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Peptide Identification (peptide + identification)

Distribution by Scientific Domains

Chemistry	100%

Selected Abstracts

HPTLC/DESI-MS imaging of tryptic protein digests separated in two dimensions,

JOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 12 2008
Sofie P. Pasilis
Abstract Desorption electrospray ionization mass spectrometry (DESI-MS) was demonstrated as a method to detect and identify peptides from two-dimensional separations of cytochrome c and myoglobin tryptic digests on ProteoChrom HPTLC Cellulose sheets. Data-dependent tandem mass spectra were acquired during lane scans across the TLC plates. Peptides and the corresponding proteins were identified using a protein database search software. Two-dimensional distributions of identified peptides were mapped for each separated protein digest. Sequence coverages for cytochrome c and myoglobin were 81 and 74%, respectively. These compared well with those determined using the more standard HPLC/ESI-MS/MS approach (89 and 84%, respectively). Preliminary results show that use of more sensitive instrumentation has the potential for improved detection of peptides with low Rf values and improvement in sequence coverage. However, less multiple charging and more sodiation were seen in HPTLC/DESI-MS spectra relative to HPLC/ESI-MS spectra, which can affect peptide identification by MS/MS. Methods to increase multiple charging and reduce the extent of sodiation are currently under investigation. Published in 2008 by John Wiley & Sons, Ltd. [source]

High-sensitivity analysis of specific peptides in complex samples by selected MS/MS ion monitoring and linear ion trap mass spectrometry: Application to biological studies

JOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 11 2007
Inmaculada Jorge
Abstract Mass spectrometry (MS) is a technique of paramount importance in Proteomics, and developments in this field have been possible owing to novel MS instrumentation, experimental strategies, and bioinformatics tools. Today it is possible to identify and determine relative expression levels of thousands of proteins in a biological system by MS analysis of peptides produced by proteolytic digestion. In some situations, however, the precise characterization of a particular peptide species in a very complex peptide mixture is needed. While single-fragment ion-based scanning modes such as selected ion reaction monitoring (SIRM) or consecutive reaction monitoring (CRM) may be highly sensitive, they do not produce MS/MS information and their actual specificity must be determined in advance, a prerequisite that is not usually met in a basic research context. In such cases, the MS detector may be programmed to perform continuous MS/MS spectra on the peptide ion of interest in order to obtain structural information. This selected MS/MS ion monitoring (SMIM) mode has a number of advantages that are fully exploited by MS detectors that, like the linear ion trap, are characterized by high scanning speeds. In this work, we show some applications of this technique in the context of biological studies. These results were obtained by selecting an appropriate combination of scans according to the purpose of each one of these research scenarios. They include highly specific identification of proteins present in low amounts, characterization and relative quantification of post-translational modifications such as phosphorylation and S -nitrosylation and species-specific peptide identification. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Estimating false discovery rates for peptide and protein identification using randomized databases

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 12 2010
Gregory Hather
Abstract MS-based proteomics characterizes protein contents of biological samples. The most common approach is to first match observed MS/MS peptide spectra against theoretical spectra from a protein sequence database and then to score these matches. The false discovery rate (FDR) can be estimated as a function of the score by searching together the protein sequence database and its randomized version and comparing the score distributions of the randomized versus nonrandomized matches. This work introduces a straightforward isotonic regression-based method to estimate the cumulative FDRs and local FDRs (LFDRs) of peptide identification. Our isotonic method not only performed as well as other methods used for comparison, but also has the advantages of being: (i) monotonic in the score, (ii) computationally simple, and (iii) not dependent on assumptions about score distributions. We demonstrate the flexibility of our approach by using it to estimate FDRs and LFDRs for protein identification using summaries of the peptide spectra scores. We reconfirmed that several of these methods were superior to a two-peptide rule. Finally, by estimating both the FDRs and LFDRs, we showed for both peptide and protein identification, moderate FDR values (5%) corresponded to large LFDR values (53 and 60%). [source]

Highly stable trypsin-aggregate coatings on polymer nanofibers for repeated protein digestion

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 7 2009
Byoung Chan Kim
Abstract A stable and robust trypsin-based biocatalytic system was developed and demonstrated for proteomic applications. The system utilizes polymer nanofibers coated with trypsin aggregates for immobilized protease digestions. After covalently attaching an initial layer of trypsin to the polymer nanofibers, highly concentrated trypsin molecules are crosslinked to the layered trypsin by way of a glutaraldehyde treatment. This process produced a 300-fold increase in trypsin activity compared with a conventional method for covalent trypsin immobilization, and proved to be robust in that it still maintained a high level of activity after a year of repeated recycling. This highly stable form of immobilized trypsin was resistant to autolysis, enabling repeated digestions of BSA over 40,days and successful peptide identification by LC-MS/MS. This active and stable form of immobilized trypsin was successfully employed in the digestion of yeast proteome extract with high reproducibility and within shorter time than conventional protein digestion using solution phase trypsin. Finally, the immobilized trypsin was resistant to proteolysis when exposed to other enzymes (i.e., chymotrypsin), which makes it suitable for use in "real-world" proteomic applications. Overall, the biocatalytic nanofibers with trypsin aggregate coatings proved to be an effective approach for repeated and automated protein digestion in proteomic analyses. [source]

Application of electron transfer dissociation (ETD) for the analysis of posttranslational modifications

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 21 2008
Julia Wiesner
Abstract Despite major advantages in the field of proteomics, the analysis of PTMs still poses a major challenge; thus far, preventing insights into the role and regulation of protein networks. Additionally, top-down sequencing of proteins is another powerful approach to reveal comprehensive information for biological function. A commonly used fragmentation technique in MS-based peptide sequencing is CID. As CID often fails in PTM-analysis and performs best on doubly-charged, short and middle-sized peptides, confident peptide identification may be hampered. A newly developed fragmentation technique, namely electron transfer dissociation (ETD), supports both, PTM- and top-down analysis, and generally results in more confident identification of long, highly charged or modified peptides. The following review presents the theoretical background of ETD and its technical implementation in mass analyzers. Furthermore, current improvements of ETD and approaches for the PTM-analysis and top-down sequencing are introduced. Alternating both fragmentation techniques, ETD and CID, increases the amount of information derived from peptide fragmentation, thereby enhancing both, peptide sequence coverage and the confidence of peptide and protein identification. [source]

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

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 5 2007
Henry Lam
Abstract 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. [source]

Improving peptide identification using an empirical peptide retention time database

RAPID COMMUNICATIONS IN MASS SPECTROMETRY, Issue 1 2009
Wei Sun
Peptide retention time (RT) is independent of tandem mass spectrometry (MS/MS) parameters and can be combined with MS/MS information to enhance peptide identification. In this paper, we utilized peptide empirical RT and MS/MS for peptide identification. This new approach resulted in the construction of an Empirical Peptide Retention Time Database (EPRTD) based on peptides showing a false-positive rate (FPR) ,1%, detected in several liquid chromatography (LC)/MS/MS analyses. In subsequent experiments, the RT of peptides with FPR >1% was compared with empirical data derived from the EPRTD. If the experimental RT was within a specified time range of the empirical value, the corresponding MS/MS spectra were accepted as positive. Application of the EPRTD approach to simple samples (known protein mixtures) and complex samples (human urinary proteome) revealed that this method could significantly enhance peptide identification without compromising the associated confidence levels. Further analysis indicated that the EPRTD approach could improve low-abundance peptides and with the expansion of the EPRTD the number of peptide identifications will be increased. This approach is suitable for large-scale clinical proteomics research, in which tens of LC/MS/MS analyses are run for different samples with similar components. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Separation with zwitterionic hydrophilic interaction liquid chromatography improves protein identification by matrix-assisted laser desorption/ionization-based proteomic analysis

BIOMEDICAL CHROMATOGRAPHY, Issue 6 2009
Atsushi Intoh
Abstract Comprehensive proteomic analyses necessitate efficient separation of peptide mixtures for the subsequent identification of proteins by mass spectrometry (MS). However, digestion of proteins extracted from cells and tissues often yields complex peptide mixtures that confound direct comprehensive MS analysis. This study investigated a zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) technique for the peptide separation step, which was verified by subsequent MS analysis. Human serum albumin (HSA) was the model protein used for this analysis. HSA was digested with trypsin and resolved by ZIC-HILIC or conventional strong cation exchange (SCX) prior to MS analysis for peptide identification. Separation with ZIC-HILIC significantly improved the identification of HSA peptides over SCX chromatography. Detailed analyses of the identified peptides revealed that the ZIC-HILIC has better peptide fractionation ability. We further demonstrated that ZIC-HILIC is useful for quantitatively surveying cell surface markers specifically expressed in undifferentiated embryonic stem cells. These results suggested the value of ZIC-HILIC as a novel and efficient separation method for comprehensive and quantitative proteomic analyses. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Extensive fractionation and identification of proteins within nasal lavage fluids from allergic rhinitis and asthmatic chronic rhinosinusitis patients

JOURNAL OF SEPARATION SCIENCE, JSS, Issue 1 2009
Linda M. Benson
Abstract Allergic rhinitis (AR), chronic rhinosinusitis (CRS), and asthma are prevalent airway diseases that can have a substantial impact on a patient's quality of life. MS analyses of biological fluids can effectively screen for proteins associated with disease processes, however, initial detection of diagnostic proteins is difficult due to protein complexity and dynamic range. To enhance the detection of lower abundance proteins, intact nasal lavage fluid (NLF) proteins from nonpolypoid AR and from asthmatic CRS patients were extensively fractionated prior to LC/MS/MS analysis. Pooled NLF samples were processed to remove low molecular weight molecules and high abundance plasma proteins. Anion exchange (AX) chromatography followed by RP-LC further separated the remaining intact NLF proteins. The resulting fractions were digested with trypsin and the peptides analyzed by LC/MS/MS. Spectra were searched with MASCOT, SEQUEST, and X!Tandem to obtain peptide identifications and subsequently analyzed by Scaffold software to identify parent proteins with at least 99% confidence. The 197 identified proteins are compared to those previously cited in the literature and the workflow evaluated to determine the usefulness for the detection of lower abundance proteins. This is the first extensive list of NLF proteins generated from CRS patients with coexisting asthma. [source]

Retention time prediction using the model of liquid chromatography of biomacromolecules at critical conditions in LC-MS phosphopeptide analysis

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 19 2010
Tatiana Yu Perlova
Abstract LC combined with MS/MS analysis of complex mixtures of protein digests is a reliable and sensitive method for characterization of protein phosphorylation. Peptide retention times (RTs) measured during an LC-MS/MS run depend on both the peptide sequence and the location of modified amino acids. These RTs can be predicted using the LC of biomacromolecules at critical conditions model (BioLCCC). Comparing the observed RTs to those obtained from the BioLCCC model can provide additional validation of MS/MS-based peptide identifications to reduce the false discovery rate and to improve the reliability of phosphoproteome profiling. In this study, energies of interaction between phosphorylated residues and the surface of RP separation media for both "classic" alkyl C18 and polar-embedded C18 stationary phases were experimentally determined and included in the BioLCCC model extended for phosphopeptide analysis. The RTs for phosphorylated peptides and their nonphosphorylated analogs were predicted using the extended BioLCCC model and compared with their experimental RTs. The extended model was evaluated using literary data and a complex phosphoproteome data set distributed through the Association of Biomolecular Resource Facilities Proteome Informatics Research Group 2010 study. The reported results demonstrate the capability of the extended BioLCCC model to predict RTs which may lead to improved sensitivity and reliability of LC-MS/MS-based phosphoproteome profiling. [source]

A well-characterised peak identification list of MALDI MS profile peaks for human blood serum

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 18 2010
Ali Tiss
Abstract MALDI MS profiling, using easily available body fluids such as blood serum, has attracted considerable interest for its potential in clinical applications. Despite the numerous reports on MALDI MS profiling of human serum, there is only scarce information on the identity of the species making up these profiles, particularly in the mass range of larger peptides. Here, we provide a list of more than 90 entries of MALDI MS profile peak identities up to 10,kDa obtained from human blood serum. Various modifications such as phosphorylation were detected among the peptide identifications. The overlap with the few other MALDI MS peak lists published so far was found to be limited and hence our list significantly extends the number of identified peaks commonly found in MALDI MS profiling of human blood serum. [source]

Experimental annotation of channel catfish virus by probabilistic proteogenomic mapping

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 10 2009
Dusan Kunec Dr.
Abstract Experimental identification of expressed proteins by proteomics constitutes the most reliable approach to identify genomic location and structure of protein-coding genes and substantially complements computational genome annotation. Channel catfish herpesvirus (CCV) is a simple comparative model for understanding herpesvirus biology and the evolution of the Herpesviridae. The canonical CCV genome has 76 predicted ORF and only 12 of these have been confirmed experimentally. We describe a modification of a statistical method, which assigns significance measures, q -values, to peptide identifications based on 2-D LC ESI MS/MS, real-decoy database searches and SEQUEST XCorr and ,Cn scores. We used this approach to identify CCV proteins expressed during its replication in cell culture, to determine protein composition of mature virions and, consequently, to refine the canonical CCV genome annotation. To complement trypsin, we used partial proteinase K digestion, which yielded greater proteome coverage. At FDR <5%, for peptide identifications, we identified 25/76 previously predicted ORF using trypsin and 31/76 using proteinase K. Furthermore, we identified 17 novel protein-coding regions (7 potential ATG-initiated ORF). Most of these novel ORF encode small proteins (<100 amino acids). Directed, strand-specific reverse transcription real-time PCR confirmed RNA expression from 6/7 novel ATG-initiated ORF investigated. [source]

The detection, correlation, and comparison of peptide precursor and product ions from data independent LC-MS with data dependant LC-MS/MS

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 6 2009
Scott J. Geromanos
Abstract The detection, correlation, and comparison of peptide and product ions from a data independent LC-MS acquisition strategy with data dependent LC-MS/MS is described. The data independent mode of acquisition differs from an LC-MS/MS data acquisition since no ion transmission window is applied with the first mass analyzer prior to collision induced disassociation. Alternating the energy applied to the collision cell, between low and elevated energy, on a scan-to-scan basis, provides accurate mass precursor and associated product ion spectra from every ion above the LOD of the mass spectrometer. The method therefore provides a near 100% duty cycle, with an inherent increase in signal intensity due to the fact that both precursor and product ion data are collected on all isotopes of every charge-state across the entire chromatographic peak width. The correlation of product to precursor ions, after deconvolution, is achieved by using reconstructed retention time apices and chromatographic peak shapes. Presented are the results from the comparison of a simple four protein mixture, in the presence and absence of an enzymatically digested protein extract from Escherichia coli. The samples were run in triplicate by both data dependant analysis (DDA) LC-MS/MS and data-independent, alternate scanning LC-MS. The detection and identification of precursor and product ions from the combined DDA search results of the four protein mixture were used for comparison to all other data. Each individual set of data-independent LC-MS data provides a more comprehensive set of detected ions than the combined peptide identifications from the DDA LC-MS/MS experiments. In the presence of the complex E. coli background, over 90% of the monoisotopic masses from the combined LC-MS/MS identifications were detected at the appropriate retention time. Moreover, the fragmentation pattern and number of associated elevated energy product ions in each replicate experiment was found to be very similar to the DDA identifications. In the case of the corresponding individual DDA LC-MS/MS experiment, 43% of the possible detectable peptides of interest were identified. The presented data illustrates that the time-aligned data from data-independent alternate scanning LC-MS experiments is highly comparable to the data obtained via DDA. The obtained information can therefore be effectively and correctly deconvolved to correlate product ions with parent precursor ions. The ability to generate precursor-product ion tables from this information and subsequently identify the correct parent precursor peptide will be illustrated in a companion manuscript. [source]

Predictions of peptides' retention times in reversed-phase liquid chromatography as a new supportive tool to improve protein identification in proteomics

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 4 2009
Tomasz B, czek Dr.
Abstract One of the initial steps of proteomic analysis is peptide separation. However, little information from RP-HPLC, employed for peptides separation, is utilized in proteomics. Meanwhile, prediction of the retention time for a given peptide, combined with routine MS/MS data analysis, could help to improve the confidence of peptide identifications. Recently, a number of models has been proposed to characterize quantitatively the structure of a peptide and to predict its gradient RP-HPLC retention at given separation conditions. The chromatographic behavior of peptides has usually been related to their amino acid composition. However, different values of retention coefficients of the same amino acid in different peptides at different neighborhoods were commonly observed. Therefore, specific retention coefficients were derived by regression analysis or by artificial neural networks (ANNs) with the use of a set of peptides retention. In the review, various approaches for peptide elution time prediction in RP-HPLC are presented and critically discussed. The contribution of sequence dependent parameters (e.g., amphipathicity or peptide sequence) and peptide physicochemical descriptors (e.g., hydrophobicity or peptide length) that have been shown to affect the peptide retention time in LC are considered and analyzed. The predictive capability of the retention time prediction models based on quantitative structure,retention relationships (QSRRs) are discussed in details. Advantages and limitations of various retention prediction strategies are identified. It is concluded that proper processing of chromatographic data by statistical learning techniques can result in information of direct use for proteomics, which is otherwise wasted. [source]

Annual Spring Meeting of the Proteomics Standards Initiative 23,25 April 2008, Toledo, Spain

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 20 2008
Sandra Orchard
Abstract The role of the Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI) is to produce and release community-accepted reporting requirements, interchange formats and controlled vocabularies for mass spectrometry proteomics and related technologies such as gel electrophoresis, column chromatography and molecular interactions. A number of significant advances were made at this workshop, with the new MS standard, mzML, being finalised prior to release on 1st June 2008 and analysisXML, which will allow protein and peptide identifications and post-translational modifications to be captured, being prepared to enter the review process this summer. The accompanying controlled vocabularies are continuing to evolve and a number of standards papers are now being finalised prior to publication. [source]

A new strategy to filter out false positive identifications of peptides in SEQUEST database search results

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 22 2007
Jiyang Zhang
Abstract Based on the randomized database method and a linear discriminant function (LDF) model, a new strategy to filter out false positive matches in SEQUEST database search results is proposed. Given an experiment MS/MS dataset and a protein sequence database, a randomized database is constructed and merged with the original database. Then, all MS/MS spectra are searched against the combined database. For each expected false positive rate (FPR), LDFs are constructed for different charge states and used to filter out the false positive matches from the normal database. In order to investigate the error of FPR estimation, the new strategy was applied to a reference dataset. As a result, the estimated FPR was very close to the actual FPR. While applied to a human K562 cell line dataset, which is a complicated dataset from real sample, more matches could be confirmed than the traditional cutoff-based methods at the same estimated FPR. Also, though most of the results confirmed by the LDF model were consistent with those of PeptideProphet, the LDF model could still provide complementary information. These results indicate that the new method can reliably control the FPR of peptide identifications and is more sensitive than traditional cutoff-based methods. [source]