1. Long Term Gene Expression in Human Induced Pluripotent Stem Cells and Cerebral Organoids to Model a Neurodegenerative Disease
- Author
-
Ferid Nassor, Rafika Jarray, Denis S. F. Biard, Auriane Maïza, Dulce Papy-Garcia, Serena Pavoni, Jean-Philippe Deslys, and Frank Yates
- Subjects
stem cells ,cerebral organoid ,neurodegenerative disease ,fronto-temporal dementia ,Alzheimer ,IPS ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Human brain organoids (mini-brains) consist of self-organized three-dimensional (3D) neural tissue which can be derived from reprogrammed adult cells and maintained for months in culture. These 3D structures manifest substantial potential for the modeling of neurodegenerative diseases and pave the way for personalized medicine. However, as these 3D brain models can express the whole human genetic complexity, it is critical to have access to isogenic mini-brains that only differ in specific and controlled genetic variables. Genetic engineering based on retroviral vectors is incompatible with the long-term modeling needed here and implies a risk of random integration while methods using CRISPR-Cas9 are still too complex to adapt to stem cells. We demonstrate in this study that our strategy which relies on an episomal plasmid vector derived from the Epstein-Barr virus (EBV) offers a simple and robust approach, avoiding the remaining caveats of mini-brain models. For this proof-of-concept, we used a normal tau protein with a fluorescent tag and a mutant genetic form (P301S) leading to Fronto-Temporal Dementia. Isogenic cell lines were obtained which were stable for more than 30 passages expressing either form. We show that the presence of the plasmid in the cells does not interfere with the mini-brain differentiation protocol and obtain the development of a pathologically relevant phenotype in cerebral organoids, with pathological hyperphosphorylation of the tau protein. Such a simple and versatile genetic strategy opens up the full potential of human organoids to contribute to disease modeling, personalized medicine and testing of therapeutics.
- Published
- 2020
- Full Text
- View/download PDF