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. 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, the coordination of which in metabolic networks may be achieved through a variety of overlapping regulation mechanism. Out of the bewildering complexity of possible regulatory interactions, generally only very few matter for a given organism and condition, and the regulatory logic of this regulation is usually highly similar in different microbes, although the molecular implementation might differ (1). In this lecture I will focus on two aspects. First I will describe our efforts in learning functionality of the protein phosphorylation the yeast Sacharomyces cerevisiae by combining phosphoproteomics and metabolomics (2). In the second part I will focus on how we delineate regulation events that actively control the coordination of metabolic fluxes in the bacterium E. coli by combining various omics methods with computational analysis (3). The surprising result is that only very 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. Oliveira AP, Ludwig C, Zampieri M, Weisser H, Aebersold R & U Sauer. Dynamic phosphoproteomics reveals TORC1-dependent regulation of yeast nucleotide and amino acid biosynthesis. Science Signaling 8(374):rs4 (2015)
3. Gerosa L, Haverkorn van Rijsewijk B, Christodoulou C, Kochanowski K, Schmidt TSB, Noor E & U Sauer. Pseudo-transition analysis identifies active transcriptional and metabolic regulators that govern bacterial nutrient adaptations. Cell Systems Biology. 1: 270-282 (2015)