# Determining cell- and spatially-distinct skeletal muscle transcriptional aberrations in insulin resistance and type 2 diabetes > **NIH NIH K99** · ADVENTHEALTH ORLANDO · 2024 · $91,500 ## Abstract PROJECT SUMMARY Type 2 Diabetes (T2D) is estimated to affect 30 million U.S. adults and skeletal muscle (SkM) insulin resistance (IR) is considered to be one of the primary aberrations. Effective insulin-stimulated SkM glucose uptake is dependent on 1) insulin-stimulated activation of terminal arteriole endothelial cells (EC) to perfuse microvascular units, 2) transport of substrates across capillary ECs and 3) stimulation of myofiber insulin signaling, resulting in glucose uptake. Therefore, both myofibers and ECs are critical cell types that can be dysregulated with IR in T2D. Previous research has identified a dysregulated transcriptional profile with SkM IR in the basal state and during insulin stimulation from a hyperinsulinemic euglycemic clamp (HE). A significant limitation of these prior studies is the restriction to whole SkM homogenates and therefore not identifying which cells or spatial area the dysregulated signals originate from. We have developed a pipeline for 3’ and 5’ amplification of single cells or nuclei from SkM using full-length SMART-Seq technology with the iCELL8 platform, resulting in 2-3 fold greater gene coverage than previous research, allowing us to investigate transcriptional aberrations at a single cell/nuclei resolution. Recent developments in spatial transcriptomics now permit transcriptional profiling on sectioned tissue. In this proposed research, we will leverage both full-length single cell and single nuclei RNA-Seq and spatial transcriptomics to determine cell- and spatially-distinct transcriptional aberrations in SkM that occur with IR in T2D. The career development training will refine my skills in; leading an independent lab, bioinformatics, and human clinical research with a focus on assessing insulin-stimulated glucose disposal (Rd) and non- oxidative glucose disposal (NOGD) using hyperinsulinemic euglycemic (HE) clamps with glucose tracers and indirect calorimetry. My K99/R00 training will uniquely position me to conduct bedside-to-bench-to-bioinformatics research to uncover the molecular profiles of SkM IR. For the first time, the transcriptional responses to insulin in human SkM will be probed at a single cell/nuclei 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 assessed simultaneously with a HE clamp. This novel and innovative approach will reveal which cells (and importantly, where in SkM) the aberrations occur with IR in T2D. The Translational Research Institute at AdventHealth is an ideal environment for developing my bedside-to- bench-to-bioinformatics research approach with cutting-edge metabolic translational research facilities and a rich interdisciplinary environment. Completion of the proposed research and career development training will facilitate my success as an independent translational investigator in SkM metabolis... ## Key facts - **NIH application ID:** 10808684 - **Project number:** 1K99DK135915-01A1 - **Recipient organization:** ADVENTHEALTH ORLANDO - **Principal Investigator:** Katie Whytock - **Activity code:** K99 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $91,500 - **Award type:** 1 - **Project period:** 2024-01-09 → 2026-01-08 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10808684 ## Citation > US National Institutes of Health, RePORTER application 10808684, Determining cell- and spatially-distinct skeletal muscle transcriptional aberrations in insulin resistance and type 2 diabetes (1K99DK135915-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10808684. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*