Population and Functional Genomics of Neisseria Revealed with Gene-by-Gene Approaches

J Clin Microbiol. 2016 Aug;54(8):1949-55. doi: 10.1128/JCM.00301-16. Epub 2016 Apr 20.

Abstract

Rapid low-cost whole-genome sequencing (WGS) is revolutionizing microbiology; however, complementary advances in accessible, reproducible, and rapid analysis techniques are required to realize the potential of these data. Here, investigations of the genus Neisseria illustrated the gene-by-gene conceptual approach to the organization and analysis of WGS data. Using the gene and its link to phenotype as a starting point, the BIGSdb database, which powers the PubMLST databases, enables the assembly of large open-access collections of annotated genomes that provide insight into the evolution of the Neisseria, the epidemiology of meningococcal and gonococcal disease, and mechanisms of Neisseria pathogenicity.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods
  • Genomics / methods*
  • Gonorrhea / epidemiology
  • Gonorrhea / microbiology*
  • Gonorrhea / pathology
  • High-Throughput Nucleotide Sequencing / methods
  • Humans
  • Meningococcal Infections / epidemiology
  • Meningococcal Infections / microbiology*
  • Meningococcal Infections / pathology
  • Neisseria / classification
  • Neisseria / genetics*
  • Neisseria / pathogenicity