Biochemical studies highlight determinants for metal selectivity in the <i>Escherichia coli</i> periplasmic solute binding protein NikA
Bibliographic record
Abstract
Nickel is an essential micronutrient for the survival of many microbes. On account of the toxicity of nickel and its scarcity in the environment, microbes have evolved specific systems for uptaking and delivering nickel to enzymes. NikA, the solute binding protein for the ATP-binding cassette (ABC) importer NikABCDE, plays a vital role in the nickel homeostasis of Escherichia coli by selectively binding nickel over other metals in the metabolically complex periplasm. While the endogenous ligand for NikA is known to be the Ni(II)-(L-His)2 complex, the molecular basis by which NikA selectively binds Ni(II)-(L-His)2 is unclear, especially considering that NikA can bind multiple metal-based ligands with comparable affinity. Here we show that, regardless of its promiscuous binding activity, NikA preferentially interacts with Ni(II)-(L-His)2, even over other metal-amino acid ligands with an identical coordination geometry for the metal. Replacing both the Ni(II) and the L-His residues in Ni(II)-(L-His)2 compromises binding of the ligand to NikA, in part because these alterations affect the degree by which NikA closes around the ligand. Replacing H416, the only NikA residue that ligates the Ni(II), with other potential metal-coordinating amino acids decreases the binding affinity of NikA for Ni(II)-(L-His)2 and compromises uptake of Ni(II) into E. coli cells, likely due to altered metal selectivity of the NikA mutants. Together, the biochemical and in vivo studies presented here define key aspects of how NikA selects for Ni(II)-(L-His)2 over other metal complexes, and can be used as a reference for studies into the metal selectivity of other microbial solute binding proteins.
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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".