Competitive electrochemiluminescence wash and no-wash immunoassays for detection of serum antibodies to smooth Brucella strains
Brucellosis is a bacterial zoonotic disease of major global importance. Natural hosts for Brucella species include animals of economic significance, such as cattle and small ruminants. Controlling brucellosis in natural hosts by high-throughput serological testing followed by the slaughter of seropositive animals helps to prevent disease transmission. This study aimed to convert an existing competitive enzyme-linked immunosorbent assay (cELISA), used for the serodiagnosis of brucellosis in ruminants, to two electrochemiluminescence (ECL) immunoassays on the Meso Scale Discovery (MSD) platform. The first assay employed a conventional plate washing step as part of the protocol. The second was a no-wash assay, made possible by the proximity-based nature of ECL signal generation by the MSD platform. Both ECL wash and no-wash assays closely matched the parent cELISA for diagnostic sensitivity and specificity. The results also demonstrated that both ECL assays met World Organization for Animal Health (OIE) standards, as defined by results for the OIE standard serum (OIEELISA(SP)SS). This report is the first to describe an ECL assay incorporating lipopolysaccharide, an ECL assay for serodiagnosis of a bacterial infectious disease, a separation-free (no-wash) ECL assay for the detection of serum antibodies, and the use of the MSD platform for serodiagnosis. The simple conversion of the cELISA to the MSD platform suggests that many other serodiagnostic tests could readily be converted. Furthermore, the alignment of these results with the multiplex capability of the MSD platform offers the potential of no-wash multiplex assays to screen for several diseases.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
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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
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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