Microfluidic device for rapid digestion of tissues into cellular suspensions

Abstract

The ability to harvest single cells from tissues is currently a bottleneck for cell-based diagnostic technologies, and remains crucial in the fields of tissue engineering and regenerative medicine. Tissues are typically broken down using proteolytic digestion and various mechanical treatments, but success has been limited due to long processing times, low yield, and high manual labor burden. Here, we present a novel microfluidic device that utilizes precision fluid flows to improve the speed and efficiency of tissue digestion. The microfluidic channels were designed to apply hydrodynamic shear forces at discrete locations on tissue specimens up to 1 cm in length and 1 mm in diameter, thereby accelerating digestion through hydrodynamic shear forces and improved enzyme-tissue contact. We show using animal organs that our digestion device with hydro-mincing capabilities was superior to conventional scalpel mincing and digestion based on recovery of DNA and viable single cells. Thus, our microfluidic digestion device can eliminate or reduce the need to mince tissue samples with a scalpel, while reducing sample processing time and preserving cell viability. Another advantage is that downstream microfluidic operations could be integrated to enable advanced cell processing and analysis capabilities. We envision our novel device being used in research and clinical settings to promote single cell-based analysis technologies, as well as to isolate primary, progenitor, and stem cells for use in the fields of tissue engineering and regenerative medicine.

Figure 1

Microfluidic digestion device design and operation. (A) Image of laser-etched acrylic sheet containing the chamber for loading tissue samples and fluidic channels including upstream (left) for hydro-mincing and downstream (right) sieves. (B) Finite-element fluid dynamics simulations showing velocity profiles in devices with different numbers of hydro-mince channels. Simulation results are shown at 1 mL/min flow rate with the chamber empty and partially blocked by a model tissue. Fewer hydro-mince channels will generate stronger fluidic jets to shear the tissue, but with less overall coverage. (C,D) Full digestion device shown in (C) side and (D) exploded views, with a PDMS gasket layer sandwiched between two acrylic sheets. Hose barbs were added to the top layer and nylon screws were used to hold the device together. (E) Experimental set-up for digestion experiments. Flow was driven by a peristaltic pump and tissue digestion was visually monitored with a camera mounted above the device.

Figure 2

Digestion device optimization using beef liver cores. (A) Model tissue cores were obtained using a Tru-Cut biopsy needle and placed inside the tissue chamber. (B) Time-lapse images of tissue digestion for devices with 3, 5, and 7 hydro-mince channels. The fluid contained collagenase, and was pumped through the device at 20 mL/min. (C) Tissue loss was quantified from images based on mean gray value and overall tissue area. Trends were similar for each design, but variability was lowest for 3 hydro-mince channels. (D) Micrographs of device effluents after 30 min operation. Scale bar is 100 µm. Error bars represent standard errors from at least three independent experiments.

Figure 3

Cell recovery from fresh mouse kidney and liver tissues. (A) Genomic DNA (gDNA) was extracted and quantified from cell suspensions obtained by digestion only, scalpel mincing and digestion, or device treatment lasting for a total of 15, 30, or 60 min. gDNA increased with treatment time, and overall was higher for kidney samples. Device treatment consistently provided more gDNA than minced controls at the same time point. In most cases, gDNA was also higher than the next digestion time point, although differences were not significant. (B) Cell counter results, showing that single cell numbers largely matched gDNA findings but with higher variability. Also, liver values were now similar comparable to kidney, suggesting that kidney suspensions may have contained more aggregates. (C) Micrographs of minced controls and device effluents after lysing red blood cells. Note the large number of aggregates in the controls, particularly at 60 min. Scale bar is 100 µm. Error bars represent standard errors from at least three independent experiments. * indicates p < 0.05 relative to minced control at the same digestion time.

Figure 4

Single cell analysis of mouse kidney and liver cell suspensions. Flow cytometry was used to identify and quantify the number of leukocytes, red blood cells, and single tissue cells in the suspensions obtained from minced controls or device treatment. (A,B) Relative numbers of each cell type are shown for (A) kidney and (B) liver samples. Red blood cells comprised the highest percentage of almost all populations, and there was no statistically significant change in population compositions across all minced control and device conditions. (C,D) Total and live tissue cell numbers per mg of tissue were determined for (C) kidney and (D) liver samples. Tissue cell recovery increased with digestion time for minced controls, but did not change significantly with device processing beyond 10 min. Importantly though, all device conditions yielded more cells than minced controls that were digested for up to 30 min. Viability remained >80% for all but the longest time points, which reached as low as 70%. The x-axis for (A) and (B) are the same as (C) and (D). Error bars represent standard errors from at least three independent experiments. * indicates p < 0.05 relative to minced control at the same digestion time. # indicates p < 0.05 compared to minced control digested for 15 min.