Analyses of microbial activity in biomass-recycle reactors using denaturing gradient gel electrophoresis of 16S rDNA and 16S rRNA PCR products
Bibliographic record
Abstract
The relationship between mixed microbial community structure and physiology when grown under substrate-limited conditions was investigated using continuous-flow bioreactors with 100% biomass recycle. Community structure was analyzed by denaturing gradient gel electrophoresis (DGGE) of the PCR and RT-PCR amplified V3 region of 16S rDNA and 16S rRNA templates, respectively. Comparisons were made of communities exposed to different types of transient conditions (e.g., long- and short-term starvation, increasing nutrients). With progressively more stringent substrate limitation over time, the specific content of community RNA declined by more than 10-fold and closely followed the decline in specific growth rate. In contrast, the DNA content was variable (up to 3-fold differences) and did not follow the same trend. Cluster analysis of the presence or absence of individual bands indicated that the fingerprints generated by the two templates were different, and community response was first observed in the rRNA fraction. However, both the rDNA and rRNA fingerprints provided a picture of temporal population dynamics. Dice similarity coefficients gave a quantitative measure of the differences and changes between the communities. In comparison, standard cultivation techniques yielded only a quarter of the phylotypes detected by DGGE, but included the most dominant population based on rRNA. Nucleotide-sequence analyses of the almost complete 16S rRNA genes of these isolates place them in the same group of organisms that is typically cultivated from environmental samples: alpha, beta, and gamma Proteobacteria and the high GC and the low GC Gram-positive divisions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".