(193aa) Multiscale Analysis of Autotroph-Heterotroph Interactions in a High-Temperature Microbial Community | AIChE

(193aa) Multiscale Analysis of Autotroph-Heterotroph Interactions in a High-Temperature Microbial Community


Hunt, K. A. - Presenter, Montana State University
Carlson, R. P., Montana State University
Microorganisms constitute a major portion of the biosphere, and drive planetary biogeochemical cycles through their metabolic activity. Iron-oxide mats in acidic (pH 2 – 4), high-temperature (> 65 oC) springs of Yellowstone National Park (YNP) contain relatively simple microbial communities and are well-characterized geochemically. Consequently, these communities are excellent model systems for studying the metabolic activity of individual populations and key microbial interactions. The primary goal of the current study was to integrate in situ and in silico data across biological process-scales encompassing enzymatic activity, cellular metabolism, community interactions, and ecosystem geochemistry to predict and quantify the functional limits of autotroph-heterotroph interactions. Metagenomic and transcriptomic data were used to reconstruct carbon and energy metabolisms of an important autotroph (Metallosphaera yellowstonensis) and heterotroph (Geoarchaeum sp. OSPB) from Fe(III)-oxide mat communities. Standard and hybrid elementary flux mode and flux balance analyses of metabolic models predicted cellular- and community-level metabolic acclimations to simulated environmental stresses. In situ geochemical analyses, including oxygen depth-profiles, Fe(III)-oxide deposition rates, stable carbon isotope fractionation and mat biomass concentrations, were combined with cellular models to interpret autotroph-heterotroph interactions important to community structure-function. Integration of metabolic modeling with in situ measurements, including the relative population abundance of autotrophs to heterotrophs, demonstrated that Fe(III)-oxide mat communities maximize total community growth rate as predicted from the maximum power principle. Integration of multiscale data with practical ecological theory provide a basis for predicting autotroph-heterotroph interactions and community-level cellular organization.