Whole Genome Next-Generation Sequencing Mutation Identification in Pseudomonas aeruginosa

Curr Protoc Mol Biol. 2018 Oct;124(1):e69. doi: 10.1002/cpmb.69. Epub 2018 Sep 21.

Abstract

Identification of spontaneous or chemically induced bacterial mutations is a powerful tool for investigation of molecular mechanisms, including the mechanism of action of novel antibiotics. However, a major bottleneck to this approach has been the identification of the causative mutation underlying a phenotype of interest. Until recently, this has required time-consuming genetic analysis. However, the advent of relatively inexpensive and rapid next-generation sequencing (NGS) technologies has revolutionized the correlation of bacterial phenotypes and genotypes. In this article we describe a simple bioinformatics pipeline to identify differences between sequenced bacterial genomes. We also describe the procedures involved in growing, extracting, and purifying DNA, and preparation of sequencing libraries for one bacterial species, Pseudomonas aeruginosa. Similar protocols will be applicable to other bacterial species. © 2018 by John Wiley & Sons, Inc.

Keywords: bacterial mutations; ethyl methanesulfonate mutagenesis; next-generation sequencing; spontaneous mutation detection.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • DNA Mutational Analysis / methods*
  • DNA, Bacterial / isolation & purification
  • Ethyl Methanesulfonate / pharmacology
  • Genome, Bacterial*
  • High-Throughput Nucleotide Sequencing / methods*
  • Mutagenesis
  • Mutation
  • Pseudomonas aeruginosa / drug effects
  • Pseudomonas aeruginosa / genetics*
  • Whole Genome Sequencing*

Substances

  • DNA, Bacterial
  • Ethyl Methanesulfonate