Cell Detection Methods to Enhance the Sorting Rate of a Large-Cell Sorter

Shrimp farming is widespread in Indonesia, and the risk of mass mortality due to disease outbreaks remains a significant concern. Recent research aimed at developing disease-resistant shrimp through genome editing has made remarkable progress. Additionally, the need for techniques that can efficiently isolate gene-edited cells is increasing. Currently, conventional cell sorters cannot be applied to millimeter-scale cells, such as egg cells; as a result, most isolation operations are still manual. To address this issue, we developed a millifluidics-based sorting system that selectively isolates only the fluorescently stained target cells from a population of large-sized cells. The sorting employs computer-based image processing, achieving high-purity sorting at a rate of 1.6 cells/s. This study aimed to improve the sorting rate while maintaining high purity by integrating the existing cell detection method with analog electronic fluorescence detection. As a result, a sorting rate of 2.85 cells/s was achieved even under non-optimized conditions, representing 1.8-fold increase in the sorting rate compared with that in a previous study. Because the cell detection speed is expected to be >10 times faster than previously described methods under optimized conditions, a sorting rate of >10 cells/s can be achieved in the future by further improving the detection circuit. This result represents a crucial step toward the practical implementation of high-speed and precision sorting technology for large cells.

Analog electronic circuit; Cell sorter; Fluorescence detection; Large-cell sorting; Real-time signal detection

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