RESUMEN
We developed an approach for identifying groups or families of Staphylococcus aureus bacteria based on genotype data. With the emergence of drug resistant strains, S. aureus represents a significant human health threat. Identifying the family types efficiently and quickly is crucial in community settings. Here, we develop a hybrid sequence algorithm approach to type this bacterium using only its spa gene. Two of the sequence algorithms we used are well established, while the third, the Best Common Gap-Weighted Sequence (BCGS), is novel. We combined the sequence algorithms with a weighted match/mismatch algorithm for the spa sequence ends. Normalized similarity scores and distances between the sequences were derived and used within unsupervised clustering methods. The resulting spa groupings correlated strongly with the groups defined by the well-established Multi locus sequence typing (MLST) method. Spa typing is preferable to MLST typing which types seven genes instead of just one. Furthermore, our spa clustering methods can be fine-tuned to be more discriminative than MLST, identifying new strains that the MLST method may not. Finally, we performed a multidimensional scaling of our distance matrices to visualize the relationship between isolates. The proposed methodology provides a promising new approach to molecular epidemiology.
Asunto(s)
Técnicas de Tipificación Bacteriana , Biología Computacional/métodos , Perfilación de la Expresión Génica , Regulación Bacteriana de la Expresión Génica , Staphylococcus aureus/genética , Algoritmos , Análisis por Conglomerados , Genotipo , Modelos Genéticos , Modelos Estadísticos , Modelos Teóricos , Epidemiología Molecular/métodos , Análisis de Secuencia por Matrices de Oligonucleótidos , Mapeo de Interacción de Proteínas , Reproducibilidad de los Resultados , Programas InformáticosRESUMEN
Drug resistance, particularly vancomycin and methicillin resistance, in Staphylococcus aureus continues to emerge as a significant public health threat in both the hospital and community settings. In addition to the limited treatment options, S. aureus strains acquire and express numerous virulence factors that continue to increase its ability to cause a wide spectrum of human disease. As a result, empirical treatment decisions are confounded and there is a heightened need for a diagnostic test (or assay) to rapidly identify antibiotic resistance and specific virulence determinants and indicate the appropriate treatment. To that end we developed a platform using multiplex molecular beacon probes with real-time PCR for the rapid detection of drug resistance-determining genes and virulence factors in S. aureus. In this study, we demonstrate the specificity and sensitivity of our platform for detection of the genes conferring methicillin (mecA) and vancomycin (vanA) resistance as well as a gene encoding the virulence factor Panton-Valentine leucocidin (lukF) in S. aureus isolates.