Showing papers in "Journal of Proteome Research in 2007"

Chemometrics in Metabonomics

Abstract: We provide an overview of how the underlying philosophy of chemometrics is integrated throughout metabonomic studies. Four steps are demonstrated: (1) definition of the aim, (2) selection of objects, (3) sample preparation and characterization, and (4) evaluation of the collected data. This includes the tools applied for linear modeling, for example, Statistical Experimental Design (SED), Principal Component Analysis (PCA), Partial least-squares (PLS), Orthogonal-PLS (OPLS), and dynamic extensions thereof. This is illustrated by examples from the literature. Keywords: Statistical Experimental Design (SED) • PCA • OPLS • Class-specific studies • Dynamic studies • Multivariate Design

Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions.

Abstract: Identifying relationships between function, amino acid sequence and protein structure represents a major challenge. In this study we propose a bioinformatics approach that identifies functional keywords in the Swiss-Prot database that correlate with intrinsic disorder. A statistical evaluation is employed to rank the significance of these correlations. Protein sequence data redundancy and the relationship between protein length and protein structure were taken into consideration to ensure the quality of the statistical inferences. Over 200,000 proteins from Swiss-Prot database were analyzed using this approach. The predictions of intrinsic disorder were carried out using PONDR VL3E predictor of long disordered regions that achieves an accuracy of above 86%. Overall, out of the 710 Swiss-Prot functional keywords that were each associated with at least 20 proteins, 238 were found to be strongly positively correlated with predicted long intrinsically disordered regions, whereas 302 were strongly negatively correlated with such regions. The remaining 170 keywords were ambiguous without strong positive or negative correlation with the disorder predictions. These functions cover a large variety of biological activities and imply that disordered regions are characterized by a wide functional repertoire. Our results agree well with literature findings, as we were able to find at least one illustrative example of functional disorder or order shown experimentally for the vast majority of keywords showing the strongest positive or negative correlation with intrinsic disorder. This work opens a series of three papers, which enriches the current view of protein structure-function relationships, especially with regards to functionalities of intrinsically disordered proteins and provides researchers with a novel tool that could be used to improve the understanding of the relationships between protein structure and function. The first paper of the series describes our statistical approach, outlines the major findings and provides illustrative examples of biological processes and functions positively and negatively correlated with intrinsic disorder.

MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis.

Abstract: Shotgun proteomics experiments are dependent upon database search engines to identify peptides from tandem mass spectra Many of these algorithms score potential identifications by evaluating the number of fragment ions matched between each peptide sequence and an observed spectrum These systems, however, generally do not distinguish between matching an intense peak and matching a minor peak We have developed a statistical model to score peptide matches that is based upon the multivariate hypergeometric distribution This scorer, part of the “MyriMatch” database search engine, places greater emphasis on matching intense peaks The probability that the best match for each spectrum has occurred by random chance can be employed to separate correct matches from random ones We evaluated this software on data sets from three different laboratories employing three different ion trap instruments Employing a novel system for testing discrimination, we demonstrate that stratifying peaks into multiple intensity

Rapid and Noninvasive Metabonomic Characterization of Inflammatory Bowel Disease

Abstract: Inflammatory bowel diseases (IBD) including Crohn's disease (CD) and ulcerative colitis (UC) have a major impact on the health of individuals and populations. Accurate diagnosis of inflammatory bowel disease (IBD) at an early stage, and correct differentiation between Crohn's disease (CD) and ulcerative colitis (UC), is important for optimum treatment and prognosis. We present here the first characterization of fecal extracts obtained from patients with CD and UC by employing a noninvasive metabonomics approach, which combines high resolution 1H NMR spectroscopy and multivariate pattern recognition techniques. The fecal extracts of both CD and UC patients were characterized by reduced levels of butyrate, acetate, methylamine, and trimethylamine in comparison with a control population, suggesting changes in the gut microbial community. Also, elevated quantities of amino acids were present in the feces from both disease groups, implying malabsorption caused by the inflammatory disease or an element of protein losing enteropathy. Metabolic differences in fecal profiles were more marked in the CD group in comparison with the control group, indicating that the inflammation caused by CD is more extensive in comparison with UC and involves the whole intestine. Furthermore, glycerol resonances were a dominant feature of fecal spectra from patients with CD but were present in much lower intensity in the control and UC groups. This work illustrates the potential of metabonomics to generate novel noninvasive diagnostics for gastrointestinal diseases and may further our understanding of disease mechanisms.

Analytical strategies in metabonomics.

Abstract: To perform metabonomics investigations, it is necessary to generate comprehensive metabolite profiles for complex samples such as biofluids and tissue/tissue extracts. Analytical technologies that can be used to achieve this aim are constantly evolving, and new developments are changing the way in which such profiles' metabolite profiles can be generated. Here, the utility of various analytical techniques for global metabolite profiling, such as, e.g., 1H NMR, MS, HPLC-MS, and GC-MS, are explored and compared.

Within-Day Reproducibility of an HPLC−MS-Based Method for Metabonomic Analysis: Application to Human Urine

Abstract: Self-evidently, research in areas supporting “systems biology” such as genomics, proteomics, and metabonomics are critically dependent on the generation of sound analytical data. Metabolic phenotyping using LC−MS-based methods is currently at a relatively early stage of development, and approaches to ensure data quality are still developing. As part of studies on the application of LC−MS in metabonomics, the within-day reproducibility of LC−MS, with both positive and negative electrospray ionization (ESI), has been investigated using a standard “quality control” (QC) sample. The results showed that the first few injections on the system were not representative, and should be discarded, and that reproducibility was critically dependent on signal intensity. On the basis of these findings, an analytical protocol for the metabonomic analysis of human urine has been developed with proposed acceptance criteria based on a step-by-step assessment of the data. Short-term sample stability for human urine was also a...

Characterization of Molecular Recognition Features, MoRFs, and Their Binding Partners

Abstract: Molecular Recognition Features (MoRFs) are short, interaction-prone segments of protein disorder that undergo disorder-to-order transitions upon specific binding, representing a specific class of intrinsically disordered regions that exhibit molecular recognition and binding functions. MoRFs are common in various proteomes and occupy a unique structural and functional niche in which function is a direct consequence of intrinsic disorder. Example MoRFs collected from the Protein Data Bank (PDB) have been divided into three subtypes according to their structures in the bound state: α-MoRFs form α-helices, β-MoRFs form β-strands, and ι-MoRFs form structures without a regular pattern of backbone hydrogen bonds. These example MoRFs were indicated to be intrinsically disordered in the absence of their binding partners by several criteria. In this study we used several geometric and physiochemical criteria to examine the properties of 62 α-, 20 β- and 176 ι-MoRF complex structures. Interface residues were examined by calculating differences in accessible surface area between the complex and isolated monomers. The compositions and physiochemical properties of MoRF and MoRF partner interface residues were compared to the interface residues of homodimers, heterodimers, and antigen-antibody complexes. Our analysis indicates that there are significant differences in residue composition and several geometric and physicochemical properties that can be used to discriminate, with a high degree of accuracy, between various interfaces in protein interaction datasets. Implications of these findings for the development of MoRF-partner interaction predictors are discussed. In addition, structural changes upon MoRF-to-partner complex formation were examined for several illustrative examples.

Technical, Experimental, and Biological Variations in Isobaric Tags for Relative and Absolute Quantitation (iTRAQ)

Abstract: We assess the reliability of isobaric-tags for relative and absolute quantitation (iTRAQ), based on different types of replicate analyses taking into account technical, experimental, and biological variations. In total, 10 iTRAQ experiments were analyzed across three domains of life involving Saccharomyces cerevisiae KAY446, Sulfolobus solfataricus P2, and Synechocystis sp. PCC 6803. The coverage of protein expression of iTRAQ analysis increases as the variation tolerance increases. In brief, a cutoff point at ±50% variation (±0.50) would yield 88% coverage in quantification based on an analysis of biological replicates. Technical replicate analysis produces a higher coverage level of 95% at a lower cutoff point of ±30% variation. Experimental or iTRAQ variations exhibit similar behavior as biological variations, which suggest that most of the measurable deviations come from biological variations. These findings underline the importance of replicate analysis as a validation tool and benchmarking technique...

Functional Anthology of Intrinsic Disorder. 3. Ligands, Post-Translational Modifications, and Diseases Associated with Intrinsically Disordered Proteins

Abstract: Currently, the understanding of the relationships between function, amino acid sequence, and protein structure continues to represent one of the major challenges of the modern protein science. As many as 50% of eukaryotic proteins are likely to contain functionally important long disordered regions. Many proteins are wholly disordered but still possess numerous biologically important functions. However, the number of experimentally confirmed disordered proteins with known biological functions is substantially smaller than their actual number in nature. Therefore, there is a crucial need for novel bionformatics approaches that allow projection of the current knowledge from a few experimentally verified examples to much larger groups of known and potential proteins. The elaboration of a bioinformatics tool for the analysis of functional diversity of intrinsically disordered proteins and application of this data mining tool to >200 000 proteins from the Swiss-Prot database, each annotated with at least one of the 875 functional keywords, was described in the first paper of this series (Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V.N. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 2007, 5, 1882-1898). Using this tool, we have found that out of the 710 Swiss-Prot functional keywords associated with at least 20 proteins, 262 were strongly positively correlated with long intrinsically disordered regions, and 302 were strongly negatively correlated. Illustrative examples of functional disorder or order were found for the vast majority of keywords showing strongest positive or negative correlation with intrinsic disorder, respectively. Some 80 Swiss-Prot keywords associated with disorder- and order-driven biological processes and protein functions were described in the first paper (see above). The second paper of the series was devoted to the presentation of 87 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes, and coding sequence diversities possessing strong positive and negative correlation with long disordered regions (Vucetic, S.; Xie, H.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions. J. Proteome Res. 2007, 5, 1899-1916). Protein structure and functionality can be modulated by various post-translational modifications or/and as a result of binding of specific ligands. Numerous human diseases are associated with protein misfolding/misassembly/misfunctioning. This work concludes the series of papers dedicated to the functional anthology of intrinsic disorder and describes approximately 80 Swiss-Prot functional keywords that are related to ligands, post-translational modifications, and diseases possessing strong positive or negative correlation with the predicted long disordered regions in proteins.

Proteomic Parsimony through Bipartite Graph Analysis Improves Accuracy and Transparency

Abstract: Assembling peptides identified from LC−MS/MS spectra into a list of proteins is a critical step in analyzing shotgun proteomics data. As one peptide sequence can be mapped to multiple proteins in a database, naive protein assembly can substantially overstate the number of proteins found in samples. We model the peptide−protein relationships in a bipartite graph and use efficient graph algorithms to identify protein clusters with shared peptides and to derive the minimal list of proteins. We test the effects of this parsimony analysis approach using MS/MS data sets generated from a defined human protein mixture, a yeast whole cell extract, and a human serum proteome after MARS column depletion. The results demonstrate that the bipartite parsimony technique not only simplifies protein lists but also improves the accuracy of protein identification. We use bipartite graphs for the visualization of the protein assembly results to render the parsimony analysis process transparent to users. Our approach also gro...

Large-scale phosphorylation analysis of alpha-factor-arrested Saccharomyces cerevisiae

Abstract: Protein phosphorylation is essential for numerous cellular processes. Large-scale profiling of phosphoproteins continues to enhance the depth and speed at which we understand these processes. The development of effective phosphoprotein and peptide enrichment techniques and improvements to mass spectrometric instrumentation have intensified phosphoproteomic research in recent years, leading to unprecedented achievements. Here, we describe a large-scale phosphorylation analysis of alpha-factor-arrested yeast. Using a multidimensional separation strategy involving preparative SDS-PAGE for prefractionation, in-gel digestion with trypsin, and immobilized metal affinity chromatography (IMAC) enrichment of phosphopeptides, followed by LC-MS/MS analysis employing a hybrid LTQ-Orbitrap mass spectrometer, we were able to catalog a substantial portion of the phosphoproteins present in yeast whole-cell lysate. This analysis yielded the confident identification of 2288 nonredundant phosphorylation sites from 985 proteins. The ambiguity score (Ascore) algorithm was utilized to determine the certainty of site localization for the entire data set. In addition, the size of the data set permitted extraction of known and novel kinase motifs using the Motif-X algorithm. Finally, a large number of members of the pheromone signaling pathway were found as phosphoproteins and are discussed.

Euk-mPLoc: a fusion classifier for large-scale eukaryotic protein subcellular location prediction by incorporating multiple sites.

Abstract: One of the critical challenges in predicting protein subcellular localization is how to deal with the case of multiple location sites. Unfortunately, so far, no efforts have been made in this regard except for the one focused on the proteins in budding yeast only. For most existing predictors, the multiple-site proteins are either excluded from consideration or assumed even not existing. Actually, proteins may simultaneously exist at, or move between, two or more different subcellular locations. For instance, according to the Swiss-Prot database (version 50.7, released 19-Sept-2006), among the 33,925 eukaryotic protein entries that have experimentally observed subcellular location annotations, 2715 have multiple location sites, meaning about 8% bearing the multiplex feature. Proteins with multiple locations or dynamic feature of this kind are particularly interesting because they may have some very special biological functions intriguing to investigators in both basic research and drug discovery. Meanwhile, according to the same Swiss-Prot database, the number of total eukaryotic protein entries (except those annotated with "fragment" or those with less than 50 amino acids) is 90,909, meaning a gap of (90,909-33,925) = 56,984 entries for which no knowledge is available about their subcellular locations. Although one can use the computational approach to predict the desired information for the blank, so far, all the existing methods for predicting eukaryotic protein subcellular localization are limited in the case of single location site only. To overcome such a barrier, a new ensemble classifier, named Euk-mPLoc, was developed that can be used to deal with the case of multiple location sites as well. Euk-mPLoc is freely accessible to the public as a Web server at http://202.120.37.186/bioinf/euk-multi. Meanwhile, to support the people working in the relevant areas, Euk-mPLoc has been used to identify all eukaryotic protein entries in the Swiss-Prot database that do not have subcellular location annotations or are annotated as being uncertain. The large-scale results thus obtained have been deposited at the same Web site via a downloadable file prepared with Microsoft Excel and named "Tab_Euk-mPLoc.xls". Furthermore, to include new entries of eukaryotic proteins and reflect the continuous development of Euk-mPLoc in both the coverage scope and prediction accuracy, we will timely update the downloadable file as well as the predictor, and keep users informed by publishing a short note in the Journal and making an announcement in the Web Page.

Direct analysis and MALDI imaging of formalin-fixed, paraffin-embedded tissue sections.

Abstract: Formalin fixation, generally followed by paraffin embedding, is the standard and well-established processing method employed by pathologist. This treatment conserves and stabilizes biopsy samples for years. Analysis of FFPE tissues from biopsy libraries has been, so far, a challenge for proteomics biomarker studies. Herein, we present two methods for the direct analysis of formalin-fixed, paraffin-embedded (FFPE) tissues by MALDI-MS. The first is based on the use of a reactive matrix, 2,4-dinitrophenylhydrazine, useful for FFPE tissues stored less than 1 year. The second approach is applicable for all FFPE tissues regardless of conservation time. The strategy is based on in situ enzymatic digestion of the tissue section after paraffin removal. In situ digestion can be performed on a specific area of the tissue as well as on a very small area (microdigestion). Combining automated microdigestion of a predefined tissue array with either in situ extraction prior to classical nanoLC/MS-MS analysis or automated microspotting of MALDI matrix according to the same array allows the identification of both proteins by nanoLC-nanoESI and MALDI imaging. When adjacent tissue sections are used, it is, thus, possible to correlate protein identification and molecular imaging. These combined approaches, along with FFPE tissue analysis provide access to massive amounts of archived samples in the clinical pathology setting.

Dynamic activity of lipid droplets: protein phosphorylation and GTP-mediated protein translocation.

Abstract: Lipid droplet is a cellular organelle with a neutral lipid core surrounded by a phospholipid monolayer and coated with structural as well as functional proteins. The determination of these proteins, especially their functional regulations and dynamic movement on and off droplets, holds a key to resolving the biological functions of the cellular organelle. To address this, we carried out a comprehensive proteomic study that includes a complete proteomic, a phosphoprotein proteomic, and a comparative proteomic analysis using purified lipid droplets and mass spectrometry techniques. The complete proteome identified 125 proteins of which 70 proteins had not been identified on droplets of mammalian cells previously. In phosphoprotein proteomic analysis, 7 functional lipid droplet proteins were determined to be phosphorylated, including adipose differentiation related protein (ADRP/ADFP), two Rab proteins, and four lipid metabolism enzymes, including adipose triglyceride lipase (ATGL). To understand the dynamic...

Nutritional Metabonomics: Applications and Perspectives

Abstract: Nowadays, nutrition focuses on improving health of individuals through diet. Current nutritional research aims at health promotion, disease prevention, and performance improvement. Modern analytical platforms allow the simultaneous measurement of multiple metabolites providing new insights in the understanding of the functionalities of cells and whole organisms. Metabonomics, "the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modifications", provides a systems approach to understanding global metabolic regulations of organisms. This concept has arisen from various applications of NMR and MS spectroscopies to study the multicomponent metabolic composition of biological fluids, cells, and tissues. The generated metabolic profiles are processed by multivariate statistics to maximize the recovery of information to be correlated with well-determined stimuli such as dietary intervention or with any phenotypic data or diet habits. Metabonomics is thus uniquely suited to assess metabolic responses to deficiencies or excesses of nutrients and bioactive components. Furthermore, metabonomics is used to characterize the metabolic phenotype of individuals integrating genetic polymorphism, metabolic interactions with commensal and symbiotic partners such as gut microflora, as well as environmental and behavioral factors including dietary preferences. This paper reports several experimental key aspects in nutritional metabonomics, reviews its applications employing targeted and holistic approach analysis for the study of the metabolic responses following dietary interventions. It also reports the assessment of intra- and inter-individual variability in animal and human populations. The potentialities of nutritional metabonomics for the discovery of new biomarkers and the characterization of metabolic phenotypes are discussed in a context of their possible utilizations for personalized nutrition to provide health maintenance at the individual level.

From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics.

Abstract: Mass spectrometry (MS) is an established technology in drug metabolite analysis and is now expanding into endogenous metabolite research. Its utility derives from its wide dynamic range, reproducible quantitative analysis, and the ability to analyze biofluids with extreme molecular complexity. The aims of developing mass spectrometry for metabolomics range from understanding basic biochemistry to biomarker discovery and the structural characterization of physiologically important metabolites. In this review, we will discuss the techniques involved in this exciting area and the current and future applications of this field.

Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions.

Abstract: Biologically active proteins without stable ordered structure (i.e., intrinsically disordered proteins) are attracting increased attention. Functional repertoires of ordered and disordered proteins are very different, and the ability to differentiate whether a given function is associated with intrinsic disorder or with a well-folded protein is crucial for modern protein science. However, there is a large gap between the number of proteins experimentally confirmed to be disordered and their actual number in nature. As a result, studies of functional properties of confirmed disordered proteins, while helpful in revealing the functional diversity of protein disorder, provide only a limited view. To overcome this problem, a bioinformatics approach for comprehensive study of functional roles of protein disorder was proposed in the first paper of this series (Xie H., Vucetic S., Iakoucheva L.M., Oldfield C.J., Dunker A.K., Obradovic Z., Uversky V.N. (2006) Functional anthology of intrinsic disorder. I. Biological processes and functions of proteins with long disordered regions. J. Proteome Res.). Applying this novel approach to Swiss-Prot sequences and functional keywords, we found over 238 and 302 keywords to be strongly positively or negatively correlated, respectively, with long intrinsically disordered regions. This paper describes ~90 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes and coding sequence diversities possessing strong positive and negative correlation with long disordered regions.

Metabonomic studies of human hepatocellular carcinoma using high-resolution magic-angle spinning 1H NMR spectroscopy in conjunction with multivariate data analysis.

Abstract: High-resolution magic-angle spinning (MAS) 1 H nuclear magnetic resonance spectroscopy has been employed to characterize the metabolite composition (i.e., metabonome) of the human hepatocellular carcinoma (HCC) tumor in combination with principal component analysis (PCA). The results showed that (a) the metabonomes of both low-grade HCC and high-grade HCC tumors differ markedly from that of the adjacent non-involved tissues; and (b) low-grade HCC tumors have clear differences in metabonome from that of the high-grade HCC tumors. Compared with the non-involved adjacent liver tissues, HCC tumors had elevated levels of lactate, glutamate, glutamine, glycine, leucine, alanine, choline metabolites, and phosphorylethanolamine (PE), but declined levels of triglycerides, glucose, and glycogen. The levels of lactate, amino acids including glutamate, glutamine, glycine, leucine and alanine, choline and phosphorylethanolamine (PE) were higher but the levels of PC, GPC, triglycerides, glucose, and glycogen were lower in high-grade HCC than in low-grade HCC tumors. Compared with non-cirrhotic, low-grade HCC tumors, the cirrhotic, low-grade HCC tumors showed statistically significant increases in lactate, phosphocholine (PC), and glycerophosphocholine (GPC). The necrosis in HCC tumors resulted in a drastic increase in the levels of observable triglycerides, signals of which dominated their 1 H NMR spectra. These results indicated that HRMAS combined with PCA offers a useful tool for

Characterisation of host defence proteins in milk using a proteomic approach.

Abstract: Besides providing nutrition to the newborn, milk also protects the neonate and the mammary gland against infection. As well as the six major proteins, bovine milk contains minor proteins, not all of which have been characterized. In this study, we have subjected bovine skim milk, whey, and milk fat globule membrane (MFGM) fractions to both direct liquid chromatography-tandem mass spectrometry (LC-MS/MS), and two-dimensional electrophoresis (2-DE) followed by matrix assisted laser desorption ionization-time-of-flight (MALDI-TOF) mass spectrometry (MS) of individual protein spots to better characterize the repertoire of minor milk proteins, particularly those involved with host defense. Milk from peak lactation as well as during the period of colostrum formation and during mastitis were analyzed to gain a more complete sampling of the milk proteome. In total, 2903 peptides were detected by LC-MS and 2770 protein spots by 2-DE. From these, 95 distinct gene products were identified, comprising 53 identified through direct LC-MS/MS and 57 through 2-DE-MS. The latter were derived from a total of 363 spots analyzed with 181 being successfully identified. At least 15 proteins were identified that are involved in host defense. These results demonstrate that the proteome of milk is more complex than has previously been reported and a significant fraction of minor milk proteins are involved in protection against infection.

Body fluid proteomics for biomarker discovery: lessons from the past hold the key to success in the future.

Abstract: Sparked by the article from Lescuyer and colleagues in a recent issue, we aim here to further encourage interest in and discussion of clinically relevant biomarker research. We express our view on proteomics for biomarker discovery by addressing multiple relevant issues, including the inherent differences between biological fluids (and how these differences affect current analytical approaches) and experimental design to maximize the efficiency of moving from the bench to the bedside. Herein, we also include suggestions for definition of the term "biomarker", based on the use of a set of universal characterization/validation requirements, and illustrate several recent examples of successful transitions of benchtop proteomic studies work to clinical practice.

Alterations in the serum glycome due to metastatic prostate cancer.

Abstract: Glycomic profiles derived from human blood sera of 10 healthy males were compared to those from 24 prostate cancer patients. The profiles were acquired using MALDI−MS of permethylated N-glycans rel...

Proteomic profiling of plasma in Huntington's disease reveals neuroinflammatory activation and biomarker candidates.

Abstract: Huntington's disease (HD) causes widespread CNS changes and systemic abnormalities including endocrine and immune dysfunction. HD biomarkers are needed to power clinical trials of potential treatments. We used multiplatform proteomic profiling to reveal plasma changes with HD progression. Proteins of interest were evaluated using immunoblotting and ELISA in plasma from 2 populations, CSF and R6/2 mice. The identified proteins demonstrate neuroinflammation in HD and warrant further investigation as possible biomarkers.

Identification of Cellular Interaction Partners of the Influenza Virus Ribonucleoprotein Complex and Polymerase Complex Using Proteomic-Based Approaches

Abstract: Cellular factors that associate with the influenza A viral ribonucleoprotein (vRNP) are presumed to play important roles in the viral life cycle. To date, interaction screens using individual vRNP components, such as the nucleoprotein or viral polymerase subunits, have revealed few cellular interaction partners. To improve this situation, we performed comprehensive, proteomics-based screens to identify cellular factors associated with the native vRNP and viral polymerase complexes. Reconstituted vRNPs were purified from human cells using Strep-tagged viral nucleoprotein (NP-Strep) as bait, and co-purified cellular factors were identified by mass spectrometry (MS). In parallel, reconstituted native influenza A polymerase complexes were isolated using tandem affinity purification (TAP)-tagged polymerase subunits as bait, and co-purified cellular factors were again identified by MS. Using these techniques, we identified 41 proteins that co-purified with NP-Strep-enriched vRNPs and four cellular proteins that co-purified with the viral polymerase complex. Two of the polymerase-associated factors, importin-beta3 and PARP-1, represent novel interaction partners. Most cellular proteins previously shown to interact with either viral NP and/or vRNP were also identified using our method, demonstrating its sensitivity. Co-immunoprecipitation studies in virus-infected cells using selected novel interaction partners, including nucleophosmin (NPM), confirmed their association with vRNP. Immunofluorescence analysis further revealed that NPM is recruited to sites of viral transcription and replication in infected cells. Additionally, overexpression of NPM resulted in increased viral polymerase activity, indicating its role in viral RNA synthesis. In summary, the proteomics-based approaches used in this study represent powerful tools to identify novel vRNP-associated cellular factors for further characterization.

Proteomic analysis of microvesicles derived from human colorectal cancer cells

Abstract: Microvesicles (MV) are membrane vesicles secreted from the plasma and endosomal membrane compartment by various cell types such as hematopoietic, epithelial, and tumor cells. Actively growing tumor cells shed MV, and the rate of shedding increases in malignant tumors. Although recent progress in this area has revealed that tumor-derived MV play multiple roles in tumor growth and metastasis via immune escape, tumor invasion, and angiogenesis, the mechanism of vesicle formation and the biological roles of tumor-derived MV are not understood. Here, we report the first global proteomic analysis of highly purified MV from human colorectal cancer cells. Using 1D SDS gel electrophoresis and nano-LC–MS/MS analyses, we identified a total of 547 microvesicular proteins from three independent experiments with high confidence; 416 proteins were identified at least in two trials, including 181 as yet unreported proteins. We identified 49 proteins involved in the biogenesis of MV, including annexins, ADP-ribosylation f...

Optimization of mass spectrometry-compatible surfactants for shotgun proteomics.

Abstract: An optimization and comparison of trypsin digestion strategies for peptide/protein identifications by microLC-MS/MS with or without MS compatible detergents in mixed organic-aqueous and aqueous systems was carried out in this study. We determine that adding MS-compatible detergents to proteolytic digestion protocols dramatically increases peptide and protein identifications in complex protein mixtures by shotgun proteomics. Protein solubilization and proteolytic efficiency are increased by including MS-compatible detergents in trypsin digestion buffers. A modified trypsin digestion protocol incorporating the MS compatible detergents consistently identifies over 300 proteins from 5 microg of pancreatic cell lysates and generates a greater number of peptide identifications than trypsin digestion with urea when using LC-MS/MS. Furthermore, over 700 proteins were identified by merging protein identifications from trypsin digestion with three different MS-compatible detergents. We also observe that the use of mixed aqueous and organic solvent systems can influence protein identifications in combinations with different MS-compatible detergents. Peptide mixtures generated from different MS-compatible detergents and buffer combinations show a significant difference in hydrophobicity. Our results show that protein digestion schemes incorporating MS-compatible detergents generate quantitative as well as qualitative changes in observed peptide identifications, which lead to increased protein identifications overall and potentially increased identification of low-abundance proteins.

De novo peptide sequencing and identification with precision mass spectrometry.

Abstract: The recent proliferation of novel mass spectrometers such as Fourier transform, QTOF, and OrbiTrap marks a transition into the era of precision mass spectrometry, providing a 2 orders of magnitude boost to the mass resolution, as compared to low-precision ion-trap detectors. We investigate peptide de novo sequencing by precision mass spectrometry and explore some of the differences when compared to analysis of low-precision data. We demonstrate how the dramatically improved performance of de novo sequencing with precision mass spectrometry paves the way for novel approaches to peptide identification that are based on direct sequence lookups, rather than comparisons of spectra to a database. With the direct sequence lookup, it is not only possible to search a database very efficiently, but also to use the database in novel ways, such as searching for products of alternative splicing or products of fusion proteins in cancer. Our de novo sequencing software is available for download at http://peptide.ucsd.edu/.

Specific MALDI Imaging and Profiling for Biomarker Hunting and Validation: Fragment of the 11S Proteasome Activator Complex, Reg Alpha Fragment, Is a New Potential Ovary Cancer Biomarker

Abstract: MALDI imaging mass spectrometry represents a new analytical tool to directly provide the spatial distribution and relative abundance of proteins in tissue. Twenty-five ovary carcinomas (stages III and IV) and 23 benign ovaries were directly analyzed using MALDI-TOF MS. The biomarker with the major prevalence (80%) has been fully identified using MALDI MS and nanoESI MS and MS/MS after separation by RP-HPLC and trypsin enzymatic digestion. This marker with an m/z of 9744 corresponds to 84 amino acid residues from the 11S proteasome activator complex, named PA28 or Reg-alpha. Validation of this marker has been performed using MALDI imaging, classical immunocytochemistry with an antibody raised against the C-terminal part of the protein, specific MALDI imaging, and Western blot analysis. The validation, using immunocytochemistry, confirmed the epithelial localization of this fragment with nucleus localization in benign epithelial cells and a cytoplasmic localization in carcinoma cells. This indicates that this antibody could be used to discriminate the borderline tumor cases. At this point, a multicentric study needs to be conducted in order to clearly establish the potential of this biomarker. Taken together these studies reflect that direct tissue analysis and specific MALDI imaging strategies facilitate biomarker hunting and validation which can be named pathological proteomics.

The art and practice of systems biology in medicine: mapping patterns of relationships.

Abstract: Systems biology has developed in recent years from a technology-driven enterprise to a new strategic tool in Life Sciences, particularly for innovative drug discovery and drug development. Combining the ultimate in systems phenotyping with in-depth investigations of biomolecular mechanisms will enable a revolution in our understanding of disease pathology and will advance translational medicine, combination therapies, integrative medicine, and personalized medicine. A prerequisite for deriving the benefits of such a systems approach is a reliable and well-validated bioanalytical platform across complementary measurement modalities, especially transcriptomics, proteomics, and metabolomics, that operates in concert with a megavariate integrative biostatistical/bioinformatics platform. The applicable bioanalytical methodologies must undergo an intense development trajectory to reach an optimal level of reliable performance and quantitative reproducibility in daily practice. Moreover, to generate such enabling systems information, it is essential to design experiments based on an understanding of the complexity and statistical characteristics of the large data sets created. Novel insights into biology and system science can be obtained by evaluating the molecular connectivity within a system through correlation networks, by monitoring the dynamics of a system, or by measuring the system responses to perturbations such as drug administration or challenge tests. In addition, cross-compartment communication and control/feed-back mechanisms can be studied via correlation network analyses. All these data analyses depend critically upon the generation of high-quality bioanalytical platform data sets. The emphasis of this paper is on the characteristics of a bioanalytical platform that we have developed to generate such data sets. The broad applicability of Systems Biology in pharmaceutical research and development is discussed with examples in disease biomarker research, in pharmacology using system response monitoring, and in cross-compartment system toxicology assessment. © 2007 American Chemical Society.

Proteomics uncovers a role for redox in drought tolerance in wheat.

Abstract: Proteomic analysis offers a new approach to identify a broad spectrum of genes that are expressed in living systems. We applied a proteomic approach to study changes in wheat grain in response to drought, a major environmental parameter adversely affecting development and crop yield. Three wheat genotypes differing in genetic background were cultivated in field under well-watered and drought conditions by following a randomized complete block design with four replications. The overall effect of drought was highly significant as determined by grain yield and total dry matter. About 650 spots were reproducibly detected and analyzed on 2-DE gels. Of these, 121 proteins showed significant change under drought condition in at least one of the genotypes. Mass spectrometry analysis using MALDI-TOF/TOF led to the identification of 57 proteins. Two-thirds of identified proteins were thioredoxin (Trx) targets, in accordance with the link between drought and oxidative stress. Further, because of contrasting changes in the tolerant and susceptible genotypes studied, several proteins emerge as key participants in the drought response. In addition to providing new information on the response to water deprivation, the present study offers opportunities to pursue the breeding of wheat with enhanced drought tolerance using identified candidate genetic markers. The 2-DE database of wheat seed proteins is available for public access at http://www.proteome.ir.

Practical points in urinary proteomics.

Abstract: During the proteomic era, one of the most rapidly growing areas in biomedical research is biomarker discovery, particularly using proteomic technologies. Urinary proteomics has become one of the most attractive subdisciplines in clinical proteomics, as the urine is an ideal source for the discovery of noninvasive biomarkers for human diseases. However, there are several barriers to the success of the field and urinary proteome analysis is not a simple task because the urine has low protein concentration, high levels of salts or other interfering compounds, and more importantly, high degree of variations (both intra-individual and inter-individual variabilities). This article provides step-by-step practical points to perform urinary proteome analysis, covering detailed information for study design, sample collection, sample storage, sample preparation, proteomic analysis, and data interpretation. The discussion herein should stimulate further discussion and refinement to develop guidelines and standardizat...