Using Label-Free Wound Healing Assay to Monitor Cell Migration and its Inhibition

Published on December 20, 2016 at 12:44 PM

Introduction

The term cell migration refers to the arbitrary movement of cells that play an important role in pathological and physiological processes. Cell migration is also a central part of fundamental biological processes like immune response, wound healing, tissue formation, and other processes like invasion and metastasis of cancer [1,2].

A cyclical 5-step procedure forms the fundamental principal of cell movement that begins with cell polarization and protrusion of the leading edge. This is followed by the leading edge attaching to the substrate and the subsequent proteolytic degradation of actomyosin contraction, tissue components, and other similar physical barriers.

In the final step, the cell rear glides forward. The remaining inter-cellular cell-cell connections of the leading edge represent the key modification of collective cell movement. As a result, the standard steps are coordinated at the same time2.

In order to devise new therapeutic strategies to control certain biological processes, for example cellular invasion that plays a central role in cancer metastasis, it is important to have a better understanding of the mechanism of collective cell migration.

Wound healing assays are a powerful tool for studying the migration of cells. When an artificial gap is created into a confluent cell monolayer, either by eliminating a growth barrier or in the form of a scratch, the assay tracks the migration of cells from the edges over time until the new cell-cell contact is established and the gap is closed again.

The rate of wound healing and the extent of wound healing give information about cell health, migration properties, as well as the potential to interact with other cells. They also provide information on how each of these parameters can be affected by test molecules.

In this article, experiments were conducted to track how different types of cells heal the wound or move into a created gap. Also demonstrated is the inhibition of wound healing with Cytochalasin D.

The wound healing experiment process was performed using 35mm µ-Dishes and culture-Inserts supplied by ibidi. BioTek’s Lionheart™ FX Automated Live Cell Imager was used to monitor wound closure, and the Gen5 software was used to perform cellular analysis of the kinetic images captured.

Materials and methods

Materials

ibidi culture-insert

The ibidi Culture-Insert was used in the place of traditional scratch assays. Located on a cell culture surface, silicon inserts offer two cell culture reservoirs. A 500 µm-thick wall separates these two chambers.

The culture insert sticks to the uniquely designed bottom of a 24-well plate or µ-Dish. With this adhesive design, the cells are unable to grow under the wall of the insert. The Culture-Inserts 2 well in a µ-Dish 35mm, high, supplied by ibidi, was used for the experiments performed here.

Cells

Immortalized keratinocytes and HT-1080 fibrosarcoma cells were bought from ATCC (Manassas, VA); and Angio-Proteomie (Boston, MA) supplied RFP expressing human neonatal dermal fibroblasts.

Wound healing inhibitor

The Cytochalasin D compound is a strong disruptor of actin filament function3 and it also interferes with actin polymerization. As a result, it was used to inhibit cell migration.

Lionheart™ FX Automated Live Cell Imager

With its Augmented Microscopy™, the Lionheart™ FX Automated Live Cell Imager delivers digital microscopy with high magnification images using up to 100x objectives. The microscopy module also offers microscopy in brightfield, color brightfield, fluorescence, and phase contrast.

The instrument has been optimized for long-term live cell imaging and kinetic assays due to environmental control such as gas control, temperature, and a humidity chamber. The system was used for tracking wound closure in phase contrast.

Gen5™ Microplate Reader and Imager Software

The Gen5™ 3.0 Microplate Reader and Imager Software was used for automated image capturing and analysis. Sample translation, focusing, and exposure control were used to fully automate image acquisition.

Precise values in variable parameters, for example object intensity and object size and area, were measured by the cell analysis tool. The customized transformation tool can be used to convert the measured values into the required presentation technique.

MetaVi Labs Cell Analysis Software

A second, independent analysis tool was used to verify the data provided and measured by the Gen5 software. Images captured over the entire incubation period were uploaded to the software, along with pixel resolution values required for calculation.

After analyzing the images, a comprehensive report, including graphs¸ was provided by the software that showed the various determinations of wound healing.

Methods

Cell preparation

The neonatal dermal fibroblasts, immortalized keratinocytes, and HT-1080 fibrosarcoma were grown in a T75-Flask until they reached a confluency of 80%. The cells were detached from the flask using a cell detachment solution, Accutase.

All cell types were re-suspended to a concentration of 5.0x105 cells/mL, followed by adding 70µL of cell suspension (35,000 cells per reservoir) to each inset chamber (Figure 1). The cells then adhered to the coated base of the dish and allowed to reach confluency overnight.

Sterile forceps were used to remove the plastic inserts. The cell patch was washed with 2mL of fresh culture medium and then with 2mL of culture medium comprising of 0nM, 100nM, or 10,000nM Cytochalasin D.

wound healing assay in the ibidi Culture-Insert

Figure 1. Performed experimental workflow for the wound healing assay in the ibidi Culture-Insert. The medium used in step 3 contained either 10,000, 100 or 0 nM Cytochalasin D.

Imaging

After placing the dishes in the µ-Dish Microscopy Rack, they were fixed with the magnetic lid for further stabilization. The µ-Dish Microscopy Rack was then placed in the Lionheart™ FX Automated Live Cell Imager, which was earlier set to 5% CO2 and 370C. The wound area was imaged every 30 minutes over a period of 20 hours using a 4x objective and phase contrast.

Image-based analysis of cell movement

Cellular analysis of all 4x phase contrast images, captured over the entire incubation period, was carried out. The Gen5 software, using the cellular analysis parameters in Table 1, automatically places the masks around the objects that meet the designated criteria.

Table 1. Gen5 cellular analysis parameters for object mask placement. Objects meeting the designated criteria will be marked with a yellow line

Cellular Analysis Parameters

Channel

Phase Contrast

Threshold

500

Background

Dark

Split Touching Objects

Uncheck

Fill holes in masks

Checked

Min. Object Size

100μm

Max. Object Size

10000μm

Include Primary Edge Objects

Checked

Analyze the entire image

Uncheck

Plug

Width: 700μm;

Length: 1457μm

Advanced Options

Evaluate Background On

1%

Image Smoothing Strength

20

Background Flattening Size

25μm (Rolling Ball diameter)

Advanced detection options were also used aside from the cellular analysis parameters. Evaluation background was reduced to 1% in order to detect the areas containing empty areas and cells within the image plug.

Background flattening was then applied to reduce the slight signal changes inside the migrating cell areas and to improve the contrast between background and object. To accurately mask the collective cell monolayer, image smoothing was applied to smooth out the differences in phase contrast signal within the cellular areas.

An image plug measuring 1457µm and 700µm in length and width, respectively was applied to the 4x image (Figure 2), instead of reviewing the entire field of view.

A 700µm width was selected to include the entire wound area as well as a tiny cell area on either side to apply and compare the phase contrast for cell analysis. The plug with 1457µm in length equaled the 4x field of view in that specific dimension.

 determination of wound healing results

Figure 2. Used metrics for determination of wound healing results. Width of the plug is 700 µm, the length is 1457 µm. Two representative lines were drawn to show the variable wound width across the entire wound length. The yellow line shows the objects masked placed by Gen5 using the parameters defined in Table 1.

Calculation of wound healing metrics

The primary mask, which quantified the area in the cell-containing image plug, was defined using the cellular analysis parameters shown in Table 1. Figure 2 shows this primary mask.

Using the Gen5 calculated metric of (sum area) acquired from the mask, the progression of cell migration can be measured as a function of time in the kinetic assay through a sequence of data reduction steps shown below.

Average wound width as function of time

Though a cell free gap can be created with the Culture Inserts, an inter- and intra-experiment variability continues to remain in its width. This can be justified for using for ‘Gen5 image analysis’ by measuring the average width of the wound for each time point.

Formula 1. Average wound width as function of time

       PA-(Sum Area)t

Wt = ---------------------

        PL

Where;

  • Wt refers to the average wound width (µm) as a function of time
  • PL is the image plug length (µm)
  • PA is the image plug area (µm2)
  • (Sum Area)t is the calculated metric form Gen5 (µm2 )

Percent confluency within the wound area

The average width of the wound at the first kinetic time point was also applied to measure the % confluency within the wound area in line with the following formula.

Formula 2. % Confluency within the wound area

                       (Sum Area)t – Pt(PW-Pt=0)

% Confluency = -----------------------------------

                        PL Wt=0

Where:

  • Wt=0 refers to the average wound width (µm) at the first time point
  • PW is the image plug width (µm)
  • PL is the image plug length (µm)
  • (Sum Area)t is the calculated metric form Gen5 (µm2)

Percent confluency in a fixed wound width gap

Further, the maximum wound-healing rate and % confluency in a fixed wound area (500µm) were calculated for the HT-1080 cell line in line with the following formula.

Formula 3. % Confluency in a fixed wound gap

                              (Sum Area)t – PL(PW-WLWW)

% ConfluencyFixed = -----------------------------------------

                           WLWW

Where:

  • WL is the fixed wound length
  • WW is the fixed wound width
  • PL is the image plug length (µm)
  • PW is the image plug width (µm)
  • (Sum Area)t is the Calculated Metric form Gen5 (µm2)

The Kinetic Analysis tool of Gen5 3.0 was then used to measure the maximum slope of the true wound area curve in order to provide the maximum rate of wound healing in µm² per minute.

Results and discussion

Label-free monitoring of wound closure over time and its inhibition with Cytochalasin D

The potential of the Lionheart™ FX to accurately image the gap closure process with three different types of cells is shown in Figures 3 to 5. After treating the cell types with 0 (control), 100, and 10,000nM Cytochalasin D, imaging was carried out every 30 minutes over a 20-hour period.

A collective phenotypic movement was shown by the HT-1080 cells, causing the wound gap to close after a period of 8 hours (Figure 3A). Though 100nM Cytochalasin slightly inhibited the wound healing process (Figure 3B), the 10,000nM Cytochalasin D in higher concentration completely inhibited cell migration when compared to the control (Figure 3C).

Image-based monitoring of HT-1080 migration

Figure 3. Image-based monitoring of HT-1080 migration. Imaging was performed over 20 hours using phase contrast and 4x magnification. Kinetic images shown for cells treated with (A) 0; (B) 100; or (C) 10,000 nM Cytochalasin D.

In comparison, keratinocytes migrated as single cells and closed the wound after a period of 9.5 hours (Figure 4A). The lower concentration of Cytochalasin D however affected the total gap closure when compared to the control, and the artificially created wound was not closed even after a period of 20 hours (Figure 4B).

When keratinocytes were treated with 10,000nM compound, it did not show any cell movement when compared to the control and there was no cell migration (Figure 4C).

Visual confirmation of keratinocyte wound healing

Figure 4. Visual confirmation of keratinocyte wound healing. Imaging was performed over 20 hours using phase contrast and 4x magnification. Kinetic images shown for cells treated with (A) 0; (B) 100; or (C) 10,000nM Cytochalasin D.

Finally, the larger, filamentous fibroblasts travelling across the gap was monitored (Figure 5A). The fibroblasts failed to reach confluency within the wound area even after an incubation period of 20 hours.

However, compared to the control, wound healing slowed down when 100nM Cytochalasin D was added to the medium (Figure 5B). Of all the tested cell models, the maximum concentration of Cytochalasin D had the highest effect. Both cell migration and cell adherence were affected, suggesting a possible necrotic effect on the fibroblasts (Figure 5C).

Image-based monitoring of fibroblasts migration

Figure 5. Image-based monitoring of fibroblasts migration. Imaging was performed over 20 hours using phase contrast and 4x magnification. Kinetic images shown for cells treated with (A) 0; (B) 100; or (C) 10,000nM Cytochalasin D

Quantification of wound healing and its inhibition using image-based cellular analysis

Using a primary mask (Sum Area)t, the cellular analysis parameters listed in Table 1 were able to measure the area in the image plug that contained cells. This is shown in Figure 6 over three time points for the HT-1080 cell model. The average Wt, wound width, and % confluency can then be measured in the data reduction tool in the Gen5 software using Formulas 1 and 2.

Representative images at different time points

Figure 6. Representative images at different time points showing the applied object mask of the cellular analysis tool provided by Gen5 3.0.

Kinetic plots are shown in Figure 7, covering a period of 21 hours for the three cell models using three different concentrations of Cytochalasin D. It was seen that cell migration is slightly different between the three cell lines.

However, in each case, Cytochalasin D inhibits the migration of cells in a dose dependent fashion, although to varying extents. After a 7-10 hour period, the cell free gap using the HT-1080 cells was closed while this was delayed to and 8 to 10 hour for the keratinocytes.

By comparison, the fibroblasts reached only 80% confluency following an incubation period of 10 hours, and showed a loss of adherence noted by negative % confluency at the maximum inhibitor concentration.

Quantification of % confluency in the wound area to show cell migration

Figure 7. Quantification of % confluency in the wound area to show cell migration. Formula 2 was used to calculate the values.

The Gen5™ software, to better explain the phenotypic results, provides simple and easy means to track wound healing using alternative metrics. These are shown by using results obtained from the HT-1080 cell model (Figure 8).

As illustrated in the upper right graph (Figure 8), calculations with a fixed wound area can help explain variations observed amongst replicates. This is very crucial when cells begin to migrate prior to initial imaging (Figure 4A and 5A).

Variable determinations of wound healing and cell migration

Figure 8. Variable determinations of wound healing and cell migration. Formula 1, 2, and 3 were used to calculate the values.

In order to demonstrate the actual wound closure, plotting the average width of the wound over time (indicated in the lower left graph in Figure 8), offers information regarding the movement of cell itself.

When Cytochalasin D is absent, the HT-1080 cells will move together, reducing the gap to a value reaching 0. In contrast, a constant average wound width was shown by HT-1080 cells treated with the maximum concentration of inhibitor.

The kinetic analysis tool included in the Gen5™ software finally assesses each curve to establish the maximum rate of wound healing. Cytochalasin D reduces wound healing (lower right graph of Figure 8) until the value approaches 0 with the highest concentration tested.

These metrics, which were automatically established by the Gen5 software, offer high information content and provide a better understanding of the wound healing process and how it can be modified using an inhibiting compound.

MetaVi Labs’s software was also used to validate the analysis carried out with the Gen5 software; both analysis software showed similar analysis results. In Figure 9, the graph showing the ‘Percent Gap Closed All Positions’ is similar to the graph illustrating the ‘% Confluency in the fixed Wound Area’ in Figure 8.

Comparison can be made between the ‘Scratch Open Area All Positions’ and the ‘Average Wound Width’ (Figure 8). The values represent different metrics, although the curve shapes correlate with the values.

The wound area in µm² was measured instead of measuring the wound width in µm. The same progress is demonstrated by both metrics over time. The ‘Gap Closure Speed’ (Figure 9) is also calculated by the software. This is in good agreement with the Gen5 software kinetic analysis of the ‘Max Wound Healing Rate’ shown in Figure 8.

Determination of wound healing using an independent cell analysis software

Figure 9. Determination of wound healing using an independent cell analysis software.

Conclusion

Cell migration can be effectively investigated using the wound healing assay, which has been shown to be a robust method. ibidi’s culture-inserts and the 35mm µ-Dishes simplify the performance and also make it easy to add compounds. The integrated experimental procedure provides results that correlate with what those published in the literature.

The new Lionheart™ FX Automated Live Cell Imager from BioTek has been specifically designed for long-term kinetic imaging of the wound healing process. The Cytation™ 5 can also perform the imaging required for the experimental set-up. The incorporation of suitable environmental settings over the incubation period can help ensure cell health.

Augmented Microscopy™ integrates precise data analysis with accurate time lapse imaging. For each cell type, % confluency was measured while the Gen5 software can be used to automatically measure various determinations of gap closure.

A second analyzing software from MetaVi Labs was used to confirm the results obtained. Cell migration can thus be investigated through a combination of an easy experimental setup, imaging, and precise data analysis.

References

  1. http://www.nature.com/subjects/cell-migration
  2. Ilina Olga and Friedl Peter; Mechanisms of Cell migration at a glance; 2009; Journal of Cell Science: 122, 3203-3208.
  3. John H. Henson, Ronniel Nazarian, Katrina L. Schulberg, Valerie A. Trabosh, Sarah E. Kolnik, Andrew R. Burns, and Kenneth J. McPartland; Wound Closure in the Lamellipodia of Single Cells: Meditation by Actin Polzmerization in the Absence of an Actomyosin Purse String; 2002; Molecular Biology of the Cell: Vol. 13, 1001-1014.

Acknowledgements

Produced from materials originally authored by: Leonie Rieger1, Brad Larson1 and Ulf Rädler2 from:

1Applications Department, BioTek Instruments, Inc., Winooski, VT

2ibidi GmbH, Martinsried, Munich, Germany

The authors would like to thank Michael Wyler, Joel Mailliet, and Gary Prescott of BioTek Instruments for their contributions to the final analysis methods included in the application note.

About BioTek Instruments, Inc.

BioTek Instruments, Inc., headquartered in Winooski, VT, USA, is a worldwide leader in the design, manufacture, and sale of microplate instrumentation and software.

These technologies are used to aid life science research, facilitate drug discovery, provide rapid and cost-effective analysis, and enable sensitive, accurate quantification of molecules across diverse applications.

BioTek espouses a “Think Possible” approach that sets the tone for fresh ideas, unsurpassed customer service and original innovations. As such, they are often honored for local accomplishments and technological innovations, including Best Places to Work in Vermont, North American New Product Innovation Award for Workflow Solutions in Life Sciences and Drug Discovery Product of the Year – Scientists' Choice Award.


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Last updated: Dec 20, 2016 at 12:53 PM

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