Selective inhibition of NikA mediated Ni(II) import in <i>E. coli</i> by the Indium(III)-EDTA complex
Bibliographic record
Abstract
Nickel is a required nutrient for bacteria to produce [NiFe]-hydrogenase and urease enzymes. [NiFe]-hydrogenase catalyzes the reversible conversion of hydrogen into protons and electrons and urease catalyzes the hydrolysis of urea into carbon dioxide and ammonia-both key in bacterial pathogenesis. As such, nickel trafficking and homeostasis are interesting targets for potential antibacterial strategies. In E. coli, NikA binds a Ni(II)-(L-His)2 chelate in the periplasm and delivers this complex to the NikBCDE transporter. Blocking Ni(II) uptake by NikA would prevent the biosynthesis of active [NiFe]-hydrogenase. Fe(III)-EDTA is a potent ligand for NikA, however due to the potential for reduction of Fe(III) to Fe(II), it has limited utility. Using Fe(III)-EDTA as a starting point for inhibitor design, similar stable complexes of Bismuth(III), Lutetium(III) and Indium(III) were investigated. The In(III)-EDTA complex is a potent inhibitor of cellular [NiFe]-hydrogenase activity (IC50 of 600 μM ± 100 μM) while being nontoxic to bacterial growth. The mechanism of In(III)-EDTA hydrogenase inhibition was confirmed by the inhibition of Ni(II)-dependent processing of HycE (hydrogenase-3), which could be rescued with the addition of exogenous nickel. To elucidate the binding affinity of In(III)-EDTA to NikA, isothermal titration calorimetry (ITC) was carried out, revealing stoichiometric 1:1 binding with a Kd of 17.3 µM ± 3.0 µM. Indium concentrations determined by inductively coupled plasma mass spectrometry in E. coli cells in the presence or absence of NikA showed no discernable difference, further supporting the competitive inhibition of nickel uptake by blocking NikA.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".