Erich Brunner

Wnt/Wingless Signaling Requires BCL9/Legless-Mediated Recruitment of Pygopus to the Nuclear β-Catenin-TCF Complex

Wnt/Wingless signaling controls many fundamental processes during animal development. Wnt transduction is mediated by the association of beta-catenin with nuclear TCF DNA binding factors. Here we report the identification of two segment polarity genes in Drosophila, legless (lgs), and pygopus (pygo), and we show that their products are required for Wnt signal transduction at the level of nuclear beta-catenin. Lgs encodes the homolog of human BCL9, and we provide genetic and molecular evidence that these proteins exert their function by physically linking Pygo to beta-catenin. Our results suggest that the recruitment of Pygo permits beta-catenin to transcriptionally activate Wnt target genes and raise the possibility that a deregulation of these events may play a causal role in the development of B cell malignancies.

Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry

A crucial aim upon the completion of the human genome is the verification and functional annotation of all predicted genes and their protein products. Here we describe the mapping of peptides derived from accurate interpretations of protein tandem mass spectrometry (MS) data to eukaryotic genomes and the generation of an expandable resource for integration of data from many diverse proteomics experiments. Furthermore, we demonstrate that peptide identifications obtained from high-throughput proteomics can be integrated on a large scale with the human genome. This resource could serve as an expandable repository for MS-derived proteome information.

A high-quality catalog of the Drosophila melanogaster proteome.

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 ∼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.

Comparative functional analysis of the Caenorhabditis elegans and Drosophila melanogaster proteomes

The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance.

Deterministic protein inference for shotgun proteomics data provides new insights into Arabidopsis pollen development and function

Pollen, the male gametophyte of flowering plants, represents an ideal biological system to study developmental processes, such as cell polarity, tip growth, and morphogenesis. Upon hydration, the metabolically quiescent pollen rapidly switches to an active state, exhibiting extremely fast growth. This rapid switch requires relevant proteins to be stored in the mature pollen, where they have to retain functionality in a desiccated environment. Using a shotgun proteomics approach, we unambiguously identified approximately 3500 proteins in Arabidopsis pollen, including 537 proteins that were not identified in genetic or transcriptomic studies. To generate this comprehensive reference data set, which extends the previously reported pollen proteome by a factor of 13, we developed a novel deterministic peptide classification scheme for protein inference. This generally applicable approach considers the gene model-protein sequence-protein accession relationships. It allowed us to classify and eliminate ambiguities inherently associated with any shotgun proteomics data set, to report a conservative list of protein identifications, and to seamlessly integrate data from previous transcriptomics studies. Manual validation of proteins unambiguously identified by a single, information-rich peptide enabled us to significantly reduce the false discovery rate, while keeping valuable identifications of shorter and lower abundant proteins. Bioinformatic analyses revealed a higher stability of pollen proteins compared to those of other tissues and implied a protein family of previously unknown function in vesicle trafficking. Interestingly, the pollen proteome is most similar to that of seeds, indicating physiological similarities between these developmentally distinct tissues.

Generating and navigating proteome maps using mass spectrometry

Proteomes, the ensembles of all proteins expressed by cells or tissues, are typically analysed by mass spectrometry. Recent technical and computational advances have greatly increased the fraction of a proteome that can be identified and quantified in a single study. Current mass spectrometry-based proteomic strategies have the potential to reproducibly, accurately, quantitatively and comprehensively measure any protein or whole proteomes from cells and tissues at different states. Achieving these goals will require complete proteome maps and analytical strategies that use these maps as prior information and will greatly enhance the impact of proteomics on biological and clinical research.

Identification and Functional Characterization of N-Terminally Acetylated Proteins in Drosophila melanogaster

A new study reveals a functional rule for N-terminal acetylation in higher eukaryotes called the (X)PX rule and describes a generic method that prevents this modification to allow the study of N-terminal acetylation in any given protein.

The Comprehensive Native Interactome of a Fully Functional Tagged Prion Protein

The enumeration of the interaction partners of the cellular prion protein, PrPC, may help clarifying its elusive molecular function. Here we added a carboxy proximal myc epitope tag to PrPC. When expressed in transgenic mice, PrPmyc carried a GPI anchor, was targeted to lipid rafts, and was glycosylated similarly to PrPC. PrPmyc antagonized the toxicity of truncated PrP, restored prion infectibility of PrPC-deficient mice, and was physically incorporated into PrPSc aggregates, indicating that it possessed all functional characteristics of genuine PrPC. We then immunopurified myc epitope-containing protein complexes from PrPmyc transgenic mouse brains. Gentle differential elution with epitope-mimetic decapeptides, or a scrambled version thereof, yielded 96 specifically released proteins. Quantitative mass spectrometry with isotope-coded tags identified seven proteins which co-eluted equimolarly with PrPC and may represent component of a multiprotein complex. Selected PrPC interactors were validated using independent methods. Several of these proteins appear to exert functions in axomyelinic maintenance.

The Drosophila melanogaster PeptideAtlas facilitates the use of peptide data for improved fly proteomics and genome annotation

BackgroundCrucial foundations of any quantitative systems biology experiment are correct genome and proteome annotations. Protein databases compiled from high quality empirical protein identifications that are in turn based on correct gene models increase the correctness, sensitivity, and quantitative accuracy of systems biology genome-scale experiments.ResultsIn this manuscript, we present the Drosophila melanogaster PeptideAtlas, a fly proteomics and genomics resource of unsurpassed depth. Based on peptide mass spectrometry data collected in our laboratory the portal http://www.drosophila-peptideatlas.org allows querying fly protein data observed with respect to gene model confirmation and splice site verification as well as for the identification of proteotypic peptides suited for targeted proteomics studies. Additionally, the database provides consensus mass spectra for observed peptides along with qualitative and quantitative information about the number of observations of a particular peptide and the sample(s) in which it was observed.ConclusionPeptideAtlas is an open access database for the Drosophila community that has several features and applications that support (1) reduction of the complexity inherently associated with performing targeted proteomic studies, (2) designing and accelerating shotgun proteomics experiments, (3) confirming or questioning gene models, and (4) adjusting gene models such that they are in line with observed Drosophila peptides. While the database consists of proteomic data it is not required that the user is a proteomics expert.

A combined proteomic and genetic analysis identifies a role for the lipid desaturase Desat1 in starvation-induced autophagy in Drosophila.

Autophagy is a lysosomal-mediated degradation process that promotes cell survival during nutrient-limiting conditions. However, excessive autophagy results in cell death. In Drosophila, autophagy is regulated nutritionally, hormonally and developmentally in several tissues, including the fat body, a nutrient-storage organ. Here, we use a proteomics approach to identify components of starvation-induced autophagic responses in the Drosophila fat body. Using cICATTM labeling and mass spectrometry, differences in protein expression levels of normal compared to starved fat bodies were determined. Candidates were analyzed genetically for their involvement in autophagy in fat bodies deficient for the respective genes. One of these genes, Desat1, encodes a lipid desaturase. Desat1 mutant cells fail to induce autophagy upon starvation. The desat1 protein localizes to autophagic structures after nutrient depletion and is required for fly development. Lipid analyses revealed that Desat1 regulates the composition of lipids in Drosophila. We propose that Desat1 exerts its role in autophagy by controlling lipid biosynthesis and/or signaling necessary for autophagic responses.