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Record W2438113208 · doi:10.1111/gtc.12383

Cyclophilin PpiB is involved in motility and biofilm formation via its functional association with certain proteins

2016· article· en· W2438113208 on OpenAlexfundno aff
Aggeliki Skagia, Chrysoula Zografou, Eleni Vezyri, Anastasia Venieraki, Panagiotis Katinakis, Maria Dimou

Bibliographic record

VenueGenes to Cells · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsnot available
FundersInstitute of GeneticsKeio University
KeywordsBiologyMotilityCyclophilin ABiofilmCyclophilinMicrobiologyCell biologyBacteriaBiochemistryGeneticsMolecular biologyGene

Abstract

fetched live from OpenAlex

PpiB belongs to the superfamily of peptidyl-prolyl cis/trans isomerases (PPIases, EC: 5.2.1.8), which catalyze the rate-limiting protein folding step at peptidyl-prolyl bonds and control several biological processes. In this study, we show that PpiB acts as a negative effector of motility and biofilm formation ability of Escherichia coli. We identify multicopy suppressors of each ΔppiB phenotype among putative PpiB prey proteins which upon deletion are often characterized by analogous phenotypes. Many putative preys show similar gene expression in wild-type and ΔppiB genetic backgrounds implying possible post-translational modifications by PpiB. We further conducted in vivo and in vitro interaction screens to determine which of them represent true preys. For DnaK, acetyl-CoA carboxylase, biotin carboxylase subunit (AccC) and phosphate acetyltransferase (Pta) we also showed a direct role of PpiB in the functional control of these proteins because it increased the measured enzyme activity of each protein and further interfered with DnaK localization and the correct folding of AccC. Taken together, these results indicate that PpiB is involved in diverse regulatory mechanisms to negatively modulate motility and biofilm formation via its functional association with certain protein substrates.

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 score0.015
Threshold uncertainty score0.340

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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

Citations27
Published2016
Admission routes1
Has abstractyes

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