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

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Authors: Patricia S. Pirbhoy, Vikram Murugan, Michael Hicks, Oswald Steward, Ranjan Gupta
Cited by: 0
References: 18

Abstract

Introduction: Successful 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. Methods: To 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 µm resolution. Results: Genes 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. Conclusions: Together, 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.

Fields of Study & Subjects

Single-cell and spatial transcriptomics Nerve injury and regeneration Muscle Physiology and Disorders

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publication date
26 February 2026
Language
EN
Document type
Preprint