Extracellular products-mediated interspecific interaction between Pseudomonas aeruginosa and Escherichia coli
Bibliographic record
Abstract
The Gram-negative pathogen Pseudomonas aeruginosa adopts several elaborate strategies to colonize a wide range of natural or clinical niches and to overcome the neighboring bacterial competitors in polymicrobial communities. However, the relationship and interaction mechanism of P. aeruginosa with other bacterial pathogens remains largely unexplored. Here we explore the interaction dynamics of P. aeruginosa and Escherichia coli, which frequently coinfect the lungs of immunocompromised hosts, by using a series of on-plate proximity assays and RNA-sequencing. We show that the extracellular products of P. aeruginosa can inhibit the growth of neighboring E. coli and induce a large-scale of transcriptional reprogramming of E. coli, especially in terms of cellular respiration-related primary metabolisms and membrane components. In contrast, the presence of E. coli has no significant effect on the growth of P. aeruginosa in short-term culture, but causes a dysregulated expression of genes positively controlled by the quorum-sensing (QS) system of P. aeruginosa during subsequent pairwise culture. We further demonstrate that the divergent QS-regulation of P. aeruginosa may be related to the function of the transcriptional regulator PqsR, which can be enhanced by E. coli culture supernatant to increase the pyocyanin production by P. aeruginosa in the absence of the central las-QS system. Moreover, the extracellular products of E. coli promote the proliferation and lethality of P. aeruginosa in infecting the Caenorhabditis elegans model. The current study provides a general characterization of the extracellular products-mediated interactions between P. aeruginosa and E. coli, and may facilitate the understanding of polymicrobial 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 | 0.001 |
| 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".