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γ链细胞因子的演变:机制、方法与应用。

Evolution of γ chain cytokines: Mechanisms, methods and applications.

作者信息

Antczak Magdalena, Cañete Pablo F, Chen Zhian, Belle Clémence, Yu Di

机构信息

The University of Queensland Diamantina Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.

Ian Frazer Centre for Children's Immunotherapy Research, Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Australia.

出版信息

Comput Struct Biotechnol J. 2022 Aug 25;20:4746-4755. doi: 10.1016/j.csbj.2022.08.050. eCollection 2022.

Abstract

The common γ chain family of cytokines and their receptors play fundamental roles in the immune system. Evolutionary studies of γ chain cytokines have elegantly illustrated how the immune system adapts to ever-changing environmental conditions. Indeed, these studies have revealed the uniqueness of cytokine evolution, which exhibits strong positive selection pressure needed to adapt to rapidly evolving threats whilst still conserving their receptor binding capabilities. In this review, we summarise the evolutionary mechanisms that gave rise to the characteristically diverse family of γ chain cytokines. We also speculate on the benefits of studying cytokine evolution, which may provide alternative ways to design novel cytokine therapeutic strategies. Additionally, we discuss current evolutionary models that elucidate the emergence of distinct cytokines (IL-4 and IL-13) and cytokine receptors (IL-2Rα and IL-15Rα). Finally, we address and reflect on the difficulties associated with evolutionary studies of rapidly evolving genes and describe a variety of computational methods that have revealed numerous aspects of cytokine evolution.

摘要

细胞因子及其受体的共同γ链家族在免疫系统中发挥着重要作用。对γ链细胞因子的进化研究精妙地阐释了免疫系统如何适应不断变化的环境条件。事实上,这些研究揭示了细胞因子进化的独特性,即它展现出适应快速演变威胁所需的强大正选择压力,同时仍保留其受体结合能力。在本综述中,我们总结了产生γ链细胞因子这一独特多样家族的进化机制。我们还推测了研究细胞因子进化的益处,这可能为设计新型细胞因子治疗策略提供替代方法。此外,我们讨论了当前阐明不同细胞因子(白细胞介素-4和白细胞介素-13)及细胞因子受体(白细胞介素-2受体α链和白细胞介素-15受体α链)出现的进化模型。最后,我们探讨并思考了与快速进化基因的进化研究相关的困难,并描述了多种揭示细胞因子进化诸多方面的计算方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f75/9465101/b5ac113b5b46/gr1.jpg

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