Degradation of biological macromolecules supports uncultured microbial populations in Guaymas Basin hydrothermal sediments
Bibliographic record
Abstract
Hydrothermal sediments contain large numbers of uncultured heterotrophic microbial lineages. Here, we amended Guaymas Basin sediments with proteins, polysaccharides, nucleic acids or lipids under different redox conditions and cultivated heterotrophic thermophiles with the genomic potential for macromolecule degradation. We reconstructed 20 metagenome-assembled genomes (MAGs) of uncultured lineages affiliating with known archaeal and bacterial phyla, including endospore-forming Bacilli and candidate phylum Marinisomatota. One Marinisomatota MAG had 35 different glycoside hydrolases often in multiple copies, seven extracellular CAZymes, six polysaccharide lyases, and multiple sugar transporters. This population has the potential to degrade a broad spectrum of polysaccharides including chitin, cellulose, pectin, alginate, chondroitin, and carrageenan. We also describe thermophiles affiliating with the genera Thermosyntropha, Thermovirga, and Kosmotoga with the capability to make a living on nucleic acids, lipids, or multiple macromolecule classes, respectively. Several populations seemed to lack extracellular enzyme machinery and thus likely scavenged oligo- or monomers (e.g., MAGs affiliating with Archaeoglobus) or metabolic products like hydrogen (e.g., MAGs affiliating with Thermodesulfobacterium or Desulforudaceae). The growth of methanogens or the production of methane was not observed in any condition, indicating that the tested macromolecules are not degraded into substrates for methanogenesis in hydrothermal sediments. We provide new insights into the niches, and genomes of microorganisms that actively degrade abundant necromass macromolecules under oxic, sulfate-reducing, and fermentative thermophilic conditions. These findings improve our understanding of the carbon flow across trophic levels and indicate how primary produced biomass sustains complex and productive ecosystems.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".