Quantitative proteomics

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and costeffective alternative to labelled quantitation.

Proteomics is the study of proteins on a large scale, encompassing the many interests scientists and physicians have in their expression and physical properties. Proteomics continues to be a rapidly expanding field, with a wealth of reports regularly appearing on technology enhancements and scientific studies using these new tools. This review focuses primarily on the quantitative aspect of protein expression and the associated computational machinery for making large-scale identifications of proteins and their posttranslational modifications. The primary emphasis is on the combination of liquid chromatography-mass spectrometry (LC-MS) methods and associated tandem mass spectrometry (LC-MS/MS). Tandem mass spectrometry, or MS/MS, involves a second analysis within the instrument after a molecular dissociative event in order to obtain structural information including but not limited to sequence information. This review further focuses primarily on the study of in vitro digested proteins known as bottom-up or shotgun proteomics. A brief discussion of recent instrumental improvements precedes a discussion on affinity enrichment and depletion of proteins, followed by a review of the major approaches (label-free and isotope-labeling) to making protein expression measurements quantitative, especially in the context of profiling large numbers of proteins. Then a discussion follows on the various computational techniques used to identify peptides and proteins from LC-MS/MS data. This review article then includes a short discussion of LC-MS approaches to three-dimensional structure determination and concludes with a section on statistics and data mining for proteomics, including comments on properly powering clinical studies and avoiding over-fitting with large data sets.

Gene expression analyses of stem cells (SCs) will help to uncover or further define signaling pathways and molecular mechanisms involved in the maintenance of self-renewal, pluripotency, and/or multipotency. In recent years, proteomic approaches have produced a wealth of data identifying proteins and mechanisms involved in SC proliferation and differentiation. Although many proteomics techniques have been developed and improved in peptide and protein separation, as well as mass spectrometry, several important issues, including sample heterogeneity, post-translational modifications, protein-protein interaction, and high-throughput quantification of hydrophobic and low-abundance proteins, still remain to be addressed and require further technical optimization. This review summarizes the methodologies used and the information gathered with proteome analyses of SCs, and it discusses biological and technical challenges for proteomic study of SCs.Disclosure of potential conflicts of interest is found at the end of this article.

Quantitative proteomics and absolute determination of proteins are topics of fast growing interest, since only the quantity of proteins or changes in their abundance reflect the status and extent of changes of a given biological system. Quantification of the desired proteins has been carried out by molecule specific MS techniques, but relative quantifications are commonplace so far even resorting to stable isotope labelling techniques such as ICAT and SILAC. In the last decade the idea of using element-selective mass spectrometric detection (e.g. ICP-MS instruments) to achieve absolute quantification has been realised and ICP-MS stands now as a new tool in the field of quantitative proteomics. In this review the emerging role of ICP-MS in protein and proteomic analysis is highlighted. The potential of ICP-MS methods and strategies for screening multiple heteroatoms (e.g. S, P, Se, metals) in proteins and their mixtures and extraordinary capabilities to tackle the problem of absolute protein quantifications, via heteroatom determinations, are discussed and illustrated. New avenues are also open derived from the use of ICP-MS for precise isotope abundance measurements in polyisotopic heteroatoms. The "heteroatom (isotope)tagged proteomics" concept is focused on the use of naturally present element tags and also extended to any protein by resorting to bioconjugation reactions (i.e. labelling sought proteins and peptides with ICP-MS detectable heteroatoms). A major point of this review is displaying the possibilities of using a "hard" ion source, the ICP, to complement wellestablished "soft" ion sources for mass spectrometry to tackle present proteomic analysis.

Virtually all mass spectrometric-based methods for quantitative proteomics are at the peptide level, whether label-mediated or label-free. Absolute quantification in particular is based on the measurement of limit peptides, defined as those peptides that cannot be further fragmented by the protease in use. Complete release of analyte and (stable isotope labelled) standard ensures that the most reliable quantification data are recovered, especially when the standard peptides are in a different primary sequence context, such as sometimes occurs in the QconCAT methodology. Moreover, in label-free methods, incomplete digestion would diminish the ion current attributable to limit peptides and lead to artifactually low quantification data. It follows that an essential requirement for peptide-based absolute quantification in proteomics is complete and consistent proteolysis to limit peptides. In this paper we describe strategies to assess completeness of proteolysis and discuss the potential for variance in digestion efficiency to compromise the ensuing quantification data. We examine the potential for kinetically favoured routes of proteolysis, particularly at the last stages of the digestion, to direct products into 'dead-end' mis-cleaved products.

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and costeffective alternative to labelled quantitation.

The receptor tyrosine kinase HER2 is an oncogene amplified in invasive breast cancer and its overexpression in mammary epithelial cell lines is a strong determinant of a tumorigenic phenotype. Accordingly, HER2-overexpressing mammary tumors are commonly indicative of a poor prognosis in patients. Several quantitative proteomic studies have employed two-dimensional gel electrophoresis in combination with MS/MS, which provides only limited information about the molecular mechanisms underlying HER2/neu signaling. In the present study, we used a SILAC-based approach to compare the proteomic profile of normal breast epithelial cells with that of Her2/neu-overexpressing mammary epithelial cells, isolated from primary mammary tumors arising in mouse mammary tumor virus-Her2/neu transgenic mice. We identified 23 proteins with relevant annotated functions in breast cancer, showing a substantial differential expression. This included overexpression of creatine kinase, retinol-binding protein 1, thymosin 4 and tumor protein D52, which correlated with the tumorigenic phenotype of Her2-overexpressing cells. The differential expression pattern of two genes, gelsolin and retinol binding protein 1, was further validated in normal and tumor tissues. Finally, an in silico analysis of published cancer microarray data sets revealed a 23-gene signature, which can be used to predict the probability of metastasis-free survival in breast cancer patients.

The mechanisms of carbon concentration in marine diatoms are controversial. At low CO 2 , decreases in O 2 evolution after inhibition of phosphoenolpyruvate carboxylases (PEPCs), and increases in PEPC transcript abundances, have been interpreted as evidence for a C 4 mechanism in Thalassiosira pseudonana, but the ascertainment of which proteins are responsible for the subsequent decarboxylation and PEP regeneration steps has been elusive.

The industrial production of cellulolytic enzymes is dominated by the filamentous fungus Trichoderma reesei (anamorph of Hypocrea jecorina). In order to develop optimal enzymatic cocktail, it is of importance to understand the natural regulation of the enzyme profile as response to the growth substrate. The influence of the complexity of cellulose on enzyme production by the microorganisms is not understood. In the present study we attempted to understand how different physical and structural properties of cellulose-rich substrates affected the levels and profiles of extracellular enzymes produced by T. reesei. Enzyme production by T. reesei Rut C-30 was studied in submerged cultures on five different cellulose-rich substrates, namely, commercial cellulose Avicel® and industrial-like cellulosic pulp substrates which consist mainly of cellulose, but also contain residual hemicellulose and lignin. In order to evaluate the hydrolysis of the substrates by the fungal enzymes, the spatial...

The accurate mass and time (AMT) tag strategy has been recognized as a powerful tool for high-throughput analysis in liquid chromatography-mass spectrometry (LC-MS)-based proteomics. Due to the complexity of the human proteome, this strategy requires highly accurate mass measurements for confident identifications. We have developed a method of building a reference map that allows relaxed criteria for mass errors yet delivers high confidence for peptide identifications. The samples used for generating the peptide database were produced by collecting cysteine-containing peptides from T47D cells and then fractionating the peptides using strong cationic exchange chromatography (SCX). LC-tandem mass spectrometry (MS/MS) data from the SCX fractions were combined to create a comprehensive reference map. After the reference map was built, it was possible to skip the SCX step in further proteomic analyses. We found that the reference-driven identification increases the overall throughput and proteomic coverage by identifying peptides with low intensity or complex interference. The use of the reference map also facilitates the quantitation process by allowing extraction of peptide intensities of interest and incorporating models of theoretical isotope distribution.

Chemoproteomics represents a new research discipline at the interface of medicinal chemistry, biochemistry, and cell biology focused on studying the molecular mechanisms of action of drugs and other bioactive small molecules. Research strategies frequently combine phenotypic screening with subsequent target identification, and aim at a proteome-wide characterization of drug-induced changes in cellular protein expression and post-translational modifications. In recent years quantitative mass spectrometry has taken center stage in many of these approaches. This review describes experimental strategies in current chemical proteomics research, discusses recent examples of successful applications, and highlights areas in drug discovery where chemical proteomics-based assays using native endogenous proteins are expected to have substantial impact.

How different integrins that bind to the same type of extracellular matrix protein mediate specific functions is unclear. We report the functional analysis of β 1 -and α v -class integrins expressed in pan-integrin-null fibroblasts seeded on fibronectin. Reconstitution with β 1 -class integrins promotes myosin-II-independent formation of small peripheral adhesions and cell protrusions, whereas expression of α v -class integrins induces the formation of large focal adhesions. Co-expression of both integrin classes leads to full myosin activation and traction-force development on stiff fibronectin-coated substrates, with α v -class integrins accumulating in adhesion areas exposed to high traction forces. Quantitative proteomics linked α v -class integrins to a GEF-H1-RhoA pathway coupled to the formin mDia1 but not myosin II, and α 5 β 1 integrins to a RhoA-Rock-myosin II pathway. Our study assigns specific functions to distinct fibronectin-binding integrins, demonstrating that α 5 β 1 integrins accomplish force generation, whereas α v -class integrins mediate the structural adaptations to forces, which cooperatively enable cells to sense the rigidity of fibronectin-based microenvironments.

The quantitative detection of allergens in the food chain is a strategic health objective as the prevalence of allergy continues to rise. Food allergenicity is caused by proteins either in their native form or in forms resulting from food processing. Progress in mass spectrometry greatly opened up the field of proteomics. These advances are now available for the detection and the quantification of traces of allergenic proteins in complex mixtures, and complete the set of biological tests used until now, such as ELISA or PCR. We review methods classified according to their ability to simultaneously quantify and identify allergenic proteins and underline major advances in the mass-spectrometric methods.

Gene expression analyses of stem cells (SCs) will help to uncover or further define signaling pathways and molecular mechanisms involved in the maintenance of self-renewal, pluripotency, and/or multipotency. In recent years, proteomic approaches have produced a wealth of data identifying proteins and mechanisms involved in SC proliferation and differentiation. Although many proteomics techniques have been developed and improved in peptide and protein separation, as well as mass spectrometry, several important issues, including sample heterogeneity, post-translational modifications, protein-protein interaction, and high-throughput quantification of hydrophobic and low-abundance proteins, still remain to be addressed and require further technical optimization. This review summarizes the methodologies used and the information gathered with proteome analyses of SCs, and it discusses biological and technical challenges for proteomic study of SCs.Disclosure of potential conflicts of interest is found at the end of this article.

Ticks are vectors of pathogens that affect human and animal health worldwide. Ticks and the pathogens they transmit have co-evolved molecular interactions involving genetic traits of both the tick and the pathogen that mediate their development and survival. Proteomics and genomics studies of infected ticks are required to understand tick-pathogen interactions and identify potential vaccine antigens to control tick infestations and pathogen transmission. In this paper, the application of quantitative proteomics to characterize differential protein expression in ticks and cultured tick cells in response to pathogen infection is reviewed. Analyses using (a) two-dimensional differential in gel electrophoresis (DIGE) labeling and (b) protein one-step in gel digestion, peptide iTRAQ labeling, and isoelectric focusing fractionation, both followed by peptide and protein identifications by mass spectrometry resulted in the identification of host, pathogen, and tick proteins differentially expressed in response to infection. Although at its infancy, these results showed that quantitative proteomics is a powerful approach to characterize the tick-pathogen interface and demonstrated pathogen and tick-specific differences in protein expression in ticks and cultured tick cells in response to pathogen infection.

Protein quantification based upon mass spectrometry is gaining ground in diverse applications of biological and clinical relevance. The present article focuses on one of the most complex biological fluids – serum – and provides a novel ICPL based quantification protocol. The results are compared to a label-free (data independent alternate scanning) absolute quantification method. The validation is performed using MRM based protein quantification technique. Regarding the ICPL approach, serum samples used in this study were depleted of high abundant proteins, labeled with ICPL and fractionated according to their respective pI (3–5, 5–7 and 7–12). The samples were further subjected to tryptic digestion followed by treatment with the Glu-C enzyme. The peptides were analyzed on a 2D-nano-LC system using four different concentrations of salt injections (45, 75, 150 and 500 mM ammonium acetate). The LC system was connected on-line with the electrospray ion-trap mass spectrometer. For the label-free quantification the serum samples were depleted and digested with trypsin. A proteome-wide comparison was performed using highly reproducible LC and data independent alternate scanning in conjunction with a high mass accuracy orthogonal time-of-flight mass spectrometer. Selected proteins, found by both methods, were validated using the MRM approach. For this purpose non-depleted tryptically digested serum samples were analyzed by LC coupled with a triple-quadrupole MS. The relative protein quantification using ICPL and mass spectrometry allowed for the detection of approximately 200 proteins, whereas about 2/3 of those contained the ICPL label and could therefore be quantified. Label-free approach used no fractionation, less sample and was able to identify and quantify over 110 proteins. The identified proteins covered generally 3–4 orders of magnitude of protein concentration in human serum. Changes in relative abundance of eight proteins were validated using MRM. This study, for the first time, shows the ability of the relative protein quantification based upon ICPL and 2D-LC–MS/MS to quantify serum biomarkers. It provides two additional label-free approaches that could validate and bring additional value to the label-based results, offering a starting point for comprehensive proteomics studies aiming at revealing biomarkers of clinical relevance.

Chronic respiratory infections caused by Burkholderia cenocepacia in patients with cystic fibrosis (CF) are characterized by low responsiveness to antibiotic therapy and, in general, to a more rapid decline of lung function. To get clues into the molecular mechanisms underlying the adaptive strategies employed to deal with the stressing conditions of the CF lung including antibiotic therapy, quantitative proteomics (2-D DIGE) was used to compare the expression programs of two clonal isolates retrieved from a chronically infected CF patient. Isolate IST439 was the first bacterium recovered while the clonal variant IST4113 was obtained after 3 years of persistent infection and intravenous therapy with ceftazidime/gentamicin. This isolate exhibits higher resistance levels towards different classes of antimicrobials. Proteins of the functional categories Energy metabolism, Translation, Nucleotide synthesis, Protein folding and stabilization are more abundant in IST4113, compared with IST439, suggesting an increased protein synthesis, DNA repair and stress resistance in IST4113. The level of proteins involved in peptidoglycan, membrane lipids and lipopolysaccharide synthesis is also altered and proteins involved in iron binding and transport are more abundant in IST4113. The quantitative comparison of the two proteomes suggests a genetic adaptation leading to increased antimicrobial resistance and bacterial persistence in the CF airways.

The quantitative detection of allergens in the food chain is a strategic health objective as the prevalence of allergy continues to rise. Food allergenicity is caused by proteins either in their native form or in forms resulting from food processing. Progress in mass spectrometry greatly opened up the field of proteomics. These advances are now available for the detection and the quantification of traces of allergenic proteins in complex mixtures, and complete the set of biological tests used until now, such as ELISA or PCR. We review methods classified according to their ability to simultaneously quantify and identify allergenic proteins and underline major advances in the mass-spectrometric methods.

Mammalian puberty requires activation of luteinizing hormone-releasing hormone (LHRH) neurons. In turn, these neurons are controlled by transsynaptic and glia-to-neuron communication pathways, which employ diverse cellular proteins for proper function. We have now used a high throughput relative quantitative proteomics technique to identify such proteins. We selected the method of two-dimensional liquid chromatography tandem mass spectrometry (2DLC-MS/MS) and cleavable isotope-coded affinity tags (cICAT), to both identify and quantify individual proteins within a complex protein mixture. The proteins used derived from the hypothalamus of juvenile (25-day-old) and peripubertal (first proestrus, LP) female rats, and their identity was established by analyzing their mass spectra via database searching. Five proteins involved in glutamate metabolism were detected and two of them appeared to be differentially expressed. They were selected for further analysis, because of their importance in controlling glutamate synthesis and degradation, and their preferential expression in astroglial cells. One, glutamate dehydrogenase (GDH) catalyzes glutamate synthesis; its hypothalamic content detected by 2DLC-MS/MS increases at first proestrus. The other, glutamine synthetase (GS), catalyzes the metabolism of glutamate to glutamine; its content decreases in proestrus. Western blot analysis verified these results. Because these changes suggested an increased glutamate production at puberty, we measured glutamate release from hypothalamic fragments from juvenile 29-day old rats, and from rats treated with PMSG to induce a premature proestrus surge of luteinizing hormone (LH). To determine the net output of glutamate in the absence of re-uptake we used the excitatory amino acid transporter (EAAT) inhibitor l-trans-pyrrolidine-2,4-dicarboxylic acid (PDC). PDC elicited significantly more glutamate-and LHRH-release from the proestrus hypothalamus. Thus, an increase excitatory drive to the LHRH neuronal network provided by glutamatergic inputs of glial origin, is an event contributing to the pubertal activation of LHRH secretion.

Described here is a stable isotope labeling protocol that can be used with a chemical modification- and mass spectrometry-based protein-ligand binding assay for detecting and quantifying both the direct and indirect binding events that result from protein-ligand binding interactions. The protocol utilizes an H{2/16}O2 and H{2/18}O2 labeling strategy to evaluate the chemical denaturant dependence of methionine oxidation in proteins both in the presence and absence of a target ligand. The differential denaturant dependence to the oxidation reactions performed in the presence and absence of ligand provides a measure of the protein stability changes that occur as a result of direct interactions of proteins with the target ligand and/or as a result of indirect interactions involving other protein-ligand interactions that are either induced or disrupted by the ligand. The described protocol utilizes the 18O/16O ratio in the oxidized protein samples to quantify the ligand-induced protein stability changes. The ratio is determined using the isotopic distributions observed for the methionine-containing peptides used for protein identification in the LC-MS-based proteomics readout. The strategy is applied to a multi-component protein mixture in this proof-of-principle experiment, which was designed to evaluate the technique's ability to detect and quantify the direct binding interaction between cyclosporin A and cyclophilin A and to detect the indirect binding interaction between cyclosporin A and calcineurin (i.e., the protein-protein interaction between cyclophilin A and calcineurin that is induced by cyclosporin A binding to cyclophilin A).

Quantitative proteomics using stable isotopic 16 O/ 18 O 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 16 O/ 18 O-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 mg 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 16 O/ 18 O labeling can be performed in the practice using linear IT MS, without compromising large-scale peptide identification efficiency.

Technological developments in the life sciences have resulted in an ever-accelerating pace of data production. Systems Biology tries to shed light upon these data by building complex models describing the interactions between biological components. However, extracting information from this morass of data requires the use of sophisticated computational techniques. Here, we propose a method suitable to integrate data drawn from quantitative proteomics into a metabolic scaffold and identify the metabolic pathways which are collectively up-regulated or downregulated. The availability of such a tool is highly desirable as the extracted information could then be taken as a starting point for in-depth analyses, in particular in fields like Synthetic Biology, where datasets need be characterized routinely.

a b s t r a c t G72/G30 is a primate-specific locus that has been repeatedly implicated as a risk factor in genetic studies of schizophrenia. The function of the longest G72 splice variant (LG72 protein) encoded by this locus is not fully understood. To investigate the role of the LG72 protein in vivo, we have generated transgenic (G72Tg) mice carrying the G72/G30 locus that exhibit schizophrenia-like symptoms. We investigated protein expression alterations in the cerebella of G72Tg compared to wild type (WT) mice using a proteomics approach based on in vivo 15 N metabolic labeling and quantitative mass spectrometry (MS). Our data revealed expression level differences of proteins involved in myelin-related processes, oxidative stress and mitochondrial function. Furthermore, in silico pathway analyses suggested common regulators and targets for the observed protein alterations. Our work sheds light on the functional role of the LG72 protein and pinpoints molecular correlates of schizophrenia-like behavior.

The sensitivity of proteomics measurements using liquid chromatography (LC) separations interfaced with electrospray ionization-mass spectrometry (ESI-MS) improves approximately inversely with liquid flow rate (for the columns having the same separation efficiency, linear velocity, and porosity), making attractive the use of smaller inner diameter LC columns. We report the development and initial application of 10 μm i.d. silica-based monolithic LC columns providing more sensitive proteomics measurements. A 50-μm-i.d. micro solid-phase extraction precolumn was used for ease of sample injection and cleanup prior to the reversed-phase LC separation, enabling the sample volume loading speed to be increased by ∼50-fold. Greater than 10-fold improvement in sensitivity was obtained compared to analyses using more conventional capillary LC, enabling e.g. the identification of >5000 different peptides by MS/MS from 100-ng of a Shewanella oneidensis tryptic digest using an ion trap MS. The low nL/min LC flow rates provide more uniform responses for different peptides, and provided improved quantitative measurements compared to conventional separation systems without the use of internal standards or isotopic labeling. The improved sensitivity allowed LC-MS measurements of immunopurified protein phosphatase 5 that were in good agreement with quantitative Western blot analyses.

The sensitivity of proteomics measurements using liquid chromatography (LC) separations interfaced with electrospray ionization-mass spectrometry (ESI-MS) improves approximately inversely with liquid flow rate (for the columns having the same separation efficiency, linear velocity, and porosity), making attractive the use of smaller inner diameter LC columns. We report the development and initial application of 10 μm i.d. silica-based monolithic LC columns providing more sensitive proteomics measurements. A 50-μm-i.d. micro solid-phase extraction precolumn was used for ease of sample injection and cleanup prior to the reversed-phase LC separation, enabling the sample volume loading speed to be increased by ∼50-fold. Greater than 10-fold improvement in sensitivity was obtained compared to analyses using more conventional capillary LC, enabling e.g. the identification of >5000 different peptides by MS/MS from 100-ng of a Shewanella oneidensis tryptic digest using an ion trap MS. The low nL/min LC flow rates provide more uniform responses for different peptides, and provided improved quantitative measurements compared to conventional separation systems without the use of internal standards or isotopic labeling. The improved sensitivity allowed LC-MS measurements of immunopurified protein phosphatase 5 that were in good agreement with quantitative Western blot analyses.

Familial hemiplegic migraine type 1 (FHM1) is caused by missense mutations in the CACNA1A gene that encodes the a1A pore-forming subunit of Ca V 2.1 Ca 21 channels. Knockin (KI) transgenic mice expressing Ca V 2.1 Ca 21 channels with a human pathogenic FHM1 mutation reveal enhanced glutamatergic neurotransmission in the cortex. In this study, we employed an iTRAQ-based LC-LC MS/MS approach to identify differentially expressed proteins in cortical synapse proteomes of Cacna1a R192Q KI and wild-type mice. All expression differences determined were subtle and in the range of 10-30%. Observed upregulated proteins in the mutant mice are involved in processes, such as neurite outgrowth and actin dynamics, vesicle turnover, and glutamate transporters. Our data support the view that in Cacna1a R192Q KI mice, several compensatory mechanisms counterbalancing a dysregulated glutamatergic signaling have come into effect. We propose that such adaptation mechanisms at the synapse level may play a role in the pathophysiology of FHM and possibly in the common forms of migraine.

Classically, experiments aimed at studying changes in protein expression have always followed a small set of proteins. This focused approach was necessary since tools to efficiently analyze large numbers of proteins were simply not available. Large-scale quantitative proteomics promises to produce reams of data that previously would have taken decades to measure with classical methods. Mass spectrometry is already a well-established protein identification tool and recent methodological developments indicate that it can also be successfully applied to extract quantitative data of protein abundance. From the first reports 4 years ago, numerous schemes to take advantage of stable isotope nuclei incorporation in proteins and peptides have been developed. Here we review the benefits and pitfalls of some of the most commonly used protocols, focusing on a procedure now being used extensively in our laboratory, stable isotope labeling with amino acids in cell culture (SILAC). The basic theory, application, and data analysis of a SILAC experiment are discussed. The emerging nature of these techniques and the rapid pace of technological development make forecasting the directions of the field difficult but we speculate that SILAC will soon be a key tool of quantitative proteomics.

Mycotoxins Quantitative proteomics a b s t r a c t aand b-zearalenol (a-ZOL and b-ZOL, respectively) are metabolites of the mycotoxin zearalenone (ZEN). All three individual mycotoxins have shown to be biological active i.e. being estrogenic and able to stimulate cellular proliferation albeit at different strengths. In this work, cytosol protein expression was determined by using stable-isotope labelling by amino acids in cell culture (SILAC) upon exposure of a-ZOL and b-ZOL to the steroidogenesis cell model H295R. A total of 14 and 5 individual proteins were found to be significantly regulated by a-ZOL and b-ZOL, respectively. Interestingly, there were no common protein regulations by the metabolites or the parent mycotoxin ZEN. Furthermore, the regulated proteins were assigned to networks and groups of actions that also differed from one another suggesting that the three individual mycotoxins may have unique biological activities.

MMSET, identified by its fusion to the IgH locus in t(4;14) MM, is universally overexpressed in t(4;14) MM. In order to identify cell surface biomarkers associated with t(4;14) MM for small molecule or antibody based therapies, we knocked down MMSET expression with shRNA and generated a cell line pair from KMS11, a t(4;14)

The adrenal glands (AGs) are endocrine organs essential for life. They undergo a fetal to adult developmental maturation process, occurring in rats during the first postnatal month. The molecular modifications underlying these ontogenic changes are essentially unknown. Here we report the results of a comparative proteomic analysis performed on neonatal (Postnatal day 3) versus adult (Postnatal day 30) AGs, searching for proteins with a relative higher abundance at each age. We have identified a subset of proteins with relevant expression in each developmental period using 2-DE and DIGE analysis. The identified proteins belong to several functional categories, including proliferation/differentiation, cell metabolism, and steroid biosynthesis. To study if the changes in the proteome are correlated with changes at the mRNA level, we have randomly selected several proteins with differential expression and measured their relative mRNA levels using quantitative RT-PCR. Cell-cycle regulating proteins (retinoblastoma binding protein 9 and prohibitin) with contrasting effects on proliferation are expressed differentially in neonatal and adult AG. Progesterone metabolizing enzymes, up-regulated in the neonatal gland, might contribute to the hyporesponsiveness of the adrenal cortex characteristic of this developmental period. We have also observed in the adult gland a marked up-regulation of enzymes involved in NAD(P)H production, thus providing the reducing power necessary for steroid hormone biosynthesis.

Circadian rhythms are self-sustained and adjustable cycles, typically entrained with light/dark and/or temperature cycles. These rhythms are present in animals, plants, fungi, and several bacteria. The central mechanism behind these "pacemakers" and the connection to the circadian regulated pathways are still poorly understood. The circadian rhythm of the cyanobacterium Synechococcus elongatus PCC 7942 (S. elongatus) is highly robust and controlled by only three proteins, KaiA, KaiB, and KaiC. This central clock system has been extensively studied functionally and structurally and can be reconstituted in vitro. These characteristics, together with a relatively small genome (2.7 Mbp), make S. elongatus an ideal model system for the study of circadian rhythms. Different approaches have been used to reveal the influence of the central S. elongatus clock on rhythmic gene expression, rhythmic mRNA abundance, rhythmic DNA topology changes, and cell division. However, a global analysis of its proteome dynamics has not been reported yet.

Meningococcal disease is a major cause of morbidity and mortality worldwide. Its epidemiology is currently dominated by five capsular serogroups (A, B, C, W, and Y). While effective vaccines already exist for serogroups A, C, W and Y, except for under clonal outbreaks, no vaccine was available against serogroup B. Recently, a four component vaccine, Bexsero(®), designed to prevent infection caused by this serogroup, has been approved in Europe and other Countries for use in individuals from two months of age and older. The active components of this vaccine are three recombinant proteins identified by reverse vaccinology combined with detergent extracted outer membrane vesicles (DOMV) prepared from a New Zealand epidemic strain. Considering their intrinsic complexity, we performed additional characterization of DOMVs on top of the standard quality control testing carried out for batch release. We applied the Hi3 label-free LC-MS(E) methodology to qualitatively and quantitatively char...

To examine whether differentially expressed proteins are present in the serum of patients with obstructive sleep apnoea (OSA), iTRAQ techniques (isobaric tags for relative and absolute quantification) were employed in a prospective study. Individuals were assigned to either a non-OSA control group (apnoea-hypopnoea index, AHI <5) or an OSA group (AHI ‡5). Blood samples were collected, aliquoted and frozen at )80°C. Protein digestion and tagging with iTRAQ4plex â and mass spectrometry analysis was then performed (MALDI TOF ⁄ TOF). Ten male subjects were included in the control group (age = 45 ± 9.7 years) and 30 male patients in the OSA group (age = 45 ± 10.7 years), the latter being then subdivided into three severity groups. A total of 103 proteins were identified with differential levels between patients with OSA and controls. Of these, 11 proteins were underexpressed and 19 were overexpressed in patients with OSA. C4BPA and thrombospondin were underexpressed in all three OSA severity groups. Among the overexpressed proteins, 13 were overexpressed in the mild OSA group, seven in the moderate group and five in the severe group. Analysis of interactions between the identified proteins revealed that protein alterations in OSA are primarily associated with derangements in lipid and vascular metabolic pathways. This study provides initial evidence that differential protein expression occurs in adults with OSA, and that such proteins change according to disease severity, and appear to primarily involve lipid and vascular metabolic pathways.

Circadian rhythms are self-sustained and adjustable cycles, typically entrained with light/dark and/or temperature cycles. These rhythms are present in animals, plants, fungi, and several bacteria. The central mechanism behind these "pacemakers" and the connection to the circadian regulated pathways are still poorly understood. The circadian rhythm of the cyanobacterium Synechococcus elongatus PCC 7942 (S. elongatus) is highly robust and controlled by only three proteins, KaiA, KaiB, and KaiC. This central clock system has been extensively studied functionally and structurally and can be reconstituted in vitro. These characteristics, together with a relatively small genome (2.7 Mbp), make S. elongatus an ideal model system for the study of circadian rhythms. Different approaches have been used to reveal the influence of the central S. elongatus clock on rhythmic gene expression, rhythmic mRNA abundance, rhythmic DNA topology changes, and cell division. However, a global analysis of its proteome dynamics has not been reported yet.

Recent improvements in proteomic technologies have collectively yielded data sets that far exceed the capabilities of typical low-throughput interpretation strategies. Unfortunately, tools designed to leverage the “peptide-centric” content of MS-based proteomics lag the current rate of data production. Here, we describe Pathway Palette (http://blaispathways.dfci.harvard.edu), a freely accessible internet application that enables researchers to easily transition from peptides to biological pathways, while simultaneously retaining the qualitative and quantitative aspects of the underlying MS data.

Recent improvements in proteomic technologies have collectively yielded data sets that far exceed the capabilities of typical low-throughput interpretation strategies. Unfortunately, tools designed to leverage the “peptide-centric” content of MS-based proteomics lag the current rate of data production. Here, we describe Pathway Palette (http://blaispathways.dfci.harvard.edu), a freely accessible internet application that enables researchers to easily transition from peptides to biological pathways, while simultaneously retaining the qualitative and quantitative aspects of the underlying MS data.

The primary goal of proteomics is to gain a better understanding of biological function at the protein expression level. As the field matures, numerous technologies are being developed to aid in the identification, quantification and characterization of protein expression and post-translational modifications on a near-global scale. Stable isotope labeling by amino acids in cell culture is one such technique that has shown broad biological applications. While we have recently shown the application of this technology to a model of metastatic prostate cancer, we now report a substantial improvement in quantitative analysis using a linear ion-trap Fourier transform ion cyclotron resonance mass spectrometer (LTQ FT) and novel quantification software. This resulted in the quantification of nearly 1400 proteins, a greater than 3-fold increase in comparison to our earlier study. This dramatic increase in proteome coverage can be attributed to (1) use of a double-labeling strategy, (2) greater sensitivity, speed and mass accuracy provided by the LTQ FT mass spectrometer, and (3) more robust quantification software. Finally, by using a concatenated target/decoy protein database for our peptide searches, we now report these data in the context of an estimated false-positive rate of one percent.

The field of proteomics has been developing rapidly toward quantification of proteins. Despite the variety of experimental techniques available for peptide and protein labelling, there are few commercially available analytical tools with the ability to interpret data from any mass spectrometer. In this study, we compare two software packages, Mascot and Peaks, for the analysis of iTRAQ data from ESI-Q/TOF mass spectrometry. In the case of a six-protein mixture combined in a known proportion, the output of the Peaks algorithm deviated from the correct result by 14% on average, while the error of the Mascot quantification was nearly 200%. When the software were used to analyse iTRAQ data from a complex protein sample, the quantification results agreed within 20% for only 26% of the quantified proteins, showing significant differences in the two quantification algorithms. This comparison and analysis revealed major intricacies in peptide and protein quantification that must be taken into consideration for software development.