Integrated sequence and -omic features reveal novel small proteome of Mycobacterium tuberculosis.

ABSTRACT: Bioinformatic studies on small proteins are under-represented due to difficulties in annotation posed by their small size. However, recent discoveries emphasize the functional significance of small proteins in cellular processes including cell signaling, metabolism, and adaptation to stress. In this study, we utilized a Random Forest classifier trained on sequence features, RNA-Seq, and Ribo-Seq data to uncover small proteins (smORFs) in M. tuberculosis. Independent predictions for the exponential and starvation conditions resulted in 695 potential smORFs. We examined the functional implications of these smORFs using homology searches, LC-MS/MS, and ChIP-seq data, testing their expression in diverse growth conditions, and identifying protein domains. We provide evidence that some of

SUBMITTER: Sinha PR 

PROVIDER: S-EPMC11133741 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature