Kinetic Analyses Reveal Multiple Steps in Forming TonB−FhuA Complexes from <i>Escherichia coli</i>
Bibliographic record
Abstract
FhuA, an outer membrane receptor of Escherichia coli, facilitates transport of hydroxamate siderophores and siderophore-antibiotic conjugates. The cytoplasmic membrane complex TonB-ExbB-ExbD provides energy for transport via the proton motive force. This energy is transduced by protein-protein interactions between TonB and FhuA, but the molecular determinants of these interactions remain uncharacterized. Our analyses of FhuA and two recombinant TonB species by surface plasmon resonance revealed that TonB undergoes a kinetically limiting rearrangement upon initial interaction with FhuA: an intermediate TonB-FhuA complex of 1:1 stoichiometry was detected. The intermediate then recruits a second TonB protein. Addition of ferricrocin, a FhuA-specific ligand, enhanced amounts of the 2:1 complex but was not essential for its formation. To assess the role of the cork domain of FhuA in forming a 2:1 TonB-FhuA complex, we tested a FhuA deletion (residues 21-128) for its ability to interact with TonB. Analytical ultracentrifugation demonstrated that deletion of this region of the cork domain resulted in a 1:1 complex. Furthermore, the high-affinity 2:1 complex requires the N-terminal region of TonB. Together these in vitro experiments establish that TonB-FhuA interactions require sequential steps of kinetically limiting rearrangements. Additionally, domains that contribute to complex formation were identified in TonB and in FhuA.
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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 | 0.001 |
| 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 | 0.000 |
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".