Automated immunofluorescence analysis for sensitive and precise dystrophin quantification in muscle biopsies

自动免疫荧光分析可灵敏、精确地定量肌肉活检中的肌营养不良蛋白

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作者:Tatyana A Vetter, Stefan Nicolau, Adrienne J Bradley, Emma C Frair, Kevin M Flanigan

Aims

Dystrophin, the protein product of the DMD gene, plays a critical role in muscle integrity by stabilising the sarcolemma during contraction and relaxation. The DMD gene is vulnerable to a variety of mutations that may cause complete loss, depletion or truncation of the protein, leading to Duchenne and Becker muscular dystrophies. Precise and reproducible dystrophin quantification is essential in characterising DMD mutations and evaluating the outcome of efforts to induce dystrophin through gene therapies. Immunofluorescence microscopy offers high sensitivity to low levels of protein expression along with confirmation of localisation, making it a critical component of quantitative dystrophin expression assays.

Conclusion

As efforts to restore dystrophin expression in dystrophic muscle bring new potential therapies into clinical trials, this methodology represents a valuable tool for efficient and precise analysis of dystrophin and other muscle markers that reflect treatment efficacy.

Methods

We have developed an automated and unbiased approach for precise quantification of dystrophin immunofluorescence in muscle sections. This methodology uses microscope images of whole-tissue sections stained for dystrophin and spectrin to measure dystrophin intensity and the proportion of dystrophin-positive coverage at the sarcolemma of each muscle fibre. To ensure objectivity, the thresholds for dystrophin and spectrin are derived empirically from non-sarcolemmal signal intensity within each tissue section. Furthermore, this approach is readily adaptable for measuring fibre morphology and other tissue markers.

Results

Our method demonstrates the sensitivity and reproducibility of this quantification approach across a wide range of dystrophin expression in both dystrophinopathy patient and healthy control samples, with high inter-operator concordance.

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