Operons are transcriptional modules that allow bacteria to adapt to environmental changes by coordinately expressing the relevant set of genes. In humans, biological pathways and their regulation are more complex. If and how human cells coordinate the expression of entire biological processes is unclear. Here, we capture 31 higher-order co-regulation modules, which we term progulons, by help of supervised machine-learning on proteomics data. Progulons consist of dozens to hundreds of proteins that together mediate core cellular functions. They are not restricted to physical interactions or co-localisation. Progulon abundance changes are primarily controlled at the level of protein synthesis and degradation. Implemented as a web app at www.proteomehd.net/progulonFinder, our approach enables the targeted search for progulons of specific cellular processes. We use it to identify a DNA replication progulon and reveal multiple new replication factors, validated by extensive phenotyping of siRNA-induced knockdowns. Progulons provide a new entry point into the molecular understanding of biological processes.
Keywords: DNA replication; mRNA coexpression; machine-learning; protein co-regulation; quantitative proteomics.
© 2023 The Authors. Published under the terms of the CC BY 4.0 license.