Das zu den Protozoen gehörende Phylum der Apicomplexa umfasst nahezu 6000 Parasitenarten. Die meisten Apicomplexa haben sich an eine obligat intrazelluläre Lebensweise angepasst und infizieren verschiedenste Tiere und den Menschen. Zu den bedeutendsten Vertretern der Apicomplexa zählen Toxoplasma, Plasmodium und Eimeria. In dieser Arbeit lag der Schwerpunkt auf den drei repräsentativen Organismen Toxoplasma gondii, Eimeria falciformis und Plasmodium berghei, welche sich alle in einem etablierten Wirt (der Maus) reproduzieren, sich allerdings hinsichtlich ihrer Wirtszellen, Persistenz sowie in ihrem Reproduktionsverhalten deutlich unterscheiden. Somit ermöglichen die genannten Parasiten eine umfassende Untersuchung der Biologie der Apicomplexa. Die meisten Entwicklungsstufen dieser Pathogene sind sehr eng mit der Wirtszelle assoziiert, was auch metabolische Wechselwirkungen beinhaltet. Das Verständnis dieser Interaktionen ist unerlässlich, um die Evolution von Parasiten zu ergründen. Grundsätzlich war das Ziel dieser Arbeit, die metabolischen Netzwerke der genannten Parasiten zu eruieren und den Einfluss des Metabolismus auf Wachstum, Pathogenese und Adaption in verschiedenen Nährstoffumgebungen zu untersuchen. Unsere Vorgehensweise verband biochemische, revers-genetische, zellbiologische und optogenetische Bottom-Up-Methoden mit Top-Down-Methoden wie Lipidomics, Metabolomics und Transcriptomics um folgende Prämissen anzugehen: • Vergleichender Entwurf der metabolischen Netzwerke in den obengenannten Parasiten • Nährstoff-Plastizität für die Überlebensfähigkeit des Parasiten in verschiedenen Milieus • Umregulierung oder Ausbeutung des Wirtsmetabolismus durch intrazelluläre Parasiten • Stadien-spezifische Regulation des Metabolismus während der asexuellen Reproduktion • Identifizierung und Validierung potentieller anti-parasitischer Wirkstoffe / The protozoan phylum apicomplexa comprises nearly 6000 parasitic species. Most apicomplexans have adapted to obligate intracellular parasitism in a wide range of organisms, including animals and humans. Some notable members of the phylum include Toxoplasma, Plasmodium and Eimeria species. This study focused on three representative parasites, namely Toxoplasma gondii, Eimeria falciformis and Plasmodium berghei, all of which infect a common and well-established model host organism (i.e. mouse), but have diverged from each other considerably with respect to the target host cells, persistence and reproduction behavior. These parasites together therefore enable a fairly inclusive study of the apicomplexan biology. Most developmental stages of these pathogens intimately associate with host cells, involving a metabolic crosstalk between the two entwined entities. A germane understanding of such interactions is vital to appreciate the evolution of parasites. In a nutshell, this work aimed to determine the design of metabolic networks in indicated parasites and the impact of metabolism on growth, pathogenesis and adaptation in discrete nutritional milieus. Our approach blended bottom-up methods of biochemistry, reverse genetics, cell biology and optogenetics with the top-down lipidomics, metabolomics and transcriptomics to address the following major premises: • Comparative design of the selected metabolic networks in aforementioned parasites • Nutritional plasticity underlying the parasite survival in variable environments • Subversion or exploitation of host metabolism by intracellular parasites • Stage-specific rewiring of parasite metabolism during asexual reproduction • Identification and endorsement of potential anti-parasitic drug targets

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Functional characterization of biochemically-isolated proteins is a central task in the biochemical and genetic description of the biology of cells and tissues. Protein identification by mass spectrometry consists of associating an isolated protein with a specific gene or protein sequence in silico, thus inferring its specific biochemical function based upon previous characterizations of that protein or a similar protein having that sequence identity. By performing this analysis on a large scale in conjunction with biochemical experiments, novel biological knowledge can be developed. The study presented here focuses on mass spectrometry-based proteomics of organisms with unsequenced genomes and corresponding developments in biological sequence database searching with mass spectrometry data. Conventional methods to identify proteins by mass spectrometry analysis have employed proteolytic digestion, fragmentation of resultant peptides, and the correlation of acquired tandem mass spectra with database sequences, relying upon exact matching algorithms; i.e. the analyzed peptide had to previously exist in a database in silico to be identified. One existing sequence-similarity protein identification method was applied (MS BLAST, Shevchenko 2001) and one alternative novel method was developed (MultiTag), for searching protein and EST databases, to enable the recognition of proteins that are generally unrecognizable by conventional softwares but share significant sequence similarity with database entries (~60-90%). These techniques and available database sequences enabled the characterization of the Xenopus laevis microtubule-associated proteome and the Dunaliella salina soluble salt-induced proteome, both organisms with unsequenced genomes and minimal database sequence resources. These sequence-similarity methods extended protein identification capabilities by more than two-fold compared to conventional methods, making existing methods virtually superfluous. The proteomics of Dunaliella salina demonstrated the utility of MS BLAST as an indispensable method for characterization of proteins in organisms with unsequenced genomes, and produced insight into Dunaliella?s inherent resilience to high salinity. The Xenopus study was the first proteomics project to simultaneously use all three central methods of representation for peptide tandem mass spectra for protein identification: sequence tags, amino acids sequences, and mass lists; and it is the largest proteomics study in Xenopus laevis yet completed, which indicated a potential relationship between the mitotic spindle of dividing cells and the protein synthesis machinery. At the beginning of these experiments, the identification of proteins was conceptualized as using ?conventional? versus ?sequence-similarity? techniques, but through the course of experiments, a conceptual shift in understanding occurred along with the techniques developed and employed to encompass variations in mass spectrometry instrumentation, alternative mass spectrum representation forms, and the complexities of database resources, producing a more systematic description and utilization of available resources for the characterization of proteomes by mass spectrometry and advanced informatic approaches. The experiments demonstrated that proteomics technologies are only as powerful in the field of biology as the biochemical experiments are precise and meaningful.

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Functional characterization of biochemically-isolated proteins is a central task in the biochemical and genetic description of the biology of cells and tissues. Protein identification by mass spectrometry consists of associating an isolated protein with a specific gene or protein sequence in silico, thus inferring its specific biochemical function based upon previous characterizations of that protein or a similar protein having that sequence identity. By performing this analysis on a large scale in conjunction with biochemical experiments, novel biological knowledge can be developed. The study presented here focuses on mass spectrometry-based proteomics of organisms with unsequenced genomes and corresponding developments in biological sequence database searching with mass spectrometry data. Conventional methods to identify proteins by mass spectrometry analysis have employed proteolytic digestion, fragmentation of resultant peptides, and the correlation of acquired tandem mass spectra with database sequences, relying upon exact matching algorithms; i.e. the analyzed peptide had to previously exist in a database in silico to be identified. One existing sequence-similarity protein identification method was applied (MS BLAST, Shevchenko 2001) and one alternative novel method was developed (MultiTag), for searching protein and EST databases, to enable the recognition of proteins that are generally unrecognizable by conventional softwares but share significant sequence similarity with database entries (~60-90%). These techniques and available database sequences enabled the characterization of the Xenopus laevis microtubule-associated proteome and the Dunaliella salina soluble salt-induced proteome, both organisms with unsequenced genomes and minimal database sequence resources. These sequence-similarity methods extended protein identification capabilities by more than two-fold compared to conventional methods, making existing methods virtually superfluous. The proteomics of Dunaliella salina demonstrated the utility of MS BLAST as an indispensable method for characterization of proteins in organisms with unsequenced genomes, and produced insight into Dunaliella?s inherent resilience to high salinity. The Xenopus study was the first proteomics project to simultaneously use all three central methods of representation for peptide tandem mass spectra for protein identification: sequence tags, amino acids sequences, and mass lists; and it is the largest proteomics study in Xenopus laevis yet completed, which indicated a potential relationship between the mitotic spindle of dividing cells and the protein synthesis machinery. At the beginning of these experiments, the identification of proteins was conceptualized as using ?conventional? versus ?sequence-similarity? techniques, but through the course of experiments, a conceptual shift in understanding occurred along with the techniques developed and employed to encompass variations in mass spectrometry instrumentation, alternative mass spectrum representation forms, and the complexities of database resources, producing a more systematic description and utilization of available resources for the characterization of proteomes by mass spectrometry and advanced informatic approaches. The experiments demonstrated that proteomics technologies are only as powerful in the field of biology as the biochemical experiments are precise and meaningful.