Bridging a Gap in Marine Sulfur Cycling: Discovery of a <scp>d</scp> -Cysteinolic Acid Degradation Pathway
Bibliographic record
Abstract
d -Cysteinolic acid is a prominent sulfur-containing compound in marine and freshwater ecosystems, yet its metabolic fate has remained largely uncharacterized. Here, we describe a newly identified d -cysteinolic acid degradation pathway in a marine model bacterium Ruegeria pomeroyi DSS-3. This pathway involves a PLP-dependent cysteinolic acid racemase (ClaA) that interconverts d - and l -cysteinolic acids, followed by a NAD + -dependent l -cysteinolic acid dehydrogenase (ClaB) that oxidizes l -cysteinolic acid to l -cysteate. A cysteate racemase (CuyB) then converts l -cysteate to d -cysteate, the preferred substrate for the sulfolyase CuyA. Bioinformatic analysis of the Tara Oceans gene atlas reveals that ClaA and CuyA homologues are widespread in marine bacterial populations, particularly within the alphaproteobacterial Roseobacter and SAR116 groups and the gammaproteobacterial SUP05 clade. Relative abundance of gene homologues correlates with surface water chlorophyll levels, linking d -cysteinolic acid degradation to photosynthetic primary production. This discovery advances our understanding of marine sulfur cycling and highlights d -cysteinolic acid as an important metabolic currency in microbial networks.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".