Label-free quality control and identification of human keratinocyte stem cells by deep learning-based automated cell tracking.

Autor: Hirose T; Graduate School of Medical Care and Technology, Teikyo University, Tokyo, Japan., Kotoku J; Graduate School of Medical Care and Technology, Teikyo University, Tokyo, Japan., Toki F; Department of Stem Cell Biology, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan., Nishimura EK; Department of Stem Cell Biology, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.; Division of Aging and Regeneration, Institute of Medical Science, The University of Tokyo, Tokyo, Japan., Nanba D; Department of Stem Cell Biology, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.
Jazyk: angličtina
Zdroj: Stem cells (Dayton, Ohio) [Stem Cells] 2021 Aug; Vol. 39 (8), pp. 1091-1100. Date of Electronic Publication: 2021 Mar 30.
DOI: 10.1002/stem.3371
Abstrakt: Stem cell-based products have clinical and industrial applications. Thus, there is a need to develop quality control methods to standardize stem cell manufacturing. Here, we report a deep learning-based automated cell tracking (DeepACT) technology for noninvasive quality control and identification of cultured human stem cells. The combination of deep learning-based cascading cell detection and Kalman filter algorithm-based tracking successfully tracked the individual cells within the densely packed human epidermal keratinocyte colonies in the phase-contrast images of the culture. DeepACT rapidly analyzed the motion of individual keratinocytes, which enabled the quantitative evaluation of keratinocyte dynamics in response to changes in culture conditions. Furthermore, DeepACT can distinguish keratinocyte stem cell colonies from non-stem cell-derived colonies by analyzing the spatial and velocity information of cells. This system can be widely applied to stem cell cultures used in regenerative medicine and provides a platform for developing reliable and noninvasive quality control technology.
(© 2021 The Authors. STEM CELLS published by Wiley Periodicals LLC on behalf of AlphaMed Press.)
Databáze: MEDLINE
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