| Literature DB >> 34073192 |
Sabine Spiess1,2, Jiri Kucera3, Hathaichanok Seelajaroen4, Amaia Sasiain1, Sophie Thallner1,2, Klemens Kremser5, David Novak3, Georg M Guebitz2,5, Marianne Haberbauer1,2.
Abstract
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.Entities:
Keywords: bioelectrochemical system; bioelectrodes; biosensor; electrode pretreatment; metagenomic analysis; microbial communities
Mesh:
Substances:
Year: 2021 PMID: 34073192 PMCID: PMC8229196 DOI: 10.3390/bios11060170
Source DB: PubMed Journal: Biosensors (Basel) ISSN: 2079-6374
Figure 1Microbial electrolysis cell (MEC) with an organic substance-oxidizing bioanode combined with a methane-producing biocathode.
Comparison of following monitored parameters in MEC1–4: COD removal rate, COD removal efficiency, CE anode, Q rate, CH4 production rate, and CE cathode.
| Cell Name | COD Removal Rate | COD Removal Efficiency | CE Anode [%] | Q Rate | CH4 Production Rate | CE Cathode [%] | Ref. |
|---|---|---|---|---|---|---|---|
| MEC1 | 40 | 25 | 64 | 60 | 0.11 | 39 | [ |
| MEC2 | 55 | 52 | 75 | 110 | 0.41 | 66 | [ |
| MEC3 | 65 | 56 | 76 | 130 | 0.41 | 57 | [ |
| MEC4 | 69 | 76 | 75 | 137 | 0.44 | 58 | This work |
Figure 2Effect of different electrode pretreatments on the enriched microbial communities of anode biofilm in MECs. Poly(neutral red) (MEC2), chitosan (MEC3), and isopropanol (MEC4) were used for the carbon felt electrode pretreatments, but the control electrode (MEC1) was not pretreated. Taxonomic profiles were set at the class (A), family (B), and genus (C) levels. Only representatives with a relative abundance >5% in at least one condition are shown. Detailed data are shown in Supplementary Table S3. Alpha diversity was estimated using the following indices: Chao1, Shannon, and Inverse Simpson.
Figure 3Phylogenetic tree, showing genetic relationships of sewage sludge community used for inoculation of all MECs. Only 50 most abundant representatives are shown. Circle color represents phylum taxa, and circle size corresponds to their relative abundance. The tree is labeled by color-coded representatives identified in the taxa of the genus.
Figure 4Effect of sewage sludge enrichment on the microbial community composition in MEC4. Sewage sludge represents the primary source for enrichment of electrochemically active microorganisms. MEC4 anode represents the microbial biofilm on the surface of the carbon felt electrode. MEC4 anolyte represents planktonic microorganisms in the anode chamber. Taxonomic profiles were set at class (A), family (B), and genus (C) levels. Only representatives with a relative abundance >5% in at least one condition are shown. Detailed data are shown in Supplementary Table S4. Alpha diversity was estimated using the following indices: Chao1, Shannon, and Inverse Simpson.