Acid mine drainage (AMD), an extreme environment characterized by low pH and high metal concentrations, can support dense acidophilic microbial biofilm communities that rely on chemoautotrophic production based on iron oxidation. Field determined production rates indicate that, despite the extreme conditions, these communities are sufficiently well adapted to their habitats to achieve primary production rates comparable to those of microbial communities occurring in some non-extreme environments. To enable laboratory studies of growth, production and ecology of AMD microbial communities, a culturing system was designed to reproduce natural biofilms, including organisms recalcitrant to cultivation. A comprehensive metabolic labeling-based quantitative proteomic analysis was used to verify that natural and laboratory communities were comparable at the functional level. Results confirmed that the composition and core metabolic activities of laboratory-grown communities were similar to a natural community, including the presence of active, low abundance bacteria and archaea that have not yet been isolated. However, laboratory growth rates were slow compared with natural communities, and this correlated with increased abundance of stress response proteins for the dominant bacteria in laboratory communities. Modification of cultivation conditions reduced the abundance of stress response proteins and increased laboratory community growth rates. The research presented here represents the first description of the application of a metabolic labeling-based quantitative proteomic analysis at the community level and resulted in a model microbial community system ideal for testing physiological and ecological hypotheses.

Proteomes of acid mine drainage biofilms at different stages of ecological succession were examined to understand microbial responses to changing community membership. We evaluated the degree of reproducibility of the community proteomes between samples of the same growth stage and found stable and predictable protein abundance patterns across time and sampling space, allowing for a set of 50 classifier proteins to be identified for use in predicting growth stages of undefined communities. Additionally, physiological changes in the dominant species, Leptospirillum Group II, were analysed as biofilms mature. During early growth stages, this population responds to abiotic stresses related to growth on the acid mine drainage solution. Enzymes involved in protein synthesis, cell division and utilization of 1- and 2-carbon compounds were more abundant in early growth stages, suggesting rapid growth and a reorganization of metabolism during biofilm initiation. As biofilms thicken and diversify, external stresses arise from competition for dwindling resources, which may inhibit cell division of Leptospirillum Group II through the SOS response. This population also represses translation and synthesizes more complex carbohydrates and amino acids in mature biofilms. These findings provide unprecedented insight into the physiological changes that may result from competitive interactions within communities in natural environments.

Extensive genomic characterization of multi-species acid mine drainage microbial consortia combined with laboratory cultivation has enabled the application of quantitative proteomic analyses at the community level. In this study, quantitative proteomic comparisons were used to functionally characterize laboratory-cultivated acidophilic communities sustained in pH 1.45 or 0.85 conditions. The distributions of all proteins identified for individual organisms indicated biases for either high or low pH, and suggests pH-specific niche partitioning for low abundance bacteria and archaea. Although the proteome of the dominant bacterium, Leptospirillum group II, was largely unaffected by pH treatments, analysis of functional categories indicated proteins involved in amino acid and nucleotide metabolism, as well as cell membrane/envelope biogenesis were overrepresented at high pH. Comparison of specific protein abundances indicates higher pH conditions favor Leptospirillum group III, whereas low pH conditions promote the growth of certain archaea. Thus, quantitative proteomic comparisons revealed distinct differences in community composition and metabolic function of individual organisms during different pH treatments. Proteomic analysis revealed other aspects of community function. Different numbers of phage proteins were identified across biological replicates, indicating stochastic spatial heterogeneity of phage outbreaks. Additionally, proteomic data were used to identify a previously unknown genotypic variant of Leptospirillum group II, an indication of selection for a specific Leptospirillum group II population in laboratory communities. Our results confirm the importance of pH and related geochemical factors in fine-tuning acidophilic microbial community structure and function at the species and strain level, and demonstrate the broad utility of proteomics in laboratory community studies.