分泌物
计算生物学
单细胞分析
细胞
旁分泌信号
细胞生物学
小RNA
细胞信号
生物
生物信息学
信号转导
遗传学
生物化学
基因
受体
作者
Fengjiao Zhu,Yangyang Long,Weiwei Shi,Bin Li,Yahui Ji,Xue Bai,Xianming Liu,Dongyuan Qi,Bo Sun,Fuyin Zhang,Tingjiao Liu,Bingcheng Lin,Yao Lu
标识
DOI:10.1016/j.bios.2024.116303
摘要
Discriminating secretory phenotypes provides a direct, intact, and dynamic way to evaluate the heterogeneity in cell states and activation, which is significant for dissecting non-genetic heterogeneity for human health studies and disease diagnostics. In particular, secreted microRNAs, soluble signaling molecules released by various cells, are increasingly recognized as a critical mediator for cell-cell communication and the circulating biomarkers for disease diagnosis. However, single-cell analysis of secreted miRNAs is still lacking due to the limited available tools. Herein, we realized three-plexed miRNA secretion analysis over four time points from single cells encapsulated in picoliter droplets with extreme simplicity, coupling vortexing-generated single-cell droplets with multiplexed molecular beacons. Notably, our platform only requires pipetting and vortexing steps to finish the assay setup within 5 minutes with minimal training, and customized software was developed for automatic data quantification. Applying the platform to human cancer cell lines and primary cells revealed previously undifferentiated heterogeneity and paracrine signaling underlying miRNA secretion. This platform can be used to dissect secretion heterogeneity and cell-cell interactions and has the potential to become a widely used tool in biomedical research.
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