Biology subjects

Gosselin, S. P.

Publications and source records attributed to Gosselin, S. P..

3 recordsLinked to original sources

bioRxiv2025

Actinobacteriophage Inteins: Host Diversity, Local Dissemination, and Non-Canonical Architecture

Intein presence within Actinobacteriophages (within PhagesDB) was last surveyed in 2016, and despite a 5-fold increase in the size of the database, has not been updated since. To address this, we present a modern survey of the current iteration of the PhagesDB database. We developed a new algorithm -- Iterative Cluster Expansion BLAST (ICE-BLAST) -- to expand our search to more divergent sequences. Nearly 800 inteins were retrieved through this process; the majority of which were previously unreported. We describe the nature of these inteins, their classes, integration target sites, distribution within phage clusters, and explore the geographical location of nearly identical intein sequences found in divergent exteins. Our findings suggest that these inteins recently invaded local phage populations. We also find two instances of a Cas4 exonuclease intein evolving from a terminase large subunit intein, and propose a model by which one of these inteins was able to utilize sequence similarity conferred by a shared nucleotide binding site to jump between genes. Additionally, we find inteins with never-before-reported homing endonucleases, and inteins with homing endonucleases encoded in a reading frame separate from that which encodes the extein and the inteins self-splicing domain. We provide predicted structures for these elements and hypothesize on their evolution and relation to free-standing homing endonucleases within phage genomes. Finally, we provide evidence that these "non-canonical" inteins are still transferring between host genomes, in a fashion similar to other inteins with canonical homing endonucleases within the dataset.

bioinformatics↗

bioRxiv2020

Systematic Detection of Large-Scale Multi-Gene Horizontal Transfer in Prokaryotes

Horizontal gene transfer (HGT) is central to prokaryotic evolution. However, little is known about the "scale" of individual HGT events. In this work, we introduce the first computational framework to help answer the following fundamental question: How often does more than one gene get horizontally transferred in a single HGT event? Our method, called HoMer, uses phylogenetic reconciliation to infer single-gene HGT events across a given set of species/strains, employs several techniques to account for inference error and uncertainty, combines that information with gene order information from extant genomes, and uses statistical analysis to identify candidate horizontal multi-gene transfers (HMGTs) in both extant and ancestral species/strains. HoMer is highly scalable and can be easily used to infer HMGTs across hundreds of genomes. We apply HoMer to a genome-scale dataset of over 22000 gene families from 103 Aeromonas genomes and identify a large number of plausible HMGTs of various scales at both small and large phylogenetic distances. Analysis of these HMGTs reveals interesting relationships between gene function, phylogenetic distance, and frequency of multi-gene transfer. Among other insights, we find that (i) the relative frequency of HMGT increases as divergence between genomes increases, (ii) HMGTs often have conserved gene functions, and (iii) rare genes are frequently acquired through HMGT. We also analyze in detail HMGTs involving the zonula occludens toxin and type III secretion systems. By enabling the systematic inference of HMGTs on a large scale, HoMer will facilitate a more accurate and more complete understanding of HGT and microbial evolution.

evolutionary biology↗

bioRxiv2020

Expanding the utility of sequence comparisons using data from whole genomes

Whole genome comparisons based on Average Nucleotide Identities (ANI), and the Genome-to-genome distance calculator have risen to prominence in rapidly classifying taxa using whole genome sequences. Some implementations have even been proposed as a new standard in species classification and have become a common technique for papers describing newly sequenced genomes. However, attempts to apply whole genome divergence data to delineation of higher taxonomic units, and to phylogenetic inference have had difficulty matching those produced by more complex phylogenetics methods. We present a novel method for generating reliable and statistically supported phylogenies using established ANI techniques. For the test cases to which we applied the developed approach we obtained accurate results up to at least the family level. The developed method uses non-parametric bootstrapping to gauge reliability of inferred groups. This method offers the opportunity make use of whole-genome comparison data that is already being generated to quickly produce accurate phylogenies. Additionally, the developed ANI methodology can assist classification of higher order taxonomic groups. Significance StatementThe average nucleotide identity (ANI) measure and its iterations have come to dominate in-silico species delimitation in the past decade. Yet the problem of gene content has not been fully resolved, and attempts made to do so contain two metrics which makes interpretation difficult at times. We provide a new single based ANI metric created from the combination of genomic content and genomic identity measures. Our results show that this method can handle comparisons of genomes with divergent content or identity. Additionally, the metric can be used to create distance based phylogenetic trees that are comparable to other tree building methods, while also providing a tentative metric for categorizing organisms into higher level taxonomic classifications.

bioinformatics↗