Heterogeneity of germinal center B cells: New insights from single-cell studies,European Journal of Immunology

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Heterogeneity of germinal center B cells: New insights from single-cell studies
European Journal of Immunology ( IF 4.5 ) Pub Date : 2021-07-29 , DOI: 10.1002/eji.202149235
Noudjoud Attaf ₁ , Sabrina Baaklini ₁ , Laurine Binet ₁ , Pierre Milpied _{1,

2}

Affiliation

Upon antigen exposure, activated B cells in antigen-draining lymphoid organs form microanatomical structures, called germinal centers (GCs), where affinity maturation occurs. Within the GC microenvironment, GC B cells undergo proliferation and B cell receptor (BCR) genes somatic hypermutation in the dark zone (DZ), and affinity-based selection in the light zone (LZ). In the current paradigm of GC dynamics, high-affinity LZ B cells may be selected by cognate T- follicular helper cells to either differentiate into plasma cells or memory B cells, or re-enter the DZ and initiate a new round of proliferation and BCR diversification, before migrating back to the LZ. Given the diversity of cell states and potential cell fates that GC B cells may adopt, the two-state DZ-LZ paradigm has been challenged by studies that explored GC B-cell heterogeneity with a variety of single-cell technologies. Here, we review studies and single-cell technologies which have allowed to refine the working model of GC B-cell cellular and molecular heterogeneity during affinity maturation. This review also covers the use of single-cell quantitative data for mathematical modeling of GC reactions, and the application of single-cell genomics to the study of GC-derived malignancies.

中文翻译：

生发中心 B 细胞的异质性：来自单细胞研究的新见解

抗原暴露后，抗原引流淋巴器官中的活化 B 细胞形成显微解剖结构，称为生发中心 (GC)，在那里发生亲和力成熟。在 GC 微环境中，GC B 细胞在暗区 (DZ) 中经历增殖和 B 细胞受体 (BCR) 基因体细胞超突变，并在亮区 (LZ) 中进行基于亲和力的选择。在目前的GC动力学范式中，同源T-滤泡辅助细胞可能会选择高亲和力LZ B细胞分化为浆细胞或记忆B细胞，或重新进入DZ并启动新一轮的增殖和BCR多元化，在迁移回 LZ 之前。鉴于 GC B 细胞可能采用的细胞状态和潜在细胞命运的多样性，使用各种单细胞技术探索 GC B 细胞异质性的研究对两国 DZ-LZ 范式提出了挑战。在这里，我们回顾了研究和单细胞技术，它们允许在亲和力成熟过程中改进 GC B 细胞细胞和分子异质性的工作模型。本综述还涵盖了使用单细胞定量数据对 GC 反应进行数学建模，以及单细胞基因组学在 GC 衍生的恶性肿瘤研究中的应用。

更新日期：2021-07-29

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