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<i>Pseudomonas aeruginosa</i> produces an extracellular deoxyribonuclease that is required for utilization of DNA as a nutrient source

2010· article· en· W1989728732 on OpenAlexaff
Heidi Mulcahy, Laetitia Charron‐Mazenod, Shawn Lewenza

Bibliographic record

VenueEnvironmental Microbiology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiologyPseudomonas aeruginosaExtracellularDeoxyribonucleaseDNAMicrobiologyDeoxyribonuclease IBiofilmBiochemistryBacteriaGenetics

Abstract

fetched live from OpenAlex

Pseudomonas aeruginosa is an opportunistic pathogen that occupies a wide variety of environmental niches. Extracellular DNA is ubiquitous in various environments and is a rich source of carbon, nitrogen and phosphate. Here we show that P. aeruginosa is capable of using DNA as a nutrient source. Under phosphate-limiting conditions, or when DNA is supplied as a source of phosphate, expression of PA3909 is induced. PA3909 encodes an extracellular deoxyribonuclease (DNase), which is required for degradation of DNA and utilization of DNA as a source of carbon, nitrogen and phosphate. Stabilization of PA3909 by the addition of excess Mg(2+) and Ca(2+) was required for DNase activity in culture supernatants. Extracellular DNase activity was seen in multiple P. aeruginosa strains and isolates from cystic fibrosis patients. The primary Xcp type II secretion system but not the Hxc type II secretion system is required for DNase activity and the ability to use DNA as a source of nutrients. This study identifies an extracellular DNase produced by P. aeruginosa that enables degradation of extracellular DNA into an accessible source of carbon, nitrogen and phosphate. DNase production by P. aeruginosa also has important implications for virulence and biofilm formation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.149
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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 teacher head, 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

Citations165
Published2010
Admission routes1
Has abstractyes

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