Development of a Digital Image-Based Method to Screen Molecules That Regulate Melanization

Abstract

Vitiligo vulgaris is an acquired disorder that is thought to arise from the suppression of melanin synthesis by melanocytes in the basal epidermal layer. To develop therapeutic agents for vitiligo vulgaris, it is critical to identify compounds that promote melanization. In this study, we established a digital image-based method to quantify melanization that does not require biochemical procedures. B16F10 cells were seeded in a white-bottom 96-well microplate. After treatment with or without α-melanocyte-stimulating hormone, followed by fixation of the cells, digital images of the microplates were captured, and the total signal intensity of each well on the image was measured. The extent of melanization in the cells in each well was defined after the subtraction of the signal from the corresponding blank well. This method was found to quantify melanization more sensitively than the conventional technique that measures the absorbance of cell lysates at UV-A wavelengths. We obtained statistical parameters showing that this method was applicable to a high-throughput screening assay; thus, this method appears to be useful for screening and identifying molecules that suppress or promote melanization, the latter of which may be developed as therapeutic agents for vitiligo vulgaris.

INTRODUCTION

Vitiligo vulgaris is an acquired hypopigmentation disorder of the skin that is considered an autoimmune disease, with genetic and environmental factors serving as background contributors. It is thought to result from the suppression of melanin synthesis by melanocytes through autoimmune mechanisms.^1,2) Multiple factors have been suggested as causes of the disease, including autoimmunity against melanocytes and various stressors that affect the function and survival of melanocytes and their precursors. However, the precise pathological mechanism has not been defined. While UV irradiation, topical application of steroids, vitamin D analogs, the calcineurin inhibitor tacrolimus, and surgical approaches consisting of tissue and cellular grafts have been clinically applied for vitiligo vulgaris, no radical treatment has been established. Therefore, the identification of drugs that effectively counteract skin hypopigmentation has long been desired to improve patient treatment.

Melanin synthesis is induced by the binding of α-melanocyte-stimulating hormone (α-MSH) to the G protein-coupled receptor melanocortin 1 receptor (MC1R) in melanocytes. MC1R activates the transcription factor cAMP response element binding protein (CREB) through the cAMP/protein kinase A (PKA) signaling cascade.^3,4) CREB induces the expression of MITF, a master regulator of melanization that induces various enzymes involved in melanin synthesis.⁵⁾ Similarly, the extracellular signal-regulated kinase (ERK) mitogen-activated protein (MAP) kinase pathway enhances melanization through activation of CREB and MITF.^3,6) Although less characterized, the p38 MAP kinase and c-Jun N-terminal kinase (JNK) pathways have also been shown to be involved in stimulating melanization.^7,8) Synthesized melanins are stored in melanosomes, which are lysosome-related organelles that are generated and matured in melanocytes. Melanosomes are transferred from melanocytes to keratinocytes, and then the melanins are polarized within the cells to form the melanin caps that protect the epidermis from UV radiation.^9–11)

Many efforts have been made to explore molecules that induce and/or activate melanization as pharmaceutical leads for vitiligo vulgaris. To evaluate the intracellular melanin content in cultured cells, the spectrophotometric measurement of the absorbance of cell extracts at UV-A wavelengths is widely used.¹²⁾ Although it is a simple method, the preparation of cell lysates is laborious and time-consuming when this method is used in applications such as compound screening.

In this study, we developed a new method that does not require biochemical procedures as a more sensitive and less laborious method to quantify melanization that can easily be applied to high-throughput screening.

MATERIALS AND METHODS

Reagents

We purchased α-MSH and H-89 from Sigma-Aldrich (St. Louis, MO, U.S.A.). SB203580 was obtained from Enzo Life Sciences (Farmingdale, NY, U.S.A.). Coomassie brilliant blue (CBB) G-250 was purchased from Tokyo Chemical Industry (Tokyo, Japan).

Cells and Cell Culture

Murine melanoma B16F10 cells were purchased from the American Type Culture Collection (Manassas, VA, U.S.A.). B16F10 cells were cultured in RPMI-1640 medium containing 8% fetal bovine serum, 50 µM 2-mercaptoethanol, 100 U/mL penicillin G, and 0.1 mg/mL streptomycin under a 5% CO₂ atmosphere at 37°C. Melanization was induced by treatment with various concentrations of α-MSH in the presence or absence of the PKA inhibitor H-89 (1, 3, and 10 µM) and the p38 MAPK inhibitor SB203580 (1, 3, and 10 µM) for 3 or 4 d. B16F10-c1 subclone cells were established using the generally used limited-dilution method.

Quantification of Melanization by Measuring the Absorbance of Cell Lysates at UV-A Wavelengths

B16F10 cells were seeded in 12-well plates and incubated for 3 d with various concentrations of α-MSH. Cells were harvested as pellets, photographed, and dissolved in 400 µL of 2 M NaOH containing 10% dimethyl sulfoxide (DMSO) at 80°C for 60 min. Next, 100 µL of the solution was loaded onto a 96-well microplate. The absorbance of cell lysates was measured at 405 nm.

B16F10-c1 cells were seeded in a 96-well microplate and incubated for 3 d with various concentrations of α-MSH. The cells were dissolved in 100 µL/well of 2 M NaOH containing 10% DMSO at 80°C for 60 min in the same microplate. The absorbance of cell lysates was then measured at 405 nm.

Quantification of Melanization by Analyzing the Digital Images of the Microplates

Cells were seeded in a white-bottom 96-well microplate (CELLSTAR®, 96 Well, F-Bottom, #655083; Greiner Bio-One, Frickenhausen, Germany or white plate for luminescence measurement with lid, MS-8096W; Sumitomo Bakelite, Tokyo, Japan) and stimulated with α-MSH for 3 d. Cells were fixed with 3.7% paraformaldehyde in phosphate-buffered saline (PBS) for 12 min, washed twice with PBS, and left to dry overnight after the removal of the fixation solution. Digital images of the microplates were acquired using the ChemiDoc Touch Imaging System (Bio-Rad, Hercules, CA, U.S.A.). Each microplate was covered with the Bottom Viewer (Ieda Boeki, Tokyo, Japan) to capture images of all wells without distortion, particularly those at the periphery of the plate. The total intensity of each well on the image was measured using the Image Lab software version 5.2.1 (Bio-Rad). The total intensity of the corresponding blank well was measured on the image of a blank plate in the same manner. The data were normalized by comparing the signal intensities between the wells in the experimental plate and the corresponding wells in the blank plate to compensate for uneven background illumination. The extent of melanization of cells in each well was defined after the subtraction of the average value of the blank wells.

Estimation of the Number of Cells Cultured in White-Bottom Microplates

Cells in a white-bottom microplate were fixed and a digital image was obtained; the cells were then stained with 0.25 w/v% CBB G-250 in 10% acetic acid and 30% methanol for 15 min, washed with 99.5% methanol for 1 min to remove background staining, and dried overnight after the removal of methanol. A digital image of the microplate was acquired, and the data were processed as described in the above section.

Validation of the Digital Image-Based Method as a High-Throughput Screening Assay

Cells were seeded in a white-bottom 96-well microplate at various concentrations and stimulated with 5 nM α-MSH for 3 d. Melanization was quantified using the digital images of the microplates as described above, and the Z′-factor and signal-to-background ratio (S/B), where background represents basal melanization in unstimulated cells, were calculated using the formulas below, as described previously.¹³⁾ Coefficient of variation (CV) was calculated to indicate the stability of the target signal.

  

$$\begin{array}{c}{\text{Z}}^{\prime }=1-(3\times \text{standard deviation of}\alpha \text{-MSH-stimulated cells}\\ [\text{72 wells}]+3\times \text{standard deviation of unstimulated cells}[16\\ \text{wells}])/(\text{average of}\alpha \text{-MSH-stimulated cells [72 wells]}–\\ \text{average of unstimulated cells [16 wells])}\end{array}$$

where S/B is the average of α-MSH-stimulated cells (72 wells)/average of unstimulated cells (16 wells) and CV is the standard deviation of α-MSH-stimulated cells (72 wells)/average of α-MSH-stimulated cells (72 wells).

RESULTS AND DISCUSSION

Evaluation of Melanization by the Conventional Method of Spectrophotometric Measurement of Cell Lysates

We stimulated B16F10 cells, which were originally established for cancer metastasis research but are often used in melanin research,¹⁴⁾ with α-MSH and examined the increase in melanization using the conventional method, in which the absorbance of cell lysates at 405 nm was measured (Fig. 1). While the increased black pigmentation in α-MSH-treated cells was detectable by visual inspection, the quantified data demonstrated a statistically significant increase in the α-MSH-induced melanization but did not appear to be sensitive enough to further examine minute changes in melanization. Thus, we sought to develop a more sensitive method to quantify melanization that ideally skips the step of cell lysis to achieve high throughput.

Fig. 1. Quantification of Melanization by Measuring the Absorbance of Cell Lysates at UV-A Wavelengths

B16F10 cells were treated with the indicated concentrations of α-MSH for 3 d, harvested as pellets, and photographed. Cell lysates were prepared, and the absorbance was measured at 405 nm. Data are shown as fold changes in melanization relative to that in untreated cells (mean ± standard error of the mean [S.E.M.]; n = 4 samples). **p < 0.01 and ***p < 0.001. Dunnett’s multiple comparison test, compared with untreated cells.

Comparison between the Digital Image-Based Method and the Spectrophotometric Measurement of Cell Lysates

We first generated cells that more sensitively responded to α-MSH by the limited dilution of parental B16F10 cells. Among the 36 isolated subclones, we selected 1 clone (B16F10-c1) with the lowest basal pigmentation and the highest responsiveness to α-MSH at visual inspection for further analysis (Supplementary Fig. 1). To develop a new method, we considered how to quantify the observable black pigmentation of α-MSH-treated B16F10-c1 cells. We thus explored seeding cells in a white-bottom cell culture plate. Different numbers of B16F10-c1 cells were seeded into each well of 2 white-bottom 96-well microplates and stimulated with various concentrations of α-MSH for 3 d (Fig. 2A). To quantify the extent of melanization using the new method, the cells in 1 plate were fixed with paraformaldehyde and dried after the removal of fixation solution; a digital image of the microplate was then acquired with an imaging analyzer (Fig. 2B). The total signal intensity of each well was measured using the image analyzing software of the imaging analyzer. The extent of melanization in the cells in each well was determined as described in the Materials and Methods section (Fig. 2C). The cells in the other plate were analyzed by the conventional method, where the absorbance of cell lysates at 405 nm was measured (Fig. 2D). Compared to the conventional method, the digital image-based method yielded higher values for α-MSH-induced fold increases in melanization, irrespective of the number of cells seeded per well and the doses of α-MSH. Most prominently, 5.1- and 2.5-fold increases in melanization were detected using the new and conventional methods, respectively, when 2.5 × 10³ cells were seeded and treated with 30 nM α-MSH.

Fig. 2. Quantification of Melanization by Analyzing the Digital Images of the Microplates

(A, B) B16F10-c1 cells were seeded in white-bottom 96-well microplates at the indicated number of cells per well and treated with the indicated concentration of α-MSH for 3 d (A). Cells were fixed with paraformaldehyde, and a digital image of the microplate was acquired (B). (C) The total signal intensity of each well on the image was measured. After subtraction of the background signal, data are shown as fold changes in melanization relative to that in untreated cells (mean ± S.E.M.; n = 3 samples). **p < 0.01 and ***p < 0.001, Dunnett’s multiple comparison test, compared with untreated cells. (D) Lysates of the cells seeded and treated as shown in (A) in an independent white-bottom 96-well microplates were prepared, and the absorbance at 405 nm was measured. Data are shown as fold changes in melanization relative to that in untreated cells (mean ± S.E.M.; n = 3 samples). **p < 0.01 and ***p < 0.001, Dunnett’s multiple comparison test, compared with untreated cells.

Evaluation of the Ability of the Digital Image-Based Method to Test Molecules That Affect Melanization

To further evaluate our new method, we first fixed the number of B16F10-c1 cells seeded per well at 2.5 × 10³ based on the comparison between the new and conventional methods described above. While dose-dependent changes in α-MSH-induced melanization at concentrations of 3–30 nM were hardly detected (Fig. 2C), we found that our method was sensitive enough to detect dose-dependent increases in melanization induced by α-MSH at lower doses (0.05–1 nM) (Fig. 3A).

Fig. 3. Evaluation of the Ability of the Digital Image-Based Method to Test Molecules That Affect Melanization

(A) B16F10-c1 cells were treated with the indicated concentrations of α-MSH for 3 d, and melanization was quantified using the digital image-based method. Data are shown as fold changes in melanization relative to that in untreated cells (mean ± S.E.M.; n = 8 samples). ***p < 0.001, Dunnett’s multiple comparison test, compared with untreated cells. (B) B16F10-c1 cells were treated with the indicated concentrations of H-89, SB203580, and 5 nM α-MSH for 3 d, and melanization was quantified using the digital image-based method. The upper graph shows fold changes in melanization relative to that in untreated cells (mean ± S.E.M.; n = 4 samples). ***p < 0.001, Tukey–Kramer’s HSD test, compared with untreated cells. ^###p < 0.001, Tukey–Kramer’s HSD test, compared with cells treated with α-MSH but untreated with any inhibitors. The microplate was then stained with CBB G-250. A digital image of the microplate was acquired, and the data were processed using the digital image-based method. The middle graph shows fold changes in the extent of CBB staining relative to that in untreated cells (mean ± S.E.M.; n = 4 samples). *p < 0.05, **p < 0.01, and ***p < 0.001, Dunnett’s multiple comparison test, compared with untreated cells. The lower graph shows fold changes in the value of melanization (fold)/CBB (fold) relative to that in untreated cells (mean ± S.E.M.; n = 4 samples). ***p < 0.001, Tukey–Kramer’s HSD test, compared with untreated cells. ^###p < 0.001, Tukey–Kramer’s HSD test, compared with cells treated with α-MSH but untreated with any inhibitors.

We next examined the ability of the new method to determine the effects of compounds that inhibit α-MSH-induced melanization. The PKA inhibitor H-89^15,16) strongly suppressed both the steady-state and α-MSH-induced melanization; the p38 MAP kinase inhibitor SB203580^7,8,17) did not inhibit basal melanization but did inhibit α-MSH-induced melanization, although to a much lesser extent than H-89 (Fig. 3B, upper graph). These results suggest that this method is applicable for evaluating both stimulatory and inhibitory molecules against melanization.

A disadvantage of this method is that the conditions of cells before fixation cannot be easily observed by phase contrast microscopy because the bottoms of the assay plates are not transparent. Therefore, we could not exclude the possibility that the strong effects of H-89 on melanization in Fig. 3B (upper graph) reflected the cytotoxicity of this compound rather than the suppression of melanization. To address this issue, we developed an easy procedure to roughly estimate cell viability using the same microplate after fixing the cells and taking a digital image. We stained the cells with CBB G-250 to visualize them and took a digital image of the microplate. Using the acquired data from both the assay plate and a blank plate, we determined specific signal intensity for each well, which reflected an approximate number of cells in each well, as was the case when we examined melanization. We confirmed the quantitativity of this procedure by showing the linearity between the quantitative value of CBB staining and cell numbers (Supplementary Fig. 2). Although the relative intensity of CBB staining decreased in response to 1, 3, and 10 µM H-89 (Fig. 3, middle graph), the adjusted data (melanization [fold]/CBB staining [fold]) (Fig. 3B, lower graph) were not basically different from the melanization data (Fig. 3B, upper graph). These results suggest that most of the effects of H-89 are due to its inhibitory effects on melanization rather than its cytotoxicity. This CBB staining procedure would help estimate whether a test compound has strong cytotoxicity without the need for any independent experiments.

Validation of the Digital Image-Based Method as a High-Throughput Screening Assay

As a simple workflow that does not require biochemical procedures, the digital image-based method may be superior to the conventional method for compound screening. Thus, we examined the suitability of our method for a high-throughput screening assay using 5 nM α-MSH as a positive control (Fig. 4A). Using data processed from the acquired image (Fig. 4B), the quality control metrics, Z′-factor, S/B, and CV (%), were calculated to be 0.73, 5.16, and 4.13, respectively, which met the criterion of a reliable assay with Z′-factor of ≥0.5¹⁸⁾ (Fig. 4C). When using parental B16F10 cells instead of B16F10-c1 cells, Z′-factor, S/B, and CV (%) were found to be 0.51, 3.65, and 8.42, respectively (Fig. 4D). This result suggests that this method does not necessarily require cells that are highly sensitive to melanization-stimulating agents but is compatible with generally available cells as well.

Fig. 4. Validation of the Digital Image-Based Method as a High-Throughput Screening Assay

(A) B16F10-c1 cells were seeded in a white-bottom 96-well microplate at 2.5 × 10³ cells per well and treated with 5 nM α-MSH for 3 d (left). Cells were fixed with paraformaldehyde, and a digital image of the entire microplate was acquired (right). (B and C) The total signal intensity of each well on the image was measured. After the subtraction of the background signal, data are shown as fold changes in melanization relative to that in untreated cells (B), and the mean ± S.E.M., Z′-factor, S/B, and CV (%) were calculated (C). (D) Melanization was quantified as shown in (A) and (B) using parental B16F10 cells. The mean ± S.E.M., Z′-factor, S/B, and CV (%) are shown.

CONCLUSION

In this study, we established a simple digital image-based method to quantify melanization. Compared with the widely used method of measuring the absorbance of cell lysates at UV-A wavelengths, our method appeared to have higher sensitivity and be less laborious because it eliminates the need for a cell lysis step and therefore was found to be suitable for a high-throughput screening assay. Recently, new methodologies have been developed, such as fluorescent probes that detect melanin¹⁹⁾ and tyrosinase,²⁰⁾ an enzyme critical for melanin production, and the detection of melanin content in melanocytes depending on their light-scattering properties,²¹⁾ all of which have potential to be applied to high-throughput screening. Nonetheless, our simple method is still valuable, particularly in conventional laboratories that do not have specialized equipment and may thus be suitable for academic drug discovery projects. We have already started to search for compounds that promote melanization using our original library, with the aim of the development of therapeutic agents for vitiligo vulgaris.

Funding

This work was supported in part by the Platform Project for Supporting Drug Discovery and Life Science Research (Basis for Supporting Innovative Drug Discovery and Life Science Research [BINDS]) from the Japan Agency for Medical Research and Development (AMED) (JP24ama121032), JSPS KAKENHI (Grant Numbers JP23KJ1762 to T. Baba, JP21K06069 to S. Tanimura, and JP23K06117 to K. Takeda), the ANRI Fellowship (to T. Baba), the Shionogi Infectious Disease Research Promotion Foundation (to S. Tanimura), and Startup support for research initiatives from the Japanese Society of Vitiligo (to H. Murota).

Conflict of Interest

The authors declare no conflict of interest.

Supplementary Materials

This article contains supplementary materials.

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