Modeling amyotrophic lateral sclerosis in pure human iPSc-derived motor neurons isolated by a novel FACS double selection technique - Institut Pasteur Accéder directement au contenu
Article Dans Une Revue Neurobiology of Disease Année : 2015

Modeling amyotrophic lateral sclerosis in pure human iPSc-derived motor neurons isolated by a novel FACS double selection technique

Résumé

Amyotrophic lateral sclerosis (ALS) is a severe and incurable neurodegenerative disease. Human motor neurons generated from induced pluripotent stem cells (iPSc) offer new perspectives for disease modeling and drug testing in ALS. In standard iPSc-derived cultures, however, the two major phenotypic alterations of ALS--degeneration of motor neuron cell bodies and axons--are often obscured by cell body clustering, extensive axon criss-crossing and presence of unwanted cell types. Here, we succeeded in isolating 100% pure and standardized human motor neurons by a novel FACS double selection based on a p75(NTR) surface epitope and an HB9::RFP lentivirus reporter. The p75(NTR)/HB9::RFP motor neurons survive and grow well without forming clusters or entangled axons, are electrically excitable, contain ALS-relevant motor neuron subtypes and form functional connections with co-cultured myotubes. Importantly, they undergo rapid and massive cell death and axon degeneration in response to mutant SOD1 astrocytes. These data demonstrate the potential of FACS-isolated human iPSc-derived motor neurons for improved disease modeling and drug testing in ALS and related motor neuron diseases.
Fichier non déposé

Dates et versions

pasteur-03255509 , version 1 (09-06-2021)

Identifiants

Citer

Diana Toli, Dorothée Buttigieg, Stéphane Blanchard, Thomas Lemonnier, Boris Lamotte d'Incamps, et al.. Modeling amyotrophic lateral sclerosis in pure human iPSc-derived motor neurons isolated by a novel FACS double selection technique. Neurobiology of Disease, 2015, 82, pp.269-280. ⟨10.1016/j.nbd.2015.06.011⟩. ⟨pasteur-03255509⟩
26 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More