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Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.

ABSTRACT: Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host's inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.84). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.

SUBMITTER: Ahn SH

PROVIDER: S-EPMC3541361 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.

Ahn Sun Hee SH Tsalik Ephraim L EL Cyr Derek D DD Zhang Yurong Y van Velkinburgh Jennifer C JC Langley Raymond J RJ Glickman Seth W SW Cairns Charles B CB Zaas Aimee K AK Rivers Emanuel P EP Otero Ronny M RM Veldman Tim T Kingsmore Stephen F SF Kingsmore Stephen F SF Lucas Joseph J Woods Christopher W CW Ginsburg Geoffrey S GS Fowler Vance G VG

PloS one 20130109 1

Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host's inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor ...[more]

PMID: 23326304

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Project description:Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the hostM-bM-^@M-^Ys inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 95 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.82). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.94, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues. To create a host gene expression-based classifier for S. aureus infection, mice from a variety of experimental conditions were utilized. Seven different strains of inbred mice (n=187 total) were challenged with four different S. aureus strains via intraperitoneal inoculation and sacrificed at various time points as described in Methods. The comparator group for model derivation included 50 A/J or C57BL/6J mice inoculated with E. coli (O18:K1:H7) as well as 54 uninfected mice. Next, the murine S. aureus classifier was externally validated in outbred CD-1 mice with S. aureus infection (Sanger 476 or USA300), E. coli infection (O18:K1:H7), or uninfected controls (10 animals per condition). Method: All experiments were performed on mice 6-8 weeks old. For the murine S. aureus predictor, seven inbred mouse strains (3 mice/strain: 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C57BL/6J, C3H/HeJ, and NOD/LtJ) were IP inoculated with 107 CFU/g of S. aureus Sanger476, euthanized at 2h after injection, and bled. This was repeated using four different S. aureus strains (USA100, USA300, MW2, and Sanger476) in A/J mice (n=3 per S. aureus strain). For time series experiments, both A/J and C57BL/6J mouse strains were IP inoculated with S. aureus Sanger476 as above, and sacrificed at 2, 4, 6, and 12h after injection (n=5 per time point).

Dataset Information

Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.

Publications

Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.

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