The ability to isolate subpopulations or even single cells from heterogeneous populations is a fundamental necessity in modern biology and biomedicine. Conventional techniques for separating subpopulations include fluorescence activated cell sorting (FACS), magnetic activated cell sorting (MACS), laser capture microdissection, and DEP array sorting. While all of these techniques are utilized in individual applications, each has its own set of advantages and drawbacks. The technique most widely used for isolating single cells from populations with high purity is FACS, thanks to its relatively gentle sorting mechanism, high sensitivity, multiparameter measurement capability, and ability to analyze both intracellular and surface markers. While FACS is widely used across all areas of cell biology, it has a significant limitation of making sort decisions based only on the average value of a cell's parameters, due to its lack of sub-cellular resolution. For example, FACS only measures the total fluorescence from a cell, and is unable to distinguish where the fluorescent probe is localized within the cell (e.g. on the cell membrane, in the cytoplasm, or in the nucleus) This is a significant limitation if one desires to separate populations of cells that may have translocated a protein from the cytoplasm to the nucleus, or if one wishes to separate cells based on a measurement of the nuclear to cytoplasmic area ratio, for example. Here, we propose to develop an image-based cell sorter based on novel signal processing algorithms and a high throughput imaging flow cytometer, already developed by Omega Biosystems. This tool, to be completed and ready for commercialization by the end of Phase II of this program, will provide a transformative advance in the sensitivity, specificity and spatial resolution of flow sorters for separating single cells and subpopulations from a heterogeneous cellular population. The advent of such a high-resolution cell sorting tool will have a broad impact across biomedicine and cell biology, as well as enable immediate advances in the fields of drug discovery and rare cell detection.
An instrument capable of sorting single cells at high throughput, based upon their brightfield, darkfield, and multi-channel fluorescence images is proposed for improving drug discovery, rare cell detection, and other applications in biomedicine and cell biology. This image-based cell sorter will enable unprecedented sensitivity and specificity in cell sorting, as well as the ability to sort cells by imaging and analyzing their su-cellular features.
