Robust analysis of prokaryotic pangenome gene gain and loss rates with Panstripe

Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches

Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety of methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. To quantify sources of bias and error related to common pan-genome analysis approaches, we evaluated different approaches applied to curated collection of 151 Mycobacterium tuberculosis ( Mtb ) isolates. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. When applied to Mtb and E. coli pan-genomes, panqc exposed distinct biases influenced by the genomic diversity of the population studied. Our findings underscore the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.

Evolutionary dynamics of the accessory genomes of Staphylococcus aureus

Staphylococcus aureus is a ubiquitous commensal and opportunistic bacterial pathogen that can cause a wide gamut of infections, which are exacerbated by the presence of multidrug-resistant and methicillin-resistant S. aureus. S. aureus is genetically heterogeneous and consists of numerous distinct lineages. Using 558 complete genomes of S. aureus, we aim to determine how the accessory genome content among phylogenetic lineages of S. aureus is structured and has evolved. Bayesian hierarchical clustering identified 10 sequence clusters, of which seven contained major sequence types (ST 1, 5, 8, 30, 59, 239, and 398). The seven sequence clusters differed in their accessory gene content, including genes associated with antimicrobial resistance and virulence. Focusing on the two largest clusters, BAPS8 and BAPS10, and each consisting mostly of ST5 and ST8, respectively, we found that the structure and connected components in the co-occurrence networks of accessory genomes varied between them. These differences are explained, in part, by the variation in the rates at which the two sequence clusters gained and lost accessory genes, with the highest rate of gene accumulation occurring recently in their evolutionary histories. We also identified a divergent group within BAPS10 that has experienced high gene gain and loss early in its history. Together, our results show highly variable and dynamic accessory genomes in S. aureus that are structured by the history of the specific lineages that carry them.IMPORTANCEStaphylococcus aureus is an opportunistic, multi-host pathogen that can cause a variety of benign and life-threatening infections. Our results revealed considerable differences in the structure and evolution of the accessory genomes of major lineages within S. aureus. Such genomic variation within a species can have important implications on disease epidemiology, pathogenesis of infection, and interactions with the vertebrate host. Our findings provide important insights into the underlying genetic basis for the success of S. aureus as a highly adaptable and resistant pathogen, which will inform current efforts to control and treat staphylococcal diseases.

Genetic barriers more than environmental associations explain Serratia marcescens population structure

Bacterial species often comprise well-separated lineages, likely emerged and maintained by genetic isolation and/or ecological divergence. How these two evolutionary actors interact in the shaping of bacterial population structure is currently not fully understood. In this study, we investigate the genetic and ecological drivers underlying the evolution of Serratia marcescens, an opportunistic pathogen with high genomic flexibility and able to colonise diverse environments. Comparative genomic analyses reveal a population structure composed of five deeply-demarcated genetic clusters with open pan-genome but limited inter-cluster gene flow, partially explained by Restriction-Modification (R-M) systems incompatibility. Furthermore, a large-scale research on hundred-thousands metagenomic datasets reveals only a partial habitat separation of the clusters. Globally, two clusters only show a separate gene composition coherent with ecological adaptations. These results suggest that genetic isolation has preceded ecological adaptations in the shaping of the species diversity, an evolutionary scenario coherent with the Evolutionary Extended Synthesis.

The bacterial genetic determinants of Escherichia coli capacity to cause bloodstream infections in humans

Escherichia coli is both a highly prevalent commensal and a major opportunistic pathogen causing bloodstream infections (BSI). A systematic analysis characterizing the genomic determinants of extra-intestinal pathogenic vs. commensal isolates in human populations, which could inform mechanisms of pathogenesis, diagnostic, prevention and treatment is still lacking. We used a collection of 912 BSI and 370 commensal E. coli isolates collected in France over a 17-year period (2000-2017). We compared their pangenomes, genetic backgrounds (phylogroups, STs, O groups), presence of virulence-associated genes (VAGs) and antimicrobial resistance genes, finding significant differences in all comparisons between commensal and BSI isolates. A machine learning linear model trained on all the genetic variants derived from the pangenome and controlling for population structure reveals similar differences in VAGs, discovers new variants associated with pathogenicity (capacity to cause BSI), and accurately classifies BSI vs. commensal strains. Pathogenicity is a highly heritable trait, with up to 69% of the variance explained by bacterial genetic variants. Lastly, complementing our commensal collection with an older collection from 1980, we predict that pathogenicity continuously increased through 1980, 2000, to 2010. Together our findings imply that E. coli exhibit substantial genetic variation contributing to the transition between commensalism and pathogenicity and that this species evolved towards higher pathogenicity.

Comparative genomics reveals the acquisition of mobile genetic elements by the plant growth-promoting Pantoea eucrina OB49 in polluted environments

Heavy metal-tolerant plant growth-promoting bacteria (PGPB) have gained popularity in bioremediation in recent years. A genome-assisted study of a heavy metal-tolerant PGPB Pantoea eucrina OB49 isolated from the rhizosphere of wheat grown on a heavy metal-contaminated site is presented. Comparative pan-genome analysis indicated that OB49 acquired heavy metal resistance genes through horizontal gene transfer. On contigs S10 and S12, OB49 has two arsRBCH operons that give arsenic resistance. On the S12 contig, an arsRBCH operon was discovered in conjunction with the merRTPCADE operon, which provides mercury resistance. P. eucrina OB49 may be involved in an ecological alternative for heavy metal remediation and growth promotion of wheat grown in metal-polluted soils. Our results suggested the detection of mobile genetic elements that harbour the ars operon and the fluoride resistance genes adjacent to the mer operon.