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Record W2039559526 · doi:10.1371/journal.ppat.1002773

GogB Is an Anti-Inflammatory Effector that Limits Tissue Damage during Salmonella Infection through Interaction with Human FBXO22 and Skp1

2012· article· en· W2039559526 on OpenAlexafffund
Ana Victoria C. Pilar, Sarah A. Reid‐Yu, Colin A. Cooper, David T. Mulder, Brian K. Coombes

Bibliographic record

VenuePLoS Pathogens · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchCanada Research ChairsGovernment of Canada
KeywordsEffectorUbiquitin ligaseBiologyProinflammatory cytokineMicrobiologyUbiquitinSalmonellaInflammationImmune systemSecretionSkp1ChemokinePathogenF-box proteinCell biologyBacteriaImmunologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

Bacterial pathogens often manipulate host immune pathways to establish acute and chronic infection. Many Gram-negative bacteria do this by secreting effector proteins through a type III secretion system that alter the host response to the pathogen. In this study, we determined that the phage-encoded GogB effector protein in Salmonella targets the host SCF E3 type ubiquitin ligase through an interaction with Skp1 and the human F-box only 22 (FBXO22) protein. Domain mapping and functional knockdown studies indicated that GogB-containing bacteria inhibited IκB degradation and NFκB activation in macrophages, which required Skp1 and a eukaryotic-like F-box motif in the C-terminal domain of GogB. GogB-deficient Salmonella were unable to limit NFκB activation, which lead to increased proinflammatory responses in infected mice accompanied by extensive tissue damage and enhanced colonization in the gut during long-term chronic infections. We conclude that GogB is an anti-inflammatory effector that helps regulate inflammation-enhanced colonization by limiting tissue damage during infection.

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 score0.017
Threshold uncertainty score0.864

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 head0.031
GPT teacher head0.273
Teacher spread0.242 · 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

Citations94
Published2012
Admission routes2
Has abstractyes

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