Aptamer Probes Labeled with Lanthanide-Doped Carbon Nanodots Permit Dual-Modal Fluorescence and Mass Cytometric Imaging.

High-dimensional imaging mass cytometry (IMC) enables simultaneous quantification of over 35 biomarkers on one tissue section. However, its limited resolution and ultralow acquisition speed remain major issues for general clinical application. Meanwhile, conventional immunofluorescence microscopy (IFM) allows sub-micrometer resolution and rapid identification of the region of interest (ROI), but only operates with low multiplicity. Herein, a series of lanthanide-doped blue-, green-, and red-fluorescent carbon nanodots (namely, B-Cdots(Ln1 ), G-Cdots(Ln2 ), and R-Cdots(Ln3 )) as fluorescence and mass dual-modal tags are developed. Coupled with aptamers, B-Cdots(159 Tb)-A10-3.2, G-Cdots(165 Ho)-AS1411, and R-Cdots(169 Tm)-SYL3C dual-functional aptamer probes, which are then multiplexed with commercially available Maxpar metal-tagged antibodies for analyzing clinical formalin-fixed, paraffin-embedded (FFPE) prostatic adenocarcinoma (PaC) tissue, are further synthesized. The rapid identification of ROI with IFM using fluorescence signals and subsequent multiplexed detection of in situ ROI with IMC using the same tissue section is demonstrated. Dual-modal probes save up to 90% IMC blind scanning time for a standard 3.5 mm × 3.5 mm overall image. Meanwhile, the IFM provides refined details and topological spatial distributions for the functional proteins at optical resolution, which compensates for the low resolution of the IMC imaging.

Immunological Hallmarks for Clinical Response to BCG in Bladder Cancer.

Intravesical Bacillus Calmette-Guerin (BCG) is an effective immunotherapy for non-muscle invasive bladder cancer (NMIBC). However, recurrence and progression remain frequent warranting deeper insights into its mechanism. We herein comprehensively profiled blood and tissues obtained from NMIBC patients before, during and after BCG treatment using cytometry by time-of-flight (CyTOF) and RNA sequencing to identify the key immune subsets crucial for anti-tumor activity. We observed the temporal changes of peripheral immune subsets including NKT cells, central memory CD4+ T cells, CD8+ T cells and regulatory T cells (Treg) during the course of BCG. Gene expression analysis revealed enriched immune pathways involving in T cell activation and chemotaxis, as well as a more diversified T cell receptor repertoire in post-BCG tissues. Moreover, tissue multiplexed-immunofluorescence (mIF) showed baseline densities of non-Treg and CD8+PD-1+ T cells were predictive of response and better recurrence-free survival after BCG. Remarkably, post-BCG tissues from responders were found to be infiltrated with more active CD8+PD-1- T cells and non-Treg CD4+FOXP3- T cells; but increased exhausted CD8+PD-1+ T cells were found in non-responders. Taken together, we identified predictive biomarkers for response and uncovered the post-treatment expansion of exhausted PD-1+CD8+ T cells as key to BCG resistance, which could potentially be restored by combining with anti-PD-1 immunotherapy.

Deep Learning in Image Cytometry: A Review.

Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and how it is applied to microscopy image data of cells and tissue samples. Starting with an analogy to neuroscience, we aim to give the reader an overview of the key concepts of neural networks, and an understanding of how deep learning differs from more classical approaches for extracting information from image data. We aim to increase the understanding of these methods, while highlighting considerations regarding input data requirements, computational resources, challenges, and limitations. We do not provide a full manual for applying these methods to your own data, but rather review previously published articles on deep learning in image cytometry, and guide the readers toward further reading on specific networks and methods, including new methods not yet applied to cytometry data. © 2018 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

A portable image-based cytometer for rapid malaria detection and quantification.

Increasing resistance by malaria parasites to currently used antimalarials across the developing world warrants timely detection and classification so that appropriate drug combinations can be administered before clinical complications arise. However, this is often challenged by low levels of infection (referred to as parasitemia) and presence of predominantly young parasitic forms in the patients' peripheral blood. Herein, we developed a simple, inexpensive and portable image-based cytometer that detects and numerically counts Plasmodium falciparum infected red blood cells (iRBCs) from Giemsa-stained smears derived from infected blood. Our cytometer is able to classify all parasitic subpopulations by quantifying the area occupied by the parasites within iRBCs, with high specificity, sensitivity and negligible false positives (~ 0.0025%). Moreover, we demonstrate the application of our image-based cytometer in testing anti-malarial efficacy against a commercial flow cytometer and demonstrate comparable results between the two methods. Collectively, these results highlight the possibility to use our image-based cytometer as a cheap, rapid and accurate alternative for antimalarial testing without compromising on efficiency and minimal processing time. With appropriate filters applied into the algorithm, to rule out leukocytes and reticulocytes, our cytometer may also be used for field diagnosis of malaria.

Foundations of identifying individual chromosomes by imaging flow cytometry with applications in radiation biodosimetry.

Biodosimetry is an important tool for triage in the case of large-scale radiological or nuclear emergencies, but traditional microscope-based methods can be tedious and prone to scorer fatigue. While the dicentric chromosome assay (DCA) has been adapted for use in triage situations, it is still time-consuming to create and score slides. Recent adaptations of traditional biodosimetry assays to imaging flow cytometry (IFC) methods have dramatically increased throughput. Additionally, recent improvements in image analysis algorithms in the IFC software have resulted in improved specificity for spot counting of small events. In the IFC method for the dicentric chromosome analysis (FDCA), lymphocytes isolated from whole blood samples are cultured with PHA and Colcemid. After incubation, lymphocytes are treated with a hypotonic solution and chromosomes are isolated in suspension, labelled with a centromere marker and stained for DNA content with DRAQ5. Stained individual chromosomes are analyzed on the ImageStream®X (EMD-Millipore, Billerica, MA) and mono- and dicentric chromosome populations are identified and enumerated using advanced image processing techniques. Both the preparation of the isolated chromosome suspensions as well as the image analysis methods were fine-tuned in order to optimize the FDCA. In this paper we describe the method to identify and score centromeres in individual chromosomes by IFC and show that the FDCA method may further improve throughput for triage biodosimetry in the case of large-scale radiological or nuclear emergencies.

Quantifying autophagy: Measuring LC3 puncta and autolysosome formation in cells using multispectral imaging flow cytometry.

The use of multispectral imaging flow cytometry has been gaining popularity due to its quantitative power, high throughput capabilities, multiplexing potential and its ability to acquire images of every cell. Autophagy is a process in which dysfunctional organelles and cellular components that accumulate during growth and differentiation are degraded via the lysosome and recycled. During autophagy, cytoplasmic LC3 is processed and recruited to the autophagosomal membranes; the autophagosome then fuses with the lysosome to form the autolysosome. Therefore, cells undergoing autophagy can be identified by visualizing fluorescently labeled LC3 puncta and/or the co-localization of fluorescently labeled LC3 and lysosomal markers. Multispectral imaging flow cytometry is able to collect imagery of large numbers of cells and assess autophagy in an objective, quantitative, and statistically robust manner. This review will examine the four predominant methods that have been used to measure autophagy via multispectral imaging flow cytometry.

Masks in imaging flow cytometry.

Data analysis in imaging flow cytometry incorporates elements of flow cytometry together with other aspects of morphological analysis of images. A crucial early step in this analysis is the creation of a mask to distinguish the portion of the image upon which further examination of specified features can be performed. Default masks are provided by the manufacturer of the imaging flow cytometer but additional custom masks can be created by the individual user for specific applications. Flawed or inaccurate masks can have a substantial negative impact on the overall analysis of a sample, thus great care must be taken to ensure the accuracy of masks. Here we discuss various types of masks and cite examples of their use. Furthermore we provide our insight for how to approach selecting and assessing the optimal mask for a specific analysis.

Multi-parametric imaging of cell heterogeneity in apoptosis analysis.

Apoptosis is a multistep process of programmed cell death where different morphological and molecular events occur simultaneously and/or consequently. Recent progress in programmed cell death analysis uncovered large heterogeneity in response of individual cells to the apoptotic stimuli. Analysis of the complex and dynamic process of apoptosis requires a capacity to quantitate multiparametric data obtained from multicolor labeling and/or fluorescent reporters of live cells in conjunction with morphological analysis. Modern methods of multiparametric apoptosis study include but are not limited to fluorescent microscopy, flow cytometry and imaging flow cytometry. In the current review we discuss the image-based evaluation of apoptosis on the single-cell and population level by imaging flow cytometry in parallel with other techniques. The advantage of imaging flow cytometry is its ability to interrogate multiparametric morphometric and fluorescence quantitative data in statistically robust manner. Here we describe the current status and future perspectives of this emerging field, as well as some challenges and limitations. We also highlight a number of assays and multicolor labeling probes, utilizing both microscopy and different variants of imaging cytometry, including commonly based assays and novel developments in the field.

Applications of imaging flow cytometry in the diagnostic assessment of acute leukaemia.

Automated imaging flow cytometry integrates flow cytometry with digital microscopy to produce high-resolution digital imaging with quantitative analysis. This enables cell identification based on morphology (cell size, shape), antigen expression, quantification of fluorescence signal intensity and localisation of detected signals (i.e. surface, cytoplasm, nuclear). We describe applications of imaging flow cytometry for the diagnostic assessment of acute leukaemia. These bone marrow malignancies are traditionally diagnosed and classified by cell morphology, phenotype and cytogenetic abnormalities. Traditionally morphology is assessed by light microscopy, phenotyping by conventional flow cytometry and genetics by karyotype and fluorescence in situ hybridisation (FISH) on interphase nuclei/metaphase spreads of cells on slides. Imaging flow cytometry adds a new dimension to the diagnostic assessment of these neoplasms. We describe three specific applications: From this we conclude that imaging flow cytometry offers benefits over conventional diagnostic methods. Specifically the ability to visualise the cells of interest, the pattern and localisation of expressed antigens and assess cytogenetic abnormalities in one integrated automated high-throughput test. Imaging flow cytometry presents a new paradigm for the diagnostic assessment of leukaemia.

Feature Analysis and Automatic Identification of Leukemic Lineage Blast Cells and Reactive Lymphoid Cells from Peripheral Blood Cell Images.

BACKGROUND: Automated peripheral blood (PB) image analyzers usually underestimate the total number of blast cells, mixing them up with reactive or normal lymphocytes. Therefore, they are not able to discriminate between myeloid or lymphoid blast cell lineages. The objective of the proposed work is to achieve automatic discrimination of reactive lymphoid cells (RLC), lymphoid and myeloid blast cells and to obtain their morphologic patterns through feature analysis. METHODS: In the training stage, a set of 696 blood cell images was selected in 32 patients (myeloid acute leukemia, lymphoid precursor neoplasms and viral or other infections). For classification, we used support vector machines, testing different combinations of feature categories and feature selection techniques. Further, a validation was implemented using the selected features over 220 images from 15 new patients (five corresponding to each category). RESULTS: Best discrimination accuracy in the training was obtained with feature selection from the whole feature set (90.1%). We selected 60 features, showing significant differences (P < 0.001) in the mean values of the different cell groups. Nucleus-cytoplasm ratio was the most important feature for the cell classification, and color-texture features from the cytoplasm were also important. In the validation stage, the overall classification accuracy and the true-positive rates for RLC, myeloid and lymphoid blast cells were 80%, 85%, 82% and 74%, respectively. CONCLUSION: The methodology appears to be able to recognize reactive lymphocytes well, especially between reactive lymphocytes and lymphoblasts.

Flow cytometry what you see matters: Enhanced clinical detection using image-based flow cytometry.

Image-based flow cytometry combines the throughput of traditional flow cytometry with the ability to visually confirm findings and collect novel data that would not be possible otherwise. Since image-based flow cytometry borrows measurement parameters and analysis techniques from microscopy, it is possible to collect unique measures (i.e. nuclear translocation, co-localization, cellular synapse, cellular endocytosis, etc.) that would not be possible with traditional flow cytometry. The ability to collect unique outcomes has led many researchers to develop novel assays for the monitoring and detection of a variety of clinical conditions and diseases. In many cases, investigators have innovated and expanded classical assays to provide new insight regarding clinical conditions and chronic disease. Beyond human clinical applications, image-based flow cytometry has been used to monitor marine biology changes, nano-particles for solar cell production, and particle quality in pharmaceuticals. This review article summarizes work from the major scientists working in the field of image-based flow cytometry.

Delineating stages of erythropoiesis using imaging flow cytometry.

Adult humans need to make 2.5million red blood cells (RBCs) every second to maintain a steady state level of 25trillion circulating RBCs. Understanding normal erythropoiesis as well as diseases that afflict the erythron, such as genetic anemias, hyperproliferative disorders, and myelodysplastic syndromes, requires a robust method to delineate erythropoietic intermediates. In order to apply the power of flow cytometry to these studies, challenges of limited immunophenotypic markers, incorporation of significant changes in morphology, and maturational changes that occur along a continuum need to be met. Imaging flow cytometry (IFC) provides a solution to address these challenges. Integration of changes in immunophenotype, loss of RNA (ribosomes), and enucleation, with morphological characteristics of cell and nuclear size, can be used to delineate erythroblasts that correlate with classical histological classifications. A protocol is described that demonstrates the basic approaches of staining panel selection, mask generation and selection of features to best sequentially refine erythroid intermediates and remove contaminating cells with overlapping immunophenotype. Ultimately erythroid cells in the murine bone marrow are divided into seven sub-populations using IFC including four erythroblasts (pro-, basophilic, polychromatophilic and orthochromatic), the pyrenocyte, which contains the eliminated nucleus, the enucleated reticulocyte and the mature RBC.

Imaging flow cytometry analysis of intracellular pathogens.

Imaging flow cytometry has been applied to address questions in infection biology, in particular, infections induced by intracellular pathogens. This methodology, which utilizes specialized analytic software makes it possible to analyze hundreds of quantified features for hundreds of thousands of individual cellular or subcellular events in a single experiment. Imaging flow cytometry analysis of host cell-pathogen interaction can thus quantitatively addresses a variety of biological questions related to intracellular infection, including cell counting, internalization score, and subcellular patterns of co-localization. Here, we provide an overview of recent achievements in the use of fluorescently labeled prokaryotic or eukaryotic pathogens in human cellular infections in analysis of host-pathogen interactions. Specifically, we give examples of Imagestream-based analysis of cell lines infected with Toxoplasma gondii or Mycobacterium tuberculosis. Furthermore, we illustrate the capabilities of imaging flow cytometry using a combination of standard IDEAS™ software and the more recently developed Feature Finder algorithm, which is capable of identifying statistically significant differences between researcher-defined image galleries. We argue that the combination of imaging flow cytometry with these software platforms provides a powerful new approach to understanding host control of intracellular pathogens.

Characterization of neutrophils and macrophages from ex vivo-cultured murine bone marrow for morphologic maturation and functional responses by imaging flow cytometry.

Neutrophils and macrophages differentiate from common myeloid progenitors in the bone marrow, where they undergo nuclear morphologic changes during maturation. During this process, both cell types acquire critical innate immune functions that include phagocytosis of pathogens, and for neutrophils the release of nuclear material called nuclear extracellular traps (NETs). Primary cells used to study these functions are typically purified from mature mouse tissues, but bone marrow-derived ex vivo cultures provide more abundant numbers of progenitors and functionally mature cells. Routine analyses of these cells use conventional microscopy and flow cytometry, which present limitations; microscopy is laborious and subjective, whereas flow cytometry lacks spatial resolution. Here we describe methods to generate enriched populations of neutrophils or macrophages from cryopreserved mouse bone marrow cultured ex vivo, and to use imaging flow cytometry that combines the resolution of microscopy with flow cytometry to analyze cells for morphologic features, phagocytosis, and NETosis.

Qualitative and quantitative analysis of PMN/T-cell interactions by InFlow and super-resolution microscopy.

Neutrophils or polymorphonuclear cells (PMN) eliminate bacteria via phagocytosis and/or NETosis. Apart from these conventional roles, PMN also have immune-regulatory functions. They can transdifferentiate and upregulate MHCII as well as ligands for costimulatory receptors which enables them to behave as antigen presenting cells (APC). The initial step for activating T-cells is the formation of an immune synapse between T-cells and antigen-presenting cells. However, the immune synapse that develops at the PMN/T-cell contact zone is as yet hardly investigated due to the non-availability of methods for analysis of large number of PMN interactions. In order to overcome these obstacles, we introduce here a workflow to analyse the immune synapse of primary human PMN and T-cells using multispectral imaging flow cytometry (InFlow microscopy) and super-resolution microscopy. For that purpose, we used CD3 and CD66b as the lineage markers for T-cells and PMN, respectively. Thereafter, we applied and critically discussed various "masks" for identification of T-cell PMN interactions. Using this approach, we found that a small fraction of transdifferentiated PMN (CD66b+CD86high) formed stable PMN/T-cell conjugates. Interestingly, while both CD3 and CD66b accumulation in the immune synapse was dependent on the maturation state of the PMN, only CD3 accumulation was greatly enhanced by the presence of superantigen. The actin cytoskeleton was weakly rearranged at the PMN side on the immune synapse upon contact with a T-cell in the presence of superantigen. A more detailed analysis using super-resolution microscopy (structured-illumination microscopy, SIM) confirmed this finding. Together, we present an InFlow microscopy based approach for the large scale analysis of PMN/T-cell interactions and - combined with SIM - a possibility for an in-depth analysis of protein translocation at the site of interactions.

Imaging flow cytometry in the assessment of leukocyte-platelet aggregates.

Platelets are subcellular blood elements with a well-established role in haemostasis. Upon activation platelets undergo granule exocytosis, resulting in α-granule P-Selectin being expressed on the cell membrane. This allows binding of activated platelets to P-Selectin glycoprotein ligand 1 (PSGL-1) expressing leukocytes, forming leukocyte-platelet aggregates (LPAs). Whole blood flow cytometry (FCM) has demonstrated that elevated circulating LPAs (especially monocyte LPAs) are linked to atherothrombosis in high risk patients, and that activated platelet binding influences monocytes towards a pro-adhesive and pro-atherogenic phenotype. However, a limitation of conventional FCM is the potential for coincident events to resemble LPAs despite no tethering. Imaging cytometry can be used to characterize LPA formation and distinguish circulating MPAs from coincidental events. Platelets and leukocyte subsets are identified by expression of surface markers (e.g. the lipopolysachharide receptor CD14 on monocytes, glycoprotein Ib CD42b on platelets). In conventional FCM, all events with both leukocyte and platelet characteristics are designated as LPAs. However, by using an 'internal' mask based on the brightfield image and the fluorescent platelet identifier, imaging flow cytometry is able to distinguish leukocytes with tethered platelets (genuine LPAs) from leukocyte with coincidental, untethered platelets nearby. Mechanisms (e.g. adhesion molecules) or consequences (e.g. signal transduction) can then be separately analysed in platelet tethered and untethered leukocytes. Imaging flow cytometry therefore provides a more accurate approach for both enumeration and analysis of LPAs than conventional FCM.

Imaging flow cytometry for the characterization of extracellular vesicles.

Extracellular Vesicles (EVs) are potent bio-activators and inter-cellular communicators that play an important role in both health and disease. It is for this reason there is a strong interest in understanding their composition and origin, with the hope of using them as important biomarkers or therapeutics. Due to their very small size, heterogeneity, and large numbers there has been a need for better tools to measure them in an accurate and high throughput manner. While traditional flow cytometry has been widely used for this purpose, there are inherent problems with this approach, as these instruments have traditionally been developed to measure whole cells, which are orders of magnitude larger and express many more molecules of identifying epitopes. Imaging flow cytometry, as performed with the ImagestreamX MKII, with its combination of increased fluorescence sensitivity, low background, image confirmation ability and powerful data analysis tools, provides a great tool to accurately evaluate EVs. We present here a comprehensive approach in applying this technology to the study of EVs.

Quantifying MHC dextramer-induced NFAT activation in antigen-specific T cells as a functional response parameter.

MHC-multimers are reagents used for the detection and enumeration of antigen-specific T cells (ASTs). These reagents exploit the mechanism by which T cell receptors (TCR) on cytotoxic CD8 T cells recognize specific antigens in the context of a major histocompatibility complex (MHC) molecule during antigen presentation. MHC-multimers are fluorescently-labeled dextran polymers that carry MHC Class I molecules and peptide sequences that can be modified to represent specific cognate sequences of the antigen of interest with dextramers having a 10-fold multiplicity of the MHC/peptide combination within a single multimer. Since the binding of antigen-specific dextramers mimics antigen presentation to the TCR, the present study sought to determine whether this TCR engagement on the AST was sufficient to elicit a functional T cell response. The effect of binding of CMV specific dextramers on the activation of the NFAT signal transduction cascade was assessed in peripheral blood from bone marrow transplant recipients previously determined to be positive for CMV-ASTs (CASTs). NFAT activation was quantified by measuring nuclear translocation of NFAT1 in CD8+ CASTs and CD8+ non-CASTs by imaging flow cytometry. Our results demonstrate that an increase in the nuclear localization of NFAT1 was detectable in the CASTs following the CMV-dextramer binding and could be observed as early as 10min post-exposure. The NFAT1 activation correlated with a downstream functional response in the form of interferon gamma production. Sample preparation, temperature, and duration of dextramer exposure were important parameters affecting the dextramer-induced NFAT activation with 2h exposure in whole blood at room temperature being the optimal of the conditions tested. Intra- and inter-individual heterogeneity was observed with regards to the NFAT activation in the CASTs. Importantly, no effect of the dextramers was observed in the CD8+ non-CASTs, and therefore dextramer negative cell populations. Exposure to PMA/ionomycin following dextramer exposure resulted in a homogeneous NFAT activation in both the dextramer-positive but NFAT1 nonresponsive CAST and non-CAST cells. Thus, the data demonstrate that binding of antigen-specific dextramers to ASTs specifically results in activation of NFAT, that the NFAT activation correlates with a downstream functional response and that the response can be heterogeneous. This functional parameter may provide insight to the issue whether enumeration alone of ASTs is a sufficient parameter to assess an individual's immune status against a specific antigen.

Spectral Unmixing Plate Reader: High-Throughput, High-Precision FRET Assays in Living Cells.

We have developed a microplate reader that records a complete high-quality fluorescence emission spectrum on a well-by-well basis under true high-throughput screening (HTS) conditions. The read time for an entire 384-well plate is less than 3 min. This instrument is particularly well suited for assays based on fluorescence resonance energy transfer (FRET). Intramolecular protein biosensors with genetically encoded green fluorescent protein (GFP) donor and red fluorescent protein (RFP) acceptor tags at positions sensitive to structural changes were stably expressed and studied in living HEK cells. Accurate quantitation of FRET was achieved by decomposing each observed spectrum into a linear combination of four component (basis) spectra (GFP emission, RFP emission, water Raman, and cell autofluorescence). Excitation and detection are both conducted from the top, allowing for thermoelectric control of the sample temperature from below. This spectral unmixing plate reader (SUPR) delivers an unprecedented combination of speed, precision, and accuracy for studying ensemble-averaged FRET in living cells. It complements our previously reported fluorescence lifetime plate reader, which offers the feature of resolving multiple FRET populations within the ensemble. The combination of these two direct waveform-recording technologies greatly enhances the precision and information content for HTS in drug discovery.

High-Throughput Spectral and Lifetime-Based FRET Screening in Living Cells to Identify Small-Molecule Effectors of SERCA.

A robust high-throughput screening (HTS) strategy has been developed to discover small-molecule effectors targeting the sarco/endoplasmic reticulum calcium ATPase (SERCA), based on a fluorescence microplate reader that records both the nanosecond decay waveform (lifetime mode) and the complete emission spectrum (spectral mode), with high precision and speed. This spectral unmixing plate reader (SUPR) was used to screen libraries of small molecules with a fluorescence resonance energy transfer (FRET) biosensor expressed in living cells. Ligand binding was detected by FRET associated with structural rearrangements of green fluorescent protein (GFP, donor) and red fluorescent protein (RFP, acceptor) fused to the cardiac-specific SERCA2a isoform. The results demonstrate accurate quantitation of FRET along with high precision of hit identification. Fluorescence lifetime analysis resolved SERCA's distinct structural states, providing a method to classify small-molecule chemotypes on the basis of their structural effect on the target. The spectral analysis was also applied to flag interference by fluorescent compounds. FRET hits were further evaluated for functional effects on SERCA's ATPase activity via both a coupled-enzyme assay and a FRET-based calcium sensor. Concentration-response curves indicated excellent correlation between FRET and function. These complementary spectral and lifetime FRET detection methods offer an attractive combination of precision, speed, and resolution for HTS.