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Record W2221693143 · doi:10.1074/jbc.m115.697599

Negative Feed-forward Control of Tumor Necrosis Factor (TNF) by Tristetraprolin (ZFP36) Is Limited by the Mitogen-activated Protein Kinase Phosphatase, Dual-specificity Phosphatase 1 (DUSP1)

2015· article· en· W2221693143 on OpenAlexafffund
Suharsh Shah, Mahmoud Mostafa, Andrew McWhae, Suzanne Traves, Robert Newton

Bibliographic record

VenueJournal of Biological Chemistry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsTristetraprolinDual-specificity phosphataseTumor necrosis factor alphaPhosphataseProtein kinase AKinaseMAP kinase kinase kinaseCancer researchChemistryCell biologyBiologyBiochemistryPhosphorylationEndocrinologyMessenger RNAGene

Abstract

fetched live from OpenAlex

TNF is central to inflammation and may play a role in the pathogenesis of asthma. The 3′-untranslated region of the TNF transcript contains AU-rich elements (AREs) that are targeted by the RNA-binding protein, tristetraprolin (also known as zinc finger protein 36 (ZFP36)), which is itself up-regulated by inflammatory stimuli, to promote mRNA degradation. Using primary human bronchial epithelial and pulmonary epithelial A549 cells, we confirm that interleukin-1β (IL1B) induces expression of dual-specificity phosphatase 1 (DUSP1), ZFP36, and TNF. Whereas IL1B-induced DUSP1 is involved in feedback control of MAPK pathways, ZFP36 exerts negative (incoherent) feed-forward control of TNF mRNA and protein expression. DUSP1 silencing increased IL1B-induced ZFP36 expression at 2 h and profoundly repressed TNF mRNA at 6 h. This was partly due to increased TNF mRNA degradation, an effect that was reduced by ZFP36 silencing. This confirms a regulatory network, whereby DUSP1-dependent negative feedback control reduces feed-forward control by ZFP36. Conversely, whereas DUSP1 overexpression and inhibition of MAPKs prevented IL1B-induced expression of ZFP36, this was associated with increased TNF mRNA expression at 6 h, an effect that was predominantly due to elevated transcription. This points to MAPK-dependent feed-forward control of TNF involving ZFP36-dependent and -independent mechanisms. In terms of repression by dexamethasone, neither silencing of DUSP1, silencing of ZFP36, nor silencing of both together prevented the repression of IL1B-induced TNF expression, thereby demonstrating the need for further repressive mechanisms by anti-inflammatory glucocorticoids. In summary, these data illustrate why understanding the competing effects of feedback and feed-forward control is relevant to the development of novel anti-inflammatory therapies. Background: ZFP36 negatively regulates AU-rich element-containing mRNAs. Results: DUSP1 silencing increases ZFP36 expression and enhances negative feed-forward control of TNF. Conclusion: MAPK inhibition initially attenuates TNF mRNA, but reduced feed-forward control subsequently produces an increase. Significance: Understanding such networks is essential to develop novel anti-inflammatory therapies or understand TNF repression by glucocorticoids, which may not require DUSP1 or ZFP36 expression.

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 integrity0.0000.001
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 head0.023
GPT teacher head0.251
Teacher spread0.227 · 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

Citations30
Published2015
Admission routes2
Has abstractyes

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