Biology subjects

Chaumeil, P.-A.

Publications and source records attributed to Chaumeil, P.-A..

7 recordsLinked to original sources

bioRxiv2026

gTranslate: rapid and accurate translation table prediction for prokaryotic genomes

BackgroundBioinformatic tools often require the prediction of protein-coding genes to make inferences about prokaryotic genomes. Typically, the genetic code used for translating genes to proteins must be specified by the user based on the taxonomic classification of a genome assembly or, for some widely used tools, established using a heuristic rule based on gene coding densities. Manual specification is at best inconvenient, but more challenging is that many bioinformatic tools are applied before taxonomic classifications have been established making specifying the translation table impractical. MethodsHere we provide a computationally efficient tool, gTranslate, that uses an ensemble of five machine learning methods to accurately predict translation tables for prokaryotic genomes. The feature vector used by gTranslate takes advantage of differences in gene coding densities when predicting genes under different translation tables along with features that consider the number and ratio of UGA stop codon reassignments to tryptophan or glycine. ResultsWe demonstrate that gTranslate correctly predicts the translation table of prokaryotic genomes >99.99% of the time (i.e. <1 error per 10,000 genomes) and outperforms a more computationally expensive prediction method and a coding density heuristic used by popular bioinformatic tools. Using gTranslate, we identify a basal lineage of Ca. Stammera capleta that uses the standard bacterial genetic code instead of the UGA stop codon to tryptophan reassignment common to other members of this species. We also identify the first instances of UGA-to-tryptophan reassignment in the Patescibacteriota making this the first bacterial phylum with members capable of using translation tables 4, 11, and 25.

bioinformatics↗

bioRxiv2025

First report of stop codon reassignment to tryptophan in members of the bacterial phylum Actinomycetota

Reassignment of stop codons is a significant evolutionary event with recoding of UGA to tryptophan being previously identified in only three bacterial phyla, the Bacillota, Pseudomonadota, and Verrucomicrobiota. Here, we present genomic evidence of this recoding in a fourth bacterial phylum, the Actinomycetota, specifically in the family Eggerthellaceae. We identify the UGA stop-to-tryptophan reassignment in 34 metagenome-assembled genomes recovered from the stool samples of diverse mammalian hosts, including equids and primates. Canonical markers for this reassignment are consistently observed including conserved UGA codons aligning to tryptophan, loss of release factor 2 (prfB), and presence of a tRNATrp(UCA) gene. We infer that this reassignment occurred at least twice as the lineages containing recoded genomes are paraphyletic, forming two distinct groups separated by a third lineage with strains that continue to use UGA as a stop codon. These lineages represent three new Eggerthellaceae genera for which we propose the type species Equivita altericodex, Gorillivita intestinalis, and Tapirivita inops reflecting isolation source and genomic properties. Genomes representing these genera, including the non-recoded Tapirivita lineage, have reduced genomes and complete or partial loss of biosynthetic pathways, suggesting a transition to obligate symbiosis. Increasing host dependency may have facilitated stop codon reassignment in Equivita and Gorillivita species. This work expands the known phylogenetic diversity of UGA stop-to-tryptophan reassignment in the bacterial domain and establishes the Eggerthellaceae as a new focal point for understanding the evolutionary drivers of genetic code plasticity.

evolutionary biology↗

bioRxiv2025

A molecular inventory of the faecal microbiomes of 23 marsupial species

Despite the recent expansion of culture-independent analyses of animal faecal microbiomes, many lineages remain understudied. Marsupials represent one such group, where despite their iconic status, direct sequencing-based analyses remain limited. Here we present a metagenomic and metabolomic exploration of the faecal microbiomes of 23 Diprotodontia marsupials, producing a reference set of 3,868 prokaryotic and 12,142 viral metagenome-assembled genomes, the majority (>80%) of which represent novel species. As with other animals, host phylogeny is the primary driver of microbiome composition, including distinct profiles for two eucalyptus folivore specialists (koalas and southern greater gliders), suggesting independent solutions to this challenging diet. Expansion of several bacterial and viral lineages were observed in these and other marsupial hosts that may provide adaptive benefits. Antimicrobial resistance genes were significantly more prevalent in captive than wild animals likely reflecting human interaction. This molecular dataset contributes to our ongoing understanding of animal faecal microbiomes. Impact statementDespite their ecological and evolutionary importance, marsupials remain underrepresented in microbiome research. Here, we present the most extensive faecal microbiome dataset to date for this group, encompassing metagenomic, metabolomic, and proximity ligation data from 23 marsupial species. As in other animals, we find the microbial community structure reflects the host species, and some marsupials carry expanded sets of certain microbial lineages indicative of within-host evolution. This work substantially expands the genomic landscape of host-associated microbes and viruses in a poorly studied mammalian clade. Data summaryRaw read data, prokaryotic MAGs [≥]50% complete with [≤]10% contamination are available via the European Nucleotide Archive under project PRJEB89408. The full set of viral genomes, clustered protein database and metabolite data (raw and processed) are available via https://doi.org/10.48610/14e37e9. Prokaryotic MAGs are also available via https://figshare.com/s/87443d80817f57aadc16.

microbiology↗

bioRxiv2022

GTDB-Tk v2: memory friendly classification with the Genome Taxonomy Database

The Genome Taxonomy Database (GTDB) and associated taxonomic classification toolkit (GTDB-Tk) have been widely adopted by the microbiology community. However, the growing size of the GTDB bacterial reference tree has resulted in GTDB-Tk requiring substantial amounts of memory (~320 GB) which limits its adoption and ease of use. Here we present an update to GTDB-Tk that uses a divide-and-conquer approach where user genomes are initially placed into a bacterial reference tree with family-level representatives followed by placement into an appropriate class-level subtree comprising species representatives. This substantially reduces the memory requirements of GTDB-Tk while having minimal impact on classification. AvailabilityGTDB-Tk is implemented in Python and licenced under the GNU General Public Licence v3.0. Source code and documentation are available at: https://github.com/ecogenomics/gtdbtk. Contactp.chaumeil@uq.edu.au or donovan.parks@gmail.com

bioinformatics↗

bioRxiv2020

A rank-normalized archaeal taxonomy based on genome phylogeny resolves widespread incomplete and uneven classifications

An increasing wealth of genomic data from cultured and uncultured microorganisms provides the opportunity to develop a systematic taxonomy based on evolutionary relationships. Here we propose a standardized archaeal taxonomy, as part of the Genome Taxonomy Database (GTDB), derived from a 122 concatenated protein phylogeny that resolves polyphyletic groups and normalizes ranks based on relative evolutionary divergence (RED). The resulting archaeal taxonomy is stable under a range of phylogenetic variables, including marker genes, inference methods, corrections for rate heterogeneity and compositional bias, tree rooting scenarios, and expansion of the genome database. Rank normalization was shown to robustly correct for substitution rates varying up to 30-fold using simulated datasets. Taxonomic curation follows the rules of the International Code of Nomenclature of Prokaryotes (ICNP) while taking into account proposals to formally recognise the rank of phylum and to use genome sequences as type material. The taxonomy is based on 2,392 quality screened archaeal genomes, the great majority of which (93.3%) required one or more changes to their existing taxonomy, mostly as a result of incomplete classification. In total, 16 archaeal phyla are described, including reclassification of three major monophyletic units from the former Euryarchaeota and one phylum resulting from uniting the TACK superphylum into a single phylum. The taxonomy is publicly available at the GTDB website (https://gtdb.ecogenomic.org).

microbiology↗

bioRxiv2019

Selection of representative genomes for 24,706 bacterial and archaeal species clusters provide a complete genome-based taxonomy

We recently introduced the Genome Taxonomy Database (GTDB), a phylogenetically consistent, genome-based taxonomy providing rank normalized classifications for nearly 150,000 genomes from domain to genus. However, nearly 40% of the genomes used to infer the GTDB reference tree lack a species name, reflecting the large number of genomes in public repositories without complete taxonomic assignments. Here we address this limitation by proposing 24,706 species clusters which encompass all publicly available bacterial and archaeal genomes when using commonly accepted average nucleotide identity (ANI) criteria for circumscribing species. In contrast to previous ANI studies, we selected a single representative genome to serve as the nomenclatural type for circumscribing each species with type strains used where available. We complemented the 8,792 species clusters with validly or effectively published names with 15,914 de novo species clusters in order to assign placeholder names to the growing number of genomes from uncultivated species. This provides the first complete domain to species taxonomic framework which will improve communication of scientific results.

microbiology↗

bioRxiv2018

A proposal for a standardized bacterial taxonomy based on genome phylogeny

Taxonomy is a fundamental organizing principle of biology, which ideally should be based on evolutionary relationships. Microbial taxonomy has been greatly restricted by the inability to obtain most microorganisms in pure culture and, to a lesser degree, the historical use of phenotypic properties as the basis for classification. However, we are now at the point of obtaining genome sequences broadly representative of microbial diversity by using culture-independent techniques, which provide the opportunity to develop a comprehensive genome-based taxonomy. Here we propose a standardized bacterial taxonomy based on a concatenated protein phylogeny that conservatively removes polyphyletic groups and normalizes ranks based on relative evolutionary divergence. From 94,759 bacterial genomes, 99 phyla are described including six major normalized monophyletic units from the subdivision of the Proteobacteria, and amalgamation of the Candidate Phyla Radiation into the single phylum Patescibacteria. In total, 73% of taxa had one or more changes to their existing taxonomy.

microbiology↗