A combined approach for comparative exoproteome analysis of Corynebacterium pseudotuberculosis.

BACKGROUND: Bacterial exported proteins represent key components of the host-pathogen interplay. Hence, we sought to implement a combined approach for characterizing the entire exoproteome of the pathogenic bacterium Corynebacterium pseudotuberculosis, the etiological agent of caseous lymphadenitis (CLA) in sheep and goats. RESULTS: An optimized protocol of three-phase partitioning (TPP) was used to obtain the C. pseudotuberculosis exoproteins, and a newly introduced method of data-independent MS acquisition (LC-MSE) was employed for protein identification and label-free quantification. Additionally, the recently developed tool SurfG+ was used for in silico prediction of sub-cellular localization of the identified proteins. In total, 93 different extracellular proteins of C. pseudotuberculosis were identified with high confidence by this strategy; 44 proteins were commonly identified in two different strains, isolated from distinct hosts, then composing a core C. pseudotuberculosis exoproteome. Analysis with the SurfG+ tool showed that more than 75% (70/93) of the identified proteins could be predicted as containing signals for active exportation. Moreover, evidence could be found for probable non-classical export of most of the remaining proteins. CONCLUSIONS: Comparative analyses of the exoproteomes of two C. pseudotuberculosis strains, in addition to comparison with other experimentally determined corynebacterial exoproteomes, were helpful to gain novel insights into the contribution of the exported proteins in the virulence of this bacterium. The results presented here compose the most comprehensive coverage of the exoproteome of a corynebacterial species so far.

Coagulase-Negative Staphylococci Isolated from Human Bloodstream Infections Showed Multidrug Resistance Profile.

Coagulase-negative staphylococci (CNS) are important pathogens causing nosocomial infections worldwide with increasing resistance to antimicrobials. The aim of this study was to characterize resistance aspects of CNS isolated from patients with bloodstream infections acquired in hospitals in Belo Horizonte, MG, Brazil. Staphylococcus strains were characterized using repetitive sequence-based polymerase chain reaction (rep-PCR) fingerprinting with (GTG)5 primer. Phenotypic resistance was analyzed using AST-P5085 card (bioMérieuxVitek®). PCR was used to detect mecA, vanA, blaZ, ermA/B/C, aac-aphD, and SCC-mec. For statistical analyses, we used hierarchical cluster, chi-square test (χ2), and correspondence. Several clusters were formed within the same species using (GTG)5 primer, and strains showed resistance to the following antimicrobials: benzylpenicillin (100%); oxacillin (93.1%); gentamicin (36.3%); ciprofloxacin (63.7%); moxifloxacin (32.7%); norfloxacin (81.0%); erythromycin (86.2%); clindamycin (75.8%); linezolid, teicoplanin and vancomycin (1.7%); tigecycline (0%); fusidic acid (10.35%); rifampicin (13.7%); and trimethoprim/sulfamethoxazole (46.5%). Regarding genotypic analyses, 40%, 0%, 78%, 42%, 100%, 24%, and 30% were positive for mecA, vanA, blaZ, ermA, ermB, ermC, and aac-aphD, respectively. Regarding staphylococcal cassette mec (SCCmec) type, 3.4% presented type I; 5.0% type II; 27.1% type III; 20.3% type IIIA; and 32.2% type IIIB. Six clusters were formed and frequency distributions of resistant strains to oxacillin, gentamicin, ciprofloxacin, moxifloxacin, norfloxacin, erythromycin, clindamycin, linezolid, teicoplanin, vancomycin, fusidic acid, rifampicin, and trimethoprim/sulfamethoxazole, and mecA, blaZ, ermC, aac-aphD, and SCCmec type differed (p < 0.001). In conclusion, the strains investigated in this study were multidrug resistant and carried multiple antibiotic resistance genes.