Klebsiella pneumoniae Yersiniabactin Promotes Respiratory Tract Infection through Evasion of Lipocalin 2
Bibliographic record
Abstract
Klebsiella pneumoniae is a pathogen of increasing concern because of multidrug resistance, especially due to K. pneumoniae carbapenemases (KPCs). K. pneumoniae must acquire iron to replicate, and it utilizes iron-scavenging siderophores, such as enterobactin (Ent). The innate immune protein lipocalin 2 (Lcn2) is able to specifically bind Ent and disrupt iron acquisition. To determine whether K. pneumoniae must produce Lcn2-resistant siderophores to cause disease, we examined siderophore production by clinical isolates (n = 129) from respiratory, urine, blood, and stool samples and by defined siderophore mutants through genotyping and liquid chromatography-mass spectrometry. Three categories of K. pneumoniae isolates were identified: enterobactin positive (Ent(+)) (81%), enterobactin and yersiniabactin positive (Ent(+) Ybt(+)) (17%), and enterobactin and salmochelin (glycosylated Ent) positive (Ent(+) gly-Ent(+)) with or without Ybt (2%). Ent(+) Ybt(+) strains were significantly overrepresented among respiratory tract isolates (P = 0.0068) and β-lactam-resistant isolates (P = 0.0019), including the epidemic KPC-producing clone multilocus sequence type 258 (ST258). In ex vivo growth assays, gly-Ent but not Ybt allowed evasion of Lcn2 in human serum, whereas siderophores were dispensable for growth in human urine. In a murine pneumonia model, an Ent(+) strain was an opportunistic pathogen that was completely inhibited by Lcn2 but caused severe, disseminated disease in Lcn2(-/-) mice. In contrast, an Ent(+) Ybt(+) strain was a frank respiratory pathogen, causing pneumonia despite Lcn2. However, Lcn2 retained partial protection against disseminated disease. In summary, Ybt is a virulence factor that is prevalent among KPC-producing K. pneumoniae isolates and promotes respiratory tract infections through evasion of Lcn2.
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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) | 0.002 | 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".