Diverse, uncultivated bacteria and archaea underlying the cycling of dissolved protein in the ocean
Bibliographic record
Abstract
Dissolved organic nitrogen (DON) supports a significant amount of heterotrophic production in the ocean. Yet, to date, the identity and diversity of microbial groups that transform DON are not well understood. To better understand the organisms responsible for transforming high molecular weight (HMW)-DON in the upper ocean, isotopically labeled protein extract from Micromonas pusilla, a eukaryotic member of the resident phytoplankton community, was added as substrate to euphotic zone water from the central California Current system. Carbon and nitrogen remineralization rates from the added proteins ranged from 0.002 to 0.35 μmol C l(-1) per day and 0.03 to 0.27 nmol N l(-1) per day. DNA stable-isotope probing (DNA-SIP) coupled with high-throughput sequencing of 16S rRNA genes linked the activity of 77 uncultivated free-living and particle-associated bacterial and archaeal taxa to the utilization of Micromonas protein extract. The high-throughput DNA-SIP method was sensitive in detecting isotopic assimilation by individual operational taxonomic units (OTUs), as substrate assimilation was observed after only 24 h. Many uncultivated free-living microbial taxa are newly implicated in the cycling of dissolved proteins affiliated with the Verrucomicrobia, Planctomycetes, Actinobacteria and Marine Group II (MGII) Euryarchaeota. In addition, a particle-associated community actively cycling DON was discovered, dominated by uncultivated organisms affiliated with MGII, Flavobacteria, Planctomycetes, Verrucomicrobia and Bdellovibrionaceae. The number of taxa assimilating protein correlated with genomic representation of TonB-dependent receptor (TBDR)-encoding genes, suggesting a possible role of TBDR in utilization of dissolved proteins by marine microbes. Our results significantly expand the known microbial diversity mediating the cycling of dissolved proteins in the ocean.
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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) | 0.001 | 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 | 0.001 |
| 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".