An Integrative Model of Carbon and Nitrogen Metabolism in a Common Deep-Sea Sponge (Geodia barretti)
Bibliographic record
Abstract
Deep-sea sponges and their microbial symbionts transform various forms of carbon (C) and nitrogen (N) via several metabolic pathways, which, for a large part, are poorly quantified. Previous flux studies on the common deep-sea sponge Geodia barretti consistently revealed net consumption of dissolved organic carbon (DOC) and oxygen (O2) and net release of nitrate ( NO3- ). Here we present a biogeochemical metabolic network model that, for the first time, quantifies C and N fluxes within the sponge holobiont in a consistent manner, including many poorly constrained metabolic conversions. Using two datasets covering a range of individual G. barretti sizes (10–3,500 ml), we found that the variability in metabolic rates partially resulted from body size as O2 uptake allometrically scales with sponge volume. Our model analysis confirmed that dissolved organic matter (DOM), with an estimated C:N ratio of 7.7 ± 1.4, is the main energy source of G. barretti. DOM is primarily used for aerobic respiration, then for dissimilatory NO3- reduction to ammonium ( NH4+) (DNRA), and, lastly, for denitrification. Dissolved organic carbon (DOC) production efficiencies (production/assimilation) were estimated as 24 ± 8% (larger individuals) and 31 ± 9% (smaller individuals), so most DOC was respired to carbon dioxide (CO2), which was released in a net ratio of 0.77–0.81 to O2 consumption. Internally produced NH4+ from cellular excretion and DNRA fueled nitrification. Nitrification-associated chemoautotrophic production contributed 5.1–6.7 ± 3.0% to total sponge production. While overall metabolic patterns were rather independent of sponge size, (volume-)specific rates were lower in larger sponges compared to smaller individuals. Specific biomass production rates were 0.16% day–1 in smaller compared to 0.067% day–1 in larger G. barretti as expected for slow-growing deep-sea organisms. Collectively, our approach shows that metabolic modeling of hard-to-reach, deep-water sponges can be used to predict community-based biogeochemical fluxes and sponge production that will facilitate further investigations on the functional integration and the ecological significance of sponge aggregations in deep-sea ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".