B 细胞群的分支随机进化模型

IF 2.2 4区 数学 Q2 BIOLOGY Journal of Mathematical Biology Pub Date : 2024-06-07 DOI:10.1007/s00285-024-02102-y
Ollivier Hyrien, Nikolay M Yanev
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引用次数: 0

摘要

我们提出了一个随机框架来描述生殖中心(GC)反应过程中 B 细胞群的演变。我们的模型被表述为一个多类型的年龄依赖性分支过程,其中包含随时间变化的移民过程。移民过程捕捉了创始 B 细胞通过随着时间的推移逐渐向生殖中心播种而启动克隆的机制,而分支过程则描述了这些克隆组成的时间演变。该模型为每个细胞分配了一种类型,以表示感兴趣的属性。属性的例子包括 B 细胞的结合亲和力类别、其克隆家族或其受体重链和轻链的核苷酸序列。该过程通常是非马尔可夫过程。我们介绍了它的特性,包括当过程为超临界时的 t → ∞,这是研究 GC B 细胞扩增最相关的情况。我们为多型分支过程引入了时间α和β多样性指数。我们重点研究了克隆优势的动态变化,强调了它的非稳态性,以及在顺序免疫背景下体细胞超突变的积累。我们评估了创始 B 细胞对 GC 持续播种对 B 细胞库动态的影响,并量化了前体频率和抗原可用性对 GC 进入时间的影响。该模型的应用说明了它如何有助于解释 BCR 测序数据。
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A branching stochastic evolutionary model of the B-cell repertoire.

We propose a stochastic framework to describe the evolution of the B-cell repertoire during germinal center (GC) reactions. Our model is formulated as a multitype age-dependent branching process with time-varying immigration. The immigration process captures the mechanism by which founder B cells initiate clones by gradually seeding GC over time, while the branching process describes the temporal evolution of the composition of these clones. The model assigns a type to each cell to represent attributes of interest. Examples of attributes include the binding affinity class of the B cells, their clonal family, or the nucleotide sequence of the heavy and light chains of their receptors. The process is generally non-Markovian. We present its properties, including as t when the process is supercritical, the most relevant case to study expansion of GC B cells. We introduce temporal alpha and beta diversity indices for multitype branching processes. We focus on the dynamics of clonal dominance, highlighting its non-stationarity, and the accumulation of somatic hypermutations in the context of sequential immunization. We evaluate the impact of the ongoing seeding of GC by founder B cells on the dynamics of the B-cell repertoire, and quantify the effect of precursor frequency and antigen availability on the timing of GC entry. An application of the model illustrates how it may help with interpretation of BCR sequencing data.

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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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