Optimal Condition of Isolation from an Adipose Tissue-Derived Stromal Vascular Fraction for the Development of Automated Systems
10.1007/s13770-019-00238-3
- Author:
Su Jin LEE
1
;
Chae Rim LEE
;
Ki Joo KIM
;
Yeon Hee RYU
;
Eunjin KIM
;
Yu Na HAN
;
Suk-Ho MOON
;
Jong-Won RHIE
Author Information
1. Department of Biomedicine and Health Sciences, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
- Publication Type:Original Article
- From:
Tissue Engineering and Regenerative Medicine
2020;17(2):203-208
- CountryRepublic of Korea
- Language:English
-
Abstract:
Background:The stromal vascular fraction (SVF) isolated from adipose tissue, which contains stem cells as well as other cell types, has been applied in various research fields. Although different enzymatic concentrations and treatment durations have been applied to isolate the SVF, optimal conditions have not been established. Thus, we aimed to establish the optimal conditions for isolation of the SVF from adipose tissue by automated systems.
Methods:The SVF was collected from removed adipose tissues of five donors during surgery. The SVF was treated with 0.1% or 0.2% collagenase type I for 20, 40, or 60 min. Then, colony forming unit (CFU) assays and flow cytometry were performed to characterize the adipose stem cells (ASCs). A cytokine array was used to investigate the correlation between colony-formation ability and the secretion of isolated ASCs.
Results:Treatment with 0.1% collagenase type I for 60 min resulted in a higher SVF yield, whereas treatment with 0.1% collagenase for 40 min resulted in higher CFU values. In addition, expression of interleukin (IL)-6, IL-8, and monocyte chemoattractant protein-1 in the SVF was higher in the high-CFU group than in the low-CFU group.
Conclusion:The optimal conditions for isolation of the SVF from adipose tissue were treatment with 0.1% collagenase type I for 40 min. We identified the conditions required for efficient SVF isolation based on high CFU values, and our results will facilitate the development of automated systems.
