Prokaryotic Pangenomes Act as Evolving Ecosystems

Heterogeneity in recombination rates and accessory gene co-occurrence distinguish Pseudomonas aeruginosa phylogroups

Pseudomonas aeruginosa (class Gammaproteobacteria) is a ubiquitous, ecologically widespread, and metabolically versatile species. It is also an opportunistic pathogen that causes a variety of chronic and acute infections in humans. Its ability to thrive in diverse environments and exhibit a wide range of phenotypes lies in part on its large gene pool, but the processes that govern inter-strain genomic variation remain unclear. Here, we aim to characterize the recombination features and accessory genome structure of P. aeruginosa using 840 globally distributed genome sequences. The species can be subdivided into five phylogenetic sequence clusters (corresponding to known phylogroups), two of which are most prominent. Notable epidemic clones are found in the two phylogroups: ST17, ST111, ST146, ST274, and ST395 in phylogroup 1, and ST235 and ST253 in phylogroup 2. The two phylogroups differ in the frequency and characteristics of homologous recombination in their core genomes, including the specific genes that most frequently recombine and the impact of recombination on sequence diversity. Each phylogroup's accessory genome is characterized by a unique gene pool, co-occurrence networks of shared genes, and anti-phage defense systems. Different pools of antimicrobial resistance and virulence genes exist in the two phylogroups and display dissimilar patterns of co-occurrence. Altogether, our results indicate that each phylogroup displays distinct histories and patterns of acquiring exogenous DNA, which may contribute in part to their predominance in the global population. Our study has important implications for understanding the genome dynamics, within-species heterogeneity, and clinically relevant traits of P. aeruginosa.

IMPORTANCE

The consummate opportunist Pseudomonas aeruginosa inhabits many nosocomial and non-clinical environments, posing a major health burden worldwide. Our study reveals phylogroup-specific differences in recombination features and co-occurrence networks of accessory genes within the species. This genomic variation partly explains its remarkable ability to exhibit diverse ecological and phenotypic traits, and thus contribute to circumventing clinical and public health intervention strategies to contain it. Our results may help inform efforts to control and prevent P. aeruginosa diseases, including managing transmission, therapeutic efforts, and pathogen circulation in non-clinical environmental reservoirs.

Context matters: assessing the impacts of genomic background and ecology on microbial biosynthetic gene cluster evolution

Encoded within many microbial genomes, biosynthetic gene clusters (BGCs) underlie the synthesis of various secondary metabolites that often mediate ecologically important functions. Several studies and bioinformatics methods developed over the past decade have advanced our understanding of both microbial pangenomes and BGC evolution. In this minireview, we first highlight challenges in broad evolutionary analysis of BGCs, including delineation of BGC boundaries and clustering of BGCs across genomes. We further summarize key findings from microbial comparative genomics studies on BGC conservation across taxa and habitats and discuss the potential fitness effects of BGCs in different settings. Afterward, recent research showing the importance of genomic context on the production of secondary metabolites and the evolution of BGCs is highlighted. These studies draw parallels to recent, broader, investigations on gene-to-gene associations within microbial pangenomes. Finally, we describe mechanisms by which microbial pangenomes and BGCs evolve, ranging from the acquisition or origination of entire BGCs to micro-evolutionary trends of individual biosynthetic genes. An outlook on how expansions in the biosynthetic capabilities of some taxa might support theories that open pangenomes are the result of adaptive evolution is also discussed. We conclude with remarks about how future work leveraging longitudinal metagenomics across diverse ecosystems is likely to significantly improve our understanding on the evolution of microbial genomes and BGCs.

Persistent, Private, and Mobile Genes: A Model for Gene Dynamics in Evolving Pangenomes

The pangenome of a species is the set of all genes carried by at least one member of the species. In bacteria, pangenomes can be much larger than the set of genes carried by a single organism. Many questions remain unanswered regarding the evolutionary forces shaping the patterns of the presence/absence of genes in pangenomes of a given species. We introduce a new model for bacterial pangenome evolution along a species phylogeny that explicitly describes the timing of appearance of each gene in the species and accounts for three generic types of gene evolutionary dynamics: persistent genes that are present in the ancestral genome, private genes that are specific to a given clade, and mobile genes that are imported once into the gene pool and then undergo frequent horizontal gene transfers. We call this model the Persistent-Private-Mobile (PPM) model. We develop an algorithm fitting the PPM model and apply it to a dataset of 902 Salmonella enterica genomes. We show that the best fitting model is able to reproduce the global pattern of some multivariate statistics like the gene frequency spectrum and the parsimony vs. frequency plot. Moreover, the gene classification induced by the PPM model allows us to study the position of accessory genes on the chromosome depending on their category, as well as the gene functions that are most present in each category. This work paves the way for a mechanistic understanding of pangenome evolution, and the PPM model developed here could be used for dynamics-aware gene classification.

Modern microbiology: Embracing complexity through integration across scales

Microbes were the only form of life on Earth for most of its history, and they still account for the vast majority of life's diversity. They convert rocks to soil, produce much of the oxygen we breathe, remediate our sewage, and sustain agriculture. Microbes are vital to planetary health as they maintain biogeochemical cycles that produce and consume major greenhouse gases and support large food webs. Modern microbiologists analyze nucleic acids, proteins, and metabolites; leverage sophisticated genetic tools, software, and bioinformatic algorithms; and process and integrate complex and heterogeneous datasets so that microbial systems may be harnessed to address contemporary challenges in health, the environment, and basic science. Here, we consider an inevitably incomplete list of emergent themes in our discipline and highlight those that we recognize as the archetypes of its modern era that aim to address the most pressing problems of the 21st century.

Bacterial lifestyle shapes pangenomes

Pangenomes vary across bacteria. Some species have fluid pangenomes, with a high proportion of genes varying between individual genomes. Other species have less fluid pangenomes, with different genomes tending to contain the same genes. Two main hypotheses have been suggested to explain this variation: differences in species' bacterial lifestyle and effective population size. However, previous studies have not been able to test between these hypotheses because the different features of lifestyle and effective population size are highly correlated with each other, and phylogenetically conserved, making it hard to disentangle their relative importance. We used phylogeny-based analyses, across 126 bacterial species, to tease apart the causal role of different factors. We found that pangenome fluidity was lower in i) host-associated compared with free-living species and ii) host-associated species that are obligately dependent on a host, live inside cells, and are more pathogenic and less motile. In contrast, we found no support for the competing hypothesis that larger effective population sizes lead to more fluid pangenomes. Effective population size appears to correlate with pangenome variation because it is also driven by bacterial lifestyle, rather than because of a causal relationship.

Comparative genomics reveals distinct diversification patterns among LysR-type transcriptional regulators in the ESKAPE pathogen Pseudomonas aeruginosa

Pseudomonas aeruginosa, a harmful nosocomial pathogen associated with cystic fibrosis and burn wounds, encodes for a large number of LysR-type transcriptional regulator proteins. To understand how and why LTTR proteins evolved with such frequency and to establish whether any relationships exist within the distribution we set out to identify the patterns underpinning LTTR distribution in P. aeruginosa and to uncover cluster-based relationships within the pangenome. Comparative genomic studies revealed that in the JGI IMG database alone ~86 000 LTTRs are present across the sequenced genomes (n=699). They are widely distributed across the species, with core LTTRs present in >93 % of the genomes and accessory LTTRs present in <7 %. Analysis showed that subsets of core LTTRs can be classified as either variable (typically specific to P. aeruginosa) or conserved (and found to be distributed in other Pseudomonas species). Extending the analysis to the more extensive Pseudomonas database, PA14 rooted analysis confirmed the diversification patterns and revealed PqsR, the receptor for the Pseudomonas quinolone signal (PQS) and 2-heptyl-4-quinolone (HHQ) quorum-sensing signals, to be amongst the most variable in the dataset. Successful complementation of the PAO1 pqsR - mutant using representative variant pqsR sequences suggests a degree of structural promiscuity within the most variable of LTTRs, several of which play a prominent role in signalling and communication. These findings provide a new insight into the diversification of LTTR proteins within the P. aeruginosa species and suggests a functional significance to the cluster, conservation and distribution patterns identified.

Contingency, repeatability, and predictability in the evolution of a prokaryotic pangenome

Pangenomes exhibit remarkable variability in many prokaryotic species, much of which is maintained through the processes of horizontal gene transfer and gene loss. Repeated acquisitions of near-identical homologs can easily be observed across pangenomes, leading to the question of whether these parallel events potentiate similar evolutionary trajectories, or whether the remarkably different genetic backgrounds of the recipients mean that postacquisition evolutionary trajectories end up being quite different. In this study, we present a machine learning method that predicts the presence or absence of genes in the Escherichia coli pangenome based on complex patterns of the presence or absence of other accessory genes within a genome. Our analysis leverages the repeated transfer of genes through the E. coli pangenome to observe patterns of repeated evolution following similar events. We find that the presence or absence of a substantial set of genes is highly predictable from other genes alone, indicating that selection potentiates and maintains gene-gene co-occurrence and avoidance relationships deterministically over long-term bacterial evolution and is robust to differences in host evolutionary history. We propose that at least part of the pangenome can be understood as a set of genes with relationships that govern their likely cohabitants, analogous to an ecosystem's set of interacting organisms. Our findings indicate that intragenomic gene fitness effects may be key drivers of prokaryotic evolution, influencing the repeated emergence of complex gene-gene relationships across the pangenome.

Human Pangenomics: Promises and Challenges of a Distributed Genomic Reference

A pangenome is a collection of the common and unique genomes that are present in a given species. It combines the genetic information of all the genomes sampled, resulting in a large and diverse range of genetic material. Pangenomic analysis offers several advantages compared to traditional genomic research. For example, a pangenome is not bound by the physical constraints of a single genome, so it can capture more genetic variability. Thanks to the introduction of the concept of pangenome, it is possible to use exceedingly detailed sequence data to study the evolutionary history of two different species, or how populations within a species differ genetically. In the wake of the Human Pangenome Project, this review aims at discussing the advantages of the pangenome around human genetic variation, which are then framed around how pangenomic data can inform population genetics, phylogenetics, and public health policy by providing insights into the genetic basis of diseases or determining personalized treatments, targeting the specific genetic profile of an individual. Moreover, technical limitations, ethical concerns, and legal considerations are discussed.