Literature DB >> 24909302

Identification of Coxiella burnetii surface-exposed and cell envelope associated proteins using a combined bioinformatics plus proteomics strategy.

Gabriela Flores-Ramirez1, Barbora Jankovicova, Zuzana Bilkova, Jan A Miernyk, Ludovit Skultety.   

Abstract

The Gram-negative pathogen Coxiella burnetii is an intracellular bacterium that replicates within the phagolysosomal vacuoles of eukaryotic cells. This pathogen can infect a wide range of hosts, and is the causative agent of Q fever in humans. Surface-exposed and cell envelope associated proteins are thought to be important for both pathogenesis and protective immunity. Herein, we propose a complementary strategy consisting of (i) in silico prediction and (ii) inventory of the proteomic composition using three enrichment approaches coupled with protein identification. The efficiency of classical Triton X-114 phase partitioning was compared with two novel procedures; isolation of alkaline proteins by liquid-phase IEF, and cell surface enzymatic shaving using biofunctional magnetic beads. Of the 2026 protein sequences analyzed using seven distinct bioinformatic algorithms, 157 were predicted to be outer membrane proteins (OMP) and/or lipoproteins (LP). Using the three enrichment protocols, we identified 196 nonredundant proteins, including 39 predicted OMP and/or LP, 32 unknown or poorly characterized proteins, and 17 effectors of the Type IV secretion system. We additionally identified eight proteins with moonlighting activities, and several proteins apparently peripherally associated with integral or anchored OMP and/or LP.
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Bioinformatic predictions; Coxiella burnetii; MS identification; Microbiology; Outer membrane proteins; Surface-exposed and cell envelope associated proteins

Mesh:

Substances:

Year:  2014        PMID: 24909302     DOI: 10.1002/pmic.201300338

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


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