Biological Activity of an Essential Oil Blend in Human Dermal Fibroblasts


Tyler Bahr*

Received Date: 00--0000 Accepted Date: 00--0000 Published Date: 00--0000

Citation: Biological Activity of an Essential Oil Blend in Human Dermal Fibroblasts. American Research Journal of Dermatology. 2017; 1(1): 1-22.

Copyright This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Abstract:

Research on thebiological activities of essential oilsin human skin cells is limited. This studyfirst analyzedthe effect of an essential oil blend (EOB) on 17 important protein biomarkers in cytokine-stimulated human dermal fibroblasts. The EOB was composed of essential oils of frankincense resin, sweet orange peel, litsea fruit, thyme plant, clove bud, summer savory plant, and niaouli leaf. The results showed that EOBhad excellentantiproliferativeactivity. It significantlyincreased vascular cell adhesion molecule 1 levels and slightly increased themonocyte chemoattractant protein 1 and epidermal growth factor receptor production. We then studied theeffect of the EOB on the expression levels of 21,224 genes in the same cells. We found that the EOBmarkedly affected genome-wide gene expression. Further analysis revealed that the EOBpleiotropically regulated multiple signaling pathways in human cells including hepatic fibrosis activation, antigen presentation, mitotic roles of the polo-like kinase, and cyclin and cell cycle regulation. Many pathways significantly affected by the EOB are closely related toinflammatory and immune responses. The results suggest thatthe EOBmayaffectbiological processes and global gene expression in human skin cells. Further research into the underlying mechanism of action of the EOB is needed.

Keywords: Essential oil; frankincense; sweet orange;litsea; thyme;inflammation; immune response; signaling pathway; tumor; genome-wide gene expression


Description:

INTRODUCTION

Essential oils are complex mixtures of aromatic compounds naturally produced in plants. Theyhave been used historically as well as currently for treating a variety of diseases and maintaining health in humans(Lv et al., 2013; Perry & Perry, 2006). Recent pre-clinical and clinical studies have provided evidence supporting the benefits of essential oils to human health (Kozioł et al., 2014; Navarra et al., 2015), resulting in a wider acceptance and use of essential oils in the US and worldwide. Despite this trend, very few studies have elucidated the mechanisms of action of essential oils inhuman cells.

Thousands of distinct terpene compounds have been identified in essential oils, many of which are known for possessing diverse biological activities. Because every essential oil is primarily composed of a unique mixture of just a few of these compounds, it is hypothesized that each oilhas its own unique array of biological activities. For example, Oregano essential oil is known to have powerful anti-fungal and anti-microbial effects due to its high phenylpropene content, while Lavender’s main constituents, linalool and linalyl acetate, are known to calm the CNS by activating GABAA receptors.

The tendency for essential oil compounds to exhibit synergy and antagonism is another phenomenon that is receiving growing attention. A recent study on membrane dynamics suggested that the ratios of constituents might affect an oil’s activity just as much as the identity of the constituents (Hac-Wydro et al., 2017). The possibility of synergy and antagonism has sparked an interest in blending, or creating mixtures of essential oils, to achieve an oil combination with novel effects. Therefore, we studiedthe biological effect of an industrial essential oil blend (EOB)on a human skin disease model, the HDF3CGF pre-inflamed dermal fibroblast system, which we have used previously to study the effects of individual essential oils. The current findings will allow comparison of this blend’s activitywith that of the individual essential oils and possibly other blends, aiding in future research on synergy, antagonism, and additive effects of essential oil blends.

The EOBcontains a mixture of essential oils from frankincense (Boswellia carterii, Boswellia frereana, and Boswelliasacra) resin, sweet orange (Citrus sinensis) peel, listea (Litsea cubeba) fruit, thyme (Thymus vulgaris) plant, clove (Eugenia caryophyllata) bud, the summer savory (Satureja hortensis) plant, and niaouli (Melaleuca quinquinervia) leaf.Although many of these individual essential oils and their active constituents are known to have various therapeutic benefits, this was the first study to examine the effect of a commercial blend of these oilson human genome-wide gene expression in the HDF3CGF model system. We also studiedthe EOB’s effect on biomarkers related to inflammation, immune responses, and tissue remodeling.

MATERIALS AND METHODS

All experiments were conducted using a biologically multiplexed activity profiling (Bio MAP) system HDF3CGF designed to model the pathology of chronic inflammation robustly and reproducibly. The system comprised three components: a cell type, stimuli to create the disease environment, and a set of biomarker (protein) readouts to examine the treatment effects on the disease environment (Berg et al., 2010). The methodologies used in this study were essentially the same as those previously described (Han & Parker, 2017a, 2017b; Kunkel et al., 2004)”container-title”:”Cogent Medicine”,”page”:”1306200”,”volume”:”4”,”issue”:”1”,”source”:”Taylor and Francis+NEJM”,”abstract”:”Although juniper (Juniperus communis. 
Reagents

The EOB (dōTERRA, Pleasant Grove, UT, USA) was diluted in dimethyl sulfoxide (DMSO) to 8× the specified concentrations (final DMSO concentration was no more than 0.1%). Then, 25 μL of each 8× solution was added to the cell culture to a final volume of 200 μL whileDMSO (0.1%) served as the vehicle control.

The composition of the EOBwas as follows: frankincense (a mixture of B. carterii, B. frereana, and B. sacra) resin oil, sweet orange (C. sinensis) peel oil, lemongrass (Cymbopogon flexuosus) leaf oil, thyme (T. vulgaris) plant oil, clove (E. caryophyllata) bud oil, summer savory (S. hortensis) plant oil, and niaouli (M. quinquinervia) leaf oil. The exact percentage composition is proprietary to the supplying company. Aromatic compounds distilled from the plant material comprised 100% of the EOB. Each essential oil originated from a country where the plant is grown. The essential oils were shipped to the US, where they were blended into the EOB. Gas chromatography-mass spectrometry analysis of the EOB showed that it contained 23–27% limonene, 11–14% alpha-pinene, 6–8% eugenol, 6–8% thymol, 5–7% carvacrol, 5–7% eucalyptol, 4–6% gamma-terpinene, and smaller amounts of other aromatic compounds.

Cell Cultures

Primary human neonatal fibroblasts were prepared as previously described (Bergamini et al., 2012) and were plated under low-serum conditions (0.125% fetal bovine serum) for 24 h. Then, the cell culture was stimulated with a mixture of interleukin (IL)-1β, tumor necrosis factor (TNF)-α, interferon (IFN)-ϒ, basic fibroblast growth factor (bFGF), epidermal growth factor (EGF), and platelet-derived growth factor (PDGF) for another 24 h. The cell culture for the HDF3CGF assays was performed in a 96-well plate,and the stimulation conditions were described in detail elsewhere (Bergamini et al., 2012; R Development Core Team, 2011).

Protein-Based Readouts

An enzyme-linked immunosorbent assay (ELISA) was used to measure the biomarker levels of cell-associated and cell membrane targets. Soluble factors in the supernatants were quantified using either homogeneous time-resolved fluorescence detection, bead-based multiplex immunoassay, or capture ELISA. The adverse effects of the test agents on cell proliferation and viability (cytotoxicity) were measured using the sulforhodamine B (SRB) assay. For proliferation assays, the cells were cultured and measured after 72 h, which is optimal for the HDF3CGF system, and the detailed procedure was described in a previous study (Bergamini et al., 2012). The measurements were performed in triplicate wells, and a glossary of the biomarkers used in this study is provided in Supplementary Table S1.



The quantitative biomarker data are presented as the mean log10 relative expression level (compared to their respective mean vehicle control value) ± standard deviation (SD) of triplicate measurements. Differences in biomarker levels between the EOB- and vehicle-treated cultures were tested for significance using the unpaired Student’s t-test. A p-value < 0.05, outside of the significance envelope, with an effect size of at least 10% (> 0.05 log10 ratio units), was considered statistically significant.
RNA Isolation
Total RNA was isolated from cell lysates using the ZymoQuick-RNAMiniPrep kit (Zymo Research Corp., Irvine, CA, USA) according to the manufacturer’s instructions. RNA concentration was determined using a NanoDrop ND-2000 system (Thermo Fisher Scientific, Waltham, MA, USA). The RNA quality was assessed using a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA) and an Agilent RNA 6000 Nano kit. All samples had an A260/A280 ratio between 1.9 and 2.1 and an RNA integrity number score greater than8.0.
Microarray Analysis of Genome-Wide Gene Expression
The effect of the EOB at a concentration of 0.0033% (v/v) was tested on the expression of 21,224 genes in the HDF3CGF system following a 24-h treatment. Samples for microarray analysis were processed by Asuragen, Inc. (Austin, TX, USA) according to the company’s standard operating procedures. Biotin-labeled cRNAwas prepared from 200 ng total RNA using an Illumina TotalPrep RNA amplification kit (Thermo Fisher Scientific, Waltham, MA, USA) and one round of amplification. The cRNA yields were quantified using ultraviolet spectrophotometry, and the distribution of the transcript sizes was assessed using the Agilent Bioanalyzer 2100. Labeled cRNA (750 ng) was used to probe Illumina human HT-12 v4 expression bead chips (Illumina, Inc., San Diego, CA, USA). Hybridization, washing, staining with streptavidin-conjugated cyanine-3, and scanning of the Illumina arrays were carried out according to the manufacturer’s instructions. The Illumina BeadScan software was used to produce the data files for each array, and the raw data were extracted using the Illumina BeadStudio software.
The raw data were uploaded into R (R Development Core Team, 2011), and the quality-control metrics was analyzed using the beadarray package (Dunning et al., 2007). The data were normalized using quantile normalization (Bolstad et al., 2003), and then re-annotated and filtered to remove probes that were nonspecific or mapped to intronic or intragenic regions (Barbosa-Morais et al., 2010)little external scrutiny has been given to the design, selection and annotation of BeadArray probes, which is a fundamental issue in data quality and interpretation. Here we present a pipeline for the complete genomic and transcriptomic re-annotation of Illumina probe sequences, also applicable to other platforms, with its output available through a Web interface and incorporated into Bioconductor packages. We have identified several problems with the design of individual probes and we show the benefits of probe re-annotation on the analysis of BeadArray gene expression data sets. We discuss the importance of aspects such as probe coverage of individual transcripts, alternative messenger RNA splicing, single-nucleotide polymorphisms, repeat sequences, RNA degradation biases and probes targeting genomic regions with no known transcription. We conclude that many of the Illumina probes have unreliable original annotation and that our re-annotation allows analyses to focus on the good quality probes, which form the majority, and also to expand the scope of biological information that can be extracted.”,”DOI”:”10.1093/nar/ gkp942”,”ISSN”:”1362-4962”,”note”:”PMID: 19923232 PMCID: PMC2817484”,”shortTitle”:”A re-annotation pipeline for Illumina BeadArrays”,”journalAbbreviation”:”Nucleic Acids Res.”,”language”:”eng”,”author”:[{“fam ily”:”Barbosa-Morais”,”given”:”Nuno L.”},{“family”:”Dunning”,”given”:”Mark J.”},{“family”:”Samarajiwa”,”given” :”Shamith A.”},{“family”:”Darot”,”given”:”Jeremy F. J.”},{“family”:”Ritchie”,”given”:”Matthew E.”},{“family”:”Lync h”,”given”:”Andy G.”},{“family”:”Tavaré”,”given”:”Simon”}],”issued”:{“date-parts”:[[“2010”,1]]}}}],”schema”:”htt ps://github.com/citation-style-language/schema/raw/master/csl-citation.json”} . The remaining probe sets comprised the data set for thesubsequent analysis. The fold-change expression for each set was calculated as the log2 ratio of EOB to the vehicle control. These fold-change values were uploadedintothe Ingenuity Pathway Analysis (IPA) program (Qiagen, Redwood City, CA, USA, www.qiagen.com/ingenuity) to generate the networks and pathway analyses.
Results and Discussion
Bioactivity Profile of EOB in HDF3CGF System
The HDF3CGF system was designed to model the pathology of chronic inflammation and wound healing in the context of Th1-type inflammation. Four different concentrations (0.01, 0.0033, 0.0011, and 0.0037% v/v) of the EOB were initially tested for cytotoxic activity in the dermal fibroblasts. A concentration of 0.01% was overtly cytotoxic and, therefore, the 0.0033% concentration was usedin the further analysis. Biomarkers were designated if the EOB values were significantly different (p < 0.05) from vehicle controls, outside the significance envelope, with an effect size of at least 10% (> 0.05 log ratio units, Figure 1).
Studies by other research groups have shown the anti-inflammatory and immune modulating properties of the major chemical constituents of the EOB, specifically limonene and α-pinene. Topically-applied limonene, the main constituent of orange oil, reduced edema in mouse skin and pretreatment with limonene reduced inflammatory markers (Chaudhary et al., 2012). In RAW 264.7 macrophages, limonene reduced several immune markers including TNF-α (Yoon et al., 2010).Limonene’s anti-inflammatory effects in rat kidney tissue were found to be associated with decreased expression of nuclear factor(NF)-κB (Rehman et al., 2014). Mouse studies demonstrated the anti-inflammatory activities of frankincense oil and α-pinene, andthe effect was likely mediated by reducingnuclear factor NF-κB nuclear translocation (Zhou et al., 2004). The immunomodulatory effect of α-pinene was attributed to the suppression of mitogen-activated protein kinases (MAPKs) and the NF-κB pathway in mouse peritoneal macrophages, which showed decreased expression of TNF-α, NF-κB, and interleukins (Kim et al., 2015).
The individual essential oils in the EOB that we have studied previously include Frankincense, Lemongrass, and Clove(Han & Parker, 2017c, 2017d, 2017e). It was interesting to observe that certain biomarker effects from the individual essential oils were conserved in the blend, while others were lost. For instance, we previously found that all three of these oils significantly inhibit cell proliferation, so it was no surprise that the blend also inhibited cell proliferation.In our previous studies we found that EGFR was significantly downregulated only by Lemongrass essential oil. EGFR downregulation remained significant in the blend despite Lemongrass comprising only a small fraction of the blend. Also noteworthy was the MCP-1 downregulation by the blend, which was not observed after treatment with any of the three individual essential oils previously studied.

This difference could be attributed to one of the other oils in the blend or perhaps the unique combination of oils. Finally, the blend had virtually no effect on collagen levels, which were significantly downregulated by Frankincense, Clove, and Lemongrass. These observations support the hypothesis that the EOB has unique biological activity that may perhaps be more than a simple sum of effects from the individual essential oils included in the blend. One obvious limitation to comparing the blend with these oils, however, is our lack of biomarker data on Niaouli, Summer Savory, Thyme, and Orange. Future research will make it possible to conduct a more comprehensive comparison of the effects of the EOB compared to its individualcomponent oils.

Fig1. The bioactivity profile of an essential oil blend (EOB, 0.0033% v/v) in a human dermal fibroblast system HDF3CGF. Y-axis denotes the relative expression levels of biomarkers compared to vehicle control values, in log10 form. Error bars represents the standard deviations (SD) of triplicate measurements. Vehicle control values are shaded in gray, denoting the 95% significance envelope. A * indicates a biomarker designated with “key activity,” i.e., biomarker values were significantly different (p < 0.05) from vehicle controls, outside of the significance envelope, with an effect size of at least 10% (more than 0.05 log ratio units). MCP-1, monocyte chemoattractant protein; VCAM-1, vascular cell adhesion molecule 1; ICAM-1, intracellular cell adhesion molecule 1; IP-10, interferon gamma-induced protein 10; I-TAC, interferon-inducible T-cell alpha chemoattractant; IL-8, interleukin-8; MIG, monokine-induced by interferon-γ; EGFR, epidermal growth factor receptor; M-CSF, macrophage colony-stimulating factor; MMP-1, matrix metalloproteinase 1; PAI-1, plasminogen activator inhibitor 1; TIMP, tissue inhibitor of metalloproteinase

Effect of EOBon Genome-Wide Gene Expression
To further explore the effect of 0.0033% (v/v) EOB on human skin cells, we analyzed its effect on the RNA expression of 21, 224 genes. The EOB significantly regulated the expression levels of hundreds of genes globally. The vast majority of the 200mostregulated genes (178) were downregulated by the EOB while the rest were upregulated (Table S2 and see Supplementary Material for more information).