Leukocyte analysis and differentiation using high speed microfluidic single cell impedance cytometry

Leukocyte differential based on an imaging and impedance flow cytometry of microfluidics coupled with deep neural networks

The differential of leukocytes functions as the first indicator in clinical examinations. However, microscopic examinations suffered from key limitations of low throughputs in classifying leukocytes while commercially available hematology analyzers failed to provide quantitative accuracies in leukocyte differentials. A home-developed imaging and impedance flow cytometry of microfluidics was used to capture fluorescent images and impedance variations of single cells traveling through constrictional microchannels. Convolutional and recurrent neural networks were adopted for data processing and feature extractions, which were then fused by a support vector machine to realize the four-part differential of leukocytes. The classification accuracies of the four-part leukocyte differential were quantified as 95.4% based on fluorescent images plus the convolutional neural network, 90.3% based on impedance variations plus the recurrent neural network, and 99.3% on the basis of fluorescent images, impedance variations, and deep neural networks. Based on single-cell fluorescent imaging and impedance variations coupled with deep neural networks, the four-part leukocyte differential can be realized with almost 100% accuracy.

Microwave Flow Cytometric Detection and Differentiation of Escherichia coli

Label-free measurement and analysis of single bacterial cells are essential for food safety monitoring and microbial disease diagnosis. We report a microwave flow cytometric sensor with a microstrip sensing device with reduced channel height for bacterial cell measurement. Escherichia coli B and Escherichia coli K-12 were measured with the sensor at frequencies between 500 MHz and 8 GHz. The results show microwave properties of E. coli cells are frequency-dependent. A LightGBM model was developed to classify cell types at a high accuracy of 0.96 at 1 GHz. Thus, the sensor provides a promising label-free method to rapidly detect and differentiate bacterial cells. Nevertheless, the method needs to be further developed by comprehensively measuring different types of cells and demonstrating accurate cell classification with improved machine-learning techniques.

Highly Sensitive and Linear Resonator-Based Biosensor for White Blood Cell Counting: Feasible Measurement Method and Intrinsic Mechanism Exploration

Since different quantities of white blood cells (WBCs) in solution possess an adaptive osmotic pressure of cells, the WBCs themselves and in solution have similar concentrations, resulting in them having similar dielectric properties. Therefore, a microwave sensor could have difficulty in sensing the quantity variation when WBCs are in solution. This paper presents a highly sensitive, linear permittivity-inspired microwave biosensor for WBCs, counting through the evaporation method. Such a measurement method is proposed to record measurements after the cell solution is dripped onto the chip and is completely evaporated naturally. The proposed biosensor consists of an air-bridged asymmetric differential inductor and a centrally located circular fork-finger capacitor fabricated on a GaAs substrate using integrated passive fabrication technology. It is optimized to feature a larger sensitive area and improved Q-factor, which increases the effective area of interaction between cells and the electromagnetic field and facilitates the detection of their changes in number. The sensing relies on the dielectric properties of the cells and the change in the dielectric constant for different concentrations, and the change in resonance properties, which mainly represents the frequency shift, corresponds to the macroscopic change in the concentration of the cells. The microwave biosensors are used to measure biological samples with concentrations ranging from 0.25 × 106 to 8 × 106 cells per mL in a temperature (26.00 ± 0.40 °C) and humidity (54.40 ± 3.90 RH%) environment. The measurement results show a high sensitivity of 25.06 Hz/cells·mL-1 with a highly linear response of r2 = 0.99748. In addition, a mathematical modeling of individual cells in suspension is performed to estimate the dielectric constant of individual cells and further explain the working mechanism of the proposed microwave biosensor.

An impedance flow cytometry with integrated dual microneedle for electrical properties characterization of single cell

Electrical characteristics of living cells have been proven to reveal important details about their internal structure, charge distribution and composition changes in the cell membrane, as well as the extracellular context. An impedance flow cytometry is a common approach to determine the electrical properties of a cell, having the advantage of label-free and high throughput. However, the current techniques are complex and costly for the fabrication process. For that reason, we introduce an integrated dual microneedle-microchannel for single-cell detection and electrical properties extraction. The dual microneedles utilized a commercially available tungsten needle coated with parylene. When a single cell flows through the parallel-facing electrode configuration of the dual microneedle, the electrical impedance at multiple frequencies is measured. The impedance measurement demonstrated the differential of normal red blood cells (RBCs) with three different sizes of microbeads at low and high frequencies, 100 kHz and 2 MHz, respectively. An electrical equivalent circuit model (ECM) was used to determine the unique membrane capacitance of individual cells. The proposed technique demonstrated that the specific membrane capacitance of an RBC is 9.42 mF/m-2, with the regression coefficients, ρ at 0.9895. As a result, this device may potentially be used in developing countries for low-cost single-cell screening and detection.

A review on intelligent impedance cytometry systems: Development, applications and advances

Impedance cytometry is a well-established technique for counting and analyzing single cells, with several advantages, such as convenience, high throughput, and no labeling required. A typical experiment consists of the following steps: single-cell measurement, signal processing, data calibration, and particle subtype identification. At the beginning of this article, we compared commercial and self-developed options extensively and provided references for developing reliable detection systems, which are necessary for cell measurement. Then, a number of typical impedance metrics and their relationships to biophysical properties of cells were analyzed with respect to the impedance signal analysis. Given the rapid advances of intelligent impedance cytometry in the past decade, this article also discussed the development of representative machine learning-based approaches and systems, and their applications in data calibration and particle identification. Finally, the remaining challenges facing the field were summarized, and potential future directions for each step of impedance detection were discussed.

RespectM revealed metabolic heterogeneity powers deep learning for reshaping the DBTL cycle

Synthetic biology, relying on Design-Build-Test-Learn (DBTL) cycle, aims to solve medicine, manufacturing, and agriculture problems. However, the DBTL cycle's Learn (L) step lacks predictive power for the behavior of biological systems, resulting from the incompatibility between sparse testing data and chaotic metabolic networks. Herein, we develop a method, "RespectM," based on mass spectrometry imaging, which is able to detect metabolites at a rate of 500 cells per hour with high efficiency. In this study, 4,321 single cell level metabolomics data were acquired, representing metabolic heterogeneity. An optimizable deep neural network was applied to learn from metabolic heterogeneity and a "heterogeneity-powered learning (HPL)" based model was trained as well. By testing the HPL based model, we suggest minimal operations to achieve high triglyceride production for engineering. The HPL strategy could revolutionize rational design and reshape the DBTL cycle.

Development of a Novel Design of Microfluidic Impedance Cytometry for Improved Sensitivity and Cell Identification

A long-standing issue for microfluidic impedance cytometry devices is the accuracy in determining the size of cells during counting and measurements. In this paper, we introduce a novel design that produces a homogeneous electric field in the sensing region and demonstrates higher accuracy than traditional designs in cell counting and sizing, reducing the reliance on cell focusing and signal postprocessing. The concept is validated, and the increased accuracy of the device over traditional designs is demonstrated through the use of finite element simulations to generate suitable data sets for particle trajectories and model expected signal variations.

Concepts, electrode configuration, characterization, and data analytics of electric and electrochemical microfluidic platforms: a review

Microfluidic cytometry (MC) and electrical impedance spectroscopy (EIS) are two important techniques in biomedical engineering. Microfluidic cytometry has been utilized in various fields such as stem cell differentiation and cancer metastasis studies, and provides a simple, label-free, real-time method for characterizing and monitoring cellular fates. The impedance microdevice, including impedance flow cytometry (IFC) and electrical impedance spectroscopy (EIS), is integrated into MC systems. IFC measures the impedance of individual cells as they flow through a microfluidic device, while EIS measures impedance changes during binding events on electrode regions. There have been significant efforts to improve and optimize these devices for both basic research and clinical applications, based on the concepts, electrode configurations, and cell fates. This review outlines the theoretical concepts, electrode engineering, and data analytics of these devices, and highlights future directions for development.

Moving perfusion culture and live-cell imaging from lab to disc: proof of concept toxicity assay with AI-based image analysis

In vitro, cell-based assays are essential in diagnostics and drug development. There are ongoing efforts to establish new technologies that enable real-time detection of cell-drug interaction during culture under flow conditions. Our compact (10 × 10 × 8.5 cm) cell culture and microscope on disc (CMoD) platform aims to decrease the application barriers of existing lab-on-a-chip (LoC) approaches. For the first time in a centrifugal device, (i) cells were cultured for up to six days while a spindle motor facilitated culture medium perfusion, and (ii) an onboard microscope enabled live bright-field imaging of cells while the data wirelessly transmitted to a computer. The quantification of cells from the acquired images was done using artificial intelligence (AI) software. After optimization, the obtained cell viability data from the AI-based image analysis proved to correlate well with data collected from commonly used image analysis software. The CMoD was also suitable for conducting a proof-of-concept toxicity assay with HeLa cells under continuous flow. The half-maximal inhibitory time (IT50) for various concentrations of doxorubicin (DOX) in the case of HeLa cells in flow, was shown to be lower than the IT50 obtained from a static cytotoxicity assay, indicating a faster onset of cell death in flow. The CMoD proved to be easy to handle, enabled cell culture and monitoring without assistance, and is a promising tool for examining the dynamic processes of cells in real-time assays.

Label-free microfluidic cell sorting and detection for rapid blood analysis

Blood tests are considered as standard clinical procedures to screen for markers of diseases and health conditions. However, the complex cellular background (>99.9% RBCs) and biomolecular composition often pose significant technical challenges for accurate blood analysis. An emerging approach for point-of-care blood diagnostics is utilizing "label-free" microfluidic technologies that rely on intrinsic cell properties for blood fractionation and disease detection without any antibody binding. A growing body of clinical evidence has also reported that cellular dysfunction and their biophysical phenotypes are complementary to standard hematoanalyzer analysis (complete blood count) and can provide a more comprehensive health profiling. In this review, we will summarize recent advances in microfluidic label-free separation of different blood cell components including circulating tumor cells, leukocytes, platelets and nanoscale extracellular vesicles. Label-free single cell analysis of intrinsic cell morphology, spectrochemical properties, dielectric parameters and biophysical characteristics as novel blood-based biomarkers will also be presented. Next, we will highlight research efforts that combine label-free microfluidics with machine learning approaches to enhance detection sensitivity and specificity in clinical studies, as well as innovative microfluidic solutions which are capable of fully integrated and label-free blood cell sorting and analysis. Lastly, we will envisage the current challenges and future outlook of label-free microfluidics platforms for high throughput multi-dimensional blood cell analysis to identify non-traditional circulating biomarkers for clinical diagnostics.

A Review on Microfluidics-Based Impedance Biosensors

Electrical impedance biosensors are powerful and continuously being developed for various biological sensing applications. In this line, the sensitivity of impedance biosensors embedded with microfluidic technologies, such as sheath flow focusing, dielectrophoretic focusing, and interdigitated electrode arrays, can still be greatly improved. In particular, reagent consumption reduction and analysis time-shortening features can highly increase the analytical capabilities of such biosensors. Moreover, the reliability and efficiency of analyses are benefited by microfluidics-enabled automation. Through the use of mature microfluidic technology, complicated biological processes can be shrunk and integrated into a single microfluidic system (e.g., lab-on-a-chip or micro-total analysis systems). By incorporating electrical impedance biosensors, hand-held and bench-top microfluidic systems can be easily developed and operated by personnel without professional training. Furthermore, the impedance spectrum provides broad information regarding cell size, membrane capacitance, cytoplasmic conductivity, and cytoplasmic permittivity without the need for fluorescent labeling, magnetic modifications, or other cellular treatments. In this review article, a comprehensive summary of microfluidics-based impedance biosensors is presented. The structure of this article is based on the different substrate material categorizations. Moreover, the development trend of microfluidics-based impedance biosensors is discussed, along with difficulties and challenges that may be encountered in the future.

High-Efficiency Single-Cell Electrical Impedance Spectroscopy

Single-cell impedance measurement is label free and noninvasive in characterizing the electrical properties of single cells. At present, though widely used for impedance measurement, electrical impedance flow cytometry (IFC) and electrical impedance spectroscopy (EIS) are used alone for most microfluidic chips. Here, we describe high-efficiency single-cell electrical impedance spectroscopy, which combines in one chip the IFC and EIS techniques for high-efficiency single-cell electrical property measurement. We envision that the strategy of combining IFC and EIS provides a new thought in the efforts to enhance the efficiency of electrical property measurement for single cells.

Erythrocyte lysis and angle-resolved light scattering measured by scanning flow cytometry result to 48 indices quantifying a gas exchange function of the human organism

Molecular/cell level of gas exchange function assumes the accurate measurement of erythrocyte characteristics and rate constants concerning to molecules involved into the CO₂ /O₂ transport. Unfortunately, common hematology analyzers provide the measurement of eight indices of erythrocytes only and say little about erythrocyte morphology and nothing about rate constants of cellular function. The aim of this study is to demonstrate the ability of the Scanning Flow Cytometer (SFC) in the complete morphological analysis of mature erythrocytes and characterization of erythrocyte function via measurement of lysing kinetics. With this study we are introducing 48 erythrocyte indices. To provide the usability of application of the SFC in clinical diagnosis, we formed four categories of indices which are as follows: content/concentration (9 indices), morphology (26 indices), age (5 indices), and function (8 indices). The erythrocytes of 39 healthy volunteers were analyzed with the SFC to fix the first-ever reference intervals for the new indices introduced. The essential measurable reliability of the presented method is expressed in terms of errors of characteristics of single erythrocytes retrieved from the solution of the inverse light-scattering problem and errors of parameters retrieved from the fitting of the experimental kinetics by molecular-kinetics model of erythrocyte lysis.

Toward five-part differential of leukocytes based on electrical impedances of single cells and neural network

The five-part differential of leukocytes plays key roles in the diagnosis of a variety of diseases and is realized by optical examinations of single cells, which is prone to various artifacts due to chemical treatments. The classification of leukocytes based on electrical impedances without cell treatments has not been demonstrated because of limitations in approaches of impedance acquisition and data processing. In this study, based on treatment-free single-cell impedance profiles collected from impedance flow cytometry leveraging constriction microchannels, two types of neural pattern recognition were conducted for comparisons with the purpose of realizing the five-part differential of leukocytes. In the first approach, 30 features from impedance profiles were defined manually and extracted automatically, and then a feedforward neural network was conducted, producing a classification accuracy of 84.9% in the five-part leukocyte differential. In the second approach, a customized recurrent neural network was developed to process impedance profiles directly and based on deep learning, a classification accuracy of 97.5% in the five-part leukocyte differential was reported. These results validated the feasibility of the five-part leukocyte differential based on label-free impedance profiles of single cells and thus provide a new perspective of differentiating white blood cells based on impedance flow cytometry.

A label-free and low-power microelectronic impedance spectroscopy for characterization of exosomes

Electrical Impedance Spectroscopy (EIS) is a non-invasive and label-free technology that can characterize and discriminate cells based on their dielectric properties at a wide range of frequency. This characterization method has not been utilized for small extracellular vesicles (exosomes) with heterogenous and nano-scale size distribution. Here, we developed a novel label-free microelectronic impedance spectroscopy for non-invasive and rapid characterization of exosomes based on their unique dielectric properties. The device is comprised of an insulator-based dielectrophoretic (iDEP) module for exosomes isolation followed by an impedance spectroscopy utilizing the embedded micro-electrodes. This device is capable of distinguishing between exosomes harvested from different cellular origins as the result of their unique membrane and cytosolic compositions at a wide range of frequency. Therefore, it has the potential to be further evolved as a rapid tool for characterization of pathogenic exosomes in clinical settings.

Rapid Screen for Antiviral T-Cell Immunity with Nanowire Electrochemical Biosensors

The ability to rapidly assess and monitor patient immune responses is critical for clinical diagnostics, vaccine design, and fundamental investigations into the presence or generation of protective immunity against infectious diseases. Recently, findings on the limits of antibody-based protection provided by B-cells have highlighted the importance of engaging pathogen-specific T-cells for long-lasting and broad protection against viruses and their emergent variants such as in SARS-CoV-2. However, low-cost and point-of-care tools for detecting engagement of T-cell immunity in patients are conspicuously lacking in ongoing efforts to assess and control population-wide disease risk. Currently available tools for human T-cell analysis are time and resource-intensive. Using multichannel silicon-nanowire field-effect transistors compatible with complementary metal-oxide-semiconductor, a device designed for rapid and label-free detection of human T-cell immune responses is developed. The generalizability of this approach is demonstrated by measuring T-cell responses against melanoma antigen MART1, common and seasonal viruses CMV, EBV, flu, as well as emergent pandemic coronavirus, SARS-CoV-2. Further, this device provides a modular and translational platform for optimizing vaccine formulations and combinations, offering quick and quantitative readouts for acquisition and persistence of T-cell immunity against variant-driven pathogens such as flu and pandemic SARS-CoV-2.

Label-free enrichment of MCF7 breast cancer cells from leukocytes using continuous flow dielectrophoresis

Circulating tumor cells (CTCs) present in the bloodstream are strongly linked to the invasive behavior of cancer; therefore, their detection holds great significance for monitoring disease progression. Currently available CTC isolation tools are often based on tumor-specific antigen or cell size approaches. However, these techniques are limited due to the lack of a unique and universal marker for CTCs, and the overlapping size between CTCs and regular blood cells. Dielectrophoresis (DEP), governed by the intrinsic dielectric properties of the particles, is a promising marker-free, accurate, fast, and low-cost technique that enables the isolation of CTCs from blood cells. This study presents a continuous flow, antibody-free DEP-based microfluidic device to concentrate MCF7 breast cancer cells, a well-established CTC model, in the presence of leukocytes extracted from human blood samples. The enrichment strategy was determined according to the DEP responses of the corresponding cells, obtained in our previously reported DEP spectrum study. It was based on the positive-DEP integrated with hydrodynamic focusing under continuous flow. In the proposed device, the parylene microchannel with two inlets and outlets was built on top of rectangular and equally spaced isolated planar electrodes rotated certain degree relative to the main flow (13°). The recovery of MCF7 cells mixed with leukocytes was 74%-98% at a frequency of 1 MHz and a magnitude of 10-12 V_pp . Overall, the results revealed that the presented system successfully concentrates MCF7 cancer cells from leukocytes, ultimately verifying our DEP spectrum study, in which the enrichment frequency and separation strategy of the microfluidic system were determined.

Developments of Conventional and Microfluidic Flow Cytometry Enabling High-Throughput Characterization of Single Cells

This article first reviews scientific meanings of single-cell analysis by highlighting two key scientific problems: landscape reconstruction of cellular identities during dynamic immune processes and mechanisms of tumor origin and evolution. Secondly, the article reviews clinical demands of single-cell analysis, which are complete blood counting enabled by optoelectronic flow cytometry and diagnosis of hematologic malignancies enabled by multicolor fluorescent flow cytometry. Then, this article focuses on the developments of optoelectronic flow cytometry for the complete blood counting by comparing conventional counterparts of hematology analyzers (e.g., DxH 900 of Beckman Coulter, XN-1000 of Sysmex, ADVIA 2120i of Siemens, and CELL-DYN Ruby of Abbott) and microfluidic counterparts (e.g., microfluidic impedance and imaging flow cytometry). Future directions of optoelectronic flow cytometry are indicated where intrinsic rather than dependent biophysical parameters of blood cells must be measured, and they can replace blood smears as the gold standard of blood analysis in the near future.

Immunomagnetic leukocyte differential in whole blood on an electronic microdevice

Leukocytes are the frontline defense mechanism of the immune system. Their composition dynamically changes as a response to a foreign body, infection, inflammation, or other malignant behavior occurring within the body. Monitoring the composition of leukocytes, namely leukocyte differential, is a crucial assay periodically performed to diagnose an infection or to assess a person's vulnerability for a health anomaly. Currently, leukocyte differential analysis is performed using hematology analyzers or flow cytometers, both of which are bulky instruments that require trained and certified personnel for operation. In this work, we demonstrate a new technique to obtain leukocyte differentials in a highly portable and integrated microfluidic chip by magnetically analyzing the CD33 expression of leukocytes. When benchmarked against conventional laboratory instruments, our technology demonstrated <5% difference on average for all subtypes. Our results show that hematology testing could be performed beyond the centralized laboratories at a low cost and ultimately provide point-of-care and at-home testing opportunities.

Blood cell quantification on dry blood samples: toward patient-centric complete blood counts

Background: Performing complete blood counts from patients' homes could have a transformative impact on e-based healthcare. Blood microsampling and sample drying are enabling elements for patient-centric healthcare. The aim of this study was to investigate the potential of dry blood samples for image-based cell quantification of red and white blood cells. Methods: A manual sample preparation method was developed and tested for image-based red and white blood cell counting. Results & conclusion: Dry blood samples enable image-based cell counting of red and white blood cells with a good correlation to gold standard hematology analyzer data (average coefficient of variation <6.5%; R² >0.8) and resolve the basic morphology of white blood cell nuclei. The presented proof-of-principle study is a first step toward patient-centric complete blood counts.

A Label-Free Electrical Impedance Spectroscopy for Detection of Clusters of Extracellular Vesicles Based on Their Unique Dielectric Properties

Extracellular vesicles (EVs) have gained considerable attention as vital circulating biomarkers since their structure and composition resemble the originating cells. The investigation of EVs' biochemical and biophysical properties is of great importance to map them to their parental cells and to better understand their functionalities. In this study, a novel frequency-dependent impedance measurement system has been developed to characterize EVs based on their unique dielectric properties. The system is composed of an insulator-based dielectrophoretic (iDEP) device to entrap and immobilize a cluster of vesicles followed by utilizing electrical impedance spectroscopy (EIS) to measure their impedance at a wide frequency spectrum, aiming to analyze both their membrane and cytosolic charge-dependent contents. The EIS was initially utilized to detect nano-size vesicles with different biochemical compositions, including liposomes synthesized with different lipid compositions, as well as EVs and lipoproteins with similar biophysical properties but dissimilar biochemical properties. Moreover, EVs derived from the same parental cells but treated with different culture conditions were characterized to investigate the correlation of impedance changes with biochemical properties and functionality in terms of pro-inflammatory responses. The system also showed the ability to discriminate between EVs derived from different cellular origins as well as among size-sorted EVs harbored from the same cellular origin. This proof-of-concept approach is the first step towards utilizing EIS as a label-free, non-invasive, and rapid sensor for detection and characterization of pathogenic EVs and other nanovesicles in the future.

Dual-frequency impedance assays for intracellular components in microalgal cells

Intracellular components (including organelles and biomolecules) at the submicron level are typically analyzed in situ by special preparation or expensive setups. Here, a label-free and cost-effective approach of screening microalgal single-cells at a subcellular resolution is available based on impedance cytometry. To the best of our knowledge, it is the first time that the relationships between impedance signals and submicron intracellular organelles and biomolecules are shown. Experiments were performed on Euglena gracilis (E. gracilis) cells incubated under different incubation conditions (i.e., aerobic and anaerobic) and 15 μm polystyrene beads (reference) at two distinct stimulation frequencies (i.e., 500 kHz and 6 MHz). Based on the impedance detection of tens of thousands of samples at a throughput of about 900 cells per second, three metrics were used to track the changes in biophysical properties of samples. As a result, the electrical diameters of cells showed a clear shrinkage in cell volume and intracellular components, as observed under a microscope. The morphology metric of impedance pulses (i.e., tilt index) successfully characterized the changes in cell shape and intracellular composition distribution. Besides, the electrical opacity showed a stable ratio of the intracellular components to cell volume under the cellular self-regulation. Additionally, simulations were used to support these findings and to elucidate how submicron intracellular components and cell morphology affect impedance signals, providing a basis for future improvements. This work opens up a label-free and high-throughput way to analyze single-cell intracellular components by impedance cytometry.

Selective Single-Cell Sorting Using a Multisectorial Electroactive Nanowell Platform

Current approaches in targeted patient treatments often require the rapid isolation of specific rare target cells. Stream-based dielectrophoresis (DEP) based cell sorters have the limitation that the maximum number of sortable cell types is equivalent to the number of output channels, which makes upscaling to a higher number of different cell types technically challenging. Here, we present a microfluidic platform for selective single-cell sorting that bypasses this limitation. The platform consists of 10 000 nanoliter wells which are placed on top of interdigitated electrodes (IDEs) that facilitate dielectrophoresis-driven capture of cells. By use of a multisectorial design formed by 10 individually addressable IDE structures, our platform can capture a large number of different cell types. The sectorial approach allows for fast and straightforward modification to sort complex samples as different cell types are captured in different sectors and therefore removes the need for individual output channels per cell type. Experimental results obtained with a mixed sample of benign (MCF-10A) and malignant (MDA-MB-231) breast cells showed a target to nontarget sorting accuracy of over 95%. We envision that the high accuracy of our platform, in addition to its versatility and simplicity, will aid clinical environments where reliable sorting of varying complex samples is essential.

Single-cell droplet microfluidics for biomedical applications

This review focuses on the recent advances in the fundamentals of single-cell droplet microfluidics and its applications in biomedicine, providing insights into design and establishment of single-cell microsystems and their further performance.

Recent Advances in Electrical Impedance Sensing Technology for Single-Cell Analysis

Cellular heterogeneity is of significance in cell-based assays for life science, biomedicine and clinical diagnostics. Electrical impedance sensing technology has become a powerful tool, allowing for rapid, non-invasive, and label-free acquisition of electrical parameters of single cells. These electrical parameters, i.e., equivalent cell resistance, membrane capacitance and cytoplasm conductivity, are closely related to cellular biophysical properties and dynamic activities, such as size, morphology, membrane intactness, growth state, and proliferation. This review summarizes basic principles, analytical models and design concepts of single-cell impedance sensing devices, including impedance flow cytometry (IFC) to detect flow-through single cells and electrical impedance spectroscopy (EIS) to monitor immobilized single cells. Then, recent advances of both electrical impedance sensing systems applied in cell recognition, cell counting, viability detection, phenotypic assay, cell screening, and other cell detection are presented. Finally, prospects of impedance sensing technology in single-cell analysis are discussed.

Fully Automated, Sample-to-Answer Leukocyte Functional Assessment Platform for Continuous Sepsis Monitoring via Microliters of Blood

We report a fully automated, sample-to-answer, and label-free leukocyte activation analysis platform for monitoring immune responses in sepsis, by integrating the multidimensional double spiral (MDDS) and isodielectric separation (IDS) subplatforms. The integrated platform can provide rapid and fully automated identification of clinically diagnosed sepsis patients from only 50 μL of peripheral blood volume within 25 min. Many critical innovations were implemented in direct interconnection between the two subplatforms, such as intermediate sample storage and sample transfer, addressing flow rate mismatch (from mL/min to μL/min), and integration of a ridge array for upstream cell focusing in the IDS subplatform. The ridge array in the IDS subplatform can prevent the distortion of electrical profiling due to the residual red blood cells even after the MDDS process. We showed that the integrated platform can separate leukocytes (up to >99.9% red blood cell removal) in the MDDS subplatform and automatically transfer them to the downstream ridge-integrated IDS subplatform for their activation analysis without any apparent ex vivo cell activation and any human intervention. We also demonstrated that the integrated platform can identify differences between leukocytes from human sepsis and healthy subjects significantly (p = 0.0024, 95% confidence interval) by looking into differences in the intrinsic electrical properties of leukocytes. The integrated platform could enable monitoring of host leukocyte function daily or even hourly as a bedside assessment tool, which is currently a critical yet unmet need for managing many critical care patients.

Biochip with multi-planar electrodes geometry for differentiation of non-spherical bioparticles in a microchannel

A biosensor capable of differentiating cells or other microparticles based on morphology finds significant biomedical applications. Examples may include morphological determination in the cellular division process, differentiation of bacterial cells, and cellular morphological variation in inflammation and cancer etc. Here, we present a novel integrated multi-planar microelectrodes geometry design that can distinguish a non-spherical individual particle flowing along a microchannel based on its electrical signature. We simulated multi-planar electrodes design in COMSOL Multiphysics and have shown that the changes in electrical field intensity corresponding to multiple particle morphologies can be distinguished. Our initial investigation has shown that top-bottom electrodes configuration produces significantly enhanced signal strength for a spherical particle as compared to co-planar configuration. Next, we integrated the co-planar and top-bottom configurations to develop a multi-planar microelectrode design capable of electrical impedance measurement at different spatial planes inside a microchannel by collecting multiple output signatures. We tested our integrated multi-planar electrode design with particles of different elliptical morphologies by gradually changing spherical particle dimensions to the non-spherical. The computed electrical signal ratio of non-spherical to spherical particle shows a very good correlation to predict the particle morphology. The biochip sensitivity is also found be independent of orientation of the particle flowing in the microchannel. Our integrated design will help develop the technology that will allow morphological analysis of various bioparticles in a microfluidic channel in the future.

Microfluidic impedance cytometry for single-cell sensing: Review on electrode configurations

Single-cell analysis has gained considerable attention for disease diagnosis, drug screening, and differentiation monitoring. Compared to the well-established flow cytometry, which uses fluorescent-labeled antibodies, microfluidic impedance cytometry (MIC) offers a simple, label-free, and noninvasive method for counting, classifying, and monitoring cells. Superior features including a small footprint, low reagent consumption, and ease of use have also been reported. The MIC device detects changes in the impedance signal caused by cells passing through the sensing/electric field zone, which can extract information regarding the size, shape, and dielectric properties of these cells. According to recent studies, electrode configuration has a remarkable effect on detection accuracy, sensitivity, and throughput. With the improvement in microfabrication technology, various electrode configurations have been reported for improving detection accuracy and throughput. However, the various electrode configurations of MIC devices have not been reviewed. In this review, the theoretical background of the impedance technique for single-cell analysis is introduced. Then, two-dimensional, three-dimensional, and liquid electrode configurations are discussed separately; their sensing mechanisms, fabrication processes, advantages, disadvantages, and applications are also described in detail. Finally, the current limitations and future perspectives of these electrode configurations are summarized. The main aim of this review is to offer a guide for researchers on the ongoing advancement in electrode configuration designs.

Characterization of stem cell-like property in cancer cells based on single-cell impedance measurement in a microfluidic platform

Investigation of stem cell-like property in cancer cells is important for the development of new therapeutic drugs targeting at malignant tumors. Currently, the standard approach for identifying cancer stem cell-like cells relies on the recognition of stem cell surface markers. However, the reliability remains controversial among biologists. In the current work, a dielectrophoretic and impedimetric hybrid microfluidic platform was developed for capturing single cells and characterizing their stem cell-like property. Single cells were captured in 20 μm trapping wells by dielectrophoretic force and their impedance spectra were measured by an impedance analyzer. The result showed that different cancer cell lines could be differentiated by impedance magnitude ranging between 2 and 20 kHz. Moreover, cancer cells and cancer stem cell-like cells could be categorized by a 2-dimensional graph of the impedance magnitudes at 2 and 20 kHz. The stem cell-like property in cancer cells was verified by stem cell surface markers and single-cell derived colony assay. Comparing with bio-chemical approach, i.e., surface markers, bio-physical approach, i.e., cell impedance, is a label-free technique to identify cancer stem cell-like cells.

Multi-frequency single cell electrical impedance measurement for label-free cell viability analysis

Cell viability is a physiological status connected to cell membrane integrity and cytoplasmic topography, which is profoundly important for fundamental biological research and practical biomedical applications. A conventional method for assessing cell viability is through cell staining analysis. However, cell staining involves laborious and complicated processing procedures and is normally cytotoxic. Intrinsic cellular phenotypes thus provide new avenues for measuring cell viability in a stain-free and non-toxic manner. In this work, we present a label-free non-destructive impedance-based approach for cell viability assessment by simultaneously characterizing multiple electrical cellular phenotypes in a high-throughput manner (>1000 cells per min). A novel concept called the complex opacity spectrum is introduced for improving the discrimination of live and dead cells. The analysis of the complex opacity spectrum leads to the discovery of two frequency ranges that are optimized for characterizing membranous and cytoplasmic electrical phenotypes. The present impedance-based approach has successfully discriminated between living and dead cells in two different experimental scenarios, including mixed living and dead cells in both homogenous and heterogeneous cell samples. This impedance-based single cell phenotyping technique provides highly accurate and consistent cell viability analysis, which has been validated by commercial fluorescence-based flow cytometry (∼1% difference) using heterogeneous cell samples. This label-free high-throughput cell viability analysis strategy will have broad applications in the field of biology and medicine.

Single-cell microfluidic impedance cytometry: from raw signals to cell phenotypes using data analytics

The biophysical analysis of single-cells by microfluidic impedance cytometry is emerging as a label-free and high-throughput means to stratify the heterogeneity of cellular systems based on their electrophysiology. Emerging applications range from fundamental life-science and drug assessment research to point-of-care diagnostics and precision medicine. Recently, novel chip designs and data analytic strategies are laying the foundation for multiparametric cell characterization and subpopulation distinction, which are essential to understand biological function, follow disease progression and monitor cell behaviour in microsystems. In this tutorial review, we present a comparative survey of the approaches to elucidate cellular and subcellular features from impedance cytometry data, covering the related subjects of device design, data analytics (i.e., signal processing, dielectric modelling, population clustering), and phenotyping applications. We give special emphasis to the exciting recent developments of the technique (timeframe 2017-2020) and provide our perspective on future challenges and directions. Its synergistic application with microfluidic separation, sensor science and machine learning can form an essential toolkit for label-free quantification and isolation of subpopulations to stratify heterogeneous biosystems.

Monitoring Single S. cerevisiae Cells with Multifrequency Electrical Impedance Spectroscopy in an Electrode-Integrated Microfluidic Device

This chapter describes an electrode-integrated microfluidic system with multiple functions of manipulating and monitoring single S. cerevisiae cells. In this system, hydrodynamic trapping and negative dielectrophoretic (nDEP) releasing of S. cerevisiae cells are implemented, providing a flexible method for single-cell manipulation. The multiplexing microelectrodes also enable sensitive electrical impedance spectroscopy (EIS) to discern the number of immobilized cells, classify different orientations of captured cells, as well as detect potential movements of immobilized single yeast cells during the overall recording duration by using principal component analysis (PCA) in data mining. The multifrequency EIS measurements can, therefore, obtain sufficient information of S. cerevisiae cells at single-cell level.

An Electrokinetically-Driven Microchip for Rapid Entrapment and Detection of Nanovesicles

Electrical Impedance Spectroscopy (EIS) has been widely used as a label-free and rapid characterization method for the analysis of cells in clinical research. However, the related work on exosomes (40–150 nm) and the particles of similar size has not yet been reported. In this study, we developed a new Lab-on-a-Chip (LOC) device to rapidly entrap a cluster of sub-micron particles, including polystyrene beads, liposomes, and small extracellular vesicles (exosomes), utilizing an insulator-based dielectrophoresis (iDEP) scheme followed by measuring their impedance utilizing an integrated electrical impedance sensor. This technique provides a label-free, fast, and non-invasive tool for the detection of bionanoparticles based on their unique dielectric properties. In the future, this device could potentially be applied to the characterization of pathogenic exosomes and viruses of similar size, and thus, be evolved as a powerful tool for early disease diagnosis and prognosis.

Positional dependence of particles and cells in microfluidic electrical impedance flow cytometry: origin, challenges and opportunities

Microfluidic electrical impedance flow cytometry is now a well-known and established method for single-cell analysis. Given the richness of the information provided by impedance measurements, this non-invasive and label-free approach can be used in a wide field of applications ranging from simple cell counting to disease diagnostics. One of its major limitations is the variation of the impedance signal with the position of the cell in the sensing area. Indeed, identical particles traveling along different trajectories do not result in the same data. The positional dependence can be considered as a challenge for the accuracy of microfluidic impedance cytometers. On the other hand, it has recently been regarded by several groups as an opportunity to estimate the position of particles in the microchannel and thus take a further step in the logic of integrating sensors in so-called "Lab-on-a-chip" devices. This review provides a comprehensive overview of the physical grounds of the positional dependence of impedance measurements. Then, both the developed strategies to reduce position influence in impedance-based assays and the recent reported technologies exploiting that dependence for the integration of position detection in microfluidic devices are reviewed.

A Machine Learning-Assisted Nanoparticle-Printed Biochip for Real-Time Single Cancer Cell Analysis

Cancers are a complex conglomerate of heterogeneous cell populations with varying genotypes and phenotypes. The intercellular heterogeneity within the same tumor and intratumor heterogeneity within various tumors are the leading causes of resistance to cancer therapies and varied outcomes in different patients. Therefore, performing single-cell analysis is essential to identify and classify cancer cell types and study cellular heterogeneity. Here, the development of a machine learning-assisted nanoparticle-printed biochip for single-cell analysis is reported. The biochip is integrated by combining powerful machine learning techniques with easily accessible inkjet printing and microfluidics technology. The biochip is easily prototype-able, miniaturized, and cost-effective, potentially capable of differentiating a variety of cell types in a label-free manner. n-feature classifiers are established and their performance metrics are evaluated. The biochip's utility to discriminate noncancerous cells from cancerous cells at the single-cell level is demonstrated. The biochip's utility in classifying cancer sub-type cells is also demonstrated. It is envisioned that such a chip has potential applications in single-cell studies, tumor heterogeneity studies, and perhaps in point-of-care cancer diagnostics-especially in developing countries where the cost, limited infrastructures, and limited access to medical technologies are of the utmost importance.

Exceedingly Sensitive Restructured Electrodes Design for Pathogen Morphology Detection using Impedance Flow Cytometry

The cellular morphology is a vital biological characteristic for determining explicit information about its physiological state. Monitoring real-time cell shape is of great importance in infectious pathogen detection. Here, we designed a highly sensitive coplanar electrode sensing system and merged it with planar electrodes for simultaneous impedance signals in two dimensions. We simulated the proposed design in this study for the detection of different single cell pathogens based on their morphology. The optimized design has a great potential to monitor and characterize different bacteria based on their sizes and shapes. In this report, spherical and rod shaped particles were used to illustrate the device performance. This simple and extremely sensitive modified electrode design is very promising for bacterial detection and will serve as a future guiding tool for discriminating different morphologies of singular cells.

Nanometer precise red blood cell sizing using a cost-effective quantitative dark field imaging system

Because of the bulk, complexity, calibration requirements, and need for operator training, most current flow-based blood counting devices are not appropriate for field use. Standard imaging methods could be much more compact, inexpensive, and with minimal calibration requirements. However, due to the diffraction limit, imaging lacks the nanometer precision required to measure red blood cell volumes. To address this challenge, we utilize Mie scattering, which can measure nanometer-scale morphological information from cells, in a dark-field imaging geometry. The approach consists of a custom-built dark-field scattering microscope with symmetrically oblique illumination at a precisely defined angle to record wide-field images of diluted and sphered blood samples. Scattering intensities of each cell under three wavelengths are obtained by segmenting images via digital image processing. These scattering intensities are then used to determine size and hemoglobin information via Mie theory and machine learning. Validation on 90 clinical blood samples confirmed the ability to obtain mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), and red cell distribution width (RDW) with high accuracy. Simulations based on historical data suggest that an instrument with the accuracy achieved in this study could be used for widespread anemia screening.

Single ascospore detection for the forecasting of Sclerotinia stem rot of canola

Smart-agriculture technologies comprise a set of management systems designed to sustainably increase the efficiency and productivity of farming. In this paper, we present a lab-on-a-chip device that can be employed as a plant disease forecasting tool for canola crop. Our device can be employed as a platform to forecast potential outbreaks of one of the most devastating diseases of canola and other crops, Sclerotinia stem rot. The system consists of a microfluidic chip capable of detecting single airborne Sclerotinia sclerotiorum ascospores. Target ascospores are injected into the chip and selectively captured by dielectrophoresis, while other spores in the sample are flushed away. Afterward, captured ascospores are released into the flow stream of the channel and are detected employing electrochemical impedance spectroscopy and coplanar microelectrodes. Our device provides a design for a low-cost, miniaturized, and automated platform technology for airborne spore detection and disease prevention.

Nanocytometer for smart analysis of peripheral blood and acute myeloid leukemia: a pilot study

We realize an ultracompact nanocytometer for real-time impedimetric detection and classification of subpopulations of living cells. Nanoscopic nanowires in a microfluidic channel act as nanocapacitors and measure in real time the change of the amplitude and phase of the output voltage and, thus, the electrical properties of living cells. We perform the cell classification in the human peripheral blood (PBMC) and demonstrate for the first time the possibility to discriminate monocytes and subpopulations of lymphocytes in a label-free format. Further, we demonstrate that the PBMC of acute myeloid leukemia and healthy samples grant the label free identification of the disease. Using the algorithm based on machine learning, we generated specific data patterns to discriminate healthy donors and leukemia patients. Such a solution has the potential to improve the traditional diagnostics approaches with respect to the overall cost and time effort, in a label-free format, and restrictions of the complex data analysis.

Continuous Label-Free Electronic Discrimination of T Cells by Activation State

The sensitivity and speed with which the immune system reacts to host disruption is unrivaled by any detection method for pathogenic biomarkers or infectious signatures. Engagement of cellular immunity in response to infections or cancer is contingent upon activation and subsequent cytotoxic activity by T cells. Thus, monitoring T cell activation can reliably serve as a metric for disease diagnosis as well as therapeutic prognosis. Rapid and direct quantification of T cell activation states, however, has been hindered by challenges associated with antigen target identification, labeling requirements, and assay duration. Here we present an electronic, label-free method for simultaneous separation and evaluation of T cell activation states. Our device utilizes a microfluidic design integrated with nanolayered electrode structures for dielectrophoresis (DEP)-driven discrimination of activated vs naïve T cells at single-cell resolution and demonstrates rapid (<2 min) separation of T cells at high single-pass efficiency as quantified by an on-chip Coulter counter module. Our device represents a microfluidic tool for electronic assessment of immune activation states and, hence, a portable diagnostic for quantitative evaluation of immunity and disease state. Further, its ability to achieve label-free enrichment of activated immune cells promises clinical utility in cell-based immunotherapies.

Quantifying Heterogeneity According to Deformation of the U937 Monocytes and U937-Differentiated Macrophages Using 3D Carbon Dielectrophoresis in Microfluidics

A variety of force fields have thus far been demonstrated to investigate electromechanical properties of cells in a microfluidic platform which, however, are mostly based on fluid shear stress and may potentially cause irreversible cell damage. This work presents dielectric movement and deformation measurements of U937 monocytes and U937-differentiated macrophages in a low conductive medium inside a 3D carbon electrode array. Here, monocytes exhibited a crossover frequency around 150 kHz and presented maximum deformation index at 400 kHz and minimum deformation index at 1 MHz frequencies at 20 V_peak-peak. Although macrophages were differentiated from monocytes, their crossover frequency was lower than 50 kHz at 10 V_peak-peak. The change of the deformation index for macrophages was more constant and lower than the monocyte cells. Both dielectric mobility and deformation spectra revealed significant differences between the dielectric responses of U937 monocytes and U937-differentiated macrophages, which share the same origin. This method can be used for label-free, specific, and sensitive single-cell characterization. Besides, damage of the cells by aggressive shear forces can, hence, be eliminated and cells can be used for downstream analysis. Our results showed that dielectric mobility and deformation have a great potential as an electromechanical biomarker to reliably characterize and distinguish differentiated cell populations from their progenitors.

Detection and differentiation of bacteria by electrical bioimpedance spectroscopy

Detecting bacteria in samples and differentiating between Gram-negative and Gram-positive species is an important challenge, and the most common method, Gram staining, is very time consuming. The aim of this study was to evaluate the electrical bioimpedance spectroscopy (EBIS) technique as an inexpensive and practical tool for real-time detection of bacteria and differentiation between Gram-positive and Gram-negative species. The relevant sensitivity for differentiating between species was found in the magnitude and phase at frequencies of 158,489 and 5248 Hz, respectively, at a bacterial concentration of 1 μg/μl. Subsequently, the sensitivity was estimated as a function of bacterial concentration. Our results demonstrated that EBIS can potentially distinguish between presence and absence of bacteria as well as between different types of bacteria.

Determination of Dielectric Properties of Cells using AC Electrokinetic-based Microfluidic Platform: A Review of Recent Advances

Cell dielectric properties, a type of intrinsic property of cells, can be used as electrophysiological biomarkers that offer a label-free way to characterize cell phenotypes and states, purify clinical samples, and identify target cancer cells. Here, we present a review of the determination of cell dielectric properties using alternating current (AC) electrokinetic-based microfluidic mechanisms, including electro-rotation (ROT) and dielectrophoresis (DEP). The review covers theoretically how ROT and DEP work to extract cell dielectric properties. We also dive into the details of differently structured ROT chips, followed by a discussion on the determination of cell dielectric properties and the use of these properties in bio-related applications. Additionally, the review offers a look at the future challenges facing the AC electrokinetic-based microfluidic platform in terms of acquiring cell dielectric parameters. Our conclusion is that this platform will bring biomedical and bioengineering sciences to the next level and ultimately achieve the shift from lab-oriented research to real-world applications.