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Record W3174078272 · doi:10.4049/jimmunol.2000891

Zebrafish otud6b Negatively Regulates Antiviral Responses by Suppressing K63-Linked Ubiquitination of irf3 and irf7

2021· article· en· W3174078272 on OpenAlexaff
Ziwen Zhou, Xiaolian Cai, Junji Zhu, Zhi Li, Guangqing Yu, Xing Liu, Gang Ouyang, Wuhan Xiao

Bibliographic record

VenueThe Journal of Immunology · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsMinistry of Agriculture
FundersNational Key Research and Development Program of ChinaChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsIRF3IRF7UbiquitinUbiquitin ligaseCell biologyZebrafishBiologyInterferon regulatory factorsHEK 293 cellsCancer researchVirologyInnate immune systemImmune systemBiochemistryGeneticsReceptorGene

Abstract

fetched live from OpenAlex

Abstract Ovarian tumor domain-containing 6B (OTUD6B) belongs to the OTU deubiquitylating enzyme family. In this study, we report that zebrafish otud6b is induced upon viral infection, and overexpression of otud6b suppresses cellular antiviral response. Disruption of otud6b in zebrafish increases the survival rate upon spring viremia of carp virus and grass carp reovirus exposure. Further assays indicate that otud6b interacts with irf3 and irf7 and diminishes traf6-mediated K63-linked polyubiquitination of irf3 and irf7. In addition, the OTU domain is required for otud6b to repress IFN-1 activation and K63-linked polyubiquitination of irf3 and irf7. Moreover, otud6b also attenuates tbk1 to bind to irf3 and irf7, resulting in the impairment of irf3 and irf7 phosphorylation. This study provides, to our knowledge, novel insights into otud6b function and sheds new lights on the regulation of irf3 and irf7 by deubiquitination in IFN-1 signaling.

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 score0.004

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)0.0010.000

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 head0.012
GPT teacher head0.250
Teacher spread0.238 · 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

Citations34
Published2021
Admission routes1
Has abstractyes

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Same venueThe Journal of ImmunologySame topicinterferon and immune responsesFrench-language works237,207