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Record W2990332431 · doi:10.1126/scisignal.aav7934

PKR-dependent cytosolic cGAS foci are necessary for intracellular DNA sensing

2019· article· en· W2990332431 on OpenAlexafffund
Siqi Hu, Hong Sun, Lijuan Yin, Jian Li, Shan Mei, Fengwen Xu, Chao Wu, Xiaoman Liu, Fei Zhao, Di Zhang, Yu Huang, Lili Ren, Shan Cen, Jianwei Wang, Chen Liang, Fei Guo

Bibliographic record

VenueScience Signaling · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of China
KeywordsCytosolIntracellularCell biologyDNAProtein kinase RDNA damageChemistryBiologyKinaseBiochemistryEnzymeProtein kinase A

Abstract

fetched live from OpenAlex

Cyclic GMP-AMP synthase (cGAS) is a major sensor of cytosolic DNA from invading pathogens and damaged cellular organelles. Activation of cGAS promotes liquid-like phase separation and formation of membraneless cytoplasmic structures. Here, we found that cGAS bound G3BP1, a double-stranded nucleic acid helicase involved in the formation of stress granules. Loss of G3BP1 blocked subcellular cGAS condensation and suppressed the interferon response to intracellular DNA and DNA virus particles in cells. Furthermore, an RNA-dependent association with PKR promoted G3BP1 foci formation and cGAS-dependent interferon responses. Together, these results indicate that PKR promotes the formation of G3BP1-dependent, membraneless cytoplasmic structures necessary for the DNA-sensing function of cGAS in human cells. These data suggest that there is a previously unappreciated link between nucleic acid sensing pathways, which requires the formation of specialized subcellular structures.

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 score0.002
Threshold uncertainty score0.007

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 integrity0.0000.001
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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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

Citations65
Published2019
Admission routes2
Has abstractyes

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