MétaCan
Menu
Back to cohort
Record W2970897351 · doi:10.3390/cells8091006

Rac1 S71 Mediates the Interaction between Rac1 and 14-3-3 Proteins

2019· article· en· W2970897351 on OpenAlexafffund
Abdalla Abdrabou, Daniel Brandwein, Changyu Liu, Zhixiang Wang

Bibliographic record

VenueCells · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topic14-3-3 protein interactions
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsRAC1PhosphorylationCell biologyImmunoprecipitationSignal transductionBiologyHEK 293 cellsProtein kinase BProtein–protein interactionChemistryBiochemistryReceptorGene

Abstract

fetched live from OpenAlex

Both 14-3-3 proteins (14-3-3s) and Rho proteins regulate cytoskeleton remodeling and cell migration, which suggests a possible interaction between the signaling pathways regulated by these two groups of proteins. Indeed, more and more emerging evidence indicates the mutual regulation of these two signaling pathways. However, all of the data regarding the interaction between Rac1 signaling pathways and 14-3-3 signaling pathways are through either the upstream regulators or downstream substrates. It is not clear if Rac1 could interact with 14-3-3s directly. It is interesting to notice that the Rac1 sequence 68RPLSYP73 is likely a 14-3-3 protein binding motif following the phosphorylation of S71 by Akt. Thus, we hypothesize that Rac1 directly interacts with 14-3-3s. We tested this hypothesis in this research. By using mutagenesis, co-immunoprecipitation (co-IP), Rac1 activity assay, immunoblotting, and indirect immunofluorescence, we demonstrate that 14-3-3s interact with Rac1. This interaction is mediated by Rac1 S71 in both phosphorylation-dependent and -independent manners, but the phosphorylation-dependent interaction is much stronger. Epidermal growth factor (EGF) strongly stimulates the phosphorylation of Rac1 S71 and the interaction between 14-3-3s and Rac1. Mutating S71 to A completely abolishes both phosphorylation-dependent and -independent interactions between 14-3-3s and Rac1. The interaction between 14-3-3s and Rac1 mostly serve to regulate the activity and subcellular localization of Rac1. Among the seven 14-3-3 isoforms, 14-3-3η, -σ, and -θ showed interactions with Rac1 in both Cos-7 and HEK 293 cells. 14-3-3γ also binds to Rac1 in HEK 293 cells, but not in Cos-7 cells. We conclude that 14-3-3s interact with Rac1. This interaction is mediated by Rac1 S71 in both phosphorylation-dependent and -independent manners. The interaction between 14-3-3 and Rac1 mostly serves to regulate the activity and subcellular localization of Rac1. Among the seven 14-3-3 isoforms, 14-3-3η, -γ, -σ, and -θ interact with Rac1.

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 score0.187
Threshold uncertainty score0.448

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 head0.008
GPT teacher head0.247
Teacher spread0.240 · 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

Citations16
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueCellsSame topic14-3-3 protein interactionsFrench-language works237,207