Quantification and Simulation of Liquid Chromatography-Mass Spectrometry Data

Computational mass spectrometry is a fast evolving field that has attracted increased attention over the last couple of years. The performance of software solutions determines the success of analysis to a great extent. New algorithms are required to reflect new experimental procedures and deal with new instrument generations. One essential component of algorithm development is the validation (as well as comparison) of software on a broad range of data sets. This requires a gold standard (or so-called ground truth), which is usually obtained by manual annotation of a real data set. Comprehensive manually annotated public data sets for mass spectrometry data are labor-intensive to produce and their quality strongly depends on the skill of the human expert. Some parts of the data may even be impossible to annotate due to high levels of noise or other ambiguities. Furthermore, manually annotated data is usually not available for all steps in a typical computational analysis pipeline. We thus developed the most comprehensive simulation software to date, which allows to generate multiple levels of ground truth and features a plethora of settings to reflect experimental conditions and instrument settings. The simulator is used to generate several distinct types of data. The data are subsequently employed to evaluate existing algorithms. Additionally, we employ simulation to determine the influence of instrument attributes and sample complexity on the ability of algorithms to recover information. The results give valuable hints on how to optimize experimental setups. Furthermore, this thesis introduces two quantitative approaches, namely a decharging algorithm based on integer linear programming and a new workflow for identification of differentially expressed proteins for a large in vitro study on toxic compounds. Decharging infers the uncharged mass of a peptide (or protein) by clustering all its charge variants. The latter occur frequently under certain experimental conditions. We employ simulation to show that decharging is robust against missing values even for high complexity data and that the algorithm outperforms other solutions in terms of mass accuracy and run time on real data. The last part of this thesis deals with a new state-of-the-art workflow for protein quantification based on isobaric tags for relative and absolute quantitation (iTRAQ). We devise a new approach to isotope correction, propose an experimental design, introduce new metrics of iTRAQ data quality, and confirm putative properties of iTRAQ data using a novel approach. All tools developed as part of this thesis are implemented in OpenMS, a C++ library for computational mass spectrometry

Metabolic network activity characterization using mass spectrometric methods

Innovative methods were developed for metabolic network activity characterization using mass spectrometry. Metabolic flux analysis (MFA) and kinetics of metabolic networks were developed and applied to Corynebacterium glutamicum. A protocol to determine metabolic fluxes at low degree of labelling using gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) by the measurement of 13C enrichment in proteinogenic amino acid hydrolyzates was described. Kinetic isotope effects played an increasing role at low degree of labeling but could be corrected. From these corrected 13C enrichments In vivo fluxes in the central metabolism were determined by numerical optimization. The GC-C-IRMS-based method involving low labeling degree of expensive tracer substrate, e.g. 1%, is therefore promising for larger laboratory and industrial pilot scale fermentations. Permeabilization of Corynebacterium glutamicum cells was investigated and optimized. Permeabilized cells are considered closer to the in-vivo situation than purified enzyme(s) for the study of kinetics. A novel strategy was developed for the determination of in-situ enzymatic network kinetics combining permeabilization and matrix-assisted laser desorption/ionization time-of—flight mass spectrometry (MALDI-TOF-MS) quantification. Quantification of small molecular mass metabolites in glycolysis and pentose-phosphate pathway using MALDI-TOF-MS with [U-13C6] glucose-6-phosphate as single internal standard was established. Signal suppression during MALDI analysis could be compensated by applying the standard addition method. Adding selected substrates and cofactors, kinetics of glycolysis and pentose-phosphate pathways were be characterized using this method.Im Rahmen dieser Arbeit wurden neue Massenspektrometrie-basierte Methoden zur Charakterisierung der Aktivität metabolischer Netzwerke entwickelt, die zur Flussanalyse in metabolischen Netzwerken sowie zur Analyse der Kinetik metabolischer Netzwerke angewendet wurden. Die Methode zur Bestimmung metabolischer Flüsse basiert auf der Messung der 13C-Anreicherung in Aminosäuren von Proteinhydrolysaten mit Hilfe von GC-C-IRMS (gas-chromatography-combustion-isotope ratio mass spectrometry). Der Vorteil dieser Methode besteht darin, dass die Bestimmung metabolischer Flüsse auch bei sehr geringen Mengen an 13C-markiertem Substrat möglich ist. Durch Messung der 13C-Anreicherung in Aminosäuren und Korrektur von Isotopen-Effekten sowie durch Anpassung der korrigierten Daten mit Hilfe numerischer Optimierungen, konnten in vivo Flussverteilungen im Zentralstoffwechsel bestimmt werden. Da bei der GC-C-IRMS basierten Methode nur sehr geringe Mengen an relativ teurem 13C markiertem Substrat benötigt werden (~1%), ist diese Methodik insbesondere für die Anwendung in größerem Maßstab geeignet. Des Weiteren wurden Techniken zur Permeabiliserung von Corynebacterium glutamicum untersucht und optimiert. Generell sind permeabilisierte Zellen zur Bestimmung von in vivo Enzymkinetiken besser geeignet als isolierte und gereinigte Enzyme. Zur in situ Bestimmung von Kinetiken in enzymatischen Netzwerken wurde in dieser Arbeit eine Methode entwickelt, bei der die Enzymaktivität in permeabilisierten Zellen bestimmt wird und des Weiteren eine MALDI-TOF-MS-basierte Quantifizierung von intrazellulären Metaboliten erfolgt. Die Quantifizierung von Metaboliten der Glykolyse und des Pentosephosphat-Wegs mittels MALDI-TOF-MS erfolgte mit Hilfe von [U-13C6] Glukose-6-Phosphat als internem Standard. Die bei der MALDI-Messung auftretenden Signal-Unterdrückungen konnten durch Zugabe des Standards korrigiert werden. Durch Messung der entsprechenden Metabolite sowie durch Bestimmung von intrazellulären Enyzmaktivitäten mit Hilfe geeigneter Substrate und Kofaktoren, konnten die Kinetiken von Glykolyse sowie des Pentose-Phosphatweg erfolgreich charakterisiert werden

Detection of Ru potential metallodrug in human urine by MALDI-TOF mass spectrometry: validation and options to enhance the sensitivity

We studied the possibility of detection of [Ru(η5 -C5H5)(PPh3)2Cl] (abbreviated by RuCp) complex as a model system for Ru-based metallodrugs in human urine by using matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) without previous purification or removal of inorganic salts. Inorganic salts might prevent the detection of RuCp by MALDI-TOF MS, most likely through the increased number and intensity of background/organic matrix signals. This problem might be overcome by the acquisition of matrix free spectra and the addition of nanoparticles, such as carbon dots, to the urine solution. Our results suggest that RuCp is easily detectable by MALDI-TOF MS in all acquisition conditions, with the CHCA matrix being the best for acquisition in phosphate-containing solutions, whereas in urine, DHB and matrix-free approach demonstrated the highest sensitivity, precision, and reproducibility. The sensitivity of matrix-free MALDI detection of RuCp could be increased by the addition of carbon dots to the urine. Based on theoretical calcu lations for all matrix/analyte combinations, the model for the interaction of RuCp with carbon dots was established, and higher sensitivity explained.info:eu-repo/semantics/publishedVersio

Peak annotation and data analysis software tools for mass spectrometry imaging

La metabolòmica espacial és la disciplina que estudia les imatges de les distribucions de compostos químics de baix pes (metabòlits) a la superfície dels teixits biològics per revelar interaccions entre molècules. La imatge d'espectrometria de masses (MSI) és actualment la tècnica principal per obtenir informació d'imatges moleculars per a la metabolòmica espacial. MSI és una tecnologia d'imatges moleculars sense marcador que produeix espectres de masses que conserven les estructures espacials de les mostres de teixit. Això s'aconsegueix ionitzant petites porcions d'una mostra (un píxel) en un ràster definit a través de tota la seva superfície, cosa que dona com a resultat una col·lecció d'imatges de distribució de ions (registrades com a relacions massa-càrrega (m/z)) sobre la mostra. Aquesta tesi té com a objectius desenvolupar eines computacionals per a l'anotació de pics de MSI i el disseny de fluxos de treball per a l'anàlisi estadística i multivariant de dades MSI, inclosa la segmentació espacial. El treball realitzat en aquesta tesi es pot separar clarament en dues parts. En primer lloc, el desenvolupament d'una eina d'anotació de pics d'isòtops i adductes adequada per facilitar la identificació de compostos de rang de massa baix. Ara podem trobar fàcilment ions monoisotòpics als nostres conjunts de dades MSI gràcies al paquet de programari rMSIannotation. En segon lloc, el desenvolupament de eines de programari per a l’anàlisi de dades i la segmentació espacial basades en soft clustering per a dades MSI.La metabolómica espacial es la disciplina que estudia las imágenes de las distribuciones de compuestos químicos de bajo peso (metabolitos) en la superficie de los tejidos biológicos para revelar interacciones entre moléculas. Las imágenes de espectrometría de masas (MSI) es actualmente la principal técnica para obtener información de imágenes moleculares para la metabolómica espacial. MSI es una tecnología de imágenes moleculares sin marcador que produce espectros de masas que conservan las estructuras espaciales de las muestras de tejido. Esto se logra ionizando pequeñas porciones de una muestra (un píxel) en un ráster definido a través de toda su superficie, lo que da como resultado una colección de imágenes de distribución de iones (registradas como relaciones masa-carga (m/z)) sobre la muestra. Esta tesis tiene como objetivo desarrollar herramientas computacionales para la anotación de picos en MSI y en el diseño de flujos de trabajo para el análisis estadístico y multivariado de datos MSI, incluida la segmentación espacial. El trabajo realizado en esta tesis se puede separar claramente en dos partes. En primer lugar, el desarrollo de una herramienta de anotación de picos de isótopos y aductos adecuada para facilitar la identificación de compuestos de bajo rango de masa. Ahora podemos encontrar fácilmente iones monoisotópicos en nuestros conjuntos de datos MSI gracias al paquete de software rMSIannotation.Spatial metabolomics is the discipline that studies the images of the distributions of low weight chemical compounds (metabolites) on the surface of biological tissues to unveil interactions between molecules. Mass spectrometry imaging (MSI) is currently the principal technique to get molecular imaging information for spatial metabolomics. MSI is a labelfree molecular imaging technology that produces mass spectra preserving the spatial structures of tissue samples. This is achieved by ionizing small portions of a sample (a pixel) in a defined raster through all its surface, which results in a collection of ion distribution images (registered as mass-to-charge ratios (m/z)) over the sample. This thesis is aimed to develop computational tools for peak annotation in MSI and in the design of workflows for the statistical and multivariate analysis of MSI data, including spatial segmentation. The work carried out in this thesis can be clearly separated in two parts. Firstly, the development of an isotope and adduct peak annotation tool suited to facilitate the identification of the low mass range compounds. We can now easily find monoisotopic ions in our MSI datasets thanks to the rMSIannotation software package. Secondly, the development of software tools for data analysis and spatial segmentation based on soft clustering for MSI data. In this thesis, we have developed tools and methodologies to search for significant ions (rMSIKeyIon software package) and for the soft clustering of tissues (Fuzzy c-means algorithm)

Biomarker discovery for cervical cancer

Proteomics of human boy fluids is still in its early stage of development with major methodological challenges ahead. This implies that much attention is given to improving the methods and strategies. One major challenge is that many samples that have been acquired in the past may not fulfill the stringent requirements of storage and sample preparation to allow comparable proteomics analyses. It is therefore important to assess the factors that may affect the final proteomics result through systematic and reproducible analyses. Therefore accuracy and sensitivity of the analytical instrumentation is not the only critical factor in this research. Blood (plasma or serum) and urine can be easily sampled from patients or healthy volunteers and are therefore often the first choice when trying to discover novel biomarkers or biomarker patterns to diagnose cancer and other diseases. There are, however, drawbacks such as the masking of low-abundance by high abundance proteins and the possible effect of sampling and sample handling procedures (e.g. different times for blood clotting). A number of different approaches to deplete highly abundant proteins from human serum were studied throughout this thesis. Further, different analytical techniques were applied, such as a miniaturized, microfluidics-based LC-MS system (chip-LC-MS) to enhance overall sensitivity. It is shown that chip-LC-MS has at least twice the resolution of the previously used standard capillary LC-MS method. Since blood composition will change under the influence of external factors, the influence of clotting time on proteome of serum was studied. It was found that most proteins were not affected by clotting time except for those directly involved in this process, such as the fibrinopeptides. Next, we describe a more comprehensive approach for evaluating the influence of various pre-analytical parameters on the serum proteome. A factorial design strategy was applied to assess the importance of seven factors considered to be of relevance, including the level of hemolysis, the digestion conditions, and the storage conditions. Finally, we analyzed serum samples from cervical cancer patients at various stages of disease before and after treatment followed by data processing and statistical data analysis. While we did not discover major changes in the serum proteome using this method, subtle changes in the protein composition were observed in relation to treatment, the significance of which are being further investigated. It is thus demonstrated that the described methods are applicable to highly complex body fluids such as serum and that further studies into the relevance of the discovered changes of the serum proteome are warranted.

Applications of Mass Spectrometry to Analysis of Prodiginines, Bioactivated Methylenedianiline Intermediates, and Hypoxia Induced Changes in the Zebrafish Skeletal Muscle Proteome

Mass spectrometry coupled with liquid chromatography and gel electrophoresis enables separation and detection of components in a complex mixture. During the last two decades, its applications were dramatically extended and remarkable progress has been made in many fields, in particular, environmental and biological analyses. This dissertation focuses on identification and characterization of biologically active compounds and comparative analysis of protein expression changes. The first two projects (Chapters 2 and 3) focus on the application of LC/MS approach to profile the bioactivated intermediates of 4, 4\u27-methylenedianiline (DAPM) from rat vascular smooth muscle cells (VSMCs) and bile. In our study, several DAPM metabolites were detected and characterized in detail by liquid chromatography-electrospray tandem mass spectrometry. The structural assignments of these metabolites from VSMCs and rat bile significantly improve our understanding of DAPM biotransformations and toxicity. The third project described in Chapter 4 focuses on using electrospray tandem mass spectrometry (ES-MS/MS) and theoretical calculation (GAUSSIAN 03 program) to investigate the unusual methyl radical loss and consecutive fragment ions that dominate the low-energy collision induced dissociation (CID) mass spectra of prodiginine compounds. Structures of the fragment ions are proposed and explanations are given to rationalize the observed competition between the formation of even-electron ions and radical ions. Our study shows that the lower apparent threshold associated with methyl radical loss points to a lower kinetic barrier. In Chapter 5, hypoxia-induced changes of zebrafish skeletal muscle were studied using two-dimensional difference in-gel electrophoresis (2D-DIGE) in vivo after 48 h in hypoxia vs. normoxia. The results showed that proteins involved in mitochondrial oxidative metabolism are down-regulated, whereas glycolytic enzymes are up-regulated to compensate for the loss of ATP synthesis in aerobic metabolism. The up-regulation of two spots identified as hemoglobin variants was also observed. These protein expression changes are consistent with a hypoxic response that enhances anaerobic metabolism or O2 transport to tissues