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调控胚胎发生的形态发生域信号网络的计算建模与分析

Computational modeling and analysis of the morphogenetic domain signaling networks regulating embryogenesis.

作者信息

Niu Ben, Bach Thao Nguyen, Chen Xingyu, Chandratre Khyati Raghunath, Isaac Murray John, Zhao Zhongying, Zhang Michael

机构信息

Center for Systems Biology, The University of Texas at Dallas, 75080, USA.

Department of Genetics, The University of Pennsylvania, USA.

出版信息

Comput Struct Biotechnol J. 2022 Jun 8;20:3653-3666. doi: 10.1016/j.csbj.2022.05.058. eCollection 2022.

Abstract

, often referred to as the 'roundworm', provides a powerful model for studying cell autonomous and cell-cell interactions through the direct observation of embryonic development . By leveraging the precisely mapped cell lineage at single cell resolution, we are able to study at a systems level how early embryonic cells communicate across morphogenetic domains for the coordinated processes of gene expressions and collective cellular behaviors that regulate tissue morphogenesis. In this study, we developed a computational framework for the exploration of the morphogenetic domain cell signaling networks that may regulate gastrulation and embryonic organogenesis. We demonstrated its utility by producing the following results, i) established a virtual reference model of developing embryos through the spatiotemporal alignment of individual embryo cell nuclear imaging samples; ii) integrated the single cell spatiotemporal gene expression profile with the established virtual embryo model by data pooling; iii) trained a Machine Learning model (Random Forest Regression), which predicts accurately the spatial positions of the cells given their gene expression profiles for a given developmental time ( total cell number of the embryo); iv) enabled virtual 4-dimensional tomographic graphical modeling of single cell data; v) inferred the biology signaling pathways that act in each of morphogenetic domains by meta-data analysis. It is intriguing that the morphogenetic domain cell signaling network seems to involve some crosstalk of multiple biology signaling pathways during the formation of tissue boundary pattern. Lastly, we developed the Software tool 'Embryo aligner version 1.0' and provided it as an Open Source program to the research community for virtual embryo modeling, and phenotype perturbation analyses (https://github.com/csniuben/embryo_aligner/wiki and https://bioinfo89.github.io/C.elegansEmbryonicOrganogenesisweb/).

摘要

通常被称为“蛔虫”,通过直接观察胚胎发育,为研究细胞自主和细胞间相互作用提供了一个强大的模型。通过利用单细胞分辨率下精确绘制的细胞谱系,我们能够在系统层面研究早期胚胎细胞如何跨形态发生域进行通信,以实现基因表达的协调过程和调节组织形态发生的集体细胞行为。在这项研究中,我们开发了一个计算框架,用于探索可能调节原肠胚形成和胚胎器官发生的形态发生域细胞信号网络。我们通过产生以下结果证明了它的实用性:i)通过单个胚胎细胞核成像样本的时空对齐建立发育胚胎的虚拟参考模型;ii)通过数据合并将单细胞时空基因表达谱与已建立的虚拟胚胎模型整合;iii)训练一个机器学习模型(随机森林回归),该模型根据给定发育时间(胚胎的总细胞数)的基因表达谱准确预测细胞的空间位置;iv)实现单细胞数据的虚拟四维断层图形建模;v)通过元数据分析推断在每个形态发生域中起作用的生物学信号通路。有趣的是,形态发生域细胞信号网络在组织边界模式形成过程中似乎涉及多种生物学信号通路的一些相互作用。最后,我们开发了软件工具“胚胎对齐器版本1.0”,并将其作为开源程序提供给研究社区,用于虚拟胚胎建模和表型扰动分析(https://github.com/csniuben/embryo_aligner/wiki和https://bioinfo89.github.io/C.elegansEmbryonicOrganogenesisweb/)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee5a/9289785/cb236d5c42d0/gr1.jpg

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