小柯机器人

美国哈佛医学院Peter V. Kharchenko团队在基于成像的空间转录组学中实现细胞分割。相关论文于2021年10月14日在线发表于国际学术期刊《自然—生物技术》。

研究人员描述了一种分割方法——Baysor，该方法考虑到转录组成和细胞形态的联合可能性，优化了二维（2D）或三维（3D）细胞的边界。虽然Baysor可以考虑到基于共染的分割，但它也可以单独根据检测到的转录物进行分割。为了评估性能，研究人员扩展了多重防错荧光原位杂交技术（MERFISH），用于纳入细胞边界的免疫染色。使用这个和其他基准，研究人员表明Baysor分割在某些情况下可以比现有工具多出近一倍的细胞数量，同时减少分割的伪影。研究人员证明Baysor在使用五种不同方案获得的数据上表现良好，使其成为分析基于成像的空间转录组学的有力工具。

据介绍，基于原位测序或多重RNA荧光杂交的单分子空间转录组学方案可以揭示详细的组织结构。然而，在这种数据中区分单个细胞的边界是具有挑战性的，并会阻碍下游分析。目前的方法通常使用细胞核染色法来近似确定细胞位置。

附：英文原文

Title: Cell segmentation in imaging-based spatial transcriptomics

Author: Petukhov, Viktor, Xu, Rosalind J., Soldatov, Ruslan A., Cadinu, Paolo, Khodosevich, Konstantin, Moffitt, Jeffrey R., Kharchenko, Peter V.

Issue&Volume: 2021-10-14

Abstract: Single-molecule spatial transcriptomics protocols based on in situ sequencing or multiplexed RNA fluorescent hybridization can reveal detailed tissue organization. However, distinguishing the boundaries of individual cells in such data is challenging and can hamper downstream analysis. Current methods generally approximate cells positions using nuclei stains. We describe a segmentation method, Baysor, that optimizes two-dimensional (2D) or three-dimensional (3D) cell boundaries considering joint likelihood of transcriptional composition and cell morphology. While Baysor can take into account segmentation based on co-stains, it can also perform segmentation based on the detected transcripts alone. To evaluate performance, we extend multiplexed error-robust fluorescence in situ hybridization (MERFISH) to incorporate immunostaining of cell boundaries. Using this and other benchmarks, we show that Baysor segmentation can, in some cases, nearly double the number of cells compared to existing tools while reducing segmentation artifacts. We demonstrate that Baysor performs well on data acquired using five different protocols, making it a useful general tool for analysis of imaging-based spatial transcriptomics. Baysor enables cell segmentation based on transcripts detected by multiplexed FISH or in situ sequencing.

DOI: 10.1038/s41587-021-01044-w

Source: https://www.nature.com/articles/s41587-021-01044-w

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex