Chénard Thierry, Guénard Frédéric, Vohl Marie-Claude, Carpentier André, Tchernof André, Najmanovich Rafael J
Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Canada.
Institute of Nutrition and Functional Foods, Université Laval, Quebec City, Canada.
BMC Syst Biol. 2017 Jun 12;11(1):60. doi: 10.1186/s12918-017-0438-9.
Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions.
We present iTC1390adip, a highly curated metabolic network of the human adipocyte presenting various improvements over the previously published iAdipocytes1809. iTC1390adip contains 1390 genes, 4519 reactions and 3664 metabolites. We validated the network obtaining 92.6% accuracy by comparing experimental gene essentiality in various cell lines to our predictions of biomass production. Using flux balance analysis under various test conditions, we predict the effect of gene deletion on both lipid droplet and biomass production, resulting in the identification of 27 genes that could reduce adipocyte hypertrophy. We also used expression data from visceral and subcutaneous adipose tissues to compare the effect of single gene deletions between adipocytes from each compartment.
We generated a highly curated metabolic network of the human adipose tissue and used it to identify potential targets for adipose tissue metabolic dysfunction leading to the development of type 2 diabetes.
2型糖尿病是全球主要的非传染性疾病之一，与肥胖中所见的脂肪组织过度积累密切相关。具体而言，脂肪组织的肥大性扩张与导致2型糖尿病的心脏代谢风险增加有关。研究脂肪细胞肥大的潜在机制可能有助于确定治疗这些疾病的潜在靶点。
我们展示了iTC1390adip，这是一个经过高度整理的人类脂肪细胞代谢网络，与之前发表的iAdipocytes1809相比有各种改进。iTC1390adip包含1390个基因、4519个反应和3664种代谢物。通过将各种细胞系中的实验基因必需性与我们对生物量产生的预测进行比较，我们验证了该网络，准确率达到92.6%。在各种测试条件下使用通量平衡分析，我们预测了基因缺失对脂滴和生物量产生的影响，从而确定了27个可能减少脂肪细胞肥大的基因。我们还使用了来自内脏和皮下脂肪组织的表达数据，比较每个隔室的脂肪细胞之间单基因缺失的影响。
我们生成了一个经过高度整理的人类脂肪组织代谢网络，并利用它来确定导致2型糖尿病发生的脂肪组织代谢功能障碍的潜在靶点。
