Khatri Indu, Diks Annieck M, van den Akker Erik B, Oosten Liesbeth E M, Zwaginga Jaap Jan, Reinders Marcel J T, van Dongen Jacques J M, Berkowska Magdalena A
Department of Immunology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.
Leiden Computational Biology Center, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands.
Vaccines (Basel). 2021 Nov 18;9(11):1352. doi: 10.3390/vaccines9111352.
To mount an adequate immune response against pathogens, stepwise mutation and selection processes are crucial functions of the adaptive immune system. To better characterize a successful vaccination response, we performed longitudinal (days 0, 5, 7, 10, and 14 after Boostrix vaccination) analysis of the single-cell transcriptome as well as the B-cell receptor (BCR) repertoire (scBCR-rep) in plasma cells of an immunized donor and compared it with baseline B-cell characteristics as well as flow cytometry findings. Based on the flow cytometry knowledge and literature findings, we discriminated individual B-cell subsets in the transcriptomics data and traced over-time maturation of plasmablasts/plasma cells (PB/PCs) and identified the pathways associated with the plasma cell maturation. We observed that the repertoire in PB/PCs differed from the baseline B-cell repertoire e.g., regarding expansion of unique clones in post-vaccination visits, high usage of IGHG1 in expanded clones, increased class-switching events post-vaccination represented by clonotypes spanning multiple IGHC classes and positive selection of CDR3 sequences over time. Importantly, the Variable gene family-based clustering of BCRs represented a similar measure as the gene-based clustering, but certainly improved the clustering of BCRs, as BCRs from duplicated Variable gene families could be clustered together. Finally, we developed a query tool to dissect the immune response to the components of the Boostrix vaccine. Using this tool, we could identify the BCRs related to anti-tetanus and anti-pertussis toxoid BCRs. Collectively, we developed a bioinformatic workflow which allows description of the key features of an ongoing (longitudinal) immune response, such as activation of PB/PCs, Ig class switching, somatic hypermutation, and clonal expansion, all of which are hallmarks of antigen exposure, followed by mutation & selection processes.
为了对病原体产生足够的免疫反应,逐步的突变和选择过程是适应性免疫系统的关键功能。为了更好地表征成功的疫苗接种反应,我们对一名免疫供体浆细胞中的单细胞转录组以及B细胞受体(BCR)库(scBCR-rep)进行了纵向(加强接种百白破疫苗后第0、5、7、10和14天)分析,并将其与基线B细胞特征以及流式细胞术结果进行比较。基于流式细胞术知识和文献发现,我们在转录组学数据中区分了单个B细胞亚群,追踪了浆母细胞/浆细胞(PB/PCs)随时间的成熟过程,并确定了与浆细胞成熟相关的途径。我们观察到,PB/PCs中的库与基线B细胞库不同,例如,在接种疫苗后的随访中独特克隆的扩增、扩增克隆中IGHG1的高使用率、接种疫苗后以跨越多个IGHC类别的克隆型为代表的类别转换事件增加以及CDR3序列随时间的阳性选择。重要的是,基于可变基因家族的BCR聚类与基于基因的聚类具有相似的效果,但肯定改善了BCR的聚类,因为来自重复可变基因家族的BCR可以聚类在一起。最后,我们开发了一个查询工具来剖析对百白破疫苗成分的免疫反应。使用这个工具,我们可以识别与抗破伤风和抗百日咳类毒素BCR相关的BCR。总体而言,我们开发了一种生物信息学工作流程,该流程可以描述正在进行的(纵向)免疫反应的关键特征,如PB/PCs的激活、Ig类别转换、体细胞超突变和克隆扩增,所有这些都是抗原暴露的标志,随后是突变和选择过程。