How do interactions between mobile genetic elements affect horizontal gene transfer?

Current Opinion in Microbiology, Год журнала: 2023, Номер 73, С. 102282 - 102282

Опубликована: Фев. 28, 2023

Horizontal gene transfer is central to bacterial adaptation and facilitated by mobile genetic elements (MGEs). Increasingly, MGEs are being studied as agents with their own interests adaptations, the interactions have one another recognised having a powerful effect on flow of traits between microbes. Collaborations conflicts nuanced can both promote inhibit acquisition new material, shaping maintenance newly acquired genes dissemination important adaptive through microbiomes. We review recent studies that shed light this dynamic oftentimes interlaced interplay, highlighting importance genome defence systems in mediating MGE-MGE conflicts, outlining consequences for evolutionary change, resonate from molecular microbiome ecosystem levels.

Язык: Английский

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

Proceedings of the National Academy of Sciences, Год журнала: 2023, Номер 121(1)

Опубликована: Дек. 26, 2023

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

Язык: Английский

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Bacterial lifestyle shapes pangenomes

Proceedings of the National Academy of Sciences, Год журнала: 2024, Номер 121(21)

Опубликована: Май 14, 2024

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

Язык: Английский

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Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance

Nature Reviews Microbiology, Год журнала: 2024, Номер 22(10), С. 650 - 665

Опубликована: Апрель 30, 2024

Язык: Английский

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A phylogenetic approach to comparative genomics

Nature Reviews Genetics, Год журнала: 2025, Номер unknown

Опубликована: Янв. 8, 2025

Язык: Английский

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Prokaryote pangenomes are dynamic entities

Current Opinion in Microbiology, Год журнала: 2022, Номер 66, С. 73 - 78

Опубликована: Янв. 31, 2022

Prokaryote pangenomes are influenced heavily by environmental factors and the opportunity for gene gain loss events. As field of pangenome analysis has expanded, so need to fully understand complexity how eco-evolutionary dynamics shape pangenomes. Here, we describe current models evolution discuss their suitability accuracy. We suggest that dynamic entities under constant flux, highlighting influence two-way interactions between environment. New classifications core accessory genes also considered, underscoring continuous evaluation nomenclature in a fast-moving field. conclude future should incorporate encompass dynamic, changeable nature.

Язык: Английский

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Distinct evolutionary trajectories in the Escherichia coli pangenome occur within sequence types

Microbial Genomics, Год журнала: 2022, Номер 8(11)

Опубликована: Ноя. 23, 2022

The Escherichia coli species contains a diverse set of sequence types and there remain important questions regarding differences in genetic content within this population that need to be addressed. Pangenomes are useful vehicles for studying gene types. Here, we analyse 21 E. type pangenomes using comparative pangenomics identify variance both pangenome structure content. We present functional breakdowns core genomes enriched metabolism, transcription cell membrane biogenesis genes. also uncover metabolism genes have variable classification, depending on which allele is present. Our approach allows detailed exploration the context species. show ongoing gain loss type-specific, may consequence distinct type-specific evolutionary drivers.

Язык: Английский

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Elucidating the functional roles of prokaryotic proteins using big data and artificial intelligence

FEMS Microbiology Reviews, Год журнала: 2023, Номер 47(1)

Опубликована: Янв. 1, 2023

Abstract Annotating protein sequences according to their biological functions is one of the key steps in understanding microbial diversity, metabolic potentials, and evolutionary histories. However, even best-studied prokaryotic genomes, not all proteins can be characterized by classical vivo, vitro, and/or silico methods—a challenge rapidly growing alongside advent next-generation sequencing technologies enormous extension ‘omics’ data public databases. These so-called hypothetical (HPs) represent a huge knowledge gap hidden potential for biotechnological applications. Opportunities leveraging available ‘Big Data’ have recently proliferated with use artificial intelligence (AI). Here, we review aims methods annotation explain different principles behind machine deep learning algorithms including recent research examples, order assist both biologists wishing apply AI tools developing comprehensive genome annotations computer scientists who want contribute this leading edge research.

Язык: Английский

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Lineage-specific variation in frequency and hotspots of recombination in invasive Escherichia coli

BMC Genomics, Год журнала: 2025, Номер 26(1)

Опубликована: Фев. 24, 2025

The opportunistic bacterium Escherichia coli can invade normally sterile sites in the human body, potentially leading to life-threatening organ dysfunction and even death. However, our understanding of evolutionary processes that shape its genetic diversity this environment remains limited. Here, we aim quantify frequency characteristics homologous recombination E. from bloodstream infections. Analysis 557 short-read genome sequences revealed propensity exchange DNA by varies within a distinct population (bloodstream) at narrow geographic (Dartmouth Hitchcock Medical Center, New Hampshire, USA) temporal (years 2016 – 2022) scope. We identified four largest monophyletic sequence clusters core phylogeny are represented prominent types (ST): BAPS1 (mainly ST95), BAPS4 ST73), BAPS10 ST131), BAPS14 ST58). show dominant vary different recombination: number single nucleotide polymorphisms due recombination, blocks, cumulative bases ratio probabilities given site was altered through mutation (r/m), rates which occurred (ρ/θ). Each cluster contains unique set antimicrobial resistance (AMR) virulence genes have experienced recombination. Common among were recombined with functions associated Curli secretion channel (csgG) ferric enterobactin transport (entEF, fepEG). did not identify any one AMR gene present all clusters. mdtABC, baeSR, emrKY tolC had BAPS4, BAPS10, BAPS14. These differences lie part on contributions vertically inherited ancestral contemporary branch-specific some genomes having relatively higher proportions DNA. Our results highlight variation via ranges. Understanding sources invasive will help inform implementation effective strategies reduce burden disease AMR.

Язык: Английский

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Genomic analysis of multidrug-resistant Escherichia coli isolated from dairy cows in Shihezi city, Xinjiang, China

Frontiers in Microbiology, Год журнала: 2025, Номер 16

Опубликована: Фев. 26, 2025

Introduction Dairy farming plays a vital role in agriculture and nutrition; however, the emergence of antimicrobial resistance (AMR) among bacterial pathogens poses significant risks to public health animal welfare. Multidrug-resistant (MDR) Escherichia coli strains are particular concern due their potential for zoonotic transmission multiple antibiotics. In this study, we investigated prevalence AMR analyzed genomes two MDR E. isolated from dairy cows Shihezi City. Methods Fecal samples were collected cows, isolated. Antibiotic susceptibility testing was conducted using Kirby-Bauer disk diffusion method against 14 Two isolates (E.coli_30 E.coli_45) selected whole-genome sequencing comparative genomic analysis. The Comprehensive Resistance Database (CARD) used identify genes, virulence factors analyzed. Phylogenetic analysis performed determine evolutionary relationships isolates, pangenome 50 assess genetic diversity. presence mobile elements (MGEs), including insertion sequences (IS) transposons, also examined. Results Among 22.9% exhibited MDR, with high imipenem ciprofloxacin, while gentamicin tetracycline remained most effective Genomic revealed key mphA , qnrS1 bla CTX-M-55 (the latter found only E.coli_45), conferring macrolides, quinolones, beta-lactams, respectively. Virulence genes encoding type III secretion systems (TTSS) adhesion identified, indicating pathogenic potential. showed that E.coli_30 E.coli_45 originated distinct ancestral lineages. extended-spectrum β-lactamase (ESBL) noticeable, so studied global national distribution We they endemic Salmonella enterica, Klebsiella pneumoniae. Pangenome diversity strains, unique related metabolism stress response. This indicates bacteria’s adaptation various environments. MGEs identified as contributors variability adaptation. Discussion study highlights growing threat farms, emphasizing critical spread genes. observed suggests strong adaptive capabilities, justifying need continuous surveillance livestock. Effective monitoring mitigation strategies essential prevent dissemination bacteria, thereby protecting both health.

Язык: Английский

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