Cyclotides are plant proteins with a unique topology, defined as the cyclic cystine knot motif. The motif endows cyclotides with exceptional chemical and biological stability. They also exhibit a wide range of biological activities including insecticidal, cytotoxic, anti-HIV and antimicrobial effects. Hence, cyclotides have become potential candidates in the development of peptide-based drugs; either as scaffolds to stabilize susceptible peptide sequences or as drugs by their own right. In this thesis, important parameters that could be inputs toward this development have been tuned. An extraction protocol that can be extended to industrial scale production of the cyclotides from natural sources was developed; accordingly, a single maceration with hydroalcoholic solutions of medium polarity represented an optimum extraction method. Moreover, it was shown that investigating the cyclotide content of cyclotide-bearing plants from diverse environments is a promising approach for extending the knowledge of both structural and biological diversity of these proteins. Five novel cyclotides with new sequence diversity were isolated and characterized from a violet that grows on Ethiopian highlands at an altitude of 3400 m. One of the areas where the cyclotide framework has attracted interest is the development of stable antimicrobial peptides. A stability study was carried out to determine the stability of the cyclotide framework in a cocktail of bacterial proteases and serum where the native forms of tested cyclotides exhibited high stability profile. Understanding the modes of cyclotide-cell interaction is certainly an important factor for the potential development of cyclotide-based drugs. Cellular studies were carried out using the comet assay and microautoradiography. A bell-shaped dose response curve was obtained for the DNA damaging effect of the cyclotides in the comet assay, which was the first toxicological assay of its kind on this class of proteins. The microautoradiography study revealed that the cyclotides penetrate into the cells even at cytotoxic concentrations. From previous reports, it was known that the cyclotides interact with membranes; the cellular studies in this thesis added to this knowledge by clearly demonstrating that these proteins have multiple modes of action.

Proteomics serves an important role at the systems-level in understanding of biological functioning. Mass spectrometry proteomics has become the tool of choice for identifying and quantifying the proteome of an organism. In the most widely used bottom-up approach to MS-based high-throughput quantitative proteomics, complex mixtures of proteins are first subjected to enzymatic cleavage, the resulting peptide products are separated based on chemical or physical properties and then analyzed using a mass spectrometer. The three fundamental challenges in the analysis of bottom-up MS-based proteomics are as follows: (i) Identifying the proteins that are present in a sample, (ii) Aligning different samples on elution (retention) time, mass, peak area (intensity) and etc, (iii) Quantifying the abundance levels of the identified proteins after alignment. Each of these challenges requires knowledge of the biological and technological context that give rise to the observed data, as well as the application of sound statistical principles for estimation and inference. In this dissertation, we present a set of statistical methods in bottom-up proteomics towards protein identification, alignment and quantification. We describe a fully Bayesian hierarchical modeling approach to peptide and protein identification on the basis of MS/MS fragmentation patterns in a unified framework. Our major contribution is to allow for dependence among the list of top candidate PSMs, which we accomplish with a Bayesian multiple component mixture model incorporating decoy search results and joint estimation of the accuracy of a list of peptide identifications for each MS/MS fragmentation spectrum. We also propose an objective criteria for the evaluation of the False Discovery Rate (FDR) associated with a list of identifications at both peptide level, which results in more accurate FDR estimates than existing methods like PeptideProphet. Several alignment algorithms have been developed using different warping functions. However, all the existing alignment approaches suffer from a useful metric for scoring an alignment between two data sets and hence lack a quantitative score for how good an alignment is. Our alignment approach uses "Anchor points" found to align all the individual scan in the target sample and provides a framework to quantify the alignment, that is, assigning a p-value to a set of aligned LC-MS runs to assess the correctness of alignment. After alignment using our algorithm, the p-values from Wilcoxon signed-rank test on elution (retention) time, M/Z, peak area successfully turn into non-significant values. Quantitative mass spectrometry-based proteomics involves statistical inference on protein abundance, based on the intensities of each protein's associated spectral peaks. However, typical mass spectrometry-based proteomics data sets have substantial proportions of missing observations, due at least in part to censoring of low intensities. This complicates intensity-based differential expression analysis. We outline a statistical method for protein differential expression, based on a simple Binomial likelihood. By modeling peak intensities as binary, in terms of "presence / absence", we enable the selection of proteins not typically amendable to quantitative analysis; e.g., "one-state" proteins that are present in one condition but absent in another. In addition, we present an analysis protocol that combines quantitative and presence / absence analysis of a given data set in a principled way, resulting in a single list of selected proteins with a single associated FDR.

Ovarian cancer is one of the most common female cancer diseases in the world today and in Sweden more than 800 new cases are diagnosed every year. The standard treatment consists of chemotherapy with paclitaxel in combination with carboplatin after initial cytoreductive surgery. The response to treatment and the severity of adverse drug reactions after chemotherapy varies greatly among individuals, and one of the most important factors responsible for these differences is now recognized to be the genetic variability. One of the major obstacles to successful treatment is drug resistance. Several potential mechanisms have been suggested for the resistance to paclitaxel, such as mutations in the target protein β-tubulin, single nucleotide polymorphisms (SNPs) in the gene ABCB1, which encodes the transport protein P-glycoprotein. P-glycoprotein can mediate efflux of various drugs from cancer cells as well as from the circulation into the intestinal lumen, and overexpression and/or high activity leads to drug resistance and/or increased elimination. Another reason might be the high interindividual variability of paclitaxel plasma concentrations, which has been suggested to be influenced by variability in metabolic enzymes, such as CYP2C8 and CYP3A4, and transport proteins e.g. P-glycoprotein. In the studies constituting this thesis we have investigated the possibilities of predicting the pharmacokinetics of paclitaxel as well as the tumor response and adverse drug reactions after chemotherapy in the preparation of personalized chemotherapy. We studied the correlation between the response and the presence of mutations in the dominant β-tubulin gene and SNPs in ABCB1. DNA from 40 ovarian tumors was screened for sequence variations in the β-tubulin gene without finding any, showing that β-tubulin mutations are rare and unlikely to be a clinically relevant resistance mechanism for paclitaxel. The SNPs G2677T/A and C3435T in the ABCB1 gene were determined in 53 ovarian cancer tumors from patients with poor (progressive disease or relapse within one year) or good (disease-free survival of more than one year) response to paclitaxel-carboplatin chemotherapy. Patients homozygously mutated for G2677T/A had a higher probability of responding to chemotherapy. There was also a dose-dependent influence of the number of mutated alleles on the response to paclitaxel treatment. No correlation was found for the C3435T variant. By using a newly developed quantitative LC/MS method for the simultaneous determination of paclitaxel and its hydroxymetabolites in human plasma we assessed the individual elimination of paclitaxel in 33 ovarian cancer patients. The patients were genotyped for SNPs in the ABCB1, CYP2C8 and CYP3A4 genes and their in vivo CYP3A4 enzyme activity, tumor response and toxicity, especially the neurotoxicity, were determined. Patients heterozygous for G/A in position 2677 in ABCB1 had a significantly higher clearance of paclitaxel than patients with the wild type or homozygously mutated, but not compared to patients carrying the G/T alleles. A lower clearance of paclitaxel was also found for patients heterozygous for CYP2C8*3 when stratified according to the ABCB1 G2677T/A genotype. The CYP3A4 enzyme activity in vivo affected the relative influence of CYP2C8 and CYP3A4 on the metabolism, but not the total clearance of paclitaxel. The exposure to paclitaxel was correlated to the neurotoxicity, but not to the treatment response. In conclusion, our findings suggest that the SNP G2677T/A in the ABCB1 gene, but not β-tubulin mutations, might be a predictor for paclitaxel response and that the interindividual variability in paclitaxel pharmacokinetics might be predicted by ABCB1 and CYP2C8 genotypes and provide useful information for individualized chemotherapy. / Ovarialcancer (äggstockscancer) är en av de vanligaste cancerformerna hos kvinnor i Sverige idag. Behandlingen består vanligen av tumörreducerande kirurgi följd av kemoterapi med paklitaxel och karboplatin. Målsättningen med detta avhandlingsarbete har varit att förbättra cytostatikabehandlingen (cellgiftsbehandlingen) med framförallt paklitaxel vid ovarialcancer genom att lägga grunden för individualisering av doser och förutsäga tumörsvaret vid behandlingen. Ett problem med dagens cancerbehandling är att många cancerceller så småningom blir resistenta mot olika cytostatika. För att angripa den mest resistenta cellen innan den induceras att öka uttrycket av, eller utveckla, fler resistensmekanismer vore det en fördel om vi före behandlingen kunde prediktera vilken dos av cytostatika som är bäst lämpad för individen samt om tumören kommer att reagera på behandlingen eller ej. En av de viktigaste faktorerna för skillnader i behandlingseffekt tros vara genetiska variationer mellan olika individer. I våra studier har vi använt genetiska metoder för att studera om vi kan prediktera tumörsvaret vid behandlingen genom att bestämma mutationer i genen för paklitaxels målprotein, β-tubulin, samt bestämma genetiska variationer i ABCB1-genen, kodande för transportproteinet P-glykoprotein. Tanken är att ett förändrat målprotein eller en förändrad förmåga hos cancercellerna eller kroppen att transportera ut paklitaxel skulle leda till en skillnad i påverkan på tumören. DNA från 40 ovarialtumörer analyserades utan att en enda sekvensvariation hittades i genen för β-tubulin, vilket tyder på att genetiska förändringar i genen för β-tubulin sannolikt inte är en klinisk relevant resistensmekanism. De normalt förekommande genetiska variationerna G2677T/A och C3435T i ABCB1-genen bestämdes i DNA från 53 ovarialtumörer där behandlingen endera givit en bra (tumörfri minst ett år) eller dålig (progression av tumören eller tumörfri mindre än ett år) anti-tumöreffekt. Patienter som var dubbelmuterade i position 2677 dvs hade endera T/T eller T/A (A/A hittades inte i materialet) i denna position hade en högre sannolikhet att få ett bra anti-tumörsvar vid behandlingen. Även antalet muterade baser påverkade utfallet, ju fler muterade baser i position 2677, desto högre sannolikhet att få ett bra svar på behandlingen. Andelen T eller A var också högre i den grupp av patienter som fått en lyckad behandling. För att kunna prediktera patientens individuella förmåga att bryta ner paklitaxel studerade vi inverkan av sekvensvariationer i generna för de nedbrytande enzymerna, CYP2C8 och CYP3A4, och transportproteinet P-glykoprotein (genen ABCB1) på eliminationen av läkemedlet i kroppen. Vi utvecklade en metod för att mäta paklitaxelkoncentrationerna i blodet och använde den för att studera hur snabbt 33 ovarialcancer patienter eliminerade cytostatikat från blodbanan. Hos dessa patienter bestämde vi förekomsten av kända genetiska variationer i generna ABCB1, CYP2C8 och CYP3A4 samt deras CYP3A4 enzymaktivitet i kroppen. Biverkningarna och tumörsvaret vid behandlingen utvärderades också. Eliminationen av paklitaxel hos dessa patienter var beroende av vilken bas som fanns i position 2677 i ABCB1-genen och förekomsten av den genetiska varianten CYP2C8*3. Enzymaktiviteten hos CYP3A4 kunde inte påvisas påverka eliminationen av paklitaxel utan snarare vilket enzym, CYP2C8 eller CYP3A4, som var relativt dominant i respektive patient. Exponeringen av paklitaxel korrelerade till den neurologiska påverkan som patienten orsakades av cytostatikat, men kunde inte korreleras till tumörsvaret vid slutet av cytostatikabehandlingen. Sammanfattningsvis ger patientens genetiska variationer i ABCB1, men inte β-tubulin, information om behandlingsutfallet. Genetiska variationer i CYP2C8 och ABCB1 påverkar patientens förmåga att eliminera paklitaxel och kan förhoppningsvis användas för att individualisera doserna. Vår förhoppning är att resultaten i denna avhandling skall kunna användas för att individualisera och ytterligare förbättra cytostatikabehandlingen vid ovarialcancer.

One trend in the ‘omics’ sciences is the generation of increasing amounts of data, describing complex biological samples. To cope with this and facilitate progress towards reliable diagnostic tools, it is crucial to develop methods for extracting representative and predictive information. In global metabolite analysis (metabolomics and metabonomics) NMR, GC/MS and LC/MS are the main platforms for data generation. Multivariate projection methods (e.g. PCA, PLS and O-PLS) have been recognized as efficient tools for data analysis within subjects such as biology and chemistry due to their ability to provide interpretable models based on many, correlated variables. In global metabolite analysis, these methods have been successfully applied in areas such as toxicology, disease diagnosis and plant functional genomics. This thesis describes the development of processing methods for the unbiased extraction of representative and predictive information from metabolic GC/MS and LC/MS data characterizing biofluids, e.g. plant extracts, urine and blood plasma. In order to allow the multivariate projections to detect and highlight differences between samples, one requirement of the processing methods is that they must extract a common set of descriptors from all samples and still retain the metabolically relevant information in the data. In Papers I and II this was done by applying a hierarchical multivariate compression approach to both GC/MS and LC/MS data. In the study described in Paper III a hierarchical multivariate curve resolution strategy (H-MCR) was developed for simultaneously resolving multiple GC/MS samples into pure profiles. In Paper IV the H-MCR method was applied to a drug toxicity study in rats, where the method’s potential for biomarker detection and identification was exemplified. Finally, the H-MCR method was extended, as described in Paper V, allowing independent samples to be processed and predicted using a model based on an existing set of representative samples. The fact that these processing methods proved to be valid for predicting the properties of new independent samples indicates that it is now possible for global metabolite analysis to be extended beyond isolated studies. In addition, the results facilitate high through-put analysis, because predicting the nature of samples is rapid compared to the actual processing. In summary this research highlights the possibilities for using global metabolite analysis in diagnosis.

<p>Proteomics is the analysis of the total complement of proteins expressed by a cell or organism grown under a specified condition. The obtained protein profile would provide a better understanding of phenotypic characteristics of a cell grown under pre-determined conditions. Mass spectrometric-based protein analysis is currently the standard method in proteomic studies; however, there are many limitations associated with its application. The major objectives of this study included the development of a strategy to analyze the confidence of identified proteins and the development of an algorithm to interpret the experimentally obtained mass spectral data. </p> <p>A two-step strategy was developed to analyze the confidence of identified proteins. In the first step, the proteins identified by a single protein identification tool were classified into two groups: high confidence proteins that were identified by unique peptides, and low confidence proteins that were identified by non-unique peptides. In the second step, the proteins identified by different tools (e.g., SEQUEST and Mascot in our work) were cross-compared. After integrating the two-step analysis, the identified proteins were classified into four levels of confidence. The proteins that were identified by the presence of unique peptides and that were commonly identified by different tools were grouped into the highest confidence level - Level 4. Even though the number of proteins in Level 4 was reduced significantly, the conclusions drawn from the proteins were more reliable.</p> <p>According to the operation of tandem mass spectrometry and the characteristics of the peptides generated by site-specific protease digestion, a two-pass approach for identifying the species-specific proteins was developed. The approach can find all possible peptides corresponding to a precursor ion and gives detailed matching information of each peptide candidate to the experimental product ion series. According to the total number of matched product ions, the total number of matched b- and y- ions, and the contiguity characteristic of identified product ions, the peptide candidates were ranked decreasingly from the most probable to the least. Combined with the concept of unique peptide, the obtained most probable peptide can then be used to predict proteins existing in the original sample.</p> <p>The developed two-pass approach and two-step strategy were then used to study the protein profiling of <i>Saccharomyces cerevisiae</i> cultivated in various gravity conditions (10 and 300 g glucose/l) in order to investigate the changes in central metabolic pathways of <i>S. cerevisiae</i>. Our fermentation data indicated that the higher glucose contents would result in lower cell growth and higher ethanol production (e.g., high ethanol concentration in fermentation broth). However, the relative ethanol yield as related to the glucose consumption was lower under higher glucose concentrations. The protein profile showed that a higher flux of nutrient was channelled into the pentose phosphate pathway when <i>S. cerevisiae</i> was grown under a high glucose concentration. The reason for this phenomenon might be that the cell needs more reducing power (e.g., NADPH) for the synthesis of macromolecules such as proteins, nucleic acids, and lipids. These materials are essential to the cell in order to modify its structure (e.g., cell wall), to survive osmotic stress and to replicate.</p>

A rapid and accurate quantitative method was developed and validated for the analysis of four urinary organic acids with nitrogen containing functional groups, formiminoglutamic acid (FIGLU), pyroglutamic acid (PYRGLU), 5-hydroxyindoleacetic acid (5-HIAA), and 2-methylhippuric acid (2-METHIP) by liquid chromatography tandem mass spectrometry (LC/MS/MS). The chromatography was developed using a weak anion-exchange amino column that provided mixed-mode retention of the analytes. The elution gradient relied on changes in mobile phase pH over a concave gradient, without the use of counter-ions or concentrated salt buffers. A simple sample preparation was used, only requiring the dilution of urine prior to instrumental analysis. The method was validated based on linearity (r2 ¡Ý 0.995), accuracy (85¨C115%), precision (C.V. < 12%), sample preparation stability (¡Ü 5%, 72h), and established patient ranges. The method was found to be both efficient and accurate for the analysis of urinary zwitterionic organic acids.

<p>Proteomics is the analysis of the total complement of proteins expressed by a cell or organism grown under a specified condition. The obtained protein profile would provide a better understanding of phenotypic characteristics of a cell grown under pre-determined conditions. Mass spectrometric-based protein analysis is currently the standard method in proteomic studies; however, there are many limitations associated with its application. The major objectives of this study included the development of a strategy to analyze the confidence of identified proteins and the development of an algorithm to interpret the experimentally obtained mass spectral data. </p> <p>A two-step strategy was developed to analyze the confidence of identified proteins. In the first step, the proteins identified by a single protein identification tool were classified into two groups: high confidence proteins that were identified by unique peptides, and low confidence proteins that were identified by non-unique peptides. In the second step, the proteins identified by different tools (e.g., SEQUEST and Mascot in our work) were cross-compared. After integrating the two-step analysis, the identified proteins were classified into four levels of confidence. The proteins that were identified by the presence of unique peptides and that were commonly identified by different tools were grouped into the highest confidence level - Level 4. Even though the number of proteins in Level 4 was reduced significantly, the conclusions drawn from the proteins were more reliable.</p> <p>According to the operation of tandem mass spectrometry and the characteristics of the peptides generated by site-specific protease digestion, a two-pass approach for identifying the species-specific proteins was developed. The approach can find all possible peptides corresponding to a precursor ion and gives detailed matching information of each peptide candidate to the experimental product ion series. According to the total number of matched product ions, the total number of matched b- and y- ions, and the contiguity characteristic of identified product ions, the peptide candidates were ranked decreasingly from the most probable to the least. Combined with the concept of unique peptide, the obtained most probable peptide can then be used to predict proteins existing in the original sample.</p> <p>The developed two-pass approach and two-step strategy were then used to study the protein profiling of <i>Saccharomyces cerevisiae</i> cultivated in various gravity conditions (10 and 300 g glucose/l) in order to investigate the changes in central metabolic pathways of <i>S. cerevisiae</i>. Our fermentation data indicated that the higher glucose contents would result in lower cell growth and higher ethanol production (e.g., high ethanol concentration in fermentation broth). However, the relative ethanol yield as related to the glucose consumption was lower under higher glucose concentrations. The protein profile showed that a higher flux of nutrient was channelled into the pentose phosphate pathway when <i>S. cerevisiae</i> was grown under a high glucose concentration. The reason for this phenomenon might be that the cell needs more reducing power (e.g., NADPH) for the synthesis of macromolecules such as proteins, nucleic acids, and lipids. These materials are essential to the cell in order to modify its structure (e.g., cell wall), to survive osmotic stress and to replicate.</p>

novel ozone-assisted aerobic sludge digestion process to stabilize and decrease the amount of excess sludge produced during biological treatment is presented in this study. Excess sludge production is a well known burden for the treatment plants both legally and financially. Moreover, with the arise in the knowledge in recalcitrant compounds it is understood that it can act as a significant secondary pollutant. With the developed pulse ozonation method, waste activated sludge samples from Ankara Tatlar and other Wastewater Treatment Plants (WWTP) were ozonated for different periods in Erlenmeyer flasks once a day on each of four consecutive days. Flasks were continuously aerated between ozone applications on an orbital shaker. The MLVSS, MLSS, COD and OUR parameters were measured routinely during the course of four days of digestion in order to optimize the process. Also pH, CST(capillary suction time) and SVI (sludge volume index) were followed. As a result MLVSS reductions of up to 95% were achieved with an ozone dose of only 0.0056 kg O3/kg-initial MLSS, at the end of the fourth day. In another experimental set, ozone dose was increased on the last day in order to destroy the selected endocrine disrupting compounds, namely diltiazem, carbamazepine, butyl benzyl phthalate and acetaminophen and two natural hormones estrone and progesterone, which accumulated onto the sludge. Over 99% removal of these contaminants were achieved on the fourth day. The analyses were conducted by using LC(ESI) MS/MS after solid phase extraction (SPE). By this process it became possible to save on contact time, as well as achieving a bio-solids digestion far exceeding the standard aerobic process at the expense of a minimum of ozone dose with the additional micropollutants removal. The developed process is deemed superior over side-stream ozonation of activated sludge in that it does not cause any reduction in active biomass amount that should be maintained in the aeration tank.

La protéine kinase TOR (Target Of Rapamycin) a été identifiée chez la levure et les mammifères comme participant à deux complexes protéiques qui servent de carrefour entre la perception des facteurs endogènes et exogènes et la stimulation de la croissance cellulaire. Depuis la découverte de la kinase AtTOR chez Arabidopsis thaliana, des études ont été menées afin de mieux caractériser son rôle chez les plantes et l'influence de son niveau d'expression sur la régulation du métabolisme et du développement.Au cours de ce travail, j'ai contribué à l'étude de cette kinase en étudiant l'influence de l'inactivation de TOR sur la composition du ribosome au niveau protéique et sur le niveau de phosphorylation de ces protéines, ainsi que sur l'organisation du méristème au niveau moléculaire et cytologique Au cours de cette étude, j'ai montré que certaines protéines constitutives du ribosome pourraient être des cibles de l'activité TOR au niveau de leur abondance et/ou de leur état de phosphorylation. Ainsi, l'inactivation de TOR entraine une diminution du niveau de phosphorylation des protéines RPS6 et pourrait influencer l'abondance des protéines acides constitutives du stalk ribosomal, une structure importante dans la régulation de la traduction. Les résultats obtenus suggèrent également que l'activité TOR est nécessaire au maintien du méristème à l'état fonctionnel en régulant les voies importantes contrôlant la division et la différentiation au sein de cette structure.

Per- and polyfluoroalkyl substances are a large group of global environmental contaminants. They can be divided into two sub-groups, 1) perfluoroalkyl acids (PFAAs) and 2) so called precursors, i.e. compounds that can potentially be transformed to form PFAAs. PFAAs are today ubiquitous in wildlife and humans. Food and drinking water are assumed to be the dominant human exposure pathways for PFAAs. The main aim of this doctoral thesis was to develop highly sensitive and fully validated analytical methods for the determination of a range of PFAAs and selected precursors in dietary samples. The methods were based on liquid chromatography coupled to mass spectrometry. Samples were extracted by solvent extraction followed by a cleanup step employing solid phase extraction. The cleanup step could at the same time be used as a fractionation of ionic PFAAs and neutral precursors. Paper I and II describe the development of methods for simultaneous analysis of three groups of PFAAs including perfluoroalkyl phosphonic acids (PFPAs) in drinking water and food. Methyl piperidine was used as ion pairing agent, leading to highly sensitive analysis of PFPAs. A first screening of tap water samples and different food items revealed that human dietary exposure to PFPAs in Europe is currently not of concern. A novel method for simultaneous analysis of perfluoroalkyl carboxylic acids (PFCAs) and polyfluoroalkyl phosphate esters (PAPs) in food and packaging materials is described in paper III. Targeted food samples and their packaging were analyzed. The results showed that PAPs may contribute to human exposure to PFCAs. In paper IV temporal trends (1991-2011) of perfluorooctane sulfonic acid (PFOS) and its precursors in herring were investigated. Rapidly decreasing trends were found for precursors, whereas PFOS did not show a significant change over time. Precursors in fish may have played an important role for human exposure to PFOS in the 1990s but are probably negligible today. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Manuscript.</p> / PERFOOD project (KBBE-227525)