Mitochondrial protein expression during sweet pepper (Capsicum annuum L.) fruit ripening: iTRAQ-based proteomic analysis and role of cytochrome c oxidase.

The physiological process of fruit ripening is associated with the late developmental stages of plants in which mitochondrial organelles play an important role in the final success of this whole process. Thus, an isobaric tag for relative and absolute quantification (iTRAQ)-based analysis was used to quantify the mitochondrial proteome in pepper fruits in this study. Analysis of both green and red pepper fruits identified a total of 2284 proteins, of which 692 were found to be significantly more abundant in unripe green fruits as compared to red fruits, while 497 showed lower levels as the ripening process proceeded. Of the total number of proteins identified, 2253 (98,6%) were found to share orthologs with Arabidopsis thaliana. Proteomic analysis identified 163 proteins which were categorized as cell components, the major part assigned to cellular, intracellular space and other subcellular locations such as cytosol, plastids and, to a lesser extent, to mitochondria. Of the 224 mitochondrial proteins detected in pepper fruits, 78 and 48 were more abundant in green and red fruits, respectively. The majority of these proteins which displayed differential abundance in both fruit types were involved in the mitochondrial electron transport chain (mETC) and the tricarboxylic acid (TCA) cycle. The abundance levels of the proteins from both pathways were higher in green fruits, except for cytochrome c (CYC2), whose abundance was significantly higher in red fruits. We also investigated cytochrome c oxidase (COX) activity during pepper fruit ripening, as well as in the presence of molecules such as nitric oxide (NO) and hydrogen peroxide (H2O2), which promote thiol-based oxidative post-translational modifications (oxiPTMs). Thus, with the aid of in vitro assays, cytochrome c oxidase (COX) activity was found to be potentially inhibited by the PTMs nitration, S-nitrosation and carbonylation. According to protein abundance data, the final segment of the mETC appears to be a crucial locus with regard to fruit ripening, but also because in this location the biosynthesis of ascorbate, an antioxidant which plays a major role in the metabolism of pepper fruits, occurs.

Quantitative proteomic analysis of serum-purified exosomes identifies putative pre-eclampsia-associated biomarkers.

BACKGROUND: The high incidence of pre-eclampsia, which affects 2-7% of all pregnancies, remains a major health concern. Detection of pre-eclampsia before the appearance of clinical symptoms is essential to allow early intervention, and would benefit from identification of plasma/serum biomarkers to help guide diagnosis and treatment. Liquid biopsy has emerged as a promising source of protein biomarkers that circumvents some of the inherent challenges of proteome-wide analysis of plasma/serum. In this respect, purified exosomes have the added benefit of being carriers of intercellular communication both in physiological and pathological conditions. METHODS: We compared the protein complement of purified exosomes from three different collections of control and pre-eclamptic serum samples, obtained at the end of the second trimester of pregnancy and at delivery. We employed shotgun label-free proteomics to investigate differential protein expression, which was then validated by targeted proteomics. RESULTS: We developed a purification method that yielded highly enriched exosome preparations. The presence of specific pregnancy protein markers suggested that a significant proportion of purified exosomes derived from tissues related to pregnancy. Quantitative proteomic analyses allowed us to identify 10, 114 and 98 differentially-regulated proteins in the three sample collections, with a high degree of concordance. Functional analysis suggested that these proteins participate in biological processes related to pre-eclampsia, including angiogenesis, inflammation and cell migration. The differential abundance of 66 proteins was validated by targeted proteomics. Finally, we studied the impact of the pre-eclampsia-associated exosomes in the proteome using an in vitro cellular model. CONCLUSIONS: We have identified and validated differential exosomal proteins in liquid biopsy of pregnant women that open new possibilities for early detection of pre-eclampsia. Additionally, the functional impact of the proteome composition of purified pre-eclamptic exosomes in target cells provides new information to better understand changes in embryo-maternal interactions and, consequently, the pathogenesis of this disease.

The surface coating of iron oxide nanoparticles drives their intracellular trafficking and degradation in endolysosomes differently depending on the cell type.

Magnetic nanoparticles (MNPs) are potential theranostic tools that are biodegraded through different endocytic pathways. However, little is known about the endolysosomal network through which MNPs transit and the influence of the surface coating in this process. Here, we studied the intracellular transit of two MNPs with identical iron oxide core size but with two distinct coatings: 3-aminopropyl-trietoxysilane (APS) and dimercaptosuccinic acid (DMSA). Using endolysosomal markers and a high throughput analysis of the associated proteome, we tracked the MNPs intracellularly in two different mouse cell lines, RAW264.7 (macrophages) and Pan02 (tumor cells). We did not detect differences in the MNP trafficking kinetics nor in the MNP-containing endolysosome phenotype in Pan02 cells. Nonetheless, DMSA-MNPs transited at slower rate than APS-MNPs in macrophages as measured by MNP accumulation in Rab7+ endolysosomes. Macrophage DMSA-MNP-containing endolysosomes had a higher percentage of lytic enzymes and catalytic proteins than their APS-MNP counterparts, concomitantly with a V-type ATPase enrichment, suggesting an acidic nature. Consequently, more autophagic vesicles are induced by DMSA-MNPs in macrophages, enhancing the expression of iron metabolism-related genes and proteins. Therefore, unlike Pan02 cells, the MNP coating appears to influence the intracellular trafficking rate and the endolysosome nature in macrophages. These results highlight how the MNP coating can determine the nanoparticle intracellular fate and biodegradation in a cell-type bias.

Monitoring one-carbon metabolism by mass spectrometry to assess liver function and disease.

Precision medicine promises to overcome the constraints of the traditional "one-for-all" healthcare approach through a clear understanding of the molecular features of a disease, allowing for innovative and tailored treatments. State-of-the-art proteomics has the potential to accurately explore the human proteome to identify, quantify, and characterize proteins associated with disease progression. There is a pressing need for informative biomarkers to diagnose liver disease early in its course to prevent severe disease for which no efficient treatment is yet available. Here, we propose the concept of a cellular pathway as a functional biomarker, whose monitorization may inform normal and pathological status. We have developed a standardized targeted selected-reaction monitoring assay to detect and quantify 13 enzymes of one-carbon metabolism (1CM). The assay is compliant with Clinical Proteomics Tumor Analysis Consortium (CPTAC) guidelines and has been included in the protein quantification assays that can be accessed through the assay portal at the CPTAC web page. To test the feasibility of the assay, we conducted a retrospective, proof-of-concept study on a collection of liver samples from healthy controls and from patients with cirrhosis or hepatocellular carcinoma (HCC). Our results indicate a significant reconfiguration of 1CM upon HCC development resulting from a process that can already be identified in cirrhosis. Our findings indicate that the systematic and integrated quantification of 1CM enzymes is a promising cell function-based biomarker for patient stratification, although further experiments with larger cohorts are needed to confirm these findings.

Iron Oxide Nanoparticle Coatings Dictate Cell Outcomes Despite the Influence of Protein Coronas.

A critical issue in nanomedicine is to understand the complex dynamics that dictate the interactions of nanoparticles (NPs) with their biological milieu. The most exposed part of a nanoparticle is its surface coating, which comes into contact with the biological medium and adsorbs proteins, forming what is known as a protein corona (PC). It is assumed that this PC mainly dictates the nanoparticle-cell interactions. As such, we set out to analyze how different coatings on iron oxide nanoparticles (MNPs) affect the composition of the PC that forms on top of them, and how these newly formed coronas influence the uptake of MNPs by macrophages and tumor cells, their subcellular location upon internalization, and their intracellular degradation. We found that different superficial charges of the coatings did not affect the PC composition, with an enrichment in proteins with affinity for divalent ions regardless of the type of coating. The iron oxide core of the MNP might become exposed to the biological medium, influencing the proteins that constitute the PCs. The presence of enzymes with hydrolase activity in the PC could explain the degradation of the coatings when they come into contact with the biological media. In terms of MNP internalization by cells, coatings mainly determine the endocytic pathways used, especially in terms of receptor-mediated endocytosis. However, the increase in hydrodynamic size provoked by the formation of the associated corona drives uptake mechanisms like macropinocytosis. Once inside the cells, the PC protected the NPs in their intracellular transit to lysosomes, where they were fully degraded. This understanding of how coatings and PCs influence different cellular processes will help design improved NPs for biomedical applications, taking into account the influence of the coating and corona on the biology of the NPs.

Which Low-Abundance Proteins are Present in the Human Milieu of Gamete/Embryo Maternal Interaction?

The improvement of the embryo culture media is of high relevance due to its influence on successful implantation rates, pregnancy, neonatal outcomes, and potential effects in adult life. The ideal conditions for embryo development are those naturally occurring in the female reproductive tract, i.e., the oviductal and uterine fluids. To shed light on the differences between chemical and natural media, we performed the first comparative study of the low abundance proteins in plasma, uterine, and oviductal fluid collected, simultaneously, from healthy and fertile women that underwent a salpingectomy. The rationale for this design derives from the fact that high-abundant proteins in these fluids are usually those coming from blood serum and frequently mask the detection of low abundant proteins with a potentially significant role in specific processes related to the embryo-maternal interaction. The proteomic analysis by 1D-nano LC ESI-MSMS detected several proteins in higher amounts in oviductal fluid when compared to uterine and plasma samples (RL3, GSTA1, EZRI, DPYSL3, GARS, HSP90A). Such oviductal fluid proteins could be a target to improve fertilization rates and early embryo development if used in the culture media. In conclusion, this study presents a high-throughput analysis of female reproductive tract fluids and contributes to the knowledge of oviductal and uterine secretome.

Identification of the Missing Protein Hyaluronan Synthase 1 in Human Mesenchymal Stem Cells Derived from Adipose Tissue or Umbilical Cord.

Currently, 14% of the human proteome is made up of proteins whose existence is not confirmed by mass spectrometry. We performed a proteomic profiling of human mesenchymal stem cells derived from adipose tissue or umbilical cord (PRIDE accession number: PXD009893) and identified peptides derived from 13 of such missing proteins. Remarkably, we found compelling evidence of the expression of hyaluronan synthase 1 (NX_Q92839-1) and confirmed its identification by the fragmentation of four heavy-labeled peptides that coeluted with their endogenous light counterparts. Our data also suggest that mesenchymal stem cells constitute a promising source for the detection of missing proteins.

A Molecular Basis for the Presentation of Phosphorylated Peptides by HLA-B Antigens.

As aberrant protein phosphorylation is a hallmark of tumor cells, the display of tumor-specific phosphopeptides by Human Leukocyte Antigen (HLA) class I molecules can be exploited in the treatment of cancer by T-cell-based immunotherapy. Yet, the characterization and prediction of HLA-I phospholigands is challenging as the molecular determinants of the presentation of such post-translationally modified peptides are not fully understood. Here, we employed a peptidomic workflow to identify 256 unique phosphorylated ligands associated with HLA-B*40, -B*27, -B*39, or -B*07. Remarkably, these phosphopeptides showed similar molecular features. Besides the specific anchor motifs imposed by the binding groove of each allotype, the predominance of phosphorylation at peptide position 4 (P4) became strikingly evident, as was the enrichment of basic residues at P1. To determine the structural basis of this observation, we carried out a series of peptide binding assays and solved the crystal structures of HLA-B*40 in complex with a phosphorylated ligand or its nonphosphorylated counterpart. Overall, our data provide a clear explanation to the common motif found in the phosphopeptidomes associated to different HLA-B molecules. The high prevalence of phosphorylation at P4 is dictated by the presence of the conserved residue Arg62 in the heavy chain, a structural feature shared by most HLA-B alleles. In contrast, the preference for basic residues at P1 is allotype-dependent and might be linked to the structure of the A pocket. This molecular understanding of the presentation of phosphopeptides by HLA-B molecules provides a base for the improved prediction and identification of phosphorylated neo-antigens, as potentially used for cancer immunotherapy.

Comparative Analysis of the Endogenous Peptidomes Displayed by HLA-B*27 and Mamu-B*08: Two MHC Class I Alleles Associated with Elite Control of HIV/SIV Infection.

Indian rhesus macaques are arguably the most reliable animal models in AIDS research. In this species the MHC class I allele Mamu-B*08, among others, is associated with elite control of SIV replication. A similar scenario is observed in humans where the expression of HLA-B*27 or HLA-B*57 has been linked to slow or no progression to AIDS after HIV infection. Despite having large differences in their primary structure, it has been reported that HLA-B*27 and Mamu-B*08 display peptides with sequence similarity. To fine-map the Mamu-B*08 binding motif and assess its similarities with that of HLA-B*27, we affinity purified the peptidomes bound to these MHC class I molecules and analyzed them by LC-MS, identifying several thousands of endogenous ligands. Sequence analysis of both sets of peptides revealed a degree of similarity in their binding motifs, especially at peptide position 2 (P2), where arginine was present in the vast majority of ligands of both allotypes. In addition, several differences emerged from this analysis: (i) ligands displayed by Mamu-B*08 tended to be shorter and to have lower molecular weight, (ii) Mamu-B*08 showed a higher preference for glutamine at P2 as a suboptimal binding motif, and (iii) the second major anchor position, found at PΩ, was much more restrictive in Mamu-B*08. In this regard, HLA-B*27 bound efficiently peptides with aliphatic, aromatic (including tyrosine), and basic C-terminal residues while Mamu-B*08 preferred peptides with leucine and phenylalanine in this position. Finally, in silico estimations of binding efficiency and competitive binding assays to Mamu-B*08 of several selected peptides revealed a good correlation between the characterized anchor motif and binding affinity. These results deepen our understanding of the molecular basis of the presentation of peptides by Mamu-B*08 and can contribute to the detection of novel SIV epitopes restricted by this allotype.

Design of a low power hybrid HIFU applicator for haemostasis based on acoustic propagation modelling.

PURPOSE: The aim of this study was to design an applicator for haemostasis usage needing lower acoustic intensities (<880 W/cm(2)) than in previous devices intended for it, which is based on ultrasound propagation FEM modelling using a 2-MHz HIFU transducer. MATERIALS AND METHODS: Acoustic field characterisation and numerical simulations in water were performed with and without the proposed applicator. Parameters such as form factor, ellipsoidal shape ratio, and Euclidean distance were used (among others) to compare simulated data with transducer measurements without applicator. A low density polyethylene cone was manufactured from geometries validated from acoustic field modelling. The hollow cone was filled with 10% polyacrylamide gel as a coupling medium with liver phantom or chicken liver. Focal temperature was measured with a thermocouple embedded in the phantom for 1-20 W driving powers for 120 s. Standing wave ratios (SWR) were used as coupling indexes. Ex vivo experimentation in chicken liver was made at 10-20 W. RESULTS: Simulated acoustic patterns showed good concordance with measurements. Experimental focal distance was 20.72 ± 0.24 mm, while the simulated was 19.79 mm (≈4% error). SWR at low power were: 2.01 with transducer emitting in air, 1.53 at applicator tip, and 1.35 after phantom placement. Average SWR at high power was 1.31. Similarity of percentages for data comparison in focal plane was over 60%. Maximum temperature measured at focus was 88.7 °C with 20 W after 85 s. CONCLUSIONS: Temperatures reached at focus suggest that this applicator has good efficiency, which notably reduces the power typically needed for haemostasis effect.

A DERL3-associated defect in the degradation of SLC2A1 mediates the Warburg effect.

Cancer cells possess aberrant proteomes that can arise by the disruption of genes involved in physiological protein degradation. Here we demonstrate the presence of promoter CpG island hypermethylation-linked inactivation of DERL3 (Derlin-3), a key gene in the endoplasmic reticulum-associated protein degradation pathway, in human tumours. The restoration of in vitro and in vivo DERL3 activity highlights the tumour suppressor features of the gene. Using the stable isotopic labelling of amino acids in cell culture workflow for differential proteome analysis, we identify SLC2A1 (glucose transporter 1, GLUT1) as a downstream target of DERL3. Most importantly, SLC2A1 overexpression mediated by DERL3 epigenetic loss contributes to the Warburg effect in the studied cells and pinpoints a subset of human tumours with greater vulnerability to drugs targeting glycolysis.

Increased diversity of the HLA-B40 ligandome by the presentation of peptides phosphorylated at their main anchor residue.

Human leukocyte antigen (HLA) class I molecules bind peptides derived from the intracellular degradation of endogenous proteins and present them to cytotoxic T lymphocytes, allowing the immune system to detect transformed or virally infected cells. It is known that HLA class I-associated peptides may harbor posttranslational modifications. In particular, phosphorylated ligands have raised much interest as potential targets for cancer immunotherapy. By combining affinity purification with high-resolution mass spectrometry, we identified more than 2000 unique ligands bound to HLA-B40. Sequence analysis revealed two major anchor motifs: aspartic or glutamic acid at peptide position 2 (P2) and methionine, phenylalanine, or aliphatic residues at the C terminus. The use of immobilized metal ion and TiO2 affinity chromatography allowed the characterization of 85 phosphorylated ligands. We further confirmed every sequence belonging to this subset by comparing its experimental MS2 spectrum with that obtained upon fragmentation of the corresponding synthetic peptide. Remarkably, three phospholigands lacked a canonical anchor residue at P2, containing phosphoserine instead. Binding assays showed that these peptides bound to HLA-B40 with high affinity. Together, our data demonstrate that the peptidome of a given HLA allotype can be broadened by the presentation of peptides with posttranslational modifications at major anchor positions. We suggest that ligands with phosphorylated residues at P2 might be optimal targets for T-cell-based cancer immunotherapy.

Air-coupled ultrasonic resonant spectroscopy for the study of the relationship between plant leaves' elasticity and their water content.

Air-coupled wideband ultrasonic piezoelectric transducers are used in the frequency range 0.3 to 1.3 MHz to excite and sense first-order thickness resonances in the leaves of four different tree species at different levels of hydration. The phase and magnitude spectra of these resonances are measured, and the inverse problem solved; that is, leaf thickness and density, ultrasound velocity, and the attenuation coefficient are obtained. The elastic constant in the thickness direction (c33) is then determined from density and velocity data. The paper focuses on the study of c33, which provides a unique, fast, and noninvasive ultrasonic method to determine leaf elasticity and leaf water content.

Inverse regulation in the metabolic genes pckA and metE revealed by proteomic analysis of the Salmonella RcsCDB regulon.

The RcsC, RcsD, and RcsB proteins compose a system used by enteric bacteria to sense envelope stress. Signal transmission occurs from the sensor RcsC to the transcriptional regulator RcsB. Accessory proteins, such as IgaA, are known to adjust the response level. In a previous transcriptomic study, we uncovered 85 genes differentially expressed in Salmonella enterica serovar Typhimurium igaA mutants. Here, we extended these observations to proteomics by performing differential isotope-coded protein labeling (ICPL) followed by liquid chromatography-electrospray ionization tandem mass spectrometry. Five-hundred five proteins were identified and quantified, with 75 of them displaying significant changes in response to alterations in the RcsCDB system. Divergent expression at the RNA and protein level was observed for the metabolic genes pckA and metE, involved in gluconeogenesis and methionine synthesis, respectively. When analyzed in diverse environmental conditions, including the intracellular niche of eukaryotic cells, inverse regulation was more evident for metE and in bacteria growing in defined minimal medium or to stationary phase. The RcsCDB system was also shown to repress the synthesis of the small RNA FnrS, previously reported to modulate metE expression. Collectively, these findings provide new insights into post-transcriptional regulatory mechanisms involving the RcsCDB system and its control over metabolic functions.

Evaluation of isotope-coded protein labeling (ICPL) in the quantitative analysis of complex proteomes.

An evaluation of the ICPL (isotope-coded protein labeling) non-isobaric labeling technique was performed using two different biological models. Two samples containing phage T4 capsids were mixed in a 1:1 ratio after being labeled with the light or heavy versions of the ICPL reagent. The analysis of this proteome demonstrated the feasibility of this approach for differential quantitative proteomics and was employed to optimize the experimental parameters of the ICPL workflow. ICPL-mediated analysis of two more complex proteomes, those of a Salmonella enterica serovar Typhimurium virulent strain and an isogenic attenuated mutant, and its comparison with the results obtained in a 2D-PAGE "classical" approach confirmed that ICPL is a valuable alternative to other labeling techniques currently in use. In addition, our results suggest that labeling at the peptide level instead of following the standard ICPL workflow should increase both the number of proteins quantified and the reliability of the quantification.

Generalized method for probability-based peptide and protein identification from tandem mass spectrometry data and sequence database searching.

Tandem mass spectrometry-based proteomics is currently in great demand of computational methods that facilitate the elimination of likely false positives in peptide and protein identification. In the last few years, a number of new peptide identification programs have been described, but scores or other significance measures reported by these programs cannot always be directly translated into an easy to interpret error rate measurement such as the false discovery rate. In this work we used generalized lambda distributions to model frequency distributions of database search scores computed by MASCOT, X!TANDEM with k-score plug-in, OMSSA, and InsPecT. From these distributions, we could successfully estimate p values and false discovery rates with high accuracy. From the set of peptide assignments reported by any of these engines, we also defined a generic protein scoring scheme that enabled accurate estimation of protein-level p values by simulation of random score distributions that was also found to yield good estimates of protein-level false discovery rate. The performance of these methods was evaluated by searching four freely available data sets ranging from 40,000 to 285,000 MS/MS spectra.

Properties of average score distributions of SEQUEST: the probability ratio method.

High throughput identification of peptides in databases from tandem mass spectrometry data is a key technique in modern proteomics. Common approaches to interpret large scale peptide identification results are based on the statistical analysis of average score distributions, which are constructed from the set of best scores produced by large collections of MS/MS spectra by using searching engines such as SEQUEST. Other approaches calculate individual peptide identification probabilities on the basis of theoretical models or from single-spectrum score distributions constructed by the set of scores produced by each MS/MS spectrum. In this work, we study the mathematical properties of average SEQUEST score distributions by introducing the concept of spectrum quality and expressing these average distributions as compositions of single-spectrum distributions. We predict and demonstrate in the practice that average score distributions are dominated by the quality distribution in the spectra collection, except in the low probability region, where it is possible to predict the dependence of average probability on database size. Our analysis leads to a novel indicator, the probability ratio, which takes optimally into account the statistical information provided by the first and second best scores. The probability ratio is a non-parametric and robust indicator that makes spectra classification according to parameters such as charge state unnecessary and allows a peptide identification performance, on the basis of false discovery rates, that is better than that obtained by other empirical statistical approaches. The probability ratio also compares favorably with statistical probability indicators obtained by the construction of single-spectrum SEQUEST score distributions. These results make the robustness, conceptual simplicity, and ease of automation of the probability ratio algorithm a very attractive alternative to determine peptide identification confidences and error rates in high throughput experiments.

Improved method for differential expression proteomics using trypsin-catalyzed 18O labeling with a correction for labeling efficiency.

Quantitative strategies relying on stable isotope labeling and isotope dilution mass spectrometry have proven to be a very robust alternative to the well established gel-based techniques for the study of the dynamic proteome. Postdigestion 18O labeling is becoming very popular mainly due to the simplicity of the enzyme-catalyzed exchange reaction, the peptide handling and storage procedures, and the flexibility and versatility introduced by decoupling protein digestion from peptide labeling. Despite recent progresses, peptide quantification by postdigestion 18O labeling still involves several computational problems. In this work we analyzed the behavior of large collections of peptides when they were subjected to postdigestion labeling and concluded that this process can be explained by a universal kinetic model. On the basis of this observation, we developed an advanced quantification algorithm for this kind of labeling. Our method fits the entire isotopic envelope to parameters related with the kinetic exchange model, allowing at the same time an accurate calculation of the relative proportion of peptides in the original samples and of the specific labeling efficiency of each one of the peptides. We demonstrated that the new method eliminates artifacts produced by incomplete oxygen exchange in subsets of peptides that have a relatively low labeling efficiency and that may be considered indicative of false protein ratio deviations. Finally using a rigorous statistical analysis based on the calculation of error rates associated with false expression changes, we showed the validity of the method in the practice by detecting significant expression changes, produced by the activation of a model preparation of T cells, with only 5 microg of protein in three proteins among a pool of more than 100. By allowing a full control over potential artifacts, our method may improve automation of the procedures for relative protein quantification using this labeling strategy.

Quantitative proteomics using 16O/18O labeling and linear ion trap mass spectrometry.

Quantitative proteomics using stable isotopic 16O/18O labeling has emerged as a very powerful tool, since it has a number of advantages over other methods, including the simplicity of chemistry, the constant mass tag at the C termini and its general applicability. However, due to the small mass difference between labeled and unlabeled peptide species, this approach has usually been restricted to high-resolution mass spectrometers. In this study we explored whether the high-resolution scanning mode, together with the extremely high scanning speed of the linear IT allows the 16O/18O-labeling method to be used for accurate, large-scale quantitative analysis of proteomes. A protocol, including digestion, desalting, labeling, MS and quantitative analysis was developed and tested using protein standards and whole proteome extracts. Using this method we were able to identify and quantify 140 proteins from only 10 mug of a proteome extract from mesenchymal stem cells. Relative expression changes larger than twofold can be identified with this method at the 95% confidence level. Our results demonstrate that accurate quantitative analysis using 16O/18O labeling can be performed in the practice using linear IT MS, without compromising large-scale peptide identification efficiency.