Abstract
Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.
Highlights
Microfluidics is a promising technology for biological inquiries at the single-cell level, such as single-cell gene expression for lineage analysis [1, 2] and signaling dynamics [3], microfluidic cell sorting [4]
Using a microfluidic channel decorated with ridges that are diagonal with respect to the flow direction (Fig 1), cells are compressed and translated when passing through the channel, and exhibit different trajectories depending on their biomechanical properties
We develop a computational pipeline for automatically extracting single-cell trajectories from video recordings of cells moving through ridged microfluidic channels
Summary
Microfluidics is a promising technology for biological inquiries at the single-cell level, such as single-cell gene expression for lineage analysis [1, 2] and signaling dynamics [3], microfluidic cell sorting [4]. One interesting application is the study of single-cell biomechanical characteristics, such as elasticity, viscosity, stiffness and adhesion [5]. Using a microfluidic channel decorated with ridges that are diagonal with respect to the flow direction (Fig 1), cells are compressed and translated when passing through the channel, and exhibit different trajectories depending on their biomechanical properties. The trajectories are affected by the channel design, in terms of the ridge height, angle, and spacing. The microfluidic approach for studying cellular biomechanics is highly cost effective compared to atomic force microscopy, and has high throughput similar to flow cytometry.
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