Cited by 3,551Genomics and Phylogenetic StudiesBacterial Identification and Susceptibility TestingAntimicrobial Resistance in Staphylococcus

Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications

Open access
Jolley, Keith A., Bray, James E., Maiden, Martin C. J.·2018·Wellcome Open Research

Abstract

The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera. Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes. Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications. The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation. Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes. There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question. In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.

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Authors
Jolley, K. A., Bray, J. E., & Maiden, M. C. J.
Affiliations
University of Oxford (GB)
Corresponding author
Jolley, Keith A.
Venue
Wellcome Open Research
Published
2018-09-24
Volume
3
Pages
124
ISSN
2398-502X (ISSN-L)
OpenAlex
W2891078715
Cited by
3,551
References
88
Citations by year
2026: 667 · 2025: 690 · 2024: 626 · 2023: 506 · 2022: 426 · 2021: 330 · 2020: 215 · 2019: 84 · 2018: 2 · 2014: 1
FWCI
55.82
Type
journal article
Language
en
Open access
Locations
  • Wellcome Open Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Wellcome Trust (104992)
  • FP7 Ideas: European Research Council (FP7-278864-2)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Bacterial Identification and Susceptibility Testing
  • Health Sciences › Medicine › Infectious Diseases › Antimicrobial Resistance in Staphylococcus
Keywords
multilocus sequence typing, antimicrobial resistance prediction, allelic variation, REST API, open access databases

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