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 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.

The Mass Distance Fingerprint: a statistical framework for de novo detection of predominant modifications using high-accuracy mass spectrometry.

We describe a statistical measure, Mass Distance Fingerprint, for automatic de novo detection of predominant peptide mass distances, i.e., putative protein modifications. The method's focus is to globally detect mass differences, not to assign peptide sequences or modifications to individual spectra. The Mass Distance Fingerprint is calculated from high accuracy measured peptide masses. For the data sets used in this study, known mass differences are detected at electron mass accuracy or better. The proposed method is novel because it works independently of protein sequence databases and without any prior knowledge about modifications. Both modified and unmodified peptides have to be present in the sample to be detected. The method can be used for automated detection of chemical/post-translational modifications, quality control of experiments and labeling approaches, and to control the modification settings of protein identification tools. The algorithm is implemented as a web application and is distributed as open source software.

Database independent detection of isotopically labeled MS/MS spectrum peptide pairs.

Mass spectrometry data generated in differential profiling of complex protein samples are classically exploited using database searches. In addition, quantitative profiling is performed by various methods, one of them using isotopically coded affinity tags, where one typically uses a light and a heavy tag. Here, we present a new algorithm, ICATcher, which detects pairs of light/heavy peptide MS/MS spectra independent of sequence databases. The method can be used for de novo sequencing and detection of posttranslational modifications. ICATcher is distributed as open source software.

Improving automatic peptide mass fingerprint protein identification by combining many peak sets.

An automated peak picking strategy is presented where several peak sets with different signal-to-noise levels are combined to form a more reliable statement on the protein identity. The strategy is compared against both manual peak picking and industry standard automated peak picking on a set of mass spectra obtained after tryptic in gel digestion of 2D-gel samples from human fetal fibroblasts. The set of spectra contain samples ranging from strong to weak spectra, and the proposed multiple-scale method is shown to be much better on weak spectra than the industry standard method and a human operator, and equal in performance to these on strong and medium strong spectra. It is also demonstrated that peak sets selected by a human operator display a considerable variability and that it is impossible to speak of a single "true" peak set for a given spectrum. The described multiple-scale strategy both avoids time-consuming parameter tuning and exceeds the human operator in protein identification efficiency. The strategy therefore promises reliable automated user-independent protein identification using peptide mass fingerprints.

Qualitative and quantitative analyses of protein phosphorylation in naive and stimulated mouse synaptosomal preparations.

Activity-dependent protein phosphorylation is a highly dynamic yet tightly regulated process essential for cellular signaling. Although recognized as critical for neuronal functions, the extent and stoichiometry of phosphorylation in brain cells remain undetermined. In this study, we resolved activity-dependent changes in phosphorylation stoichiometry at specific sites in distinct subcellular compartments of brain cells. Following highly sensitive phosphopeptide enrichment using immobilized metal affinity chromatography and mass spectrometry, we isolated and identified 974 unique phosphorylation sites on 499 proteins, many of which are novel. To further explore the significance of specific phosphorylation sites, we used isobaric peptide labels and determined the absolute quantity of both phosphorylated and non-phosphorylated peptides of candidate phosphoproteins and estimated phosphorylation stoichiometry. The analyses of phosphorylation dynamics using differentially stimulated synaptic terminal preparations revealed activity-dependent changes in phosphorylation stoichiometry of target proteins. Using this method, we were able to differentiate between distinct isoforms of Ca2+/calmodulin-dependent protein kinase (CaMKII) and identify a novel activity-regulated phosphorylation site on the glutamate receptor subunit GluR1. Together these data illustrate that mass spectrometry-based methods can be used to determine activity-dependent changes in phosphorylation stoichiometry on candidate phosphopeptides following large scale phosphoproteome analysis of brain tissue.

Towards the proteome of Burkholderia cenocepacia H111: setting up a 2-DE reference map.

Polyphasic-taxonomic studies of the past decade have shown that the Burkholderia cepacia complex (Bcc) comprises at least nine species, which share a high degree of 16S rDNA (98-100%) sequence similarity but only moderate levels of DNA-DNA hybridization. Members of the Bcc are well known as opportunistic pathogens of plants, animals and humans but also as biocontrol and bioremediation agents. In this study intra-, surface-associated and extracellular proteins of B. cenocepacia H111, which was isolated from a cystic fibrosis patient, were examined by 2-DE coupled to MALDI-TOF MS. MS and MS/MS data were searched against a database comprising all currently available annotated proteins of genetically closely related strains. In total 642 proteins spots were successfully identified corresponding to 390 different protein species, which were classified into functional categories. The majority of these proteins could be linked to housekeeping functions in energy production, amino acid metabolism, protein folding, post-translational modification and turnover, and translation. Noteworthy is the fact that a significant number of truly secreted and membrane proteins were identified in the extracellular and surface-associated sub-proteomes. This indicates that the pre-fractionation protocol used in this study is a highly valuable strategy for unravelling the cellular location of the identified proteins.

Identification and relative quantification of membrane proteins by surface biotinylation and two-dimensional peptide mapping.

Membrane proteins play a central role in biological processes, but their separation and quantification using two-dimensional gel electrophoresis is often limited by their poor solubility and relatively low abundance. We now present a method for the simultaneous recovery, separation, identification, and relative quantification of membrane proteins, following their selective covalent modification with a cleavable biotin derivative. After cell lysis, biotinylated proteins are purified on streptavidin-coated resin and proteolytically digested. The resulting peptides are analyzed by high-pressure liquid chromatography and mass spectrometry, thus yielding a two-dimensional peptide map. Matrix assisted laser desorption/ionization-time of flight signal intensity of peptides, in the presence of internal standards, is used to quantify the relative abundance of membrane proteins from cells treated in different experimental conditions. As experimental examples, we present (i) an analysis of a BSA-spiked human embryonic kidney membrane protein extract, and (ii) an analysis of membrane proteins of human umbilical vein endothelial cells cultured in normoxic and hypoxic conditions. This last study allowed the recovery of the vascular endothelial-cadherin/actin/catenin complex, revealing an increased accumulation of beta-catenin at 2% O(2) concentration.

Further steps in standardisation. Report of the second annual Proteomics Standards Initiative Spring Workshop (Siena, Italy 17-20th April 2005).

The spring workshop of the HUPO-PSI convened in Siena to further progress the data standards which are already making an impact on data exchange and deposition in the field of proteomics. Separate work groups pushed forward existing XML standards for the exchange of Molecular Interaction data (PSI-MI, MIF) and Mass Spectrometry data (PSI-MS, mzData) whilst significant progress was made on PSI-MS' mzIdent, which will allow the capture of data from analytical tools such as peak list search engines. A new focus for PSI (GPS, gel electrophoresis) was explored; as was the need for a common representation of protein modifications by all workers in the field of proteomics and beyond. All these efforts are contextualised by the work of the General Proteomics Standards workgroup; which in addition to the MIAPE reporting guidelines, is continually evolving an object model (PSI-OM) from which will be derived the general standard XML format for exchanging data between researchers, and for submission to repositories or journals.