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Record W3006291327 · doi:10.1038/s41467-020-14581-w

Quantitative SUMO proteomics identifies PIAS1 substrates involved in cell migration and motility

2020· article· en· W3006291327 on OpenAlexafffund
Chongyang Li, Francis P. McManus, Cédric Plutoni, Cristina Mirela Pascariu, Trent Nelson, Lara Elis Alberici Delsin, Grégory Emery, Pierre Thibault

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversité de MontréalUniversité du QuébecInstitute for Research in Immunology and Cancer
FundersNatural Sciences and Engineering Research Council of CanadaFonds de recherche du Québec – Nature et technologiesCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéGenome Canada
KeywordsSUMO proteinMotilityCell biologyHEK 293 cellsUbiquitin ligaseIntermediate Filament ProteinProteomicsVimentinMutantBiologyDNA ligaseChemistryCytoskeletonCellMolecular biologyIntermediate filamentCell cultureUbiquitinBiochemistryGeneticsGeneImmunology

Abstract

fetched live from OpenAlex

The protein inhibitor of activated STAT1 (PIAS1) is an E3 SUMO ligase that plays important roles in various cellular pathways. Increasing evidence shows that PIAS1 is overexpressed in various human malignancies, including prostate and lung cancers. Here we used quantitative SUMO proteomics to identify potential substrates of PIAS1 in a system-wide manner. We identified 983 SUMO sites on 544 proteins, of which 62 proteins were assigned as putative PIAS1 substrates. In particular, vimentin (VIM), a type III intermediate filament protein involved in cytoskeleton organization and cell motility, was SUMOylated by PIAS1 at Lys-439 and Lys-445 residues. VIM SUMOylation was necessary for its dynamic disassembly and cells expressing a non-SUMOylatable VIM mutant showed a reduced level of migration. Our approach not only enables the identification of E3 SUMO ligase substrates but also yields valuable biological insights into the unsuspected role of PIAS1 and VIM SUMOylation on cell motility.

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 score0.007
Threshold uncertainty score0.389

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 head0.038
GPT teacher head0.296
Teacher spread0.257 · 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

Citations79
Published2020
Admission routes2
Has abstractyes

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