Physiological and genomic features of highly alkaliphilic hydrogen-utilizing Betaproteobacteria from a continental serpentinizing site
Bibliographic record
Abstract
Serpentinization, or the aqueous alteration of ultramafic rocks, results in challenging environments for life in continental sites due to the combination of extremely high pH, low salinity and lack of obvious electron acceptors and carbon sources. Nevertheless, certain Betaproteobacteria have been frequently observed in such environments. Here we describe physiological and genomic features of three related Betaproteobacterial strains isolated from highly alkaline (pH 11.6) serpentinizing springs at The Cedars, California. All three strains are obligate alkaliphiles with an optimum for growth at pH 11 and are capable of autotrophic growth with hydrogen, calcium carbonate and oxygen. The three strains exhibit differences, however, regarding the utilization of organic carbon and electron acceptors. Their global distribution and physiological, genomic and transcriptomic characteristics indicate that the strains are adapted to the alkaline and calcium-rich environments represented by the terrestrial serpentinizing ecosystems. We propose placing these strains in a new genus ‘Serpentinomonas’. Microbes can dwell in highly alkaline environments in the absence of obvious food sources. Here, the authors describe physiological and genomic features of a group of bacteria that live on hydrogen, calcium carbonate and oxygen at a very high pH.
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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 | 0.000 | 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 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".