Ethanol stimulates trehalose production through a SpoT-DksA-AlgU dependent pathway in <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
Abstract Pseudomonas aeruginosa frequently resides among ethanol-producing microbes, making its response to these microbially-produced concentrations of ethanol relevant to understanding its biology. Our ranscriptome analysis found that the genes involved in trehalose metabolism were induced by low concentrations of ethanol, and levels of intracellular trehalose increased significantly upon growth with ethanol. The increase in trehalose was dependent on the TreYZ pathway, but not other trehalose metabolic enzymes TreS or TreA. The sigma factor AlgU (AlgT), a homolog of RpoE in other species, was required for increased expression of the treZ gene and trehalose levels, but induction was not controlled by the well-characterized proteolysis of its antisigma factor MucA. Growth with ethanol led to increased SpoT-dependent (p)ppGpp accumulation, which stimulates AlgU-dependent transcription of treZ and other AlgU-regulated genes through DksA, a (p)ppGpp and RNA polymerase binding protein. Ethanol stimulation of trehalose also required acylhomoserine lactone (AHL)-mediated quorum sensing, as induction was not observed in a Δ lasR Δ rhlR strain. A network analysis using a model, eADAGE, built from publicly available P. aeruginosa transcriptome datasets (1) provided strong support for our model that treZ and co-regulated genes are controlled by both AlgU and AHL-mediated QS (QS). Consistent with (p)ppGpp and AHL-mediated quorum sensing regulation, ethanol, even when added at the time of culture inoculation, stimulated treZ transcript levels and trehalose production in cells from post-exponential phase cultures but not from exponential phase cultures. These data highlight the integration of growth and cell density cues in the P. aeruginosa transcriptional response to ethanol. Importance Pseudomonas aeruginosa is often found with bacteria and fungi that produce fermentation products including ethanol. At concentrations similar to those produced by environmental microbes, we found that ethanol stimulated expression of trehalose biosynthetic genes and cellular levels of trehalose, a disaccharide that protects against environmental stresses. The induction of trehalose by ethanol required the alternative sigma factor AlgU through DksA and SpoT-dependent (p)ppGpp. Trehalose accumulation also required AHL quorum sensing and only occurred in post-exponential phase cultures. This work highlights how cells integrate cell-density and growth cues in their responses to products made by other microbes and a reveals a new role for (p)ppGpp in the regulation of AlgU activity.
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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 | 0.001 |
| 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 | 0.001 |
| 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".