RNA-based spatial community analysis revealed intra-reactor variation and expanded collection of direct interspecies electron transfer microorganisms in anaerobic digestion
Bibliographic record
Abstract
Granular activated carbon (GAC) has been shown to mediate direct interspecies electron transfer (DIET) in anaerobic digestion. Adding GAC to up-flow anaerobic sludge bed reactor increased the total biomass slightly from 20.0 to 26.6 gVSS/reactor, and maximum organic removal capacity remarkably from 285 to 1660 mgCOD/L/d. Since GAC occupied 7% of reactor volume (denser than suspended sludge, settled to the reactor bottom), we used a spatial sampling strategy (sludge bed top/mid/bottom layers, and tightly attached GAC-biofilm) and DNA- and RNA-based community analyses. RNA-based analysis demonstrated significant community differences between the non-GAC and GAC-amended reactors (p < 0.05) based on ANOSIM statistical analysis. In comparison, DNA-based analysis showed little community difference between these reactors (p > 0.05). RNA-based analysis revealed active enrichments in GAC-biofilm, including bacteria Geobacter, Syntrophus, Desulfovibrio and Blvii28, and archaea Methanosaeta and Methanospirillum. These are potential electro-active syntrophic microorganisms related with DIET, which expand the previously defined list of DIET microorganisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".