Gene Expression-Based Classifiers Identify Staphylococcus aureus Infection in Mice and Humans
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PROVIDER: PRJNA148969 | ENA |
REPOSITORIES: ENA
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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 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 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.
2013-01-11 | GSE33341 | GEO
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).
2013-01-11 | E-GEOD-33341 | biostudies-arrayexpress
Project description:Gene Expression-Based Classifiers Identify Staphylococcus aureus Infection in Mice and Humans
2019-03-26 | E-ENAD-29 | ExpressionAtlas
Project description:Gene Expression-Based Classifiers Identify Staphylococcus aureus Infection in Mice and Humans
2019-03-20 | E-ENAD-28 | ExpressionAtlas
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 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.
| S-EPMC3541361 | biostudies-literature
Project description:Previously, we used mouse and non-human primate models to show that serum miRNAs may predict the biological impact of lethal and sublethal radiation doses. We hypothesized that these results can be replicated in humans treated with total body irradiation (TBI), and that miRNAs may be used as clinically feasible biodosimeters. To test this hypothesis, serial serum samples were obtained from 25 patients who underwent allogeneic stem-cell transplantation and profiled for miRNA expression using next-generation sequencing. Differential expression results were largely consistent with previous studies and allowed us to select miRNAs, including miR-150-5p, miR-126-5p, miR-375, miR-215-5p, miR-144-5p, miR-122-5p, miR-320d and miR-10b-5p to build classifiers using qPCR-based quantification. We therefore conclude that serum miRNAs reflect radiation exposure and dose for humans undergoing TBI and may be used as functional biodosimeters for precise identification of people exposed to clinically significant radiation doses.
2021-05-20 | GSE174705 | GEO
Project description:Staphylococcus aureus is one of the most important pathogens in humans and animals, multiply resistant strains are increasingly widespread, new agents are needed for the treatment of S. aureus. Rhein, a natural plant product, has potential antimicrobial activity against Staphylococcus aureus. We employed Affymetrix Staphylococcus aureus GeneChipsTM arrays to investigate the global transcriptional profiling of Staphylococcus aureus ATCC25923 treated with rhein. Results provided insight into mechanisms involved in rhein - Staphylococcus aureus interactions. Keywords: rhein response
2007-06-15 | GSE8135 | GEO
Project description:Staphylococcus aureus is one of the most important pathogens in humans and animals, multiply resistant strains are increasingly widespread, new agents are needed for the treatment of S. aureus. Rhein, a natural plant product, has potential antimicrobial activity against Staphylococcus aureus. We employed Affymetrix Staphylococcus aureus GeneChipsTM arrays to investigate the global transcriptional profiling of Staphylococcus aureus ATCC25923 treated with rhein. Results provided insight into mechanisms involved in rhein - Staphylococcus aureus interactions. Keywords: rhein response Staphylococcus aureus cells were exposed for 45 minutes to rhein at concentration of 8 µg/ml (1/2à MIC), 6 samples including 3 control samples are analyzed.
2010-06-10 | E-GEOD-8135 | biostudies-arrayexpress
Project description:Serum miRNA-based signature to identify radiation exposure and dose in humans
| PRJNA731156 | ENA
Project description:Gene expression classifiers identify bacterial and viral etiologies of acute respiratory illness in Sri Lanka.
| PRJNA630674 | ENA