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PubMed2005

A proteome approach defines protective functions of tobacco leaf trichomes.

The leaf surface of most terrestrial plants is covered with plant hairs called trichomes. These epidermal appendages are thought to contribute to many aspects of plant defense against biotic and abiotic stresses in a variety of species. Trichome development has been intensively studied in Arabidopsis, and the phytochemical composition of trichomes was analyzed in a number of plant species. However, comparatively little is known of the proteins expressed. We therefore initiated a proteome approach to better define the cellular mechanisms operating in plant trichomes using two-dimensional gel electrophoresis to separate proteins of whole leaves and isolated trichomes. Tobacco was chosen due to the presence of glandular trichomes involved in the secretion of defense compounds. Comparative image analysis of the protein patterns indicated a number of spots, which were highly enriched in trichomes relative to leaves. These spots were excised for identification by mass spectrometry. The results showed that among the proteins specifically enriched in trichomes, the components of stress defense responses were strongly represented. The high expression of stress-related proteins was verified by Western blotting. Superoxide dismutase isoforms were additionally analyzed by activity staining. Our results demonstrate feasibility of the proteome approach to elucidate the cell biology of plant trichomes.

Amino Acid Sequence↗

PubMed2003

ELM server: A new resource for investigating short functional sites in modular eukaryotic proteins.

Multidomain proteins predominate in eukaryotic proteomes. Individual functions assigned to different sequence segments combine to create a complex function for the whole protein. While on-line resources are available for revealing globular domains in sequences, there has hitherto been no comprehensive collection of small functional sites/motifs comparable to the globular domain resources, yet these are as important for the function of multidomain proteins. Short linear peptide motifs are used for cell compartment targeting, protein-protein interaction, regulation by phosphorylation, acetylation, glycosylation and a host of other post-translational modifications. ELM, the Eukaryotic Linear Motif server at http://elm.eu.org/, is a new bioinformatics resource for investigating candidate short non-globular functional motifs in eukaryotic proteins, aiming to fill the void in bioinformatics tools. Sequence comparisons with short motifs are difficult to evaluate because the usual significance assessments are inappropriate. Therefore the server is implemented with several logical filters to eliminate false positives. Current filters are for cell compartment, globular domain clash and taxonomic range. In favourable cases, the filters can reduce the number of retained matches by an order of magnitude or more.

Amino Acid Motifs↗

PubMed2003

Application of proteomics to the study of molecular mechanisms in neurotoxicology.

The proteome is the protein compliment of the genome and is the result of genetic expression, ribosomal synthesis and proteolytic degradation. Proteins participate in most major cell processes and their function is highly regulated by post-translational modifications such as phosphorylation and glycosylation. As a result, neurotoxicant-induced changes in protein levels, function or regulation could have a negative impact on neuronal viability. At the molecular level, direct oxidative or covalent modifications of individual proteins by various chemicals or drugs is likely to lead to perturbation of tertiary structure and a loss of function. The proteome and the functional determinants of its individual protein components are, therefore, likely targets of neurotoxicant action and resulting characteristic disruptions could be critically involved in corresponding mechanisms of neurotoxicity. Clearly, investigating changes in the proteome can provide important clues for deciphering mechanisms of toxicant action and, therefore, proteomics, the study of the proteome, is currently, and will likely remain, a significant experimental approach for mechanistic research in neurotoxicology. The purpose of this review is to discuss proteomics as a tool for neurotoxicological investigations. A variety of classic proteomic techniques (e.g. liquid chromatography (LC)/tandem mass spectroscopy, two-dimensional gel image analysis) as well as more recently developed approaches (e.g. two-hybrid systems, antibody arrays, protein chips, isotope-coded affinity tags, ICAT) are available to determine protein levels, identify components of multiprotein complexes and to detect post-translational changes. Proteomics, therefore, offers a comprehensive overview of cell proteins, and in the case of neurotoxicant exposure, can provide quantitative data regarding changes in corresponding expression levels and/or post-translational modifications that might be associated with neuron injury.

Animals↗

PubMedDate not supplied

Antigens up the nose: identification of putative biomarkers for nasal tolerance induction functional studies combined with proteomics.

Intranasal autoantigen delivery is the most effective means of inducing mucosal tolerance and suppression of autoimmune disease. In an effort to identify markers of the "tolerant state", we employed proteomics technology at the level of the cervical lymph node. The analysis revealed that nasal antigen administration (without adiuvant) led to modulation of various proteins among which the most prominent were haptoglobin, nonintegrin 67 kDa laminin receptor, and MRP8. The immunoregulatory haptoglobin may qualify as (bio)marker for effective immunotherapy.

Adipokines↗

PubMed2003

Cardiac natriuretic peptides:a proteomic window to cardiac function and clinical management.

Congestive heart failure (CHF) is a leading cause of adult hospitalization in the United States, and despite advancements in treatment, the disease remains a major clinical challenge. The chief symptom of CHF is dyspnea, but in the urgent-care setting, it is often difficult to distinguish between cardiac and pulmonary causes of this symptom. B-type natriuretic peptide (BNP) is mainly synthesized, stored, and released in the ventricular myocardium and is strongly induced during ventricular-wall tension or stretch. It can be measured rapidly at the point of care and can be used to differentiate cardiac from pulmonary etiologies of dyspnea. In addition to its diagnostic utility, it also has prognostic value and may help guide the treatment of patients with CHF. Thus, it is likely that future algorithms incorporating BNP levels and other clinical indicators will become available to guide critical-care physicians in making management decisions for their CHF patients.

Biomarkers↗

PubMed2005

Examining the proteins of functional retinal lipofuscin using proteomic analysis as a guide for understanding its origin.

PURPOSE: To elucidate the origins of biologically active retinal lipofuscin (RLF) by examining its protein composition. METHODS: Total protein and total lipid were extracted and quantified. Proteins in this lipoprotein granule were identified by limited-scale proteomic analysis using both two-dimensional (2D) gel electrophoresis and SDS-PAGE coupled with MALDI-QqToF MSMS and automated LCMSMS, respectively. RESULTS: RLF granules were 44% protein and 50% lipid. Proteomic analyses identified 41 constituent proteins. Hydrophobic proteins and several proteins specific to photoreceptors, including rhodopsin, that have not previously been reported, were identified. Extensive protein modification, especially oxidative damage, was observed. CONCLUSIONS: Proteins identified support the model that RLF accumulates in RPE cells as a result of the buildup of undigested material from the phagocytosis of photoreceptor outer segments. Perhaps oxidative damage renders some of these proteins indigestible and thus leads to the accumulation of RLF granules.

Adult↗

PubMed2006

Tracing the origin of functional and conserved domains in the human proteome: implications for protein evolution at the modular level.

BACKGROUND: The functional repertoire of the human proteome is an incremental collection of functions accomplished by protein domains evolved along the Homo sapiens lineage. Therefore, knowledge on the origin of these functionalities provides a better understanding of the domain and protein evolution in human. The lack of proper comprehension about such origin has impelled us to study the evolutionary origin of human proteome in a unique way as detailed in this study. RESULTS: This study reports a unique approach for understanding the evolution of human proteome by tracing the origin of its constituting domains hierarchically, along the Homo sapiens lineage. The uniqueness of this method lies in subtractive searching of functional and conserved domains in the human proteome resulting in higher efficiency of detecting their origins. From these analyses the nature of protein evolution and trends in domain evolution can be observed in the context of the entire human proteome data. The method adopted here also helps delineate the degree of divergence of functional families occurred during the course of evolution. CONCLUSION: This approach to trace the evolutionary origin of functional domains in the human proteome facilitates better understanding of their functional versatility as well as provides insights into the functionality of hypothetical proteins present in the human proteome. This work elucidates the origin of functional and conserved domains in human proteins, their distribution along the Homo sapiens lineage, occurrence frequency of different domain combinations and proteome-wide patterns of their distribution, providing insights into the evolutionary solution to the increased complexity of the human proteome.

Animals↗

PubMed2004

Proteomics: state of the art and its application in cardiovascular research.

The cellular and molecular mechanisms underlying cardiovascular dysfunctions are widely unknown. Basically, pathological changes in the cardiovascular system arise from protein alterations. Proteomics comprises a set of tools for the large-scale study of gene expression at the protein level thereby allowing for the identification of protein alterations responsible for the development and the pathological outcome of diseases including those of the cardiovascular system. In principle these alterations include those of suitable candidates for drug targets and disease biomarkers as well as therapeutic proteins/peptides. Since gene therapy depends on the function of a therapeutic protein encoded by a "therapeutic" gene proteomic analyses also provide the basis for the design and application of gene therapies. Proteomic technologies allow to identify not only proteins but also the nature of their posttranslational modifications thus enabling the elucidation of signal transduction pathways and their deregulation under pathological conditions. The linkage of information about proteome changes with functional consequences lead to the development of functional proteomic studies. Functional proteomic analyses will particularly help to better understand the relations between proteome changes and cardiovascular dysfunctions. The storage and administration of experimental data obtained by the application of proteomic analyses is supported by species- and tissue-specific protein databases and specific software. Publications in this field are reviewed in this paper.

Animals↗

PubMedDate not supplied

Human proteomic databases: a powerful resource for functional genomics in health and disease.

Decoding of the genome information in terms of regulation and function will be the next great challenge in the life sciences in this millennium and indeed, today we are experiencing a rapid explosion of technology for the high throughput expression analysis of genes and their products (functional genomics). In particular, the field of proteomics is booming as proteins are often the functional molecules and represent important targets for the pharmaceutical industry. The proteomic technology is complex, and comprises a plethora of state-of-the-art techniques to resolve, identify and detect their interacting partners, as well as to store and communicate protein information in comprehensive two-dimensional polyacrylamide gel electrophoresis (2D PAGE) databases. Besides annotating the genome, these databases will offer a global approach to the study of gene expression both in health and disease. Here, we review the current status of human 2D PAGE databases that we are systematically constructing for the study of bladder cancer and skin ageing.

Databases, Protein↗

PubMed2006

Unsupervised immunophenotypic profiling of chronic lymphocytic leukemia.

BACKGROUND: Proteomics and functional genomics have revolutionized approaches to disease classification. Like proteomics, flow cytometry (FCM) assesses concurrent expression of many proteins, with the advantage of using intact cells that may be differentially selected during analysis. However, FCM has generally been used for incremental marker validation or construction of predictive models based on known patterns, rather than as a tool for unsupervised class discovery. We undertook a retrospective analysis of clinical FCM data to assess the feasibility of a cell-based proteomic approach to FCM by unsupervised cluster analysis. METHODS: Multicolor FCM data on peripheral blood (PB) and bone marrow (BM) lymphocytes from 140 consecutive patients with B-cell chronic lymphoproliferative disorders (LPDs), including 81 chronic lymphocytic leukemia (CLLs), were studied. Expression was normalized for CD19 totals, and recorded for 10 additional B-cell markers. Data were subjected to hierarchical cluster analysis using complete linkage by Pearson's correlation. Analysis of CLL in PB samples (n = 63) discovered three major clusters. One cluster (14 patients) was skewed toward "atypical" CLL and was characterized by high CD20, CD22, FMC7, and light chain, and low CD23. The remaining two clusters consisted almost entirely (48/49) of cases recorded as typical BCLL. The smaller "typical" BCLL cluster differed from the larger cluster by high CD38 (P = 0.001), low CD20 (P = 0.001), and low CD23 (P = 0.016). These two typical BCLL clusters showed a trend toward a difference in survival (P = 0.1090). Statistically significant cluster stability was demonstrated by expanding the dataset to include BM samples, and by using a method of random sampling with replacement. CONCLUSIONS: This study supports the concept that unsupervised immunophenotypic profiling of FCM data can yield reproducible subtypes of lymphoma/chronic leukemia. Expanded studies are warranted in the use of FCM as an unsupervised class discovery tool, akin to other proteomic methods, rather than as a validation tool.

ADP-ribosyl Cyclase 1↗

PubMed2005

Bioinformatics in microbial biotechnology--a mini review.

The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i) genomics--sequencing and comparative study of genomes to identify gene and genome functionality, (ii) proteomics--identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii) cell visualization and simulation to study and model cell behavior, and (iv) application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1) analysis based upon the available experimental wet-lab data, (2) the use of mathematical modeling to derive new information, and (3) an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene expression analysis to derive regulatory pathways, the development of statistical techniques, clustering techniques and data mining techniques to derive protein-protein and protein-DNA interactions, and modeling of 3D structure of proteins and 3D docking between proteins and biochemicals for rational drug design, difference analysis between pathogenic and non-pathogenic strains to identify candidate genes for vaccines and anti-microbial agents, and the whole genome comparison to understand the microbial evolution. The development of bioinformatics techniques has enhanced the pace of biological discovery by automated analysis of large number of microbial genomes. We are on the verge of using all this knowledge to understand cellular mechanisms at the systemic level. The developed bioinformatics techniques have potential to facilitate (i) the discovery of causes of diseases, (ii) vaccine and rational drug design, and (iii) improved cost effective agents for bioremediation by pruning out the dead ends. Despite the fast paced global effort, the current analysis is limited by the lack of available gene-functionality from the wet-lab data, the lack of computer algorithms to explore vast amount of data with unknown functionality, limited availability of protein-protein and protein-DNA interactions, and the lack of knowledge of temporal and transient behavior of genes and pathways.

Journal Article↗

PubMed2006

Proteomic analysis of reporter genes for molecular imaging of transplanted embryonic stem cells.

Study of stem cells may reveal promising treatment for diseases. The fate and function of transplanted stem cells remain poorly defined. Recent studies demonstrate that reporter genes can monitor real-time survival of transplanted stem cells in living subjects. We examined the effects of a novel and versatile triple fusion (TF) reporter gene construction on embryonic stem (ES) cell function by proteomic analysis. Murine ES cells were stably transduced with a self-inactivating lentiviral vector containing fluorescence (firefly luciferase; Fluc), bioluminescence (monomeric red fluorescence protein; mRFP), and positron emission tomography (herpes simplex virus type 1 truncated thymidine kinase; tTK) reporter genes. Fluorescence-activated cell sorting (FACS) analysis isolated stably transduced populations. TF reporter gene effects on cellular function were evaluated by quantitative proteomic profiling of control ES cells versus ES cells stably expressing the TF construct (ES-TF). Overall, no significant changes in protein quantity were observed. TF reporter gene expression had no effect on ES cell viability, proliferation, and differentiation capability. Molecular imaging studies tracked ES-TF cell survival and proliferation in living animals. In summary, this is the first proteomic study, demonstrating the unique potential of reporter gene imaging for tracking ES cell transplantation non-invasively, repetitively, and quantitatively.

Animals↗

PubMed2005

Prediction of orthologous relationship by functionally important sites.

Making accurate functional predictions plays an important role in the era of proteomics. Reliable functional information can be extracted from orthologs in other species when annotating an unknown gene. Here a site-based approach called PORFIS is proposed to predict orthologous relationship. When applied to the bacterial transcription factor PurR/LacI family and the protein kinase AGC family, our method was able to identify, with few false positives, the important sites that agree with those verified by biological experiments. We also tested it on the alpha-proteasome family, the glycoprotein hormone family and the growth hormone family to demonstrate its ability to predict orthologous relationship. Compared with other prediction methods based on phylogenetic analysis or hidden Markov models, PORFIS not only has competitive prediction accuracy, but also provides valuable biological information of functionally important sites associated with orthologs which can be further studied in biological experiments.

Humans↗

PubMed1999

The Yeast Proteome Database (YPD): a model for the organization and presentation of genome-wide functional data.

The Yeast Proteome Database (YPD) is a model for the organization and presentation of comprehensive protein information. Based on the detailed curation of the scientific literature for the yeast Saccharomyces cerevisiae, YPD contains more than 50 000 annotations lines derived from the review of 8500 research publications. The information concerning each of the approximately 6100 yeast proteins is structured around a convenient one-page format, the Yeast Protein Report, with additional information provided as pop-up windows. Protein classification schema have been revised this year, defining each protein's cellular role, function and pathway, and adding a Functional to the Yeast Protein Report. These changes provide the user with a succinct summary of the protein's function and its place in the biology of the cell, and they enhance the power of YPD Search functions. Precalculated sequence alignments have been added, to provide a crossover point for comparative genomics. The first transcript profiling data has been integrated into the YPD Protein Reports, providing the framework for the presentation of genome-wide functional data. The Yeast Proteome Database can be accessed on the Web at http://www.proteome.com/YPDhome.html

Computational Biology↗

PubMed2003

Synergistic computational and experimental proteomics approaches for more accurate detection of active serine hydrolases in yeast.

An analysis of the structurally and catalytically diverse serine hydrolase protein family in the Saccharomyces cerevisiae proteome was undertaken using two independent but complementary, large-scale approaches. The first approach is based on computational analysis of serine hydrolase active site structures; the second utilizes the chemical reactivity of the serine hydrolase active site in complex mixtures. These proteomics approaches share the ability to fractionate the complex proteome into functional subsets. Each method identified a significant number of sequences, but 15 proteins were identified by both methods. Eight of these were unannotated in the Saccharomyces Genome Database at the time of this study and are thus novel serine hydrolase identifications. Three of the previously uncharacterized proteins are members of a eukaryotic serine hydrolase family, designated as Fsh (family of serine hydrolase), identified here for the first time. OVCA2, a potential human tumor suppressor, and DYR-SCHPO, a dihydrofolate reductase from Schizosaccharomyces pombe, are members of this family. Comparing the combined results to results of other proteomic methods showed that only four of the 15 proteins were identified in a recent large-scale, "shotgun" proteomic analysis and eight were identified using a related, but similar, approach (neither identifies function). Only 10 of the 15 were annotated using alternate motif-based computational tools. The results demonstrate the precision derived from combining complementary, function-based approaches to extract biological information from complex proteomes. The chemical proteomics technology indicates that a functional protein is being expressed in the cell, while the computational proteomics technology adds details about the specific type of function and residue that is likely being labeled. The combination of synergistic methods facilitates analysis, enriches true positive results, and increases confidence in novel identifications. This work also highlights the risks inherent in annotation transfer and the use of scoring functions for determination of correct annotations.

Amino Acid Sequence↗

PubMed2005

The nutritional phenotype in the age of metabolomics.

The concept of the nutritional phenotype is proposed as a defined and integrated set of genetic, proteomic, metabolomic, functional, and behavioral factors that, when measured, form the basis for assessment of human nutritional status. The nutritional phenotype integrates the effects of diet on disease/wellness and is the quantitative indication of the paths by which genes and environment exert their effects on health. Advances in technology and in fundamental biological knowledge make it possible to define and measure the nutritional phenotype accurately in a cross section of individuals with various states of health and disease. This growing base of data and knowledge could serve as a resource for all scientific disciplines involved in human health. Nutritional sciences should be a prime mover in making key decisions that include: what environmental inputs (in addition to diet) are needed; what genes/proteins/metabolites should be measured; what end-point phenotypes should be included; and what informatics tools are available to ask nutritionally relevant questions. Nutrition should be the major discipline establishing how the elements of the nutritional phenotype vary as a function of diet. Nutritional sciences should also be instrumental in linking the elements that are responsive to diet with the functional outcomes in organisms that derive from them. As the first step in this initiative, a prioritized list of genomic, proteomic, and metabolomic as well as functional and behavioral measures that defines a practically useful subset of the nutritional phenotype for use in clinical and epidemiological investigations must be developed. From this list, analytic platforms must then be identified that are capable of delivering highly quantitative data on these endpoints. This conceptualization of a nutritional phenotype provides a concrete form and substance to the recognized future of nutritional sciences as a field addressing diet, integrated metabolism, and health.

Diet↗

PubMed2002

Proteome-wide analysis of protein function composition reveals the clustering and phylogenetic properties of organisms.

A 17-dimensional vector named the proteome vector is defined to represent an organism. The components of the vector reflect the relative contents of protein-encoding genes of the 17 cluster of orthologous groups of proteins (COGs) classes in the whole genome of the relevant organism. Based on the definition of this proteome vector, the fuzzy clustering of 36 completely sequenced organisms (8 archaea, 24 bacteria, and 4 eukarya) was performed and a proteome tree was constructed. Our results show that (1) the 36 organisms can be 100% correctly classified into three clusters corresponding to the three primary kingdoms, (2) our proteome tree is remarkably similar to that derived from 16S rRNA, and (3) the chromosomes and/or plasmids belonging to the same organism have very similar gene composition. Based on these results, we argue that the 17-dimensional proteome vector could be a good criterion for clustering approaches and to a large extent reveals the phylogenetic properties of organisms; the Three Primary Kingdoms Hypothesis is trustworthy although the existence of lateral gene transfer (LGT) brings controversy to the construction of the "universal tree of life."

Algorithms↗

PubMed2004

Application of proteomics to the study of platelet regulatory mechanisms.

Newly developed proteomic technologies now permit the routine identification of hundreds or even thousands of proteins in a single experiment. However, the global study of any proteome has unique challenges that set it apart from comprehensive studies of genes and transcripts. The detection of low-abundance, biologically relevant proteins poses a particular challenge, especially given that the dynamic range of proteins in cells is estimated to be > or =10(6). Nevertheless, the incorporation of proteomics into functional biochemical and biologic investigation has proved to be a powerful tool when applied to platelet biology. This review highlights recent proteomic approaches to the characterization of the proteins released from activated platelets and to the identification of integrin-associated regulators of platelet function. Also described are efforts to link platelet-proteomic and platelet-transcriptional data.

Blood Platelets↗