Cyanophycin and its biosynthesis: not hot but very cool
Bibliographic record
Abstract
Covering: 1878 to early 2023Cyanophycin is a biopolymer consisting of a poly-aspartate backbone with arginines linked to each Asp sidechain through isopeptide bonds. Cyanophycin is made by cyanophycin synthetase 1 or 2 through ATP-dependent polymerization of Asp and Arg, or β-Asp-Arg, respectively. It is degraded into dipeptides by exo-cyanophycinases, and these dipeptides are hydrolyzed into free amino acids by general or dedicated isodipeptidase enzymes. When synthesized, chains of cyanophycin coalesce into large, inert, membrane-less granules. Although discovered in cyanobacteria, cyanophycin is made by species throughout the bacterial kingdom, and cyanophycin metabolism provides advantages for toxic bloom forming algae and some human pathogens. Some bacteria have developed dedicated schemes for cyanophycin accumulation and use, which include fine temporal and spatial regulation. Cyanophycin has also been heterologously produced in a variety of host organisms to a remarkable level, over 50% of the host's dry mass, and has potential for a variety of green industrial applications. In this review, we summarize the progression of cyanophycin research, with an emphasis on recent structural studies of enzymes in the cyanophycin biosynthetic pathway. These include several unexpected revelations that show cyanophycin synthetase to be a very cool, multi-functional macromolecular machine.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".