bioRxivPhysiologyPreprint
Pantothenate Kinase 4 controls efficient skeletal muscle energy substrate metabolism via acetyl-CoA
A. Miranda-Cervantes, A. M. Fritzen, S. H. Raun, O. Hodek, L. L. V. Moller, K. Johann, L. Deisen, P. Gregorevic, A. Gudiksen, A. Artati, J. Adamski, N. R. Andersen, P. Schjerling, A. Cebrian-Serrano, M. Jaehnert, P. Gottmann, I. Burtscher, H. Lickert, H. Pilegaard, A. Schuermann, M. H. Tschoep, T. Moritz, T. D. Mueller, L. Sylow, B. Kiens, , M. Kleinert
Abstract
Metabolic inflexibility in skeletal muscle (SkM) is closely linked to metabolic diseases. Exercise improves metabolic flexibility, rendering it a valuable discovery tool of mechanisms promoting efficient metabolism of glucose and lipids. We herein discover pantothenate kinase 4 (PanK4) as a conserved exercise target with high abundance in SkM. We go on to show that murine muscle Pank4 is dysregulated with high-fat diet feeding, and identify human PANK4 variants that associate with glycemic control and body mass index traits, indicating important roles of PanK4 in glucose metabolism and growth. Consistent with the latter, germline deletion of PanK4 reduces circulating IGF-1 and stunts growth in mice. Deletion specifically in mouse SkM reveals that PanK4 facilitates fatty acid oxidation by acting as a regulator of SkM acetyl-CoA, a key node in metabolism of both glucose and lipids. Consequently, without PanK4, elevated SkM acetyl-CoA levels allosterically gridlock key enzymes required for efficient lipid and glucose utilization, and these SkM metabolic perturbations manifest in whole-body insulin resistance. As proof of principle, we show that an increase in muscle PanK4 lowers SkM acetyl-CoA and increases SkM glucose utilization. Our findings identify PanK4 as a novel regulator of SkM energy substrate metabolism, warranting inclusion in comprehensive strategies against metabolic disease.
- organism: mouse
- organism: human
- assay: proteomics
- assay: metabolomics
- research focus: metabolism & bioenergetics
- research focus: gene regulatory network inference
- approach: experimental assay
- approach: statistical model
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