Histological validation of a predictive cosmetogenomics study ex vivo Peno-Mazzarino L.1, Patatian A.2, Bader Th.2, Percoco G.1, Gasser Philippe1, Scalvino S.1 Reby D.1, Durand C.1, Lati E.1 and Benech P.2, 3

1- Laboratoire BIO-EC, 1 chemin de Saulxier, 91160 Longjumeau, France 2- Genex, 1 chemin de Saulxier, 91160 Longjumeau, France 3- Aix Marseille Université, CNRS, NICN UMR 7259, 13916 Marseilles, France

Introduction The ex vivo human skin explants is a choice model system to objectivate the activity of cosmetic products. Close to in vivo conditions, it allows evaluating some final products by taking into count the penetration dimension. In addition, it allows the use of more invasive methods requiring biological samples (cells, tissues, supernatants). The genomic study which is a powerful tool that allows early to identify activated by cosmetic products, can be combined with the ex vivo studies. Thus, the laboratories BIO-EC and GENEX have developed a model system of cosmetogenomics using ex vivo human skin explants. In order to explore the capability of this association and to correlate the expression by histology to activation by transcriptomic analysis, we investigated the effects of a commercial cosmetic product.

The use of topically applied vitamins has become an ubiquitous part of skin care. While a part of the skin's antioxidant system that assists in protecting skin from oxidative damage, vitamins A, C, and E have also proven their ability to treat photoaging, acne, cutaneous inflammation, and hyperpigmentation [1]. Retinoic acid, a metabolite of vitamin A, is known to be a key signaling molecule in regulating epithelial cell differentiation. Topical natural retinoic acid precursors such as retinaldehyde or retinol are less irritant than acidic retinoids and may be combined with other compounds with complementary actions against ageing. According to its recognized activity and its well known action process, we have chosen a cosmetic product containing retinol. In this study, we investigated on human skin explants, derived from two donors, the effects of a commercial product containing retinol. For an extended period of more than a week, skin explants were treated with the product and samples were taken at different time points and compared to untreated controls. Genes of interest, identified by microarray analysis, were followed-up by immunochemistry on thin sections of explants as well as by RT-qPCR.

Materials and methods

Tested products A commercial product, a cosmetic anti-ageing product containing retinol (R) has been applied to ex vivo human skin explants cultured for 6 days.

Ex vivo human skin explants Human skin explants were obtained from two abdominoplasties from a 30 and a 49-year- old woman (plastic surgery). The hypodermis was removed from the skin and circular samples were prepared using a punch instrument. The diameter of each explant was ~10mm. The explants were maintained in survival in a liquid–air interface in BIOEC’s ® Explant Medium (BEM ) at 37°C in moist atmosphere containing 5% CO2 for 24h before the study began. Half of the medium (1 ml) was renewed every other day. Living skin explants were treated as shown in Table 1.

Batch Treatments Explants Nb Sampling times

D-1 none 3 D-1

U Untreated batch 21 D0/D0+3h/D0+9h/D1/D2/D3/D6

R Retinol 18 D0+3h/D0+9h/D1/D2/D3/D6

Table 1 Experimental conditions of living skin explants

Product applications A commercial cosmetic anti-ageing product was applied to ex vivo human skin explants cultured for more than one week. The retinol-containing product was applied topically every other day at 1 mg/cm².

Sampling Explants were collected at the following incubation times: 3 hours, 9 hours, 1 day, 2 days, 3 days and 6 days. The explants were then cut in three parts. One part was fixed in buffered formol solution, the second one frozen at -80° C and the third used for RNA extraction and analysis.

Gene Expression Profile Total RNAs were extracted at each sampling time for each explant using the RNeasy Fibrous Tissue Kit-Qiagen after disruption and homogenization using the TissueLyser Kit. To evaluate the effects of a treatment, we focused our first investigation on the samples coming from a 49 years old donor. After 3h, 9h, 24h (D1), 48(D2), 72 (D3) of treatment, five hundred nanograms of RNA of each sample were processed further for retrotranscription, amplification and cyanine labeling, using the Illumina Whole Microarray (HT12 v 4.0) which presents more than 47.000 probes, derived from the National Center for Biotechnology Information Reference Sequence (NCBI) RefSeq. In a second step with donor #2 the more prominent time point(D2) was validated by microarray starting from sixty nanograms of RNA and using the low input Quick Amp one- color labeling kit (Agilent technologies) which contains 60.000 probes. Subsequently, the expression of key genes the modulation of which showed an impact of the treatment at crucial points of different signaling pathways involved in skin biology was evaluated by RT-qPCR at D2; D3 and D6 of the kinetics. After qualitative validation and normalization of the microarray data, intensities of the treated samples were compared with untreated samples. Only those genes that were modulated at least in 2 consecutive time points with a fold-change (FC) of at least ≥1.45 and ≤0.5 were considered for evaluation by PredictSearch™ analysis. PredictSearch™ is a proprietary data and text mining software that searches and retrieves correlations between genes and biological processes or diseases through millions of scientific publications [2-3]. The functional correlation based on the Fisher test allows statistical co-citation analysis of annotated keywords in order to define relationships between genes, biological processes and concepts, metabolites, diseases, and tissue/cells/organs with a direction of effect rather than mere associations.

Histological process After 24 hours of fixation in formol solution, the samples were dehydrated and paraffin impregnated with a Leica 1020 dehydrator automat. After preparation, explants were embedded at a Leica EG 1160 coating station and 5 μm sections were cut with a Minot-type microtome, (Leica 2125) and mounted on superfrosted silanized glass histology slides. Microscopical observations were performed by optical microscopy with a 40x objective. Photo-micrographs were performed with a DP72 Olympus camera and archived with Olympus CellD data storing software.

Staining and immunostaining The observations of general morphology were carried out on formalin fixed paraffin embedded skin sections stained according to Masson’s trichrome Goldner variant, using a ST 4040 Leica staining automat. Cellular or tissular modifications were noted in the stratum corneum, living epidermis, papillary and reticular dermis. The general morphology resulted in observational and descriptive data and without statistical analysis.

Formalin-fixed paraffin embedded skin sections were subjected to immunostaining according to the following process: deparaffinizing and rehydration (Clearen, alcohol), quenching of endogenous peroxidase with 1% H2O2 in phosphate-buffered saline (PBS) for 10 min; washing 3 times in PBS; blocking with normal horse serum (Vector Laboratories) for 30 min at RT; incubation for 1 hour at RT with the primary antibody (list below), washing 3 times in 0.05% Tween-20 in PBS; incubation for 30 min at RT with R.T.U. Biotinylated Universal Antibody (Vectastain Universal Elite ABC Kit, Vector Laboratories); washing 3 times in 0.05% Tween 20 in PBS; incubation for 30 min at RT with R.T.U. Elite ABC Reagent (Vectastain Universal Elite ABC Kit, Vector Laboratories); washing 3 times in 0.05% Tween-20 in PBS, and revelation with VIP substrate (Vector Laboratories) for a period specific for each primary antibody. Negative controls were performed by replacing the primary antibody with PBS. Primary antibodies: anti-Ki67 (7B11 mouse monoclonal, Zymed), anti-involucrine (SY5 mouse monoclonal, Novus Biologicals), anti-FABP5 (rabbit polyclonal, Santa Cruz Biotechnology), anti-filaggrin (AKH1 mouse monoclonal, Santa Cruz Biotechnology), and anti-CRABP2 (rabbit polyclonal, Sigma-Aldrich).

Results & Discussion The number of modulated gene was evaluated for at least 2 consecutive time points (FC≥1.45 or FC≤0.5). Based on these criteria, 18 genes were significantly up-regulated at 3 and 9 hours; 14 genes at 9-24h; 51 genes at 24-48h and 75 genes at 48-72h. Similarly, 35 genes were repressed at 3-9h; 12 genes at 9-24h; 13 genes at 24-48h, and 92 genes at 48-72h. The number of modulated genes increased after 48 and 72h of treatment. Thus, our next transcriptomic approach was centered on the validation of the results after 48h treatment of skin explants from the second donor. As expected, the expression of a set of genes (DHRS3, DHRS9, CRABP2, FABP5 and CYP26B1) involved in retinol metabolism was induced in both donors (Table 2a). Among all modulated sequences, genes, which were induced at early times of treatment (3h and 9h), were associated with cell proliferation. In contrast, genes, which were induced at 24-48-72h were associated with differentiation (Table 2b).

a)

b)

Table 2: a) Expression of genes involved in retinol metabolism. Fold-changes at 3h, 9h, 24h, 48h, 72h were calculated for donor 1. Only the 48h treatment was performed for donor 2 (indicated by an asterisk). b) Expression of genes involved in differentiation.

It is important to underline that similar results were obtained with both donors although RNAs were processed differently and microarrays were performed on distinct platforms. (Illumina for donor 1 and Agilent for donor 2). Using PredictSearch™, we were able to insert these genes within biological networks highlighting the role of retinol in the induction of transcriptional activities that lead to dual functions (Figure 1). Indeed, the metabolism of retinol is regulated by groups of enzymes that control conversion of retinol into active retinoid aldehyde and retinoic acid. The enzymes involved in the first step of retinol metabolism belong to the alcohol dehydrogenases encoded by DHRS3 (dehydrogenase/reductase (SDR family) member 3) and DHRS9 (dehydrogenase/reductase (SDR family) member 9) and catalyze the oxidation of retinol into retinaldehyde. The next step in retinol metabolism consists of the conversion of retinaldehyde into retinoic acid through aldehyde dehydrogenase encoded by ALDH3A1 (aldehyde dehydrogenase 3 family, member A1) [4]. Retinoid metabolism and retinoid concentrations in skin are tightly regulated ensuring sufficient levels of the endogenous RAR activator all-trans retinoic acid (RA). Retinoids mediate their effects through the retinoic acid and retinoid X nuclear receptors (RAR and RXR, respectively), which form RAR-RXR heterodimers, RXR homodimers, and heterodimers of RXR and certain orphan receptors. These receptor dimers bind to distinct response elements, thus activating separate pathways [5]. RA can activate both receptors depending on specific transport : Fabp5 initiates PPAR signaling whereas Crabp2 promotes RAR signaling. Both signaling pathways induce expression of distinct genes as shown in Figure 1. Among RA-RAR signaling target genes, the expression of LCN2 (lipocalin 2), ALDH3A1 (aldehyde dehydrogenase 3 family, member A1), CYP26B1 (cytochrome P450, family 26, subfamily B, polypeptide 1) and CRABP2 (cellular retinoic acid binding protein 2) were induced in our study [6]. LCN2 induction is correlated to regulation of growth arrest and is sufficient to promote cell migration and wound healing [7]. RA levels in tissue are stringently regulated through a balance of uptake assured by induction of CYP26B1. Similarly, expression of several genes such as KRT6 (keratin 6), KRT16 (Keratin16), HBEGF (heparin-binding EGF-like growth factor), FABP5 (fatty acid binding protein 5), and IVL (involucrin) is positively regulated by the RA-PPAR signaling pathway. Elevated mRNA levels at early time points of KRT6, KRT16 and HBEGF induction correlated with keratinocyte proliferation. Epidermal fatty acid-binding protein (FABP5) was exclusively expressed in post-mitotic (PM) keratinocytes, corresponding to their localization in the highest suprabasal layers, while it was barely expressed in keratinocyte stem cells (KSC) and transit amplifying (TA) keratinocytes [8]. The crucial role of FABP5 in keratinocyte differentiation is demonstrated by several studies [8-9]. Indeed, inactivation of FABP5 by siRNA in keratinocytes down- regulates K10 and IVL (involucrin) expression and reduces cell differentiation. As for IVL, many other genes such as S100A7 and S100A9 are located on region 1q21, known as the epidermal differentiation complex [10]. Additionally, CASP14 (Caspase 14) activation is associated with terminal differentiation of human keratinocytes and stratum corneum formation [11]. Human CASP14 is a protease that is mainly expressed in suprabasal epidermal layers and activated during keratinocyte cornification [12]. CASP14 plays a crucial role in filaggrin catabolism that is required for filaggrin (repressed at 48 and 72h) degradation to natural moisturizing factors in the skin. Retinoic acid dose-dependently suppressed caspase-14 mRNA and protein expression thus inhibiting terminal differentiation of keratinocytes [13]. The keratinocyte differentiation process is also regulated by strong induction of ID1 (inhibitor of differentiation 1), another target gene of the retinoic acid signaling pathway [14]. The ID helix-loop-helix proteins (inhibitor of differentiation or DNA binding) are important mediators of and proliferation in a variety of cell types through regulation of gene expression. Overexpression of these ID proteins in normal human keratinocytes results in extension of culture lifespan, indicating that these proteins are important for epidermal differentiation [15]. Thus, the critical role of retinol metabolites in the regulation of growth and differentiation processes of adult skin was confirmed. This duality of function illustrates not only the importance of feedback loops but also the complex interplay of signaling pathways. It is then not surprising that the common features observed among the different cells in skin explants also conserve communication between cells. Therefore, the retinol treatment of skin explants in our study demonstrates the importance of an adequate experimental design, including the kinetics time points for RNA analysis and protein evaluation by immunostaining. RNA quantification remains a useful tool in determining how the transcriptional cell machinery is affected in the presence of external signals such as cosmetic products or environmental stimuli, or the mechanisms of skin development and the molecular interactions.

Figure 1: Retinol signaling pathway. Induced genes are noted in blue. Asterisk indicates genes whose expression was similarly induced after 48h of treatment on the explants generated from the second donor.

Histological correlation: gene expression and protein evaluation Following microarray experiments, validation of the gene expression was performed by RT-qPCR (data not shown) and by immunostaining to detect presence of FABP5, CRABP2, involucrin (IVL) and filaggrin (FLG) at D3 and D6. As shown in figure 2, the explants exhibit a morphology, which illustrates the viability of the different cell populations and the integrity of the cutaneous compartments. However, an increase of the epidermal thickness supported by a higher number of cellular layers (figure 2c and 2d versus 2a and 2b) upon retinol treatment was detected. This observation is in line with the proliferative effect of retinol.

a c

b d

50 µm Figure 2: Epidermal morphology of untreated (a: day 3 and b: day 6) or retinol treated skin explants (c: day 3 and d: day 6).

In order to compare immunostaining in untreated and treated conditions, we defined a scoring based on visual differences (table 4), which allows to appreciate the modulation of protein expression (PE). The differential expression (PE) seen in immunostaining of CRABP2 and filaggrin confirms the modulation of the corresponding genes seen after 72h (D3) of treatment (see the histograms in figure 3). However, FABP5 and involucrin were detected only at D6 while expression of the related genes was seen at D3. This delay might depend on the time required to translate significant amount of FABP5 and IVL RNAs into proteins.

W M QC C VC S

Δ PE 0.5 1 1.5 2 2.5 3

Table 4 Variation of protein expression (PE) in treated versus untreated explants obtained by microscopical examination ranked from weak (W), moderate (M), quite clear (QC), clear (C), very clear (VC) to strong (S).

Figure 3: Detection of CRABP2, FABP5, involucrin and filaggrin by immunostaining. Histograms were deduced from the scoring of the PE at D3 and D6. FC corresponds to the fold change determined in microarrays using RNAs extracted from explants of donor 1 at D3 in untreated and treated conditions. Image immunostaining (see materials and methods) from untreated explants (U) or retinol treated explants (R) at D3 and D6 are shown.

Conclusion Our results illustrate the importance of the experimental design including the different kinetic time points that allow to obtain much more confident data as they show a significant progressive modulation of genes over time. Moreover, a significant correlation was observed between gene expression levels (at 3h-9h-24h-D2-D3) and their translated proteins at D3 and D6 in response to retinol treatment of the skin explants. Expression of retinol target genes is strongly induced. Most of these genes are involved in retinol metabolism and some of them contribute to retinoic acid synthesis. Among the target genes, overexpression of KRT6, KRT16, and HBEGF is associated with cell proliferation, while overexpression of IVL, S100A7 and FABP5 is related to cell differentiation. The coexistence of both proliferation and differentiation triggered by retinol metabolism or in response to retinoic acid synthesis is well documented. Altogether our results demonstrate a good correlation between modulation of gene expression and presence of the corresponding proteins in skin explant models. Thus, these combined approaches offer a complete evaluation of activities and mechanisms of actions triggered by cosmetic care products.

References

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