Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning

Abstract

ABSTRACTThe virulence factors of Staphylococcus aureus are tightly controlled by two-component systems (TCSs) and small RNA (sRNA). TCSs have been well studied over the past several decades, but our understanding of sRNA functions lags far behind that of TCS functions. Here, we studied the biological role of sRNA from 506 S. aureus RNA-seq datasets using independent component analysis (ICA). We found that a previously neglected sRNA, Sau-41, functions in the Agr system. Sau-41 is located within the PSMα operon and controlled by the Agr system. It was predicted to share 22-base complementarity with RNAIII, a major regulator of S. aureus virulence. The EMSA results demonstrated that Sau-41 directly binds to RNAIII. Furthermore, our results found that Sau-41 is capable of repressing S. aureus haemolysin activity by downregulating α-haemolysin and δ-toxin. The repression of α-haemolysin was attributed to the competition between the 5’ UTR of hla and Sau-41 for binding RNAIII. We observed that Sau-41 mitigated S. aureus virulence in an orthopaedic implant infection mouse model and alleviated osteolysis. Together, our results indicate that Sau-41 is a virulence-regulating RNA and suggest that Sau-41 might be involved in a negative feedback mechanism to control the Agr system. This work is a demonstration of using ICA in sRNA identification by mining high-throughput data and could be extended to other organisms as well.

Keywords

• machine learning
• Staphylococcus aureus
• sRNA
• independent component analysis
• RNA-seq