Quantitative single-cell biology via intelligent Drop-Screen
Chia-Hung Chen
Department of Biomedical Engineering, City University of Hong Kong
chiachen@cityu.edu.hk
Abstract
Single-cell analysis is essential to precisely analyze bioprocesses in physiological systems to evaluate clinical situations. In this study an intelligent Drop-Screen system was developed to rapidly determine single cell phenotypes, which provide a valuable insight into functional heterogeneity indicating disease progressions, such as tumor metastasis. To reach this goal, we designed an integrative platform employing droplet-based technology, imaging technology, and data driven computational method for high-throughput continuous-flow single-cell assays. The single cells and chemical sensors were encapsulated within the droplets via microfluidics. A system with high-speed fluorescence analysis of single cells and a high rate of data transmission between modules and software was developed for continuous flow cell analysis. Analog voltage signals from the Photomultiplier tubes (PMTs) were converted to digital form through a data acquisition (DAQ) system (National Instruments, USA) at a sampling rate of ~12,500 samples/s. To perform high throughput cell type identification, a library (data base) of different cell lines was constructed. With this data base, k-NN algorithm was conducted to identify the species of unknown single tumor cells for rapid tumor profiling. For example, multiple clinical enzyme (protease) activities in single cells were measured by compartmentalizing colored enzymatic substrates (showing distinguished emissions) and individual cells in the droplets. After incubation, droplets were uploaded to a Droplet-Screen system for high-throughput single cell analysis in a continuous-flow manner (~100 droplets per second) to evaluate tumor’s migration capabilities. Similar approach was also used to indicate/sort drug resistant of single cells in a tumor.
Short Bio
Dr. Chen is focused on developing integrative platforms for biomedical applications. Compared with most platforms using gene sequence for quantitative biology, integrative functional assay offers unique advantages for the rapid characterization of biological samples for diagnosis and timely precision medicine. With the possibility of high-throughput biological sample screening and cell sorting using the integrative platform, statistically information could be obtained for effective quantitative biological analysis. For example, an intelligent system that integrated imaging technology, multiplexed chemical sensors and a computational data-analysis method was previously developed to analyze small amounts of physiological samples to determine the disease progression of individual patients with cancer. Before joining City University of Hong Kong, Dr. Chen worked at National University of Singapore and Massachusetts Institute of Technology. He received his Ph.D. degree at University of Cambridge. He earned his M.S. degree at Harvard University, and earned his B.S. degree at National Taiwan University.