Biology subjects

Gourle, H.

Publications and source records attributed to Gourle, H..

8 recordsLinked to original sources

bioRxiv2025

Large-scale insights into the biosynthetic potential of the Bacillus cereus group

Bacterial secondary metabolites (SMs) are a critical source of natural product-derived drugs. However, SM discovery efforts have focused overwhelmingly on Actinomycetes, potentially overlooking other key producers. Here, we explore the biosynthetic potential of the Bacillus cereus group, an underexplored complex of SM producers. Using a combined rule- and machine learning-based approach, we mine an unprecedented number of B. cereus group genomes (n = 9,744) for SM-producing biosynthetic gene clusters (BGCs; n = 200,196). Notably, 158,678 B. cereus group BGCs (78.2%) did not cluster with previously described BGCs, suggesting new chemical scaffolds to be explored. B. pseudomycoides was particularly prolific in terms of its SM production potential (30.8 BGC families/genome, Kruskal-Wallis p < 0.0001), and we identify a previously uncharacterized, B. pseudomycoides-unique peptide. Overall, our study represents the largest survey of B. cereus group biosynthetic potential to date and posits the complex as an under-queried SM resource.

microbiology↗

bioRxiv2025

Scalable single-cell metagenomic analysis with Bascet and Zorn

Single-cell metagenomic sequencing (scMetaG) can provide maximum-resolution insights into complex microbial communities. However, existing bioinformatic tools are not equipped to handle the massive amounts of data generated by novel high-throughput scMetaG methods. Here, we present a bioinformatic toolkit for complete, end-to-end scMetaG analysis: (i) Bascet, a command-line suite designed to scale to massive scMetaG datasets ([≥]1 million cells); (ii) Zorn, an R package/workflow manager that enables reproducible scMetaG data analysis, exploration, and visualization (http://zorn.henlab.org/). Enabled by recent advances in droplet microfluidics, we use Bascet and Zorn to develop and optimize a high-throughput scMetaG method on a ten-species mock community. To showcase their utility on a real-world sample, we use Bascet and Zorn to characterize a human saliva sample, generating single-amplified genomes (SAGs) from >10k prokaryotic cells. Overall, Bascet and Zorn enable reproducible scMetaG analysis, allowing users to query microbiomes at unprecedented resolution and scale.

microbiology↗

bioRxiv2025

Fast, flexible gene cluster family delineation with IGUA

Prokaryotic genomes harbor a variety of functional elements encoded as contiguous multi-gene clusters, with biosynthetic gene clusters (BGCs, genetic determinants of secondary metabolite biosynthesis) serving as a notable example. In a typical workflow, BGCs are clustered into Gene Cluster Families (GCFs), units that group BGCs encoding similar biosynthetic pathways together. However, existing methods cannot readily scale to massive datasets and cannot be used for GCF delineation tasks beyond BGC clustering. Here, we present IGUA (Iterative Gene clUster Analysis; https://github.com/zellerlab/IGUA), a scalable, flexible GCF delineation method for genomic segments with multi-gene architectures. On a BGC clustering task, IGUA is [≥]10x faster than the state-of-the-art (BiG-SCAPE/BiG-SLiCE), without sacrificing accuracy. To highlight its scalability, we use IGUA to cluster >2.8 million BGCs from {approx}1 million prokaryotic genomes in <18 hours (n = 2,829,071 BGCs to 56,960 GCFs). To showcase its utility beyond BGC clustering, we use IGUA to cluster (i) secretion systems and (ii) prophages into GCFs (n = 10,576 and 356,776 gene clusters to 2,744 and 213,699 GCFs, respectively). Overall, IGUA represents a versatile GCF delineation tool with unmatched computational efficiency and flexibility, enabling (meta)genomic mining applications at unprecedented scales. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/654203v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1f27216org.highwire.dtl.DTLVardef@203ccborg.highwire.dtl.DTLVardef@7766c8org.highwire.dtl.DTLVardef@fcd4b5_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

InSilicoSeq 2.0: Simulating realistic amplicon-based sequence reads

MotivationSimulating high-throughput sequencing reads that mimic empirical sequence data is of major importance for designing and validating sequencing experiments, as well as for benchmarking bioinformatic workflows and tools. ResultsHere, we present InSilicoSeq 2.0, a software package that can simulate realistic Illumina-like sequencing reads for a variety of sequencing machines and assay types. InSilicoSeq now supports amplicon-based sequencing and comes with premade error models of various quality levels for Illumina MiSeq, HiSeq, NovaSeq and NextSeq platforms. It provides the flexibility to generate custom error models for any short-read sequencing platform from a BAM-file. We demonstrated the novel amplicon sequencing algorithm by simulating Adaptive Immune Receptor Repertoire (AIRR) reads. Our benchmark revealed that the simulated reads by InSilicoSeq 2.0 closely resemble the Phred-scores of actual Illumina MiSeq, HiSeq, NovaSeq and NextSeq sequencing data. InSilicoSeq 2.0 generated 15 million amplicon based paired-end reads in under an hour at a total cost of {euro}4.3e-05 per million bases advocating for testing experimental designs through simulations prior to actual sequencing. Availability and implementationInSilicoSeq 2.0 is implemented in Python and is freely available under the MIT licence at https://github.com/HadrienG/InSilicoSeq

bioinformatics↗

bioRxiv2023

A community-curated, global atlas of Bacillus cereus sensu lato genomes for epidemiological surveillance

The ability to cause foodborne illness, anthrax, and other infections has been attributed to numerous lineages within Bacillus cereus sensu lato (s.l.). However, existing pathogen surveillance databases facilitate dangerous pathogen misidentifications when applied to B. cereus s.l., potentially hindering outbreak or bioterrorism attack response efforts. To address this, we developed BTyperDB (www.btyper.app), an atlas of B. cereus s.l. genomes with standardized, community-curated metadata. BTyperDB aggregates all publicly available B. cereus s.l. genomes (including >2,600 previously unassembled genomes) with novel genomes donated by laboratories around the world, nearly doubling the number of publicly available B. cereus s.l. genomes. To showcase its utility for pathogen surveillance, we use BTyperDB to identify emerging anthrax toxin- and capsule-harboring lineages. Overall, our study provides insight into the epidemiology of an under-studied group of emerging pathogens and highlights the benefits of inclusive, community-driven metadata FAIRification efforts.

microbiology↗

bioRxiv2021

nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning

The analysis of shotgun metagenomic data provides valuable insights into microbial communities, while allowing resolution at individual genome level. In absence of complete reference genomes, this requires the reconstruction of metagenome assembled genomes (MAGs) from sequencing reads. We present the nf-core/mag pipeline for metagenome assembly, binning and taxonomic classification. It can optionally combine short and long reads to increase assembly continuity and utilize sample-wise group-information for co-assembly and genome binning. The pipeline is easy to install - all dependencies are provided within containers -, portable and reproducible. It is written in Nextflow and developed as part of the nf-core initiative for best-practice pipeline development. All code is hosted on GitHub under the nf-core organization https://github.com/nf-core/mag and released under the MIT license.

bioinformatics↗

bioRxiv2020

Molecular Ecology of Coral Reef Microorganisms in the Western Indian Ocean coast of Kenya

Coral reefs face increased environmental threats from anthropomorphic climate change and pollution, from agriculture, industries and tourism. They are economically vital for many people worldwide, and harbour a fantastically diverse ecosystem, being the home for many species of fish and algae. Surprisingly little is known about the microbial communities living in and in the surrounding of coral reefs. Here we employ high throughput sequencing for investigating the bacteria living in the water column and upper sediment layer in close proximity to coral reefs on the Kenyan coast of the West Indian Ocean. We show that while the read-level taxonomic distribution of bacteria is similar with ones obtained from 16S metabarcoding, whole metagenome sequencing provides valuable functional insights not available with 16S metabarcoding. We find evidence of pollution, marked by the presence of Vibrio and more importantly the presence of antibiotic resistance notably to vancomycin, that we attribute to the use of avoparcin in agriculture. Additionally, 175 bacterial genomes not previously sequenced were discovered. Our study is the first whole-metagenome study from the West Indian Ocean, provides a much-needed baseline to study microbes surrounding coral reefs under different conditions as well as the microbiome of coral reefs.

ecology↗

bioRxiv2019

A peek into Western Indian Ocean microbial richness: a pilot for a coral microbiome study

Microbial communities are essential components of natural ecosystems. Of the global oceans, the Indian Ocean remains the least studied in terms of its microbial diversity, despite it being a highly dynamic tropical water body. Metagenomics methods have significantly advanced studies in marine microbial ecology in recent years. Preliminary metabarcoding assessments are recommended to mitigate against the associated costs, prior to the metagenomics study, to give an impression of the diversity expected and determine the sequencing effort required.\n\nWe report here the first metabarcoding survey of bacterial diversity of the western Indian Ocean (WIO) using samples used for optimizing environmental DNA (eDNA) isolation as pilot experiment for a metagenomic study investigating the coral-reef microbiome of the region. Sampling of water and sediment samples was done near-shore sublittoral and within the coral reef.\n\nAbout 3,000 microbial ribotypes were inferred, from which 41 phyla were uncovered. Sediments registered higher alpha diversity than seawater samples. The phylum Proteobacteria was dominant with its members constituting over 60% of the ribosomal sequence variants (RSVs). The other abundant bacteria were members of Bacteroidetes and Cyanobacteria phyla. We identified bacterial species with potential broad biotechnological applications, underscoring the WIOs richness and the usefulness of eDNA metabarcoding approaches in bioprospecting as well as monitoring and/or surveying marine ecosystems.

genomics↗