On the compatibility of single-cell microcarriers (nanovials) with microfluidic impedance cytometry.

We investigate for the first time the compatibility of nanovials with microfluidic impedance cytometry (MIC). Nanovials are suspendable crescent-shaped single-cell microcarriers that enable specific cell adhesion, the creation of compartments for undisturbed cell growth and secretion, as well as protection against wall shear stress. MIC is a label-free single-cell technique that characterizes flowing cells based on their electrical fingerprints and it is especially targeted to cells that are naturally in suspension. Combining nanovial technology with MIC is intriguing as it would represent a robust framework for the electrical analysis of single adherent cells at high throughput. Here, as a proof-of-concept, we report the MIC analysis of mesenchymal stromal cells loaded in nanovials. The electrical analysis is supported by numerical simulations and validated by means of optical analysis. We demonstrate that the electrical diameter can discriminate among free cells, empty nanovials, cell-loaded nanovials, and clusters, thus grounding the foundation for the use of nanovials in MIC. Furthermore, we investigate the potentiality of MIC to assess the electrical phenotype of cells loaded in nanovials and we draw directions for future studies.

Rapid Assessment of Susceptibility of Bacteria and Erythrocytes to Antimicrobial Peptides by Single-Cell Impedance Cytometry.

Antimicrobial peptides (AMPs) represent a promising class of compounds to fight antibiotic-resistant infections. In most cases, they kill bacteria by making their membrane permeable and therefore exhibit low propensity to induce bacterial resistance. In addition, they are often selective, killing bacteria at concentrations lower than those at which they are toxic to the host. However, clinical applications of AMPs are hindered by a limited understanding of their interactions with bacteria and human cells. Standard susceptibility testing methods are based on the analysis of the growth of a bacterial population and therefore require several hours. Moreover, different assays are required to assess the toxicity to host cells. In this work, we propose the use of microfluidic impedance cytometry to explore the action of AMPs on both bacteria and host cells in a rapid manner and with single-cell resolution. Impedance measurements are particularly well-suited to detect the effects of AMPs on bacteria, due to the fact that the mechanism of action involves perturbation of the permeability of cell membranes. We show that the electrical signatures of Bacillus megaterium cells and human red blood cells (RBCs) reflect the action of a representative antimicrobial peptide, DNS-PMAP23. In particular, the impedance phase at high frequency (e.g., 11 or 20 MHz) is a reliable label-free metric for monitoring DNS-PMAP23 bactericidal activity and toxicity to RBCs. The impedance-based characterization is validated by comparison with standard antibacterial activity assays and absorbance-based hemolytic activity assays. Furthermore, we demonstrate the applicability of the technique to a mixed sample of B. megaterium cells and RBCs, which paves the way to study AMP selectivity for bacterial versus eukaryotic cells in the presence of both cell types.

Extensional-Flow Impedance Cytometer for Contactless and Optics-Free Erythrocyte Deformability Analysis.

OBJECTIVE: Deformability is an essential feature of red blood cells (RBCs), enabling them to undergo significant shape change in response to external forces. Impaired erythrocyte deformability is associated with several pathologic conditions, and quantitative measurement of RBC deformability is critical to understanding and diagnosing RBC related diseases. Whereas traditional approaches to cell mechanical characterization generally have limited throughput, emerging microscale technologies are opening new opportunities for high-throughput deformability cytometry at the single-cell level. METHODS: In this work, we propose an innovative microfluidic system based on (i) a hyperbolic microchannel to induce erythrocyte deformation by extensional flow, and (ii) an electrical sensing zone with coplanar electrodes to evaluate the deformed cell shape. RESULTS: RBC deformation under extensional flow is achieved, and the deformed cell shape is quantified by means of an electrical anisotropy index, at a throughput of 300 cell/s. Measurements of healthy and chemically stiffened RBCs demonstrate that the anisotropy index can be used to characterize RBC deformability, as an alternative to deformation indices based on high-speed image processing. CONCLUSION: A contactless and optics-free approach for RBC deformability analysis has been presented. SIGNIFICANCE: Due to its simplicity and potential for integration, the proposed approach holds promises for fast and low-cost erythrocyte deformability assays, especially in point-of-care and resource-limited settings.

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.

Electro-Optical Classification of Pollen Grains via Microfluidics and Machine Learning.

OBJECTIVE: 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.

Pepperberg plot: Modeling flash response saturation in retinal rods of mouse.

Retinal rods evolved to be able to detect single photons. Despite their exquisite sensitivity, rods operate over many log units of light intensity. Several processes inside photoreceptor cells make this incredible light adaptation possible. Here, we added to our previously developed, fully space resolved biophysical model of rod phototransduction, some of the mechanisms that play significant roles in shaping the rod response under high illumination levels: the function of RGS9 in shutting off G protein transducin, and calcium dependences of the phosphorylation rates of activated rhodopsin, of the binding of cGMP to the light-regulated ion channel, and of two membrane guanylate cyclase activities. A well stirred version of this model captured the responses to bright, saturating flashes in WT and mutant mouse rods and was used to explain "Pepperberg plots," that graph the time during which the response is saturated against the natural logarithm of flash strength for bright flashes. At the lower end of the range, saturation time increases linearly with the natural logarithm of flash strength. The slope of the relation (τD) is dictated by the time constant of the rate-limiting (slowest) step in the shutoff of the phototransduction cascade, which is the hydrolysis of GTP by transducin. We characterized mathematically the X-intercept ( Φ o ) which is the number of photoisomerizations that just saturates the rod response. It has been observed that for flash strengths exceeding a few thousand photoisomerizations, the curves depart from linearity. Modeling showed that the "upward bend" for very bright flash intensities could be explained by the dynamics of RGS9 complex and further predicted that there would be a plateau at flash strengths giving rise to more than ~107 photoisomerizations due to activation of all available PDE. The model accurately described alterations in saturation behavior of mutant murine rods resulting from transgenic perturbations of the cascade targeting membrane guanylate cyclase activity, and expression levels of GRK, RGS9, and PDE. Experimental results from rods expressing a mutant light-regulated channel purported to lack calmodulin regulation deviated from model predictions, suggesting that there were other factors at play.

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.

A Bayesian Approach for Coincidence Resolution in Microfluidic Impedance Cytometry.

OBJECTIVE: Cell counting and characterization is fundamental for medicine, science and technology. Coulter-type microfluidic devices are effective and automated systems for cell/particle analysis, based on the electrical sensing zone principle. However, their throughput and accuracy are limited by coincidences (i.e., two or more particles passing through the sensing zone nearly simultaneously), which reduce the observed number of particles and may lead to errors in the measured particle properties. In this work, a novel approach for coincidence resolution in microfluidic impedance cytometry is proposed. METHODS: The approach relies on: (i) a microchannel comprising two electrical sensing zones and (ii) a model of the signals generated by coinciding particles. Maximum a posteriori probability (MAP) estimation is used to identify the model parameters and therefore characterize individual particle properties. RESULTS: Quantitative performance assessment on synthetic data streams shows a counting sensitivity of 97% and a positive predictive value of 99% at concentrations of 2×106 particles/ml. An application to red blood cell analysis shows accurate particle characterization up to a throughput of about 2500 particles/s. An original formula providing the expected number of coinciding particles is derived, and good agreement is found between experimental results and theoretical predictions. CONCLUSION: The proposed cytometer enables the decomposition of signals generated by coinciding particles into individual particle contributions, by using a Bayesian approach. SIGNIFICANCE: This system can be profitably used in applications where accurate counting and characterization of cell/particle suspensions over a broad range of concentrations is required.

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 label-free characterization of viable, necrotic and apoptotic human lymphoma cells in a coplanar-electrode microfluidic impedance chip.

The study and the characterization of cell death mechanisms are fundamental in cell biology research. Traditional death/viability assays usually involve laborious sample preparation and expensive equipment or reagents. In this work, we use electrical impedance spectroscopy as a label-free methodology to characterize viable, necrotic and apoptotic human lymphoma U937 cells. A simple three-electrode coplanar layout is used in a differential measurement scheme and thousands of cells are measured at high-throughput (≈200 cell/s). Tailored signal processing enables accurate and robust cell characterization without the need for cell focusing systems. The results suggest that, at low frequency (0.5 MHz), signal magnitude enables the discrimination between viable/necrotic cells and cell fragments, whereas phase information allows discriminating between viable cells and necrotic cells. At higher frequency (10 MHz) two subpopulations of cell fragments are distinguished. This work substantiates the prominent role of electrical impedance spectroscopy for the development of next-generation cell viability assays.

High-throughput electrical position detection of single flowing particles/cells with non-spherical shape.

We present an innovative impedance cytometer for the measurement of the cross-sectional position of single particles or cells flowing in a microchannel. As predicted by numerical simulations and experimentally validated, the proposed approach is applicable to particles/cells with either spherical or non-spherical shape. In particular, the optics-free high-throughput position detection of individual flowing red blood cells (RBCs) is demonstrated and applied to monitor RBCs hydrodynamic focusing under different sheath flow conditions. Moreover, the device provides multiparametric information useful for lab-on-a-chip applications, including particle inter-arrival times and velocity profile, as well as RBCs mean corpuscular volume, distribution width and electrical opacity.

A simple electrical approach to monitor dielectrophoretic focusing of particles flowing in a microchannel.

This paper reports an impedance-based system for the quantitative assessment of dielectrophoretic (DEP) focusing of single particles flowing in a microchannel. Particle lateral positions are detected in two electrical sensing zones placed before and after a DEP-focusing region, respectively. In each sensing zone, particle lateral positions are estimated using the unbalance between the opposite pulses of a differential current signal obtained with a straightforward coplanar electrode configuration. The system is used to monitor the focusing of polystyrene beads of 7 or 10 µm diameter, under various conditions of DEP field intensities and flow rates that produce different degrees of focusing. This electrical approach represents a simple and valuable alternative to optical methods for monitoring of particle focusing systems.

Simulation and performance analysis of a novel high-accuracy sheathless microfluidic impedance cytometer with coplanar electrode layout.

The performance of a novel microfluidic impedance cytometer (MIC) with coplanar configuration is investigated in silico. The main feature of the device is the ability to provide accurate particle-sizing despite the well-known measurement sensitivity to particle trajectory. The working principle of the device is presented and validated by means of an original virtual laboratory providing close-to-experimental synthetic data streams. It is shown that a metric correlating with particle trajectory can be extracted from the signal traces and used to compensate the trajectory-induced error in the estimated particle size, thus reaching high-accuracy. An analysis of relevant parameters of the experimental setup is also presented.

Coplanar electrode microfluidic chip enabling accurate sheathless impedance cytometry.

Microfluidic impedance cytometry offers a simple non-invasive method for single-cell analysis. Coplanar electrode chips are especially attractive due to ease of fabrication, yielding miniaturized, reproducible, and ultimately low-cost devices. However, their accuracy is challenged by the dependence of the measured signal on particle trajectory within the interrogation volume, that manifests itself as an error in the estimated particle size, unless any kind of focusing system is used. In this paper, we present an original five-electrode coplanar chip enabling accurate particle sizing without the need for focusing. The chip layout is designed to provide a peculiar signal shape from which a new metric correlating with particle trajectory can be extracted. This metric is exploited to correct the estimated size of polystyrene beads of 5.2, 6 and 7 µm nominal diameter, reaching coefficient of variations lower than the manufacturers' quoted values. The potential impact of the proposed device in the field of life sciences is demonstrated with an application to Saccharomyces cerevisiae yeast.

Numerical Investigation of a Novel Wiring Scheme Enabling Simple and Accurate Impedance Cytometry.

Microfluidic impedance cytometry is a label-free approach for high-throughput analysis of particles and cells. It is based on the characterization of the dielectric properties of single particles as they flow through a microchannel with integrated electrodes. However, the measured signal depends not only on the intrinsic particle properties, but also on the particle trajectory through the measuring region, thus challenging the resolution and accuracy of the technique. In this work we show via simulation that this issue can be overcome without resorting to particle focusing, by means of a straightforward modification of the wiring scheme for the most typical and widely used microfluidic impedance chip.

High accuracy particle analysis using sheathless microfluidic impedance cytometry.

This paper describes a new design of microfluidic impedance cytometer enabling accurate characterization of particles without the need for focusing. The approach uses multiple pairs of electrodes to measure the transit time of particles through the device in two simultaneous different current measurements, a transverse (top to bottom) current and an oblique current. This gives a new metric that can be used to estimate the vertical position of the particle trajectory through the microchannel. This parameter effectively compensates for the non-uniform electric field in the channel that is an unavoidable consequence of the use of planar parallel facing electrodes. The new technique is explained and validated using numerical modelling. Impedance data for 5, 6 and 7 µm particles are collected and compared with simulations. The method gives excellent coefficient of variation in (electrical) radius of particles of 1% for a sheathless configuration.

A Simple and Robust Event-Detection Algorithm for Single-Cell Impedance Cytometry.

Microfluidic impedance cytometry is emerging as a powerful label-free technique for the characterization of single biological cells. In order to increase the sensitivity and the specificity of the technique, suited digital signal processing methods are required to extract meaningful information from measured impedance data. In this study, a simple and robust event-detection algorithm for impedance cytometry is presented. Since a differential measuring scheme is generally adopted, the signal recorded when a cell passes through the sensing region of the device exhibits a typical odd-symmetric pattern. This feature is exploited twice by the proposed algorithm: first, a preliminary segmentation, based on the correlation of the data stream with the simplest odd-symmetric template, is performed; then, the quality of detected events is established by evaluating their E2O index, that is, a measure of the ratio between their even and odd parts. A thorough performance analysis is reported, showing the robustness of the algorithm with respect to parameter choice and noise level. In terms of sensitivity and positive predictive value, an overall performance of 94.9% and 98.5%, respectively, was achieved on two datasets relevant to microfluidic chips with very different characteristics, considering three noise levels. The present algorithm can foster the role of impedance cytometry in single-cell analysis, which is the new frontier in "Omics."

Identification of key factors that reduce the variability of the single photon response.

Rod photoreceptors mediate vision in dim light. Their biological function is to discriminate between distinct, very low levels of illumination, i.e., they serve as reliable photon counters. This role requires high reproducibility of the response to a particular number of photons. Indeed, single photon responses demonstrate unexpected low variability, despite the stochastic nature of the individual steps in the transduction cascade. We analyzed individual system mechanisms to identify their contribution to variability suppression. These include: (i) cooperativity of the regulation of the second messengers; (ii) diffusion of cGMP and Ca(2+) in the cytoplasm; and (iii) the effect of highly localized cGMP hydrolysis by activated phosphodiesterase resulting in local saturation. We find that (i) the nonlinear relationships between second messengers and current at the plasma membrane, and the cGMP hydrolysis saturation effects, play a major role in stabilizing the system; (ii) the presence of a physical space where the second messengers move by Brownian motion contributes to stabilization of the photoresponse; and (iii) keeping Ca(2+) at its dark level has only a minor effect on the variability of the system. The effects of diffusion, nonlinearity, and saturation synergize in reducing variability, supporting the notion that the observed high fidelity of the photoresponse is the result of global system function of phototransduction.

Kinetics of rhodopsin deactivation and its role in regulating recovery and reproducibility of rod photoresponse.

The single photon response (SPR) in vertebrate phototransduction is regulated by the dynamics of R* during its lifetime, including the random number of phosphorylations, the catalytic activity and the random sojourn time at each phosphorylation level. Because of this randomness the electrical responses are expected to be inherently variable. However the SPR is highly reproducible. The mechanisms that confer to the SPR such a low variability are not completely understood. The kinetics of rhodopsin deactivation is investigated by a Continuous Time Markov Chain (CTMC) based on the biochemistry of rhodopsin activation and deactivation, interfaced with a spatio-temporal model of phototransduction. The model parameters are extracted from the photoresponse data of both wild type and mutant mice, having variable numbers of phosphorylation sites and, with the same set of parameters, the model reproduces both WT and mutant responses. The sources of variability are dissected into its components, by asking whether a random number of turnoff steps, a random sojourn time between steps, or both, give rise to the known variability. The model shows that only the randomness of the sojourn times in each of the phosphorylated states contributes to the Coefficient of Variation (CV) of the response, whereas the randomness of the number of R* turnoff steps has a negligible effect. These results counter the view that the larger the number of decay steps of R*, the more stable the photoresponse is. Our results indicate that R* shutoff is responsible for the variability of the photoresponse, while the diffusion of the second messengers acts as a variability suppressor.

Diffusion of the second messengers in the cytoplasm acts as a variability suppressor of the single photon response in vertebrate phototransduction.

The single photon response in vertebrate phototransduction is highly reproducible despite a number of random components of the activation cascade, including the random activation site, the random walk of an activated receptor, and its quenching in a random number of steps. Here we use a previously generated and tested spatiotemporal mathematical and computational model to identify possible mechanisms of variability reduction. The model permits one to separate the process into modules, and to analyze their impact separately. We show that the activation cascade is responsible for generation of variability, whereas diffusion of the second messengers is responsible for its suppression. Randomness of the activation site contributes at early times to the coefficient of variation of the photoresponse, whereas the Brownian path of a photoisomerized rhodopsin (Rh*) has a negligible effect. The major driver of variability is the turnoff mechanism of Rh*, which occurs essentially within the first 2-4 phosphorylated states of Rh*. Theoretically increasing the number of steps to quenching does not significantly decrease the corresponding coefficient of variation of the effector, in agreement with the biochemical limitations on the phosphorylated states of the receptor. Diffusion of the second messengers in the cytosol acts as a suppressor of the variability generated by the activation cascade. Calcium feedback has a negligible regulatory effect on the photocurrent variability. A comparative variability analysis has been conducted for the phototransduction in mouse and salamander, including a study of the effects of their anatomical differences such as incisures and photoreceptors geometry on variability generation and suppression.