Culture-dependent and -independent approaches establish the complexity of a PAH-degrading microbial consortium
Bibliographic record
Abstract
A microbial consortium (AM) obtained by sequential enrichment in liquid culture with a polycyclic aromatic hydrocarbon (PAH) mixture of three- and four-ringed PAHs as a sole source of carbon and energy was examined using a triple-approach method based on various cultivation strategies, denaturing gradient gel electrophoresis (DGGE), and the screening of 16S and 18S rRNA gene clone libraries. Eleven different sequences by culture-dependent techniques and seven by both DGGE and clone libraries were obtained. The comparison of three variable regions (V3-V5) of the 16S rRNA gene between the sequences obtained yielded 19 different microbial components. Proteobacteria were the dominant group, representing 83% of the total, while the Cytophaga-Flexibacter-Bacteroides group (CFB) was 11% and the Ascomycota fungi 6%. Beta-proteobacteria were predominant in the DGGE and clone library methods, whereas they were a minority in culturable strains. The highest diversity and number of noncoincident sequences were achieved by the cultivation method that showed members of the alpha-, beta-, and gamma-Proteobacteria; CFB bacterial group; and Ascomycota fungi. Only six of the 11 strains isolated showed PAH-degrading capability. The bacterial strain (AMS7) and the fungal strain (AMF1), which were similar to Sphingomonas sp. and Fusarium sp., respectively, achieved the greatest PAH depletion. The results indicate that polyphasic assessment is necessary for a proper understanding of the composition of a microbial consortium.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".