Background: Reliable biomarkers are needed to evade the risk of injury, invasiveness and discomfort of endoscopies, which are required for inflammatory bowel disease (IBD) diagnosis and extent of disease assessment in ulcerative colitis (UC) patients. The need for biomarkers is accentuated in children, wherein the most frequently used IBD biomarker yields low specificity. Proteomics of clinical samples or their enriched components is a means to evaluate and identify alterations in proteins reflective of disease, with the potential for use as biomarkers and for providing insight on disease pathogenesis. Methods: Proteins were isolated from the intestinal mucosal-luminal interface (MLI), collected from the ascending and descending colon of pediatric treatment-naive patients. The intestinal MLI proteomes of 42 IBD and 18 control patients were analyzed by high resolution mass spectrometry (HRMS). Multivariate analysis and receiver operating characteristics curves were performed to develop protein biomarker panels to discriminate IBD from control, and for UC extent of disease. ELISAs were used to assess a subset of biomarker candidates in stool samples from an independent pediatric cohort (n=24). Extracellular vesicles (EVs) were isolated by ultracentrifugation from the intestinal MLI of 11 IBD and seven control patients, and analyzed by electron microscopy, nanoparticle tracking analysis and HRMS. Results: A biomarker panel of four proteins classified patients as either controls or active IBD with 97.5% accuracy. A second biomarker panel correctly classified 100% of UC patients as presenting with pancolitis or non-pancolitis. The differential protein expression of two biomarker candidates (catalase and leukotriene A-4 hydrolase) identified from the intestinal MLI was comparable in stool samples. Comparison of EV proteomes isolated from IBD patients and controls identified differential expression of processes related to host defense and immunity. Conclusions: Proteomic analysis of clinical samples identified differentially expressed proteins that can classify IBD patients from non-IBD controls and distinguish UC patients with pancolitis from those without pancolitis; proteins identified in intestinal aspirates displayed consistent differential expression in stool. Furthermore enrichment of EVs from the intestinal MLI indicates that these may contribute to the dysregulated host response against the intestinal microbiota which is observed in IBD.

The proteome is in constant flux and therefore it is important to understand the contribution of protein dynamics to the function of an organism. The zebrafish (Danio rerio) is a recognised model organism that is widely used to investigate physiological processes. The focus of this thesis was to develop a method to calculate the rates of synthesis of heart proteins of zebrafish on a proteome-wide scale. The initial stage of the project involved the optimisation of a method to characterise the protein complement of individual zebrafish hearts. It was concluded that for the rapid screening of proteins 1-dimensional gel electrophoresis in conjunction with high resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) was the most appropriate experimental approach. In order to determine the rates of protein synthesis, zebrafish were administered with a stable isotope-labelled amino acid ([2H7] L-leucine) via the diet and its incorporation into heart proteins was monitored over an 8 week time course. Using this method it was possible to calculate the synthesis rates of over 600 proteins. The experimental strategy was then applied to define the changes in protein synthesis rates in hearts from zebrafish that were subjected to chronic unpredictable stress (CUS). A variety of stressors on zebrafish comprising air emersion, net chasing or net confinement were employed to model CUS. These approaches were validated by a parallel behavioural analysis. The results revealed that glycolytic and gluconeogenic enzymes as well as proteins involved in hypoxia had significantly altered synthesis rates in response to induced stress. This thesis describes for the first time a proteomics approach to determine the rates of synthesis of individual proteins in the zebrafish and its application to investigate the effects of stress conditions on heart proteome dynamics.

Influenza virus H1N1 is a huge threat on human health. Influenza occurs with seasonal variations and reaches peak prevalence in winter, with many people killed worldwide every year. In the research of interaction between influenza virus and cells, four major parts were in the range of our consideration, namely the proteins of virus, the proteome of host cell, the method of proteomic and the potencial medicine related with those significant proteins. Hemagglutinin (HA), as an envelope protein, plays an important role in influenza A virus. It was found that HA has a series of isoforms in two dimensional gels in this study. For the investigation of HA, firstly, virus was purified by sucrose density-gradient centrifugation, followed by the separation of virus proteins through electrophoresis method, and then these proteins were digested by different enzymes and analyzed through MALDI-TOF MS and ESI-Q-TOF MS. Database searching was used for identification of sequences. The results of the virus samples digested by different enzymes were compared, and the isoforms of HA were proved to be related with the glycan and their glycosylation sites. A novel strategy of stable-isotope N-phosphorylation labeling was developed for peptide de novo sequencing and protein quantification based on organic phosphorus chemistry. Different from other stable-isotope labeling reagents that needed to be activated in advance for peptide coupling, N-phosphorylation labeling reagents were activated in situ to form labeling intermediates with high activity and selectivity targeting on N-terminus and -amino group of lysine under various reaction conditions. The obtained results showed excellent correlation of the measured ratios to theoretical ratios with errors that ranging from 0.5 to 6.7 % and relative standard deviation of less than 10.6 %, indicating the reproducibility and preciseness of the developed method. The method development based on organic phosphorus chemistry offered a new approach for quantitative proteomics by using novel stable-isotope labeling reagents. A method combining hydrazide chemistry, stable isotope labeling and mass spectrometry analysis was developed and applied to study glycoproteins of H1N1 (A/Purto Rico/8/1934) infected cell line (A549). The result showed that some glycoproteins were significant in influenza virus infected cells. In these glycoproteins, RPC1_HUMAN, RHG25_HUMAN , RPTOR_HUMAN, ARHGC_HUMAN, ROCK1_HUMAN, DOCK3_HUMAN were down-regulated. Protein named TITIN_HUMAN, DESP_HUMAN, PTN13_HUMAN were up-regulated. High dose of N-acetylcysteine (NAC) was recently reported for a therapy of H1N1 influenza pneumonia. NAC was used as a small-molecule organic probe to investigate the protein expression of human lung carcinoma cell line (A549) infected by influenza virus H1N1. The obtained results showed that NAC kept cells away from apoptosis. Virus-infected cells were arrested in G0/G1 phase. The lowest cell population of G0/G1 phase was detected when the cells were treated by 10 mM NAC for one day. Software analysis showed that 4 proteins had close relationship. The results indicated that NAC as a small-molecule probe might effect the proteins expression of A549 cells infected by the H1N1 virus

Proteins are the primary functional units of biology and the direct targets of most drugs, yet there is limited knowledge of the genetic factors determining inter-individual variation in protein levels (protein quantitative trait loci (pQTLs)). Limitations in high-throughput proteomic measurement technology have meant well-powered genome-wide association studies for large number of proteins so far have lagged behind many of the other "omic" studies such as transcriptomics and metabolomics. This is made more challenging by the complexity of human plasma, characterised by high dynamic range spanning several magnitudes of concentrations and a large number of low abundance proteins. By using an expanded high-throughput multiplex aptamer-based proteomic assay with more than twice the proteome coverage of previous studies, I am able to greatly expand on existing knowledge on genetic determinants of human plasma proteins through testing 10.6 million DNA variants against levels of 2,994 proteins in 3,301 individuals. I identify 1,927 genetic associations with 1,478 proteins, replicating many previous associations as well as gaining novel insights into the genetic architecture of the human plasma proteome. I use several approaches to highlight the application of pQTLs to biology and disease. I show several examples linking distant pQTLs to biologically plausible genes and demonstrate the mediation of distant pQTL by local protein levels, highlighting the role of protein-protein interactions. In addition, I find epistatic effects of genetically determined phenotypes (blood group and secretor status) on protein levels. Through linking previous disease associations, I show that disease associated variants are enriched for pQTLs and I provide insights into possible mechanisms underpinning some of the disease loci. Finally, I identify causal roles for protein biomarkers in disease through multivariable Mendelian randomisation (MR) analysis, leveraging on the simultaneous measurement of multiple functionally related proteins in a locus to account for potential pleiotropic effects. Whereas MR studies of plasma proteins have been constrained by availability of few suitable genetic instruments, the data generated here remedy this bottleneck by furnishing an extensive toolkit. Overall, the work within this thesis foreshadows major advances in post-genomic science through increasing application of novel bioassay technologies to major population biobanks.

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Methylation is a post-translational modification which occurs on lysine and arginine residues. Methylation is difficult to detect due to its low abundance and lack of charge. Our laboratory previously developed a novel enrichment approach, ProMENADe, for lysine and arginine methylation in the human embryonic kidney (HEK) 293T cell line which is coupled with mass spectrometry. Simplifying a lysate with subcellular fractionation prior to enrichment increased the identification of methylation sites by 39.5% while using multiple proteases for digestion increased identification by 27%. Combining these methods yielded a 47.2% increase. Analysis at the 1% methylation level FDR filtered for C-terminal methylation identified 169 sites and further analysis revealed 74 of these sites overlap with the PhosphoSite database. This ProMENADe enrichment strategy yielded 95 novel methylation sites to the field and can be a key tool in the field of methylation allowing for the enrichment and identification of methylated proteins.

Philosophiae Doctor - PhD / Apple (Malus x domestica) production in the Western Cape, South Africa, is one of the major contributors to the gross domestic product (GDP) of the region. The production of apples is affected by a number of diseases. One of the economically important diseases is apple scab that is caused by the pathogenic fungus, Venturia inaequalis. Research to introduce disease resistance ranges from traditional plant breeding through to genetic manipulation. Parallel disease management regimes are also implemented to combat the disease, however, such strategies are increasingly becoming more ineffective since some fungal strains have become resistant to fungicides. The recently sequenced apple genome has opened the door to study the plant pathogen interaction at a molecular level. This study reports on proteomic and transcriptomic analyses of apple seedlings infected with Venturia inaequalis. In the proteomic analysis, two-dimensional gel electrophoresis (2-DE) in combination with mass spectrometry (MS) was used to separate, visualise and identify apple leaf proteins extracted from infected and uninfected apple seedlings. Using MelanieTM 2-DE Gel Analysis Software version 7.0 (Genebio, Geneva, Switzerland), a comparative analysis of leaf proteome expression patterns between the uninfected and infected apple leaves were conducted. The results indicated proteins with similar expression profiles as well as qualitative and quantitative differences between the two leaf proteomes. Thirty proteins from the apple leaf proteome were identified as differentially expressed. These were selected for analysis using a combination of MALDI-TOF and MALDI-TOF-TOF MS, followed by database searching. Of these spots, 28 were positively identified with known functions in photosynthesis and carbon metabolism (61%), protein destination and storage (11%), as well as those involved in redox/response to stress, followed by proteins involved in protein synthesis and disease/defence (7%), nucleotide and transport (3%). RNA-Seq was used to identify differentially expressed genes in response to the fungal infection over five time points namely Day 0, 2, 4, 8 and 12. cDNA libraries were constructed, sequenced using Illumina HiScan SQTM and MiSeqTM instruments. Nucleotide reads were analysed by aligning it to the apple genome using TopHat spliceaware aligner software, followed by analysis with limma/voom and edgeR, R statistical packages for finding differentially expressed genes. These results showed that 398 genes were differentially expressed in response to fungal infection over the five time points. These mapped to 1164 transcripts in the apple transcripts database, which were submitted to BLAST2GO. Eighty-six percent of the genes obtained a BLAST hit to which 77% of the BLAST hits were assigned GO terms. These were classed into three ontology categories i.e. biological processes, molecular function and cellular components. By focussing on the host responsive genes, modulation of genes involved in signal perception, transcription, stress/detoxification, defence related proteins, transport and secondary metabolites have been observed. A comparative analysis was performed between the Day 4 proteomic and Day 4 transcriptomic data. In the infected and uninfected apple leaf proteome of Day 4, we found 9 proteins responsive to fungal infection were up-regulated. From the transcriptome data of Day 4, 162 genes were extracted, which mapped to 395 transcripts in the apple transcripts. These were submitted to BLAST2GO for functional annotation. Proteins encoded by the up-regulated transcripts were functionally categorised. Pathways affected by the up-regulated genes are carbon metabolism, protein synthesis, defence, redox/response to stress. Up-regulated genes were involved in signal perception, transcription factors, stress/detoxification, defence related proteins, disease resistance proteins, transport and secondary metabolites. We found that the same pathways including energy, disease/defence and redox/response to stress were affected for the comparative analysis. The results of this study can be used as a starting point for targeting host responsive genes in genetic manipulation of apple cultivars.

Human malaria caused by Plasmodium falciparum is a major global burden killing between 700,000 and 2.7 million people every year. Africa bears the greatest portion of this burden, with over three quarters of deaths occurring in African children, accounting for 18% of all child deaths in sub-Saharan Africa. Synthesis of tetrahydrofolate through the folate biosynthetic pathway is vital for the survival of P. falciparum parasites and is lacking in the human host. As such, enzymes of this pathway have long presented attractive targets for drug therapy and although increasingly being compromised by resistance, anti-folates such as pyrimethamine and sulfadoxine are still very valuable drugs in many malaria-endemic regions.In this project, further investigation of the enzymes of the folate biosynthetic pathway has been attempted by developing protocols to quantify these proteins and others through proteomic techniques. Two quantification techniques were pursued. The first was quantification using whole, heterologously expressed, stable-isotope labelled forms of P. falciparum proteins for use as heavy standards in mass spectrometry. Great difficulty was experienced in the effort to express and purify P. falciparum enzymes in E. coli expression systems, with only one enzyme successfully expressed and purified in a 13C-labelled form. This one protein was taken forward into quantification experiments. The second quantification technique used a stable-isotope labelled ‘QConcat’ protein, consisting of a number of peptides from 12 P. falciparum proteins of interest, as a heavy standard in mass spectrometry. This was successfully expressed and purified in a 13C-labelled form from an artificial gene using an E. coli expression system. This too was taken forward into quantification experiments.Quantification experiments using the QConcat-based quantification technique were successfully performed on whole P. falciparum extract. Among the proteins quantified were SHMT and DHFR, two proteins of great interest from the folate biosynthetic pathway. Consistent with results from different expression analysis techniques in the literature, the folate enzymes were found to be of lower abundance than housekeeping enzymes and SHMT was found to be more abundant than DHFR.For deep quantitative analysis of the P. falciparum proteome, it was found that fractionation was necessary. Fractionation in this project was performed using a ZOOM™ IEF fractionator (Invitrogen), an OFFGEL™ IEF fractionator (Agilent) and 1D SDS-PAGE. It was found that by using these fractionation techniques, more proteins could be identified within the P. falciparum proteome, with all but one of the enzymes of the folate biosynthetic pathway being identified. Significant advances in the sensitivity of mass spectrometers during this project have also greatly facilitated the investigation of the proteome. In some cases, this meant that proteins which were only previously accessible by prefractionation of the proteome could be seen in whole P. falciparum extract. Unfortunately, QConcat-based quantification using both fractionation and sensitive mass spectrometry could not be successfully achieved in the time available. However, the promising results obtained suggest that, after careful optimisation, such an approach will be valuable.

Contemporary proteomics studies require computational approaches to deal with both the complexity of the data generated, and with the volume of data produced. The amalgamation of mass spectrometry -- the analytical tool of choice in proteomics -- with the computational and statistical sciences is still recent, and several avenues of exploratory data analysis and statistical methodology remain relatively unexplored. The current study focuses on three broad analytical domains, and develops novel exploratory approaches and practical tools in each. Data transform approaches are the first explored. These methods re-frame data, allowing for the visualization and exploitation of features and trends that are not immediately evident. An exploratory approach making use of the correlation transform is developed, and is used to identify mass-shift signals in mass spectra. This approach is used to identify and map post-translational modifications on individual peptides, and to identify SILAC modification-containing spectra in a full-scale proteomic analysis. Secondly, matrix decomposition and projection approaches are explored; these use an eigen-decomposition to extract general trends from groups of related spectra. A data visualization approach is demonstrated using these techniques, capable of visualizing trends in large numbers of complex spectra, and a data compression and feature extraction technique is developed suitable for use in spectral modeling. Finally, a general machine learning approach is developed based on conditional random fields (CRFs). These models are capable of dealing with arbitrary sequence modeling tasks, similar to hidden Markov models (HMMs), but are far more robust to interdependent observational features, and do not require limiting independence assumptions to remain tractable. The theory behind this approach is developed, and a simple machine learning fragmentation model is developed to test the hypothesis that reproducible sequence-specific intensity ratios are present within the distribution of fragment ions originating from a common peptide bond breakage. After training, the model shows very good performance associating peptide sequences and fragment ion intensity information, lending strong support to the hypothesis. / Medicine, Faculty of / Medicine, Department of / Experimental Medicine, Division of / Graduate

Lysine acetylation is a post-translational modification (PTM) studied extensively in the context of histone proteins as a regulator of chromatin dynamics. Recent proteomic studies have revealed that as much as 10% of prokaryotic and mammalian proteins undergo lysine acetylation, and as such, the study of its biological consequences is rapidly expanding to include virtually all cellular processes. Unravelling the complex regulatory network governed by lysine acetylation will require an in depth knowledge of the lysine acetyltransferase enzymes that mediate catalysis, and moreover the development of methods that can identify enzyme-substrate relationships in vivo. This is complex task and will be aided significantly through the use of model organisms and systems biology approaches. The work presented in this thesis explores the function of the highly conserved NuA4 lysine acetyltransferase enzyme complex in the model organism Saccharomyces cerevisiae using systems biology approaches. By exploiting genetic screening tools available to the budding yeast model, I have systematically assessed the cellular roles of NuA4, thereby identifying novel cellular processes impacted by the function of the complex, such as vesicle-mediated transport and the stress response, and moreover identified specific pathways and proteins that are impacted by NuA4 KAT activity, including cytokinesis through the regulation of septin protein dynamics. Moreover, I have developed a mass spectrometry-based technique to identify NuA4-dependent acetylation sites amongst proteins that physically interact with NuA4 in vivo. Together this work demonstrates the diversity of processes impacted by NuA4 function in vivo and moreover highlights the utility of global screening techniques to characterize KAT function.