This study aims to generate robust tools and workflows for creating human induced pluripotent stem cell (hIPSC)-based models of autism spectrum disorder (ASD), and to develop scalable assays for predictive molecular and cellular phenotypes relevant to autism. We have identified several key bottlenecks in the widespread adoption of hIPSCs as tools that allow the dissection of molecular mechanisms underlying neurological disease and enable preclinical drug screening. We have assembled a team of five leading experts in neuroscience, stem cell biology and computational biology, who will collaborate up with three innovation-driven biotech companies (Fluidigm, BD Biosciences and Synthetic Genomics) to overcome these roadblocks. Since autism is considered a disorder of synapse development and function that ultimately leads to circuit dysfunction in the brain, we will develop quantitative assays of synapse end network function that can be used in high-throughput drug screens. We also aim to uncover the upstream molecular events that precipitate synaptic and network dysregulation, and identify predictive RNA and protein signatures. Our strategy is to engineer models of genetic forms of autism by genomic manipulation using a well- characterized, neurotypical hIPSC line as the starting point. We will then differentiate these normal and mutant cells to cortical neurons and astrocytes, the two cell types that have been most strongly implicated in autism pathophysiology. Highly quantitative and sensitive assays at the single-cell level will be used to identify changes in protein and RNA expression that can distinguish ASD neurons and astrocytes from normal cells. Finally, we will develop assays measuring synapse density and strength using advanced technology that can be used in high-throughput format. We envision that our tools, technologies and assays, all of which we will make publicly available as they are being generated, will both critically contribute to our understanding of ASD and accelerate preclinical research of neurological disease.
Autism is a complex disorder of brain development whose core symptoms cannot be currently treated with medicines. By using genetically engineered stem cells, we aim to take advantage of recent insights into the genetic basis of autism to develop tools and technologies that allow its modeling in the laboratory. Ultimately, our research will help identify potential drug targets and new diagnostic methods for this increasingly common condition.
| Mesci, Pinar; Macia, Angela; LaRock, Christopher N et al. (2018) Modeling neuro-immune interactions during Zika virus infection. Hum Mol Genet 27:41-52 |
| Chailangkarn, Thanathom; Noree, Chalongrat; Muotri, Alysson R (2018) The contribution of GTF2I haploinsufficiency to Williams syndrome. Mol Cell Probes 40:45-51 |
| Brito, Anita; Russo, Fabiele Baldino; Muotri, Alysson Renato et al. (2018) Autism spectrum disorders and disease modeling using stem cells. Cell Tissue Res 371:153-160 |
| Fernandes, Isabella R; Cruz, Ana C P; Ferrasa, Adriano et al. (2018) Genetic variations on SETD5 underlying autistic conditions. Dev Neurobiol 78:500-518 |
| Mesci, Pinar; Macia, Angela; Moore, Spencer M et al. (2018) Blocking Zika virus vertical transmission. Sci Rep 8:1218 |
| Beltrão-Braga, Patricia C B; Muotri, Alysson R (2017) Modeling autism spectrum disorders with human neurons. Brain Res 1656:49-54 |
| Song, Yan; Botvinnik, Olga B; Lovci, Michael T et al. (2017) Single-Cell Alternative Splicing Analysis with Expedition Reveals Splicing Dynamics during Neuron Differentiation. Mol Cell 67:148-161.e5 |
| de Souza, Janaina S; Carromeu, Cassiano; Torres, Laila B et al. (2017) IGF1 neuronal response in the absence of MECP2 is dependent on TRalpha 3. Hum Mol Genet 26:270-281 |
| Shiryaev, Sergey A; Mesci, Pinar; Pinto, Antonella et al. (2017) Repurposing of the anti-malaria drug chloroquine for Zika Virus treatment and prophylaxis. Sci Rep 7:15771 |
| Kakaradov, Boyko; Arsenio, Janilyn; Widjaja, Christella E et al. (2017) Early transcriptional and epigenetic regulation of CD8+ T cell differentiation revealed by single-cell RNA sequencing. Nat Immunol 18:422-432 |
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