Sequestration of the phagocyte metabolite itaconate by Pseudomonas aeruginosa RpoN promotes successful pulmonary infection
Bibliographic record
Abstract
Inhaled opportunistic pathogens such as Pseudomonas aeruginosa actively modify gene expression to meet the challenges of a new environment. In the infected airway the bacteria must respond to the immunometabolite itaconate, which is abundantly produced by macrophages and has anti-inflammatory and anti-oxidant functions that protect the host from airway damage and causes toxicity to bacteria. As a dicarboxylate that targets cysteine residues, itaconate can modify both bacterial and host proteins often altering metabolic activity. We demonstrate that itaconate promotes a global metabolic response in P. aeruginosa by enhancing the activity of the major alternative transcription factor RpoN. Itaconate is actively transported into the bacteria, induces σ54 rpoN expression and covalently binds cysteine residues 218 and 275 on RpoN helping to neutralize its toxicity. The S-itaconated RpoN exhibits a gain of function driving increased glucose catabolism and enhanced utilization of the bioenergetically efficient Entner–Doudoroff pathway. Thus, the accumulation of itaconate in the infected airway promotes the adaptation of P. aeruginosa to the lung by optimizing its metabolic activity and ability to cause pneumonia. Itaconate is an airway metabolite released by phagocytes in response to infection. Here, the authors show that itaconate acts as a signal to simulate the adaptation of Pseudomonas aeruginosa to the lung by modifying RpoN through S-itaconation.
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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".