High-throughput experimental techniques and bioinformatics tools make it
possible to obtain reconstructions of the metabolism of microbial species.
Combined with mathematical frameworks such as flux balance analysis, which
assumes that nutrients are used so as to maximize growth, these reconstructions
enable us to predict microbial growth.
Although such predictions are generally accurate, these approaches do not
give insights on how different nutrients are used to produce growth, and thus
are difficult to generalize to new media or to different organisms.
Here, we propose a systems-level phenomenological model of metabolism
inspired by the virial expansion. Our model predicts biomass production given
the nutrient uptakes and a reduced set of parameters, which can be easily
determined experimentally. To validate our model, we test it against in silico
simulations and experimental measurements of growth, and find good agreement.
From a biological point of view, our model uncovers the impact that individual
nutrients and the synergistic interaction between nutrient pairs have on
growth, and suggests that we can understand the growth maximization principle
as the optimization of nutrient synergies.Comment: 31 pages, 13 figure