Swarming motility in Pseudomonas aeruginosa : a complex adaptation with implications for antibiotic resistance and virulence
Bibliographic record
Abstract
Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen that possesses intrinsic antibiotic resistance. Highly adaptable, P. aeruginosa is capable of different forms of motility, including swarming, swimming, twitching and surfing. Swarming motility is a multicellular movement of cells across semisolid surfaces that is associated with complex adaptations including adaptive antibiotic resistance. Here a disc diffusion assay showed that swarming bacteria were resistant to multiple antibiotics, including aminoglycosides, β-lactams, chloramphenicol, ciprofloxacin, macrolides, tetracycline, and trimethoprim. RNA-Seq of swarming cells showed the dysregulation of 1,581 genes, including 104 regulatory factors, upregulated virulence and iron acquisition factors, and downregulated ribosomal genes. Forty-one mutants resistant to tobramycin under swarming conditions were found, including prtN, a regulator of pyocin, and wbpW, involved in LPS biosynthesis. RNA-Seq of swarming cells treated with tobramycin revealed the upregulation of the multidrug efflux pump mexXY. To investigate the role of swarming in vivo, a screen for swarming-specific mutants was performed, revealing ptsP, a regulator of carbon and nitrogen metabolism. The ∆ptsP mutant was deficient specifically in swarming but not swimming or twitching motility. Interestingly, ∆ptsP also had greatly reduced organ invasion in a mouse infection model, suggesting a likely role for swarming in vivo. Besides ptsP, small RNAs also regulated swarming motility, typically via post-transcriptional means. A screen of sRNA overexpressing strains revealed an sRNA, PA0805.1 that influenced diverse bacterial behaviours including swarming, swimming, twitching, cytotoxicity, adherence and tobramycin resistance. RNA-Seq and proteomics uncovered a broad regulatory profile with 1,121 differentially expressed genes and 925 proteins, including 118 regulatory factors, downregulated pilus genes, upregulated adherence and virulence factors, and upregulated multidrug efflux systems including mexXY and mexGHI-opmD. Another sRNA, PA2952.1, when overexpressed influenced swarming, swimming, and tobramycin, gentamicin and trimethoprim resistance. Transcriptomics and proteomics showed differential abundance of 784 genes and 445 proteins, encompassing 82 regulatory factors, downregulated pili, dysregulated flagellar genes, upregulated mexGHI-opmD and the upregulated arn operon involved in LPS modification. Overall this thesis has shown that swarming motility is a complex adaptation conferring multiple antibiotic resistance, that is regulated by sRNAs and coupled to virulence adaptations in vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.000 | 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".