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Record W2124299428 · doi:10.1093/infdis/jit817

IsdB-dependent Hemoglobin Binding Is Required for Acquisition of Heme by Staphylococcus aureus

2013· article· en· W2124299428 on OpenAlexaff
Gleb Pishchany, Jessica R. Sheldon, Claire F. Dickson, Md Tauqeer Alam, Timothy D. Read, David A. Gell, David E. Heinrichs, Eric P. Skaar

Bibliographic record

VenueThe Journal of Infectious Diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsWestern University
FundersNational Institute of Allergy and Infectious Diseases
KeywordsHemoglobinHemeStaphylococcus aureusMicrobiologyBiochemistryBiologyChemistryBacteriaEnzymeGenetics

Abstract

fetched live from OpenAlex

Staphylococcus aureus is a Gram-positive pathogen responsible for tremendous morbidity and mortality. As with most bacteria, S. aureus requires iron to cause disease, and it can acquire iron from host hemoglobin. The current model for staphylococcal hemoglobin-iron acquisition proposes that S. aureus binds hemoglobin through the surface-exposed hemoglobin receptor IsdB. IsdB removes heme from bound hemoglobin and transfers this cofactor to other proteins of the Isd system, which import and degrade heme to release iron in the cytoplasm. Here we demonstrate that the individual components of the Isd system are required for growth on low nanomolar concentrations of hemoglobin as a sole source of iron. An in-depth study of hemoglobin binding by IsdB revealed key residues that are required for hemoglobin binding. Further, we show that these residues are necessary for heme extraction from hemoglobin and growth on hemoglobin as a sole iron source. These processes are found to contribute to the pathogenicity of S. aureus in a murine model of infection. Together these results build on the model for Isd-mediated hemoglobin binding and heme-iron acquisition during the pathogenesis of S. aureus infection.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.286
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations89
Published2013
Admission routes1
Has abstractyes

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