pH-Responsive DNA-Binding Activity of Helicobacter pylori NikR
Bibliographic record
Abstract
Helicobacter pylori NikR (HpNikR) is a nickel-responsive transcription factor. In addition to a role in nickel homeostasis, HpNikR is proposed to serve as a master activator-repressor for H. pylori acid adaptation by directly or indirectly regulating the expression of a battery of genes. One potential mechanism of this regulation is modulation of the DNA-binding activity of HpNikR by the decrease in internal pH that occurs upon exposure to acidic shock. To test this hypothesis, several properties of HpNikR were investigated under acidic conditions. At pH 5.8, the secondary and quaternary structures of the protein are not affected, and it still binds stoichiometric nickel in the same site, although with a slightly weaker affinity than that at pH 7.6. DNA-binding assays performed at pH 5.8 reveal that, in contrast to pH 7.6, HpNikR binds to the ureA promoter in a nickel-independent fashion. Binding to the nikR promoter at the lower pH is nickel dependent, however. Deletion of amino acids 3-11 of HpNikR abolished the nickel-responsive activity and enhanced nonspecific DNA binding. Site-directed mutagenesis of HpNikR indicates that either Asp7 or Asp8 in the N-terminus of HpNikR plays a part in the activation of DNA binding. Furthermore, Lys6 contributes selectively to complex formation with the nikR promoter sequence. The direct influence of pH on the activity of HpNikR may be critical to the role of this activator-repressor in the viability of H. pylori.
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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) | 0.002 | 0.001 |
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".