Identification, Characterization and Bioevaluation of Polyphenols from Martynia Annua Linn

IDENTIFICATION, CHARACTERIZATION AND BIOEVALUATION OF POLYPHENOLS FROM MARTYNIA ANNUA LINN.

A Dissertation Submitted to the Department of Chemistry, Quaid-i-Azam University, Islamabad

In partial fulfillment of the requirements for the degree of

Doctor of Philosophy In Organic Chemistry By Saba Muazzam

Department of Chemistry Quaid-i-Azam University, Islamabad 2019

DEDICATION

I dedicate my dissertation to my father Mr. Muazzam Ali for his love, endless support and encouragement ACKNOWLEDGEMENTS

First and foremost, I am thankful to Almighty Allah, who gave me courage and strength to accomplish this task. This dissertation would be impossible without the contribution from many others. I will first express my sincere gratitude to my advisor Dr. Muhammad Farman, Associate Professor, Department of Chemistry, Quaid-i-Azam University Islamabad, for his guidance, influence and support. He has guided me through the ups and downs of my academic career. My sincere thanks are also due to Professor Dr. Shahid Hameed, Chairman, Department of Chemistry, Quaid-i-Azam University Islamabad and Professor Dr. Aamer Saeed, Head of Organic Section, Department of Chemistry, Quaid-i-Azam University Islamabad, for providing necessary facilities and their support during my research work. I would also like to thank Professor Dr. James McCullagh, Head of Mass Spectrometry Research Facility, Chemistry Research Laboratory, University of Oxford, United Kingdom for providing necessary facilities and for the invaluable discussions and advices regarding chromatography and mass spectrometry. It was honor to learn and work with him. I am also grateful to Dr. Naureen Rana, Assistant Professor, Department of Zoology and Fisheries, University of Agriculture Faisalabad, for her moral support. Completion of this dissertation would have been difficult without the financial support from Higher Education Commission, Islamabad, Pakistan. I would like to thanks my fellows, labmates, friends for their motivation, enthusiasm help and moral support throughout my research work. Last but not the least, I pay my thanks to my family, my father, brother, sister, my uncles and aunts, in-laws. I would like to give special thanks to my loving and caring husband who has tolerated the long distance separation for years but been standing by me throughout my academic career and has been a constant source of encouragement and support, and also thanks to my cute son who has been affected in every way possible by this quest.

SABA MUAZZAM TABLE OF CONTENTS LIST OF ABBREVIATIONS...... I

LIST OF FIGURES ...... III

LIST OF TABLES ...... VI

ABSTRACT...... VIII

1. INTRODUCTION ...... 1

1.1. Natural Products...... 1 1.2. Medicinal Plants...... 1 1.3. Secondary Metabolites...... 1 1.4. Polyphenols ...... 2 1.5. Flavonoids ...... 2 1.5.1. Biosynthesis ...... 3 1.5.2. Chemical Structures ...... 3 1.5.3. Classification ...... 4 1.5.4. Structural Diversity ...... 6 1.5.5. Biological Impact of Flavonoids ...... 6 1.6. Analytical Methods in Research of Polyphenols ...... 7 1.6.1. High Performance Liquid Chromatography ...... 7 1.6.2. Electrospray Ionization in Mass Spectrometry...... 7 1.6.3. Mass Spectrometry ...... 8 1.7. Objectives ...... 9

2. LITERATURE REVIEW…...... 10

2.1. Martynia ...... 10 2.2. Martynia annua L…...... 10 2.2.1. Occurance ...... 10 2.2.2. Vernacular Names ...... 10 2.2.3. Plant Taxonomy ...... 10 2.3. Morphology ...... 11 2.4. Ethnobotany ...... 11 2.5. Phytochemistry ...... 13 2.6. Pharmacological Activities ...... 15 2.6.1. Antifertility Activity ...... 16 2.6.2. Analgesic and Antipyretic Activity ...... 16 2.6.3. Anthelmintic Activity ...... 16 2.6.4. Antinociceptive Activity and CNS Depressant Activity ...... 16 2.6.5. Antioxidant Activity ...... 17 2.6.6. Anticonvulsant Activity ...... 17 2.6.7. Antibacterial Activity ...... 18 2.6.8. Wound Healing ...... 18 2.6.9. Hair Growth Promoting Activity ...... 19

3. MATERIALS AND METHODS ...... 20

3.1. Chemicals and Reagents ...... 20 3.2. Plant Material ...... 20 3.3. Sample Preparation ...... 20 3.4. Untargeted/TargetedAnalysis...... 20 3.4.1. Extraction Protocols...... 20 3.4.2. Authentic Standard Sample Preparation…...... 21 3.4.3. LC-ESI-MS Method/Instrumentation ...... 21 3.4.4. Tandem Mass Spectrometry...... 22 3.4.5. Data Processing ...... 22 3.4.6. Quality Control (QC) Samples ...... 22 3.4.7. Method Validation………….. ………………………………………………………………………23 3.4.7.1. Precision………………………………………………………………………...... …...23 3.4.7.2. Limit of Detection (LOD)……………………………………………………….………………….23 3.4.7.3. Limit of Quantification (LOQ)………………………………………………...... …….23 3.5. GC-MS Analysis………………………………………………………………...………………………..23 3.5.1. Extraction and Sample Preparation…………………………………………………………...…….23 3.5.2. Instrumental Parameters…………………………………………………………………………….....23 3.6. Total Phenolic Content…………………………………………………………………………………..24 3.7. Total Flavonoid Content………………………………………………………………………………...24 3.8. Antioxidant Activity……………………………………………………………………………...……....24 3.8.1. Extraction………………………………………………………………………………………………...24 3.8.2. Fractionation……………………………………………………………………………………….…....25 3.8.3. Thin Layer Chromatography (TLC)…………………………………………………..…………….25 3.8.4. Sample Preparation………………………………………………………………………………….....25 3.8.5. DPPH Antioxidant Activity………….……………………………………………………………....25 3.8.6. ABTS Radical Scavenging Activity……………………………………………….…………...…..26

3.8.7. Ferric Reducing Power (FRAP) Assay…………………………………………………….……....26 3.9. Cytotoxic Activity……………………………………………………………………………………...…27 3.9.1. Cell Culture and Treatment…………………………………………………………………………..27 3.9.2. Cytotoxicity……………………………………………………………………………………………...27 3.9.3. MTT Assay……………………………………………………………….…………………………..….28 3.10. Statistical Analysis……………………………………………………………………..………………..28

4. RESULTS AND DISCUSSION...... 29

4.1. LC-MS/MS Analysis……………………………………………………………………………………..29 4.2. Method Validation………………………………………………………………………………..…….…29 4.2.1. Precision…………………………………………………………………………………………………..29 4.2.2. Linearity…………………………………………………………………………………………...……...30 4.2.3. Limit of Detection (LOD) and Limit of Quantification (LOQ)………………………...…….30 4.3. Untargeted LC/MS Analysis…………………………………………………………………………….32 4.3.1. Comparison of Extraction Protocols……………………………………………………….………..32 4.3.2. Measurement of Individual Compounds Features across Five Parts of the Plant…...... 35 4.4. Targeted LC-MS/MS Analysis…………………………………………………………………….……36 4.4.1. Establishing an in-house Polyphenol Database………………….……………………...……...... 36 4.4.2. Identification of Phenolic acid and Flavonoids…………………………………………………....36 4.4.3. Quantitative Measurements of Identified Compounds………………….……………………….40 4.4.4. MS Structural Characterization of Phenolic acid and Flavonoid Glycosides………….....40 4.5. Identification of Compounds by GC-MS Analysis..…………………………………………...... 73 4.6. Total Phenolic Content (TPC)………………………………………………………………………...80 4.7.Total Flavonoid Content (TFC)……………………………………………………………….……….81 4.8.Antioxidant Activity…………………………………………………………………………………...... 82 4.8.1. DPPH Antioxidant Activity……………………………………………………..………………....82 4.8.1.1. DPPH Antioxidant Activity of Leaves Fractions…………………………..………………...84 4.8.2. ABTS Antioxidant Activity………………………………………….……………………………...85 4.8.2.1. ABTS Antioxidant Activity of Leaves Fractions………………………………….…….……86 4.8.3. FRAP Reducing Power Method…...……….……………………………………………….………87 4.8.3.1. FRAP Antioxidant Activity of Leaves Fractions …...... 89 4.9. Cytotoxicity……………………………………………………………………………………………...... 92 4.9.1. Cell Morphology………………………………………………………………………………………..93 4.9.2. Cell Proliferation (MTT) Assay…………………………………………..…………………………94 4.9.3. Cytotoxic Activity of Crude Extracts of Martynia annua ……………….…………………..95 4.9.4. Cytotoxic Activity of Leaves Fractions……………………………..……….……….……..97

CONCLUSIONS...... 102

REFERENCES………...... 104

APPENDICES...... 127

LIST OF ABBREVIATIONS

[M] Monoisotopic Mass of the Compound 2-D TLC Two Dimensional Thin Layer Chromatography AGC Automatic Gain Control amu atomic mass unit ANOVA Analysis of Variance BAW Butanol:Acetic acid:Water CE-MS Capillary Electrophoresis Coupled to Mass Spectrometry CNS Central Nervous System CRD Complete Randomize Design DAD Diode Array Detector DF Degree of Freedom EI Electron Impact ESI-MS Electrospray Ionization-Mass Spectrometry GAE Gallic Acid Equivalent GC Gas Chromatography GC-MS Gas Chromatography Coupled to Mass Spectrometry HILIC Hydrophilic Interaction Liquid Ion Chromatography HPLC High Performance Liquid Chromatography HR-ESI High Resolution Electrospray Ionizaton HRT Hormonal Replacement Therapies

IC50 Half Maximal Inhibitory Concentration LC-MS Liquid Chromatography Coupled to Mass Spectrometry LC-QTOF-MS Liquid Chromatography Coupled to Quadrupole Time-Of-Flight Mass Spectrometry LOD Limit of Detection LOQ Limit of Quantification m/z mass-to-charge ratio

MS Mass Spectrometry MS/MS Tandem Mass Spectrometry NIST National Institute of Standards and Technology NMR Nuclear Magnetic Resonance NP Normal-Phase ORAC Oxygen Radical Absorbance Capacity OSCs Organosulphur Compounds PA Peak Area PBS Phosphate Buffer Saline PC Paper Chromatography PCA Principle Component Analysis QC Quality Control QE Quercetin Equivalent RE Rutin Equivalent RNS Reactive Nitrogen Species ROS Reactive Oxygen Species RP Reversed-Phase RSD Relative Standard Deviation RT Retention Time SOV Source of Variance TEAC Trolox Equivalent Antioxidant Capacity TFC Total Flavonoid Content TIC Total Ion Current TLC Thin Layer Chromatography TPC Total Phenolic Content UHPLC Ultra-High Performance Liquid Chromatography UHPLC-ESI-MS Ultra-High Performance Liquid Chromatography coupled to Electrospray Ionization Mass Spectrometry UV/Vis Ultraviolet-Visible WHO World Health Organization

LIST OF FIGURES

No. Description Page No. 1.1 Structures of common flavonoids skeleton 03 1.2 Typical structures of flavonoids belonging to different sub-groups 05 2.1 Martynia annua L. (a) Leaves (b) Stem (c) Fruits (d) Flowers (e) Roots 12 4.1 Calibration curve for trans-Ferulic acid. Similar calibration curves were 30 constructed for each metabolite where authentic standards were available.

4.2 Principal Components Analysis (PCA) shows the relative variability of each 33 extraction method tested. A = Homogenisation; B = Sonication; C = Maceration. The homogenization method demonstrated the most consistent results between experimental replicates (n=3 for each method.) D = all extraction methods combined.

4.3 The number of individual compound features measured in each of the five 35 different plant part extracts from Martynia annua. Analysis by LC-MS/MS.

4.4 The chemical structures of flavonoids and phenolic acids positively identified by 39 comparison with commercial standards 4.5 MS2 spectrum of compound 17 43 4.6 Structure of the identified compound 17 44 4.7 MS2 spectrum of compound 18 44 4.8 Structure of the identified compound 18 45 4.9 MS2 spectrum of compound 19 46 4.10 Structure of the identified compound 19 46 4.11 MS2 spectrum of compound 20 47 4.12 Structure of the identified compound 20 48 4.13 MS2 spectrum of compound 21 48 4.14 Structure of the identified compound 21 49

III

4.15 MS2 spectrum of compound 22 49 4.16 Structure of the identified compound 22 50 4.17 MS2 spectrum of compound 23 51 4.18 Structure of the identified compound 23 51 4.19 MS2 spectrum of compound 24 52 4.20 Structure of the identified compound 24 53 4.21 MS2 spectrum of compound 25 53 4.22 Structure of the identified compound 25 54 4.23 MS2 spectrum of compound 26 55 4.24 Structure of the identified compound 26 55 4.25 MS2 spectrum of compound 27 56 4.26 Structure of the identified compound 27 57 4.27 MS2 spectrum of compound 28 57 4.28 Structure of the identified compound 28 58 4.29 MS2 spectrum of compound 29 59 4.30 Structure of the identified compound 29 59 4.31 MS2 spectrum of compound 30 60 4.32 Structure of the identified compound 30 60 4.33 MS2 spectrum of compound 31 61 4.34 Structure of the identified compound 31 62 4.35 MS2 spectrum of compound 32 62 4.36 Structure of the identified compound 32 63 4.37 MS2 spectrum of compound 33 64 4.38 Structure of the identified compound 33 65 4.39 MS2 spectrum of compound 34 66 4.40 Structure of the identified compound 34 66 4.41 Structures of some of the prevailing bioactive compounds from Martynia annua 77 4.42 Calibration curve for total phenolic determination 80 4.43 Calibration curve for total flavonoid determination 81 4.44 Reaction of DPPH molecule with antioxidant 83 4.45 DPPH antioxidant activity of Martynia annua parts 83

4.46 DPPH antioxidant activity of leaves a) solvent and b) TLC fractions 84 4.47 Reduction of ABTS to ABTS•+ radical cation 85 4.48 ABTS antioxidant activity of Martynia annua parts 86 4.49 ABTS antioxidant activity of leaves a) solvent fractions b) TLC fractions 87 4.50 Reduction of Ferric tripyridyltriazine [Fe3+-TPTZ] complex to ferrous 88 tripyridyltriazine [Fe2+-TPTZ] 4.51 FRAP antioxidant activity of Martynia annua part 88 4.52 FRAP antioxidant activity of leaves a) solvent and b) TLC fractions 89 4.53 Cell morphology of a) HeLa b) LN18 & c) 293T 93 4.54 Reduction of MTT into Formazan 94 4.55 Percentage cell viability of Martynia annua parts versus extract concentration 95 against HeLa (a) and LN18 (b) cell lines 4.56 50% Inhibitory concentration of HeLa and LN18 in different parts of Martynia 97 annua 4.57 Percentage cell viability of Martynia annua leaves fractions against a) HeLa and 98 b) LN18 4.58 Percentage cell viability of Martynia annua leaves fractions against a) HeLa b) 99 LN18

LIST OF TABLES

No. Description Page No. 1 Limits of detection, limits of quantification, R2 values, line equations and %RSD 31 values calculated from individual calibration curves, signal: noise ratios and precision (%RSD) represented by replicate injection of standards.

2 Heat-map showing the average concentration of each level-1 identified metabolite 34 derived from each of the three extraction methods (ng/g plant material). The weighted average extraction efficiency is slightly higher for the maceration method but it is not as reproducible as the homogenization method (red = highest abundance, green= medium abundance, and blue = lowest abundance).

3 Identified compounds from Martynia annua provides a list of the 16 plant 37 secondary metabolites and associated analytical data.

4 Absolute concentration of identified compounds across each plant part (ng/g plant 40 material).

5 Mass spectral identification of phenolic acid and flavonoid glycosides 42 6 Putative metabolite identifications based on multi-parameter matches with the 68 human metabolome database (HMDB). “Note these putative identifications are included based on matching with the HMDB database via correspondence between accurate m/z values, isotope patterns and matching multiple fragmentation peaks. The chemical formulae are likely to be correct, however, a number structural isomers may exist in nature that are not represented by the HMDB so it is not possible to be certain ‘accepted description’ are correct, hence their designation as ‘putative identifications’.”

7 Known biological and medicinal activity of identified compounds. 72

8 Compounds identified from Martynia annua by GC-MS analysis. 74

9 TPC, TFC and antioxidant activities of different parts of Martynia annua. 90 10 ANOVA mean squares values of plant parts by DPPH, ABTS and FRAP 90 antioxidant methods

11 Antioxidant activities of fractions of crude extract of Martynia annua leaves. 91

2 12 IC50 and R values of Martynia annua parts against HeLa, LN18 and 293T. 96

13 IC50 values of reference compounds. 96

2 14 IC50 and R values of Martynia annua crude leaves fractions against HeLa and 100 LN18.

VII

ABSTRACT

Martynia annua L. is a medicinal plant found local to sub-continent where it is consumed for self-treatment of various diseases and ailments. The objectives of this study were to analyze different extracts of plant parts using untargeted and targeted metabolic profiling, identification/quantitation of selected compounds and evaluation of antioxidant and cytotoxic activities of all plant part’s extracts. A validated LC-MS/MS method was used for untargeted and targeted analysis of a range of extracts from the plant. Individual plant metabolites were identified/quantified by comparison with authentic standards, published fragmentation profiles and online database matching. For antioxidant activity, three different assays were used. Tetrazolium reduction method was employed to evaluate cytotoxic activity. A total of 89 compounds were identified and their relative abundances were estimated across five separate parts of the plant (leaves, stem, fruits, flowers and roots). Sixteen of these compounds were identified by comparison with authentic standards and were subsequently ascertained in all plant parts. The identity of 18 glycosides compounds were determined by deduction engaging accurate mass, isotope pattern and experimental collision induced dissociation fragmentation spectra. Fifty five compounds were identified putatively by matching with HMDB (Human Metabolome Database). A number of compounds identified at higher abundance which include: homovanilic acid, syringic acid, trans-ferulic acid, apigenin, luteolin, hispidulin and isorhamnetin have biological properties and also estimated their concentration and independently determined bio- therapeutic properties. The plant extracts showed significant antioxidant and cytotoxic activity. These findings significantly extend the plant metabolites identified in the Martynia annua. These results anticipate a biochemical support for future studies addressing bio-therapeutic potential of this plant.

VIII

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INTRODUCTION 1.1. Natural Products Natural products have long been sources of medicines, and a vast portion of the pharmaceutical applications in medicine are directly/indirectly acquired from nature. Natural products are versatile and diverse and are also of prime importance in the area of drug development as they permit the identification of leading compounds of interest for the development of new therapeutics (Newman et al., 2003). The field of natural products appeared around one fifty years ago and the structure elucidation of these products was a major task of organic chemistry research. Structure determination was a steering force in the development of organic chemistry and analytical techniques in the first half of the nineteenth century. Development of modern analytical techniques required lesser amount of sample needed for structure determination and thus, changed completely this field of research (Cabrera, 2006). 1.2. Medicinal Plants The uses of medicinal plants were an important part of the medical system in the world. Herbal medicinal products are often useful therapy providing a safe form of treatment options, and in many cases, specific treatments have been shown to be clinically effective. Their use is widespread and increasing. Chemical structures and biological evidence-based analyses of traditional medicinal plants for the impact of new developments are inevitable. In pharmaceuticals, foods, and cosmetics, for the massive production, biologically active compounds (i.e., quinines, phenylpropanoids and alkaloids) from the plants are of great interest from scientific and economic point of view. The biologically active compounds including flavonoids, isoflavones, coumarins, lignins, and many small phenolics, derived from phenyl propanoid pathways, are involved in many plant functions like structure defense, pigmentation and signaling of plants (Douglas, 1996; Hendrich, 2002). 1.3. Secondary Metabolites Plants are engineered to produce and store a large amount of organic compounds known as secondary metabolites in an evolutionary response. Most of these compounds are engaged in plant defense mechanism in the survival of the plants against natural enemies (microbial pathogens and herbivores). Active secondary metabolites are very popular in biochemistry because of interact with targets in human body (Wink, 2008).

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There are still many plant species in the word that have not been subjected to phytochemical screening for studying bioactive compounds. Majority of secondary metabolites are recognized in medicinal plants display a pleiotropic potential to interact with various targets (Wink, 2008). Hence, traditional phytomedicines provide a promising solution for global increasing demand of new therapeutic agents (Balandrin et al., 1985; Newman et al., 2000).

1.4. Polyphenols

Natural products have garnered substantial interest due to their potential beneficial antioxidant and biochemical effects. Polyphenols is the most important group of secondary plant metabolites that may be divided into various sub-groups on the basis of number of phenol rings and structural features that connect these rings to one another. Major groups involve lignins, phenolic acids, stilbenes and flavonoids (Pandey and Rizvi, 2009). Flavonoids are most widespread and universal plant secondary metabolites and these are the popular constituents for chemotaxonomic surveys of plant families and genera due to their ubiquitous presence in medicinal plants, structural diversity, easy detection and identification (Harborne and Turner, 1984).

1.5. Flavonoids

Flavonoids are wide spread in nature and are frequently found in grains, fruits, vegetables and legumes. There are over 10,000 known flavonoids (Tahara, 2007) and these are the characteristic components of medicinal plants excluding horn worts and algae. Flavonoids found in almost all parts of plant including wood, leaves, bark, seeds, nectar, pollen, berries, flowers, and roots (Markham, 1982) as aglycones, glycosides and methylated derivatives and they contribute to the dazzling shades of yellow, scarlet, blue and orange in leaves, fruits and flowers (Brouillard and Cheminat, 1988). Generally, an increased number of flavonoids are present in highly released and taxonomically related plant groups. Thus, the probability of being in a particular plant flavonoid types of useful information, such as those from the same genus or family may be acquired by referring to study literature documented on specific plants (Harborne and William, 1976).

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1.5.1. Biosynthesis The different flavonoid classes are connected through ordinary biogenesis routes from “acetate-malonate" and "shikimate" pathways. First flavonoid formed initially through biosynthesis is chalcone, and all other forms are imitative from this using various paths (Markham, 1982; Heller and Forkmann, 1988). 1.5.2. Chemical Structures Flavonoids found in various chemical structures, share fifteen carbon skeleton (two aromatic rings) organized as C6-C3-C6 order (labelled A and B) connected by a 3-carbon chain. In most flavonoids, the 3-carbon ring is closed making this a heterocyclic ring but remains open in chalcones and dihydrochalcones. For convenience, each of the individual carbon atom on rings are labelled using numbered system that applied common numbers for A and C aromatic rings while using prime numbers for B ring as shown in the Fig.1.1 Moreover, a reorganized numbering system is applied for chalcones with primed numerals for ring A and common numerals for the ring B. These numbered systems are also given to Aurones disparately because of lack of one carbon atom on ring C (Markham, 1982; Stafford, 1990).

Fig. 1.1. Structures of common flavonoids skeleton

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1.5.3. Classification Natural flavonoids could be classified into different key groups like flavonoids, isoflavonoids and neoflavonoids. These groups further divided into sub groups as shown in Fig. 1.2 (Markham, 1982).

Flavonoids Flavones

Flavanones

Flavonols

Flavanols

Anthocyanidins

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Isoflavonoids

Isoflavones

Isoflavanones

Isoflavanols

Neoflavonoids

4-Arylcoumarines

Neoflavones

Biflavonoids

Fig. 1.2. Typical structures of flavonoids belonging to different sub-groups

R1, R2, R3, R4, R5 = H, OH, OCH3, OAc, Glc

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1.5.4. Structural Diversity Flavonoids modification can take place at many stages resulting in: introduction to hydroxylation, isoprenylation and methylation of –OH groups/aglycone moiety, ortho- dihydroxyl group’s methylation, bisulphation and dimerization to produce biflavonoids. Glycosylation of -OH groups formed O-glycosides and glycosylation on aglycone moiety formed C-glycosides. Complexity and diversity of the flavonoids based on two important characters; 1) maximum possible number of glycosides (in acylated forms mostly) and 2) various form of aglycone moieties (Gross, 1987; Markham, 1982). 1.5.5. Biological Impact of Flavonoids Compounds functions and their effects on plants are important, when investigating the plant features. Phenolic compounds are classified into secondary metabolites and these grouping have gravitated to imitate and have not enough information regarding their physiological and ecological significance (Swain, 1977). Phenolics have been considered as byproducts or waste products and now this idea is gone and their various biological functions and activities are by their side. Pharmacological and epidemiological studies have revealed that intake of flavonoids is allianced with many beneficial health effects, such as antioxidative (Burda and Oleszek, 2001; Ishige et al., 2001), antiviral (Guo et al., 2007), antitumor (Cãrdenas et al., 2006), antiinflammatory (Gonzãlez-Gallego et al., 2007), hepatoprotective activities (Yao et al., 2007) and the prevention of cardiovascular diseases (Tijburg et al., 1997). Isoflavonoids exhibited endorsing bioactivity in hormonal replacement therapies (HRT) (Pakalapati et al., 2009). Literature reports confirmed the ability of catechins to scavenge free radicals and eliminates oxidative stress thus, suggesting them as a supportive anti-aging remedy, anti-neurodegenerative (Abbas and Wink, 2009; Abbas and Wink, 2010) and as anticancer (Wang et al., 2010). Biological activities of flavonoids are due to diversity in their structural conformations which made them popular in different science fields like biotechnology, medicine and ecology (Abbas and Wink, 2010; Hattenschwiler and Vitousek, 2000). Chemical structures of flavonoids also influence their biological properties such as bioavailability, antioxidant capacity and reaction with cell receptors, enzymes and other activities due to structural diversities of polyphenolic skeletons and the nature of glycosides (O-glycosides or C-glycosides).

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1.6. Analytical Methods in Research of Polyphenols The study of polyphenolics due to their vast variety and reactivity is very challenging (Bronze and Boas, 1998). Phenolic compounds are ideal molecules for the analysis by modern detection and separation techniques, such as hyphenated techniques like, high performance liquid chromatography (HPLC) and gas chromatography (GC) along with mass spectrometry (MS), ultraviolet-visible (UV/Vis) spectrophotometry and nuclear magnetic resonance (NMR) spectroscopy. Liquid chromatography, gas chromatography, paper chromatography and group-selective chemical reactions are significant techniques in the qualitative analysis of phenolics. Similarly, thin layer chromatography has its own benefits (e.g., inexpensiveness and rapidity) and modern densitometry and video-camera detection methods have further elevated versatility as more commonly used analytical tool for phenolic constituents (Summanen et al., 1998). 1.6.1. High Performance Liquid Chromatography Now-a-days, in the field of phytochemistry, HPLC is a widely used technique for the plant analysis. This technique has been applied successfully in the identification and discovery of novel bioactive secondary metabolites. These techniques based on liquid-solid partition because the analytes are separated on the basis of their affinity towards solid stationary phase (column). Analytes will be retained in the column initially and then travel under the force of mobile phase, thus, results in the partition of different compounds at different retention times. Generally, two main concepts are applied while studying HPLC, Normal Phase (NP) and Reverse Phase (RP) and make the HPLC technique a tool par excellence for its ability to carry out partition of compounds on vast range of polarities (Waksmundzka-Hajnos and Sherma, 2010). 1.6.2. Electrospray Ionization in Mass Spectrometry Development of analytical techniques from the last five or six decades has revolutionized the task of isolation/extraction and online identification of a large number of phenolics either to unknown. For the determination of phenolic constituents, many detection techniques have been employed with HPLC. Phenolics are generally studied using UV-Vis, DAD (Diode Array Detector), MS detector, Fluorescence but UV detection is the most common approach (Devilliers et al., 2011) due to the phenolics absorbance in the ultra-violet region (Bénédicte et al., 2013). ESI-MS is one of the big throw in this respect and the significance can be further addressed by the fact that John Fenn was given the Chemistry Nobel Prize in 2002 for the development of

CHAPTER 1 electrospray ionization mass spectrometry in the late 1980. So far, various phytochemical research works have been conducted to identify and characterize new secondary metabolites of biological interest (Harborne, 1988). 1.6.3. Mass Spectrometry Mass spectrometry used for structural analysis of flavonoids after the development of emerging technologies. Coupling of MS detectors to separation techniques, in particular HPLC has permitted the identification and characterization of phenolics in complex samples, and a preliminary structural elucidation of phenolics without compound isolation and purification requirement. So, it is a mile stone in phytochemistry, where a plant sample has very small amount/concentration of studied analyte/molecule. Mass spectrometry was initially employed to acquire molecular mass of the compounds. Previous ionization techniques such as EI (Electron Ionization) confined this use to non- polar/volatiles compounds. Introducing a soft ionization techniques permitted the analysis of polar and thermo labile molecules having unlimited chemical and physical properties to be analyzed by mass spectrometry. (Wolfender et al., 1992; Takayama et al., 1991; Grossert, 2001). Hyphenated MS techniques, such as GC-MS, LC-MS and CE-MS allow the analysis of very small sample amount without purification. Hence, flavonoids are the most popular secondary metabolites that have been studied by MS. At present, due to the increasing chemopreventive properties and health benefits of flavonoids, continuous efforts have been made towards advanced analytical methods for structural elucidation of flavonoids and tracking their level in plant extracts, as well as developing new methods for monitoring the association of flavonoids with biological compounds. Tandem mass spectrometry (MS/MS) in connection with liquid chromatography (LC) is the prominent technique that has been employed for structural characterization of flavonoids. Metal complexation methods have proven to be best for increasing the ionization of flavonoids and produced major diagnostic product ions for isomers differentiation (March and Brodbelt, 2008).

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1.7. Objectives In perspective of the widespread medicinal values of polyphenolic compounds and the availability of spectroscopic techniques, it is imperative to carry out phytochemical study of the medicinal plant Martynia annua. So, a research work is planned with following objectives:

 Extraction of plant constituents through various extraction protocols (Maceration, Ultra sonication and Homogenization)  Fractionation of crude extract using chromatographic techniques  Qualitative and quantitative analysis of polyphenolic compounds through spectroscopic techniques like UV/VIS, UPLC-MS and GC-MS  Untargeted and targeted metabolic profiling to capture global metabolite coverage and to compare extracts from different plant parts including leaves, roots, stem, flowers and fruit through LC-MS/MS analysis  Identification of selected polyphenolic compounds, some of which are known to have therapeutic activity and to determine how they are distributed across the plant.  Method validation of the developed LC-MS method  Determination of Total Phenolics and Flavonoids Contents  Antioxidant and cytotoxic activity of plant extracts; crude/fractions

CHAPTER 2

LITERATURE REVIEW 2.1. Martynia Martynia belongs to the family Martyniaceae. It is a monotypic genus and contains one species only, Martynia annua L., known as “cat's claw” and “devil's claw”. It is native to Mexico and Asia. Carl Linnaeus described first time this genus and species in his “Species Plantarum” publication in 1753. In native american tribes, it is a popular material for making basket. William Houstoun a scottish naval surgeon first time collected this species in Mexico near Veracruz, and in 1731 dispatched this new plant seed to chief gardener at the Chelsea Physic Garden (Mr. Philip Miller). Houstoun gave the name of this newly discovered plant Martynia in honour of John Martyn (Professor of botany at Cambridge). In Martyn's famous work Historia Plantarum Rariorum the plant was first seen in print with a full illustration and description with the following name: Martynia annua villosa et viscosa, folio subrotundo, flore magno rubro (Bretting, 1981; Hevly, 1969).

2.2. Martynia annua L. 2.2.1. Occurance Martynia annua Linn. is endemic to Mexico and also found throughout India and Pakistan, in waste places, rubbish heaps and road sides. 2.2.2. Vernacular Names • Cat’s claw (English) • Devil’s claw (English) • Bichchhu (Hindi) • Puli nagam (Tamil) • Kakanasika (Sanskrit) • Vichchida (Gujarati) 2.2.3. Plant Taxonomy • Kingdom: Plantae • Division: Magnoliophyta • Class: Angiosperms • Order: Lamiales • Family: Martyniaceae

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• Genus: Martynia • Species: Martynia annua • Botanical name: Martynia annua L • Synonym: Martynia diandra Gloxin 2.3. Morphology It is a hairy, branch and erect herb growing annually up to 0.9-1.2 m in height. Stems are green, robust, branched and covered with glandular hairs. Leaves are green, simple, opposite, and sticky as mainly covered by glutinous dew-like material (Nagda et al., 2011). Hairs discharge a greasy sap which provides a clammy sense to plant. Fruits of the plant are oblong and green in color when young but at maturity stage, it becomes woody and black with 1-1.5 cm wide and 3-4 cm long, reduced into a claw (long beak). Fruits when dry, breaks into two sharp re-curved hooks. Seeds of the plant are brown to black in color, flat, elongated, each pod containing two seeds (residing inside of the pod) (Wink, 2008). Racemes are erect, terminal and long, while corolla are hairy glandular with many oblique mouth lobes (Balandrin et al., 1985; Newman et al., 2000). Plant flowers are pale mauve, drooping, large in short spikes at terminal branches. Flowers are pink/dark purple blotched with inside yellow, tubular/foxglove shaped (4- 6 cm long), ill-smelling and breaks in in 5 spreading lobes with an eminent spot between each lobe (Manandhar and Manandhar, 2002). 2.4. Ethnobotany The plant is known as kakanasika in an indian traditional medicine (Ayurveda). It is used for the treatment of inflammation, tuberculosis and epilepsy (Daayf and Lattanzio, 2008). The most bioactive parts of this plant are leaves and fruits (Flora et al., 2013; Nagda et al., 2009). The leaves are edible and have been shown to have anti-convulsant activity against MES and PTZ animal models (Babu et al., 2010). Leaves extract is used for sore throats as a gargle and the paste of leaves are used for the wounds of domestic animals (Nagda et al., 2011; Manandhar and Manandhar, 2002). Fruits of the plant are used as alexiteric and in inflammation while the ash of fruits added in coconut oil for treating burns (Daayf and Lattanzio, 2008). Martynia annua oil seeds were applied on abscesses and used for the treatment of skin infections and itching (Babu et al., 2010). Fruits are applied as local sedative and are also used as antidote to venomous stings, bites and scorpion bites/stings (Anonymous, 1982).

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(a) Leaves (b) Stem

(e) Roots

Fig. 2.1. Martynia annua L. (a) Leaves (b) Stem (c) Fruits (d) Flowers (e) Roots

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2.5. Phytochemistry Kirtikar and Basu, 1987 determined that the flowers of the plant mainly contain pelargonidin-3,5-diglucoside, cyanidin-3-galactoside while gentisic acid found in fruits. Cyclopropenoid, arachidic acid, linoleic acid, oleic acid, palmitic acid, malvalic acid and stearic acid was found in seeds.

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Rastogi and Melhotra, 1998 conducted the phytochemical study on Martynia annua which showed that the plant is quite rich in phenolic compounds which contained pelargonidin- 3,5-diglucoside, cyanidin-3-galactoside, p-hydroxybenzoic acid, linoleic acid, palmitic acid, arachidic acid, stearic acid, gentisic acid, apigenin, apigenin-7-O-glucuronide. GC-MS studies on both alcohol and aqueous extracts have shown the presence of 28 constituents, and oleic acid forms the major portion.

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Mali et al., 2002 showed that the leaves predominantly contain chlorogenic acid, p- hydroxybenzoic acid, sinapic acid and fatty acids like stearic acid and palmitic acid.

Sermakkani and Thangapandian, 2010 demonstrated that the leaves extract in methanol exhibit the presence of greater amount of terpenoids, glycosides, alkaloids, steroids, saponins, tannins and average concentration of cardiac glycosides, anthraquinones and phenols, while resins and flavonoids was not found. Lodhi and Singhai, 2011 determined that chemical investigation of Martynia annua plant unveil the presence of tannins, glycosides, carbohydrates, anthocyanins, phenols and flavonoids.

2.6. Pharmacological Activities Applications of Martynia annua in medicine is sufficiently large, but only for few cases its curative efficacies have been evaluated. A detail study of pharmacological activities of Martynia annua is presented below.

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2.6.1. Antifertility Activity (Mali et al., 2002) studied the effects of 50% ethanolic extract of Martynia annua root on the reproduction of male rats. Research work was divided into 4 sets of five animals each. The first batch (I) serve as control (received vehicle alone). The second, third and fourth batchs (II, III and IV) of animals were orally administrated the root extract daily at 50, 100 and 200 mg/kg body weight, po, respectively, for the duration of 60 days. Significant decreases in the mass of epididymides, testes, ventral prostate and seminal vesicle were observed. Prominent reduction in serum concentration of luteinizing hormone and testosterone were also observed. Hence, it is deduced that the antifertility potential of ethanolic extract (50%) of Martynia annua root produced dose related effects on male reproduction without disturbing general body metabolism. 2.6.2. Analgesic and Antipyretic Activity (Kar et al., 2004) evaluated analgesic effect in swiss albino mice by tail flick and hot plate assays and for antipyretic effect against brewers-yeast induced hyperpyrexia in adult Wistar rats. In both assays, the extracts of Martynia annua fruits (ethanol chloroform, petroleum ether and aqueous extracts) were administrated orally at the dosage of 20 mg/kg. The extracts revealed significant analgesic and antipyretic activities. The study concluded that, chloroform and petroleum ether extracts showed higher analgesic and antipyretic activities in comparison with aqueous and ethanol extracts of Martynia annua fruits. 2.6.3. Anthelmintic Activity (Nikalje et al., 2007) determined that extract of petroleum ether of roots of Martynia annua exhibited strong anthelmintic activity towards Pheritima posthuma earthworms as compared with albendazole (standard compound). 2.6.4. Antinociceptive Activity and CNS Depressant Activity (Bhalke and Jadhav, 2009) evaluated CNS depressant and antinociceptive activity of methanol, ethyl acetate and petroleum ether extracts of Martynia annua roots. Hot plate method was used to investigate these activities. Extract of petroleum ether at the dosage of 50 mg/kg, revealed prominent increase in reaction period among all extracts and also exhibited high inhibitory effect on writhing instigate by acetic acid towards petroleum ether, ethyl acetate, methanolic extracts and pentazocine and paracetamol respectively (standard drugs). Besides, all these at similar dosage, petroleum ether extract have also shown prominent decrease in the

CHAPTER 2 locomotor activity on comparing with the reference drug diazepam and it heighten pentobarbitone sodium engender sleeping time up to 215.34% at the dosage of 30 mg/kg. 2.6.5. Antioxidant Activity (Nagda et al., 2009) determined the in vitro antioxidant activity of Martynia annua leaves extracts (aqueous and methanol) by various assays, DPPH radical-scavenging assay, nitric oxide scavenging assay, reducing power method, superoxide free radical scavenging method, H2O2 radical scavenging method, hydroxyl radical-scavenging method and total antioxidant potential. The methanolic extract of Martynia annua leaves revealed higher antioxidant activity as compared to aqueous extract. (Flora et al., 2013) determined the antioxidant activity of different parts of Martynia annua (leaves, stem and endocarp with seed). The research work showed that, flavonoid content of the plant extracts (expressed as quercetin equivalent) was 0.26 ± 0.1 mg Qt/g to 0.49 ±0.12 mg Qt/g in stem. The plant leaves have the greater amount of tannin (1.78±0.09 mgCE/g) and the seed with endocarp have lesser amount of tannin (0.98±0.08 mgCE/g). Study showed that, these parts of Martynia annua plant have significant amount of ascorbic acid. 2.6.6. Anticonvulsant Activity (Babu et al., 2010) presented an investigation report on anti-seizure activity of Martynia annua. The methanolic extract of Martynia annua (MEMA) was screened for anticonvulsant activity and then subjected to acute toxicity on Pentylenetetrazole (PTZ) and Maximal Electroshock (MES) and persuaded seizures models in albino wistar rats. Acute toxicity of extract was non-toxic up to the recommended dose of 2000 mg/kg body weight orally as per OECD guidelines No. 423. Animals were treated with MEMA at doses of 200 and 400 mg/kg body weight. These studies showed that, as compared to control group mean duration of extensor phase of test group reduced to significant level. By comparing with the reference drug phenytoin (100%) the MEMA 200 mg/kg have shown 66.31 % and a dosage of 400 mg/kg showed 82.731 % protection towards MES instigate seizures while by comparing with the reference drug diazepam (100%), the MEMA at 200 and 400 mg/kg manifested 70.33% and 82.88% prevention of convulsion and 83.33% and 100% prevention of transience respectively, against PTZ (pentylenetetrazol) engender epilepsy. So, the results revealed that, MEMA showed anticonvulsant activity against MES and PTZ animal models.

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2.6.7. Antibacterial Activity (Sermakkani and Thangapandian, 2010) evaluated antibacterial activity of methanol, chloroform and ethyl acetate extract of leaves of Martynia annua L. against gram positive and negative bacteria. Disc Diffusion method was employed to perform antibacterial activity in which all the extracts were used at 100% concentration. All extracts exhibited antibacterial activity towards both bacteria’s. Extract of chloroform exhibited higher antibacterial action against Proteus vulgaris, B. thuringensis and B. subtilis. Extract of ethyl acetate was strong towards Salmonella paratyphi A, Salmonella paratyphi B, P. vulgaris, Klebsiella pneumonia and Proteus mirabilis while the methanolic extract, parade higher antibacterial activity against B. subtilis, S. paratyphi B, Pseudomonas aeruginosa and Proteus vulgaris. (Kalaichelvi and Dhivya, 2016) evaluated phytochemical screening and antibacterial activity of aqueous, ethanol, acetone and petroleum ether extract of Martynia annua leaves and Premna latifolia. Qualitative phytochemical screenings were carried out by standard biochemical assays. Antimicrobial activity of Martynia annua plant was determined by agar well diffusion assay carried out by microdilution techniques against two gram negative human pathogenic bacteria. The preliminary phytochemical analysis of Martynia annua and Premna latifolia leaves revealed the presence of flavonoids, phytosterols, alkaloids, glycosides, phenolic constituents and tannin in all the solvents except aqueous extract whereas amino acids was absent in all the solvent. Out of the four extracts evaluated the ethanolic leaf extract of both the study plants showed promising activity against four pathogenic bacteria with maximum zone of inhibition (30mm).The acetone and petroleum ether were found to be less effective and showed moderate zone of inhibition towards all the examined microorganisms. The poor response was obtained with aqueous extract which showed less activity towards all examined microorganisms. Results revealed that, Martynia annua leaves and Premna latifolia might be a new source of phytoconstituents and antimicrobial active components that can determine the scientific base for modern medicine. 2.6.8. Wound Healing (Lodhi and Singhai, 2011) examined the wound healing potential from fractions of ethanolic extract of Martynia annua leaves. Three different fractions (MAF-A, MAF-B and MAF-C) of ethanol extract of Martynia annua leaves were fractionated and screened for wound healing potential with the help of two models, incision and excision on rats. For study, incision

CHAPTER 2 and excision wounds were created on dorsal portion of rats. Biochemical parameters (hydroxyproline level and protein level), Wound contraction, and histopathological study were conducted in excision wound model whereas incision model was utilized for determination of tensile strength. The Povidone-Iodine ointment was applied as a reference for comparison purpose. The Thin Layer Chromatography (TLC) profiles of all fractions were analyzed and TLC of luteolin was also observed. The methanol fraction MAF-C exhibited significant wound healing activity by trigging of wound contraction and epithelialization as compared to MAF-A and MAF-B fractions. Phytochemical literature showed that the methanolic fraction mostly contains flavonoid. Luteolin was responsible for increasing wound healing activity because of free radical scavenging process. 2.6.9. Hair Growth Promoting Activity (Itankar et al., 2013) determined hair growth promoting potential of Martynia annua leaves and fruits in testosterone engender alopecia in mice. Medicated oils of leaves and fruits of this plant were prepared using method reported in Ayurveda for topical application. Alopecia was engendering in albino mice by testosterone (1% w/w) administration hypodermically for 20 days. Its inhibition was examined by simultaneous administration of medicated oils formed from leaves and fruits using follicular density and telogen/anagen (A/T) ratio. Whereas 0.2% Finasteride (5alpha-reductase inhibitor) was used as positive control. Follicular density and A/T ratio revealed that medicated oil of Martynia annua leaf extract showed prominent hair growth promoting activity. This process was also found successful in bringing higher number of hair follicles in anagenic stage as compared to control. These results revealed that the medicated oil of Martynia annua leaf extract (MOLE) exhibit strong hair growth potential along with antiandrogenic potential in testosterone engender alopecia method in comparison with standard Finasteride.

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MATERIALS AND METHODS 3.1. Chemicals and Reagents All HPLC-grade solvents methanol, ethanol, acetonitrile, formic acid, polyphenolic standards and chemicals used in antioxidant and cytotoxic assays were purchased from Sigma Aldrich (Sigma-Aldrich, Gillingham, UK). 3.2. Plant Material Aerial parts (leaves, stem, fruits, flowers) and roots of Martynia annua were collected in October-November, 2013 from Quaid-i-Azam University, Islamabad campus. Plant authentication was performed by Prof. Dr. Mir Ajab Khan, Department of Plant Sciences, Quaid- i-Azam University, Islamabad and a voucher specimen (No. 308) was deposited in herbarium of the same department. 3.3. Sample Preparation Sample preparation is the first step after proper sample handling which includes milling, grinding, and homogenization, because an immediate analysis of freshly harvested plant material is frequently inconvenient and impracticable. Before processing to extraction and further analyses plant samples were air/shade dried to reduce the risk of bio or enzymatic degradation during storage and are more easily ground which facilitates the sampling for further processing and stored in an air-tight container before extraction. 3.4. Untargeted/Targeted Analysis 3.4.1. Extraction Protocols Maceration: 100 mg of each dried plant part (leaves, stems, fruits, flowers & roots) were placed in separate 1.5 mL Eppendorf tubes and was added 1mL of methanol to each. Kept the solution overnight at room temperature. Centrifugation of the mixture was performed at 10,000 rpm for 15 min. and the resulting supernatant was filtered using 0.45 µM nylon filter syringe. (Thermofisher Scientific, Hemmel, UK). Extraction was repeated in triplicate. The extracted stock solutions were then diluted further with methanol (10 µL stock solution to 1000 µL MeOH) in preparation for LC-MS. Each sample was frozen and stored at -20°C until analysis.

Ultrasonication: Dried plant parts (100 mg each of leaves, stems, fruits, flowers & roots) were added separately to methanol (1 mL) in a 1.5 mL Eppendorf tube and kept in an ultrasonic bath for 15 min. Extract was then centrifuged at 10,000 rpm for 15 min. and the resulting supernatant

CHAPTER 3 was filtered using 0.45 µM nylon filter syringe (Thermofisher Scientific, Hemmel, UK). The extraction was repeated in triplicate. The extracts were then diluted further with methanol (10 µL stock solution to 1000 µL MeOH) in preparation for LC-MS. Each sample was frozen and stored at -20°C until analysis.

Homogenization: Dried plant parts (100 mg each of leaves, stems, fruits, flowers & roots) were added to separate 15 mL Precellys homogenizer vials with ceramic beads (zirconium dioxide) and 1 mL of methanol was added to each. Homogenization took place for 1 min. at 50,000 rpm with a pause time of 25 sec (Precellys Evolution154 homogenizer (Bertin Instrument, Montigny‐ le‐Bretonneux, France). The mixture was then centrifuged at 10,000 rpm for 15 min. and the resulting supernatant was filtered through a 0.45 µM nylon syringe filter (ThermofisherScientific, Hemmel, UK). The extraction was repeated in triplicate. The extracts were then diluted further with methanol (10 µL stock solution to 1000 µL MeOH) in preparation for LC-MS. Each sample was frozen and stored at -20°C until the day of analysis. 3.4.2. Authentic Standard Sample Preparation Stock solutions of each metabolite standard were prepared by mixing 8 compounds together in methanol: milli-Q water (50:50%) at a concentration of 1mg/mL. All standard solutions were further diluted to 10 µg/mL with methanol in preparation for LC-MS analysis. 3.4.3. LC-ESI-MS Method/Instrumentation Compounds were identified in plant extracts using a liquid chromatography (Thermo Scientific Ultimate 3000) system coupled directly to a Mass Spectrometer (Q-Exactive HF Hybrid Qudrupole-Orbitrap). The ionization source used was HESI II electrospray (Thermo Scientific, San Jose, CA). Waters Acquity UPLC HSST3 column (2.1x100mm and 1.8 µM particle size) was used to perform chromatographic separation and a loop injection of 10 µL was used for complete analyses. The flow rate of mobile phase was 0.4 mL/min and the total acquisition time was 12 minutes. Composition of mobile phase was as follows: Mobile phase A consist of 0.1% aqueous formic acid and Mobile phase B consist of acetonitrile (HPLC grade). A linear elution gradient program was used as; 0mins, 1% B; 1min, 1% B; 8min, 95% B; 9mins, 95% B; 9.1mins, 1% B; 12mins, 1% B. Negative ionization mode was used to perform analyses with the scan range m/z 60-900 Da. The resolution was set to 70,000. Setting of tune file source parameters were as follows: sheath gas flow 60; aux gas flow 20; spray voltage 3.6kV; capillary

CHAPTER 3 temperature 320ºC; S-lens RF value 70; heater temperature 300 ºC. AGC target was set to 1e6 and the Max IT value was 250 ms. Temperature of the column was maintained at 30 ºC throughout analyses. Identification of peaks retention times were obtained through injection of authentic standards at the concentration of 10 µg/mL in Milli-Q water. Metabolite identification was performed using a combination of accurate mass measurements (< 5ppm), retention time < 0.1 min, isotope cluster recognition and tandem MS peak matching. Thermo Scientific Xcaliber (Thermofisher Scientific, Hemmel, UK) and Waters Progenesis QI (Waters, Elstree, UK) were used for processing raw data and compound identification 3.4.4. Tandem Mass Spectrometry The full scan data was combined with data directed MS2 scanning to provide fragmentation spectra for selected peaks at 17,500 resolution. The MS/MS settings were as follows: AGC 1e5, Max IT 50 ms, loop count 5, isolation window 1.0 m/z, NCE 30, intensity threshold 2e4. 3.4.5. Data Processing Processing of raw data were made using Progenesis QI for small molecules (Waters, Elstree, UK) and Xcaliber Qualbrowser and Quanbrowser (Thermofisher Scientific, Hemmel, UK). Untargeted profiling incorporated alignment of chromatographic peak, peak picking (isotope cluster recognition) and metabolite identification. Identification was based on matching experimental measurements for each compound to values obtained from an in-house database of authentic standards. Four orthogonal measurements were compared for each compound. These were: accurate mass analysis (< 5ppm) based on theoretical mass originated from the molecular formula, experimental retention time matching (< 0.1 min.), isotope pattern matching (> 90%) calculated from molecular formula and MS fragmentation matching from an authentic standard (available where these were from survey scan). All experimental values in the library were acquired from the analysis of authentic standards (Appendix A, Figure A1 & A2). 3.4.6. Quality Control (QC) Samples Quality Control (QC) samples were analyzed to monitor reproducibility, precision, variability, and bias of LC-MS data. The 5 µL (10 µg/mL) QC samples comprised 5 µL of each sample added together in a single vial and injected 10 times at the start of the sample sequence and 6 times at the end.

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3.4.7. Method Validation 3.4.7.1. Precision Typical analytical precision was characterised via 3 replicate measurements of the standard. The result is expressed as a relative standard deviation (% RSD). 3.4.7.2. Limit of Detection (LOD) The LOD was measured based on a signal to noise ratio of approximately 3:1 for the analyte compared to baseline noise. 3.4.7.3. Limit of Quantification (LOQ) LOQs were calculated by establishing a calibration curve separately for every compound and determine the lowest possible concentration in linear range of the curve with signal to noise ratio >10:1. 3.5. GC-MS Analysis 3.5.1. Extraction and Sample Preparation

The whole plant (20 g) was air dried and ground. Powdery mass was successively extracted by various solvents such as n-hexane, acetone and chloroform (50 mL each respectively) by employing Ultrasound Assisted Extraction (Ultrasonic LC 30 H). After filtration, solvents were evaporated under reduced pressure (BÜCHI Rota vapor R-200). The extracts of the plant were then used for GC-MS analysis. 3.5.2. Instrumental Parameters The analysis of volatile constituents was performed on Gas Chromatography-Mass Spectrometry instrument model no. 6890N (Agilent technologies) equipped with an Electron Impact (EI) ion source. Separation of analytes was performed on DB-5MS [(5 % pheny1)- methy1 polysiloxane] capillary column (30m × 0.25mm) internal diameter and (0.25µm) film thickness). The temperature of the oven was set as follows: initially, 120 °C for 1 minute then increased to; 170 °C at 10 °C/min. 220 °C at 10 °C/min. 270 °C at 10 °C/min. and then ramped to 280 at 5 °C/min.; 280 °C was maintained for 5 min. Carrier gas helium (99%) maintained at 1mL/min constant flow rate. The ion source, transfer line and injection port were all kept as 280 °C. Electron impact (EI) mode with 70 eV was used and the full mass scanning range were 50- 1000 amu. Split less mood was used for injection and injection volume was 5 µL. Enhanced Chem Station [2004] software was used to process mass spectra and chromatograms.

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Identification was executed by matching obtained mass spectra with those from mass spectral and NIST databases. 3.6. Total Phenolic Content (TPC) TPC of all plant parts (leaf, stem, fruit, flower and root) separately were measured by Folin-Ciocalteu Reagent assay with slight modification (Singleton et al., 1999). Aliquots of 100 mg lyophilized powder of plant (leaf, stem, fruit, flower and root) were dissolved respectively in 1 mL MeOH. The 0.1 mL solution was mixed with 2.8 mL of distilled water, 2 mL of 2 % sodium bicarbonate (Na2CO3) and 0.1 mL 50 % Folin-Ciocalteu reagent. Incubate the reaction mixture for 30 min at room temperature. Absorbance of the solution was taken at 750 nm against a MeOH blank on a spectrophotometer (Cary 4000 UV-Vis, Cary-Series UV-Vis spectrophotometer, Agilent Technologies). Gallic acid was used as standard compound. The level of total phenolic content was calculated in triplicate by using 7 point standard curves (0- 200 mg/L). The data were expressed as milligram Gallic Acid Equivalent (GAE)/g of lyophilized powder. 3.7. Total Flavonoid Content (TFC) The TFC of plant parts (leaf, stem, fruit, flower and root) were evaluated separately by aluminum chloride colorimetric assay reported by (Chang et al., 2002). Aliquots of 100 mg of plant parts (leaf, stem, fruit, flower and root) respectively were dissolved in 1 mL MeOH. The 0.5 mL solution was mixed with 1.5 mL of 95 % alcohol, 0.1 mL of 10 % aluminum chloride, 0.1 mL of 1 M potassium acetate and 2.8 mL of distilled water. Incubate the reaction mixture for 40 min at room temperature. Absorbance was recorded at 415 nm against a MeOH blank on a UV-Vis Spectrophotometer (Cary 4000 UV-Vis, Cary-Series UV-Vis Spectrophotometer, Agilent Technologies). Quercetin was used as a standard compound. The level of total flavonoid content was calculated in triplicate by using 7 point standard curve (0-50 mg/L). The data were expressed as milligram Quercetin Equivalents (QE/g) lyophilized powder. 3.8. Antioxidant Activity 3.8.1. Extraction The powdery mass (20 g) of each Martynia annua parts (leaf, stem, fruit, flower and root) were added in 100 mL methanol and irradiated for 15 min in ultrasonicate bath. After filtration, solvent was evaporated under reduce pressure. Resultant residues were then dissolved in methanol for antioxidant activity.

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3.8.2. Fractionation Fractionation was carried out using liquid-liquid extraction technique. The 100 g of crude ethanolic extract was used in the fractionation process. Three types of organic solvents namely; ethyl acetate, butanol and n-hexane were selected to partition crude extract into individual fractions. Crude extract was reconstituted in water in a 100 mL separating funnel and forcibly extracted by 50 mL ethyl acetate. After extraction, this solution was allowed to stand for phase separation. Organic phase was withdrawn, and another 50 mL ethyl acetate was added again into the remaining aqueous solution for extraction. This fractionation procedure was repeated in triplicates. The organic fraction of ethyl acetate was then combined and filtered through filter paper to remove particles. The residue free fraction was then evaporated under reduce pressure by rotary evaporator (BÜCHI Rota vapor R-200) until dryness. A similar fractionation procedure was also carried out to prepare n-hexane and butanol fractions (Lodhi and Singhai, 2011). 3.8.3. Thin Layer Chromatography (TLC) Thin layer chromatography was used with different gradient elution to obtain phenolic rich fractions. A strip of crude ethanolic extract of leaves was applied on TLC plates Whatman No. 42 (Cellulose was used as stationary phase). Dried plates were eluted with BAW (Butanol:Acetic acid:Water in 4:1:5) and 15 % Acetic acid. No clear bands were seen in BAW eluted plates before and after exposing to ammonia vapors under UV lamp. Six TLC fractions (F1-F6) obtained on the basis of their colors appeared under UV lamp (254 and 365 nm). Four bands were clearly observed in the plate eluted with 15 % acetic acid and two bands got intense after exposing ammonia vapors at 365 nm under UV light. After repeating the process same results were obtained. 3.8.4. Sample Preparation For sample preparation, each part of plant extract and fraction prepared at the concentration of 1 mg/mL in methanol and diluted to different concentrations. 3.8.5. DPPH Antioxidant Activity Antioxidant activity of plant extracts and fractions of Martynia annua were determined by 1, 1-Diphenyl-2-picryl hydrazyl (DPPH) assay (Brand-Williams et al., 1995). Briefly, 0.1 mM solution of DPPH in methanol was prepared. One mL solution of DPPH was added to 3 ml of plant extracts in methanol at various concentrations (50, 100, 200 and 400 μg/mL). The stock solution was prepared by dissolving 10 mg/mL methanol and their different concentrations were

CHAPTER 3 prepared by dilution method. The mixture was shaken strongly and allowed to stand for 30 min. at room temperature. Absorbance was recorded at 517 nm by using spectrophotometer (Cary 4000 UV-Vis, Cary-Series UV-Vis Spectrophotometer, Agilent Technologies). Gallic acid was used as a reference compound and triplicate measurements of the experiment were made. The

IC50 value of the solution was estimated by log dose inhibition curve. The percentage of DPPH inhibition was determined by following equation:

(%) age inhibition = A0 - A1 / A0 × 100

Where A0 is the Absorbance of control and A1 is the Absorbance of the sample 3.8.6. ABTS Free Radical Scavenging Activity ABTS method was based on the capability of polyphenolic compounds to scavenge 2, 2’- Azino-bis (ethylbenzthiazoline-6-sulfonic acid) radical cation (Arnao et al., 2001). ABTS.+ was prepared by adding 7 mM ABTS stock solution into 2.5 mM potassium persulfate (1/1, v/v) and kept the solution overnight until the process was complete and the absorbance was stable. This solution was diluted with methanol to an absorbance 0.700 ± 0.500 at 734 nm for experiment. 1mL of extracts/fractions at four different concentration (50, 100, 200 and 400 µg/mL) were mixed with 4 mL ABTS+ solution. Absorbance was taken immediately at 734 nm by using spectrophotometer (Cary 4000 UV-Vis, Cary-Series UV-Vis Spectrophotometer, Agilent Technologies). Gallic acid was used as a reference compound and triplicate measurements of the experiment were made. Antioxidant activity of plant extracts was calculated by evaluating decrease in absorbance at various concentrations using the following equation;

(%) age inhibition = A0 - A1 / A0 × 100

Where A0 is the Absorbance of control and A1 is the Absorbance of the sample. 3.8.7. Ferric Reducing Power Assay (FRAP) The potential of phenolic compounds to reduce ferric ions was determined according to the method reported by (Benzie and Strain, 1996). FRAP reagent was produced by mixing 300 mM sodium acetate buffer (pH 3.6), 10 mM TPTZ (2,4,6-Tripyridyl-s-triazine) solution in 40 mM HCl and 20 mM FeCl3.6H2O solution (10:1:1) in volume. 1 mL of extracts/fractions at four concentration (50, 100, 200 and 400 µg/mL) were mixed with 3 mL of FRAP reagent and the reaction mixture was incubated for 30 min at 37 ºC. Blue colored product [ferrous tripyridyltriazine complex] was obtained. The increase in absorbance was taken at 593 nm using spectrophotometer (Cary 4000 UV-Vis, Cary-Series UV-Vis Spectrophotometer, Agilent

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Technologies). Trolox was chosen as a standard compound to construct calibration curve and triplicate measurements of the experiment were made. Antioxidant capacity of the samples was estimated from the linear calibration curve. 3.9. Cytotoxic Activity 3.9.1. Cell Culture and Treatment HeLa (human cervical cell), LN18 (human glioblastoma cell) and HEK 293T (human normal kidney cell) were purchased from Internal Cell Bank, CRL (Chemistry Research Laboratory), University of Oxford, United Kingdom. Cancer cell lines were grown in a biochrom medium DMEM D6546, a modified eagle’s medium (Dulbecco), FBS (Fetal Bovine Serum) &

1% GlutaMAX (L-alanyl-L-glutamine dipeptide (200 mM) in NaCl (0.85%) in 5 % CO2 at 37

ºC in CO2 incubator (BINDER CB 150). HeLa and LN18 at 80-90% confluence were grown in flasks (T75) containing 1 mL trypsin/EDTA (0.25 %) solution, while 293T cells were grown in a non-adherent medium (no trypsin). An automated cell counter (Countess II FL, Thermo Fischer scientific, UK) was used to perform cell counting using trypan blue dye. 3.9.2. Cytotoxicity HeLa, LN-18 and 293T cells were seeded at a 1.17×103 cells/ 100 μL/well (HeLa cells), 3.52×103 (LN18 cells) and 5.28×103 (293T cells) in all wells except blanks (having no cells) onto a 96-well microplate. The cells were incubated overnight at 37 ºC in 5 % CO2 atmosphere. The stock solution of plant extracts/fractions and standards were prepared at a concentration of 10 mg/mL in DMSO and then diluted in four different concentrations (50, 100, 200 and 400 µg/mL) in same medium (10 % FBS and 1 % GlutaMAX). The old medium was removed at 80% confluence cells after incubation at 37 ºC and 5 % CO2, after 24 h. Washing of plates were done with 100 µL phosphate buffer saline (PBS). The wells were treated with fresh medium containing various extracts/fractions concentrations and incubated at 37 ºC and 5 % CO2 for 24 h. The above method was also performed with standards (Gallic acid, Apigenin, Luteolin, Fluorouracil and Quercetin). Control cells were tested with media (100 µL) and 0.05 % (v/v) DMSO. Blank wells were also tested containing only medium (100 µL).

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3.9.3. MTT Assay After incubation of 24 h, supernatant was discarded and washed microplates with 100 µL of PBS. A 20 µL of MTT (5 mg/mL) dye solution in PBS was added to every well and incubated at 37 ºC in 5 % CO atmosphere for 3 hr. After that, the MTT-formazan crystals (purple in color) were dissolved in each well by adding 100 µL DMSO. Absorbance of the samples was recorded (at 544 nm) with microplate reader (Polarstar Optima BMG Labtech, Germany). The experiment repeated in triplicate. Cytotoxic effects of different extracts and fractions were expressed as relative cell viability, using the following formula: (Dikmen et al., 2010); % age of cell viability = (Optical density of drug-treated sample/Optical density of untreated sample) × 100 3.10. Statistical Analysis

Experiments were conducted in triplicates and all values measured, represent the means of three replicates. Microsoft Excel (2010) and statistical analysis software GraphPad Prism 7 were used to analyze data. A dose response curve was plotted for reduced cell viability at each concentration. Analysis of variance under Complete Randomize Design was performed to analyze any difference in antioxidant potential resulting from different protocols. IC50 values were calculated by nonlinear regression analysis.

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RESULTS AND DISCUSSION 4.1. LC-MS/MS Analysis In natural products, LC-QTOF-MS (Liquid Chromatography coupled to Quadrupole Time-Of-Flight Mass Spectrometry) anticipates excellent separation and greater sensitivity that enable the identification of metabolic pathways. This acquires MS/MS data from a single injection at low and high energy without specific precursor ion selection (Nordström et al., 2006; Konishi et al., 2007; Wrona et al., 2005). Orbitrap Exactive configuration is more suited for plant secondary metabolites studies because it decreases the acquisition time and sample amount needed due to positive/negative polarity mode. It is a powerful versatile technique in metabolomics and has been shown to be popular substantially (Zhao and Lin, 2014). A modified version of the ultra-performance liquid chromatography method published by Want and co-workers (Want et al., 2012) was used coupled to an Orbitrap Q-Exactive tandem mass spectrometer for the analysis of medium and low polarity compounds including polyphenols from the various plant metabolite extracts. It developed focused on ensuring maximal metabolite coverage over 12 min. to balance run-time efficiency, robustness and compound coverage. Analysis of 101 authentic polyphenol standards was used to establish experimental parameters. Analysis of a range of extracts (extracts from plant parts and different processes for metabolite extraction) from leaves stems, fruits, flowers and roots of the plant to determine an efficient methodology for metabolite extraction and measurement of relative abundances of the metabolites in different parts of the plant. Detection in negative ionization mode was used to acquire more precise information on the structural characteristics of the unconjugated and conjugated form of phenolic constituents.

4.2. Method Validation The modified LC-MS method was validated by creating limits of detection (LOD), limits of quantification (LOQ), linearity via calibration curves and method selectivity (Precision). 4.2.1. Precision “Precision of the analytical method is the measure of statistical variability” (i.e., closeness of repeated individual measures of the sample). Typical analytical precision was characterised via 3 replicate measurements of the standard. The result is expressed as a relative standard deviation (% RSD) as shown in Table 1.

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4.2.2. Linearity The linearity was showed via calibration curve. All compounds showed good linearity, i.e., in the range of 0.992-0.999 R2 values for all the identified compounds. Fig. 4.1 provides the calibration curve for trans-Ferulic acid. Calibration curves were created for each metabolite identified. The calibration equation was found to be Y= 152043x – 40336 and correlation coefficient value is 0.999 for trans-Ferulic acid.

Y= 152043x – 40336 R2 = 0.999 35000000

30000000

25000000

20000000

15000000 Peak atrea atrea Peak

10000000

5000000

0 0 0.05 0.1 0.15 0.2 0.25 Concentration

Fig. 4.1. Calibration curve for trans-Ferulic acid. Similar calibration curves were constructed for each metabolite where authentic standards were available.

4.2.3. Limit of Detection (LOD) and Limit of Quantification (LOQ) “LOD is the lowest analyte concentration that the analytical method can reliably differentiate from background noise”.While limit of quantification is the lowest analyte concentration at which the performance of analytical method is admissible for its particular use”. Table of LOD and LOQ values for each compound measure can be found in Table 1. Correlation coefficient (R2) values were based on 3 replicate analyses of each compound from the authentic standard mixture.

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Table 1: Limits of detection, limits of quantification, R2 values, line equations and %RSD values calculated from individual calibration curves, signal: noise ratios and precision (%RSD) represented by replicate injection of standards.

No Compound ID LOD LOQ R2 Line equation %RSD (ng/mL) (ng/mL) (n=3) 1 Protocatechuic 0.27 8 0.999 y = 4E+08x - 3E+07 0.99 acid 2 Gentisic acid 0.53 1.6 0.999 y = 4E+08x - 1E+06 3.79 3 Caffeic acid 0.27 8 0.999 y = 6E+08x - 3E+06 2.02 4 Syringic acid 13.3 40 0.998 y = 7E+06x - 142448 3.19 5 Rutin 13.3 40 0.992 y = 9E+07x - 443343 12.45 6 Homovanillic 13.3 40 0.999 y = 2E+07x - 731919 4.61 acid 7 p-Coumaric acid 13.3 40 0.997 y = 7E+08x + 283714 1.68 8 Sinapic acid 0.27 8 0.999 y = 5E+07x + 3E+06 7.42 9 trans-Ferulic 0.27 8 0.999 y = 2E+08x + 40336 9.63 acid 10 Salicylic acid 13.3 40 0.996 y = 1E+09x + 2E+07 4.29 11 Luteolin 0.53 1.6 0.999 y = 9E+08x + 3E+06 3.53 12 Apigenin 0.0213 0.064 0.995 y = 1E+09x + 7E+07 5.05 13 Kaempferol 0.27 8 0.994 y = 2E+09x + 2E+08 2.83 14 Hispidulin 2.7 8 0.999 y = 9E+08x + 3E+06 6.26 15 Hesperetin 0.53 1.6 0.999 y = 6E+08x - 3E+06 10.75 16 Isorhamnetin 0.27 8 0.978 y = 2E+08x + 1E+07 3.24

By using least square method, a linear regression equation was calculated. Limit of detection and quantification were calculated by standard deviation of the regression slope (S) and line (σ). Such as; LOD = 3.3 σ/S and LOQ = 10 σ/S. The LOD was determined based on a signal to noise ratio of approximately 3:1 for the analyte compared to baseline noise. The LODs were in the range 4.2 pg/mL and 13.3 ng/mL for the identified metabolites for which authentic standards were available. LOQs were calculated by establishing a calibration curve separately for every compound and determine the lowest possible concentration in linear range of the curve with signal to noise ratio > 10:1. The LOQs were in the range from 12.8 pg/mL and 200 ng/mL for the identified

CHAPTER 4 metabolites. Good linear correlation and high sensitivity under these conditions were obtained in the concentration range studied. 4.3. Untargeted LC-MS Analysis In LC-MS analysis, a very complex data are generated, because of large number of analytical measurements associated to the number of observations i.e., (production of mass spectrum at each retention time in each sample). In LC-MS analysis, data produced from each chromatogram are organized in data sets having information of m/z (mass to charge ratio), intensities and retention time (RT). In the analysis of every sample, highly complex and information rich mass spectrum data are produced which involve particular standard methods for its dealing (Katajamaa and Orešič, 2005, 2007). The untargeted studies allow a comprehensive evaluation of all measurable metabolites in a sample, including uncharacterized compounds i.e. a complete analysis of metabolomics profile (Martin et al., 2015). Therefore, untargeted MS data analysis protocols needed highly substantial processing of LC-MS chromatograms because a huge amount of complex data is generated and difficult to deal manually. Therefore, particular algorithms and softwares are required (DeVos et al., 2007). A software assisted untargeted analysis was used on Martynia annua using Progenesis QI. Data processing includes import data, feature or peak detection, sample normalization, sample scaling and sample transformation. Peak matching involves aligning of chromatographic characteristics between biological/technical replicates of a sample in comparison of a reference sample QC (Quality Control). The objectives of detecting features and peak resolution are to distinguish real chemical compounds from false positive (e.g., background noise) (Tautenhahn et al., 2008). 4.3.1. Comparison of Extraction Protocols In order to determine an optimal metabolite extraction protocol for each of the plant parts, three separate methods were tested: Homogenization, maceration, and ultra-sonication. Extracts, using the three methods were generated and then compared by LC-MS/MS. Fig. 4.2 provides principal components analysis (PCA) for the abundances of all measured ion features (representing compounds in the sample) for each extraction method (A-C) and combined methods data (D).

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Fig. 4.2. Principal Components Analysis (PCA) shows the relative variability of each extraction method tested. A = Homogenisation; B = Sonication; C = Maceration. The homogenization method demonstrated the most consistent results between experimental replicates (n=3 for each method.) D = all extraction methods combined.

The plots also demonstrate visually that total chemical composition variability between plant parts is greatest between leaves and flowers compared to other parts of the plant. Stem, roots, and interestingly the fruit, tend to be closer to each other in their small molecule composition

The three points for each plant part represent three independent extractions from the same plant starting material. The difference in the reproducibility of each method, represented by all measured compounds can be estimated by how well the experimental replicates cluster together. The homogenization method was the most reproducible (Muazzam et al., 2018).

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Table 2 provides a heat-map ranking the average calculated concentration for each of the identified metabolites from leaf extracts (see next section). Red = most abundant; green = median abundance and blue = least abundant.

Table 2. Heat-map showing the average concentration of each level-1 identified metabolite derived from each of the three extraction methods (ng/g plant material). The weighted average extraction efficiency is slightly higher for the maceration method but it is not as reproducible as the homogenization method (red = highest abundance, green = medium abundance, and blue = lowest abundance).

Maceration Ultra-sonication Homogenisation Apigenin 591 120 239 Caffeic acid 177 148 154 Gentisic acid 17 6 11 Hesperetin 21 25 22 Hispidulin 342 129 169 Homovanillic acid 584 624 608 Isorhamnetin 11736 8839 6837 Kaempferol n/a n/a n/a Luteolin 109 54 60 p-coumaric acid 24 4 11 Protocatechuic acid 48 33 38 Rutin Hydrate 42 23 41 Salicylic acid 57 11 39 Sinapic acid 163 169 168 Syringic acid 822 723 757 trans-Ferulic acid 35744 54242 34118

The maceration method provided higher ion abundances but given its significantly greater reproducibility the homogenisation method and average extraction efficiency, the homogenization method was used to conduct all subsequent plant extractions in this study (Muazzam et al., 2018).

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4.3.2 Measurement of Individual Compounds Features across Five Parts of the Plant Having validated the analytical method and sample extraction protocol’s we analyzed three biological replicates from each plant’s part using the homogenization extraction method. A total of 7697 unique ion features were recorded with a % CV < 30 (representing compounds that were well characterized by the analytical method) across each of the plant extracts. This was commensurate with previous untargeted metabolite profiling of plant extracts (French et al., 2018). The peak area for each ion feature representing a metabolite was assigned a unique retention time and accurate mass value prior to metabolite identification. Fig.4.3. depicts provides a graph with the number of compounds identified and their distribution across each of the five plant extracts. Extracts from the plant’s flowers provided the greatest number of different compounds (5121) and those from the stem the least (4403). The majority of compounds were identified in common across multiple plant-parts.

6000

5000

4000

3000

2000

1000

0 Stem Roots Leaves Fruit Numberofcompound features measured Flower

Fig. 4.3. The number of individual compound features measured in each of the five different plant part extracts from Martynia annua. Analysis by LC-MS/MS.

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4.4. Targeted LC-MS/MS Analysis The targeted approach is used for the study of selected group of metabolites i.e., it gives more precise and sensitive detection of predetermined compounds. To search for the compound of interest i.e., in this study, a phenolic acid or a flavonoid, initial step needed is the elaboration of referential database (external or internal database) having information of their exact and nominal molecular weight, retention time, molecular formula and m/z values (Dudley et al., 2010). For the present study, an external “Polyphenol Explorer Database”, “Human Metabolome Database” and in-house built database are used for the identification. 4.4.1. Establishing an in-house Polyphenol Database For the identification of polyphenolic compounds, an in-house phenolic database was developed containing accurate masses, retention times, isotope abundances and fragmentation patterns for 101 phenolic acids and flavonoids from authentic standards purchased from commercial sources. Measurements of these four parameters were then made for each compound across all experimental samples and the database used to find matches. The criteria for a positive identification were based on all the following being met: A peak within 5ppm of the calculated accurate mass value which was also within 10 seconds of the retention time for the authentic standard and > 95% similarity in its measured and theoretical isotope pattern. Fragmentation patterns were an additional confirmatory criterion used for over 80 % of the identifications but were not available for every compound due to the data-directed nature of LC-MS/MS fragmentation method used, and the chemical complexity of the samples. 4.4.2 Identification of Phenolic acid and Flavonoids A total of 16 compounds were conclusively identified by comparing retention time, accurate mass, isotopic similarity and mass fragmentation patterns with our in-house polyphenol database of authentic standards. Table 3 provides a list of the metabolites and the analytical measurements used to identify them. Their structures are shown in Fig 4.4 (See Appendix B for Mass Spectra of Compound1-16).

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Table 3. Identified compounds from Martynia annua provides a list of the 16 plant secondary metabolites and associated analytical data.

No. Compound ID RT (min.) RT error [M-H]- Mass error Isotope pattern Fragmentation Compound ID (min) (ppm) similarity (%) score (%) level* 1 Protocatechuic acid 2.10 -0.11 153.0193 -0.1 98 91.8 1 2 Gentisic acid 3.21 -0.04 153.0193 0.1 98 80.1 1 3 Caffeic acid 3.54 0.01 179.0346 -1.6 97 93 1 4 Syringic acid 3.66 -0.01 197.0454 -0.6 95 0 1 5 Rutin 3.97 0.02 609.1457 -0.5 0 87.9 1 6 Homovanilic acid 4.00 0.32 181.0504 -0.8 96 0 1 7 p-Coumaric acid 4.01 -0.03 163.0399 -0.5 97 96.6 1 8 Sinapic acid 4.23 0.00 223.0612 0.1 0 65 1 9 trans-Ferulic acid 4.23 -0.02 193.0504 1.8 99 99.3 1 10 Salicylic acid 4.83 0.07 137.0423 -0.4 94 0 1 11 Luteolin 5.07 -0.02 285.0410 2.1 99 81.7 1 12 Apigenin 5.50 -0.04 269.0457 0.6 97 48.8 1 13 Kaempferol 5.58 -0.01 285.0410 2.1 99 55.0 1 14 Hispidulin 5.62 0.01 299.0567 2.0 97 98.8 1 15 Hesperetin 5.67 -0.01 301.0723 2.0 98 75.7 1 16 Isorhamnetin 5.68 -0.01 315.0515 1.6 94 78.5 1 *Metabolite identification level

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Flavonoids R1 R2 R3 R4 R5 R6 Apigenin H OH H OH OH H Luteolin H OH OH OH OH H Isorhamnetin OH OH OCH3 OH OH H Kaempferol OH OH H OH OH H Hispidulin H OH H OH OH OCH3

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Fig. 4.4. The chemical structures of flavonoids and phenolic acids positively identified by comparison with commercial standards

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4.4.3. Quantitative Measurements of Identified Compounds An external calibration curve for each of the 16 compounds was constructed and used to estimate the concentration of each the compounds identified in the plant extracts as shown in Fig. 4.1 and Table 1. The calculated absolute concentrations, for each of the identified compounds in each of the plant extracts, are shown in Table 4.

Table 4. Absolute concentration of identified compounds across each plant part (ng/g plant material).

Minimum concentrations (ng/g of plant material) No. Identified Compound Leaves Stem Fruit Flower Root 1 Protocatechuic acid 38 33 32 56 26 2 Gentisic acid 11 4 4 4 6 3 Caffeic acid 154 153 141 145 138 4 Syringic acid 757 714 715 718 712 5 Rutin 41 13 - 761 - 6 Homovanilic acid 608 597 593 664 567 7 p-Coumaric acid 11 2 - 1 - 8 Sinapic acid 168 177 174 170 172 9 trans-Ferulic acid 34118 43252 36100 36298 53288 10 Salicylic acid 39 15 16 28 23 11 Luteolin 60 - 35 492 - 12 Apigenin 239 6 110 682 7 13 Kaempferol 5 - - - - 14 Hispidulin 169 40 91 1017 7 15 Hesperetin 22 21 21 25 - 16 Isorhamnetin 6837 - - 263 - - Below the limit of quantification

4.4.4 MS Structural Characterization of Phenolic acid and Flavonoid Glycosides In MS analysis, negative ionization mode of HESI was used as it is more sensitive than positive ion mode and provided substantial structural information for many phenolic acid and flavonoids aglycone and glycosides. Detection of the deprotonated molecular ions was coupled with MS2 fragmentation using a data directed method and an ion intensity threshold of 2e4. Accurate masses, isotope abundances and fragmentation patterns were measured for majority of the 7697 compounds

CHAPTER 4 characterized across the experimental samples. Using these criteria to match against the theoretical values obtained from chemical formulae and structures of a much larger number of polyphenols found in the scientific literature, we made further putative identifications. Fragmentation of conjugated species often revealed carbohydrate and aglycone fragments making it relatively straightforward to identify constituents of the molecule. Flavonoid aglycones are diverse class structurally due to the variations that occur at hydroxyl and methoxyl groups (at the level of oxygenation) and flavonoids and isoflavonoids (the point of attachment of ring B). With the help of tandem mass spectra of flavonoids, we were able to acquire molecular weight, structure of the flavonoid aglycone (order of hydroxylation on aglycone, attachment point of B ring on C ring), information about sugar hydroxyl groups acylation, possibility of methylation/sulphation of hydroxyl’s on aglycone, range of sugar moieties, their configuration and in some cases placement of glycosidic bonds (Iwashina, 2000). Flavonoids occur as flavonoid -O and -C glycosides but more commonly -O glycosides, in which one or more -OH groups of the aglycone are linked to a sugar moiety (commonly, glucose, galactose, rhamnose, xylose) with the formation of an acid-labile hemiacetal bond known as glycosidic (O—C) bond. The -OH groups of flavonoids may be glycosylated but some positions are supported e.g., the 7-OH group in flavones, isoflavones and flavanones. In flavonol and flavanols the 3- and 7- OH and the 3- and 5-OH in anthocyanidins are most common glycosylation points. Acylated glycosides are also found in nature, in which one or more of the sugar –OH groups are esterified with an acid. Disaccharides like rutinose (rhamnosyl-[1→6]- glucose) and neohesperidose (rhamnosyl-[1→2]-glucose) are also found in association with flavonoids and occasionally tri- and even tetra saccharides also occur (Markham, 1982). Precursor ions could exist in a number of different adducts forms. For simplicity the compounds identified below were all shown to be represented by [M-H]- precursor ions.

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Table 5. Mass spectral identification of phenolic acid and flavonoid glycosides

No. Compound ID RT [M-H]- Mass error Base peak Isotopic Mass fragments ID Level (min.) (ppm) (m/z) similarity (%)

17 4-Hydroxybenzoic acid 4-O- 0.68 299.0780 2.5 137.0243 96 [M-H-glucose]- 2 glucoside 18 Cinnamoyl glucose 0.79 309.0990 3.1 89.0243 93 [M-H-glucose-acetic 2 acid radical]- 19 Ferulic acid 4-O-glucoside 3.11 355.1051 4.5 193.0506 96 [M-H-glucose]- 2 20 Luteolin-7-O-rutinoside 3.24 593.1507 -0.7 284.0337 89 [M-H-rutinose]- 2 21 p-Coumaric acid-4-O-glucoside 3.28 325.0941 3.6 163.0399 95 [M-H-glucose]- 2 22 Hispidulin-7-O-rutinoside 3.95 609.1458 -0.5 300.0284 95 [M-H-rutinose]- 2 23 Luteolin 7-O-(2-apiosyl- 4.02 579.1348 -1.2 284.0333 95 [M-H-glucose- 2 glucoside) xylose]- 24 Verbascoside 4.02 623.1975 -1.0 161.0243 99 [M-H-glucose- 2 rhamnose- hydroxytyrosol]- 25 Quercetin-3-O-glucuronide 4.10 477.0696 4.3 301.0365 96 [M-H-glucuronic 2 acid]- 26 Isorhamnetin-3-O-glucoside 4.12 477.1059 4.2 315.0522 92 [M-H-glucose]- 2 27 Isorhamnetin-3-O-glucuronide 4.13 491.0856 4.9 315.0524 95 [M-H-glucuronic 2 acid]- 28 Caffeic acid 4-O-glucoside 4.27 341.0891 3.8 164.0475 95 [M-H-glucose- 2 methyl]- 29 Apigenin-7-O-glucuronide 4.36 445.0761 -3.4 269.0455 89 [M-H-glucuronic 2 acid]- 30 Scutellarien 4.42 285.0409 1.6 285.0409 99 [M-H]- 2 31 p-Coumaroyl glycolic acid 4.67 221.0456 0.2 159.0811 95 [M-H-carboxylic 2 acid-water]- 32 Kaempferol-3-O-acetyl-glucoside 4.99 489.1061 4.6 474.0824 95 [M-H-methyl]- 2 33 3,7-Dimethylquercetin 5.67 329.0679 3.7 314.0442 98 [M-H-methyl]- 2 34 Cirsilineol 6.47 343.0838 4.1 328.0597 95 [M-H-methyl]- 2

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Compound 17 The compound 17 eluted at retention time 0.86 min. in a TIC profile. The MS spectrum presents the molecular ion peak at m/z 299.0780 in the negative ionization mode i.e., [M-H]-, from here it came to know that the monoisotopic mass of the compound is 300.0827, [M]. The isotopic similarity was found to be 96.18 %. The MS/MS spectrum is shown in Fig. 4.5.

MA24H2_1 #330 RT: 0.86 AV: 1 NL: 3.62E5 F: FTMS - p ESI d Full ms2 [email protected] [50.00-325.00] 137.0243 100

50 93.0344

RelativeAbundance 30

10 107.7389 89.6302 123.5167 195.2578 223.4087 255.5786 0 60 80 100 120 140 160 180 200 220 240 260 280 300 320 m/z Fig. 4.5. MS2 spectrum of compound 17

The base peak at m/z 137.0243 of the MS/MS spectrum was attributed to the cleavage of a glucose moiety by the loss of 162.0537 mass units from the compound i.e. [M-H-glc]- ,[300-1- 162=137]-. An additional daughter ion peak appeared at m/z 93.0344 which corresponded to the

cleavage of a -CO2 molecule from 4-Hydroxy benzoic acid i.e. characteristic fragment of - - Phenolic acid, [4-Hydroxybenzoic acid-H-CO2] ,[138-1-44=93] . Accurate mass isotopic matching and fragmentation data suggested the eluted compound was 4-Hydroxybenzoic acid-4- O-glucoside (Bystrom et al., 2008). The structure of the identified compound is shown in Fig. 4.6.

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Fig. 4.6 Structure of the identified compound 17 Compound 18 The ESI-MS displayed the molecular ion peak at m/z 309.099 in the negative ionization mode i.e., [M-H]- at retention time 0.79 min. From here, it deduced that the accurate mass of the compound is 310.0137, [M]. Isotopic pattern matching was found to be 93.39 %. The MS/MS spectrum is shown in Fig. 4.7.

MA21M2_2 #297 RT: 0.79 AV: 1 NL: 1.70E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-335.00] 309.1214 100

80 89.0243

70 101.0245

40 71.0137

RelativeAbundance 59.0139 147.0665 174.9563 30 129.0558 119.0354 20 247.9697 282.4287

0 60 80 100 120 140 160 180 200 220 240 260 280 300 320 m/z Fig. 4.7 MS2 spectrum of compound 18

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A fragment ion peak in the MS/MS spectrum at m/z 147.0665 corresponded to the loss of 162.0325 mass units indicating a glucose moiety and corresponded to cinnamic acid. i.e. [M-H- glcl]- ,[310-1-162=147]-. A daughter fragment ion peak appeared at m/z 119.0354 due to the removal of –CO molecule by the loss of 28 mass unit from cinnamic acid i.e. [Cinnamic acid-H- CO]- , [148-1-28=119]-. Another daughter ion peak also known as base peak at m/z 89.0243 - corresponded to the loss of –CH2O molecule i.e. [Cinnamic acid-H-CO-CH2O] , [148-1-28- 30=89]-. The mass accuracy, isotopic similarity and fragmentation data corresponded to the compound Cinnamoyl glucose (Schuster and Herrmann, 1985). The structure of the identified compound is shown in Fig. 4.8.

Fig. 4.8 Structure of the identified compound 18 Compound 19 The compound 19 eluted at 3.11 min in a chromatogram. The mass spectrum presents the molecular ion peak at m/z 355.1051 in the negative ionization mode i.e., [M-H]-, from here it came to know that the monoisotopic mass of the compound is 356.1098. The isotopic similarity was 96.30 %. The MS/MS spectrum is shown in Fig. 4.9.

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MA24H2_2 #1208 RT: 3.11 AV: 1 NL: 4.87E5 F: FTMS - p ESI d Full ms2 [email protected] [50.00-380.00] 193.0504 100

70 134.0372

RelativeAbundance 30 178.0271

10 80.5168 109.2992 162.1198 351.6719 0 50 100 150 200 250 300 350 m/z Fig. 4.9 MS2 spectrum of compound 19

The base peak in the MS/MS spectrum was observed at m/z 193.0504, a loss of 162.0545 mass units which corresponded to the loss of a glucose moiety from the molecular mass i.e., [M- H-glc]- ,[356-1-162=193]-.The accurate mass m/z 193.0504 corresponds to deprotonated Ferulic acid. From accurate mass, isotopic matching and fragmentation spectra the compound was identified as Ferulic acid-4-O-glucoside (Wang et al., 2008). The structure of the identified compound is shown in Fig. 4.10.

Fig. 4.10 Structure of the identified compound 19

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Compound 20 ESI-MS of Compound 20 displayed corresponding to TIC time 3.24 min. in negative ionization mode. The pseudomolecular ion peak appeared at m/z 593.1508 i.e., [M-H]-, from here it came to view that the monoisotopic accurate mass of the compound is 594.1584. The isotopic similarity of the compound was found to be 89.90 %. The MS/MS spectrum is shown in Fig. 4.11.

MA24H2_2 #1260 RT: 3.24 AV: 1 NL: 6.74E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-625.00] 284.0331 100

RelativeAbundance

10 70.5944 139.7795

0 50 100 150 200 250 300 350 400 450 500 550 600 m/z Fig. 4.11 MS2 spectrum of compound 20

In the MS spectrum, the base peak appeared at m/z 284.0331 [M-2H]2- suggested the aglycone is luteolin (Roux et al., 1998) due to loss of 308.1127 mass units which inferred the removal of rutinose (Abu-Reidah et al., 2013) (glucose and rhamnose) moiety from the molecular mass of the compound i.e. [M-2H-glc-rha]2-, [594-2-146-162=284]2-.On the basis of these results, the compound was identified as Luteolin-7-rutinoside (Brito et al., 2014).The structure of the identified compound is shown in Fig. 4.12.

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Fig. 4.12 Structure of the identified compound 20 Compound 21 The ESI-MS of Compound 21 was represented by a peak at m/z 325.0941 in the negative ion mode i.e., [M-H]- at m/z 325.0941corresponding to TIC time 3.28 min. in negative ionization mode. The monoisotopic mass of the compound was calculated to be 326.1001, [M]. The isotopic matching was 95.72 %. The MS/MS spectrum is shown in Fig. 4.13.

MA21H2_3 #1268 RT: 3.28 AV: 1 NL: 1.56E5 F: FTMS - p ESI d Full ms2 [email protected] [50.00-350.00] 163.0399 100

60 119.0501

RelativeAbundance

10 67.8614 83.9420 104.7961 140.3839 174.9553 194.6284 301.6105 0 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z Fig. 4.13 MS2 spectrum of compound 21

The base peak in the MS/MS spectrum was found at m/z 163.0399 and agreed the cleavage of a glucose moiety i.e. the loss of 162.0545 mass units from the molecular mass i.e. [M-H-glc]- ,[325-1-162=163]-. On the basis of mass accuracy, isotopic matching and

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fragmentation data the compound was identified as p-Coumaric acid-4-O-glucoside (Rebecca and Robbins, 2003; Bystrom et al., 2008).The structure of the identified compound is shown in Fig. 4.14.

Fig. 4.14. Structure of the identified compound 21

Compound 22 The compound 22 eluted at retention time on a TIC tray at 3.95 min. and showed the molecular ion peak at m/z 609.1458 in the negative ionization mode i.e. [M-H]-, So, the monoisotopic accurate mass of the compound is m/z 610.1505. The MS/MS spectrum is shown in Fig. 4.15.

MA24H2_1 #1536 RT: 3.95 AV: 1 NL: 4.63E5 F: FTMS - p ESI d Full ms2 [email protected] [50.00-640.00] 300.0284 100

RelativeAbundance

20 609.1473

10 151.0041 61.9253 271.0244 343.0462 440.7778 0 50 100 150 200 250 300 350 400 450 500 550 600 m/z Fig. 4.15. MS2 spectrum of compound 22

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In the mass spectrum, the base peak was observed at m/z 300.0284 [M-2H]2- due to removal of 308.1127 mass units corresponding to the cleavage of a rutinose moiety from the molecular mass of the compound i.e. [M-2H-rutinose]2- ,[610-2-146-162=300]2-. From the accurate mass and MS/MS fragmentation, the compound was identified as Hispidulin-7-O- rutinoside (Phakeovilay et al., 2013). The structure of the identified compound is shown in Fig. 4.16.

Fig. 4.16. Structure of the identified compound 22 Compound 23 ESI-MS of Compound 23 corresponding to TIC time 4.02 min showed molecular ion peak at m/z 579.1348 in the negative ion mode, i.e., [M-H]-, from here it deduced that the monoisotopic mass of the compound is m/z 580.1395 [M]. Isotopic matching of the compound is 95.71 %. The MS/MS spectrum is shown in Fig. 4.17.

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MA24H2_2 #1568 RT: 4.02 AV: 1 NL: 5.92E5 F: FTMS - p ESI d Full ms2 [email protected] [50.00-610.00] 284.0333 100

RelativeAbundance 30

10 579.1346 178.9978 255.0303 57.7411 148.4231 419.6726 0 50 100 150 200 250 300 350 400 450 500 550 600 m/z Fig. 4.17 MS2 spectrum of compound 23 The MS data showed the fragment signal at m/z 284.0333 [M-2H]2- suggesting the aglycone was luteolin corresponding to loss of 294 mass units which inferred the cleavage of apiosyl and glucose moieties from the molecular mass of the compound i.e. [M-2H-xyl-glc]2- ,[580-2-132-162=284]2-. From the accurate mass, isotopic similarity and mass fragmentation the compound identified as Luteolin-7-O-(2-apiosyl-glucoside) (Barberán et al., 1985). The structure of the identified compound is shown in Fig. 4.18.

Fig. 4.18. Structure of the identified compound 23

CHAPTER 4

Compound 24 The compound 24 eluted at retention time 4.02 min. in a TIC profile and represented by a peak at m/z 623.1971 in the negative ionization mode, i.e. [M-H]-. The accurate mass of the compound was calculated as 624.2054, [M]. The isotopic matching of the compound was found to be 99.14 %. The MS/MS spectrum is shown in Fig. 4.19.

MA24H2_1 #1564 RT: 4.02 AV: 1 NL: 1.39E7 F: FTMS - p ESI d Full ms2 [email protected] [50.00-655.00] 161.0242 100

RelativeAbundance

20 461.1696

10 113.0243 623.1971 71.0137 179.0348 315.1096 233.0452 443.1580 477.1420 0 50 100 150 200 250 300 350 400 450 500 550 600 650 m/z Fig. 4.19. MS2 spectrum of compound 24

The MS/MS spectrum showed a peak at m/z 461.1696, a loss of 162.0275 mass units which inferred the cleavage of a glucose moiety from the molecular mass of the compound i.e. [M-H-glc]- ,[624-1-162=461]-. Another fragment peak was observed at m/z 315.1096 corresponding to the loss of 308.0875 (146+162) mass units which inferred the removal of glucose and rhamnose moiety from the compound i.e. [M-H-glc-rha]-, [624-1-162-146=315]-. The appearance of a fragment peak at m/z 161.0742 was attributed due to the loss of 462.1229 mass unit in an agreement to the cleavage of hydroxytyrosol molecule along with glucose and rhamnose moieties from the molar mass of the compound i.e. [M-H-glc-rha-hydroxytyrosol]-, [624-1-162-146-154=161]-. The MS fragmentation data, isotopic similarity and accurate mass measurements enabled identification of compound as Verbascoside (also known as Acetoside) (Blazics et al., 2011; Alipieva et al., 2014). The structure of the identified compound is shown in Fig. 4.20.

CHAPTER 4

Fig. 4.20. Structure of the identified compound 24

Compound 25 The compound 25 eluted at retention time at 4.10 min. on a TIC profile. ESI-MS spectrum indicated the molecular ion peak at m/z 477.0675 in the negative ion mode, i.e., [M-H]- , from here it came to view that the molecular mass of the compound is 478.0708, [M]. The isotopic matching was found to be 96 %. The MS/MS spectrum is shown in Fig. 4.21.

MA21H2_2 #1607 RT: 4.10 AV: 1 NL: 5.87E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-505.00] 301.0362 100

80 257.0459 70 283.0253 60

RelativeAbundance 315.0526 30

10 427.0383 462.0838 66.1986 114.8738 153.1395 239.5705

0 50 100 150 200 250 300 350 400 450 500 m/z Fig. 4.21. MS2 spectrum of compound 25

CHAPTER 4

The MS/MS data showed a base peak at m/z 301.0362 corresponding to the removal of 176.0331 mass units which attributed to the cleavage of a glucuronic acid moiety from the molar mass of the compound i.e. [M-H-glucuronic acid]- ,[478-1-176=301]-.These data suggested identification of the compound as Quercetin-3-O-Glucuronide (Badalica-Petrescu et al., 2014). The structure of the identified compound is shown in Fig. 4.22.

Fig. 4.22. Structure of the identified compound 25

Compound 26 The ESI-MS spectrum showed the molecular ion peak at m/z 477.1059 in the negative ionization mode, i.e., [M-H]- at a retention time of 4.12 min. So, it deduced that the accurate mass of the compound is 478.1106, [M]. The isotopic matching of the compound is 92.41 %. The MS/MS spectrum is shown in Fig. 4.23.

CHAPTER 4

MA24H2_2 #1610 RT: 4.12 AV: 1 NL: 3.49E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-505.00] 315.0522 100

90 283.0254

50 257.0446 462.0833 40

RelativeAbundance

477.1053 20 244.3831

83.9568 110.0874 156.6286 220.3257 10

0 50 100 150 200 250 300 350 400 450 500 m/z Fig. 4.23. MS2 spectrum of compound 26

The MS/MS data showed a peak at m/z 462.0833 corresponding to the loss of 15 mass unit which inferred the cleavage of methyl group from the compound i.e. [M-H-methyl].- ,[478- 1-15=462].-. The base peak appeared at m/z 315.0522 corresponding to the loss of 162.0545 which indicated the loss of glucose moiety from the compound i.e. [M-H-glc]- ,[478-1-162=315]- .With the help of accurate mass, isotopic pattern matching and mass fragmentation data the eluted compound was identified as Isorhamnetin-3-O-Glucoside (Carazzone et al., 2013). The structure of the identified compound is shown in Fig. 4.24.

Fig. 4.24. Structure of the identified compound 26

CHAPTER 4

Compound 27 In a total ion chromatogram, the compound 27 eluted at retention time 4.13 min. The MS spectrum presents the molecular ion peak at m/z 491.09 in the negative ionization mode, i.e., [M- H]-, from here it came to view that the monoisotopic accurate mass of the compound is 492.0903, [M]. The isotopic similarity is 95 %. The MS/MS spectrum is shown in Fig. 4.25.

MA21H2_2 #1616 RT: 4.13 AV: 1 NL: 3.62E5 F: FTMS - p ESI d Full ms2 [email protected] [50.00-520.00] 315.0520 100

RelativeAbundance

20 300.0278

10 113.0244 85.0293 205.4444 278.4374 473.0240 0 50 100 150 200 250 300 350 400 450 500 m/z

Fig. 4.25. MS2 spectrum of compound 27

In the MS/MS spectrum, the base peak was observed at m/z 315.0520 and represented a singly charged ion. A neutral loss of 176.0332 mass units corresponded to the cleavage of a glucuronic acid moiety from the precursor ion i.e. [M-H-glucuronic acid]-, [492-1-176=315]-. From the accurate mass, isotopic similarity and MS/MS fragmentation data, the compound was identified as Isorhamnetin-3-O-Glucuronide (Ferreres et al., 2013). The structure of the identified compound is shown in Fig. 4.26.

CHAPTER 4

Fig. 4.26. Structure of the identified compound 27

Compound 28 Compound 28 represented by a peak at m/z 341.0891 in the negative ionization mode, i.e., [M-H]-. The monoisotopic mass of the compound was calculated as 342.0950, [M]. Isotopic matching was 95.59 %. The MS/MS spectrum is shown in Fig. 4.27.

MA24H2_2 #1670 RT: 4.27 AV: 1 NL: 1.15E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-365.00] 164.0480 100

60 179.0716 50

RelativeAbundance 241.6437 30 119.7044 316.5539 60.1538 102.2465 156.1696 269.9023 20

0 50 100 150 200 250 300 350 m/z Fig. 4.27. MS2 spectrum of compound 28

CHAPTER 4

The MS/MS spectrum showed a fragment peak at m/z 179.0716 corresponding to the cleavage of a glucose moiety by the loss of 162.0475 mass units from the molecular mass i.e. [M-H-glc]- ,[342-1-162=179]-. The base peak was observed at m/z 164.0480 [M-H]-, a loss of 15 mass units which inferred that the cleavage of methyl from the caffeic acid aglycone i.e. [M-H- glc-methyl]- ,[342-1-162-15=164]-. From the accurate mass, isotopic matching and MS/MS fragmentation, the compound was identified as Caffeic acid-4-O-Glucoside (Shakya and Navarre, 2006). The structure of the identified compound is shown in Fig. 4.28.

Fig. 4.28. Structure of the identified Compound 28

Compound 29 The compound 29 eluted at retention time 4.36 on a TIC chromatogram. In the mass spectrum, the molecular ion peak appeared at m/z 445.0761 in the negative ionization mode i.e., [M-H]-, from here it came to observe that the accurate mass of the compound is 446.0849, [M]. The isotopic matching of the compound was found to be 89.78 %. The MS/MS spectrum is shown in Fig. 4.29.

CHAPTER 4

MA21H2_2 #1710 RT: 4.36 AV: 1 NL: 3.85E6 F: FTMS - p ESI d Full ms2 [email protected] [50.00-470.00] 269.0456 100

RelativeAbundance

20 113.0244 85.0294 10 59.0138 129.0193 175.0248 0 50 100 150 200 250 300 350 400 450 m/z Fig. 4.29. MS2 spectrum of compound 29

The base peak appeared at m/z 269.0455, a singly charged species corresponding to Apigenin (aglycone). The loss of 176.0261 mass units from the precursor ion indicated the presence of a glucuronic acid moiety i.e. [M-H-glucuronic acid]-, [446-1-176=269]-.The accurate mass, isotopic matching and fragmentation data corresponded with the identification of Apigenin-7-O-Glucuronide (Qu et al., 2001).The structure of the identified compound is shown in Fig. 4.30.

Fig. 4.30. Structure of the identified compound 29

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Compound 30 ESI-MS of Compound 30 displayed molecular ion peak at m/z 285.0409 in the negative ionization mode i.e., [M-H]- corresponding to TIC time 4.42 min. that indicated the accurate mass of the compound is 286.0456, [M]. The isotopic similarity of the compound was 99.67 %. The MS/MS spectrum is shown in Fig. 4.31.

MA21H2_3 #1726 RT: 4.42 AV: 1 NL: 6.05E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-310.00] 285.0810 100

RelativeAbundance

30 154.8986

10 126.9036 60.6415 73.0614 120.4682 162.0536 258.4825 0 60 80 100 120 140 160 180 200 220 240 260 280 300 m/z Fig. 4.31. MS2 spectrum of compound 30

The MS/MS spectrum provided a base peak at m/z 285.0810 i.e. [286-1=285]-. From the accurate mass, isotopic matching, and mass fragmentation the compound eluted as Scutellarein (Tang et al., 2015). The structure of the identified compound is shown in Fig. 4.32.

Fig. 4.32. Structure of the identified compound 30

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Compound 31 The elution of compound 31 take place at retention time 4.67 min. in a TIC chromatogram.The ESI-MS spectrum showed molecular ion peak at m/z 221.0456 in the negative ionization mode, i.e., [M-H]-, so it deduced that the accurate mass of the compound is 222.0503, [M]. The isotopic matching was found to be 95.33 %. The MS/MS spectrum is shown in Fig. 4.33.

MA21H2_2 #1836 RT: 4.67 AV: 1 NL: 3.14E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-245.00] 159.0811 100 177.0919

40 221.0822

RelativeAbundance 30

20 131.0502 81.0345 118.9419 162.8392 10 65.0368 89.8587 234.4438

0 60 80 100 120 140 160 180 200 220 240 m/z Fig. 4.33. MS2 spectrum of compound 31

A high intensity peak was observed at m/z 177.0919 corresponding to the loss of –CO2 - molecule due to the loss of 44 mass units from the molecular mass i.e. [M-H-CO2] ,[222-1- 44=177]-. The base peak appeared at m/z 159.0811 corresponding to the loss of a water molecule - - (H2O) from the precursor ion i.e. [M-H-CO2-H2O] ,[222-1-44-18=159] . From mass fragmentation, isotopic matching and accurate mass measurements the compound was identified as p-Coumaroyl glycolic acid (Plazonić et al., 2009). The structure of the identified compound is shown in Fig. 4.34.

CHAPTER 4

Fig. 4.34. Structure of the identified compound 31 Compound 32 The ESI-MS of Compound 32 displayed molecular ion peak at m/z 489.1064 i.e., [M-H]- corresponding to TIC time 4.99 min. in negative ionization mode. From here, it came to know that the monoisotopic accurate mass of the compound is 490.111, [M]. Isotopic pattern matching was found to be 95.98 %. The MS/MS spectrum is shown in Fig. 4.35.

MA24H2_2 #1958 RT: 4.99 AV: 1 NL: 3.22E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-515.00] 474.0821 100

489.1064 60

298.0500 50

RelativeAbundance

30 283.0264 20 456.7755 105.0347 152.3802 202.1768 373.7828 10 55.1530

0 50 100 150 200 250 300 350 400 450 500 m/z Fig. 4.35. MS2 spectrum of compound 32

CHAPTER 4

The MS/MS data showed a base peak at m/z 474.0821 a loss of 15.0237 mass units corresponding to the cleavage of a methyl group i.e., [M-H-methyl]- ,[490-1-15=474]-. Another fragment peak was observed at 456.7755 due to the loss of a water molecule from m/z 474 i.e., - - [475-H-H2O] ,[475-1-18=456] . Another daughter fragment appeared at m/z 298.0500 corresponding to the cleavage of a glucose moiety along with a methyl radical (14 mass unit) from m/z 474 i.e., [475-H-glc-methyl radical]-,[475-1-162-14=298]-.The MS fragmentation data suggested the compound is Kaempferol-3-O-acetylglucoside (Kajdžanoska et al., 2010). The structure of the identified compound is shown in Fig. 4.36.

Fig. 4.36. Structure of the identified compound 32

Compound 33 The compound 33 eluted at 5.61 min. in the TIC profile. The mass spectrum showed peak at m/z 329.0679 in the negative ionization mode, i.e., [M-H]-. The molecular mass of the compound was calculated as 330.0739, [M]. The isotopic similarity was found to be 98.79 %. The MS/MS spectrum is shown in Fig. 4.37.

CHAPTER 4

MA21H2_2 #2211 RT: 5.61 AV: 1 NL: 5.25E5 F: FTMS - p ESI d Full ms2 [email protected] [50.00-355.00] 314.0442 100

70 299.0205

RelativeAbundance 329.0680 30

10 146.9615 174.9556 271.0247 84.5687 111.8053 0 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z Fig. 4.37. MS2 spectrum of compound 33

The MS/MS spectrum showed a base peak at m/z 314.0442 [M-H]- corresponding to the loss of 15.0237 mass units which inferred the cleavage of methyl from the molar mass of the compound i.e., [M-H-methyl]- ,[330-1-15=314]-. The other fragment ion signal was observed at m/z 299.0205 [M-H]- due to the neutral loss of another methyl molecule from the molecular - - ·- compound i.e., [M-H-dimethyl] , [330-1-15-15=299] . The loss of [M-H-CH3] is a characteristic loss of methylated flavonoids. On the basis of accurate mass, isotopic similarity and MS/MS fragmented data the compound was identified as 3,7-dimethylquercetin (Guerrero et al., 2002). The structure of the identified compound is shown in Fig. 4.38.

CHAPTER 4

Fig. 4.38. Structure of the identified compound 33

Compound 34 The ESI-MS of Compound 34 displayed molecular ion peak at m/z 343.0838 i.e., [M-H]- corresponding to TIC time 6.47 min. in the negative ion mode. The accurate mass of the compound is 344.0885, [M]. The isotopic matching of the compound was 95.05 %. The MS/MS spectrum is shown in Fig. 4.39.

CHAPTER 4

MA21H2_2 #2568 RT: 6.47 AV: 1 NL: 3.08E4 F: FTMS - p ESI d Full ms2 [email protected] [50.00-370.00] 328.0597 100

80 313.0376 70

RelativeAbundance 30

20 238.5788 343.0829 55.0025 111.6807 157.7939 259.8119 10 181.8426

0 50 100 150 200 250 300 350 m/z Fig. 4.39. MS2 spectrum of compound 34 The appearance of a base peak at m/z 328.0597 was attributed to the loss of a methyl - - from the molecular mass i.e., [M-H-CH3] ,[344-1-15=328] . Another fragment signal appeared at - - m/z 313.0376 [M-H] due to the loss of second methyl from the molecule i.e., [M-H-2CH3] ,[344-1-30=313]-. The accurate mass, isotopic matching and fragmentation data supported the identification of the compound as Cirsilineol (Sheng et al., 2008). The structure of the identified compound is shown in Fig. 4.40.

Fig. 4.40. Structure of the identified compound 34

CHAPTER 4

Finally, the measured accurate mass value, measured isotope pattern and tandem mass spectra for each metabolite were compared with those from the human metabolome database (HMDB). The HMDB is an online structural database with over 75,000 compounds that have been found in human samples, from both endogenous and exogenous origins. It therefore, contains, and is a useful source of, plant-derived compounds. We identified 55 additional compounds that met the combined criteria: 5 ppm or less mass accuracy, > 90 % isotope pattern similarity and a match between experimental and theoretical tandem mass spectra. A putative identification was assigned only when at least the base peak and an additional ‘high abundance’ peak in the tandem mass spectra (that was not the [M-H]- peak) were present with less than 5ppm mass accuracy. These were classed as level 2 putative identifications and are listed in Table 6. It should be noted that based on accurate mass values, isotope profile and some fragmentation matching alone it is not possible to be certain all structural isomers are distinguished, particularly those not present in the HMDB database. Hence some ‘accepted descriptions’ in Table 6 may not be correct, hence their ‘putative identification’ status. However, all 34 level-1 and level-2 identifications found in Table 4 and Table 5 were also identified using the HMDB search which provides some confidence in the ability of the HMDB search to correctly identify plant-derived metabolites. These have been excluded from Table 6 so as not to recapitulate data. A total of 89 compounds (composed of level-1 and level-2 assignments) were identified from the Martynia annua extracts.

CHAPTER 4

Table 6. Putative metabolite identifications based on multi-parameter matches with the human metabolome database (HMDB). “Note these putative identifications are included based on matching with the HMDB database via correspondence between accurate m/z values, isotope patterns and matching multiple fragmentation peaks. The chemical formulae are likely to be correct, however, a number structural isomers may exist in nature that are not represented by the HMDB so it is not possible to be certain ‘accepted description’ are correct, hence their designation as ‘putative identifications’.”

Accepted Description m/z Retention Highest Maximum Formula Fragmentat Mass Error Isotope time (min) Mean Abundance ion Score (ppm) Similarity

Abscisic acid 263.1291 8.03 Leaves 2222.82 C15H20O4 80.6 0.73 95.82

Aflatoxin G2a 345.0629 5.62 Flower 132.31 C17H14O8 56.7 3.90 95.66

Aflatoxin M2 329.0679 5.61 Leaves 9810.18 C17H14O7 55.8 3.57 98.79

Alpha-dihydroartemisinin 283.1558 5.67 Leaves 562.32 C15H24O5 56 2.53 93.19

Alpha-dimorphecolic acid 295.2287 8.15 Flower 32239.17 C18H32O3 41.4 2.94 96.13

Biochanin A 283.0619 6.65 Leaves 146.31 C16H12O5 95.6 4.28 95.71

Brassinolide 479.3401 9.39 Stem 2845.41 C28H48O6 60.1 4.81 90.74

Calonectrin 349.1672 5.91 Roots 1162.46 C19H26O6 43.5 4.50 94.62

Cyclopassifloic acid B 519.3699 8.59 Leaves 18736.74 C31H52O6 49.1 1.58 91.39

Dihydrocortisol 363.2173 8.15 Flower 1990.35 C21H32O5 21.3 -1.14 91.01

Dodecanedioic acid 229.1445 5.96 Flower 3695.27 C12H22O4 73.5 -0.17 96.88

Ethyl glucuronide 221.0667 0.75 Leaves 186.82 C8H14O7 58 -0.07 98.73

Glyyunnansapogenin B 487.3452 7.20 Roots 18325.24 C30H48O5 60.3 4.67 95.53

Isopropyl apiosylglucoside 353.1468 3.54 Roots 2091.95 C14H26O10 68.9 4.21 93.13

Nigellic acid 279.1243 4.40 Leaves 1174.59 C15H20O5 52.4 1.72 96.17

Panaxatriol 475.3814 9.94 Leaves 43687.13 C30H52O4 57 4.54 94.91

Pantothenic acid 218.1033 1.40 Flower 2145.94 C9H17NO5 26.6 -0.26 96.14

Phytocassane E 315.1976 7.61 Roots 1883.78 C20H28O3 41.3 3.30 93.81

Polyethylene, oxidized 243.1239 4.83 Leaves 647.68 C12H20O5 54.1 0.29 95.84

Prenyl glucoside 247.1187 3.92 Stem 1494.89 C11H20O6 34.7 -0.01 94.60

Propyl 1- 239.06 9.58 Leaves 8508.75 C9H20OS3 44.2 -1.55 93.47 (propylsulfinyl)propyl

CHAPTER 4 disulfide

Quercetin 301.0362 5.07 Flower 195.05 C15H10O7 88.9 2.66 97.11

Suberic acid 173.082 4.08 Flower 10977.59 C8H14O4 25.6 0.49 96.73

Triamterene 252.1005 10.07 Stem 77743.52 C12H11N7 35.2 0.67 92.02

Undecanedioic acid 215.1287 5.52 Stem 7891.77 C11H20O4 71.5 -0.65 97.36

Yucalexin P8 329.1773 6.65 Roots 17518.31 C20H26O4 67.6 4.30 96.16

(+)-15,16- 315.2552 8.37 Stem 11035.59 C18H36O4 68.7 3.59 95.30 Dihydroxyoctadecanoic acid (+)-Chebulic acid 355.0303 6.42 Flower 432.50 C14H12O11 43.2 -1.11 96.96

(3β,6β -Furanoeremophilane- 291.161 7.90 Leaves 3823.51 C17H24O4 74 2.85 95.95 3,6-diol 6-acetate (S)-10,16- 287.2235 7.05 Flower 2340.00 C16H32O4 22.8 2.46 94.74 Dihydroxyhexadecanoic acid 1,3,5,8-Tetrahydroxy-6- 477.1059 4.54 Flower 1589.23 C22H22O12 37.8 4.30 90.63 methoxy-2- methylanthraquinone 8-O- β - D-glucoside 2,4-Dimethylpimelic acid 187.0975 4.59 Flower 41029.50 C9H16O4 45.7 -0.47 97.95

2-Carboxy-4-dodecanolide 241.1447 6.74 Flower 5149.62 C13H22O4 71.3 0.71 96.31

2-Ethylsuberic acid 201.1132 5.06 Flower 6571.97 C10H18O4 55.1 -0.32 97.26

2-Methyl-3-ketovaleric acid 129.0557 2.88 Roots 46.30 C6H10O3 31 0.15 96.58

2-Octenedioic acid 171.0664 4.25 Flower 1394.70 C8H12O4 23.4 0.63 90.81

3,4-Dimethyl-5-pentyl-2- 349.2763 9.90 Stem 7306.00 C22H38O3 88.4 4.36 92.71 furanundecanoic acid 3,4-Methyleneazelaic acid 211.0974 5.44 Flower 873.99 C11H16O4 53.2 -0.85 94.53

3,4-Methylenesebacic acid 225.1133 5.35 Flower 838.09 C12H18O4 55.6 0.31 96.55

3',5-Dihydroxy-4',7- 315.0885 6.16 Fruits 190.72 C17H16O6 37.6 3.37 94.75 dimethoxyflavanone 3-Hydroxy-6,8-dimethoxy- 309.1722 6.95 Flower 4788.15 C17H26O5 15.5 4.83 92.47 7(11)-eremophilen-12,8-olide 3-Hydroxyisoheptanoic acid 145.087 4.73 Flower 693.67 C7H14O3 19.4 -0.01 95.96

3-Hydroxysebacic acid 217.1081 4.20 Flower 620.32 C10H18O5 30.1 -0.41 91.76

3-hydroxytridecanoic acid 229.1811 8.10 Leaves 689.64 C13H26O3 29.9 0.64 94.76

3-Oxododecanoic acid 213.1495 5.73 Flower 580.24 C12H22O3 55.4 -0.46 95.07

CHAPTER 4

4,11,13,15- 267.1605 6.65 Leaves 1147.25 C15H24O4 46 1.25 95.05 Tetrahydroridentin B 4-Hydroxybenzoic acid 137.0243 3.10 Leaves 2255.49 C7H6O3 19.5 -0.52 98.87

4-Nonylphenol 219.1755 8.88 Fruits 2675.73 C15H24O 19.9 0.08 95.55

5'-(3'-Methoxy-4'- 221.0819 4.68 Roots 2070.27 C12H14O4 60 -0.04 96.44 hydroxyphenyl)-gamma- valerolactone 5-Heptyltetrahydro-2-oxo-3- 227.129 6.17 Leaves 3040.23 C12H20O4 36.9 0.54 96.78 furancarboxylic acid 5-Hexyltetrahydro-2- 297.2445 8.56 Flower 7981.16 C18H34O3 18.2 3.15 94.65 furanoctanoic acid 6-Hydroxyhexanoic acid 131.0713 3.77 Flower 332.22 C6H12O3 38.7 -0.26 98.79

7(14)-Bisabolene-2,3,10,11- 271.1919 7.22 Stem 2324.33 C15H28O4 47 1.47 96.14 tetrol 9-Hydroxydecanoic acid 187.1338 6.57 Flower 1188.85 C10H20O3 51.3 -0.85 96.91

CHAPTER 4

Five of the most abundant compounds identified using authentic standards (trans-ferulic acid, syringic acid, apigenin, isorhamnetin and hispidulin) have previously been shown to possess bioactive, medicinal properties (Muazzam et al., 2018). The most abundant identified compound was trans-ferulic acid which is a constituent of plant cell walls. It has anti-oxidant properties which have also been shown to have anti-tumor and pro-apoptotic activities on cancer cells (Kampa et al., 2004; Lee, 2005). Isorhamnetin was the second most abundant compound identified in leaves. This compound has been shown to have anti-inflammatory activity in vitro as well as being an iNOS protein and mRNA expression inhibitor, when tested in macrophages, stimulated with lipopolysaccharide (LPS) (Kim et al., 2014; Hamalainen et al., 2007; Kim and Choi, 2013; Antunes-Ricardo et al., 2015; Sherry et al., 2012). Syringic acid, the third most abundant compound identified in all plant parts, has been previously shown to have antioxidant, antibacterial and hepatoprotective activity (Itoh et al., 2010; Kong et al., 2008). Apigenin, abundant in leaves and flowers has potent antibacterial effects (Nayaka et al., 2014) and antileukemic activity (Budhraja et al., 2012). It also induces autophagy and has been shown to bind to multiple receptors (adenosine, GABA, and opioids); it's, therefore, a multi-mode agonist with potential therapeutic effects (Viols et al., 1995; Jacobson et al., 2002; Losi et al., 2004; Katavic et al., 2007). Hispidulin, most abundant in flowers is a bioactive flavone and has been reported as an effective anti-cancer agent and the strongest ligand of the benzodiazepine (BZD) site of the GABAA receptor (Kavvadias et al., 2004). Table 5 provides an overview of known biological/medicinal effects of the compounds identified and quantified in the Martynia annua extracts.

CHAPTER 4

Table 7. Known biological and medicinal activity of identified compounds.

No. Compound ID Type of compound Biological /medicinal effect References for medicinal/biological activity

1 Protocatechuic acid Phenolic acid Cytotoxic, chemopreventive, apoptotic and neuroprotective (Yip et al., 2006; Yin et al., 2009; An et activity al., 2006) 2 Gentisic acid Phenolic acid Anti-inflammatory, antirheumatic and cytostatic properties (Ashidate et al., 2005) 3 Caffeic acid Phenolic acid Antimicrobial and anticancer activity (Alves et al., 2013; Hwang et al., 2006) 4 Syringic acid Phenolic acid Antioxidant, antibacterial and hepatoprotective activity (Itoh et al., 2010; Kong et al., 2008) 5 Rutin Flavonol glycoside Antioxidant, antihyperglycaemic (Zielińska et al., 2010; Kamalakkannan and anticancer activity and Prince, 2006; Dixit 2014) 6 Homovanilic acid Phenolic acid Hepatoprotective and a novel specific inhibitor of snake venom (Itoh et al., 2010; Dhananjaya et al., 2009) 5'-nucleotidase 7 p-Coumaric acid Phenolic acid Antioxidant, antitumor and antimicrobial activity (Rice-Evans et al., 1996; Heleno et al., 2014a; Heleno et al., 2014b) 8 Sinapic acid Phenolic acid Antioxidant and antiproliferative activity (Galano et al., 2011; Kampa et al., 2004) 9 trans-Ferulic acid Phenolic acid Antioxidant, anti-proliferative and apoptotic property (Kikuzaki et al., 2002 ; Kampa et al., 2004; (Lin and Nakatsui, 1998) 10 Salicylic acid Phenolic acid Analgesic, antipyretic, anti-inflammatory, antiseptic and (Lin and Nakatsui, 1998) antifungal properties 11 Luteolin Flavone Antioxidant, anticancer, anti-leishmanial and anti-inflammatory (Brown and Rice-Evans, 1998; Fang et al., activity 2007; Mittra et al., 2000; Ziyan et al., 2007) 12 Apigenin Flavone Antibacterial and antileukemic activity (Nayaka et al., 2014; Budhraja et al., 2012) 13 Kaempferol Flavonol Anticancer activity (Luo et al., 2009; Damianaki et al., 2000; Kim et al., 2014) 14 Hispidulin Flavone Anticancer activity (Kavvadias et al., 2004) 15 Hesperetin Flavanone Anticancer, antioxidant and neuroprotective activity (Shirzad et al., 2015; Roohbakhsh et al., 2015; Cho, 2006) 16 Isorhamnetin Flavonol Anti-inflammatory activity (Hamalainen et al., 2007)

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4.5. Identification of Compounds by GC-MS Analysis The interest in plants volatile compounds is focused on their biological potential, which includes antimicrobials, antibacterial, antifungal and antioxidant properties and inhibition of prostaglandin, antidiabetic and antiplatelet effects (Edris, 2007). In addition, they are deeply appreciated due to their flavor and fragrances and are also important for food, pharmaceutics, cosmetics and textile industries. Therefore, systematical protocols should be entrenched to study compositional features of volatile compounds including productive sampling technique and sensitive detection. GC-MS is a powerful technique in term of separation and detection of volatile compounds as it required no purity and very low sample amount. In qualitative analysis the more precise information can be obtained through it (Zhang et al., 2007).

The present exploration involved the task of initial structural deduction on the basis of molecular weight, molecular formula, peak area and retention time. A list of identified compounds is presented in Table 8. Structures of some of the prominent compounds are shown in Fig. 4.41. GC-MS analysis unveiled the presence of 73 volatile constituents that could contribute the medicinal quality of the plant. From the results obtained, it is evident that the separated compounds are belonging to hydrocarbons, esters, alcohols, aldehydes, ketones, aromatics, carboxylic acids, alkaloids, terpenes, steroids and carbohydrates.

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Table 8. Compounds identified from Martynia annua by GC-MS analysis.

No. Compound ID Molecular RT (min.) Formula Peak area Mass (%) 1 1-Methyl-4-propan-2-ylbenzene 134 2.121 C10H14 21.243

2 (5-methylfuran-2-yl)methanol 112 2.201 C6H8O2 61.985

3 Methoxymethylbenzene 122 2.201 C8H10O 16.272

4 Ethyl-4-oxopentanoate 144 2.230 C7H12O3 21.744

5 6-methyl-5-propan-2-ylhept-5-en-3-yn-2-ol 166 2.258 C11H18O 17.819

6 3-Propan-2-yloxyaniline 151 2.447 C9H13NO 7.378

7 Propyl tetradecanoate 270 2.888 C17H34O2 4.676

8 Ethyl nonanoate 186 5.068 C11H22O2 3.138

9 3-Methylcyclohex-2-en-1-one 110 5.451 C7H10O 1.713

10 5-Methyl-1H-pyrazole 82 5.468 C4H6N2 16.003

11 (1R,2S,4R,5S)-cyclohexane-1,2,4,5-tetrol 148 5.920 C6H12O4 2.757

12 [(E)-2-ethoxyethenyl] acetate 130 6.390 C6H10O3 1.160

13 Pyridin-2-ylhydrazine 109 6.584 C5H7N3 16.259

14 1-Methylcyclohexane-1-carboxylic acid 142 6.590 C8H14O 16.259

15 1-Methylpyrrole-2-carbaldehyde 109 6.590 C6H7NO 18.448

16 9-Oxabicyclo[6.1.0]non-2-en-7-one 138 6.596 C8H10O2 28.772

17 4-Aminophenol 109 6.601 C6H7NO 18.894

18 Benzene-1,4-diol 110 6.664 C6H6O2 11.254

19 2-Methylundecan-5-ol 186 6.756 C12H26O 14.729

20 Cyclohexane propanoic acid 158 6.767 C9H18O2 3.216

21 2-(tert-butylamino)ethanol 117 6.779 C6H15NO 5.432

22 3-(2-methylprop-1-enyl)-1H-indene 170 6.933 C13H14 2.903

23 (Z)-8-methylundec-2-ene 168 7.002 C12H24 3.467

24 Methyl-4,4-dimethyl-3-oxopentanoate 158 7.002 C8H14O3 3.467

25 2-(diethylamino)ethyl prop-2-enoate 171 7.729 C9H17NO2 0.417

26 (3R,4R,5S,6R)-6-(hydroxymethyl)oxane-2,3,4,5-tetrol 180 7.786 C6H12O6 32.744

27 (3R,4R,5R)-2-methoxyoxane-3,4,5-triol 164 7.906 C6H12O5 10.328

28 (3R,4R,5R)-2-methoxyoxane-3,4,5-triol 164 7.929 C6H12O5 20.582

29 (3R,4S,5S,6R)-2-ethoxy-6-(hydroxymethyl)oxane-3,4,5-triol 208 8.003 C8H16O6 8.450

30 2,6,6-trimethyl-3,4-diphenyl-2-phosphabicyclo[3.1.0]hex-3- 292 10.921 C20H21P 1.143 ene 31 Methyl tetradecanoate 242 11.419 C15H30O2 3.074

32 Ethyl hexadecanoate 284 11.431 C18H36O2 0.605

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33 (5S,8R,9S,10S,13R,17S)-17-ethyl-10,13-dimethyl- 286 11.957 C21H34 0.768 2,3,4,5,6,7,8,9,11,12,16,17-Dodecahydro-1H- cyclopenta[a]phenanthrene

34 Tetradecan-4-yl 2-methoxyacetate 286 12.421 C17H34O3 1.164

35 Nona-1,8-diyne 120 12.489 C9H12 1.117

36 (Z)-1,1-dimethoxyoctadec-9-ene 312 12.575 C20H40O2 8.152

37 1-Methoxyoctadec-9-ene 282 12.587 C19H38O 1.439

38 (E,7R,11R)-3,7,11,15-tetramethylhexadec-2-en-1-ol 296 12.598 C20H40O 4.759

39 Ethyl (9Z,12Z)-octadeca-9,12-dienoate 308 13.033 C20H36O2 1.505

40 Pentadecan-4-yl 2,2,2-trifluoroacetate 324 13.994 C17H31F3O2 1.181

41 (Z)-tricos-7-ene 322 14.051 C23H46 1.949

42 (E)-3-(1-ethyl-5-methylpyrazol-4-yl)-1-(1H-pyrrol-2-yl)prop- 229 14.715 C13H15N3O 1.622 2-en-1-one 43 (4bS,8aS)-4b,8,8-trimethyl-2-propan-2-yl-5,6,7,8a,9,10- 286 14.767 C20H30O 24.279 hexahydrophenanthren-3-ol

44 (17-ethyl-10,13-dimethyl-2,3,4,5,6,7,8,9,11,12,14,15,16,17- 346 14.778 C23H38O2 9.753 tetradecahydro-1H-cyclopenta[a]phenanthren-3-yl) acetate 45 (Z)-octadec-9-enamide 281 14.870 C18H35NO 2.410

46 bis(6-methylheptyl) hexanedioate 370 15.001 C22H42O4 0.350

47 8,10-Diethylbenzo[a]acridine 285 15.345 C21H19N 14.683

48 7-(4-methoxyphenyl)-5-oxo-2,3-dihydro-[1,3]thiazolo[3,2- 285 15.511 C14H11N3O2S 9.610 a]pyrimidine-6-carbonitrile 49 1-Pentyl-2-propylcyclopentane 182 15.654 C13H26 1.972

50 (Z)-pentacos-12-ene 350 15.705 C25H50 6.865

51 Nonadecane 268 15.831 C19H40 5.550

52 2-Methylheptadecane 254 17.570 C18H38 2.734

53 Heptacosane 380 17.576 C27H56 2.734

54 Triacontane 422 17.582 C30H62 3.440

55 Tricosane 324 17.587 C23H48 5.252

56 (6Z)-2,6-dimethylocta-2,6-diene 138 18.955 C10H18 13.155

57 7,11-Dimethyl-3-methylidenedodeca-1,6,10-triene 204 18.955 C15H24 82.657

58 (6E,10E,14E,18E)-2,6,10,15,19,23-hexamethyltetracosa- 410 18.972 C30H50 13.128 2,6,10,14,18,22-hexaene 59 (6E,10E,14E,18E)-2,6,10,14,18-pentamethylicosa- 342 18.995 C25H42 1.362 2,6,10,14,18-pentaene 60 3,3-Dimethylbicyclo[2.2.1]heptan-2-one 138 19.865 C9H14O 2.946

61 Docosane 310 20.031 C22H46 0.706

62 Hexacosane 366 20.054 C26H54 11.622

63 2,6,10,14-tetramethylhexadecane 282 20.065 C20H42 13.169

64 Nonacosane 408 17.582 C29H60 9.136

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65 4-Octyl-N-(4-octylphenyl)aniline 393 21.381 C28H43N 0.395

66 2-Methylicosane 296 23.761 C21H44 20.053

67 Eicosane 282 23.773 C20H42 20.804

68 Pentacosane 352 23.893 C25H52 8.865

69 Dodecyl-2-sulfanylacetate 260 29.501 C14H28O2S 1.124

70 Hentriacontane 436 29.695 C31H64 11.162

71 (3S,8S,9S,10R,13R,14S,17R)-17-[(2R,5R)-5-ethyl-6- 414 30.537 C29H50O 1.155 methylheptan-2-yl]-10,13-dimethyl- 2,3,4,7,8,9,11,12,14,15,16,17-Dodecahydro-1H- cyclopenta[a]phenanthren-3-ol

72 Heneicosane 296 38.450 C21H44 4.716

73 Tridecan-2-yl-2-methoxyacetate 272 38.484 C16H32O3 4.716

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Fig. 4.41. Structures of some of the prevailing bioactive compounds from Martynia annua

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From the study, it is cleared that esters constitute the major portion of the identified compounds. For normal growth, unsaturated fatty acids are significant to every cell in the body, especially of the blood vessels and nerves and to keep the skin youthful due to their lubricating quality. These are nutrients which are extremely useful for the production and movement of energy throughout the body. They are also used as an oxygen regulator for transportation and are crucial in sustaining the integrity of cell structure and have the unique ability to lower the blood cholesterol levels (William, 2000).For instance, Ethyl hexadecanoate one of the identified compound showed nematicide, pesticide, hypocholesterolemic, flavor, lubricant, antiandrogenic and 5α reductase inhibitor antioxidant activity (Jegadeeswari et al., 2012) and lenoleic acid, ethyl/methyl esters exhibit antimicrobial and antimalarial activities (Paula et al., 2012). The occurrence of esters in Martynia annua may be the reason behind the use of extracts in the self- treatment of wounds/ailments as the previous reports suggests (Satyavati et al., 1987). Phytol, a reactive oxygen species (ROS) belongs to an auspicious class of pharmaceuticals, that stimulating substances used for the treatment of arthritis and inflammatory chronic diseases (Ogunlesi et al., 2009). Identification of Phytol showed antibacterial activities against staphylococcus aureus by engender cell membrane breakage which results in the spillage of potassium ions (Inoue et al., 2005). Ferruginol (a monoterpene, having a partial terpenoid structure) one of the identified constituent and possesses anti-tumor, antibacterial activity. Gastroprotective effects of ferruginol have also been reported (Carlos et al., 2008). β-Sitosterol is one of the investigated compound and showed hypercholesterolemia, cardiac effect and anti-cancer activities. Steroids are wide spread in nature; many steroidal derivatives have physiological activities. Steroid hormones control fertility and sexual reproduction in the human body. Based upon their physiological functions steroids are used in medicine for curing cancer, arthritis or allergies and in birth control (Okwu and Ighodaro, 2010). Carbohydrates comprise a large portion of investigated compounds. These compounds are the major source of fuel for metabolism and used as an energy supplier in biosynthetic pathways and take part in the cellular structures of plant and animal. They play a pivotal role in blood clotting, fertilization, pathogenesis, protein folding and placement and in the immune

CHAPTER 4 system. Carbohydrates investigation is important in research and development as they are potential bio informative molecules (Campa et al., 2006). Nitrogen (alkaloids) and sulfur containing compounds have also been screened in this study. Heterocyclic compounds have a great scope in clinical and pharmaceutical studies. Alkaloids exhibit anti-microbial, antipyretics, antimalarial, antiarrhythmic, stimulant, analgesic and antitumor activities. The antibiotics, antimicrobial and antioxidant activities of organosulfur compounds have also been reported. Organosulphur compounds (OSCs) offer protection against cancer as they slow down or prevent the carcinogenic process instigate by a variety of chemical carcinogens. These include inhibition of the carcinogens, dermatitis and other small wounds (Jumare et al., 2015).

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4.6.Total Phenolic Content (TPC) Plant phenolic constituents endeavor their health beneficial effects predominantly through antioxidant activity (Fang et al., 2002). Phenolic compounds have the ability to intercept singlet oxygen, decreasing oxygen amount, phenolic scavenge initial radicals such as hydroxyl by preventing 1st chain initiation, disintegrate primary products of oxidation to non-radical species, binding metal catalysts ion and terminating chain reactions (Shahidi and Naczk, 2003). Current study exhibited the phenolic content of leaves, stem, fruit, flower and root of Martynia annua. Folin-Ciocalteu’s reagent assay was used to determine total phenolic content in the plant samples. TPC is expressed in term of Gallic Acid Equivalent (GAE) using the standard curve as shown in Fig. 4.42. The values obtained for total phenolic contents are presented as µg/mL gallic acid equivalent.

0.8

0.7 y = 0.0011x + 0.0163 R² = 0.9922 0.6

0.5

0.4

Absorbance 0.3

0.2

0.1

0 0 100 200 300 400 500 600 700 Concentration (ug/mL)

Fig. 4.42. Calibration curve for total phenolic determination

Phenolic content of the plant was determined by using calibration equation (y=0.0011x+0.0163) and the R2 (coefficient of determination) value was 0.99. It revealed that, the higher phenolic content was found in leaves extract i.e., 226.84 µg/mL. The phenolic content was lower in Stem i.e., 56.79 µg/mL gallic acid equivalents. The order of total phenolic content

CHAPTER 4 in plant parts was as follows; Leaves > Flower > Root > Fruit > Stem. Results indicated that, leaves and flowers extracts have considerable amount of phenolics (Muazzam and Farman, 2018).

4.7.Total Flavonoid Content (TFC) One of the most versatile and diverse groups of natural compounds is flavonoids. These compounds exhibit wide range of chemical and biological properties predominantly free radical scavenging activities. From the epidemiological studies, it is suggested that utilization of flavonoid rich diet prevents from human diseases correlated to oxidative stress (Hempel and Bohm, 1996; Romani et al., 2004). To determine the potential part of flavonoids on antioxidant capacity, TFCs of the extracts were analyzed using a calibration curve of Rutin as shown in Fig. 4.43. The flavonoid contents are shown in µg/mL Rutin Equivalent (RE) as presented in Table 9.

0.3 y = 0.0009x - 0.017 0.25 R² = 0.989

0.2

0.15

Absorbance 0.1

0.05

0 0 50 100 150 200 250 300 350 Concentration (µg/mL)

Fig. 4.43. Calibration curve for total flavonoid determination

Flavonoid content was determined by using calibration equation (y= 0.0009x-0.017) and the R2 (coefficient of determination) value was 0.98. The leaves part of Martynia annua contained higher quantity of flavonoids by its total flavonoid content i.e., 152.02 µg/mL RE. Stem have lower flavonoid content i.e., 21.78 µg/mL, which is in agreement that leaves contain highest content of flavonoids among all the parts.

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Flowers contain high content of flavonoids in it. The order of TFC in all plant parts was same as TPC i.e. Leaves > Flower > Root > Fruit > Stem (Muazzam and Farman, 2018).

4.8. Antioxidant Activity “Any compound that inhibit oxidation is called antioxidant compound” Flavonoids composed a large group of plant secondary metabolites. Flavonoids have proved to be natural antioxidant compounds and prevent the oxidative stress of the cellular systems. Redox properties of phenolic compounds are mainly responsible for their antioxidant activities. Flavonoids act as reducing agents (free radical scavenger), hydrogen donors, metal chelator and singlet oxygen alleviator (Cook and Samman, 1996). Studies suggested that intake of antioxidant rich diet offers health advantages (Aruoma, 1998). In plants, phenolic compounds are chemically diverse and complex in their composition which becomes difficult and inefficient to separate each compound and deal it individually. Therefore, it is often more appropriate to measure total antioxidant capacity of complex plant extract because of cooperative antioxidant action. For that purpose, various protocols are applicable to measure antioxidant activity of natural metabolites in foods, biological systems and in medicinal plant extracts. Commonly used antioxidant assays include, DPPH, ABTS, FRAP,

H2O2, TREC, ORAC Nitric oxide antioxidant methods. In this study, three different antioxidant assays i.e., DPPH, ABTS and FRAP have been used to assess the antioxidant potential of M. annua. 4.8.1. DPPH Antioxidant Activity The antioxidant potential of different extracts of M. annua plant are examined by using 2,2-diphenyl-1-hydrazine (DPPH) reagent. It is a very stable free radical and can accept an electron or hydrogen radical to convert into a stable molecule as shown in Fig. 4.44. Freshly prepared methanolic solution of DPPH showed a purple color which exhibits a strong absorption at 517 nm, because of its odd electron number. The DPPH solution generally loses its color when antioxidant molecules in the plant extracts quench free radicals of DPPH (i.e., by electron donation or by providing hydrogen atoms) and convert them into a colorless substance (a substituted analogous hydrazine). A decrease in absorbance was monitored at 517 nm by spectrophotometrically.

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Fig. 4.44. Reaction of DPPH molecule with antioxidant

The antioxidant capacity of all plant parts were presented in terms of percentage (%) inhibition as shown in Fig. 4.45 and IC50 values (µg/mL) shown in Table 9. In a parallel examination of plant extracts, the antioxidant activity of gallic acid as a standard compound was also measured and compared to the values of plant extracts.

100

40 (%) 20

0 Gallic Leaves Stem Fruit Flower Root DPPH DPPH scavenging radical activity acid Plant parts

Fig. 4.45. DPPH antioxidant activity of Martynia annua parts

Leaves and flowers have greater antioxidant activity with lower IC50 values (95 µg/mL) and (114 µg/mL) respectively, this might be due to higher TPC and TFC and versatility of phenolic compounds found in these parts (Muazzam and Farman, 2018).

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4.8.1.1.DPPH Antioxidant Activity of Leaves Fractions Methanolic extract of leaves was further fractioned into three different fractions on the basis of solvent polarity i.e., ethylacetate, butanol and n-hexane fractions and six TLC fractions on the basis of their colors appeared under UV lamp (254 & 365 nm). These fractions were monitored to check their antioxidant activity with reference compound gallic acid. The %age inhibition of these fractions is placed against different concentrations as shown in Fig. 4.46.

120

100 a 80 Gallic acid 60 EtOAc

40 BuOH %ageInhibition 20 nHx

0 50 100 200 400 Concentration (ug/mL)

120

100 b Gallic acid 80 F1 60 F2 F3 40 %ageInhibition F4 20 F5 0 F6 50 100 200 400 Concentration (ug/mL)

Fig. 4.46. DPPH antioxidant activity of leaves a) solvent and b) TLC fractions

The results showed that antioxidant activity retained in phenolic rich fractions. Ethylacetate and butanol phenolic rich fractions have comparable antioxidant activity as crude leaves extract. Among TLC fractions, fractions F1, F2, F3 and F6 have greater antioxidant

CHAPTER 4 potential as compared to rest which indicates higher phenolic content in these fractions as shown in Table 11.

4.8.2. ABTS Antioxidant Activity Antioxidant activity of different plant parts are monitored by ABTS assay. The ABTS assay has the advantage in that it can be worked at various pH levels. It is soluble in organic and aqueous solvents and therefore useful in measurements of antioxidant potential of extracts in various media (Ou et al., 2002). This method was dependent on the ability of samples to scavenge ABTS•+ radical cation. ABTS radical cation was produced by reaction of ABTS molecule with strong oxidizing agent potassium persulfate. Oxidation of 1 electron converted the colorless (ABTS) compound into blue-green radical (ABTS•+) (Miller and Rice-Evans, 1997) as depicted in Fig. 4.47.

Fig. 4.47. Reduction of ABTS to ABTS•+ radical cation

The antioxidant capacity of all plant parts were presented in terms of percentage inhibition as shown in Fig. 4.48 and IC50 values (μg/ml) shown in Table 9. The values of standard compound Trolox were measured and compared to the values of antioxidant activity of plant extracts.

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100

(%) 40

0 ABTS ABTS radicalscavenging activity Trolox Leaves Stem Fruit Flower Root Plant parts

Fig. 4.48. ABTS antioxidant activity of Martynia annua parts

Extracts from different parts of Martynia annua revealed strong to good antioxidant potential. Leaves and flowers extracts showed higher percentage inhibition values as compared to standard compound. Flowers extract revealed excellent antioxidant capacity (IC50 142 µg/mL) after leaves extract. These findings have not been documented previously that support the dissension that extracts from leaves and flowers have higher phenolic and flavonoid contents comparable to other parts (Muazzam and Farman, 2018).

4.8.2.1. ABTS Antioxidant Activity of Leaves Fractions The percentage inhibition of solvent and TLC fractions of crude leaves extract were plotted against four different concentrations with reference compound Trolox. The graphical trends are shown in Fig. 4.49 and their IC50 values are placed in Table 11. In solvent fractions, ethylacetate and butanol fraction showed higher antioxidant capacity as compared to n-hexane fraction. These fractions are also comparable to reference compound Trolox. Among TLC fractions, F1, F2, F3 and F6 fractions exhibit greater antioxidant potential and indicated these fractions have more phenolic content.

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100 90 80 70 60 Trolox 50 EtOAc 40 BuOH

%ageInhibition 30 20 nHx 10 0 50 100 200 400 Concentration (ug/mL)

100 90 80 Trolox 70 60 F1 50 F2 40 F3

%ageInhibition 30 F4 20 10 F5 0 F6 50 100 200 400 Concentration (ug/mL)

Fig. 4.49. ABTS antioxidant activity of leaves a) solvent fractions b) TLC fractions

4.8.3. FRAP Reducing Power Method The free radical scavenging activity of plant extracts was also measured by FRAP reducing antioxidant power assay. FRAP method determine the reducing potential of an antioxidant compound that reacts with ferric tripyridyltriazine [Fe3+-TPTZ] complex and a colored ferrous tripyridyltriazine [Fe2+-TPTZ] was formed (Benzie and Strain, 1996) that can be monitored at 593 nm as shown in Fig. 4.50.

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Fig. 4.50. Reduction of Ferric tripyridyltriazine [Fe3+-TPTZ] complex to ferrous tripyridyltriazine [Fe2+-TPTZ]

Generally, the reducing properties are integrated with the presence of molecules which execute their mechanism by transferring a hydrogen atom to break the free radical chain (Duh et al., 1999). In a redox-linked colorimetric process, the FRAP method treats the antioxidants in the plant extracts as a reductant (Guo et al., 2003). In this study, the absorbance of Martynia annua increased, due to the production of the (Fe2+-TPTZ) complex. The FRAP values of different plant extracts were exhibited in µM Fe2+ /g compared to reference compound as shown in Fig. 4.51.

700

600

500

400

300

200

100

FRAP FRAP antioxidant activity Fe uM/g 0 Trolox Leaves Stem Fruit Flower Root Plant parts

Fig. 4.51. FRAP antioxidant activity of Martynia annua part

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The leaves and flowers extracts exhibited good FRAP reducing values i.e., leaves (404 µM Fe2+/g) and flowers (368 µM Fe2+/g) respectively as compared to Trolox (580 µM Fe2+/g) as shown in Table 9 (Muazzam and Farman, 2018).

4.8.3.1. FRAP Antioxidant Activity of Leaves Fractions The µM Fe2+/g concentration of solvent and TLC fractions in comparison with standard compound Trolox are shown in Fig. 4.52.

700 600 500 400

300 uM/g 200 100

FRAP FRAP antioxidant activity Fe 0 Trolox EtOAc BuOH nH Leaves Solvent Fractions

700 600 500 400

uM/g 300 200 100

FRAP FRAP antioxidant activity Fe 0 Trolox F1 F2 F3 F4 F5 F6 Leaves TLC Fractions

Fig. 4.52. FRAP antioxidant activity of leaves a) solvent and b) TLC fractions

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Same results were obtained with FRAP reducing assays. Martynia annua leaves have strong antioxidant potential and these activities also retained in its solvent and TLC phenolic fractions as depicted in Table 11.

Table 9. TPC, TFC and antioxidant activities of different parts of Martynia annua Martynia TPC TFC DPPH ABTS FRAP 2+ annua (µg/mL GAE) (µg/mL RE) (IC50 µg/mL) (IC50 µg/mL) (µM Fe /g) Leaves 226.84 152.02 95.97 116.9 404 Stem 56.79 21.78 308.5 217.7 284 Fruit 57.67 51.58 207.8 204.9 309 Flower 149.31 122.22 114.5 142.7 368 Root 72.65 70.35 166.7 158.7 332

Table 10. ANOVA mean squares values of plant parts by DPPH, ABTS and FRAP antioxidant methods

SOV DF Leaves Stem Fruit Flower Root Treatment 2 100364** 50880.3** 60281.9** 80841.7** 66273.1** Error 6 0.4688 1.1 0.5 0.1 0.3 Total 8 * = P < 0.05, ** = P < 0.01

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Table 11. Antioxidant activities of fractions of crude extract of Martynia annua leaves

Fractionation of DPPH IC50 ABTS IC50 FRAP crude leave extracts (µg/mL) (µg/mL) (µM Fe2+/g) Solvent fractions EtOAc 93.49 104.7 424 BuOH 92.22 108.8 402 nHx 215.7 266.7 238 TLC fractions F1 88.11 105.0 407 F2 80.79 120.4 398 F3 80.79 104.1 419 F4 127.6 148.7 304 F5 124.1 255.9 317 F6 68.79 108.8 406

Antioxidant activities of phenolic rich fractions of leaves extract were considerably higher as compared to their crude extract that indicates these fractions abstract more phenolic compounds.

As an estimated, the radical scavenging values (IC50 µg/mL) of all fractions was calculated and compared to that of whole crude extract. The fractions, when they were present together in the same extract, had weak antioxidant effect as compared to their individual effects.

Martynia annua showed strong antioxidant potential and this ability can be associated to different types of identified compounds (flavonoids and phenolic acids) in this species. Phenolics are observed as strong antioxidant (in vitro) and study revealed that they are more powerful than carotenoids and vitamin C and E (Rice-Evans et al., 1995; 1996). Antioxidant activities of phenolic constituents can be moderated by different processes, i.e., i) production of RNS/ROS can be by conquered by inhibiting enzymes ii) scavenging free radical substances like RNS/ROS iii) and preventing antioxidant defense mechanisms (Cotelle, 2001).

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Flavonoids have perfect structure activity chemistry for scavenging free radicals. Some structural characteristics and substituents nature on B and C ring promote the antioxidant activity of flavonoids as follows; 1) The hydroxylation level and position of –OH group in ring B, particularly a catechol like structure (an ortho-dihydroxy pattern on ring B), exhibit higher antioxidant activity, because it showed higher stability to the aroxyl radical by delocalization of electrons (Van acker et al., 1996) and also function as an ideal binding site for trace metals substances (Pietta, 2000). 2) Radical scavenging ability of flavonoids can be enhanced by conjugated C-2 and C3 double bond with 4-oxo group in C ring (Pietta, 2000). 3) The presence of 3´,4´ and 5´- sites of B ring (a pyrogallol structure) has been documented to increase the antioxidant activity of flavonoids as compared to single hydroxyl group (Van acker et al., 1996). It has been reported that, the conversion of 3´,4´ dihydroxyphenyl enhances the anthocyanidins antioxidant activity but for catechins it decreases (Seeram and Nair 2002). 4) Double bond at positions C-2 and C-3 incorporate with 3-OH group in C ring enhances the antioxidant ability of flavonoids e.g., in kaempferol (Van acker et al., 1996). Substituent on 3- hydroxyl resulted an increase in torsion strain (loss of coplanarity) and ultimately decreases antioxidant potential (Seeram and Nair 2002). 5) In ring B, replacement of OH- groups with methoxyl affects redox potential and alters the free radical scavenging activity of flavonoids (Pietta, 2000; Seeram and Nair, 2002). 4.9.Cytotoxicity Cancer is considered as a major cause of death now-a-days and cancer-related research is conducted worldwide. As estimation, the number of new cancer cases has reached 10 million in year 2000 and will reach 24 million new cases in year 2050 approximately. Similarly, the number of deaths have increased from 6 million (2000) to 10 million (2020) and to over 16 million in (2050). A total of 17 million new cancer cases will be in poor developed countries and only about 7 million new cases will be diagnosed in more developed countries (Schwartsmann et al., 2002). Cervical cancer (derived from cervix of women) is a more common cancer after breast and oral in women of Pakistan. A prediction of WHO (World Health Organization), around half

CHAPTER 4 a million women will die of cervical cancer in year 2030 and from these, over 98% deaths are expected to occur in developing countries like Pakistan. LN-18, human glioblastoma an apoptotic inducible cell line derived from human glioma (the name arises from human glial cells). A type of tumor, glioma is derived from brain or Spine (Mamelak and Jacoby, 2007). Cancer related studies often analyze the effects of bioactive substances on cancer cell lines, most of these substances are secondary metabolites and originate from plants. As per WHO calculation (WHO, 2003), about 80% of world’s inhabitants problem should treated for health care by herbal medicinal drugs. Plant derived constituents (Natural Products predominantly) have long been sources of drugs and used in pharmaceuticals, flavor and fragrance, textiles, agrochemicals and as food additives. In the process of drug development, natural products are of great interest due to their large diversity, and permit the identification of interesting molecules for the development of new therapeutic agents. Therefore, it’s a need to examine reliable and immeasurable sources of natural stuff (Newman et al., 2003). 4.9.1. Cell Morphology Two types of cancer lines were selected in this study, i.e., HeLa (Human Cervical Carcinoma cancer cell line) and LN18 (Human Glioblastoma cell line). HeLa is an immortal cancer cells taken from “Henrietta Lacks” (who donate her cells in 1951 after her death). To save Lack’s obscurity, these cell lines were named after “Helen Lane” (Sharrer, 2006). LN18, an apoptotic inducible cell line derived from human glioma (the name arises from human glial cells). Glioma is a type of tumor derived from brain or Spine (Mamelak and Jacoby, 2007). Human kidney cells 293T were used as a normal cell line. The cells morphology is shown in Fig. 4.53.

(a) (b) (c)

Fig. 4.53. Cell morphology of a) HeLa b) LN18 & c) 293T

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4.9.2. Cell Proliferation (MTT) Assay Tetrazolium reduction assays are most widely used assays to evaluate the viable cells. Commonly used tetrazolium compounds includes; MTS, MTT, WST-1 and XTT. In this study, MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) method was used to measure cytotoxic activity. Mitochondrial dehydrogenase enzyme of living cells reduces the MTT molecule into formazan crystal (purple in color). MTT is a widely-used test to evaluate the in vitro cytotoxic potential of medicinal plants by measuring the mitochondrial succinate dehydrogenase enzyme activity for the evaluation of metabolic activity of cultured cells. Reduction of MTT (i.e., change of color from yellow to purple) have been observed in both extract treated cell lines (Berridge and Tan, 1993) as shown in Fig. 4.54.

Fig. 4.54. Reduction of MTT into Formazan

The cellular mechanism of MTT reduction is not clearly described. It can assume that the reaction between NADH (Dihydro Nichotinamide Adenine Dinucleotide) or same reducing molecules that can act as electron donor to MTT compound (Berridge and Tan, 1993; Berridge et al., 1996; Marshall et al., 1995). MTT is a specialized test used for both i.e. quantification of cell viability as well as cell cultures in 96-well plates. In the present in vitro study, the test is used to assess the cytotoxic effects of different plant parts and leaves fractions of Martynia annua. Therefore, two cancer cells lines HeLa, LN18 and 293T normal cells were exposed to increasing concentrations of extracts/fractions (50-400 µg/mL) for 24 h incubation.

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4.9.3. Cytotoxic Activity of Crude Extracts of Martynia annua

The results of cytotoxicity are shown in %age of cell viability and IC50 values. The trend of % age cell viability versus extracts concentration (50-400 µg/mL) against HeLa and LN18 are shown in Fig. 4.55 and their IC50 values are presented in Table 12. It is clear from the results that cell viability decreases by increasing concentration of extracts. The graphical trend showed that the cytotoxic effect is higher at higher extract concentration i.e., % age of cell viability in leaves extract is observed only 37.60 % at maximum concentration with the IC50 value 81 µg/mL against HeLa and found 117 µg/mL against LN18 cell lines.

90 a 80 70 60 Leaves 50 Stem 40 30 Fruit

%age Cell %ageCell Viability 20 Flower 10 Root 0 50 100 200 400 Concentration (ug/mL)

80 b 70 60 50 Leaves 40 Stem 30 Fruit

%age Cell %ageCell Viability 20 Flower 10 Root 0 50 100 200 400 Concentration (ug/mL)

Fig. 4.55. Percentage cell viability of Martynia annua parts versus extract concentration against HeLa (a) and LN18 (b) cell lines

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The cell inhibition also observed in other parts of the plant. A lower %age of cell viability is also observed in flower and root at maximum concentration i.e., 400 µg/mL. The flower killed 60% and 56% cell with IC50 values 95.31 and 155.9 µg/mL. Root exhibit IC50 values 175.6 and 184.4 µg/mL against HeLa and LN18 respectively. Stem is more active towards LN18 (305 µg/mL) than HeLa (315 µg/mL).

2 Table 12. IC50 & R values of Martynia annua parts against HeLa, LN18 & 293T

2 Martynia annua IC50 (µg/mL) R values HeLa LN-18 293T HeLa LN18 Leaves 45.65 117.7 >400 0.77 0.88 Stem 315.8 307.1 >400 0.94 0.92 Fruit 292.9 391.5 >400 0.91 0.93 Flower 95.31 155.9 >400 0.97 0.83 Root 175.6 184.4 >400 0.91 0.96

Table 13. IC50 values of reference compounds Compound HeLa LN18

(IC50 µg/mL) (IC50 µg/mL) Fluorouracil 152 120 Gallic acid 25 35 Apigenin 48 65 Luteolin 75 86 Diosmetin 85 90

The cell reduction was also compared with standard compounds i.e., flouracil, apigenin, gallic acid, luteolin and diosmetin as presented in Table 13. The results indicate strong cytotoxic effect of leaves and flowers extract on HeLa cell line as compared to LN18. The root extract exhibit approximately the same 50% growth inhibition values on both cell lines. All parts showed cell reduction in a dose response method under 24h of subjection towards both cancer cells but inactive towards normal cells. Reduction of cell viability was not observed with control

CHAPTER 4 containing 100 µL media, however in case of DMSO 0.05% (v/v) as control group only a small reduction i.e., 2-6% cell reduction was observed. The IC50 values differed among different parts of the plant towards both cell lines as shown in Fig. 4.56.

450

400

350

300

250 Hela 200 LN18 150

100

Inhibitory Concentration IC50 (ug/mL) IC50 Concentration Inhibitory 50

0 Leaves Stem Fruit Flower Root Plant Parts Fig. 4.56. 50% Inhibitory Concentration of HeLa and LN18 in different parts of Martynia annua

The high cytotoxic activity was observed with leaves and flowers. These results demonstrated good anticancer potential of this species which may be due to phenolic constituents specifically flavonoids as confirmed by LC-MS analysis of this plant.

4.9.4. Cytotoxic Activity of Leaves Fractions The methanol extract of leaves showed prominent cytotoxic activity towards HeLa and LN-18 cancer cells. So, crude extract of leaves were aimed to fractionating into three different solvents i.e., ethyl acetate, n-butanol, and n-hexane on the basis of polarity difference to extract polyphenolic rich fraction. This process separated the phenolic constituents in the plant extracts based on their polarity difference so the fractions with greater cytotoxicity could be measured. The %age of cell viability of these fractions at different concentration (50-400 µg/mL) against HeLa and LN-18 cells are presented in Fig. 4.57. .

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100

60 EtOAc 40 BuOH

%age cell viability 20 nH 0 50 100 200 400 Concentration (ug/mL)

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60 EtOAc 40 BuOH

%age cell viability 20 nH 0 50 100 200 400 Concentration (ug/mL)

Fig. 4.57. Percentage cell viability of Martynia annua leaves fractions against a) HeLa and b) LN18

A higher cytotoxicity of ethyl acetate fraction was observed at 400 µg/mL. It may be indicated that this solvent extracts more polyphenolic compounds. A decreased in cell viability is also observed with n-butanol fraction, but n-hexane did not show prominent activity against both cell lines. Different phytochemical classes e.g., phenolic, flavonoids, coumarin, steroids, saponins show different colours when exposed to UV light. Leaves were further fractionation into six fractions and assessed for cytotoxic activity on same cell lines at four different concentrations. The shape of the curve shows decrease in cell viability against two cell lines as shown in Fig. 4.58. These fractions show cell reduction which gives the impression of cytotoxic compounds present in these fractions.

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80 70 60 F1 50 F2 40 F3 30

20 F4 %age cell viability 10 F5 0 F6 50 100 200 400 Concentration (ug/mL)

80 70

60 F1 50 F2 40 F3 30 F4

%age cell viability 20 10 F5 0 F6 50 100 200 400 Concentration (ug/mL)

Fig. 4.58. Percentage cell viability of Martynia annua Leaves fractions against a) HeLa b) LN18

The results showed cytotoxic activity retained in leaves fractions. Fractions F1, F2, F3 exhibit higher cytotoxic activity at concentration 400 µg/mL i.e., F1, F2, F3 and F6 decrease the cell viability to 31.78 %, 46.77 %, 30.43 % and 34.78 % on HeLa cell line respectively. The same fractions (F1, F2, F3 and F6) also effective on LN18 with the reduction of cell viability to 42.98 %, 49.33 %, 42.49 % and 41.67 % respectively. Fractions F4 and F5 indicated lower cell reduction even at maximum concentration with higher IC50 values (> 400) in both cell lines. 2 Table 14 shows the IC50 and Correlation coefficient (R ) values of each leaves fraction.

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2 Table 14. IC50 & R values of Martynia annua crude leaves fractions against HeLa & LN18

2 TLC fractions IC50 (µg/mL) R values of crude leaves HeLa LN18 HeLa LN18 extract F1 60.9 123.2 0.87 0.83 F2 241.3 318.5 0.94 0.92 F3 63.6 183.2 0.81 0.97 F4 >400 360.9 0.78 0.97 F5 >400 >400 0.94 0.98 F6 100.4 150.9 0.99 0.86 Solvent fractions EtOAc 53.58 133.4 0.85 0.91 BuOH 114.3 156.6 0.95 0.89 nHx >400 >400 0.98 0.97

Furthermore, as an estimated the cytotoxic activity (IC50 µg/mL) of all TLC fractions of leaves was calculated and compared to the whole extract. The fractions, when they were present together in the crude extract, had strong cytotoxic effect on both HeLa and LN18 cell lines as compared to the effect expected from a simple addition of the individual effects of the fractions, accordingly, a synergistic cytotoxic effect between the fractions was presumed. Ethnopharmacological research is helpful to lead the search for plants with potential cytotoxic activity. The screening of plant derived natural products for their anticancer activity is helpful in the identification of putative compounds with structure novelty or mechanism of action. The result of this work indicates Martynia annua is considered to be inestimable source of effective cytotoxic compounds. The leaves and flower extracts showed significant cytotoxic potential against HeLa and LN18 cell lines and considered to be highly rich in anticancer compounds. Leaves has previously been reported to have fatty acids, apigenin, luteolin, apigenin-7-O-glucuronide (Lodhi and Singhai, 2013) which may be responsible for higher antiproliferatve activity of leaves against both cell lines. Flowers have also been shown to promising cytotoxic activity after leaves and suggest that higher cytotoxicity in these extracts

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CHAPTER 4 may be correlated to high concentration of potent unique cytotoxic compounds. Previous studies demonstrated the general bioactivity of Martynia annua but not the cytotoxic activity. Flavonoids have greater potential for arbitrating the protective effect of diet rich in vegetables & fruits against colorectal cancer (Ghasemzadeh et al., 2012). Several studies attributed the reduction of cancer cells in the consumption of foods containing phenolic acids and flavonoids (Ferguson et al., 2004). It has been indicated that flavonoid may suppress breast cancer cells (Pouget et al., 2001) and human colon carcinoma cell proliferation (Park et al., 2008). Anticancer activities of flavonoids inhibits cell growth, inhibits protein kinase activities, and apoptosis induction (Kuntz et al., 1999; Yin et al., 1999). The interaction between flavonoids and reduced cancer are in agreement with this finding since the phytochemical/LC-MS screening of this plant exhibit the presence of flavonoids that might be responsible for cytotoxic activity of Martynia annua.

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CONCLUSIONS Martynia annua L. is native plant and it is commonly consumed for its reported medicinal qualities. Pharmacological studies have shown extracts to have anti-septic, anti- inflammatory and anti-epileptic properties in vitro, however the biochemical composition and active compounds responsible for purported health benefits, remained hitherto unknown. A validated method of LC-MS/MS analysis was performed on various extracts using targeted and untargeted metabolic profiling. Volatile compounds were investigated through GC- MS analysis and evaluation of antioxidant and anticancer properties by using different methods was effected. Three separate extraction protocols were conducted to determine optimal metabolite extraction method for each of the plant parts i.e., Homogenization, maceration, and ultrasonication. PCA analysis showed that the homogenization method was the most reproducible one. On average, the maceration method provided higher ion abundances. Given the greater reproducibility, the homogenization method along with slightly higher extraction efficiency (on average). This approach was used as standard to conduct all the plant extracts reported in the rest of the project. Seven thousand six hundred and ninety seven (7697) unique ion features were measured across all plant extracts employing untargeted approach. Plant flowers’ extracts gave the greatest number of different metabolites i.e., (5121) and those from the stem extracts, the least (4403). Majority of the identified compounds were in common across all plant parts. Targeted analysis was performed to identify and quantify selected polyphenolic compounds and determine how they are distributed across the plant. Eighty nine metabolites were identified from Martynia annua plant extracts (consisting of level-1 and level-2 endeavor) and their relative and absolute abundances were measured in all five separate parts of the plant. Sixteen of the compounds were identified/characterized and quantified positively with authentic standards with < 5 ppm mass accuracy, < 0.1 min retention time, isotope-pattern matching and MS fragmentation matching. The identity and structural confirmation of 18 conjugated metabolites was sorted out by comparison with accurate mass measurements, isotope profile matching and detailed published MS fragmentation data without engaging authentic standards. An additional 55 compounds were identified with human metabolome database (HMDB) matching. Syringic acid, trans-ferulic acid, apigenin, hispidulin and isorhamnetin were the most

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abundant identified compounds that have been shown to have bioactive and bio-therapeutic properties. GC-MS exploration involved the task of initial structural deduction on the basis of molecular mass, molecular formula, retention time and peak area. GC-MS analysis unveiled the presence of seventy three volatile constituents that could contribute the medicinal quality of the plant. The separated compounds belonged to hydrocarbon, ester, alcohol, aldehyde, ketone, aromatic, carboxylic acid, alkaloid, terpene, steroid and carbohydrate classes. Antioxidant activity was evaluated using DPPH, ABTS and FRAP antioxidant protocols while TPC, TFC were also calculated. Flowers and leaves extracts have higher TPC and TFC and exhibited significant antioxidant activity. Methanolic extracts of all parts of plant i.e., (leaf, stem, fruits, flower and roots) and sub- fractions of leaves extract were assessed for antiproliferative activity against HeLa and LN18 cancer cell lines by MTT assay. Among all parts leaves and flower demonstrated significant antiproliferative activity with lower IC50 values, thus suggesting higher concentrations of cytotoxic compounds in these parts. Reduction in cell viability in sub-fractions of leaves revealed that cytotoxic activity was retained in these fractions. This is the first comprehensive report on the identification of polyphenols from Martynia annua which, we hope, will contribute to a better understanding of the relationship between polyphenol composition and its biological activity in the context of medicinal uses.

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Appendix A: Data Processing

Data processing includes import data, feature or peak detection, sample normalization, sample scaling and sample transformation. Peak matching involves aligning of chromatographic characteristics between biological/technical replicates of a sample in comparison of a reference sample QC (Quality Control). The objectives of detecting features and peak resolution is to distinguish a real chemical compounds from false positive (background noise).

Figure A1: (a) vector editing, (b) transition, (c) ion intensity map and (d) total ion chromatogram. An alignment vector is a representation of the difference in retention time between an ion in one of the LC-MS runs and the equivalent ion in the alignment reference run. The alignment vectors are displayed in the form of Vector Editing as a vertical line or more correctly, the retention time of the ion in the selected run to the position of the equivalent ion in the alignment reference, which is a quality control sample in this study. The data is aligned with the help of reference sample and it was chosen automatically by the software. The transition window continuously fading between the two i.e., current and reference runs, and shows the same area of the runs as appear in the vector editing window. Before runs are aligned, the ions will appear to move back and forwards in the retention time direction; once correctly aligned, the ions will appear stationary, but may pulse due to intensity differences between the current run and the

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reference run. The ion intensity map showing here is the entire current run. The green area defines the quality of alignment of current run as reflected in the other 3 windows. The total ion chromatogram for the current run shown in green, overlaid with the reference run chromatogram in magenta (reference sample). The retention time range displayed matches that shown in the Vector editing and Transition windows; therefore the chromatogram is also aligned. Ion Map: An ion intensity map or (Ion Map) shown in Figure A2 is the representative of the sample's MS signal by m/z and RT, i.e., a 2D representation of the ions in an LC-MS run. In an ion map m/z increases from left to right while retention time increases from top to bottom. The darkest area in a map shows higher intensities of ions in the MS signal.

FigureA2. Ion Map

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Appendix B: Mass Spectra TIC and MS/MS Spectra of Compounds 1-16

Compound 1: (Protocatechuic acid)

Figure B1: Mass spectrum, TIC and MS/MS of compound 1

Compound 2 (Gentisic acid)

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Figure B2: Mass spectrum, TIC and MS/MS of compound 2

Compound 3 (Caffeic acid)

Figure B3: Mass spectrum, TIC and MS/MS of compound 3

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Compound 4 (Syringic acid)

Figure B4: Mass spectrum, TIC and MS/MS of compound 4

Compound 5 (Rutin)

Figure B5: Mass spectrum, TIC and MS/MS of compound 5

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Compound 6 (Homovanilic acid)

Figure B6: Mass spectrum, TIC and MS/MS of compound 6

Compound 7 (p-Coumaric acid)

Figure B7: Mass spectrum, TIC and MS/MS of compound 7

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Compound 8 (Sinapic acid)

Figure B8: Mass spectrum, TIC and MS/MS of compound 8

Compound 9 (trans-Ferulic acid)

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Figure B9: Mass spectrum, TIC and MS/MS of compound 9

Compound 10 (Salicylic acid)

Figure B10: Mass spectrum, TIC and MS/MS of compound 10

Compound 11 (Luteolin)

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Figure B11: Mass spectrum, TIC and MS/MS of compound 11

Compound 12(Apigenin)

Figure B12: Mass spectrum, TIC and MS/MS of compound 12

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Compound 13 (Kaempferol)

Figure B13: Mass spectrum, TIC and MS/MS of compound 13

Compound 14 (Hispidulin)

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Figure B14: Mass spectrum, TIC and MS/MS of compound 14

Compound 15 (Hesperetin)

Figure B15: Mass spectrum, TIC and MS/MS of compound 15

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Compound 16 (Isorhamnetin)

Figure B16: Mass spectrum, TIC and MS/MS of compound 16

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