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#23576245   2013/04/10 To Up

Development of a bead-based multiplex assay for the simultaneous detection of porcine inflammation markers using xMAP technology.

Commercially available assays for the simultaneous detection of multiple inflammatory and cardiac markers in porcine blood samples are currently lacking. Therefore, this study was aimed at developing a bead-based, multiplexed flow cytometric assay to simultaneously detect porcine cytokines [interleukin (IL)-1β, IL-6, IL-10, and tumor necrosis factor alpha], chemokines (IL-8 and monocyte chemotactic protein 1), growth factors [basic fibroblast growth factor (bFGF), vascular endothelial growth factor, and platelet-derived growth factor-bb], and injury markers (cardiac troponin-I) as well as complement activation markers (C5a and sC5b-9). The method was based on the Luminex xMAP technology, resulting in the assembly of a 6- and 11-plex from the respective individual singleplex situation. The assay was evaluated for dynamic range, sensitivity, cross-reactivity, intra-assay and interassay variance, spike recovery, and correlation between multiplex and commercially available enzyme-linked immunosorbent assay as well as the respective singleplex. The limit of detection ranged from 2.5 to 30,000 pg/ml for all analytes (6- and 11-plex assays), except for soluble C5b-9 with a detection range of 2-10,000 ng/ml (11-plex). Typically, very low cross-reactivity (<3% and <1.4% by 11- and 6-plex, respectively) between analytes was found. Intra-assay variances ranged from 4.9 to 7.4% (6-plex) and 5.3 to 12.9% (11-plex). Interassay variances for cytokines were between 8.1 and 28.8% (6-plex) and 10.1 and 26.4% (11-plex). Correlation coefficients with singleplex assays for 6-plex as well as for 11-plex were high, ranging from 0.988 to 0.997 and 0.913 to 0.999, respectively. In this study, a bead-based porcine 11-plex and 6-plex assay with a good assay sensitivity, broad dynamic range, and low intra-assay variance and cross-reactivity was established. These assays therefore represent a new, useful tool for the analysis of samples generated from experiments with pigs.
Anjan K Bongoni, Jonas Lanz, Robert Rieben, Yara Banz

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