Eurypsychrophilic acidophiles: From (meta)genomes to low-temperature biotechnologies
Bibliographic record
Abstract
Low temperature and acidic environments encompass natural milieus such as acid rock drainage in Antarctica and anthropogenic sites including drained sulfidic sediments in Scandinavia. The microorganisms inhabiting these environments include polyextremophiles that are both extreme acidophiles (defined as having an optimum growth pH < 3), and eurypsychrophiles that grow at low temperatures down to approximately 4°C but have an optimum temperature for growth above 15°C. Eurypsychrophilic acidophiles have important roles in natural biogeochemical cycling on earth and potentially on other planetary bodies and moons along with biotechnological applications in, for instance, low-temperature metal dissolution from metal sulfides. Five low-temperature acidophiles are characterized, namely, Acidithiobacillus ferriphilus, Acidithiobacillus ferrivorans, Acidithiobacillus ferrooxidans , “ Ferrovum myxofaciens ,” and Alicyclobacillus disulfidooxidans , and their characteristics are reviewed. Our understanding of characterized and environmental eurypsychrophilic acidophiles has been accelerated by the application of “omics” techniques that have aided in revealing adaptations to low pH and temperature that can be synergistic, while other adaptations are potentially antagonistic. The lack of known acidophiles that exclusively grow below 15°C may be due to the antagonistic nature of adaptations in this polyextremophile. In conclusion, this review summarizes the knowledge of eurypsychrophilic acidophiles and places the information in evolutionary, environmental, biotechnological, and exobiology perspectives.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".