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Biophysical analysis of drug efficacy on C. elegans models for neurodegenerative and neuromuscular diseases

Caenorhabditis elegans has emerged as a powerful model organism for drug screening due to its cellular simplicity, genetic amenability and homology to humans combined with its small size and low cost. Currently, high-throughput drug screening assays are mostly based on image-based phenotyping with t...

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Detalles Bibliográficos
Autores principales: Sofela, Samuel, Sahloul, Sarah, Song, Yong-Ak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8195402/
https://www.ncbi.nlm.nih.gov/pubmed/34115761
http://dx.doi.org/10.1371/journal.pone.0246496
Descripción
Sumario:Caenorhabditis elegans has emerged as a powerful model organism for drug screening due to its cellular simplicity, genetic amenability and homology to humans combined with its small size and low cost. Currently, high-throughput drug screening assays are mostly based on image-based phenotyping with the focus on morphological-descriptive traits not exploiting key locomotory parameters of this multicellular model with muscles such as its thrashing force, a critical biophysical parameter when screening drugs for muscle-related diseases. In this study, we demonstrated the use of a micropillar-based force assay chip in combination with a fluorescence assay to evaluate the efficacy of various drugs currently used in treatment of neurodegenerative and neuromuscular diseases. Using this two-dimensional approach, we showed that the force assay was generally more sensitive in measuring efficacy of drug treatment in Duchenne Muscular Dystrophy and Parkinson’s Disease mutant worms as well as partly in Amyotrophic Lateral Sclerosis model. These results underline the potential of our force assay chip in screening of potential drug candidates for the treatment of neurodegenerative and neuromuscular diseases when combined with a fluorescence assay in a two-dimensional analysis approach.