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Proximity‐Labeling by BioID Reveals Pleiotropic Role of Ski in Cardiac Fibrosis

2019· article· en· W3173620358 on OpenAlexafffundabout
Natalie M. Landry, Sunil G. Rattan, Mark Hnatowich, Ian Dixon

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHippo pathway signaling and YAP/TAZ
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersCanadian Institutes of Health ResearchResearch Manitoba
KeywordsInteractomeHippo signaling pathwayEffectorCell biologyCardiac fibrosisComputational biologyBiologyChemistryFibrosisMedicineBiochemistryPathology

Abstract

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Despite recent improvements made in cardiac patient treatment and outcomes, current therapies only serve to alleviate the symptoms of cardiac fibrosis, rather than correct the disease itself. Our lab has previously established Ski as a potent inhibitor of TGF‐β signalling in cardiac myofibroblasts, the primary effectors of fibrosis; however our recent investigations suggest that Ski may inhibit a multitude of pro‐fibrotic pathways, including Hippo. We have specifically observed upon Ski overexpression in primary cardiac fibroblasts, a marked reduction in the expression of TAZ (or WWTR1), one of the main nuclear effectors of the Hippo pathway. To further expand the current knowledge on Ski's anti‐fibrotic properties, and provide insight into potential mechanisms of action, we mapped its interactome using enzyme‐catalyzed biotin proximity labelling (BioID2). Using the BioID2 vector, E. coli BirA* biotin ligase was fused to the N‐terminus of human Ski and the fusion protein was then expressed in fibroblasts in the presence of an excess of free biotin. Whole cell lysates were then subject to streptavidin‐mediated protein capture and potential Ski binding partners were identified by tandem time‐of‐flight mass spectrometry. The resulting candidates included several known Ski interactors (eg. RSmad2 and co‐Smad4), but also revealed novel interactors which potentially link Ski's anti‐fibrotic capacity and interaction with the Hippo signaling pathway. We also observed several interactions with cytoskeletal components, including those involved in actin dynamics and stress fiber formation. To confirm results from the affinity capture, candidate interactors were verified using immunoblotting. In addition, the expression of potential Ski interactors was examined in a rat model of cardiac fibrosis, post‐myocardial infarction. Our data suggest that Ski serves not only as a Smad‐dependent TGF‐β inhibitor, but also interacts with the Hippo, Wnt/β‐catenin, and FoxO signaling pathways‐‐all of which are suspected contributors to fibrosis. In addition, Ski's interaction with various points of cytoskeletal organization further indicates that its functions in the cell go beyond simple inhibitory protein‐protein interactions. Support or Funding Information NM Landry's research has been funded by studentships from the Canadian Institutes of Health Research (CIHR), Research Manitoba, as well as the Bank of Montreal (BMO). IMC Dixon is grateful to the Heart & Stroke Foundation of Canada for a grant (G‐17‐10018631) in support of this research, as well as the St. Boniface Hospital and Research Foundation for their continued operating patronage. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.005
GPT teacher head0.209
Teacher spread0.204 · 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".

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Citations0
Published2019
Admission routes3
Has abstractyes

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