Single‐Cell Sequencing and Transcriptomic Sequencing Exploration of the Mechanisms Governing Lactylation in Mitochondrial Diseases

Mitochondrial diseases (MDs) consist of a heterogeneous spectrum of disorders resulting from mutations in either nuclear or mitochondrial DNA, disrupting the function of multiple organ systems due to the importance of mitochondria in energy generation and metabolic activity. Exploring the association between lactylation and MDs offers valuable insights into the underlying molecular pathology and may reveal new therapeutic strategies for these disorders. Both single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic analyses were used to investigate the potential role of lactylation in MDs. Analytical methods included cellular subtype clustering, lactylation scoring, machine learning-based gene prioritization, immune cell infiltration profiling, regulatory network mapping, and pathway enrichment analyses of key genes. Furthermore, qRT-PCR and Western blotting were performed on skeletal muscle samples from MD patients to experimentally validate gene expression results. The single-cell analysis revealed several distinct immune cell clusters, among which CD4⁺ T cells exhibited the highest lactylation scores. Machine learning algorithms identified three core genes that were strongly associated with MD pathogenesis and subsequently confirmed in muscle tissue, including EIF3D, SOD1, and RPS26. These genes demonstrated significant correlations with specific immune cell populations, implicating them in immune regulation. Additional network and pathway analyses revealed signaling mechanisms that may contribute to MD development. These results offer novel molecular insights into lactylation-associated mechanisms in MDs and highlight EIF3D, SOD1, and RPS26 as key regulators of immune and metabolic processes. These findings deepen our understanding of MD pathogenesis and suggest potential molecular targets for future therapeutic intervention.