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Discrimination between self and non-self
The innate immune system in both vertebrates and non-vertebrates is able to identify micro-organisms as foreign by pattern recognition receptors (PRRs) of the host (Royet, 2004). The non-self molecules recognized by PRRs are generally present on the surface of microbes and are known as pathogen associated molecular patterns (PAMPs). Their recognition by PRRs activates the Toll-like and/or IMD pathways of host cells, especially in phagocytic hemocytes and the digestive cells lining the lumen of the midgut (Brennan & Anderson, 2004).
In arthropods such as Drosophila, PRRs which have been implicated in pathogen recognition include the peptidoglycan binding protein (PGBP) for Gram-positive bacteria (Kang et al., 1998) and the Gram negative-binding protein (GNBP), which recognizes lipopolysaccharide (LPS) and β-1,3-glucan (Lee et al., 1996; Kim et al., 2000). PRRs differ in specificity due to the fact that different pathogenic organisms exhibit different PAMPs on their surface. In addition, a LPS binding protein (LBP) has been isolated from hemolymph of the American cockroach Periplaneta americana (Jomori et al., 1990). Lectins in turn recognize pathogen-specific carbohydrate moieties on the pathogen surface, thereby facilitating opsonization, phagocytosis and cytolysis (Janeway & Medzhitov, 2002).
The first peptidoglycan receptor protein (PGRP) was discovered in the silkworm, Bombyx mori (Yoshida et al., 1996). Infection-induced proteins that bind to peptidoglycan (PGN), trigger the proteolytic melanization cascade. In Drosophila approximately 13 PGRPs have been identified which share a 160 amino acid PGN recognition domain. They occur as secreted (S) and transmembrane (L) forms (Kang et al., 1998; Michel et al., 2001; Werner et al., 2000, 2003). PGRP-Lconsists of transmembrane and cytoplasmic domains and has different extracellular PGN recognition domains which trigger the IMD pathway (Choe et al., 2002; Werner et al., 2003). PGRP-L also plays an essential role in the recognition and distinguishing between Gram-negative and Gram-positive PGN (Werner et al., 2003). PGRP-S consists of a single recognition domain and binds Gram-positive PGN with high affinity (Werner et al., 2000; Michel et al., 2001).
Lee et al. (1996) discovered a GNBP in the silkworm, B. mori. It is a 50 kDa hemolymph protein which has a strong affinity for the cell walls of Gram-negative bacteria, and is up-regulated during bacterial infection. The GNBP sequence contains a region displaying significant homology to the putative catalytic region of a group of bacterial β-1,3 and β-1,4 glucanases. Silkworm GNBP was also shown to have an amino acid sequence similar to the vertebrate LPS receptor CD14.
Chapter: 1 Introduction
1.1 Problem statement
1.2 Ornithodoros savignyi as a model organism for this study
1.3 The invertebrate innate immunity
1.3.1 Discrimination between self and non-self
1.3.2 Cellular immune responses
1.3.3 Humoral immune responses
1.3.4 Coagulation
1.3.5 Iron sequestration
1.3.6 Oxidative stress
1.4 Aims of thesis
Chapter 2: Identification of tick proteins recognizing Gram-negative bacteria
2.1 Introduction
2.2 Hypothesis
2.3 Materials and methods
2.3.1 Ticks
2.3.2 Reagents
2.3.3 E. coli binding proteins in hemolymph plasma from unchallenged ticks
2.3.4 E. coli binding proteins in hemolymph plasma from challenged ticks
2.3.5 Protein identification by MS/MS analysis and de novo sequencing
2.3.6 E. coli binding proteins in hemocyte extracts
2.4 Results and discussion
2.4.1 Analysis of E. coli binding proteins in hemolymph from unchallenged ticks
2.4.2 Analysis of E. coli binding proteins in hemolymph from challenged ticks
2.4.3 Protein identification
2.4.4 The source of Protein X and Y
Chapter 3: Protein X and its relation to savicalin, a lipocalin in hemocyte
3.1 Introduction
3.1.1 Lipocalins found in hard ticks
3.1.2 Lipocalins found in soft ticks
3.2 Hypothesis
3.3 Materials and methods
3.3.1 Hemolymph collection and RNA extraction
3.3.2 Single stranded cDNA synthesis
3.3.3 Degenerate primer design
3.3.4 Cloning and sequencing of amplified cDNA
3.3.5 Sequence retrieval for multiple sequence alignments and phylogenetic analysis
3.3.6 Homology modeling and quality assessment
3.3.7 Transcriptional profiling
3.4 Results and discussion
3.4.1 Sequence analysis
3.4.2 Multiple sequence alignments of tick lipocalins
3.4.3 Structural modeling of savicalin
3.4.4 Phylogenetic analysis
3.4.5 Tissue expression profile of savicalin
Chapter 4: Attempted identification of the Gram-positive antibacterial activity in the salivary glands of O. savignyi
4.1 Introduction
4.2 Hypothesis
4.3 Materials and methods
4.3.1 Flow diagram
4.3.2 Ticks
4.3.3 Reagents
4.3.4 Sample preparation, collection and extraction
4.3.5 Antibacterial assay
4.3.6 Purification of the Gram-positive antibacterial activity
4.3.7 Tricine SDS-PAGE analysis
4.3.8 Blotting of protein bands obtained from trice SDS-PAGE
4.3.9 Edman sequencing
4.3.10 MS/MS analysis and de novo sequencing
4.3.11 Anti-bacterial analysis of synthetic actin fragments
4.4 Results and discussion
4.4.1 Purification of the Gram-positive antimicrobial activity and identification using N-terminal sequencing
4.4.2 Purification of the Gram-positive antibacterial activity and identification using M
4.4.3 MS/MS ion search and de novo sequencing of the active fraction
4.4.4 Testing of actin-derived peptides for Gram-positive antibacterial
activity
Chapter 5: Concluding discussion
