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. Author manuscript; available in PMC: 2020 Dec 22.
Published in final edited form as: J Immunol Methods. 2020 Jan 17;479:112747. doi: 10.1016/j.jim.2020.112747

A high-throughput chemotaxis detection method for CCR4+ T cell migration inhibition using image cytometry

Elizabeth L Magnotti a,1, Leo Li-Ying Chan b,*,1, Quan Zhu a, Wayne A Marasco a,*
PMCID: PMC7755103  NIHMSID: NIHMS1617812  PMID: 31958449

Abstract

Chemotaxis is an important aspect of immune cell behavior within the tumor microenvironment (TME). One prominent example of chemotaxis within the TME is the migration of regulatory T cells (Tregs) in response to the chemokine ligands CCL17 and CCL22. Tregs within the TME cause the suppression of anti-tumor immunity and inhibition of the effect of immunotherapeutic treatments. Therefore, the ability to screen for therapeutic antibodies that can inhibit or stimulate the chemotaxis of various immune cell types is crucial. Traditionally, chemotaxis is studied by determining the number of cells in the bottom reservoir of a Transwell microplate using flow cytometry; however, this method is time-consuming and thus not appropriate for high-throughput screening purposes. The Celigo Image Cytometer has been employed to perform high-throughput cell-based assays and was used to develop a new detection method for chemotaxis measurement. The image-based detection method was developed using chemokine ligands CCL17 and CCL22 to induce the migration of CCR4+ T cells and directly count them on the bottom of the Transwell plates. Finally, the method was applied to measure the inhibitory effects of commercially available anti-CCL17 and anti-CCL22 antibodies, which caused a dose-dependent decrease in the number of migrated T cells. The proposed image cytometry method allowed screening of multiple antibodies at various concentrations, simultaneously, which can improve the efficiency for discovering potential antibody candidates that can induce or inhibit recruitment of immune cells to the tumor microenvironment.

Keywords: Chemotaxis, T cell migration, CCR4, CCL17, CCL22, Tumor microenvironment, Transwell, Image cytometry, Celigo

1. Introduction

Chemotaxis plays an important role in the migration of immune cells within the complex network of the tumor microenvironment (TME) (Roussos et al., 2011) and within the inflammatory response (Banfield et al., 2010). The recruitment of regulatory T cells (Tregs) through chemotaxis into the tumor inhibits the antitumor response, thus reducing efficacy of immunotherapeutic treatments (Mizukami et al., 2008; Najafi et al., 2018). Clinically, lower survival rates of cancer patients have been correlated with an increase of Tregs in the TME. Under normal conditions, Tregs are a small subpopulation (4–5%) of CD4+ T cells that typically protect against autoimmune diseases and maintain immune system homeostasis (Ganeshan and Bryce, 2012). Phenotypically, Tregs have positive expression for CD4, CD25high, and forkhead box P3 (Foxp3), where Foxp3 contributes specifically to their regulatory activities (Thornton and Shevach, 1998; Klyushnenkova et al., 2005; Lim et al., 2006; Ganeshan and Bryce, 2012). Currently, immuno-oncology researchers are attempting to develop strategies to inhibit the migration of Tregs to the TME, which can potentially reduce immune regulation and improve antitumor activities (Najafi et al., 2018). It has been reported that chemokine ligands (CCL) 17 and 22 within the TME can stimulate recruitment of Tregs through chemokine receptor CCR4 and impair anti-tumor immunity in ovarian cancer (Mizukami et al., 2008; Chang et al., 2016). In addition, the chemotaxis of CCR4+ Th2 cells in response to CCL22 and CCL17 plays a role in allergic immune responses (Bosnjak et al., 2011; Yoshie and Matsushima, 2015). For example, CCL17 is elevated in the human nasal epithelium in response to allergen provocation in patients with allergic rhinitis, which may contribute to the presence of CCR4 mRNA-expressing cells found in the nasal mucosa. Furthermore, IL-4 and IFN-γ are elevated, consistent with a local Th2-type allergic response (Banfield et al., 2010). Similarly, it is reported that CCL17 and CCL22 are elevated in allergic asthma, causing the migration of Th2 cells to the lungs (Bosnjak et al., 2011) and induction of airway inflammation (Perros et al., 2009). One strategy for blocking the accumulation of Tregs in the TME and for reducing the Th2-type allergic response is the development of therapeutics which block the chemotaxis of CCR4+ cells. In order to evaluate these therapeutics, a high-throughput screening method to identify potential therapeutics that inhibit the migration of CCR4+ T cells is needed.

There are different detection methods for chemotaxis measurement. The most common method is employing the use of a microfluidic device that allows for the formation of chemokine concentration gradients within the chambers in the planar direction (Kim et al., 2007; Zhang et al., 2015). These microfluidic devices are typically manufactured in glass or plastic chips that can hold single or multiple samples, which requires optical imaging of the entire chamber over time to analyze chemotaxis. In general, the microfluidic devices are used to determine the migration pattern of target cells using special image analysis tracking software. Another chemotaxis detection method employs the use of Transwell microplates aimed for high-throughput screening (Unger et al., 2009). The Transwell plates in 24-or 96-well format contain top and bottom reservoirs. The bottom reservoir or bottom of the well can receive the chemokine solution to create a high concentration location. The top reservoir or the Transwell insert is placed directly into the bottom reservoir, which has a thin membrane with a selection of different pore sizes. Target cells can migrate through the pores into the bottom reservoir due to the chemokine concentration gradients. Typically, suspension cells such as T cells can migrate through and fall to the bottom of the well, and be counted using flow cytometry. However, measurement by flow cytometry is time-consuming and low-throughput, and thus does not easily allow for screening multiple target antibodies for the inhibition of cell migration.

In the recent years, image cytometry has increased in popularity for cell-based assays. Specifically, the Celigo Image Cytometer has been used to perform high-throughput cell-based assays by analyzing acquired whole well images (Chan et al., 2016; Zhang et al., 2017; Zigon et al., 2018; Rosen et al., 2019). In this work, we developed a high-throughput image-based detection method to measure CCR4+ T cell chemotaxis using the combination of 96-well Transwell plates and Celigo Image Cytometer. Initially, an in vitro cell-based model was established in the Transwell device with 5 μm pores, where CCR4+ T cells in the top reservoirs are allowed to migrate to the bottom reservoirs containing CCL17 or CCL22. After the image-based method was developed, the application was tested for its ability to detect anti-CCL17-and anti-CCL22 antibody-based CCR4+ T cell migration inhibition. The proposed image cytometry method enables accurate and consistent counting of migrated CCR4+ T cells in whole wells. The ability to perform high-throughput analysis provides a useful tool that improves efficiency in screening potential antibodies that can inhibit the migration of Treg or Th2 cells.

2. Materials and methods

2.1. Preparation of stimulated T cells

CD4+ T cells were purified from fresh PBMCs by negative selection using the EasySep™ Human CD4+ T Cell Enrichment Kit (StemCell Technologies, Cambridge, MA). The CD4+ T cells were then stimulated with soluble CD3/CD28 at 25 μL/mL (10,971, StemCell Technologies) on day one. Next, the cells were maintained in T cell media (RPMI 1640, 10% FBS, 25 mM HEPES, Pen/Strep 1×) at 37 °C and 5% CO2 for a maximum of one week at approximately 1 × 106 cells/mL. IL-2 (20 IU/mL) and TGF-β (5 ng/mL) were purchased from Peprotech (Rockhill, NJ) and added to the cell culture every two days. The T cells were not allowed to proliferate above the optimal concentration of 2 × 106 cells/mL, where the cells began to die if over grown. The phenotype of the T cell population was determined by flow cytometry (Fortessa™ HTS, BD Biosciences, Billerica, MA). T cells were stained with CD3-BV510, CD4-BV711, CD25-BV421, and CCR4-APC according to established protocols by BioLegend (San Diego, CA) and analyzed on the Fortessa™ HTS flow cytometer. We hypothesized that the CD3+CD4+CD25+CCR4+ cells are putative Tregs and that the CD3+CD4+CD25−CCR4+ cells are putative Th2 cells (gating strategy shown in Supplementary Fig. 1) (Kim et al., 2010; Svensson et al., 2012). Intracellular staining for FOXP3 and GATA3, however, was not performed. The stimulated T cells were suitable for the short-term assays performed in this work.

2.2. Preparation of chemokines, antibodies, and Hoechst fluorescent stain

The chemokine ligands CCL17 (MAB364-SP, Novus Biologicals, Centennial, CO) and CCL22 (694,403, BioLegend) were prepared to stimulate the migration of CCR4+ T cells. CCL17 and CCL22 were dissolved in 600 μL of T cell media to 25 and 100 nM of stock concentrations, respectively. Next, three-fold serial dilutions of working concentrations were prepared from 25 to 0.004 nM for CCL17 and from 100 to 0.015 nM for CCL22 at 200 μL for each concentration.

The anti-CCL17 mab364 (MAB364-SP, Novus Biologicals, Centennial, CO), anti-CCL22 LEAF (694,403, BioLegend, San Diego, CA), and anti-influenza HA clone F10 (anti-HA F10, obtained in-house) antibodies were prepared to a stock concentration of 40 μg/mL. Next, five-fold serial dilutions were prepared from 40 to 0.064 μg/mL working concentrations for each antibody.

Hoechst 33342 (CS1–0128–5 mL, Nexcelom Bioscience, Lawrence, MA) was prepared with 16 μL in 20 mL of T cell media to a working concentration of 16 μM.

2.3. Celigo Image Cytometer instrumentation

The Celigo Image Cytometer employed one bright-field (BF) and four fluorescent (FL) imaging channels: blue (EX377/50 nm, EM470/22 nm), green (EX 483/32 nm, EM 536/40 nm), red (EX 531/40 nm, EM 629/53 nm), and far red (EX 628/40 nm, EM 688/31 nm), to perform high-throughput cell-based assays. The Celigo operation and analysis software consisted of five major steps START, SCAN, ANALYZE, GATE, and RESULTS, where the users can enter general information, setup scan/analysis parameters, perform scan/analysis, and then view/export images and results. First, software application “Target 1 + 2” was utilized to autofocus and acquire bright field and blue fluorescent images at 1 μm2/pixel with exposure times set to auto-exposure and 50,000 μs with a gain of 150, respectively. Next, the software was used to directly count the number of Hoechst positive T cells on the bottom of the 96-well plates at different chemokine and antibody concentrations. The ANALYZE parameters for the Blue channel were set to: “Algorithm = Fluorescence”, “Intensity Threshold = 4”, “Precision = High”, “Cell Diameter = 10”, “Dilation Radius = 0”, “Background Correction = Check”, “Separate Touching Objects = Check”, “Minimum Cell Area = 20”. The BF images were not utilized by setting the “Intensity Threshold” to 255. The counting results were used to determine the level of immune trafficking and inhibitory effects of the antibodies.

2.4. CCL-mediated CCR4+ T cell migration chemotaxis assay

The prepared CCL17 and CCL22 solutions (100 μL) were pipetted into the lower reservoirs of two separate 96-well Transwell plates (CLS3388–2EA, Sigma-Aldrich, St. Louis, MO). Next, the prepared Hoechst stain (100 μL) was added to the lower reservoirs, making a final staining concentration of 8 μM. The final CCL17 concentrations were 12.500, 4.167, 1.389, 0.463, 0.154, 0.051, 0.017, 0.006, and 0.002 nM. The final CCL22 concentrations were 50.000, 16.667, 5.556, 1.852, 0.617, 0.206, 0.069, 0.023, and 0.008 nM. Additionally, wells without CCL17 and CCL22 were setup as the negative controls (spontaneous migration). Each concentration was performed in duplicates.

The Transwell inserts were placed into each well, and ~641,000 CD4+ T cells (approximately 300,000 CCR4+ T cells) in 80 μL of T cell media were pipetted into the top reservoirs (~3.75 × 106 cells/mL). The Transwell plates were covered and incubated for 3 h before the initial image cytometry analysis.

After 3 h of incubation (Bach et al., 2007), the plate was immediately imaged using the image cytometer. Next, the Transwell inserts were removed from each well, and the plate was centrifuged at 1200 RPM at 5 min to settle the T cells still in suspension. Subsequently, the plate was imaged again and analyzed to generate CCL17 and CCL22 dose dependent migrated CCR4+ T cell counts. The results were exported into EXCEL and plotted using Graphpad Prism to determine the EC50 values.

2.5. CCL-mediated CCR4+ T cell migration inhibition assay

Based on the chemotaxis EC50 results obtained from the previous experiment, the CCL17 and CCL22 were prepared to working concentrations of 0.6 and 1.0 nM for the chemotaxis inhibition assay, respectively. First, CCL17 and CCL22 solutions (100 μL) were pipetted into the lower reservoirs of two separate 96-well Transwell plate. Next, the prepared Hoechst stain (100 μL) was added to the lower reservoirs. The final CCL17 and CCL22 concentrations were 0.3 nM and 0.5 nM, respectively. Similarly, wells without CCL17 and CCL22 (media only) were setup as the negative controls.

The Transwell inserts were placed into two empty plates, then ~641,000 CD4+ T cells (approximately 300,000 CCR4+ T cells) in 40 μL of T cell media were pipetted into the top reservoirs (~7.50 × 106 cells/mL). Next, the titrations of anti-CCL17 and anti-CCL22 were added separately into the top reservoirs of the two plates, resulting in the final concentrations at 20, 4, 0.8, 0.16, and 0.032 μg/mL. In addition, anti-HA F10 control antibodies were added to both plates serving as the negative control. Finally, the inserts were moved into the plates with CCL17 and CCL22, and then covered and incubated for 3 h before the initial image cytometry analysis.

After 3 h of incubation, the plate was immediately scanned using the image cytometer. Next, the Transwell inserts were removed from each well, and the plate was centrifuged at 1200 RPM at 5 min to settle the T cells still in suspension. Subsequently, the plate was imaged again and analyzed to generate migrated CCR4+ T cell counts in the presence or absence of antibodies. The counting results were exported into EXCEL, where spontaneous migrated cell counts were subtracted from each sample and plotted using Graphpad Prism to determine the IC50 values.

3. Results and discussion

3.1. Measurement of CCL17- and CCL22-induced CCR4+ T cell migration

In this work, the Celigo Image Cytometer was used to develop a high-throughput image-based detection method for measuring CCR4+ T cell migration. In order to demonstrate the ability to directly count migrated CCR4+ T cells in the Transwell plate, we utilized the chemokine ligands CCL17 and CCL22 that are typically abundant in tumor microenvironment to stimulate chemotaxis (Adeegbe and Nishikawa, 2015). The image cytometer was used to image and count every Hoechst+ T cells in the well, which enabled more efficient and accurate method to determine the level of chemotaxis (Fig. 1). During the initial method development, the Transwell plates were imaged without removal of the top reservoir inserts and without centrifuging to further minimize time required to perform the assays. However, we noticed that there were still T cells in suspension that would not be counted by just imaging the bottom surface, thus the plates must be centrifuged prior to imaging. Centrifuging without removing the inserts have also caused T cells to be physically forced through the pores, thus increasing nonspecific migration cell counts. Therefore, the final proposed method required the removal of inserts and centrifugation at the end point of the migration assay.

Fig. 1.

Fig. 1.

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Bright field and fluorescent images of the Transwell and migrated T cells. (Top) Whole well and zoomed bright field images of the Transwell. (Bottom) Whole well and zoomed fluorescent images with Hoechst staining. The T cells that have migrated to the bottom can be directly counted using the image cytometry software to determine the level of chemotaxis. See Materials and methods for experiment set up.

Examples of dose-dependent fluorescent images are shown in Fig. 2a, where the number of T cells migrated to the bottom reservoir correlated well with CCL17 or CCL22 concentrations. The dose response curves are shown in Fig. 2b, where the measured EC50 values are 0.163 and 0.339 nM for CCL17 and CCL22, respectively, which indicated that CCL17 induced a circa 2-fold stronger chemotactic response for CCR4+ T cells. However, CCL22 induced a much higher number of cells to migrate compared to CCL17. It is interesting to note that fewer T cells migrated to the bottom reservoirs at higher chemokine ligand concentrations, which has been observed previously (Ottoson et al., 2001).

Fig. 2.

Fig. 2.

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Stimulatory dose response of CCL17-and CCL22-induced CCR4+ T cell migration. (a) Dose response fluorescent images of Hoechst+ T cells on the bottom of the Transwell. A clear increase in the number of T cells as chemokine ligand concentration increased can be observed. (b) Dose response curves of CCL17 and CCL22 showing EC50 values at 0.163 and 0.339 nM, respectively. Notice that T cell migration decreased at high chemokine ligand concentrations.

3.2. Measurement of anti-CCL17 and anti-CCL22-inhibited T cell migration

The chemotaxis inhibition assays were performed to demonstrate the capability of image cytometry to measure inhibitory dose response with commercially available antibodies. In this experiment, we utilized the EC50 values determined previously to select the CCL17 and CC22 concentrations for the baseline CCR4+ T cell migration. The anti-CCL17 and anti-CCL22 were used to inhibit the migration of T cells through the Transwell membrane. In addition, the anti-HA F10 published previously was used as the negative control for T cell chemotaxis inhibition assays (Sui et al., 2009).

As expected, the tested antibodies were able to inhibit the migration of CCR4+ T cells through the Transwell membrane. Examples of dose-dependent fluorescent images are shown in Figs. 3a and 4a, where an obvious decrease in T cell numbers is displayed with respect to the increase of anti-CCL17 or anti-CCL22 antibody concentrations. The dose response curves are shown in Figs. 3b and 4b, where the IC50 values are 0.234 and 2.304 μg/mL or 1.56 nM and 15.36 nM for anti-CCL17 and anti-CCL22 antibodies, respectively. In contrast, the anti-HA F10 antibodies did not inhibit cell migration, as expected.

Fig. 3.

Fig. 3.

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Inhibitory dose response of the anti-CCL17 antibodies on CCR4+ T cell migration. (a) Dose response fluorescent images of Hoechst+ T cells, where T cell migration decreased as the antibody concentration increased. In contrast, the anti-HA F10 control antibody did not show decrease in T cell migration. (b) Dose response curves of the inhibitory effects of anti-CCL17 showing an IC50 value at 0.234 μg/mL. Interestingly, anti-CCL17 seemed to completely inhibit T cell migration, where spontaneous migrated T cells appeared to be also inhibited at high antibody concentrations.

Fig. 4.

Fig. 4.

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Inhibitory dose response of the anti-CCL22 antibodies on CCR4+ T cell migration. (a) Dose response fluorescent images of Hoechst+ T cells, where T cell migration decreased as the antibody concentration increased. In contrast, the anti-HA F10 control antibody did not show decrease in T cell migration. (b) Dose response curves of the inhibitory effects of anti-CCL22 showing an IC50 value at 2.304 μg/mL. In comparison, anti-CCL17 showed a stronger inhibitory effect on CCL17 than anti-CCL22 on CCL22.

In order to accurately represent the level of CCR4+ T cell chemo-taxis, the spontaneous migration cell counts from the negative control (without chemokine ligands) were averaged and subtracted from the test samples. The anti-CCL22 inhibition curve showed a clear dose response. Note that after subtraction of spontaneous migration, the cell counts at each concentration remained positive. It indicates that high antibody concentrations did not fully inhibit spontaneous CCR4+ T cell chemotaxis. In contrast, while the anti-CCL17 showed complete migration inhibition at antibody concentrations greater than 0.8 μg/mL, it appears that the anti-CCL17 at high concentrations also inhibited spontaneous T cell migration to a certain degree. A low degree of inhibitory effects were also observed at high concentration of the control anti-HA F10 antibody in the presence of CCL17.

4. Conclusion

The Celigo Image Cytometer was able to perform high-throughput counting of migrated CCR4+ T cells using the Tranwell microplates. The method can perform rapid imaging and analysis of the entire 96-well plate in less than 10 min for one bright field and one fluorescent channel. Utilizing image cytometry allowed the screening of multiple antibodies at various concentrations, which can improve the efficiency for discovering highly qualified antibody candidates for the stimulation or inhibition of immune cell recruitment to the TME.

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jim.2020.112747.

Supplementary Material

Supplementary Material

Acknowledgments

The author EM acknowledges support from the T32 Training Program in Cancer Immunology (5T32CA207201). The authors WAM and EM acknowledge support from the Claudia Adams Barr Award.

Footnotes

Declaration of Competing Interest

The author LLC declares competing financial interests. The research in this manuscript is for reporting on biological application using an instrument of Nexcelom Bioscience, LLC. The work was to demonstrate a high-throughput method for detecting T cell migration inhibition using the Celigo Image Cytometer.

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