Determination of the Essentiality of the Eight Cysteine Residues of the NrtA Protein for High-Affinity Nitrate Transport and the Generation of a Functional Cysteine-less Transporter
Bibliographic record
Abstract
All eight cysteine residues, C90, C94, C143, C147, C219, C325, C367, and C431, present in transmembrane domains of the Aspergillus nidulans NrtA nitrate transporter protein were altered individually by site-specific mutagenesis. The results indicate that six residues, C90, C147, C219, C325, C367, and C431, are not required for nitrate transport. Although alterations of C94 and C143 are less well tolerated, these residues are not mandatory and their possible role is discussed. A series of constructs, all completely devoid of cysteine residues, was generated to permit future cysteine-scanning mutagenesis. The optimum cysteine-less combination was identified as C90A, C94A, C143A, C147T, C219S, C325S, C367S, and C431S. This mutant combination yielded transformant strains with up to 40% of wild-type nitrate transport activity. Furthermore, the K(m) value and the level of protein expression were found to be similar to those of the wild-type. This cysteine-less vector should allow us to investigate in detail potentially interesting NrtA amino acids (e.g. identified from homology comparisons) which may be involved in transport, by altering these singly to cysteine and studying such residues by thiol chemistry.
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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) | 0.001 | 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".