Single-molecule fluorescence-activated cell sorting (smFACS): sorting cells molecule by molecule

The goal of this project is to develop a flow cytometer with single-molecule sensitivity, for characterising and sorting cells with low copy numbers of membrane proteins. Contemporary flow cytometers cannot distinguish individual molecules due to the background fluorescence produced by cells, which is much larger than the emission produced by a single fluorescent antibody. This will be overcome by developing a novel sensitive imaging flow cytometry device, that will produce a 3D representation of each cell to visualise individual membrane proteins. This microfluidic device will use high-speed single-molecule light-sheet microscopy, which overcomes sensitivity limitations of contemporary cytometers to enable characterisation of cells at high flow rates (up to 100 cells/s). Because of the high image acquisition rate (100 kHz), it will be necessary to analyse images in real time on an embedded imaging platform. Field Programmable Gate Arrays (FPGA) will be utilised for the high-speed camera interface, data flow and peripheral interface, while graphics processing units will be employed for image processing. The well-defined solution set lends itself to AI/deep learning solutions and it is expected that this system will have a processing rate of three orders of magnitude beyond traditional approaches. Not only will this ensure a high throughput rate for flow cytometry, but it will also enable fluorescence-activated cell sorting (FACS) with single-molecule sensitivity (smFACS).
Developed devices will be used to explore how the increased sensitivity can aid in screening patient cells. This project will push the limits of how fast single-molecule imaging can be performed and ultimately the goal is for such a device to be employed in hospitals to maximise the number of patients that can be treated by targeting specific molecules expressed on cell membranes.