A previously uncharacterized, nonphotosynthetic member of the Chromatiaceae is the primary CO2-fixing constituent in a self-regenerating biocathode.

Biocathode extracellular electron transfer (EET) may be exploited for biotechnology applications, including microbially mediated O2 reduction in microbial fuel cells and microbial electrosynthesis. However, biocathode mechanistic studies needed to improve or engineer functionality have been limited to a few select species that form sparse, homogeneous biofilms characterized by little or no growth. Attempts to cultivate isolates from biocathode environmental enrichments often fail due to a lack of some advantage provided by life in a consortium, highlighting the need to study and understand biocathode consortia in situ. Here, we present metagenomic and metaproteomic characterization of a previously described biocathode biofilm (+310 mV versus a standard hydrogen electrode [SHE]) enriched from seawater, reducing O2, and presumably fixing CO2 for biomass generation. Metagenomics identified 16 distinct cluster genomes, 15 of which could be assigned at the family or genus level and whose abundance was roughly divided between Alpha- and Gammaproteobacteria. A total of 644 proteins were identified from shotgun metaproteomics and have been deposited in the the ProteomeXchange with identifier PXD001045. Cluster genomes were used to assign the taxonomic identities of 599 proteins, with Marinobacter, Chromatiaceae, and Labrenzia the most represented. RubisCO and phosphoribulokinase, along with 9 other Calvin-Benson-Bassham cycle proteins, were identified from Chromatiaceae. In addition, proteins similar to those predicted for iron oxidation pathways of known iron-oxidizing bacteria were observed for Chromatiaceae. These findings represent the first description of putative EET and CO2 fixation mechanisms for a self-regenerating, self-sustaining multispecies biocathode, providing potential targets for functional engineering, as well as new insights into biocathode EET pathways using proteomics.
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