bioRxivCell BiologyPreprint
Perturbed actin cap and nuclear morphology in primary fibroblasts of Huntington's disease patients as a new phenotypic marker for personalized drug evaluation
S. Gharaba, O. Paz, L. Feld, A. Abashidze, M. Weinrab, H. Wolfenson, M. Weil
Abstract
Human primary skin fibroblast cells from patients skin biopsies were used previously as a model to study different neurodegenerative diseases, including Huntingtons Disease (HD). These cells are directly isolated from the patients tissue without any alteration in the genome, retaining in culture conditions their endogenous cellular characteristics and biochemical properties, as well as their cellular proliferation capacity for several passages. The aim of this study was to identify a distinctive cellular phenotype in primary skin fibroblasts from various HD patients, using image-based high content analysis, which could be used in the future for personalized drug screening treatment evaluation. We show that HD fibroblasts have a distinctive nuclear morphology associated with a nuclear actin cap deficiency, which in turn affects cell motility in a similar manner to primary skin fibroblasts from Hutchinson-Gilford progeria syndrome (HGPS) patients used as known actin cap deficient cells. Moreover, treatment of the HD cells with either Latrunculin B, used to disrupt actin cap formation, or the antioxidant agent Mitoquinone, used to improve mitochondrial activity, show opposite effects on actin cap associated morphological features and cell motility. The former exacerbates the HD phenotype while the latter improves it. Deep data analysis of the HD nuclear and actin cap features using custom developed image analysis algorithms allow strong cluster classification distinct from HGPS and healthy matching controls, supporting the finding of a novel HD cellular phenotypic marker that could be modulated by pharmacological agents in this patient-based disease model.
- organism: human
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- approach: microscopy & imaging analysis
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