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As novel liquid chromatography-mass spectrometry (LC-MS) technologies for proteomics offer a substantial increase in LC-MS runs per day, robust and reproducible sample preparation emerges as a new bottleneck for throughput. We introduce a novel strategy for positive-pressure 96-well filter-aided sample preparation (PF96) on a commercial positive-pressure solid-phase extraction device. PF96 allows for a five-fold increase in throughput in conjunction with extraordinary reproducibility with Pearson product-moment correlations on the protein level of r = 0.9993, as demonstrated for mouse heart tissue lysate in 40 technical replicates. The targeted quantification of 16 peptides in the presence of stable-isotope-labeled reference peptides confirms that PF96 variance is barely assessable against technical variation from nanoLC-MS instrumentation. We further demonstrate that protein loads of 36-60 μg result in optimal peptide recovery, but lower amounts ≥3 μg can also be processed reproducibly. In summary, the reproducibility, simplicity, and economy of time provide PF96 a promising future in biomedical and clinical research.

Chemical cross-linking of proteins is an emerging field with huge potential for the structural investigation of proteins and protein complexes. Owing to the often relatively low yield of cross-linking products, their identification in complex samples benefits from enrichment procedures prior to mass spectrometry analysis. So far, this is mainly accomplished by using biotin moieties in specific cross-linkers or by applying strong cation exchange chromatography (SCX) for a relatively crude enrichment. We present a novel workflow to enrich cross-linked peptides by utilizing charge-based fractional diagonal chromatography (ChaFRADIC). On the basis of two-dimensional diagonal SCX separation, we could increase the number of identified cross-linked peptides for samples of different complexity: pure cross-linked BSA, cross-linked BSA spiked into a simple protein mixture, and cross-linked BSA spiked into a HeLa lysate. We also compared XL-ChaFRADIC with size exclusion chromatography-based enrichment of cross-linked peptides. The XL-ChaFRADIC approach is straightforward, reproducible, and independent of the cross-linking chemistry and cross-linker properties.

In proteomics, liquid chromatography-tandem mass spectrometry (LC-MS/MS) is established for identifying peptides and proteins. Duplicated spectra, that is, multiple spectra of the same peptide, occur both in single MS/MS runs and in large spectral libraries. Clustering tandem mass spectra is used to find consensus spectra, with manifold applications. First, it speeds up database searches, as performed for instance by Mascot. Second, it helps to identify novel peptides across species. Third, it is used for quality control to detect wrongly annotated spectra. We compare different clustering algorithms based on the cosine distance between spectra. CAST, MS-Cluster, and PRIDE Cluster are popular algorithms to cluster tandem mass spectra. We add well-known algorithms for large data sets, hierarchical clustering, DBSCAN, and connected components of a graph, as well as the new method N-Cluster. All algorithms are evaluated on real data with varied parameter settings. Cluster results are compared with each other and with peptide annotations based on validation measures such as purity. Quality control, regarding the detection of wrongly (un)annotated spectra, is discussed for exemplary resulting clusters. N-Cluster proves to be highly competitive. All clustering results benefit from the so-called DISMS2 filter that integrates additional information, for example, on precursor mass.

Complex mass spectrometry based proteomics data sets are mostly analyzed by protein database searches. While this approach performs considerably well for sequenced organisms, direct inference of peptide sequences from tandem mass spectra, i.e., de novo peptide sequencing, oftentimes is the only way to obtain information when protein databases are absent. However, available algorithms suffer from drawbacks such as lack of validation and often high rates of false positive hits (FP). Here we present a simple method of combining results from commonly available de novo peptide sequencing algorithms, which in conjunction with minor tweaks in data acquisition ensues lower empirical FDR compared to the analysis using single algorithms. Results were validated using state-of-the art database search algorithms as well specifically synthesized reference peptides. Thus, we could increase the number of PSMs meeting a stringent FDR of 5% more than 3-fold compared to the single best de novo sequencing algorithm alone, accounting for an average of 11 120 PSMs (combined) instead of 3476 PSMs (alone) in triplicate 2 h LC-MS runs of tryptic HeLa digestion.

We present a novel straightforward method for enrichment of N-terminal peptides, utilizing charge-based fractional diagonal chromatography (ChaFRADIC). Our method is robust, easy to operate, fast, specific, and more sensitive than existing methods, enabling the differential quantitation of 1459 nonredundant N-terminal peptides between two S. cerevisiae samples within 10 h of LC-MS, starting from only 50 μg of protein per condition and analyzing only 40% of the obtained fractions. Using ChaFRADIC we compared mitochondrial proteins from wild-type and icp55Δ yeast (30 μg each). Icp55 is an intermediate cleaving peptidase, which, following mitochondrial processing peptidase (MPP)-dependent cleavage of signal sequences, removes a single amino acid from a specific set of proteins according to the N-end rule. Using ChaFRADIC we identified 36 icp55 substrates, 14 of which were previously unknown, expanding the set of known icp55 substrates to a total of 52 proteins. Interestingly, a novel substrate, Isa2, is likely processed by Icp55 in two consecutive steps and thus might represent the first example of a triple processing event in a mitochondrial precursor protein. Thus, ChaFRADIC is a powerful and practicable tool for protease and peptidase research, providing the sensitivity to characterize even samples that can be obtained only in small quantities.

To study human cancer development, cell culture models for malignant transformation can be used. In 1999 Hahn and Coworkers introduced such a model system and established herewith a basis for research on human tumorigenesis. Primary human fibroblasts are sequentially transduced with defined genetic elements (hTERT, SV40 ER, and H-RasV12), resulting in four defined cell lines, whereby the last has a fully transformed phenotype. In order to get a deeper insight into the molecular biology of human tumorigenesis, we compared the proteomes of these four cell lines following a multimethod concept. At the beginning we assumed SILAC and sample fractionation with COFRADIC is the method of choice to analyze the cell culture model for malignant transformation. Here, the compared samples are combined before sample preparation, thus avoiding differences in sample preparation, and using COFRADIC notably reduces sample complexity. Because 2D-PAGE is a standard method for the separation and visualization of closely related proteomes, we decided to analyze and compare the proteomes of these four cell lines in a first approach by differential 2D-PAGE. Surprisingly, we discovered much more unique results with iTRAQ and sample fractionation with SCX than with the combination of 2D-PAGE and SILAC-COFRADIC. Moreover, iTRAQ outperforms the other strategies not only in number of yielded results but also in analysis time. Here, we present the iTRAQ quantification results and compare them with the results of 2D-PAGE and SILAC-COFRADIC. We found changes in the protein level at each transition. Thereby, SV40 has the strongest impact on the proteome. In detail we identified 201 regulated proteins. Beside others, these proteins are involved in cytoskeleton, RNA processing, and cell cycle, such as CDC2, hnRNPs, snRNPs, collagens, and MCM proteins. For example, MCM proteins are up-regulated and collagens are down-regulated due to SV40 ER expression. Furthermore we made the observation that proteins containing the same domain have analogous regulation profiles during malignant transformation. For instance, several proteins containing a CH or LIM domain are down-regulated. Moreover, by this study and the defined cell culture model, changes could be clearly matched to specific steps during tumorigenesis.

The Thermo Proteome Discoverer program integrates both peptide identification and quantification into a single workflow for peptide-centric proteomics. Furthermore, its close integration with Thermo mass spectrometers has made it increasingly popular in the field. Here, we present a Java library to parse the msf files that constitute the output of Proteome Discoverer. The parser is also implemented as a graphical user interface allowing convenient access to the information found in the msf files, and in Rover, a program to analyze and validate quantitative proteomics information. All code, binaries, and documentation is freely available at http://thermo-msf-parser.googlecode.com. acceptedVersion

The centrosome functions as the main microtubule-organization center of the cell and is of importance for all microtubule-dependent processes such as organelle transport and directionality of cell migration. One of the major model organisms in centrosome research is the slime mold Dictyostelium discoideum. Since only 10 centrosomal proteins are known so far in Dictyostelium discoideum, the elucidation of new centrosomal components may give a more comprehensive understanding of centrosomal function. To distinguish between centrosomal and contaminating proteins we established different separation and relative quantification strategies including techniques such as iTRAQ and DIGE. In this work, we present the identification of several known components as well as more than 70 new candidates--currently subject of further investigations--for the protein inventory of the Dictyostelium centrosome. Among these protein identifications, 44% represent hypothetical proteins of still unknown function associated with the centrosome.

With the increasing popularity of comparative studies of complex proteomes, reporter ion-based quantification methods such as iTRAQ and TMT have become commonplace in biological studies. Their appeal derives from simple multiplexing and quantification of several samples at reasonable cost. This advantage yet comes with a known shortcoming: precursors of different species can interfere, thus reducing the quantification accuracy. Recently, two methods were brought to the community alleviating the amount of interference via novel experimental design. Before considering setting up a new workflow, tuning the system, optimizing identification and quantification rates, etc. one legitimately asks: is it really worth the effort, time and money? The question is actually not easy to answer since the interference is heavily sample and system dependent. Moreover, there was to date no method allowing the inline estimation of error rates for reporter quantification. We therefore introduce a method called iQuARI to compute false discovery rates for reporter ion based quantification experiments as easily as Target/Decoy FDR for identification. With it, the scientist can accurately estimate the amount of interference in his sample on his system and eventually consider removing shadows subsequently, a task for which reporter ion quantification might not be the solution of choice.

Shotgun proteomic investigations rely on the algorithmic assignment of mass spectra to peptides. The quality of these matches is therefore a cornerstone in the analysis and has been the subject of numerous recent developments. In order to establish the benefits of novel algorithms, they are applied to reference samples of known content. However, these were recently shown to be either too simple to resemble typical real-life samples or as leading to results of lower accuracy as the method itself. Here, we describe how to use the proteome of Pyrococcus furiosus , a hyperthermophile, as a standard to evaluate proteomics identification workflows. Indeed, we prove that the Pyrococcus furiosus proteome provides a valid method for detecting random hits, comparable to the decoy databases currently in popular use, but we also prove that the Pyrococcus furiosus proteome goes squarely beyond the decoy approach by also providing many hundreds of highly reliable true positive hits. Searching the Pyrococcus furiosus proteome can thus be used as a unique test that provides the ability to reliably detect both false positives as well as proteome-scale true positives, allowing the rigorous testing of identification algorithms at the peptide and protein level.

In fish of the genus Xiphophorus, different grades of pigment cell lesions from nevi to melanoma can be gained by simple crossbreeding. With this model, one can easily access tissues of different malignancies from animals with highly identical genetic background. To find protein expression differences between healthy, benign and malignant tissues, we performed 2D PAGE and DIGE and found among regulated proteins antioxidant proteins that were overexpressed with increasing malignancy.

Beside their main physiological function in hemostasis, platelets are also highly involved in pathological processes, such as atherothrombosis and inflammation. During hemostasis, binding of adhesive substrates to tyrosine-kinase-linked adhesion receptors and/or soluble agonists to G-protein coupled receptors leads to a cascade of intracellular signaling processes based on substrate (de)phosphorylation. The same mechanisms are involved in platelet activation at sites of atherosclerotic plaque rupture, contributing to vessel occlusion and consequently to pathologic states, such as myocardial infarction, stroke, or peripheral artery disease. To gain a deeper insight into platelet function, we analyzed the phosphoproteome of resting platelets and identified 564 phosphorylation sites from more than 270 proteins, of which many have not been described in platelets before. Among those were several unknown potential protein kinase A (PKA) and protein kinase G (PKG) substrates. Because platelet inhibition is tightly regulated especially by PKA and PKG activity, these proteins may represent important new targets for cardiovascular research. Thus, our finding that GPIbalpha is phosphorylated at Ser603 in resting platelets may represent a novel mechanism for the regulation of one of the most important platelet receptor (GPIb-IX-V) mediated signaling pathways by PKA/PKG.

Comprehensive knowledge about the plasma membrane protein profile of a given brain region, at defined developmental stages, will greatly foster the understanding of brain function and dysfunction. Protocols are required which selectively enrich plasma membranes from small brain regions, thereby resulting in high yields. Here, we present a suitable protocol that is based on aqueous polymer two-phase systems. It is material saving, easy to perform, fast, and low-priced. Evidence for its effectiveness was obtained by marker enzyme assays, immunoblot analyses, and mass spectrometry. Plasma membranes from all parts of the cells (somata, dendrites, and axons) were enriched, whereas there was a reduction of mitochondria and endoplasmic reticulum. The total of 15.0% of the initial activity of the plasma membrane marker was recovered, while the activity of the mitochondrial marker and the marker for the endoplasmic reticulum was 0.2% of the initial activity. Mass spectrometric analyses of proteins purified from approximately one-fourth of rat cerebellum (i.e., 80 mg of tissue) resulted in the identification of 525 different proteins, with 27.3% (gene ontology) or 38.2% (gene cards) being allocated to the plasma membrane. When accepting 4.7% of the initial mitochondrial marker activity and 2.9% of the initial activity of the marker for the endoplasmic reticulum as contaminations, the yield of the plasma membrane marker increased to 28.8%. Under these conditions, 586 different proteins were identified by mass spectrometry, 26.1-36.5% of which were plasma membrane proteins. Taken together, our protocol represents a powerful tool for the analysis of the plasma membrane subproteome of distinct brain regions.