Confidence assignment for mass spectrometry based peptide identifications via the extreme value distribution.

PubMed

Alves, Gelio; Yu, Yi-Kuo

2016-09-01

There is a growing trend for biomedical researchers to extract evidence and draw conclusions from mass spectrometry based proteomics experiments, the cornerstone of which is peptide identification. Inaccurate assignments of peptide identification confidence thus may have far-reaching and adverse consequences. Although some peptide identification methods report accurate statistics, they have been limited to certain types of scoring function. The extreme value statistics based method, while more general in the scoring functions it allows, demands accurate parameter estimates and requires, at least in its original design, excessive computational resources. Improving the parameter estimate accuracy and reducing the computational cost for this method has two advantages: it provides another feasible route to accurate significance assessment, and it could provide reliable statistics for scoring functions yet to be developed. We have formulated and implemented an efficient algorithm for calculating the extreme value statistics for peptide identification applicable to various scoring functions, bypassing the need for searching large random databases. The source code, implemented in C ++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit yyu@ncbi.nlm.nih.gov Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.

PubMed

Andreatta, Massimo; Karosiene, Edita; Rasmussen, Michael; Stryhn, Anette; Buus, Søren; Nielsen, Morten

2015-11-01

A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding register prediction is concerned with determining the minimal core region of nine residues directly in contact with the MHC binding cleft, a crucial piece of information both for the identification and design of CD4(+) T cell antigens. When applied to a set of 51 crystal structures of peptide-MHC complexes with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1 .

A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics

PubMed Central

Nesvizhskii, Alexey I.

2010-01-01

This manuscript provides a comprehensive review of the peptide and protein identification process using tandem mass spectrometry (MS/MS) data generated in shotgun proteomic experiments. The commonly used methods for assigning peptide sequences to MS/MS spectra are critically discussed and compared, from basic strategies to advanced multi-stage approaches. A particular attention is paid to the problem of false-positive identifications. Existing statistical approaches for assessing the significance of peptide to spectrum matches are surveyed, ranging from single-spectrum approaches such as expectation values to global error rate estimation procedures such as false discovery rates and posterior probabilities. The importance of using auxiliary discriminant information (mass accuracy, peptide separation coordinates, digestion properties, and etc.) is discussed, and advanced computational approaches for joint modeling of multiple sources of information are presented. This review also includes a detailed analysis of the issues affecting the interpretation of data at the protein level, including the amplification of error rates when going from peptide to protein level, and the ambiguities in inferring the identifies of sample proteins in the presence of shared peptides. Commonly used methods for computing protein-level confidence scores are discussed in detail. The review concludes with a discussion of several outstanding computational issues. PMID:20816881

Species Identification of Archaeological Skin Objects from Danish Bogs: Comparison between Mass Spectrometry-Based Peptide Sequencing and Microscopy-Based Methods

PubMed Central

Brandt, Luise Ørsted; Schmidt, Anne Lisbeth; Mannering, Ulla; Sarret, Mathilde; Kelstrup, Christian D.; Olsen, Jesper V.; Cappellini, Enrico

2014-01-01

Denmark has an extraordinarily large and well-preserved collection of archaeological skin garments found in peat bogs, dated to approximately 920 BC – AD 775. These objects provide not only the possibility to study prehistoric skin costume and technologies, but also to investigate the animal species used for the production of skin garments. Until recently, species identification of archaeological skin was primarily performed by light and scanning electron microscopy or the analysis of ancient DNA. However, the efficacy of these methods can be limited due to the harsh, mostly acidic environment of peat bogs leading to morphological and molecular degradation within the samples. We compared species assignment results of twelve archaeological skin samples from Danish bogs using Mass Spectrometry (MS)-based peptide sequencing, against results obtained using light and scanning electron microscopy. While it was difficult to obtain reliable results using microscopy, MS enabled the identification of several species-diagnostic peptides, mostly from collagen and keratins, allowing confident species discrimination even among taxonomically close organisms, such as sheep and goat. Unlike previous MS-based methods, mostly relying on peptide fingerprinting, the shotgun sequencing approach we describe aims to identify the complete extracted ancient proteome, without preselected specific targets. As an example, we report the identification, in one of the samples, of two peptides uniquely assigned to bovine foetal haemoglobin, indicating the production of skin from a calf slaughtered within the first months of its life. We conclude that MS-based peptide sequencing is a reliable method for species identification of samples from bogs. The mass spectrometry proteomics data were deposited in the ProteomeXchange Consortium with the dataset identifier PXD001029. PMID:25260035

Improving sensitivity in proteome studies by analysis of false discovery rates for multiple search engines

PubMed Central

Jones, Andrew R.; Siepen, Jennifer A.; Hubbard, Simon J.; Paton, Norman W.

2010-01-01

Tandem mass spectrometry, run in combination with liquid chromatography (LC-MS/MS), can generate large numbers of peptide and protein identifications, for which a variety of database search engines are available. Distinguishing correct identifications from false positives is far from trivial because all data sets are noisy, and tend to be too large for manual inspection, therefore probabilistic methods must be employed to balance the trade-off between sensitivity and specificity. Decoy databases are becoming widely used to place statistical confidence in results sets, allowing the false discovery rate (FDR) to be estimated. It has previously been demonstrated that different MS search engines produce different peptide identification sets, and as such, employing more than one search engine could result in an increased number of peptides being identified. However, such efforts are hindered by the lack of a single scoring framework employed by all search engines. We have developed a search engine independent scoring framework based on FDR which allows peptide identifications from different search engines to be combined, called the FDRScore. We observe that peptide identifications made by three search engines are infrequently false positives, and identifications made by only a single search engine, even with a strong score from the source search engine, are significantly more likely to be false positives. We have developed a second score based on the FDR within peptide identifications grouped according to the set of search engines that have made the identification, called the combined FDRScore. We demonstrate by searching large publicly available data sets that the combined FDRScore can differentiate between between correct and incorrect peptide identifications with high accuracy, allowing on average 35% more peptide identifications to be made at a fixed FDR than using a single search engine. PMID:19253293

Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry.

PubMed

Yao, Jingwen; Utsunomiya, Shin-Ichi; Kajihara, Shigeki; Tabata, Tsuyoshi; Aoshima, Ken; Oda, Yoshiya; Tanaka, Koichi

2014-01-01

A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/).

Peptide Peak Detection for Low Resolution MALDI-TOF Mass Spectrometry

PubMed Central

Yao, Jingwen; Utsunomiya, Shin-ichi; Kajihara, Shigeki; Tabata, Tsuyoshi; Aoshima, Ken; Oda, Yoshiya; Tanaka, Koichi

2014-01-01

A new peak detection method has been developed for rapid selection of peptide and its fragment ion peaks for protein identification using tandem mass spectrometry. The algorithm applies classification of peak intensities present in the defined mass range to determine the noise level. A threshold is then given to select ion peaks according to the determined noise level in each mass range. This algorithm was initially designed for the peak detection of low resolution peptide mass spectra, such as matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) mass spectra. But it can also be applied to other type of mass spectra. This method has demonstrated obtaining a good rate of number of real ions to noises for even poorly fragmented peptide spectra. The effect of using peak lists generated from this method produces improved protein scores in database search results. The reliability of the protein identifications is increased by finding more peptide identifications. This software tool is freely available at the Mass++ home page (http://www.first-ms3d.jp/english/achievement/software/). PMID:26819872

Peptide de novo sequencing of mixture tandem mass spectra.

PubMed

Gorshkov, Vladimir; Hotta, Stéphanie Yuki Kolbeck; Verano-Braga, Thiago; Kjeldsen, Frank

2016-09-01

The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they decrease the identification performance using database search engines. De novo sequencing approaches are expected to be even more sensitive to the reduction in mass spectrum quality resulting from peptide precursor co-isolation and thus prone to false identifications. The deconvolution approach matched complementary b-, y-ions to each precursor peptide mass, which allowed the creation of virtual spectra containing sequence specific fragment ions of each co-isolated peptide. Deconvolution processing resulted in equally efficient identification rates but increased the absolute number of correctly sequenced peptides. The improvement was in the range of 20-35% additional peptide identifications for a HeLa lysate sample. Some correct sequences were identified only using unprocessed spectra; however, the number of these was lower than those where improvement was obtained by mass spectral deconvolution. Tight candidate peptide score distribution and high sensitivity to small changes in the mass spectrum introduced by the employed deconvolution method could explain some of the missing peptide identifications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detachable strong cation exchange monolith, integrated with capillary zone electrophoresis and coupled with pH gradient elution, produces improved sensitivity and numbers of peptide identifications during bottom-up analysis of complex proteomes.

PubMed

Zhang, Zhenbin; Yan, Xiaojing; Sun, Liangliang; Zhu, Guijie; Dovichi, Norman J

2015-04-21

A detachable sulfonate-silica hybrid strong cation-exchange monolith was synthesized in a fused silica capillary, and used for solid phase extraction with online pH gradient elution during capillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) proteomic analysis. Tryptic digests were prepared in 50 mM formic acid and loaded onto the strong cation-exchange monolith. Fractions were eluted using a series of buffers with lower concentration but higher pH values than the 50 mM formic acid background electrolyte. This combination of elution and background electrolytes results in both sample stacking and formation of a dynamic pH junction and allows use of relatively large elution buffer volumes while maintaining reasonable peak efficiency and resolution. A series of five pH bumps were applied to elute E. coli tryptic peptides from the monolith, followed by analysis using CZE coupled to an LTQ-Orbitrap Velos mass spectrometer; 799 protein groups and 3381 peptides were identified from 50 ng of the digest in a 2.5 h analysis, which approaches the identification rate for this organism that was obtained with an Orbitrap Fusion. We attribute the improved numbers of peptide and protein identifications to the efficient fractionation by the online pH gradient elution, which decreased the complexity of the sample in each elution step and improved the signal intensity of low abundance peptides. We also performed a comparative analysis using a nanoACQUITY UltraPerformance LCH system. Similar numbers of protein and peptide identifications were produced by the two methods. Protein identifications showed significant overlap between the two methods, whereas peptide identifications were complementary.

A combinatorial perspective of the protein inference problem.

PubMed

Yang, Chao; He, Zengyou; Yu, Weichuan

2013-01-01

In a shotgun proteomics experiment, proteins are the most biologically meaningful output. The success of proteomics studies depends on the ability to accurately and efficiently identify proteins. Many methods have been proposed to facilitate the identification of proteins from peptide identification results. However, the relationship between protein identification and peptide identification has not been thoroughly explained before. In this paper, we devote ourselves to a combinatorial perspective of the protein inference problem. We employ combinatorial mathematics to calculate the conditional protein probabilities (protein probability means the probability that a protein is correctly identified) under three assumptions, which lead to a lower bound, an upper bound, and an empirical estimation of protein probabilities, respectively. The combinatorial perspective enables us to obtain an analytical expression for protein inference. Our method achieves comparable results with ProteinProphet in a more efficient manner in experiments on two data sets of standard protein mixtures and two data sets of real samples. Based on our model, we study the impact of unique peptides and degenerate peptides (degenerate peptides are peptides shared by at least two proteins) on protein probabilities. Meanwhile, we also study the relationship between our model and ProteinProphet. We name our program ProteinInfer. Its Java source code, our supplementary document and experimental results are available at: >http://bioinformatics.ust.hk/proteininfer.

Practical and Efficient Searching in Proteomics: A Cross Engine Comparison

PubMed Central

Paulo, Joao A.

2014-01-01

Background Analysis of large datasets produced by mass spectrometry-based proteomics relies on database search algorithms to sequence peptides and identify proteins. Several such scoring methods are available, each based on different statistical foundations and thereby not producing identical results. Here, the aim is to compare peptide and protein identifications using multiple search engines and examine the additional proteins gained by increasing the number of technical replicate analyses. Methods A HeLa whole cell lysate was analyzed on an Orbitrap mass spectrometer for 10 technical replicates. The data were combined and searched using Mascot, SEQUEST, and Andromeda. Comparisons were made of peptide and protein identifications among the search engines. In addition, searches using each engine were performed with incrementing number of technical replicates. Results The number and identity of peptides and proteins differed across search engines. For all three search engines, the differences in proteins identifications were greater than the differences in peptide identifications indicating that the major source of the disparity may be at the protein inference grouping level. The data also revealed that analysis of 2 technical replicates can increase protein identifications by up to 10-15%, while a third replicate results in an additional 4-5%. Conclusions The data emphasize two practical methods of increasing the robustness of mass spectrometry data analysis. The data show that 1) using multiple search engines can expand the number of identified proteins (union) and validate protein identifications (intersection), and 2) analysis of 2 or 3 technical replicates can substantially expand protein identifications. Moreover, information can be extracted from a dataset by performing database searching with different engines and performing technical repeats, which requires no additional sample preparation and effectively utilizes research time and effort. PMID:25346847

Manual method of visually identifying candidate signals for a targeted peptide.

PubMed

Filimonov, Aleksey; Kopylov, Arthur; Lisitsa, Andrey; Archakov, Alexander

2018-04-15

The purpose of this study is to improve peptide signal identification in groups of extracted ion chromatograms (XICs) obtained with the liquid chromatography-selected reaction monitoring (LC-SRM) technique and a triple quadrupole mass spectrometer (QqQ) operating in one of the supported multiple reaction monitoring (MRM) modes. The imperfection of quadrupole mass analyzers causes ion interference, which impedes the identification of peptide signals as chromatographic peak groups in relevant retention time intervals. To investigate this problem in depth, the QqQ conversion of the eluate into XIC groups was considered as the consecutive transformations of the particles' abundances as the corresponding functions of retention time. In this study, the hypothesis that, during this conversion, the same chromatographic profile should be preserved as an implicit sign in each chromatographic peak of the signal was confirmed for peptides. To examine chromatographic profiles, continuous transformations of XIC groups were derived and implemented in srm2prot Express software (s2pe, http://msr.ibmc.msk.ru/s2pe). Because of ion interference, several peptide-like signals may appear in one XIC group. Therefore, these signals must be considered candidates for a targeted peptide's signal and should be resolved after identification. The theoretical investigation of intensity functions as XICs that are not distorted by noise produced three rules for Identifying Candidate Signals for a targeted Peptide (ICSP, http://msr.ibmc.msk.ru/ICSP) that constitute the proposed manual visual method. We theoretically and experimentally compared this method with the conventional semiempirical intuitive technique and found that the former significantly streamlines peptide signal identification and avoids typical errors. Copyright © 2018 Elsevier B.V. All rights reserved.

Incorporating sequence information into the scoring function: a hidden Markov model for improved peptide identification.

PubMed

Khatun, Jainab; Hamlett, Eric; Giddings, Morgan C

2008-03-01

The identification of peptides by tandem mass spectrometry (MS/MS) is a central method of proteomics research, but due to the complexity of MS/MS data and the large databases searched, the accuracy of peptide identification algorithms remains limited. To improve the accuracy of identification we applied a machine-learning approach using a hidden Markov model (HMM) to capture the complex and often subtle links between a peptide sequence and its MS/MS spectrum. Our model, HMM_Score, represents ion types as HMM states and calculates the maximum joint probability for a peptide/spectrum pair using emission probabilities from three factors: the amino acids adjacent to each fragmentation site, the mass dependence of ion types and the intensity dependence of ion types. The Viterbi algorithm is used to calculate the most probable assignment between ion types in a spectrum and a peptide sequence, then a correction factor is added to account for the propensity of the model to favor longer peptides. An expectation value is calculated based on the model score to assess the significance of each peptide/spectrum match. We trained and tested HMM_Score on three data sets generated by two different mass spectrometer types. For a reference data set recently reported in the literature and validated using seven identification algorithms, HMM_Score produced 43% more positive identification results at a 1% false positive rate than the best of two other commonly used algorithms, Mascot and X!Tandem. HMM_Score is a highly accurate platform for peptide identification that works well for a variety of mass spectrometer and biological sample types. The program is freely available on ProteomeCommons via an OpenSource license. See http://bioinfo.unc.edu/downloads/ for the download link.

Urea free and more efficient sample preparation method for mass spectrometry based protein identification via combining the formic acid-assisted chemical cleavage and trypsin digestion.

PubMed

Wu, Shuaibin; Yang, Kaiguang; Liang, Zhen; Zhang, Lihua; Zhang, Yukui

2011-10-30

A formic acid (FA)-assisted sample preparation method was presented for protein identification via mass spectrometry (MS). Detailedly, an aqueous solution containing 2% FA and dithiothreitol was selected to perform protein denaturation, aspartic acid (D) sites cleavage and disulfide linkages reduction simultaneously at 108°C for 2h. Subsequently, FA wiped off via vacuum concentration. Finally, iodoacetamide (IAA) alkylation and trypsin digestion could be performed ordinally. A series of model proteins (BSA, β-lactoglobulin and apo-Transferrin) were treated respectively using such method, followed by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The identified peptide number was increased by ∼ 80% in comparison with the conventional urea-assisted sample preparation method. Moreover, BSA identification was achieved efficiently down to femtomole (25 ± 0 sequence coverage and 16 ± 1 peptides) via such method. In contrast, there were not peptides identified confidently via the urea-assisted method before desalination via the C18 zip tip. The absence of urea in this sample preparation method was an advantage for the more favorable digestion and MALDI-TOF MS analysis. The performances of two methods for the real sample (rat liver proteome) were also compared, followed by a nanoflow reversed-phase liquid chromatography with electrospray ionization tandem mass spectrometry system analysis. As a result, 1335 ± 43 peptides were identified confidently (false discovery rate <1%) via FA-assisted method, corresponding to 295 ± 12 proteins (of top match=1 and requiring 2 unique peptides at least). In contrast, there were only 1107 ± 16 peptides (corresponding to 231 ± 10 proteins) obtained from the conventional urea-assisted method. It was serving as a more efficient protein sample preparation method for researching specific proteomes better, and providing assistance to develop other proteomics analysis methods, such as, peptide quantitative analysis. Copyright © 2011 Elsevier B.V. All rights reserved.

The synergistic use of computation, chemistry and biology to discover novel peptide-based drugs: the time is right.

PubMed

Audie, J; Boyd, C

2010-01-01

The case for peptide-based drugs is compelling. Due to their chemical, physical and conformational diversity, and relatively unproblematic toxicity and immunogenicity, peptides represent excellent starting material for drug discovery. Nature has solved many physiological and pharmacological problems through the use of peptides, polypeptides and proteins. If nature could solve such a diversity of challenging biological problems through the use of peptides, it seems reasonable to infer that human ingenuity will prove even more successful. And this, indeed, appears to be the case, as a number of scientific and methodological advances are making peptides and peptide-based compounds ever more promising pharmacological agents. Chief among these advances are powerful chemical and biological screening technologies for lead identification and optimization, methods for enhancing peptide in vivo stability, bioavailability and cell-permeability, and new delivery technologies. Other advances include the development and experimental validation of robust computational methods for peptide lead identification and optimization. Finally, scientific analysis, biology and chemistry indicate the prospect of designing relatively small peptides to therapeutically modulate so-called 'undruggable' protein-protein interactions. Taken together a clear picture is emerging: through the synergistic use of the scientific imagination and the computational, chemical and biological methods that are currently available, effective peptide therapeutics for novel targets can be designed that surpass even the proven peptidic designs of nature.

DeepSig: deep learning improves signal peptide detection in proteins.

PubMed

Savojardo, Castrense; Martelli, Pier Luigi; Fariselli, Piero; Casadio, Rita

2018-05-15

The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website. pierluigi.martelli@unibo.it. Supplementary data are available at Bioinformatics online.

Mass Defect Labeling of Cysteine for Improving Peptide Assignment in Shotgun Proteomic Analyses

PubMed Central

Hernandez, Hilda; Niehauser, Sarah; Boltz, Stacey A.; Gawandi, Vijay; Phillips, Robert S.; Amster, I. Jonathan

2006-01-01

A method for improving the identification of peptides in a shotgun proteome analysis using accurate mass measurement has been developed. The improvement is based upon the derivatization of cysteine residues with a novel reagent, 2,4-dibromo-(2′-iodo)acetanilide. The derivitization changes the mass defect of cysteine-containing proteolytic peptides in a manner that increases their identification specificity. Peptide masses were measured using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron mass spectrometry. Reactions with protein standards show that the derivatization of cysteine is rapid and quantitative, and the data suggest that the derivatized peptides are more easily ionized or detected than unlabeled cysteine-containing peptides. The reagent was tested on a 15N-metabolically labeled proteome from M. maripaludis. Proteins were identified by their accurate mass values and from their nitrogen stoichiometry. A total of 47% of the labeled peptides are identified versus 27% for the unlabeled peptides. This procedure permits the identification of proteins from the M. maripaludis proteome that are not usually observed by the standard protocol and shows that better protein coverage is obtained with this methodology. PMID:16689545

RAId_DbS: Peptide Identification using Database Searches with Realistic Statistics

PubMed Central

Alves, Gelio; Ogurtsov, Aleksey Y; Yu, Yi-Kuo

2007-01-01

Background The key to mass-spectrometry-based proteomics is peptide identification. A major challenge in peptide identification is to obtain realistic E-values when assigning statistical significance to candidate peptides. Results Using a simple scoring scheme, we propose a database search method with theoretically characterized statistics. Taking into account possible skewness in the random variable distribution and the effect of finite sampling, we provide a theoretical derivation for the tail of the score distribution. For every experimental spectrum examined, we collect the scores of peptides in the database, and find good agreement between the collected score statistics and our theoretical distribution. Using Student's t-tests, we quantify the degree of agreement between the theoretical distribution and the score statistics collected. The T-tests may be used to measure the reliability of reported statistics. When combined with reported P-value for a peptide hit using a score distribution model, this new measure prevents exaggerated statistics. Another feature of RAId_DbS is its capability of detecting multiple co-eluted peptides. The peptide identification performance and statistical accuracy of RAId_DbS are assessed and compared with several other search tools. The executables and data related to RAId_DbS are freely available upon request. PMID:17961253

A peptide affinity column for the identification of integrin alpha IIb-binding proteins.

PubMed

Daxecker, Heide; Raab, Markus; Bernard, Elise; Devocelle, Marc; Treumann, Achim; Moran, Niamh

2008-03-01

To understand the regulation of integrin alpha(IIb)beta(3), a critical platelet adhesion molecule, we have developed a peptide affinity chromatography method using the known integrin regulatory motif, LAMWKVGFFKR. Using standard Fmoc chemistry, this peptide was synthesized onto a Toyopearl AF-Amino-650 M resin on a 6-aminohexanoic acid (Ahx) linker. Peptide density was controlled by acetylation of 83% of the Ahx amino groups. Four recombinant human proteins (CIB1, PP1, ICln and RN181), previously identified as binding to this integrin regulatory motif, were specifically retained by the column containing the integrin peptide but not by a column presenting an irrelevant peptide. Hemoglobin, creatine kinase, bovine serum albumin, fibrinogen and alpha-tubulin failed to bind under the chosen conditions. Immunodetection methods confirmed the binding of endogenous platelet proteins, including CIB1, PP1, ICln RN181, AUP-1 and beta3-integrin, from a detergent-free platelet lysate. Thus, we describe a reproducible method that facilitates the reliable extraction of specific integrin-binding proteins from complex biological matrices. This methodology may enable the sensitive and specific identification of proteins that interact with linear, membrane-proximal peptide motifs such as the integrin regulatory motif LAMWKVGFFKR.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Qibin; Petyuk, Vladislav A.; Schepmoes, Athena A.

Non-enzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. While electron transfer dissociation (ETD) has been shown to outperform collision-induced dissociation (CID) in sequencing glycated peptides by tandem mass spectrometry, ETD instrumentation is not yet available in all laboratories. In this study, we evaluated different advanced CID techniques (i.e., neutral-loss triggered MS3 and multi-stage activation) during LC-MSn analyses of Amadori-modified peptides enriched from human serum glycated in vitro. During neutral-loss triggered MS3 experiments, MS3 scans triggered by neutral-losses of 3 H2O or 3 H2O + HCHO produced similar results in terms of glycatedmore » peptide identifications. However, neutral losses of 3 H2O resulted in significantly more glycated peptide identifications during multi-stage activation experiments. Overall, the multi-stage activation approach produced more glycated peptide identifications, while the neutral-loss triggered MS3 approach resulted in much higher specificity. Both techniques offer a viable alternative to ETD for identifying glycated peptides when that method is unavailable.« less

Fungal Secretome Analysis via PepSAVI-MS: Identification of the Bioactive Peptide KP4 from Ustilago maydis

NASA Astrophysics Data System (ADS)

Kirkpatrick, Christine L.; Parsley, Nicole C.; Bartges, Tessa E.; Cooke, Madeline E.; Evans, Wilaysha S.; Heil, Lilian R.; Smith, Thomas J.; Hicks, Leslie M.

2018-05-01

Fungal secondary metabolites represent a rich and largely untapped source for bioactive molecules, including peptides with substantial structural diversity and pharmacological potential. As methods proceed to take a deep dive into fungal genomes, complimentary methods to identify bioactive components are required to keep pace with the expanding fungal repertoire. We developed PepSAVI-MS to expedite the search for natural product bioactive peptides and herein demonstrate proof-of-principle applicability of the pipeline for the discovery of bioactive peptides from fungal secretomes via identification of the antifungal killer toxin KP4 from Ustilago maydis P4. This work opens the door to investigating microbial secretomes with a new lens, and could have broad applications across human health, agriculture, and food safety. [Figure not available: see fulltext.

Fungal Secretome Analysis via PepSAVI-MS: Identification of the Bioactive Peptide KP4 from Ustilago maydis

NASA Astrophysics Data System (ADS)

Kirkpatrick, Christine L.; Parsley, Nicole C.; Bartges, Tessa E.; Cooke, Madeline E.; Evans, Wilaysha S.; Heil, Lilian R.; Smith, Thomas J.; Hicks, Leslie M.

2018-02-01

Fungal secondary metabolites represent a rich and largely untapped source for bioactive molecules, including peptides with substantial structural diversity and pharmacological potential. As methods proceed to take a deep dive into fungal genomes, complimentary methods to identify bioactive components are required to keep pace with the expanding fungal repertoire. We developed PepSAVI-MS to expedite the search for natural product bioactive peptides and herein demonstrate proof-of-principle applicability of the pipeline for the discovery of bioactive peptides from fungal secretomes via identification of the antifungal killer toxin KP4 from Ustilago maydis P4. This work opens the door to investigating microbial secretomes with a new lens, and could have broad applications across human health, agriculture, and food safety. [Figure not available: see fulltext.

Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics.

PubMed

Dittrich, Julia; Ceglarek, Uta

2017-01-01

The increasing number of peptide and protein biomarker candidates requires expeditious and reliable quantification strategies. The utilization of liquid chromatography coupled to quadrupole tandem mass spectrometry (LC-MS/MS) for the absolute quantitation of plasma proteins and peptides facilitates the multiplexed verification of tens to hundreds of biomarkers from smallest sample quantities. Targeted proteomics assays derived from bottom-up proteomics principles rely on the identification and analysis of proteotypic peptides formed in an enzymatic digestion of the target protein. This protocol proposes a procedure for the establishment of a targeted absolute quantitation method for middle- to high-abundant plasma proteins waiving depletion or enrichment steps. Essential topics as proteotypic peptide identification and LC-MS/MS method development as well as sample preparation and calibration strategies are described in detail.

Practical and Efficient Searching in Proteomics: A Cross Engine Comparison.

PubMed

Paulo, Joao A

2013-10-01

Analysis of large datasets produced by mass spectrometry-based proteomics relies on database search algorithms to sequence peptides and identify proteins. Several such scoring methods are available, each based on different statistical foundations and thereby not producing identical results. Here, the aim is to compare peptide and protein identifications using multiple search engines and examine the additional proteins gained by increasing the number of technical replicate analyses. A HeLa whole cell lysate was analyzed on an Orbitrap mass spectrometer for 10 technical replicates. The data were combined and searched using Mascot, SEQUEST, and Andromeda. Comparisons were made of peptide and protein identifications among the search engines. In addition, searches using each engine were performed with incrementing number of technical replicates. The number and identity of peptides and proteins differed across search engines. For all three search engines, the differences in proteins identifications were greater than the differences in peptide identifications indicating that the major source of the disparity may be at the protein inference grouping level. The data also revealed that analysis of 2 technical replicates can increase protein identifications by up to 10-15%, while a third replicate results in an additional 4-5%. The data emphasize two practical methods of increasing the robustness of mass spectrometry data analysis. The data show that 1) using multiple search engines can expand the number of identified proteins (union) and validate protein identifications (intersection), and 2) analysis of 2 or 3 technical replicates can substantially expand protein identifications. Moreover, information can be extracted from a dataset by performing database searching with different engines and performing technical repeats, which requires no additional sample preparation and effectively utilizes research time and effort.

MixGF: spectral probabilities for mixture spectra from more than one peptide.

PubMed

Wang, Jian; Bourne, Philip E; Bandeira, Nuno

2014-12-01

In large-scale proteomic experiments, multiple peptide precursors are often cofragmented simultaneously in the same mixture tandem mass (MS/MS) spectrum. These spectra tend to elude current computational tools because of the ubiquitous assumption that each spectrum is generated from only one peptide. Therefore, tools that consider multiple peptide matches to each MS/MS spectrum can potentially improve the relatively low spectrum identification rate often observed in proteomics experiments. More importantly, data independent acquisition protocols promoting the cofragmentation of multiple precursors are emerging as alternative methods that can greatly improve the throughput of peptide identifications but their success also depends on the availability of algorithms to identify multiple peptides from each MS/MS spectrum. Here we address a fundamental question in the identification of mixture MS/MS spectra: determining the statistical significance of multiple peptides matched to a given MS/MS spectrum. We propose the MixGF generating function model to rigorously compute the statistical significance of peptide identifications for mixture spectra and show that this approach improves the sensitivity of current mixture spectra database search tools by a ≈30-390%. Analysis of multiple data sets with MixGF reveals that in complex biological samples the number of identified mixture spectra can be as high as 20% of all the identified spectra and the number of unique peptides identified only in mixture spectra can be up to 35.4% of those identified in single-peptide spectra. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

MixGF: Spectral Probabilities for Mixture Spectra from more than One Peptide*

PubMed Central

Wang, Jian; Bourne, Philip E.; Bandeira, Nuno

2014-01-01

In large-scale proteomic experiments, multiple peptide precursors are often cofragmented simultaneously in the same mixture tandem mass (MS/MS) spectrum. These spectra tend to elude current computational tools because of the ubiquitous assumption that each spectrum is generated from only one peptide. Therefore, tools that consider multiple peptide matches to each MS/MS spectrum can potentially improve the relatively low spectrum identification rate often observed in proteomics experiments. More importantly, data independent acquisition protocols promoting the cofragmentation of multiple precursors are emerging as alternative methods that can greatly improve the throughput of peptide identifications but their success also depends on the availability of algorithms to identify multiple peptides from each MS/MS spectrum. Here we address a fundamental question in the identification of mixture MS/MS spectra: determining the statistical significance of multiple peptides matched to a given MS/MS spectrum. We propose the MixGF generating function model to rigorously compute the statistical significance of peptide identifications for mixture spectra and show that this approach improves the sensitivity of current mixture spectra database search tools by a ≈30–390%. Analysis of multiple data sets with MixGF reveals that in complex biological samples the number of identified mixture spectra can be as high as 20% of all the identified spectra and the number of unique peptides identified only in mixture spectra can be up to 35.4% of those identified in single-peptide spectra. PMID:25225354

Combinatorial Approach for Large-scale Identification of Linked Peptides from Tandem Mass Spectrometry Spectra*

PubMed Central

Wang, Jian; Anania, Veronica G.; Knott, Jeff; Rush, John; Lill, Jennie R.; Bourne, Philip E.; Bandeira, Nuno

2014-01-01

The combination of chemical cross-linking and mass spectrometry has recently been shown to constitute a powerful tool for studying protein–protein interactions and elucidating the structure of large protein complexes. However, computational methods for interpreting the complex MS/MS spectra from linked peptides are still in their infancy, making the high-throughput application of this approach largely impractical. Because of the lack of large annotated datasets, most current approaches do not capture the specific fragmentation patterns of linked peptides and therefore are not optimal for the identification of cross-linked peptides. Here we propose a generic approach to address this problem and demonstrate it using disulfide-bridged peptide libraries to (i) efficiently generate large mass spectral reference data for linked peptides at a low cost and (ii) automatically train an algorithm that can efficiently and accurately identify linked peptides from MS/MS spectra. We show that using this approach we were able to identify thousands of MS/MS spectra from disulfide-bridged peptides through comparison with proteome-scale sequence databases and significantly improve the sensitivity of cross-linked peptide identification. This allowed us to identify 60% more direct pairwise interactions between the protein subunits in the 20S proteasome complex than existing tools on cross-linking studies of the proteasome complexes. The basic framework of this approach and the MS/MS reference dataset generated should be valuable resources for the future development of new tools for the identification of linked peptides. PMID:24493012

Engineered Peptides for Applications in Cancer-Targeted Drug Delivery and Tumor Detection.

PubMed

Soudy, R; Byeon, N; Raghuwanshi, Y; Ahmed, S; Lavasanifar, A; Kaur, K

2017-01-01

Cancer-targeting peptides as ligands for targeted delivery of anticancer drugs or drug carriers have the potential to significantly enhance the selectivity and the therapeutic benefit of current chemotherapeutic agents. Identification of tumor-specific biomarkers like integrins, aminopeptidase N, and epidermal growth factor receptor as well as the popularity of phage display techniques along with synthetic combinatorial methods used for peptide design and structure optimization have fueled the advancement and application of peptide ligands for targeted drug delivery and tumor detection in cancer treatment, detection and guided therapy. Although considerable preclinical data have shown remarkable success in the use of tumor targeting peptides, peptides generally suffer from poor pharmacokinetics, enzymatic instability, and weak receptor affinity, and they need further structural modification before successful translation to clinics is possible. The current review gives an overview of the different engineering strategies that have been developed for peptide structure optimization to confer selectivity and stability. We also provide an update on the methods used for peptide ligand identification, and peptide- receptor interactions. Additionally, some applications for the use of peptides in targeted delivery of chemotherapeutics and diagnostics over the past 5 years are summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Analysis of illegal peptide biopharmaceuticals frequently encountered by controlling agencies.

PubMed

Vanhee, Celine; Janvier, Steven; Desmedt, Bart; Moens, Goedele; Deconinck, Eric; De Beer, Jacques O; Courselle, Patricia

2015-09-01

Recent advances in genomics, recombinant expression technologies and peptide synthesis have led to an increased development of protein and peptide therapeutics. Unfortunately this goes hand in hand with a growing market of counterfeit and illegal biopharmaceuticals, including substances that are still under pre-clinical and clinical development. These counterfeit and illegal protein and peptide substances could imply severe health threats as has been demonstrated by numerous case reports. The Belgian Federal Agency for Medicines and Health Products (FAMHP) and customs are striving, together with their global counterparts, to curtail the trafficking and distributions of these substances. At their request, suspected protein and peptide preparations are analysed in our Official Medicines Control Laboratory (OMCL). It stands to reason that a general screening method would be beneficiary in the battle against counterfeit and illegal peptide drugs. In this paper we present such general screening method employing liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the identification of counterfeit and illegal injectable peptide preparations, extended with a subsequent quantification method using ultra-high performance liquid chromatography with diode array detection (UHPLC-DAD). The screening method, taking only 30 min, is able to selectively detect 25 different peptides and incorporates the proposed minimum of five identification points (IP) as has been recommended for sports drug testing applications. The group of peptides represent substances which have already been detected in illegal and counterfeit products seized by different European countries as well as some biopharmaceutical peptides which have not been confiscated yet by the controlling agencies, but are already being used according to the many internet users forums. Additionally, we also show that when applying the same LC gradient, it is also possible to quantify these peptides without the need for derivatization or the use of expensive labelled peptides. This quantification method was successfully validated for a representative subset of 10 different peptides by using the "total error" approach in accordance with the validation requirements of ISO-17025. Copyright © 2015 Elsevier B.V. All rights reserved.

Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures.

PubMed

Li, Guo-Zhong; Vissers, Johannes P C; Silva, Jeffrey C; Golick, Dan; Gorenstein, Marc V; Geromanos, Scott J

2009-03-01

A novel database search algorithm is presented for the qualitative identification of proteins over a wide dynamic range, both in simple and complex biological samples. The algorithm has been designed for the analysis of data originating from data independent acquisitions, whereby multiple precursor ions are fragmented simultaneously. Measurements used by the algorithm include retention time, ion intensities, charge state, and accurate masses on both precursor and product ions from LC-MS data. The search algorithm uses an iterative process whereby each iteration incrementally increases the selectivity, specificity, and sensitivity of the overall strategy. Increased specificity is obtained by utilizing a subset database search approach, whereby for each subsequent stage of the search, only those peptides from securely identified proteins are queried. Tentative peptide and protein identifications are ranked and scored by their relative correlation to a number of models of known and empirically derived physicochemical attributes of proteins and peptides. In addition, the algorithm utilizes decoy database techniques for automatically determining the false positive identification rates. The search algorithm has been tested by comparing the search results from a four-protein mixture, the same four-protein mixture spiked into a complex biological background, and a variety of other "system" type protein digest mixtures. The method was validated independently by data dependent methods, while concurrently relying on replication and selectivity. Comparisons were also performed with other commercially and publicly available peptide fragmentation search algorithms. The presented results demonstrate the ability to correctly identify peptides and proteins from data independent acquisition strategies with high sensitivity and specificity. They also illustrate a more comprehensive analysis of the samples studied; providing approximately 20% more protein identifications, compared to a more conventional data directed approach using the same identification criteria, with a concurrent increase in both sequence coverage and the number of modified peptides.

NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets.

PubMed

Nielsen, Morten; Andreatta, Massimo

2016-03-30

Binding of peptides to MHC class I molecules (MHC-I) is essential for antigen presentation to cytotoxic T-cells. Here, we demonstrate how a simple alignment step allowing insertions and deletions in a pan-specific MHC-I binding machine-learning model enables combining information across both multiple MHC molecules and peptide lengths. This pan-allele/pan-length algorithm significantly outperforms state-of-the-art methods, and captures differences in the length profile of binders to different MHC molecules leading to increased accuracy for ligand identification. Using this model, we demonstrate that percentile ranks in contrast to affinity-based thresholds are optimal for ligand identification due to uniform sampling of the MHC space. We have developed a neural network-based machine-learning algorithm leveraging information across multiple receptor specificities and ligand length scales, and demonstrated how this approach significantly improves the accuracy for prediction of peptide binding and identification of MHC ligands. The method is available at www.cbs.dtu.dk/services/NetMHCpan-3.0 .

Identification and absolute quantification of enzymes in laundry detergents by liquid chromatography tandem mass spectrometry.

PubMed

Gaubert, Alexandra; Jeudy, Jérémy; Rougemont, Blandine; Bordes, Claire; Lemoine, Jérôme; Casabianca, Hervé; Salvador, Arnaud

2016-07-01

In a stricter legislative context, greener detergent formulations are developed. In this way, synthetic surfactants are frequently replaced by bio-sourced surfactants and/or used at lower concentrations in combination with enzymes. In this paper, a LC-MS/MS method was developed for the identification and quantification of enzymes in laundry detergents. Prior to the LC-MS/MS analyses, a specific sample preparation protocol was developed due to matrix complexity (high surfactant percentages). Then for each enzyme family mainly used in detergent formulations (protease, amylase, cellulase, and lipase), specific peptides were identified on a high resolution platform. A LC-MS/MS method was then developed in selected reaction monitoring (SRM) MS mode for the light and corresponding heavy peptides. The method was linear on the peptide concentration ranges 25-1000 ng/mL for protease, lipase, and cellulase; 50-1000 ng/mL for amylase; and 5-1000 ng/mL for cellulase in both water and laundry detergent matrices. The application of the developed analytical strategy to real commercial laundry detergents enabled enzyme identification and absolute quantification. For the first time, identification and absolute quantification of enzymes in laundry detergent was realized by LC-MS/MS in a single run. Graphical Abstract Identification and quantification of enzymes by LC-MS/MS.

Toward the characterization of biological toxins using field-based FT-IR spectroscopic instrumentation

NASA Astrophysics Data System (ADS)

Schiering, David W.; Walton, Robert B.; Brown, Christopher W.; Norman, Mark L.; Brewer, Joseph; Scott, James

2004-12-01

IR spectroscopy is a broadly applicable technique for the identification of covalent materials. Recent advances in instrumentation have made Fourier Transform infrared (FT-IR) spectroscopy available for field characterization of suspect materials. Presently, this instrumentation is broadly deployed and used for the identification of potential chemical hazards. This discussion concerns work towards expanding the analytical utility of field-based FT-IR spectrometry in the characterization of biological threats. Two classes of materials were studied: biologically produced chemical toxins which were non-peptide in nature and peptide toxin. The IR spectroscopic identification of aflatoxin-B1, trichothecene T2 mycotoxin, and strychnine was evaluated using the approach of spectral searching against large libraries of materials. For pure components, the IR method discriminated the above toxins at better than the 99% confidence level. The ability to identify non-peptide toxins in mixtures was also evaluated using a "spectral stripping" search approach. For the mixtures evaluated, this method was able to identify the mixture components from ca. 32K spectral library entries. Castor bean extract containing ricin was used as a representative peptide toxin. Due to similarity in protein spectra, a SIMCA pattern recognition methodology was evaluated for classifying peptide toxins. In addition to castor bean extract the method was validated using bovine serum albumin and myoglobin as simulants. The SIMCA approach was successful in correctly classifying these samples at the 95% confidence level.

A peptide-retrieval strategy enables significant improvement of quantitative performance without compromising confidence of identification.

PubMed

Tu, Chengjian; Shen, Shichen; Sheng, Quanhu; Shyr, Yu; Qu, Jun

2017-01-30

Reliable quantification of low-abundance proteins in complex proteomes is challenging largely owing to the limited number of spectra/peptides identified. In this study we developed a straightforward method to improve the quantitative accuracy and precision of proteins by strategically retrieving the less confident peptides that were previously filtered out using the standard target-decoy search strategy. The filtered-out MS/MS spectra matched to confidently-identified proteins were recovered, and the peptide-spectrum-match FDR were re-calculated and controlled at a confident level of FDR≤1%, while protein FDR maintained at ~1%. We evaluated the performance of this strategy in both spectral count- and ion current-based methods. >60% increase of total quantified spectra/peptides was respectively achieved for analyzing a spike-in sample set and a public dataset from CPTAC. Incorporating the peptide retrieval strategy significantly improved the quantitative accuracy and precision, especially for low-abundance proteins (e.g. one-hit proteins). Moreover, the capacity of confidently discovering significantly-altered proteins was also enhanced substantially, as demonstrated with two spike-in datasets. In summary, improved quantitative performance was achieved by this peptide recovery strategy without compromising confidence of protein identification, which can be readily implemented in a broad range of quantitative proteomics techniques including label-free or labeling approaches. We hypothesize that more quantifiable spectra and peptides in a protein, even including less confident peptides, could help reduce variations and improve protein quantification. Hence the peptide retrieval strategy was developed and evaluated in two spike-in sample sets with different LC-MS/MS variations using both MS1- and MS2-based quantitative approach. The list of confidently identified proteins using the standard target-decoy search strategy was fixed and more spectra/peptides with less confidence matched to confident proteins were retrieved. However, the total peptide-spectrum-match false discovery rate (PSM FDR) after retrieval analysis was still controlled at a confident level of FDR≤1%. As expected, the penalty for occasionally incorporating incorrect peptide identifications is negligible by comparison with the improvements in quantitative performance. More quantifiable peptides, lower missing value rate, better quantitative accuracy and precision were significantly achieved for the same protein identifications by this simple strategy. This strategy is theoretically applicable for any quantitative approaches in proteomics and thereby provides more quantitative information, especially on low-abundance proteins. Published by Elsevier B.V.

Mass spectrometry-based protein identification by integrating de novo sequencing with database searching.

PubMed

Wang, Penghao; Wilson, Susan R

2013-01-01

Mass spectrometry-based protein identification is a very challenging task. The main identification approaches include de novo sequencing and database searching. Both approaches have shortcomings, so an integrative approach has been developed. The integrative approach firstly infers partial peptide sequences, known as tags, directly from tandem spectra through de novo sequencing, and then puts these sequences into a database search to see if a close peptide match can be found. However the current implementation of this integrative approach has several limitations. Firstly, simplistic de novo sequencing is applied and only very short sequence tags are used. Secondly, most integrative methods apply an algorithm similar to BLAST to search for exact sequence matches and do not accommodate sequence errors well. Thirdly, by applying these methods the integrated de novo sequencing makes a limited contribution to the scoring model which is still largely based on database searching. We have developed a new integrative protein identification method which can integrate de novo sequencing more efficiently into database searching. Evaluated on large real datasets, our method outperforms popular identification methods.

A sensitive mass spectrometric method for hypothesis-driven detection of peptide post-translational modifications: multiple reaction monitoring-initiated detection and sequencing (MIDAS).

PubMed

Unwin, Richard D; Griffiths, John R; Whetton, Anthony D

2009-01-01

The application of a targeted mass spectrometric workflow to the sensitive identification of post-translational modifications is described. This protocol employs multiple reaction monitoring (MRM) to search for all putative peptides specifically modified in a target protein. Positive MRMs trigger an MS/MS experiment to confirm the nature and site of the modification. This approach, termed MIDAS (MRM-initiated detection and sequencing), is more sensitive than approaches using neutral loss scanning or precursor ion scanning methodologies, due to a more efficient use of duty cycle along with a decreased background signal associated with MRM. We describe the use of MIDAS for the identification of phosphorylation, with a typical experiment taking just a couple of hours from obtaining a peptide sample. With minor modifications, the MIDAS method can be applied to other protein modifications or unmodified peptides can be used as a MIDAS target.

Identification and accurate quantification of structurally related peptide impurities in synthetic human C-peptide by liquid chromatography-high resolution mass spectrometry.

PubMed

Li, Ming; Josephs, Ralf D; Daireaux, Adeline; Choteau, Tiphaine; Westwood, Steven; Wielgosz, Robert I; Li, Hongmei

2018-06-04

Peptides are an increasingly important group of biomarkers and pharmaceuticals. The accurate purity characterization of peptide calibrators is critical for the development of reference measurement systems for laboratory medicine and quality control of pharmaceuticals. The peptides used for these purposes are increasingly produced through peptide synthesis. Various approaches (for example mass balance, amino acid analysis, qNMR, and nitrogen determination) can be applied to accurately value assign the purity of peptide calibrators. However, all purity assessment approaches require a correction for structurally related peptide impurities in order to avoid biases. Liquid chromatography coupled to high resolution mass spectrometry (LC-hrMS) has become the key technique for the identification and accurate quantification of structurally related peptide impurities in intact peptide calibrator materials. In this study, LC-hrMS-based methods were developed and validated in-house for the identification and quantification of structurally related peptide impurities in a synthetic human C-peptide (hCP) material, which served as a study material for an international comparison looking at the competencies of laboratories to perform peptide purity mass fraction assignments. More than 65 impurities were identified, confirmed, and accurately quantified by using LC-hrMS. The total mass fraction of all structurally related peptide impurities in the hCP study material was estimated to be 83.3 mg/g with an associated expanded uncertainty of 3.0 mg/g (k = 2). The calibration hierarchy concept used for the quantification of individual impurities is described in detail. Graphical abstract ᅟ.

Meat Authentication via Multiple Reaction Monitoring Mass Spectrometry of Myoglobin Peptides.

PubMed

Watson, Andrew D; Gunning, Yvonne; Rigby, Neil M; Philo, Mark; Kemsley, E Kate

2015-10-20

A rapid multiple reaction monitoring (MRM) mass spectrometric method for the detection and relative quantitation of the adulteration of meat with that of an undeclared species is presented. Our approach uses corresponding proteins from the different species under investigation and corresponding peptides from those proteins, or CPCP. Selected peptide markers can be used for species detection. The use of ratios of MRM transition peak areas for corresponding peptides is proposed for relative quantitation. The approach is introduced by use of myoglobin from four meats: beef, pork, horse and lamb. Focusing in the present work on species identification, by use of predictive tools, we determine peptide markers that allow the identification of all four meats and detection of one meat added to another at levels of 1% (w/w). Candidate corresponding peptide pairs to be used for the relative quantification of one meat added to another have been observed. Preliminary quantitation data presented here are encouraging.

Peptidomic strategy for purification and identification of potential ACE-inhibitory and antioxidant peptides in Tetradesmus obliquus microalgae.

PubMed

Montone, Carmela Maria; Capriotti, Anna Laura; Cavaliere, Chiara; La Barbera, Giorgia; Piovesana, Susy; Zenezini Chiozzi, Riccardo; Laganà, Aldo

2018-06-01

Microalgae are unicellular marine organisms that have promoted complex biochemical pathways to survive in greatly competitive marine environments. They could contain significant amounts of high-quality proteins which, because of their structural diversity, contain a range of yet undiscovered novel bioactive peptides. In this work, a peptidomic platform was developed for the separation and identification of bioactive peptides in protein hydrolysates. In this work, a peptidomic platform was developed for the extraction, separation, and identification of bioactive peptides in protein hydrolysates. Indeed, extraction of proteins from recalcitrant tissues is still a challenge due to their strong cell walls and high levels of non-protein interfering compounds. Therefore, seven different protein extraction protocols, based on mechanical and chemical methods, were tested in order to produce high-quality protein extracts. Proteins obtained by means of the best protocol, consisting of milling the recalcitrant tissue with glass beads, were subjected to enzymatic digestion with Alcalase® and subsequently the hydrolysate was purified by two-dimensional semi-preparative reversed phase liquid chromatography. Fractions were assayed for antioxidant and antihypertensive activities and only the most active ones were finally analyzed by RP nanoHPLC-MS/MS. Around 500 peptide sequences were identified in these fractions. The identified peptides were subjected to an in silico analysis by PeptideRanker algorithm in order to assign a score of bioactivity probability. Twenty-five sequenced peptides were found with potential antioxidant and angiotensin-converting-enzyme-inhibitory activities. Four of these peptides, WPRGYFL, GPDRPKFLGPF, WYGPDRPKFL, SDWDRF, were selected for synthesis and in vitro tested for specific bioactivity, exhibiting good values of antioxidant and ACE-inhibitory activity. Graphical abstract Workflow showing the entire peptidomic approach developed for identification of bioactive peptides in microalgae.

Spectrum-based method to generate good decoy libraries for spectral library searching in peptide identifications.

PubMed

Cheng, Chia-Ying; Tsai, Chia-Feng; Chen, Yu-Ju; Sung, Ting-Yi; Hsu, Wen-Lian

2013-05-03

As spectral library searching has received increasing attention for peptide identification, constructing good decoy spectra from the target spectra is the key to correctly estimating the false discovery rate in searching against the concatenated target-decoy spectral library. Several methods have been proposed to construct decoy spectral libraries. Most of them construct decoy peptide sequences and then generate theoretical spectra accordingly. In this paper, we propose a method, called precursor-swap, which directly constructs decoy spectral libraries directly at the "spectrum level" without generating decoy peptide sequences by swapping the precursors of two spectra selected according to a very simple rule. Our spectrum-based method does not require additional efforts to deal with ion types (e.g., a, b or c ions), fragment mechanism (e.g., CID, or ETD), or unannotated peaks, but preserves many spectral properties. The precursor-swap method is evaluated on different spectral libraries and the results of obtained decoy ratios show that it is comparable to other methods. Notably, it is efficient in time and memory usage for constructing decoy libraries. A software tool called Precursor-Swap-Decoy-Generation (PSDG) is publicly available for download at http://ms.iis.sinica.edu.tw/PSDG/.

A peptide N-terminal protection strategy for comprehensive glycoproteome analysis using hydrazide chemistry based method

PubMed Central

Huang, Junfeng; Qin, Hongqiang; Sun, Zhen; Huang, Guang; Mao, Jiawei; Cheng, Kai; Zhang, Zhang; Wan, Hao; Yao, Yating; Dong, Jing; Zhu, Jun; Wang, Fangjun; Ye, Mingliang; Zou, Hanfa

2015-01-01

Enrichment of glycopeptides by hydrazide chemistry (HC) is a popular method for glycoproteomics analysis. However, possible side reactions of peptide backbones during the glycan oxidation in this method have not been comprehensively studied. Here, we developed a proteomics approach to locate such side reactions and found several types of the side reactions that could seriously compromise the performance of glycoproteomics analysis. Particularly, the HC method failed to identify N-terminal Ser/Thr glycopeptides because the oxidation of vicinal amino alcohol on these peptides generates aldehyde groups and after they are covalently coupled to HC beads, these peptides cannot be released by PNGase F for identification. To overcome this drawback, we apply a peptide N-terminal protection strategy in which primary amine groups on peptides are chemically blocked via dimethyl labeling, thus the vicinal amino alcohols on peptide N-termini are eliminated. Our results showed that this strategy successfully prevented the oxidation of peptide N-termini and significantly improved the coverage of glycoproteome. PMID:25959593

Improved Methods for the Enrichment and Analysis of Glycated Peptides

PubMed Central

Zhang, Qibin; Schepmoes, Athena A.; Brock, Jonathan W. C.; Wu, Si; Moore, Ronald J.; Purvine, Samuel O.; Baynes, John W.; Smith, Richard D.; Metz, Thomas O.

2009-01-01

Nonenzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. Herein we report improved methods for the enrichment and analysis of glycated peptides using boronate affinity chromatography and electron-transfer dissociation mass spectrometry, respectively. The enrichment of glycated peptides was improved by replacing an off-line desalting step with an online wash of column-bound glycated peptides using 50 mM ammonium acetate, followed by elution with 100 mM acetic acid. The analysis of glycated peptides by MS/MS was improved by considering only higher charged (≥3) precursor ions during data-dependent acquisition, which increased the number of glycated peptide identifications. Similarly, the use of supplemental collisional activation after electron transfer (ETcaD) resulted in more glycated peptide identifications when the MS survey scan was acquired with enhanced resolution. Acquiring ETD-MS/MS data at a normal MS survey scan rate, in conjunction with the rejection of both 1+ and 2+ precursor ions, increased the number of identified glycated peptides relative to ETcaD or the enhanced MS survey scan rate. Finally, an evaluation of trypsin, Arg-C, and Lys-C showed that tryptic digestion of glycated proteins was comparable to digestion with Lys-C and that both were better than Arg-C in terms of the number of glycated peptides and corresponding glycated proteins identified by LC–MS/MS. PMID:18989935

Comparative evaluation of electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) and high-pH reversed phase (Hp-RP) chromatography in profiling of rat kidney proteome.

PubMed

Hao, Piliang; Ren, Yan; Dutta, Bamaprasad; Sze, Siu Kwan

2013-04-26

ERLIC and high-pH RP (Hp-RP) have been reported to be promising alternatives to strong cation exchange (SCX) in proteome fractionation. Here we compared the performance of ERLIC, concatenated ERLIC and concatenated Hp-RP in proteome profiling. The protein identification is comparable in these three strategies, but significantly more unique peptides are identified by the two concatenation methods, resulting in a significant increase of the average protein sequence coverage. The pooling of fractions from spaced intervals results in more uniform distribution of peptides in each fraction compared with the chromatogram-based pooling of adjacent fractions. ERLIC fractionates peptides according to their pI and GRAVY values. These properties remains but becomes less remarkable in concatenated ERLIC. In contrast, the average pI and GRAVY values of the peptides are comparable in each fraction in concatenated Hp-RP. ERLIC performs the best in identifying peptides with pI>9 among the three strategies, while concatenated Hp-RP is good at identifying peptides with pI<4. These advantages are useful when either basic or acidic peptides/proteins are analytical targets. The power of ERLIC in identification of basic peptides seems to be due to their efficient separation from acidic peptides. This study facilitates the choice of proper fractionation strategies based on specific objectives. For in-depth proteomic analysis of a cell, tissue and plasma, multidimensional liquid chromatography (MDLC) is still necessary to reduce sample complexity for improving analytical dynamic range and proteome coverage. This work conducts a direct comparison of three promising first-dimensional proteome fractionation methods. They are comparable in identifying proteins, but concatenated ERLIC and concatenated Hp-RP identify significantly more unique peptides than ERLIC. ERLIC is good at analyzing basic peptides, while concatenated Hp-RP performs the best in analyzing acidic peptides with pI<4. This will facilitate the choice of the proper peptide fractionation strategy based on a specific need. A combination of different fractionation strategies can be used to increase the sequence coverage and number of protein identification due to the complementary effect between different methods. Copyright © 2013 Elsevier B.V. All rights reserved.

Diagnostic Peptide Discovery: Prioritization of Pathogen Diagnostic Markers Using Multiple Features

PubMed Central

Carmona, Santiago J.; Sartor, Paula A.; Leguizamón, María S.; Campetella, Oscar E.; Agüero, Fernán

2012-01-01

The availability of complete pathogen genomes has renewed interest in the development of diagnostics for infectious diseases. Synthetic peptide microarrays provide a rapid, high-throughput platform for immunological testing of potential B-cell epitopes. However, their current capacity prevent the experimental screening of complete “peptidomes”. Therefore, computational approaches for prediction and/or prioritization of diagnostically relevant peptides are required. In this work we describe a computational method to assess a defined set of molecular properties for each potential diagnostic target in a reference genome. Properties such as sub-cellular localization or expression level were evaluated for the whole protein. At a higher resolution (short peptides), we assessed a set of local properties, such as repetitive motifs, disorder (structured vs natively unstructured regions), trans-membrane spans, genetic polymorphisms (conserved vs. divergent regions), predicted B-cell epitopes, and sequence similarity against human proteins and other potential cross-reacting species (e.g. other pathogens endemic in overlapping geographical locations). A scoring function based on these different features was developed, and used to rank all peptides from a large eukaryotic pathogen proteome. We applied this method to the identification of candidate diagnostic peptides in the protozoan Trypanosoma cruzi, the causative agent of Chagas disease. We measured the performance of the method by analyzing the enrichment of validated antigens in the high-scoring top of the ranking. Based on this measure, our integrative method outperformed alternative prioritizations based on individual properties (such as B-cell epitope predictors alone). Using this method we ranked 10 million 12-mer overlapping peptides derived from the complete T. cruzi proteome. Experimental screening of 190 high-scoring peptides allowed the identification of 37 novel epitopes with diagnostic potential, while none of the low scoring peptides showed significant reactivity. Many of the metrics employed are dependent on standard bioinformatic tools and data, so the method can be easily extended to other pathogen genomes. PMID:23272069

Peptide Identification by Database Search of Mixture Tandem Mass Spectra*

PubMed Central

Wang, Jian; Bourne, Philip E.; Bandeira, Nuno

2011-01-01

In high-throughput proteomics the development of computational methods and novel experimental strategies often rely on each other. In certain areas, mass spectrometry methods for data acquisition are ahead of computational methods to interpret the resulting tandem mass spectra. Particularly, although there are numerous situations in which a mixture tandem mass spectrum can contain fragment ions from two or more peptides, nearly all database search tools still make the assumption that each tandem mass spectrum comes from one peptide. Common examples include mixture spectra from co-eluting peptides in complex samples, spectra generated from data-independent acquisition methods, and spectra from peptides with complex post-translational modifications. We propose a new database search tool (MixDB) that is able to identify mixture tandem mass spectra from more than one peptide. We show that peptides can be reliably identified with up to 95% accuracy from mixture spectra while considering only a 0.01% of all possible peptide pairs (four orders of magnitude speedup). Comparison with current database search methods indicates that our approach has better or comparable sensitivity and precision at identifying single-peptide spectra while simultaneously being able to identify 38% more peptides from mixture spectra at significantly higher precision. PMID:21862760

Development of a Trypanosoma cruzi strain typing assay using MS2 peptide spectral libraries (Tc-STAMS2)

PubMed Central

de Oliveira, Gilberto Santos; Kawahara, Rebeca; Rosa-Fernandes, Livia; Avila, Carla Cristi; Teixeira, Marta M. G.; Larsen, Martin R.

2018-01-01

Background Chagas disease also known as American trypanosomiasis is caused by the protozoan Trypanosoma cruzi. Over the last 30 years, Chagas disease has expanded from a neglected parasitic infection of the rural population to an urbanized chronic disease, becoming a potentially emergent global health problem. T. cruzi strains were assigned to seven genetic groups (TcI-TcVI and TcBat), named discrete typing units (DTUs), which represent a set of isolates that differ in virulence, pathogenicity and immunological features. Indeed, diverse clinical manifestations (from asymptomatic to highly severe disease) have been attempted to be related to T.cruzi genetic variability. Due to that, several DTU typing methods have been introduced. Each method has its own advantages and drawbacks such as high complexity and analysis time and all of them are based on genetic signatures. Recently, a novel method discriminated bacterial strains using a peptide identification-free, genome sequence-independent shotgun proteomics workflow. Here, we aimed to develop a Trypanosoma cruzi Strain Typing Assay using MS/MS peptide spectral libraries, named Tc-STAMS2. Methods/Principal findings The Tc-STAMS2 method uses shotgun proteomics combined with spectral library search to assign and discriminate T. cruzi strains independently on the genome knowledge. The method is based on the construction of a library of MS/MS peptide spectra built using genotyped T. cruzi reference strains. For identification, the MS/MS peptide spectra of unknown T. cruzi cells are identified using the spectral matching algorithm SpectraST. The Tc-STAMS2 method allowed correct identification of all DTUs with high confidence. The method was robust towards different sample preparations, length of chromatographic gradients and fragmentation techniques. Moreover, a pilot inter-laboratory study showed the applicability to different MS platforms. Conclusions and significance This is the first study that develops a MS-based platform for T. cruzi strain typing. Indeed, the Tc-STAMS2 method allows T. cruzi strain typing using MS/MS spectra as discriminatory features and allows the differentiation of TcI-TcVI DTUs. Similar to genomic-based strategies, the Tc-STAMS2 method allows identification of strains within DTUs. Its robustness towards different experimental and biological variables makes it a valuable complementary strategy to the current T. cruzi genotyping assays. Moreover, this method can be used to identify DTU-specific features correlated with the strain phenotype. PMID:29608573

Optimization of mass spectrometric parameters improve the identification performance of capillary zone electrophoresis for single-shot bottom-up proteomics analysis.

PubMed

Zhang, Zhenbin; Dovichi, Norman J

2018-02-25

The effects of MS1 injection time, MS2 injection time, dynamic exclusion time, intensity threshold, and isolation width were investigated on the numbers of peptide and protein identifications for single-shot bottom-up proteomics analysis using CZE-MS/MS analysis of a Xenopus laevis tryptic digest. An electrokinetically pumped nanospray interface was used to couple a linear-polyacrylamide coated capillary to a Q Exactive HF mass spectrometer. A sensitive method that used a 1.4 Th isolation width, 60,000 MS2 resolution, 110 ms MS2 injection time, and a top 7 fragmentation produced the largest number of identifications when the CZE loading amount was less than 100 ng. A programmable autogain control method (pAGC) that used a 1.4 Th isolation width, 15,000 MS2 resolution, 110 ms MS2 injection time, and top 10 fragmentation produced the largest number of identifications for CZE loading amounts greater than 100 ng; 7218 unique peptides and 1653 protein groups were identified from 200 ng by using the pAGC method. The effect of mass spectrometer conditions on the performance of UPLC-MS/MS was also investigated. A fast method that used a 1.4 Th isolation width, 30,000 MS2 resolution, 45 ms MS2 injection time, and top 12 fragmentation produced the largest number of identifications for 200 ng UPLC loading amount (6025 unique peptides and 1501 protein groups). This is the first report where the identification number for CZE surpasses that of the UPLC at the 200 ng loading level. However, more peptides (11476) and protein groups (2378) were identified by using UPLC-MS/MS when the sample loading amount was increased to 2 μg with the fast method. To exploit the fast scan speed of the Q-Exactive HF mass spectrometer, higher sample loading amounts are required for single-shot bottom-up proteomics analysis using CZE-MS/MS. Copyright © 2017 Elsevier B.V. All rights reserved.

Modification Site Localization in Peptides.

PubMed

Chalkley, Robert J

2016-01-01

There are a large number of search engines designed to take mass spectrometry fragmentation spectra and match them to peptides from proteins in a database. These peptides could be unmodified, but they could also bear modifications that were added biologically or during sample preparation. As a measure of reliability for the peptide identification, software normally calculates how likely a given quality of match could have been achieved at random, most commonly through the use of target-decoy database searching (Elias and Gygi, Nat Methods 4(3): 207-214, 2007). Matching the correct peptide but with the wrong modification localization is not a random match, so results with this error will normally still be assessed as reliable identifications by the search engine. Hence, an extra step is required to determine site localization reliability, and the software approaches to measure this are the subject of this part of the chapter.

Identification of specific bovine blood biomarkers with a non-targeted approach using HPLC ESI tandem mass spectrometry.

PubMed

Lecrenier, M C; Marbaix, H; Dieu, M; Veys, P; Saegerman, C; Raes, M; Baeten, V

2016-12-15

Animal by-products are valuable protein sources in animal nutrition. Among them are blood products and blood meal, which are used as high-quality material for their beneficial effects on growth and health. Within the framework of the feed ban relaxation, the development of complementary methods in order to refine the identification of processed animal proteins remains challenging. The aim of this study was to identify specific biomarkers that would allow the detection of bovine blood products and processed animal proteins using tandem mass spectrometry. Seventeen biomarkers were identified: nine peptides for bovine plasma powder; seven peptides for bovine haemoglobin powder, including six peptides for bovine blood meal; and one peptide for porcine blood. They were not detected in several commercial compound feed or feed materials, such as blood by-products of other animal origins, milk-derived products and fish meal. These biomarkers could be used for developing a species-specific and blood-specific detection method. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development of a Trypanosoma cruzi strain typing assay using MS2 peptide spectral libraries (Tc-STAMS2).

PubMed

de Oliveira, Gilberto Santos; Kawahara, Rebeca; Rosa-Fernandes, Livia; Mule, Simon Ngao; Avila, Carla Cristi; Teixeira, Marta M G; Larsen, Martin R; Palmisano, Giuseppe

2018-04-01

Chagas disease also known as American trypanosomiasis is caused by the protozoan Trypanosoma cruzi. Over the last 30 years, Chagas disease has expanded from a neglected parasitic infection of the rural population to an urbanized chronic disease, becoming a potentially emergent global health problem. T. cruzi strains were assigned to seven genetic groups (TcI-TcVI and TcBat), named discrete typing units (DTUs), which represent a set of isolates that differ in virulence, pathogenicity and immunological features. Indeed, diverse clinical manifestations (from asymptomatic to highly severe disease) have been attempted to be related to T.cruzi genetic variability. Due to that, several DTU typing methods have been introduced. Each method has its own advantages and drawbacks such as high complexity and analysis time and all of them are based on genetic signatures. Recently, a novel method discriminated bacterial strains using a peptide identification-free, genome sequence-independent shotgun proteomics workflow. Here, we aimed to develop a Trypanosoma cruzi Strain Typing Assay using MS/MS peptide spectral libraries, named Tc-STAMS2. The Tc-STAMS2 method uses shotgun proteomics combined with spectral library search to assign and discriminate T. cruzi strains independently on the genome knowledge. The method is based on the construction of a library of MS/MS peptide spectra built using genotyped T. cruzi reference strains. For identification, the MS/MS peptide spectra of unknown T. cruzi cells are identified using the spectral matching algorithm SpectraST. The Tc-STAMS2 method allowed correct identification of all DTUs with high confidence. The method was robust towards different sample preparations, length of chromatographic gradients and fragmentation techniques. Moreover, a pilot inter-laboratory study showed the applicability to different MS platforms. This is the first study that develops a MS-based platform for T. cruzi strain typing. Indeed, the Tc-STAMS2 method allows T. cruzi strain typing using MS/MS spectra as discriminatory features and allows the differentiation of TcI-TcVI DTUs. Similar to genomic-based strategies, the Tc-STAMS2 method allows identification of strains within DTUs. Its robustness towards different experimental and biological variables makes it a valuable complementary strategy to the current T. cruzi genotyping assays. Moreover, this method can be used to identify DTU-specific features correlated with the strain phenotype.

Efficient Identification of Murine M2 Macrophage Peptide Targeting Ligands by Phage Display and Next-Generation Sequencing.

PubMed

Liu, Gary W; Livesay, Brynn R; Kacherovsky, Nataly A; Cieslewicz, Maryelise; Lutz, Emi; Waalkes, Adam; Jensen, Michael C; Salipante, Stephen J; Pun, Suzie H

2015-08-19

Peptide ligands are used to increase the specificity of drug carriers to their target cells and to facilitate intracellular delivery. One method to identify such peptide ligands, phage display, enables high-throughput screening of peptide libraries for ligands binding to therapeutic targets of interest. However, conventional methods for identifying target binders in a library by Sanger sequencing are low-throughput, labor-intensive, and provide a limited perspective (<0.01%) of the complete sequence space. Moreover, the small sample space can be dominated by nonspecific, preferentially amplifying "parasitic sequences" and plastic-binding sequences, which may lead to the identification of false positives or exclude the identification of target-binding sequences. To overcome these challenges, we employed next-generation Illumina sequencing to couple high-throughput screening and high-throughput sequencing, enabling more comprehensive access to the phage display library sequence space. In this work, we define the hallmarks of binding sequences in next-generation sequencing data, and develop a method that identifies several target-binding phage clones for murine, alternatively activated M2 macrophages with a high (100%) success rate: sequences and binding motifs were reproducibly present across biological replicates; binding motifs were identified across multiple unique sequences; and an unselected, amplified library accurately filtered out parasitic sequences. In addition, we validate the Multiple Em for Motif Elicitation tool as an efficient and principled means of discovering binding sequences.

Cell density signal protein suitable for treatment of connective tissue injuries and defects

DOEpatents

Schwarz, Richard I.

2002-08-13

Identification, isolation and partial sequencing of a cell density protein produced by fibroblastic cells. The cell density signal protein comprising a 14 amino acid peptide or a fragment, variant, mutant or analog thereof, the deduced cDNA sequence from the 14 amino acid peptide, a recombinant protein, protein and peptide-specific antibodies, and the use of the peptide and peptide-specific antibodies as therapeutic agents for regulation of cell differentiation and proliferation. A method for treatment and repair of connective tissue and tendon injuries, collagen deficiency, and connective tissue defects.

The challenge of on-tissue digestion for MALDI MSI- a comparison of different protocols to improve imaging experiments.

PubMed

Diehl, Hanna C; Beine, Birte; Elm, Julian; Trede, Dennis; Ahrens, Maike; Eisenacher, Martin; Marcus, Katrin; Meyer, Helmut E; Henkel, Corinna

2015-03-01

Mass spectrometry imaging (MSI) has become a powerful and successful tool in the context of biomarker detection especially in recent years. This emerging technique is based on the combination of histological information of a tissue and its corresponding spatial resolved mass spectrometric information. The identification of differentially expressed protein peaks between samples is still the method's bottleneck. Therefore, peptide MSI compared to protein MSI is closer to the final goal of identification since peptides are easier to measure than proteins. Nevertheless, the processing of peptide imaging samples is challenging due to experimental complexity. To address this issue, a method development study for peptide MSI using cryoconserved and formalin-fixed paraffin-embedded (FFPE) rat brain tissue is provided. Different digestion times, matrices, and proteases were tested to define an optimal workflow for peptide MSI. All practical experiments were done in triplicates and analyzed by the SCiLS Lab software, using structures derived from myelin basic protein (MBP) peaks, principal component analysis (PCA) and probabilistic latent semantic analysis (pLSA) to rate the experiments' quality. Blinded experimental evaluation in case of defining countable structures in the datasets was performed by three individuals. Such an extensive method development for peptide matrix-assisted laser desorption/ionization (MALDI) imaging experiments has not been performed so far, and the resulting problems and consequences were analyzed and discussed.

Species Identification of Bovine, Ovine and Porcine Type 1 Collagen; Comparing Peptide Mass Fingerprinting and LC-Based Proteomics Methods.

PubMed

Buckley, Mike

2016-03-24

Collagen is one of the most ubiquitous proteins in the animal kingdom and the dominant protein in extracellular tissues such as bone, skin and other connective tissues in which it acts primarily as a supporting scaffold. It has been widely investigated scientifically, not only as a biomedical material for regenerative medicine, but also for its role as a food source for both humans and livestock. Due to the long-term stability of collagen, as well as its abundance in bone, it has been proposed as a source of biomarkers for species identification not only for heat- and pressure-rendered animal feed but also in ancient archaeological and palaeontological specimens, typically carried out by peptide mass fingerprinting (PMF) as well as in-depth liquid chromatography (LC)-based tandem mass spectrometric methods. Through the analysis of the three most common domesticates species, cow, sheep, and pig, this research investigates the advantages of each approach over the other, investigating sites of sequence variation with known functional properties of the collagen molecule. Results indicate that the previously identified species biomarkers through PMF analysis are not among the most variable type 1 collagen peptides present in these tissues, the latter of which can be detected by LC-based methods. However, it is clear that the highly repetitive sequence motif of collagen throughout the molecule, combined with the variability of the sites and relative abundance levels of hydroxylation, can result in high scoring false positive peptide matches using these LC-based methods. Additionally, the greater alpha 2(I) chain sequence variation, in comparison to the alpha 1(I) chain, did not appear to be specific to any particular functional properties, implying that intra-chain functional constraints on sequence variation are not as great as inter-chain constraints. However, although some of the most variable peptides were only observed in LC-based methods, until the range of publicly available collagen sequences improves, the simplicity of the PMF approach and suitable range of peptide sequence variation observed makes it the ideal method for initial taxonomic identification prior to further analysis by LC-based methods only when required.

Off-Line Multidimensional Liquid Chromatography and Auto Sampling Result in Sample Loss in LC/LC–MS/MS

PubMed Central

2015-01-01

Large-scale proteomics often employs two orthogonal separation methods to fractionate complex peptide mixtures. Fractionation can involve ion exchange separation coupled to reversed-phase separation or, more recently, two reversed-phase separations performed at different pH values. When multidimensional separations are combined with tandem mass spectrometry for protein identification, the strategy is often referred to as multidimensional protein identification technology (MudPIT). MudPIT has been used in either an automated (online) or manual (offline) format. In this study, we evaluated the performance of different MudPIT strategies by both label-free and tandem mass tag (TMT) isobaric tagging. Our findings revealed that online MudPIT provided more peptide/protein identifications and higher sequence coverage than offline platforms. When employing an off-line fractionation method with direct loading of samples onto the column from an eppendorf tube via a high-pressure device, a 5.3% loss in protein identifications is observed. When off-line fractionated samples are loaded via an autosampler, a 44.5% loss in protein identifications is observed compared with direct loading of samples onto a triphasic capillary column. Moreover, peptide recovery was significantly lower after offline fractionation than in online fractionation. Signal-to-noise (S/N) ratio, however, was not significantly altered between experimental groups. It is likely that offline sample collection results in stochastic peptide loss due to noncovalent adsorption to solid surfaces. Therefore, the use of the offline approaches should be considered carefully when processing minute quantities of valuable samples. PMID:25040086

Stepwise identification of HLA-A*0201-restricted CD8+ T-cell epitope peptides from herpes simplex virus type 1 genome boosted by a StepRank scheme.

PubMed

Bi, Jianjun; Song, Rengang; Yang, Huilan; Li, Bingling; Fan, Jianyong; Liu, Zhongrong; Long, Chaoqin

2011-01-01

Identification of immunodominant epitopes is the first step in the rational design of peptide vaccines aimed at T-cell immunity. To date, however, it is yet a great challenge for accurately predicting the potent epitope peptides from a pool of large-scale candidates with an efficient manner. In this study, a method that we named StepRank has been developed for the reliable and rapid prediction of binding capabilities/affinities between proteins and genome-wide peptides. In this procedure, instead of single strategy used in most traditional epitope identification algorithms, four steps with different purposes and thus different computational demands are employed in turn to screen the large-scale peptide candidates that are normally generated from, for example, pathogenic genome. The steps 1 and 2 aim at qualitative exclusion of typical nonbinders by using empirical rule and linear statistical approach, while the steps 3 and 4 focus on quantitative examination and prediction of the interaction energy profile and binding affinity of peptide to target protein via quantitative structure-activity relationship (QSAR) and structure-based free energy analysis. We exemplify this method through its application to binding predictions of the peptide segments derived from the 76 known open-reading frames (ORFs) of herpes simplex virus type 1 (HSV-1) genome with or without affinity to human major histocompatibility complex class I (MHC I) molecule HLA-A*0201, and find that the predictive results are well compatible with the classical anchor residue theory and perfectly match for the extended motif pattern of MHC I-binding peptides. The putative epitopes are further confirmed by comparisons with 11 experimentally measured HLA-A*0201-restrcited peptides from the HSV-1 glycoproteins D and K. We expect that this well-designed scheme can be applied in the computational screening of other viral genomes as well.

Complementation of UPLC-Q-TOF-MS and CESI-Q-TOF-MS on identification and determination of peptides from bovine lactoferrin.

PubMed

Chen, Hui; Shi, Pujie; Fan, Fengjiao; Tu, Maolin; Xu, Zhe; Xu, Xianbing; Du, Ming

2018-05-01

Digested peptides of bovine lactoferrin as the functional hydrolysates were identified by the Q-TOF tandem mass spectrometry (Q-TOF-MS) coupled with ultra performance liquid chromatograph (UPLC) and capillary electrophoresis (CE). The former (UPLC-Q-TOF-MS) identified 106 peptides while the latter (CE-Q-TOF-MS) characterized 102 peptides after comparison of peptides in terms of their molecular weight (MW), mass-to-charge ratio (m/z), and isoelectric point (pI). In addition, the hydrophilic value, net charge (q), and molecular radius (r) of the peptides were calculated, and a correlation analysis of the two methods was conducted between the retention time (RT) and r/q ratio of the peptides in order to elucidate the different separation principles of the unique peptides. It was shown that the peptides with larger hydrophilic value were beneficial to be separated by UPLC, while the peptides with larger r/q ratio were beneficial to be separated by CE. Combination of the above mentioned two complementary techniques have confidently improved the sequence coverage of lactoferrin and enhanced the identification of peptides, which makes it up to 65.8% in this study. Copyright © 2018. Published by Elsevier B.V.

Analysis of the low molecular weight serum peptidome using ultrafiltration and a hybrid ion trap-Fourier transform mass spectrometer.

PubMed

Zheng, Xiaoyang; Baker, Haven; Hancock, William S

2006-07-07

Advances in proteomics are continuing to expand the ability to analyze the serum proteome. In recent years, it has been realized that in addition to the circulating proteins, human serum also contains a large number of peptides. Many of these peptides are believed to be fragments of larger proteins that have been at least partially degraded by various enzymes such as metalloproteases. Identifying these peptides from a small amount of serum/plasma is difficult due to the complexity of the sample, the low levels of these peptides, and the difficulties in getting a protein identification from a single peptide. In this study, we modified previously published protocols for using centrifugal ultrafiltration, and unlike past studies did not digest the filtrate with trypsin with the intent of identifying endogenous peptides with this method. The filtrate fraction was concentrated and analyzed by a reversed phase-high performance liquid chromatography system connected to a nanospray ionization hybrid ion trap-Fourier transform mass spectrometer (LTQ-FTMS). The mass accuracy of this instrument allows confidence for identifying the protein precursors by a single peptide. The utility of this approach was demonstrated by the identification of over 300 unique peptides with 2 ppm or better mass accuracy per serum sample. With confident identifications, the origin and function of native serum peptides can be more seriously explored. Interestingly, over 34 peptide ladders were observed from over 17 serum proteins. This indicates that a cascade of proteolytic processes affects the serum peptidome. To examine whether this result was an artifact of serum, matched plasma and serum samples were analyzed with similar peptide ladders found in each.

The RAPID method for blood processing yields new insight in plasma concentrations and molecular forms of circulating gut peptides.

PubMed

Stengel, Andreas; Keire, David; Goebel, Miriam; Evilevitch, Lena; Wiggins, Brian; Taché, Yvette; Reeve, Joseph R

2009-11-01

The correct identification of circulating molecular forms and measurement of peptide levels in blood entails that the endocrine peptide being studied is stable and recovered in good yields during blood processing. However, it is not clear whether this is achieved in studies using standard blood processing. Therefore, we compared peptide concentration and form of 12 (125)I-labeled peptides using the standard procedure (EDTA-blood on ice) and a new method employing Reduced temperatures, Acidification, Protease inhibition, Isotopic exogenous controls, and Dilution (RAPID). During standard processing there was at least 80% loss for calcitonin-gene-related peptide and cholecystokinin-58 (CCK-58) and more than 35% loss for amylin, insulin, peptide YY forms (PYY((1-36)) and PYY((3-36))), and somatostatin-28. In contrast, the RAPID method significantly improved the recovery for 11 of 12 peptides (P < 0.05) and eliminated the breakdown of endocrine peptides occurring after standard processing as reflected in radically changed molecular forms for CCK-58, gastrin-releasing peptide, somatostatin-28, and ghrelin. For endogenous ghrelin, this led to an acyl/total ghrelin ratio of 1:5 instead of 1:19 by the standard method. These results show that the RAPID method enables accurate assessment of circulating gut peptide concentrations and forms such as CCK-58, acylated ghrelin, and somatostatin-28. Therefore, the RAPID method represents an efficacious means to detect circulating variations in peptide concentrations and form relevant to the understanding of physiological function of endocrine peptides.

Improving CID, HCD, and ETD FT MS/MS degradome-peptidome identifications using high accuracy mass information

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Yufeng; Tolic, Nikola; Purvine, Samuel O.

2011-11-07

The peptidome (i.e. processed and degraded forms of proteins) of e.g. blood can potentially provide insights into disease processes, as well as a source of candidate biomarkers that are unobtainable using conventional bottom-up proteomics approaches. MS dissociation methods, including CID, HCD, and ETD, can each contribute distinct identifications using conventional peptide identification methods (Shen et al. J. Proteome Res. 2011), but such samples still pose significant analysis and informatics challenges. In this work, we explored a simple approach for better utilization of high accuracy fragment ion mass measurements provided e.g. by FT MS/MS and demonstrate significant improvements relative to conventionalmore » descriptive and probabilistic scores methods. For example, at the same FDR level we identified 20-40% more peptides than SEQUEST and Mascot scoring methods using high accuracy fragment ion information (e.g., <10 mass errors) from CID, HCD, and ETD spectra. Species identified covered >90% of all those identified from SEQUEST, Mascot, and MS-GF scoring methods. Additionally, we found that the merging the different fragment spectra provided >60% more species using the UStags method than achieved previously, and enabled >1000 peptidome components to be identified from a single human blood plasma sample with a 0.6% peptide-level FDR, and providing an improved basis for investigation of potentially disease-related peptidome components.« less

Identification of metastable states in peptide's dynamics

NASA Astrophysics Data System (ADS)

Ruzhytska, Svitlana; Jacobi, Martin Nilsson; Jensen, Christian H.; Nerukh, Dmitry

2010-10-01

A recently developed spectral method for identifying metastable states in Markov chains is used to analyze the conformational dynamics of a four-residue peptide valine-proline-alanine-leucine. We compare our results to empirically defined conformational states and show that the found metastable states correctly reproduce the conformational dynamics of the system.

Direct Maximization of Protein Identifications from Tandem Mass Spectra*

PubMed Central

Spivak, Marina; Weston, Jason; Tomazela, Daniela; MacCoss, Michael J.; Noble, William Stafford

2012-01-01

The goal of many shotgun proteomics experiments is to determine the protein complement of a complex biological mixture. For many mixtures, most methodological approaches fall significantly short of this goal. Existing solutions to this problem typically subdivide the task into two stages: first identifying a collection of peptides with a low false discovery rate and then inferring from the peptides a corresponding set of proteins. In contrast, we formulate the protein identification problem as a single optimization problem, which we solve using machine learning methods. This approach is motivated by the observation that the peptide and protein level tasks are cooperative, and the solution to each can be improved by using information about the solution to the other. The resulting algorithm directly controls the relevant error rate, can incorporate a wide variety of evidence and, for complex samples, provides 18–34% more protein identifications than the current state of the art approaches. PMID:22052992

Methodology for identification of pore forming antimicrobial peptides from soy protein subunits β-conglycinin and glycinin.

PubMed

Xiang, Ning; Lyu, Yuan; Zhu, Xiao; Bhunia, Arun K; Narsimhan, Ganesan

2016-11-01

Antimicrobial peptides (AMPs) inactivate microbial cells through pore formation in cell membrane. Because of their different mode of action compared to antibiotics, AMPs can be effectively used to combat drug resistant bacteria in human health. AMPs can also be used to replace antibiotics in animal feed and immobilized on food packaging films. In this research, we developed a methodology based on mechanistic evaluation of peptide-lipid bilayer interaction to identify AMPs from soy protein. Production of AMPs from soy protein is an attractive, cost-saving alternative for commercial consideration, because soy protein is an abundant and common protein resource. This methodology is also applicable for identification of AMPs from any protein. Initial screening of peptide segments from soy glycinin (11S) and soy β-conglycinin (7S) subunits was based on their hydrophobicity, hydrophobic moment and net charge. Delicate balance between hydrophilic and hydrophobic interactions is necessary for pore formation. High hydrophobicity decreases the peptide solubility in aqueous phase whereas high hydrophilicity limits binding of the peptide to the bilayer. Out of several candidates chosen from the initial screening, two peptides satisfied the criteria for antimicrobial activity, viz. (i) lipid-peptide binding in surface state and (ii) pore formation in transmembrane state of the aggregate. This method of identification of antimicrobial activity via molecular dynamics simulation was shown to be robust in that it is insensitive to the number of peptides employed in the simulation, initial peptide structure and force field. Their antimicrobial activity against Listeria monocytogenes and Escherichia coli was further confirmed by spot-on-lawn test. Copyright © 2016 Elsevier Inc. All rights reserved.

Systematic Errors in Peptide and Protein Identification and Quantification by Modified Peptides*

PubMed Central

Bogdanow, Boris; Zauber, Henrik; Selbach, Matthias

2016-01-01

The principle of shotgun proteomics is to use peptide mass spectra in order to identify corresponding sequences in a protein database. The quality of peptide and protein identification and quantification critically depends on the sensitivity and specificity of this assignment process. Many peptides in proteomic samples carry biochemical modifications, and a large fraction of unassigned spectra arise from modified peptides. Spectra derived from modified peptides can erroneously be assigned to wrong amino acid sequences. However, the impact of this problem on proteomic data has not yet been investigated systematically. Here we use combinations of different database searches to show that modified peptides can be responsible for 20–50% of false positive identifications in deep proteomic data sets. These false positive hits are particularly problematic as they have significantly higher scores and higher intensities than other false positive matches. Furthermore, these wrong peptide assignments lead to hundreds of false protein identifications and systematic biases in protein quantification. We devise a “cleaned search” strategy to address this problem and show that this considerably improves the sensitivity and specificity of proteomic data. In summary, we show that modified peptides cause systematic errors in peptide and protein identification and quantification and should therefore be considered to further improve the quality of proteomic data annotation. PMID:27215553

Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

PubMed Central

Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID:21048197

Identification of major matrix metalloproteinase-20 proteolytic processing products of murine amelogenin and tyrosine-rich amelogenin peptide using a nuclear magnetic resonance spectroscopy based method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buchko, Garry W.; Arachchige, Rajith M. J.; Tao, Jinhui

Here, the aim of this study was to identify major matrix metalloproteinase-20 (MMP20) proteolytic processing products of amelogenin over time and determine if the tyrosine-rich amelogenin peptide (TRAP) was a substrate of MMP20.

Identification of major matrix metalloproteinase-20 proteolytic processing products of murine amelogenin and tyrosine-rich amelogenin peptide using a nuclear magnetic resonance spectroscopy based method

DOE PAGES

Buchko, Garry W.; Arachchige, Rajith M. J.; Tao, Jinhui; ...

2018-06-01

Here, the aim of this study was to identify major matrix metalloproteinase-20 (MMP20) proteolytic processing products of amelogenin over time and determine if the tyrosine-rich amelogenin peptide (TRAP) was a substrate of MMP20.

Identification of Dekkera bruxellensis (Brettanomyces) from Wine by Fluorescence In Situ Hybridization Using Peptide Nucleic Acid Probes

PubMed Central

Stender, Henrik; Kurtzman, Cletus; Hyldig-Nielsen, Jens J.; Sørensen, Ditte; Broomer, Adam; Oliveira, Kenneth; Perry-O'Keefe, Heather; Sage, Andrew; Young, Barbara; Coull, James

2001-01-01

A new fluorescence in situ hybridization method using peptide nucleic acid (PNA) probes for identification of Brettanomyces is described. The test is based on fluorescein-labeled PNA probes targeting a species-specific sequence of the rRNA of Dekkera bruxellensis. The PNA probes were applied to smears of colonies, and results were interpreted by fluorescence microscopy. The results obtained from testing 127 different yeast strains, including 78 Brettanomyces isolates from wine, show that the spoilage organism Brettanomyces belongs to the species D. bruxellensis and that the new method is able to identify Brettanomyces (D. bruxellensis) with 100% sensitivity and 100% specificity. PMID:11157265

Predicting intensity ranks of peptide fragment ions.

PubMed

Frank, Ari M

2009-05-01

Accurate modeling of peptide fragmentation is necessary for the development of robust scoring functions for peptide-spectrum matches, which are the cornerstone of MS/MS-based identification algorithms. Unfortunately, peptide fragmentation is a complex process that can involve several competing chemical pathways, which makes it difficult to develop generative probabilistic models that describe it accurately. However, the vast amounts of MS/MS data being generated now make it possible to use data-driven machine learning methods to develop discriminative ranking-based models that predict the intensity ranks of a peptide's fragment ions. We use simple sequence-based features that get combined by a boosting algorithm into models that make peak rank predictions with high accuracy. In an accompanying manuscript, we demonstrate how these prediction models are used to significantly improve the performance of peptide identification algorithms. The models can also be useful in the design of optimal multiple reaction monitoring (MRM) transitions, in cases where there is insufficient experimental data to guide the peak selection process. The prediction algorithm can also be run independently through PepNovo+, which is available for download from http://bix.ucsd.edu/Software/PepNovo.html.

Predicting Intensity Ranks of Peptide Fragment Ions

PubMed Central

Frank, Ari M.

2009-01-01

Accurate modeling of peptide fragmentation is necessary for the development of robust scoring functions for peptide-spectrum matches, which are the cornerstone of MS/MS-based identification algorithms. Unfortunately, peptide fragmentation is a complex process that can involve several competing chemical pathways, which makes it difficult to develop generative probabilistic models that describe it accurately. However, the vast amounts of MS/MS data being generated now make it possible to use data-driven machine learning methods to develop discriminative ranking-based models that predict the intensity ranks of a peptide's fragment ions. We use simple sequence-based features that get combined by a boosting algorithm in to models that make peak rank predictions with high accuracy. In an accompanying manuscript, we demonstrate how these prediction models are used to significantly improve the performance of peptide identification algorithms. The models can also be useful in the design of optimal MRM transitions, in cases where there is insufficient experimental data to guide the peak selection process. The prediction algorithm can also be run independently through PepNovo+, which is available for download from http://bix.ucsd.edu/Software/PepNovo.html. PMID:19256476

Screening and Identification of Peptides Specifically Targeted to Gastric Cancer Cells from a Phage Display Peptide Library

PubMed

Sahin, Deniz; Taflan, Sevket Onur; Yartas, Gizem; Ashktorab, Hassan; Smoot, Duane T

2018-04-25

Background: Gastric cancer is the second most common cancer among the malign cancer types. Inefficiency of traditional techniques both in diagnosis and therapy of the disease makes the development of alternative and novel techniques indispensable. As an alternative to traditional methods, tumor specific targeting small peptides can be used to increase the efficiency of the treatment and reduce the side effects related to traditional techniques. The aim of this study is screening and identification of individual peptides specifically targeted to human gastric cancer cells using a phage-displayed peptide library and designing specific peptide sequences by using experimentally-eluted peptide sequences. Methods: Here, MKN-45 human gastric cancer cells and HFE-145 human normal gastric epithelial cells were used as the target and control cells, respectively. 5 rounds of biopannning with a phage display 12-peptide library were applied following subtraction biopanning with HFE-145 control cells. The selected phage clones were established by enzyme-linked immunosorbent assay and immunofluorescence detection. We first obtain random phage clones after five biopanning rounds, determine the binding levels of each individual clone. Then, we analyze the frequencies of each amino acid in best binding clones to determine positively overexpressed amino acids for designing novel peptide sequences. Results: DE532 (VETSQYFRGTLS) phage clone was screened positive, showing specific binding on MKN-45 gastric cancer cells. DE-Obs (HNDLFPSWYHNY) peptide, which was designed by using amino acid frequencies of experimentally selected peptides in the 5th round of biopanning, showed specific binding in MKN-45 cells. Conclusion: Selection and characterization of individual clones may give us specifically binding peptides, but more importantly, data extracted from eluted phage clones may be used to design theoretical peptides with better binding properties than even experimentally selected ones. Both peptides, experimental and designed, may be potential candidates to be developed as useful diagnostic or therapeutic ligand molecules in gastric cancer research. Creative Commons Attribution License

PepArML: A Meta-Search Peptide Identification Platform

PubMed Central

Edwards, Nathan J.

2014-01-01

The PepArML meta-search peptide identification platform provides a unified search interface to seven search engines; a robust cluster, grid, and cloud computing scheduler for large-scale searches; and an unsupervised, model-free, machine-learning-based result combiner, which selects the best peptide identification for each spectrum, estimates false-discovery rates, and outputs pepXML format identifications. The meta-search platform supports Mascot; Tandem with native, k-score, and s-score scoring; OMSSA; MyriMatch; and InsPecT with MS-GF spectral probability scores — reformatting spectral data and constructing search configurations for each search engine on the fly. The combiner selects the best peptide identification for each spectrum based on search engine results and features that model enzymatic digestion, retention time, precursor isotope clusters, mass accuracy, and proteotypic peptide properties, requiring no prior knowledge of feature utility or weighting. The PepArML meta-search peptide identification platform often identifies 2–3 times more spectra than individual search engines at 10% FDR. PMID:25663956

LC-MS/MS Identification of Species-Specific Muscle Peptides in Processed Animal Proteins.

PubMed

Marchis, Daniela; Altomare, Alessandra; Gili, Marilena; Ostorero, Federica; Khadjavi, Amina; Corona, Cristiano; Ru, Giuseppe; Cappelletti, Benedetta; Gianelli, Silvia; Amadeo, Francesca; Rumio, Cristiano; Carini, Marina; Aldini, Giancarlo; Casalone, Cristina

2017-12-06

An innovative analytical strategy has been applied to identify signature peptides able to distinguish among processed animal proteins (PAPs) derived from bovine, pig, fish, and milk products. Proteomics was first used to elucidate the proteome of each source. Starting from the identified proteins and using a funnel based approach, a set of abundant and well characterized peptides with suitable physical-chemical properties (signature peptides) and specific for each source was selected. An on-target LC-ESI-MS/MS method (MRM mode) was set up using standard peptides and was then applied to selectively identify the PAP source and also to distinguish proteins from bovine carcass and milk proteins. We believe that the method described meets the request of the European Commission which has developed a strategy for gradually lifting the "total ban" toward "species to species ban", therefore requiring official methods for species-specific discrimination in feed.

Identification and application of self-binding zipper-like sequences in SARS-CoV spike protein.

PubMed

Zhang, Si Min; Liao, Ying; Neo, Tuan Ling; Lu, Yanning; Liu, Ding Xiang; Vahlne, Anders; Tam, James P

2018-05-22

Self-binding peptides containing zipper-like sequences, such as the Leu/Ile zipper sequence within the coiled coil regions of proteins and the cross-β spine steric zippers within the amyloid-like fibrils, could bind to the protein-of-origin through homophilic sequence-specific zipper motifs. These self-binding sequences represent opportunities for the development of biochemical tools and/or therapeutics. Here, we report on the identification of a putative self-binding β-zipper-forming peptide within the severe acute respiratory syndrome-associated coronavirus spike (S) protein and its application in viral detection. Peptide array scanning of overlapping peptides covering the entire length of S protein identified 34 putative self-binding peptides of six clusters, five of which contained octapeptide core consensus sequences. The Cluster I consensus octapeptide sequence GINITNFR was predicted by the Eisenberg's 3D profile method to have high amyloid-like fibrillation potential through steric β-zipper formation. Peptide C6 containing the Cluster I consensus sequence was shown to oligomerize and form amyloid-like fibrils. Taking advantage of this, C6 was further applied to detect the S protein expression in vitro by fluorescence staining. Meanwhile, the coiled-coil-forming Leu/Ile heptad repeat sequences within the S protein were under-represented during peptide array scanning, in agreement with that long peptide lengths were required to attain high helix-mediated interaction avidity. The data suggest that short β-zipper-like self-binding peptides within the S protein could be identified through combining the peptide scanning and predictive methods, and could be exploited as biochemical detection reagents for viral infection. Copyright © 2018. Published by Elsevier Ltd.

NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.

PubMed

Jurtz, Vanessa; Paul, Sinu; Andreatta, Massimo; Marcatili, Paolo; Peters, Bjoern; Nielsen, Morten

2017-11-01

Cytotoxic T cells are of central importance in the immune system's response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC class I molecules. Peptide binding to MHC molecules is the single most selective step in the Ag-presentation pathway. Therefore, in the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has attracted widespread attention. In the past, predictors of peptide-MHC interactions have primarily been trained on binding affinity data. Recently, an increasing number of MHC-presented peptides identified by mass spectrometry have been reported containing information about peptide-processing steps in the presentation pathway and the length distribution of naturally presented peptides. In this article, we present NetMHCpan-4.0, a method trained on binding affinity and eluted ligand data leveraging the information from both data types. Large-scale benchmarking of the method demonstrates an increase in predictive performance compared with state-of-the-art methods when it comes to identification of naturally processed ligands, cancer neoantigens, and T cell epitopes. Copyright © 2017 by The American Association of Immunologists, Inc.

MALDI Mass Spectrometry Imaging: A Novel Tool for the Identification and Classification of Amyloidosis.

PubMed

Winter, Martin; Tholey, Andreas; Kristen, Arnt; Röcken, Christoph

2017-11-01

Amyloidosis is a group of diseases caused by extracellular accumulation of fibrillar polypeptide aggregates. So far, diagnosis is performed by Congo red staining of tissue sections in combination with polarization microscopy. Subsequent identification of the causative protein by immunohistochemistry harbors some difficulties regarding sensitivity and specificity. Mass spectrometry based approaches have been demonstrated to constitute a reliable method to supplement typing of amyloidosis, but still depend on Congo red staining. In the present study, we used matrix-assisted laser desorption/ionization mass spectrometry imaging coupled with ion mobility separation (MALDI-IMS MSI) to investigate amyloid deposits in formalin-fixed and paraffin-embedded tissue samples. Utilizing a novel peptide filter method, we found a universal peptide signature for amyloidoses. Furthermore, differences in the peptide composition of ALλ and ATTR amyloid were revealed and used to build a reliable classification model. Integrating the peptide filter in MALDI-IMS MSI analysis, we developed a bioinformatics workflow facilitating the identification and classification of amyloidosis in a less time and sample-consuming experimental setup. Our findings demonstrate also the feasibility to investigate the amyloid's protein composition, thus paving the way to establish classification models for the diverse types of amyloidoses and to shed further light on the complex process of amyloidogenesis. © 2017 The Authors, Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization of angiotensin-I converting enzyme inhibiting peptide from Venerupis philippinarum with nano-liquid chromatography in combination with orbitrap mass spectrum detection and molecular docking

NASA Astrophysics Data System (ADS)

Shi, Lei; Wu, Tizhi; Sheng, Naijuan; Yang, Li; Wang, Qian; Liu, Rui; Wu, Hao

2017-06-01

The complexity and diversity of peptide mixture from protein hydrolysates make their characterization difficult. In this study, a method combining nano LC-MS/MS with molecular docking was applied to identifying and characterizing a peptide with angiotensin-I converting enzyme (ACE-I) inhibiting activity from Venerupis philippinarum hydrolysate. Firstly, ethanol supernatant of V. philippinarum hydrolysate was separated into active fractions with chromatographic methods such as ion-exchange chromatography and high performance liquid chromatography in combination. Then seven peptides from active fraction were identified according to the searching result of the MS/MS spectra against protein databases. Peptides were synthesized and subjected to ACE-I-inhibition assay. The peptide NTLTLIDTGIGMTK showed the highest potency with an IC50 of 5.75 μmol L-1. The molecular docking analysis showed that the ACE-I inhibiting peptide NTLTLIDTGIGMTK bond with residues Glu123, Glu403, Arg522, Glu376, Gln281 and Asn285 of ACE-I. Therefore, active peptides could be identified with the present method rather than the traditional purification and identification strategies. It may also be feasible to identify other food-derived peptides which target other enzymes and receptors with the method developed in this study.

Analysis of iodinated quorum sensing peptides by LC-UV/ESI ion trap mass spectrometry.

PubMed

Janssens, Yorick; Verbeke, Frederick; Debunne, Nathan; Wynendaele, Evelien; Peremans, Kathelijne; De Spiegeleer, Bart

2018-02-01

Five different quorum sensing peptides (QSP) were iodinated using different iodination techniques. These iodinated peptides were analyzed using a C 18 reversed phase HPLC system, applying a linear gradient of water and acetonitrile containing 0.1% (m/v) formic acid as mobile phase. Electrospray ionization (ESI) ion trap mass spectrometry was used for the identification of the modified peptides, while semi-quantification was performed using total ion current (TIC) spectra. Non-iodinated peptides and mono- and di-iodinated peptides (NIP, MIP and DIP respectively) were well separated and eluted in that order. Depending on the used iodination method, iodination yields varied from low (2%) to high (57%).

iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates*

PubMed Central

Shteynberg, David; Deutsch, Eric W.; Lam, Henry; Eng, Jimmy K.; Sun, Zhi; Tasman, Natalie; Mendoza, Luis; Moritz, Robert L.; Aebersold, Ruedi; Nesvizhskii, Alexey I.

2011-01-01

The combination of tandem mass spectrometry and sequence database searching is the method of choice for the identification of peptides and the mapping of proteomes. Over the last several years, the volume of data generated in proteomic studies has increased dramatically, which challenges the computational approaches previously developed for these data. Furthermore, a multitude of search engines have been developed that identify different, overlapping subsets of the sample peptides from a particular set of tandem mass spectrometry spectra. We present iProphet, the new addition to the widely used open-source suite of proteomic data analysis tools Trans-Proteomics Pipeline. Applied in tandem with PeptideProphet, it provides more accurate representation of the multilevel nature of shotgun proteomic data. iProphet combines the evidence from multiple identifications of the same peptide sequences across different spectra, experiments, precursor ion charge states, and modified states. It also allows accurate and effective integration of the results from multiple database search engines applied to the same data. The use of iProphet in the Trans-Proteomics Pipeline increases the number of correctly identified peptides at a constant false discovery rate as compared with both PeptideProphet and another state-of-the-art tool Percolator. As the main outcome, iProphet permits the calculation of accurate posterior probabilities and false discovery rate estimates at the level of sequence identical peptide identifications, which in turn leads to more accurate probability estimates at the protein level. Fully integrated with the Trans-Proteomics Pipeline, it supports all commonly used MS instruments, search engines, and computer platforms. The performance of iProphet is demonstrated on two publicly available data sets: data from a human whole cell lysate proteome profiling experiment representative of typical proteomic data sets, and from a set of Streptococcus pyogenes experiments more representative of organism-specific composite data sets. PMID:21876204

Peptide code-on-a-microplate for protease activity analysis via MALDI-TOF mass spectrometric quantitation.

PubMed

Hu, Junjie; Liu, Fei; Ju, Huangxian

2015-04-21

A peptide-encoded microplate was proposed for MALDI-TOF mass spectrometric (MS) analysis of protease activity. The peptide codes were designed to contain a coding region and the substrate of protease for enzymatic cleavage, respectively, and an internal standard method was proposed for the MS quantitation of the cleavage products of these peptide codes. Upon the cleavage reaction in the presence of target proteases, the coding regions were released from the microplate, which were directly quantitated by using corresponding peptides with one-amino acid difference as the internal standards. The coding region could be used as the unique "Protease ID" for the identification of corresponding protease, and the amount of the cleavage product was used for protease activity analysis. Using trypsin and chymotrypsin as the model proteases to verify the multiplex protease assay, the designed "Trypsin ID" and "Chymotrypsin ID" occurred at m/z 761.6 and 711.6. The logarithm value of the intensity ratio of "Protease ID" to internal standard was proportional to trypsin and chymotrypsin concentration in a range from 5.0 to 500 and 10 to 500 nM, respectively. The detection limits for trypsin and chymotrypsin were 2.3 and 5.2 nM, respectively. The peptide-encoded microplate showed good selectivity. This proposed method provided a powerful tool for convenient identification and activity analysis of multiplex proteases.

Structure-based multiscale approach for identification of interaction partners of PDZ domains.

PubMed

Tiwari, Garima; Mohanty, Debasisa

2014-04-28

PDZ domains are peptide recognition modules which mediate specific protein-protein interactions and are known to have a complex specificity landscape. We have developed a novel structure-based multiscale approach which identifies crucial specificity determining residues (SDRs) of PDZ domains from explicit solvent molecular dynamics (MD) simulations on PDZ-peptide complexes and uses these SDRs in combination with knowledge-based scoring functions for proteomewide identification of their interaction partners. Multiple explicit solvent simulations ranging from 5 to 50 ns duration have been carried out on 28 PDZ-peptide complexes with known binding affinities. MM/PBSA binding energy values calculated from these simulations show a correlation coefficient of 0.755 with the experimental binding affinities. On the basis of the SDRs of PDZ domains identified by MD simulations, we have developed a simple scoring scheme for evaluating binding energies for PDZ-peptide complexes using residue based statistical pair potentials. This multiscale approach has been benchmarked on a mouse PDZ proteome array data set by calculating the binding energies for 217 different substrate peptides in binding pockets of 64 different mouse PDZ domains. Receiver operating characteristic (ROC) curve analysis indicates that, the area under curve (AUC) values for binder vs nonbinder classification by our structure based method is 0.780. Our structure based method does not require experimental PDZ-peptide binding data for training.

Identification and characterization of B-cell epitopes of 3FTx and PLA(2) toxins from Micrurus corallinus snake venom.

PubMed

Castro, K L; Duarte, C G; Ramos, H R; Machado de Avila, R A; Schneider, F S; Oliveira, D; Freitas, C F; Kalapothakis, E; Ho, P L; Chávez-Olortegui, C

2015-01-01

The main goal of this work was to develop a strategy to identify B-cell epitopes on four different three finger toxins (3FTX) and one phospholipase A2 (PLA2) from Micrurus corallinus snake venom. 3FTx and PLA2 are highly abundant components in Elapidic venoms and are the major responsibles for the toxicity observed in envenomation by coral snakes. Overlapping peptides from the sequence of each toxin were prepared by SPOT method and three different anti-elapidic sera were used to map the epitopes. After immunogenicity analysis of the spot-reactive peptides by EPITOPIA, a computational method, nine sequences from the five toxins were chemically synthesized and antigenically and immunogenically characterized. All the peptides were used together as immunogens in rabbits, delivered with Freund's adjuvant for a first cycle of immunization and Montanide in the second. A good antibody response against individual synthetic peptides and M. corallinus venom was achieved. Anti-peptide IgGs were also cross-reactive against Micrurus frontalis and Micrurus lemniscatus crude venoms. In addition, anti-peptide IgGs inhibits the lethal and phospholipasic activities of M. corallinus crude venom. Our results provide a rational basis to the identification of neutralizing epitopes on coral snake toxins and show that their corresponding synthetic peptides could improve the generation of immuno-therapeutics. The use of synthetic peptide for immunization is a reasonable approach, since it enables poly-specificity, low risk of toxic effects and large scale production. Copyright © 2014 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Qibin; Schepmoes, Athena A; Brock, Jonathan W

Non-enzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. Herein we report improved methods for the enrichment and analysis of glycated peptides using boronate affinity chromatography and electron transfer dissociation mass spectrometry, respectively. The enrichment of glycated peptides was improved by replacing an off-line desalting step with an on-line wash of column-bound glycated peptides using 50 mM ammonium acetate. The analysis of glycated peptides by MS/MS was improved by considering only higher charged (≥3) precursor-ions during data-dependent acquisition, which increased the number of glycated peptide identifications. Similarly, the use of supplemental collisional activationmore » after electron transfer (ETcaD) resulted in more glycated peptide identifications when the MS survey scan was acquired with enhanced resolution. In general, acquiring ETD-MS/MS data at a normal MS survey scan rate, in conjunction with the rejection of both 1+ and 2+ precursor-ions, increased the number of identified glycated peptides relative to ETcaD or the enhanced MS survey scan rate. Finally, an evaluation of trypsin, Arg-C, and Lys-C showed that tryptic digestion of glycated proteins was comparable to digestion with Lys-C and that both were better than Arg-C in terms of the number glycated peptides identified by LC-MS/MS.« less

Proteomic Identification of Monoclonal Antibodies from Serum

PubMed Central

2015-01-01

Characterizing the in vivo dynamics of the polyclonal antibody repertoire in serum, such as that which might arise in response to stimulation with an antigen, is difficult due to the presence of many highly similar immunoglobulin proteins, each specified by distinct B lymphocytes. These challenges have precluded the use of conventional mass spectrometry for antibody identification based on peptide mass spectral matches to a genomic reference database. Recently, progress has been made using bottom-up analysis of serum antibodies by nanoflow liquid chromatography/high-resolution tandem mass spectrometry combined with a sample-specific antibody sequence database generated by high-throughput sequencing of individual B cell immunoglobulin variable domains (V genes). Here, we describe how intrinsic features of antibody primary structure, most notably the interspersed segments of variable and conserved amino acid sequences, generate recurring patterns in the corresponding peptide mass spectra of V gene peptides, greatly complicating the assignment of correct sequences to mass spectral data. We show that the standard method of decoy-based error modeling fails to account for the error introduced by these highly similar sequences, leading to a significant underestimation of the false discovery rate. Because of these effects, antibody-derived peptide mass spectra require increased stringency in their interpretation. The use of filters based on the mean precursor ion mass accuracy of peptide-spectrum matches is shown to be particularly effective in distinguishing between “true” and “false” identifications. These findings highlight important caveats associated with the use of standard database search and error-modeling methods with nonstandard data sets and custom sequence databases. PMID:24684310

PIPI: PTM-Invariant Peptide Identification Using Coding Method.

PubMed

Yu, Fengchao; Li, Ning; Yu, Weichuan

2016-12-02

In computational proteomics, the identification of peptides with an unlimited number of post-translational modification (PTM) types is a challenging task. The computational cost associated with database search increases exponentially with respect to the number of modified amino acids and linearly with respect to the number of potential PTM types at each amino acid. The problem becomes intractable very quickly if we want to enumerate all possible PTM patterns. To address this issue, one group of methods named restricted tools (including Mascot, Comet, and MS-GF+) only allow a small number of PTM types in database search process. Alternatively, the other group of methods named unrestricted tools (including MS-Alignment, ProteinProspector, and MODa) avoids enumerating PTM patterns with an alignment-based approach to localizing and characterizing modified amino acids. However, because of the large search space and PTM localization issue, the sensitivity of these unrestricted tools is low. This paper proposes a novel method named PIPI to achieve PTM-invariant peptide identification. PIPI belongs to the category of unrestricted tools. It first codes peptide sequences into Boolean vectors and codes experimental spectra into real-valued vectors. For each coded spectrum, it then searches the coded sequence database to find the top scored peptide sequences as candidates. After that, PIPI uses dynamic programming to localize and characterize modified amino acids in each candidate. We used simulation experiments and real data experiments to evaluate the performance in comparison with restricted tools (i.e., Mascot, Comet, and MS-GF+) and unrestricted tools (i.e., Mascot with error tolerant search, MS-Alignment, ProteinProspector, and MODa). Comparison with restricted tools shows that PIPI has a close sensitivity and running speed. Comparison with unrestricted tools shows that PIPI has the highest sensitivity except for Mascot with error tolerant search and ProteinProspector. These two tools simplify the task by only considering up to one modified amino acid in each peptide, which results in a higher sensitivity but has difficulty in dealing with multiple modified amino acids. The simulation experiments also show that PIPI has the lowest false discovery proportion, the highest PTM characterization accuracy, and the shortest running time among the unrestricted tools.

SwePep, a database designed for endogenous peptides and mass spectrometry.

PubMed

Fälth, Maria; Sköld, Karl; Norrman, Mathias; Svensson, Marcus; Fenyö, David; Andren, Per E

2006-06-01

A new database, SwePep, specifically designed for endogenous peptides, has been constructed to significantly speed up the identification process from complex tissue samples utilizing mass spectrometry. In the identification process the experimental peptide masses are compared with the peptide masses stored in the database both with and without possible post-translational modifications. This intermediate identification step is fast and singles out peptides that are potential endogenous peptides and can later be confirmed with tandem mass spectrometry data. Successful applications of this methodology are presented. The SwePep database is a relational database developed using MySql and Java. The database contains 4180 annotated endogenous peptides from different tissues originating from 394 different species as well as 50 novel peptides from brain tissue identified in our laboratory. Information about the peptides, including mass, isoelectric point, sequence, and precursor protein, is also stored in the database. This new approach holds great potential for removing the bottleneck that occurs during the identification process in the field of peptidomics. The SwePep database is available to the public.

A novel algorithm for validating peptide identification from a shotgun proteomics search engine.

PubMed

Jian, Ling; Niu, Xinnan; Xia, Zhonghang; Samir, Parimal; Sumanasekera, Chiranthani; Mu, Zheng; Jennings, Jennifer L; Hoek, Kristen L; Allos, Tara; Howard, Leigh M; Edwards, Kathryn M; Weil, P Anthony; Link, Andrew J

2013-03-01

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has revolutionized the proteomics analysis of complexes, cells, and tissues. In a typical proteomic analysis, the tandem mass spectra from a LC-MS/MS experiment are assigned to a peptide by a search engine that compares the experimental MS/MS peptide data to theoretical peptide sequences in a protein database. The peptide spectra matches are then used to infer a list of identified proteins in the original sample. However, the search engines often fail to distinguish between correct and incorrect peptides assignments. In this study, we designed and implemented a novel algorithm called De-Noise to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. The novel algorithm uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Using proteomics data generated on different types of mass spectrometers, we optimized the De-Noise algorithm on the basis of the resolution and mass accuracy of the mass spectrometer employed in the LC-MS/MS experiment. Our results demonstrate De-Noise improves peptide identification compared to other methods used to process the peptide sequence matches assigned by SEQUEST. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines.

Rapid screening and identification of ACE inhibitors in snake venoms using at-line nanofractionation LC-MS.

PubMed

Mladic, Marija; de Waal, Tessa; Burggraaff, Lindsey; Slagboom, Julien; Somsen, Govert W; Niessen, Wilfried M A; Manjunatha Kini, R; Kool, Jeroen

2017-10-01

This study presents an analytical method for the screening of snake venoms for inhibitors of the angiotensin-converting enzyme (ACE) and a strategy for their rapid identification. The method is based on an at-line nanofractionation approach, which combines liquid chromatography (LC), mass spectrometry (MS), and pharmacology in one platform. After initial LC separation of a crude venom, a post-column flow split is introduced enabling parallel MS identification and high-resolution fractionation onto 384-well plates. The plates are subsequently freeze-dried and used in a fluorescence-based ACE activity assay to determine the ability of the nanofractions to inhibit ACE activity. Once the bioactive wells are identified, the parallel MS data reveals the masses corresponding to the activities found. Narrowing down of possible bioactive candidates is provided by comparison of bioactivity profiles after reversed-phase liquid chromatography (RPLC) and after hydrophilic interaction chromatography (HILIC) of a crude venom. Additional nanoLC-MS/MS analysis is performed on the content of the bioactive nanofractions to determine peptide sequences. The method described was optimized, evaluated, and successfully applied for screening of 30 snake venoms for the presence of ACE inhibitors. As a result, two new bioactive peptides were identified: pELWPRPHVPP in Crotalus viridis viridis venom with IC 50  = 1.1 μM and pEWPPWPPRPPIPP in Cerastes cerastes cerastes venom with IC 50  = 3.5 μM. The identified peptides possess a high sequence similarity to other bradykinin-potentiating peptides (BPPs), which are known ACE inhibitors found in snake venoms.

Large-scale database searching using tandem mass spectra: looking up the answer in the back of the book.

PubMed

Sadygov, Rovshan G; Cociorva, Daniel; Yates, John R

2004-12-01

Database searching is an essential element of large-scale proteomics. Because these methods are widely used, it is important to understand the rationale of the algorithms. Most algorithms are based on concepts first developed in SEQUEST and PeptideSearch. Four basic approaches are used to determine a match between a spectrum and sequence: descriptive, interpretative, stochastic and probability-based matching. We review the basic concepts used by most search algorithms, the computational modeling of peptide identification and current challenges and limitations of this approach for protein identification.

Use of synthetic peptide libraries for the H-2Kd binding motif identification.

PubMed

Quesnel, A; Casrouge, A; Kourilsky, P; Abastado, J P; Trudelle, Y

1995-01-01

To identify Kd-binding peptides, an approach based on small peptide libraries has been developed. These peptide libraries correspond to all possible single-amino acid variants of a particular Kd-binding peptide, SYIPSAEYI, an analog of the Plasmodium berghei 252-260 antigenic peptide SYIPSAEKI. In the parent sequence, each position is replaced by all the genetically encoded amino acids (except cysteine). The multiple analog syntheses are performed either by the Divide Couple and Recombine method or by the Single Resin method and generate mixtures containing 19 peptides. The present report deals with the synthesis, the purification, the chemical characterization by amino acid analysis and electrospray mass spectrometry (ES-MS), and the application of such mixtures in binding tests with a soluble, functionally empty, single-chain H-2Kd molecule denoted SC-Kd. For each mixture, bound peptides were eluted and analyzed by sequencing. Since the binding tests were realized in noncompetitive conditions, our results show that a much broader set of peptides bind to Kd than expected from previous studies. This may be of practical importance when looking for low affinity peptides such as tumor peptides capable of eliciting protective immune response.

Novel Peptide Sequence (“IQ-tag”) with High Affinity for NIR Fluorochromes Allows Protein and Cell Specific Labeling for In Vivo Imaging

PubMed Central

McCarthy, Jason R.; Weissleder, Ralph

2007-01-01

Background Probes that allow site-specific protein labeling have become critical tools for visualizing biological processes. Methods Here we used phage display to identify a novel peptide sequence with nanomolar affinity for near infrared (NIR) (benz)indolium fluorochromes. The developed peptide sequence (“IQ-tag”) allows detection of NIR dyes in a wide range of assays including ELISA, flow cytometry, high throughput screens, microscopy, and optical in vivo imaging. Significance The described method is expected to have broad utility in numerous applications, namely site-specific protein imaging, target identification, cell tracking, and drug development. PMID:17653285

An untargeted approach for the analysis of the urine peptidome of women with preeclampsia.

PubMed

Kononikhin, A S; Starodubtseva, N L; Bugrova, A E; Shirokova, V A; Chagovets, V V; Indeykina, M I; Popov, I A; Kostyukevich, Y I; Vavina, O V; Muminova, K T; Khodzhaeva, Z S; Kan, N E; Frankevich, V E; Nikolaev, E N; Sukhikh, G T

2016-10-21

Preeclampsia (PE) is a pregnancy complication characterized by high blood pressure and proteinuria. The disorder usually occurs after the 20th week of pregnancy and gets worse over time. PE increases the risk of poor outcomes for both the mother and the baby. In the study we applied LC-MS/MS method for the analysis of the urine peptidome of women with PE. Samples were prepared using size-exclusion chromatography method which gives more than twice peptides identities if compared with solid phase extraction. Thirty urine samples from women with mild and severe preeclampsia and the control group were analyzed. In total 1786 peptides were identified using complementary search engines (Mascot, MaxQuant and PEAKS). A high level of agreement in peptide identification was observed with previously published data. Label-free data comparison resulted in 35 peptides which reliably distinguished a particular PE group (severe or mild) from controls. Our results revealed unique identifications (correlate to alpha-1-antitrypsin, collagen alpha-1(I) chain, collagen alpha-1 (III) chain, and uromodulin, for instance) that can potentially serve as early indicators of PE. Copyright © 2016 Elsevier B.V. All rights reserved.

Design of a dual-function peptide probe as a binder of angiotensin II and an inducer of silver nanoparticle aggregation for use in label-free colorimetric assays.

PubMed

Okochi, Mina; Kuboyama, Masashi; Tanaka, Masayoshi; Honda, Hiroyuki

2015-09-01

Label-free colorimetric assays using metallic nanoparticles have received much recent attention, for their application in simple and sensitive methods for detection of biomolecules. Short peptide probes that can bind to analyte biomolecules are attractive ligands in molecular nanotechnology; however, identification of biological recognition motifs is usually based on trial-and-error experiments. Herein, a peptide probe was screened for colorimetric detection of angiotensin II (Ang II) using a mechanism for non-crosslinking aggregation of silver nanoparticles (AgNPs). The dual-function peptides, which bind to the analyte and induce AgNP aggregation, were identified using a two-step strategy: (1) screening of an Ang II-binding peptide from an Ang II receptor sequence library, using SPOT technology, which enable peptides synthesis on cellulose membranes via an Fmoc method and (2) selection of peptide probes that effectively induce aggregation of AgNPs using a photolinker modified peptide array. Using the identified peptide probe, KGKNKRRR, aggregation of AgNPs was detected by observation of a pink color in the absence of Ang II, whereas AgNPs remained dispersed in the presence of Ang II (yellow). The color changes were not observed in the presence of other hormone molecules. Ang II could be detected within 15 min, with a detection limit of 10 µM, by measuring the ratio of absorbance at 400 nm and 568 nm; the signal could also be observed with the naked eye. These data suggest that the peptide identified here could be used as a probe for simple and rapid colorimetric detection of Ang II. This strategy for the identification of functional peptides shows promise for the development of colorimetric detection of various diagnostically important biomolecules. Copyright © 2015 Elsevier B.V. All rights reserved.

Over 2,300 phosphorylated peptide identifications with single-shot capillary zone electrophoresis-tandem mass spectrometry in a 100 min separation

PubMed Central

Ludwig, Katelyn R.; Sun, Liangliang; Zhu, Guijie; Dovichi, Norman J.; Hummon, Amanda B.

2015-01-01

Ultra-performance liquid chromatography (UPLC)-electrospray ionization (ESI)-tandem mass spectrometry (MS/MS) is typically employed for phosphoproteome analysis. Alternatively, capillary zone electrophoresis (CZE) - ESI-MS/MS has great potential for phosphoproteome analysis due to the significantly different migration times of phosphorylated and unphosphorylated forms of peptides. In this work, we systematically compared UPLC-MS/MS and CZE-MS/MS for phosphorylated peptide identifications (IDs) using an enriched phosphoproteome from the MCF-10A cell line. When the sample loading amount of UPLC was 10 times higher than that of CZE (2 μg vs. 200 ng), UPLC generated more phosphorylated peptide IDs than CZE (3,313 vs. 1,783). However, when the same sample loading amounts were used for CZE and UPLC (2–200 ng), CZE-MS/MS consistently and significantly outperformed UPLC-MS/MS in terms of phosphorylated peptide and total peptide IDs. This superior performance is most likely due to the higher peptide intensity generated by CZE-MS/MS. More importantly, compared with UPLC data from 2 μg sample, CZE-MS/MS can identify over 500 unique phosphorylated peptides from 200 ng sample, suggesting that CZE and UPLC are complementary for phosphorylated peptide IDs. With further improved loading capacity via a dynamic pH junction method, 2,313 phosphorylated peptides were identified with single-shot CZE-MS/MS in a 100 min analysis. This number of phosphorylated peptide IDs is over one order of magnitude higher than the number of phosphorylated peptide IDs previously reported by single-shot CZE-MS/MS. PMID:26399161

Post-staining electroblotting for efficient and reliable peptide blotting.

PubMed

Lee, Der-Yen; Chang, Geen-Dong

2015-01-01

Post-staining electroblotting has been previously described to transfer Coomassie blue-stained proteins from polyacrylamide gel onto polyvinylidene difluoride (PVDF) membranes. Actually, stained peptides can also be efficiently and reliably transferred. Because of selective staining procedures for peptides and increased retention of stained peptides on the membrane, even peptides with molecular masses less than 2 kDa such as bacitracin and granuliberin R are transferred with satisfactory results. For comparison, post-staining electroblotting is about 16-fold more sensitive than the conventional electroblotting for visualization of insulin on the membrane. Therefore, the peptide blots become practicable and more accessible to further applications, e.g., blot overlay detection or immunoblotting analysis. In addition, the efficiency of peptide transfer is favorable for N-terminal sequence analysis. With this method, peptide blotting can be normalized for further analysis such as blot overlay assay, immunoblotting, and N-terminal sequencing for identification of peptide in crude or partially purified samples.

A novel strategy for global mapping of O-GlcNAc proteins and peptides using selective enzymatic deglycosylation, HILIC enrichment and mass spectrometry identification.

PubMed

Shen, Bingquan; Zhang, Wanjun; Shi, Zhaomei; Tian, Fang; Deng, Yulin; Sun, Changqing; Wang, Guangshun; Qin, Weijie; Qian, Xiaohong

2017-07-01

O-GlcNAcylation is a kind of dynamic O-linked glycosylation of nucleocytoplasmic and mitochondrial proteins. It serves as a major nutrient sensor to regulate numerous biological processes including transcriptional regulation, cell metabolism, cellular signaling, and protein degradation. Dysregulation of cellular O-GlcNAcylated levels contributes to the etiologies of many diseases such as diabetes, neurodegenerative disease and cancer. However, deeper insight into the biological mechanism of O-GlcNAcylation is hampered by its extremely low stoichiometry and the lack of efficient enrichment approaches for large-scale identification by mass spectrometry. Herein, we developed a novel strategy for the global identification of O-GlcNAc proteins and peptides using selective enzymatic deglycosylation, HILIC enrichment and mass spectrometry analysis. Standard O-GlcNAc peptides can be efficiently enriched even in the presence of 500-fold more abundant non-O-GlcNAc peptides and identified by mass spectrometry with a low nanogram detection sensitivity. This strategy successfully achieved the first large-scale enrichment and characterization of O-GlcNAc proteins and peptides in human urine. A total of 474 O-GlcNAc peptides corresponding to 457 O-GlcNAc proteins were identified by mass spectrometry analysis, which is at least three times more than that obtained by commonly used enrichment methods. A large number of unreported O-GlcNAc proteins related to cell cycle, biological regulation, metabolic and developmental process were found in our data. The above results demonstrated that this novel strategy is highly efficient in the global enrichment and identification of O-GlcNAc peptides. These data provide new insights into the biological function of O-GlcNAcylation in human urine, which is correlated with the physiological states and pathological changes of human body and therefore indicate the potential of this strategy for biomarker discovery from human urine. Copyright © 2017. Published by Elsevier B.V.

Identification and the molecular mechanism of a novel myosin-derived ACE inhibitory peptide.

PubMed

Yu, Zhipeng; Wu, Sijia; Zhao, Wenzhu; Ding, Long; Shiuan, David; Chen, Feng; Li, Jianrong; Liu, Jingbo

2018-01-24

The objective of this work was to identify a novel ACE inhibitory peptide from myosin using a number of in silico methods. Myosin was evaluated as a substrate for use in the generation of ACE inhibitory peptides using BIOPEP and ExPASy PeptideCutter. Then the ACE inhibitory activity prediction of peptides in silico was evaluated using the program peptide ranker, following the database search of known and unknown peptides using the program BIOPEP. In addition, the interaction mechanisms of the peptide and ACE were evaluated by DS. All of the tripeptides were predicted to be nontoxic. Results suggested that the tripeptide NCW exerted potent ACE inhibitory activity with an IC 50 value of 35.5 μM. Furthermore, the results suggested that the peptide NCW comes into contact with Zn 701, Tyr 523, His 383, Glu 384, Glu 411, and His 387. The potential molecular mechanism of the NCW/ACE interaction was investigated. Results confirmed that the higher inhibitory potency of NCW might be attributed to the formation of more hydrogen bonds with the ACE's active site. Therefore, the in silico method is effective to predict and identify novel ACE inhibitory peptides from protein hydrolysates.

A Graph-Centric Approach for Metagenome-Guided Peptide and Protein Identification in Metaproteomics

PubMed Central

Tang, Haixu; Li, Sujun; Ye, Yuzhen

2016-01-01

Metaproteomic studies adopt the common bottom-up proteomics approach to investigate the protein composition and the dynamics of protein expression in microbial communities. When matched metagenomic and/or metatranscriptomic data of the microbial communities are available, metaproteomic data analyses often employ a metagenome-guided approach, in which complete or fragmental protein-coding genes are first directly predicted from metagenomic (and/or metatranscriptomic) sequences or from their assemblies, and the resulting protein sequences are then used as the reference database for peptide/protein identification from MS/MS spectra. This approach is often limited because protein coding genes predicted from metagenomes are incomplete and fragmental. In this paper, we present a graph-centric approach to improving metagenome-guided peptide and protein identification in metaproteomics. Our method exploits the de Bruijn graph structure reported by metagenome assembly algorithms to generate a comprehensive database of protein sequences encoded in the community. We tested our method using several public metaproteomic datasets with matched metagenomic and metatranscriptomic sequencing data acquired from complex microbial communities in a biological wastewater treatment plant. The results showed that many more peptides and proteins can be identified when assembly graphs were utilized, improving the characterization of the proteins expressed in the microbial communities. The additional proteins we identified contribute to the characterization of important pathways such as those involved in degradation of chemical hazards. Our tools are released as open-source software on github at https://github.com/COL-IU/Graph2Pro. PMID:27918579

Peptide fingerprinting of Alzheimer's disease in cerebrospinal fluid: identification and prospective evaluation of new synaptic biomarkers.

PubMed

Jahn, Holger; Wittke, Stefan; Zürbig, Petra; Raedler, Thomas J; Arlt, Sönke; Kellmann, Markus; Mullen, William; Eichenlaub, Martin; Mischak, Harald; Wiedemann, Klaus

2011-01-01

Today, dementias are diagnosed late in the course of disease. Future treatments have to start earlier in the disease process to avoid disability requiring new diagnostic tools. The objective of this study is to develop a new method for the differential diagnosis and identification of new biomarkers of Alzheimer's disease (AD) using capillary-electrophoresis coupled to mass-spectrometry (CE-MS) and to assess the potential of early diagnosis of AD. Cerebrospinal fluid (CSF) of 159 out-patients of a memory-clinic at a University Hospital suffering from neurodegenerative disorders and 17 cognitively-healthy controls was used to create differential peptide pattern for dementias and prospective blinded-comparison of sensitivity and specificity for AD diagnosis against the Criterion standard in a naturalistic prospective sample of patients. Sensitivity and specificity of the new method compared to standard diagnostic procedures and identification of new putative biomarkers for AD was the main outcome measure. CE-MS was used to reliably detect 1104 low-molecular-weight peptides in CSF. Training-sets of patients with clinically secured sporadic Alzheimer's disease, frontotemporal dementia, and cognitively healthy controls allowed establishing discriminative biomarker pattern for diagnosis of AD. This pattern was already detectable in patients with mild cognitive impairment (MCI). The AD-pattern was tested in a prospective sample of patients (n = 100) and AD was diagnosed with a sensitivity of 87% and a specificity of 83%. Using CSF measurements of beta-amyloid1-42, total-tau, and phospho(181)-tau, AD-diagnosis had a sensitivity of 88% and a specificity of 67% in the same sample. Sequence analysis of the discriminating biomarkers identified fragments of synaptic proteins like proSAAS, apolipoprotein J, neurosecretory protein VGF, phospholemman, and chromogranin A. The method may allow early differential diagnosis of various dementias using specific peptide fingerprints and identification of incipient AD in patients suffering from MCI. Identified biomarkers facilitate face validity for the use in AD diagnosis.

Computer aided identification of a Hevein-like antimicrobial peptide of bell pepper leaves for biotechnological use.

PubMed

Games, Patrícia Dias; daSilva, Elói Quintas Gonçalves; Barbosa, Meire de Oliveira; Almeida-Souza, Hebréia Oliveira; Fontes, Patrícia Pereira; deMagalhães, Marcos Jorge; Pereira, Paulo Roberto Gomes; Prates, Maura Vianna; Franco, Gloria Regina; Faria-Campos, Alessandra; Campos, Sérgio Vale Aguiar; Baracat-Pereira, Maria Cristina

2016-12-15

Antimicrobial peptides from plants present mechanisms of action that are different from those of conventional defense agents. They are under-explored but have a potential as commercial antimicrobials. Bell pepper leaves ('Magali R') are discarded after harvesting the fruit and are sources of bioactive peptides. This work reports the isolation by peptidomics tools, and the identification and partially characterization by computational tools of an antimicrobial peptide from bell pepper leaves, and evidences the usefulness of records and the in silico analysis for the study of plant peptides aiming biotechnological uses. Aqueous extracts from leaves were enriched in peptide by salt fractionation and ultrafiltration. An antimicrobial peptide was isolated by tandem chromatographic procedures. Mass spectrometry, automated peptide sequencing and bioinformatics tools were used alternately for identification and partial characterization of the Hevein-like peptide, named HEV-CANN. The computational tools that assisted to the identification of the peptide included BlastP, PSI-Blast, ClustalOmega, PeptideCutter, and ProtParam; conventional protein databases (DB) as Mascot, Protein-DB, GenBank-DB, RefSeq, Swiss-Prot, and UniProtKB; specific for peptides DB as Amper, APD2, CAMP, LAMPs, and PhytAMP; other tools included in ExPASy for Proteomics; The Bioactive Peptide Databases, and The Pepper Genome Database. The HEV-CANN sequence presented 40 amino acid residues, 4258.8 Da, theoretical pI-value of 8.78, and four disulfide bonds. It was stable, and it has inhibited the growth of phytopathogenic bacteria and a fungus. HEV-CANN presented a chitin-binding domain in their sequence. There was a high identity and a positive alignment of HEV-CANN sequence in various databases, but there was not a complete identity, suggesting that HEV-CANN may be produced by ribosomal synthesis, which is in accordance with its constitutive nature. Computational tools for proteomics and databases are not adjusted for short sequences, which hampered HEV-CANN identification. The adjustment of statistical tests in large databases for proteins is an alternative to promote the significant identification of peptides. The development of specific DB for plant antimicrobial peptides, with information about peptide sequences, functional genomic data, structural motifs and domains of molecules, functional domains, and peptide-biomolecule interactions are valuable and necessary.

Removal of detergents from proteins and peptides in a spin-column format.

PubMed

Antharavally, Babu S

2012-08-01

To enable downstream analysis, it is critical to remove unbound detergents from protein and peptide samples. This unit describes the use of a high-performance resin that offers exceptional detergent removal for proteins and peptides. The easy-to-use spin format significantly improves results over the standard drip column and batch methodologies, with >95% removal of 1% to 5% detergents, including SDS, sodium deoxycholate, CHAPS, Triton X-100, Triton X-114, NP-40, Brij-35, octyl glucoside, octyl thioglucoside, and lauryl maltoside, with high recovery of proteins and peptides. Detergent removal efficiency is evaluated using colorimetric methods and mass spectrometry (MS). BSA tryptic peptides have been successfully analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and matrix-assisted laser desorption/ionization (MALDI)-MS for identification of protein, following detergent removal using the resin. Advantages of this method include speed (less than 15 min), efficient detergent removal, and high recovery of proteins and peptides. © 2012 by John Wiley & Sons, Inc.

Exploring peptide hormones in plants: identification of four peptide hormone-receptor pairs and two post-translational modification enzymes

PubMed Central

MATSUBAYASHI, Yoshikatsu

2018-01-01

The identification of hormones and their receptors in multicellular organisms is one of the most exciting research areas and has lead to breakthroughs in understanding how their growth and development are regulated. In particular, peptide hormones offer advantages as cell-to-cell signals in that they can be synthesized rapidly and have the greatest diversity in their structure and function. Peptides often undergo post-translational modifications and proteolytic processing to generate small oligopeptide hormones. In plants, such small post-translationally modified peptides constitute the largest group of peptide hormones. We initially explored this type of peptide hormone using bioassay-guided fractionation and later by in silico gene screening coupled with biochemical peptide detection, which led to the identification of four types of novel peptide hormones in plants. We also identified specific receptors for these peptides and transferases required for their post-translational modification. This review summarizes how we discovered these peptide hormone–receptor pairs and post-translational modification enzymes, and how these molecules function in plant growth, development and environmental adaptation. PMID:29434080

Exploring peptide hormones in plants: identification of four peptide hormone-receptor pairs and two post-translational modification enzymes.

PubMed

Matsubayashi, Yoshikatsu

2018-01-01

The identification of hormones and their receptors in multicellular organisms is one of the most exciting research areas and has lead to breakthroughs in understanding how their growth and development are regulated. In particular, peptide hormones offer advantages as cell-to-cell signals in that they can be synthesized rapidly and have the greatest diversity in their structure and function. Peptides often undergo post-translational modifications and proteolytic processing to generate small oligopeptide hormones. In plants, such small post-translationally modified peptides constitute the largest group of peptide hormones. We initially explored this type of peptide hormone using bioassay-guided fractionation and later by in silico gene screening coupled with biochemical peptide detection, which led to the identification of four types of novel peptide hormones in plants. We also identified specific receptors for these peptides and transferases required for their post-translational modification. This review summarizes how we discovered these peptide hormone-receptor pairs and post-translational modification enzymes, and how these molecules function in plant growth, development and environmental adaptation.

Rapid Identification of Staphylococcus aureus Directly from Blood Cultures by Fluorescence In Situ Hybridization with Peptide Nucleic Acid Probes

PubMed Central

Oliveira, Kenneth; Procop, Gary W.; Wilson, Deborah; Coull, James; Stender, Henrik

2002-01-01

A new fluorescence in situ hybridization (FISH) method with peptide nucleic acid (PNA) probes for identification of Staphylococcus aureus directly from positive blood culture bottles that contain gram-positive cocci in clusters (GPCC) is described. The test (the S. aureus PNA FISH assay) is based on a fluorescein-labeled PNA probe that targets a species-specific sequence of the 16S rRNA of S. aureus. Evaluations with 17 reference strains and 48 clinical isolates, including methicillin-resistant and methicillin-susceptible S. aureus species, coagulase-negative Staphylococcus species, and other clinically relevant and phylogenetically related bacteria and yeast species, showed that the assay had 100% sensitivity and 96% specificity. Clinical trials with 87 blood cultures positive for GPCC correctly identified 36 of 37 (97%) of the S. aureus-positive cultures identified by standard microbiological methods. The positive and negative predictive values were 100 and 98%, respectively. It is concluded that this rapid method (2.5 h) for identification of S. aureus directly from blood culture bottles that contain GPCC offers important information for optimal antibiotic therapy. PMID:11773123

Identification of novel peptides for horse meat speciation in highly processed foodstuffs.

PubMed

Claydon, Amy J; Grundy, Helen H; Charlton, Adrian J; Romero, M Rosario

2015-01-01

There is a need for robust analytical methods to support enforcement of food labelling legislation. Proteomics is emerging as a complementary methodology to existing tools such as DNA and antibody-based techniques. Here we describe the development of a proteomics strategy for the determination of meat species in highly processed foods. A database of specific peptides for nine relevant animal species was used to enable semi-targeted species determination. This principle was tested for horse meat speciation, and a range of horse-specific peptides were identified as heat stable marker peptides for the detection of low levels of horse meat in mixtures with other species.

Isolation and identification of a cardioactive peptide from Tenebrio molitor and Spodoptera eridania.

PubMed

Furuya, K; Liao, S; Reynolds, S E; Ota, R B; Hackett, M; Schooley, D A

1993-12-01

We isolated several cardioactive peptides from extracts of whole heads of the mealworm, Tenebrio molitor, and the southern armyworm, Spodoptera eridania, using a semi-isolated heart of Manduca sexta for bioassay. We have now isolated from each species the peptide with the strongest effect on rate of contraction of the heart. The peptides were identified using micro Edman sequencing and mass spectrometric methods. This cardioactive peptide has the same primary structure from both species: Pro-Phe-Cys-Asn-Ala-Phe-Thr-Gly-Cys-NH2, a cyclic nonapeptide which is identical to crustacean cardioactive peptide (CCAP) originally isolated from the shore crab, Carcinus maenas, and subsequently isolated from Locusta migratoria and Manduca sexta. This is additional evidence that CCAP has widespread occurrence in arthropoda.

Improving sensitivity in proteome studies by analysis of false discovery rates for multiple search engines.

PubMed

Jones, Andrew R; Siepen, Jennifer A; Hubbard, Simon J; Paton, Norman W

2009-03-01

LC-MS experiments can generate large quantities of data, for which a variety of database search engines are available to make peptide and protein identifications. Decoy databases are becoming widely used to place statistical confidence in result sets, allowing the false discovery rate (FDR) to be estimated. Different search engines produce different identification sets so employing more than one search engine could result in an increased number of peptides (and proteins) being identified, if an appropriate mechanism for combining data can be defined. We have developed a search engine independent score, based on FDR, which allows peptide identifications from different search engines to be combined, called the FDR Score. The results demonstrate that the observed FDR is significantly different when analysing the set of identifications made by all three search engines, by each pair of search engines or by a single search engine. Our algorithm assigns identifications to groups according to the set of search engines that have made the identification, and re-assigns the score (combined FDR Score). The combined FDR Score can differentiate between correct and incorrect peptide identifications with high accuracy, allowing on average 35% more peptide identifications to be made at a fixed FDR than using a single search engine.

Mass Spectrometry Imaging and Identification of Peptides Associated with Cephalic Ganglia Regeneration in Schmidtea mediterranea*

PubMed Central

Ong, Ta-Hsuan; Romanova, Elena V.; Roberts-Galbraith, Rachel H.; Yang, Ning; Zimmerman, Tyler A.; Collins, James J.; Lee, Ji Eun; Kelleher, Neil L.; Newmark, Phillip A.; Sweedler, Jonathan V.

2016-01-01

Tissue regeneration is a complex process that involves a mosaic of molecules that vary spatially and temporally. Insights into the chemical signaling underlying this process can be achieved with a multiplex and untargeted chemical imaging method such as mass spectrometry imaging (MSI), which can enable de novo studies of nervous system regeneration. A combination of MSI and multivariate statistics was used to differentiate peptide dynamics in the freshwater planarian flatworm Schmidtea mediterranea at different time points during cephalic ganglia regeneration. A protocol was developed to make S. mediterranea tissues amenable for MSI. MS ion images of planarian tissue sections allow changes in peptides and unknown compounds to be followed as a function of cephalic ganglia regeneration. In conjunction with fluorescence imaging, our results suggest that even though the cephalic ganglia structure is visible after 6 days of regeneration, the original chemical composition of these regenerated structures is regained only after 12 days. Differences were observed in many peptides, such as those derived from secreted peptide 4 and EYE53-1. Peptidomic analysis further identified multiple peptides from various known prohormones, histone proteins, and DNA- and RNA-binding proteins as being associated with the regeneration process. Mass spectrometry data also facilitated the identification of a new prohormone, which we have named secreted peptide prohormone 20 (SPP-20), and is up-regulated during regeneration in planarians. PMID:26884331

Identification of lanthanum-specific peptides for future recycling of rare earth elements from compact fluorescent lamps.

PubMed

Lederer, Franziska L; Curtis, Susan B; Bachmann, Stefanie; Dunbar, W Scott; MacGillivray, Ross T A

2017-05-01

As components of electronic scrap, rare earth minerals are an interesting but little used source of raw materials that are highly important for the recycling industry. Currently, there exists no cost-efficient technology to separate rare earth minerals from an electronic scrap mixture. In this study, phage surface display has been used as a key method to develop peptides with high specificity for particular inorganic targets in electronic scrap. Lanthanum phosphate doped with cerium and terbium as part of the fluorescent phosphors of spent compact fluorescent lamps (CFL) was used as a target material of economic interest to test the suitability of the phage display method to the separation of rare earth minerals. One random pVIII phage library was screened for peptide sequences that bind specifically to the fluorescent phosphor LaPO 4 :Ce 3+ ,Tb 3+ (LAP). The library contained at least 100 binding pVIII peptides per phage particle with a diversity of 1 × 10 9 different phage per library. After three rounds of enrichment, a phage clone containing the surface peptide loop RCQYPLCS was found to bind specifically to LAP. Specificity and affinity of the identified phage bound peptide was confirmed by using binding and competition assays, immunofluorescence assays, and zeta potential measurements. Binding and immunofluorescence assays identified the peptide's affinity for the fluorescent phosphor components CAT (CeMgAl 11 O 19 :Tb 3+ ) and BAM (BaMgAl 10 O 17 :Eu 2+ ). No affinity was found for other fluorescent phosphor components such as YOX (Y 2 O 3 :Eu 3+ ). The binding specificity of the RCQYPLCS peptide loop was improved 3-51-fold by using alanine scanning mutagenesis. The identification of peptides with high specificity and affinity for special components in the fluorescent phosphor in CFLs provides a potentially new strategic approach to rare earth recycling. Biotechnol. Bioeng. 2017;114: 1016-1024. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

PubMed

Kundu, Kousik; Backofen, Rolf

2017-01-01

Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

Mapping the tumour human leukocyte antigen (HLA) ligandome by mass spectrometry.

PubMed

Freudenmann, Lena Katharina; Marcu, Ana; Stevanović, Stefan

2018-07-01

The entirety of human leukocyte antigen (HLA)-presented peptides is referred to as the HLA ligandome of a cell or tissue, in tumours often termed immunopeptidome. Mapping the tumour immunopeptidome by mass spectrometry (MS) comprehensively views the pathophysiologically relevant antigenic signature of human malignancies. MS is an unbiased approach stringently filtering the candidates to be tested as opposed to epitope prediction algorithms. In the setting of peptide-specific immunotherapies, MS-based strategies significantly diminish the risk of lacking clinical benefit, as they yield highly enriched amounts of truly presented peptides. Early immunopeptidomic efforts were severely limited by technical sensitivity and manual spectra interpretation. The technological progress with development of orbitrap mass analysers and enhanced chromatographic performance led to vast improvements in mass accuracy, sensitivity, resolution, and speed. Concomitantly, bioinformatic tools were developed to process MS data, integrate sequencing results, and deconvolute multi-allelic datasets. This enabled the immense advancement of tumour immunopeptidomics. Studying the HLA-presented peptide repertoire bears high potential for both answering basic scientific questions and translational application. Mapping the tumour HLA ligandome has started to significantly contribute to target identification for the design of peptide-specific cancer immunotherapies in clinical trials and compassionate need treatments. In contrast to prediction algorithms, rare HLA allotypes and HLA class II can be adequately addressed when choosing MS-guided target identification platforms. Herein, we review the identification of tumour HLA ligands focusing on sources, methods, bioinformatic data analysis, translational application, and provide an outlook on future developments. © 2018 John Wiley & Sons Ltd.

Enrichment of low-molecular-weight proteins from biofluids for biomarker discovery.

PubMed

Chertov, Oleg; Simpson, John T; Biragyn, Arya; Conrads, Thomas P; Veenstra, Timothy D; Fisher, Robert J

2005-01-01

The dramatic progress in mass spectrometry-based methods of protein identification has triggered a new quest for disease-associated biomarkers. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and its variant surface-enhanced laser desorption/ionization mass spectrometry, provide effective means to explore the less studied information slice of the human serum proteome -- low-molecular-weight proteins and peptides. These low-molecular-weight proteins and peptides are promising for the detection of important biomarkers. Due to the significant experimental problems imposed by high-abundance and high-molecular-weight proteins, it is important to effectively remove these species prior to mass spectrometry analysis of the low-molecular-weight serum and plasma proteomes. In this review, the advantages afforded by recently introduced methods for prefractionation of serum, as they pertain to the detection and identification of biomarkers, will be discussed.

SATPdb: a database of structurally annotated therapeutic peptides

PubMed Central

Singh, Sandeep; Chaudhary, Kumardeep; Dhanda, Sandeep Kumar; Bhalla, Sherry; Usmani, Salman Sadullah; Gautam, Ankur; Tuknait, Abhishek; Agrawal, Piyush; Mathur, Deepika; Raghava, Gajendra P.S.

2016-01-01

SATPdb (http://crdd.osdd.net/raghava/satpdb/) is a database of structurally annotated therapeutic peptides, curated from 22 public domain peptide databases/datasets including 9 of our own. The current version holds 19192 unique experimentally validated therapeutic peptide sequences having length between 2 and 50 amino acids. It covers peptides having natural, non-natural and modified residues. These peptides were systematically grouped into 10 categories based on their major function or therapeutic property like 1099 anticancer, 10585 antimicrobial, 1642 drug delivery and 1698 antihypertensive peptides. We assigned or annotated structure of these therapeutic peptides using structural databases (Protein Data Bank) and state-of-the-art structure prediction methods like I-TASSER, HHsearch and PEPstrMOD. In addition, SATPdb facilitates users in performing various tasks that include: (i) structure and sequence similarity search, (ii) peptide browsing based on their function and properties, (iii) identification of moonlighting peptides and (iv) searching of peptides having desired structure and therapeutic activities. We hope this database will be useful for researchers working in the field of peptide-based therapeutics. PMID:26527728

Detection of co-eluted peptides using database search methods

PubMed Central

Alves, Gelio; Ogurtsov, Aleksey Y; Kwok, Siwei; Wu, Wells W; Wang, Guanghui; Shen, Rong-Fong; Yu, Yi-Kuo

2008-01-01

Background Current experimental techniques, especially those applying liquid chromatography mass spectrometry, have made high-throughput proteomic studies possible. The increase in throughput however also raises concerns on the accuracy of identification or quantification. Most experimental procedures select in a given MS scan only a few relatively most intense parent ions, each to be fragmented (MS2) separately, and most other minor co-eluted peptides that have similar chromatographic retention times are ignored and their information lost. Results We have computationally investigated the possibility of enhancing the information retrieval during a given LC/MS experiment by selecting the two or three most intense parent ions for simultaneous fragmentation. A set of spectra is created via superimposing a number of MS2 spectra, each can be identified by all search methods tested with high confidence, to mimick the spectra of co-eluted peptides. The generated convoluted spectra were used to evaluate the capability of several database search methods – SEQUEST, Mascot, X!Tandem, OMSSA, and RAId_DbS – in identifying true peptides from superimposed spectra of co-eluted peptides. We show that using these simulated spectra, all the database search methods will gain eventually in the number of true peptides identified by using the compound spectra of co-eluted peptides. Open peer review Reviewed by Vlad Petyuk (nominated by Arcady Mushegian), King Jordan and Shamil Sunyaev. For the full reviews, please go to the Reviewers' comments section. PMID:18597684

BiodMHC: an online server for the prediction of MHC class II-peptide binding affinity.

PubMed

Wang, Lian; Pan, Danling; Hu, Xihao; Xiao, Jinyu; Gao, Yangyang; Zhang, Huifang; Zhang, Yan; Liu, Juan; Zhu, Shanfeng

2009-05-01

Effective identification of major histocompatibility complex (MHC) molecules restricted peptides is a critical step in discovering immune epitopes. Although many online servers have been built to predict class II MHC-peptide binding affinity, they have been trained on different datasets, and thus fail in providing a unified comparison of various methods. In this paper, we present our implementation of seven popular predictive methods, namely SMM-align, ARB, SVR-pairwise, Gibbs sampler, ProPred, LP-top2, and MHCPred, on a single web server named BiodMHC (http://biod.whu.edu.cn/BiodMHC/index.html, the software is available upon request). Using a standard measure of AUC (Area Under the receiver operating characteristic Curves), we compare these methods by means of not only cross validation but also prediction on independent test datasets. We find that SMM-align, ProPred, SVR-pairwise, ARB, and Gibbs sampler are the five best-performing methods. For the binding affinity prediction of class II MHC-peptide, BiodMHC provides a convenient online platform for researchers to obtain binding information simultaneously using various methods.

Site-specific N-glycosylation analysis: matrix-assisted laser desorption/ionization quadrupole-quadrupole time-of-flight tandem mass spectral signatures for recognition and identification of glycopeptides.

PubMed

Krokhin, Oleg; Ens, Werner; Standing, Kenneth G; Wilkins, John; Perreault, Hélène

2004-01-01

The identification of glycosylation sites in proteins is often possible through a combination of proteolytic digestion, separation, mass spectrometry (MS) and tandem MS (MS/MS). Liquid chromatography (LC) in combination with MS/MS has been a reliable method for detecting glycopeptides in digestion mixtures, and for assigning glycosylation sites and glycopeptide sequences. Direct interfacing of LC with MS relies on electrospray ionization, which produces ions with two, three or four charges for most proteolytic peptides and glycopeptides. MS/MS spectra of such glycopeptide ions often lead to ambiguous interpretation if deconvolution to the singly charged level is not used. In contrast, the matrix-assisted laser desorption/ionization (MALDI) technique usually produces singly charged peptide and glycopeptide ions. These ions require an extended m/z range, as provided by the quadrupole-quadrupole time-of-flight (QqTOF) instrument used in these experiments, but the main advantages of studying singly charged ions are the simplicity and consistency of the MS/MS spectra. A first aim of the present study is to develop methods to recognize and use glycopeptide [M+H]+ ions as precursors for MS/MS, and thus for glycopeptide/glycoprotein identification as part of wider proteomics studies. Secondly, this article aims at demonstrating the usefulness of MALDI-MS/MS spectra of N-glycopeptides. Mixtures of diverse types of proteins, obtained commercially, were prepared and subjected to reduction, alkylation and tryptic digestion. Micro-column reversed-phase separation allowed deposition of several fractions on MALDI plates, followed by MS and MS/MS analysis of all peptides. Glycopeptide fractions were identified after MS by their specific m/z spacing patterns (162, 203, 291 u) between glycoforms, and then analyzed by MS/MS. In most cases, MS/MS spectra of [M+H]+ ions of glycopeptides featured peaks useful for determining sugar composition, peptide sequence, and thus probable glycosylation site. Peptide-related product ions could be used in database search procedures and allowed the identification of the glycoproteins. Copyright 2004 John Wiley & Sons, Ltd.

Next-generation ELISA diagnostic assay for Chagas Disease based on the combination of short peptidic epitopes

PubMed Central

Volcovich, Romina; Altcheh, Jaime; Bracamonte, Estefanía; Marco, Jorge D.; Nielsen, Morten; Buscaglia, Carlos A.

2017-01-01

Chagas Disease, caused by the protozoan Trypanosoma cruzi, is a major health and economic problem in Latin America for which no vaccine or appropriate drugs for large-scale public health interventions are yet available. Accurate diagnosis is essential for the early identification and follow up of vector-borne cases and to prevent transmission of the disease by way of blood transfusions and organ transplantation. Diagnosis is routinely performed using serological methods, some of which require the production of parasite lysates, parasite antigenic fractions or purified recombinant antigens. Although available serological tests give satisfactory results, the production of reliable reagents remains laborious and expensive. Short peptides spanning linear B-cell epitopes have proven ideal serodiagnostic reagents in a wide range of diseases. Recently, we have conducted a large-scale screening of T. cruzi linear B-cell epitopes using high-density peptide chips, leading to the identification of several hundred novel sequence signatures associated to chronic Chagas Disease. Here, we performed a serological assessment of 27 selected epitopes and of their use in a novel multipeptide-based diagnostic method. A combination of 7 of these peptides were finally evaluated in ELISA format against a panel of 199 sera samples (Chagas-positive and negative, including sera from Leishmaniasis-positive subjects). The multipeptide formulation displayed a high diagnostic performance, with a sensitivity of 96.3% and a specificity of 99.15%. Therefore, the use of synthetic peptides as diagnostic tools are an attractive alternative in Chagas’ disease diagnosis. PMID:28991925

Novel T-cell epitopes of ovalbumin in BALB/c mouse: Potential for peptide-immunotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Marie; Mine, Yoshinori

The identification of food allergen T-cell epitopes provides a platform for the development of novel immunotherapies. Despite extensive knowledge of the physicochemical properties of hen ovalbumin (OVA), a major egg allergen, the complete T-cell epitope map of OVA has surprisingly not been defined in the commonly used BALB/c mouse model. In this study, spleen cells obtained from OVA-sensitized mice were incubated in the presence of 12-mer overlapping synthetic peptides, constructed using the SPOTS synthesis method. Proliferative activity was assessed by 72-h in vitro assays with use of the tetrazolium salt WST-1 and led to identification of four mitogenic sequences, i.e.,more » A39R50, S147R158, K263E274, and A329E340. ELISA analyses of interferon (IFN)-{gamma} and interleukin (IL)-4 productions in cell culture supernatants upon stimulation with increasing concentrations of peptides confirmed their immunogenicity. Knowledge of the complete T-cell epitope map of OVA opens the way to a number of experimental investigations, including the exploration of peptide-based immunotherapy.« less

Mixed-Isotope Labeling with LC-IMS-MS for Characterization of Protein–Protein Interactions by Chemical Cross-Linking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merkley, Eric D.; Baker, Erin S.; Crowell, Kevin L.

2013-02-20

Chemical cross-linking of proteins followed by proteolysis and mass spectrometric analysis of the resulting cross-linked peptides can provide insights into protein structure and protein-protein interactions. However, cross-linked peptides are by necessity of low stoichometry and have different physicochemical properties than linear peptides, routine unambiguous identification of the cross-linked peptides has remained difficult. To address this challenge, we demonstrated the use of liquid chromatography and ion mobility separations coupled with mass spectrometry in combination with a heavy-isotope labeling method. The combination of mixed-isotope cross-linking and ion mobility provided unique and easily interpretable spectral multiplet features for the intermolecular cross-linked peptides. Applicationmore » of the method to two different homodimeric proteins - SrfN, a virulence factor from Salmonella Typhimurium and SO_2176, a protein of unknown function from Shewanella oneidensis- revealed several cross-linked peptides from both proteins that were identified with a low false discovery rate (estimated using a decoy approach). A greater number of cross-linked peptides were identified using ion mobility drift time information in the analysis than when the data were summed across the drift time dimension before analysis. The identified cross-linked peptides migrated more quickly in the ion mobility drift tube than the unmodified peptides.« less

Selective enrichment and desalting of hydrophilic peptides using graphene oxide.

PubMed

Jiang, Miao; Qi, Linyu; Liu, Peiru; Wang, Zijun; Duan, Zhigui; Wang, Ying; Liu, Zhonghua; Chen, Ping

2016-08-01

The wide variety and low abundance of peptides in tissue brought great difficulties to the separation and identification of peptides, which is not in favor of the development of peptidomics. RP-HPLC, which could purify small molecules based on their hydrophobicity, has been widely used in the separation and enrichment of peptide due to its fast, good reproducibility and high resolution. However, RP-HPLC requires the instrument and expensive C18 column and its sample capacity is also limited. Recently, graphene oxide has been applied to the adsorption of amino acids. However, the enrichment efficiency and selectivity of graphene oxide for peptides remain unclear. In this study, the adsorption efficiency and selectivity of graphene oxide and RP-C18 matrix were compared on trypsinized α-actin and also on tissue extracts from pituitary gland and hippocampus. For α-actin, there exhibit similar elution peaks for total trypsinized products and those adsorpted by GO and C18 matrix. But peptides adsorbed by GO showed the higher hydrophilic peaks than which adsorbed by C18 matrix. The resulted RP-HPLC profile showed that most of peptides enriched by graphene oxide were eluted at low concentration of organic solvent, while peptides adsorbed by RP-C18 matrix were mostly eluted at relatively high concentration. Moreover, mass spectrometry analysis suggested that, in pituitary sample, there were 495 peptides enriched by graphene oxide, 447 peptides enriched by RP-C18 matrix while in hippocampus sample 333 and 243 peptides respectively. The GRAVY value analysis suggested that the graphene oxide has a stronger adsorption for highly hydrophilic peptides compared to the RP-C18 matrix. Furthermore, the combination of these two methods could notably increase the number of identification peptides but also the number of predicted protein precursors. Our study provided a new thought to the role of graphene oxide during the enrichment of peptides from tissue which should be useful for peptidomics study. Copyright © 2016 Elsevier B.V. All rights reserved.

Extraction and preliminary chemical characterization of the venom of the spider wasp Pepsis decorata (Hymenoptera: Pompilidae).

PubMed

Nolasco, Matheus; Biondi, Ilka; Pimenta, Daniel C; Branco, Alexsandro

2018-04-26

Arthropod venoms may be considered important sources of bioactive molecules; however, technical difficulties, such as venom extraction and homogeneity may impair the biochemical identification of new molecules. In this context, we have developed a method to maintain wasps in captivity that allows the collection of the venom, without use of chemical, mechanical or electrical stimuli. The crude venom was analyzed by RP-HPLC-ESIQ-ToF and 20 peptides were identified by de novo peptide sequencing, among them Eumenine-Mastoparan and a Ponericin-G2-simile peptide. Copyright © 2018. Published by Elsevier Ltd.

Targeted Identification of SUMOylation Sites in Human Proteins Using Affinity Enrichment and Paralog-specific Reporter Ions*

PubMed Central

Lamoliatte, Frederic; Bonneil, Eric; Durette, Chantal; Caron-Lizotte, Olivier; Wildemann, Dirk; Zerweck, Johannes; Wenshuk, Holger; Thibault, Pierre

2013-01-01

Protein modification by small ubiquitin-like modifier (SUMO) modulates the activities of numerous proteins involved in different cellular functions such as gene transcription, cell cycle, and DNA repair. Comprehensive identification of SUMOylated sites is a prerequisite to determine how SUMOylation regulates protein function. However, mapping SUMOylated Lys residues by mass spectrometry (MS) is challenging because of the dynamic nature of this modification, the existence of three functionally distinct human SUMO paralogs, and the large SUMO chain remnant that remains attached to tryptic peptides. To overcome these problems, we created HEK293 cell lines that stably express functional SUMO paralogs with an N-terminal His6-tag and an Arg residue near the C terminus that leave a short five amino acid SUMO remnant upon tryptic digestion. We determined the fragmentation patterns of our short SUMO remnant peptides by collisional activation and electron transfer dissociation using synthetic peptide libraries. Activation using higher energy collisional dissociation on the LTQ-Orbitrap Elite identified SUMO paralog-specific fragment ions and neutral losses of the SUMO remnant with high mass accuracy (< 5 ppm). We exploited these features to detect SUMO modified tryptic peptides in complex cell extracts by correlating mass measurements of precursor and fragment ions using a data independent acquisition method. We also generated bioinformatics tools to retrieve MS/MS spectra containing characteristic fragment ions to the identification of SUMOylated peptide by conventional Mascot database searches. In HEK293 cell extracts, this MS approach uncovered low abundance SUMOylated peptides and 37 SUMO3-modified Lys residues in target proteins, most of which were previously unknown. Interestingly, we identified mixed SUMO-ubiquitin chains with ubiquitylated SUMO proteins (K20 and K32) and SUMOylated ubiquitin (K63), suggesting a complex crosstalk between these two modifications. PMID:23750026

Peptide immunisation of HLA-DR-transgenic mice permits the identification of a novel HLA-DRbeta1*0101- and HLA-DRbeta1*0401-restricted epitope from p53.

PubMed

Rojas, José Manuel; McArdle, Stephanie E B; Horton, Roger B V; Bell, Matthew; Mian, Shahid; Li, Geng; Ali, Selman A; Rees, Robert C

2005-03-01

Because of the central role of CD4(+) T cells in antitumour immunity, the identification of the MHC class II-restricted peptides to which CD4(+) T cells respond has become a priority of tumour immunologists. Here, we describe a strategy permitting us to rapidly determine the immunogenicity of candidate HLA-DR-restricted peptides using peptide immunisation of HLA-DR-transgenic mice, followed by assessment of the response in vitro. This strategy was successfully applied to the reported haemaglutinin influenza peptide HA(307-319), and then extended to three candidate HLA-DR-restricted p53 peptides predicted by the evidence-based algorithm SYFPEITHI to bind to HLA-DRbeta1*0101 (HLA-DR1) and HLA-DRbeta1*0401 (HLA-DR4) molecules. One of these peptides, p53(108-122), consistently induced responses in HLA-DR1- and in HLA-DR4-transgenic mice. Moreover, this peptide was naturally processed by dendritic cells (DCs), and induced specific proliferation in the splenocytes of mice immunised with p53 cDNA, demonstrating that immune responses could be naturally mounted to the peptide. Furthermore, p53(108-122) peptide was also immunogenic in HLA-DR1 and HLA-DR4 healthy donors. Thus, the use of this transgenic model permitted the identification of a novel HLA-DR-restricted epitope from p53 and constitutes an attractive approach for the rapid identification of novel immunogenic MHC class II-restricted peptides from tumour antigens, which can ultimately be incorporated in immunotherapeutic protocols.

Separomics applied to the proteomics and peptidomics of low-abundance proteins: Choice of methods and challenges - A review.

PubMed

Baracat-Pereira, Maria Cristina; de Oliveira Barbosa, Meire; Magalhães, Marcos Jorge; Carrijo, Lanna Clicia; Games, Patrícia Dias; Almeida, Hebréia Oliveira; Sena Netto, José Fabiano; Pereira, Matheus Rodrigues; de Barros, Everaldo Gonçalves

2012-06-01

The enrichment and isolation of proteins are considered limiting steps in proteomic studies. Identification of proteins whose expression is transient, those that are of low-abundance, and of natural peptides not described in databases, is still a great challenge. Plant extracts are in general complex, and contaminants interfere with the identification of proteins involved in important physiological processes, such as plant defense against pathogens. This review discusses the challenges and strategies of separomics applied to the identification of low-abundance proteins and peptides in plants, especially in plants challenged by pathogens. Separomics is described as a group of methodological strategies for the separation of protein molecules for proteomics. Several tools have been used to remove highly abundant proteins from samples and also non-protein contaminants. The use of chromatographic techniques, the partition of the proteome into subproteomes, and an effort to isolate proteins in their native form have allowed the isolation and identification of rare proteins involved in different processes.

Separomics applied to the proteomics and peptidomics of low-abundance proteins: Choice of methods and challenges – A review

PubMed Central

Baracat-Pereira, Maria Cristina; de Oliveira Barbosa, Meire; Magalhães, Marcos Jorge; Carrijo, Lanna Clicia; Games, Patrícia Dias; Almeida, Hebréia Oliveira; Sena Netto, José Fabiano; Pereira, Matheus Rodrigues; de Barros, Everaldo Gonçalves

2012-01-01

The enrichment and isolation of proteins are considered limiting steps in proteomic studies. Identification of proteins whose expression is transient, those that are of low-abundance, and of natural peptides not described in databases, is still a great challenge. Plant extracts are in general complex, and contaminants interfere with the identification of proteins involved in important physiological processes, such as plant defense against pathogens. This review discusses the challenges and strategies of separomics applied to the identification of low-abundance proteins and peptides in plants, especially in plants challenged by pathogens. Separomics is described as a group of methodological strategies for the separation of protein molecules for proteomics. Several tools have been used to remove highly abundant proteins from samples and also non-protein contaminants. The use of chromatographic techniques, the partition of the proteome into subproteomes, and an effort to isolate proteins in their native form have allowed the isolation and identification of rare proteins involved in different processes. PMID:22802713

High-Density Peptide Arrays for Malaria Vaccine Development.

PubMed

Loeffler, Felix F; Pfeil, Johannes; Heiss, Kirsten

2016-01-01

The development of an efficacious and practicable vaccine conferring sterile immunity towards a Plasmodium infection represents a not yet achieved goal. A crucial factor for the impact of a given anti-plasmodial subunit vaccine is the identification of the most potent parasitic components required to induce protection from both infection and disease. Here, we present a method based on a novel high-density peptide array technology that allows for a flexible readout of malaria antibodies. Peptide arrays applied as a screening method can be used to identify novel immunogenic antibody epitopes under a large number of potential antigens/peptides. Ultimately, discovered antigen candidates and/or epitope sequences can be translated into vaccine prototype design. The technology can be further utilized to unravel antibody-mediated immune responses (e.g., involved in the establishment of semi-immunity) and moreover to confirm vaccine potency during the process of clinical development by verifying the induced antibody responses following vaccination.

A large synthetic peptide and phosphopeptide reference library for mass spectrometry-based proteomics.

PubMed

Marx, Harald; Lemeer, Simone; Schliep, Jan Erik; Matheron, Lucrece; Mohammed, Shabaz; Cox, Jürgen; Mann, Matthias; Heck, Albert J R; Kuster, Bernhard

2013-06-01

We present a peptide library and data resource of >100,000 synthetic, unmodified peptides and their phosphorylated counterparts with known sequences and phosphorylation sites. Analysis of the library by mass spectrometry yielded a data set that we used to evaluate the merits of different search engines (Mascot and Andromeda) and fragmentation methods (beam-type collision-induced dissociation (HCD) and electron transfer dissociation (ETD)) for peptide identification. We also compared the sensitivities and accuracies of phosphorylation-site localization tools (Mascot Delta Score, PTM score and phosphoRS), and we characterized the chromatographic behavior of peptides in the library. We found that HCD identified more peptides and phosphopeptides than did ETD, that phosphopeptides generally eluted later from reversed-phase columns and were easier to identify than unmodified peptides and that current computational tools for proteomics can still be substantially improved. These peptides and spectra will facilitate the development, evaluation and improvement of experimental and computational proteomic strategies, such as separation techniques and the prediction of retention times and fragmentation patterns.

MALDI versus ESI: The Impact of the Ion Source on Peptide Identification.

PubMed

Nadler, Wiebke Maria; Waidelich, Dietmar; Kerner, Alexander; Hanke, Sabrina; Berg, Regina; Trumpp, Andreas; Rösli, Christoph

2017-03-03

For mass spectrometry-based proteomic analyses, electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) are the commonly used ionization techniques. To investigate the influence of the ion source on peptide detection in large-scale proteomics, an optimized GeLC/MS workflow was developed and applied either with ESI/MS or with MALDI/MS for the proteomic analysis of different human cell lines of pancreatic origin. Statistical analysis of the resulting data set with more than 72 000 peptides emphasized the complementary character of the two methods, as the percentage of peptides identified with both approaches was as low as 39%. Significant differences between the resulting peptide sets were observed with respect to amino acid composition, charge-related parameters, hydrophobicity, and modifications of the detected peptides and could be linked to factors governing the respective ion yields in ESI and MALDI.

Improving automatic peptide mass fingerprint protein identification by combining many peak sets.

PubMed

Rögnvaldsson, Thorsteinn; Häkkinen, Jari; Lindberg, Claes; Marko-Varga, György; Potthast, Frank; Samuelsson, Jim

2004-08-05

An automated peak picking strategy is presented where several peak sets with different signal-to-noise levels are combined to form a more reliable statement on the protein identity. The strategy is compared against both manual peak picking and industry standard automated peak picking on a set of mass spectra obtained after tryptic in gel digestion of 2D-gel samples from human fetal fibroblasts. The set of spectra contain samples ranging from strong to weak spectra, and the proposed multiple-scale method is shown to be much better on weak spectra than the industry standard method and a human operator, and equal in performance to these on strong and medium strong spectra. It is also demonstrated that peak sets selected by a human operator display a considerable variability and that it is impossible to speak of a single "true" peak set for a given spectrum. The described multiple-scale strategy both avoids time-consuming parameter tuning and exceeds the human operator in protein identification efficiency. The strategy therefore promises reliable automated user-independent protein identification using peptide mass fingerprints.

MapReduce implementation of a hybrid spectral library-database search method for large-scale peptide identification.

PubMed

Kalyanaraman, Ananth; Cannon, William R; Latt, Benjamin; Baxter, Douglas J

2011-11-01

A MapReduce-based implementation called MR-MSPolygraph for parallelizing peptide identification from mass spectrometry data is presented. The underlying serial method, MSPolygraph, uses a novel hybrid approach to match an experimental spectrum against a combination of a protein sequence database and a spectral library. Our MapReduce implementation can run on any Hadoop cluster environment. Experimental results demonstrate that, relative to the serial version, MR-MSPolygraph reduces the time to solution from weeks to hours, for processing tens of thousands of experimental spectra. Speedup and other related performance studies are also reported on a 400-core Hadoop cluster using spectral datasets from environmental microbial communities as inputs. The source code along with user documentation are available on http://compbio.eecs.wsu.edu/MR-MSPolygraph. ananth@eecs.wsu.edu; william.cannon@pnnl.gov. Supplementary data are available at Bioinformatics online.

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks*

PubMed Central

Bandeira, Nuno

2016-01-01

Peptide and protein identification remains challenging in organisms with poorly annotated or rapidly evolving genomes, as are commonly encountered in environmental or biofuels research. Such limitations render tandem mass spectrometry (MS/MS) database search algorithms ineffective as they lack corresponding sequences required for peptide-spectrum matching. We address this challenge with the spectral networks approach to (1) match spectra of orthologous peptides across multiple related species and then (2) propagate peptide annotations from identified to unidentified spectra. We here present algorithms to assess the statistical significance of spectral alignments (Align-GF), reduce the impurity in spectral networks, and accurately estimate the error rate in propagated identifications. Analyzing three related Cyanothece species, a model organism for biohydrogen production, spectral networks identified peptides from highly divergent sequences from networks with dozens of variant peptides, including thousands of peptides in species lacking a sequenced genome. Our analysis further detected the presence of many novel putative peptides even in genomically characterized species, thus suggesting the possibility of gaps in our understanding of their proteomic and genomic expression. A web-based pipeline for spectral networks analysis is available at http://proteomics.ucsd.edu/software. PMID:27609420

The presence of food-derived collagen peptides in human body-structure and biological activity.

PubMed

Sato, Kenji

2017-12-13

It has been demonstrated that the ingestion of some protein hydrolysates exerts health-promoting effects. For understanding the underlying mechanisms responsible for these effects, the identification of bioactive peptides in the target organ is crucial. For this purpose, in vitro activity-guided fractionation for peptides in the protein hydrolysate has been performed. However, the peptides in the hydrolysate may be further degraded during digestion. The concentration of the active peptides, which were identified by in vitro activity-guided fractionation, in human blood is frequently very low (nanomolar levels). In contrast, micromolar levels of food-derived collagen peptides are present in human blood. Pro-Hyp, one of the major food-derived collagen peptides, enhances the growth of fibroblasts and synthesis of hyaluronic acid. These observations partially explain the beneficial effects of collagen hydrolysate ingestion on the enhancement of wound healing and improvement in the skin condition. The recent advancement involving liquid chromatography and mass spectrometry coupled with a pre-column derivatization technique has enabled the identification of food-derived peptides at nanomolar levels in the body post-ingestion of protein hydrolysates. Thus, this technique can be used for the identification of bioactive food-derived peptides in the body.

Identification of Crosslinked Peptides after Click-based Enrichment Using Sequential CID and ETD Tandem Mass Spectrometry

PubMed Central

Chowdhury, Saiful M.; Du, Xiuxia; Tolić, Nikola; Wu, Si; Moore, Ronald J.; Mayer, M. Uljana; Smith, Richard D.; Adkins, Joshua N.

2010-01-01

Chemical crosslinking combined with mass spectrometry can be a powerful approach for the identification of protein-protein interactions and for providing constraints on protein structures. However, enrichment of crosslinked peptides is crucial to reduce sample complexity before mass spectrometric analysis. In addition compact crosslinkers are often preferred to provide short spacer lengths, surface accessibility to the protein complexes, and must have reasonable solubility under condition where the native complex structure is stable. In this study, we present a novel compact crosslinker that contains two distinct features: 1) an alkyne tag and 2) a small molecule detection tag (NO2-) to maintain reasonable solubility in water. The alkyne tag enables enrichment of the crosslinked peptide after proteolytic cleavage after coupling of an affinity tag using alkyne-azido click chemistry. Neutral loss of the small NO2- moiety provides a secondary means of detecting crosslinked peptides in MS/MS analyses, providing additional confidence in peptide identifications. We show the labeling efficiency of this crosslinker, which we termed CLIP (Click-enabled Linker for Interacting Proteins) using ubiquitin. The enrichment capability of CLIP is demonstrated for crosslinked ubiquitin in highly complex E. coli cell lysates. Sequential CID-MS/MS and ETD-MS/MS of inter-crosslinked peptides (two peptides connected with a crosslinker) are also demonstrated for improved automated identification of crosslinked peptides. PMID:19496583

Predicted MHC peptide binding promiscuity explains MHC class I 'hotspots' of antigen presentation defined by mass spectrometry eluted ligand data.

PubMed

Jappe, Emma Christine; Kringelum, Jens; Trolle, Thomas; Nielsen, Morten

2018-02-15

Peptides that bind to and are presented by MHC class I and class II molecules collectively make up the immunopeptidome. In the context of vaccine development, an understanding of the immunopeptidome is essential, and much effort has been dedicated to its accurate and cost-effective identification. Current state-of-the-art methods mainly comprise in silico tools for predicting MHC binding, which is strongly correlated with peptide immunogenicity. However, only a small proportion of the peptides that bind to MHC molecules are, in fact, immunogenic, and substantial work has been dedicated to uncovering additional determinants of peptide immunogenicity. In this context, and in light of recent advancements in mass spectrometry (MS), the existence of immunological hotspots has been given new life, inciting the hypothesis that hotspots are associated with MHC class I peptide immunogenicity. We here introduce a precise terminology for defining these hotspots and carry out a systematic analysis of MS and in silico predicted hotspots. We find that hotspots defined from MS data are largely captured by peptide binding predictions, enabling their replication in silico. This leads us to conclude that hotspots, to a great degree, are simply a result of promiscuous HLA binding, which disproves the hypothesis that the identification of hotspots provides novel information in the context of immunogenic peptide prediction. Furthermore, our analyses demonstrate that the signal of ligand processing, although present in the MS data, has very low predictive power to discriminate between MS and in silico defined hotspots. © 2018 John Wiley & Sons Ltd.

Characterization and identification of proteases secreted by Aspergillus fumigatus using free flow electrophoresis and MS.

PubMed

Neustadt, Madlen; Costina, Victor; Kupfahl, Claudio; Buchheidt, Dieter; Eckerskorn, Christoph; Neumaier, Michael; Findeisen, Peter

2009-06-01

Early diagnosis of life-threatening invasive aspergillosis in neutropenic patients remains challenging because current laboratory methods have limited diagnostic sensitivity and/or specificity. Aspergillus species are known to secrete various pathogenetically relevant proteases and the monitoring of their protease activity in serum specimens might serve as a new diagnostic approach.For the characterization and identification of secreted proteases, the culture supernatant of Aspergillus fumigatus was fractionated using free flow electrophoresis (Becton Dickinson). Protease activity of separated fractions was measured using fluorescently labeled reporter peptides. Fractions were also co-incubated in parallel with various protease inhibitors that specifically inhibit a distinct class of proteases e.g. metallo- or cysteine-proteases. Those fractions with high protease activity were further subjected to LC-MS/MS analysis for protease identification. The highest protease activity was measured in fractions with an acidic pH range. The results of the 'inhibitor-panel' gave a clear indication that it is mainly metallo- and serine-proteases that are involved in the degradation of reporter peptides. Furthermore, several proteases were identified that facilitate the optimization of reporter peptides for functional protease profiling as a diagnostic tool for invasive aspergillosis.

Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication

PubMed Central

Gunning, Yvonne; Watson, Andrew D.; Rigby, Neil M.; Philo, Mark; Peazer, Joshua K.; Kemsley, E. Kate

2016-01-01

We describe a simple protocol for identifying and quantifying the two components in binary mixtures of species possessing one or more similar proteins. Central to the method is the identification of 'corresponding proteins' in the species of interest, in other words proteins that are nominally the same but possess species-specific sequence differences. When subject to proteolysis, corresponding proteins will give rise to some peptides which are likewise similar but with species-specific variants. These are 'corresponding peptides'. Species-specific peptides can be used as markers for species determination, while pairs of corresponding peptides permit relative quantitation of two species in a mixture. The peptides are detected using multiple reaction monitoring (MRM) mass spectrometry, a highly specific technique that enables peptide-based species determination even in complex systems. In addition, the ratio of MRM peak areas deriving from corresponding peptides supports relative quantitation. Since corresponding proteins and peptides will, in the main, behave similarly in both processing and in experimental extraction and sample preparation, the relative quantitation should remain comparatively robust. In addition, this approach does not need the standards and calibrations required by absolute quantitation methods. The protocol is described in the context of red meats, which have convenient corresponding proteins in the form of their respective myoglobins. This application is relevant to food fraud detection: the method can detect 1% weight for weight of horse meat in beef. The corresponding protein, corresponding peptide (CPCP) relative quantitation using MRM peak area ratios gives good estimates of the weight for weight composition of a horse plus beef mixture. PMID:27685654

Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication.

PubMed

Gunning, Yvonne; Watson, Andrew D; Rigby, Neil M; Philo, Mark; Peazer, Joshua K; Kemsley, E Kate

2016-09-20

We describe a simple protocol for identifying and quantifying the two components in binary mixtures of species possessing one or more similar proteins. Central to the method is the identification of 'corresponding proteins' in the species of interest, in other words proteins that are nominally the same but possess species-specific sequence differences. When subject to proteolysis, corresponding proteins will give rise to some peptides which are likewise similar but with species-specific variants. These are 'corresponding peptides'. Species-specific peptides can be used as markers for species determination, while pairs of corresponding peptides permit relative quantitation of two species in a mixture. The peptides are detected using multiple reaction monitoring (MRM) mass spectrometry, a highly specific technique that enables peptide-based species determination even in complex systems. In addition, the ratio of MRM peak areas deriving from corresponding peptides supports relative quantitation. Since corresponding proteins and peptides will, in the main, behave similarly in both processing and in experimental extraction and sample preparation, the relative quantitation should remain comparatively robust. In addition, this approach does not need the standards and calibrations required by absolute quantitation methods. The protocol is described in the context of red meats, which have convenient corresponding proteins in the form of their respective myoglobins. This application is relevant to food fraud detection: the method can detect 1% weight for weight of horse meat in beef. The corresponding protein, corresponding peptide (CPCP) relative quantitation using MRM peak area ratios gives good estimates of the weight for weight composition of a horse plus beef mixture.

Peptidomics methods for the identification of peptidase-substrate interactions

PubMed Central

Lone, Anna Mari; Kim, Yun-Gon; Saghatelian, Alan

2013-01-01

Peptidases have important roles in controlling physiological signaling through their regulation of bioactive peptides. Understanding and controlling bioactive peptide regulation is of great biomedical interest and approaches that elucidate the interplay between peptidases and their substrates are vital for achieving this goal. Here, we highlight the utility of recent peptidomics approaches in identifying endogenous substrates of peptidases. These approaches reveal bioactive substrates and help characterize the biochemical functions of the enzyme. Most recently, peptidomics approaches have been applied to address the challenging question of identifying the peptidases responsible for regulating specific bioactive peptides. Since peptidases are of great biomedical interest, these approaches will begin to impact our ability to identify new drug targets that regulate important bioactive peptides. PMID:23332665

Mass spectrometry-based protein identification with accurate statistical significance assignment.

PubMed

Alves, Gelio; Yu, Yi-Kuo

2015-03-01

Assigning statistical significance accurately has become increasingly important as metadata of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of metadata at any level may propagate to downstream analyses, undermining the validity of scientific conclusions thus drawn. From the perspective of mass spectrometry-based proteomics, even though accurate statistics for peptide identification can now be achieved, accurate protein level statistics remain challenging. We have constructed a protein ID method that combines peptide evidences of a candidate protein based on a rigorous formula derived earlier; in this formula the database P-value of every peptide is weighted, prior to the final combination, according to the number of proteins it maps to. We have also shown that this protein ID method provides accurate protein level E-value, eliminating the need of using empirical post-processing methods for type-I error control. Using a known protein mixture, we find that this protein ID method, when combined with the Sorić formula, yields accurate values for the proportion of false discoveries. In terms of retrieval efficacy, the results from our method are comparable with other methods tested. The source code, implemented in C++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Analysis of the endogenous peptide profile of milk: identification of 248 mainly casein-derived peptides.

PubMed

Baum, Florian; Fedorova, Maria; Ebner, Jennifer; Hoffmann, Ralf; Pischetsrieder, Monika

2013-12-06

Milk is an excellent source of bioactive peptides. However, the composition of the native milk peptidome has only been partially elucidated. The present study applied matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) directly or after prefractionation of the milk peptides by reverse-phase high-performance liquid chromatography (RP-HPLC) or OFFGEL fractionation for the comprehensive analysis of the peptide profile of raw milk. The peptide sequences were determined by MALDI-TOF/TOF or nano-ultra-performance liquid chromatography-nanoelectrospray ionization-LTQ-Orbitrap-MS. Direct MALDI-TOF-MS analysis led to the assignment of 57 peptides. Prefractionation by both complementary methods led to the assignment of another 191 peptides. Most peptides originate from α(S1)-casein, followed by β-casein, and α(S2)-casein. κ-Casein and whey proteins seem to play only a minor role as peptide precursors. The formation of many, but not all, peptides could be explained by the activity of the endogenous peptidases, plasmin or cathepsin D, B, and G. Database searches revealed the presence of 22 peptides with established physiological function, including those with angiotensin-converting-enzyme (ACE) inhibitory, immunomodulating, or antimicrobial activity.

Identification of potential serum peptide biomarkers of biliary tract cancer using MALDI MS profiling

PubMed Central

2014-01-01

Background The aim of this discovery study was the identification of peptide serum biomarkers for detecting biliary tract cancer (BTC) using samples from healthy volunteers and benign cases of biliary disease as control groups. This work was based on the hypothesis that cancer-specific exopeptidases exist and that their activities in serum can generate cancer-predictive peptide fragments from circulating proteins during coagulation. Methods This case control study used a semi-automated platform incorporating polypeptide extraction linked to matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to profile 92 patient serum samples. Predictive models were generated to test a validation serum set from BTC cases and healthy volunteers. Results Several peptide peaks were found that could significantly differentiate BTC patients from healthy controls and benign biliary disease. A predictive model resulted in a sensitivity of 100% and a specificity of 93.8% in detecting BTC in the validation set, whilst another model gave a sensitivity of 79.5% and a specificity of 83.9% in discriminating BTC from benign biliary disease samples in the training set. Discriminatory peaks were identified by tandem MS as fragments of abundant clotting proteins. Conclusions Serum MALDI MS peptide signatures can accurately discriminate patients with BTC from healthy volunteers. PMID:24495412

DeMix Workflow for Efficient Identification of Cofragmented Peptides in High Resolution Data-dependent Tandem Mass Spectrometry*

PubMed Central

Zhang, Bo; Pirmoradian, Mohammad; Chernobrovkin, Alexey; Zubarev, Roman A.

2014-01-01

Based on conventional data-dependent acquisition strategy of shotgun proteomics, we present a new workflow DeMix, which significantly increases the efficiency of peptide identification for in-depth shotgun analysis of complex proteomes. Capitalizing on the high resolution and mass accuracy of Orbitrap-based tandem mass spectrometry, we developed a simple deconvolution method of “cloning” chimeric tandem spectra for cofragmented peptides. Additional to a database search, a simple rescoring scheme utilizes mass accuracy and converts the unwanted cofragmenting events into a surprising advantage of multiplexing. With the combination of cloning and rescoring, we obtained on average nine peptide-spectrum matches per second on a Q-Exactive workbench, whereas the actual MS/MS acquisition rate was close to seven spectra per second. This efficiency boost to 1.24 identified peptides per MS/MS spectrum enabled analysis of over 5000 human proteins in single-dimensional LC-MS/MS shotgun experiments with an only two-hour gradient. These findings suggest a change in the dominant “one MS/MS spectrum - one peptide” paradigm for data acquisition and analysis in shotgun data-dependent proteomics. DeMix also demonstrated higher robustness than conventional approaches in terms of lower variation among the results of consecutive LC-MS/MS runs. PMID:25100859

Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography—Tandem Mass Spectrometry

PubMed Central

Tabb, David L.; Vega-Montoto, Lorenzo; Rudnick, Paul A.; Variyath, Asokan Mulayath; Ham, Amy-Joan L.; Bunk, David M.; Kilpatrick, Lisa E.; Billheimer, Dean D.; Blackman, Ronald K.; Cardasis, Helene L.; Carr, Steven A.; Clauser, Karl R.; Jaffe, Jacob D.; Kowalski, Kevin A.; Neubert, Thomas A.; Regnier, Fred E.; Schilling, Birgit; Tegeler, Tony J.; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Fisher, Susan J.; Gibson, Bradford W.; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Stein, Steven E.; Tempst, Paul; Paulovich, Amanda G.; Liebler, Daniel C.; Spiegelman, Cliff

2009-01-01

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35–60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies. PMID:19921851

Automatic poisson peak harvesting for high throughput protein identification.

PubMed

Breen, E J; Hopwood, F G; Williams, K L; Wilkins, M R

2000-06-01

High throughput identification of proteins by peptide mass fingerprinting requires an efficient means of picking peaks from mass spectra. Here, we report the development of a peak harvester to automatically pick monoisotopic peaks from spectra generated on matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) mass spectrometers. The peak harvester uses advanced mathematical morphology and watershed algorithms to first process spectra to stick representations. Subsequently, Poisson modelling is applied to determine which peak in an isotopically resolved group represents the monoisotopic mass of a peptide. We illustrate the features of the peak harvester with mass spectra of standard peptides, digests of gel-separated bovine serum albumin, and with Escherictia coli proteins prepared by two-dimensional polyacrylamide gel electrophoresis. In all cases, the peak harvester proved effective in its ability to pick similar monoisotopic peaks as an experienced human operator, and also proved effective in the identification of monoisotopic masses in cases where isotopic distributions of peptides were overlapping. The peak harvester can be operated in an interactive mode, or can be completely automated and linked through to peptide mass fingerprinting protein identification tools to achieve high throughput automated protein identification.

Global combined precursor isotopic labeling and isobaric tagging (cPILOT) approach with selective MS(3) acquisition.

PubMed

Evans, Adam R; Robinson, Renã A S

2013-11-01

Recently, we reported a novel proteomics quantitation scheme termed "combined precursor isotopic labeling and isobaric tagging (cPILOT)" that allows for the identification and quantitation of nitrated peptides in as many as 12-16 samples in a single experiment. cPILOT offers enhanced multiplexing and posttranslational modification specificity, however excludes global quantitation for all peptides present in a mixture and underestimates reporter ion ratios similar to other isobaric tagging methods due to precursor co-isolation. Here, we present a novel chemical workflow for cPILOT that can be used for global tagging of all peptides in a mixture. Specifically, through low pH precursor dimethylation of tryptic or LysC peptides followed by high pH tandem mass tags, the same reporter ion can be used twice in a single experiment. Also, to improve triple-stage mass spectrometry (MS(3) ) data acquisition, a selective MS(3) method that focuses on product selection of the y1 fragment of lysine-terminated peptides is incorporated into the workflow. This novel cPILOT workflow has potential for global peptide quantitation that could lead to enhanced sample multiplexing and increase the number of quantifiable spectra obtained from MS(3) acquisition methods. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ICPD-a new peak detection algorithm for LC/MS.

PubMed

Zhang, Jianqiu; Haskins, William

2010-12-01

The identification and quantification of proteins using label-free Liquid Chromatography/Mass Spectrometry (LC/MS) play crucial roles in biological and biomedical research. Increasing evidence has shown that biomarkers are often low abundance proteins. However, LC/MS systems are subject to considerable noise and sample variability, whose statistical characteristics are still elusive, making computational identification of low abundance proteins extremely challenging. As a result, the inability of identifying low abundance proteins in a proteomic study is the main bottleneck in protein biomarker discovery. In this paper, we propose a new peak detection method called Information Combining Peak Detection (ICPD ) for high resolution LC/MS. In LC/MS, peptides elute during a certain time period and as a result, peptide isotope patterns are registered in multiple MS scans. The key feature of the new algorithm is that the observed isotope patterns registered in multiple scans are combined together for estimating the likelihood of the peptide existence. An isotope pattern matching score based on the likelihood probability is provided and utilized for peak detection. The performance of the new algorithm is evaluated based on protein standards with 48 known proteins. The evaluation shows better peak detection accuracy for low abundance proteins than other LC/MS peak detection methods.

Seed Storage Proteins as a System for Teaching Protein Identification by Mass Spectrometry in Biochemistry Laboratory

ERIC Educational Resources Information Center

Wilson, Karl A.; Tan-Wilson, Anna

2013-01-01

Mass spectrometry (MS) has become an important tool in studying biological systems. One application is the identification of proteins and peptides by the matching of peptide and peptide fragment masses to the sequences of proteins in protein sequence databases. Often prior protein separation of complex protein mixtures by 2D-PAGE is needed,…

Milk derived bioactive peptides and their impact on human health - A review.

PubMed

Mohanty, D P; Mohapatra, S; Misra, S; Sahu, P S

2016-09-01

Milk-derived bioactive peptides have been identified as potential ingredients of health-promoting functional foods. These bioactive peptides are targeted at diet-related chronic diseases especially the non-communicable diseases viz., obesity, cardiovascular diseases and diabetes. Peptides derived from the milk of cow, goat, sheep, buffalo and camel exert multifunctional properties, including anti-microbial, immune modulatory, anti-oxidant, inhibitory effect on enzymes, anti-thrombotic, and antagonistic activities against various toxic agents. Majority of those regulate immunological, gastrointestinal, hormonal and neurological responses, thereby playing a vital role in the prevention of cancer, osteoporosis, hypertension and other disorders as discussed in this review. For the commercial production of such novel bioactive peptides large scale technologies based on membrane separation and ion exchange chromatography methods have been developed. Separation and identification of those peptides and their pharmacodynamic parameters are necessary to transfer their potent functional properties into food applications. The present review summarizes the preliminary classes of bioactive milk-derived peptides along with their physiological functions, general characteristics and potential applications in health-care.

Binding Modes of Thioflavin T Molecules to Prion Peptide Assemblies Identified by Using Scanning Tunneling Microscopy

PubMed Central

2011-01-01

The widely used method to monitor the aggregation process of amyloid peptide is thioflavin T (ThT) assay, while the detailed molecular mechanism is still not clear. In this work, we report here the direct identification of the binding modes of ThT molecules with the prion peptide GNNQQNY by using scanning tunneling microscopy (STM). The assembly structures of GNNQQNY were first observed by STM on a graphite surface, and the introduction of ThT molecules to the surface facilitated the STM observations of the adsorption conformations of ThT with peptide strands. ThT molecules are apt to adsorb on the peptide assembly with β-sheet structure and oriented parallel with the peptide strands adopting four different binding modes. This effort could benefit the understanding of the mechanisms of the interactions between labeling species or inhibitory ligands and amyloid peptides, which is keenly needed for developing diagnostic and therapeutic approaches. PMID:22778872

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

PubMed Central

Nielsen, Morten; Lundegaard, Claus; Lund, Ole

2007-01-01

Background Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles. Results The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR), we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors. Conclusion The SMM-align method was shown to outperform other state of the art MHC class II prediction methods. The method predicts quantitative peptide:MHC binding affinity values, making it ideally suited for rational epitope discovery. The method has been trained and evaluated on the, to our knowledge, largest benchmark data set publicly available and covers the nine HLA-DR supertypes suggested as well as three mouse H2-IA allele. Both the peptide benchmark data set, and SMM-align prediction method (NetMHCII) are made publicly available. PMID:17608956

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method.

PubMed

Nielsen, Morten; Lundegaard, Claus; Lund, Ole

2007-07-04

Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles. The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR), we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors. The SMM-align method was shown to outperform other state of the art MHC class II prediction methods. The method predicts quantitative peptide:MHC binding affinity values, making it ideally suited for rational epitope discovery. The method has been trained and evaluated on the, to our knowledge, largest benchmark data set publicly available and covers the nine HLA-DR supertypes suggested as well as three mouse H2-IA allele. Both the peptide benchmark data set, and SMM-align prediction method (NetMHCII) are made publicly available.

Binomial probability distribution model-based protein identification algorithm for tandem mass spectrometry utilizing peak intensity information.

PubMed

Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu

2013-01-04

Mass spectrometry has become one of the most important technologies in proteomic analysis. Tandem mass spectrometry (LC-MS/MS) is a major tool for the analysis of peptide mixtures from protein samples. The key step of MS data processing is the identification of peptides from experimental spectra by searching public sequence databases. Although a number of algorithms to identify peptides from MS/MS data have been already proposed, e.g. Sequest, OMSSA, X!Tandem, Mascot, etc., they are mainly based on statistical models considering only peak-matches between experimental and theoretical spectra, but not peak intensity information. Moreover, different algorithms gave different results from the same MS data, implying their probable incompleteness and questionable reproducibility. We developed a novel peptide identification algorithm, ProVerB, based on a binomial probability distribution model of protein tandem mass spectrometry combined with a new scoring function, making full use of peak intensity information and, thus, enhancing the ability of identification. Compared with Mascot, Sequest, and SQID, ProVerB identified significantly more peptides from LC-MS/MS data sets than the current algorithms at 1% False Discovery Rate (FDR) and provided more confident peptide identifications. ProVerB is also compatible with various platforms and experimental data sets, showing its robustness and versatility. The open-source program ProVerB is available at http://bioinformatics.jnu.edu.cn/software/proverb/ .

Identification of Potent ACE Inhibitory Peptides from Wild Almond Proteins.

PubMed

Mirzapour, Mozhgan; Rezaei, Karamatollah; Sentandreu, Miguel Angel

2017-10-01

In this study, the production, fractionation, purification and identification of ACE (angiotensin-I-converting enzyme) inhibitory peptides from wild almond (Amygdalus scoparia) proteins were investigated. Wild almond proteins were hydrolyzed using 5 different enzymes (pepsin, trypsin, chymotrypsin, alcalase and flavourzyme) and assayed for their ACE inhibitory activities. The degree of ACE inhibiting activity obtained after hydrolysis was found to be in the following order: alcalase > chymotrypsin > trypsin/pepsin > flavourzyme. The hydrolysates obtained from alcalase (IC 50 = 0.8 mg/mL) were fractionated by sequential ultrafiltration at 10 and 3 kDa cutoff values and the most active fraction (<3 kDa) was further separated using reversed phase high-performance liquid chromatography (RP-HPLC). Peptide sequence identifications were carried out on highly potential fractions obtained from RP-HPLC by means of liquid chromatography coupled to electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS). Sequencing of ACE inhibitory peptides present in the fraction 26 of RP-HPLC resulted in the identification of 3 peptide sequences (VVNE, VVTR, and VVGVD) not reported previously in the literature. Sequence identification of fractions 40 and 42 from RP-HPLC, which showed the highest ACE inhibitory activities (84.1% and 86.9%, respectively), resulted in the identification of more than 40 potential ACE inhibitory sequences. The results indicate that wild almond protein is a rich source of potential antihypertensive peptides and can be suggested for applications in functional foods and drinks with respect to hindrance and mitigation of hypertension after in vivo assessment. This study has shown the potential of wild almond proteins as good sources for producing ACE-inhibitory active peptides. According to this finding, peptides with higher ACE inhibitory activities could be released during the gastrointestinal digestion and contribute to the health- promoting activities of this natural protein source. © 2017 Institute of Food Technologists®.

Doping control analysis of seven bioactive peptides in horse plasma by liquid chromatography-mass spectrometry.

PubMed

Kwok, Wai Him; Ho, Emmie N M; Lau, Ming Yip; Leung, Gary N W; Wong, April S Y; Wan, Terence S M

2013-03-01

In recent years, there has been an ongoing focus for both human and equine doping control laboratories on developing detection methods to control the misuse of peptide therapeutics. Immunoaffinity purification is a common extraction method to isolate peptides from biological matrices and obtain sufficient detectability in subsequent instrumental analysis. However, monoclonal or polyclonal antibodies for immunoaffinity purification may not be commercially available, and even if available, such antibodies are usually very costly. In our study, a simple mixed-mode anion exchange solid-phase extraction cartridge was employed for the extraction of seven target peptides (GHRP-1, GHRP-2, GHRP-6, ipamorelin, hexarelin, CJC-1295, and N-acetylated LKKTETQ (active ingredient of TB-500)) and their in vitro metabolites from horse plasma. The final extract was subject to ultra-high-performance liquid chromatographic separation and analysed with a hybrid high-resolution mass spectrometer. The limits of detection for all seven peptides were estimated to be less than 50 pg/mL. Method validation was performed with respect to specificity, precision, and recovery. The applicability of this multi-analyte method was demonstrated by the detection of N-acetylated LKKTETQ and its metabolite N-acetylated LK from plasma samples obtained after subcutaneous administration of TB-500 (10 mg N-acetylated LKKTETQ) to two thoroughbred geldings. This method could easily be modified to cover more bioactive peptides, such as dermorphin, β-casomorphin, and desmopressin. With the use of high-resolution mass spectrometry, the full-scan data acquired can also be re-processed retrospectively to search for peptides and their metabolites that have not been targeted at the time of analysis. To our knowledge, this is the first identification of in vitro metabolites of all the studied peptides other than TB-500 in horses.

High-throughput Database Search and Large-scale Negative Polarity Liquid Chromatography–Tandem Mass Spectrometry with Ultraviolet Photodissociation for Complex Proteomic Samples*

PubMed Central

Madsen, James A.; Xu, Hua; Robinson, Michelle R.; Horton, Andrew P.; Shaw, Jared B.; Giles, David K.; Kaoud, Tamer S.; Dalby, Kevin N.; Trent, M. Stephen; Brodbelt, Jennifer S.

2013-01-01

The use of ultraviolet photodissociation (UVPD) for the activation and dissociation of peptide anions is evaluated for broader coverage of the proteome. To facilitate interpretation and assignment of the resulting UVPD mass spectra of peptide anions, the MassMatrix database search algorithm was modified to allow automated analysis of negative polarity MS/MS spectra. The new UVPD algorithms were developed based on the MassMatrix database search engine by adding specific fragmentation pathways for UVPD. The new UVPD fragmentation pathways in MassMatrix were rigorously and statistically optimized using two large data sets with high mass accuracy and high mass resolution for both MS1 and MS2 data acquired on an Orbitrap mass spectrometer for complex Halobacterium and HeLa proteome samples. Negative mode UVPD led to the identification of 3663 and 2350 peptides for the Halo and HeLa tryptic digests, respectively, corresponding to 655 and 645 peptides that were unique when compared with electron transfer dissociation (ETD), higher energy collision-induced dissociation, and collision-induced dissociation results for the same digests analyzed in the positive mode. In sum, 805 and 619 proteins were identified via UVPD for the Halobacterium and HeLa samples, respectively, with 49 and 50 unique proteins identified in contrast to the more conventional MS/MS methods. The algorithm also features automated charge determination for low mass accuracy data, precursor filtering (including intact charge-reduced peaks), and the ability to combine both positive and negative MS/MS spectra into a single search, and it is freely open to the public. The accuracy and specificity of the MassMatrix UVPD search algorithm was also assessed for low resolution, low mass accuracy data on a linear ion trap. Analysis of a known mixture of three mitogen-activated kinases yielded similar sequence coverage percentages for UVPD of peptide anions versus conventional collision-induced dissociation of peptide cations, and when these methods were combined into a single search, an increase of up to 13% sequence coverage was observed for the kinases. The ability to sequence peptide anions and cations in alternating scans in the same chromatographic run was also demonstrated. Because ETD has a significant bias toward identifying highly basic peptides, negative UVPD was used to improve the identification of the more acidic peptides in conjunction with positive ETD for the more basic species. In this case, tryptic peptides from the cytosolic section of HeLa cells were analyzed by polarity switching nanoLC-MS/MS utilizing ETD for cation sequencing and UVPD for anion sequencing. Relative to searching using ETD alone, positive/negative polarity switching significantly improved sequence coverages across identified proteins, resulting in a 33% increase in unique peptide identifications and more than twice the number of peptide spectral matches. PMID:23695934

Efficient marginalization to compute protein posterior probabilities from shotgun mass spectrometry data

PubMed Central

Serang, Oliver; MacCoss, Michael J.; Noble, William Stafford

2010-01-01

The problem of identifying proteins from a shotgun proteomics experiment has not been definitively solved. Identifying the proteins in a sample requires ranking them, ideally with interpretable scores. In particular, “degenerate” peptides, which map to multiple proteins, have made such a ranking difficult to compute. The problem of computing posterior probabilities for the proteins, which can be interpreted as confidence in a protein’s presence, has been especially daunting. Previous approaches have either ignored the peptide degeneracy problem completely, addressed it by computing a heuristic set of proteins or heuristic posterior probabilities, or by estimating the posterior probabilities with sampling methods. We present a probabilistic model for protein identification in tandem mass spectrometry that recognizes peptide degeneracy. We then introduce graph-transforming algorithms that facilitate efficient computation of protein probabilities, even for large data sets. We evaluate our identification procedure on five different well-characterized data sets and demonstrate our ability to efficiently compute high-quality protein posteriors. PMID:20712337

Comprehensive Identification of Glycated Peptides and Their Glycation Motifs in Plasma and Erythrocytes of Control and Diabetic Subjects

PubMed Central

Zhang, Qibin; Monroe, Matthew E.; Schepmoes, Athena A.; Clauss, Therese R. W.; Gritsenko, Marina A.; Meng, Da; Petyuk, Vladislav A.; Smith, Richard D.; Metz, Thomas O.

2011-01-01

Non-enzymatic glycation of proteins sets the stage for formation of advanced glycation end-products and development of chronic complications of diabetes. In this report, we extended our previous methods on proteomics analysis of glycated proteins to comprehensively identify glycated proteins in control and diabetic human plasma and erythrocytes. Using immunodepletion, enrichment, and fractionation strategies, we identified 7749 unique glycated peptides, corresponding to 3742 unique glycated proteins. Semi-quantitative comparisons showed that glycation levels of a number of proteins were significantly increased in diabetes and that erythrocyte proteins were more extensively glycated than plasma proteins. A glycation motif analysis revealed that some amino acids were favored more than others in the protein primary structures in the vicinity of the glycation sites in both sample types. The glycated peptides and corresponding proteins reported here provide a foundation for potential identification of novel markers for diabetes, hyperglycemia, and diabetic complications in future studies. PMID:21612289

Identification of Alternative Splice Variants Using Unique Tryptic Peptide Sequences for Database Searches.

PubMed

Tran, Trung T; Bollineni, Ravi C; Strozynski, Margarita; Koehler, Christian J; Thiede, Bernd

2017-07-07

Alternative splicing is a mechanism in eukaryotes by which different forms of mRNAs are generated from the same gene. Identification of alternative splice variants requires the identification of peptides specific for alternative splice forms. For this purpose, we generated a human database that contains only unique tryptic peptides specific for alternative splice forms from Swiss-Prot entries. Using this database allows an easy access to splice variant-specific peptide sequences that match to MS data. Furthermore, we combined this database without alternative splice variant-1-specific peptides with human Swiss-Prot. This combined database can be used as a general database for searching of LC-MS data. LC-MS data derived from in-solution digests of two different cell lines (LNCaP, HeLa) and phosphoproteomics studies were analyzed using these two databases. Several nonalternative splice variant-1-specific peptides were found in both cell lines, and some of them seemed to be cell-line-specific. Control and apoptotic phosphoproteomes from Jurkat T cells revealed several nonalternative splice variant-1-specific peptides, and some of them showed clear quantitative differences between the two states.

Protein N- and C-Termini Identification Using Mass Spectrometry and Isotopic Labeling

USDA-ARS?s Scientific Manuscript database

A new method for protein N- and C-terminal analysis using mass spectrometry is introduced. A novel stable isotopic labeling scheme has been developed to identify terminal peptides generated from an enzyme digestion for the determination of both N- and C-termini of the protein. This method works dire...

LC-MS/MS Peptide Mapping with Automated Data Processing for Routine Profiling of N-Glycans in Immunoglobulins

NASA Astrophysics Data System (ADS)

Shah, Bhavana; Jiang, Xinzhao Grace; Chen, Louise; Zhang, Zhongqi

2014-06-01

Protein N-Glycan analysis is traditionally performed by high pH anion exchange chromatography (HPAEC), reversed phase liquid chromatography (RPLC), or hydrophilic interaction liquid chromatography (HILIC) on fluorescence-labeled glycans enzymatically released from the glycoprotein. These methods require time-consuming sample preparations and do not provide site-specific glycosylation information. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) peptide mapping is frequently used for protein structural characterization and, as a bonus, can potentially provide glycan profile on each individual glycosylation site. In this work, a recently developed glycopeptide fragmentation model was used for automated identification, based on their MS/MS, of N-glycopeptides from proteolytic digestion of monoclonal antibodies (mAbs). Experimental conditions were optimized to achieve accurate profiling of glycoforms. Glycan profiles obtained from LC-MS/MS peptide mapping were compared with those obtained from HPAEC, RPLC, and HILIC analyses of released glycans for several mAb molecules. Accuracy, reproducibility, and linearity of the LC-MS/MS peptide mapping method for glycan profiling were evaluated. The LC-MS/MS peptide mapping method with fully automated data analysis requires less sample preparation, provides site-specific information, and may serve as an alternative method for routine profiling of N-glycans on immunoglobulins as well as other glycoproteins with simple N-glycans.

Protein Inference from the Integration of Tandem MS Data and Interactome Networks.

PubMed

Zhong, Jiancheng; Wang, Jianxing; Ding, Xiaojun; Zhang, Zhen; Li, Min; Wu, Fang-Xiang; Pan, Yi

2017-01-01

Since proteins are digested into a mixture of peptides in the preprocessing step of tandem mass spectrometry (MS), it is difficult to determine which specific protein a shared peptide belongs to. In recent studies, besides tandem MS data and peptide identification information, some other information is exploited to infer proteins. Different from the methods which first use only tandem MS data to infer proteins and then use network information to refine them, this study proposes a protein inference method named TMSIN, which uses interactome networks directly. As two interacting proteins should co-exist, it is reasonable to assume that if one of the interacting proteins is confidently inferred in a sample, its interacting partners should have a high probability in the same sample, too. Therefore, we can use the neighborhood information of a protein in an interactome network to adjust the probability that the shared peptide belongs to the protein. In TMSIN, a multi-weighted graph is constructed by incorporating the bipartite graph with interactome network information, where the bipartite graph is built with the peptide identification information. Based on multi-weighted graphs, TMSIN adopts an iterative workflow to infer proteins. At each iterative step, the probability that a shared peptide belongs to a specific protein is calculated by using the Bayes' law based on the neighbor protein support scores of each protein which are mapped by the shared peptides. We carried out experiments on yeast data and human data to evaluate the performance of TMSIN in terms of ROC, q-value, and accuracy. The experimental results show that AUC scores yielded by TMSIN are 0.742 and 0.874 in yeast dataset and human dataset, respectively, and TMSIN yields the maximum number of true positives when q-value less than or equal to 0.05. The overlap analysis shows that TMSIN is an effective complementary approach for protein inference.

Identification of Cyclin A Binders with a Fluorescent Peptide Sensor.

PubMed

Pazos, Elena; Mascareñas, José L; Vázquez, M Eugenio

2016-01-01

A peptide sensor that integrates the 4-dimethylaminophthalimide (4-DMAP) fluorophore in a short cyclin A binding sequence displays a large fluorescence emission increase upon interacting with the cyclin A Binding Groove (CBG). Competitive displacement assays of this probe allow the straightforward identification of peptides that interact with the CBG, which could potentially block the recognition of CDK/cyclin A kinase substrates.

Identification of Carboxypeptidase Substrates by C-Terminal COFRADIC.

PubMed

Tanco, Sebastian; Aviles, Francesc Xavier; Gevaert, Kris; Lorenzo, Julia; Van Damme, Petra

2017-01-01

We here present a detailed procedure for studying protein C-termini and their posttranslational modifications by C-terminal COFRADIC. In fact, this procedure can enrich for both C-terminal and N-terminal peptides through a combination of a strong cation exchange fractionation step at low pH, which removes the majority of nonterminal peptides in whole-proteome digests, while the actual COFRADIC step segregates C-terminal peptides from N-terminal peptides. When used in a differential mode, C-terminal COFRADIC allows for the identification of neo-C-termini generated by the action of proteases, which in turn leads to the identification of protease substrates. More specifically, this technology can be applied to determine the natural substrate repertoire of carboxypeptidases on a proteome-wide scale.

Comparative Evaluation of Small Molecular Additives and Their Effects on Peptide/Protein Identification.

PubMed

Gao, Jing; Zhong, Shaoyun; Zhou, Yanting; He, Han; Peng, Shuying; Zhu, Zhenyun; Liu, Xing; Zheng, Jing; Xu, Bin; Zhou, Hu

2017-06-06

Detergents and salts are widely used in lysis buffers to enhance protein extraction from biological samples, facilitating in-depth proteomic analysis. However, these detergents and salt additives must be efficiently removed from the digested samples prior to LC-MS/MS analysis to obtain high-quality mass spectra. Although filter-aided sample preparation (FASP), acetone precipitation (AP), followed by in-solution digestion, and strong cation exchange-based centrifugal proteomic reactors (CPRs) are commonly used for proteomic sample processing, little is known about their efficiencies at removing detergents and salt additives. In this study, we (i) developed an integrative workflow for the quantification of small molecular additives in proteomic samples, developing a multiple reaction monitoring (MRM)-based LC-MS approach for the quantification of six additives (i.e., Tris, urea, CHAPS, SDS, SDC, and Triton X-100) and (ii) systematically evaluated the relationships between the level of additive remaining in samples following sample processing and the number of peptides/proteins identified by mass spectrometry. Although FASP outperformed the other two methods, the results were complementary in terms of peptide/protein identification, as well as the GRAVY index and amino acid distributions. This is the first systematic and quantitative study of the effect of detergents and salt additives on protein identification. This MRM-based approach can be used for an unbiased evaluation of the performance of new sample preparation methods. Data are available via ProteomeXchange under identifier PXD005405.

Offline pentafluorophenyl (PFP)-RP prefractionation as an alternative to high-pH RP for comprehensive LC-MS/MS proteomics and phosphoproteomics.

PubMed

Grassetti, Andrew V; Hards, Rufus; Gerber, Scott A

2017-07-01

Technological advances in liquid chromatography and tandem mass spectrometry (LC-MS/MS) have enabled comprehensive analyses of proteins and their post-translational modifications from cell culture and tissue samples. However, sample complexity necessitates offline prefractionation via a chromatographic method that is orthogonal to online reversed-phase high-performance liquid chromatography (RP-HPLC). This additional fractionation step improves target identification rates by reducing the complexity of the sample as it is introduced to the instrument. A commonly employed offline prefractionation method is high pH reversed-phase (Hi-pH RP) chromatography. Though highly orthogonal to online RP-HPLC, Hi-pH RP relies on buffers that interfere with electrospray ionization. Thus, samples that are prefractionated using Hi-pH RP are typically desalted prior to LC-MS/MS. In the present work, we evaluate an alternative offline prefractionation method, pentafluorophenyl (PFP)-based reversed-phase chromatography. Importantly, PFP prefractionation results in samples that are dried prior to analysis by LC-MS/MS. This reduction in sample handling relative to Hi-pH RP results in time savings and could facilitate higher target identification rates. Here, we have compared the performances of PFP and Hi-pH RP in offline prefractionation of peptides and phosphopeptides that have been isolated from human cervical carcinoma (HeLa) cells. Given the prevalence of isobaric mass tags for peptide quantification, we evaluated PFP chromatography of peptides labeled with tandem mass tags. Our results suggest that PFP is a viable alternative to Hi-pH RP for both peptide and phosphopeptide offline prefractionation.

Definition of natural T cell antigens with mimicry epitopes obtained from dedicated synthetic peptide libraries.

PubMed

Hiemstra, H S; van Veelen, P A; Schloot, N C; Geluk, A; van Meijgaarden, K E; Willemen, S J; Leunissen, J A; Benckhuijsen, W E; Amons, R; de Vries, R R; Roep, B O; Ottenhoff, T H; Drijfhout, J W

1998-10-15

Progress has recently been made in the use of synthetic peptide libraries for the identification of T cell-stimulating ligands. T cell epitopes identified from synthetic libraries are mimics of natural epitopes. Here we show how the mimicry epitopes obtained from synthetic peptide libraries enable unambiguous identification of natural T cell Ags. Synthetic peptide libraries were screened with Mycobacterium tuberculosis-reactive and -autoreactive T cell clones. In two cases, database homology searches with mimicry epitopes isolated from a dedicated synthetic peptide library allowed immediate identification of the natural antigenic protein. In two other cases, an amino acid pattern that reflected the epitope requirements of the T cell was determined by substitution and omission mixture analysis. Subsequently, the natural Ag was identified from databases using this refined pattern. This approach opens new perspectives for rapid and reliable Ag definition, representing a feasible alternative to the biochemical and genetic approaches described thus far.

Enrichment and Analysis of Non-enzymatically Glycated Peptides: Boronate Affinity Chromatography Coupled with Electron Transfer Dissociation Mass Spectrometry

PubMed Central

Zhang, Qibin; Tang, Ning; Brock, Jonathan W. C.; Mottaz, Heather M.; Ames, Jennifer M.; Baynes, John W.; Smith, Richard D.; Metz, Thomas O.

2008-01-01

Non-enzymatic glycation of peptides and proteins by D-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. However, no effective high-throughput methods exist for identifying proteins containing this low abundance post-translational modification in bottom-up proteomic studies. In this report, phenylboronate affinity chromatography was used in a two-step enrichment scheme to selectively isolate first glycated proteins and then glycated, tryptic peptides from human serum glycated in vitro. Enriched peptides were subsequently analyzed by alternating electron transfer dissociation (ETD) and collision induced dissociation (CID) tandem mass spectrometry. ETD fragmentation mode permitted identification of a significantly higher number of glycated peptides (87.6% of all identified peptides) versus CID mode (17.0% of all identified peptides), when utilizing enrichment on first the protein and then the peptide level. This study illustrates that phenylboronate affinity chromatography coupled with LC-MS/MS and using ETD as the fragmentation mode is an efficient approach for analysis of glycated proteins and may have broad application in studies of diabetes mellitus. PMID:17488106

Prediction and analysis of promiscuous T cell-epitopes derived from the vaccine candidate antigens of Leishmania donovani binding to MHC class-II alleles using in silico approach.

PubMed

Kashyap, Manju; Jaiswal, Varun; Farooq, Umar

2017-09-01

Visceral leishmaniasis is a dreadful infectious disease and caused by the intracellular protozoan parasites, Leishmania donovani and Leishmania infantum. Despite extensive efforts for developing effective prophylactic vaccine, still no vaccine is available against leishmaniasis. However, advancement in immunoinformatics methods generated new dimension in peptide based vaccine development. The present study was aimed to identify T-cell epitopes from the vaccine candidate antigens like Lipophosphogylcan-3(LPG-3) and Nucleoside hydrolase (NH) from the L. donovani using in silico methods. Available best tools were used for the identification of promiscuous peptides for MHC class-II alleles. A total of 34 promiscuous peptides from LPG-3, 3 from NH were identified on the basis of their 100% binding affinity towards all six HLA alleles, taken in this study. These peptides were further checked computationally to know their IFN-γ and IL4 inducing potential and nine peptides were identified. Peptide binding interactions with predominant HLA alleles were done by docking. Out of nine docked promiscuous peptides, only two peptides (QESRILRVIKKKLVR, RILRVIKKKLVRKTL), from LPG-3 and one peptide (FDKFWCLVIDALKRI) from NH showed lowest binding energy with all six alleles. These promiscuous T-cell epitopes were predicted on the basis of their antigenicity, hydrophobicity, potential immune response and docking scores. The immunogenicity of predicted promiscuous peptides might be used for subunit vaccine development with immune-modulating adjuvants. Copyright © 2017 Elsevier B.V. All rights reserved.

LESSONS IN DE NOVO PEPTIDE SEQUENCING BY TANDEM MASS SPECTROMETRY

PubMed Central

Medzihradszky, Katalin F.; Chalkley, Robert J.

2015-01-01

Mass spectrometry has become the method of choice for the qualitative and quantitative characterization of protein mixtures isolated from all kinds of living organisms. The raw data in these studies are MS/MS spectra, usually of peptides produced by proteolytic digestion of a protein. These spectra are “translated” into peptide sequences, normally with the help of various search engines. Data acquisition and interpretation have both been automated, and most researchers look only at the summary of the identifications without ever viewing the underlying raw data used for assignments. Automated analysis of data is essential due to the volume produced. However, being familiar with the finer intricacies of peptide fragmentation processes, and experiencing the difficulties of manual data interpretation allow a researcher to be able to more critically evaluate key results, particularly because there are many known rules of peptide fragmentation that are not incorporated into search engine scoring. Since the most commonly used MS/MS activation method is collision-induced dissociation (CID), in this article we present a brief review of the history of peptide CID analysis. Next, we provide a detailed tutorial on how to determine peptide sequences from CID data. Although the focus of the tutorial is de novo sequencing, the lessons learned and resources supplied are useful for data interpretation in general. PMID:25667941

Peptide identification

DOEpatents

Jarman, Kristin H [Richland, WA; Cannon, William R [Richland, WA; Jarman, Kenneth D [Richland, WA; Heredia-Langner, Alejandro [Richland, WA

2011-07-12

Peptides are identified from a list of candidates using collision-induced dissociation tandem mass spectrometry data. A probabilistic model for the occurrence of spectral peaks corresponding to frequently observed partial peptide fragment ions is applied. As part of the identification procedure, a probability score is produced that indicates the likelihood of any given candidate being the correct match. The statistical significance of the score is known without necessarily having reference to the actual identity of the peptide. In one form of the invention, a genetic algorithm is applied to candidate peptides using an objective function that takes into account the number of shifted peaks appearing in the candidate spectrum relative to the test spectrum.

Comparison of fractionation strategies for offline two-dimensional liquid chromatography tandem mass spectrometry analysis of proteins from mouse adipose tissue.

PubMed

Sajic, Tatjana; Varesio, Emmanuel; Szanto, Ildiko; Hopfgartner, Gérard

2015-09-01

In the frame of protein identification from mouse adipose tissue, two strategies were compared for the offline elution of peptides from a strong cation exchange (SCX) column in two-dimensional liquid chromatography tandem mass spectrometry (2D-LC-MS/MS) analyses. First, the salt gradient (using K(+) as displacing agent) was evaluated from 25 to 500mM KCl. Then, a less investigated elution mode using a pH gradient (using citric acid and ammonium hydroxide) was carried out from pH 2.5 to 9.0. Equal amounts of peptide digest derived from mouse adipose tissue were loaded onto the SCX column and fractionated according to the two approaches. A total of 15 fractions were collected in two independent experiments for each SCX elution strategy. Then, each fraction was analyzed on a nanoLC-MS/MS platform equipped with a column-switching unit for desalting and enrichment. No substantial differences in peptide quality characteristics (molecular weight, isoelectric point, or GRAVY [grand average of hydropathicity] index distributions) were observed between the two datasets. The pH gradient approach was found to be superior, with 27.5% more unique peptide identifications and 10% more distinct protein identifications compared with the salt-based elution method. In conclusion, our data imply that the pH gradient SCX fractionation is more desirable for proteomics analysis of entire adipose tissue. Copyright © 2015 Elsevier Inc. All rights reserved.

Library Design-Facilitated High-Throughput Sequencing of Synthetic Peptide Libraries.

PubMed

Vinogradov, Alexander A; Gates, Zachary P; Zhang, Chi; Quartararo, Anthony J; Halloran, Kathryn H; Pentelute, Bradley L

2017-11-13

A methodology to achieve high-throughput de novo sequencing of synthetic peptide mixtures is reported. The approach leverages shotgun nanoliquid chromatography coupled with tandem mass spectrometry-based de novo sequencing of library mixtures (up to 2000 peptides) as well as automated data analysis protocols to filter away incorrect assignments, noise, and synthetic side-products. For increasing the confidence in the sequencing results, mass spectrometry-friendly library designs were developed that enabled unambiguous decoding of up to 600 peptide sequences per hour while maintaining greater than 85% sequence identification rates in most cases. The reliability of the reported decoding strategy was additionally confirmed by matching fragmentation spectra for select authentic peptides identified from library sequencing samples. The methods reported here are directly applicable to screening techniques that yield mixtures of active compounds, including particle sorting of one-bead one-compound libraries and affinity enrichment of synthetic library mixtures performed in solution.

Identification of an ACE-Inhibitory Peptide from Walnut Protein and Its Evaluation of the Inhibitory Mechanism.

PubMed

Wang, Cong; Tu, Maolin; Wu, Di; Chen, Hui; Chen, Cheng; Wang, Zhenyu; Jiang, Lianzhou

2018-04-11

In the present study, a novel angiotensin I-converting enzyme inhibitory (ACE inhibitory) peptide, EPNGLLLPQY, derived from walnut seed storage protein, fragment residues 80-89, was identified by ultra-high performance liquid chromatography electrospray ionization quadrupole time of flight mass spectrometry (UPLC-ESI-Q-TOF-MS/MS) from walnut protein hydrolysate. The IC 50 value of the peptide was 233.178 μM, which was determined by the high performance liquid chromatography method by measuring the amount of hippuric acid (HA) generated from the ACE decomposition substrate (hippuryl-l-histidyl-l-leucine (HHL) to assess the ACE activity. Enzyme inhibitory kinetics of the peptide against ACE were also conducted, by which the inhibitory mechanism of ACE-inhibitory peptide was confirmed. Moreover, molecular docking was simulated by Discovery Studio 2017 R2 software to provide the potential mechanisms underlying the ACE-inhibitory activity of EPNGLLLPQY.

Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger.

PubMed

Wright, James C; Sugden, Deana; Francis-McIntyre, Sue; Riba-Garcia, Isabel; Gaskell, Simon J; Grigoriev, Igor V; Baker, Scott E; Beynon, Robert J; Hubbard, Simon J

2009-02-04

Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS) and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR). 405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6%) of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models. This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST) data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method.

Identification and characterization of pyrokinin and CAPA peptides, and corresponding GPCRs from spotted wing drosophila, Drosophila suzukii

USDA-ARS?s Scientific Manuscript database

To date, some biological activities have been confirmed as different named peptides, however, most FXPRLamide peptides are still poorly understood although these peptides are found in all insects. So, the study of receptors for these peptides is particularly important. Receptors of FXPRLamide peptid...

[Partial purification of peptides present in the Tityus macrochirus (Buthidae) scorpion venom and preliminary assessment of their cytotoxicity].

PubMed

Rincón-Cortés, Clara Andrea; Reyes-Montaño, Edgar Antonio; Vega-Castro, Nohora Angélica

2017-06-01

Scorpion venom contains peptides with neurotoxic action primarily active on ion channels in the nervous system of insects and mammals. They are also characterized as cytolytic and anticancer, biological characteristics that have not yet been reported for the Tityus macrochirus venom. To assess if the total T. macrochirus venom and the fraction of partially purified peptides decrease the viability of various tumor-derived cell lines. The scorpion venom was collected by electrical stimulation and, subsequently, subjected to chromatography, electrophoresis, and ultrafiltration with Amicon Ultra 0.5® membranes for the partial identification and purification of its peptides. The cytotoxic activity of the venom and the peptides fraction trials on tumor-derived cell lines were carried out by the MTT method. The T. macrochirus scorpion venom has peptides with molecular weights ranging between 3 and 10 kDa. They were partially purified using the ultrafiltration technique, and assessed by the RP-HPLC method. Cytotoxicity trials with the whole T. macrochirus venom showed a higher viability decrease on the PC3 cell line compared to the other cell lines assessed, while the partially purified peptides decreased the HeLa cell line viability. Peptides in the T. macrochirus scorpion venom showed cytotoxic activity on some tumorderived cell lines. We observed some degree of selectivity against other cell lines assessed.

Rapid microscale in-gel processing and digestion of proteins using surface acoustic waves.

PubMed

Kulkarni, Ketav P; Ramarathinam, Sri H; Friend, James; Yeo, Leslie; Purcell, Anthony W; Perlmutter, Patrick

2010-06-21

A new method for in-gel sample processing and tryptic digestion of proteins is described. Sample preparation, rehydration, in situ digestion and peptide extraction from gel slices are dramatically accelerated by treating the gel slice with surface acoustic waves (SAWs). Only 30 minutes total workflow time is required for this new method to produce base peak chromatograms (BPCs) of similar coverage and intensity to those observed for traditional processing and overnight digestion. Simple set up, good reproducibility, excellent peptide recoveries, rapid turnover of samples and high confidence protein identifications put this technology at the fore-front of the next generation of proteomics sample processing tools.

LC-QTOF-MS identification of porcine-specific peptide in heat treated pork identifies candidate markers for meat species determination.

PubMed

Sarah, S A; Faradalila, W N; Salwani, M S; Amin, I; Karsani, S A; Sazili, A Q

2016-05-15

The purpose of this study was to identify porcine-specific peptide markers from thermally processed meat that could differentiate pork from beef, chevon and chicken meat. In the initial stage, markers from tryptic digested protein of chilled, boiled and autoclaved pork were identified using LC-QTOF-MS. An MRM method was then established for verification. A thorough investigation of LC-QTOF-MS data showed that only seven porcine-specific peptides were consistently detected. Among these peptides, two were derived from lactate dehydrogenase, one from creatine kinase, and four from serum albumin protein. However, MRM could only detect four peptides (EVTEFAK, LVVITAGAR, FVIER and TVLGNFAAFVQK) that were consistently present in pork samples. In conclusion, meat species determination through a tandem mass spectrometry platform shows high potential in providing scientifically valid and reliable results even at peptide level. Besides, the specificity and selectivity offered by the proteomics approach also provide a robust platform for Halal authentication. Copyright © 2015 Elsevier Ltd. All rights reserved.

Engineering peptide ligase specificity by proteomic identification of ligation sites.

PubMed

Weeks, Amy M; Wells, James A

2018-01-01

Enzyme-catalyzed peptide ligation is a powerful tool for site-specific protein bioconjugation, but stringent enzyme-substrate specificity limits its utility. We developed an approach for comprehensively characterizing peptide ligase specificity for N termini using proteome-derived peptide libraries. We used this strategy to characterize the ligation efficiency for >25,000 enzyme-substrate pairs in the context of the engineered peptide ligase subtiligase and identified a family of 72 mutant subtiligases with activity toward N-terminal sequences that were previously recalcitrant to modification. We applied these mutants individually for site-specific bioconjugation of purified proteins, including antibodies, and in algorithmically selected combinations for sequencing of the cellular N terminome with reduced sequence bias. We also developed a web application to enable algorithmic selection of the most efficient subtiligase variant(s) for bioconjugation to user-defined sequences. Our methods provide a new toolbox of enzymes for site-specific protein modification and a general approach for rapidly defining and engineering peptide ligase specificity.

Multiplexed Post-Experimental Monoisotopic Mass Refinement ( m PE-MMR) to Increase Sensitivity and Accuracy in Peptide Identifications from Tandem Mass Spectra of Cofragmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Madar, Inamul Hasan; Ko, Seung-Ik; Kim, Hokeun

Mass spectrometry (MS)-based proteomics, which uses high-resolution hybrid mass spectrometers such as the quadrupole-orbitrap mass spectrometer, can yield tens of thousands of tandem mass (MS/MS) spectra of high resolution during a routine bottom-up experiment. Despite being a fundamental and key step in MS-based proteomics, the accurate determination and assignment of precursor monoisotopic masses to the MS/MS spectra remains difficult. The difficulties stem from imperfect isotopic envelopes of precursor ions, inaccurate charge states for precursor ions, and cofragmentation. We describe a composite method of utilizing MS data to assign accurate monoisotopic masses to MS/MS spectra, including those subject to cofragmentation. Themore » method, “multiplexed post-experiment monoisotopic mass refinement” (mPE-MMR), consists of the following: multiplexing of precursor masses to assign multiple monoisotopic masses of cofragmented peptides to the corresponding multiplexed MS/MS spectra, multiplexing of charge states to assign correct charges to the precursor ions of MS/ MS spectra with no charge information, and mass correction for inaccurate monoisotopic peak picking. When combined with MS-GF+, a database search algorithm based on fragment mass difference, mPE-MMR effectively increases both sensitivity and accuracy in peptide identification from complex high-throughput proteomics data compared to conventional methods.« less

Analysis of illegal peptide drugs via HILIC-DAD-MS.

PubMed

Janvier, Steven; De Sutter, Evelien; Wynendaele, Evelien; De Spiegeleer, Bart; Vanhee, Celine; Deconinck, Eric

2017-11-01

Biopharmaceuticals have established themselves as highly efficient medicines, and are still one of the fastest growing parts of the health-product industry. Unfortunately, the introduction of these promising new drugs went hand in hand with the creation of a black market for illegal and counterfeit biotechnology drugs. Particularly popular are the lyophilised peptides with a molecular weight of less than 5kDa. Most of them are meant for subcutaneous injection and are easily accessible via the internet. In recent years, different methods based on reversed phase liquid chromatography have been developed to detect and quantify these peptides. The emerging of more polar peptides however requires the introduction of other separation techniques. Therefore, we set out to develop and validate an analytical method based on hydrophilic interaction liquid chromatography (HILIC) to identify and quantify the most frequently encountered illegal peptides on the European market. For this objective, five different HILIC columns were selected and screened for their chromatographic performance. Among those columns, the ZIC HILIC column showed the best performance under the tested screening conditions in terms of resolution and symmetry factor for the targeted peptide set. Hence, the operational conditions were further optimised for the identification of illegal preparations via mass spectrometry (MS) and quantification via UV. Validation was performed via accuracy profiles based on the ISO 17025 guideline. The obtained validated HILIC-method allows for the detection and quantification of the most frequently encountered illegal peptides on the internet in a total run time of 35min including post gradient equilibration and online cleaning step. Combined with a previously developed RPLC-method, the ZIC HILIC system allows for the detection and quantification of a wide spectrum of illicit peptide drugs available on the internet. Furthermore, the developed method could also be envisaged for the detection of new emerging polar peptide drugs. Copyright © 2017 Elsevier B.V. All rights reserved.

Rapid screening and identification of dominant B cell epitopes of HBV surface antigen by quantum dot-based fluorescence polarization assay

NASA Astrophysics Data System (ADS)

Meng, Zhongji; Song, Ruihua; Chen, Yue; Zhu, Yang; Tian, Yanhui; Li, Ding; Cui, Daxiang

2013-03-01

A method for quickly screening and identifying dominant B cell epitopes was developed using hepatitis B virus (HBV) surface antigen as a target. Eleven amino acid fragments from HBV surface antigen were synthesized by 9-fluorenylmethoxy carbonyl solid-phase peptide synthesis strategy, and then CdTe quantum dots were used to label the N-terminals of all peptides. After optimizing the factors for fluorescence polarization (FP) immunoassay, the antigenicities of synthetic peptides were determined by analyzing the recognition and combination of peptides and standard antibody samples. The results of FP assays confirmed that 10 of 11 synthetic peptides have distinct antigenicities. In order to screen dominant antigenic peptides, the FP assays were carried out to investigate the antibodies against the 10 synthetic peptides of HBV surface antigen respectively in 159 samples of anti-HBV surface antigen-positive antiserum. The results showed that 3 of the 10 antigenic peptides may be immunodominant because the antibodies against them existed more widely among the samples and their antibody titers were higher than those of other peptides. Using three dominant antigenic peptides, 293 serum samples were detected for HBV infection by FP assays; the results showed that the antibody-positive ratio was 51.9% and the sensitivity and specificity were 84.3% and 98.2%, respectively. In conclusion, a quantum dot-based FP assay is a very simple, rapid, and convenient method for determining immunodominant antigenic peptides and has great potential in applications such as epitope mapping, vaccine designing, or clinical disease diagnosis in the future.

Identification and classification of conopeptides using profile Hidden Markov Models.

PubMed

Laht, Silja; Koua, Dominique; Kaplinski, Lauris; Lisacek, Frédérique; Stöcklin, Reto; Remm, Maido

2012-03-01

Conopeptides are small toxins produced by predatory marine snails of the genus Conus. They are studied with increasing intensity due to their potential in neurosciences and pharmacology. The number of existing conopeptides is estimated to be 1 million, but only about 1000 have been described to date. Thanks to new high-throughput sequencing technologies the number of known conopeptides is likely to increase exponentially in the near future. There is therefore a need for a fast and accurate computational method for identification and classification of the novel conopeptides in large data sets. 62 profile Hidden Markov Models (pHMMs) were built for prediction and classification of all described conopeptide superfamilies and families, based on the different parts of the corresponding protein sequences. These models showed very high specificity in detection of new peptides. 56 out of 62 models do not give a single false positive in a test with the entire UniProtKB/Swiss-Prot protein sequence database. Our study demonstrates the usefulness of mature peptide models for automatic classification with accuracy of 96% for the mature peptide models and 100% for the pro- and signal peptide models. Our conopeptide profile HMMs can be used for finding and annotation of new conopeptides from large datasets generated by transcriptome or genome sequencing. To our knowledge this is the first time this kind of computational method has been applied to predict all known conopeptide superfamilies and some conopeptide families. Copyright © 2012 Elsevier B.V. All rights reserved.

Construction of the Free Energy Landscape of Peptide Aggregation from Molecular Dynamics Simulations.

PubMed

Riccardi, Laura; Nguyen, Phuong H; Stock, Gerhard

2012-04-10

To describe the structure and dynamics of oligomers during peptide aggregation, a method is proposed that considers both the intramolecular and intermolecular structures of the multimolecule system and correctly accounts for its degeneracy. The approach is based on the "by-parts" strategy, which partitions a complex molecular system into parts, determines the metastable conformational states of each part, and describes the overall conformational state of the system in terms of a product basis of the states of the parts. Starting from a molecular dynamics simulation of n molecules, the method consists of three steps: (i) characterization of the intramolecular structure, that is, of the conformational states of a single molecule in the presence of the other molecules (e.g., β-strand or random coil); (ii) characterization of the intermolecular structure through the identification of all occurring aggregate states of the peptides (dimers, trimers, etc.); and (iii) construction of the overall conformational states of the system in terms of a product basis of the n "single-molecule" states and the aggregate states. Considering the Alzheimer β-amyloid peptide fragment Aβ16-22 as a first application, about 700 overall conformational states of the trimer (Aβ16-22)3 were constructed from all-atom molecular dynamics simulation in explicit water. Based on these states, a transition network reflecting the free energy landscape of the aggregation process can be constructed that facilitates the identification of the aggregation pathways.

Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences*

PubMed Central

Pirmoradian, Mohammad

2017-01-01

Most implementations of mass spectrometry-based proteomics involve enzymatic digestion of proteins, expanding the analysis to multiple proteolytic peptides for each protein. Currently, there is no consensus of how to summarize peptides' abundances to protein concentrations, and such efforts are complicated by the fact that error control normally is applied to the identification process, and do not directly control errors linking peptide abundance measures to protein concentration. Peptides resulting from suboptimal digestion or being partially modified are not representative of the protein concentration. Without a mechanism to remove such unrepresentative peptides, their abundance adversely impacts the estimation of their protein's concentration. Here, we present a relative quantification approach, Diffacto, that applies factor analysis to extract the covariation of peptides' abundances. The method enables a weighted geometrical average summarization and automatic elimination of incoherent peptides. We demonstrate, based on a set of controlled label-free experiments using standard mixtures of proteins, that the covariation structure extracted by the factor analysis accurately reflects protein concentrations. In the 1% peptide-spectrum match-level FDR data set, as many as 11% of the peptides have abundance differences incoherent with the other peptides attributed to the same protein. If not controlled, such contradicting peptide abundance have a severe impact on protein quantifications. When adding the quantities of each protein's three most abundant peptides, we note as many as 14% of the proteins being estimated as having a negative correlation with their actual concentration differences between samples. Diffacto reduced the amount of such obviously incorrectly quantified proteins to 1.6%. Furthermore, by analyzing clinical data sets from two breast cancer studies, our method revealed the persistent proteomic signatures linked to three subtypes of breast cancer. We conclude that Diffacto can facilitate the interpretation and enhance the utility of most types of proteomics data. PMID:28302922

Analysis of non-enzymatically glycated peptides: neutral-loss-triggered MS3 versus multi-stage activation tandem mass spectrometry

PubMed Central

Zhang, Qibin; Petyuk, Vladislav A.; Schepmoes, Athena A.; Orton, Daniel J.; Monroe, Matthew E.; Yang, Feng; Smith, Richard D.; Metz, Thomas O.

2009-01-01

Non-enzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. While electron transfer dissociation (ETD) has been shown to outperform collision-induced dissociation (CID) in sequencing glycated peptides by tandem mass spectrometry, ETD instrumentation is not yet widely available and often suffers from significantly lower sensitivity than CID. In this study, we evaluated different advanced CID techniques (i.e., neutral-loss-triggered MS3 and multi-stage activation) during liquid chromatography/multi-stage mass spectrometric (LC/MSn) analyses of Amadori-modified peptides enriched from human serum glycated in vitro. During neutral-loss-triggered MS3 experiments, MS3 scans triggered by neutral losses of 3 H2O or 3 H2O + HCHO produced similar results in terms of glycated peptide identifications. However, neutral losses of 3 H2O resulted in significantly more glycated peptide identifications during multi-stage activation experiments. Overall, the multi-stage activation approach produced more glycated peptide identifications, while the neutral-loss-triggered MS3 approach resulted in much higher specificity. Both techniques are viable alternatives to ETD for identifying glycated peptides. PMID:18763275

Toward an Upgraded Honey Bee (Apis mellifera L.) Genome Annotation Using Proteogenomics.

PubMed

McAfee, Alison; Harpur, Brock A; Michaud, Sarah; Beavis, Ronald C; Kent, Clement F; Zayed, Amro; Foster, Leonard J

2016-02-05

The honey bee is a key pollinator in agricultural operations as well as a model organism for studying the genetics and evolution of social behavior. The Apis mellifera genome has been sequenced and annotated twice over, enabling proteomics and functional genomics methods for probing relevant aspects of their biology. One troubling trend that emerged from proteomic analyses is that honey bee peptide samples consistently result in lower peptide identification rates compared with other organisms. This suggests that the genome annotation can be improved, or atypical biological processes are interfering with the mass spectrometry workflow. First, we tested whether high levels of polymorphisms could explain some of the missed identifications by searching spectra against the reference proteome (OGSv3.2) versus a customized proteome of a single honey bee, but our results indicate that this contribution was minor. Likewise, error-tolerant peptide searches lead us to eliminate unexpected post-translational modifications as a major factor in missed identifications. We then used a proteogenomic approach with ~1500 raw files to search for missing genes and new exons, to revive discarded annotations and to identify over 2000 new coding regions. These results will contribute to a more comprehensive genome annotation and facilitate continued research on this important insect.

A Non-parametric Cutout Index for Robust Evaluation of Identified Proteins*

PubMed Central

Serang, Oliver; Paulo, Joao; Steen, Hanno; Steen, Judith A.

2013-01-01

This paper proposes a novel, automated method for evaluating sets of proteins identified using mass spectrometry. The remaining peptide-spectrum match score distributions of protein sets are compared to an empirical absent peptide-spectrum match score distribution, and a Bayesian non-parametric method reminiscent of the Dirichlet process is presented to accurately perform this comparison. Thus, for a given protein set, the process computes the likelihood that the proteins identified are correctly identified. First, the method is used to evaluate protein sets chosen using different protein-level false discovery rate (FDR) thresholds, assigning each protein set a likelihood. The protein set assigned the highest likelihood is used to choose a non-arbitrary protein-level FDR threshold. Because the method can be used to evaluate any protein identification strategy (and is not limited to mere comparisons of different FDR thresholds), we subsequently use the method to compare and evaluate multiple simple methods for merging peptide evidence over replicate experiments. The general statistical approach can be applied to other types of data (e.g. RNA sequencing) and generalizes to multivariate problems. PMID:23292186

MLACP: machine-learning-based prediction of anticancer peptides

PubMed Central

Manavalan, Balachandran; Basith, Shaherin; Shin, Tae Hwan; Choi, Sun; Kim, Myeong Ok; Lee, Gwang

2017-01-01

Cancer is the second leading cause of death globally, and use of therapeutic peptides to target and kill cancer cells has received considerable attention in recent years. Identification of anticancer peptides (ACPs) through wet-lab experimentation is expensive and often time consuming; therefore, development of an efficient computational method is essential to identify potential ACP candidates prior to in vitro experimentation. In this study, we developed support vector machine- and random forest-based machine-learning methods for the prediction of ACPs using the features calculated from the amino acid sequence, including amino acid composition, dipeptide composition, atomic composition, and physicochemical properties. We trained our methods using the Tyagi-B dataset and determined the machine parameters by 10-fold cross-validation. Furthermore, we evaluated the performance of our methods on two benchmarking datasets, with our results showing that the random forest-based method outperformed the existing methods with an average accuracy and Matthews correlation coefficient value of 88.7% and 0.78, respectively. To assist the scientific community, we also developed a publicly accessible web server at www.thegleelab.org/MLACP.html. PMID:29100375

From Mollusks to Medicine: A Venomics Approach for the Discovery and Characterization of Therapeutics from Terebridae Peptide Toxins.

PubMed

Verdes, Aida; Anand, Prachi; Gorson, Juliette; Jannetti, Stephen; Kelly, Patrick; Leffler, Abba; Simpson, Danny; Ramrattan, Girish; Holford, Mandë

2016-04-19

Animal venoms comprise a diversity of peptide toxins that manipulate molecular targets such as ion channels and receptors, making venom peptides attractive candidates for the development of therapeutics to benefit human health. However, identifying bioactive venom peptides remains a significant challenge. In this review we describe our particular venomics strategy for the discovery, characterization, and optimization of Terebridae venom peptides, teretoxins. Our strategy reflects the scientific path from mollusks to medicine in an integrative sequential approach with the following steps: (1) delimitation of venomous Terebridae lineages through taxonomic and phylogenetic analyses; (2) identification and classification of putative teretoxins through omics methodologies, including genomics, transcriptomics, and proteomics; (3) chemical and recombinant synthesis of promising peptide toxins; (4) structural characterization through experimental and computational methods; (5) determination of teretoxin bioactivity and molecular function through biological assays and computational modeling; (6) optimization of peptide toxin affinity and selectivity to molecular target; and (7) development of strategies for effective delivery of venom peptide therapeutics. While our research focuses on terebrids, the venomics approach outlined here can be applied to the discovery and characterization of peptide toxins from any venomous taxa.

Novel ligands for cancer diagnosis: selection of peptide ligands for identification and isolation of B-cell lymphomas.

PubMed

McGuire, Michael J; Samli, Kausar N; Chang, Ya-Ching; Brown, Kathlynn C

2006-04-01

Lymphoma and leukemia account for nearly 8% of cancer fatalities each year. Present treatments do not differentiate between normal and malignant cells. New reagents that distinguish malignant cells and enable the isolation of these cells from the normal background will enhance the molecular characterization of disease and specificity of treatment. Peptide ligands were selected from a phage-displayed peptide library by biopanning on the B-cell lymphoma line, A20. The isolated peptides were assessed as reagents for identification and isolation of lymphoma cells by flow cytometry and cell capture with magnetic beads. Two novel peptides and one obtained previously on cardiomyocytes were selected. A20 cells bind phage displaying these peptides 250- to 450-fold over control phage. These phage bind to other bone marrow-derived cancel lines including some macrophage and T cells but do not bind to normal splenocytes. Synthetic constructs of these peptides have binding affinities comparable to B-cell-specific antibodies. Similar to antibodies, these peptides can be used in flow cytometry and magnetic bead capture to distinguish lymphoma cells from normal splenocytes. Bone marrow-derived malignant cells express cell surface markers that can be used to distinguish them from normal cells. These results demonstrate the ability to use an unbiased screen to rapidly generate high-affinity peptide ligands for identification and isolation of lymphoma cells.

Identification of Lasso Peptide Topologies Using Native Nanoelectrospray Ionization-Trapped Ion Mobility Spectrometry-Mass Spectrometry.

PubMed

Dit Fouque, Kevin Jeanne; Moreno, Javier; Hegemann, Julian D; Zirah, Séverine; Rebuffat, Sylvie; Fernandez-Lima, Francisco

2018-04-17

Lasso peptides are a fascinating class of bioactive ribosomal natural products characterized by a mechanically interlocked topology. In contrast to their branched-cyclic forms, lasso peptides have higher stability and have become a scaffold for drug development. However, the identification and separation of lasso peptides from their unthreaded topoisomers (branched-cyclic peptides) is analytically challenging since the higher stability is based solely on differences in their tertiary structures. In the present work, a fast and effective workflow is proposed for the separation and identification of lasso from branched cyclic peptides based on differences in their mobility space under native nanoelectrospray ionization-trapped ion mobility spectrometry-mass spectrometry (nESI-TIMS-MS). The high mobility resolving power ( R) of TIMS resulted in the separation of lasso and branched-cyclic topoisomers ( R up to 250, 150 needed on average). The advantages of alkali metalation reagents (e.g., Na, K, and Cs salts) as a way to increase the analytical power of TIMS is demonstrated for topoisomers with similar mobilities as protonated species, efficiently turning the metal ion adduction into additional separation dimensions.

Assay Development for the Determination of Phosphorylation Stoichiometry using MRM methods with and without Phosphatase Treatment: Application to Breast Cancer Signaling Pathways

PubMed Central

Domanski, Dominik; Murphy, Leigh C.; Borchers, Christoph H.

2010-01-01

We have developed a phosphatase-based phosphopeptide quantitation (PPQ) method for determining phosphorylation stoichiometry in complex biological samples. This PPQ method is based on enzymatic dephosphorylation, combined with specific and accurate peptide identification and quantification by multiple reaction monitoring (MRM) detection with stable-isotope-labeled standard peptides. In contrast with the classical MRM methods for the quantitation of phosphorylation stoichiometry, the PPQ-MRM method needs only one non-phosphorylated SIS (stable isotope-coded standard) and two analyses (one for the untreated and one for the phosphatase-treated sample), from which the expression and modification levels can accurately be determined. From these analyses, the % phosphorylation can be determined. In this manuscript, we compare the PPQ-MRM method with an MRM method without phosphatase, and demonstrate the application of these methods to the detection and quantitation of phosphorylation of the classic phosphorylated breast cancer biomarkers (ERα and HER2), and for phosphorylated RAF and ERK1, which also contain phosphorylation sites with important biological implications. Using synthetic peptides spiked into a complex protein digest, we were able to use our PPQ-MRM method to accurately determine the total phosphorylation stoichiometry on specific peptides, as well as the absolute amount of the peptide and phosphopeptide present. Analyses of samples containing ERα protein revealed that the PPQ-MRM is capable of determining phosphorylation stoichiometry in proteins from cell lines, and is in good agreement with determinations obtained using the direct MRM approach in terms of phosphorylation and total protein amount. PMID:20524616

Protein identification and quantification from riverbank grape, Vitis riparia: Comparing SDS-PAGE and FASP-GPF techniques for shotgun proteomic analysis.

PubMed

George, Iniga S; Fennell, Anne Y; Haynes, Paul A

2015-09-01

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in-gel digestion and in-solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS-PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP-GPF was used. FASP-GPF is more reproducible, less expensive and a better method than SDS-PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 (http://proteomecentral.proteomexchange.org/dataset/PXD001399). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Qibin; Tang, Ning; Brock, Jonathan W.

Non-enzymatic glycation of peptides and proteins by D-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. However, no effective high-throughput methods exist for identifying proteins containing this low abundance post-translational modification in bottom-up proteomic studies. In this report, phenylboronate affinity chromatography was used in a two-step enrichment scheme to selectively isolate first glycated proteins and then glycated, tryptic peptides from human serum glycated in vitro. Enriched peptides were subsequently analyzed by alternating electron transfer dissociation (ETD) and collision induced dissociation (CID) tandem mass spectrometry. It was observed that ETD fragmentation mode resultedmore » in a significantly higher number of glycated peptide identifications (87.6% of all identified peptides) versus CID mode (17.0% of all identified peptides), when utilizing dual glycation enrichment on both the protein and peptide level. This study illustrates that phenylboronate affinity chromatography coupled with LC-MS/MS with ETD as the fragmentation mode is an efficient approach for analyses of glycated proteins and can have broad applications in studies of diabetes mellitus.« less

LC-MS/MS with 2D mass mapping of skin secretions' peptides as a reliable tool for interspecies identification inside Rana esculenta complex.

PubMed

Samgina, Tatyana Yu; Gorshkov, Vladimir A; Artemenko, Konstantin A; Vorontsov, Egor A; Klykov, Oleg V; Ogourtsov, Sergey V; Zubarev, Roman A; Lebedev, Albert T

2012-04-01

Identification of species constituting Rana esculenta complex represents a certain problem as two parental species Rana ridibunda and Rana lessonae form their hybrid R. esculenta, while external signs and sizes of the members of this complex are intersected. However the composition of skin secretion consisting mainly of peptides is different for the species of the complex. LC-MS/MS is an ideal analytical tool for the quantitative and qualitative analysis of these peptides. The results covering elemental composition of these peptides, their levels in the secretion, as well as their belonging to a certain family of peptides may be visualized by means of 2D mass maps. The proposed approach proved itself to be a perspective tool for the reliable identification of all 3 species constituting R. esculenta complex. Easy distinguishing between the species may be achieved using 2D maps as fingerprints. Besides this approach may be used to study hybridogenesis and mechanisms of hemiclonal transfer of genetic information, when rapid and reliable identification of species involved in the process is required. Copyright © 2012 Elsevier Inc. All rights reserved.

Vegetable foods: a cheap source of proteins and peptides with antihypertensive, antioxidant, and other less occurrence bioactivities.

PubMed

García, M C; Puchalska, P; Esteve, C; Marina, M L

2013-03-15

Despite less explored than foods from animal origin, plant derived foods also contain biologically active proteins and peptides. Bioactive peptides can be present as an independent entity in the food or, more frequently, can be in a latent state as part of the sequence of a protein. Release from that protein requires protein hydrolysis by enzymatic digestion, fermentation or autolysis. Different methodologies have been used to test proteins and peptides bioactivities. Fractionation, separation, and identification techniques have also been employed for the isolation and identification of bioactive proteins or peptides. In this work, proteins and peptides from plant derived foods exerting antihypertensive, antioxidant, hypocholesterolemic, antithrombotic, and immunostimulating capacities or ability to reduce food intake have been reviewed. Copyright © 2013 Elsevier B.V. All rights reserved.

ICPD-A New Peak Detection Algorithm for LC/MS

PubMed Central

2010-01-01

Background The identification and quantification of proteins using label-free Liquid Chromatography/Mass Spectrometry (LC/MS) play crucial roles in biological and biomedical research. Increasing evidence has shown that biomarkers are often low abundance proteins. However, LC/MS systems are subject to considerable noise and sample variability, whose statistical characteristics are still elusive, making computational identification of low abundance proteins extremely challenging. As a result, the inability of identifying low abundance proteins in a proteomic study is the main bottleneck in protein biomarker discovery. Results In this paper, we propose a new peak detection method called Information Combining Peak Detection (ICPD ) for high resolution LC/MS. In LC/MS, peptides elute during a certain time period and as a result, peptide isotope patterns are registered in multiple MS scans. The key feature of the new algorithm is that the observed isotope patterns registered in multiple scans are combined together for estimating the likelihood of the peptide existence. An isotope pattern matching score based on the likelihood probability is provided and utilized for peak detection. Conclusions The performance of the new algorithm is evaluated based on protein standards with 48 known proteins. The evaluation shows better peak detection accuracy for low abundance proteins than other LC/MS peak detection methods. PMID:21143790

Fluorescence In Situ Hybridization with Peptide Nucleic Acid Probes for Rapid Identification of Candida albicans Directly from Blood Culture Bottles

PubMed Central

Rigby, Susan; Procop, Gary W.; Haase, Gerhard; Wilson, Deborah; Hall, Geraldine; Kurtzman, Cletus; Oliveira, Kenneth; Von Oy, Sabina; Hyldig-Nielsen, Jens J.; Coull, James; Stender, Henrik

2002-01-01

A new fluorescence in situ hybridization (FISH) method that uses peptide nucleic acid (PNA) probes for identification of Candida albicans directly from positive-blood-culture bottles in which yeast was observed by Gram staining (herein referred to as yeast-positive blood culture bottles) is described. The test (the C. albicans PNA FISH method) is based on a fluorescein-labeled PNA probe that targets C. albicans 26S rRNA. The PNA probe is added to smears made directly from the contents of the blood culture bottle and hybridized for 90 min at 55°C. Unhybridized PNA probe is removed by washing of the mixture (30 min), and the smears are examined by fluorescence microscopy. The specificity of the method was confirmed with 23 reference strains representing phylogenetically related yeast species and 148 clinical isolates covering the clinically most significant yeast species, including C. albicans (n = 72), C. dubliniensis (n = 58), C. glabrata (n = 5), C. krusei (n = 2), C. parapsilosis (n = 4), and C. tropicalis (n = 3). The performance of the C. albicans PNA FISH method as a diagnostic test was evaluated with 33 routine and 25 simulated yeast-positive blood culture bottles and showed 100% sensitivity and 100% specificity. It is concluded that this 2.5-h method for the definitive identification of C. albicans directly from yeast-positive blood culture bottles provides important information for optimal antifungal therapy and patient management. PMID:12037084

Brute-Force Approach for Mass Spectrometry-Based Variant Peptide Identification in Proteogenomics without Personalized Genomic Data

NASA Astrophysics Data System (ADS)

Ivanov, Mark V.; Lobas, Anna A.; Levitsky, Lev I.; Moshkovskii, Sergei A.; Gorshkov, Mikhail V.

2018-02-01

In a proteogenomic approach based on tandem mass spectrometry analysis of proteolytic peptide mixtures, customized exome or RNA-seq databases are employed for identifying protein sequence variants. However, the problem of variant peptide identification without personalized genomic data is important for a variety of applications. Following the recent proposal by Chick et al. (Nat. Biotechnol. 33, 743-749, 2015) on the feasibility of such variant peptide search, we evaluated two available approaches based on the previously suggested "open" search and the "brute-force" strategy. To improve the efficiency of these approaches, we propose an algorithm for exclusion of false variant identifications from the search results involving analysis of modifications mimicking single amino acid substitutions. Also, we propose a de novo based scoring scheme for assessment of identified point mutations. In the scheme, the search engine analyzes y-type fragment ions in MS/MS spectra to confirm the location of the mutation in the variant peptide sequence.

Context Dependence of Protein Misfolding and Structural Strains in Neurodegenerative Diseases

PubMed Central

Mehta, Anil K.; Rosen, Rebecca F.; Childers, W. Seth; Gehman, John D.; Walker, Lary C.; Lynn, David G.

2014-01-01

Vast arrays of structural forms are accessible to simple amyloid peptides and environmental conditions can direct assembly into single phases. These insights are now being applied to the aggregation of the Aβ peptide of Alzheimer’s disease (AD) and the identification of causative phases. We extend use of the imaging agent Pittsburgh compound B (PiB) to discriminate among Aβ phases and begin to define conditions of relevance to the disease state. And we specifically highlight the development of methods for defining the structures of these more complex phases. PMID:23893572

Identification of B cell epitopes of alcohol dehydrogenase allergen of Curvularia lunata.

PubMed

Nair, Smitha; Kukreja, Neetu; Singh, Bhanu Pratap; Arora, Naveen

2011-01-01

Epitope identification assists in developing molecules for clinical applications and is useful in defining molecular features of allergens for understanding structure/function relationship. The present study was aimed to identify the B cell epitopes of alcohol dehydrogenase (ADH) allergen from Curvularia lunata using in-silico methods and immunoassay. B cell epitopes of ADH were predicted by sequence and structure based methods and protein-protein interaction tools while T cell epitopes by inhibitory concentration and binding score methods. The epitopes were superimposed on a three dimensional model of ADH generated by homology modeling and analyzed for antigenic characteristics. Peptides corresponding to predicted epitopes were synthesized and immunoreactivity assessed by ELISA using individual and pooled patients' sera. The homology model showed GroES like catalytic domain joined to Rossmann superfamily domain by an alpha helix. Stereochemical quality was confirmed by Procheck which showed 90% residues in most favorable region of Ramachandran plot while Errat gave a quality score of 92.733%. Six B cell (P1-P6) and four T cell (P7-P10) epitopes were predicted by a combination of methods. Peptide P2 (epitope P2) showed E(X)(2)GGP(X)(3)KKI conserved pattern among allergens of pathogenesis related family. It was predicted as high affinity binder based on electronegativity and low hydrophobicity. The computational methods employed were validated using Bet v 1 and Der p 2 allergens where 67% and 60% of the epitope residues were predicted correctly. Among B cell epitopes, Peptide P2 showed maximum IgE binding with individual and pooled patients' sera (mean OD 0.604±0.059 and 0.506±0.0035, respectively) followed by P1, P4 and P3 epitopes. All T cell epitopes showed lower IgE binding. Four B cell epitopes of C. lunata ADH were identified. Peptide P2 can serve as a potential candidate for diagnosis of allergic diseases.

Identification of Microcystis aeruginosa Peptides Responsible for Allergic Sensitization and Characterization of Functional Interactions between Cyanobacterial Toxins and Immunogenic Peptides

PubMed Central

Geh, Esmond N.; Ghosh, Debajyoti; McKell, Melanie; de la Cruz, Armah A.; Stelma, Gerard

2015-01-01

Background The cyanobacterium species Microcystis aeruginosa produces microcystin and an array of diverse metabolites believed responsible for their toxicity and/or immunogenicity. Previously, chronic rhinitis patients were demonstrated to elicit a specific IgE response to nontoxic strains of M. aeruginosa by skin-prick testing, indicating that cyanobacteria allergenicity resides in a non-toxin–producing component of the organism. Objectives We sought to identify and characterize M. aeruginosa peptide(s) responsible for allergic sensitization in susceptible individuals, and we investigated the functional interactions between cyanobacterial toxins and their coexpressed immunogenic peptides. Methods Sera from patients and extracts from M. aeruginosa toxic [MC(+)] and nontoxic [MC(–)] strains were used to test IgE-specific reactivity by direct and indirect ELISAs; 2D gel electrophoresis, followed by immunoblots and mass spectrometry (MS), was performed to identify the relevant sensitizing peptides. Cytotoxicity and mediator release assays were performed using the MC(+) and MC(–) lysates. Results We found specific IgE to be increased more in response to the MC(–) strain than the MC(+) strain. This response was inhibited by preincubation of MC(–) lysate with increasing concentrations of microcystin. MS revealed that phycocyanin and the core-membrane linker peptide are the responsible allergens, and MC(–) extracts containing these proteins induced β-hexosaminidase release in rat basophil leukemia cells. Conclusions Phycobiliprotein complexes in M. aeruginosa have been identified as the relevant sensitizing proteins. Our finding that allergenicity is inhibited in a dose-dependent manner by microcystin toxin suggests that further investigation is warranted to understand the interplay between immunogenicity and toxicity of cyanobacteria under diverse environmental conditions. Citation Geh EN, Ghosh D, McKell M, de la Cruz AA, Stelma G, Bernstein JA. 2015. Identification of Microcystis aeruginosa peptides responsible for allergic sensitization and characterization of functional interactions between cyanobacterial toxins and immunogenic peptides. Environ Health Perspect 123:1159–1166; http://dx.doi.org/10.1289/ehp.1409065 PMID:25902363

Identification of ace inhibitory cryptides in Tilapia protein hydrolysate by UPLC-MS/MS coupled to database analysis.

PubMed

Yesmine, Ben Henda; Antoine, Bonnet; da Silva Ortência Leocádia, Nunes Gonzalez; Rogério, Boscolo Wilson; Ingrid, Arnaudin; Nicolas, Bridiau; Thierry, Maugard; Jean-Marie, Piot; Frédéric, Sannier; Stéphanie, Bordenave-Juchereau

2017-05-01

An ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry method was developed and applied to identify short angiotensin-I-converting enzyme (ACE) inhibitory cryptides in Tilapia (Oreochromis Niloticus) protein hydrolyzate. A database was created with previously identified ACE-inhibitory di- and tripeptides and the lowest molecular weight fraction of Tilapia hydrolysate was analysed for coincidences. Only VW and VY were identified. Further analysis of collected fractions conducted to the identification of 51 different peptides in major fractions. 19 peptides selected were synthesised and tested for their ACE inhibitory potential. TL, TI, IK, LR, LD, IQ, DI, AILE, ALLE, ALIE and AIIE were identified as new ACE inhibitors. The findings from this study point UPLC-MS/MS combined with the creation of a database as an efficient technique to identify specific short peptides within a complex hydrolysate, in addition with de novo sequencing. This efficient characterisation of bioactive factors like cryptides in protein hydrolysates will extend their use as functional foods. Copyright © 2017 Elsevier B.V. All rights reserved.

Elucidation of Peptide-Directed Palladium Surface Structure for Biologically Tunable Nanocatalysts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bedford, Nicholas M.; Ramezani-Dakhel, Hadi; Slocik, Joseph M.

Peptide-enabled synthesis of inorganic nanostructures represents an avenue to access catalytic materials with tunable and optimized properties. This is achieved via peptide complexity and programmability that is missing in traditional ligands for catalytic nanomaterials. Unfortunately, there is limited information available to correlate peptide sequence to particle structure and catalytic activity to date. As such, the application of peptide-enabled nanocatalysts remains limited to trial and error approaches. In this paper, a hybrid experimental and computational approach is introduced to systematically elucidate biomolecule-dependent structure/function relationships for peptide-capped Pd nanocatalysts. Synchrotron X-ray techniques were used to uncover substantial particle surface structural disorder, whichmore » was dependent upon the amino acid sequence of the peptide capping ligand. Nanocatalyst configurations were then determined directly from experimental data using reverse Monte Carlo methods and further refined using molecular dynamics simulation, obtaining thermodynamically stable peptide-Pd nanoparticle configurations. Sequence-dependent catalytic property differences for C-C coupling and olefin hydrogenation were then eluddated by identification of the catalytic active sites at the atomic level and quantitative prediction of relative reaction rates. This hybrid methodology provides a clear route to determine peptide-dependent structure/function relationships, enabling the generation of guidelines for catalyst design through rational tailoring of peptide sequences« less

Elucidation of peptide-directed palladium surface structure for biologically tunable nanocatalysts.

PubMed

Bedford, Nicholas M; Ramezani-Dakhel, Hadi; Slocik, Joseph M; Briggs, Beverly D; Ren, Yang; Frenkel, Anatoly I; Petkov, Valeri; Heinz, Hendrik; Naik, Rajesh R; Knecht, Marc R

2015-05-26

Peptide-enabled synthesis of inorganic nanostructures represents an avenue to access catalytic materials with tunable and optimized properties. This is achieved via peptide complexity and programmability that is missing in traditional ligands for catalytic nanomaterials. Unfortunately, there is limited information available to correlate peptide sequence to particle structure and catalytic activity to date. As such, the application of peptide-enabled nanocatalysts remains limited to trial and error approaches. In this paper, a hybrid experimental and computational approach is introduced to systematically elucidate biomolecule-dependent structure/function relationships for peptide-capped Pd nanocatalysts. Synchrotron X-ray techniques were used to uncover substantial particle surface structural disorder, which was dependent upon the amino acid sequence of the peptide capping ligand. Nanocatalyst configurations were then determined directly from experimental data using reverse Monte Carlo methods and further refined using molecular dynamics simulation, obtaining thermodynamically stable peptide-Pd nanoparticle configurations. Sequence-dependent catalytic property differences for C-C coupling and olefin hydrogenation were then elucidated by identification of the catalytic active sites at the atomic level and quantitative prediction of relative reaction rates. This hybrid methodology provides a clear route to determine peptide-dependent structure/function relationships, enabling the generation of guidelines for catalyst design through rational tailoring of peptide sequences.

Prediction and identification of potential immunodominant epitopes in glycoproteins B, C, E, G, and I of herpes simplex virus type 2.

PubMed

Pan, Mingjie; Wang, Xingsheng; Liao, Jianmin; Yin, Dengke; Li, Suqin; Pan, Ying; Wang, Yao; Xie, Guangyan; Zhang, Shumin; Li, Yuexi

2012-01-01

Twenty B candidate epitopes of glycoproteins B (gB2), C (gC2), E (gE2), G (gG2), and I (gI2) of herpes simplex virus type 2 (HSV-2) were predicted using DNAstar, Biosun, and Antheprot methods combined with the polynomial method. Subsequently, the biological functions of the peptides were tested via experiments in vitro. Among the 20 epitope peptides, 17 could react with the antisera to the corresponding parent proteins in the EIA tests. In particular, five peptides, namely, gB2(466-473) (EQDRKPRN), gC2(216-223) (GRTDRPSA), gE2(483-491) (DPPERPDSP), gG2(572-579) (EPPDDDDS), and gI2(286-295) (CRRRYRRPRG) had strong reaction with the antisera. All conjugates of the five peptides with the carrier protein BSA could stimulate mice into producing antibodies. The antisera to these peptides reacted strongly with the corresponding parent glycoproteins during the Western Blot tests, and the peptides reacted strongly with the antibodies against the parent glycoproteins during the EIA tests. The antisera against the five peptides could neutralize HSV-2 infection in vitro, which has not been reported until now. These results suggest that the immunodominant epitopes screened using software algorithms may be used for virus diagnosis and vaccine design against HSV-2.

SpecOMS: A Full Open Modification Search Method Performing All-to-All Spectra Comparisons within Minutes.

PubMed

David, Matthieu; Fertin, Guillaume; Rogniaux, Hélène; Tessier, Dominique

2017-08-04

The analysis of discovery proteomics experiments relies on algorithms that identify peptides from their tandem mass spectra. The almost exhaustive interpretation of these spectra remains an unresolved issue. At present, an important number of missing interpretations is probably due to peptides displaying post-translational modifications and variants that yield spectra that are particularly difficult to interpret. However, the emergence of a new generation of mass spectrometers that provide high fragment ion accuracy has paved the way for more efficient algorithms. We present a new software, SpecOMS, that can handle the computational complexity of pairwise comparisons of spectra in the context of large volumes. SpecOMS can compare a whole set of experimental spectra generated by a discovery proteomics experiment to a whole set of theoretical spectra deduced from a protein database in a few minutes on a standard workstation. SpecOMS can ingeniously exploit those capabilities to improve the peptide identification process, allowing strong competition between all possible peptides for spectrum interpretation. Remarkably, this software resolves the drawbacks (i.e., efficiency problems and decreased sensitivity) that usually accompany open modification searches. We highlight this promising approach using results obtained from the analysis of a public human data set downloaded from the PRIDE (PRoteomics IDEntification) database.

Hydrophilic Strong Anion Exchange (hSAX) Chromatography for Highly Orthogonal Peptide Separation of Complex Proteomes

PubMed Central

2013-01-01

Due to its compatibility and orthogonality to reversed phase (RP) liquid chromatography (LC) separation, ion exchange chromatography, and mainly strong cation exchange (SCX), has often been the first choice in multidimensional LC experiments in proteomics. Here, we have tested the ability of three strong anion exchanger (SAX) columns differing in their hydrophobicity to fractionate RAW264.7 macrophage cell lysate. IonPac AS24, a strong anion exchange material with ultralow hydrophobicity, demonstrated to be superior to other materials by fractionation and separation of tryptic peptides from both a mixture of 6 proteins as well as mouse cell lysate. The chromatography displayed very high orthogonality and high robustness depending on the hydrophilicity of column chemistry, which we termed hydrophilic strong anion exchange (hSAX). Mass spectrometry analysis of 34 SAX fractions from RAW264.7 macrophage cell lysate digest resulted in an identification of 9469 unique proteins and 126318 distinct peptides in one week of instrument time. Moreover, when compared to an optimized high pH/low pH RP separation approach, the method presented here raised the identification of proteins and peptides by 10 and 28%, respectively. This novel hSAX approach provides robust, reproducible, and highly orthogonal separation of complex protein digest samples for deep coverage proteome analysis. PMID:23294059

Interaction Analysis through Proteomic Phage Display

PubMed Central

2014-01-01

Phage display is a powerful technique for profiling specificities of peptide binding domains. The method is suited for the identification of high-affinity ligands with inhibitor potential when using highly diverse combinatorial peptide phage libraries. Such experiments further provide consensus motifs for genome-wide scanning of ligands of potential biological relevance. A complementary but considerably less explored approach is to display expression products of genomic DNA, cDNA, open reading frames (ORFs), or oligonucleotide libraries designed to encode defined regions of a target proteome on phage particles. One of the main applications of such proteomic libraries has been the elucidation of antibody epitopes. This review is focused on the use of proteomic phage display to uncover protein-protein interactions of potential relevance for cellular function. The method is particularly suited for the discovery of interactions between peptide binding domains and their targets. We discuss the largely unexplored potential of this method in the discovery of domain-motif interactions of potential biological relevance. PMID:25295249

Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger

PubMed Central

Wright, James C; Sugden, Deana; Francis-McIntyre, Sue; Riba-Garcia, Isabel; Gaskell, Simon J; Grigoriev, Igor V; Baker, Scott E; Beynon, Robert J; Hubbard, Simon J

2009-01-01

Background Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS) and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR). Results 405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6%) of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models. Conclusion This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST) data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method. PMID:19193216

A Bioinformatics Workflow for Variant Peptide Detection in Shotgun Proteomics*

PubMed Central

Li, Jing; Su, Zengliu; Ma, Ze-Qiang; Slebos, Robbert J. C.; Halvey, Patrick; Tabb, David L.; Liebler, Daniel C.; Pao, William; Zhang, Bing

2011-01-01

Shotgun proteomics data analysis usually relies on database search. However, commonly used protein sequence databases do not contain information on protein variants and thus prevent variant peptides and proteins from been identified. Including known coding variations into protein sequence databases could help alleviate this problem. Based on our recently published human Cancer Proteome Variation Database, we have created a protein sequence database that comprehensively annotates thousands of cancer-related coding variants collected in the Cancer Proteome Variation Database as well as noncancer-specific ones from the Single Nucleotide Polymorphism Database (dbSNP). Using this database, we then developed a data analysis workflow for variant peptide identification in shotgun proteomics. The high risk of false positive variant identifications was addressed by a modified false discovery rate estimation method. Analysis of colorectal cancer cell lines SW480, RKO, and HCT-116 revealed a total of 81 peptides that contain either noncancer-specific or cancer-related variations. Twenty-three out of 26 variants randomly selected from the 81 were confirmed by genomic sequencing. We further applied the workflow on data sets from three individual colorectal tumor specimens. A total of 204 distinct variant peptides were detected, and five carried known cancer-related mutations. Each individual showed a specific pattern of cancer-related mutations, suggesting potential use of this type of information for personalized medicine. Compatibility of the workflow has been tested with four popular database search engines including Sequest, Mascot, X!Tandem, and MyriMatch. In summary, we have developed a workflow that effectively uses existing genomic data to enable variant peptide detection in proteomics. PMID:21389108

Phage display biopanning and isolation of target-unrelated peptides: in search of nonspecific binders hidden in a combinatorial library.

PubMed

Bakhshinejad, Babak; Zade, Hesam Motaleb; Shekarabi, Hosna Sadat Zahed; Neman, Sara

2016-12-01

Phage display is known as a powerful methodology for the identification of targeting ligands that specifically bind to a variety of targets. The high-throughput screening of phage display combinatorial peptide libraries is performed through the affinity selection method of biopanning. Although phage display selection has proven very successful in the discovery of numerous high-affinity target-binding peptides with potential application in drug discovery and delivery, the enrichment of false-positive target-unrelated peptides (TUPs) without any actual affinity towards the target remains a major problem of library screening. Selection-related TUPs may emerge because of binding to the components of the screening system rather than the target. Propagation-related TUPs may arise as a result of faster growth rate of some phage clones enabling them to outcompete slow-propagating clones. Amplification of the library between rounds of biopanning makes a significant contribution to the selection of phage clones with propagation advantage. Distinguishing nonspecific TUPs from true target binders is of particular importance for the translation of biopanning findings from basic research to clinical applications. Different experimental and in silico approaches are applied to assess the specificity of phage display-derived peptides towards the target. Bioinformatic tools are playing a rapidly growing role in the analysis of biopanning data and identification of target-irrelevant TUPs. Recent progress in the introduction of efficient strategies for TUP detection holds enormous promise for the discovery of clinically relevant cell- and tissue-homing peptides and paves the way for the development of novel targeted diagnostic and therapeutic platforms in pharmaceutical areas.

Extensive characterization of Tupaia belangeri neuropeptidome using an integrated mass spectrometric approach.

PubMed

Petruzziello, Filomena; Fouillen, Laetitia; Wadensten, Henrik; Kretz, Robert; Andren, Per E; Rainer, Gregor; Zhang, Xiaozhe

2012-02-03

Neuropeptidomics is used to characterize endogenous peptides in the brain of tree shrews (Tupaia belangeri). Tree shrews are small animals similar to rodents in size but close relatives of primates, and are excellent models for brain research. Currently, tree shrews have no complete proteome information available on which direct database search can be allowed for neuropeptide identification. To increase the capability in the identification of neuropeptides in tree shrews, we developed an integrated mass spectrometry (MS)-based approach that combines methods including data-dependent, directed, and targeted liquid chromatography (LC)-Fourier transform (FT)-tandem MS (MS/MS) analysis, database construction, de novo sequencing, precursor protein search, and homology analysis. Using this integrated approach, we identified 107 endogenous peptides that have sequences identical or similar to those from other mammalian species. High accuracy MS and tandem MS information, with BLAST analysis and chromatographic characteristics were used to confirm the sequences of all the identified peptides. Interestingly, further sequence homology analysis demonstrated that tree shrew peptides have a significantly higher degree of homology to equivalent sequences in humans than those in mice or rats, consistent with the close phylogenetic relationship between tree shrews and primates. Our results provide the first extensive characterization of the peptidome in tree shrews, which now permits characterization of their function in nervous and endocrine system. As the approach developed fully used the conservative properties of neuropeptides in evolution and the advantage of high accuracy MS, it can be portable for identification of neuropeptides in other species for which the fully sequenced genomes or proteomes are not available.

Calibration of mass spectrometric peptide mass fingerprint data without specific external or internal calibrants

PubMed Central

Wolski, Witold E; Lalowski, Maciej; Jungblut, Peter; Reinert, Knut

2005-01-01

Background Peptide Mass Fingerprinting (PMF) is a widely used mass spectrometry (MS) method of analysis of proteins and peptides. It relies on the comparison between experimentally determined and theoretical mass spectra. The PMF process requires calibration, usually performed with external or internal calibrants of known molecular masses. Results We have introduced two novel MS calibration methods. The first method utilises the local similarity of peptide maps generated after separation of complex protein samples by two-dimensional gel electrophoresis. It computes a multiple peak-list alignment of the data set using a modified Minimum Spanning Tree (MST) algorithm. The second method exploits the idea that hundreds of MS samples are measured in parallel on one sample support. It improves the calibration coefficients by applying a two-dimensional Thin Plate Splines (TPS) smoothing algorithm. We studied the novel calibration methods utilising data generated by three different MALDI-TOF-MS instruments. We demonstrate that a PMF data set can be calibrated without resorting to external or relying on widely occurring internal calibrants. The methods developed here were implemented in R and are part of the BioConductor package mscalib available from . Conclusion The MST calibration algorithm is well suited to calibrate MS spectra of protein samples resulting from two-dimensional gel electrophoretic separation. The TPS based calibration algorithm might be used to correct systematic mass measurement errors observed for large MS sample supports. As compared to other methods, our combined MS spectra calibration strategy increases the peptide/protein identification rate by an additional 5 – 15%. PMID:16102175

Virtual screening of a milk peptide database for the identification of food-derived antimicrobial peptides.

PubMed

Liu, Yufang; Eichler, Jutta; Pischetsrieder, Monika

2015-11-01

Milk provides a wide range of bioactive substances, such as antimicrobial peptides and proteins. Our study aimed to identify novel antimicrobial peptides naturally present in milk. The components of an endogenous bovine milk peptide database were virtually screened for charge, amphipathy, and predicted secondary structure. Thus, 23 of 248 screened peptides were identified as candidates for antimicrobial effects. After commercial synthesis, their antimicrobial activities were determined against Escherichia coli NEB5α, E. coli ATCC25922, and Bacillus subtilis ATCC6051. In the tested concentration range (<2 mM), bacteriostatic activity of 14 peptides was detected including nine peptides inhibiting both Gram-positive and Gram-negative bacteria. The most effective fragment was TKLTEEEKNRLNFLKKISQRYQKFΑLPQYLK corresponding to αS2 -casein151-181 , with minimum inhibitory concentration (MIC) of 4.0 μM against B. subtilis ATCC6051, and minimum inhibitory concentrations of 16.2 μM against both E. coli strains. Circular dichroism spectroscopy revealed conformational changes of most active peptides in a membrane-mimic environment, transitioning from an unordered to α-helical structure. Screening of food peptide databases by prediction tools is an efficient method to identify novel antimicrobial food-derived peptides. Milk-derived antimicrobial peptides may have potential use as functional food ingredients and help to understand the molecular mechanisms of anti-infective milk effects. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Streptavidin mutants

DOEpatents

Sano, Takeshi; Cantor, Charles R.; Vajda, Sandor; Reznik, Gabriel O.; Smith, Cassandra L.; Pandori, Mark W.

2000-01-01

The present invention relates to streptavidin proteins and peptides having a altered physical properties such as an increased stability or increased or decreased affinity for binding biotin. The invention also relates to methods for the detection, identification, separation and isolation of targets using streptavidin proteins or peptides. Streptavidin with increased or reduced affinity allows for the use of the streptavidin-biotin coupling systems for detection and isolation systems wherein it is necessary to remove of one or the other of the binding partners. Such systems are useful for the purification of functional proteins and viable cells. The invention also relates to nucleic acids which encode these streptavidin proteins and peptides and to recombinant cells such as bacteria, yeast and mammalian cells which contain these nucleic acids.

Screening and identification of linear B-cell epitopes and entry-blocking peptide of severe acute respiratory syndrome (SARS)-associated coronavirus using synthetic overlapping peptide library.

PubMed

Hu, Hongbo; Li, Li; Kao, Richard Y; Kou, Binbin; Wang, Zhanguo; Zhang, Liang; Zhang, Huiyuan; Hao, Zhiyong; Tsui, Wayne H; Ni, Anping; Cui, Lianxian; Fan, Baoxing; Guo, Feng; Rao, Shuan; Jiang, Chengyu; Li, Qian; Sun, Manji; He, Wei; Liu, Gang

2005-01-01

A 10-mer overlapping peptide library has been synthesized for screening and identification of linear B-cell epitopes of severe acute respiratory syndrome associated coronavirus (SARS-CoV), which spanned the major structural proteins of SARS-CoV. One hundred and eleven candidate peptides were positive according to the result of PEPscan, which were assembled into 22 longer peptides. Five of these peptides showed high cross-immunoreactivities (approximately 66.7 to 90.5%) to SARS convalescent patients' sera from the severest epidemic regions of the China mainland. Most interestingly, S(471-503), a peptide located at the receptor binding domain (RBD) of SARS-CoV, could specifically block the binding between the RBD and angiotensin-converting enzyme 2, resulting in the inhibition of SARS-CoV entrance into host cells in vitro. The study demonstrated that S(471-503) peptide was a potential immunoantigen for the development of peptide-based vaccine or a candidate for further drug evaluation against the SARS-CoV virus-cell fusion.

A linear programming model for protein inference problem in shotgun proteomics.

PubMed

Huang, Ting; He, Zengyou

2012-11-15

Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.

Optimization of the β-Elimination/Michael Addition Chemistry on Reversed-Phase Supports for Mass Spectrometry Analysis of O-Linked Protein Modifications

PubMed Central

Nika, Heinz; Nieves, Edward; Hawke, David H.; Angeletti, Ruth Hogue

2013-01-01

We previously adapted the β-elimination/Michael addition chemistry to solid-phase derivatization on reversed-phase supports, and demonstrated the utility of this reaction format to prepare phosphoseryl peptides in unfractionated protein digests for mass spectrometric identification and facile phosphorylation-site determination. Here, we have expanded the use of this technique to β-N-acetylglucosamine peptides, modified at serine/threonine, phosphothreonyl peptides, and phosphoseryl/phosphothreonyl peptides, followed in sequence by proline. The consecutive β-elimination with Michael addition was adapted to optimize the solid-phase reaction conditions for throughput and completeness of derivatization. The analyte remained intact during derivatization and was recovered efficiently from the silica-based, reversed-phase support with minimal sample loss. The general use of the solid-phase approach for enzymatic dephosphorylation was demonstrated with phosphoseryl and phosphothreonyl peptides and was used as an orthogonal method to confirm the identity of phosphopeptides in proteolytic mixtures. The solid-phase approach proved highly suitable to prepare substrates from low-level amounts of protein digests for phosphorylation-site determination by chemical-targeted proteolysis. The solid-phase protocol provides for a simple, robust, and efficient tool to prepare samples for phosphopeptide identification in MALDI mass maps of unfractionated protein digests, using standard equipment available in most biological laboratories. The use of a solid-phase analytical platform is expected to be readily expanded to prepare digest from O-glycosylated- and O-sulfonated proteins for mass spectrometry-based structural characterization. PMID:23997661

Capillary zone electrophoresis for analysis of complex proteomes using an electrokinetically pumped sheath flow nanospray interface

PubMed Central

Sun, Liangliang; Zhu, Guijie; Yan, Xiaojing; Champion, Mathew M.

2014-01-01

The vast majority of proteomic studies employ reversed-phase high-performance liquid chromatography coupled with tandem mass spectrometry for analysis of the tryptic digest of a cellular lysate. This technology is quite mature, and typically provides identification of hundreds to thousands of peptides, which is used to infer the identity of hundreds to thousands of proteins. These approaches usually require milligrams to micrograms of starting material. Capillary zone electrophoresis provides an interesting alternative separation method based on a different separation mechanism than HPLC. Capillary electrophoresis received some attention for protein analysis beginning 25 years ago. Those efforts stalled because of the limited performance of the electrospray interfaces and the limited speed and sensitivity of mass spectrometers of that era. This review considers a new electrospray interface design coupled with Orbitrap Velos and linear Q-trap mass spectrometers. Capillary zone electrophoresis coupled with this interface and these detectors provides single shot detection of >1,250 peptides from an E. coli digest in less than one hour, identification of nearly 5,000 peptides from analysis of seven fractions produced by solid-phase extraction of the E. coli digest in a six hour total analysis time, low attomole detection limits for peptides generated from standard proteins, and high zeptomole detection limits for selected ion monitoring of peptides. Incorporation of an integrated on-line immobilized trypsin microreactor allows digestion and analysis of picogram amounts of a complex eukaryotic proteome. PMID:24277677

Authentication of processed meat products by peptidomic analysis using rapid ambient mass spectrometry.

PubMed

Montowska, Magdalena; Alexander, Morgan R; Tucker, Gregory A; Barrett, David A

2015-11-15

We present the application of a novel ambient LESA-MS method for the authentication of processed meat products. A set of 25 species and protein-specific heat stable peptide markers has been detected in processed samples manufactured from beef, pork, horse, chicken and turkey meat. We demonstrate that several peptides derived from myofibrillar and sarcoplasmic proteins are sufficiently resistant to processing to serve as specific markers of processed products. The LESA-MS technique required minimal sample preparation without fractionation and enabled the unambiguous and simultaneous identification of skeletal muscle proteins and peptides as well as other components of animal origin, including the milk protein such as casein alpha-S1, in whole meat product digests. We have identified, for the first time, six fast type II and five slow/cardiac type I MHC peptide markers in various processed meat products. The study demonstrates that complex mixtures of processed proteins/peptides can be examined effectively using this approach. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modification site localization scoring integrated into a search engine.

PubMed

Baker, Peter R; Trinidad, Jonathan C; Chalkley, Robert J

2011-07-01

Large proteomic data sets identifying hundreds or thousands of modified peptides are becoming increasingly common in the literature. Several methods for assessing the reliability of peptide identifications both at the individual peptide or data set level have become established. However, tools for measuring the confidence of modification site assignments are sparse and are not often employed. A few tools for estimating phosphorylation site assignment reliabilities have been developed, but these are not integral to a search engine, so require a particular search engine output for a second step of processing. They may also require use of a particular fragmentation method and are mostly only applicable for phosphorylation analysis, rather than post-translational modifications analysis in general. In this study, we present the performance of site assignment scoring that is directly integrated into the search engine Protein Prospector, which allows site assignment reliability to be automatically reported for all modifications present in an identified peptide. It clearly indicates when a site assignment is ambiguous (and if so, between which residues), and reports an assignment score that can be translated into a reliability measure for individual site assignments.

HLaffy: estimating peptide affinities for Class-1 HLA molecules by learning position-specific pair potentials.

PubMed

Mukherjee, Sumanta; Bhattacharyya, Chiranjib; Chandra, Nagasuma

2016-08-01

T-cell epitopes serve as molecular keys to initiate adaptive immune responses. Identification of T-cell epitopes is also a key step in rational vaccine design. Most available methods are driven by informatics and are critically dependent on experimentally obtained training data. Analysis of a training set from Immune Epitope Database (IEDB) for several alleles indicates that the sampling of the peptide space is extremely sparse covering a tiny fraction of the possible nonamer space, and also heavily skewed, thus restricting the range of epitope prediction. We present a new epitope prediction method that has four distinct computational modules: (i) structural modelling, estimating statistical pair-potentials and constraint derivation, (ii) implicit modelling and interaction profiling, (iii) feature representation and binding affinity prediction and (iv) use of graphical models to extract peptide sequence signatures to predict epitopes for HLA class I alleles. HLaffy is a novel and efficient epitope prediction method that predicts epitopes for any Class-1 HLA allele, by estimating the binding strengths of peptide-HLA complexes which is achieved through learning pair-potentials important for peptide binding. It relies on the strength of the mechanistic understanding of peptide-HLA recognition and provides an estimate of the total ligand space for each allele. The performance of HLaffy is seen to be superior to the currently available methods. The method is made accessible through a webserver http://proline.biochem.iisc.ernet.in/HLaffy : nchandra@biochem.iisc.ernet.in Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Probabilistic consensus scoring improves tandem mass spectrometry peptide identification.

PubMed

Nahnsen, Sven; Bertsch, Andreas; Rahnenführer, Jörg; Nordheim, Alfred; Kohlbacher, Oliver

2011-08-05

Database search is a standard technique for identifying peptides from their tandem mass spectra. To increase the number of correctly identified peptides, we suggest a probabilistic framework that allows the combination of scores from different search engines into a joint consensus score. Central to the approach is a novel method to estimate scores for peptides not found by an individual search engine. This approach allows the estimation of p-values for each candidate peptide and their combination across all search engines. The consensus approach works better than any single search engine across all different instrument types considered in this study. Improvements vary strongly from platform to platform and from search engine to search engine. Compared to the industry standard MASCOT, our approach can identify up to 60% more peptides. The software for consensus predictions is implemented in C++ as part of OpenMS, a software framework for mass spectrometry. The source code is available in the current development version of OpenMS and can easily be used as a command line application or via a graphical pipeline designer TOPPAS.

Identification of a Novel Lysosomal Trafficking Peptide using Phage Display Biopanning Coupled with Endocytic Selection Pressure

PubMed Central

2015-01-01

Methods to select ligands that accumulate specifically in cancer cells and traffic through a defined endocytic pathway may facilitate rapid pairing of ligands with linkers suitable for drug conjugate therapies. We performed phage display biopanning on cancer cells that are treated with selective inhibitors of a given mechanism of endocytosis. Using chlorpromazine to inhibit clathrin-mediated endocytosis in H1299 nonsmall cell lung cancer cells, we identified two clones, ATEPRKQYATPRVFWTDAPG (15.1) and a novel peptide LQWRRDDNVHNFGVWARYRL (H1299.3). The peptides segregate by mechanism of endocytosis and subsequent location of subcellular accumulation. The H1299.3 peptide primarily utilizes clathrin-mediated endocytosis and colocalizes with Lamp1, a lysosomal marker. Conversely, the 15.1 peptide is clathrin-independent and localizes to a perinuclear region. Thus, this novel phage display scheme allows for selection of peptides that selectively internalize into cells via a known mechanism of endocytosis. These types of selections may allow for better matching of linker with targeting ligand by selecting ligands that internalize and traffic to known subcellular locations. PMID:25188559

PEPA test: fast and powerful differential analysis from relative quantitative proteomics data using shared peptides.

PubMed

Jacob, Laurent; Combes, Florence; Burger, Thomas

2018-06-18

We propose a new hypothesis test for the differential abundance of proteins in mass-spectrometry based relative quantification. An important feature of this type of high-throughput analyses is that it involves an enzymatic digestion of the sample proteins into peptides prior to identification and quantification. Due to numerous homology sequences, different proteins can lead to peptides with identical amino acid chains, so that their parent protein is ambiguous. These so-called shared peptides make the protein-level statistical analysis a challenge and are often not accounted for. In this article, we use a linear model describing peptide-protein relationships to build a likelihood ratio test of differential abundance for proteins. We show that the likelihood ratio statistic can be computed in linear time with the number of peptides. We also provide the asymptotic null distribution of a regularized version of our statistic. Experiments on both real and simulated datasets show that our procedures outperforms state-of-the-art methods. The procedures are available via the pepa.test function of the DAPAR Bioconductor R package.

Separation of multiphosphorylated peptide isomers by hydrophilic interaction chromatography on an aminopropyl phase.

PubMed

Singer, David; Kuhlmann, Julia; Muschket, Matthias; Hoffmann, Ralf

2010-08-01

The separation of isomeric phosphorylated peptides is challenging and often impossible for multiphosphorylated isomers using chromatographic and capillary electrophoretic methods. In this study we investigated the separation of a set of single-, double-, and triple-phosphorylated peptides (corresponding to the human tau protein) by ion-pair reversed-phase chromatography (IP-RPC) and hydrophilic interaction chromatography (HILIC). In HILIC both hydroxyl and aminopropyl stationary phases were tested with aqueous acetonitrile in order to assess their separation efficiency. The hydroxyl phase separated the phosphopeptides very well from the unphosphorylated analogue, while on the aminopropyl phase even isomeric phosphopeptides attained baseline separation. Thus, up to seven phosphorylated versions of a given tau domain were separated. Furthermore, the low concentration of an acidic ammonium formate buffer allowed an online analysis with electrospray ionization tandem mass spectrometry (ESI-MS/MS) to be conducted, enabling peptide sequencing and identification of phosphorylation sites.

Mapping Protein Surface Accessibility via an Electron Transfer Dissociation Selectively Cleavable Hydrazone Probe*

PubMed Central

Vasicek, Lisa; O'Brien, John P.; Browning, Karen S.; Tao, Zhihua; Liu, Hung-Wen; Brodbelt, Jennifer S.

2012-01-01

A protein's surface influences its role in protein-protein interactions and protein-ligand binding. Mass spectrometry can be used to give low resolution structural information about protein surfaces and conformations when used in combination with derivatization methods that target surface accessible amino acid residues. However, pinpointing the resulting modified peptides upon enzymatic digestion of the surface-modified protein is challenging because of the complexity of the peptide mixture and low abundance of modified peptides. Here a novel hydrazone reagent (NN) is presented that allows facile identification of all modified surface residues through a preferential cleavage upon activation by electron transfer dissociation coupled with a collision activation scan to pinpoint the modified residue in the peptide sequence. Using this approach, the correlation between percent reactivity and surface accessibility is demonstrated for two biologically active proteins, wheat eIF4E and PARP-1 Domain C. PMID:22393264

Identification of sixteen peptides reflecting heat and/or storage induced processes by profiling of commercial milk samples.

PubMed

Ebner, Jennifer; Baum, Florian; Pischetsrieder, Monika

2016-09-16

Peptide profiles of different drinking milk samples were examined to study how the peptide fingerprint of milk reflects processing conditions. The combination of a simple and fast method for peptide extraction using stage tips and MALDI-TOF-MS enabled the fast and easy generation and relative quantification of peptide fingerprints for high-temperature short-time (HTST), extended shelf life (ESL) and ultra-high temperature (UHT) milk of the same dairies. The relative quantity of 16 peptides changed as a function of increasing heat load. Additional heating experiments showed that among those, the intensity of peptide β-casein 196-209 (m/z 1460.9Da) was most heavily influenced by heat treatment indicating a putative marker peptide for milk processing conditions. Storage experiments with HTST- and UHT milk revealed that the differences between different types of milk samples were not only caused by the heating process. Relevant was also the proteolytic activity of enzymes during storage, which were differently influenced by the heat treatment. These results indicate that the peptide profile may be suitable to monitor processing as well as storage conditions of milk. In the present study, peptide profiling of different types of milk was carried out by MALDI-TOF-MS after stage-tip extraction and relative quantification using an internal reference peptide. Although MALDI-TOF-MS covers only part of the peptidome, the method is easy and quick and is, therefore, suited for routine analysis to address several aspects of food authenticity. Using this method, 16 native peptides were detected in milk that could be modulated by different industrial processes. Subsequent heating and storage experiments with pasteurized and UHT milk confirmed that these peptides are indeed related to the production or storage conditions of the respective products. Furthermore, the heating experiments revealed one peptide, namely the β-casein-derived sequence β-casein 196-209, which underwent particularly sensitive modulation by heat treatment. The present results indicate that the modulated peptides, and especially β-casein 196-209, may be suitable markers to monitor processing parameters for industrial milk production. Furthermore, the model experiments suggest mechanisms leading to the formation or degradation of peptides, which help to evaluate putative marker peptides. Copyright © 2016 Elsevier B.V. All rights reserved.

Revealing the first uridyl peptide antibiotic biosynthetic gene cluster and probing pacidamycin biosynthesis.

PubMed

Rackham, Emma J; Grüschow, Sabine; Goss, Rebecca J M

2011-01-01

There is an urgent need for new antibiotics with resistance continuing to emerge toward existing classes. The pacidamycin antibiotics possess a novel scaffold and exhibit unexploited bioactivity rendering them attractive research targets. We recently reported the first identification of a biosynthetic cluster encoding uridyl peptide antibiotic assembly and the engineering of pacidamycin biosynthesis into a heterologous host. We report here our methods toward identifying the biosynthetic cluster. Our initial experiments employed conventional methods of probing a cosmid library using PCR and Southern blotting, however it became necessary to adopt a state-of-the-art genome scanning  and in silico hybridization approach  to pin point the cluster. Here we describe our "real" and "virtual" probing methods and contrast the benefits and pitfalls of each approach. 

Identification of glycopeptides as post-translationally modified neoantigens in leukemia

PubMed Central

Malaker, Stacy A.; Penny, Sarah A.; Steadman, Lora G.; Myers, Paisley T.; Loke, Justin C; Raghavan, Manoj; Bai, Dina L.; Shabanowitz, Jeffrey; Hunt, Donald F.; Cobbold, Mark

2017-01-01

Leukemias are highly immunogenic but have a low mutational load, providing few mutated peptide targets. Thus, the identification of alternative neoantigens is a pressing need. Here, we identify 36 MHC class I–associated peptide antigens with O-linked β-N-acetylglucosamine (O-GlcNAc) modifications as candidate neoantigens, using three experimental approaches. Thirteen of these peptides were also detected with disaccharide units on the same residues and two contain either mono- and/or di-methylated arginine residues. A subset were linked with key cancer pathways, and these peptides were shared across all of the leukemia patient samples tested (5/5). Seven of the O-GlcNAc peptides were synthesized and five (71%) were shown to be associated with multifunctional memory T-cell responses in healthy donors. An O-GlcNAc-specific T-cell line specifically killed autologous cells pulsed with the modified peptide, but not the equivalent unmodified peptide. Therefore, these post-translationally modified neoantigens provide logical targets for cancer immunotherapy. PMID:28314751

Computational approaches to protein inference in shotgun proteomics

PubMed Central

2012-01-01

Shotgun proteomics has recently emerged as a powerful approach to characterizing proteomes in biological samples. Its overall objective is to identify the form and quantity of each protein in a high-throughput manner by coupling liquid chromatography with tandem mass spectrometry. As a consequence of its high throughput nature, shotgun proteomics faces challenges with respect to the analysis and interpretation of experimental data. Among such challenges, the identification of proteins present in a sample has been recognized as an important computational task. This task generally consists of (1) assigning experimental tandem mass spectra to peptides derived from a protein database, and (2) mapping assigned peptides to proteins and quantifying the confidence of identified proteins. Protein identification is fundamentally a statistical inference problem with a number of methods proposed to address its challenges. In this review we categorize current approaches into rule-based, combinatorial optimization and probabilistic inference techniques, and present them using integer programing and Bayesian inference frameworks. We also discuss the main challenges of protein identification and propose potential solutions with the goal of spurring innovative research in this area. PMID:23176300

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

PubMed

Piehowski, Paul D; Petyuk, Vladislav A; Sandoval, John D; Burnum, Kristin E; Kiebel, Gary R; Monroe, Matthew E; Anderson, Gordon A; Camp, David G; Smith, Richard D

2013-03-01

For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection--referred to as STEPS--utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true-positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

reSpect: Software for Identification of High and Low Abundance Ion Species in Chimeric Tandem Mass Spectra

PubMed Central

Shteynberg, David; Mendoza, Luis; Hoopmann, Michael R.; Sun, Zhi; Schmidt, Frank; Deutsch, Eric W.; Moritz, Robert L.

2016-01-01

Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contributes to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), that enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the following iterations. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website. PMID:26419769

Extracellular Identification of a Processed Type II ComR/ComS Pheromone of Streptococcus mutans

PubMed Central

Khan, Rabia; Rukke, Håkon V.; Ricomini Filho, Antonio Pedro; Fimland, Gunnar; Arntzen, Magnus Ø.; Thiede, Bernd

2012-01-01

The competence-stimulating peptide (CSP) and the sigX-inducing peptide (XIP) are known to induce Streptococcus mutans competence for genetic transformation. For both pheromones, direct identification of the native peptides has not been accomplished. The fact that extracellular XIP activity was recently observed in a chemically defined medium devoid of peptides, as mentioned in an accompanying paper (K. Desai, L. Mashburn-Warren, M. J. Federle, and D. A. Morrison, J. Bacteriol. 194:3774–3780, 2012), provided ideal conditions for native XIP identification. To search for the XIP identity, culture supernatants were filtered to select for peptides of less than 3 kDa, followed by C18 extraction. One peptide, not detected in the supernatant of a comS deletion mutant, was identified by tandem mass spectrometry (MS/MS) fragmentation as identical to the ComS C-terminal sequence GLDWWSL. ComS processing did not require Eep, a peptidase involved in processing or import of bacterial small hydrophobic peptides, since eep deletion had no inhibitory effect on XIP production or on synthetic XIP response. We investigated whether extracellular CSP was also produced. A reporter assay for CSP activity detection, as well as MS analysis of supernatants, revealed that CSP was not present at detectable levels. In addition, a mutant with deletion of the CSP-encoding gene comC produced endogenous XIP levels similar to those of a nondeletion mutant. The results indicate that XIP pheromone production is a natural phenomenon that may occur in the absence of natural CSP pheromone activity and that the heptapeptide GLDWWSL is an extracellular processed form of ComS, possibly the active XIP pheromone. This is the first report of direct identification of a ComR/ComS pheromone. PMID:22609914

reSpect: software for identification of high and low abundance ion species in chimeric tandem mass spectra.

PubMed

Shteynberg, David; Mendoza, Luis; Hoopmann, Michael R; Sun, Zhi; Schmidt, Frank; Deutsch, Eric W; Moritz, Robert L

2015-11-01

Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contribute to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), which enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post-search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the iterations that follow. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website. Graphical Abstract ᅟ.

reSpect: Software for Identification of High and Low Abundance Ion Species in Chimeric Tandem Mass Spectra

NASA Astrophysics Data System (ADS)

Shteynberg, David; Mendoza, Luis; Hoopmann, Michael R.; Sun, Zhi; Schmidt, Frank; Deutsch, Eric W.; Moritz, Robert L.

2015-11-01

Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contribute to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), which enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post-search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the iterations that follow. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website.

Mass Spectrometric Identification of the Arginine and Lysine deficient Proline Rich Glutamine Rich Wheat Storage Proteins

USDA-ARS?s Scientific Manuscript database

Tandem mass spectrometry (MS/MS) of enzymatic digest has made possible identification of a wide variety of proteins and complex samples prepared by such techniques as RP-HPLC or 2-D gel electrophoresis. Success requires peptide fragmentation to be indicative of the peptide amino acid sequence. The f...

MALDI TOF imaging mass spectrometry in clinical pathology: a valuable tool for cancer diagnostics (review).

PubMed

Kriegsmann, Jörg; Kriegsmann, Mark; Casadonte, Rita

2015-03-01

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) is an evolving technique in cancer diagnostics and combines the advantages of mass spectrometry (proteomics), detection of numerous molecules, and spatial resolution in histological tissue sections and cytological preparations. This method allows the detection of proteins, peptides, lipids, carbohydrates or glycoconjugates and small molecules.Formalin-fixed paraffin-embedded tissue can also be investigated by IMS, thus, this method seems to be an ideal tool for cancer diagnostics and biomarker discovery. It may add information to the identification of tumor margins and tumor heterogeneity. The technique allows tumor typing, especially identification of the tumor of origin in metastatic tissue, as well as grading and may provide prognostic information. IMS is a valuable method for the identification of biomarkers and can complement histology, immunohistology and molecular pathology in various fields of histopathological diagnostics, especially with regard to identification and grading of tumors.

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Na, Seungjin; Payne, Samuel H.; Bandeira, Nuno

The spectral networks approach enables the detection of pairs of spectra from related peptides and thus allows for the propagation of annotations from identified peptides to unidentified spectra. Beyond allowing for unbiased discovery of unexpected post-translational modifications, spectral networks are also applicable to multi-species comparative proteomics or metaproteomics to identify numerous orthologous versions of a protein. We present algorithmic and statistical advances in spectral networks that have made it possible to rigorously assess the statistical significance of spectral pairs and accurately estimate the error rate of identifications via propagation. In the analysis of three related Cyanothece species, a model organismmore » for biohydrogen production, spectral networks identified peptides with highly divergent sequences with up to dozens of variants per peptide, including many novel peptides in species that lack a sequenced genome. Furthermore, spectral networks strongly suggested the presence of novel peptides even in genomically characterized species (i.e. missing from databases) in that a significant portion of unidentified multi-species networks included at least two polymorphic peptide variants.« less

Peptide Array X-Linking (PAX): A New Peptide-Protein Identification Approach

PubMed Central

Okada, Hirokazu; Uezu, Akiyoshi; Soderblom, Erik J.; Moseley, M. Arthur; Gertler, Frank B.; Soderling, Scott H.

2012-01-01

Many protein interaction domains bind short peptides based on canonical sequence consensus motifs. Here we report the development of a peptide array-based proteomics tool to identify proteins directly interacting with ligand peptides from cell lysates. Array-formatted bait peptides containing an amino acid-derived cross-linker are photo-induced to crosslink with interacting proteins from lysates of interest. Indirect associations are removed by high stringency washes under denaturing conditions. Covalently trapped proteins are subsequently identified by LC-MS/MS and screened by cluster analysis and domain scanning. We apply this methodology to peptides with different proline-containing consensus sequences and show successful identifications from brain lysates of known and novel proteins containing polyproline motif-binding domains such as EH, EVH1, SH3, WW domains. These results suggest the capacity of arrayed peptide ligands to capture and subsequently identify proteins by mass spectrometry is relatively broad and robust. Additionally, the approach is rapid and applicable to cell or tissue fractions from any source, making the approach a flexible tool for initial protein-protein interaction discovery. PMID:22606326

Isolation and identification of a plasmatocyte-spreading peptide from the hemolymph of the lepidopteran insect Pseudoplusia includens.

PubMed

Clark, K D; Pech, L L; Strand, M R

1997-09-12

Insect blood cells (hemocytes) play an essential role in defense against parasites and other pathogenic organisms that infect insects. A key class of hemocytes involved in insect cellular immunity is plasmatocytes. Here we describe the isolation and identification of a peptide from the moth Pseudoplusia includens that mediates the spreading of plasmatocytes to foreign surfaces. This peptide, designated plasmatocyte-spreading peptide (PSP1), contains 23 amino acid residues in the following sequence: H-ENFNGGCLAGYMRTADGRCKPTF-OH. In vitro assays using the synthetic peptide at concentrations >/=2 nM induced plasmatocytes from P. includens to spread on the surface of culture dishes. Injection of this peptide into P. includens larvae caused a transient depletion of plasmatocytes from circulation. Labeling studies indicated that this peptide induced 75% of plasmatocytes that were double-labeled by the monoclonal antibodies 49G3A3 and 43E9A8 to spread, whereas plasma induced significantly more plasmatocytes to spread. This suggests that only a certain subpopulation of plasmatocytes responds to the peptide and that other peptidyl factors mediate plasmatocyte adhesion responses.

Tandem mass spectrometry of human tryptic blood peptides calculated by a statistical algorithm and captured by a relational database with exploration by a general statistical analysis system.

PubMed

Bowden, Peter; Beavis, Ron; Marshall, John

2009-11-02

A goodness of fit test may be used to assign tandem mass spectra of peptides to amino acid sequences and to directly calculate the expected probability of mis-identification. The product of the peptide expectation values directly yields the probability that the parent protein has been mis-identified. A relational database could capture the mass spectral data, the best fit results, and permit subsequent calculations by a general statistical analysis system. The many files of the Hupo blood protein data correlated by X!TANDEM against the proteins of ENSEMBL were collected into a relational database. A redundant set of 247,077 proteins and peptides were correlated by X!TANDEM, and that was collapsed to a set of 34,956 peptides from 13,379 distinct proteins. About 6875 distinct proteins were only represented by a single distinct peptide, 2866 proteins showed 2 distinct peptides, and 3454 proteins showed at least three distinct peptides by X!TANDEM. More than 99% of the peptides were associated with proteins that had cumulative expectation values, i.e. probability of false positive identification, of one in one hundred or less. The distribution of peptides per protein from X!TANDEM was significantly different than those expected from random assignment of peptides.

Experimental Methods for Protein Interaction Identification and Characterization

NASA Astrophysics Data System (ADS)

Uetz, Peter; Titz, Björn; Cagney, Gerard

There are dozens of methods for the detection of protein-protein interactions but they fall into a few broad categories. Fragment complementation assays such as the yeast two-hybrid (Y2H) system are based on split proteins that are functionally reconstituted by fusions of interacting proteins. Biophysical methods include structure determination and mass spectrometric (MS) identification of proteins in complexes. Biochemical methods include methods such as far western blotting and peptide arrays. Only the Y2H and protein complex purification combined with MS have been used on a larger scale. Due to the lack of data it is still difficult to compare these methods with respect to their efficiency and error rates. Current data does not favor any particular method and thus multiple experimental approaches are necessary to maximally cover the interactome of any target cell or organism.

Bioactive peptides derived from traditional Chinese medicine and traditional Chinese food: A review.

PubMed

Liu, Ming; Wang, Yunpu; Liu, Yuhuan; Ruan, Roger

2016-11-01

There is an urgent treat of numerous chronic diseases including heart disease, stroke, cancer, chronic respiratory diseases and diabetes, which have a significant influence on the health of people worldwide. In addition to numerous preventive and therapeutic drug treatments, important advances have been achieved in the identification of bioactive peptides that may contribute to long-term health. Although bioactive peptides with various biological activities received unprecedented attention, as a new source of bioactive peptides, the significant role of bioactive peptides from traditional Chinese medicine and traditional Chinese food has not fully appreciated compared to other bioactive components. Hence, identification and bioactivity assessment of these peptides could benefit the pharmaceutical and food industry. Furthermore, the functional properties of bioactive peptides help to demystify drug properties and health benefits of traditional Chinese medicine and traditional Chinese food. This paper reviews the generation and biofunctional properties of various bioactive peptides derived from traditional Chinese medicine and traditional Chinese food. Mechanisms of digestion, bioavailability of bioactive peptides and interactions between traditional Chinese medicine and traditional Chinese food are also summarized in this review. Copyright © 2016 Elsevier Ltd. All rights reserved.

Screening Method for the Discovery of Potential Bioactive Cysteine-Containing Peptides Using 3D Mass Mapping

NASA Astrophysics Data System (ADS)

van Oosten, Luuk N.; Pieterse, Mervin; Pinkse, Martijn W. H.; Verhaert, Peter D. E. M.

2015-12-01

Animal venoms and toxins are a valuable source of bioactive peptides with pharmacologic relevance as potential drug leads. A large subset of biologically active peptides discovered up till now contain disulfide bridges that enhance stability and activity. To discover new members of this class of peptides, we developed a workflow screening specifically for those peptides that contain inter- and intra-molecular disulfide bonds by means of three-dimensional (3D) mass mapping. Two intrinsic properties of the sulfur atom, (1) its relatively large negative mass defect, and (2) its isotopic composition, allow for differentiation between cysteine-containing peptides and peptides lacking sulfur. High sulfur content in a peptide decreases the normalized nominal mass defect (NMD) and increases the normalized isotopic shift (NIS). Hence in a 3D plot of mass, NIS, and NMD, peptides with sulfur appear in this plot with a distinct spatial localization compared with peptides that lack sulfur. In this study we investigated the skin secretion of two frog species; Odorrana schmackeri and Bombina variegata. Peptides from the crude skin secretions were separated by nanoflow LC, and of all eluting peptides high resolution zoom scans were acquired in order to accurately determine both monoisotopic mass and average mass. Both the NMD and the NIS were calculated from the experimental data using an in-house developed MATLAB script. Candidate peptides exhibiting a low NMD and high NIS values were selected for targeted de novo sequencing, and this resulted in the identification of several novel inter- and intra-molecular disulfide bond containing peptides.

The NISTmAb tryptic peptide spectral library for monoclonal antibody characterization.

PubMed

Dong, Qian; Liang, Yuxue; Yan, Xinjian; Markey, Sanford P; Mirokhin, Yuri A; Tchekhovskoi, Dmitrii V; Bukhari, Tallat H; Stein, Stephen E

2018-04-01

We describe the creation of a mass spectral library composed of all identifiable spectra derived from the tryptic digest of the NISTmAb IgG1κ. The library is a unique reference spectral collection developed from over six million peptide-spectrum matches acquired by liquid chromatography-mass spectrometry (LC-MS) over a wide range of collision energy. Conventional one-dimensional (1D) LC-MS was used for various digestion conditions and 20- and 24-fraction two-dimensional (2D) LC-MS studies permitted in-depth analyses of single digests. Computer methods were developed for automated analysis of LC-MS isotopic clusters to determine the attributes for all ions detected in the 1D and 2D studies. The library contains a selection of over 12,600 high-quality tandem spectra of more than 3,300 peptide ions identified and validated by accurate mass, differential elution pattern, and expected peptide classes in peptide map experiments. These include a variety of biologically modified peptide spectra involving glycosylated, oxidized, deamidated, glycated, and N/C-terminal modified peptides, as well as artifacts. A complete glycation profile was obtained for the NISTmAb with spectra for 58% and 100% of all possible glycation sites in the heavy and light chains, respectively. The site-specific quantification of methionine oxidation in the protein is described. The utility of this reference library is demonstrated by the analysis of a commercial monoclonal antibody (adalimumab, Humira®), where 691 peptide ion spectra are identifiable in the constant regions, accounting for 60% coverage for both heavy and light chains. The NIST reference library platform may be used as a tool for facile identification of the primary sequence and post-translational modifications, as well as the recognition of LC-MS method-induced artifacts for human and recombinant IgG antibodies. Its development also provides a general method for creating comprehensive peptide libraries of individual proteins.

The NISTmAb tryptic peptide spectral library for monoclonal antibody characterization

PubMed Central

Dong, Qian; Liang, Yuxue; Yan, Xinjian; Markey, Sanford P.; Mirokhin, Yuri A.; Tchekhovskoi, Dmitrii V.; Bukhari, Tallat H.; Stein, Stephen E.

2018-01-01

ABSTRACT We describe the creation of a mass spectral library composed of all identifiable spectra derived from the tryptic digest of the NISTmAb IgG1κ. The library is a unique reference spectral collection developed from over six million peptide-spectrum matches acquired by liquid chromatography-mass spectrometry (LC-MS) over a wide range of collision energy. Conventional one-dimensional (1D) LC-MS was used for various digestion conditions and 20- and 24-fraction two-dimensional (2D) LC-MS studies permitted in-depth analyses of single digests. Computer methods were developed for automated analysis of LC-MS isotopic clusters to determine the attributes for all ions detected in the 1D and 2D studies. The library contains a selection of over 12,600 high-quality tandem spectra of more than 3,300 peptide ions identified and validated by accurate mass, differential elution pattern, and expected peptide classes in peptide map experiments. These include a variety of biologically modified peptide spectra involving glycosylated, oxidized, deamidated, glycated, and N/C-terminal modified peptides, as well as artifacts. A complete glycation profile was obtained for the NISTmAb with spectra for 58% and 100% of all possible glycation sites in the heavy and light chains, respectively. The site-specific quantification of methionine oxidation in the protein is described. The utility of this reference library is demonstrated by the analysis of a commercial monoclonal antibody (adalimumab, Humira®), where 691 peptide ion spectra are identifiable in the constant regions, accounting for 60% coverage for both heavy and light chains. The NIST reference library platform may be used as a tool for facile identification of the primary sequence and post-translational modifications, as well as the recognition of LC-MS method-induced artifacts for human and recombinant IgG antibodies. Its development also provides a general method for creating comprehensive peptide libraries of individual proteins. PMID:29425077

A modern approach for epitope prediction: identification of foot-and-mouth disease virus peptides binding bovine leukocyte antigen (BoLA) class I molecules

USDA-ARS?s Scientific Manuscript database

Major histocompatibility complex (MHC) class I molecules regulate adaptive immune responses through the presentation of antigenic peptides to CD8positive T-cells. Polymorphisms in the peptide binding region of class I molecules determine peptide binding affinity and stability during antigen presenta...

Analysis of host-cell proteins in biotherapeutic proteins by comprehensive online two-dimensional liquid chromatography/mass spectrometry

PubMed Central

Xenopoulos, Alex; Fadgen, Keith; Murphy, Jim; Skilton, St. John; Prentice, Holly; Stapels, Martha

2012-01-01

Assays for identification and quantification of host-cell proteins (HCPs) in biotherapeutic proteins over 5 orders of magnitude in concentration are presented. The HCP assays consist of two types: HCP identification using comprehensive online two-dimensional liquid chromatography coupled with high resolution mass spectrometry (2D-LC/MS), followed by high-throughput HCP quantification by liquid chromatography, multiple reaction monitoring (LC-MRM). The former is described as a “discovery” assay, the latter as a “monitoring” assay. Purified biotherapeutic proteins (e.g., monoclonal antibodies) were digested with trypsin after reduction and alkylation, and the digests were fractionated using reversed-phase (RP) chromatography at high pH (pH 10) by a step gradient in the first dimension, followed by a high-resolution separation at low pH (pH 2.5) in the second dimension. As peptides eluted from the second dimension, a quadrupole time-of-flight mass spectrometer was used to detect the peptides and their fragments simultaneously by alternating the collision cell energy between a low and an elevated energy (MSE methodology). The MSE data was used to identify and quantify the proteins in the mixture using a proven label-free quantification technique (“Hi3” method). The same data set was mined to subsequently develop target peptides and transitions for monitoring the concentration of selected HCPs on a triple quadrupole mass spectrometer in a high-throughput manner (20 min LC-MRM analysis). This analytical methodology was applied to the identification and quantification of low-abundance HCPs in six samples of PTG1, a recombinant chimeric anti-phosphotyrosine monoclonal antibody (mAb). Thirty three HCPs were identified in total from the PTG1 samples among which 21 HCP isoforms were selected for MRM monitoring. The absolute quantification of three selected HCPs was undertaken on two different LC-MRM platforms after spiking isotopically labeled peptides in the samples. Finally, the MRM quantitation results were compared with TOF-based quantification based on the Hi3 peptides, and the TOF and MRM data sets correlated reasonably well. The results show that the assays provide detailed valuable information to understand the relative contributions of purification schemes to the nature and concentrations of HCP impurities in biopharmaceutical samples, and the assays can be used as generic methods for HCP analysis in the biopharmaceutical industry. PMID:22327428

The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: I. Statistically annotated datasets for peptide sequences and proteins identified via the application of ICAT and tandem mass spectrometry to proteins copurifying with T cell lipid rafts.

PubMed

von Haller, Priska D; Yi, Eugene; Donohoe, Samuel; Vaughn, Kelly; Keller, Andrew; Nesvizhskii, Alexey I; Eng, Jimmy; Li, Xiao-jun; Goodlett, David R; Aebersold, Ruedi; Watts, Julian D

2003-07-01

Lipid rafts were prepared according to standard protocols from Jurkat T cells stimulated via T cell receptor/CD28 cross-linking and from control (unstimulated) cells. Co-isolating proteins from the control and stimulated cell preparations were labeled with isotopically normal (d0) and heavy (d8) versions of the same isotope-coded affinity tag (ICAT) reagent, respectively. Samples were combined, proteolyzed, and resultant peptides fractionated via cation exchange chromatography. Cysteine-containing (ICAT-labeled) peptides were recovered via the biotin tag component of the ICAT reagents by avidin-affinity chromatography. On-line micro-capillary liquid chromatography tandem mass spectrometry was performed on both avidin-affinity (ICAT-labeled) and flow-through (unlabeled) fractions. Initial peptide sequence identification was by searching recorded tandem mass spectrometry spectra against a human sequence data base using SEQUEST software. New statistical data modeling algorithms were then applied to the SEQUEST search results. These allowed for discrimination between likely "correct" and "incorrect" peptide assignments, and from these the inferred proteins that they collectively represented, by calculating estimated probabilities that each peptide assignment and subsequent protein identification was a member of the "correct" population. For convenience, the resultant lists of peptide sequences assigned and the proteins to which they corresponded were filtered at an arbitrarily set cut-off of 0.5 (i.e. 50% likely to be "correct") and above and compiled into two separate datasets. In total, these data sets contained 7667 individual peptide identifications, which represented 2669 unique peptide sequences, corresponding to 685 proteins and related protein groups.

Performance Investigation of Proteomic Identification by HCD/CID Fragmentations in Combination with High/Low-Resolution Detectors on a Tribrid, High-Field Orbitrap Instrument

PubMed Central

Shen, Shichen; Sheng, Quanhu; Shyr, Yu; Qu, Jun

2016-01-01

The recently-introduced Orbitrap Fusion mass spectrometry permits various types of MS2 acquisition methods. To date, these different MS2 strategies and the optimal data interpretation approach for each have not been adequately evaluated. This study comprehensively investigated the four MS2 strategies: HCD-OT (higher-energy-collisional-dissociation with Orbitrap detection), HCD-IT (HCD with ion trap, IT), CID-IT (collision-induced-dissociation with IT) and CID-OT on Orbitrap Fusion. To achieve extensive comparison and identify the optimal data interpretation method for each technique, several search engines (SEQUEST and Mascot) and post-processing methods (score-based, PeptideProphet, and Percolator) were assessed for all techniques for the analysis of a human cell proteome. It was found that divergent conclusions could be made from the same dataset when different data interpretation approaches were used and therefore requiring a relatively fair comparison among techniques. Percolator was chosen for comparison of techniques because it performs the best among all search engines and MS2 strategies. For the analysis of human cell proteome using individual MS2 strategies, the highest number of identifications was achieved by HCD-OT, followed by HCD-IT and CID-IT. Based on these results, we concluded that a relatively fair platform for data interpretation is necessary to avoid divergent conclusions from the same dataset, and HCD-OT and HCD-IT may be preferable for protein/peptide identification using Orbitrap Fusion. PMID:27472422

Assessment of Sample Preparation Bias in Mass Spectrometry-Based Proteomics.

PubMed

Klont, Frank; Bras, Linda; Wolters, Justina C; Ongay, Sara; Bischoff, Rainer; Halmos, Gyorgy B; Horvatovich, Péter

2018-04-17

For mass spectrometry-based proteomics, the selected sample preparation strategy is a key determinant for information that will be obtained. However, the corresponding selection is often not based on a fit-for-purpose evaluation. Here we report a comparison of in-gel (IGD), in-solution (ISD), on-filter (OFD), and on-pellet digestion (OPD) workflows on the basis of targeted (QconCAT-multiple reaction monitoring (MRM) method for mitochondrial proteins) and discovery proteomics (data-dependent acquisition, DDA) analyses using three different human head and neck tissues (i.e., nasal polyps, parotid gland, and palatine tonsils). Our study reveals differences between the sample preparation methods, for example, with respect to protein and peptide losses, quantification variability, protocol-induced methionine oxidation, and asparagine/glutamine deamidation as well as identification of cysteine-containing peptides. However, none of the methods performed best for all types of tissues, which argues against the existence of a universal sample preparation method for proteome analysis.

Evaluation of comprehensive multidimensional separations using reversed-phase, reversed-phase liquid chromatography/mass spectrometry for shotgun proteomics.

PubMed

Nakamura, Tatsuji; Kuromitsu, Junro; Oda, Yoshiya

2008-03-01

Two-dimensional liquid-chromatographic (LC) separation followed by mass spectrometric (MS) analysis was examined for the identification of peptides in complex mixtures as an alternative to widely used two-dimensional gel electrophoresis followed by MS analysis for use in proteomics. The present method involves the off-line coupling of a narrow-bore, polymer-based, reversed-phase column using an acetonitrile gradient in an alkaline mobile phase in the first dimension with octadecylsilanized silica (ODS)-based nano-LC/MS in the second dimension. After the first separation, successive fractions were acidified and dried off-line, then loaded on the second dimension column. Both columns separate peptides according to hydrophobicity under different pH conditions, but more peptides were identified than with the conventional technique for shotgun proteomics, that is, the combination of a strong cation exchange column with an ODS column, and the system was robust because no salts were included in the mobile phases. The suitability of the method for proteomics measurements was evaluated.

Proteomics analysis of "Rovabiot Excel", a secreted protein cocktail from the filamentous fungus Penicillium funiculosum grown under industrial process fermentation.

PubMed

Guais, Olivier; Borderies, Gisèle; Pichereaux, Carole; Maestracci, Marc; Neugnot, Virginie; Rossignol, Michel; François, Jean Marie

2008-12-01

MS/MS techniques are well customized now for proteomic analysis, even for non-sequenced organisms, since peptide sequences obtained by these methods can be matched with those found in databases from closely related sequenced organisms. We used this approach to characterize the protein content of the "Rovabio Excel", an enzymatic cocktail produced by Penicillium funiculosum that is used as feed additive in animal nutrition. Protein separation by bi-dimensional electrophoresis yielded more than 100 spots, from which 37 proteins were unambiguously assigned from peptide sequences. By one-dimensional SDS-gel electrophoresis, 34 proteins were identified among which 8 were not found in the 2-DE analysis. A third method, termed 'peptidic shotgun', which consists in a direct treatment of the cocktail by trypsin followed by separation of the peptides on two-dimensional liquid chromatography, resulted in the identification of two additional proteins not found by the two other methods. Altogether, more than 50 proteins, among which several glycosylhydrolytic, hemicellulolytic and proteolytic enzymes, were identified by combining three separation methods in this enzymatic cocktail. This work confirmed the power of proteome analysis to explore the genome expression of a non-sequenced fungus by taking advantage of sequences from phylogenetically related filamentous fungi and pave the way for further functional analysis of P. funiculosum.

Preprocessing Significantly Improves the Peptide/Protein Identification Sensitivity of High-resolution Isobarically Labeled Tandem Mass Spectrometry Data*

PubMed Central

Sheng, Quanhu; Li, Rongxia; Dai, Jie; Li, Qingrun; Su, Zhiduan; Guo, Yan; Li, Chen; Shyr, Yu; Zeng, Rong

2015-01-01

Isobaric labeling techniques coupled with high-resolution mass spectrometry have been widely employed in proteomic workflows requiring relative quantification. For each high-resolution tandem mass spectrum (MS/MS), isobaric labeling techniques can be used not only to quantify the peptide from different samples by reporter ions, but also to identify the peptide it is derived from. Because the ions related to isobaric labeling may act as noise in database searching, the MS/MS spectrum should be preprocessed before peptide or protein identification. In this article, we demonstrate that there are a lot of high-frequency, high-abundance isobaric related ions in the MS/MS spectrum, and removing isobaric related ions combined with deisotoping and deconvolution in MS/MS preprocessing procedures significantly improves the peptide/protein identification sensitivity. The user-friendly software package TurboRaw2MGF (v2.0) has been implemented for converting raw TIC data files to mascot generic format files and can be downloaded for free from https://github.com/shengqh/RCPA.Tools/releases as part of the software suite ProteomicsTools. The data have been deposited to the ProteomeXchange with identifier PXD000994. PMID:25435543

MALDI based identification of soybean protein markers--possible analytical targets for allergen detection in processed foods.

PubMed

Cucu, Tatiana; De Meulenaer, Bruno; Devreese, Bart

2012-02-01

Soybean (Glycine max) is extensively used all over the world due to its nutritional qualities. However, soybean is included in the "big eight" list of food allergens. According to the EU directive 2007/68/EC, food products containing soybeans have to be labeled in order to protect the allergic consumers. Nevertheless, soybeans can still inadvertently be present in food products. The development of analytical methods for the detection of traces of allergens is important for the protection of allergic consumers. Mass spectrometry of marker proteolytical fragments of protein allergens is growingly recognized as a detection method in food control. However, quantification of soybean at the peptide level is hindered due to limited information regarding specific stable markers derived after proteolytic digestion. The aim of this study was to use MALDI-TOF/MS and MS/MS as a fast screening tool for the identification of stable soybean derived tryptic markers which were still identifiable even if the proteins were subjected to various changes at the molecular level through a number of reactions typically occurring during food processing (denaturation, the Maillard reaction and oxidation). The peptides (401)Val-Arg(410) from the G1 glycinin (Gly m 6) and the (518)Gln-Arg(528) from the α' chain of the β-conglycinin (Gly m 5) proved to be the most stable. These peptides hold potential to be used as targets for the development of new analytical methods for the detection of soybean protein traces in processed foods. Copyright © 2011 Elsevier Inc. All rights reserved.

A distributed computational search strategy for the identification of diagnostics targets: application to finding aptamer targets for methicillin-resistant staphylococci.

PubMed

Flanagan, Keith; Cockell, Simon; Harwood, Colin; Hallinan, Jennifer; Nakjang, Sirintra; Lawry, Beth; Wipat, Anil

2014-06-30

The rapid and cost-effective identification of bacterial species is crucial, especially for clinical diagnosis and treatment. Peptide aptamers have been shown to be valuable for use as a component of novel, direct detection methods. These small peptides have a number of advantages over antibodies, including greater specificity and longer shelf life. These properties facilitate their use as the detector components of biosensor devices. However, the identification of suitable aptamer targets for particular groups of organisms is challenging. We present a semi-automated processing pipeline for the identification of candidate aptamer targets from whole bacterial genome sequences. The pipeline can be configured to search for protein sequence fragments that uniquely identify a set of strains of interest. The system is also capable of identifying additional organisms that may be of interest due to their possession of protein fragments in common with the initial set. Through the use of Cloud computing technology and distributed databases, our system is capable of scaling with the rapidly growing genome repositories, and consequently of keeping the resulting data sets up-to-date. The system described is also more generically applicable to the discovery of specific targets for other diagnostic approaches such as DNA probes, PCR primers and antibodies.

A distributed computational search strategy for the identification of diagnostics targets: Application to finding aptamer targets for methicillin-resistant staphylococci.

PubMed

Flanagan, Keith; Cockell, Simon; Harwood, Colin; Hallinan, Jennifer; Nakjang, Sirintra; Lawry, Beth; Wipat, Anil

2014-06-01

The rapid and cost-effective identification of bacterial species is crucial, especially for clinical diagnosis and treatment. Peptide aptamers have been shown to be valuable for use as a component of novel, direct detection methods. These small peptides have a number of advantages over antibodies, including greater specificity and longer shelf life. These properties facilitate their use as the detector components of biosensor devices. However, the identification of suitable aptamer targets for particular groups of organisms is challenging. We present a semi-automated processing pipeline for the identification of candidate aptamer targets from whole bacterial genome sequences. The pipeline can be configured to search for protein sequence fragments that uniquely identify a set of strains of interest. The system is also capable of identifying additional organisms that may be of interest due to their possession of protein fragments in common with the initial set. Through the use of Cloud computing technology and distributed databases, our system is capable of scaling with the rapidly growing genome repositories, and consequently of keeping the resulting data sets up-to-date. The system described is also more generically applicable to the discovery of specific targets for other diagnostic approaches such as DNA probes, PCR primers and antibodies.

Neuropeptides in Heteroptera: Identification of allatotropin-related peptide and tachykinin-related peptides using MALDI-TOF mass spectrometry

USDA-ARS?s Scientific Manuscript database

Recently, the peptidomic analysis of neuropeptides from the retrocerebral complex and abdominal perisympathetic organs of polyphagous stinkbugs (Pentatomidae) revealed the group-specific sequences of pyrokinins, CAPA peptides (CAPA-periviscerokinins/PVKs and CAPA-pyrokinin), myosuppressin, corazonin...

Screening and identification of novel B cell epitopes of Toxoplasma gondii SAG1.

PubMed

Wang, Yanhua; Wang, Guangxiang; Zhang, Delin; Yin, Hong; Wang, Meng

2013-04-30

The identification of protein epitopes is useful for diagnostic purposes and for the development of peptide vaccines. In this study, the epitopes of Toxoplasma gondii SAG1 were identified using synthetic peptide techniques with the aid of bioinformatics. Eleven peptides derived from T. gondii SAG1 were assessed by ELISA using pig sera from different time points after infection. Four (PS4, PS6, PS10 and PS11), out of the eleven peptides tested were recognized by all sera. Then, shorter peptides that were derived from PS4, PS6, PS10 and PS11 were predicted using bioinformatics and tested by experimentation. Four out of nine shorter peptides were identified successfully (amino acids 106-120, 166-180, 289-300 and 313-332). We have precisely located the epitopes of T. gondii SAG1 using pig sera collected at different time points after infection. The identified epitopes may be useful for the further study of epitope-based vaccines and diagnostic reagents.

Assigning statistical significance to proteotypic peptides via database searches

PubMed Central

Alves, Gelio; Ogurtsov, Aleksey Y.; Yu, Yi-Kuo

2011-01-01

Querying MS/MS spectra against a database containing only proteotypic peptides reduces data analysis time due to reduction of database size. Despite the speed advantage, this search strategy is challenged by issues of statistical significance and coverage. The former requires separating systematically significant identifications from less confident identifications, while the latter arises when the underlying peptide is not present, due to single amino acid polymorphisms (SAPs) or post-translational modifications (PTMs), in the proteotypic peptide libraries searched. To address both issues simultaneously, we have extended RAId’s knowledge database to include proteotypic information, utilized RAId’s statistical strategy to assign statistical significance to proteotypic peptides, and modified RAId’s programs to allow for consideration of proteotypic information during database searches. The extended database alleviates the coverage problem since all annotated modifications, even those occurred within proteotypic peptides, may be considered. Taking into account the likelihoods of observation, the statistical strategy of RAId provides accurate E-value assignments regardless whether a candidate peptide is proteotypic or not. The advantage of including proteotypic information is evidenced by its superior retrieval performance when compared to regular database searches. PMID:21055489

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Sacks, David B.; Yu, Yi-Kuo

2018-06-01

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

PubMed

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

Large-Scale Interaction Profiling of Protein Domains Through Proteomic Peptide-Phage Display Using Custom Peptidomes.

PubMed

Seo, Moon-Hyeong; Nim, Satra; Jeon, Jouhyun; Kim, Philip M

2017-01-01

Protein-protein interactions are essential to cellular functions and signaling pathways. We recently combined bioinformatics and custom oligonucleotide arrays to construct custom-made peptide-phage libraries for screening peptide-protein interactions, an approach we call proteomic peptide-phage display (ProP-PD). In this chapter, we describe protocols for phage display for the identification of natural peptide binders for a given protein. We finally describe deep sequencing for the analysis of the proteomic peptide-phage display.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity: in silico bioinformatic step-by-step guide using quantitative structure-activity relationships.

PubMed

Hattotuwagama, Channa K; Doytchinova, Irini A; Flower, Darren R

2007-01-01

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

Acid/Salt/pH Gradient Improved Resolution and Sensitivity in Proteomics Study Using 2D SCX-RP LC-MS.

PubMed

Zhu, Ming-Zhi; Li, Na; Wang, Yi-Tong; Liu, Ning; Guo, Ming-Quan; Sun, Bao-Qing; Zhou, Hua; Liu, Liang; Wu, Jian-Lin

2017-09-01

The usage of strong cation exchange (SCX) chromatography in proteomics is limited by its poor resolution and nonspecific hydrophobic interactions with peptides, which lead to peptide overlap across fractions and change of peptide retention, respectively. The application of high concentration of salt (up to 1000 mM) in SCX also restricted its use in online 2D SCX-RP LC. In the present research, we first exploited the chromatographic ability of online 2D SCX-RP LC by combination of acid, salt, and pH gradient, three relatively independent modes of eluting peptides from SCX column. 50% ACN was added to elution buffer for eliminating hydrophobic interactions between SCX matrix and peptides, and the concentration of volatile salt was reduced to 50 mM. Acid/salt/pH gradient showed superior resolution and sensitivity as well as uniform distribution across fractions, consequently leading to significant improvements in peptide and protein identification. 112 191 unique peptides and 7373 proteins were identified by acid/salt/pH fractionation, while 69 870 unique peptides and 4536 proteins were identified by salt elution, that is, 62.5 and 60.6% more proteins and unique peptides, respectively, identified by the former. Fraction overlap was also significantly minimized by acid/salt/pH approach. Furthermore, acid/salt/pH elution showed more identification for acidic peptides and hydrophilic peptides.

In Silico Prediction of Neuropeptides/Peptide Hormone Transcripts in the Cheilostome Bryozoan Bugula neritina

PubMed Central

Zhang, Gen; He, Li-Sheng; Qian, Pei-Yuan

2016-01-01

The bryozoan Bugula neritina has a biphasic life cycle that consists of a planktonic larval stage and a sessile juvenile/adult stage. The transition between these two stages is crucial for the development and recruitment of B. neritina. Metamorphosis in B. neritina is mediated by both the nervous system and the release of developmental signals. However, no research has been conducted to investigate the expression of neuropeptides (NP)/peptide hormones in B. neritina larvae. Here, we report a comprehensive study of the NP/peptide hormones in the marine bryozoan B. neritina based on in silico identification methods. We recovered 22 transcripts encompassing 11 NP/peptide hormone precursor transcript sequences. The transcript sequences of the 11 isolated NP precursors were validated by cDNA cloning using gene-specific primers. We also examined the expression of three peptide hormone precursor transcripts (BnFDSIG, BnILP1, BnGPB) in the coronate larvae of B. neritina, demonstrating their distinct expression patterns in the larvae. Overall, our findings serve as an important foundation for subsequent investigations of the peptidergic control of bryozoan larval behavior and settlement. PMID:27537380

Venom characterization of the Amazonian scorpion Tityus metuendus.

PubMed

Batista, C V F; Martins, J G; Restano-Cassulini, R; Coronas, F I V; Zamudio, F Z; Procópio, R; Possani, L D

2018-03-01

The soluble venom from the scorpion Tityus metuendus was characterized by various methods. In vivo experiments with mice showed that it is lethal. Extended electrophysiological recordings using seven sub-types of human voltage gated sodium channels (hNav1.1 to 1.7) showed that it contains both α- and β-scorpion toxin types. Fingerprint analysis by mass spectrometry identified over 200 distinct molecular mass components. At least 60 sub-fractions were recovered from HPLC separation. Five purified peptides were sequenced by Edman degradation, and their complete primary structures were determined. Additionally, three other peptides have had their N-terminal amino acid sequences determined by Edman degradation and reported. Mass spectrometry analysis of tryptic digestion of the soluble venom permitted the identification of the amino acid sequence of 111 different peptides. Search for similarities of the sequences found indicated that they probably are: sodium and potassium channel toxins, metalloproteinases, hyaluronidases, endothelin and angiotensin-converting enzymes, bradykinin-potentiating peptide, hypothetical proteins, allergens, other enzymes, other proteins and peptides. Copyright © 2018 Elsevier Ltd. All rights reserved.

Combining De Novo Peptide Sequencing Algorithms, A Synergistic Approach to Boost Both Identifications and Confidence in Bottom-up Proteomics.

PubMed

Blank-Landeshammer, Bernhard; Kollipara, Laxmikanth; Biß, Karsten; Pfenninger, Markus; Malchow, Sebastian; Shuvaev, Konstantin; Zahedi, René P; Sickmann, Albert

2017-09-01

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.

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling.

PubMed

Huang, Xin; Tolmachev, Aleksey V; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A; Smith, Richard D; Chan, Wing C; Hinrichs, Steven H; Fu, Kai; Ding, Shi-Jian

2011-03-04

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.

UNiquant, a Program for Quantitative Proteomics Analysis Using Stable Isotope Labeling

PubMed Central

Huang, Xin; Tolmachev, Aleksey V.; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A.; Smith, Richard D.; Chan, Wing C.; Hinrichs, Steven H.; Fu, Kai; Ding, Shi-Jian

2011-01-01

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for post-measurement normalization of peptide ratios, which is required by the other programs. PMID:21158445

Accurate localization and relative quantification of arginine methylation using nanoflow liquid chromatography coupled to electron transfer dissociation and orbitrap mass spectrometry.

PubMed

Wang, Hao; Straubinger, Robert M; Aletta, John M; Cao, Jin; Duan, Xiaotao; Yu, Haoying; Qu, Jun

2009-03-01

Protein arginine (Arg) methylation serves an important functional role in eucaryotic cells, and typically occurs in domains consisting of multiple Arg in close proximity. Localization of methylarginine (MA) within Arg-rich domains poses a challenge for mass spectrometry (MS)-based methods; the peptides are highly charged under electrospray ionization (ESI), which limits the number of sequence-informative products produced by collision induced dissociation (CID), and loss of the labile methylation moieties during CID precludes effective fragmentation of the peptide backbone. Here the fragmentation behavior of Arg-rich peptides was investigated comprehensively using electron-transfer dissociation (ETD) and CID for both methylated and unmodified glycine-/Arg-rich peptides (GAR), derived from residues 679-695 of human nucleolin, which contains methylation motifs that are widely-represented in biological systems. ETD produced abundant information for sequencing and MA localization, whereas CID failed to provide credible identification for any available charge state (z = 2-4). Nevertheless, CID produced characteristic neutral losses that can be employed to distinguish among different types of MA, as suggested by previous works and confirmed here with product ion scans of high accuracy/resolution by an LTQ/Orbitrap. To analyze MA-peptides in relatively complex mixtures, a method was developed that employs nano-LC coupled to alternating CID/ETD for peptide sequencing and MA localization/characterization, and an Orbitrap for accurate precursor measurement and relative quantification of MA-peptide stoichiometries. As proof of concept, GAR-peptides methylated in vitro by protein arginine N-methyltransferases PRMT1 and PRMT7 were analyzed. It was observed that PRMT1 generated a number of monomethylated (MMA) and asymmetric-dimethylated peptides, while PRMT7 produced predominantly MMA peptides and some symmetric-dimethylated peptides. This approach and the results may advance understanding of the actions of PRMTs and the functional significance of Arg methylation patterns.

Accurate Localization and Relative Quantification of Arginine Methylation Using Nanoflow Liquid Chromatography Coupled to Electron Transfer Dissociation and Orbitrap Mass Spectrometry

PubMed Central

Wang, Hao; Straubinger, Robert M.; Aletta, John M.; Cao, Jin; Duan, Xiaotao; Yu, Haoying; Qu, Jun

2012-01-01

Protein arginine (Arg) methylation serves an important functional role in eukaryotic cells, and typically occurs in domains consisting of multiple Arg in close proximity. Localization of methylarginine (MA) within Arg-rich domains poses a challenge for mass spectrometry (MS)-based methods; the peptides are highly-charged under electrospray ionization (ESI), which limits the number of sequence-informative products produced by collision induced dissociation (CID), and loss of the labile methylation moieties during CID precludes effective fragmentation of the peptide backbone. Here the fragmentation behavior of Arg-rich peptides was investigated comprehensively using electron transfer dissociation (ETD) and CID for both methylated and unmodified glycine-/Arg-rich peptides (GAR), derived from residues 679-695 of human nucleolin, which contains methylation motifs that are widely-represented in biological systems. ETD produced abundant information for sequencing and MA localization, whereas CID failed to provide credible identification for any available charge state (z=2-4). Nevertheless, CID produced characteristic neutral losses that can be employed to distinguish among different types of MA, as suggested by previous works and confirmed here with product ion scans of high accuracy/resolution by an LTQ/Orbitrap. To analyze MA-peptides in relatively complex mixtures, a method was developed that employs nano-LC coupled to alternating CID/ETD for peptide sequencing and MA localization/characterization, and an Orbitrap for accurate precursor measurement and relative quantification of MA-peptide stoichiometries. As proof of concept, GAR-peptides methylated in vitro by protein arginine N-methyltransferases PRMT1 and PRMT7 were analyzed. It was observed that PRMT1 generated a number of monomethylated (MMA) and asymmetric-dimethylated peptides, while PRMT7 produced predominantly MMA peptides and some symmetric-dimethylated peptides. This approach and the results may advance understanding of the actions of PRMTs and the functional significance of Arg methylation patterns. PMID:19110445

Automated protein identification by the combination of MALDI MS and MS/MS spectra from different instruments.

PubMed

Levander, Fredrik; James, Peter

2005-01-01

The identification of proteins separated on two-dimensional gels is most commonly performed by trypsin digestion and subsequent matrix-assisted laser desorption ionization (MALDI) with time-of-flight (TOF). Recently, atmospheric pressure (AP) MALDI coupled to an ion trap (IT) has emerged as a convenient method to obtain tandem mass spectra (MS/MS) from samples on MALDI target plates. In the present work, we investigated the feasibility of using the two methodologies in line as a standard method for protein identification. In this setup, the high mass accuracy MALDI-TOF spectra are used to calibrate the peptide precursor masses in the lower mass accuracy AP-MALDI-IT MS/MS spectra. Several software tools were developed to automate the analysis process. Two sets of MALDI samples, consisting of 142 and 421 gel spots, respectively, were analyzed in a highly automated manner. In the first set, the protein identification rate increased from 61% for MALDI-TOF only to 85% for MALDI-TOF combined with AP-MALDI-IT. In the second data set the increase in protein identification rate was from 44% to 58%. AP-MALDI-IT MS/MS spectra were in general less effective than the MALDI-TOF spectra for protein identification, but the combination of the two methods clearly enhanced the confidence in protein identification.

An Azido-Biotin Reagent for Use in the Isolation of Protein Adducts of Lipid-derived Electrophiles by Streptavidin Catch and Photorelease*

PubMed Central

Kim, Hye-Young H.; Tallman, Keri A.; Liebler, Daniel C.; Porter, Ned A.

2009-01-01

HNE (4-hydroxynonenal), a byproduct of lipid peroxidation, reacts with nucleophilic centers on proteins. A terminal alkynyl analog of HNE (alkynyl HNE, aHNE) serves as a surrogate for HNE itself, both compounds reacting with protein amine and thiol functional groups by similar chemistry. Proteins modified with aHNE undergo reaction with a click reagent that bears azido and biotin groups separated by a photocleavable linker. Peptides and proteins modified in this way are affinity purified on streptavidin beads. Photolysis of the beads with a low intensity UV light releases bound biotinylated proteins or peptides, i.e. proteins or peptides modified by aHNE. Two strategies, (a) protein catch and photorelease and (b) peptide catch and photorelease, are employed to enrich adducted proteins or peptide mixtures highly enriched in adducts. Proteomics analysis of the streptavidin-purified peptides by LC-MS/MS permits identification of the adduction site. Identification of 30 separate peptides from human serum albumin by peptide catch and photorelease reveals 18 different aHNE adduction sites on the protein. Protein catch and photorelease shows that both HSA and ApoA1 in human plasma undergo significant modification by aHNE. PMID:19483245

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements.

PubMed

Qian, Chen; Hettich, Robert L

2017-07-07

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling. Liquid chromatography coupled to high-performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to proteome extraction and subsequent MS measurement. To this end, we have designed an experimental method to improve microbial proteome measurement by removing the soil-borne humic substances coextraction from soils. Our approach employs an in situ detergent-based microbial lysis/TCA precipitation coupled to an additional cleanup step involving acidified precipitation and filtering at the peptide level to remove most of the humic acid interferences prior to proteolytic peptide measurement. The novelty of this approach is an integration to exploit two different characteristics of humic acids: (1) Humic acids are insoluble in acidic solution but should not be removed at the protein level, as undesirable protein removal may also occur. Rather it is better to leave the humics acids in the samples until the peptide level, at which point the significant differential solubility of humic acids versus peptides at low pH can be exploited very efficiently. (2) Most of the humic acids have larger molecule weights than the peptides. Therefore, filtering a pH 2 to 3 peptide solution with a 10 kDa filter will remove most of the humic acids. This method is easily interfaced with normal proteolytic processing approaches and provides a reliable and straightforward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or biasing protein identification in mass spectrometry. In general, this humic acid removal step is universal and can be adopted by any workflow to effectively remove humic acids to avoid them negatively competing with peptides for binding with reversed-phase resin or ionization in the electrospray.

A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples.

PubMed

Boskamp, Tobias; Lachmund, Delf; Oetjen, Janina; Cordero Hernandez, Yovany; Trede, Dennis; Maass, Peter; Casadonte, Rita; Kriegsmann, Jörg; Warth, Arne; Dienemann, Hendrik; Weichert, Wilko; Kriegsmann, Mark

2017-07-01

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 Elsevier B.V. All rights reserved.

Identification of cancer-specific motifs in mimotope profiles of serum antibody repertoire.

PubMed

Gerasimov, Ekaterina; Zelikovsky, Alex; Măndoiu, Ion; Ionov, Yurij

2017-06-07

For fighting cancer, earlier detection is crucial. Circulating auto-antibodies produced by the patient's own immune system after exposure to cancer proteins are promising bio-markers for the early detection of cancer. Since an antibody recognizes not the whole antigen but 4-7 critical amino acids within the antigenic determinant (epitope), the whole proteome can be represented by a random peptide phage display library. This opens the possibility to develop an early cancer detection test based on a set of peptide sequences identified by comparing cancer patients' and healthy donors' global peptide profiles of antibody specificities. Due to the enormously large number of peptide sequences contained in global peptide profiles generated by next generation sequencing, the large number of cancer and control sera is required to identify cancer-specific peptides with high degree of statistical significance. To decrease the number of peptides in profiles generated by nextgen sequencing without losing cancer-specific sequences we used for generation of profiles the phage library enriched by panning on the pool of cancer sera. To further decrease the complexity of profiles we used computational methods for transforming a list of peptides constituting the mimotope profiles to the list motifs formed by similar peptide sequences. We have shown that the amino-acid order is meaningful in mimotope motifs since they contain significantly more peptides than motifs among peptides where amino-acids are randomly permuted. Also the single sample motifs significantly differ from motifs in peptides drawn from multiple samples. Finally, multiple cancer-specific motifs have been identified.

A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry.

PubMed

Chavez, Juan D; Eng, Jimmy K; Schweppe, Devin K; Cilia, Michelle; Rivera, Keith; Zhong, Xuefei; Wu, Xia; Allen, Terrence; Khurgel, Moshe; Kumar, Akhilesh; Lampropoulos, Athanasios; Larsson, Mårten; Maity, Shuvadeep; Morozov, Yaroslav; Pathmasiri, Wimal; Perez-Neut, Mathew; Pineyro-Ruiz, Coriness; Polina, Elizabeth; Post, Stephanie; Rider, Mark; Tokmina-Roszyk, Dorota; Tyson, Katherine; Vieira Parrine Sant'Ana, Debora; Bruce, James E

2016-01-01

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.

De Novo Design of Skin-Penetrating Peptides for Enhanced Transdermal Delivery of Peptide Drugs.

PubMed

Menegatti, Stefano; Zakrewsky, Michael; Kumar, Sunny; De Oliveira, Joshua Sanchez; Muraski, John A; Mitragotri, Samir

2016-03-09

Skin-penetrating peptides (SPPs) are attracting increasing attention as a non-invasive strategy for transdermal delivery of therapeutics. The identification of SPP sequences, however, currently performed by experimental screening of peptide libraries, is very laborious. Recent studies have shown that, to be effective enhancers, SPPs must possess affinity for both skin keratin and the drug of interest. We therefore developed a computational process for generating and screening virtual libraries of disulfide-cyclic peptides against keratin and cyclosporine A (CsA) to identify SPPs capable of enhancing transdermal CsA delivery. The selected sequences were experimentally tested and found to bind both CsA and keratin, as determined by mass spectrometry and affinity chromatography, and enhance transdermal permeation of CsA. Four heptameric sequences that emerged as leading candidates (ACSATLQHSCG, ACSLTVNWNCG, ACTSTGRNACG, and ACSASTNHNCG) were tested and yielded CsA permeation on par with previously identified SPP SPACE (TM) . An octameric peptide (ACNAHQARSTCG) yielded significantly higher delivery of CsA compared to heptameric SPPs. The safety profile of the selected sequences was also validated by incubation with skin keratinocytes. This method thus represents an effective procedure for the de novo design of skin-penetrating peptides for the delivery of desired therapeutic or cosmetic agents. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Building high-quality assay libraries for targeted analysis of SWATH MS data.

PubMed

Schubert, Olga T; Gillet, Ludovic C; Collins, Ben C; Navarro, Pedro; Rosenberger, George; Wolski, Witold E; Lam, Henry; Amodei, Dario; Mallick, Parag; MacLean, Brendan; Aebersold, Ruedi

2015-03-01

Targeted proteomics by selected/multiple reaction monitoring (S/MRM) or, on a larger scale, by SWATH (sequential window acquisition of all theoretical spectra) MS (mass spectrometry) typically relies on spectral reference libraries for peptide identification. Quality and coverage of these libraries are therefore of crucial importance for the performance of the methods. Here we present a detailed protocol that has been successfully used to build high-quality, extensive reference libraries supporting targeted proteomics by SWATH MS. We describe each step of the process, including data acquisition by discovery proteomics, assertion of peptide-spectrum matches (PSMs), generation of consensus spectra and compilation of MS coordinates that uniquely define each targeted peptide. Crucial steps such as false discovery rate (FDR) control, retention time normalization and handling of post-translationally modified peptides are detailed. Finally, we show how to use the library to extract SWATH data with the open-source software Skyline. The protocol takes 2-3 d to complete, depending on the extent of the library and the computational resources available.

Comparison between Procedures using Sodium Dodecyl Sulfate for Shotgun Proteomic Analyses of Complex Samples

PubMed Central

Bereman, Michael S.; Egertson, Jarrett D.; MacCoss, Michael J.

2012-01-01

Filter aided sample preparation (FASP) and a new sample preparation method using a modified commercial SDS removal spin column are quantitatively compared in terms of their performance for shotgun proteomic experiments in three complex proteomic samples: a Saccharomyces cerevisiae lysate (insoluble fraction), a Caenorhabditis elegans lysate (soluble fraction), and a human embryonic kidney cell line (HEK293T). The characteristics and total number of peptides and proteins identified are compared between the two procedures. The SDS spin column procedure affords a conservative 4-fold improvement in throughput, is more reproducible, less expensive (i.e., requires less materials), and identifies between 30–107% more peptides at a q≤0.01, than the FASP procedure. The peptides identified by SDS spin column are more hydrophobic than species identified by the FASP procedure as indicated by the distribution of GRAVY scores. Ultimately, these improvements correlate to as great as a 50% increase in protein identifications with 2 or more peptides. PMID:21656683

Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate.

PubMed

Park, Gun Wook; Hwang, Heeyoun; Kim, Kwang Hoe; Lee, Ju Yeon; Lee, Hyun Kyoung; Park, Ji Yeong; Ji, Eun Sun; Park, Sung-Kyu Robin; Yates, John R; Kwon, Kyung-Hoon; Park, Young Mok; Lee, Hyoung-Joo; Paik, Young-Ki; Kim, Jin Young; Yoo, Jong Shin

2016-11-04

In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

Performing Comparative Peptidomics Analyses of Salmonella from Different Growth Conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adkins, Joshua N.; Mottaz, Heather; Metz, Thomas O.

2010-01-08

Host–pathogen interactions are complex competitions during which both the host and the pathogen adapt rapidly to each other in order for one or the other to survive. Salmonella enterica serovar Typhimurium is a pathogen with a broad host range that causes a typhoid fever-like disease in mice and severe food poisoning in humans. The murine typhoid fever is a systemic infection in which S.typhimurium evades part of the immune system by replicating inside macrophages and other cells. The transition from a foodborne contaminant to an intracellular pathogen must occur rapidly in multiple,ordered steps in order for S. typhimurium to thrivemore » within its host environment. Using S. typhimurium isolated from rich culture conditions and from conditions that mimic the hostile intracellular environment of the host cell, a native low molecular weight protein fraction, or peptidome, was enriched from cell lysates by precipitation with organic solvents. The enriched peptidome was analyzed by both LC–MS/MS and LC–MS-based methods, although several other methods are possible. Pre-fractionation of peptides allowed identification of small proteins and protein degradation products that would normally be overlooked. Comparison of peptides present in lysates prepared from Salmonella grown under different conditions provided a unique insight into cellular degradation processes as well as identification of novel peptides encoded in the genome but not annotated. The overall approach is detailed here as applied to Salmonella and is adaptable to a broad range of biological systems.« less

In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics.

PubMed

Audain, Enrique; Uszkoreit, Julian; Sachsenberg, Timo; Pfeuffer, Julianus; Liang, Xiao; Hermjakob, Henning; Sanchez, Aniel; Eisenacher, Martin; Reinert, Knut; Tabb, David L; Kohlbacher, Oliver; Perez-Riverol, Yasset

2017-01-06

In mass spectrometry-based shotgun proteomics, protein identifications are usually the desired result. However, most of the analytical methods are based on the identification of reliable peptides and not the direct identification of intact proteins. Thus, assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is a critical step in proteomics research. Currently, different protein inference algorithms and tools are available for the proteomics community. Here, we evaluated five software tools for protein inference (PIA, ProteinProphet, Fido, ProteinLP, MSBayesPro) using three popular database search engines: Mascot, X!Tandem, and MS-GF+. All the algorithms were evaluated using a highly customizable KNIME workflow using four different public datasets with varying complexities (different sample preparation, species and analytical instruments). We defined a set of quality control metrics to evaluate the performance of each combination of search engines, protein inference algorithm, and parameters on each dataset. We show that the results for complex samples vary not only regarding the actual numbers of reported protein groups but also concerning the actual composition of groups. Furthermore, the robustness of reported proteins when using databases of differing complexities is strongly dependant on the applied inference algorithm. Finally, merging the identifications of multiple search engines does not necessarily increase the number of reported proteins, but does increase the number of peptides per protein and thus can generally be recommended. Protein inference is one of the major challenges in MS-based proteomics nowadays. Currently, there are a vast number of protein inference algorithms and implementations available for the proteomics community. Protein assembly impacts in the final results of the research, the quantitation values and the final claims in the research manuscript. Even though protein inference is a crucial step in proteomics data analysis, a comprehensive evaluation of the many different inference methods has never been performed. Previously Journal of proteomics has published multiple studies about other benchmark of bioinformatics algorithms (PMID: 26585461; PMID: 22728601) in proteomics studies making clear the importance of those studies for the proteomics community and the journal audience. This manuscript presents a new bioinformatics solution based on the KNIME/OpenMS platform that aims at providing a fair comparison of protein inference algorithms (https://github.com/KNIME-OMICS). Six different algorithms - ProteinProphet, MSBayesPro, ProteinLP, Fido and PIA- were evaluated using the highly customizable workflow on four public datasets with varying complexities. Five popular database search engines Mascot, X!Tandem, MS-GF+ and combinations thereof were evaluated for every protein inference tool. In total >186 proteins lists were analyzed and carefully compare using three metrics for quality assessments of the protein inference results: 1) the numbers of reported proteins, 2) peptides per protein, and the 3) number of uniquely reported proteins per inference method, to address the quality of each inference method. We also examined how many proteins were reported by choosing each combination of search engines, protein inference algorithms and parameters on each dataset. The results show that using 1) PIA or Fido seems to be a good choice when studying the results of the analyzed workflow, regarding not only the reported proteins and the high-quality identifications, but also the required runtime. 2) Merging the identifications of multiple search engines gives almost always more confident results and increases the number of peptides per protein group. 3) The usage of databases containing not only the canonical, but also known isoforms of proteins has a small impact on the number of reported proteins. The detection of specific isoforms could, concerning the question behind the study, compensate for slightly shorter reports using the parsimonious reports. 4) The current workflow can be easily extended to support new algorithms and search engine combinations. Copyright © 2016. Published by Elsevier B.V.

Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine.

PubMed

Giménez, Estela; Gay, Marina; Vilaseca, Marta

2017-01-30

Here we demonstrate the potential of nano-UPLC-LTQ-FT-MS and the Byonic™ proteomic search engine for the separation, detection, and identification of N- and O-glycopeptide glycoforms in standard glycoproteins. The use of a BEH C18 nanoACQUITY column allowed the separation of the glycopeptides present in the glycoprotein digest and a baseline-resolution of the glycoforms of the same glycopeptide on the basis of the number of sialic acids. Moreover, we evaluated several acquisition strategies in order to improve the detection and characterization of glycopeptide glycoforms with the maximum number of identification percentages. The proposed strategy is simple to set up with the technology platforms commonly used in proteomic labs. The method allows the straightforward and rapid obtention of a general glycosylated map of a given protein, including glycosites and their corresponding glycosylated structures. The MS strategy selected in this work, based on a gas phase fractionation approach, led to 136 unique peptides from four standard proteins, which represented 78% of the total number of peptides identified. Moreover, the method does not require an extra glycopeptide enrichment step, thus preventing the bias that this step could cause towards certain glycopeptide species. Data are available via ProteomeXchange with identifier PXD003578. We propose a simple and high-throughput glycoproteomics-based methodology that allows the separation of glycopeptide glycoforms on the basis of the number of sialic acids, and their automatic and rapid identification without prior knowledge of protein glycosites or type and structure of the glycans. Copyright © 2016 Elsevier B.V. All rights reserved.

Salivary proteomics of healthy dogs: An in depth catalog

PubMed Central

Furrow, Eva; Souza, Clarissa P.; Granick, Jennifer L.; de Jong, Ebbing P.; Griffin, Timothy J.; Wang, Xiong

2018-01-01

Objective To provide an in-depth catalog of the salivary proteome and endogenous peptidome of healthy dogs, evaluate proteins and peptides with antimicrobial properties, and compare the most common salivary proteins and peptides between different breed phylogeny groups. Methods 36 healthy dogs without evidence of periodontal disease representing four breed phylogeny groups, based upon single nucleotide polymorphism haplotypes (ancient, herding/sighthound, and two miscellaneous groups). Saliva collected from dogs was pooled by phylogeny group and analyzed using nanoscale liquid chromatography-tandem mass spectrometry. Resulting tandem mass spectra were compared to databases for identification of endogenous peptides and inferred proteins. Results 2,491 proteins and endogenous peptides were found in the saliva of healthy dogs with no periodontal disease. All dog phylogeny groups’ saliva was rich in proteins and peptides with antimicrobial functions. The ancient breeds group was distinct in that it contained unique proteins and was missing many proteins and peptides present in the other groups. Conclusions and clinical relevance Using a sophisticated nanoscale liquid chromatography-tandem mass spectrometry, we were able to identify 10-fold more salivary proteins than previously reported in dogs. Seven of the top 10 most abundant proteins or peptides serve immune functions and many more with various antimicrobial mechanisms were found. This is the most comprehensive analysis of healthy canine saliva to date, and will provide the groundwork for future studies analyzing salivary proteins and endogenous peptides in disease states. PMID:29329347

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping.

PubMed

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren; Nielsen, Morten

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

PubMed Central

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope. PMID:28095436

Seed storage proteins as a system for teaching protein identification by mass spectrometry in biochemistry laboratory.

PubMed

Wilson, Karl A; Tan-Wilson, Anna

2013-01-01

Mass spectrometry (MS) has become an important tool in studying biological systems. One application is the identification of proteins and peptides by the matching of peptide and peptide fragment masses to the sequences of proteins in protein sequence databases. Often prior protein separation of complex protein mixtures by 2D-PAGE is needed, requiring more time and expertise than instructors of large laboratory classes can devote. We have developed an experimental module for our Biochemistry Laboratory course that engages students in MS-based protein identification following protein separation by one-dimensional SDS-PAGE, a technique that is usually taught in this type of course. The module is based on soybean seed storage proteins, a relatively simple mixture of proteins present in high levels in the seed, allowing the identification of the main protein bands by MS/MS and in some cases, even by peptide mass fingerprinting. Students can identify their protein bands using software available on the Internet, and are challenged to deduce post-translational modifications that have occurred upon germination. A collection of mass spectral data and tutorials that can be used as a stand-alone computer-based laboratory module were also assembled. Copyright © 2013 International Union of Biochemistry and Molecular Biology, Inc.

Recent Advances in Conotoxin Classification by Using Machine Learning Methods.

PubMed

Dao, Fu-Ying; Yang, Hui; Su, Zhen-Dong; Yang, Wuritu; Wu, Yun; Hui, Ding; Chen, Wei; Tang, Hua; Lin, Hao

2017-06-25

Conotoxins are disulfide-rich small peptides, which are invaluable peptides that target ion channel and neuronal receptors. Conotoxins have been demonstrated as potent pharmaceuticals in the treatment of a series of diseases, such as Alzheimer's disease, Parkinson's disease, and epilepsy. In addition, conotoxins are also ideal molecular templates for the development of new drug lead compounds and play important roles in neurobiological research as well. Thus, the accurate identification of conotoxin types will provide key clues for the biological research and clinical medicine. Generally, conotoxin types are confirmed when their sequence, structure, and function are experimentally validated. However, it is time-consuming and costly to acquire the structure and function information by using biochemical experiments. Therefore, it is important to develop computational tools for efficiently and effectively recognizing conotoxin types based on sequence information. In this work, we reviewed the current progress in computational identification of conotoxins in the following aspects: (i) construction of benchmark dataset; (ii) strategies for extracting sequence features; (iii) feature selection techniques; (iv) machine learning methods for classifying conotoxins; (v) the results obtained by these methods and the published tools; and (vi) future perspectives on conotoxin classification. The paper provides the basis for in-depth study of conotoxins and drug therapy research.

EpiProfile Quantifies Histone Peptides With Modifications by Extracting Retention Time and Intensity in High-resolution Mass Spectra*

PubMed Central

Yuan, Zuo-Fei; Lin, Shu; Molden, Rosalynn C.; Cao, Xing-Jun; Bhanu, Natarajan V.; Wang, Xiaoshi; Sidoli, Simone; Liu, Shichong; Garcia, Benjamin A.

2015-01-01

Histone post-translational modifications contribute to chromatin function through their chemical properties which influence chromatin structure and their ability to recruit chromatin interacting proteins. Nanoflow liquid chromatography coupled with high resolution tandem mass spectrometry (nanoLC-MS/MS) has emerged as the most suitable technology for global histone modification analysis because of the high sensitivity and the high mass accuracy of this approach that provides confident identification. However, analysis of histones with this method is even more challenging because of the large number and variety of isobaric histone peptides and the high dynamic range of histone peptide abundances. Here, we introduce EpiProfile, a software tool that discriminates isobaric histone peptides using the distinguishing fragment ions in their tandem mass spectra and extracts the chromatographic area under the curve using previous knowledge about peptide retention time. The accuracy of EpiProfile was evaluated by analysis of mixtures containing different ratios of synthetic histone peptides. In addition to label-free quantification of histone peptides, EpiProfile is flexible and can quantify different types of isotopically labeled histone peptides. EpiProfile is unique in generating layouts (i.e. relative retention time) of histone peptides when compared with manual quantification of the data and other programs (such as Skyline), filling the need of an automatic and freely available tool to quantify labeled and non-labeled modified histone peptides. In summary, EpiProfile is a valuable nanoflow liquid chromatography coupled with high resolution tandem mass spectrometry-based quantification tool for histone peptides, which can also be adapted to analyze nonhistone protein samples. PMID:25805797

Metabolism of an insect diuretic hormone by Malpighian tubules studied by liquid chromatography coupled with electrospray ionization mass spectrometry

PubMed Central

Li, Hong; Wang, Houle; Schegg, Kathleen M.; Schooley, David A.

1997-01-01

The larger of two diuretic hormones of the tobacco hornworm, Manduca sexta, (Mas-DH) is a peptide of 41 residues. It is one of a family of seven currently known insect diuretic hormones that are similar to the corticotropin-releasing factor–urotensin–sauvagine family of peptides. We investigated the possible inactivation of Mas-DH by incubating it in vitro with larval Malpighian tubules (Mt), the target organ of the hormone. The medium was analyzed, and degradation products were identified, using on-line microbore reversed-phase liquid chromatography coupled to electrospray ionization mass spectrometry (RPLC-ESI-MS). This sensitive technique allows identification of metabolites of Mas-DH (present at an initial level of ≈1 μM). An accurate Mr value for a metabolite is usually sufficient for unambiguous identification. Mas-DH is cleaved by Mt proteases initially at L29–R30 and R30–A31 under our assay conditions; some Mas-DH is also oxidized, apparently at M2 and M11. The proteolysis can be inhibited by 5 mM EDTA, suggesting that divalent metals are needed for peptide cleavage. The oxidation of the hormone can be inhibited by catalase or 1 mM methionine, indicating that H2O2 or related reactive oxygen species are responsible for the oxidative degradation observed. RPLC-ESI-MS is shown here to be an elegant and efficient method for studying peptide hormone metabolism resulting from unknown proteases and pathways. PMID:9391048

A Cocoa Peptide Protects Caenorhabditis elegans from Oxidative Stress and β-Amyloid Peptide Toxicity

PubMed Central

Martorell, Patricia; Bataller, Esther; Llopis, Silvia; Gonzalez, Núria; Álvarez, Beatriz; Montón, Fernando; Ortiz, Pepa; Ramón, Daniel; Genovés, Salvador

2013-01-01

Background Cocoa and cocoa-based products contain different compounds with beneficial properties for human health. Polyphenols are the most frequently studied, and display antioxidant properties. Moreover, protein content is a very interesting source of antioxidant bioactive peptides, which can be used therapeutically for the prevention of age-related diseases. Methodology/Principal Findings A bioactive peptide, 13L (DNYDNSAGKWWVT), was obtained from a hydrolyzed cocoa by-product by chromatography. The in vitro inhibition of prolyl endopeptidase (PEP) was used as screening method to select the suitable fraction for peptide identification. Functional analysis of 13L peptide was achieved using the transgenic Caenorhabditis elegans strain CL4176 expressing the human Aβ1–42 peptide as a pre-clinical in vivo model for Alzheimer's disease. Among the peptides isolated, peptide 13L (1 µg/mL) showed the highest antioxidant activity (P≤0.001) in the wild-type strain (N2). Furthermore, 13L produced a significant delay in body paralysis in strain CL4176, especially in the 24–47 h period after Aβ1–42 peptide induction (P≤0.0001). This observation is in accordance with the reduction of Aβ deposits in CL4176 by western blot. Finally, transcriptomic analysis in wild-type nematodes treated with 13L revealed modulation of the proteosomal and synaptic functions as the main metabolic targets of the peptide. Conclusions/Significance These findings suggest that the cocoa 13L peptide has antioxidant activity and may reduce Aβ deposition in a C. elegans model of Alzheimer's disease; and therefore has a putative therapeutic potential for prevention of age-related diseases. Further studies in murine models and humans will be essential to analyze the effectiveness of the 13L peptide in higher animals. PMID:23675471

A HUPO test sample study reveals common problems in mass spectrometry-based proteomics

PubMed Central

Bell, Alexander W.; Deutsch, Eric W.; Au, Catherine E.; Kearney, Robert E.; Beavis, Ron; Sechi, Salvatore; Nilsson, Tommy; Bergeron, John J.M.

2009-01-01

We carried out a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in LC-MS-based proteomics. We distributed a test sample consisting of an equimolar mix of 20 highly purified recombinant human proteins, to 27 laboratories for identification. Each protein contained one or more unique tryptic peptides of 1250 Da to also test for ion selection and sampling in the mass spectrometer. Of the 27 labs, initially only 7 labs reported all 20 proteins correctly, and only 1 lab reported all the tryptic peptides of 1250 Da. Nevertheless, a subsequent centralized analysis of the raw data revealed that all 20 proteins and most of the 1250 Da peptides had in fact been detected by all 27 labs. The centralized analysis allowed us to determine sources of problems encountered in the study, which include missed identifications (false negatives), environmental contamination, database matching, and curation of protein identifications. Improved search engines and databases are likely to increase the fidelity of mass spectrometry-based proteomics. PMID:19448641

Mass spectrometry compatible surfactant for optimized in-gel protein digestion.

PubMed

Saveliev, Sergei V; Woodroofe, Carolyn C; Sabat, Grzegorz; Adams, Christopher M; Klaubert, Dieter; Wood, Keith; Urh, Marjeta

2013-01-15

Identification of proteins resolved by SDS-PAGE depends on robust in-gel protein digestion and efficient peptide extraction, requirements that are often difficult to achieve. A lengthy and laborious procedure is an additional challenge of protein identification in gel. We show here that with the use of the mass spectrometry compatible surfactant sodium 3-((1-(furan-2-yl)undecyloxy)carbonylamino)propane-1-sulfonate, the challenges of in-gel protein digestion are effectively addressed. Peptide quantitation based on stable isotope labeling showed that the surfactant induced 1.5-2 fold increase in peptide recovery. Consequently, protein sequence coverage was increased by 20-30%, on average, and the number of identified proteins saw a substantial boost. The surfactant also accelerated the digestion process. Maximal in-gel digestion was achieved in as little as one hour, depending on incubation temperature, and peptides were readily recovered from gel eliminating the need for postdigestion extraction. This study shows that the surfactant provides an efficient means of improving protein identification in gel and streamlining the in-gel digestion procedure requiring no extra handling steps or special equipment.

Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

DOE PAGES

Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; ...

2013-03-07

In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of chargedmore » peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.« less

Elucidating Proteoform Families from Proteoform Intact-Mass and Lysine-Count Measurements

PubMed Central

2016-01-01

Proteomics is presently dominated by the “bottom-up” strategy, in which proteins are enzymatically digested into peptides for mass spectrometric identification. Although this approach is highly effective at identifying large numbers of proteins present in complex samples, the digestion into peptides renders it impossible to identify the proteoforms from which they were derived. We present here a powerful new strategy for the identification of proteoforms and the elucidation of proteoform families (groups of related proteoforms) from the experimental determination of the accurate proteoform mass and number of lysine residues contained. Accurate proteoform masses are determined by standard LC–MS analysis of undigested protein mixtures in an Orbitrap mass spectrometer, and the lysine count is determined using the NeuCode isotopic tagging method. We demonstrate the approach in analysis of the yeast proteome, revealing 8637 unique proteoforms and 1178 proteoform families. The elucidation of proteoforms and proteoform families afforded here provides an unprecedented new perspective upon proteome complexity and dynamics. PMID:26941048

Label-Free Discovery Array Platform for the Characterization of Glycan Binding Proteins and Glycoproteins.

PubMed

Gray, Christopher J; Sánchez-Ruíz, Antonio; Šardzíková, Ivana; Ahmed, Yassir A; Miller, Rebecca L; Reyes Martinez, Juana E; Pallister, Edward; Huang, Kun; Both, Peter; Hartmann, Mirja; Roberts, Hannah N; Šardzík, Robert; Mandal, Santanu; Turnbull, Jerry E; Eyers, Claire E; Flitsch, Sabine L

2017-04-18

The identification of carbohydrate-protein interactions is central to our understanding of the roles of cell-surface carbohydrates (the glycocalyx), fundamental for cell-recognition events. Therefore, there is a need for fast high-throughput biochemical tools to capture the complexity of these biological interactions. Here, we describe a rapid method for qualitative label-free detection of carbohydrate-protein interactions on arrays of simple synthetic glycans, more complex natural glycosaminoglycans (GAG), and lectins/carbohydrate binding proteins using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. The platform can unequivocally identify proteins that are captured from either purified or complex sample mixtures, including biofluids. Identification of proteins bound to the functionalized array is achieved by analyzing either the intact protein mass or, after on-chip proteolytic digestion, the peptide mass fingerprint and/or tandem mass spectrometry of selected peptides, which can yield highly diagnostic sequence information. The platform described here should be a valuable addition to the limited analytical toolbox that is currently available for glycomics.

Matrix-assisted laser desorption-ionization mass spectrometry peptide mass fingerprinting for proteome analysis: identification efficiency after on-blot or in-gel digestion with and without desalting procedures.

PubMed

Lamer, S; Jungblut, P R

2001-03-10

In theory, peptide mass fingerprinting by matrix assisted laser desorption-ionization mass spectrometry (MALDI-MS) has the potential to identify all of the proteins detected by silver staining on gels. In practice, if the genome of the organism investigated is completely sequenced, using current techniques, all proteins stained by Coomassie Brilliant Blue can be identified. This loss of identification sensitivity of ten to hundred-fold is caused by loss of peptides by surface contacts. Therefore, we performed digestion and transfer of peptides in the lower microl range and reduced the number of steps. The peptide mix obtained from in-gel or on-blot digestion was analyzed directly after digestion or after concentration on POROS R2 beads. Eight protein spots of a 2-DE gel from Mycobacterium bovis BCG were identified using these four preparation procedures for MALDI-MS. Overall, on-blot digestion was as effective as in-gel digestion. Whereas higher signal intensities resulted after concentration, hydrophilic peptides are better detected by direct measurement of the peptide mix without POROS R2 concentration.

Transmissible gastroenteritis virus; identification of M protein-binding peptide ligands with antiviral and diagnostic potential

USDA-ARS?s Scientific Manuscript database

The membrane (M) protein is one of the major structural proteins of coronavirus particles. In this study, the M protein of transmissible gastroenteritis virus (TGEV) was used to biopan a 12-mer phage display random peptide library. Three phages expressing TGEV-M-binding peptides were identified and ...

Screening and identification of novel B cell epitopes of Toxoplasma gondii SAG1

PubMed Central

2013-01-01

Background The identification of protein epitopes is useful for diagnostic purposes and for the development of peptide vaccines. In this study, the epitopes of Toxoplasma gondii SAG1 were identified using synthetic peptide techniques with the aid of bioinformatics. Findings Eleven peptides derived from T. gondii SAG1 were assessed by ELISA using pig sera from different time points after infection. Four (PS4, PS6, PS10 and PS11), out of the eleven peptides tested were recognized by all sera. Then, shorter peptides that were derived from PS4, PS6, PS10 and PS11 were predicted using bioinformatics and tested by experimentation. Four out of nine shorter peptides were identified successfully (amino acids 106–120, 166–180, 289–300 and 313–332). Conclusions We have precisely located the epitopes of T. gondii SAG1 using pig sera collected at different time points after infection. The identified epitopes may be useful for the further study of epitope-based vaccines and diagnostic reagents. PMID:23631709

Combinatorial peptide libraries and biometric score matrices permit the quantitative analysis of specific and degenerate interactions between clonotypic TCR and MHC peptide ligands.

PubMed

Zhao, Y; Gran, B; Pinilla, C; Markovic-Plese, S; Hemmer, B; Tzou, A; Whitney, L W; Biddison, W E; Martin, R; Simon, R

2001-08-15

The interaction of TCRs with MHC peptide ligands can be highly flexible, so that many different peptides are recognized by the same TCR in the context of a single restriction element. We provide a quantitative description of such interactions, which allows the identification of T cell epitopes and molecular mimics. The response of T cell clones to positional scanning synthetic combinatorial libraries is analyzed with a mathematical approach that is based on a model of independent contribution of individual amino acids to peptide Ag recognition. This biometric analysis compares the information derived from these libraries composed of trillions of decapeptides with all the millions of decapeptides contained in a protein database to rank and predict the most stimulatory peptides for a given T cell clone. We demonstrate the predictive power of the novel strategy and show that, together with gene expression profiling by cDNA microarrays, it leads to the identification of novel candidate autoantigens in the inflammatory autoimmune disease, multiple sclerosis.

Bioaffinity magnetic reactor for peptide digestion followed by analysis using bottom-up shotgun proteomics strategy.

PubMed

Korecká, Lucie; Jankovicová, Barbora; Krenková, Jana; Hernychová, Lenka; Slováková, Marcela; Le-Nell, Anne; Chmelik, Josef; Foret, Frantisek; Viovy, Jean-Louis; Bilková, Zusana

2008-02-01

We report an efficient and streamlined way to improve the analysis and identification of peptides and proteins in complex mixtures of soluble proteins, cell lysates, etc. By using the shotgun proteomics methodology combined with bioaffinity purification we can remove or minimize the interference contamination of a complex tryptic digest and so avoid the time-consuming separation steps before the final MS analysis. We have proved that by means of enzymatic fragmentation (endoproteinases with Arg-C or/and Lys-C specificity) connected with the isolation of specific peptides we can obtain a simplified peptide mixture for easier identification of the entire protein. A new bioaffinity sorbent was developed for this purpose. Anhydrotrypsin (AHT), an inactive form of trypsin with an affinity for peptides with arginine (Arg) or lysine (Lys) at the C-terminus, was immobilized onto micro/nanoparticles with superparamagnetic properties (silica magnetite particles (SiMAG)-Carboxyl, Chemicell, Germany). This AHT carrier with a determined binding capacity (26.8 nmol/mg of carrier) was tested with a model peptide, human neurotensin, and the resulting MS spectra confirmed the validity of this approach.

Identification of small peptides arising from hydrolysis of meat proteins in dry fermented sausages.

PubMed

López, Constanza M; Bru, Elena; Vignolo, Graciela M; Fadda, Silvina G

2015-06-01

In this study, proteolysis and low molecular weight (LMW) peptides (<3kDa) from commercial Argentinean fermented sausages were characterized by applying a peptidomic approach. Protein profiles and peptides obtained by Tricine-SDS-PAGE and RP-HPLC-MS, respectively, allowed distinguishing two different types of fermented sausages, although no specific biomarkers relating to commercial brands or quality were recognized. From electrophoresis, α-actin, myoglobin, creatine kinase M-type and L-lactate dehydrogenase were degraded at different intensities. In addition, a partial characterization of fermented sausage peptidome through the identification of 36 peptides, in the range of 1000-2100 Da, arising from sarcoplasmic (28) and myofibrillar (8) proteins was achieved. These peptides had been originated from α-actin, myoglobin, and creatine kinase M-type, but also from the hydrolysis of other proteins not previously reported. Although muscle enzymes exerted a major role on peptidogenesis, microbial contribution cannot be excluded as it was postulated herein. This work represents a first peptidomic approach for fermented sausages, thereby providing a baseline to define key peptides acting as potential biomarkers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Methods for Studying Interactions Between Atg8/LC3/GABARAP and LIR-Containing Proteins.

PubMed

Johansen, T; Birgisdottir, Å B; Huber, J; Kniss, A; Dötsch, V; Kirkin, V; Rogov, V V

2017-01-01

LC3/GABARAP proteins (LC3/GABARAPs) are mammalian orthologues of yeast Atg8, small ubiquitin (Ub)-like proteins (UBLs) whose covalent attachment to lipid membranes is crucial for the growth and closure of the double membrane vesicle called the autophagosome. In the past decade, it was demonstrated that Atg8/LC3/GABARAPs are also required for autophagic degradation of cargos in a selective fashion. Cargo selectivity is ensured by receptor proteins, such as p62/SQSTM1, NBR1, Cue5, Atg19, NIX, Atg32, NCOA4, and FAM134B, which simultaneously bind Atg8/LC3/GABARAPs and the cargo together, thereby linking the core autophagic machinery to the target structure: a protein, an organelle, or a pathogen. LC3-interacting regions (LIRs) are short linear motifs within selective autophagy receptors and some other structural and signaling proteins (e.g., ULK1, ATG13, FIP200, and Dvl2), which mediate binding to Atg8/LC3/GABARAPs. Identification and characterization of LIR-containing proteins have provided important insights into the biology of the autophagy pathway, and studying their interactions with the core autophagy machinery represents a growing area of autophagy research. Here, we present protocols for the identification of LIR-containing proteins, i.e., by yeast-two-hybrid screening, glutathione S-transferase (GST) pulldown experiments, and peptide arrays. The use of two-dimensional peptide arrays also represents a powerful method to identify the residues of the LIR motif that are critical for binding. We also describe a biophysical method for studying interactions between Atg8/LC3/GABARAP and LIR-containing proteins and a protocol for preparation and purification of LIR peptides. © 2017 Elsevier Inc. All rights reserved.

Identification of Extracellular Segments by Mass Spectrometry Improves Topology Prediction of Transmembrane Proteins.

PubMed

Langó, Tamás; Róna, Gergely; Hunyadi-Gulyás, Éva; Turiák, Lilla; Varga, Julia; Dobson, László; Várady, György; Drahos, László; Vértessy, Beáta G; Medzihradszky, Katalin F; Szakács, Gergely; Tusnády, Gábor E

2017-02-13

Transmembrane proteins play crucial role in signaling, ion transport, nutrient uptake, as well as in maintaining the dynamic equilibrium between the internal and external environment of cells. Despite their important biological functions and abundance, less than 2% of all determined structures are transmembrane proteins. Given the persisting technical difficulties associated with high resolution structure determination of transmembrane proteins, additional methods, including computational and experimental techniques remain vital in promoting our understanding of their topologies, 3D structures, functions and interactions. Here we report a method for the high-throughput determination of extracellular segments of transmembrane proteins based on the identification of surface labeled and biotin captured peptide fragments by LC/MS/MS. We show that reliable identification of extracellular protein segments increases the accuracy and reliability of existing topology prediction algorithms. Using the experimental topology data as constraints, our improved prediction tool provides accurate and reliable topology models for hundreds of human transmembrane proteins.

Sequence-Specific Model for Peptide Retention Time Prediction in Strong Cation Exchange Chromatography.

PubMed

Gussakovsky, Daniel; Neustaeter, Haley; Spicer, Victor; Krokhin, Oleg V

2017-11-07

The development of a peptide retention prediction model for strong cation exchange (SCX) separation on a Polysulfoethyl A column is reported. Off-line 2D LC-MS/MS analysis (SCX-RPLC) of S. cerevisiae whole cell lysate was used to generate a retention dataset of ∼30 000 peptides, sufficient for identifying the major sequence-specific features of peptide retention mechanisms in SCX. In contrast to RPLC/hydrophilic interaction liquid chromatography (HILIC) separation modes, where retention is driven by hydrophobic/hydrophilic contributions of all individual residues, SCX interactions depend mainly on peptide charge (number of basic residues at acidic pH) and size. An additive model (incorporating the contributions of all 20 residues into the peptide retention) combined with a peptide length correction produces a 0.976 R 2 value prediction accuracy, significantly higher than the additive models for either HILIC or RPLC. Position-dependent effects on peptide retention for different residues were driven by the spatial orientation of tryptic peptides upon interaction with the negatively charged surface functional groups. The positively charged N-termini serve as a primary point of interaction. For example, basic residues (Arg, His, Lys) increase peptide retention when located closer to the N-terminus. We also found that hydrophobic interactions, which could lead to a mixed-mode separation mechanism, are largely suppressed at 20-30% of acetonitrile in the eluent. The accuracy of the final Sequence-Specific Retention Calculator (SSRCalc) SCX model (∼0.99 R 2 value) exceeds all previously reported predictors for peptide LC separations. This also provides a solid platform for method development in 2D LC-MS protocols in proteomics and peptide retention prediction filtering of false positive identifications.

Identification and quantification of ricin in biomedical samples by magnetic immunocapture enrichment and liquid chromatography electrospray ionization tandem mass spectrometry.

PubMed

Ma, Xiaoxi; Tang, Jijun; Li, Chunzheng; Liu, Qin; Chen, Jia; Li, Hua; Guo, Lei; Xie, Jianwei

2014-08-01

Ricin is a toxic protein derived from castor beans and composed of a cytotoxic A chain and a galactose-binding B chain linked by a disulfide bond, which can inhibit protein synthesis and cause cell death. Owing to its high toxicity, ease of preparation, and lack of medical countermeasures, ricin has been listed as both chemical and biological warfare agents. For homeland security or public safety, the unambiguous, sensitive, and rapid methods for identification and quantification of ricin in complicated matrices are of urgent need. Mass spectrometric analysis, which provides specific and sensitive characterization of protein, can be applied to confirm and quantify ricin. Here, we report a liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) method in which ricin was extracted and enriched from serum by immunocapture using anti-ricin monoclonal antibody 3D74 linked to magnetic beads, then digested by trypsin, and analyzed by LC-ESI-MS/MS. Among 19 distinct peptides observed in LC-quadrupole/time of flight-MS (LC-QTOF-MS), two specific and sensitive peptides, T7A ((49)VGLPINQR(56)) and T14B ((188)DNCLTSDSNIR(198)), were chosen, and a highly sensitive determination of ricin was established in LC-triple quadrupole-MS (LC-QqQ-MS) operating in multiple reaction monitoring mode. These specific peptides can definitely distinguish ricin from the homologous protein Ricinus communis agglutinin (RCA120), even though the amino acid sequence homology of the A-chain of ricin and RCA120 is up to ca. 93% and that of B-chain is ca. 85%. Furthermore, peptide T7A was preferred in the quantification of ricin because its sensitivity was at least one order of magnitude higher than that of the peptide T14B. Combined with immunocapture enrichment, this method provided a limit of detection of ca. 2.5 ng/mL and the limit of quantification was ca. 5 ng/mL of ricin in serum, respectively. Both precision and accuracy of this method were determined and the RSD was less than 15%. This established method was then applied to measure ricin in serum samples collected from rats exposed to ricin at the dosage of 50 μg/kg in an intravenous injection manner. The results showed that ca. 10 ng/mL of the residual ricin in poisoned rats serum could be detected even at 12 h after exposure.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping.

PubMed

Mukherjee, Sumanta; Warwicker, Jim; Chandra, Nagasuma

2015-07-01

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

Resin-assisted Enrichment of N-terminal Peptides for Characterizing Proteolytic Processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jong Seo; Dai, Ziyu; Aryal, Uma K.

2013-06-17

Proteolytic processing is a ubiquitous, irreversible posttranslational modification that plays an important role in cellular regulation in all living organisms. Herein we report a resin-assisted positive selection method for specifically enriching protein N-terminal peptides to facilitate the characterization of proteolytic processing events by liquid chromatography-tandem mass spectrometry. In this approach, proteins are initially reduced and alkylated and their lysine residues are converted to homoarginines. Then, protein N-termini are selectively converted to reactive thiol groups. We demonstrate that these sequential reactions were achieved with nearly quantitative efficiencies. Thiol-containing N-terminal peptides are then captured (>98% efficiency) by a thiol-affinity resin, a significantmore » improvement over the traditional avidin/biotin enrichment. Application to cell lysates of Aspergillus niger, a filamentous fungus of interest for biomass degradation, enabled the identification of 1672 unique protein N-termini and proteolytic cleavage sites from 690 unique proteins.« less

Identification and validation of FGFR2 peptide for detection of early Barrett's neoplasia

PubMed Central

Zhou, Juan; He, Lei; Pang, Zhijun; Appelman, Henry D.; Kuick, Rork; Beer, David G.; Li, Meng; Wang, Thomas D.

2017-01-01

The incidence of esophageal adenocarcinoma (EAC) is rising rapidly, and early detection within the precursor state of Barrett's esophagus (BE) is challenged by flat premalignant lesions that are difficult detect with conventional endoscopic surveillance. Overexpression of cell surface fibroblast growth factor receptor 2 (FGFR2) is an early event in progression of BE to EAC, and is a promising imaging target. We used phage display to identify the peptide SRRPASFRTARE that binds specifically to the extracellular domain of FGFR2. We labeled this peptide with a near-infrared fluorophore Cy5.5, and validated the specific binding to FGFR2 overexpressed in cells in vitro. We found high affinity kd = 68 nM and rapid binding k = 0.16 min−1 (6.2 min). In human esophageal specimens, we found significantly greater peptide binding to high-grade dysplasia (HGD) versus either BE or normal squamous epithelium, and good correlation with anti-FGFR2 antibody. We also observed significantly greater peptide binding to excised specimens of esophageal squamous cell carcinoma and gastric cancer compared to normal mucosa. These results demonstrate potential for this FGFR2 peptide to be used as a clinical imaging agent to guide tissue biopsy and improve methods for early detection of EAC and potentially other epithelial-derived cancers. PMID:29152066

Peptidome characterization and bioactivity analysis of donkey milk.

PubMed

Piovesana, Susy; Capriotti, Anna Laura; Cavaliere, Chiara; La Barbera, Giorgia; Samperi, Roberto; Zenezini Chiozzi, Riccardo; Laganà, Aldo

2015-04-24

Donkey milk is an interesting commercial product for its nutritional values, which make it the most suitable mammalian milk for human consumption, and for the bioactivity associated with it and derivative products. To further mine the characterization of donkey milk, an extensive peptidomic study was performed. Two peptide purification strategies were compared to remove native proteins and lipids and enrich the peptide fraction. In one case the whole protein content was precipitated by organic solvent using cold acetone. In the other one the precipitation of the most abundant milk proteins, caseins, was performed under acidic conditions by acetic acid at pH4.6, instead. The procedures were compared and proved to be partially complementary. Considered together they provided 1330 peptide identifications for donkey milk, mainly coming from the most abundant proteins in milk. The bioactivity of the isolated peptides was also investigated, both by angiotensin-converting-enzyme inhibitory and antioxidant activity assays and by bioinformatics, proving that the isolated peptides did have the tested biological activities. The rationale behind this study is that peptides in food matrices often play an important biological role and, despite the extensive study of the protein composition of different samples, they remain poorly characterized. In fact, in a typical shotgun proteomics study endogenous peptides are not properly characterized. In proteomics workflows one limiting point is the isolation process: if it is specific for the purification of proteins, it often comprises a precipitation step which aims at isolating pure protein pellets and remove unwonted interferent compounds. In this way endogenous peptides, which are not effectively precipitated as well as proteins, are removed too and not analyzed at the end of the process. Moreover, endogenous peptides do often originate from precursor proteins, but in phenomena which are independent of the shotgun digestion protocol, thus they can be obtained from cleavage specificities other than trypsin's, which is the main proteolytic enzyme employed in proteomic experiments. For this reason, in the end, database search will not be effective for identification of these peptides, thus the need to provide different workflows for peptide analysis. In the work presented in this paper this issue is considered for the first time for the analysis of the peptides isolated in donkey milk samples, which have been chosen for its nutritional interest. This study provides additional knowledge on this milk, already characterized by traditional proteomics studies and peptidomic studies after simulated digestion. This type of study is not just a description of the naturally occurring peptidome of a sample, but also represents a starting point to discover and characterize those naturally occurring peptides responsible for the observed bioactivities of biological samples, as in the case of donkey milk, which would remain uncharacterized by other approaches. In this paper an analytical protocol was described for the efficient isolation and purification of peptides in donkey milk, assessing the effect of the purification protocol on the final identifications. Purified peptide samples were also checked to empirically elucidate any ACE inhibitory or antioxidant activity. Finally, the peptidomic results were also further mined by a bioinformatic-driven approach for bioactive peptide identification in the donkey milk samples. In our opinion, the main strengths of this study are related to the improved analytical workflow (either as purification protocol comparison or analytical platform development) which provides a high number of identified peptides, for which the biological significance as potential bioactive peptides has also been investigated. Copyright © 2015 Elsevier B.V. All rights reserved.

Pepitome: evaluating improved spectral library search for identification complementarity and quality assessment

PubMed Central

Dasari, Surendra; Chambers, Matthew C.; Martinez, Misti A.; Carpenter, Kristin L.; Ham, Amy-Joan L.; Vega-Montoto, Lorenzo J.; Tabb, David L.

2012-01-01

Spectral libraries have emerged as a viable alternative to protein sequence databases for peptide identification. These libraries contain previously detected peptide sequences and their corresponding tandem mass spectra (MS/MS). Search engines can then identify peptides by comparing experimental MS/MS scans to those in the library. Many of these algorithms employ the dot product score for measuring the quality of a spectrum-spectrum match (SSM). This scoring system does not offer a clear statistical interpretation and ignores fragment ion m/z discrepancies in the scoring. We developed a new spectral library search engine, Pepitome, which employs statistical systems for scoring SSMs. Pepitome outperformed the leading library search tool, SpectraST, when analyzing data sets acquired on three different mass spectrometry platforms. We characterized the reliability of spectral library searches by confirming shotgun proteomics identifications through RNA-Seq data. Applying spectral library and database searches on the same sample revealed their complementary nature. Pepitome identifications enabled the automation of quality analysis and quality control (QA/QC) for shotgun proteomics data acquisition pipelines. PMID:22217208

Elucidation of cross-species proteomic effects in human and hominin bone proteome identification through a bioinformatics experiment.

PubMed

Welker, F

2018-02-20

The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identifications at increased evolutionary distances due to a larger number of protein sequence differences between the database sequence and the analyzed organism. Error-tolerant proteomic search algorithms should theoretically overcome this problem at both the peptide and protein level; however, this has not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against sequence databases at increasing evolutionary distances: the human (0 Ma), chimpanzee (6-8 Ma) and orangutan (16-17 Ma) reference proteomes, respectively. Incorrectly suggested amino acid substitutions are absent when employing adequate filtering criteria for mutable Peptide Spectrum Matches (PSMs), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations between the target and database sequences are the main factors influencing mutable PSM identification. The error-tolerant results suggest that the cross-species proteomics problem is not overcome at increasing evolutionary distances, even at the protein level. Peptide and protein loss has the potential to significantly impact divergence dating and proteome comparisons when using ancient samples as there is a bias towards the identification of conserved sequences and proteins. Effects are minimized between moderately divergent proteomes, as indicated by almost complete recovery of informative positions in the search against the chimpanzee proteome (≈90%, 6-8 Ma). This provides a bioinformatic background to future phylogenetic and proteomic analysis of ancient hominin proteomes, including the future description of novel hominin amino acid sequences, but also has negative implications for the study of fast-evolving proteins in hominins, non-hominin animals, and ancient bacterial proteins in evolutionary contexts.

Distinguishing Sulfotyrosine Containing Peptides from their Phosphotyrosine Counterparts Using Mass Spectrometry

NASA Astrophysics Data System (ADS)

Chen, Guangming; Zhang, Yixiang; Trinidad, Jonathan C.; Dann, Charles

2018-03-01

Sulfotyrosine and phosphotyrosine are two post-translational modifications present in higher eukaryotes. A simple and direct mass spectrometry method to distinguish between these modifications is crucial to advance our understanding of the sulfoproteome. While sulfation and phosphorylation are nominally isobaric, the accurate mass of the sulfuryl moiety is 9.6 mDa less than the phosphoryl moiety. Based on this difference, we have used an Orbitrap Fusion Lumos mass spectrometer to characterize, resolve, and distinguish between sulfotyrosine and phosphotyrosine modifications using a set of model peptides. Multiple fragmentation techniques, namely HCD, CID, ETD, ETciD, and EThcD, have been used to compare the different fragmentation behaviors between peptides modified with these species. Sulfotyrosine undergoes neutral loss using HCD and CID, but the sulfuryl moiety is largely stable under ETD. In contrast, phosphotyrosine is stable during fragmentation using all these methods. This differential stability provides a mechanism to distinguish sulfopeptides from phosphopeptides. Based on the rigorous characterization presented herein, this work serves as a model for accurate identification of phosphotyrosine and, more challenging, sulfotyrosine, in complex proteomic samples. [Figure not available: see fulltext.

Identification of Fusarium virguliforme FvTox1-Interacting Synthetic Peptides for Enhancing Foliar Sudden Death Syndrome Resistance in Soybean

PubMed Central

Wang, Bing; Swaminathan, Sivakumar; Bhattacharyya, Madan K.

2015-01-01

Soybean is one of the most important crops grown across the globe. In the United States, approximately 15% of the soybean yield is suppressed due to various pathogen and pests attack. Sudden death syndrome (SDS) is an emerging fungal disease caused by Fusarium virguliforme. Although growing SDS resistant soybean cultivars has been the main method of controlling this disease, SDS resistance is partial and controlled by a large number of quantitative trait loci (QTL). A proteinacious toxin, FvTox1, produced by the pathogen, causes foliar SDS. Earlier, we demonstrated that expression of an anti-FvTox1 single chain variable fragment antibody resulted in reduced foliar SDS development in transgenic soybean plants. Here, we investigated if synthetic FvTox1-interacting peptides, displayed on M13 phage particles, can be identified for enhancing foliar SDS resistance in soybean. We screened three phage-display peptide libraries and discovered four classes of M13 phage clones displaying FvTox1-interacting peptides. In vitro pull-down assays and in vivo interaction assays in yeast were conducted to confirm the interaction of FvTox1 with these four synthetic peptides and their fusion-combinations. One of these peptides was able to partially neutralize the toxic effect of FvTox1 in vitro. Possible application of the synthetic peptides in engineering SDS resistance soybean cultivars is discussed. PMID:26709700

Chemical proteomics for target discovery of head-to-tail cyclized mini-proteins

NASA Astrophysics Data System (ADS)

Hellinger, Roland; Thell, Kathrin; Vasileva, Mina; Muhammad, Taj; Gunasekera, Sunithi; Kümmel, Daniel; Göransson, Ulf; Becker, Christian W.; Gruber, Christian W.

2017-10-01

Target deconvolution is one of the most challenging tasks in drug discovery, but a key step in drug development. In contrast to small molecules, there is a lack of validated and robust methodologies for target elucidation of peptides. In particular, it is difficult to apply these methods to cyclic and cysteine-stabilized peptides since they exhibit reduced amenability to chemical modification and affinity capture; however, such ribosomal synthesized and post-translationally modified peptide natural products are rich sources of promising drug candidates. For example, plant-derived circular peptides called cyclotides have recently attracted much attention due to their immunosuppressive effects and oral activity in the treatment of multiple sclerosis in mice, but their molecular target has hitherto not been reported. In this study a chemical proteomics approach using photo-affinity crosslinking was developed to determine a target of the circular peptide [T20K]kalata B1. Using this prototypic nature-derived peptide enabled the identification of a possible modulation of 14-3-3 proteins. This biochemical interaction was validated via competition pull down assays as well as a cellular reporter assay indicating an effect on 14-3-3-dependent transcriptional activity. As proof of concept, the presented approach may be applicable for target elucidation of various cyclic peptides and mini-proteins, in particular cyclotides, which represent a promising class of molecules in drug discovery and development.

Identification of protein–protein interfaces by decreased amide proton solvent accessibility

PubMed Central

Mandell, Jeffrey G.; Falick, Arnold M.; Komives, Elizabeth A.

1998-01-01

Matrix-assisted laser desorption ionization–time-of-flight mass spectrometry was used to identify peptic fragments from protein complexes that retained deuterium under hydrogen exchange conditions due to decreased solvent accessibility at the interface of the complex. Short deuteration times allowed preferential labeling of rapidly exchanging surface amides so that primarily solvent accessibility changes and not conformational changes were detected. A single mass spectrum of the peptic digest mixture was analyzed to determine the deuterium content of all proteolytic fragments of the protein. The protein–protein interface was reliably indicated by those peptides that retained more deuterons in the complex compared with control experiments in which only one protein was present. The method was used to identify the kinase inhibitor [PKI(5–24)] and ATP-binding sites in the cyclic-AMP-dependent protein kinase. Three overlapping peptides identified the ATP-binding site, three overlapping peptides identified the glycine-rich loop, and two peptides identified the PKI(5–24)-binding site. A complex of unknown structure also was analyzed, human α-thrombin bound to an 83-aa fragment of human thrombomodulin [TMEGF(4–5)]. Five peptides from thrombin showed significantly decreased solvent accessibility in the complex. Three peptides identified the anion-binding exosite I, confirming ligand competition experiments. Two peptides identified a new region of thrombin near the active site providing a potential mechanism of how thrombomodulin alters thrombin substrate specificity. PMID:9843953

Expression analysis and identification of antimicrobial peptide transcripts from six North American frog species

USGS Publications Warehouse

Robertson, Laura S.; Fellers, Gary M.; Marranca, Jamie Marie; Kleeman, Patrick M.

2013-01-01

Frogs secrete antimicrobial peptides onto their skin. We describe an assay to preserve and analyze antimicrobial peptide transcripts from field-collected skin secretions that will complement existing methods for peptide analysis. We collected skin secretions from 4 North American species in the field in California and 2 species in the laboratory. Most frogs appeared healthy after release; however, Rana boylii in the Sierra Nevada foothills, but not the Coast Range, showed signs of morbidity and 2 died after handling. The amount of total RNA extracted from skin secretions was higher in R. boylii and R. sierrae compared to R. draytonii, and much higher compared to Pseudacris regilla. Interspecies variation in amount of RNA extracted was not explained by size, but for P. regilla it depended upon collection site and date. RNA extracted from skin secretions from frogs handled with bare hands had poor quality compared to frogs handled with gloves or plastic bags. Thirty-four putative antimicrobial peptide precursor transcripts were identified. This study demonstrates that RNA extracted from skin secretions collected in the field is of high quality suitable for use in sequencing or quantitative PCR (qPCR). However, some species do not secrete profusely, resulting in very little extracted RNA. The ability to measure transcript abundance of antimicrobial peptides in field-collected skin secretions complements proteomic analyses and may provide insight into transcriptional mechanisms that could affect peptide abundance.

[Research progress on identification and quality evaluation of glues medicines].

PubMed

Li, Hui-Hu; Ren, Gang; Chen, Li-Min; Zhong, Guo-Yue

2018-01-01

Glues medicines is a special kind of traditional Chinese medicine.As the market demand is large, the raw materials are in short supply and lacks proper quality evaluation technology, which causes inconsistent quality of products on the market. Its authentic identification and evaluation stay a problem to be solved. In this paper, the research progress of the methods and techniques of the evaluation of the identification and quality of glues medicines were reviewed. The researches of medicinal glue type identification and quality evaluation mainly concentrated in four aspects of medicinal materials of physical and chemical properties, trace elements, organic chemicals and biological genetic methods and techniques. The methods of physicochemical properties include thermal analysis, gel electrophoresis, isoelectric focusing electrophoresis, infrared spectroscopy, gel exclusion chromatography, and circular dichroism. The methods including atomic absorption spectrometry, X-ray fluorescence spectrometry, plasma emission spectrometry and visible spectrophotometry were used for the study of the trace elements of glues medicines. The organic chemical composition was studied by methods of composition of amino acids, content detection, odor detection, lipid soluble component, organic acid detection. Methods based on the characteristics of biogenetics include DNA, polypeptide and amino acid sequence difference analysis. Overall, because of relative components similarity of the glues medicines (such as amino acids, proteins and peptides), its authenticity and quality evaluation index is difficult to judge objectively, all sorts of identification evaluation methods have different characteristics, but also their limitations. It indicates that further study should focus on identification of evaluation index and various technology integrated application combining with the characteristics of the production process. Copyright© by the Chinese Pharmaceutical Association.

Identification and Characterization of Strychnine-Binding Peptides Using Phage-Display Screening.

PubMed

Zhang, Fang; Wang, Min; Qiu, Zheng; Wang, Xiao-Meng; Xu, Chun-Lei; Zhang, Xia

2017-01-01

In drug development, phage display is a high-throughput method for identifying the specific cellular targets of drugs. However, insoluble small chemicals remain intractable to this technique because of the difficulty of presenting molecules to phages without occupying or destroying the limited functional groups. In the present study, we selected Strychnine (Stry) as a model compounda and sought to develope an alternative in vitro biopanning strategy against insoluble suspension. A phage library displaying random sequences of fifteen peptides was employed to screen for interactions between Stry and its cellular selective binding peptides, which are of great value to have a complete understanding of the mechanism of Stry for its antitumor activity. After four rounds of biopanning, a selection of 100 binding clones was randomly picked and subjected to modified proliferation and diffusion assays to evaluate the binding affinity of the clones. Finally, eleven clones were identified as positive binders. The corresponding peptides were synthesized and detected for their binding activities using surface plasmon resonance imaging (SPRi). Our study provides a feasible scheme for confirming the interaction of chemical compounds and cellular binding peptides. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Software Analysis of Uncorrelated MS1 Peaks for Discovery of Post-Translational Modifications.

PubMed

Pascal, Bruce D; West, Graham M; Scharager-Tapia, Catherina; Flefil, Ricardo; Moroni, Tina; Martinez-Acedo, Pablo; Griffin, Patrick R; Carvalloza, Anthony C

2015-12-01

The goal in proteomics to identify all peptides in a complex mixture has been largely addressed using various LC MS/MS approaches, such as data dependent acquisition, SRM/MRM, and data independent acquisition instrumentation. Despite these developments, many peptides remain unsequenced, often due to low abundance, poor fragmentation patterns, or data analysis difficulties. Many of the unidentified peptides exhibit strong evidence in high resolution MS(1) data and are frequently post-translationally modified, playing a significant role in biological processes. Proteomics Workbench (PWB) software was developed to automate the detection and visualization of all possible peptides in MS(1) data, reveal candidate peptides not initially identified, and build inclusion lists for subsequent MS(2) analysis to uncover new identifications. We used this software on existing data on the autophagy regulating kinase Ulk1 as a proof of concept for this method, as we had already manually identified a number of phosphorylation sites Dorsey, F. C. et al (J. Proteome. Res. 8(11), 5253-5263 (2009)). PWB found all previously identified sites of phosphorylation. The software has been made freely available at http://www.proteomicsworkbench.com . Graphical Abstract ᅟ.

Identification and binding mechanism of phage displayed peptides with specific affinity to acid-alkali treated titanium.

PubMed

Sun, Yuhua; Tan, Jing; Wu, Baohua; Wang, Jianxin; Qu, Shuxin; Weng, Jie; Feng, Bo

2016-10-01

Acid-alkali treatment is one of means widely used for preparing bioactive titanium surfaces. Peptides with specific affinity to titanium surface modified by acid-alkali two-steps treatment were obtained via phage display technology. Out of the eight new unique peptides, titanium-binding peptide 54 displayed by monoclonal M13 phage at its pIII coat protein (TBP54-M13 phage) was proved to have higher binding affinity to the substrate. The binding interaction occurred at the domain from phenylalanine at position 1 to arginine at position 6 in the sequences of TBP54 (FAETHRGFHFSF) mainly via the reaction of these residues with the Ti surface. Together the coordination and electrostatic interactions controlled the specific binding of the phage to the substrate. The binding affinity was dependent on the surface basic hydroxyl group content. In addition, the phage showed a different interaction way with the Ti surface without acid-alkali treatment along with an impaired affinity. This study could provide more understanding of the interaction mechanism between the selected peptide and its specific substrate, and develop a promising method for the biofunctionalization of titanium. Copyright © 2016 Elsevier B.V. All rights reserved.

Rapid Generation of a Nanocrystal-Labeled Peptide Library for Specific Identification of the Bacterium Clostrium Botulinum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tok, J B

2004-11-11

Several peptide libraries containing up to 2 million unique peptide ligands have been synthesized. The peptides are attached onto a 80 micron resin and the length of these peptide ligands ranges from 5 to 9 amino acid residues. Using a novel calorimetric assay, the libraries were screened for binding to the ganglioside-binding domain of Clostridium Tetanus Toxin, a structural similar analog of the Clostridium Botulinum toxin. Several binding peptide sequences were identified, in which the detailed binding kinetics are currently underway using the Surface Plasmon Resonance (SPR) technique.

Identifying the site of spin trapping in proteins by a combination of liquid chromatography, ELISA, and off-line tandem mass spectrometry.

PubMed

Lardinois, Olivier M; Detweiler, Charles D; Tomer, Kenneth B; Mason, Ronald P; Deterding, Leesa J

2008-03-01

An off-line mass spectrometry method that combines immuno-spin trapping and chromatographic procedures has been developed for selective detection of the nitrone spin trap 5,5-dimethyl-1-pyrroline-N-oxide (DMPO) covalently attached to proteins, an attachment which occurs only subsequent to DMPO trapping of free radicals. In this technique, the protein-DMPO nitrone adducts are digested to peptides with proteolytic agents, peptides from the enzymatic digest are separated by HPLC, and enzyme-linked immunosorbent assays (ELISA) using polyclonal anti-DMPO nitrone antiserum are used to detect the eluted HPLC fractions that contain DMPO nitrone adducts. The fractions showing positive ELISA signals are then concentrated and characterized by tandem mass spectrometry (MS/MS). This method, which constitutes the first liquid chromatography-ELISA-mass spectrometry (LC-ELISA-MS)-based strategy for selective identification of DMPO-trapped protein residues in complex peptide mixtures, facilitates location and preparative fractionation of DMPO nitrone adducts for further structural characterization. The strategy is demonstrated for human hemoglobin, horse heart myoglobin, and sperm whale myoglobin, three globin proteins known to form DMPO-trappable protein radicals on treatment with H(2)O(2). The results demonstrate the power of the new experimental strategy to select DMPO-labeled peptides and identify sites of DMPO covalent attachments.

Draft genome sequence of Streptomyces sp. strain SS, which produces a series of uridyl peptide antibiotic sansanmycins.

PubMed

Wang, Lifei; Xie, Yunying; Li, Qinglian; He, Ning; Yao, Entai; Xu, Hongzhang; Yu, Ying; Chen, Ruxian; Hong, Bin

2012-12-01

Streptomyces sp. SS produces a series of uridyl peptide antibiotic sansanmycins. Here, we present a draft genome sequence of Streptomyces sp. SS containing the biosynthetic gene cluster for the antibiotics. The identification of the biosynthetic gene cluster of sansanmycins may provide further insight into biosynthetic mechanisms for uridyl peptide antibiotics.

Identification and characterization of a sex peptide receptor-like transcript from the western tarnished plant bug, Lygus hesperus

USDA-ARS?s Scientific Manuscript database

Lygus hesperus females exhibit a post-mating behavioral switch that triggers increased egg laying and decreased sexual interest. In Drosophila melanogaster, post-mating changes in behavior are controlled by sex peptide (SP) and the sex peptide receptor (DmSPR). SPR is present in most insect genome...

Direct Identification of On-Bead Peptides Using Surface-Enhanced Raman Spectroscopic Barcoding System for High-Throughput Bioanalysis

PubMed Central

Kang, Homan; Jeong, Sinyoung; Koh, Yul; Geun Cha, Myeong; Yang, Jin-Kyoung; Kyeong, San; Kim, Jaehi; Kwak, Seon-Yeong; Chang, Hye-Jin; Lee, Hyunmi; Jeong, Cheolhwan; Kim, Jong-Ho; Jun, Bong-Hyun; Kim, Yong-Kweon; Hong Jeong, Dae; Lee, Yoon-Sik

2015-01-01

Recently, preparation and screening of compound libraries remain one of the most challenging tasks in drug discovery, biomarker detection, and biomolecular profiling processes. So far, several distinct encoding/decoding methods such as chemical encoding, graphical encoding, and optical encoding have been reported to identify those libraries. In this paper, a simple and efficient surface-enhanced Raman spectroscopic (SERS) barcoding method using highly sensitive SERS nanoparticles (SERS ID) is presented. The 44 kinds of SERS IDs were able to generate simple codes and could possibly generate more than one million kinds of codes by incorporating combinations of different SERS IDs. The barcoding method exhibited high stability and reliability under bioassay conditions. The SERS ID encoding based screening platform can identify the peptide ligand on the bead and also quantify its binding affinity for specific protein. We believe that our SERS barcoding technology is a promising method in the screening of one-bead-one-compound (OBOC) libraries for drug discovery. PMID:26017924

Direct identification of on-bead peptides using surface-enhanced Raman spectroscopic barcoding system for high-throughput bioanalysis.

PubMed

Kang, Homan; Jeong, Sinyoung; Koh, Yul; Geun Cha, Myeong; Yang, Jin-Kyoung; Kyeong, San; Kim, Jaehi; Kwak, Seon-Yeong; Chang, Hye-Jin; Lee, Hyunmi; Jeong, Cheolhwan; Kim, Jong-Ho; Jun, Bong-Hyun; Kim, Yong-Kweon; Hong Jeong, Dae; Lee, Yoon-Sik

2015-05-28

Recently, preparation and screening of compound libraries remain one of the most challenging tasks in drug discovery, biomarker detection, and biomolecular profiling processes. So far, several distinct encoding/decoding methods such as chemical encoding, graphical encoding, and optical encoding have been reported to identify those libraries. In this paper, a simple and efficient surface-enhanced Raman spectroscopic (SERS) barcoding method using highly sensitive SERS nanoparticles (SERS ID) is presented. The 44 kinds of SERS IDs were able to generate simple codes and could possibly generate more than one million kinds of codes by incorporating combinations of different SERS IDs. The barcoding method exhibited high stability and reliability under bioassay conditions. The SERS ID encoding based screening platform can identify the peptide ligand on the bead and also quantify its binding affinity for specific protein. We believe that our SERS barcoding technology is a promising method in the screening of one-bead-one-compound (OBOC) libraries for drug discovery.

Enhanced Peptide Detection Toward Single-Neuron Proteomics by Reversed-Phase Fractionation Capillary Electrophoresis Mass Spectrometry

NASA Astrophysics Data System (ADS)

Choi, Sam B.; Lombard-Banek, Camille; Muñoz-LLancao, Pablo; Manzini, M. Chiara; Nemes, Peter

2018-05-01

The ability to detect peptides and proteins in single cells is vital for understanding cell heterogeneity in the nervous system. Capillary electrophoresis (CE) nanoelectrospray ionization (nanoESI) provides high-resolution mass spectrometry (HRMS) with trace-level sensitivity, but compressed separation during CE challenges protein identification by tandem HRMS with limited MS/MS duty cycle. Here, we supplemented ultrasensitive CE-nanoESI-HRMS with reversed-phase (RP) fractionation to enhance identifications from protein digest amounts that approximate to a few mammalian neurons. An 1 to 20 μg neuronal protein digest was fractionated on a RP column (ZipTip), and 1 ng to 500 pg of peptides were analyzed by a custom-built CE-HRMS system. Compared with the control (no fractionation), RP fractionation improved CE separation (theoretical plates 274,000 versus 412,000 maximum, resp.), which enhanced detection sensitivity (2.5-fold higher signal-to-noise ratio), minimized co-isolation spectral interferences during MS/MS, and increased the temporal rate of peptide identification by up to 57%. From 1 ng of protein digest (<5 neurons), CE with RP fractionation identified 737 protein groups (1,753 peptides), or 480 protein groups ( 1,650 peptides) on average per analysis. The approach was scalable to 500 pg of protein digest ( a single neuron), identifying 225 protein groups (623 peptides) in technical triplicates, or 141 protein groups on average per analysis. Among identified proteins, 101 proteins were products of genes that are known to be transcriptionally active in single neurons during early development of the brain, including those involved in synaptic transmission and plasticity and cytoskeletal organization. [Figure not available: see fulltext.

Enhanced Peptide Detection Toward Single-Neuron Proteomics by Reversed-Phase Fractionation Capillary Electrophoresis Mass Spectrometry

NASA Astrophysics Data System (ADS)

Choi, Sam B.; Lombard-Banek, Camille; Muñoz-LLancao, Pablo; Manzini, M. Chiara; Nemes, Peter

2017-11-01

The ability to detect peptides and proteins in single cells is vital for understanding cell heterogeneity in the nervous system. Capillary electrophoresis (CE) nanoelectrospray ionization (nanoESI) provides high-resolution mass spectrometry (HRMS) with trace-level sensitivity, but compressed separation during CE challenges protein identification by tandem HRMS with limited MS/MS duty cycle. Here, we supplemented ultrasensitive CE-nanoESI-HRMS with reversed-phase (RP) fractionation to enhance identifications from protein digest amounts that approximate to a few mammalian neurons. An 1 to 20 μg neuronal protein digest was fractionated on a RP column (ZipTip), and 1 ng to 500 pg of peptides were analyzed by a custom-built CE-HRMS system. Compared with the control (no fractionation), RP fractionation improved CE separation (theoretical plates 274,000 versus 412,000 maximum, resp.), which enhanced detection sensitivity (2.5-fold higher signal-to-noise ratio), minimized co-isolation spectral interferences during MS/MS, and increased the temporal rate of peptide identification by up to 57%. From 1 ng of protein digest (<5 neurons), CE with RP fractionation identified 737 protein groups (1,753 peptides), or 480 protein groups ( 1,650 peptides) on average per analysis. The approach was scalable to 500 pg of protein digest ( a single neuron), identifying 225 protein groups (623 peptides) in technical triplicates, or 141 protein groups on average per analysis. Among identified proteins, 101 proteins were products of genes that are known to be transcriptionally active in single neurons during early development of the brain, including those involved in synaptic transmission and plasticity and cytoskeletal organization. [Figure not available: see fulltext.

Autonomic control network active in Aplysia during locomotion includes neurons that express splice variants of R15-neuropeptides.

PubMed

Romanova, Elena V; McKay, Natasha; Weiss, Klaudiusz R; Sweedler, Jonathan V; Koester, John

2007-01-01

Splice-variant products of the R15 neuropeptide gene are differentially expressed within the CNS of Aplysia. The goal of this study was to test whether the neurons in the abdominal ganglion that express the peptides encoded by this gene are part of a common circuit. Expression of R15 peptides had been demonstrated previously in neuron R15. Using a combination of immunocytochemical and analytical methods, this study demonstrated that R15 peptides are also expressed in heart exciter neuron RB(HE), the two L9(G) gill motoneurons, and L40--a newly identified interneuron. Mass spectrometric profiling of individual neurons that exhibit R15 peptide-like immunoreactivity confirmed the mutually exclusive expression of two splice-variant forms of R15 peptides in different neurons. The L9(G) cells were found to co-express pedal peptide in addition to the R15 peptides. The R15 peptide-expressing neurons examined here were shown to be part of an autonomic control circuit that is active during fictive locomotion. Activity in this circuit contributes to implementing a central command that may help to coordinate autonomic activity with escape locomotion. Chronic extracellular nerve recording was used to determine the activity patterns of a subset of neurons of this circuit in vivo. These results demonstrate the potential utility of using shared patterns of neuropeptide expression as a guide for neural circuit identification.

Preserved Proteins from Extinct Bison latifrons Identified by Tandem Mass Spectrometry; Hydroxylysine Glycosides are a Common Feature of Ancient Collagen*

PubMed Central

Hill, Ryan C.; Wither, Matthew J.; Nemkov, Travis; Barrett, Alexander; D'Alessandro, Angelo; Dzieciatkowska, Monika; Hansen, Kirk C.

2015-01-01

Bone samples from several vertebrates were collected from the Ziegler Reservoir fossil site, in Snowmass Village, Colorado, and processed for proteomics analysis. The specimens come from Pleistocene megafauna Bison latifrons, dating back ∼120,000 years. Proteomics analysis using a simplified sample preparation procedure and tandem mass spectrometry (MS/MS) was applied to obtain protein identifications. Several bioinformatics resources were used to obtain peptide identifications based on sequence homology to extant species with annotated genomes. With the exception of soil sample controls, all samples resulted in confident peptide identifications that mapped to type I collagen. In addition, we analyzed a specimen from the extinct B. latifrons that yielded peptide identifications mapping to over 33 bovine proteins. Our analysis resulted in extensive fibrillar collagen sequence coverage, including the identification of posttranslational modifications. Hydroxylysine glucosylgalactosylation, a modification thought to be involved in collagen fiber formation and bone mineralization, was identified for the first time in an ancient protein dataset. Meta-analysis of data from other studies indicates that this modification may be common in well-preserved prehistoric samples. Additional peptide sequences from extracellular matrix (ECM) and non-ECM proteins have also been identified for the first time in ancient tissue samples. These data provide a framework for analyzing ancient protein signatures in well-preserved fossil specimens, while also contributing novel insights into the molecular basis of organic matter preservation. As such, this analysis has unearthed common posttranslational modifications of collagen that may assist in its preservation over time. The data are available via ProteomeXchange with identifier PXD001827. PMID:25948757

Why are they missing? : Bioinformatics characterization of missing human proteins.

PubMed

Elguoshy, Amr; Magdeldin, Sameh; Xu, Bo; Hirao, Yoshitoshi; Zhang, Ying; Kinoshita, Naohiko; Takisawa, Yusuke; Nameta, Masaaki; Yamamoto, Keiko; El-Refy, Ali; El-Fiky, Fawzy; Yamamoto, Tadashi

2016-10-21

NeXtProt is a web-based protein knowledge platform that supports research on human proteins. NeXtProt (release 2015-04-28) lists 20,060 proteins, among them, 3373 canonical proteins (16.8%) lack credible experimental evidence at protein level (PE2:PE5). Therefore, they are considered as "missing proteins". A comprehensive bioinformatic workflow has been proposed to analyze these "missing" proteins. The aims of current study were to analyze physicochemical properties, existence and distribution of the tryptic cleavage sites, and to pinpoint the signature peptides of the missing proteins. Our findings showed that 23.7% of missing proteins were hydrophobic proteins possessing transmembrane domains (TMD). Also, forty missing entries generate tryptic peptides were either out of mass detection range (>30aa) or mapped to different proteins (<9aa). Additionally, 21% of missing entries didn't generate any unique tryptic peptides. In silico endopeptidase combination strategy increased the possibility of missing proteins identification. Coherently, using both mature protein database and signal peptidome database could be a promising option to identify some missing proteins by targeting their unique N-terminal tryptic peptide from mature protein database and or C-terminus tryptic peptide from signal peptidome database. In conclusion, Identification of missing protein requires additional consideration during sample preparation, extraction, digestion and data analysis to increase its incidence of identification. Copyright © 2016. Published by Elsevier B.V.

Enhancing bioactive peptide release and identification using targeted enzymatic hydrolysis of milk proteins.

PubMed

Nongonierma, Alice B; FitzGerald, Richard J

2018-06-01

Milk proteins have been extensively studied for their ability to yield a range of bioactive peptides following enzymatic hydrolysis/digestion. However, many hurdles still exist regarding the widespread utilization of milk protein-derived bioactive peptides as health enhancing agents for humans. These mostly arise from the fact that most milk protein-derived bioactive peptides are not highly potent. In addition, they may be degraded during gastrointestinal digestion and/or have a low intestinal permeability. The targeted release of bioactive peptides during the enzymatic hydrolysis of milk proteins may allow the generation of particularly potent bioactive hydrolysates and peptides. Therefore, the development of milk protein hydrolysates capable of improving human health requires, in the first instance, optimized targeted release of specific bioactive peptides. The targeted hydrolysis of milk proteins has been aided by a range of in silico tools. These include peptide cutters and predictive modeling linking bioactivity to peptide structure [i.e., molecular docking, quantitative structure activity relationship (QSAR)], or hydrolysis parameters [design of experiments (DOE)]. Different targeted enzymatic release strategies employed during the generation of milk protein hydrolysates are reviewed herein and their limitations are outlined. In addition, specific examples are provided to demonstrate how in silico tools may help in the identification and discovery of potent milk protein-derived peptides. It is anticipated that the development of novel strategies employing a range of in silico tools may help in the generation of milk protein hydrolysates containing potent and bioavailable peptides, which in turn may be used to validate their health promoting effects in humans. Graphical abstract The targeted enzymatic hydrolysis of milk proteins may allow the generation of highly potent and bioavailable bioactive peptides.

Definition and characterization of a "trypsinosome" from specific peptide characteristics by nano-HPLC-MS/MS and in silico analysis of complex protein mixtures.

PubMed

Le Bihan, Thierry; Robinson, Mark D; Stewart, Ian I; Figeys, Daniel

2004-01-01

Although HPLC-ESI-MS/MS is rapidly becoming an indispensable tool for the analysis of peptides in complex mixtures, the sequence coverage it affords is often quite poor. Low protein expression resulting in peptide signal intensities that fall below the limit of detection of the MS system in combination with differences in peptide ionization efficiency plays a significant role in this. A second important factor stems from differences in physicochemical properties of each peptide and how these properties relate to chromatographic retention and ultimate detection. To identify and understand those properties, we compared data from experimentally identified peptides with data from peptides predicted by in silico digest of all corresponding proteins in the experimental set. Three different complex protein mixtures extracted were used to define a training set to evaluate the amino acid retention coefficients based on linear regression analysis. The retention coefficients were also compared with other previous hydrophobic and retention scale. From this, we have constructed an empirical model that can be readily used to predict peptides that are likely to be observed on our HPLC-ESI-MS/MS system based on their physicochemical properties. Finally, we demonstrated that in silico prediction of peptides and their retention coefficients can be used to generate an inclusion list for a targeted mass spectrometric identification of low abundance proteins in complex protein samples. This approach is based on experimentally derived data to calibrate the method and therefore may theoretically be applied to any HPLC-MS/MS system on which data are being generated.

Gas-Phase Enrichment of Multiply Charged Peptide Ions by Differential Ion Mobility Extend the Comprehensiveness of SUMO Proteome Analyses

NASA Astrophysics Data System (ADS)

Pfammatter, Sibylle; Bonneil, Eric; McManus, Francis P.; Thibault, Pierre

2018-04-01

The small ubiquitin-like modifier (SUMO) is a member of the family of ubiquitin-like modifiers (UBLs) and is involved in important cellular processes, including DNA damage response, meiosis and cellular trafficking. The large-scale identification of SUMO peptides in a site-specific manner is challenging not only because of the low abundance and dynamic nature of this modification, but also due to the branched structure of the corresponding peptides that further complicate their identification using conventional search engines. Here, we exploited the unusual structure of SUMO peptides to facilitate their separation by high-field asymmetric waveform ion mobility spectrometry (FAIMS) and increase the coverage of SUMO proteome analysis. Upon trypsin digestion, branched peptides contain a SUMO remnant side chain and predominantly form triply protonated ions that facilitate their gas-phase separation using FAIMS. We evaluated the mobility characteristics of synthetic SUMO peptides and further demonstrated the application of FAIMS to profile the changes in protein SUMOylation of HEK293 cells following heat shock, a condition known to affect this modification. FAIMS typically provided a 10-fold improvement of detection limit of SUMO peptides, and enabled a 36% increase in SUMO proteome coverage compared to the same LC-MS/MS analyses performed without FAIMS. [Figure not available: see fulltext.

Simultaneous Glycan-Peptide Characterization Using Hydrophilic Interaction Chromatography and Parallel Fragmentation by CID, Higher Energy Collisional Dissociation, and Electron Transfer Dissociation MS Applied to the N-Linked Glycoproteome of Campylobacter jejuni*

PubMed Central

Scott, Nichollas E.; Parker, Benjamin L.; Connolly, Angela M.; Paulech, Jana; Edwards, Alistair V. G.; Crossett, Ben; Falconer, Linda; Kolarich, Daniel; Djordjevic, Steven P.; Højrup, Peter; Packer, Nicolle H.; Larsen, Martin R.; Cordwell, Stuart J.

2011-01-01

Campylobacter jejuni is a gastrointestinal pathogen that is able to modify membrane and periplasmic proteins by the N-linked addition of a 7-residue glycan at the strict attachment motif (D/E)XNX(S/T). Strategies for a comprehensive analysis of the targets of glycosylation, however, are hampered by the resistance of the glycan-peptide bond to enzymatic digestion or β-elimination and have previously concentrated on soluble glycoproteins compatible with lectin affinity and gel-based approaches. We developed strategies for enriching C. jejuni HB93-13 glycopeptides using zwitterionic hydrophilic interaction chromatography and examined novel fragmentation, including collision-induced dissociation (CID) and higher energy collisional (C-trap) dissociation (HCD) as well as CID/electron transfer dissociation (ETD) mass spectrometry. CID/HCD enabled the identification of glycan structure and peptide backbone, allowing glycopeptide identification, whereas CID/ETD enabled the elucidation of glycosylation sites by maintaining the glycan-peptide linkage. A total of 130 glycopeptides, representing 75 glycosylation sites, were identified from LC-MS/MS using zwitterionic hydrophilic interaction chromatography coupled to CID/HCD and CID/ETD. CID/HCD provided the majority of the identifications (73 sites) compared with ETD (26 sites). We also examined soluble glycoproteins by soybean agglutinin affinity and two-dimensional electrophoresis and identified a further six glycosylation sites. This study more than doubles the number of confirmed N-linked glycosylation sites in C. jejuni and is the first to utilize HCD fragmentation for glycopeptide identification with intact glycan. We also show that hydrophobic integral membrane proteins are significant targets of glycosylation in this organism. Our data demonstrate that peptide-centric approaches coupled to novel mass spectrometric fragmentation techniques may be suitable for application to eukaryotic glycoproteins for simultaneous elucidation of glycan structures and peptide sequence. PMID:20360033

Simultaneous glycan-peptide characterization using hydrophilic interaction chromatography and parallel fragmentation by CID, higher energy collisional dissociation, and electron transfer dissociation MS applied to the N-linked glycoproteome of Campylobacter jejuni.

PubMed

Scott, Nichollas E; Parker, Benjamin L; Connolly, Angela M; Paulech, Jana; Edwards, Alistair V G; Crossett, Ben; Falconer, Linda; Kolarich, Daniel; Djordjevic, Steven P; Højrup, Peter; Packer, Nicolle H; Larsen, Martin R; Cordwell, Stuart J

2011-02-01

Campylobacter jejuni is a gastrointestinal pathogen that is able to modify membrane and periplasmic proteins by the N-linked addition of a 7-residue glycan at the strict attachment motif (D/E)XNX(S/T). Strategies for a comprehensive analysis of the targets of glycosylation, however, are hampered by the resistance of the glycan-peptide bond to enzymatic digestion or β-elimination and have previously concentrated on soluble glycoproteins compatible with lectin affinity and gel-based approaches. We developed strategies for enriching C. jejuni HB93-13 glycopeptides using zwitterionic hydrophilic interaction chromatography and examined novel fragmentation, including collision-induced dissociation (CID) and higher energy collisional (C-trap) dissociation (HCD) as well as CID/electron transfer dissociation (ETD) mass spectrometry. CID/HCD enabled the identification of glycan structure and peptide backbone, allowing glycopeptide identification, whereas CID/ETD enabled the elucidation of glycosylation sites by maintaining the glycan-peptide linkage. A total of 130 glycopeptides, representing 75 glycosylation sites, were identified from LC-MS/MS using zwitterionic hydrophilic interaction chromatography coupled to CID/HCD and CID/ETD. CID/HCD provided the majority of the identifications (73 sites) compared with ETD (26 sites). We also examined soluble glycoproteins by soybean agglutinin affinity and two-dimensional electrophoresis and identified a further six glycosylation sites. This study more than doubles the number of confirmed N-linked glycosylation sites in C. jejuni and is the first to utilize HCD fragmentation for glycopeptide identification with intact glycan. We also show that hydrophobic integral membrane proteins are significant targets of glycosylation in this organism. Our data demonstrate that peptide-centric approaches coupled to novel mass spectrometric fragmentation techniques may be suitable for application to eukaryotic glycoproteins for simultaneous elucidation of glycan structures and peptide sequence.

Multiple-approaches to the identification and quantification of cytochromes P450 in human liver tissue by mass spectrometry.

PubMed

Seibert, Cathrin; Davidson, Brian R; Fuller, Barry J; Patterson, Laurence H; Griffiths, William J; Wang, Yuqin

2009-04-01

Here we report the identification and approximate quantification of cytochrome P450 (CYP) proteins in human liver microsomes as determined by nano-LC-MS/MS with application of the exponentially modified protein abundance index (emPAI) algorithm during database searching. Protocols based on 1D-gel protein separation and 2D-LC peptide separation gave comparable results. In total, 18 CYP isoforms were unambiguously identified based on unique peptide matches. Further, we have determined the absolute quantity of two CYP enzymes (2E1 and 1A2) in human liver microsomes using stable-isotope dilution mass spectrometry, where microsomal proteins were separated by 1D-gel electrophoresis, digested with trypsin in the presence of either a CYP2E1- or 1A2-specific stable-isotope labeled tryptic peptide and analyzed by LC-MS/MS. Using multiple reaction monitoring (MRM) for the isotope-labeled tryptic peptides and their natural unlabeled analogues quantification could be performed over the range of 0.1-1.5 pmol on column. Liver microsomes from four individuals were analyzed for CYP2E1 giving values of 88-200 pmol/mg microsomal protein. The CYP1A2 content of microsomes from a further three individuals ranged from 165 to 263 pmol/mg microsomal protein. Although, in this proof-of-concept study for CYP quantification, the two CYP isoforms were quantified from different samples, there are no practical reasons to prevent multiplexing the method to allow the quantification of multiple CYP isoforms in a single sample.

Multiple-approaches to the identification and quantification of cytochromes P450 in human liver tissue by mass spectrometry

PubMed Central

Seibert, Cathrin; Davidson, Brian R.; Fuller, Barry J.; Patterson, Laurence H.; Griffiths, William J.; Wang, Yuqin

2009-01-01

Here we report the identification and approximate quantification of cytochrome P450 (CYP) proteins in human liver microsomes as determined by nano-LC-MS/MS with application of the exponentially modified protein abundance index (emPAI) algorithm during database searching. Protocols based on 1D-gel protein separation and 2D-LC peptide separation gave comparable results. In total 18 CYP isoforms were unambiguously identified based on unique peptide matches. Further, we have determined the absolute quantity of two CYP enzymes (2E1 and 1A2) in human liver microsomes using stable-isotope dilution mass spectrometry, where microsomal proteins were separated by 1D-gel electrophoresis, digested with trypsin in the presence of either a CYP2E1- or 1A2-specific stable-isotope labelled tryptic peptide and analysed by LC-MS/MS. Using multiple reaction monitoring (MRM) for the isotope-labelled tryptic peptides and their natural unlabelled analogues quantification could be performed over the range of 0.1 – 1.5 pmol on column. Liver microsomes from four individuals were analysed for CYP2E1 giving values of 88 - 200 pmol/mg microsomal protein. The CYP1A2 content of microsomes from a further three individuals ranged from 165 – 263 pmol/mg microsomal protein. Although, in this proof-of-concept study for CYP quantification, the two CYP-isoforms were quantified from different samples, there are no practical reasons to prevent multiplexing the method to allow the quantification of multiple CYP-isoforms in a single sample. PMID:19714871

A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and identification-decoupled strategy.

PubMed

Wang, Hongbin; Zhang, Yongqian; Gui, Shuqi; Zhang, Yong; Lu, Fuping; Deng, Yulin

2017-08-15

Comparisons across large numbers of samples are frequently necessary in quantitative proteomics. Many quantitative methods used in proteomics are based on stable isotope labeling, but most of these are only useful for comparing two samples. For up to eight samples, the iTRAQ labeling technique can be used. For greater numbers of samples, the label-free method has been used, but this method was criticized for low reproducibility and accuracy. An ingenious strategy has been introduced, comparing each sample against a 18 O-labeled reference sample that was created by pooling equal amounts of all samples. However, it is necessary to use proportion-known protein mixtures to investigate and evaluate this new strategy. Another problem for comparative proteomics of multiple samples is the poor coincidence and reproducibility in protein identification results across samples. In present study, a method combining 18 O-reference strategy and a quantitation and identification-decoupled strategy was investigated with proportion-known protein mixtures. The results obviously demonstrated that the 18 O-reference strategy had greater accuracy and reliability than other previously used comparison methods based on transferring comparison or label-free strategies. By the decoupling strategy, the quantification data acquired by LC-MS and the identification data acquired by LC-MS/MS are matched and correlated to identify differential expressed proteins, according to retention time and accurate mass. This strategy made protein identification possible for all samples using a single pooled sample, and therefore gave a good reproducibility in protein identification across multiple samples, and allowed for optimizing peptide identification separately so as to identify more proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

NOVEL CONTINUOUS PH/SALT GRADIENT AND PEPTIDE SCORE FOR STRONG CATION EXCHANGE CHROMATOGRAPHY IN 2D-NANO-LC/MSMS PEPTIDE IDENTIFICATION FOR PROTEOMICS

EPA Science Inventory

Tryptic digests of human serum albumin (HSA) and human lung epithelial cell lysates were used as test samples in a novel proteomics study. Peptides were separated and analyzed using 2D-nano-LC/MSMS with strong cation exchange (SCX) and reverse phase (RP) chromatography and contin...

An FPGA Implementation to Detect Selective Cationic Antibacterial Peptides

PubMed Central

Polanco González, Carlos; Nuño Maganda, Marco Aurelio; Arias-Estrada, Miguel; del Rio, Gabriel

2011-01-01

Exhaustive prediction of physicochemical properties of peptide sequences is used in different areas of biological research. One example is the identification of selective cationic antibacterial peptides (SCAPs), which may be used in the treatment of different diseases. Due to the discrete nature of peptide sequences, the physicochemical properties calculation is considered a high-performance computing problem. A competitive solution for this class of problems is to embed algorithms into dedicated hardware. In the present work we present the adaptation, design and implementation of an algorithm for SCAPs prediction into a Field Programmable Gate Array (FPGA) platform. Four physicochemical properties codes useful in the identification of peptide sequences with potential selective antibacterial activity were implemented into an FPGA board. The speed-up gained in a single-copy implementation was up to 108 times compared with a single Intel processor cycle for cycle. The inherent scalability of our design allows for replication of this code into multiple FPGA cards and consequently improvements in speed are possible. Our results show the first embedded SCAPs prediction solution described and constitutes the grounds to efficiently perform the exhaustive analysis of the sequence-physicochemical properties relationship of peptides. PMID:21738652

Comparative Analyses of Data Independent Acquisition Mass Spectrometric Approaches: DIA, WiSIM‐DIA, and Untargeted DIA

PubMed Central

Ho, Jenny T. C.; Smit, August B.; Li, Ka Wan

2018-01-01

Abstract Data‐independent acquisition (DIA) is an emerging technology for quantitative proteomics. Current DIA focusses on the identification and quantitation of fragment ions that are generated from multiple peptides contained in the same selection window of several to tens of m/z. An alternative approach is WiSIM‐DIA, which combines conventional DIA with wide‐SIM (wide selected‐ion monitoring) windows to partition the precursor m/z space to produce high‐quality precursor ion chromatograms. However, WiSIM‐DIA has been underexplored; it remains unclear if it is a viable alternative to DIA. We demonstrate that WiSIM‐DIA quantified more than 24 000 unique peptides over five orders of magnitude in a single 2 h analysis of a neuronal synapse‐enriched fraction, compared to 31 000 in DIA. There is a strong correlation between abundance values of peptides quantified in both the DIA and WiSIM‐DIA datasets. Interestingly, the S/N ratio of these peptides is not correlated. We further show that peptide identification directly from DIA spectra identified >2000 proteins, which included unique peptides not found in spectral libraries generated by DDA. PMID:29134766

Identification of tissue-specific targeting peptide

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Lee, Nam Kyung; Kang, Sang-Kee; Choi, Seung-Hoon; Kim, Daejin; Park, Kisoo; Choi, Kihang; Choi, Yun-Jaie; Jung, Dong Hyun

2012-11-01

Using phage display technique, we identified tissue-targeting peptide sets that recognize specific tissues (bone-marrow dendritic cell, kidney, liver, lung, spleen and visceral adipose tissue). In order to rapidly evaluate tissue-specific targeting peptides, we performed machine learning studies for predicting the tissue-specific targeting activity of peptides on the basis of peptide sequence information using four machine learning models and isolated the groups of peptides capable of mediating selective targeting to specific tissues. As a representative liver-specific targeting sequence, the peptide "DKNLQLH" was selected by the sequence similarity analysis. This peptide has a high degree of homology with protein ligands which can interact with corresponding membrane counterparts. We anticipate that our models will be applicable to the prediction of tissue-specific targeting peptides which can recognize the endothelial markers of target tissues.

Computational tools for exploring sequence databases as a resource for antimicrobial peptides.

PubMed

Porto, W F; Pires, A S; Franco, O L

Data mining has been recognized by many researchers as a hot topic in different areas. In the post-genomic era, the growing number of sequences deposited in databases has been the reason why these databases have become a resource for novel biological information. In recent years, the identification of antimicrobial peptides (AMPs) in databases has gained attention. The identification of unannotated AMPs has shed some light on the distribution and evolution of AMPs and, in some cases, indicated suitable candidates for developing novel antimicrobial agents. The data mining process has been performed mainly by local alignments and/or regular expressions. Nevertheless, for the identification of distant homologous sequences, other techniques such as antimicrobial activity prediction and molecular modelling are required. In this context, this review addresses the tools and techniques, and also their limitations, for mining AMPs from databases. These methods could be helpful not only for the development of novel AMPs, but also for other kinds of proteins, at a higher level of structural genomics. Moreover, solving the problem of unannotated proteins could bring immeasurable benefits to society, especially in the case of AMPs, which could be helpful for developing novel antimicrobial agents and combating resistant bacteria. Copyright © 2017 Elsevier Inc. All rights reserved.

Single-step inline hydroxyapatite enrichment facilitates identification and quantitation of phosphopeptides from mass-limited proteomes with MudPIT

PubMed Central

Fonslow, Bryan R.; Niessen, Sherry M.; Singh, Meha; Wong, Catherine C.; Xu, Tao; Carvalho, Paulo C.; Choi, Jeong; Park, Sung Kyu; Yates, John R.

2012-01-01

Herein we report the characterization and optimization of single-step inline enrichment of phosphopeptides directly from small amounts of whole cell and tissue lysates (100 – 500 μg) using a hydroxyapatite (HAP) microcolumn and Multidimensional Protein Identification Technology (MudPIT). In comparison to a triplicate HILIC-IMAC phosphopeptide enrichment study, ~80% of the phosphopeptides identified using HAP-MudPIT were unique. Similarly, analysis of the consensus phosphorylation motifs between the two enrichment methods illustrates the complementarity of calcium-and iron-based enrichment methods and the higher sensitivity and selectivity of HAP-MudPIT for acidic motifs. We demonstrate how the identification of more multiply phosphorylated peptides from HAP-MudPIT can be used to quantify phosphorylation cooperativity. Through optimization of HAP-MudPIT on a whole cell lysate we routinely achieved identification and quantification of ca. 1000 phosphopeptides from a ~1 hr enrichment and 12 hr MudPIT analysis on small quantities of material. Finally, we applied this optimized method to identify phosphorylation sites from a mass-limited mouse brain region, the amygdala (200 – 500 μg), identifying up to 4000 phosphopeptides per run. PMID:22509746

Use of specific peptide biomarkers for quantitative confirmation of hidden allergenic peanut proteins Ara h 2 and Ara h 3/4 for food control by liquid chromatography-tandem mass spectrometry.

PubMed

Careri, M; Costa, A; Elviri, L; Lagos, J-B; Mangia, A; Terenghi, M; Cereti, A; Garoffo, L Perono

2007-11-01

A liquid chromatography-electrospray-tandem mass spectrometry (LC-ESI-MS-MS) method based on the detection of biomarker peptides from allergenic proteins was devised for confirming and quantifying peanut allergens in foods. Peptides obtained from tryptic digestion of Ara h 2 and Ara h 3/4 proteins were identified and characterized by LC-MS and LC-MS-MS with a quadrupole-time of flight mass analyzer. Four peptides were chosen and investigated as biomarkers taking into account their selectivity, the absence of missed cleavages, the uniform distribution in the Ara h 2 and Ara h 3/4 protein isoforms together with their spectral features under ESI-MS-MS conditions, and good repeatability of LC retention time. Because of the different expression levels, the selection of two different allergenic proteins was proved to be useful in the identification and univocal confirmation of the presence of peanuts in foodstuffs. Using rice crisp and chocolate-based snacks as model food matrix, an LC-MS-MS method with triple quadrupole mass analyzer allowed good detection limits to be obtained for Ara h 2 (5 microg protein g(-1) matrix) and Ara h 3/4 (1 microg protein g(-1) matrix). Linearity of the method was established in the 10-200 microg g(-1) range of peanut proteins in the food matrix investigated. Method selectivity was demonstrated by analyzing tree nuts (almonds, pecan nuts, hazelnuts, walnuts) and food ingredients such as milk, soy beans, chocolate, cornflakes, and rice crisp.

Frog secretions and hunting magic in the upper Amazon: identification of a peptide that interacts with an adenosine receptor.

PubMed Central

Daly, J W; Caceres, J; Moni, R W; Gusovsky, F; Moos, M; Seamon, K B; Milton, K; Myers, C W

1992-01-01

A frog used for "hunting magic" by several groups of Panoan-speaking Indians in the borderline between Brazil and Peru is identified as Phyllomedusa bicolor. This frog's skin secretion, which the Indians introduce into the body through fresh burns, is rich in peptides. These include vasoactive peptides, opioid peptides, and a peptide that we have named adenoregulin, with the sequence GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV as determined from mass spectrometry and Edman degradation. The natural peptide may contain a D amino acid residue, since it is not identical in chromatographic properties to the synthetic peptide. Adenoregulin enhances binding of agonists to A1 adenosine receptors; it is accompanied in the skin secretion by peptides that inhibit binding. The vasoactive peptide sauvagine, the opioid peptides, and adenoregulin and related peptides affect behavior in mice and presumably contribute to the behavioral sequelae observed in humans. Images PMID:1438301

Frog secretions and hunting magic in the upper Amazon: identification of a peptide that interacts with an adenosine receptor.

PubMed

Daly, J W; Caceres, J; Moni, R W; Gusovsky, F; Moos, M; Seamon, K B; Milton, K; Myers, C W

1992-11-15

A frog used for "hunting magic" by several groups of Panoan-speaking Indians in the borderline between Brazil and Peru is identified as Phyllomedusa bicolor. This frog's skin secretion, which the Indians introduce into the body through fresh burns, is rich in peptides. These include vasoactive peptides, opioid peptides, and a peptide that we have named adenoregulin, with the sequence GLWSKIKEVGKEAAKAAAKAAGKAALGAVSEAV as determined from mass spectrometry and Edman degradation. The natural peptide may contain a D amino acid residue, since it is not identical in chromatographic properties to the synthetic peptide. Adenoregulin enhances binding of agonists to A1 adenosine receptors; it is accompanied in the skin secretion by peptides that inhibit binding. The vasoactive peptide sauvagine, the opioid peptides, and adenoregulin and related peptides affect behavior in mice and presumably contribute to the behavioral sequelae observed in humans.

Identification of the minimum peptide from mouse myostatin prodomain for human myostatin inhibition.

PubMed

Takayama, Kentaro; Noguchi, Yuri; Aoki, Shin; Takayama, Shota; Yoshida, Momoko; Asari, Tomo; Yakushiji, Fumika; Nishimatsu, Shin-ichiro; Ohsawa, Yutaka; Itoh, Fumiko; Negishi, Yoichi; Sunada, Yoshihide; Hayashi, Yoshio

2015-02-12

Myostatin, an endogenous negative regulator of skeletal muscle mass, is a therapeutic target for muscle atrophic disorders. Here, we identified minimum peptides 2 and 7 to effectively inhibit myostatin activity, which consist of 24 and 23 amino acids, respectively, derived from mouse myostatin prodomain. These peptides, which had the propensity to form α-helix structure, interacted to myostatin with KD values of 30-36 nM. Moreover, peptide 2 significantly increased muscle mass in Duchenne muscular dystrophy model mice.

Comparability analysis of protein therapeutics by bottom-up LC-MS with stable isotope-tagged reference standards

PubMed Central

Manuilov, Anton V; Radziejewski, Czeslaw H

2011-01-01

Comparability studies lie at the heart of assessments that evaluate differences amongst manufacturing processes and stability studies of protein therapeutics. Low resolution chromatographic and electrophoretic methods facilitate quantitation, but do not always yield detailed insight into the effect of the manufacturing change or environmental stress. Conversely, mass spectrometry (MS) can provide high resolution information on the molecule, but conventional methods are not very quantitative. This gap can be reconciled by use of a stable isotope-tagged reference standard (SITRS), a version of the analyte protein that is uniformly labeled with 13C6-arginine and 13C6-lysine. The SITRS serves as an internal control that is trypsin-digested and analyzed by liquid chromatography (LC)-MS with the analyte sample. The ratio of the ion intensities of each unlabeled and labeled peptide pair is then compared to that of other sample(s). A comparison of these ratios provides a readily accessible way to spot even minute differences among samples. In a study of a monoclonal antibody (mAb) spiked with varying amounts of the same antibody bearing point mutations, peptides containing the mutations were readily identified and quantified at concentrations as low as 2% relative to unmodified peptides. The method was robust, reproducible and produced a linear response for every peptide that was monitored. The method was also successfully used to distinguish between two batches of a mAb that were produced in two different cell lines while two batches produced from the same cell line were found to be highly comparable. Finally, the use of the SITRS method in the comparison of two stressed mAb samples enabled the identification of sites susceptible to deamidation and oxidation, as well as their quantitation. The experimental results indicate that use of a SITRS in a peptide mapping experiment with MS detection enables sensitive and quantitative comparability studies of proteins at high resolution. PMID:21654206

Comparability analysis of protein therapeutics by bottom-up LC-MS with stable isotope-tagged reference standards.

PubMed

Manuilov, Anton V; Radziejewski, Czeslaw H; Lee, David H

2011-01-01

Comparability studies lie at the heart of assessments that evaluate differences amongst manufacturing processes and stability studies of protein therapeutics. Low resolution chromatographic and electrophoretic methods facilitate quantitation, but do not always yield detailed insight into the effect of the manufacturing change or environmental stress. Conversely, mass spectrometry (MS) can provide high resolution information on the molecule, but conventional methods are not very quantitative. This gap can be reconciled by use of a stable isotope-tagged reference standard (SITRS), a version of the analyte protein that is uniformly labeled (13)C6-arginine and (13)C6-lysine. The SITRS serves as an internal control that is trypsin-digested and analyzed by liquid chromatography (LC)-MS with the analyte sample. The ratio of the ion intensities of each unlabeled and labeled peptide pair is then compared to that of other sample(s). A comparison of these ratios provides a readily accessible way to spot even minute differences among samples. In a study of a monoclonal antibody (mAb) spiked with varying amounts of the same antibody bearing point mutations, peptides containing the mutations were readily identified and quantified at concentrations as low as 2% relative to unmodified peptides. The method is robust, reproducible and produced a linear response for every peptide that was monitored. The method was also successfully used to distinguish between two batches of a mAb that were produced in two different cell lines while two batches produced from the same cell line were found to be highly comparable. Finally, the use of the SITRS method in the comparison of two stressed mAb samples enabled the identification of sites susceptible to deamidation and oxidation, as well as their quantitation. The experimental results indicate that use of a SITRS in a peptide mapping experiment with MS detection enables sensitive and quantitative comparability studies of proteins at high resolution.

[Identification of mouse brain neuropeptides by high throughput mass spectrometry].

PubMed

Shao, Xianfeng; Ma, Min; Chen, Ruibing; Jia, Chenxi

2018-04-25

Neuropeptides play an important role in the physiological functions of the human body. The physiological activities such as pain, sleep, mood, learning and memory are affected by neuropeptides. Neuropeptides mainly exist in the nerve tissue of the body, and a small amount of them are distributed in body fluid and organs. At present, analysis of large-scale identification of neuropeptides in whole brain tissue is still challenging. Therefore, high-throughput detection of these neuropeptides is greatly significant to understand the composition and function of neuropeptides. In this study, 1 830 endogenous peptides and 99 novel putative neuropeptides were identified by extraction of endogenous peptides from whole brain tissue of mice by liquid phase tandem mass spectrometry (LC-MS / MS). The identification of these endogenous peptides provides not only a reference value in the treatment and mechanism studies of diseases and the development of drugs, but also the basis for the study of a new neuropeptides and their functions.

POPISK: T-cell reactivity prediction using support vector machines and string kernels

PubMed Central

2011-01-01

Background Accurate prediction of peptide immunogenicity and characterization of relation between peptide sequences and peptide immunogenicity will be greatly helpful for vaccine designs and understanding of the immune system. In contrast to the prediction of antigen processing and presentation pathway, the prediction of subsequent T-cell reactivity is a much harder topic. Previous studies of identifying T-cell receptor (TCR) recognition positions were based on small-scale analyses using only a few peptides and concluded different recognition positions such as positions 4, 6 and 8 of peptides with length 9. Large-scale analyses are necessary to better characterize the effect of peptide sequence variations on T-cell reactivity and design predictors of a peptide's T-cell reactivity (and thus immunogenicity). The identification and characterization of important positions influencing T-cell reactivity will provide insights into the underlying mechanism of immunogenicity. Results This work establishes a large dataset by collecting immunogenicity data from three major immunology databases. In order to consider the effect of MHC restriction, peptides are classified by their associated MHC alleles. Subsequently, a computational method (named POPISK) using support vector machine with a weighted degree string kernel is proposed to predict T-cell reactivity and identify important recognition positions. POPISK yields a mean 10-fold cross-validation accuracy of 68% in predicting T-cell reactivity of HLA-A2-binding peptides. POPISK is capable of predicting immunogenicity with scores that can also correctly predict the change in T-cell reactivity related to point mutations in epitopes reported in previous studies using crystal structures. Thorough analyses of the prediction results identify the important positions 4, 6, 8 and 9, and yield insights into the molecular basis for TCR recognition. Finally, we relate this finding to physicochemical properties and structural features of the MHC-peptide-TCR interaction. Conclusions A computational method POPISK is proposed to predict immunogenicity with scores which are useful for predicting immunogenicity changes made by single-residue modifications. The web server of POPISK is freely available at http://iclab.life.nctu.edu.tw/POPISK. PMID:22085524

POPISK: T-cell reactivity prediction using support vector machines and string kernels.

PubMed

Tung, Chun-Wei; Ziehm, Matthias; Kämper, Andreas; Kohlbacher, Oliver; Ho, Shinn-Ying

2011-11-15

Accurate prediction of peptide immunogenicity and characterization of relation between peptide sequences and peptide immunogenicity will be greatly helpful for vaccine designs and understanding of the immune system. In contrast to the prediction of antigen processing and presentation pathway, the prediction of subsequent T-cell reactivity is a much harder topic. Previous studies of identifying T-cell receptor (TCR) recognition positions were based on small-scale analyses using only a few peptides and concluded different recognition positions such as positions 4, 6 and 8 of peptides with length 9. Large-scale analyses are necessary to better characterize the effect of peptide sequence variations on T-cell reactivity and design predictors of a peptide's T-cell reactivity (and thus immunogenicity). The identification and characterization of important positions influencing T-cell reactivity will provide insights into the underlying mechanism of immunogenicity. This work establishes a large dataset by collecting immunogenicity data from three major immunology databases. In order to consider the effect of MHC restriction, peptides are classified by their associated MHC alleles. Subsequently, a computational method (named POPISK) using support vector machine with a weighted degree string kernel is proposed to predict T-cell reactivity and identify important recognition positions. POPISK yields a mean 10-fold cross-validation accuracy of 68% in predicting T-cell reactivity of HLA-A2-binding peptides. POPISK is capable of predicting immunogenicity with scores that can also correctly predict the change in T-cell reactivity related to point mutations in epitopes reported in previous studies using crystal structures. Thorough analyses of the prediction results identify the important positions 4, 6, 8 and 9, and yield insights into the molecular basis for TCR recognition. Finally, we relate this finding to physicochemical properties and structural features of the MHC-peptide-TCR interaction. A computational method POPISK is proposed to predict immunogenicity with scores which are useful for predicting immunogenicity changes made by single-residue modifications. The web server of POPISK is freely available at http://iclab.life.nctu.edu.tw/POPISK.

Aptamer based peptide enrichment for quantitative analysis of gonadotropin-releasing hormone by LC-MS/MS.

PubMed

Richards, S L; Cawley, A T; Cavicchioli, R; Suann, C J; Pickford, R; Raftery, M J

2016-04-01

Over recent years threats to racing have expanded to include naturally occurring biological molecules, such as peptides and proteins, and their synthetic analogues. Traditionally, antibodies have been used to enable detection of these compounds as they allow purification and concentration of the analyte of interest. The rapid expansion of peptide-based therapeutics necessitates a similarly rapid development of suitable antibodies or other means of enrichment. Potential alternative enrichment strategies include the use of aptamers, which offer the significant advantage of chemical synthesis once the nucleic acid sequence is known. A method was developed for the enrichment, detection and quantitation of gonadotropin-releasing hormone (GnRH) in equine urine using aptamer-based enrichment and LC-MS/MS. The method achieved comparable limits of detection (1 pg/mL) and quantification (2.5 pg/mL) to previously published antibody-based enrichment methods. The intra- and inter-assay precision achieved was less than 10% at both 5 and 20 pg/mL, and displayed a working dynamic range of 2.5-100 pg/mL. Significant matrix enhancement (170 ± 8%) and low analytical recovery (29 ± 15%) was observed, although the use of an isotopically heavy labelled GnRH peptide, GnRH (Pro(13)C5,(15)N), as the internal standard provides compensation for these parameters. Within the current limits of detection GnRH was detectable up to 1h post administration in urine and identification of a urinary catabolite extended this detection window to 4h. Based on the results of this preliminary investigation we propose the use of aptamers as a viable alternative to antibodies in the enrichment of peptide targets from equine urine. Copyright © 2016 Elsevier B.V. All rights reserved.

MStern Blotting-High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates.

PubMed

Berger, Sebastian T; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

2015-10-01

We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

MStern Blotting–High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates*

PubMed Central

Berger, Sebastian T.; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

2015-01-01

We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. PMID:26223766

Proteomic analysis of processing by-products from canned and fresh tuna: identification of potentially functional food proteins.

PubMed

Sanmartín, Esther; Arboleya, Juan Carlos; Iloro, Ibon; Escuredo, Kepa; Elortza, Felix; Moreno, F Javier

2012-09-15

Proteomic approaches have been used to identify the main proteins present in processing by-products generated by the canning tuna-industry, as well as in by-products derived from filleting of skeletal red muscle of fresh tuna. Following fractionation by using an ammonium sulphate precipitation method, three proteins (tropomyosin, haemoglobin and the stress-shock protein ubiquitin) were identified in the highly heterogeneous and heat-treated material discarded by the canning-industry. Additionally, this fractionation method was successful to obtain tropomyosin of high purity from the heterogeneous starting material. By-products from skeletal red muscle of fresh tuna were efficiently fractionated to sarcoplasmic and myofibrillar fractions, prior to the identification based mainly on the combined searching of the peptide mass fingerprint (MALDI-TOF) and peptide fragment fingerprinting (MALDI LIFT-TOF/TOF) spectra of fifteen bands separated by 1D SDS-PAGE. Thus, the sarcoplasmic fraction contained myoglobin and several enzymes that are essential for efficient energy production, whereas the myofibrillar fraction had important contractile proteins, such as actin, tropomyosin, myosin or an isoform of the enzyme creatine kinase. Application of proteomic technologies has revealed new knowledge on the composition of important by-products from tuna species, enabling a better evaluation of their potential applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

Hydrofluoric Acid-Based Derivatization Strategy To Profile PARP-1 ADP-Ribosylation by LC-MS/MS.

PubMed

Gagné, Jean-Philippe; Langelier, Marie-France; Pascal, John M; Poirier, Guy G

2018-06-11

Despite significant advances in the development of mass spectrometry-based methods for the identification of protein ADP-ribosylation, current protocols suffer from several drawbacks that preclude their widespread applicability. Given the intrinsic heterogeneous nature of poly(ADP-ribose), a number of strategies have been developed to generate simple derivatives for effective interrogation of protein databases and site-specific localization of the modified residues. Currently, the generation of spectral signatures indicative of ADP-ribosylation rely on chemical or enzymatic conversion of the modification to a single mass increment. Still, limitations arise from the lability of the poly(ADP-ribose) remnant during tandem mass spectrometry, the varying susceptibilities of different ADP-ribose-protein bonds to chemical hydrolysis, or the context dependence of enzyme-catalyzed reactions. Here, we present a chemical-based derivatization method applicable to the confident identification of site-specific ADP-ribosylation by conventional mass spectrometry on any targeted amino acid residue. Using PARP-1 as a model protein, we report that treatment of ADP-ribosylated peptides with hydrofluoric acid generates a specific +132 Da mass signature that corresponds to the decomposition of mono- and poly(ADP-ribosylated) peptides into ribose adducts as a consequence of the cleavage of the phosphorus-oxygen bonds.

Epitope Structure of the Carbohydrate Recognition Domain of Asialoglycoprotein Receptor to a Monoclonal Antibody Revealed by High-Resolution Proteolytic Excision Mass Spectrometry

NASA Astrophysics Data System (ADS)

Stefanescu, Raluca; Born, Rita; Moise, Adrian; Ernst, Beat; Przybylski, Michael

2011-01-01

Recent studies suggest that the H1 subunit of the carbohydrate recognition domain (H1CRD) of the asialoglycoprotein receptor is used as an entry site into hepatocytes by hepatitis A and B viruses and Marburg virus. Thus, molecules binding specifically to the CRD might exert inhibition towards these diseases by blocking the virus entry site. We report here the identification of the epitope structure of H1CRD to a monoclonal antibody by proteolytic epitope excision of the immune complex and high-resolution MALDI-FTICR mass spectrometry. As a prerequisite of the epitope determination, the primary structure of the H1CRD antigen was characterised by ESI-FTICR-MS of the intact protein and by LC-MS/MS of tryptic digest mixtures. Molecular mass determination and proteolytic fragments provided the identification of two intramolecular disulfide bridges (seven Cys residues), and a Cys-mercaptoethanol adduct formed by treatment with β-mercaptoethanol during protein extraction. The H1CRD antigen binds to the monoclonal antibody in both native and Cys-alkylated form. For identification of the epitope, the antibody was immobilized on N-hydroxysuccinimide (NHS)-activated Sepharose. Epitope excision and epitope extraction with trypsin and FTICR-MS of affinity-bound peptides provided the identification of two specific epitope peptides (5-16) and (17-23) that showed high affinity to the antibody. Affinity studies of the synthetic epitope peptides revealed independent binding of each peptide to the antibody.

A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products*

PubMed Central

auf dem Keller, Ulrich; Prudova, Anna; Gioia, Magda; Butler, Georgina S.; Overall, Christopher M.

2010-01-01

Terminal amine isotopic labeling of substrates (TAILS), our recently introduced platform for quantitative N-terminome analysis, enables wide dynamic range identification of original mature protein N-termini and protease cleavage products. Modifying TAILS by use of isobaric tag for relative and absolute quantification (iTRAQ)-like labels for quantification together with a robust statistical classifier derived from experimental protease cleavage data, we report reliable and statistically valid identification of proteolytic events in complex biological systems in MS2 mode. The statistical classifier is supported by a novel parameter evaluating ion intensity-dependent quantification confidences of single peptide quantifications, the quantification confidence factor (QCF). Furthermore, the isoform assignment score (IAS) is introduced, a new scoring system for the evaluation of single peptide-to-protein assignments based on high confidence protein identifications in the same sample prior to negative selection enrichment of N-terminal peptides. By these approaches, we identified and validated, in addition to known substrates, low abundance novel bioactive MMP-2 targets including the plasminogen receptor S100A10 (p11) and the proinflammatory cytokine proEMAP/p43 that were previously undescribed. PMID:20305283

The Analytical Chemistry of Drug Monitoring in Athletes

NASA Astrophysics Data System (ADS)

Bowers, Larry D.

2009-07-01

The detection and deterrence of the abuse of performance-enhancing drugs in sport are important to maintaining a level playing field among athletes and to decreasing the risk to athletes’ health. The World Anti-Doping Program consists of six documents, three of which play a role in analytical development: The World Anti-Doping Code, The List of Prohibited Substances and Methods, and The International Standard for Laboratories. Among the classes of prohibited substances, three have given rise to the most recent analytical developments in the field: anabolic agents; peptide and protein hormones; and methods to increase oxygen delivery to the tissues, including recombinant erythropoietin. Methods for anabolic agents, including designer steroids, have been enhanced through the use of liquid chromatography/tandem mass spectrometry and gas chromatography/combustion/isotope-ratio mass spectrometry. Protein and peptide identification and quantification have benefited from advances in liquid chromatography/tandem mass spectrometry. Incorporation of techniques such as flow cytometry and isoelectric focusing have supported the detection of blood doping.

Detection and Site Localization of Phosphorylcholine-Modified Peptides by NanoLC-ESI-MS/MS Using Precursor Ion Scanning and Multiple Reaction Monitoring Experiments

NASA Astrophysics Data System (ADS)

Timm, Thomas; Lenz, Christof; Merkel, Dietrich; Sadiffo, Christian; Grabitzki, Julia; Klein, Jochen; Lochnit, Guenter

2015-03-01

Phosphorylcholine (PC)-modified biomolecules like lipopolysaccharides, glycosphingolipids, and (glyco)proteins are widespread, highly relevant antigens of parasites, since this small hapten shows potent immunomodulatory capacity, which allows the establishment of long-lasting infections of the host. Especially for PC-modified proteins, structural data is rare because of the zwitterionic nature of the PC substituent, resulting in low sensitivities and unusual but characteristic fragmentation patterns. We have developed a targeted mass spectrometric approach using hybrid triple quadrupole/linear ion trap (QTRAP) mass spectrometry coupled to nanoflow chromatography for the sensitive detection of PC-modified peptides from complex proteolytic digests, and the localization of the PC-modification within the peptide backbone. In a first step, proteolytic digests are screened using precursor ion scanning for the marker ions of choline ( m/z 104.1) and phosphorylcholine ( m/z 184.1) to establish the presence of PC-modified peptides. Potential PC-modified precursors are then subjected to a second analysis using multiple reaction monitoring (MRM)-triggered product ion spectra for the identification and site localization of the modified peptides. The approach was first established using synthetic PC-modified synthetic peptides and PC-modified model digests. Following the optimization of key parameters, we then successfully applied the method to the detection of PC-peptides in the background of a proteolytic digest of a whole proteome. This methodological invention will greatly facilitate the detection of PC-substituted biomolecules and their structural analysis.

Matrix assisted laser desorption ionization mass spectrometry imaging identifies markers of ageing and osteoarthritic cartilage

PubMed Central

2014-01-01

Introduction Cartilage protein distribution and the changes that occur in cartilage ageing and disease are essential in understanding the process of cartilage ageing and age related diseases such as osteoarthritis. The aim of this study was to investigate the peptide profiles in ageing and osteoarthritic (OA) cartilage sections using matrix assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI). Methods The distribution of proteins in young, old and OA equine cartilage was compared following tryptic digestion of cartilage slices and MALDI-MSI undertaken with a MALDI SYNAPT™ HDMS system. Protein identification was undertaken using database searches following multivariate analysis. Peptide intensity differences between young, ageing and OA cartilage were imaged with Biomap software. Analysis of aggrecanase specific cleavage patterns of a crude cartilage proteoglycan extract were used to validate some of the differences in peptide intensity identified. Immunohistochemistry studies validated the differences in protein abundance. Results Young, old and OA equine cartilage was discriminated based on their peptide signature using discriminant analysis. Proteins including aggrecan core protein, fibromodulin, and cartilage oligomeric matrix protein were identified and localised. Fibronectin peptides displayed a stronger intensity in OA cartilage. Age-specific protein markers for collectin-43 and cartilage oligomeric matrix protein were identified. In addition potential fibromodulin and biglycan peptides targeted for degradation in OA were detected. Conclusions MALDI-MSI provided a novel platform to study cartilage ageing and disease enabling age and disease specific peptides in cartilage to be elucidated and spatially resolved. PMID:24886698

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries.

PubMed

Wu, Jemma X; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P

2016-07-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries*

PubMed Central

Wu, Jemma X.; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P.

2016-01-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. PMID:27161445

Efficient one-cycle affinity selection of binding proteins or peptides specific for a small-molecule using a T7 phage display pool.

PubMed

Takakusagi, Yoichi; Kuramochi, Kouji; Takagi, Manami; Kusayanagi, Tomoe; Manita, Daisuke; Ozawa, Hiroko; Iwakiri, Kanako; Takakusagi, Kaori; Miyano, Yuka; Nakazaki, Atsuo; Kobayashi, Susumu; Sugawara, Fumio; Sakaguchi, Kengo

2008-11-15

Here, we report an efficient one-cycle affinity selection using a natural-protein or random-peptide T7 phage pool for identification of binding proteins or peptides specific for small-molecules. The screening procedure involved a cuvette type 27-MHz quartz-crystal microbalance (QCM) apparatus with introduction of self-assembled monolayer (SAM) for a specific small-molecule immobilization on the gold electrode surface of a sensor chip. Using this apparatus, we attempted an affinity selection of proteins or peptides against synthetic ligand for FK506-binding protein (SLF) or irinotecan (Iri, CPT-11). An affinity selection using SLF-SAM and a natural-protein T7 phage pool successfully detected FK506-binding protein 12 (FKBP12)-displaying T7 phage after an interaction time of only 10 min. Extensive exploration of time-consuming wash and/or elution conditions together with several rounds of selection was not required. Furthermore, in the selection using a 15-mer random-peptide T7 phage pool and subsequent analysis utilizing receptor ligand contact (RELIC) software, a subset of SLF-selected peptides clearly pinpointed several amino-acid residues within the binding site of FKBP12. Likewise, a subset of Iri-selected peptides pinpointed part of the positive amino-acid region of residues from the Iri-binding site of the well-known direct targets, acetylcholinesterase (AChE) and carboxylesterase (CE). Our findings demonstrate the effectiveness of this method and general applicability for a wide range of small-molecules.

Evaluation of mass spectrometric data using principal component analysis for determination of the effects of organic lakes on protein binder identification.

PubMed

Hrdlickova Kuckova, Stepanka; Rambouskova, Gabriela; Hynek, Radovan; Cejnar, Pavel; Oltrogge, Doris; Fuchs, Robert

2015-11-01

Matrix-assisted laser desorption/ionisation-time of flight (MALDI-TOF) mass spectrometry is commonly used for the identification of proteinaceous binders and their mixtures in artworks. The determination of protein binders is based on a comparison between the m/z values of tryptic peptides in the unknown sample and a reference one (egg, casein, animal glues etc.), but this method has greater potential to study changes due to ageing and the influence of organic/inorganic components on protein identification. However, it is necessary to then carry out statistical evaluation on the obtained data. Before now, it has been complicated to routinely convert the mass spectrometric data into a statistical programme, to extract and match the appropriate peaks. Only several 'homemade' computer programmes without user-friendly interfaces are available for these purposes. In this paper, we would like to present our completely new, publically available, non-commercial software, ms-alone and multiMS-toolbox, for principal component analyses of MALDI-TOF MS data for R software, and their application to the study of the influence of heterogeneous matrices (organic lakes) for protein identification. Using this new software, we determined the main factors that influence the protein analyses of artificially aged model mixtures of organic lakes and fish glue, prepared according to historical recipes that were used for book illumination, using MALDI-TOF peptide mass mapping. Copyright © 2015 John Wiley & Sons, Ltd.

A novel quantification-driven proteomic strategy identifies an endogenous peptide of pleiotrophin as a new biomarker of Alzheimer's disease.

PubMed

Skillbäck, Tobias; Mattsson, Niklas; Hansson, Karl; Mirgorodskaya, Ekaterina; Dahlén, Rahil; van der Flier, Wiesje; Scheltens, Philip; Duits, Floor; Hansson, Oskar; Teunissen, Charlotte; Blennow, Kaj; Zetterberg, Henrik; Gobom, Johan

2017-10-17

We present a new, quantification-driven proteomic approach to identifying biomarkers. In contrast to the identification-driven approach, limited in scope to peptides that are identified by database searching in the first step, all MS data are considered to select biomarker candidates. The endopeptidome of cerebrospinal fluid from 40 Alzheimer's disease (AD) patients, 40 subjects with mild cognitive impairment, and 40 controls with subjective cognitive decline was analyzed using multiplex isobaric labeling. Spectral clustering was used to match MS/MS spectra. The top biomarker candidate cluster (215% higher in AD compared to controls, area under ROC curve = 0.96) was identified as a fragment of pleiotrophin located near the protein's C-terminus. Analysis of another cohort (n = 60 over four clinical groups) verified that the biomarker was increased in AD patients while no change in controls, Parkinson's disease or progressive supranuclear palsy was observed. The identification of the novel biomarker pleiotrophin 151-166 demonstrates that our quantification-driven proteomic approach is a promising method for biomarker discovery, which may be universally applicable in clinical proteomics.

Protein 3-Nitrotyrosine in Complex Biological Samples: Quantification by High-Pressure Liquid Chromatography/Electrochemical Detection and Emergence of Proteomic Approaches for Unbiased Identification of Modification Sites

PubMed Central

Nuriel, Tal; Deeb, Ruba S.; Hajjar, David P.; Gross, Steven S.

2008-01-01

Nitration of tyrosine residues by nitric oxide (NO)-derived species results in the accumulation of 3-nitrotyrosine in proteins, a hallmark of nitrosative stress in cells and tissues. Tyrosine nitration is recognized as one of the multiple signaling modalities used by NO-derived species for the regulation of protein structure and function in health and disease. Various methods have been described for the quantification of protein 3-nitrotyrosine residues, and several strategies have been presented toward the goal of proteome-wide identification of protein tyrosine modification sites. This chapter details a useful protocol for the quantification of 3-nitrotyrosine in cells and tissues using high-pressure liquid chromatography with electrochemical detection. Additionally, this chapter describes a novel biotin-tagging strategy for specific enrichment of 3-nitrotyrosine-containing peptides. Application of this strategy, in conjunction with high-throughput MS/MS-based peptide sequencing, is anticipated to fuel efforts in developing comprehensive inventories of nitrosative stress-induced protein-tyrosine modification sites in cells and tissues. PMID:18554526

Using the QCM Biosensor-Based T7 Phage Display Combined with Bioinformatics Analysis for Target Identification of Bioactive Small Molecule.

PubMed

Takakusagi, Yoichi; Takakusagi, Kaori; Sugawara, Fumio; Sakaguchi, Kengo

2018-01-01

Identification of target proteins that directly bind to bioactive small molecule is of great interest in terms of clarifying the mode of action of the small molecule as well as elucidating the biological phenomena at the molecular level. Of the experimental technologies available, T7 phage display allows comprehensive screening of small molecule-recognizing amino acid sequence from the peptide libraries displayed on the T7 phage capsid. Here, we describe the T7 phage display strategy that is combined with quartz-crystal microbalance (QCM) biosensor for affinity selection platform and bioinformatics analysis for small molecule-recognizing short peptides. This method dramatically enhances efficacy and throughput of the screening for small molecule-recognizing amino acid sequences without repeated rounds of selection. Subsequent execution of bioinformatics programs allows combinatorial and comprehensive target protein discovery of small molecules with its binding site, regardless of protein sample insolubility, instability, or inaccessibility of the fixed small molecules to internally located binding site on larger target proteins when conventional proteomics approaches are used.

Spectrum-to-Spectrum Searching Using a Proteome-wide Spectral Library*

PubMed Central

Yen, Chia-Yu; Houel, Stephane; Ahn, Natalie G.; Old, William M.

2011-01-01

The unambiguous assignment of tandem mass spectra (MS/MS) to peptide sequences remains a key unsolved problem in proteomics. Spectral library search strategies have emerged as a promising alternative for peptide identification, in which MS/MS spectra are directly compared against a reference library of confidently assigned spectra. Two problems relate to library size. First, reference spectral libraries are limited to rediscovery of previously identified peptides and are not applicable to new peptides, because of their incomplete coverage of the human proteome. Second, problems arise when searching a spectral library the size of the entire human proteome. We observed that traditional dot product scoring methods do not scale well with spectral library size, showing reduction in sensitivity when library size is increased. We show that this problem can be addressed by optimizing scoring metrics for spectrum-to-spectrum searches with large spectral libraries. MS/MS spectra for the 1.3 million predicted tryptic peptides in the human proteome are simulated using a kinetic fragmentation model (MassAnalyzer version2.1) to create a proteome-wide simulated spectral library. Searches of the simulated library increase MS/MS assignments by 24% compared with Mascot, when using probabilistic and rank based scoring methods. The proteome-wide coverage of the simulated library leads to 11% increase in unique peptide assignments, compared with parallel searches of a reference spectral library. Further improvement is attained when reference spectra and simulated spectra are combined into a hybrid spectral library, yielding 52% increased MS/MS assignments compared with Mascot searches. Our study demonstrates the advantages of using probabilistic and rank based scores to improve performance of spectrum-to-spectrum search strategies. PMID:21532008

Viral peptides-MHC interaction: Binding probability and distance from human peptides.

PubMed

Santoni, Daniele

2018-05-23

Identification of peptides binding to MHC class I complex can play a crucial role in retrieving potential targets able to trigger an immune response. Affinity binding of viral peptides can be estimated through effective computational methods that in the most of cases are based on machine learning approach. Achieving a better insight into peptide features that impact on the affinity binding rate is a challenging issue. In the present work we focused on 9-mer peptides of Human immunodeficiency virus type 1 and Human herpes simplex virus 1, studying their binding to MHC class I. Viral 9-mers were partitioned into different classes, where each class is characterized by how far (in terms of mutation steps) the peptides belonging to that class are from human 9-mers. Viral 9-mers were partitioned in different classes, based on the number of mutation steps they are far from human 9-mers. We showed that the overall binding probability significantly differs among classes, and it typically increases as the distance, computed in terms of number of mutation steps from the human set of 9-mers, increases. The binding probability is particularly high when considering viral 9-mers that are far from all human 9-mers more than three mutation steps. A further evidence, providing significance to those special viral peptides and suggesting a potential role they can play, comes from the analysis of their distribution along viral genomes, as it revealed they are not randomly located, but they preferentially occur in specific genes. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification of peptide sequences that target to the brain using in vivo phage display.

PubMed

Li, Jingwei; Zhang, Qizhi; Pang, Zhiqing; Wang, Yuchen; Liu, Qingfeng; Guo, Liangran; Jiang, Xinguo

2012-06-01

Phage display technology could provide a rapid means for the discovery of novel peptides. To find peptide ligands specific for the brain vascular receptors, we performed a modified phage display method. Phages were recovered from mice brain parenchyma after administrated with a random 7-mer peptide library intravenously. A longer circulation time was arranged according to the biodistributive brain/blood ratios of phage particles. Following sequential rounds of isolation, a number of phages were sequenced and a peptide sequence (CTSTSAPYC, denoted as PepC7) was identified. Clone 7-1, which encodes PepC7, exhibited translocation efficiency about 41-fold higher than the random library phage. Immunofluorescence analysis revealed that Clone 7-1 had a significant superiority on transport efficiency into the brain compared with native M13 phage. Clone 7-1 was inhibited from homing to the brain in a dose-dependent fashion when cyclic peptides of the same sequence were present in a competition assay. Interestingly, the linear peptide (ATSTSAPYA, Pep7) and a scrambled control peptide PepSC7 (CSPATSYTC) did not compete with the phage at the same tested concentration (0.2-200 pg). Labeled by Cy5.5, PepC7 exhibited significant brain-targeting capability in in vivo optical imaging analysis. The cyclic conformation of PepC7 formed by disulfide bond, and the correct structure itself play a critical role in maintaining the selectivity and affinity for the brain. In conclusion, PepC7 is a promising brain-target motif never been reported before and it could be applied to targeted drug delivery into the brain.

Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data.

PubMed

Tu, Chengjian; Sheng, Quanhu; Li, Jun; Ma, Danjun; Shen, Xiaomeng; Wang, Xue; Shyr, Yu; Yi, Zhengping; Qu, Jun

2015-11-06

The two key steps for analyzing proteomic data generated by high-resolution MS are database searching and postprocessing. While the two steps are interrelated, studies on their combinatory effects and the optimization of these procedures have not been adequately conducted. Here, we investigated the performance of three popular search engines (SEQUEST, Mascot, and MS Amanda) in conjunction with five filtering approaches, including respective score-based filtering, a group-based approach, local false discovery rate (LFDR), PeptideProphet, and Percolator. A total of eight data sets from various proteomes (e.g., E. coli, yeast, and human) produced by various instruments with high-accuracy survey scan (MS1) and high- or low-accuracy fragment ion scan (MS2) (LTQ-Orbitrap, Orbitrap-Velos, Orbitrap-Elite, Q-Exactive, Orbitrap-Fusion, and Q-TOF) were analyzed. It was found combinations involving Percolator achieved markedly more peptide and protein identifications at the same FDR level than the other 12 combinations for all data sets. Among these, combinations of SEQUEST-Percolator and MS Amanda-Percolator provided slightly better performances for data sets with low-accuracy MS2 (ion trap or IT) and high accuracy MS2 (Orbitrap or TOF), respectively, than did other methods. For approaches without Percolator, SEQUEST-group performs the best for data sets with MS2 produced by collision-induced dissociation (CID) and IT analysis; Mascot-LFDR gives more identifications for data sets generated by higher-energy collisional dissociation (HCD) and analyzed in Orbitrap (HCD-OT) and in Orbitrap Fusion (HCD-IT); MS Amanda-Group excels for the Q-TOF data set and the Orbitrap Velos HCD-OT data set. Therefore, if Percolator was not used, a specific combination should be applied for each type of data set. Moreover, a higher percentage of multiple-peptide proteins and lower variation of protein spectral counts were observed when analyzing technical replicates using Percolator-associated combinations; therefore, Percolator enhanced the reliability for both identification and quantification. The analyses were performed using the specific programs embedded in Proteome Discoverer, Scaffold, and an in-house algorithm (BuildSummary). These results provide valuable guidelines for the optimal interpretation of proteomic results and the development of fit-for-purpose protocols under different situations.

Identification of a Unique Amyloid Sequence in AA Amyloidosis of a Pig Associated With Streptococcus Suis Infection.

PubMed

Kamiie, J; Sugahara, G; Yoshimoto, S; Aihara, N; Mineshige, T; Uetsuka, K; Shirota, K

2017-01-01

Here we report a pig with amyloid A (AA) amyloidosis associated with Streptococcus suis infection and identification of a unique amyloid sequence in the amyloid deposits in the tissue. Tissues from the 180-day-old underdeveloped pig contained foci of necrosis and suppurative inflammation associated with S. suis infection. Congo red stain, immunohistochemistry, and electron microscopy revealed intense AA deposition in the spleen and renal glomeruli. Mass spectrometric analysis of amyloid material extracted from the spleen showed serum AA 2 (SAA2) peptide as well as a unique peptide sequence previously reported in a pig with AA amyloidosis. The common detection of the unique amyloid sequence in the current and past cases of AA amyloidosis in pigs suggests that this amyloid sequence might play a key role in the development of porcine AA amyloidosis. An in vitro fibrillation assay demonstrated that the unique AA peptide formed typically rigid, long amyloid fibrils (10 nm wide) and the N-terminus peptide of SAA2 formed zigzagged, short fibers (7 nm wide). Moreover, the SAA2 peptide formed long, rigid amyloid fibrils in the presence of sonicated amyloid fibrils formed by the unique AA peptide. These findings indicate that the N-terminus of SAA2 as well as the AA peptide mediate the development of AA amyloidosis in pigs via cross-seeding polymerization.

Miniaturized Mass-Spectrometry-Based Analysis System for Fully Automated Examination of Conditioned Cell Culture Media

PubMed Central

Weber, Emanuel; Pinkse, Martijn W. H.; Bener-Aksam, Eda; Vellekoop, Michael J.; Verhaert, Peter D. E. M.

2012-01-01

We present a fully automated setup for performing in-line mass spectrometry (MS) analysis of conditioned media in cell cultures, in particular focusing on the peptides therein. The goal is to assess peptides secreted by cells in different culture conditions. The developed system is compatible with MS as analytical technique, as this is one of the most powerful analysis methods for peptide detection and identification. Proof of concept was achieved using the well-known mating-factor signaling in baker's yeast, Saccharomyces cerevisiae. Our concept system holds 1 mL of cell culture medium and allows maintaining a yeast culture for, at least, 40 hours with continuous supernatant extraction (and medium replenishing). The device's small dimensions result in reduced costs for reagents and open perspectives towards full integration on-chip. Experimental data that can be obtained are time-resolved peptide profiles in a yeast culture, including information about the appearance of mating-factor-related peptides. We emphasize that the system operates without any manual intervention or pipetting steps, which allows for an improved overall sensitivity compared to non-automated alternatives. MS data confirmed previously reported aspects of the physiology of the yeast-mating process. Moreover, matingfactor breakdown products (as well as evidence for a potentially responsible protease) were found. PMID:23091722

Ga2O3 photocatalyzed on-line tagging of cysteine to facilitate peptide mass fingerprinting.

PubMed

Qiao, Liang; Su, Fangzheng; Bi, Hongyan; Girault, Hubert H; Liu, Baohong

2011-09-01

β-Ga(2)O(3) is a wide-band-gap semiconductor having strong oxidation ability under light irradiation. Herein, the steel target plates modified with β-Ga(2)O(3) nanoparticles have been developed to carry out in-source photo-catalytic oxidative reactions for online peptide tagging during laser desorption/ionization mass spectrometry (LDI-MS) analysis. Under UV laser irradiation, β-Ga(2)O(3) can catalyze the photo-oxidation of 2-methoxyhydroquinone added to a sample mixture to 2-methoxy benzoquinone that can further react with the thiol groups of cysteine residues by Michael addition reaction. The tagging process leads to appearance of pairs of peaks with an m/z shift of 138.1Th. This online labelling strategy is demonstrated to be sensitive and efficient with a detection-limit at femtomole level. Using the strategy, the information on cysteine content in peptides can be obtained together with peptide mass, therefore constraining the database searching for an advanced identification of cysteine-containing proteins from protein mixtures. The current peptide online tagging method can be important for specific analysis of cysteine-containing proteins especially the low-abundant ones that cannot be completely isolated from other high-abundant non-cysteine-proteins. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An improved stable isotope N-terminal labeling approach with light/heavy TMPP to automate proteogenomics data validation: dN-TOP.

PubMed

Bertaccini, Diego; Vaca, Sebastian; Carapito, Christine; Arsène-Ploetze, Florence; Van Dorsselaer, Alain; Schaeffer-Reiss, Christine

2013-06-07

In silico gene prediction has proven to be prone to errors, especially regarding precise localization of start codons that spread in subsequent biological studies. Therefore, the high throughput characterization of protein N-termini is becoming an emerging challenge in the proteomics and especially proteogenomics fields. The trimethoxyphenyl phosphonium (TMPP) labeling approach (N-TOP) is an efficient N-terminomic approach that allows the characterization of both N-terminal and internal peptides in a single experiment. Due to its permanent positive charge, TMPP labeling strongly affects MS/MS fragmentation resulting in unadapted scoring of TMPP-derivatized peptide spectra by classical search engines. This behavior has led to difficulties in validating TMPP-derivatized peptide identifications with usual score filtering and thus to low/underestimated numbers of identified N-termini. We present herein a new strategy (dN-TOP) that overwhelmed the previous limitation allowing a confident and automated N-terminal peptide validation thanks to a combined labeling with light and heavy TMPP reagents. We show how this double labeling allows increasing the number of validated N-terminal peptides. This strategy represents a considerable improvement to the well-established N-TOP method with an enhanced and accelerated data processing making it now fully compatible with high-throughput proteogenomics studies.

Software Analysis of Uncorrelated MS1 Peaks for Discovery of Post-Translational Modifications

NASA Astrophysics Data System (ADS)

Pascal, Bruce D.; West, Graham M.; Scharager-Tapia, Catherina; Flefil, Ricardo; Moroni, Tina; Martinez-Acedo, Pablo; Griffin, Patrick R.; Carvalloza, Anthony C.

2015-12-01

The goal in proteomics to identify all peptides in a complex mixture has been largely addressed using various LC MS/MS approaches, such as data dependent acquisition, SRM/MRM, and data independent acquisition instrumentation. Despite these developments, many peptides remain unsequenced, often due to low abundance, poor fragmentation patterns, or data analysis difficulties. Many of the unidentified peptides exhibit strong evidence in high resolution MS1 data and are frequently post-translationally modified, playing a significant role in biological processes. Proteomics Workbench (PWB) software was developed to automate the detection and visualization of all possible peptides in MS1 data, reveal candidate peptides not initially identified, and build inclusion lists for subsequent MS2 analysis to uncover new identifications. We used this software on existing data on the autophagy regulating kinase Ulk1 as a proof of concept for this method, as we had already manually identified a number of phosphorylation sites Dorsey, F. C. et al (J. Proteome. Res. 8(11), 5253-5263 (2009)). PWB found all previously identified sites of phosphorylation. The software has been made freely available at http://www.proteomicsworkbench.com .

MALDI-based identification of stable hazelnut protein derived tryptic marker peptides.

PubMed

Cucu, T; De Meulenaer, B; Devreese, B

2012-01-01

Food allergy is an important health problem especially in industrialised countries. Tree nuts, among which are hazelnuts (Corylus avellana), are typically causing serious and life-threatening symptoms in sensitive subjects. Hazelnut is used as a food ingredient in pastry, confectionary products, ice cream and meat products, therefore undeclared hazelnut can be often present as a cross-contaminant representing a threat for allergic consumers. Mass spectrometric techniques are used for the detection of food allergens in processed foods, but limited information regarding stable tryptic peptide markers for hazelnut is available. The aim of this study was to detect stable peptide markers from modified hazelnut protein through the Maillard reaction and oxidation in a buffered solution. Peptides ³⁹⁵Gly-Arg⁴⁰³ from Cor a 11 and ²⁰⁹Gln-Arg²¹⁷, ³⁵¹Ile-Arg³⁶³, ⁴⁶⁴Ala-Arg⁴⁷⁸ and ⁴⁰¹Val-Arg⁴¹⁷ from Cor a 9 hazelnut allergens proved to be the most stable and could be detected and confirmed with high scores in most of the modified samples. The identified peptides can be further used as analytical targets for the development of more robust quantitative methods for hazelnut detection in processed foods.

High Sensitivity Crosslink Detection Coupled With Integrative Structure Modeling in the Mass Spec Studio *

PubMed Central

Sarpe, Vladimir; Rafiei, Atefeh; Hepburn, Morgan; Ostan, Nicholas; Schryvers, Anthony B.; Schriemer, David C.

2016-01-01

The Mass Spec Studio package was designed to support the extraction of hydrogen-deuterium exchange and covalent labeling data for a range of mass spectrometry (MS)-based workflows, to integrate with restraint-driven protein modeling activities. In this report, we present an extension of the underlying Studio framework and provide a plug-in for crosslink (XL) detection. To accommodate flexibility in XL methods and applications, while maintaining efficient data processing, the plug-in employs a peptide library reduction strategy via a presearch of the tandem-MS data. We demonstrate that prescoring linear unmodified peptide tags using a probabilistic approach substantially reduces search space by requiring both crosslinked peptides to generate sparse data attributable to their linear forms. The method demonstrates highly sensitive crosslink peptide identification with a low false positive rate. Integration with a Haddock plug-in provides a resource that can combine multiple sources of data for protein modeling activities. We generated a structural model of porcine transferrin bound to TbpB, a membrane-bound receptor essential for iron acquisition in Actinobacillus pleuropneumoniae. Using mutational data and crosslinking restraints, we confirm the mechanism by which TbpB recognizes the iron-loaded form of transferrin, and note the requirement for disparate sources of restraint data for accurate model construction. The software plugin is freely available at www.msstudio.ca. PMID:27412762

CS-AMPPred: An Updated SVM Model for Antimicrobial Activity Prediction in Cysteine-Stabilized Peptides

PubMed Central

Porto, William F.; Pires, Állan S.; Franco, Octavio L.

2012-01-01

The antimicrobial peptides (AMP) have been proposed as an alternative to control resistant pathogens. However, due to multifunctional properties of several AMP classes, until now there has been no way to perform efficient AMP identification, except through in vitro and in vivo tests. Nevertheless, an indication of activity can be provided by prediction methods. In order to contribute to the AMP prediction field, the CS-AMPPred (Cysteine-Stabilized Antimicrobial Peptides Predictor) is presented here, consisting of an updated version of the Support Vector Machine (SVM) model for antimicrobial activity prediction in cysteine-stabilized peptides. The CS-AMPPred is based on five sequence descriptors: indexes of (i) α-helix and (ii) loop formation; and averages of (iii) net charge, (iv) hydrophobicity and (v) flexibility. CS-AMPPred was based on 310 cysteine-stabilized AMPs and 310 sequences extracted from PDB. The polynomial kernel achieves the best accuracy on 5-fold cross validation (85.81%), while the radial and linear kernels achieve 84.19%. Testing in a blind data set, the polynomial and radial kernels achieve an accuracy of 90.00%, while the linear model achieves 89.33%. The three models reach higher accuracies than previously described methods. A standalone version of CS-AMPPred is available for download at and runs on any Linux machine. PMID:23240023

High Sensitivity Crosslink Detection Coupled With Integrative Structure Modeling in the Mass Spec Studio.

PubMed

Sarpe, Vladimir; Rafiei, Atefeh; Hepburn, Morgan; Ostan, Nicholas; Schryvers, Anthony B; Schriemer, David C

2016-09-01

The Mass Spec Studio package was designed to support the extraction of hydrogen-deuterium exchange and covalent labeling data for a range of mass spectrometry (MS)-based workflows, to integrate with restraint-driven protein modeling activities. In this report, we present an extension of the underlying Studio framework and provide a plug-in for crosslink (XL) detection. To accommodate flexibility in XL methods and applications, while maintaining efficient data processing, the plug-in employs a peptide library reduction strategy via a presearch of the tandem-MS data. We demonstrate that prescoring linear unmodified peptide tags using a probabilistic approach substantially reduces search space by requiring both crosslinked peptides to generate sparse data attributable to their linear forms. The method demonstrates highly sensitive crosslink peptide identification with a low false positive rate. Integration with a Haddock plug-in provides a resource that can combine multiple sources of data for protein modeling activities. We generated a structural model of porcine transferrin bound to TbpB, a membrane-bound receptor essential for iron acquisition in Actinobacillus pleuropneumoniae Using mutational data and crosslinking restraints, we confirm the mechanism by which TbpB recognizes the iron-loaded form of transferrin, and note the requirement for disparate sources of restraint data for accurate model construction. The software plugin is freely available at www.msstudio.ca. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Quantitative site-specific reactivity profiling of S-nitrosylation in mouse skeletal muscle using cysteinyl peptide enrichment coupled with mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Dian; Shukla, Anil K.; Chen, Baowei

2013-04-01

S-nitrosylation (SNO) is an important reversible thiol oxidation event that has been increasingly recognized for its role in cell signaling. While many proteins susceptible to S-nitrosylation have been reported, site-specific identification of physiologically relevant SNO modifications remains an analytical challenge due to the low-abundance and labile nature of the modification. Herein we present further improvement and optimization of the recently reported, resin-assisted cysteinyl peptide enrichment protocol for SNO identification and the extension of this application to mouse skeletal muscle to identify specific sites sensitive to S-nitrosylation by quantitative reactivity profiling. The results of our data indicate that the protein- andmore » peptide-level enrichment protocols provide comparable specificity and coverage of SNO-peptide identifications. S-nitrosylation reactivity profiling was performed by quantitatively comparing the site-specific SNO modification levels in samples treated with S-nitrosoglutathione (GSNO), an NO donor, at two different physiologically relevant concentrations (i.e., 10 μM and 100 μM). The reactivity profiling experiments overall identified 489 SNO-modified cysteine sites from 197 proteins with the specificity of 95.2% at the unique-peptide-level based on the percentage of Cys-peptides. Among these sites, 260 sites from 135 proteins were observed with relatively high reactivity to S-nitrosylation; such SNO-sensitive sites are more likely to be physiologically relevant. Many of the SNO-sensitive proteins are preferentially localized in mitochondria, contractile fiber and actin cytoskeleton, suggesting the susceptibility of these subcellular compartments to redox regulation. Moreover, the SNO-sensitive proteins seem to be primarily involved in metabolic pathways, including TCA cycle, glycolysis/gluconeogenesis, glutathione metabolism, and fatty acid metabolism, suggesting the importance of redox regulation in muscle metabolism and insulin action.« less

Cadherin juxtamembrane region derived peptides inhibit TGFβ1 induced gene expression

PubMed Central

Stavropoulos, Ilias; Golla, Kalyan; Moran, Niamh; Martin, Finian; Shields, Denis C

2014-01-01

Bioactive peptides in the juxtamembrane regions of proteins are involved in many signaling events. The juxtamembrane regions of cadherins were examined for the identification of bioactive regions. Several peptides spanning the cytoplasmic juxtamembrane regions of E- and N-cadherin were synthesized and assessed for the ability to influence TGFβ responses in epithelial cells at the gene expression and protein levels. Peptides from regions closer to the membrane appeared more potent inhibitors of TGFβ signaling, blocking Smad3 phosphorylation. Thus inhibiting nuclear translocation of phosphorylated Smad complexes and subsequent transcriptional activation of TGFβ signal propagating genes. The peptides demonstrated a peptide-specific potential to inhibit other TGFβ superfamily members, such as BMP4. PMID:25108297

Performance Evaluation of the Q Exactive HF-X for Shotgun Proteomics.

PubMed

Kelstrup, Christian D; Bekker-Jensen, Dorte B; Arrey, Tabiwang N; Hogrebe, Alexander; Harder, Alexander; Olsen, Jesper V

2018-01-05

Progress in proteomics is mainly driven by advances in mass spectrometric (MS) technologies. Here we benchmarked the performance of the latest MS instrument in the benchtop Orbitrap series, the Q Exactive HF-X, against its predecessor for proteomics applications. A new peak-picking algorithm, a brighter ion source, and optimized ion transfers enable productive MS/MS acquisition above 40 Hz at 7500 resolution. The hardware and software improvements collectively resulted in improved peptide and protein identifications across all comparable conditions, with an increase of up to 50 percent at short LC-MS gradients, yielding identification rates of more than 1000 unique peptides per minute. Alternatively, the Q Exactive HF-X is capable of achieving the same proteome coverage as its predecessor in approximately half the gradient time or at 10-fold lower sample loads. The Q Exactive HF-X also enables rapid phosphoproteomics with routine analysis of more than 5000 phosphopeptides with short single-shot 15 min LC-MS/MS measurements, or 16 700 phosphopeptides quantified across ten conditions in six gradient hours using TMT10-plex and offline peptide fractionation. Finally, exciting perspectives for data-independent acquisition are highlighted with reproducible identification of 55 000 unique peptides covering 5900 proteins in half an hour of MS analysis.

Systematic Optimization of Long Gradient Chromatography Mass Spectrometry for Deep Analysis of Brain Proteome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hong; Yang, Yanling; Li, Yuxin

2015-02-06

Development of high resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC-MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse phase column (100 μm x 150 cm) coupled with Q Exactive MS. The column was capable of achieving a peak capacity of approximately 700 in a 720 min gradient of 10-45% acetonitrile. The optimal loading level was about 6 micrograms of peptides, although the column allowed loading as many as 20 micrograms. Gas phasemore » fractionation of peptide ions further increased the number of peptide identification by ~10%. Moreover, the combination of basic pH LC pre-fractionation with the long gradient LC-MS/MS platform enabled the identification of 96,127 peptides and 10,544 proteins at 1% protein false discovery rate in a postmortem brain sample of Alzheimer’s disease. As deep RNA sequencing of the same specimen suggested that ~16,000 genes were expressed, current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC-MS/MS platform were also discussed.« less

ETD Outperforms CID and HCD in the Analysis of the Ubiquitylated Proteome

NASA Astrophysics Data System (ADS)

Porras-Yakushi, Tanya R.; Sweredoski, Michael J.; Hess, Sonja

2015-09-01

Comprehensive analysis of the ubiquitylome is a prerequisite to fully understand the regulatory role of ubiquitylation. However, the impact of key mass spectrometry parameters on ubiquitylome analyses has not been fully explored. In this study, we show that using electron transfer dissociation (ETD) fragmentation, either exclusively or as part of a decision tree method, leads to ca. 2-fold increase in ubiquitylation site identifications in K-ɛ-GG peptide-enriched samples over traditional collisional-induced dissociation (CID) or higher-energy collision dissociation (HCD) methods. Precursor ions were predominantly observed as 3+ charged species or higher and in a mass range 300-1200 m/z. N-ethylmaleimide was used as an alkylating agent to reduce false positive identifications resulting from overalkylation with halo-acetamides. These results demonstrate that the application of ETD fragmentation, in addition to narrowing the mass range and using N-ethylmaleimide yields more high-confidence ubiquitylation site identification than conventional CID and HCD analysis.

BiPPred: Combined sequence- and structure-based prediction of peptide binding to the Hsp70 chaperone BiP.

PubMed

Schneider, Markus; Rosam, Mathias; Glaser, Manuel; Patronov, Atanas; Shah, Harpreet; Back, Katrin Christiane; Daake, Marina Angelika; Buchner, Johannes; Antes, Iris

2016-10-01

Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi-scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence-based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence-based prediction models were fitted using this and other peptide binding data. A structure-based position-specific scoring matrix (SB-PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB-PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA-based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi-scale pipeline can readily be applied to other protein-peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence-based prediction models is not available. Proteins 2016; 84:1390-1407. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Hunting for unexpected post-translational modifications by spectral library searching with tier-wise scoring.

PubMed

Ma, Chun Wai Manson; Lam, Henry

2014-05-02

Discovering novel post-translational modifications (PTMs) to proteins and detecting specific modification sites on proteins is one of the last frontiers of proteomics. At present, hunting for post-translational modifications remains challenging in widely practiced shotgun proteomics workflows due to the typically low abundance of modified peptides and the greatly inflated search space as more potential mass shifts are considered by the search engines. Moreover, most popular search methods require that the user specifies the modification(s) for which to search; therefore, unexpected and novel PTMs will not be detected. Here a new algorithm is proposed to apply spectral library searching to the problem of open modification searches, namely, hunting for PTMs without prior knowledge of what PTMs are in the sample. The proposed tier-wise scoring method intelligently looks for unexpected PTMs by allowing mass-shifted peak matches but only when the number of matches found is deemed statistically significant. This allows the search engine to search for unexpected modifications while maintaining its ability to identify unmodified peptides effectively at the same time. The utility of the method is demonstrated using three different data sets, in which the numbers of spectrum identifications to both unmodified and modified peptides were substantially increased relative to a regular spectral library search as well as to another open modification spectral search method, pMatch.

Signal peptide discrimination and cleavage site identification using SVM and NN.

PubMed

Kazemian, H B; Yusuf, S A; White, K

2014-02-01

About 15% of all proteins in a genome contain a signal peptide (SP) sequence, at the N-terminus, that targets the protein to intracellular secretory pathways. Once the protein is targeted correctly in the cell, the SP is cleaved, releasing the mature protein. Accurate prediction of the presence of these short amino-acid SP chains is crucial for modelling the topology of membrane proteins, since SP sequences can be confused with transmembrane domains due to similar composition of hydrophobic amino acids. This paper presents a cascaded Support Vector Machine (SVM)-Neural Network (NN) classification methodology for SP discrimination and cleavage site identification. The proposed method utilises a dual phase classification approach using SVM as a primary classifier to discriminate SP sequences from Non-SP. The methodology further employs NNs to predict the most suitable cleavage site candidates. In phase one, a SVM classification utilises hydrophobic propensities as a primary feature vector extraction using symmetric sliding window amino-acid sequence analysis for discrimination of SP and Non-SP. In phase two, a NN classification uses asymmetric sliding window sequence analysis for prediction of cleavage site identification. The proposed SVM-NN method was tested using Uni-Prot non-redundant datasets of eukaryotic and prokaryotic proteins with SP and Non-SP N-termini. Computer simulation results demonstrate an overall accuracy of 0.90 for SP and Non-SP discrimination based on Matthews Correlation Coefficient (MCC) tests using SVM. For SP cleavage site prediction, the overall accuracy is 91.5% based on cross-validation tests using the novel SVM-NN model. © 2013 Published by Elsevier Ltd.

Host-defense and trefoil factor family peptides in skin secretions of the Mawa clawed frog Xenopus boumbaensis (Pipidae).

PubMed

Conlon, J Michael; Mechkarska, Milena; Kolodziejek, Jolanta; Leprince, Jérôme; Coquet, Laurent; Jouenne, Thierry; Vaudry, Hubert; Nowotny, Norbert; King, Jay D

2015-10-01

Peptidomic analysis of norepinephrine-stimulated skin secretions from the octoploid Mawa clawed frog Xenopus boumbaensis Loumont, 1983 led to the identification and characterization of 15 host-defense peptides belonging to the magainin (two peptides), peptide glycine-leucine-amide (PGLa; three peptides), xenopsin precursor fragment (XPF; three peptides), caerulein precursor fragment (CPF; two peptides), and caerulein precursor fragment-related peptide (CPF-RP; five peptides) families. In addition, caerulein and three peptides with structural similarity to the trefoil factor family (TFF) peptides, xP2 and xP4 from Xenopus laevis were also present in the secretions. Consistent with data from comparisons of the nucleotides sequence of mitochondrial and nuclear genes, the primary structures of the peptides suggest a close phylogenetic relationship between X. boumbaensis and the octoploid frogs Xenopus amieti and Xenopus andrei. As the three species occupy disjunct ranges within Cameroon, it is suggested that they diverged from a common ancestor by allopatric speciation. Copyright © 2015 Elsevier Inc. All rights reserved.

Identification of RIP-II toxins by affinity enrichment, enzymatic digestion and LC-MS.

PubMed

Fredriksson, Sten-Åke; Artursson, Elisabet; Bergström, Tomas; Östin, Anders; Nilsson, Calle; Åstot, Crister

2015-01-20

Type 2 ribosome-inactivating protein toxins (RIP-II toxins) were enriched and purified prior to enzymatic digestion and LC-MS analysis. The enrichment of the RIP-II family of plant proteins, such as ricin, abrin, viscumin, and volkensin was based on their affinity for galactosyl moieties. A macroporous chromatographic material was modified with a galactose-terminated substituent and packed into miniaturized columns that were used in a chromatographic system to achieve up to 1000-fold toxin enrichment. The galactose affinity of the RIP-II proteins enabled their selective enrichment from water, beverages, and extracts of powder and wipe samples. The enriched fractions were digested with trypsin and RIP-II peptides were identified based on accurate mass LC-MS data. Their identities were unambiguously confirmed by LC-MS/MS product ion scans of peptides unique to each of the toxins. The LC-MS detection limit achieved for ricin target peptides was 10 amol and the corresponding detection limit for the full method was 10 fmol/mL (0.6 ng/mL). The affinity enrichment method was applied to samples from a forensic investigation into a case involving the illegal production of ricin and abrin toxins.

Developing a fluorescence-coupled capillary electrophoresis based method to probe interactions between QDs and colorectal cancer targeting peptides.

PubMed

Liu, Feifei; Wang, Jianhao; Yang, Li; Liu, Li; Ding, Shumin; Fu, Minli; Deng, Linhong; Gao, Li-Qian

2016-08-01

As is well known, quantum dots (QDs) have become valuable probes for cancer imaging. In particular, QD-labeled targeting peptides are capable of identifying cancer or tumors cells. A new colorectal cancer targeting peptide, cyclo(1, 9)-CTPSPFSHC, has strong targeting ability and also shows great potential in the identification and treatment of colon cancer. Herein, we synthesized a dual functional polypeptide, cyclo(1, 9)-CTPSPFSHCD2 G2 DP9 G3 H6 (H6 -TCP), to investigate its interaction with QDs inside the capillary. Fluorescence-coupled CE was adopted and applied to characterize the self-assembly of H6 -TCP onto QDs. It was indicated that the formation of the assembly was affected by H6 -TCP/QD molar ratio and sampling time. This novel in-capillary assay greatly reduced the sample consumption and the detection time, which was beneficial for the environment. It is expected that this kind of detection method could find more applications to provide more useful information for cancer diagnosis and detection of harm and hazardous substances/organisms in the environment in the future. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural Characterization and Absolute Quantification of Microcystin Peptides Using Collision-Induced and Ultraviolet Photo-Dissociation Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Attard, Troy J.; Carter, Melissa D.; Fang, Mengxuan; Johnson, Rudolph C.; Reid, Gavin E.

2018-05-01

Microcystin (MC) peptides produced by cyanobacteria pose a hepatotoxic threat to human health upon ingestion from contaminated drinking water. While rapid MC identification and quantification in contaminated body fluids or tissue samples is important for patient treatment and outcomes, conventional immunoassay-based measurement strategies typically lack the specificity required for unambiguous determination of specific MC variants, whose toxicity can significantly vary depending on their structures. Furthermore, the unambiguous identification and accurate quantitation of MC variants using tandem mass spectrometry (MS/MS)-based methods can be limited due to a current lack of appropriate stable isotope-labeled internal standards. To address these limitations, we have systematically examined here the sequence and charge state dependence to the formation and absolute abundance of both "global" and "variant-specific" product ions from representative MC-LR, MC-YR, MC-RR, and MC-LA peptides, using higher-energy collisional dissociation (HCD)-MS/MS, ion-trap collision-induced dissociation (CID)-MS/MS and CID-MS3, and 193 nm ultraviolet photodissociation (UPVD)-MS/MS. HCD-MS/MS was found to provide the greatest detection sensitivity for both global and variant-specific product ions in each of the MC variants, except for MC-YR where a variant-specific product uniquely formed via UPVD-MS/MS was observed with the greatest absolute abundance. A simple methodology for the preparation and characterization of 18O-stable isotope-labeled MC reference materials for use as internal standards was also developed. Finally, we have demonstrated the applicability of the methods developed herein for absolute quantification of MC-LR present in human urine samples, using capillary scale liquid chromatography coupled with ultra-high resolution / accurate mass spectrometry and HCD-MS/MS.

Identification of an HLA-A24-restricted OY-TES-1 epitope recognized by cytotoxic T-cells.

PubMed

Okumura, Hideo; Noguchi, Yuji; Uenaka, Akiko; Aji, Toshiki; Ono, Toshiro; Nakagawa, Kazuhiko; Aoe, Motoi; Shimizu, Nobuyoshi; Nakayama, Eiichi

2005-01-01

OY-TES-1 was identified as a human homologue of the mouse, guinea pig, and pig proacrosin binding protein sp32 precursor. Differential expression levels of OY-TES-1 mRNA between testis and other normal tissues, and its expression in cancers indicated that OY-TES-1 would be classified as a cancer/testis antigen and considered to be a candidate of target antigen for cancer immunotherapy. In this study, we showed identification of HLA-A24-binding OY-TES-1 peptide, TES(401-409) (KTPFVSPLL) recognized by CD8 T-cells. Purified CD8 T-cells from healthy donors stimulated in vitro with the peptide-pulsed autologous DC and PBMC produced IFNgamma in response to the peptide-pulsed PBMC and showed cytotoxicity against the peptide-pulsed autologous EBV-B specifically. Furthermore, cytotoxicity was also observed against an OY-TES-1 mRNA-expressing tumor line, LK79. The retention time of the fraction in HPLC of the acid eluate from LK79 cells that showed positive sensitization against autologous EBV-B cells in recognition by CD8 CTL was the same as that of the fraction of the TES(401-409) peptide itself, suggesting that the TES(401-409) was a naturally processed peptide on LK79.

High-throughput screening of T7 phage display and protein microarrays as a methodological approach for the identification of IgE-reactive components.

PubMed

San Segundo-Acosta, Pablo; Garranzo-Asensio, María; Oeo-Santos, Carmen; Montero-Calle, Ana; Quiralte, Joaquín; Cuesta-Herranz, Javier; Villalba, Mayte; Barderas, Rodrigo

2018-05-01

Olive pollen and yellow mustard seeds are major allergenic sources with high clinical relevance. To aid with the identification of IgE-reactive components, the development of sensitive methodological approaches is required. Here, we have combined T7 phage display and protein microarrays for the identification of allergenic peptides and mimotopes from olive pollen and mustard seeds. The identification of these allergenic sequences involved the construction and biopanning of T7 phage display libraries of mustard seeds and olive pollen using sera from allergic patients to both biological sources together with the construction of phage microarrays printed with 1536 monoclonal phages from the third/four rounds of biopanning. The screening of the phage microarrays with individual sera from allergic patients enabled the identification of 10 and 9 IgE-reactive unique amino acid sequences from olive pollen and mustard seeds, respectively. Five immunoreactive amino acid sequences displayed on phages were selected for their expression as His6-GST tag fusion proteins and validation. After immunological characterization, we assessed the IgE-reactivity of the constructs. Our results show that protein microarrays printed with T7 phages displaying peptides from allergenic sources might be used to identify allergenic components -peptides, proteins or mimotopes- through their screening with specific IgE antibodies from allergic patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative synthesis of genetically encoded glycopeptide libraries displayed on M13 phage.

PubMed

Ng, Simon; Jafari, Mohammad R; Matochko, Wadim L; Derda, Ratmir

2012-09-21

Phage display is a powerful technology that enables the discovery of peptide ligands for many targets. Chemical modification of phage libraries have allowed the identification of ligands with properties not encountered in natural polypeptides. In this report, we demonstrated the synthesis of 2 × 10(8) genetically encoded glycopeptides from a commercially available phage-displayed peptide library (Ph.D.-7) in a two-step, one-pot reaction in <1.5 h. Unlike previous reports, we bypassed genetic engineering of phage. The glycan moiety was introduced via an oxime ligation following oxidation of an N-terminal Ser/Thr; these residues are present in the peptide libraries at 20-30% abundance. The construction of libraries was facilitated by simple characterization, which directly assessed the yield and regioselectivity of chemical reactions performed on phage. This quantification method also allowed facile yield determination of reactions in 10(9) distinct molecules. We envision that the methodology described herein will find broad application in the synthesis of custom chemically modified phage libraries.

Comparing Simplification Strategies for the Skeletal Muscle Proteome

PubMed Central

Geary, Bethany; Young, Iain S.; Cash, Phillip; Whitfield, Phillip D.; Doherty, Mary K.

2016-01-01

Skeletal muscle is a complex tissue that is dominated by the presence of a few abundant proteins. This wide dynamic range can mask the presence of lower abundance proteins, which can be a confounding factor in large-scale proteomic experiments. In this study, we have investigated a number of pre-fractionation methods, at both the protein and peptide level, for the characterization of the skeletal muscle proteome. The analyses revealed that the use of OFFGEL isoelectric focusing yielded the largest number of protein identifications (>750) compared to alternative gel-based and protein equalization strategies. Further, OFFGEL led to a substantial enrichment of a different sub-population of the proteome. Filter-aided sample preparation (FASP), coupled to peptide-level OFFGEL provided more confidence in the results due to a substantial increase in the number of peptides assigned to each protein. The findings presented here support the use of a multiplexed approach to proteome characterization of skeletal muscle, which has a recognized imbalance in the dynamic range of its protein complement. PMID:28248220

Designing of interferon-gamma inducing MHC class-II binders

PubMed Central

2013-01-01

Background The generation of interferon-gamma (IFN-γ) by MHC class II activated CD4+ T helper cells play a substantial contribution in the control of infections such as caused by Mycobacterium tuberculosis. In the past, numerous methods have been developed for predicting MHC class II binders that can activate T-helper cells. Best of author’s knowledge, no method has been developed so far that can predict the type of cytokine will be secreted by these MHC Class II binders or T-helper epitopes. In this study, an attempt has been made to predict the IFN-γ inducing peptides. The main dataset used in this study contains 3705 IFN-γ inducing and 6728 non-IFN-γ inducing MHC class II binders. Another dataset called IFNgOnly contains 4483 IFN-γ inducing epitopes and 2160 epitopes that induce other cytokine except IFN-γ. In addition we have alternate dataset that contains IFN-γ inducing and equal number of random peptides. Results It was observed that the peptide length, positional conservation of residues and amino acid composition affects IFN-γ inducing capabilities of these peptides. We identified the motifs in IFN-γ inducing binders/peptides using MERCI software. Our analysis indicates that IFN-γ inducing and non-inducing peptides can be discriminated using above features. We developed models for predicting IFN-γ inducing peptides using various approaches like machine learning technique, motifs-based search, and hybrid approach. Our best model based on the hybrid approach achieved maximum prediction accuracy of 82.10% with MCC of 0.62 on main dataset. We also developed hybrid model on IFNgOnly dataset and achieved maximum accuracy of 81.39% with 0.57 MCC. Conclusion Based on this study, we have developed a webserver for predicting i) IFN-γ inducing peptides, ii) virtual screening of peptide libraries and iii) identification of IFN-γ inducing regions in antigen (http://crdd.osdd.net/raghava/ifnepitope/). Reviewers This article was reviewed by Prof Kurt Blaser, Prof Laurence Eisenlohr and Dr Manabu Sugai. PMID:24304645

Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach.

PubMed

Nielsen, Morten; Lundegaard, Claus; Worning, Peder; Hvid, Christina Sylvester; Lamberth, Kasper; Buus, Søren; Brunak, Søren; Lund, Ole

2004-06-12

Prediction of which peptides will bind a specific major histocompatibility complex (MHC) constitutes an important step in identifying potential T-cell epitopes suitable as vaccine candidates. MHC class II binding peptides have a broad length distribution complicating such predictions. Thus, identifying the correct alignment is a crucial part of identifying the core of an MHC class II binding motif. In this context, we wish to describe a novel Gibbs motif sampler method ideally suited for recognizing such weak sequence motifs. The method is based on the Gibbs sampling method, and it incorporates novel features optimized for the task of recognizing the binding motif of MHC classes I and II. The method locates the binding motif in a set of sequences and characterizes the motif in terms of a weight-matrix. Subsequently, the weight-matrix can be applied to identifying effectively potential MHC binding peptides and to guiding the process of rational vaccine design. We apply the motif sampler method to the complex problem of MHC class II binding. The input to the method is amino acid peptide sequences extracted from the public databases of SYFPEITHI and MHCPEP and known to bind to the MHC class II complex HLA-DR4(B1*0401). Prior identification of information-rich (anchor) positions in the binding motif is shown to improve the predictive performance of the Gibbs sampler. Similarly, a consensus solution obtained from an ensemble average over suboptimal solutions is shown to outperform the use of a single optimal solution. In a large-scale benchmark calculation, the performance is quantified using relative operating characteristics curve (ROC) plots and we make a detailed comparison of the performance with that of both the TEPITOPE method and a weight-matrix derived using the conventional alignment algorithm of ClustalW. The calculation demonstrates that the predictive performance of the Gibbs sampler is higher than that of ClustalW and in most cases also higher than that of the TEPITOPE method.

Compositions and methods involving methyladenosine phosphorylase in the diagnosis and treatment of proliferative disorders

DOEpatents

Olopade, Olufunmilayo I.

2007-03-20

Disclosed are novel nucleic acid and peptide compositions comprising methylthioadenosine phosphorylase (MTAP) and methods of use for MTAP amino acid sequences and DNA segments comprising MTAP in the diagnosis of human cancers and development of MTAP-specific antibodies. Also disclosed are methods for the diagnosis and treatment of tumors and other proliferative cell disorders, and identification of tumor suppressor genes and gene products from the human 9p21-p22 chromosome region. Such methods are useful in the diagnosis of multiple tumor types such as bladder cancer, lung cancer, breast cancer, pancreatic cancer, brain tumors, lymphomas, gliomas, melanomas, and leukemias.

Assigning Peptide Disulfide Linkage Pattern Among Regio-Isomers via Methoxy Addition to Disulfide and Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Durand, Kirt L.; Tan, Lei; Stinson, Craig A.; Love-Nkansah, Chasity B.; Ma, Xiaoxiao; Xia, Yu

2017-06-01

Pinpointing disulfide linkage pattern is critical in the characterization of proteins and peptides consisting of multiple disulfide bonds. Herein, we report a method based on coupling online disulfide modification and tandem mass spectrometry (MS/MS) to distinguish peptide disulfide regio-isomers. Such a method relies on a new disulfide bond cleavage reaction in solution, involving methanol as a reactant and 254 nm ultraviolet (UV) irradiation. This reaction leads to selective cleavage of a disulfide bond and formation of sulfenic methyl ester (-SOCH3) at one cysteine residue and a thiol (-SH) at the other. Under low energy collision-induced dissociation (CID), cysteine sulfenic methyl ester motif produces a signature methanol loss (-32 Da), allowing its identification from other possible isomeric structures such as S-hydroxylmethyl (-SCH2OH) and methyl sulfoxide (-S(O)-CH3). Since disulfide bond can be selectively cleaved and modified upon methoxy addition, subsequent MS2 CID of the methoxy addition product provides enhanced sequence coverage as demonstrated by the analysis of bovine insulin. More importantly, this reaction does not induce disulfide scrambling, likely due to the fact that radical intermediates are not involved in the process. An approach based on methoxy addition followed by MS3 CID has been developed for assigning disulfide linkage patterns in peptide disulfide regio-isomers. This methodology was successfully applied to characterizing peptide systems having two disulfide bonds and three disulfide linkage isomers: side-by-side, overlapped, and looped-within-a-loop configurations. [Figure not available: see fulltext.

Identification and analysis of cytochrome P450IID6 antigenic sites recognized by anti-liver-kidney microsome type-1 antibodies (LKM1).

PubMed

Yamamoto, A M; Cresteil, D; Boniface, O; Clerc, F F; Alvarez, F

1993-05-01

Anti-liver-kidney microsome type-1 antibodies (LKM1), present in sera from a group of patients with autoimmune hepatitis, are directed against P450IID6. Previous work, using cDNA constructions spanning most of the P450IID6 protein defined the main immunogenic site between the amino acids (aa), 254-271 and predicted the presence of other putative immunogenic sites in the molecule. Fusion proteins from new cDNA constructions, spanning so-far-untested regions between aa 1-125 and 431-522, were not recognized by LKM1-positive sera. Synthetic peptides, representing sequences from putative immunogenic regions or previously untested regions, allowed a precise definition of four antigenic sites located between peptides 257-269, 321-351, 373-389 and 410-429, which were recognized, respectively, by 14, 8, 1 and 2 out of 15 LKM1-positive sera tested. The minimal sequence of the main antigenic site (peptide 257-269) recognized by the autoantibody was established to be WDPAQPPRD (peptide 262-270). In addition, deletion and replacement experiments showed that aa 263 (Asp) was essential for the binding of the autoantibody to peptide 262-270. Analysis of the second most frequently recognized peptide between aa 321-351, was performed using peptides 321-339 and 340-351 in competitive inhibition studies. Complete elimination of antibody binding to peptide 321-351 obtained by absorption of both shorter peptides indicated that peptide 321-351 is a discontinuous antigenic site. LKM1-positive sera reacting against peptide 321-351 recognized either both the shorter peptides or just one of them preferentially. Results of the present study suggest that the production of LKM1 antibodies is an antigen-driven, poly- or oligoclonal B cell response. The identification of antigenic sites will allow: (i) the development of specific diagnostic tests and (ii) further studies on the pathogenic value of LKM1 antibodies in autoimmune hepatitis.

Identification of small ORFs in vertebrates using ribosome footprinting and evolutionary conservation

PubMed Central

Bazzini, Ariel A; Johnstone, Timothy G; Christiano, Romain; Mackowiak, Sebastian D; Obermayer, Benedikt; Fleming, Elizabeth S; Vejnar, Charles E; Lee, Miler T; Rajewsky, Nikolaus; Walther, Tobias C; Giraldez, Antonio J

2014-01-01

Identification of the coding elements in the genome is a fundamental step to understanding the building blocks of living systems. Short peptides (< 100 aa) have emerged as important regulators of development and physiology, but their identification has been limited by their size. We have leveraged the periodicity of ribosome movement on the mRNA to define actively translated ORFs by ribosome footprinting. This approach identifies several hundred translated small ORFs in zebrafish and human. Computational prediction of small ORFs from codon conservation patterns corroborates and extends these findings and identifies conserved sequences in zebrafish and human, suggesting functional peptide products (micropeptides). These results identify micropeptide-encoding genes in vertebrates, providing an entry point to define their function in vivo. PMID:24705786

Cholera toxin can catalyze ADP-ribosylation of cytoskeletal proteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaslow, H.R.; Groppi, V.E.; Abood, M.E.

1981-11-01

Cholera toxin catalyzes transfer of radiolabel from (/sup 32/P)NAD/sup +/ to several peptides in particulate preparations of human foreskin fibroblasts. Resolution of these peptides by two-dimensional gel electrophoresis allowed identification of two peptides of M/sub r/ = 42,000 and 52,000 as peptide subunits of a regulatory component of adenylate cyclase. The radiolabeling of another group of peptides (M/sub r/ = 50,000 to 65,000) suggested that cholera toxin could catalyze ADP-ribosylation of cytoskeletal proteins. This suggestion was confirmed by showing that incubation with cholera toxin and (/sup 32/P)NAD/sup +/ caused radiolabeling of purified microtubule and intermediate filament proteins.

Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.

PubMed

Seng, Piseth; Drancourt, Michel; Gouriet, Frédérique; La Scola, Bernard; Fournier, Pierre-Edouard; Rolain, Jean Marc; Raoult, Didier

2009-08-15

Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry accurately identifies both selected bacteria and bacteria in select clinical situations. It has not been evaluated for routine use in the clinic. We prospectively analyzed routine MALDI-TOF mass spectrometry identification in parallel with conventional phenotypic identification of bacteria regardless of phylum or source of isolation. Discrepancies were resolved by 16S ribosomal RNA and rpoB gene sequence-based molecular identification. Colonies (4 spots per isolate directly deposited on the MALDI-TOF plate) were analyzed using an Autoflex II Bruker Daltonik mass spectrometer. Peptidic spectra were compared with the Bruker BioTyper database, version 2.0, and the identification score was noted. Delays and costs of identification were measured. Of 1660 bacterial isolates analyzed, 95.4% were correctly identified by MALDI-TOF mass spectrometry; 84.1% were identified at the species level, and 11.3% were identified at the genus level. In most cases, absence of identification (2.8% of isolates) and erroneous identification (1.7% of isolates) were due to improper database entries. Accurate MALDI-TOF mass spectrometry identification was significantly correlated with having 10 reference spectra in the database (P=.01). The mean time required for MALDI-TOF mass spectrometry identification of 1 isolate was 6 minutes for an estimated 22%-32% cost of current methods of identification. MALDI-TOF mass spectrometry is a cost-effective, accurate method for routine identification of bacterial isolates in <1 h using a database comprising > or =10 reference spectra per bacterial species and a 1.9 identification score (Brucker system). It may replace Gram staining and biochemical identification in the near future.

Development of a dedicated peptide tandem mass spectral library for conservation science.

PubMed

Fremout, Wim; Dhaenens, Maarten; Saverwyns, Steven; Sanyova, Jana; Vandenabeele, Peter; Deforce, Dieter; Moens, Luc

2012-05-30

In recent years, the use of liquid chromatography tandem mass spectrometry (LC-MS/MS) on tryptic digests of cultural heritage objects has attracted much attention. It allows for unambiguous identification of peptides and proteins, and even in complex mixtures species-specific identification becomes feasible with minimal sample consumption. Determination of the peptides is commonly based on theoretical cleavage of known protein sequences and on comparison of the expected peptide fragments with those found in the MS/MS spectra. In this approach, complex computer programs, such as Mascot, perform well identifying known proteins, but fail when protein sequences are unknown or incomplete. Often, when trying to distinguish evolutionarily well preserved collagens of different species, Mascot lacks the required specificity. Complementary and often more accurate information on the proteins can be obtained using a reference library of MS/MS spectra of species-specific peptides. Therefore, a library dedicated to various sources of proteins in works of art was set up, with an initial focus on collagen rich materials. This paper discusses the construction and the advantages of this spectral library for conservation science, and its application on a number of samples from historical works of art. Copyright © 2012 Elsevier B.V. All rights reserved.

Identification of trimannoside-recognizing peptide sequences from a T7 phage display screen using a QCM device.

PubMed

Nishiyama, Kazusa; Takakusagi, Yoichi; Kusayanagi, Tomoe; Matsumoto, Yuki; Habu, Shiori; Kuramochi, Kouji; Sugawara, Fumio; Sakaguchi, Kengo; Takahashi, Hideyo; Natsugari, Hideaki; Kobayashi, Susumu

2009-01-01

Here, we report on the identification of trimannoside-recognizing peptide sequences from a T7 phage display screen using a quartz-crystal microbalance (QCM) device. A trimannoside derivative that can form a self-assembled monolayer (SAM) was synthesized and used for immobilization on the gold electrode surface of a QCM sensor chip. After six sets of one-cycle affinity selection, T7 phage particles displaying PSVGLFTH (8-mer) and SVGLGLGFSTVNCF (14-mer) were found to be enriched at a rate of 17/44, 9/44, respectively, suggesting that these peptides specifically recognize trimannoside. Binding checks using the respective single T7 phage and synthetic peptide also confirmed the specific binding of these sequences to the trimannoside-SAM. Subsequent analysis revealed that these sequences correspond to part of the primary amino acid sequence found in many mannose- or hexose-related proteins. Taken together, these results demonstrate the effectiveness of our T7 phage display environment for affinity selection of binding peptides. We anticipate this screening result will also be extremely useful in the development of inhibitors or drug delivery systems targeting polysaccharides as well as further investigations into the function of carbohydrates in vivo.

Identification of multiply charged proteins and amino acid clusters by liquid nitrogen assisted spray ionization mass spectrometry.

PubMed

Kumar Kailasa, Suresh; Hasan, Nazim; Wu, Hui-Fen

2012-08-15

The development of liquid nitrogen assisted spray ionization mass spectrometry (LNASI MS) for the analysis of multiply charged proteins (insulin, ubiquitin, cytochrome c, α-lactalbumin, myoglobin and BSA), peptides (glutathione, HW6, angiotensin-II and valinomycin) and amino acid (arginine) clusters is described. The charged droplets are formed by liquid nitrogen assisted sample spray through a stainless steel nebulizer and transported into mass analyzer for the identification of multiply charged protein ions. The effects of acids and modifier volumes for the efficient ionization of the above analytes in LNASI MS were carefully investigated. Multiply charged proteins and amino acid clusters were effectively identified by LNASI MS. The present approach can effectively detect the multiply charged states of cytochrome c at 400 nM. A comparison between LNASI and ESI, CSI, SSI and V-EASI methods on instrumental conditions, applied temperature and observed charge states for the multiply charged proteins, shows that the LNASI method produces the good quality spectra of amino acid clusters at ambient conditions without applied any electric field and heat. To date, we believe that the LNASI method is the most simple, low cost and provided an alternative paradigm for production of multiply charged ions by LNASI MS, just as ESI-like ions yet no need for applying any electrical field and it could be operated at low temperature for generation of highly charged protein/peptide ions. Copyright © 2012 Elsevier B.V. All rights reserved.

Identification, Characterization, and Recombinant Expression of Epidermicin NI01, a Novel Unmodified Bacteriocin Produced by Staphylococcus epidermidis That Displays Potent Activity against Staphylococci

PubMed Central

Sandiford, Stephanie

2012-01-01

We describe the discovery, purification, characterization, and expression of an antimicrobial peptide, epidermicin NI01, which is an unmodified bacteriocin produced by Staphylococcus epidermidis strain 224. It is a highly cationic, hydrophobic, plasmid-encoded peptide that exhibits potent antimicrobial activity toward a wide range of pathogenic Gram-positive bacteria including methicillin-resistant Staphylococcus aureus (MRSA), enterococci, and biofilm-forming S. epidermidis strains. Purification of the peptide was achieved using a combination of hydrophobic interaction, cation exchange, and high-performance liquid chromatography (HPLC). Matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) analysis yielded a molecular mass of 6,074 Da, and partial sequence data of the peptide were elucidated using a combination of tandem mass spectrometry (MS/MS) and de novo sequencing. The draft genome sequence of the producing strain was obtained using 454 pyrosequencing technology, thus enabling the identification of the structural gene using the de novo peptide sequence data previously obtained. Epidermicin NI01 contains 51 residues with four tryptophan and nine lysine residues, and the sequence showed approximately 50% identity to peptides lacticin Z, lacticin Q, and aureocin A53, all of which belong to a new family of unmodified type II-like bacteriocins. The peptide is active in the nanomolar range against S. epidermidis, MRSA isolates, and vancomycin-resistant enterococci. Other unique features displayed by epidermicin include a high degree of protease stability and the ability to retain antimicrobial activity over a pH range of 2 to 10, and exposure to the peptide does not result in development of resistance in susceptible isolates. In this study we also show the structural gene alone can be cloned into Escherichia coli strain BL21(DE3), and expression yields active peptide. PMID:22155816

Identification and mapping of linear antibody epitopes in human serum albumin using high-density Peptide arrays.

PubMed

Hansen, Lajla Bruntse; Buus, Soren; Schafer-Nielsen, Claus

2013-01-01

We have recently developed a high-density photolithographic, peptide array technology with a theoretical upper limit of 2 million different peptides per array of 2 cm(2). Here, we have used this to perform complete and exhaustive analyses of linear B cell epitopes of a medium sized protein target using human serum albumin (HSA) as an example. All possible overlapping 15-mers from HSA were synthesized and probed with a commercially available polyclonal rabbit anti-HSA antibody preparation. To allow for identification of even the weakest epitopes and at the same time perform a detailed characterization of key residues involved in antibody binding, the array also included complete single substitution scans (i.e. including each of the 20 common amino acids) at each position of each 15-mer peptide. As specificity controls, all possible 15-mer peptides from bovine serum albumin (BSA) and from rabbit serum albumin (RSA) were included as well. The resulting layout contained more than 200.000 peptide fields and could be synthesized in a single array on a microscope slide. More than 20 linear epitope candidates were identified and characterized at high resolution i.e. identifying which amino acids in which positions were needed, or not needed, for antibody interaction. As expected, moderate cross-reaction with some peptides in BSA was identified whereas no cross-reaction was observed with peptides from RSA. We conclude that high-density peptide microarrays are a very powerful methodology to identify and characterize linear antibody epitopes, and should advance detailed description of individual specificities at the single antibody level as well as serologic analysis at the proteome-wide level.

Random and independent sampling of endogenous tryptic peptides from normal human EDTA plasma by liquid chromatography micro electrospray ionization and tandem mass spectrometry.

PubMed

Dufresne, Jaimie; Florentinus-Mefailoski, Angelique; Ajambo, Juliet; Ferwa, Ammara; Bowden, Peter; Marshall, John

2017-01-01

Normal human EDTA plasma samples were collected on ice, processed ice cold, and stored in a freezer at - 80 °C prior to experiments. Plasma test samples from the - 80 °C freezer were thawed on ice or intentionally warmed to room temperature. Protein content was measured by CBBR binding and the release of alcohol soluble amines by the Cd ninhydrin assay. Plasma peptides released over time were collected over C18 for random and independent sampling by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) and correlated with X!TANDEM. Fully tryptic peptides by X!TANDEM returned a similar set of proteins, but was more computationally efficient, than "no enzyme" correlations. Plasma samples maintained on ice, or ice with a cocktail of protease inhibitors, showed lower background amounts of plasma peptides compared to samples incubated at room temperature. Regression analysis indicated that warming plasma to room temperature, versus ice cold, resulted in a ~ twofold increase in the frequency of peptide identification over hours-days of incubation at room temperature. The type I error rate of the protein identification from the X!TANDEM algorithm combined was estimated to be low compared to a null model of computer generated random MS/MS spectra. The peptides of human plasma were identified and quantified with low error rates by random and independent sampling that revealed 1000s of peptides from hundreds of human plasma proteins from endogenous tryptic peptides.

Identification and in silico characterization of a novel peptide inhibitor of angiotensin converting enzyme from pigeon pea (Cajanus cajan).

PubMed

Nawaz, K A Ayub; David, Swapna Merlin; Murugesh, Easwaran; Thandeeswaran, Murugesan; Kiran, Kalarikkal Gopikrishnan; Mahendran, Ramasamy; Palaniswamy, Muthusamy; Angayarkanni, Jayaraman

2017-12-01

Plants are important sources of bioactive peptides. Among these, angiotensin converting enzyme (ACE) inhibitory peptides have a major focus on their ability to prevent hypertension. Inhibition of ACE has been established as an effective approach for the treatment of ACE associated diseases. Some synthetic ACE inhibitory drugs cause side effects and hence there is a constant interest in natural compounds as alternatives. The study was designed to identify and characterize a peptide molecule from pigeon pea which has the biological property to inhibit ACE and can be developed as a therapeutic approach towards hypertension. Seeds of pigeon pea (Cajanus cajan (L.) Millsp.) was fermented with Aspergillus niger, a proteolytic fungus isolated from spoiled milk sweet. The extract was purified by size exclusion chromatography by FPLC system. The fractions that showed ACE inhibition was subjected to LC-MS/MS for sequence identification. The stability of the peptide was analyzed by molecular dynamic simulations and the interaction sites with ACE were identified by molecular docking. The study report a novel ACE inhibitory octapeptide Val-Val-Ser-Leu-Ser-Ile-Pro-Arg with a molecular mass of 869.53 Da. The Lineweaver-Burk plot indicated that the inhibition of ACE by this peptide is in competitive mode. Also, molecular docking and simulation studies showed a strong and stable interaction of the peptide with ACE. The results clearly show the inhibitory property of the peptide against ACE and hence it can be explored as a therapeutic strategy towards hypertension and other ACE associated diseases. Copyright © 2017 Elsevier GmbH. All rights reserved.

Screening and identification of RhD antigen mimic epitopes from a phage display random peptide library for the serodiagnosis of haemolytic disease of the foetus and newborn.

PubMed

Wang, Jiao; Song, Jingjing; Zhou, Shuimei; Fu, Yourong; Bailey, Jeffrey A; Shen, Changxin

2018-01-16

Identification of RhD antigen epitopes is a key component in understanding the pathogenesis of haemolytic disease of the foetus and newborn. Research has indicated that phage display libraries are useful tools for identifying novel mimic epitopes (mimotopes) which may help to determine antigen specificity. We selected the mimotopes of blood group RhD antigen by affinity panning a phage display library using monoclonal anti-D. After three rounds of biopanning, positive phage clones were identified by enzyme-linked immunosorbent assay (ELISA) and then sent for sequencing and peptides synthesis. Next, competitive ELISA and erythrocyte haemagglutination inhibition tests were carried out to confirm the inhibitory activity of the synthetic peptide. To evaluate the diagnostic performance of the synthetic peptide, a diagnostic ELISA was examined. Fourteen of 35 phage clones that were chosen randomly from the titering plate were considered to be positive. Following DNA sequencing and translation, 11 phage clones were found to represent the same peptide - RMKMLMMLMRRK (P4) - whereas each of the other three clones represented a unique peptide. Through the competitive ELISA and erythrocyte haemagglutination inhibition tests, the peptide (P4) was verified to have the ability to mimic the RhD antigen. The diagnostic ELISA for P4 proved to be sensitive (82.61%) and specific (88.57%). This study reveals that the P4 peptide can mimic RhD antigen and paves the way for the development of promising targeted diagnostic and therapeutic platforms for haemolytic disease of the foetus and newborn.

An accurate proteomic quantification method: fluorescence labeling absolute quantification (FLAQ) using multidimensional liquid chromatography and tandem mass spectrometry.

PubMed

Liu, Junyan; Liu, Yang; Gao, Mingxia; Zhang, Xiangmin

2012-08-01

A facile proteomic quantification method, fluorescent labeling absolute quantification (FLAQ), was developed. Instead of using MS for quantification, the FLAQ method is a chromatography-based quantification in combination with MS for identification. Multidimensional liquid chromatography (MDLC) with laser-induced fluorescence (LIF) detection with high accuracy and tandem MS system were employed for FLAQ. Several requirements should be met for fluorescent labeling in MS identification: Labeling completeness, minimum side-reactions, simple MS spectra, and no extra tandem MS fragmentations for structure elucidations. A fluorescence dye, 5-iodoacetamidofluorescein, was finally chosen to label proteins on all cysteine residues. The fluorescent dye was compatible with the process of the trypsin digestion and MALDI MS identification. Quantitative labeling was achieved with optimization of reacting conditions. A synthesized peptide and model proteins, BSA (35 cysteines), OVA (five cysteines), were used for verifying the completeness of labeling. Proteins were separated through MDLC and quantified based on fluorescent intensities, followed by MS identification. High accuracy (RSD% < 1.58) and wide linearity of quantification (1-10(5) ) were achieved by LIF detection. The limit of quantitation for the model protein was as low as 0.34 amol. Parts of proteins in human liver proteome were quantified and demonstrated using FLAQ. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

8 Allergenic Composition of Polymerized Allergen Extracts of Betula verrucosa, Dermatophagoides Pteronyssinus and Phleum Pratense

PubMed Central

Fernandez-Caldas, Enrique; Cases, Barbara; Tudela, Jose Ignacio; Fernandez, Eva Abel; Casanovas, Miguel; Subiza, Jose Luis

2012-01-01

Background Allergoids have been successfully used in the treatment of respiratory allergic diseases. They are modified allergen extracts that allow the administration of high allergen doses, due to their reduced IgE binding capacity.They maintain allergen-specific T-cell recognition. Since they are native allergen extracts that have been polymerized with glutaraldehyde, identification of the allergenic molecules requires more complicated methods. The aim of the study was to determine the qualitative composition of different polymerized extracts and investigate the presence of defined allergenic molecules using Mass spectrometry. Methods Proteomic analysis was carried out at the Proteomics Facility of the Hospital Nacional de Parapléjicos (Toledo, Spain). After reduction and alkylation, proteins were digested with trypsin and the resulting peptides were cleaned using C18 SpinTips Sample Prep Kit; peptides were separated on an Ultimate nano-LC system using a Monolithic C18 column in combination with a precolumn for salt removal. Fractionation of the peptides was performed with a Probot microfraction collector and MS and MS/MS analysis of offline spotted peptide samples were performed using the Applied Biosystems 4800 plus MALDI TOF/TOF Analyzer mass spectrometer. ProteinPilot Software V 2.0.1 and the Paragon algorithm were used for the identification of the proteins. Each MS/MS spectrum was searched against the SwissProt 2010_10 database, Uniprot-Viridiplantae database and Uniprot_Betula database. Results Analysis of the peptides revealed the presence of native allergens in the polymerized extracts: Der p 1, Der p 2, Der p 3, Der p 8 and Der p 11 in D. pteronyssinus; Bet v 2, Bet v 6, Bet v 7 and several Bet v 1 isoforms in B. verrucosa and Phl p 1, Phl p 3, Phl p 5, Phl p 11 and Phl p 12 in P. pratense allergoids. In all cases, potential allergenic proteins were also identified, including ubiquitin, actin, Eenolase, fructose-bisphosphate aldolase, luminal-binding protein (Heat shock protein 70), calmodulin, among others. Conclusions The characterization of the allergenic composition of allergoids is possible using MS/MS analysis. The analysis confirms the presence of native allergens in the allergoids. Mayor allergens are preserved during polymerization.

Identification of novel bacteriophage peptides using a combination of gene sequence LC-MS-MS analysis and BLASTP

USDA-ARS?s Scientific Manuscript database

Introduction: In an effort to characterize novel bacteriophage with lytic activity against pathogenic E.coli associated with foodborne illness, gene sequencing and mass spectrometry have been used to identify expressed peptides which differentiate isolated bacteriophage from other known phage. Here,...

Peptidomics approach to elucidate the proteolytic regulation of bioactive peptides

PubMed Central

Kim, Yun-Gon; Lone, Anna Mari; Nolte, Whitney M.; Saghatelian, Alan

2012-01-01

Peptide hormones and neuropeptides have important roles in physiology and therefore the regulation of these bioactive peptides is of great interest. In some cases proteolysis controls the concentrations and signaling of bioactive peptides, and the peptidases that mediate this biochemistry have proven to be extremely successful drug targets. Due to the lack of any general method to identify these peptidases, however, the role of proteolysis in the regulation of most neuropeptides and peptide hormones is unknown. This limitation prompted us to develop an advanced peptidomics-based strategy to identify the peptidases responsible for the proteolysis of significant bioactive peptides. The application of this approach to calcitonin gene-related peptide (CGRP), a neuropeptide associated with blood pressure and migraine, revealed the endogenous CGRP cleavage sites. This information was then used to biochemically purify the peptidase capable of proteolysis of CGRP at those cleavage sites, which led to the identification of insulin-degrading enzyme (IDE) as a candidate CGRP-degrading enzyme. CGRP had not been identified as an IDE substrate before and we tested the physiological relevance of this interaction by quantitative measurements of CGRP using IDE null (IDE−/−) mice. In the absence of IDE, full-length CGRP levels are elevated in vivo, confirming IDE as an endogenous CGRP-degrading enzyme. By linking CGRP and IDE, this strategy uncovers a previously unknown pathway for CGRP regulation and characterizes an additional role for IDE. More generally, this work suggests that this may be an effective general strategy for characterizing these pathways and peptidases moving forward. PMID:22586115

Comprehensive analysis of proteins of pH fractionated samples using monolithic LC/MS/MS, intact MW measurement and MALDI-QIT-TOF MS

PubMed Central

Yoo, Chul; Patwa, Tasneem H.; Kreunin, Paweena; Miller, Fred R.; Huber, Christian G.; Nesvizhskii, Alexey I.; Lubman, David M.

2012-01-01

A comprehensive platform that integrates information from the protein and peptide levels by combining various MS techniques has been employed for the analysis of proteins in fully malignant human breast cancer cells. The cell lysates were subjected to chromatofocusing fractionation, followed by tryptic digestion of pH fractions for on-line monolithic RP-HPLC interfaced with linear ion trap MS analysis for rapid protein identification. This unique approach of direct analysis of pH fractions resulted in the identification of large numbers of proteins from several selected pH fractions, in which approximately 1.5 μg of each of the pH fraction digests was consumed for an analysis time of ca 50 min. In order to combine valuable information retained at the protein level with the protein identifications obtained from the peptide level information, the same pH fraction was analyzed using nonporous (NPS)-RP-HPLC/ESI-TOF MS to obtain intact protein MW measurements. In order to further validate the protein identification procedures from the fraction digest analysis, NPS-RP-HPLC separation was performed for off-line protein collection to closely examine each protein using MALDI-TOF MS and MALDI-quadrupole ion trap (QIT)-TOF MS, and excellent agreement of protein identifications was consistently observed. It was also observed that the comparison to intact MW and other MS information was particularly useful for analyzing proteins whose identifications were suggested by one sequenced peptide from fraction digest analysis. PMID:17206599

Structure and further fragmentation of significant [a3 + Na - H]+ ions from sodium-cationized peptides.

PubMed

Wang, Huixin; Wang, Bing; Wei, Zhonglin; Zhang, Hao; Guo, Xinhua

2015-01-01

A good understanding of gas-phase fragmentation chemistry of peptides is important for accurate protein identification. Additional product ions obtained by sodiated peptides can provide useful sequence information supplementary to protonated peptides and improve protein identification. In this work, we first demonstrate that the sodiated a3 ions are abundant in the tandem mass spectra of sodium-cationized peptides although observations of a3 ions have rarely been reported in protonated peptides. Quantum chemical calculations combined with tandem mass spectrometry are used to investigate this phenomenon by using a model tetrapeptide GGAG. Our results reveal that the most stable [a3 + Na - H](+) ion is present as a bidentate linear structure in which the sodium cation coordinates to the two backbone carbonyl oxygen atoms. Due to structural inflexibility, further fragmentation of the [a3 + Na - H](+) ion needs to overcome several relatively high energetic barriers to form [b2 + Na - H](+) ion with a diketopiperazine structure. As a result, low abundance of [b2 + Na - H](+) ion is detected at relatively high collision energy. In addition, our computational data also indicate that the common oxazolone pathway to generate [b2 + Na - H](+) from the [a3 + Na - H](+) ion is unlikely. The present work provides a mechanistic insight into how a sodium ion affects the fragmentation behaviors of peptides. Copyright © 2015 John Wiley & Sons, Ltd.

Molecular identification of poisonous mushrooms using nuclear ITS region and peptide toxins: a retrospective study on fatal cases in Thailand.

PubMed

Parnmen, Sittiporn; Sikaphan, Sujitra; Leudang, Siriwan; Boonpratuang, Thitiya; Rangsiruji, Achariya; Naksuwankul, Khwanruan

2016-02-01

Cases of mushroom poisoning in Thailand have increased annually. During 2008 to 2014, the cases reported to the National Institute of Health included 57 deaths; at least 15 died after ingestion of amanitas, the most common lethal wild mushrooms inhabited. Hence, the aims of this study were to identify mushroom samples from nine clinically reported cases during the 7-year study period based on nuclear ITS sequence data and diagnose lethal peptide toxins using a reversed phase LC-MS method. Nucleotide similarity was identified using BLAST search of the NCBI database and the Barcode of Life Database (BOLD). Clade characterization was performed by maximum likelihood and Bayesian phylogenetic approaches. Based on BLAST and BOLD reference databases our results yielded high nucleotide similarities of poisonous mushroom samples to A. exitialis and A. fuliginea. Detailed phylogenetic analyses showed that all mushroom samples fall into their current classification. Detection of the peptide toxins revealed the presence of amatoxins and phallotoxins in A. exitialis and A. fuliginea. In addition, toxic α-amanitin was identified in a new provisional species, Amanita sp.1, with the highest toxin quantity. Molecular identification confirmed that the mushrooms ingested by the patients were members of the lethal amanitas in the sections Amanita and Phalloideae. In Thailand, the presence of A. exitialis was reported here for the first time and all three poisonous mushroom species provided new and informative data for clinical studies.

When is Mass Spectrometry Combined with Affinity Approaches Essential? A Case Study of Tyrosine Nitration in Proteins

NASA Astrophysics Data System (ADS)

Petre, Brînduşa-Alina; Ulrich, Martina; Stumbaum, Mihaela; Bernevic, Bogdan; Moise, Adrian; Döring, Gerd; Przybylski, Michael

2012-11-01

Tyrosine nitration in proteins occurs under physiologic conditions and is increased at disease conditions associated with oxidative stress, such as inflammation and Alzheimer's disease. Identification and quantification of tyrosine-nitrations are crucial for understanding nitration mechanism(s) and their functional consequences. Mass spectrometry (MS) is best suited to identify nitration sites, but is hampered by low stabilities and modification levels and possible structural changes induced by nitration. In this insight, we discuss methods for identifying and quantifying nitration sites by proteolytic affinity extraction using nitrotyrosine (NT)-specific antibodies, in combination with electrospray-MS. The efficiency of this approach is illustrated by identification of specific nitration sites in two proteins in eosinophil granules from several biological samples, eosinophil-cationic protein (ECP) and eosinophil-derived neurotoxin (EDN). Affinity extraction combined with Edman sequencing enabled the quantification of nitration levels, which were found to be 8 % and 15 % for ECP and EDN, respectively. Structure modeling utilizing available crystal structures and affinity studies using synthetic NT-peptides suggest a tyrosine nitration sequence motif comprising positively charged residues in the vicinity of the NT- residue, located at specific surface- accessible sites of the protein structure. Affinities of Tyr-nitrated peptides from ECP and EDN to NT-antibodies, determined by online bioaffinity- MS, provided nanomolar KD values. In contrast, false-positive identifications of nitrations were obtained in proteins from cystic fibrosis patients upon using NT-specific antibodies, and were shown to be hydroxy-tyrosine modifications. These results demonstrate affinity- mass spectrometry approaches to be essential for unequivocal identification of biological tyrosine nitrations.

Decoding the Effect of Isobaric Substitutions on Identifying Missing Proteins and Variant Peptides in Human Proteome.

PubMed

Choong, Wai-Kok; Lih, Tung-Shing Mamie; Chen, Yu-Ju; Sung, Ting-Yi

2017-12-01

To confirm the existence of missing proteins, we need to identify at least two unique peptides with length of 9-40 amino acids of a missing protein in bottom-up mass-spectrometry-based proteomic experiments. However, an identified unique peptide of the missing protein, even identified with high level of confidence, could possibly coincide with a peptide of a commonly observed protein due to isobaric substitutions, mass modifications, alternative splice isoforms, or single amino acid variants (SAAVs). Besides unique peptides of missing proteins, identified variant peptides (SAAV-containing peptides) could also alternatively map to peptides of other proteins due to the aforementioned issues. Therefore, we conducted a thorough comparative analysis on data sets in PeptideAtlas Tiered Human Integrated Search Proteome (THISP, 2017-03 release), including neXtProt (2017-01 release), to systematically investigate the possibility of unique peptides in missing proteins (PE2-4), unique peptides in dubious proteins, and variant peptides affected by isobaric substitutions, causing doubtful identification results. In this study, we considered 11 isobaric substitutions. From our analysis, we found <5% of the unique peptides of missing proteins and >6% of variant peptides became shared with peptides of PE1 proteins after isobaric substitutions.

Enzyme-Assisted Discovery of Antioxidant Peptides from Edible Marine Invertebrates: A Review

PubMed Central

Chai, Tsun-Thai; Law, Yew-Chye; Wong, Fai-Chu; Kim, Se-Kwon

2017-01-01

Marine invertebrates, such as oysters, mussels, clams, scallop, jellyfishes, squids, prawns, sea cucumbers and sea squirts, are consumed as foods. These edible marine invertebrates are sources of potent bioactive peptides. The last two decades have seen a surge of interest in the discovery of antioxidant peptides from edible marine invertebrates. Enzymatic hydrolysis is an efficient strategy commonly used for releasing antioxidant peptides from food proteins. A growing number of antioxidant peptide sequences have been identified from the enzymatic hydrolysates of edible marine invertebrates. Antioxidant peptides have potential applications in food, pharmaceuticals and cosmetics. In this review, we first give a brief overview of the current state of progress of antioxidant peptide research, with special attention to marine antioxidant peptides. We then focus on 22 investigations which identified 32 antioxidant peptides from enzymatic hydrolysates of edible marine invertebrates. Strategies adopted by various research groups in the purification and identification of the antioxidant peptides will be summarized. Structural characteristic of the peptide sequences in relation to their antioxidant activities will be reviewed. Potential applications of the peptide sequences and future research prospects will also be discussed. PMID:28212329

Enzyme-Assisted Discovery of Antioxidant Peptides from Edible Marine Invertebrates: A Review.

PubMed

Chai, Tsun-Thai; Law, Yew-Chye; Wong, Fai-Chu; Kim, Se-Kwon

2017-02-16

Marine invertebrates, such as oysters, mussels, clams, scallop, jellyfishes, squids, prawns, sea cucumbers and sea squirts, are consumed as foods. These edible marine invertebrates are sources of potent bioactive peptides. The last two decades have seen a surge of interest in the discovery of antioxidant peptides from edible marine invertebrates. Enzymatic hydrolysis is an efficient strategy commonly used for releasing antioxidant peptides from food proteins. A growing number of antioxidant peptide sequences have been identified from the enzymatic hydrolysates of edible marine invertebrates. Antioxidant peptides have potential applications in food, pharmaceuticals and cosmetics. In this review, we first give a brief overview of the current state of progress of antioxidant peptide research, with special attention to marine antioxidant peptides. We then focus on 22 investigations which identified 32 antioxidant peptides from enzymatic hydrolysates of edible marine invertebrates. Strategies adopted by various research groups in the purification and identification of the antioxidant peptides will be summarized. Structural characteristic of the peptide sequences in relation to their antioxidant activities will be reviewed. Potential applications of the peptide sequences and future research prospects will also be discussed.

Identification of an immunodominant region of Fel d 1 and characterization of constituent epitopes.

PubMed

Bateman, E A L; Ardern-Jones, M R; Ogg, G S

2008-11-01

Characterization of T cell epitopes restricted by common HLA alleles is a powerful tool in the understanding of the immune responses to allergens and for the identification of potential peptides for future peptide immunotherapy (PIT). One important requirement is the identification and use of peptides that will bind to HLA molecules covering a large proportion of the population. To identify commonly recognized CD4(+) T cell epitopes in Fel d 1, restricted through frequently expressed HLA molecules for potential future use in PIT. HLA matched antigen presenting cells, HLA blocking antibodies, and peptide truncations were used in ELISpot assays to establish HLA-restricted T cell epitopes. Cytokine responses were measured by ex vivo and cultured IFN-gamma, IL-4, and IL-10 ELISpots. Responses to an immunodominant region of chain 2 were identified in the majority of atopic individuals and epitopes restricted by HLA-DQB1(*)06 and -DPB1(*)0401 were characterized in detail. Significantly higher ex vivo IL-4 and lower IFN-gamma responses were observed to both epitopes in individuals with atopic dermatitis (AD) compared with those without disease. IL-10 responses were significantly lower in those with AD in the individuals with HLA-DPB1(*)0401. We have identified an immunodominant region of Fel d 1 which is frequently recognized by CD4(+) T cells from atopic individuals and contains epitopes that are restricted by very common HLA alleles.

Identification of structural traits that increase the antimicrobial activity of a chimeric peptide of human β-defensins 2 and 3.

PubMed

Spudy, Björn; Sönnichsen, Frank D; Waetzig, Georg H; Grötzinger, Joachim; Jung, Sascha

2012-10-12

Antimicrobial peptides participate in the first line of defence of many organisms against pathogens. In humans, the family of β-defensins plays a pivotal role in innate immunity. Two human β-defensins, β-defensin-2 and -3 (HBD2 and HBD3), show substantial sequence identity and structural similarity. However, HBD3 kills Staphylococcus (S.) aureus with a 4- to 8-fold higher efficiency compared to HBD2, whereas their activities against Escherichia (E.) coli are very similar. The generation of six HBD2/HBD3-chimeric molecules led to the identification of distinct molecular regions which mediate their divergent killing properties. One of the chimeras (chimera C3) killed both E. coli and S. aureus with an even higher efficacy compared to the wild-type molecules. Due to the broad spectrum of its antimicrobial activity against many human multidrug-resistant pathogens, this HBD2/HBD3-chimeric peptide represents a promising candidate for a new class of antibiotics. In order to investigate the structural basis of its exceptional antimicrobial activity, the peptide's tertiary structure was determined by NMR spectroscopy, which allowed its direct comparison to the published structures of HBD2 and HBD3 and the identification of the activity-increasing molecular features. Copyright © 2012 Elsevier Inc. All rights reserved.

Proteomics as a Quality Control Tool of Pharmaceutical Probiotic Bacterial Lysate Products

PubMed Central

Klein, Günter; Schanstra, Joost P.; Hoffmann, Janosch; Mischak, Harald; Siwy, Justyna; Zimmermann, Kurt

2013-01-01

Probiotic bacteria have a wide range of applications in veterinary and human therapeutics. Inactivated probiotics are complex samples and quality control (QC) should measure as many molecular features as possible. Capillary electrophoresis coupled to mass spectrometry (CE/MS) has been used as a multidimensional and high throughput method for the identification and validation of biomarkers of disease in complex biological samples such as biofluids. In this study we evaluate the suitability of CE/MS to measure the consistency of different lots of the probiotic formulation Pro-Symbioflor which is a bacterial lysate of heat-inactivated Escherichia coli and Enterococcus faecalis. Over 5000 peptides were detected by CE/MS in 5 different lots of the bacterial lysate and in a sample of culture medium. 71 to 75% of the total peptide content was identical in all lots. This percentage increased to 87–89% when allowing the absence of a peptide in one of the 5 samples. These results, based on over 2000 peptides, suggest high similarity of the 5 different lots. Sequence analysis identified peptides of both E. coli and E. faecalis and peptides originating from the culture medium, thus confirming the presence of the strains in the formulation. Ontology analysis suggested that the majority of the peptides identified for E. coli originated from the cell membrane or the fimbrium, while peptides identified for E. faecalis were enriched for peptides originating from the cytoplasm. The bacterial lysate peptides as a whole are recognised as highly conserved molecular patterns by the innate immune system as microbe associated molecular pattern (MAMP). Sequence analysis also identified the presence of soybean, yeast and casein protein fragments that are part of the formulation of the culture medium. In conclusion CE/MS seems an appropriate QC tool to analyze complex biological products such as inactivated probiotic formulations and allows determining the similarity between lots. PMID:23840518

ProteinInferencer: Confident protein identification and multiple experiment comparison for large scale proteomics projects.

PubMed

Zhang, Yaoyang; Xu, Tao; Shan, Bing; Hart, Jonathan; Aslanian, Aaron; Han, Xuemei; Zong, Nobel; Li, Haomin; Choi, Howard; Wang, Dong; Acharya, Lipi; Du, Lisa; Vogt, Peter K; Ping, Peipei; Yates, John R

2015-11-03

Shotgun proteomics generates valuable information from large-scale and target protein characterizations, including protein expression, protein quantification, protein post-translational modifications (PTMs), protein localization, and protein-protein interactions. Typically, peptides derived from proteolytic digestion, rather than intact proteins, are analyzed by mass spectrometers because peptides are more readily separated, ionized and fragmented. The amino acid sequences of peptides can be interpreted by matching the observed tandem mass spectra to theoretical spectra derived from a protein sequence database. Identified peptides serve as surrogates for their proteins and are often used to establish what proteins were present in the original mixture and to quantify protein abundance. Two major issues exist for assigning peptides to their originating protein. The first issue is maintaining a desired false discovery rate (FDR) when comparing or combining multiple large datasets generated by shotgun analysis and the second issue is properly assigning peptides to proteins when homologous proteins are present in the database. Herein we demonstrate a new computational tool, ProteinInferencer, which can be used for protein inference with both small- or large-scale data sets to produce a well-controlled protein FDR. In addition, ProteinInferencer introduces confidence scoring for individual proteins, which makes protein identifications evaluable. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015. Published by Elsevier B.V.

Computational Framework for Prediction of Peptide Sequences That May Mediate Multiple Protein Interactions in Cancer-Associated Hub Proteins.

PubMed

Sarkar, Debasree; Patra, Piya; Ghosh, Abhirupa; Saha, Sudipto

2016-01-01

A considerable proportion of protein-protein interactions (PPIs) in the cell are estimated to be mediated by very short peptide segments that approximately conform to specific sequence patterns known as linear motifs (LMs), often present in the disordered regions in the eukaryotic proteins. These peptides have been found to interact with low affinity and are able bind to multiple interactors, thus playing an important role in the PPI networks involving date hubs. In this work, PPI data and de novo motif identification based method (MEME) were used to identify such peptides in three cancer-associated hub proteins-MYC, APC and MDM2. The peptides corresponding to the significant LMs identified for each hub protein were aligned, the overlapping regions across these peptides being termed as overlapping linear peptides (OLPs). These OLPs were thus predicted to be responsible for multiple PPIs of the corresponding hub proteins and a scoring system was developed to rank them. We predicted six OLPs in MYC and five OLPs in MDM2 that scored higher than OLP predictions from randomly generated protein sets. Two OLP sequences from the C-terminal of MYC were predicted to bind with FBXW7, component of an E3 ubiquitin-protein ligase complex involved in proteasomal degradation of MYC. Similarly, we identified peptides in the C-terminal of MDM2 interacting with FKBP3, which has a specific role in auto-ubiquitinylation of MDM2. The peptide sequences predicted in MYC and MDM2 look promising for designing orthosteric inhibitors against possible disease-associated PPIs. Since these OLPs can interact with other proteins as well, these inhibitors should be specific to the targeted interactor to prevent undesired side-effects. This computational framework has been designed to predict and rank the peptide regions that may mediate multiple PPIs and can be applied to other disease-associated date hub proteins for prediction of novel therapeutic targets of small molecule PPI modulators.

Genome Mining for Ribosomally Synthesized Natural Products

PubMed Central

Velásquez, Juan E.; van der Donk, Wilfred

2011-01-01

In recent years, the number of known peptide natural products that are synthesized via the ribosomal pathway has rapidly grown. Taking advantage of sequence homology among genes encoding precursor peptides or biosynthetic proteins, in silico mining of genomes combined with molecular biology approaches has guided the discovery of a large number of new ribosomal natural products, including lantipeptides, cyanobactins, linear thiazole/oxazole-containing peptides, microviridins, lasso peptides, amatoxins, cyclotides, and conopeptides. In this review, we describe the strategies used for the identification of these ribosomally-synthesized and posttranslationally modified peptides (RiPPs) and the structures of newly identified compounds. The increasing number of chemical entities and their remarkable structural and functional diversity may lead to novel pharmaceutical applications. PMID:21095156

Oligoalanine helical callipers for cell penetration.

PubMed

Pazo, Marta; Juanes, Marisa; Lostalé-Seijo, Irene; Montenegro, Javier

2018-06-04

Even for short peptides that are enriched in basic amino acids, the large chemical space that can be spanned by combinations of natural amino acids hinders the rational design of cell penetrating peptides. We here report on short oligoalanine scaffolds for the fine-tuning of peptide helicity in different media and the study of cell penetrating properties. This strategy allowed the extraction of the structure/activity features required for maximal membrane interaction and cellular penetration at minimal toxicity. These results confirmed oligoalanine helical callipers as optimal scaffolds for the rational design and the identification of cell penetrating peptides.

Identification of intracellular degradation intermediates of aldolase B by antiserum to the denatured enzyme.

PubMed Central

Reznick, A Z; Rosenfelder, L; Shpund, S; Gershon, D

1985-01-01

A method has been developed that enables us to identify intracellular degradation intermediates of fructose-bisphosphate aldolase B (D-fructose-1,6-bisphosphate D-glyceraldehyde-3-phosphate-lyase, EC 4.1.2.13). This method is based on the use of antibody against thoroughly denatured purified aldolase. This antibody has been shown to recognize only denatured molecules, and it did not interact with "native" enzyme. supernatants (24,000 X g for 30 min) of liver and kidney homogenates were incubated with antiserum to denatured enzyme. The antigen-antibody precipitates thus formed were subjected to NaDodSO4/PAGE, followed by electrotransfer to nitrocellulose paper and immunodecoration with antiserum to denatured enzyme and 125I-labeled protein A. Seven peptides with molecular weights ranging from 38,000 (that of the intact subunit) to 18,000, which cross-reacted antigenically with denatured fructose-bisphosphate aldolase, could be identified in liver. The longest three peptides were also present in kidney. The possibility that these peptides were artifacts of homogenization was ruled out as follows: 125I-labeled tagged purified native aldolase was added to the buffer prior to liver homogenization. The homogenates were than subjected to NaDodSO4/PAGE followed by autoradiography, and the labeled enzyme was shown to remain intact. This method is suggested for general use in the search for degradation products of other cellular proteins. Images PMID:3898080

Identification and Characterization of Pheasant and Quail Avian Beta Defensin 2

USDA-ARS?s Scientific Manuscript database

Peptides play significant roles in physiology as hormones, neurotransmitters, growth, antimicrobial, and signal transducing factors. Identification of their tissue specific occurrence and abundance may lead to a better understanding of their physiological significance. Previously, we identified matu...

EPOR-Based Purification and Analysis of Erythropoietin Mimetic Peptides from Human Urine by Cys-Specific Cleavage and LC/MS/MS

NASA Astrophysics Data System (ADS)

Vogel, Matthias; Thomas, Andreas; Schänzer, Wilhelm; Thevis, Mario

2015-09-01

The development of a new class of erythropoietin mimetic agents (EMA) for treating anemic conditions has been initiated with the discovery of oligopeptides capable of dimerizing the erythropoietin (EPO) receptor and thus stimulating erythropoiesis. The most promising amino acid sequences have been mounted on various different polymeric structures or carrier molecules to obtain highly active EPO-like drugs exhibiting beneficial and desirable pharmacokinetic profiles. Concomitant with creating new therapeutic options, erythropoietin mimetic peptide (EMP)-based drug candidates represent means to artificially enhance endurance performance and necessitate coverage by sports drug testing methods. Therefore, the aim of the present study was to develop a strategy for the comprehensive detection of EMPs in doping controls, which can be used complementary to existing protocols. Three model EMPs were used to provide proof-of-concept data. Following EPO receptor-facilitated purification of target analytes from human urine, the common presence of the cysteine-flanked core structure of EMPs was exploited to generate diagnostic peptides with the aid of a nonenzymatic cleavage procedure. Sensitive detection was accomplished by targeted-SIM/data-dependent MS2 analysis. Method characterization was conducted for the EMP-based drug peginesatide concerning specificity, linearity, precision, recovery, stability, ion suppression/enhancement, and limit of detection (LOD, 0.25 ng/mL). Additionally, first data for the identification of the erythropoietin mimetic peptides EMP1 and BB68 were generated, demonstrating the multi-analyte testing capability of the presented approach.

Differential protein expression analysis using stable isotope labeling and PQD linear ion trap MS technology.

PubMed

Armenta, Jenny M; Hoeschele, Ina; Lazar, Iulia M

2009-07-01

An isotope tags for relative and absolute quantitation (iTRAQ)-based reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS) method was developed for differential protein expression profiling in complex cellular extracts. The estrogen positive MCF-7 cell line, cultured in the presence of 17beta-estradiol (E2) and tamoxifen (Tam), was used as a model system. MS analysis was performed with a linear trap quadrupole (LTQ) instrument operated by using pulsed Q dissociation (PQD) detection. Optimization experiments were conducted to maximize the iTRAQ labeling efficiency and the number of quantified proteins. MS data filtering criteria were chosen to result in a false positive identification rate of <4%. The reproducibility of protein identifications was approximately 60%-67% between duplicate, and approximately 50% among triplicate LC-MS/MS runs, respectively. The run-to-run reproducibility, in terms of relative standard deviations (RSD) of global mean iTRAQ ratios, was better than 10%. The quantitation accuracy improved with the number of peptides used for protein identification. From a total of 530 identified proteins (P < 0.001) in the E2/Tam treated MCF-7 cells, a list of 255 proteins (quantified by at least two peptides) was generated for differential expression analysis. A method was developed for the selection, normalization, and statistical evaluation of such datasets. An approximate approximately 2-fold change in protein expression levels was necessary for a protein to be selected as a biomarker candidate. According to this data processing strategy, approximately 16 proteins involved in biological processes such as apoptosis, RNA processing/metabolism, DNA replication/transcription/repair, cell proliferation and metastasis, were found to be up- or down-regulated.

Chromatography and mass spectrometry of prebiological and biological molecules

NASA Astrophysics Data System (ADS)

Navale, Vivek

The detection and identification of prebiological and biological molecules are of importance for understanding chemical and biological processes occurring within the solar system. Molecular mass measurements, peptide mapping, and disulfide bond analysis of enzymes and recombinant proteins are important in the development of therapeutic drugs for human diseases. Separation of hydrocarbons (C1 to C6) and nitriles was achieved by 14%-cyanopropylphenyl-86%- dimethylpolysiloxane (CPPS-DMPS) stationary phase in a narrow bore metal capillary column. The calculation of modeling numbers enabled the differentiation of the C4 hydrocarbon isomers of 1-butene (cis and trans). The modeled retention time values for benzene, toluene, xylene, acetonitrile, propane, and propene nitriles were in good agreement with the measurements. The separation of C2 hydrocarbons (ethane and ethene) from predominantly N2 matrix was demonstrated for the first time on wall coated narrow bore low temperature glassy carbon column. Identification and accurate mass measurements of pepsin, an enzymatic protein with less number of basic amino acid residues were successfully demonstrated by matrix- assisted laser desorption ionization mass spectrometry (MALDI-MS). The molecular mass of pepsin was found to be 34,787 Da. Several decomposition products of pepsin, in m/z range of 3,500 to 4,700 were identified. Trypsin, an important endopeptidase enzyme had a mass of 46829.7 Da. Lower mass components with m/z 8047.5, 7776.6, 5722, 5446.2 and 5185 Da were also observed in trypsin spectrum. Both chemokine and growth factor recombinant proteins were mass analyzed as 8848.1 ± 3.5 and 16178.52 ± 4.1 Da, respectively. The accuracy of the measurements was in the range of 0.01 to 0.02%. Reduction and alkylation experiments on the chemokine showed the presence of six cysteines and three disulfide bonds. The two cysteines of the growth factor contained the free sulfhydryl groups and the accurate average mass of the growth factor protein was 16175.6 Da. MALDI analysis of trypsin digest of Myeloid progenitor inhibitory factor chemokine verified the disulfide bridging among cysteine residues. Several partially digested trypsin and V8 peptides were detected that verified significant portions of the primary structure of the chemokine. Mass difference amounting to the loss of a single amino acid, serine was also identified. The cyanogen bromide (CNBr) treated chemokine produced three peptides 7051, 6910.1 and 1492 Da. The analysis of Keratinocyte growth factor (KGF) peptide mixtures showed suppression effects during the MALDI ionization process. Several partially digested peptides with mass values 3214, 9980, 10325 and 10497 Da were identified. Direct MALDI-MS analysis of cyanogen bromide treated KGF molecule demonstrated the formation of peptides with mass 7567.3, 4992.6 and 3118.6 Da. The high sensitivity of MALDI-MS provided a rapid method for confirming the fidelity of gene expression in the host system. The present work showed that the combined methods of chromatography and mass spectrometry are efficient means for identification and characterization of prebiological and biological molecules.

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qian, Chen; Hettich, Robert L.

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling, perhaps most specifically with respect to impact on plant growth but also more broadly to global impact on carbon and nitrogen-cycling. Liquid chromatography coupled to high performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to soil proteome extraction and subsequent MS measurement. To address some of the major issues, we have designed and optimized an experimental method to enhance microbialmore » proteome extraction concomitant with minimizing the soil-borne humic substances co-extraction from soils. Among the range of interferences, humic substances are often the worst in terms of adversely impacting proteome extraction and mass spectrometry measurement. Our approach employs an in-situ detergent-based microbial lysis / TCA precipitation coupled with an additional acidification precipitation step at the peptide level which efficiently removes humic acids. By combing filtration and pH adjustment of the final peptide solution, the remaining humic acids can be differentially precipitated and removed with a membrane filter, thereby leaving much cleaner proteolytic peptide samples for MS measurement. As a result, this modified method is a reliable and straight-forward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or reducing or biasing protein identification in mass spectrometry.« less

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements

DOE PAGES

Qian, Chen; Hettich, Robert L.

2017-05-24

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling, perhaps most specifically with respect to impact on plant growth but also more broadly to global impact on carbon and nitrogen-cycling. Liquid chromatography coupled to high performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to soil proteome extraction and subsequent MS measurement. To address some of the major issues, we have designed and optimized an experimental method to enhance microbialmore » proteome extraction concomitant with minimizing the soil-borne humic substances co-extraction from soils. Among the range of interferences, humic substances are often the worst in terms of adversely impacting proteome extraction and mass spectrometry measurement. Our approach employs an in-situ detergent-based microbial lysis / TCA precipitation coupled with an additional acidification precipitation step at the peptide level which efficiently removes humic acids. By combing filtration and pH adjustment of the final peptide solution, the remaining humic acids can be differentially precipitated and removed with a membrane filter, thereby leaving much cleaner proteolytic peptide samples for MS measurement. As a result, this modified method is a reliable and straight-forward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or reducing or biasing protein identification in mass spectrometry.« less

Screening and identification of genetic loci involved in producing more/denser inclusion bodies in Escherichia coli

PubMed Central

2013-01-01

Background Many proteins and peptides have been used in therapeutic or industrial applications. They are often produced in microbial production hosts by fermentation. Robust protein production in the hosts and efficient downstream purification are two critical factors that could significantly reduce cost for microbial protein production by fermentation. Producing proteins/peptides as inclusion bodies in the hosts has the potential to achieve both high titers in fermentation and cost-effective downstream purification. Manipulation of the host cells such as overexpression/deletion of certain genes could lead to producing more and/or denser inclusion bodies. However, there are limited screening methods to help to identify beneficial genetic changes rendering more protein production and/or denser inclusion bodies. Results We report development and optimization of a simple density gradient method that can be used for distinguishing and sorting E. coli cells with different buoyant densities. We demonstrate utilization of the method to screen genetic libraries to identify a) expression of glyQS loci on plasmid that increased expression of a peptide of interest as well as the buoyant density of inclusion body producing E. coli cells; and b) deletion of a host gltA gene that increased the buoyant density of the inclusion body produced in the E. coli cells. Conclusion A novel density gradient sorting method was developed to screen genetic libraries. Beneficial host genetic changes could be exploited to improve recombinant protein expression as well as downstream protein purification. PMID:23638724

Screening and identification of genetic loci involved in producing more/denser inclusion bodies in Escherichia coli.

PubMed

Pandey, Neeraj; Sachan, Annapurna; Chen, Qi; Ruebling-Jass, Kristin; Bhalla, Ritu; Panguluri, Kiran Kumar; Rouviere, Pierre E; Cheng, Qiong

2013-05-02

Many proteins and peptides have been used in therapeutic or industrial applications. They are often produced in microbial production hosts by fermentation. Robust protein production in the hosts and efficient downstream purification are two critical factors that could significantly reduce cost for microbial protein production by fermentation. Producing proteins/peptides as inclusion bodies in the hosts has the potential to achieve both high titers in fermentation and cost-effective downstream purification. Manipulation of the host cells such as overexpression/deletion of certain genes could lead to producing more and/or denser inclusion bodies. However, there are limited screening methods to help to identify beneficial genetic changes rendering more protein production and/or denser inclusion bodies. We report development and optimization of a simple density gradient method that can be used for distinguishing and sorting E. coli cells with different buoyant densities. We demonstrate utilization of the method to screen genetic libraries to identify a) expression of glyQS loci on plasmid that increased expression of a peptide of interest as well as the buoyant density of inclusion body producing E. coli cells; and b) deletion of a host gltA gene that increased the buoyant density of the inclusion body produced in the E. coli cells. A novel density gradient sorting method was developed to screen genetic libraries. Beneficial host genetic changes could be exploited to improve recombinant protein expression as well as downstream protein purification.

Chagas disease vector blood meal sources identified by protein mass spectrometry

PubMed Central

Keller, Judith I.; Ballif, Bryan A.; St. Clair, Riley M.; Vincent, James J.; Monroy, M. Carlota

2017-01-01

Chagas disease is a complex vector borne parasitic disease involving blood feeding Triatominae (Hemiptera: Reduviidae) insects, also known as kissing bugs, and the vertebrates they feed on. This disease has tremendous impacts on millions of people and is a global health problem. The etiological agent of Chagas disease, Trypanosoma cruzi (Kinetoplastea: Trypanosomatida: Trypanosomatidae), is deposited on the mammalian host in the insect’s feces during a blood meal, and enters the host’s blood stream through mucous membranes or a break in the skin. Identifying the blood meal sources of triatomine vectors is critical in understanding Chagas disease transmission dynamics, can lead to identification of other vertebrates important in the transmission cycle, and aids management decisions. The latter is particularly important as there is little in the way of effective therapeutics for Chagas disease. Several techniques, mostly DNA-based, are available for blood meal identification. However, further methods are needed, particularly when sample conditions lead to low-quality DNA or to assess the risk of human cross-contamination. We demonstrate a proteomics-based approach, using liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify host-specific hemoglobin peptides for blood meal identification in mouse blood control samples and apply LC-MS/MS for the first time to Triatoma dimidiata insect vectors, tracing blood sources to species. In contrast to most proteins, hemoglobin, stabilized by iron, is incredibly stable even being preserved through geologic time. We compared blood stored with and without an anticoagulant and examined field-collected insect specimens stored in suboptimal conditions such as at room temperature for long periods of time. To our knowledge, this is the first study using LC-MS/MS on field-collected arthropod disease vectors to identify blood meal composition, and where blood meal identification was confirmed with more traditional DNA-based methods. We also demonstrate the potential of synthetic peptide standards to estimate relative amounts of hemoglobin acquired when insects feed on multiple blood sources. These LC-MS/MS methods can contribute to developing Ecohealth control strategies for Chagas disease transmission and can be applied to other arthropod disease vectors. PMID:29232402

Identification and Characterization of a Suite of Tumor Targeting Peptides for Non-Small Cell Lung Cancer

NASA Astrophysics Data System (ADS)

McGuire, Michael J.; Gray, Bethany Powell; Li, Shunzi; Cupka, Dorothy; Byers, Lauren Averett; Wu, Lei; Rezaie, Shaghayegh; Liu, Ying-Horng; Pattisapu, Naveen; Issac, James; Oyama, Tsukasa; Diao, Lixia; Heymach, John V.; Xie, Xian-Jin; Minna, John D.; Brown, Kathlynn C.

2014-03-01

Tumor targeting ligands are emerging components in cancer therapies. Widespread use of targeted therapies and molecular imaging is dependent on increasing the number of high affinity, tumor-specific ligands. Towards this goal, we biopanned three phage-displayed peptide libraries on a series of well-defined human non-small cell lung cancer (NSCLC) cell lines, isolating 11 novel peptides. The peptides show distinct binding profiles across 40 NSCLC cell lines and do not bind normal bronchial epithelial cell lines. Binding of specific peptides correlates with onco-genotypes and activation of particular pathways, such as EGFR signaling, suggesting the peptides may serve as surrogate markers. Multimerization of the peptides results in cell binding affinities between 0.0071-40 nM. The peptides home to tumors in vivo and bind to patient tumor samples. This is the first comprehensive biopanning for isolation of high affinity peptidic ligands for a single cancer type and expands the diversity of NSCLC targeting ligands.

Characterization and identification of novel antidiabetic and anti-obesity peptides from camel milk protein hydrolysates.

PubMed

Mudgil, Priti; Kamal, Hina; Yuen, Gan Chee; Maqsood, Sajid

2018-09-01

In-vitro inhibitory properties of peptides released from camel milk proteins against dipeptidyl peptidase-IV (DPP-IV), porcine pancreatic α-amylase (PPA), and porcine pancreatic lipase (PPL) were studied. Results revealed that upon hydrolysis by different enzymes, camel milk proteins displayed dramatic increase in inhibition of DPP-IV and PPL, but slight improvement in PPA inhibition was noticed. Peptide sequencing revealed a total of 20 and 3 peptides for A9 and B9 hydrolysates respectively, obtained the score of 0.8 or more on peptide ranker and were categorized as potential DPP-IV inhibitory peptides. KDLWDDFKGL in A9 and MPSKPPLL in B9 were identified as most potent PPA inhibitory peptide. For PPL inhibition only 7 and 2 peptides qualified as PPL inhibitory peptides from hydrolysates A9 and B9, respectively. The present study report for the first time PPA and PPL inhibitory and only second for DPP-IV inhibitory potential of protein hydrolysates from camel milk. Copyright © 2018 Elsevier Ltd. All rights reserved.

Identification and Characterization of a Suite of Tumor Targeting Peptides for Non-Small Cell Lung Cancer

PubMed Central

McGuire, Michael J.; Gray, Bethany Powell; Li, Shunzi; Cupka, Dorothy; Byers, Lauren Averett; Wu, Lei; Rezaie, Shaghayegh; Liu, Ying-Horng; Pattisapu, Naveen; Issac, James; Oyama, Tsukasa; Diao, Lixia; Heymach, John V.; Xie, Xian-Jin; Minna, John D.; Brown, Kathlynn C.

2014-01-01

Tumor targeting ligands are emerging components in cancer therapies. Widespread use of targeted therapies and molecular imaging is dependent on increasing the number of high affinity, tumor-specific ligands. Towards this goal, we biopanned three phage-displayed peptide libraries on a series of well-defined human non-small cell lung cancer (NSCLC) cell lines, isolating 11 novel peptides. The peptides show distinct binding profiles across 40 NSCLC cell lines and do not bind normal bronchial epithelial cell lines. Binding of specific peptides correlates with onco-genotypes and activation of particular pathways, such as EGFR signaling, suggesting the peptides may serve as surrogate markers. Multimerization of the peptides results in cell binding affinities between 0.0071–40 nM. The peptides home to tumors in vivo and bind to patient tumor samples. This is the first comprehensive biopanning for isolation of high affinity peptidic ligands for a single cancer type and expands the diversity of NSCLC targeting ligands. PMID:24670678

Identification of osteocalcin as a permanent aging constituent of the bone matrix: basis for an accurate age at death determination.

PubMed

Ritz, S; Turzynski, A; Schütz, H W; Hollmann, A; Rochholz, G

1996-01-12

Age at death determination based on aspartic acid racemization in dentin has been applied successfully in forensic odontology for several years now. An age-dependent accumulation of D-aspartic acid has also recently been demonstrated in bone osteocalcin, one of the most abundant noncollagenous proteins of the organic bone matrix. Evaluation of these initial data on in vivo racemization of aspartic acid in bone osteocalcin was taken a step further. After purification of osteocalcin from 53 skull bone specimens, the extent of aspartic acid racemization in this peptide was determined. The D-aspartic acid content of purified bone osteocalcin exhibited a very close relationship to age at death. This confirmed identification of bone osteocalcin as a permanent, 'aging' peptide of the organic bone matrix. Its D-aspartic acid content may be used as a measure of its age and hence that of the entire organism. The new biochemical approach to determination of age at death by analyzing bone is complex and demanding from a methodologic point of view, but appears to be superior in precision and reproducibility to most other methods applicable to bone.

Identification and Application of Neutralizing Epitopes of Human Adenovirus Type 55 Hexon Protein

PubMed Central

Tian, Xingui; Ma, Qiang; Jiang, Zaixue; Huang, Junfeng; Liu, Qian; Lu, Xiaomei; Luo, Qingming; Zhou, Rong

2015-01-01

Human adenovirus type 55 (HAdV55) is a newly identified re-emergent acute respiratory disease (ARD) pathogen with a proposed recombination of hexon gene between HAdV11 and HAdV14 strains. The identification of the neutralizing epitopes is important for the surveillance and vaccine development against HAdV55 infection. In this study, four type-specific epitope peptides of HAdV55 hexon protein, A55R1 (residues 138 to 152), A55R2 (residues 179 to 187), A55R4 (residues 247 to 259) and A55R7 (residues 429 to 443), were predicted by multiple sequence alignment and homology modeling methods, and then confirmed with synthetic peptides by enzyme-linked immunosorbent assay (ELISA) and neutralization tests (NT). Finally, the A55R2 was incorporated into human adenoviruses 3 (HAdV3) and a chimeric adenovirus rAd3A55R2 was successfully obtained. The chimeric rAd3A55R2 could induce neutralizing antibodies against both HAdV3 and HAdV55. This current study will contribute to the development of novel adenovirus vaccine candidate and adenovirus structural analysis. PMID:26516903

Direct Identification of Tyrosine Sulfation by using Ultraviolet Photodissociation Mass Spectrometry

NASA Astrophysics Data System (ADS)

Robinson, Michelle R.; Moore, Kevin L.; Brodbelt, Jennifer S.

2014-08-01

Sulfation is a common post-translational modification of tyrosine residues in eukaryotes; however, detection using traditional liquid chromatography-mass spectrometry (LC-MS) methods is challenging based on poor ionization efficiency in the positive ion mode and facile neutral loss upon collisional activation. In the present study, 193 nm ultraviolet photodissociation (UVPD) is applied to sulfopeptide anions to generate diagnostic sequence ions, which do not undergo appreciable neutral loss of sulfate even using higher energy photoirradiation parameters. At the same time, neutral loss of SO3 is observed from the precursor and charge-reduced precursor ions, a spectral feature that is useful for differentiating tyrosine sulfation from the nominally isobaric tyrosine phosphorylation. LC-MS detection limits for UVPD analysis in the negative mode were determined to be around 100 fmol for three sulfated peptides, caerulein, cionin, and leu-enkephalin. The LC-UVPD-MS method was applied for analysis of bovine fibrinogen, and its key sulfated peptide was confidently identified.

Direct Identification of Tyrosine Sulfation by using Ultraviolet Photodissociation Mass Spectrometry

PubMed Central

Robinson, Michelle R.; Moore, Kevin L.; Brodbelt, Brodbelt

2014-01-01

Sulfation is a common post-translational modification of tyrosine residues in eukaryotes; however, detection using traditional liquid chromatography-mass spectrometry (LC-MS) methods is challenging based on poor ionization efficiency in the positive ion mode and facile neutral loss upon collisional activation. In the present study, 193 nm ultraviolet photodissociation (UVPD) is applied to sulfopeptide anions to generate diagnostic sequence ions which do not undergo appreciable neutral loss of sulfate even using higher energy photoirradiation parameters. At the same time, neutral loss of sulfate is observed from the precursor and charge reduced precursor ions, a spectral feature that is useful for differentiating tyrosine sulfation from the nominally isobaric tyrosine phosphorylation. LC-MS detection limits for UVPD analysis in the negative mode were determined to be around 100 fmol for three sulfated peptides, caerulein, cionin, and leu-enkephalin. The LC-UVPD-MS method was applied for analysis of bovine fibrinogen, and its key sulfated peptide was confidently identified. PMID:24845354

Methods for recalibration of mass spectrometry data

DOEpatents

Tolmachev, Aleksey V [Richland, WA; Smith, Richard D [Richland, WA

2009-03-03

Disclosed are methods for recalibrating mass spectrometry data that provide improvement in both mass accuracy and precision by adjusting for experimental variance in parameters that have a substantial impact on mass measurement accuracy. Optimal coefficients are determined using correlated pairs of mass values compiled by matching sets of measured and putative mass values that minimize overall effective mass error and mass error spread. Coefficients are subsequently used to correct mass values for peaks detected in the measured dataset, providing recalibration thereof. Sub-ppm mass measurement accuracy has been demonstrated on a complex fungal proteome after recalibration, providing improved confidence for peptide identifications.

Identification of Proteins and Peptide Biomarkers for Detecting Banned Processed Animal Proteins (PAPs) in Meat and Bone Meal by Mass Spectrometry.

PubMed

Marbaix, Hélène; Budinger, Dimitri; Dieu, Marc; Fumière, Olivier; Gillard, Nathalie; Delahaut, Philippe; Mauro, Sergio; Raes, Martine

2016-03-23

The outbreak of bovine spongiform encephalopathy (BSE) in the United Kingdom in 1986, with processed animal proteins (PAPs) as the main vector of the disease, has led to their prohibition in feed. The progressive release of the feed ban required the development of new analytical methods to determine the exact origin of PAPs from meat and bone meal. We set up a promising MS-based method to determine the species and the source (legal or not) present in PAPs: a TCA-acetone protein extraction followed by a cleanup step, an in-solution tryptic digestion of 5 h (with a 1:20 protein/trypsin ratio), and mass spectrometry analyses, first without any a priori, with a Q-TOF, followed by a targeted triple-quadrupole analysis. Using this procedure, we were able to overcome some of the major limitations of the official methods to analyze PAPs, detecting and identifying prohibited animal products in feedstuffs by the monitoring of peptides specific for cows, pigs, and sheep in PAPs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Datta, Susmita

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statisticalmore » inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.« less

Computer aided manual validation of mass spectrometry-based proteomic data.

PubMed

Curran, Timothy G; Bryson, Bryan D; Reigelhaupt, Michael; Johnson, Hannah; White, Forest M

2013-06-15

Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics. Copyright © 2013 Elsevier Inc. All rights reserved.

Rapid and Accurate Identification of Animal Species in Natural Leather Goods by Liquid Chromatography/Mass Spectrometry

PubMed Central

Izuchi, Yukari; Takashima, Tsuneo; Hatano, Naoya

2016-01-01

The demand for leather goods has grown globally in recent years. Industry revenue is forecast to reach $91.2 billion by 2018. There is an ongoing labelling problem in the leather items market, in that it is currently impossible to identify the species that a given piece of leather is derived from. To address this issue, we developed a rapid and simple method for the specific identification of leather derived from cattle, horses, pigs, sheep, goats, and deer by analysing peptides produced by the trypsin-digestion of proteins contained in leather goods using liquid chromatography/mass spectrometry. We determined species-specific amino acid sequences by liquid chromatography/tandem mass spectrometry analysis using the Mascot software program and demonstrated that collagen α-1(I), collagen α-2(I), and collagen α-1(III) from the dermal layer of the skin are particularly useful in species identification. PMID:27313979

Dereplication of peptidic natural products through database search of mass spectra

PubMed Central

Mohimani, Hosein; Gurevich, Alexey; Mikheenko, Alla; Garg, Neha; Nothias, Louis-Felix; Ninomiya, Akihiro; Takada, Kentaro; Dorrestein, Pieter C.; Pevzner, Pavel A.

2016-01-01

Peptidic Natural Products (PNPs) are widely used compounds that include many antibiotics and a variety of other bioactive peptides. While recent breakthroughs in PNP discovery raised the challenge of developing new algorithms for their analysis, identification of PNPs via database search of tandem mass spectra remains an open problem. To address this problem, natural product researchers utilize dereplication strategies that identify known PNPs and lead to the discovery of new ones even in cases when the reference spectra are not present in existing spectral libraries. DEREPLICATOR is a new dereplication algorithm that enabled high-throughput PNP identification and that is compatible with large-scale mass spectrometry-based screening platforms for natural product discovery. After searching nearly one hundred million tandem mass spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure, DEREPLICATOR identified an order of magnitude more PNPs (and their new variants) than any previous dereplication efforts. PMID:27820803

Mapping of Epitopes Occurring in Bovine α(s1)-Casein Variants by Peptide Microarray Immunoassay.

PubMed

Lisson, Maria; Erhardt, Georg

2016-01-01

Immunoglobulin E epitope mapping of milk proteins reveals important information about their immunologic properties. Genetic variants of αS1-casein, one of the major allergens in bovine milk, are until now not considered when discussing the allergenic potential. Here we describe the complete procedure to assess the allergenicity of αS1-casein variants B and C, which are frequent in most breeds, starting from milk with identification and purification of casein variants by isoelectric focusing (IEF) and anion-exchange chromatography, followed by in vitro gastrointestinal digestion of the casein variants, identification of the resulting peptides by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), in silico analysis of the variant-specific peptides as allergenic epitopes, and determination of their IgE-binding properties by microarray immunoassay with cow's milk allergic human sera.

Enzyme II/sup Mtl/ of the Escherichia coli phosphoenolpyruvate-dependent phosphotransferase system: identification of the activity-linked cysteine on the mannitol carrier

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pas, H.H.; Robillard, G.T.

1988-07-26

The cysteine of the membrane-bound mannitol-specific enzyme II (EII/sup Mtl/) of the Escherichia coli phosphoenolpyruvate-dependent phosphotransferase system have been labeled with 4-vinylpyridine. After proteolytic breakdown and reversed-phase HPLC, the peptides containing cysteines 110, 384, and 571 could be identified. N-Ethylmaleimide (NEM) treatment of the native unphosphorylated enzyme results in incorporation of one NEM label per molecule and loss of enzymatic activity. NEM treatment and inactivation prevented 4-vinylpyridine incorporation into the Cys-384-containing peptide, identifying this residue as the activity-linked cysteine. Both oxidation and phosphorylation of the native enzyme protected the enzyme against NEM labeling of Cys-384. Positive identification of the activity-linkedmore » cysteine was accomplished by inactivation with (/sup 14/C)iodoacetamide, proteolytic fragmentation, isolation of the peptide, and amino acid sequencing.« less

In Vivo Biomarkers for Targeting Colorectal Neoplasms

PubMed Central

Hsiung, Pei-Lin; Wang, Thomas

2011-01-01

Summary Colorectal carcinoma continues to be a leading cause of cancer morbidity and mortality despite widespread adoption of screening methods. Targeted detection and therapy using recent advances in our knowledge of in vivo cancer biomarkers promise to significantly improve methods for early detection, risk stratification, and therapeutic intervention. The behavior of molecular targets in transformed tissues is being comprehensively assessed using new techniques of gene expression profiling and high throughput analyses. The identification of promising targets is stimulating the development of novel molecular probes, including significant progress in the field of activatable and peptide probes. These probes are being evaluated in small animal models of colorectal neoplasia and recently in the clinic. Furthermore, innovations in optical imaging instrumentation are resulting in the scaling down of size for endoscope compatibility. Advances in target identification, probe development, and novel instruments are progressing rapidly, and the integration of these technologies has a promising future in molecular medicine. PMID:19126961

Photoreactive Stapled BH3 Peptides to Dissect the BCL-2 Family Interactome

PubMed Central

Braun, Craig R.; Mintseris, Julian; Gavathiotis, Evripidis; Bird, Gregory H.; Gygi, Steven P.; Walensky, Loren D.

2010-01-01

SUMMARY Defining protein interactions forms the basis for discovery of biological pathways, disease mechanisms, and opportunities for therapeutic intervention. To harness the robust binding affinity and selectivity of structured peptides for interactome discovery, we engineered photoreactive stapled BH3 peptide helices that covalently capture their physiologic BCL-2 family targets. The crosslinking α-helices covalently trap both static and dynamic protein interactors, and enable rapid identification of interaction sites, providing a critical link between interactome discovery and targeted drug design. PMID:21168768

Alternative Surfactants for Improved Efficiency of In Situ Tryptic Proteolysis of Fingermarks

NASA Astrophysics Data System (ADS)

Patel, Ekta; Clench, Malcolm R.; West, Andy; Marshall, Peter S.; Marshall, Nathan; Francese, Simona

2015-06-01

Despite recent improvements to in situ proteolysis strategies, a higher efficiency is still needed to increase both the number of peptides detected and the associated ion intensity, leading to a complete and reliable set of biomarkers for diagnostic or prognostic purposes. In the study presented here, an extract of a systematic study is illustrated investigating a range of surfactants assisting trypsin proteolytic activity. Method development was trialled on fingermarks; this specimen results from a transfer of sweat from an individual's fingertip to a surface upon contact. As sweat carries a plethora of biomolecules, including peptides and proteins, fingermarks are, potentially, a very valuable specimen for non-invasive prognostic or diagnostic screening. A recent study has demonstrated the opportunity to quickly detect peptides and small proteins in fingermarks using Matrix Assisted Laser Desorption Ionization Mass Spectrometry Profiling (MALDI MSP). However, intact detection bears low sensitivity and does not allow species identification; therefore, a shotgun proteomic approach was employed involving in situ proteolysis. Data demonstrate that in fingermarks, further improvements to the existing method can be achieved using MEGA-8 as surfactant in higher percentages as well as combinations of different detergents. Also, for the first time, Rapigest SF, normally used in solution digestions, has been shown to successfully work also for in situ proteolysis.

Rapid detection of proteins in transgenic crops without protein reference standards by targeted proteomic mass spectrometry.

PubMed

Schacherer, Lindsey J; Xie, Weiping; Owens, Michaela A; Alarcon, Clara; Hu, Tiger X

2016-09-01

Liquid chromatography coupled with tandem mass spectrometry is increasingly used for protein detection for transgenic crops research. Currently this is achieved with protein reference standards which may take a significant time or efforts to obtain and there is a need for rapid protein detection without protein reference standards. A sensitive and specific method was developed to detect target proteins in transgenic maize leaf crude extract at concentrations as low as ∼30 ng mg(-1) dry leaf without the need of reference standards or any sample enrichment. A hybrid Q-TRAP mass spectrometer was used to monitor all potential tryptic peptides of the target proteins in both transgenic and non-transgenic samples. The multiple reaction monitoring-initiated detection and sequencing (MIDAS) approach was used for initial peptide/protein identification via Mascot database search. Further confirmation was achieved by direct comparison between transgenic and non-transgenic samples. Definitive confirmation was provided by running the same experiments of synthetic peptides or protein standards, if available. A targeted proteomic mass spectrometry method using MIDAS approach is an ideal methodology for detection of new proteins in early stages of transgenic crop research and development when neither protein reference standards nor antibodies are available. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

The minor histocompatibility antigen HA-3 arises from differential proteasome-mediated cleavage of the lymphoid blast crisis (Lbc) oncoprotein.

PubMed

Spierings, Eric; Brickner, Anthony G; Caldwell, Jennifer A; Zegveld, Suzanne; Tatsis, Nia; Blokland, Els; Pool, Jos; Pierce, Richard A; Mollah, Sahana; Shabanowitz, Jeffrey; Eisenlohr, Laurence C; van Veelen, Peter; Ossendorp, Ferry; Hunt, Donald F; Goulmy, Els; Engelhard, Victor H

2003-07-15

Minor histocompatibility (H) antigens crucially affect the outcome of human leukocyte antigen (HLA)-identical allogeneic stem cell transplantation (SCT). To understand the basis of alloimmune responses against minor H antigens, identification of minor H peptides and their antigenicity-determining mechanisms is essential. Here we report the identification of HA-3 and its encoding gene. The HA-3 peptide, VTEPGTAQY (HA-3T), is encoded by the lymphoid blast crisis (Lbc) oncogene. We thus show for the first time that a leukemia-associated oncogene can give rise to immunogenic T-cell epitopes that may have participated in antihost and antileukemic alloimmune responses. Genotypic analysis of HA-3- individuals revealed the allelic counterpart VMEPGTAQY (HA-3M). Despite the lack of T-cell recognition of HA-3- cells, the Thr-->Met substitution had only a modest effect on peptide binding to HLA-A1 and a minimal impact on recognition by T cells when added exogenously to target cells. This substitution did not influence transporter associated with antigen processing (TAP) transport, but, in contrast to the HA-3T peptide, HA-3M is destroyed by proteasome-mediated digestion. Thus, the immunogenicity of minor H antigens can result from proteasome-mediated destruction of the negative allelic peptide.

1-(3-aminopropyl)-3-butylimidazolium bromide for carboxyl group derivatization: potential applications in high sensitivity peptide identification by mass spectrometry.

PubMed

Qiao, Xiaoqiang; Zhou, Yuan; Hou, Chunyan; Zhang, Xiaodan; Yang, Kaiguang; Zhang, Lihua; Zhang, Yukui

2013-03-01

The cationic reagent 1-(3-aminopropyl)-3-butylimidazolium bromide (BAPI) was exploited for the derivatization of carboxyl groups on peptides. Nearly 100% derivatization efficiency was achieved with the synthetic peptide RVYVHPI (RI-7). Furthermore, the peptide derivative was stable in a 0.1% TFA/water solution or a 0.1% (v/v) TFA/acetonitrile/water solution for at least one week. The effect of BAPI derivatization on the ionization of the peptide RI-7 was further investigated, and the detection sensitivity was improved >42-fold via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), thus outperforming the commercial piperazine derivatization approach. Moreover, the charge states of the peptide were largely increased via BAPI derivatization by electrospray ionization (ESI) MS. The results indicate the potential merits of BAPI derivatization for high sensitivity peptide analysis by MS.

Integrated CZE-ESI-MS/MS system with an immobilized trypsin microreactor for online digestion and analysis of picogram amounts of RAW 264.7 cell lysate

PubMed Central

Sun, Liangliang; Zhu, Guijie; Dovichi, Norman J.

2013-01-01

A capillary zone electrophoresis (CZE) electrospray ionization (ESI) tandem mass spectrometry (MS/MS) system was integrated with an immobilized trypsin microreactor. The system was evaluated and then applied for online digestion and analysis of picogram loadings of RAW 264.7 cell lysate. Protein samples were dissolved in a buffer containing 50% (v/v) acetonitrile (ACN), and then directly loaded into the capillary for digestion, followed by CZE separation and MS/MS identification. The organic solvent (50% (v/v) ACN) assisted the immobilized trypsin digestion and simplified the protein sample preparation protocol. Neither protein reduction nor alkylation steps were employed, which minimized sample loss and contamination. The integrated CZE-ESI-MS/MS system generated confident identification of bovine serum albumin (BSA) with 19% sequence coverage and 14 peptide IDs when 20 fmole was loaded. When only 1 fmole BSA was injected, one BSA peptide was consistently detected. For the analysis of a standard protein mixture, the integrated system produced efficient protein digestion and confident identification for proteins with different molecular weights and isoelectric points when low fmole amount was loaded for each protein. We further applied the system for triplicate analysis of a RAW 264.7 cell lysate; 2 ± 1 and 7 ± 2 protein groups were confidently identified from only 300 pg and 3 ng loadings, respectively. The 300 pg sample loading corresponds to the protein content of three RAW 264.7 cells. In addition to high sensitivity analysis, the integrated CZE-ESI-MS/MS system produces good reproducibility in terms of peptide and protein IDs, peptide migration time, and peptide intensity. PMID:23510126

Middle-Down and Chemical Proteomic Approaches to Reveal Histone H4 Modification Dynamics in Cell Cycle: Label-Free Semi-Quantification of Histone Tail Peptide Modifications Including Phosphorylation and Highly Sensitive Capture of Histone PTM Binding Proteins Using Photo-Reactive Crosslinkers

PubMed Central

Yamamoto, Kazuki; Chikaoka, Yoko; Hayashi, Gosuke; Sakamoto, Ryosuke; Yamamoto, Ryuji; Sugiyama, Akira; Kodama, Tatsuhiko; Okamoto, Akimitsu; Kawamura, Takeshi

2015-01-01

Mass spectrometric proteomics is an effective approach for identifying and quantifying histone post-translational modifications (PTMs) and their binding proteins, especially in the cases of methylation and acetylation. However, another vital PTM, phosphorylation, tends to be poorly quantified because it is easily lost and inefficiently ionized. In addition, PTM binding proteins for phosphorylation are sometimes resistant to identification because of their variable binding affinities. Here, we present our efforts to improve the sensitivity of detection of histone H4 tail peptide phosphorylated at serine 1 (H4S1ph) and our successful identification of an H4S1ph binder candidate by means of a chemical proteomics approach. Our nanoLC-MS/MS system permitted semi-quantitative label-free analysis of histone H4 PTM dynamics of cell cycle-synchronized HeLa S3 cells, including phosphorylation, methylation, and acetylation. We show that H4S1ph abundance on nascent histone H4 unmethylated at lysine 20 (H4K20me0) peaks from late S-phase to M-phase. We also attempted to characterize effects of phosphorylation at H4S1 on protein–protein interactions. Specially synthesized photoaffinity bait peptides specifically captured 14-3-3 proteins as novel H4S1ph binding partners, whose interaction was otherwise undetectable by conventional peptide pull-down experiments. This is the first report that analyzes dynamics of PTM pattern on the whole histone H4 tail during cell cycle and enables the identification of PTM binders with low affinities using high-resolution mass spectrometry and photo-affinity bait peptides. PMID:26819910

An Approach for Peptide Identification by De Novo Sequencing of Mixture Spectra.

PubMed

Liu, Yi; Ma, Bin; Zhang, Kaizhong; Lajoie, Gilles

2017-01-01

Mixture spectra occur quite frequently in a typical wet-lab mass spectrometry experiment, which result from the concurrent fragmentation of multiple precursors. The ability to efficiently and confidently identify mixture spectra is essential to alleviate the existent bottleneck of low mass spectra identification rate. However, most of the traditional computational methods are not suitable for interpreting mixture spectra, because they still take the assumption that the acquired spectra come from the fragmentation of a single precursor. In this manuscript, we formulate the mixture spectra de novo sequencing problem mathematically, and propose a dynamic programming algorithm for the problem. Additionally, we use both simulated and real mixture spectra data sets to verify the merits of the proposed algorithm.

Broad spectrum antibiotic compounds and use thereof

DOEpatents

Koglin, Alexander; Strieker, Matthias

2016-07-05

The discovery of a non-ribosomal peptide synthetase (NRPS) gene cluster in the genome of Clostridium thermocellum that produces a secondary metabolite that is assembled outside of the host membrane is described. Also described is the identification of homologous NRPS gene clusters from several additional microorganisms. The secondary metabolites produced by the NRPS gene clusters exhibit broad spectrum antibiotic activity. Thus, antibiotic compounds produced by the NRPS gene clusters, and analogs thereof, their use for inhibiting bacterial growth, and methods of making the antibiotic compounds are described.

Characterization of protein N-glycosylation by tandem mass spectrometry using complementary fragmentation techniques

DOE PAGES

Ford, Kristina L.; Zeng, Wei; Heazlewood, Joshua L.; ...

2015-08-28

The analysis of post-translational modifications (PTMs) by proteomics is regarded as a technically challenging undertaking. While in recent years approaches to examine and quantify protein phosphorylation have greatly improved, the analysis of many protein modifications, such as glycosylation, are still regarded as problematic. Limitations in the standard proteomics workflow, such as use of suboptimal peptide fragmentation methods, can significantly prevent the identification of glycopeptides. The current generation of tandem mass spectrometers has made available a variety of fragmentation options, many of which are becoming standard features on these instruments. Lastly, we have used three common fragmentation techniques, namely CID, HCD,more » and ETD, to analyze a glycopeptide and highlight how an integrated fragmentation approach can be used to identify the modified residue and characterize the N-glycan on a peptide.« less

Genome mining for ribosomally synthesized natural products.

PubMed

Velásquez, Juan E; van der Donk, Wilfred A

2011-02-01

In recent years, the number of known peptide natural products that are synthesized via the ribosomal pathway has rapidly grown. Taking advantage of sequence homology among genes encoding precursor peptides or biosynthetic proteins, in silico mining of genomes combined with molecular biology approaches has guided the discovery of a large number of new ribosomal natural products, including lantipeptides, cyanobactins, linear thiazole/oxazole-containing peptides, microviridins, lasso peptides, amatoxins, cyclotides, and conopeptides. In this review, we describe the strategies used for the identification of these ribosomally synthesized and posttranslationally modified peptides (RiPPs) and the structures of newly identified compounds. The increasing number of chemical entities and their remarkable structural and functional diversity may lead to novel pharmaceutical applications. Copyright © 2010 Elsevier Ltd. All rights reserved.

Antimicrobial proline-rich peptides from the hemolymph of marine snail Rapana venosa.

PubMed

Dolashka, Pavlina; Moshtanska, Vesela; Borisova, Valika; Dolashki, Aleksander; Stevanovic, Stefan; Dimanov, Tzvetan; Voelter, Wolfgang

2011-07-01

Hemolymph of Rapana venosa snails is a complex mixture of biochemically and pharmacologically active components such as peptides and proteins. Antimicrobial peptides are gaining attention as antimicrobial alternatives to chemical food preservatives and commonly used antibiotics. Therefore, for the first time we have explored the isolation, identification and characterisation of 11 novel antimicrobial peptides produced by the hemolymph of molluscs. The isolated peptides from the hemolymph applying ultrafiltration and reverse-phase high-performance liquid chromatography (RP-HPLC) have molecular weights between 3000 and 9500 Da, determined by mass spectrometric analysis. The N-terminal sequences of the peptides identified by Edman degradation matched no peptides in the MASCOT search database, indicating novel proline-rich peptides. UV spectra revealed that these substances possessed the characteristics of protein peptides with acidic isoelectric points. However, no Cotton effects were observed between 190 and 280 nm by circular dichroism spectroscopy. Four of the pro-rich peptides also showed strong antimicrobial activities against tested microorganisms including Gram-positive and Gram-negative bacteria. Copyright © 2011 Elsevier Inc. All rights reserved.

Antigenic properties of HCMV peptides displayed by filamentous bacteriophages vs. synthetic peptides.

PubMed

Ulivieri, Cristina; Citro, Alessandra; Ivaldi, Federico; Mascolo, Dina; Ghittoni, Raffaella; Fanigliulo, Daniela; Manca, Fabrizio; Baldari, Cosima Tatiana; Li Pira, Giuseppina; Del Pozzo, Giovanna

2008-08-15

Several efforts have been invested in the identification of CTL and Th epitopes, as well as in the characterization of their immunodominance and MHC restriction, for the generation of a peptide-based HCMV vaccine. Small synthetic peptides are, however, poor antigens and carrier proteins are important for improving the efficacy of synthetic peptide vaccines. Recombinant bacteriophages appear as promising tools in the design of subunit vaccines. To investigate the antigenicity of peptides carried by recombinant bacteriophages we displayed different HCMV MHCII restricted peptides on the capsid of filamentous bacteriophage (fd) and found that hybrid bacteriophages are processed by human APC and activate HCMV-specific CD4 T-cells. Furthermore we constructed a reporter T-cell hybridoma expressing a chimeric TCR comprising murine alphabeta constant regions and human variable regions specific for the HLA-A2 restricted immunodominant NLV peptide of HCMV. Using the filamentous bacteriophage as an epitope carrier, we detected a more robust and long lasting response of the reporter T-cell hybridoma compared to peptide stimulation. Our results show a general enhancement of T-cell responses when antigenic peptides are carried by phages.

Combining results of multiple search engines in proteomics.

PubMed

Shteynberg, David; Nesvizhskii, Alexey I; Moritz, Robert L; Deutsch, Eric W

2013-09-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.