Iron acquisition by the haem-binding Isd proteins in <i>Staphylococcus aureus</i>: studies of the mechanism using magnetic circular dichroism
Bibliographic record
Abstract
The bacterium Staphylococcus aureus is responsible for numerous hospital-acquired infections ranging from superficial wound lesions to more severe infections such as pneumonia, osteomyelitis and septicaemia and, in some cases, death. The Isd (iron-regulated surface determinant) proteins expressed by S. aureus and select other bacteria are anchored to the bacterial cell wall and membrane and are involved in extracting haem from haemoglobin as an iron source. Our knowledge of the overall haem-scavenging mechanism on the bacterial surface is limited. A detailed description of the haem-binding properties in the transport pathway is critical to our understanding of the mechanism for haem-iron scavenging in S. aureus. Our work involves using a combination of techniques to characterize both the dynamic and steady-state haem-binding properties of these proteins. UV-visible absorption and MCD (magnetic circular dichroism) spectroscopy provide diagnostic spectral data sensitive to the axial ligands, the spin state and oxidation state of the central haem-iron. Electrospray MS provides stoichiometric information on the numbers of haems bound, the effect of haem binding on the overall folding of each protein and kinetic information about the rate of haem binding. Together, these data allow us to address the outstanding questions regarding the mechanism of haem transport via the Isd protein chain in S. aureus.
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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) | 0.000 | 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".