Staphylococcus aureus is a versatile pathogen and a leading urgent threat to human health. The clinical burden of this organism is predicted to steadily grow worldwide as it becomes resistant to an increasing number of currently available antibiotics. At the same time, development of new effective antibiotics have dropped precipitously in the past decades. The confluence of these two factors is setting the stage for a “post-antibiotic” era where a great portion of S. aureus infection may not be treatable by the existing regimen. In order to stay ahead of this emerging resistance wave, a deeper understanding of the fundamental biology underlying S. aureus resistance and pathogenesis is necessary.

Emerging works have demonstrated that resistance and virulence are deeply linked to other aspects of physiology such as metabolism and stress response by criss crossing gene regulation. However, untangling these complex regulatory systems from bottom up approaches can be challenging. This dissertation focuses on resolving these complexities in transcriptional regulation by applying Independent Component Analysis (ICA) to RNA sequencing data. ICA recovers the underlying signals from regulators that combine together to shape the expression profile of the cell, creating a scalable and operable model of the TRN. We utilized ICA to describe the structure and composition of the TRN in S. aureus USA300 strains. Next, we used the TRN model in conjunction with metabolic models to understand how metabolic and regulatory cross-talks coordinate carbon and nitrogen metabolism to direct protein synthesis. Finally, we modeled TRNs from multiple strains and revealed how gene-regulator interactions have evolved during the emergence of the endemic USA300 strains. Together, this demonstrates the utility of ICA in studying the TRN of S. aureus to rapidly discover its organization and its evolution over time.