AGR system characterization and determination of clonal profile by PFGE and MLST in MRSA isolated of patients from a teaching hospital

• Grant number: 14/26687-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): March 01, 2015
• Effective date (End): February 29, 2016
• Field of knowledge: Biological Sciences - Microbiology - Biology and Physiology of Microorganisms
• Principal Investigator: Maria de Lourdes Ribeiro de Souza da Cunha
• Grantee: Wivian Caroline Ramos
• Host Institution: Instituto de Biociências (IBB). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil

Abstract

Staphylococcus aureus is one of the most isolated pathogens in infections in the hospital setting and is a major problem for public health systems because of the ease of acquiring resistance to antimicrobial agents conventionally used. Recent studies point to increased incidence of infections caused by S. aureus and this is accompanied to wide spread of microorganism methicillin-resistant from hospital environments (Methicillin-Resistant Staphylococcus aureus - MRSA). MRSA is responsible for a variety of infections, reaching from the surface to the deepest tissues where they penetrate through the breaking of the natural barriers being associated with skin diseases, soft tissues, and severe infections such as sepsis, which can be fatal. Genotyping of isolates to the level of strains is increasingly important in order to ascertain whether the bodies involved in nosocomial outbreaks or cross-transmission events have possible clonal relationship. This project aims to determine the prevalence of S. aureus and MRSA in blood cultures collected from patients admitted in the Hospital das Clinicas (HC), Botucatu Medical School (FMB) to determine the virulence and antimicrobial resistance profile of these strains, as well as research prevalent clones in the hospital to be held it to clonal characterization by Pulsed - Field Gel Electrophoresis (PFGE) and Multilocus Sequence Typing (MLST) for recognition prevalent clusters in different units of the HC of FMB.