<i>Salmonella</i> Rapidly Regulates Membrane Permeability To Survive Oxidative Stress
Bibliographic record
Abstract
UNLABELLED: The outer membrane (OM) of Gram-negative bacteria provides protection against toxic molecules, including reactive oxygen species (ROS). Decreased OM permeability can promote bacterial survival under harsh circumstances and protects against antibiotics. To better understand the regulation of OM permeability, we studied the real-time influx of hydrogen peroxide in Salmonella bacteria and discovered two novel mechanisms by which they rapidly control OM permeability. We found that pores in two major OM proteins, OmpA and OmpC, could be rapidly opened or closed when oxidative stress is encountered and that the underlying mechanisms rely on the formation of disulfide bonds in the periplasmic domain of OmpA and TrxA, respectively. Additionally, we found that a Salmonella mutant showing increased OM permeability was killed more effectively by treatment with antibiotics. Together, these results demonstrate that Gram-negative bacteria regulate the influx of ROS for defense against oxidative stress and reveal novel targets that can be therapeutically targeted to increase bacterial killing by conventional antibiotics. IMPORTANCE: Pathogenic bacteria have evolved ways to circumvent inflammatory immune responses. A decrease in bacterial outer membrane permeability during infection helps protect bacteria from toxic molecules produced by the host immune system and allows for effective colonization of the host. In this report, we reveal molecular mechanisms that rapidly alter outer membrane pores and their permeability in response to hydrogen peroxide and oxidative stress. These mechanisms are the first examples of pores that are rapidly opened or closed in response to reactive oxygen species. Moreover, one of these mechanisms can be targeted to artificially increase membrane permeability and thereby increase bacterial killing by the antibiotic cefotaxime during in vitro experiments and in a mouse model of infection. We envision that a better understanding of the regulation of membrane permeability will lead to new targets and treatment options for multidrug-resistant infections.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".