B2 - Autophagy as a regulator of adipose tissue inflammation and dysfunction: an Immuno-metabolic function of E2F1

We identified E2F1 as a key transcription factor driving increased autophagy gene expression in human adipose tissue (AT) in obesity. Here we hypothesize hat adipose tissue E2F1, a transcription factor that molecularly defines a high-risk obese sub­pheno­type, participates in a bi-directional E2F1-miRNA co-regulatory network, resulting in increased AT autophagy, inflammation and dysfunction. To test this hypothesis, we define the following aims:

Aim 1. To elucidate mechanisms upstream of dysregulated autophagy and inflammation:

i. Transcriptional and post-transcriptional mechanisms for E2F1 up-regulation;

ii. Obesity-related E2F1-miRNA regulatory network alterations, and

iii. Their putative role in regulating AT autophagy, inflammation and dysfunction.

Aim 2. To explore the downstream consequences of elevated adipose E2F1 and autophagy in obesity:

i. Identify pathways linked to increased AT E2F1 in obesity (unbiased approach derived from RNA-Seq of E2F1high Vs E2F1low adipose tissue of similarly obese patients);

ii. Investigate by a novel in vivo model (an inducible, adipocyte-specific Atg7-KO) whether tempering AT autophagy in obesity can relieve inflammation and metabolic-endocrine dysfunction.

Impact: These studies will unravel the role of AT macrophage autophagy, and of an E2F1-miRNA network, in dysregulating AT autophagy, inflammation, and metabolic-endocrine functions in obesity.

Figure 1. Increased human AT E2F1 expression and E2F1 mRNA stability. A. Hierarchical clustering of differentially expressed genes. Differential trans­criptome between E2F1high and E2F1low is presented, divided to clusters of upregulated and downregulated genes. B and C. Selected pathway analyses, using STRING10© protein-interaction database. Shown are predicted and/or experimentally established pathways of ECM-related genes and TNF-related superfamily genes, differentially expressed in our cohort. Line thickness represents confidence level of the interaction.

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Tal Precht, PhD student

Yulia Haim, PhD student