Microbial community origin and fate through a rural wastewater treatment plant
Bibliographic record
Abstract
Conventional wastewater treatment relies on a complex microbiota; however, much of this community is still to be characterized. To better understand the origin, dynamics and fate of bacteria within a wastewater treatment plant: untreated primary wastewater, activated sludge and post-treatment effluent were characterized. From 3163 exact sequence variants (ESVs), 860 were annotated to species-level. In primary wastewater, 28% of ESVs were putative bacterial species previously associated with humans, 14% with animals and 5% as common to the environment. Differential abundance analysis revealed significant relative reductions in ESVs from potentially human-associated species from primary wastewater to activated sludge, and significant increases in ESVs from species associated with nutrient cycling. Between primary wastewater and effluent, 51% of ESVs from human-associated species did not significantly differ, and species such as Bacteroides massiliensis and Bacteroides dorei increased. These findings illustrate that activated sludge increased extracellular protease and urease-producing species, ammonia and nitrite oxidizers, denitrifiers and specific phosphorus accumulators. Although many human-associated species declined, some persisted in effluent, including strains of potential health or environmental concern. Species-level microbial assessment may be useful for understanding variation in wastewater treatment efficiency as well as for monitoring the release of microbes into surface water and the wider ecosystem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 teacher head, 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".