A Workflow for Spatial Transcriptomic Analysis from Intra-operative Human Skeletal Muscle Biopsies

Abstract

IntroductionSuccessful reinnervation following peripheral nerve injury is highly variable, and the molecular programs underlying human muscle degeneration and recovery remain poorly defined. There is a critical need for high-resolution, spatially resolved gene expression data from human skeletal muscle obtained in clinically relevant settings. This study aimed to establish the feasibility of applying spatial transcriptomics to intra-operatively human muscle biopsies and to generate a framework for identifying gene expression signatures associated with reinnervation outcomes. MethodsTo validate the workflow, we collected biopsies intraoperatively from upper-extremity muscles during standard-of-care orthopaedic surgical procedures 5 months after traumatic brachial plexus injury. The flash-frozen biopsy was processed using the 10x Genomics Visium HD high-resolution platform. Quality metrics confirmed high RNA integrity and robust transcript detection at 8 {micro}m resolution. ResultsGenes involved in neuromuscular junction formation, degeneration, and regeneration were identified at subcellular resolution and showed fiber-type-specific expression patterns. Analyses were performed using complementary approaches in Seurat and Loupe Browser. ConclusionsTogether, these findings demonstrate the feasibility of spatial transcriptomics in human muscle, establish baseline gene-expression signatures, and provide a foundation for future studies aimed at identifying biomarkers associated with successful reinnervation and improved nerve-repair strategies.