of how natural selection contributes to the emergence and proliferation of potentially dangerous SARS-CoV-2 lineages and CLades (RASCL). The RASCL pipeline enables continuous comparative phylogenetics-based selection analyses of rapidly growing clade-focused genome surveillance datasets, such as those produced following the initial detection of potentially dangerous variants. From such datasets RASCL automatically generates down-sampled codon alignments of individual genes/ORFs containing contextualizing background reference sequences, analyzes these with a battery of selection tests, and outputs results as both machine readable JSON files, and interactive notebook-based visualizations. AvailabilityRASCL is available from a dedicated repository at https://github.com/veg/RASCL and as a Galaxy workflow https://usegalaxy.eu/u/hyphy/w/rascl. Existing clade/variant analysis results are available here: https://observablehq.com/@aglucaci/rascl. ContactDr. Sergei L Kosakovsky Pond (spond@temple.edu). Supplementary informationN/A

bioinformatics↗

bioRxiv2021

Variable loss of antibody potency against SARS-CoV-2 B.1.1.529 (Omicron)

The recently-emerged SARS-CoV-2 B.1.1.529 variant (Omicron) is spreading rapidly in many countries, with a spike that is highly diverged from the pandemic founder, raising fears that it may evade neutralizing antibody responses. We cloned the Omicron spike from a diagnostic sample which allowed us to rapidly establish an Omicron pseudotyped virus neutralization assay, sharing initial neutralization results only 13 days after the variant was first reported to the WHO, 8 days after receiving the sample. Here we show that Omicron is substantially resistant to neutralization by several monoclonal antibodies that form part of clinical cocktails. Further, we find neutralizing antibody responses in pooled reference sera sampled shortly after infection or vaccination are substantially less potent against Omicron, with neutralizing antibody titers reduced by up to 45 fold compared to those for the pandemic founder. Similarly, in a cohort of convalescent sera prior to vaccination, neutralization of Omicron was low to undetectable. However, in recent samples from two cohorts from Stockholm, Sweden, antibody responses capable of cross-neutralizing Omicron were prevalent. Sera from infected-then-vaccinated healthcare workers exhibited robust cross-neutralization of Omicron, with an average potency reduction of only 5-fold relative to the pandemic founder variant, and some donors showing no loss at all. A similar pattern was observed in randomly sampled recent blood donors, with an average 7-fold loss of potency. Both cohorts showed substantial between-donor heterogeneity in their ability to neutralize Omicron. Together, these data highlight the extensive but incomplete evasion of neutralizing antibody responses by the Omicron variant, and suggest that increasing the magnitude of neutralizing antibody responses by boosting with unmodified vaccines may suffice to raise titers to levels that are protective.

immunology↗

bioRxiv2021

Recent zoonotic spillover and tropism shift of a Canine Coronavirus is associated with relaxed selection and putative loss of function in NTD subdomain of spike protein.

A recent study reported the occurrence of Canine Coronavirus (CCoV) in nasopharyngeal swabs from a small number of patients hospitalized with pneumonia during a 2017-18 period in Sarawak, Malaysia. Because the genome sequence for one of these isolates is available, we conducted comparative evolutionary analyses of the spike gene of this strain (CCoV-HuPn-2018), with other available Alphacoronavirus 1 spike sequences. The most N-terminus subdomain (0-domain) of the CCoV-HuPn-2018 spike protein has sequence similarity to Transmissible Gastroenteritis Virus (TGEV) and CCoV2b strains, but not to other members of the type II Alphacoronaviruses (i.e., CCoV2a and Feline CoV2-FCoV2). This 0-domain in CCoV-HuPn-2018 has evidence for relaxed selection pressure, an increased rate of molecular evolution, and a number of unique amino acid substitutions relative to CCoV2b and TGEV sequences. A region of the 0-domain determined to be key to sialic acid binding and pathogenesis in TGEV had clear differences in amino acid sequences in CCoV-HuPn-2018 relative to both CCoV2b (enteric) and TGEV (enteric and respiratory). The 0-domain of CCoV-HuPn-2018 also had several sites inferred to be under positive diversifying selection, including sites within the signal peptide. Downstream of the 0-domain, FCoV2 shared sequence similarity to the CCoV2b and TGEV sequences, with analyses of this larger alignment identifying positively selected sites in the putative Receptor Binding Domain (RBD) and Connector Domain (CD). Recombination analyses strongly implicated a particular FCoV2 strain in the recombinant history of CCoV-HuPn-2018 with molecular divergence times estimated at around 60 years ago. We hypothesize that CCoV-HuPn-2018 had an enteric origin, but that it has lost that particular tropism, because of mutations in the sialic acid binding region of the spike 0-domain. As selection pressure on this region was reduced, the virus evolved a respiratory tropism, analogous to other Alphacoronavirus 1, such as Porcine Respiratory Coronavirus (PRCV), that have lost this region entirely. We also suggest that signals of positive selection in the signal peptide as well as other changes in the 0-domain of CCoV-HuPn-2018 could represent an adaptive role in this new host and that this could be in part due to the different spatial distribution of the N-linked glycan repertoire for this strain.

evolutionary biology↗

bioRxiv2021

A novel lineage of polyomaviruses identified in bark scorpions

Polyomaviruses are non-enveloped viruses with circular double-stranded DNA genomes that range in size from [~]4-7 kilobasepairs. Initially identified in mammals, polyomaviruses have now been identified in birds and a few fish species. Although fragmentary polyomavirus-like sequences have been detected as apparent hitchhikers in shotgun genomics datasets for various arthropods, the possible diversity of these viruses in invertebrates remains unclear. In general, polyomaviruses are host-specific, showing strong evidence of host-virus co-evolution. Identification of polyomaviruses in a broader range of animals could shed useful light on the evolutionary history of this medically important group of viruses. Scorpions are predatory arachnids that are among the oldest terrestrial animals. Thus far, viromes of arachnids have been under-sampled and understudied. Here, high-throughput sequencing and traditional molecular techniques were used to explore the diversity of circular DNA viruses associated with bark scorpions (Centruroides sculpturatus) from the greater Phoenix area, Arizona, USA. The complete genomes of eight novel polyomaviruses were identified. Analysis of Centruroides transcriptomic datasets elucidated the splicing of the viral late gene array, which is more complex than that of vertebrate polyomaviruses. Phylogenetic analysis provides further evidence of co-divergence of polyomaviruses with their hosts, suggesting that at least one ancestral species of polyomaviruses was circulating amongst the primitive common ancestors of arthropods and chordates.

microbiology↗

bioRxiv2020

Integrated Molecular Characterisation of the MAPK Pathways in Human Cancers

The mitogen-activated protein kinase (MAPK) pathways are a crucial regulator of the cellular processes that fuel the malignant transformation of normal cells. The genetic underpinnings of molecular aberrations which lead to cancer involve mutations in and, transcription variations of, various MAPK pathway genes. Here, we use datasets of 40,848 patient-derived tumours representing 101 distinct human cancers to identify cancer-associated mutations in MAPK signalling pathway genes. We identify the subset of these genes within which mutations tend to be associated with the worst disease outcomes. Furthermore, by integrating information extracted from various large-scale molecular datasets, we expose the relationship between the fitness of cancer cells after CRISPR mediated gene knockout of MAPK pathway genes, and their dose-responses to MAPK pathway inhibitors. Besides providing new insights into MAPK pathways, we unearth vulnerabilities in specific pathway genes that are reflected in the responses of cancer cells to MAPK drug perturbations: a revelation with great potential for guiding the development of innovative therapeutic strategies.

bioinformatics↗

bioRxiv2019

crAssphage abundance and genomic selective pressure correlate with altered bacterial abundance in the fecal microbiota of South African mother-infant dyads

crAssphages are a class of bacteriophages that are highly abundant in the human gastrointestinal tract. Accordingly, crAssphage genomes have been identified in most human fecal viral metagenome studies. However, we currently have an incomplete understanding of factors impacting the transmission frequencies of these phages between mothers and infants, and the evolutionary pressures associated with such transmissions. Here, we use metagenome sequencing of stool-associated virus-like particles to identify the prevalence of crAssphage across ten South African mother-infant dyads that are discordant for HIV infection. We report the identification of a complete 97kb crAssphage genome, parts of which are detected at variable levels across each mother-infant dyad. We observed average nucleotide sequence identities of >99% for crAssphages from related mother-infant pairs but [~]97% identities between crAssphages from unrelated mothers and infants: a finding strongly suggestive of vertical mother to infant transmission. We further analyzed patterns of nucleotide diversity across the crAssphage sequences described here, identifying particularly elevated positive selection in RNA polymerase and phage tail protein encoding genes, which we validated against a crAssphage genome from previous studies. Using 16S rRNA gene sequencing, we found that the relative abundances of Bacteroides thetaiotaomicron and Parabacteroides merdae (Order: Bacteroidales) were differentially correlated with crAssphage abundance. Together, our results reveal that crAssphages may be vertically transmitted from mothers to their infants and that hotspots of selection within crAssphage RNA polymerase and phage tail protein encoding genes are potentially mediated by interactions between crAssphages and their bacterial partners.\n\nImportancecrAssphages are an ubiquitous member of the human gut microbiome and modulate interactions with key bacterial associates within the order Bacteroidales. However, the role of this interaction in the genomic evolution of crAssphage remains unclear. Across a longitudinally sampled cohort of ten South African mother-infant dyads, we use metagenome sequencing of the fecal virome and 16S rRNA gene sequencing of the fecal bacterial microbiota to elucidate the ecological and evolutionary dynamics of these interactions. Here, we demonstrate elevated levels of crAssphage average nucleotide identity between related mother-infant dyads as compared to unrelated individuals, suggesting vertical transmission. We report strong positive selection in crAssphage RNA polymerase and phage tail protein genes. Finally, we demonstrate that crAssphage abundance is linearly correlated (P < 0.014) with the abundance of two bacterial taxa, Bacteroides thetaiotaomicron and Parabacteroides merdae. These results suggest that phage-bacterial interactions may help shape ecological and evolutionary dynamics in the gut.

microbiology↗