High-throughput Imaging Platform Research Articles

Electrochemiluminescence of hot exciton nanomaterial with boosted efficiency for visual bioanalysis

The electrochemiluminescence (ECL) efficiency (ΦECL) of organic ECL emitters is greatly influenced by the excited state property and component. Here we design a hot exciton molecule (BCzP-BT) with hybridized local and charge-transfer (HLCT) excited state property to prepare the first hot exciton organic nanorods (BB NRs). The BB NRs exhibit both sensitive annihilation and intense coreactant ECL emissions with a band gap emission model. Due to the reverse intersystem crossing among high-lying excited states (hRISC), the HLCT excited state property leads to highly efficient utilization of triplet excitons and thus high photoluminescence quantum yields (ΦPL) of more than 80% at 554 nm, which is demonstrated by solvatochromic experiments and quantum chemical calculations. The high ΦPL endows BB NRs with superior ΦECL over other nanoemitters, even the thermally activated delayed fluorescence materials, and thus offers highly-efficient nanoemitters for the design of ECL imaging strategy. As a proof of concept, an ECL probe is constructed by assembling BHQ2-ssDNA on BB NRs to integrate CRISPR/Cas12a system for target recognition, which produces a rapid and high-throughput ECL imaging platform. The proposed imaging method for HPV16 DNA detection shows excellent performance with a detection limit of 0.6 fM. This work broadens the application of hot exciton materials in ECL field, and opens a new avenue for developing next-generation ECL devices.

Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications.

Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing trials, a number of retrospective approaches can be adopted to understand differences in response, recurrence and progression by examining the patient's TME from tissue samples obtained at baseline and at various time points along the treatment. The multiplex immunofluorescence (mIF) technique provides insight on patient specific cell populations and their relative spatial distribution as qualitative measures of a favorable treatment outcome. Spatial analysis of these images provides an understanding of the intratumoral heterogeneity and clustering among cell populations in the TME. A number of mathematical models, which establish clustering as a measure of deviation from complete spatial randomness, can be applied to the mIF images represented as spatial point patterns. These mathematical models, developed for landscape ecology and geographic information studies, can be applied to the TME after careful consideration of the tumor type (cold vs. hot) and the tumor immune landscape. The spatial modelling of mIF images can show observable engagement of T cells expressing immune checkpoint molecules and this can then be correlated with single-cell RNA sequencing data.

Abstract 18778: Patient-Derived Stem Cell Models of Pediatric Restrictive Cardiomyopathy Exhibit Increased Resting Tension and Cardiomyocyte Calcium Sensitivity

Introduction: Pediatric Restrictive Cardiomyopathy (RCM) is a genetic cardiomyopathy resulting from profoundly increased stiffness of the wall of the cardiac ventricle with normal or low normal contractility. Treatment options are limited, with most patients necessitating heart transplant. Therapies that can improve diastolic function are needed for this severe disease. However, development of novel therapies has been limited by a paucity of models of this rare disease. Here, we develop two novel models of pediatric RCM and use novel high-throughput functional analysis to measure diastolic dysfunction and defects in calcium handling. Hypothesis: Patient-derived human induced pluripotent stem cell (hiPSC) models of pediatric RCM will exhibit increased resting tension indicative of diastolic dysfunction, as well as increased calcium sensitivity. Methods: Cardiomyocytes were differentiated from hiPSCs derived from two pediatric patients with RCM, as well as a paired isogenic CRISPR-corrected lines. Cells were replated onto polyacrylamide gels and stained with calcium sensitive dyes, and contractility, resting tension, and calcium sensitivity were measured using a novel high-throughput functional imaging platform. Results: RCM cells from both patients showed elevated contractility, resting tension, and calcium sensitivity compared to their isogenic controls. Conclusions: Patient-derived RCM cells show alterations in calcium sensitivity and resting tension that recapitulate and explain the diastolic dysfunction seen in patients. These lines, combined with the high-throughput measurement platform described here, will provide a powerful platform for exploring novel therapeutic strategies for this severe disease.

A high-throughput single-particle imaging platform for antibody characterization and a novel competition assay for therapeutic antibodies

Monoclonal antibodies (mAbs) play an important role in diagnostics and therapy of infectious diseases. Here we utilize a single-particle interferometric reflectance imaging sensor (SP-IRIS) for screening 30 mAbs against Ebola, Sudan, and Lassa viruses (EBOV, SUDV, and LASV) to find out the ideal capture antibodies for whole virus detection using recombinant vesicular stomatitis virus (rVSV) models expressing surface glycoproteins (GPs) of EBOV, SUDV, and LASV. We also make use of the binding properties on SP-IRIS to develop a model for mapping the antibody epitopes on the GP structure. mAbs that bind to mucin-like domain or glycan cap of the EBOV surface GP show the highest signal on SP-IRIS, followed by mAbs that target the GP1-GP2 interface at the base domain. These antibodies were shown to be highly efficacious against EBOV infection in non-human primates in previous studies. For LASV detection, 8.9F antibody showed the best performance on SP-IRIS. This antibody binds to a unique region on the surface GP compared to other 15 mAbs tested. In addition, we demonstrate a novel antibody competition assay using SP-IRIS and rVSV-EBOV models to reveal the competition between mAbs in three successful therapeutic mAb cocktails against EBOV infection. We provide an explanation as to why ZMapp cocktail has higher efficacy compared to the other two cocktails by showing that three mAbs in this cocktail (13C6, 2G4, 4G7) do not compete with each other for binding to EBOV GP. In fact, the binding of 13C6 enhances the binding of 2G4 and 4G7 antibodies. Our results establish SP-IRIS as a versatile tool that can provide high-throughput screening of mAbs, multiplexed and sensitive detection of viruses, and evaluation of therapeutic antibody cocktails.

Abstract 15247: A Novel Patient-Derived Stem Cell Model of Restrictive Cardiomyopathy Exhibits Impaired Cardiomyocyte Relaxation Secondary to Increased Myocardial Calcium Sensitivity

Introduction: Restrictive Cardiomyopathy (RCM) is a rare disease characterized by profound, isolated defects in myocardial relaxation, normal or near-normal myocardial wall thickness, and preserved contractile function. Outcomes for patients with RCM are poor, with increased morbidity and mortality compared to other forms of cardiomyopathy. In some patients, RCM can be caused by genetic mutations, notably in genes encoding for components of the sarcomere. While many mutations have been described in RCM patients, the molecular and cellular mechanisms leading from these mutations to the patient’s physiological phenotype are poorly described. Hypothesis: Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) derived from RCM patients will recapitulate the myocardial relaxation defects seen in RCM and provide a novel in vitro model for investigating the molecular mechanisms underpinning this disease. Methods: Induced pluripotent stem cells (iPSCs) were derived from a pediatric patient with RCM caused by a TNNT2 R94C mutation. CRISPR was used to correct the mutation, and cellular mechanics and calcium handling properties were compared to the patient line using a novel high-throughput traction-force imaging platform. Transcriptional profiles were compared using RNA-seq. Results: RCM cells carrying the TNNT2 R94C mutation show increased calcium sensitivity leading to increased resting tension at baseline, as well as prolonged calcium kinetics leading to prolonged relaxation times. Gene expression profiling reveals changes in expression of ECM genes, which may further contribute to the impaired myocardial relaxation seen in RCM. Conclusions: Patient-derived hiPSC-CMs from an RCM patient recapitulate the relaxation defects seen in RCM and highlight the central role of increased calcium sensitivity in impaired myocardial relaxation.

Abstract P2113: A Novel Patient-derived Stem Cell Model Of Restrictive Cardiomyopathy Exhibits Impaired Cardiomyocyte Relaxation Secondary To Increased Myocardial Calcium Sensitivity

Introduction: Restrictive Cardiomyopathy (RCM) is a rare disease characterized by profound, isolated defects in myocardial relaxation, normal or near-normal myocardial wall thickness, and preserved contractile function. Outcomes for patients with RCM are poor, with increased morbidity and mortality compared to other forms of cardiomyopathy. In some patients, RCM can be caused by genetic mutations, notably in genes encoding for components of the sarcomere. While many mutations have been described in RCM patients, the molecular and cellular mechanisms leading from these mutations to the patient’s physiological phenotype are poorly described. Hypothesis: Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) derived from RCM patients will recapitulate the myocardial relaxation defects seen in RCM and provide a novel in vitro model for investigating the molecular mechanisms underpinning this disease. Methods: Induced pluripotent stem cells (iPSCs) were derived from a pediatric patient with RCM caused by a TNNT2 R94C mutation. CRISPR was used to correct the mutation, and cellular mechanics and calcium handling properties were compared to the patient line using a novel high-throughput traction-force imaging platform. Transcriptional profiles were compared using RNA-seq. Results: RCM cells carrying the TNNT2 R94C mutation show increased calcium sensitivity leading to increased resting tension at baseline, as well as prolonged calcium kinetics leading to prolonged relaxation times. Gene expression profiling reveals changes in expression of ECM genes, which may further contribute to the impaired myocardial relaxation seen in RCM. Conclusions: Patient-derived hiPSC-CMs from an RCM patient recapitulate the relaxation defects seen in RCM and highlight the central role of increased calcium sensitivity in impaired myocardial relaxation.

Abstract 2978: Unique 3D organoids autologous TIL coculture platform enables high throughput immune-oncology drug response studies

Abstract Background: Cancer progression and response to therapy are governed by complex cellular interactions in the tumor microenvironment (TME). A better understanding of TME and the immune microenvironment requires robust experimental systems modeling patient specific immune interactions. Conventional 2D cultures lack in recapitulating 3D morphological structures and complex immune biology of native human tumors. A vastly heterogenous TME impacts patient treatment response. There is a dearth of 2D or 3D in vitro models that mimic in vivo diversity of TME, including infiltrating immune populations. 3D organoid cultures typically contain neoplastic epithelium and fail to retain syngeneic tumor-infiltrating lymphocytes (TILs) interactions vital for exhibiting a clinically significant drug response. Here we describe patient-derived xenograft (PDX) derived 3D organoid (PDXO) cultures with autologous TILs to avoid alloreactivity and simulate tumor specific immune response. The described model allows the evaluation of TIL infiltration and high throughput screening of immune-modulatory therapies. Methods: Patient-derived xenografts from mice were enzymatically digested to establish PDXO. PDXO were characterized for expression of cancer specific cell-surface markers. TILs were expanded in culture from PBMCs from matching patients and characterized using flow cytometry. Organoids and TILs from the same patient were fluorescently labeled and cocultured for four days, and tumor infiltration and drug cytotoxicity with and without immune-therapeutics was evaluated. CellInsight CX7 high content imaging platform was used to track TILs, and cancer cells, and TIL infiltration was confirmed via immunofluorescence. Luminex technology was used to quantify changes in the cytokine profile upon drug treatment. Results: PDXO were established to mimic in vivo tumor biology. Tumor-specific TILs were expanded and characterized for expression of memory, inhibitory, proliferation, and regulatory T cell markers. TIL infiltration in organoids was observed from day one in culture and maintained over four days. Immunofluorescence for T cell marker CD3 (cluster of differentiation 3) within PDXO confirmed TIL infiltration. Infiltrating TILs and tumor cell killing evaluation using fluorescent dyes via high throughput imaging platform showed disease and patient-specific response. PDXO treatment with immune-modulatory therapeutics led to changes in the secreted levels of cytokines IL2 (interleukin 2), IFNγ (interferon gamma), and TNFα (tumor necrotic factor alpha). Conclusion: Our patient autologous TILs - PDXO culture platform can be used for high throughput drug screening to model immune-therapeutic response with the tumor specific immune microenvironment. Citation Format: Garima Kaushik, Padma Kamineny, Amy Wesa. Unique 3D organoids autologous TIL coculture platform enables high throughput immune-oncology drug response studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2978.

Low false positive and accurate detection of yeast cell viability and concentration using an automatic staining and lensfree imaging platform

Yeast cell viability and concentration are the crucial factors affecting product quality in food industry and bio-fuel production, as well as the evaluation basis for environmental toxic compounds. To overcome the drawbacks of existing methods, including high error, false positive and low automation, we propose a highly accurate approach based on an automatic staining and high-throughput lensfree imaging platform. A precisely controlled staining process is implemented automatically, which largely avoids the error caused by inappropriate exposure times. Based on optical simulation analysis, energy distribution characteristics are proposed. They are better with steady theoretical evidence for live yeast cell recognition. The parameters are directly extracted from raw cell fingerprints without any reconstruction. Those progresses improve robustness and increase efficiency. Availability of this approach is validated by compared the detection results with gold-standard PI counting method in a H2O2 toxicity test. So it is expected to be widely used in industrial production and environmental toxicity assessment.

An Automated, Single Cell Quantitative Imaging Microscopy Approach to Assess Micronucleus Formation, Genotoxicity and Chromosome Instability.

Micronuclei are small, extranuclear bodies that are distinct from the primary cell nucleus. Micronucleus formation is an aberrant event that suggests a history of genotoxic stress or chromosome mis-segregation events. Accordingly, assays evaluating micronucleus formation serve as useful tools within the fields of toxicology and oncology. Here, we describe a novel micronucleus formation assay that utilizes a high-throughput imaging platform and automated image analysis software for accurate detection and rapid quantification of micronuclei at the single cell level. We show that our image analysis parameters are capable of identifying dose-dependent increases in micronucleus formation within three distinct cell lines following treatment with two established genotoxic agents, etoposide or bleomycin. We further show that this assay detects micronuclei induced through silencing of the established chromosome instability gene, SMC1A. Thus, the micronucleus formation assay described here is a versatile and efficient alternative to more laborious cytological approaches, and greatly increases throughput, which will be particularly beneficial for large-scale chemical or genetic screens.

Optimization of Insect Odorant Receptor Trafficking and Functional Expression Via Transient Transfection in HEK293 Cells.

Insect odorant receptors (ORs) show a limited functional expression in various heterologous expression systems including insect and mammalian cells. This may be in part due to the absence of key components driving the release of these proteins from the endoplasmic reticulum and directing them to the plasma membrane. In order to mitigate this problem, we took advantage of small export signals within the human HCN1 and Rhodopsin that have been shown to promote protein release from the endoplasmic reticulum and the trafficking of post-Golgi vesicles, respectively. Moreover, we designed a new vector based on a bidirectional expression cassette to drive the functional expression of the insect odorant receptor coreceptor (Orco) and an odor-binding OR, simultaneously. We show that this new method can be used to reliably express insect ORs in HEK293 cells via transient transfection and that is highly suitable for downstream applications using automated and high-throughput imaging platforms.

Convolutional Deblurring for Natural Imaging.

In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to many imaging applications that suffer from optical imperfections. Despite numerous deconvolution methods that blindly estimate blurring in either inclusive or exclusive forms, they are practically challenging due to high computational cost and low image reconstruction quality. Both conditions of high accuracy and high speed are prerequisites for high-throughput imaging platforms in digital archiving. In such platforms, deblurring is required after image acquisition before being stored, previewed, or processed for high-level interpretation. Therefore, on-the-fly correction of such images is important to avoid possible time delays, mitigate computational expenses, and increase image perception quality. We bridge this gap by synthesizing a deconvolution kernel as a linear combination of finite impulse response (FIR) even-derivative filters that can be directly convolved with blurry input images to boost the frequency fall-off of the point spread function (PSF) associated with the optical blur. We employ a Gaussian low-pass filter to decouple the image denoising problem for image edge deblurring. Furthermore, we propose a blind approach to estimate the PSF statistics for two Gaussian and Laplacian models that are common in many imaging pipelines. Thorough experiments are designed to test and validate the efficiency of the proposed method using 2054 naturally blurred images across six imaging applications and seven state-of-the-art deconvolution methods.

Comparison and extension of three methods for automated registration of multimodal plant images

With the introduction of high-throughput multisensory imaging platforms, the automatization of multimodal image analysis has become the focus of quantitative plant research. Due to a number of natural and technical reasons (e.g., inhomogeneous scene illumination, shadows, and reflections), unsupervised identification of relevant plant structures (i.e., image segmentation) represents a nontrivial task that often requires extensive human-machine interaction. Registration of multimodal plant images enables the automatized segmentation of ’difficult’ image modalities such as visible light or near-infrared images using the segmentation results of image modalities that exhibit higher contrast between plant and background regions (such as fluorescent images). Furthermore, registration of different image modalities is essential for assessment of a consistent multiparametric plant phenotype, where, for example, chlorophyll and water content as well as disease- and/or stress-related pigmentation can simultaneously be studied at a local scale. To automatically register thousands of images, efficient algorithmic solutions for the unsupervised alignment of two structurally similar but, in general, nonidentical images are required. For establishment of image correspondences, different algorithmic approaches based on different image features have been proposed. The particularity of plant image analysis consists, however, of a large variability of shapes and colors of different plants measured at different developmental stages from different views. While adult plant shoots typically have a unique structure, young shoots may have a nonspecific shape that can often be hardly distinguished from the background structures. Consequently, it is not clear a priori what image features and registration techniques are suitable for the alignment of various multimodal plant images. Furthermore, dynamically measured plants may exhibit nonuniform movements that require application of nonrigid registration techniques. Here, we investigate three common techniques for registration of visible light and fluorescence images that rely on finding correspondences between (i) feature-points, (ii) frequency domain features, and (iii) image intensity information. The performance of registration methods is validated in terms of robustness and accuracy measured by a direct comparison with manually segmented images of different plants. Our experimental results show that all three techniques are sensitive to structural image distortions and require additional preprocessing steps including structural enhancement and characteristic scale selection. To overcome the limitations of conventional approaches, we develop an iterative algorithmic scheme, which allows it to perform both rigid and slightly nonrigid registration of high-throughput plant images in a fully automated manner.

A high-throughput ratiometric method for imaging hypertrophic growth in cultured primary cardiac myocytes

Maladaptive hypertrophy of cardiac myocytes increases the risk of heart failure. The underlying signaling can be triggered and interrogated in cultured neonatal ventricular myocytes (NRVMs) using sophisticated pharmacological and genetic techniques. However, the methods for quantifying cell growth are, by comparison, inadequate. The lack of quantitative, calibratable and computationally-inexpensive high-throughput technology has limited the scope for using cultured myocytes in large-scale analyses. We present a ratiometric method for quantifying the hypertrophic growth of cultured myocytes, compatible with high-throughput imaging platforms. Protein biomass was assayed from sulforhodamine B (SRB) fluorescence, and image analysis calculated the quotient of signal from extra-nuclear and nuclear regions. The former readout relates to hypertrophic growth, whereas the latter is a reference for correcting protein-independent (e.g. equipment-related) variables. This ratiometric measure, when normalized to the number of cells, provides a robust quantification of cellular hypertrophy. The method was tested by comparing the efficacy of various chemical agonists to evoke hypertrophy, and verified using independent assays (myocyte area, transcripts of markers). The method's high resolving power and wide dynamic range were confirmed by the ability to generate concentration-response curves, track the time-course of hypertrophic responses with fine temporal resolution, describe drug/agonist interactions, and screen for novel anti-hypertrophic agents. The method can be implemented as an end-point in protocols investigating hypertrophy, and is compatible with automated plate-reader platforms for generating high-throughput data, thereby reducing investigator-bias. Finally, the computationally-minimal workflow required for obtaining measurements makes the method simple to implement in most laboratories.

Application progress of new detection techniques for peripheral blood circulating tumor cells in prostate cancer

Circulating tumor cells (CTC) refer to tumor cells that survive from the primary or metastatic tumors through active or passive blood entry and escape immune killing. With the continuous development of modern detection technology, the studies on some new CTC detection and separation technology including Cell Search system, Adna Test system, high-throughput imaging platform and microfluidic chip technology in prostate cancer have gradually made in-depth progresses. This article reviews the latest application progress of these new detection techniques in prostate cancer. Key words: Prostatic neoplasms; Neoplastic cells, circulating; Prognosis

An automatable, field camera track system for phenotyping crop lodging and crop movement

Abstract High throughput phenotyping systems enable rapid data collection for plant breeders. Some plant traits such as lodging, or the breaking and falling over of plant stems under wind stress, are complex and not easily measured through existing high throughput imaging platforms. We present designs for an automatable camera system that can be used in the quantification of crop lodging and crop movement under field wind conditions. Using a 360FLY 4K hemispherical video camera, industrial curtain track, and a raspberry pi computer, the camera system is capable of capturing aspects of crop lodging and movement unquantifiable by other phenotyping systems, such as unmanned aerial vehicles. The design is versatile and inexpensive relative to commercial camera track systems, and could be employed to quantify a variety of plant traits from detailed images in a field setting.

Systematic Profiling of Histone Readers in Arabidopsis thaliana

Histone post-translational modifications (PTMs) and their recognition by histone readers exert crucial functions in eukaryotes. Despite extensive studies, conservation and diversity of histone PTM regulation between animals and plants remain less explored because of a lack of systematic knowledge of histone readers in plants. Based on a high-throughput surface plasmon resonance imaging (SPRi) platform, we report the lab-on-chip profiling of interactions between 204 putative reader domains and 11 types of histone peptides in Arabidopsis thaliana. Eleven reader hits were then chosen for histone combinatorial readout pattern profiling. Systematic analysis of histone PTM recognition in Arabidopsis thaliana reveals that plant and human histone readers share conservation in domain types and recognition mechanisms. The differences in particular histone mark recognition by transcription regulator EML1 and DNA damage repair factor MSH6 indicate plant-specific histone PTMs function in Arabidopsis thaliana acquired during evolution.

Abstract 429: Assessment of Functional Mitochondrial Parameters in Single Cardiomyocytes Reveals Critical Events Not Identified in Cell Populations

In cardiomyocytes (CMs), mitochondria play a dual role, maintaining the high energy supply required for rhythmic contraction, but also regulating critical cell death signaling. Impaired mitochondrial function can affect cellular homeostasis and contribute to sub-lethal injury; if mitochondrial impairment is more severe or persistent, pro-death pathways are activated. It is becoming increasingly clear, however, that within a population of cells there is considerable heterogeneity in mitochondrial function between individual CMs; and within a single cell there is also heterogeneity between individual mitochondria/mitochondrial regions. We have developed a high-throughput fluorescence imaging platform to quantitate single CM mitochondrial function in large numbers of cells, yielding information missed using standard assays that evaluate cell populations. When CMs are exposed to H 2 O 2 , they exhibit a dramatic hyperpolarization prior to the loss of mitochondrial membrane potential at the onset of cell contraction and death. There is marked heterogeneity in the timing of this response, with three distinct populations identified using Gaussian mixture models, and the duration of hyperpolarization longer for CMs that hypercontract earlier after H 2 O 2 exposure. This hyperpolarization is accompanied by a simultaneous increase in [Ca 2+ ] i and is preceded by an increase in ROS. Standard methods, which average populations of cells, miss these responses. Blockade of MPT opening with cyclosporine A delays hypercontracture and cell death but does not prevent hyperpolarization. Finally, we have used our platform to track individual mitochondria/mitochondrial regions within a single live CM, identifying mitochondrial heterogeneity within a single cell, which is increased after exposure to H 2 O 2 , isoproterenol or in CMs from mice after ischemia-reperfusion injury. By tracking individual CMs and individual mitochondria within a single CM, we have opened a window to the complex heterogeneities in mitochondrial stress response.

A quantitative real-time approach for discriminating apoptosis and necrosis

Apoptosis and necrosis are the two major forms of cell death mechanisms. Both forms of cell death are involved in several physiological and pathological conditions and also in the elimination of cancer cells following successful chemotherapy. Large number of cellular and biochemical assays have evolved to determine apoptosis or necrosis for qualitative and quantitative purposes. A closer analysis of the assays and their performance reveal the difficulty in using any of these methods as a confirmatory approach, owing to the secondary induction of necrosis in apoptotic cells. This highlights the essential requirement of an approach with a real-time analysis capability for discriminating the two forms of cell death. This paper describes a sensitive live cell-based method for distinguishing apoptosis and necrosis at single-cell level. The method uses cancer cells stably expressing genetically encoded FRET-based active caspase detection probe and DsRed fluorescent protein targeted to mitochondria. Caspase activation is visualized by loss of FRET upon cleavage of the FRET probe, while retention of mitochondrial fluorescence and loss of FRET probe before its cleavage confirms necrosis. The absence of cleavage as well as the retention of mitochondrial fluorescence indicates live cells. The method described here forms an extremely sensitive tool to visualize and quantify apoptosis and necrosis, which is adaptable for diverse microscopic, flow cytometric techniques and high-throughput imaging platforms with potential application in diverse areas of cell biology and oncology drug screening.

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

High-throughput analysis of horse sperms’ 3D swimming patterns using computational on-chip imaging

Using a high-throughput optical tracking technique that is based on partially-coherent digital in-line holography, here we report a detailed analysis of the statistical behavior of horse sperms’ three-dimensional (3D) swimming dynamics. This dual-color and dual-angle lensfree imaging platform enables us to track individual 3D trajectories of ∼1000 horse sperms at sub-micron level within a sample volume of ∼9μL at a frame rate of 143 frames per second (FPS) and collect thousands of sperm trajectories within a few hours for statistical analysis of their 3D dynamics. Using this high-throughput imaging platform, we recorded >17,000 horse sperm trajectories that can be grouped into six major categories: irregular, linear, planar, helical, ribbon, and hyperactivated, where the hyperactivated swimming patterns can be further divided into four sub-categories, namely hyper-progressive, hyper-planar, hyper-ribbon, and star-spin. The large spatio-temporal statistics that we collected with this 3D tracking platform revealed that irregular, planar, and ribbon trajectories are the dominant 3D swimming patterns observed in horse sperms, which altogether account for >97% of the trajectories that we imaged in plasma-free semen extender medium. Through our experiments we also found out that horse seminal plasma in general increases sperms’ straightness in their 3D trajectories, enhancing the relative percentage of linear swimming patterns and suppressing planar swimming patterns, while barely affecting the overall percentage of ribbon patterns.