Literature DB >> 30239153

Whole Genome Next-Generation Sequencing Mutation Identification in Pseudomonas aeruginosa.

Murat Cetinbas1,2, Shen Yu1,2, Ruslan I Sadreyev1,3.   

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. © 2018 John Wiley & Sons, Inc.

Entities:  

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

Mesh:

Substances:

Year:  2018        PMID: 30239153      PMCID: PMC6168388          DOI: 10.1002/cpmb.69

Source DB:  PubMed          Journal:  Curr Protoc Mol Biol        ISSN: 1934-3647


  3 in total

1.  Next-Generation Sequencing for Identification of EMS-Induced Mutations in Caenorhabditis elegans.

Authors:  Nicolas J Lehrbach; Fei Ji; Ruslan Sadreyev
Journal:  Curr Protoc Mol Biol       Date:  2017-01-05

2.  CloudMap: a cloud-based pipeline for analysis of mutant genome sequences.

Authors:  Gregory Minevich; Danny S Park; Daniel Blankenberg; Richard J Poole; Oliver Hobert
Journal:  Genetics       Date:  2012-10-10       Impact factor: 4.562

3.  The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update.

Authors:  Enis Afgan; Dannon Baker; Marius van den Beek; Daniel Blankenberg; Dave Bouvier; Martin Čech; John Chilton; Dave Clements; Nate Coraor; Carl Eberhard; Björn Grüning; Aysam Guerler; Jennifer Hillman-Jackson; Greg Von Kuster; Eric Rasche; Nicola Soranzo; Nitesh Turaga; James Taylor; Anton Nekrutenko; Jeremy Goecks
Journal:  Nucleic Acids Res       Date:  2016-05-02       Impact factor: 16.971

  3 in total

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