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Record W2006210604 · doi:10.1371/journal.pone.0065371

A Loss-of-Function Screen for Phosphatases that Regulate Neurite Outgrowth Identifies PTPN12 as a Negative Regulator of TrkB Tyrosine Phosphorylation

2013· article· en· W2006210604 on OpenAlexfundno aff
Malene Ambjørn, Véronique Dubreuil, Federico Miozzo, Fabienne Nigon, Bente K. Møller, Shohreh Issazadeh‐Navikas, Jacob Berg, Michael Lees, Jan Sap

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
FundersCopenhagen Graduate School for Nanoscience and NanotechnologyLundbeckfondenLunds UniversitetUniversitat de BarcelonaYork UniversityInstitute for Research in BiomedicineMcGill UniversityVera og Carl Johan Michaelsens LegatRegeneron PharmaceuticalsArvid Nilssons Fond
KeywordsProtein tyrosine phosphataseNeuriteTropomyosin receptor kinase BPhosphorylationCell biologyPhosphataseNeurotrophinReceptor tyrosine kinaseBiologyTyrosine phosphorylationKinaseTrk receptorNeurotrophic factorsTyrosineBiochemistryReceptor

Abstract

fetched live from OpenAlex

Alterations in function of the neurotrophin BDNF are associated with neurodegeneration, cognitive decline, and psychiatric disorders. BDNF promotes axonal outgrowth and branching, regulates dendritic tree morphology and is important for axonal regeneration after injury, responses that largely result from activation of its tyrosine kinase receptor TrkB. Although intracellular neurotrophin (NT) signaling presumably reflects the combined action of kinases and phosphatases, little is known about the contributions of the latter to TrkB regulation. The issue is complicated by the fact that phosphatases belong to multiple independently evolved families, which are rarely studied together. We undertook a loss-of-function RNA-interference-based screen of virtually all known (254) human phosphatases to understand their function in BDNF/TrkB-mediated neurite outgrowth in differentiated SH-SY5Y cells. This approach identified phosphatases from diverse families, which either positively or negatively modulate BDNF-TrkB-mediated neurite outgrowth, and most of which have little or no previously established function related to NT signaling. "Classical" protein tyrosine phosphatases (PTPs) accounted for 13% of the candidate regulatory phosphatases. The top classical PTP identified as a negative regulator of BDNF-TrkB-mediated neurite outgrowth was PTPN12 (also called PTP-PEST). Validation and follow-up studies showed that endogenous PTPN12 antagonizes tyrosine phosphorylation of TrkB itself, and the downstream activation of ERK1/2. We also found PTPN12 to negatively regulate phosphorylation of p130cas and FAK, proteins with previously described functions related to cell motility and growth cone behavior. Our data provide the first comprehensive survey of phosphatase function in NT signaling and neurite outgrowth. They reveal the complexity of phosphatase control, with several evolutionarily unrelated phosphatase families cooperating to affect this biological response, and hence the relevance of considering all phosphatase families when mining for potentially druggable targets.

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 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.062
GPT teacher head0.254
Teacher spread0.193 · 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".

Quick stats

Citations15
Published2013
Admission routes1
Has abstractyes

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