Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

High-throughput whole genome sequencing has unlocked a multitude of possibilities enabling members of the Neisseria genus to be examined with unprecedented detail, including the human pathogens Neisseria meningitidis and Neisseria gonorrhoeae. To maximise the potential benefit of this for public health, it is becoming increasingly important to ensure that this plethora of data are adequately stored, disseminated and made readily accessible. Investigations facilitating cross-species comparisons as well as the analysis of global datasets will allow differences among and within species and across geographic locations and different times to be identified, improving our understanding of the distinct phenotypes observed. Recent advances in high-throughput platforms that measure the transcriptome, proteome and/or epigenome are also becoming increasingly employed to explore the complexities of Neisseria biology. An integrated approach to the analysis of these is essential to fully understand the impact these may have in the Neisseria genus. This article reviews the current status of some of the tools available for next generation sequence analysis at the dawn of the 'post-genomic' era.

Original publication

DOI

10.1093/femspd/ftx060

Type

Journal article

Journal

Pathog Dis

Publication Date

31/08/2017

Volume

75

Keywords

Neisseria gonorrhoeae; Omics analyses, Neisseria meningitidis, next-generation sequencing, Anti-Bacterial Agents, DNA, Bacterial, Databases, Genetic, Datasets as Topic, Drug Resistance, Bacterial, Genome, Bacterial, Genomics, Gonorrhea, High-Throughput Nucleotide Sequencing, Humans, Meningitis, Meningococcal, Neisseria gonorrhoeae, Neisseria meningitidis, Transcriptome, Virulence, Whole Genome Sequencing