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Record W2954088709 · doi:10.14288/1.0379720

The regulation and characterization of surfing motility in Pseudomonas aeruginosa

2019· article· en· W2954088709 on OpenAlexaff
Evelyn Sun

Bibliographic record

VenuecIRcle (University of British Columbia) · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPseudomonas aeruginosaMotilityBiologyChemistryMicrobiologyBacteriaCell biologyGenetics

Abstract

fetched live from OpenAlex

Pseudomonas aeruginosa is an opportunistic pathogen associated with a high incidence of infections in hospitalized and cystic fibrosis (CF) patients. P. aeruginosa is highly adaptable and exhibits diverse lifestyle adaptations depending on its surrounding environment. Here I studied a complex motility lifestyle termed surfing that occurs in the presence of mucin, a glycoprotein that is found in large abundance in the CF lung, and showed that surfing was associated with broad-spectrum antibiotic resistance, conserved in several bacterial species, and regulated by a complex networks of regulators. RNA-Seq revealed ~1,024 genes dysregulated in P. aeruginosa under surfing conditions, while a screen of the PA14 transposon mutant library revealed 192 mutants that exhibited surfing deficiency, 40 of which were regulatory genes, including the putative chemotaxis regulator, PA1463, and two-component regulator, pfeR. Both PA1463 and pfeR were found to be master regulators of P. aeruginosa surfing and mutants in these genes demonstrated dysregulation of the majority of other regulators influencing surfing. Using disk diffusion assays, I investigated the adaptive antibiotic resistance associated with surfing motility. P. aeruginosa surfing cells were significantly more resistant to several antibiotics including all tested aminoglycosides, carbapenems, polymyxins, fluoroquinolones, and trimethoprim, tetracycline, and chloramphenicol. To identify the genes mediating surfing-dependent antibiotic resistance, transposon mutants in antibiotic susceptibility genes that were dysregulated under surfing conditions were screened for altered susceptibility under surfing conditions. This revealed 65 mutants, including mutants in armR, recG, atpB, clpS, nuoB, that exhibited changes in susceptibility to one or more antibiotics, consistent with a contribution to the observed adaptive resistance. It was further demonstrated that other motile bacterial species, including Escherichia coli, Salmonella enterica, Vibrio harveyi, Enterobacter cloacae, Proteus mirabilis, and Bacillus subtilis, exhibited similar characteristics of surfing as observed for P. aeruginosa in the presence of mucin, including rapid surface growth, dependence on flagella, and broad- spectrum adaptive resistance. Therefore, surfing is a conserved motile lifestyle regulated by complex networks of regulators and leads to broad spectrum adaptive antibiotic resistance.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.159
Teacher spread0.155 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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