Investigating the Use of Impedance Flow Cytometry for Classifying the Viability State of E. coli

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.

Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation

Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical properties in real time. However, the accurate differentiation of different species of bacteria by IFC technology remains a challenge owing to the insignificant differences in data. Here, we developed a convolutional neural networks (ConvNet) deep learning approach to enhance the accuracy and efficiency of the IFC toward distinguishing various species of bacteria. First, more than 1 million sets of impedance data (comprising 42 characteristic features for each set) of various groups of bacteria were trained by the ConvNet model. To improve the efficiency for data analysis, the Spearman correlation coefficient and the mean decrease accuracy of the random forest algorithm were introduced to eliminate feature interaction and extract the opacity of impedance related to the bacterial wall and membrane structure as the predominant features in bacterial differentiation. Moreover, the 25 optimized features were selected with differentiation accuracies of >96% for three groups of bacteria (bacilli, cocci, and vibrio) and >95% for two species of bacilli (Escherichia coli and Salmonella enteritidis), compared to machine learning algorithms (complex tree, linear discriminant, and K-nearest neighbor algorithms) with a maximum accuracy of 76.4%. Furthermore, bacterial differentiation was achieved on spiked samples of different species with different mixing ratios. The proposed ConvNet deep learning-assisted data analysis method of IFC exhibits advantages in analyzing a huge number of data sets with capacity for extracting predominant features within multicomponent information and will bring about progress and advances in the fields of both biosensing and data analysis.

Progress in methods for the detection of viable Escherichia coli

Escherichia coli (E. coli) is a prevalent enteric bacterium and a necessary organism to monitor for food safety and environmental purposes. Developing efficient and specific methods is critical for detecting and monitoring viable E. coli due to its high prevalence. Conventional culture methods are often laborious and time-consuming, and they offer limited capability in detecting potentially harmful viable but non-culturable E. coli in the tested sample, which highlights the need for improved approaches. Hence, there is a growing demand for accurate and sensitive methods to determine the presence of viable E. coli. This paper scrutinizes various methods for detecting viable E. coli, including culture-based methods, molecular methods that target DNAs and RNAs, bacteriophage-based methods, biosensors, and other emerging technologies. The review serves as a guide for researchers seeking additional methodological options and aiding in the development of rapid and precise assays. Moving forward, it is anticipated that methods for detecting E. coli will become more stable and robust, ultimately contributing significantly to the improvement of food safety and public health.

Probiotic and postbiotic analytical methods: a perspective of available enumeration techniques

Probiotics are the largest non-herbal/traditional dietary supplements category worldwide. To be effective, a probiotic strain must be delivered viable at an adequate dose proven to deliver a health benefit. The objective of this article is to provide an overview of the various technologies available for probiotic enumeration, including a general description of each technology, their advantages and limitations, and their potential for the future of the probiotics industry. The current "gold standard" for analytical quantification of probiotics in the probiotic industry is the Plate Count method (PC). PC measures the bacterial cell's ability to proliferate into detectable colonies, thus PC relies on cultivability as a measure of viability. Although viability has widely been measured by cultivability, there has been agreement that the definition of viability is not limited to cultivability. For example, bacterial cells may exist in a state known as viable but not culturable (VBNC) where the cells lose cultivability but can maintain some of the characteristics of viable cells as well as probiotic properties. This led to questioning the association between viability and cultivability and the accuracy of PC in enumerating all the viable cells in probiotic products. PC has always been an estimate of the number of viable cells and not a true cell count. Additionally, newer probiotic categories such as Next Generation Probiotics (NGPs) are difficult to culture in routine laboratories as NGPs are often strict anaerobes with extreme sensitivity to atmospheric oxygen. Thus, accurate quantification using culture-based techniques will be complicated. Another emerging category of biotics is postbiotics, which are inanimate microorganisms, also often referred to as tyndallized or heat-killed bacteria. Obviously, culture dependent methods are not suitable for these products, and alternative methods are needed for their quantification. Different methodologies provide a more complete picture of a heterogeneous bacterial population versus PC focusing exclusively on the eventual multiplication of the cells. Alternative culture-independent techniques including real-time PCR, digital PCR and flow cytometry are discussed. These methods can measure viability beyond cultivability (i.e., by measuring cellular enzymatic activity, membrane integrity or membrane potential), and depending on how they are designed they can achieve strain-specific enumeration.

Label-free multidimensional bacterial characterization with an ultrawide detectable concentration range by microfluidic impedance cytometry

Rapid and accurate identification of bacteria is of great importance to public health in various fields, including medical diagnostics, food safety, and environmental monitoring. However, most existing bacterial detection methods have very narrow detectable concentration ranges and limited detection information, which easily leads to wrong diagnosis and treatment. This work presents a novel high-throughput microfluidic electrical impedance-based multidimensional single-bacterium profiling system for ultrawide concentration range detection and accurate differentiation of viability and Gram types of bacteria. The electrical impedance-based microfluidic cytometry is capable of multi-frequency impedance quantification, which allows profiling of the bacteria size, concentration, and membrane impedance as an indicator of bacterial viability and Gram properties in a single flow-through interrogation. It has been demonstrated that this novel impedance cytometry has an ultrawide bacterial counting range (102-108 cells per mL), and exhibits a rapid and accurate discrimination of viability and Gram types of bacteria in a label-free manner. Escherichia coli (E. coli) has been used as an analog species for the accuracy assessment of the electrical impedance-based bacterial detection system in an authentic complex beverage matrix within 24 hours. The impedance-based quantifications of viable bacteria are consistent with those obtained by the classical bacterial colony counting method (R2 = 0.996). This work could pave the way for providing a novel microfluidic cytometry system for rapid and multidimensional bacterial detection in diverse areas.

Collaborative cytometric inter-laboratory ring test for probiotics quantification

Introduction

Probiotics are live microorganisms that, when administered in adequate amounts, confer a health benefit on the host. From this definition, accurate enumeration of probiotic products is a necessity. Nonetheless, this definition does not specify the methods for assessing such viability. Colony forming units is the de facto gold standard for enumerating viable in probiotic products. The notion of microbial viability has been anchored in the concept of cultivability, which refers to a cell's capacity to replicate and form colonies on agar media. However, there is a growing consensus that the term "viability" should not be exclusively tied to the ability to cultivate cells. For example, bacterial cells can exist in a Viable But Non-Culturable (VBNC) state, characterized by the maintenance of characteristics such as membrane integrity, enzymatic activity, pH gradients, and elevated levels of rRNA, despite losing the ability to form colonies.

Methods

Herein we present the results of a collaborative inter-laboratory ring test for cytometric bacterial quantification. Specifically, membrane integrity fluorescence flow cytometry (FFC) method and the newer impedance flow cytometry (IFC) method have been used. Both methods interrogate single cells in solution for the presence of intact membranes. FFC exploits fluorochromes that reflect the presence or absence of an intact membrane. IFC probes membrane integrity in a label-free approach by detecting membrane-induced hindrances to the propagation of electricity.

Results

A performance ring-test and comparison design on the FFC method showed that the method is robust against the exchange of equipment, procedures, materials, and operators. After initial method optimization with assessments of rehydration medium, wake-up duration, and phase shift gating on the individual strains, the IFC method showed good agreement with the FFC results. Specifically, we tested 6 distinct species of probiotic bacteria (3 Lactobacillus and 3 Bifidobacterium strains) finding good agreement between FFC and IFC results in terms of total and live cells.

Discussion

Together, these results demonstrate that flow cytometry is a reliable, precise, and user-friendly culture-independent method for bacterial enumeration.

Correlating Antibiotic-Induced Dysbiosis to Clostridioides difficile Spore Germination and Host Susceptibility to Infection Using an Ex Vivo Assay

Antibiotic-induced microbiota disruption and its persistence create conditions for dysbiosis and colonization by opportunistic pathogens, such as those causing Clostridioides difficile (C. difficile) infection (CDI), which is the most severe hospital-acquired intestinal infection. Given the wide differences in microbiota across hosts and in their recovery after antibiotic treatments, there is a need for assays to assess the influence of dysbiosis and its recovery dynamics on the susceptibility of the host to CDI. Germination of C. difficile spores is a key virulence trait for the onset of CDI, which is influenced by the level of primary vs secondary bile acids in the intestinal milieu that is regulated by the microbiota composition. Herein, the germination of C. difficile spores in fecal supernatant from mice that are subject to varying degrees of antibiotic treatment is utilized as an ex vivo assay to predict intestinal dysbiosis in the host based on their susceptibility to CDI, as determined by in vivo CDI metrics in the same mouse model. Quantification of spore germination down to lower detection limits than the colony-forming assay is achieved by using impedance cytometry to count single vegetative bacteria that are identified based on their characteristic electrical physiology for distinction vs aggregated spores and cell debris in the media. As a result, germination can be quantified at earlier time points and with fewer spores for correlation to CDI outcomes. This sets the groundwork for a point-of-care tool to gauge the susceptibility of human microbiota to CDI after antibiotic treatments.

Electrical Characterization and Analysis of Single Cells and Related Applications

Biological parameters extracted from electrical signals from various body parts have been used for many years to analyze the human body and its behavior. In addition, electrical signals from cancer cell lines, normal cells, and viruses, among others, have been widely used for the detection of various diseases. Single-cell parameters such as cell and cytoplasmic conductivity, relaxation frequency, and membrane capacitance are important. There are many techniques available to characterize biomaterials, such as nanotechnology, microstrip cavity resonance measurement, etc. This article reviews single-cell isolation and sorting techniques, such as the micropipette separation method, separation and sorting system (dual electrophoretic array system), DEPArray sorting system (dielectrophoretic array system), cell selector sorting system, and microfluidic and valve devices, and discusses their respective advantages and disadvantages. Furthermore, it summarizes common single-cell electrical manipulations, such as single-cell amperometry (SCA), electrical impedance sensing (EIS), impedance flow cytometry (IFC), cell-based electrical impedance (CEI), microelectromechanical systems (MEMS), and integrated microelectrode array (IMA). The article also enumerates the application and significance of single-cell electrochemical analysis from the perspectives of CTC liquid biopsy, recombinant adenovirus, tumor cells like lung cancer DTCs (LC-DTCs), and single-cell metabolomics analysis. The paper concludes with a discussion of the current limitations faced by single-cell analysis techniques along with future directions and potential application scenarios.

Bio-inspired microfluidics: A review

Biomicrofluidics, a subdomain of microfluidics, has been inspired by several ideas from nature. However, while the basic inspiration for the same may be drawn from the living world, the translation of all relevant essential functionalities to an artificially engineered framework does not remain trivial. Here, we review the recent progress in bio-inspired microfluidic systems via harnessing the integration of experimental and simulation tools delving into the interface of engineering and biology. Development of "on-chip" technologies as well as their multifarious applications is subsequently discussed, accompanying the relevant advancements in materials and fabrication technology. Pointers toward new directions in research, including an amalgamated fusion of data-driven modeling (such as artificial intelligence and machine learning) and physics-based paradigm, to come up with a human physiological replica on a synthetic bio-chip with due accounting of personalized features, are suggested. These are likely to facilitate physiologically replicating disease modeling on an artificially engineered biochip as well as advance drug development and screening in an expedited route with the minimization of animal and human trials.

Opportunities in optical and electrical single-cell technologies to study microbial ecosystems

New techniques are revolutionizing single-cell research, allowing us to study microbes at unprecedented scales and in unparalleled depth. This review highlights the state-of-the-art technologies in single-cell analysis in microbial ecology applications, with particular attention to both optical tools, i.e., specialized use of flow cytometry and Raman spectroscopy and emerging electrical techniques. The objectives of this review include showcasing the diversity of single-cell optical approaches for studying microbiological phenomena, highlighting successful applications in understanding microbial systems, discussing emerging techniques, and encouraging the combination of established and novel approaches to address research questions. The review aims to answer key questions such as how single-cell approaches have advanced our understanding of individual and interacting cells, how they have been used to study uncultured microbes, which new analysis tools will become widespread, and how they contribute to our knowledge of ecological interactions.

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.

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.

Recent Progress of Surface-Enhanced Raman Spectroscopy for Bacteria Detection

There are various pathogenic bacteria in the surrounding living environment, which not only pose a great threat to human health but also bring huge losses to economic development. Conventional methods for bacteria detection are usually time-consuming, complicated and labor-intensive, and cannot meet the growing demands for on-site and rapid analyses. Sensitive, rapid and effective methods for pathogenic bacteria detection are necessary for environmental monitoring, food safety and infectious bacteria diagnosis. Recently, benefiting from its advantages of rapidity and high sensitivity, surface-enhanced Raman spectroscopy (SERS) has attracted significant attention in the field of bacteria detection and identification as well as drug susceptibility testing. Here, we comprehensively reviewed the latest advances in SERS technology in the field of bacteria analysis. Firstly, the mechanism of SERS detection and the fabrication of the SERS substrate were briefly introduced. Secondly, the label-free SERS applied for the identification of bacteria species was summarized in detail. Thirdly, various SERS tags for the high-sensitivity detection of bacteria were also discussed. Moreover, we emphasized the application prospects of microfluidic SERS chips in antimicrobial susceptibility testing (AST). In the end, we gave an outlook on the future development and trends of SERS in point-of-care diagnoses of bacterial infections.

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.

Parallel Impedance Cytometry for Real-Time Screening of Bacterial Single Cells from Nano- to Microscale

The benefits of impedance cytometry include high-throughput and label-free detection, while long-term calibration is required to remove the effects of the detection circuits. This study presents a novel impedance cytometry system, called parallel impedance cytometry, to simplify the calibration and analysis of the impedance signals. Furthermore, target objects can be detected even when benchmarked against similar objects. Parallel dual microchannels allow the simultaneous detection of reference and target particles in two separate microchannels, without the premixing of reference and target suspensions. The impedance pulses of both can appear separately on the opposite sides of the same time series, which have been verified via simulation and experimental results. Raw impedance signals can easily distinguish target particles from reference ones. Polystyrene beads with different sizes ranging from nano- to microscale (e.g., 500, 750 nm, 1, 2, 3, and 4.5 μm) confirm the nanosensitivity of the system. In addition, the detection of antibiotic-treated Escherichia coli cells demonstrates that our system can be used for the quantitative assessment of the dielectric properties of individual cells, as well as for the proportion of susceptible cells. Through benchmarking against untreated E. coli cells in the other channel, our method enables the discrimination of susceptible cells from others and the comparison of susceptible and insusceptible cells in the target suspension. Those findings indicate that the parallel impedance cytometry can greatly facilitate the measurement and calibration of the impedances of various particles or cells and provide a means to compare their dielectric properties.

Digital models in biotechnology: Towards multi-scale integration and implementation

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

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.

Deep Learning Assisted Microfluidic Impedance Flow Cytometry for Label-free Foodborne Bacteria Analysis and Classification. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:7087-7090. [PMID: 34892734 DOI: 10.1109/embc46164.2021.9630684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

According to the urgent need for rapid detection and identification of foodborne bacteria to prevent public health event, a microfluidic electrical impedance flow cytometry assisted with convolutional neural network (ConvNet) based deep learning algorithm was proposed in this study to analyze the impedance signals of bacteria. With the assistance of the deep learning algorithm, Escherichia coli (EPEC), Salmonella enteritidis (SE) and Vibrio parahaemolyticus (VP) were identified with an accuracy of 100%. The proposed impedance based analysis system can be potentially applied for pre-classification of different subtypes of bacteria in a label-free manner.Clinical Relevance-The whole platform can be miniaturized and applied for point-of-care testing (POCT) of pathogenic bacteria detection.

Impedance flow cytometry for viability analysis of Corynebacterium glutamicum

Corynebacterium glutamicum efficiently produces glutamate when growth is inhibited. Analyses of viability in this non-growing state requires time consuming plating and determination of colony forming units. We here establish impedance flow cytometry measurements to assess the viability of non-growing, glutamate producing C. glutamicum cultures within minutes.

The diagnostic tools for viable but nonculturable pathogens in the food industry: Current status and future prospects

Viable but nonculturable (VBNC) microorganisms have been recognized as pathogenic contaminants in foods and environments. The failure of VBNC cells to form the visible colonies hinders the ability to use conventional media for their detection. Efficient and rapid detection of pathogens in the VBNC state is a prerequisite to ensure the food safety and public health. Despite their nonculturability, VBNC cells have distinct characteristics, such as morphology, metabolism, chemical composition, and gene and protein expression, that have been used as the basis for the development of abundant diagnostic tools. This review covers the current status and advances in various approaches for examining microorganisms in the VBNC state, including but not limited to the methodological aspects, advantages, and drawbacks of each technique. Existing methods, such as direct viable count, SYTO/PI dual staining, and propidium monoazide quantitative polymerase chain reaction (PCR), as well as some techniques with potential to be applied in the future, such as digital PCR, enhanced-surface Raman spectroscopy, and impedance-based techniques, are summarized in depth. Finally, future prospects for the one-step detection of VBNC bacteria are proposed and discussed. We believe that this review can provide more optional methods for researchers and promote the development of rapid, accurate detecting methods, and for inspectors, the diagnostic tools can provide data to undertake risk analysis of VBNC cells.