2025年3月17日，美国剑桥大学Bianca Dumitrascu团队在《自然—方法学》杂志发表论文，宣布他们的研究开发出了空间机械转录组学的计算管道。

在这里，该研究组开发了一个计算框架，可以在空间转录组学的背景下对转录和机械信号进行联合统计分析。为了阐明该方法的应用和效用，课题组人员将来自发育中的无主题胚胎的空间转录组学数据用于推断作用于单个细胞的力，并将这些结果用于识别预测组织隔室边界的机械、形态计量学和基因表达特征。此外，该课题组研究人员主题的土工结构方程建模，以确定基因模块，预测细胞的力学行为在一个无偏的方式。这个计算框架很容易推广到其他空间剖面背景，为探索组织中生物分子和机械线索的相互作用提供了一个通用方案。

据悉，空间分析技术的进步为分子程序如何受到局部信号和环境线索的影响提供了见解。然而，细胞命运规范和组织模式涉及生化和机械反馈的相互作用。

附：英文原文

Title: A computational pipeline for spatial mechano-transcriptomics

Author: Hallou, Adrien, He, Ruiyang, Simons, Benjamin D., Dumitrascu, Bianca

Issue&Volume: 2025-03-17

Abstract: Advances in spatial profiling technologies are providing insights into how molecular programs are influenced by local signaling and environmental cues. However, cell fate specification and tissue patterning involve the interplay of biochemical and mechanical feedback. Here we develop a computational framework that enables the joint statistical analysis of transcriptional and mechanical signals in the context of spatial transcriptomics. To illustrate the application and utility of the approach, we use spatial transcriptomics data from the developing mouse embryo to infer the forces acting on individual cells, and use these results to identify mechanical, morphometric and gene expression signatures that are predictive of tissue compartment boundaries. In addition, we use geoadditive structural equation modeling to identify gene modules that predict the mechanical behavior of cells in an unbiased manner. This computational framework is easily generalized to other spatial profiling contexts, providing a generic scheme for exploring the interplay of biomolecular and mechanical cues in tissues.

DOI: 10.1038/s41592-025-02618-1

Source: https://www.nature.com/articles/s41592-025-02618-1