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Volume 145, 2022, 108054

Systems-informed genome mining for electroautotrophic microbial production

Anthony J. Abela,1, Jacob M. Hilzingerb,1, Adam P. Arkinb,c, Douglas S. Clarka,d

Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720, USA.


Electromicrobial production (EMP) systems can store renewable energy and CO2 in many-carbon molecules inaccessible to abiotic electrochemistry. Here, we develop a multiphysics model to investigate the fundamental and practical limits of EMP enabled by direct electron uptake. We also identify potential electroautotrophic organisms and metabolic engineering strategies to enable electroautotrophy in organisms lacking the native capability. Systematic model comparisons of microbial respiration and carbon fixation strategies revealed that, under aerobic conditions, the CO2 fixation rate is limited to < 6 μmol/cm2/hr by O2 mass transport despite efficient electron utilization. In contrast, anaerobic nitrate respiration enables CO2 fixation rates > 50 μmol/cm2/hr for microbes using the reductive tricarboxylic acid cycle. Phylogenetic analysis, validated by recapitulating experimental demonstrations of electroautotrophy, predicted multiple probable electroautotrophic organisms and a significant number of genetically tractable strains that require heterologous expression of < 5 proteins to gain electroautotrophic function. The model and analysis presented here will guide microbial engineering and reactor design for practical EMP systems.

Keywords: Electromicrobial production, Genome mining, Multiphysics modeling, Microbial electrosynthesis, Extracellular electron transfer.

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