Hemoglobin Binding and Catalytic Heme Extraction by IsdB Near Iron Transporter Domains
Bibliographic record
Abstract
The Isd (iron-regulated surface determinant) system is a multiprotein transporter that allows bacterium Staphylococcus aureus to take up iron from hemoglobin (Hb) during human infection. In this system, IsdB is a cell wall-anchored surface protein that contains two near iron transporter (NEAT) domains, one of which binds heme. IsdB rapidly extracts heme from Hb and transfers it to IsdA for relay into the bacterial cell. Using a series of recombinant IsdB constructs that included at least one NEAT domain, we demonstrated that both domains are required to bind Hb with high affinity (KD = 0.42 ± 0.05 μM) and to extract heme from Hb. Moreover, IsdB extracted heme only from oxidized metHb, although it also bound oxyHb and the Hb-CO complex. In a reconstituted model of the biological heme relay pathway, IsdB catalyzed the transfer of heme from metHb to IsdA with a Km for metHb of 0.75 ± 0.07 μN and a kcat of 0.22 ± 0.01 s(-1). The latter is consistent with the transfer of heme from metHb to IsdB being the rate-limiting step. With both NEAT domains and the linker region present in a single contiguous polypeptide, high-affinity Hb binding was achieved, rapid heme uptake was observed, and multiple turnovers of heme extraction from metHb and transfer to IsdA were conducted, representing all known Hb-heme uptake functions of the full-length IsdB protein.
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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".