Non-Linear Cellular Dielectrophoretic Behavior Characterization Using Dielectrophoretic Tweezers-Based Force Spectroscopy inside a Microfluidic Device

Cellular subpopulations identified using an ensemble average of multiple dielectrophoresis measurements

While the average value measurement approach can successfully analyze and predict the general behavior and biophysical properties of an isogenic cell population, it fails when significant differences among individual cells are generated in the population by intracellular changes such as the cell cycle, or different cellular responses to certain stimuli. Detecting such single-cell differences in a cell population has remained elusive. Here, we describe an easy-to-implement and generalizable platform that measures the dielectrophoretic cross-over frequency of individual cells by decreasing measurement noise with a stochastic method and computing ensemble average statistics. This platform enables multiple, real-time, label-free detection of individual cells with significant dielectric variations over time within an isogenic cell population. Using a stochastic method in combination with the platform, we distinguished cell subpopulations from a mixture of drug-untreated and -treated isogenic cells. Furthermore, we demonstrate that our platform can identify drug-treated isogenic cells with different recovery rates.

On-Chip Single-Cell Bioelectrical Analysis for Identification of Cell Electrical Phenotyping in Response to Sequential Electric Signal Modulation

In recent years, an interesting biomarker called membrane breakdown voltage has been examined using artificial planar lipid bilayers. Even though they have great potential to identify cell electrical phenotyping for distinguishing similar cell lines or cells under different physiological conditions, the biomarker has not been evaluated in the context of living cell electrical phenotyping. Herein, we present a single-cell analysis platform to continuously measure the electric response in a large number of cells in parallel using electric frequency and voltage variables. Using this platform, we measured the direction of cell displacement and transparent cell image alteration as electric polarization of the cell responds to signal modulation, extracting the dielectrophoretic crossover frequency and membrane breakdown voltage for each cell, and utilizing the measurement results in the same spatiotemporal environment. We developed paired parameters using the dielectrophoretic crossover frequency and membrane breakdown voltage for each cell and evaluated the paired parameter efficiency concerning the identification of two different breast cancer cells and cell drug response. Moreover, we showed that the platform was able to identify cell electrical phenotyping, which was generated by subtle changes in cholesterol depletion-induced cell membrane integrity disruption when the paired parameter was used. Our platform introduced in this paper is extremely useful for facilitating more accurate and efficient evaluation of cell electrical phenotyping in a variety of applications, such as cell biology and drug discovery.

Ultra-sensitive dielectrophoretic surface charge multiplex detection inside a micro-dielectrophoretic device

Label-free dielectrophoretic force-based surface charge detection has shown great potential for highly sensitive and selective sensing of metal ions and small biomolecules. However, this method suffers from a complex calibration process and measurement signal interference in simultaneous multi-analyte detection, thus creating difficulties in multiplex detection. We have developed a method to overcome these issues based on the optical discrimination of the dielectrophoretic behaviors of multiple microparticle probes considering the surface charge difference before and after self-assembling conjugation. In this report, we demonstrate and characterize this dielectrophoretic force-based surface charge detection method with particle probes functionalized by various biomolecules. This technique achieved an attomolar limit of detection (LOD) for Hg²⁺ in distilled water and a femtomolar LOD in drinking water using DNA aptamer-functionalized particle probes. More importantly, using two different DNA aptamer-functionalized particle probes for Hg²⁺ and Ag⁺, label-free dielectrophoretic multiplex detection of these species in drinking water with a femtomolar and a nanomolar LOD was achieved for the first time.

Effect of geometry on dielectrophoretic trap stiffness in microparticle trapping

Dielectrophoresis, an electrokinetic technique, can be used for contactless manipulation of micro- and nano-size particles suspended in a fluid. We present a 3-D microfluidic DEP device with an orthogonal electrode configuration that uses negative dielectrophoresis to trap spherical polystyrene micro-particles. Traps with three different basic geometric shapes, i.e. triangular, square, and circular, and a fixed trap area of around 900 μm² were investigated to determine the effect of trap shape on dynamics and strength of particle trapping. Effects of trap geometry were quantitatively investigated by means of trap stiffness, with applied electric potentials from 6 V_P-P to 10 V_P-P at 1 MHz. Analyzing the trap stiffness with a trapped 4.42 μm spherical particle showed that the triangular trap is the strongest, while the square shape trap is the weakest. The trap stiffness grew more than eight times in triangular traps and six times in both square and circular traps when the potential of the applied electric field was increased from 6 V_P-P to 10 V_P-P at 1 MHz. With the maximum applied potential, i.e. 10 V_P-P at 1 MHz, the stiffness of the triangular trap was 60% and 26% stronger than the square and circular trap, respectively. A finite element model of the microfluidic DEP device was developed to numerically compute the DEP force for these trap shapes. The findings from the numerical computation demonstrate good agreement with the experimental analysis. The analysis of three different trap shapes provides important insights to predict trapping location, strength of the trapping zone, and optimized geometry for high throughput particle trapping.

Quantitative analysis of the three-dimensional trap stiffness of a dielectrophoretic corral trap

Dielectrophoresis is a robust approach for the manipulation and separation of (bio)particles using microfluidic platforms. We developed a dielectrophoretic corral trap in a microfluidic device that utilizes negative dielectrophoresis to capture single spherical polystyrene particles. Circular-shaped micron-size traps were employed inside the device and the three-dimensional trap stiffness (restoring trapping force from equilibrium trapping location) was analyzed using 4.42 μm particles and 1 MHz of an alternating electric field from 6 V_P-P to 10 V_P-P . The trap stiffness increased exponentially in the x- and y-direction, and linearly in the z-direction. Image analysis of the trapped particle movements revealed that the trap stiffness is increased 608.4, 539.3, and 79.7% by increasing the voltage from 6 V_P-P to 10 V_P-P in the x-, y-, and z-direction, respectively. The trap stiffness calculated from a finite element simulation of the device confirmed the experimental results. This analysis provides important insights to predict the trapping location, strength of the trapping, and optimum geometry for single particle trapping and its applications such as single-molecule analysis and drug discovery.

Toward low-voltage dielectrophoresis-based microfluidic systems: A review

Dielectrophoretically driven microfluidic devices have demonstrated great applicability in biomedical engineering, diagnostic medicine, and biological research. One of the potential fields of application for this technology is in point-of-care (POC) devices, ideally allowing for portable, fully integrated, easy to use, low-cost diagnostic platforms. Two main approaches exist to induce dielectrophoresis (DEP) on suspended particles, that is, electrode-based DEP and insulator-based DEP, each featuring different advantages and disadvantages. However, a shared concern lies in the input voltage used to generate the electric field necessary for DEP to take place. Therefore, input voltage can determine portability of a microfluidic device. This review outlines the recent advances in reducing stimulation voltage requirements in DEP-driven microfluidics.

A novel automatic segmentation and tracking method to measure cellular dielectrophoretic mobility from individual cell trajectories for high throughput assay

BACKGROUND AND OBJECTIVE

The dielectrophoresis (DEP) technique is increasingly being recognised as a potentially valuable tool for non-contact manipulation of numerous cells as well as for biological single cell analysis with non-invasive characterisation of a cell's electrical properties. Several studies have attempted to track multiple cells to characterise their cellular DEP mobility. However, they encountered difficulties in simultaneously tracking the movement of a large number of individual cells in a bright-field image sequence because of interference from the background electrode pattern. Consequently, this present study aims to develop an automatic system for imaging-based characterisation of cellular DEP mobility, which enables the simultaneous tracking of several hundred of cells inside a microfluidic device.

METHODS

The proposed method for segmentation and tracking of cells consists of two main stages: pre-processing and particle centre localisation. In the pre-processing stage, background subtraction and contrast enhancement were performed to distinguish the cell region from the background image. In the particle centre localisation stage, the unmarked cell was automatically detected via graph-cut algorithm-based K-means clustering.

RESULTS

Our algorithm enabled segmentation and tracking of numerous Michigan Cancer Foundation-7 (MCF-7) cell trajectories while the DEP force was oscillated between positive and negative. The cell tracking accuracy and cell count capability was at least 90% of the total number of cells with the newly developed algorithm. In addition, the cross-over frequency was measured by analysing the segmented and tracked trajectory data of the cellular movements caused by the positive and negative DEP force. The measured cross-over frequency was compared with previous results. The multi-cellular movements investigation based on the measured cross-over frequency was repeated until the viability of cells was unchanged in the same environment as in a microfluidic device. The results were statistically consistent, indicating that the developed algorithm was reliable for the investigation of DEP cellular mobility.

CONCLUSION

This study developed a powerful platform to simultaneously measure the DEP-induced trajectories of numerous cells, and to investigate in a robust, efficient, and accurate manner the DEP properties at both the single cell and cell ensemble level.

Variable Membrane Dielectric Polarization Characteristic in Individual Live Cells

Investigation of the dielectric properties of cell membranes plays an important role in understanding the biological activities that sustain cellular life and realize cellular functionalities. Herein, the variable dielectric polarization characteristics of cell membranes are reported. In controlling the dielectric polarization of a cell using dielectrophoresis force spectroscopy, different cellular crossover frequencies were observed by modulating both the direction and sweep rate of the frequency. The crossover frequencies were used for the extraction of the variable capacitance, which is involved in the dielectric polarization across the cell membranes. In addition, this variable phenomenon was investigated by examining cells whose membranes were cholesterol-depleted with methyl-β-cyclodextrin, which verified a strong correlation between the variable dielectric polarization characteristics and membrane composition changes. This study presented the dielectric polarization properties in live cells' membranes that can be modified by the regulation of external stimuli and provided a powerful platform to explore cellular membrane dielectric polarization.

Personalized Drug Efficacy Monitoring Chip

Cancer drug resistance mechanisms such as tumor heterogeneity and adaptable feedback loops are prevalent issues facing cancer therapy development. Drug resistance can be unique to a cancer type and, most importantly, to each individual cancer patient. Consequently, testing different dosages and therapeutics directly on each individual patient sample (i.e., tumor and cancer cells) has compelling advantages compared to large scale in vitro drug testing and is a step toward personalized drug selection and effective treatment development. Recently, microfluidic-based chemo-sensitivity assays on patient biopsies have been proposed. Despite their novelty, these platforms usually rely on optical labels, optical equipment, or complex microfabricated channel geometries and structures. In this work, we proposed a novel lab on a chip platform capable of real-time and continuous screening of drug efficacy on (cancer) cell subpopulations without the need of labels or bulky readout optical equipment. In this platform, several label-free and rapid techniques have been implemented for the precise capturing of cells of interest in parallel with the real-time measurement and characterization of the effectiveness of candidate therapeutic agents. To demonstrate the utility of the platform, the effect of an apoptotic inducer, topoisomerase I inhibitor, 7-ethyl-10-hydrocamptothecin (SN38) on human colorectal carcinoma cancer cells (HCT 116) was used as a study model. Additionally, electrical results were optically verified to examine the continuous measurements of the biological mechanisms, specifically, apoptosis and necrosis, during therapeutic agent characterizations. The proposed device is a versatile platform which can also be easily redesigned for the automated and arrayed analysis of cell-drug interaction down to the single cell level. Our platform is another step toward enabling the personalized screening of drug efficacy on individual patients' samples that potentially leads to a better understanding of drug resistance and the optimization of patients' treatments.