Wu Guanhao, Liang Yuchao, Xi Qilemuge, Zuo Yongchun
State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Institutes of Biomedical Sciences, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China.
Int J Mol Sci. 2025 Apr 23;26(9):3997. doi: 10.3390/ijms26093997.
The dynamic and meticulously regulated networks established the foundation for embryonic development, where the intercellular interactions and signal transduction assumed a pivotal role. In recent years, high-throughput technologies such as single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have advanced dramatically, empowering the systematic dissection of cell-to-cell regulatory networks. The emergence of comprehensive databases and analytical frameworks has further provided unprecedented insights into embryonic development and cell-cell interactions (CCIs). This paper reviewed the exponential increased CCIs works related to developmental biology from 2008 to 2023, comprehensively collected and categorized 93 analytical tools and 39 databases, and demonstrated its practical utility through illustrative case studies. In parallel, the article critically scrutinized the persistent challenges within this field, such as the intricacies of spatial localization and transmembrane state validation at single-cell resolution, and underscored the interpretative limitations inherent in current analytical frameworks. The development of CCIs' analysis tools with harmonizing multi-omics data and the construction of cross-species dynamically updated CCIs databases will be the main direction of future research. Future investigations into CCIs are poised to expeditiously drive the application and clinical translation within developmental biology, unlocking novel dimensions for exploration and progress.
这些动态且调控精细的网络为胚胎发育奠定了基础，其中细胞间相互作用和信号转导发挥着关键作用。近年来，诸如单细胞RNA测序（scRNA-seq）和空间转录组学（ST）等高通量技术取得了显著进展，使得对细胞间调控网络进行系统剖析成为可能。综合数据库和分析框架的出现，进一步为胚胎发育和细胞-细胞相互作用（CCI）提供了前所未有的见解。本文回顾了2008年至2023年间与发育生物学相关的细胞-细胞相互作用研究呈指数增长的情况，全面收集并分类了93种分析工具和39个数据库，并通过实例研究展示了其实际应用价值。与此同时，本文批判性地审视了该领域持续存在的挑战，如单细胞分辨率下空间定位的复杂性和跨膜状态验证问题，并强调了当前分析框架固有的解释局限性。开发能够整合多组学数据的细胞-细胞相互作用分析工具以及构建跨物种动态更新的细胞-细胞相互作用数据库将是未来研究的主要方向。对细胞-细胞相互作用的未来研究有望迅速推动发育生物学领域的应用和临床转化，为探索和进步开辟新的维度。
