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通过对原代B细胞进行多参数分析来分析抗体反应。

Profiling antibody responses by multiparametric analysis of primary B cells.

作者信息

Story Craig M, Papa Eliseo, Hu Chih-Chi Andrew, Ronan Jehnna L, Herlihy Kara, Ploegh Hidde L, Love J Christopher

机构信息

Whitehead Institute for Biomedical Research, Cambridge, MA 02139, USA.

出版信息

Proc Natl Acad Sci U S A. 2008 Nov 18;105(46):17902-7. doi: 10.1073/pnas.0805470105. Epub 2008 Nov 12.

DOI:10.1073/pnas.0805470105
PMID:19004776
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2584674/
Abstract

Determining the efficacy of a vaccine generally relies on measuring neutralizing antibodies in sera. This measure cannot elucidate the mechanisms responsible for the development of immunological memory at the cellular level, however. Quantitative profiles that detail the cellular origin, extent, and diversity of the humoral (antibody-based) immune response would improve both the assessment and development of vaccines. Here, we describe a novel approach to collect multiparametric datasets that describe the specificity, isotype, and apparent affinity of the antibodies secreted from large numbers of individual primary B cells (approximately 10(3)-10(4)). The antibody/antigen binding curves obtained by this approach can be used to classify closely related populations of cells using algorithms for data clustering, and the relationships among populations can be visualized graphically using affinity heatmaps. The technique described was used to evaluate the diversity of antigen-specific antibody-secreting cells generated during an in vivo humoral response to a series of immunizations designed to mimic a multipart vaccination. Profiles correlating primary antibody-producing cells with the molecular characteristics of their secreted antibodies should facilitate both the evaluation of candidate vaccines and, broadly, studies on the repertoires of antibodies generated in response to infectious or autoimmune diseases.

摘要

确定疫苗的效力通常依赖于检测血清中的中和抗体。然而,这种检测方法无法阐明在细胞水平上负责免疫记忆形成的机制。详细描述体液(基于抗体)免疫反应的细胞起源、程度和多样性的定量概况,将有助于改进疫苗的评估和研发。在此,我们描述了一种新方法,用于收集多参数数据集,这些数据集描述了大量单个原代B细胞(约10³-10⁴个)分泌的抗体的特异性、同种型和表观亲和力。通过这种方法获得的抗体/抗原结合曲线可用于使用数据聚类算法对密切相关的细胞群体进行分类,并且群体之间的关系可以使用亲和力热图以图形方式可视化。所描述的技术用于评估在针对一系列旨在模拟多组分疫苗接种的免疫过程中体内体液反应期间产生的抗原特异性抗体分泌细胞的多样性。将原代抗体产生细胞与其分泌抗体的分子特征相关联的概况,应有助于评估候选疫苗,并广泛促进对针对感染性或自身免疫性疾病产生的抗体库的研究。

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