Metagenomic profiling of Arctic microbial mat communities as nutrient scavenging and recycling systems
Bibliographic record
Abstract
By way of metagenomics and high‐throughput pyrosequencing, we addressed the hypothesis that cyanobacterial mats in polar aquatic ecosystems maintain a nutrient‐rich microenvironment via decomposition and scavenging processes. Analysis of more than 592,554 genomic deoxyribonucleic acid (DNA) reads (total of 11.5 million base pairs) showed that the ribosomal and protein‐coding genes of two High Arctic ice‐shelf mat communities were dominated by Proteobacteria , not Cyanobacteria , which implies a broad range of bacterial decomposition and nutrient recycling processes in addition to phototrophy. Principal component analysis of genes for light‐, nitrogen‐, and phosphorus‐related processes provided evidence of partitioning of mat function among taxonomically different constituents of the mat consortia. Viruses were also present (notably Alpha ‐, Beta ‐, Gammaproteobacteria phages and cyanophages), which likely contribute to cellular lysis and recycling, as well as other Bacteria, Archaea, and microbial eukaryotes. Nitrogen‐related genes were dominated by ammoniumassimilation systems, implying that the microbial mats are sites of intense mineralization, but not N‐oxidation, since nitrification genes were absent. Nutrient scavenging systems were detected, including genes for transport proteins and enzymes for converting larger molecules into more readily assimilated inorganic forms (allantoin degradation, cyanate hydrolysis, exophosphatases, phosphonatases). Metagenomic profiling results underscore the rich diversity of microbial life even in extreme polar habitats, and the capability of mat consortia to retain and recycle nutrients in the benthic microenvironment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".