Impacts of Small RNAs and Their Chaperones on Bacterial Pathogenicity.
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ABSTRACT:
SUBMITTER: Djapgne L
PROVIDER: S-EPMC8311930 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The genus Herbaspirillum includes several strains isolated from different grasses. The identification of non-coding RNAs (ncRNAs) in the genus Herbaspirillum is an important stage studying the interaction of these molecules and the way they modulate physiological responses of different mechanisms, through RNA⁻RNA interaction or RNA⁻protein interaction. This interaction with their target occurs through the perfect pairing of short sequences (cis-encoded ncRNAs) or by the partial pairing of short sequences (trans-encoded ncRNAs). However, the companion Hfq can stabilize interactions in the trans-acting class. In addition, there are Riboswitches, located at the 5' end of mRNA and less often at the 3' end, which respond to environmental signals, high temperatures, or small binder molecules. Recently, CRISPR (clustered regularly interspaced palindromic repeats), in prokaryotes, have been described that consist of serial repeats of base sequences (spacer DNA) resulting from a previous exposure to exogenous plasmids or bacteriophages. We identified 285 ncRNAs in Herbaspirillum seropedicae (H. seropedicae) SmR1, expressed in different experimental conditions of RNA-seq material, classified as cis-encoded ncRNAs or trans-encoded ncRNAs and detected RNA riboswitch domains and CRISPR sequences. The results provide a better understanding of the participation of this type of RNA in the regulation of the metabolism of bacteria of the genus Herbaspirillum spp.
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Project description:While eukaryotic noncoding RNAs have recently received intense scrutiny, it is becoming clear that bacterial transcription is at least as pervasive. Bacterial small RNAs and antisense RNAs (sRNAs) are often assumed to be noncoding, due to their lack of long open reading frames (ORFs). However, there are numerous examples of sRNAs encoding for small proteins, whether or not they also have a regulatory role at the RNA level.Here, we apply flexible machine learning techniques based on sequence features and comparative genomics to quantify the prevalence of sRNA ORFs under natural selection to maintain protein-coding function in 14 phylogenetically diverse bacteria. Importantly, we quantify uncertainty in our predictions, and follow up on them using mass spectrometry proteomics and comparison to datasets including ribosome profiling.A majority of annotated sRNAs have at least one ORF between 10 and 50 amino acids long, and we conservatively predict that 409±191.7 unannotated sRNA ORFs are under selection to maintain coding (mean estimate and 95% confidence interval), an average of 29 per species considered here. This implies that overall at least 10.3±0.5% of sRNAs have a coding ORF, and in some species around 20% do. 165±69 of these novel coding ORFs have some antisense overlap to annotated ORFs. As experimental validation, many of our predictions are translated in published ribosome profiling data and are identified via mass spectrometry shotgun proteomics. B. subtilis sRNAs with coding ORFs are enriched for high expression in biofilms and confluent growth, and S. pneumoniae sRNAs with coding ORFs are involved in virulence. sRNA coding ORFs are enriched for transmembrane domains and many are predicted novel components of type I toxin/antitoxin systems.We predict over two dozen new protein-coding genes per bacterial species, but crucially also quantified the uncertainty in this estimate. Our predictions for sRNA coding ORFs, along with predicted novel type I toxins and tools for sorting and visualizing genomic context, are freely available in a user-friendly format at http://disco-bac.web.pasteur.fr. We expect these easily-accessible predictions to be a valuable tool for the study not only of bacterial sRNAs and type I toxin-antitoxin systems, but also of bacterial genetics and genomics.
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