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Microbial sequence typing in the genomic era.

Marcos Pérez-Losada1, Miguel Arenas2, Eduardo Castro-Nallar3

  • 1Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Ashburn, VA 20147, USA; CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, Vairão 4485-661, Portugal; Children's National Medical Center, Washington, DC 20010, USA.

Infection, Genetics and Evolution : Journal of Molecular Epidemiology and Evolutionary Genetics in Infectious Diseases
|September 26, 2017
PubMed
Summary
This summary is machine-generated.

Next-generation sequencing (NGS) revolutionizes microbial genomics by enabling comprehensive gene and genome analysis. This review details NGS methods for microbial typing and their applications in epidemiology and phylogenetics.

Keywords:
BacteriaEpidemiologyMLSTPathogenTypingWGS

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Area of Science:

  • Microbial Genomics
  • Bioinformatics

Background:

  • Next-generation sequencing (NGS) offers a cost-effective, comprehensive alternative to traditional Sanger sequencing for microbial genomics.
  • NGS expands traditional nucleotide variation-based typing methods (MLST, MLVA, rMLST, cgMLST) to millions of sequences, including whole genomes (WGS, NGMLST, HiMLST).

Purpose of the Study:

  • To review standard and novel microbial sequence typing approaches at gene and genome levels using NGS.
  • To provide guidelines for analyzing high-dimensional NGS data and discuss computational frameworks.
  • To present applications of NGS-based typing in genotyping, phylogenetics, and molecular epidemiology.

Main Methods:

  • Review of existing literature on NGS technologies and their application in microbial typing.
  • Description of standard and emerging sequence typing strategies, from gene fragments to whole genomes.
  • Discussion of analytical and statistical techniques required for high-dimensional NGS data.

Main Results:

  • NGS significantly enhances the scope and depth of microbial genomic analysis compared to older methods.
  • New NGS-based typing strategies (WGS, NGMLST, HiMLST) allow for variation analysis across millions of sequences.
  • Development of novel analytical and statistical techniques is crucial for interpreting complex NGS data.

Conclusions:

  • NGS is transforming microbial genomics, offering unprecedented insights into microbial diversity, structure, and composition.
  • Effective analysis of NGS data requires advanced computational and statistical methods.
  • NGS-based typing has broad applications in molecular epidemiology, phylogenetics, and genotyping.