Department of Mechanical Engineering, University of British Columbia, Vancouver, BC, Canada.
Centre for Blood Research, University of British Columbia, Vancouver, BC, Canada.
Commun Biol. 2022 Jul 30;5(1):768. doi: 10.1038/s42003-022-03703-3.
Single cell RNA sequencing has the potential to elucidate transcriptional programs underlying key cellular phenotypes and behaviors. However, many cell phenotypes are incompatible with indiscriminate single cell sequencing because they are rare, transient, or can only be identified by imaging. Existing methods for isolating cells based on imaging for single cell sequencing are technically challenging, time-consuming, and prone to loss because of the need to physically transport single cells. Here, we developed See-N-Seq, a method to rapidly screen cells in microwell plates in order to isolate RNA from specific single cells without needing to physically extract each cell. Our approach involves encapsulating the cell sample in a micropatterned hydrogel with spatially varying porosity to selectively expose specific cells for targeted RNA extraction. Extracted RNA can then be captured, barcoded, reverse transcribed, amplified, and sequenced at high-depth. We used See-N-Seq to isolate and sequence RNA from cell-cell conjugates forming an immunological synapse between T-cells and antigen presenting cells. In the hours after synapsing, we found time-dependent bifurcation of single cell transcriptomic profiles towards Type 1 and Type 2 helper T-cells lineages. Our results demonstrate how See-N-Seq can be used to associate transcriptomic data with specific functions and behaviors in single cells.
单细胞 RNA 测序有可能阐明关键细胞表型和行为背后的转录程序。然而，许多细胞表型与无差别单细胞测序不兼容，因为它们是罕见的、短暂的，或者只能通过成像来识别。现有的基于成像对单细胞进行测序的细胞分离方法在技术上具有挑战性，耗时且容易丢失，因为需要物理提取单细胞。在这里，我们开发了 See-N-Seq 方法，该方法可以快速筛选微孔板中的细胞，以便在不需要物理提取每个细胞的情况下，从特定的单个细胞中分离 RNA。我们的方法涉及将细胞样本包封在具有空间变化孔隙率的微图案水凝胶中，以选择性地暴露特定细胞，进行靶向 RNA 提取。然后可以捕获、标记、反转录、扩增和测序提取的 RNA，深度高。我们使用 See-N-Seq 从 T 细胞和抗原呈递细胞之间形成免疫突触的细胞-细胞连接体中分离和测序 RNA。在突触形成后的几个小时内，我们发现单细胞转录组谱朝着 1 型和 2 型辅助 T 细胞谱系的时间依赖性分支。我们的结果表明了 See-N-Seq 如何用于将转录组数据与单个细胞中的特定功能和行为相关联。
