Diversity and Metabolic Potential of Microbial Communities in a Serpentinite-Hosted Spring at the Tablelands
Bibliographic record
Abstract
Abstract The geochemical process of serpentinization releases energy and organic carbon: two of the basic requirements needed to support life. Sites of active serpentinization in the deep subsurface provide the intriguing possibility of a non-photosynthetically-supported biosphere. However, serpentinization also creates conditions, such as high pH and limited electron acceptors, which may limit microbial growth and diversity. Gaining an understanding of the identity and metabolic potential of microbes that thrive in these environments may provide insight as to whether serpentinization is sufficient to independently support life. Tablelands Ophiolite in Gros Morne National Park, Newfoundland, Canada is a continental site of serpentinization where serpentinite springs form surface pools. These pools provide easy sampling access to subsurface fluids and may allow for sampling of the subsurface microbial community. However, identification of members of the subsurface community in these pools is complicated by both surface contamination and contamination by organisms that inhabit the transition zone where hydrogen-rich subsurface fluids meet oxygen-rich surface fluids. This study was designed to distinguish among these potential sources of microorganisms by using a sampling technique that more effectively samples subsurface fluids. Community dissimilarity comparisons using environmental 16S rRNA gene sequencing indicate that the sampling design led to more direct access to subsurface fluids. These results are supported by metagenomic analyses that show metabolic pathways consistent with non-photosynthetic carbon fixation in the samples expected to represent subsurface fluids and that show hydrogen oxidation pathways in samples associated with the surface sources. These results provide a clearer picture of the diversity and metabolic potential of microbial communities potentially inhabiting subsurface, serpentinite-hosted habitats.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".