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Record W2704296017 · doi:10.1152/ajpheart.00738.2016

Metabolism and acetylation contribute to leucine-mediated inhibition of cardiac glucose uptake

2017· article· en· W2704296017 on OpenAlexaff
Edith Renguet, Audrey Ginion, Roselle Gélinas, Laurent Bultot, Julien Auquier, Isabelle Robillard Frayne, Caroline Daneault, Jean‐Louis Vanoverschelde, Christine Des Rosiers, Louis Hue, Sandrine Horman, Christophe Beauloye, Luc Bertrand

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersCliniques Universitaires Saint-LucUniversité Catholique de LouvainFonds De La Recherche Scientifique - FNRSAstraZeneca
KeywordsAcetylationMetabolismLeucineChemistryCarbohydrate metabolismBiochemistryInternal medicineEndocrinologyPharmacologyBiologyMedicineAmino acidGene

Abstract

fetched live from OpenAlex

High plasma leucine levels strongly correlate with type 2 diabetes. Studies of muscle cells have suggested that leucine alters the insulin response for glucose transport by activating an insulin-negative feedback loop driven by the mammalian target of rapamycin/p70 ribosomal S6 kinase (mTOR/p70S6K) pathway. Here, we examined the molecular mechanism involved in leucine’s action on cardiac glucose uptake. Leucine was indeed able to curb glucose uptake after insulin stimulation in both cultured cardiomyocytes and perfused hearts. Although leucine activated mTOR/p70S6K, the mTOR inhibitor rapamycin did not prevent leucine’s inhibitory action on glucose uptake, ruling out the contribution of the insulin-negative feedback loop. α-Ketoisocaproate, the first metabolite of leucine catabolism, mimicked leucine’s effect on glucose uptake. Incubation of cardiomyocytes with [13C]leucine ascertained its metabolism to ketone bodies (KBs), which had a similar negative impact on insulin-stimulated glucose transport. Both leucine and KBs reduced glucose uptake by affecting translocation of glucose transporter 4 (GLUT4) to the plasma membrane. Finally, we found that leucine elevated the global protein acetylation level. Pharmacological inhibition of lysine acetyltransferases counteracted this increase in protein acetylation and prevented leucine’s inhibitory action on both glucose uptake and GLUT4 translocation. Taken together, these results indicate that leucine metabolism into KBs contributes to inhibition of cardiac glucose uptake by hampering the translocation of GLUT4-containing vesicles via acetylation. They offer new insights into the establishment of insulin resistance in the heart. NEW & NOTEWORTHY Catabolism of the branched-chain amino acid leucine into ketone bodies efficiently inhibits cardiac glucose uptake through decreased translocation of glucose transporter 4 to the plasma membrane. Leucine increases protein acetylation. Pharmacological inhibition of acetylation reverses leucine’s action, suggesting acetylation involvement in this phenomenon. Listen to this article’s corresponding podcast at http://ajpheart.podbean.com/e/leucine-metabolism-inhibits-cardiac-glucose-uptake/ .

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)0.0010.000
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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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

Citations35
Published2017
Admission routes1
Has abstractyes

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