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Record W2744418261 · doi:10.1242/jcs.206425

A genome-wide CRISPR screen reconciles the role of N-linked glycosylation in galectin-3 transport to the cell surface

2017· article· en· W2744418261 on OpenAlexfundno aff
Sarah E. Stewart, Sam A. Menzies, Stephanie J. Popa, Natalia Savinykh, Anna Petrunkina Harrison, Paul J. Lehner, Kévin Moreau

Bibliographic record

VenueJournal of Cell Science · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicGalectins and Cancer Biology
Canadian institutionsnot available
FundersWellcomeMedical Research CouncilNational Institute for Health and Care ResearchMedical Research Council CanadaNIHR Cambridge Biomedical Research CentreWellcome Trust
KeywordsBiologyCRISPRGlycosylationGalectinGenomeGeneticsCellCell biologyComputational biologyGene

Abstract

fetched live from OpenAlex

Galectins are a family of lectin binding proteins expressed both intracellularly and extracellularly. Galectin-3 (Gal-3, also known as LGALS3) is expressed at the cell surface; however, Gal-3 lacks a signal sequence, and the mechanism of Gal-3 transport to the cell surface remains poorly understood. Here, using a genome-wide CRISPR/Cas9 forward genetic screen for regulators of Gal-3 cell surface localization, we identified genes encoding glycoproteins, enzymes involved in N-linked glycosylation, regulators of ER-Golgi trafficking and proteins involved in immunity. The results of this screening approach led us to address the controversial role of N-linked glycosylation in the transport of Gal-3 to the cell surface. We find that N-linked glycoprotein maturation is not required for Gal-3 transport from the cytosol to the extracellular space, but is important for cell surface binding. Additionally, secreted Gal-3 is predominantly free and not packaged into extracellular vesicles. These data support a secretion pathway independent of N-linked glycoproteins and extracellular vesicles.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.246
Teacher spread0.234 · 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

Citations46
Published2017
Admission routes1
Has abstractyes

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