Cell Cytometry: Review and Perspective on Biotechnological Advances

Advances in Hematology Analyzers Technology

The evolution of complete blood count (CBC) methodology from manual calculations to sophisticated high throughput hematology analyzers is the focus of this article. In recent years, hematology testing has greatly benefitted from the combination of various technologies with automated neural networks. In addition to an increasing complexity of the laboratory instrumentation, there is a demand on point of care CBC testing with its benefits and drawbacks. This article highlights exciting advancements of hematology testing from the past to the present and into the future.

Enhanced photodynamic inactivation against Escherichia coli O157:H7 provided by chitosan/curcumin coating and its application in food contact surfaces

Sterilisation technologies are essential to eliminate foodborne pathogens from food contact surfaces. However, most of the current sterilisation methods involve high energy and chemical consumption. In this study, a photodynamic inactivation coating featuring excellent antibacterial activity was prepared by dispersing curcumin as a plant-based photosensitiser in a chitosan solution. The coating generated abundant reactive oxygen species (ROS) after light irradiation at 420 nm, which eradicated ≥99.999 % of Escherichia coli O157:H7. It was also found that ROS damaged the cell membrane, leading to the leakage of cell contents and cell shrinkage on the basis of chitosan. In addition, the production of ROS first excited the bacterial antioxidant defence system resulting in the increase of peroxidase (POD) and superoxide dismutase (SOD). ROS levels exceed its capacity, causing damage to the defence system and further oxidative decomposition of large molecules, such as DNA and proteins, eventually leading to the death of E. coli O157:H7. We also found the curcumin/chitosan coating could effectively remove E. coli O157:H7 biofilms by oxidative of extracellular polysaccharides and proteins. All the contributors made the chitosan/curcumin coating an efficient detergent comparable with HClO.

CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny

BACKGROUND

The rapid advancement of new genomic sequencing technology has enabled the development of multi-omic single-cell sequencing assays. These assays profile multiple modalities in the same cell and can often yield new insights not revealed with a single modality. For example, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) simultaneously profiles the RNA transcriptome and the surface protein expression. The surface protein markers in CITE-Seq can be used to identify cell populations similar to the iterative filtration process in flow cytometry, also called "gating", and is an essential step for downstream analyses and data interpretation. While several packages allow users to interactively gate cells, they often do not process multi-omic sequencing datasets and may require writing redundant code to specify gate boundaries. To streamline the gating process, we developed CITEViz which allows users to interactively gate cells in Seurat-processed CITE-Seq data. CITEViz can also visualize basic quality control (QC) metrics allowing for a rapid and holistic evaluation of CITE-Seq data.

RESULTS

We applied CITEViz to a peripheral blood mononuclear cell CITE-Seq dataset and gated for several major blood cell populations (CD14 monocytes, CD4 T cells, CD8 T cells, NK cells, B cells, and platelets) using canonical surface protein markers. The visualization features of CITEViz were used to investigate cellular heterogeneity in CD14 and CD16-expressing monocytes and to detect differential numbers of detected antibodies per patient donor. These results highlight the utility of CITEViz to enable the robust classification of single cell populations.

CONCLUSIONS

CITEViz is an R-Shiny app that standardizes the gating workflow in CITE-Seq data for efficient classification of cell populations. Its secondary function is to generate basic feature plots and QC figures specific to multi-omic data. The user interface and internal workflow of CITEViz uniquely work together to produce an organized workflow and sensible data structures for easy data retrieval. This package leverages the strengths of biologists and computational scientists to assess and analyze multi-omic single-cell datasets. In conclusion, CITEViz streamlines the flow cytometry gating workflow in CITE-Seq data to help facilitate novel hypothesis generation.

Evaluation of the cytotoxicity, antioxidant activity, and molecular docking of biogenic zinc oxide nanoparticles derived from pumpkin seeds

This study aimed to investigate the characterization of zinc oxide nanoparticles (ZnONPs) produced from Cucurbita pepo L. (pumpkin seeds) and their selective cytotoxic effectiveness on human colon cancer cells (HCT 116) and African Green Monkey Kidney, Vero cells. The study also investigated the antioxidant activity of ZnONPs. The study also examined ZnONPs' antioxidant properties. This was motivated by the limited research on the comparative cytotoxic effects of ZnO NPs on normal and HCT116 cells. The ZnO NPs were characterized using Fourier-transform infrared spectroscopy (FTIR), Thermogravimetric Analysis (TGA), Transmission Electron Microscope/Selected Area Electron Diffraction (TEM/SAED), and Scanning Electron Microscope-Energy Dispersive X-ray (SEM-EDX) for determination of chemical fingerprinting, heat stability, size, and morphology of the elements, respectively. Based on the results, ZnO NPs from pumpkins were found to be less than 5 μm and agglomerates in nature. Furthermore, the ZnO NPs fingerprinting and SEM-EDX element analysis were similar to previous literature, suggesting the sample was proven as ZnO NPs. The ZnO NPs also stable at a temperature of 380°C indicating that the green material is quite robust at 60-400°C. The cell viability of Vero cells and HCT 116 cell line were measured at two different time points (24 and 48 h) to assess the cytotoxicity effects of ZnO NP on these cells using AlamarBlue assay. Cytotoxic results have shown that ZnO NPs did not inhibit Vero cells but were slightly toxic to cancer cells, with a dose-response curve IC50 = ~409.7 μg/mL. This green synthesis of ZnO NPs was found to be non-toxic to normal cells but has a slight cytotoxicity effect on HCT 116 cells. A theoretical study used molecular docking to investigate nanoparticle interaction with cyclin-dependent kinase 2 (CDK2), exploring its mechanism in inhibiting CDK2's role in cancer. Further study should be carried out to determine suitable concentrations for cytotoxicity studies. Additionally, DPPH has a significant antioxidant capacity, with an IC50 of 142.857 μg/mL. RESEARCH HIGHLIGHTS: Pumpkin seed extracts facilitated a rapid, high-yielding, and environmentally friendly synthesis of ZnO nanoparticles. Spectrophotometric analysis was used to investigate the optical properties, scalability, size, shape, dispersity, and stability of ZnO NPs. The cytotoxicity of ZnO NPs on Vero and HCT 116 cells was assessed, showing no inhibition of Vero cells and cytotoxicity of cancer cells. The DPPH assay was also used to investigate the antioxidant potential of biogenic nanoparticles. A molecular docking study was performed to investigate the interaction of ZnO NPs with CDK2 and to explore the mechanism by which they inhibit CDK2's role in cancer.

Flow cytometry: Aspects and application in plant and biological science

Flow cytometry is a potent method that enables the quick and concurrent investigation of several characteristics of single cells in solution. Photodiodes or photomultiplier tubes are employed to detect the dispersed and fluorescent light signals that are produced by the laser beam as it passes through the cells. Photodetectors transform the light signals produced by the laser into electrical impulses. A computer then analyses these electrical impulses to identify and measure the various cell populations depending on their fluorescence or light scattering characteristics. Based on their fluorescence or light scattering properties, cell populations can be examined and/or isolated. This review covers the basic principle, components, working and specific biological applications of flow cytometry, including studies on plant, cell and molecular biology and methods employed for data processing and interpretation as well as the potential future relevance of this methodology in light of retrospective analysis and recent advancements in flow cytometry.

Identification, sorting and profiling of functional killer cells via the capture of fluorescent target-cell lysate

Assays for assessing cell-mediated cytotoxicity are largely target-cell-centric and cannot identify and isolate subpopulations of cytotoxic effector cells. Here we describe an assay compatible with flow cytometry for the accurate identification and sorting of functional killer-cell subpopulations in co-cultures. The assay, which we named PAINTKiller (for 'proximity affinity intracellular transfer identification of killer cells'), relies on the detection of an intracellular fluorescent protein 'painted' by a lysed cell on the surface of the lysing cytotoxic cell (specifically, on cell lysis the intracellular fluorescein derivative carboxyfluorescein succinimidyl ester is captured on the surface of the natural killer cell by an antibody for anti-fluorescein isothiocyanate linked to an antibody for the pan-leucocyte surface receptor CD45). The assay can be integrated with single-cell RNA sequencing for the analysis of molecular pathways associated with cell cytotoxicity and may be used to uncover correlates of functional immune responses.

An integrated centrifugal microfluidic strategy for point-of-care complete blood counting

Centrifugal microfluidics holds the potential to revolutionize point-of-care (POC) testing by simplifying laboratory tests through automating fluid and cell manipulation within microfluidic channels. This technology can facilitate blood testing, the most frequent clinical test, at the POC. However, an integrated centrifugal microfluidic device for complete blood counting (CBC) has not yet been fully realized. To address this, we propose an integrated portable system comprising a centrifuge and a hybrid microfluidic disc specifically designed for CBC analysis at the POC. The disc enables the implementation of various spin profiles in different stages of CBC to facilitate in-situ cell separation, solution metering and mixing, and differential cell counting. Furthermore, our system is coupled with a custom script that automates the process and ensures precise quantification of cells using light and fluorescent images captured from the detection chamber of the disc. We demonstrate a close correlation between the proposed method and the hematology analyzer, considered the gold standard, for quantifying hematocrit (R2 = 0.99), white blood cell count (R2 = 0.98), white blood cell differential count (granulocyte/agranulocyte; R2 = 0.89), red blood cell count (R2 = 0.97), and mean corpuscular volume (R2 = 0.94). The integration of our portable system offers significant advantages, enabling more accessible and affordable CBC testing at the POC. Considering the simplicity, affordability (∼$250 capital cost and <$2 operational cost per test), as well as low power consumption (>100 tests using a typical 24 V/10 Ah battery), this system has the potential to enhance healthcare delivery, particularly in resource-limited settings and remote areas where access to traditional laboratory facilities is limited.

Cellaca® PLX image cytometer as an alternative for immunophenotyping, GFP/RFP transfection efficiencies, and apoptosis analysis

Cell and gene therapy is a fast-growing field for cancer therapeutics requiring reliable instrumentation and technologies. Key parameters essential for satisfying Chemistry Manufacturing and Controls criteria standards are routinely performed using flow cytometry. Recently, image cytometry was developed for cell characterization and cell-based assays but had not yet demonstrated sufficient sensitivity for surface marker detection. We developed the Cellaca® PLX image cytometry system and the respective methodologies required for immunophenotyping, GFP and RFP transfection/transduction efficiencies, and cell health analyses for routine cell characterization. All samples tested were compared directly to results from the CytoFLEX flow cytometer. PBMCs were stained with T-cell surface markers for immunophenotyping, and results show highly comparable CD3, CD4, and CD8 populations (within 5 %). GFP- or RFP-expressing cell lines were analyzed for transfection/transduction efficiencies, and the percentage positive cells and respective viabilities were equivalent on both systems. Staurosporine-treated Jurkat cells were stained for apoptotic markers, where annexin V and caspase-3 positive cells were within 5 % comparing both instruments. The proposed system may provide a complementary tool for performing routine cell-based experiments with improved efficiency and sensitivity compared to prior image cytometers, which may be significantly valuable to the cell and gene therapy field.

Using dielectrophoretic spectra to identify and separate viable yeast cells

Immotile yeast cells were transiently moved in nonuniform sinusoidal electric fields using multiple pairs of micro-parallel cylindrical electrodes equipped with a sequential signal generator (SSG) to analyze cell viability at a clinical scale for the brewery/fermentation industry. Living yeast cells of Saccharomyces cerevisiae during the exponential-stationary phase, with a cell density of 1.15 × 105 cells mL-1 were suspended in sucrose medium. The conductivity (σs) was adjusted to 0.01 S m-1 with added KCl. Cells exposed in electric field strengths ranging from 32.89 to 40.98 kV m-1, exhibited positive dielectrophoresis (pDEP) with the lower critical frequencies (LCF) at 85.72 ± 3.59 kHz. The optimized value of LCF was shifted upwards to 780.00 ± 83.67 kHz when σswas increased to 0.10 S m-1. Dielectrophoretic and LCF spectra (translational speed of cells vs. electric field frequencies) of yeast suspensions during positive dielectrophoresis were analyzed in terms of the dielectric properties of the cell membrane and cytoplasm which reflect yeast cell viability and metabolic health status. The dielectrophoretic collection yield of cells using positive dielectrophoresis was reported on the monitor of sequential signal generator software to evaluate the number of living and dead cells through a real-time image processing analyzer. The spectra of both positive dielectrophoresis of the living and dead cells had distinguishable dielectric properties. The conductivity of the yeast cytoplasm (σc) of the dead cells was significantly less (≈ ≤ 0.05 S m-1) than that of the living yeast cells which typically had a cytoplasmic conductivity of ≈ 0.2 S m-1. This difference between viable and non-viable cells is sufficient for cell separation procedures. KEY POINTS: • Dielectrophoresis can be used to separate viable and non-viable yeast cells, • Cellular dielectric properties can be derived from the analysis of their dielectric spectra, • Cytoplasmic conductivity of viable cells is ≈ 0.2 S m-1 while that of non-viable cells ≈ ≤ 0.05 S m-1.

Impact of rising seawater temperature on a phagocytic cell population during V. parahaemolyticus infection in the sea anemone E. pallida

Climate change is increasing ocean temperatures and consequently impacts marine life (e.g., bacterial communities). In this context, studying host-pathogen interactions in marine organisms is becoming increasingly important, not only for ecological conservation, but also to reduce economic loss due to mass mortalities in cultured species. In this study, we used Exaiptasia pallida (E. pallida), an anemone, as an emerging marine model to better understand the effect of rising temperatures on the infection induced by the pathogenic marine bacterium Vibrio parahaemolyticus. The effect of temperature on E. pallida was examined at 6, 24, or 30 h after bath inoculation with 108 CFU of V. parahaemolyticus expressing GFP (Vp-GFP) at 27°C (husbandry temperature) or 31°C (heat stress). Morphological observations of E. pallida and their Hsps expression demonstrated heat stress induced increasing damage to anemones. The kinetics of the infections revealed that Vp-GFP were localized on the surface of the ectoderm and in the mucus during the first hours of infection and in the mesenterial filaments thereafter. To better identify the E. pallida cells targeted by Vp-GFP infection, we used spectral flow cytometry. E. pallida cell types were identified based on their autofluorescent properties. corresponding to different cell types (algae and cnidocytes). We identified an AF10 population whose autofluorescent spectrum was identical to that of human monocytes/macrophage, suggesting that this spectral print could be the hallmark of phagocytic cells called "amebocytes''. AF10 autofluorescent cells had a high capacity to phagocytize Vp-GFP, suggesting their possible role in fighting infection. This was confirmed by microscopy using sorted AF10 and GFP-positive cells (AF10+/GFP+). The number of AF10+/GFP+ cells were reduced at 31°C, demonstrating that increased temperature not only damages tissue but also affects the immune response of E. pallida. In conclusion, our study provides a springboard for more comprehensive studies of immune defense in marine organisms and paves the way for future studies of the dynamics, activation patterns, and functional responses of immune cells when encountering pathogens.

Projection Micro-Stereolithography to Manufacture a Biocompatible Micro-Optofluidic Device for Cell Concentration Monitoring

In this work, a 3D printed biocompatible micro-optofluidic (MoF) device for two-phase flow monitoring is presented. Both an air-water bi-phase flow and a two-phase mixture composed of micrometric cells suspended on a liquid solution were successfully controlled and monitored through its use. To manufacture the MoF device, a highly innovative microprecision 3D printing technique was used named Projection Microstereolithography (PμSL) in combination with the use of a novel 3D printable photocurable resin suitable for biological and biomedical applications. The concentration monitoring of biological fluids relies on the absorption phenomenon. More precisely, the nature of the transmission of the light strictly depends on the cell concentration: the higher the cell concentration, the lower the optical acquired signal. To achieve this, the microfluidic T-junction device was designed with two micrometric slots for the optical fibers' insertion, needed to acquire the light signal. In fact, both the micro-optical and the microfluidic components were integrated within the developed device. To assess the suitability of the selected biocompatible transparent resin for optical detection relying on the selected working principle (absorption phenomenon), a comparison between a two-phase flow process detected inside a previously fully characterized micro-optofluidic device made of a nonbiocompatible high-performance resin (HTL resin) and the same made of the biocompatible one (BIO resin) was carried out. In this way, it was possible to highlight the main differences between the two different resin grades, which were further justified with proper chemical analysis of the used resins and their hydrophilic/hydrophobic nature via static water contact angle measurements. A wide experimental campaign was performed for the biocompatible device manufactured through the PμSL technique in different operative conditions, i.e., different concentrations of eukaryotic yeast cells of Saccharomyces cerevisiae (with a diameter of 5 μm) suspended on a PBS (phosphate-buffered saline) solution. The performed analyses revealed that the selected photocurable transparent biocompatible resin for the manufactured device can be used for cell concentration monitoring by using ad hoc 3D printed micro-optofluidic devices. In fact, by means of an optical detection system and using the optimized operating conditions, i.e., the optimal values of the flow rate FR=0.1 mL/min and laser input power P∈{1,3} mW, we were able to discriminate between biological fluids with different concentrations of suspended cells with a robust working ability R2=0.9874 and Radj2=0.9811.

Study of hesperetin effect on modulating transcription levels of MLH1 and MSH2 genes in SKBR3 breast cancer cell line

Hesperetin (HSP), a flavonoid, has been validated to modify gene expression and function as an epigenetic agent to stop the development of breast carcinoma cells. HSP was investigated in this research to evaluate the expression of the MLH1 and MSH2 genes in cancerous breast cell lines (SKBR3) and healthy cell lines (MCF-11A) after exposure to different dosages (200, 400, and 600 µM/mL) of HSP. After 48 h of exposure, SKBR3's half-maximal inhibitory concentration was 289.6 µM/mL and MCF-10A's was 855.4 µM/mL. The research found that increasing HSP concentrations were closely correlated with an increase in MLH1 gene levels in the SKBR3 cell line, as shown by median and percentile values. HSP therapy caused the MLH1 gene expression to substantially vary in different groups, and in the SKBR3 cell line, MSH2 gene expressions were elevated in a dose-escalating manner. Moreover, HSP also raised the number of apoptotic cells, with the fraction of apoptotic cells escalating substantially at doses of 400 and 600 µM/mL. The outcomes suggested that HSP has the potential to be utilized as a therapeutic intervention for breast cancer, as it can induce apoptosis and reduce cell viability.

Computer vision meets microfluidics: a label-free method for high-throughput cell analysis

In this paper, we review the integration of microfluidic chips and computer vision, which has great potential to advance research in the life sciences and biology, particularly in the analysis of cell imaging data. Microfluidic chips enable the generation of large amounts of visual data at the single-cell level, while computer vision techniques can rapidly process and analyze these data to extract valuable information about cellular health and function. One of the key advantages of this integrative approach is that it allows for noninvasive and low-damage cellular characterization, which is important for studying delicate or fragile microbial cells. The use of microfluidic chips provides a highly controlled environment for cell growth and manipulation, minimizes experimental variability and improves the accuracy of data analysis. Computer vision can be used to recognize and analyze target species within heterogeneous microbial populations, which is important for understanding the physiological status of cells in complex biological systems. As hardware and artificial intelligence algorithms continue to improve, computer vision is expected to become an increasingly powerful tool for in situ cell analysis. The use of microelectromechanical devices in combination with microfluidic chips and computer vision could enable the development of label-free, automatic, low-cost, and fast cellular information recognition and the high-throughput analysis of cellular responses to different compounds, for broad applications in fields such as drug discovery, diagnostics, and personalized medicine.

High-Throughput Single-Cell Analysis of Nanoparticle-Cell Interactions

Understanding nanoparticle-cell interactions at single-nanoparticle and single-cell resolutions is crucial to improving the design of next-generation nanoparticles for safer, more effective, and more efficient applications in nanomedicine. This review focuses on recent advances in the continuous high-throughput analysis of nanoparticle-cell interactions at the single-cell level. We highlight and discuss the current trends in continual flow high-throughput methods for analyzing single cells, such as advanced flow cytometry techniques and inductively coupled plasma mass spectrometry methods, as well as their intersection in the form of mass cytometry. This review further discusses the challenges and opportunities with current single-cell analysis approaches and provides proposed directions for innovation in the high-throughput analysis of nanoparticle-cell interactions.

YOLOv5-FPN: A Robust Framework for Multi-Sized Cell Counting in Fluorescence Images

Cell counting in fluorescence microscopy is an essential task in biomedical research for analyzing cellular dynamics and studying disease progression. Traditional methods for cell counting involve manual counting or threshold-based segmentation, which are time-consuming and prone to human error. Recently, deep learning-based object detection methods have shown promising results in automating cell counting tasks. However, the existing methods mainly focus on segmentation-based techniques that require a large amount of labeled data and extensive computational resources. In this paper, we propose a novel approach to detect and count multiple-size cells in a fluorescence image slide using You Only Look Once version 5 (YOLOv5) with a feature pyramid network (FPN). Our proposed method can efficiently detect multiple cells with different sizes in a single image, eliminating the need for pixel-level segmentation. We show that our method outperforms state-of-the-art segmentation-based approaches in terms of accuracy and computational efficiency. The experimental results on publicly available datasets demonstrate that our proposed approach achieves an average precision of 0.8 and a processing time of 43.9 ms per image. Our approach addresses the research gap in the literature by providing a more efficient and accurate method for cell counting in fluorescence microscopy that requires less computational resources and labeled data.

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

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

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.

Microalgae identification: Future of image processing and digital algorithm

The identification of microalgae species is an important tool in scientific research and commercial application to prevent harmful algae blooms (HABs) and recognizing potential microalgae strains for the bioaccumulation of valuable bioactive ingredients. The aim of this study is to incorporate rapid, high-accuracy, reliable, low-cost, simple, and state-of-the-art identification methods. Thus, increasing the possibility for the development of potential recognition applications, that could identify toxic-producing and valuable microalgae strains. Recently, deep learning (DL) has brought the study of microalgae species identification to a much higher depth of efficiency and accuracy. In doing so, this review paper emphasizes the significance of microalgae identification, and various forms of machine learning algorithms for image classification, followed by image pre-processing techniques, feature extraction, and selection for further classification accuracy. Future prospects over the challenges and improvements of potential DL classification model development, application in microalgae recognition, and image capturing technologies are discussed accordingly.

Ultraportable Flow Cytometer Based on an All-Glass Microfluidic Chip

The flow cytometer has become a powerful and widely accepted measurement device in both biological studies and clinical diagnostics. The application of the flow cytometer in emerging point-of-care scenarios, such as instant detection in remote areas and emergency diagnosis, requires a significant reduction in physical dimension, cost, and power consumption. This requirement promotes studies to develop portable flow cytometers, mostly based on the utilization of polymer microfluidic chips. However, due to the relatively poor optical performance of polymer materials, existing microfluidic flow cytometers are incapable of accurate blood analysis, such as the four-part leukocyte differential count, which is necessary to monitor the immune system and to assess the risk of allergic inflammation or viral infection. To address this issue, an ultraportable flow cytometer based on an all-glass microfluidic chip (AG-UFCM) has been developed in this study. Compared with that of a typical commercial flow cytometer (BD FACSAria III), the volume of the AG-UFCM was reduced by 90 times (from 720 to 8 L). A two-step laser processing was employed to fabricate an all-glass microfluidic chip with a surface roughness of less than 1 nm, significantly improving the optical performance of on-chip micro-lens. The signal-to-noise ratio was enhanced by 3 dB, compared with that of polymer materials. For the first time, a four-part leukocyte differential count based on single fluorescence staining was realized using a miniaturized flow cytometer, laying a foundation for the point-of-care testing of miniaturized flow cytometers.

Antimicrobial potential of known and novel probiotics on in vitro periodontitis biofilms

Several oral diseases are characterized by a shift within the oral microbiome towards a pathogenic, dysbiotic composition. Broad-spectrum antimicrobials are often part of patient care. However, because of the rising antibiotic resistance, alternatives are increasingly desirable. Alternatively, supplying beneficial species through probiotics is increasingly showing favorable results. Unfortunately, these probiotics are rarely evaluated comparatively. In this study, the in vitro effects of three known and three novel Lactobacillus strains, together with four novel Streptococcus salivarius strains were comparatively evaluated for antagonistic effects on proximal agar growth, antimicrobial properties of probiotic supernatant and the probiotic's effects on in vitro periodontal biofilms. Strain-specific effects were observed as differences in efficacy between genera and differences within genera. While some of the Lactobacillus candidates were able to reduce the periodontal pathobiont A. actinomycetemcomitans, the S. salivarius strains were not. However, the S. salivarius strains were more effective against periodontal pathobionts P. intermedia, P. gingivalis, and F. nucleatum. Vexingly, most of the Lactobacillus strains also negatively affected the prevalence of commensal species within the biofilms, while this was lower for S. salivarius strains. Both within lactobacilli and streptococci, some strains showed significantly more inhibition of the pathobionts, indicating the importance of proper strain selection. Additionally, some species showed reductions in non-target species, which can result in unexpected and unexplored effects on the whole microbiome.

Double Emulsion Flow Cytometry for Rapid Single Genome Detection

Established techniques in droplet microfluidics have utilized single emulsion (SE) drops to compartmentalize and analyze single cells achieving high-throughput, low input analysis. Building upon this foundation, double emulsion (DE) droplet microfluidics has emerged with distinct advantages in terms of stable compartmentalization, resistance to merging, and most importantly direct compatibility with flow cytometry. In this chapter, we describe a simple-to-fabricate, single-layer DE drop generation device that achieves spatial control over surface wetting with a plasma treatment step. This easy-to-operate device allows for the robust production of single-core DEs with excellent control over the monodispersity. We further explain the use of these DE drops for single-molecule and single-cell assays. Detailed protocols are described to perform single molecule detection using droplet digital PCR in DE drops and automated detection of DE drops on a fluorescence-activated cell sorter (FACS). Due to the wide availability of FACS instruments, DE methods can facilitate the broader adoption of drop-based screening. As the applications of FACS-compatible DE droplets are immensely varied and extend well beyond what can be explored here, this chapter should be seen as an introduction to DE microfluidics.

Cell counting and velocity algorithms for hydrodynamic study of unsteady biological flows in micro-channels

In this paper, the combination of two algorithms, a cell counting algorithm and a velocity algorithm based on a Digital Particle Image Velocimetry (DPIV) method, is presented to study the collective behavior of micro-particles in response to hydrodynamic stimuli. A wide experimental campaign was conducted using micro-particles of different natures and diameters (from 5 to 16 μ m ), such as living cells and silica beads. The biological fluids were injected at the inlet of a micro-channel with an external oscillating flow, and the process was monitored in an investigated area, simultaneously, through a CCD camera and a photo-detector. The proposed data analysis procedure is based on the DPIV-based algorithm to extrapolate the micro-particles velocities and a custom counting algorithm to obtain the instantaneous micro-particles number. The counting algorithm was easily integrated with the DPIV-based algorithm, to automatically run the analysis to different videos and to post-process the results in time and frequency domain. The performed experiments highlight the difference in the micro-particles hydrodynamic responses to external stimuli and the possibility to associate them with the micro-particles physical properties. Furthermore, in order to overcome the hardware and software requirements for the development of a real-time approach, it was also investigated the possibility to detect the flows by photo-detector signals as an alternative to camera acquisition. The photo-detector signals were compared with the velocity trends as a proof of concept for further simplification and speed-up of the data acquisition and analysis. The algorithm flexibility underlines the potential of the proposed methodology to be suitable for real-time detection in embedded systems.

High-Efficiency Single-Cell Electrical Impedance Spectroscopy

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

After Theranos: Using point-of-care testing to advance measures of health biomarkers in human biology research

OBJECTIVES

The rise and fall of the health technology startup Theranos is emblematic of the promise and peril of point-of-care testing (POCT). Instruments that deliver immediate results from minimally invasive samples at the location of collection can provide powerful tools to deliver health data in clinical and public health contexts. Yet, POCT availability is driven largely by market interests, which limits the development of inexpensive tests for diverse health conditions that can be used in resource-limited settings. These constraints, combined with complex regulatory hurdles and substantial ethical challenges, have contributed to the underutilization of POCT in human biology research.

METHODS

We evaluate current POCT capabilities and limitations, discuss promising applications for POCT devices in resource-limited settings, and discuss the future of POCT.

RESULTS

As evidenced by publication trends, POCT platforms have rapidly advanced in recent years, gaining traction among clinicians and health researchers. We highlight POCT devices of potential interest to population-based researchers and present specific examples of POCT applications in human biology research.

CONCLUSIONS

Several barriers can limit POCT applications, including cost, lack of regulatory approval for non-clinical use, requirements for expensive equipment, and the dearth of validation in remote field conditions. Despite these issues, we see immense potential for emerging POCT technology capable of analyzing new sample types and used in conjunction with increasingly common technology (e.g., smart phones). We argue that the fallout from Theranos may ultimately provide an opportunity to advance POCT, leading to more ethical data collection and novel opportunities in human biology research.

TNTdetect.AI: A Deep Learning Model for Automated Detection and Counting of Tunneling Nanotubes in Microscopy Images

BACKGROUND

Tunneling nanotubes (TNTs) are cellular structures connecting cell membranes and mediating intercellular communication. TNTs are manually identified and counted by a trained investigator; however, this process is time-intensive. We therefore sought to develop an automated approach for quantitative analysis of TNTs.

METHODS

We used a convolutional neural network (U-Net) deep learning model to segment phase contrast microscopy images of both cancer and non-cancer cells. Our method was composed of preprocessing and model development. We developed a new preprocessing method to label TNTs on a pixel-wise basis. Two sequential models were employed to detect TNTs. First, we identified the regions of images with TNTs by implementing a classification algorithm. Second, we fed parts of the image classified as TNT-containing into a modified U-Net model to estimate TNTs on a pixel-wise basis.

RESULTS

The algorithm detected 49.9% of human expert-identified TNTs, counted TNTs, and calculated the number of TNTs per cell, or TNT-to-cell ratio (TCR); it detected TNTs that were not originally detected by the experts. The model had 0.41 precision, 0.26 recall, and 0.32 f-1 score on a test dataset. The predicted and true TCRs were not significantly different across the training and test datasets (p = 0.78).

CONCLUSIONS

Our automated approach labeled and detected TNTs and cells imaged in culture, resulting in comparable TCRs to those determined by human experts. Future studies will aim to improve on the accuracy, precision, and recall of the algorithm.

Serial flow cytometry in an inertial focusing optofluidic microchip for direct assessment of measurement variations

Flow cytometry is an invaluable technology in biomedical research, but confidence in single-cell measurements remains limited due to a lack of appropriate techniques for uncertainty quantification (UQ). It is particularly challenging to evaluate the potential for different instrumentation designs or operating parameters to influence the measurement physics in ways that change measurement repeatability. Here, we report a direct experimental approach to UQ using a serial flow cytometer that measured each particle more than once along a flow path. The instrument was automated for real-time characterization of measurement precision and operated with particle velocities exceeding 1 m s^-1, throughputs above 100 s^-1, and analysis yields better than 99.9%. These achievements were enabled by a novel hybrid inertial and hydrodynamic particle focuser to tightly control particle positions and velocities. The cytometer identified ideal flow conditions with fluorescence area measurement precision on the order of 1% and characterized tradeoffs between precision, throughput, and analysis yield. The serial cytometer is anticipated to improve single-cell measurements through estimation (and subsequent control) of uncertainty contributions from various other instrument parameters leading to overall improvements in the ability to better classify sample composition and to find rare events.

Development and clinical translation considerations for the next wave of gene modified hematopoietic stem and progenitor cells therapies

INTRODUCTION

Consistent and reliable manufacture of gene modified hematopoietic stem and progenitor cell (HPSC) therapies will be of the utmost importance as they become more mainstream and address larger populations. Robust development campaigns will be needed to ensure that these products will be delivered to patients with the highest quality standards.

AREAS COVERED

Through publicly available manuscripts, press releases, and news articles - this review touches on aspects related to HSPC therapy, development, and manufacturing.

EXPERT OPINION

Recent advances in genome modification technology coupled with the longstanding clinical success of HSPCs warrants great optimism for the next generation of engineered HSPC-based therapies. Treatments for some diseases that have thus far been intractable now appear within reach. Reproducible manufacturing will be of critical importance in delivering these therapies but will be challenging due to the need for bespoke materials and methods in combination with the lack of off-the-shelf solutions. Continued progress in the field will manifest in the form of industrialization which currently requires attention and resources directed toward the custom reagents, a focus on closed and automated processes, and safer and more precise genome modification technologies that will enable broader, faster, and safer access to these life-changing therapies.

Performance Comparison of Five Methods for Tetrahymena Number Counting on the ImageJ Platform: Assessing the Built-in Tool and Machine-Learning-Based Extension

Previous methods to measure protozoan numbers mostly rely on manual counting, which suffers from high variation and poor efficiency. Although advanced counting devices are available, the specialized and usually expensive machinery precludes their prevalent utilization in the regular laboratory routine. In this study, we established the ImageJ-based workflow to quantify ciliate numbers in a high-throughput manner. We conducted Tetrahymena number measurement using five different methods: particle analyzer method (PAM), find maxima method (FMM), trainable WEKA segmentation method (TWS), watershed segmentation method (WSM) and StarDist method (SDM), and compared their results with the data obtained from the manual counting. Among the five methods tested, all of them could yield decent results, but the deep-learning-based SDM displayed the best performance for Tetrahymena cell counting. The optimized methods reported in this paper provide scientists with a convenient tool to perform cell counting for Tetrahymena ecotoxicity assessment.

Cell-TypeAnalyzer: A flexible Fiji/ImageJ plugin to classify cells according to user-defined criteria

Fluorescence microscopy techniques have experienced a substantial increase in the visualization and analysis of many biological processes in life science. We describe a semiautomated and versatile tool called Cell-TypeAnalyzer to avoid the time-consuming and biased manual classification of cells according to cell types. It consists of an open-source plugin for Fiji or ImageJ to detect and classify cells in 2D images. Our workflow consists of (a) image preprocessing actions, data spatial calibration, and region of interest for analysis; (b) segmentation to isolate cells from background (optionally including user-defined preprocessing steps helping the identification of cells); (c) extraction of features from each cell; (d) filters to select relevant cells; (e) definition of specific criteria to be included in the different cell types; (f) cell classification; and (g) flexible analysis of the results. Our software provides a modular and flexible strategy to perform cell classification through a wizard-like graphical user interface in which the user is intuitively guided through each step of the analysis. This procedure may be applied in batch mode to multiple microscopy files. Once the analysis is set up, it can be automatically and efficiently performed on many images. The plugin does not require any programming skill and can analyze cells in many different acquisition setups.

Oral Cells-On-Chip: Design, Modeling and Experimental Results

Recent advances in periodontal studies have attracted the attention of researchers to the relation between oral cells and gum diseases, which is a real threat to overall human health. Among various microfabrication technologies, Complementary Metal Oxide Semiconductors (CMOSs) enable the development of low-cost integrated sensors and circuits for rapid and accurate assessment of living cells that can be employed for the early detection and control of periodontal diseases. This paper presents a CMOS capacitive sensing platform that can be considered as an alternative for the analysis of salivatory cells such as oral neutrophils. This platform consists of two sensing electrodes connected to a read-out capacitive circuitry designed and fabricated on the same chip using Austria Mikro Systeme (AMS) 0.35 µm CMOS process. A graphical user interface (GUI) was also developed to interact with the capacitive read-out system and the computer to monitor the capacitance changes due to the presence of saliva cells on top of the chip. Thanks to the wide input dynamic range (IDR) of more than 400 femto farad (fF) and high resolution of 416 atto farad (aF), the experimental and simulation results demonstrate the functionality and applicability of the proposed sensor for monitoring cells in a small volume of 1 µL saliva samples. As per these results, the hydrophilic adhesion of oral cells on the chip varies the capacitance of interdigitated electrodes (IDEs). These capacitance changes then give an assessment of the oral cells existing in the sample. In this paper, the simulation and experimental results set a new stage for emerging sensing platforms for testing oral samples.

Simplified, Shear Induced Generation of Double Emulsions for Robust Compartmentalization during Single Genome Analysis

Drop microfluidics has driven innovations for high throughput, low input analysis techniques such as single-cell RNA-seq. However, the instability of single emulsion (SE) drops occasionally causes significant merging during drop processing, limiting most applications to single-step reactions in drops. Here, we show that double emulsion (DE) drops address this critical limitation and completely prevent drop contents from mixing. DEs show excellent stability during thermal cycling. More importantly, DEs undergo rupture into the continuous phase instead of merging, preventing content mixing and eliminating unstable drops from the downstream analysis. Due to the lack of drop merging, the monodispersity of drops is maintained throughout a workflow, enabling the deterministic manipulation of drops downstream. We also developed a simple, one-layer DE drop maker compatible with simple surface treatment using a plasma cleaner. The device allows for the robust production of single-core DEs at a wide range of flow rates and better control over the shell thickness, both of which have been significant limitations of conventional two-layer devices. This approach makes the fabrication of DE devices much more accessible, facilitating its broader adoption. Finally, we show that DE droplets eliminate content mixing and maintain compartmentalization of single virus genomes during PCR-based amplification and barcoding, while SEs mixed contents due to merging. With their resistance to content mixing, DE drops have key advantages for multistep reactions in drops, which is limited in SEs due to merging and content mixing.

Intracellular and Extracellular Antifreeze Protein Significantly Improves Mammalian Cell Cryopreservation

Cell cryopreservation is an essential part of the biotechnology, food, and health care industries. There is a need to develop more effective, less toxic cryoprotective agents (CPAs) and methods, especially for mammalian cells. We investigated the impact of an insect antifreeze protein from Anatolica polita (ApAFP752) on mammalian cell cryopreservation using the human embryonic kidney cell line HEK 293T. An enhanced green fluorescent protein (EGFP)-tagged antifreeze protein, EGFP-ApAFP752, was transfected into the cells and the GFP was used to determine the efficiency of transfection. AFP was assessed for its cryoprotective effects intra- and extracellularly and both simultaneously at different concentrations with and without dimethyl sulfoxide (DMSO) at different concentrations. Comparisons were made to DMSO or medium alone. Cells were cryopreserved at -196 °C for ≥4 weeks. Upon thawing, cellular viability was determined using trypan blue, cellular damage was assessed by lactate dehydrogenase (LDH) assay, and cellular metabolism was measured using a metabolic activity assay (MTS). The use of this AFP significantly improved cryopreserved cell survival when used with DMSO intracellularly. Extracellular AFP also significantly improved cell survival when included in the DMSO freezing medium. Intra- and extracellular AFP used together demonstrated the most significantly increased cryoprotection compared to DMSO alone. These findings present a potential method to improve the viability of cryopreserved mammalian cells.

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.

Identification of Stingless Bee Honey Adulteration Using Visible-Near Infrared Spectroscopy Combined with Aquaphotomics

Honey is a natural product that is considered globally one of the most widely important foods. Various studies on authenticity detection of honey have been fulfilled using visible and near-infrared (Vis-NIR) spectroscopy techniques. However, there are limited studies on stingless bee honey (SBH) despite the increase of market demand for this food product. The objective of this work was to present the potential of Vis-NIR absorbance spectroscopy for profiling, classifying, and quantifying the adulterated SBH. The SBH sample was mixed with various percentages (10−90%) of adulterants, including distilled water, apple cider vinegar, and high fructose syrup. The results showed that the region at 400−1100 nm that is related to the color and water properties of the samples was effective to discriminate and quantify the adulterated SBH. By applying the principal component analysis (PCA) on adulterants and honey samples, the PCA score plot revealed the classification of the adulterants and adulterated SBHs. A partial least squares regression (PLSR) model was developed to quantify the contamination level in the SBH samples. The general PLSR model with the highest coefficient of determination and lowest root means square error of cross-validation (RCV2=0.96 and RMSECV=5.88 %) was acquired. The aquaphotomics analysis of adulteration in SBH with the three adulterants utilizing the short-wavelength NIR region (800−1100 nm) was presented. The structural changes of SBH due to adulteration were described in terms of the changes in the water molecular matrix, and the aquagrams were used to visualize the results. It was revealed that the integration of NIR spectroscopy with aquaphotomics could be used to detect the water molecular structures in the adulterated SBH.

Using the Autofluorescence Finder on the Sony ID7000TM Spectral Cell Analyzer to Identify and Unmix Multiple Highly Autofluorescent Murine Lung Populations

Autofluorescence (AF) is a feature of all cell types, though some have more than others. In tissues with complex heterogeneous cellularity, AF is frequently a source of high background, masking faint fluorescent signals and reducing the available dynamic range of detectors for detecting fluorescence signals from markers of interest in a flow cytometry panel. Pulmonary flow cytometry presents unique challenges because lung cells are heterogeneous and contain varying amounts of high AF. The goal of this study was to demonstrate how a novel AF Finder tool on the Sony ID7000™ Spectral Cell Analyzer can be used to identify and screen multiple AF subsets in complex highly AF tissues like murine lungs. In lung single cell suspensions, the AF Finder tool identified four distinct AF spectra from six highly AF subsets. The subtraction of these distinct AF spectra resulted in a resolution increase by several log decades in several fluorescent channels. The major immune and lung tissue resident cells in a murine model of asthma were easily identified in a multi-color panel using AF subtraction. The findings demonstrate the practicality of the AF Finder tool, particularly when analyzing samples with multiple AF populations of varying intensities, in order to reduce fluorescence background and increase signal resolution in spectral flow cytometry.

What is the future of electrical impedance spectroscopy in flow cytometry?

More than 20 years ago, electrical impedance spectroscopy (EIS) was proposed as a potential characterization method for flow cytometry. As the setup is comparably simple and the method is label-free, EIS has attracted considerable interest from the research community as a potential alternative to standard optical methods, such as fluorescence-activated cell sorting (FACS). However, until today, FACS remains by and large the laboratory standard with highly developed capabilities and broad use in research and clinical settings. Nevertheless, can EIS still provide a complement or alternative to FACS in specific applications? In this Perspective, we will give an overview of the current state of the art of EIS in terms of technologies and capabilities. We will then describe recent advances in EIS-based flow cytometry, compare the performance to that of FACS methods, and discuss potential prospects of EIS in flow cytometry.

Giant Unilamellar Vesicle Electroformation: What to Use, What to Avoid, and How to Quantify the Results

Since its inception more than thirty years ago, electroformation has become the most commonly used method for growing giant unilamellar vesicles (GUVs). Although the method seems quite straightforward at first, researchers must consider the interplay of a large number of parameters, different lipid compositions, and internal solutions in order to avoid artifactual results or reproducibility problems. These issues motivated us to write a short review of the most recent methodological developments and possible pitfalls. Additionally, since traditional manual analysis can lead to biased results, we have included a discussion on methods for automatic analysis of GUVs. Finally, we discuss possible improvements in the preparation of GUVs containing high cholesterol contents in order to avoid the formation of artifactual cholesterol crystals. We intend this review to be a reference for those trying to decide what parameters to use as well as an overview providing insight into problems not yet addressed or solved.

Analysis of clonogenic growth in vitro

The clonogenic assay measures the capacity of single cells to form colonies in vitro. It is widely used to identify and quantify self-renewing mammalian cells derived from in vitro cultures as well as from ex vivo tissue preparations of different origins. Varying research questions and the heterogeneous growth requirements of individual cell model systems led to the development of several assay principles and formats that differ with regard to their conceptual setup, 2D or 3D culture conditions, optional cytotoxic treatments and subsequent mathematical analysis. The protocol presented here is based on the initial clonogenic assay protocol as developed by Puck and Marcus more than 60 years ago. It updates and extends the 2006 Nature Protocols article by Franken et al. It discusses different strategies and principles to analyze clonogenic growth in vitro and presents the clonogenic assay in a modular protocol framework enabling a diversity of formats and measures to optimize determination of clonogenic growth parameters. We put particular focus on the phenomenon of cellular cooperation and consideration of how this can affect the mathematical analysis of survival data. This protocol is applicable to any mammalian cell model system from which single-cell suspensions can be prepared and which contains at least a small fraction of cells with self-renewing capacity in vitro. Depending on the cell system used, the entire procedure takes ~2-10 weeks, with a total hands-on time of <20 h per biological replicate.

Water monitoring by means of digital microscopy identification and classification of microalgae

Marine and freshwater microalgae belong to taxonomically and morphologically diverse groups of organisms spanning many phyla with thousands of species. These organisms play an important role as indicators of water ecosystem conditions since they react quickly and predictably to a broad range of environmental stressors, thus providing early signals of dangerous changes. Traditionally, microscopic analysis has been used to identify and enumerate different types of organisms present within a given environment at a given point in time. However, this approach is both time-consuming and labor intensive, as it relies on manual processing and classification of planktonic organisms present within collected water samples. Furthermore, it requires highly skilled specialists trained to recognize and distinguish one taxa from another on the basis of often subtle morphological differences. Given these restrictions, a considerable amount of effort has been recently funneled into automating different steps of both the sampling and classification processes, making it possible to generate previously unprecedented volumes of plankton image data and obtain an essential database to analyze the composition of plankton assemblages. In this review we report state-of-the-art methods used for automated plankton classification by means of digital microscopy. The computer-microscope system hardware and the image processing techniques used for recognition and classification of planktonic organisms (segmentation, shape feature extraction, pigment signature determination and neural network grouping) will be described. An introduction and overview of the topic, its current state and indications of future directions the field is expected to take will be provided, organizing the review for both experts and researchers new to the field.

Comparative Mutational Profiling of Hematopoietic Progenitor Cells and Circulating Endothelial Cells (CECs) in Patients with Primary Myelofibrosis

A role of endothelial cells (ECs) in Primary Myelofibrosis (PMF) was supposed since JAK2 mutation was found in endothelial precursor cells (EPCs) and in ECs captured by laser microdissection. By Cell Search method, the circulating endothelial cells (CECs) from 14 PMF patients and 5 healthy controls have been isolated and compared by NGS with CD34+Hematopoietic stem and progenitors cells (HSPCs) for panel of 54 myeloid-associated mutations. PMF patients had higher levels of CECs. No mutation was found in HSPCs and CECs from controls, while CECs from PMF patients presented several somatic mutations. 72% of evaluable patients shared at least one mutation between HSPCs and CECs. 2 patients shared the JAK2 mutation, together with ABL1, IDH1, TET2 and ASXL1, KMT2A, respectively. 6 out of 8 shared only NON MPN-driver mutations: TET2 and NOTCH1 in one case; individual paired mutations in TP53, KIT, SRSF2, NOTCH1 and WT1, in the other cases. In conclusion, 70% of PMF patients shared at least one mutation between HSPCs and CECs. These latter harbored several myeloid-associated mutations, besides JAK2V617F mutation. Our results support a primary involvement of EC in PMF and provide a new methodological approach for further studies exploring the role of the “neoplastic” vascular niche.

Multi-volume hemacytometer

Cell counting has become an essential method for monitoring the viability and proliferation of cells. A hemacytometer is the standard device used to measure cell numbers in most laboratories which are typically automated to increase throughput. The principle of both manual and automated hemacytometers is to calculate cell numbers with a fixed volume within a set measurement range (10⁵ ~ 10⁶ cells/ml). If the cell concentration of the unknown sample is outside the range of the hemacytometer, the sample must be prepared again by increasing or decreasing the cell concentration. We have developed a new hemacytometer that has a multi-volume chamber with 4 different depths containing different volumes (0.1, 0.2, 0.4, 0.8 µl respectively). A multi-volume hemacytometer can measure cell concentration with a maximum of 10⁶ cells/ml to a minimum of 5 × 10³ cells/ml. Compared to a typical hemacytometer with a fixed volume of 0.1 µl, the minimum measurable cell concentration of 5 × 10³ cells/ml on the multi-volume hemacytometer is twenty times lower. Additionally, the Multi-Volume Cell Counting model (cell concentration calculation with the slope value of cell number in multi-chambers) showed a wide measurement range (5 × 10³ ~ 1 × 10⁶ cells/ml) while reducing total cell counting numbers by 62.5% compared to a large volume (0.8 µl-chamber) hemacytometer.

A cytofluorimetric analysis of a Saccharomyces cerevisiae population cultured in a fed-batch bioreactor

The yeast Saccharomyces cerevisiae is a reference model system and one of the widely used microorganisms in many biotechnological processes. In industrial yeast applications, combined strategies aim to maximize biomass/product yield, with the fed-batch culture being one of the most frequently used. Flow cytometry (FCM) is widely applied in biotechnological processes and represents a key methodology to monitor cell population dynamics. We propose here an application of FCM in the analysis of yeast cell cycle along the time course of a typical S. cerevisiae fed-batch culture. We used two different dyes, SYTOX Green and SYBR Green, with the aim to better define each stage of cell cycle during S. cerevisiae fed-batch culture. The results provide novel insights in the use of FCM cell cycle analysis for the real-time monitoring of S. cerevisiae bioprocesses.

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.

Optimization of a Clinically Relevant Chemical-Mechanical Tissue Dissociation Workflow for Single-Cell Analysis

INTRODUCTION

While single-cell analysis technology has flourished, obtaining single cells from complex tissues continues to be a challenge. Current methods require multiple steps and several hours of processing. This study investigates chemical and mechanical methods for clinically relevant preparation of single-cell suspension from frozen biopsy cores of complex tissues. The developed protocol can be completed in 15 min.

METHODS

Frozen bovine liver biopsy cores were normalized by weight, dimension, and calculated cellular composition. Various chemical reagents were tested for their capability to dissociate the tissue via confocal microscopy, hemocytometry and quantitative flow cytometry. Images were processed using ImageJ. Quantitative flow cytometry with gating analysis was also used for the analysis of dissociation. Physical modeling simulations were conducted in COMSOL Multiphysics.

RESULTS

A rapid method for tissue dissociation was developed for single-cell analysis techniques. The results of this study show that a combination of 1% type-1 collagenase and pronase or hyaluronidase in 100 U/µL HBSS solution is the most effective at dissociating 2.5 mm thawed bovine liver biopsy cores in 15 min, with dissociation efficiency of 37-42% and viability >90% as verified using live MDA-MB-231 cancer cells. Cellular dissociation is significantly improved by adding a controlled mechanical force during the chemical process, to dissociate 93 ± 8% of the entire tissue into single cells.

CONCLUSIONS

Understanding cellular dissociation in ex vivo tissues is essential to the development of clinically relevant dissociation workflows. Controlled mechanical force in combination with chemical treatment produces high quality tissue dissociation. This research is relevant to the understanding and assessment of tissue dissociation and the establishment of an automated preparatory workflow for single cell diagnostics.

SUPPLEMENTARY INFORMATION

The online version of this article (10.1007/s12195-021-00667-y) contains supplementary material, which is available to authorized users.

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

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