No description available.

Vector borne-diseases make up a significant portion of morbidity and mortality worldwide, being responsible for around 700,000 deaths annually according to the World Health Organization. Neglected, tropical diseases such as Chagas disease have a significant impact on people in Latin America, affecting millions, and especially those residing in rural areas. Chagas disease is the number one cause for heart disease in Latin America, and is caused by the Trypanosoma cruzi parasite, carried by Triatominae insect vectors. The intricate life cycle of the parasite, ecology and behavior of the vector, and lack of disease treatment options, make Chagas disease challenging to control. Prevention measures are highly sought after, and implementation science approaches such as Ecohealth management engage affected communities in disease prevention. Knowing what insect vectors are feeding on sheds light on vector ecology and behavior, aiding in vector management which is pivotal in disease prevention. While DNA-based methods have traditionally been used to study vector blood meals, they come with limitations and challenges, such as the need for fresh, high abundance blood meals. Therefore, the goal of this research was to evaluate Chagas vector blood meal sources using an innovative protein mass spectrometry-based approach. We demonstrate first the ability to utilize liquid chromatography tandem mass spectrometry (LC-MS/MS) to correctly identify hemoglobin protein peptides from mouse blood and subsequently identify Chagas vector blood meal sources from field-collected insect vectors where blood meal identification is compared with traditional DNA-based methods as a control. An experimental feeding study allowed us to then demonstrate the longevity of hemoglobin protein peptides for blood meal detection, showing LC-MS/MS-based blood meal identification outperforms DNA-based polymerase chain reaction (PCR) at least 4 weeks post-feeding and 12 weeks post-molting. This allowed us to test the limits of our innovative detection method experimentally and comparatively. Finally, we evaluated blood meals in field-caught insect vectors collected as part of a large collaborative Ecohealth project in Central America. LC-MS/MS identified two times as many blood meals in insect vectors, including those that did not have blood meals detected with DNA-based PCR. As single vectors often feed on multiple sources, we also validated our ability to decipher multiple blood meals from an individual vector and showed the ability to quantify a blood meal using synthetic AQUA (Absolute QUAntification) peptides, a first step in using quantification data for identifying blood meals not currently in our underlying database. Furthermore, we show that lower resolution mass spectrometers are able to identify blood meals from taxa correctly, an important and strong attribute of our LC-MS/MS-based method, opening the door to using proteomics in countries where Chagas disease is endemic and resources are limited. Even though expertise and resources of research labs differ in locations across the globe, herein is described how LC-MS/MS is a valuable additional tool for fighting neglected tropical diseases. Ultimately, hemoglobin-based LC-MS/MS vector blood meal identification is a complementary technique to available molecular methods and can confidently identify Chagas vector blood meal sources to aid in understanding vector biology and ecology, and aid in developing appropriate Ecohealth vector control measures.

Proteomic technology has been increasingly incorporated into agricultural research, as characterization of proteomes can provide valuable information for potential biomarkers of health and physiological status of an animal. As dairy cattle are a dominant production animal in the USA, their biofluids such as milk, blood, urine, and rumen fluid have been examined by proteomic analysis. The research outlined herein was performed to further characterize the dynamics of specific proteomes and relate them to dairy cattle physiology. The first experiment evaluated the diurnal dynamicity of the rumen metaproteome in Holstein dairy cattle. Rumen fluid was collected from three mid to late lactation multiparous dairy cattle (207 ± 53.5 days in milk) at three time points relative to their first morning offering of a total mixed ration (TMR) (0 h, 4 h, and 6 h after feeding). Samples were processed and labeled using Tandem Mass tagging before being further fractionated with a high pH reversed-phase peptide fractionation kit. Samples were analyzed by LC-MS/MS and statistically analyzed for variations across hour of sampling using the MIXED procedure of SAS with orthogonal contrasts. A total of 242 proteins were characterized across 12 microbial species, with 35 proteins identified from a variety of 9 species affected by time of collection. Translation-related proteins were correlated positively with increasing hour of sampling while more specific metabolic proteins were negatively correlated with increasing hour of sampling. Results suggest that as nutrients become more readily available, microbes shift from conversion-focused biosynthetic routes to more encompassing DNA-driven pathways. The second experiment aimed to characterize the milk fat globule membrane (MFGM) proteomes of colostrum and transition milk for comparison from multi- (n = 10) and primiparous (n = 10) Holstein dairy cattle. Samples were collected at four timepoints post-partum (milkings 1, 2, 4, and 14). After isolation of the protein lysates from the MFGM, proteins were labeled using Tandem Mass tagging and analyzed using LC-MS/MS techniques. Protein identification was completed using MASCOT and Sequest in Proteome Discoverer 2.2. Protein abundance values were scaled and analyzed using the MIXED procedure in SAS to determine the effect of parity, milking number, and parity x milking number, and the adaptive false-discovery rate (FDR)-adjusted P values were determined using the MULTTEST procedure of SAS. There were 104 proteins identified within the MFGM. Statistical analysis revealed that 44.2% of proteins were affected by parity, 70.2% by milking number, and 32.7% by the variable of parity x milking number. There was a two-fold difference in calcium sensing S100 proteins in cows differing in parity possibly due to the multiparous mammary gland being more adapted to the physiological demand of lactation or the lesser requirement of calcium in primiparous cows because of a lower production rate.

Myostatin is a negative regulator of muscle growth. When it is not present or non-functional double-muscling occurs, the primary characteristic of this phenotype being an increase in muscle mass. Another characteristic of double-muscling is an increased proportion of type IIB muscle fibres, which rely on glycolysis as their primary energy source, as opposed to type IIA and type I fibres which rely on oxidative phosphorylation. This switch in muscle metabolism directly impacts on the mitochondria, as mitochondria from glycolytic muscle fibres have been shown to have differences in metabolic activity. The increased proportion of glycolytic muscle fibres present in myostatin knockout animals provides a unique model to investigate alterations in muscle fibre type metabolism. The mouse model of myostatin knockout utilised during this study was generated by genetic deletion of exon three of the myostatin gene. Verification of this knockout was attempted by western blot analysis, but only the latency associated protein (LAP) was detected. Interestingly, the LAP was barely detectable in the knockout muscle suggesting deletion of exon three affects binding of anti-myostatin antibodies to the LAP, as that part of the gene is not deleted. A comparison of the basal mitochondrial stress levels was made, also by western blot analysis. The knockout mitochondria showed no change in levels of heat shock protein 60 or superoxide dismutase 2, indicating that they are not being subjected to any increased stress due to the myostatin knockout phenotype. A comparative proteomics approach was used to detect changes in the mitochondrial proteome of myostatin knockout gastrocnemius muscle to gain clues to how mitochondria from glycolytic muscle fibres differ from those present in oxidative fibres. This was undertaken using two-dimensional electrophoresis (2-DE), in-gel tryptic digests and peptide mass fingerprinting by mass spectrometry. A 2-DE gel protein loading of 220 g was shown to give the best protein spot resolution and the most crucial step in the loading process was found to be the laying of the immobilized pH gradient, which had to be performed very carefully to obtain a consistent loading pattern. This study resolved only around 160 protein spots out of the estimated 1,000 to 2,000 proteins present in the mitochondria. Modulation of six proteins was seen at a plt0.1 level, but were unable to be identified using the current methodology. More abundant mitochondrial proteins were able to be identified, but showed no significant modulation. Malate dehydrogenase and 3-hydroxyacyl-CoA dehydrogenase, which were identified during this study, have been reported to have decreased activity in mitochondria from glycolytic muscle fibres. This study suggests that the change in activity observed by other researchers is due to inhibition of these enzymes in the glycolytic fibres or activation in the oxidative fibres.

Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (Ph. D)--Ohio State University, 2006. / Available online via OhioLINK's ETD Center; full text release delayed at author's request until 2007 Aug 16

Thesis (Ph.D.)--York University, 2003. Graduate Programme in Biology. / Typescript. Includes bibliographical references. Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pNQ99195

Separations coupled to mass spectrometry (MS) are widely used for large-scale protein identification in order to reduce the adverse effects of analyte ion suppression, increase the dynamic range, and as a deconvolution technique for complex datasets typical of cellular protein complements. In this work, matrix assisted laser desorption-ionization is coupled with ion mobility (IM) separation for the analysis of biological molecules. The utility of liquid-phase separations coupled to MS lies in the orthogonality of the two separation dimensions for all analytes. The data presented in this work illustrates that IM-MS relies on the correlation between separation dimensions for different classes (either structural or chemical) of analyte ions to obtain a useful separation. For example, for a series of peptide ions of increasing mass-to-charge (m/z) a plot drift time in the IM drift cell vs. m/z increases in a near-linear fashion, but DNA or lipids having similar m/z values will have very different IM drift time-m/z relationships, thus drift time vs. m/z can be used as a qualitative tool for compound class identification. In addition, IM-MS is applied to the analysis of large peptide datasets in order to determine the peak capacity of the method for bottom-up experiments in proteomics, and it is found that IM separation increases the peak capacity of an MS-only experiment by a factor of 5-10. The population density of the appearance area for peptides is further characterized in terms of the gas-phase structural propensities for tryptic peptide ions. It is found that a small percentage (~3%) of peptide sequences form extended (i.e., helical or β-sheet type) structures in the gas-phase, thus influencing the overall appearance area for peptide ions. Furthermore, the ability of IM-MS to screen for the presence of phosphopeptides is characterized, and it is found that post translationally modified peptides populate the bottom one-half to one-third of the total appearance area for peptide ions. In general, the data presented in this work indicates that IM-MS offers dynamic range and deconvolution capabilities comparable to liquid-phase separation techniques coupled to MS on a time scale (ms) that is fully compatible to current MS, including TOF-MS, technology.

The beginning of the twenty-first century has been characterized by an explosion of biological information. The avalanche of data grows daily and arises as a consequence of advances in the fields of molecular biology and genomics and proteomics. The challenge for nowadays biologist lies in the de-codification of this huge and complex data, in order to achieve a better understanding of how our genes shape who we are, how our genome evolved, and how we function. Without the annotation and data mining, the information provided by for example high throughput genomic sequencing projects is not very useful. Bioinformatics is the application of computer science and technology to the management and analysis of biological data, in an effort to address biological questions. The work presented in this thesis has focused on the use of Grid and High Performance Computing for solving computationally expensive bioinformatics tasks, where, due to the very large amount of available data and the complexity of the tasks, new solutions are required for efficient data analysis and interpretation. Three major research topics are addressed; First, the use of grids for distributing the execution of sequence based proteomic analysis, its application in optimal epitope selection and in a proteome-wide effort to map the linear epitopes in the human proteome. Second, the application of grid technology in genetic association studies, which enabled the analysis of thousand of simulated genotypes, and finally the development and application of a economic based model for grid-job scheduling and resource administration. The applications of the grid based technology developed in the present investigation, results in successfully tagging and linking chromosomes regions in Alzheimer disease, proteome-wide mapping of the linear epitopes, and the development of a Market-Based Resource Allocation in Grid for Scientific Applications. / QC 20100622