Russell Andrew J C, Weir Jackson A, Nadaf Naeem M, Shabet Matthew, Kumar Vipin, Kambhampati Sandeep, Raichur Ruth, Marrero Giovanni J, Liu Sophia, Balderrama Karol S, Vanderburg Charles R, Shanmugam Vignesh, Tian Luyi, Wu Catherine J, Yoon Charles H, Macosko Evan Z, Chen Fei
bioRxiv. 2023 Apr 3:2023.04.01.535228. doi: 10.1101/2023.04.01.535228.
Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed. Missing from these measurements, however, is the ability to routinely and easily spatially localise these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are 'tagged' with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 micron spatial resolution, and delivered whole-transcriptome data that was indistinguishable in quality from ordinary snRNA-seq. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil, and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualised receptor-ligand interactions driving B-cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to virtually any single-cell measurement technology. As proof of principle, we performed multiomic measurements of open chromatin, RNA, and T-cell receptor sequences in the same cells from metastatic melanoma. We identified spatially distinct tumour subpopulations to be differentially infiltrated by an expanded T-cell clone and undergoing cell state transition driven by spatially clustered accessible transcription factor motifs. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.
最近的技术创新使得能够对单个细胞内的基因表达和表观遗传调控进行高通量定量,改变了我们对复杂组织构建方式的理解。然而,这些测量中缺少的是能够常规且轻松地对这些被分析的细胞进行空间定位的能力。我们开发了一种名为Slide-tags的策略,其中完整组织切片内的单个细胞核被来自具有已知位置的DNA条形码珠子的空间条形码寡核苷酸“标记”。然后,这些被标记的细胞核可以用作各种单核分析检测的输入。将Slide-tags应用于小鼠海马体,能够以小于10微米的空间分辨率定位细胞核,并提供质量与普通单细胞核RNA测序(snRNA-seq)难以区分的全转录组数据。为了证明Slide-tags可以应用于多种人体组织,我们对脑、扁桃体和黑色素瘤进行了该检测。我们揭示了跨皮质层的细胞类型特异性空间变化的基因表达,以及在淋巴组织中驱动B细胞成熟的空间背景化受体-配体相互作用。Slide-tags的一个主要优点是它很容易适应几乎任何单细胞测量技术。作为原理验证,我们对转移性黑色素瘤的同一细胞中的开放染色质、RNA和T细胞受体序列进行了多组学测量。我们确定了空间上不同的肿瘤亚群被一个扩增的T细胞克隆不同程度地浸润,并经历由空间聚集的可及转录因子基序驱动的细胞状态转变。Slide-tags提供了一个通用平台,用于将已有的单细胞测量数据集引入空间基因组学领域。