Automated immunoassays enable robust running of assays with reproducible results and reduced hands-on time. The Gyrolab® platform runs automated immunoassays with nanoliter sample volumes, replacing ELISA and other plate-based methods. Gyrolab method development is fast, the assay time is short and the automation allows for walk-away and overnight running. In addition, the small volumes save precious samples and expensive reagents. The output from the Gyrolab runs also provides extra information. Each data value is associated with a fluorescent column profile. Here we describe how the profiles can be used for method development, trouble-shooting and to detect true data outliers.
In the Gyrolab microfluidic platform samples and reagents are automatically delivered to miniaturized streptavidin columns (15 nL) on rotating discs. Biotinylated capture reagents bind to the columns and analytes are detected by Alexa Fluor™ 647 labeled detection reagents. The flow-through format makes the assays tolerant to various biological matrices. While the system is easy to use and can be run in an operator-independent manner, the output from the Gyrolab runs also provides extra information. Each data value is associated with a fluorescent column profile where profile shape and intensity give details on antibody affinity and a quality assessment of the results.
Assay optimization and affinity characterization
The column profiles can guide the selection of antibody pairs, as it will inform on antibody-analyte interactions, or help optimize other assay parameters. In this example the column profiles were used to screen antibody clones to select candidates for the development of robust assays. High-affinity clones have a sharp dose response peak that is shifted to the left. Right shifted broad peaks represent lower affinity interactions.
Overlay of standard curves generated for multiple antibody clones using the same analyte concentrations. Example column profiles for each of the 6 clones assessed demonstrate the utility of the viewer profiles, identifying where the whole peak falls within the integration area (white square)
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