A MS data search method for improved 15N‐labeled protein identification

Quantitative proteomics using stable isotope labeling strategies combined with MS is an important tool for biomarker discovery. Methods involving stable isotope metabolic labeling result in optimal quantitative accuracy, since they allow the immediate combination of two or more samples. Unfortunately, stable isotope incorporation rates in metabolic labeling experiments using mammalian organisms usually do not reach 100%. As a consequence, protein identifications in ¹⁵N database searches have poor success rates. We report on a strategy that significantly improves the number of ¹⁵N‐labeled protein identifications and results in a more comprehensive and accurate relative peptide quantification workflow.     

Comparison of full versus partial metabolic labeling for quantitative proteomics analysis in Arabidopsis thaliana

In recent years a variety of quantitative proteomics techniques have been developed, allowing characterization of changes in protein abundance in a variety of organisms under various biological conditions. Because it allows excellent control for error at all steps in sample preparation and analysis, full metabolic labeling using (15)N has emerged as an important strategy for quantitative proteomics, having been applied in a variety of organisms from yeast to Arabidopsis and even rats. However, challenges associated with complete replacement of (14)N with (15)N can make its application in many complex eukaryotic systems impractical on a routine basis. Extending a concept proposed by Whitelegge et al. (Whitelegge, J. P., Katz, J. E., Pihakari, K. A., Hale, R., Aguilera, R., Gomez, S. M., Faull, K. F., Vavilin, D., and Vermaas, W. (2004) Subtle modification of isotope ratio proteomics; an integrated strategy for expression proteomics. Phytochemistry 65, 1507-1515), we investigate an alternative strategy for quantitative proteomics that relies upon the subtle changes in isotopic envelope shape that result from partial metabolic labeling to compare relative abundances of labeled and unlabeled peptides in complex mixtures. We present a novel algorithm for the automated quantitative analysis of partial incorporation samples via LC-MS. We then compare the performance of partial metabolic labeling with traditional full metabolic labeling for quantification of controlled mixtures of labeled and unlabeled Arabidopsis peptides. Finally we evaluate the performance of each technique for comparison of light- versus dark-grown Arabidopsis with respect to reproducibility and numbers of peptide and protein identifications under more realistic experimental conditions. Overall full metabolic labeling and partial metabolic labeling prove to be comparable with respect to dynamic range, accuracy, and reproducibility, although partial metabolic labeling consistently allows quantification of a higher percentage of peptide observations across the dynamic range. This difference is especially pronounced at extreme ratios. Ultimately both full metabolic labeling and partial metabolic labeling prove to be well suited for quantitative proteomics characterization.     

Double standards in quantitative proteomics: direct comparative assessment of difference in gel electrophoresis and metabolic stable isotope labeling

Quantitative protein expression profiling is a crucial part of proteomics and requires methods that are able to efficiently provide accurate and reproducible differential expression values for proteins in two or more biological samples. In this report we evaluate in a direct comparative assessment two state-of-the-art quantitative proteomic approaches, namely difference in gel electrophoresis (DiGE) and metabolic stable isotope labeling. Therefore, Saccharomyces cerevisiae was grown under well defined experimental conditions in chemostats under two single nutrient-limited growth conditions using (14)N- or (15)N-labeled ammonium sulfate as the single nitrogen source. Following lysis and protein extraction from the two yeast samples, the proteins were fluorescently labeled using different fluorescent CyDyes. Subsequently, the yeast samples were mixed, and the proteins were separated by two-dimensional gel electrophoresis. Following in-gel digestion, the resulting peptides were analyzed by mass spectrometry using a MALDI-TOF mass spectrometer. Relative ratios in protein expression between these two yeast samples were determined using both DiGE and metabolic stable isotope labeling. Focusing on a small, albeit representative, set of proteins covering the whole gel range, including some protein isoforms and ranging from low to high abundance, we observe that the correlation between these two methods of quantification is good with the differential ratios determined following the equation R(Met.Lab.) = 0.98R(DiGE) with r(2) = 0.89. Although the correlation between DiGE and metabolic stable isotope labeling is exceptionally good, we do observe and discuss (dis)advantages of both methods as well as in relation to other (quantitative) approaches.     

定量蛋白质组学中的同位素标记技术

定量蛋白质组学的目的是对复杂的混合体系中所有的蛋白质进行鉴定,并对蛋白质的量及量的变化进行准确的测定,是当前系统生物科学研究的重要内容。近年来,由于质谱技术和生物信息学的进步,定量蛋白质组学在分析蛋白质组或亚蛋白质组方面已取得了令人瞩目的成就,但其最显著的成就应该归功于稳定同位素标记技术的应用。该技术使用针对某一类蛋白具有特异性的化学探针来标记目的蛋白质或肽段,同时化学探针要求含有用以精确定量的稳定同位素信号。在此基础上,实现了对表达的蛋白质差异和翻译后修饰的蛋白质差异进行精确定量分析。综述了在定量蛋白质组学中使用的各种同位素标记技术及其应用。     

Stable Isotope Metabolic Labeling with a Novel 15N-Enriched Bacteria Diet for Improved Proteomic Analyses of Mouse Models for Psychopathologies

The identification of differentially regulated proteins in animal models of psychiatric diseases is essential for a comprehensive analysis of associated psychopathological processes. Mass spectrometry is the most relevant method for analyzing differences in protein expression of tissue and body fluid proteomes. However, standardization of sample handling and sample-to-sample variability are problematic. Stable isotope metabolic labeling of a proteome represents the gold standard for quantitative mass spectrometry analysis. The simultaneous processing of a mixture of labeled and unlabeled samples allows a sensitive and accurate comparative analysis between the respective proteomes. Here, we describe a cost-effective feeding protocol based on a newly developed ¹⁵N bacteria diet based on Ralstonia eutropha protein, which was applied to a mouse model for trait anxiety. Tissue from ¹⁵N-labeled vs. ¹⁴N-unlabeled mice was examined by mass spectrometry and differences in the expression of glyoxalase-1 (GLO1) and histidine triad nucleotide binding protein 2 (Hint2) proteins were correlated with the animals'' psychopathological behaviors for methodological validation and proof of concept, respectively. Additionally, phenotyping unraveled an antidepressant-like effect of the incorporation of the stable isotope ¹⁵N into the proteome of highly anxious mice. This novel phenomenon is of considerable relevance to the metabolic labeling method and could provide an opportunity for the discovery of candidate proteins involved in depression-like behavior. The newly developed ¹⁵N bacteria diet provides researchers a novel tool to discover disease-relevant protein expression differences in mouse models using quantitative mass spectrometry.     

Novel approach for peptide quantitation and sequencing based on 15N and 13C metabolic labeling

Here we describe a method for protein identification and quantification using stable isotopes via in vivo metabolic labeling of the hyperthermophilic crenarchaeon Sulfolobus solfataricus. Stable isotope labeling for quantitative proteomics is becoming increasingly popular; however, its usefulness in protein identification has not been fully exploited. We use both 15N and 13C labeling to create three different versions of the same peptide, corresponding to the unlabeled, 15N and 13C labeled versions. The peptide then appears as three different peaks in a TOF-MS scan and three corresponding sets of MS/MS spectra are obtained. With this information, the elemental carbon and nitrogen compositions for each peptide and each fragment can be calculated. When this is used as a constraint in database searching and/or de novo sequencing, the confidence of a match is increased (for an example intact peptide from 34 choices to 1). This makes the method a useful proteomic tool for both sequenced and unsequenced organisms. Furthermore, it allows for accurate protein quantitation (standard deviations over >4 peptides per protein were within 10%) of three phenotypes in one MS experiment. Abundances for each peptide are calculated by determining the relative areas of each of the three peaks in the TOF-MS spectrum.     

In-depth quantitative cardiac proteomics combining electron transfer dissociation and the metalloendopeptidase Lys-N with the SILAC mouse

In quantitative proteomics stable isotope labeling has progressed from cultured cells toward the total incorporation of labeled atoms or amino acids into whole multicellular organisms. For instance, the recently introduced (13)C(6)-lysine labeled SILAC mouse allows accurate comparison of protein expression directly in tissue. In this model, only lysine, but not arginine, residues are isotope labeled, as the latter may cause complications to the quantification by in vivo conversion of arginine to proline. The sole labeling of lysines discourages the use of trypsin, as not all peptides will be quantifiable. Therefore, in the initial work Lys-C was used for digestion. Here, we demonstrate that the lysine-directed protease metalloendopeptidase Lys-N is an excellent alternative. As lysine directed peptides generally yield longer and higher charged peptides, alongside the more traditional collision induced dissociation we also implemented electron transfer dissociation in a quantitative stable isotope labeling with amino acid in cell culture workflow for the first time. The utility of these two complementary approaches is highlighted by investigating the differences in protein expression between the left and right ventricle of a mouse heart. Using Lys-N and electron transfer dissociation yielded coverage to a depth of 3749 proteins, which is similar as earlier investigations into the murine heart proteome. In addition, this strategy yields quantitative information on ～ 2000 proteins with a median coverage of four peptides per protein in a single strong cation exchange-liquid chromatography-MS experiment, revealing that the left and right ventricle proteomes are very similar qualitatively as well as quantitatively.     

Study of early leaf senescence in Arabidopsis thaliana by quantitative proteomics using reciprocal 14N/15N labeling and difference gel electrophoresis

Leaf senescence represents the final stage of leaf development and is associated with fundamental changes on the level of the proteome. For the quantitative analysis of changes in protein abundance related to early leaf senescence, we designed an elaborate double and reverse labeling strategy simultaneously employing fluorescent two-dimensional DIGE as well as metabolic (15)N labeling followed by MS. Reciprocal (14)N/(15)N labeling of entire Arabidopsis thaliana plants showed that full incorporation of (15)N into the proteins of the plant did not cause any adverse effects on development and protein expression. A direct comparison of DIGE and (15)N labeling combined with MS showed that results obtained by both quantification methods correlated well for proteins showing low to moderate regulation factors. Nano HPLC/ESI-MS/MS analysis of 21 protein spots that consistently exhibited abundance differences in nine biological replicates based on both DIGE and MS resulted in the identification of 13 distinct proteins and protein subunits that showed significant regulation in Arabidopsis mutant plants displaying advanced leaf senescence. Ribulose 1,5-bisphosphate carboxylase/oxygenase large and three of its four small subunits were found to be down-regulated, which reflects the degradation of the photosynthetic machinery during leaf senescence. Among the proteins showing higher abundance in mutant plants were several members of the glutathione S-transferase family class phi and quinone reductase. Up-regulation of these proteins fits well into the context of leaf senescence since they are generally involved in the protection of plant cells against reactive oxygen species which are increasingly generated by lipid degradation during leaf senescence. With the exception of one glutathione S-transferase isoform, none of these proteins has been linked to leaf senescence before.     

Quantitative proteomics by amino acid labeling in C. elegans

We demonstrate labeling of Caenorhabditis elegans with heavy isotope-labeled lysine by feeding them with heavy isotope-labeled Escherichia coli. Using heavy isotope-labeled worms and quantitative proteomics methods, we identified several proteins that are regulated in response to loss or RNAi-mediated knockdown of the nuclear hormone receptor 49 in C. elegans. The combined use of quantitative proteomics and selective gene knockdown is a powerful tool for C. elegans biology.     

SILIP: a novel stable isotope labeling method for in planta quantitative proteomic analysis

Due to ease of manipulation, metabolic isotope coding of samples for proteomic analysis is typically performed in cell culture, thus preventing an accurate in vivo quantitative analysis, which is only achievable in intact organisms. To address this issue in plant biology, we developed SILIP (stable isotope labeling in planta) using tomato plants (Solanum lycopersicum cv. Rutgers) as a method that allows soil-grown plants to be efficiently labeled using a 14N/15N isotope coding strategy. After 2 months of growth on 14N- and 15N-enriched nitrogen sources, proteins were extracted from four distinct tomato tissues (roots, stems, leaves and flowers), digested, and analyzed by LC/MS/MS (data-dependent acquisition, DDA) and alternating low- and elevated-energy MS scans (data-independent acquisition, MS(E)). Using a derived relationship to generate a theoretical standard curve, the measured ratio of the M (monoisotopic) and M-1 isotopologues of 70 identified 15N-labeled peptides from 16 different proteins indicated that 15N incorporation was almost 99%, which is in excellent agreement with the 99.3% 15N-enriched nitrate used in the soil-based medium. Values for the various tissues ranged from 98.2 +/- 0.3% 15N incorporation in leaves to 98.8 2 +/- 0.2% in stems, demonstrating uniform labeling throughout the plant. In addition, SILIP is compatible with root-knot nematode (Meloidogyne spp.) development, and thus provides a new quantitative proteomics tool to study both plant and plant-microorganism systems.     

The 15N isotope effect in Escherichia coli: A neutron can make the difference

Several techniques based on stable isotope labeling are used for quantitative MS. These include stable isotope metabolic labeling methods for cells in culture as well as live organisms with the assumption that the stable isotope has no effect on the proteome. Here, we investigate the ¹⁵N isotope effect on Escherichia coli cultures that were grown in either unlabeled (¹⁴N) or ¹⁵N‐labeled media by LC‐ESI‐MS/MS‐based relative protein quantification. Consistent protein expression level differences and altered growth rates were observed between ¹⁴N and ¹⁵N‐labeled cultures. Furthermore, targeted metabolite analyses revealed altered metabolite levels between ¹⁴N and ¹⁵N‐labeled bacteria. Our data demonstrate for the first time that the introduction of the ¹⁵N isotope affects protein and metabolite levels in E. coli and underline the importance of implementing controls for unbiased protein quantification using stable isotope labeling techniques.     

Quantitative analysis of the yeast proteome by incorporation of isotopically labeled leucine

Quantitative comparison of protein expression levels in 2D gels is complicated by the variables associated with protein separation and mass spectrometric responses. Metabolic labeling allows cells from different experiments to be mixed prior to analysis. This approach has been reported for prokaryotic cells. Here, we demonstrate that metabolic labeling can also be successfully applied to the eukaryote Saccharormyces cerevisiae. Yeast leucine auxotrophs grown on synthetic complete media containing natural abundance Leu or D10-Leu were mixed prior to 2D gel separation and MALDI analysis of the digested proteins. D10-Leu labeling provided an effective internal calibrant for peptide MS analysis, and the number of Leu residues yielded an additional parameter for peptide identification at low mass resolution (1000). Metabolic incorporation of D10-Leu into yeast proteins was found to be quantitative since the intensities of the peptide peaks corresponded to those expected on the basis of the percent label in the media. Thus, D10-Leu labeling should provide reliable data for comparing proteomes both quantitatively and qualitatively from wild-type and nonessential-gene-null-mutant strains of S. cerevisiae. Given the central role played by yeast in our understanding of eukaryotic gene and protein expression, it is anticipated that the quantitative expressional proteomic method outlined here will have widespread applications.     

Homologous and unique G protein alpha subunits in the nematode Caenorhabditis elegans.

A cDNA corresponding to a known G protein alpha subunit, the alpha subunit of Go (Go alpha), was isolated and sequenced. The predicted amino acid sequence of C. elegans Go alpha is 80-87% identical to other Go alpha sequences. An mRNA that hybridizes to the C. elegans Go alpha cDNA can be detected on Northern blots. A C. elegans protein that crossreacts with antibovine Go alpha antibody can be detected on immunoblots. A cosmid clone containing the C. elegans Go alpha gene (goa-1) was isolated and mapped to chromosome I. The genomic fragments of three other C. elegans G protein alpha subunit genes (gpa-1, gpa-2, and gpa-3) have been isolated using the polymerase chain reaction. The corresponding cosmid clones were isolated and mapped to disperse locations on chromosome V. The sequences of two of the genes, gpa-1 and gpa-3, were determined. The predicted amino acid sequences of gpa-1 and gpa-3 are only 48% identical to each other. Therefore, they are likely to have distinct functions. In addition they are not homologous enough to G protein alpha subunits in other organisms to be classified. Thus C. elegans has G proteins that are identifiable homologues of mammalian G proteins as well as G proteins that appear to be unique to C. elegans. Study of identifiable G proteins in C. elegans may result in a further understanding of their function in other organisms, whereas study of the novel G proteins may provide an understanding of unique aspects of nematode physiology.     

Quantitative Proteome Analysis Reveals RNA Processing Factors As Modulators of Ionizing Radiation-Induced Apoptosis in the C. elegans Germline

The nematode Caenorhabditis elegans is an organism most recognized for forward and reverse genetic and functional genomic approaches. Proteomic analyses of DNA damage-induced apoptosis have not been shown because of a limited number of cells undergoing apoptosis. We applied mass spectrometry-based quantitative proteomics to evaluate protein changes induced by ionizing radiation (IR) in isolated C. elegans germlines. For this purpose, we used isobaric peptide termini labeling (IPTL) combined with the data analysis tool IsobariQ, which utilizes MS/MS spectra for relative quantification of peak pairs formed during fragmentation. Using stringent statistical critera, we identified 48 proteins to be significantly up- or down-regulated, most of which are part of a highly interconnected protein-protein interaction network dominated by proteins involved in translational control. RNA-mediated depletion of a selection of the IR-regulated proteins revealed that the conserved CAR-1/CGH-1/CEY-3 germline RNP complex acts as a novel negative regulator of DNA-damage induced apoptosis. Finally, a central role of nucleolar proteins in orchestrating these responses was confirmed as the H/ACA snRNP protein GAR-1 was required for IR-induced apoptosis in the C. elegans germline.     

The immunoglobulin superfamily in Drosophila melanogaster and Caenorhabditis elegans and the evolution of complexity

Drosophila melanogaster is an arthropod with a much more complex anatomy and physiology than the nematode Caenorhabditis elegans. We investigated one of the protein superfamilies in the two organisms that plays a major role in development and function of cell-cell communication: the immunoglobulin superfamily (IgSF). Using hidden Markov models, we identified 142 IgSF proteins in Drosophila and 80 in C. elegans. Of these, 58 and 22, respectively, have been previously identified by experiments. On the basis of homology and the structural characterisation of the proteins, we can suggest probable types of function for most of the novel proteins. Though overall Drosophila has fewer genes than C. elegans, it has many more IgSF cell-surface and secreted proteins. Half the IgSF proteins in C. elegans and three quarters of those in Drosophila have evolved subsequent to the divergence of the two organisms. These results suggest that the expansion of this protein superfamily is one of the factors that have contributed to the formation of the more complex physiological features that are found in Drosophila.     

The enzymatic biotinylation of proteins: a post-translational modification of exceptional specificity.

Biotin is a coenzyme essential to all life forms. The vitamin has biological activity only when covalently attached to certain key metabolic enzymes. Most organisms have only one enzyme for attachment of biotin to other proteins and the sequences of these proteins and their substrate proteins are strongly conserved throughout nature. Structures of both the biotin ligase and the biotin carrier protein domain from Escherichia coli have been determined. These, together with mutational analyses of biotinylated proteins, are beginning to elucidate the exceptional specificity of this protein modification.     

Quantitative proteome analysis using isotope-coded affinity tags and mass spectrometry

A main objective of proteomics research is to systematically identify and quantify proteins in a given proteome (cells, subcellular fractions, protein complexes, tissues or body fluids). Protein labeling with isotope-coded affinity tags (ICAT) followed by tandem mass spectrometry allows sequence identification and accurate quantification of proteins in complex mixtures, and has been applied to the analysis of global protein expression changes, protein changes in subcellular fractions, components of protein complexes, protein secretion and body fluids. This protocol describes protein-sample labeling with ICAT reagents, chromatographic fractionation of the ICAT-labeled tryptic peptides, and protein identification and quantification using tandem mass spectrometry. The method is suitable for both large-scale analysis of complex samples including whole proteomes and small-scale analysis of subproteomes, and allows quantitative analysis of proteins, including those that are difficult to analyze by gel-based proteomics technology.     

Characterization of global yeast quantitative proteome data generated from the wild-type and glucose repression saccharomyces cerevisiae strains: the comparison of two quantitative methods

The quantitative proteomic analysis of complex protein mixtures is emerging as a technically challenging but viable systems-level approach for studying cellular function. This study presents a large-scale comparative analysis of protein abundances from yeast protein lysates derived from both wild-type yeast and yeast strains lacking key components of the Snf1 kinase complex. Four different strains were grown under well-controlled chemostat conditions. Multidimensional protein identification technology followed by quantitation using either spectral counting or stable isotope labeling approaches was used to identify relative changes in the protein expression levels between the strains. A total of 2388 proteins were relatively quantified, and more than 350 proteins were found to have significantly different expression levels between the two strains of comparison when using the stable isotope labeling strategy. The stable isotope labeling based quantitative approach was found to be highly reproducible among biological replicates when complex protein mixtures containing small expression changes were analyzed. Where poor correlation between stable isotope labeling and spectral counting was found, the major reason behind the discrepancy was the lack of reproducible sampling for proteins with low spectral counts. The functional categorization of the relative protein expression differences that occur in Snf1-deficient strains uncovers a wide range of biological processes regulated by this important cellular kinase.