Genome-Scale Transcriptional Profiling in \u3ci\u3eStaphylococcus aureus\u3c/i\u3e : Bringing Order Out of Chaos

We used the Staphylococcus aureus microarray meta-database (SAMMD) to compare the transcriptional profiles defined by different experiments targeting the same phenomenon in S. aureus. We specifically examined differences associated with the accessory gene regulator (agr), the staphylococcal accessory regulator (sarA), and growth within a biofilm. We found that in all three cases, there was a striking lack of overlap between the transcriptional profiles. For instance, while all experiments focusing on biofilm formation identified hundreds of differentially expressed genes, only one of these was common to all transcriptomes. Several factors could potentially contribute to this variability including the use of different biofilm models, different growth media, different microarray platforms, and, perhaps most importantly, different strains of S. aureus. The last appeared to be particularly important in the case of the agr and sarA transcriptomes. While these results emphasize the need to introduce some degree of standardization into genome-scale, microarray-based transcriptional profiling experiments, they also demonstrate the need to consider multiple strains of S. aureus in order to avoid any strain-specific bias in the interpretation of results. Our comparisons also illustrate how identification of strain-dependent differences using SAMMD can lead to the development of specific hypotheses that can then be experimentally addressed. Based on this, we have added new features to SAMMD that allow for direct comparisons between transcriptional profiling experiments