CV7000S Applications

Application : CV7000S

• Long-term time lapse analysis
  • Spheroid growth
  • HeLa Cell
• High speed time lapse analysis
  • Calcium Signal Analysis
  • Calcium response of Inomycin
• Fixed cell analysis
  • Cell cytoskeleton
  • GPCR Internalization
  • Translocation of NFκB
  • Translocation of PKC
  • Neurite outgrowth of PC12 Cell
  • Apoptosis
  • Cell Cycle

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Long-term time lapse analysis

Spheroid growth

Compare to mono-layered cultured cells, spheroid has similar structures and functions as tissues in living organisms. So spheroid is getting common for a lot of researches , such as drug discovery and toxicity assay.

Detection of spheroid –growth in round bottom well
HeLa-Azami cells were seeded on 96well plate (Corning#4520)with200cells/well condition and cultured O/N, following time-lapse imaging analysis for three days using CV7000. 11 Z-slice images were created as a MIP(Maximum Intensity Projection) 2D-image to quantify area of spheroid. The graph (D) shows a spheroid area at indicated time-points.

Fig. 3 - MIP-images of a spheroid at indicated time points

Fig. 4 - Time-dependent change of size of a spheroid

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HeLa Cell

While live cell imaging is a powerful tool to analyze biological changes in detail, behaviors of individual live cell could be different even under the identical culture/imaging conditions, thus, it is quite useful to track and analyze each cell to obtain accurate analytical results. With the CV7000 “Tracking Analysis” algorism, it is possible to individually track behaviors of many cells over time and quantitatively analyze the data based on various parameters. Long term cell tracking enables cell lineage analysis, too.

Fig.1 - Time-series images of the cells to show recognition of individual cell (play)


Fig. 2 - Tracking of individual cell with gravity center tracing (play)


Fig. 3 - Tracking results of an individual cell for 48 hours

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High speed time lapse analysis

Calsium signal

 

Because of the hydrophobicity of the lipid bilayer of cell membrane, polar molecules are not able to cross cell membrane. It is crucial to keep concentration gradient of solutes between cytosol and extracellular fluid, or intracellular organelles surrounded by membrane. There are many transporter proteins in the cell membrane, which transport polar molecules such as ions into or out of the cells, or intracellular compartments surrounded by membrane. In the case of eukaryote, even when exposed to very high Ca²⁺ concentration such as 10^-3M, cytoplasmic Ca²⁺ concentration can be kept at as low as 10^-7M, while free Ca²⁺ concentration inside the cytoplasm greatly increase as a result of only a small amount of Ca²⁺ influx into a cell. Since Ca²⁺ influx into a cell depending on extra-cellular signals and being enabled by steep concentration gradient is one of the most important way of signal transduction, keeping the concentration gradient of Ca²⁺ is very important for the cells. Ionomycin is an ionophore which is hydrophobic and can dissolve into the lipid bilayer, and thus is effective to enhance membrane permeability of Ca²⁺. Here we present an example of the analysis of changes in the intracellular Ca²⁺ by Ionomycin, by using “Sequential fluorescent intensity analysis” function of the CV6000.

Fig. 1 - Changes in the intracellular Ca²⁺ concentration of each cell in A-1 well.
You can confirm increase in the intracellular Ca²⁺ concentration right after Ionomycin addition.

(a) Raw image before Ionomycin addition

(b) Analyzed image(a)

(c) Raw image after Ionomycin addition

(d) Analyzed image(c)

(e) Changes in the intracellular Ca²⁺ concentration of each cell.

By correlating all time-lapse images of each cell, it is possible to analyze the changes in each individual sell, and thus it is possible to detect cells which show specific characteristics.

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Calsium response of Inomycin

Analysis of the changes in the intracellular Calcium concentration is one of the most important analytical factors in such research area as intracellular signal transduction and muscular contraction. Here we present an example of CV6000 analysis of the Ionomycin-dose dependent changes in intracellular Ca2+ concentration, by using A10 cells loaded with a Calcium dye, Fluo-4, and adding various dosage of Ionomycin,a Calcium ionophore.

Fig. 1

(a) Images at 0.2 sec. interval extracted from the images of 2.6 sec. after start up to 5.4 sec. Ionomycin was added at 3.0 sec. from the start.(Red-framed image)

(b )Before addition of Ionomycin

(c) After addition of Ionomycin

Fig. 2

(a) Averaged fluorescent intensity of individual cell within each well.

(b) Averaged cellular fluorescent intensity pf each well.

(c) Averaged cellular fluorescent intensity as shown at each Ionomycin dosage.

Fig. 3 - Dispenser setting

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Fixed cell analysis

Cell cytoskeleton

The Cytoskeleton provides the cell with structure and shape and plays important roles in both various intracellular transport and cellular division. The eukaryotic cytoskeleton is composed of microfilaments, intermediate filaments and microtubules. There is a great number of proteins associated with them, each controlling a cell‘s structure by directing, bundling, and aligning filaments、thus significant changes in the status of microfilaments,; such ａｓ total number, length, distibution, movement or stability could be observed after drug stimulation. Here, we present an example of cytoskeltal morphology analysis through the observation of fluorescently stained actin, one of major proteins to construct microfilaments.

Fig. 2 - Morphology changes in A10 cells after apoptosis induction

（1）Raw images (a.c) and analyzed images (b.d): Staurosporine: 0uM (a,c), 10uM (b.d)

（2）Total number of actin filament (Cytoskeleton)

（3）Average length of actin filaments (Cytoskeleton) and its deviation

（4）Distribution of actin filament (Cytoskeleton) length

（5）Polarity distribution of cytoskeleton
(Polarity of individual cytoskeleton was measured by defining the horizontal direction as 0 degree)

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GPCR Internalization

GPCR, it will be internalized When a ligand binds tointo cytoplasm from cell membrane to form endosome.
You can measure degree of GPCR Internalization by using such parameters as granular count in endosome and total area of endosomes.

Fig. 1 Images captured by CellVoyager6000.
Blue:  Hoechst33342（nucleus), Green:  Alexa488（NK1R）

（a）SubstanceP : No stimulus

（b）SubstanceP : stimulus（1 M）

（c）Analysis result of image(a)

（d）Analysis result of image(b)

Fig. 2 - Correlation between concentration of SubstanceP and NK1R internarization
（a）Dose-response curve
X axis:SubstanceP, Y axis:Granule count / Cell count

（b）Dose-response curve
X axis:SubstanceP, Y axis:Granule Area / Cell count

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Translocation of NFκB

By using CV6000 “Nuclear Translocation Analysis” algorism, translocation of proteins between cytoplasm and nuclei can be analyzed multilaterally.
Here is an example of the analysis of NFκB translocation after cytokine stimulation.

Fig.1 Images captured by CellVoyager6000
Superimposed images of Hoechst33342(nuclei) and Alexa488（NFκB） are shown.

（a）Raw image before IL-1β stimulation

（b）Raw image after IL-1β(100 ng/ml) stimulation

（c）Processed image of （a） to recognize nuclei and NFκB signals

（d）Processed image of （b）to recognize nuclei and NFκB signals
Superimposed images of Hoechst33342(nuclei) and Alexa488（NFκB） are shown.

Fig. 2 - Relationship between IL-1β dosage and NFκB translocation to nuclei

（a） Dose response curve
X: IL-1β dosage, Y:Mean Nuclei/Cytoplasm Intensity

（b） Scatter plot of Individual cells
X:Nuclei Intensity, Y:Cytoplasm Intensity

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Translocation of PKC

PKC (protein kinase C) is a signaling molecule existing at the downstream of receptor tyrosine kinase or GPCR (G-protein coupled receptor). It is well know that phorbol esters, most typically PMA (phorbol 12-myristate 13-acetate), activates PKC to cause its translocation from cytoplasm to cell membrane. Here we present an example of translocation analysis of PMA treated HeLa cells by using Cellvoyager. Images were acquired by CV6000 (Fig.1a, 1b) and changes in the PKC localization were analyzed by using CellVoyager Analysis Software. As a result, PMA dose-dependent increase in PKC granules on the cell membrane was clearly observed and dose-response curve was obtained (Fig. 2a, 2b). Furthermore, the Analysis software gives numerical data of each cell, such as granule area and fluorescent intensity, and thus is capable for drawing graphs of the data of each cell by using Spotfire software. (Fig, 3a,3b)

Fig. 1

(a) Image of PMA 0ng/ml

(b) Image of PMA 100ng/ml

Fig. 2 - Dose response curve
(a) Dose response curve of the total area of the granules existing on cell membrane

(b) Dose response curve of total fluorescent intensity of the granules existing on cell membrane

Fig. 3 - Analysis result
(a) Ratio of the cells whose total granular area on the cell membrane is higher than 160 (Green), at each PMA dosage.

(b)Ratio of the cells whose total fluorescent intensity of the granules on cell membrane is higher than 240,000(Green), at each PMA dosage.

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Neurite outgrowth of PC12 Cell

CV6000 “Neurite Outgrowth Analysis” algorism is to measure neurite outgrowth by analyzing morphological changes in neuronal cells and quantitate neurite formation, composition and behavior in response to chemical agents and growth conditions, which is useful most typically for neuronal cytotoxicity assay, and for many neuropharmacology research and screening in relation to neuropathological disorders and neuronal injury/regeneration.

By using CV6000, individual cell data in each well can be acquired, which enables detailed evaluation of compounds targeting at neurodegenerative diseases.
Here is an example of the analysis of neurite outgrowth after NGF stimulation of PC12 cell, which is a widely used neuronal cell model originated from adrenal medullary pheochromocytoma.

Fig.1 Images captured by CellVoyager6000.

(a) Raw image before NGF stimulation.

(b) Raw image after NGF (111ng/ml) stimulation.

(c) Processed image (a)  to recognize nuclei and β-TubulinⅢ signals

(d) Processed image (b) to recognize nuclei and β-TubulinⅢ signals
Superimposed images of Hoechst33342 (nuclei) and Alexa488 (β-TubulinⅢ) are shown.

Fig. 2 - Effects of NGF dosage on neurite growth
(a) Dose response of neurite count per cell. Similar dose response curves can be acquired for multiple parameters such as neurite length and branches.

(b) Distribution analysis of neurite length of each individual cell at each NGF dosage. It is possible to analyze individual cell data for each parameter like this graph.

(c) Dose response curve
X:  Staurosporine dosage, Y:  Inclusion Lntensity/Cell Count

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Apoptosis

Under apoptosis, you may observe various phenomena under microscope, such as changes in plasma membrane, Cytochrome-C release, morphological changes such as DNA fragmentation, and behavior of some specific proteins such as caspase. “Nuclear Morphology Analysis” protocol uses DNA aggregation or fragmentation as parameters for apoptosis analysis.

Fig.1 Images captured by CellVoyager6000.

(a) Raw image before Staurosporine stimulation

(b) Raw image after Staurosporine(10M) stimulation

(c) Processed image of (a) to recognize signals

(d) Processed image of (b) to recognize signals

Fig. 2 - Relationship between Staurosporine dosage and nuclei fragmentation
(a) Dose response curve
X: Staurosporine dosage, Y:  Inclusion Count/Cell Count

(b) Dose response curve
X:  Staurosporine dosage, Y:  Inclusion Area/Cell Count

(c) Dose response curve
X: Staurosporine dosage, Y:  Inclusion Lntensity/Cell Count

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Cell Cycle

Measurement of the nuclear DNA level is one of major cell cycle analysis methods, and fluorescent imaging after staining nuclei with DNA dyes such as Hoechst33342 is a simplest way to measure the DNA. If the DNA level at “G1 phase” was 1, it doubles at “S phase” due to DNA synthesis, and thus reaches at 2 at “G2 phase”. Here is an example of Cell Cycle Analysis In HeLa cells by using the CV6000.

To enable data analysis to cover a wider area within each well (Fig. 1). Nuclei were recognized by “Nuclear Morphology” protocol (Fig.3). CV6000 analysis software has “Feature Range Filter” function which groups objects by confirming each image. Here, cell cycle grouping was done based on the fluorescent intensity histogram（Fig.4) Numerical data such as total fluorescent intensity which corresponds to nucleus area and DNA level of each cell, and maximum fluorescent intensity were calculated. Grouped data were summarized by “Feature Range Filter” function, and shown as scatter diagram which may indicate each cell cycle group. (Fig.1) 4 each images per well were captured and analyzed as one image by the CV6000 analysis software. (Fig.2 a,b,c) Scatter diagram based on each single cell in which X is “Total Intensity” and Y is “Mean Intensity”.