An optimized force-triggered density gradient sedimentation method for isolation of pelage follicle dermal papilla cells from neonatal mouse skin

Author:

Du Lijuan,Gan Yuyang,Zheng Bowen,Huang Junfei,Hu Zhiqi,Miao YongORCID

Abstract

Abstract Background The dermal papilla cells are a specialized population of mesenchymal cells located at the base of the hair follicle (HF), which possess the capacity to regulate HF morphogenesis and regeneration. However, lack of cell-type specific surface markers restricts the isolation of DP cells and application for tissue engineering purposes. Methods We describe a novel force-triggered density gradient sedimentation (FDGS) method to efficiently obtain purified follicular DP-spheres cells from neonatal mouse back skin, utilizing only centrifugation and optimized density gradients. Results Expression of characteristic DP cell markers, alkaline phosphatase, β-catenin, versican, and neural cell adhesion molecules, were confirmed by immunofluorescence. Further, the patch assays demonstrated that DP cells maintained their hair regenerative capacity in vivo. Compared with current methods, including microdissection and fluorescence-activated cell sorting, the FDGS technique is simpler and more efficient for isolating DP cells from neonatal mouse skin. Conclusions The FDGS method will improve the research potential of neonatal mouse pelage-derived DP cells for tissue engineering purposes.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

Springer Science and Business Media LLC

Subject

Cell Biology,Biochemistry, Genetics and Molecular Biology (miscellaneous),Molecular Medicine,Medicine (miscellaneous)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3