Back to Search Start Over

Identification of Pathogenicity-Associated Loci in Klebsiella pneumoniae from Hospitalized Patients

Authors :
Rebekah M. Martin
Jie Cao
Weisheng Wu
Lili Zhao
David M. Manthei
Ali Pirani
Evan Snitkin
Preeti N. Malani
Krishna Rao
Michael A. Bachman
Source :
mSystems, Vol 3, Iss 3 (2018)
Publication Year :
2018
Publisher :
American Society for Microbiology, 2018.

Abstract

ABSTRACT Despite insights gained through experimental models, the set of bacterial genes important for human infection is unclear for many of our most threatening pathogens. Klebsiella pneumoniae is a leading cause of health care-associated infections (HAIs) and commonly colonizes hospitalized patients, but the factors that determine whether a particular isolate causes disease or remains a colonizer are poorly understood. To identify bacterial genes associated with K. pneumoniae infection, a case-control study was performed comparing infected and asymptomatic colonized patients. Comparative bacterial genomics was combined with a conditional logit model that identified patient factors differentiating cases from controls. This method identified five gene loci associated with infection after adjustment for patient factors, including a psicose sugar utilization locus that was validated as a fitness factor during mouse lung infection. These results indicate that bacterial genome-wide association studies of patients can identify loci associated with HAIs and important in infection models. IMPORTANCE Klebsiella pneumoniae is a common cause of infections in the health care setting. This work supports a paradigm for K. pneumoniae pathogenesis where the accessory genome, composed of genes present in some but not all isolates, influences whether a strain causes infection or asymptomatic colonization, after accounting for patient-level factors. Identification of patients at high risk of infection could allow interventions to prevent or rapidly treat K. pneumoniae infections. Author Video: An author video summary of this article is available.

Details

Language :
English
ISSN :
23795077
Volume :
3
Issue :
3
Database :
Directory of Open Access Journals
Journal :
mSystems
Publication Type :
Academic Journal
Accession number :
edsdoj.40a29fbd0ddd46af832ba1d1635f4756
Document Type :
article
Full Text :
https://doi.org/10.1128/mSystems.00015-18