Unraveling Gardnerella vaginalis surface proteins using cell shaving proteomics

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Abstract

Gardnerella vaginalis is one of the main etiologic agents of bacterial vaginosis (BV). This infection is responsible for a wide range of public health costs and is associated with several adverse outcomes during pregnancy. Improving our understanding of G. vaginalis protein cell surface will assist in BV diagnosis. This study represents the first proteomic approach that has analyzed the exposed proteins on G. vaginalis cell surface using a shaving approach. The 261 G. vaginalis proteins identified using this approach were analyzed with bioinformatic tools to detect characteristic motifs from surface-exposed proteins, such as signal peptides (36 proteins), lipobox domains (17 proteins), LPXTG motifs (5 proteins) and transmembrane alpha-helices (66 proteins). One third of the identified proteins were found to have at least one typical motif of surface-exposed proteins. Furthermore, the subcellular location was examined using two predictors (PSORT and Gpos-mPLoc). These bioinformatic tools classified 17% of the identified proteins as surface-associated proteins. Interestingly, we identified 13 members of the ATP-binding cassette (ABC) superfamily, which were mainly involved in the translocation of various substrates across membranes. To validate the location of the G. vaginalis surface-exposed proteins, an immunofluorescence assay with antibodies against Escherichia coli GroEL was performed to reveal the extracellular location of the moonlighting GroEL. In addition, monoclonal antibodies (mAb) against G. vaginalis Cna protein were produced and used to validate the location of Cna on the surface of the G. vaginalis. These high affinity anti-Cna mAb represent a useful tool for the study of this pathogenic microorganism and the BV.

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Marín, E., Haesaert, A., Padilla, L., Adán, J., Hernáez, M. L., Monteoliva, L., & Gil, C. (2018). Unraveling Gardnerella vaginalis surface proteins using cell shaving proteomics. Frontiers in Microbiology, 9(MAY). https://doi.org/10.3389/fmicb.2018.00975

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