Transcriptional profiling of the response to starvation and fattening reveals differential regulation of autophagy genes in mammals

Margarita Galves, Michal Sperber, Fatima Amer-Sarsour, Ran Elkon, Avraham Ashkenazi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Nutrient deprivation (starvation) induced by fasting and hypercaloric regimens are stress factors that can influence cell and tissue homeostasis in mammals. One of the key cellular responses to changes in nutrient availability is the cell survival pathway autophagy. While there has been much research into the protein networks regulating autophagy, less is known about the gene expression networks involved in this fundamental process. Here, we applied a network algorithm designed to analyse omics datasets, to identify sub-networks that are enriched for induced genes in response to starvation. This enabled us to identify two prominent active modules, one composed of key stress-induced transcription factors, including members of the Jun, Fos and ATF families, and the other comprising autophagosome sub-network genes, including ULK1. The results were validated in the brain, liver and muscle of fasting mice. Moreover, differential expression analysis of autophagy genes in the brain, liver and muscle of high-fat diet-exposed mice showed significant suppression of GABARAPL1 in the liver. Finally, our data provide a resource that may facilitate the future identification of regulators of autophagy.

Original languageEnglish
Article number20230407
JournalProceedings of the Royal Society B: Biological Sciences
Volume290
Issue number1995
DOIs
StatePublished - 2023

Funding

FundersFunder number
Aufzien Family Center for the Prevention and Treatment of Parkinson's Disease
Taube Koret Global Collaboration in Neurodegenerative Diseases
Yoran Institute for Human Genome Research
Azrieli Foundation

    Keywords

    • autophagy
    • high-fat diet
    • nutrient deprivation
    • transcriptional networks

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