Abstract
Interactions among microbial community members can lead to emergent properties, such as enhanced productivity, stability, and robustness. Iron-oxide mats in acidic (pH 2–4), high-temperature (> 65 °C) springs of Yellowstone National Park 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 goals of the current study were to integrate data collected in situ with in silico calculations across process-scales encompassing enzymatic activity, cellular metabolism, community interactions, and ecosystem biogeochemistry, as well as 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 the studied 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, respectively. In situ geochemical analyses, including oxygen depth-profiles, Fe(III)-oxide deposition rates, stable carbon isotopes and mat biomass concentrations, were combined with cellular models to explore 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 operate at their maximum total community growth rate (i.e. sum of autotroph and heterotroph growth rates), as opposed to net community growth rate (i.e. total community growth rate subtracting autotroph consumed by heterotroph), as predicted from the maximum power principle. Integration of multiscale data with ecological theory provides a basis for predicting autotroph-heterotroph interactions and community-level cellular organization.
Highlights
IntroductionMicroorganisms are the largest component of the biosphere and drive biogeochemical cycles through metabolic activity [1]
The systematic approach used is broadly applicable to any microbial community with modest activity and metagenomic data as well as provides a mechanism to characterize interaction motifs in communities that include uncultivated organisms
Microorganisms are the largest component of the biosphere and drive biogeochemical cycles through metabolic activity [1]
Summary
Microorganisms are the largest component of the biosphere and drive biogeochemical cycles through metabolic activity [1]. Most natural microbial communities have diverse microbial populations and an array of nutrient and energy sources, which often precludes detailed analyses of microbial interactions linked to metabolic activity. The phylogenetic diversity of microorganisms within Fe(III)-oxide microbial mats of acidsulfate-chloride springs in Yellowstone National Park (YNP) is limited due to high temperature (65–75 ̊C) and low pH (~ 3) [5,6,7]. These biomineralizing communities are formed and inhabited by a limited number of distinct phylotypes, including crenarchaea from the order Sulfolobales
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