Controlled Measurements of Multiple Cellular Components in E. coli As a Resource for Integrative Computational Modeling of Cellular Subsystems

Genome wide models are a useful tool in synthetic engineering of biology. Most genome-wide models however focus on individual subsystems, or networks, of the cell, such as in flux balance models of metabolism. Recent effort has been focused on how to best integrate models of separate subsystems (e.g. transcription, metabolism, etc.). Thus, there is a need for consistent and comparable measurements of these different cellular components. Though many large data sets exist for specific types of cellular components (e.g. RNA expression, protein abundances, metabolites, etc.) there is a lack of data that span multiple different sub-systems under the same controlled conditions. Here we present genome-wide measurements on RNA and proteins as well as lipids and metabolic fluxes from E. coli grown under identically controlled conditions. These data serve as a resource for building integrative models of cellular processes. Specifically, we present data from a long-term glucose starvation time course. These data comprise the first completed results from a series of planned experiments considering different environmental conditions. We will discuss the general trends seen in this time course as well as compare and contrast our data sets on different sub-processes. Finally, we will present a mechanistic, large-scale, and predictive model of gene regulation connecting protein and RNA expression profiles. This model could be used to quantitatively predict changes in protein expression given differences in genetic background and/or environmental conditions with a minimum of additional information.