Microfluidic characterization of specific membrane capacitance and cytoplasm conductivity of singlecells

Oxidative Phosphorylation Does Not Violate the Second Law of Thermodynamics

In a recent series of papers, James W. Lee reported that mitochondrial oxidative phosphorylation violates the second law of thermodynamics and that it is allowed to do so because it is a "Type-B" process that features lateral and longitudinal membrane asymmetry. We show here that these contentions are based on problematic interpretations of the literature. More reliable values of ΔGredox and ΔGATP synthesis show that the second law is not violated. More recent reports on the structures of the redox-driven proton pumps (Complexes I, III, and IV) suggest that longitudinal membrane asymmetry does not exist. Finally, Lee's predictions for the concentration of protons localized at the P-side surface of the bioenergetic membrane are likely to be much too high due to several errors; thus, his predicted high values of ΔpHsurface that violate the second law are likely to be wrong. There is currently no strong experimental or theoretical evidence to support the contention that oxidative phosphorylation violates the second law of thermodynamics.

A new label free spiral sensor using impedance spectroscopy to characterize hepatocellular carcinoma in tissue and serum samples

Hepatocellular carcinoma (HCC) stands as the most prevalent form of primary liver cancer, predominantly affecting patients with chronic liver diseases such as hepatitis B or C-induced cirrhosis. Diagnosis typically involves blood tests (assessing liver functions and HCC biomarkers), imaging procedures such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), and liver biopsies requiring the removal of liver tissue for laboratory analysis. However, these diagnostic methods either entail lengthy lab processes, require expensive imaging equipment, or involve invasive techniques like liver biopsies. Hence, there exists a crucial need for rapid, cost-effective, and noninvasive techniques to characterize HCC, whether in serum or tissue samples. In this study, we developed a spiral sensor implemented on a printed circuit board (PCB) technology that utilizes impedance spectroscopy and applied it to 24 tissues and sera samples as proof of concept. This newly devised circuit has successfully characterized HCC and normal tissue and serum samples. Utilizing the distinct dielectric properties between HCC cells and serum samples versus the normal samples across a specific frequency range, the differentiation between normal and HCC samples is achieved. Moreover, the sensor effectively characterizes two HCC grades and distinguishes cirrhotic/non-cirrhotic samples from tissue specimens. In addition, the sensor distinguishes cirrhotic/non-cirrhotic samples from serum specimens. This pioneering study introduces Electrical Impedance Spectroscopy (EIS) spiral sensor for diagnosing HCC and liver cirrhosis in clinical serum-an innovative, low-cost, rapid (< 2 min), and precise PCB-based technology without elaborate sample preparation, offering a novel non-labeled screening approach for disease staging and liver conditions.

Electroactive composite biofilms integrating Kombucha, Chlorella and synthetic proteinoid Proto-Brains

In this study, we present electroactive biofilms made from a combination of Kombucha zoogleal mats and thermal proteinoids. These biofilms have potential applications in unconventional computing and robotic skin. Proteinoids are synthesized by thermally polymerizing amino acids, resulting in the formation of synthetic protocells that display electrical signalling similar to neurons. By incorporating proteinoids into Kombucha zoogleal cellulose mats, hydrogel biofilms can be created that have the ability to efficiently transfer charges, perform sensory transduction and undergo processing. We conducted a study on the memfractance and memristance behaviours of composite biofilms, showcasing their capacity to carry out unconventional computing operations. The porous nanostructure and electroactivity of the biofilm create a biocompatible interface that can be used to record and stimulate neuronal networks. In addition to in vitro neuronal interfaces, these soft electroactive biofilms show potential as components for bioinspired robotics, smart wearables, unconventional computing devices and adaptive biorobotic systems. Kombucha-proteinoids composite films are a highly customizable material that can be synthesized to suit specific needs. These films belong to a unique category of 'living' materials, as they have the ability to support cellular systems and improve bioelectronic functionality. This makes them an exciting prospect in various applications. Ongoing efforts are currently being directed towards enhancing the compositional tuning of conductivity, signal processing and integration within hybrid bioelectronic circuits.

Metal-pad-enhanced resistive pulse sensor reveals complex-valued Braess paradox

A resistive pulse sensor measures the electrical impedance of an electrolyte-filled channel as particles flow through it. Ordinarily, the presence of a nonconductive particle increases the impedance of the channel. Here we report a surprising experimental result in which a microfluidic resistive pulse sensor experiences the opposite effect: The presence of a nonconductive particle decreases the channel impedance. We explain the counterintuitive phenomenon by relating to the Braess paradox from traffic network theory, and we call it the complex-valued Braess paradox (CVBP). We develop theoretical models to study the CVBP and corroborate the experimental data using finite element simulations and lumped-element circuit modeling. We then discuss implications and potential applications of the CVBP in resistive pulse sensing and beyond.

Performance-enhanced clogging-free viscous sheath constriction impedance flow cytometry

As a label-free and high-throughput single cell analysis platform, impedance flow cytometry (IFC) suffers from clogging caused by a narrow microchannel as mechanical constriction (MC). Current sheath constriction (SC) solutions lack systematic evaluation of the performance and proper guidelines for the sheath fluid. Herein, we hypothesize that the viscosity of the non-conductive liquid is the key to the performance of SC, and propose to employ non-conductive viscous sheath flow in SC to unlock the tradeoff between sensitivity and throughput, while ensuring measurement accuracy. By placing MC and SC in series in the same microfluidic chip, we established an evaluation platform to prove the hypothesis. Through modeling analysis and experiments, we confirmed the accuracy (error < 1.60% ± 4.71%) of SC w.r.t. MC, and demonstrated that viscous non-conductive PEG solution achieved an improved sensitivity (7.92×) and signal-to-noise ratio (1.42×) in impedance measurement, with the accuracy maintained and free of clogging. Viscous SC IFC also shows satisfactory ability to distinguish different types of cancer cells and different subtypes of human breast cancer cells. It is envisioned that viscous SC IFC paves the way for IFC to be really usable in practice with clogging-free, accurate, and sensitive performance.

Quantitative comparison of EGFR expression levels of optically trapped individual cells using a capacitance biosensor

Cellular endocytosis is an essential phenomenon which induces cellular reactions, such as waste removal, nutrient absorption, and drug delivery, in the process of cell growth, division, and proliferation. To observe capacitance responses upon endocytosis on a single-cell scale, this study combined an optical tweezer that can optically place a single cell on a desired location with a capacitance sensor and a cell incubation chamber. Single HeLa cancer cell was captured and moved to a desired location through optical trapping, and the single-cell capacitance change generated during the epidermal growth factor (EGF) molecule endocytosis was measured in real time. It was found that single HeLa cells showed a larger increase in capacitance values compared to that of the single NIH3T3 cells when exposed to varying EGF concentrations. In addition, the capacitance change was in proportion to the cell's EGF receptor (EGFR) level when cells of different levels of EGFR expression were tested. An equation derived from these results was able to estimate the EGFR expression level of a blind-tested cell. The biosensor developed in this research can not only quickly move a single cell to a desired location in a non-invasive manner but also distinguish specific responses between cancer and normal cells by continuous measurement of real-time interactions of a single cell in culture to the external ligands.

Single-Cell Classification Based on Population Nucleus Size Combining Microwave Impedance Spectroscopy and Machine Learning

Many recent efforts in the diagnostic field address the accessibility of cancer diagnosis. Typical histological staining methods identify cancer cells visually by a larger nucleus with more condensed chromatin. Machine learning (ML) has been incorporated into image analysis for improving this process. Recently, impedance spectrometers have been shown to generate all-inclusive lab-on-a-chip platforms to detect nucleus abnormities. In this paper, a wideband electrical sensor and data analysis paradigm that can identify nuclear changes shows the realization of a single-cell microfluidic device to detect nuclei of altered sizes. To model cells of altered nucleus, Jurkat cells were treated to enlarge or shrink their nucleus followed by broadband sensing to obtain the S-parameters of single cells. The ability to deduce important frequencies associated with nucleus size is demonstrated and used to improve classification models in both binary and multiclass scenarios, despite a heterogeneous and overlapping cell population. The important frequency features match those predicted in a double-shell circuit model published in prior work, demonstrating a coherent new analytical technique for electrical data analysis. The electrical sensing platform assisted by ML with impressive accuracy of cell classification looks forward to a label-free and flexible approach to cancer diagnosis.

Classification between Normal and Cancerous Human Urothelial Cells by Using Micro-Dimensional Electrochemical Impedance Spectroscopy Combined with Machine Learning

Although the high incidence and recurrence rates of urothelial cancer of the bladder (UCB) are heavy burdens, a noninvasive tool for effectively detecting UCB as an alternative to voided urine cytology, which has low sensitivity, is yet to be reported. Herein, we propose an intelligent discrimination method between normal (SV-HUC-1) and cancerous (TCCSUP) urothelial cells by using a combination of micro-dimensional electrochemical impedance spectroscopy (µEIS) with machine learning (ML) for a noninvasive and high-accuracy UCB diagnostic tool. We developed a unique valved flow cytometry, equipped with a pneumatic valve to increase sensitivity without cell clogging. Since contact between a cell and electrodes is tight with a high volume fraction, the electric field can be effectively confined to the cell. This enables the proposed sensor to highly discriminate different cell types at frequencies of 10, 50, 100, 500 kHz, and 1 MHz. A total of 236 impedance spectra were applied to six ML models, and systematic comparisons of the ML models were carried out. The hyperparameters were estimated by conducting a grid search or Bayesian optimization. Among the ML models, random forest strongly discriminated between SV-HUC-1 and TCCSUP, with an accuracy of 91.7%, sensitivity of 92.9%, precision of 92.9%, specificity of 90%, and F1-score of 93.8%.

Biosensors and machine learning for enhanced detection, stratification, and classification of cells: a review

Biological cells, by definition, are the basic units which contain the fundamental molecules of life of which all living things are composed. Understanding how they function and differentiating cells from one another, therefore, is of paramount importance for disease diagnostics as well as therapeutics. Sensors focusing on the detection and stratification of cells have gained popularity as technological advancements have allowed for the miniaturization of various components inching us closer to Point-of-Care (POC) solutions with each passing day. Furthermore, Machine Learning has allowed for enhancement in the analytical capabilities of these various biosensing modalities, especially the challenging task of classification of cells into various categories using a data-driven approach rather than physics-driven. In this review, we provide an account of how Machine Learning has been applied explicitly to sensors that detect and classify cells. We also provide a comparison of how different sensing modalities and algorithms affect the classifier accuracy and the dataset size required.

Recent Advances in Microscale Electroporation

Electroporation (EP) is a commonly used strategy to increase cell permeability for intracellular cargo delivery or irreversible cell membrane disruption using electric fields. In recent years, EP performance has been improved by shrinking electrodes and device structures to the microscale. Integration with microfluidics has led to the design of devices performing static EP, where cells are fixed in a defined region, or continuous EP, where cells constantly pass through the device. Each device type performs superior to conventional, macroscale EP devices while providing additional advantages in precision manipulation (static EP) and increased throughput (continuous EP). Microscale EP is gentle on cells and has enabled more sensitive assaying of cells with novel applications. In this Review, we present the physical principles of microscale EP devices and examine design trends in recent years. In addition, we discuss the use of reversible and irreversible EP in the development of therapeutics and analysis of intracellular contents, among other noteworthy applications. This Review aims to inform and encourage scientists and engineers to expand the use of efficient and versatile microscale EP technologies.

A critique of the capacitor-based "Transmembrane Electrostatically Localized Proton" hypothesis

In his Transmembrane Electrostatically Localized Proton hypothesis (TELP), James W. Lee has modeled the bioenergetic membrane as a simple capacitor. According to this model, the surface concentration of protons is completely independent of proton concentration in the bulk phase, and is linearly proportional to the transmembrane potential. Such a proportionality runs counter to the results of experimental measurements, molecular dynamics simulations, and electrostatics calculations. We show that the TELP model dramatically overestimates the surface concentration of protons, and we discuss the electrostatic reasons why a simple capacitor is not an appropriate model for the bioenergetic membrane.

Mitochondrial energetics with transmembrane electrostatically localized protons: do we have a thermotrophic feature?

Transmembrane electrostatically localized protons (TELP) theory has been recently recognized as an important addition over the classic Mitchell's chemiosmosis; thus, the proton motive force (pmf) is largely contributed from TELP near the membrane. As an extension to this theory, a novel phenomenon of mitochondrial thermotrophic function is now characterized by biophysical analyses of pmf in relation to the TELP concentrations at the liquid-membrane interface. This leads to the conclusion that the oxidative phosphorylation also utilizes environmental heat energy associated with the thermal kinetic energy (kBT) of TELP in mitochondria. The local pmf is now calculated to be in a range from 300 to 340 mV while the classic pmf (which underestimates the total pmf) is in a range from 60 to 210 mV in relation to a range of membrane potentials from 50 to 200 mV. Depending on TELP concentrations in mitochondria, this thermotrophic function raises pmf significantly by a factor of 2.6 to sixfold over the classic pmf. Therefore, mitochondria are capable of effectively utilizing the environmental heat energy with TELP for the synthesis of ATP, i.e., it can lock heat energy into the chemical form of energy for cellular functions.

Energy Renewal: Isothermal Utilization of Environmental Heat Energy with Asymmetric Structures

Through the research presented herein, it is quite clear that there are two thermodynamically distinct types (A and B) of energetic processes naturally occurring on Earth. Type A, such as glycolysis and the tricarboxylic acid cycle, apparently follows the second law well; Type B, as exemplified by the thermotrophic function with transmembrane electrostatically localized protons presented here, does not necessarily have to be constrained by the second law, owing to its special asymmetric function. This study now, for the first time, numerically shows that transmembrane electrostatic proton localization (Type-B process) represents a negative entropy event with a local protonic entropy change (ΔSL) in a range from -95 to -110 J/K∙mol. This explains the relationship between both the local protonic entropy change (ΔSL) and the mitochondrial environmental temperature (T) and the local protonic Gibbs free energy (ΔGL=TΔSL) in isothermal environmental heat utilization. The energy efficiency for the utilization of total protonic Gibbs free energy (ΔGT including ΔGL=TΔSL) in driving the synthesis of ATP is estimated to be about 60%, indicating that a significant fraction of the environmental heat energy associated with the thermal motion kinetic energy (kBT) of transmembrane electrostatically localized protons is locked into the chemical form of energy in ATP molecules. Fundamentally, it is the combination of water as a protonic conductor, and thus the formation of protonic membrane capacitor, with asymmetric structures of mitochondrial membrane and cristae that makes this amazing thermotrophic feature possible. The discovery of energy Type-B processes has inspired an invention (WO 2019/136037 A1) for energy renewal through isothermal environmental heat energy utilization with an asymmetric electron-gated function to generate electricity, which has the potential to power electronic devices forever, including mobile phones and laptops. This invention, as an innovative Type-B mimic, may have many possible industrial applications and is likely to be transformative in energy science and technologies for sustainability on Earth.

How to Choose a Proper Theoretical Analysis Model Based on Cell Adhesion and Nonadhesion Impedance Measurement

The accurate equivalent circuit model contributes to the better fitting of required cell characteristics, such as cell impedance, cell adhesion area, and cell-electrode distance. However, so many theoretical models on specific modules make it difficult for new researchers to understand the whole model of electrode system physically. Besides, the accurate theoretical model and the simplified calculations obviously contradict each other; therefore, it is confusing for many researchers to choose the proper theoretical model to calculate the specific parameters required. In this review, we first discuss the problems and suggestions of electrode system design for cell adhesion-based measurement in terms of parasitic capacitance, detection range of cell number, electric field distribution, and interelectrode distance. The design of electrode system for cell nonadhesion measurement was analyzed in terms of microchannel size and electrode position. Then, we discuss the advantages and disadvantages of various equivalent circuit models according to different requirements of researchers, and simultaneously provide a corresponding theoretical model for researchers. Various factors influencing electric impedance spectroscopy (EIS) such as the parasitic capacitance between microelectrodes, the changes of cell adhesion area and cell-electrode distance, the electrode geometry, and the surface conductivity of electrode were quantitatively analyzed to contribute to better understanding of the equivalent models. Finally, we gave advice to optimize the theoretical models further and perspectives on building uniform principles of theoretical model optimization in the future.

Evaluating cell viability heterogeneity based on information fusion of multiple adhesion strengths

Cell viability evaluation is significantly meaningful for cellular assays. Some cells with weak viability are easily killed in the detection of anticancer drugs, while others with strong viability survive and proliferate, ultimately leading to the treatment failure or the inaccuracy of biological assays. Accurately evaluating cell viability heterogeneity still remains difficult. This article proposed a multiphysical property information fusion method for evaluating cell viability heterogeneity based on polynomial regression in a single-channel integrated microfluidic chip. In this method, adhesion strengths τ_N , that are defined as the magnitude of shear stress needed to detach (100 - N) % of cell population, were extracted as the independent variables of polynomial regression model by calculating the nonlinear fitting of the impedance-response curves for shear stress (cell detachment assay). Besides, by calculating the nonlinear fitting of the drug dose-response curves for cancer cells (IC₅₀ assay), the half-maximal inhibitory concentration (IC₅₀ ) was extracted as the dependent variables of polynomial regression model. The results show that the mean relative error of our fusion method averagely reduces by 6.04% and 62.79% compared with the multiple linear regression method and the cell counting method. Moreover, a simplified theoretical model used to describe the quantitative relationship between cell viability and its adhesion strengths was built to provide a theoretical basis for our fusion method.

Discrimination of cell-differentiation using a cell-binding assay based on the conversion of cell-patterns with dielectrophoresis

We developed a simple, rapid, and label-free method to obtain the ratio of cells with a specific surface protein from heterogeneous cell populations, and applied it to estimate the cell differentiation states. The repulsive force of negative dielectrophoresis was used to form the first pattern of HL60 cells on a substrate immobilized with anti-CD13 or anti-CD11b antibody. Next, the patterned cells were converted to form the second pattern by switching the pattern of the electric field. The cells exhibiting a specific protein remained in the original position due to the immunorecognition event, while the unwanted cells that were not bound to the antibody on the substrates could be simply removed. The cell-binding efficiencies of substrates modified with anti-CD13 and anti-CD11b decreased and increased, respectively, with increasing duration of cell culture in medium containing differentiation-inducing agents, including all-trans retinoic acid. This is explained by the downregulation of CD13 and upregulation of CD11b throughout the differentiation process of HL60 cells. Furthermore, the assay was applied to investigate the effects of various differentiation-inducing agents. The total assay time required for discriminating the proteins expressed on the cell surface in each differentiation state was as short as 120 s. No fluorescence label is required for the proposed assay. The method could be useful to estimate the cell differentiation and factors that influence the differentiation trajectory for numerous cell types.

Protonic conductor: better understanding neural resting and action potential

With the employment of the transmembrane electrostatic proton localization theory with a new membrane potential equation, neural resting and action potential is now much better understood as the voltage contributed by the localized protons/cations at a neural liquid- membrane interface. Accordingly, the neural resting/action potential is essentially a protonic/cationic membrane capacitor behavior. It is now understood with a newly formulated action potential equation: when action potential is <0 (negative number), the localized protons/cations charge density at the liquid-membrane interface along the periplasmic side is >0 (positive number); when the action potential is >0, the concentration of the localized protons and localized nonproton cations is <0, indicating a "depolarization" state. The nonlinear curve of the localized protons/cations charge density in the real-time domain of an action potential spike appears as an inverse mirror image to the action potential. The newly formulated action potential equation provides biophysical insights for neuron electrophysiology, which may represent a complementary development to the classic Goldman-Hodgkin-Katz equation. With the use of the action potential equation, the biological significance of axon myelination is now also elucidated as to provide protonic insulation and prevent any ions both inside and outside of the neuron from interfering with the action potential signal, so that the action potential can quickly propagate along the axon with minimal (e.g., 40 times less) energy requirement.NEW & NOTEWORTHY The newly formulated action potential equation provides biophysical insights for neuron electrophysiology, which may represent a complementary development to the classic Goldman-Hodgkin-Katz equation. The nonlinear curve of the localized protons/cations charge density in the real-time domain of an action potential spike appears as an inverse mirror image to the action potential. The biological significance of axon myelination is now elucidated as to provide protonic insulation and prevent any ions from interfering with action potential signal.

Isothermal Environmental Heat Energy Utilization by Transmembrane Electrostatically Localized Protons at the Liquid-Membrane Interface

This study employing the latest theory on transmembrane electrostatic proton localization has now, for the first time, consistently elucidated a decades-longstanding bioenergetic conundrum in alkalophilic bacteria and more importantly discovered an entirely new feature: isothermal environmental heat utilization by electrostatically localized protons at the liquid-membrane interface. It was surprisingly revealed that the protonic motive force (equivalent to Gibbs free energy) from the isothermal environmental heat energy utilization through the electrostatically localized protons is not constrained by the overall energetics of the redox-driven proton pump system because of the following: (a) the transmembrane electrostatically localized protons are not free to move away from the membrane surface as a protonic capacitor feature; (b) the proton pumps embedded in the cell membrane extend beyond the localized proton layer apparently as an asymmetric property of the biological membrane; and (c) the protonic inlet mouth of the ATP synthase that accepts protons is located within this layer as another natural property of the asymmetric biological membrane. This work has now, for the first time, shown a novel thermotrophic feature where biological systems can isothermally utilize environmental heat energy through transmembrane electrostatically localized protons to help drive ATP synthesis.

Protonic Capacitor: Elucidating the biological significance of mitochondrial cristae formation

For decades, it was not entirely clear why mitochondria develop cristae? The work employing the transmembrane-electrostatic proton localization theory reported here has now provided a clear answer to this fundamental question. Surprisingly, the transmembrane-electrostatically localized proton concentration at a curved mitochondrial crista tip can be significantly higher than that at the relatively flat membrane plane regions where the proton-pumping respiratory supercomplexes are situated. The biological significance for mitochondrial cristae has now, for the first time, been elucidated at a protonic bioenergetics level: 1) The formation of cristae creates more mitochondrial inner membrane surface area and thus more protonic capacitance for transmembrane-electrostatically localized proton energy storage; and 2) The geometric effect of a mitochondrial crista enhances the transmembrane-electrostatically localized proton density to the crista tip where the ATP synthase can readily utilize the localized proton density to drive ATP synthesis.

Electrostatically localized proton bioenergetics: better understanding membrane potential

In Mitchell's chemiosmotic theory, membrane potential Δ ψ was given as the electric potential difference across the membrane. However, its physical origin for membrane potential Δ ψ was not well explained. Using the Lee proton electrostatic localization model with a newly formulated equation for protonic motive force (pmf) that takes electrostatically localized protons into account, membrane potential has now been better understood as the voltage difference contributed by the localized surface charge density ( [ H L + ] + ∑ i = 1 n [ M L i + ] ) at the liquid-membrane interface as in an electrostatically localized protons/cations-membrane-anions capacitor. That is, the origin of membrane potential Δ ψ is now better understood as the electrostatic formation of the localized surface charge density that is the sum of the electrostatically localized proton concentration [ H L + ] and the localized non-proton cations density ∑ i = 1 n [ M L i + ] at the liquid membrane interface. The total localized surface charge density equals to the ideal localized proton population density [ H L + ] 0 before the cation-proton exchange process; since the cation-proton exchange process does not change the total localized charges density, neither does it change to the membrane potential Δ ψ . The localized proton concentration [ H L + ] represents the dominant component, which accounts about 78% of the total localized surface charge density at the cation-proton exchange equilibrium state in animal mitochondria. Liquid water as a protonic conductor may play a significant role in the biological activities of membrane potential formation and utilization.

Biophysical phenotyping of cells via impedance spectroscopy in parallel cyclic deformability channels

This paper describes a new microfluidic biosensor with capabilities of studying single cell biophysical properties. The chip contains four parallel sensing channels, where each channel includes two constriction regions separated by a relaxation region. All channels share a pair of electrodes to record the electrical impedance. Single cell impedance magnitudes and phases at different frequencies were obtained. The deformation and transition time information of cells passing through two sequential constriction regions were gained from the time points on impedance magnitude variations. Constriction channels separated by relaxation regions have been proven to improve the sensitivity of distinguishing single cells. The relaxation region between two sequential constriction channels provides extra time stamps that can be identified in the impedance plots. The new chip allows simultaneous measurement of the biophysical attributes of multiple cells in different channels, thereby increasing the overall throughput of the chip. Using the biomechanical parameters represented by the time stamps in the impedance results, breast cancer cells (MDA-MB-231) and the normal epithelial cells (MCF-10A) could be distinguished by 85%. The prediction accuracy at the single-cell level reached 97% when both biomechanical and bioelectrical parameters were utilized. While the new label-free assay has been tested to distinguish between normal and cancer cells, its application can be extended to include cell-drug interactions and circulating tumor cell detection in blood.

A biosensor capable of identifying low quantities of breast cancer cells by electrical impedance spectroscopy

Breast cancer (BC) is a malignant disease with a high prevalence worldwide. The main cause of death is not the primary tumor, but instead the spread of tumor cells to distant sites. The aim of the present study was to examine a new method for the detection of cancer cells in aqueous medium using bioimpedance spectroscopy assisted with magnetic nanoparticles (MNP's) exposure to a constant magnetic field. The spectroscopic patterns were identified for three breast cancer cell lines. Each BC cell line represents a different pathologic stage: the early stage (MCF-7), invasive phase (MDA-MB-231) and metastasis (SK-BR-3). For this purpose, bioimpedance measurements were carried out at a certain frequency range with the aid of nanoprobes, consisting of magnetic nanoparticles (MNPs) coupled to a monoclonal antibody. The antibody was specific for the predominant cell surface protein for each cell line, which was identified by using RT-qPCR and flow cytometry. Accordingly, EpCAM corresponds to MCF-7, MUC-1 to MDA-MB-231, and HER-2 to SK-BR-3. Despite their low concentrations, BC cells could be detected by impedance spectroscopy. Hence, this methodology should permit the monitoring of circulating tumor cells (CTC) and therefore help to prevent recurrences and metastatic processes during BC treatment.

Kernel-Based Microfluidic Constriction Assay for Tumor Sample Identification

A high-throughput multiconstriction microfluidic channels device can distinguish human breast cancer cell lines (MDA-MB-231, HCC-1806, MCF-7) from immortalized breast cells (MCF-10A) with a confidence level of ∼81-85% at a rate of 50-70 cells/min based on velocity increment differences through multiconstriction channels aligned in series. The results are likely related to the deformability differences between nonmalignant and malignant breast cells. The data were analyzed by the methods/algorithms of Ridge, nonnegative garrote on kernel machine (NGK), and Lasso using high-dimensional variables, including the cell sizes, velocities, and velocity increments. In kernel learning based methods, the prediction values of 10-fold cross-validations are used to represent the difference between two groups of data, where a value of 100% indicates the two groups are completely distinct and identifiable. The prediction value is used to represent the difference between two groups using the established algorithm classifier from high-dimensional variables. These methods were applied to heterogeneous cell populations prepared using primary tumor and adjacent normal tissue obtained from two patients. Primary breast cancer cells were distinguished from patient-matched adjacent normal cells with a prediction ratio of 70.07%-75.96% by the NGK method. Thus, this high-throughput multiconstriction microfluidic device together with the kernel learning method can be used to perturb and analyze the biomechanical status of cells obtained from small primary tumor biopsy samples. The resultant biomechanical velocity signatures identify malignancy and provide a new marker for evaluation in risk assessment.

3D cell electrorotation and imaging for measuring multiple cellular biophysical properties

3D rotation is one of many fundamental manipulations to cells and imperative in a wide range of applications in single cell analysis involving biology, chemistry, physics and medicine. In this article, we report a dielectrophoresis-based, on-chip manipulation method that can load and rotate a single cell for 3D cell imaging and multiple biophysical property measurements. To achieve this, we trapped a single cell in constriction and subsequently released it to a rotation chamber formed by four sidewall electrodes and one transparent bottom electrode. In the rotation chamber, rotating electric fields were generated by applying appropriate AC signals to the electrodes for driving the single cell to rotate in 3D under control. The rotation spectrum for in-plane rotation was used to extract the cellular dielectric properties based on a spherical single-shell model, and the stacked images of out-of-plane cell rotation were used to reconstruct the 3D cell morphology to determine its geometric parameters. We have tested the capabilities of our method by rotating four representative mammalian cells including HeLa, C3H10, B lymphocyte, and HepaRG. Using our device, we quantified the area-specific membrane capacitance and cytoplasm conductivity for the four cells, and revealed the subtle difference of geometric parameters (i.e., surface area, volume, and roughness) by 3D cell imaging of cancer cells and normal leukocytes. Combining microfluidics, dielectrophoresis, and microscopic imaging techniques, our electrorotation-on-chip (EOC) technique is a versatile method for manipulating single cells under investigation and measuring their multiple biophysical properties.

Label-Free On-Chip Selective Extraction of Cell-Aggregate-Laden Microcapsules from Oil into Aqueous Solution with Optical Sensor and Dielectrophoresis

Microfluidic encapsulation of cells or tissues in biocompatible solidlike hydrogels has wide biomedical applications. However, the microfluidically encapsulated cells/tissues are usually suspended in oil and need to be extracted into aqueous solution for further culture or use. Current extracting techniques are either nonselective for the cell/tissue-laden hydrogel microcapsules or rely on fluorescence labeling of the cells/tissues, which may be undesired for their further culture or use. Here we developed a microelectromechanical system (MEMS) to achieve label-free on-chip selective extraction of cell-aggregate-laden hydrogel microcapsules from oil into aqueous solution. The system includes a microfluidic device, an optical sensor, a dielectrophoretic (DEP) actuator, and microcontrollers. The microfluidic device is for encapsulating cell aggregates in hydrogel microcapsules using the flow-focusing function with microchannels for extracting microcapsules. The optical sensor is to detect the cell aggregates, based on the difference of the optical properties between the cell aggregates and surrounding solution before their encapsulation in hydrogel microcapsules. This strategy is used because the difference in optical property between the cell-aggregate-laden hydrogel microcapsules and empty microcapsules is too small to tell them apart with a commonly used optical sensor. The DEP actuator, which is controlled by the sensor and microcontrollers, is for selectively extracting the targeted hydrogel microcapsules by DEP force. The results indicate this system can achieve selective extraction of cell-aggregate-laden hydrogel microcapsules with ∼100% efficiency without compromising the cell viability, and can improve the purity of the cell-aggregate-laden microcapsules by more than 75 times compared with nonselective extraction.

Recent advances in the use of microfluidic technologies for single cell analysis

The inherent heterogeneity in cell populations has become of great interest and importance as analytical techniques have improved over the past decades. With the advent of personalized medicine, understanding the impact of this heterogeneity has become an important challenge for the research community. Many different microfluidic approaches with varying levels of throughput and resolution exist to study single cell activity. In this review, we take a broad view of the recent microfluidic developments in single cell analysis based on microwell, microchamber, and droplet platforms. We cover physical, chemical, and molecular biology approaches for cellular and molecular analysis including newly emerging genome-wide analysis.

A Novel On-Chip Impedance Sensor for the Detection of Particle Contamination in Hydraulic Oil

A novel impedance sensor based on a microfluidic chip is presented. The sensor consists of two single-layer coils and a straight micro-channel, and can detect, not only ferromagnetic and non-ferromagnetic particles in oil as an inductive sensor, but also, water droplets and air bubbles in oil as a capacitive sensor. The experiments are carried out at different excitation frequencies, number of coil turns and particle sizes. For the inductance detection, the inductance signals are found to increase with the excitation frequency and the noise is constant; both the inductance signals and the noise increase with the number of coil turns, but because the noise increases at a faster rate than the signal, the signal-to-noise ratio decreases with the number of coil turns. We demonstrate the successful detection of 40 μm iron particles and 110 μm copper particles using the coil with 20 turns at the excitation frequency of 2 MHz. For the capacitance detection, capacitance signals decrease with the excitation frequency and the noise is constant; the capacitance signals decrease with the number of coil turns, while the noise increases, thus, the signal-to-noise ratio decreases with the number of coil turns. We can detect 100 μm water droplets and 180 μm bubbles successfully using the coil with 20 turns at the excitation frequency of 0.3 MHz.

Ex vivo characterization of age-associated impedance changes of single vascular endothelial cells using micro electrical impedance spectroscopy with a cell trap

We aimed to characterize aging of single vascular endothelial cells, which are indicators of senescence, using micro electrical impedance spectroscopy (μEIS) for the first time. The proposed μEIS was equipped with two barriers under the membrane actuator near the sensing electrodes, increasing its cell-trapping capability and minimizing the interference between the target cell and subsequent cells. The cell-trapping capability in μEIS with barriers was considerably improved (90%) with a capture time of 5 s or less, compared to μEIS without barriers (30%). Cells were extracted from transgenic zebrafish to minimize an initial discrepancy originating from genetic differences. In order to estimate useful parameters, cytoplasm resistance and membrane capacitance were estimated by fitting an electrical equivalent circuit to the data of ex vivo sensor output. The estimated cytoplasm resistance and membrane capacitance in the younger vascular endothelial cells were 20.16 ± 0.79 kΩ and 17.46 ± 0.76 pF, respectively, whereas those in the older cells were 17.81 ± 0.98 kΩ and 20.08 ± 1.38 pF, respectively. Discrimination of each group with different aging showed statistical significance in terms of cytoplasm resistance (p < 0.001) and membrane capacitance (p < 0.001). Considering both of the sensor and cellular level, the optimal frequency was determined as 1 MHz at which the electrical impedance of each group was clearly discriminated (p < 0.001).

Single Cell Electrical Characterization Techniques

Electrical properties of living cells have been proven to play significant roles in understanding of various biological activities including disease progression both at the cellular and molecular levels. Since two decades ago, many researchers have developed tools to analyze the cell’s electrical states especially in single cell analysis (SCA). In depth analysis and more fully described activities of cell differentiation and cancer can only be accomplished with single cell analysis. This growing interest was supported by the emergence of various microfluidic techniques to fulfill high precisions screening, reduced equipment cost and low analysis time for characterization of the single cell’s electrical properties, as compared to classical bulky technique. This paper presents a historical review of single cell electrical properties analysis development from classical techniques to recent advances in microfluidic techniques. Technical details of the different microfluidic techniques are highlighted, and the advantages and limitations of various microfluidic devices are discussed.

Making a big thing of a small cell--recent advances in single cell analysis

Single cell analysis is an emerging field requiring a high level interdisciplinary collaboration to provide detailed insights into the complex organisation, function and heterogeneity of life. This review is addressed to life science researchers as well as researchers developing novel technologies. It covers all aspects of the characterisation of single cells (with a special focus on mammalian cells) from morphology to genetics and different omics-techniques to physiological, mechanical and electrical methods. In recent years, tremendous advances have been achieved in all fields of single cell analysis: (1) improved spatial and temporal resolution of imaging techniques to enable the tracking of single molecule dynamics within single cells; (2) increased throughput to reveal unexpected heterogeneity between different individual cells raising the question what characterizes a cell type and what is just natural biological variation; and (3) emerging multimodal approaches trying to bring together information from complementary techniques paving the way for a deeper understanding of the complexity of biological processes. This review also covers the first successful translations of single cell analysis methods to diagnostic applications in the field of tumour research (especially circulating tumour cells), regenerative medicine, drug discovery and immunology.

On-chip sample preparation for complete blood count from raw blood

This paper describes a monolithic microfluidic device capable of on-chip sample preparation for both RBC and WBC measurements from whole blood. For the first time, on-chip sample processing (e.g. dilution, lysis, and filtration) and downstream single cell measurement were fully integrated to enable sample preparation and single cell analysis from whole blood on a single device. The device consists of two parallel sub-systems that perform sample processing and electrical measurements for measuring RBC and WBC parameters. The system provides a modular environment capable of handling solutions of various viscosities by adjusting the length of channels and precisely controlling mixing ratios, and features a new 'offset' filter configuration for increased duration of device operation. RBC concentration, mean corpuscular volume (MCV), cell distribution width, WBC concentration and differential are determined by electrical impedance measurement. Experimental characterization of over 100,000 cells from 10 patient blood samples validated the system's capability for performing on-chip raw blood processing and measurement.

Decreased deformability of lymphocytes in chronic lymphocytic leukemia

This paper reports the first study of stiffness/deformability changes of lymphocytes in chronic lymphocytic leukemia (CLL) patients, demonstrating that at the single cell level, leukemic metastasis progresses are accompanied by biophysical property alterations. A microfluidic device was utilized to electrically measure cell volume and transit time of single lymphocytes from healthy and CLL patients. The results from testing thousands of cells reveal that lymphocytes from CLL patients have higher stiffness (i.e., lower deformability), as compared to lymphocytes in healthy samples, which was also confirmed by AFM indentation tests. This observation is in sharp contrast to the known knowledge on other types of metastatic cells (e.g., breast and lung cancer cells) whose stiffness becomes lower as metastasis progresses.

Microfluidic contactless conductivity cytometer for electrical cell sensing and counting

An integrated and cost-effective microfluidic contactless conductivity cytometer for cell sensing and counting.

Characterization of red blood cell deformability change during blood storage

Stored red blood cells (RBCs) show progressive deformability changes during blood banking/storage. Their deformability changes over an 8 weeks' storage period were measured using a microfluidic device. Hydrodynamic focusing controls the orientation and position of individual RBCs within the microchannel. High-speed imaging (5000 frames s(-1)) captures the dynamic deformation behavior of the cells, and together with automated image analysis, enables the characterization of over 1000 RBCs within 3 minutes. Multiple parameters including deformation index (DI), time constant (shape recovery rate), and RBC circularity were quantified. Compared to previous studies on stored RBC deformability, our results include a significantly higher number of cells (>1000 cells per sample vs. a few to tens of cells per sample) and, for the first time, reveal deformation changes of stored RBCs when traveling through human-capillary-like microchannels. Contrary to existing knowledge, our results demonstrate that the deformation index of RBCs under folding does not change significantly over blood storage. However, significant differences exist in time constants and circularity distribution widths, which can be used to quantify stored RBC quality or age.

Electrical measurement of red blood cell deformability on a microfluidic device

This paper describes a microfluidic system and a technique for electrically measuring the deformability of red blood cells (RBCs). RBCs are deformed when they flow through a small capillary (microfluidic channel). The microfluidic device consists of two stages of microchannels as two measurement units for measuring cell size/volume and cell deformability. A low frequency voltage signal is established across the microfluidic channel, and electrical current signal is sampled continuously when RBCs pass through the measurement areas. Mechanical opacity is defined to mitigate the coupled effect of cell size/volume and deformability. The system performed tests on controlled, glutaraldehyde-treated, and heated RBCs using a number of driving pressures. The experimental results proved the capability of the system for distinguishing different RBC populations based on their deformability with a throughput of ~10 cells s(-1).

Recent advances in microfluidic techniques for single-cell biophysical characterization

Biophysical (mechanical and electrical) properties of living cells have been proven to play important roles in the regulation of various biological activities at the molecular and cellular level, and can serve as promising label-free markers of cells' physiological states. In the past two decades, a number of research tools have been developed for understanding the association between the biophysical property changes of biological cells and human diseases; however, technical challenges of realizing high-throughput, robust and easy-to-perform measurements on single-cell biophysical properties have yet to be solved. In this paper, we review emerging tools enabled by microfluidic technologies for single-cell biophysical characterization. Different techniques are compared. The technical details, advantages, and limitations of various microfluidic devices are discussed.

A microfluidic impedance flow cytometer for identification of differentiation state of stem cells

This paper presents a microfluidic electrical impedance flow cytometer (FC) for identifying the differentiation state of single stem cells. This device is comprised of a novel dual micropore design, which not only enhances the processing throughput, but also allows the associated electrodes to be used as a reference for one another. A signal processing algorithm, based on the support vector machine (SVM) theory, and a data classification method were developed to automate the identification of sample types and cell differentiation state based on measured impedance values. The device itself was fabricated using a combination of standard and soft lithography techniques to generate a PDMS-gold electrode construct. Experimental testing with non-biological particles and mouse embryonic carcinoma cells (P19, undifferentiated and differentiated) was carried out using a range of excitation frequencies. The effects of the frequency and the interrogation parameters on sample identification performance were investigated. It was found that the real and imaginary part of the detected impedance signal were adequate for distinguishing the undifferentiated P19 cells from non-biological polystyrene beads at all tested frequencies. A higher frequency and an opacity index were required to resolve the undifferentiated and differentiated P19 cells by capturing capacitive changes in electrophysiological properties arising from differentiation. The experimental results demonstrated salient accuracy of the device and algorithm, and established its feasibility for non-invasive, label-free identification of the differentiation state of the stem cells.