B11J-0568
Metatranscriptome Analysis of Aquifer Samples Reveals Unexpected Metabolic Lifestyles Relevant to Active Biogeochemical Cycling
Abstract:
Modern molecular ecology techniques are revealing the metabolic potential of uncultivated microorganisms, but there is still much to be learned about the actual biogeochemical roles of microbes that have cultivated relatives. Here, we present metatranscriptomic and metagenomic data from a field study that provides evidence of coupled redox processes that have not been documented in cultivated relatives and, indeed, represent strains with metabolic traits that are novel with respect to closely related isolates.The data come from omics analysis of groundwater samples collected during an experiment in which nitrate (a native electron acceptor) was injected into a perennially suboxic aquifer in Rifle (CO). Transcriptional data indicated that just two groups of chemolithoautotrophic bacteria accounted for a very large portion (~80%) of overall community gene expression: (1) members of the Fe(II)-oxidizing Gallionellaceae family and (2) strains of the S-oxidizing species, Sulfurimonas denitrificans. Metabolic lifestyles for Gallionellaceae strains that were novel compared to cultivated representatives included nitrate-dependent Fe(II) oxidation and S oxidation. Evidence for these metabolisms included highly correlated temporal expression in binned data of nitrate reductase (e.g., narGHI) genes (which have never been reported in Gallionellaceae genomes) and Fe(II) oxidation genes (e.g., mtoA) or S oxidation genes (e.g., dsrE, aprA). Of the two most active strains of S. denitrificans, only one showed strong expression of S oxidation genes, whereas the other was apparently using an unexpected (as-yet unidentified) primary electron donor.
Transcriptional data added considerable interpretive value to this study, as (1) metagenomic data would not have highlighted these organisms, which had a disproportionately large role in community metabolism relative to their populations, and (2) co-expression of coupled pathway genes could not be predicted based solely on metagenomic data.