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1. Deciphering transcript architectural complexity in bacteria and archaea

   https://doi.org/10.1128/mbio.02359-24  

   Mattick, John_S A; Bromley, Robin E; Watson, Kaylee J; Adkins, Ricky S; Holt, Christopher I; Lebov, Jarrett F; Sparklin, Benjamin C; Tyson, Tyonna S; Rasko, David A; Dunning_Hotopp, Julie C (October 2024, mBio)

   Parkhill, Julian (Ed.)

   ABSTRACT RNA transcripts are potential therapeutic targets, yet bacterial transcripts have uncharacterized biodiversity. We developed an algorithm for transcript prediction called tp.py using it to predict transcripts (mRNA and other RNAs) inEscherichia coliK12 and E2348/69 strains (Bacteria:gamma-Proteobacteria),Listeria monocytogenesstrains Scott A and RO15 (Bacteria:Firmicute),Pseudomonas aeruginosastrains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), andHaloferax volcanii(Archaea:Halobacteria). From >5 millionE. coliK12 and >3 millionE. coliE2348/69 newly generated Oxford Nanopore Technologies direct RNA sequencing reads, 2,487 K12 mRNAs and 1,844 E2348/69 mRNAs were predicted, with the K12 mRNAs containing more than half of the predictedE. coliK12 proteins. While the number of predicted transcripts varied by strain based on the amount of sequence data used, across all strains examined, the predicted average size of the mRNAs was 1.6–1.7 kbp, while the median size of the 5′- and 3′-untranslated regions (UTRs) were 30–90 bp. Given the lack of bacterial and archaeal transcript annotation, most predictions were of novel transcripts, but we also predicted many previously characterized mRNAs and ncRNAs, including post-transcriptionally generated transcripts and small RNAs associated with pathogenesis in theE. coliE2348/69LEEpathogenicity islands. We predicted small transcripts in the 100–200 bp range as well as >10 kbp transcripts for all strains, with the longest transcript for two of the seven strains being thenuooperon transcript, and for another two strains it was a phage/prophage transcript. This quick, easy, and reproducible method will facilitate the presentation of transcripts, and UTR predictions alongside coding sequences and protein predictions in bacterial genome annotation as important resources for the research community.IMPORTANCEOur understanding of bacterial and archaeal genes and genomes is largely focused on proteins since there have only been limited efforts to describe bacterial/archaeal RNA diversity. This contrasts with studies on the human genome, where transcripts were sequenced prior to the release of the human genome over two decades ago. We developed software for the quick, easy, and reproducible prediction of bacterial and archaeal transcripts from Oxford Nanopore Technologies direct RNA sequencing data. These predictions are urgently needed for more accurate studies examining bacterial/archaeal gene regulation, including regulation of virulence factors, and for the development of novel RNA-based therapeutics and diagnostics to combat bacterial pathogens, like those with extreme antimicrobial resistance. 

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2. The Impact of Leadered and Leaderless Gene Structures on Translation Efficiency, Transcript Stability, and Predicted Transcription Rates in Mycobacterium smegmatis

   https://doi.org/10.1128/JB.00746-19  

   Nguyen, Tien G.; Vargas-Blanco, Diego A.; Roberts, Louis A.; Shell, Scarlet S. (April 2020, Journal of Bacteriology)

   Henkin, Tina M. (Ed.)

   ABSTRACT Regulation of gene expression is critical for Mycobacterium tuberculosis to tolerate stressors encountered during infection and for nonpathogenic mycobacteria such as Mycobacterium smegmatis to survive environmental stressors. Unlike better-studied models, mycobacteria express ∼14% of their genes as leaderless transcripts. However, the impacts of leaderless transcript structures on mRNA half-life and translation efficiency in mycobacteria have not been directly tested. For leadered transcripts, the contributions of 5′ untranslated regions (UTRs) to mRNA half-life and translation efficiency are similarly unknown. In M. tuberculosis and M. smegmatis , the essential sigma factor, SigA, is encoded by a transcript with a relatively short half-life. We hypothesized that the long 5′ UTR of sigA causes this instability. To test this, we constructed fluorescence reporters and measured protein abundance, mRNA abundance, and mRNA half-life and calculated relative transcript production rates. The sigA 5′ UTR conferred an increased transcript production rate, shorter mRNA half-life, and decreased apparent translation rate compared to a synthetic 5′ UTR commonly used in mycobacterial expression plasmids. Leaderless transcripts appeared to be translated with similar efficiency as those with the sigA 5′ UTR but had lower predicted transcript production rates. A global comparison of M. tuberculosis mRNA and protein abundances failed to reveal systematic differences in protein/mRNA ratios for leadered and leaderless transcripts, suggesting that variability in translation efficiency is largely driven by factors other than leader status. Our data are also discussed in light of an alternative model that leads to different conclusions and suggests leaderless transcripts may indeed be translated less efficiently. IMPORTANCE Tuberculosis, caused by Mycobacterium tuberculosis , is a major public health problem killing 1.5 million people globally each year. During infection, M. tuberculosis must alter its gene expression patterns to adapt to the stress conditions it encounters. Understanding how M. tuberculosis regulates gene expression may provide clues for ways to interfere with the bacterium’s survival. Gene expression encompasses transcription, mRNA degradation, and translation. Here, we used Mycobacterium smegmatis as a model organism to study how 5′ untranslated regions affect these three facets of gene expression in multiple ways. We furthermore provide insight into the expression of leaderless mRNAs, which lack 5′ untranslated regions and are unusually prevalent in mycobacteria. 

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3. APA-Scan: detection and visualization of 3′-UTR alternative polyadenylation with RNA-seq and 3′-end-seq data

   https://doi.org/10.1186/s12859-022-04939-w  

   Fahmi, Naima Ahmed; Ahmed, Khandakar Tanvir; Chang, Jae-Woong; Nassereddeen, Heba; Fan, Deliang; Yong, Jeongsik; Zhang, Wei (September 2022, BMC Bioinformatics)

   Abstract BackgroundThe eukaryotic genome is capable of producing multiple isoforms from a gene by alternative polyadenylation (APA) during pre-mRNA processing. APA in the 3′-untranslated region (3′-UTR) of mRNA produces transcripts with shorter or longer 3′-UTR. Often, 3′-UTR serves as a binding platform for microRNAs and RNA-binding proteins, which affect the fate of the mRNA transcript. Thus, 3′-UTR APA is known to modulate translation and provides a mean to regulate gene expression at the post-transcriptional level. Current bioinformatics pipelines have limited capability in profiling 3′-UTR APA events due to incomplete annotations and a low-resolution analyzing power: widely available bioinformatics pipelines do not reference actionable polyadenylation (cleavage) sites but simulate 3′-UTR APA only using RNA-seq read coverage, causing false positive identifications. To overcome these limitations, we developed APA-Scan, a robust program that identifies 3′-UTR APA events and visualizes the RNA-seq short-read coverage with gene annotations. MethodsAPA-Scan utilizes either predicted or experimentally validated actionable polyadenylation signals as a reference for polyadenylation sites and calculates the quantity of long and short 3′-UTR transcripts in the RNA-seq data. APA-Scan works in three major steps: (i) calculate the read coverage of the 3′-UTR regions of genes; (ii) identify the potential APA sites and evaluate the significance of the events among two biological conditions; (iii) graphical representation of user specific event with 3′-UTR annotation and read coverage on the 3′-UTR regions. APA-Scan is implemented in Python3. Source code and a comprehensive user’s manual are freely available athttps://github.com/compbiolabucf/APA-Scan. ResultAPA-Scan was applied to both simulated and real RNA-seq datasets and compared with two widely used baselines DaPars and APAtrap. In simulation APA-Scan significantly improved the accuracy of 3′-UTR APA identification compared to the other baselines. The performance of APA-Scan was also validated by 3′-end-seq data and qPCR on mouse embryonic fibroblast cells. The experiments confirm that APA-Scan can detect unannotated 3′-UTR APA events and improve genome annotation. ConclusionAPA-Scan is a comprehensive computational pipeline to detect transcriptome-wide 3′-UTR APA events. The pipeline integrates both RNA-seq and 3′-end-seq data information and can efficiently identify the significant events with a high-resolution short reads coverage plots. 

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4. APA-Scan: Detection and Visualization of 3’-UTR APA with RNA-seq and 3’-end-seq Data

   https://doi.org/10.1101/2020.02.16.951657  

   Fahmi, Naima Ahmed; Chang, Jae-Woong; Nassereddeen, Heba; Ahmed, Khandakar Tanvir; Fan, Deliang; Yong, Jeongsik; Zhang, Wei (January 2020, BioRxiv)

   The eukaryotic genome is capable of producing multiple isoforms from a gene by alternative polyadenylation (APA) during pre-mRNA processing. APA in the 3’-untranslated region (3’-UTR) of mRNA produces transcripts with shorter 3’-UTR. Often, 3’-UTR serves as a binding platform for microRNAs and RNA-binding proteins, which affect the fate of the mRNA transcript. Thus, 3’-UTR APA provides a means to regulate gene expression at the post-transcriptional level and is known to promote translation. Current bioinformatics pipelines have limited capability in profiling 3’-UTR APA events due to incomplete annotations and a low-resolution analyzing power: widely available bioinformatics pipelines do not reference actionable polyadenylation (cleavage) sites but simulate 3’-UTR APA only using RNA-seq read coverage, causing false positive identifications. To overcome these limitations, we developed APA-Scan, a robust program that identifies 3’-UTR APA events and visualizes the RNA-seq short-read coverage with gene annotations. APA-Scan utilizes either predicted or experimentally validated actionable polyadenylation signals as a reference for polyadenylation sites and calculates the quantity of long and short 3’-UTR transcripts in the RNA-seq data. The performance of APA-Scan was validated by qPCR. 

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5. Small RNAs positively and negatively control transcription elongation through modulation of Rho utilization site accessibility

   https://doi.org/10.1101/2024.02.02.578684  

   Farley, Kristen R; Buechler, Andrew K; Bianco, Colleen M; Vanderpool, Carin K (February 2024, bioRxiv)

   Abstract Bacteria use a multi-layered regulatory strategy to precisely and rapidly tune gene expression in response to environmental cues. Small RNAs (sRNAs) form an important layer of gene expression control and most act post-transcriptionally to control translation and stability of mRNAs. We have shown that at least five different sRNAs inEscherichia coliregulate the cyclopropane fatty acid synthase (cfa) mRNA. These sRNAs bind at different sites in the long 5’ untranslated region (UTR) ofcfamRNA and previous work suggested that they modulate RNase E-dependent mRNA turnover. Recently, thecfa5’ UTR was identified as a site of Rho-dependent transcription termination, leading us to hypothesize that the sRNAs might also regulatecfatranscription elongation. In this study we find that a pyrimidine-rich region flanked by sRNA binding sites in thecfa5’ UTR is required for premature Rho-dependent termination. We discovered that both the activating sRNA RydC and repressing sRNA CpxQ regulatecfaprimarily by modulating Rho-dependent termination ofcfatranscription, with only a minor effect on RNase E-mediated turnover ofcfamRNA. A stem-loop structure in thecfa5’ UTR sequesters the pyrimidine-rich region required for Rho-dependent termination. CpxQ binding to the 5’ portion of the stem increases Rho-dependent termination whereas RydC binding downstream of the stem decreases termination. These results reveal the versatile mechanisms sRNAs use to regulate target gene expression at transcriptional and post-transcriptional levels and demonstrate that regulation by sRNAs in long UTRs can involve modulation of transcription elongation. ImportanceBacteria respond to stress by rapidly regulating gene expression. Regulation can occur through control of messenger RNA (mRNA) production (transcription elongation), stability of mRNAs, or translation of mRNAs. Bacteria can use small RNAs (sRNAs) to regulate gene expression at each of these steps, but we often do not understand how this works at a molecular level. In this study, we find that sRNAs inEscherichia coliregulate gene expression at the level of transcription elongation by promoting or inhibiting transcription termination by a protein called Rho. These results help us understand new molecular mechanisms of gene expression regulation in bacteria. 

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