化学
仿形(计算机编程)
微流控
计算生物学
抗体
纳米技术
生物物理学
免疫学
材料科学
计算机科学
生物
操作系统
作者
Thijs Roebroek,W. Van Roy,Sophie Roth,Laura Chacon Orellana,Zhenxiang Luo,Youssef El Jerrari,Chad Arnett,Kasper Claes,Seungkyu Ha,Karolien Jans,Riet Labie,Ziduo Lin,Martin Obst,Deise Origuella,Van Hung Pham,Frederic Van Bellinghen,Anil Krishna,Elnaz Vaezzadeh,W. Vanhove,Joost Van Duppen
标识
DOI:10.1021/acs.analchem.5c00385
摘要
Flow cytometry commonly utilizes fluorescence labeling and extensive sample preparation to detect specific cell surface markers, making analysis under native cell conditions impractical. In this work, a label-free flow cytometry technique is presented that spatiotemporally resolves cell-surface interactions in antibody-coated microfluidic channels. Using computational imaging, numerous cells are tracked across a large field of view (12 × 3 mm2) and the resulting motion profiles are used for phenotypic cell characterization. As proof-of-principle, experiments targeting T-cell receptor CD8 are performed directly on cell cultures. Individual T-cells are successfully tracked in 98% cases for flow velocities of 1-3 mm·s-1. In 14 μm high channels coated with only nonspecific antibodies, both CD8-positive SUP-T1 and CD8-negative Jurkat cells exhibit mostly constant velocities. In contrast, using channels functionalized with CD8-specific antibodies, numerous CD8-positive cells but not CD8-negative cells show temporary delays in motion linked to surface interaction. Cell classification based on the observed interactions results in a clear contrast ratio of 23.9 ± 11.6 (mean ± standard deviation) between SUP-T1 and Jurkat cells at 1 mm·s-1. The contrast decreases at higher flow velocities as fewer cells interact due to the increased hydrodynamic lift. Our results affirm our method's ability to differentiate cells without prior labeling or sample preparation.
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