Genomic evidence of functional diversity in DPANN archaea, from oxic species to anoxic vampiristic consortia
Bibliographic record
Abstract
DPANN archaea account for half of the archaeal diversity of the biosphere, but with few cultivated representatives, their metabolic potential and environmental functions are poorly understood. The extreme geochemical and environmental conditions in meromictic ice-capped Lake A, in the Canadian High Arctic, provided an isolated, stratified model ecosystem to resolve the distribution and metabolism of uncultured aquatic DPANN archaea living across extreme redox and salinity gradients, from freshwater oxygenated conditions, to saline, anoxic, sulfidic waters. We recovered 28 metagenome-assembled genomes (MAGs) of DPANN archaea that provided genetic insights into their ecological function. Thiosulfate oxidation potential was detected in aerobic Woesearchaeota, whereas diverse metabolic functions were identified in anaerobic DPANN archaea, including degradation and fermentation of cellular compounds, and sulfide and polysulfide reduction. We also found evidence for "vampiristic" metabolism in several MAGs, with genes coding for pore-forming toxins, peptidoglycan degradation, and RNA scavenging. The vampiristic MAGs co-occurred with other DPANNs having complementary metabolic capacities, leading to the possibility that DPANN form interspecific consortia that recycle microbial carbon, nutrients and complex molecules through a DPANN archaeal shunt, adding hidden novel complexity to anaerobic microbial food webs.
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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) | 0.001 | 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".