Exploring the transcriptomic and metabolomic profiles of adipose tissues: Insights and implications for fat grafting

Abstract

BackgroundExpanding on our prior research on murine fat grafts' metabolic shift, this study delves deeper into the metabolic profiles of human adipose tissues, specifically the superficial subcutaneous adipose tissue (SSAT) and deep subcutaneous adipose tissue (DSAT). MethodsUtilizing RNA-sequencing, metabolome, and metabolic flux analyses, we examined SSAT and DSAT samples obtained during deep inferior epigastric perforator flap breast reconstructions. Transcript data underwent unsupervised hierarchical clustering and Gene set enrichment analysis. Metabolomics involved analyzing samples for cationic and anionic metabolites via Capillary Electrophoresis Time-of-Flight Mass Spectrometry (CE-TOFMS), followed by principal component analysis (PCA) and heat map generation. Additionally, primary adipocytes from SSAT and DSAT were assessed using the Seahorse® extracellular flux analyzer. ResultsPCA and heat map analyses highlighted distinct transcriptome and metabolome differences between SSAT and DSAT. SSAT predominantly upregulated genes linked to adipogenesis (false discovery rate [FDR] q < 0.0001), oxidative phosphorylation (FDR q < 0.0001), fatty acid metabolism (FDR q <0.0001), and glycolysis (FDR q = 0.001). In contrast, DSAT showed a significant upregulation in inflammatory response genes (FDR q <0.05). Metabolite analysis revealed an abundance of glycolytic metabolites in SSAT, whereas DSAT was rich in metabolites associated with fatty acid metabolism and oxidative phosphorylation. Cellular flux analysis further confirmed SSAT's elevated glycolysis and spare oxidative phosphorylation capacities. ConclusionOur results highlight the metabolic uniqueness of SSAT and DSAT in humans, with SSAT exhibiting superior metabolic flexibility. The implications of these metabolic differences, especially in fat grafting procedures, necessitate further research and exploration in future studies. Data availabilityThe ribonucleic acid sequencing data were deposited in the Gene Expression Omnibus database (GSE216803). https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE216803 (GEO token: qnsngiuqplqdpaf).