Mass spectrometry is the primary technology of proteomics. For the analysis of complex proteomes, protein identities and quantities are inferred from their peptides that are generated by cleaving all proteins with the endopeptidase trypsin. But there is one major disadvantage that is due to biophysical differences, different peptides cause different intensities. Miscellaneous approaches have been developed to circumvent this problem based on the chemical or metabolic introduction of heavy stable isotopes. This enables to monitor protein abundance differences of two or more samples on the same tryptic peptides that differ in mass only. Absolute quantification can be achieved similar by spiking-in synthetic isotopical labeled counterparts of a sample’s tryptic peptides. However, labeling technics suffer from high prices, introduced biases, need for extensive manual control, laborious implementation and implementation restrictions. Therefore, a multiplicity of label-free approaches have been developed that profit from instrumental improvements targeting reliability of identifications and reproducibility of quantitative values. No extensive systematic comparison of label-free quantitative parameters has been published so far presumably because of the laborious implementation. An analysis of primary label-free parameters and associated normalization methods is presented here that compares dynamic and linear ranges and accuracies in the estimation of protein amounts. This facilitated the establishment of label-free procedures addressing three fundamental questions in proteomics: what is a sample’s composition, are proteins that share a specific property enriched and what are the differences between two (or more) samples. A new mathematic model is presented that defines and elucidates enrichment. The procedures were applied first to analyze and compare stem cell plasma membrane proteomes. This is an ambitious model for proteomics because of only small amounts of arduous to analyze, partial hydrophobic proteins in a complex proteomic and chemical background. It is of scientific relevance, as membrane proteins are the cell’s communication interface that enable cell type specific processes and hence can be used to define, isolate and quantify those. The success of cell surface proteome enrichment, the quantitative composition of the proteome and the proteomic difference between stem cells isolated from the dental pulp and cultivated in different media is shown. Secondly, the procedures were applied to the analysis of transient protein networks that assemble onto proteo-liposomes in a newly designed recruitment assay that fully recapitulates membrane sorting as seen in vivo. All transmembrane proteins need to be trafficked to other organelles’ membranes by vesicular trafficking. Sorting signals within the cytosolic regions of the protein cargos trigger the formation of trafficking complexes around those. The transient membrane complexes additionally recognize organelle or organelle-domain specific membrane lipids, such as phosphatidylinositol phosphates. Different trafficking ways are characterized by different trafficking complexes. The elucidation of trafficking complexes that form around a transmembrane protein of interest discloses its trafficking routes and involved signaling processes. The synthetic proteo-liposomes were prepared from chemically defined lipids and heterologous expressed cytosolic domains of type I or type II membrane receptors. The proteomic analyses of such samples are challenging because of huge proteomic backgrounds of proteins binding to the liposomes irrespective of the receptor and relatively small amounts and numbers of receptor-specific binders. Though the basic idea is to elucidate sorting machineries and study membrane trafficking processes, such experiments are untargeted and miscellaneous discoveries were achieved. We elucidated that the apical determinant crumbs 2 is a cargo of the retromer complex. This revealed a fameless level of control for the establishment of cell polarity. We found retromer along with the adapter complexes AP 4 and AP 5 trafficking the beta amyloid precursor protein APP. This confirmed recent publications and yielded new insights. Moreover, many more proteins and complexes appeared to associate with the cytosolic part of APP (AICD) in a membrane context-dependent or -independent manner. Among those, some were so far unknown to interact with AICD, like mTORC1 and the PIKFyve complex.

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.