Dielectric characterization of Plasmodium falciparum-infected red blood cells using microfluidic impedance cytometry

On-Chip Impedance Spectroscopy of Malaria-Infected Red Blood Cells

Malaria is a disease that affects millions of people worldwide, particularly in developing countries. The development of accurate and efficient methods for the detection of malaria-infected cells is crucial for effective disease management and control. This paper presents the electrical impedance spectroscopy (EIS) of normal and malaria-infected red blood cells. An EIS microfluidic device, comprising a microchannel and a pair of coplanar electrodes, was fabricated for single-cell measurements in a continuous manner. Based on the EIS results, the aim of this work is to discriminate Plasmodium falciparum-infected red blood cells from the normal ones. Different from typical impedance spectroscopy, our measurement was performed for the cells in a low-conductivity medium in a frequency range between 50 kHz and 800 kHz. Numerical simulation was utilized to study the suitability parameters of the microchannel and electrodes for the EIS experiment over the measurement frequencies. The measurement results have shown that by using the low-conductivity medium, we could focus on the change in the conductance caused by the presence of a cell in the sensing electrode gap. The results indicated a distinct frequency spectrum of the conductance between the normal and infected red blood cells, which can be further used for the detection of the disease.

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.

Machine learning implementation strategy in imaging and impedance flow cytometry

Imaging and impedance flow cytometry is a label-free technique that has shown promise as a potential replacement for standard flow cytometry. This is due to its ability to provide rich information and archive high-throughput analysis. Recently, significant efforts have been made to leverage machine learning for processing the abundant data generated by those techniques, enabling rapid and accurate analysis. Harnessing the power of machine learning, imaging and impedance flow cytometry has demonstrated its capability to address various complex phenotyping scenarios. Herein, we present a comprehensive overview of the detailed strategies for implementing machine learning in imaging and impedance flow cytometry. We initiate the discussion by outlining the commonly employed setup to acquire the data (i.e., image or signal) from the cell. Subsequently, we delve into the necessary processes for extracting features from the acquired image or signal data. Finally, we discuss how these features can be utilized for cell phenotyping through the application of machine learning algorithms. Furthermore, we discuss the existing challenges and provide insights for future perspectives of intelligent imaging and impedance flow cytometry.

Investigations on the Novel Antimalarial Ferroquine in Biomimetic Solutions Using Deep UV Resonance Raman Spectroscopy and Density Functional Theory

Deep ultraviolet (DUV) resonance Raman experiments are performed, investigating the novel, promising antimalarial ferroquine (FQ). Two buffered aqueous solutions with pH values of 5.13 and 7.00 are used, simulating the acidic and neutral conditions inside a parasite's digestive vacuole and cytosol, respectively. To imitate the different polarities of the membranes and interior, the buffer's 1,4-dioxane content was increased. These experimental conditions should mimic the transport of the drug inside malaria-infected erythrocytes through parasitophorous membranes. Supporting density functional theory (DFT) calculations on the drug's micro-speciation were performed, which could be nicely assigned to shifts in the peak positions of resonantly enhanced high-wavenumber Raman signals at λ_exc = 257 nm. FQ is fully protonated in polar mixtures like the host interior and the parasite's cytoplasm or digestive vacuole (DV) and is only present as a free base in nonpolar ones, such as the host's and parasitophorous membranes. Additionally, the limit of detection (LoD) of FQ at vacuolic pH values was determined using DUV excitation wavelengths at 244 and 257 nm. By applying the resonant laser line at λ_exc = 257 nm, a minimal FQ concentration of 3.1 μM was detected, whereas the pre-resonant excitation wavelength 244 nm provides an LoD of 6.9 μM. These values were all up to one order of magnitude lower than the concentration found for the food vacuole of a parasitized erythrocyte.

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.

Using Impedance Flow Cytometry for Rapid Viability Classification of Heat-Treated Bacteria

In the future, rapid electrical characterization of cells with impedance flow cytometry promises to be a fast and accurate method for the evaluation of cell properties. In this paper, we investigate how the conductivity of the suspending medium along with the heat exposure time affects the viability classification of heat-treated E. coli. Using a theoretical model, we show that perforation of the bacteria membrane during heat exposure changes the impedance of the bacterial cell from effectively less conducting than the suspension medium to effectively more conducting. Consequently, this results in a shift in the differential argument of the complex electrical current that can be measured with impedance flow cytometry. We observe this shift experimentally through measurements on E. coli samples with varying medium conductivity and heat exposure times. We show that increased exposure time and lower medium conductivity results in improved classification between untreated and heat-treated bacteria. The best classification was achieved with a medium conductivity of 0.045 S/m after 30 min of heat exposure.

Advances in Microfluidics for Single Red Blood Cell Analysis

The utilizations of microfluidic chips for single RBC (red blood cell) studies have attracted great interests in recent years to filter, trap, analyze, and release single erythrocytes for various applications. Researchers in this field have highlighted the vast potential in developing micro devices for industrial and academia usages, including lab-on-a-chip and organ-on-a-chip systems. This article critically reviews the current state-of-the-art and recent advances of microfluidics for single RBC analyses, including integrated sensors and microfluidic platforms for microscopic/tomographic/spectroscopic single RBC analyses, trapping arrays (including bifurcating channels), dielectrophoretic and agglutination/aggregation studies, as well as clinical implications covering cancer, sepsis, prenatal, and Sickle Cell diseases. Microfluidics based RBC microarrays, sorting/counting and trapping techniques (including acoustic, dielectrophoretic, hydrodynamic, magnetic, and optical techniques) are also reviewed. Lastly, organs on chips, multi-organ chips, and drug discovery involving single RBC are described. The limitations and drawbacks of each technology are addressed and future prospects are discussed.

Microfluidic Systems for Blood and Blood Cell Characterization

A laboratory blood test is vital for assessing a patient's health and disease status. Advances in microfluidic technology have opened the door for on-chip blood analysis. Currently, microfluidic devices can reproduce myriad routine laboratory blood tests. Considerable progress has been made in microfluidic cytometry, blood cell separation, and characterization. Along with the usual clinical parameters, microfluidics makes it possible to determine the physical properties of blood and blood cells. We review recent advances in microfluidic systems for measuring the physical properties and biophysical characteristics of blood and blood cells. Added emphasis is placed on multifunctional platforms that combine several microfluidic technologies for effective cell characterization. The combination of hydrodynamic, optical, electromagnetic, and/or acoustic methods in a microfluidic device facilitates the precise determination of various physical properties of blood and blood cells. We analyzed the physical quantities that are measured by microfluidic devices and the parameters that are determined through these measurements. We discuss unexplored problems and present our perspectives on the long-term challenges and trends associated with the application of microfluidics in clinical laboratories. We expect the characterization of the physical properties of blood and blood cells in a microfluidic environment to be considered a standard blood test in the future.

Ring stage classification of Babesia microti and Plasmodium falciparum using optical diffraction 3D tomographic technique

Background

Babesia is an intraerythrocytic parasite often misdiagnosed as a malaria parasite, leading to inappropriate treatment of the disease especially in co-endemic areas. In recent years, optical diffraction tomography (ODT) has shown great potential in the field of pathogen detection by quantification of three-dimensional (3D) imaging tomograms. The 3D imaging of biological cells is crucial to investigate and provide valuable information about the mechanisms behind the pathophysiology of cells and tissues.

Methods

The early ring stage of P. falciparum were obtained from stored stock of infected RBCs and of B. microti were obtained from infected patients during diagnosis. The ODT technique was applied to analyze and characterize detailed differences between P. falciparum and B. microti ring stage at the single cell level. Based on 3D quantitative information, accurate measurement was performed of morphological, biochemical, and biophysical parameters.

Results

Accurate measurements of morphological parameters indicated that the host cell surface area at the ring stage in B. microti was significantly smaller (140.2 ± 17.1 µm2) than that in P. falciparum (159.0 ± 15.2 µm2), and sphericities showed higher levels in B. microti-parasitized cells (0.66 ± 0.05) than in P. falciparum (0.60 ± 0.04). Based on biochemical parameters, host cell hemoglobin level was significantly higher and membrane fluctuations were respectively more active in P. falciparum-infected cells (30.25 ± 2.96 pg; 141.3 ± 24.68 nm) than in B. microti (27.28 ± 3.52 pg; 110.1 ± 38.83 nm). The result indicates that P. falciparum more actively altered host RBCs than B. microti.

Conclusion

Although P. falciparum and B. microti often show confusable characteristics under the microscope, and the actual three-dimensional properties are different. These differences could be used in differential clinical diagnosis of erythrocytes infected with B. microti and P. falciparum.

Graphical Abstract

Label-Free Microfluidic Impedance Cytometry for Acrosome Integrity Assessment of Boar Spermatozoa

Microfluidics and lab-on-chip technologies have been used in a wide range of biomedical applications. They are known as versatile, rapid, and low-cost alternatives for expensive equipment and time-intensive processing. The veterinary industry and human fertility clinics could greatly benefit from label-free and standardized methods for semen analysis. We developed a tool to determine the acrosome integrity of spermatozoa using microfluidic impedance cytometry. Spermatozoa from boars were treated with the calcium ionophore A23187 to induce acrosome reaction. The magnitude, phase and opacity of individual treated and non-treated (control) spermatozoa were analyzed and compared to conventional staining for acrosome integrity. The results show that the opacity at 19 MHz over 0.5 MHz is associated with acrosome integrity with a cut-off threshold at 0.86 (sensitivity 98%, specificity 97%). In short, we have demonstrated that acrosome integrity can be determined using opacity, illustrating that microfluidic impedance cytometers have the potential to become a versatile and efficient alternative in semen analysis and for fertility treatments in the veterinary industry and human fertility clinics.

Deciphering impedance cytometry signals with neural networks

Microfluidic impedance cytometry is a label-free technique for high-throughput single-cell analysis. Multi-frequency impedance measurements provide data that allows full characterisation of cells, linking electrical phenotype to individual biophysical properties. To efficiently extract the information embedded in the electrical signals, potentially in real-time, tailored signal processing is needed. Artificial intelligence approaches provide a promising new direction. Here we demonstrate the ability of neural networks to decipher impedance cytometry signals in two challenging scenarios: (i) to determine the intrinsic dielectric properties of single cells directly from raw impedance data streams, (ii) to capture single-cell signals that are hidden in the measured signals of coincident cells. The accuracy of the results and the high processing speed (fractions of ms per cell) demonstrate that neural networks can have an important role in impedance-based single-cell analysis.

Blood Cell Analysis: From Traditional Methods to Super-Resolution Microscopy

Blood cell analysis is essential for the diagnosis and identification of hematological malignancies. The use of digital microscopy systems has been extended in clinical laboratories. Super-resolution microscopy (SRM) has attracted wide attention in the medical field due to its nanoscale spatial resolution and high sensitivity. It is considered to be a potential method of blood cell analysis that may have more advantages than traditional approaches such as conventional optical microscopy and hematology analyzers in certain examination projects. In this review, we firstly summarize several common blood cell analysis technologies in the clinic, and analyze the advantages and disadvantages of these technologies. Then, we focus on the basic principles and characteristics of three representative SRM techniques, as well as the latest advances in these techniques for blood cell analysis. Finally, we discuss the developmental trend and possible research directions of SRM, and provide some discussions on further development of technologies for blood cell analysis.

Modified Red Blood Cells as Multimodal Standards for Benchmarking Single-Cell Cytometry and Separation Based on Electrical Physiology

Biophysical cellular information at single-cell sensitivity is becoming increasingly important within analytical and separation platforms that associate the cell phenotype with markers of disease, infection, and immunity. Frequency-modulated electrically driven microfluidic measurement and separation systems offer the ability to sensitively identify single cells based on biophysical information, such as their size and shape, as well as their subcellular membrane morphology and cytoplasmic organization. However, there is a lack of reliable and reproducible model particles with well-tuned subcellular electrical phenotypes that can be used as standards to benchmark the electrical physiology of unknown cell types or to benchmark dielectrophoretic separation metrics of novel device strategies. Herein, the application of red blood cells (RBCs) as multimodal standard particles with systematically modulated subcellular electrophysiology and associated fluorescence level is presented. Using glutaraldehyde fixation to vary membrane capacitance and by membrane resealing after electrolyte penetration to vary interior cytoplasmic conductivity and fluorescence in a correlated manner, each modified RBC type can be identified at single-cell sensitivity based on phenomenological impedance metrics and fitted to dielectric models to compute biophysical information. In this manner, single-cell impedance data from unknown RBC types can be mapped versus these model RBC types for facile determination of subcellular biophysical information and their dielectrophoretic separation conditions, without the need for time-consuming algorithms that often require unknown fitting parameters. Such internal standards for biophysical cytometry can advance in-line phenotypic recognition strategies.

Advance of microfluidic constriction channel system of measuring single-cell cortical tension/specific capacitance of membrane and conductivity of cytoplasm

This paper reported a microfluidic platform which realized the characterization of inherent single-cell biomechanical and bioelectrical parameters simultaneously. Individual cells traveled through a constriction channel with deformation images and impedance variations captured and processed into cortical tension T_c , specific membrane capacitance C_sm , and cytoplasmic conductivity σ_cy based on an equivalent biophysical model. These properties of thousands of individual cells of K562, Jurkat, HL-60, HL-60 treated with paraformaldehyde (PA)/cytochalasin D (CD)/concanavalin A (ConA), granulocytes of Donor 1, Donor 2, and Donor 3 were quantified for the first time. Leveraging T_c , C_sm , and σ_cy , (1) high accuracies of classifying wild-type and processed HL-60 cells (e.g., 93.5% of PA treated vs. CD treated HL-60 cells) were realized, revealing the effectiveness of using these three biophysical parameters in cell-type classification; (2) low accuracies of classifying normal granulocytes from three donors (e.g., 56.4% of Donor 1 vs. 2), indicating comparable parameters for normal granulocytes. In conclusion, this platform can characterize single-cell T_c , C_sm , and σ_cy concurrently and quantify multiple parameters in single-cell analysis.

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.

Systematic Review: Microfluidics and Plasmodium

Malaria affects 228 million people worldwide each year, causing severe disease and worsening the conditions of already vulnerable populations. In this review, we explore how malaria has been detected in the past and how it can be detected in the future. Our primary focus is on finding new directions for low-cost diagnostic methods that unspecialized personnel can apply in situ. Through this review, we show that microfluidic devices can help pre-concentrate samples of blood infected with malaria to facilitate the diagnosis. Importantly, these devices can be made cheaply and be readily deployed in remote locations.

Electro-optical classification of pollen grains via microfluidics and machine learning

In aerobiological monitoring and agriculture there is a pressing need for accurate, label-free and automated analysis of pollen grains, in order to reduce the cost, workload and possible errors associated to traditional approaches. Methods: We propose a new multimodal approach that combines electrical sensing and optical imaging to classify pollen grains flowing in a microfluidic chip at a throughput of 150 grains per second. Electrical signals and synchronized optical images are processed by two independent machine learning-based classifiers, whose predictions are then combined to provide the final classification outcome. Results: The applicability of the method is demonstrated in a proof-of-concept classification experiment involving eight pollen classes from different taxa. The average balanced accuracy is 78.7 % for the electrical classifier, 76.7 % for the optical classifier and 84.2 % for the multimodal classifier. The accuracy is 82.8 % for the electrical classifier, 84.1 % for the optical classifier and 88.3 % for the multimodal classifier. Conclusion: The multimodal approach provides better classification results with respect to the analysis based on electrical or optical features alone. Significance: The proposed methodology paves the way for automated multimodal palynology. Moreover, it can be extended to other fields, such as diagnostics and cell therapy, where it could be used for label-free identification of cell populations in heterogeneous samples.

On the Coupling between Mechanical Properties and Electrostatics in Biological Membranes

Cell membrane structure is proposed as a lipid matrix with embedded proteins, and thus, their emerging mechanical and electrostatic properties are commanded by lipid behavior and their interconnection with the included and absorbed proteins, cytoskeleton, extracellular matrix and ionic media. Structures formed by lipids are soft, dynamic and viscoelastic, and their properties depend on the lipid composition and on the general conditions, such as temperature, pH, ionic strength and electrostatic potentials. The dielectric constant of the apolar region of the lipid bilayer contrasts with that of the polar region, which also differs from the aqueous milieu, and these changes happen in the nanometer scale. Besides, an important percentage of the lipids are anionic, and the rest are dipoles or higher multipoles, and the polar regions are highly hydrated, with these water molecules forming an active part of the membrane. Therefore, electric fields (both, internal and external) affects membrane thickness, density, tension and curvature, and conversely, mechanical deformations modify membrane electrostatics. As a consequence, interfacial electrostatics appears as a highly important parameter, affecting the membrane properties in general and mechanical features in particular. In this review we focus on the electromechanical behavior of lipid and cell membranes, the physicochemical origin and the biological implications, with emphasis in signal propagation in nerve cells.

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.

Apoptotic Bodies in the Pancreatic Tumor Cell Culture Media Enable Label-Free Drug Sensitivity Assessment by Impedance Cytometry

The ability to rapidly and sensitively predict drug response and toxicity using in vitro models of patient-derived tumors is essential for assessing chemotherapy efficacy. Currently, drug sensitivity assessment for solid tumors relies on imaging adherent cells or by flow cytometry of cells lifted from drug-treated cultures after fluorescent staining for apoptotic markers. Subcellular apoptotic bodies (ABs), including microvesicles that are secreted into the culture media under drug treatment can potentially serve as markers for drug sensitivity, without the need to lift cells under culture. However, their stratification to quantify cell disassembly is challenging due to their compositional diversity, with tailored labeling strategies currently needed for the recognition and cytometry of each AB type. It is shown that the high frequency impedance phase versus size distribution of ABs determined by high-throughput single-particle impedance cytometry of supernatants in the media of gemcitabine-treated pancreatic tumor cultures exhibits phenotypic resemblance to lifted apoptotic cells and enables shape-based stratification within distinct size ranges, which is not possible by flow cytometry. It is envisioned that this tool can be applied in conjunction with the appropriate pancreatic tumor microenvironment model to assess drug sensitivity and toxicity of patient-derived tumors, without the need to lift cells from cultures.

Energy absorption of human red blood cells and conductivity of the cytoplasm influenced by temperature

The energy absorbed into tissues is known as the specific energy absorption (SAR) which is dependent on conductivity of the tissue. We calculated cytoplasmic conductivity of human red blood cell (HRBC) using the intracellular ionic concentrations and the Debye-Hückel-Onsager relation. The overall concentration is determined by cell volume and cell water content. The calculated HRBC conductivity at 25 ^o C was σ_c,₂₅ = 0.5566 ± 0.0146 S m^-1, ±SE). It is exponentially related to temperature: Q₁₀ ≈ 1.866. At 37 ^o C, the calculated SAR value is 1.6 W kg^-1 using a linear temperature compensation of conductivity. However, if using a biologically realistic non-linear temperature compensated conductivity, the SAR is ≈ 2.62 ± 0.05 W kg^-1. The relationship between SAR and temperature increase is not straightforward. Since there is a wide variance in cellular ionic and water perfusion rates more tissue-specific SAR limits which consider temperature-related factors would be valuable.

Label-Free Quantification of Cell Cycle Synchronicity of Human Neural Progenitor Cells Based on Electrophysiology Phenotypes

The ability to coax human-induced pluripotent stem cells (hiPSCs) into human neural progenitor cells (hNPCs) can lead to novel drug discovery and transplant therapy platforms for neurological diseases. Since hNPCs can form organoids that mimic brain development, there is emerging interest in their label-free characterization for controlling cell composition to optimize organoid formation in three-dimensional (3D) cultures. However, this requires the ability to quantify hNPCs in heterogeneous samples with subpopulations of similar phenotype. Using high-throughput (>6000 cells per condition), single-cell impedance cytometry, we present the utilization of electrophysiology for quantification of hNPC subpopulations that are altered in cell cycle synchronicity by camptothecin (CPT) exposure. Electrophysiology phenotypes are determined from impedance magnitude and phase metrics for distinguishing each cell cycle phase, as validated by flow cytometry, for a wide range of subpopulation proportions. Using multishell dielectric models for each cell cycle phase, electrophysiology alterations with CPT dose could be predicted. This label-free detection strategy can prevent loss of cell viability to speed the optimization of cellular compositions for organoid development.

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.

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.

Quantifying bacterial spore germination by single-cell impedance cytometry for assessment of host microbiota susceptibility to Clostridioides difficile infection

The germination of ingested spores is often a necessary first step required for enabling bacterial outgrowth and host colonization, as in the case of Clostridioides difficile (C. difficile) infection. Spore germination rate in the colon depends on microbiota composition and its level of disruption by antibiotic treatment since secretions by commensal bacteria modulate primary to secondary bile salt levels to control germination. Assessment of C. difficile spore germination typically requires measurement of colony-forming units, which is labor intensive and takes at least 24 h to perform but is regularly required due to the high recurrence rates of nosocomial antibiotic-associated diarrhea. We present a rapid method to assess spore germination by using high throughput single-cell impedance cytometry (>300 events/s) to quantify live bacterial cells, by gating for their characteristic electrophysiology versus spores, so that germination can be assessed after just 4 h of culture at a detection limit of ~100 live cells per 50 μL sample. To detect the phenotype of germinated C. difficile bacteria, we utilize its characteristically higher net conductivity versus that of spore aggregates and non-viable C. difficile forms, which causes a distinctive high-frequency (10 MHz) impedance phase dispersion within moderately conductive media (0.8 S/m). In this manner, we can detect significant differences in spore germination rates within just 4 h, with increasing primary bile salt levels in vitro and using ex vivo microbiota samples from an antibiotic-treated mouse model to assess susceptibility to C. difficile infection. We envision a rapid diagnostic tool for assessing host microbiota susceptibility to bacterial colonization after key antibiotic treatments.

The Role of Single-Cell Technology in the Study and Control of Infectious Diseases

The advent of single-cell research in the recent decade has allowed biological studies at an unprecedented resolution and scale. In particular, single-cell analysis techniques such as Next-Generation Sequencing (NGS) and Fluorescence-Activated Cell Sorting (FACS) have helped show substantial links between cellular heterogeneity and infectious disease progression. The extensive characterization of genomic and phenotypic biomarkers, in addition to host-pathogen interactions at the single-cell level, has resulted in the discovery of previously unknown infection mechanisms as well as potential treatment options. In this article, we review the various single-cell technologies and their applications in the ongoing fight against infectious diseases, as well as discuss the potential opportunities for future development.

Determination of membrane capacitance and cytoplasm conductivity by simultaneous electrorotation

Membrane capacitances and cytoplasm conductivities of hematopoietic cells were investigated by simultaneous electrorotation (ROT) systems of multiple cells. Simultaneous ROT was achieved by the rotation of electric fields in grid arrays formed with three-dimensional interdigitated array (3D-IDA) electrodes that can be easily fabricated using two substrates with IDA electrodes. When AC signals were applied to four microband electrodes with a 90° phase difference to each electrode, cells dispersed randomly in the 3D-IDA device started to rotate and moved to the center of each grid. Multiple cells were simultaneously rotated at the center of grids without friction from contact with other cells and substrates. The averages and variance of ROT rates of cells at each frequency can be measured during a single operation of the device within 5 min, resulting in the acquisition of ROT spectra. Membrane capacitances and cytoplasm conductivities of hematopoietic cells (K562 cells, Jurkat cells, and THP-1 cells) were determined by fitting ROT spectra obtained experimentally to the curves calculated theoretically. The values determined by using the simultaneous ROT systems well coincided with the values reported previously. The membrane capacitances and cytoplasm conductivities of WEHI-231 cells were firstly determined to be 8.89 ± 0.25 mF m^-2 and 0.28 ± 0.03 S m^-1, respectively. Furthermore, the difference of the ROT rates based on the difference of the electric properties of cells was applied to discriminate the types of cells. The acquisition of rotation rates of multiple cells within a single operation makes the statistical analysis extremely profitable for determining the electrical properties of cells.

A neural network approach for real-time particle/cell characterization in microfluidic impedance cytometry

Microfluidic applications such as active particle sorting or selective enrichment require particle classification techniques that are capable of working in real time. In this paper, we explore the use of neural networks for fast label-free particle characterization during microfluidic impedance cytometry. A recurrent neural network is designed to process data from a novel impedance chip layout for enabling real-time multiparametric analysis of the measured impedance data streams. As demonstrated with both synthetic and experimental datasets, the trained network is able to characterize with good accuracy size, velocity, and cross-sectional position of beads, red blood cells, and yeasts, with a unitary prediction time of 0.4 ms. The proposed approach can be extended to other device designs and cell types for electrical parameter extraction. This combination of microfluidic impedance cytometry and machine learning can serve as a stepping stone to real-time single-cell analysis and sorting. Graphical Abstract.

High-throughput dynamical analysis of dielectrophoretic frequency dispersion of single cells based on deflected flow streamlines

Phenotypic quantification of cells based on their plasma membrane capacitance and cytoplasmic conductivity, as determined by their dielectrophoretic frequency dispersion, is often used as a marker for their biological function. However, due to the prevalence of phenotypic heterogeneity in many biological systems of interest, there is a need for methods capable of determining the dielectrophoretic dispersion of single cells at high throughput and without the need for sample dilution. We present a microfluidic device methodology wherein localized constrictions in the microchannel are used to enhance the field delivered by adjoining planar electrodes, so that the dielectrophoresis level and direction on flow-focused cells can be determined on each traversing cell in a high-throughput manner based on their deflected flow streamlines. Using a sample of human red blood cells diluted to 2.25 × 10⁸ cells/mL, the dielectrophoretic translation of single cells traversing at a flow rate of 1.68 μL/min is measured at a throughput of 1.1 × 10⁵ cells/min, to distinguish positive versus negative dielectrophoresis and determine their crossover frequency in media of differing conductivity for validation of the computed membrane capacitance to that from prior methods. We envision application of this dynamic dielectrophoresis (Dy-DEP) method towards high-throughput measurement of the dielectric dispersion of single cells to stratify phenotypic heterogeneity of a particular sample based on their DEP crossover frequency, without the need for significant sample dilution. Grapical abstract.

High-Speed Single-Cell Dielectric Spectroscopy

Single-cell impedance cytometry is a label-free analysis technique that is now widely used to measure the electrical properties of a cell and to differentiate different subpopulations. Current techniques are limited to measuring the impedance of a single cell at one or two simultaneous frequencies. Also, there are no methods that extrapolate the intrinsic electrical properties of single cells. We demonstrate a new approach that uses multifrequency impedance measurements to determine the complete intrinsic electrical properties of thousands of single cells at high throughput. The applicability of the method is demonstrated by measuring the properties of red blood cells and red cell ghosts, deriving the unique values of conductivity and permittivity of the membrane and cytoplasm for each individual cell.

Electrophysiology-based stratification of pancreatic tumorigenicity by label-free single-cell impedance cytometry

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer lacking specific biomarkers that can be correlated to disease onset, promotion and progression. To assess whether tumor cell electrophysiology may serve as a marker for PDAC tumorigenicity, we use multi-frequency impedance cytometry at high throughput (∼350 cells/s) to measure the electrical phenotype of single PDAC tumor cells from xenografts, which are derived from primary pancreatic tumors versus those from liver metastases of different patients. A novel phase contrast metric based on variations in the high and low frequency impedance phase responses that is related to electrophysiology of the cell interior is found to be systematically altered as a function of tumorigenicity. PDAC cells of higher tumorigenicity exhibited lowered interior conductivity and enhanced permittivity, which is validated by the dielectrophoresis on the respective cell types. Using genetic analysis, we suggest the role of dysregulated Na⁺ transport and removal of Ca²⁺ ions from the cytoplasm on key oncogenic KRAS-driven processes that may be responsible for lowering of the interior cell conductivity. We envision that impedance cytometry can serve as a tool to quantify phenotypic heterogeneity for rapidly stratifying tumorigenicity. It can also aid in protocols for dielectrophoretic isolation of cells with a particular phenotype for prognostic studies on patient survival and to tailor therapy selection to specific patients.

Endothelial glycocalyx regulates cytoadherence in Plasmodium falciparum malaria

Malaria is associated with significant microcirculation disorders, especially when the infection reaches its severe stage. This can lead to a range of fatal conditions, from cerebral malaria to multiple organ failure, of not fully understood pathogenesis. It has recently been proposed that a breakdown of the glycocalyx, the carbohydrate-rich layer lining the vascular endothelium, plays a key role in severe malaria, but direct evidence supporting this hypothesis is still lacking. Here, the interactions between Plasmodium falciparum infected red blood cells ( PfRBCs) and endothelial glycocalyx are investigated by developing an in vitro, physiologically relevant model of human microcirculation based on microfluidics. Impairment of the glycocalyx is obtained by enzymatic removal of sialic acid residues, which, due to their terminal location and net negative charge, are implicated in the initial interactions with contacting cells. We show a more than twofold increase of PfRBC adhesion to endothelial cells upon enzymatic treatment, relative to untreated endothelial cells. As a control, no effect of enzymatic treatment on healthy red blood cell adhesion is found. The increased adhesion of PfRBCs is also associated with cell flipping and reduced velocity as compared to the untreated endothelium. Altogether, these results provide a compelling evidence of the increased cytoadherence of PfRBCs to glycocalyx-impaired vascular endothelium, thus supporting the advocated role of glycocalyx disruption in the pathogenesis of this disease.