CellPathfinder, High Content Analysis Software

The intuitive, easy-to-use interface guides the user throughout the process, including the easy graphing of image data. Yokogawa machine-learning function dramatically increasing its target recognition capability. It analyzes and digitizes complex, high degree-of-difficulty high content imaging experiment data, such as from 3D culture systems and live imaging, using several evaluation systems. The CellPathfinder software is a powerful tool for HCA.

You can download trial software. Software download

CallPathfinder Resolves Difficulties

For screening

CellPathfinder resolves screening bottlenecks.

  • A specialized interface for inspecting multiple samples makes image comparison easy, improving efficiency
  • Advanced analysis using AI is possible through simple operation, even for beginners
  • Various graph creation functions and simple image and video creation, reducing hassles at the time of reporting

For cancer research and regenerative medicine screening

CellPathfinder provides leading HCA through proprietary analysis technology.

  • Label-free analysis of samples that you don’t want to stain is possible using Yokogawa’s proprietary image generation technology “CE Bright Field”
  • Newly-developed easy-to-use machine-learning (standard function) makes previously difficult phenomena detection easy
  • Detection of rare events (CTC, etc.) with high speed and high accuracy

 

Applications

Applications

Simple workflow from images to analysis and graphs

1. Display image data

・Easy to compare images between wells

 

2. Load and execute analysis protocol

・Easy-to-understand graphical icons
・Choose a preset template for your analysis

 

3. Gating

・Specific populations can be extracted by gating the feature value data of recognized objects
・The extracted populations can be analyzed further

 

4. Make the graphs

・Various graph options to visualize the results
・The link between graph and images enables quick visual check of images by clicking data points

 

5. To examine further details…list the profiles of interesting cells

・Images and numerical data can be collected by clicking cells

Yokogawa technology

Machine-learning

Machine-learning functionality allows for unbiased digitization in experiments evaluated through appearance.
Automated shape recognition can be performed by simply clicking on the shape you wish the software to learn.

Machine-learning

 

CE Bright Field(Contrast-enhanced Bright Field )

By using Yokogawa’s “CE-Bright Field” proprietary image creation technology, two types of images can be output from bright field images. The first is an image resembling a phase-difference image, created from a regular DPC (digital phase contrast) image, and is effective for cytoplasm recognition. The second is an image resembling a fluorescence image, effective for nuclear recognition.

CE Bright Field

Abundant analysis functions

3D analysis

・Analysis of Z-stack images in three-dimensional space. ・The volume and the location of objects in 3D space can be quantified.

3D analysis

 

Label-free Analysis

The recognition of cells without the use of labeling is possible using images created with CE Bright Field technology.
Time, cost and effects on cells due to fluorescent labeling are eliminated from phenotype analysis.

labelfree

 

Image Stitching*1

Tiled images are generated through image stitching and analyzed, allowing for accurate quantification.
Ideal for analysis spanning across fields, such as of spheroids, tissue sections and neurites.

Tiling

 

Manual Region definition*1

Manual region of analysis regions is possible for complex trends that are difficult to identify through automated image processing.
Morphology in the defined regions can be visualized, facilitating analysis.

Manual Region definition
Data provided by Dr. Yasuhito Shimada, Mie University Graduate School of Medicine

 

*1: Coming soon

Total Solution - from Imaging to Analysis -

Offering Total Solutions, from Measurement to Analysis Plate transport via robot, measurement using CellVoyager or CQ1, data management using CellLibrarian, and image analysis using CellPathfinder. We offer optimum combinations matched to user’s needs and budgets.

System

Large image: Click

Related products

  • Ultimate HCA system for high-quality imaging and high-throughput screening with water immersion objectives and multiple cameras
  • Built-in robot pipettor for kinetic assays
  • Bench top size confocal system
  • Simple operation and automated image acquisition of many sample
  • Live cell imaging
CellLibrarian
  • Management of image data acquired by CellVoyager and CQ1
  • Through the internet, group members and collaborators can access, visualize and share their image data
  • CellPathfinder runs analysis on data in CellLibrarian

※Data acquired in CellVoyager CV1000 are not supported.
※CellPathfinder system contain the software and the workstation.

System configuration

・Software
・Workstation
・Displays

Specifications of the workstation
Model: Dell Precision
CPU: Intel® Xeon
Memory:128 GB
HDD: System(C:) 4TB Storage, (D:) 4TB
OS: Windows® 10 Pro 64 bit Japanese/English

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Overview:

Introduction

Embryonic stem cells (ES cells) have been a fundamental resource in gene engineering and regenerative medicine. It has been known that various transcription factors play crucial roles in the regulation of pluripotency of ES cells.
Time lapse analysis in live cells has provided essential information regarding the temporal regulation of such pluripotency regulators. For example, a recent long-term single-cell tracking study in monolayer ES colonies revealed the less stringently implemented interactions of pluripotency regulators than assumed based on previous studies*1.
It has been considered that the interactions between a cell and its surrounding neighbors are also an important determinant to regulate the expression of pluripotency regulators. Therefore, analyzing the cellular behaviors in three-dimensional (3D) culture systems, which can mimic the actual in vivo environment more closely than traditional monolayer cell cultures, is an indispensable strategy to assess the regulatory functions in ES cells.
Here we report 3D time lapse analysis of the expression of Nanog, a critical pluripotency regulator, in cultured mouse ES cell colonies using Yokogawa’s all-in-one confocal image cytometer CQ1.

Methods

  • A knock-in ES cell line, in which a Nanog allele was targeted with enhanced green fluorescent protein (EGFP) at the translation start site (Nanog-EGFP) and histone 2B-mCherry fusion protein (H2B-mCherry) was forcibly expressed, was created.
  • ES cells were cultured in DMEM supplemented with 20% fetal bovine serum and 1,000 U/ml LIF on mitomycin C-treated mouse embryonic fibroblast feeder cells.
  • Time lapse imaging (48 hours, 30 min interval, 40x objective lens , 2 fields) was conducted in CQ1 equipped with an forced-humidified internal incubation chamber to control the temperature and the concentration of O2 and CO2.

Results

1. Measurement of Nanog-EGFP expression in individual cells in ES cell colonies growing in 3D

Measurement of Nanog-EGFP expression in individual cells in ES cell colonies growing in 3D
Measurement of Nanog-EGFP expression in individual cells in ES cell colonies growing in 3D
   
Time lapse movie : Play

Fig. 1. Measurement of Nanog-EGFP expression in individual cells in ES cell colonies.
(A) Time lapse maximum intensity projection (MIP) images of ES cell colonies. Four colonies at the beginning of the experiment (arrows) gradually fused each other and became a large colony.
(B) Z stack images of this colony at 48 hour in culture. Green and red outlines indicate the Nanog-EGFP-positive and -negative cells recognized by CQ1, respectively.
(C) Scatter plot of the fluorescence intensity of Nanog-EGFP and H2B-mCherry of individual cells in the colonies in (A).
(D-G) Temporal change of the volume of the colonies (D), number of cells in the colonies (E), ratio of Nanog-EGFP-expressing cells among cells in the colonies (F) and the amount of Nanog-EGFP in the Nanog-EGFP-expressing cells (G). Bars with different colors represent different colonies in (A).
(H) Time lapse movie (Selected).
 

2. Distribution of Nanog-EGFP expression in a ES cell colony

Measurement of Nanog-EGFP expression in individual cells in ES cell colonies growing in 3D

Fig. 2. Distribution of Nanog-EGFP expression in a ES cell colony.
(A) Inner and outer compartment of the colony.
(B) Percentage of the number of Nanog-EGFP-expressing cells to the total cell count in the inner and the outer compartment.
(C) Amount of the expression of Nanog-EGFP in the Nanog-EGFP-positive cells in the inner and the outer compartment.

Summary & Discussions

  • The expression of Nanog-EGFP in individual cells in a colony of a Nanog-EGFP knock-in ES cell line was quantified by 3D time lapse live cell imaging.
  • The expression Nanog-EGFP increased with time and the expression level of Nanog-EGFP seemed different between the inner and the outer compartment in a colony examined.
  • Time lapse live cell imaging combined with single-cell tracking and/or cultures with microfluidics would be useful to reveal the detail of the regulation of pluripotency in 3D environments.

This study was conducted under the supervision of Prof. Horie, Nara Medical University, on the responsibility of Yokogawa Electric Corporation. 
Reference : *1. Filipczyk et al., Nat Cell Biology 17, 1236-1246 (2015).


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Overview:

Introduction

Time lapse confocal imaging has been an essential method to investigate the 3D dynamic behaviors of cells in tissue cultures. For long-term live cell imaging, it is critical to reduce phototoxic damage to the cells caused by repeated laser scanning. Yokogawa CSU (confocal scanner unit) is a confocal unit using a microlens-enhanced dual Nipkow disk confocal optical system, which has been shown to be less harmful to living cells compared to conventional single beam scanning devices. The CQ1 is an all-in-one confocal quantitative imaging cytometer based on the CSU. Here we report the 3D time lapse live cell imaging in a multilayered cell sheet using CQ1.

Methods

  1. Five-layered myoblast cell sheets were constructed from human skeletal muscle myoblasts (HSMM) and human skeletal muscle fibroblasts (HSMF) .
  2. HSMMs and HSMFs were labeled with CellTrackerTM Orange
  3. Human umbilical vein endothelial cells (HUVEC) expressing GFP (GFP-HUVEC) were overlaid by the cell sheet and co-cultured.
  4. Time lapse imaging (67 hours, 30 min interval, 40x objective lens , 49 fields) was performed by CQ1 equipped with an internal incubation chamber to regulate culture environment.

Methods

Results

1.Dynamic migration and network formation of GFP-HUVECs captured by 3D time lapse imaging

Time lapse images of the cell sheet. 
Time lapse movie Play

Fig. 1-1. Time lapse images of the cell sheet.
Images were reconstructed of the field indicated by the yellow frame in the large field stitched image in Method fig.2.

Migration of the GFP-HUVECs into the cell sheet.

Fig. 1-2. Migration of the GFP-HUVECs into the cell sheet.
Single slice images showing the migration of HUVECs into upper layers. (Rows, from top to bottom) Single slice images of layers 3, 2, 1 and corresponding Y-Z plane images of the cell sheet. (Columns, from left to right) Images acquired at 0, 17, 34 and 51 hr incubation. The image filed is the same as fig. 1-1.

2.Quantification of the migration of GFP-HUVECs into the five-layered cell sheet

Temporal change of the distribution GFP-HUVECs in the cell sheet.

Fig. 2. Temporal change of the distribution GFP-HUVECs in the cell sheet.
GFP fluorescence intensity in each layer was indicated as the ratio against the total GFP intensity in the cell sheet.

Summary & Discussions

  • GFP-HUVECs dynamically migrated upward into the five-layered cell sheet constructed from HSMMs and HSMFs.
  • The GFP-HUVECs formed a reticulate network in the horizontal plane in the middle layers.
  • Long-term 3D time lapse imaging by CQ1 revealed a dynamic process of the active migration and the formation of the cellular network in the multilayered cell sheet.
  • CQ1 would be a powerful research tool in tissue engineering as well as regenerative medicine and drug screening.

Data provided by Dr. Nagamori, Osaka Institute of Technology
Reference: Nagamori E. et al., Biomaterials, 34, 662-668. (2013)


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Application Note
Overview:

Introduction

Angiogenesis is a physiological process in which new branches and the network of blood vessels are generated in the tissues. Although angiogenesis is essential for living bodies, it is also involved in a variety of diseases. For example, cancers induce the formation of vascular networks to supply energy and nutrient to themselves.
In vivo experiments using animal models have been prevalent for the research of angiogenesis. However, it is often difficult to obtain quantitative and reproducible data in such experiments, and the low throughout makes them unsuitable for drug discovery screening.  On the other hand, in vitro culture assays are useful for drug screening because such systems allow strict control of the experimental conditions. CQ1 enables automated high-throughput in vitro assays. This application note shows an example of the analysis of the angiogenesis by cultured HUVEC in Matrigel.

Figure 1. Vascular network-like structure formed by HUVECs.

Figure 1. Vascular network-like structure formed by HUVECs.
(A) A whole-well image showing the network formed by cultured HUVECs in Matrigel.
(B) Recognition by CQ1.
(C and D) Higher magnification images of the areas (white frames) in (A) and (B), respectively.

Experimental procedures

Human umbilical vein endothelial cells (HUVECs) were incubated in the serum starvation condition (1 % FBS) for 24 hours.
Cells were seeded in a Matrigel-coated, 96-well microplate (10,000 cells/well).
After incubation (4 hours) to allow them to form blood vessel-like networks, Suramin (0 – 50 µM) and CellTracker Red (5 µM) were added to the culture medium and cells were incubated for an hour at 37℃.
Images were acquired with CQ1 (4 x objective, 561 nm laser). Maximum intensity projection (MIP) images were constructed from 12 z slices (764 µm from bottom to top), then whole-well images were reconstructed from four adjacent images. The images were analyzed in the CQ1 software.

Length of line objects

 

Figure 2. Effects of Suramin

Figure 2. Effects of Suramin
Suramin is a reagent which is known as an inhibitor of angiogenesis in a dose-dependent manner. (A) Control well. The network formed by HUVECs covers the whole-well. (B) The well treated with 50 µM Suramin. The network is largely disrupted.

Figure 3. Dose-response curve for the effects of Suramin

Figure 3. Dose-response curve for the effects of Suramin
Images were analyzed using Skelton function in the CQ1 software and dose-response curves were constructed for the effects of Suramin on length of the line objects (left), the number of branching points (middle) and number of branches (right) per well. 

Results and discussion

The effects of Suramin on the vascular network-like structure formed by cultured HUVECs were analyzed and quantified using CQ1. Users can easily make automated procedures from image acquisition through image analysis in CQ1. By using such procedures, users can effectively collect quantitative and reproducible data in high throughput.
Even in the case of the samples like the vascular network in Matrigel, where cells are distributed in the coating material with uneven thickness, CQ1 can capture the complete three-dimensional structure of the network by acquiring z-stack images without missing out-of-focus cells.
The microlens-enhanced dual Nipkow disk confocal system in CQ1 cause only a very low level of photobleaching and phototoxicity on the samples. This feature allows repeated image acquisitions in CQ1 with a minimal damage to the samples.
A tiled image which consists of four fields acquired with the 4 x objective lens in CQ1 covers a whole-well in a 96-well microplate. CQ1 software can generate a large field image by stitching images of adjacent fields. Analysis of the tiled images would provide more realistic results avoiding possible errors caused by analyzing each field separately.
The dynamic process of angiogenesis can be investigated in the time-lapse live cell imaging using CQ1 with optional environmental control system.

 


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Application Note
Overview:

Introduction

Autophagy is the mechanism of the cell that disassembles unnecessary proteins and organelles to recycle or metabolize them. When placed in certain physiological conditions, the cells produce phagophore to cover unnecessary components and form autophagosome. The autophagosome fuses with lysosome (production of autolysosome), and acid hydrolase from lysosome degrades the unnecessary components. Autophagy has been confirmed to be related to cancer and neurodegenerative diseases such as Alzheimer and Parkinson’s disease, and as possessing a physiological function in aging.
The following are the results of experiments using the CQ1 for imaging and the high content analysis software CellPathfinder for analysis. In this experiment, DALGreen-Autophagy Detection (Donjindo Molecular Technologies, Inc.)*1 was used; it penetrates cell membranes and is drawn into autophagosome along with unnecessary components, fusing with lysosome and then increasing fluorescence in the acid environment in autolysosome.

Experiment Procedure

  1. HeLa cells were cultured in 96-well plates (Greiner #655087) for 24 hours. 
  2. DALGreen – Autophagy Detection was added according to the attached protocol and incubated for 30 minutes.
  3. The cells were washed in the cultured medium, and then medium were changed to normal medium, autophagy inducer medium (not containing amino acid) and autophagy inhibition medium (Bafilomycin added to the inducer medium at the final concentration of 100nM). Time-lapse imaging using the CQ1 was implemented every 30 min, for 6 hours (object lens magnification of 20x, 4 fields, 6 Z-slices per well), and fluorescence images processed with DALGreen (Ex:405nm/Em:500-550nm) and bright field images were captured.
  4. Contrast-enhanced Bright Field (CE Bright Field) images*2 were created from the bright field images using the CellPathfinder, and the cells were counted. Granules produced through autophagy were analyzed in the fluorescence images.

Autophagy detection

Fig. 1: Autophagy detection Fluorescence images of the control (A), autophagy induction (B) and autophagy inhibition (C) 6 hours after changing the medium. 
(D) (E) (F): CE Bright Field images of (A), (B) and (C) respectively (Scale bar: 100 µm)
(G): Images (from left) immediately after changing the medium, 3 hours later and 6 hours later (Scale bar: 50 µm).
  Time lapse movie : Play


Autophagy analysis result

Fig. 2: Autophagy analysis result Merged images of the control (A), autophagy induction (B) and autophagy inhibition (C) 6 hours after changing the medium.
(D) (E) (F): Analyzed images of (A), (B) and (C) respectively (Blue points: centers of recognized cells; Red: recognized regions of autophagy granules) .
(G) (H): Change of count and total area of granules per cell over time. Error bars indicate SE (n=3). (Blue: control, Red: autophagy induction, Green: autophagy inhibition).
The count and total area of granules increased over time only in the autophagy induction.

Results and Discussion

It was confirmed that live cell autophagy can be easily observed using the CQ1 and DALGreen-Autophagy Detection. Also, autophagy was induced in the media not containing amino acid and inhibited by adding Bafilomycin. The CQ1 allows for the observation of changes with time while maintaining the culture environment through the use of its stage heater for the control of temperature and humidity, as well as the concentrations of CO2 and O2 through the combined use of a gas mixer.

*1 Reference: Iwashita et al., Small fluorescent molecules for monitoring autophagic flux, FEBS Lett,2018,592(4),559.

*2 CE Bright Field images
Contrast-enhanced Bright Field (CE Bright Field) images refer to processed images emphasizing the cell thick areas (Fluor type) and contours and details (Phase type), which are suitable for cell recognition without staining.

CE Bright Field images


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Overview:

Introduction

For years, many types of high-density culture methods, such as spheroids, fiber scaffolds, and extracellular matrixes, have been proposed for in vitro cell-based assays. These culture systems have been recognized to more accurately simulate a cells natural environment than standard monolayer cultures on a flat substrate. Therefore, cells in high-density culture conditions are expected to exhibit responses against chemical treatments that closely resemble responses of tissues in vivo.

General homogeneous assay protocols originally developed for monolayer culture can be applicable to these high-density culture systems with minor modifications.
However, for microscopy and other image-based assays, there are significant obstacles to overcome when applying conventional image analysis protocols to high-density cultures. The optical architectures of most microscope-coupled research instruments do not capture light based information throughout the entire thickness cell aggregates due to depth-of-field limitations. In addition, image-analysis software optimized for monolayer cell culture are not able to perform cell-by-cell object recognition and resulting quantification.

Here we show a set of examples with an ultra-high density HepG2 (hepatocellular carcinoma) cell culture to explain how the CQ1 can capture clear images from entire thickness of a cell layer three-dimensionally. Additionally, we will show how the CQ1 can analyze cell responses against chemical treatment, on a cell-by-cell basis.
The protocol on this note has a potential applications for analyses of various high-density cultures, including three dimensional cell culture conditions.

Figure 1. Images of highly dense HepG2 cultures and nuclear contouring.

Figure 1. Images of highly dense HepG2 cultures and nuclear contouring.
Non-treated (a) or staurosporine (10-7 M for 48 h) treated (c) cells.
Three dimensional cell-by-cell nuclear recognition was carried out by using the Spheroid Analysis Algorithm of the  CQ1 software (b and d). Objective lens: 20X.

Experimental procedure

•A 96-well glass bottom microplate was coated with an extra cellular matrix, Matrigel (5 fold dilution with culture medium).
•HepG2 (hepatocellular carcinoma) cells were seeded on the pre-coated plate at a density of 5X104 cells/well. The plate was incubated for 48 hours  to create an over-confluent state.
•Staurosporine was added to experimental wells and the plate was incubated for and additional 48 hours.
•Cells were fixed with a formaldehyde solution then tagged with anti-active caspase-3 and anti-H3Ser10P. Bound primary antibodies were visualized with fluorescently labelled secondary antibodies. Cell nuclei were stained with Draq7 in the presence of RNaseA.
•Cell images were captured and the images analyzed by the CQ1. Graphing and statistical processing was carried out using FCS Express™ 5 Image Cytometry (De Novo Software, Glendale, CA) (optional).

Results and discussions

An ultra high-density HepG2 cell culture was created and cell-by-cell analysis was carried out by the CQ1 to evaluate cell responses against staurosporine, a hepatotoxic chemical.
•To facilitate dense cell layer formation, the plate was coated with an extracellular matrix. In preliminary tests, compared with culture on a non-coated normal plastic-bottom plate, HepG2 cells plated on the matrix-coated substrate exhibited approximately ten-fold  higher sensitivity toward staurosporine toxicity (data not shown).
•Images of fluorescently labelled cells were captured in three-dimensions from the thick cell layer formation (Fig 2). Two molecular markers, H3Ser10P (cell growth) and active caspase-3 (apoptosis) were selected for immunofluorescent labelling.
•Segmentation of individual cell nuclei enabled cell-by-cell characterization in response to sturosporine (Fig 3).
•The CQ1 is a versatile system that allows simultaneous analysis of multiple markers and parameters at the single cell level in high density cell culture based assays, including thick cultures of hepatocytes.

Figure 2. 3D reconstitution of HepG2 cell images

Figure 2. 3D reconstitution of HepG2 cell images.
Twenty-one slices (along the Z-axis) of a multicolor image encompassing 50  µm of thickness were reconstructed to create a 3D image. Non-treated (a) or staurosporine treated (b) cells were fluorescently immunostained with anti-H3Ser10P (magenta) and anti-active caspase-3 (green). Cell nuclei were stained with Draq7 (gray). Objective lens: 20X.

Figure 3.  Multi-parametric analysis of two cell markers

Figure 3.  Multi-parametric analysis of two cell markers
Image analysis data from the CQ1 of non-treated (a) or staurosporine treated (b) cells was exported and further analyzed by scatter plots in FCS Express™ 5 Image Cytometry. The proportions of the growing or dead cell populations were evaluated quantitatively. On each scatter plot, 1X104 events were plotted.

 


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Application Note
Overview:

Fucci Cell Cycle Analysis

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.

fucci

Left: Control (0.1% DMSO)  Right: MitomycinC 3uM

Time lapse movie  Play


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Overview:

Imaging of Calcium Signals in iPSC-derived Myocardial Cells

High speed time lapse (20fps) imaging of individual spheroids’ calcium flux.
iCell Cardiomyocytes (CDI, Inc) were incubated on Elplasia (Kuraray Co., Ltd.), spheroids were formed, and individual spheroids’ mean intensity was calculated using a calcium indicator.



Time lapse movie  Play

Left. High speed time lapse of calcium signals in iPSC-derived myocardial cells (objective lens: 10x, imaging speed: 20fps)
Right. Signal waveforms in individual spheroids

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Application Note
Overview:

Introduction

Micronucleus test is carried out to evaluate the genotoxicity of chemical substances. Micronucleus is a smaller nucleus which are left in the cytoplasm without being taken into the main nucleus when cell division occurs due to abnormality in the chromosomes. In this test, micronucleus is counted after cells are exposed to the chemicals examined. CQ1 users can take high quality confocal images and set analysis protocols to automate the detection and counting of the micronucleus and main nucleus. In this application note, we examined the genotoxic effects of mitomycin C (MMC), which is commonly used as a positive control in micronucleus test. An important requirement in this test is the division of nucleus during and/or after exposure to the test substances. In the present experiment, we treated the cells with cytochalasin D, an inhibitor of actin polymerization, so that we distinguished multinucleated cells, in which the nucleus had divided at least once, from mononucleated cells, in which the nucleus had not divided after exposure to MMC. Then we counted cells having micronucleus, mononucleus and multinucleus.

Figure 1. Detection of micronucleus in CQ1

Figure 1. Detection of micronucleus in CQ1
(A and B) Examples of cells without (A) and with (B) MMC treatment. Cell (left, CellMaskTM Deep Red), nuclei (middle, Hoechst 33342) and the recognition by CQ1 (right). Main nuclei (blue dots),  cell bodies (red outlines) and micronuclei (green dots) are recognized. Only bi-nucleated cells were analyzed in this figure.
(C) A micronucleus (arrow in left and orange dot in right) which is not completely separated from the main nucle
 

Figure 2. Frequency of the cells with micronucleus among multinucleated cells.

Figure 2. Frequency of the cells with micronucleus among multinucleated cells.
MMC induces micronucleus in dose-dependent manner.



Figure 3. Detection of multinucleated cells.
(A) Examples of cells (green outlines) having 1 to 4 nuclei (red dots) recognized by CQ1. (B) Number of cells with 1 to 4 nuclei. Colors indicate the number of nuclei. (C) Ratio of multinucleated cells against mononucleatedcells.

Experimental procedures

Experimental procedures
  • CHO-K1 cells were seeded in a 96-well plate (NUNC #165305, 3,000 cells/well) and incubated for a day.
  • Cells were incubated for another 24 hr in the presence of MMC.
  • Cells were treated with 6µM cytochalasin D for 24 hr.
  • Cells were fixed with formaldehyde, then the nuclei were labeled with Hoechst 33342 and plasma membrane was stained with CellMaskTM Deep Red.
  • Images were acquired by CQ1 (20x objective lens, z slice: 1µm x 31).

 

Results and Discussion

We could detect not only micronuclei isolated in the cytoplasm but also those not completely separated from the main nuclei in the image so that we were able to quantify the increase of the frequency of the cells with micronucleus precisely. In micronucleus test, it must be ensured that the nucleus has divided during and/or after the exposure to the substances examined. For this purpose, we used cytochalasin D to prevent the division of cytoplasm, and counted the number of main nucleus in individual cells to distinguish multinucleated cells and mononucleated cells. The number of mono and multinucleated cells is necessary also to estimate cytotoxic side effects. In the present experiment, high dose of MMC not only induced micronucleus but also prevented cell division.
The present results demonstrate that users can collect data necessary for micronucleus test by confocal imaging and image analysis in CQ1. CQ1’s flexible analysis function enables users to analyze with multiple measures such as the number of micronucleus and main nucleus, volume and length as needed. Therefore, CQ1 would be a powerful research tool not only for micronucleus test but also for the basic research of cell division mechanism.

Mitomycin C (MMC)
MMC has genotoxicity including cutting DNA and induces micronucleus.

Cytochalasin D
An inhibitor of actin polymerization. Cytochalasin D prevents the division of cytoplasm, but does not of nucleus, so that it induces multinucleated cells.

 


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Overview:

Introduction

Cell number is one of the most basic and significant metrics for evaluating effects of chemicals on cultured cells. Analyzing factors related to cell number, such as change of cell cycle pattern and apoptosis frequency as well as molecular events, are useful ways to understand the mode of action of chemicals. The combination of fluorescently labeling individual phenotype markers and analyzing with the CQ1’s multicolor image acquisition feature enables the collection of multiple streams of quantitative information simultaneously.
Below we describe a basic example of multi-parameter analysis using HeLa cells treated with an anti-cancer therapeutic agent, VX-680 (Tozasertib).

Figure 1. Molecular mode of action of VX-680 and its effect on HeLa cells.

Figure 1. Molecular mode of action of VX-680 and its effect on HeLa cells.
a) Schematic representation of  molecular mechanism of VX-680;
b) Dose-response curve of VX-680 vs Cell Count. Error bar: SEM (n=3).
c) Multi-color cell images of negative control (upper) and VX-680 treated (lower) wells. Red: Phosphorylated histone H3Ser10 immunostain; Green: caspase-3 active form immunostain; Blue: Druq7 nuclear stain (pseudo color).

Experimental procedure

•HeLa cells were seeded in a 96-well microplate at a density of 2X 104 cells/well.
•Serial dilutions of VX-680 were added to the culture (Fig 2) and incubated for 24 h followed by fixation with formaldehyde solution.
•Phosphorylated histone H3Ser10 (G2/M progression marker) and active form caspase-3 (apoptosis marker) were fluorescently visualized by double-immunostaining. Cell nuclei were stained with Draq7.
•Cell images were captured using the CQ1 with a 4X objective lens and fluorescent excitation by 488/561/640 nm lasers.
•Acquired digital images were analyzed by the CQ1 software and obtained numerical data were further processed with the FCS Express™ 5 Image Cytometry (De Novo Software, optional) and statistical software.

Figure 2. Plate layout for the VX-680 dose-response experiment

 

Figure 2. Plate layout for the VX-680 dose-response experiment.

Results and discussions

HeLa cells were treated with VX-680 in an increasing dose-dependent manner and multiple parameters related to cell number were analyzed using the CQ1.
•Cell cycle histograms show 4N cell accumulation indicating cell cycle arrest at G2/M-phase (Fig 3a upper and Fig c).
•Scattergram analysis of immunostaining intensities of individual cells show an apparent reduction of H3Ser10 phosphorylation even at low chemical doses (Fig 3a middle and Fig b).
•Active form caspase-3 intensities of immunostained cells indicated an increase in apoptosis level (Fig 3a lower and Fig d).
•A comparison of these three parameters indicate that the reduction of phosphorylated H3Ser10 started at a low concentration of the chemical. This result implies suppression of Aurora kinasis an early event that triggers cell cycle arrest leading to apoptosis.
•In total, these sequential phenomena lead to the reduction of  HeLa cell number by VX-680.

Figure 3 Analysis of three  parameters of VX-680 treated HeLa cells.

Figure 3 Analysis of three  parameters of VX-680 treated HeLa cells.
(a) Numerical data of cell measurement was exported from the CQ1, then cell population data was further analyzed by three parameters: DNA content (upper panels), DNA content and phospho-histone H3Ser10 immunostain intensity (middle panels) or DNA content and active caspase-3 immunostaining intensity (lower panels). 
(b-d) Dose-response curves of phospho-histone H3Ser10 of G2/M gated cell population (b), average DNA content (c) and active caspase-3 from whole cell population (d). Error bar: SEM (n=3).


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Overview:

Neurite Outgrowth of iPSC-derived Neurons

Analysis of neurite outgrowth and spontaneous ignition of calcium-indicated iCells.
iCell DopaNeuron was cultured in a mixed culture fluid of BrainPhys Neuronal Medium (STEMCELL) and Neuron Culture Medium (WAKO).

State of spontaneous ignition after 20 days.

Time lapse movie Play


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Overview:

Introduction

DNA is under continuous genotoxic stresses from variety of environmental factors and cells have mechanisms to repair damaged DNA. The DNA repair machinery can be visualized as the granules in the nucleus by labeling proteins contained in the protein complex formed around the damaged part of DNA. Quantitative analysis of these granules is essential in the research fields such as anticancer agent, influence of radiation, monitoring the genotoxicity of environmental chemicals including tobacco ingredients, and the basic research of cell cycle and DNA repair mechanisms as well. This application note offers an example of the analysis of granules in the nucleus with CQ1. We performed fluorescent immunocytochemical staining for γH2AX then confocal images were acquired and analyzed with CQ1. Confocal optical system is ideal for the quantitative analysis of intracellular granules because it eliminates fluorescence from out-of-focus plane. In this experiment, we examined the production of phosphorylated histone H2AX (γH2AX) induced by hydrogen peroxide  (H2O2) and the effect of wortmanin, an inhibitor of DNA repair.

Figure 1. Detection of the granules of γH2AX with CQ1.

Figure 1. Detection of the granules of γH2AX with CQ1.
(A) Cells treated with H2O2. Right pictures show the higher magnification view of the cells marked by the arrows in the lower magnification view in the left. Nuclei and γH2AX granules are labeled with Hoechst33342 and Alexa Fluor 488, respectively.
(B) Cells without H2O2 treatment. (C) Cells exposed to H2O2 after wortmannin treatment.

Figure 2. Production of γH2AX granules in response to H2O2 treatment and the inhibition of the granule production by wortmannin
Figure 2. Production of γH2AX granules in response to H2O2 treatment and the inhibition of the granule production by wortmannin
Confocal images were analyzed with the dot analysis template in the CQ1 software. Mean number of granules in a cell, size of the granules and the total intensity of the granules were quantified for each well (n = 5 wells for each experimental condition). Bars indicate s.e.m.

Experimental procedures

HeLa cells were seeded (10,000 cells/well) in a 96-well plate (Greiner#655896) and incubated for a day.
Wortmannin was applied in the wells (0 – 25 µM final concentration , 10 min, room temperature).
H2O2 was applied in the wells (1 mM final concentration, 45 min, 37℃).
Cells were fixed with formaldehyde.
Nuclei were stained with Hoechst33342 and γH2AX was labeled with rabbit anti-γH2AX antibody (Enzo, No. ADI-905-771-100) and Alexa Fluor 488-labeled 2nd antibody .
Confocal images were acquired with CQ1 (40x objective lens, 25 fields per well) and analyzed with the CQ1 software.

Results and discussion

In this experiment, we confirmed that H2O2 induces an increase in the number, size and amount of fluorescence of the γH2AX granules. In addition, the present results also confirmed the dose-dependent inhibitory effect of wortmaninn on the formation of γH2AX granules. It has been known that variety of proteins are recruited to form the DNA repair complex and a large number of H2AXs are phosphorylated in chain around the damaged part of DNA. The present results are consistent with the known mechanism of the production  of γH2AX granule.
The present experiment shows that CQ1 is an excellent tool for the quantitative analysis of  intracellular granules.

*γH2AX
Histone H2AX is contained in the histone protein cores of DNA winds in nucleosomes. γH2AX is the phosphorylated form of H2AX and involved in DNA repair.


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Overview:

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.

Application Note
Overview:

SH-SY5Y Neurite Outgrowth

Analysis of cell proliferation and neurite outgrowth over time (without staining)

SH-SY5Y

Left: CE Bright filed
Right: Analyzed Pink: Neurite, Blue: Cell body

Time lapse movie : Play

Time lapse imaging of SY-SY5Y cells was conducted over 67.5 hrs at 1.5 hr intervals, analyzed using CE Bright filed images.
Cell count, total neurite length and junction count were calculated.


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Overview:

List of Selected Publications : CV8000, CV7000, CV6000

Overview:

Introduction

Cell migration is fundamental in various physiological processes including ontogeny, and is involved in variety of diseases such as osteoporosis, arthritis, congenital brain and heart abnormalities and cancer metastasis.
Cell migration is also important for the regeneration of damaged tissues.
To assess the capability of cells to migrate, the scratch assay is one of the most widely used assay because of its simplicity and inexpensiveness. In this application note, we provide an example of scratch assay by using CQ1. We carried out time lapse live cell imaging to examine the temporal change of the distribution and the number of cells in scratch assay.

 

Figure 1. Time lapse images of monolayer cultures of HeLa cells transfected with Fucci. Figure 1. Time lapse images of monolayer cultures of HeLa cells transfected with Fucci.

Figure 1. Time lapse images of monolayer cultures of HeLa cells transfected with Fucci.
(A and B) Cultures without (A) and with (B) mitomycin C (MMC) treatment.
Upper and lower panels shows large field images and higher magnification images showing recognized cells in the white frame in the upper panels.
Red and green labels indicate cells in G1 and S/G2/M phase, respectively.

 

Figure 2. Temporal change of the number of cells in the cell-free gap

Figure 2. Temporal change of the number of cells in the cell-free gap
Number of cells in the cultures shown in figure 1 is plotted against time. Red and green bars represent cells in G1 and in S/G2/M phase, respectively.

 

Figure 3. Scratch assay

Figure 3. Scratch assay
A Cell-free gap are created by making a scratch on confluent monolayer cell culture. Then the invasion of migrating and/or proliferating cells into the gap is assessed.

 

Experimental procedures

• HeLa cells transfected with Fucci were seeded in a 24-well plate (Greiner#662160) and incubated for a day.
• A scratch was created with a pipette tip on the confluent monolayer cell culture.
• MMC was applied in the well for an hour to stop the cell division cycle then washed out.
• Time lapse images were acquired by CQ1 for three days.
• Image acquisition settings: 10x objective lens, 30% laser power, 500 ms exposure and 1 hr interval.

Results and Discussion

We performed scratch assay by using CQ1 and were able to capture the process of infiltration of the cells into the cell-free gap with time.
In the well without MMC treatment, the cell cycle proceeded and the number of cells both in G1 phase and cells in S/G2/M phase increased in the cell-free gap with time, suggesting that the gap was filled with migrating and proliferating cells.
The number of cells in the gap also increased with time in the well treated with MMC.
However, most of the cells in the MMC treated well were in S/G2/M phase indicating that the cell cycle was arrested.
This result suggests that the gap was filled mostly with migrating cells.
The present experiment demonstrates that CQ1 is an excellent tool for the quantitative analysis of cell migration and proliferation.

 

*FUCCI
Fluorescent Ubiquitination-based Cell Cycle Indicator.
Cells transfected with this probe emit red fluorescence in G1, and green fluorescence in S/G2/M phase, respectively.

*Mitomycin C (MMC)
MMC damages DNA and prevents DNA replication by making DNA crosslinks and producing free radicals when metabolized.


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Overview:

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

Overview:

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

Overview:

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.

Overview:

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

Overview:

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

Overview:

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

Overview:

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

Overview:

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

Overview:

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.

Yokogawa Technical Report
Overview:

We have been developing a prototype of a genomic drug test support system using our CSU confocal scanner. This system administers chemical compounds that serve as potential drug candidates into living cells, which are the most basic components of all living organisms, records the changes in the amount and localization of target molecules inside cells with the CSU confocal scanner and a highly sensitive CCD camera, and processes and quantifies the captured high-resolution image data.

Yokogawa Technical Report
18.6 MB
Yokogawa Technical Report
6.1 MB

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