Bacterial community dynamics in liquid swine manure during storage: molecular analysis using DGGE/PCR of 16S rDNA
Bibliographic record
Abstract
Denaturant gradient gel electrophoresis (DGGE) analysis of polymerase chain reaction-amplified DNA fragments prepared from extracted DNA using universal 16S rDNA primers was used to compare the composition of bacterial communities in liquid swine manure (LSM) during incubation in aerated and in non-aerated laboratory reactors. The LSM was initially dominated by 13 phylotypes whose identities were established by excising and cloning DGGE bands, and comparing the 16S rDNA sequences with those available in GenBank. With varying degrees of similarity, Clostridium butyricum, Clostridium disporicum, a Pedobacter sp., two Rhodanobacter sp., a spirochete, and seven uncultured eubacterial sequences were identified. The chemical composition, total microbial populations determined by direct microscopic count, and DGGE profiles of the LSM were stable during anaerobic storage for 7 weeks. However, the community composition of the LSM changed substantially with aeration, the DGGE bands in the original sample receding in intensity as the manure community became dominated by phylotypes most closely related to the aerobes Bacillus thuringiensis, Sphingobacterium mizutae, a ‘Sphingobacterium-like’ bacterium, and a Paenibacillus sp. When continuously aerated, the pH rose from 8 to 9.5, the ammonium-N content decreased, populations of culturable aerobes increased 150-fold, and total bacterial populations remained stable. DGGE analysis of manure fractionated into planktonic and biofilm (flocs and aggregates) communities suggested that Clostridium populations were stable in biofilms during aeration, whereas the aerobes that ultimately dominated the LSM community were primarily in the planktonic phase.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".