Intelligent image-activated cell sorting 2.0.

The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. 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, fluorescence-activated cell sorting (FACS), and deep learning. Here we report an iIACS machine that far surpasses the state-of-the-art iIACS machine in system performance in order to expand the range of applications and discoveries enabled by the technology. Specifically, it provides a high throughput of ∼2000 events per second and a high sensitivity of ∼50 molecules of equivalent soluble fluorophores (MESFs), both of which are 20 times superior to those achieved in previous reports. This is made possible by employing (i) an image-sensor-based optomechanical flow imaging method known as virtual-freezing fluorescence imaging and (ii) a real-time intelligent image processor on an 8-PC server equipped with 8 multi-core CPUs and GPUs for intelligent decision-making, in order to significantly boost the imaging performance and computational power of the iIACS machine. We characterize the iIACS machine with fluorescent particles and various cell types and show that the performance of the iIACS machine is close to its achievable design specification. Equipped with the improved capabilities, this new generation of the iIACS technology holds promise for diverse applications in immunology, microbiology, stem cell biology, cancer biology, pathology, and synthetic biology.

Real-time single-cell imaging of protein secretion.

Protein secretion, a key intercellular event for transducing cellular signals, is thought to be strictly regulated. However, secretion dynamics at the single-cell level have not yet been clarified because intercellular heterogeneity results in an averaging response from the bulk cell population. To address this issue, we developed a novel assay platform for real-time imaging of protein secretion at single-cell resolution by a sandwich immunoassay monitored by total internal reflection microscopy in sub-nanolitre-sized microwell arrays. Real-time secretion imaging on the platform at 1-min time intervals allowed successful detection of the heterogeneous onset time of nonclassical IL-1ß secretion from monocytes after external stimulation. The platform also helped in elucidating the chronological relationship between loss of membrane integrity and IL-1ß secretion. The study results indicate that this unique monitoring platform will serve as a new and powerful tool for analysing protein secretion dynamics with simultaneous monitoring of intracellular events by live-cell imaging.