Peptides In Proteomics Research Articles

Tregitopes and impaired antigen presentation: Drivers of the immunomodulatory effects of IVIg?

IntroductionAlthough intravenous immunoglobulin (IVIg) is commonly used in the clinic to treat various autoimmune and severe inflammatory diseases, the mode of action is not fully elucidated. This work investigates two proposed mechanisms: (1) the potential role of regulatory T‐cell epitopes (Tregitopes) from the constant domain of IgG in the immunosuppressive function of IVIg; and (2) a potential impact of IVIg on the ability of antigen presenting cells (APCs) to present peptides.Methods and ResultsInvestigation of the HLA class II peptide repertoire from IVIg‐loaded dendritic cells (DCs) via MHC‐associated peptide proteomics (MAPPs) revealed that numerous IgG‐derived peptides were strongly presented along the antibody sequence. Surprisingly, Tregitopes 167 and 289 did not show efficient natural presentation although they both bound to HLA class II when directly loaded as “naked” peptides on human DCs. In addition, both Tregitopes could not reproduce the inhibitory effect of IVIg in a human in vitro T‐cell proliferation assay as well as in vivo in mice. MAPPs data demonstrate that presentation of peptides from several antigens remained unchanged even when competed with high doses of IVIg, in both human and mouse.ConclusionThese data suggest that the effects mediated by IVIg are not caused by Tregitopes nor by impaired antigen presentation.

Characterization of CD4 T Cell Epitopes of Infliximab and Rituximab Identified from Healthy Donors.

The chimeric antibodies anti-CD20 rituximab (Rtx) and anti-TNFα infliximab (Ifx) induce antidrug antibodies (ADAs) in many patients with inflammatory diseases. Because of the key role of CD4 T lymphocytes in the initiation of antibody responses, we localized the CD4 T cell epitopes of Rtx and Ifx. With the perspective to anticipate immunogenicity of therapeutic antibodies, identification of the CD4 T cell epitopes was performed using cells collected in healthy donors. Nine T cell epitopes were identified in the variable chains of both antibodies by deriving CD4 T cell lines raised against either Rtx or Ifx. The T cell epitopes often exhibited a good affinity for human leukocyte antigen (HLA)-DR molecules and were part of the peptides identified by MHC-associated peptide proteomics assay from HLA-DR molecules of dendritic cells (DCs) loaded with the antibodies. Two-third of the T cell epitopes identified from the healthy donors stimulated peripheral blood mononuclear cells from patients having developed ADAs against Rtx or Ifx and promoted the secretion of a diversity of cytokines. These data emphasize the predictive value of evaluating the T cell repertoire of healthy donors and the composition of peptides bound to HLA-DR of DCs to anticipate and prevent immunogenicity of therapeutic antibodies.

PROTEOMICS IN MEAT SCIENCE — CURRENT STATUS AND FUTURE PERSPECTIVE

The aim of proteomics is to identify all proteins, their biological activity, post-translational modifications and interactions in a cell, and to identify (quantify?) changes in «proteome» in response to altered biological conditions. A typical proteomics work flow consists of protein extraction, separation, protein or peptide identification and data analysis. Mass spectrometry is the most common method used to detect proteins or peptides in proteomics. This strategy has many applications, including research in meat science, but it is limited by huge biochemical heterogeneity of the proteins and an inability to detect accurately low-abundance proteins. The aim of the present review is to summarize the current knowledge and identify future potential application of proteomics in meat science and technology.

Discovery of short linear motif-mediated interactions through phage display of intrinsically disordered regions of the human proteome.

The intrinsically disordered regions of eukaryotic proteomes are enriched in short linear motifs (SLiMs), which are of crucial relevance for cellular signaling and protein regulation; many mediate interactions by providing binding sites for peptide-binding domains. The vast majority of SLiMs remain to be discovered highlighting the need for experimental methods for their large-scale identification. We present a novel proteomic peptide phage display (ProP-PD) library that displays peptides representing the disordered regions of the human proteome, allowing direct large-scale interrogation of most potential binding SLiMs in the proteome. The performance of the ProP-PD library was validated through selections against SLiM-binding bait domains with distinct folds and binding preferences. The vast majority of identified binding peptides contained sequences that matched the known SLiM-binding specificities of the bait proteins. For SHANK1 PDZ, we establish a novel consensus TxF motif for its non-C-terminal ligands. The binding peptides mostly represented novel target proteins, however, several previously validated protein-protein interactions (PPIs) were also discovered. We determined the affinities between the VHS domain of GGA1 and three identified ligands to 40-130μm through isothermal titration calorimetry, and confirmed interactions through coimmunoprecipitation using full-length proteins. Taken together, we outline a general pipeline for the design and construction of ProP-PD libraries and the analysis of ProP-PD-derived, SLiM-based PPIs. We demonstrated the methods potential to identify low affinity motif-mediated interactions for modular domains with distinct binding preferences. The approach is a highly useful complement to the current toolbox of methods for PPI discovery.

Integrative Analysis of Proteomics Data to Obtain Clinically Relevant Markers.

The analysis of proteomics data can be significantly challenging. Beyond the technical challenges of accurately identifying and quantifying peptides, identifying the most biologically coherent set of biomarkers can be a particularly daunting step. In this chapter, we will review a series of methods implemented in the software AltAnalyze that can be used to normalize proteomics peptide counts, identify a minimal set of the most distinguishing morbidity-associated biomarkers, and connect up these results to known pathways and interacting protein and regulatory networks. Here, we will apply this workflow to two examples that highlight different benefits of an integrated analysis workflow: (1) urine proteomics samples from patients with distinct kidney transplantation morbidities and (2) sudden infant death syndrome. By the end of this chapter, the reader should be able to apply a similar workflow to their own datasets to identify biologically significant protein markers and relevant networks.

Improved affinity at the cost of decreased specificity: a recurring theme in PDZ-peptide interactions.

The E6 protein from human papillomavirus (HPV) plays an important role during productive infection and is a potential drug target. We have previously designed a high affinity bivalent protein binder for the E6 protein, a fusion between a helix from the E6 associated protein and PDZØ9, an engineered variant (L391F/K392M) of the second PDZ domain from synapse associated protein 97 (SAP97 PDZ2). How the substitutions improve the affinity of SAP97 PDZ2 for HPV E6 is not clear and it is not known to what extent they affect the specificity for cellular targets. Here, we explore the specificity of wild type SAP97 PDZ2 and PDZØ9 through proteomic peptide phage display. In addition, we employ a double mutant cycle of SAP97 PDZ2 in which the binding kinetics for nine identified potential cellular peptide ligands are measured and compared with those for the C-terminal E6 peptide. The results demonstrate that PDZØ9 has an increased affinity for all peptides, but at the cost of specificity. Furthermore, there is a peptide dependent coupling free energy between the side chains at positions 391 and 392. This corroborates our previous allosteric model for PDZ domains, involving sampling of intramolecular energetic pathways.

Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance: Simultaneous Component Analysis.

Complex shotgun proteomics peptide profiles obtained in quantitative differential protein expression studies, such as in biomarker discovery, may be affected by multiple experimental factors. These preanalytical factors may affect the measured protein abundances which in turn influence the outcome of the associated statistical analysis and validation. It is therefore important to determine which factors influence the abundance of peptides in a complex proteomics experiment and to identify those peptides that are most influenced by these factors. In the current study we analyzed depleted human serum samples to evaluate experimental factors that may influence the resulting peptide profile such as the residence time in the autosampler at 4 °C, stopping or not stopping the trypsin digestion with acid, the type of blood collection tube, different hemolysis levels, differences in clotting times, the number of freeze-thaw cycles, and different trypsin/protein ratios. To this end we used a two-level fractional factorial design of resolution IV (2(IV)(7-3)). The design required analysis of 16 samples in which the main effects were not confounded by two-factor interactions. Data preprocessing using the Threshold Avoiding Proteomics Pipeline (Suits, F.; Hoekman, B.; Rosenling, T.; Bischoff, R.; Horvatovich, P. Anal. Chem. 2011, 83, 7786-7794, ref 1) produced a data-matrix containing quantitative information on 2,559 peaks. The intensity of the peaks was log-transformed, and peaks having intensities of a low t-test significance (p-value > 0.05) and a low absolute fold ratio (<2) between the two levels of each factor were removed. The remaining peaks were subjected to analysis of variance (ANOVA)-simultaneous component analysis (ASCA). Permutation tests were used to identify which of the preanalytical factors influenced the abundance of the measured peptides most significantly. The most important preanalytical factors affecting peptide intensity were (1) the hemolysis level, (2) stopping trypsin digestion with acid, and (3) the trypsin/protein ratio. This provides guidelines for the experimentalist to keep the ratio of trypsin/protein constant and to control the trypsin reaction by stopping it with acid at an accurately set pH. The hemolysis level cannot be controlled tightly as it depends on the status of a patient's blood (e.g., red blood cells are more fragile in patients undergoing chemotherapy) and the care with which blood was sampled (e.g., by avoiding shear stress). However, its level can be determined with a simple UV spectrophotometric measurement and samples with extreme levels or the peaks affected by hemolysis can be discarded from further analysis. The loadings of the ASCA model led to peptide peaks that were most affected by a given factor, for example, to hemoglobin-derived peptides in the case of the hemolysis level. Peak intensity differences for these peptides were assessed by means of extracted ion chromatograms confirming the results of the ASCA model.

New technologies of molecular engineering and screening for cell signaling studies.

New technologies of molecular engineering and screening for cell signaling studies.

Proteomic peptide phage display uncovers novel interactions of the PDZ1-2 supramodule of syntenin.

Syntenin has crucial roles in cell adhesion, cell migration and synaptic transmission. Its closely linked postsynaptic density‐95, discs large 1, zonula occludens‐1 (PDZ) domains typically interact with C‐terminal ligands. We profile syntenin PDZ1‐2 through proteomic peptide phage display (ProP‐PD) using a library that displays C‐terminal regions of the human proteome. The protein recognizes a broad range of peptides, with a preference for hydrophobic motifs and has a tendency to recognize cryptic internal ligands. We validate the interaction with nectin‐1 through orthogonal assays. The study demonstrates the power of ProP‐PD as a complementary approach to uncover interactions of potential biological relevance.

Ion source-dependent performance of 4-vinylpyridine, iodoacetamide, and N-maleoyl derivatives for the detection of cysteine-containing peptides in complex proteomics.

Cysteine is unique among the proteinogenic amino acids due to its ability to form disulfide bonds. While this property is of vital importance for protein structures and biological processes, it causes difficulties for the mass spectrometric identification of cysteine-containing peptides. A common approach to overcome these problems in bottom-up proteomics is the reduction and covalent modification of sulfhydryl groups prior to enzymatic digestion. In this study, established alkylating agents and N-maleoyl amino acids with variable hydrophobicity were characterized with respect to a variety of relevant parameters and subsequently evaluated in a large-scale analysis using different ion sources. Depending on the compound, the ion source had a profound impact on the relative and absolute identification of cysteine-containing peptides. The best results were obtained by derivatization of the cysteine residues with 4-vinylpyridine and subsequent matrix-assisted laser desorption ionization (MALDI). Modification with 4-vinylpyridine increased the number of cysteine-containing peptides identified with any other compound using LC-MALDI/MS at least by a factor of 2. This experimental observation is mirrored by differences in the gas-phase basicities, which were computed for methyl thiolate derivatives of the compounds using density functional theory. With electrospray ionization (ESI), complementary use of reagents from three different compound classes, e.g., iodoacetamide, 4-vinylpyridine, and N-maleoyl beta-alanine, was beneficial compared to the application of a single reagent.

Collision-Induced Dissociation Mass Spectrometry: A Powerful Tool for Natural Product Structure Elucidation.

Mass spectrometry is a powerful tool in natural product structure elucidation, but our ability to directly correlate fragmentation spectra to these structures lags far behind similar efforts in peptide sequencing and proteomics. Often, manual data interpretation is required and our knowledge of the expected fragmentation patterns for many scaffolds is limited, further complicating analysis. Here, we summarize advances in natural product structure elucidation based upon the application of collision induced dissociation fragmentation mechanisms.

Special issue of 13th Chinese International Peptide Symposium

Chinese peptide research has a legendary history, marked by the successful total synthesis of crystalline insulin as early as in the 1960s. The Chinese International Peptide Symposium was started in 1990 to promote the development of peptide chemistry and biology in China and the communication between Chinese and international scientists in related fields. As a bi-annual meeting, the Symposium has witnessed the rapid advances of Chinese peptide research that was well supported by the great economic growth of China. The 13th Chinese International Peptide Symposium with the theme of ‘Peptides: Treasure of Chemistry and Biology’ took place from June 30 to July 4, 2014 in Datong City, Shanxi Province, China. There were about 300 scientists attending the Symposium, including about 50 international delegates from the USA, Australia, Japan, UK, France, Singapore, Greek, Korea, Canada, and Switzerland. The Symposium was also attended and supported by over 30 domestic and international companies. The Symposium presented the most recent developments of peptide research in the following fields: synthesis of natural and unnatural amino acids and analogues; methodology of peptide/protein synthesis; amino acids and peptides-based asymmetric catalysis; peptide drugs, mimetics, and conjugates; antimicrobial peptides, peptide vaccines, glycopeptides, and neuropeptides; peptide/protein material sciences; structural and conformational studies of peptides/proteins; technological advances in peptide purification and analysis; peptide ligands, receptors, and signaling; role of peptides in genomics, proteomics, and peptidomics. This issue of Journal of Peptide Science collects a representative number of articles presented at the Symposium. We wish to share with the readers some of the current research trends and technology level of peptide research in China. We would like to thank all authors for their excellent contributions. We would also like to thank Luis Moroder for helping us in handling the manuscripts.

H1N1 viral proteome peptide microarray predicts individuals at risk for H1N1 infection and segregates infection versus Pandemrix(®) vaccination.

A high content peptide microarray containing the entire influenza A virus [A/California/08/2009(H1N1)] proteome and haemagglutinin proteins from 12 other influenza A subtypes, including the haemagglutinin from the [A/South Carolina/1/1918(H1N1)] strain, was used to gauge serum IgG epitope signatures before and after Pandemrix® vaccination or H1N1 infection in a Swedish cohort during the pandemic influenza season 2009. A very narrow pattern of pandemic flu-specific IgG epitope recognition was observed in the serum from individuals who later contracted H1N1 infection. Moreover, the pandemic influenza infection generated IgG reactivity to two adjacent epitopes of the neuraminidase protein. The differential serum IgG recognition was focused on haemagglutinin 1 (H1) and restricted to classical antigenic sites (Cb) in both the vaccinated controls and individuals with flu infections. We further identified a novel epitope VEPGDKITFEATGNL on the Ca antigenic site (251–265) of the pandemic flu haemagglutinin, which was exclusively recognized in serum from individuals with previous vaccinations and never in serum from individuals with H1N1 infection (confirmed by RNA PCR analysis from nasal swabs). This epitope was mapped to the receptor-binding domain of the influenza haemagglutinin and could serve as a correlate of immune protection in the context of pandemic flu. The study shows that unbiased epitope mapping using peptide microarray technology leads to the identification of biologically and clinically relevant target structures. Most significantly an H1N1 infection induced a different footprint of IgG epitope recognition patterns compared with the pandemic H1N1 vaccine.

Quantitative proteomics reveals the kinetics of trypsin-catalyzed protein digestion.

Trypsin is the popular protease to digest proteins into peptides in shotgun proteomics, but few studies have attempted to systematically investigate the kinetics of trypsin-catalyzed protein digestion in proteome samples. In this study, we applied quantitative proteomics via triplex stable isotope dimethyl labeling to investigate the kinetics of trypsin-catalyzed cleavage. It was found that trypsin cleaves the C-terminal to lysine (K) and arginine (R) residues with higher rates for R. And the cleavage sites surrounded by neutral residues could be quickly cut, while those with neighboring charged residues (D/E/K/R) or proline residue (P) could be slowly cut. In a proteome sample, a huge number of proteins with different physical chemical properties coexists. If any type of protein could be preferably digested, then limited digestion could be applied to reduce the sample complexity. However, we found that protein abundance and other physicochemical properties, such as molecular weight (Mw), grand average of hydropathicity (GRAVY), aliphatic index, and isoelectric point (pI) have no notable correlation with digestion priority of proteins.

NRPquest: Coupling Mass Spectrometry and Genome Mining for Nonribosomal Peptide Discovery.

Nonribosomal peptides (NRPs) such as vancomycin and daptomycin are among the most effective antibiotics. While NRPs are biomedically important, the computational techniques for sequencing these peptides are still in their infancy. The recent emergence of mass spectrometry techniques for NRP analysis (capable of sequencing an NRP from small amounts of nonpurified material) revealed an enormous diversity of NRPs. However, as many NRPs have nonlinear structure (e.g., cyclic or branched-cyclic peptides), the standard de novo sequencing tools (developed for linear peptides) are not applicable to NRP analysis. Here, we introduce the first NRP identification algorithm, NRPquest, that performs mutation-tolerant and modification-tolerant searches of spectral data sets against a database of putative NRPs. In contrast to previous studies aimed at NRP discovery (that usually report very few NRPs), NRPquest revealed nearly a hundred NRPs (including unknown variants of previously known peptides) in a single study. This result indicates that NRPquest can potentially make MS-based NRP identification as robust as the identification of linear peptides in traditional proteomics.

Extended bottom-up proteomics with secreted aspartic protease Sap9.

Advances in biological applications of mass spectrometry-based bottom-up proteomics are oftentimes limited by the extreme complexity of biological samples, e.g., proteomes or protein complexes. One of the reasons for it is in the complexity of the mixtures of enzymatically (most often using trypsin) produced short (<3 kDa) peptides, which may exceed the analytical capabilities of liquid chromatography and mass spectrometry. Information on localization of protein modifications may also be affected by the small size of typically produced peptides. On the other hand, advances in high-resolution mass spectrometry and liquid chromatography have created an intriguing opportunity of improving proteome analysis by gradually increasing the size of enzymatically-derived peptides in MS-based bottom-up proteomics. Bioinformatics has already confirmed the envisioned advantages of such approach. The remaining bottle-neck is an enzyme that could produce longer peptides. Here, we report on the characterization of a possible candidate enzyme, Sap9, which may be considered for producing longer, e.g., 3-7 kDa, peptides and lead to a development of extended bottom-up proteomics.

MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments.

MSstats is an R package for statistical relative quantification of proteins and peptides in mass spectrometry-based proteomics. Version 2.0 of MSstats supports label-free and label-based experimental workflows and data-dependent, targeted and data-independent spectral acquisition. It takes as input identified and quantified spectral peaks, and outputs a list of differentially abundant peptides or proteins, or summaries of peptide or protein relative abundance. MSstats relies on a flexible family of linear mixed models. The code, the documentation and example datasets are available open-source at www.msstats.org under the Artistic-2.0 license. The package can be downloaded from www.msstats.org or from Bioconductor www.bioconductor.org and used in an R command line workflow. The package can also be accessed as an external tool in Skyline (Broudy et al., 2014) and used via graphical user interface.

N-terminal sequence tagging using reliably determined b2 ions: a useful approach to deconvolute tandem mass spectra of co-fragmented peptides in proteomics.

With the recent introduction of higher-energy collisional dissociation (HCD) in Orbitrap mass spectrometry, the popularity of that technique has grown tremendously in the proteomics society. HCD spectra, however, are characterized by a limited distribution of bn-type ions, which permit the generation of reliable sequence tags based on complementary b,y pairs both for de novo sequencing and sequence tagging strategies. Instead, most peptide HCD spectra (~95%) are dominated with b2 ions. In this work, we analyzed positive predictive values of b2 ions in HCD, and found that b2 ions can be determined with >97% certainty in the presence of a2 and its complementary yn-2 ions. Analytically, b2 ions provide information on the composition of the first two N-terminal amino acids in peptides. Their utilization in N-terminal sequence tagging leads to a significant decrease in false discovery rate by filtering out false positives while retaining true positive identifications. As a consequence, the number of peptide spectrum matches (PSMs) increased by 4.8% at fixed FDR (1%). This approach allows for deconvolution of mixture spectra and increased the number of PSM to 9.2% in a complex human sample and to 24% in a complex sample of synthetic peptides at 1% FDR.

Boron nitride as desalting material in combination with phosphopeptide enrichment in shotgun proteomics

Hydrophilic peptides in shotgun proteomics have been shown to be problematic in conventional chromatography. Typically, C18 solid phase extraction or peptide traps are used for desalting the sample prior to mass spectrometry analysis, but the capacity to retain hydrophilic peptides is not very high, causing a bias toward more hydrophobic peptides. This is particularly problematic in phosphoproteomic studies. We tested the compatibility of commercially available boron nitride as a novel material for peptide desalting. Boron nitride can be used to recover a wide range of peptides with different physicochemical properties comparable to combined C18 and graphite carbon material.

Aggregation of Human Recombinant Monoclonal Antibodies Influences the Capacity of Dendritic Cells to Stimulate Adaptive T-Cell Responses In Vitro

Subvisible proteinaceous particles which are present in all therapeutic protein formulations are in the focus of intense discussions between health authorities, academics and biopharmaceutical companies in the context of concerns that such particles could promote unwanted immunogenicity via anti-drug antibody formation. In order to provide further understanding of the subject, this study closely examines the specific biological effects proteinaceous particles may exert on dendritic cells (DCs) as the most efficient antigen-presenting cell population crucial for the initiation of the adaptive immune response. Two different model IgG antibodies were subjected to three different types of exaggerated physical stress to generate subvisible particles in far greater concentrations than the ones typical for the currently marketed biotherapeutical antibodies. The aggregated samples were used in in vitro biological assays in order to interrogate the early DC-driven events that initiate CD4 T-cell dependent humoral adaptive immune responses – peptide presentation capacity and co-stimulatory activity of DCs. Most importantly, antigen presentation was addressed with a unique approach called MHC-associated Peptide Proteomics (MAPPs), which allows for identifying the sequences of HLA-DR associated peptides directly from human dendritic cells.The experiments demonstrated that highly aggregated solutions of two model mAbs generated under controlled conditions can induce activation of human monocyte-derived DCs as indicated by upregulation of typical maturation markers including co-stimulatory molecules necessary for CD4 T-cell activation. Additional data suggest that highly aggregated proteins could induce in vitro T-cell responses. Intriguingly, strong aggregation-mediated changes in the pattern and quantity of antigen-derived HLA-DR associated peptides presented on DCs were observed, indicating a change in protein processing and presentation. Increasing the amounts of subvisible proteinaceous particles correlated very well with the pronounced increase in the peptide number and clusters presented in the context of class II HLA-DR molecules, suggesting a major involvement of a mass-action mechanism of altering the presentation.