Exceeding 80% Efficiency of Single-Bead Encapsulation in Microdroplets through Hydrogel Coating-Assisted Close-Packed Ordering.

biorxiv(2023)

引用 1|浏览7
暂无评分
摘要
High-efficiency encapsulation of single microbeads in microdroplets is essential for droplet-based high-throughput analysis such as single-cell genomics and digital immunoassays. However, the demand has been hindered by the Poisson statistics of beads arbitrarily distributed in the droplet partitions. Although techniques such as inertial ordering have been proven useful to improve bead-loading efficiency, a general method that requires no advanced microfluidics and owns compatibility with diverse bead types is still highly desired. In this paper, we present hydrogel coating-assisted close-packed ordering, a simple strategy that improves the bead-loading efficiency to over 80%. In the strategy, the raw beads are coated with a thin layer of hydrogel to become slightly compressible and lubricious, so that they can be close-packed in a microfluidic device and loaded into droplets in a synchronized manner. We first show that the thin hydrogel coating can be realized conveniently through jetting microfluidics or vortex emulsification. When loading single 30-μm polystyrene beads, we experimentally determine an overall efficiency of 81% with the proposed hydrogel coating strategy. Of note, the strategy is not sensitive to the selection of raw beads and can tolerate their polydispersity. Using the strategy, we achieve a cell capture rate of 68.8% when co-encapsulating HEK293T cells and polydispersed barcoded beads for single-cell transcriptomics. Further sequencing results verify that the reversible hydrogel coating does not affect the RNA capture behavior of the encapsulated barcoded beads. Given its convenience and broad compatibility, we anticipate that our strategy can be applied to various droplet-based high-throughput assays to improve their efficiency drastically.
更多
查看译文
关键词
microdroplets,single-bead,coating-assisted,close-packed
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要