Granular activated carbon enhances microbial activity in anaerobic reactors: Insights from metagenomics and metaproteomics
Why this work is in the frame
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Bibliographic record
Abstract
Granular activated carbon (GAC) enhances anaerobic digestion (AD) primarily by promoting direct interspecies electron transfer (DIET). However, as most biomass in bioreactors is suspended rather than attached, GAC may also play additional roles in stimulating suspended biomass beyond DIET. In this study, two lab-scale up-flow anaerobic sludge blanket (UASB) reactors were operated for 150 days with propionate-rich synthetic wastewater, one of which was amended with GAC to investigate its broader effects on microbial activity and metabolic function. Results showed that GAC addition significantly improved chemical oxygen demand (COD) removal (92.1 ± 5.0%) and methane yield (70.3 ± 8.2%) compared to the non-GAC reactor (81.0 ± 2.1% and 55.4 ± 5.2%). Metagenomic analysis revealed a shift toward hydrogenotrophic methanogenesis, with an increased abundance of Methanobacterium sp. (31.4%). Metaproteomic profiling and functional gene prediction indicated elevated expression of proteins involved in methanogenesis (e.g., methyl-coenzyme M reductase), energy metabolism (e.g., ATP synthase), and cofactor biosynthesis (e.g., CobS and CobT enzymes). Additionally, batch tests using reactor effluents demonstrated that the GAC-amended system contained active substances capable of stimulating methane production, indicating the release of bioavailable metabolites. These findings suggest that GAC enhances microbial activity not only by facilitating DIET but also by stimulating the biosynthesis of key functional proteins and cofactors. This understanding supports the development of GAC-enhanced anaerobic systems for more stable and efficient reactors in full-scale applications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it