Genetic isolation and metabolic complexity of an Antarctic subglacial microbiome
Bibliographic record
Abstract
Microbes inhabiting and evolving in aquatic ecosystems beneath polar ice sheets subsist under energy-limited conditions while in relative isolation from surface gene pools and their common ancestral populations of origin. Samples obtained from beneath West Antarctic Ice Sheet (WAIS) allowed us to examine evolutionary relationships of and identify metabolic pathways in microbial genomes recovered from the Mercer Subglacial Lake (SLM) ecosystem. We obtained 1,374 single-cell amplified genomes (SAGs) from individual bacterial and archaeal cells that were isolated from samples of SLM's water column and sediments. These genomes reveal that a diversity of microorganisms including Patescibacteria exists in SLM. Comparative analyses show that most genomes correspond to new species and taxonomic groups, with phylogenomic and functional evidence supporting their genetic isolation from marine and surface biomes. Genomic data reveal diverse metabolisms in SLM that are capable of oxidizing organic and inorganic compounds via aerobic or anaerobic respiration. Distinct metabolic guild structures are observed for the subglacial populations, where trophic shifts from organotrophy to chemolithotrophy may depend on oxygen availability. Our SAG data suggest versatile metabolic capabilities in the characterized microbial assemblage, reveal key energy-generating strategies in the subglacial aquatic ecosystem, and provide a framework to assess microbial evolution beneath WAIS.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".