Large-scale genomic sequencing of extraintestinal pathogenic Escherichia coli strains
- Stephen J. Salipante,
- David J. Roach,
- Jacob O. Kitzman,
- Matthew W. Snyder,
- Bethany Stackhouse,
- Susan M. Butler-Wu,
- Choilee Lee,
- Brad T. Cookson and
- Jay Shendure1
- ↵* Corresponding author; email: shendure{at}uw.edu
Abstract
Large-scale bacterial genome sequencing efforts to date have provided limited information on the most prevalent category of disease: sporadically acquired infections caused by common pathogenic bacteria. Here, we performed whole genome sequencing and de novo assembly of 312 blood- or urine-derived isolates of extraintestinal pathogenic (ExPEC) Escherichia coli, a common agent of sepsis and community-acquired urinary tract infections, obtained during the course of routine clinical care at a single institution. We find that ExPEC E. coli are highly genomically heterogeneous, consistent with pan-genome analyses encompassing the larger species. Investigation of differential virulence factor content and antibiotic resistance phenotypes reveals markedly different profiles among lineages and among strains infecting different bodily sites. We use high-resolution molecular epidemiology to explore the dynamics of infections at the level of individual patients, including identification of possible person-to-person transmission. Notably, a limited number of discrete lineages caused the majority of bloodstream infections, including one sub-clone (ST131-H30) responsible for 28% of bacteremic E. coli infections over a three-year period. We additionally use a microbial genome-wide-association study (GWAS) approach to identify individual genes responsible for antibiotic resistance, successfully recovering known genes but notably not identifying any novel factors. We anticipate that in the near future, whole genome sequencing of microorganisms associated with clinical disease will become routine. Our study reveals what kinds of information can be obtained from sequencing clinical isolates on a large scale, even well-characterized organisms such as E. coli, and provides insight into how this information might be utilized in a healthcare setting.
- Received June 19, 2014.
- Accepted November 3, 2014.
- Published by Cold Spring Harbor Laboratory Press
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