An isotope coding strategy for proteomics involving both amine and carboxyl group labeling

This paper describes a heavy isotope coding strategy for the analysis of all types of tryptic peptides, including those that are N-terminally blocked and from the C-terminus of proteins. The method exploits differential derivatization of amine and carboxyl groups generated during proteolysis as a means of coding. Carboxyl groups produced during proteolysis incorporate 18O from H218O. Peptides from the C-terminus of proteins were not labeled with 18O unless they contained a basic C-terminal amino acid. Primary amines from control and experimental samples were differentially acylated after proteolysis with either 1H3- or 2H3-N-acetoxysuccinamide. When these two types of labeling were combined, unique coding patterns were achieved for peptides arising from the C-termini and blocked N-termini of proteins. This method was used to (1) distinguish C-terminal peptides in model proteins, (2) recognize N-terminal peptides from proteins in which the amino terminus is acylated, and (3) identify primary structure variations between proteins from different sources.     

Quantification in proteomics through stable isotope coding: a review

This review focuses on techniques for quantification and identification in proteomics by stable isotope coding. Methods are examined for analyzing expression, post-translational modifications, protein:protein interactions, single amino acid polymorphism, and absolute quantification. The bulk of the quantification literature in proteomics focuses on expression analysis, where a wide variety of methods targeting different features of proteins are described. Methods for the analysis of post-translational modification (PTM) focus primarily on phosphorylation and glycosylation, where quantification is achieved in two ways, either by substitution or tagging of the PTM with an isotopically coded derivatizing agent in a single process or by coding and selecting PTM modified peptides in separate operations. Absolute quantification has been achieved by age-old internal standard methods, in which an isotopically labeled isoform of an analyte is synthesized and added to a mixture at a known concentration. One of the surprises is that isotope coding can be a valuable aid in the examination of intermolecular association of proteins through stimulus:response studies. Preliminary efforts to recognize single amino acid polymorphism are also described. The review ends with the conclusion that (1) isotope ratio analysis of protein concentration between samples does not necessarily relate directly to protein expression and rate of PTM and (2) that multiple new methods must be developed and applied simultaneously to make existing stable isotope quantification methods more meaningful. Although stable isotope coding is a powerful, wonderful new technique, multiple analytical issues must be solved for the technique to reach its full potential as a tool to study biological systems.     

Schizophrenia proteomics: biomarkers on the path to laboratory medicine?

Over two million Americans are afflicted with schizophrenia, a debilitating mental health disorder with a unique symptomatic and epidemiological profile. Genomics studies have hinted towards candidate schizophrenia susceptibility chromosomal loci and genes. Modern proteomic tools, particularly mass spectrometry and expression scanning, aim to identify both pathogenic-revealing and diagnostically significant biomarkers. Only a few studies on basic proteomics have been conducted for psychiatric disorders relative to the plethora of cancer specific experiments. One such proteomic utility enables the discovery of proteins and biological marker fingerprinting profiling techniques (SELDI-TOF-MS), and then subjects them to tandem mass spectrometric fragmentation and de novo protein sequencing (MALDI-TOF/TOF-MS) for the accurate identification and characterization of the proteins. Such utilities can explain the pathogenesis of neuro-psychiatric disease, provide more objective testing methods, and further demonstrate a biological basis to mental illness. Although clinical proteomics in schizophrenia have yet to reveal a biomarker with diagnostic specificity, methods that better characterize the disorder using endophenotypes can advance findings. Schizophrenia biomarkers could potentially revolutionize its psychopharmacology, changing it into a more hypothesis and genomic/proteomic-driven science.     

Protein sequence tags: a novel solution for comparative proteomics

Comparative proteome profiling using stable isotope peptide labelling and mass spectrometry has emerged as a promising strategy. Here, we show the broad potential of our proprietary protein sequence tag (PST) technology. A special feature of PST is its ability to detect a wide variety of proteins including the pharmaceutically relevant membrane and nuclear proteins. This procedure addresses a similar number of proteins, compared to the multidimensional protein identification technology approach, but offers additionally a quantitative analysis with its recently developed quantitative PST version.     

A comparative proteomics approach to detect unintended effects in transgenic Arabidopsis

Recently, as part of biosafety assessments, unintended effects have been given much attention. In this study, we applied a proteomics approach to elucidate the unintended effects of random T-DNA insertion in transgenic plants. Separated proteins extracted from 12 transgenic Arabidopsis thaliana with different T-DNA insertion sites and from wild-type (ecotype Col-o) were analyzed. In the transgenic plants, 102 significantly altered protein spots were detected, in which 59 were up-regulated and 43 down-regulated. MALDI-TOF MS analysis showed that most of these expression level-altered proteins were involved in energy transfer, oxidative respiration and photosynthesis. However, none of these proteins was a toxic protein or allergen. Using plants with or without cold treatment, a natural environmental stress, as controls, we found that the number of the altered proteins was even less in those transgenic plants than those triggered by the cold treatment, suggesting that the transgenic events had a weaker impact on the plants than the environmental stresses. Interestingly,the phosphinothricin acetyl transferase (PAT), the BAR-encoded protein, was detected in nine out of twelve different T-DNA insertion lines at five different insertion sites. These data suggest that the most significant impact of transgenic events on the host plants is from the transgene itself, i.e., from the predictable intended effects, rather than unintended effects. This study also suggests that the proteomics approach has the potential to detect the unintended effects in transgenic plants.     

A comparative proteomics approach to detect unintended effects in transgenic Arabidopsis

Recently, as part of biosafety assessments, unintended effects have been given much attention. In this study, we applied a proteomics approach to elucidate the unintended effects of random T-DNA insertion in transgenic plants. Separated proteins extracted from 12 transgenic Arabidopsis thaliana with different T-DNA insertion sites and from wild-type （ecotype Col-o） were analyzed. In the transgenic plants, 102 significantly altered protein spots were detected, in which 59 were up-regulated and 43 down-regulated. MALDI-TOF MS analysis showed that most of these expression level-altered proteins were involved in energy transfer, oxidative respiration and photosynthesis. However, none of these proteins was a toxic protein or allergen. Using plants with or without cold treatment, a natural environmental stress, as controls, we found that the number of the altered proteins was even less in those transgenic plants than those triggered by the cold treatment, suggesting that the transgenic events had a weaker impact on the plants than the environmental stresses. Interestingly, the phosphinothricin acetyl transferase （PAT）, the BAR-encoded protein, was detected in nine out of twelve different T-DNA insertion lines at five different insertion sites. These data suggest that the most significant impact of transgenic events on the host plants is from the transgene itself, i.e., from the predictable intended effects, rather than unintended effects. This study also suggests that the proteomics approach has the potential to detect the unintended effects in transgenic plants.     

Signal maps for mass spectrometry-based comparative proteomics

Mass spectrometry-based proteomic experiments, in combination with liquid chromatography-based separation, can be used to compare complex biological samples across multiple conditions. These comparisons are usually performed on the level of protein lists generated from individual experiments. Unfortunately given the current technologies, these lists typically cover only a small fraction of the total protein content, making global comparisons extremely limited. Recently approaches have been suggested that are built on the comparison of computationally built feature lists instead of protein identifications. Although these approaches promise to capture a bigger spectrum of the proteins present in a complex mixture, their success is strongly dependent on the correctness of the identified features and the aligned retention times of these features across multiple experiments. In this experimental-computational study, we went one step further and performed the comparisons directly on the signal level. First signal maps were constructed that associate the experimental signals across multiple experiments. Then a feature detection algorithm used this integrated information to identify those features that are discriminating or common across multiple experiments. At the core of our approach is a score function that faithfully recognizes mass spectra from similar peptide mixtures and an algorithm that produces an optimal alignment (time warping) of the liquid chromatography experiments on the basis of raw MS signal, making minimal assumptions on the underlying data. We provide experimental evidence that suggests uniqueness and correctness of the resulting signal maps even on low accuracy mass spectrometers. These maps can be used for a variety of proteomic analyses. Here we illustrate the use of signal maps for the discovery of diagnostic biomarkers. An imple-mentation of our algorithm is available on our Web server.     

Mitochondrial comparative proteomics: strengths and pitfalls

In this review, we describe the various techniques available to carry out valid comparative proteomics, their advantages and their disadvantages according to the goal of the research. Two-dimensional electrophoresis and 2D-DIGE are compared to shotgun proteomics and SILE. We give our opinion on the best fields of application in the domain of comparative proteomics. We emphasize the usefulness of these new tools, providing mass data to study physiology and mitochondrial plasticity when faced with a specific mitochondrial insufficiency or exogenic stress. We illustrate the subject with results obtained in our laboratory specifying the importance of an approach of comparative proteomics combined from mitochondria and from the cell, which makes it possible to obtain important information on the status of the mitochondrial function at the cellular level. Finally, we draw attention to the dangers of the extrapolation of proteomic data to metabolic flows which requires the greatest care.     

Quantitation using enhanced signal tags: a technique for comparative proteomics

Differential amidination of N-termini and lysine residues provides the basis for a novel approach to protein quantitation using MALDI mass spectrometry. Because the amidination of lysines increases their basicity and therefore MALDI ionization yields, the method is called quantitation using enhanced signal tags (QUEST). Amidine labels differ by methylene groups, leading to 14 Da mass differentials. The utility of QUEST is demonstrated while analyzing the digests of two model proteins using MALDI-TOF mass spectrometry.     

Gel-free and gel-based proteomics in Bacillus subtilis: a comparative study

The proteome of exponentially growing Bacillus subtilis cells was dissected by the implementation of shotgun proteomics and a semigel-based approach for a particular exploration of membrane proteins. The current number of 745 protein identifications that was gained by the use of two-dimensional gel electrophoresis could be increased by 473 additional proteins. Therefore, almost 50% of the 2500 genes expressed in growing B. subtilis cells have been demonstrated at the protein level. In terms of exploring cellular physiology and adaptation to environmental changes or stress, proteins showing an alteration in expression level are of primary interest. The large number of vegetative proteins identified by gel-based and gel-free approaches is a good starting point for comparative physiological investigations. For this reason a gel-free quantitation with the recently introduced iTRAQ (isobaric tagging for relative and absolute quantitation) reagent technique was performed to investigate the heat shock response in B. subtilis. A comparison with gel-based data showed that both techniques revealed a similar level of up-regulation for proteins belonging to well studied heat hock regulons (SigB, HrcA, and CtsR). However, additional datasets have been obtained by the gel-free approach indicating a strong heat sensitivity of specific enzymes involved in amino acid synthesis.     

Pressures in archaeal protein coding genes: a comparative study

Our studies on the bases of codons from 11 completely sequenced archaeal genomes show that, as we move from GC-rich to AT-rich protein-coding gene-containing species, the differences between G and C and between A and T, the purine load (AG content), and also the overall persistence (i.e. the tendency of a base to be followed by the same base) within codons, all increase almost simultaneously, although the extent of increase is different over the three positions within codons. These findings suggest that the deviations from the second parity rule (through the increasing differences between complementary base contents) and the increasing purine load hinder the chance of formation of the intra-strand Watson-Crick base-paired secondary structures in mRNAs (synonymous with the protein-coding genes we dealt with), thereby increasing the translational efficiency. We hypothesize that the ATrich protein-coding gene-containing archaeal species might have better translational efficiency than their GC-rich counterparts.     

Mixed-effects statistical model for comparative LC-MS proteomics studies

Comparing a protein's concentrations across two or more treatments is the focus of many proteomics studies. A frequent source of measurements for these comparisons is a mass spectrometry (MS) analysis of a protein's peptide ions separated by liquid chromatography (LC) following its enzymatic digestion. Alas, LC-MS identification and quantification of equimolar peptides can vary significantly due to their unequal digestion, separation, and ionization. This unequal measurability of peptides, the largest source of LC-MS nuisance variation, stymies confident comparison of a protein's concentration across treatments. Our objective is to introduce a mixed-effects statistical model for comparative LC-MS proteomics studies. We describe LC-MS peptide abundance with a linear model featuring pivotal terms that account for unequal peptide LC-MS measurability. We advance fitting this model to an often incomplete LC-MS data set with REstricted Maximum Likelihood (REML) estimation, producing estimates of model goodness-of-fit, treatment effects, standard errors, confidence intervals, and protein relative concentrations. We illustrate the model with an experiment featuring a known dilution series of a filamentous ascomycete fungus Trichoderma reesei protein mixture. For 781 of the 1546 T. reesei proteins with sufficient data coverage, the fitted mixed-effects models capably described the LC-MS measurements. The LC-MS measurability terms effectively accounted for this major source of uncertainty. Ninety percent of the relative concentration estimates were within 0.5-fold of the true relative concentrations. Akin to the common ratio method, this model also produced biased estimates, albeit less biased. Bias decreased significantly, both absolutely and relative to the ratio method, as the number of observed peptides per protein increased. Mixed-effects statistical modeling offers a flexible, well-established methodology for comparative proteomics studies integrating common experimental designs with LC-MS sample processing plans. It favorably accounts for the unequal LC-MS measurability of peptides and produces informative quantitative comparisons of a protein's concentration across treatments with objective measures of uncertainties.     

癌症差异蛋白质组学研究中样品分离和鉴定分析技术

随着人类基因组测序的完成,癌症研究的重点从基因组学转移到蛋白质组学研究中。癌症研究中的差异蛋白质组学技术也飞速发展,包括癌症样品制备、分离,蛋白质鉴定分析、蛋白质组定量研究和翻译后修饰研究等。这些技术极大地推动了与癌症相关的差异蛋白质组学研究,使蛋白质组学在癌症早期诊断、治疗,监测以及发现新药物治疗靶标方面发挥更大的作用。本文主要综述了近年来癌症差异蛋白质组学研究中样品分离和鉴定分析技术。     

Proteome informatics II: bioinformatics for comparative proteomics

The present review attempts to cover the most recent initiatives directed towards representing, storing, displaying and processing protein-related data suited to undertake "comparative proteomics" studies. Data interpretation is brought into focus. Efforts invested into analysing and interpreting experimental data increasingly express the need for adding meaning. This trend is perceptible in work dedicated to determining ontologies, modelling interaction networks, etc. In parallel, technical advances in computer science are spurred by the development of the Web and the growing need to channel and understand massive volumes of data. Biology benefits from these advances as an application of choice for many generic solutions. Some examples of bioinformatics solutions are discussed and directions for on-going and future work conclude the review.     

High-performance proteomics as a tool in biomarker discovery

Biomarkers allowing early detection of disease or therapy control have a huge influence in curing a disease. A wide variety of methods were applied to find new biomarkers. In contrast to methods focused on DNA or mRNA techniques, approaches considering proteins as potential biomarker candidates have the advantage that proteins are more diverse than DNA or RNA and are more reflective of a biological system. Here, we present an approach for the identification of new biomarkers relying on our experience from the past 10 years of proteomics, outlining a concept of "high-performance proteomics" This approach is based on quantitative proteome analysis using a sufficient number of clinical samples and statistical validation of proteomics data by independent methods, such as Western blot analysis or immunohistochemistry.     

Human Proteinpedia as a resource for clinical proteomics

Clinical proteomics is an emerging field that deals with the use of proteomic technologies for medical applications. With a major objective of identifying proteins involved in pathological processes and as potential biomarkers, this field is already gaining momentum. Consequently, clinical proteomics data are being generated at a rapid pace, although mechanisms of sharing such data with the biomedical community lag far behind. Most of these data are either provided as supplementary information through journal web sites or directly made available by the authors through their own web resources. Integration of these data within a single resource that displays information in the context of individual proteins is likely to enhance the use of proteomic data in biomedical research. Human Proteinpedia is one such portal that unifies human proteomic data under a single banner. The goal of this resource is to ultimately capture and integrate all proteomic data obtained from individual studies on normal and diseased tissues. We anticipate that harnessing of these data will help prioritize experiments related to protein targets and also permit meta-analysis to uncover molecular signatures of disease. Finally, we encourage all biomedical investigators to maximize dissemination of their valuable proteomic data to rest of the community by active participation in existing repositories such as Human Proteinpedia.     

Comparative proteomics of glycoproteins based on lectin selection and isotope coding

Lectins have been widely used in glycan structure analysis. The studies described here exploit this fact to select glycopeptides carrying disease-associated modifications in their oligosaccharides. Coupling lectin affinity selection with recent advances in stable isotope coding for quantitative proteomics allowed a comparative proteomics method to be developed for examining aberrant glycosylation in cancer. Control and experimental samples were individually tryptic digested and differentially coded with stable isotope coding agents before they were mixed and affinity selected with a lectin affinity chromatography column. Glycopeptides carrying an alpha-L-fucose residue were selected with Lotus tetragonolobus agglutinin (LTA) immobilized on a chromatography matrix. Because the oligosaccharides of glycoproteins are generally heterogeneous and often of unknown structure, it was necessary to deglycosylate the selected peptides with PNGase F before they could be compared to sequences in DNA and protein databases. After deglycosylated peptides were transferred to a reversed phase chromatography (RPC) column and fractionated by gradient elution with increasing amounts of acetonitrile. The RPC fractions were then analyzed by both matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) and electrospray ionization mass spectrometry (ESI-MS). When this method was applied to a study of lymphosarcoma in canines, it was found that during chemotherapy, a series of fucosylated proteins in the blood of patients decreased in concentration more than 2-fold. Two of the proteins identified, CD44 and E-selectin, are known to be involved in cell adhesion and cancer cell migration. The observed aberrant fucosylation of these proteins is consistent with the hypothesis that CD44 and E-selectin play a key role in metastasis and the spread of cancer cells to remote sites.