Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Sci Adv. 2019 Jan 23;5(1):eaau9223. doi: 10.1126/sciadv.aau9223. eCollection 2019 Jan.
Specialized immune cell subsets are involved in autoimmune disease, cancer immunity, and infectious disease through a diverse range of functions mediated by overlapping pathways and signals. However, subset-specific responses may not be detectable in analyses of whole blood samples, and no efficient approach for profiling cell subsets at high throughput from small samples is available. We present a low-input microfluidic system for sorting immune cells into subsets and profiling their gene expression. We validate the system's technical performance against standard subset isolation and library construction protocols and demonstrate the importance of subset-specific profiling through in vitro stimulation experiments. We show the ability of this integrated platform to identify subset-specific disease signatures by profiling four immune cell subsets in blood from patients with systemic lupus erythematosus (SLE) and matched control subjects. The platform has the potential to make multiplexed subset-specific analysis routine in many research laboratories and clinical settings.
特异性免疫细胞亚群通过重叠的途径和信号介导的多种功能参与自身免疫性疾病、癌症免疫和传染病。然而,在全血样本分析中可能无法检测到亚群特异性反应,并且没有从小样本中高通量分析细胞亚群的有效方法。我们提出了一种低输入微流控系统,用于将免疫细胞分选成亚群并分析其基因表达。我们通过与标准亚群分离和文库构建方案进行对比,验证了该系统的技术性能,并通过体外刺激实验证明了亚群特异性分析的重要性。我们展示了该集成平台通过分析系统性红斑狼疮(SLE)患者和匹配对照者血液中的四个免疫细胞亚群来鉴定亚群特异性疾病特征的能力。该平台有可能使许多研究实验室和临床环境中的多重亚群特异性分析成为常规。