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5-2012

EXTRACTION AND IDENTIFICATION OFVOLATILE CONSTITUENTS OFOPLOPANAX HORRIDUSGregory JonesClemson University, gregjones111887@gmail.com

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Recommended CitationJones, Gregory, "EXTRACTION AND IDENTIFICATION OF VOLATILE CONSTITUENTS OF OPLOPANAX HORRIDUS "(2012). All Theses. 1327.https://tigerprints.clemson.edu/all_theses/1327

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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

ii

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

iii

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.

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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.

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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.

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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

vii

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

viii

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

ix

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

x

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

1

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

2

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).

3

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).

4

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

5

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

6

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).

7

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

8

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.

9

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).

10

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).

11

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

12

causing inhibition of cell proliferation at dose dependant concentrations (23). The anti-

proliferation 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-

13

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

14

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

15

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

16

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

17

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

18

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

19

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).

20

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

21

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

22

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

23

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

24

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).

25

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

26

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

27

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).

28

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

concentration obey the following equation of 2

0

1sn KV C where ns is the moles of analyte

absorbed by the stationary phase, K is the distribution constant of an analyte between the

stationary and aqueous phases, V1 is volume of the stationary phase and C20 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).

29

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

30

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

31

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

32

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

33

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-

34

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

35

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

36

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).

37

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

38

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

39

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

40

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

41

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

42

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

43

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

44

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

45

(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

46

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).

47

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

48

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).

49

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).

50

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66

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

67

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

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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

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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.

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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.

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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

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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

73

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-

isothermal KI values were calculated using the equation 1

( )

( )100 100 x n

n n

x

t t

t tnKI

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

74

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.

75

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

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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

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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

78

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-

79

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).

80

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

81

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).

82

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

83

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

84

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

85

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.

86

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.

87

2.5 Figures and Tables

Table 2.1 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

injector 250°C

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-

MS interface 250°C

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)

88

Table 2.2 Volatile Composition of Oplopanax horridus Essential Oil Extracted by

Simultaneous Distillation Extraction

Compounda

KIb

Bark

%

Bark

SD

Leaf %

Leaf S

D

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,

(E,E)- 993 - - 1.300 0.112

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-

(acetylmethyl)- 1393 - - 0.742 0.077

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-

aromadendrene 1461 0.516 0.539 - -

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 - -

89

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

hydrate (cis-) 1619 - - 0.517 0.048

Cubenol 1624 0.916 0.129 0.913 0.080

(-)-Caryophyllene

oxide 1638 0.459 0.137 - -

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

90

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

Unknown KIb

6 7 8 9 10

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)

91

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

Compounda KI

b

P-V

alue

Lev

el of

Sig

nifican

ce

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

92

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

Distillation Extraction

93

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

Distillation Extraction

94

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101

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

105

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

106

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,

107

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

( ) ( )

( 1) ( )

100* 100r A r n

r n r n

t tKI n

t t

where tr(A) is the analyte retention time, tr(n) is the

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,

108

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

β0, β1 and β2 terms was fitted first and had a coefficient of determination (R2 = 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

modeled after Y=β0+β1X+β2X2+ε. Area under the peak curve from the mass spectral total

ion chromatogram was modeled as Area=β0+β1(Concentration)+β2(Concentration)2+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 (0.05<p<0.10). Octanal, 3-decen-2-one, zingiberene, (E)-

nerolidol, and α-cadinol were significantly different with the middle level of significance

tested (0.05>p>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

129

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

130

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-

131

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

132

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

133

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.

134

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

injector 250°C

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-

MS interface 250°C

Carrier Gas 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)

135

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

Statistical Estimates

Compound β0 P-Value Sa β1 P-Value S

a β2 P-Value S

a R

2

Octanalb 4.454E+06

2-Nonanoneb 2.960E+06

Octanoic Acidb 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

136

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

Statistical Estimates

Compound β0 P-Value Sa β1 P-Value S

a β2 P-Value Sa R

2

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

137

Table 3.4 Volatile Compounds of Oplopanax horridus HS-SPME extract

Compounda

RIb

Bark

%

Bark

SD

Leaf %

Leaf S

D

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-

methylpropyl)- 1194 - - 0.553 0.097

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-

(acetylmethyl)- 1393 - - 0.375 0.297

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

138

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-

tetrahydro-4,4,7a-trimethyl- 1540 - - 0.710 0.053

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 - -

139

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

140

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

Unknown KIb

6 7 8 9 10

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)

141

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 1678 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)

142

Table 3.6 Paired T-test Statistical Analysis of Bark and Leaf Percent Composition of

Oplopanax horridus extracted using SPME

Bark vs Leaf

Percent

Composition Bark vs Leaf

Concentration

Compounda KI

b

P-V

alue

Lev

el of

Sig

nifican

ce

P-V

alue

Lev

el of

Sig

nifican

ce

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

143

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

HS-SPME SDE

Compounda

KIb

Bark

%

Bark

SD

Leaf %

Leaf S

D

Bark

%

Bark

SD

Leaf %

Leaf S

D

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,

(E,E)- 993

- - - -

- - 1.300 0.112

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-

dimethyl-5-(1-

methylpropyl)-

1194 - - 0.553 0.097

- - - -

n-Octyl acetate 1207 - - - - 0.235 0.032 - - Decanal 1208 - - 0.527 0.015 - - - -

144

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-

octadien-1-ol 1373 0.145 0.014

- -

- - - - α-Copaene 1388 0.161 0.032 - - - - - -

(+)-3-Carene, 10-

(acetylmethyl)- 1393

- - 0.375 0.297

- - 0.742 0.077

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-

epi-(E)-) 1452 0.463 0.074

- -

- - - -

145

β-Farnesene 1452 - - 1.363 0.378 5.836 3.049 2.885 0.546

Dehydro-

aromadendrene 1461

- - - - 0.516 0.539

- - 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,

5,6,7,7a-tetrahydro-

4,4,7a-trimethyl-

1540 - - 0.710 0.053

- - - -

Unknown 4 1541 - - - - 2.000 0.146 - - Unknown 5 1544 5.619 0.585 - - - - - -

146

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

hydrate (cis-) 1619

- - - -

- - 0.517 0.048

147

Cubenol 1624 1.510 0.084 1.261 0.220 0.916 0.129 0.913 0.080

(-)-Caryophyllene

oxide 1638

- - - - 0.459 0.137

- - Unknown 19 1639 - - 0.722 0.161 - - 1.224 0.108

trans-Z- α-

Bisabolene epoxide 1666 0.101 0.019

- -

- - - - 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-

Bisabolene epoxide 1666 0.101 0.019

- -

- - - - 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

148

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

Composition Leaf

Composition

Compounda KI

b

P-V

alue

Lev

el of

Sig

nifican

ce

P-V

alue

Lev

el of

Sig

nifican

ce

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)-(+)-

3-Carene 1393

0.113 -

(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 -

149

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

150

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

151

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

152

Figure 3.3 Effect of Sample Temperature on Detector Response.

0

50

100

150

200

250

40 45 50 55 60 65 70 75 80

Are

a C

ou

nt

Mill

ion

s

Sample Temperature (°C)

t-cadinol

(E)-Nerolidol

Octanal

153

Figure 3.4 Effect of Sample Absorption Time on Detector Response.

0

50

100

150

200

250

300

350

0 20 40 60 80 100 120

Are

a U

nit

s M

illio

ns

Absorption Time

t-cadinol

(E)-nerolidol

Octanal

2-nonanone

154

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161

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

162

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.

163

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.

164

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