Abstract

In natural environments, cells live in complex communities and experience a high degree of heterogeneity internally and in the environment. Unfortunately, most of the metabolic modeling approaches that are currently used assume ideal conditions and that each cell is identical, limiting their application to pure cultures in well-mixed vessels. Here we describe our development of MultIscale MultiObjective Systems Analysis (MIMOSA), a metabolic modeling approach that can track individual cells in both space and time, track the diffusion of nutrients and light and the interaction of cells with each other and the environment. As a proof-of concept study, we used MIMOSA to model the growth of Trichodesmium erythraeum, a filamentous diazotrophic cyanobacterium which has cells with two distinct metabolic modes. The use of MIMOSA significantly improves our ability to predictively model metabolic changes and phenotype in more complex cell cultures.