FhuD1, a Ferric Hydroxamate-binding Lipoprotein in Staphylococcus aureus
Bibliographic record
Abstract
Staphylococcus aureus can utilize ferric hydroxamates as a source of iron under iron-restricted growth conditions. Proteins involved in this transport process are: FhuCBG, which encodes a traffic ATPase; FhuD2, a post-translationally modified lipoprotein that acts as a high affinity receptor at the cytoplasmic membrane for the efficient capture of ferric hydroxamates; and FhuD1, a protein with similarity to FhuD2. Gene duplication likely gave rise to fhuD1 and fhuD2. While the genomic locations of fhuCBG and fhuD2 in S. aureus strains are conserved, both the presence and the location of fhuD1 are variable. The apparent redundancy of FhuD1 led us to examine the role of this protein. We demonstrate that FhuD1 is expressed only under conditions of iron limitation through the regulatory activity of Fur. FhuD1 fractions with the cell membrane and binds hydroxamate siderophores but with lower affinity than FhuD2. Using small angle x-ray scattering, the solution structure of FhuD1 resembles that of FhuD2, and only a small conformational change is associated with ferrichrome binding. FhuD1, therefore, appears to be a receptor for ferric hydroxamates, like FhuD2. Our data to date suggest, however, that FhuD1 is redundant to FhuD2 and plays a minor role in hydroxamate transport. However, given the very real possibility that we have not yet identified the proper conditions where FhuD1 does provide an advantage over FhuD2, we anticipate that FhuD1 serves an enhanced role in the transport of untested hydroxamate siderophores and that it may play a prominent role during the growth of S. aureus in its natural environments.
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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 | 0.001 | 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".