A method for detecting hepatitis C envelope specific memory B cells from multiple genotypes using cocktail E2 tetramers
Hepatitis C (HCV) is a rapidly mutating RNA virus, with a strong propensity to cause chronic infection and progressive liver disease. Recent evidence has shown that early appearance of neutralizing antibodies in primary infection is associated with clearance. Little is known about the characteristics of HCV-specific B cells and their correlation with outcomes in primary infection, as there is a lack of sensitive tools for HCV-specific B cells which are present at very low frequency. We describe the development and optimisation of tetramer staining for flow cytometric detection of HCV-specific B cells using a cocktail of two recombinant HCV Envelope-2 (rE2) glycoproteins (from genotype 1a and 3a; Gt1a and Gt3a) and streptavidin dyes. The optimal weight to weight (w/w) ratio of streptavidin-phycoerythrin (PE) and rE2 proteins were determined for sensitive detection using HCV E2-specific hybridoma cell lines and peripheral blood mononuclear cells (PBMC) from HCV-infected individuals. In a cross-sectional set of PBMC samples collected from 33 subjects with either chronic infection or previous clearance, HCV E2-specific B cells (CD19+CD20+CD10-IgD-tetramer+) were detected in 29 subjects (87.8%), with a mean frequency of 0.45% (0.012-2.20%). To validate the specificity of tetramer staining, 367 HCV E2-specific B cells were single cell sorted from 9 PBMC samples before monoclonal antibodies (mAbs) were synthesised, with 87.5% being reactive to E2 via ELISA. Of these mAbs, 284 and 246 clones were reactive to either Gt1a or Gt3a E2 proteins, respectively. This is a sensitive and robust method for future studies investigating B cell responses against the HCV Envelope protein.Keywords: E2-specific B cells; HCV; Monoclonal antibodies and hybridoma cells; Tetramer.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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