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Characterization of Staphylococcus epidermidis clinical and commensal isolates transcriptome upon interaction with human blood

ABSTRACT: The release of cells from S. epidermidis biofilms formed on medical devices has been associated with the onset of bloodstream infections, resulting in increased morbidity and mortality rates. This has to do, in part, with the difficulty to accurately diagnose S. epidermidis bloodstream infections. S. epidermidis is a ubiquitous commensal of human skin and mucosa and, thus, a positive blood culture does not always represent an infection, possibly being the result of contamination during blood collection. As such, there is a high demand to find markers that can help clinicians to distinguish infection (clinical isolates) from contamination (commensal strains). With that in mind, several studies comparing phenotypic or genetic characteristics of clinical and commensal isolates have been performed over the years. However, because S. epidermidis virulence factors seem to be the same that confer its fitness as a commensal, we hypothesized that the ability of S. epidermidis strains to adapt to the host environment may not depend on a specific phenotypic and/or genetic makeup, but rather on the regulation of gene transcription. Thus, using RNA-Sequencing (RNA-seq), we characterized the transcriptome of commensal and clinical isolates in the context of infection to try to uncover differences and, thus, identify markers that could be used for the diagnostics. Several markers with the potential to discriminate between both groups were highlighted. Nevertheless, when the results obtained were confirmed in a wider collection of clinical and commensal isolates the discriminatory power of the genes initially identified was lost. Although we cannot rule out that the characterization of a larger collection of isolates would identify potential candidates, our transcriptomic data was not able to confirm our initial hypothesis, evidencing S. epidermidis opportunistic nature.

ORGANISM(S): Staphylococcus epidermidis

PROVIDER: GSE179407 | GEO | 2022/12/09

REPOSITORIES: GEO

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Project description:Leber2015 - Mucosal immunity and gut microbiome interaction during C. difficile infection This model is described in the article: Systems Modeling of Interactions between Mucosal Immunity and the Gut Microbiome during Clostridium difficile Infection. Leber A, Viladomiu M, Hontecillas R, Abedi V, Philipson C, Hoops S, Howard B, Bassaganya-Riera J. PLoS ONE 2015; 10(7): e0134849 Abstract: Clostridium difficile infections are associated with the use of broad-spectrum antibiotics and result in an exuberant inflammatory response, leading to nosocomial diarrhea, colitis and even death. To better understand the dynamics of mucosal immunity during C. difficile infection from initiation through expansion to resolution, we built a computational model of the mucosal immune response to the bacterium. The model was calibrated using data from a mouse model of C. difficile infection. The model demonstrates a crucial role of T helper 17 (Th17) effector responses in the colonic lamina propria and luminal commensal bacteria populations in the clearance of C. difficile and colonic pathology, whereas regulatory T (Treg) cells responses are associated with the recovery phase. In addition, the production of anti-microbial peptides by inflamed epithelial cells and activated neutrophils in response to C. difficile infection inhibit the re-growth of beneficial commensal bacterial species. Computational simulations suggest that the removal of neutrophil and epithelial cell derived anti-microbial inhibitions, separately and together, on commensal bacterial regrowth promote recovery and minimize colonic inflammatory pathology. Simulation results predict a decrease in colonic inflammatory markers, such as neutrophilic influx and Th17 cells in the colonic lamina propria, and length of infection with accelerated commensal bacteria re-growth through altered anti-microbial inhibition. Computational modeling provides novel insights on the therapeutic value of repopulating the colonic microbiome and inducing regulatory mucosal immune responses during C. difficile infection. Thus, modeling mucosal immunity-gut microbiota interactions has the potential to guide the development of targeted fecal transplantation therapies in the context of precision medicine interventions. This model is hosted on BioModels Database and identified by: BIOMD0000000583. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Characterization of Staphylococcus epidermidis clinical and commensal isolates transcriptome upon interaction with human blood

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