An inventory of early branch points in microbial phosphonate biosynthesis
Bibliographic record
Abstract
Microbial phosphonate biosynthetic machinery has been identified in ~5 % of bacterial genomes and encodes natural products like fosfomycin as well as cell surface decorations. Almost all biological phosphonates originate from the rearrangement of phosphoenolpyruvate (PEP) to phosphonopyruvate (PnPy) catalysed by PEP mutase (Ppm), and PnPy is often converted to phosphonoacetaldehyde (PnAA) by PnPy decarboxylase (Ppd). Seven enzymes are known or likely to act on either PnPy or PnAA as early branch points en route to diverse biosynthetic outcomes, and these enzymes may be broadly classified into three reaction types: hydride transfer, aminotransfer, and carbon-carbon bond formation. However, the relative abundance of these branch points in microbial phosphonate biosynthesis is unknown. Also unknown is the proportion of ppm -containing gene neighbourhoods encoding new branch point enzymes and potentially novel phosphonates. In this study we computationally sorted 434 ppm -containing gene neighbourhoods based on these seven branch point enzymes. Unsurprisingly, the majority (56 %) of these pathways encode for production of the common naturally occurring compound 2-aminoethylphosphonate (AEP) or a hydroxylated derivative. The next most abundant genetically encoded intermediates were phosphonoalanine (PnAla, 9.2 %), 2-hydroxyethylphosphonate (HEP, 8.5 %), and phosphonoacetate (PnAc, 6 %). Significantly, about 13 % of the gene neighbourhoods could not be assigned to any of the seven branch points and may encode novel phosphonates. Sequence similarity network analysis revealed families of unusual gene neighbourhoods including possible production of phosphonoacrylate and phosphonofructose, the apparent biosynthetic use of the C-P lyase operon, and a virus-encoded phosphonate. Overall, these results highlight the utility of branch point inventories to identify novel gene neighbourhoods and guide future phosphonate discovery efforts.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".