Construction of neurotoxin database and screening for potential therapeutic agents

CONSTRUCTION OF NEUROTOXIN DATABASE AND SCREENING FOR POTENTIAL THERAPUETIC AGENTS BY JOYCE SIEW PHUI YEE A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF SCIENCE DEPARTMENT OF BIOCHEMISTRY NATIONAL UNIVERSITY OF SINGAPORE 2004 i In loving memory To my father, Mr. Siew Yew Chuan i Acknowledgements I would like to express my sincere thanks to my supervisor, Professor Kandiah Jeyaseelan for his dedicated supervision, constant encouragement and continued support during the course of this project. I am also grateful for the assistance of Associate Professor Vladimir Brusic from Institute of Infocomm Research for his kind help in the construction of the neurotoxin database. My sincere appreciation also goes out to Dr Arunmozhiarasi Armugam for her valuable input and advice throughout the entire course of my studies. I am grateful to the Department of Biochemistry, National University of Singapore for the outstanding academic training it had provided me during my 6 years of undergraduate and graduate studies here. A big thank you to my labmates, past and present – Ram, Charmian, Dawn, Siaw Ching, Sam and Yimin for all their wonderful friendship, support and kind assistance in every possible way. Finally, words are not enough to express my gratitude to my family, my mentor in life, Dr. Daisaku Ikeda, and Sun, who have always been supportive and understanding of my long absence from home and many late nights in the lab. Thank you from the bottom of my heart!! i Table of contents Acknowledgements i Contents ii Publications vi List of Figures vii List of Tables ix Abbreviations x Summary xi Chapter 1: Introduction Chapter 1: Introduction 1.1 General introduction 1 1.2 Snake venom components 4 1.3 Neurotoxins 5 1.3.1 Neurotransmission 6 1.3.2 Neurotoxins and envenomation 7 1.4 Classification of neurotoxins 9 1.4.1 Presynaptic neurotoxins 9 1.4.2 β-neurotoxins 9 1.4.3 Acetylcholinesterase inhibitors 11 1.4.4 Potassium channel inhibitors 12 1.5 Postsynaptic neurotoxins 13 1.5.1 Nicotinic acetylcholine receptor 13 1.5.2 α-Neurotoxins 16 ii 1.5.3 Short- and long-chain neurotoxins 17 1.5.4 Kappa neurotoxins 18 1.5.5 Weak neurotoxins 18 1.6 Application of snake venom neurotoxins in research and therapy 19 1.6.1 Viral infection 19 1.6.2 Myasthenia gravis 21 1.6.3 Alzheimer’s disease 22 1.6.4 Thrombotic disease 22 1.6.5 Research tools 22 1.6.6 Novel functional homologs 24 1.6.7 Chimeric toxins 25 1.7 Scorpion 25 1.7.1 Buthus martensi Karsch 25 1.7.2 Scorpion venom 26 1.8 Microarray 26 1.8.1 DNA microarray 28 1.8.2 Applications of DNA microarray 29 1.9 Neurogenesis 31 1.10 Database creation 32 1.10.1 Current problem with analysis of snake toxins using bioinformatic resources 35 1.11 Aims of the project 35 iii Chapter 2: Materials and Methods Section A 2.1 Bioinformatics 38 2.2 Data collection and cleaning 39 2.3 Data annotation 40 2.4 Data analysis 41 2.5 Phylogenetic study 42 2.6 Bioinformatics tools used 42 2.7 Scorpion venom and venom glands 44 2.8 Purification of scorpion venom 44 2.9 Purification of snake Bcntx-4 44 2.10 Mass spectrometry determination and N-terminal amino acid sequencing 45 2.11 Protein estimation 45 2.12 Cell culture and medium 45 2.13 MTT cell viability assay 45 2.14 Microarray 46 2.15 Total RNA cleanup 46 2.16 cDNA synthesis 47 2.16.1 Primer hybridization 47 2.16.2 Temperature adjustment 47 2.16.3 First strand synthesis 48 Section B iv 2.17 Second strand cDNA synthesis 48 2.18 Cleanup of double stranded cDNA 49 2.19 Synthesis of biotin-labeled cRNA 50 2.20 Cleaning up and quantifying in vitro transcription (IVT) products. 51 2.21 Fragmentation of cRNA for target preparation 51 2.22 Eukaryotic target hybridization 52 2.23 Probe Array washing, staining and scanning 53 2.24 Microarray data analysis 56 2.25 Isolation of total RNA 57 2.26 RNA gel electrophoresis 57 2.27 Real-time quantitative PCR 58 2.28 Purification of Torpedo californica acetylcholine receptors 59 2.29 Competitive binding assay 60 2.30 Statistical analysis 60 Section C List of chemicals used 61 Chapter 3: Construction of protein database of snake venom neurotoxins 3.1 Introduction 67 3.2 Data acquisition 67 3.3 Database features 69 3.4 Descriptions of the svNTX individual record 72 3.5 Classification of snake venom neurotoxins 75 3.6 Receptor binding studies to test the in silico prediction tool in the database 91 3.7 Conclusion 93 v Chapter 4: Therapuetic leads screening in BMK fraction II using toxicogenomic approach 4.1 Introduction 94 4.2 Purification of BMKII using reverse phase-high performance liquid chromatography 95 4.3 MTT test 96 4.4 Total RNA isolation 97 4.5 Microarray analysis 97 4.6 Quantitative Real-time PCR analysis of genes affecting neurogenesis and angiogenesis 107 4.7 Further purification of BmkII using reverse phase-high performance liquid chromatography 110 4.7.1 Effects of BMKII fractions 1 – 9 on gene expression of ten selected genes 4.7.2 Further separation of fractions RP5-7 using RP-HPLC 113 4.7.3 Effects of BmKII fraction RP5, 6 and 7 on six selected genes 116 4.7.4 Purification of the five fractions using RP-HPLC and determination of protein mass using MALDI-TOF 117 4.7.5 Effects of BmKII subfractions RP5 and 6 on six selected genes 125 4.8 N-terminal sequencing of subfractions 5, 6 and 7 127 4.9 Conclusion 128 Chapter 5: Discussion 5.1 Neurotoxin database 130 vi 5.2 Conclusion and future studies 132 5.3 Screening of scorpion venom for therapeutic peptides 133 5.3.1 Galanin 134 5.3.2 Amphiregulin 136 5.3.2.1 Application 138 5.3.3 GABA (A) receptor a-5 subunit 139 5.3.4 Sensory and motor-neuron derived factor (neuregulin) 140 5.3.5 Fibroblast growth factor 2 (FGF2) 141 5.3.6 Krit1 144 5.4 Conclusions and future studies 145 References 146 vii Summary Snake and scorpion venoms contain many toxins that have important application as therapeutic agents and also as research tools. As a first part of this study, a snake venom neurotoxin (NTX) database was constructed using bioinformatics. Snake NTXs are a large family of active peptides with considerable sequence homology, but with different biological properties. Sequence, functional and structural information on snake venom neurotoxins (svNTXs) are scattered across multiple sources such as journals, books and public databases, with very limited functional annotation. Through this study, an on-line database of NTX proteins has been made available at http://sdmc.12r.a- star.edu.sg/Templar/DB/snake_neurotoxin. This database can also be found under SwissProt Toxin Annotation Project website http://www.expasy.org/sprot. At present, 272 NTXs sequences are available in the database and each sequence contains fully annotated function and literature references. An annotation tool was also incorporated to aid functional prediction of newly identified NTXs as an additional resource for toxinologists. In addition, a classification system based on structure-function and phylogeny relationship derived from 272 NTXs has been proposed and discussed in detail in the thesis. In Traditional Chinese Medicine, the scorpion venom has been used in the treatment of neuromuscular diseases such as paralysis, epilepsy, apoplexy, hemiplegic and facial paralysis. The screening of these peptides have been carried out using proteomics. Hence, as a second part of this study, a preliminary screening for therapeutic peptides has been carries out using the gene chip microarray and real-time PCR on the Chinese scorpion venom. Several interesting peptides have been found to induce changes in expression of genes that are involved in neurogenesis in the brain, a finding that is previously unknown. viii Publications Journal article Joyce Siew Phui Yee, Gong Nanling, Fatemah Afifiyan, Ma Donghui, Poh Siew Lay, Arunmozhiarasi Armugam, Kandiah Jeyaseelan (2004) Snake postsynaptic neurotoxins: gene structure, phylogeny and applications in research and therapy. Biochimie 86, 137149. Joyce Siew Phui Yee, Asif M. Khan, Paul TJ Tan, Judice LY Koh, Seah Seng Hong, Chuay Yeng Koo, Siaw Ching Chai, Arunmozhiarasi Armugam, Vladimir Brusic and Kandiah Jeyaseelan (2004). Systematic analysis of snake neurotoxins functional classification using a data warehousing approach. Bioinformatics July 22. Conference abstract Siew Phui Yee Joyce; Asif Khan; Tan Thiam Joo Paul; Judice Koh, Arunmozhiarasi Armugam; Kandiah Jeyaseelan; and Vladimir Brusic. (2003) Systemization of snake venom neurotoxins based on structure and function. 14-19th September, Adelaide, Australia. ix List of Tables Table 1.1 Systematic classification of different species of snakes around the world. 4 Table 1.2 Some of the common components in snake venoms of different species. 5 Table 1.3 Envenomation effects of neurotoxins across three different species. 8 Table 2.1 Primers sequences used for real-time PCR. 58 Table 3.1 Summary of the 272 neurotoxin entries extracted from various sources. 68 Table 3.2 Sequence identity for the four unique toxins that are not found in public databases but available in published journals. 69 Table 3.3 Number of the complete, incomplete and missing sequences in the snake venom neurotoxins final data set. 69 Table 3.4 The distinct disulfide pairing pattern of mature svNTXs. 78 Table 3.5 Summary of the individual entries based on GenBank Accession Number of each member in each group as depicted in Fig 3.6 84 Table 4.1 Summary of the 875 genes function that was altered by treatment of BMKII in human neuroblastoma cell. 98 Table 4.2 List of the ten selected genes after microarray gene chip analysis 99 Table 4.3 Changes in gene expression level as detected by microarray and real-time P 108 Table 4.4 Relative level of gene expression of the six genes using nine subfractions from BmKII. 113 Table 4.5 Relative level of gene expression on the six genes using subfractions of fractions RP5, 6 and 7. 117 Table 4.6 Relative level of gene expression on the six genes using 10 ng/ml subfractions of fractions RP5 and 6. 125 Table 4.7 Relative level of gene expression on six genes using 50 ng/ml subfractions of fractions RP5 and 6. 126 Table 4.8 Results of the N-terminal sequencing of five fractions. 127 Table 4.9 Blast search of the five peptides. 128 x List of Figures Figure 1.1 Venom apparatus of Naja sputatrix, a Malayan spitting cobra . 3 Figure 1.2 Mechanism of acetylcholine transmission at neuromuscular junction. 7 Figure 1.3 Clinical manesfestations of a snake bite. 8 Figure 1.4 The structure of nicotinic acetylcholine receptor and its binding protein . 15 Figure 1.5 The 3D-structures of three-finger neurotoxins from snake venoms that interact with nicotinic acetylcholine receptors. 16 Figure 1.6 A model showing homology of rabies glycoprotein with the "toxic" loop of the neurotoxins. 21 Figure 1.7 Comparison of the lynx1 model and the αBgt experimental structure. 24 Figure 1.8 Anatomical structure of Buthus martensi Karsch . 30 Figure 2.1 A schematic representation of CysAlign methodology. 41 Figure 3.1 The user interface of the svNTXs database. 70 Figure 3.2 An output feature of the search (partial) using the keyword “Bungarotoxin”. 71 Figure 3.3 An example of an outlay of record available in the database. 72 Figure 3.4 Summary of the types of errors encountered in the public databases. 74 Figure 3.5 Unique disulfide pairing patterns of all the neurotoxins. 77 Figure 3.6 Classification of snake NTX based on structure, function and phylogenetic information. 81 Figure 3.7 Phylogenetic trees performed using parsimony analysis of all the mature svNTX. 90 Figure 3.8 Competitive binding studies of 125I-α-Bgt and native Bc-ntx4 to nAChR of Torpedo receptor. 91 Figure 3.9 Output of the annotation tool in svNTXs. 92 Figure 4.1 Separation of BmK crude venom using gel filtration. 95 xi Figure 4.2 Cell survival test of human neuroblastoma cells treated with various concentration of BmkII. 96 Figure 4.3 Total RNA isolation from human neuroblastoma cells treated with 35 µg/ml BmKII. 97 Figure 4.4 Cluster 1 genes identified using Genesis® software. 100 Figure 4.5 Cluster 2 genes identified using Genesis® software. 101 Figure 4.6 Cluster 3 genes identified using Genesis® software. 102 Figure 4.7 Cluster 4 genes identified using Genesis® software. 103 Figure 4.8 Cluster 5 genes identified using Genesis® software. 104 Figure 4.9 Cluster 6 genes identified using Genesis® software. 105 Figure 4.10 Cluster 7 genes identified using Genesis® software. 106 Figure 4.11 Schematic representation of real-time PCR with the SYBR Green I dye. 107 Figure 4.12 Gene expression profile of ten genes studies using microarray and real-time PCR. 109 Figure 4.13 RP-HPLC of BmKII from scorpion venom. 111 Figure 4.14 Real-time PCR analysis using fractions RP1-9. 112 Figure 4.15 RP-HPLC of fraction RP5. 113 Figure 4.16 RP-HPLC of fraction RP6. 114 Figure 4.17 RP-HPLC of fraction RP7. 115 Figure 4.18 Real-time PCR assay of six genes using subfractions of fractions of RP5, 6 and 7 BmKII. 116 Figure 4.19 Fraction RP5.2 separated in Jupiter C4 µBore RP-HPLC column. 118 Figure 4.20 Fraction RP6.2 separated in Jupiter C8 µBore RP-HPLC column. 119 Figure 4.21 Fraction RP6.3 separated in Jupiter C8 µBore RP-HPLC column. 120 xii Figure 4.22 Fraction RP6.4 separated in Jupiter C4 µBore RP-HPLC column. 121 Figure 4.23 MALDI-TOF of the five fractions. 124 Figure 4.24 Real-time PCR assay of six genes using 10 ng/ml of subfractions RP5 and 6. 125 Figure 4.25 Real-time PCR assay of six genes using 50 ng/ml of subfractions RP5 and 6. 126 Figure 5.1 Galanin receptord and their transduction mechanisms. 136 Figure 5.2 The ERBB signalling network. 138 Figure 5.3 Schematic diagram of FGF-2 signalling pathways which has been shown to activate a number of intracellular routes. 143 xiii Abbreviations α-Bgt Alpha bungarotoxin AR Amphiregulin BLAST Basic local alignment search tool BmK Buthus martensi Karsch BSA Bovine serum albumin db database dNTP deoxyribonuclease ESI-MS electron spray ionization-mass spectrometry FGF2 fibroblast growth factor hr hour IC50 concentration for 50% inhibition kD kilodalton krit1 Krev interaction trapped 1 mg milligram min minute mM millimolar MW molecular weight nAChR nicotinic acetylcholine receptor nM nanomolar NTX neurotoxin PCR polymerase chain reaction xiv PLA2 phospholipase A2 RP-HPLC reverse phase-high performance liquid chromatography RT reverse transcription SMDF sensory motor derived neuron SR sacroplasmic reticulum svNTXs snake venom neurotoxins µg microgram µl microlitre xv Introduction INTRODUCTION Introduction CHAPTER ONE INTRODUCTION 1.1 General introduction The animal kingdom contains many venomous species, including the coelenterates, flatworms, annelids, echinoderms, mollusks, arthropods and chordates. These venomous animals produce a variety of toxins to defend themselves from predators, to subdue their prey and for digestion. Therefore, animal toxins have immobilizing effects and killing functions towards a wide variety of creatures. Snake venoms have attracted much medical attention since ancient civilizations and had been used in medical treatment for thousands of years. In the 12th century, doctors used snake venom to treat leprosy. Snakes belong to the order Squamata and suborder Serpentes (Ophidia) of the class Reptilia (Kochva, 1987). They appeared in the Lower Cretaceous Period about 130 million years ago, and have been considered to have evolved from lizards, Varanidae, probably 30 million years ago (Clifford, 1955). There are about 3200 species of snakes found worldwide, and 1300 of which are venomous (Hider, 1991). Venomous snakes belong to the infraorder Caenophidia under Ophidia. They are more advanced and widespread throughout the world (Phelps, 1989). Venomous snakes usually are defined as those possessing a pair of venom glands and specialized fangs connected to venom glands by ducts. The venom apparatus enables them to inflict serious bites in their victims. The venom apparatus of a snake typically consists of a venom gland, venom duct and one or more fangs located on each side of the head (Figure 1.1A). Venom is produced in paired modified salivary glands which in most venomous snakes are located superficially beneath the scales in the posterior part of the head and eyes. The gland is linked to the fang by a duct. Contraction of muscles around the gland compresses the gland, forcing the flow of venom along the duct to the fang where the size of these structures depends on the size and species of the snakes. 1 Introduction Generally, four families of venomous snakes are known: Elapidae (cobra, mamba); Hydrophiidae (sea snakes); Viperidae (true vipers and pit vipers and rattlesnakes) and Colubridae (boomslang and mangrove; Fenton, 2002). The elapids are a large group of venomous snakes, which are distributed over Africa, Asia, the Southern parts of North America, Central and South America and Australia (Phelps, 1989). There are about two hundred and twenty species of elapid snakes which are represented by sixty-two genera. Generally, the elapids possess fixed front fangs that are situated in the front of the upper jaw (Figure 1.1B). Most elapids are either terrestrial or aquatic; only two genera are arboreal, the mambas and the tree cobras, Pseudohaje (Phelps, 1989). Hydrophids or sea snakes are widely distributed throughout the equatorial and tropical regions of the Indian and Pacific oceans, from the coast of Africa and America. They are closely related to the elapids, having a similar venom and fang apparatus. Medically important genera include Enhydrina, Hydrophis, Pelamis and Laticauda. Viperids are amongst the best known and probably the most medically important venomous snakes. They are divided into two subfamilies, the viperin and crotalid. The crotalid encompasses all the pit vipers and are so called because they possess heat sensitive pits situated on each side of the head between the nostril and the eye. The heat-sensing pits enable the animals to detect a temperature change of 1 – 2°C above ambient from a distance of 1 – 2 feet. This facility is used for hunting warm-blooded preys at night. All members of the viperid family have a set of very well-developed anteriorly-placed proteroglyphous fang structure. The fangs are on a modified maxilla which is capable of considerable rotation thus allowing the fangs to be folded against the roof of the mouth when not in use. This has enabled the development of larger fangs than in other venomous snakes of equivalent size. The crotalids are typically New World snakes found in America and parts of Southeast Asia, but are absent from Australia and Europe. Medically-important genera include Crotalus, Trimeresurus, Agkistrodon, and Sistrurus. The subfamily of crotalids, viperin is found in Africa, Asia and Europe. 2 Introduction The colubrid family is the largest single snake family with over 2500 species. It is found throughout the world on all continents except Antarctica (where no snakes exist). There are some species within this family which have developed toxic salivary secretions which may enter a snake bite wound during the envenomation. However, current evidence suggests that the majority of colubrids do not produce toxic secretions. All colubrids are back-fanged (Minton, 1990). The position of the fangs limits fang length and makes it less easy for the snake to bite its victim. Nevertheless, several colubrids have extremely potent venoms and can cause serious envenomation and death in Man. The best known and most important of these are some South African colubrids. The distribution of venomous snakes in the world and their characteristics are summarized in Table 1.1. Figure 1.1: Venom apparatus of Naja sputatrix, a Malayan spitting cobra. A) Illustration showing fangs, venom duct and the main venom gland. B) Scanning electron micrograph of the fang (Gopalakrishnakone, 1990). 3 Introduction Family Species Distribution Special characterictics Elapidae Kraits, Cobra, Mambas, Coral snakes America, Asia, Africa, and Australia Small head, short and fixed fangs Viperidae Viper snakes Europe, Africa, Asia and America Large, flattened triangular head; large grooved fangs on the maxillary bone Colubridae Tree snakes In all parts of the world except Australia Similar to Viperidae, but they possess heat-snesitive pits on head Hydrophiidae Sea snakes Asia and Australia Nostrils dorsally on head; flattened tail Table 1.1: Systematic classification of different species of snakes around the world (Harris et al. 1991). 1.2 Snake venom components Snake venoms are a complex mixture of various components with wide-ranging activities. The composition is variable within a single subspecies or even an individual snake, depending on age and season. The function of the venom is to subdue the prey. It also serves as a defensive adaptation and to facilitate in the digestion of they prey (Zeller, 1977). Snake venoms are usually colorless to dark amber viscous fluids with a viscosity of 1.5 to 2.5 and specific gravity of 1.03 to 1.12 (Devi, 1968). Most of the snake venoms consist of a complex mixture of proteins and non-protein components. The non-polypeptide components are the least biologically active venom fraction. They are mainly amines, carbohydrates, nucleosides, lipids, small peptides and metal ions (Devi, 1968). The lipids, carbohydrates and nucleosides are present in low amount (1 - 2% of dry weight). Enzymatic and non-enzymatic components constitute the polypeptide protein and together they are made up over 90% of dry weight of snake venom (Hider et al., 1991). Most enzymes and toxins are very stable. It was found that dried snake venom retains lethality and some enzymatic activities even after storage for 25 – 50 years (Minton, 1990). The enzymatic components range between 13 – 150kD and more than twenty enzymes have been detected in snake venoms. Twelve of them are found in all venoms, although their levels differ markedly (Table 1.2). 4 Introduction Many of these enzymes are hydrolases such as exo- and endopeptidases and proteinases that play a role in digestion. Others include neurotoxic phospholipase A2 (PLA2) that blocks neuromuscular transmission, and hyaluronidase which facilitates the distribution of other venom components throughout the prey (Harris, 1991). In addition, proteases that are involved in blood coagulation can also be found in snake venom (Matsui et al., 2000). The non-enzymatic polypeptides (5 – 10kD) found in snake venoms include cardiotoxins (CTX, also called cytotoxins), neurotoxins, proteinase inhibitors, dendrotoxins, myotoxins and acetylcholinesterase inhibitors (Hider, 1991). Snakes All snakes Enzymes L- Amino acid oxidase, phosphodiesterase, 5'-nucleotidase, phosphomonoesterase, deoxyribonuclease, hyaluronidase, NAD-nucleosidase, peptidase and phospholipase A2,ribonuclease, adenosine triphosphatase, Crotalids and viperids Endopeptidase, arginine ester hydrolase, kininogenase, thrombin-like enzyme, factor X- activator, prothrombin activator Elapids Acetylcholinesterase, phospholipase B amnd glycerophosphatase Some snakes Glutamic-pyruvic transaminase, catalase, amylase and B-glucosaminidase Table 1.2: Some of the common components in snake venoms of different species. 1.3 Neurotoxins The first amino acid sequence of a neurotoxin, Tx α from Naja nigricollis was reported in 1967 (Eaker and Porath, 1967). Since then, a large number of neurotoxins have been isolated and characterized. Reports on the amino acid sequences of a number of homologous neurotoxins from snakes such as cobras, kraits, mambas and sea snakes have been added to this growing list of neurotoxins. At present, more than 100 neurotoxin amino acid sequences are known and they form one of the largest families of protein with known primary structures (Endo and Tamiya, 1991). 5 Introduction Neurotoxins are capable of blocking nerve transmission by binding specifically to nicotinic acetylcholine receptor (nAChR) located on the postsynaptic membranes of skeletal muscles and neurons resulting in prevention of neuromuscular transmission leading to death by asphyxiation (Tu, 1973). 1.3.1 Neurotransmission Neurotransmission takes place between neuron and neuron as well as between nerve and muscle cells. When a normal nerve impulse (depolarization wave) passes through the axon and reaches the end of that axon, the calcium ion concentration in axon is increased and the neurotransmitter, acetylcholine, is released from the vesicle at the end of the nerve. This neurotransmitter moves across the synaptic crevice and reaches its receptor (acetylcholine receptor, AChR) in the next neuron (as in nerve-nerve synapse) or in muscle (as in nervemuscle synapse; Figure 1.2). The neuronal AChR is composed of five subunits, α2β3. When two molecules of acetylcholine attach to the two α-subunits, the AChR changes its configuration and becomes an open ion channel, permitting certain ions to pass through so that the cell’s plasma membrane gets depolarized relatively rapidly, yet transiently, from its resting value (-50 mV to –100 mV) to a potential more positive than 0 mV. The depolarization wave reaches the next neuron and can be transmitted to muscle similarly. The depolarization wave transmitted to muscle is further propagated through the muscle plasma membranes, T-tubules and sarcoplasmic reticulum (SR). The SR has a very high concentration of calcium ions. When the depolarization wave reaches the SR, the calcium ions begin to leak out of SR and into the myoplasm, causing the myofilaments to contract. As soon as the muscle is relaxed, the calcium ions move back into the SR. 6 Introduction Figure 1.2: Mechanism of acetylcholine transmission at neuromuscular junction. Acetylcholine is formed by choline and acetylcholine-CoA by choline acetyltransferase in the cytosol and stored in synaptic vesicle. The arrival of action potential at the terminus of presynaptic membrane causes release of acetylcholine which leads to resulting influx of Na+ into the postsynaptic membrane. After release from synaptic cleft, acetylcholine will be degraded by acetylcholinesterase into choline and acetate. Image obtained from Changeux (1993). 1.3.2 Neurotoxins and envenomation Snake envenomation is a major clinical problem worldwide, particularly in parts of the Asian region where the annual mortality is estimated to be 100, 000 (Ingels, 2001). Neurotoxins have been found most frequently in venoms of snakes of the family Elapidae and their closest relatives, Hydrophiidae. Only a few neurotoxins have been identified in venoms of vipers (Viperidae). The clinical manifestations of snakebite depend on two important factors: the intrinsic toxicity of the venom on man and the amount injected. A general observation of neurotoxic snake envenomation is the development of cranial nerve palsies which is characterized by ptosis, blurred vision, difficulty in swallowing, slurred speech, weakness of facial muscle and occasionally loss of the sense of taste and smell (Figure 1.3). This syndrome is often accompanied by drowsiness, sometimes with mental confusion and euphoria. The onset of this observation may be as soon as three minutes after a bite or as late as 24 hours. 7 Introduction Both groups of pre- and postsynaptic apparently involved in most of the clinical manifestations. Evidence suggests that presynaptic neurotoxins are associated with delayed onset, prolonged symptoms and poor response to antivenoms, whereas the postsynaptic toxins account for the early paralytic symptoms such as ptosis (Minton, 1990). A brief summary of neurotoxin envenoming in Elapidae, Hydrophiidae and Viperinae families of snake is presented in Table 1.3. Elapidae Hydrophiidae Viperinae √ √ Renal failure √ √ √ √ √ √ Hypovolemic shock x x √ √ √ √ √ √ √ Cranial nerve palsies Local pain and swelling Local necrosis Respiratory paralysis Rhabdomyonecrosis x √ √ √ Table 1.3: Envenomation effects of neurotoxins across three different species. Data adapted from Minton, (1990). √ and x indicate the presence and absence of the observed clinical conditions in human respectively. B A Figure 1.3: Clinical manisfestations of a snake bite. A. Ptosis and moderate facial weakness following the bite of an Australian tiger snake. B. Muscular weakness with the inability to raise the head seen following a cobra bite in Malaysia. This is typical of a “broken-neck” syndrome reported after bites of snake with neurotoxic venoms (Minton, 1990). 8 Introduction 1.4 Classification of neurotoxins Snake neurotoxins can be divided into two groups: presynaptic or postsynaptic neurotoxins depending on their mode of action. Presynaptic neurotoxins are either phospholipase A2 enzymes or contain these enzymes as an integral part of the neurotoxin complex and, essentially, mediate their neurotoxicity by inhibiting the release of acetylcholine (Yang, 1994). The postsynaptic neurotoxins bind to postsynaptic nAChRs at the skeletal muscle neuromuscular junction to produce blockade of neuromuscular transmission (Lee, 1972). These neurotoxins are also referred to as curaremimetic or α-neurotoxins. 1.4.1 Presynaptic neurotoxins A toxin is considered presynaptically active if it can affect transmitter synthesis, storage, release or turnover, no matter whether the toxin concerned is active in other regards or not (Harris, 1991). Two kinds of snake venom presynaptic toxins have been recognized so far: 1) β-neurotoxins characterized by a phospholipase A2 (PLA2) activity; 2) neurotoxins devoid of enzymatic activity of PLA2, acting either by blocking a voltage-sensitive K+-channel, like dendrotoxin (Hawgood and Bon, 1991) or by inhibiting the activity of acetylcholinesterase, with similar overall effect to the increase of acetylcholine, like acetylcholinesterase inhibitor (Dajas et al., 1987; Lin et al., 1987). 1.4.2 β-neurotoxins β-neurotoxins are defined as presynaptically active PLA2 toxins which have a dominant inhibitory action on the indirectly elicited twitch in in vitro neuromuscular preparations by blocking the acetylcholine release (Fletcher and Rosenberg, 1997). The first β-neurotoxins characterized is β-bungarotoxin from Bungarus multicinctus (Chang and Lee, 1963). It is now clear that many of the snake venom PLA2 from kraits, elapids, crotalids and virepids are presynaptically active (Harris, 1991; Hawgood and Bon, 1991). 9 Introduction β-neurotoxins may be single chain polypeptides as in notexin (Halpert and Eaker, 1975), multisubunit complexes as in crotoxin (A and B chains; Bouchier et al., 1991) and taipoxin (α, β, γ chains; Fohlman et al., 1977), or covalently linked assemblies of two or more subunits as in βbungarotoxin (Kondo et al., 1978), and textilotoxin consisting of five subunits (A, B, C and two D) with only two identical D subunits covalently linked (Tyler et al., 1987). The lethal activity of these proteins largely depends on the complexity of their quarternary structures. Multimeric β-neurotoxins have been found to be more potent than monomeric toxins. LD50 (median lethal dose, µg/ kg mouse) varies, from 50 in case of crotoxin, to 15 for βbungarotoxin, 2 for taipoxin and 1 for textilotoxin (Lee and Ho, 1982). In all cases, systematic intoxication resulted in respiratory paralysis due to cessation of neurotransmission. β-bungarotoxin being the first presynaptic neurotoxins to be discovered, is very well studied. The toxin is made up of two structurally different subunits linked by a disulfide bridge. Chain A (120 amino acid, MW 13.5 kDa) is a PLA2 and chain B resembles proteinase inhibitors and dendrotoxin or toxin I from Dendroaspis venoms. The overall fold in β-bungarotoxin is strikingly similar to that of the mammalian class I and class II PLA2 enzymes (Kondo et al., 1982a, b; Kwong et al., 1995). It was postulated that neuronal acceptors of β-neurotoxins existed to direct β-neurotoxins almost exclusively towards the neuronal presynaptic plasma membrane. For example, the acceptors for β-bungarotoxin have been found to consist of subunits of voltage-sensitive K+ channels (Benishin, 1990). Chain B of β-bungarotoxin, which is structurally similar to dendrotoxin, has been found to be responsible for the interaction between toxin and its receptor. This result has been further supported by the observation that βbungarotoxin can bind at high-affinity with dendrotoxin receptors. Crotoxin, another multisubunit β-neurotoxin, has been found to dissociate on reaching its target site, with the nonenzymatic subunit chaperoning the PLA2 subunit to high-affinity sites in synaptic membranes (Bon et al., 1979). It seems that all β-neurotoxins selectively decrease the fast K+ current flowing out of the nerve terminal and hence, they interact with a voltage-sensitive K+ channel, as in the case of βbungarotoxin and dendrotoxin. On the other hand, the absence of competition for their highaffinity binding on synaptosomal membranes between the various β-neurotoxins indicates that 10 Introduction the various β-neurotoxins bind to different acceptor proteins. Hence, one can conclude that various β-neurotoxins recognize various subtypes of voltage-sensitive K+ channel. Presynaptic neurotoxins induce blockage of neurotransmitter release in three phases. The initial transient inhibitory phase is followed by a facilitatory second phase and a late inhibitory phase which is irreversible. In the first two phases, the enzymatic activity of the toxins apparently plays no role, but is undoubtly needed in the third phase, in which a substantial decrease in the number of the synaptic vesicles leads to final disappearance of the amount of neurotransmitter stock in the nerve endings. A synaptic vesicle cycle is found to consist of 9 steps: docking, priming, fusion/exocytosis, endocytosis, translocation, endosome fusion, budding, neurotransmitter uptake and translocation back to the active zone at the plasma membrane in the synaptic cleft (Sudhof, 1995; Van der Kloot and Kloot, 1994). The disappearance of the neurotransmitter may be due to the interference of the last five steps of the synaptic vesicle recycling. Clues related to the neurotoxicity of β-neurotoxins have been available, even though further studies are still required. First, the enzymatic activity is known to be required for the expression of neurotoxicity, as shown in the third phase of β-neurotoxin intoxication cascade. In addition, residues 59-89 (which encompasses the β-structure) seemed to be important for neurotoxicity as drawn from studies on structural comparison of notexin from Notechis scutatus scutatus, with other β-neurotoxins, and non-neurotoxic enzymes (Dufton and Hider, 1983a; Kini and Iwanaga, 1986; Tsai et al., 1987; Kondo et al., 1989). More recently, Hains et al. (1999) developed a testable two-step proposal of neurotoxic PLA2 activity; involving the favourable binding to acceptor molecules followed by enzymatic intrusion upon the target membrane. 1.4.3 Acetylcholinesterase inhibitors This group of neurotoxins cause continuous excitement of the muscle by binding to acetylcholinesterase and thus rendering acetylcholine unhydrolysed (Rodriguez-Ithurralde et al., 1981, 1983). Since they are capable of affecting transmitter turnover, they can be grouped as presynaptic neurotoxins (Harris, 1991). Acetylcholinesterase inhibitors have so far been 11 Introduction isolated only from African mambas (Dendroaspis), including fasciculin (Dajas et al., 1987) and F7 (Lin et al., 1987) from D. augusticeps and toxin C and D from D. polylepis polylepis (Joubert and Strydom, 1978; Karlsson et al., 1984). Structurally, they are related to cardiotoxin and α-neurotoxins. They consist of 57-60 amino acid residues in a single polypeptide chain, cross-linked by four disulfide bonds, showing similar primary structure to postsynaptic neurotoxins and cardiotoxins. In addition, they show similar 3-D structure as shown by the crystalline structure of fasciculin 2 (Le Du et al., 1989). However, they act by different mode from α-neurotoxins and cardiotoxins. Fasciculin 2 has no presynaptic action on transmitter release or on postsynaptic receptor-blocking action. Its main action is on acetylcholinesterase (Harvey et al., 1984; Anderson et al., 1985). By inhibiting acetylcholinesterase, fasciculin increased the amplitude and time course of the endplate potential (Lee et al., 1985) as well as the amplitude of the miniature endplate potential (Cervenansky et al., 1991). 1.4.4 Potassium channel inhibitors Dendrotoxins are small proteins that were isolated 20 years ago from mamba snake venoms. Dendrotoxin is the first snake toxin found to bind voltage-sensitive K+ channel which is known to play an important role in the repolarization process in nerve transmission. In addition, three dendrotoxins (α-DaTX, β-DaTX, δ-DaTX) have also been isolated from the venom of D. augusticeps. Furthermore, toxin I (DTX14) from venom of D. polylepis polylepis and βbungarotoxin from venom of B. multicinctus have also been isolated. The functional effects of dendrotoxins have been well described in a review by Harvey (2001). The first noticeable effect of dendrotoxin is to facilitate transmitter release at peripheral synapses. Subsequently, the facilitatory effects of the dendrotoxins have been explained by their blockage of some neuronal K+ channels. This toxin has been suggested to block rapidly activating K+ current that is important for the control of the excitability of motor nerve terminals. When injected into the central nervous system, dendrotoxin induces epileptiform activity (Velluti et al., 1987; Coleman et al., 1992) and in high doses, can lead to neuronal damage (Bagetta et al., 1992; Mourre et al., 1997). In addition, dendrotoxin increases inhibitory postsynaptic currents in Purkinje regions of the mouse cerebellar slice preparations 12 Introduction (Harvey, 2001). Dendrotoxin also increases acetylcholine release in rat striatal slices, an effect attributed to the block of channels containing Kv1.2 subunits (Fischer and Saria, 1999). 1.5 Postsynaptic neurotoxins Postsynaptic neurotoxins are those capable of blocking nerve transmission by binding specifically to nicotinic acetylcholine receptors located on the postsynaptic membranes of skeletal muscles and/ or of neurons. These toxins, which mimic the neuromuscular blocking effects of plant alkaloid, tubocurarine, but with approximately 15 – 20-fold greater affinity and poor reversibility of action, are also known as curaremimetic neurotoxins or simply as αneurotoxins, a suffix of historical significance (Chang, 1979; Chang, 1999). Most αneurotoxins are derived from Elapidae or Hydrophiidae snake venom and belong to the threefinger toxin family. It must be emphasized that snake venoms are not the only exclusive source of α-neurotoxins. The venoms of marine cone snails also represent a rich combinatorial-like library of evolutionarily selected, neuropharmacologically active peptides called conotoxins that target a wide variety of receptors and ion channels. α-neurotoxins bear the imprint of a region of the nAChR that is likely to be in proximity to, and perhaps even overlap, the binding site for the natural neurotransmitter acetylcholine (Servent and Menez, 2001). 1.5.1 Nicotinic acetylcholine receptor The discussion of α-neurotoxins will not be completed without a brief introduction to this well characterized receptor. The nAChR is perhaps one of the best characterized ion-channel to date, due in part to the discovery of α-bungarotoxin and a rich and accessible source of receptor from the electric ray and eel. Consequently, the mammalian neuromuscular junction is also the most studied and best understood synaptic region (Naguib et al., 2002). The nAChRs are transmembrane allosteric proteins of MW approximately 290 kDa that are involved in fast ionic responses to acetylcholine (Karlin et al., 2002). They are pentamers formed by the association of five subunits arranged symmetrically around the ionic pore in a plane perpendicular to the membrane (Miyazawa et al., 2003). Each subunit is composed of a large amino-terminal domain that contributes to the formation of the ligand binding pocket; four 13 Introduction membrane-spanning domains (MI, MII, MIII, MIV); a large and variable cytoplasmic loop between MIII and MIV; and a small extracellular carboxyl terminal. The MII domains of all five subunits contribute to the formation of the cation channel pore (Figures 1.4 A & B). In vertebrates, the combinatorial assembly of various nicotinic receptor subunits (α1- α10, β1- β4, δ, γ, and ε) generates a wide diversity of receptors, with various electrical and binding properties. Generally, nicotinic receptors can be divided into two main families: the muscle and neuronal nAChRs (Corringer et al., 2000). The well-characterized muscle receptor consists of a combination of α1, β1, δ and γ or ε subunits in the stoichiometry of (α1)2 β1 γ δ or (α1)2 β1 ε δ in the embryonic or adult receptor, respectively. These are densely distributed on the postsynaptic membrane of the neuromuscular junction and mediate intercellular communication between the nerve ending and skeletal muscle. The muscle-type receptor (α1)2 β1 γ δ is also found in abundance in the electric organ of the Torpedo ray. Neuronal nicotinic receptors are composed of α2 – α10 and β2 – β4 subunits. An excellent insights into the structure of nAChRs and ligand-gated ion channels in general, was made possible by the discovery and characterization of an acetylcholine-binding protein (AChBP) from the snail Lymnaea stagnalis (Figures 1.4C & D; Smit et al., 2001; Brejc et al., 2001) which is a remarkable homologue of the amino-terminal extracellular domain of nAChR. The crystal structure of the AChBP revealed that each ligand-binding site is located in a cleft at the subunit interface, conforming to the existing biochemical and mutational data on nAChRs (Brejc et al., 2001). Based on the structure of AChBP, nearly all the residues of the agonistbinding site of nAChR that were previously identified by photoaffinity labeling and mutagenesis experiments are located in the small cavity of about 10 – 12 Å diameter that is primarily formed by aromatic residues contributed by participating subunits (Grutter et al., 2001; Karlin, 2002; Sixma and Smit, 2003). 14 Introduction A B C Extracellular domain N-terminus D Transmembrane domains MI - MIV Ligand-binding sites Cell membrane Channel pore Intracellular domain Figure 1.4: The structure of nicotinic acetylcholine receptor and its binding protein. A: The nAChR is a pentamer of five homologous subunits. The muscle receptor of the stoichiometry (α1)2β1γδ is represented in this model. The receptor is depicted perpendicular to the axis of the ion channel pore. For clarity, the γ subunit is not shown. Each subunit is composed of four helical transmembrane domains (MI, MII, MIII, MIV). The MII domain of all five subunits lines the channel pore. B: Top view of the pentameric receptor, viewed along the five-fold axis, showing the association of the five subunits. The extracellular aminoterminal domain of the α1-subunit and the adjacent subunit (γ or δ) cooperate to form two distinct binding pockets for acetylcholine (or other agonists or competitive agonists) at the interface between the subunits. C, D: The acetylcholine from binding protein from snail brain, a structural homologue of the nAChR ligand-binding domain. C: Each subunit is a single protein domain. The cavity and pocket at each interface likely constitutes the ligand binding site. D: As viewed perpendicular to the five-fold axis (Nirthanan and Gwee, 2004). 15 Introduction 1.5.2 α-Neurotoxins α-Neurotoxins from Elapid and Hydrophiid snake venoms belong to the three-finger toxin superfamily of non-enzymatic polypeptides containing 60 – 74 amino acid residues. The characteristic feature of all three-finger toxins is their distinctive structure formed by three adjacent loops that emerge from a small, globular, hydrophobic core that is cross-linked by four conserved disulfide bridges (Endo and Tamiya, 1991; Menez, 1998). The three loops that project from the core region resemble three outstrectched fingers of the hand (Figure 1.5). The toxin is essentially a flat “leaf-like” molecule. In addition to the structural plasticity of the three fingers, the three-finger fold is also amenable to a variety of overt and subtle deviations, such as the number of the β-strands present, size of the loops and C-terminal tail as well as twists and turns of various loops, all of which may have great significance with respect to functional diversity and selectivity of molecular targets (Servent and Menez, 2001; Kini, 2002). Hence, despite the similar overall fold, three-finger toxins demonstrate an assorted range of pharmacological activities including, but not limited to, peripheral and central neurotoxicity, cytotoxicity, cardiotoxicity, inhibition of enzymes such as acetylcholinesterase and proteinases, hypotensive effect, and platelet aggregation (Tsetlin, 1999; Kini, 2002; Hodgson and Wickramaratna, 2002). It has been proposed that three finger scaffold is used by snake to target different combinations of functional groups, generating a panoply of target specificities. A Short-chain toxin C B D Weak toxin Kappa toxin Long-chain i Figure 1.5: The 3D-structures of three-finger neurotoxins from snake venoms that interact with nicotinic acetylcholine receptors. The three-dimensional structures are shown in similar orientation and in line ribbon representation. Disulfide bridges are shown in black. The species names and the Protein Data Bank accession codes for structures are as follows: A: Erabutoxin-a (Laticauda semifasciata,5EBX, Corfield et al., 1989) B: Candoxin (Bungarus candidus, 1JGK, Paaventhan et al., 16 Introduction 2001) C: α-Cobratoxin (Naja kaouthia, 2CTX, Betzel et al., 1991) D: α-Bungarotoxin (B. multicintus, 2NBT, Sutcliffe et al., 1992). All are averaged NMR structures except erabutoxin-a, 2.0-Å crystal structure and α-cobratoxin, 2.4-Å-crystal structure. To date, more than 100 three-finger α-neurotoxins have been isolated and sequenced from Elapidae and Hydrophiidae snakes. Depending on their amino acid sequence and tertiary structures, α-neurotoxins can be classified into short-chain, long-chain, kappa and weak neurotoxins. Although the primary target of all these categories of the three-finger neurotoxins appears to be the muscle-type nAChR, some toxins are known to interact with other subtypes of nAChRs such as neuronal nAChR. 1.5.3 Short- and long-chain neurotoxins Based on the length of their polypeptide chains, α-neurotoxins were initially classified as shortchain α-neurotoxins that have 60 – 62 residues and four conserved disulfide bonds in common positions, between Cys-3 and Cys-24, Cys-17 and Cys-45, Cys-40 and Cys-61, Cys-62 and Cys-68 (Figure 1.5A). These neurotoxins bind with high affinity to muscular-type nAChRs. The second group constitutes the long-chain α-neurotoxins consisting of 66 – 70 amino acid residues with disulfide bonds, the fifth being between Cys-30 and Cys-34, in addition to the four disulfide binds that are common in short-chain α-neurotoxins (Figure 1.5C). Notwithstanding their classification a short-chain and long-chain neurotoxins, both types of αneurotoxins bind with high affinity to the Torpedo or muscle (α1)2β1γδ nAChRs (Servent and Menez, 2001). Nonetheless, it has been reported that short-chain α-neurotoxins tend to associate with the nAChR 6 – 7 fold faster and dissociate 5 – 9 fold faster than long-chain αneurotoxins (Chicheportiche et al., 1975). Apart from differences in structure, long-chain but not short-chain α-neurotoxins are also able to bind with high affinity (Kd approximately 10-8 – 10-9 M) to neuronal homopentameric α7, α8 and α9 nicotinic receptors (Servent et al., 2000; Antil-Delbeke et al., 2000). 17 Introduction 1.5.4 Kappa neurotoxins κ-Neurotoxins form a new family of snake venom neurotoxins that are structurally related to long neurotoxins. With the exception of κ-cobrotoxin, all the other κ-neurotoxins identified consist of 66 amino acid residues and on the basis of amino acid alignment, contain five disulphide bonds as in long neurotoxins (Figure 1.5D). The first κ-neurotoxin, κ-bungarotoxin was purified from B. multicinctus venom and it is a minor component representing only 0.1% of total venom (Grant and Chiapinelli, 1985). κ-bungarotoxin exists in physiological solution as a dimer of identical subunits, each subunit having a molecular weight about 7.3 kDa. The dimer is not covalently linked and is dissociated into monomers in the presence of sodium dodecyl sulfate, urea, or high-ionic strength and high-pH buffers (Chiappinelli et al., 1985), in contrast to monomeric α-neurotoxins either in solution or in crystal. All κ-neurotoxins also contain the amino acid deletions in positions 16 – 20 and amino acid additions between positions 36 and 40, which are characteristic of long neurotoxins (Fiordalisi, 1994). Moreover, the κ-neurotoxins display a unique single-residue insertion in position 52 (Fiordalisi, 1994). These toxins have shorter carboxyl-terminal tail than any other long chain αneurotoxins. κ-Neurotoxins bind with high affinity to the α3-containing neuronal nAChRs and with low affinity to the α4-subunit-containing neuronal nAChR (Chiappinelli, 1992). Contrary to short and long neurotoxins, κ-neurotoxins are weak antagonists to muscle-type nAChR (Grant et al., 1985; Dewan et al., 1994; Sutcliffe et al., 1992) The absence of Trp-32 in all the κ-neurotoxins could be the reason for the lack of binding to muscle-type nAChR (Grant, 1988). To date, this group contains nine members isolated from Bungarus (Grant et al., 1985) and one from Naja (Chang et al., 1998). The exact basis of the distinct physiological selectivity of these structurally-similar α- and κ-neurotoxins is not well understood. 1.5.5 Weak neurotoxins Weak neurotoxins, also known as atypical or miscellaneous toxins, constitute another class of three-finger toxins that consist of 62 – 68 amino acid residues and five disulfide bridges. However, unlike long-chain α-neurotoxins and κ-neurotoxins, the fifth disulfide bridge in weak 18 Introduction neurotoxins is located in loop I (N-terminus loop, Figure 1.4B). Weak toxins are typically characterized by a lower order of toxicity with lethal dose (LD50) varying from 5 – 80 mg/ kg as opposed to prototypical α-neurotoxins with LD50 approximately 0.04 – 0.3 mg/ kg. Weak neurotoxins from cobra venoms such as WTX (Naja kaouthia) and Wntx-5 (N. sputatrix) produced a weak inhibition of muscle nAChRs in micromolar inhibitory concentrations (Utkin et al., 2001; Poh et al., 2002). Candoxin from B. candidus was a potent inhibitor of muscle nAChRs in low nanomolar range (IC50 approximately 10 nM). This toxin was also found to inhibit neuronal α7 nAChRs at low nanomolar (IC50 approximately 50 nM) inhibitory concentration (Nirthanan et al., 2002). It is conceivable that weak neurotoxins that bind weakly to muscle nAChRs may yet have other unidentified molecular targets. 1.6 Applications of snake venom neurotoxins in research and therapy Although early venom research was motivated by the desire for satisfactory cures for snake envenomation, the general perspectives on animal toxins have changed dramatically due to the accumulating data that has revealed a far wider scope for these natural biomolecules. It has been 40 years since it was first realized that the physiologically active components of snake venoms might have therapeutic potentials (Senior, 1999). These biomolecules have assumed great importance as molecular probes and pharmacological tools to investigate the functional biology of receptors and ion channels as well as providing lead compounds for the design of clinically useful drugs (Harvey et al., 1998; Harvey, 2002a, b). There is perhaps no better example to highlight the significant contributions made by venom peptides to science and medicine than the discovery of α-bungarotoxin from Taiwan banded krait, which has spawned the field molecular pharmacology by enabling the isolation and characterization of nAChR from electric eel and other sources (Chang and Lee, 1963; Lee, 1972). 1.6.1 Viral infection The possibility that nAChR is a host cell receptor for the neurotropic rabies virus was first discussed by Lentz et al. (1982). These authors suggest that the virus binds at neuromuscular junction and the binding is drastically reduced by the specific AChR antagonist α19 Introduction bungarotoxin (α-Bgt). A stricking homology between a region of rabies virus glycoprotein and the putative functional sites of snake venom neurotoxin has been demonstrated by Lentz et al. (1984). This would imply a functional convergence between these distantly related proteins. Purified rabies virus glycoprotein was able to compete with the potent neurotoxin of snake B. multicinctus α-bungarotoxin for binding to acetylcholine receptor. Moreover, anti-peptide monoclonal antibodies against glycoprotein 190-203 had been found to efficiently inhibit the binding of both rabies virus glycoprotein and α-bgt to acetylcholine receptor. In general, the regions of virus molecules involved in binding to the cellular components acting as viral receptors might be structurally similar to the binding domains of cellular proteins that normally bind to the cell components (Figure 1.6). Such similarity between parts of viruses and ligands or normal cell constituents may provide a basis for the pathogenesis of some autoimmune diseases because viral infection could be followed by production of antibodies to the idiotypes, which would react with the cellular structures (Sege et al., 1983). Identification of the viral domains that bind to cells should be important in the treatment of viral diseases. Neri et al. (1990) also reported the homology of the neurotoxin toxic loop with the sequence of 164-174 of HIV-1 gp120. Human rhabdomyosarcoma cell line, TE671, is known to express a muscle-like nicotinic receptor (Schoepfer et al., 1988) to which α-bungarotoxin binds with high affinity. The binding of α-bungarotoxin to TE671 cells was found to be inhibited by gp120 from HIV-1 strain IIIB. Therefore, HIV infection of muscular and neuronal cells in vitro might be mediated by gp120 binding to nicotinic acetylcholine receptor present in these cells; which raises the same possibility that the same mechanism may be observed for HIV neurotropism. The results suggest that nAChR may also bind HIV-1 gp120 in neuronal cells since α-bgt binds to some population of nicotinic receptor expressed in the nervous system. 20 Introduction Figure 1.6: A model showing homology of rabies glycoprotein with the “toxic” loop of the neurotoxins. The segment of the glycoprotein (residues 174 to 202) corresponding to loop 2 of the long neurotoxins (position 25 to 44) as determined by computer modeling is positioned relative to a schematic representation of loop 2. Within circles, residues or gaps in the glycoprotein are shown on the left and those in the neurotoxin on the right. One letter in the circle implied the same residue in glycoprotein and toxin. Bold circles are residues highly conserved or invariant among all the neurotoxins. A ten-residue insertion in the glycoprotein is enclosed in the box. The rabies virus sequence is from CVS strain. Neurotoxin sequence is from Ophiophagus hannah, toxin b (inset). Schematic representation of neurotoxin structure showing positions of loops 1, 2 and 3 (Lentz et al., 1984). 1.6.2 Myasthenia gravis α-Bgt played an important role in understanding the pathogenesis of myasthenia gravis (MG), a disease which causes weakness of skeletal muscles. Muscular tissue of patients exhibited a considerably reduced number of nAChR sites available for toxin binding (Mebs, 1989). The autoimmune nature of the disease became evident when animals immunized with isolated nAChR developed symptoms essentially identical to MG. It became clear that an autoimmune attack directed to the body’s own nAChR causes accelerated degradation of these receptors in skeletal muscles (Drachman, 1981). The challenge now is to find selective and efficient 21 Introduction markers and blockers of those neuronal AChRs and perhaps weak neurotoxins can be used as potential tools to answer this question. 1.6.3 Alzheimer’s disease Recently, Nirthanan et al. (2002) identified candoxin from B. candidus as a reversible antagonist of muscle nicotinic acetylcholine receptors and an irreversible ligand to neuronal nicotinic acetylcholine receptor. This compound may be useful as a probe to label, identify or isolate the α7-subtype of neuronal nicotinic receptor, in which this receptor is of great interest in several disease conditions such as Alzheimer’s disease. The rapid onset and reversible properties of candoxin, like d-tubocurarine which is used as a muscle relaxant, can be exploited for therapeutic use. 1.6.4 Thrombotic disease A potent glycoprotein from Dendroaspis jamesonii which is structurally related to short neurotoxins was discovered by McDowell et al. (1982) to be platelet aggregation inhibitor. The finding that an Elapidae snake has a protein with the general structure of a neurotoxin but with the function of platelet inhibitor, is unique and have important implications for evolutionary biology. This unique inhibitor named mambin is non-neurotoxic and may have therapeutic potential for treatment of thrombotic disease (McDowell et al., 1982). 1.6.5 Research tools Muscle nAChRs are pseudosymmetric pentameric complexes formed by four different subunits (α, β, γ or ε and δ) whereas neuronal nAChRs identified so far are pentamers formed by one (αx), two (αx, βγ) or three (αx, αy, βz) types of subunits (McLane et al., 1993). Neuronal nAChRs, in addition to having alternative subunit stiochiometries, are composed of several different subunit subtypes, with at least eight different α subunits and five different β subunits being identified (reviewed in Deneris, 1991). 22 Introduction By far, the most valuable probes to characterize muscle nAChR are long and short neurotoxins from snakes which bind with extremely high affinity (KD = 10-12 – 10-9 M) to skeletal muscle nAChRs (Chiappinelli, 1991). Occupation of the toxin of either one or both of the ACh recognition sites on the α subunits of a muscle receptor prevents the ion channel associated with the receptor from opening in response to cholinergic agonists (Neubig and Cohen, 1980). In addition, long neurotoxins have been used to characterize neuronal nAChRs containing α7 subunits (Seguela et al., 1993). These neuronal receptors have a high affinity for the long neurotoxins at KD = 0.7-1.7nM (Tindall et al., 1978; Wolf et al., 1988). For example, αbungarotoxin has been an important antagonist in establishing the functional properties of these neuronal AChRs (Zhang et al., 1994). The α-bungarotoxin-sensitive neuronal receptors have certain properties unlike other AChRs such as the ability to form functional homomeric channels in oocyte expression studies and high permeability to Ca2+ ions (Seguela et al., 1993; Alkondon et al, 1993). κ-Neurotoxins are selective and potent antagonists used to characterize neuronal nAChRs in which short and long neurotoxins have no effect (Chiapianelli, 1991). For example, κbungarotoxin had been used as a potent inhibitor of α3β2 neuronal nAChRs (McLane et al., 1993). One of the many applications of toxin as a probe was exploited by Sekhon et al. (1999). They tested their hypothesis that maternal smoking during pregnancy is associated with alterations in pulmonary function at birth and increase respiratory illnesses after birth. They found that the direct results of these observations are due to nicotine binding with nAChRs. Labeled αbungarotoxin was used to label α7 nAChRs in developing monkey lung and the results demonstrated that nicotine significantly increased α7 nAChRs in airway epithelial cells, alveolar type II cells, alveolar macrophages and pulmonary neuroendocrine cells (PNEC). Hence the use of labeled neurotoxin in this study can contribute to the understanding of mechanistic changes that occur in the fetus of smoking mothers. The role(s) of weak neurotoxin in the venom is still unknown and the challenge now is to fully unravel its physiological importance in the snake. 23 Introduction 1.6.6 Novel functional homologs Miwa et al., (1999) discovered a novel, endogenous homolog of snake neurotoxins, lynx1 in mouse cerebellum, hippocampus, and cortex. This new relative of the family of elapid neurotoxins was identified in the course of a search for developmentally regulated genes in the cerebellum. Based on overall sequence similarity, conservation of cysteine-rich consensus motif, and common gene structure with neurotoxin gene, lynx1 was classified as a small (11kD) toxin-like (prototoxin) central nervous system protein (Figures 1.7A and B). In contrast to secreted snake neurotoxin, lynx1 is normally present at the cell surface as a glycophosphatidylinositol (GPI)-anchored protein (Miwa et al., 1999). Further studies found that this protein could associate and modulate nAChR, exhibiting preferential binding to α7 and α4 subunits (Ibanez-Tallon et al., 2002). Studies on mice carrying lynx1 null mutations could shed light on the role for this protein in the CNS of mammals. Figure 1.7: Comparison of the lynx1 model and the αBgt experimental structure. (A) The figure shows the three-dimensional model of lynx1. Strands are shown as green arrows and disulfide bridges are coloured yellow. (B) Experimental NMR structure of α-Bgt (PDB 1abt). The orientation and colouring is the same as for lynx1. N- and C-terminal ends of both molecules are labeled (Miwa et al., 1999). 24 Introduction 1.6.7 Chimeric toxins It was observed that when a long neurotoxin whose characteristic fifth disulphide bond was selectively reduced, it behaved like a short neurotoxin in terms of specificity of receptor recognition (Servent et al., 1998). Addition of a fifth disulphide bond at the tip of the central loop of a short neurotoxin increases its affinity for neuronal receptors. Ricciardi et al. (2000) tested the idea that structural deviations between toxins adapting the same fold reflect functional diversity. They also demonstrated that when a recombinant fasciculin/ toxin α chimera containing loop 1 and tip of loop 2 of fasciculin was transferred into toxin α, the chimera exhibited nearly all acetylcholinesterase-blocking activites of fasciculins (Ricciardi et al., 2000). This would imply that toxin usually adopt a limited structural deviations which can result in a multiple functional diversity. 1.7 Scorpion Scorpions belong to arthropods in the animal kingdom and they are the largest as well as the oldest arachids. They are representated by 1, 500 distinct species. To date, scorpions have a wide geographical distribution and live on all major land masses except Antarctica. Their habitats include desert, savanna, grasslands, temperate forests, tropical forests, rain forests and the intertidal zones. Some remarkable species are found even at snow-covered mountain over 5, 500 m in altitude and in caves at depth of more than 800 m (Francke, 1982). Scorpions can be divided into six families: Bothriuridae, Scorpionidae, Buthidae, Vejovidae, Chlaerilidae and Chactidae. Only Buthidae scorpions produce neurotoxic secretions. Scorpions which are dangerous to humans are found in desert or semiarid regions throughout the world. Among the approximately 1500 scorpion species, only about 25 species are of medical importance. Morbidity and mortality rates due to scorpion stings are especially high in children have been reported in various countries. In Mexico, Brazil, North Africa, India and in the Middle East (Mazzotti, 1963; Bucherl, 1971; Balozet, 1971; Bawaskar, 1989), scorpions still possess a medical problem and life hazard to humans. 25 Introduction 1.7.1 Buthus martensi Karsch The Chinese scorpion Buthus martensi Karsch (BmK) belonging to the Buthidae family is widely distributed from northwestern China to Mongolia and Korea. The sting by this species can cause excruciating local pain that might last for several hours and induce a series of inflammation and pain responses (Balozet, 1971; Bai et al., 2003). They can grow up to 4.8 – 5.2 cm in length. As early as one thousand years ago, the pharmaceutical role of scorpions was widely recognized by the Chinese. Li Shi-Zhen in 1578 described the properties and curative effects of scorpions in detail. In Traditional Chinese Medicine at this present time, the whole scorpion body especially the tail, is being used as a medicine to treat neuromuscular diseases such as paralysis and epilepsy. In addition, scorpions have been used for treatment in apoplexy, hemiplegic and facial paralysis. Detailed knowledge about the biological properties of the venom of BmK has been generally limited and only little is known about the neurotoxic components present in the venom of this species. In the past years, BmK venoms has been studied extensively and this lead to the discovery of 77 different peptides (Goudet et al., 2002). 1.7.2 Scorpion venom Scorpions produce powerful venom in glands located in the distal end of its tail, known the telson. The venom is injected into a victim through a sharp stinger. Scorpion venoms are lethal to a broad spectrum of animals such as rodents (rats, mice and guinea pigs), rabbits, chicks, fish, arthropods (fly larvae, crickets, moths and mealworm) and many others. There are however, a few animals which are resistant to scorpions venoms such as the tarantula spider, locust and of course, scorpions themselves. Although Chinese scorpion is generally not dangerous to human, the venom is considered to be a mixture of ‘rather active toxins’, suggesting that it had probably several toxic components (Balozet, 1971). The toxicity (LD50, i.p) of this venom in mice was found to be 3.38 mg/ kg weight (Gong et al., 1992), which is moderate in comparison with the LD50 of the venoms of 26 Introduction other species. BmK venoms induce convulsions and paralysis in mammals, crusteacea and insects. Scorpion venoms, like the snake venom contain a complex protein composition. They consist of mucopolysaccharides, small amounts of hyaluronidase and phospholipases, low molecular weight compounds such as noraderenaline, serotonin, histamine, protease inhibitors and histamine releasers and multiple basic, predominantly neurotoxic proteins (Simard and Watt, 1990; Martin-Eauclaire and Courad, 1995;). The scorpion venom contains an array of several structurally distinct families of peptides that modulate ion channels. These toxins can be classified into four groups according to their effects on specific ion channels, such as Na+, K+, Ca2+ and Cl- ion channels (Garcia et al., 1997; Gordon et al., 1998; Tytgat et al., 1999; Valdivia and Possani, 1998; Possani et al., 1999). Ion channels are crucial elements for the activity of living cells, targeting these membranebound proteins is thus an efficient means for venomous animals to capture their preys or to defend themselves against enemies. Natural toxins also provide powerful tools for understanding the physiological contribution of ion channels to cell and organ behaviour and for probing and correlating ion channel structure and function. Moreover, elucidation of the mechanisms of toxin action especially on their three-dimensional structures provide wider perspectives in designing of drugs (Menez, 1998). The best studied peptides are long-chain toxins that contain 60 – 70 amino acids residues with four disulfide bridges (Possani, 1984). The targets of these toxins are voltage-sensitive Na+ channels of excitable muscle and nerve cells. These ion channel toxins can be divided into αtoxins and β-toxins, based on their physiological effect on the opening and closing kinetics of Na+ channels. The α-toxins prolong the action potential by blocking Na+ channel inactivation and β-toxins shift the voltage activation towards a more negative potential thereby affecting Na+ channel activation and promoting spontaneous and repetitive firing (Couraud et al., 1982; Catterall et al., 1986). 27 Introduction The difference in the effects of the α- and β-toxins is attributed to their ability to bind to two distinct sites on the Na+ channel receptor. α- and β-toxins bind to sites 3 and 4 on the Na+ channel respectively (Jover et al, 1980). Alternatively, Na+ channel toxins classified based on their species specificity as insect-, mammal-, and crustacean-specific toxins (Gordon et al., 1996; Meves et al., 1984; Garcia et al., 1997). An exception to this rule is toxin AaH IT4 which is cross-species specific affecting both insects and mammals (Loret et al., 1991). Hundreds of distinct peptides specific for Na+ channels have been purified from 20 – 30 species of scorpions; at least 120 complete primary structures have been identified. On the other hand, a subset of short-chain scorpion toxins has also been found to interact with the voltage-dependent or Ca2+-activated K+ channels or with Cl- channels. Toxins that affect voltage-gated K+ toxins typically contain 31 – 38 amino acids with three or four disulfide bridges (Garcia et al., 1997). A recently purified 23-residue toxin from the scorpion Tityus cambridgei was reported to block K+ channel (Batista et al., 2000). Two scorpion peptides have been reported to modify the binding of ryanodine to Ca2+ - channels. Imperatoxin A, which is 33 amino acids long, increases the binding of ryanodine resulting in continuous Ca2+ channel stimulation (Zamudio et al., 1997a). Imperatoxin I is a heterodimer which blocks Ca2+channel by inhibition of ryanodine binding (Zamudio et al., 1997b). Scorpion toxins that interact with Cl- channels and their homolog are approximately 36 amino acids long with four disulfide bridges (Lippens et al;, 1995; DeBin et al., 1993). Chlorotoxin is the first high-affinity peptide ligand for Cl- channels. In recent years, Cl- channel have been a significant focus of interest as defect in this channel is the cause of cystic fibrosis. 1.8 Microarray A microarray is an ordered array of microscopic elements that allows specific binding of genes or gene products. Microarray is a new scientific word derived from the Greek word mikro (small) and the French word arayer (arranged). Microarrays, also known as biochips, DNA chips and gene chips contain minute quantities of DNA, protein or small organic compounds which can be probed with possible binding ligands. The first use of microarray was in 28 Introduction immunological assays but progress in genome sequencing has created a demand for simultaneous multi-gene analysis (Ekins, 1989; Ekins and Chu, 1992). Microarray technology developed in the early 1990s by Mark Schena and collegues at Stanford University rely heavily on six major disciplines: biology, chemistry, physics, engineering, mathematics and computer science (Schena et al., 1995). The advent of this miniaturized technology for the study of molecule-molecule interactions has changed the way that new challenges are approached in cell biology. In addition, major advances in detecting fluorescence-based experiment had enabled simultaneous analysis of thousands of variables in a single experiment (Howbrook et al., 2003). 1.8.1 DNA microarray Array-based gene expression analysis in which immobilized DNA probes hybridizing to RNA and cDNA targets has become an important primary tool in many research projects. Expression analysis for the quantitative gene expression of many genes can be performed using one- or two-color fluorescent schemes. One colour analysis is primarily used for arrays prepared using photolithography method. In 1991, Fodor described an innovative application of photolithography, which has been used in the industrial production of electronic semiconductor devices. Photolithography uses ultraviolet light and solid-phase synthesis to manufacture microarray (Fodor et al., 1991). This light-based synthesis approached became one of the widely used methods in the manufacture of microarray. Briefly, we attached synthetic linker modified with photochemically removable protecting groups to a glass substrate and direct light through a photolithographic mask to specific areas on the surface to produce localized photodeprotection. The first series of chemical building block is incubated with the surface and chemical coupling occurs at those sites that have been illuminated in the preceding step. Next, light is beamed to different regions of the substrate by a new mask and chemical cycle is repeated (Pirrung et al., 1998). Photolithography allows the construction of arrays with extremely high information content. Since the arrays are constructed on a rigid material (glass), they can be mounted and inverted in a temperature-controlled hybridization 29 Introduction Experimental design Biological experiment Sample B: eg. treated sample Sample A: eg. untreated sample RNA extraction RNA sample A RNA sample B Fluorescent labeling Microarray fabrication Labeled sample A Labeled sample B Microarray Microarray hybridization Image acquisition Image analysis Data preprocessing and normalization Identification of differentially expressed Figure 1.8: Exploratory data analysis Classification Other analyses (e.g. pathway Flowchart showing a typical microarray experimental procedure. After carrying out the biological experiment, the samples from tissues or cells, are collected. For example, sample A is the control experiment and sample B is the tested experiment. Total RNA is isolated and labeled with fluorescent dyes and co-hybridized with the microarray. The hybridized microarray is scanned to acquire the fluorescent images. Statistical analysis can be used to infer the microarray data, depending on one’s aim of study. Image adapted from Leung and Cavalieri, (2003). 30 Introduction chamber (Lipshutz et al., 1999). A fluorescently tagged nucleic acid sample injected into the chamber is allowed to hybridize to the complementary oligonucleotides on the array. Laser excitation enters through the back of the glass support and focused at the interface of the array surface and target solution. The fluorescence emission caused is collected by a lens and passed through a series of optical filters to a sensitive detector which converts it to a quantitative twodimensional fluorescence image (Ekins, 1989; Ekins and Chu, 1992). A summary of a typical microarray experiment is depicted in Figure 1.8. 1.8.2 Applications of DNA microarray Gene expression studies using DNA microarray accounts for 81% of the scientific publications to date, but microarrays are being used for many other purposes including genotyping, tissue analysis, and protein studies. In the field of development, microarrays can be employed to build a database of gene expression levels as a function of cell and tissue type. These databases are extremely valuable as they provide deeper understanding of the basic mechanisms that control multicellular development and might shed some insights into the pathological cellular events, including the onset and progression of human disease. The onset and progression of human disease are determined by a complex set of factors, including genetics, diet, the environment, and the presence of infectious agents. Microarray makes a unique tool in studying each of these contributing factors. For example, gene expression patterns in brain tissue from normal individuals and Alzheimer’s patients can be studied to elucidate the genetic basis of this illness. Almost all human diseases can be studied using microarray analysis and the ultimate goal of this work is to develop treatments or cures for every human disease by 2050 (Schena, 2003). Drug discovery is one of the hottest areas in research and development. Many known drugs impart their therapeutic activity by binding to specific cellular targets, inhibiting protein function, and altering the expression of cellular genes. In principle, it is possible to use microarray for drug discovery and clinical trials by generating gene expression profiles in patients undergoing disease progression or drug treatment. Many illnesses lead to specific 31 Introduction changes in gene expression and drugs that reverse these changes might be beneficial. Expression profiling may be useful in identifying drugs that alter gene expression of nontarget genes, as a means of identifying drugs with possible side effects. This might lead to safer medicines with minimal side effects. In addition, this technology can be used for patient genotyping, and the capacity to partition the population into drug responders and nonresponders based on genotype may enable more personalized medicine. Microarray has also been successfully used for providing the biological and medical community with a greater understanding of venom – induced pathologies and the subsequent treatment of envenoming (Gallagher et al., 2003). This microarray – based toxicological approach was employed in vivo to investigate the effects of phospholipase A2 from Naja sputatrix to study the change in global gene expression especially on aquaporins and Na+/ K+ATPase genes (Cher et al., 2003). Another group used an in vitro system to study venominduced apoptosis in human umbilical vein endothelial cells by use of subpathological levels of Crotalus atrox and Bothrops jararaca (Gallagher et al., 2003). These studies collectively demonstrate that snake venom components can be used as biologically active proteins in pharmaceutical lead compounds. 1.9 Neurogenesis The pioneering neuroscientist Ramon y Cajal (1928) observed that: “In adult centers the nerve paths are something fixed, ended, immutable. Everything may die, nothing may be regenerated. It is for the science of the future to change, if possible, this harsh decree.” The mature central nervous system (CNS) was distinguished from the developing nervous system by the lack of growth and cellular regeneration. The fixed neuronal population of the adult brain was understood for necessary maintenance of functional brain circuitry. This might account for the lack of endogenous CNS repair following injury or disease. 32 Introduction However, in the last several decades, mounting evidence has led to the view of the CNS as a dynamic, plastic organ, endowed with some potential for self-repair and regeneration. Great progress have been made in the understanding of continued neurogenesis in adult brain and this has raised hopes that self-renewal leading to structural repair by neurons may be possible in new neurons (Hallbergson et al., 2003). Neurogenesis in the adult brain can be divided into three phases in accordance with the sequence of neurogenesis during CNS development: (a) proliferation, where new cells are generated; (b) migration towards the target areas; and (c) terminal differentiation into distinct phenotypes (Hallbergson et al., 2003). Neurogenesis is a term which implies progression through differentiation and not only where cases of proliferation is studied. Studies have found that new functional neurons are generated in two adult germinal centres, adding further complexity to the definition of adult plasticity to include circuitry (van Praag et al., 2002). An important observation showed that adult neurogenesis is not static but indeed responds to environmental factors such as physical activity, environmental enrichment, caloric restriction and modulation of neural activity (Peterson, 2002; Ray and Peterson, 2002). The responsiveness of adult neurogenesis to environmental influences may suggest that its regulation is under the control of expressed factors whose level of availability dictates the rate of neurogenesis (Hallbergson et al., 2003). The spatial and temporal expression of various trophic or growth factors play a role in guiding cell-fate choices and determine the size of the neuronal population. In addition to protecting neurons, trophic factors have been shown to stimulate proliferation of adult-derived stem cells and to instruct their differentiation. Examples of trophic factors include amphiregulin and fibroblast growth factor (FGF) (Kuhn et al., 1997, Zigova et al., 1998; Pencea et al., 2001; Benraiss et al., 2001; Falk et al., 2002). Amphiregulin is part of the family of endothelial growth factor (EGF) protein and it has have been suggested to play a role in stem cell proliferation and neurogenesis in the adult brain (Falk et al., 2002). FGF-2 on the other hand, 33 Introduction is another potent mitogen for a variety of cells and modulates embryonic development and differentiation, adult angiogenesis, wound healing and tissue repair. In the brain, FGF-2 is important as a survival factor and is neuroprotective against a variety of insults (Peterson and Gage, 1999). So far, about 70 toxins from BmK have been identified. They are mostly α and β-toxins as well as toxins blocking K+ and Cl- channels. These toxins have been identified mostly using conventional method such as proteomics. It would be interesting to see if BmK might have any pharmacologically important factors that can affect neurogenesis in human brain cells. 1.10 Database creation The first characterization of α-bungarotoxin 40 years ago led to a boom in the discovery of other similar snake neurotoxins. In 1990, there are about 100 known neurotoxin protein sequences in GenBank. However, to date, there are approximately 555 neurotoxin entries in public databases, from snake venom alone. Therefore, the accumulation of snake venom neurotoxins (svNTXs) had greatly increased over the years and this makes it an attractive bioinformatics study for further functional and structural characterizations of svNTXs. Established methods of determining functions of svNTXs are based on study of chemical mutagenesis (reviewed by Karlsson, 1979), structural studies (reviewed by Dufton and Hider, 1983b) and pharmacological and biochemical characterization experiments (Endo and Tamiya, 1991). Many research groups have focused on isolating, purifying and characterizing individual toxins or small groups of toxins. The number of characterized svNTXs reported in the literature and molecular databases is increasing rapidly. In addition, functional properties of individual svNTXs are poorly annotated in molecular databases. Insufficient cross-linking between databases leads to redundancy and often conflicting information, indicating potential errors in data. The growing number of well-studied svNTXs and the high complexity of related information, such as their structural and functional properties have created a need for improved data 34 Introduction management. The analysis of svNTXs data is growing increasingly complex and there is a need for a single, well annotated, and cleaned database, which will facilitate svNTXs analysis. Data for the study of svNTXs are scattered across multiple sources. Hence, there is a need for specialized database in svNTXs to be used as a tool for the study of svNTXs. The database contains entries collected from different sources, organized, analysed and classified according to their structure-function relationship. The svNTXs were annotated for their pharmacological properties and enzymatic activity from literature sources. From the data, pharmacological groups were formed to classify svNTXs based on structure and function relationship. This general classification of svNTXs can be used to identify putative residues for each pharmacological property by sequence comparison between the groups. Well organized and rich data allow the use of sophisticated tools for improved structure-function analysis. 1.10.1 Current problems with analysis of snake toxins using bioinformatic resources Current data on svNTXs are deposited in public repositories GenBank, EMBL (Stoesser et al., 2001), DDBJ (Tateno et al., 2000), SwissProt, and PIR (Barker et al., 2001). The svNTXs three dimensional structures are deposited in the PDB database. Functional properties of svNTXs can be found mainly in published articles while functional annotation of sequences in public sequence databases is very limited (Brusic et al., 2000). Structural properties of some svNTXs can be found in the PDB database and published articles. Of 272 svNTXs reported in February 2004, 1.5% have been published in journals articles only, and the remaining 98.5% have been found in public databases. A recent analysis on scorpion toxin data (Srinivasan et al., 2002) from public databases revealed the presence of numerous errors in the sequences, incomplete data, poor annotation and discrepancies of information for the same entry from different sources. For example, some of the errors encountered were wrong link between databases, different names for the same sequence, different sequences for the same toxin and absence of link between databases. In order to minimize these errors, certain measures such as cross-checking with original publications were taken. In the context of all known data, a unified classification of svNTXs 35 Introduction does not exist. Detailed classification based on structure-function relationship was also constructed. Several bioinformatics tools for analysis of biological data include: 1) pairwise sequence alignment, ii) multiple sequence alignment (local and global), ii) phylogenetic analysis, iii) 3-D structure analysis. i) Pairwise alignment is carried out to locate the conserved regions between two sequences. In global alignment, entire sequences are aligned at the same time using extension of dynamic programming, while in local alignment, conserved regions are found by statistical methods, derived by removing stretches of global alignment. BLAST 2.0 (Altschul et al., 1997) and CLUSTAL X 1.82 are used for local and global alignment respectively. ii) Multiple sequences alignment is the hierarchical extension of pairwise alignment. They are widely used to identify conserved motifs and to predict functional role. It is also a basis for phylogenetic analysis. iii) Phylogenetic analysis helps to determine which sequences are more closely related evolutionarily. 36 Introduction 1.11 Aims of the project The aim of this project has been divided into two parts. The initial part of the project has been to build a snake venom neurotoxin database. The specific goals are: 1) To build a clean information enriched database for svNTXs. 2) To classify toxins based on their structure and function relationships. 3) To provide an in-house platform to predict function of new toxins. The second aim of the project has been to screen for potential therapeutic agent(s) in the venom of Chinese scorpion, Buthus martensi Karsch (BmK) using DNA microarray and realtime PCR. The motivation is to elucidate some of the biological basis of using scorpion venom in traditional medicine. This scorpion venom has been found to have effects on the cardiomuscular system (Gong et al, 1992) in addition to having analgesic effect and antitumor activity (Liu and Pei, 1989; Zhang et al., 1987). It will be interesting to discover novel drug leads in this well studied scorpion. The specific goals are: 1) To examine the subtoxic effects of venoms on gene expression on human neuroblastoma cells and to highlight its potential use in the drug discovery. 2) To screen for active fraction(s) in the venom affecting the expression of genes involved in neurogenesis and angiogenesis using real-time PCR. 37 Materials and Methods MATERIALS AND METHODS Materials and Methods CHAPTER TWO MATERIALS AND METHODS Section A: 2.1 Bioinformatics The flowchart below demonstrates the overall picture of the entire bioinformatics project. Public sequence databases Data Keyword search retrieval BioWare Raw data set Filtering Initial data set Further cleaning Final preliminary data set Data integrated to BioWare format Redundant entries removed Final data set PDB svNTX, 3-D structures svNTX database Functional annotation Published journal reports Analysis Applications of database CysAlign Disulfide bridge patterns Pharmacological properties Classification tree 38 Phylogenetic analysis Materials and Methods 2.2 Data collection and cleaning Structural and functional data in svNTX database where obtained from various sources. Protein sequences information was gathered from public databases such as GenBank, SwissProt and EMBL. The three dimensional (3-D) structures of svNTXs were extracted from PDB. The BioWare system available on-line at http://sdmc.a-star.i2r.org.sg/Templar from Institute for Infocomm Research (I2R) was used to facilitate data retrieval from public databases. Protein sequence entries were gathered from the public databases by query ‘Serpentes and neurotoxin’ using keyword search via BioWare Retrieve module. The return result, a raw data set, underwent a preliminary filtering to remove irrelevant records, such as neurotoxins from other species and neurotoxin fragments. Records not selected at this step were recorded into a rejected list by BioWare to avoid future retrieval of the same entry during database updates. The raw data set after preliminary filtering will be referred to as the initial data set. Data from various databases vary in format. There was a need to integrate these data into one single format. Therefore the data were merged and formulated for the BioWare integrated format. The final preliminary data set was next checked for duplicate entries. This was facilitated by the BioWare preparation module, which generates a sequence comparison report summary, based on pairwise alignment of etries in the data set. Entries having the same sequence (100%) identity were treated as duplicates. Duplicates of the same name and taxon (organism source) were compared; the entry judged to contain the most complete information was kept and the rest were deleted. Duplicates from different species were retained in the data set. Sequences having shared fragment or partial identity, where one sequence was an identical fragment of another, were checked for their uniqueness by referring to journals and cross-references field from the public 39 Materials and Methods databases. Most of the entries that formed earlier versions of entries in the data set were also removed. All the deleted entries were added to the rejected file. The resultant data set was considered as the final data set. The cleaned, final data set is available on-line at http://sdmc.a- star.i2r.org.sg/Templar/DB/snake_neurotoxin which was created using the BioWare-Templar module. In addition, protein 3-D structures were searched in the PDB databases. PDB structures were extracted and added to the svNTX database. Sequence entries and their corresponding 3-D structures were then manually linked. 2.3 Data annotation Nearly 300 published journal articles and papers listed in the database were analysed for data enrichment with functional and structural enrichment. Six new fields containing information normally absent in public database entries were created for each entry. These fields are Action_site, Physiological_function, Critical_residues, Toxin_activity, Binding_affinity, and Miscellaneous. Action_site denotes the site of action of svNTXs. Physiological_function and Toxin_activity refer to published svNTXs function and LD50 values, respectively. Critical_residues reveal the critical amino acid residues that are involved in toxin-receptor interaction. Information from binding studies performed on svNTXs-receptor is represented by the Binding_affinity field. Miscellaneous field refers to other additional information relevant to functional or structural description of a svNTX. The description of data annotation is further discussed under results section. 40 Materials and Methods 2.4 Data analysis The svNTXs database was analysed to form a classification chart for the svNTXs based on structure and function. The disulfide bridge patterns, evolutionary relationships and pharmacological properties were used for the analysis. Sequence comparison of svNTX was carried out using CLUSTALW with the default parameters. From the multiple alignment analysis, it is evident that svNTXs contain highly conserved cysteine residues. Cysteine residues in a protein usually form a disulphide bridge with another specific cysteine residue. Classification of protein family based on cysteine pairing pattern has been used to classify scorpion toxins (Tan et al., 2001). It might be interesting to test this pairing pattern in svNTXs. The use of CysAlign tool in BioWare is diagrammed below. Database in flat file format Plot disulphide bridge pattern for each entry that has disulphide bond information Search through each entry for information on disulphide bond Group entries with similar disulphide bridge pattern Figure 2.1: A schematic representation of CysAlign methodology. 41 Materials and Methods 2.5 Phylogenetic study Signal and leader sequences were removed and only mature, full length amino acid was used for phylogenetic studies. Phylogenetic studies were undertaken only for groups having more than four or more members for better statistical realiability. CLUSTAL-X (Thompson et al., 1997) was used for multiple alignment of amino acid sequences. The pairwise alignment parameters used were a gap opening penalty of 35 and a gap extension penalty of 0.75 whereas the multiple alignment parameters were a gap opening penalty of 15 and a gap extension penalty of 0.30. Each phylogenetic subgroup was generated by using the SEQBOOT program of PHYLIP 3.6a2 (Felsenstein, 1985; 2001). Statistical reliability of the trees was assessed using 100 bootstrap replications. The bootstrap values of 90 and above are considered to be significant. The most parsimonious trees were calculated using the PROTPARS program using the maximum parsimony (MP) method (Saitou and Nei, 1987). MP method was chosen because this program takes into account the number of changes required at the nucleotide level to substitute one amino acid for another. In this scheme, the most accurate phylogenetic tree is one that is based in the fewest changes in the genetic code. The strict consensus trees were obtained using the CONSENSE program (Felsenstein, 2001). The rooted tree diagrams were generated with the TREEVIEW program (Page, 1996). Bee venom PLA2 (Swiss-Prot A59055) and Lynx1 (SwissProt AAF16899) were utilised as outgroups for analysis of presynaptic and postsynaptic NTXs subgroups, respectively. 2.6 Bioinformatics tools used BioWare (Biological Data Warehousing) is a convenient, user-friendly tool for rapid building of data warehouses containing biological information. It contains different programs to retrieve raw data from diverse sources on the Internet, formulate and integrate this information into a central 42 Materials and Methods repository and for rapid building of personal databases using a well-defined framework of the resultant database. This software is divided into three main modules which are used in the creation of svNTX database. 1. BioWare-Retrieve obtains the required data from GenBank, Swiss-Prot and PDB sources. 2. BioWare-preparation allows manual annotation of the data prior to creation of the database. 3. Templar creates a personal searchable database as according to the specifications of the users on the uploaded data file. CysAlign facilitates in the grouping of entries in the database which share similar disulphide pattern, provided the pairing information is present in the entry. These groupings can be used to classify similar protein structurally. Clustal X, is a general purpose multiple alignment program for protein or DNA. BLAST (Basic Local Alignment Search Tool) is a local alignment program that uses a heuristic algorithm to detect relationships among sequences which share only isolated regions of similarity (Altschul et al., 1990). BLAST output assigns a statistical score to sequences similar to query sequence, making it easier to differentiate real and false hits. PHYLIP (the PHYLogeny Inference Package) is a set of modular programs used for inferring phylogenies based on evolutionary trees. It contains a broad variety of analytical methods such as parsimony, distance matrix, and likelihood methods. This program was used to build evolutionary trees in this project. 43 Materials and Methods Section B: Experiment protocols 2.7 Scorpion venom and venom glands The venom and venom glands of the Chinese scorpion, Buthus martensi Karsch were obtained from Wuhan University, China. 2.8 Purification of scorpion venom Lyophilized crude venom (20 mg) was reconstituted in 2 ml water and separated on a gel flitration chromatography using Sephadex G50 column. Peak II of eluant was subjected to RPHPLC (Amersham) using a Jupiter C18 or C4 µBore column. The buffer systems used were 0.1% of trifluoroacetic acid (Buffer A) and 80% acetonitrile in 0.1% trifluroacetic acid (Buffer B). Flow rate was maintained at 1 ml/min. Individual fractions were collected, dried by speed vac, and reconstituted in 100 µl of water and subjected to gene expression studies. 2.9 Purification of snake Bcntx-4 Bungarus candidus crude venom (4 mg) was purified on RP-HPLC (SMART system, Pharmacia) using a Jupiter C4 column. The buffer systems used were 0.1% of trifluoroacetic acid (Buffer A) and 80% acetonitrile in 0.1% trifluroacetic acid (Buffer B). Flow rate was maintained at 1 ml/min. Individual fractions were collected, dried by speed vac, and reconstituted in 100 µl of water and subjected to receptor binding studies. 44 Materials and Methods 2.10 Mass spectrometry determination and N-terminal amino acid sequencing The RP-HPLC purified proteins were subjected to N-terminal amino acid sequencing using a liquid-phase sequencer equipped with an on-line amino acid analyzer after analysis by matrix-assisted light desorption ionization mass spectrometry-time of flight (MALDI-TOF). 2.11 Protein estimation Protein concentrations were determined by Bradford microassay procedure (Bradford, 1976) using Bio-Rad reagents. The samples were diluted 5 times and 1 ml of 5 times diluted dye concentrate reagent was added into the sample. After 15 minutes of incubation, the absorbance was read at 595 nm. A standard curve was drawn using bovine serum albumin (BSA) at concentrations ranging from 2 –10 µg/ml. 2.12 Cell culture and medium Human neuroblastoma cells (ATCC number: CRL2270) were grown in DMEM medium supplemented with 10% fetal bovine serum, 50 units of penicillin, 50 µg/ml streptomycin. Cells were cultured in incubator using 5% CO2 and 95% air at 37°C. 2.13 MTT cell viability assay MTT test is a colorimetric assay system which measures the reduction of 3-(4, 5dimetylthiazole-2-yl)-2, 5-diphenyl tetrazolium bromide; MTT) into an insoluble formazan product by activity of the mitochondrial enzymes in viable cells. 25 mg of MTT was dissolved in 50 ml of DMEM to a concentration of 0.5 mg/ml, filtered and stored in dark until use. A 96 well plate was seeded with 5000 cells per well and allowed to grow for 24 hrs to 80% confluency at 37°C with 5% CO2. The cells were then treated with 600, 400, 200, 100, 45 Materials and Methods 50 µg/ml of BmKII fractions and incubated for 24 hrs. After incubation, the media was removed, cells washed twice with 1x saline and 60 µl MTT was added. MTT incubation was carried out for 1 hr. The medium was removed and the undissolved purple formazan crystals were solubilized in 250 µl of dimethylsulfoxide (DMSO). Complete dissolution of crystals was achieved by shaking plates gently for 10 min at room temperature. Blanks were set up in wells that did not contain cells. Absorbance at 550 nm wavelength was measured spectrophotometrically. Viability of exposed cells was expressed as a percentage of untreated cells (100%). 2.14 Microarray Neuroblastoma cells were treated with 35 µg/ml of BmKII fraction for 18 hrs. Total RNA was isolated according to protocol in section 2.25. RNA isolated was processed and hydridized to each array of the U133 GeneChip™ Array Set according to the protocols described in the GeneChip™ expression analysis technical manual (Affymetrix, Santa Clara, CA). Untreated sample was used as a negative control. Data from each treatment were scaled to an average intensity of 800. Relative mRNA expression levels were expressed as plus or minus fold changes compared with untreated control using Microarray Suite software 5.0 (Affymetrix, Santa Clara, USA). All genes showing 4-fold or more were included in the subsequent analyses. Cluster members were classified according to their biological function as described in the NetAffy database (Affymetrix, Santa Clara, USA). 2.15 Total RNA cleanup Total RNA (20 –50 µg) was cleaned up using RNeasy spin columns (QIAGEN) before microarray analysis. The final volume of total RNA is made up to 100 µl with sterile water. 46 Materials and Methods RLT buffer (350 µl) was then added into the RNA and transferred into a spin column. The tube was spun for 2 min. Eluant was collected and spun again for 2 min. Eluant was discarded and 500 µl of RPE buffer was added in this washing step. Tube was spun again for 2 min and waste discarded. The column was air dried until β-mercaptoethanol was not apparent. RNase-free water (15-30 µl) was added into column, waited for 1 min, followed by centrifugation for 2-3 min. The eluted RNA was quantitated spectrophotometrically at 260 and 280 nm. 2.16 cDNA synthesis A total of 5 µg of cleaned RNA was used for first strand synthesis. 2.16.1 Primer hybridization Reagents used in the first strand synthesis: Total RNA 5 µg T7-d(T) 24 primer (100 pmol/µl ) 1 µl DEPC-H2O for final reaction volume of 20 µl The above reaction mix was incubated at 70°C for 10 min. Then, the tube was briefly pulsed and put on ice. 2.16.2 Temperature adjustment The above reaction was then added into the following reagents and incubated at 37°C for 2 min. 5x first strand cDNA buffer 4 µl 100 mM DTT 2 µl 10 mM dNTP mix 1 µl 47 Materials and Methods 2.16.3 First strand synthesis SuperScript II RT (1 µl) was added to the above tube and incubated at 37°C for 1 hr. The reaction was terminated on ice. The tube was centrifuged briefly to bring down condensation of water on the sides of the tube. 2.17 Second strand cDNA synthesis The second strand synthesis was immediately carried out after the first strand synthesis. The following reagents were added to the first strand synthesis tube. DEPC-treated water 91 µl 5x second strand reaction buffer 30 µl 10 mM dNTP mix 3 µl 10 U/µl E.coli DNA ligase 1 µl 10 U/µl E.coli DNA polymerase I 4 µl 2 U/µl E.coli RNase H 1 µl The contents in the tube were gently tapped and briefly spun to remove condensation. Then, the reaction mixture was incubated at 16°C for 2 hrs in a cooling waterbath. Following 2 hrs incubation, 2 µl [10 U] of T4 DNA polymerase was added and incubated again at 16°C for 5 min. The reaction was terminated by addition of 10 µl 0.5 M EDTA. 48 Materials and Methods 2.18 Cleanup of double stranded cDNA The clean-up was carried out in a two-step reaction. The first step involved the phase lock gels (PLG)-phenol/chloroform extraction and the final step involved ethanol precipitation. PLG form an inert, sealed barrier between the aqueous and organic phases of phenolchloroform extractions. The solid barrier allows more complete recovery of the sample (aqueous phase) and minimizes interface contamination of the sample. A standard phenol/chloroform extraction can be performed as an alternative to the PLG procedure. The PLG tube was briefly spun for 12, 000 x g for 20-30 sec. 162 µl of phenol:chloroform:isoamyl alcohol in a 25:24:1 ratio saturated with 10 mM Tris-HCl pH 8.0, 1 mM EDTA) was added to the final cDNA synthesis preparation. The tube was vortexed briefly. The entire 324 µl cDNA-phenol/chloroform mixture was added to the PLG tube. This suspension was centrifuged at 12,000 x g for 2 min. The upper aqueous phase was transferred to a fresh 1.5 ml tube. In the preceding step, 0.5 volumes of 7.5 N ammonium acetate and 2.5 volumes of absolute ethanol were added to the sample and vortexed. The mixture was centrifuged at 12, 000 x g for 20 min. The supernatant was removed and the pellet was washed with 0.5 ml of 80% ethanol (stored at -20°C). The tube was then centrifuged at 12, 000 x g at room temperature for 5 min. The 80% ethanol was carefully removed and the 80% ethanol step was repeated once again. The pellet was air-dried. The dried pellet was resuspended in a small volume of RNase-free water (12 – 15 µl). 49 Materials and Methods 2.19 Synthesis of biotin-labeled cRNA The RNA labeling transcript step is important for the production of large amounts of hybridizable biotin-labeled RNA targets by in vitro transcription from bacteriophage T7 RNA polymerase promoter. The use of T7 RNA polymerase and biotin-labeled nucleotides, large amounts of single-stranded nonradioactive RNA molecules can be produced during short incubation period. RNA-DNA hybrids have a higher melting temperature than corresponding DNA-DNA hybrids, therefore, single stranded RNA targets offer higher target avidity and greater sensitivity than DNA probes. The RNA targets offer selectivity unavailable with DNA targets – being single stranded, they are strand specific and hybridize more effectively to probes because the target population does not self-hybridize. Microchip array assays effectively used RNA transcripts that are labeled with biotin-modified ribonucleotides. The biotin labeled RNA targets that are hybridized to arrays of DNA probes can be detected by a reporter molecule linked to streptavidin, avidin or anti-biotin antibody. This type of complex can be detected directly by excitation of a fluorophore conjugated to streptavidin or indirectly by using an enzyme conjugate that can produce an insoluble colored precipitate. The following components were added to an RNase-free microfuge tube. Template DNA 1 µg of cDNA Distilled or deionised water to final reaction volume of 40 µl 10x HY reaction buffer 4 µl 10x Biotin labeled ribonucleotides 4 µl 10x DTT 4 µl 10x RNase inhibitor mix 4 µl 20x T7 RNA polymerase 2 µl 50 Materials and Methods The mixture was carefully mixed and collected at the bottom of the tube by a brief centrifugation. The tube was immediately placed in a 37°C waterbath. The tube was tapped gently every 30 – 40 min during the 4 – 5 hrs incubation. The end-product was stored at 20°C. 2.20 Cleaning up and quantifying in vitro transcription (IVT) products. The IVT cleanup reaction is essential to remove unincorporated NTPs. Only one-half of the IVT reaction was used for the cleanup. We employed RNeasy spin columns from QIAGEN as preferred method for IVT cleanup. The pure, eluted IVT product was quantitated using spectrophotometric analysis. For quantification of cRNA using total RNA as starting material, an adjusted cRNA yield was calculated to reflect carryover of unlabeled total RNA. Using an estimated 100% carryover, the following formula was used to determine adjusted cRNA yield. Adjusted cRNA yield = RNAm – (total RNAi) (y) RNAm = amount of cRNA measured after IVT (µg) Total RNAi = starting amount of total RNA (µg) y = fraction of cDNA reaction used in IVT The minimum concentration of purified cRNA must be 0.6 µg/µl before the cRNA can be fragmented for target preparation. 2.21 Fragmentation of cRNA for target preparation The adjusted cRNA concentration was used in this reaction. The following components were added to initiate the fragmentation reaction. 51 Materials and Methods 20 µg cRNA 1 – 32 µl 5x fragmentation buffer 8 µl RNase-free water to 40 µl The final concentration of RNA in the fragmentation mixture can range from 0.5 µg/µl to 2 µg/µl. The fragmentation buffer has been optimized to breakdown full length cRNA to 35 – 200 bases fragments by metal-induced hydrolysis. The fragmentation mixture was incubated at 94°C for 35 min. Reaction was terminated on ice. The undiluted, fragmented sample RNA was kept at -20°C. 2.22 Eukaryotic target hybridization In a hybridization cocktail for a single probe array, the following components were added: Fragmented cRNA 15 µg Control oligonucleotide B2 (3 nM) 5 µl 20X Eukaryotic Hybridization Controls 15 µl Herring Sperm DNA (10 mg/ml) 3 µl Acetylated BSA (50 mg/ml) 3 µl 2X hybridization buffer 150 µl H2O to final volume of 300 µl The frozen stock of 20X GeneChip® Eukaryotic Hybridization Control cocktail was heated at 65°C for 5 min to completely resuspend the cRNA before aliquoting. It contains bioB, bioC, bioD and cre prokaryotic enzymes. BioB, BioC and BioD are genes of the biotin synthesis pathway from the bacteria E.coli. cre is the recombinase gene from P1 bacteriophage. These genes can be labeled and could served as hybridization controls when mixed with labeled 52 Materials and Methods eukaryotic cRNA samples. The antisense strand of B. subtilis RNA controls are used for BioB, BioC and BioD genes. These controls can be spiked into samples during mRNA preparation to monitor the efficiency of target preparation, hybridization, washing and staining. The probe array was equilibrated to room temperature immediately before use. The hybridization cocktail was heated to 99°C for 5 min in a heat block. The probe array and a test array that were filled with 200 µl 1X hybridization buffer were incubated at 45°C for 10 min with rotation. The hybridization cocktail that has been heated at 99°C was transferred to a 45°C heat block or 5 min. The cocktail was spun at a maximum speed in a microcentrifuge for 5 min to remove any insoluble material from the hybridization mixture. The buffer solution was removed from the probe array cartridge and filled with 250 µl of the hybridization cocktail avoiding any insoluble matter in the solution at the bottom of the tube. Probe array was placed in a rotisserie box in a 45°C oven. The probe array was rotated at 60 rpm for 16hrs. 2.23 Washing, staining and scanning After 16 hrs of hybridization, the hybridization cocktail was removed from the probe array and kept in a centrifuge tube. The probe array was filled with 200 µl of non-stringent wash buffer. We employed an antibody amplification wash and stain procedure. Streptavidin phycoerythrin (SAPE) staining reagent was prepared. SAPE was stored in the dark at 4°C. It should not be frozen. The tube was tapped to mix well before preparation of any stain solution. The SAPE stain solution should be prepared immediately before use. 53 Materials and Methods For each probe array to be stained, the following components were combined in a microcentrifuge tube: 2X MES stain buffer 600 µl 50 mg/ml acetylated BSA 48 µl 1 mg/ml SAPE 12 µl distilled water 540 µl The SAPE solution is mixed well and divided into two aliquots of 600 µl each to be used for first and third staining respectively. An antibody mixture was prepared with the following reagents. 2X MES Stain buffer 300.0 µl 50 mg/ml acetylated BSA 24.0 µl 10 mg/ml normal goat IgG 6.0 µl 0.5 mg/ml biotinylated antibody 3.6 µl distilled water 266.4 µl A fluidics protocol was used to test the array chip and test chip. 80 µl of hybridization buffer was added into the test chip and the following steps were used to test the quality of reagents. Post Hyb Wash #1 10 cycles of 2 mixes/cycle with wash buffer A at 25°C Post Hyb Wash #2 8 cycles of 15 mixes/cycle with wash buffer B at 50°C Stain The test probe was stained for 10 minutes in SAPE solution at 25°C Post stain wash 10 cycles of 4 mixes/cycle with wash buffer A at 30°C 2nd stain The probe array was stained for 10 min in the antibody solution at 25°C 3rd stain The probe array was stained for 10 min in SAPE solution at 25°C Final Wash 15 cycles of 4 mixes/ cycle with wash buffer A at 35°C. 54 Materials and Methods Temperature was held at 25°C. At the end of this wash, 80 µl of hybridization buffer was removed from the test chip and mixed back into the rest of 220 µl hybridization buffer. The 300 µl of hybridization buffer was injected into the probe array chip and the following steps were performed in the fluidics station. Post Hyb Wash #1 10 cycles of 2 mixes/cycle with wash buffer A at 25°C Post Hyb Wash #2 4 cycles of 15 mixes/cycle with wash buffer B at 50°C Stain The probe array was stained for 10 minutes in SAPE solution at 25°C Post stain wash 10 cycles of 4 mixes/cycle with wash buffer A at 25°C 2nd stain The probe array was stained for 10 min in antibody solution at 25°C 3rd stain The probe array was stained for 10 min in SAPE solution at 25°C Final wash 15 cycles of 4 mixes/cycle with wash buffer A at 30°C. The final holding temperature is 25°C. The above fluidics protocol was selected and ran using the GeneChip® Fluidics Station 400. At the end of the wash protocol, the probe array was scanned by Affymetrix® Microarray Suite. The laser was warmed up prior to scanning by turning the laser at least 15 min before use. Probe array that was stored at 4°C had to be warmed up to room temperature before scanning. After scanning the probe array, the resulting image data created was stored on the hard drive of the GeneChip® Analysis Suite/ Microarray Suite workstation as a .dat file with the name of the scanned experiment. 55 Materials and Methods 2.24 Microarray data analysis In the first step of the analysis, a grid was automatically placed over the .dat file demarcating each probe cell. One of the probe array library files, the .cif file was used by Microarray Suite to determine the appropriate grid size used. The alignment of the grid was confirmed by zooming in on each of the four corners and on the center of the image. If the grid was not aligned properly, the alignment was adjusted by placing the cursor on an outside edge or corner of the grid. The cursor image will be changed to a small double-headed arrow. The grid will then be adjusted using the arrow keys on the keyboard or by clicking and dragging the borders with a mouse. Affymetrix® Microarray Suite was employed to analyze hybridization intensity data from GeneChip® expression probe arrays. This software calculates a set of metrics that describe probe set performance. The gene expression levels from treated and untreated samples were compared using a comparison expression analysis that is available in the software to calculate a set of comparison metrics. Some of the metrics which were used by a decision matrix to determine a Difference Call for each transcript: Increased (I), Decreased (D), Marginally Increased (MI), Marginally Decreased (MD) or No change (NC). In our microarray experiment, we only took into consideration I and D transcript level call for further analysis. A “fold change” calculation was also computed to indicate the relative change of each transcript represented on the probe array. Only those set of genes having 4 fold change in their expression level were included for further functional annotation. The detailed steps for running the software is available on the Microarray Suite User’s Guide (Affymetrix, Santa Clara, USA). 56 Materials and Methods 2.25 Isolation of total RNA Total RNA was isolated by a single-step method using TRIZOL® (Invitrogen). The total RNA was treated with RNase-free DNase I at 37°C for 20 min and kept at -70°C until further use. The concentration and purity of RNA was then estimated spectrophotometrically at 260 nm and 280 nm. The intregrity of RNA was analysed using 1% denaturing formaldehyde gel elelectrophoresis. 2.26 RNA gel electrophoresis Denaturing agarose-formaldehyde gel electrophoresis was used for the size fractionation of RNA (Lehrach et al., 1977). Container or gel tank in contact with RNA samples were swiped in 70% ethanol. A 1% (w/v) agarose-formaldehyde was prepared by melting 0.5 g of agarose in 43.5 ml of autoclaved water and cooled to 60°C. 5 ml of 10x MOPS, 1 ml of 37% formaldehyde and 1 µl of 10 mg/ml of ethidium bromide were added and casting of the gel was carried out in fume hood. RNA sample was prepared as follows: RNA (0.5 µg – 10 µg) 4.5 µl 10x MOPS buffer 2.0 µl Formaldehyde (pH>4.0, 37%) 3.5 µl Deionized formamide 10.0 µl RNA loading buffer 3.5 µl The sample was mixed and heated to 60°C for 10 min prior to loading and electrophoresis was carried out in 1x MOPS buffer. RNA bands were visualized under UV-light after electrophoresis. The image was recorded, captured and saved using a gel documentation system (Bio-Rad, USA). 57 Materials and Methods 2.27 Real-time quantitative PCR Gene specific PCR primers were designed using the PrimerExpress 2.0 (Applied Biosystems, USA) according to their corresponding mRNA sequences. The primers were designed to yield amplicons of less than 100 base pairs and synthesized by Alpha DNA USA). 18S ribosomal RNA was used as an internal calibrator. The primer sequences for the ten genes examined were listed in Table 2.1. Gene Tm Amplicon Size 58 60 70 bp Rev: 5' CCCTCTCGGAAGCATCCATA 3' Amphiregulin Fwd: 5' ACTCGGCTCAGGCCATTATG 3' Rev: 5' ATGGTTCACGCTTCCCAGAGTA 3' 62 66 68 bp Annexin A2 Fwd: 5' GTGCATATGGGTCTGTCAAAGC 3' Rev: 5' TGGCTGTTTCAATGTTCAAAGC 3' 66 62 72 bp Calponin 3 Fwd: 5' ACATTACAGCCGGTGGACAAC 3' Rev: 5' TCCTTTCTGGGAAGCAACTTTG 3' 64 64 72 bp Cysteine rich protein 1 Fwd: 5' CCAAGTGCAACAAGGAGGTGTA 3' Rev: 5' CCCACATTTCTCGCACTTCA 3' 66 60 92bp Fibroblast growth factor 2 Fwd: 5' AGCGACCCTCACATCAAGCT 3' Rev: 5' CGGTTAGCACACACTCCTTTGATA 3 62 70 77 bp GABA(A) alpha 5 receptor Fwd: 5' CCCCAGACACGTTCTTCCA 3' Rev: 5' TTGTTGGGCGTGGTCATGT 3' 60 58 64 bp Galanin Fwd: 5' GAACAGCGCGGGCTACCT 3' Rev: 5' GGCCATTCTTGTCGCTGAA 3' 60 58 71 bp KRIT2 Fwd: 5' GGAATGCGTCTCTCTCAAGAAAC 3' Rev: 5' TGGCCAGTCACGAACATGTT 3' 68 60 117 bp Neuregulin 1 Fwd: 5' TGTGCAAGTGCCCAAATGAG 3' Rev: 5' ACTGTAGAAGCTGGCCATTACGT 3' 60 68 68 bp Aldehyde dehydrogenase Primers sequences Fwd : 5' GCAGTGAAGGCCGCAAGA 3' Table 2.1: Primer sequences used for real-time PCR. Primers were designed using PrimerExpress 2.0 software (Applied Biosystems, USA). A two-step reaction was used in this study. For each reverse transcription (RT) reaction, the following reagents composition was used. 10x PCR Buffer 1.0 µl MgCl2 (25 mM) 2.2 µl 58 dNTPs (25 mM each of dATP, dCTP, dGTP and dUTP) Materials and Methods 2.0 µl Random hexamers (224 µM) 0.6 µl RNase inhibitor (20 U/λ) 0.2 µl Reverse transcriptase (50 U/λ) 0.3 µl DEPC H2O 2.76 µl A total of 12 µl of RT reaction mixture and 3 µl of total RNA (100 ng/µl) was used to carried out RT reaction. RT reaction was carried out as: 25°C/ 10”, 37°C/ 60” and 95°C/ 5”. PCR was then performed on the RT products. For each PCR reaction, the following reagents were used: SYBR® green mix 25 µl Sense primer (100 nM) x µl Anti-sense primer (100 nM) y µl Sterile water 14.8 µl The PCR amplification was then performed at 50°C for 2 min and 95°C for 10 min per cycle for 40 cycles with each cycle at 94°C for 15 sec and 60°C for 1 min. All reactions were carried out in triplicate using the ABI Prism 7000 SDS (Applied Biosystems, USA). 2.28 Purification of Torpedo californica acetylcholine receptors Preparation of nicotinic acetylcholine receptor from Torpedo californica was carried out according to the procedure described by Ishikawa et al. (1977) with some modifications. 10 g of frozen tissue was defrosted and cut into small pieces. The tissue was homogenized with 20 ml distilled water for 4 min with 3 interval time in a warring blender in ice-cold vessel. The 59 Materials and Methods suspension was then again homogenized in IKA-Werk homogenizer (200 rpm) followed by low speed centrifugation at 3000 x g for 10 min at 4°C. The supernatant was centrifuged at 10, 000 x g for 20 min at 4°C. The pellet was resuspended in 8 ml of Tris buffer and homogenized with natural homogenizer. The homogenate was spun as above and the pellet was resuspended in 5 ml of Tris buffer and centrifuged as above. The pellet then was resuspended in Tris buffer to the concentration of 1 mg/ml, aliquoted in eppendorf tubes and kept at -70°C. The whole procedure was done at 4°C. 2.29 Competitive binding assay Competitive binding assay were performed using nAChR. Increasing concentrations of unlabelled Bc-ntx4 was added to a single concentration of 5 nM 125 I-α-Bgt to study their inhibitory effect on high affinity toxin binding. 2.5 µg of Torpedo membrane was incubated with 125 I-α-Bgt at room temperature for 1 hr in presence of increasing concentrations of competitors in the total volume of 200 µl. Reaction was terminated on ice and the membranes were recovered by centrifugation at 10, 000 x g for 5 min. Membranes were was washed with 1 ml of Tris buffer supplemented with 0.1% bovine serum albumin (BSA) and dried before subjecting to radioactive monitoring in a COBRA Auto Gamma Counter (Parkard Instrument Company, USA). 2.30 Statistical analysis Statistical analyses were performed using unpaired Student’s t test and results were expressed as mean ± S.E. p value of < 0.05 was considered statistically significant. 60 Materials and Methods Section C List of chemicals used: Chemical and solvents are all of analytical reagent grade obtained mainly through National University Medical Institutes (NUMI) laboratory from the following suppliers: Sigma Chemicals Co., St. Louis, MO, USA Bovine serum albumin (BSA), formamide, L-glutamine, MOPS (3,-(N-Morpholino) propanesulfonic acid), DMEM basal medium, MES free acid monohydrate, MES sodium salt, EDTA disodium salt (0.5 M solution), Tween-20. Sigma-Aldrich Goat IgG, anti-streptavidin antibody (goat), MTT Gibco-BRL Gaitherssburg, MD, USA Agarose, fetal bovine serum Pharmacia Bromophenol blue, RNase-free DNase I. Merck 37% Formaldehdye Boehringer Mannheim Deoxyribonucleotides (dATP, dCTP, dGTP, dTTP, dUTP) BDH Ethidium bromide Roche SYBR® Green PCR Master Mix, TaqMan® RT Master Mix. Invitrogen Life Technologies Trizol® Reagant, Acetylated bovine serum albumin (BSA) solution (50 mg/ml) 61 Materials and Methods Promega Corporation Herring sperm DNA Affymetrix, Santa Clara, CA, USA Human genome gene chip U133 Plus 2.0 Array, GeneChip® Eukaryotic Hybridization Control Kit (contains Control cRNA and Control oligo B2) Molecular Probes R-Phycoerythrin Streptavidin Solutions and buffers 2.32 Reagents for PR-HPLC 2.32.1 Buffer A: Trifluoroacetic acid (TFA, HPLC grade) 0.1% (v/v) 2.32.2 Buffer B: Acetonitrile (HPLC grade) 80% (v/v) Trifluoroacetic acid (TFA, HPLC grade) 0.1% (v/v) 2.33 Buffers for RNA clean-up 2.33.1 RLT buffer Commercially available from QIAGEN. Contains guanidine thiocyanate. 10 µl of 14.3 M of β-mercaptoethanol was added to 1 ml of RLT buffer. This mixture was found to be stable for a month. 2.33.2 RPE buffer Commercially available from QIAGEN. 2.34 Buffers for cRNA target hybridization 2.34.1 12X MES stock 62 Materials and Methods MES free acid monohydrate 1.2 M MES sodium salt 0.89 M The reagents was mixed throughly and adjusted to final volume of 1000 ml of autoclaved water. The solution (pH between 6.5 – 6.7) was filtered through a 0.2 µm filter. Solution was stored at 4°C and shielded from light. The solution was discarded if colour turned yellowish. 2.34.2 2X hybridization buffer 12X MES Stock 0.1 M 5 M NaCl 1M 0.5 M EDTA 0.02 M 10% Tween 20 0.1% (v/v) The final volume of buffer was adjusted to 50 ml of autoclaved water. It was stored at 4°C and shielded from light. 2.35 Buffers for array processing, washing and staining 2.35.1 Non-stringent Wash Buffer (Wash Buffer A) NaCl 0.9 M NaH2PO4 0.06 M EDTA 0.006 M 10% Tween-20 0.01 % (v/v) The final buffer volume was adjusted to 1000 ml of water and was filtered through a 0.2 µm filter and stored at 4°C. 2.35.2 Stringent Wash Buffer (Wash Buffer B) 12X MES Stock Buffer 0.1 M NaCl 0.1 M 63 Materials and Methods 0.01 % (v/v) Tween 20 The final buffer volume was adjusted to 1000 ml of water and filtered through a 0.2 µm filter and stored at 4°C. 2.35.3 2X stain buffer 12X MES stock buffer 0.1 M NaCl 1M Tween 20 0.05 % (v/v) The final volume of buffer was adjusted to 250 ml of water and filtered through a 0.2 µm filter. Solution was stored at 4°C and shielded from light. 2.35.4 10 mg/ml Goat IgG Stock The antibody stock was resuspended in 5 ml PBS and stored at 4°C. 2.35.5 20X SSPE buffer NaCl 3M NaH2PO4 0.2 M EDTA 0.02 M 2.36 10X Phosphate-buffered saline (PBS) NaCl 0.2 M KCl 0.0027 M Na2HPO4 0.0081 M KH2PO4 0.00176 M The above reagents were weighted and added into 800 ml distilled water. The pH was adjusted to 7.4 with HCl and topped up with H2O until a final volume of 1000 ml. Stock PBS solution was autoclaved and stored at room temperature. 64 Materials and Methods 2.37 Reagents for RNA gel electrophoresis 2.37.1 Ethidium bromide Ethidium bromide was dissolved in water at 10 mg/ml concentration and stored in a light-tight bottle. The final working concentration was 0.1 µg/ml. 2.37.2 10x MOPS running buffer Morpholinopropanesulphonic acid (MOPS), pH 7 0.4 M Sodium acetate 0.1 M EDTA (pH 8) 0.01 M The above solution was adjusted pH7 and topped up to a final volume of 1000 ml. 2.73.3 DEPC-treated water Diethyl pyrocarbonate (DEPC) 0.2 % (v/v) DEPC was added to 100 ml of deionised water and shaken vigorously to mix. It was incubated at 37°C for 1 hr and autoclaved to inactivate the DEPC. The solution was stored at room temperature. 2.37.4 Deionized formamide Formamide (550 ml) was added to 500 mg Dowex XG8 mixed bed resin for 1h, followed by filtration through Whatman No.1 paper. Deionized formamide was stored at -20°C. 2.37.5 RNA loading buffer Glycerol 50% (v/v) EDTA (pH 8) 1 mM 65 Materials and Methods Bromophenol blue 0.4% (w/v) The above reagents were made up to 10 ml of water and stored at room temperature. 2.37.6 Formaldehdye Formaldehdye (37% v/v) was prepared and stored in a light-tight container at room temperature. 2.38 Buffer for real-time PCR 2.38.1 10x PCR buffer Tris-HCl (pH 8.3) 0.1 M KCl 0.5 M Gelatin 0.01% (v/v) 2.39 Buffer for receptor binding studies 2.39.1 Krebs-Ringer HEPES (KRH) buffer, pH 7.4 NaCl 0.128 M KCl 0.005 M CaCl2 0.0027 M MgSO4 0.0012 M Na2HPO4 0.001 M Glucose 0.01 mM HEPES 0.02 mM 66 Materials and Methods RESULTS Results CHAPTER THREE CONSTRUCTION OF PROTEIN DATABASE OF SNAKE VENOM NEUROTOXINS 3.1 Introduction The most serious effects of snake envenomation are due to neurotoxins (NTXs). For example, the most toxic component in cobra venom is the postsynaptic neurotoxins with an LD50 (i.v.) of 0.05 – 0.2 µg/g of mouse (Tan, 1983). Toxin entries in public DNA and protein databases represent only a tiny fraction of less than 1% of the estimated natural library (Tan et al., 2003). Because of growing number of identified svNTX sequences, it is increasingly difficult to study them by experimentation alone. Detailed bioinformatics analysis offers a convenient methodology for efficient in silico preliminary analysis of possible function of new toxins. The in silico approach can assist in designing experiments for functional characterization of the newly identified svNTX sequences, particularly those identified as novel cDNAs. A bioinformatics approach was utilized in the construction of a svNTXs database. This chapter focuses on the compilation and consolidation of svNTXs data, which were stored in a newly created, specialized database. The entries in svNTXdB have been classified and annotated to enhance new knowledge discovery. It also had a set of tools including structure-function prediction module. Our primary objectives were to facilitate information retrieval and data analysis of enriched and unique compilation of svNTXs extracted from public databases and published reports. Each database entry is then hyperlinked to an external database such as NCBI, SwissProt or EMBL. 3.2 Data acquisition As of April 2003, the svNTXs database contains 272 unique entries of neurotoxin. A preliminary search using BioWare retrieval software with the keyword “Serpentes and Neurotoxin” returned 821 entries on svNTXs. Serpentes keyword was included in the search as it much more representative of all snake species and together with neurotoxin word in the 67 Results search, entries that had both terms were extracted. These 821 entries were the initial data set. Depending on their function, various databases carry a wide range of format. We merged the initial dataset into a BioWare integrated format. Preliminary filtering was carried out to remove nonsnake neurotoxins and replicate entries. Ultimately, 272 entries remained in the dataset, which are unique. This entry was referred to as the final data set. The breakdown of the each entry was listed in Table 3.1. Four entries were found only in the published journal. These were listed in Table 3.2. The majority of the entries in the final data set were mainly complete mature peptides with the signal peptide. Out of 272 entries, 260 neurotoxins had the complete mature peptide and 12 were incomplete. Only 99 neurotoxins out of 272 entries had the signal peptide sequence. The summary of the protein identify was listed in Table 3.3. Table 3.1: Summary of the 272 neurotoxin entries extracted from various sources. 68 Results T o x in F15 Sequence H L L Q F N K M IK F E T R K N A V P F Y A F Y G C Y C G W G G Q R R P K D A T D R C C F V H D C C Y G K L T K C N T K W D IY R Y S L K S G Y IT C G K G T W C K E Q IC E C D R V A A E C L R R S L S T Y K N E Y M F Y P K SRCRRPSETC R e fe re n c e s T o y a m a e t a l., 2 0 0 3 W - I II FVCHNQ Q SSQ PPTTTNCSG G ENKCYKKQ W SDHRG K I IE R G C G C P T V K K G IK L H C C T T E K C N N S a m e jim a e t a l., 1 9 9 7 W - IV L L C H N Q Q S S T S P T T T C C S G G E S K C Y K K R W P T H R G T IT E R G C G C P T V K K G IE L H C C T T D Q C N L S a m e jim a e t a l., 1 9 9 7 D IC L S T P D V K S K T C P P G N ir th a n a n e t a l., 2 0 0 2 M ik a t o x in Table 3.2: Sequence identity for the four unique toxins that are not found in public databases but available in published journals. Sequence Complete Incomplete Missing Total Signal peptide 99 11 162 272 Mature 260 12 272 Table 3.3: Number of the complete, incomplete and missing sequences in the snake venom neurotoxins in the final data set. 3.3 Database features Snake NTX had five major search or extraction tools: BLAST search, Query svNTX, Structure viewer, Download FASTA and Annotate svNTX. BLAST search allows user to perform a sequence similarity search against snake NTX database (Altschul et al., 1997). Users can specify output alignment result in either standard BLAST output or color-coded multiple sequence alignment generated using Mview program (Brown et al., 1998). The Query svNTX feature allows users to search entries in the database by simple keywords such as Naja, bungarotoxin, or ion channel toxin. The search results are displayed in a tabular form as a list containing accession numbers, species and toxin name. Each match in the result output is hyperlinked to the full data record. Structure viewer feature (requires Internet Explorer 6.0 or Netscape 4.75) consists of three-dimensional (3-D) structures of snake venom NTXs that are extracted from PDB. This simple feature allows users to view available 3-D file using Chime viewer or download PDB files of user-specified records. Annotate svNTX is a simple prediction module tool which allows user to predict function of an unknown svNTX. Users can 69 Results also choose to download FASTA formatted files of amino acid from the database under the option Download FASTA. Figure 3.1 shows the typical outlay of the svNTXs homepage. The five major extraction tools were indicated on the left. Figure 3.2 shows the summary of the search result using keyword search “Bungarotoxin”. Figure 3.1: The user interface of the svNTXs database. Description of the five major tools will be discussed in the text. 70 Results Figure 3.2: An output feature of the search (partial) using the keyword “Bungarotoxin”. The accession number labeled blue can be hyperlink to the database records. 71 Results 3.4 Descriptions of the svNTX individual record Each NTX entry in the database is stored as an individual record. A representative record in shown in Figure 3.3. Figure 3.3: An example of an outlay of record available in the database. The individual fields in each record will be explained in the preceding section. This entry shows fields that are 72 Results found mostly in each entry. Complete entries have additional fields for structural and functional information. Each NTX entry in the database was given a unique accession number ‘DBACC’ in the form of [D][six digit number], where the six digit number was the unique descriptor for each record. ‘Date’ field indicates the date when the entry was made. ‘Name’ field contains the name of the toxin used in published journal and in public databases. The ‘Accession’ field provides hyperlinks to corresponding entries of the relevant databases such as GenBank, Swiss-Prot or EMBL where the original sequence was deposited. The organism source of each toxin and its taxonomical classification can be found in the ‘Source’ and ‘Species’ fields respectively. Functional information based on experimental studies from various reports had been included to enhance unique features of the database. These were represented by six fields known as ‘Action_site’, ‘Physiological_function’, ‘Critical_residues’, ‘Toxin_activity’, ‘Binding_affinity’ and ‘Miscellaneous’. The ‘Binding_affinity’ and ‘Critical_residues’ fields are unique in our database and not available in any public domain. The ‘Action_site’ field indicates the site of action in which the NTX acts either presynaptically or postsynaptically. A brief description of the NTX function is denoted by the field ‘Physiological_function’. ‘Toxin_activity’ fields refer to the toxicity in terms of LD50 values. ‘Binding_affinity’ fields refer to the toxin-receptor interaction in terms of Kd or IC50 values. The critical amino acid residues involved in receptor binding and other miscellaneous comments are provided in the ‘Critical Residues’ and ‘Miscellaneous’ fields respectively. Each record has its corresponding reference(s) listed. Structural features of the toxin, such as residues forming the disulfide bridges are described in the field ‘Features’. Putative structural information derived by similarity to known structures by amino acid alignment is indicated as ‘BY SIMILARITY’. A ‘svNTXdB’ sign followed by ‘BY SIMILARITY’ field implies data added by the authors which was not available in the public databases. In addition any ‘Conflict’ field list down the amino acid discrepancies between records of a particular NTX in different databases or published journal. The field 73 Results ‘Translation’ provides the amino acid sequence of the toxin. ‘Structure’ field contain internal hyperlink to the PDB structure stored in the database, subjected to the availability of the 3-D structures. The ‘Reference’ field consists of a list of literature references, with author names and journal titles. Some reference entries have the sign ‘svNTXdB’ which denotes publications that have been added by us which are not listed in any public databases. The svNTX database was largely compiled from public databases, which are unfortunately prone to errors. Common errors that are encountered as summarized in Figure 3.4. For example, entries Q9PSN6, Q91138 and Q91139 in the public database show the origin of these toxins from Naja naja (Indian cobra) when the correct species should be Naja sputatrix (Malayan cobra). Other common errors from these sources were different names for similar toxin and different sequence for similar toxins. Although Swiss-Prot typically provides lethal dose (LD50) values, one particular entry - long NTX OH-5 (P80965) - did not have this information although its LD50 is available in the original paper. These errors were reduced by checking database entries and cross-checking with original publications. Figure 3.4: Summary of the types of errors encountered in the public databases. 74 Results 3.5 Classification of snake venom neurotoxins svNTX data was analysed to form a classification system for prediction of their structure and function. Properties such as cysteine pairing patterns, phylogenetic relationships, and detailed functional and structural classification were considered in order to build a classification chart. Initially, cysteine pairing pattern was analysed as this method has been shown to accurately classify the members of scorpion toxin families (Tan et al., 2003). However, the result was inconclusive as distinct structure-function relationship could not be observed for each disulphide bridging pattern. Although 12 unique disulfide pairing patterns were observed, we could not correlate any significant structure-function relationship because multiple functional groups were observed in one individual disulphide group (Figure 3.5). For example, fasciculins (acts presynaptically and inhibiting acetylcholinesterase) and short-chain neurotoxins (acts postsynaptically and binds to nAChR) in cysteine pairing group 1 (Table 3.4) share similar disulfide pairing pattern but exhibit very different pharmacological functions. Hence, disulfide pairing pattern cannot be used as an indicator for structure-function prediction in snake neurotoxins. One of the more commonly used bioinformatics method for analyzing venom-toxin data is phylogenetic analysis (see Tan et al., 2003). This method had been employed to determine diversification of conotoxins and classification of scorpion and snake toxins (Tytgat et al., 1999; Espiritu et al., 2001; Okuda et al., 2001; Tsai et al., 2002; Fry et al., 2003). However, phylogenetic groups alone did not correlate well to functional groups of svNTXs. Therefore, we decided to classify svNTXs by combining pharmacological function and phylogenetic studies. Phylogeny was determined using maximum parsimony (MP) method to test whether a direct structure-function prediction can be deduced. Members in a clade having a bootstrap value of 90 are grouped together. Groups having 5 or more members will only be considered for phylogenetic analysis. Detailed pharmacological functional data such as site of action and molecular targets of the svNTXs was used based on annotations available in the database. We combined the functional annotation with the MP method to define structure-function classifications. The database currently contains data of 260 full length svNTXs that have welldefined pharmacological functions. 53 (20.4%) proteins belong to the presynaptic NTXs group, 155 (59.6%) proteins belong to the postsynaptic NTXs, 3 (1.2%) have both pre and 75 Results postsynaptic effect, and 49 (18.8%) have other functional properties. Those classified as “other” may have either pre or postsynaptic effects but their exact function(s) are currently unknown. A B C1 C2 C3 C4 C5 C6 C7 C8 C C1 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 D C2 C3 C4 C5 C6 C7 C8 C9 C10 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 F E C1 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C2 H G C1 C1 C2 C3 C4 C3 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 76 C2 C4 C5 C6 Results I C1 J C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C1 C2 C3 C4 C5 C6 L K C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11C12C13C14C15C16 Figure 3.5: Unique disulfide pairing patterns of all the neurotoxins. The C represent the cysteine residue in the mature peptide, followed by a number (n) indicating the nth cysteine in the peptide. 77 Results Gr oups Ent r i es A O57327 BAC78199 P01403 P01432 P01415 Q9YGJ5 Q9W7J7 P25683 Q9W7K0 Q9DEQ3 0901189A Q9W7J9 P25675 P25495 P10808 Q9PRJ7 P01428 P19959 P01424 Q9PRJ6 P83302 Q90VW1 P25494 P01427 P01431 P01420 Q9W717 Q8UW26 P01423 Q9PRJ3 AAB36087 A27580 CAB43097 P59276 P10458 S14003 Q9YGX0 P14613 P59275 P01430 P32879 O57326 Q9YHU9 AAM00185 Q9PRJ0 AAD40971 Q9YGW8 P82462 B P01384 P25670 P15817 P80965 764177A AAC83986 P01395 P01383 P01379 AAC83982 P34073 P25672 P14612 AAC83996 P07526 P01390 O12961 P25668 Q9W726 P01393 P01385 P01381 AAC83985 Q8UW29 C CAA06886 P81783 P29182 P01401 Q9W7I3 Q9YGI1 Q9W796 P25680 Q9W7I4 P01400 P81782 Q9YGJ0 O12963 Q9YGI2 P29181 D PSKFAU AAB36096 Q8AXW2 Q8AXW0 Q8QFW3 P00619 P59018 Q9PTA7 E P10116 P00608 Q8UUI0 Q9DF52 P00628 P20258 P00614 Q9PSN5 F P00979 P00982 P00981 P00980 G Q10755 P24027 I51381 P14420 H P24335 I P00626 J AAC83988 K Q9PTA1 L P00616 P01421 P01425 P01414 P82464 P80495 Q8UW27 P10460 P01437 Q9W7K2 P19960 P01417 W-IV P43445 P25493 N1NJ2P P01433 P80548 P25492 P25676 Q9YGI0 P01438 P81030 Q9PUB7 Q9YGX1 S48648 P01435 P25681 Q91138 P19958 P01434 0901189B P18328 Q9PRI1 P01412 P25497 P80494 P01429 P01426 Q9YGC4 Q9YGW9 Q9W7K1 Q9W7J6 Q9PWJ4 P34075 P83346 P01422 Q91139 AAB50805 Q9YGC7 Q9YHV0 P34076 Q9W727 671059A Q9YGJ6 P14534 Q9DE57 P01416 Q9YGI8 P82849 Q9PRJ5 Q9PSN6 P01418 W-III Q9YGC2 P80958 P25496 AAC83981 P01391 Q9W729 P25674 P01394 P15816 P82662 AAC83987 CAA72434 P01397 P01387 P25673 P01389 BAA32992 P01386 P25671 CAB51841 AAC83997 P15815 P01398 P01380 P01396 O42256 P58370 P25679 P15818 P29180 Q9YGH9 Q9YGI7 CAD18848 O42255 P01399 P29179 O93422 P82935 Q9PTA5 P17934 P00617 Q90251 Q9PU97 Q9PTA6 Q8QFW4 P00618 PSKF3U P20259 Q8UUH8 P00610 P00609 P23026 P00629 Q8UUH9 Q8UUH7 Q02471 P11407 P14424 P14421 Q8JFG0 P13495 O12962 Q8UW28 O42257 Q9W7J5 AAC83990 P80156 P01382 P01388 P25667 AAC83995 Q9W797 Table 3.4: The distinct disulfide pairing pattern of mature svNTXs. Functional grouping could not be observed using this method. For example, fasciculin (P01403) and short neurotoxins in Group A share similar disulfide pairing pattern but different pharmacological function. The entry in red is a partial sequence of a short neurotoxin. 78 Results The classification trees of the full length svNTXs was depicted in Figure 3.6. This classification system was broken into six layers. Layer 1 depicts the NTX site of action; layers 2 and 3 represent functional and structural properties of NTXs respectively; layer 4 denotes the molecular target of each svNTX, and layer 5 represents the subclassification of NTX based on phylogeny relationship. The final layer represents group labels. Presynaptic NTXs exhibit at least eight different functions (Figure 3.6, layer 2), and can be classified into five major groups: 1) NTXs that inhibit acetylcholine release; 2) NTXs that facilitate acetylcholine release either by blocking voltage gated potassium channel or some unknown mechanism; 3) NTXs that inhibit acetylcholinesterase and 4) NTXs that block calcium channel; and 5) NTXs that exhibit multiple functions such as myotoxicity, hemorraghic/hypotensive or bactericidal activity. Group 1 neurotoxins had two distinct groups, those possessing inter disulfide (S-S) chains and those without. The molecular target of these neurotoxins is the phospholipid membrane. The group 1 of svNTXs formed six phylogenetic subgroups (Figure 3.6; layer 6). Toxins in groups 1-A1, 1-A2, 1B-3 and 1B-4 originate from the Elapidae snake family and groups 1B-1and 1B2 were from Viperidae family toxins. Several interesting features can be observed from Figure 3.6. Phospholipase A2 KPA2 (Q9DF52) from Bungarus caeruleus and phospholipase A2 He (Q9PSN5) from Notechis scutatus scutatus in group 1B-4 exhibit additional function such as anticoagulant or myotoxic activities. However, three other members (P00628, P00629, P00616) from this group do not show anticoagulant activity. This could suggest that, based on evidence from phylogenetic analysis, these three svNTXs could possibly have anticoagulant/myotoxic activity that is yet to be determined. One svNTX from group 1B-2 (F15; Toyama et al., 2003) and two svNTXs from group 1B-3 (P00608 and P00610) also demonstrated additional functional properties besides neurotoxicity (Figure 3.6; Table 3.5). Some of the functions were myotoxicity, hemorrhagic and bactericidal activities. It may be possible that other neuoroxins members in these groups possess multiple function(s) as well. Groups 2A1-3 of presynaptic neurotoxins from Dendroaspis facilitate acetylcholine release and block voltage-gated potassium channel (Harvey and Anderson, 1991). Group 2B was found to be a unique group – it is the only three-finger neurotoxin reported to date to act 79 Results presynaptically to facilitate acetylcholine release (Kuhn et al., 2000). Group 3 consisted of presynaptic neurotoxins that inhibit acetylcholinesterase activity. Acetylcholinesterase-type NTXs had so far been isolated from African mambas (Dendroaspis) and are cross-linked by four disulfide bonds. Group 4 consisted of only one member, lethal peptide I (P24335) which contained only 1 disulfide bond and found to block calcium channels at the presynaptic membrane (Aiken, 1992). Group 5 svNTXs had multiple functions in vivo such as myotoxicity, anticoagulant, hemorraghic/ hypotensive or bactericidal effects. In contrast, postsynaptic svNTXs fall into two major groups based on their interaction with either nicotinic acetylcholine receptor (nAChR) or L-type calcium channels. The postsynaptic neurotoxins that interact with nAChR were subdivided into five subgroups such as short, long, weak, kappa, and the unknown group of svNTXs (Groups 6 – 10). Groups 6 – 9 NTXs formed a similar folding pattern of three loops adopting the three-stranded antiparallel α-pleated sheet but group 10 svNTXs had a non-3 finger fold with one disulfide bond (P24335). We employed a phylogenetic analysis on the short-chain neurotoxins and found six subgroups. Suprisingly, all short-chain neurotoxins originate from the Elapidae family (Figure 3.6). From extensive literature search, ten short-chain neurotoxins have been reported to interact with muscle-type nAChR (Marchot et al., 1988; Weber and Changeux, 1974; Pillet et al., 1993; Gong et al., 1999, 2000). One interesting neurotoxin was fasciatoxin from group 7B-1 (P14534). It is an unusual short-chain neurotoxin from Bungarus fasciatus (Liu et al., 1989). This protein is 63 amino long but has a unique C-terminal tail of PSTPST not found in any other short-chain neurotoxins. So far, short-chain neurotoxins are found to interact specifically with muscle-type nAChRs. Critical residues that are involved in the molecular recognition of toxin-receptor were studied elsewhere by individual chemical modifications (review by Endo and Tamiya, 1991). Lys-27 and Lys-47 are critical for receptor binding (Hori and Tamiya, 1976; Ishikawa et al., 1977; Faure et al., 1983). Pillet et al. (1993) suggested that three ionogenic residues Lys-27, Asp-31 and Arg-33 in erabutoxin a from L. semifasciata are involved in direct interaction with AChR. 80 Results Layer 1 Layer 2 Layer 3 Layer 4 Inter S-S chain Layer 5 Phospholipid Inhibits Ach release No inter S-S chain Blocks voltage gated K+ channel Facilitates Ach release Presynaptic membrane Inhibits acetylcholinesterase Blocks Ca2+ channel Phospholipid Intra S-S chain GRP 1A-1 2 GRP 1A-2 3 GRP 1B-1 9 GRP 1B-2 12 GRP 1B-3 5 GRP 1B-4 Kv1.1 3 GRP 2A-1 Kv1.2 2 GRP 2A-2 Kv1.6 1 GRP 2A-3 Intra S-S chain 1 GRP 2B Intra S-S chain 2 GRP 3 Intra S-S chain 1 GRP 4 1 Myotoxic, anticoagulant , hemorraghic/hypotensive and bactericidal activity No inter S-S chain Phospholipid GRP 5A-1 1 GRP 5A-2 3 GRP 5A-3 1 Muscle-type nAChR α-7 neuronal nAChR long Blocks neuromuscular transmission 4 unknown short unknown kappa unknown Binds L-type calcium channel unknown Presynaptic & postsynaptic membrane unknown α-3 neuronal nAChR 2 α-7 neuronal nAChR 1 unknown weak Hemorraghic/ hypotensive activity Intra S-S chain GRP 6A-1 GRP 6A-2 GRP 6B 3 Muscle-type nAChR Postsynaptic membrane Layer 6 14 1 GRP 6C-1 42 GRP 6C-2 4 GRP 7A-1 2 GRP 7A-2 1 GRP 7A-3 3 GRP 7A-4 1 GRP 7B-1 75 GRP 7B-2 GRP 8A GRP 8B 3 GRP 8C-1 3 GRP 8C-2 Muscle-type nAChR 3 α-7 Neuronal nAChR 3 unknown 3 GRP 9C Muscle-type nAChR 1 GRP 10 GRP 9A GRP 9B GRP 11 2 GRP 12 2 Phospholipid No inter S-S chain No inter S-S chain 1 2 GRP 13 GRP 14 GRP 15 49 Figure 3.6: Classification of snake NTX based on structure, function and phylogenetic information. Only full length neurotoxins are included in this classification. Boxed number refers to the total number of neurotoxins sharing the same physiological function. Layer 1 denotes the neurotoxin site of action; layers 2 and 3 represent functional and structural properties of neurotoxin respectively; layer 4 refers the molecular target of each svNTX layer 5 represents the subclassification of neurotoxin based on phylogenetic relationship. Layer 6 represents group labels. 81 Results Long-chain neurotoxins from Elapidae family were subclassified into five subgroups. Several members of long-chain neurotoxins interact with alpha-7 neuronal nAChR (Group 6B), in contrast to short-chain neurotoxins. Phylogenetic analysis could not be performed on this group because it has only three members at present. To date, five and three long-chain neurotoxins were demonstrated experimentally to interact with muscle-type nAChR (Group 6A-1 and 6A-2; Figure 3.6) and alpha-7 neuronal nAChR (Group 6B-1) respectively (Ishikawa et al., 1977; Chang et al., 1993; Servent et al. 1998). The presence of the fifth disulfide bond in long-chain neurotoxins had been implicated in the interaction with neuronal nAChR (Servent et al., 2000). Arg-33 was especially important for this binding specificity (Antil et al., 1999). It would be of great interest if the important residues that interact with these two receptors can be delineated. Forty five long neurotoxins were not experimentally determined whether they interact with either muscle-type or neuronal nAChR. Phylogenetic analysis indicated two main groups within this orphan group: groups 6C-1 and 6C-2 (Figure 3.7E). svNTXs in group 7A-1 and 7A-2 did not have the consensus Lys-27, Asp-31 and Arg-33 residues which were implicated in receptor binding (Pillet et al., 1993). However, svNTXs in groups 7A-3 and 7A-4 (except P01426) possessed conserved residues of Lys-27, Asp-31 and Arg-33 for receptor interaction. Known kappa neurotoxins have 65-66 amino acid residues. Their disulphide bonding pattern had not yet been determined. One distinguishing functional property of kappa svNTXs was their ability to interact with α3 neuronal nAChR (Figure 3.6, Group 8A). So far, kappa svNTXs were found only in Bungarus species and it was believed that they do not interact with muscle nAChR. In addition, the specific receptor of six kappa neurotoxins remain unknown (Group 8C-1 and C2) and phylogenetic analysis showed two distinct groupings. Phylogenetic analysis was not performed on weak neurotoxins because of the small number of toxins (Groups 9A-C). This group of toxins was found to interact weakly with muscle- and α7neuronal nicotinic acetylcholine receptor (Poh et al., 2002; Utkin et al., 2001). To date, our database contains 86, 50, 8 and 6 full length short, long, kappa and weak NTXs, respectively. Certain postsynaptic neurotoxins (Figure 3.6, group 11) interact with L-type calcium channel (Strydom, 1977; Yasuda et al., 1994). Crotoxin (P24027) and phospholipase A2 HTe 82 Results (Q9PSN5) in group 12 exerted their effect postsynaptically (Bon et al., 1979; Francis et al., 1995). However, their specific postsynaptic actions are yet to be determined. Three toxins in groups 13 and 14 exerted neurotoxic effect both pre- and postsynaptically (Francis et al., 1995; Bon et al., 1979). Specific functions of toxins in group 15 are still unknown. They are designated as neurotoxin homologs, neurotoxin-like proteins, or neurotoxin isoforms that are still not well studied. The individual records of neurotoxin in each group in Figure 3.6 are listed in Table 3.5 according to their GenBank Accession Number. 83 Results Table 3.5: Summary of the individual entries based on GenBank Accession Number of each member in each group as depicted in Figure 3.6. Field in red bold and underlined indicates the presence of entry in more than one group. Fields in italic (F15, W-III and W-IV) represents entries found in published journal but not in any public database. 84 Results A B 85 Results C D 86 Results E outgroup P01383 Q9W7J5 P13495 Group 6C-1 Q42257 P25671 P25672 P25673 764177A P25668 P01388 P01389 P01390 P25674 P01386 P07526 P01387 P01393 P01396 P25667 P01397 P01395 P01394 P25670 RAA32922 0901189A 0901189B Q8UW29 Q8UW28 P01381 P01380 P34073 P01384 P01385 ACC83990 ACC83998 ACC83992 ACC83985 ACC83986 ACC83987 CAB51841 ACC83995 ACC83997 ACC83996 87 Group 6C-2 Results F 88 Results G 89 Results H Figure 3.7: Phylogenetic trees performed using parsimony analysis of all the mature svNTX. Bootstrap values are the result of 100 replicates. Only bootstrap values of greater than 90 in the each internal node are grouped as one group. The outgroup Bee venom PLA2 (Swiss-Prot A59055) and Lynx1 (Swiss-Prot AAF16899) were utilised as outgroups for analysis of presynaptic and postsynaptic NTXs subgroups respectively. Outgroup was used to give a better representation of the evolutionary relationship. A and B: Presynaptic neurotoxins; C: Presynaptic neurotoxins with multiple functions; D: long neurotoxins with known receptor binding; E: orphan long neurotoxins; F: short neurotoxins with known receptor binding; G: orphan short neurotoxins with unknown receptor functions and H: orphan kappa neurotoxins with unknown receptor functions. 90 Results 3.6 Receptor binding studies to test the in silico prediction tool in the database A native Bc-ntx4 protein (B. candidus toxin with an unknown function) was tested using competitive binding studies with 125I-α-Bgt in muscle (Torpedo) nAChR. The binding activity studies of Bc-ntx4 on AChR isolated from T. californica showed weak affinity even in the micromolar range (Figure 3.8). Using the ‘Annotate svNTX’ function in the database, Bc-ntx4 was predicted to be a weak neurotoxin. This further validates the proof-of-concept of the in silico prediction tool. Amino acid sequence of Bc-ntx4 is LTCLICPEKYCQKVHTCRDEENLCVKRFYEGKRFGKKYPRGCAATCPEAKPHEIVECC STDKCNK (AY611643). 10-10 10-9 10-8 Figure 3.8: Competitive binding studies of 10-7 125 105 I-α-Bgt and native Bc-ntx4 to nAChR of Torpedo receptor. Data are average values of duplicate determinations. 91 10-6 Results Figure 3.9: Output of the annotation tool in svNTXs. Bc-ntx4, a protein of unknown function was purified from RP-HPLC and annotate in silico using Annotate svNTX in the database. The output result returns a putative function of weak neurotoxin – like activity. This agrees with our experimental result in Figure 3.8 which found Bc-ntx4 to be a weak neurotoxin. 92 Results 3.7 Conclusion Snake NTXs are a large family of active peptide with considerable sequence homology, but with different biological properties. Sequence, functional and structural information on snake venom neurotoxins (svNTXs) are scattered across multiple sources such as journals, books, and public databases, with very limited functional annotation. A svNTXs database was created at http://sdmc.i2r.a-star.edu.sg/Templar/DB/snake_neurotoxin. This database can also be found under Swiss-Prot Toxin Annotation Project website (http://www.expasy.org/sprot/). At present, 272 NTXs sequences are available in the database and each sequence contains fully annotated function and literature references. An annotation tool to aid functional prediction of newly identified NTXs as an additional resource for toxinologists. In addition, a classification system based on structure-function and phylogenetic relationship derived from the 272 NTXs was also developed to allow better prediction tools. 93 Results CHAPTER FOUR SCREENING FOR POTENTIAL THERAPUETIC AGENTS USING TOXICOGENOMIC APPROACH 4.1 Introduction Scorpion venoms consist of biologically active proteins that contribute to the pathological effects of the venom. Traditionally, venoms have been studied with the aim of understanding the structure and function of individual toxins and their mechanism of action. The typical method is to isolate the protein, followed by biochemical characterization and then determination of its biological activity in vitro and in vivo. Recently, proteomics studies on Buthidae venoms was employed to analyze toxic fractions from the venom of Brazilian scorpion, Tityus serrulatus in order to shed light on the molecular composition of this venom and to facilitate the search of pharmacologically active compounds (Pimenta et al., 2001). Using this method, the researchers are able to detect 380 different components present in the scorpion venom. These studies clearly indicate that scorpion venom represents a wide variety of proteins. Thus, scorpion venoms may be considered to be a naturally occurring ‘library’ of biologically active components that could be potentially exploited for drug discovery. To date, Buthus martensi Karsch (BmK) contains more than 70 different peptides, toxins or homologues (Goudet et al., 2002). These toxins have been found to act on Na+, K+ and Cl- channels. Technological advances in microarray applications now allow for a rapid, broadband analysis of the functional effects of substances on expression of genes in cells and tissues. This investigation is to assess the use of scorpion venoms as pharmaco-active libraries. The hypothesis of the study is that at LD50 concentrations (where no overt phenotypic effect of the venom on cells in tissue culture is observed), the venom will produce effects on the gene expression profiles of the cells that may lead to some of the scorpion venom components as pharmaceutically useful compounds. 94 Results 4.2 Purification of scorpion venom using gel filtration chromatography Gel filtration separates proteins based on their molecular sizes. Protein mixtures are applied to a gel filtration column containing a matrix of defined pore size, eluted with an aqueous buffer and collected as individual fractions and analysed. Sephadex G50 was used to isolate proteins in the range of 1.5 – 30kD. 20mg of lyophilized BmK crude venom was reconstituted in 2 ml water and separated using gel filtration. Two fractions were obtained (Figure 4.1). The first peak, BmKI consisted of high molecular weight proteins (10-20kD). The second peak, BmKII containing low molecular weight proteins (3-7 kD) was subjected to further studies. BmKII 1.8 1.6 BmKI 1.4 OD, 280nm 1.2 1 0.8 0.6 0.4 0.2 0 0 10 20 30 40 -0.2 Fraction, 1.5ml Fig 4.1 Separation of BmK crude venom using gel filtration. 95 50 60 70 Results 4.3 MTT test The cell survival test (Figure 4.2) showed that BmKII is not toxic to human neuroblastoma cells even at a concentration of 500 µg/ml. At 35 µg/ml, the cell survival was at 99%. Hence, 35 µg/ml of BmKII was subsequently used in all experiments treated with this venom. 110 100 90 % cell survival 80 70 60 50 40 30 20 10 [BMKII] ug/ ml 0 0 100 200 300 400 500 600 concentration of BMKII, ug/ ml Figure 4.2: Cell survival test of human neuroblastoma cells treated with various concentration of BmKII. 96 Results 4.4 Total RNA isolation Total RNA was isolated from human neuroblastoma cells treated with BmKII at a concentration of 35 µg/ml and incubated for 18hrs. The intregrity of RNA was found to be acceptable for further studies as they showed two distinct bands for 28S and 18S ribosomal RNAs (Figure 4.3). 1 2 28S 18S Figure 4.3: Total RNA isolation from human neuroblastoma cells treated with 35µg/ml BmKII for 18hrs. Lane 1: untreated neuroblastoma cells; lane 2: 35µg/ml BmKII-treated neuroblastoma cells. 4.5 Microarray analysis Neuroblastoma cells were treated with partially purified BmKII (35 µg/ml) for 18 hrs. The global gene expression changes were monitored by microarray genechip procedure. Results from microarray analysis showed 875 genes that were four-fold upregulated upon treatment with BmKII fraction. The 875 genes were analyzed in terms of their function using molecular information available at http://www.affymetrix.com and published journals in NCBI database. The summary of the function of 875 genes is listed in Table 4.1. From the microaray analysis, ten genes were finally selected. They were found to be involved in neurogenesis and angiogenesis pathways as well as other genes involved in metabolic pathway, neurotransmission, development and signaling pathway. These ten genes were listed in Table 4.2. Figures 4.4 – 4.10 show the results of cluster analysis (Clustals 1-7) which contain the ten selected genes. 97 Results Actin/myosin binding protein Angiogenesis Anti coagulant Anti inflammatory Anti proliferative/ Tumor suppre. Anti-apoptosis Anti-differentiation Anti-oxidant Apoptosis Cell adhesion Cell cycle Cell motility Detoxification Development Differentiation DNA repair/damage Endocytosis/Exocytosis Homeostasis Immune response Inflammation Inhibitor of growth suppressor Metabolic pathway Neurogenesis Protein biosynthesis Protein degradation/turnover RNA binding protein RNA synthesis/processing Signalling pathway Solute carrier/ channel Transcription factor Transport/ Trafficking Change in of gene expression + + + + + + + + + + + + + + + + + + unchanged + + + + unchanged + + + + Table 4.1: Summary of the 875 genes function that was altered by treatment of BmKII in human neuroblastoma cell. Functions of the genes were annotated using published literature in NCBI. + and – sign indicate up- and down-regulation of genes respectively. 98 Results Gene name Fold change Neurogenesis Amphiregulin Fibroblast growth factor 13.9 5 Angiogenesis Krit-1 0.21 Others Calponin 3 GABA (A) receptor alpha 5 Annexin A2 Galanin Cysteine rich protein 1 Aldehyde dehydrogenase 1 Neuregulin 1 (sensory and motor-neuron derived isoform) 0.2 103 4.3 9.2 803 81.6 7.8 Table 4.2: List of the ten selected genes after microarray gene chip analysis. The gene expression profiles of these ten genes were further studied using real-time PCR. 99 Results 12 EST/DB_XREF=gi:A44 PRO tudor domain containing 1 plectin zinc finger protein 237 phospholamban (PLN) selectin E (SELE) cDNA FLJ12153 fis clone MAMMA 100458 lipoprotein lipase (LPL) gamma aminobutyric acid A receptor small inducible cytokine subfamily B tumor necrosis factor deleted in azoospermia (DAZ4) FEA=EST/DB_XREF=gi:10743006 hypothetical protein VPS33A hypothetical protein MGC10731 FEA=EST/DB_XREF=gi:2402080 mRNA for PQBP-1b EVH1 domain regulating protein cellular growth-regulating protein caldesmon II FEA=ES/DB_XREF=gi:796550 cDNA:FLJ22585 caspase 8, apoptosis-related cysteine protese (CASP 8) myosin, heavy polypeptide 13, skeletal muscle (MYH13) hypothetical protein FLJ13166 FEA=EST/DB_XREF=gi:5856236 regulated in glioma (RIG) cysteine rich motor neuron (CRIM1) matrilin rich precursor (MATN3)creatine kinase, mitochondrial 1 PAC296K21 on chromosome X cysteine knot superfamily 1, BMP antagonist 1 FEA=EST/DB_XREF=gi:10837689 protein kinase DYRK4 hypothetical protein FLJ23119 retinal outer segment membrane protein 1 (ROM1) FN5 protein (FN5) integrin beta 4 (ITGB4) neuregulin 1 (NRG) solute carrier family 22 calcineurin A1 sequence from clone RP11-55H7 mitogen activated protein kinase kinase 6 (MAP2K6) FEA=EST/DB_XREF=gi:6228495 DKFZP5640962 clone hepatocyte transcription factor mRNA FEA=EST/DB_XREF=gi:13295908 FEA/EST/DB_XREF=gi:10811389 FLJ23029 clone RP5-843L14 on chromosome 20 rTS beta protein dentin phosphoryn Figure 4.4: Cluster 1 genes identified using Genesis® software. Two genes, GABA (A) receptor and neuregulin 1 in this cluster were selected for further studied. Lane 1: untreated neuroblastoma cell; lane 2: neuroblastoma cell treated with 35 µg/ml BmK II for 18 hrs. Green bar and red bar represent gene downregulation and upregulation respectively. 100 Results 12 ubiquitous TRP motif, Y isoform (UTY) cDNA DKFZp586E121 hypothetical protein FLJ22477 clone FLB4941 PRO1292 lipocalin 2 insulin-like growth factor 1 (IGFBP-1) hypothetical protein FLJ14146 FEA=EST/DB_EST=gi:11954150 cathepsin X precursor paired immunoglobulin-like receptor alpha junction plakoglobin (JUP) cDNA FLJ22868 hypothetical protein FLJ20272 fibroblast growth factor 2 (FGF2) FEA=EST/DB_XREF=gi:10809262 FK506 binding protein 1B (FKBP1B) vaccinia related kinase 2 (VRK2) cDNA FLJ11303 hypothetcial protein (RIF) lengsin (LGS) Figure 4.5: Cluster 2 genes identified using Genesis® software. Fibroblast growth factor, FGF2 in this cluster which is involved in neurogenesis was further investigated. Please refer to Figure 4.4 for legends. 101 Results 12 protein tyrosine phosphatase FEA=EST/DB_XREF=gi:2824690 CD2-associated protein clone HQD131 KIAA0941 FEA=EST/DB_XREF=est7 putative DNA dependent ATPase cDNA DKFZp584F059 est501657122R1 hypothetical protein FLJ12178 SUMO-1 specific protease clone 4484560 KIAA0042 FEA=EST/DB_XREF=gi:5364202 tryptophan 2,3-dioxygenase serologically defined colon cancer antigen 1 human autonomously replicating sequence (ARS) FEA=EST/DB_XREF=gi:10284299 Ran-binding protein FEA=EST/DB_XREF=gi: 119428450153 est 02485841F1 KIAA1109 protein FEA=EST/DB_XREF=gi:500781 FEA=EST/DB_XREF=gi:12803262 vav2 oncogene KIAA0395 gene estbc44bc8 helicase II FEA=EST/DB_XREF=gi:2574859 esttz22b10 FEA=EST/DB-XREF=gi:8159499 Krit1 KIAA0270 gene KIAA0372 gene product clone RP11-15H23 clone HQD105 structural maintenance of chromosome (SMC) family member W D-2 protein FEA=EST/DB_XREF=gi:10797095 nucleobindin 2 FEA=EST/DB_XREF=gi:13338044 FEA=EST/DB_XREF=gi:5803553 FEA=EST/DB-XREF=gi:11016007 Notch homolog 3 FEA=EST/DB_XREF=gi:5885103 hypothetical protein FLJ23321 glycoprotein nmb heparan sulfate sulfotransferase cadherin 11 granule associated RNA binding protein KIAA0203 FEA=EST/DB_XREF=gi:5850810 FEA=EST/DB_XREF=gi:5837414 tetratricopeptide repeat domain 3 ribonuclear protein subantigen subunit unknown protein clone MOC:3860 zinc finger protein 195 FEA=EST/DB_XREF=gi: 5382740 FEA=EST/DB_XREF=gi:5390527 FEA=EST/DB_XREF=gi:1158223 cDNA FLJ202742 forkhead box F1 decorin variant c membrane-associated nucleic acid binding protein KIAA0914 protein FEA=EST/DB_XREF=gi:3948440 FEA=EST/DB_XREF=gi:1940853 insulin-like growth factor 2 receptor FEA=EST/DB_XREF=gi:1128208 KIAA0995 protein cDNA clone FL23455 sequence from clone RP11-108L7 homoe box c10 filamin c FEA=EST/DB_XREF=gi:1337022 myosin, heavy polypeptide 3 titin Figure 4.6: Cluster 3 genes identified using Genesis® software. Krit-1 is a gene involved in angiogenesis and its gene expression was further studied. Please refer to Figure 4.4 for legends. 102 Results 12 FEA=EST/DB_XREF=gi:6704806 aspartyl tRNA synthetase FEA=EST/DB_XREF=gi:10744829 plasminogen activator FEA=EST/DB_XREF=gi:5003552 neuritin dystrophin associated glycoprotein tissue factor pathway inhibitor beta aldolase c prostaglandin-endoperoxide synthase dikkopf homolog 3 hypothetical portein FLJ10493 FEA=EST/DB_XREF=gi:10828334 MHC class I antigen alpha-2 type IV antigen dihydropyrimidine dehydrogenase selenium binding protein 1 FEA=EST/DB_XREF=gi:2348877 FEA=EST/DB_XREF=gi:2789059 FEA=EST/DB_XREF=gi:5894201 FEA=EST/DB-_XREF=gi:2797331 unknown protein W W -domian containing oxidoreductase (W W OX) HLA class I heavy chain Cw1 antigen FEA=EST/DB_XREF=gi:847688 HLA-B mRNA cDNA DKFZp4348044 B-cell RAG associated protein FEA=EST/DB_XREF=gi:3500885 cDNA DKFZp434N0813 collagen type IV FEA=EST/DB_XREF=gi:5036103 FEA=EST/DB_XREF=gi:110D9578 cDNA FL21183 proalpha 1 procollagen FEA=EST/DB_XREF=gi:384900 collagen alpha 2 chain precursor FEA=EST/DB_XREF=gi:2321327 lumican FEA=EST/DB_XREF=gi:5868436 FEA=EST/DB-XREF=gi:11006648 selenoprotein P sal-1 like protein lipopolysaccharide-binding protein (LBP) matrix metalloproteinase 2 (MMP2) FEA=EST/DB_XREF=gi:970050 calponin 3 KIAA0970 protein plelenomorphicadenoma gene-like e-syn protooncogene cNDAFL22535 FEA=EST/DB_XREF=gi:2042123 protein kinase c latrophilin transcription factor c-maf FEA=EST/DB_XREF=gi:3232123 HSP0040 protein FEA=EST/DB_XREF-gi:1685105 protocadherin gamma subfamily A platelet derived growth factor C chondroitin sulfate proteoglycan 2 est602020842F1 fibulin FEA=EST/DB_XREF=gi:5143449 proteoglycan PGM OB-cadherin-1 FEA=EST/DB_XREF=gi:11112418 Figure 4.7: Cluster 4 genes identified using Genesis® software. Calponin 3 is a gene involved in angiogenesis and its gene expression was further studied. Please refer to Figure 4.4 for legends. 103 Results 12 cDNA DKFZ434H1419 cystineglutamate exhanger FEA=EST/DB_XREF=gi:5769332 nucleosome assembly protein 1-like 2 cell cycle progression 8 protein KIAA0843 protein immunoglobulin heavy chain gene CYR61 PRO02259 clone MGC:2854 cDNA FLJ20660 RNA binding motif protein 3 FLJ23353 angiogenic inducer, 61 CYR61 hypothetical protein FLJ11151 peptidylprolyl isomerase D FEA=EST/DB_XREF=gi:3228954 hypothetical protein HSPCO31 FEA=EST/DB_XREF=gi:5233843 hypotheticla protein FLJ22551 lipocortin (LIP) 2 gene hypothetical protein FLJ13840 ADO21 protein lipopolysaccharide specific-repsonse-68 protein FEA=EST/DB_XREF=gi:2875596 Cdc6-related protein FEA=EST/DB_XREF=gi:2321394 pyruvate dehydrogenase kinase casein kinase 1 v-crk avian sarcoma virus oncogene homolog (CRK) CDC6 homolog DMC1 hypothetical protein FLJ20224 regulator for ribosome resistance homolog clone MGC:12262 ATPase hypothetical protein FLJ14054 tyhymidine kinase 1 RNA-binding protein potassium channel (TW K-1) gamma-aminobutyric acid (GABA) A receptor uroplakin 1B pseudouridine synthase 1 FEA=EST/DB_XREF=gi:4068966 insulin receptor substrate-2 (IRS2) tetraspa NET-6 protein pregancy associated plasma protein 1 FEA=EST/DB_XREF=gi:10302396 transcription factor CP2 fibronectin leucine rich transmembrane protein 3 (FLRT3) FEA=EST/DB_XREF=gi:5177504 BCG induced integral membrane protein clone RP-4-76112 testin metastatic-suppresor gene CC3 15-hydroxyprostaglandin dehydrogenase prostaglandin E synthase gene encoding homeobox related protein FEA=EST/DB_XREF=gi:AL578310 hypothetical protein DKFZp586H0623 cell death regulator aven cDNA DKFZp5860051 estrogen-responsive B box protein cDNA: FLJ23564 fatty acid coenzyme A ligase hypothetical proteinFLJ12525 secreted frizzle-related protein 1 FEA=EST/DB_XREF=gi:11006713 epiregulin gro-beta fatty acid hydroxylase signal transducer mRNA DEADH polypeptide nephropontin clone 747H23 mitochondrial ribosomal protein S12 ATP-binding cassette FEA=EST/DB_XREF=gi:4685039 solute carrier family 3 interleukin 18 cytokeratin 8 eukaryotic translation initiation factor 5A prgrammed cell death 5 gene tumor protein D52-like 1 trp-met fusion oncogene FEA=EST/DB_XREF=gi:10373121 phosphogluconate dehydrogenase (PGD) FEA=EST/DB_XREF=gi:12677244 Ets-related transcription factor FEA=EST/DB_XREF=gi:6576051 peroxisome proliferative activated receptor gene SIH003 gene aldehdye dehydrogenase 1 S100 calcium-binding protein A10 hypothetical protein PP5395 clone GS1-99HB CD24 Kunitz-type protease inhibitor retinoic acid induced 3 aspartate beta-hydroxylase (ASPH) FEA=EST/DB_XREF=gi:2910111 cDNA FLJ20161 clone MGC:10332 gamma glutamyltransferase 1 mRNA for clone 9112 receptor tyrosine kinase-like orphan receptor 1 Figure 4.8: Cluster 5 genes identified using Genesis® software. Aldehdye dehydrogenase was upregulated 81.6 fold and its gene expression profile was further investigated. Please refer to Figure 4.4 for legends. 104 Results 12 asparagine synthetase fibroblast growth factor receptor 2 decay accelerating factor for complement N-isoform-exon 11 hypothetical portein PR00758 FEA=EST/DB_XREF=gi:1093055 growth arrets and DNA-damage-inducible cDNA DKFZp701H087 single Ig LI-1R related molecule FEA=EST/DB_XREF=gi:12900950 MAD homolog 6 aspartyl beta-hydroxylase 2.8 kb transcript Tat-interacting protein (30kD) junctate spindle pole body protein FEA=EST/DB_XREF=gi:1015897 KIAA0064 gene product polyadenylate binding protein-interacting protein 1 apolipoprotein C-1 transcription factor 2 hepatic nucler factor hypothetical portein FLJ20607 CD24 signal transducer S100-calcium binding protein A4 carnonate anhydrase VIII lymphotoxin beta receptor FEA=EST/DB_XREF=gi:11252643 FEA=EST/DB_XREF=gi:2263220 S100 calcium binding portein P RAB4 hypothetical protein FLJ20273 hypothetcial protein FLJ23235 rhodanase hypothetical protein FLJ20130 gamma aminobutyric acid A receptor solute carrier family 21 mitogen-activated protein kinase kinase kinase 8 keratin 7 cytochrome P450 (CYP4F11) hypothetical protein FLJ12591 cytochrome P450 (CYP24) glucosaminyl transferase 3 clone 018603 gene cysteine-rich protein 1 (CRIP1) carbohydrate sulfotransferase 6 cytochrome b-245 GRO1 oncogene hypothetical protein FL20452 serine protease inhibitor ATPase, Na+/K+ transporting KIAA0748 secreted apoptosis related protein 2 1, 2 cyclic-inositol-phosphate phosphodiesterase ferrodoxin reductase cDNA FLJ21431 FEA=EST/DB_XREF=gi:2525497 FEA=EST/DB_XREF=gi:6903427 FEA=EST/DB_XREF=gi:13134301 hypothetical protein FLJ20495 Figure 4.9: Cluster 6 genes identified using Genesis® software. Cysteine-rich protein 1 has the highest gene upregulation when studied using microarray. Please refer to Figure 4.4 for legends. 105 Results 12 Keratin 19 Keratin 10 FEA=EST/ DB_XREF=gi: 11130198 FEA=EST/ DB_XREF=gi: 3740962 aldo-keto reductase family 1 (AKR1B1) Clone MGC: 5333 UDP-glucose dehydrogenase (UGHD) aldo-keto reductase family 1 isoform dihydrodiol dehydrogenase aldehyde dehydrogenase 3 family cytochrome b-5 reductase chlordecone reductase homolog cytochrome P450 insulin-like growth factor-binding protein 4 pseudochlordecone reductase tumor necrosis factor superfamily FEA=EST/ DB_XREF=gi:12673408 UDP glycosyltransferase 1 family Hypothetical protein MGC5395 FEA=EST/ DB_XREF=gi: 1040569 Tumor antigen (L6) cDNA: FLJ 22893 Sjorgens syndromesoleroderma autoantigen 1 (SSSCA1) Ribonucleotide reductase M2 polypetide IAP homolog C (MIHC) Periplakin (PPL) Annexin A2 (ANXA2) ATP binding cassette, sub-family C Thioredoxin reductase 1, slone MGC:1920 Hypothetical protein FLJ10430 Brain acid-soluble protein 1 CCAAT enhancer binding protein (CEBP) MHC class I polypeptide-related sequence B (MICB) LPS-induced TNF-alpha factor (PIG7) Potassium intermediate small conductance calcium-activated channel NAD+-dependent 15 hydroxyprostaglandin dehydrogenase (PDGH) LIM protein Hypothetical protein MGC5338 Kynureninase Nuclear receptor subfamily O (NROB1) Gravin Galanin Aldehyde dehyrogenase 3 (ALDH3) Heat-shock 70kD protein 1A Id-1h diaphorase inhibitor of DNA binding 3 FEA=EST/BD_XREF=gi:11769659 Leucine zipper, down-regulated in cancer 1 Midline 1 Solute carrier family 21 Phosphotidic acid phosphorylase type-2c Glutamate-cycteine ligase FEA=EST/BD-XREF/gi:4188641 Proteoglycan 1 Epithelial-specific transcription factor Glutamate cysteine ligase Crk-associated substrate related protein Clone MGC:4419 FEA=EST/DB_XREF=gi:1383407 Tropomodulin 3 Serum inducible kinase Small inducible cytokine subfamily A FEA=EST/DB_XREF=gi:13545549 J domain containing protein 1 (JDP1) Dual specificity phosphatase 1 (DUSP1) Beta 1,4 glycosyltransferase Nonspecific crossreacting antigen RAB4 Protein tyrosine phosphotase Hypothetical protein FLJ11149 Neuregulin 1 (NRDG), transcript variant 1 SMDF Annexin A4 Proliferating cell nuclear antigen Pirin Tissue inhibitor of metalloproteinase 3 (TIMP3) Secretory granule proteoglycan peptide core Desmoplakin FEA=EST/DB_XREF=gi: 12800058 Aldehyde dehydrogenase 3 Transcription factor 8 Insulin-like growth binding protein 6 KIAA0307 gene product Solute carrier family 16 FEA=EST/DB_XREF=gi: 10739541 KIAA0869 protein NIT protein 2 Clone 640 unknown Hematological and neurological expressed 1 mRNA for hepatocyte nuclear factor-3 FEA=EST/DB_XREF=gi: 11591542 Fatty acid binding protein 5 Tat-interacting protein (30kD) Hypothetical protein FLJ10847 Clone MGC: 12282 FEA=EST/DB_XREF=gi: 12335213 Syndecan 1 Thyroid autoantigen FEA=EST/DB_XREF=gi:12933969 FEA=EST/DB_XREF=gi:10732039 FEA=EST/DB_XREF=gi:4435781 Hypothetical protein FLJ11798 Hypothetical protein clone 1010 FEA=EST/DB_XREF=gi: 1727858 Latexin protein (LXN) Glutaminyl peptide cyclotransferase Hypothetical protein FLJ11264 Fucosyltransferase 8 Fatty acid co-enzyme A ligase 40S ribosomal protein S27 isoform dickkopf homolog 1 (DKK1) aldo-keto reductase family 1 amphiregulin Figure 4.10: Cluster 7 genes identified using Genesis ® software. Three genes in this cluster, annexin A2, galanin and amphiregulin were chosen for further studied. Please refer to Figure 4.4 for legends. 106 Results 4.6 Quantitative Real-time PCR analysis of genes affecting neurogenesis and angiogenesis Quantitative real-time PCR is one of the most powerful and sensitive gene analysis techniques. Its versatility has made it one of the fastest growing tools in molecular biology. The easier way to monitor fluorescence in quantitative PCR is to use a dye that emits light upon intercalation in double stranded DNA (Wittwer et al., 1997). The intensity of the fluorescent signal is directly proportional to the amount of dsDNA species in the reaction. Denature Anneal Extend Figure 4.11: Schematic representation of real-time PCR with the SYBR Green I dye. SYBR Green I dye (black diamonds) becomes fluorescent (green diamonds) upon binding to double-stranded DNA, providing a direct method for quantitating PCR products in real time. Gray arrow head represent the forward primer. SYBR® Green assay was chosen in this studies as it is cheaper and relatively easy to use than TaqMan® probes. Ribosomal RNA present in the total RNA sample is used as an internal standard. Optimum concentration of total RNA for real-time PCR detection was found to be 100ng. A non-template control in which sterile buffer replaced template RNA served as the negative control. The amount of target was normalized to ribosomal RNA. The following formula was used to calculate the level of gene expression: 107 Results ∆CTS = ∆CT (sample) – ∆CT 18S RNA ∆∆CTS = ∆CTS – ∆CTS (of respective control) Relative gene expression = 2-∆∆CTS In order to confirm the level of gene expression in the microarray study, real-time PCR was performed on these ten genes using SYBR® Green assay. Approximately 100 ng of total RNA was used for real-time PCR experiment. Krit1 and calponin gene expression were found to be downregulated in both microarray and real-time PCR (Table 4.3). The other eight genes were found to be upregulated in both microarray and real-time PCR. In summary, the gene expression changes in microarray experiment were positively confirmed using real-time PCR (Table 4.3 and Figure 4.12). Amphiregulin Krit1 FGF2 Calponin 3 GABA(A) receptor Annexin A2 Galanin Cysteine rich protein ALDH Neuregulin Microarray 14.00 -5.00 5.00 -6.80 104.00 4.30 9.20 803.00 81.00 7.80 Real-time 2.90 -22.00 1.10 -60.00 3.10 5.20 3.20 2.50 433.00 1.20 Real-time SD 0.40 0.38 0.23 1.43 0.25 0.02 0.13 0.26 0.13 0.17 Table 4.3: Changes in gene expression level as detected by microarray and real-time PCR. SD represents standard deviation. 108 Results 900.00 Microarray 800.00 Real-time 700.00 600.00 Fold change 500.00 400.00 300.00 200.00 100.00 0.00 Amphiregulin Krit1 FGF2 Calponin 3 GABA(A) receptor Annexin A2 Galanin Cysteine rich protein ALDH Neuregulin -100.00 -200.00 Gene Figure 4.12: Gene expression profiles of ten genes studied using microarray and realtime PCR. Real-time PCR was repeated twice and carried out in triplicates. 109 Results 4.7 Further purification of BmKII using reverse phase-high performance liquid chromatography After confirming the expression of the ten genes, BmKII was then subjected to RP-HPLC. The RP-HPLC separation of any peptide or protein mixture is dependent upon the strength of the hydrophobic interaction of each component in the mixture with the hydrophobic surface of the column matrix and the elution strength of the organic solvent in the mobile phase. As the concentration of the organic solvent increases, the elution of the polar species occurs first followed by the elution of non-polar species. Peptide or protein mixtures are applied to a RP column containing a chromatographic matrix with a defined hydrophobic character. The absorbed peptides or proteins are eluted in order of least to most strongly bound molecules by increasing the organic solvent concentration in the elution buffer, collected as individual chromatographic fractions, and analysed separately. The main difference between hydrophobic interaction and reverse phase matrices is the relative hydrophobicity of the matrix, with the reverse phase matrix having greater hydrophobicity. In this method, the stationary phase is hydrophobic (non-polar), while the mobile phase is polar. The functional groups normally attached to the silica gel are the alkyl chains such as C18 (octyl). Venom polypeptides and toxins have compact spatial structure which allows their charge and hydrophobic character to be expressed mainly on the surface of the molecule. Partially purified BmKII venom was successfully separated into discernable peaks by RPHPLC using the Jupiter C18 column. The column was equilibrated with 0.1% trifluoroacetic acid (TFA). The absorbed protein was eluted with 0.1% TFA at a flow rate of 1 ml/min. A linear gradient (30 – 50%) of 0.1% TFA in water (Buffer A) and 0.1% TFA in 80% acetonitrile (Buffer B) was applied for 20 min. Several proteins peaks were obtained during the gradient elution. Once the protein fractions are collected, they are dried by speed-vac, resuspended in sterile water and re-dried by speed vac again. In this way, the BmKII fraction was divided into nine small subfractions (Figure 4.13). Each subfraction was pooled and its protein concentration determined using Bradford assay. The individual fraction was examined by real-time PCR (Table 4.4 and Figure 4.14) for its effects on expressions of genes in neuroblastoma cells. 110 Results RP1 RP2 RP3 RP4 RP5 RP6 RP7 RP8 RP9 70 5000 4500 60 4000 3500 mAU 3000 40 2500 2000 30 1500 20 1000 500 10 0 31 37 42 47 53 -500 58 63 69 0 Fraction, ml/min Figure 4.13: RP-HPLC of BmKII from scorpion venom. This profile shows the BmKII fractions containing small molecular weight protein of 7kD. 124 0 25001.0 Results 4.7.5 Effects of BmKII subfractions RP5 and 6 on six selected genes Fractions RP5.2, RP6.2, RP6.3 and RP6.4 were subjected to another round of RP-HPLC and found to contain single peaks (Figures 4.19- 4.22). Hence, they were considered a relatively pure sample for further characterization. The MALDI-TOF analysis confirms that all fractions contain a major peak of about 7kD (Figures 4.23). Two concentrations of 10 ng/ml and 50 ng/ml of fractions RP5.2G1, RP6.2F4, RP6.3F4, RP6.3F5 and RP6.4F7 were tested on neuroblastoma cells and the gene expression changes measured using real-time PCR. Figure 4.24 and Table 4.6 show the gene expression profile of Krit1, galanin, FGF2, amphiregulin, neuregulin and GABA (A) treated with 10 ng/ml of the five fractions. Krit1 Galanin 7 FGF2 Amphiregulin 6 Neuregulin GABA(A) Fold change 5 4 3 2 1 F7 6.4 RP F5 6.3 RP F4 6.3 RP -1 F4 6.2 RP G1 5.2 RP 0 Fraction Figure 4.24: Real-time PCR assay of six genes using 10 ng/ml of subfractions RP5 and 6. RP5.2G1 RP6.2F4 RP6.3F4 RP6.3F5 RP6.4F7 Krit1 Fold SD Galanin Fold SD FGF2 Fold SD Amphiregulin Fold SD Neuregulin Fold SD GABA(A) Fold SD 1.08 1.70 1.87 1.69 1.46 0.04 0.17 0.18 0.42 0.31 0.40 1.63 0.21 0.77 0.42 0.02 0.38 0.27 0.53 0.31 0.10 0.14 0.27 0.42 0.33 0.10 0.14 0.27 0.42 0.33 4.40 5.38 3.50 6.13 4.57 0.09 0.22 0.17 0.42 0.32 0.08 0.15 0.19 0.42 0.31 0.08 0.15 0.19 0.42 0.31 0.45 0.73 0.53 0.67 0.60 0.01 0.14 0.20 0.43 0.30 Table 4.6: Relative level of gene expression of the six genes using 10 ng/ml subfractions of fractions RP5 and 6. 125 Results 20 Krit1 18 Galanin 16 FGF2 14 Neuregulin Amphiregulin GABA(A) Fold change 12 10 8 6 4 2 0 RP5.2G1 RP6.2F4 RP6.3F4 RP6.3F5 RP6.4F7 -2 Fraction Figure 4.25: Real-time PCR assay of six genes using 50 ng/ml of subfractions RP5 and 6. RP5.2G1 RP6.2F4 RP6.3F4 RP6.3F5 RP6.4F7 Krit1 Fold SD Galanin Fold SD FGF2 Fold SD Amphiregulin Fold SD Neuregulin Fold SD GABA(A) Fold SD 1.19 2.20 8.00 1.00 1.70 0.29 0.14 0.23 0.21 0.44 17.55 1.44 4.10 0.80 1.80 0.10 0.17 0.11 0.10 0.42 2.60 0.77 4.30 0.90 2.10 0.11 1.21 0.14 0.05 0.41 2.10 1.10 4.20 0.76 1.70 0.12 0.11 0.15 0.08 0.42 2.44 0.10 3.38 0.85 1.50 0.10 0.12 0.10 0.05 0.42 5.80 3.90 11.20 3.72 5.21 0.11 0.17 0.19 0.13 0.43 Table 4.7: Relative level of gene expression of six genes using 50 ng/ml subfractions of fractions RP5 and 6. At low concentration of 10 ng/ml treatment, amphiregulin and krit1 genes are consistently upregulated. Galanin, FGF2, neuregulin and GABA (A) genes showed similar pattern of gene downregulation. However a higher concentration of 50 ng/ml treatment showed very varied level of gene expressions. Galanin was the most highly upregulated gene in RP5.2G1 (Table 4.7 and Figure 4.25). Interestingly, GABA (A) receptor gene was found to be consistently 126 Results upregulated across the five treatments. In RP6.3F5, all the genes except for GABA (A) receptor were downregulated (Table 4.7 and Figure 4.25). 4.8 N-terminal sequencing of the selected five subfractions RP5 and 6 N-terminal sequencing was performed on fractions RP5.2G1, RP6.2F4, RP6.3F4, RP6.3F5 and RP6.4F7 purified on RP-HPLC column was determined by automatic Edman degradation using a Procise-HT (Model 494) pulsed liquid-phase Protein Sequencer attached to a 140C PTH amino acid analyzer (Applied Biosystems, Inc., USA). The sample containing 1-5 nmol of protein was dissolved in 200 µl of 0.1% TFA and 10 µl was used for sequence determination. The N-terminal sequence of the 5 fractions was determined up to 27 amino acid residues. The results of the N-terminal sequencing is listed in Table 4.8. Residue number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 RP5.2G1 7202 Da V R D G F I A D P K Protein fraction RP6.2F4 7016 Da D R D A Y I A D P E N A V Y A G N E RP6.3F4 7031 Da G R D A Y I A D S E N T Y T A L N P Y G N D L T RP6.3F5 7024 Da G R D A Y I A D S E N T Y T A K N P Y N D L T RP6.4F7 7028 Da G R Y I A D S E Table 4.8: Results of the N-terminal sequencing of five fractions. Amino acid residues are indicated by the standard one-letter abbreviations. 127 Results Blast search on the five fractions showed highest percentage similarity to known neurotoxins from Chinese scorpions (Table 4.9). Protein RP5.2G1 showed similarity to bukatoxin and toxin BmKT precursor, both which are alpha toxins from B. martensi. Both toxins bind to the receptor at site 3 of the sodium channel and specifically prolong the action potential by blocking the sodium channel inactivation. The interaction of alpha-toxin to the receptor is voltage dependent. RP6.2F4 has similar identity to two toxins, BmK-IV and BmKalphaTx13 both alpha-type neurotoxins. These toxins bind to sodium channels and inhibit the inactivation of the activated channels, thereby blocking neuronal transmission. It is interesting that fractions RP6.3F4 and 6.3F5 displayed high protein sequence similarity with makatoxin I. Both toxins shared similar sequence except at position 21 where leucine is replaced with lysine in RP6.3F5. Makatoxin I is also an alpha toxin, where it binds to sodium channel and prolong the action potential by blocking the sodium channel inactivation. In addition, fraction RP6.4F7 displayed highest protein similarity to makatoxin I and BmKVIII. Both toxins belong to the alpha toxin family. Fraction Toxin identity Percentage similarity 87% 87% GenBank Accession Number P82815 Q95P69 RP5.2G1 Bukatoxin Toxin BmKT precursor (BmK T) (Antitumor-analgesic peptide) RP6.2F4 Alpha-like neurotoxin BmK-IV (BmK4) (BmK-M4) Alpha-neurotoxin TX13 precursor (BmKalphaTx13) 78% 78% P58328 Q9NJC8 RP6.3F4 Makatoxin I (MkTx I) 88% P56569 RP6.3F5 Makatoxin I (MkTx I) 84% P56569 RP6.4F7 Makatoxin I (MkTx I) BmK-VIII (BmKVIII) (BmK8) 80% 80% P56569 P54135 Table 4.9: Blast search of the five peptides. 4.9 Conclusion Scorpion venom BmKII was found to alter the gene expression pattern in human neuroblastoma cell. 875 genes were upregulated by four-fold in our preliminary microarray study. Six genes involved in neurogenesis and angiogenesis pathways were selected for further gene expression analysis using real-time PCR. Crude venom BmKII was further separated into 128 Results nine individual fractions and fractions 5, 6 and 7 were found to modulate gene expression of six of the genes. Fraction RP5.2 consistently caused highest gene upregulation in the six chosen genes with RP6.3 causing downregulation in GABA (A) receptor. The major toxin in the five subfractions was found to be alpha-toxins from Buthus martensi. Alpha-toxins have been shown to bind to sodium channel to cause prolonged channel inactivation. This study has demonstrated that alpha-toxin may be exploited to bring about neurogenesis and angiogenesis. 129 Discussion DISCUSSION 130 Discussion CHAPTER FIVE DISCUSSION Section A 5.1 Neurotoxin database A specialized database has been constructed using bioinformatics and for structure-function studies on snake venom neurotoxins. The toxins data that are scattered across all databases are finally consolidated into a single repository. This cleaned and annotated data set can give a better insight into data representation, and also into the structure-function relationships of the svNTXs. Currently, the svNTXs database contains 272 entries of neurotoxins. This number is expected to increase exponentially with time. BioWare provides a platform for easy update of new data from any public databases. The objectives of building a svNTX database for improved data management and comprehensive analysis of the data have been fulfilled in this study. The svNTX database is largely complied from public databases which can be prone to errors. Any errors or mistakes in the database have been reduced by cross checking with published journal. This database is intended to aid in the molecular analysis snake venom neurotoxins by facilitating the selection of important experiments and design of experimental protocols. Collected dataset of svNTXs have allowed for better structure and functional classification. This information on the structural and functional prediction had lead to a building of a prediction tool in the database. We tested native Bc-ntx4 protein, a B. candidus toxin with unknown function, using competitive binding studies with 125I-α-Bgt in both muscle (Torpedo) nAChR . The binding activity studies of Bc-ntx4 on AChR isolated from T. californica showed weak binding (Figure 3.8). Using the ‘Annotate svNTX’ function in the database, Bc-ntx4 was predicted to be weak neurotoxins. This further validated our proof-of-concept of the in silico prediction tool. 130 Discussion The second aim of this bioinformatics study was to classify svNTXs according to structure and function relationship based on several approaches. The first approach was to study cysteine pairing pattern in the svNTXs dataset. It revealed 12 interesting disulphide pairing pattern. Information for disulfide bridge patterns were only found in 251 entries but were absent in 21 entries. Some of the cysteine pairing groups had one or two members which formed insufficient representatives for classification, as these patterns could be due to sequencing errors. In addition, fasciculins (that act presynaptically by inhibiting acetylcholinesterase) and short svNTXs (that act postsynaptically and bind to nAChR) share similar disulfide pairing pattern but exhibited very different functions (Table 3.3). Hence, disulfide pairing pattern cannot be used as an indicator for structure-function prediction. The phylogenetic relationships of the three finger snake venom toxins have been extensively reviewed (Dufton 1984; Tamiya and Yagi, 1985; Dufton and Hider 1991; Fry et al., 2003). Dufton (1984) had systematically examined 139 homologous short and long svNTXs and cytotoxins from elapid snake venoms and grouped the toxins according to similarity. In spite of this, no clear picture has emerged to connect the structure-function relationship based on phylogeny. Phylogenetic studies provide for better understanding of any evolutionary pattern in svNTXs. Protein parsimony analysis available in PHYLIP statistical software was used to classify the svNTXs. 15 specific evolutionary groups were obtained and all the members shared similar function. With the exception of several members, some entries in each group have multiple functions. It could be due to the fact that additional functions in other members are yet to be found. Interestingly, some neurotoxins exhibit multiple functions unlike toxins from scorpion venoms. Some of the toxins that exhibit multiple functions are listed in Table 3.6. The svNTXs database revealed several interesting features. A thorough systematic characterization of svNTXs, to our knowledge has not been carried out. We fill this gap with the construction of clear and concise classification table based on structure-function and phylogeny relationship (Figure 3.6). This table can also be used to predict function of newly discovered snake neurotoxin. The svNTXs database had several special features which are sets it apart from other sequence databases: (i) 3-D structure feature viewer (ii) functional annotation of individual entries, and (iii) functional properties prediction tool. 131 Discussion The field of toxinology is growing rapidly especially in terms of information provided by cDNA and protein data in the public database. The availability of a specialized database allows easier systematic data analysis and also enables incremental data analysis upon updating with new data. This database and analysis system will serve as an example for bioinformatics application in the studies of snake neurotoxins. The present work has laid the foundation for a more detailed and more systematic studies of svNTXs. The prediction module available in our database can be used for functional prediction of any novel neurotoxins cloned or characterized in the future. We envisage that increasing number of svNTXs in the future will make bioinformatics an attractive tool to speed up experimental research. 5.2 Conclusion and future studies This section focused on a systematic bioinformatics approach towards building a database for svNTX and their structure-function study. The database contains functional and structural information on svNTX gathered from various sources. Each record in the database, originally from the public databases, was enriched by extracting information from the literature and incorporating this into the svNTX database. The publically-available database may facilitate bioinformatics study of structure-function of svNTX. In addition to the tools available in svNTX, BLAST search, Query svNTX, Structure viewer, Download FASTA and Annotate svNTX, this database can be further enriched with tools that allow dynamic phylogeny. Dynamic phylogeny will allow users to construct phylogeny trees on the spot in the database Then, any new evolutionary relationship of novel sequences can be checked with the existing sequences for structure-function prediction. As a proof of concept, an experimental procedure was carried for an unknown snake neurotoxin. This toxin was found to be a weak neurotoxin based on in vitro and in silico approaches. 132 Discussion Section B 5.3 Screening of scorpion venom for therapeutic peptides Scorpion venoms are a rich resource of bioactive peptides. Accumulated data have demonstrated that scorpion neurotoxins affect the ion permeability of excitable cells by specific interaction with calcium, potassium, sodium, and chloride ion channels (Catterall, 1980). Detailed knowledge about the biological properties of the venom of the Chinese scorpion, Buthus martensi Karsch (BmK), has been limited to neurotoxic components present in the venom of this species. BmK has been used in traditional Chinese medicine to treat epilepsy, antihyperalgesic and reversal effects on circulation failure (Zhou et al., 1989; Wang et al., 2000; Peng et al., 2002). Although many peptides have been identified in this venom, no modulators of genes affecting biological processes such as angiogenesis and neurogenesis have been identified. The effect of BmKII fractions on cell viability was first tested using MTT assay. As shown in Figure 4.2, the venom is non-toxic to cells. This is further supported by the evidence that the scorpion venom showed a LD50 value of 2.4 mg/kg following intraperitonial injection and a minimum lethal dose (MLD) of 0.074 mg/kg after intracerebroventricular injection in mice (Goudet et al., 2002). From the MTT assay, cells were found to show a 95% cell viability at 35 µg/ml of BmKII. Thus gene expression studies were carried out at 35 µg/ml BmKII using a human neuroblastoma cell line. Ten interesting genes that are involved in angiogenesis, neurogenesis and ion channel modulation have been identified. In order to confirm the microarray results, real-time PCR was used and the results supported each other. One hypothesis was that BmKII partially purified fractions might possibly contain modulators of these ten genes. The BmKII fraction was further purified into nine different subfractions, termed RP1 – 9 using RP-HPLC. Each fraction was tested individually and the expression of genes were monitored using using real-time PCR. Fractions RP5, 6, and 7 caused the greatest 133 Discussion change in gene expression of those ten putative genes. Hence, these fractions were used for further studies. From extensive literature search six genes: galanin, krit1, neuregulin, GABA(A) receptor α5 subunit, amphiregulin and FGF2, are involved in many biological function in vivo such as nerve regeneration, angiogenesis, cell proliferation and survival. The summary of the six genes functions are described as below. 5.3.1 Galanin Neuropeptides are a heterogenous class of biologically active substances that modulate the function of neuronal circuits. These neuropeptides co-localized with the classical neurotransmitters and determine a unique immunochemical profile of distinct neuronal populations throughout the brain (Mazarati et al., 2001). These neuropeptides are released from neurons in response to stimulus entering the spinal cord, binds to specific receptors on target neurons and modulate the action of classical neurotransmitter in either negative or positive fashion (Drake et al., 1994; Boehm and Betz 1997). Galanin is a 29 or 30 amino acids long neuroendocrine peptide, originally isolated by Tatemoto et al. 1983 from porcine upper intestine. Galanin has been identified in many species, including rodents and primates (Langel and Bartfai, 1998). It is not a member of any known family of neuropeptides, despite repeated efforts to discover related peptides. This protein binds to family of receptors that belong to a superfamily of G-protein coupled receptors (Amiranoff et al., 1989; Consolo et al., 1991). To date, three different receptor subtypes of galanin receptor (GALR) have been cloned (GalR1, GalR2 and GalR3) from rodents and humans (Mazarati et al., 2001; Figure 5.1). Ligand and receptor interactions modulates release of neurotransmitters, affects learning and memory feeding, nociception and nerve regeneration (Vrontakis et al., 2002). Galanin mRNA and protein are found in specific neuronal systems in the brain, spinal cord, as well as peripheral nervous system (Zhang et al., 1993a & b, 1995; Merchenthaler et al, 1993). The protein exerts a strong neuroendocrine effect by modulating the release gonadotrophins, 134 Discussion insulin, prolactin, growth hormone, and somastostatin (Vrontakis et al., 1991; Bartfai et al., 1993). It is a potent inhibitor of the release of a number of neurotransmitters and hormones, including acetylcholine, dopamine, insulin and gastrin (Rossowski and Coy, 1989; Pramanik and Ogren, 1992). A distinctive feature of galanin gene expression is its dramatic upregulation by estrogens, after nerve injury, in the basal forebrain of Alzheimer’s patients and during development (Vrontakis et al., 1989; Villar et al., 1989; Crawley, 1993; Xu et al., 1996). The galanin mRNA and protein levels also change in some acute and chronic inflammation especially the neurons where galanin is strongly upregulated following inflammation (Ji et al., 1995). In the preliminary screening of all the BmKII fractions, galanin gene was upregulated the most in RP5.2G1. This may be proved useful as a potential agonist. Galanin agonists have been used in preventing anoxic damage and have additional advantage over Ca2+ channel blockers. An application of galanin receptor agonists would be useful in preventing oxidative damage during open heart surgery. Galanin receptor agonist can also be used to enhance the release of growth hormone without effecting the diurnal rhythm of this process and therefore appear as attractive agents to increase growth hormone secretion in humans (Bauer et al., 1986). Galanin receptors seem to control prolactin release from pituitary adenomas and are considered as targets for endocrine manipulation of these tumors. In addition, galanin agonist although not a potent analgesic agent on its own, appears to prolong the morphine analgesia four-to eightfold. This may contribute to the reduction of morphine doses to manage chronic pain (Wiesenfeld-Hallin et al., 1990). 135 Discussion Figure 5.1: Galanin receptors and their transduction mechanisms. The first galanin receptor was cloned from human Bowes melanoma cells by Habert-Ortoli et al., (1994). Thereafter, two more galanin receptors, GAL2 and 3 have been cloned and the signal transduction pathways have been determined for all the three receptors. GAL1 and GAL3 receptors can induce hyperpolarization and inhibit adenylyl cyclase (AC). AC can be inhibited via GAL2 receptors. In addition, GAL2 receptors can also stimulate phospholipase C (PLC), resulting in mobilization of Ca2+ and activation of protein kinase C (PKC) via diacylglycerol (DAG). There is also evidence for the activation of the mitogen-activated protein kinase (MAPK) pathway via GAL1 and GAL2 receptors. Image adapted from Liu and Hokfelt, 2002. 5.3.2 Amphiregulin Cell growth and differentiation are regulated in part by the specific interaction of secreted growth factors and their membrane-bound receptors. Receptor-ligand interaction results in activation of intracellular signals leading to specific cellular responses. Epidermal growth factor (EGF) consists of two families of structurally related ligands: the EGF-like growth factors and the neuregulins. The former family includes transforming growth-factor alpha (TGFα), heparin-binding EGF (HB-EGF), betacellulin (BTC) and epiregulin (ERP) and amphiregulin (AR) (Lee et al., 2003; Troyer and Lee, 2001). EGF family 136 Discussion members transmit their growth-modulating signals by binding to and activating receptors with intrinsic tyrosine kinase activity (Plowman et al., 1990). Tyrosine kinase receptors (TRK) belong to the ERBB family that are essential for the normal development and are prominent targets for dysregulation in cancer (Lee et al., 2003). The ERBB-signalling network comprises four homologous receptor tyrosine kinase named ERBB1 – 4 after the prototype EGF receptor (EGFR)/ERBB1 (Troyer and Lee, 2001). The binding of the polypeptide ligand results in receptor homo or heterodimerization with activation of the intrinsic tyrosine kinase, leading to the transphosphorylation of ERBB cytoplasmic tails (Troyer and Lee, 2001). The phosphorylated tyrosines then serve as docking sites for cytoplasmic signaling proteins, resulting in the activation of various downstream pathways, including Ras-MAP kinase cascade, phosphatidylinositol-3 kinase and Stat transcription factors (Troyer and Lee, 2001). The overall downstream signaling events may be involved in regulation of cell proliferation, migration, differentiation or survival depending on cell type and context. AR protein was first discovered in MCF-7 cells and was termed amphiregulin to reflect it bifunctional activities: it inhibits the growth of many human tumor cells and stimulate proliferation of normal fibroblasts (Shoyab et al., 1988; 1989). This protein is a heparinbinding glycoprotein and exists as monomer as of either 78 or 84 amino acids long. AR primarily composed of basic, hydrophilic residues as with other growth factors (Plowman et al., 1990). AR mRNA had been found in ovary, testis, breast, placenta, pancreas, heart, colon, lungs and brain (Plowman et al., 1990; Falk et al., 2002). Recently, AR has been demonstrated as a potent EGF in adult neural stem cell (Falk et al. 2002). Its mRNA is highly expressed in choroid plexus as well as in hippocampal cells thus suggesting that AR may regulate neural stem cell proliferation and neurogenesis in the adult brain (Falk et al., 2002). It is also highly expressed in vascular smooth muscle cells (Kato et al., 2003). This mitogen can also upregulate its own mRNA as well as α-thrombin. In addition, AR can also caused an approximate 30-fold increase in DNA synthesis (Kato et al., 2003). 137 Discussion Figure 5.2: The ERBB signaling network. The four ERBB receptors are shown along with their activating EGF family and tyrosine kinase activity. Amphiregulin and ERBB1/ EGFR are required for ductal morphogenesis, but is unclear whether ERBB2 is involved in this process. Abbreviations of the ligands are described in the text. Image obtained from Troyer and Lee, 2001. 5.3.2.1 Applications As mentioned earlier, neural stem cell cultures could be initiated with AR as the only growth factor, demonstrating that at last some neural stem cells are responsive to AR in vivo. Fraction RP6.3F4 BmKII upregulated the expression of AR gene 4-fold in vitro. This could mean that AR could be used as a potential therapy to replace lost neurons in neurological diseases, either by expanding the stem cells in vitro to transplant cells or by stimulating the neurogenesis in vivo (Falk et al., 2002). 138 Discussion 5.3.3 GABA (A) receptor α-5 subunit Although the brain is undoubtedly the most complex organ, it is possible to distil the way it works into two opposing forces; excitation and inhibition. Neurons using neurotransmitters receptor system, are excited by neurotransmitter glutamate and inhibited by the neurotransmitter γ-aminobutyric acid (GABA; Whiting, 1999). GABA (A) receptors are ligand-gated ion channels that are the major modulators of the inhibitory tone throughout the central nervous system (CNS). They are the site of action of a number of clinically important drugs, including benzodiazepines (BZs), barbiturates, and anesthetics (Whiting, 2001). It is generally accepted that this receptor is a pentamer with an integral protein chloride ion channel formed by the second transmembrane domain of each of the five subunits (Sur et al., 1998). Over- or under-activity of excitatory or inhibitory force has been proposed to play a role in a variety of neurodegenerative conditions such as stroke, Parkinson’s disease, epilepsy, schizophrenia and anxiety (Kemp and McKernan, 2002; Meldrum and Whiting, 2001). In the late 1980s and 1990s, with the application of molecular biology approaches, it becomes clear that GABA (A) receptor subtypes are formed by co-assembly from 16 subunits (α 1 – 6, β1 – 3, γ1 – 3, δ, ε, π, θ; Whiting, 2001). Information of the physiological role of the various subunits was contributed by gene knock-out studies (Collinson et al., 2002). The primary role of the GABA (A) receptors α5 subunit had remained undefined until gene knock-out studies were performed. α5-containing receptors have a particularly restricted distribution in the hippocampus (Sur et al., 1998, 1999), cortex and olfactory bulb (Rosahl et al., 2003). This localization suggests the receptor subtype may have a role to play in learning and memory (Collinson et al., 2002). Mice lacking α5-subunit have been found to have no major abnormalities, have normal lifespan and no spontaneous seizures (Collinson et al., 2002). However, these mice demonstrated an improved performance in working memory task (Collinson et al., 2002). In addition, another group which studied partial knock-out α5 mouse found that trace fear conditioning was enhanced in these mutant mice (Crestani et al., 2002). Altogether, this data suggest that the α-5 subunit of GABA (A) receptor has an important role in controlling 139 Discussion learning and memory, which makes the α5-containing GABA (A) receptor an interesting novel drug target for the development of cognition enhancers (Rosahl, 2003). In our screening experiments, BmKII crude venom upregulate GABA (A) receptor α5 subunit gene expression in both microarray and real time experiment. Fractions RP5.2G1, RP6.4F7, RP6.3F4, RP6.3F5 and RP6.2F4 at 50 ng/ml were found to upregulate the receptor gene. Fraction RP6.3F4 was found to upregulate the gene expression by 11.2-fold (Table 4.7). At low concentration of 10ng/ml, the receptor gene expression was downregulated in all the five fractions. It is interesting to note that GABA (A) receptor is a chloride channel. However, the major toxin in these five fractions were found to be alpha-toxins which bind to sodium channels. Therefore, we can actually perform binding activity of toxin-receptor in vitro. 5.3.4 Sensory and motor-neuron derived factor (neuregulin) Neuregulins belong to the family of ERBB ligands. The neuregulins include numerous isoforms derived from four independent genes by alternative splicing. One of the neuregulin isoforms, a sensory and motor-neuron derived factor (SMDF) directly binds ERBB3 and ERBB4. It has been suggested that mammalian differentiation is regulated by neuregulin receptors (Troyer and Lee, 2001). SMDF is a neural-specific gene and is found expressed in human brain, spinal cord, and dorsal root ganglia (Ho et al., 1995). The high expression level of mRNA is maintained in the adult rat motor neurons and dorsal root ganglia. SMDF is biologically active and upon ligand – receptor interaction stimulates tyrosine phosphorylation of a 185kD protein (Hayes et al., 1992). The biological functions of SMDF are varied. Its high expression in spinal motor neurons and dorsal root ganglia in the developing human and rodents might suggests a role at the developing neuromuscular junction and possible role in the motor and sensory neuron development (Ho et al., 1995). Consistent with this, SMDF promotes Schwann cell proliferation as there is high level of gene expression in large neurons. Similar to other neuronal peptides, SMDF may be produced in the motor neuron cell body but is transported through the motor axons to the nerve terminal, where it exerts its effects on muscle acetylcholine receptor synthesis and/ or the proliferation of Schwann cells (Hall and Sanes, 140 Discussion 1993). In addition, the expression of SMDF in the adult rat spinal cord motor neurons suggests that it may also act at mature neuromuscular junctions via reinnervation of muscle fibers by motor neurons following nerve damage. In our screening experiment on the BmKII fraction, we found that fractions RP5.2G1, RP6.4F7 and RP6.3F4 were able to increase gene expression of SMDF. These fractions can be tested on PC12 cells to see whether it may promote nerve growth following nerve growth damage in vitro. 5.3.5 Fibroblast growth factor 2 (FGF2) FGF-2 is a member of a large family of structurally related proteins that affect the growth, differentiation, migration and survival of a wide variety of cell types (Bikfalvi et al, 1997). FGF2 or also known as basic FGF is a major growth factor extracted from prostatic tissue (Dow et al., 2000). This molecule belongs to a member of a large family of proteins that bind heparin and heparin sulfate and modulate the function of a wide range of cell types. FGF-2 interacts with specific cell surface receptor proteins derived from four separate genes. FGF-2 has been proposed to have two separate receptor binding sites which may allow a single FGF-2 to bind to two receptors or to interact with a single receptor in two separate positions (Kan et al., 1993). FGF-2 is released from cells as result of cell damage, death and non-lethal membrane disruptions and they are stored in the extracellular matrix and basement membrane (Conrad, 1998; Folkman et al., 1988). Extracellular FGF-2 binds to cell surface receptors and heparin sulfate proteoglycans (HSPG) and is subjected to internalization and lysosomal degradation (Nugent and Iozzo, 2000). FGF2 plays major roles in development, remodeling and disease states in almost every organ system (Bikfalvi et al, 1997). The most well studied function of FGF-2 is its ability to regulate growth and function of vascular cells such as endothelial and smooth muscle cells. It has also been implicated in the development and growth of new blood vessels (angiogenesis) and in the pathogenesis of vascular diseases such as atherosclerosis (Bikfalvi et al, 1997). In addition, FGF-2 stimulates wound healing, tissue repair, and hematopoiesis, and stem cell survival 141 Discussion (Dow et al., 2000). FGF-2 also found to play a key role in tumorigenesis though its ability to induce angiogenesis. In the brain especially in cerebral cortex, hippocampus, cerebellum, retina, ciliary ganglion and spinal cord, FGF-2 promotes proper function of the nervous system (Dow et al., 2000). The authors postulated that basic FGF-2 stimulates glial cells to produce a trophic factor(s) which in turn elicits enhanced neuronal survival and neurite outgrowth. FGF-2 has pronounced effects on central nervous system astrocytes stimulating their proliferation and inducing the synthesis of glial fibrillary acidic protein (GFAP; Morrison et al., 1986). The summary of FGF2 intracellular signaling pathway is depicted in Figure 5.3. FGF-2 gene expression was increased upon treatment with RP5.2G1, RP6.4F7 and RP6.3F4. Since FGF2 is able to promote neurite outgrowth, these three fractions can be tested on PC12 cells as an assay for neurite outgrowth. In addition, the synthesis of GFAP can be measured by immunostaining with a GFAP antibody in an astrocytic cell line such as U-373 MG. 142 Discussion Figure 5.3: Schematic diagram of FGF-2 signalling pathways which has been shown to activate a number of intracellular signalling routes. Binding of FGF-2 to its receptors is enhanced by cell surface HSPG and leads to activation of autophosphorylation of the FGF-R in several tyrosine residues. Some of the phosphotyrosine residues are binding sites for src homology domain containing proteins such as phospholipase C- and others are binding sites for proteins with phosphotyrosine-binding domains such as FGF receptor substrate 2 (FRS2) and SHC. SHC and FRS2 function as docking proteins which bind the GRB2–SOS complex which then activates RAS. RAS recruits RAF-1, a serine/threonine kinase that actives MEK. MEK proceeds to activate the mitogen activated protein kinases (MAPK) which translocate to the nucleus where they directly activate transcription factors by phosphorylation. The activation of PLC- also plays a major role in transmitting the eventual FGF-2-mediated biological signals. PLC- activation results in hydrolysis of phosphatidylinositol to inositol-3phosphate and diacylglycerol (DAG) leading to Ca2+ release and activation of protein kinase C (PKC). The biological end responses for FGF-2 may lead to stimulation of cell proliferation and migration as well as neuronal survival. Image adapted from Nugent and Iozzo, (2000). 143 Discussion 5.3.6 Krit1 Krit1 (for Krev Interaction Trapped 1) is a protein of 529 amino acid, with a amino-terminal ankyrin repeat domain and a novel carboxyl-terminal domain required for association with Krev-1 (Serebriiskii et al., 1997). Krev-1 is an evolutionarily conserved Ras-family GTPase whose cellular function remains unclear but has been proposed to function as a tumor suprressor gene and may act as a Ras antagonist. Mutation of krit1 caused cerebral cavernous malformations (CCM), a type of congenital vascular anomalies of the brain that can cause significant neurological disabilities, including intractable seizures and hemorrhagic stroke (Sahoo et al., 1999). Interaction of Krev-1 and Krit1 may involve in signaling pathway in angiogenesis and cerebovascular disease. So far, not much is known about Krit1 as it is not strongly homologous to any previously described protein. Krit1 is suspected to interact weakly with a family of cytoskeletal and membrane-associated proteins defined by erythrocyte protein 4.1 (Conboy et al., 1986). It may also be a potential positive regulator of Krev-1 activity and provide an indirect mechanism to enhance tumor progression (Serebriiskii et al., 1997). As additional evidence for Krit1 involvement in tumor suppression processes, krit1 ortholog was found to be transcriptionally upregulated in Chinese hamster ovary (CHO) cell. In addition, Krit1 may act in localizing the Krev-1 to an appropriate cellular compartment for function in tumor progression and cellular growth control (Serebriiskii et al., 1997). Northern analysis of krit1 showed weak expression in heart, muscle and brain but not in a number of other tissues (Serebriiskii et al., 1997). In the screening experiment, several fractions of BmKII were found to alter Krit1 gene expression. BmKII downregulated the gene expression of Krit1 by 5-fold and 22-fold in microarray and real-time studies respectively. Intriguingly, subfractions of RP1–9 upregulated Krit1 gene expression. Fraction RP5.2 caused the highest fold of changes of 7-fold gene upregulation. 144 Discussion 5.4 Conclusion and future studies A proteomics study can be performed by checking the protein profile of the six genes using Western Blot. Each of the fractions RP5.2G1, RP6.2F4, RP6.3F4, RP6.3F5 and RP6.4F7 can be individually tested on the neuroblastoma cell line to check for presence of amphiregulin, neuregulin, Krit1, GABA (A) receptor, FGF2 and galanin protein expression level using specific antibody. This may provide useful evidence whether these toxin fractions caused any translational regulation as it did at the transcriptional level. So far, the role of these toxins focused largely on the physiological function at the Na+ channel. RP5.2G1 which shares sequence similarity to bukatoxin and BmK T toxins (Table 4.9). Bukatoxin belongs to α-toxins family that prolongs the action potential of excitable cells by blocking sodium channel inactivation and neuronal transmission. It can also produce a marked, concentration-dependent relaxation of precontracted rat anococcygeus muscle (ACM; Srinivasan et al., 2001). BmK T has anti tumor effect and strong inhibitory effect on pain (Liu et al., 2003). BmK toxin I, a voltage-gated Na+ channel modulator was found to evoke profound change in c-Fos protein expression pattern in rat spinal cord (Bai et al., 2003). The authors found that BmK toxin I may be a key contributor of c-Fos expression induced by BmK venom. 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Cell Neurosci. 11, 234-245. 164 [...]... catalase, amylase and B-glucosaminidase Table 1.2: Some of the common components in snake venoms of different species 1.3 Neurotoxins The first amino acid sequence of a neurotoxin, Tx α from Naja nigricollis was reported in 1967 (Eaker and Porath, 1967) Since then, a large number of neurotoxins have been isolated and characterized Reports on the amino acid sequences of a number of homologous neurotoxins... structural plasticity of the three fingers, the three-finger fold is also amenable to a variety of overt and subtle deviations, such as the number of the β-strands present, size of the loops and C-terminal tail as well as twists and turns of various loops, all of which may have great significance with respect to functional diversity and selectivity of molecular targets (Servent and Menez, 2001; Kini,... Introduction 1.5.4 Kappa neurotoxins κ-Neurotoxins form a new family of snake venom neurotoxins that are structurally related to long neurotoxins With the exception of κ-cobrotoxin, all the other κ-neurotoxins identified consist of 66 amino acid residues and on the basis of amino acid alignment, contain five disulphide bonds as in long neurotoxins (Figure 1.5D) The first κ -neurotoxin, κ-bungarotoxin... paired modified salivary glands which in most venomous snakes are located superficially beneath the scales in the posterior part of the head and eyes The gland is linked to the fang by a duct Contraction of muscles around the gland compresses the gland, forcing the flow of venom along the duct to the fang where the size of these structures depends on the size and species of the snakes 1 Introduction... other subtypes of nAChRs such as neuronal nAChR 1.5.3 Short- and long-chain neurotoxins Based on the length of their polypeptide chains, α-neurotoxins were initially classified as shortchain α-neurotoxins that have 60 – 62 residues and four conserved disulfide bonds in common positions, between Cys-3 and Cys-24, Cys-17 and Cys-45, Cys-40 and Cys-61, Cys-62 and Cys-68 (Figure 1.5A) These neurotoxins bind... patterns of all the neurotoxins 77 Figure 3.6 Classification of snake NTX based on structure, function and phylogenetic information 81 Figure 3.7 Phylogenetic trees performed using parsimony analysis of all the mature svNTX 90 Figure 3.8 Competitive binding studies of 125I-α-Bgt and native Bc-ntx4 to nAChR of Torpedo receptor 91 Figure 3.9 Output of the annotation tool in svNTXs 92 Figure 4.1 Separation of. .. homologous neurotoxins from snakes such as cobras, kraits, mambas and sea snakes have been added to this growing list of neurotoxins At present, more than 100 neurotoxin amino acid sequences are known and they form one of the largest families of protein with known primary structures (Endo and Tamiya, 1991) 5 Introduction Neurotoxins are capable of blocking nerve transmission by binding specifically to nicotinic... of a “broken-neck” syndrome reported after bites of snake with neurotoxic venoms (Minton, 1990) 8 Introduction 1.4 Classification of neurotoxins Snake neurotoxins can be divided into two groups: presynaptic or postsynaptic neurotoxins depending on their mode of action Presynaptic neurotoxins are either phospholipase A2 enzymes or contain these enzymes as an integral part of the neurotoxin complex and, ... arthropods and chordates These venomous animals produce a variety of toxins to defend themselves from predators, to subdue their prey and for digestion Therefore, animal toxins have immobilizing effects and killing functions towards a wide variety of creatures Snake venoms have attracted much medical attention since ancient civilizations and had been used in medical treatment for thousands of years In... structure and α-cobratoxin, 2.4-Å-crystal structure To date, more than 100 three-finger α-neurotoxins have been isolated and sequenced from Elapidae and Hydrophiidae snakes Depending on their amino acid sequence and tertiary structures, α-neurotoxins can be classified into short-chain, long-chain, kappa and weak neurotoxins Although the primary target of all these categories of the three-finger neurotoxins ... Professor Kandiah Jeyaseelan for his dedicated supervision, constant encouragement and continued support during the course of this project I am also grateful for the assistance of Associate Professor... Institute of Infocomm Research for his kind help in the construction of the neurotoxin database My sincere appreciation also goes out to Dr Arunmozhiarasi Armugam for her valuable input and advice... scales in the posterior part of the head and eyes The gland is linked to the fang by a duct Contraction of muscles around the gland compresses the gland, forcing the flow of venom along the duct to