Molecular analyses of the diversity and function of the family 1 β-glucosidase-producing microbial community in compost
Bibliographic record
Abstract
The diversity and transcription efficiency of GH1 family β-glucosidase genes were investigated in natural and inoculated composts using a DNA clone library and real-time qPCR. Compositional differences were observed in the functional communities between the two composting processes. Proteobacteria, Actinobacteria, Firmicutes, and Chloroflexi were the dominant phyla. Twenty representative β-glucosidase genes were quantitatively analyzed from the DNA and RNA pools. Principal component analysis and Pearson’s correlation analysis showed that cellulose degradation is correlated with the composition and succession of functional microbial communities, and this correlation was mainly observed in Proteobacteria and Actinobacteria. Compared with inoculated compost, the functional microbial communities in natural compost with a low diversity index exhibited a weak buffering capacity for function in response to environmental changes. This may explain the consistency and dysfunction of cellulose degradation and transcriptional regulation by dominant β-glucosidase genes. Except for the β-glucosidase genes encoding constitutive enzymes, individual β-glucosidase genes responded to environmental changes more drastically than the group β-glucosidase genes. The correlation results suggested that β-glucosidase genes belonging to Micrococcales play an important role in the regulation of intracellular β-glucosidase. These results indicated that the responses of functional microorganisms were different during both composting processes and were reflected at both the individual and group levels.
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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".