Multiprotein Heme Shuttle Pathway in <i>Staphylococcus aureus</i>: Iron-Regulated Surface Determinant Cog-Wheel Kinetics
Bibliographic record
Abstract
Iron is a critically important nutrient for all species. Bacteria have evolved specialist survival systems to chelate and transport iron across the wall and membrane into the cytoplasm. One such system in the human pathogenic bacteria Staphylococcus aureus involves extracting heme from hemoglobin and then transporting the intact heme across the wall and membrane. The iron-regulated surface determinant (Isd) proteins act in concert to carry out the heme scavenging and subsequent transport. While details of the static heme-binding reaction are currently quite well known, little mechanistic data are available. In this paper, we describe detailed time-resolved mass spectral and magnetic circular dichroism spectral data recorded as heme is transferred unidirectionally from holo-IsdA to apo-IsdE via IsdC. The electrospray mass spectral data simultaneously monitor the concentrations of six protein species involved in the trans-wall transport of the extracted heme and show for the first time the mechanistic details of heme transfer that is key to the Staphylococcus aureus Isd heme-scavenging system. Bimolecular kinetic analysis of the ESI-mass spectral data shows that heme transfer from IsdA to IsdC is very fast, whereas the subsequent heme transfer from IsdC to IsdE is slower. Under limiting IsdC conditions, the IsdC intermediary cycles between heme-free and heme-containing forms until either all heme has been transferred from holo-IsdA or no further apo-IsdE is available. The data show that a unique role for IsdC is acting as the central cog-wheel that facilitates heme transfer from IsdA to IsdE.
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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) | 0.001 | 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".