Substrate-restricted methanogenesis and limited volatile organic compound degradation in highly diverse and heterogeneous municipal landfill microbial communities
Bibliographic record
Abstract
Microbial communities in landfills transform waste and generate methane in an environment unique from other built and natural environments. Landfill microbial diversity has predominantly been observed at the phylum level, without examining the extent of shared organismal diversity across space or time. We used 16S rRNA gene amplicon and shotgun metagenomic sequencing to examine the taxonomic and functional diversity of the microbial communities inhabiting a Southern Ontario landfill. The microbial capacity for volatile organic compound degradation in leachate and groundwater samples was correlated with geochemical conditions. Across the landfill, 25 bacterial and archaeal phyla were present at >1% relative abundance within at least one landfill sample, with Patescibacteria, Bacteroidota, Firmicutes, and Proteobacteria dominating. Methanogens were neither numerous nor particularly abundant, and were predominantly constrained to either acetoclastic or methylotrophic methanogenesis. The landfill microbial community was highly heterogeneous, with 90.7% of organisms present at only one or two sites within this interconnected system. Based on diversity measures, the landfill is a microbial system undergoing a constant state of disturbance and change, driving the extreme heterogeneity observed. Significant differences in geochemistry occurred across the leachate and groundwater wells sampled, with calcium, iron, magnesium, boron, meta and para xylenes, ortho xylenes, and ethylbenzene concentrations contributing most strongly to observed site differences. Predicted microbial degradation capacities indicated a heterogeneous community response to contaminants, including identification of novel proteins implicated in anaerobic degradation of key volatile organic compounds.
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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 | 0.001 | 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".