近日，美国麻省理工学院Aviv Regev等研究人员合作开发出高效成像转录组学的新技术。这一研究成果于2021年4月15日在线发表在国际学术期刊《自然—生物技术》上。

研究人员报道了复合原位成像（CISI），该方法利用细胞和组织中基因表达的结构来限制获得空间分辨的基因表达图所需的成像周期数。CISI定义了基因模块，可以使用复合测量来检测。然后将数据解压缩以恢复单个基因的表达值。CISI不依赖于点级分辨率，从而进一步降低了成像时间，实现了更低的放大倍率采集，并且总体上比目前的方法高出约500倍的效率。将CISI应用于12个小鼠的脑部切片，研究人员从11个复合测量中准确地恢复了37个基因的空间丰度。

据了解，用于组织样品空间成像的最新方法可以在单细胞分辨率下鉴定多达约100种单独的蛋白质或RNA。但是，在这些方法中可以研究的蛋白质或基因的数量受到长成像时间的限制。

附：英文原文

Title: Compressed sensing for highly efficient imaging transcriptomics

Author: Brian Cleary, Brooke Simonton, Jon Bezney, Evan Murray, Shahul Alam, Anubhav Sinha, Ehsan Habibi, Jamie Marshall, Eric S. Lander, Fei Chen, Aviv Regev

Issue&Volume: 2021-04-15

Abstract: Recent methods for spatial imaging of tissue samples can identify up to ~100 individual proteins1,2,3 or RNAs4,5,6,7,8,9,10 at single-cell resolution. However, the number of proteins or genes that can be studied in these approaches is limited by long imaging times. Here we introduce Composite In Situ Imaging (CISI), a method that leverages structure in gene expression across both cells and tissues to limit the number of imaging cycles needed to obtain spatially resolved gene expression maps. CISI defines gene modules that can be detected using composite measurements from imaging probes for subsets of genes. The data are then decompressed to recover expression values for individual genes. CISI further reduces imaging time by not relying on spot-level resolution, enabling lower magnification acquisition, and is overall about 500-fold more efficient than current methods. Applying CISI to 12 mouse brain sections, we accurately recovered the spatial abundance of 37 individual genes from 11 composite measurements covering 180mm2 and 476,276 cells.

DOI: 10.1038/s41587-021-00883-x

Source: https://www.nature.com/articles/s41587-021-00883-x