Rapid determination of general cell status, cell viability, and optimal harvest time in eukaryotic cell cultures by impedance flow cytometry

Capacitance sensors in cell-based bioprocesses: online monitoring of biomass and more

Biocapacitance measurement has emerged as a widely used technique for monitoring bioprocesses that involve living cells. Over time, hardware and software developments have enabled this method to move from food towards biopharma industries for improved characterisation, monitoring and control of the bioprocess, even in strictly regulated production environments. In alignment with the general trends in biopharma towards new modalities such as virus-based and cell-based therapies, biocapacitance measurement is entering this area and provides new opportunities for process development and control. Based on the recent progress, the authors strongly believe that even though biocapacitance measurement is a mature, established technology for online biomass monitoring, the nearest future will bring its new and exciting developments and applications that will enhance bioprocess understanding and bring new solutions for enhanced process understanding, monitoring and control.

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.

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.

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

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

Portable impedance-sensing device for microorganism characterization in the field

A variety of biosensors have been proposed to quickly detect and measure the properties of individual microorganisms among heterogeneous populations, but challenges related to cost, portability, stability, sensitivity, and power consumption limit their applicability. This study proposes a portable microfluidic device based on impedance flow-cytometry and electrical impedance spectroscopy that can detect and quantify the size of microparticles larger than 45 µm, such as algae and microplastics. The system is low cost ($300), portable (5 cm [Formula: see text] 5 cm), low-power (1.2 W), and easily fabricated utilizing a 3D-printer and industrial printed circuit board technology. The main novelty we demonstrate is the use of square wave excitation signal for impedance measurements with quadrature phase-sensitive detectors. A linked algorithm removes the errors associated to higher order harmonics. After validating the performance of the device for complex impedance models, we used it to detect and differentiate between polyethylene microbeads of sizes between 63 and 83 µm, and buccal cells between 45 and 70 µm. A precision of 3% is reported for the measured impedance and a minimum size of 45 µm is reported for the particle characterization.

Rapid Phenotypic Antimicrobial Susceptibility Testing Using a Coulter Counter and Proliferation Rate Discrepancy

The rapid determination of antimicrobial susceptibility and evidence-based antimicrobial prescription is necessary to combat widespread antimicrobial resistance and promote effectively treatment for bacterial infections. This study developed a rapid phenotypic antimicrobial susceptibility determination method competent for seamless clinical implementation. A laboratory-friendly Coulter counter-based antimicrobial susceptibility testing (CAST) was developed and integrated with bacterial incubation, population growth monitoring, and result analysis to quantitatively detect differences in bacterial growth between resistant and susceptible strains following a 2 h exposure to antimicrobial agents. The distinct proliferation rates of the different strains enabled the rapid determination of their antimicrobial susceptibility phenotypes. We evaluated the performance efficacy of CAST for 74 clinically isolated Enterobacteriaceae subjected to 15 antimicrobials. The results were consistent with those obtained via the 24 h broth microdilution method, showing 90.18% absolute categorical agreement.

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.

Circular RNA hsa_circ_0001658 regulates apoptosis and autophagy in gastric cancer through microRNA-182/Ras-related protein Rab-10 signaling axis

Gastric cancer (GC) is a tumor with high incidence and lack of early diagnostic markers. The aim of this study was to explore novel regulatory circular RNAs (circRNAs) in GC and their underlying mechanisms. Differentially expressed circRNAs were analyzed using the Gene Expression Omnibus (GEO). mRNA and miRNA expression levels were determined using real-time reverse transcription polymerase chain reaction (RT-qPCR). Protein expression was detected using Western blotting. Cellular functions were evaluated using the cell counting kit-8 (CCK-8) assay and flow cytometry analysis. Immunofluorescence analysis was used to visually identify microtubule-associated protein 1 light chain 3 (LC3) puncta on a per-cell basis. Furthermore, dual-luciferase reporter and RNA pull-down assays were performed to verify the interaction between microRNA (miR)-182 and circ_0001658/Ras-related protein Rab-10 (RAB10). Circ_0001658 was identified to be aberrantly expressed in GC tissues and was demonstrated in GC cell lines (AGS and HGC27) in vitro. MiR-182 bound to circ_0001658 and RAB10. Circ_0001658 and RAB10 were upregulated, whereas miR-182 was suppressed in AGS and HGC27 cells. GC cell viability and autophagy were inhibited and apoptosis was promoted after circ_0001658 knockdown, and the cellular functions were reversed by downregulating miR-182. Moreover, upregulated RAB10 neutralized the effects of miR-182 on cell viability, autophagy, and apoptosis of GC cells. Silencing circ_0001658 restrained cell viability, suppressed autophagy, and promoted apoptosis of GC cells by sponging miR-182 to suppress the expression of RAB10. Therefore, circ_0001658 may be a potential therapeutic target for GC.

Development of a flow cytometry-based plating-free system for strain engineering in industrial fungi

Recent technical advances regarding filamentous fungi have accelerated the engineering of fungal-based production and benefited basic science. However, challenges still remain and limit the speed of fungal applications. For example, high-throughput technologies tailored to filamentous fungi are not yet commonly available for genetic modification. The currently used fungal genetic manipulations are time-consuming and laborious. Here, we developed a flow cytometry-based plating-free system to directly screen and isolate the transformed protoplasts in industrial fungi Myceliophthora thermophila and Aspergillus niger. This system combines genetic engineering via the 2A peptide and the CRISPR-Cas9 system, strain screening by flow cytometry, and direct sorting of colonies for deep-well-plate incubation and phenotypic analysis while avoiding culturing transformed protoplasts in plates, colony picking, conidiation, and cultivation. As a proof of concept, we successfully applied this system to generate the glucoamylase-hyperproducing strains MtYM6 and AnLM3 in M. thermophila and A. niger, respectively. Notably, the protein secretion level and enzyme activities in MtYM6 were 17.3- and 25.1-fold higher than in the host strain. Overall, these findings suggest that the flow cytometry-based plating-free system can be a convenient and efficient tool for strain engineering in fungal biotechnology. We expect this system to facilitate improvements of filamentous fungal strains for industrial applications. KEY POINTS: • Development of a flow cytometry-based plating-free (FCPF) system is presented. • Application of FCPF system in M. thermophila and A. niger for glucoamylase platform. • Hyper-produced strains MtYM6 and AnLM3 for glucoamylase production are generated.

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.

Study of Oenological Fermentation: Which Strategy and Which Tools?

Wine fermentation is a specific and complex research subject and its control is essential to ensure full process completion while improving wine quality. It displays several specificities, in particular, (i) musts with a very high sugar content, low pH, and some limiting nutrients, as well as a great variability in must composition according to the year, grape variety, and so on; (ii) atypical fermentation conditions with non-isothermal temperature profiles, a quasi-anaerobiosis and legal constraints with a limited and predefined list of authorized operations. New challenges have emerged, related to the increasing diversity of commercially available yeast strains; the fluctuating composition of musts, particularly owing to climate change; and sustainability, which has become a key issue. This paper synthesizes approaches implemented to address all these issues. It details the example of our laboratory that, for many years, has been developing an integrated approach to study yeast diversity, understand their metabolism, and develop new fermentation control strategies. This approach requires the development of specific fermentation devices to study yeast metabolism in a controlled environment that mimics practical conditions and to develop original fermentation control strategies. All these tools are described here, together with their role in the overall scientific strategy and complementary approaches in the literature.

Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions

Microbial biomass concentration is a key bioprocess parameter, estimated using various labor, operator and process cross-sensitive techniques, analyzed in a broad context and therefore the subject of correct interpretation. In this paper, the authors present the results of P. pastoris cell density estimation based on off-line (optical density, wet/dry cell weight concentration), in-situ (turbidity, permittivity), and soft-sensor (off-gas O₂/CO₂, alkali consumption) techniques. Cultivations were performed in a 5 L oxygen-enriched stirred tank bioreactor. The experimental plan determined varying aeration rates/levels, glycerol or methanol substrates, residual methanol levels, and temperature. In total, results from 13 up to 150 g (dry cell weight)/L cultivation runs were analyzed. Linear and exponential correlation models were identified for the turbidity sensor signal and dry cell weight concentration (DCW). Evaluated linear correlation between permittivity and DCW in the glycerol consumption phase (<60 g/L) and medium (for Mut⁺ strain) to significant (for Mut^S strain) linearity decline for methanol consumption phase. DCW and permittivity-based biomass estimates used for soft-sensor parameters identification. Dataset consisting from 4 Mut⁺ strain cultivation experiments used for estimation quality (expressed in NRMSE) comparison for turbidity-based (8%), permittivity-based (11%), O₂ uptake-based (10%), CO₂ production-based (13%), and alkali consumption-based (8%) biomass estimates. Additionally, the authors present a novel solution (algorithm) for uncommon in-situ turbidity and permittivity sensor signal shift (caused by the intensive stirrer rate change and antifoam agent addition) on-line identification and minimization. The sensor signal filtering method leads to about 5-fold and 2-fold minimized biomass estimate drifts for turbidity- and permittivity-based biomass estimates, respectively.

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.

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

Bacteria detection, counting and analysis is of great importance in several fields. When viability plays a major role in decision making, the counting of colony-forming units grown on agar plates remains the gold standard. However, because plate counts depend on the growth of the bacteria, it is a slow procedure and only works with culturable species. Impedance flow cytometry (IFC) is a promising technology for particle detection, counting and characterization. It relies on the perturbation of an electric field by particles flowing through a microfluidic channel. The perturbation is directly related to the electrical properties of the particles, and therefore provides information about their composition and structure. In this work we investigate whether IFC can be used to differentiate viable cells from inactivated cells. Our findings demonstrate that the specific viability state of the bacteria has to be considered, but that with proper characterization thresholds, IFC can be used to classify bacterial viability states. By using three different inactivation methods-ethanol, heat and autoclavation-we have been able to show that the impedance response of Escherichia coli depends on its viability state, but that the specific response depends on the inactivation method. With these findings we expect to be able to optimize IFC for more reliable bacteria detection and counting in the future.

Impedance flow cytometry allows the early prediction of embryo yields in wheat (Triticum aestivum L.) microspore cultures

Haplomethods are key biotechnological tools that make it possible to rapidly produce perfectly homozygous lines, speeding up plant breeding programs. Under specific stress conditions, microspores are reprogrammed toward sporophytic pathways, leading to embryo formation. Various endogenous and exogenous factors affect embryo yield in androgenesis, so the improvement of androgenesis efficiency requires the development of early, reliable and robust reactivity markers. During the last decade, numerous cytological, cellular and biochemical approaches were carried out to finely characterize microspore development and fate during androgenesis. However, the different available markers are often species-dependent, and their development and application are time-consuming and cumbersome. In this study, we show the suitable use of impedance flow cytometry (IFC) to develop new robust, reliable and strong markers of androgenesis reactivity in wheat, leading to: (i) routine monitoring of the viability of heterogeneous cell cultures; (ii) quick and simple evaluation of stress treatment efficiency; and (iii) early prediction of embryo yields from microspore suspensions. IFC can therefore provide the fine characterization of all of the microspore developmental pathways that occur in a cell suspension, for embryogenic microspores as well as pollen-like microspores. IFC technology has become a very useful tool to track and characterize wheat microspores in androgenesis, but can also be adapted to other species and other in vitro cell culture systems.

Label-free impedance flow cytometry for nanotoxicity screening

The development of reliable and cost-efficient methods to assess the toxicity of nanomaterials (NMs) is critical for the proper identification of their impact on human health and for ensuring a safe progress of nanotechnology. In this study, we investigated the reliability and applicability of label-free impedance flow cytometry (IFC) for in vitro nanotoxicity screening, which avoids time-consuming labelling steps and minimizes possible NM-induced interferences. U937 human lymphoma cells were exposed for 24 h to eight different nanomaterials at five concentrations (2, 10, 20, 50, and 100 μg/mL). The NMs' effect on viability was measured using IFC and the results were compared to those obtained by trypan blue (TB) dye exclusion and conventional flow cytometry (FC). To discriminate viable from necrotic cells, the IFC measurement settings regarding signal trigger level and frequency, as well as the buffer composition, were optimised. A clear discrimination between viable and necrotic cells was obtained at 6 MHz in a sucrose-based measurement buffer. Nanomaterial-induced interferences were not detected for IFC. The IFC and TB assay results were in accordance for all NMs. The IFC was found to be robust, reliable and less prone to interferences due to the advantage of being label-free.