Department of Pathology, University of California San Francisco, San Francisco, CA, USA.
ImmunoX Initiative, University of California San Francisco, San Francisco, CA, USA.
Nat Methods. 2020 Aug;17(8):833-843. doi: 10.1038/s41592-020-0880-2. Epub 2020 Jul 6.
Spatial transcriptomics seeks to integrate single cell transcriptomic data within the three-dimensional space of multicellular biology. Current methods to correlate a cell's position with its transcriptome in living tissues have various limitations. We developed an approach, called 'ZipSeq', that uses patterned illumination and photocaged oligonucleotides to serially print barcodes ('zipcodes') onto live cells in intact tissues, in real time and with an on-the-fly selection of patterns. Using ZipSeq, we mapped gene expression in three settings: in vitro wound healing, live lymph node sections and a live tumor microenvironment. In all cases, we discovered new gene expression patterns associated with histological structures. In the tumor microenvironment, this demonstrated a trajectory of myeloid and T cell differentiation from the periphery inward. A combinatorial variation of ZipSeq efficiently scales in the number of regions defined, providing a pathway for complete mapping of live tissues, subsequent to real-time imaging or perturbation.
空间转录组学旨在整合多细胞生物学中三维空间内的单细胞转录组数据。目前,将细胞位置与其在活组织中转录组相关联的方法存在各种局限性。我们开发了一种名为“ZipSeq”的方法,该方法使用图案化照明和光笼寡核苷酸实时、在线地将条形码(“zipcode”)逐个打印到完整组织中的活细胞上,并可实时选择图案。使用 ZipSeq,我们在三种情况下绘制了基因表达图谱:体外伤口愈合、活淋巴结切片和活肿瘤微环境。在所有情况下,我们都发现了与组织学结构相关的新的基因表达模式。在肿瘤微环境中,这表明了从外围向内的髓样细胞和 T 细胞分化轨迹。ZipSeq 的组合变体可有效地扩展定义区域的数量,为实时成像或干扰后完整活组织图谱绘制提供了途径。