Dose-response curve of a microfluidic magnetic bead-based surface coverage sandwich assay

Magnetic micro-and nanoparticles ('magnetic beads') have been used to advantage in many microfluidic devices for sensitive antigen (Ag) detection. Today, assays that use as read-out of the signal the number count of immobilized beads on a surface for quantification of a sample's analyte concentration have been among the most sensitive and have allowed protein detection lower than the fg mL(-1) concentration range. Recently, we have proposed in this category a magnetic bead surface coverage assay (Tekin et al., 2013 [1]), in which 'large' (2.8 mm) antibody (Ab)-functionalized magnetic beads captured their Ag from a serum and these Ag-carrying beads were subsequently exposed to a surface pattern of fixed 'small' (1.0 mm) Ab-coated magnetic beads. When the system was exposed to a magnetic induction field, the magnet dipole attractive interactions between the two bead types were used as a handle to approach both bead surfaces and assist with Ag-Ab immunocomplex formation, while unspecific binding (in absence of an Ag) of a large bead was reduced by exploiting viscous drag flow. The dose-response curve of this type of assay had two remarkable features: (i) its ability to detect an output signal (i.e. bead number count) for very low Ag concentrations, and (ii) an output signal of the assay that was non-linear with respect to Ag concentration. We explain here the observed dose-response curves and show that the type of interactions and the concept of our assay are in favour of detecting the lowest analyte concentrations (where typically either zero or one Ag is carried per large bead), while higher concentrations are less efficiently detected. We propose a random walk process for the Ag-carrying bead over the magnetic landscape of small beads and this model description explains the enhanced overall capture probability of this assay and its particular non-linear dose response curves. Research Paper

Published in:
New Biotechnology, 32, 5, 433-440
Amsterdam, Elsevier

 Record created 2015-09-28, last modified 2018-03-17

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