Imaging Flow Cytometer Research Articles

The Imaging Flow Cytometry-Based Cytokinesis-Block MicroNucleus (CBMN) Assay.

The dose of ionizing radiation received by an individual can be determined using biodosimetry methods which measure biomarkers of exposure in tissue samples from that individual. These markers can be expressed in many ways, including DNA damage and repair processes. Following a mass casualty event involving radiological or nuclear material, it is important to rapidly provide this information to medical responders to assist in the medical management of potentially exposed casualties. Traditional methods of biodosimetry rely on microscope analysis, making them time-consuming and labor-intensive. To increase sample throughput following a large-scale radiological mass casualty event, several biodosimetry assays have been adapted for analysis by imaging flow cytometry. This chapter briefly reviews these methods with a focus on the most current methodology to identify and quantify micronuclei in binucleated cells within the cytokinesis-block micronucleus assay using an imaging flow cytometer.

The ruthenium complex assists in nuclear targeting and selective killing of tumor cells.

In clinical studies, the toxicity of platinum-based antitumor drugs limits their use. DNA is the most widely studied target of metal-based complexes. Thus, nuclear targeting and selective killing have become the purpose of ruthenium complex design. We synthesized a carboline derivative and its ruthenium complex, NBD and NBD-Ru, and characterized their properties. UV spectra were used to monitor their stability. Transmission electron microscopy and dynamic light scattering were used to identify the self-assembly properties. Inductively coupled plasma mass spectrometry was used to assay the distribution of the Ru complexes in cells with or without transferrin. Besides, the tumor cell killing activities with or without transferrin were detected by MTT assay. An imaging flow cytometer was applied to observe the fluorescence further to identify the cellular distribution. The effects of NBD and NBD-Ru on DNA and the cell cycle were also measured. In vivo, the antitumor and antimetastatic activities of NBD and NBD-Ru were assessed in S180 and LLC tumor-bearing mice. We found that introducing Ru improved the solubility and stability, enabling NBD-Ru to self-assemble into nanoparticles with the EPR effect. At the same time, binding affinity with transferrin increased significantly after complexation, meaning NBD-Ru could target and selectively kill tumors via Tf/TfR pathway. More interestingly, ruthenium assisted the complex in achieving nuclear penetration, which can kill tumor cells by interacting with DNA. In vivo experiments further verified our conclusion in vitro. NBD-Ru could inhibit not only the growth of a primary tumor but also lung metastasis, which was related to the killing effect of the complex on tumor cells (Ki67) and inhibition of neovascularization (CD31). At the same time, the systemic toxicity of the ruthenium complex in vivo was reduced because of the targeting effect, and the biosafety was improved. In conclusion, we found that ruthenium assisted in nuclear targeting and selective killing in vitro and in vivo.

Optimizing FlowCam Imaging Flow Cytometry Operation for Classification and Quantification of Microcystis Morphospecies.

Microcystis is a globally known cyanobacterium causing potentially toxic blooms worldwide. Different morphospecies with specific morphological and physiological characters usually co-occur during blooming, and their quantification employing light microscopy can be time-consuming and problematic. A benchtop imaging flow cytometer (IFC) FlowCam (Yokogawa Fluid Imaging Technologies, USA) was used to identify and quantitate different Microcystis morphospecies from environmental samples. We describe here theFlowCam methodology for sample processing and analysis of five European morphospecies of Microcystis common to the temperate zone. The FlowCam technique allows detection of different Microcystis morphospecies providing objective qualitative and quantitative data for statistical analysis.

Development of an Imaging and Impedance Flow Cytometer Based on a Constriction Microchannel and Deep Neural Pattern Recognition

This article presents an imaging and impedance flow cytometer based on a constriction microchannel with corresponding cell-type classification based on deep neural pattern recognition. When an incoming cell reached the entrance of the constriction microchannel, the image of the nucleus labeled with fluorescence was captured by a high-speed camera without the concern of losing focus, whereas when the cell deformed through the constriction microchannel by effectively blocking electrical lines, large impedance variations were sampled by an impedance analyzer. Six key biostructural and bioelectrical parameters (e.g., cell diameter, nuclear roundness, and cytoplasmic conductivity) from thousands of single cells were extracted, producing a successful rate of 88.3% in classifying A549 versus Jurkat versus K562 cells based on the feedforward neural network. In addition, multilayer neural networks of deep learning (e.g., VGG16 of CNN and LSTM of RNN) were also used to process fluorescent images and impedance profiles, producing an almost 100% successful rate in cell-type classification. In summary, the microfluidic flow cytometer reported in this article could characterize single-cell biostructural and bioelectrical properties in a high throughput manner, realizing high successful rates of cell-type classification.

IGH cytogenetic abnormalities can be detected in multiple myeloma by imaging flow cytometry

AimsCytogenetic abnormalities involving the IGH gene are seen in up to 55% of patients with multiple myeloma. Current testing is performed manually by fluorescence in situ hybridisation (FISH) on purified...

Towards operational phytoplankton recognition with automated high-throughput imaging, near-real-time data processing, and convolutional neural networks

Plankton communities form the basis of aquatic ecosystems and elucidating their role in increasingly important environmental issues is a persistent research question. Recent technological advances in automated microscopic imaging, together with cloud platforms for high-performance computing, have created possibilities for collecting and processing detailed high-frequency data on planktonic communities, opening new horizons for testing core hypotheses in aquatic ecosystems. Analyzing continuous streams of big data calls for development and deployment of novel computer vision and machine learning systems. The implementation of these analysis systems is not always straightforward with regards to operationality, and issues regarding data flows, computing and data treatment need to be considered. We created a data pipeline for automated near-real-time classification of phytoplankton during remote deployment of imaging flow cytometer (Imaging FlowCytobot, IFCB). Convolutional neural network (CNN) is used to classify continuous imaging data with probability thresholds used to filter out images not belonging to our existing classes. The automated data flow and classification system were used to monitor dominating species of filamentous cyanobacteria on the coast of Finland during summer 2021. We demonstrate that good phytoplankton recognition can be achieved with transfer learning utilizing a relatively shallow, publicly available, pre-trained CNN model and fine-tuning it with community-specific phytoplankton images (overall F1-score of 0.95 for test set of our labeled image data complemented with a 50% unclassifiable image portion). This enables both fast training and low computing resource requirements for model deployment making it easy to modify and applicable in wide range of situations. The system performed well when used to classify a natural phytoplankton community over different seasons (overall F1-score 0.82 for our evaluation data set). Furthermore, we address the key challenges of image classification for varying planktonic communities and analyze the practical implications of confused classes. We published our labeled image data set of Baltic Sea phytoplankton community for the training of image recognition models (~63000 images in 50 classes) to accelerate implementation of imaging systems for other brackish and freshwater communities. Our evaluation data set, 59 fully annotated samples of natural communities throughout an annual cycle, is also available for model testing purposes (~150000 images).

Combining imaging flow cytometry and machine learning for high-throughput schistocyte quantification: A SVM classifier development and external validation cohort.

SummaryBackgroundSchistocyte counts are a cornerstone of the diagnosis of thrombotic microangiopathy syndrome (TMA). Their manual quantification is complex and alternative automated methods suffer from pitfalls that limit their use. We report a method combining imaging flow cytometry (IFC) and artificial intelligence for the direct label-free and operator-independent quantification of schistocytes in whole blood.MethodsWe used 135,045 IFC images from blood acquisition among 14 patients to extract 188 features with IDEAS® software and 128 features from a convolutional neural network (CNN) with Keras framework in order to train a support vector machine (SVM) blood elements’ classifier used for schistocytes quantification.FindingKeras features showed better accuracy (94.03%, CI: 93.75-94.31%) than ideas features (91.54%, CI: 91.21-91.87%) in recognising whole-blood elements, and together they showed the best accuracy (95.64%, CI: 95.39-95.88%). We obtained an excellent correlation (0.93, CI: 0.90-0.96) between three haematologists and our method on a cohort of 102 patient samples. All patients with schistocytosis (>1% schistocytes) were detected with excellent specificity (91.3%, CI: 82.0-96.7%) and sensitivity (100%, CI: 89.4-100.0%). We confirmed these results with a similar specificity (91.1%, CI: 78.8-97.5%) and sensitivity (100%, CI: 88.1-100.0%) on a validation cohort (n=74) analysed in an independent healthcare centre. Simultaneous analysis of 16 samples in both study centres showed a very good correlation between the 2 imaging flow cytometers (Y=1.001x).InterpretationWe demonstrate that IFC can represent a reliable tool for operator-independent schistocyte quantification with no pre-analytical processing which is of most importance in emergency situations such as TMA.FundingNone.

Multimodal NASH prognosis using 3D imaging flow cytometry and artificial intelligence to characterize liver cells

To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) morphology at single-cell resolution. In this study, HSC and LEC were obtained from biopsy-proven NASH subjects with early-stage NASH (F2-F3) and healthy controls. Here, we applied single-cell imaging and 3D digital reconstructions of healthy and diseased cells to analyze a spatially resolved set of morphometric cellular and texture parameters that showed regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN) based on label-free cell transmission and side scattering images obtained from a 3D imaging flow cytometer, we demonstrated key regulated cell types involved in the development of NASH and cell classification performance superior to conventional machine learning methods.

P964: IMMUNOPHENOTYPED-SUSPENSION-MULTIPLEX FISH BY IMAGING FLOW CYTOMETRY FOR THE SIMULTANEOUS DIAGNOSIS OF THREE PIVOTAL IGH TRANSLOCATIONS IN MULTIPLE MYELOMA

Background: The cytogenetic abnormalities including t(4;14)(p16;q32), t(14;16)(q32;q23), and t(11;14)(q13;q32) are associated with the molecular profiles, clinical features, and treatment outcome in multiple myeloma (MM). Although the double-color interphase fluorescence in situ hybridization (DC-FISH) is well established to detect those translocations, the conventional method can analyze only one abnormality on each slide. Aims: To analyze multiple chromosomal abnormalities simultaneously with high sensitivity and specificity, we aimed to develop a new diagnostic modality of four-color FISH for multiple translocations in immunophenotyped cells in suspension using imaging flow cytometry (immunophenotyped-suspension-multiplex (ISM)-FISH). Methods: For the ISM-FISH, we first subjected Carnoy-fixed cells in suspension to immunostaining using a brilliant violet 421-conjugated anti-CD138 antibody. Then, we hybridized with four different FISH probes, i.e., Texas Red (TxRed)-conjugated probe for IGH, fluorescein isothiocyanate (FITC)-conjugated probe for FGFR3, Gold-conjugated probe for cyclin D1 (CCND1), and Cy5-conjugated probe for c-MAF, in suspension. Then, more than 2.5 × 104 nucleated cells for each sample were analyzed with imaging flow cytometer MI-1000 (Sysmex) by six channels: one for immunophenotyping, four for FISH and one for bright field image. In the process of imaging flowcytometric analysis, we sorted CD138-positive cell fraction, computed the distance between FISH probes using originally developed spot counting tool, and determined to be positive for translocation when the distance is under the threshold. Results: By this ISM-FISH system, we simultaneously examined three chromosomal translocations, including t(4;14), t(14;16), and t(11;14), in three MM cell lines, KMS-11, KMS-21-BM, KMS-26, and successfully detect the abnormalities. Using different proportions of transformation-positive MM cells spiked with transformation-negative leukemic cells, HL-60, ISM-FISH showed a sensitivity of less than 0.1%. Next, ISM-FISH and conventional DC-FISH were performed for bone marrow nucleated cells from 70 patients with MM or monoclonal gammopathy of undetermined significance (MGUS) and the experiments showed a promising qualitative diagnostic ability in detecting t(11;14), t(4;14), and t(14;16) of our ISM-FISH, which was more sensitive than standard DC-FISH, examining 200 interphase cells with its optimal sensitivity of up to 1.0%. Furthermore, the ISM-FISH showed a positive concordance of 83.3% and negative concordance of 97.4% using standard DC-FISH, examining 200 interphase cells. Furthermore, in three patients (4%), t(4;14) or t(11;14) were positive by ISM-FISH but negative by DC-FISH examining 200 cells. Extensive DC-FISH study examining additional 1,000 cells showed positive in these ISM-FISH-positive/DC-FISH (200cells)-negative samples, suggesting higher sensitivity of ISM-FISH than that of the standard DC-FISH. Image:Summary/Conclusion: This study developed the new diagnostic system of ISM-FISH, which enables the simultaneous diagnosis of three clinically pivotal chromosomal translocations, t(4;14), t(14;16), and t(11;14), in MGUS and MM. This system may facilitate rapid and reliable cytogenetic diagnosis and promote patient-oriented therapy according to the type of chromosomal translocation in the clinical practice setting.

Reporting of methods for automated devices: A systematic review and recommendation for studies using FlowCam for phytoplankton

AbstractAccurate and detailed reporting of methods is essential for scientific progress, yet it is widely accepted that authors across all scientific fields tend to provide insufficient methods detail. Given the recent proliferation of automated and semi‐automated technologies for data collection, to address this widespread issue the details needed for interpretation and reproducibility for each specific technique first need to be identified. A systematic literature review assessed the comprehensiveness of method details reported by 116 peer‐reviewed studies published between 2017 and 2020 using the FlowCam (a widely used imaging flow cytometer) to image phytoplankton, finding all to be lacking in critical details, inhibiting reproducibility, and limiting the veracity of some findings. Through this review and three case studies, we identify several key method details that should be reported by FlowCam studies to ensure their findings are credible, comparable, and replicable and illustrate the wide‐reaching implications for not doing so. Future studies using FlowCam for phytoplankton analyses should ensure clear reporting of all relevant details relating to the FlowCam unit, sample preparation, run settings, post‐processing of images, and the considered use of only verified measurement outputs. A methods reporting template is presented as a guideline intended to enhance the quality, interpretability, and repeatability of future FlowCam papers. The pervasiveness of inadequacies in FlowCam methods reporting identified here highlights how vital it is for users of any automated or semi‐automated scientific technologies to have a clear understanding of the impact of all method details on their findings, and to report these details adequately.

Photoinducible Azobenzene trimethylammonium bromide (AzoTAB)-mediated giant vesicle fusion compatible with synthetic protein translation reactions

Lipid giant vesicles represent a versatile minimal model system to study the physicochemical basis of lipid membrane fusion. Membrane fusion processes are also of interest in synthetic cell research, where cell-mimicking behavior often requires dynamically interacting compartments. For these applications, triggered fusion compatible with transcription-translation systems is key in achieving complexity. Recently, a photosensitive surfactant, azobenzene trimethylammonium bromide (AzoTAB), has been reported to induce membrane fusion by a photoinduced conformational change. Using imaging flow cytometer (IFC) and confocal microscopy we quantitatively investigated photoinduced AzoTAB-mediated fusion of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine vesicles. The IFC analysis result showed that the fusion rate could reach about 40% following AzoTAB addition and UV irradiation in optimized conditions. We confirmed the compatibility between AzoTAB-induced vesicle fusion and a synthetic cell-free protein translation system using green fluorescent protein as reporter. With the techniques presented, cell-sized vesicle fusion can be quantitatively analyzed and optimized, paving the way to controllable synthetic cells with fundamental biological functions like the ability to express proteins from encapsulated plasmids.

Multiparametric Phenotyping of Circulating Tumor Cells for Analysis of Therapeutic Targets, Oncogenic Signaling Pathways and DNA Repair Markers.

Simple SummaryDetection of circulating tumor cells (CTCs) has been established as an independent prognostic marker in solid cancer. In order to expand the clinical utility of this blood–based minimally invasive biomarker we established a protocol allowing multiparametric phenotyping of CTCs to analyze the expression levels of therapeutic target proteins. By applying this assay, we demonstrated intratumoral heterogeneity of PD–L1 expression in CTCs from head and neck cancer patients, an observation previously reported in tumor tissue specimens. We further verified the feasibility of applying the protocol to analyze the activation status of important oncogenic pathways and the extent of DNA repair following radiation. These promising preliminary results warrant further study and may lead to the implementation of this assay in clinical routine for improved treatment selection and monitoring.Detection of circulating tumor cells (CTCs) has been established as an independent prognostic marker in solid cancer. Multiparametric phenotyping of CTCs could expand the area of application for this liquid biomarker. We evaluated the Amnis® brand ImageStream®X MkII (ISX) (Luminex, Austin, TX, USA) imaging flow cytometer for its suitability for protein expression analysis and monitoring of treatment effects in CTCs. This was carried out using blood samples from patients with head and neck squamous cell carcinoma (n = 16) and breast cancer (n = 8). A protocol for negative enrichment and staining of CTCs was established, allowing quantitative analysis of the therapeutic targets PD–L1 and phosphorylated EGFR (phospho–EGFR), and the treatment response marker γH2AX as an indicator of radiation–induced DNA damage. Spiking experiments revealed a sensitivity of 73% and a specificity of 100% at a cut–off value of ≥3 CTCs, and thus confirmed the suitability of the ISX-based protocol to detect phospho–EGFR and γH2AX foci in CTCs. Analysis of PD–L1/–L2 in both spiked and patient blood samples further showed that assessment of heterogeneity in protein expression within the CTC population was possible. Further validation of the diagnostic potential of this ISX protocol for multiparametric CTC analysis in larger clinical cohorts is warranted.

High-Efficiency Bovine Sperm Sexing Used Magnetic-Activated Cell Sorting by Coupling scFv Antibodies Specific to Y-Chromosome-Bearing Sperm on Magnetic Microbeads

Simple SummaryFemale calves are favored for milk production and genetic advancement in the dairy industry, and sex selection by using sexed semen has been long considered. A potential alternative sperm sexing technique is magnetic-activated cell sorting combined with an immunological method that uses scFv antibodies against male-specific sites on Y-chromosome-bearing sperm; however, the technique should be evaluated for validity and accuracy. This study focuses on how well bovine sperm are separated by the use of magnetic microbeads coupled with scFv antibodies against Y-chromosome-bearing sperm (PY-microbeads). The results showed that sexed bovine sperm using PY-microbeads was a highly effective technique for distinguishing X- and Y-chromosome-bearing sperm. It had no negative impact on the quality of X-chromosome-bearing sperm. The technique produced 82.65% of X-chromosome sperm in the X-enriched fraction semen and 81.43% of Y-chromosome sperm in the Y-enriched fraction semen, which was utilized to generate target sexed bovine semen.Sperm sexing technique is favored in the dairy industry. This research focuses on the efficiency of bovine sperm sexing using magnetic-activated cell sorting (MACS) by scFv antibody against Y-chromosome-bearing sperm (Y-scFv) coupled to magnetic microbeads and its effects on kinematic variables, sperm quality, and X/Y-sperm ratio. In this study, the optimal concentration of Y-scFv antibody coupling to the surface of magnetic microbeads was 2–4 mg/mL. PY-microbeads revealed significantly enriched Y-chromosome-bearing sperm (Y-sperm) in the eluted fraction (78.01–81.43%) and X-chromosome-bearing sperm (X-sperm) in the supernatant fraction (79.04–82.65%). The quality of frozen–thawed sexed sperm was analyzed by CASA and imaging flow cytometer, which showed that PY-microbeads did not have a negative effect on X-sperm motility, viability, or acrosome integrity. However, sexed Y-sperm had significantly decreased motility and viability. The X/Y-sperm ratio was determined using an imaging flow cytometer and real-time PCR. PY-microbeads produced sperm with up to 82.65% X-sperm in the X-enriched fraction and up to 81.43% Y-sperm in the Y-enriched fraction. Bovine sperm sexing by PY-microbeads showed high efficiency in separating Y-sperm from X-sperm and acceptable sperm quality. This initial technique is feasible for bovine sperm sexing, which increases the number of heifers in dairy herds while lowering production expenses.

A rapid and fully automated in vitro micronucleus assay using imaging flow cytometry and convolutional neural network analysis

Abstract Micronuclei (MN) originate from whole chromosomes or chromosome fragments that lag behind during cell division and fail to be incorporated into one of the two main nuclei. As a result, scoring MN using the well-established in vitro micronucleus assay evaluates the ability of chemicals or other agents to induce DNA damage. This technique is typically performed by manual microscopy, which can be time-consuming and prone to variability. Additionally, automated methods lack cytoplasmic visualization when using slide-scanning microscopy, and conventional flow cytometry doesn’t provide visual confirmation of MN. The ImageStream®X Mk II (ISX) imaging flow cytometer combines the high-resolution imagery of microscopy with conventional flow cytometry’s speed and statistical robustness in a single system. Previously, we developed a rapid and automated MN assay based on high-throughput image capture and feature-based image analysis using IDEAS® Software. However, the feature-based analysis was not readily applicable to multiple cell lines and chemicals, so we developed a deep learning method based on convolutional neural networks to score imaging flow cytometry data in both the cytokinesis-blocked and unblocked versions of the MN assay using Amnis® AI Software. Our current study validates our previously established assay and analyses using three different chemicals (Mitomycin C, Cyclophosphamide, and Eugenol) and three different cell lines (TK6, L5178Y, CHO-K1). Here, we demonstrate how using Amnis AI to score imagery acquired on the ISX provides a rapid and fully automated in vitro MN assay with improved accuracy, reproducibility, and time-to-results in toxicity and biodosimetry applications across multiple cell lines.

Gene signature of circulating platelet-bound neutrophils is associated with poor prognosis in cancer patients.

Beyond their critical role in hemostasis, platelets physically interact with neutrophils to form neutrophil‐platelet aggregates (NPAs), enhancing neutrophil effector functions during inflammation. NPAs may also promote disease worsening in various inflammatory diseases. However, characterization of NPAs in cancer remains totally unexplored. Using ImageStreamX (ISX) imaging flow cytometer, we were not only allowed able to detect CD15+ CD14− CD36+ ITGA2B+ NPAs in both healthy donors' (HDs) and cancer patients' bloods, but we also showed that NPAs result from the binding of platelets preferentially to low‐density neutrophils (LDNs) as opposed to normal‐density neutrophils (NDNs). By reanalyzing two independent public scRNAseq data of whole blood leukocytes from cancer patients and HDs, we could identify a subset of neutrophils with high platelet gene expression that may correspond to NPAs. Moreover, we showed that cancer patients' derived NPAs possessed a distinct molecular signature compared to the other neutrophil subsets, independently of platelet genes. Gene ontology (GO) term enrichment analysis of this NPAs‐associated neutrophil transcriptomic signature revealed a significant enrichment of neutrophil degranulation, chemotaxis and trans‐endothelial migration GO terms. Lastly, using The Cancer Genome Atlas (TCGA), we could show by multivariate Cox analysis that the NPAs‐associated neutrophil transcriptomic signature was associated with a worse patient prognosis in several cancer types. These results suggest that neutrophils from NPAs are systemically primed by platelets empowering them with cancer progression capacities once at tumor site. NPAs may therefore hold clinical utility as novel noninvasive blood prognostic biomarker in cancer patients with solid tumors.

A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer

We develop a high-throughput technique to relate positions of individual cells to their three-dimensional (3D) imaging features with single-cell resolution. The technique is particularly suitable for nonadherent cells where existing spatial biology methodologies relating cell properties to their positions in a solid tissue do not apply. Our design consists of two parts, as follows: recording 3D cell images at high throughput (500 to 1,000 cells/s) using a custom 3D imaging flow cytometer (3D-IFC) and dispensing cells in a first-in-first-out (FIFO) manner using a robotic cell placement platform (CPP). To prevent errors due to violations of the FIFO principle, we invented a method that uses marker beads and DNA sequencing software to detect errors. Experiments with human cancer cell lines demonstrate the feasibility of mapping 3D side scattering and fluorescent images, as well as two-dimensional (2D) transmission images of cells to their locations on the membrane filter for around 100,000 cells in less than 10 min. While the current work uses our specially designed 3D imaging flow cytometer to produce 3D cell images, our methodology can support other imaging modalities. The technology and method form a bridge between single-cell image analysis and single-cell molecular analysis.

Machine learning assisted real-time deformability cytometry of CD34+ cells allows to identify patients with myelodysplastic syndromes

Diagnosis of myelodysplastic syndrome (MDS) mainly relies on a manual assessment of the peripheral blood and bone marrow cell morphology. The WHO guidelines suggest a visual screening of 200 to 500 cells which inevitably turns the assessor blind to rare cell populations and leads to low reproducibility. Moreover, the human eye is not suited to detect shifts of cellular properties of entire populations. Hence, quantitative image analysis could improve the accuracy and reproducibility of MDS diagnosis. We used real-time deformability cytometry (RT-DC) to measure bone marrow biopsy samples of MDS patients and age-matched healthy individuals. RT-DC is a high-throughput (1000 cells/s) imaging flow cytometer capable of recording morphological and mechanical properties of single cells. Properties of single cells were quantified using automated image analysis, and machine learning was employed to discover morpho-mechanical patterns in thousands of individual cells that allow to distinguish healthy vs. MDS samples. We found that distribution properties of cell sizes differ between healthy and MDS, with MDS showing a narrower distribution of cell sizes. Furthermore, we found a strong correlation between the mechanical properties of cells and the number of disease-determining mutations, inaccessible with current diagnostic approaches. Hence, machine-learning assisted RT-DC could be a promising tool to automate sample analysis to assist experts during diagnosis or provide a scalable solution for MDS diagnosis to regions lacking sufficient medical experts.

An Imaging Flow Cytometry Protocol for Studying Immunoregulatory Receptor-Mediated Regulation of Phagocytosis.

Advances in flow cytometry have allowed for innovative functional investigations of innate immune cell responses. Imaging flow cytometers combine the imaging capabilities of microscopy with rapid, high-throughput data acquisition attributes of standard flow cytometers. Here, we describe a detailed method for co-expressing stimulatory and inhibitory immunoregulatory receptor-types in AD293 cells and then measuring receptor cross-talk during the regulation of the phagocytic response. Information on reagent selection, imaging flow cytometry calibration, and automated template analyses are included.

CD33 BiTE ® Construct Mediated Immunological Synapse Formation and Downstream Signaling in T Cells Is Dependent on Expression of Costimulatory Molecules on Target Cells

CD33 BiTE ® Construct Mediated Immunological Synapse Formation and Downstream Signaling in T Cells Is Dependent on Expression of Costimulatory Molecules on Target Cells

Characterizing Naked Nuclei Frequency and Movement in Primary AML Cell Culture Using an ECM-Based Model

INTRODUCTIONNaked nuclei (NN) are observed upon examining bone marrow aspirate slides from healthy individuals and from those with hematologic malignancies, but are not well understood. Without characteristic findings like cytoplasm or plasma membrane, NN are considered remnants of slide preparation or are discounted as cells of undetermined significance. NN have been associated with poor prognosis in several solid cancers. Understanding the significance of NN in hematologic malignancies such as acute myelogenous leukemia (AML) may elucidate valuable diagnostic and prognostic knowledge. Decellularized Wharton's jelly matrix (DWJM) is an extra cellular matrix (ECM)-based in vitro model that shares similar elements with the bone marrow ECM and can be used as scaffolding to culture leukemia cells. We hypothesize that NN exist in AML and interact with other cells, suggesting potential biological relevance within the bone marrow microenvironment.METHODSPrimary AML samples obtained by leukapheresis were cultured in suspension with growth media or in the presence of DWJM submerged in growth media. In samples grown with DWJM, cells that were non-adherent to the matrix were collected first and then adherent cells were isolated by treating DWJM with collagenase. Live cells were stained with CellVue Maroon (CVM) for membrane, CellTracker Green (CTG) for cytoplasm, and Hoechst 33342 for nucleus, followed by analysis with Amnis/Luminex ImageStream-X imaging flow cytometer (Figure 1A). NN were defined as events positive for nuclear stain and negative for cytoplasmic and membrane stains (Figure 1B). 3-D movement of adherent AML cells in DWJM was captured in real time using confocal microscopy. Fixed cells from leukemia cell line K562 served as a control for movement. NN (Hoechst positive only), non-nucleated (Hoechst negative/CTG positive), and nucleated cells (Hoechst and CTG positive) were identified by fluorescent labeling. NN were also observed after isolation by cell sorting. Cell speed, cell displacement from origin, and change in distance to closest neighboring cell over time were measured. Additionally, flow sorted NN were examined by immunohistochemistry (IHC).RESULTSAdherent populations contained significantly more NN than non-adherent and suspension populations. The frequency of NN in matrix adherent cells ranged from 0.4-2.4% at day 3 and 0.5-5.4% at day 7 of culture (Figure 1C). Through confocal microscopic analysis, we observed NN, nucleated, and non-nucleated cells moving at speeds ranging from 0.002-0.08 µm/sec. Fixed cells showed no discernible movement in DWJM. The average speed of NN [0.019 mm/s, SD 0.011] significantly differed from the average speed of nucleated and non-nucleated cells [0.027 mm/s, SD 0.016] (p=0.004) (Figure 1E). To demonstrate directional movement, we measured change in distance between NN and closest neighboring nucleated or non-nucleated cells over time. Cells (nucleated and non-nucleated) and NN moved closer to each other over time suggesting directional movement (p=0.001) (Figure 1D). NN also showed movement in DWJM after isolation by cell sorting. IHC analysis showed sorted NN stained positive for nuclear lamin A/C, which are considered markers of nuclear membrane (Figure 1F).CONCLUSIONSOur findings confirm that NN are present in primary AML cells cultured in vitro using ourECM-based model and that they can be isolated using flow cytometry. Additionally, NN display directional movement in DWJM suggesting that they interact with other cells and may be biologically relevant structures in the bone marrow microenvironment. [Display omitted] DisclosuresBaran: AstraZeneca/Acerta: Research Funding. Chu: Pfizer: Current equity holder in publicly-traded company; Acerta/AstraZeneca: Research Funding; TG Therapeutics: Research Funding.