Modeling Analyte Transport and Capture in Porous Bead Sensors

Abstract

Porous agarose microbeads, with high surface to volume ratios and high binding densities, are attracting attention as highly sensitive, affordable sensor elements for a variety of high performance bioassays. While such polymer microspheres have been extensively studied and reported on previously and are now moving into real-world clinical practice, very little work has been completed to date to model the convection, diffusion, and binding kinetics of soluble reagents captured within such fibrous networks. Here, we report the development of a three-dimensional computational model and provide the initial evidence for its agreement with experimental outcomes derived from the capture and detection of representative protein and genetic biomolecules in 290μm porous beads. We compare this model to antibody-mediated capture of C-reactive protein and bovine serum albumin, along with hybridization of oligonucleotide sequences to DNA probes. These results suggest that due to the porous interior of the agarose bead, internal analyte transport is both diffusion- and convection-based, and regardless of the nature of analyte, the bead interiors reveal an interesting trickle of convection-driven internal flow. Based on this model, the internal to external flow rate ratio is found to be in the range of 1:3100 to 1:170 for beads with agarose concentration ranging from 0.5% to 8% for the sensor ensembles here studied. Further, both model and experimental evidence suggest that binding kinetics strongly affect analyte distribution of captured reagents within the beads. These findings reveal that high association constants create a steep moving boundary in which unbound analytes are held back at the periphery of the bead sensor. Low association constants create a more shallow moving boundary in which unbound analytes diffuse further into the bead before binding. These models agree with experimental evidence and thus serve as a new tool set for the study of bio-agent transport processes within a new class of medical microdevices.

Enhancement of performance in porous bead-based microchip sensors: effects of chip geometry on bio-agent capture

“…As the fluid delivered to the array of beads was forced to flow through each bead sensor, a bypass area-dependent pressure gradient was observed at and around the beads while the pressure at the bottom of the wells dropped to zero. 37 …”

“…37 Briefly, a three-dimensional model consisting of incompressible Navier-Stokes and convection-diffusion equations allowed for the simulation of analyte transport and modeling in a single well. The well, modeled and imported from AutoCAD, consisted either of a PF or CPF micro-well.…”

“…Previous computational fluid dynamic model studies characterized bio-agent capture and fluid flow dynamics for pressure-driven flow in the inverted PF microchip of the p-BNC system. 37 These results suggested that pressure-driven flow increases analyte capture within porous sensors.…”

Microfluidics for DNA and Protein Analysis with Multiplex Microbead-Based Assays

“…A variety of biocompatible materials have been used for fabrication of bead-based solid support for capture of target biomolecules, such as silica [34], polystyrene (PS) [35], agarose [36], and paramagnetic materials [37]. Methods for increasing the binding capacity in beads have also been intensively studied, which focused on modifying the chemical functionalization of the bead surface, tuning the bead size, and physically compressing the bead.…”

Diagnostic performance study of an antigen microarray for the detection of antiphospholipid antibodies in human serum

“…This might cause unequal flow over the sensor surface and therefore an uneven distribution of the injected analyte. Generally, a thinning of analyte concentration is possible, especially for high association constants [18,19]. To assess the overall performance of the detection and microfluidic system, BSA/anti-BSA (50 μg/mL) was used as model system.…”