Image-guided cell sorting using fast scanning lasers

Classification of cell types and isolation of targeted cells according to their imaging and spatial characteristics, beyond traditional fluorescently labeled biomarkers, enable the development of new biological insight and establishment of connections between phenotypical and morphological, and geno...

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Bibliographic Details
Main Authors: Xinyu Chen, Yi Gu, Jiajie Chen, Chang-Hung Lee, Ivan Gagne, Rui Tang, Lauren Waller, Zunming Zhang, Alex Ce Zhang, Yuanyuan Han, Weian Wang, Ian Y. Lian, Sung Hwan Cho, Yu-Hwa Lo
Format: Article
Language:English
Published: AIP Publishing LLC 2020-04-01
Series:APL Photonics
Online Access:http://dx.doi.org/10.1063/1.5144117
Description
Summary:Classification of cell types and isolation of targeted cells according to their imaging and spatial characteristics, beyond traditional fluorescently labeled biomarkers, enable the development of new biological insight and establishment of connections between phenotypical and morphological, and genomic cell information in normal and diseased states. Here, we demonstrate a microfluidic flow cytometer cell sorter that uses fast scanning laser excitation sources and photomultiplier tubes (PMTs), coupled with real-time image processing, to image and sort cells based on user-defined spatial features. Dozens of features, including label-free characteristics such as size, shape, scattering pattern, morphology, as well as the spatial distribution of fluorescently labeled biomarkers, greatly expand the available information space in cell analysis. The use of a disposable microfluidic cartridge that is compatible with the imaging system contributes to size reduction and lowered risk of cross contamination. The so-called cameraless design that uses PMTs to replace CCD makes the system more compatible with conventional fluorescence-activated cell sorters and user friendly, while enjoying the sensitivity and benefits of PMTs. The cell image features can be directly extracted from the temporal waveforms or from the reconstructed cell images via temporal–spatial transformation.
ISSN:2378-0967