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. Using electron microscopy (EM) we found that S235D alters virus-induced membrane rearrangements while EM using 'APEX2'-tagged viruses demonstrated S235D-mediated enrichment of NS5A in irregular membranous foci. Finally, using a customized siRNA screen of candidate NS5A kinases and subsequent analysis using a phospho-specific antibody, we show that phosphatidylinositol-4 kinase III alpha (PI4KIIIα) is important for Ser-235 phosphorylation. We conclude that Ser-235 phosphorylation of NS5A is essential for HCV RNA replication and normal replication complex formation and is regulated by PI4KIIIα.

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. METHODS AND RESULTS: This protocol gives highly detailed instructions, with examples, for (1) successfully performing tryptic peptide MALDI imaging on formalin-fixed cancer tissue using a MALDI-TOF/TOF MS instrument, (2) tentatively generating identifications through nLC/MS/MS, and (3) validating these identifications by in situ MS/MS of peptides of interest. CONCLUSIONS: This protocol provides a detailed and straightforward description of the methods required for groups new to MALDI imaging to begin analysis of formalin-fixed clinical samples.

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. The sample preparation closely resembled the MALDI imaging workflow in order to create representative reference data sets containing peptides also observable in MALDI imaging experiments. This resulted in 3844 distinct peptide sequences, at a false discovery rate of 1%, for the entire cohort and an average of 982 distinct peptide sequences per sample. From this, a total of 840 proteins and, on average, 297 proteins per sample could be inferred. To support the efforts of the Chromosome-centric Human Proteome Project Consortium, we have annotated these proteins with their respective chromosome location. In the presented work, the benefit of using a large cohort of data sets was exemplified by correct identification of several m/z species observed in a MALDI imaging experiment. The tryptic peptide data sets generated will facilitate peptide identification in future MALDI imaging studies on ovarian cancer.

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. This variability is currently addressed using external calibration, which limits achievable mass accuracy for MALDI-IMS and makes it difficult to match these data to downstream LC-MS/MS results. To overcome this challenge, the work presented here details a method for internally calibrating data sets generated from tryptic peptide MALDI-IMS on formalin-fixed paraffin-embedded sections of ovarian cancer. By calibrating all spectra to internal peak features the m/z error for matches made between MALDI-IMS m/z values and LC-MS/MS identified peptide m/z values was significantly reduced. This improvement was confirmed by follow up matching of LC-MS/MS spectra to in situ MS/MS spectra from the same m/z peak features. The sum of the data presented here indicates that internal calibrants should be a standard component of tryptic peptide MALDI-IMS experiments.

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. We have found that Lys-N digestion yields peptides with easily assigned CID spectra. Using a mixture of purified proteins as well as a complex yeast lysate, we have shown that Lys-N efficiently digests all proteins at the predicted sites of cleavage. Shotgun proteomics analyses of Lys-N digests of both the standard mixture and yeast lysate yielded peptide and protein identification numbers that were generally comparable to trypsin digestion, whereas the combination data from Lys-N and trypsin digestion substantially enhanced protein coverage. During CID fragmentation, the additional amino terminal basicity enhanced b-ion intensity which was reflected in long b-ion tags that were particularly pronounced during CID in a quadrupole. Finally, immonium ion peaks produced from Lys-N digested peptides originate from the carboxy terminus in contrast to tryptic peptides where immonium ions originate from the amino terminus.

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. However, many of the software applications that assign probabilities for MS/MS spectra to sequence matches were developed using training data sets from 3D ion-trap mass spectrometers. Given the variety of types of mass spectrometers that have become commercially available over the last 5 years, we sought to generate a data set of reference data covering multiple instrumentation platforms to facilitate both the refinement of existing computational approaches and the development of novel software tools. We analyzed the proteolytic peptides in a mixture of tryptic digests of 18 proteins, named the "ISB standard protein mix", using 8 different mass spectrometers. These include linear and 3D ion traps, two quadrupole time-of-flight platforms (qq-TOF), and two MALDI-TOF-TOF platforms. The resulting data set, which has been named the Standard Protein Mix Database, consists of over 1.1 million spectra in 150+ replicate runs on the mass spectrometers. The data were inspected for quality of separation and searched using SEQUEST. All data, including the native raw instrument and mzXML formats and the PeptideProphet validated peptide assignments, are available at http://regis-web.systemsbiology.net/PublicDatasets/.

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. A high-quality spectral library was constructed by combining the high-confidence identifications of millions of spectra taken from various data repositories and searched using four sequence search engines. The resulting library consists of over 30,000 spectra for Saccharomyces cerevisiae. Using this library, SpectraST vastly outperforms the sequence search engine SEQUEST in terms of speed and the ability to discriminate good and bad hits. A unique advantage of SpectraST is its full integration into the popular Trans Proteomic Pipeline suite of software, which facilitates user adoption and provides important functionalities such as peptide and protein probability assignment, quantification, and data visualization. This method of spectral library searching is especially suited for targeted proteomics applications, offering superior performance to traditional sequence searching.

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. cerevisiae ORFs with a Gene Ontology annotation of 'molecular function unknown', and 76% of ORFs with Gene names. We highlight the use of this resource for data mining, construction of high quality lists for targeted proteomics, validation of proteins, and software development.

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). Through labeling with [18O]water solvent and LC-MALDI analysis, the method further allows the possible distinction between Type 0 and Type 1 or Type 2 modified peptides (monolinks and looplinks or cross-links), although such a distinction is more readily made from analysis of tandem mass spectrometry data. When applied to the bacterial Colicin E7 DNAse/Im7 heterodimeric protein complex, 23 cross-links were identified including six intersubunit cross-links, all between residues that are close in space when examined in the context of the X-ray structure of the heterodimer. In addition, cross-links were successfully identified in five single subunit proteins, beta-lactoglobulin, cytochrome c, lysozyme, myoglobin, and ribonuclease A, establishing the generality of the approach.

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. These include deficiencies of the scoring schemes implemented in the database search tools, sequence variations (e.g. single nucleotide polymorphisms) or omissions in the database searched, post-translational or chemical modifications of the peptide analyzed, or the observation of sequences that are not anticipated from the genomic sequence (e.g. splice forms, somatic rearrangement, and processed proteins). To increase the amount of information that can be extracted from proteomic MS/MS datasets we developed a robust method that detects high quality spectra within the fraction of spectra unassigned by conventional sequence database searching and computes a quality score for each spectrum. We also demonstrate that iterative search strategies applied to such detected unassigned high quality spectra significantly increase the number of spectra that can be assigned from datasets and that biologically interesting new insights can be gained from existing data.

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.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

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. To date, 78 plasma proteins have been unambiguously identified by manual validation from 16% (15/96 FFE total fractions) of the collected FFE pools; 55 identifications were based on > or = 2 tryptic peptides and 23 using single peptides. The molecular weight range of proteins and peptides isolated by this method ranged from approximately 190 K (e.g., Complement C3 and C4) to approximately 4-6 K (e.g., CRISPP and Apolipoprotein C1). This FFE/RP-HPLC approach reveals low-abundance proteins and peptides (e.g., L-Selectin approximately 17 ng/mL and the cancer-associated SCM-recognition, immunodefense suppression, and serine protease protection peptide (CRISPP) at approximately 0.5-1 ng/mL), where CRISPP was found in association with alpha-1-antitrypsin as a non-covalent complex, in the fraction containing the depleted high-abundance proteins. In contrast to shotgun proteomic approaches, the FFE/RP-HPLC method described here allows the identification of potentially interesting peptides to be traced back to their protein of origin, and for the first time, has confirmed the "protein sponge" hypothesis where the 35 residue CRISPP polypeptide is non-covalently complexed with the major circulating plasma protein alpha-1-antitrypsin.

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. The currently accepted "mobile proton" model was expanded to derive a new classification scheme for peptide mass spectra, the "relative proton mobility" scale, which considers peptide ion charge state and amino acid composition to categorize peptide mass spectra into peptide ions containing "nonmobile", "partially mobile", or "mobile" protons. Quantitation of amide bond fragmentation, both N- and C-terminal to any given amino acid, as well as the positional effect of an amino acid in a peptide and peptide length on such fragmentation, has been determined. Peptide bond cleavage propensities, both positive (i.e., enhanced) and negative (i.e., suppressed), were determined and ranked in order of their cleavage preferences as primary, secondary, or tertiary cleavage effects. For example, primary positive cleavage effects were observed for Xaa-Pro and Asp-Xaa bond cleavage for mobile and nonmobile peptide ion categories, respectively. We also report specific pairwise interactions (e.g., Asn-Gly) that result in enhanced amide bond cleavages analogous to those observed in solution-phase chemistry. Peptides classified as nonmobile gave low or insignificant scores, below reported MS/MS score thresholds (cutoff filters), indicating that incorporation of the relative proton mobility scale classification would lead to improvements in current MS/MS scoring functions.

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. MS/MS is required to provide structural / amino acid sequence information on a peptide and thus allow protein identity to be inferred from individual peptides. Currently these spectra need to be manually validated because: (a) the potential of false positive matches i.e., protein not in database, and (b) observed fragmentation trends may not be incorporated into current MS/MS search algorithms. This validation represents a significant bottleneck associated with high-throughput proteomic strategies. We have developed CHOMPER, a software program which reduces the time required to both visualize and confirm MS/MS search results and generate post-analysis reports and protein summary tables. CHOMPER extracts the identification information from SEQUEST MS/MS search result files, reproduces both the peptide and protein identification summaries, provides a more interactive visualization of the MS/MS spectra and facilitates the direct submission of manually validated identifications to a database.