Differential dimethyl labeling of N-termini of peptides after guanidination for proteome analysis

We describe an enabling technique for proteome analysis based on isotope-differential dimethyl labeling of N-termini of tryptic peptides followed by microbore liquid chromatography (LC) matrix-assisted laser desorption and ionization (MALDI) mass spectrometry (MS). In this method, lysine side chains are blocked by guanidination to prevent the incorporation of multiple labels, followed by N-terminal labeling via reductive amination using d(0),(12)C-formaldehyde or d(2),(13)C-formaldehyde. Relative quantification of peptide mixtures is achieved by examining the MALDI mass spectra of the peptide pairs labeled with different isotope tags. A nominal mass difference of 6 Da between the peptide pair allows negligible interference between the two isotopic clusters for quantification of peptides of up to 3000 Da. Since only the N-termini of tryptic peptides are differentially labeled and the a(1) ions are also enhanced in the MALDI MS/MS spectra, interpretation of the fragment ion spectra to obtain sequence information is greatly simplified. It is demonstrated that this technique of N-terminal dimethylation (2ME) after lysine guanidination (GA) or 2MEGA offers several desirable features, including simple experimental procedure, stable products, using inexpensive and commercially available reagents, and negligible isotope effect on reversed-phase separation. LC-MALDI MS combined with this 2MEGA labeling technique was successfully used to identify proteins that included polymorphic variants and low abundance proteins in bovine milk. In addition, by analyzing a mixture of two equal amounts of milk whey fraction as a control, it is shown that the measured average ratio for 56 peptide pairs from 14 different proteins is 1.02, which is very close to the theoretical ratio of 1.00. The calculated percentage error is 2.0% and relative standard deviation is 4.6%.     

Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations

Researchers have several options when designing proteomics experiments. Primary among these are choices of experimental method, instrumentation and spectral interpretation software. To evaluate these choices on a proteome scale, we compared triplicate measurements of the yeast proteome by liquid chromatography tandem mass spectrometry (LC-MS/MS) using linear ion trap (LTQ) and hybrid quadrupole time-of-flight (QqTOF; QSTAR) mass spectrometers. Acquired MS/MS spectra were interpreted with Mascot and SEQUEST algorithms with and without the requirement that all returned peptides be tryptic. Using a composite target decoy database strategy, we selected scoring criteria yielding 1% estimated false positive identifications at maximum sensitivity for all data sets, allowing reasonable comparisons between them. These comparisons indicate that Mascot and SEQUEST yield similar results for LTQ-acquired spectra but less so for QSTAR spectra. Furthermore, low reproducibility between replicate data acquisitions made on one or both instrument platforms can be exploited to increase sensitivity and confidence in large-scale protein identifications.     

SIMSI-Transfer: Software-Assisted Reduction of Missing Values in Phosphoproteomic and Proteomic Isobaric Labeling Data Using Tandem Mass Spectrum Clustering

Isobaric stable isotope labeling techniques such as tandem mass tags (TMTs) have become popular in proteomics because they enable the relative quantification of proteins with high precision from up to 18 samples in a single experiment. While missing values in peptide quantification are rare in a single TMT experiment, they rapidly increase when combining multiple TMT experiments. As the field moves toward analyzing ever higher numbers of samples, tools that reduce missing values also become more important for analyzing TMT datasets. To this end, we developed SIMSI-Transfer (Similarity-based Isobaric Mass Spectra 2 [MS2] Identification Transfer), a software tool that extends our previously developed software MaRaCluster (© Matthew The) by clustering similar tandem MS2 from multiple TMT experiments. SIMSI-Transfer is based on the assumption that similarity-clustered MS2 spectra represent the same peptide. Therefore, peptide identifications made by database searching in one TMT batch can be transferred to another TMT batch in which the same peptide was fragmented but not identified. To assess the validity of this approach, we tested SIMSI-Transfer on masked search engine identification results and recovered >80% of the masked identifications while controlling errors in the transfer procedure to below 1% false discovery rate. Applying SIMSI-Transfer to six published full proteome and phosphoproteome datasets from the Clinical Proteomic Tumor Analysis Consortium led to an increase of 26 to 45% of identified MS2 spectra with TMT quantifications. This significantly decreased the number of missing values across batches and, in turn, increased the number of peptides and proteins identified in all TMT batches by 43 to 56% and 13 to 16%, respectively.     

Validation of peptide MS/MS spectra using metabolic isotope labeling for spectral matching-based shotgun proteome analysis

We report an isotope labeling shotgun proteome analysis strategy to validate the spectrum-to-sequence assignments generated by using sequence-database searching for the construction of a more reliable MS/MS spectral library. This strategy is demonstrated in the analysis of the E. coli K12 proteome. In the workflow, E. coli cells were cultured in normal and (15)N-enriched media. The differentially labeled proteins from the cell extracts were subjected to trypsin digestion and two-dimensional liquid chromatography quadrupole time-of-flight tandem mass spectrometry (2D-LC QTOF MS/MS) analysis. The MS/MS spectra of the two samples were individually searched using Mascot against the E. coli proteome database to generate lists of peptide sequence matches. The two data sets were compared by overlaying the spectra of unlabeled and labeled matches of the same peptide sequence for validation. Two cutoff filters, one based on the number of common fragment ions and another one on the similarity of intensity patterns among the common ions, were developed and applied to the overlaid spectral pairs to reject the low quality or incorrectly assigned spectra. By examining 257,907 and 245,156 spectra acquired from the unlabeled and (15)N-labeled samples, respectively, an experimentally validated MS/MS spectral library of tryptic peptides was constructed for E. coli K12 that consisted of 9,302 unique spectra with unique sequence and charge state, representing 7,763 unique peptide sequences. This E. coli spectral library could be readily expanded, and the overall strategy should be applicable to other organisms. Even with this relatively small library, it was shown that more peptides could be identified with higher confidence using the spectral search method than by sequence-database searching.     

Global proteome discovery using an online three-dimensional LC-MS/MS

We have developed a proteomics technology featuring on-line three-dimensional liquid chromatography coupled to tandem mass spectrometry (3D LC-MS/MS). Using 3D LC-MS/MS, the yeast-soluble, urea-solubilized peripheral membrane and SDS-solubilized membrane protein samples collectively yielded 3019 unique yeast protein identifications with an average of 5.5 peptides per protein from the 6300-gene Saccharomyces Genome Database searched with SEQUEST. A single run of the urea-solubilized sample yielded 2255 unique protein identifications, suggesting high peak capacity and resolving power of 3D LC-MS/MS. After precipitation of SDS from the digested membrane protein sample, 3D LC-MS/MS allowed the analysis of membrane proteins. Among 1221 proteins containing two or more predicted transmembrane domains, 495 such proteins were identified. The improved yeast proteome data allowed the mapping of many metabolic pathways and functional categories. The 3D LC-MS/MS technology provides a suitable tool for global proteome discovery.     

Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.     

Precursor-ion mass re-estimation improves peptide identification on hybrid instruments

Mass spectrometry-based proteomics experiments have become an important tool for studying biological systems. Identifying the proteins in complex mixtures by assigning peptide fragmentation spectra to peptide sequences is an important step in the proteomics process. The 1-2 ppm mass-accuracy of hybrid instruments, like the LTQ-FT, has been cited as a key factor in their ability to identify a larger number of peptides with greater confidence than competing instruments. However, in replicate experiments of an 18-protein mixture, we note parent masses deviate 171 ppm, on average, for ion-trap data directed identifications and 8 ppm, on average, for preview Fourier transform (FT) data directed identifications. These deviations are neither caused by poor calibration nor by excessive ion-loading and are most likely due to errors in parent mass estimation. To improve these deviations, we introduce msPrefix, a program to re-estimate a peptide's parent mass from an associated high-accuracy full-scan survey spectrum. In 18-protein mixture experiments, msPrefix parent mass estimates deviate only 1 ppm, on average, from the identified peptides. In a cell lysate experiment searched with a tolerance of 50 ppm, 2295 peptides were confidently identified using native data and 4560 using msPrefixed data. Likewise, in a plasma experiment searched with a tolerance of 50 ppm, 326 peptides were identified using native data and 1216 using msPrefixed data. msPrefix is also able to determine which MS/MS spectra were possibly derived from multiple precursor ions. In complex mixture experiments, we demonstrate that more than 50% of triggered MS/MS may have had multiple precursor ions and note that spectra with multiple candidate ions are less likely to result in an identification using TANDEM. These results demonstrate integration of msPrefix into traditional shotgun proteomics workflows significantly improves identification results.     

Probability-based evaluation of peptide and protein identifications from tandem mass spectrometry and SEQUEST analysis: the human proteome

Large-scale protein identifications from highly complex protein mixtures have recently been achieved using multidimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) and subsequent database searching with algorithms such as SEQUEST. Here, we describe a probability-based evaluation of false positive rates associated with peptide identifications from three different human proteome samples. Peptides from human plasma, human mammary epithelial cell (HMEC) lysate, and human hepatocyte (Huh)-7.5 cell lysate were separated by strong cation exchange (SCX) chromatography coupled offline with reversed-phase capillary LC-MS/MS analyses. The MS/MS spectra were first analyzed by SEQUEST, searching independently against both normal and sequence-reversed human protein databases, and the false positive rates of peptide identifications for the three proteome samples were then analyzed and compared. The observed false positive rates of peptide identifications for human plasma were significantly higher than those for the human cell lines when identical filtering criteria were used, suggesting that the false positive rates are significantly dependent on sample characteristics, particularly the number of proteins found within the detectable dynamic range. Two new sets of filtering criteria are proposed for human plasma and human cell lines, respectively, to provide an overall confidence of >95% for peptide identifications. The new criteria were compared, using a normalized elution time (NET) criterion (Petritis et al. Anal. Chem. 2003, 75, 1039-1048), with previously published criteria (Washburn et al. Nat. Biotechnol. 2001, 19, 242-247). The results demonstrate that the present criteria provide significantly higher levels of confidence for peptide identifications from mammalian proteomes without greatly decreasing the number of identifications.     

Membrane protein identifications by mass spectrometry using electrocapture-based separation as part of a two-dimensional fractionation system

A two-dimensional (2D) separation method was used to decrease sample complexity in analysis of tryptic peptides from glomerular membrane proteins by tandem mass spectrometry (MS/MS). The first dimension was carried out by electrocapture (EC), which fractionates peptides according to electrophoretic mobility. The second dimension was reverse-phase liquid chromatography (RP-LC), in which EC fractions were further separated and analyzed online by MS/MS. Using this methodology, we now identify 102 glomerular proteins (57 membrane proteins). Many peptides were possible to observe and select for MS/MS only using the 2D approach. Others were detectable in both one-dimensional (1D, without the EC step) and 2D experiments but were selectable for sequence analysis only from the 2D separations because the decrease in complexity then gives time for the mass analyzer to select the peptide and switch to the MS/MS mode. A minority of the peptides were detectable only in the 1D mode (presumably because of handling losses), but at the end this did not decrease the number of proteins identified by the 2D separation. After a database search, the combination of EC and RP-LC MS/MS versus a 1D RP-LC MS/MS separation resulted in a threefold increase in the number of proteins identified and improved the sequence coverage in the identifications, bringing our proteome-identified glomerular proteins to 282.     

Application of peptide LC retention time information in a discriminant function for peptide identification by tandem mass spectrometry

We describe the application of a peptide retention time reversed phase liquid chromatography (RPLC) prediction model previously reported (Petritis et al. Anal. Chem. 2003, 75, 1039) for improved peptide identification. The model uses peptide sequence information to generate a theoretical (predicted) elution time that can be compared with the observed elution time. Using data from a set of known proteins, the retention time parameter was incorporated into a discriminant function for use with tandem mass spectrometry (MS/MS) data analyzed with the peptide/protein identification program SEQUEST. For singly charged ions, the number of confident identifications increased by 12% when the elution time metric is included compared to when mass spectral data is the sole source of information in the context of a Drosophila melanogaster database. A 3-4% improvement was obtained for doubly and triply charged ions for the same biological system. Application to the larger Rattus norvegicus (rat) and human proteome databases resulted in an 8-9% overall increase in the number of confident identifications, when both the discriminant function and elution time are used. The effect of adding "runner-up" hits (peptide matches that are not the highest scoring for a spectra) from SEQUEST is also explored, and we find that the number of confident identifications is further increased by 1% when these hits are also considered. Finally, application of the discriminant functions derived in this work with approximately 2.2 million spectra from over three hundred LC-MS/MS analyses of peptides from human plasma protein resulted in a 16% increase in confident peptide identifications (9022 vs 7779) using elution time information. Further improvements from the use of elution time information can be expected as both the experimental control of elution time reproducibility and the predictive capability are improved.     

Improving protein identification using complementary fragmentation techniques in fourier transform mass spectrometry

Identification of proteins by MS/MS is performed by matching experimental mass spectra against calculated spectra of all possible peptides in a protein data base. The search engine assigns each spectrum a score indicating how well the experimental data complies with the expected one; a higher score means increased confidence in the identification. One problem is the false-positive identifications, which arise from incomplete data as well as from the presence of misleading ions in experimental mass spectra due to gas-phase reactions, stray ions, contaminants, and electronic noise. We employed a novel technique of reduction of false positives that is based on a combined use of orthogonal fragmentation techniques electron capture dissociation (ECD) and collisionally activated dissociation (CAD). Since ECD and CAD exhibit many complementary properties, their combined use greatly increased the analysis specificity, which was further strengthened by the high mass accuracy (approximately 1 ppm) afforded by Fourier transform mass spectrometry. The utility of this approach is demonstrated on a whole cell lysate from Escherichia coli. Analysis was made using the data-dependent acquisition mode. Extraction of complementary sequence information was performed prior to data base search using in-house written software. Only masses involved in complementary pairs in the MS/MS spectrum from the same or orthogonal fragmentation techniques were submitted to the data base search. ECD/CAD identified twice as many proteins at a fixed statistically significant confidence level with on average a 64% higher Mascot score. The confidence in protein identification was hereby increased by more than 1 order of magnitude. The combined ECD/CAD searches were on average 20% faster than CAD-only searches. A specially developed test with scrambled MS/MS data revealed that the amount of false-positive identifications was dramatically reduced by the combined use of CAD and ECD.     

Large-scale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry

Human saliva contains a large number of proteins and peptides (salivary proteome) that help maintain homeostasis in the oral cavity. Global analysis of human salivary proteome is important for understanding oral health and disease pathogenesis. In this study, large-scale identification of salivary proteins was demonstrated by using shotgun proteomics and two-dimensinal gel electrophoresis-mass spectrometry (2-DE-MS). For the shotgun approach, whole saliva proteins were prefractionated according to molecular weight. The smallest fraction, presumably containing salivary peptides, was directly separated by capillary liquid chromatography (LC). However, the large protein fractions were digested into peptides for subsequent LC separation. Separated peptides were analyzed by on-line electrospray tandem mass spectrometry (MS/MS) using a quadrupole-time of flight mass spectrometer, and the obtained spectra were automatically processed to search human protein sequence database for protein identification. Additionally, 2-DE was used to map out the proteins in whole saliva. Protein spots 105 in number were excised and in-gel digested; and the resulting peptide fragments were measured by matrix-assisted laser desorption/ionization-mass spectrometry and sequenced by LC-MS/MS for protein identification. In total, we cataloged 309 proteins from human whole saliva by using these two proteomic approaches.     

Highly informative proteome analysis by combining improved N-terminal sulfonation for de novo peptide sequencing and online capillary reverse-phase liquid chromatography/tandem mass spectrometry

Recently, various chemical modifications of peptides have been incorporated into mass spectrometric analyses of proteome samples, predominantly in conjunction with matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS), to facilitate de novo sequencing of peptides. In this work, we investigate systematically the utility of N-terminal sulfonation of tryptic peptides by 4-sulfophenyl isothiocyanate (SPITC) for proteome analysis by capillary reverse-phase liquid chromatography/tandem mass spectrometry (cRPLC/MS/MS). The experimental conditions for the sulfonation were carefully adjusted so that SPITC reacts selectively with the N-terminal amino groups, even in the presence of the epsilon-amino groups of lysine residues. Mass spectrometric analyses of the modified peptides by cRPLC/MS/MS indicated that SPITC derivatization proceeded toward near completion under the experimental conditions employed here. The SPITC-derivatized peptides underwent facile fragmentation, predominantly resulting in y-series ions in the MS/MS spectra. Combining SPITC derivatization and cRPLC/MS/MS analyses facilitated the acquisition of sequence information for lysine-terminated tryptic peptides as well as arginine-terminated peptides without the need for additional peptide pretreatment, such as guanidination of lysine amino group. This process alleviated the biased detection of arginine-terminated peptides that is often observed in MALDI MS experiments. We will discuss the utility of the technique as a viable method for proteome analyses and present examples of its application in analyzing samples having different levels of complexity.     

Comprehensive yeast proteome analysis using a capillary isoelectric focusing-based multidimensional separation platform coupled with ESI-MS/MS

As demonstrated in this study, a CIEF-based multidimensional separation platform not only is compatible with the detergent-based membrane protein preparation protocol, but also achieves both the largest yeast membrane proteome coverage and the most comprehensive analysis of the yeast proteome to date. By using a 1% false discovery rate for total peptide identifications, a total of 2513 distinct yeast proteins are identified from the SDS-solubilized fraction with an average of 5.4 peptides leading to each protein identification. Among proteins identified from the SDS-solubilized fraction, 407 proteins are predicted to contain at least two or more transmembrane domains using TMHMM (www.cbs.dtu.dk/services/TMHMM-2.0/), corresponding to 46% yeast membrane proteome coverage. Only four additional membrane proteins are identified in the soluble and urea-solubilized fractions, affirming the utility of SDS extraction for enriching the membrane proteome. By combining proteome results obtained from the soluble, urea-solubilized, and SDS-solubilized fractions, a single yeast proteome analysis yields the identification of 3632 distinct yeast proteins, corresponding to 55% theoretical yeast proteome coverage or 70% of proteins predicted to be expressed during log-phase growth in rich media.     

Large-scale identification of Caenorhabditis elegans proteins by multidimensional liquid chromatography-tandem mass spectrometry

A proteome of a model organism, Caenorhabditis elegans, was analyzed by an integrated liquid chromatography (LC)-based protein identification system, which was constructed by microscale two-dimensional liquid chromatography (2DLC) coupled with electrospray ionization (ESI) tandem mass spectrometry (MS/MS) on a high-resolution hybrid mass spectrometer with an automated data analysis system. Soluble and insoluble protein fractions were prepared from a mixed growth phase culture of the worm C. elegans, digested with trypsin, and fractionated separately on the 2DLC system. The separated peptides were directly analyzed by on-line ESI-MS/MS in a data-dependent mode, and the resultant spectral data were automatically processed to search a genome sequence database, wormpep 66, for protein identification. The total number of proteins of the composite proteome identified in this method was 1,616, including 110 secreted/targeted proteins and 242 transmembrane proteins. The codon adaptation indices of the identified proteins suggested that the system could identify proteins of relatively low abundance, which are difficult to identify by conventional 2D-gel electrophoresis (GE) followed by an offline mass spectrometric analysis such as peptide mass fingerprinting. Among the approximately 5,400 peptides assigned in this study, many peptides with post-translational modifications, such as N-terminal acetylation and phosphorylation, were detected. This expression profile of C. elegans, containing 571 hypothetical gene products, will serve as the basic data of a major proteome set expressed in the worm.     

A novel quantitative proteomics workflow by isobaric terminal labeling

Quantification by series of b, y fragment ion pairs generated from isobaric-labeled peptides in MS2 spectra has recently been considered an accurate strategy in quantitative proteomics. Here we developed a novel MS2 quantification approach named quantitation by isobaric terminal labeling (QITL) by coupling (18)O labeling with dimethylation. Trypsin-digested peptides were labeled with two (16)O or (18)O atoms at their C-termini in H(2)(16)O or H(2)(18)O. After blocking all ε-amino groups of lysines through guanidination, the N-termini of the peptides were accordingly labeled with formaldehyde-d(2) or formaldehyde. These indistinguishable, isobaric-labeled peptides in MS1 spectra produce b, y fragment ion pairs in the whole mass range of MS2 spectra that can be used for quantification. In this study, the feasibility of QITL was first demonstrated using standard proteins. An accurate and reproducible quantification over a wide dynamic range was achieved. Then, complex rat liver samples were used to verify the applicability of QITL for large-scale quantitative analysis. Finally, QITL was applied to profile the quantitative proteome of hepatocellular carcinoma (HCC) and adjacent non-tumor liver tissues. Given its simplicity, low-cost, and accuracy, QITL can be widely applied in biological samples (cell lines, tissues, and body fluids, etc.) for quantitative proteomic research.     

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.     

To tag or not to tag: a comparative evaluation of immunoaffinity-labeling and tandem mass spectrometry for the identification and localization of posttranslational protein carbonylation by 4-hydroxy-2-nonenal, an end-product of lipid peroxidation

Posttranslational carbonylation of proteins by the covalent attachment of the lipid peroxidation product 4-hydroxy-2-nonenal (HNE) is a biomarker of oxidative stress. Tandem mass spectrometry (MS/MS) has become an essential tool for characterization of this modification. Chemical tagging methods have been used to facilitate the immunoaffinity-based enrichment or even quantification of HNE-modified peptides and proteins. With MS/MS spectra of the untagged modified peptides considered as references, a comparative evaluation is presented focusing on the impact of affinity-tagging with four carbonyl-specific reagents (2,4-dinitrophenyl hydrazine, biotin hydrazide, biotinamidohexanoic acid hydrazide and N'-aminooxymethylcarbonyl-hydrazino D-biotin) on collision-induced dissociation of the tagged HNE-carbonylated peptides. Our study has shown that chemical labeling may not be carried out successfully for all the peptides and with all the reagents. The attachment of a tag usually cannot circumvent the occurrence of strong neutral losses observed with untagged species and, in addition, fragmentation of the introduced tag may also happen. Chemical tagging of certain peptides may, nevertheless, afford more sequence ions upon MS/MS than the untagged carbonylated peptide, especially when Michael addition of the lipid peroxidation product occurs on cysteine residues. Therefore, tagging may increase the confidence of identifications of HNE-modified peptides by database searches.     

Human urine proteome analysis by three separation approaches

The urinary proteome is known to be a valuable field of study related to organ functions. There have been several extensive urine proteome studies. However, the overlapping rate among different studies is relatively low. Whether the low overlapping rate was caused by different sample sources, preparation, separation and identification methods is unknown. Moreover, low molecular mass (<10 kDa) proteins have not been studied extensively. In this report, male and female pooled urine samples were collected from healthy volunteers. The urinary proteins were acetone precipitated, separated and identified by three approaches, 1-DE plus 1-D LC/MS/MS, direct 1-D LC/MS/MS and 2-D LC/MS/MS. 1-D tricine gels were used to separate low molecular mass proteins. The tandem mass spectra of positive identifications were quality controlled both by manual validation and using advanced mass spectrum scanner software. A total of 226 urinary proteins were identified; 171 proteins were identified by proteomics approach for the first time, including 4 male-specific proteins. Twelve low molecular mass proteins were identified. Most urinary proteins had a molecular mass between 30 and 60 kDa and a pI between 4 and 10. The apparent molecular masses of many proteins were different from theoretical ones, which indicated their post-translational modification and degradation. The effects of sample preparation, separation and identification methods on the overlapping rate of different experiments are discussed.     

Quantitative proteomic analysis of the secretory proteins from rat adipose cells using a 2D liquid chromatography-MS/MS approach

We have developed two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) and 18O proteolytic labeling strategies to identify and compare levels of secretory proteins with low abundance in the conditioned medium of rat adipose cells without or with insulin stimulation. Culture medium was concentrated and secreted proteins were separated on a RP-HPLC followed by LC-MS/MS analysis. For 18O proteolytic labeling, 16O- to 18O-exchange in the digested peptides from eight individual fractions was carried out in parallel in H2(16)O and H(2)18O with immobilized trypsin, and the ratios of isotopically distinct peptides were measured by mass spectrometry. A total of 84 proteins was identified as secreted adipokines. This large number of secretory proteins comprise multiple functional categories. Comparative proteomics of 18O proteolytic labeling allows the detection of different levels of many secreted proteins as exemplified here by the difference between basal and insulin treatment of adipose cells. Taken together, our proteomic approach is able to identify and quantify the comprehensive secretory proteome of adipose cells. Thus, our data support the endocrine role of adipose cells in pathophysiological states through the secretion of signaling molecules.