训练免疫:在健康和疾病中重新编程先天免疫。

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
ACS Synthetic Biology Pub Date : 2021-04-26 Epub Date: 2021-02-26 DOI:10.1146/annurev-immunol-102119-073855
Siroon Bekkering, Jorge Domínguez-Andrés, Leo A B Joosten, Niels P Riksen, Mihai G Netea
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引用次数: 121

摘要

传统上,先天免疫系统和适应性免疫系统是由它们的特异性和记忆能力来区分的。然而,近年来,这种范式发生了转变:先天免疫系统的细胞似乎能够在短暂的刺激后获得记忆特征,从而在二次挑战时增强反应。这种现象被称为训练免疫。训练免疫的特点是非特异性的反应性增加,通过广泛的代谢和表观遗传重编程介导。经过训练的免疫解释了疫苗的异源效应,从而增强了对继发性感染的保护。然而,在慢性炎症条件下,经过训练的免疫可诱导适应不良效应,并导致高炎症和心血管疾病、自身炎症综合征和神经炎症的进展。在这篇综述中,我们总结了训练免疫领域的现状,它的机制,以及它在健康和疾病中的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trained Immunity: Reprogramming Innate Immunity in Health and Disease.

Traditionally, the innate and adaptive immune systems are differentiated by their specificity and memory capacity. In recent years, however, this paradigm has shifted: Cells of the innate immune system appear to be able to gain memory characteristics after transient stimulation, resulting in an enhanced response upon secondary challenge. This phenomenon has been called trained immunity. Trained immunity is characterized by nonspecific increased responsiveness, mediated via extensive metabolic and epigenetic reprogramming. Trained immunity explains the heterologous effects of vaccines, which result in increased protection against secondary infections. However, in chronic inflammatory conditions, trained immunity can induce maladaptive effects and contribute to hyperinflammation and progression of cardiovascular disease, autoinflammatory syndromes, and neuroinflammation. In this review we summarize the current state of the field of trained immunity, its mechanisms, and its roles in both health and disease.

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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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