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Record W2012167979 · doi:10.4161/auto.7.3.14046

The ubiquitin-binding adaptor proteins p62/SQSTM1 and NDP52 are recruited independently to bacteria-associated microdomains to target Salmonella to the autophagy pathway

2011· article· en· W2012167979 on OpenAlexaff
Marija Cemma, Peter K. Kim, John H. Brumell

Bibliographic record

VenueAutophagy · 2011
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsAutophagySignal transducing adaptor proteinBiologySalmonella entericaUbiquitinCell biologyBacteriaInnate immune systemBAG3SalmonellaMicrobiologySignal transductionImmune systemBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

Autophagy is an innate immune defense against bacterial invasion. Recent studies show that two adaptor proteins, p62 and NDP52, are required for autophagy of the bacterial pathogen Salmonella enterica serovar Typhimurium (S. typhimurium). However, it is not known why two different adaptors are required to target the same bacterial cargo to autophagy. Here we show that both adaptors are recruited to bacteria with similar kinetics, that they are recruited to bacteria independently of each other, and that depletion of either adaptor leads to impairment of antibacterial autophagy. Depletion of both adaptors does not synergistically impair autophagy, indicating they act in the same pathway. Remarkably, we observed that these adaptors do not colocalize, but rather form non-overlapping microdomains surrounding bacteria. We conclude that p62 and NDP52 act cooperatively to drive efficient antibacterial autophagy by targeting the protein complexes they coordinate to distinct micro-domains associated with bacteria.

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)0.0000.000
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 head0.033
GPT teacher head0.256
Teacher spread0.223 · 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

Citations205
Published2011
Admission routes1
Has abstractyes

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