A novel method for kinetic measurements of rare cell proliferation using Cellometer image-based cytometry

Image cytometry as an alternative to flow cytometry for the transplant histocompatibility crossmatch assay

The lymphocyte crossmatch is currently the only cell-based compatibility assay performed by histocompatibility laboratories for transplant purposes. While in many transplant programs the complement-dependent cytotoxicity crossmatch (CDCXM) remains in use, when available, the flow cytometry crossmatch (FCXM) is the method of choice because of its superior sensitivity and specificity. Unfortunately, the maintenance and cost of a flow cytometer is a considerable limitation for small histocompatibility laboratories. Therefore, in this study, we evaluated the use of the Cellometer Vision CBA image cytometer (Nexcelom Bioscience LLC, Lawrence, Massachusetts) as an alternative instrument to perform the crossmatch assay. The 3-color FCXM protocol was modified into two separate 2-color panel image cytometry crossmatches (IXMs), one for T cells and one for B cells. After initial serum and cell incubation, a cocktail consisting of PE/Cy5-conjugated anti-human CD3 or CD19 and PE-conjugated anti-human IgG F(ab')₂ was added to the T cell and B cell panels, respectively. The final cell preparation was added to a separate counting chamber. Images were captured using the Cellometer Vision CBA, an image cytometer designed for cell counting, size analysis and fluorescence intensity measurement. Thirty-nine IXMs were performed and compared with the FCXM. We obtained a concordance sensitivity of 94.1% and 100% and specificity of 100% and 88.9% for T cells and B cells, respectively. The linearity of the system was verified using dilutions of a sample containing known donor-specific anti-HLA antibodies (DSA) against the target cells. This feasibility study demonstrates that the FCXM test could be easily adapted to the Cellometer Vision CBA image cytometer without compromising specificity and sensitivity. The low instrumentation cost, minimal maintenance, and simple operation allow for efficient implementation or transition from the FCXM to the IXM method.

A high-throughput AO/PI-based cell concentration and viability detection method using the Celigo image cytometry

To ensure cell-based assays are performed properly, both cell concentration and viability have to be determined so that the data can be normalized to generate meaningful and comparable results. Cell-based assays performed in immuno-oncology, toxicology, or bioprocessing research often require measuring of multiple samples and conditions, thus the current automated cell counter that uses single disposable counting slides is not practical for high-throughput screening assays. In the recent years, a plate-based image cytometry system has been developed for high-throughput biomolecular screening assays. In this work, we demonstrate a high-throughput AO/PI-based cell concentration and viability method using the Celigo image cytometer. First, we validate the method by comparing directly to Cellometer automated cell counter. Next, cell concentration dynamic range, viability dynamic range, and consistency are determined. The high-throughput AO/PI method described here allows for 96-well to 384-well plate samples to be analyzed in less than 7 min, which greatly reduces the time required for the single sample-based automated cell counter. In addition, this method can improve the efficiency for high-throughput screening assays, where multiple cell counts and viability measurements are needed prior to performing assays such as flow cytometry, ELISA, or simply plating cells for cell culture.

Discriminating multiplexed GFP reporters in primary articular chondrocyte cultures using image cytometry

Flow cytometry has become a standard tool for defining a heterogeneous cell population based on surface expressed epitopes or GFP reporters that reflect cell types or cellular differentiation. The introduction of image cytometry raised the possibility of adaptation to discriminate GFP reporters used to appreciate cell heterogeneity within the skeletal lineages. The optical filters and LEDs were optimized for the reporters used in transgenic mice expressing various fluorescent proteins. In addition, the need for compensation between eGFP and surrounding reporters due to optical cross-talk was eliminated by selecting the appropriate excitation and emission filters. Bone marrow or articular cartilage cell cultures from GFP and RFP reporter mouse lines were established to demonstrate the equivalency in functionalities of image to flow cytometry analysis. To examine the ability for monitoring primary cell differentiation, articular chondrocyte cell cultures were established from mice that were single or doubly transgenic (Dkk3eGFP and Col2A1GFPcyan), which identify the progression of superficial small articular cell to a mature chondrocyte. The instrument was able to rapidly and accurately discriminate cells that were Dkk3eGFP only, Dkk3eGFP/Col2A1GFPcyan, and Col2A1GFP, which provides a useful tool for studying the impact of culture conditions on lineage expansion and differentiation.

Use of image cytometry for quantification of pathogenic fungi in association with host cells

Studies of the cellular pathogenesis mechanisms of pathogenic yeasts such as Candida albicans, Histoplasma capsulatum, and Cryptococcus neoformans commonly employ infection of mammalian hosts or host cells (i.e. macrophages) followed by yeast quantification using colony forming unit analysis or flow cytometry. While colony forming unit enumeration has been the most commonly used method in the field, this technique has disadvantages and limitations, including slow growth of some fungal species on solid media and low and/or variable plating efficiencies, which is of particular concern when comparing growth of wild-type and mutant strains. Flow cytometry can provide rapid quantitative information regarding yeast viability, however, adoption of flow cytometric detection for pathogenic yeasts has been limited for a number of practical reasons including its high cost and biosafety considerations. Here, we demonstrate an image-based cytometric methodology using the Cellometer Vision (Nexcelom Bioscience, LLC) for the quantification of viable pathogenic yeasts in co-culture with macrophages. Our studies focus on detection of two human fungal pathogens: Histoplasma capsulatum and Candida albicans. H. capsulatum colonizes alveolar macrophages by replicating within the macrophage phagosome, and here, we quantitatively assess the growth of H. capsulatum yeasts in RAW 264.7 macrophages using acridine orange/propidium iodide staining in combination with image cytometry. Our method faithfully recapitulates growth trends as measured by traditional colony forming unit enumeration, but with significantly increased sensitivity. Additionally, we directly assess infection of live macrophages with a GFP-expressing strain of C. albicans. Our methodology offers a rapid, accurate, and economical means for detection and quantification of important human fungal pathogens in association with host cells.

Accurate measurement of peripheral blood mononuclear cell concentration using image cytometry to eliminate RBC-induced counting error

Peripheral blood mononuclear cells (PBMCs) have been widely researched in the fields of immunology, infectious disease, oncology, transplantation, hematological malignancy, and vaccine development. Specifically, in immunology research, PBMCs have been utilized to monitor concentration, viability, proliferation, and cytokine production from immune cells, which are critical for both clinical trials and biomedical research. The viability and concentration of isolated PBMCs are traditionally measured by manual counting with trypan blue (TB) using a hemacytometer. One of the common issues of PBMC isolation is red blood cell (RBC) contamination. The RBC contamination can be dependent on the donor sample and/or technical skill level of the operator. RBC contamination in a PBMC sample can introduce error to the measured concentration, which can pass down to future experimental assays performed on these cells. To resolve this issue, RBC lysing protocol can be used to eliminate potential error caused by RBC contamination. In the recent years, a rapid fluorescence-based image cytometry system has been utilized for bright-field and fluorescence imaging analysis of cellular characteristics (Nexcelom Bioscience LLC, Lawrence, MA). The Cellometer image cytometry system has demonstrated the capability of automated concentration and viability detection in disposable counting chambers of unpurified mouse splenocytes and PBMCs stained with acridine orange (AO) and propidium iodide (PI) under fluorescence detection. In this work, we demonstrate the ability of Cellometer image cytometry system to accurately measure PBMC concentration, despite RBC contamination, by comparison of five different total PBMC counting methods: (1) manual counting of trypan blue-stained PBMCs in hemacytometer, (2) manual counting of PBMCs in bright-field images, (3) manual counting of acetic acid lysing of RBCs with TB-stained PBMCs, (4) automated counting of acetic acid lysing of RBCs with PI-stained PBMCs, and (5) AO/PI dual staining method. The results show comparable total PBMC counting among all five methods, which validate the AO/PI staining method for PBMC measurement in the image cytometry method.

Novel image cytometric method for detection of physiological and metabolic changes in Saccharomyces cerevisiae

The studying and monitoring of physiological and metabolic changes in Saccharomyces cerevisiae (S. cerevisiae) has been a key research area for the brewing, baking, and biofuels industries, which rely on these economically important yeasts to produce their products. Specifically for breweries, physiological and metabolic parameters such as viability, vitality, glycogen, neutral lipid, and trehalose content can be measured to better understand the status of S. cerevisiae during fermentation. Traditionally, these physiological and metabolic changes can be qualitatively observed using fluorescence microscopy or flow cytometry for quantitative fluorescence analysis of fluorescently labeled cellular components associated with each parameter. However, both methods pose known challenges to the end-users. Specifically, conventional fluorescent microscopes lack automation and fluorescence analysis capabilities to quantitatively analyze large numbers of cells. Although flow cytometry is suitable for quantitative analysis of tens of thousands of fluorescently labeled cells, the instruments require a considerable amount of maintenance, highly trained technicians, and the system is relatively expensive to both purchase and maintain. In this work, we demonstrate the first use of Cellometer Vision for the kinetic detection and analysis of vitality, glycogen, neutral lipid, and trehalose content of S. cerevisiae. This method provides an important research tool for large and small breweries to study and monitor these physiological behaviors during production, which can improve fermentation conditions to produce consistent and higher-quality products.

A novel image-based cytometry method for autophagy detection in living cells

Autophagy is an important cellular catabolic process that plays a variety of important roles, including maintenance of the amino acid pool during starvation, recycling of damaged proteins and organelles, and clearance of intracellular microbes. Currently employed autophagy detection methods include fluorescence microscopy, biochemical measurement, SDS-PAGE and western blotting, but they are time consuming, labor intensive, and require much experience for accurate interpretation. More recently, development of novel fluorescent probes have allowed the investigation of autophagy via standard flow cytometry. However, flow cytometers remain relatively expensive and require a considerable amount of maintenance. Previously, image-based cytometry has been shown to perform automated fluorescence-based cellular analysis comparable to flow cytometry. In this study, we developed a novel method using the Cellometer image-based cytometer in combination with Cyto-ID(®) Green dye for autophagy detection in live cells. The method is compared with flow cytometry by measuring macroautophagy in nutrient-starved Jurkat cells. Results demonstrate similar trends of autophagic response, but different magnitude of fluorescence signal increases, which may arise from different analysis approaches characteristic of the two instrument platforms. The possibility of using this method for drug discovery applications is also demonstrated through the measurement of dose-response kinetics upon induction of autophagy with rapamycin and tamoxifen. The described image-based cytometry/fluorescent dye method should serve as a useful addition to the current arsenal of techniques available in support of autophagy-based drug discovery relating to various pathological disorders.