Bacillus subtilis is the best-characterized member of the Gram-positive bacteria. Its genome of 4,214,810 base pairs comprises 4,100 protein-coding genes. Of these protein-coding genes, 53% are represented once, while a quarter of the genome corresponds to several gene families that have been greatly expanded by gene duplication, the largest family containing 77 putative ATP-binding transport proteins. In addition, a large proportion of the genetic capacity is devoted to the utilization of a variety of carbon sources, including many plant-derived molecules. The identification of five signal peptidase genes, as well as several genes for components of the secretion apparatus, is important given the capacity of Bacillus strains to secrete large amounts of industrially important enzymes. Many of the genes are involved in the synthesis of secondary metabolites, including antibiotics, that are more typically associated with Streptomyces species. The genome contains at least ten prophages or remnants of prophages, indicating that bacteriophage infection has played an important evolutionary role in horizontal gene transfer, in particular in the propagation of bacterial pathogenesis.

The Escherichia coli species represents one of the best-studied model organisms, but also encompasses a variety of commensal and pathogenic strains that diversify by high rates of genetic change. We uniformly (re-) annotated the genomes of 20 commensal and pathogenic E. coli strains and one strain of E. fergusonii (the closest E. coli related species), including seven that we sequenced to completion. Within the ∼18,000 families of orthologous genes, we found ∼2,000 common to all strains. Although recombination rates are much higher than mutation rates, we show, both theoretically and using phylogenetic inference, that this does not obscure the phylogenetic signal, which places the B2 phylogenetic group and one group D strain at the basal position. Based on this phylogeny, we inferred past evolutionary events of gain and loss of genes, identifying functional classes under opposite selection pressures. We found an important adaptive role for metabolism diversification within group B2 and Shigella strains, but identified few or no extraintestinal virulence-specific genes, which could render difficult the development of a vaccine against extraintestinal infections. Genome flux in E. coli is confined to a small number of conserved positions in the chromosome, which most often are not associated with integrases or tRNA genes. Core genes flanking some of these regions show higher rates of recombination, suggesting that a gene, once acquired by a strain, spreads within the species by homologous recombination at the flanking genes. Finally, the genome's long-scale structure of recombination indicates lower recombination rates, but not higher mutation rates, at the terminus of replication. The ensuing effect of background selection and biased gene conversion may thus explain why this region is A+T-rich and shows high sequence divergence but low sequence polymorphism. Overall, despite a very high gene flow, genes co-exist in an organised genome.

International audiencePlasmids are key vectors of horizontal gene transfer and essential genetic engineering tools. They code for genes involved in many aspects of microbial biology, including detoxication, virulence, ecological interactions, and antibiotic resistance. While many studies have decorticated the mechanisms of mobility in model plasmids, the identification and characterization of plasmid mobility from genome data are unexplored. By reviewing the available data and literature, we established a computational protocol to identify and classify conjugation and mobilization genetic modules in 1,730 plasmids. This allowed the accurate classification of proteobacterial conjugative or mobilizable systems in a combination of four mating pair formation and six relaxase families. The available evidence suggests that half of the plasmids are nonmobilizable and that half of the remaining plasmids are conjugative. Some conjugative systems are much more abundant than others and preferably associated with some clades or plasmid sizes. Most very large plasmids are nonmobilizable, with evidence of ongoing domestication into secondary chromosomes. The evolution of conjugation elements shows ancient divergence between mobility systems, with relaxases and type IV coupling proteins (T4CPs) often following separate paths from type IV secretion systems. Phylogenetic patterns of mobility proteins are consistent with the phylogeny of the host prokaryotes, suggesting that plasmid mobility is in general circumscribed within large clades. Our survey suggests the existence of unsuspected new relaxases in archaea and new conjugation systems in cyanobacteria and actinobacteria. Few genes, e.g., T4CPs, relaxases, and VirB4, are at the core of plasmid conjugation, and together with accessory genes, they have evolved into specific systems adapted to specific physiological and ecological contexts

Microbial pathogenesis studies are typically performed with reference strains, thereby overlooking microbial intra-species virulence heterogeneity. Here we integrated human epidemiological and clinical data with bacterial population genomics to harness the biodiversity of the model foodborne pathogen Listeria monocytogenes and decipher the basis of its neural and placental tropisms.Taking advantage of the clonal structure of this bacterial species, we identify clones epidemiologically associated with either food or human central nervous system (CNS) and maternal-neonatal (MN) listeriosis. The latter are also most prevalent in patients without immunosuppressive comorbidities. Strikingly, CNS and MN clones are hypervirulent in a humanized mouse model of listeriosis. By integrating epidemiological data and comparative genomics, we uncovered multiple novel putative virulence factors and demonstrated experimentally the contribution of the first gene cluster mediating Listeria monocytogenes neural and placental tropisms. This study illustrates the exceptional power of harnessing microbial biodiversity to identify clinically relevant microbial virulence attributes.

Listeria monocytogenes (Lm) is a major human foodborne pathogen. Numerous Lm outbreaks have been reported worldwide and associated with a high case fatality rate, reinforcing the need for strongly coordinated surveillance and outbreak control. We developed a universally applicable genome-wide strain genotyping approach and investigated the population diversity of Lm using 1,696 isolates from diverse sources and geographical locations. We define, with unprecedented precision, the population structure of Lm, demonstrate the occurrence of international circulation of strains and reveal the extent of heterogeneity in virulence and stress resistance genomic features among clinical and food isolates. Using historical isolates, we show that the evolutionary rate of Lm from lineage I and lineage II is low (∼2.5 × 10 substitutions per site per year, as inferred from the core genome) and that major sublineages (corresponding to so-called 'epidemic clones') are estimated to be at least 50-150 years old. This work demonstrates the urgent need to monitor Lm strains at the global level and provides the unified approach needed for global harmonization of Lm genome-based typing and population biology.

CRISPR (clustered regularly interspaced short palindromic repeats) arrays and their associated (Cas) proteins confer bacteria and archaea adaptive immunity against exogenous mobile genetic elements, such as phages or plasmids. CRISPRCasFinder allows the identification of both CRISPR arrays and Cas proteins. The program includes: (i) an improved CRISPR array detection tool facilitating expert validation based on a rating system, (ii) prediction of CRISPR orientation and (iii) a Cas protein detection and typing tool updated to match the latest classification scheme of these systems. CRISPRCasFinder can either be used online or as a standalone tool compatible with Linux operating system. All third-party software packages employed by the program are freely available. CRISPRCasFinder is available at https://crisprcas.i2bc.paris-saclay.fr.

Microbial minimal generation times range from a few minutes to several weeks. They are evolutionarily determined by variables such as environment stability, nutrient availability, and community diversity. Selection for fast growth adaptively imprints genomes, resulting in gene amplification, adapted chromosomal organization, and biased codon usage. We found that these growth-related traits in 214 species of bacteria and archaea are highly correlated, suggesting they all result from growth optimization. While modeling their association with maximal growth rates in view of synthetic biology applications, we observed that codon usage biases are better correlates of growth rates than any other trait, including rRNA copy number. Systematic deviations to our model reveal two distinct evolutionary processes. First, genome organization shows more evolutionary inertia than growth rates. This results in over-representation of growth-related traits in fast degrading genomes. Second, selection for these traits depends on optimal growth temperature: for similar generation times purifying selection is stronger in psychrophiles, intermediate in mesophiles, and lower in thermophiles. Using this information, we created a predictor of maximal growth rate adapted to small genome fragments. We applied it to three metagenomic environmental samples to show that a transiently rich environment, as the human gut, selects for fast-growers, that a toxic environment, as the acid mine biofilm, selects for low growth rates, whereas a diverse environment, like the soil, shows all ranges of growth rates. We also demonstrate that microbial colonizers of babies gut grow faster than stabilized human adults gut communities. In conclusion, we show that one can predict maximal growth rates from sequence data alone, and we propose that such information can be used to facilitate the manipulation of generation times. Our predictor allows inferring growth rates in the vast majority of uncultivable prokaryotes and paves the way to the understanding of community dynamics from metagenomic data.

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