Optical estimation of the expression of surface molecules

The expression level of specific surface molecules – antigens – on certain cells can be diagnostic for disease. Flow cytometry is the gold standard technique for assessing antigen expression, but it’s expensive and labor-intensive. Recently, a group of bioengineers led by Rashid Bashir at the University of Illinois have invented a microfluidic device for measuring the number of antigens on a particle. They report their device’s potential as a cheap, rapid point-of-care, single use instrument for patient diagnoses in APL Bioengineering.

First author, Tanmay Ghonge emphasized the novelty of assessing antigen expression using an optical sensor, adding that while experimentalists have captured particles, “they couldn’t easily extract the number of protein molecules on the surface.” Ghonge explained how they built a statistical model based on the theoretically expected profile of captured particles in the microfluidic channel.

The team fabricated a microfluidic device with thousands of 30µm diameter pillars, presenting a large surface area for capture of the antigen expressing particles. The device had to satisfy all of the assumptions and requirements of the mathematical framework, for instance, a constant distance between each interaction of a particle in the fluid. To test their device, sets of beads coated in different concentrations of biotin were captured on neutravidin coated pillars. The position of captured particles was measured from microscopic images and the surface density of biotin molecules was back-calculated. Control measurements were performed using flow cytometry.

Bashir explained that the next step is to test actual clinical samples. The researchers are also working to miniaturize the imaging apparatus, looking to further the convenience and speed of diagnoses by using smartphones to image particle capture.

Source: “A microfluidic technique to estimate antigen expression on particles,” by Tanmay Ghonge, Anurup Ganguli, Enrique Valera, Mariam Saadah, Gregory L. Damhorst, Jacob Berger, Gelson Pagan Diaz, Umer Hassan, Monish Chheda, Zeeshan Haidry, Stan Liu, Carissa Hwu, and Rashid Bashir, APL Bioengineering (2017). The article can be accessed at https://doi.org/10.1063/1.4989380 .