@article {1535327,
	title = {Droplet encapsulation improves accuracy of immune cell cytokine capture assays},
	journal = {Lab on a Chip},
	volume = {20},
	year = {2020},
	pages = {1513-1520},
	abstract = {
	Quantification of cell-secreted molecules,\&nbsp;e.g., cytokines, is fundamental to the characterization of immune responses. Cytokine capture assays that use engineered antibodies to anchor the secreted molecules to the secreting cells are widely used to characterize immune responses because they allow both sensitive identification and recovery of viable responding cells. However, if the cytokines diffuse away from the secreting cells, non-secreting cells will also be identified as responding cells. Here we encapsulate immune cells in microfluidic droplets and perform in-droplet cytokine capture assays to limit the diffusion of the secreted cytokines. We use microfluidic devices to rapidly encapsulate single natural killer NK-92 MI cells and their target K562 cells into microfluidic droplets. We perform in-droplet IFN-γ capture assays and demonstrate that NK-92 MI cells recognize target cells within droplets and become activated to secrete IFN-γ. Droplet encapsulation prevents diffusion of secreted products to neighboring cells and dramatically reduces both false positives and false negatives, relative to assays performed without droplets. In a sample containing 1\% true positives, encapsulation reduces, from 94\% to 2\%, the number of true-positive cells appearing as negatives; in a sample containing 50\% true positives, the number of non-stimulated cells appearing as positives is reduced from 98\% to 1\%. After cells are released from the droplets, secreted cytokine remains captured onto secreting immune cells, enabling FACS-isolation of populations highly enriched for activated effector immune cells. Droplet encapsulation can be used to reduce background and improve detection of any single-cell secretion assay.

},
	url = {https://pubs.rsc.org/--/content/articlelanding/2020/lc/c9lc01261c/unauth$\#$!divAbstract},
	author = {Yuan, Yuan and Brouchon, Julie and Calvo-Calle, J. Mauricio and Xia, Jing and Sun, Li and Zhang, Xu and Clayton, Kiera L. and Ye, Fangfu and Weitz, DavidA. and Heyman, John}
}
