Maguire Sarah E, Credle Joel, Bertelson Elizabeth M W, Lee Sunny, Cha Boyoung, Xie Dan, Kirk Greg, Ray Debjit, George Logan, Suru Aditya, Maalouf Alexandre, Ikenaga Chiseko, Lloyd Thomas, Llosa Nicolas J, Larman H Benjamin
Portal Bioscience, LLC, Baltimore, MD, 21205, USA.
Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Biochem Biophys Rep. 2025 Aug 18;43:102207. doi: 10.1016/j.bbrep.2025.102207. eCollection 2025 Sep.
New biological insights are increasingly dependent upon a deeper understanding of tissue architectures. Critical to such studies are spatial transcriptomics technologies, especially those amenable to analysis of the most widely available human tissue type, formalin-fixed and paraffin-embedded (FFPE) clinical specimens. Here we build on our previous oligonucleotide probe ligation-based approach to accurately analyze FFPE mRNA, which suffers from variable levels of degradation. Ligation In Situ Hybridization followed by rolling circle amplification (LISH-Lock'n'Roll or LISH-LnR), provides a streamlined method to detect the spatial location of specific mRNA isoforms within FFPE tissue architectures. Iterative fluorescent probe hybridization and imaging enables highly multiplexed spatial transcriptomic studies, as demonstrated herein for fixed specimens from inclusion body myositis patients and pediatric rhabdomyosarcoma patients. We additionally demonstrate a system of molecular rheostats that can be used to fine tune the performance of the LISH-LnR assay. Combined with LISH-seq and LISH-QC, the LISH-LnR methodology provides a powerful toolkit for spatial transcriptomics.
新的生物学见解越来越依赖于对组织结构的更深入理解。此类研究的关键是空间转录组学技术,尤其是那些适用于分析最广泛可用的人类组织类型——福尔马林固定石蜡包埋(FFPE)临床标本的技术。在此,我们基于之前基于寡核苷酸探针连接的方法,对易降解程度不一的FFPE mRNA进行准确分析。原位连接杂交后进行滚环扩增(LISH-Lock'n'Roll或LISH-LnR),提供了一种简化的方法来检测FFPE组织结构内特定mRNA异构体的空间位置。迭代荧光探针杂交和成像能够实现高度多重的空间转录组学研究,本文中对包涵体肌炎患者和小儿横纹肌肉瘤患者的固定标本进行了验证。我们还展示了一个分子变阻器系统,可用于微调LISH-LnR检测的性能。结合LISH-seq和LISH-QC,LISH-LnR方法为空间转录组学提供了一个强大的工具包。