OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models

Rapid Methane Oxidation in a Landfill Cover Soil

Methane oxidation rates observed in a topsoil covering a retired landfill are the highest reported (45 g m(−2) day(−1)) for any environment. This microbial community had the capacity to rapidly oxidize CH(4) at concentrations ranging from <1 ppm (microliters per liter) (first-order rate constant [k] = −0.54 h(−1)) to >10(4) ppm (k = −2.37 h(−1)). The physiological characteristics of a methanotroph isolated from the soil (characteristics determined in aqueous medium) and the natural population, however, were similar to those of other natural populations and cultures: the Q(10) and optimum temperature were 1.9 and 31°C, respectively, the apparent half-saturation constant was 2.5 to 9.3 μM, and 19 to 69% of oxidized CH(4) was assimilated into biomass. The CH(4) oxidation rate of this soil under waterlogged (41% [wt/vol] H(2)O) conditions, 6.1 mg liter(−1) day(−1), was near rates reported for lake sediment and much lower than the rate of 116 mg liter(−1) day(−1) in the same soil under moist (11% H(2)O) conditions. Since there are no large physiological differences between this microbial community and other CH(4) oxidizers, we attribute the high CH(4) oxidation rate in moist soil to enhanced CH(4) transport to the microorganisms; gas-phase molecular diffusion is 10(4)-fold faster than aqueous diffusion. These high CH(4) oxidation rates in moist soil have implications that are important in global climate change. Soil CH(4) oxidation could become a negative feedback to atmospheric CH(4) increases (and warming) in areas that are presently waterlogged but are projected to undergo a reduction in summer soil moisture