Biology subjects

Dylus, D.

Publications and source records attributed to Dylus, D..

6 recordsLinked to original sources

bioRxiv2023

The brittle star genome illuminates the genetic basis of animal appendage regeneration

Species within nearly all extant animal lineages are capable of regenerating body parts. However, it remains unclear whether the gene expression programme controlling regeneration is evolutionarily conserved. Brittle stars are a species-rich class of echinoderms with outstanding regenerative abilities, but investigations into the genetic bases of regeneration in this group have been hindered by the limited genomic resources. Here, we report a chromosome-scale genome assembly for the brittle star Amphiura filiformis. We show that the brittle star genome is the most rearranged amongst echinoderms sequenced to date, featuring a reorganised Hox cluster reminiscent of the rearrangements observed in sea urchins. In addition, we performed an extensive profiling of gene expression during brittle star adult arm regeneration and identified sequential waves of gene expression governing wound healing, proliferation and differentiation. We conducted comparative transcriptomic analyses with other invertebrate and vertebrate models for appendage regeneration and uncovered hundreds of genes with conserved expression dynamics, particularly during the proliferative phase of regeneration. Our findings emphasise the crucial importance of echinoderms to detect long-range expression conservation between vertebrates and classical invertebrate regeneration model systems.

evolutionary biology↗

bioRxiv2023

Human Th17- and IgG3-associated autoimmunity induced by a translocating gut pathobiont

Extraintestinal autoimmune diseases are multifactorial with translocating gut pathobionts implicated as instigators and perpetuators in mice. However, the microbial contributions to autoimmunity in humans remain largely unclear, including whether specific pathological human adaptive immune responses are triggered by such pathobionts. We show here that the translocating pathobiont Enterococcus gallinarum induces human IFN{gamma}+ Th17 differentiation and IgG3 subclass switch of anti-E. gallinarum RNA and correlating anti-human RNA autoantibody responses in patients with systemic lupus erythematosus and autoimmune hepatitis. Human Th17 induction by E. gallinarum is cell-contact dependent and involves TLR8-mediated human monocyte activation. In murine gnotobiotic lupus models, E. gallinarum translocation triggers IgG3 anti-RNA autoantibody titers that correlate with renal autoimmune pathophysiology and with disease activity in patients. Overall, we define cellular mechanisms of how a translocating pathobiont induces human T- and B-cell-dependent autoimmune responses, providing a framework for developing host- and microbiota-derived biomarkers and targeted therapies in extraintestinal autoimmune diseases. One Sentence SummaryTranslocating pathobiont Enterococcus gallinarum promotes human Th17 and IgG3 autoantibody responses linked to disease activity in autoimmune patients.

immunology↗

bioRxiv2022

Read2Tree: scalable and accurate phylogenetic trees from raw reads

The inference of phylogenetic trees is foundational to biology. However, state-of-the-art phylogenomics requires running complex pipelines, at significant computational and labour costs, with additional constraints in sequencing coverage, assembly and annotation quality. To overcome these challenges, we present Read2Tree, which directly processes raw sequencing reads into groups of corresponding genes. In a benchmark encompassing a broad variety of datasets, our assembly-free approach was 10-100x faster than conventional approaches, and in most cases more accurate--the exception being when sequencing coverage was high and reference species very distant. To illustrate the broad applicability of the tool, we reconstructed a yeast tree of life of 435 species spanning 590 million years of evolution. Applied to Coronaviridae samples, Read2Tree accurately classified highly diverse animal samples and near-identical SARS-CoV-2 sequences on a single tree--thereby exhibiting remarkable breadth and depth. The speed, accuracy, and versatility of Read2Tree enables comparative genomics at scale.

bioinformatics↗

bioRxiv2019

The phylogenetic range of bacterial and viral pathogens of vertebrates

Many major human pathogens are multi-host pathogens, able to infect other vertebrate species. Describing the general patterns of host-pathogen associations across pathogen taxa is therefore important to understand risk factors for human disease emergence. However, there is a lack of comprehensive curated databases for this purpose, with most previous efforts focusing on viruses. Here, we report the largest manually compiled host-pathogen association database, covering 2,595 bacteria and viruses infecting 2,656 vertebrate hosts. We also build a tree for host species using nine mitochondrial genes, giving a quantitative measure of the phylogenetic similarity of hosts. We find that the majority of bacteria and viruses are specialists infecting only a single host species, with bacteria having a significantly higher proportion of specialists compared to viruses. Conversely, multi-host viruses have a more restricted host range than multi-host bacteria. We perform multiple analyses of factors associated with pathogen richness per host species and the pathogen traits associated with greater host range and zoonotic potential. We show that factors previously identified as important for zoonotic potential in viruses--such as phylogenetic range, research effort, and being vector-borne--are also predictive in bacteria. We find that the fraction of pathogens shared between two hosts decreases with the phylogenetic distance between them. Our results suggest that host phylogenetic similarity is the primary factor for host-switching in pathogens.

ecology↗

bioRxiv2018

OMA standalone: orthology inference among public and custom genomes and transcriptomes

Genomes and transcriptomes are now typically sequenced by individual labs, but analysing them often remains challenging. One essential step in many analyses lies in identifying orthologs--corresponding genes across multiple species--but this is far from trivial. The OMA (Orthologous MAtrix) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature of OMA standalone is that users can combine their own data with existing public data by exporting genomes and pre-computed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of the Lophotrochozoa, a challenging clade within the Protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/losses in specific clades, and identifying potential drug targets in non-model organisms. OMA Standalone is available at http://omabrowser.org/standalone under the permissible open source Mozilla Public License Version 2.0.

bioinformatics↗

bioRxiv2017

Taxon sampling unequally affects individual nodes in a phylogenetic tree: consequences for model gene tree construction in SwissTree

Medium to large phylogenetic gene trees constructed from datasets of different species density and taxonomic range are rarely topologically consistent because of missing phylogenetic signal, non-phylogenetic signal and error. In this study, we first use simulations to show that taxon sampling unequally affects nodes in a gene tree, which likely contributes to controversial conclusions from taxon sampling experiments and contradicting species phylogenies such as for the boreoeutherians. Hence, because it is unlikely that a large gene tree can be reconstructed correctly based on a single optimized dataset, we take a two-step approach for the construction of model gene trees. First, stable and unstable clades are identified by comparing phylogenetic trees inferred from multiple datasets and data types (nucleotide, amino acid, codon) from the same gene family. Subsequently, data subsets are optimized for the analysis of individual uncertain clades. Results are summarized in form of a model tree that illustrates the evolutionary relationship of gene loci. A case study shows how a seemingly complex gene phylogeny becomes increasingly consistent with the reference species tree by attentive taxon sampling and subtree analysis. The procedure is progressively introduced to SwissTree (http://swisstree.vital-it.ch), a resource of high confidence model gene (locus) trees. Finally we demonstrate the usefulness of SwissTree for orthology benchmarking.

bioinformatics↗