Protein‐Protein Interactions in Nickel Acquisition of <i>Escherichia coli</i>
Bibliographic record
Abstract
Nickel is a required cofactor for [NiFe]‐hydrogenase, an enzyme involved in bacterial metabolism and pathogenesis.1 Due to the toxicity of nickel,2 bacteria need to control its uptake and distribution intracellularly.3 In Escherichia coli , control of intracellular nickel is achieved by nickel uptake by membrane transporters and nickel delivery to the correct destinations by metallochaperone proteins; however, it is not clear how these two systems are linked. Previous results suggested that there is an interaction between the nickel metallochaperone HypB and a nucleotide binding domain of Nik transporter NikE. This protein‐protein interaction would support the hypothesis that HypB, a key protein in nickel delivery to the [NiFe]‐hydrogenase precursor protein, receives nickel directly from the Nik transporter. In the present work, the NikE‐HypB interaction is examined under various nucleotide‐loaded and metal‐loaded states of HypB. Support or Funding Information This work was supported in part by funding from NSERC and CIHR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".