Plasmids of the urinary microbiota.

microbiome plasmid plasmidome urinary tract urobiome

Journal

Access microbiology
ISSN: 2516-8290
Titre abrégé: Access Microbiol
Pays: England
ID NLM: 101746927

Informations de publication

Date de publication:
2022
Historique:
received: 14 02 2022
accepted: 09 09 2022
entrez: 16 1 2023
pubmed: 17 1 2023
medline: 17 1 2023
Statut: epublish

Résumé

Studies of the last decade have identified a phylogenetically diverse community of bacteria within the urinary tract of individuals with and without urinary symptoms. Mobile genetic elements (MGEs), including plasmids and phages, within this niche have only recently begun to be explored. These MGEs can expand metabolic capacity and increase virulence, as well as confer antibiotic resistance. As such, they have the potential to contribute to urinary symptoms. While plasmids for some of the bacterial taxa found within the urinary microbiota (urobiome) have been well characterized, many urinary species are under-studied with few genomes sequenced to date. Using a two-pronged bioinformatic approach, we have conducted a comprehensive investigation of the plasmid content of urinary isolates representative of 102 species. The bioinformatic tools plasmidSPAdes and Recycler were used in tandem to identify plasmid sequences from raw short-read sequence data followed by manual curation. In total, we identified 603 high-confidence plasmid sequences in 20 different genera of the urobiome. In total, 70 % of these high-confidence plasmids exhibit sequence similarity to plasmid sequences from the gut. This observation is primarily driven by plasmids from

Identifiants

pubmed: 36644432
doi: 10.1099/acmi.0.000429
pii: 000429
pmc: PMC9833419
doi:

Types de publication

Journal Article

Langues

eng

Pagination

acmi000429

Subventions

Organisme : NIDDK NIH HHS
ID : R25 DK122954
Pays : United States

Informations de copyright

© 2022 The Authors.

Déclaration de conflit d'intérêts

A.J.W. serves on the Scientific Advisor Boards of Pathnostics and Urobiome Therapeutics.

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Auteurs

Genevieve Johnson (G)

Bioinformatics Program, Loyola University Chicago, Chicago, IL, USA.

Seanna Bataclan (S)

Biology Program, Division of Natural Sciences, University of Guam, Mangilao, GU, USA.

Minerva So (M)

School of Life Sciences, Arizona State University, Tempe, AZ, USA.

Swarnali Banerjee (S)

Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA.

Alan J Wolfe (AJ)

Department of Microbiology and Immunology, Loyola University Chicago, Maywood, IL, USA.

Catherine Putonti (C)

Bioinformatics Program, Loyola University Chicago, Chicago, IL, USA.
Department of Microbiology and Immunology, Loyola University Chicago, Maywood, IL, USA.
Department of Biology, Loyola University Chicago, Chicago, IL, USA.

Classifications MeSH