Literature DB >> 29020636

Self-Organized Cerebral Organoids with Human-Specific Features Predict Effective Drugs to Combat Zika Virus Infection.

Momoko Watanabe1, Jessie E Buth1, Neda Vishlaghi1, Luis de la Torre-Ubieta2, Jiannis Taxidis3, Baljit S Khakh4, Giovanni Coppola2, Caroline A Pearson1, Ken Yamauchi1, Danyang Gong5, Xinghong Dai5, Robert Damoiseaux5, Roghiyh Aliyari6, Simone Liebscher7, Katja Schenke-Layland8, Christine Caneda9, Eric J Huang10, Ye Zhang9, Genhong Cheng6, Daniel H Geschwind11, Peyman Golshani2, Ren Sun5, Bennett G Novitch12.   

Abstract

The human cerebral cortex possesses distinct structural and functional features that are not found in the lower species traditionally used to model brain development and disease. Accordingly, considerable attention has been placed on the development of methods to direct pluripotent stem cells to form human brain-like structures termed organoids. However, many organoid differentiation protocols are inefficient and display marked variability in their ability to recapitulate the three-dimensional architecture and course of neurogenesis in the developing human brain. Here, we describe optimized organoid culture methods that efficiently and reliably produce cortical and basal ganglia structures similar to those in the human fetal brain in vivo. Neurons within the organoids are functional and exhibit network-like activities. We further demonstrate the utility of this organoid system for modeling the teratogenic effects of Zika virus on the developing brain and identifying more susceptibility receptors and therapeutic compounds that can mitigate its destructive actions.
Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Zika virus; cerebral cortex; differentiation; embryonic stem cell; human brain; neural development; neural stem cell; neurogenesis; organoid

Mesh:

Substances:

Year:  2017        PMID: 29020636      PMCID: PMC5637483          DOI: 10.1016/j.celrep.2017.09.047

Source DB:  PubMed          Journal:  Cell Rep            Impact factor:   9.423


  53 in total

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