Metabolic fingerprinting of cell types in mouse skeletal muscle by combining TOF-SIMS with immunofluorescence staining

Abstract

Skeletal muscle tissue is composed of various muscle cell types which differ in physiological functions. Changes in cell type composition of skeletal muscle are associated with the development of metabolic diseases. Skeletal muscle cell types are currently distinguished by immunofluorescence (IF) staining based on myosin heavy chain (MHC) isoform difference. However, it remains a challenge to provide metabolic fingerprints of different muscle cell types by IF staining. Therefore, in this study, we proposed a method to examine metabolite distribution within different cell types by time-of-flight secondary ion mass spectrometry (TOF-SIMS) with high spatial resolution. Skeletal muscle samples from C57/BL6 mice were obtained by slicing. Cell types in TOF-SIMS images were labelled corresponding to IF images from the same region of serially cut sections. Mass spectra corresponding to individual muscle cells were extracted to compare metabolic fingerprints among cell types. Skeletal muscle cells were classified into two clusters based on the mass spectra of individual cells. Unsaturated diacylglycerol (DG) and fatty acid (FA) species were found to be distributed in a cell-type dependent manner. Moreover, relative quantification showed that the content of unsaturated DGs, oleic acid and linoleic acid was higher in type I and type IIA cells than in type IIB cells. TOF-SIMS in combination with IF enables us to directly visualize metabolite distribution in different cell types, to find potential biomarkers for cell type classification. TOF-SIMS imaging coupled with IF staining has been proved to be a promising tool for metabolic fingerprinting of different skeletal muscle cell types.