Understanding an organism's metabolism at a system level requires knowledge of the physicochemical constraints limiting its metabolic capabilities under different growth conditions, and the genetic regulatory mechanisms that ultimately allow it to adapt to a changing environment. In some cases there is an obvious connection between an environmental change and the regulatory mechanisms responding to it, an example being a switch from aerobic to anaerobic growth [1
]. However, there are constraints leading to less obvious metabolic changes, involving a complex global rearrangement of the cell's metabolism. A key aim of systems biology is to uncover the metabolic constraints determining such complex phenotypic changes, which can be understood only when the system is analyzed at a global scale [2
In the absence of cell-scale kinetic models, flux balance analysis (FBA) provides experimentally testable predictions on an organism's metabolic flux state [4
], which are based on conservation principles, particularly mass conservation, and metabolic capacity constraints. The impact of local constraints, such as uptake capacities, have been investigated [4
], and capacity constraints over full metabolic pathways have been considered as well [9
]. Moreover, it has been hypothesized that the high concentration of macromolecules in the cell's cytoplasm imposes a global constraint on the metabolic capacity of an organism [10
]. More recently, we demonstrated that the key quantity is the total intracellular volume available to metabolic enzymes that result in a limited solvent capacity [12
]. The addition of the solvent capacity constraint to a FBA model allowed us to explain, within a metabolic efficiency framework, the hierarchy of substrate consumption of E. coli
cells growing in a mixture of carbon sources [12
]. On the other hand, the pattern of substrate consumption can also be reproduced by superimposing regulatory information obtained e.g., from microarray data [13
]. Taking together, these results indicate that the FBA model together with the solvent capacity constraint can be used to predict the regulatory mechanisms and, equally importantly, to understand their advantage in terms of metabolic efficiency and constraints. It is not clear, however, if the limited capacity constraint play a role at other physiological growth conditions, e.g., when nutrients are scarce.
Here we study the impact of the limited solvent capacity on E. coli cell metabolism at different physiological growth conditions. We demonstrate that this constraint is relevant for fast growing cells, and predict the existence of a metabolic switch between cells growing at low and high nutrient abundance, respectively. We carry out flux measurements of several reactions in the E. coli central metabolism, observing a partial agreement with the model predictions. Moreover, to uncover the regulatory mechanisms that control the changes in flux rates, we perform gene expression and enzyme activity measurements, finding that the switch is controlled predominantly at the enzyme activity level implemented by changes in the activity of a few key enzymes in the E. coli central metabolism. Finally, we discuss the potential relevance of the limited solvent capacity constraint to experimental observations in other organisms.