A systems-level atlas of carbon-response transcriptional states in Escherichia coli - Jongoh Shin; Arjun Patel; Xuwen A. Lou; Edward Alexander Catoiu; Jayanth Krishnan; Ying Hefner; Richard Szubin; Jaemin Sung; Hyeoncheol Francis Son; Daniel C. Zielinski; Bernhard Ørn Palsson (Proceedings of the National Academy of Sciences, 2026)
Escherichia coli encounters chemically diverse carbon sources, and the observed outputs of its transcriptional regulatory network (TRN) vary with substrate chemistry, metabolic entry route, and growth physiology. Here, we compiled PRECISE-NP881, an 881-condition transcriptome compendium comprising 346 RNA-seq profiles generated for this study during growth on 43 individual carbon sources, and used independent component analysis to quantify condition-specific activities of 137 iModulons, defined here as statistically independent gene-expression modules. We identified 25 carbon-catabolism iModulons and summarized their activity patterns across the 43 substrates into four activity-defined substrate groups. These activity patterns were associated with measured growth rates, substrate chemical classes, central-metabolic entry routes, carbon-normalized stoichiometric yield, and model-estimated proteome allocation. Faster-growing sugar conditions showed low CRP-linked iModulon activity, whereas slower-growing conditions showed elevated, condition-specific activity of CRP-linked and substrate-specific catabolic iModulons. TCA-entry and amino acid–associated conditions were linked with NtrC-1 and Propionate iModulon activities, with targeted knock-out assays supporting the conditional physiological relevance of selected propionyl-CoA-associated genes. A subset of nitrogen-containing, slower-growth conditions with predicted ammonium release induced the cryptic prophage-associated SgcABCEQX iModulon. Projection of an independent glucose starvation/refeeding time-course dataset revealed overlapping dynamics among selected carbon-catabolism iModulons and coordinated changes in growth- and stress-associated TRN outputs. Together, these results provide a systems-level atlas of observed carbon-responsive transcriptional states and systematize carbon physiology at scale.