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重建小鼠免疫细胞间的细胞间相互作用网络。

Reconstructing the cell-cell interaction network among mouse immune cells.

机构信息

Bioinformatics and Computational Omics Lab (BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University (TMU), Tehran, Iran.

Department of Molecular Virology, Pasteur Institute of Iran, Tehran, Iran.

出版信息

Biotechnol Bioeng. 2023 Sep;120(9):2756-2764. doi: 10.1002/bit.28431. Epub 2023 May 25.

DOI:10.1002/bit.28431
PMID:37227044
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10524935/
Abstract

Intercellular interactions and cell-cell communication are critical to regulating cell functions, especially in normal immune cells and immunotherapies. Ligand-receptor pairs mediating these cell-cell interactions can be identified using diverse experimental and computational approaches. Here, we reconstructed the intercellular interaction network between Mus musculus immune cells using publicly available receptor-ligand interaction databases and gene expression data from the immunological genome project. This reconstructed network accounts for 50,317 unique interactions between 16 cell types between 731 receptor-ligand pairs. Analysis of this network shows that cells of hematopoietic lineages use fewer communication pathways for interacting with each other, while nonhematopoietic stromal cells use the most network communications. We further observe that the WNT, BMP, and LAMININ pathways are the most significant contributors to the overall number of cell-cell interactions among the various pathways in the reconstructed communication network. This resource will enable the systematic analysis of normal and pathologic immune cell interactions, along with the study of emerging immunotherapies.

摘要

细胞间相互作用和细胞间通讯对于调节细胞功能至关重要,尤其是在正常免疫细胞和免疫疗法中。可以使用各种实验和计算方法来鉴定介导这些细胞间相互作用的配体-受体对。在这里,我们使用公开的受体-配体相互作用数据库和免疫基因组计划中的基因表达数据,重建了 Mus musculus 免疫细胞之间的细胞间相互作用网络。该重建网络包括 731 对受体-配体对的 16 种细胞类型之间的 50,317 个独特相互作用。对该网络的分析表明,造血谱系的细胞彼此之间使用的通信途径较少,而非造血基质细胞使用的网络通信最多。我们进一步观察到,WNT、BMP 和 LAMININ 途径是重建通讯网络中各种途径中细胞间相互作用总数的最重要贡献者。该资源将能够系统地分析正常和病理性免疫细胞相互作用,以及新兴免疫疗法的研究。

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