UC San Diego
Cameraless High-throughput Imaging Flow Cytometry for Biomedical Applications
- Author(s): Han, Yuanyuan
- Advisor(s): Lo, Yu-Hwa
- Ng, Tse Nga
- et al.
High-throughput optical sensing and imaging instrument for capture and analysis of cells are among the most essential tools for biomedical applications. While optical microscopy is one of the most widely used methods for unveiling the molecular composition of biological specimens, flow cytometry is the gold standard high-throughput tool for single-cell characterization in numerous biomedical and clinical applications. The strong desire to fill in the technological gap between the high-content fluorescence microscope and high-throughput flow cytometer has inspired us to develop a cell analyzer platform with three-dimensional (3D) imaging capabilities.
This dissertation details the development of a 3D imaging flow cytometer, in which microfluidics, acousto-optical, optical and electronic systems are integrated. Based on one enabling technology, namely spatial-temporal transformation, we first developed a novel high-throughput two-dimensional imaging tool for flow cytometry applications. Instead of replacing the single-pixel photodetectors commonly used in flow cytometry with mega-pixelated cameras, this technology uses mathematical algorithms and a specially designed spatial filter to give flow cytometers capabilities of high-throughput, motion-blur-free, multi-color, and multi-mode imaging of single cells. By virtue of the simplicity, high flexibility, and high scalability of this technology, we then combined it with optical sectioning and high-speed laser scanning techniques to enable 3D fluorescence and 90-degree side-scattering imaging of single cells at flow speeds as high as a meter per second. The cameraless 3D imaging flow cytometry uses multiple scanning techniques to add spatial information in a fairly conventional flow cytometry architecture amenable to wide adoption. By precisely mapping time to space, photodetector readout at one timepoint corresponds to one voxel in a 3D space. Through experiments on various biological samples, we demonstrate the functionality of the 3D imaging flow cytometry platform.
As big data create a bonanza for scientists and image-based cell sorter has been brought about, such a high-throughput 3D imaging flow cytometry system will be an enabler to connect phenotype and genotype studies in the fields of immunology, oncology, cell- and gene- therapy, and drug discovery, where heterogeneity is recognized.