In vivo growth of Staphylococcus lugdunensis is facilitated by the concerted function of heme and non-heme iron acquisition mechanisms
Bibliographic record
Abstract
Staphylococcus lugdunensis has increasingly been recognized as a pathogen that can cause serious infection indicating this bacterium overcomes host nutritional immunity. Despite this, there exists a significant knowledge gap regarding the iron acquisition mechanisms employed by S. lugdunensis, especially during infection of the mammalian host. Here we show that S. lugdunensis can usurp hydroxamate siderophores and staphyloferrin A and B from Staphylococcus aureus. These transport activities all required a functional FhuC ATPase. Moreover, we show that the acquisition of catechol siderophores and catecholamine stress hormones by S. lugdunensis required the presence of the sst-1 transporter-encoding locus, but not the sst-2 locus. Iron-dependent growth in acidic culture conditions necessitated the ferrous iron transport system encoded by feoAB. Heme iron was acquired via expression of the iron-regulated surface determinant (isd) locus. During systemic infection of mice, we demonstrated that while S. lugdunensis does not cause overt illness, it does colonize and proliferate to high numbers in the kidneys. By combining mutations in the various iron acquisition loci (isd, fhuC, sst-1, and feo), we demonstrate that only a strain deficient for all of these systems was attenuated in its ability to proliferate to high numbers in the murine kidney. We propose the concerted action of heme and non-heme iron acquisition systems also enable S. lugdunensis to cause human infection.
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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".