Metabolic and population profiles of active subseafloor autotrophs in young oceanic crust at deep-sea hydrothermal vents
Bibliographic record
Abstract
ABSTRACT At deep-sea hydrothermal vents, magmatically driven rock-water reactions in the crust generate gases and other reduced compounds that subseafloor microorganisms use for chemolithoautotrophy. In this study, microbial autotrophs from three diffuse flow hydrothermal vents at Axial Seamount in 2013 and 2014 were isotopically labeled using RNA stable isotope probing, targeting subseafloor autotrophic mesophiles (30°C), thermophiles (55°C), and hyperthermophiles (80°C). We constructed taxonomic and functional profiles of active chemolithoautotrophs, examined population distributions across sites, and linked primary producers to their specific metabolic strategies within the subseafloor community. Dominant autotrophs exhibited hydrogen-dependent dissimilatory metabolisms, such as sulfur and nitrate reduction and methanogenesis, as well as microaerophilic sulfide oxidation even at 80°C, consistent with fluid chemistries at each site. While hydrogenotrophic methanogenic archaea ( Methanothermococcus ) were restricted in their distribution and activity, hydrogenotrophic sulfur and nitrate reducers from the Aquificota ( Thermovibrio ) and Campylobacterota (Nautiliaceae, Hydrogenimonas , and Desulfurobacteriaceae) were consistently active and present at all sites and years at both the population and community levels. Hydrogenase transcripts were significantly differentially expressed, and diverse hydrogenases were found in metagenome-assembled genomes of Aquificota members, highlighting the importance and versatility of their hydrogen utilization strategies, which likely contribute to their cosmopolitan distribution across geochemically disparate subseafloor sites. Together, this study provides new insights into the functional dynamics and distribution of key subseafloor autotrophic microbial communities in young oceanic crust at deep-sea hydrothermal vents. IMPORTANCE Deep-sea hydrothermal vents are hotspots for life in the dark ocean, where rich animal ecosystems are supported by microbial primary producers utilizing the abundant chemical energy supplied by high-temperature water-rock reactions. Despite increasing knowledge about the geochemistry and microbiology of deep-sea hydrothermal vents, there is still a gap in our understanding of the key microbial players who fix much of the carbon at these sites, especially in the productive subseafloor. In this study, stable isotope probing was used to label active microbial autotrophs in diffuse flow venting fluids from three sites over 2 years and was combined with metatranscriptomic sequencing to identify their specific metabolic strategies. This research highlights the microbial community composition, function, gene regulation, and population dynamics that enable hydrothermal ecosystems to persist.
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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 | 0.000 |
| 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 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".