Integrated analysis of population genomics, transcriptomics and virulence provides novel insights into Streptococcus pyogenes pathogenesis

Research output: Contribution to journalArticleScientificpeer-review

Researchers

  • Priyanka Kachroo
  • Jesus M. Eraso
  • Randall J. Olsen
  • Stephen B. Beres
  • Luchang Zhu
  • Waleed Nasser
  • Paul E. Bernard
  • Concepcion C. Cantu
  • Matthew Ojeda Saavedra
  • María José Arredondo
  • Benjamin Strope
  • Hackwon Do
  • Muthiah Kumaraswami
  • Jaana Vuopio
  • Kirsi Gröndahl-Yli-Hannuksela
  • Karl G. Kristinsson
  • Magnus Gottfredsson
  • Johan Pensar
  • Emily R. Davenport
  • Andrew G. Clark
  • Jukka Corander
  • Dominique A. Caugant
  • Shahin Gaini
  • Marita Debess Magnussen
  • Samantha L. Kubiak
  • Hoang A.T. Nguyen
  • S. Wesley Long
  • Adeline R. Porter
  • Frank R. DeLeo
  • James M. Musser

Research units

  • Houston Methodist Hospital
  • Cornell University
  • University of Turku
  • National Institute for Health and Welfare
  • Landspitali University Hospital
  • University of Iceland
  • University of Helsinki
  • University of Oslo
  • Norwegian Institute of Public Health
  • National Hospital of the Faroe Islands
  • University of Southern Denmark
  • Thetis
  • University of the Faroe Islands
  • National Institutes of Health

Abstract

Streptococcus pyogenes causes 700 million human infections annually worldwide, yet, despite a century of intensive effort, there is no licensed vaccine against this bacterium. Although a number of large-scale genomic studies of bacterial pathogens have been published, the relationships among the genome, transcriptome, and virulence in large bacterial populations remain poorly understood. We sequenced the genomes of 2,101 emm28 S. pyogenes invasive strains, from which we selected 492 phylogenetically diverse strains for transcriptome analysis and 50 strains for virulence assessment. Data integration provided a novel understanding of the virulence mechanisms of this model organism. Genome-wide association study, expression quantitative trait loci analysis, machine learning, and isogenic mutant strains identified and confirmed a one-nucleotide indel in an intergenic region that significantly alters global transcript profiles and ultimately virulence. The integrative strategy that we used is generally applicable to any microbe and may lead to new therapeutics for many human pathogens.

Details

Original languageEnglish
Pages (from-to)548-559
Number of pages12
JournalNATURE GENETICS
Volume51
Issue number3
Publication statusPublished - 1 Mar 2019
MoE publication typeA1 Journal article-refereed

ID: 33657762