Unveiling the bioelectrocatalyzing behaviors and microbial ecological mechanisms behind caproate production without exogenous electron donor.

Environ Res

College of Environmental Science and Engineering, Taiyuan University of Technology, Taiyuan, China; Shanxi Engineer Research Institute of Sludge Disposition and Resources, Taiyuan University of Technology, Taiyuan, China. Electronic address:

Published: December 2022


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Article Abstract

Bioelectrochemical systems were proposed as a promising approach for the efficient valorization of biomass into 6-8 carbon atom medium-chain fatty acids (MCFAs), the precursors for high value-added chemicals or renewable energy, via acetyl-CoA-mediated chain elongation (CE). To achieve CE processes, exogenous electron donors (EDs), e.g., ethanol or lactic acid, were normally prerequisites. This research built a microbial electrolysis cell (MEC) for MCFAs biosynthesis from acetate without exogenous EDs addition. A wide range of applied voltages (0.6-1.2 V) was first employed to investigate the bioelectrocatalyzing response. The results show that caproate and butyrate were the main products formed from acetate under different applied voltages. Maximum caproate concentration (501 ± 12 mg COD/L) was reached at 0.8 V on day 3. Under this applied voltage, hydrogen partial pressure stabilized at about 0.1 bar, beneficial for MCFA production. Electron and carbon balances revealed that the electron-accepting capacity achieved 32% at 0.8 V, showing the highest interspecies electron transfer efficiency. Most of the carbon was recovered in the form of caproate (carbon loss was 9%). MiSeq sequencing revealed Rhodobacter and Clostridium_sensu_stricto playing the crucial role in the biosynthesis of caproate, while Acetobacterium, Acetoanaerobium, and Acetobacter represented the main ED contributors. Four available flora, i.e., homo-acetogen, anaerobic fermentation bacteria, electrode active bacteria, and nitrate-reducing bacteria, interacted and promoted caproate synthesis by molecular ecological network analysis.

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http://dx.doi.org/10.1016/j.envres.2022.114077DOI Listing

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