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Offline high-pH reversed-phase fractionation is widely used to reduce sample complexity in proteomic workflows. This is due to the semi-orthogonality and high peak resolution of the two separations. Offline 2D fractionation, however, is low throughput and requires several manual manipulations and is prone to sample losses. To address these issues, we developed an online two dimensional high-pH - low-pH reversed-phase-reversed-phase (2D RPRP) LC-MRM method whereby hundreds of peptides can be quantified in a single LC-MS/MS injection. The method allowed the reproducible and sensitive quantitation of a test panel of 367 peptides (168 proteins) from undepleted and non-enriched human plasma. Of these, we were able to detect and quantify 95 peptides (29 proteins) by 2D-RPRP that were not detectable by 1D LC-MRM-MS. Online 2D RPRP resulted in an average increase of roughly 10-fold in sensitivity compared to traditional 1D low-pH separations, while improving reproducibility and sample throughput relative to offline 2D RPRP by factors of 1.7 and 5, respectively, compared to offline 2D RPRP. This paper serves as proof-of-concept of the feasibility and efficacy of online 2D RPRP at analytical flow rates for highly multiplexed targeted proteomic analyses.

Seed germination provides an excellent model to study the process of mitochondrial biogenesis. It is a complex and strictly regulated process which requires a proper biogenesis of fully active organelles from existing promitochondrial structures. We have previously reported that the lack of the inner mitochondrial membrane protease FTSH4 delayed Arabidopsis seed germination. Here, we implemented a targeted mass spectrometry-based approach, Multiple Reaction Monitoring (MRM), with stable-isotope-labeled standard peptides for increased sensitivity, to quantify mitochondrial proteins in dry and germinating wild-type and ftsh4 mutant seeds, lacking the FTSH4 protease. Using total seed protein extracts we measured the abundance of the peptide targets belonging to the OXPHOS complexes, AOX1A, transport, and inner membrane scaffold as well as mitochondrial proteins that are highly specific to dry and germinating seeds. The MRM assay showed that the abundance of these proteins in ftsh4 did not differ substantially from that observed in wild-type at the level of dry seed and after stratification, but we observed a reduction in protein abundance in most of the examined OXPHOS subunits in the later stages of germination. These changes in OXPHOS protein levels in ftsh4 mutants were accompanied by a lower cytochrome pathway activity as well as an increased AOX1A amount at the transcript and protein level and alternative pathway activity. The analyses of the steady-state transcript levels of mitochondrial and nuclear genes encoding OXPHOS subunits did not show significant difference in their amount, indicating that the observed changes in the OXPHOS occurred at the post-transcriptional level. At the time when ftsh4 seeds were fully germinated, the abundance of the OXPHOS proteins in the mutant was either slightly lowered or comparable to these amounts in wild-type seeds at the similar developmental stage. By the implementation of an integrative approach combining targeted proteomics, quantitative transcriptomics, and physiological studies we have shown that the FTSH4 protease has an important role in the biogenesis of OXPHOS and thus biogenesis of mitochondria during germination of Arabidopsis seeds.

There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography–mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. Biological significance The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics.

Three common urological diseases are bladder cancer, urinary tract infection, and hematuria. Seventeen bladder cancer biomarkers were previously discovered using iTRAQ - these findings were verified by MRM-MS in this current study. Urine samples from 156 patients with hernia (n=57, control), bladder cancer (n=76), or urinary tract infection/hematuria (n=23) were collected and subjected to multiplexed LC-MRM/MS to determine the concentrations of 63 proteins that are normally considered to be plasma proteins, but which include proteins found in our earlier iTRAQ study. Sixty-five stable isotope-labeled standard proteotypic peptides were used as internal standards for 63 targeted proteins. Twelve proteins showed higher concentrations in the bladder cancer group than in the hernia and the urinary tract infection/hematuria groups, and thus represent potential urinary biomarkers for detection of bladder cancer. Prothrombin had the highest AUC (0.796), with 71.1% sensitivity and 75.0% specificity for differentiating bladder cancer (n=76) from non-cancerous (n=80) patients. The multiplexed MRM-MS data was used to generate a six-peptide marker panel. This six-peptide panel (afamin, adiponectin, complement C4 gamma chain, apolipoprotein A-II precursor, ceruloplasmin, and prothrombin) can discriminate bladder cancer subjects from non-cancerous subjects with an AUC of 0.814, with a 76.3% positive predictive value, and a 77.5% negative predictive value. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

In this study we demonstrate the use of a multiplexed MRM-based assay to distinguish among normal (NL) and iron-metabolism disorder mouse models, particularly, iron-deficiency anemia (IDA), inflammation (INFL), and inflammation and anemia (INFL + IDA). Our initial panel of potential biomarkers was based on the analysis of 14 proteins expressed by candidate genes involved in iron transport and metabolism. Based on this study, we were able to identify a panel of 8 biomarker proteins: apolipoprotein A4 (APO4), transferrin, transferrin receptor 1, ceruloplasmin, haptoglobin, lactoferrin, hemopexin, and matrix metalloproteinase-8 (MMP8) that clearly distinguish among the normal and disease models. Within this set of proteins, transferrin showed the best individual classification accuracy over all samples (72%) and within the NL group (94%). Compared to the best single-protein biomarker, transferrin, the use of the composite 8-protein biomarker panel improved the classification accuracy from 94% to 100% in the NL group, from 50% to 72% in the INFL group, from 66% to 96% in the IDA group, and from 79% to 83% in the INFL + IDA group. Based on these findings, validation of the utility of this potentially important biomarker panel in human samples in an effort to differentiate IDA, inflammation, and combinations thereof, is now warranted. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

The analytical performance of a standard-flow ultra-high-performance liquid chromatography (UHPLC) and a nano-flow high-performance liquid chromatography (HPLC) system, interfaced to the same state-of-the-art triple-quadrupole mass spectrometer, were compared for the multiple reaction monitoring (MRM)-mass spectrometry (MS)-based quantitation of a panel of 48 high-to-moderate-abundance cardiovascular disease-related plasma proteins. After optimization of the MRM transitions for sensitivity and testing for chemical interference, the optimum sensitivity, loading capacity, gradient, and retention-time reproducibilities were determined. We previously demonstrated the increased robustness of the standard-flow platform, but we expected that the standard-flow platform would have an overall lower sensitivity. This study was designed to determine if this decreased sensitivity could be compensated for by increased sample loading. Significantly fewer interferences with the MRM transitions were found for the standard-flow platform than for the nano-flow platform (2 out of 103 transitions compared with 42 out of 103 transitions, respectively), which demonstrates the importance of interference-testing when nano-flow systems are used. Using only interference-free transitions, 36 replicate LC/MRM-MS analyses resulted in equal signal reproducibilities between the two platforms (9.3 % coefficient of variation (CV) for 88 peptide targets), with superior retention-time precision for the standard-flow platform (0.13 vs. 6.1 % CV). Surprisingly, for 41 of the 81 proteotypic peptides in the final assay, the standard-flow platform was more sensitive while for 9 of 81 the nano-flow platform was more sensitive. For these 81 peptides, there was a good correlation between the two sets of results (R 2 = 0.98, slope = 0.97). Overall, the standard-flow platform had superior performance metrics for most peptides, and is a good choice if sufficient sample is available.

Induction of terpene synthase (TPS) gene expression and enzyme activity is known to occur in response to various chemical and biological stimuli in several species of spruce (genus Picea). However, high sequence identity between TPS family members has made it difficult to determine the induction patterns of individual TPS at the protein and transcript levels and whether specific TPS enzymes respond differentially to treatment. In the present study we used a multi-level approach to measure the induction and activity of TPS enzymes in protein extracts of Norway spruce (Picea abies) bark tissue following treatment with methyl jasmonate (MeJA). Measurements were made on the transcript, protein, enzyme activity and metabolite levels. Using a relatively new proteomics application, selective reaction monitoring (SRM), it was possible to differentiate and quantitatively measure the abundance of several known TPS proteins and three 1-deoxy-D-xylulose 5-phosphate synthase (DXS) isoforms in Norway spruce. Protein levels of individual TPS and DXS enzymes were differentially induced upon MeJA treatment and good correlation was generally observed between induction of transcripts, proteins, and enzyme activities. Most of the mono- and diterpenoid metabolites accumulated with similar temporal patterns of induction as part of the coordinated multi-compound chemical defense response. Protein and enzyme activity levels of the monoTPS (+)-3-carene synthase and the corresponding accumulation of (+)-3-carene was induced to a higher fold change than any other TPS or metabolite measured, indicating an important role in the induced terpenoid defense response in Norway spruce.

One challenge in Multiple Reaction Monitoring (MRM)-based proteomics is to select the most appropriate surrogate peptides to represent a target protein. We present here a software package to automatically generate these most appropriate surrogate peptides for an LC/MRM–MS analysis. Our method integrates information about the proteins, their tryptic peptides, and the suitability of these peptides for MRM which is available online in UniProtKB, NCBI's dbSNP, ExPASy, PeptideAtlas, PRIDE, and GPMDB. The scoring algorithm reflects our knowledge in choosing the best candidate peptides for MRM, based on the uniqueness of the peptide in the targeted proteome, its physiochemical properties, and whether it previously has been observed. The modularity of the workflow allows further extension and additional selection criteria to be incorporated. We have developed a simple Web interface where the researcher provides the protein accession number, the subject organism, and peptide-specific options. Currently, the software is designed for human and mouse proteomes, but additional species can be easily be added. Our software improved the peptide selection by eliminating human error, considering multiple data sources and all of the isoforms of the protein, and resulted in faster peptide selection — approximately 50 proteins per hour compared to 8 per day. Biological significance Compiling a list of optimal surrogate peptides for target proteins to be analyzed by LC/MRM–MS has been a cumbersome process, in which expert researchers retrieved information from different online repositories and used their own reasoning to find the most appropriate peptides. Our scientific workflow automates this process by integrating information from different data sources including UniProt, Global Proteome Machine, NCBI's dbSNP, and PeptideAtlas, simulating the researchers' reasoning, and incorporating their knowledge of how to select the best proteotypic peptides for an MRM analysis. The developed software can help to standardize the selection of peptides, eliminate human error, and increase productivity.

Targeted proteomics using multiple reaction monitoring (MRM) has become the method of choice for the rapid, precise, and reproducible quantitation of proteins in complex biological matrices. MRM-based targeted proteomics allows protein profiling in complex biological samples and accurate comparisons of between samples [1-6], typically using a bottom-up LC-MS/MS approach [7]. While relative quantitation approaches report differences in fold-changes between the samples being compared, absolute methods measure the concentrations [8], ideally based on isotopically labeled internal standard peptides that are analogues of the endogenous proteotypic target peptides [9]. The use of stable-isotope labeled standard (SIS) peptides is a key factor in the precision and reproducibility of absolute quantitation experiments using LC/MRM-MS, but the results may still not be accurate. Experimentally derived concentrations for specific tissues or biofluids can vary as a function of digestion protocol, or even which peptides are selected to represent a given protein [10-12]. This article is protected by copyright. All rights reserved

β-escin is a mixture of triterpene saponins isolated from the horse chestnut seeds (Aesculus hippocastanum L.). The anti-edematous, anti-inflammatory and venotonic properties of β-escin have been the most extensively clinically investigated effects of this plant-based drug and randomized controlled trials have proved the efficacy of β-escin for the treatment of chronic venous insufficiency. However, despite the clinical recognition of the drug its pharmacological mechanism of action still remains largely elusive. To determine the cellular and molecular basis for the therapeutic effectiveness of β-escin we performed discovery and targeted proteomic analyses and in vitro evaluation of cellular and molecular responses in human endothelial cells under inflammatory conditions. Our results demonstrate that in endothelial cells β-escin potently induces cholesterol synthesis which is rapidly followed with marked fall in actin cytoskeleton integrity. The concomitant changes in cell functioning result in a significantly diminished responses to TNF-α stimulation. These include reduced migration, alleviated endothelial monolayer permeability, and inhibition of NFκB signal transduction leading to down-expression of TNF-α-induced effector proteins. Moreover, the study provides evidence for novel therapeutic potential of β-escin beyond the current vascular indications.

A highly-multiplexed MRM-based assay for determination of cardiovascular disease (CVD) status and disease classification has been developed for clinical research. A high-flow system using ultra-high performance LC and an Agilent 6490 triple quadrupole mass spectrometer, equipped with an ion funnel, provided ease of use and increased the robustness of the assay. The assay uses 135 stable isotope-labeled peptide standards for the quantitation of 67 putative biomarkers of CVD in tryptic digests of whole plasma in a 30-min assay. Eighty-five analyses of the same sample showed no loss of sensitivity (20% CV for 134/135 peptides) and no loss of retention time accuracy (0.5% CV for all peptides). The maximum linear dynamic range of the MRM assays ranged from 10(3) -10(5) for 106 of the assays. Excellent linear responses (r0.98) were obtained for 117 of the 135 peptide targets with attomole level limits of quantitation (20% CV and accuracy 80-120%) for 81 of the 135 peptides. The assay presented in this study is easy to use, robust, sensitive, and has high-throughput capabilities through short analysis time and complete automated sample preparation. It is therefore well suited for CVD biomarker validation and discovery in plasma.

Blood sample processing and handling can have a significant impact on the stability and levels of proteins measured in biomarker studies. Such pre-analytical variability needs to be well understood in the context of the different proteomics platforms available for biomarker discovery and validation. In the present study we evaluated different types of blood collection tubes including the BD P100 tube containing protease inhibitors as well as CTAD tubes, which prevent platelet activation. We studied the effect of different processing protocols as well as delays in tube processing on the levels of 55 mid and high abundance plasma proteins using novel multiple-reaction monitoring-mass spectrometry (MRM-MS) assays as well as 27 low abundance cytokines using a commercially available multiplexed bead-based immunoassay. The use of P100 tubes containing protease inhibitors only conferred proteolytic protection for 4 cytokines and only one MRM-MS-measured peptide. Mid and high abundance proteins measured by MRM are highly stable in plasma left unprocessed for up to six hours although platelet activation can also impact the levels of these proteins. The levels of cytokines were elevated when tubes were centrifuged at cold temperature, while low levels were detected when samples were collected in CTAD tubes. Delays in centrifugation also had an impact on the levels of cytokines measured depending on the type of collection tube used. Our findings can help in the development of guidelines for blood collection and processing for proteomic biomarker studies.

We have developed a phosphatase-based phosphopeptide quantitation (PPQ) method for determining phosphorylation stoichiometry in complex biological samples. This PPQ method is based on enzymatic dephosphorylation, combined with specific and accurate peptide identification and quantification by multiple reaction monitoring (MRM) with stable-isotope-labeled standard peptides. In contrast with classical MRM methods for the quantitation of phosphorylation stoichiometry, the PPQ-MRM method needs only one nonphosphorylated SIS (stable isotope-coded standard) and two analyses (one for the untreated sample and one for the phosphatase-treated sample), from which the expression and modification levels can accurately be determined. From these analyses, the percent phosphorylation can be determined. In this manuscript, we compare the PPQ-MRM method with an MRM method without phosphatase and demonstrate the application of these methods to the detection and quantitation of phosphorylation of the classic phosphorylated breast cancer biomarkers (ERalpha and HER2), and for phosphorylated RAF and ERK1, which also contain phosphorylation sites of biological importance. Using synthetic peptides spiked into a complex protein digest, we were able to use our PPQ-MRM method to accurately determine the total phosphorylation stoichiometry on specific peptides as well as the absolute amount of the peptide and phosphopeptide present. Analyses of samples containing ERalpha protein revealed that the PPQ-MRM method is capable of determining phosphorylation stoichiometry in proteins from cell lines, and is in good agreement with determinations obtained using the direct MRM approach in terms of phosphorylation and total protein amount.

Despite the extensive use of wildlife species in elucidating important biological processes, very few gene expression tools are available. For example, many frog species with different sensitivities and ecological niches are used as sentinel species for environmental contaminants and as developmental models. However, gene expression analyses have been essentially limited to one laboratory species. In an attempt to extend gene expression analyses to relevant indigenous species, we have developed a frog cDNA array with probes designed against conserved protein-encoding sequences. Changes in gene expression profiles were identified in cultured tail tips of Rana catesbeiana tadpoles during induction of tail regression by exogenous thyroid hormone and are associated with a transition from active cell proliferation to increased apoptotic activity. The expression profiles of selected genes representative of different response patterns were further characterized in tails of tadpoles undergoing natural metamorphosis using de novo designed biomarker probes and quantitative real-time polymerase chain reaction analysis. The results support the cross-species application of cDNA arrays that can direct the development of gene expression biomarkers for indigenous wildlife species.