PARPs database: a LIMS systems for protein-protein interaction data mining or laboratory information management system.

BACKGROUND: In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteins and the rapid advancement of this technique, in combination with other proteomics methods, results in an increasing amount of proteome data. This data must be archived and analysed using specialized bioinformatics tools. DESCRIPTION: We herein describe "PARPs database," a data analysis and management pipeline for liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics. PARPs database is a web-based tool whose features include experiment annotation, protein database searching, protein sequence management, as well as data-mining of the peptides and proteins identified. CONCLUSION: Using this pipeline, we have successfully identified several interactions of biological significance between PARP-1 and other proteins, namely RFC-1, 2, 3, 4 and 5.

Peptide Shifter: enhancing separation reproducibility using correlated expression profiles.

Chromatographic protein and peptide separation technologies enable comprehensive proteomic analysis of plasma and other complex biological samples by mass spectrometry. However, as the number of separations and/or fractions increases, so does the number of peptides split across fraction boundaries. Irreproducibility of peptide chromatographic separation results in peptides on or near the boundary moving partially or entirely into adjacent fractions. Peptide shifting across fraction boundaries increases the variability of measured peptide abundance, and so there is a trade-off between proteomic comprehensiveness using separation technologies and accurate quantitative proteomic measurements. In this paper, a method for detecting and correcting split peptides, called Peptide Shifter, is introduced and evaluated. An essential component of Peptide Shifter is a global peptide expression profile analysis that allows the inference of the underlying peptide shift pattern without the use of peptide labeling or internal standards. A controlled proteomic analysis of plasma samples demonstrates a 34% decrease in peptide intensity variability after the application of Peptide Shifter.

Protein depletion from blood plasma using a volatile buffer.

Removal of high abundance proteins is widely used in sample processing for proteomics studies of blood plasma. Immunoaffinity (IA) depletion is currently the most specific method for performing this step. Historically, IA depletion matrices have been designed to be used with inorganic buffers. However, the presence of salts in depleted samples presents a particular problem, and these must be removed in order to make samples compatible with post-depletion processing. Desalting (dialysis, ultrafiltration, size-exclusion, etc.) usually diminishes sample integrity due to labware associated losses. Moreover, these steps require additional labor, increasing the processing time and cost of analysis. In order to avoid these problems, we have developed an IA method using a volatile buffer that can be removed from depleted samples by lyophilization. This method allows the execution of reproducible and efficient depletion of blood plasma in a semi-automated manner.

Experimental and bioinformatic approaches for interrogating protein-protein interactions to determine protein function.

An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. One strategy to determine protein function is to identify the protein-protein interactions. The increasing use of high-throughput and large-scale bioinformatics-based studies has generated a massive amount of data stored in a number of different databases. A challenge for bioinformatics is to explore this disparate data and to uncover biologically relevant interactions and pathways. In parallel, there is clearly a need for the development of approaches that can predict novel protein-protein interaction networks in silico. Here, we present an overview of different experimental and bioinformatic methods to elucidate protein-protein interactions.

Protein biomarker quantification by mass spectrometry.

The protein biomarker field is becoming increasingly interested in multiple reaction monitoring mass spectrometry (MRM-MS) assays for biomarker tests. Originally developed years ago and used extensively to quantify small molecules, this technique is now being adapted to peptides. A summary is presented of MRM-MS techniques for quantification of protein biomarkers, including biomarker panels, and clinical applications of this approach. A survey of the current literature relating to the use of MRM-MS to quantify protein biomarker panels was conducted. Future directions for MRM-MS include qualification and verification of candidate protein biomarkers. Furthermore, the analytical characteristics of the MRM-MS approach make it ideally suited for the clinical laboratory as an assay for biomarker tests.

Industrialized MS-based proteomics in the search for circulating biomarkers.

Proteomics is the study of the expression, structure and function of proteins under a range of cellular conditions. A rapidly evolving component of this field is clinical proteomics, which focuses on proteins involved in human disease and how they are affected by therapeutic intervention. MS is the main analytical technology for identifying and quantifying proteins whose expression is modulated across the normal to disease continuum. Applying this technology to clinical samples, however, is particularly challenging due to high biological variability in the population, a variety of disease stages, nonuniform response to therapy, multiple concomitant treatments and special requirements for handling samples from clinical trials. Given these challenges, an 'industrialized' approach is best suited to clinical biomarker development, with its standard operating procedures, process control and 'chain of custody'. This review will focus, therefore, on MS-based industrialized proteomics for the discovery and verification of circulating candidate clinical protein biomarkers.

Proteome profiling of human epithelial ovarian cancer cell line TOV-112D.

A proteome profiling of the epithelial ovarian cancer cell line TOV-112D was initiated as a protein expression reference in the study of ovarian cancer. Two complementary proteomic approaches were used in order to maximise protein identification: two-dimensional gel electrophoresis (2DE) protein separation coupled to matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and one-dimensional gel electrophoresis (1DE) coupled to liquid-chromatography tandem mass spectrometry (LC MS/MS). One hundred and seventy-two proteins have been identified among 288 spots selected on two-dimensional gels and a total of 579 proteins were identified with the 1DE LC MS/MS approach. This proteome profiling covers a wide range of protein expression and identifies several proteins known for their oncogenic properties. Bioinformatics tools were used to mine databases in order to determine whether the identified proteins have previously been implicated in pathways associated with carcinogenesis or cell proliferation. Indeed, several of the proteins have been reported to be specific ovarian cancer markers while others are common to many tumorigenic tissues or proliferating cells. The diversity of proteins found and their association with known oncogenic pathways validate this proteomic approach. The proteome 2D map of the TOV-112D cell line will provide a valuable resource in studies on differential protein expression of human ovarian carcinomas while the 1DE LC MS/MS approach gives a picture of the actual protein profile of the TOV-112D cell line. This work represents one of the most complete ovarian protein expression analysis reports to date and the first comparative study of gene expression profiling and proteomic patterns in ovarian cancer.

Disruptor of telomeric silencing-1 is a chromatin-specific histone H3 methyltransferase.

Yeast disruptor of telomeric silencing-1 (DOT1) is involved in gene silencing and in the pachytene checkpoint during meiotic cell cycle. Here we show that the Dot1 protein possesses intrinsic histone methyltransferase (HMT) activity. When compared with Rmt1, another putative yeast HMT, Dot1 shows very distinct substrate specificity. While Rmt1 methylates histone H4, Dot1 targets histone H3. In contrast to Rmt1, which can only modify free histones, Dot1 activity is specific to nucleosomal substrates. This was also confirmed using native chromatin purified from yeast cells. We also demonstrate that, like its mammalian homolog PRMT1, Rmt1 specifically dimethylates an arginine residue at position 3 of histone H4 N-terminal tail. In surprising contrast, methylation by Dot1 occurs in the globular domain of nucleosomal histone H3. Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) analysis suggests that H3 lysine 79 is trimethylated by Dot1. The intrinsic nucleosomal histone H3 methyltransferase activity of Dot1 is certainly a key aspect of its function in gene silencing at telomeres, most likely by directly modulating chromatin structure and Sir protein localization. In agreement with a role in regulating localization of histone deacetylase complexes like SIR, an increase of bulk histone acetylation is detected in dot1- cells.

A proteomic approach to the identification of heterogeneous nuclear ribonucleoproteins as a new family of poly(ADP-ribose)-binding proteins.

A new class of poly(ADP-ribose) (pADPr)-binding proteins, heterogeneous nuclear ribonucleoproteins (hnRNPs), has been identified by a proteomic approach using matrix-assisted laser-desorption-ionization time-of-flight ('MALDI-TOF') MS. Liquid-phase isoelectric focusing with a Rotofor cell (Bio-Rad) allowed pre-fractionation of proteins extracted from HeLa cells. Rotofor protein fractions were further separated by SDS/PAGE and then transferred to a PVDF membrane. pADPr-binding proteins were analysed by autoradiography of the protein blot after incubation with (32)P-labelled automodified pADPr polymerase-1 (PARP-1). Peptide mass fingerprinting of selected bands identified the most abundant pADPr-binding proteins as hnRNPs, a family of proteins that bind pre-mRNA into functional complexes involved in mRNA maturation and transport to the cytoplasm. Sequence homology database searching against a previously reported pADPr-binding sequence motif revealed that the hnRNPs contain a putative pADPr-binding sequence pattern [Pleschke, Kleczkowska, Strohm and Althaus (2000) J. Biol. Chem. 275, 40974-40980]. pADPr-binding assays performed with synthetic peptides by the dot-blot technique and with nitrocellulose-transferred recombinant hnRNPs confirmed the pADPr-binding protein identification and the specificity of the interaction. These results could establish a link between increased levels of pADPr in DNA damaged cells and the modified protein expression pattern resulting from altered mRNA trafficking.