Error accumulated in DNA during replication has been considered as a cause of aging and cancer development. Immortal strand hypothesis has been proposed, which explained a DNA segregation mechanism of parent stem cell to diminish the accumulation of error in DNA. The observation of such mechanism has been reported on muscle stem cell of mice with pulse chase experiments. However, such observations are considered as indirect evidence, either with indirect distance-based or drug treatment for cell pair identification, or with artificial way to trigger the mechanism. Such mechanism has also been reported and captured by videomicroscopy on muscle stem cell of perinatal mice with low frequency, whether the mechanism also occurred on adult muscle stem cells is in concerned.

To address with,...[ Read more ]

Error accumulated in DNA during replication has been considered as a cause of aging and cancer development. Immortal strand hypothesis has been proposed, which explained a DNA segregation mechanism of parent stem cell to diminish the accumulation of error in DNA. The observation of such mechanism has been reported on muscle stem cell of mice with pulse chase experiments. However, such observations are considered as indirect evidence, either with indirect distance-based or drug treatment for cell pair identification, or with artificial way to trigger the mechanism. Such mechanism has also been reported and captured by videomicroscopy on muscle stem cell of perinatal mice with low frequency, whether the mechanism also occurred on adult muscle stem cells is in concerned.

To address with, live cell imaging with time-lapse microscopy is used to capture adult muscle stem cells of mice with high cell density in culture to record large amounts of cell divisions as direct evidence for the study of the hypothesis. Since the mechanism has remained unclear, to reduce the uncertainty of the experiments, label-free imaging techniques are considered. Rapid morphological change of the muscle stem cells would be a challenge on cell tracking. Also, the use of high cell density could further increase the difficulty of tracking cell and identifying cell pairs accurately.

In this work, label-free framework for cell tracking with optical time-lapse imaging and machine learning is proposed to study the hypothesis. Multiple state-of-the-art deep learning model for segmentation is examined to determine model with the best performance, followed with cell tracker to perform cell tracking. This thesis demonstrates the use of the framework for cell tracking and the study of immortal strand hypotheses on adult muscle stem cells of mice in culture by cell pairs identification and DNA strand segregation evaluation.