Leonard Foster

The adaptive immune system relies on antigen presentation governed by major histocompatibility complexes (MHCs), which initiate immune responses upon recognition by T- lymphocytes. Vaccines are designed to create immunological memory by delivering pathogen- derived antigens. Understanding the preferences of MHCs for epitopes is essential for effective vaccine design. Current research lacks insights into why certain antigens, while strongly presented by one MHC allele, may not be recognized at all by others. This thesis investigates the binding preferences for MHC-II-presented peptides, providing a comprehensive understanding of antigen presentation across diverse MHC alleles. If we understand better which epitopes are best recognized and presented by MHCs then we will be able to design more effective vaccines.In the first data chapter, Mild Acid Elution (MAE) is demonstrated as an effective method for isolating MHC-II-presented immunopeptides. This method's potential advantages are highlighted, and the importance of additional separation techniques, such as ion mobility cells and offline reverse-phase chromatography, is emphasized for enhancing peptide identification. Insights into background contamination sources in MAE are explored, paving the way for cleaner data and more accurate immunopeptide identification.The second data chapter addresses the challenges posed by genetic diversity in vaccine development by strategically selecting a panel of 30 cell lines from the 1000 Genomes Project, ensuring global HLA diversity representation. This chapter unveils the intricate nature of antigen identification and binding predictions, emphasizing the unpredictability of immunopeptidomics, and underscoring the need for experimental validation in epitope prediction. The investigation into Salmonella enterica lysate exposure provides valuable insights into potential vaccine candidates and the efficient identification of MHC-presented immunopeptides.This research lays a foundation for leveraging immunopeptidomics in vaccine design and understanding antigen presentation, offering promising avenues for advancements in personalized medicine and vaccine development. In summary, this thesis unveils the potential of MAE for immunopeptide isolation, addresses the complexities of genetic diversity in vaccine development, and emphasizes the importance of experimental identification of vaccine targets.

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This thesis describes several experiments aiming to improve the understanding ofVairimorpha ceranae’s pathology in the honey bee midgut epithelium. Using high resolutionmass spectrometry-based methods, I assessed global changes in the honeybee midgut proteome and phosphoproteome, identifying host processes impactedduring infection such as heme binding and carbohydrate metabolism. I also adapted ahigh throughput mass spectrometry-based protein interaction mapping technique toobtain a first draft of the honey bee midgut protein interaction network. With thisresource, I was able to experimentally assemble protein interactions occurring in thehost, and some host-pathogen protein interactions in infected samples, providing newinsight into protein arrangement in honey bees and how these interactions can changein the context of disease. Finally, I conducted a field-based experiment to evaluate theeffects of using a bee product, propolis, to treat honey bees that were naturally infectedwith V. ceranae. Using bottom-up proteomics, we were able to find evidence indicatingthat propolis treatment might improve honey bees’ response to V. ceranae infection.Altogether, in this dissertation, I highlight the versatility of mass spectrometry-basedproteomics for understanding disease in non-model organisms, and I show new insightinto Vairimorpha’s infection processes in honey bees that can form the basis of futurestudies aimed at elucidating mechanisms of action in the infection process of thispathogen.

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Biological functions are mediated by the dynamic organization of DNA, RNA, proteins, and other biomolecules in complex networks of interactions. Efforts to chart the network of biologically relevant macromolecular interactions—the “interactome”—therefore occupy a central position in the endeavour to understand the biochemical basis of human physiology, and its perturbation in disease. However, existing interactome maps are incomplete, even for well-studied organisms. Moreover, the dynamics of the interactome in response to cellular stimuli and across normal physiological contexts remain incompletely understood.This thesis considers the application of a quantitative proteomic approach, protein correlation profiling (PCP), to map the interactome in its native physiological context. I explore computational methods for the analysis of PCP data, and describe their application to infer a dataset of protein-protein interactions from seven mouse tissues.In Chapter 2, I studied the dominant paradigm used to analyze PCP data, which entails the use of supervised machine-learning methods to infer interaction networks from these complex datasets. I found that one widely used strategy needlessly biases network inference towards highly studied proteins and away from novel interactions between functionally un-connected proteins. In Chapter 3, I applied the methods studied in Chapter 2 to a newly collected, in vivo PCP dataset. I used the same machine-learning approach to infer tissue-specific protein-protein interaction networks for seven mouse tissues. I then analyzed these tissue interactome networks to uncover insights about protein function, network evolution, and human disease. Collectively, the work described in this thesis provides a framework to understand the rewiring of the protein-protein interaction network across physiological conditions using PCP.

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Salmonella species are a pathogen of humans and animals. Pathogenesis is mediated by effector proteins that are translocated into host cells. These effector proteins interact with host proteins and cellular processes to establish a replication permissive niche for Salmonella. Efforts to determine the roles of the effector proteins have revealed many insights, however the understanding of the interaction between host and pathogen is incomplete. To further investigate the impact of Salmonella effector proteins on host cells, we developed high throughput proteomic methods to assess changes that occur during infection. First, we describe a flow cytometry-based method to identify the Salmonella SPI-2 effector(s) that mediate suppression of MHC II surface complexes which interferes with Ag-dependent T-cell proliferation. Second, we develop an assay to identify protein-protein interactions that occur in a wild type Salmonella infection compared to the SPI-2 double effector mutant sifAsseJ strain which is deficient in the formation of membrane tubules that facilitate intracellular replication. This assay utilises Blue Native PAGE to fractionate proteins and protein complexes based on size through the gel matrix prior to mass spectrometry. A machine learning classifier then analyses the fractionation profile of every protein pair through the gel matrix to predict protein-protein interactions. Comparison of interactions between experimental conditions is achieved by the stable isotope labelling technique SILAC. Third, we adapt a protocol for analysing changes in protein subcellular distribution, LOPIT-DC, to compare the wild type Salmonella infection to the sifAsseJ strain. This protocol fractionates the cell lysate by differential centrifugation, and SILAC labelling enables comparison between the experimental conditions. This work was successful in further developing methodologies to investigate the host-pathogen interactions between Salmonella Typhimurium and host cells. The approaches described within were successful in identifying known host target proteins for Salmonella effectors, or otherwise recruited to the Salmonella containing vacuole and associated membranes. There was substantial overlap of identified proteins in the datasets generated with other published datasets, along with good coverage of other host proteins which may be involved in Salmonella pathogenesis.

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Spinal cord injury (SCI) is a debilitating condition with no curative treatment. In recent years metabolism has been suggested as a factor that could be altered to enhance recovery after SCI, and research from the Tetzlaff lab showed that a ketogenic diet (KD) can improve recovery after a cervical SCI in rodents. KDs are high fat, low carbohydrate diets that have been successfully used as a treatment for drug-resistant epilepsy in children. KDs produce high levels of the ketone body, beta-hydroxybutyrate (BHB), which can act as an energy source or bind and activate the cell surface receptor, hydroxycarboxylic acid receptor 2 (HCAR2). BHB levels can also be increased by oral ketone ester (KE) supplementation making KE a potential alternative to KD. In Chapter 2, the use of KD on recovery after a cervical forceps crush SCI in mice was assessed. In this injury model KD did not improve recovery of the mice. In Chapter 3, the effect of KD following a more clinically relevant T9 midline contusive SCI was investigated. We observed that KD could reduce pro-inflammatory cytokines CCL3 and CCL4 at 7 days post-injury and a scRNA-sequencing analysis of CD45+ cells at the injury site at 7 days after injury confirmed KD-mediated downregulation of many immune pathways. We also used the T9 contusion injury model with wild type and HCAR2₋/₋ mice to investigate the role of HCAR2 activation on KD-mediated effects. We found that KD could reduce the influx of CD45+CD11b+ myeloid cells into the injury site at 7 days post-injury, which required the HCAR2 receptor. Chapter 4 investigated the use of KE supplementation as a treatment following a C5 hemi-contusive injury in rats. Proteomic analysis at 2 weeks after injury showed that KE and KD appear to impact different cellular pathways. In this model, KE showed only minor improvements in behavioural recovery. Together these results suggest that KD can reduce inflammation at 7 days after injury in mice and that different paradigms of KE supplementation may be needed to see behavioral improvement following SCI in rats.

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Nanoparticle drug delivery vehicles can be used for in vivo delivery of a variety of bioactive molecules including nucleic acid polymers and small molecule drugs for applications ranging from gene therapy to improving the efficacy of anticancer drugs. This thesis explores different variations of lipid nanoparticles (LNP) formulated with microfluidic mixing method, for encapsulation of a wide range of bioactive agents.The first part of the thesis focuses on the effect of cationic lipid content of the LNP and its effect on encapsulation of negatively charged small cargo. The ability of the rapid mixing/cationic lipid protocol to encapsulate small negatively charged molecules and short oligonucleotides in LNP systems containing ionizable cationic lipids and/or permanently positively charged cationic lipids is explored. It was found that encapsulation of small cargo is dependent on molecule size and charge and that permanently charged LNP are more efficacious at encapsulating small, charged cargo than ionizable LNP. It is also shown that charged prodrug forms of molecules that are neutral in their native form can be encapsulated and delivered using this method. The results of these studies can be used as general guidelines for entrapment and delivery of novel bioactive molecules that are typically difficult to formulate.While the cationic lipid plays an obvious role in entrapment and delivery of negatively charged molecules, the role of helper lipids is not very clear. The second chapter of the thesis looks at the effect of helper lipid titration and variation in in vitro cellular uptake and knockdown and in vivo hepatocyte gene silencing, using ionizable-LNP containing siRNA. It was found that while in vitro knockdown might not be greatly affected when the conventional 10 mol% DSPC (1,2-distearoyl-sn-glycero-3-phosphocholine) is varied, in vivo hepatocyte gene silencing was almost fully disrupted by helper lipid variations. The results of these studies could lead to a more targeted LNP simply by varying the helper lipid that enables avoiding certain cell types or targets specific tissues.

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Honey bees (Apis mellifera) are integral components of the agricultural industry, but diseases and parasites like the Varroa destructor mite threaten their health and longevity. Some honey bee colonies harbor natural disease-resistance traits, and proteomics has been a fruitful tool to investigate mechanisms of disease resistance; however, Varroa proteomics is a budding field. One troubling trend is that both honey bee and Varroa proteomics samples consistently result in lower peptide identifications compared to conventional model species, which is hindering research on not only social disease-resistance mechanisms and honey bee-mite interactions, but countless other biological topics. We begin by conducting a proteogenomics interrogation to suggest improvements for both the Varroa and the honey bee genome annotations, and to help alleviate the limitations of proteomics technology. The resulting protein databases and web-based protein atlas will serve as resources for future Varroa and honey bee proteomics experiments. Next, we investigate the chemical ecological aspects underpinning hygienic behaviour in honey bees (one form of social immunity against parasites like Varroa). We use gas chromatography-mass spectrometry to analyze abundances of volatile and non-volatile odorants in freeze-killed and age-matched healthy brood, as well as Varroa-infested and non-infested brood. We identified 10 differentially emitted compounds, 2 of which (β-ocimene and oleic acid) are intriguing candidates as hygienic behaviour-inducers based on their previously known functions in honey bees and other social insects. Next, we investigate these two compounds’ abilities to induce hygienic behaviour using a series of behavioural assays. We found that, depending on the context, both odorants can induce hygienic behavior, and they may be acting synergistically. Finally, we begin to investigate physical and biochemical interactions between these odorants and two odorant binding proteins – OBP16 and OBP18 – which are thought to aid in disease odorant detection. We find that β-ocimene is a ligand of OBP16 and oleic acid is a ligand of both OBPs. We conclude by beginning to develop RNAi and transgenic methods for investigating the roles of these proteins in vivo. Overall, these studies are starting to reveal the simple molecular mechanisms underlying a complex social immunity trait in honey bees.

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Immune responses are tightly controlled mechanisms that serve as the primary means by which invading pathogens are eradicated. These mechanisms are governed by the action of several proteins that, when activated, regulate a cascade of downstream effectors in immune cells that help control and, often eliminate the infection. We have discovered a protein, ABCF1, which regulates this immune response cascade through Toll-like receptor (TLR) signaling and helps maintain cellular homeostasis. ABCF1 is the only known member of the ATP-Binding Cassette (ABC) superfamily that lacks a trans-membrane domain and thus doesn’t function as a transporter. Previous studies on ABCF1 indicate a role for this protein in DNA sensing mechanisms and in the pathophysiology of rheumatoid arthritis and autoimmune pancreatitis.We have discovered that ABCF1 is the sole member of the ABC superfamily possessing E2 ubiquitin-conjugating enzyme activity and exclusively regulates TLR4 endocytosis in murine macrophages. In our studies, ABCF1 was found to target Spleen Tyrosine Kinase (SYK) and TNF Receptor Associated Factor (TRAF3) proteins for K63-linked polyubiquitination, thereby regulating the shift from MyD88-dependent to TRIF-dependent signaling. We also observed that ABCF1 negatively regulates MyD88-dependent pro-inflammatory cytokine production in TLR2 and TLR9 signaling, thereby controlling macrophage polarization to the M2 phenotype.ABCF1 was also found to control viral immune responses by regulating OAS1a enzyme activity and negatively regulating ABCE1 thereby modulating RNase L activation. ABCF1 also seemed to control FcγR II-mediated phagocytosis through phosphorylation of SRC Family Kinases (SFKs).Our data also revealed that ABCF1 negatively regulates cytokine storm during the inflammatory phase of sepsis. It associates with TRAF3 and targets TRAF3 for K63-linked poly ubiquitination, thereby controlling the shift from inflammatory phase to immune compromised phase during sepsis. ABCF1 haploinsufficiency was found to trigger lethal renal circulatory dysfunction, which drastically reduced survival rates during the inflammatory phase of sepsis.We herein report the discovery of a novel E2 enzyme, ABCF1, whose E2 ubiquitin-conjugating activity controls TLR-mediated inflammation and cytokine storm during sepsis in murine macrophages.

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Viruses exist as obligate intracellular parasites, with one of the largest classifications of viruses being the positive single stranded RNA viruses ((+)ssRNA). Viral families in this group are incredibly diverse in their replication schemes and host tropisms. Despite this, there exist fundamental principles between them. Unravelling these common mechanisms can give rise to a greater understanding of virus biology and lead to the development of novel antiviral therapies and biotechnology. Members of the Dicistroviridae contain monopartite, (+)ssRNA genomes, between 8 to 10 kilobases in size. Infectious to agriculturally and economically important arthropods, these viruses have served as model systems to study fundamental cellular processes such as translation and innate immunity. Dicistroviruses contain two open reading frames (ORFs), which are translated by two distinct internal ribosome entry sites (IRESs). The 5’ untranslated region IRES drives translation of the viral non-structural proteins encoded in ORF1, whereas the intergenic region (IGR) IRES directs translation of the viral structural proteins of ORF2. The scheme by which these viruses replicate is poorly described. Here, we develop the first infectious clones of the dicistrovirus type species, Cricket paralysis virus (CrPV), termed CrPV-2 and -3. We demonstrate that this clone is fully infectious in Drosophila S2 cells and causes mortality when injected into adult flies. Utilizing this clone, we examined how specific mutations in the IGR IRES affect viral gene expression in vivo. Moreover, we demonstrate that the CrPV IGR IRES uses an unusual mechanism for +1-frame translation of a hidden overlapping ORF, which is important for viral pathogenesis. Finally, using a combination of biochemical and mass spectrometry based approaches we show that CrPV may usurp cellular pathways to obtain an envelope. This thesis offers insights into the complex replication scheme of dicistroviruses and provides a foundation for future studies into the life cycle of these viruses.

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The Arabidopsis transcription factor MYB75 has been described in the literature as a positive transcriptional regulator of anthocyanin biosynthetic genes. More recently, MYB75 was shown to also negatively regulate lignin and other secondary cell wall biosynthetic genes. MYB75 has two canonical MAP kinase phosphorylation sites, at threonines 126 and 131; we wanted to explore the possibility that MYB75 is regulated post translationally through phosphorylation by MPKs. In our lab, Dr. Yonge found that MYB75 could be phosphorylated in vitro by MPK3, MPK4, MPK6 and MPK11, almost exclusively at threonine 131. Subsequently, I demonstrated that MYB75 interacts in vitro with a large number of Arabidopsis MAP kinases, suggesting that it could be a target for multiple MPKs. We decided to explore how phosphorylation affects MYB75 function, in terms of protein-protein interaction, protein turnover and localization, and describe the impact of this putative phosphorylation event on the ability of MYB75 to drive transcription of target genes. For this purpose we used point mutants, MYB75T131A and MYB75T131E to mimic permanently non-phosphorylated and phosphorylated versions of MYB75, respectively. While protein localization and protein-protein interactions of MYB75 were not strongly impacted in the point mutants, several in vivo experiments indicated that MYB75T131E is more labile than either MYB75WT or MYB75T131A, suggesting that phosphorylation at T-131 negatively affects protein stability. Over-expressor lines, 35Spr:3xHA:MYB75 gene, as well as inducible DEXpr:3xHA:MYB75 gene lines were used, to analyze MYB75 protein dynamics in vivo and to assess the ability of each phosphovariant to drive anthocyanin production. Arabidopsis plants over-expressing MYB75WT, MYB75T131A or MYB75T131E displayed increased anthocyanin production, compared to Col-0 WT, suggesting that phosphorylation status at T-131 does not affect this aspect of MYB75 function. However, HPLC analysis revealed quantitative differences between the biochemical species of anthocyanins and flavonols that accumulate in different phosphovariant over-expressing plants. Transcriptome analysis revealed that MYB75T131E is a more potent regulator of gene expression. This finding, along with distinct developmental differences between MYB75 phosphovariants, suggest that phosphorylation at T-131 could affect the ability of MYB75 to drive the expression of a broader spectrum of genes than previously described in the literature. Supplementary materials available at: http://hdl.handle.net/2429/66660

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Chromosomal translocations can cause cancer, often through the formation of fusion genes that code for an unnatural tyrosine kinase that promotes constitutive activation of a signaling pathway controlling cell proliferation and differentiation. For example, the diagnostic hallmark of chronic myelogenous leukemia (CML) is an oncogene fusion formed from a reciprocal translocation (t(9;22)(q34.1;q11.2)) between chromosomes 9 and 22 that results in an altered chromosome 22q known as the Philadelphia chromosome. Approximately 95% of all CML patients harbor the gene fusion, BCR-ABL, which is formed via a double stranded break (DSB) within both the Abelson oncogene 1 (ABL) on chromosome 9q, which codes for a non-receptor tyrosine kinase (ABL), and the breakpoint cluster region gene (BCR) on chromosome 22q. BCR-ABL encodes a constitutively active tyrosine kinase BCR-ABL responsible for the uncontrolled proliferation associated with chronic myelogenous leukemia. The identification of these translocation events and/or associated fusion genes in clinical samples is critical to ensure the appropriate treatment for patients where the drug and related course of therapy target an activated fusion kinase. Clinical detection of complex chromosomal rearrangements is often conducted using fluorescence in situ hybridization (FISH). The FISH analysis, though effective, offers relatively poor sensitivity while being expensive, time-consuming and technically challenging to perform. Here we have developed and validated a new general platform for creating assays against complex chromosomal rearrangements, including both reciprocal and non-reciprocal translocations. It utilizes droplet digital PCR (ddPCR) technology in lieu of FISH to quantify the rearrangement of proto-oncogenes that undergo rearrangement as part of the translocation event. The platform is applied to the creation of two new assays of potential clinical use in cancer diagnostics or theranostics. The first provides a reliable and sensitive measure of DSBs within the major breakpoint region of BCR (M-BCR), permitting initial diagnosis of CML through unequivocal detection of the BCR-ABL fusion gene to a frequency of 0.25%. The second provides for the highly sensitive detection of DSBs in the anaplastic lymphoma kinase (ALK) gene that result in a non-reciprocal (inversion) translocation (inv(2)(p21;p23)) associated with an ALK-positive non-small cell lung cancer (NSCLC).

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A protein network can be thought of as a graph with nodes and edges, where nodes represent proteins and edges represent protein-protein interactions. Neither proteins nor their interactions are stable constituents in the cell; they are constantly changing in response to external stimulation or internal programming. Changes in protein expression are regulated by transcription, translation and protein degradation, whereas protein interaction changes have been shown in focused studies to be regulated by post translational modification. To investigate the processes influencing the regulation of protein expression and interaction changes, mass spectrometry based proteomics was applied because it has two key advantages for the study of protein networks: 1) it directly detects peptides from the proteins, and so does not rely on antibodies or the generation of fusion proteins; 2) by combining mass spectrometry based proteomics with quantitative techniques, such as stable isotope labeling by amino acids in cell culture (SILAC), it is possible to quantify thousands of proteins in a single experiment. Here a systems biology approach was applied to investigate protein expression change, synthesis and degradation of proteins during cellular differentiation in two different cell lines. This allowed observing that protein expression during cellular differentiation is largely controlled by changes in the relative synthesis rate, whereas the relative degradation rate of the majority of proteins changed little. By comparing the data with previously published data of mRNA levels, there could be provide strong evidence that the generally poor correlation observed between transcript and protein levels can be explained once the protein synthesis and degradation rates are taken into account. To study how protein interactions change in response to perturbation, a novel approach was developed combining size exclusion chromatography (SEC) and protein correlation profiling (PCP)-SILAC. Stimulation with epidermal growth factor (EGF) caused 351 proteins to alter their interactions with other proteins and, interestingly, when compared to previously published phosphorylation data, these proteins tended to also have altered phosphorylation under similar experimental conditions. This approach allowed identification of protein interactions in numbers comparable to other high throughput techniques, but also enabled quantification of protein stoichiometry between proteins participating in multiple complexes.

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Lipid rafts are cholesterol enriched membrane microdomains involved in many cellular functions. Caveolae are a sub-type of lipid rafts that are smooth invaginations of the plasma membrane (PM) whose formation requires caveolin-1 (Cav1). Here, we determined the lipid rafts and caveolae proteome from various cells in an unbiased manner and examined the dynamic raft proteome change during Salmonella infection using quantitative proteomics. In chapter 2, we approach the status of mitochondrial proteins in detergent-resistant membrane (DRM) preparations by employing Stable Isotope Labeling by Amino acids in Cell culture (SILAC) to evaluate the composition of differentially purified subcellular fractions. Our data demonstrate that mitochondrial proteins that were previously identified as raft components are partially co-purifying contaminants of raft preparations. In tumor cells deficient for Golgi β-1,6N-acetylglucosaminyltransferase V (Mgat5), reduced Cav1 expression is associated not with caveolae but with oligomerized Cav1 domains, or scaffolds. These cell lines displaying differing Cav1/caveolae phenotypes are effective tools for probing the composition of caveolae. Using SILAC in chapter 3, we are able to quantitatively distinguish the composition of caveolae from the background of DRM proteins and show that the presence of caveolae enriches protein composition of DRM, including the recruitment of multiple heterotrimeric G-protein subunits. Furthermore in chapter 4, we explored the dynamic change of membrane protein composition according to an external signal. Salmonella are Gram-negative intracellular bacteria believed to attack lipid rafts as the site of entry. We applied SILAC examined the change of host raft proteome at a couple of time points during Salmonella infection. Dozens of proteins have shown to be highly regulated, one of them – Cav1 is shown to be required by Salmonella entrance. We also developed a high-content screening assay that is able to estimate the number of bacteria entered or survived inside the host for future functional studies of the novel proteins identified. This research gives us a better understanding of the raft proteome and how rafts are localized, as well as it can be changed. The Salmonella infection work leads to a global raft proteome dynamic analysis and identifies several proteins that may be novel bacterial host targets.

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Salmonella enterica is an intracellular bacterium causing gastroenteritis and typhoid fever. Virulence is achieved by two type III secretion systems (T3SS) encoded on Salmonella pathogenicity islands 1 and 2 (SPI-1 and SPI-2) that translocate effector proteins into host cells where they mimic or block host protein function. Effectors translocated by T3SS-1 facilitate internalization of the bacteria into the Salmonella-containing vacuole (SCV), actively stimulate intracellular signaling cascades, and regulate trafficking of the SCV to avoid degradation. A T3SS-1 effector, SopB has been shown to regulate a vast array of host processes important for pathogenesis, but only a few host proteins have been identified as targets of this effector. Here quantitative mass spectrometry-based proteomics and bioinformatics techniques have been employed to identify novel host targets of SopB. Quantitative immunoprecipitation experiments identified Cell division control protein 42 (Cdc42) as a direct SopB binding partner, and the binding site within SopB was localized to residues 117-168. SopB and active Cdc42 were shown to colocalize at membrane ruffles on the host cell surface, and two SopB monoubiquitylation sites were identified. To globally analyze host protein phosphorylation events regulated by SopB, a phosphoproteomics method employing heat and chaotropic denaturation for phosphatase inactivation, peptide fractionation by in-solution isoelectric focusing, and phosphopeptide enrichment by metal oxide chromatography was developed. Quantitative analysis of host protein phosphorylation during the initial 20 minutes post Salmonella infection identified >9000 phosphorylation sites, >2000 of which were dynamic. Signaling cascades downstream of T3SS-1 were compared to those induced by growth factor simulation, revealing stark differences between these signaling mechanisms. Kinase prediction upstream of dynamic phosphosites revealed protein kinases B and C as master host regulators during Salmonella infection, and phosphorylation dynamics following wild type versus ΔsopB infection were compared to identify novel host targets of SopB. This work has greatly improved our understanding of SopB’s activity within host cells. It has also provided the first global view of host protein phosphorylation dynamics during bacterial infection, and developed several techniques that can be widely applied within the field of pathogen-host interactions.

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The honey bee Apis mellifera is an extremely beneficial insect due to its role in pollination and honey production. Honey bees are vulnerable to many diseases, one of which is caused by the bacterium Paenibacillus larvae. Ingestion of its spores by honey bees early in their larval stage results in death before adulthood. This disease is known as American foulbrood. Interestingly, this deadly consequence does not occur when older larvae or adults consume the spores, a phenomenon which we hypothesize to be the result of an underdeveloped immune system in young larvae. To address this issue, we mainly employed mass spectrometry-based proteomics techniques to learn about the protein effectors that are present in the host. We focused on the hemolymph (insect blood) where a significant repertoire of immunity-related proteins exists. In our comparison of adults and larvae, we saw age-correlated differences in the levels of the antimicrobial peptide hymenoptaecin, the phenoloxidase enzyme which lead to the production of cytotoxic free radicals, and several bacterial recognition proteins. This prompted a detailed study of the larval development in which many new expression trends were revealed; for example, the age-related decrease of antioxidant proteins, proteins associated with translational machinery, and enzymes related to protein turnover. Unexpectedly, most immunity-related proteins showed no significant age correlation, except the antimicrobial peptide apisimin and phenoloxidase. The latter protein was particularly intriguing, given that its increased expression and activity with respect to age agreed with the buildup of resistance against P. larvae. Furthermore, this protein was upregulated in P. larvae infected larvae compared to healthy controls. This enzyme may be an important factor of the host immune response. The decrease of nutrient storage proteins in the diseased state which we observed also implied that the defense response was mounted with an associated energetic cost. Data from the work covered in this thesis has helped explain, from a molecular point-of-view, the pathogenesis of American foulbrood. Although our focus was on honey bee immunity, the proteomics-based approach taken here has provided protein evidence and expression data that will serve as a resource for the wider scientific community.

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