Determining cell- and spatially-distinct skeletal muscle transcriptional aberrations in insulin resistance and type 2 diabetes

About This Grant

Type 2 Diabetes (T2D) is estimated to affect over 30 million US adults and skeletal muscle (SkM) insulin resistance (IR) is one of the primary aberrations. SkM is a complex organ comprised of different cell types including: myofibers, endothelial cells (EC), smooth muscle cells, fibro-adipogenic progenitors, satellite cells and immune cells. Effective insulin-stimulated SkM glucose uptake is dependent on 1) insulin-stimulated activation of terminal arteriole EC to perfuse microvascular units, 2) transport of substrates across capillary ECs and 3) stimulation of myofiber insulin signaling, resulting in glucose uptake. Each of these steps can be dysregulated by pro-inflammatory cytokines released from localized immune cells in the SkM niche. Therefore, different cell types in SkM can impact insulin sensitivity. Previous research has identified a dysregulated transcriptional profile with SkM IR in the basal state and during insulin stimulation. A significant limitation of these prior studies is the restriction to whole SkM homogenates and therefore not identifying which cells or spatial area within the tissue the dysregulated signals originate from.  We have developed a pipeline for full-length amplification of single cells from SkM using the iCELL8 platform, resulting in 2-3 fold greater gene coverage than previous research, allowing us to investigate transcriptional aberrations that occur with SkM IR at a single cell resolution. Recent developments in spatial transcriptomics now permit transcriptional profiling on sectioned SkM tissue which identifies the location and proximity of dysregulated cells and how they relate to IR in SkM. This study will leverage a hyper-insulinemic euglycemic (HE) clamp with stable glucose isotope tracers and indirect calorimetry to assess insulin-stimulated glucose disposal (Rd) and non-oxidative glucose disposal (NOGD) in individuals with obesity with and without IR compared to an insulin sensitive control group. For the first time, the transcriptional responses to insulin in human SkM will be probed at a single cell and spatial resolution. We will identify which cells and areas of SkM respond to insulin and if they are spatially localized to each other and if their gene-network profiles correlate with a greater in vivo Rd and NOGD. This novel and innovative approach will reveal which cells (and importantly, where in SkM) the aberrations occur with SkM IR whilst dissociating the confounding effects of Obesity. Results from this proposal will identify specific molecular targets to alleviate SkM IR that will be targeted in future interventions.