High Content Analysis CellVoyager

PhenoVista Biosciences is the leading provider of custom, imaging-based, phenotypic assay services. With a collaborative and scientifically driven project design and management approach, PhenoVista has a proven track record of delivering high-quality data from robust and scalable assays. PhenoVista’s key advantage lies in the ability of their industry-trained scientists to combine world-class understanding of diverse biological systems with cutting-edge quantitative imaging to deliver clear, actionable output data.

Since 2010, German: Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) has been using CellVoyager™ series as the High-content Analysis system of a highly sophisticated screening platform in DZNE Laboratory Automation Technologies (LAT). The team has been collaborating with a lot of scientists and contributing to science advancement via their excellent platform. Dr. Philip Denner is the leader of LAT. 

single-cell analysis specifically transcription by steroid receptors primarily estrogen and androgen receptors

Cell stage categorized using FucciTime lapse imaging of Fucci-added Hela cells was conducted over 48 hrs at 1 hr intervals. Gating was performed based on the mean intensities of 488 nm and 561 nm for each cell. They were categorized into four stages, and the cell count for each was calculated.

The CV8000 nuclear translocation analysis software enables the analysis of changes in the localization of signal molecules that transfer between cytoplasm and nuclei, such as proteins. The following is an example of the translocation analysis of NFκB, a transcription factor.

Fluorescent ubiquitination-based cell cycle indicator (Fucci) is a set of fluorescent probes which enables the visualization of cell cycle progression in living cells.

In this application, the combination of the CQ1 with the stocker with Incubator and CellPathfinder enabled continuous and automatic long-term observation of the process of single cells forming colonies.

The CQ1 confocal image acquisition mechanism with the distinctive CSU® unit has a function to sequentially acquire fine cell images along the Z-axis and capture information from the entire thickness of
cells which include heterogenic populations of various cell cycle stages. In addition, saved digital images can be useful for precise observation and analysis of spatial distribution of intracellular molecules.
The CQ1 capability to seamlessly analyze images and obtain data for things such as cell population statistics to individual cell morphology will provide benefits for both basic research and drug discovery
targetingM-cell cycle phase.

• Colony Formation
• Scratch Wound
• Cytotoxicity
• Neurite Outgrowth
• Co-culture Analysis
• Cell Tracking

Cell clusters are directly measured with high-throughput 3D imaging Confocal Quantitative Image Cytometer

Yokogawa collaborates with scientists in the medical and pharmacology fields to identify best practices for cell painting and high-content screening, thereby enhancing image analysis and reproducibility.

List of Selected Publications : CQ1

List of Selected Publications : CV8000, CV7000, CV6000

In this tutorial, we will learn how to perform cell tracking with CellPathfinder through the analysis of test images.

In this tutorial, using images of zebrafish whose blood vessels are labeled with EGFP, tiling of the images and recognition of blood vessels within an arbitrary region will be explained.

In this tutorial, a method for analyzing ramified structure, using CellPathfinder, for the analysis of the vascular endothelial cell angiogenesis function will be explained.

In this tutorial, we will learn how to perform time-lapse analysis of objects with little movement using CellPathfinder, through calcium imaging of iPS cell-derived cardiomyocytes.

In this tutorial, we will observe the change in number and length of neurites due to nerve growth factor (NGF) stimulation in PC12 cells.

In this tutorial, image analysis of collapsing stress fibers will be performed, and concentration-dependence curves will be drawn for quantitative evaluation.

In this tutorial, we’ll compare positive and negative condition for the count and total area of lipid droplets by adding the oleic acid or Triacsin C.

In this tutorial, we will identify the cell cycles G1-phase, G2/M-phase, etc. using the intranuclear DNA content.

In this tutorial, intranuclear and intracytoplasmic NFκB will be measured and their ratios calculated, and a dose-response curve will be created.

In this tutorial, spheroid diameter and cell (nuclei) count within the spheroid will be analyzed.

In this tutorial, a method for analyzing ramified structure, using CellPathfinder, for the analysis of the vascular endothelial cell angiogenesis function will be explained.

The CV8000 features a cell incubator with an improved airtight design that facilitates the observation of cell behavior over long periods of time. In addition, the CV8000 comes with CellPathfinder, a new program that can analyze images of unlabeled cells and 3D images of samples. With these features, the CV8000 improves the efficiency of drug discovery research and biomedical research on leading-edge subjects such as iPS and ES cells.

YOKOGAWA will contribute to technology evolution particularly in measurement and analytical tools to help build a world where researchers will increasingly focus on insightful interpretation of data, and advancing Life Science to benefit humanity.

Visualizing the complex spatiotemporal dynamics of human stem cells as they proliferate and make cell fate decisions is key to improving our understanding of how to robustly engineer differentiated tissues for therapeutic applications.

In this webinar, Dr. Rafael Carazo Salas will describe multicolor, multiday high-content microscopy pipelines that his group has recently developed to visualize the dynamical cell fate changes of human Pluripotent Stem Cells (hPSCs).

Key Topics:

• Visualizing how human Pluripotent Stem Cells (hPSCs) proliferate and undergo early differentiation in vitro, by high content microscopy
• Learning about experimental and computational pipelines that enable monitoring single-cell fate dynamics
• Learning about novel “live” reporters of hPSC cell fate

Speaker
Rafael Carazo Salas, PhD
Professor, School of Cellular and Molecular Medicine
University of Bristol

Are you looking to improve laboratory workflows, data management, and imaging analysis?

This webinar covers the integration of a high-content imager into a modern laboratory automation system and workflows built to utilize it. This on-demand webinar describes the integration topology used in the High Throughput Bioscience Center at St. Jude and the technical challenges that emerged pertaining to data handling and analysis. The webinar addresses the variety of ways we have used our high-content imager in the context of a high throughput screening center, using examples of experiment workflows from recent users.

Key Topics:

• Body Copy:
  • Key considerations for integrating a high-content imager into a laboratory robot system
  • Methods for interfacing between robots and the imager
  • Important considerations for imaging data management and analysis
  • How the St. Jude High Throughput Bioscience Center supports the diverse imaging needs of its projects

3D imaging experts from Yokogawa and Insphero have come together to provide helpful tips and tricks on acquiring the best 3D spheroid and organoid imaging. This webinar focuses on sample preparation, imaging, and analysis for both fixed and live cells in High Content Screening assays. The experts also discuss automated tools that can help researchers understand the large volume of data in these High Content Imaging Analysis Systems.

Physiologically relevant 3D cell models are being adopted for disease modeling, drug discovery and preclinical research due to their functional and architectural similarity to their tissue/sample of origin, especially for oncology research. Multifunctional profiling and assays using 3D cell models such as tumoroids tend to be manual and tedious. Further, high-content imaging of biomarkers in 3D cell models can be difficult.
In this two-part webinar present to you streamlined technologies which can bring consistent timesaving, ease-of-use, and high-quality data to your 3D cell-based workflows:

(A)  The Pu·MA System is a microfluidics-based benchtop automated device for performing “hands-off” 3D cell-based assays. In this webinar, application scientist Dr. Katya Nikolov will present data from optimized assays using tumoroids followed by Yokogawa’s high-content imaging systems for biomarker detection.

(B) Yokogawa’s high-content imaging systems such as CellVoyager CQ1 provide superior confocal imaging using the Nipkow Spinning Disk Confocal Technology. Here, application scientist, Dan Collins will present details of the high-content imaging capabilities, easy to use and intuitive image acquisition software, especially for increasing productivity and a streamlined workflow.

Learn How:

• The open platform, Pu·MA System can be used to automate your 3D cell-based assays
• To perform automated IF staining for biomarkers using tumoroid models without perturbing your precious samples
• Image acquisition from 3D cell models using Yokogawa’s high-content imaging platforms
• Image analysis from cells, complex spheroids, colonies, or tissues using the CellPathfinder high content analysis software

Physiologically relevant 3D cell models are essential for drug discovery and preclinical research due to their functional and architectural similarity to solid tumors. One of the challenges faced by researchers is that many of the assays using these precious samples tend to be manual and tedious.

Using proprietary microfluidics technology, Protein Fluidics has created the Pu·MA System for automated complex 3D cell-based assays. In this webinar, application scientist Dr. Katya Nikolov will present her work on combining this novel automation technology with Yokogawa’s high-content imaging systems for biomarker detection in 3D cell models. Nikolov will demonstrate the utility of an automated immunofluorescence staining workflow followed by confocal imaging within the Pu·MA System flowchips. This automated workflow enables quantitative assessment of biomarkers which provides valuable data for further understanding disease mechanisms, preclinical drug efficacy studies, and in personalized medicine.

This webinar will explore:

• The Pu·MA System and novel technology for automated 3D cell-based assays
• How to perform automated immunofluorescence staining for biomarkers with a “hands-off” assay workflow
• How to visualize biomarkers after the assay with high-content imaging within the flowchip

This webinar highlights Yokogawa’s High Content Solutions, the benchtop confocal CellVoyager CQ1, and CellVoyager CV8000. Utilizing Yokogawa’s dual-wide microlens spinning disk confocal technology, these automated HCA systems provide remarkable image quality while increasing your output. This frees up time to complete other research activities. Also, recent additions to the CSU-W1 confocal upgrade is discussed. The SoRa, a super-resolution solution, and the Uniformizer, an image flattening device. Both of which can be added to the lightpath of your CSU-W1-enhanced microscope.

Agenda:
Introduction to Yokogawa
SoRa for CSU-W1 super-resolution with confocal
Two high content instruments from Yokogawa: The CQ1 and the CV8000

Presenter:
Dan J. Collins, Applications Scientist, Yokogawa Life Science

In the last few decades, the pharmaceutical industry has transformed people’s lives. However, the development of new drugs is becoming increasingly difficult and a paradigm shift in the drug discovery workflow is required to reduce attrition and transform conventional drug screening assays into translatable analytical techniques for the analysis of drugs in complex environments, both in-vitro and ex-vivo. The ability to visualize unlabelled compounds inside the cell at physiological dosages can offer valuable insight into the compound behavior both on and off-target.

SiLC-MS is a semi-automated methodology that allows the collection of intracellular contents using a modified CQ1 imaging system developed by Yokowaga. The instrument is equipped with a confocal microscope that allows bright field imaging as well as fluorescence imaging with 4 lasers (405, 488, 561, and 640 nm). Sampling is performed using the tips developed by Professor Masujima (1-4).

In this study, we show the applicability of the SiLC-MS technology to drug discovery, as it is crucial to identify compound and its metabolites when incubated in a mammalian cell at a therapeutic dose. We report on the validation studies performed using the SiLC-MS platform, in these validation studies we assess the ability to distinguish different cell types based on their metabolomic fingerprint, furthermore, we have also evaluated if this assay was sensitive enough to detect drugs intracellularly.

Presenter: Carla Newman, Scientific Leader (Celluar Imaging and Dynamics), GSK

Image-based phenotypic screening relies on the extraction of multivariate information from cells cultured in a large number of screened conditions. In this webinar, we explored the application of complex and biologically relevant model systems for drug screening, such as small intestinal organoids.

Key topics include:

• Learn how to upscale, streamline, and automate intestinal organoid handling
• Learn how to image in complex three-dimensional (3D) model systems and how to approach large imaging datasets
• Understand the basics of multivariate analysis on image-inferred features

Generating translatable high-content imaging data from physiologically-relevant cell models, including 2D and 3D structures, is extremely valuable for drug discovery and pre-clinical research. In this webinar, James Evans, CEO of PhenoVista Biosciences presents case studies on how Yokogawa’s Benchtop CQ1 Confocal System can improve throughput and standardize processes for complex 3D cell-based phenotypic assays.

Key learning objectives:

• Strategies for designing and implementing high-content screening assays
• Approaches for deciding between 2D and 3D model systems