4.7 Article

Efficient derivation of sympathetic neurons from human pluripotent stem cells with a defined condition

Journal

SCIENTIFIC REPORTS
Volume 8, Issue -, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41598-018-31256-1

Keywords

-

Funding

  1. Japan Agency for Medical Research and Development (AMED)
  2. AMED [17935244]
  3. Japan Society for the Promotion of Science (JSPS) KAKENHI [16673093, 16H02682]
  4. Mochida Memorial Foundation for Medical and Pharmaceutical Research
  5. Takeda Science Foundation
  6. iPS Cell Research Fund
  7. Grants-in-Aid for Scientific Research [16H02682] Funding Source: KAKEN

Ask authors/readers for more resources

Sympathetic neurons (SNs) are an essential component of the autonomic nervous system. They control vital bodily functions and are responsible for various autonomic disorders. However, obtaining SNs from living humans for in vitro study has not been accomplished. Although human pluripotent stem cell (hPSC)-derived SNs could be useful for elucidating the pathophysiology of human autonomic neurons, the differentiation efficiency remains low and reporter-based cell sorting is usually required for the subsequent pathophysiological analysis. To improve the efficiency, we refined each differentiation stage using PHOX2B::eGFP reporter hPSC lines to establish a robust and efficient protocol to derive functional SNs via neuromesodermal progenitor-like cells and trunk neural crest cells. Sympathetic neuronal progenitors could be expanded and stocked during differentiation. Our protocol can selectively enrich sympathetic lineage-committed cells at high-purity (approximate to 80%) from reporter-free hPSC lines. Our system provides a platform for diverse applications, such as developmental studies and the modeling of SN-associated diseases.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available