Acidity and sulfur oxidation intermediate concentrations controlled by O <sub>2</sub> -driven partitioning of sulfur oxidizing bacteria in a mine tailings impoundment
Bibliographic record
Abstract
Abstract Acidification of freshwater in mining impacted areas is a major global environmental problem catalyzed by sulfur-oxidizing bacteria (SOB). To date, little is known about the active bacteria in mine tailings impoundments and their environmental niches. Here, biological sulfur oxidation was investigated over four years in a mine tailings impoundment, integrating sulfur geochemistry, genome-resolved metagenomics and metatranscriptomics. We demonstrated oxygen driven niche partitioning of SOB and their metabolic pathways that explain acidity generation and thiosulfate persistence. Four chemolithoautotrophic SOB, Halothiobacillus, Thiobacillus, Sulfuricurvum and Sediminibacterium comprised 37% to 73% of the analyzed communities. The impoundment waters alternated between the dominance of Halothiobacillus versus a Thiobacillus, Halothiobacillus, Sulfuricurvum and Sediminibacterium consortia. Halothiobacillus dominance was associated with lower pH values (∼4.3), higher [H + ]/[SO 4 2- ] and lower [S 2 O 3 2- ], collectively indicative of extensive sulfur oxidation. Halothiobacillus , which couple sulfur oxidation via the Sox pathway to aerobic respiration or NO 2 - reduction, were present throughout the depth profile, yet their expression of sox genes occurred only in upper highly oxygenated waters. Conversely, when consortia of Thiobacillus, Halothiobacillus, Sulfuricurvum and Sediminibacterium dominated, recycling/disproportionating reactions were more prevalent. Thiobacillus, which dominated deeper micro-oxic/anoxic waters, oxidized sulfur primarily through the rDSR pathway, coupled to NO 3 - /NO 2 - reduction, resulting in lower [H + ]/[SO 4 2- ] and higher [S 2 O 3 2- ] relative to upper waters. These field results mirror the Sox/rDSR-geochemical patterns of experimental SOB enrichments and reveal opportunities for biological treatments of recalcitrant reduced sulfur compounds, as well as gene-based monitoring and in situ RNA detection to predict the onset of problematic geochemistry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".