Carbohydrate Kinase (RhaK)-Dependent ABC Transport of Rhamnose in Rhizobium leguminosarum Demonstrates Genetic Separation of Kinase and Transport Activities
Bibliographic record
Abstract
In Rhizobium leguminosarum the ABC transporter responsible for rhamnose transport is dependent on RhaK, a sugar kinase that is necessary for the catabolism of rhamnose. This has led to a working hypothesis that RhaK has two biochemical functions: phosphorylation of its substrate and affecting the activity of the rhamnose ABC transporter. To address this hypothesis, a linker-scanning random mutagenesis of rhaK was carried out. Thirty-nine linker-scanning mutations were generated and mapped. Alleles were then systematically tested for their ability to physiologically complement kinase and transport activity in a strain carrying an rhaK mutation. The rhaK alleles generated could be divided into three classes: mutations that did not affect either kinase or transport activity, mutations that eliminated both transport and kinase activity, and mutations that affected transport activity but not kinase activity. Two genes of the last class (rhaK72 and rhaK73) were found to have similar biochemical phenotypes but manifested different physiological phenotypes. Whereas rhaK72 conferred a slow-growth phenotype when used to complement rhaK mutants, the rhaK73 allele did not complement the inability to use rhamnose as a sole carbon source. To provide insight to how these insertional variants might be affecting rhamnose transport and catabolism, structural models of RhaK were generated based on the crystal structure of related sugar kinases. Structural modeling suggests that both rhaK72 and rhaK73 affect surface-exposed residues in two distinct regions that are found on one face of the protein, suggesting that this protein's face may play a role in protein-protein interaction that affects rhamnose transport.
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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 | 0.000 |
| 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".