Megaconial Congenital Muscular Dystrophy (CMD) is a rare autosomal recessive disorder characterized by enlarged mitochondria located mainly at the periphery of muscle fibers and caused by mutations in the Choline Kinase Beta (CHKB) gene. Although the pathogenesis of this disease is not well understood, there is accumulating evidence for the presence of mitochondrial dysfunction. In this study, we aimed to investigate whether imbalanced mitochondrial dynamics affects mitochondrial function and bioenergetic efficiency in skeletal muscle cells of Megaconial CMD. Immunofluorescence, confocal and transmission electron microscopy studies revealed impaired mitochondrial network, morphology, and localization in primary skeletal muscle cells of Megaconial CMD. The organelle disruption was specific only to skeletal muscle cells grown in culture. The expression levels of mitochondrial fission proteins (DRP1, MFF, FIS1) were found to be decreased significantly in both primary skeletal muscle cells and tissue sections of Megaconial CMD by Western blotting and/or immunofluorescence analysis. The metabolomic and fluxomic analysis, which were performed in Megaconial CMD for the first time, revealed decreased levels of phosphonucleotides, Krebs cycle intermediates, ATP, and altered energy metabolism pathways. Our results indicate that reduced mitochondrial fission and altered mitochondrial energy metabolism contribute to mitochondrial dysmorphology and dysfunction in the pathogenesis of Megaconial CMD.

Recent research effort in biomaterial development has largely focused on engineering bio-instructive materials to stimulate specific cell signaling. Assessing the biological performance of these materials using time-consuming and trial-and-error traditional low-throughput screening techniques remains a critical challenge in the field. In contrast, the use of increasingly sophisticated omics technologies to facilitate high-throughput screening of unbiased global understanding of cell–biomaterial interactions at gene, epigenetic, mRNA, protein, metabolite, and lipid levels holds great potential to predict the therapeutic outcome of biomaterials with specific properties. In this review, we highlight the potential use of omics technologies – namely transcriptomics, proteomics, metabolomics and lipidomics – in biomaterial design and deciphering of the fundamental cell behaviors (e.g., adhesion, migration, differentiation) in response to cell–biomaterial interactions. Moreover, the potential challenges and prospects of high-throughput analysis platforms are discussed rationally, providing an insight into the developing field and its use in biomaterials science.