SEARCH · PubMed Health

Results for “combinatorial PTMs”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

3 recordsLinked to original sources

PubMed2025

ProteoformDB: A Built-In Application to Generate Proteoform Database.

Proteins play essential functions through their complex regulations on cell-type-specific expression, localization, and molecular complexes. Protein complexity is further enhanced by proteoforms, which are the diverse molecular forms that each gene can produce through genomic alterations, transcriptional variations, translational regulations, and protein modifications. Profiling of proteoforms is a promising method for gaining a deeper understanding of the role of proteins in biological pathways and disease mechanisms. Here, we developed ProteoformDB, an application tool for generating proteoform databases, and we cataloged a total of over one million unique single-site human proteoforms. We showed that ProteoformDB can serve as a valuable resource to document the experimentally identified proteoforms in a database, supporting protein characterization in quantitative proteomics for both total protein abundances and modified protein forms.

Humans↗

PubMed2025

Post-translational modifications of the nucleoid protein H-NS: sites, mechanisms, and regulatory cues.

Histone-like nucleoid structuring protein H-NS plays a pivotal role in orchestrating bacterial chromatin and regulating horizontal gene transfer (HGT) elements. In response to environmental signals, H-NS undergoes dynamic post-translational modifications (PTMs) that resemble the epigenetic codes of eukaryotic histones. This review explores how environmental cues regulate PTMs at specific sites within distinct domains of H-NS, thereby modulating its oligomerization and DNA-binding capabilities to reprogram bacterial responses. Notably, HGT elements commonly encode counter-silencing factors, including PTM-modifying enzymes, that counteract H-NS repression. We propose that combinatorial PTM patterns on H-NS form the bacterial histone-like epigenetic code, regulating the expression of HGT elements. Collectively, these interactions establish a sophisticated network of silencing and counter-silencing mechanisms that drive bacterial genome evolution.

Protein Processing, Post-Translational↗

PubMed2026

Metab8D: a metabolic regulome network from multiomics and machine learning.

To explore multiomic regulation of the metabolome, we used machine learning to predict metabolomic variation across ~1000 different cancer cell lines with matched omics data from eight biomolecular classes: genomic copy number variation, mutations, DNA methylation, histone post-translational modifications (PTMs), transcriptomics and RNA splice variants, non-coding transcriptomics (miRNA and lncRNA), proteomics, and phosphoproteomics. Overall, the metabolome is tightly associated with the transcriptome, with coding and non-coding RNAs emerging as top predictors. Peripheral metabolites are predictable via levels of corresponding enzymes, while those in central metabolism require combinatorial predictors in signaling and redox pathways, and may not reflect corresponding pathway expression. We reconstruct multiomic interaction subnetworks for highly predictable metabolites, and YAP1 signaling emerged as a top global predictor across four omic layers. We prioritize predictive multiomic features for single-cell and spatial metabolomics assays. Top predictors were enriched for synthetic-lethal interactions and synergistic combination therapies that target compensatory metabolic modulators.

Machine Learning↗