Intelligent Image-Activated Cell Sorting: A Tutorial
January 8, 2020
Keisuke Goda, Ph.D.
University of Tokyo
University of California, Los Angeles
About the Presenter
Dr. Goda is a professor in the Department of Chemistry at the University of Tokyo, an adjunct professor in the Institute of Technological Sciences at Wuhan University, and an adjunct professor in the Department of Bioengineering at UCLA. He obtained a BA degree from UC Berkeley summa cum laude in 2001 and a PhD from MIT in 2007, both in physics. At MIT, he worked on the development of gravitational-wave detectors in the LIGO group which led to the 2017 Nobel Prize in Physics. After several years of work on high-speed imaging and microfluidics at UCLA, he joined the University of Tokyo as a professor. His research group focuses on the development of serendipity-enabling technologies based on molecular imaging and spectroscopy together with microfluidics and computational analytics to push the frontier of science. He is an associate editor of Cytometry Part A and APL Photonics. He has published >350 journal and conference papers, filed >30 patents, and received numerous awards such as Japan Academy Medal, JSPS Prize, and Analytical Chemistry Young Innovator Award.
The advent of intelligent Image-Activated Cell Sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells or cell clusters with unique morphochemical features that are difficult to discern when compressing these spatial data into intensity signals in fluorescence-activated cell sorting (FACS) [Nitta et al., Cell 175, 266-276 (2018)]. iIACS is an on-chip microfluidic technology that builds on a seamless integration of a high-throughput fluorescence microscope, cell focuser, cell sorter, and deep neural network on a hybrid software-hardware data management architecture, thereby providing the combined merits of optical microscopy, FACS, and deep learning [Isozaki et al., Nature Protocols 14, 2370-2425 (2019)]. Therefore, iIACS serves as an essential part of holistic single-cell analysis by providing direct connections between population-level analysis (flow cytometry), cell-level analysis (microscopy), and gene-level analysis (sequencing) of sorted cells. In this webinar, I will give a tutorial about the principles and applications of iIACS and compare the usability of iIACS with other technologies such as FACS, imaging flow cytometry (without sorting), and image-based cell pickers.
Explore the principles and applications of the iIACS technology
Who Should Attend
FACS developers/users, imaging flow cytometry developers/users, single-cell analysis researchers, etc.