Robert Philippe A, Rastogi Ananya, Binder Sebastian C, Meyer-Hermann Michael
Systems Immunology Department and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Inhoffenstr. 7, 38126, Braunschweig, Germany.
Institut de Génétique Moléculaire de Montpellier, CNRS, UMR 5535, Université de Montpellier, 34293, Montpellier, France.
Methods Mol Biol. 2017;1623:303-334. doi: 10.1007/978-1-4939-7095-7_22.
Germinal centers host a mini-evolutionary environment where B cells can mutate their receptor and be selected depending on its affinity to target antigens in a process called affinity maturation. Starting from founder cells with a weak B cell receptor affinity, germinal centers release output cells as antibody-secreting cells or memory cells with a very high affinity, a property which is essential for pathogen clearance and immune memory. Therapeutic interventions on the germinal centers are tantalizing approaches to improve vaccines or to support rejection of chronic pathogens such as HIV. However, the complexity of the selection processes makes it very hard to make reliable predictions. Here, we present in detail how to build an agent-based model (hyphasma), accounting for the dynamics of the germinal center. It encompasses the core quantitative traits of affinity maturation, and allowed to make reliable predictions in previous studies.
生发中心拥有一个小型进化环境,在这个环境中,B细胞可以使其受体发生突变,并根据其对靶抗原的亲和力在一个称为亲和力成熟的过程中被选择。从具有弱B细胞受体亲和力的起始细胞开始,生发中心释放出作为抗体分泌细胞或具有非常高亲和力的记忆细胞的输出细胞,这一特性对于病原体清除和免疫记忆至关重要。对生发中心的治疗干预是改进疫苗或支持对抗诸如HIV等慢性病原体的诱人方法。然而,选择过程的复杂性使得很难做出可靠的预测。在这里,我们详细介绍如何构建一个基于主体的模型(Hyphasma),该模型考虑了生发中心的动态变化。它涵盖了亲和力成熟的核心定量特征,并在先前的研究中能够做出可靠的预测。