(337an) Stress Responsive Small Non-Coding RNA Networks in Mycobacteria revealed By Coupled Experimental and Bioinformatic Approach | AIChE

(337an) Stress Responsive Small Non-Coding RNA Networks in Mycobacteria revealed By Coupled Experimental and Bioinformatic Approach

Authors 

Contreras, L., The University of Texas at Austin
Research Interests: structure and function of proteins and RNAs, computationally aided high-throughput experiments, bioinformatics, drug discovery. Prior Work - drug delivery, spray drying, particle engineering, process optimization via first-principles modeling, amorphous solid dispersion and tablet formulation

Antibiotic resistance is an increasing world health concern, with numerous bacterial pathogens rising in infection occurrences. With advances in next-generation sequencing, expression of non-coding RNAs in diseases and pathogens have elucidated interest as potential biomarkers and therapeutic targets. In bacteria, one type of non-coding RNA, small RNAs (sRNAs), have gained notoriety for their rapid and powerful post-transcriptional regulation. sRNAs are often produced in response to environmental stresses, including those experienced by pathogens during infection. They regulate the stability and translation of mRNAs, some of which encode for essential proteins for pathogenesis. However, the native transcriptional regulation of sRNAs remains under-characterized due, in part, to the diversity of conditions that activate sRNA expression. The complex transcription of sRNAs suggests tight coordination of many cooperative and competitive DNA-binding proteins near the sRNA promoters.

Recently, a technique called IPOD-HR, or in vivo protein occupancy display—high resolution, has allowed for the isolation of all DNA regions bound by proteins at a given time, agnostic to the identity of each protein that might be involved in transcriptional regulation.1 IPOD-HR has been benchmarked in E. coli to efficiently capture known transcription factor networks.1 When coupled with datamined and concurrent RNA-seq bioinformatics, we have expanded the utility to high-throughput prediction of transcription factors regulating sRNA expression2. Since the proof-of-concept study, we have collected new datasets in E. coli, under different nutritional conditions, and have biochemically validated numerous novel transcription factors predicted to bind in sRNA promoters. Notably, most of these sRNA promoters have numerous protein occupancy regions throughout growth, supporting the hypothesis of coordinated DNA-binding proteins controlling their complex induction.

The most recent avenue of our work is expanding the IPOD-HR supported experimental and bioinformatic approach to uncover larger networks of sRNAs in relation to pathogenesis. Namely, we have extended these approaches to the pathogenic family, Mycobacteria. Mycobacteria tuberculosis is the causative agent for tuberculosis and has been showing concerning levels of antibiotic resistance worldwide in part due to its ability to survive macrophages and live dormant in the host for long periods of time. Using its close relative and vaccine strain, M. bovis BCG, we have applied our coupled approach to understand the global roles of sRNAs in these host-imparted conditions, starting with oxidative and iron-starvation stresses. Overall, these high-throughput approaches have uncovered regulatory networks of sRNAs in response to these stresses, including those relevant to mycobacterial pathogenesis.

1 Freddolino PL, Amemiya HM, Goss TJ, Tavazoie S (2021) PLOS Biol 19(6):e3001306.

2 Mihailovic MK, Ekdahl AM et al. (2021) Front Cell Infect Microbiol 11:696533.