Rapid neurogenesis through transcriptional activation in human stem cells
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Busskamp-2014-Rapid neurogenesis t.pdf
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Author(s)
Guye, Patrick
Li, Yinqing
Weiss, Ron
Busskamp, Volker
Lewis, Nathan E.
Ng, Alex H. M.
Shipman, Seth L.
Byrne, Susan M.
Li, Shangzhong
Stadler, Michael
Date Issued
November 2014
Journal
Molecular Systems Biology
Publisher
Nature Publishing Group
Citation
Busskamp, Volker, Nathan E. Lewis, Patrick Guye, Alex H.M. Ng, Seth L. Shipman, Susan M. Byrne, Neville E. Sanjana, et al. “Rapid Neurogenesis through Transcriptional Activation in Human Stem Cells.” Molecular Systems Biology 10, no. 11 (November 1, 2014): 760–760.
Version
Final published version
Abstract
Advances in cellular reprogramming and stem cell differentiation now enable ex vivo studies of human neuronal differentiation. However, it remains challenging to elucidate the underlying regulatory programs because differentiation protocols are laborious and often result in low neuron yields. Here, we overexpressed two Neurogenin transcription factors in human‐induced pluripotent stem cells and obtained neurons with bipolar morphology in 4 days, at greater than 90% purity. The high purity enabled mRNA and microRNA expression profiling during neurogenesis, thus revealing the genetic programs involved in the rapid transition from stem cell to neuron. The resulting cells exhibited transcriptional, morphological and functional signatures of differentiated neurons, with greatest transcriptional similarity to prenatal human brain samples. Our analysis revealed a network of key transcription factors and microRNAs that promoted loss of pluripotency and rapid neurogenesis via progenitor states. Perturbations of key transcription factors affected homogeneity and phenotypic properties of the resulting neurons, suggesting that a systems‐level view of the molecular biology of differentiation may guide subsequent manipulation of human stem cells to rapidly obtain diverse neuronal types.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
McGovern Institute for Brain Research at MIT
Picower Institute for Learning and Memory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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DOI of Published Version
https://doi.org/10.15252/msb.20145508
