Comparative Metagenomics of Anaerobic Digester Communities Reveals Sulfidogenic and Methanogenic Microbial Subgroups in Conventional and Plug Flow Residential Septic Tank Systems
Bibliographic record
Abstract
On-site wastewater treatment systems (OWTS) are primarily monitored using physiochemical factors, including chemical oxygen demand (COD) and residual total suspended solids (TSS), which are indirect measures of the microbial action during the anaerobic digestion process. Changes in anaerobic digester microbial communities can alter the digester performance, but this information cannot be directly obtained from traditional physicochemical indicators. The potential of metagenomic DNA sequencing as a tool for taxonomic and functional profiling of microbial communities was examined in both common conventional and plug flow-type anaerobic digesters (single-pass and recirculating). Compared to conventional digesters, plug flow-type digesters had higher relative levels of sulfate-reducing bacteria (Desulfovibrio spp.) and hydrogenotrophic methanogens (Methanospirillum spp.). In contrast, recirculating anaerobic digesters were enriched with denitrifier bacteria and hydrogenotrophic methanogens, and both were significantly correlated with physicochemical factors such as COD and TSS. Stratification of microbial communities was observed along the digester treatment process according to hydrolytic, acidogenic, acetogenic, and methanogenic subgroups. These results indicate that the high-throughput DNA sequencing may be useful as a monitoring tool to characterize the changes in bacterial communities and the functional profile due to differences in digester design in on-site systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".