Inside SMP proteomics: six years German Human Brain Proteome Project (HBPP) - a summary

In 2001, the German Federal Ministry of Education and Research (BMBF) initiated the National Genome Research Network (NGFN; www.ngfn.de) as a nation-wide multidisciplinary networking platform aiming at the analysis of common human diseases and aging. Within the NGFN the Human Brain Proteome Project (HBPP; www.smp-proteomics.de) focuses on the analysis of the human brain in health and disease. The concept is based on two consecutive steps: (i) Elaborating and establishing the necessary technology platforms. (ii) Application of the established technologies for research in Alzheimer's disease and Parkinson's disease. In the first funding period, HBPP1, running from 2001 to 2004, necessary technologies were established and optimized. In HBPP2, which started 2004 and will end in May 2008, the developed technologies are used for large-scale experiments, offering new links for disease related research and therapies. The following overview describes structure, aims and outcome of this unique German Brain Proteome Project.     

Proteome biology of stem cells

The notion that integration of cutting-edge technologies in stem cell research would be enhanced by proteomic analyses has emanated from rapid advances in proteome technology. These advances have increased the probability that basic properties of stem cells will be elucidated more effectively, leading to acceleration toward novel stem cell therapies. We have therefore sought to establish a world-wide alliance of proteomics and stem cell researchers, which has resulted in the foundation of an initiative supported by the Human Proteome Organisation (HUPO) and the International Society for Stem Cell Research (ISSCR) called the Proteome Biology of Stem Cells Initiative. Here we report on the rationale and goals of this initiative.     

Rice Proteome Database: A Step toward Functional Analysis of the Rice Genome

The technique of proteome analysis using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this study, the proteins of rice were cataloged, a rice proteome database was constructed, and a functional characterization of some of the identified proteins was undertaken. Proteins extracted from various tissues and subcellular compartments in rice were separated by 2D-PAGE and an image analyzer was used to construct a display of the proteins. The Rice Proteome Database contains 23 reference maps based on 2D-PAGE of proteins from various rice tissues and subcellular compartments. These reference maps comprise 13129 identified proteins, and the amino acid sequences of 5092 proteins are entered in the database. Major proteins involved in growth or stress responses were identified using the proteome approach. Some of these proteins, including a β-tubulin, calreticulin, and ribulose-1,5-bisphosphate carboxylase/oxygenase activase in rice, have unexpected functions. The information obtained from the Rice Proteome Database will aid in cloning the genes for and predicting the function of unknown proteins.     

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.     

A Human Proteome Detection and Quantitation Project

The lack of sensitive, specific, multiplexable assays for most human proteins is the major technical barrier impeding development of candidate biomarkers into clinically useful tests. Recent progress in mass spectrometry-based assays for proteotypic peptides, particularly those with specific affinity peptide enrichment, offers a systematic and economical path to comprehensive quantitative coverage of the human proteome. A complete suite of assays, e.g. two peptides from the protein product of each of the ∼20,500 human genes (here termed the human Proteome Detection and Quantitation project), would enable rapid and systematic verification of candidate biomarkers and lay a quantitative foundation for subsequent efforts to define the larger universe of splice variants, post-translational modifications, protein-protein interactions, and tissue localization.There is growing interest in the idea of a comprehensive Human Proteome Project (1) to exploit and extend the successful effort to sequence the human genome. Major challenges in defining a comprehensive Human Proteome Project (and distinguishing it from the genome effort) are 1) the potentially very large number of proteins with modified forms; 2) the diversity of technology platforms involved in their study; 3) the variety of overlapping biological “units” into which the proteome might be divided for organized conquest; and 4) sensitivity limitations in detecting proteins present in trace amounts. The process of analyzing and discussing these issues may (and ought to) be lengthy, as it addresses core scientific unknowns as well as decisions about the organization and scale of biomedical research in the future. The benefits of taking time to involve the entire biological research community, and especially the medical research segment, in these discussions are substantial.Progress in systematically measuring proteins, however, need not wait for the conclusion of such discussions. We propose a near-term tactical approach, called the human Proteome Detection and Quantitation (hPDQ)¹ project that will enable measurement of the human proteome in a way that would yield immediately useful results while the strategy for a comprehensive Human Proteome Project is worked out. The hPDQ project is aimed at overcoming present difficulties in answering basic biological questions about the relationship between protein abundance (or concentration) and gene expression, phenotype, disease, and treatment response; i.e., the growing field of protein biomarkers. It is thus focused on the study of biological variation affecting protein expression rather than study of structure and mechanism and in this initial form does not directly address splice variants or most post-translational modifications. It is aimed at providing immediately useful capabilities to the human biology research community, in a way that does not adversely impact funding for individual investigators and does not generate administrative constraints on their ability to set and change courses in the conduct of research. Specifically, the goal of the hPDQ is to enable individual biological researchers to measure defined collections of human proteins in biological samples with 1 ng/ml sensitivity and absolute specificity, at throughput and cost levels that permit the study of meaningfully large biological populations (∼500–5,000 samples).We clearly do not have this capability today. If an investigator defines a set of 20 proteins hypothesized to change in relation to some biological process or event, assays for only a minority (often none!) will typically be available. Further, these assays will lack absolute specificity and will not easily be multiplexed. Current proteomics research platforms are focused mainly on discovery; providing increasingly broad protein sampling surveys, generally at low throughput and high cost. Such approaches generally do not yield an economical or accurate measurement of a defined set of proteins in every sample. There is thus a fundamental barrier to hypothesis testing in quantitative proteomics, where relationships between protein abundance and biology are sought. A particularly important instance of this limitation occurs in the effort to establish useful biomarkers of disease, for diagnosis, for measuring efficacy of treatment, and for monitoring of disease recurrence. This limitation is largely responsible for the research community''s failure in recent years to bring forward significant numbers of new proteins as Food and Drug Administration approved diagnostic tests (2). However, if a robust, economical, and widely diffused capability to measure all human proteins existed, the research community would have the collective means to assess the utility of all human proteins as biomarkers in hundreds of diseases and other processes in the most efficient way.The need for new or improved biomarkers in many areas of healthcare has become critical. Early detection of cancer, coupled with surgical intervention, has the potential to radically improve survival (3), provided early markers exist and can be found. Without good biomarkers, degenerative diseases such as Alzheimer and chronic obstructive pulmonary disease (COPD) are difficult to detect early enough to benefit from the potential therapies. Clinical development of new drugs increasingly depends on identification of biomarkers for pharmacodynamic assessment of drug action to help guide dose and schedule, and predictive biomarkers for selection of patients who will benefit from therapy (4). Companion diagnostics are the currency of personalized medicine and represent those predictive or response biomarkers that are linked to specific therapeutics, substantially increasing their clinical value. Surrogate biomarkers (those biomarkers that substitute for a clinical outcome or response) are the most difficult to discover and to verify because of the long timeframe required but can radically shorten appropriate clinical trials. The impact of a vigorous increase in clinical biomarkers could thus be enormous, both in terms of patient well being and financial viability of healthcare systems worldwide.Protein measurements are also likely to play an important role in assessing the quality of material stored in large clinical sample collections (Biobanks). Much discussion has occurred recently regarding the value of banked samples because of unknown degrees of protein degradation occurring during acquisition, processing, and storage. This matter is of acute concern in the case of serum, where coagulation initiates a plethora of proteolytic cleavage events. The hPDQ may provide the opportunity to determine the value of each sample through the development of prototypic peptides tracking the stability of labile proteins.An attractive technology for achieving the objective of hPDQ is quantitative mass spectrometry, the sensitivity, and specificity of which are well established in the measurement of small molecules (5,6) and peptides (7,8). To achieve comprehensive quantitation of proteins, given the immense variability in their physical properties, these larger molecules are digested to component peptides using an enzyme such as trypsin, and protein amount is measured using proteotypic peptides (9,10) as specific stoichiometric surrogates. Multiple peptides from a target protein provide independent confirmation of this stoichiometry (equivalent to having multiple enzyme-linked immunosorbent assays with different antibody pairs), serving to control for the possibility of incomplete digestion or subsequent losses. Accurate calibration is achieved by spiking digested samples with known quantities of synthetic stable-isotope labeled peptides as internal standards (11,12). The sensitivity of this approach for multiplexed analysis of proteins in plasma has been extended from the microgram (13) to nanogram/ml levels by depletion of abundant proteins and limited peptide fractionation prior to analysis (14) or by capture of the subset of glycopeptides (15). Sensitivity and throughput of peptide MS measurements can be further increased to levels required in hPDQ by specific enrichment of the target peptides using anti-peptide antibodies. This method, called SISCAPA (for “stable isotope standards and capture by anti-peptide antibodies”) (16) or iMALDI (for immuno-MALDI) (17), combines the enhanced sensitivity of immunoassays with the specificity of mass spectrometry, while maintaining multiplexing capability. For these reasons we emphasize SISCAPA and iMALDI in this hPDQ proposal, although proteins in the 100 ng/ml or higher concentration are readily accessible by targeted MS in plasma without antibody enrichment. Combining these elements results in a measurement system, with the potential to measure 10–100 selected proteins at ng/ml levels in small (∼10 μl) samples of human plasma in a single short analytical run. Sensitivity can be further increased through the use of larger samples and/or advances in MS sensitivity. In comparison to the conventional ELISA approach, MS-based SISCAPA assays are less expensive to develop (one antibody instead of a carefully matched pair), easier to multiplex (off-target interactions being less likely with peptides than proteins), and provide absolute structural specificity (by reading the masses of multiple specific peptide fragments). This improved specificity solves a major problem plaguing clinical immunoassays for proteins such as thyroglobulin (18) and has led to the development of first clinical SISCAPA assay (19). In addition, since the mass spectrometer functions as a “second antibody” that identifies the captured peptides, the anti-peptide antibody used for peptide enrichment need not have perfect specificity. This greatly reduces the cost of affinity reagents, currently a limiting factor in developing ELISA assays for large numbers of protein analytes.Achieving the hPDQ goal by this approach would require that four resources be generally available. 1) A comprehensive database of proteotypic (protein-unique) peptides for each of the 21,500 human proteins (20), coupled with experimental or computational data identifying the best peptides for MS measurement and associated optimized MS instrument parameters. 2) At least two synthetic proteotypic peptides, labeled with stable isotope(s) and available in accurately quantitated aliquots, for use as internal measurement standards for quantitation of each protein. Such peptides are readily available today through custom order, at rapidly declining prices. 3) Anti-peptide antibodies specific for the same two proteotypic peptides per target protein, capable of binding the peptides with dissociation constants < 1e-9 (the level required in theory and practice to enrich low-abundance peptides from complex sample digests). Such antibodies are now being made for a variety of targets, and a robust production pipeline is being developed. Monoclonal antibodies would be preferred, despite their higher development cost, to establish a stable reagent supply, especially for those targets that prove useful as biomarkers. 4) Robust and affordable instrument platforms for quantitative analysis of small (amol to fmol) amounts of tryptic peptides and for sample preparation. Existing triple-quadrupole mass spectrometers (with a current worldwide installed base of more than 6,000 instruments) coupled with nanoflow (∼300–600 nl/min) liquid chromatography systems can meet this requirement and are undergoing rapid improvement with declining cost. MALDI platforms may provide similar capabilities at even higher throughput.We estimate that an initial pilot phase targeting 2,000 proteins selected for biomarker potential could be completed in two years at a cost of less than $50 million through funding of existing academic and commercial resources in a distributed network. In the following five years, the remaining 18,500 proteins could be targeted for $250 million, making use of anticipated technical improvements, particularly in the strategies for generating suitable high affinity monoclonal antibodies (21) in large numbers at low cost (22).Although the natural mechanism for providing the hPDQ database (resource 1 above) is through an academic collaboration, perhaps modeled on the successful Global Protein Machine (23) and Peptide Atlas (24) databases, the other resources would benefit from commercial distribution by experienced providers of instruments and reagents. The required instrument platforms (4 above) serve existing markets, and their further development is unlikely to require additional funding for hPDQ applications. However, business economics does not presently justify the expense of developing well characterized antibodies and peptides for quantitation of proteins that are not already recognized as pivotal in biological research (i.e. precisely those in need of the attention of the research community). Hence a substantial portion of the required funding for the proposed approach for such antibody and peptide reagents will be needed from government and philanthropic sources. A significant advantage of such diversified support would be the leverage it would provide in retaining in the public domain the identities of the selected peptides, their parameters and basic measurement protocols.The value of a general protein measurement capability for research is very substantial, but the proposed effort would not solve several larger issues that must await definition of a broader human proteome program. For example, the hPDQ project does not address the basic process of de novo proteome-wide discovery; the comprehensive exploration of splice forms, post-translational modifications, active fragments of preproteins or genetic variants (although once known, most of these can be targeted by the methods used here); interactions among proteins or with other molecules; or spatial arrangement of proteins in organs and tissues. Each of these areas would benefit from the resources proposed in hPDQ, but will likely require separate, coordinated large-scale efforts that are likely to identify additional sets of biomarkers. Thus although a complete suite of targeted assays is only a first step toward the complete human proteome, we feel that its fundamental importance for progress in biomarker research and its value as a foundation for protein quantitation justifies consideration as an initial step.In the beginning of the study of protein diagnostics, investigators at the Behring Institute discovered many of the well known plasma proteins and made associated specific antibodies and antibody-based quantitative tests available to the research community worldwide, spurring the initial round of plasma biomarker research. The application of monoclonal antibodies sparked additional discoveries through close coupling of protein “discovery” with simple quantitative monoclonal antibody-based assays - this “shortcut” to clinical measurement allowed investigators to publish more than 1,000 papers referring to the ovarian cancer marker CA125 (measured by ELISA) before the sequence of the protein was finally identified in 2001 (25). The broader proteomics technologies (beginning with the two-dimensional electrophoresis technology that formed the basis of the Human Protein Index Project (26) formulated by two of us almost 30 years ago, and extending to modern shotgun-style MS-based approaches) have radically expanded the universe of observable proteins. However, quantitative specific assay capabilities have not kept pace with this expansion, leading to the current gap between biomarker proteomics and clinical biomarker output. It is now time to address this gap and realize the benefits of a clinically accessible human proteome. Effective translation of basic research into tangible medical benefit requires it.     

17th Chromosome‐Centric Human Proteome Project Symposium in Tehran

This report describes the 17th Chromosome‐Centric Human Proteome Project which was held in Tehran, Iran, April 27 and 28, 2017. A brief summary of the symposium's talks including new technical and computational approaches for the identification of novel proteins from non‐coding genomic regions, physicochemical and biological causes of missing proteins, and the close interactions between Chromosome‐ and Biology/Disease‐driven Human Proteome Project are presented. A synopsis of decisions made on the prospective programs to maintain collaborative works, share resources and information, and establishment of a newly organized working group, the task force for missing protein analysis are discussed.     

Large-Scale Differential Proteome Analysis in Plasmodium falciparum under Drug Treatment

Proteome studies contribute markedly to our understanding of parasite biology, host-parasite interactions, and mechanisms of drug action. For most antimalarial drugs neither mode of action nor mechanisms of resistance development are fully elucidated although this would be important prerequisites for successfully developing urgently required novel antimalarials. Here, we establish a large-scale quantitative proteomic approach to examine protein expression changes in trophozoite stages of the malarial parasite Plasmodium falciparum following chloroquine and artemisinin treatment. For this purpose SIL (stable isotope labeling) using ¹⁴N-isoleucine and ¹³C₆,¹⁵N₁-isoleucine was optimized to obtain 99% atomic percent enrichment. Proteome fractionation with anion exchange chromatography was used to reduce sample complexity and increase quantitative coverage of protein expression. Tryptic peptides of subfractions were subjected to SCX/RP separation, measured by LC-MS/MS and quantified using the novel software tool Census. In drug treated parasites, we identified a total number of 1,253 proteins, thus increasing the overall number of proteins identified in the trophozoite stage by 30%. A relative quantification was obtained for more than 800 proteins. Under artemisinin and chloroquine treatment 41 and 38 proteins respectively were upregulated (>1.5) whereas 14 and 8 proteins were down-regulated (<0.5). Apart from specifically regulated proteins we also identified sets of proteins which were regulated as a general response to drug treatment. The proteomic data was confirmed by Western blotting. The methodology described here allows for the efficient large-scale differential proteome analysis of P. falciparum to study the response to drug treatment or environmental changes. Only 100 µg of protein is required for the analysis suggesting that the method can also be transferred to other apicomplexan parasites.     

7th HUPO World Congress of Proteomics: Launching the Second Phase of the HUPO Plasma Proteome Project (PPP‐2) 16–20 August 2008, Amsterdam,The Netherlands

The HUPO Plasma Proteome Project new phase, PPP‐2, held its initial workshop on 17 August, 2008, at the 7^th World Congress of Proteomics in Amsterdam. Technology platforms, data repositories, informatics, and engagement of research groups for the submission of major datasets were key topics. Plasma is expected to be the common pathway for biomarker development and application through collaboration and integration with other HUPO initiatives.     

血液蛋白质组学的研究技术及进展

人血液含有来源于几乎所有细胞、组织、器官的蛋白质,可以直接反映病理、生理状态,是各种疾病诊断、生物标志物发现的最有价值的标本。因此,长期以来,血浆蛋白质组一直是人们研究的热点,并被人类蛋白质组组织(HUPO)列为首批启动的重大国际合作研究项目。血浆蛋白质含量动态范围非常广、成分极其复杂,血浆蛋白质组的研究极富挑战性。近年来,血浆高丰度蛋白质去除、蛋白质/肽段分离、质谱鉴定、数据处理等多种相关技术都取得了很大的进展。本文简要综述了上述技术领域的研究和应用进展。     

Accentuate the Negative:Proteome Comparisons Using the Negative Proteome Database

The availability of complete genome sequence information for diverse organisms including model genetic organisms has ushered in a new era of protein sequence comparisons making it possible to search for commonalities among entire proteomes using the Basic Local Alignment Search Tool (BLAST). Although the identification and analysis of proteins shared by humans and model organisms has proven an invaluable tool to understanding gene function, the sets of proteins unique to a given model organism's proteome have remained largely unexplored. We have constructed a searchable database that allows biologists to identify proteins unique to a given proteome. The Negative Proteome Database (NPD) is populated with pair-wise protein sequence comparisons between each of the following proteomes: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Dictyostelium discoideum, Chlamydomonus reinhardti, Escherichia coli K12, Arabidopsis thaliana and Methanoscarcina acetivorans. Our analysis of negative proteome datasets using the NPD has thus far revealed 107 proteins in humans that may be involved in motile cilia function, 1628 potential pesticide target proteins in flies, 659 proteins shared by flies and humans that are not represented in the less neurologically complex worm proteome, and 180 nuclear encoded human disease associated proteins that are absent from the fly proteome. The NPD is the only online resource where users can quickly perform complex negative and positive comparisons of model organism proteomes. We anticipate that the NPD and the adaptable algorithm which can readily be used to duplicate this analysis on custom sets of proteomes will be an invaluable tool in the investigation of organism specific protein sets.     

Proteome profile of whole cerebellum of the mature rat

Cerebellum is an important brain region involved in motor, cognition, learning and memory functions. Proteome mapping of the 21 days old rat cerebellum identified total 285 proteins, out of which 76 proteins were not reported earlier from rat brain. This includes 49 neuronal activity-specific proteins, 7 of which are reported for the first time from the cerebellum in this study. The protein sequence data for 31 proteins reported here have been integrated in the UniProt Knowledgebase.     

The Human Eye Proteome Project: Perspectives on an emerging proteome

There are an estimated 285 million people with visual impairment worldwide, of whom 39 million are blind. The pathogenesis of many eye diseases remains poorly understood. The human eye is currently an emerging proteome that may provide key insight into the biological pathways of disease. We review proteomic investigations of the human eye and present a catalogue of 4842 nonredundant proteins identified in human eye tissues and biofluids to date. We highlight the need to identify new biomarkers for eye diseases using proteomics. Recent advances in proteomics do now allow the identification of hundreds to thousands of proteins in tissues and fluids, characterization of various PTMs and simultaneous quantification of multiple proteins. To facilitate proteomic studies of the eye, the Human Eye Proteome Project (HEPP) was organized in September 2012. The HEPP is one of the most recent components of the Biology/Disease‐driven Human Proteome Project (B/D‐HPP) whose overarching goal is to support the broad application of state‐of‐the‐art measurements of proteins and proteomes by life scientists studying the molecular mechanisms of biological processes and human disease. The large repertoire of investigative proteomic tools has great potential to transform vision science and enhance understanding of physiology and disease processes that affect sight.     

Proteome analysis of hepatocellular carcinoma

Development of hepatocellular carcinoma (HCC) is a complex process involving multiple changes in gene expression and usually occurs in the presence of liver cirrhosis. In this research, we observed proteome alterations of three tissue types isolated from livers of HCC patients: normal, cirrhotic, and tumorous tissue. Proteome alterations were observed using two-dimensional polyacrylamide gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Comparing the tissue types with each other, a significant change in expression level was found in 21 proteins. Of these proteins, sarcosine dehydrogenase, liver carboxylesterase, peptidyl-prolyl isomerase A, and lamin B1 are considered novel HCC marker candidates. In particular, lamin B1 may be considered as a marker for cirrhosis, because its expression level changes considerably in cirrhotic tissue compared with normal tissue. The proteins revealed in this experiment can be used in the future for studies pertaining to hepatocarcinogenesis, or as diagnostic markers and therapeutic targets for HCC.     

Heat Shock Protein Reports on Proteome Stress

Proper regulation of protein homeostasis (proteostasis) is essential to maintain cellular fitness. Proteome stress causes imbalance of the proteostasis, leading to various diseases represented by neurodegenerative diseases, cancers, and metabolic disorders. The biosensor community recently embarked on the development of proteome stress sensors to report on the integrity of proteostasis in live cells. While most of these sensors are based on metastable mutants of specific client proteins, a recent sensor takes advantage of the specific association of heat shock protein 27 with protein aggregates and exhibits a diffusive to punctate fluorescent change in cells that are subjected to stress conditions. Thus, heat shock proteins can be also used as a family of sensors to monitor proteome stress.     

Proteome microarray technology and application: higher,wider, and deeper

ABSTRACT

Introduction: Protein microarray is a powerful tool for both biological study and clinical research. The most useful features of protein microarrays are their miniaturized size (low reagent and sample consumption), high sensitivity and their capability for parallel/high-throughput analysis. The major focus of this review is functional proteome microarray.

Areas covered: For proteome microarray, this review will discuss some recently constructed proteome microarrays and new concepts that have been used for constructing proteome microarrays and data interpretation in past few years, such as PAGES, M-NAPPA strategy, VirD technology, and the first protein microarray database. this review will summarize recent proteomic scale applications and address the limitations and future directions of proteome microarray technology.

Expert opinion: Proteome microarray is a powerful tool for basic biological and clinical research. It is expected to see improvements in the currently used proteome microarrays and the construction of more proteome microarrays for other species by using traditional strategies or novel concepts. It is anticipated that the maximum number of features on a single microarray and the number of possible applications will be increased, and the information that can be obtained from proteome microarray experiments will more in-depth in the future.     

Comparative Analysis of Proteome and Transcriptome in Human Hepatocellular Carcinoma using 2D-DIGE and SAGE

Proteome analysis of human hepatocellular carcinoma was conducted using two-dimensional difference gel electrophoresis, and the protein expression profiles were compared to the mRNA expression profiles made from serial analysis of gene expression (SAGE) in identical samples from a single patient. Image-to-image analysis of protein abundances together with protein identification by peptide mass fingerprinting yielded the protein expression profiles. A total of 188 proteins were identified, and the expression profiles of 164 proteins which had the corresponding SAGE data were compared to the mRNA expression profiles. Among them, 40 proteins showed significant differences in the mRNA expression levels between non HCC and HCC. We compared expression changes of proteins with those of mRNAs. We found that the expression tendency of 24 proteins were similar to that of mRNA, whereas 16 proteins showed different or opposite tendency to the mRNA expression.     

Analysis of gene ontology features in microarray data using the Proteome BioKnowledge Library

Microarray technology has resulted in an explosion of complex, valuable data. Integrating data analysis tools with a comprehensive underlying database would allow efficient identification of common properties among differentially regulated genes. In this study we sought to compare the utility of various databases in microarray analysis. The Proteome BioKnowledge Library (BKL), a manually curated, proteome-wide compilation of the scientific literature, was used to generate a list of Gene Ontology (GO) Biological Process (BP) terms enriched among proteins involved in cardiovascular disease. Analysis of DNA microarray data generated in a study of rat vascular smooth muscle cell responses revealed significant enrichment in a number of GO BPs that were also enriched among cardiovascular disease-related proteins. Using annotation from LocusLink and chip annotation from the Gene Expression Omnibus yielded fewer enriched cardiovascular disease-associated GO BP terms. Data sets of orthologous genes from mouse and human were generated using the BKL Retriever. Analysis of these sets focusing on BKL Disease annotation, revealed a significant association of these genes with cardiovascular disease. These results and the extensive presence of experimental evidence for BKL GO and Disease features, underscore the benefits of using this database for microarray analysis.     

Standard guidelines for the chromosome-centric human proteome project

The objective of the international Chromosome-Centric Human Proteome Project (C-HPP) is to map and annotate all proteins encoded by the genes on each human chromosome. The C-HPP consortium was established to organize a collaborative network among the research teams responsible for protein mapping of individual chromosomes and to identify compelling biological and genetic mechanisms influencing colocated genes and their protein products. The C-HPP aims to foster the development of proteome analysis and integration of the findings from related molecular -omics technology platforms through collaborations among universities, industries, and private research groups. The C-HPP consortium leadership has elicited broad input for standard guidelines to manage these international efforts more efficiently by mobilizing existing resources and collaborative networks. The C-HPP guidelines set out the collaborative consensus of the C-HPP teams, introduce topics associated with experimental approaches, data production, quality control, treatment, and transparency of data, governance of the consortium, and collaborative benefits. A companion approach for the Biology and Disease-Driven HPP (B/D-HPP) component of the Human Proteome Project is currently being organized, building upon the Human Proteome Organization's organ-based and biofluid-based initiatives (www.hupo.org/research). The common application of these guidelines in the participating laboratories is expected to facilitate the goal of a comprehensive analysis of the human proteome.     

Proteome Analysis Database: online application of InterPro and CluSTr for the functional classification of proteins in whole genomes

The SWISS-PROT group at EBI has developed the Proteome Analysis Database utilising existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archaea and eukaryotes (http://www.ebi.ac. uk/proteome/). The two main projects used, InterPro and CluSTr, give a new perspective on families, domains and sites and cover 31-67% (InterPro statistics) of the proteins from each of the complete genomes. CluSTr covers the three complete eukaryotic genomes and the incomplete human genome data. The Proteome Analysis Database is accompanied by a program that has been designed to carry out InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.