Dataset Information

Comparative exoproteome profiling of an invasive and a commensal Staphylococcus haemolyticus isolate

ABSTRACT: Staphylococcus haemolyticus is a skin commensal emerging as an opportunistic pathogen. Nosocomial isolates of S. haemolyticus are the most antibiotic resistant members of the coagulase negative staphylococci (CoNS), but information about other S.haemolyticus virulence factors is scarce. Bacterial virulence is mediated by membrane vesicles (MVs) which enable secretion and long distance delivery of bacterial effector molecules while protecting the cargo from proteolytic degradation from the environment. We wanted to determine if the MV protein cargo of S.haemolyticus is strain specific and enriched in certain MV associated proteins compared to the totalsecretome. The present study shows that both clinical and commensal S. haemolyticus isolates produce membrane vesicles. The MV cargo of both strains was enriched in proteins involved in adhesion and in acquisition of iron. The MV cargo of the clinical strain was further enriched in antimicrobial resistance proteins.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Staphylococcus Haemolyticus

SUBMITTER: Jack-Ansgar Bruun

LAB HEAD: Jorunn Pauline Cavanagh

PROVIDER: PXD010389 | Pride | 2018-11-30

REPOSITORIES: Pride

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Comparative exoproteome profiling of an invasive and a commensal Staphylococcus haemolyticus isolate.

Cavanagh Jorunn Pauline JP Pain Maria M Askarian Fatemeh F Bruun Jack-Ansgar JA Urbarova Ilona I Wai Sun Nyunt SN Schmidt Frank F Johannessen Mona M

Journal of proteomics 20181122

Staphylococcus haemolyticus is a skin commensal emerging as an opportunistic pathogen. Nosocomial isolates of S. haemolyticus are the most antibiotic resistant members of the coagulase negative staphylococci (CoNS), but information about other S. haemolyticus virulence factors is scarce. Bacterial membrane vesicles (MVs) are one mediator of virulence by enabling secretion and long distance delivery of bacterial effector molecules while protecting the cargo from proteolytic degradation from the e ...[more]

PMID: 30472255

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Project description:Several studies indicate that adult stem cells may improve the recovery from acute tissue injury. It has been suggested that they may contribute to tissue regeneration by the release of paracrine factors promoting proliferation of tissue resident cells. However, the factors involved remain unknown. In the present study we found that microvesicles (MV) derived from human liver stem cells (HLSC) were able to stimulate in vitro proliferation and apoptosis resistance of human and rat hepatocytes. These effects required internalization of MV in the hepatocytes by an alpha4 integrin-dependent mechanism. However, when treated with RNase, MV despites their internalization were unable to induce hepatocyte proliferation and apoptosis resistance, suggesting an RNA dependent effect. Microarray analysis and quantitative RT-PCR demonstrated that MV were shuttling a specific subset of cellular mRNA, such as mRNA associated in the control of transcription, translation, proliferation and apoptosis. When administered in vivo, MV were found to accelerate the morphological and functional recovery of liver in a model of 70% hepatectomy in rats by inducing an hepatocytes proliferation that was abolished by RNase treatment. Using human AGO2 gene, which is shuttled by MV, as a reporter gene, we found the expression of human AGO2 mRNA and protein in the liver of hepatectomized rats treated with MV. This suggest a translation of the MV shuttled mRNA within hepatocytes of treated rats. Conclusion: these results suggest that MV derived from HLSC may activate a proliferative program in remnant hepatocytes after hepatectomy by a horizontal transfer of specific mRNA subsets. MV contained mRNA was submitted to microarray analysis not to define the amount of mRNA but only to define which transcripts were present. Total RNA was prepared from two independent preparation of vesicles. 250, 500 and 1000 ngs from each preparation were transformed in biotin-labeled cRNA. A simple statistical linear model was used to identify transcript signals linearly correlated to the increment of total RNA concentration used to prepare cRNA.

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