Monitoring of bacteria in acid mine environments by reverse sample genome probing
Bibliographic record
Abstract
A variety of microorganisms can exist in acid mine drainage (AMD) environments, although their contribution to AMD problems is unclear. Environmental strains of Thiobacillus ferrooxidans and Thiobacillus acidophilus were purified by repeated plating and single-colony isolation on iron salts and tetrathionate media, respectively. Thiobacillus thiooxidans was enriched on sulfur-containing media. For the isolation of Leptospirillum ferrooxidans, iron salts and pyrite media were inoculated with environmental samples. However, L. ferrooxidans was never recovered on solid media. Denatured chromosomal DNAs from type and (or) isolated strains of T. ferrooxidans, T. acidophilus, T. thiooxidans, and L. ferrooxidans were spotted on a master filter for their detection in a variety of samples by reverse sample genome probing (RSGP). Analysis of enrichments of environmental samples by RSGP indicated that ferrous sulfate medium enriched T. ferrooxidans strains, whereas all thiobacilli grew in sulfur medium, T. thiooxidans strains being dominant. Enrichment in glucose medium followed by transfer to tetrathionate medium resulted in the selection of T. acidophilus strains. DNA was also extracted directly (without enrichment) from cells recovered from AMD water or sediments, and was analyzed by RSGP to describe the communities present. Strains showing homology with T. ferrooxidans and T. acidophilus were found to be major community components. Strains showing homology with T. thiooxidans were a minor community component, whereas strains showing homology with L. ferrooxidans were not detected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".