Lan, T. C. T. | bioRxiv Science

bioRxiv2021

Translational activation by an alternative sigma factor in Bacillus subtilis

Sigma factors are an important class of bacterial transcription factors that lend specificity to RNA polymerases by binding to distinct promoter elements for genes in their regulons. Here we show that activation of the general stress sigma factor, {sigma}B, in Bacillus subtilis paradoxically leads to dramatic induction of translation for a subset of its regulon genes. These genes are translationally repressed when transcribed by the housekeeping sigma factor, {sigma}A, owing to extended RNA secondary structures as determined in vivo using DMS-MaPseq. Transcription from {sigma}B-dependent promoters liberates the secondary structures and activates translation, leading to dual induction. Translation efficiencies between {sigma}B- and {sigma}A-dependent RNA isoforms can vary by up to 100-fold, which in multiple cases exceeds the magnitude of transcriptional induction. These results highlight the role of long-range RNA folding in modulating translation and demonstrate that a transcription factor can regulate protein synthesis beyond its effects on transcript levels.

microbiology↗

bioRxiv2020

Structure of the full SARS-CoV-2 RNA genome in infected cells

SARS-CoV-2 is a betacoronavirus with a single-stranded, positive-sense, 30-kilobase RNA genome responsible for the ongoing COVID-19 pandemic. Currently, there are no antiviral drugs with proven efficacy, and development of these treatments are hampered by our limited understanding of the molecular and structural biology of the virus. Like many other RNA viruses, RNA structures in coronaviruses regulate gene expression and are crucial for viral replication. Although genome and transcriptome data were recently reported, there is to date little experimental data on native RNA structures in SARS-CoV-2 and most putative regulatory sequences are functionally uncharacterized. Here we report secondary structure ensembles of the entire SARS-CoV-2 genome in infected cells at single nucleotide resolution using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and the algorithm detection of RNA folding ensembles using expectation-maximization clustering (DREEM). Our results reveal previously undescribed alternative RNA conformations across the genome, including structures of the frameshift stimulating element (FSE), a major drug target, that are drastically different from prevailing in vitro population average models. Importantly, we find that this structural ensemble promotes frameshifting rates (~40%) similar to in vivo ribosome profiling studies and much higher than the canonical minimal FSE (~20%). Overall, our result highlight the value of studying RNA folding in its native, dynamic and cellular context. The genomic structures detailed here lays the groundwork for coronavirus RNA biology and will guide the design of SARS-CoV-2 RNA-based therapeutics.

biochemistry↗