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Journal articles on the topic 'High-Content automated microscopy'

Author: Grafiati

Published: 7 July 2024

Last updated: 31 July 2025

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1

Conrad, Christian, and Daniel W. Gerlich. "Automated microscopy for high-content RNAi screening." Journal of Cell Biology 188, no. 4 (2010): 453–61. http://dx.doi.org/10.1083/jcb.200910105.

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Fluorescence microscopy is one of the most powerful tools to investigate complex cellular processes such as cell division, cell motility, or intracellular trafficking. The availability of RNA interference (RNAi) technology and automated microscopy has opened the possibility to perform cellular imaging in functional genomics and other large-scale applications. Although imaging often dramatically increases the content of a screening assay, it poses new challenges to achieve accurate quantitative annotation and therefore needs to be carefully adjusted to the specific needs of individual screening

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Wang, Jun, Xiaobo Zhou, Pamela L. Bradley, Shih-Fu Chang, Norbert Perrimon, and Stephen T. C. Wong. "Cellular Phenotype Recognition for High-Content RNA Interference Genome-Wide Screening." Journal of Biomolecular Screening 13, no. 1 (2007): 29–39. http://dx.doi.org/10.1177/1087057107311223.

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Genome-wide, cell-based screens using high-content screening (HCS) techniques and automated fluorescence microscopy generate thousands of high-content images that contain an enormous wealth of cell biological information. Such screens are key to the analysis of basic cell biological principles, such as control of cell cycle and cell morphology. However, these screens will ultimately only shed light on human disease mechanisms and potential cures if the analysis can keep up with the generation of data. A fundamental step toward automated analysis of high-content screening is to construct a robu

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Kraus, Oren Z., Ben T. Grys, Jimmy Ba, et al. "Automated analysis of high‐content microscopy data with deep learning." Molecular Systems Biology 13, no. 4 (2017): 924. http://dx.doi.org/10.15252/msb.20177551.

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Nghi, Do Huu, and Le Mai Huong. "APPLICATION OF IMAGE-BASED HIGH CONTENT ANALYSIS FOR THE SCREENING OF BIOACTIVE NATURAL PRODUCTS." Vietnam Journal of Science and Technology 56, no. 4A (2018): 1. http://dx.doi.org/10.15625/2525-2518/56/4a/13065.

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Each bioactive compound induces phenotypic changes in target cells that can be made visible by labelling selected molecules of the cells with fluorescent dyes and/or directly observed under the high-throughput microscope. A comparison of the cellular phenotype induced by a compound of interest with known cellular targets allows predicting its mode of action. Over the past 15 years, high-throughput microscopy has been one of the fastest growing fields in cell biology. When combined with automated multiparametric image and data analysis, it is referred to as high-content screening (HCS). Whilst

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Gilbert, Daniel F., Till Meinhof, Rainer Pepperkok, and Heiko Runz. "DetecTiff©: A Novel Image Analysis Routine for High-Content Screening Microscopy." Journal of Biomolecular Screening 14, no. 8 (2009): 944–55. http://dx.doi.org/10.1177/1087057109339523.

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In this article, the authors describe the image analysis software DetecTiff©, which allows fully automated object recognition and quantification from digital images. The core module of the LabView©-based routine is an algorithm for structure recognition that employs intensity thresholding and size-dependent particle filtering from microscopic images in an iterative manner. Detected structures are converted into templates, which are used for quantitative image analysis. DetecTiff © enables processing of multiple detection channels and provides functions for template organization and fast interp

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Bray, Mark-Anthony, Adam N. Fraser, Thomas P. Hasaka, and Anne E. Carpenter. "Workflow and Metrics for Image Quality Control in Large-Scale High-Content Screens." Journal of Biomolecular Screening 17, no. 2 (2011): 266–74. http://dx.doi.org/10.1177/1087057111420292.

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Automated microscopes have enabled the unprecedented collection of images at a rate that precludes visual inspection. Automated image analysis is required to identify interesting samples and extract quantitative information for high-content screening (HCS). However, researchers are impeded by the lack of metrics and software tools to identify image-based aberrations that pollute data, limiting experiment quality. The authors have developed and validated approaches to identify those image acquisition artifacts that prevent optimal extraction of knowledge from high-content microscopy experiments

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Moreau, Dimitri, and Jean Gruenberg. "Automated Microscopy and High Content Screens (Phenotypic Screens) in Academia Labs." CHIMIA International Journal for Chemistry 70, no. 12 (2016): 878–82. http://dx.doi.org/10.2533/chimia.2016.878.

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Preston, K. "High-resolution image analysis." Journal of Histochemistry & Cytochemistry 34, no. 1 (1986): 67–74. http://dx.doi.org/10.1177/34.1.3941268.

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In many departments of cytology, cytogenetics, hematology, and pathology, research projects using high-resolution computerized microscopy are now being mounted for computation of morphometric measurements on various structural components, as well as for determination of cellular DNA content. The majority of these measurements are made in a partially automated, computer-assisted mode, wherein there is strong interaction between the user and the computerized microscope. At the same time, full automation has been accomplished for both sample preparation and sample examination for clinical determi

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Dorval, Thierry, Arnaud Ogier, Auguste Genovesio, et al. "Contextual Automated 3D Analysis of Subcellular Organelles Adapted to High-Content Screening." Journal of Biomolecular Screening 15, no. 7 (2010): 847–57. http://dx.doi.org/10.1177/1087057110374993.

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Advances in automated imaging microscopy allow fast acquisitions of multidimensional biological samples. Those microscopes open new possibilities for analyzing subcellular structures and spatial cellular arrangements. In this article, the authors describe a 3D image analysis framework adapted to medium-throughput screening. Upon adaptive and regularized segmentation, followed by precise 3D reconstruction, they achieve automatic quantification of numerous relevant 3D descriptors related to the shape, texture, and fluorescence intensity of multiple stained subcellular structures. A global analys

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Wen, Yuan, Kevin A. Murach, Ivan J. Vechetti, et al. "MyoVision: software for automated high-content analysis of skeletal muscle immunohistochemistry." Journal of Applied Physiology 124, no. 1 (2018): 40–51. http://dx.doi.org/10.1152/japplphysiol.00762.2017.

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Analysis of skeletal muscle cross sections is an important experimental technique in muscle biology. Many aspects of immunohistochemistry and fluorescence microscopy can now be automated, but most image quantification techniques still require extensive human input, slowing progress and introducing the possibility of user bias. MyoVision is a new software package that was developed to overcome these limitations. The software improves upon previously reported automatic techniques and analyzes images without requiring significant human input and correction. When compared with data derived by manu

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Gasparri, Fabio, Paolo Cappella, and Arturo Galvani. "Multiparametric Cell Cycle Analysis by Automated Microscopy." Journal of Biomolecular Screening 11, no. 6 (2006): 586–98. http://dx.doi.org/10.1177/1087057106289406.

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Cell cycle analysis using flow cytometry (FC) to measure cellular DNA content is a common procedure in drug mechanism of action studies. Although this technique lends itself readily to cell lines that grow in suspension, adherent cell cultures must be resuspended in a cumbersome and potentially invasive procedure that normally involves trypsinization and mechanical agitation of monolayer cultures. High-content analysis (HCA), an automated microscopy-based technology, is well suited to analysis of monolayer cell cultures but provides intrinsically less accurate determination of cellular DNA con

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Mata, Gadea, Miroslav Radojević, Carlos Fernandez-Lozano, et al. "Automated Neuron Detection in High-Content Fluorescence Microscopy Images Using Machine Learning." Neuroinformatics 17, no. 2 (2018): 253–69. http://dx.doi.org/10.1007/s12021-018-9399-4.

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Thomas, Nick. "Review Article: High-Content Screening: A Decade of Evolution." Journal of Biomolecular Screening 15, no. 1 (2009): 1–9. http://dx.doi.org/10.1177/1087057109353790.

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In the past decade, high-content screening has become a highly developed approach to obtaining richly descriptive quantitative phenotypic data using automated microscopy. From early use in drug screening, the technique has evolved to embrace a diverse range of applications in both academic and industrial sectors and is now widely recognized as providing an efficient and effective approach to large-scale programs investigating cell biology in situ and in context.

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Ibáñez, Glorymar, Paul A. Calder, Constantin Radu, et al. "Evaluation of Compound Optical Interference in High-Content Screening." SLAS DISCOVERY: Advancing the Science of Drug Discovery 23, no. 4 (2017): 321–29. http://dx.doi.org/10.1177/2472555217707725.

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Compound optical interference remains an inherent problem in chemical screening and has been well documented for biochemical assays and less so for automated microscopy-based assays. It has also been the assumption that the latter should not suffer from such interference because of the washing steps involved in the process, thus eliminating the residual nonspecific compound effects. Instead, these compounds may have no relevance to the actual target, and as such, compound optical interference contributes to a number of false-positives, resulting in a high attrition rate during subsequent follo

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Menduti, Giovanna, and Marina Boido. "Recent Advances in High-Content Imaging and Analysis in iPSC-Based Modelling of Neurodegenerative Diseases." International Journal of Molecular Sciences 24, no. 19 (2023): 14689. http://dx.doi.org/10.3390/ijms241914689.

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In the field of neurodegenerative pathologies, the platforms for disease modelling based on patient-derived induced pluripotent stem cells (iPSCs) represent a valuable molecular diagnostic/prognostic tool. Indeed, they paved the way for the in vitro recapitulation of the pathological mechanisms underlying neurodegeneration and for characterizing the molecular heterogeneity of disease manifestations, also enabling drug screening approaches for new therapeutic candidates. A major challenge is related to the choice and optimization of the morpho-functional study designs in human iPSC-derived neur

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Simonen, Marjo, Yvonne Ibig-Rehm, Gabriele Hofmann, et al. "High-Content Assay to Study Protein Prenylation." Journal of Biomolecular Screening 13, no. 6 (2008): 456–67. http://dx.doi.org/10.1177/1087057108318757.

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The mevalonate pathway leads to synthesis of cholesterol and isoprenoid lipids. Prenyltransferases attach the isoprenoid lipids to the C-terminus of several small guanosine triphosphate—binding proteins. The prenyl groups are essential for the biological activity of these proteins. The prenyltransferases and other components of the mevalonate pathway are either present or potential drug targets for cancer, osteoporosis, restenosis, or high serum cholesterol level. Until recently, cellular assays to study protein prenylation have been tedious, low-throughput assays. The authors have developed a

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Ge, Y., D. Zhang, X. Zhou, and Z. Zhang. "High-content Analysis in Monastrol Suppressor Screens." Methods of Information in Medicine 50, no. 03 (2011): 265–72. http://dx.doi.org/10.3414/me09-01-0030.

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SummaryObjectives: High-content screening (HCS) via automated fluorescent microscopy is a powerful technology for the effective expression of cellular processes. However, HCS will generally produce tremendous image datasets, which leads to difficulties of handling and analyzing. We proposed an automatic classification approach for simultaneous feature extraction and cell phenotype recognition of monoaster and bipolar cells in HCS system.Methods: The proposed approach was composed of image segmentation, feature extraction, and classification. The image segmentation was based on the Laplacian of

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Li, Zhuyin, Yongping Yan, Elaine A. Powers, et al. "Identification of Gap Junction Blockers Using Automated Fluorescence Microscopy Imaging." Journal of Biomolecular Screening 8, no. 5 (2003): 489–99. http://dx.doi.org/10.1177/1087057103257309.

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Gap junctions coordinate electrical signals and facilitate metabolic synchronization between cells. In this study, the authors have developed a novel assay for the identification of gap junction blockers using fluorescence microscopy imaging-based high-content screening technology. In the assay, the communication between neighboring cells through gap junctions was measured by following the redistribution of a fluorescent marker. The movement of calcein dye from dye-loaded donor cells to dye-free acceptor cells through gap junctions overexpressed on cell surface membranes was monitored using au

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Frölich, Sonja, Rebecca Robker, and Darryl Russell. "Development of Automated Microscopy‐Assisted High‐Content Multiparametric Assays for Cell Cycle Staging and Foci Quantitation." Cytometry Part A 97, no. 4 (2020): 378–93. http://dx.doi.org/10.1002/cyto.a.23988.

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Fetz, V., H. Prochnow, M. Brönstrup, and F. Sasse. "Target identification by image analysis." Natural Product Reports 33, no. 5 (2016): 655–67. http://dx.doi.org/10.1039/c5np00113g.

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Biologically active compounds induce phenotypic changes in target cells, which can be used to predict their modes of action. Such changes were initially detected by a visual inspection of images, while recent studies are based on high content analysis (HCA) methods using automated microscopy and analysis software.

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Krausz, Eberhard, Ronald de Hoogt, Emmanuel Gustin, et al. "Translation of a Tumor Microenvironment Mimicking 3D Tumor Growth Co-culture Assay Platform to High-Content Screening." Journal of Biomolecular Screening 18, no. 1 (2012): 54–66. http://dx.doi.org/10.1177/1087057112456874.

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For drug discovery, cell-based assays are becoming increasingly complex to mimic more realistically the nature of biological processes and their diversifications in diseases. Multicellular co-cultures embedded in a three-dimensional (3D) matrix have been explored in oncology to more closely approximate the physiology of the human tumor microenvironment. High-content analysis is the ideal technology to characterize these complex biological systems, although running such complex assays at higher throughput is a major endeavor. Here, we report on adapting a 3D tumor co-culture growth assay to aut

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Martinent, Rémi, Javier López-Andarias, Dimitri Moreau, Yangyang Cheng, Naomi Sakai, and Stefan Matile. "Automated high-content imaging for cellular uptake, from the Schmuck cation to the latest cyclic oligochalcogenides." Beilstein Journal of Organic Chemistry 16 (August 14, 2020): 2007–16. http://dx.doi.org/10.3762/bjoc.16.167.

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Recent progress with chemistry tools to deliver into living cells has seen a shift of attention from counterion-mediated uptake of cell-penetrating peptides (CPPs) and their mimics, particularly the Schmuck cation, toward thiol-mediated uptake with cell-penetrating poly(disulfide)s (CPDs) and cyclic oligochalcogenides (COCs), here exemplified by asparagusic acid. A persistent challenge in this evolution is the simultaneous and quantitative detection of cytosolic delivery and cytotoxicity in a high-throughput format. Here, we show that the combination of the HaloTag-based chloroalkane penetrati

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Olszewski, Maciej B., Natalia Gostynska, Klaudia Lesniak, Alicja Martyniak, and Magdalena Kieltyka. "Abstract 5663: High-content screening platform for comprehensive profiling in drug discovery." Cancer Research 85, no. 8_Supplement_1 (2025): 5663. https://doi.org/10.1158/1538-7445.am2025-5663.

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A robust, multi-modal high-content screening (HCS) platform enables fast and quantitative assessment of cellular phenotypes over a variety of research applications. Our integrated system combines innovative imaging technologies, automated analysis, and cell profiling capabilities to drive drug discovery and biological research programs. Selvita HCS platform features multiparametric cellular phenotyping: simultaneous measurement of morphological, functional, and molecular cellular properties. The data is acquired by automated fluorescence microscopy: high-resolution imaging with multiplexed flu

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Li, Tong, Hadrien Mary, Marie Grosjean, et al. "MAARS: a novel high-content acquisition software for the analysis of mitotic defects in fission yeast." Molecular Biology of the Cell 28, no. 12 (2017): 1601–11. http://dx.doi.org/10.1091/mbc.e16-10-0723.

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Faithful segregation of chromosomes during cell division relies on multiple processes such as chromosome attachment and correct spindle positioning. Yet mitotic progression is defined by multiple parameters, which need to be quantitatively evaluated. To study the spatiotemporal control of mitotic progression, we developed a high-content analysis (HCA) approach that combines automated fluorescence microscopy with real-time quantitative image analysis and allows the unbiased acquisition of multiparametric data at the single-cell level for hundreds of cells simultaneously. The Mitotic Analysis an

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Haasen, Dorothea, Susanne Merk, Peter Seither, Domnic Martyres, Silke Hobbie, and Ralf Heilker. "Pharmacological Profiling of Chemokine Receptor–Directed Compounds Using High-Content Screening." Journal of Biomolecular Screening 13, no. 1 (2007): 40–53. http://dx.doi.org/10.1177/1087057107312128.

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High-content screening, typically defined as automated fluorescence microscopy combined with image analysis, is now well established as a means to study test compound effects in cellular disease-modeling systems. In this work, the authors establish several high-content screening assays in the 384-well format to measure the activation of the CC-type chemokine receptors 2B and 3 (CCR2B, CCR3). As a cellular model system, the authors use Chinese hamster ovary cells, stably transfected with 1 of the respective receptors. They characterize receptor stimulation by human monocyte chemoattractant prot

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Alworth, Samuel V., Hirotada Watanabe, and James S. J. Lee. "Teachable, High-Content Analytics for Live-Cell, Phase Contrast Movies." Journal of Biomolecular Screening 15, no. 8 (2010): 968–77. http://dx.doi.org/10.1177/1087057110373546.

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CL-Quant is a new solution platform for broad, high-content, live-cell image analysis. Powered by novel machine learning technologies and teach-by-example interfaces, CL-Quant provides a platform for the rapid development and application of scalable, high-performance, and fully automated analytics for a broad range of live-cell microscopy imaging applications, including label-free phase contrast imaging. The authors used CL-Quant to teach off-the-shelf universal analytics, called standard recipes, for cell proliferation, wound healing, cell counting, and cell motility assays using phase contra

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Whittaker, Ross, Patricia A. Loy, Eugene Sisman, et al. "Identification of MicroRNAs That Control Lipid Droplet Formation and Growth in Hepatocytes via High-Content Screening." Journal of Biomolecular Screening 15, no. 7 (2010): 798–805. http://dx.doi.org/10.1177/1087057110374991.

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Hepatic lipid droplets (LDs) are associated with metabolic syndrome, type 2 diabetes, hepatitis C, and both alcoholic and nonalcoholic fatty liver disease. MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the level of translation. Approximately 1000 different miRNA species are encoded within the human genome, and many are differentially expressed by healthy and diseased liver. However, few studies have investigated the role of miRNAs in regulating LD expression. Accordingly, a high-content assay (HCA) was performed in which human hepatocytes (Huh-7 cells) were trans

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McDonough, Patrick M., Ramses M. Agustin, Randall S. Ingermanson, et al. "Quantification of Lipid Droplets and Associated Proteins in Cellular Models of Obesity via High-Content/High-Throughput Microscopy and Automated Image Analysis." ASSAY and Drug Development Technologies 7, no. 5 (2009): 440–60. http://dx.doi.org/10.1089/adt.2009.0196.

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Schneidereit, Dominik, Larissa Kraus, Jochen C. Meier, Oliver Friedrich, and Daniel F. Gilbert. "Step-by-step guide to building an inexpensive 3D printed motorized positioning stage for automated high-content screening microscopy." Biosensors and Bioelectronics 92 (June 2017): 472–81. http://dx.doi.org/10.1016/j.bios.2016.10.078.

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Azegrouz, Hind, Gopal Karemore, Alberto Torres, et al. "Cell-Based Fuzzy Metrics Enhance High-Content Screening (HCS) Assay Robustness." Journal of Biomolecular Screening 18, no. 10 (2013): 1270–83. http://dx.doi.org/10.1177/1087057113501554.

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High-content screening (HCS) allows the exploration of complex cellular phenotypes by automated microscopy and is increasingly being adopted for small interfering RNA genomic screening and phenotypic drug discovery. We introduce a series of cell-based evaluation metrics that have been implemented and validated in a mono-parametric HCS for regulators of the membrane trafficking protein caveolin 1 (CAV1) and have also proved useful for the development of a multiparametric phenotypic HCS for regulators of cytoskeletal reorganization. Imaging metrics evaluate imaging quality such as staining and f

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Rameseder, Jonathan, Konstantin Krismer, Yogesh Dayma, et al. "A Multivariate Computational Method to Analyze High-Content RNAi Screening Data." Journal of Biomolecular Screening 20, no. 8 (2015): 985–97. http://dx.doi.org/10.1177/1087057115583037.

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High-content screening (HCS) using RNA interference (RNAi) in combination with automated microscopy is a powerful investigative tool to explore complex biological processes. However, despite the plethora of data generated from these screens, little progress has been made in analyzing HC data using multivariate methods that exploit the full richness of multidimensional data. We developed a novel multivariate method for HCS, multivariate robust analysis method (M-RAM), integrating image feature selection with ranking of perturbations for hit identification, and applied this method to an HC RNAi

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Garner, Kathryn L. "High content imaging for monitoring signalling dynamics in single cells." Journal of Molecular Endocrinology 65, no. 4 (2020): R91—R100. http://dx.doi.org/10.1530/jme-20-0169.

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All living cells are sensors of their environment: they sense signals, hormones, cytokines, and growth factors, among others. Binding of these signals to cell surface receptors initiates the transmission of messages along intracellular signalling pathways through protein–protein interactions, enzymatic modifications and conformational changes. Typically, the activation of signalling pathways are monitored in whole populations of cells, giving population average measures, often using experimental methods that destroy and homogenise the cell population. High content imaging is an automated, high

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Okolo, Chidinma A., Thomas M. Fish, Kamal L. Nahas, et al. "A combination of soft X-ray and laser light sources offer 3D high content information on the native state of the cellular environment." Journal of Physics: Conference Series 2380, no. 1 (2022): 012042. http://dx.doi.org/10.1088/1742-6596/2380/1/012042.

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Abstract Beamline B24 is a life sciences correlative cryo-imaging beamline at Diamond Light Source. B24 uses a combination of conventional and super-resolution visible-light fluorescence microscopy and soft X-ray tomography (cryoSXT) to provide 3D imaging of the cellular landscape at a resolution up to 25 nm in cryo-preserved biological samples up to 12 μm thick. B24 offers user-friendly, semi-automated 3D correlative cryo-imaging through an integrated platform of methods that encompass (a) sample preparation and evaluation, (b) data collection and processing and (c) data analysis and correlat

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Isherwood, Beverley J., Rebecca E. Walls, Mark E. Roberts, et al. "High-Content Analysis to Leverage a Robust Phenotypic Profiling Approach to Vascular Modulation." Journal of Biomolecular Screening 18, no. 10 (2013): 1246–59. http://dx.doi.org/10.1177/1087057113499775.

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Phenotypic screening seeks to identify substances that modulate phenotypes in a desired manner with the aim of progressing first-in-class agents. Successful campaigns require physiological relevance, robust screening, and an ability to deconvolute perturbed pathways. High-content analysis (HCA) is increasingly used in cell biology and offers one approach to prosecution of phenotypic screens, but challenges exist in exploitation where data generated are high volume and complex. We combine development of an organotypic model with novel HCA tools to map phenotypic responses to pharmacological per

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Vianello, Caterina, Federica Dal Bello, Sang Hun Shin, et al. "High-Throughput Microscopy Analysis of Mitochondrial Membrane Potential in 2D and 3D Models." Cells 12, no. 7 (2023): 1089. http://dx.doi.org/10.3390/cells12071089.

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Recent proteomic, metabolomic, and transcriptomic studies have highlighted a connection between changes in mitochondria physiology and cellular pathophysiological mechanisms. Secondary assays to assess the function of these organelles appear fundamental to validate these -omics findings. Although mitochondrial membrane potential is widely recognized as an indicator of mitochondrial activity, high-content imaging-based approaches coupled to multiparametric to measure it have not been established yet. In this paper, we describe a methodology for the unbiased high-throughput quantification of mit

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Moreno-Andrés, Daniel, Anuk Bhattacharyya, Anja Scheufen, and Johannes Stegmaier. "LiveCellMiner: A new tool to analyze mitotic progression." PLOS ONE 17, no. 7 (2022): e0270923. http://dx.doi.org/10.1371/journal.pone.0270923.

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Live-cell imaging has become state of the art to accurately identify the nature of mitotic and cell cycle defects. Low- and high-throughput microscopy setups have yield huge data amounts of cells recorded in different experimental and pathological conditions. Tailored semi-automated and automated image analysis approaches allow the analysis of high-content screening data sets, saving time and avoiding bias. However, they were mostly designed for very specific experimental setups, which restricts their flexibility and usability. The general need for dedicated experiment-specific user-annotated

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Nardou, Katya, Michael Nicolas, Fabien Kuttler, et al. "Identification of New Vulnerabilities in Conjunctival Melanoma Using Image-Based High Content Drug Screening." Cancers 14, no. 6 (2022): 1575. http://dx.doi.org/10.3390/cancers14061575.

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Recent evidence suggests that numerous similarities exist between the genomic landscapes of both conjunctival and cutaneous melanoma. Since alterations of several components of the MAP kinases, PI3K/mTOR, and cell cycle pathways have been reported in conjunctival melanoma, we decided to assess the sensitivity of conjunctival melanoma to targeted inhibition mostly of kinase inhibitors. A high content drug screening assay based on automated fluorescence microscopy was performed in three conjunctival melanoma cell lines with different genomic backgrounds with 489 kinase inhibitors and 53 other in

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Laan, Sebastiaan N. J., Richard J. Dirven, Petra E. Bürgisser, Jeroen Eikenboom, and Ruben Bierings. "Automated segmentation and quantitative analysis of organelle morphology, localization and content using CellProfiler." PLOS ONE 18, no. 6 (2023): e0278009. http://dx.doi.org/10.1371/journal.pone.0278009.

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One of the most used and versatile methods to study number, dimensions, content and localization of secretory organelles is confocal microscopy analysis. However, considerable heterogeneity exists in the number, size and shape of secretory organelles that can be present in the cell. One thus needs to analyze large numbers of organelles for valid quantification. Properly evaluating these parameters requires an automated, unbiased method to process and quantitatively analyze microscopy data. Here, we describe two pipelines, run by CellProfiler software, called OrganelleProfiler and OrganelleCont

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George, Thaddeus, Anne Spurkland, Vibeke Sundvold-Gjerstadt, et al. "Quantitative analysis of immune synapse formation using imaging flow cytometry. (130.18)." Journal of Immunology 184, no. 1_Supplement (2010): 130.18. http://dx.doi.org/10.4049/jimmunol.184.supp.130.18.

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Abstract Antigen-specific immune responses are initiated via direct cellular contact between an antigen presenting cell (APC) and an effector cell. Early events in the interaction between these two cells involve reorganization of the actin cytoskeleton and recruitment of adhesive and signaling molecules to the immunological synapse (IS), which ultimately results in effector cell activation. Because manual image acquisition and quantitative image analysis are time consuming processes, microscopic analyses of protein recruitment to the IS have remained either qualitative or statistically limited

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Lempereur, Sylvain, Arnim Jenett, Elodie Machado, et al. "Automated segmentation of thick confocal microscopy 3D images for the measurement of white matter volumes in zebrafish brains." Mathematical Morphology - Theory and Applications 4, no. 1 (2020): 31–45. http://dx.doi.org/10.1515/mathm-2020-0100.

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AbstractTissue clearing methods have boosted the microscopic observations of thick samples such as whole-mount mouse or zebrafish. Even with the best tissue clearing methods, specimens are not completely transparent and light attenuation increases with depth, reducing signal output and signal-to-noise ratio. In addition, since tissue clearing and microscopic acquisition techniques have become faster, automated image analysis is now an issue. In this context, mounting specimens at large scale often leads to imperfectly aligned or oriented samples, which makes relying on predefined, sample-indep

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Ferron, P. J., S. Huet, K. Hogeveen, V. Fessard, and L. Le Hegarat Anses. "Effects of food chemical contaminants in human HepaRG and Caco-2 cells using an automated microscopy and high content analysis based approach." Toxicology Letters 238, no. 2 (2015): S86—S87. http://dx.doi.org/10.1016/j.toxlet.2015.08.290.

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Geraud, Mathéa, Lara Fernandez Martinez, Andrea Carla Ajello, Agnese Cristini, and Olivier Sordet. "Protocol for single-cell analysis of DNA double-strand break production and repair in cell-cycle phases by automated high-content microscopy." STAR Protocols 6, no. 1 (2025): 103662. https://doi.org/10.1016/j.xpro.2025.103662.

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Yip, Kenneth W., Michael Cuddy, Clemencia Pinilla, et al. "A High-Content Screening (HCS) Assay for the Identification of Chemical Inducers of PML Oncogenic Domains (PODs)." Journal of Biomolecular Screening 16, no. 2 (2011): 251–58. http://dx.doi.org/10.1177/1087057110394181.

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PML is a multi-functional protein with roles in tumor suppression and host defense against viruses. When active, PML localizes to subnuclear structures named PML oncogenic domains (PODs) or PML nuclear bodies (PML-NBs), whereas inactive PML is located diffusely throughout the nucleus of cells. The objective of the current study was to develop a high content screening (HCS) assay for the identification of chemical activators of PML. We describe methods for automated analysis of POD formation using high throughput microscopy (HTM) to localize PML immunofluorescence in conjunction with image anal

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Aggarwal, Sonam, Sheifali Gupta, Deepali Gupta, et al. "An Artificial Intelligence-Based Stacked Ensemble Approach for Prediction of Protein Subcellular Localization in Confocal Microscopy Images." Sustainability 15, no. 2 (2023): 1695. http://dx.doi.org/10.3390/su15021695.

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Predicting subcellular protein localization has become a popular topic due to its utility in understanding disease mechanisms and developing innovative drugs. With the rapid advancement of automated microscopic imaging technology, approaches using bio-images for protein subcellular localization have gained a lot of interest. The Human Protein Atlas (HPA) project is a macro-initiative that aims to map the human proteome utilizing antibody-based proteomics and related c. Millions of images have been tagged with single or multiple labels in the HPA database. However, fewer techniques for predicti

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Pandey, Gunjan, Jens Westhoff, Franz Schaefer, and Jochen Gehrig. "A Smart Imaging Workflow for Organ-Specific Screening in a Cystic Kidney Zebrafish Disease Model." International Journal of Molecular Sciences 20, no. 6 (2019): 1290. http://dx.doi.org/10.3390/ijms20061290.

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The zebrafish is being increasingly used in biomedical research and drug discovery to conduct large-scale compound screening. However, there is a lack of accessible methodologies to enable automated imaging and scoring of tissue-specific phenotypes at enhanced resolution. Here, we present the development of an automated imaging pipeline to identify chemical modifiers of glomerular cyst formation in a zebrafish model for human cystic kidney disease. Morpholino-mediated knockdown of intraflagellar transport protein Ift172 in Tg(wt1b:EGFP) embryos was used to induce large glomerular cysts represe

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Ramm, Susanne, Robert Vary, Twishi Gulati, et al. "High-Throughput Live and Fixed Cell Imaging Method to Screen Matrigel-Embedded Organoids." Organoids 2, no. 1 (2022): 1–19. http://dx.doi.org/10.3390/organoids2010001.

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Technical advances in microscopy and automation have enabled image-based phenotypic screening of spheroids and organoids to become increasingly high throughput and high content at the same time. In particular, matrix-embedded 3D structures can recapitulate many aspects of parent (e.g., patient) tissues. Live-cell imaging of growing structures allows tremendous insight into population heterogeneity during drug treatment. However, screening for targeted markers and more detailed morphological analyses typically require fixation of 3D structures, and standard formaldehyde (FA) incubation conditio

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Pelicci, Simone, Laura Furia, Pier Giuseppe Pelicci, and Mario Faretta. "From Cell Populations to Molecular Complexes: Multiplexed Multimodal Microscopy to Explore p53-53BP1 Molecular Interaction." International Journal of Molecular Sciences 25, no. 9 (2024): 4672. http://dx.doi.org/10.3390/ijms25094672.

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Surpassing the diffraction barrier revolutionized modern fluorescence microscopy. However, intrinsic limitations in statistical sampling, the number of simultaneously analyzable channels, hardware requirements, and sample preparation procedures still represent an obstacle to its widespread diffusion in applicative biomedical research. Here, we present a novel pipeline based on automated multimodal microscopy and super-resolution techniques employing easily available materials and instruments and completed with open-source image-analysis software developed in our laboratory. The results show th

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Furia, Laura, Simone Pelicci, Mirco Scanarini, Pier Giuseppe Pelicci, and Mario Faretta. "From Double-Strand Break Recognition to Cell-Cycle Checkpoint Activation: High Content and Resolution Image Cytometry Unmasks 53BP1 Multiple Roles in DNA Damage Response and p53 Action." International Journal of Molecular Sciences 23, no. 17 (2022): 10193. http://dx.doi.org/10.3390/ijms231710193.

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53BP1 protein has been isolated in-vitro as a putative p53 interactor. From the discovery of its engagement in the DNA-Damage Response (DDR), its role in sustaining the activity of the p53-regulated transcriptional program has been frequently under-evaluated, even in the case of a specific response to numerous DNA Double-Strand Breaks (DSBs), i.e., exposure to ionizing radiation. The localization of 53BP1 protein constitutes a key to decipher the network of activities exerted in response to stress. We present here an automated-microscopy for image cytometry protocol to analyze the evolution of

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Hernando-Rodríguez, Blanca, Annmary Paul Erinjeri, María Jesús Rodríguez-Palero, et al. "Combined flow cytometry and high-throughput image analysis for the study of essential genes in Caenorhabditis elegans." BMC Biology 16, no. 1 (2018): 36. https://doi.org/10.1186/s12915-018-0496-5.

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<strong>Background: </strong>Advances in automated image-based microscopy platforms coupled with high-throughput liquid workflows have facilitated the design of large-scale screens utilising multicellular model organisms such as <i>Caenorhabditis elegans</i> to identify genetic interactions, therapeutic drugs or disease modifiers. However, the analysis of essential genes has lagged behind because lethal or sterile mutations pose a bottleneck for high-throughput approaches, and a systematic way to analyse genetic interactions of essential genes in multicellular organisms has been lacking.<stron

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Jayamani, Elamparithi, Rajmohan Rajamuthiah, Jonah Larkins-Ford, et al. "Insect-Derived Cecropins Display Activity against Acinetobacter baumannii in a Whole-Animal High-Throughput Caenorhabditis elegans Model." Antimicrobial Agents and Chemotherapy 59, no. 3 (2015): 1728–37. http://dx.doi.org/10.1128/aac.04198-14.

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ABSTRACTThe rise of multidrug-resistantAcinetobacter baumanniiand a concomitant decrease in antibiotic treatment options warrants a search for new classes of antibacterial agents. We have found thatA. baumanniiis pathogenic and lethal to the model host organismCaenorhabditis elegansand have exploited this phenomenon to develop an automated, high-throughput, high-content screening assay in liquid culture that can be used to identify novel antibiotics effective againstA. baumannii. The screening assay involves coincubatingC. eleganswithA. baumanniiin 384-well plates containing potential antibact

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