Functional Immunogenomics Section, Systemic Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA.
Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA.
RNA. 2022 Sep;28(9):1263-1278. doi: 10.1261/rna.079239.122. Epub 2022 Jun 28.
Measurement of gene expression at the single-cell level has advanced the study of transcriptional regulation programs in healthy and disease states. In particular, single-cell approaches have shed light on the high level of transcriptional heterogeneity of individual cells, both at baseline and in response to experimental or environmental perturbations. We have developed a method for high-content imaging (HCI)-based quantification of relative changes in transcript abundance at the single-cell level in human primary immune cells and have validated its performance under multiple experimental conditions to demonstrate its general applicability. This method, named hcHCR, combines the sensitivity of the hybridization chain reaction (HCR) for the visualization of RNA in single cells, with the speed, scalability, and reproducibility of HCI. We first tested eight cell attachment substrates for short-term culture of primary human B cells, T cells, monocytes, or neutrophils. We then miniaturized HCR in 384-well format and documented the ability of the method to detect changes in transcript abundance at the single-cell level in thousands of cells for each experimental condition by HCI. Furthermore, we demonstrated the feasibility of multiplexing gene expression measurements by simultaneously assaying the abundance of three transcripts per cell at baseline and in response to an experimental stimulus. Finally, we tested the robustness of the assay to technical and biological variation. We anticipate that hcHCR will be suitable for low- to medium-throughput chemical or functional genomics screens in primary human cells, with the possibility of performing screens on cells obtained from patients with a specific disease.
单细胞水平的基因表达测量推动了健康和疾病状态下转录调控程序的研究。特别是,单细胞方法揭示了单个细胞在基线水平和对实验或环境干扰的反应中具有高度的转录异质性。我们开发了一种基于高内涵成像(HCI)的方法,用于定量人原代免疫细胞中单细胞水平转录物丰度的相对变化,并在多种实验条件下验证了其性能,以证明其通用性。该方法命名为 hcHCR,将 HCR 用于单细胞中 RNA 可视化的敏感性与 HCI 的速度、可扩展性和可重复性相结合。我们首先测试了八种细胞附着底物,用于短期培养原代人 B 细胞、T 细胞、单核细胞或中性粒细胞。然后,我们将 HCR 微型化到 384 孔格式,并通过 HCI 记录了该方法在每种实验条件下检测数千个细胞中单细胞水平转录物丰度变化的能力。此外,我们证明了通过同时检测每个细胞三种转录物的丰度来进行基因表达测量的多重化的可行性,无论是在基线水平还是对实验刺激的反应。最后,我们测试了该测定对技术和生物学变异的稳健性。我们预计 hcHCR 将适合于人原代细胞的低至中通量化学或功能基因组学筛选,并且有可能对患有特定疾病的患者获得的细胞进行筛选。