The Ecology and Evolution of Pangenomes

Brockhurst, Michael A.; Harrison, Ellie; Hall, James P. J.; Richards, Thomas A.; McNally, Alan; MacLean, R. Craig

doi:10.1016/j.cub.2019.08.012

Cited by 240 publications

(259 citation statements)

References 137 publications

(153 reference statements)

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“…An improvement in the method could be to normalize the data to remove sampling bias. But as suggested by Brockhurst et al [42], this issue should first be examined from a biological perspective by collecting and analyzing genomes from ecologically coherent microbial populations or ecotypes.…”

Section: Resultsmentioning

confidence: 99%

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

et al. 2020

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The use of comparative genomics for functional, evolutionary, and epidemiological studies requires methods to classify gene families in terms of occurrence in a given species. These methods usually lack multivariate statistical models to infer the partitions and the optimal number of classes and don't account for genome organization. We introduce a graph structure to model pangenomes in which nodes represent gene families and edges represent genomic neighborhood. Our method, named PPanGGOLiN, partitions nodes using an Expectation-Maximization algorithm based on multivariate Bernoulli Mixture Model coupled with a Markov Random Field. This approach takes into account the topology of the graph and the presence/absence of genes in pangenomes to classify gene families into persistent, cloud, and one or several shell partitions. By analyzing the partitioned pangenome graphs of isolate genomes from 439 species and metagenome-assembled genomes from 78 species, we demonstrate that our method is effective in estimating the persistent genome. Interestingly, it shows that the shell genome is a key element to understand genome dynamics, presumably because it reflects how genes present at intermediate frequencies drive adaptation of species, and its proportion in genomes is independent of genome size. The graph-based approach proposed by PPanGGOLiN is useful to depict the overall genomic diversity of thousands of strains in a compact structure and provides an effective basis for very large scale comparative genomics. The software is freely available at https://github.com/labgem/ PPanGGOLiN. PLOS COMPUTATIONAL BIOLOGYPLOS Computational Biology | https://doi.org/10.

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Section: Resultsmentioning

confidence: 99%

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

et al. 2020

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“…These results are highly important for an ecological understanding of prokaryotic evolution and this represents the first time that these factors are quantified in a natural setting. Nonetheless, different theories and concepts have been postulated to explain microbial evolution in response to the environment [8,76]. For example, it has long been thought that a large pool of accessory genes would be beneficial in certain habitats (and habitat combinations).…”

Section: Discussionmentioning

confidence: 99%

Disentangling the impact of environmental and phylogenetic constraints on prokaryotic within-species diversity

et al. 2020

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Microbial organisms inhabit virtually all environments and encompass a vast biological diversity. The pangenome concept aims to facilitate an understanding of diversity within defined phylogenetic groups. Hence, pangenomes are increasingly used to characterize the strain diversity of prokaryotic species. To understand the interdependence of pangenome features (such as the number of core and accessory genes) and to study the impact of environmental and phylogenetic constraints on the evolution of conspecific strains, we computed pangenomes for 155 phylogenetically diverse species (from ten phyla) using 7,000 high-quality genomes to each of which the respective habitats were assigned. Species habitat ubiquity was associated with several pangenome features. In particular, core-genome size was more important for ubiquity than accessory genome size. In general, environmental preferences had a stronger impact on pangenome evolution than phylogenetic inertia. Environmental preferences explained up to 49% of the variance for pangenome features, compared with 18% by phylogenetic inertia. This observation was robust when the dataset was extended to 10,100 species (59 phyla). The importance of environmental preferences was further accentuated by convergent evolution of pangenome features in a given habitat type across different phylogenetic clades. For example, the soil environment promotes expansion of pangenome size, while host-associated habitats lead to its reduction. Taken together, we explored the global principles of pangenome evolution, quantified the influence of habitat, and phylogenetic inertia on the evolution of pangenomes and identified criteria governing species ubiquity and habitat specificity.These authors contributed equally: Oleksandr M. Maistrenko, Daniel R. Mende

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“…In sum, our analysis adds to the knowledge on the pace and drivers of gene loss and acquisition in bacteria evolving over multiple years in a human host environment Introduction Gene acquisition and gene loss are prominent in bacterial evolution and are also important for adaptation. [1,2] In contrast to point mutations, small insertions and deletions (microindels), inversions, and translocations that gradually alter existing genomic content, the acquisition or loss of entire genes rapidly confers large changes to the genomic content, and gene acquisition and loss alters phenotypes such as virulence, antibiotic resistance, and metabolic capability. [3,4] Thus, genome-wide analysis of the gene presence or absence is necessary to better understand the bacterial evolution and adaptation.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, we only have a limited understanding of how lineage gene loss and acquisition is driven by selective versus genetic drift. [1,2] Evolutionary studies on individual bacterial lineages are dependent on the ability to obtain multiple samples of the same lineage which can be difficult in natural, in vivo, environments that constantly change, so studies are more easily performed in vitro. However, P. aeruginosa infections in cystic fibrosis (CF) patients represent an infectious disease scenario in which the genomic evolution of individual bacterial lineages can be followed over years; thus, gives an opportunity to research bacterial evolution and adaptation in vivo in the human host.…”

Section: Introductionmentioning

confidence: 99%

Gene loss and acquisition in lineages of bacteria evolving in a human host environment

Gabrielaitė

Molin

et al. 2020

Preprint

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While genome analyses have documented that there are differences in the gene repertoire between evolutionary distant lineages of the same bacterial species, less is known about micro-evolutionary dynamics of gene loss and acquisition within lineages of bacteria as they evolve over the timescale of years. This knowledge is valuable to understand both the basic mutational steps that on long timescales lead to evolutionary distant bacterial lineages, and the evolution of the individual lineages themselves.In the case that lineages evolve in a human host environment, gene loss and acquisition may furthermore have implication for disease.We analyzed the genomes of 45 Pseudomonas aeruginosa lineages evolving in the lungs of cystic fibrosis patients to identify genes that are lost or acquired during the first years of infection in each of the different lineages. On average, the lineage genome content changed with 88 genes (range 0-473). Genes were more often lost than acquired, and prophage genes were more variable than bacterial genes. We identified genes that were lost or acquired independently across different clonal lineages, i.e. convergent molecular evolution. Convergent evolution suggests that there is a selection for loss and acquisition of certain genes in the host environment. We find that a significant proportion of such genes are associated with virulence; a trait previously shown to be important for adaptation. Furthermore, we also compared the genomes across lineages to show that within-lineage variable genes more often belonged to genomic content not shared across all lineages. Finally, we used 4,760 genes shared by 446 P. aeruginosa genomes to develop a stable and discriminatory typing scheme for P. aeruginosa clone types (Pactyper, https://github.com/MigleSur/Pactyper). In sum, our analysis adds to the knowledge on the pace and drivers of gene loss and acquisition in bacteria evolving over multiple years in a human host environment 3 and provides a basis to further understand how gene loss and acquisition plays a role in lineage differentiation and host adaptation.

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The Ecology and Evolution of Pangenomes

Cited by 240 publications

References 137 publications

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

Disentangling the impact of environmental and phylogenetic constraints on prokaryotic within-species diversity

Gene loss and acquisition in lineages of bacteria evolving in a human host environment

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