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Patrick G. A. Pedrioli

Bio: Patrick G. A. Pedrioli is an academic researcher from ETH Zurich. The author has contributed to research in topics: Kinase & Proteome. The author has an hindex of 26, co-authored 42 publications receiving 4020 citations. Previous affiliations of Patrick G. A. Pedrioli include Institute for Systems Biology & University of Dundee.

Papers
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Journal ArticleDOI
TL;DR: The 'mzXML' format is introduced, an open, generic XML (extensible markup language) representation of MS data that will facilitate data management, interpretation and dissemination in proteomics research.
Abstract: A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.

788 citations

Journal ArticleDOI
TL;DR: K63-Ub oligomers are identified as a major substrate of HOIP in cells where the MyD88-dependent signaling network is activated and may help to resolve the debate about the relative importance of K63-pUb and M1-p Ub chains in activating the canonical IKK complex.
Abstract: Polyubiquitin (pUb) chains formed between the C terminus of ubiquitin and lysine 63 (K63) or methionine 1 (M1) of another ubiquitin have been implicated in the activation of the canonical IκB kinase (IKK) complex. Here, we demonstrate that nearly all of the M1-pUb chains formed in response to interleukin-1, or the Toll-Like Receptors 1/2 agonist Pam3CSK4, are covalently attached to K63-pUb chains either directly as K63-pUb/M1-pUb hybrids or indirectly by attachment to the same protein. Interleukin-1 receptor (IL-1R)-associated kinase (IRAK) 1 is modified first by K63-pUb chains to which M1-pUb linkages are added subsequently, and myeloid differentiation primary response gene 88 (MyD88) and IRAK4 are also modified by both K63-pUb and M1-pUb chains. We show that the heme-oxidized IRP2 ubiquitin ligase 1 interacting protein (HOIP) component of the linear ubiquitin assembly complex catalyzes the formation of M1-pUb chains in response to interleukin-1, that the formation of K63-pUb chains is a prerequisite for the formation of M1-pUb chains, and that HOIP interacts with K63-pUb but not M1-pUb linkages. These findings identify K63-Ub oligomers as a major substrate of HOIP in cells where the MyD88-dependent signaling network is activated. The TGF-beta–activated kinase 1 (TAK1)-binding protein (TAB) 2 and TAB3 components of the TAK1 complex and the NFκB Essential Modifier (NEMO) component of the canonical IKK complex bind to K63-pUb chains and M1-pUb chains, respectively. The formation of K63/M1-pUb hybrids may therefore provide an elegant mechanism for colocalizing both complexes to the same pUb chain, facilitating the TAK1-catalyzed activation of IKKα and IKKβ. Our study may help to resolve the debate about the relative importance of K63-pUb and M1-pUb chains in activating the canonical IKK complex.

356 citations

Journal ArticleDOI
TL;DR: A system-wide analysis of protein phosphorylation in yeast reveals robustness in the network of kinases and phosphatases and reinforces the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.
Abstract: The phosphorylation and dephosphorylation of proteins by kinases and phosphatases constitute an essential regulatory network in eukaryotic cells. This network supports the flow of information from sensors through signaling systems to effector molecules and ultimately drives the phenotype and function of cells, tissues, and organisms. Dysregulation of this process has severe consequences and is one of the main factors in the emergence and progression of diseases, including cancer. Thus, major efforts have been invested in developing specific inhibitors that modulate the activity of individual kinases or phosphatases; however, it has been difficult to assess how such pharmacological interventions would affect the cellular signaling network as a whole. Here, we used label-free, quantitative phosphoproteomics in a systematically perturbed model organism (Saccharomyces cerevisiae) to determine the relationships between 97 kinases, 27 phosphatases, and more than 1000 phosphoproteins. We identified 8814 regulated phosphorylation events, describing the first system-wide protein phosphorylation network in vivo. Our results show that, at steady state, inactivation of most kinases and phosphatases affected large parts of the phosphorylation-modulated signal transduction machinery-and not only the immediate downstream targets. The observed cellular growth phenotype was often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling and reinforce the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.

310 citations

Journal ArticleDOI
TL;DR: It is shown that high-quality proteomics data provide crucial information to amend genome annotation and to confirm many predicted gene models, and this library of proteotypic peptides should enable fast, targeted and quantitative proteomic studies to elucidate the systems biology of this model organism.
Abstract: Understanding how proteins and their complex interaction networks convert the genomic information into a dynamic living organism is a fundamental challenge in biological sciences. As an important step towards understanding the systems biology of a complex eukaryote, we cataloged 63% of the predicted Drosophila melanogaster proteome by detecting 9,124 proteins from 498,000 redundant and 72,281 distinct peptide identifications. This unprecedented high proteome coverage for a complex eukaryote was achieved by combining sample diversity, multidimensional biochemical fractionation and analysis-driven experimentation feedback loops, whereby data collection is guided by statistical analysis of prior data. We show that high-quality proteomics data provide crucial information to amend genome annotation and to confirm many predicted gene models. We also present experimentally identified proteotypic peptides matching approximately 50% of D. melanogaster gene models. This library of proteotypic peptides should enable fast, targeted and quantitative proteomic studies to elucidate the systems biology of this model organism.

273 citations

Journal ArticleDOI
12 Mar 2009-Nature
TL;DR: Functional analysis reveals that the thiolation function of Urm1p is critical to regulate cellular responses to nutrient starvation and oxidative stress conditions, most likely by increasing translation fidelity.
Abstract: Ubiquitin-like proteins (UBLs) can change protein function, localization or turnover by covalent attachment to lysine residues. Although UBLs achieve this conjugation through an intricate enzymatic cascade, their bacterial counterparts MoaD and ThiS function as sulphur carrier proteins. Here we show that Urm1p, the most ancient UBL, acts as a sulphur carrier in the process of eukaryotic transfer RNA (tRNA) modification, providing a possible evolutionary link between UBL and sulphur transfer. Moreover, we identify Uba4p, Ncs2p, Ncs6p and Yor251cp as components of this conserved pathway. Using in vitro assays, we show that Ncs6p binds to tRNA, whereas Uba4p first adenylates and then directly transfers sulphur onto Urm1p. Finally, functional analysis reveals that the thiolation function of Urm1p is critical to regulate cellular responses to nutrient starvation and oxidative stress conditions, most likely by increasing translation fidelity.

252 citations


Cited by
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Journal ArticleDOI
TL;DR: The ProteoWizard Toolkit is developed, a robust set of open-source, software libraries and applications designed to facilitate proteomics research that implements the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats.
Abstract: Mass-spectrometry-based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples1, identify pathways affected by endogenous and exogenous perturbations2, and characterize protein complexes3. Despite successes, the interpretation of vast proteomics datasets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access4,5. In response, we have developed the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.

2,480 citations

Journal ArticleDOI
22 Jan 2010-Science
TL;DR: A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function.
Abstract: A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.

2,225 citations

Journal ArticleDOI
14 Apr 2006-Science
TL;DR: Recent advances in mass spectrometry instrumentation are reviewed in the context of current and emerging research strategies in protein science.
Abstract: Mass spectrometry is a central analytical technique for protein research and for the study of biomolecules in general. Driven by the need to identify, characterize, and quantify proteins at ever increasing sensitivity and in ever more complex samples, a wide range of new mass spectrometry-based analytical platforms and experimental strategies have emerged. Here we review recent advances in mass spectrometry instrumentation in the context of current and emerging research strategies in protein science.

1,992 citations

Journal ArticleDOI
TL;DR: This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes.
Abstract: This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed.

1,954 citations

Journal ArticleDOI
15 Jun 2017-Cell
TL;DR: Roles for mRNA modification in nearly every aspect of the mRNA life cycle, as well as in various cellular, developmental, and disease processes are revealed.

1,855 citations