interFLOW:用于识别介导多种受体信号汇聚的因素的最大流量框架。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Ron Sheinin, Koren Salomon, Eilam Yeini, Shai Dulberg, Ayelet Kaminitz, Ronit Satchi-Fainaro, Roded Sharan, Asaf Madi
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引用次数: 0

摘要

细胞-细胞串联涉及多种受体和配体的同时相互作用,随后下游信号级联通过受体汇聚到主导转录因子,再由主导转录因子将多种信号整合并传播到细胞反应中。从确定的微环境中分离出的多个细胞亚群的单细胞 RNAseq 为我们提供了一个独特的机会来了解反映在其基因表达水平上的这种相互作用。我们开发了 interFLOW 框架,根据蛋白质-蛋白质相互作用(PPI)网络中的最大流计算,绘制不同细胞亚群之间潜在的配体-受体相互作用图。最大流方法还能进一步描述细胞内从不同表达的受体到主导转录因子的下游信号转导,因此能将一组受体与其下游激活途径联系起来。重要的是,我们能够确定多种受体信号通路汇聚的关键转录因子。这些已确定的因子在特定的细胞-细胞相互作用后的信号整合和传播过程中发挥着独特的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

interFLOW: maximum flow framework for the identification of factors mediating the signaling convergence of multiple receptors.

interFLOW: maximum flow framework for the identification of factors mediating the signaling convergence of multiple receptors.

Cell-cell crosstalk involves simultaneous interactions of multiple receptors and ligands, followed by downstream signaling cascades working through receptors converging at dominant transcription factors, which then integrate and propagate multiple signals into a cellular response. Single-cell RNAseq of multiple cell subsets isolated from a defined microenvironment provides us with a unique opportunity to learn about such interactions reflected in their gene expression levels. We developed the interFLOW framework to map the potential ligand-receptor interactions between different cell subsets based on a maximum flow computation in a network of protein-protein interactions (PPIs). The maximum flow approach further allows characterization of the intracellular downstream signal transduction from differentially expressed receptors towards dominant transcription factors, therefore, enabling the association between a set of receptors and their downstream activated pathways. Importantly, we were able to identify key transcription factors toward which the convergence of multiple receptor signaling pathways occurs. These identified factors have a unique role in the integration and propagation of signaling following specific cell-cell interactions.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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