GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 20 07 2022
accepted: 29 10 2022
entrez: 16 2 2023
pubmed: 17 2 2023
medline: 22 2 2023
Statut: epublish

Résumé

Whole genome sequencing (WGS) of clinical bacterial isolates has the potential to transform the fields of diagnostics and public health. To realize this potential, bioinformatic software that reports identification results needs to be developed that meets the quality standards of a diagnostic test. We developed GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking) using k-mer based strategies for identification of bacteria based on WGS reads. GAMBIT incorporates this algorithm with a highly curated searchable database of 48,224 genomes. Herein, we describe validation of the scoring methodology, parameter robustness, establishment of confidence thresholds and the curation of the reference database. We assessed GAMBIT by way of validation studies when it was deployed as a laboratory-developed test in two public health laboratories. This method greatly reduces or eliminates false identifications which are often detrimental in a clinical setting.

Identifiants

pubmed: 36795668
doi: 10.1371/journal.pone.0277575
pii: PONE-D-22-20500
pmc: PMC9934365
doi:

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S. Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0277575

Subventions

Organisme : NIAID NIH HHS
ID : R15 AI130816
Pays : United States

Informations de copyright

Copyright: © 2023 Lumpe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Jared Lumpe (J)

Independent Researcher, Meriden, Connecticut, United States of America.

Lynette Gumbleton (L)

Nevada State Public Health Laboratory, Reno, NV, United States of America.

Andrew Gorzalski (A)

Nevada State Public Health Laboratory, Reno, NV, United States of America.

Kevin Libuit (K)

Theiagen Consulting LLC, Highlands Ranch, CO, United States of America.

Vici Varghese (V)

Alameda County Department of Public Health, Oakland, CA, United States of America.

Tyler Lloyd (T)

Alameda County Department of Public Health, Oakland, CA, United States of America.

Farid Tadros (F)

Biology Department, Santa Clara University, Santa Clara, CA, United States of America.

Tyler Arsimendi (T)

Biology Department, Santa Clara University, Santa Clara, CA, United States of America.

Eileen Wagner (E)

Theiagen Consulting LLC, Highlands Ranch, CO, United States of America.

Craig Stephens (C)

Biology Department, Santa Clara University, Santa Clara, CA, United States of America.

Joel Sevinsky (J)

Theiagen Consulting LLC, Highlands Ranch, CO, United States of America.

David Hess (D)

Nevada State Public Health Laboratory, Reno, NV, United States of America.
Biology Department, Santa Clara University, Santa Clara, CA, United States of America.
Department of Pathology and Laboratory Medicine, University of Nevada, Reno School of Medicine, Reno, NV, United States of America.

Mark Pandori (M)

Nevada State Public Health Laboratory, Reno, NV, United States of America.
Alameda County Department of Public Health, Oakland, CA, United States of America.
Department of Pathology and Laboratory Medicine, University of Nevada, Reno School of Medicine, Reno, NV, United States of America.
Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, Reno, NV, United States of America.

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Classifications MeSH