Informace o publikaci

Impact of Carbon Felt Electrode Pretreatment on Anodic Biofilm Composition in Microbial Electrolysis Cells

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SPIESS Sabine KUČERA Jiří SEELAJAROEN Hathaichanok SASIAIN Amaia THALLNER Sophie KREMSER Klemens NOVÁK David GUEBITZ Georg M. HABERBAUER Marianne

Rok publikování 2021
Druh Článek v odborném periodiku
Časopis / Zdroj Biosensors
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www https://doi.org/10.3390/bios11060170
Doi http://dx.doi.org/10.3390/bios11060170
Klíčová slova bioelectrochemical system; bioelectrodes; biosensor; electrode pretreatment; metagenomic analysis; microbial communities
Popis Sustainable technologies for energy production and storage are currently in great demand. Bioelectrochemical systems (BESs) offer promising solutions for both. Several attempts have been made to improve carbon felt electrode characteristics with various pretreatments in order to enhance performance. This study was motivated by gaps in current knowledge of the impact of pretreatments on the enrichment and microbial composition of bioelectrochemical systems. Therefore, electrodes were treated with poly(neutral red), chitosan, or isopropanol in a first step and then fixed in microbial electrolysis cells (MECs). Four MECs consisting of organic substance-degrading bioanodes and methane-producing biocathodes were set up and operated in batch mode by controlling the bioanode at 400 mV vs. Ag/AgCl (3M NaCl). After 1 month of operation, Enterococcus species were dominant microorganisms attached to all bioanodes and independent of electrode pretreatment. However, electrode pretreatments led to a decrease in microbial diversity and the enrichment of specific electroactive genera, according to the type of modification used. The MEC containing isopropanol-treated electrodes achieved the highest performance due to presence of both Enterococcus and Geobacter. The obtained results might help to select suitable electrode pretreatments and support growth conditions for desired electroactive microorganisms, whereby performance of BESs and related applications, such as BES-based biosensors, could be enhanced.
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