Stable Isotope and Metagenomic Profiling of a Methanogenic Naphthalene-Degrading Enrichment Culture
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAH) such as naphthalene are widespread, recalcitrant pollutants in anoxic and methanogenic environments. A mechanism catalyzing PAH activation under methanogenic conditions has yet to be discovered, and the microbial communities coordinating their metabolism are largely unknown. This is primarily due to the difficulty of cultivating PAH degraders, requiring lengthy incubations to yield sufficient biomass for biochemical analysis. Here, we sought to characterize a new methanogenic naphthalene-degrading enrichment culture using DNA-based stable isotope probing (SIP) and metagenomic analyses. 16S rRNA gene sequencing of fractionated DNA pinpointed an unclassified Clostridiaceae species as a putative naphthalene degrader after two months of SIP incubation. This finding was supported by metabolite and metagenomic evidence of genes predicted to encode for enzymes facilitating naphthalene carboxylic acid CoA-thioesterification and degradation of an unknown arylcarboxyl-CoA structure. Our findings also suggest a possible but unknown role for Desulfuromonadales in naphthalene degradation. This is the first reported functional evidence of PAH biodegradation by a methanogenic consortium, and we envision that this approach could be used to assess carbon flow through other slow growing enrichment cultures and environmental samples.
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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 | 0.000 | 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".