Mechano-Node-Pore Sensing: A Rapid, Label-Free Platform for Multi-Parameter Single-Cell Viscoelastic Measurements
December 2nd, 2022
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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Overview
This article presents a method for mechanically phenotyping single cells using an electronics-based microfluidic platform known as mechano-node-pore sensing (mechano-NPS). The platform enables the measurement of both elastic and viscous properties of cells at a throughput of up to 10 cells per second, facilitating minimal sample preparation and non-destructive analysis.
Key Study Components
Area of Science
- Neuroscience
- Cell Biology
- Microfluidics
Background
- Mechano-NPS is an innovative platform for studying single cell mechanics.
- The method allows for the analysis of various cell types, including primary samples.
- It provides insights into the viscoelastic properties of cells.
- The approach is compatible with downstream analyses, enhancing its utility in research.
Purpose of Study
- To develop a method for mechanical phenotyping of single cells.
- To measure the elastic and viscous properties of cells efficiently.
- To facilitate understanding of cell behavior and disease progression.
Methods Used
- Electronics-based microfluidic platform for cell analysis.
- Measurement of single cell viscoelasticity.
- Minimal sample preparation required.
- Non-destructive measurement compatible with further analyses.
Main Results
- Successful measurement of elastic and viscous properties of various cell types.
- Demonstrated application of mechano-NPS in studying subcellular components.
- Potential for monitoring drug responses and understanding disease mechanisms.
Conclusions
- Mechano-NPS is a valuable tool for mechanical phenotyping of cells.
- The platform offers a cost-effective alternative to traditional methods.
- It opens new avenues for research in cell mechanics and biophysics.
Frequently Asked Questions
Executive Industry Relevance
Mechano-node-pore sensing (mechano-NPS) enables rapid, label-free, multi-parameter viscoelastic profiling of single cells, addressing the need for higher-throughput, quantitative mechanical phenotyping in discovery-stage biopharma R&D. By providing both elastic and viscous measurements at moderate throughput with minimal sample preparation, this platform supports predictive confidence in target validation and mechanistic de-risking. Its compatibility with downstream analyses positions it as a reusable capability for portfolio-wide biological interrogation and risk-adjusted advancement.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables quantitative interrogation of cell mechanical phenotypes relevant to disease progression and drug response.
- Supports functional target validation by distinguishing cell states based on viscoelastic properties.
- Facilitates mechanistic de-risking by linking subcellular components to measurable biophysical outputs.
- Provides multi-parameter data to inform predictive confidence and triage in early discovery.
Screening & Assay Development
- Prepares validated, label-free mechanical phenotyping assays for downstream compound screening.
- Delivers standardized, reproducible, and quantitative viscoelastic readouts for assay development.
- Enables moderate-throughput screening readiness without reliance on complex optical systems.
- Supports reliable evaluation of compound effects on cell mechanics.
Translational & Preclinical Research
- Aligns mechanical phenotyping with disease-relevant cellular states for translational biomarker exploration.
- Maintains continuity from discovery through preclinical validation by enabling downstream molecular analyses.
- Provides risk-adjusted data for advancement decisions based on biophysical cell state changes.
- Offers predictive de-risking for mechanistic hypotheses in disease models.
Pipeline & Workflow Integration
Mechano-NPS integrates into the discovery-to-preclinical continuum by enabling hypothesis testing, pathway clarification, and biological de-risking at the single-cell level.
- Discovery Biology: Quantifies viscoelastic properties to test mechanistic hypotheses and clarify disease pathways.
- Screening: Provides reproducible, quantitative outputs for compound evaluation and assay standardization.
- Analytics: Generates multi-parameter measurements (size, deformation, recovery) for robust statistical comparison.
- Translational Research: Supports biomarker alignment and downstream molecular profiling of phenotyped cells.
- Enterprise Reuse: Offers a scalable, adaptable platform for repeated use across diverse cell types and programs.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in target validation.
- Operational Value: Delivers standardized, scalable, and reproducible mechanical phenotyping with minimal sample prep.
- Strategic Value: Improves go/no-go decisions and capital efficiency by providing actionable biophysical data early.
- Portfolio Impact: Enables risk-adjusted prioritization and advancement across multiple discovery programs.
Implementation Considerations
- Requires expertise in microfluidics, electronics-based measurement, and data analysis.
- Needs access to standard soft lithography fabrication and electronic data acquisition infrastructure.
- Demands cross-team standardization for sample preparation and data interpretation.
- Adaptable to a range of cell types and compatible with downstream molecular analyses.
- Throughput is moderate (up to 10 cells/sec), balancing depth of measurement with screening needs.
