The Medicago truncatula small protein proteome and peptidome

The small protein and native peptide component of plant tissues is a neglected area of proteomic studies. We have used fractionation techniques for denatured and nondenatured protein preparations combined with 2-D LC tandem mass spectrometry to examine the sequences of small proteins and peptides in four tissues of the model legume, Medicago truncatula: the root tip and root of germinating seedlings, nitrogen fixing nodules, and young leaves. The isolation and fractionation strategies successfully enriched the small protein and native peptide content of the samples. Eighty-one small M. truncatula proteins and native peptides were identified. Most samples were dominated by ribosomal and histone proteins, and leaf samples possessed photosynthesis-related proteins. Secreted proteins such as lipid transfer proteins were common to several tissues. Twenty-four hours after germination, the roots and root tip tissues possessed several "seed-specific" and late-embryogenesis proteins. We conclude that these proteins are present in cells prior to germination and that they are subsequently used as a nutritional source for the young tissues. Native UV absorbing peptides were detected in very low molecular weight fractions and sequenced. Each peptide shared C-terminal residues and showed homology to the seed storage protein legumin. The strategies used here would be suitable for combining bioassays and mass spectrometry to identify bioactive peptides in the M. truncatula peptidome.     

Helices in peptoids of alpha- and beta-peptides

Peptoids of alpha- and beta-peptides (alpha- and beta-peptoids) can be obtained by shifting the amino acid side chains from the backbone carbon atoms of the monomer constituents to the peptide nitrogen atoms. They are, therefore, N-substituted poly-glycines and poly-beta-alanines, respectively. Due to the substituted nitrogen atoms, the ability for hydrogen bond formation between peptide bonds gets lost. It may be very interesting to see whether such non-natural oligomers could be regarded as foldamers, which fold into definite backbone conformers. In this paper, we provide a complete overview on helix formation in alpha- and beta-peptoids on the basis of systematic theoretical conformational analyses employing the methods of ab initio molecular orbital (MO) theory. It can be shown that the alpha- and beta-peptoid structures form helical structures with both trans and cis peptide bonds despite the missing hydrogen bonds. Obviously, the conformational properties of the backbone are more important for folding than the possibility of hydrogen bonding. There are close relationships between the helices of alpha-peptoids and poly-glycine and poly-proline helices of alpha-peptides, whereas the helices of beta-peptoids correspond to the well-known helical structures of beta-peptides as, for instance, the 3(1)-helix of beta-peptides with 14-membered hydrogen-bonded rings. Thus, alpha- and beta-peptoids enrich the field of foldamers and may be used as useful tools in peptide and protein design.     

A computational approach toward label-free protein quantification using predicted peptide detectability

We propose here a new concept of peptide detectability which could be an important factor in explaining the relationship between a protein's quantity and the peptides identified from it in a high-throughput proteomics experiment. We define peptide detectability as the probability of observing a peptide in a standard sample analyzed by a standard proteomics routine and argue that it is an intrinsic property of the peptide sequence and neighboring regions in the parent protein. To test this hypothesis we first used publicly available data and data from our own synthetic samples in which quantities of model proteins were controlled. We then applied machine learning approaches to demonstrate that peptide detectability can be predicted from its sequence and the neighboring regions in the parent protein with satisfactory accuracy. The utility of this approach for protein quantification is demonstrated by peptides with higher detectability generally being identified at lower concentrations over those with lower detectability in the synthetic protein mixtures. These results establish a direct link between protein concentration and peptide detectability. We show that for each protein there exists a level of peptide detectability above which peptides are detected and below which peptides are not detected in an experiment. We call this level the minimum acceptable detectability for identified peptides (MDIP) which can be calibrated to predict protein concentration. Triplicate analysis of a biological sample showed that these MDIP values are consistent among the three data sets.     

The sequence TGAAKAVALVL from glyceraldehyde-3-phosphate dehydrogenase displays structural ambivalence and interconverts between alpha-helical and beta-hairpin conformations mediated by collapsed conformational states.

The peptide TGAAKAVALVL from glyceraldehyde-3-phosphate dehydrogenase adopts a helical conformation in the crystal structure and is a site for two hydrated helical segments, which are thought to be helical folding intermediates. Overlapping sequences of four to five residues from the peptide, sample both helical and strand conformations in known protein structures, which are dissimilar to glyceraldehyde-3-phosphate dehydrogenase suggesting that the peptide may have a structural ambivalence. Molecular dynamics simulations of the peptide sequence performed for a total simulation time of 1.2 micros, starting from the various initial conformations using GROMOS96 force field under NVT conditions, show that the peptide samples a large number of conformational forms with transitions from alpha-helix to beta-hairpin and vice versa. The peptide, therefore, displays a structural ambivalence. The mechanism from alpha-helix to beta-hairpin transition and vice versa reveals that the compact bends and turns conformational forms mediate such conformational transitions. These compact structures including helices and hairpins have similar hydrophobic radius of gyration (Rgh) values suggesting that similar hydrophobic interactions govern these conformational forms. The distribution of conformational energies is Gaussian with helix sampling lowest energy followed by the hairpins and coil. The lowest potential energy of the full helix may enable the peptide to take up helical conformation in the crystal structure of the glyceraldehyde-3-phosphate dehydrogenase, even though the peptide has a preference for hairpin too. The relevance of folding and unfolding events observed in our simulations to hydrophobic collapse model of protein folding are discussed.     

Nitrogen fixation associated with sago (Metroxylon sagu) and some implications

Aims: To determine the presence and contribution of diazotrophic bacteria to nitrogen concentrations in edible starch derived from the sago palm (Metroxylon sagu). Methods and Results: Isolation of diazotrophic bacteria and analysis of nitrogen fixation were conducted on pith, root and sago starch samples. Acetylene reduction showed that five of ten starch samples were fixing nitrogen. Two presumptive nitrogen‐fixing bacteria from starch fixed nitrogen in pure culture and five isolates were positive for the nif H gene. Nitrogen concentrations in 51 starch samples were low (37 samples <0·2 g kg^?1; 14 ranging from 0·2 to 2·0 g kg^?1). Conclusions: Nitrogen fixation occurs in sago starch, which undoubtedly plays a role in fermentation ecology. Nitrogen levels are considered too low to be of nutritional benefit and to protect against nutritional‐associated illnesses. Significance and Impact of the Study: Sago starch does not add significantly to the protein calorie intake and may be associated with susceptibility to nutritional‐associated illness.     

Fast and accurate identification of semi-tryptic peptides in shotgun proteomics

MOTIVATION: One of the major problems in shotgun proteomics is the low peptide coverage when analyzing complex protein samples. Identifying more peptides, e.g. non-tryptic peptides, may increase the peptide coverage and improve protein identification and/or quantification that are based on the peptide identification results. Searching for all potential non-tryptic peptides is, however, time consuming for shotgun proteomics data from complex samples, and poses a challenge for a routine data analysis. RESULTS: We hypothesize that non-tryptic peptides are mainly created from the truncation of regular tryptic peptides before separation. We introduce the notion of truncatability of a tryptic peptide, i.e. the probability of the peptide to be identified in its truncated form, and build a predictor to estimate a peptide's truncatability from its sequence. We show that our predictions achieve useful accuracy, with the area under the ROC curve from 76% to 87%, and can be used to filter the sequence database for identifying truncated peptides. After filtering, only a limited number of tryptic peptides with the highest truncatability are retained for non-tryptic peptide searching. By applying this method to identification of semi-tryptic peptides, we show that a significant number of such peptides can be identified within a searching time comparable to that of tryptic peptide identification.     

Bayesian Analysis of iTRAQ Data with Nonrandom Missingness: Identification of Differentially Expressed Proteins

iTRAQ (isobaric Tags for Relative and Absolute Quantitation) is a technique that allows simultaneous quantitation of proteins in multiple samples. In this paper, we describe a Bayesian hierarchical model-based method to infer the relative protein expression levels and hence to identify differentially expressed proteins from iTRAQ data. Our model assumes that the measured peptide intensities are affected by both protein expression levels and peptide specific effects. The values of these two effects across experiments are modeled as random effects. The nonrandom missingness of peptide data is modeled with a logistic regression which relates the missingness probability for a peptide with the expression level of the protein that produces this peptide. We propose a Markov chain Monte Carlo method for the inference of model parameters, including the relative expression levels across samples. Our simulation results suggest that the estimates of relative protein expression levels based on the MCMC samples have smaller bias than those estimated from ANOVA models or fold changes. We apply our method to an iTRAQ dataset studying the roles of Caveolae for postnatal cardiovascular function.     

Spontaneous degradation of polypeptides at aspartyl and asparaginyl residues: effects of the solvent dielectric.

We have investigated the spontaneous degradation of aspartate and asparagine residues via succinimide intermediates in model peptides in organic co-solvents. We find that the rate of deamidation at asparagine residues is markedly reduced in solvents of low dielectric strength. Theoretical considerations suggest that this decrease in rate is due to the destabilization of the deprotonated peptide bond nitrogen anion that is the postulated attacking species in succinimide formation. This result suggests that asparagine residues in regions with low dielectric constants, such as the interior of a protein or in a membrane bilayer, are protected from this type of degradation reaction. On the other hand, we found little or no effect on the rate of succinimide-mediated isomerization of aspartate residues when subjected to the same changes in dielectric constant. In this case, the destabilization of the attacking peptide bond nitrogen anion may be balanced by increased protonation of the aspartyl side chain carboxyl group, a reaction that results in a superior leaving group. Consequently, any protein structure or conformation that would increase the protonation of an aspartate side chain carboxyl group can be expected to render that residue more labile. These results may help explain why particular aspartate residues have been found to degrade in proteins at rates comparable to those of asparagine residues, even though aspartyl-containing peptides degrade more slowly than corresponding asparaginyl-containing peptides in aqueous solutions.     

P-Mod: an algorithm and software to map modifications to peptide sequences using tandem MS data

The discovery of unanticipated protein modifications is one of the most challenging problems in proteomics. Whereas widely used algorithms such as Sequest and Mascot enable mapping of modifications when the mass and amino acid specificity are known, unexpected modifications cannot be identified with these tools. We have developed an algorithm and software called P-Mod, which enables discovery and sequence mapping of modifications to target proteins known to be represented in the analysis or identified by Sequest. P-Mod matches MS/MS spectra to peptide sequences in a search list. For spectra of modified peptides, P-Mod calculates mass differences between search peptide sequences and MS/MS precursors and localizes the mass shift to a sequence position in the peptide. Because modifications are detected as mass shifts, P-Mod does not require the user to guess at masses or sequence locations of modifications. P-Mod uses extreme value statistics to assign p value estimates to sequence-to-spectrum matches. The reported p values are scaled to account for the number of comparisons, so that error rates do not increase with the expanded search lists that result from incorporating potential peptide modifications. Combination of P-Mod searches from multiple LC-MS/MS analyses and multiple samples revealed previously unreported BSA modifications, including a novel decarboxymethylation or D-->G substitution at position 579 of the protein. P-Mod can serve a unique role in the identification of protein modifications both from exogenous and endogenous sources and may be useful for identifying modified protein forms as biomarkers for toxicity and disease processes.     

Mass spectrometry of protein modifications by reactive oxygen and nitrogen species

The modification of proteins by reactive oxygen and nitrogen species plays an important role in various biologic processes involving protein activation and inactivation, protein translocation and turnover during signal transduction, stress response, proliferation, and apoptosis. Recent advances in protein and peptide separation and mass spectrometry provide increasingly sophisticated tools for the quantitative analysis of such protein modifications, which are absolutely necessary for their correlation with biologic phenomena. The present review focuses specifically on the qualitative and quantitative mass spectrometric analysis of the most common protein modifications caused by reactive oxygen and nitrogen species in vivo and in vitro and details a case study on a membrane protein the sarco/endoplasmic reticulum Ca-ATPase (SERCA).     

Two-dimensional mass spectra generated from the analysis of 15N-labeled and unlabeled peptides for efficient protein identification and de novo peptide sequencing

Protein identification has been greatly facilitated by database searches against protein sequences derived from product ion spectra of peptides. This approach is primarily based on the use of fragment ion mass information contained in a MS/MS spectrum. Unambiguous protein identification from a spectrum with low sequence coverage or poor spectral quality can be a major challenge. We present a two-dimensional (2D) mass spectrometric method in which the numbers of nitrogen atoms in the molecular ion and the fragment ions are used to provide additional discriminating power for much improved protein identification and de novo peptide sequencing. The nitrogen number is determined by analyzing the mass difference of corresponding peak pairs in overlaid spectra of (15)N-labeled and unlabeled peptides. These peptides are produced by enzymatic or chemical cleavage of proteins from cells grown in (15)N-enriched and normal media, respectively. It is demonstrated that, using 2D information, i.e., m/z and its associated nitrogen number, this method can, not only confirm protein identification results generated by MS/MS database searching, but also identify peptides that are not possible to identify by database searching alone. Examples are presented of analyzing Escherichia coli K12 extracts that yielded relatively poor MS/MS spectra, presumably from the digests of low abundance proteins, which can still give positive protein identification using this method. Additionally, this 2D MS method can facilitate spectral interpretation for de novo peptide sequencing and identification of posttranslational or other chemical modifications. We envision that this method should be particularly useful for proteome expression profiling of organelles or cells that can be grown in (15)N-enriched media.     

Vibrational averaging of chemical shift anisotropies in model peptides

The effects of chemical shift anisotropy (CSA) are evident in line-shapes or side-band analysis in solid-state NMR, in the observed line positions in partially oriented samples, and in relaxation effects in liquid-state studies. In all of these cases, the effective shielding tensor is influenced by fast vibrational averaging in addition to larger-amplitude internal motions and to overall libration or rotation. Here we compute the contributions of vibrational averaging (including zero-point motions) to the CSA relaxation strengths for the nitrogen and carbonyl carbon in two simple peptide models, and for snapshots taken from a path-integral simulation of a small protein. Because the ¹⁵N shielding tensor is determined by all the atoms of the peptide group, it is less influenced by vibrational motion than (for example) the N–H dipolar interaction, which is more sensitive to the motion of the light hydrogen atom. Computed order parameters for CSA averaging are hence much closer to unity than are N–H dipolar order parameters. This leads to a reduction by about 9% in the magnitude of the amide nitrogen CSA that is needed to fit liquid-state relaxation data. Similar considerations apply to the carbonyl carbon shielding tensor, but in this case the differences between dipolar and CSA averaging are smaller. These considerations will be important for making comparisons between CSA tensors extracted from various NMR experiments, and for comparisons to quantum chemical calculations carried out on static conformers.     

Structure and stability of the CuII complexes with tandem repeats of the chicken prion

Prion protein (PrP) misfolding is one of the pivotal issues in understanding the rudiments of neurodegenerative disorders. The conformational change of mammalian cellular PrP to scrapie PrP is caused by an unknown agent, but there is reasonable evidence supporting the key role of copper ions in this process. The structure of the avian PrP was found to be very similar to the mammalian protein, although there is only 30% homology in the secondary structure. This work shows that copper ions are very effectively bound by hexarepeat fragments of chicken prion protein, although not as effectively as it was found in the case of mammalian protein. By means of potentiometric and spectroscopic techniques (nuclear magnetic resonance, circular dichroism, UV-vis, and electronic paramagnetic resonance), it was shown that Cu(II) ions coordinate to the chicken PrP hexapeptide domain in physiological pH via imidazole nitrogen donors of His residue(s). The binding pattern changes the structure of peptide involved, indicating a possible impact of Cu(II) ions in the biology and pathology of nonmammalian PrP, which could be similar to that found for mammalian PrP. The present study shows that, similar to the human prion octapeptide repeats, chicken prion hexapeptide repeats might bind copper ions in two different ways, depending on the number of repeats and metal/ligand molar ratio: (i) an intra-repeat coordination mode in which copper ion is chelated by His imidazole and deprotonated amide nitrogen in monomeric peptide and (ii) an inter-repeat coordination mode in which a polymeric peptide ligand (dimer and trimer) forms polyimidazole complexes that are very stable at physiological pH. Two proline residues inserted into the hexapeptide unit have a critical impact on the metal-binding ability.     

A profile of an endosymbiont-enriched fraction of the coral Stylophora pistillata reveals proteins relevant to microbial-host interactions

This study examines the response of Symbiodinium sp. endosymbionts from the coral Stylophora pistillata to moderate levels of thermal "bleaching" stress, with and without trace metal limitation. Using quantitative high throughput proteomics, we identified 8098 MS/MS events relating to individual peptides from the endosymbiont-enriched fraction, including 109 peptides meeting stringent criteria for quantification, of which only 26 showed significant change in our experimental treatments; 12 of 26 increased expression in response to thermal stress with little difference affected by iron limitation. Surprisingly, there were no significant increases in antioxidant or heat stress proteins; those induced to higher expression were generally involved in protein biosynthesis. An outstanding exception was a massive 114-fold increase of a viral replication protein indicating that thermal stress may substantially increase viral load and thereby contribute to the etiology of coral bleaching and disease. In the absence of a sequenced genome for Symbiodinium or other photosymbiotic dinoflagellate, this proteome reveals a plethora of proteins potentially involved in microbial-host interactions. This includes photosystem proteins, DNA repair enzymes, antioxidant enzymes, metabolic redox enzymes, heat shock proteins, globin hemoproteins, proteins of nitrogen metabolism, and a wide range of viral proteins associated with these endosymbiont-enriched samples. Also present were 21 unusual peptide/protein toxins thought to originate from either microbial consorts or from contamination by coral nematocysts. Of particular interest are the proteins of apoptosis, vesicular transport, and endo/exocytosis, which are discussed in context of the cellular processes of coral bleaching. Notably, the protein complement provides evidence that, rather than being expelled by the host, stressed endosymbionts may mediate their own departure.     

Use of a chimeric synthetic peptide from the core p19 protein and the envelope gp46 glycoprotein in the immunodiagnosis of HTLV-II virus infection

A chimeric synthetic peptide incorporating immunodominant epitope of the p19 gag protein (116-134) and the gp46 env protein (178-200) of HTLV-II virus, separated by two glycine residues, was synthesized by conventional solid-phase peptide synthesis. The antigenic activity of this peptide was evaluated by Ultramicro Enzyme-linked immunosorbent assay (UMELISA) by using panels of anti-HTLV-II positive sera (n = 9), anti-HTLV-I/II positive sera (n = 2), HTLV-positive (untypeable) serum samples (n = 1),and anti-HTLV-I positive sera (n = 14), while specificity was evaluated with samples from healthy blood donors (n = 20). The efficacy of the chimeric peptide in solid-phase immunoassays was compared with the monomeric peptides. Data demonstrated that the chimeric peptide was the most reactive because it detected antibodies to virus efficiently. This may be related to peptide adsorption to the solid surface and epitope accessibility to the antibodies. The results indicate that chimeric peptide as coating antigen is very useful for the immunodiagnosis of HTLV-II infection.     

Global stability of plasma proteomes for mass spectrometry-based analyses

Peptide-based mass spectrometry approaches, such as multiple reaction monitoring, provide a powerful means to measure candidate protein biomarkers in plasma. A potential confounding problem is the effect of preanalytical variables, which may affect the integrity of proteins and peptides. Although some blood proteins undergo rapid physiological proteolysis ex vivo, the stability of most plasma proteins to preanalytical variables remains largely unexplored. We applied liquid chromatography-tandem mass spectrometry shotgun proteomics and multiple reaction monitoring analyses to characterize the stability of proteins at the peptide level in plasma. We systematically evaluated the effects of delay in plasma preparation at different temperatures, multiple freeze-thaw cycles and erythocyte hemolysis on peptide and protein inventories in prospectively collected human plasma. Time course studies indicated few significant changes in peptide and protein identifications, semitryptic peptides and methionine-oxidized peptides in plasma from blood collected in EDTA plasma tubes and stored for up to a week at 4 °C or room temperature prior to plasma isolation. Similarly, few significant changes were observed in similar analyses of plasma subjected to up to 25 freeze-thaw cycles. Hemolyzed samples produced no significant differences beyond the presence of hemoglobin proteins. Finally, paired comparisons of plasma and serum samples prepared from the same patients also yielded few significant differences, except for the depletion of fibrinogen in serum. Blood proteins thus are broadly stable to preanalytical variables when analyzed at the peptide level. Collection protocols to generate plasma for multiple reaction monitoring-based analyses may have different requirements than for other analyses directed at intact proteins.     

Peptide mapping of heterogeneous protein samples.

A simple two-dimensional electrophoretic method for peptide mapping of heterogeneous protein samples is presented. The reduced and denatured proteins of the mixture are separated in a first dimension by sodium dodecyl sulfate-polyacrylamide slab gel electrophoresis. After completion of the electrophoresis, the whole gel lane is equilibrated in stacking gel buffer and is transferred at right angles onto a second slab gel. A protease solution is overlayed on the gel lane and a partial proteolysis of the proteins to be analyzed is performed during the stacking phase of the second electrophoresis. The second electrophoresis resolves the characteristic pattern of peptides of each individual protein as a series of spots located below the original position of the undigested protein. The peptide maps of the following samples are presented as examples: protein P23 and P23* of bacteriophage T4, membranes of Dictyostelium discoideum, membranes of human erythrocytes, and 35S-labeled proteins of D. discoideum synthesized in vivo or in a cell-free wheat germ extract. In complex samples, up to 20 individual proteins can be analyzed at once and a protein comprising only 1% of the total sample generates a clearly identifiable peptide pattern. Good reproducibility of the patterns obtained allows the comparison of samples of different origins.     

The importance of peptide detectability for protein identification, quantification, and experiment design in MS/MS proteomics

Peptide detectability is defined as the probability that a peptide is identified in an LC-MS/MS experiment and has been useful in providing solutions to protein inference and label-free quantification. Previously, predictors for peptide detectability trained on standard or complex samples were proposed. Although the models trained on complex samples may benefit from the large training data sets, it is unclear to what extent they are affected by the unequal abundances of identified proteins. To address this challenge and improve detectability prediction, we present a new algorithm for the iterative learning of peptide detectability from complex mixtures. We provide evidence that the new method approximates detectability with useful accuracy and, based on its design, can be used to interpret the outcome of other learning strategies. We studied the properties of peptides from the bacterium Deinococcus radiodurans and found that at standard quantities, its tryptic peptides can be roughly classified as either detectable or undetectable, with a relatively small fraction having medium detectability. We extend the concept of detectability from peptides to proteins and apply the model to predict the behavior of a replicate LC-MS/MS experiment from a single analysis. Finally, our study summarizes a theoretical framework for peptide/protein identification and label-free quantification.