TY - JOUR TI - Calibration and analysis of genome-based models for microbial ecology AU - Louca, Stilianos AU - Doebeli, Michael A2 - Shou, Wenying VL - 4 PY - 2015 DA - 2015/10/16 SP - e08208 C1 - eLife 2015;4:e08208 DO - 10.7554/eLife.08208 UR - https://doi.org/10.7554/eLife.08208 AB - Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology. KW - experimental evolution KW - microbial metabolism KW - flux balance analysis KW - model calibration KW - diversity KW - microbial ecology JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -