Numerical Analysis of DNA-Functionalized Colloidal Particle Deposition in a Channel Flow

Aggregating particulate flows are at the heart of an extremely broad range of phenomena in science, medicine and engineering, including biofilm formation in pipes and cellular aggregation in blood flow. These phenomena also are extremely popular targets for computer simulations, and impressive algorithmic developments over the years have enabled sophisticated, multiscale simulations of aggregating particulate flows in a variety of settings [e.g., 1,2]. Although various numerical models for particulate flow have been shown to capture many qualitative phenomena correctly, in most cases their predictive ability is not well established. Often, this is due to the sheer complexity of the various coupled phenomena at play.

One example in which this complexity is highly evident is the aggregation of platelets flowing over an injury in a blood vessel [1]. Here, each platelet represents a complex ‘particle’ with time-dependent shape, activity (or ‘stickiness’) that is also able to communicate with its local environment via an intricate sequence of biochemical pathways. The aggregation of these particles over the injury site is a multifaceted problem that requires the consideration of fluid mechanics, biochemical reaction networks, and particle assembly. While microfluidic models of platelet aggregation have greatly simplified the analysis of thrombosis [3], the complexity of the platelet biology is still present. Here, we consider a simplified microfluidic model system that removes much of this complexity, while retaining some of the essential physics. In particular, DNA-functionalized spherical particles [4] are used to simulate activated platelets, which interact with, and stick to, a patch on the microfluidic channel that presents a brush of complementary DNA single-strands.

The experimental model is simulated using several types of fluid-structure simulation (e.g., immersed boundary method and Brownian dynamics) in order to assess the roles of inter-particle DNA-mediated and hydrodynamic interactions, Brownian fluctuations, and various geometric and flow factors. The interplay between these factors and the resulting aggregation behavior is studied statistically with the aim of generating a reduced-order representation of the aggregation process.

[1] M. H. Flamm et al., Blood 120, 190 (2012).

[2]. J. K. W. Chesnutt and J. S. Marshall, Comput Fluids 38, 1782 (2009).

[3] T. V. Colace, G. W. Tormoen, O. J. T. McCarty, and S. L. Diamond, Annu Rev Biomed Eng. 15, 283 (2013).

[4] M. T. Casey, R. T. Scarlett, W. B. Rogers, I. Jenkins, T. Sinno, and J. C. Crocker, Nature Communications 3, 1209 (1-8) (2012).