Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA.
Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology, Cambridge, MA, USA.
Nat Med. 2020 Apr;26(4):511-518. doi: 10.1038/s41591-020-0799-2. Epub 2020 Mar 23.
Cellular immunity is critical for controlling intracellular pathogens, but individual cellular dynamics and cell-cell cooperativity in evolving human immune responses remain poorly understood. Single-cell RNA-sequencing (scRNA-seq) represents a powerful tool for dissecting complex multicellular behaviors in health and disease and nominating testable therapeutic targets. Its application to longitudinal samples could afford an opportunity to uncover cellular factors associated with the evolution of disease progression without potentially confounding inter-individual variability. Here, we present an experimental and computational methodology that uses scRNA-seq to characterize dynamic cellular programs and their molecular drivers, and apply it to HIV infection. By performing scRNA-seq on peripheral blood mononuclear cells from four untreated individuals before and longitudinally during acute infection, we were powered within each to discover gene response modules that vary by time and cell subset. Beyond previously unappreciated individual- and cell-type-specific interferon-stimulated gene upregulation, we describe temporally aligned gene expression responses obscured in bulk analyses, including those involved in proinflammatory T cell differentiation, prolonged monocyte major histocompatibility complex II upregulation and persistent natural killer (NK) cell cytolytic killing. We further identify response features arising in the first weeks of infection, for example proliferating natural killer cells, which potentially may associate with future viral control. Overall, our approach provides a unified framework for characterizing multiple dynamic cellular responses and their coordination.
细胞免疫对于控制细胞内病原体至关重要,但在不断进化的人类免疫反应中,单个细胞的动态变化和细胞间的协作仍知之甚少。单细胞 RNA 测序 (scRNA-seq) 代表了一种强大的工具,可以解析健康和疾病中复杂的多细胞行为,并提名可测试的治疗靶点。将其应用于纵向样本可以提供一个机会,在不引入潜在的个体间变异性的情况下,揭示与疾病进展演变相关的细胞因素。在这里,我们提出了一种实验和计算方法,该方法使用 scRNA-seq 来描述动态细胞程序及其分子驱动因素,并将其应用于 HIV 感染。通过对未经治疗的 4 名个体的外周血单核细胞在急性感染前和感染期间进行 scRNA-seq 分析,我们能够在每个个体中发现随时间和细胞亚群变化的基因反应模块。除了先前未被重视的个体和细胞类型特异性干扰素刺激基因上调外,我们还描述了在批量分析中被掩盖的时间对齐的基因表达反应,包括那些涉及促炎 T 细胞分化、单核细胞主要组织相容性复合物 II 持续上调和持续自然杀伤 (NK) 细胞细胞毒性杀伤的反应。我们进一步确定了在感染的最初几周内出现的反应特征,例如增殖的自然杀伤细胞,这可能与未来的病毒控制有关。总的来说,我们的方法为描述多种动态细胞反应及其协调提供了一个统一的框架。