Full-length RNA profiling of Mycobacterium tuberculosis with SEnd-seq

Mycobacterium tuberculosis (Mtb) is a bacterial pathogen that causes tuberculosis (TB), an infectious disease that inflicts major health and economic costs around the world. Mtb encounters diverse environments during its lifecycle and responds to these changes by reprogramming its transcriptional output. However, the mechanisms and regulation of Mtb transcription remains poorly understood. In this work, we simultaneously determine the 5' and 3' ends of individual RNA molecules in Mtb cells using the SEnd-seq method, which enables us to profile the Mtb transcriptome at high resolution. Unexpectedly, we find that most Mtb transcripts are incomplete, with their 5' ends aligned at transcription start sites and 3' ends located 200-500 nucleotides downstream. Using native elongating transcript sequencing, we show that these short RNAs are mainly associated with paused RNA polymerases (RNAPs) rather than products of premature termination. We further show that the high propensity of Mtb RNAP to pause early in transcription is dependent on the binding of the sigma factor. Finally, we show that a translating ribosome promotes transcription elongation, suggesting a role for transcription-translation coupling in Mtb gene expression. In sum, our findings depict a mycobacterial transcriptome that prominently features incomplete transcripts resulting from RNAP pausing. We propose that the pausing phase constitutes an important transcriptional checkpoint in Mtb that allows the bacterium to adapt to new environments and could be exploited for TB therapeutics. SEnd-seq and NET-SEnd-seq methods were employed to investigate the transcriptome of Mtb cells under different growth conditions. These included wild-type cells in both log and stationary phases, Mtb cells after Rho knockdown, and cells subjected to treatments with linezolid, rifampicin, streptomycin, and clarithromycin separately at different time points. Additionally, the genomic occupancy of RpoB and SigA in Mtb was further profiled using ChIP-seq.