768 research outputs found
A case study on the comparison of different software tools for automated quantification of peptides
No full textMS-driven proteomics has evolved over the past two decades to a high tech and high impact research field. Two distinct factors clearly influenced its expansion: the rapid growth of an arsenal of instrument and proteomic techniques that led to an explosion of high quality data and the development of software tools to analyze and interpret these data which boosted the number of scientific discoveries. In analogy with the benchmarking of new instruments and proteomic techniques, such software tools must be thoroughly tested and analyzed. Recently, new tools were developed for automatic peptide quantification in quantitative proteomic experiments. Here we present a case study where the most recent and frequently used tools are analyzed and compared
Targeted profiling of protein phosphorylation in plants
No full textProteins are crucial for controlling different cellular processes by perceiving and converting external environmental cues into cellular responses. Therefore, regulation of protein activities is pivotal for the development and survival of an organism. This is often mediated by posttranslational modifications, which usually are carried out on specific residues of a target protein by a “writer” protein. The (reversible) modifications of different residues may lead to different signaling outputs. In the case of protein phosphorylation, one of the most common posttranslational modifications, this writer protein is a protein kinase. In this chapter, we report a comprehensive and versatile workflow to identify the phosphorylation profile of a target protein in plants from a putative kinase-target pair by combining an in planta phosphorylation assay and mass spectrometry analysis
Cell surface biotinylation using furan cross-linking chemistry
No full textA detailed study of the cellular surfaceome poses major challenges for mass spectrometry analysis. Surface proteins are low abundant compared to intracellular proteins, and their inefficient extraction in aqueous medium leads to their aggregation and precipitation. To tackle such problems, surface biotinylation is frequently used to tag surface proteins with biotin, allowing for their enrichment, leading to a more sensitive mapping of surface proteomes. We here detail a new surface biotinylation protocol based on furan-biotin affinity purification to enrich plasma membrane proteins for proteomics. This protocol involves biotinylation of cell surface membrane proteins on viable cells, followed by affinity enrichment using streptavidin beads, trypsin digestion, peptide cleanup, and LC-MS/MS analysis
Increasing the overall proteome coverage by combining protein digestion by Tryp-N and trypsin
No full textMass spectrometry-based proteomics combining more than one protease in parallel facilitates the identification of more peptides and proteins than when a single protease is used. Trypsin cleaves proteins C-terminally to arginine and lysine, while its mirroring protease Tryp-N cleaves N-terminally to the same amino acids. Here, we combine trypsin and Tryp-N with the commercially available S-Trap columns, which purify protein samples and catalyze digestion. Comparison of trypsin or Tryp-N coupled with S-Trap columns demonstrates plasma and cell lysate proteins unique to one protease. We thus suggest the use of both proteases in a complementary manner to obtain deeper proteome coverage
The substrate repertoire and the specificity of proteases assessed by peptide-centric proteomics
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Virotrap : trapping protein complexes in virus-like particles
No full textThe discovery of protein-protein interactions can provide crucial information on protein function by linking proteins into known pathways or complexes within the cell. Mass spectrometry (MS)-based methods, such as affinity purification (AP)-MS and proximity-dependent biotin identification (BioID), allowed for a vast increase in the number of reported protein complexes. As a more recent addition to the arsenal of MS-based methods, Virotrap represents a unique technology that benefits from the specific properties of the human immunodeficiency virus-1 (HIV-1) Gag polyprotein. More specifically, Virotrap captures protein complexes in virus-like particles budded from human embryonic kidney (HEK293T) cells, bypassing the need for cell lysis and thus supporting identification of their content using MS. Being intrinsically different to its two main predecessors, affinity purification MS (AP-MS) and biotin-dependent identification (BioID), Virotrap was shown to complement data obtained with the existing MS-based toolkit. The proven complementarity of these MS-based strategies underlines the importance of using different techniques to enable comprehensive mapping of protein-protein interactions (PPIs). In this chapter, we provide a detailed overview of the Virotrap protocol to screen for PPIs using a bait protein of interest
Sensitive and High-Throughput Exploration of Protein N-Termini by TMT-TAILS N-Terminomics
No full textTerminal amine isotopic labeling of substrates (TAILS) is a sensitive and robust quantitative mass spectrometry (MS)-based proteomics method used for the characterization of physiological or proteolytically processed protein N-termini, as well as other N-terminal posttranslational modifications (PTMs). TAILS is a well-established, high-throughput, negative enrichment workflow that enables system-wide exploration of N-terminomes independent of sample complexity. TAILS makes use of amine reactivity of free N-termini and a highly efficient aldehyde-functionalized polymer to deplete internal peptides generated after proteolytic digestion during sample preparation. Thereby, it enriches for natural N-termini, allowing for unbiased and complete investigation of differential proteolysis, protease substrate discovery, and analysis of N-terminal PTMs. In this chapter, we provide a state-of-the-art protocol, with detailed steps in all parts of the TAILS sample preparation, MS analysis, and post-processing of acquired data
Studying in vitro and in vivo protease processing in models of cancer cell death and viral infection by N-terminal COFRADIC
No full textBeing an irreversible protein modification, proteolytic processing has an important role in many biological processes. Together with proteases and their inhibitors, protease substrates are the key components of proteolytic networks. Knowledge on the substrate repertoire of individual proteases is therefore crucial for a thorough understanding of protease biology. Over the last decade several screening methods for proteome-wide identification of protease substrates were developed. These methods are based on targeted, N-terminal proteomics and include the N-terminal COFRADIC technology developed in the lab in which my PhD project was performed.
During my PhD project N-terminal COFRADIC was used to identify unknown protease cleavage sites in two model systems. In a first study, I tried to gain novel insight into the proteases involved in cell death induced by the chemotherapeutic agent paclitaxel or taxol. Amongst others, my results shed new light on the caspase-dependency of this cell death model. In a second series of screens, protease processing during HIV-1 infection was studied. Unknown protease cleavage sites were found both in infected cells and purified HIV-1 virions. Furthermore, novel information on non-processing events was obtained from these experiments. Finally, several in vitro substrate catalogues were generated for proteases linked to both these previous studies and a novel experimental design to compile these catalogues was developed. In the latter procedure laborious manual annotation of cleavage sites was replaced by software-based quantification and annotation.
Taken together, this thesis project illustrates the power of N-terminal proteomics in protease research, but also indicates its limitations in analyzing in vivo protease cleavage sites. Nevertheless, many novel interesting results were obtained, providing clues for further research in the future
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