We are witnessing a dramatic increase in the prevalence of obesity, which is driving an alarming increase in type 2 diabetes worldwide. Rational therapeutic approaches targeting the early stages of this disease continuum requires a comprehensive understanding of the mechanisms that link insulin resistance to excess caloric consumption. An association between skeletal muscle lipid accumulation, insulin resistance, and impaired glucose metabolism is widely recognized, yet the mechanistic underpinnings of the association remain elusive. Indeed, intramyocellular TAG accumulation can be associated with improved muscle performance and metabolic flexibility. During a period of R24 seed grant support, we have built a unified interdisciplinary research team, conducted feasibility and proof-of-concept studies, and designed a full R24 project to address this problem. We will test the central hypothesis that myocellular lipid accumulation triggers both adaptive and maladaptive (lipotoxic) responses, that these can influence glucose utilization via insulin signaling-dependent and -independent mechanisms, and that a dynamic balance between these responses determines the evolution of muscle insulin resistance. This project, which will harness the combined powers of unbiased chemical biology and functional genomics screening, is composed of five inter-connected Specific Aims. Chemical biology (Aim 1) and functional genomic (Aim 2) screens will be conducted using cultured skeletal myocytes loaded with excess fatty acid. To efficiently assess muscle autonomous vs. non-autonomous effects in vivo, a Drosophila model of obesity will be used to rapidly validate the genes (Aim 3). A Systems Integration Group will oversee the collection, storage, filtering, and analysis of the data generated by the studies of each Aim, to establish prioritized lists of genes, small molecule modifiers, and corresponding target pathways. After initial metabolic classification and prioritization, an iterative process of deep cellular and metabolic characterization together with metabolomic, lipidomic, and transcriptomic profiling, will be conducted to define phenotypic fingerprints or signatures representing adaptive and maladaptive sub-categories or "bins" of relevant myocyte perturbations (Aim 4). The phenotypic signatures will then be compared with similar profiles collected for muscle biopsy specimens from well-characterized human volunteers across a range of fitness and metabolic disease cohorts (Aim 5). The long-term goal of this project is to identify new genes, pathways, and molecular probes relevant to muscle lipotoxicity, serving as a valuable hypothesis-generating resource for the field and establishing a pipeline for drug development and biomarker discovery aimed at the earliest stages of insulin resistance.