Handheld optofluidic platform towards binding dynamics applications in field-settings

We have introduced a lensfree optofluidic platform that incorporates subwavelength nanohole arrays, a compact microfluidics system, and on-chip computational imaging to enable label-free identification of biomolecular interactions. Our platform weighs only 260 g and has dimensions of 16 cm x 10 cm x 11 cm. It utilizes a CMOS imager to capture plasmonic diffraction field images, offering a wide field-of-view of up to 11.5 mm2 for refractive index sensing. To illuminate the plasmonic chip, we employ an LED source positioned close to the transmission resonance of the nanohole arrays. This LED source creates diffraction patterns on the imager. The platform ensures the targeted delivery of analytes to the ligand-coated sensing surface using microfluidics. By analyzing real-time variations within the diffraction field images, we could reveal the time-dependent binding dynamics of biomolecules. Our platform has demonstrated an experimentally obtained limit of detection (LOD) as low as 5 ng/mL for protein IgG. Furthermore, based on the real-time diffraction field images, we successfully determine the association and disassociation constants, which account for the binding and detachment between protein A/G and IgG. We have also developed a software that allows full control of the hardware settings of the portable platform, including the camera and pump system. This software also incorporates an image-processing algorithm to calculate the binding parameters for the analytes of interest. Providing high-quality sensing capabilities in a cost-effective infrastructure, we believe that our optofluidic biosensor platform offers significant advantages for surface plasmon resonance (SPR) applications for field-settings.

Automated summary

We have developed a lensfree optofluidic platform for label-free identification of biomolecular interactions. Our platform is compact, portable, and utilizes microfluidics and on-chip computational imaging. The experimental results demonstrate the high sensing capabilities and cost-effective infrastructure of our platform, making it a promising tool for biosensing applications.