Multiparametric analysis of human plasma exosome phenotype by conventional flow cytometry

Abstract

Purpose: Extracellular vesicles (EVs) are circulating membranous particles released from nearly all cell types. Exosomes, the smallest form of EVs (30-150 nm in diameter), contain significant amounts of protein, mRNA, miRNA, and some small noncoding RNAs (lncRNA, cirRNA). Exosomes influence various functions of both recipient and parent cells by transferring their cargo. Synovial fluid derived exosomes of patients with osteoarthritis significantly stimulated the release of inflammatory cytokine IL-1β, chemokines (CCL7, CCL15, CCL20 and CXCL1) and metalloproteinases by M1 macrophages. The goal of this study is to establish multiparametric analysis methods to characterize human plasma and synovial fluid exosome phenotypes by conventional flow cytometry, for correlation with aging and osteoarthritis phenotype and outcomes. Methods: Frozen plasma samples from 6 healthy donors (age 33.83 ± 22.08 years, Body Mass Index BMI) 23.71 ± 3.28 kg/m2, 3 male and 3 female) with EDTA as anticoagulant were purchased from a commercial vendor. The samples were completely thawed and centrifuged twice at 3000 g for 15 minutes to remove cellular debris. Exosomes in plasma were isolated by the ExoQuick ULTRA kit. Precipitated exosomes were resuspended by the ExoQuick ULTRA buffer B, and diluted in double filtered PBS (df-PBS) for staining. Fluorescence-conjugated antibodies against human CD63, CD81, CD3, CD19, CD14 and CD16 were used for exosome surface staining. Exosomes without antibody were used to determine the staining background. The Sub-micron Particle Size Reference Kit (containing 20, 100, 200, 500, 1000 and 2000 nm beads) was used to determine the size of acquired events. The ExoQuick ULTRA buffer B and df-PBF in the absence or presence of the indicated antibodies were used to determine the background noise. The percentages of the exosomes expressing each tested molecule were determined using a BD Fortessa X-20 Flow Cytometer with the BD FACSDiVa software. Flow cytometry data analysis was performed using FlowJo software. Statistical analysis of one-way ANOVA and correlation was performed using GraphPad Prism software. Results: The percentage of exosomes expressing the CD3 (T cell) marker was significantly higher (9.85% ± 6.97) than the percentage of exosomes expressing the CD63 (tetraspanin family member, 0.19% ± 0.26, p<0.01), CD16 (neutrophil, 0.23% ± 0.23, p<0.01), or CD19 (B cell, 2.96% ± 5.69, p<0.05) markers. Exosome expression was not statistically significantly different for CD3 vs. tetraspanin family member CD81 (4.37% ± 1.87) or vs. the monocyte marker CD14 (4.59% ± 4.51). Interestingly, age was significantly negatively correlated with the percentage of CD81+ exosomes (p = 0.0488, r = -0.8138), and non-significantly negatively correlated with the percentage of CD3+exosomes (p = 0.1447, r = -0.6708), suggesting the association of these exosomes with aging and aging related diseases. BMI was significantly negatively correlated with the percentage of CD16+ exosomes (p = 0.0418, r = -0.8281), and non-significantly negatively correlated with the percentage of CD14+ exosomes (p = 0.0859, r = -0.7500). There was no significant difference between male and female subjects on all tested markers. Conclusions: With optimized acquisition parameters and appropriate controls, we were able to characterize the surface phenotype of plasma exosomes by conventional flow cytometry. Our data provide evidence that T cells (producing CD3+ exosomes) are one of the major cell sources of plasma exosomes. CD81+ and CD3+ exosomes are attractive candidates as direct biomarkers of aging and aging related disease, such as osteoarthritis. Our future study will focus on segregation of exosome subpopulations for characterization of their cargo to provide insights into their role in aging and osteoarthritis as well as their biomarker and therapeutic potential. We wish to acknowledge funding support from NIH R56AG060895.