Image-Based Single Cell Sorting Automation in Droplet Microfluidics

Abstract

the recent boom in single-cell omics has brought researchers one step closer to understanding the biological mechanisms associated with cell heterogeneity. Rare cells that have historically been obscured by bulk measurement techniques are being studied by single cell analysis and providing valuable insight into cell function. To support this progress, novel upstream capabilities are required for single cell preparation for analysis. Presented here is a droplet microfluidic, image-based single-cell sorting technique that is flexible and programmable. The automated system performs real-time dualcamera imaging (brightfield & fluorescent), processing, decision making and sorting verification. To demonstrate capabilities, the system was used to overcome the Poisson loading problem by sorting for droplets containing a single red blood cell with 85% purity. Furthermore, fluorescent imaging and machine learning was used to load single K562 cells amongst clusters based on their instantaneous size and circularity. the presented system aspires to replace manual cell handling techniques by translating expert knowledge into cell sorting automation via machine learning algorithms. This powerful technique finds application in the enrichment of single cells based on their micrographs for further downstream processing and analysis. Cell populations are remarkably heterogeneous. Even considering a similarly tasked sub-population of cells; there exists significant variability in their morphological properties and more so in their active genes and regulations 1,2. The recent genome-scale downstream capabilities (DNA 3 , RNA 4,5) at the single-cell resolution provide unprecedented insight into cellular heterogeneity, especially in cases where rare cell populations are masked by bulk measurements. This calls for alternative upstream techniques of selecting single cells for analysis. Compared to conventional manual cell handling techniques, microfluidics offers significant reagent volume reduction and ease of automation with enhanced repeatability and detection accuracy on low-cost, disposable chips 6. In this work, a droplet microfluidic system is developed to isolate single cells by image-based sorting. The platform aims to provide researchers with the methods to capture single cells of interest and study some of the deeper mechanisms involved in cell regulation and function. There already exists well-established methods for the detection and isolation of single cells for analysis. Some of these techniques are label-free 7-12 while others rely on fluorescent 13-16 or magnetic labelling. Labelling might not be possible for some systems due to lack of biomarkers or potential cytotoxicity of the labels (e.g. DNA intercalators) 17. Additionally, labels might be undesired if they interfere with the study such as in stem cell differentiation 18. Well known techniques for single cell preparation are Fluorescence Activated Cell Sorting 19,20 , Magnetic Assisted Cell Sorting 21,22 , Fluorescence Activated Droplet Sorting 23 , Laser Capture Mi...

Droplet flow cytometry for single-cell analysis

“…Moreover, imaging ow cytometry (IFC) has become an attractive tool for single-cell analysis in diverse biomedical elds, and a two-dimensional image signal has been employed for real-time classication and sorting of droplets encapsulating with cancer 131,132 and planktonic cells. 133 Combining with high-speed image-based sorting, [134][135][136][137][138][139] this will eventually be used in the process of isolating individual cells exhibiting properties of interest.…”

Sorting droplets into many outlets

“…the last decade, a whole suite of tools for manipulating droplets upstream and downstream of sorting has been developed. 30 Microfluidic FACS (fluorescence activated cell sorting) systems 31 that do use emulsion droplets, 32 as well as those that do not use emulsion droplets 33,34 have been attempted. While the first FACS system used a microfluidic device, 35 most current FACS systems use sheath flow to position cells in a small detection cross section followed by aerosol generation at a nozzle.…”

Three step flow focusing enables image-based discrimination and sorting of late stage 1 Haematococcus pluvialis cells

“…Digital microfluidics combined with image-based droplet sorting has been recommended as an alternative for this purpose by many researchers [12][13][14][15]. In these approaches, the target cells are encapsulated into droplets for subsequent sorting.…”