Multiplexed Label-Free Fractionation of Peripheral Blood Mononuclear Cells for Identification of Monocyte–Platelet Aggregates

作者
Hui Min Tay,Wei Hseun Yeap,Rinkoo Dalan,Siew Cheng Wong,Han Wei Hou
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:90 (24): 14535-14542 被引量:21
标识
DOI:10.1021/acs.analchem.8b04415
摘要

Monocytes and platelets play key roles in atherosclerosis and thrombosis, and circulating monocyte–platelet aggregates (MPA) in blood have been widely proposed as surrogate biomarkers for cardiovascular risk stratification and monitoring antiplatelet therapies. However, conventional MPA characterization is based on whole-blood fixation and flow cytometry analysis which adversely affect cell viability and detection accuracy due to significant leukocyte and platelet contaminations. Herein, we introduce a rapid and label-free microfluidic approach for complete size-based fractionation of peripheral blood mononuclear cells (PBMCs) into monocytes, lymphocytes, and platelets. The developed biochip enables gentle sorting of intact MPA in the enriched monocytes with efficient depletion of lymphocytes and platelets for accurate MPA quantification. We first compared the developed microfluidic technology (dean flow fractionation, DFF) with standard magnetic negative isolation (MACS) and observed that DFF-sorted monocytes had similar viability, purity, and key immune functions (phagocytosis, macrophage differentiation) as MACS-sorted monocytes. As proof of concept for diabetes testing, we isolated and characterized monocytes/MPA from a cohort of healthy ( n = 5) and type 2 diabetes mellitus (T2DM) subjects ( n = 8) in PBMCs and DFF-sorted monocytes. High-speed imaging, immunofluorescence, and flow cytometry analysis clearly indicated higher levels of MPA in T2DM patients ( P < 0.05) with enhanced MPA detection sensitivity in DFF-sorted monocytes ( P < 0.05). Taken together, the developed DFF technology greatly facilitates high-throughput (∼130 μL min –1 ) label-free isolation of monocyte/MPA from PBMCs and can be further developed into a clinical tool for point-of-care cardiovascular risk stratification in metabolic disorders including T2DM.

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