AI Article Synopsis

  • Neuromuscular disorders can lead to muscle weakness and include serious conditions like amyotrophic lateral sclerosis (ALS) and myopathies.
  • Raman spectroscopy is being evaluated as a diagnostic tool to detect abnormal protein structures in muscles affected by these disorders, aiming to identify specific changes in protein folding.
  • The study found that myopathic conditions showed reduced α-helix structures and increased β-sheet structures, with Raman spectroscopy achieving high accuracy in identifying myopathy in both preclinical and human samples.

Article Abstract

Neuromuscular disorders are a group of conditions that can result in weakness of skeletal muscles. Examples include fatal diseases such as amyotrophic lateral sclerosis and conditions associated with high morbidity such as myopathies (muscle diseases). Many of these disorders are known to have abnormal protein folding and protein aggregates. Thus, easy to apply methods for the detection of such changes may prove useful diagnostic biomarkers. Raman spectroscopy has shown early promise in the detection of muscle pathology in neuromuscular disorders and is well suited to characterising the conformational profiles relating to protein secondary structure. In this work, we assess if Raman spectroscopy can detect differences in protein structure in muscle in the setting of neuromuscular disease. We utilise Raman spectroscopy measurements from preclinical models of amyotrophic lateral sclerosis and the myopathy Duchenne muscular dystrophy, together with measurements of human muscle samples from individuals with and without myopathy. Using quantitative conformation profiling and matrix factorisation we demonstrate that quantitative 'conformational fingerprinting' can be used to identify changes in protein folding in muscle. Notably, myopathic conditions in both preclinical models and human samples manifested a significant reduction in α-helix structures, with concomitant increases in β-sheet and, to a lesser extent, nonregular configurations. Spectral patterns derived through non-negative matrix factorisation were able to identify myopathy with a high accuracy (79% in mouse, 78% in human tissue). This work demonstrates the potential of conformational fingerprinting as an interpretable biomarker for neuromuscular disorders.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11056770PMC
http://dx.doi.org/10.1039/d4an00320aDOI Listing

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