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Time‐resolved analysis of amino acid deprivation responses reveals dynamic relationship between GCN2 and mTORC1

2017· article· en· W4389021988 on OpenAlexaff
Inna A. Nikonorova, Michael Goudie, Emily T. Mirek, Yongping Wang, Tracy G. Anthony

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsGovernment of New Brunswick
FundersNational Institutes of Health
KeywordsmTORC1ATF4Integrated stress responseAmino acidTranslation (biology)Translational regulationKinaseeIF2ChemistryPhosphorylationProtein biosynthesisCell biologyBiochemistryRegulatorEukaryotic initiation factorTranscription factorBiologyMessenger RNAGene

Abstract

fetched live from OpenAlex

In higher eukaryotes, sensing of amino acids by liver is critical for fine tuning of whole body metabolism according to nutrient availability. Amino acid (AA) depletion activates General Control Nonderepressible 2 (GCN2, or eIF2AK4) kinase and consequential phosphorylation of eukaryotic initiation factor 2 (eIF2). Phosphorylated eIF2 allows for preferential translation of specific mRNAs, such as activating transcription factor 4 (ATF4). AA depletion also reduces the activity of another AA sensor, mammalian target of rapamycin complex 1 (mTORC1), a major regulator of cell growth. The GCN2 pathway inhibits mTORC1 activity, but how remains unclear. Our study aimed to define the role of GCN2 in the regulation of mTORC1 activity to AA depletion in vivo . We used the anti‐cancer drug asparaginase (ASNase) as a molecular tool to induce AA depletion in wild type (WT) and Gcn2 −/− mice. Following a single injection of ASNase, hepatic signaling via GCN2 and mTORC1 was analyzed. In this experimental setup we addressed three types of possible regulation: 1) immediate protein‐protein interactions (15–30 min), 2) early translational changes (1–3 h) and 3) long term transcriptional alterations (6–18 h). We found that genetic disruption of GCN2 lead to hyperactivation of hepatic mTORC1 at 15–30 min following ASNase. This indicates that GCN2 modulates hepatic mTORC1 activity via protein‐protein interaction(s). Examination of translational changes via polyribosome profiling revealed enhanced translation of ATF4 in WT, but not Gcn2 −/− livers, at 1h. This suggests that: 1) translational induction of ATF4 by ASNase requires GCN2 and 2) hyperactivation of mTORC1 per se is not enough to induce ATF4 synthesis. Analysis of transcriptional changes induced by ATF4 revealed that Sestrin2, an inhibitor of mTORC1, is induced at a much later time point,12–18 h following ASNase, and is not involved in immediate or early control. Taken together, our data provide a mechanistic framework for dynamic interaction of the GCN2 pathway with mTORC1 during amino acid stress. Support or Funding Information This work was supported by NIH grant RO1HD070487 to T.G.A. and NIH K12 grant IRACDA New Jersey‐New York for Science Partnerships in Research and Education to I.A.N.

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 head0.031
GPT teacher head0.310
Teacher spread0.279 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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