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Protein Arrays and Their Role in Proteomics
Abstract
Arraying technologies have shown the way to smaller sample volumes, more efficient analyses and higher throughput. Proteomics is a field, which has grown in significance in the last five years. This review outlines recent developments in protein arrays and their applications in proteomics, and discusses the requirements, current limitations and the potential and future perspectives of the technology.
... For the purpose of this review, metabolite profiling will be referred to as metabolomics from here on. In contrast with transcriptomics, proteomics and metabolomics are not yet routine and standardized procedures, and continue to face challenges such as sample preparation, technological sensitivity, lack of standardized statistical methods and public databases (13)(14)(15)(16)(17)(18). Nevertheless, their potential benefits for health management are undisputed and have fuelled current efforts to assess, utilize, interpret, and ultimately integrate these global technologies in order to define a phenotype characterizing health status. ...
The recognition that nutrients have the ability to interact and modulate molecular mechanisms underlying an organism's physiological functions has prompted a revolution in the field of nutrition. Performing population-scaled epidemiological studies in the absence of genetic knowledge may result in erroneous scientific conclusions and misinformed nutritional recommendations. To circumvent such issues and more comprehensively probe the relationship between genes and diet, the field of nutrition has begun to capitalize on both the technologies and supporting analytical software brought forth in the post-genomic era. The creation of nutrigenomics and nutrigenetics, two fields with distinct approaches to elucidate the interaction between diet and genes but with a common ultimate goal to optimize health through the personalization of diet, provide powerful approaches to unravel the complex relationship between nutritional molecules, genetic polymorphisms, and the biological system as a whole. Reluctance to embrace these new fields exists primarily due to the fear that producing overwhelming quantities of biological data within the confines of a single study will submerge the original query; however, the current review aims to position nutrigenomics and nutrigenetics as the emerging faces of nutrition that, when considered with more classical approaches, will provide the necessary stepping stones to achieve the ambitious goal of optimizing an individual's health via nutritional intervention.
... These technologies require large amounts of input material, and need good ways to identify markers. To overcome those shortcomings, various protein microarray technologies have been developed (Cahill et al., 2003;Ivanov et al., 2004;MacBeath and Schreiber, 2000). ...
Proteins play a crucial role in biological activity, so much can be learned from measuring protein expression and post-translational modification quantitatively. The reverse-phase protein lysate arrays allow us to quantify the relative expression levels of a protein in many different cellular samples simultaneously. Existing approaches to quantify protein arrays use parametric response curves fit to dilution series data. The results can be biased when the parametric function does not fit the data.
We propose a non-parametric approach which adapts to any monotone response curve. The non-parametric approach is shown to be promising via both simulation and real data studies; it reduces the bias due to model misspecification and protects against outliers in the data. The non-parametric approach enables more reliable quantification of protein lysate arrays.
Code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/jhu/lysatearray-analysis/
... These technologies have limitations on their speed, sensitivity, throughput, and reproducibility [6]. Extensive studies have been conducted to develop protein arrays for protein expression and functional analysis [7][8][9][10][11][12][13]. The protein arrays are designed based on the physical and chemical interactions between known proteins and other proteins or nonprotein materials [14][15][16]. ...
A number of different ligands have been tested in the course of the development of protein array technology. The most extensively studied example of protein ligands has been based on antibody-antigen interaction. Other examples include protein-protein, protein-nucleic acid, and protein-small molecule interactions. All these ligands can recognize and specifically bind to protein epitopes. In this study, we have developed a novel technology using DNA-based aptamers to detect proteins based on their amino acid sequences. Mouse cathepsin D was used for the proof of principle experiment. Four tripeptides, Leu-Ala-Ser, Asp-Gly-Ile, Gly-Glu-Leu, and Lys-Ala-Ile, were selected based on the published amino acid sequence of mouse cathepsin D. DNA aptamers against the tripeptides were isolated using the systematic evolution of ligands of exponential enrichment method. We have demonstrated that the aptamers specifically interacted with mouse cathepsin D using the structure-switch method. We further performed a proximity-dependent ligation assay to demonstrate that multiple aptamers could specifically detect the protein from cell extracts. In principle, one library containing 8000 aptamers should be enough to detect almost all proteins in the whole proteome in all organisms. This technology could be applied to generate a new generation of protein arrays.
... Using extensive molecular catalogues and powerful mathematical software to objectively probe massive biological datasets, various analytical platforms will provide requisite and complementary information implicit in unraveling the mechanisms underlying metabolic disorders; however, these platforms are advancing at distinctly different rates. Whereas transcriptomics has benefited from the complete sequencing and annotation of several mammalian genomes [1][2][3][4][5], standardized methods for archiving data [6,7] and bioinformatic tools to ease the interpretation of these massive datasets, proteomics and metabolomics are not yet routine and standardized procedures, and continue to face challenges such as sample preparation, technological sensitivity, lack of standardized biomathematical analysis, and publicly interpretable databases, etc. [8][9][10][11][12]. Nevertheless, their potential benefits for BIOTECHNOLOGY ANNUAL REVIEW VOLUME 12 ISSN 1387-2656 DOI: 10.1016/S1387-2656(06)12003-7 r 2006 ELSEVIER B.V. ALL RIGHTS RESERVED health management are recognized and fuel the current effort to utilize and integrate these global technologies with the goal to more accurately define a phenotype characterizing health status [13,14]. ...
The recognition that altered lipid metabolism underlies many metabolic disorders challenging Western society highlights the importance of this metabolomic subset, herein referred to as the lipidome. Although comprehensive lipid analyses are not a recent concept, the novelty of a lipidomic approach lies with the application of robust statistical algorithms to highlight subtle, yet significant, changes in a population of lipid molecules. First-generation lipidomic studies have demonstrated the sensitivity of interpreting quantitative datasets with computational software; however, the innate power of comprehensive lipid profiling is often not exploited, as robust statistical models are not routinely utilized. Therefore, the current review aims to briefly describe the current technologies suitable for comprehensive lipid analysis, outline innovative mathematical models that have the ability to reveal subtle changes in metabolism, which will ameliorate our understanding of lipid biochemistry, and demonstrate the biological revelations found through lipidomic approaches and their potential implications for health management.
... Fusion proteins with a common 6ÂHistidine tag are overexpressed in E. coli, before the bacterial colonies are spotted onto membranes. With the help of an anti-histidine antibody, E. coli colonies are re-arrayed to create a library, which exclusively contains cells expressing His-tagged fusion proteins (for review see Cahill and Nordhoff, 2003). This enables to screen for epitopes recognized by specific antibodies or by autoantibodies in human patient sera. ...
Whole-genome analyses become more and more necessary for pharmaceutical research. DNA chip hybridizations are an important tool for monitoring gene expression profiles during diseases or medical treatment. However, drug target identification and validation as well as an increasing number of antibodies and other polypeptides tested as potential drugs produce an increasing demand for genome-wide functional assays. Protein arrays are an important step into this direction. Peptide arrays and protein expression libraries are useful for the identification of antibodies and for epitope mapping. Antibody arrays allow protein quantification, protein binding studies, and protein phosphorylation assays. Tissue micro-arrays give a detailed information about the localization of macromolecules. More complex interactions can be addressed in cells spotted in array format. Finally, microfluidics chips enable us to describe the communication between cells in a tissue. In this review, possibilities, limitations and chances of different protein array techniques are discussed.
... With the completion of several genome projects, attention has turned to the elucidation of the functional activities of the encoded proteins. Due to the enormous number of newly discovered open reading frames (ORF), progress in the analysis of the corresponding proteins depends on the ability to perform characterization in a parallel and high throughput (HTS) format (Cahill and Nordhoff 2003). This typically involves construction of protein arrays based on recombinant proteins. ...
Enzymes are biocatalysts evolved in nature to achieve the speed and coordination of nearly all the chemical reactions that define cellular metabolism necessary to develop and maintain life. The application of biocatalysis is growing rapidly, since enzymes offer potential for many exciting applications in industry. The advent of whole genome sequencing projects enabled new approaches for biocatalyst development, based on specialised methods for enzyme heterologous expression and engineering. The engineering of enzymes with altered activity, specificity and stability, using sitedirected mutagenesis and directed evolution techniques are now well established. Over the last decade, enzyme immobilisation has become important in industry. New methods and techniques for enzyme immobilisation allow for the reuse of the catalysts and the development of efficient biotechnological processes. This chapter reviews advances in enzyme technology as well as in the techniques and strategies used for enzyme production, engineering and immobilisation and discuss their advantages and disadvantages.
... The detection and/or quantification of the biomarker can be accomplished using either a second antibody (or chemical moiety) to the same protein (currently the most common setup for clinical laboratory immunoassays) or other physical means including mass spectrometry. The development and testing of protein chips for biomarker analysis is a rapidly growing field, and how they eventually will be incorporated into the diagnostics arena is still unknown [8,20,25]. The development of many of the components of protein arrays such as immobilization strategies [24]; fabrication and support [30,32]; sensors [28,37] and the use of microfluidic systems [6] or capillary electrophoresis/MS methods [33] have to be enhanced before protein chips can become a mainstream technology. ...
Heart disease is the leading cause of mortality and morbidity in the world. As such, biomarkers are needed for the diagnosis, prognosis, therapeutic monitoring and risk stratification of acute injury (acute myocardial infarction (AMI)) and chronic disease (heart failure). The procedure for biomarker development involves the discovery, validation, and translation into clinical practice of a panel of candidate proteins to monitor risk of heart disease. Two types of biomarkers are possible; heart-specific and cardiovascular pulmonary system monitoring markers. Here we review the use of MS in the process of cardiac biomarker discovery and validation by proteomic analysis of cardiac myocytes/tissue or serum/plasma. An example of the use of MS in biomarker discovery is given in which the albumin binding protein sub-proteome was examined using MALDI-TOF MS/MS. Additionally, an example of MS in protein validation is given using affinity surface enhanced laser desorption ionization (SELDI) to monitor the disease-induced post-translational modification and the ternary status of myocyte-originating protein, cardiac troponin I in serum.
... The sequences themselves provide a wealth of information, but functional annotation is a necessary step toward comprehensive description of genetic systems of cellular controls, including those whose malfunctioning becomes the basis of genetic disorders such as cancer (Kitano, 2002;Steinmetz and Deutschbauer, 2002;Ideker, Galitski and Hood, 2001). High-throughput functional technologies, such as genomic (Lipshutz et al., 1999;Schena et al., 1995) and soon proteomic microarrays (Cahill and Nordhoff, 2003;Sydor and Nock, 2003;Oleinikov et al., 2003;Huang, 2003;Cutler, 2003), allow one to rapidly assess general functions and interactions of proteins in the cell. While classical genetic and cell biology techniques continue to play an important role in the detailed understanding of cellular mechanisms, the combination of rapid functional annotation with targeted exploration by traditional methods will facilitate fast and accurate identification of causal genes and key pathways affected in disease. ...
The broad range of genome sequencing projects and large-scale experimental characterization techniques are responsible for the rapid accumulation of biological data. A range of data-mining techniques have been developed to handle this tremendous data overload. Experimentally produced data obtained by large-scale protein interaction experiments imply a large variability of information types. Information related to the protein and gene sequences, structures and functions, as well as interaction complexes and pathways, is produced with powerful experimental approaches and published in the form of scientific articles. The scientific text constitutes the primary source of functional information not only for single researchers, but also for the annotation of databases. To be able to handle all this information it is important to link gene and protein sequences with the available functional information deposited in the biomedical literature, where the experimental evidence is described in detail. The emerging field of biomedical text mining has provided the first generation of methods and tools to extract and analyze collections of genes, functions and interactions. Here we describe the current status, possibilities and limitations offered by those methods and their relation with the corresponding areas of molecular biology, with particular attention to the analysis of protein interaction networks. References
... Protein microarray technologies [e.g. Cahill and Nordhoff (2003); Ivanov et al. (2004); MacBeath and Schreiber (2000)] have been developed to measure protein concentrations in a high-throughput fashion. Extensive reviews of this technology can be found in Borrebaeck and Wingren (2007) and Poetz et al. (2005). ...
The reverse-phase protein lysate arrays have been used to quantify the relative expression levels of a protein in a number of cellular samples simultaneously. To avoid quantification bias due to mis-specification of commonly used parametric models, a nonparametric approach based on monotone response curves may be used. The existing methods, however, aggregate the protein concentration levels of replicates of each sample, and therefore fail to account for within-sample variability.
We propose a method of regularization on protein concentration estimation at the level of individual dilution series to account for within-sample or within-group variability. We use an efficient algorithm to optimize an approximate objective function, with a data-adaptive approach to choose the level of shrinkage. Simulation results show that the proposed method quantifies protein concentration levels well. We show through the analysis of protein lysate array data from cell lines of different cancer groups that accounting for within-sample variability leads to better statistical analysis.
Code written in statistical programming language R is available at: http://odin.mdacc.tmc.edu/~jhhu/Reno
... Protein microarray technology has become a useful tool in the discovery of novel protein-protein interactions, providing a method of capturing thousands of proteins in ordered arrays [21][22][23][24][25][26]. The use of microarrays has several advantages. ...
Low-affinity extracellular protein interactions are critical for cellular recognition processes, but existing methods to detect them are limited in scale, making genome-wide interaction screens technically challenging. To address this, we report here the miniaturization of the AVEXIS (avidity-based extracellular interaction screen) assay by using protein microarray technology. To achieve this, we have developed protein tags and sample preparation methods that enable the parallel purification of hundreds of recombinant proteins expressed in mammalian cells. We benchmarked the protein microarray-based assay against a set of known quantified receptor-ligand pairs and show that it is sensitive enough to detect even very weak interactions that are typical of this class of interactions. The increase in scale enables interaction screening against a dilution series of immobilized proteins on the microarray enabling the observation of saturation binding behaviors to show interaction specificity and also the estimation of interaction affinities directly from the primary screen. These methodological improvements now permit screening for novel extracellular receptor-ligand interactions on a genome-wide scale.
... Interactive analysis by biology and bioinformatics researchers is critical in extracting biological information from both genomic [1], [2] and proteomic [3], [4], [5], [6], [7] microarrays. Many supervised and unsupervised microarray analysis techniques have been developed [8], [9], [10], [11], and the majority of these techniques share a common need for visual, interactive evaluation of results to examine important patterns, explore interesting genes, or consider key predictions and their biological context. ...
Microarray experiments can provide molecular-level insight into a variety of biological processes, from yeast cell cycle to tumorogenesis. However, analysis of both genomic and protein microarray data requires interactive collaborative investigation by biology and bioinformatics researchers. To assist collaborative analysis, remote collaboration tools for integrative analysis and visualization of microarray data are necessary. Such tools should: (i) provide fast response times when used with visualization- intensive genomics applications over a low-bandwidth wide area network, (ii) eliminate transfer of large and often sensitive datasets, (iii) work with any analysis software, and (iv) be platform-independent. Existing visualization systems do not satisfy all requirements. We have developed a remote visualization system called Varg that extends the platform-independent remote desktop system VNC with a novel global compression method. Our evaluations show that the Varg system can support interactive visualization-intensive genomic applications in a remote environment by reducing bandwidth requirements from 30:1 to 289:1.
... Thus, sensitivity comparable to or exceeding ELISA can be achieved on microarrays using only a fraction (down to 1/1000 th ) of the sample size required for ELISA. The advantage gained by miniaturization, high sensitivity, and high throughput makes protein microarrays a potentially powerful technology for discovery of new markers and detection of known protein markers [14][15][16][17][18][19][20]. ...
This study presents the development and application of protein lysate microarray (LMA) technology for verification of presence and quantification of human tissue samples for protein biomarkers. Sub-picogram range sensitivity has been achieved on LMA using a non-enzymatic protein detection methodology. Results from a set of quality control experiments are presented and demonstrate the high sensitivity and reproducibility of the LMA methodology. The optimized LMA methodology has been applied for verification of the presence and quantification of disease markers for atherosclerosis. LMA were used to measure lipoprotein [a] and apolipoprotein B100 in 52 carotid endarterectomy samples. The data generated by LMA were validated by ELISA using the same protein lysates. The correlations of protein amounts estimated by LMA and ELISA were highly significant, with r2 > or = 0.98 (p < or = 0.001) for lipoprotein [a] and with r2 > or = 0.94 (p < or = 0.001) for apolipoprotein B100. This is the first report to compare data generated using proteins microarrays with ELISA, a standard technology for the verification of the presence of protein biomarkers. The sensitivity, reproducibility, and high-throughput quality of LMA technology make it a potentially powerful technology for profiling disease specific protein markers in clinical samples.
N-glycosylation of proteins is the predominant glycosylation in mammals and confers specific conformations, localization, and functions to proteins. High-throughput proteomics techniques have focused on the identification of proteins through amino acid sequence determination, with little attention paid to their post-translational modification, in particular, glycosylation. High-throughput mass spectrometric data often contain information about glycosylation, but this is systematically discarded by proteomic search engines. We have developed an algorithm, StrOligo (for STRucture of OLIGOsaccharides), capable of automated analysis of oligosaccharide composition and possible structures by mass spectrometry. The algorithm analyzes tandem mass spectrometry (MS/MS) data in an automated three-step process and provides possible structures and a discrimination score. In the first step, the algorithm constructs a relationship tree of the monosaccharide moiety losses observed in the MS/MS spectrum. In the second step, the algorithm uses the tree to propose possible compositions and structures from combinations of adduct and fragment ions as well as a discrimination score, which reflects the fit with the experimental results. Finally, an interface is available to visualize the proposed structures and their scores. As well, the MS/MS spectrum is displayed with relevant peaks labeled for the proposed structure with the highest discrimination score, using a modified nomenclature.
The availability of extensive genomic information and content has spawned an era of high-throughput screening that is generating large sets of functional genomic data. In particular, the need to understand the biochemical wiring within a cell has introduced novel approaches to map the intricate networks of biological interactions arising from the interactions of proteins. The current technologies for assaying protein interactions--yeast two-hybrid and immunoprecipitation with mass spectrometric detection--have met with considerable success. However, the parallel use of these approaches has identified only a small fraction of physiologically relevant interactions among proteins, neglecting all nonprotein interactions, such as with metabolites, lipids, DNA and small molecules. This highlights the need for further development of proteome scale technologies that enable the study of protein function. Here we discuss recent advances in high-throughput technologies for displaying proteins on functional protein microarrays and the real-time label-free detection of interactions using probes of the local index of refraction, carbon nanotubes and nanowires, or microelectromechanical systems cantilevers. The combination of these technologies will facilitate the large-scale study of protein interactions with proteins as well as with other biomolecules.
Dilated cardiomyopathy (DCM) is a myocardial disease characterized by progressive depression of myocardial contractile function and ventricular dilatation. Thirty percent of DCM patients belong to the inherited genetic form; the rest may be idiopathic, viral, autoimmune, or immune-mediated associated with a viral infection. Disturbances in humoral and cellular immunity have been described in cases of myocarditis and DCM. A number of autoantibodies against cardiac cell proteins have been identified in DCM. In this study, we have profiled the autoantibody repertoire of plasma from DCM patients against a human protein array consisting of 37,200 redundant, recombinant human proteins and performed qualitative and quantitative validation of these putative autoantigens on protein microarrays to identify novel putative DCM specific autoantigens. In addition to analyzing the whole IgG autoantibody repertoire, we have also analyzed the IgG3 antibody repertoire in the plasma samples to study the characteristics of IgG3 subclass antibodies. By combining screening of a protein expression library with protein microarray technology, we have detected 26 proteins identified by the IgG antibody repertoire and 6 proteins bound by the IgG3 subclass. Several of these autoantibodies found in plasma of DCM patients, such as the autoantibody against the Kv channel-interacting protein, are associated with heart failure.
This chapter describes the use of an open-source, freely available informatics system for the identification of proteins using tandem mass spectra of peptides derived from an enzymatic digest of a mixture of mature proteins. The chapter describes the use of features of the Global Proteome Machine (GPM) interface that assist in making comprehensive assignments between spectra and sequences, including the detection of point mutations, posttranslational modifications, and experimental artifacts. The use of this interface to validate results using the GPM Database is also described. This data repository allows analysts to compare their own results to those obtained by other scientists to determine the degree to which their data are consistent with previous measurements.
Microarray experiments can provide molecular-level insight into a variety of biological processes, from yeast cell cycle to tumorogenesis. However, analysis of both genomic and protein microarray data requires interactive collaborative investigation by biology and bioinformatics researchers. To assist collaborative analysis, remote collaboration tools for integrative analysis and visualization of microarray data are necessary. Such tools should: (i) provide fast response times when used with visualization-intensive genomics applications over a low-bandwidth wide area network, (ii) eliminate transfer of large and often sensitive datasets, (iii) work with any analysis software, and (iv) be platform-independent. Existing visualization systems do not satisfy all requirements. We have developed a remote visualization system called Varg that extends the platform-independent remote desktop system VNC with a novel global compression method. Our evaluations show that the Varg system can support interactive visualization-intensive genomic applications in a remote environment by reducing bandwidth requirements from 30:1 to 289:1.
Protein glycosylation has long been recognized as a very common posttranslational modification. Protein glycosylation is prevalent in proteins destined for extracellular environments. These include proteins localized on the extracellular surface and those secreted to body fluids. In search of a method that has the potential to identify and quantify most proteins found in body fluids or the cell surface, we have recently developed a novel method for solid-phase extraction of formerly N-linked glycosylated peptides from glycoproteins. It has been shown that proteins secreted to body fluids or localized on the cell surface can be specifically enriched by this method. The technique is based on the conjugation of glycoproteins to a solid support using hydrazide chemistry, removal of nonglycosylated peptides by trypsin digestion, stable isotope labeling of glycopeptides, and the specific release of formerly N-linked glycosylated peptides via peptide-N-glycosidase. The recovered formerly N-linked glycopeptides are then identified and quantified by tandem mass spectrometry.
Multidimensional chromatography coupled to mass spectrometry is an emerging technique for the analysis of complex protein mixtures. One approach in this general category, multidimensional protein identification technology (MudPIT), couples biphasic or triphasic microcapillary columns to high-performance liquid chromatography, tandem mass spectrometry, and database searching. The integration of each of these components is critical to the implementation of MudPIT in a laboratory. MudPIT can be used for the analysis of complex peptide mixtures generated from biofluids, tissues, cells, organelles, or protein complexes. The information described in this chapter will provide researchers with details for sample preparation, column assembly, and chromatography parameters for complex peptide mixture analysis.
An important goal in proteomics is to compare the relative amounts of different proteins in biological samples and to try to correlate these differences with changes in physiological state. The isotopecoded affinity tag technique pioneered in Aebersold's laboratory takes advantage of differential tagging of cysteine residues in proteins with stable isotopes to significantly reduce the complexity of peptide mixtures and increase the number of sequences that are identified in a single tandem mass spectrometry experiment. In this approach, two samples are isotopically labeled (one heavy, one light) through a reactive group that specifically binds to cysteine residues; the samples are combined, separated with chromatography, and analyzed by mass spectrometry. The results are then database searched and a list of hundreds of proteins and their heavy:light ratio is obtained.
The importance of regulatory control in metabolic processes is widely acknowledged, and several enquiries (both local and global) are being made in understanding regulation at various levels of the metabolic hierarchy. The wealth of biological information has enabled identifying the individual components (genes, proteins, and metabolites) of a biological system, and we are now in a position to understand the interactions between these components. Since phenotype is the net result of these interactions, it is immensely important to elucidate them not only for an integrated understanding of physiology, but also for practical applications of using biological systems as cell factories. We present some of the recent "-omics" approaches that have expanded our understanding of regulation at the gene, protein, and metabolite level, followed by analysis of the impact of this progress on the advancement of metabolic engineering. Although this review is by no means exhaustive, we attempt to convey our ideology that combining global information from various levels of metabolic hierarchy is absolutely essential in understanding and subsequently predicting the relationship between changes in gene expression and the resulting phenotype. The ultimate aim of this review is to provide metabolic engineers with an overview of recent advances in complementary aspects of regulation at the gene, protein, and metabolite level and those involved in fundamental research with potential hurdles in the path to implementing their discoveries in practical applications.
Size-exclusion chromatography (SEC), coupled with "on-line" static laser light scattering (LS), refractive index (RI), and ultraviolet (UV) detection, provides a universal approach for determination of the molar mass and oligomeric state in solution of native proteins as well as glycosylated proteins or membrane proteins solubilized in non-ionic detergents. Such glycosylated proteins or protein-detergent complexes show anomalous behavior on SEC, thus presenting a challenge to determination of molar mass and oligomeric state in solution. In the SEC-UV/LS/RI approach, SEC serves solely as a fractionation step, while the responses from the three detectors are utilized to calculate the molar mass for the polypeptide portion of the native or modified protein. The amount of sugar, lipid, or detergent bound to the polypeptide chain can also be estimated from the SEC-UV/LS/RI analysis.
Proteolysis is a key mechanism for protein homeostasis in living cells. This process is effected by different classes of proteases. The proteasome is one of the most abundant and versatile proteases, bearing three different proteolytic active sites. The proteasome plays an important role in essential biological pathways such as antigen presentation, signal transduction, and cell-cycle control feedback loops. The aim of this work is to design novel chemical strategies for capturing, detection, identification, and quantification--in one word, profiling--the active protease fractions of interest, in cells of different phenotypes. Here, a set of chemistry-based functional proteomics techniques is demonstrated by profiling the multi-catalytic protease activities of the proteasome. Importantly, functional profiling is complementary to expression level profiling and is an indispensable parameter for better understanding of mechanisms underlying biological processes.
Antibody microarray measurements show great potential for the simultaneous quantification of many proteins in small amounts of body fluids and extracts. Over the last few years, a micro-array platform centered around the concept of microarrays in microtiter wells was developed, and for the best assays we have achieved lower limits of detection in the femtomolar range using resonance light-scattering particles for the staining of biotinylated detection antibodies. Although conceptually simple, these multiplexed sandwich assays are technically challenging. Here we describe in detail our protocols and procedures for the manufacturing of antibody microarrays with up to 48 different antibodies and for performing plasma measurements.
Protein microarrays are a miniaturized format for displaying in close spatial density hundreds or thousands of purified proteins that provide a powerful platform for the high-throughput assay of protein function. The traditional method of producing them requires the high-throughput production and printing of proteins, a laborious method that raises concerns about the stability of the proteins and the shelf life of the arrays. A novel method of producing protein microarrays, called nucleic acid programmable protein array (NAPPA), overcomes these limitations by synthesizing proteins in situ. NAPPA entails spotting plasmid DNA encoding the relevant proteins, which are then simultaneously transcribed and translated by a cell-free system. The expressed proteins are captured and oriented at the site of expression by a capture reagent that targets a fusion protein on either the N- or C-terminus of the protein. Using a mammalian extract, NAPPA expresses and captures 1000-fold more protein per feature than conventional protein-printing arrays. Moreover, this approach minimizes concerns about protein stability and integrity, because proteins are produced just in time for assaying. NAPPA has already proven to be a robust tool for protein functional assays.
The combination of surface plasmon pesonance (SPR) and mass spectrometry (MS) provides a unique methodology for studying proteins and their interactions. SPR is utilized to assess protein quantitative variations and the kinetic aspects of protein interactions, whereas MS complements the analysis by providing an exclusive look at the structural features of the interacting proteins via measurement of their mass. Thus, intrinsic protein structural modifications that go unregistered via the SPR detection can readily be assessed from the MS data. The purpose of this chapter is dissemination of the procedures and protocols for successful SPR-MS analysis. The individual steps of the complete SPRMS process are illustrated via analysis of cardiac troponin I (cTnI).
A primary objective of many protein expression studies is to define expression patterns that can distinguish between normal and diseased states, enabling a better understanding of molecular events associated with disease development and progression and ultimately potentially finding novel markers or therapeutic targets. Exploration and confirmation of many proteins is often done using Western blotting with normalization against "housekeeping proteins", such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH), beta-actin, or beta-tubulin, to correct for protein loading and factors, such as transfer efficiency. Increasingly, in studies examining gene transcript levels, it has been shown that some of the commonly used housekeeping genes may be unsuitable due to the influence of various physiological and pathological factors on their expression. This has not been examined to any great extent for proteins, however. This study examines the degree of variability of three commonly used "housekeeping" proteins (GAPDH, beta-actin, and beta-tubulin) together with class I beta-tubulin, with comparisons being made between a number of different established renal cancer cell lines, matched pairs of renal tumor and normal kidney lysates as well as nine different human tissues and highlights some of the problems encountered.
Protein biochips have a great potential in future parallel processing of complex samples as a research tool and in diagnostics. For the generation of protein biochips, highly automated technologies have been developed for cDNA expression library production, high throughput protein expression, large scale analysis of proteins, and protein microarray generation. Using this technology, we present here a strategy to identify potential autoantigens involved in the pathogenesis of alopecia areata, an often chronic disease leading to the rapid loss of scalp hair. Only little is known about the putative autoantigen(s) involved in this process. By combining protein microarray technology with the use of large cDNA expression libraries, we profiled the autoantibody repertoire of sera from alopecia areata patients against a human protein array consisting of 37,200 redundant, recombinant human proteins. The data sets obtained from incubations with patient sera were compared with control sera from clinically healthy persons and to background incubations with anti-human IgG antibodies. From these results, a smaller protein subset was generated and subjected to qualitative and quantitative validation on highly sensitive protein microarrays to identify novel alopecia areata-associated autoantigens. Eight autoantigens were identified by protein chip technology and were successfully confirmed by Western blot analysis. These autoantigens were arrayed on protein microarrays to generate a disease-associated protein chip. To confirm the specificity of the results obtained, sera from patients with psoriasis or hand and foot eczema as well as skin allergy were additionally examined on the disease-associated protein chip. By using alopecia areata as a model for an autoimmune disease, our investigations show that the protein microarray technology has potential for the identification and evaluation of autoantigens as well as in diagnosis such as to differentiate alopecia areata from other skin diseases.
Technological advances in the field of microarray production and analysis lead to the development of protein microarrays. Of these, antigen microarrays are one particular format that allows the study of antigen-antibody interactions in a miniaturized and highly multiplexed fashion. Here, we describe the parallel detection of antibodies with different specificities in human serum, a procedure also called antibody profiling. Autoantigens printed on microarray slides are reacted with test sera and the bound antibodies are identified by fluorescently labeled secondary reagents. Reactivity patterns generated this way characterize individuals and can help design novel diagnostic tools.
Protein microarrays allow for the parallel analysis of a large number of proteins with respect to their abundance or activity and, therefore, are playing an emerging role in proteome research.Protein expression profiling, detection of enzymatic activity and protein interaction mapping are the most important applications of protein microarrays. The biological content, as well as the detection strategies, vary significantly between these applications, making the protein microarray technologies much more varied than those used with DNA microarrays.In most cases, the biological content on the microarray, as well as the analytes, are proteins, which, due to their delicate nature and the heterogeneity of their properties, complicate the manufacturing and assay design. The potential advantages of protein microarrays over nonparallel, macroscopic technologies cannot, however, be overestimated.Keywords:Capture Agents;Enzyme Activity Profiling;Multiplexed Protein Assay;Protein Expression Profiling;Protein Interaction Profiling;Protein Microarray
Ayurveda proclaims food and drugs are intersecting concepts that are vital for human survival and for the prevention and mitigation of diseases. Food interferes with the molecular mechanisms of an organism's “physiome”. It is consumed in large amounts compared to any drug. Hence, research on its effect and interaction with genome is highly relevant toward understanding diseases and their therapies. Ayurgenomics presents a personalized approach in the predictive, preventive, and curative aspects of stratified medicine with molecular variability, which embodies the study of interindividual variability due to genetic variability in humans for assessing susceptibility, and establishing diagnosis and prognosis, mainly on the basis of the constitution type of a person's Prakriti. Ayurnutrigenomics is an emerging field of interest pervading Ayurveda systems biology, where the selection of a suitable dietary, therapeutic, and lifestyle regime is made on the basis of clinical assessment of an individual maintaining one's Prakriti. This Ayurveda-inspired concept of personalized nutrition is a novel concept of nutrigenomic research for developing personalized functional foods and nutraceuticals suitable for one's genetic makeup with the help of Ayurveda. Here, we propose and present this novel concept of Ayurnutrigenomics and its emerging areas of research, which may unfold future possibilities toward smart yet safe therapeutics.
A variety of data analysis tools has been developed to accommodate the various applications for microarray analysis. This chapter discusses some common analytical strategies for expression analysis, which can be potentially adapted for most microarray applications. The major steps involved in microarray data analysis are (1) microarray image acquisition and raw data generation, (2) data normalization and transformation, (3) classification and exploratory data analysis, and (4) post-analysis follow-up and validation. The first step, microarray image acquisition and raw data generation, is heavily platform dependent. Regardless of the approach chosen, the arrays are scanned after hybridization. Independent grayscale images, typically 16 bit tagged information file format files (tiff), are generated for each sample to be analyzed. Image analysis software is then used to identify arrayed spots and measure the relative fluorescence intensities for each element. There are many commercial and freely available software packages for image quantitation. Although there are differences between various imaging software, most give high quality, reproducible measures of hybridization intensities.
Metabolomics is based on the simultaneous analysis of multiple low-molecular-weight metabolites from a given sample. The goals of metabolomics are to catalog and quantify the myriad small molecules found in biological fluids under different conditions. The metabolomics represents the collection of all metabolites in a biological organism, and metabolic profiling can give an instantaneous 'snapshot' of the physiology of that cell. Together with the other more established omics technologies, metabolomics will strengthen its claim to contribute to the detailed understanding of the in vivo function of gene products, biochemical analysis, regulatory networks and more ambitious, the mathematical description and simulation of the whole cell in the systems biology approach. This phenomenon will allow the construction of designer organisms for process application using biotransformation and fermentative approaches making effective use of single enzymes, whole microbial and even higher cells and allows the connection of data from genomics, proteomics to enables coordinating the timing of the analysis to physiologically important windows.
ELISAs used to detect antibodies specific for common infectious agents such as Epstein Barr Virus (EBV), Cytomegalovirus (CMV), Toxoplasma gondii (T. gondii) and Hepatitis C Virus (HCV) are time-consuming and require large volumes of samples, which restrict their use. We propose a new assay based on a multiplexed infectious protein (MIP) microarray combining different epitopes representative of the four germs. Antigens and lysates were printed on nitrocellulose slides to constitute the microarray. First, the microarray was incubated with human serum samples. Then, the suitability of the microarray for analysis of the specificity of purified monoclonal immunoglobulins (mc Ig) was assessed using serum and mc Ig of HCV-positive patients [1,2]. Bound human IgG were detected using fluorescently labelled secondary antibodies and the signals were quantified. Results obtained in serum samples with the new MIP microarray immunoassay were compared to ELISAs: we observed a concordance of 95% for EBV, 93% for CMV, 91% for T. gondii and 100% for HCV. Regarding purified mc Ig of HCV-positive patients, 3/3 recognized antigens printed on the microarray. Hence, the novel EBV/CMV/T. gondii/HCV MIP microarray allows simultaneous diagnosis of polyclonal and monoclonal immune response to infectious diseases using very small volume samples.
This chapter focuses on the generation and utilization of a C. elegans interactome network. The first part describes the high-throughput ORF cloning and high-throughput two-hybrid technique in order to determine the protein-protein interactions and to generate such a protein-protein interaction map. In the second part, elements of the topological structures of interactomes in general as well as the C. elegans interactome more specifically are presented. The biological utility of such an approach is discussed. The last part focuses on the integration of protein-protein interactions with other postgenomics data in order to filter these datasets as well as to give a dynamical view of this interactome.
Microarrays, more popularly known as chips, have found their way into our laboratories within a rather short time. Their development represents a decisive step toward modernization, or even revolutionization, of laboratory tests. The possibilities for applying microarray techniques vary widely and their potential has not yet been fully explored: 1.
Oligonucleotide- or cDNA-microarrays for analysis of mRNA gene expression signatures of defined tumor entities have become firmly established in research. Their application in routine clinical and molecular pathological diagnostics awaits extensive validation studies. Great expectations are pinned on their success: to draw diagnostic and prognostic conclusions as well as to identify those genes that can be influenced by treatment.
2.
DNA-microarrays are used for genomics: matrix- or array-CGH (comparative genomic hybridization) detects DNA deletions, gains and amplifications with unprecedented resolution.
3.
DNA-arrays for the analysis of single nucleotide polymorphisms (SNPs) are employed to enable prediction of the individual incidence probabilities of certain diseases or of responsiveness to medications and environmental influences.
4.
Arrays of thousands of tumor tissue samples (tissue-micro-array, TMA) with similar histomorphological properties are used to validate conspicuous gene expression patterns.
5.
Antibody and protein chips are utilized to provide evidence of alterations at the protein level. The possibilities for application range from serological determinations to detection of protein interactions within signalling pathways.
6.
All in all, the goal is to be able to perform almost all laboratory analyses on a mini scale (lab-on-a-chip microarray) and thus be able to economically determine many characteristic parameters simultaneously.
Affinity proteomics, mainly represented by antibody microarrays, has in recent years been established as a powerful tool for high-throughput (disease) proteomics. The technology can be used to generate detailed protein expression profiles, or protein maps, of focused set of proteins in crude proteomes and potentially even high-resolution portraits of entire proteomes. The technology provides unique opportunities, for example biomarker discovery, disease diagnostics, patient stratification and monitoring of disease, and taking the next steps toward personalized medicine. However, the process of designing high-performing, high-density antibody micro- and nanoarrays has proven to be challenging, requiring truly cross-disciplinary efforts to be adopted. In this mini-review, we address one of these key technological issues, namely, the choice of probe format, and focus on the use of recombinant antibodies vs. polyclonal and monoclonal antibodies for the generation of antibody arrays.
Protein microarrays present an innovative and versatile approach to study protein abundance and function at an unprecedented scale. Given the chemical and structural complexity of the proteome, the development of protein microarrays has been challenging. Despite these challenges there has been a marked increase in the use of protein microarrays to map interactions of proteins with various other molecules, and to identify potential disease biomarkers, especially in the area of cancer biology. In this review, we discuss some of the promising advances made in the development and use of protein microarrays.
Over the past 75 years, antibodies have gone from being recognized as disease biomarkers to being used as very powerful therapeutic tools. This evolution has been accelerated by the identification of mAb and the extensive use of immunological tools both at fundamental and clinical levels. In this review, we evaluate how antibodies can be used to assess the proteome of cells or tissues and their relevance for clinical applications. These antibody-based proteomics approaches also require analytical and technological pipelines as well as specific enabling tools which are described. Our first objective was to establish how large-scale datasets (provided by high-throughput studies such as proteomics and transcriptomics) can be integrated with literature searches and clinical data to identify potentially relevant markers against which antibodies should be raised. Then based on an extensive literature review and our experience, we compare the methodologies developed to produce specific antibodies either in vivo or in vitro. This is followed by the description of the validation tools currently available and it also includes the use of antibody-based approaches in the establishment of molecular signatures utilized at the bench and soon available for bedside use.
Advances in protein microarray technology allow the generation of high content, reliable information about complex, multilevel protein interaction networks. Yet antigen arrays are used mostly only as devices for parallel immune assays describing multitudes of individual binding events. We propose here that the huge amount of immunological information hidden in the plasma of an individual could be better revealed by combining the characterization of antibody binding to target epitopes with improved estimation of effector functions triggered by these binding events. Furthermore, we could generate functional immune profiles characterizing general immune responsiveness of the individual by designing arrays incorporating epitope collections from diverse subsets of antibody targets.
Modern experimental techniques have produced a wealth of high-throughput data that has enabled the ongoing genomic revolution. As the field continues to integrate experimental and computational analyzes of this data, it is essential that performance evaluations of high-throughput results be carried out in a consistent and biologically informative manner. Here, we present an overview of evaluation techniques for high-throughput experimental data and computational methods, and we discuss a number of potential pitfalls in this process. These primarily involve the biological diversity of genomic data, which can be masked or misrepresented in overly simplified global evaluations. We describe systems for preserving information about biological context during dataset evaluation, which can help to ensure that multiple different evaluations are more directly comparable. This biological variety in high-throughput data can also be taken advantage of computationally through data integration and process specificity to produce richer systems-level predictions of cellular function. An awareness of these considerations can greatly improve the evaluation and analysis of any high-throughput experimental dataset.
A unique peptide sequence of HGGHHG screening from a combinatorial synthetic peptide library showed a good chelating ability to bind a transition metal on a chip better than hexa-His peptide. It was directly conjugated with a His-Tagged proteins onto a chip in a mild aqueous solution and can be used this chip as a high throughput technique for protein array in order to detect and purify the His-Tagged proteins.
Approaches aimed at deciphering the proteome have illustrated the need for relatively complex and highly sensitive methodologies. The major elements of proteome analysis, such as powerful protein separation and enzymatic processing, mass spectrometry and dedicated bioinformatics have been assembled in the development of the molecular scanner. This highly flexible and data-rich approach has combined the power of electrophoretic protein separation, the simultaneous digestion and transfer of proteins through an enzymatic membrane, the immediate use of the MALDI mass spectrometer to scan a collecting membrane, and the development of dedicated bioinformatics tools to perform protein identification and molecular imaging of the proteome. Clinical applications of the molecular scanner have also started to be developed for disease diagnosis in biological material.
To treat soluble and solid wastes and recover energy from them, high rate methane fermentation, especially using the UASB (upflow anaerobic sludge blanket) reactor, and hydrogen fermentation using various microorganisms and microbial consortia have been investigated intensively in Japan. In this chapter, recent works on high rate methane fermentation in Japan are reviewed, focusing on: 1) basic studies into the applicability of the UASB reactor for various substrates such as propionate, lactate, ethanol, glucose and phenol; 2) its applications to unfeasible conditions, such as lipid and protein containing wastes, low temperature and high salt-containing wastes; 3) progress made in the field of advanced UASB reactors, and; 4) research into methane fermentation from solid wastes, such as from cellulosic materials, municipal sewage sludge, and mud sediments. Following this, although hydrogen fermentation with photosynthetic microorganisms or anaerobic bacteria was researched, for this review we have focused on fermentative hydrogen production using strictly or facultative anaerobes and microbial consortia in Japan, since high rate production of hydrogen-methane via a two-stage process was judged to be more attractive for biological hydrogen production and wastewater treatments.
Recent advances in the improvement of microbial cultivation are reviewed, with emphasis on biochemical engineering techniques as a means of obtaining high production rate of bioproduct. Possible uses of high cell density culture include their use in food industry as well as in the production of new medicines and in biotechnology. Concentration of microorganisms using a hollow fiber membrane or centrifuge, and increase in cell density by controlling the pH, dissolved oxygen, or carbon source concentrations of the culture broth with control algorithms are discussed. In a culture of filamentous microorganisms the mycelial morphology is hard to define and it is difficult to quantify its amount, and this is one of the bottlenecks hampering the improvement of production rate. Specific features of mycelial cultivation in the presence of highly pulpy mycelia and entangled-pellets are scrutinized by visual inspection through a microscope that is linked to a computer, and using software that can characterize the mycelial morphology. Image analysis technology for analyzing the mycelial image captured by a digital camera is a potential tool for morphological analysis, including analysis of the morphological development of filamentous microorganisms.
A novel immunoproteomic assay, combining specificity of antibody with precision of mass spectral analysis is described, and a number of practical applications are presented. The assay is carried out in three steps. The first step of the assay involves antibody immobilization, using a bacterial Fc binding support. The second step is antigen capture and washing to remove non-specific binding. The third step involves analysis of the captured antigens by SELDI-TOF. The assay has many advantages in sensitivity, speed, and economy of reagents in detection of specific antigens or antibodies. In addition, under appropriate experimental conditions, semi-quantitative data may be obtained. By combining the increasing range of selective specific antibody reagents available, in part due to advances in antibody engineering technology, and the resolving power available, using mass spectrometry, immunoproteomics is a valuable technique in proteomic analysis. A number of examples of the application of this technique to analysis of biological systems are presented.
Gene expression microarrays are becoming increasingly widespread, especially as a way to rapidly identify putative functions of unknown genes. Accurate microarray data analysis, however, still remains a challenge. The recent availability of multiple types of high-throughput functional genomic data can facilitate accurate and effective analysis of microarray experiments and thereby accelerate functional annotation of sequenced genomes. But genomic data often sacrifice specificity for scale, yielding very large quantities of relatively lower quality data than traditional experimental methods. Advanced analysis methods are thus necessary to make accurate functional interpretation of these large-scale datasets. This chapter outlines recently developed methods that integrate the analysis of microarray data with sequence, interaction, localization, and literature data and further outlines specific problems in currently available integrated analysis technologies.
A rapid method for the identification of known proteins separated by two-dimensional gel electrophoresis is described in which molecular masses of peptide fragments are used to search a protein sequence database. The peptides are generated by in situ reduction, alkylation, and tryptic digestion of proteins electroblotted from two-dimensional gels. Masses are determined at the subpicomole level by matrix-assisted laser desorption/ionization mass spectrometry of the unfractionated digest. A computer program has been developed that searches the protein sequence database for multiple peptides of individual proteins that match the measured masses. To ensure that the most recent database updates are included, a theoretical digest of the entire database is generated each time the program is executed. This method facilitates simultaneous processing of a large number of two-dimensional gel spots. The method was applied to a two-dimensional gel of a crude Escherichia coli extract that was electroblotted onto poly(vinylidene difluoride) membrane. Ten randomly chosen spots were analyzed. With as few as three peptide masses, each protein was uniquely identified from over 91,000 protein sequences. All identifications were verified by concurrent N-terminal sequencing of identical spots from a second blot. One of the spots contained an N-terminally blocked protein that required enzymatic cleavage, peptide separation, and Edman degradation for confirmation of its identity.
The efficiency of sequencing by hybridization to an oligonucleotide microchip grows with an increase in the number and in
the length of the oligonucleotides; however, such increases raise enormously the complexity of the microchip and decrease
the accuracy of hybridization. We have been developing the technique of contiguous stacking hybridization (CSH) to circumvent
these shortcomings. Stacking interactions between adjacent bases of two oligonucleotides stabilize their contiguous duplex
with DNA. The use of such stacking increases the effective length of microchip oligonucleotides, enhances sequencing accuracy
and allows the sequencing of longer DNA. The effects of mismatches, base composition, length and other factors on the stacking
are evaluated. Contiguous stacking hybridization of DNA with immobilized 8mers and one or two 5mers labeled with two different
fluorescent dyes increases the effective length of sequencing oligonucleotides from 8 to 13 and 18 bases, respectively. The
incorporation of all four bases or 5-nitroindole as a universal base into different positions of the 5mers permitted a decrease
in the number of additional rounds of hybridization. Contiguous stacking hybridization appears to be a promising approach
to significantly increasing the efficiency of sequencing by hybridization.
We have demonstrated the assembly of two-dimensional patterns of functional antibodies on a surface. In particular, we have selectively adsorbed micrometer-scale regions of biotinylated immunoglobulin that exhibit specific antigen binding after adsorption. The advantage of this technique is its potential adaptability to adsorbing arbitrary proteins in tightly packed monolayers while retaining functionality. The procedure begins with the formation of a self-assembled monolayer of n-octadecyltrimethoxysilane (OTMS) on a silicon dioxide surface. This monolayer can then be selectively removed by UV photolithography. Under appropriate solution conditions, the OTMS regions will adsorb a monolayer of bovine serum albumin (BSA), while the silicon dioxide regions where the OTMS has been removed by UV light will adsorb less than 2% of a monolayer, thus creating high contrast patterned adsorption of BSA. The attachment of the molecule biotin to the BSA allows the pattern to be replicated in a layer of streptavidin, which bonds to the biotinylated BSA and in turn will bond an additional layer of an arbitrary biotinylated protein. In our test case, functionality of the biotinylated goat antibodies raised against mouse immunoglobulin was demonstrated by the specific binding of fluorescently labeled mouse IgG.
A simple procedure for manufacturing microchips containing various gel-immobilized compounds is described. A gel photopolymerization technique is introduced to produce micromatrices of polyacrylamide gel pads (25 x 25 x 20 microm and larger) separated by a hydrophobic glass surface. A pin device for the manual application of a compound in solution onto the activated polyacrylamide gel pad for immobilization is described. Oligonucleotide, DNA, and protein microchips have been produced by this method and tested by hybridization and immunoanalysis monitored with a fluorescence microscope. The effect of the lengths of the immobilized oligonucleotides and the hybridized RNA and DNA on hybridization of the oligonucleotide microchips was evaluated. This method can also be used for manufacturing microchips containing a variety of other compounds.
We have developed a technique to establish catalogues of protein products of arrayed cDNA clones identified by DNA hybridisation
or sequencing. A human fetal brain cDNA library was directionally cloned in a bacterial vector that allows IPTG-inducible
expression of His6-tagged fusion proteins. Using robot technology, the library was arrayed in microtitre plates and gridded
onto high-density in situ filters. A monoclonal antibody recognising the N-terminal RGSH6 sequence of expressed proteins (RGS·His antibody, Qiagen) detected 20% of the library as putative expression clones. Two
example genes, GAPDH and HSP90α, were identified on high-density filters using DNA probes and antibodies against their proteins.
Two large-scale yeast two-hybrid screens were undertaken to identify protein-protein interactions between full-length open reading frames predicted from the Saccharomyces cerevisiae genome sequence. In one approach, we constructed a protein array of about 6,000 yeast transformants, with each transformant expressing one of the open reading frames as a fusion to an activation domain. This array was screened by a simple and automated procedure for 192 yeast proteins, with positive responses identified by their positions in the array. In a second approach, we pooled cells expressing one of about 6,000 activation domain fusions to generate a library. We used a high-throughput screening procedure to screen nearly all of the 6,000 predicted yeast proteins, expressed as Gal4 DNA-binding domain fusion proteins, against the library, and characterized positives by sequence analysis. These approaches resulted in the detection of 957 putative interactions involving 1,004 S. cerevisiae proteins. These data reveal interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes. The results of these screens are shown here.
Many new gene products are being discovered by large-scale genomics and proteomics strategies, the challenge is now to develop high throughput approaches to systematically analyse these proteins and to assign a biological function to them. Having access to these gene products as recombinantly expressed proteins, would allow them to be robotically arrayed to generate protein chips. Other applications include using these proteins for the generation of specific antibodies, which can also be arrayed to produce antibody chips. The availability of such protein and antibody arrays would facilitate the simultaneous analysis of thousands of interactions within a single experiment. This chapter will focus on current strategies used to generate protein and antibody arrays and their current applications in biological research, medicine and diagnostics. The shortcomings of these approaches, the developments required, as well as the potential applications of protein and antibody arrays will be discussed.
To facilitate studies of the yeast proteome, we cloned 5800 open reading frames and overexpressed and purified their corresponding proteins. The proteins were printed onto slides at high spatial density to form a yeast proteome microarray and screened for their ability to interact with proteins and phospholipids. We identified many new calmodulin- and phospholipid-interacting proteins; a common potential binding motif was identified for many of the calmodulin-binding proteins. Thus, microarrays of an entire eukaryotic proteome can be prepared and screened for diverse biochemical activities. The microarrays can also be used to screen protein-drug interactions and to detect posttranslational modifications.
We developed a high-throughput technique for the generation of cDNA libraries in the yeast Saccharomyces cerevisiae which enables the selection of cloned cDNA inserts containing open reading frames (ORFs). For direct screening of random-primed cDNA libraries, we have constructed a yeast shuttle/expression vector, the so-called ORF vector pYEXTSH3, which allows the enriched growth of protein expression clones. The selection system is based on the HIS3 marker gene fused to the C terminus of the cDNA insert. The cDNAs cloned in-frame result in histidine prototrophic yeast cells growing on minimal medium, whereas clones bearing the vector without insert or out-of-frame inserts should not grow on this medium. A randomly primed cDNA library from human fetal brain tissue was cloned in this novel vector, and using robot technology the selected clones were arrayed in microtiter plates and were analyzed by sequencing and for protein expression. In the constructed cDNA expression library, about 60% of clones bear an insert in the correct reading frame. In comparison to unselected libraries it was possible to increase the clones with inserts in the correct reading frame more than fourfold, from 14% to 60%. With the expression system described here, we could avoid time-consuming and costly techniques for identification of clones expressing protein by using antibody screening on high-density filters and subsequently rearraying the selected clones in a new "daughter" library. The advantage of this ORF vector is that, in a one-step screening procedure, it allows the generation of expression libraries enriched for clones with correct reading frames as sources of recombinant proteins.
We present a new MALDI sample preparation technique for peptide analysis using the matrix alpha -cyano-4-hydroxycinnamic acid (CHCA) and prestructured sample supports. The preparation integrates sample purification, based on the affinity of microcrystalline CHCA for peptides, thereby simplifying the analysis of crude peptide mixtures. Enzymatic digests can thus be prepared directly, without preceding purification. Prepared samples are homogeneous, facilitating automatic spectra acquisition, This method allows preparation of large numbers of samples with little effort and without the need for automation. These features make the described preparation suitable for cost-efficient high-throughput protein identification. Performance of the sample preparation is demonstrated with in situ proteolytic digests of human brain proteins separated by two-dimensional gel electrophoresis.
Micropatterned arrays of active proteins are vital to the next generation of high-throughput multiplexed biosensors and advanced medical diagnostics. We have developed a simple method for fabricating antibody arrays using a micromolded hydrogel “stamper” and an aminosilylated receiving surface. The stamping procedure permits direct protein deposition and micropatterning while avoiding cross-contamination of separate patterned regions. Three different antibodies were stamped in adjacent arrays of 50−80 μm circular areas with retention of activity. 125I labeling and atomic force microscopy studies showed that the stamper deposited protein as a submonolayer. The fluorescent signal-to-background ratio of labeled bound antigen was greater than 25:1.
The array format has revolutionised biomedical experimentation and diagnostics, enabling ordered high-throughput analysis. During the past decade, classic solid phase substrates, such as microtitre plates, membrane filters and microscopic slides, were turned into high-density, chip-like structures. The concept of the arrayed library was central to this development which now extends from DNA to protein. The new and versatile protein array technology allows high-throughput screening for gene expression and molecular interactions. As a major platform for functional genomics, it is already on its way into medical diagnostics.
Protein–protein interactions have been widely used to study gene expression pathways and may be considered as a new approach
to drug discovery. Here I report the development of a universal protein array (UPA) system that provides a sensitive, quantitative,
multi-purpose, effective and easy technology to determine not only specific protein–protein interactions, but also specific
interactions of proteins with DNA, RNA, ligands and other small chemicals. (i) Since purified proteins are used, the results
can be easily interpreted. (ii) UPA can be used multiple times for different targets, making it economically affordable for
most laboratories, hospitals and biotechnology companies. (iii) Unlike DNA chips or DNA microarrays, no additional instrumentation
is required. (iv) Since the UPA uses active proteins (without denaturation and renaturation), it is more sensitive compared
with most existing methods. (v) Because the UPA can analyze hundreds (even thousands on a protein microarray) of proteins
in a single experiment, it is a very effective method to screen proteins as drug targets in cancer and other human diseases.
Array-based sensors provide an architecture for multianalyte sensing. In this paper, we report a new approach for array fabrication. Sensors are made by immobilizing different reactive chemistries on the surfaces of microspheres. Sensor arrays are prepared by randomly distributing a mixture of microsphere sensors on an optical substrate containing thousands of micrometer-scale wells. The sensors occupy a different location from array to array; thus the identity of each sensor is ascertained and registered on the detector using encoding schemes, rather than by a predetermined location in the array. The approach thereby shifts the demand from fabrication to signal processing. The availability of commercial image analysis software makes such a shift both cost-effective and time efficient.
This paper combines the topographic imaging capability of the atomic force microscope (AFM) with a compositionally patterned array of immobilized antigenic rabbit IgG on gold as an approach to performing immunoassays. The substrates are composed of micrometer-sized domains of IgG that are covalently linked to a photolithographically patterned array of a monolayer-based coupling agent. The immobilized coupling agent, which is prepared by the chemisorption of dithiobis(succinimidyl undecanoate) on gold, is separated by micrometer-sized grids of a monolayer formed from octadecanethiol (ODT). The strong hydrophobicity of the ODT adlayer, combined with the addition of the surfactant Tween 80 to the buffer solution that is used in forming the antibody-antigen pairs, minimizes the nonspecific adsorption of proteinaceous materials to the grid regions. This minimization allows the grids to function as a reference plane for the AFM detection of the height increase when a complementary antibody-antigen pair is formed. The advantageous features of this strategy, which include ease of sample preparation, an internal reference plane for the detection of topographic changes, and the potential for regeneration and reuse, are demonstrated using rabbit IgG as an immobilized antigen and goat anti-rabbit IgG as the complementary antibody. The prospects for further miniaturization are discussed.
A computer searching algorithm has been used to identify protein sequences in the Protein Information Resource (PIR) database with peptide mass information (mass map) obtained from proteolytic digests of proteins analyzed by microcapillary high-performance liquid chromatography electrospray ionization mass spectrometry. A theoretical analysis of the cytochrome c family demonstrates the ability to identify protein sequences in the PIR database with a high degree of accuracy using a set of six predicted tryptic peptide masses. This method was also applied to experimentally determined peptide masses for a small GTP-binding protein, a protein from pig uterus, the human sex steroid binding protein, and a thermostable DNA polymerase. The results demonstrate that a set of observed masses which is less than 50% of the total number of predicted masses can be used to identify a protein sequence in the database. For the analysis presented in this paper, a mass matching tolerance of 1 amu is used. Under these conditions, mass maps created by fast atom bombardment mass spectrometry and matrix-assisted laser desorption time-of-flight would also be applicable. In cases where multiple matches are observed or verification of the protein identification is needed, tandem mass spectrometry sequencing can be used to establish sequence similarity.
During the last decade new ionization techniques have made it possible to measure the molecular weight of many intact proteins by mass spectrometry, and they have made it much easier to obtain a mass spectrometric peptide map of a protein. At the same time advances in protein and DNA sequencing technology are resulting in an exponential increase in the number of sequences deposited in databases. Here we investigate the possibility to use mass spectrometric data to identify proteins in databases. Searching a database by total molecular weight is found to be an easy and sometimes sufficient approach. For more specificity and for error tolerance in both the mass spectrometric data and the database information we search by partial mass spectrometric peptide map of the protein. In general, just four to six proteolytic peptides measured with a mass accuracy between 0.1 and 0.01% allow a useful search of databases such as the Protein Identification Resource (PIR). As the size of DNA and protein sequence databases grows, protein identification by partial mass spectrometric peptide maps should become increasingly powerful and may become a general method to identify and characterize proteins.
We have developed an algorithm for identifying proteins at the sub-microgram level without sequence determination by chemical degradation. The protein, usually isolated by one- or two-dimensional gel electrophoresis, is digested by enzymatic or chemical means and the masses of the resulting peptides are determined by mass spectrometry. The resulting mass profile, i.e., the list of the molecular masses of peptides produced by the digestion, serves as a fingerprint which uniquely defines a particular protein. This fingerprint may be used to search the database of known sequences to find proteins with a similar profile. If the protein is not yet sequenced the profile can serve as a unique marker. This provides a rapid and sensitive link between genomic sequences and 2D gel electrophoresis mapping of cellular proteins.
Proteins from silver-stained gels can be digested enzymatically and the resulting peptide analyzed and sequenced by mass spectrometry. Standard proteins yield the same peptide maps when extracted from Coomassie- and silver-stained gels, as judged by electrospray and MALDI mass spectrometry. The low nanogram range can be reached by the protocols described here, and the method is robust. A silver-stained one-dimensional gel of a fraction from yeast proteins was analyzed by nano-electrospray tandem mass spectrometry. In the sequencing, more than 1000 amino acids were covered, resulting in no evidence of chemical modifications due to the silver staining procedure. Silver staining allows a substantial shortening of sample preparation time and may, therefore, be preferable over Coomassie staining. This work removes a major obstacle to the low-level sequence analysis of proteins separated on polyacrylamide gels.
Many genes and signalling pathways controlling cell proliferation, death and differentiation, as well as genomic integrity, are involved in cancer development. New techniques, such as serial analysis of gene expression and cDNA microarrays, have enabled measurement of the expression of thousands of genes in a single experiment, revealing many new, potentially important cancer genes. These genome screening tools can comprehensively survey one tumor at a time; however, analysis of hundreds of specimens from patients in different stages of disease is needed to establish the diagnostic, prognostic and therapeutic importance of each of the emerging cancer gene candidates. Here we have developed an array-based high-throughput technique that facilitates gene expression and copy number surveys of very large numbers of tumors. As many as 1000 cylindrical tissue biopsies from individual tumors can be distributed in a single tumor tissue microarray. Sections of the microarray provide targets for parallel in situ detection of DNA, RNA and protein targets in each specimen on the array, and consecutive sections allow the rapid analysis of hundreds of molecular markers in the same set of specimens. Our detection of six gene amplifications as well as p53 and estrogen receptor expression in breast cancer demonstrates the power of this technique for defining new subgroups of tumors.
A fluorescence-based immunosensor has been developed for simultaneous analysis of multiple samples. A patterned array of recognition elements immobilized on the surface of a planar waveguide is used to "capture" analyte present in samples; bound analyte is then quantified by means of fluorescent detector molecules. Upon excitation of the fluorescent label by a small diode laser, a CCD camera detects the pattern of fluorescent antigen:antibody complexes on the sensor surface. Image analysis software correlates the position of fluorescent signals with the identity of the analyte. This immunosensor was used to detect physiologically relevant concentrations of staphylococcal enterotoxin B (SEB), F1 antigen from Yersinia pestis, and D-dimer, a marker of sepsis and thrombotic disorders, in spiked clinical samples.
Genome sequencing provides a wealth of information on predicted gene products (mostly proteins), but the majority of these have no known function. Two-dimensional gel electrophoresis and mass spectrometry have, coupled with searches in protein and EST databases, transformed the protein-identification process. The proteome is the expressed protein complement of a genome and proteomics is functional genomics at the protein level. Proteomics can be divided into expression proteomics, the study of global changes in protein expression, and cell-map proteomics, the systematic study of protein-protein interactions through the isolation of protein complexes.
Proteins translate genomic sequence information into function, enabling biological processes. As a complementary approach to gene expression profiling on cDNA microarrays, we have developed a technique for high-throughput gene expression and antibody screening on chip-size protein microarrays. Using a picking/spotting robot equipped with a new transfer stamp, protein solutions were gridded onto polyvinylidene difluoride filters at high density. Specific purified protein was detected on the filters with high sensitivity (250 amol or 10 pg of a test protein). On a microarray made from bacterial lysates of 92 human cDNA clones expressed in a microtiter plate, putative protein expressors could be reliably identified. The rate of false-positive clones, expressing proteins in incorrect reading frames, was low. Product specificity of selected clones was confirmed on identical microarrays using monoclonal antibodies. Cross-reactivities of some antibodies with unrelated proteins imply the use of protein microarrays for antibody specificity screening against whole libraries of proteins. Because this application would not be restricted to antigen-antibody systems, protein microarrays should provide a general resource for high-throughput screens of gene expression and receptor-ligand interactions.
For any attempt to understand the biology of an organism the incorporation of a cDNA-based approach is unavoidable, because it is a major approach to studying gene function. The complete sequence of the genome alone is not sufficient to understand any organism; its gene regulation, expression, splice variation, posttranslational modifications, and proteinprotein interactions all need to be addressed. Because the majority of vertebrate genes have probably been identified as ESTs44,52 the next stage of the Human Genome Project is attributing functional information to these sequences. In most cases hybridization-based approaches on arrayed pieces of DNA represent the most efficient way to study the expression level and splicing of a gene in a given tissue. Similar technology, now being applied at the protein level using protein expression libraries, high-density protein membranes, and antibody screening, should allow studies of protein localization and modifications.
A microchip-based enzyme assay for protein kinase A is described. The microchips were prepared by standard photolithographic techniques. The assay reagents were placed in wells on the microchips, and electroosmosis was used to transport aliquots of these reagents into the network of etched channels, where the enzymatic reaction takes place. Protein kinase A catalyzes the transfer of a phosphate group from ATP to the serine residue of the heptapeptide LeuArgArgAlaSerLeuGly (Kemptide). The outcome of the enzymatic reaction was assessed by performing an on-chip electrophoretic separation of the fluorescently labeled peptide substrate and product. All liquid-handling steps were performed by controlling the electroosmotically driven flow from reagent and buffer wells using electrical current. On-chip dilutions of the peptide substrate, ATP and H-89, a known protein kinase A inhibitor, were performed and the kinetic constants (K(m), K(i)) of these compounds were determined. This prototype assay demonstrates the usefulness of the microchips for performing enzymatic assays for which fluorogenic substrates cannot easily be designed.
We have constructed a human fetal brain cDNA library in an Escherichia coli expression vector for high-throughput screening of recombinant human proteins. Using robot technology, the library was arrayed in microtiter plates and gridded onto high-density filter membranes. Putative expression clones were detected on the filters using an antibody against the N-terminal sequence RGS-His(6) of fusion proteins. Positive clones were rearrayed into a new sublibrary, and 96 randomly chosen clones were analyzed. Expression products were analyzed by SDS-PAGE, affinity purification, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry, and the determined protein masses were compared to masses predicted from DNA sequencing data. It was found that 66% of these clones contained inserts in a correct reading frame. Sixty-four percent of the correct reading frame clones comprised the complete coding sequence of a human protein. High-throughput microtiter plate methods were developed for protein expression, extraction, purification, and mass spectrometric analyses. An enzyme assay for glyceraldehyde-3-phosphate dehydrogenase activity in native extracts was adapted to the microtiter plate format. Our data indicate that high-throughput screening of an arrayed protein expression library is an economical way of generating large numbers of clones producing recombinant human proteins for structural and functional analyses.
A new strategy for identifying proteins in sequence data-bases by MALDI-MS peptide mapping is reported. The strategy corrects for systematic deviations of determined peptide molecular masses using information contained in the opened database and thereby renders unnecessary internal spectrum calibration. As a result, data acquisition is simplified and less error prone. Performance of the new strategy is demonstrated by identification of a set of recombinant, human cDNA expression products as well as native proteins isolated from crude mouse brain extracts by 2-D electrophoresis. Using one set of calibration constants for the mass spectrometric analyses, 20 proteins were identified without applying any molecular weight restrictions, which was not possible without data correction. A sequence database search program has been written that performs all necessary calculations automatically, access to which will be provided to the scientific community in the Internet.
In order to quantify autoantibodies in the sera of patients with autoimmune disease, we have created a microarray-based immunoassay that allows the simultaneous analysis of 18 known autoantigens. The microarrays contain serial dilutions of the various antigens, thereby allowing accurate determination of autoantibody titer using minimal amounts of serum. The assay is very sensitive and highly specific: as little as 40 fg of a known protein standard can be detected with little or no cross-reactivity to nonspecific proteins. The signal intensities observed from serial dilutions of immobilized antigen correlate well with serial dilutions of autoimmune sera. Miniaturized and highly parallelized immunoassays like these will reduce costs by decreasing reagent consumption and improve efficiency by greatly increasing the number of assays that can be performed with a single serum sample. This system will significantly facilitate and accelerate the diagnostics of autoimmune diseases and can be adapted easily to any other kind of immunoassay.
We have developed a novel technique for high-throughput screening of recombinant antibodies, based on the creation of antibody arrays. Our method uses robotic picking and high-density gridding of bacteria containing antibody genes followed by filter-based enzyme-linked immunosorbent assay (ELISA) screening to identify clones that express binding antibody fragments. By eliminating the need for liquid handling, we can thereby screen up to 18,342 different antibody clones at a time and, because the clones are arrayed from master stocks, the same antibodies can be double spotted and screened simultaneously against 15 different antigens. We have used our technique in several different applications, including isolating antibodies against impure proteins and complex antigens, where several rounds of phage display often fail. Our results indicate that antibody arrays can be used to identify differentially expressed proteins.
We have constructed a novel Pichia pastoris/Escherichia coli dual expression vector for the production of recombinant proteins in both host systems. In this vector, an E. coli T7 promoter region, including the ribosome binding site from the phage T7 major capsid protein for efficient translation is placed downstream from the yeast alcohol oxidase promoter (AOX). For detection and purification of the target protein, the vector contains an amino-terminal oligohistidine domain (His6) followed by the hemaglutinine epitope (HA) adjacent to the cloning sites. A P. pastoris autonomous replicating sequence (PARS) was integrated enabling simple propagation and recovery of plasmids from yeast and bacteria (1). In the present study, the expression of human proteins in P. pastoris and E. coli was compared using this single expression vector. For this purpose we have subcloned a cDNA expression library deriving from human fetal brain (2) into our dual expression T7 vector and investigated 96 randomly picked clones. After sequencing, 29 clones in the correct reading frame have been identified, their plasmids isolated and shuttled from yeast to bacteria. All proteins were expressed soluble in P. pastoris, whereas in E. coli only 31% could be purified under native conditions. Our data indicates that this dual expression vector allows the economic expression and purification of proteins in different hosts without subcloning.
Proteomics-based approaches, which examine the expressed proteins of a tissue or cell type, complement the genome initiatives and are increasingly being used to address biomedical questions. Proteins are the main functional output, and the genetic code cannot always indicate which proteins are expressed, in what quantity, and in what form. For example, post-translational modifications of proteins, such as phosphorylation or glycosylation, are very important in determining protein function. Similarly, the effects of environmental factors or multigenic processes such as ageing or disease cannot be assessed simply by examination of the genome alone. This review describes the underlying technology and illustrates several areas of biomedical research, ranging from pathogenesis of neurological disorders to drug and vaccine design, in which potential clinical applications are being explored.
Developments in 'soft' ionisation techniques have revolutionized mass-spectro-metric approaches for the analysis of protein structure. For more than a decade, such techniques have been used, in conjuction with digestion b specific proteases, to produce accurate peptide molecular weight 'fingerprints' of proteins. These fingerprints have commonly been used to screen known proteins, in order to detect errors of translation, to characterize post-translational modifications and to assign diulphide bonds. However, the extent to which peptide-mass information can be used alone to identify unknown sample proteins, independent of other analytical methods such as protein sequence analysis, has remained largely unexplored.
We report here on the development of the molecular weight search (MOWSE) peptide-mass database at the SERC Daresbury Laboratory. Practical experience has shown that sample proteins can be uniquely identified from a few as three or four experimentally determined peptide masses when these are screened against a fragment database that is derived from over 50 000 proteins. Experimental errors of a few Daltons are tolerated by the scoring algorithms, thus permitting the use of inexpensive time-of-flight mass spectrometers. As with other types of physical data, such as amino-acid composition or linear sequence, peptide masses provide a set of determinants that are sufficiently discriminating to identify or match unknown sample proteins.
Peptide-mass fingerprints can prove as discriminating as linear peptide sequences, but can be obtained in a fraction of the time using less protein. In many cases, this allows for a rapid identification of a sample protein before committing it to protein sequence analysis. Fragment masses also provide information, at the protein level, that is complementary to the information provided by large-scale DNA sequencing or mapping projects.