Showing papers in "Journal of Proteome Research in 2009"
TL;DR: This report presents the consensus on SOPs for the collection, processing, handling, and storage of serum and plasma for biomarker discovery and validation in clinical research.
Abstract: Specimen collection is an integral component of clinical research. Specimens from subjects with various stages of cancers or other conditions, as well as those without disease, are critical tools in the hunt for biomarkers, predictors, or tests that will detect serious diseases earlier or more readily than currently possible. Analytic methodologies evolve quickly. Access to high-quality specimens, collected and handled in standardized ways that minimize potential bias or confounding factors, is key to the "bench to bedside" aim of translational research. It is essential that standard operating procedures, "the how" of creating the repositories, be defined prospectively when designing clinical trials. Small differences in the processing or handling of a specimen can have dramatic effects in analytical reliability and reproducibility, especially when multiplex methods are used. A representative working group, Standard Operating Procedures Internal Working Group (SOPIWG), comprised of members from across Early Detection Research Network (EDRN) was formed to develop standard operating procedures (SOPs) for various types of specimens collected and managed for our biomarker discovery and validation work. This report presents our consensus on SOPs for the collection, processing, handling, and storage of serum and plasma for biomarker discovery and validation.
611 citations
TL;DR: The combined method provides a streamlined protocol for rapid and sensitive membrane proteome mapping and provides a generic protocol for combining FASP with StageTip-based ion exchange fractionation, which is generally applicable to proteome analysis.
Abstract: Membrane proteomics is challenging because the desirable strong detergents are incompatible with downstream analysis. Recently, we demonstrated efficient removal of SDS by the filter aided sample preparation method (FASP). Here we combine FASP with our previously described small-scale membrane enrichment protocol. Analysis of a single mouse hippocampus enables identification of more than 1000 membrane proteins in a single LC-MS/MS run without protein or peptide prefractionation. To extend proteome coverage, we developed a simple anion exchange fractionation method in a StageTip format. When separating peptides into six fractions, a duplicate analysis resulted in identification of 4206 proteins of which 64% were membrane proteins. This data set covers 83% of glutamate and GABA receptor subunits identified in hippocampus in the Allen Brain Atlas and adds further isoforms. The combined method provides a streamlined protocol for rapid and sensitive membrane proteome mapping. We also provide a generic protocol...
523 citations
TL;DR: The data suggest greater dynamic crosstalk between interfering factors affecting underestimations, and that these interferences were largely scenario-specific, dependent on sample complexity.
Abstract: The increasing popularity of iTRAQ for quantitative proteomics applications makes it necessary to evaluate its relevance, accuracy, and precision for biological interpretation. Here, we have assess...
510 citations
TL;DR: In this paper, the authors applied both high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) and gas chromatography mass spectrometry (GC/MS) to analyze metabolites in biopsied colorectal tumors and their matched normal mucosae obtained from 31 CRC patients.
Abstract: Current clinical strategy for staging and prognostication of colorectal cancer (CRC) relies mainly upon the TNM or Duke system. This clinicopathological stage is a crude prognostic guide because it reflects in part the delay in diagnosis in the case of an advanced cancer and gives little insight into the biological characteristics of the tumor. We hypothesized that global metabolic profiling (metabonomics/metabolomics) of colon mucosae would define metabolic signatures that not only discriminate malignant from normal mucosae, but also could distinguish the anatomical and clinicopathological characteristics of CRC. We applied both high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) and gas chromatography mass spectrometry (GC/MS) to analyze metabolites in biopsied colorectal tumors and their matched normal mucosae obtained from 31 CRC patients. Orthogonal partial least-squares discriminant analysis (OPLS-DA) models generated from metabolic profiles obtained by both analytical approaches could robustly discriminate normal from malignant samples (Q(2) > 0.50, Receiver Operator Characteristic (ROC) AUC >0.95, using 7-fold cross validation). A total of 31 marker metabolites were identified using the two analytical platforms. The majority of these metabolites were associated with expected metabolic perturbations in CRC including elevated tissue hypoxia, glycolysis, nucleotide biosynthesis, lipid metabolism, inflammation and steroid metabolism. OPLS-DA models showed that the metabolite profiles obtained via HR-MAS NMR could further differentiate colon from rectal cancers (Q(2)> 0.60, ROC AUC = 1.00, using 7-fold cross validation). These data suggest that metabolic profiling of CRC mucosae could provide new phenotypic biomarkers for CRC management.
424 citations
TL;DR: A software package that interfaces Mascot with Percolator, a well performing machine learning method for rescoring database search results, is presented and it is demonstrated to be amenable for both low and high accuracy mass spectrometry data.
Abstract: Sound scoring methods for sequence database search algorithms such as Mascot and Sequest are essential for sensitive and accurate peptide and protein identifications from proteomic tandem mass spectrometry data. In this paper, we present a software package that interfaces Mascot with Percolator, a well performing machine learning method for rescoring database search results, and demonstrate it to be amenable for both low and high accuracy mass spectrometry data, outperforming all available Mascot scoring schemes as well as providing reliable significance measures. Mascot Percolator can be readily used as a stand alone tool or integrated into existing data analysis pipelines.
381 citations
TL;DR: This study clearly demonstrated that the coverage of N-glycosites could be significantly increased due to the adoption of multiple enzyme digestion, and led to the establishment of the largest data set of glycoproteome from human liver up to now.
Abstract: The study of protein glycosylation has lagged far behind the progress of current proteomics because of the enormous complexity, wide dynamic range distribution and low stoichiometric modification of glycoprotein. Solid phase extraction of tryptic N-glycopeptides by hydrazide chemistry is becoming a popular protocol for the analysis of N-glycoproteome. However, in silico digestion of proteins in human proteome database by trypsin indicates that a significant percentage of tryptic N-glycopeptides is not in the preferred detection mass range of shotgun proteomics approach, that is, from 800 to 3500 Da. And the quite big size of glycan groups may block trypsin to access the K, R residues near N-glycosites for digestion, which will result in generation of big glycopeptides. Thus many N-glycosites could not be localized if only trypsin was used to digest proteins. Herein, we describe a comprehensive way to analyze the N-glycoproteome of human liver tissue by combination of hydrazide chemistry method and multiple enzyme digestion. The lysate of human liver tissue was digested with three proteases, that is, trypsin, pepsin and thermolysin, with different specificities, separately. Use of trypsin alone resulted in identification of 622 N-glycosites, while using pepsin and thermolysin resulted in identification of 317 additional N-glycosites. Among the 317 additional N-glycosites, 98 (30.9%) could not be identified by trypsin in theory because the corresponding in silico tryptic peptides are either too small or too big to detect in mass spectrometer. This study clearly demonstrated that the coverage of N-glycosites could be significantly increased due to the adoption of multiple enzyme digestion. A total number of 939 N-glycosites were identified confidently, covering 523 noredundant glycoproteins from human liver tissue, which leads to the establishment of the largest data set of glycoproteome from human liver up to now.
378 citations
TL;DR: This report reviews recently developed platform technologies for emerging applications of clinical proteomics and biomarker development and highlights the capability of using a "universal" approach to perform quantitative assays for a wide spectrum of proteins with minimum restrictions.
Abstract: The recent advance in technology for mass spectrometry-based targeted protein quantification has opened new avenues for a broad range of proteomic applications in clinical research. The major breakthroughs are highlighted by the capability of using a “universal” approach to perform quantitative assays for a wide spectrum of proteins with minimum restrictions and the ease of assembling multiplex detections in a single measurement. The quantitative approach relies on the use of synthetic stable isotope labeled peptides or proteins, which precisely mimic their endogenous counterparts and act as internal standards to quantify the corresponding candidate proteins. This report reviews recently developed platform technologies for emerging applications of clinical proteomics and biomarker development.
377 citations
TL;DR: In this article, the authors performed a serum metabolic analysis to test the hypothesis that the distinct metabolite profiles of malignant tumors are reflected in biofluids, and identified 33 metabolites from 64 colorectal cancer (CRC) patients and 65 healthy controls using gas chromatography time-of-flight mass spectrometry (GC−TOFMS) and Acquity ultraperformance liquid chromatography quadrupole time of flight mass analyzer (Acquity UPLC−QTOFMs).
Abstract: Colorectal carcinogenesis involves the overexpression of many immediate-early response genes associated with growth and inflammation, which significantly alters downstream protein synthesis and small-molecule metabolite production. We have performed a serum metabolic analysis to test the hypothesis that the distinct metabolite profiles of malignant tumors are reflected in biofluids. In this study, we have analyzed the serum metabolites from 64 colorectal cancer (CRC) patients and 65 healthy controls using gas chromatography time-of-flight mass spectrometry (GC−TOFMS) and Acquity ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (Acquity UPLC−QTOFMS). Orthogonal partial least-squares discriminate analysis (OPLS-DA) models generated from GC−TOFMS and UPLC−QTOFMS metabolic profile data showed robust discrimination from CRC patients and healthy controls. A total of 33 differential metabolites were identified using these two analytical platforms, five of which were detected in ...
361 citations
TL;DR: The main nitration reactions and elucidate why nitration is not a random chemical process are reviewed and the possibility of an in vivo denitration process is indicated.
Abstract: Protein tyrosine nitration (PTN) is a post-translational modification occurring under the action of a nitrating agent. Tyrosine is modified in the 3-position of the phenolic ring through the addition of a nitro group (NO2). In the present article, we review the main nitration reactions and elucidate why nitration is not a random chemical process. The particular physical and chemical properties of 3-nitrotyrosine (e.g., pKa, spectrophotometric properties, reduction to aminotyrosine) will be discussed, and the biological consequences of PTN (e.g., modification of enzymatic activity, sensitivity to proteolytic degradation, impact on protein phosphorylation, immunogenicity and implication in disease) will be reviewed. Recent data indicate the possibility of an in vivo denitration process, which will be discussed with respect to the different reaction mechanisms that have been proposed. The second part of this review article focuses on analytical methods to determine this post-translational modification in com...
356 citations
TL;DR: The new version of IDPicker is more robust against false positive proteins, especially in searches using multispecies databases, by requiring additional novel peptides in the parsimony process.
Abstract: Tandem mass spectrometry-based shotgun proteomics has become a widespread technology for analyzing complex protein mixtures A number of database searching algorithms have been developed to assign peptide sequences to tandem mass spectra Assembling the peptide identifications to proteins, however, is a challenging issue because many peptides are shared among multiple proteins IDPicker is an open-source protein assembly tool that derives a minimum protein list from peptide identifications filtered to a specified False Discovery Rate Here, we update IDPicker to increase confident peptide identifications by combining multiple scores produced by database search tools By segregating peptide identifications for thresholding using both the precursor charge state and the number of tryptic termini, IDPicker retrieves more peptides for protein assembly The new version is more robust against false positive proteins, especially in searches using multispecies databases, by requiring additional novel peptides in t
336 citations
TL;DR: It is proposed that proteomics approaches, particularly bottom-up proteomics, will play a significant role in analyses of clinical samples leading to the identification of new markers of disease development and progression.
Abstract: The Maillard reaction, starting from the glycation of protein and progressing to the formation of advanced glycation end-products (AGEs), is implicated in the development of complications of diabetes mellitus, as well as in the pathogenesis of cardiovascular, renal, and neurodegenerative diseases. In this perspective review, we provide an overview on the relevance of the Maillard reaction in the pathogenesis of chronic disease and discuss traditional approaches and recent developments in the analysis of glycated proteins by mass spectrometry. We propose that proteomics approaches, particularly bottom-up proteomics, will play a significant role in analyses of clinical samples leading to the identification of new markers of disease development and progression.
TL;DR: This work has analyzed time-dependent changes in the incorporation of a stable amino acid resolved precursor using a protocol referred to as "dynamic SILAC", using 1-D gel separation followed by in-gel digestion and LC-MS/MS analyses to profile the intracellular stability of almost 600 proteins from human A549 adenocarcinoma cells.
Abstract: The proteome of any system is a dynamic entity, such that the intracellular concentration of a protein is dictated by the relative rates of synthesis and degradation. In this work, we have analyzed...
TL;DR: The present study used a mass spectrometry-based, shotgun proteomics approach to explore the possibility that a subset of the proteins found in saliva are derived from exosomes, membrane-bound vesicles of endosomal origin within multivesicular endosomes.
Abstract: Human ductal saliva contributes over a thousand unique proteins to whole oral fluids. The mechanism by which most of these proteins are secreted by salivary glands remains to be determined. The present study used a mass spectrometry-based, shotgun proteomics approach to explore the possibility that a subset of the proteins found in saliva are derived from exosomes, membrane-bound vesicles of endosomal origin within multivesicular endosomes. Using MudPIT (multidimensional protein identification technology) mass spectrometry, we catalogued 491 proteins in the exosome fraction of human parotid saliva. Many of these proteins were previously observed in ductal saliva from parotid glands (265 proteins). Furthermore, 72 of the proteins in parotid exosomes overlap with those previously identified as urinary exosome proteins, proteins which are also frequently associated with exosomes from other tissues and cell types. Gene Ontology (GO) and KEGG pathway analyses found that cytosolic proteins comprise the largest ...
TL;DR: The proteome of the recently discovered bacterium Methylocella silvestris has been characterized using three profiling and comparative proteomics approaches and results obtained have been compared with respect to number of proteins identified, confidence in identification, sequence coverage and agreement of regulated proteins.
Abstract: The proteome of the recently discovered bacterium Methylocella silvestris has been characterized using three profiling and comparative proteomics approaches. The organism has been grown on two different substrates enabling variations in protein expression to be identified. The results obtained using the experimental approaches have been compared with respect to number of proteins identified, confidence in identification, sequence coverage and agreement of regulated proteins. The sample preparation, instrumental time and sample loading requirements of the differing experiments are compared and discussed. A preliminary screen of the protein regulation results for biological significance has also been performed.
TL;DR: This comprehensive proteomic analysis of the human salivary proteome in type-2 diabetes provides the first global view of potential mechanisms perturbed in diabetic saliva and their utility in detection and monitoring of diabetes.
Abstract: The identification of biomarkers to noninvasively detect prediabetes/diabetes will facilitate interventions designed to prevent or delay progression to frank diabetes and its attendant complications. The purpose of this study was to characterize the human salivary proteome in type-2 diabetes to identify potential biomarkers of diabetes. Whole saliva from control and type-2 diabetic individuals was characterized by multidimensional liquid chromatography/tandem mass spectrometry (2D-LC-MS/MS). Label-free quantification was used to identify differentially abundant protein biomarkers. Selected potential biomarkers were then independently validated in saliva from control, diabetic, and prediabetic subjects by Western immunoblotting and ELISA. Characterization of the salivary proteome identified a total of 487 unique proteins. Approximately 33% of these have not been previously reported in human saliva. Of these, 65 demonstrated a greater than 2-fold difference in abundance between control and type-2 diabetes samples. A majority of the differentially abundant proteins belong to pathways regulating metabolism and immune response. Independent validation of a subset of potential biomarkers utilizing immunodetection confirmed their differential expression in type-2 diabetes, and analysis of prediabetic samples demonstrated a trend of relative increase in their abundance with progression from the prediabetic to the diabetic state. This comprehensive proteomic analysis of the human salivary proteome in type-2 diabetes provides the first global view of potential mechanisms perturbed in diabetic saliva and their utility in detection and monitoring of diabetes. Further characterization of these markers in a larger cohort of subjects may provide the basis for new, noninvasive tests for diabetes screening, detection, and monitoring.
TL;DR: Between and within batch calibration techniques are applied and the analytical error is reduced significantly (increase of 25% of peaks with RSD lower than 20%) and does not hamper or interfere with statistical analysis of the final data.
Abstract: Analytical errors caused by suboptimal performance of the chosen platform for a number of metabolites and instrumental drift are a major issue in large-scale metabolomics studies. Especially for MS-based methods, which are gaining common ground within metabolomics, it is difficult to control the analytical data quality without the availability of suitable labeled internal standards and calibration standards even within one laboratory. In this paper, we suggest a workflow for significant reduction of the analytical error using pooled calibration samples and multiple internal standard strategy. Between and within batch calibration techniques are applied and the analytical error is reduced significantly (increase of 25% of peaks with RSD lower than 20%) and does not hamper or interfere with statistical analysis of the final data.
TL;DR: Improvements to Percolator are described, including a method, Q-ranker, for directly optimizing the number of identified spectra at a specified q value, which achieves further gains.
Abstract: Shotgun proteomics coupled with database search software allows the identification of a large number of peptides in a single experiment. However, some existing search algorithms, such as SEQUEST, use score functions that are designed primarily to identify the best peptide for a given spectrum. Consequently, when comparing identifications across spectra, the SEQUEST score function Xcorr fails to discriminate accurately between correct and incorrect peptide identifications. Several machine learning methods have been proposed to address the resulting classification task of distinguishing between correct and incorrect peptide-spectrum matches (PSMs). A recent example is Percolator, which uses semisupervised learning and a decoy database search strategy to learn to distinguish between correct and incorrect PSMs identified by a database search algorithm. The current work describes three improvements to Percolator. (1) Percolator's heuristic optimization is replaced with a clear objective function, with intuitive reasons behind its choice. (2) Tractable nonlinear models are used instead of linear models, leading to improved accuracy over the original Percolator. (3) A method, Q-ranker, for directly optimizing the number of identified spectra at a specified q value is proposed, which achieves further gains.
TL;DR: This study demonstrated that iTRAQ technology combined with 2D-nanoLC- nanoESI-MS/MS quantitative proteomics is a powerful tool for biomarker discovery.
Abstract: The proteins found in tears have an important role in the maintenance of the ocular surface and changes in the quality and quantity of tear components reflect changes in the health of the ocular surface. In this study, we have used quantitative proteomics, iTRAQ technology coupled with 2D-nanoLC-nano-ESI-MS/MS and with a statistical model to uncover proteins that are significantly and reliably changed in the tears of dry eye patients in an effort to reveal potential biomarker candidates. Fifty-six patients with dry eye and 40 healthy subjects were recruited for this study. In total, 93 tear proteins were identified with a ProtScore >or=2 (>or=99% confidence). Associated with dry eye were 6 up-regulated proteins, alpha-enolase, alpha-1-acid glycoprotein 1, S100 A8 (calgranulin A), S100 A9 (calgranulin B), S100 A4 and S100 A11 (calgizzarin) and 4 down-regulated proteins, prolactin-inducible protein (PIP), lipocalin-1, lactoferrin and lysozyme. Receiver operating curves (ROC) were evaluated for individual biomarker candidates and a biomarker panel. With the use of a 4-protein biomarker panel, the diagnostic accuracy for dry eye was 96% (sensitivity, 91.0%; specificity, 90.0%). Two biomarker candidates (alpha-enolase and S100 A4) generated from iTRAQ experiments were successfully verified using an ELISA assay. The levels of these 10 tear proteins reflect aqueous secretion deficiency by lacrimal gland, inflammatory status of the ocular surface. The clinical classification of the severity of the dry eye condition was successfully correlated to the proteomics by using three proteins that are associated with inflammation, alpha1-acid glycoprotein 1, S100 A8 and S100 A9. The nine tear protein biomarker candidates (except alpha1-acid glycoprotein 1) were also verified using an independent age-matched patient sample set. This study demonstrated that iTRAQ technology combined with 2D-nanoLC-nanoESI-MS/MS quantitative proteomics is a powerful tool for biomarker discovery.
TL;DR: Data suggest a conditional host genetic involvement in selection of the microbial species in each host strain, and that both lean and obese animals could have specific metabolic phenotypes that are linked to their individual microbiomes.
Abstract: Covariation in the structural composition of the gut microbiome and the spectroscopically derived metabolic phenotype (metabotype) of a rodent model for obesity were investigated using a range of multivariate statistical tools. Urine and plasma samples from three strains of 10-week-old male Zucker rats (obese (fa/fa, n = 8), lean (fa/−, n = 8) and lean (−/−, n = 8)) were characterized via high-resolution 1H NMR spectroscopy, and in parallel, the fecal microbial composition was investigated using fluorescence in situ hydridization (FISH) and denaturing gradient gel electrophoresis (DGGE) methods. All three Zucker strains had different relative abundances of the dominant members of their intestinal microbiota (FISH), with the novel observation of a Halomonas and a Sphingomonas species being present in the (fa/fa) obese strain on the basis of DGGE data. The two functionally and phenotypically normal Zucker strains (fa/− and −/−) were readily distinguished from the (fa/fa) obese rats on the basis of their met...
TL;DR: The fundamental principles of statistical experimental design are reviewed, and their application to quantitative mass spectrometry-based proteomics is discussed, and how randomization, replication and blocking help avoid systematic biases due to the experimental procedure are discussed.
Abstract: We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.
TL;DR: This work compares signal intensity calibration methods based on either urinary creatinine or stable isotope labeled synthetic marker analogues (absolute quantification) with those based on ion counting using highly abundant collagen fragments as nonmarker references (relative quantification), and indicates that relative quantification of biomarker excretionbased on ion counts in reference to endogenous "housekeeping" peptides is sufficient for the determination of urinary polypeptide levels.
Abstract: A limitation of proteomic methods with respect to their clinical applicability is the lack of possibilities to directly deduce the amount of a protein or peptide from a particular mass spectrometry (MS) spectrum. For quantification of chronic kidney disease (CKD)-specific urinary polypeptides in capillary electrophoresis coupled with mass spectrometry (CE-MS), we compared signal intensity calibration methods based on either urinary creatinine or stable isotope labeled synthetic marker analogues (absolute quantification) with those based on ion counting using highly abundant collagen fragments as nonmarker references (relative quantification). Our results indicate that relative quantification of biomarker excretion based on ion counts in reference to endogenous “housekeeping” peptides is sufficient for the determination of urinary polypeptide levels. The calculation of absolute concentrations via exogenous stable isotope-labeled peptide standards is of no additional benefit.
TL;DR: The protein composition of these two mucus layers from the mouse colon is analyzed and the Fcgbp protein is probably cleaved at GD/PH and covalently attached to Muc2 via one or several of its von Willebrand D domains.
Abstract: The colon epithelium is protected from the luminal microbes as recently revealed by an inner firmly attached mucus layer impervious to bacteria and an outer loose mucus layer that is the habitat of bacteria. For an additional understanding of these layers, we analyzed the protein composition of these two mucus layers from the mouse colon. Proteomics using nano-LC−MS and MS/MS revealed more than 1000 protein entries. As the mucus layers contain detached cells, a majority of the proteins had an intracellular origin. However, at least 44 entries were described as secreted proteins and predicted to be mucus constituents together with extracellular/plasma and bacterial proteins, the latter largely in the loose mucus layer. A major protein was the Muc2 mucin that by its net-like disulfide-bonded polymer structure builds the mucus. When guanidinium chloride insoluble Muc2 units were analyzed, N-terminal parts of the Fc-gamma binding protein (Fcgbp) was found to be covalently attached in mouse and human colon, wh...
TL;DR: In this paper, a high level of variability was observed with the median ratio of minimal to maximal values of 6.17 and significant age- and gender-specific differences, ranging from very low to very high.
Abstract: Plasma glycans were analyzed in 1008 individuals to evaluate variability and heritability, as well as the main environmental determinants that affect glycan structures. By combining HPLC analysis of fluorescently labeled glycans with sialidase digestion, glycans were separated into 33 chromatographic peaks and quantified. A high level of variability was observed with the median ratio of minimal to maximal values of 6.17 and significant age- and gender-specific differences. Heritability estimates for individual glycans varied widely, ranging from very low to very high. Glycome-wide environmental determinants were also detected with statistically significant effects of different variables including diet, smoking and cholesterol levels.
TL;DR: Data indicate that folding stress is generally decreased at lower cultivation temperatures, enabling more efficient heterologous protein secretion in P. pastoris host cells.
Abstract: The impact of environmental factors on the productivity of yeast cells is poorly investigated so far. Therefore, it is a major concern to improve the understanding of cellular physiology of microbial protein production hosts, including the methylotrophic yeast Pichia pastoris. Two-Dimensional Fluorescence Difference Gel electrophoresis and protein identification via mass spectrometry were applied to analyze the impact of cultivation temperature on the physiology of a heterologous protein secreting P. pastoris strain. Furthermore, specific productivity was monitored and fluxes through the central carbon metabolism were calculated. Chemostat culture conditions were applied to assess the adaption to different growth temperatures (20, 25, 30 °C) at steady-state conditions. Many important cellular processes, including the central carbon metabolism, stress response and protein folding are affected by changing the growth temperature. A 3-fold increased specific productivity at lower cultivation temperature for a...
TL;DR: Contrary to the intuition, the "two-peptide" rule reduces the number of protein identifications in the target database more significantly than in the decoy database and results in increased false discovery rates, compared to the case when single-hit proteins are not discarded.
Abstract: Most proteomics studies attempt to maximize the number of peptide identifications and subsequently infer proteins containing two or more peptides as reliable protein identifications. In this study, we evaluate the effect of this “two-peptide” rule on protein identifications, using multiple search tools and data sets. Contrary to the intuition, the “two-peptide” rule reduces the number of protein identifications in the target database more significantly than in the decoy database and results in increased false discovery rates, compared to the case when single-hit proteins are not discarded. We therefore recommend that the “two-peptide” rule should be abandoned, and instead, protein identifications should be subject to the estimation of error rates, as is the case with peptide identifications. We further extend the generating function approach (originally proposed for evaluating matches between a peptide and a single spectrum) to evaluating matches between a protein and an entire spectral data set.
TL;DR: This work used an analysis platform that coupled hexapeptide libraries for dynamic range compression (DRC) with three-dimensional (3D) peptide fractionation to identify 2340 proteins in whole saliva, which represents the largest saliva proteomic dataset generated using a single analysis platform.
Abstract: Comprehensive identification of proteins in whole human saliva is critical for appreciating its full diagnostic potential. However, this is challenged by the large dynamic range of protein abundance within the fluid. To address this problem, we used an analysis platform that coupled hexapeptide libraries for dynamic range compression (DRC) with three-dimensional (3D) peptide fractionation. Our approach identified 2340 proteins in whole saliva and represents the largest saliva proteomic dataset generated using a single analysis platform. Three-dimensional peptide fractionation involving sequential steps of preparative isoelectric focusing (IEF), strong cation exchange, and capillary reversed-phase liquid chromatography was essential for maximizing gains from DRC. Compared to saliva not treated with hexapeptide libraries, DRC substantially increased identified proteins across physicochemical and functional categories. Approximately 20% of total salivary proteins are also seen in plasma, and proteins in both fluids show comparable functional diversity and disease-linkage. However, for a subset of diseases, saliva has higher apparent diagnostic potential. These results expand the potential for whole saliva in health monitoring/diagnostics and provide a general platform for improving proteomic coverage of complex biological samples.
TL;DR: These studies show the breadth and the depth of gut microbiome modulations of host biochemistry and reveal that major mammalian metabolic processes are under symbiotic homeostatic control.
Abstract: Coevolution shapes interorganismal crosstalk leading to profound and diverse cellular and metabolic changes as observed in gut dysbiosis in human diseases. Here, we modulated a simplified gut microbiota using pro-, pre-, and synbiotics to assess the depth of systemic metabolic exchanges in mice, using a multicompartmental modeling approach with metabolic signatures from 10 tissue/fluid compartments. The nutritionally induced microbial changes modulated host lipid, carbohydrate, and amino acid metabolism at a panorganismal scale. Galactosyl-oligosaccharides reduced lipogenesis, triacylglycerol incorporation into lipoproteins and triglyceride concentration in the liver and the kidney. Those changes were not correlated with decreased plasma lipoproteins that were specifically induced by L. rhamnosus supplementation. Additional alteration of transmethylation metabolic pathways (homocysteine-betaine) was observed in the liver and the pancreas following pre- and synbiotic microbial modulation, which may be of i...
TL;DR: Altered serum levels of glucose and ketonic bodies suggest alterations of energy metabolism, while the urine data point to alterations of gut microbiota, and metabolicomics may provide further hints on the biochemistry of the disease.
Abstract: Celiac disease (CD) is a multifactorial disorder involving genetic and environmental factors, thus, having great potential impact on metabolism. This study aims at defining the metabolic signature ...
TL;DR: The novel method outperformed PQD and HCD regarding its limit of detection, the number of identified peptides and the analytical precision of quantitation, and was applied to study changes in protein expression in mouse hearts upon transverse aortic constriction, a model for cardiac stress.
Abstract: The development of quantitative techniques in mass spectrometry has generated the ability to systematically monitor protein expression. Isobaric tags for relative and absolute quantification (iTRAQ) have become a widely used tool for the quantification of proteins. However, application of iTRAQ methodology using ion traps and hybrid mass spectrometers containing an ion trap such as the LTQ-Orbitrap was not possible until the development of pulsed Q dissociation (PQD) and higher energy C-trap dissociation (HCD). Both methods allow iTRAQ-based quantification on an LTQ-Orbitrap but are less suited for protein identification at a proteomic scale than the commonly used collisional induced dissociation (CID) fragmentation. We developed an analytical strategy combining the advantages of CID and HCD, allowing sensitive and accurate protein identification and quantitation at the same time. In a direct comparison, the novel method outperformed PQD and HCD regarding its limit of detection, the number of identified p...
TL;DR: To obtain reproducible results for solvent-precipitated plasma, the "conditioning" of the system with injections of matrix prior to the main analytical run was essential and the repeatability of the methodology was improved significantly when the sample preparation was performed using solid phase extraction.
Abstract: A study of the factors involved in obtaining valid global metabolite profiles from the LC-MS of human plasma for the purposes of metabonomic analysis has been undertaken. Plasma proteins were either precipitated with 3 vol of organic solvent (methanol or acetonitrile) or subjected to solid phase extraction (SPE) on a C18-bonded phase. For chromatography, a reversed-phase gradient system, based on acidified water/methanol, was used. Ultra performance liquid chromatography (UPLC) was performed on a C18-bonded stationary phase using sub 2 μm particles packed into a 2.1 × 100 mm column. The eluent from the column was subjected to analysis by positive electrospray ionization using a time-of-flight mass spectrometer. To obtain reproducible results for solvent-precipitated plasma, the “conditioning” of the system with injections of matrix prior to the main analytical run was essential. The repeatability of the methodology was improved significantly when the sample preparation was performed using solid phase extr...