Single-cell segmentation in bacterial biofilms with an optimized deep learning method enables tracking of cell lineages and measurements of growth rates.

Bacteria often grow into matrix-encased three-dimensional (3D) biofilm communities, which can be imaged at cellular resolution using confocal microscopy. From these 3D images, measurements of single-cell properties with high spatiotemporal resolution are required to investigate cellular heterogeneity and dynamical processes inside biofilms. However, the required measurements rely on the automated segmentation of bacterial cells in 3D images, which is a technical challenge. To improve the accuracy of single-cell segmentation in 3D biofilms, we first evaluated recent classical and deep learning segmentation algorithms. We then extended StarDist, a state-of-the-art deep learning algorithm, by optimizing the post-processing for bacteria, which resulted in the most accurate segmentation results for biofilms among all investigated algorithms. To generate the large 3D training dataset required for deep learning, we developed an iterative process of automated segmentation followed by semi-manual correction, resulting in >18,000 annotated Vibrio cholerae cells in 3D images. We demonstrate that this large training dataset and the neural network with optimized post-processing yield accurate segmentation results for biofilms of different species and on biofilm images from different microscopes. Finally, we used the accurate single-cell segmentation results to track cell lineages in biofilms and to perform spatiotemporal measurements of single-cell growth rates during biofilm development.

Identification of neutrophils and eosinophils in upper airway mucosa with immunofluorescence multiplex image cytometry.

Characterization of inflammation in chronic rhinosinusitis with (CRSwNP) and without nasal polyps (CRSsNP) is an ongoing research process. To overcome limitations of current cytologic techniques, we investigated whether immunofluorescence multiplex image cytometry could quantify intact neutrophils, eosinophils, and other immune cells in solid upper airway mucosa. We used a four-channel immunofluorescence-microscopy technique for the simultaneous detection of the leukocyte marker CD45, the neutrophil marker myeloperoxidase, two eosinophil markers, i.e., major basic protein and eosinophil peroxidase, and DAPI (4',6-diamidin-2-phenylindole), in formalin-fixed paraffin-embedded upper airway tissue samples of patients with CRSwNP and CRSsNP, as well as of patients free of CRS with inferior turbinate hypertrophy (controls). Image acquisition and analysis were performed with TissueFAXS and StrataQuest (TissueGnostics, Vienna, Austria), respectively. Positive and negative immunostaining were differentiated with a specific fluorescence signal/background signal ratio. Isotype controls were used as negative controls. In six controls, nine patients with CRSsNP, and 11 patients with CRSwNP, the median area scanned and median cell count per patient were 14.2 mm2 and 34,356, respectively. In CRSwNP, the number of eosinophils was three times higher (23%) than that of neutrophils (7%). Three times more immune cells were encountered in CRSwNP (33%) compared to CRSsNP (11%). In controls, inflammation was balanced between the epithelial layer and lamina propria, in contrast to CRS (three times more pronounced inflammation in the lamina propria). The quantification of intact neutrophils, eosinophils, and other immune cells in solid tissue with undisrupted architecture seems feasible with immunofluorescence multiplex image cytometry.

OPTIMAL: An OPTimized Imaging Mass cytometry AnaLysis framework for benchmarking segmentation and data exploration.

Analysis of imaging mass cytometry (IMC) data and other low-resolution multiplexed tissue imaging technologies is often confounded by poor single-cell segmentation and suboptimal approaches for data visualization and exploration. This can lead to inaccurate identification of cell phenotypes, states, or spatial relationships compared to reference data from single-cell suspension technologies. To this end we have developed the "OPTimized Imaging Mass cytometry AnaLysis (OPTIMAL)" framework to benchmark any approaches for cell segmentation, parameter transformation, batch effect correction, data visualization/clustering, and spatial neighborhood analysis. Using a panel of 27 metal-tagged antibodies recognizing well-characterized phenotypic and functional markers to stain the same Formalin-Fixed Paraffin Embedded (FFPE) human tonsil sample tissue microarray over 12 temporally distinct batches we tested several cell segmentation models, a range of different arcsinh cofactor parameter transformation values, 5 different dimensionality reduction algorithms, and 2 clustering methods. Finally, we assessed the optimal approach for performing neighborhood analysis. We found that single-cell segmentation was improved by the use of an Ilastik-derived probability map but that issues with poor segmentation were only really evident after clustering and cell type/state identification and not always evident when using "classical" bivariate data display techniques. The optimal arcsinh cofactor for parameter transformation was 1 as it maximized the statistical separation between negative and positive signal distributions and a simple Z-score normalization step after arcsinh transformation eliminated batch effects. Of the five different dimensionality reduction approaches tested, PacMap gave the best data structure with FLOWSOM clustering out-performing phenograph in terms of cell type identification. We also found that neighborhood analysis was influenced by the method used for finding neighboring cells with a "disc" pixel expansion outperforming a "bounding box" approach combined with the need for filtering objects based on size and image-edge location. Importantly, OPTIMAL can be used to assess and integrate with any existing approach to IMC data analysis and, as it creates .FCS files from the segmentation output and allows for single-cell exploration to be conducted using a wide variety of accessible software and algorithms familiar to conventional flow cytometrists.

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.

A Multiplex Assay to Simultaneously Monitor Apoptosis and Necrosis Using the Cellaca® PLX Image Cytometer.

Apoptosis is the programmed cell death pathway that is critical for maintaining homeostasis, in which cancer cells can evade to ensure survival. For pharmaceutical drug discovery, it is important to characterize and compare different cancer therapeutics (i.e., small molecules, antibody drugs, cell therapies) that can initiate the process of apoptosis, enabling the identification of potential therapeutic candidates. In this work, we developed and demonstrated a multiplex detection method for monitoring apoptosis and necrosis with Annexin V, Caspase-3, and Propidium Iodide (PI) using the Cellaca® PLX Image Cytometer (Revvity Health Sciences, Inc., Lawrence, MA). First, apoptosis was induced in Jurkat and K562 cell lines with staurosporine over the course of 24 h, where apoptosis and necrosis were assessed at 0, 1, 1.5, 2, 4, 20, and 24 h timepoints. Samples were stained with Hoechst 33342 (total dye), Annexin V-APC (early-stage apoptosis), Caspase-3 488 (late-stage apoptosis), and PI (necrosis) at each timepoint and evaluated using image cytometry. Results showed that apoptotic factors and cascades were successfully detected along the pathway from early- to late-stage apoptosis, and ultimately necrosis. A clear trend was observed analyzing apoptotic and necrotic populations during the first 1.5 h, showing differences of up to ~15% in single Annexin V+ and Caspase-3+ populations in treated Jurkat cells, however, a significant increase in double positive apoptotic/necrotic cells for Annexin V+PI+ and Capase-3+PI+ was not observed until 20 h. Upon further analysis between apoptotic populations only, Annexin V+ only populations were higher than Caspase-3+ only populations by up to ~20% between 0 and 1.5 h. Conversely, K562 cells did not exhibit a notable change in apoptotic and necrotic populations due to low sensitivity to staurosporine. The proposed image cytometric detection method may provide an effective and efficient tool for rapid and reliable simultaneous detection of early- late-stage apoptosis, and necrosis. Therefore, allowing researchers to better characterize and screen potential cancer therapeutic drug candidates for their treatment efficacy in a higher throughput manner.

High-Throughput SARS-CoV-2 Antiviral Testing Method Using the Celigo Image Cytometer.

The COVID-19 pandemic has created a worldwide public health crisis that has since resulted in 6.8 million reported deaths. The pandemic prompted the immediate response of researchers around the world to engage in rapid vaccine development, surveillance programs, and antiviral testing, which resulted in the delivery of multiple vaccines and repurposed antiviral drug candidates. However, the emergence of new highly transmissible SARS-CoV-2 variants has renewed the desire for discovering new antiviral drug candidates with high efficacy against the emerging variants of concern. Traditional antiviral testing methods employ the plaque-reduction neutralization tests (PRNTs), plaque assays, or RT-PCR analysis, but each assay can be tedious and time-consuming, requiring 2-3 days to complete the initial antiviral assay in biologically relevant cells, and then 3-4 days to visualize and count plaques in Vero cells, or to complete cell extractions and PCR analysis. In recent years, plate-based image cytometers have demonstrated high-throughput vaccine screening methods, which can be adopted for screening potential antiviral drug candidates. In this work, we developed a high-throughput antiviral testing method employing the Celigo Image Cytometer to investigate the efficacy of antiviral drug candidates on SARS-CoV-2 infectivity using a fluorescent reporter virus and their safety by measuring the cytotoxicity effects on the healthy host cell line using fluorescent viability stains. Compared to traditional methods, the assays defined here eliminated on average 3-4 days from our standard processing time for antiviral testing. Moreover, we were able to utilize human cell lines directly that are not typically amenable to PRNT or plaque assays. The Celigo Image Cytometer can provide an efficient and robust method to rapidly identify potential antiviral drugs to effectively combat the rapidly spreading SARS-CoV-2 virus and its variants during the pandemic.

Comparison of chimeric antigen receptor-T cell-mediated cytotoxicity assays with suspension tumor cells using plate-based image cytometry method.

In the recent decade, chimeric antigen receptor (CAR)-T cell therapy has revolutionized strategies for cancer treatments due to its highly effective clinical efficacy and response for B cell malignancies. The success of CAR-T cell therapy has stimulated the increase in the research and development of various CAR constructs to target different tumor types. Therefore, a robust and efficient in vitro potency assay is needed to quickly identify potential CAR gene design from a library of construct candidates. Image cytometry methodologies have been utilized for various CAR-T cell-mediated cytotoxicity assay using different fluorescent labeling methods, mainly due to their ease-of-use, ability to capture cell images for verification, and higher throughput performance. In this work, we employed the Celigo Image Cytometer to evaluate and compare two CAR-T cell-mediated cytotoxicity assays using GFP-expressing or fluorescent dye-labeled myeloma and plasmacytoma cells. The GFP-based method demonstrated higher sensitivity in detecting CAR-T cell-mediated cytotoxicity when compared to the CMFDA/DAPI viability method. We have established the criteria and considerations for the selection of cytotoxicity assays that are fit-for-purpose to ensure the results produced are meaningful for the specific testing conditions.

Analysis of cells of epithelial, connective tissue and immune differentiation in HPV-positive-, HPV-negative oropharyngeal carcinoma and normal oropharyngeal tissue by immunofluorescence multiplex image cytometry: a preliminary report.

BACKGROUND: Epithelial, connective tissue and immune cells contribute in various ways to the pathophysiology of HPV positive (HPV+) and HPV negative (HPV-) oropharyngeal squamous cell carcinoma (OPSCC). We aimed to investigate the abundance of these cell lineages and their coexpression patterns in patients with HPV + and HPV- OPSCC. METHODS: We used a 4-channel immunofluorescence-microscopy technique for the simultaneous detection of three direct-conjugated antibodies (pancytokeratin, vimentin and CD45/CD18) and DAPI (4',6-Diamidin-2-phenylindole) in formalin fixed paraffin-embedded tissue samples (FFPE) of patients with HPV + and HPV- OPSCC, and of control patients. Image acquisition and analysis were performed with TissueFAXS and StrataQuest (TissueGnostics, Vienna, Austria), respectively, in tumor cell clusters/stroma in OPSCC specimens and epithelial layer/lamina propria in control specimens. Cell populations were created based on antibodies' coexpression patterns. Isotype and positive controls were examined for plausibility. RESULTS: The proportion of cells of epithelial differentiation in tumor cell clusters was higher in HPV + OPSCC (55%) than in HPV- OPSCC samples (44%). The proportion of connective tissue cells in tumor cell cluster was lower in HPV + OPSCC patients (18%) than in HPV- OPSCC patients (26%). The proportion of immune cells in tumor cell clusters was higher in HPV + OPSCC patients (25%) than in HPV- OPSCC patients (18%). The percentage of anaplastic, potentially de-differentiated cells, was 2% in control patients, and it was higher in HPV- OPSCC (21%) than in HPV + OPSCC samples (6%). CONCLUSIONS: This study provided the first quantitative data for the abundance of cells of epithelial, connective tissue and immune differentiation, in patients with OPSCC and control patients. The abundance of these different crucial cell populations was consistently originating from the same tissue sample. De-differentiation of tumor cells was higher in HPV- OPSCC than in HPV + OPSCC. In tumor cells clusters, the antitumoral host immune response was higher in HPV + OPSCC than in HPV- OPSCC, whereas the fibroblast response was higher in HPV- OPSCC than in HPV + OPSCC. This study contributed to the understanding of histopathologic differences between HPV + OPSCC and HPV- OPSCC patients.

Practical Characterization Strategies for Comparison, Qualification, and Selection of Cell Viability Detection Methods for Cellular Therapeutic Product Development and Manufacturing.

Cellular therapy development and manufacturing has focused on providing novel therapeutic cell-based products for various diseases. The International Organization for Standardization (ISO) has provided guidance on critical quality attributes (CQAs) that shall be considered when testing and releasing cellular therapeutic products. Cell count and viability measurements are two of the CQAs that are determined during development, manufacturing, testing, and product release. The ISO Cell Counting Standard Part 1 and 2 addressed the needs for improving the quality of cell counting results. However, there is currently no guidance on the qualification and selection of a fit-for-purpose cell viability detection method. In this work, we present strategies for the characterization and comparison of AO/PI and AO/DAPI staining methods using the heat-killed (HK) and low temperature/nutrient-deprived (LT/ND) cell death models to evaluate the comparability of cell viability measurements and identify potential causes of differences. We compared the AO/PI and AO/DAPI staining methods using HK and LT/ND-generated dead cells, investigated the staining time effects on cell viability measurements, and determined their viability linearity with different mixtures of live and dead cells. Furthermore, we validated AO/PI and AO/DAPI cell viability measurement with a long-term cell proliferation assay. Finally, we demonstrate a practical example of cell viability measurement comparison using AO/PI and AO/DAPI on antibiotic-selected transduced Jurkat and THP-1 cells to select a fit-for-purpose method for functional genomics screening. The proposed strategies may potentially enable scientists to properly characterize, compare, and select cell viability detection methods that are critical for cellular therapeutic product development and manufacturing.

A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation.

Mixed microorganism cultures are prevalent in the food industry. A variety of microbiological mixtures have been used in these unique fermenting processes to create distinctive flavor profiles and potential health benefits. Mixed cultures are typically not well characterized, which may be due to the lack of simple measurement tools. Image-based cytometry systems have been employed to automatically count bacteria or yeast cells. In this work, we aim to develop a novel image cytometry method to distinguish and enumerate mixed cultures of yeast and bacteria in beer products. Cellometer X2 from Nexcelom was used to count of Lactobacillus plantarum and Saccharomyces cerevisiae in mixed cultures using fluorescent dyes and size exclusion image analysis algorithm. Three experiments were performed for validation. (1) Yeast and bacteria monoculture titration, (2) mixed culture with various ratios, and (3) monitoring a Berliner Weisse mixed culture fermentation. All experiments were validated by comparing to manual counting of yeast and bacteria colony formation. They were highly comparable with ANOVA analysis showing p-value > 0.05. Overall, the novel image cytometry method was able to distinguish and count mixed cultures consistently and accurately, which may provide better characterization of mixed culture brewing applications and produce higher quality products.

TITAN: An end-to-end data analysis environment for the Hyperion™ imaging system.

Imaging Mass Cytometry (IMC) is a powerful high-throughput technique enabling resolution of up to 37 markers in a single fixed tissue section while also preserving in situ spatial relationships. Currently, IMC processing and analysis necessitates the use of multiple different software, labour-intensive pipeline development, different operating systems and knowledge of bioinformatics, all of which are a barrier to many potential users. Here we present TITAN - an open-source, single environment, end-to-end pipeline that can be utilized for image visualization, segmentation, analysis and export of IMC data. TITAN is implemented as an extension within the publicly available 3D Slicer software. We demonstrate the utility, application, reliability and comparability of TITAN using publicly available IMC data from recently-published breast cancer and COVID-19 lung injury studies. Compared with current IMC analysis methods, TITAN provides a user-friendly, efficient single environment to accurately visualize, segment, and analyze IMC data for all users.

Automated Assessment of Cancer Drug Efficacy On Breast Tumor Spheroids in Aggrewell™400 Plates Using Image Cytometry.

Tumor spheroid models have proven useful in the study of cancer cell responses to chemotherapeutic compounds by more closely mimicking the 3-dimensional nature of tumors in situ. Their advantages are often offset, however, by protocols that are long, complicated, and expensive. Efforts continue for the development of high-throughput assays that combine the advantages of 3D models with the convenience and simplicity of traditional 2D monolayer methods. Herein, we describe the development of a breast cancer spheroid image cytometry assay using T47D cells in Aggrewell™400 spheroid plates. Using the Celigo® automated imaging system, we developed a method to image and individually track thousands of spheroids within the Aggrewell™400 microwell plate over time. We demonstrate the use of calcein AM and propidium iodide staining to study the effects of known anti-cancer drugs Doxorubicin, Everolimus, Gemcitabine, Metformin, Paclitaxel and Tamoxifen. We use the image cytometry results to quantify the fluorescence of calcein AM and PI as well as spheroid size in a dose dependent manner for each of the drugs. We observe a dose-dependent reduction in spheroid size and find that it correlates well with the viability obtained from the CellTiter96® endpoint assay. The image cytometry method we demonstrate is a convenient and high-throughput drug-response assay for breast cancer spheroids under 400 µm in diameter, and may lay a foundation for investigating other three-dimensional spheroids, organoids, and tissue samples.

DNA image cytometry parameters to identify high-grade cervical lesions.

OBJECTIVE: Evaluate the performance of different DNA image cytometry (DNA-ICM) ploidy parameters in the categorisation of DNA-ICM results and identification of high-grade cervical intraepithelial neoplasia or worse (≥ CIN2). METHODS: Cervical samples from 232 women were collected for DNA-ICM analysis and biopsy confirmation. Five DNA parameters were used to define DNA aneuploidy: number of cells with exceeding events (EE) over 2.5cEE, 4cEE, 5cEE and 9cEE, and aneuploid stemlines. DNA-ICM results were categorised as normal, suspicious, and abnormal. RESULTS: For individual DNA ploidy parameters, sensitivity values for 50 cells with 2.5cEE, 45 cells with 4cEE, 1 cell with 9cEE and aneuploid stemline were 72.95%. 54.1%, 69.67% and 54.1%, while specificity values were 80.0%, 90.0%, 89.09% and 95.45%, respectively. For the 5cEE parameter, the sensitivity values for 1, 2, 3, 4 and 5 cells were 93.44%, 85.25%, 81.97%, 77.87% and 75.41%, while specificity values were 46.36%, 63.64%, 74.55%, 76.36% and 80.91%, respectively. For categorised DNA-ICM results, a suspicious result showed superior sensitivity than an abnormal result (87.70% vs 82.79%, P = 0.031), but lower specificity (54.55% vs 75.45%, P < 0.001). Both types of DNA-ICM result were statistically significantly different from a normal result (P < 0.05). CONCLUSION: For prognostic purposes, 1 cell with 9cEE, 45 cells with 4cEE and aneuploid stemline are the best parameters with which to categorise an abnormal DNA-ICM result, followed by 50 cells with 2.5cEE and 4 cells with 5cEE. For screening purposes, 10 cells with 2.5cEE, 10 cells with 4cEE, and 2 cells with 5cEE are suitable parameters with which to categorise a suspicious DNA-ICM result.

Use of DNA image cytometry in conducting oral cancer screening in rural India.

OBJECTIVES: Oral cancer screening can assist in the early detection of oral potentially malignant lesions (OPMLs) and prevention of oral cancers. It can be challenging for clinicians to differentiate OPMLs from benign conditions. Adjunct screening tools such as fluorescence visualisation (FV) and DNA image cytometry (DNA-ICM) have shown success in identifying OPMLs in high-risk clinics. For the first time we aimed to assess these technologies in Indian rural settings and evaluate if these tools helped clinicians identify high-risk lesions during screening. METHODS: Dental students and residents screened participants in five screening camps held in villages outside of Hyderabad, India, using extraoral, intraoral, and FV examinations. Lesion and normal tissue brushings were collected for DNA-ICM analysis and cytology. RESULTS: Of the 1116 participants screened, 184 lesions were observed in 152 participants. Based on white light examination (WLE), 45 lesions were recommended for biopsy. Thirty-five were completed on site; 25 (71%) were diagnosed with low-grade dysplasias (17 mild, 8 moderate) and the remaining 10 showed no signs of dysplasia. FV loss was noted in all but one dysplastic lesion and showed a sensitivity of 96% and specificity of 17%. Cytology combined with DNA-ICM had a sensitivity of 64% and specificity of 86% in detecting dysplasia. CONCLUSION: DNA-ICM combined with cytology identified the majority of dysplastic lesions and identified additional lesions, which were not considered high-risk during WLE and biopsy on site. Efforts to follow-up with these participants are ongoing. FV identified most high-risk lesions but added limited value over WLE.

From Double-Strand Break Recognition to Cell-Cycle Checkpoint Activation: High Content and Resolution Image Cytometry Unmasks 53BP1 Multiple Roles in DNA Damage Response and p53 Action.

53BP1 protein has been isolated in-vitro as a putative p53 interactor. From the discovery of its engagement in the DNA-Damage Response (DDR), its role in sustaining the activity of the p53-regulated transcriptional program has been frequently under-evaluated, even in the case of a specific response to numerous DNA Double-Strand Breaks (DSBs), i.e., exposure to ionizing radiation. The localization of 53BP1 protein constitutes a key to decipher the network of activities exerted in response to stress. We present here an automated-microscopy for image cytometry protocol to analyze the evolution of the DDR, and to demonstrate how 53BP1 moved from damaged sites, where the well-known interaction with the DSB marker γH2A.X takes place, to nucleoplasm, interacting with p53, and enhancing the transcriptional regulation of the guardian of the genome protein. Molecular interactions have been quantitatively described and spatiotemporally localized at the highest spatial resolution by a simultaneous analysis of the impairment of the cell-cycle progression. Thanks to the high statistical sampling of the presented protocol, we provide a detailed quantitative description of the molecular events following the DSBs formation. Single-Molecule Localization Microscopy (SMLM) Analysis finally confirmed the p53-53BP1 interaction on the tens of nanometers scale during the distinct phases of the response.

Characterization of epithelial cells, connective tissue cells and immune cells in human upper airway mucosa by immunofluorescence multichannel image cytometry: a pilot study.

Epithelial, connective tissue and immune cells contribute in various ways to the pathophysiology of chronic rhinosinusitis (CRS). However, data of their distribution in upper airway mucosa are sparse. We aimed to provide quantitative, purely informative data on the distribution of these cell lineages and their coexpression patterns, which might help identifying, e.g., cells in the epithelium undergoing through epithelial-mesenchymal transition (EMT). For this purpose, we used immunofluorescence multichannel image cytometry (IMIC). We examined fixed paraffin-embedded tissue samples (FFPE) of six patients with chronic rhinosinusitis (CRS) and of three patients without CRS (controls). The direct-conjugated antibodies pancytokeratin, vimentin and CD45/CD18 were used for coexpression analysis in epithelial layer and lamina propria. Image acquisition and analysis were performed with TissueFAXS and StrataQuest, respectively. To distinguish positive from negative expression, a ratio between cell-specific immunostaining intensity and background was developed. Isotype controls were used as negative controls. Per patient, a 4.5-mm2 tissue area was scanned and a median of 14,875 cells was recognized. The most common cell types were cytokeratin-single-positive (26%), vimentin-single-positive (13%) and CD45/CD18-single-positive with CD45/CD18-vimentin-double-positive cells (29%). In the patients with CRS, CD45/CD18-single-positive cells were 3-6 times higher compared to the control patients. In the epithelial layer, cytokeratin-vimentin-double-positive EMT cells were observed 3-5 times higher in the patients with CRS than in the control patients. This study provided quantitative data for the distribution of crucial cell types in CRS. Future studies may focus on the distribution and coexpression patterns of different immune cells in CRS or even cancer tissue.

High-Throughput Image Cytometry Detection Method for CAR-T Transduction, Cell Proliferation, and Cytotoxicity Assays.

Chimeric antigen receptor (CAR)-T cell therapy has drawn much attention due to its recent clinical success in B-cell malignancies. In general, the CAR-T cell discovery process consists of CAR identification, T-cell activation, transduction, and expansion, as well as assessment of CAR-T cytotoxicity. The current evaluation methods for the CAR-T discovery process can be time-consuming, low-throughput and requires the preparation of multiple sacrificial samples in order to produce kinetic data. In this study, we employed the use of a plate-based image cytometer to monitor anti-CAIX (carbonic anhydrase IX) G36 CAR-T generation and assess its cytotoxic potency of direct and selective killing against CAIX+ SKRC-59 human renal cell carcinoma cells. The transduction efficiency and cytotoxicity results were analyzed using image cytometry and compared directly to flow cytometry and Chromium 51 (51 Cr) release assays, showing that image cytometry was comparable against these conventional methods. Image cytometry method streamlines the assays required during the CAR-T cell discovery process by analyzing a plate of T cells from CAR-T generation to in vitro functional assays with minimum disruption. The proposed method can reduce assay time and uses less cell samples by imaging and analyze the same plate over time without the need to sacrifice any cells. The ability to monitor kinetic data can allow additional insights into the behavior and interaction between CAR-T and target tumor cells. © 2020 International Society for Advancement of Cytometry.

Open-source method of image cytometry in dorsal root ganglia tissue with immunofluorescence.

Immunohistochemistry (IHC) is a valuable tool in clinical and biological research for evaluating proteins and other antigens in spatially bound tissue. In neuroinflammatory pain research, primary afferent neurons of the dorsal root ganglion (DRG) are studied to understand molecular signaling mechanisms involved in nociception (pain) and inflammation. Measuring IHC (immunofluorescence) in DRG neurons requires manual hand tracing of nuclear and somatic boundaries, which is laborious, error-prone, and may require several weeks to collect the appropriate sample size with a mouse or pen-input display monitor. To overcome these limitations and increase standardization of sampling and measurement, we employed a reliable neuronal cytoplasmic reporter, exclusive to DRG neuronal soma, in a semi-automated algorithm-based approach of Image Cytometry in rat DRG (IC-DRG). The resulting output images are binary nuclear and somatic masks of DRG neurons, defining boundaries of measurement for CellProfiler and manually scored at 94% accurate. Herein, we successfully show a novel approach of automated image analysis for DRG neurons using a robust ImageJ/FIJI script, overcoming morphological variability and imaging artifacts native to imaging frozen tissue sections processed with immunofluorescence.

An improved algorithm using a Health Canada-approved DNA-image cytometry system for non-invasive screening of high-grade oral lesions.

BACKGROUND: DNA-image cytometry (DNA-ICM) is able to detect gross alterations of cellular DNA-content representing aneuploidy, a biomarker of malignancy. A Health Canada-approved DNA-ICM system, ClearCyte® in combination with a cytopathologist's review, has demonstrated high sensitivity (89%) and specificity (97%) in identifying high-grade oral lesions. The study objective was to create an improved automated algorithm (iClearcyte) and test its robustness in differentiating high grade from benign reactive oral lesions without a cytopathologist's input. METHODS: A set of 214 oral brushing samples of oral cancer (n = 92), severe dysplasia (n = 20), reactive lesions (n = 52), and normal samples (n = 50) were spun down onto slides and stained using Feulgen-Thionin reaction. Following ClearCyte® scan, nuclear features were calculated, and nuclei categorized into "diploid," "hyperdiploid," "tetraploid," and "aneuploid" DNA ploidy groups by the ClearCyte® software. The samples were randomized into training and test sets (70:30) based on patient's age, sex, tobacco use, and lesion site risk. The training set was used to create a new algorithm which was then validated using the remaining samples in the test set, where sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS: The proposed iClearCyte algorithm (>1 "aneuploid" cell or ≥ 1.7% combined "hyperdiploid" and "tetraploid" nuclei frequency) identified high-grade samples with sensitivity, specificity, PPV, and NPV of 100.0%, 86.7%, 89.7%, and 100.0%, respectively, in the test set. CONCLUSION: The iClearCyte test has potential to serve as a robust non-invasive automated oral cancer screening tool promoting early oral cancer detection and decreasing the number of unnecessary invasive biopsies.

DNA ploidy measurement and human papillomavirus in abnormal cervical cytology.

OBJECTIVE: To compare the efficacy of high-risk human papillomavirus (HR-HPV) and DNA image cytometry (DNA-ICM) status for identifying high-grade cervical intraepithelial neoplasia or worse (≥CIN2). METHODS: This cross-sectional study was performed in women undergoing follow-up procedure after a previous abnormal cervical cytology. Cervical cells were collected for HPV detection and DNA ploidy measurement. Biopsy samples were taken for histological confirmation. Sensitivity and specificity values for ≥CIN2 detection with HR-HPV and DNA-ICM were determined. RESULTS: HR-HPV was present in 74.5% of the women. The most frequent HPV infection was HPV 16, followed by HPV 31, 33 and 58. Aneuploidy was observed in 60.6% of all cases. Referral cytology revealed 78.0% sensitivity and 68.6% specificity for detecting a ≥CIN2 lesion. The HR-HPV test alone showed 92.7% sensitivity, albeit it was not statistically different from DNA-ICM (88.1%, P > .05). Positivity for HPV or DNA-ICM resulted in 100% sensitivity. Higher specificity was observed for the combination of HR-HPV and DNA-ICM (88.6%), with no difference from DNA-ICM alone (85.7%, P > .05). CONCLUSION: DNA-ICM or HR-HPV positivity identified all cases of ≥CIN2 in women undergoing follow-up procedure after a previous abnormal cervical cytology. Routine cervical cancer screening could be improved by the incorporation of DNA-ICM as a complementary method to primary screening to identify which women need closer follow-up.