淋巴细胞动力学中代谢与表观遗传学交叉的细胞计数。

IF 2.1 4区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS
Nicole Vaughn
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引用次数: 0

摘要

世纪之交具有里程碑意义的研究揭示了代谢重编程是淋巴细胞分化和功能的驱动力。除了代谢变化,分化淋巴细胞必须重塑其表观遗传景观,以正确地重新连接其基因表达。最近的发现表明,代谢变化可以通过改变淋巴细胞的表观遗传状态来塑造淋巴细胞的命运,将这两个领域的研究结合在一起。高维细胞术的不断发展使得淋巴细胞代谢和表观遗传景观的分析越来越全面,超越了过去的技术限制。在这里,我们回顾了最近对淋巴细胞代谢和表观遗传学之间相互作用的见解,以及其失调如何导致免疫功能障碍和疾病。我们还讨论了细胞术的最新技术进步,这些技术进步使这些发现成为可能,我们预计这些技术进步将推动这一领域未来的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cytometry at the Intersection of Metabolism and Epigenetics in Lymphocyte Dynamics

Landmark studies at the turn of the century revealed metabolic reprogramming as a driving force for lymphocyte differentiation and function. In addition to metabolic changes, differentiating lymphocytes must remodel their epigenetic landscape to properly rewire their gene expression. Recent discoveries have shown that metabolic shifts can shape the fate of lymphocytes by altering their epigenetic state, bringing together these two areas of inquiry. The ongoing evolution of high-dimensional cytometry has enabled increasingly comprehensive analyses of metabolic and epigenetic landscapes in lymphocytes that transcend the technical limitations of the past. Here, we review recent insights into the interplay between metabolism and epigenetics in lymphocytes and how its dysregulation can lead to immunological dysfunction and disease. We also discuss the latest technical advances in cytometry that have enabled these discoveries and that we anticipate will advance future work in this area.

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来源期刊
Cytometry Part A
Cytometry Part A 生物-生化研究方法
CiteScore
8.10
自引率
13.50%
发文量
183
审稿时长
4-8 weeks
期刊介绍: Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques. The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome: Biomedical Instrumentation Engineering Biophotonics Bioinformatics Cell Biology Computational Biology Data Science Immunology Parasitology Microbiology Neuroscience Cancer Stem Cells Tissue Regeneration.
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