EXTRACTION and IDENTIFICATION of VOLATILE CONSTITUENTS of <I>

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5-2012 EXTRACTION AND IDENTIFICATION OF VOLATILE CONSTITUENTS OF OPLOPANAX HORRIDUS Gregory Jones Clemson University, [email protected]

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EXTRACTION AND IDENTIFICATION OF VOLATILE CONSTITUENTS OF OPLOPANAX HORRIDUS

A Thesis Presented to the Graduate School of Clemson University

In Partial Fulfillment of the Requirements for the Degree Master of Science Food, Nutrition, and Culinary Science

by Gregory Steven Jones May 2012

Accepted by: Dr. Feng Chen, Committee Chair Dr. Paul Dawson Dr. Terry Walker

ABSTRACT

O. horridus is an important medicinal and spiritual plant for native peoples where it natively grows. Secondary volatile metabolites which compose the essential oil were isolated by atmospheric simultaneous distillation-solvent extraction (SDE) and headspace solid phase microextraction (HS-SPME) from the bark and leaves of Oplopanax horridus. The differences between the two extraction methods was investigated for their sensitivity, precision and use in separating volatile compounds from sample matricies.

The extracts were analyzed by capillary gas chromatography with mass spectrometric detection. Compounds were identified according to their non-isothermal

Kovats indexes, mass spectra, or by comparison with analytical standard substances. The bark essential oil was a pale yellow oil that had a higher average yield (w/w) of

0.96±0.06% whereas the leaf extract had a lower essential oil yield of 0.15±0.04% and had a darker brown color. The bark and leaf essential oil extracts were rich (>65% composition) in sesquiterpenes. (E)-nerolidol, τ-cadinol, β-farnesene found in the bark oil and (E)-nerolidol, ar-curcumene, and β-sesquiphylledrene in the leaf oil were important compositional compounds in the essential oils contributing more than 5% of the oils.

The coupling of headspace solid-phase microextraction (HS-SPME) under optimized extraction parameters with a highly sensitive gas chromatography mass spectrometry (GC-MS) system allows for rapid sampling and analysis of volatile and semivolatile compounds in complex herbal tissues. Volatile metabolites from the bark and leaves of Oplopanax horridus were absorbed by the polydimethylsiloxane (PDMS) stationary phase via SPME and analyzed by capillary gas chromatography with mass

ii spectrometric detection. The use of HS-SPME extraction and injection of the volatiles of the bark and leaf yielded 48 spectrally unique compounds in the bark and 39 in the leaves. The identified compounds from the bark that had the highest percent concentration were (E)-nerolidol (25.371%), τ-cadinol (15.049%), and spathulenol

(8.384%) which comprise 48.804% of the total amount of the bark volatile mixture; similarly, principle compounds of the SPME leaf extract were (E)-nerolidol (37.469%),

τ-cadinol (9.315%), ar-turmerol (5.033%), (E)-γ-bisabolene (5.439%), and β-bisabolene

(2.730%) which accounted for 59.986% of the volatile mixture.

iii DEDICATION

I wish to dedicate this work to my parents Kenneth and Deborah Jones, my siblings Jennifer and Kyle Jones, my grandparents William and Marilyn Jones and

Alexander and Stella Boris. This thesis would not have been possible without their love, encouragement, and appreciation for higher education.

iv ACKNOWLEDGMENTS

I would like to express my deepest appreciate and gratitude to my supervisor, Dr.

Feng Chen for his continuous guidance and assistance throughout the entirety of my postgraduate study and enabling me to further my education in flavor chemistry and food science.

I would also like to thank my committee members Dr. Paul Dawson and Dr. Terry

Walker for their helpful assistance and effort. I would like to thank Dr. Julia Sharp for assisting me in the initial statistical coding of my datasets.

Finally, I wish to thank my family for their endless support, love, encouragement, and help throughout my education and for actively taking part in guiding me to become the person that I am today.

v TABLE OF CONTENTS

Page

TITLE PAGE ...... i

ABSTRACT ...... ii

DEDICATION ...... iv

ACKNOWLEDGMENTS ...... v

LIST OF TABLES ...... ix

LIST OF FIGURES ...... x

CHAPTER

I. LITERATURE REVIEW ...... 1

1.1 History of Oplopanax horridus ...... 1 1.2 Oplopanax horridus traditional uses ...... 2 1.2.1 Physical Medicinal Preparations ...... 2 1.2.2 Spiritual Use...... 5 1.3 Separation and Identification O. horridus Extracts ...... 5 1.3.1 Separation ...... 5 1.3.2 Identification ...... 7 1.4 Phytochemical and Biological Activity ...... 9 1.5 Relating Research to Traditional Use of O. horridus ...... 15 1.6 Volatile Extraction Methods ...... 16 1.6.1 Simultaneous Steam Distillation Extraction (SDE) ...... 16 1.6.2 Headspace Solid Phase Microextraction (HS-SPME) ...... 20 1.7 Gas Chromatography ...... 29 1.8 Medicinal Plants and Phytomedicine ...... 33 1.9 Essential Oils ...... 37 1.10 Essential Oil Modes of Action ...... 42 1.11 Secondary Metabolite Synergy ...... 46 References ...... 50

vi Table of Contents (Continued)

II. ATMOSPHERIC SIMULTANEOUS DISTILLATION SOLVENT EXTRACTION OF VOLATILE COMPOUNDS IN OPLOPANAX HORRIDUS LEAF AND BARK ...... 66

Abstract ...... 66 2.1 Introduction ...... 66 2.2 Materials and Methods ...... 70 2.2.1 Chemicals ...... 70 2.2.2 Plant Material ...... 70 2.2.3 Sample Preparation ...... 70 2.2.4 Isolation of the Volatile Oils ...... 70 2.2.5 Gas Chromatography Mass Spectrometry Analysis ...... 72 2.2.6 Identification and Quantification of volatile components ...... 72 2.2.7 Statistical Analysis ...... 74 2.3 Results and Discussion ...... 74 2.4 Conclusions ...... 86 2.5 Figures and Tables ...... 87 2.6 References ...... 94

III. HEADSPACE SOLID PHASE MICROEXTRACTION OF VOLATILE COMPOUNDS IN OPLOPANAX HORRIDUS STEM BARK AND LEAVES ...... 101

Abstract ...... 101 3.1 Introduction ...... 102 3.2 Materials and Methods ...... 103 3.2.1 Equipment ...... 103 3.2.2 Sample Preparation ...... 104 3.2.3 Headspace Solid Phase Microextraction (HS-SPME) ...... 104 3.2.4 Statistical Analysis ...... 108 3.3 Results and Discussion ...... 108 3.3.1 Method Optimization ...... 108 3.3.1.1 Sample Extraction Temperature ...... 109 3.3.1.2 Equilibration Time ...... 112 3.3.1.3 Absorption Time ...... 112 3.3.1.4 Desorption Time ...... 114 3.3.2 Concentration Standard Curves ...... 116

vii Table of Contents (Continued)

3.3.3 HS-SPME Extraction ...... 119 3.3.4 Class Distribution of Volatiles ...... 120 3.3.5 Statistical Analysis of Essential Oil Differences in HS-SPME ...... 121 3.3.5.1 Relationship between concentration in plant tissues ...... 121 3.3.5.2 Relationship Between Percent Composition in plant tissues ...... 122 3.3.6 Comparison of Percent Composition in Different Extraction Methods ...... 123 3.3.6.1 Comparison of extracted percent Composition between HS-SPME and Hydrodistillation ...... 123 3.3.6.2 Comparison of extracted percent Composition between HS-SPME and Simultaneous Distillation and Extraction ...... 126 3.3.7 Essential Oil Components ...... 129 3.3.8 Bioactivitiy of Volatile Compounds Identified in O. horridus ...... 130 3.4 Conclusions ...... 132 3.5 Figures and Tables ...... 134 3.6 References ...... 154

IV. GENERAL CONCLUSIONS ...... 161

REFERENCES ...... 164

viii LIST OF TABLES

Table Page

2.1 Operating Parameters of the GC-MS ...... 87

2.2 Volatile Composition of Oplopanax horridus Simultaneous Distillation Extraction Essential Oil...... 88

2.3 Electron Ionization Quadrupole Mass Spectra of Principle Ions for Unknown Compounds in Oplopanax horridus extracted using SPME…………………………...90

2.4 Paired T-test Statistical analysis of Oplopanax horridus percent composition of bark and leaf essential oils extracted using Simultaneous Distillation and Extraction ...... 91

3.1 Operating Parameters of the GC-MS ...... 134

3.2 SPME Absorption Isotherms Modeling effect of Sample Temperature on MS Response ...... 135

3.3 SPME Absorption Isotherms for Sample Absorption Time at 60°C on MS Response ...... 136

3.4 Volatile Compounds of Oplopanax horridus HS-SPME extract ...... 137

3.5 Electron Ionization Quadrupole Mass Spectra of Principle Ions for Unknown Compounds in Oplopanax horridus extracted using SPME ...... 140

3.6 Paired T-test Statistical Analysis of Bark and Leaf Percent Composition of Oplopanax horridus extracted using SPME ...... 142

3.7 Percent Composition of HS-SPME and SDE Volatile Extracts...... 143

3.8 Paired T-Test Statistical Analysis of the Bark and Leaf Composition of Oplopanax horridus comparing SPME and SDE extraction methods ...... 148

ix LIST OF FIGURES

Figure Page

2.1 GC-MS Total Ion Chromatogram of SDE essential oil of Oplopanax horridus Bark ...... 92

2.2 GC-MS Total Ion Chromatogram of SDE essential oil of Oplopanax horridus Leaf ...... 93

3.1 GC-MS Total Ion Chromatogram of optimized HS-SPME extraction of Oplopanax horridus Bark ...... 150

3.2 GC-MS Total Ion Chromatogram of optimized HS-SPME extraction of Oplopanax horridus Leaf ...... 151

3.3 Effect of Sample Temperature on Detector Response ...... 152

3.4 Effect of Sample Absorption Time on Detector Response ...... 153

x CHAPTER ONE

LITERATURE REVIEW

1.1 History of Oplopanax horridus

Oplopanax horridus is one of the three species in the genus Oplopanax in the

Family Araliaceae which contains the commonly known medicinal Ginseng plants.

Oplopanax horridus is also referred to in literature by synonyms Fatsia horrida Benth. &

Hook., Panax horridum J.E. Smith, Riconophyllum horridum Pall. and Echinopanax horridum Decne. & Planch (1, 2). O. horridus, commonly referred to as devil’s club, is an understory shrub which can be commonly found in the northwestern United States and western Canada. This plant is found predominantly in Alaska, and south to the central part of Oregon, and eastward to the Canadian Rockies, Montana and Idaho (3). This plant belongs to the family Araliaceae which also contains prominent medicinal plants including Asian ginseng (Panax ginseng), American ginseng (Panax quinquefolius), and eleuthero (Eleutherococcus senticos) formerly called Siberian ginseng (2). Nearly all species within the Panax genus are traditional herbal medicines and are erect, perennial, herbaceous plants with permanent aerial, woody stems (4). The plant is native to the region it is found, and has is an erect to slightly spreading deciduous shrub that is from one to three meters in height, is sparsely branched with dense spines on the stems and has prominent leaf veins (5). The stems are upright to decumbent, covered with yellow to brown needle-like spines and have large palmately lobed leaves that spirally grow around the stems (2, 4). O. horridus has small green to white flowers, borne in terminal

1 pyramidal clusters that bloom and ripen to shiny flattened bright red berries between June and July that persist over the winter (2, 5).

O. horridus is common in semi-open temperate forests on moist to wet, well- drained soils along stream edges, in seepage sites, and on floodplains (3, 6). O. horridus is considered shade tolerant and can survive in the understory of a diverse range of forest types including western red cedar (Thuja plicata Donn ex D. Don), western hemlock

(Tsuga heterophylla (Raf.) Sarg.), red alder (Alnus rubra Bong.), Sitka spruce (Picea sitchensis (Bong.) Carrière), and amabilis fir (Abies amabilis (Douglas ex Loud.) Douglas ex J. Forbes) (6). O. horridus is frequently the predominant species in the shrub layer, but also has the ability to grow in mixed populations of shrubs including Alaska blueberry (Vaccinium alaskaense Howell), red elderberry (Sambucus racemosa L.), red huckleberry (Vaccinium parvifolium Smith), oval-leaved blueberry (Vaccinium ovalifolium Smith), salal (Gaultheria shallon Pursh), salmonberry (Rubus spectabilis

Pursh), and thimbleberry (Rubus parviflorus Nutt.) (3, 6, 7). It is found to produce additional ramets through basal stem sprouting, and layers resulting in clonal expansion

(3, 6), which is of primary importance in population maintenance due the fact O. horridus rarely grows starting from seed (3, 6). The upright stems will layer by becoming horizontal and producing adventitious roots along their axes with attached branches becoming potentially physiologically independent (3). The type of environment as well as the age of the forest stands the plant is found to differ significantly based upon the age of the stand (3). Clonal fragments in various stands were found to grow to be quite old

(up to 30 years) but the majority were intermediate in age (3).

2 1.2 Oplopanax horridus traditional uses

O. horridus has two predominant categories based upon its applications by indigenous peoples. The first is as a medicinal plant to treat physical ailments and the second used for a spiritual one (8, 9).

1.2.1 Physical Medicinal Preparations

The use of O. horridus dates back to 1842 by Eduardo Blaschke, chief physician, for the Russian American Company, who reported ashed O. horridus as a treatment for sores (10). The increased interest in O. horridus as a nutraceutical product (7) has lead to many investigations not only as to what important bioactive chemicals are in the plant, but also what bioactivity the compounds possess in different systems. When pursuing a naturally derived nutraceutical product as a dietary supplement for medicinal treatment, there are some potential advantages over single ingredient medicinal therapy that include: enhancing the efficacy of a drug, reducing unwanted side effects, increasing the stability and or bioavailability of the drugs and/or selected components of the supplement (11).

Thirty-five groups west of the Rocky Mountains are reported to use O. horridus and seven more groups lack specific information on O. horridus use. However, there is a high medicinal value to using O. horridus as a medicinal plant (8). Indigenous people to the range where O. horridus is found suggest the plant’s extracts have antipyretic, antitussive, antibacterial and hypoglycemic properties (1, 12). The traditional preparations of O. horridus include decotions, ash, tonics, salves, and tea, which are primarily prepared from the roots, inner bark, and outer bark (2, 8).

3 Traditionally, O. horridus has been prepared both in ways that it is ingested, as well as topically applied to the dermis with more than 34 broad categories of use (2).

When ingested it is used to treat arthritis, blood spitting, blood disorders, cancer, chest pains, colds, constipation, coughs, diabetes, fever, flu, gallstones, gastrointestinal problems, headaches, heart disorders, indigestion, influenza, measles, respiratory illnesses, rheumatism, sore throats, stomach pain, stomach ulcers, tuberculosis, wounds, as a purgative, cure all, and as a smudge (8, 13). O. horridus may also be used topically as a topical analgesic, antiseptic, and anti-inflammatory agent; additionally, it is used to control dandruff and prevent lice (14).

A hot water extract prepared by infusing fresh or dried root bark has been used for a long time by Pacific Coast Indians and is one of the traditional means of preparing a medicinal extract from O. horridus (14-16). The medicinal tea is prepared by slowly boiling stem bark and roots in a pot over a period of four to six hours (12). Both young and old roots were found to have the same potency when made up in equal extraction concentrations (15). For example, the concentrated water extract in an animal study involving hares found that O. horridus tea, when ingested orally, demonstrated hypoglycaemic properties and didn’t have any apparent marked toxic effects during the study period (15). Conversely, in a study using two cases and two controls, there was no significant effect on consumption of O. horridus tea on blood glucose levels (16).

O. horridus bark traditionally would be heated and directly applied to an external injury such as cuts, burns or sores or would be chewed and expectorated onto the wound as a topical analgesic and antiseptic agent (14), while its stems can be burned into ashes

4 and mixed with grease, which has hygroscopic and detumescent effects on inflammation

(17). A poultice made from root or stem barks is another means for treatment of external injuries to reduce swelling and manage infection on wounds (18). The plant’s berries can be crushed and applied the scalp to prevent lice and dandruff (16) .

1.2.2 Spiritual Use

Like many other herbal medicines, the traditional use of O. horridus has multiple purposes, not only for illness treatment, but also for luck, which is one of the characteristics that demonstrates the ethnic importance of O. horridus to the peoples of northwestern North America. For instance, a ritual of the Haida tribe involves procuring

40 sticks of O. horridus each being the length from the elbow to finger tip to be placed in a circle where a hunter or fisherman preparing to go out to collect food (19). The person then chewed and swallowed strips of the O. horridus causing nausea, diarrhea and an altered state of consciousness (19). O. horridus was found with to have use as charms for protection or luck and can be used in ritualistic practices to improve power and healing

(8). Another important example of its importance as a spiritual medicine is to use a stick over doorways to protect against witchcraft (1). O. horridus has been found used for protection against supernatural entities, purification and cleansing, combating witchcraft, and as a face paint (2).

1.3 Separation and Identification of O. horridus Extracts

1.3.1 Separation

The search for new plant based medicines has yielded fruitful results as 47% of the 155 anticancer drugs developed since the 1940s are either derived from or are natural

5 products themselves. In addition, among the 877 small molecule based therapeutics introduced between 1981 and 2002, approximately 50% of them were naturally derived either as a whole material, semi-synthetic product analogue, or based upon a pharmacophore sourced from a natural product (20). Developing an extraction method that has high purity, minimal loss of bioactive compounds, and ease of extraction, purification, and quantification of bioactive compounds for accurate dosing are all properties that are highly sought after if laboratory scale were scaled up to pharmaceutical production level. There are many methods of extraction, purification, and identification with their own unique benefits and shortcomings to determine what kinds of bioactive compounds exist naturally in medicinal herbs including O. horridus. Steam distillation (SD), solvent extraction (SE), pressurized liquid extraction (PLE) also known as accelerated solvent extraction (ASE), and liquid-liquid extraction (LLE) have been used to extract and elute compounds prior to identification from O. horridus extracts.

Steam Distillation was performed to extract the essential oils from O. horridus stem bark and root bark before analyzing the volatile compounds in the essential oil (5).

The critical procedure for determining the bioactive nonvolatile fraction of O. horridus relies on utilizing a solvent to remove the lipophilic fraction before fractionating the crude extract into different fractions to allow for easier purification and identification in later steps (4, 11, 21-23). In an attempt to maximize the efficiency and quantity of their extract, PLE was investigated for it suitability by Huang et al. (21). LLE has been used many times as the means to extract bioactive compound prior to counter current chromatography (CCC) taking place (11, 24, 25).

6 Purification and fractionation methods include using a high performance liquid chromatography (HPLC), gas chromatography (GC), vacuum liquid chromatography

(VLC), counter current chromatography (CCC), centrifugation, solvent fractionation, and thin layer chromatography (TLC). A purification system using a HPLC column has the advantage that stationary phase resins with great specificity are commercially available.

Therefore, it is possible to have the ability to yield relatively high purities of single compounds from crude plant extracts. Use of a TLC method is advantageous in that after separation on the stationary phase, sections of the plate can be scraped off and then eluted with solvent yielding specific regional fractions that can have relatively similar properties, although it is limited in resolution. CCC has the ability to separate compounds without using a solid phase therefore preventing irreversible adsorption into the solid phase; additionally, it also maintains the ability to reduce the biomass of the extract and separate out distinctive fractions in a single step with high purity. Centrifugation was utilized to separate out the different fractions from heavier particles by Tai et al. (10).

Vacuum liquid chromatography was used to separate and identify a group of chemicals which were later determined to have antimycobacterial properties by Kobaisy et al. (22).

1.3.2 Identification

Identification of the chemicals can be separated into two primary categories based on their volatility. Gas chromatography mass spectrometer (GCMS) identification was used for volatile compound identification (5, 26) while high performance liquid chromatography (HPLC) can be used to separate and identify nonvolatile compounds in the O. horridus extracts (4, 10, 23, 26-28). Thin layer chromatography (TLC) is another

7 commonly employed way to crudely separate and purify the compounds in O. horridus extracts (11, 24-26). Nuclear magnetic resonance (NMR) has been used to specifically identify the chemical structures of the purified compounds to give validity to the preliminary identification of the compounds using mass spectral data or ultra violet signature of the compounds (22, 23, 25, 26).

After the process of fractionation and purification of the crude O. horridus extract, various chemical and biological assays can be performed to determine the physical and biological properties that the plant extracts have. Antioxidant tests can be conducted, which include total phenolic content (TPC), DPPH free radical scavenging activity and an oxygen radical absorbance capacity (ORAC) assay to identify antioxidant characteristics of fractionated extracts (28). Biological assays which have been conducted include: cell proliferation assays (4, 10, 28), cell cycle assays (4, 23) , cell cycle Analysis utilizing flow cytometry (27), apoptosis assays, (4, 23), cell differentiation assays including both differentiation into granulocyte lineage by NBT reduction assay (10) and differentiation into macrophage/monocyte lineage by non- specific esterase (NSE) activity assay (10). Besides inhibition of LPS-activated nitric oxide (NO) production by RAW264.7 cells (10) and cyclin A assays (4), microplate alamar blue assays (MABA) (24, 25) were performed. The antibacterial, antitubercular and anticancer properties have been conducted in a number of studies involving many different bacteria and include many different cell lines of tuberculosis, and cancer lines of leukemia, breast, ovarian, prostate, and colon cells.

8 1.4 Phytochemical and Biological Activity

Volatile compounds of O. horridus extracted by steam distillation were identified using GC-MS which yielded essential oils with principle components (E)-nerolidol, bicyclogermacrene and τ-cadinol which composed 74.5% of the bark total extract while

(E)-nerolidol and τ-cadinol yielded 71.5% of the root bark extract (5). Their biological activity was not analyzed. Conversely, much more data and analyses of the biological activity of nonvolatile extracts have lead to the support for the traditional uses of O. horridus.

The traditional uses of O. horridus for treating respiratory illnesses, tuberculosis, dressing wounds, as a skin wash, and for diabetic effects validated empirical confirmation of O. horridus above a level one classification according to the methodology for cross- cultural ethnomedical research by Browner et al. (29). The available research with bioassay, cellular assays and phytochemical data suggest reasonable scientific support for the traditional treatments of ailments using O. horridus discussed by Johnson (8). In addition, an increased body of knowledge and scientific evidence support the properties of antimycobacterial (22, 30), antibacterial (22, 31), antifungal (22, 32), and antiviral

(33) activities of O. horridus as a medicinal herb. The first published data regarding the extraction of compounds from O. horridus was a hot water extraction using fresh and dried barks from the roots of the shrub (15). Stuhr and Henry were some of the first investigators to perform chemical investigation into the chemical constituents of different

O. horridus extracts and found unsaturated fatty acids, saponins, glycerides and tannins to be present (34).

9 A 70% ethanol extraction was effective in <1/1500 dilution on K562 and HL60 leukemia and MDA-MB-468 breast tumor lines and at 1/500 dilution on MCF7 breast tumor cell line (27). Stronger anti-proliferation activities of nonpolar compounds compared to the polar extracts suggests the presence of key compounds in the lipophilic fraction of the plant extract. Ethyl acetate extracts had greater activity given higher dilutions compared to the water extracts (27). The compounds extracted also were not heat lible when boiled for sixty minutes nor were they found in the volatile fraction (27).

Crude extracts had higher anti-proliferation activity than further separated mixtures which suggests possible additive or synergistic activity (27). Since the extracts have a significant anti-proliferation effect on A2780, A2780CP70, OVCAR3 OVCAR10 ovarian cancer cell lines at a µg/mL range it is possible that consumption of a solvent extracted

O. horridus extract would be within a reasonable level for treatment (27). Additive effects of O. horridus extracts with conventional ovarian cancer therapeutic drugs were confirmed with a positive effect on both drug sensitive and drug resistant human ovarian cancer lines which could improve the drug efficacy in fighting cancer’s progression (27).

Ethanol in varying percentages has been a common solvent choice for extracting bioactive compounds from O. horridus. For example, oplopanphesides A, B, and C, and phenolic glycosides, were present in O. horridus using an 85% aqueous ethanol (35).

Despite being identified and isolated, when tested against MDA-231 and MCF-7 human cancer lines they had an IC50 concentration more than 100µm and were considered inactive (35).

10 The antiproliferative effect of 70% ethanolic extract from O. horridus bark was found to have significant antiproliferative effects on all cell lines when tested against three colorectal cancer cell lines (i.e., SW-480, HCT-116, and HT-29), breast cancer cell line MCF-7, and a non-small cell lung cancer cell line (4). In contrast, the extract of O. horridus berries had significantly less activity than that of the bark, and were only significantly antiproliferative on MCF-7 cells (4). Cell growth inhibition was studied using the SW-480 cancer cells, which were measured using flow cytometry after staining with propidium iodide by Wang et al. (4). Their results showed that after applying a treatment dose of either 0.05 mg/ml or 0.1 mg/ml extract to the cell lines and allowing incubation, significant changes were observed in the cell cycle profiles that differed for both treatments from the control, and increased the expression of cyclin A (4). Increased cyclin A levels are important in promoting cell cycle arrest in S- and G2/M- phases (4).

Treatment of both 0.05 and 0.1 mg/ml dosages of the extract also resulted in an increase of apoptotic cells as dose increased. Additionally, an increased treatment time increased cell apoptosis measured using flow cytometry after staining with annexin V and PI (4).

Utilizing a 70% ethanol solvent to extract O. horridus ground root bark, separation and structural identification of 1-acetate-9,17-octadecadiene-12,14-diyne-

1,11,16-triol, oplopandiol acetate, falcarindiol, oplopandiol, trans-nerolidol, and τ- cadinol (23) . Falcarindiol, a polyacetylene, was found to have the strongest in vitro apoptotic anticancer activities of human colon cancer HCT-116 cells (23). Polyacetylenes

1-acetate-9,17-octadecadiene-12,14-diyne-1,11,16-triol, oplopandiol acetate, and falcarindiol induced HCT-116 cell arrest in the G2/M phase and induced apoptosis thus

11 causing inhibition of cell proliferation at dose dependant concentrations (23). The antiproliferation effects of the lowest two levels of treatment, 10µM and 20µM were not concentration dependent and were not significantly correlated with anti-proliferation using the cell cycle test (23).

An 80% methanol extract of O. horridus bark was lyophilized and yielded the known sesquiterpenes which include: α-cubebene, trans-nerolidol, spathulenol, and oplopanone (14). An 80% methanol extract yielded the sterol stigmasterol and trans- nerolidol a terpenoid (26). O. horridus bark was also found to contain the phenolic compounds including: gallic acid, caffeic acid, 4-O-feruloylquinic acid, 5-O- feruloylquinic acid, methyl-feruloylquinate, ferulic acid, methyl-ferulate, and quercetin.

The oxygen radical absorbance capacity (ORAC) values of the solvent extracts was

198.11 trolox equivalents /100g dried weight for the crude extract (28). The DPPH free radical scavenging capacity for the whole extract was 5649.05 BE/100g dried bark which was about 18% higher than the sum of the different fractionated solvent extracts. When tested on the HT-29 human colonic adenocarcinoma cell line it had an antiproliferation effect of 76.18% and 54.96% at concentrations of 1mg/mL and 2mg/mL respectively

(28). A methanolic extract of O. horridus yielded the identification of oplopantriol A, oplopantriol B, (11S,16S,9Z)-9,17-octadecadiene-12,14-diyne-1,11,16-triol-1-acetate, oplopandiol acetate, falcarindiol, oplopandiol, and (S,E)-nerolidol with the aid of SPE and HPLC, which can be useful in creating a quality control profile of O. horridus (21).

A methanolic extract of O. horridus yielded 5 polyynes: (1) falcarinol, (2) 9- heptadecene-4,6-diyne-3,8-diol, (3) 1-acetate-9,17-octadecadiene-12,14-diyne-1,11,16-

12 triol, (4) 9-heptadecene-4,6-diyne-3,8-diolacetate, and (5) falcarindiol, expanding the known chemicals that have bioactivity (22). The methanol extract was found to have antimycobacterial activity against Mycobacterium tuberculosis and isoniazid-resistant

Mycobacteria avium using a disk-diffusion assay (22). The extracted polyynes had antibiotic activity against two gram positive microbactira, Staphlococcus aureus and

Bacillus subtilis, two gram negative bacteria Eschericia coli DC2 and Pseudomonas aeruginosa Z61 and a yeast, Candida albicans (22). The methanolic extract and subsequent fractions of the extract had activity at a concentration of 10 µg/disk using a disk diffusion assay (22).

O. horridus inner bark was found to have antibiotic activity against Bacillus subtilis, Mycobacter phlei, Pseudomonas aeruginosa H188, Staphlococus aureus methicillin sensitive, Staphlococcus aureus methicillin resistant P00017, and Salmonella typhimurium TA98 (31). An extract prepared from the inner bark was later tested by against a number of fungi and exhibited antifungal activity against Aspergillus fumigates,

Candida albicans, Saccharomyces cerevisiae, Trichoderma viridae, Fusarium tricuictum,

Microsporum cookeri, Microsporum gypseum, Trichophyton mentagrophytes among which the extract had the greatest effect against M. cookeri and T. mentagrophytes (32).

Additionally, an inner bark methanolic extract demonstrated partial inhibition of bovine respiratory syncytial virus (Paramyxoviridae) (33).

A combination of the three solvents DCM, MeOH, and 50%MeOH were used to extract O. horridus bark into a crude extract (11). The crude whole extract was separated into two multiple distinct fractions and used to identify the effect of compounds and their

13 possible synergistic effect. The less fractionated extracts had higher activity than those which were more distinctly separated (11). Bioactivity studies supported that there was a synergistic interaction between some of the recombined fractions to form cocktails that had higher bioactivity than individual compounds against tuberculosis using a microplate alamar blue assays (11). One of the most notable findings was that even with different combinations of fractions there was no antagonistic effects of the cocktails (11). A later study that prepared an extract from the inner stem bark of O. horridus yielded the isolation and structural identification of five novel chemicals: (1) 3,10-epoxy-3,7,11- trimethyldodeca-1,6-dien-11-ol, named neroplomacrol, (2) rel-(3S,6R,7S,10R)-7,10- epoxy-3,7,11-trimethyldodec-1-ene-3,6,11-triol, named neroplofurol, (3) oplopandiol, (4) falcarindiol, and (5) sesamin after being separated and extracted using chloroform, methanol, and 50% methanol (25).

In extracting the bioactive chemical fractions from O. horridus, there is a significant reduction in the extract mass as a fraction of the whole. After solvent extraction, an extract with a yield 29.936% (w/w) of the initial biomass of O. horridus root was observed (24). Different extraction methods, solvent systems, purification processes, and fractionation techniques performed lead to the identification of a variety of different compounds. Antioxidant tests showed that the crude O. horridus extracts were found to have higher total phenolic content, a higher ORAC equivalent, higher DPPH

Free Radical Scavenging Activity (28), and a higher TEAC value than the individual fractions studied (10). These compounds in addition to their antiproliferation effects are

14 of interest when looking at the possible nutraceutical and pharmacological benefits of dietary supplementation.

Reductions of viable cancer cell counts by antiproliferative tests determine the anticancer impact of a treatment in vitro. The crude extract of O. horridus has been found to have greater activity than individual fractions. Natural product extracts frequently contain multiple compounds which have additive or synergistic effects which can increase the effect of the bioactive compounds which is different than single compound medicines. Support for the presence of synergistic compounds in O. horridus as it is found in non overlapping fractions which have different polarities (11).

1.5 Relating Research to Traditional Use of O. horridus

The traditional use of O. horridus being ground up and brewed in a tea is less of a benefit to the indigenous peoples who consume it regularly, as it is evidenced by the smaller anti-proliferation activity of a water extract compared to a 100% ethanol extract.

This activity difference led to the hypothesis that the bioactive compounds in O. horridus might be in the hydrophobic fraction of the extract. Tests to determine the heat lability of the compounds in O. horridus extract as well attempts to narrow down the compounds in

O. horridus extract that have the most significant effect on cancer cell proliferation were conducted by Tai et al. (27). In the study when the extract was heated in boiling water for one hour, there was not have a difference on the antiproliferation activity of the extract compared to the control, which led to the conclusion that the active compounds are not heat labile. Reconstituted ethanol extract and ethyl acetate samples also maintained their cancer cell antiproliferation activity after being dried at 60°C leading to

15 the conclusion that the antiproliferation activity is not in the volatile fraction (27).

Nerolidol, a chemical present in O. horridus (5, 26), was studied for its antiproliferation activity, whereas a pure nerolidol treatment had significantly lower antiproliferation ability when compared to the crude O. horridus extract (27). Additionally, there was a dose dependent inhibition of nitric oxide production by the ethanolic extract on the lipopolysaccharide activated RAW 264.7 cells, which is an important marker in host immune response (10). Also, the ethanolic extract of O. horridus bark showed some synergitistic antiproliferative effect and additive-antiproliferative effects on several human tumor cell lines (10).

1.6 Volatile Extraction Methods

1.6.1 Simultaneous Steam Distillation Solvent Extraction (SDE)

Isolation, separation and concentration of volatile compounds from complex plant matrices has been a challenge since there are many different biosynthetic processes to generate different classes of aromas and fragrances. Application of distillation of compounds has been common and is typically associated with flavor and fragrance to collect essential oils for the perfumery business. A novel apparatus was created in 1964 to apply both the concepts of distillation and solvent extraction occurring at the same time (36). Simultaneous distillation-extraction (SDE) is a one-step isolation and concentration of flavor constituents which functions by partitioning the non-polar flavor compounds into a solvent immiscible with water. The recycling of organic solvent and water permit the SDE apparatus to not only be a time saving method of sample preparation but also allows for consumption of less organic solvent which saves a great

16 deal of cost for analysis (37). The different heights of the distillate-return arms permit the use of the apparatus for both less-dense-than-water solvents as well as denser-than-water solvents. The extraction takes place by first placing the sample into a round bottom flask and being mixed with water followed by being brought to a boil. The volatiles are steam- distilled through the upper part of the appropriate arm while at the same time the organic solvent vapors are also distilled but through the other arm. The center chamber allows for mixing of both the steam-distilled vapor and organic solvent vapors which then condense on the cold-finger to fall together into the separator where the emulsion of polar and apolar phases separate prior to recycling back to their respective flasks.

Solvent flow rates of their vapors through the necks of the apparatus and the rate at which they interact is dependent on their temperature and is an important factor in SDE

(38). The rate at which each phase is volatilized and condensed can alter the ratio of solvents condensing on the cold finger and ultimately can alter the separation properties of the phase emulsion in the separation part of the SDE. Increasing the steam and solvent vapor flows showed increased recovery rate of compounds (39). The solubility of the analytes in the selected solvent system selected and the temperatures of the samples and the nature of their volatile constituents are important factors when choosing a suitable extraction method for applying SDE to recover the volatiles from a sample (38). SDE has been found to have varying recovery percentages based upon a number of factors but predominantly the extraction time, pH, solvent type, activity of the glass, temperature of cold-finger, type of condenser used, sample volatile concentration, atmospheric pressure, and salt concentration (37, 39-43). The types of compounds being analyzed after

17 extraction and concentration using SDE is also of concern as thermolabile compounds can decompose as well as the elevated temperature at which SDE occurs promotes a higher tendency toward volatile oxidation (44).

The choice of an organic solvent for SDE has varied as some have higher densities than water while others are less dense. The most commonly used solvent is typically dichloromethane (DCM) as it has a high recovery percent for a large variety of compounds (37, 39, 40, 45-47) and elutes rapidly in GC and is easily evaporated in order to concentrate extracted volatiles (42). Despite the common use of DCM, pentane (40,

45), iso-pentane (46), hexane (47), chloroform (45), ethyl acetate (45), diethyl ether (47), methyl t-butyl ether (45), trichlorfluoromethane(46), 1,1,2-trichlorotrifluoroethane (47) and solvent mixtures such as pentane/diethyl ether (47) have also been used. As heating temperatures were the controlling factor in extraction and different solvents have different latent heats of vaporization, they had different flows so that adjustments need to be made to allow for proper separation of the emulsion without allowing the aqueous phase to travel to the other neck of the apparatus where the organic phase returns as it would ultimately cause problems in concentrating the extracted volatiles and is not good for the columns in GC (39).

Extraction time has been analyzed up to 48 hours in high fat materials in which hard to recover samples were analyzed but for plant material and carbohydrate based foods (48) extraction is typically conducted for only one to two hours. The pressure at which extraction occurs also has an impact on the volatiles that compose the final extract

(39, 42). Modifications of the original device have afforded the ability to operate at

18 parameters other than atmospheric pressures for extraction (39, 42) at both reduced pressure (39, 49) and static vacuum (42). Despite other extraction pressure having been investigated, the extraction of volatiles at atmospheric conditions is not necessarily optimized fully, but it has shown the highest recovery for the largest set of compounds

(37). Artifact compounds are a cause for concern for SDE when looking for analytical quantitation as qualitative analysis of compounds is inherent in a particular type of analyte. The purity of solvents, sample, operational environment, surface activity of the glass SDE are important factors to consider (50-53). Although high purity solvents are commercially available, it is usually best to run a blank experiment to identify any contaminants from the glassware, solvent or other contributors to artifact compounds

(51).

Despite the drawbacks of SDE, high recovery yields with low variability from a variety of matrices and ability to model the loss of solvent during an experiment by including an internal standard to the sample solidify its use in flavor research (41). The addition of an internal standard has afforded SDE use in separation, qualitative analysis and quantitative analysis of volatiles from many different types of materials. Recovered isolates which contain nearly all the volatile compounds as the starting materials without interfering lipid-containing compounds which would be obtained in solvent extraction are another reason that SDE is a suitable method of volatile extraction (54). Utilizing a magnetic stirring bar to increase the extraction efficiency of SDE in conjunction with

DCM as the non-polar solvent was the most efficient means for conducting atmospheric

SDE extraction (39).

19 1.6.2 Headspace Solid Phase Microextraction (HS-SPME)

Headspace analysis is a sampling technique that is unique to gas chromatography and is used in determining the organic volatiles in the gaseous headspace within a sealed vial above the sample desired to be analyzed (55). When performing analysis of plant organic volatiles, it is important to consider not only the physical properties of the sampling technique, but also cost, portability, convenience, time, hazardous chemical production, matrix complexities, extraction temperature, chromatographic conditions, recovery, precision, accuracy, and automation for high throughput analyses. Headspace

GC (HS-GC) is dependent upon the vapor pressure of the analyte and partition coefficient of the matrix in which it is present. Solid phase microextraction (SPME) is a sampling technique which can be used in conjunction with headspace analysis to selectively extract and concentrate the organic volatiles from a sample and employs modified fused silica fibers with a liquid stationary phase (56). SPME has advantages over other types of extraction of volatiles in that it is solventless, able to reduce signals of blanks (on chromatograms), and can greatly reduce the extraction time for volatile organic compounds (56). The application of HS-SPME to perform rapid and sensitive analysis of medicinal plant volatiles in searching for possible leads in bioactive phytochemicals has proven effective (57, 58).

Primitive forms of SPME fibers tested different stationary phases including polyimide, fused silica, liquid crystal polyacrylate, Carbowax, cross-linked Langmuir-

Blodgett layers, graphite, poly(dimethylsiloxane), and others (56, 59). SPME is applicable to both gas and liquid phase for sample extraction, and has a large linear

20 dynamic range, low detection limits approaching and below 15 parts per trillion (ppt) for both liquid and gas phases (56, 59-62). For instance, SPME allowed for levels of detection at the pg/ml level when used in conjunction with GC ion trap mass spectrometry (63). SPME has a broad range of applications and is not limited to headspace analysis of organic volatiles, but also can be used in environmental testing, pesticide analysis, clinical uses, industrial process control, and many others (60).

The small diameter of the fused silica fibers and the variety of stationary phase thicknesses allow for on-column thermal desorption inside the injection port of a GC and also allows for better catering of the extraction parameters to fit a broader variety of laboratory applications (56). The coatings used for stationary phases are normally viscous liquids which function to perform a non-exhaustive liquid-liquid extraction (60). The mass transport of the analytes in the headspace and their subsequent partitioning to adsorb/absorb to the liquid stationary phase occurs via diffusion assuming a static environment. The use of an internal standard when performing equilibration isotherms allows the rate of partitioning through the phases to be calculated and as such permits non-equilibrium extraction parameters (56). The differences in the slopes of the calibration curves for a given coating thickness is due to the distribution constant differences between compounds (60). HS-SPME also allows for prevention of extraction of high MW compounds that could otherwise damage the capillary column.

There are a variety of factors which affect the suitability of applying SPME to extraction of samples for analysis. The physical kinetics of analytes is of particular importance in obtaining a suitable and representative of the sample being analyzed. The

21 equilibration in headspace SPME (HS-SPME) is reliant upon equilibration between three phases being the analyte and the solvent, the solvent and the headspace and then between the headspace and the SPME fiber. The rate limiting steps of the equilibration are between the sample and the solvent phase and then also the solvent phase equilibrating with the headspace (64). Normally when performing HS-SPME the assumption is made that sufficient time has been allowed for the sample and solvent phase to equilibrate (64).

Application of HS-PME allows for shorter equilibration times relative to equilibration times in liquid due to the fact that gases reach equilibrium four orders of magnitude higher than the aqueous phase (64, 65). The equilibration with the fiber requires less than

1 minute due to the large diffusion coefficients of gases (66). The absorption of analyte is based on their ability to partition between the liquid stationary phase of the SPME fiber and the sample being analyzed, unless there is a small sample size of which the volume is not necessary to be accurately measured (67). Experimentally in practice, “equilibrium time” is the time at which the mass absorbed by the fiber coating has reached approximately 90% of its final total mass (64). HS-SPME is suitable for analyzing volatile organic compounds due to the fact most organic compounds have large Henry’s constants which means they have relatively short equilibration times (64). The ability to concentrate trace analytes from a sample matrix into the fiber coating allows for very low levels of detection and levels of quantitation (64). When compounds with very high distribution constants (K) are extracted, there is a risk that the initial analyte concentration may be significantly changed and as such additional extractions from one vial would not be suitable (60). Due to the variable nature of the principles upon which

22 SPME works, an average relative standard deviation of 7% is generally acceptable in trace organic analysis (68).

The presence of electrolytes in an adsorption system can influence the adsorption by modifying the properties of the phase boundary and decreasing solubility of hydrophobic compounds and thus HS-SPME performance can significantly change (68).

Also, the extraction temperature has an effect on the detection sensitivity of less volatile compounds as at lower temperatures they have less ability to partition into the headspace above the sample; conversely, more volatile compounds will have a decrease in peak areas at higher temperatures due to reduced fiber-headspace distribution constants (69).

Increasing the temperature of the extraction vial allows for the analysis of volatiles from complex matrices without additional clean up steps and makes for easier analysis of large quantities of complex matrices such as soil or sludge (64). When performing HS-SPME analysis, for highly volatile compounds like l,l,l-trichloroethane and carbon tetrachloride changing the extraction temperature by 10°C yields a significantly increased amount of analytes absorbed by the stationary phase by approximately 20% (70). A warmer aqueous solution for extraction yields a greater amount of analyte in the headspace due to the temperature dependence on the aqueous and gas phase partition coefficient (71).

Decreasing the headspace to solvent ratio inside a vial will also decrease the limit of detection (64). Higher sensitivity in HS-SPME methods can also be obtained using headspaces that are kept as small as possible as the volume of gas phase doesn’t have an influence on the actual amount adsorbed onto the fiber (68). The shape and quantity of headspace volume relative to the volume of solvent can affect the precision of HS-SPME

23 analysis. Worse precision is noticeable when using small sample volume headspace vials

(72) of which the shape of the septum can have a large effect whether it is convex or concave after sealing the vials (73).

The thicker stationary phases require longer equilibration times and longer extraction times in order to get repeatable extractions. Additionally, the thicker stationary phases allow for an increased amount of extracted organic volatiles to be identified. The thickness of the stationary phase is also important because the loss of analytes from the stationary phase due to volatilization decreases as the thickness increases (74). As stationary phase volume increases by increasing either the thickness of the stationary phase or the length of the fiber, more analyte can be absorbed to the fiber and thus increase the linear range of the SPME fiber (74). Thicker films most efficiently absorb compounds with low distribution constants due to reduced influence of flux restrictions of small partition coefficient compounds (59). The increased equilibration times allow the compounds to distribute themselves within the stationary phase of the fiber because it allows for better partitioning into the thicker stationary phase relative to a thinner one.

Conversely, thinner stationary phases are more suitable for compounds with high distribution constants and have shorter equilibration times (59). The increased thickness of a stationary phase improves the sensitivity of the method and decreases the level of detection and level of quantitation while increasing equilibration time (60). More volatile compounds require thicker phases to have good repeatability compared to semi-volatile compounds (75).

24 The polarity and nature of the liquids that are coated onto the SPME fiber has a great effect on the type and degree of analysis of compounds at low concentrations.

When trying to analyze more polar compounds, a more polar stationary phase allows for greater selectivity of the extracted compounds (60). Large less polar molecules with high octanol/water distribution constants are expected to have proportionally lower limits of detection when using a poly(dimethylsiloxane)-coated fiber (60). Methyl groups of polydimethylsiloxane (PDMS) are relatively nonpolar. Due to its relatively nonpolar nature, a fiber with a PDMS stationary phase is excellent for analyzing the volatile composition of botanicals and medicinal plants (76). Absorption is the primary mechanism of extraction when PDMS SPME fibers are used (77). The length of the

SPME fiber is another way to increase the volume of the stationary phase used to extract and sample from a matrix, but has a maximum limit of approximately four centimeters

(60).

Sensitivity of HS-SPME can be lower than direct SPME if the system is allowed to reach equilibrium. However, due to the desire for short equilibration times for trace analysis, normally increased sensitivity of HS-SPME relies on the much longer equilibration times of a two phase liquid solvent and SPME system (72). A major limitation of HS-SPME is that the amount of analyte extracted by the SPME fiber from equilibrated headspace system is smaller or equal that of a system without a headspace

(72). Prolonged sampling times increases the possibility of analyte loss due to adsorption onto vial walls and septum, decomposition, loss to atmosphere etc., which could outweigh the additional benefits of increased HS-SPME extraction times (72). Rapid

25 extraction can be achieved if the capacity of the headspace is at least 20 times larger than the capacity of the fiber or increasing the partition coefficient of the headspace by increasing the temperature or salting out the analyte from the liquid phase (72).

Absorption-time profiling can be useful in understanding and creating equilibration isotherms for a number of compounds by plotting the area count of a chromatogram vs the adsorption time. As SPME has grown to be a more commonly used form of analysis many means have been developed to increase sensitivity and decrease level of detection, and equilibration time. The first few minutes of adsorption is usually rapid with a highly responsive increase in area count prior to reaching a point where it begins to gradually increase until eventually reaching a maximum value either of the GC detector’s response or of the complete saturation of the SPME fiber (56, 60). A stirred solution has similar shape but higher response than an unstirred solution. Therefore, an increased response in detectability per unit time extracted allows for shorter extraction times when the solution is thoroughly stirred (56). Stirring at a maximum rate has higher mass transport rates than using a sonication for mixing of the solution (60).

Sonication will improve the extraction of compounds in solution but not as much as maximum stirring (60, 64).Additionally, the size and shape of the stirring bar have an effect on the extraction efficiency of analytes from the sample matrix (78). Sonication consequently results in sample heating during the extraction, which induced decomposition and thus has limited practical application (78, 79). Fiber vibration was explored and is efficient in chemical absorption in small 2mL vials, but its efficiency decreased with an increase in vial size (79). Flow through extraction using a SPME fiber

26 for adsorption of pesticides from aqueous samples has been shown to have high efficiency and potential for aqueous sample monitoring in environmental applications

(79). The temperature of the SPME fiber is also important to consider because as the temperature of the fiber increases, the partition coefficient between the liquid phase of the fiber and the sample being extracted decreases (80).

The location and depth at which the sample is desorbed from the SPME fiber inside the GC injection port has an effect on the degree of desorption (56). Therefore, it should be carefully controlled either through use of an autosampler or manual injection that optimizes the desorption from the SPME fiber. The location inside the GC injector is critical because without being at the hottest part of the injector and at the same depth proper desorption cannot be achieved (59). The higher the syringe is in the injection port of the GC, the less analyte will be desorbed due to a temperature difference within the injector. This problem is one of the reasons for the variability of precision of desorption in the injection port enabling repetitive locations of injection and sample desorption within the GC port (61). Desorption time is another important factor to be considered.

The longer the fiber is desorbed in the injector, more compounds can be thermally desorbed from the SPME fiber and injected onto the column. Subsequently, longer desorption times allow for an increase in detector response up until no significant increases in detector response per increased time is noticed. Complete desorption is important to prevent carryover and artifacting of compounds on the fiber. Desorption times are normally from the order of a few seconds to a few minutes and should be studied for each sample analyzed (69).

27 Equilibration rate is limited by mass transfer of analytes through a static aqueous layer at the fiber-sampling phase interface, distribution constant of the liquid stationary phase of the fiber, the polymer type and thickness of the coating (56, 60, 61, 63, 81). One of the consequences of these aforementioned factors is that the extraction needs to be long enough to allow for the rate of absorption of the analytes to reach an equilibrium as the end concentrations are dependent upon the adsorption isotherms (56). The commercially available fibers from suppliers like Supelco have allowed for an increase in repeatability, and a decreased variability from sample to sample extraction, although it was common to have 10% relative standard deviation (56).

The linear relationship between the amount sorbed into the stationary phase and the concentration in the sample must be mathematically corrected to properly calculate the concentration under those specific extraction parameters. The linear relationship between the amount of solute absorbed by the fiber at equilibrium and the analyte’s

0 concentration obey the following equation of ns  KV1 C2 where ns is the moles of analyte absorbed by the stationary phase, K is the distribution constant of an analyte between the

0 stationary and aqueous phases, V1 is volume of the stationary phase and C2 is the initial analyte concentration in water (59). The partition coefficients of the volatile organic compounds extracted are affected by temperature variations and the composition of the extraction matrix (60). While typically not used for quantitation purposes due to the complex matrix interactions, it is possible to perform reasonable qualitative analysis with

HS-SPME although standard addition and isotopic dilution could also be used for quantitative analysis using HS-SPME (62, 68).

28 1.7 Gas Chromatography

Gas chromatography is based upon the principle of partition, adsorption and desorption of the solute between a stationary (liquid) phase and a mobile (gas) phase with the mobile phase flowing through a capillary column coated with the liquid phase (82).

The retention of a compound is dependent upon the individual solute molecule’s interaction with and ability to partition, adsorb and desorb to the stationary phase. The analytes can be separated out from a complex mixture into individual compounds.

Moreover, closely similar structures can be identified by comparison with authentic standards, mass spectral fragmentation, and Kovats retention indices. The means of injection is important when considering elution profiles of compounds. Ideally, on- column cool injection is the optimum technique for quantitative analysis and thermal- decomposition free samples to be introduced to the GC column, but it is limited to clean samples (83). High flowrate injections can also cause peak broadening and decreased quality of separation of low molecular weight compounds when using splitless injection

(84).

Gas chromatography is carried out either in isothermal (IGC) or temperature- programmed modes (TPGC) with the principle difference being that temperature programmed modes increase gradually with time compared to holding a constant temperature for the duration of the experimental separation. An important consideration when calculating the Kovats retention indices is that in IGC the elution of an analyte and its adjacent n-alkanes elute is dependent upon time as temperature is held constant throughout the separation. Utilizing a temperature gradient in TPGC, elution of analytes

29 can occur at a broader temperature range allowing for better peak separation and shape as the conditions of the TPGC system (gas flow rate, pressure, and temperature) will continuously vary with the temperature-programming rate (82). The elution of compounds at progressively increasing temperatures will allow analyte peaks to separate out visualized by narrower and more symmetrical peaks (82). Important differences between IGC and TPGC is that the retention indices of the n-alkane standards used to calculate the retention indices will elute at the same temperature in IGC where as in

TPGC each of the alkane standards elution times are dependent upon the temperature of the column (82). In capillary TPGC, the analyte retention times should not undergo dead time correction due to their dependence on temperature, pressure of carrier gas and flow rate on the column vary throughout the analysis and are not constant as in IGC (82). An important consideration for analysis of highly volatile compounds is the reproducibility and linearity of the n-alkane elutions as some consider that linearity exists from pentane

(85, 86), heptane (87), or nonane (88, 89). When a gas chromatograph is used to separate out the volatile components of an essential oil, it is not practical to mix an n-alkane standard into the sample solution so the standards are most commonly run separately using the same method and then used to calculate the retention indices (90).

Kovats introduced the series of n-alkanes as retention markers by assigning the retention indices of the n-alkanes in increments equal to 100 times the number of carbon atoms in the molecule in order to avoid the use of decimals in the index (91, 92). The elution of analyte molecules is relative to the interaction with the stationary phase and will vary depending on the chemical structure of the compound relative to the n-alkanes

30 that provide reference boundaries (82, 93). Temperature-programming rate will have an impact on the retention temperature and time of an analyte in a gas chromatogram but due to the nature of the Kovat retention index the 100 unit difference between the elution of successive n-alkane standards will still be maintained regardless of isothermal, linear or nonlinear temperature programming, or any other means of temperature programming

(82).

Retention temperature and boiling point of a compound are related because at the boiling point intermolecular interactions are at a minimum allowing the liquid to change phases and become a vapor (82). The intermolecular interactions between the analyte and stationary phase molecules are at a minimum allowing the analyte to become eluted from the column (82). The retention indices of n-alkanes are based upon the number of carbon atoms and does not relate to other molecular properties of the n-alkanes although they are closely related to the boiling points of the n-alkanes (82). In TPGC the higher the rate of temperature increase the shorter the retention times and the higher the retention temperature of both n-alkanes and analytes (82). Several compounds can have the same retention index on a column so additional data about the composition of an eluting compound is necessary to provide adequate identification. In most cases, mass spectrometry provides additional identity to the compounds in addition to their retention index (94).

The chemical structures of analytes are important to understand their effects on the retention index. The n-alkanes retention indices are based upon the methylene carbon atoms interaction with the stationary phase of the column on a per-atom basis and thus

31 the arbitrary unit difference of 100 accounts for the increase of one methylene unit. The chemical functional groups of analyte compounds result in the shift of KI compared to the n-alkane reference times. The differences between methylene units and the structures of analytes is important because the effect that electron density and molecular structures have on retention indices are due to atoms, bond structures, functional groups and column polarity (82). Changes in these characteristics will change the resulting retention time and can cause visible differences of chromatographic separation depending on the nature of the interaction with the stationary phase of the column.

In general terms the presence of an electron-withdrawing function groups containing nitrogen and oxygen atoms such as –NH2, –OH, and –COOH have longer retention times and is largely due to the electronegativity of the atoms in the functional group (82). In non polar columns the ranking of retention time from largest to smallest is that of (diols) > (amino-alcohols) > (diamines) > (glycols) > (acids) > (alcohols) >

(amines), for which the commonly used column for analysis was a DB-5 column, which is a (5% phenyl, 95% methyl silicone) capillary column (60m x 0.25mm ID x 0.25µm film thickness) at which the non polarity was most similar to the DB-1 column (82).

The interaction between the analyte and its affinity for adsorption to the column liquid stationary phase is the dominant surface reaction as adsorption is one of the principle interactions in allowing gas chromatography to function while the steric configuration of analyte molecules can influence the resulting retention time too (82).

The n-alkanes are saturated linear hydrocarbons and each of the carbon atoms of the individual analytes will interact with the stationary phase thus if any of the hydrogens

32 were substituted for a different functional group or atom the retention times would also change (82). When substitutions take place from being a saturated hydrocarbon in particular when compounds have functional groups with chain branching or double or triple bonds the spatial orientation can cause a different retention index due to the stearic effects of the functional groups (82).

Although a flame ionization detector (FID) usually has a wider linear dynamic range and stable response while maintaining high sensitivity, it lacks the ability to identify molecular fragments in the way that a mass spectrometry detector can. The mass spectrometer allows for ionization and fragmentation of molecules that are separated according to their mass-to-charge ratio. With the aid of commercial libraries, the identification of compounds can be determined in addition to calculating their retention indices from the compound retention time relative to an n-alkanes series. Another benefit of the MS detector is that it also has a lower detection limit than the FID. For example, some MS have detection limits in the femtogram range using a quadropole mass filter using selected ion monitoring (SIM) of representative ions of a specific compound (95).

1.8 Medicinal Plants and Phytomedicine

The use of plants in treating and preventing illness has existed for hundreds of years. There has been an increased interest in functional foods, “nutraceuticals”, and medicinal plants in the North American market (96). In the United States the herbal use increased 380% from 1990-1997 (97) and has been driven by preventative medicine (98).

Traditional medicines continue to be used in every country throughout the world and play a critical role in the treatment of illness and disease in developing countries where 70-

33 95% of the population rely on traditional medicines for primary care (99). The global market for traditional medicines was estimated to be growing exponentially with a 2008 value estimated at $83 billion (99).The primary difference between nutraceuticals and medicinal plants is that medicinal plants are used to exert specific medicinal action without serving a nutritional role in the diet where as nutraceuticals do have a nutritional role in the diet and long-term consumption may lead to health benefits such as chemoprevention (100). The phytochemical activity of medicinal plants is unique to the plant species. Their secondary metabolites are also unique in a particular species and can be taxonomically distinct from other plants in the same family (99, 101).

Traditional Chinese Medicine (TCM) primarily involves the use of medicinal herbs, spices, and other plants may provide alternatives for traditional single component drug treatment as novel bioactive substances also offer opportunities to treat illnesses and cancer (102, 103). Many traditional medicines have found extensive use for a long period of time (104). Traditional medical systems typically combine extracts from several unrelated medicinal plants whereas modern phytomedicine tends to employ monoextracts

(105). The synthesis and accumulation of nonessential organic molecules is a common feature of plants and are usually termed secondary metabolites or natural products (105).

Application of multiple antibiotic chemicals with different modes of action provides the potential for an increased likelihood of controlling the spread of disease compared to single antibiotic treatments as the development of resistance to multiple chemicals would be more difficult (105), which provides some support for the use of TCM. Additionally, while in vitro studies are frequently used to identify new sources of bioactive chemicals

34 from plants, the ability to link in vitro to in vivo studies using humans with the proper control measures and pharmacokinetic data for most medicinal plants is lacking (106).

Plant secondary plant metabolites of pharmacological interest primarily are categorized into the alkaloids, terpenes, terpenoids, and phenolics (20). These groups can then be subdivided into two large groups of secondary plant metabolites, i.e., those highly active compounds with a great selectivity for cellular targets, and those compounds that are weakly active but can have the ability to interact and attack various cellular targets which provide a more broad phytochemical response (20). Many of these weaker broad spectrum phytochemicals can be classified into groups of flavonoids, coumarins, tannins, and terpenoids, iridoids, lignans, and anthracenes(20). Despite the fact that highly active metabolites have high specificity and higher activity compared to less active ones, having a broad metabolite profile will provide more of an advantage for the plants that synthesize them. This can be attributed to the fact that having a broad spectrum defense permits the plant to ward off attack from a broader range of threats compared to a few highly potent compounds (20). The solution for many plants to resist predatory attack and invasion is to synthesize combinations of multi-targeted compound complexes, which is important because it decreases the development of resistance to monotarget drugs. An application of this theory in medicine would be chemotherapeutics commonly used in cancer therapy. The application of a symphony of lesser active phytochemicals would decrease the drug resistance by interacting with cancerous cells at multiple sites rather than only one and is a present means of therapy (20). The ability of a plant to synthesize a novel terpene composition may be a defensive adaptive response to prevent further

35 damage by creating compound(s) that a predator does not have defenses for within a population (107). Highly complex mixtures of compound within a plant that contain groups of compounds with different chemical and physical properties may allow for a much more rapid defensive response or a longer defense duration (108). Most diseases are multi-factorial, thus targeting a single disease cause using a single drug may not deliver satisfactory treatment results (20). Treatment of disease using multi-component drug treatments is considered advantageous for pleiotropic disease treatment relative to single-component drugs (109).

The treatment of illness with a variety of different compounds does bring with it the associated interactions between the phytochemicals as they may have either positive or negative biological effects and thus the complex blend of phytochemicals synthesized by plants must be examined to determine the cumulative effects of their interaction and associated cytotoxicity, mutagenicity, carcinogenicity etc. (110). The interactions of multi-component compounds may involve the protection of active substances such as antibiotics from enzymatic degradation, modify the transport properties of the substance across membranes, or circumvent multi-drug resistance mechanisms and signaling associated with xenobiotic compounds entering the cell when used as a whole extract compared to monocomponent treatment (111).

1.9 Essential Oils

Essential oils (EOs) are plant secondary metabolites that are volatile aromatic oily liquids derived from all plant organs including the bark, buds, flowers, fruits, herbs, leaves, seeds, twigs, roots, glandular trichomes, resin ducts and wood of plants (112-114).

36 Secretory tissues in a plant have been shown to contain a much higher concentration of terpenoids in tomato plants without being toxic (115). There are a number of both biotic and abiotic factors that are responsible for the fluctuation in plants that can be manipulated so that secondary metabolites can be produced in higher quantities. Also, plants can be genetically engineered by changing the genes controlling secondary metabolite production and modified to promote over expression, antisense expression or cosuppression of biosynthetic genes (96). Physicochemical constraints on the volatility of compounds produced and released by plants through various organs into the atmosphere is limited to low-molecular weight and largely lipophilic products (95).

These secondary metabolites are stored in secretory cells, cavities, canals, glandular trichomes or epidermic cells (113). They can serve as plant growth regulators, gene expression modulators and have potential roles as signal tranductors (116). Essential oils are lipid soluble and soluble in organic solvents. The ability for lipophilic planar secondary metabolites allows for intercalation between stacks of DNA bases and leads to a stabilization of the DNA double helix (105, 117, 118). Additionally, plant-derived secondary metabolites target and disrupt the cell membrane, intercalate into RNA or

DNA, and can bind and inhibit specific proteins (20).

Monoterpene and sesquiterpene hydrocarbons and their oxygenated derivatives

(constituted mainly of alcohols, aldehydes and ketones) are the general chemical components of volatile essential oil extracts (119) . These substances are derived from the metabolism of mono- and sesqui-terpenes, phenylpropanoids, amino acids and fatty acids

(120). Terpenoids are derived from mevalonate and isopentenyl pyrophosphate and are a

37 major component of the essential oil fraction of plant extracts where a diversity of terpenoid structures can be found (121). These low molecular weight compounds have some antioxidant activities in planta by being able to serve as quenching compounds for reactive oxygen species (122, 123)

At an industrial scale monoterpenoids can be used to synthesize sesquiterpenoids, which are composed of three five-carbon isoprene units (120). In addition to being useful for creation of flavors and aromas from an industrial aspect, they serve as deterrents for insect feeding, pheromones and phytoalexins (124). The development of a diverse group of secondary metabolites plays both a defensive role against herbivory, and pathogen attack but also allows for better inter-plant competition as attracting beneficial and symbiotic organisms (125). Sesquiterpenoids are produced in the cytosol, plastids, and mitochondria (126-128). Sesquiterpenoids can serve both as above ground signal molecules as well as below ground as in the case of attracting predatory nematodes in response to attack by Diabrotica virgifera virgifera(129). The structural configuration of the many terpenoids can vary quite a lot from species to species but within a specific species it usually has qualitative and quantitative variation among the varieties in a species (129, 130).

The two or three main components of the essential oil are used to characterize

EOs and may be at concentrations of 20-85% of the EO while the other components are present at trace levels (113, 120, 131, 132). Two groups of distinct biosynthetical origin exist in essential oils the first being terpenes and terpenoids and the other group consisting of aromatic and aliphatic constituents (133, 134, 134, 135). Terpenes are made

38 from combinations of 5-carbon-base isoprene units and are formed biosynthetically from isopentenyl diphosphate (IPP) precursor whose successive addition of IPPs to form the prenyldiphosphate precursor of various classes of terpenes (113). Modification of allylic prenyldiphosphate by specific synthetases is what forms the terpene skeleton which undergoes modification by enzymes to attribute functional properties to various types of terpenes (113). Monoterpenes and sesquiterpenes are the main terpenes but other forms exist such as hemiterpenes, diterpenes, triterpenes, and tetraterpenes. If any terpene contains an oxygen atom, it is then referred to as a terpenoid (113). Synthesis of sesquiterpenes from three isoprene units increases the number of cyclisations possible and allows for a large number of structures and enantiomers are commonly found (113).

Sesquiterpenes have structures that can be terpenic alcohols, carbures, epoxides, ketones, etc. (113).

Many essential oils contain monoterpenes and sesquiterpenes two compound classes that are good information carrying compounds due to their low-molecular weight, high vapor pressures at environmental temperatures, lipophilic structures and highly diverse structures allow for specific signaling to occur via changes in biosynthetic pathways (108). Monoterpenes containing a hydroxyl group have higher solubilities than mono and dicyclic terpene hydrocarbons in water (136). Terpene hydrocarbons due to low polarity have low solubility in water and will predominantly partition into the headspace of a sealed vial.

Despite the majority of compounds found in an essential oil occurring in trace amounts, some evidence supports that the minor components of essential oils have an

39 important role in antibacterial activity (135) as a result of synergistic effects of multiple compounds (105, 112). The exact composition of the essential oils has been found to vary from a particular species of plant according to the age, stress level, temperature, UV exposure, mineral nutrients, climate, season, plant organ, soil composition and vegetative cycle stage that it is collected and extracted (20, 105, 116, 137, 138). In addition to the effect of these factors on the composition of the essential oil components of a plant, the postharvest processing, extraction, and preparation may have a large influence on the final composition of an essential oil extract and as such should be standardized to minimize as much batch to batch variation as possible (20). These practices should be performed in accordance with good agricultural and collection practice (GACP) protocols, sustainable harvesting, and good manufacturing processes (GMP) to better provide a safer and more consistent product for consumers.

Wild harvesting medicinal plants is less ideal than cultivation in a mass production scale because the former can cause problems not only from the variation of composition, but variation in the bioactivities, biodiversity loss, misidentification of plants, differences of growth environment, and increased time to harvest and select plants that are of suitable age (96). Herbs harvested during or immediately after flowering produce essential oils with the highest antimicrobial activity (139, 140). Presently there are approximately 3,000 known essential oils, among which 300 are commercially important for agronomic, cosmetic, food, perfume, sanitary and pharmaceutical industries

(113). Intersample variability of a growing, harvesting, storage, extraction, identification and quantification method will occur due to the natural variation of the plant material

40 being used and as such much care needs to be taken to standardize plant age, development, light, nutritional and soil conditions, and time of day of collection even if clonal plant lines are used (95).

Commercial production of EOs is predominantly through use of steam distillation for its cost benefits (112). Several extraction techniques exist for essential oils including: headspace microextraction (HSME) (141), liquid-liquid extraction (142), simultaneous distillation extraction (5, 37, 38, 45, 50), solid phase microextraction (SPME) (69, 143-

145), solid phase extraction (146), and Soxhlet extraction (147) .

Extraction at low temperature using super critical carbon dioxide is also another means of extraction with preferential chemical and physical properties (119). Benefits of supercritical fluid extraction (SFE) is that this process maintains an organoleptic profile that is more similar to the starting material than solvent extraction and is devoid of colorants, fatty acids, resins, and waxes which would require subsequent clean up steps to remove (119). Differences in organoleptic profiles between the methods of extraction of the essential oils indicate differences in the composition of oils obtained from different methods of extraction and may influence the properties of the oil and its bioactivity(112).

Individual compounds can be isolated from the complex mixture of compounds in an essential oil by crystallization or distillation (120). The extraction method applied to separate and analyze essential oils is critical in the chemical profile of essential oils. The extracted chemical profile is what an analyst will ultimately determine as the volatile components from the plant. Important factors which influence the data collected are the environmental conditions of the collection chamber, light intensity, temperature, relative

41 humidity, gas composition of the environment, state of hydrolysis, as well as the kinetic rate at which extraction takes place (95).

Due to their volatile nature, detailed compositional analysis can be achieved by gas chromatography and mass spectrometry of the essential oils. Principle means of essential oil identification presently is through direct injection of the essential oil, solid phase micro extraction (SPME), purge and trap, dynamic headspace sampling, and static headspace sampling.

1.10 Essential Oil Modes of Action

Essential oils and their large number of constituents can be used to identify the means through which they act on cells, but detailed assays must be conducted in order to draw conclusions. Essential oils as a whole appear to have no specific cellular targets and typically are described in broader terms such as antimicrobial, antiviral etc. (148). The lipophilic nature of essential oils allows them to diffuse and pass through the cell wall and cytoplasmic membrane disrupting layers of polysaccharides, fatty acids and phospholipids permitting the layers to become permeable (113). The nonpolar components in an essential oil allow for diffusion across the biomembrane while the phospholipid membrane is impermeable for polar and charged molecules (149), of which their principle targets are cell membranes. The toxicity of terpenes can be associated with the loss of chemiosmotic control (150, 151). The permeabilization of membranes, especially in the mitochondrial membranes, can lead to cellular apoptosis and necrosis

(152, 153). Changing the degree of fluidity of a membrane can result in leakage of radicals, cytochrome C, calcium ions and proteins (113). Depolarization of the

42 mitochondrial membrane by reducing the membrane potential, ionic Ca2+ cycling (154-

156) and additional ion channels will reduce the pH gradient and thus have adverse effects on the levels of ATP generated through cellular respiration. Small lipophilic secondary metabolites can be trapped by biomembranes, which interact with the hydrophobic tails of the phospholipid membrane and can influence membrane fluidity as well as the lipophilic core of proteins causing conformation changes (105). The use of terpenes in drug formulations and treatment allows for enhanced drug delivery activity by increasing the means through which bacteriocidal compounds can enter and kill cells.

In nature, essential oils function as protectants of the plant as they have a variety of useful roles as antibacterials, antifungals, antivirals, and insecticides (113). Essential oils have been used in food as flavoring ingredients, and in other areas as perfumes, aromatherapeutic agents and pharmaceuticals. The cytotoxic properties of essential oils are of great interest not only for control of cancer, pathogens and parasites but also in treating parasites (113). The primary compounds responsible for the biological cytotoxicity of compounds are terpenic alcohols, aldehydes and phenols (157, 158). The degree of cytotoxic activity is dependent on the state of cell growth, for example, dividing yeast cells were more sensitive than other stages of growth (159). Essential oils have been found to have effective control of many types of organisms including bacteria, viruses, fungi, protozoa, parasites, acarids, larvae, worms, insects, and mollusks (113). In addition to having a variety of modes of action, the effectiveness of essential oils on cells is dependent upon the growth phase of the cells (113). The damage sustained to mitochondria and the mitochondrial DNA of mother cells is one way through which

43 essential oils act and can help control cell proliferation (159).The mode of application of the essential oil as a cytotoxic solution likely has an effect on the bacterial susceptibility or resistance in addition to the nature of the cell membrane (160). The ability to increase permeability of cell membranes also offers a means to use it in conjunction with traditional antibiotics to facilitate the control of bacteria and pathogens more appropriately (160).

Essential oils have also shown promising cytotoxic activity of mammalian cells in vitro using a variety of tests including Neural Red Uptake (NRU) test (161), MTT (3-

(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide Test (162), Alamar Blue

(24, 25), Hoechst 33342 (163), and propidium iodine (163) tests. The cytotoxicity in mammalian cells is caused by induction of apoptosis and necrosis (113). Most essential oils have been found to possess nonmutagenic and cytotoxic activity at treatment dosages which may suggest that most are devoid of carcinogenicity (113). The majority of essential oils being free from long-term genotoxic risks provides a big advantage in treating illness and ailments (113).

Antioxidant capacity of essential oils is another aspect of which they interact in vivo and can help quench radical species in the body preventing the damaging of effects of lipid oxidation, protein oxidation and DNA damage (113). The antioxidant property of essential oils is often determined in vitro by physical-chemical methods including: peroxide value, thiobarbituric acid reactive substances (TBARS), Kreis test, anisidine value, ABTS assay, total radical trapping antioxidant parameter (TRAP), phycoerythrin assay, electron spin resonance (ESR) spin-trap test, 1,1-diphenyl-2-picryl-hydrazyl

44 (DPPH) test, total phenolic content (TPC), oxygen radical absorbance capacity (ORAC)

(164, 165).

The antioxidant properties of essential oils in vitro have suggested their beneficial consumption and use for human health. Dietary intake as well as through other means of introduction to the body has brought forth the ability for additional bioavailability to quench radicals generated through oxidative stress reactions and have antimutagenic

(166), and anticarcinogenic activity due to their ability to scavenge radicals (167-170).

The state of cellular redox status of terpenic and phenolic compounds in essential oils may lead to cell apoptosis and necrosis causing cytotoxic effects by damaging proteins and DNA (113, 171). The state of an antioxidant quenching an oxidative radical and in turn becoming a radical occurs at low antioxidant concentrations (172). It is hypothesized that the permeabilization of mitochondrial membranes may be the primary event that converts the antioxidants into prooxidants of essential oil antioxidants (113).

1.11 Secondary Metabolite Synergy

The nature of how secondary plant metabolites interact in vitro and in vivo in humans may be significantly different and thus animal modeling provides some additional insight into the means through which secondary metabolites exhibit bioactivity. The bioactivity of a plant is typically compared on the basis of the composition of the compounds extracted. While some purified forms of medicinal herbs are simply extracted, others may be purified to yield the sole chemical of interest from a

45 natural source. The synergistic activity of whole plant extracts compared to that of single chemical extracts has been difficult to define and there have been multiple means through which a clear definition has been attempted (106, 110, 173). Significant synergy is defined as at least a two-fold increase in activity of a whole extract relative to a fractionated one (173). The composition of essential oils has a great effect on the effectiveness of the oil as the minor compounds may have a large effect on the cell permeability characteristics of an essential oil or essential oil and specific drug treatment

(174). The additional trace components in an essential oil may have important characteristics by modifying its solubility, density, fragrance, texture, color, cellular distribution, membrane composition and fixation and permeability properties (113).

There are differences in ways that positive interactions can be defined and as such there is a varying degree of difficulty in defining the effects of multicomponent plant extracts and the positive effects they have over individual compounds. Potentiation is the positive interaction between compounds that enhance the potency of a bioactive compound by an inactive adjuvant substance (20). Additive effects can be defined as the combined outcome of substances is equal to the sum of the individual components while synergy is used to define the combination of multiple components having a greater effect than the sum of the individual components (20). Antagonism occurs when combined substances have an effect that is less than the sum of the individual components (175,

176). In defining synergy, the most frequently used method is an isobologram used to determine the iso-dose of two drugs and compares them to determine the interaction between the two (177).

46 Problems associated with defining the synergistic effects of plant extracts can be due to plant material processing, differences in protocols used in a clinical setting relative to native use, poor fractionation, chemical oxidation, poor biological assays and models, degradation of bioactive chemicals during extraction, fractionation, and storage (178,

179). The use of multiple compounds as found in a whole extract relative to a group of pure drugs separated from plants rarely have the same level of bioactivity at a same dose concentration as compared to a whole plant extract (179). The whole extract with multiple compounds working synergistically can be beneficial as it eliminates possible problematic side effects that are associated with a single xenobiotic compound in the body. In addition to saving time and money from further separation and processing, many whole plant extracts contain multi-drug resistance (MDR) inhibitors (178). The compounds that offer MDR often have little or no direct antimicrobial or cytotoxic effect.

When they are combined, their activities may yield a much higher level of antimicrobial activity (180). Pharmacodynamic synergy involves a number of different substances acting at different target receptor cites to enhance the therapeutic effect of treatment medicine by improving bioavailability, reversal of resistance, modulation of adverse effects, changing membrane structure and susceptibility, decreasing metabolism and decreasing excretion of the main active phytochemical in treating a disease (178).

Extracts or single component drugs can stimulate the degree of immunity and may be able to contribute to treatment and prophylaxis of malaria, viral, bacterial, parasitic, and fungal diseases (181, 182). So long as complete plant extracts do not contain potentially toxic compounds to the host being treated at therapeutic dosages, the necessity for further

47 clean up steps does not necessarily justify the loss of the bioavailability of the extracts and thus it is important to assess the toxicity of the whole prior to analysis of single chemicals (178).

Bioavailability and metabolism of medicinal compounds in vivo can be affected by the composition of plant constituents through inhibition of pump mechanisms for elimination of the drugs, modification of absorption, distribution, metabolism and excretion of active constituents, and changing the permeability of membranes to cytotoxic components (178). The physical and chemical reasons for positive interactions between multi-component mixtures can be due to a change in one of the following possible ways: bioavailability, cellular transport process interference, deactivation of active compounds to inactive metabolites, activation of pro-drugs, signal cascade interference, protein modification inhibiting binding just to name a few (183). Plant secondary metabolites may function in humans by resembling endogenous hormones, ligands, metabolites, neurotransmitters, or signal transduction molecules; additionally, by having similar structures to endogenous compounds, they have the ability to interact in vivo with potential target sites (116). As beneficial actions of medicinal plants are related to the specific combination of bioactive phytochemicals in their composition, the addition or deletion of a single component of this mixture could adversely affect the efficacy of a natural based pharmaceutical (96). These factors all play a role in the efficacy of the particular plant extract on the immune system of the host in suppressing or eliminating the cause of the disease (182).

48 In natural product research, the extraction of a single compound in particular from essential oils is not directly accomplished without additional clean up and separation steps after initial extraction. Although the primary compounds may account for the majority of the chemical composition, the presence of trace compounds cannot be ruled out as having a synergistic role in interacting with the mixture as a whole (184). A proposed synergistic effect would be if the compounds in the mixture facilitate the uptake of polar compounds into the cell or possess the ability to inhibit defense systems that inactivate xenobiotic toxins (105).

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65 CHAPTER TWO

ATMOSPHERIC SIMULTANEOUS DISTILLATION SOLVENT EXTRACTION OF

ESSENTIAL OIL OF OPLOPANAX HORRIDUS LEAF AND BARK

Abstract

Secondary volatile metabolites that compose the essential oil were isolated by atmospheric simultaneous distillation-solvent extraction (SDE) from the bark and leaves of Oplopanax horridus. Dichloromethane (DCM) was employed as the organic phase in

SDE. A nonpolar DB-5MS column was used to separate the volatile compounds in the gas chromatograph (GC). The extracts were analyzed by capillary gas chromatography with mass spectrometric detection. Compounds were identified according to their non- isothermal Kovats indexes, mass spectra, or by comparison with analytical standard substances. The bark essential oil was a pale yellow oil that had a higher average yield

(w/w) of 0.96±0.06% whereas the leaf extract had a lower essential oil yield of

0.15±0.04% and had a darker brown color. The bark and leaf essential oil extracts were rich (>65% composition) in sesquiterpenes. (E)-nerolidol, τ-cadinol, β-farnesene found in the bark oil and (E)-nerolidol, ar-curcumene, and β-sesquiphylledrene in the leaf oil were important compositional compounds in the essential oils contributing more than 5% of the oils.

2.1 Introduction

Identification and quantitation of plant volatile compounds has growing interest as the volatile compounds that make up the essential oil of a plant extract have ever

66 increasing identified biological activities and serve not only as aromatherapeutic agents, but also biological signaling, antifeedant, insecticidal, antifungal, antibacterial, anticancer agents and other additional areas of interest to manufacturers (1, 2). Oplopanax horridus is an important spiritual and medicinal plant to inhabitants of northwestern North

America and belongs to the family Araliaceae. O. horridus, commonly referred to as devil’s club, is an understory shrub that can be commonly found in the northwestern

United States and in western Canada. It is found predominantly in Alaska south to the central part of Oregon and is found eastward to the Canadian Rockies, Montana and

Idaho. The plant is an erect to slightly spreading deciduous shrub that is from one to three meters in height, is sparsely branched with dense spines on the stems, has prominent leaf veins, upright to decumbent stems covered with yellow to brown spines that have large palmately lobed leaves that grow spirally around the stem (3-5).

O. horridus has small green to white flowers, in terminal pyramidal clusters that bloom and ripen to shiny flattened bright red berries between June and July that persist over the winter (3, 4). This native plant belongs to the family Araliaceae, which also contains prominent medicinal plants including Asian ginseng (Panax ginseng), American ginseng (Panax quinquefolius), and eleuthero (Eleutherococcus senticos) formerly called

Siberian ginseng (4, 6). Nearly all species within the Panax genus are used as traditional herbal medicines; additionally, they are erect, perennial, herbaceous plants with permanent aerial, woody stems and may be suggestive of its biological use due to activity that may be of genetic relationships between species in the same genus (5). The botanical relationship to ginsengs has raised interest in commercialization of O. horridus

67 as a source of phytochemicals to assist in the treatment of ailments and illness (4). The traditional preparations of O. horridus include decotions, ash, tonics, and tea, which are prepared from the roots, inner bark, and outer bark (4). These different forms of extracts have been used to treat arthritis, cancer, colds, headaches, flu, illness treated using a purgative, tuberculosis, stomach ulcers, respiratory illnesses, and wounds (7). Volatile analysis of O. horridus was first performed by Garneau et al. in 2006 using steam distillation as means for extraction of stem and root bark essential oils. O. horridus liquid extracts have provided some evidence of the traditional uses of ailments and has been found to have anti-mycobacterial, antimycobacterial (8, 9), antibacterial (9, 10), antifungal (9, 11), and antiviral (12) activities.

Volatile organic compounds (VOCs) are released by plants for a host of physiological and biological reasons. The leaves, flowers, and fruits release these small molecular weight compounds into the atmosphere and soil directly in contact with the plant. Essential oils are secondary metabolic end products produced by plants, and are principally composed of terpenes and terpenoids including monoterpenes, sesquiterpenes, as well as aromatic derivatives of mono and sesquiterpenes. Essential oils are used not only as pharmaceutical components but also can be found as use in cosmetics, soaps, detergents, perfumes, packaging films, beverages, sauces, candles and more. Many of the more complex VOCs synthesized by plants are commercially used as flavors and fragrances (13). The biologically synthetic VOCs are important as signaling molecules as well as defense compounds but only when there is a use for them as the synthesis could cause unwanted side effects such as depletion of specific resources that could otherwise

68 be used for growth, which in many environments any process that take away from the ability to access nutrients and light burning through carbon stores is detrimental to the survivability of the plant.

Essential oils are complex in nature, which primarily are composed of volatile monoterpenes and sesquiterpenes and their oxygenated derivatives as well as alcohols, aldehydes and esters (14). The ability to determine volatile components in substances is important in many industries as a source of quality control, identity validation, and safety.

There are many extraction techniques that can be employed to extract the volatile fraction from a complex matrix which include: steam distillation, liquid-liquid extraction, liquid- liquid extraction with ultrasound, simultaneous steam distillation extraction, solid-phase extraction, purge and trap, headspace sampling, and solid phase microextraction (SPME).

The role of Traditional Chinese Medicines (TCMs) has played an important role historically in drug discovery and clinical therapy due to high bioactivity, low toxicity and rare complications of medicine interaction (15). In many TCMs such as Panax ginseng, there are active components in their essential oils. Bioactivity can be measured in a number of ways using in vitro cancer cell lines, bacteria, viruses, chemical systems, enzymes, in vivo bioassays and many others. The measurement of bioactivity of TCMs can serve as a baseline for therapeutic levels much the same ways as identifying the chemical compounds found in a TCM as a fingerprint of identity.

69 2.2 Materials and Methods

2.2.1 Chemicals:

Certified A.C.S. grade anhydrous sodium sulfate and high performance liquid chromatography grade methylene chloride (DCM) were purchased from Fisher Scientific

(Norcross, GA, USA). Standards of alkanes (C8-C20), nerolidol (purity >98%), and farnesene (purity >99%), were purchased from Sigma-Aldrich (St. Louis, MO, USA).

Water was supplied using a Millipore Synergy UV system (Millipore Billerica, MA,

USA).

2.2.2 Plant Material

The leaves and stem bark of Oplopanax horridus were wild harvested near

Anchorage, Alaska, under the auspices of David Smith. Samples were collected between

June and August and were air dried prior to being shipped to Clemson, SC for chemical characterization. Characteristic samples of the stems have been retained as voucher specimens.

2.2.3 Sample Preparation

Samples were allowed to air dry to a final moisture content of 8% by weight. The air dried outer stem bark and leaves were ground using a Thomas-Wiley Laboratory Mill

Model 4 (Swedesboro, NJ, USA) at 25°C with a final screen size of 2mm yielding finely ground O. horridus bark and leaf samples. The samples were ground in <50g batches and the mill was operated in a 25˚C environment. Samples were stored in air tight zippered bags which were then placed inside heat sealed plastic bags. The finely ground samples were stored at -20˚C in the dark until they were ready for essential oil extraction.

70 2.2.4 Isolation of the volatile oils

A Likens and Nickerson (16) type simultaneous distillation and solvent extraction

(SDE) apparatus was used to extract volatiles from the plant matrix. An amount of 25.19 grams of the ground O. horridus bark was weighed and loaded into a 1L round bottom flask containing 500mL millipure purified water. Glass beads were added to the flask to decrease foam formation. The sample and solvent were stirred until evenly dispersed and attached to the appropriate arm of the SDE apparatus. A volume of 250mL of DCM was loaded into a 500mL round bottom flask and attached to the other arm. The solutions were heated to the point of reflux and allowed to distill and extract for 3 hours. The condenser of the SDE column was cooled using water with a circulation pump at ~0˚C using water. After three hours, the heating elements were turned off and the samples were allowed to cool to room temperature while still attached to the SDE apparatus lasting approximately 2.5 hours. Then, the solvent fraction was collected from the neck of the

SDE apparatus into the organic solvent flask. The volatile compounds in the DCM were then filtered through anhydrous sodium sulfate contained in a Whatman #4 filter and collected in a 500mL round bottom flask. The solution was attached to a Brinkman Buchi

Rotavapor rotary evaporator and concentrated to a volume of approximately 50mL. The solution was then transferred to a 100mL round bottom flask and 20mL of stock DCM was used to rinse the 500mL flask and the rinsate was added to the 100mL flask. The solution was concentrated to approximately 10mL and then poured into a 25mL flask.

Ten mL of the stock DCM was used to rinse the 100mL flask and the rinsate was then added to the 25mL flask. Once the solution was concentrated to a volume of

71 approximately one mL it was then transferred via micropipette into an amber headspace vial and concentrated under Nitrogen until it maintained a stable weight. The essential oil was then calculated based upon a dry weight basis. The extracts were diluted with 1mL of

DCM and appropriate dilutions were carried out for analysis. Samples were stored in

1.5mL amber glass vials, and sealed with polytetrafluoroethylene (PTFE)/silicone septums with appropriate open centered screw cap lids. Samples were stored in a -20˚C freezer in the dark until time of analysis. O. horridus leaf extract was prepared in the same method as mentioned above. SDE experiments for bark and leaf were extracted in triplicate and the mean values of composition were used for statistical comparisons.

2.2.5 Gas Chromatography Mass Spectrometry Analysis

An aliquot of 0.5µL of the volatile extracts was manually injected using the splitless mode (into a Shimadzu GC-17A Gas Chromatograph coupled to a Shimadzu

GCMS-QP5050A Mass Spectrometer, which was equipped with an Agilent J&W (Santa

Clara, CA) DB-5 (5% Phenyl, 95% methyl silicone) capillary column (60m x 0.25mm ID x 0.25µm film thickness). Ultrahigh Purity (UHP) helium (99.999%) was the carrier gas with a flow rate of 0.9mL/minute under a column pressure of 105.5 kPa. GC oven conditions were set as follows: initially 50˚C for 2 minutes, increasing at 5˚C/min until

150˚C, held for 2 minutes, then increasing at 1˚C/minute until 220˚C then held for ten minutes. The mass spectrometer was set to scan with a frequency range of 40 to 350 m/z with a cut off time of 10 minutes. All mass spectra were collected using electron impact mode (70eV) and 250˚ ion source temperature.

2.2.6 Identification and quantification of volatile components

72 In this study the identification of each peak was based on Kovats retention index

(KI) as well as the mass spectra of the compounds using the NIST, Wiley 7, and

Shimadzu Terpene and Terpenoid reference libraries. A series of alkane standards diluted in hexane were run independently in triplicate to determine the retention time of the C8-

C20 alkanes which would be used for calculating the non-isothermal KI values. Non-

()ttxn isothermal KI values were calculated using the equation KI x 100n 100 ()ttnn1  where n is the number of the alkane hydrocarbon, tx is the retention time of the unknown sample, tn is the retention time of the alkane elution before the unknown and tn+1 is the retention time of the alkane eluting after the unknown. Correction of manual injection deviation in retention times between sample analyses was made by adjusting the retention times based on the shift in the alkane standard. The KI values in Table 2.2 were calculated based on the average elution time of the alkanes.

The identification of compounds was based upon the following methods: (1) their

Kovat’s retention indices (2) GC-MS retention indices (authentic chemicals), and (3) mass spectra using NIST 08 (National Institute of Standards and Technology,

Gaithersburg, MD, USA), Shimadzu Terpene and Terpenoid (Shimadzu, Tokyo, Japan), and Wiley 08 (Wiley, New York, NY, USA) mass spectral library collections. Primary identifications were made by comparing their respective KI values as well as their mass spectra with those reported in literature (17-38).

Compounds whose reported KI values are identical or very close to each other were assigned identical values based upon the observed GC data; additionally, the

73 identification of compounds of the same KI value are identified in conjuction with the agreement between their experimentally observed and reported mass spectral data.

Identification was considered tentative when only the mass spectral identification was made. The identification of compounds with a KI value of less than 900, or the equivalent of nonane, was not possible due to the tailing peak of the solvent.

2.2.7 Statistical Analysis

A completely randomized design was used to perform triplicate extractions of bark and leaf oils. The statistical analysis comparing the percent composition of bark and leaf essential oils was done using a paired t-test was calculated using SAS 9.3 (SAS

Institute Inc. Cary, NC, USA). A significance level of α=0.1 was used. Any p-value less than 0.1 was considered significantly different with the degree of significance indicated.

2.3 Results and Discussion

The essential oil composition of O. horridus is given in Table 2.2. The GC-MS analysis led to the identification of 32 and 45 spectrally unique compounds in the bark and leaf essential oils respectively which is similar to the number of compounds identified in the bark previously (3). Identification of 84.476% of the total percent composition of the bark was possible where as 93.823% of the leaf oil compounds were identified. The extraction of the stem bark essential oil from O. horridus using SDE yielded 22 tentatively identified new compounds for the first time in the stem bark. The leaves of O. horridus have not been previously studied. Of the 32 compounds whose mass spectra was collected, only one was found in only trace levels (≤0.1%). None of the

45 leaf oil compounds were found at trace levels.

74 In this study, highly significant qualitative and quantitative similarities and differences were observed among the essential oils obtained from the bark and leaves.

The bark essential oil was pale yellow and had a higher average yield (w/w) of 0.96% whereas the leaf extract had a lower yield of 0.15% (w/w) and was a darker brown color.

Extraction of volatiles from the bark using SDE with DCM as a solvent provided a higher mean yield (0.96% w/w) compared to the hydrodistilled bark extract which yielded

(0.23% w/w) (3). A likely cause for the higher yield concentration is the much larger condenser area of a Lickens-Nickerson apparatus compared to a typical Clevenger apparatus and more complete condensation of the volatiles from the gas phase into the liquid phase is possible. Additionally, SDE using DCM as a solvent was shown to have the ability to extract and recover a greater quantity of compounds than simply using steam distillation (39).

The principle components (>5%) of the oil from the bark were (E)-nerolidol

(41.825%), τ-cadinol (11.930%), unknown 9 (6.503%), unknown 13 (5.742%), and β- farnesene (5.386%); in the leaf oil the principle components were (E)-nerolidol

(19.050%), ar-curcumene (9.838%), τ-cadinol (9.908%), and β-sesquiphylledrene

(5.824%). Sesquiterpenes were the predominant compound class in both the bark and leaf essential oils with 18 and 20 identified compounds respectively. Those 18 sesquiterpenes account for 72.841% of the bark essential oil. The five unknown compounds in the bark account for 15.524% of the essential oil while the remaining compounds are 4 aldehydes

(7.238%), 3 carboxylic acids (3.864%), 1 ketone (0.881%) and 1 acetate (0.235%). In the leaf essential oil, 20 sesquiterpenes account for 69.146% of the total composition. 8

75 aldehydes, 6 carboxylic acids, 5 unknowns, 3 ketones, 2 monoterpenes, and 1 alcohol accounted for 10.863%, 7.248%, 6.177%, 2.396%, 1.299%, 2.873% respectively.

Sesquiterpenes are the principle compound class for both the bark and leaf essential oils extracted using SDE. The quantity of aldehydes is greater in the leaves (8) than in the bark (4). Both the leaf oil and bark oil had 5 unidentified compounds, none of which were the same. The bark extract had half the number of carboxylic acid compounds when compared to the bark. The leaf oil had three ketone compounds while the bark had one identified. Two monoterpenes, geraniol and 10-(acetylmethyl)-(+)-3-Carene, were identified in the leaf compared to zero monoterpenes identified in the bark. The bark had one acetate compound, n-Octyl acetate, while the leaf did not; however, this was the opposite of compounds classified as alcohols where one volatile, phenylethyl alcohol, was identified in the leaf and none were identified in the bark.

Similar to this study, Garneau et al. (2006) identified 36 and 26 compounds respectively when investigating the hydrodistilled stem bark and root bark. Three principle compounds (>5%) in the stem bark oil were (E)-nerolidol (54.5%), bicyclogermacrene (10.4%), and τ-cadinol (9.6%) while in the root oil there was (E)- nerolidol, τ-cadinol, and γ-cadinene (6.4%). The compositions of the essential oils are different between the extracts from hydrodistillation (HD) and SDE. There are 7 stem oil components that are found at trace levels and five trace level compounds in the root essential oil extracted using HD while there is only one in the bark and none in the leaves in the SDE extract. There are fewer minimal compounds (0.1% < X < 1%) in the hydrodistilled extracts, for which the stem oil has 16 and the root oil was found to contain

76 13. In the present SDE study, there are 18 in the bark and 23 in the leaf. In the hydrodistilled essential oils, there are 9 minor compounds (1%≤ X < 5%) in the stem oil and 5 in the root oil whereas there are 8 in the bark and 18 in the leaf extracted using

SDE. There are fewer primary compounds (≥5%) in the hydrodistilled stem and root oils with only three primary compounds each, where as the SDE extracts have 5 primary compounds in the bark and 4 in the leaf.

The results in Table 2.2 show that the compounds of essential oils are dependent upon the tissue of the plant extracted. There were more compounds isolated from the leaf compared to the bark and this is likely due to the fact that the majority of VOCs are synthesized in the leaves as there is a large supply of enzymes, carbon, and ATP available for synthesis. While the four primary compounds in the leaf essential oil account for 44.62% of the total composition, the 18 minor and 23 minimal compounds account for 40.415% and 14.965% respectively. The absence of trace compounds suggests that at the time of harvest there were sufficient levels of the same secondary metabolites that were necessary for plant defense, animal attractant, and inter-plant signaling.

SDE of leaf and bark yielded essential oils that had 17 compounds that were found in both the essential oils and were evaluated for their percent composition using a paired t-test and can be found in Table 2.4. The seven compounds that were not significantly different were hexanoic acid, nonanal, octanoic acid, β-farnesene, δ- cadinene, spathulenol, and cubenol. Hexanoic acid in the SDE extract was found to have a mean in the bark of 1.262% and 0.736% in the leaf. Due to the large standard deviation

77 of the bark oil in the triplicate extractions, the difference between the compounds were not significantly different (p=0.570). Nonanal was found to be 0.460% in the bark and

0.602% in the leaf and there was a higher standard deviation of composition in the bark which likely caused the difference in between the triplicate of bark and leaf samples to not be significantly different (p=0.261). Octanoic acid levels for the bark were higher in the bark (2.510%) than in the leaf (2.357%) and as with many of the lower molecular weight compounds had a higher standard deviation of mean percent composition in the bark than the leaf. β-Farnesene composed 5.386% of the bark while 2.885% of the leaf and had the second highest percent standard deviation of 3.049% and due to the influence of one very high extraction composition (9.166%) compared to the other two (3.182% and 5.160%). The difference of β-farnesene percent composition between the bark and leaf was undetectable using the present sample size of three replicates per extraction

(p=0.178). δ-cadinene was identified to have 0.434% in the bark and 0.393% in the leaf and were not significantly different (p=0.352). Spathulenol which accounted for 4.659% of the bark and 4.718% in the leaf had a much larger standard deviation in the bark oil

(0.600%) compared to the leaf which was (0.146%) and was not significantly different in the SDE essential oils (p=0.881). Cubenol did not have significantly different composition in the SDE extracted essential oils as it accounted for 0.916% of the bark and 0.913% of the leaf oil. The very similar percent composition and similar standard deviations is one of the reasons that it had the highest p-values (p=0.972).

Ten of the 17 compounds were significantly different ( α=0.10) between the two sample tissues from O. horridus. Octanal, 2-nonanone, nonanoic acid, ar-curcumene, α-

78 farnesene, β-bisabolene, cis-γ-cadinene, (E)-nerolidol, τ-cadinol, and α-cadinol had statistically significant percent compositions in the two essential oils. Octanal was identified and found at different levels (p=0.060) of 4.363% in the bark 2.319% in the leaf. 2-Nonanone, a ketone, was 0.881% in the bark and 1.066% in the leaf, which were seemingly similar but were statistically significantly different (p=0.070). Nonanoic acid which was found at levels of 0.092% in the bark and 1.360% in the leaf were statistically different (p=0.010); however, the bark sample had a very high standard deviation of

0.108% and led to high sample to sample variability which was higher than the mean level of the compound. The compound ar-curcumene, had highly different amounts

(p=0.002) accounting for 0.311% and 9.838% in the bark and in the leaf respectively. α-

Farnesene was identified and found at different levels (p=0.080) of 2.149% in the bark and 0.419% in the leaf. β-Bisabolene which was found at levels of 0.440% in the bark and 3.504% in the leaf were different (p=0.001) and this was the smallest p-value indicating the highest degree of confidence in the compositional difference between the

SDE extracts. The compound, cis-γ-cadinene, had different amounts (p=0.080) in the bark and in the leaf accounting for 1.284% and 0.783% respectively. (E)-Nerolidol was found at levels of 41.825% in the bark and 19.050% in the leaf. They were moderately different (p=0.02). The compound τ-cadinol had highly different amounts (p=0.002) in the bark and in the leaf at levels of 11.930% and 9.908% respectively. The amount of α- cadinol which accounted for 0.224% of the bark essential oil and 1.594% of the leaf essential oil was highly different (p= 0.007).

79 Existing literature (3) on O. horridus essential oils are presented as means and do not have presented standard deviations so drawing exact statistical comparisons is not possible. However, generalized comparisons can still be made to the extracted essential oils using the SDE and the hydrodistillation extraction methods. Hexanoic acid, nonanal, octanoic acid, octanal, 2-nonanone, nonane, nonanoic acid, β-bisabolene, and cis-γ- cadinene were not identified previously in the hydrodistilled stem bark and root bark essential oils (3). The work of Garneau et al. 2006 will be used for comparisons of SDE extracts to the hydrodistilled extracts (3).

There are a few instances where the levels of the SDE extracts have similar compositional properties as the hydrodistilled stem bark oil and root bark oils. The cubenol concentration of approximately 0.913% for both bark and leaf SDE extracts was lower but possibly the same as the reported values of 1.2 and 1.7% in the stem and root oils. τ-Cadinol which was found to be 9.908% of the leaf SDE oil appears to be very similar to the levels found in the existing stem bark hydrodistilled oil 9.6% although it is significantly different from the SDE bark oil. Although there were some similarities, the compounds that could be compared between the extraction methods based upon percent composition are more numerous.

The levels of β-farnesene extracted from the leaf and bark both appear different, and are above the reported values of the stem bark essential oil which had 0.9% composition. Ar-curcumene which was found in the HD stem oil in 0.2% composition was found in a little bit higher levels in the SDE bark oil (0.311%) but in much greater quantities in the SDE leaf (9.838%). α-Farnesene’s SDE levels of 2.149% was higher

80 than the reported levels of 1.2% in the HD bark oil. The levels of α-farnesene in the leaf

(0.419%) were less than either of the bark oils. δ-Cadinene also appears to be different and much lower, as the SDE samples yielded 0.434 and 0.393% in the bark and leaf respectively compared to the stem oil of 2.5% and the root oil 3.9% in the HD oil. (E)-

Nerolidol which was the principle component in all four essential oils yielded lower amounts of 41.825 and 19.050% in the SDE bark and leaf extracts of respectively when compared to the very similar hydrodistilled stem and root oils of 54.5 and 54.6% respectively. Spathulenol was accounted for approximately 4.7% in each the leaf and bark extracts using SDE which are much higher than that found the HD stem and root oils of 0.7% and 2.6%. τ-Cadinol which was found to be 11.930% of the bark SDE oil is less than that of the reported HD rootbark oil (16.9%) and appears different. α-Cadinol which was 0.224% of the SDE bark was lower than the 0.6% hydrodistilled bark and 0.4% root essential oils which are lower than the 1.594% of the SDE leaf oil. The principle compound bicyclogermacrene which was 10.4% in the HD stem oil and was a major component accounting for 4.4% in the HD root oil was not identified in either of the SDE extracts.

Most essential oils have been found to be cytotoxic without being mutagenic (40).

Due to lipophilic nature of terpenoids, there is an affinity for and partitioning within the lipid bilayer in biological membranes which may significantly impact both the structural and functional properties (41). This is a likely cause for the ability to increase permeability to extracellular compounds such as ethidium bromide and antibiotics (42).

81 The stem bark extract was found to have the same two primary compounds (E)- nerolidol and τ-cadinol as those previously reported but have different percentages of composition (3). The process of simultaneous distillation and extraction yielded fewer identified compounds (34) than the essential oil extract prepared by hydrodistillation

(41). Unknowns 9 and 13 were not able to have their structures identified. β-Farnesene which composes 5.836% of the stem bark is synthesized via the Mevalonic acid (MVA) pathway and serves as an alarm pheromone (43). It is also produced following tissue damage in glandular trichomes, secretory cells, mesophyll and root wounded tissues (44).

Predominant volatiles in the leaf essential oil, such as (E)-nerolidol, ar- curcumene, τ-cadinol, and β-sesquiphylledrene are important signal compounds and have different bioactivities. Ar-curcumene is a sodium channel blocker in neuron membranes

(45), inhibits ergosterin biosynthesis (45), inhibits RNA polymerase (45), and has antifeedant (46), antiulcer (47), antirhinoviral (48) activities. β-Sesquiphylledrene has been shown to have antioxidant activity using a DPPH bioautography assay (49).

Zingiberene, which is a common constituent of Zingiber officinale accounting for 4.569% of the leaf essential oil has antiulcer (47) and antirhinoviral, (48) activity. Himachalol provided increased protection against invasive aspergillosis (50) as well as having antispasmodic activity (51).

Nerolidol (3-hydroxy-3,7,l 1-trimethyl-l,6,10-dodecatriene) was the principal component of the bark and leaf essential oils. Nerolidol is a major acyclic sesquiterpene alcohol (isoprenol) found in nature (52). It is a non-toxic and non-sensitizing (53) sesquiterpene alcohol that is generally recognized as safe (GRAS) (42, 54) and is

82 approved by the Food and Drug Administration (FDA) as a flavor (21 CFR 172.515) (55) with annual use in the region of 10-100 metric tons (53). Nerolidol has anti-leishmanial

(54), antineoplastic (52), anti-protozoal (56, 57), anti-malarial (56, 57), anti-fungal (58) anti-ulcer (59), sedative properties (60), and trypanocidal (61) effects. It has also been found to significantly decrease the effect of DNA mutations from azoxymethane resulting in fewer rats developing adenomatous polyps of the large bowel and fewer polyps per rat when orally ingested (52). Nerolidol was found to enhance skin penetration of 5- fluorouracil which suggests it could be used in improving the transdermal delivery of therapeutic drugs (62).

The high degree of unsaturation in nerolidol in its chemical structure can suggest its high degree of biological activity when compared to other compounds in the same group (61) and its terminal methylene can react with sulfhydryl groups in proteins which enhances the bioactivity of this compound (63). Inhibition of biosynthesis of dolichol, ergosterol and ubiquinones by nerolidol in Listeria amazonensis suggests that nerolidol is an inhibitor at an early step in the isoprenoid biosynthetic pathway namely FPP biosynthesis (54). It is also active against promastigotes, in vitro-cultured amistogotes and intracellular amistogotes of L. amazonensis (54). Nerolidol and farnesol have also shown the ability to prevent transition from yeast-like to mycelial growth in Candida albicans which is important because pathogenicity is associated with mycelial forms and may serve as a control to this bacteria (64). Nerolidol has also shown to improve the permeation of antibiotics and ethidium bromide into bacteria (42). The inhibition of synthesis of ubiquinone and dolichol (56, 57) hinders the growth of Plasmodium

83 falciparum growth in vitro (65). In vitro assays of essential oils containing nerolidol have shown that nerolidol has cytotoxic activity when assessed against human lung carcinoma cell line A-549 and human colon adenocarcinoma cell line DLD-1 with 50% inhibition levels of 6.4±0.4 and 5.8±0.04 µg/mL (66). Nerolidol has also had cytotoxic activity against hormone dependent prostate carcinoma LNCaP at a concentration of

15.56±0.22(67). Nerolidol is an alarm pheromone (44) too, and is a signal of plant attack in maize attracting wasps to prey on attacking mites (68).

τ-Cadinol was a principle component of both the bark and leaf essential oils. It was the second principle component of the bark and the third principle component of the leaf oil. τ-Cadinol is a pharmacolologically active substance that enhanced T cell stimulatory capacity (69). Macrophage inflammatory protein MIP-3β, induced intracellular calcium mobilization in τ-cadinol primed dendritic cells (69). τ-Cadinol has been shown inhibitory activity against CT-induced intestinal hypersecretion in mice and electricity induced contractions in isolated guinea pig ileium (70). Additionally, it has been shown to act as a calcium antagonist at high doses and interacts with dihydropyridine binding sites on voltage-operated calcium channels (71). It also maintains smooth muscle relaxant properties (70). The antibacterial activity against

Staphlococcus aureus has also been investigated (72). The activities of τ-cadinol suggest it may be used in dendritic cells-based immunotherapy for cancer treatments (69).

In the Chromatograms of the bark and leaves there is a contaminant peak at retention time 12.5 min and was determined to be a result of contaminant of the solvent after direct injection of the solvent into the GC-MS using the same GC program outlined

84 above. Despite homogenous sampling attempts from the ground leaves, the leaf to leaf variability can come not only from sampling variability but also from variability between plants. In general, differences in compositions of essential oils can be attributed to environmental factors such as plant stress level, soil type, agricultural practices, daylight exposure as well as genetic factors. O. horridus is predominantly wild harvested and large sample to sample differences in chemical makeup can be attributed to clonal expansion as means of growth (6).

The fact that many terpenoids exist in the form of glycosides in the majority of plant materials means that without application of high heat or through means of enzymatic, acid, or base hydrolysis the free volatile form of the terpenoids may not be detectable and extracted from the plant material (73). The function of airborne volatile organic compounds (VOCs) include defense against herbivores and pathogens, attracting beneficial animals and serve as signal molecules (74) . A number of molecules in O. horridus essential oil are signal compounds which may in turn account for the purpose of the differences in the essential oil compounds based upon tissue source of the plant.

Drawbacks of the process of extraction using SDE is that in the process of heating, many low molecular weight compounds are lost to the atmosphere as the SDE is not a closed system of extraction. Additionally, there are some problems involving recovery and extraction of highly polar, water soluble compounds that have high boiling points above that of water. Also, the presence of artifact compounds from previous extractions is possible if the extraction vessel is not cleaned properly between each use.

Compounds which are miscible with water have difficulty in being recovered.

85 Simultaneous distillation and extraction of O. horridus leaves and bark did not yield as many low molecular weight compounds when compared to the existing literature (3).

2.4 Conclusions

The improved recovery and discovery of new identifiable compounds results in an analytical extraction and identification procedure possessing high accuracy (3 MS libraries for structure identification and good correlation of retention indicies) and for compositional analysis of the essential oil derived from the local origin and stress level of the plants at time of harvest as well as high sensitivity. Among the compounds obtained by this present research project as well as the published data from Garneau et al. (3), the principle compounds that make up the essential oil extracts of O. horridus appear to have the predominant fraction coming from the group of sesquiterpenes. (E)-nerolidol and τ- cadinol, are important identified compounds as they appear in each essential fraction regardless of the plant tissue that they extracted. These compounds may be used as identifier compounds for identification of O. horridus essential oils from those that may otherwise be adulterated. The identification of the essential oil components of O. horridus and their previously established bioactivity support the use of it as a medicinal plant.

Acknowledgements:

Much gratitude is wished to be expressed to Mr. David Smith for supplying the

Oplopanax horridus samples for analysis and Dr. Julia Sharp for assisting in the statistical analysis coding.

2.5 Figures and Tables

Table 2.1 Operating Parameters of the GC-MS

GC Conditions Type of GC GC-17A (Shimadzu, T okyo, Japan) Injection Port Splitless (3.5mm ID liner) Temperature of 250°C injector Desorption time 60 s Analytical column DB5-MS Dimensions: 60m x 0.25mm ID x 0.25µm film thickness (Agilent J&W, Santa Clara, CA, USA) Temperature program 50°C (2min hold), 5°C/min 150°C (2 min hold), 1°C/min 180°C (2min hold), 10°C/min 250°C (10 min hold) Temperature of GC- 250°C MS interface Carrier Gas UHP He (24.3cm/s) 99.999%

MS conditions Type of MS GCMS-QP5050A (Shimadzu , Tokyo, Japan) Ionization mode electron impact (70eV) Scan Mode full scan monitoring (from 40 to 350 m/z) Scan time 0.5 sec interval Data acquisition GCMSsolution Ver.2 (Shimadzu, Tokyo, Japan) MS libraries Wiley 7 (Wiley, Hoboken, NJ, USA) NIST 08 (National Institute of Standards and Technology Gaithersburg, MD, USA) Shimadzu Terpene and Terpenoid (Shimadzu, Tokyo, Japan)

87 Table 2.2 Volatile Composition of Oplopanax horridus Essential Oil Extracted by Simultaneous Distillation Extraction

Bark SD Bark

Leaf SD Leaf

Bark

Leaf

Compounda Heptanal 910 1.456 0.542 - - 5-methylfurfural 966 - - 0.621 0.085 Hexanoic Acid 974 1.262 0.922 0.736 0.023 2,4-Heptadienal, 993 - - 1.300 0.112 (E,E)- Octanal 1005 4.363 0.693 2.319 0.427 Unknown 1 1016 - - 0.988 0.077 Benzeneacetaldehyde 1051 2.236 0.182 2-Nonanone 1092 0.881 0.121 1.066 0.183 Nonanal 1107 0.460 0.135 0.602 0.067 Phenylethyl Alcohol 1120 - - 2.873 0.211 2-Nonenal, (E)- 1164 - - 0.800 0.166 Octanoic Acid 1167 2.510 0.712 2.357 0.109 n-Octyl acetate 1207 0.235 0.032 - - Geraniol 1250 - 0.557 0.035 Nonanoic acid 1256 0.092 0.108 1.360 0.057 2-Decenal, (E) 1264 0.959 0.029 - - 2-Undecanone 1293 - - 0.747 0.058 2,4-Decadienal, (E- Z) 1299 - - 0.710 0.025 2,4-Decadienal, (E,E)- 1322 - - 2.275 0.093 3-Decen-2-one 1341 - - 0.583 0.009 n-Decanoic acid 1360 - - 0.697 0.012 (+)-3-Carene, 10- 1393 - - 0.742 0.077 (acetylmethyl)- 2-decenoic acid 1401 - - 0.798 0.095 γ-Elemene 1437 - - 0.210 0.019 (E)-Geranylacetone 1447 - - 0.990 0.031 β-Farnesene 1452 5.836 3.049 2.885 0.546 Dehydro- 1461 0.516 0.539 - - aromadendrene Ar-Curcumene 1487 0.311 0.029 9.838 0.637 (Z)-α-Farnesene 1489 0.170 0.012 - - Zingiberene 1501 - - 4.569 0.521 Cubenene 1501 0.164 0.195 - -

88 α-Farnesene 1505 2.149 1.152 0.419 0.252 β-Bisabolene 1513 0.440 0.216 3.504 0.205 (cis)-γ-Cadinene 1524 1.284 0.297 0.783 0.036 δ-Cadinene 1526 0.434 0.060 0.393 0.003 β- Sesquiphellandrene 1529 - - 5.824 0.490 Calamene (Trans-) 1530 0.428 0.056 - - Unknown 4 1541 2.000 0.146 - - α-Calacorene 1550 0.826 0.035 - - Unknown 7 1554 0.635 0.029 - - Unknown 9 1557 6.503 0.194 - - Unknown 11 1561 - - 2.289 0.251 E-Nerolidol 1562 41.825 6.315 19.050 0.802 Unknown 13 1577 5.742 0.283 - - Unknown 14 1582 0.644 0.207 - - ar-Turmerol 1588 - - 1.464 0.088 Spathulenol 1592 4.659 0.600 4.718 0.146 α-Bisabolol 1598 0.270 0.128 - - Globulol 1599 - - 0.611 0.030 Veridiflorol 1608 - - 0.397 0.011 Unknown 18 1614 - - 1.082 0.150 Sesquisabinene 1619 - - 0.517 0.048 hydrate (cis-) Cubenol 1624 0.916 0.129 0.913 0.080 (-)-Caryophyllene 1638 0.459 0.137 - - oxide Unknown 19 1639 - - 1.224 0.108 τ-cadinol 1652 11.930 0.617 9.908 0.715 Himachalol 1656 - - 0.559 0.025 α-Cadinol 1662 0.224 0.044 1.594 0.049 Unknown 21 1717 - - 0.594 0.116 Tetradecanoic acid 1760 - - 1.300 0.667 a Identifications based on Mass spectral data and linear retention indices on DB-5MS b Kovats retention index based on DB-5MS capillary column using custom temperature programming Significance is characterized as (*) α=0.1, (**) α=0.05, (***) α=0.01, (-) = samples are not significantly different Unknown compounds in order of Retention Index are based upon combined Data set of all identified mass spectra

89 Table 2.3 Electron Ionization Quadrupole Mass Spectra of Principle Ions for Unknown Compounds in Oplopanax horridus extracted using SDE

Principle Ions 1 2 3 4 5

6 7 8 9 10 Unknown KIb 1 1016 101.20 (100.00) 73.15 (69.48) 55.15 (55.46) 41.25 (35.35) 43.15 (32.41) 45.10 (21.00) 70.05 (19.53) 57.15 (15.73) 40.05 (10.19) 42.05 (9.56) 4 1541 119.1 (100.00) 105.05 (71.41) 161.05 (67.55) 204.20 (26.71) 120.10 (15.46) 92.05 (12.96) 162.15 (10.68) 42.05 (8.35) 91.00 (7.49) 70.10 (6.81) 7 1554 43.10 (100.00) 143.15 (45.50) 44.15 (34.37) 83.15 (32.65) 41.15 (31.49) 71.10 (23.06) 67.15 (22.31) 57.15 (21.57) 55.05 (20.21) 70.4 (15.55) 9 1557 43.00 (100.00) 143.10 (97.66) 85.05 (53.58) 125.05 (50.43) 71.00 (44.10) 54.95 (28.48) 40.95 (27.70) 81.10 (23.66) 107.05 (17.68) 83.05 (17.37) 11 1561 109.10 (100.00) 43.00 (89.55) 69.10 (66.41) 41.00 (37.92) 55.00 (26.48) 111.10 (20.39) 71.05 (20.15) 93.05 (17.10) 138.10 (16.02) 83.10 (14.89) 13 1577 177.10 (100.00) 159.15 (48.06) 119.05 (45.07) 135.15 (22.77) 105.10 (21.90) 220.15 (18.33) 91.05 (16.49) 178.15 (16.34) 107.10 (16.00) 117.05 (13.52) 14 1582 43.00 (100.00) 93.00 (73.57) 119.05 (41.18) 40.95 (36.84) 91.00 (31.87) 162.15 (29.59) 147.05 (26.91) 78.90 (23.23) 105.05 (22.53) 107.40 (21.75) 18 1614 42.95 (100.00) 109.40 (55.73) 107.10 (54.58) 122.15 (53.11) 41.05 (53.05) 69.05 (46.71) 55.00 (39.83) 161.15 (39.31) 81.10 (35.54) 93.05 (35.22) 19 1639 42.95 (100.00) 41.05 (48.21) 109.10 (44.52) 69.05 (39.77) 93.10 (27.49) 55.05 (26.32) 67.00 (24.98) 81.05 (23.38) 68.05 (22.46) 71.05 (22.43) 21 1717 44.10 (100.00) 91.10 (71.34) 135.20 (56.65) 53.05 (44.88) 103.45 (41.00) 95.05 (40.05) 149.65 (38.43) 128.85 (37.77) 69.10 (32.64) 121.30 (32.14)

Table 2.4 Paired T-test Statistical analysis of Oplopanax horridus percent composition of bark and leaf essential oils extracted using Simultaneous Distillation and Extraction

Significance

Level Level of

Value

a b

Compound KI Hexanoic Acid 974 0.570 - Octanal 1005 0.060 * 2-Nonanone 1092 0.070 * Nonanal 1107 0.261 - Octanoic Acid 1167 0.703 - Nonanoic acid 1256 0.010 ** β-Farnesene 1452 0.178 - Curcumene (ar-) 1487 0.002 *** α-Farnesene 1505 0.080 * β -Bisabolene 1513 0.001 *** (cis)-γ-Cadinene 1524 0.080 * δ-Cadinene 1526 0.352 - E-Nerolidol 1562 0.020 ** Spathulenol 1592 0.881 - Cubenol 1624 0.972 - t-cadinol 1652 0.002 *** α-Cadinol 1662 0.007 *** a Identifications based on Mass spectral data and linear retention indices on DB-5MS b Kovats Retention index based on DB-5MS capillary column using custom temperature programming Significance is characterized as (*) α=0.1, (**) α=0.05, (***) α=0.01, (-) = samples are not significantly different

Figure 3.1 GC-MS Total Ion Chromatogram of Oplopanax horridus Bark essential oil extract using Simultaneous

Distillation Extraction

Figure 3.2 GC-MS Total Ion Chromatogram of Oplopanax horridus Leaf essential oil extract using Simultaneous

Distillation Extraction

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70. Claeson, P.; Zygmunt, P.; Högestätt, E.D. Calcium Antagonistic Properties of the Sesquiterpene T-Cadinol: A Comparison with Nimodipine in the Isolated Rat Aorta. Pharmacol. Toxicol. 1991, 69, 173-177.

71. Zygmunt, P.M.; Larsson, B.; Sterner, O.; Vinge, E.; Högestätt, E.D. Calcium Antagonistic Properties of the Sesquiterpene T-Cadinol and Related Substances: Structure-Activity Studies. Pharmacol. Toxicol. 1993, 73, 3-9.

72. Rahman, M.M.; Garvey, M.; Piddock, L.J.V.; Gibbons, S. Antibacterial terpenes from the oleo-resin of Commiphora molmol (Engl.). Phytotherapy Research 2008, 22, 1356-1360.

73. Mateo, J.J.; Jiménez, M. Monoterpenes in grape juice and wines. Journal of Chromatography A 2000, 881, 557-567.

74. Dudareva, N.; Pichersky, E. Metabolic engineering of plant volatiles. Curr. Opin. Biotechnol. 2008, 19, 181-189.

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CHAPTER THREE

HEADSPACE SOLID PHASE MICROEXTRACTION OF VOLATILE COMPOUNDS

IN OPLOPANAX HORRIDUS STEM BARK AND LEAVES

Abstract

Solid phase microextraction (SPME) has become an increasingly used method for separation of target analytes from a variety of matrices since its inception in the 1990’s by Pawliszyn and his team (1). The coupling of headspace solid-phase microextraction

(HS-SPME) under optimized extraction parameters with a highly sensitive gas chromatography mass spectrometry (GC-MS) system allows for rapid sampling and analysis of volatile and semivolatile compounds in complex herbal tissues. Volatile metabolites from the bark and leaves of Oplopanax horridus were absorbed by the polydimethylsiloxane (PDMS) stationary phase via SPME and analyzed by capillary gas chromatography with mass spectrometric detection. Compounds were identified according to their non-isothermal Kovats indices, mass spectra (EI, 70eV), or by comparison with analytical standard substances. The use of HS-SPME extraction and injection of the volatiles of the bark and leaf yielded 48 spectrally unique compounds in the bark and 39 in the leaves. The identified compounds from the bark that had the highest percent concentration were (E)-nerolidol (25.371%), τ-cadinol (15.049%), and spathulenol (8.384%) which comprise 48.804% of the total amount of the bark volatile mixture; similarly, principle compounds of the SPME leaf extract were (E)-nerolidol

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(37.469%), τ-cadinol (9.315%), ar-turmerol (5.033%), (E)-γ-bisabolene (5.439%), and β- bisabolene (2.730%) which accounted for 59.986% of the volatile mixture.

3.1 Introduction

O. horridus, commonly referred to as devil’s club, is an understory shrub which can be commonly found in the northwestern United States and in western Canada and is an important medicinal and spiritual plant for the indigenous peoples that use it as a medicinal plant (2, 3). It is found predominantly in Alaska south to the central part of

Oregon and is found eastward to the Canadian Rockies, Montana and Idaho (4). This plant belongs to the family Araliaceae which also contains prominent medicinal plants including Asian ginseng (Panax ginseng), American ginseng (Panax quinquefolius), and eleuthero (Eleutherococcus senticos) formerly called Siberian ginseng (5). Nearly all species within the Panax genus are traditional herbal medicines and are erect, perennial, herbaceous plants with permanent aerial, woody stems (6). The plant is native to the region it is found, is an erect to slightly spreading deciduous shrub that is from one to three meters in height, is sparsely branched with dense spines on the stems and has prominent leaf veins (7). The stems are upright to decumbent, covered with yellow to brown needle-like spines and have large palmately lobed leaves that spirally grow around the stems (5, 6). O. horridus has small green to white flowers, borne in terminal pyramidal clusters that bloom and ripen to shiny flattened bright red berries between June and July that persist over the winter (5, 7).

Oral ingestion and topical application of O. horridus preparations have been used to treat physical ailments, arthritis, blood spitting, blood disorders, cancer, chest pains,

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colds, constipation, coughs, diabetes, fever, flu, gallstones, gastrointestinal problems, headaches, heart disorders, indigestion, influenza, measles, respiratory illnesses, rheumatism, sore throats, stomach pain, stomach ulcers, tuberculosis, wounds, as a purgative, cure all, and as a smudge (2, 8) in addition to spiritual uses for protection, luck, a ward against witchcraft and supernatural entities (2, 5, 9).

To date there are many bioactive compounds that have been identified in O. horridus and their pharmacological activities have been investigated. The pharmacological activities presently found support the use of O. horridus as a therapeutic treatment due to its antimycobacterial (10, 11), antibacterial (11, 12), antifungal (11, 13), and antiviral (14) activities. These activities of O. horridus support its traditional use as a medicinal herb. Although the predominant focus of the pharmacological extracts has been linked to solvent extraction of nonvolatiles focusing on the hydrophobic fractions, with two principle chemical groups of interest, namely sesquiterpene and polyyne compounds. Although the essential oil extracts of many plants have been investigated to date, there is only one published article involving the volatile components of the essential oil of O. horridus (7).

3.2 Materials and Methods

3.2.1 Equipment:

A manual SPME holder and a 24 gauge SPME fiber composed of 100 μm polydimethylsiloxane (PDMS) stationary phase was purchased from Supelco (Supelco

Inc., Bellefonte, PA, USA) and was used for manual injection of static headspace volatile compounds. Glass sample vials with a volume of 5.0mL were purchased from Supelco

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(Supelco Inc., Bellefonte, PA, USA) and were sealed with an open core cap lined with a polytetrafluoroethylene (PTFE)/silicone liner. Certified A.C.S. grade anhydrous sodium sulfate and high performance liquid chromatography (HPLC) grade methylene chloride

(DCM) were purchased from Fisher Scientific (Norcross, GA, USA). Standards of alkanes (C8-C20), nerolidol (>98% purity), farnesene, and α-terpineol were purchased from Sigma-Aldrich (St. Louis, MO, USA).

3.2.2 Sample Preparation:

The leaves and stem bark of Oplopanax horridus were wild harvested near

Anchorage, Alaska, under the auspices of David Smith. Samples were collected between

June and August and were air dried prior to being shipped to Clemson, SC for chemical characterization. Characteristic samples of the stems have been retained as voucher specimens. Upon arrival, samples were placed in air tight bags, heat sealed, and stored at

-20°C in the dark. Prior to analysis, moisture content of the air dried samples was determined to be 8% by weight. Dried outer stem bark and leaves were ground using a

Thomas-Wiley laboratory mill model 4 (Thomas-Wiley, Swedesboro, NJ, USA) with a final screen size of 2mm yielding finely ground O. horridus bark and leaf samples. The samples were ground in <50g batches in a 25˚C environment. Samples were stored in air tight zippered bags and placed inside heat sealed plastic bags. The finely ground samples were stored at -20˚C in the dark until analysis.

3.2.3 Headspace Solid Phase Microextraction (HS-SPME)

For extraction and isolation of analytes, a SPME holder for manual sampling with a 10mm fiber coated 100 μm polydimethylsiloxane (PDMS) stationary phase (Supelco

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Inc., Bellefonte, PA, USA) was used for manual injection of absorbed volatiles from the stem bark and leaves. Prior to extraction, the fiber was conditioned by baking at 250°C for 3 hours under a flow of Ultrahigh purity (UHP) helium (99.999%) in the GC injection port. Analysis of compounds was performed via GC-MS on a Shimadzu GC-17A gas chromatograph coupled to a Shimadzu QP5050A quadrupole mass spectrometer. GC-MS conditions can be found in Table 3.1.

The sample in an amount of 0.300g of was weighed into a 5 mL headspace tube manufactured by Supelco and purchased from Sigma-Aldrich Co. (St. Louis, MO, USA) and mixed with 2 mL of millipure distilled water supplied by a Synergy UV system

(Millipore, Billerica, MA, USA). An aliquot 100µL of 500ppm α-terpineol internal standard was added to improve reproducibility of extractions to help control for matrix effects between samples and minimize inter-sample variability of the MS detector. The tube was were sealed and placed in a water bath set to 60 ± 0.2°C and allowed to equilibrate for 45 minutes. The samples were held in a metal clamp in the heated water bath maintaining the same location in the water bath for each analysis as well as distance from the manual SPME fiber holder. Sample equilibration time was 45 minutes to allow for analytes to reach thermal equilibrium between the headspace and aqueous phase.

However, this was insufficient time for volatiles to reach equilibrium between the phases.

After equilibration, the tube septum were pierced with the SPME fiber and the fiber was fully extended 11mm into the tube which was placed the tip of the fiber 0.1mm above the surface of the sample/standard/solvent mixture, fully exposing the 10mm stationary phase. The manual holder was held in the same position during each extraction by a

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clamp to minimize extraction variation due to the effect of absorption location within the sample vial. An extraction time of 60 minutes was chosen for practical reasons as the principle compound had reached at least 80% its maximum absorbed concentration and was a good compromise between experimental duration and method sensitivity.

Immediately after extraction, the SPME apparatus was transferred to a GC splitless injector maintained at 250°C and was fully inserted into the GC injection port. The needle penetrated the injector septum and the fiber was fully extended as the GC program started. Samples were thermally desorbed in the GC injector for 1 minute at 250°C which prevented carryover between samples. Blank runs confirmed the suitability of 1 minute desorption time which was determined by the absence of (E)-nerolidol in the total ion chromatogram and a stable, peakless baseline. Fully inserting the fiber into the injection port allowed for repeatable desorption location and temperature inside the injector, thus minimizing desorption variability between samples. Utilizing a low initial column temperature, the desorbed analytes condensed at the head of the column and eluted as the temperature of the GC oven increased according to the temperature program. The chromatographic column was a DB-5 (5% phenyl, 95% methyl silicone) capillary column

(60m x 0.25mm ID x 0.25µm film thickness) (Agilent J&W, Santa Clara, CA, USA). The

GC operating conditions can be found in Table 3.1. The identification of compounds was based upon the following methods: (1) their non-isothermal Kovat’s retention indices

(KI), (2) GC-MS retention indices and mass spectra (authentic chemicals), and (3) mass spectra compared to the following libraries: NIST 08 (National Institute of Standards and

Technology, Gaithersburg, MD, USA), Shimadzu Terpene and Terpenoid (Shimadzu,

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Kyoto, Japan), and Wiley7 (Wiley, Hoboken, NJ, USA) library collections. Primary identifications were made by comparing their respective KI values as well as their mass spectra with those reported in literature (15-36). The spectra were collected in scan mode from 40-350 m/z ratio and retention times were based upon the detection of a single peak in the total ion chromatogram at a corresponding retention time. Identification was considered tentative when only the mass spectral identification and KI values matched the unknown peak and analytical standards were unavailable. Triplicate extractions of samples were performed to identify the reproducibility of the chromatographic separation on the column, the mean retention time and detector response, and concentration of the individual compounds. Kovats indices of compounds were calculated using an external standard series of n-alkanes (C8-C20) separated under the same experimental conditions as the samples. Experimental, non-isothermal Kovats indices were calculated using

ttr()() A r n KI100* 100 n where tr(A) is the analyte retention time, tr(n) is the tt r( n 1) r ( n ) retention time of the n-alkane eluting directly before tr(A), tr(n+1) is the retention time of the n-alkane eluting directly after tr(A), and n is the number of carbon atoms for tr(n) (37, 38).

Compounds whose reported KI values are identical or very close to each other were assigned identical values based upon the observed GC data. Additionally, the identification of compounds with the same KI value are identified in conjunction with the agreement between their experimentally observed and reported mass spectral data. The identification of compounds with a KI value of less than 900, or the equivalent of nonane,

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was not possible herein due to the tailing peak of the solvent, hexane, which is what the alkane standards were dissolved in.

3.2.4 Statistical Analysis

The mean value of the triplicate extractions within individual samples was analyzed using a paired t-test and calculated using SAS 9.3 (SAS Institute Inc. Cary, NC,

USA). The samples were analyzed both for percent composition and concentration within the HS-SPME samples. A significance level of α=0.10 was used to determine significance of t-tests and ANOVA. All of the Bark and Leaf extractions were evaluated in triplicate. The quality of extraction was evaluated by plotting the extracted compound area counts versus the mean of the other extractions. Any extractions that were outside 2 standard deviations of the predicted levels of (E)-nerolidol, the principle component, were repeated. The equilibration models were developed with a minimum of two replications. An F-test was used in determining the appropriateness of the model fit using

ANOVA of the different models fit when determining the effect of sample temperature and absorption time on the MS detector response.

3.3 Results and Discussion

3.3.1 Method Optimization

The effects of extraction temperature and time, desorption time were investigated systematically using 0.300g of the medicinal herb O. horridus to account for the nature of matrix effects that vary between the physical nature of the sample partitioning into the water and subsequently headspace of the GC vials prior to absorption by the fiber stationary phase. The effectiveness of each treatment was analyzed based upon the MS

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detector response of the principle compound, (E)-nerolidol. (E)-Nerolidol was used to model the effectiveness of the treatments due to the fact that it has a reasonably high molecular weight (222.37 Da) and is the principle component in both the bark and leaf volatile extracts. The same 100µm PDMS SPME fiber was used for each of the analyses.

The purpose of sample temperature optimization was twofold: (1) to increase the sensitivity of the extraction method, (2) decrease the extraction time while maintaining the maximum levels of (E)-nerolidol within the maximum linear range of the MS detector.

3.3.1.1 Sample Extraction Temperature

The first step in terms of optimization of experimental parameters studied the effect of sample temperature on the quantity and types of volatiles that were absorbed to the SPME fiber. The molecular weight of the compounds as well as their three- dimensional structures, partition coefficients, boiling points and many other factors must be taken into consideration when looking at sample extraction temperature in general terms. The sample temperature was controlled using a water bath during the 45 minute sample equilibration time and 10 minute extraction time to determine the effect of sample temperature on the absorption parameters for HS-SPME extraction in order to increase recovery of the extraction process to improve identification of minor compounds.

Temperatures of 40, 50, 60, 70, and 80°C were studied using a ten minute extraction time. Under those conditions, the compounds with higher molecular weights partitioned into the headspace and absorbed to the fiber showed a greater difference in detector response as temperature increased. This is due to the fact they have higher

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boiling points and more complex structures compared to the low molecular weight compounds. The more complex mono and sesquiterpenes compounds were more affected by the sample temperature than the smaller molecular weight compounds such as the aldehydes octanal and nonanal. Octanal and nonanal were not greatly affected by the increase in temperature between extractions. Due to the higher partitioning mass of the higher molecular weight volatiles and the resulting higher MS response (data not shown),

80°C was initially chosen as the optimal sample temperature. After performing a literature review, extractions commonly to had a two hour duration with a 100µm PDMS fiber. This is necessary to allow for the maximum mass of volatiles to be absorbed into the liquid stationary phase of the SPME fiber as a thicker phase takes a longer duration for compounds to reach equilibrium. The problem that ensued was that under those conditions (i.e., 80°C and 120 min absorption time) the major compound, (E)-nerolidol, was beyond the maximum detectable limits of the MS detector and its quantity was not mathematically integrated. The next lower temperature, 70°C, was studied with a 120 minute absorption time after equilibrating 45 minutes, but it still exceeded the range of the MS detector (the statistical variation was more than 2 standard deviations away from the mean when run in triplicate) and so this temperature was not used either. After the analyses of 70°C and 80°C were studied and found to have poorly reproducible results,

60°C was used for further experiments. The combination of 45 minute equilibration time,

60°C sample temperature, and 120 minute extraction time was at the uppermost limit of the linear range of the MS detector. After running ANOVA and multiple regression

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analyses on the experimental data, the models for selected analytes were generated using single factor analysis and are shown in Table 3.2 and Table 3.3.

Many of the lower molecular weight compounds modeled were partitioned and absorbed to the fiber at a rate that was independent of the sample temperature, and were found to have little variation of the mean concentration at different extraction temperatures. When regression analysis was performed of three low molecular weight compounds, i.e., octanal, 2-nonanone, and octanoic acid there was not an improved fit of the model including a temperature factor. The difference in model fit was evaluated using an F-test to determine the improved fit of Y=β0+ β1(Temperature) compared to Y=β0 the addition of the β1 term, the addition of the temperature term did not improve the model and was not statistically significant in any of the three compounds (p=.2607), (p=0.6836), and (p=0.1324) respectively. As molecular weight increased, the effect of sample temperature began to be significant as the boiling points of the compounds also increased.

For this reason, the principle compounds which were principally sesquiterpenoids were modeled due to the significance of their amounts in the volatile extract of O. horridus.

(E)-nerolidol was the principle volatile component of both the bark and leaves. It has a relatively high molecular weight and boiling point for volatile analysis and as such, sample temperature had a significant effect on the quantity that was partitioned into the headspace and subsequently absorbed by the SPME fiber. The quadratic model fit with

2 β0, β1 and β2 terms was fitted first and had a coefficient of determination (R = 0.991) when fitting two replications of sample temperatures. After running regression analysis, the intercept value was determined not be significant (p=0.2975) while the β1 (p=0.0926)

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and β2 (p=.0079) terms were significant with values in the final fit model for (E)- nerolidol being Y=-5.5859E6(concentration) + 9.4273E4(concentration)2.

All of the experimental data points were within 95% prediction intervals calculated by SAS. The effect of chemical structure on the absorption and partition properties of the volatile compounds was studied and is visible through the differences in the modeled absorption isotherm equations for (E)-nerolidol and τ-cadinol. Despite the two compounds having the same molecular weight, their structures are rather different as

(E)-nerolidol is an acyclic sesquiterpene alcohol and τ-cadinol is a bicyclic sesquiterpenoid. Their difference in MS response to the increase in sample temperature is displayed in Figure 3.3, from which it can be seen by the generated curves that the absorption isotherms show a greater temperature effect on τ-cadinol than on (E)- nerolidol. In general, a higher sample temperature provided a higher quantity of extracted analyte absorbed and injected into the GC-MS.

3.3.1.2 Equilibration Time

An equilibration time of 45 minutes was chosen for practical reasons as this amount of time ensured temperature uniformity of the sample with the water bath and allowed sufficient time to allow both low molecular weight and higher molecular weight compounds to partition to qualitative, detectable levels in scan operation mode of the MS detector. Increasing the equilibration time to 60 minutes prior to extraction was not shown to have a generally noticeable difference in detector response.

3.3.1.3 Absorption Time

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At an extraction temperature of 60°C, absorption times of (1, 2, 30, 45, 60, 120 minutes) were selected for analysis. Statistical models were fit for octanal, 2-nonanone, octanoic acid, cis-γ-cadinene, unknown 4, unknown 7, Unknown 9, (E)-nerolidol, unknown 13, spathulenol, cubenol, and τ-cadinol. For the above analyte compounds, all but octanoic acid were best modeled by a quadratic regression equation in plotting area counts of the MS detector against the extraction times (1, 2, 30, 45, 60, 120 minutes), which are listed in Table 3.3. An absorption time of 150 minutes did not have a significantly different mean level on (E)-nerolidol due to large standard deviations from the mean. Therefore, 120 minutes was the maximum analyzed time for absorption. In general, as absorption time increased, the amount of sample analyte absorbed into the stationary phase on the fiber also increased.

Peak areas for most analytes, in particular the less volatile, more structurally complex sesquiterpenoids, did not reach equilibrium within a 120 minute time period. τ-

Cadinol serves as a good example of the continued increase in absorbed analyte as time increases at an extraction temperature of 60°C. The 120 minute extraction at 60°C had detectable levels but had much higher sample to sample variation so the data was not as precise or repeatable compared to the 60 minute absorption time. In contrast to 120 minutes, a shorter absorption time of 60 minutes offered less variation between samples and had better repeatability which was more important than the detector response.

Decreasing absorbance time to sixty minutes did not decrease the sensitivity of the extraction method (measured by the number of unique compounds identified) when compared to the 120 minute absorbance time. With an absorption time of 60 minutes and

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sample temperature of 60°C, (E)-nerolidol was 81% of its maximum absorbed levels (120 minute extraction) and still maintained values that were within a 95% prediction interval for detector response. Therefore, 60 minute absorption time was chosen as it offered good precision, and repeatability for qualitative analysis despite not being under equilibrium extraction conditions between the three phases (solution, headspace and fiber). A 60 minute extraction also allowed for more efficient utilization of time in that higher throughput was made possible under non-equilibrium conditions without losing experimental sensitivity.

3.3.1.4 Desorption Time

The effect of desorption time in the GC injector was studied at a temperature of 250°C. A previous experiment (7) showed that all of the analytes of hydrodistilled essential oil had boiling points below 250°C. Peak areas of analytes increased with an increasing desorption time up until the point that all compounds fully desorbed from the SPME fiber. Desorption times of 30 seconds, 60 seconds and 120 seconds at 250°C were studied to determine their suitability for maximal quantitation purposes for trace level headspace extraction. The point at which complete thermal desorption of volatiles from the SPME fiber was reached. The headspace extracted compounds desorbed quantitatively at 250°C in more than 30 seconds and fewer than 60 seconds and did not have carry over. A desorption time of 60 seconds was selected since a desorption time of greater than 60 seconds gave no further peak response increase. The complete desorption was verified by blanking the fiber after a chromatographic run to ensure that all compounds were completely desorbed by the absence of (E)-nerolidol on the total ion chromatogram.

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The detection limits and the amount of analyte absorbed by the stationary phase is dependent upon a number of factors including: the thickness of the fiber coating, the distribution constant of the analyte, polarity of the analyte compound, sampling parameters of volume, temperature, time, relative humidity and internal standard (39).

The levels of quantification were similar between the three analytical standards that were used to semiquantitatively identify the extraction levels of the headspace samples of O. horridus. Each of the standards (i.e., β-farnesene, β-bisabolene, and (E)-nerolidol) were quantifiable at levels above 2 ppm in scan mode. The concentrations of standards used for quantification were conducted so that the levels of the HS-SPME extracts were within the linear range of the standard curve. Precision of the extraction method was determined using the relative standard deviation of (E)-nerolidol under optimized parameters, which was 8.736% (n=3) when extracting from the stem bark plant matrix.

The use of a 100µm thick liquid phase on the SPME fiber provides slower diffusion and equilibration times of both volatile and semivolatile compounds; more importantly though, it allows for retention of the more highly volatile compounds to a greater extent than a thinner, 7 μm, phase would. The characteristics of the thicker 100μm fiber coating is more useful than a 7μm fiber when studying complex volatile mixtures from plants, in particular sesquiterpenoids, due to the fact they have higher boiling points and require longer equilibration times than low molecular weight compounds (39).

Although useful for qualitative purposes in identifying the compounds of interest, using

SPME can be difficult or impractical for quantitation of compounds when dealing with many compounds that have different distribution constants such as plant extracts (39).

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In the present study, long equilibration times for optimized SPME sampling of

(E)-nerolidol in the headspace above the samples was necessary. The extraction time for the final optimized analyses were based upon the equilibration rate for (E)-nerolidol. The optimized extraction time of 60 minutes allowed for (E)-nerolidol to absorb to the SPME fiber to the point at which the rate of adsorption of to the SPME fiber began to slowed as time increased and can be seen graphically in Figure 3.4. The combination of the sample temperature, equilibration time, and absorption time meant that (E)-nerolidol was in quantities at the maximum detectable linear limit of the MS detector. Similarly, Field et al. (1996) reported long equilibration times for SPME sampling of the sesquiterpene caryophyllene which has a KI values of 1452 and was present in the volatile extract from the bark and leaves of O. horridus.

The use of non-isothermal (temperature-programmed) Kovat’s retention index system was used to adjust for the effect and elution of the n-alkanes from the column to calculate the retention indices of the eluted compounds. The retention indices vary between laboratories and have seen change due to different temperature programs, column lengths, and ages of columns. These are possible reasons for this phenomenon as well as the lack of isothermal chromatographic conditions through which the oven temperature changes may vary slightly from instrument to instrument. Although modern processing and manufacture of columns allow much greater quality control and decrease variation, there is still batch to batch variation and the exact surface structure of the column can still vary even within the same lot of production.

3.3.2 Concentration Standard Curves

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Standards such as β-farnesene, β-bisabolene, and (E)-nerolidol were used for determining the relative concentrations of the extractions to determine the different effects of extraction optimization parameters on concentration. Regression modeling was used to determine the linearity of detector response. The equation that was used to calibrate the β-farnesene standard for the mass spectral total ion chromatogram (TIC) from a concentration of 11 ppm to 1661 ppm was modeled as linear, Y=β0+β1X+ε. The line was fitted using a level of significance equal to 0.05 and whose coefficients were calculated: β0=0 (p= 0.2045), β1= 12854 (p=<0.0001), and ε= 1031369. The final equation fitted was Area= 12854*Concentration. The quadratic model was also tested to see if it was more suitable than the linear model; however, the value of the β2 term was insignificant (p=0.1469). Therefore, the linear model was chosen as the final model for this compound. The concentration of β-farnesene in the bark was 1428 ppm and 403 ppm in the leaves under nonequilibrium experimental conditions per gram of dry sample.

The equation that was used to calibrate the β-bisabolene standard for the mass spectral TIC from a concentration of 13.7 ppm to 2057.6 ppm was modeled as linear,

Y=β0+β1X+ε. The line was fitted using a level of significance equal to 0.05 and whose coefficients were calculated: β0=0 (p=0.3186), β1=11760 (p=<0.0001), and ε= 1142822.

Similarly, the quadratic model was also tested to see if it was more suitable than the linear model but the value of the β2 term was insignificant (p=0.1537); therefore the linear model was chosen as the final model for this compound. The final equation fitted was Area= 11760*Concentration. Levels of β-bisabolene were found at levels of 476 ppm in the bark and 925 ppm in the leaves per gram of dry sample.

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The equation that was used to calibrate the (E)-nerolidol standard for the mass spectral detector from a concentration of 14.4ppm to 44057ppm was quadratic and

2 modeled after Y=β0+β1X+β2X +ε. Area under the peak curve from the mass spectral total

2 ion chromatogram was modeled as Area=β0+β1(Concentration)+β2(Concentration) +ε.

The line was fitted using a level of significance equal to 0.05 and whose coefficients were calculated: β0=0 (p= 0.4902), β1= 17018.015 (p=<0.0001), β2= -0.180 (p=<0.001) and

ε= 13582691. The final equation fitted was quadratic due to a lower mean square error value as well as a higher R2 value than the linear model and was calculated to be Y=

17018.015(Concentration) - 0.180(Concentration)2. The fit of the equation is good but in order to accurately quantitate the standards (in relative levels), the data was split into two smaller concentration curves with the low concentration curve covering from 14 ppm to

2879ppm to quantitate its concentration in the leaf and the higher concentration curve was from 8637ppm to 44057ppm and was used to quantitate (E)-nerolidol’s concentration in the bark. The lower concentration curve fit was

Y=17885.7260*Concentration (R2= 0.9943). The higher concentration curve was Area=

101717122.8+7017.8(Concentration) (R2=0.9798). These two linear models were used to quantify the levels of (E)-nerolidol. (E)-Nerolidol was found at a level of 112430 ppm in the bark and 8648 ppm in the leaf under the experimental conditions per gram dry sample.

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3.3.3 HS-SPME Extraction

The use of HS-SPME for extraction of volatiles from O. horridus yielded forty eight spectrally unique, identifiable compounds from the stem bark and thirty nine from the leaf samples. The compounds from the bark that had the highest percent concentration were (E)-nerolidol (25.469%), τ-cadinol (15.107%), Unknown 13 (11.987%), Unknown

11 (9.274%), and spathulenol (8.416%) which comprise 70.253% of the total amount of the bark volatile mixture. The principle compounds of the SPME leaf extract were (E)- nerolidol (41.150%), τ-cadinol (10.230%), (E)-γ-bisabolene (5.973%), and ar-turmerol

(5.528%) which accounted for 62.881% of the volatile mixture. Neither the bark, nor the leaf HS-SPME samples had trace level (<0.1%) compounds in them. There were fewer minimal compounds (0.1% < X < 1%) in the leaf (21) than the bark (35) with an increased number of minor compounds (1% < X < 5%) (14) in the leaf than in the bark

(7). The bark had two more principle (>5%) compounds with 6 total, than the leaf did.

The principle compound of both the SPME extracts was (E)-nerolidol with a mean percent composition of 25.469% for the bark and 41.150% in the leaf. It was therefore used to optimize the extraction parameters. When modeling the amount of (E)- nerolidol absorbed onto the fiber versus the extraction time (shown in Table 3.5), the mass of (E)-nerolidol begin to approach a plateau at an extraction time of 60 minutes after a 45 minute equilibration time for a sample held at a constant temperature of 60°C.

Although at T=60 the mass of (E)-nerolidol absorbed onto the fiber is only 81% of the observed area count detectable at T=120 minutes, the nonlinearity of the detector response at 120 minutes had too much sample to sample variation with more than two

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standard deviations of error between triplicate runs so that it was not used. Relative concentration of the non-equilibrium experimental conditions yielded a concentration of

(E)-nerolidol of 112430 ppm in the bark and 8648 ppm in the leaf based upon dry weight.

β-Farnesene was found at aconcentration of 403 ppm in the leaf and 1428 ppm in the bark per gram dry weight sample. β-Bisabolene was found at relative concentrations of 925 ppm in the leaf and 476ppm in the bark per gram dry weight sample.

3.3.4 Class distribution of Volatiles

In the bark and leaf compounds, 48 spectrally unique compounds were identified in the bark and 39 in the leaves of O. horridus. Eleven of the bark and six of the leaf compounds were not identifiable, but the principle ions of their mass spectra can are listed in Table 3.5. The eleven unidentified compounds in the bark accounted for

32.191% of the extract and the six compounds in the leaf accounted for 9.722 % of the leaf extract. The predominant class of identified compounds in O. horridus bark is the sesquiterpenes. These 25 compounds accounted for 58.516% of the total volatile extract.

The second predominant compound type is the aldehydes. This class contained five compounds including heptanal, octanal, nonanal, 2-(E)-nonenal, and 2-(E)-decenal, which accounted for 4.450% of the extract. The three carboxylic acids i.e., hexanoic, heptanoic and octanoic acid accounted for 2.662% of the bark extract. The compound classes that had only one compound in them were ketone, alcohol, alkane, and alkyne whose compounds accounted for 1.272%, 0.145%, 0.213%, and 0.166% respectively.

The predominant class of compounds in O. horridus leaves is the sesquiterpenes which have 14 compounds totaling 72.501% of the volatile extract. The second

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predominant compound type is aldehydes. This class was composed of the six compounds heptanal, octanal, 2-octenal, nonanal, decanal, and 2-(E)-decenal which accounted for 2.611% of the extract. Three classes have three compounds each and those are: (1) ketones: 2-nonanone, 2-undecanone, 3-decen-2-one (1.916%), (2) alcohols: 2- nonanol, 1,8-octandiol, 2-butyl-2,7-octadien-1-ol (1.331%), and (3) monoterpenes: geraniol, 1,2-dihydrolinalool, and 10-(acetylmethyl)-(+)-3-Carene (1.019%) of the leaf volatile mixture respectively. 5,6,7,7a-tetrahydro-4,4,7a-trimethyl-2(4H)-Benzofuranone, was the only furan compound responsible for 0.710%. One carboxylic acid, octanoic acid accounted for 0.306% while the one alkane, tetradecane attributed 0.388% composition.

Additionally, 2,3-dimethyl-5-(1-methylpropyl)-pyrazine, was the only nitrogen containing compound and had 0.553%.

3.3.5 Statistical Analysis of Essential Oil differences

3.3.5.1 Relationship between concentration in plant tissue

Fifteen compounds that were found in both the bark and leaf HS-SPME samples were compared on both their concentration levels as well as percent composition of the volatile mixtures under experimentally optimized extraction parameters. A paired t-test was used to determine the difference in the mean concentration levels in the bark and leaf volatiles, which is shown in Table 3.6. When comparing the concentration in the plant tissues (based upon the area counts of the compounds using the same extraction conditions), twelve of the fifteen compounds were found to have concentrations that differed significantly using a level of significance, α=0.10. Conversely, ar-curcumene

(p=0.170), zingiberene (p=0.143), and β-bisabolene (p=0.178) were found to have the

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same concentration in both the stem bark and leaves of O. horridus. Twelve of the fifteen compounds that were found in both the bark and leaves of O. horridus had different concentrations following the same extraction parameters. Levels of significance tested were α=0.1, α=0.05 and α=0.01 to characterize the degree of confidence in the concentration difference. Heptanal was the only compound to have significantly different concentrations (p=0.073) with an α=0.1. Two compounds, octanoic acid (p=0.039) and cis-γ-cadinene (p=0.010) had different concentration between the bark and leaf at the second level of confidence (α=0.05). The remaining nine compounds had differing levels of concentration at the highest level of significance (α=0.01).

3.3.5.2 Relationship between percent composition in plant tissues

Thirteen of the fifteen compounds were determined to have significantly different

(minimum α=0.10) percent composition between the two sample tissues from O. horridus that were extracted using HS-SPME. The two compounds that were not significantly different were cubenol (p=0.244) and α-cadinol (p=0.130). Using a level of significance,

α=0.1, the aldehyde heptanal (p=0.096) and the sesquiterpene (cis)-γ-cadinene were found to have significantly different concentrations. Using a higher degree of confidence, α=0.05, nine of the fifteen compounds were significantly different. Two compounds, octanal (p=0.006) and (E)-geranylacetone (p=0.005) were significantly different using the highest level of confidence in this study, α=0.01.

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3.3.6 Comparison of percent composition in different extraction methods

There were some compounds that were found in the HS-SPME extract of the O. horridus bark and leaf that have been identified previously. These compounds include

(E)-nerolidol (7, 40, 41), τ-cadinol (7, 41), α-cubebene (40), spathulenol (40), and oplopanone (40). Their presence in multiple forms of extraction suggest that they are generally synthesized by O. horridus under normal growing conditions and could serve as marker compounds for phytochemical identification and quality control purposes.

3.3.6.1 Comparison of extracted percent composition between HS-SPME and hydrodistillation

Existing literature (7) on O. horridus essential oils are presented as means and do not have presented standard deviations so drawing exact statistical comparisons is not possible. However, generalized comparisons can still be made to the extracted essentials using HS-SPME and the hydrodistilled (HD) oils. The work of Garneau et al. 2006 will be used for comparisons of HS-SPME extracts to the HD extracts. There are a few instances where the levels of the HS-SPME extracts have similar compositional properties as the HD stem bark oil and root bark oils. Similar to this study, Garneau et al.

(2006) when investigating the hydrodistilled stem bark and root bark identified thirty six and twenty six compounds respectively when investigating the hydrodistilled stem bark and root bark. There were three principle compounds (>5%) in the hydrodistilled stem bark oil: (E)-nerolidol (54.5%), bicyclogermacrene (10.4%), and τ-cadinol (9.6%); while in the root oil there was (E)-nerolidol (54.6%), τ-cadinol (16.4%), and γ-cadinene (6.4%) as the primary compounds.

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There were six principle (>5%) compounds in the HS-SPME bark extract, they were Unknown 5, Unknown 11, Unknown 13, (E)-nerolidol, spathulenol and τ-cadinol that accounted for 75.602% of the total volatile extract. (E)-nerolidol was the primary compound with 25.371% composition while τ-cadinol was the second predominant compound with 15.049% composition of the HS-SPME bark extract. When looking at the levels of (E)-nerolidol, the reported levels of 54.5% in the stem bark oil was approximately double the experimentally detected levels using the HS-SPME extraction.

The levels of τ-cadinol were higher in the HS-SPME extraction than in the HD bark extract. Bicyclogermacrene was not identified in the HS-SPME extraction of O. horridus bark. It is possible that due to the fact the HS-SPME extractions were carried out under optimized nonisothermal conditions, (E)-nerolidol was not allowed to reach equilibrium and as such the partitioning from the bark into the water, then into the headspace prior to absorption into the PDMS stationary phase is a contributing factor to the apparent different levels between the two extraction methods as well as the variation that occurs between plant location, growing conditions and stress levels.

The four principle compounds in the HS-SPME leaf extract were (E)-γ- biasbolene, (E)-nerolidol, ar-turmerol, and τ-cadinol; together, they accounted for

57.256% of the volatile mixture. (E)-Nerolidol was the primary compound in the HS-

SPME leaf extract with a percent composition of 37.461. The second primary compound was τ-cadinol (9.315%) followed by (E)-γ-biasbolene (5.439%) and ar-turmerol

(5.033%). The percent concentration of the HS-SPME leaf extract was lower than both of the HD oils. The levels of τ-cadinol in the HS-SPME leaf was very similar to the mean

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percent composition of the chemical in the HD stem oil as it has 9.6% composition. (E)-

γ-Biasbolene and ar-turmerol were not previously identified in the HD stem oil and root oil.

The distribution of the compositions of the essential oils is different between hydrodistillation and HS-SPME. In the HD oils, there are seven stem oil components that are found at trace levels and five trace level compounds in the root essential oil while in the HS-SPME extract there are no trace level compounds in either the bark or leaf extracts. There are fewer minimal compounds (0.1% < X < 1%) in the HD extracts as the stem oil has 16 and the root oil was found to contain 13. In the present HS-SPME study, there are 35 in the bark and 22 in the leaf. In the HD essential oils, there are 9 minor compounds (1%≤ X < 5%) in the stem oil and 5 in the root oil whereas there are 7 in the bark and 13 in the leaf extracted using HS-SPME. There are fewer primary compounds

(≥5%) in the HD stem and root oils with only three primary compounds each, where as the HS-SPME extracts have 6 primary compounds in the bark and 4 in the leaf.

In total, there are nine compounds that were present at detectable levels in either the bark or the leaf HS-SPME extracts that were also identified in the HD extracts. Ar-

Curcumene, α-farnesene, δ-cadinene, (E)-nerolidol, spathulenol, gleenol, τ-cadinol, and

α-cadinol are the eight compounds in the bark, which could be compared between the

HS-SPME bark oil and the HD bark oil. The level of ar-curcumene in the bark extract was 0.315% of the volatile extract is very similar to the HD stem oil. α-Farnesene appears to be in dissimilar concentrations. It is 0.352% in the bark HS-SPME extract while in the

HD bark oil it is 1.2% which is nearly a four-fold difference. δ-Cadinene with levels of

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0.556% in the bark oil was much lower than that in either of the HD stem and root oils, which have levels of 2.5% and 3.9% respectively. The spathulenol level in the bark extract was 8.384% which appears different from that in 0.7% and 2.6% of the HD stem and root oils. The gleenol level in the bark extract (0.256%) was in the middle of both the HD stem (0.2%) and root (0.3%) oils and had similar concentrations. τ-Cadinol levels in the bark (15.049%) were dissimilar and higher than that in the HD stem oil (9.6%) but similar to the HD root oil (16.9%). α-Cadinol level in the bark was 0.474% which was very similar to that in the HD root oil (0.4%) and close to that of the HD stem oil (0.6%).

β-Farnesene, (E)-nerolidol, τ-cadinol, and α-cadinol are the four compounds in the leaf HS-SPME extracts that were also previously identified. The level of β-farnesene in the leaf (1.363%) was higher than that in the HD stem oil (0.9%) while the levels of

(E)-nerolidol was lower in the leaf than both the HD stem and root oils. τ-Cadinol level in the leaf (9.315%) was very similar to that in the HD stem oil (9.6%) but dissimilar from that in the HD root oil (16.9%). The level of α-cadinol (0.819%) in the leaf extract was higher than that in both the HD stem (0.6%) and root (0.4%) oils.

3.3.6.2 Comparison of extracted percent composition between HS-SPME and

Simultaneous Distillation and Extraction

HS-SPME and SDE were the two different extraction techniques applied to extract the volatile compounds from O. horridus bark and leaves. Both techniques have advantages and disadvantages and as a result, the combination of the data taken from each technique would offer a more comprehensive and realistic view into the actual compounds that are found in O. horridus. HS-SPME offers researchers the ability to

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extract and monitor subtle changes in real time plant stress status although at many physiological conditions, the time for equilibration would be longer for true equilibration between the plant and the headspace of the sample container than the optimized extraction parameters studied in this experiment. HS-SPME with appropriate sampling containers allows for analysis of living plants without having to remove the sample for analysis. The ability of one fiber to perform more than 100 extractions before a noticeable change in performance allows for a more cost effective and real analytical state of plant volatile release to the environment. SDE has high extraction efficiency but requires organic solvents and as a result of the selection of the solvent, the quantity and type of compounds that are extracted will vary depending on the polarity of the solvent.

Additionally, the solvent choices are somewhat limited as the solvent is required to be immiscible with water and then after extraction must be properly disposed of as they are hazardous waste. Artifact generation in the glass extraction vessel is a constant concern and the reactive nature of the large surface area of the borosilicate glass extraction vessel is also a concern. As a result, silanizing the reaction vessel and cold fingers would help to decrease the active sites on the glass but is somewhat impractical.

Experimentally, HS-SPME yielded a different number of compounds and had some similar and differing percent composition in the volatile fraction of O. horridus bark and leaf when compared to the essential oil extracted using SDE. Table 3.8 shows the paired t-test statistical comparisons between compounds by sample tissue. Nineteen compounds were identified in both the HS-SPME and SDE bark extracts. Six compounds were not found in different compositions based upon the extraction method, which

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includes: hexanoic acid, ar-curcumene, β-bisabolene, (cis)-γ-Cadinene, trans-calamene, and α-cadinol. Heptanal, octanal, nonanal, and τ-cadinol were significantly different with the minimum level of significance (α=0.10). 2-Nonanone, octanoic acid, δ-cadinene, (E)- nerolidol, spathulenol and cubenol were significantly different with the middle level of significance tested (0.05>p>0.01). 2-(E)-Decenal, α-calacorene, and unknown 13 were significantly different with the highest experimentally tested level of significance

(p<0.01).

Twenty one compounds were identified in both the HS-SPME and SDE leaf extracts. Nine compounds were not found to have significantly different compositions based upon the extraction method which include: 2-nonanone, nonanal, geraniol, (+)-3- carene, 10-(acetylmethyl)-, ar-curcumene, β-bisabolene, (cis)-γ-Cadinene, unknown 18, and τ-cadinol. β-farnesene, Cubenol, and Unknown 19 were significantly different at the lowest level of significance (0.05p>0.01). Octanoic acid, 2-undecanone, (E)-geranylacetone, ar-turmerol were significantly different with the highest experimentally tested level of significance

(p<0.01).

The temperature differences between the extractions can be attributed to a major reason that resulted differences of the recovery and percent composition between HS-

SPME and SDE. The percent composition of (E)-neroldiol was 19.050% in the SDE leaf extract and was lower than the HS-SPME leaf (37.469%) and bark (25.371%) as well as the SDE bark (41.825%) samples. There appears to be an interaction between this

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compound and the experimental conditions. Under optimized conditions for HS-SPME, the extraction occurs at 60°C which is forty degrees cooler than the 100°C that SDE and hydrodistillation are performed. Higher temperatures of extraction used in SDE compared to the HS-SPME non-equilibrium conditions, would be expected to have higher recovery and percentages of (E)-nerolidol since it has a relatively high boiling point. This is observed within the SDE bark vs HS-SPME bark since the SDE percent compotision of

(E)-nerolidol is 16.454% higher than HS-SPME bark. It is therefore hypothesized that there is some interaction taking place between (E)-nerolidol extracted from the headspace in the leaves due to the observed results. The higher temperature of extraction of SDE provides an environment that is more prone to thermal breakdown of more complex chemical structures and may result in the cleaving of glycosides from volatiles that are normally a result of an enzymatic cleavage when a plant is subject to insect feeding. One of the primary reasons for possible differences in the percent compositions between the

HS-SPME, SDE extracts (outlined in Chapter 2), and hydrodistilled essential oils are the physical means of extraction. Many volatiles stored in plants have glucosides attached which can be enzymatically hydrolyzed resulting in release of the volatiles from the tissue it is stored (42-44).

The widening of the principle compounds was due to due to their high concentration and the subsequent high response of the MS detector. Using a shorter extraction time the peaks resolved with good shape. Semivolatile compounds typically have large SPME stationary phase/headspace equilibrium constants so that the fiber depletes the amount of semivolatiles in the sample (45). Some of the experimental

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variance could be explained by active sites developing in the GC injection port liner causing sample degredation (46) .

3.3.7 Essential Oil Components

Essential oils are secondary metabolic end products produced by plants which are principally composed of terpenes and terpenoids including monoterpenes, sesquiterpenes, as well as aromatic derivatives of mono and sesquiterpenes. Essential oils are used not only as pharmaceutical components but also can be found as use in cosmetics, soaps, detergents, perfumes, packaging films, beverages, sauces, candles and more. Many of the more complex VOCs synthesized by plants are commercially used as flavors and fragrances (47). The synthesis of VOCs is important as signaling molecules as well as defense compounds but only when there is a use for them as the synthesis could cause unwanted side effects such as depletion of specific resources that could otherwise be used for growth, which in many environments any processes that take away from the ability to access nutrients and light burning through carbon stores is detrimental to the survivability of the plant.

3.3.8 Bioactivity of volatile compounds Identified in O. horridus

The principle two compounds of both the bark and leaf were (E)-nerolidol and τ- cadinol. Nerolidol is a major acyclic sesquiterpene alcohol (isoprenol) found in nature

(48) and is non-toxic and non-sensitizing (49). It is generally recognized as safe (GRAS)

(50, 51) and has been approved by the Food and Drug Administration (FDA) as a flavor

(21 CFR 172.515) (52) with annual use in the region of 10-100 metric tons (49).

Nerolidol has anti-leishmanial (51), antineoplastic (48), anti-protozoal(53, 54), anti-

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malarial (53, 54), anti-fungal (55) anti-ulcer (56), sedative (57), and trypanocidal (58) effects. Nerolidol has also been found to significantly decrease the effect of DNA mutations from azoxymethane in rats when consumed orally (48). Enhancement of the skin penetration of 5-fluorouracil suggests the use of nerolidol in improving the transdermal delivery of therapeutic drugs (59).

Nerolidol has a high degree of unsaturation structurally which lends some suggestion to the high biological activity compared to other sesquiterpenes (58).

Nerolidol has a terminal methylene group which can react with sulfhydryl groups in proteins and enhance the bioactivity of this compound (60). Inhibition of biosynthesis of dolichol, ergosterol and ubiquinones by nerolidol in Listeria amazonensis suggests that nerolidol is an hinhibitor at an early step in the isoprenoid biosynthetic pathway namely

FPP biosynthesis (51). The activity against promastigotes, in vitro-cultured amistogotes and intracellular amistogotes of L. amazonensis by nerolidol also provides insight into its biological activity (51). Nerolidol and farnesol have the ability to prevent yeast-like to mycelial growth in Candida albicans which is important to the pathogenicity associated with mycelial forms of the bacteria (61). Nerolidol improves the permeation of antibiotics and ethidium bromide into bacteria (50) and inhibits the synthesis of ubiquinone and dolichol (53, 54) which hinders the growth of Plasmodium falciparum growth in vitro

(62).

Cytotoxity without mutagenicity is an important quality of most therapeutic uses of essential oils (63). In vitro assays of essential oils containing nerolidol have shown cytotoxic activity when assessed against human lung carcinoma cell line A-549 and

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human colon adenocarcinoma cell line DLD-1 with 50% inhibition levels of 6.4±0.4 and

5.8±0.04 µg/mL (64). Nerolidol has cytotoxic activity against hormone dependent prostate carcinoma LNCaP at a concentration of 15.56±0.22 (65).

τ-Cadinol has been found in numerous plants including Heteropyxis dehniae,

Laggera aurita Schulz, Lantana camara, and Juniperus sect. Juniperus but its biological activity has not presently been identified to date. Spathulenol has not had its biological activity identified to date. β-bisabolene has been tested for cytotoxicity against A549,

MCF7, KB, and human vincristine resistant KBVin cells for biological activity with unspecified biological activity. β-farnesene is an alarm pheromone which repels aphids and attracts aphid consuming enemies under laboratory conditions (66, 67).

Similarly with Garneau’s work, the majority of compounds extracted using HS-

SPME were terpenes and terpenoids. Previously, the volatile compounds consisted of sesquiterpenes and oxygenated sesquiterpenes with the exception of the five most volatile compounds, monoterpenes and conjugated polyenes (7). Due to lipophilic nature of terpenoids, there is an affinity for and partitioning within the lipid bilayer in biological membranes which may significantly impact both the structural and functional properties

(68). This is a likely cause for the ability to increase permeability to extracellular compounds such as ethidium bromide and antibiotics (50).

3.4 Conclusions

HS-SPME can be applied as a high resolution qualitative extraction method for sampling a large variety of target analytes. Optimization of the extraction can help to maximize the detectability of trace compounds and when coupled to a MS detector

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identification of compounds is made possible even with low initial sample concentration and weight. HS-SPME offers low levels of baseline noise which helps to enhance the levels of detection and quantitation when using a GC-MS for qualitative identification and relative percent compositions of complex plant volatiles from different matrices. The biological activity of the principle components of the essential oil would support the use of Oplopanax horridus as a medicinal plant based upon the physiological and observed bioactive properties of its component chemicals.

Acknowledgements:

Much gratitude is wished to be expressed to Mr. David Smith for supplying the

Oplopanax horridus samples for analysis and Dr. Julia Sharp for her gracious assistance in the statistical analysis coding.

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3.5 Figures and Tables

Table 3.1 Operating Parameters of the GC-MS

GC Conditions Type of GC GC-17A (Shimadzu, Tokyo, Japan) Injection Port Splitless (3.5mm ID liner) Temperature of 250°C injector Desorption time 60 s Analytical column 60m x 0.25mm ID DB5-MS x 0.25µm film thickness (Agilent J&W, Santa Clara, CA, USA) Temperature program 50°C (2min hold), 5°C/min 150°C (2 min hold), 1°C/min 180°C (2min hold), 10°C/min 250°C (10 min hold) Temperature of GC- 250°C MS interface Carrier Gas He (24.3cm/s) 99.999%

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Table 3.2 SPME Absorption Isotherms Modeling effect of Sample Temperature on MS Response

Statistical Estimates a a a 2 Compound β0 P-Value S β1 P-Value S β2 P-Value S R b Octanal 4.454E+06 b 2-Nonanone 2.960E+06 b Octanoic Acid 1.661E+06 Cis-γ-Cadinene 4.409E+07 0.1000 NS -1.730E+06 0.0666 * 1.778E+04 0.0280 ** 0.709 Unknown 4 2.452E+07 0.0194 ** -1.015E+06 0.0074 *** 1.078E+04 0.0014 *** 0.891 (E)-Nerolidol 9.050E+07 0.2975 NS -5.586E+06 0.0926 * 9.428E+04 0.0079 *** 0.990 Spathulenol 3.241E+07 0.0533 * -1.490E+06 0.0149 ** 1.819E+04 0.0013 *** 0.943 Cubenol 1.776E+07 0.0004 *** -6.528E+05 0.0003 *** 6.202E+03 <0.0001 *** 0.879 τ-Cadinol 1.243E+08 0.0075 *** -5.196E+06 0.0020 *** 5.496E+04 0.0003 *** 0.938 Sa Levels of significance are as follows: NS= Not Significantly Different, * α= 0.1, ** α= 0.05, ***α=0.01 b represents the mean area under the curve for compounds that were not better modeled using more complex models

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Table 3.3 SPME Absorption Isotherms for Sample Absorption time at 60°C on MS Response

Statistical Estimates a a a 2 Compound β0 P-Value S β1 P-Value S β2 P-Value S R Octanal 9379101 <0.0001 *** 334076 <0.0001 *** -1114 0.0028 *** 0.951 2-Nonanone 4721491 <.0001 *** 161250 <.0001 *** -556 0.0001 *** 0.974 Octanoic Acid 5666711 0.0007 *** 195894 0.0046 *** -512 0.2962 NS 0.787 Cis-γ-Cadinene 1148968 0.0213 ** 430130 <.0001 *** -1581 <.0001 *** 0.991 Unknown 4 1338283 0.3774 NS 1479747 <.0001 *** -8147 <.0001 *** 0.983 Unknown 7 1778436 0.0915 NS 489215 <.0001 *** -2987 <.0001 *** 0.919 Unknown 9 9187049 0.1344 NS 2754367 <.0001 *** -18359 <.0001 *** 0.897 (E)-Nerolidol 36997561 0.0035 *** 5809338 <.0001 *** -28445 <.0001 *** 0.956 Unknown 13 3603743 0.21 NS 2983840 <.0001 *** -16434 <.0001 *** 0.985 Spathulenol 390350.4 0.5793 NS 327932 <.0001 *** -1588 <.0001 *** 0.945 Cubenol 429976.6 0.4543 NS 360917 <.0001 *** -1670 <.0001 *** 0.971 τ-Cadinol 4049030 0.3995 NS 3645098 <.0001 *** -17642 <.0001 *** 0.979 Sa Levels of significance are as follows: NS= Not Significantly Different, * α= 0.1, ** α= 0.05, ***α=0.01

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Table 3.4 Volatile Compounds of Oplopanax horridus HS-SPME extract

Leaf SD Leaf

Bark SD Bark

Bark

Leaf

Compounda Heptanal 910 0.431 0.055 0.130 0.151 Hexanoic Acid 974 0.752 0.087 - - Octanal 1005 2.786 0.183 0.756 0.115 2-Octenal 1061 - - 0.404 0.029 Heptanoic Acid 1068 0.334 0.015 - - 2-Nonanone 1092 1.272 0.020 1.088 0.070 2-Nonanol 1102 - - 0.437 0.138 Nonanal 1107 0.182 0.012 0.450 0.106 3-Dodecyne 1130 0.166 0.007 - - 2-Nonenal, (E)- 1164 0.389 0.030 - - Octanoic Acid 1167 1.577 0.485 0.306 0.037 Pyrazine, 2,3-dimethyl-5-(1- 1194 - - 0.553 0.097 methylpropyl)- Decanal 1208 - - 0.527 0.015 Geraniol 1250 - - 0.485 0.053 2-Decenal, (E) 1264 0.662 0.006 0.345 0.058 1,8-Octandiol 1283 - - 0.208 0.069 1,2-Dihydrolinalool 1291 - - 0.159 0.042 2-Undecanone 1293 - - 0.444 0.084 2-Dodecanol 1303 - - 0.685 0.182 3-Decen-2-one 1341 - - 0.384 0.043 α-Cubebene 1355 0.106 0.008 - - 2-Butyl-2,7-octadien-1-ol 1373 0.145 0.014 - - α-Copaene 1388 0.161 0.032 - - (+)-3-Carene, 10- 1393 - - 0.375 0.297 (acetylmethyl)- β-Longipinene 1400 0.154 0.020 - - Tetradecane 1401 - - 0.388 0.085 (E)-Geranylacetone 1447 0.555 0.006 2.039 0.183 Caryophyllene (9-epi-(E)-) 1452 0.463 0.074 - - β-Farnesene 1452 - - 1.363 0.378 Ar-Curcumene 1487 0.315 0.277 - - Zingiberene 1501 0.106 0.002 2.230 0.640

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α-Farnesene 1505 0.352 0.023 - - β -Bisabolene 1513 0.135 0.012 2.730 0.830 (cis)-γ-Cadinene 1524 2.021 0.295 1.135 0.292 σ-Cadinene 1525 - - 0.472 0.065 δ-Cadinene 1526 0.556 0.027 - - Calamenene 1528 0.246 0.028 - - (E)-γ-Bisabolene 1529 - - 5.439 1.544 Calamene (Trans-) 1530 0.364 0.016 - - Unknown 2 1536 0.533 0.030 - - Unknown 3 1538 0.197 0.005 - -

2(4H)-Benzofuranone, 5,6,7,7a- 1540 - - 0.710 0.053 tetrahydro-4,4,7a-trimethyl-

Unknown 5 1544 5.619 0.585 - - α-Calacorene 1550 0.463 0.013 - - Unknown 6 1552 0.727 0.035 - - Unknown 8 1556 1.863 0.167 - - Unknown 10 1558 - - 2.375 0.254 Unknown 11 1561 9.238 0.357 - - E-Nerolidol 1562 25.371 2.223 37.469 3.991 Unknown 12 1573 - - 2.496 0.169 Unknown 13 1577 11.941 0.747 - - Unknown 14 1582 - - 1.628 0.107 Unknown 15 1585 1.408 0.067 - - Turmerol (ar-) 1588 - - 5.033 0.473 Spathulenol 1592 8.384 0.328 - - Unknown 16 1604 0.135 0.010 - - Gleenol 1606 0.256 0.013 - - Veridiflorol 1608 0.431 0.010 - - Unknown 17 1611 0.225 0.041 - - Unknown 18 1614 - - 1.503 0.405 Cubenol 1624 1.510 0.084 1.261 0.220 Unknown 19 1639 - - 0.722 0.161 trans-Z- α-Bisabolene epoxide 1666 0.101 0.019 - - t-cadinol 1652 15.049 0.965 9.315 0.557 α-Cadinol 1662 0.474 0.044 0.819 0.266 trans-Z- α-Bisabolene epoxide 1666 0.101 0.019 - - α-Bisabolol 1672 0.198 0.038 - - Unknown 20 1678 0.305 0.039 - -

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Apritone (Z-) 1695 - - 1.717 0.170 Acorenone 1699 - - 1.480 1.218 Heptadecane 1699 0.213 0.025 - - Oplopanone 1740 0.645 0.059 - - Unknown 22 1747 - - 0.997 0.155 a Identifications based on Mass spectral data and linear retention indicies on DB-5MS b Retention index based on DB-5MS capillary column using custom temperature programming Unknown compounds in order of Retention Index are based upon combined data set of all identified mass spectra "-" Signifies compounds not detected

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Table 3.5 Electron Ionization Quadrupole Mass Spectra of Principle Ions for Unknown Compounds in Oplopanax horridus extracted using SPME

Principle Ions 1 2 3 4 5

6 7 8 9 10 Unknown KIb 2 1536 43.00 (100.00) 108.10 (55.31) 71.00 (32.46) 126.15 (30.65) 111.10 (27.89) 93.00 (24.26) 127.10 (21.38) 83.10 (20.71) 41.05 (20.10) 69.05 (16.82) 3 1538 143.15 (100.00) 43.00 (98.70) 85.05 (70.18) 125.05 (50.04) 71.00 (40.63) 81.05 (27.99) 41.05 (26.47) 54.95 (25.47) 58.95 (18.58) 107.10 (18.32) 5 1544 43.00 (100.00) 143.05 (99.83) 125.05 (49.28) 85.05 (43.35) 71.00 (42.10) 41.00 (26.31) 54.95 (24.61) 81.05 (20.87) 107.05 (17.17) 83.05 (16.25) 6 1552 43.00 (100.00) 109.15 (95.12) 69.1 (82.90) 41.05 (57.24) 54.95 (33.93) 93.05 (30.01) 138.1 (26.86) 71.05 (23.13) 67.05 (19.98) 81.05 (17.71) 8 1556 43.10 (100.00) 69.15 (70.19) 41.10 (69.13) 109.20 (51.85) 55.10 (36.10) 71.10 (19.86) 67.10 (16.19) 93.15 (15.78) 81.15 (12.89) 111.20 (12.69) 10 1558 43.15 (100.00) 41.10 (90.67) 73.10 (54.65) 69.15 (51.30) 55.15 (50.21) 60.10 (46.44) 109.20 (32.88) 57.15 (24.68) 71.15 (20.90) 42.15 (15.69) 11 1561 109.10 (100.00) 43.00 (89.55) 69.10 (66.41) 41.00 (37.92) 55.00 (26.48) 111.10 (20.39) 71.05 (20.15) 93.05 (17.10) 138.10 (16.02) 83.10 (14.89) 12 1573 109.10 (100.00) 43.00 (93.03) 69.10 (84.83) 41.00 (56.30) 55.00 (32.58) 93.05 (28.81) 71.05 (24.13) 111.10 (18.76) 67.00 (18.29) 80.95 (16.68)

140

13 1577 177.10 (100.00) 159.15 (48.06) 119.05 (45.07) 135.15 (22.77) 105.10 (21.90) 220.15 (18.33) 91.05 (16.49) 178.15 (16.34) 107.10 (16.00) 117.05 (13.52) 14 1582 43.00 (100.00) 93.00 (73.57) 119.05 (41.18) 40.95 (36.84) 91.00 (31.87) 162.15 (29.59) 147.05 (26.91) 78.90 (23.23) 105.05 (22.53) 107.40 (21.75) 15 1585 43.00 (100.00) 93.00 (73.57) 119.05 (41.18) 40.95 (36.84) 91.00 (31.87) 162.15 (29.59) 147.05 (26.91) 78.90 (23.23) 105.05 (22.53) 107.1 (21.75) 16 1604 81.10 (100.00) 41.15 (99.66) 55.10 (79.59) 91.10 (78.68) 79.10 (62.48) 161.30 (60.43) 43.10 (55.08) 77.00 (49.26) 107.45 (49.23) 123.15 (48.85) 17 1611 43.00 (100.00) 41.05 (31.33) 109.15 (28.72) 70.90 (28.49) 54.95 (24.49) 81.10 (21.19) 79.05 (20.30) 93.10 (19.63) 95.10 (19.35) 137.10 (18.19) 18 1614 42.95 (100.00) 109.40 (55.73) 107.10 (54.58) 122.15 (53.11) 41.05 (53.05) 69.05 (46.71) 55.00 (39.83) 161.15 (39.31) 81.10 (35.54) 93.05 (35.22) 19 1639 42.95 (100.00) 41.05 (48.21) 109.10 (44.52) 69.05 (39.77) 93.10 (27.49) 55.05 (26.32) 67.00 (24.98) 81.05 (23.38) 68.05 (22.46) 71.05 (22.43) 20 167 8 42.95 (100.00) 111.10 (95.58) 41.05 (42.50) 83.05 (37.93) 55.00 (32.81) 68.85 (30.46) 177.10 (29.91) 126.10 (27.50) 97.1 (21.90) 108.10 (20.65) 22 1747 147.1 (100.00) 41.05 (70.97) 69.05 (53.46) 43.05 (50.86) 91.05 (42.59) 79.1 (42.19) 105.05 (41.95) 119.1 (37.39) 175.15 (37.37) 93.05 (32.39)

141

Table 3.6 Paired T-test Statistical Analysis of Bark and Leaf Percent Composition of Oplopanax horridus extracted using SPME

Bark vs Leaf Percent Bark vs Leaf Composition Concentration

Significance Significance

Level Level of Level of

P P

- -

Value Value

Compounda KIb Heptanal 910 0.096 * 0.073 *

Octanal 1005 0.006 *** 0.004 ***

2-Nonanone 1092 0.025 ** 0.001 ***

Nonanal 1107 0.040 ** 0.004 ***

Octanoic Acid 1167 0.043 ** 0.039 **

2-Decenal, (E-) 1264 0.011 ** 0.001 ***

(E)-Geranylacetone 1447 0.005 *** 0.005 ***

Ar-Curcumene 1487 0.018 ** 0.170 -

Zingiberene 1501 0.029 ** 0.143 -

β -Bisabolene 1513 0.033 ** 0.178 -

(cis)-γ-Cadinene 1524 0.054 * 0.010 **

E-Nerolidol 1562 0.048 ** 0.004 ***

Cubenol 1624 0.244 - 0.003 ***

τ-cadinol 1652 0.014 ** 0.002 ***

α-Cadinol 1662 0.130 - 0.001 ***

a Identifications based on Mass spectral data and linear retention indices on DB-5MS b Retention index based on DB-5MS capillary column using custom temperature programming Significance is characterized as (*) α=0.1, (**) α=0.05, (***) α=0.01, (-) = samples are not significantly different

142

Table 3.7 Percent Composition of HS-SPME and SDE Volatile Extracts

HS-SPME SDE

Leaf SD Leaf

Bark SD Bark SDBark

Leaf SD Leaf

Bark Bark

Leaf Leaf

% %

Compounda Heptanal 910 0.431 0.055 0.130 0.151 1.456 0.542 - - 5-methylfurfural 966 ------0.621 0.085 Hexanoic Acid 974 0.752 0.087 - - 1.262 0.922 0.736 0.023 2,4-Heptadienal, 993 1.300 0.112 (E,E)------Octanal 1005 2.786 0.183 0.756 0.115 4.363 0.693 2.319 0.427 Unknown 1 1016 ------0.988 0.077 Benzeneacetaldehyde 1051 ------2.236 0.182 2-Octenal 1061 - - 0.404 0.029 - - - - Heptanoic Acid 1068 0.334 0.015 ------2-Nonanone 1092 1.272 0.020 1.088 0.070 0.881 0.121 1.066 0.183 2-Nonanol 1102 - - 0.437 0.138 - - - - Nonanal 1107 0.182 0.012 0.450 0.106 0.460 0.135 0.602 0.067 Phenylethyl Alcohol 1120 ------2.873 0.211 3-Dodecyne 1130 0.166 0.007 ------2-Nonenal, (E)- 1164 0.389 0.030 - - - - 0.800 0.166 Octanoic Acid 1167 1.577 0.485 0.306 0.037 2.510 0.712 2.357 0.109 Pyrazine, 2,3- 1194 - - 0.553 0.097 - - - - dimethyl-5-(1- methylpropyl)- n-Octyl acetate 1207 - - - - 0.235 0.032 - - Decanal 1208 - - 0.527 0.015 - - - -

143

Geraniol 1250 - - 0.485 0.053 - - 0.557 0.035 Nonanoic acid 1256 - - - - 0.092 0.108 1.360 0.057 2-Decenal, (E) 1264 0.662 0.006 0.345 0.058 0.959 0.029 - - 1,8-Octandiol 1283 - - 0.208 0.069 - - - - 1,2-Dihydrolinalool 1291 - - 0.159 0.042 - - - - 2-Undecanone 1293 - - 0.444 0.084 - - 0.747 0.058 2,4-Decadienal, (E- Z) 1299 ------0.710 0.025 2-Dodecanol 1303 - - 0.685 0.182 - - - - 2,4-Decadienal, (E,E)- 1322 ------2.275 0.093 3-Decen-2-one 1341 - - 0.384 0.043 - - 0.583 0.009 α-Cubebene 1355 0.106 0.008 ------n-Decanoic acid 1360 ------0.697 0.012 2-Butyl-2,7- 1373 0.145 0.014 octadien-1-ol ------α-Copaene 1388 0.161 0.032 ------(+)-3-Carene, 10- 1393 0.375 0.297 0.742 0.077 (acetylmethyl)- - - - - β-Longipinene 1400 0.154 0.020 ------Tetradecane 1401 - - 0.388 0.085 - - - - 2-decenoic acid 1401 ------0.798 0.095 γ-Elemene 1437 ------0.210 0.019 (E)-Geranylacetone 1447 0.555 0.006 2.039 0.183 - - 0.990 0.031 Caryophyllene (9- 1452 0.463 0.074 epi-(E)-) ------

144

β-Farnesene 1452 - - 1.363 0.378 5.836 3.049 2.885 0.546 Dehydro- 1461 0.516 0.539 aromadendrene ------Ar-Curcumene 1487 0.315 0.277 - - 0.311 0.029 9.838 0.637 (Z)-α-Farnesene 1489 - - - - 0.170 0.012 - - Zingiberene 1501 0.106 0.002 2.230 0.640 - - 4.569 0.521 Cubenene 1501 - - - - 0.164 0.195 - - α-Farnesene 1505 0.352 0.023 - - 2.149 1.152 0.419 0.252 β -Bisabolene 1513 0.135 0.012 2.730 0.830 0.440 0.216 3.504 0.205 (cis)-γ-Cadinene 1524 2.021 0.295 1.135 0.292 1.284 0.297 0.783 0.036 σ-Cadinene 1525 - - 0.472 0.065 - - - - δ-Cadinene 1526 0.556 0.027 - - 0.434 0.060 0.393 0.003 Calamenene 1528 0.246 0.028 ------(E)-γ-Bisabolene 1529 - - 5.439 1.544 - - - - β- Sesquiphellandrene 1529 ------5.824 0.490 Calamene (Trans-) 1530 0.364 0.016 - - 0.428 0.056 - - Unknown 2 1536 0.533 0.030 ------Unknown 3 1538 0.197 0.005 ------2(4H)- Benzofuranone, 1540 - - 0.710 0.053 - - - - 5,6,7,7a-tetrahydro- 4,4,7a-trimethyl- Unknown 4 1541 - - - - 2.000 0.146 - - Unknown 5 1544 5.619 0.585 ------

145

α-Calacorene 1550 0.463 0.013 - - 0.826 0.035 - - Unknown 6 1552 0.727 0.035 ------Unknown 7 1554 - - - - 0.635 0.029 - - Unknown 8 1556 1.863 0.167 ------Unknown 9 1557 - - 6.503 0.194 - - Unknown 10 1558 - - 2.375 0.254 - - Unknown 11 1561 9.238 0.357 - - - - 2.289 0.251 E-Nerolidol 1562 25.371 2.223 37.469 3.991 41.825 6.315 19.050 0.802 Unknown 12 1573 - - 2.496 0.169 - - - - Unknown 13 1577 11.941 0.747 - - 5.742 0.283 - - Unknown 14 1582 - - 1.628 0.107 0.644 0.207 - - Unknown 15 1585 1.408 0.067 ------Turmerol (ar-) 1588 - - 5.033 0.473 - - 1.464 0.088 Spathulenol 1592 8.384 0.328 - - 4.659 0.600 4.718 0.146 α-Bisabolol 1598 - - - - 0.270 0.128 - - Globulol 1599 ------0.611 0.030 Unknown 16 1604 0.135 0.010 ------Gleenol 1606 0.256 0.013 ------Veridiflorol 1608 0.431 0.010 - - - - 0.397 0.011 Unknown 17 1611 0.225 0.041 ------Unknown 18 1614 - - 1.503 0.405 - - 1.082 0.150 Sesquisabinene 1619 0.517 0.048 hydrate (cis-) ------

146

Cubenol 1624 1.510 0.084 1.261 0.220 0.916 0.129 0.913 0.080 (-)-Caryophyllene 1638 0.459 0.137 oxide ------Unknown 19 1639 - - 0.722 0.161 - - 1.224 0.108 trans-Z- α- 1666 0.101 0.019 Bisabolene epoxide ------t-cadinol 1652 15.049 0.965 9.315 0.557 11.930 0.617 9.908 0.715 Himachalol 1656 ------0.559 0.025 α-Cadinol 1662 0.474 0.044 0.819 0.266 0.224 0.044 1.594 0.049 trans-Z- α- 0.101 0.019 Bisabolene epoxide 1666 ------α-Bisabolol 1672 0.198 0.038 ------Unknown 20 1678 0.305 0.039 ------Apritone (Z-) 1695 - - 1.717 0.170 - - - - Acorenone 1699 - - 1.480 1.218 - - - - Heptadecane 1699 0.213 0.025 ------Unknown 21 1717 ------0.594 0.116 Oplopanone 1740 0.645 0.059 ------Unknown 22 1747 - - 0.997 0.155 - - - - Tetradecanoic acid 1760 ------1.300 0.667 a Identifications based on Mass spectral data and linear retention indicies on DB-5MS b Retention index based on DB-5MS capillary column using custom temperature programming "-" Signifies compound levels below detection

147

Table 3.8 Paired T-Test Statistical Analysis of the Bark and Leaf Composition of Oplopanax horridus comparing SPME and SDE extraction methods

SPME vs SDE Bark Leaf Composition Composition

Significance Significan

Level Level of Level of

P P

- -

Value Value

Compounda KIb Heptanal 910 0.068 *

Hexanoic Acid 974 0.589 -

Octanal 1005 0.087 * 0.035 **

2-Nonanone 1092 0.037 ** 0.885 -

Nonanal 1107 0.080 * 0.242 -

Octanoic Acid 1167 0.045 ** 0.001 ***

Geraniol 1250 0.266 -

2-Decenal, (E) 1264 0.004 ***

2-Undecanone 1293 0.004 ***

3-Decen-2-one 1341 0.011 **

10-(acetylmethyl)-(+)- 1393 0.113 - 3-Carene (E)-Geranylacetone 1447 0.007 ***

β-Farnesene 1452 0.097 *

Ar-Curcumene 1487 0.982 - 0.522 -

Zingiberene 1501 0.035 **

β -Bisabolene 1513 0.142 - 0.322 -

(cis)-γ-Cadinene 1524 0.120 - 0.204 -

148

δ-Cadinene 1526 0.028 **

trans-Calamene 1530 0.234 -

α-Calacorene 1550 0.006 ***

E-Nerolidol 1562 0.036 ** 0.022 **

Unknown 13 1577 0.009 ***

Ar-turmerol 1588 0.006 ***

Spathulenol 1592 0.016 **

Unknown 18 1614 0.263 -

Cubenol 1624 0.040 ** 0.051 *

Unknown 19 1639 0.079 *

t-cadinol 1652 0.065 * 0.479 -

α-Cadinol 1662 0.186 - 0.049 ** a Identifications based on Mass spectral data and linear retention indicies on DB-5MS b Retention index based on DB-5MS capillary column using custom temperature programming Significance is characterized as (*) α=0.1, (**) α=0.05, (***) α=0.01, (-) = samples are not significantly different

149

Figure 3.1 GC-MS Total Ion Chromatogram of optimized HS-SPME extraction of Oplopanax horridus Bark

150

Figure 3.2 GC-MS Total Ion Chromatogram of optimized HS-SPME extraction of Oplopanax horridus Leaf

151

t-cadinol 250

(E)-Nerolidol Millions Octanal

200

150

Area CountArea 100

0 40 45 50 55 60 65 70 75 80 Sample Temperature (°C)

Figure 3.3 Effect of Sample Temperature on Detector Response.

152

t-cadinol 350 (E)-nerolidol

Millions 300 Octanal 2-nonanone

250

200

Area Units Area 150

100

0 0 20 40 60 80 100 120 Absorption Time

Figure 3.4 Effect of Sample Absorption Time on Detector Response.

153

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CHAPTER FOUR

GENERAL CONCLUSIONS

The volatile compounds which can be attributed to animal attractant, anti-feedant, alarm signaling, and general defense compounds are all important in the complex bouquet of volatile organic compounds that are released into the environment by the plant. The volatile constituents in the tissues are related to their habitat, stress level, and means of extraction. The regional area where O. horridus was cultivated and wild harvested outside of Anchorage, Alaska, USA could also have a different group of volatiles necessary for plant signaling in a specific microenvironment. The effect of wild harvesting of medicinal plants poses its own unique set of obstacles for homogeneous sampling units although if representative samples are removed within a specific environmental ecosystem, the type of volatile defense and signaling compounds synthesized may provide insight into the nature of the predatory response within the ecosystem.

The volatile constituents and their percent composition and concentration levels in

Oplopanax horridus were determined through two extraction methods SDE and HS-

SPME. Sesquiterpenes were the major group to contribute to the volatile fraction of O. horridus regardless of extraction method. Additionally, of the 103 compounds spectrally identified in this research, 81 were tentatively identified in O. horridus and grouped into different chemical groups including: aldehydes, alkanes, alkynes, carboxylic acids, monoterpenes, sesquiterpenes, N-containing, and furans. The volatiles identified and categorized by extraction method and tissue type (i.e. bark and leaves) showed

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differences in the distribution of compounds is different between both extraction types within a tissue, and also between tissues. Each type of extraction means from plants provides one piece of information regarding the nature of the compounds produced within a specific plant as some means of extraction such as SDE and steam distillation require high temperature and introduce problems such as lipid oxidation and artifacting of compounds. An alternative of extraction such as HS-SPME can be applied not only on harvested plant samples, but also can be used to identify and track changes in the symphony of compounds synthesized and subsequently released to the environment from living plants if appropriate sampling measures are taken. HS-SPME offers suitable trace level analysis of compounds. When optimized, it can help to decrease the sampling time and can be used to measure the stress status of a plant. HS-SPME offers low levels of baseline noise which helps to enhance the levels of detection and quantitation when using a GC-MS for qualitative identification and relative percent compositions of complex plant volatiles from different matrices.

Additional means of extraction of the volatiles from O. horridus such as supercritical fluid extraction (SFE) or solvent extraction would continue to provide insight into the overall volatile profile of devil’s club. This would allow for a more thorough investigation into optimized plant extractions resulting in the highest yields of key bioactive compounds of interest. These volatiles may serve not only as bioactive chemicals in their novel state but can also serve as synthetic precursors for therapeutic drugs.

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The high degree of bioactivity of the identified compounds from O. horridus provides support into the many applied medical uses. The principle compounds (E)- nerolidol and τ-cadinol have been principle compounds in the different extracts from leaves, root bark and stem bark of O. horridus. Their bioactivity should be further studied to see what ways they interact with cells utilizing both in vitro and in vivo analyses if their functionality is to truly be understood for its pharmaceutical applications. The synthesis of a wide number of structurally unique sesquiterpenes such as (E)-nerolidol which can then undergo a number of directed organic reactions to generate mono- and poly-cyclic sesquiterpenes may also be a key area to study due to the high percentage of

(E)-nerolidol in each of the extraction methods. Further research applying additional spectroscopic analysis of the unknown compounds that were not able to be elucidated using their mass spectra and nonisothermal Kovats indicies would provide identification of the real make up of the O. horridus volatile extracts. NMR could be used to identify the structures of the unknown and confirm purified samples to then be tested using in vitro studies for cancer therapy as well as determining the antioxidant and bioactivity of the O. horridus essential oil.

Overall, the environment, stress state of the plant, and the complex interactions that take place within the ecosystem the O. horridus samples are harvested have a critical role in the volatile profile of the plant. Compiling the volatile metabolome of O. horridus and combining it with the known compounds from solvent extracts of O. horridus provide scientific justification for the traditional uses and can assist in unraveling the true defense mechanisms that devil’s club uses to survive and thrive in its ecosystem.

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