Skin regenerative capacity declines with age, but the underlying mechanisms are largely unknown. Here we demonstrate a functional link between epidermal growth factor receptor (EGFR) signaling and type XVII collagen (COL17A1) proteolysis on age-associated alteration of keratinocyte stem cell dynamics in skin regeneration. Live-imaging and computer simulation experiments predicted that human keratinocyte stem cell motility is coupled with self-renewal and epidermal regeneration. Receptor tyrosine kinase array identified the age-associated decline of EGFR signaling in mouse skin wound healing. Culture experiments proved that EGFR activation drives human keratinocyte stem cell motility with increase of COL17A1 by inhibiting its proteolysis through the secretion of tissue inhibitor of metalloproteinases 1 (TIMP1). Intriguingly, COL17A1 directly regulated keratinocyte stem cell motility and collective cell migration by coordinating actin and keratin filament networks. We conclude that EGFR-COL17A1 axis–mediated keratinocyte stem cell motility drives epidermal regeneration, which provides a novel therapeutic approach for age-associated impaired skin regeneration.

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.