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

dc.contributor.author Ahn, Sun Hee
dc.contributor.author Tsalik, Ephraim L
dc.contributor.author Cyr, Derek D
dc.contributor.author Zhang, Yurong
dc.contributor.author van Velkinburgh, Jennifer C
dc.contributor.author Langley, Raymond J
dc.contributor.author Glickman, Seth W
dc.contributor.author Cairns, Charles B
dc.contributor.author Zaas, Aimee K
dc.contributor.author Rivers, Emanuel P
dc.contributor.author Otero, Ronny M
dc.contributor.author Veldman, Tim
dc.contributor.author Kingsmore, Stephen F
dc.contributor.author Kingsmore, Stephen F
dc.contributor.author Lucas, Joseph
dc.contributor.author Woods, Christopher W
dc.contributor.author Ginsburg, Geoffrey S
dc.contributor.author Fowler, Vance G
dc.coverage.spatial United States
dc.date.accessioned 2017-01-01T20:12:04Z
dc.date.issued 2013
dc.identifier http://www.ncbi.nlm.nih.gov/pubmed/23326304
dc.identifier PONE-D-12-25216
dc.identifier.uri https://hdl.handle.net/10161/13321
dc.description.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.
dc.language eng
dc.publisher Public Library of Science (PLoS)
dc.relation.ispartof PLoS One
dc.relation.isversionof 10.1371/journal.pone.0048979
dc.subject Adult
dc.subject Aged
dc.subject Aged, 80 and over
dc.subject Animals
dc.subject Anti-Bacterial Agents
dc.subject Gene Expression Profiling
dc.subject Host-Pathogen Interactions
dc.subject Humans
dc.subject Mice
dc.subject Mice, 129 Strain
dc.subject Mice, Inbred BALB C
dc.subject Mice, Inbred C3H
dc.subject Mice, Inbred C57BL
dc.subject Mice, Inbred NOD
dc.subject Mice, Inbred Strains
dc.subject Middle Aged
dc.subject Oligonucleotide Array Sequence Analysis
dc.subject Reproducibility of Results
dc.subject Sensitivity and Specificity
dc.subject Sepsis
dc.subject Species Specificity
dc.subject Staphylococcal Infections
dc.subject Staphylococcus aureus
dc.subject Young Adult
dc.title Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.
dc.type Journal article
duke.contributor.id Tsalik, Ephraim L|0373391
duke.contributor.id Zaas, Aimee K|0278273
duke.contributor.id Lucas, Joseph|0308238
duke.contributor.id Woods, Christopher W|0075873
duke.contributor.id Ginsburg, Geoffrey S|0331881
duke.contributor.id Fowler, Vance G|0025542
pubs.author-url http://www.ncbi.nlm.nih.gov/pubmed/23326304
pubs.begin-page e48979
pubs.issue 1
pubs.organisational-group Basic Science Departments
pubs.organisational-group Biomedical Engineering
pubs.organisational-group Biostatistics & Bioinformatics
pubs.organisational-group Clinical Science Departments
pubs.organisational-group Duke
pubs.organisational-group Duke Cancer Institute
pubs.organisational-group Duke Clinical Research Institute
pubs.organisational-group Global Health Institute
pubs.organisational-group Institutes and Centers
pubs.organisational-group Institutes and Provost's Academic Units
pubs.organisational-group Medicine
pubs.organisational-group Medicine, Cardiology
pubs.organisational-group Medicine, Infectious Diseases
pubs.organisational-group Molecular Genetics and Microbiology
pubs.organisational-group Pathology
pubs.organisational-group Pratt School of Engineering
pubs.organisational-group School of Medicine
pubs.organisational-group School of Nursing
pubs.organisational-group School of Nursing - Secondary Group
pubs.organisational-group Social Science Research Institute
pubs.organisational-group University Institutes and Centers
pubs.publication-status Published
pubs.volume 8
dc.identifier.eissn 1932-6203
duke.contributor.orcid Tsalik, Ephraim L|0000-0002-6417-2042
duke.contributor.orcid Woods, Christopher W|0000-0001-7240-2453
duke.contributor.orcid Ginsburg, Geoffrey S|0000-0003-4739-9808


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