Discovery of cyanophycin dipeptide hydrolase enzymes suggests widespread utility of the natural biopolymer cyanophycin
Bibliographic record
Abstract
Cyanophycin is a bacterial polymer mainly used for nitrogen storage. It is composed of a peptide backbone of L-aspartate residues with L-arginines attached to their side chains through isopeptide bonds. Cyanophycin is degraded in two steps: Cyanophycinase cleaves the polymer into β-Asp-Arg dipeptides, which are hydrolyzed into free Asp and Arg by enzymes possessing isoaspartyl dipeptide hydrolase activity. Two unrelated enzymes with this activity, isoaspartyl dipeptidase (IadA) and isoaspartyl aminopeptidase (IaaA) have been shown to degrade β-Asp-Arg dipeptides, but bacteria which encode cyanophycin-metabolizing genes can lack iaaA and iadA genes. In this study, we investigate a previously uncharacterized enzyme whose gene can cluster with cyanophycin-metabolizing genes. This enzyme, which we name cyanophycin dipeptide hydrolase (CphZ), is specific for dipeptides derived from cyanophycin degradation. Accordingly, a co-complex structure of CphZ and β-Asp-Arg shows that CphZ, unlike IadA or IaaA, recognizes all portions of its β-Asp-Arg substrate. Bioinformatic analyses showed that CphZ is found in very many proteobacteria and is homologous to an uncharacterized protein encoded in the “arginine/ornithine transport” (aot) operon of many pseudomonas species, including Pseudomonas aeruginosa . In vitro assays show that AotO is indeed a CphZ, and in cellulo growth experiments show that this enzyme and the aot operon allow P. aeruginosa to take up and use β-Asp-Arg as a sole carbon and nitrogen source. Together the results establish the novel, highly specific enzyme subfamily of CphZs, suggesting that cyanophycin is potentially used by a much wider range of bacteria than previously appreciated.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".