Phosphorylation of NS5A Serine-235 is essential to hepatitis C virus RNA replication and normal replication compartment formation.

Hepatitis C virus (HCV) NS5A protein is essential for HCV RNA replication and virus assembly. Here we report the identification of NS5A phosphorylation sites Ser-222, Ser-235 and Thr-348 during an infectious HCV replication cycle and demonstrate that Ser-235 phosphorylation is essential for HCV RNA replication. Confocal microscopy revealed that both phosphoablatant (S235A) and phosphomimetic (S235D) mutants redistribute NS5A to large juxta-nuclear foci that display altered colocalization with known replication complex components.

Matrix-assisted laser desorption/ionization imaging protocol for in situ characterization of tryptic peptide identity and distribution in formalin-fixed tissue.

Rationale: Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry provides the means to map the in situ distribution of tryptic peptides in formalin-fixed clinical tissue samples. The ability to analyze clinical samples is of great importance to further developments in the imaging field. However, there is a requirement in this field of research for additional methods describing the characterization of tryptic peptides by MALDI imaging.

Tryptic peptide reference data sets for MALDI imaging mass spectrometry on formalin-fixed ovarian cancer tissues.

MALDI imaging mass spectrometry is a powerful tool for morphology-based proteomic tissue analysis. However, peptide identification is still a major challenge due to low S/N ratios, low mass accuracy and difficulties in correlating observed m/z species with peptide identities. To address this, we have analyzed tryptic digests of formalin-fixed paraffin-embedded tissue microarray cores, from 31 ovarian cancer patients, by LC-MS/MS.

Internal calibrants allow high accuracy peptide matching between MALDI imaging MS and LC-MS/MS.

One of the important challenges for MALDI imaging mass spectrometry (MALDI-IMS) is the unambiguous identification of measured analytes. One way to do this is to match tryptic peptide MALDI-IMS m/z values with LC-MS/MS identified m/z values. Matching using current MALDI-TOF/TOF MS instruments is difficult due to the variability of in situ time-of-flight (TOF) m/z measurements.

Proteomic analyses using Grifola frondosa metalloendoprotease Lys-N.

Proteomic analysis typically has been performed using proteins digested with trypsin because of the excellent fragmentation patterns they produce in collision induced dissociation (CID). For analyses in which high protein coverage is desirable, such as global monitoring of post-translational modifications, additional sequences can be seen using parallel digestion with a second enzyme. We have benchmarked a relatively obscure basidomycete-derived zinc metalloendopeptidase, Lys-N, that selectively cleaves the amide bond N-terminal of lysine residues.

Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics.

Background: Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis.

Differential Plasma Glycoproteome of p19 Skin Cancer Mouse Model Using the Corra Label-Free LC-MS Proteomics Platform.

A proof-of-concept demonstration of the use of label-free quantitative glycoproteomics for biomarker discovery workflow is presented here, using a mouse model for skin cancer as an example. Blood plasma was collected from 10 control mice, and 10 mice having a mutation in the p19(ARF) gene, conferring them high propensity to develop skin cancer after carcinogen exposure. We enriched for N-glycosylated plasma proteins, ultimately generating deglycosylated forms of the modified tryptic peptides for liquid chromatography mass spectrometry (LC-MS) analyses.

Building consensus spectral libraries for peptide identification in proteomics.

Spectral searching has drawn increasing interest as an alternative to sequence-database searching in proteomics. We developed and validated an open-source software toolkit, SpectraST, to enable proteomics researchers to build spectral libraries and to integrate this promising approach in their data-analysis pipeline. It allows individual researchers to condense raw data into spectral libraries, summarizing information about observed proteomes into a concise and retrievable format for future data analyses.

The standard protein mix database: a diverse data set to assist in the production of improved Peptide and protein identification software tools.

Tandem mass spectrometry (MS/MS) is frequently used in the identification of peptides and proteins. Typical proteomic experiments rely on algorithms such as SEQUEST and MASCOT to compare thousands of tandem mass spectra against the theoretical fragment ion spectra of peptides in a database. The probabilities that these spectrum-to-sequence assignments are correct can be determined by statistical software such as PeptideProphet or through estimations based on reverse or decoy databases.

Development and validation of a spectral library searching method for peptide identification from MS/MS.

A notable inefficiency of shotgun proteomics experiments is the repeated rediscovery of the same identifiable peptides by sequence database searching methods, which often are time-consuming and error-prone. A more precise and efficient method, in which previously observed and identified peptide MS/MS spectra are catalogued and condensed into searchable spectral libraries to allow new identifications by spectral matching, is seen as a promising alternative. To that end, an open-source, functionally complete, high-throughput and readily extensible MS/MS spectral searching tool, SpectraST, was developed.

Analysis of the Saccharomyces cerevisiae proteome with PeptideAtlas.

We present the Saccharomyces cerevisiae PeptideAtlas composed from 47 diverse experiments and 4.9 million tandem mass spectra. The observed peptides align to 61% of Saccharomyces Genome Database (SGD) open reading frames (ORFs), 49% of the uncharacterized SGD ORFs, 54% of S.

Protein cross-linking analysis using mass spectrometry, isotope-coded cross-linkers, and integrated computational data processing.

Distance constraints in proteins and protein complexes provide invaluable information for calculation of 3D structures, identification of protein binding partners and localization of protein-protein contact sites. We have developed an integrative approach to identify and characterize such sites through the analysis of proteolytic products derived from proteins chemically cross-linked by isotopically coded cross-linkers using LC-MALDI tandem mass spectrometry and computer software. This method is specifically tailored toward the rapid analysis of low microgram amounts of proteins or multimeric protein complexes cross-linked with nonlabeled and deuterium-labeled bis-NHS ester cross-linking reagents (both commercially available and readily synthesized).

The PeptideAtlas project.

The completion of the sequencing of the human genome and the concurrent, rapid development of high-throughput proteomic methods have resulted in an increasing need for automated approaches to archive proteomic data in a repository that enables the exchange of data among researchers and also accurate integration with genomic data. PeptideAtlas (http://www.peptideatlas.

Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptides.

In mass spectrometry-based proteomics, frequently hundreds of thousands of MS/MS spectra are collected in a single experiment. Of these, a relatively small fraction is confidently assigned to peptide sequences, whereas the majority of the spectra are not further analyzed. Spectra are not assigned to peptides for diverse reasons.

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.

Application of 2-D free-flow electrophoresis/RP-HPLC for proteomic analysis of human plasma depleted of multi high-abundance proteins.

Free-flow electrophoresis (FFE) and rapid (6 min) RP-HPLC was used to fractionate human citrate-treated plasma. Prior to analysis, the six most abundant proteins in plasma were removed by immunoaffinity chromatography; both depleted plasma and the fraction containing the six abundant proteins depleted were taken for MS-based analysis. Fractionated proteins were digested with trypsin and the generated peptides were subjected to MS-based peptide sequencing.

Mining a tandem mass spectrometry database to determine the trends and global factors influencing peptide fragmentation.

A database of 5500 unique peptide tandem mass spectra acquired in an ion trap mass spectrometer was assembled for peptides derived from proteins digested with trypsin. Peptides were identified initially from their tandem mass spectra by the SEQUEST algorithm and subsequently validated manually. Two different statistical methods were used to identify sequence-dependent fragmentation patterns that could be used to improve fragmentation models incorporated into current peptide sequencing and database search algorithms.

CHOMPER: a bioinformatic tool for rapid validation of tandem mass spectrometry search results associated with high-throughput proteomic strategies.

Current efforts aimed at developing high-throughput proteomics focus on increasing the speed of protein identification. Although improvements in sample separation, enrichment, automated handling, mass spectrometric analysis, as well as data reduction and database interrogation strategies have done much to increase the quality, quantity and efficiency of data collection, significant bottlenecks still exist. Various separation techniques have been coupled with tandem mass spectrometric (MS/MS) approaches to allow a quicker analysis of complex mixtures of proteins, especially where a high number of unambiguous protein identifications are the exception, rather than the rule.