An Oxidative Pathway for Microbial Utilization of Methylphosphonic Acid as a Phosphate Source
Bibliographic record
Abstract
Methylphosphonic acid is synthesized by marine bacteria and is a prominent component of dissolved organic phosphorus. Consequently, methylphosphonic acid also serves as a source of inorganic phosphate (Pi) for marine bacteria that are starved of this nutrient. Conversion of methylphosphonic acid into Pi is currently only known to occur through the carbon–phosphorus lyase pathway, yielding methane as a byproduct. In this work, we describe an oxidative pathway for the catabolism of methylphosphonic acid in Gimesia maris DSM8797. G. maris can use methylphosphonic acid as Pi sources despite lacking a phn operon encoding a carbon–phosphorus lyase pathway. Instead, the genome contains a locus encoding homologues of the non-heme Fe(II) dependent oxygenases HF130 PhnY* and HF130 PhnZ, which were previously shown to convert 2-aminoethylphosphonic acid into glycine and Pi. Gm PhnY* and Gm PhnZ1 were produced in E. coli and purified for characterization in vitro. The substrate specificities of the enzymes were evaluated with a panel of synthetic phosphonates. Via 31 P NMR spectroscopy, it is demonstrated that the Gm PhnY* converts methylphosphonic acid to hydroxymethylphosphonic acid, which in turn is oxidized by Gm PhnZ1 to produce formic acid and Pi. In contrast, 2-aminoethylphosphonic acid is not a substrate for Gm PhnY* and is therefore not a substrate for this pathway. These results thus reveal a new metabolic fate for methylphosphonic acid.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".