Coordination of Metabolism Through Metabolite-Protein Interactions

Abstract

The omics revolution has vastly expanded our ability to monitor intracellular molecular events. This technological advance has typically not been matched with conceptual advances in our ability to interpret and understand such data or to systematically generate hypotheses from them. The iterative systems biology cycle of experiment and computational analysis is a great promise, but turns in practise typically only one or twice per project. A particular challenge for all cell types, from bacteria to humans, are the multiple, overlapping regulatory mechanisms that coordinate adaptation to changing environments. Myriads of regulatory interactions have been identified at the level of transcription, translation, post-translational modification and metabolite feedback, but our understanding which of them govern a given adaptation and actually control a given biological function is very limited. For metabolism this function is the flux of small molecules that is coordinated through a variety of overlapping regulation mechanism. Although the specific molecular implementation might differ, the regulatory logic is usually highly similar in different microbes (1). In this lecture I will focus on the key role of metabolite-protein interactions in achieving this coordination in E. coli, both as input into transcriptional regulation and by directly affecting enzyme activity, and outline how we delineate regulation events that actively control the coordination of metabolic fluxes by combining various omics methods with computational analysis (2, 3). Out of the bewildering complexity of possible regulatory interactions, surprisingly few regulation events appear to be required for a given transition, typically involving less than a handful of active regulators. 1. Chubukov, Gerosa, Kochanowski & Sauer. Nat Rev Microbiol 12: 327 (2014) 2. Gerosa, Haverkorn, Christodoulou, Kochanowski, Schmidt, Noor & Sauer. Cell Systems Biology. 1: 270-282 (2015) 3. Link, Fuhrer, Gerosa, Zamboni & Sauer. Nature Methods 12: 1091-1079 (2015).