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DOI: 10.3791/64665-v
Andre Lai*1, Rachel Rex*2, Kristen L. Cotner1, Alan Dong3, Michael Lustig1,3, Lydia L. Sohn1,2
1Graduate Program in Bioengineering,University of California, Berkeley and University of California, San Francisco, 2Department of Mechanical Engineering,University of California, Berkeley, 3Department of Electrical Engineering and Computer Sciences,University of California, Berkeley
Presented here is a method to mechanically phenotype single cells using an electronics-based microfluidic platform called mechano-node-pore sensing (mechano-NPS). This platform maintains moderate throughput of 1-10 cells/s while measuring both the elastic and viscous biophysical properties of cells.
We present an electronics-based microfluidic platform for mechanical phenotyping of single cells. Specifically, we measure single cell elastic and viscous properties at a throughput of up to 10 cells per second. Our method requires minimal sample preparation, utilizes a straightforward electronic measurement, replacing expensive optical hardware and complex image analysis, and is non-destructive, meaning our approach is compatible with downstream analyses.
Mechano-NPS has been applied to many cell types, including primary samples, and has measured the effect of subcellular components on single cell viscoelasticity. It could be used for understanding cell behavior, determining disease progression, or monitoring drug response. To begin, remove the plasma treated components from the plasma chamber.
Pipet a two to one solution of methanol and deionized water on the glass substrate with pre-fabricated electrodes. Then place the PDMS mold with the feature side down on top of the glass substrate. Place the device under the stereoscope to adjust alignment.
Bake the aligned device to complete device fabrication. Prepare the pressure source, PCB, benchtop hardware, and data acquisition software. Next, align the clamps header pins with the holes on the PCB and align the clamps spring loaded pins with the electrode contact pads on the microfluidic device.
Then insert the clamps header pins into the PCB holes, making sure the spring loaded pins stay aligned with the electrode contact pads. Set up and connect the electronic hardware. Next, set the values to initialize the data acquisition session and set the sample rate for acquisition.
Culture and prepared the cells according to the appropriate cell culture protocol of the cell line of choice. Then suspend the cells in a prepared solution of 2%FBS and 1X PBS at a concentration between 100, 000 and 500, 000 cells per milliliter. Keep the cells on ice for the duration of the experiments.
To load cells into the microfluidic device, cut 30 centimeters of polytetrafluoroethylene tubing with a razor blade. Use a syringe to drop the cell sample into the end of the tubing and connect the same end into the device inlet. Finally, connect the opposite end of the tubing to the microfluidic pressure controller.
To run the experiment, set the desired constant driving pressure on the pressure controller software and allow the sample to fill the device. If bubbles form in the microfluidic channels, use dead-end filling. Plug the device outlet and apply a low pressure to the inlet to force air out through the gas permeable PDMS.
Then set the desired voltage by rotating the voltage knob on the power supply and enable the voltage by pressing the on button. Turn on the current preamplifier and set the sensitivity as low as possible. Alternatively, set the gain as high as possible without overloading the preamplifier or exceeding the maximum analog input voltage of the DAQ.
Press the green Run button in the MATLAB ribbon menu to begin the data acquisition script NPS. m, and start sampling and saving the data. To end the experiment, press the Stop button in the lower left corner of the live plot window to end the data acquisition script.
Then disable the power supply output by pressing the On button. Finally, set the pressure source to zero pressure in the pressure controller software. For data analysis, the raw signal should have a sufficient signal-to-noise ratio to filter out the noise and extract the significant components.
Critically, the current signal rise from each node should be robust enough such that subpulses can be easily identified from the difference signal. Malignant MCF-7 cells have a greater wCDI distribution than non-malignant MCF-10A cells, indicating that the malignant MCF-7 cells are softer than their nonmalignant MCF-10A counterparts. MCF-10A and MCF-7 cells treated with latrunculin show an increase in wCDI.
A distinct wCDI distribution differentiating the two primary cell types indicates that LEP cells are softer than MEP cells. Nonmalignant MCF-10As and untreated MCF-10A and MCF-7s have a greater proportion of cells that recover instantly, indicating lower viscosity than their malignant or latrunculin treated counterpart. If the live current readout appears abnormal, stop your experiment and inspect the microfluidic channel.
Ensure that there are no air bubbles and no clogs such that the cells are flowing freely from the inlet to the outlet. Because our method doesn't harm cells, downstream analyses like RNA-seq or immunofluorescence can be performed. This could help uncover some underlying reasons why cells have distinct mechanical phenotypes.
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