Diverse intrinsic properties shape transcript stability and stabilization in Mycolicibacterium smegmatis .

Autor:	Sun H; Program in Bioinformatics and Computational Biology, Worcester Polytechnic Institute, Worcester, MA 01609, USA., Vargas-Blanco DA; Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA 01609, USA., Zhou Y; Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA 01609, USA., Masiello CS; Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA 01609, USA., Kelly JM; Program in Bioinformatics and Computational Biology, Worcester Polytechnic Institute, Worcester, MA 01609, USA.; Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA 01609, USA., Moy JK; Program in Bioinformatics and Computational Biology, Worcester Polytechnic Institute, Worcester, MA 01609, USA., Korkin D; Program in Bioinformatics and Computational Biology, Worcester Polytechnic Institute, Worcester, MA 01609, USA., Shell SS; Program in Bioinformatics and Computational Biology, Worcester Polytechnic Institute, Worcester, MA 01609, USA.; Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Jazyk:	angličtina
Zdroj:	NAR genomics and bioinformatics [NAR Genom Bioinform] 2024 Nov 04; Vol. 6 (4), pp. lqae147. Date of Electronic Publication: 2024 Nov 04 (Print Publication: 2024).
DOI:	10.1093/nargab/lqae147
Abstrakt:	Mycobacteria regulate transcript degradation to facilitate adaptation to environmental stress. However, the mechanisms underlying this regulation are unknown. Here we sought to gain understanding of the mechanisms controlling mRNA stability by investigating the transcript properties associated with variance in transcript stability and stress-induced transcript stabilization. We measured mRNA half-lives transcriptome-wide in Mycolicibacterium smegmatis in log phase growth and hypoxia-induced growth arrest. The transcriptome was globally stabilized in response to hypoxia, but transcripts of essential genes were generally stabilized more than those of non-essential genes. We then developed machine learning models that enabled us to identify the non-linear collective effect of a compendium of transcript properties on transcript stability and stabilization. We identified properties that were more predictive of half-life in log phase as well as properties that were more predictive in hypoxia, and many of these varied between leadered and leaderless transcripts. In summary, we found that transcript properties are differentially associated with transcript stability depending on both the transcript type and the growth condition. Our results reveal the complex interplay between transcript features and microenvironment that shapes transcript stability in mycobacteria. (© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)
Databáze:	MEDLINE
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