Involvement of the <i>cynABDS</i> Operon and the CO <sub>2</sub> -Concentrating Mechanism in the Light-Dependent Transport and Metabolism of Cyanate by Cyanobacteria
Bibliographic record
Abstract
The cyanobacteria Synechococcus elongatus strain PCC7942 and Synechococcus sp. strain UTEX625 decomposed exogenously supplied cyanate (NCO-) to CO2 and NH3 through the action of a cytosolic cyanase which required HCO3- as a second substrate. The ability to metabolize NCO- relied on three essential elements: proteins encoded by the cynABDS operon, the biophysical activity of the CO2-concentrating mechanism (CCM), and light. Inactivation of cynS, encoding cyanase, and cynA yielded mutants unable to decompose cyanate. Furthermore, loss of CynA, the periplasmic binding protein of a multicomponent ABC-type transporter, resulted in loss of active cyanate transport. Competition experiments revealed that native transport systems for CO2, HCO3-, NO3-, NO2-, Cl-, PO4(2-), and SO4(2-) did not contribute to the cellular flux of NCO- and that CynABD did not contribute to the flux of these nutrients, implicating CynABD as a novel primary active NCO- transporter. In the S. elongatus strain PCC7942 DeltachpX DeltachpY mutant that is defective in the full expression of the CCM, mass spectrometry revealed that the cellular rate of cyanate decomposition depended upon the size of the internal inorganic carbon (Ci) (HCO3- + CO2) pool. Unlike wild-type cells, the rate of NCO- decomposition by the DeltachpX DeltachpY mutant was severely depressed at low external Ci concentrations, indicating that the CCM was essential in providing HCO3- for cyanase under typical growth conditions. Light was required to activate and/or energize the active transport of both NCO- and Ci. Putative cynABDS operons were identified in the genomes of diverse Proteobacteria, suggesting that CynABDS-mediated cyanate metabolism is not restricted to cyanobacteria.
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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 | 0.000 | 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 | 0.000 |
| 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".