Abstract
Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only about 6 days after reprogramming initiation, iPS cells can be experimentally determined via fluorescent probes. What is more, the ratio of progenitor cells during early reprograming period is below 5%, which is too low to capture experimentally in the early stage. In this paper, we propose a novel computational approach for the identification of iPS progenitor cells based on machine learning and microscopic image analysis. Firstly, we record the reprogramming process using a live cell imaging system after 48 hours of infection with retroviruses expressing Oct4, Sox2 and Klf4, later iPS progenitor cells and normal murine embryonic fibroblasts (MEFs) within 3 to 5 days after infection are labeled by retrospectively tracing the time-lapse microscopic image. We then calculate 11 types of cell morphological and motion features such as area, speed, etc., and select best time windows for modeling and perform feature selection. Finally, a prediction model using XGBoost is built based on the selected six types of features and best time windows. Our model allows several missing values/frames in the sample datasets, thus it is applicable to a wide range of scenarios. Cross-validation, holdout validation and independent test experiments show that the minimum precision is above 52%, that is, the ratio of predicted progenitor cells within 3 to 5 days after viral infection is above 52%. The results also confirm that the morphology and motion pattern of iPS progenitor cells is different from that of normal MEFs, which helps with the machine learning methods for iPS progenitor cell identification.
Highlights
Induced pluripotent stem cells are cells with embryonic-like state reprogrammed from mouse embryonic or adult fibroblasts by introducing the defined factors [1]
Since Takahashi and Yamanaka [1] first proposed the methods of reprogramming somatic cells to induced pluripotent stem (iPS) cells, it has become an important method for clinical cell therapy, and revolutionized regenerative medicine [2], such as platelet deficiency [3], spinal cord injury [4], macular degeneration [5], Parkinson’s disease [6] and Alzheimer’s disease [7]
Datasets were generated from the training datasets, which were about 52~59 iPS cells and 259~294 normal murine embryonic fibroblasts (MEFs) for time windows with 10 frames, 43~50 iPS cells and 238~264 normal MEFs for time windows with 19 frames
Summary
Induced pluripotent stem (iPS) cells are cells with embryonic-like state reprogrammed from mouse embryonic or adult fibroblasts by introducing the defined factors [1]. Since Takahashi and Yamanaka [1] first proposed the methods of reprogramming somatic cells to iPS cells, it has become an important method for clinical cell therapy, and revolutionized regenerative medicine [2], such as platelet deficiency [3], spinal cord injury [4], macular degeneration [5], Parkinson’s disease [6] and Alzheimer’s disease [7]. Obstacles still remain in scientific and clinical applications for iPS cells because of potential tumorigenicity and low efficiency of reprogramming technique [8,9,10]. Inefficiency concerns low frequency for reprogramming cells, which is less than a small proportion of 5%. The ratio of progenitor cells during the early stage of reprogramming is even under 0.5%
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