Transcriptional Profiling and Co-expression Integration for the Filtering of Relevant Bacterial sRNA–mRNA Interactions: Application to Staphylococcus aureus Biofilm

Abstract Small regulatory RNAs (sRNAs) are fast-acting non-coding RNAs (ncRNAs), stress-responsive regulators that fine-tune bacterial gene expression, shaping virulence, antimicrobial resistance, metabolism, and biofilm development. At the post-transcriptional level, sRNAs pair with target mRNAs to block or enhance translation, remodel secondary structures, adjust transcript stability, and act as molecular sponges for other sRNAs. Staphylococcus aureus , a leading cause of hospital-acquired infections, relies on a multiple-layered regulatory network, including post-transcriptional mechanisms, to transition between planktonic and biofilm lifestyles. Here, we expand the cross-lineage sRNA repertoire of S. aureus by integrating newly generated RNA-seq data from the Brazilian ST239 strain Bmb9393 with public datasets from five USA-lineage strains previously uncharacterized for sRNAs. Using sequence homology and covariance models, we predicted and annotated candidate sRNA loci across all analyzed genomes, quantified their expression under planktonic and biofilm conditions, and assigned genomic context. Integration of differential-expression (DE) profiles with weighted gene co-expression network analysis (WGCNA) identified sRNAs associated with biofilm and virulence, in modules that include well-known regulators ( sarA, mgrA , RNAIII) and the adhesin clfA . To prioritize functional target interactions, we combined DEG concordance, network features, and interaction-energy thresholds, depleting millions of initial predictions to thousands of high-confidence sRNA–mRNA pairs. Our integrative bioinformatics framework provides additional insights into sRNA-mediated regulation in S. aureus , highlighting biofilm- and resistance-linked candidates, and yields a ranked, reusable set of sRNA–mRNA interactions to guide hypothesis-driven experiments across diverse genetic backgrounds.