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Record W2155097679 · doi:10.1186/1471-2180-13-175

Spatial distributions of Pseudomonas fluorescens colony variants in mixed-culture biofilms

2013· article· en· W2155097679 on OpenAlexafffund
Matthew L. Workentine, Siyuan Wang, Howard Ceri, Raymond J. Turner

Bibliographic record

VenueBMC Microbiology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche Médicale
KeywordsBiofilmBiologyPseudomonas fluorescensWild typePhenotypeColonizationMicrobiologyColony morphologyMutantGeneticsBacteriaGene

Abstract

fetched live from OpenAlex

BACKGROUND: The emergence of colony morphology variants in structured environments is being recognized as important to both niche specialization and stress tolerance. Pseudomonas fluorescens demonstrates diversity in both its natural environment, the rhizosphere, and in laboratory grown biofilms. Sub-populations of these variants within a biofilm have been suggested as important contributors to antimicrobial stress tolerance given their altered susceptibility to various agents. As such it is of interest to determine how these variants might be distributed in the biofilm environment. RESULTS: Here we present an analysis of the spatial distribution of Pseudomonas fluorescens colony morphology variants in mixed-culture biofilms with the wildtype phenotype. These findings reveal that two variant colony morphotypes demonstrate a significant growth advantage over the wildtype morphotype in the biofilm environment. The two variant morphotypes out-grew the wildtype across the entire biofilm and this occurred within 24 h and was maintained through to 96 h. This competitive advantage was not observed in homogeneous broth culture. CONCLUSIONS: The significant advantage that the variants demonstrate in biofilm colonization over the wildtype denotes the importance of this phenotype in structured environments.

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 score0.067
Threshold uncertainty score0.641

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 head0.007
GPT teacher head0.216
Teacher spread0.208 · 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

Citations11
Published2013
Admission routes2
Has abstractyes

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