Metaproteomics reveals differential modes of metabolic coupling among ubiquitous oxygen minimum zone microbes
Bibliographic record
Abstract
Marine oxygen minimum zones (OMZs) are intrinsic water column features arising from respiratory oxygen demand during organic matter degradation in stratified waters. Currently OMZs are expanding due to global climate change with resulting feedback on marine ecosystem function. Here we use metaproteomics to chart spatial and temporal patterns of gene expression along defined redox gradients in a seasonally stratified fjord to better understand microbial community responses to OMZ expansion. The expression of metabolic pathway components for nitrification, anaerobic ammonium oxidation (anammox), denitrification, and inorganic carbon fixation were differentially expressed across the redoxcline and covaried with distribution patterns of ubiquitous OMZ microbes including Thaumarchaeota, Nitrospina, Nitrospira, Planctomycetes, and SUP05/ARCTIC96BD-19 Gammaproteobacteria. Nitrification and inorganic carbon fixation pathways affiliated with Thaumarchaeota dominated dysoxic waters, and denitrification, sulfur oxidation, and inorganic carbon fixation pathways affiliated with the SUP05 group of nitrate-reducing sulfur oxidizers dominated suboxic and anoxic waters. Nitrifier nitrite oxidation and anammox pathways affiliated with Nirospina, Nitrospira, and Planctomycetes, respectively, also exhibited redox partitioning between dysoxic and suboxic waters. The numerical abundance of SUP05 proteins mediating inorganic carbon fixation under anoxic conditions suggests that SUP05 will become increasingly important in global ocean carbon and nutrient cycling as OMZs expand.
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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 | 0.001 |
| 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".