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ABSTRACT: Selected Reaction Monitoring (SRM) is emerging as a standard tool for high-throughput protein quantification. For reliable and reproducible SRM protein quantification it is essential that system performance is stable. We present here a quality control workflow that is based on repeated analysis of a standard sample to allow insight into the stability of the key properties of a SRM setup. This is supported by automated software to monitor system performance and display information like signal intensities and retention time stability over time, and alert upon deviations from expected metrics. Utilizing the software to evaluate 407 repeated injections of a standard sample during half a year, outliers in relative peptide signal intensities and relative peptide fragment ratios are identified, indicating the need for instrument maintenance. We therefore believe the software could be a vital and powerful tool for any lab regularly performing SRM, increasing the reliability and quality of the SRM platform. This article is part of a Special Issue entitled: Standardization and Quality Control BIOLOGICAL SIGNIFICANCE: Selected Reaction Monitoring (SRM) mass spectrometry is becoming established as a standard technique for accurate protein quantification. However, to achieve the required quantification reproducibility of the liquid chromatography(LC)-SRM setup, system performance needs to be monitored over time. Here we introduce a workflow with associated software to enable automated monitoring of LC-SRM setups. We believe that usage of the presented concepts will further strengthen the role of SRM as a reliable tool for protein quantification.
Journal of proteomics 04/2013; · 5.07 Impact Factor
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ABSTRACT: Protein quantification using different LC-MS techniques is becoming standard practice. However, with a multitude of experimental setups to choose from, as well as a wide array of software solutions for subsequent data processing, it is non-trivial to select the most appropriate workflow for a given biological question. In this review, we highlight different issues that need to be addressed by software for quantitative LC-MS experiments and describe different approaches that are available. With focus on label-free quantification, examples are discussed both for LC-MS/MS and LC-SRM data processing. We further elaborate on current quality control methodology for performing accurate protein quantification experiments.
Biochimica et Biophysica Acta 04/2013; · 4.66 Impact Factor
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ABSTRACT: Selected reaction monitoring mass spectrometry (SRM-MS) is a targeted proteomics technology used to identify and quantify proteins with high sensitivity, specificity and high reproducibility. Execution of SRM-MS relies on protein-specific SRM assays, a set of experimental parameters that requires considerable effort to develop. Here we present a proteome-wide SRM assay repository for the gram-positive human pathogen group A Streptococcus. Using a multi-layered approach we generated SRM assays for 10,412 distinct group A Streptococcus peptides followed by extensive testing of the selected reaction monitoring assays in >200 different group A Streptococcus protein pools. Based on the number of SRM assay observations we created a rule-based selected reaction monitoring assay-scoring model to select the most suitable assays per protein for a given cellular compartment and bacterial state. The resource described here represents an important tool for deciphering the group A Streptococcus proteome using selected reaction monitoring and we anticipate that concepts described here can be extended to other pathogens.
Nature Communications 12/2012; 3:1301. · 7.40 Impact Factor
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ABSTRACT: Several of the most significant bacterial pathogens in humans, including Streptococcus pyogenes, express surface proteins that bind IgG antibodies via their fragment crystallizable (Fc) region, and the dogma is that this protects the bacteria against phagocytic killing in blood. However, analysis of samples from a patient with invasive S. pyogenes infection revealed dramatic differences in the presence and orientation of IgG antibodies at the surface of bacteria from different sites. In the throat, IgG was mostly bound to the bacterial surface via Fc, whereas in the blood IgG was mostly bound via fragment antigen-binding (Fab). In infected and necrotic tissue, the Fc-binding proteins were removed from the bacterial surface. Further investigation showed that efficient bacterial IgGFc-binding occurs only in IgG-poor environments, such as saliva. As a consequence, the bacteria are protected against phagocytic killing, whereas in blood plasma where the concentration of IgG is high, the antibodies preferentially bind via Fab, facilitating opsonization and bacterial killing. IgG-poor environments represent the natural habitat for IgGFc-binding bacteria, and IgGFc-binding proteins may have evolved to execute their function in such environments. The lack of protection in plasma also helps to explain why cases of severe invasive infections with IgGFc-binding bacteria are so rare compared with superficial and uncomplicated infections.
Journal of Experimental Medicine 12/2012; · 13.85 Impact Factor
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ABSTRACT: Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.
Journal of Proteome Research 06/2012; 11(7):3766-73. · 5.11 Impact Factor
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ABSTRACT: Transforming growth factor-β1 (TGF-β1) is a potent regulator of cell growth and differentiation. TGF-β1 has been shown to be a key player in tissue remodeling processes in a number of disease states by inducing expression of extracellular matrix proteins. In this study a quantitative proteomic analysis was undertaken to investigate if TGF-β1 contributes to tissue remodeling by mediating mRNA splicing and production of alternative isoforms of proteins.
The expression of proteins involved in mRNA splicing from TGF-β1-stimulated lung fibroblasts was compared to non-stimulated cells by employing isotope coded affinity tag (ICATTM) reagent labeling and tandem mass spectrometry. A total of 1733 proteins were identified and quantified with a relative standard deviation of 11% +/- 8 from enriched nuclear fractions. Seventy-six of these proteins were associated with mRNA splicing, including 22 proteins involved in splice site selection. In addition, TGF-β1 was observed to alter the relative expression of splicing proteins that may be important for alternative splicing of fibronectin. Specifically, TGF-β1 significantly induced expression of SRp20, and reduced the expression of SRp30C, which has been suggested to be a prerequisite for generation of alternatively spliced fibronectin. The induction of SRp20 was further confirmed by western blot and immunofluorescence.
The results show that TGF-β1 induces the expression of proteins involved in mRNA splicing and RNA processing in human lung fibroblasts. This may have an impact on the production of alternative isoforms of matrix proteins and can therefore be an important factor in tissue remodeling and disease progression.
Fibrogenesis & Tissue Repair 04/2012; 5(1):6.
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ABSTRACT: The objective of this study was to examine the effects of heparan sulfate (HS) on factors involved in the remodeling of connective
tissue observed in patients with fibrotic respiratory disorders such as asthma. A suitable working model is to stimulate human
fetal lung fibroblasts in vitro with structurally different forms of HS. Highly sulfated and iduronic acid (IdoUA)-rich HS
specifically decreased cell proliferaton, production of jyaluronan (HA), transforming growth factor (TGF)-β1, and TFF-β-induced α-smooth muscle actin but did not affect the overall proteoglycan production in the cells. These repressed
factors are suggested to play a critical role in the early stages of remodeling and myofibroblast activation. Low sulfated
and IdoUA-poor HS did not display any effects on these factors. Furthermore, analysis of the protein expression pattern by
two-dimensional gel electrophoresis revealed a 70% increased expression of annexin II, which has previously been shown to
have a high affinity for both heparin and HS. Heat-shock protein 27 and arsenite translocating factor, both involved in actin
organization and polymerization, were also increased in the HS-stimulated cells. Thus, the reduced expression of HA and TGF-β1, both important in the development of fibrosis, seems to be mediated by pecific changes in protein expression of the fibroblast.
The observed inhibition of cell proliferation, HA, and TGF-β1 allows speculation of highly sulfated HS as a antifibrotic candidate in the early stage of remodeling.
Clinical Proteomics 04/2012; 1(3):271-284.
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Sofia Waldemarson,
Morten Krogh,
Ayodele Alaiya,
Ufuk Kirik,
Kjell Schedvins,
Gert Auer,
Karin M Hansson,
Reto Ossola,
Ruedi Aebersold,
Hookeun Lee, Johan Malmström,
Peter James
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ABSTRACT: Epithelial ovarian carcinoma has in general a poor prognosis since the vast majority of tumors are genomically unstable and clinically highly aggressive. This results in rapid progression of malignancy potential while still asymptomatic and thus in late diagnosis. It is therefore of critical importance to develop methods to diagnose epithelial ovarian carcinoma at its earliest developmental stage, that is, to differentiate between benign tissue and its early malignant transformed counterparts. Here we present a shotgun quantitative proteomic screen of benign and malignant epithelial ovarian tumors using iTRAQ technology with LC-MALDI-TOF/TOF and LC-ESI-QTOF MS/MS. Pathway analysis of the shotgun data pointed to the PI3K/Akt signaling pathway as a significant discriminatory pathway. Selected candidate proteins from the shotgun screen were further confirmed in 51 individual tissue samples of normal, benign, borderline or malignant origin using LC-MRM analysis. The MRM profile demonstrated significant differences between the four groups separating the normal tissue samples from all tumor groups as well as perfectly separating the benign and malignant tumors with a ROC-area of 1. This work demonstrates the utility of using a shotgun approach to filter out a signature of a few proteins only that discriminates between the different sample groups.
Journal of Proteome Research 04/2012; 11(5):2876-89. · 5.11 Impact Factor
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ABSTRACT: Targeted proteomics allows researchers to study proteins of interest without being drowned in data from other, less interesting proteins or from redundant or uninformative peptides. While the technique is mostly used for smaller, focused studies, there are several reasons to conduct larger targeted experiments. Automated, highly robust software becomes more important in such experiments. In addition, larger experiments are carried out over longer periods of time, requiring strategies to handle the sometimes large shift in retention time often observed. We present a complete proof-of-principle software stack that automates most aspects of selected reaction monitoring workflows, a targeted proteomics technology. The software allows experiments to be easily designed and carried out. The steps automated are the generation of assays, generation of mass spectrometry driver files and methods files, and the import and analysis of the data. All data are normalized to a common retention time scale, the data are then scored using a novel score model, and the error is subsequently estimated. We also show that selected reaction monitoring can be used for label-free quantification. All data generated are stored in a relational database, and the growing resource further facilitates the design of new experiments. We apply the technology to a large-scale experiment studying how Streptococcus pyogenes remodels its proteome under stimulation of human plasma.
Journal of Proteome Research 03/2012; 11(3):1644-53. · 5.11 Impact Factor
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ABSTRACT: Streptococcus pyogenes is a major bacterial pathogen and a potent inducer of inflammation causing plasma leakage at the site of infection. A combination
of label-free quantitative mass spectrometry-based proteomics strategies were used to measure how the intracellular proteome
homeostasis of S. pyogenes is influenced by the presence of human plasma, identifying and quantifying 842 proteins. In plasma the bacterium modifies
its production of 213 proteins, and the most pronounced change was the complete down-regulation of proteins required for fatty
acid biosynthesis. Fatty acids are transported by albumin (HSA) in plasma. S. pyogenes expresses HSA-binding surface proteins, and HSA carrying fatty acids reduced the amount of fatty acid biosynthesis proteins
to the same extent as plasma. The results clarify the function of HSA-binding proteins in S. pyogenes and underline the power of the quantitative mass spectrometry strategy used here to investigate bacterial adaptation to a
given environment.
Journal of Biological Chemistry 01/2012; 287(2):1415-1425. · 4.77 Impact Factor
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ABSTRACT: Galectins, a family of small carbohydrate binding proteins, have been implicated in regulation of inflammatory reactions, including asthma and fibrosis in the lungs. Galectins are found in cells of the airways and in airway secretions, but their glycoprotein ligands there have only been studied to a very limited extent.
Bronchoalveolar lavage (BAL) fluid from mild asthmatics and healthy volunteers were fractionated by affinity chromatography on the immobilized galectins. Total (10-30μg) and galectin bound (~1-10μg) protein fractions were identified, quantified and compared using shot-gun proteomics and spectral counts.
About 175 proteins were identified in unfractionated BAL-fluid, and about 100 bound galectin-3 and 60 bound galectin-8. These included plasma glycoproteins, and typical airway proteins such as SP-A2, PIGR and SP-B. The concentration of galectin-binding proteins was 100-300 times higher than the concentration of galectins in BAL.
The low relative concentration of galectins in BAL makes it likely that functional interactions with glycoproteins occur at sites rich in galectin, such as cells of the airways, rather than the extracellular fluid itself. The profile of galectin bound proteins differed between samples from asthma patients and healthy subjects and correlated with the presence of fibroblasts or eosinophils. This included appearance of a specific galectin-8-binding glycoform of haptoglobin, previously shown to be increased in serum in other inflammatory conditions.
It is technically feasible to identify galectin-binding glycoproteins in low concentration patient samples such as BAL-fluid, to generate biomedically interesting results. This article is part of a Special Issue entitled Glycoproteomics.
Biochimica et Biophysica Acta 01/2012; 1820(9):1429-36. · 4.66 Impact Factor
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ABSTRACT: Streptococcus pyogenes is a major bacterial pathogen and a potent inducer of inflammation causing plasma leakage at the site of infection. A combination of label-free quantitative mass spectrometry-based proteomics strategies were used to measure how the intracellular proteome homeostasis of S. pyogenes is influenced by the presence of human plasma, identifying and quantifying 842 proteins. In plasma the bacterium modifies its production of 213 proteins, and the most pronounced change was the complete down-regulation of proteins required for fatty acid biosynthesis. Fatty acids are transported by albumin (HSA) in plasma. S. pyogenes expresses HSA-binding surface proteins, and HSA carrying fatty acids reduced the amount of fatty acid biosynthesis proteins to the same extent as plasma. The results clarify the function of HSA-binding proteins in S. pyogenes and underline the power of the quantitative mass spectrometry strategy used here to investigate bacterial adaptation to a given environment.
Journal of Biological Chemistry 11/2011; 287(2):1415-25. · 4.77 Impact Factor
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ABSTRACT: Severe infectious diseases remain a major and life-threatening health problem. In serious cases a systemic activation of the coagulation cascade and hypovolemic shock are critical complications that are associated with high mortality rates. Here we report that blood mononuclear cells, stimulated with M1 protein of Streptococcus pyogenes or other bacterial virulence factors, produce not only pro-coagulant, but also pro-inflammatory microparticles (MPs). Our results also show that activation of the contact system on MPs contributes to these two effects. Phosphatidylserine (PS) plays an important role in these processes as its upregulation on MPs allows an assembly and activation of the contact system. This in turn results in stabilization of the tissue factor-induced clot and a processing of high-molecular-weight kininogen by plasma kallikrein followed by the release of bradykinin, a potent vascular mediator. Pro-coagulant monocyte-derived MPs were identified in plasma samples from septic patients and further analysis of MPs from these patients revealed that their pro-coagulant activity is dependent on the tissue factor- and contact system-driven pathway.
Cellular Microbiology 09/2011; 14(1):107-19. · 5.46 Impact Factor
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ABSTRACT: Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC-MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
Molecular Systems Biology 07/2011; 7:510. · 8.63 Impact Factor
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ABSTRACT: The rapidly increasing ability to sequence complete genomes of different microbial species and strains provides us with information regarding their genetic variability. Genetic variability is a mechanism for human pathogens to adapt to and avoid the immune system and to also develop resistance to antibiotics. However, the assessment of the contributions of individual genetic differences to resistance or other phenotypes is not a priori apparent from the genomic variability. Quantitative proteomics can provide accurate molecular phenotypes of microbes that are difficult to determine using alternative technologies. Over the recent few years we and others have developed a range of proteomic technologies for the quantitative analysis of microbial proteomes. Here, we describe the most commonly used techniques and discuss their strengths and weaknesses and illustrate their respective performance for the identification of virulence factors in Streptococcus pyogenes.
Proteomics 06/2011; 11(15):2947-56. · 4.43 Impact Factor
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Terry Farrah,
Eric W Deutsch,
Gilbert S Omenn,
David S Campbell,
Zhi Sun,
Julie A Bletz,
Parag Mallick,
Jonathan E Katz, Johan Malmström,
Reto Ossola,
Julian D Watts,
Biaoyang Lin,
Hui Zhang,
Robert L Moritz,
Ruedi Aebersold
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ABSTRACT: Human blood plasma can be obtained relatively noninvasively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.
Molecular & Cellular Proteomics 06/2011; 10(9):M110.006353. · 7.40 Impact Factor
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ABSTRACT: Mass-spectrometry-based methods for relative proteome quantification have broadly affected life science research. However, important research directions, particularly those involving mathematical modelling and simulation of biological processes, also critically depend on absolutely quantitative data--that is, knowledge of the concentration of the expressed proteins as a function of cellular state. Until now, absolute protein concentration measurements of a considerable fraction of the proteome (73%) have only been derived from genetically altered Saccharomyces cerevisiae cells, a technique that is not directly portable from yeast to other species. Here we present a mass-spectrometry-based strategy to determine the absolute quantity, that is, the average number of protein copies per cell in a cell population, for a large fraction of the proteome in genetically unperturbed cells. Applying the technology to the human pathogen Leptospira interrogans, a spirochete responsible for leptospirosis, we generated an absolute protein abundance scale for 83% of the mass-spectrometry-detectable proteome, from cells at different states. Taking advantage of the unique cellular dimensions of L. interrogans, we used cryo-electron tomography morphological measurements to verify, at the single-cell level, the average absolute abundance values of selected proteins determined by mass spectrometry on a population of cells. Because the strategy is relatively fast and applicable to any cell type, we expect that it will become a cornerstone of quantitative biology and systems biology.
Nature 09/2009; 460(7256):762-5. · 36.28 Impact Factor
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ABSTRACT: Proteomics, the detailed understanding of the role that proteins play in health and disease, is a necessary complement to genetic analysis. Rapid progress within the proteomics field has opened up possibilities for direct intervention in the medical and clinical area where diseases, disease progression and cause of disease can be investigated at a molecular level. This review introduces the proteomics field, illustrating the link to disease and organ dysfunctions, and the problem-solving progress currently ongoing in other research areas. The proteomics research field is progressing through developments in novel technology that have recently driven the biological interpretation of proteomics studies forward. A personal overview is presented with examples from the areas of clinical proteomics, tissue imaging and profiling, as well as examples of targeted proteomics studies.
07/2009; 1(1):83-94.
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Sabine P Schrimpf,
Manuel Weiss,
Lukas Reiter,
Christian H Ahrens,
Marko Jovanovic, Johan Malmström,
Erich Brunner,
Sonali Mohanty,
Martin J Lercher,
Peter E Hunziker,
Ruedi Aebersold,
Christian von Mering,
Michael O Hengartner
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ABSTRACT: The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance.
PLoS Biology 04/2009; 7(3):e48. · 11.45 Impact Factor
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ABSTRACT: Blood plasma is the most complex human-derived proteome, containing other tissue proteomes as subsets. This proteome has only been partially characterized due to the extremely wide dynamic range of the plasma proteins of more than ten orders of magnitude. Thus, the reduction in sample complexity prior to mass spectrometric analysis is particularly important and alternative separation methodologies are required to more effectively mine the lower abundant plasma proteins. Here, we demonstrated a novel separation approach using 2-D free-flow electrophoresis (FFE) separating proteins and peptides in solution according to their pI prior to LC-MS/MS. We used the combination of sequential protein and peptide separation by first separating the plasma proteins into specific FFE fractions. Tryptic digests of the separated proteins were generated and subsequently separated using FFE. The protein separation medium was optimized to segregate albumin into specific fractions containing only few other proteins. An optimization of throughput for the protein separation reduced the separation time of 1 mL of plasma to approximately 3 h providing sufficient material for digestion and the subsequent peptide separation. Our approach revealed low-abundant proteins (e.g., L-selectin at 17 ng/mL and vascular endothelial-cadherin precursor at 30 ng/mL) and several tissue leakage products, thus providing a powerful orthogonal separation step in the proteomics workflow.
PROTEOMICS 01/2008; 7(23):4218-27. · 4.51 Impact Factor
