Global gene expression analysis using NGS technology (RNA-seq) offers a powerful approach to study the large-scale structure of transcription and transcriptional regulation. This approach has been employed successfully to identify and characterize genetic networks regulating gene expression in many different model systems. Work that has been done in bacteria has focused primarily on chromosomal gene expression, and this work has generated rich data on operon and other genetic regulatory structures at the whole-genome level that have substantially enhanced understanding of bacterial gene expression. In these experiments, we are employing both short read and long-read NGS technologies to study the organization of transcription in multi-drug resistant clinical bacterial isolates. We are additionally investigating substrate-induced transcription, which may lend clues to the function of uncharacterized proteins that constitute a significant proportion of coding sequencing of some resistance plasmids. Strand-specific methods will be employed to distinguish antisense from overlapping sense expression, and regulatory antisense RNA expression will be studied with this technique. Work done during the current fiscal year developed and optimized SOPs for RNA extraction, rRNA depletion, and strand-specific library preparation from selected isolates. Additionally, computational approaches to data analysis were developed and optimized. Initial experiments have demonstrated that robust and reproducible rRNA-depleted strand-specific transcriptional maps can be obtained from chromosomes and plasmids of clinical isolates. In the next fiscal year, these studies will be expanded to a larger set of clinical isolates.
