Acinetobacter baumannii can use multiple siderophores for iron acquisition, but only acinetobactin is required for virulence
Bibliographic record
Abstract
Acinetobacter baumannii is an emerging pathogen that poses a global health threat due to a lack of therapeutic options for treating drug-resistant strains. In addition to acquiring resistance to last-resort antibiotics, the success of A. baumannii is partially due to its ability to effectively compete with the host for essential metals. Iron is fundamental in shaping host-pathogen interactions, where the host restricts availability of this nutrient in an effort to curtail bacterial proliferation. To circumvent restriction, pathogens possess numerous mechanisms to obtain iron, including through the use of iron-scavenging siderophores. A. baumannii elaborates up to ten distinct siderophores, encoded from three different loci: acinetobactin and pre-acinetobactin (collectively, acinetobactin), baumannoferrins A and B, and fimsbactins A-F. The expression of multiple siderophores is common amongst bacterial pathogens and often linked to virulence, yet the collective contribution of these siderophores to A. baumannii survival and pathogenesis has not been investigated. Here we begin dissecting functional redundancy in the siderophore-based iron acquisition pathways of A. baumannii. Excess iron inhibits overall siderophore production by the bacterium, and the siderophore-associated loci are uniformly upregulated during iron restriction in vitro and in vivo. Further, disrupting all of the siderophore biosynthetic pathways is necessary to drastically reduce total siderophore production by A. baumannii, together suggesting a high degree of functional redundancy between the metabolites. By contrast, inactivation of acinetobactin biosynthesis alone impairs growth on human serum, transferrin, and lactoferrin, and severely attenuates survival of A. baumannii in a murine bacteremia model. These results suggest that whilst A. baumannii synthesizes multiple iron chelators, acinetobactin is critical to supporting growth of the pathogen on host iron sources. Given the acinetobactin locus is highly conserved and required for virulence of A. baumannii, designing therapeutics targeting the biosynthesis and/or transport of this siderophore may represent an effective means of combating this pathogen.
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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".