Rozprawy doktorskie na temat „Proteomic pattern”

Familial Adenomatous Polyposis (FAP) is one of the most important clinical forms of inherited susceptibility to colorectal cancer, that is characterized by the development of hundreds to thousands of adenomas in the colon and rectum during the second decade of life. FAP is due to a germline mutation in the APC gene or to biallelic variations of MutYH gene. Almost all patients will develop cancer if the disease is not identified and surgically treated at an early stage. The aim of this study was to characterize, by peptidomic and genetic approaches, 4 pa-tients that, although at the colonoscopy showed many polyps, they did not present any mutations of APC and MutYH genes (defined here unresolved FAP). Regarding the peptidomic study, MALDI-TOF analysis was performed on mutated and unresolved FAP patients. These data were compared with the one from adenoma patients, CRC patients and healthy control subjects. The peptide fingerprint of mutated FAP patients was obtained after performing statistical analysis. A subset of 45 ionic species was found differently expressed in the four groups considered, 12 of them peculiar of FAP patients. Four ionic species were found significantly different in the switch between adenoma and malignant carcinoma. In this study, the potentially prognostic peptides identified derive mainly from circulating proteins and some of them are involved in the inflammatory response. In particular, proteins such as Complement C3 and C4 are known to be cleaved by exoproteases that seem pathology-related. In the case of unresolved FAP patients, in order to better define a specific pattern, the data from MALDI-TOF were combined with whole exome sequencing. The peptidomics data clearly mark a substantial difference between mutated and unresolved FAP patients. Indeed, unresolved FAP patients have characteristics similar to the control subjects, adenoma patients, CRC patients but not to mutated FAP patients. To understand the possible molecular pathway involved in the unresolved FAP cases, the whole exome sequencing (WES) was performed. From WES data analysis, 285 genes present in all the four unresolved FAP patients were filtered and selected. Among them, the O-linked glycans pathway of the mucins was the most represented. In conclusion, in this study it was defined for the first time a specific panel of peptides for mutated FAP patients, that could be useful to monitor and predict the pathological evolution of adenocarcinoma malignancy. Furthermore, it was possible to characterize a preliminary genetic variations pattern for unresolved FAP patients, in which mucin genes might represent the key of the molecular pathway involved. However, further study are necessary to relate the identified mucin gene variations to their possible causative role in the polyposis. Future analysis of this pattern will be helpful, indeed, to better understand the interatome (the biological network that in-cludes the whole set of direct and indirect molecular interactions in a cell) of these un-resolved FAP patients.
La poliposi adenomatosa familiare (FAP) è una delle più importanti forme cliniche di cancro colo-rettale ereditario ed è caratterizzata dallo sviluppo di centinaia/migliaia di polipi adenomatosi nel colon e nel retto durante la seconda decade di vita. La FAP è causata da una mutazione germinale del gene APC o da varianti bialleliche del gene MutYH. Quasi tutti i pazienti FAP sviluppano il cancro se la patologia non viene precocemente identificata e trattata chirurgicamente. Lo scopo di questo lavoro è stato caratterizzare 4 pazienti in cui, nonostante l’esame colonscopico presentasse una poliposi conclamata, non risultavano mutazioni nei gene APC e MutYH (in questa tesi definiti pazienti FAP irrisolti) utilizzando un approccio integrato di peptidomica e genomica. Riguardo la peptidomica, il MALDI-TOF è stato utilizzato per studiare il profilo peptidico plasmatico di pazienti FAP mutati ed irrisolti comparando i dati ottenuti con quelli derivanti dallo studio di pazienti con adenoma, cancro colo-rettale e soggetti sani di controllo. Dopo analisi statistica è stato ottenuto il fingerprint peptidico dei pazienti FAP mutati. Sono state ottenute 45 specie ioniche differentemente espresse nei quattro gruppi considerati, 12 delle quali peculiari per i pazienti FAP. L’intensità di segnale di quattro di queste specie ioniche è stata trovata statisticamente alterata nello switch tra adenoma e carcinoma maligno. I peptidi potenzialmente prognostici identificati in questo studio derivano principalmente da proteine circolanti, alcune delle quali implicate nella risposta infiammatoria. In particolare è noto dalla letteratura che proteine del sistema del complemento come C3 e C4 vengono tagliate da esoproteasi che sembrano essere patologia correlate. Riguardo ai pazienti FAP irrisolti, per definirne un pattern specifico, i dati derivanti dall’analisi con il MALDI-TOF sono stati combinati con quelli ottenuti dal sequenzia-mento dell’esoma. I dati di peptidomica hanno chiaramente evidenziato le differenze tra pazienti FAP mutati e FAP irrisolti. Infatti i pazienti FAP irrisolti presentano caratteristiche simili a quelle dei soggetti di controllo, dei pazienti con adenoma e cancro colo rettale ma non a quelle dei pazienti FAP mutati. Allo scopo di capire la via di trasduzione del segnale implicata, è stato quindi eseguito il sequenziamento dell'esoma dei pazienti FAP irrisolti. Da questa analisi sono stati selezionati 285 geni variati in tutti i pazienti e tra questi la via di trasduzione del segnale della O-glicosilazione delle mucine è risultata la più rappresentata. In conclusione, in questo studio è stato definito per la prima volta un set peptidico specifico per i pazienti FAP mutati che potrebbe essere utilizzato per monitorare e predire l’evoluzione patologica della malattia. Inoltre è stato possibile caratterizzare un pattern preliminare per i pazienti FAP irrisolti in cui i geni delle mucine potrebbero rappresentare la chiave della via di trasduzione del segnale implicata. Ulteriori studi saranno necessari per correlare i geni delle mucine con la poliposi e costruire l'interatoma (network biologico definito come l’insieme di tutte le interazioni molecolari dirette e indirette che ci sono all'interno di una cellula e di un organismo) di questi pazienti FAP irrisolti.

Glioblastoma multiforme (GBM) is the most common primary brain tumor. Given the current standard of care, the prognosis for patients diagnosed with this disease is still poor. There consequently exists a need to improve current treatments, as well as to develop new ones. Many obstacles however need to be overcome to facilitate this effort and one of these involves the development of improved methods to monitor treatment effects. At present, the effects of treatment are typically assessed by radiological means several months after its initiation, which is unsatisfactory for a fast growing tumor like GBM. It is however likely that treatment effects can be detected on a molecular level long before radiological response, especially considering many of the targeted therapies that are currently being developed. Biomarkers for treatment efficacy may be of great importance in the future individualization of brain tumor treatment. The work presented herein was primarily focused on detecting early effects of GBM treatment. To this end, we designed experiments in the BT4C rat glioma model in which we studied effects of both conventional radiotherapy and an experimental angiogenesis inhibitor, vandetanib. Brain tissue samples were analyzed using a high throughput mass spectrometry (MS) based screening, known as Surface Enhanced Laser Desorption/Ionization - Time of Flight - Mass Spectrometry (SELDI-TOF-MS). The vast amounts of data generated were subsequently analyzed by established multivariate statistical methods, such as Principal Component Analysis (PCA), Partial Least Squares (PLS), and Orthogonal Partial Least Squares (OPLS), developed for analysis of large and complex datasets. In the radiotherapy study we detected a protein spectrum pattern clearly related to tumor progression. We notably observed how this progression pattern was hampered by radiotherapy. The vandetanib study also revealed significant alterations of protein expression following treatment of different durations, both in tumor tissue and in normal brain contralateral to the tumor. In an effort to further elucidate the pathophysiology of GBM, particularly in relation to treatment, we collected extracellular fluid (ECF) samples from 11 patients diagnosed with inoperable GBM. The samples were collected by means of stereotactic microdialysis, both from within the contrast enhancing tumor and the brain adjacent to tumor (BAT). Samples were collected longitudinally from each patient in a time span of up to two weeks, during which the patient received the first five fractions of radiotherapy. The ECF samples were then analyzed by Gas Chromatography Mass Spectrometry (GC-MS) to screen them with respect to concentrations of low molecular weight compounds (metabolites). Suitable multivariate analysis strategies enabled us to extract patterns of varying metabolite concentrations distinguishing between samples collected at different locations in the brain as well as between samples collected at different time points in relation to treatment. In a separate study, we also applied SELDI-TOF-MS and multivariate statistical methods to unravel possible differences in protein spectra between invasive and non-invasive WHO grade I meningiomas. This type of tumor can usually be cured by surgical resection however sometimes it grows invasively into the bone, ultimately causing clinical problems. This study revealed the possibility to differentiate between invasive and non-invasive benign meningioma based on the expression pattern of a few proteins. Our approach, which includes sample analysis and data handling, is applicable to a wide range of screening studies. In this work we demonstrated that the combination of MS screening and multivariate analyses is a powerful tool in the search for patterns related to treatment effects and diagnostics in brain tumors.

The knowledge of the human genome sequence, as revealed in the HUGO project, has created exciting new possibilities for biomedical research. The Swedish Human Proteome Resource (HPR) program aims to make use of this information to gain further insight into the human proteome. Recombinant proteins are generated from coding sequences identified from the human genome sequence and used to produce specific antibodies to target proteins. Antibodies are subsequently utilized for functional analysis of the corresponding proteins using tissue micro arrays. The aim of my project was to investigate the possibility of distinguishing characteristic distribution patterns of intracellular proteins in the resolution capacity offered by light microscopy. A map of representative distribution patterns was created using immunohistological staining with commercially available antibodies toward well-characterised proteins in the cell. Such a map could then aid in interpreting the results of immunohistological staining of intracellular proteins using antibodies produced within the Human Proteome Resource program. Proteins manifested in nucleus, nuclear membrane and plasma membrane were clearly visible at the expected location. Proteins manifested in different organelles in the cytoplasm however, showed all a similar staining pattern, making determination of exact protein location uncertain. A possible explanation is the resolution of the light microscope not being sufficient to visualize certain proteins specific to organelles in the cytoplasm. Results may also have been influenced by the choice of secondary antibody, where the strenghtened signal generated by an enzyme labelled polymer may have a negative effect on depiction of details in the image generated.

Proteins are essential building blocks in every living cell, and since the complete human genome was sequenced in 2004, researchers have attempted to map the human proteome, which is the functional representation of the genome. One such initiative is the Human Protein Atlas programme (HPA), which generates monospecific antibodies towards all human proteins and uses these for high-throughput tissue profiling on tissue microarrays (TMAs). The results are publically available at the website www.proteinatlas.org. In this thesis, TMAs were used for analysis of expression patterns in various research areas. Different search queries in the HPA were tested and evaluated, and a number of potential biomarkers were identified, e.g. proteins exclusively expressed in islets of Langerhans, but not in exocrine glandular cells or other abdominal organs close to pancreas. The identified candidates were further analyzed on TMAs with pancreatic tissues from normal and diabetic individuals, and colocalization studies with insulin and glucagon revealed that several of the investigated proteins (DGCR2, GBF1, GPR44 and SerpinB10) appeared to be beta cell specific. Moreover, a set of proteins differentially expressed in lung cancer stroma was further analyzed on a clinical lung cancer cohort in the TMA format, and one protein (CD99) was significantly associated with survival. In addition, TMAs with tissue samples from different species were generated, e.g. for mapping of influenza virus attachment in various human and avian tissues. The results showed that the gull influenza virus H16N3 attached to human respiratory tract and eye, suggesting possible transmission of the virus between gull and human. TMAs were also used for analysis of protein expression differences between humans and other primates, and two proteins (TCF3 and SATB2) proved to be significantly differentially expressed on the human lineage at both the protein level and the RNA level.   In conclusion, this thesis exemplifies the potential of the TMA technology, which can be used for analysis of expression patterns in a large variety of research fields, such as biomarker discovery, influenza virus research or further understanding of human evolution.

The evolution of synapses from early proto-synaptic protein complexes in unicellular eukaryotes to sophisticated machines comprising thousands of proteins parallels the emergence of finely tuned synaptic plasticity, a molecular correlate for memory and learning. Phenotypic change in organisms is ultimately the result of evolution of their genotype at the molecular level. Selection pressure is a measure of how changes in genome sequence that arise though naturally occurring processes in populations are fixed or eliminated in subsequent generations. Inferring phylogenetic information about proteins such as the variation of selection pressure across coding sequences can provide valuable information not only about the origin of proteins, but also the contribution of specific sites within proteins to their current roles within an organism. Recent evolutionary studies of synaptic proteins have generated attractive hypotheses about the emergence of finely-tuned regulatory mechanisms in the post-synaptic proteome related to learning, however, these analyses are relatively superficial. In this thesis, I establish a scalable molecular phylogenetic modelling framework based on three new inference methodologies to investigate temporal and spatial aspects of selection pressure changes for the whole human proteome using protein orthologs from up to 68 taxa. Temporal modelling of evolutionary selection pressure reveals informative features and patterns for the entire human proteome and identifies groups of proteins that share distinct diversification timelines. Multi-ontology enrichment analysis of these gene cohorts was used to aid biological interpretation, but these approaches are statistically under powered and do not capture a clear picture of the emergence of synaptic plasticity. Subsequent pathway-centric analysis of key synaptic pathways extends the interpretation of temporal data and allows for revision of previous hypotheses about the evolution of complex synaptic function. I proceed to integrate inferred selection pressure timeline information in the context of static protein-protein interaction data. A network analysis of the full human proteome reveals systematic patterns linking the temporal profile of proteins’ evolution and their topological role in the interaction graph. These graphs were used to test a mechanistic hypothesis that proposed a propagating diversification signal between interactors using the temporal modelling data and network analysis tools. Finally, I analyse the data of amino-acid level spatial modelling of selection pressure events in Arc, one of the master regulators of synaptic plasticity, and its interactors for which detailed experimental data is available. I use the Arc interactome as an example to discuss episodic and localised diversifying selection pressure events in tightly coupled complexes of protein and showcase potential for a similar systematic analysis of larger complexes of proteins using a pathway-centric approach. Through my work I revised our understanding of temporal evolutionary patterns that shaped contemporary synaptic function through profiling of emergence and refinement of proteins in multiple pathways of the nervous system. I also uncovered systematic effects linking dependencies between proteins with their active diversification, and hypothesised about their extension to domain level selection pressure events.

In this thesis, methods to study gene and protein expression in cells and tissues were developed and utilized in combination with protein-specific antibodies, with the overall objective to attain greater understanding of protein function.

To analyze protein expression in in vitro cultured cell lines, a cell microarray (CMA) was developed, facilitating antibody-based protein profiling of cell lines using immunohistochemistry (IHC). Staining patterns in cell lines were analyzed using image analysis, developed to automatically identify cells and immunohistochemical staining, providing qualitative and quantitative measurements of protein expression. Quantitative IHC data from CMAs stained with nearly 3000 antibodies was used to evaluate the adequacy of using cell lines as models for cancer tissue. We found that cell lines are homogenous with respect to protein expression profiles, and generally more alike each other, than corresponding cancer cells in vivo. However, we found variability between cell lines in regards to the level of retained tumor phenotypic traits, and identified cell lines with a preserved link to corresponding cancer, suggesting that some cell lines are appropriate model systems for specific tumor types.

Specific gene expression patterns were analyzed in vitiligo vulgaris and malignant melanoma. Transcriptional profiling of vitiligo melanocytes revealed dysregulation of genes involved in melanin biosynthesis and melanosome function, thus highlighting some mechanisms possibly involved in the pathogenesis of vitiligo. Two new potential markers for infiltrating malignant melanoma, Syntaxin-7 and Discs large homolog 5, were identified using antibody-based protein profiling of melanoma in a tissue microarray format. Both proteins were expressed with high specificity in melanocytic lesions, and loss of Syntaxin-7 expression was associated with more high-grade malignant melanomas.

In conclusion, the combination of antibody-based proteomics and microarray technology provided valuable information of expression patterns in cells and tissues, which can be used to better understand associations between protein signatures and disease.

Thesis (PhD)--Stellenbosch University, 2013.
ENGLISH ABSTRACT: Introduction: Coronary heart disease (CHD) is the leading cause of death worldwide with 3.8 million men and 3.4 million women dying globally each year. Although existing myocardial reperfusion strategies such as thrombolysis and percutaneous coronary intervention (PCI), if applied in a timely manner, limit myocardial infarct size, the mortality and morbidity remains significantly high. Ischaemic preconditioning (IPC) may offer the potential to attenuate myocardial ischaemia/reperfusion injury through cardioprotective signaling pathways which is recruited at the time of myocardial reperfusion, thereby improving clinical outcomes in patients with coronary artery disease. Ischaemic preconditioning is a phenomenon whereby short intermittent episodes of coronary occlusion followed by reperfusion protect the myocardium against a subsequent period of sustained ischaemia. This protection is reflected in the limitation of infarct size and improved functional recovery of the ischaemic heart during reperfusion. Despite intensive research efforts, the promise of an effective cardioprotective strategy using the endogenous protective mechanisms of the heart which underlies IPC, has not yet been materialized. Although progress has been made in terms of signaling mechanisms in the preconditioned heart, the identification of the myocardial reperfusion phase as the critical “window” for cardioprotection, requires the elucidation of the signal transduction pathways during the reperfusion phase after IPC. In view of the above, the aims of the present study were to investigate: i. the involvement of the RISK pathway and p38 MAP kinase pathway in IPC during early and late reperfusion ii. the involvement of heat shock protein-27 (HSP-27), heat shock protein-70 (HSP-70), GSK-3β, CAMKII, AMPK and the transcription factor CREB in the context of IPC during early reperfusion iii. the involvement of autophagy and apoptosis during early and late reperfusion after IPC iv. the correlation of the protein kinases with the hemodynamic parameters of the heart v. the mechanism of IPC by means of two-dimensional (2D) proteomics Methods: The isolated perfused working rat heart model was used with functional recovery as end-point. Hearts were preconditioned (IPC) for 3x5 min global ischaemia, alternated with 5 min reperfusion. Hearts were subjected to 25 min sustained global ischaemia, followed by 5, 10, 15 or 30 min reperfusion when hearts were snap-frozen for western blotting analysis. Alternatively, hearts were reperfused for 30 min to record hemodynamic parameters and measure functional recovery. Non-preconditioned (Non-IPC) hearts were stabilized for 30 min and subjected to 25 min sustained global ischaemia followed by 5, 10, 15 or 30 min reperfusion when hearts were snap-frozen. Alternatively Non-IPC hearts were reperfused for 30 min to serve as control for the 30 min reperfused IPC group. Activation of the protein kinases was determined by western blotting analysis. For the proteomic study mitochondrial and cytosolic proteins were isolated from heart tissue and separated in the first dimension by isoelectric focusing, followed by separation in the second dimension by two dimensional gel electrophoresis. The PD Quest software programme was used to identify significantly expressed protein spots. Protein spots of interest were excised and subjected to in-gel digestion and the resulting peptides were analysed by mass spectrometry. Proteins were identified by Mascot and the Swiss Prot database. Results: Western blotting analysis demonstrated that the RISK pathway and p38 MAPK are activated very early in reperfusion, but the activation is not sustained during the reperfusion period. Autophagy is also upregulated during this early reperfusion phase; it is attenuated in the middle reperfusion phase and increase for a second peak of upregulation in the late reperfusion phase. In addition, we identified CAMKII as a novel marker of functional recovery in IPC after reperfusion. The proteomic analysis identified twenty differentially expressed mitochondrial and thirty six differentially expressed cytosolic proteins between Non-IPC and IPC hearts. Functions ascribed to the majority of these individual proteins were directly related to cardiac metabolism. Conclusion: Activation of the majority of the protein kinases investigated in the present study is associated with the hemodynamic parameters of the heart instead of functional recovery. Results indicated that the variable signaling patterns could be attributed to differences in heart rate and the effect thereof (ejection fraction, minimum and maximum rate of contraction), as a result of sympathetic stimulation due to psychological stress in the animals before slaughtering. Proteomics results demonstrated that IPC hearts which failed after ischaemia /reperfusion are metabolically compromised and “worse off” compared to non-IPC hearts.
AFRIKAANSE OPSOMMING: Inleiding: Koronêre hartsiekte is die vernaamste oorsaak van sterftes wêreldwyd met 3.8 miljoen mans en 3.4 miljoen vrouens wat jaarliks sterf. Alhoewel bestaande miokardiale herperfusie strategieë soos trombolise en perkutane koronêre intervensie (PKI), wanneer betyds toegepas, miokardiale infarktgrootte beperk, bly mortaliteit en morbiditeit steeds hoog. Isgemiese prekondisionering (IPK) beskik oor die potensiaal om miokariale isgemie/herperfusie skade te verminder deur beskermende seinoordragpaaie tydens miokardiale herperfusie te aktiveer en sodoende die pasiënte wat aan koronêre arterie siekte ly, se prognose te verbeter. Isgemiese prekondisionering verwys na die verskynsel waartydens kort episodes van isgemie opgevolg deur herperfusie, die miokardium teen ‘n daaropvolgende langdurige isgemiese insident beskerm. Hierdie beskerming word gereflekteer in die beperking van infarktgrootte en verbeterde funksionele herstel van die isgemiese hart tydens herperfusie. Ten spyte van intensiewe navorsingspogings is die presiese meganisme van endogene beskerming tydens IPK nog nie ten volle ontrafel nie. Die identifisering van die miokardiale herperfusie fase se kritiese “vensterperiode” van beskerming, noodsaak ‘n volledige analise van die seinoordragpaaie wat geaktiveer word tydens die herperfusie fase na IPK. In die lig van bogenoemde, was die doel van die huidige studie om die volgende te ondersoek: i. die betrokkenheid van die RISK seinoordragpad en p38 MAP kinase tydens vroeë en laat herperfusie na IPK ii. die betrokkenheid van “heat shock protein-27” (HSP-27), “heat shock protein- 70” (HSP-70), GSK -3β, CAMKII, AMPK en die transkripsie faktor, CREB, in die konteks van IPK tydens vroeë herperfusie iii. die betrokkenheid van outofagie en apoptose tydens vroeë en laat herperfusie na IPK iv. die korrelasie van die proteïenkinases met die hemodinamiese parameters van die hart v. die meganisme van IPK deur middel van twee dimensionele proteomika Metodes: Die geïsoleerde werkende rothart model, met funksionele herstel as eindpunt, is gebruik. Harte is geprekondisioneer (IPK) met 3x5 min globale isgemie, afgewissel met 5 min herperfusie. Daarna is harte blootgestel aan 25 min volgehoue globale isgemie, gevolg deur 5, 10, 15 of 30 min herperfusie, waartydens harte gevriesklamp is. Alternatiewelik, is harte blootgestel aan 30 min herperfusie ten einde funksionele herstel te meet en hemodinamiese parameters te registreer. Nie-geprekondisioneerde (Non-IPK) harte is gestabiliseer vir 30 min, waarna dit onderwerp is aan 25 min volgehoue globale isgemie, gevolg deur 5, 10, 15 of 30 min herperfusie, waartydens harte gevriesklamp is vir westelike klad analise. Alternatiewelik, is Non-IPK harte onderwerp aan 30 min herperfusie om te dien as kontrole vir die 30 min IPK groep. Aktivering van die proteïenkinases is bepaal deur westelike klad analise. Vir die proteomiese studie, is onderskeidelik mitokondriale en sitosoliese proteïene geïsoleer en geskei in die eerste dimensie met behulp van isoelektriese fokusering, gevolg deur skeiding in die tweede dimensie met behulp van twee dimensionele gel elektroforese. Die PDQuest sagteware program is gebruik om proteïenkolle te identifiseer wat statisties beduidende verskille toon. Proteïenkolle van belang is uitgesny en onderwerp aan in-gel tripsinering en die peptiede wat sodoende verkry is, is deur middel van massa spektrometrie geanaliseer. Proteïene is geïdentifiseer deur Mascot en die Swiss Prot databasis. Resultate: Westelike klad analise het aangetoon dat die RISK pad en p38 MAPK geaktiveer is tydens vroeë herperfusie, maar die aktivering word nie volgehou tydens die hele herperfusie periode nie. Outofagie word gestimuleer tydens die vroeë herperfusie fase; dit word onderdruk in die middel herperfusie fase en bereik ‘n tweede piek van stimulering in die laat herperfusie fase. Die proteomiese analise het onderskeidelik twintig differensieel gereguleerde mitokondriale proteïene en ses en dertig differensieel gereguleerde sitosoliese proteïene geïdentifiseer tussen Non-IPK en IPK. Die grootste persentasie van hierdie proteïene is direk betrokke by miokardiale energie metabolisme. CAMKII is geidentifiseer as ‘n unieke merker van funksionele herstel in IPK tydens reperfusie. Gevolgtrekking: Aktivering van die meeste van die proteïenkinases wat ondersoek is in die huidige studie, is geassosieer met die hemodinamiese parameters van die hart, in plaas van funksionele herstel. Die resultate het aangetoon dat die varierende patrone van kinase aktivering toegeskryf kan word word aan verskille in harttempo en die effek daarvan (ejeksie fraksie, minimum en maksimum tempo van kontraksie), as gevolg van simpatiese stimulasie toegeskryf aan sielkundige stres in die diere voor slagting. Proteomiese analise het getoon dat IPK harte wat faal na isgemie/reperfusie metabolies gekompromiseer is en “slegter daaraan toe” is, in vergelyking met Non-IPK harte.

Fundulus is a diverse and widespread genus of small teleost fish of North America. Due to its high tolerance for physiochemical variation (e.g. temperature, oxygen, salinity), Fundulus is a model organism to study physiological and molecular adaptations to environmental stress. The thesis focuses on patterns of protein expression in Fundulus heteroclitus and F. grandis.The patterns of protein expression were investigated using traditional methods of enzyme activity measurements and recent proteomic approaches. The findings of the study can be used to guide future studies on the proteomic responses of vertebrates to environmental stress. Chapter 2 focuses on measurement of the temporal effects of oxygen treatments on the maximal specific activities of nine glycolytic enzymes in liver and skeletal muscle during chronic exposure (28d) of Fundulus heteroclitus. The fish was exposed to four different oxygen treatments: hyperoxia, normoxia, moderate hypoxia, and severe hypoxia. The time course of changes in maximal glycolytic enzyme specific activities was assessed at 0, 8, 14 and 28 d. The results demonstrate that chronic hypoxia alters the capacity for carbohydrate metabolism in F. heteroclitus, with the important observation that the responses are both tissue- and enzyme-specific. Chapter 3 studies the effect of tissue storage on protein profile of tissues of F. grandis. The technique of one dimensional gel electrophoresis (1D-SDS-PAGE) was used to assess the effects of tissue sampling, flash frozen in liquid nitrogen versus immersion of fresh tissue in RNA later, for five tissues, liver, skeletal muscle, brain, gill, and heart, followed by LC-MS/MS to identify protein bands that were differentially stabilized in gill and liver. The study shows that, in F. grandis, the preferred method of preservation was tissue specific. xi Chapter 4 focuses on the use of advanced 2DE-MS/MS to characterize the proteome of multiple tissues in F. grandis. Database searching resulted in the identification of 253 non-redundant proteins in five tissues: liver, muscle, brain, gill, and heart. Identifications include enzymes of energy metabolism, heat shock proteins, and structural proteins. The protein identification rate was approximately 50 % of the protein spots analyzed. This identification rate for a species without a sequenced genome demonstrates the utility of F. grandis as a model organism for environmental proteomic studies in vertebrates.

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The ovarian cancer is difficult to diagnose in the early stages of development. In this work we bring a study of a new method that gave us great accuracy rates based on a bioinformatics tool called surface enhanced for laser desorption and ionization (SELDI-TOF) used to generate proteomic patterns which is one of the technologies advanced in the diagnosis. Our goal is to contribute to effectiveness of this tool, which already helps diagnosis earlier, our methodology uses independent component analysis (ICA) for feature extraction and neural networks to classify between malignancy and no malignancy in a database of the research center cancer in the U.S.A. Our work rates obtained acurracy 97%, 98% specificity and 96% sensitivity.
O câncer de ovário possui difícil diagnóstico nas primeiras fases de desenvolvimento. Neste trabalho trazemos um estudo de um novo método que nos deu ótimas taxas de precisão baseado em uma ferramenta da bio-informática chamada superfície mehorada a laser para ionização e dessorção (SELDI-TOF) usada para geração de padrões proteômicos que é uma das tecnologias mais avançada no auxílio ao diagnóstico. Nosso objetivo é contribuir para eficácia desta esta ferramenta, que já auxilia o dignóstico precoce, nossa metodologia usa análise de componentes independentes (ICA) para extração de caractéristicas e redes neurais para classificar entre malignidade e não malignidade em uma base de dados do centro de pesquisa do câncer nos EUA. Nosso trabalho obteve taxas de 97% de acurária, 98% de especifidade e 96 % de sensibilidade.

碩士
實踐大學
食品營養研究所
93
Monascus pigments are important colorings in food application, but Monascus biochemical pathways and regulation of nutrient metabolism concerning pigment production remain unknown. Rice starch and sodium nitrate substrates were firstly reported as better pigment-producing substrates compared to lactose and yeast extract substrates. A comparison of protein expression by proteomic analysis with two-dimensional gel electrophoresis, matrix-assisted laser desorption ionization time of flight/time of flight mass spectrometry (MALDI-TOF/TOF MS), tandem mass spectrometry (MS/MS) and database interrogation was conducted on Monascus pilosus grown between the rice nitrate and lactose yeast extract growth substrates. Out of eleven Monascus strains in the screening experiment, M. pilosus BCRC 31527 was selected; it had a maximum pigment production and revealed two types of culture development patterns between this two different growth substrates. In cultivation of M. pilosus BCRC 31527, carbon source in the lactose yeast extract growth substrate remained almost unused during the fermentation and, in the rice nitrate growth substrate, rice starch was consumed gradually. Of the total of measured proteins, 17% of the proteins were identified. The average expression levels of the enzymes in the lactose yeast extract growth substrate showed approximately 3-fold increases when compared to the rice nitrate growth substrate. The occurrence of up-regulation of four glycolytic enzymes, including glyceraldehyde-3-phosphate dehydrogenase, enolase, pyruvate kinase,and adenylate kinase, and three providing reducing equivalent energy enzymes at the initiation of the stationary phase in the lactose yeast extract growth substrate was presumed to result from the release of carbon catabolite repression due to carbon limitaion. Cencerning the NM growth substrate due to lack of the KH2PO4, the NM growth substrate could be considered as a low-potassium and -phosphate complex medium relative to the control. We found that the NM growth substrate induced an up-regulation in aldehyde dehydrogenase and several glycolytic enzymes, including glyceraldehyde-3-phosphate dehydrohygenase, enolase, pyruvate kinase.

Pattern discovery in protein structures is a fundamental task in computational biology, with important applications in protein structure prediction, profiling and alignment. We propose a novel approach for pattern discovery in protein structures using Particle Swarm-based flying windows over potentially promising regions of the search space. Using a heuristic search, based on Particle Swarm Optimization (PSO) is, however, easily trapped in local optima due to the sparse nature of the problem search space. Thus, we introduce a novel fitness-based stagnation detection technique that effectively and efficiently restarts the search process to escape potential local optima. The proposed fitness-based method significantly outperforms the commonly-used distance-based method when tested on eight classical and advanced (shifted/rotated) benchmark functions, as well as on two other applications for proteomic pattern matching and discovery. The main idea is to make use of the already-calculated fitness values of swarm particles, instead of their pairwise distance values, to predict an imminent stagnation situation. That is, the proposed fitness-based method does not require any computational overhead of repeatedly calculating pairwise distances between all particles at each iteration. Moreover, the fitness-based method is less dependent on the problem search space, compared with the distance-based method. The proposed pattern discovery algorithms are first applied to protein contact maps, which are the 2D compact representation of protein structures. Then, they are extended to work on actual protein 3D structures and interaction networks, offering a novel and low-cost approach to protein structure classification and interaction prediction. Concerning protein structure classification, the proposed PSO-based approach correctly distinguishes between the positive and negative examples in two protein datasets over 50 trials. As for protein interaction prediction, the proposed approach works effectively on complex, mostly sparse protein interaction networks, and predicts high-confidence protein-protein interactions — validated by more than one computational and experimental source — through knowledge transfer between topologically-similar interaction patterns of close proximity. Such encouraging results demonstrate that pattern discovery in protein structures and interaction networks are promising new applications of the fast-growing and far-reaching PSO algorithms, which is the main argument of this thesis.
Thesis (Ph.D, Computing) -- Queen's University, 2014-04-21 12:54:03.37

Prostate cancer is a significant public health concern due to its high incidence and mortality, and that no consensus exists regarding the best form of treatment for any stage of the disease. Prostate cancer mortality can be reduced by the early prostate cancer detection. The earlier the detection the more effective the treatment would be. Prostate cancer screening or early detection has been accomplished applying the digital rectal examination (DRE) , the measurement of serum the prostate specific antigen (PSA), transrectal ultrasonography and combinations of these tests. MS based proteomics and particularly MS-SEDLI-TOF technology have assisted in discovering prostate cancer biomarkers. On the other hand, a major cause of mortality for women is the ovarian cancer. Malignant ovarian tumors are heterogeneous in their biological and clinical behaviour and a greater understanding of how they develop and progress is a prerequisite to successful early detection, screening programs, and treatment modalities. Accordingly, the aims of the present thesis are: (i) To develop a reliable pattern recognition system for the discrimination of healthy from patients with prostate cancer as well as controls from patients with ovarian cancer ,(ii) To develop efficient algorithms in order to handle the large number of features that are extracted from proteomic spectra, (iii) To develop a methodology to facilitate the investigation of the low intensity peaks which are the peaks in which biologists are mostly interested in, (iv) To propose potential biomarkers for discriminating healthy from prostate cancer cases and healthy from ovarian cancer cases . To cope with the above issues and in search of efficient methods for handling proteomic spectra a novel multi classifier pattern recognition methodology has been designed, developed and implemented, for the analysis of prostate and ovarian proteomic data. Furthermore, a novel method for splitting and grouping peaks according to their intensities has been developed to be consistent with biologist interest in investigating low intensity peaks.
Τα δεδομένα πρωτεομικής τα οποία εξάγονται από φασματογράφο μάζας έχουν ως αποτέλεσμα την δημιουργία ενός μονοδιάστατου σήματος το οποίο στον οριζόντιο άξονα έχει τιμές μάζας/φορτίο και στον κατακόρυφο άξονα έχει τις αντίστοιχες τιμές έντασης. Οι τιμές στον οριζόντιο άξονα (μάζα/φορτίο) οι οποίες αντιπροσωπεύουν πεπτίδια ή πρωτεΐνες έχουν ένα εύρος από 0 έως δεκάδες χιλιάδες. Επομένως τα πρωτεομικά φάσματα θεωρούνται ιδιαίτερα πολύπλοκα. Η διαχείριση της πληροφορίας των πρωτεομικών φασμάτων καθώς και η εξαγωγή διαγνωστικών συμπερασμάτων είναι ένα πεδίο ανοιχτό προς έρευνα. Ο καρκίνος του προστάτη αποτελεί την δεύτερη πιο σημαντική αιτία θανάτου στην Ηνωμένες Πολιτείες Αμερικής και τον Καναδά. Η θνησιμότητα που οφείλεται στον καρκίνο του προστάτη μπορεί να μειωθεί από την έγκαιρη πρόγνωσή του. Όσο ποιο έγκαιρη είναι η πρόγνωσή του τόσο ποιο αποτελεσματική είναι η θεραπεία του. Ο προστάτης είναι ένας αδένας που βρίσκεται στο εσωτερικό του σώματος, κάτω από την ουροδόχο κύστη του άνδρα και περιβάλλει την ουρήθρα. Τον αδένα αυτό τον έχει ένας άνδρας ήδη από την στιγμή που γεννιέται. Με την λειτουργία του συμβάλει, στον έλεγχο της ούρησης, το οποίο το πετυχαίνει λόγω της ανατομικής του θέσης, στον εμπλουτισμό του σπέρματος με χρήσιμα και απαραίτητα συστατικά και στη λειτουργία της εκσπερμάτισης. Ο καρκίνος του προστάτη είναι η ανάπτυξη καρκινικών κυττάρων στον αδένα αυτόν. Τα καρκινικά κύτταρα πολλαπλασιάζονται πολύ πιο γρήγορα από τα φυσιολογικά κύτταρα, και έτσι, η ολοένα αυξανόμενη συγκέντρωσή τους δημιουργεί όγκους. Επιπλέον, τα καρκινικά κύτταρα έχουν την δυνατότητα να μεταφέρονται σε άλλα σημεία του σώματος (κάνουν μετάσταση) και να καταστρέφουν τα υγιή κύτταρα. Η πρωτεομική με την εφαρμογή της φασματογραφίας μάζας έχει βοηθήσει σημαντικά στην πρόγνωση του καρκίνου του προστάτη και στην ανακάλυψη γνωστών βιοδεικτών του καρκίνου του προστάτη όπως είναι το ειδικό αντιγόνο του προστάτη (PSA), η προστατική όξινη φωσφατάση (PAP), το ειδικό πεπτίδιο του προστάτη (PSP) και το ειδικό αντιγόνο μεμβράνης του προστάτη (PSMA). Ο καρκίνος των ωοθηκών είναι μια συνήθεις γυναικολογική κακοήθεια με ποικίλα ιστολογικά χαρακτηριστικά. Είναι η κύρια αιτία θανάτου από καρκίνου ανάμεσα σε όλες τις γυναικολογικές κακοήθειες, καθώς και ο πέμπτος πιο συχνός τύπος καρκίνου μεταξύ γυναικών του δυτικού κόσμου. Η πλειοψηφία των κακοηθών όγκων των ωοθηκών εμφανίζεται σε γυναίκες ηλικίας άνω των 65 χρόνων, ενώ οι καλοήθεις όγκοι είναι συνηθέστεροι σε νεότερης ηλικίας γυναίκες μεταξύ 25 και 45 χρόνων. Λόγω της πολυπαραγοντικής φύσης του καρκίνου, είναι πολύ πιθανό, μια ομάδα βιοδεικτών να είναι πιο ενδεικτικοί για την πρόβλεψη της βιολογικής συμπεριφοράς διαφόρων όγκων, από την χρήση ενός μόνο βιοδείκτη. Το CA-125 είναι ένας δείκτης ο οποίος χρησιμοποιείται για την διάγνωσης και συγκεκριμένα στην πρόγνωση του καρκίνου των ωοθηκών. Η επιβεβαίωση του και αξιοπιστία του βιοδείκτη CA-125 οδήγησε στην ευρέως χρήση του, ως βιοδείκτης για τον καρκίνο των ωοθηκών, καθώς και στην κλινική διάγνωση της ανταπόκρισης του ασθενούς κατά την θεραπεία του καρκίνου. Πρόσφατες προσπάθειες επικεντρώθηκαν στην βελτίωση της διαγνωστικής ακρίβειας του CA-125, είτε χρησιμοποιώντας μόνο τον συγκεκριμένο βιοδείκτη (CA-125), είτε χρησιμοποιώντας τον με νέους βιοδείκτες που έχουν συσχετιστεί με τον καρκίνο των ωοθηκών. Ο βιοδείκτης CA-125 βρίσκεται στο μητρικό γάλα και στο αμνιακό υγρό στις υγιείς γυναίκες. Παρόλα αυτά υπάρχει επίσης σε γυναίκες με γυναικολογικά προβλήματα όπως μητρικό λειομύωμα και ενδομητρίωση μειώνοντας έτσι την ειδικότητα του βιοδείκτη. Επιπροσθέτως άλλοι βιοδείκτες οι οποίοι έχουν βρεθεί είναι οι prostasin, OVX1, CA-15.3, CA-72.4, και inhibin. Έτσι οι στόχοι της παρούσας διατριβής είναι: (i) ο κατάλληλος συνδυασμός των βημάτων, προεπεξεργασίας, εξαγωγής χαρακτηριστικών, επιλογής χαρακτηριστικών και επιλογής ταξινομητή ώστε η διάγνωση να είναι ακριβέστερη από τις υπάρχουσες μεθόδους. (ii) να προταθούν βιοδείκτες (biomarkers) και συγκεκριμένα τιμές φάσματος (μάζας/φορτίου) οι οποίες ενδεχομένως να σχετίζονται με τις ασθένειες προς μελέτη (Καρκίνου του προστάτη και των ωοθηκών). Για την εκπλήρωση των ανωτέρω στόχων σχεδιάστηκαν και αναπτύχθηκαν μεθοδολογίες με στόχο την ακριβή διάκριση των υγειών από ασθενείς με καρκίνο του προστάτη και ωοθηκών. Προτείνονται τιμές μάζας/φορτίο οι οποίες ενδεχομένως να αποτελέσουν χρήσιμους βιοδείκτες για τον καρκίνο του προστάτη και για τον καρκίνο των ωοθηκών. Επίσης υλοποιήθηκε μεθοδολογία για να μπορέσουμε να ερευνήσουμε την διαγνωστική αξία των κορυφών, των πρωτεομικών φασμάτων, με διάφορες τιμές έντασης και κυρίως των χαμηλών, οι οποίες θεωρούνται ως πλούσιες σε πληροφορία από τους βιολόγους.

Dissertação de Erasmus Mundus para obtenção do grau de mestre em Técnicas Laboratoriais Forenses
The emergence and abuse of new synthetic cannabinoids has been on the rise because legal regulations against particular derivatives of cannabinoids tend to cause the introduction of new variants as the law is made for specific molecules and not for a group of molecules. They come with no clinical indications of use on their labels, and vaguely described intoxicating effects hence they were not banned. Consequently, they are also referred to as ‘Smart Drugs’ or more formally ‘New Psychoactive Substances’ (NPSS). Many classified synthetic cannabinoid agonists remain available to users in many countries mainly through ‘smart’ and online shops. The challenges posed to the regulation of these products are due to their ever-changing composition, adulterants and variable vehicles of distribution. Synthetic cannabinoids are famous for their recreational effects similar to that of marijuana, which has neuropsychiatric effects due to the action of its primary active ingredient, Δ9-tetrahydrocannabinol (Δ9-THC), binding to endogenous cannabinoid receptors. This study was conducted first to find the best microorganism model for the development of a new screening method for the analysis of synthetic cannabinoids by using the proteome expression patterns obtained from proteins of Saccharomyces cerevisiae and E. coli. The research also sought to find an efficient protein extraction and concentration method for expressed microorganism proteins for two-dimension gel electrophoresis. Saccharomyces cerevisiae and Escherichia coli were studied in this work. S. cerevisiae rather than E. coli proved to be a better microorganism model for to be exploited for findings in this research. Diclofenac and JWH-018 standard were used as test drugs. The Amicon® membrane filter concentration method was found to be the most efficient with protein yield greater than 20mg/mL for 500mL cell culture volume. Even though twodimension gels did not show a large number of protein spots, the application of more concentrated protein solution from S. Cerevisiae is paramount to get a better proteomic pattern for use as a sensor.

Οι ραγδαίες εξελίξεις στη Φασματομετρία Μάζας και η εισαγωγή νέων πειραματικών τεχνικών ιονισμού, όπως οι τεχνικές Matrix-Assisted Laser Desorption Ionization (MALDI) και Surface-Enhanced Laser Desorption Ionization (SELDI) έχει καταστήσει δυνατή τη μελέτη των επιπέδων της πρωτεϊνικής έκφρασης σε σύνθετα μείγματα πρωτεϊνών από διάφορα βιολογικά δείγματα, όπως serum, πλάσμα και ούρα. Τα δεδομένα που προκύπτουν από αυτές τις τεχνολογίες μπορούν να χρησιμοποιηθούν για την αναγνώριση πρωτεϊνικών προτύπων, τα οποία θα μπορούν επιτυχώς να διαχωρίζουν καταστάσεις (π.χ. υγιής – ασθενής) καθώς και για την ανακάλυψη νέων πιθανών βιοδεικτών (biomarkers). Αυτά τα πρότυπα έχουν υψηλή διαγνωστική σημασία, καθώς μπορούν να χρησιμοποιηθούν για έγκαιρη διάγνωση, πρόγνωση, παρακολούθηση της εξέλιξης μιας ασθένειας ή της απόδοσης μιας συγκεκριμένης θεραπείας. Αυτή η στρατηγική έχει ήδη χρησιμοποιηθεί σε διάφορους τύπους καρκίνου, όπως ωοθηκών, μαστού και προστάτη, δίνοντας πολύ ενδιαφέροντα αποτελέσματα. Παρόλα αυτά, η σύνθετη φύση των πρωτεϊνικών δεδομένων κάνει την ανάλυση τους αρκετά απαιτητική, καθώς τα αρχικά, ακατέργαστα δεδομένα είναι πολύ δύσκολο να επεξεργαστούν. Πιο συγκεκριμένα, τα δεδομένα που ανακτώνται μετά από ένα πείραμα Φασματομετρίας Μάζας περιέχουν κάποιες εκατοντάδες δείγματα (δηλαδή φάσματα μάζας) και σε κάθε δείγμα αντιστοιχούν δεκάδες χιλιάδες χαρακτηριστικά. Επιπρόσθετα με το πρόβλημα των μεγάλων διαστάσεων και ταυτόχρονα λίγων δειγμάτων, κάθε φάσμα περιέχει σημαντικό ποσοστό θορύβου και τεχνουργημάτων, κυρίως εξαιτίας της υψηλής ευαισθησίας του μηχανήματος, της επιμόλυνση του δείγματος αλλά και διαφόρων ηλεκτρικών πηγών θορύβου. Ένα άλλο κοινό πρόβλημα είναι η λάθος βαθμονόμηση (calibration) των φασμάτων, που καθιστά τα δεδομένα αδύνατον να συγκριθούν. Για όλους αυτούς τους λόγους, είναι παραπάνω από προφανές ότι για να καταφέρουμε να εξάγουμε γνώση σχετικά με τις πραγματικές υποκείμενες βιολογικές διαφοροποιήσεις του πρωτεώματος πρέπει να εκτελέσουμε διάφορα βήματα προεπεξεργασίας. Ο βασικός στόχος της προεπεξεργασίας είναι η δημιουργία ενός πίνακα που θα περιέχει τα σημαντικά χαρακτηριστικά (δηλαδή τις κορυφές) και τις αντίστοιχες τιμές έντασης, ο οποίος θα αναλυθεί περαιτέρω χρησιμοποιώντας μια ποικιλία υπολογιστικών μεθόδων. Για να επιτύχουμε κάτι τέτοιο, πρέπει αρχικά να αφαιρέσουμε το θόρυβο, τα τεχνουργήματα και τη συστηματική απόκλιση χωρίς απώλεια πληροφορίας και έπειτα να ανιχνεύσουμε και να ποσοτικοποιήσουμε ένα σύνολο κορυφών. Η προεπεξεργασία περιλαμβάνει ένα σύνολο βημάτων τα οποία αλληλεπιδρούν μεταξύ τους και έχει δειχθεί ότι αν δεν εφαρμοστεί προσεκτικά θα είναι πολύ δύσκολο να εξαχθούν συμπεράσματα για την υποκείμενη ασθένεια. Η επιλογή του καλύτερου συνδυασμού μεθόδων είναι ιδιαίτερα δύσκολη, καθώς για κάθε βήμα έχουν προταθεί αρκετές εναλλακτικές μέθοδοι. Επιπλέον, είναι δύσκολο να αποτιμηθεί η απόδοση κάθε μεθόδου και να προταθεί μια μοναδική στρατηγική, καθώς για κάθε σύνολο δεδομένων προκύπτει και διαφορετικός συνδυασμός ως πιο κατάλληλος. Στα πλαίσια της παρούσας διπλωματικής εργασίας δημιουργήθηκε ένα ολοκληρωμένο σύστημα ανάλυσης πρωτεϊνικών δεδομένων, το οποίο ενσωματώνει μια καινούρια μέθοδο προεπεξεργασίας πρωτεϊνικών δεδομένων. Η μέθοδος αυτή αντιμετωπίζει τα προβληματικά χαρακτηριστικά αυτού του τύπου δεδομένων και εκμεταλλεύεται τα πλεονεκτήματα διάφορων γνωστών μεθόδων. Πιο συγκεκριμένα, η στρατηγική που προτείνουμε εστιάζει σε τρία σημαντικά προβλήματα: τη διόρθωση των λαθών της βαθμονόμησης, την ανίχνευση των κορυφών με ευαίσθητο αλλά και σταθερό τρόπο και την ακριβή ποσοτικοποίηση κάθε κορυφής. Η ανίχνευση κορυφής πραγματοποιήθηκε μέσω μιας μεθόδου βασισμένης στη λογική της χρήσης του μέσου φάσματος, όπου πρώτα ανιχνεύουμε τις κορυφές ανά κατηγορία, έπειτα εφαρμόζουμε διάφορα κριτήρια αποκοπής για να βεβαιώσουμε την αναπαραγωγιμότητα τους και μετά τις συνενώνουμε σε ένα σύνολο κορυφών, κοινό για όλες τις κατηγορίες. Αντί να χρησιμοποιούμε συγκεκριμένες θέσεις για κάθε κορυφή, προτείνουμε τη χρήση διαστημάτων κορυφής, έτσι ώστε να βεβαιώσουμε ότι οι μικρές αποκλίσεις δε δημιουργούν σφάλματα στην ποσοτικοποίηση. Για να αποτιμήσουμε τα αποτελέσματα της μεθόδου μας, στα δεδομένα που προέκυψαν μετά την προεπεξεργασία εφαρμόστηκε ένα τελικό βήμα επιλογής χαρακτηριστικών και ταξινόμησης, με χρήση του αλγορίθμου ταξινόμησης Support Vector Machines. Η προτεινόμενη μέθοδος μας εφαρμόστηκε σε ένα σύνολο MALDI MS δεδομένων, το οποίο μας παρείχε η Ερευνητική Μονάδα Πρωτεωμικής του Ιδρύματος Ιατροβιολογικών Εφαρμογών Ακαδημίας Αθηνών (ΙΙΒΕΑΑ). Το συγκεκριμένο σύνολο δεδομένων περιέχει 200 περίπου δείγματα από ασθενείς με καρκίνο ουροδόχου κύστεως (υψηλού ή χαμηλού βαθμού) ή καλοήθη ασθένεια. Μετά την εφαρμογή της προτεινόμενης μεθόδου, καταλήξαμε σε έναν πίνακα 456 κορυφών και αντίστοιχων εντάσεων. Η εφαρμογή του βήματος της ταξινόμησης πέτυχε πολύ υψηλά ποσοστά ακρίβειας, ευαισθησίας και ειδικότητας. Επιπλέον, αναγνωρίστηκαν 31 στατιστικά σημαντικά χαρακτηριστικά, μερικά από τα οποία δεν ανιχνεύονται από τις υπάρχουσες μεθόδους.
The rapid developments in mass spectrometry (MS) and the introduction of new experimental ionization methods, like matrix-assisted laser desorption ionization (MALDI) and surface-enhanced laser desorption ionization (SELDI), has made it possible to study protein expression levels in complex mixtures of proteins from various biological samples, like serum plasma and urine. The data generated from these technologies can be used to identify proteomic patterns that can successfully separate states (e.g. normal versus disease) and possibly discover novel disease biomarkers. Those patterns have high diagnostic significance, as they can be used for early diagnosis, prognosis, monitoring disease progression or therapeutic response. This strategy has already been used in various types of cancer, like ovarian, breast and prostate cancer, giving interesting results. However, the complex nature of proteomics data makes their analysis a challenging task, as the initial raw data are very difficult to handle. More specifically, the data retrieved after an MS experiment contain hundreds of samples (i.e. mass spectra), and in each sample correspond tens of thousands of features. In addition to this high dimensionality – small sample size problem, each spectrum contains a great amount of noise and artifacts, mostly due to the high sensitivity of the instrument, sample contamination and electrical noise. Another common problem is the miscalibration of the spectra that makes the data impossible to compare. For all those reasons, it is more than obvious that in order to extract knowledge about the true underlying biological differences in the proteome, various preprocessing steps need to be applied. The main goal of preprocessing is to come up with a matrix of important features (i.e. peaks) and their corresponding intensity values, which can be further analyzed using a variety of computational methods. To achieve this, one must first remove noise, artifacts and systematic bias without loss of information and then detect and quantify a set of peaks. Preprocessing involves various steps that are highly interrelated and it has been shown that if those steps are not applied carefully, it will be difficult to extract meaningful conclusions about the underlying disease. For each step, a number of methods have been proposed making the decision about the best combination of methods a very challenging task. Furthermore, it is difficult to evaluate the performance of each method and come up with a standard strategy, as for each dataset a different set of methods appear to be more effective. This thesis presents a new pipeline method for the analysis of proteomics data, which incorporates a new preprocessing method. This proposed method deals with the problematic characteristics of this type of data and exploits the advantages of various existing methods. More specifically, our proposed strategy focuses on three main problems: correcting the miscalibration of the mass spectra, detecting the peaks in a sensitive yet robust manner and extracting the true intensity values that correspond in each peak. For the peak finding step, we used a method based on the mean spectrum approach, where we first find the peaks per category, then apply certain criteria to ensure their reproducibility and then combine them in a single peak list. Instead of working with peak locations, we propose the use of peak intervals, to ensure that the small shifts present in the data do not interfere with the final results. In order to evaluate the results of our method, a final feature extraction and classification step was applied in the preprocessed data, using the Support Vector Machines classification algorithm. Our proposed pipeline method was applied in a MALDI MS dataset, obtained by the Proteomics Research Unit of the Biomedical Research Foundation. This particular dataset contained approximately 200 samples, concerning patients with bladder cancer (high or low grade) and benign bladder disease. After the application of the proposed preprocessing method we ended up with a matrix of 456 peak bins and corresponding intensities. The application of the classification algorithm achieved extremely high performance in terms of accuracy, sensitivity and specificity. Furthermore, 31 statistically important peaks were identified, some of which are not detected by existing methods.

碩士
實踐大學
食品營養與保健生技研究所
95
Monascus species have the unique ability to economically produce many secondary metabolites. However, most metabolic regulation processes in the production of secondary metabolites in Monascus remain unclear. Nitrogen is a major component of nearly all of the complex macromolecules central to the structure and function of all living organisms. Here, the first objective of this study was to use proteomic analysis to investigate the influence of nitrogen-limited substrate to the medium on the biochemical metabolisms concerning culture growth and pigment production in cultivated Monascus pilosus BCRC 31527. Furthermore, we also found that translational inhibitor cycloheximide (CHX) induced different expression patterns between the pigment production and growth mass in M. pilosus BCRC 31527. We used proteomic approach of two-dimensional gel electrophoresis, matrix-assisted laser desorption ionization time-of-flight/time-of-flight liquid chromatography mass spectrometry (MALDI-TOF/TOF LC-MS), tandem mass spectrometry (MS/MS) to identify the intracellular and mitochondrial proteins of M. pilosus BCRC 31527 among the treatments and the controls. The results revealed that nitrogen limitation to the glucose nitrate medium induced an up-regulation of some transcriptional proteins, such as DNA-directed RNA polymerase and histone deacetylase, and several protein synthesis enzymes in M. pilosus BCRC 31527 relative to the control. The cycloheximide-induced down-regulation proteins were also involved in transcription regulation, peptide translation synthesis, such as valyl-tRNA synthetase and valyl-tRNA synthetase, and other metabolisms, such as 1-aminocyclopropane-1-carboxylate deaminase for the methylation of secondary metabolites. In contrast, several energy-related proteins were up-regulated in the control of cycloheximide treatment. KEYWORDS: Monascus; food pigments; nitrogen-limited; cycloheximide; proteome