Evidence for Existence of “Mesotogas,” Members of the Order<i>Thermotogales</i>Adapted to Low-Temperature Environments
Bibliographic record
Abstract
All cultivated isolates of the bacterial order Thermotogales are either thermophiles or hyperthermophiles, but Thermotogales 16S rRNA gene sequences have been detected in many mesophilic anaerobic and microaerophilic environments, particularly within communities involved in the remediation of pollutants. Here we provide metagenomic evidence for the existence of Thermotogales lineages, which we informally call "mesotoga," that are adapted to growth at lower temperatures. Two fosmid clones containing mesotoga DNA, originating from a low-temperature enrichment culture that degrades a polychlorinated biphenyl congener, were sequenced. Phylogenetic analysis clearly puts this bacterial lineage within the Thermotogales order, with the rRNA gene trees and 21 of 58 open reading frames strongly supporting this relationship. An analysis of protein sequence composition showed that mesotoga proteins are adapted to function at lower temperatures than are their identifiable homologs from thermophilic and hyperthermophilic members of the order Thermotogales, supporting the notion that this bacterium lives and grows optimally at lower temperatures. The phylogenetic analysis suggests that the mesotoga lineage from which our fosmids derive has used both the acquisition of genes from its neighbors and the modification of existing thermophilic sequences to adapt to a mesophilic lifestyle.
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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 | 0.000 | 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) | 0.001 | 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".