ArticleLiterature Review

Pharmacoproteomics: A chess game on a protein field

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Abstract

The application of proteomics in the field of drug discovery development and the assessment of drug administration is known as pharmacoproteomics. As a branch of proteomics--perhaps the most promising and rapidly evolving field of the post-genomic era--pharmacoproteomics has inherited all the promises that pharmacogenomics has hitherto left unfulfilled. On the road to tailor-made drugs, whole protein profiles of healthy individuals have been progressively expanded, either qualitatively or quantitatively. In this review article, we provide general information about technical advancements in the field of proteomics (the pieces of this intriguing chess game) and show how this progress has furthered our understanding of biological systems. Pitfalls on the field of biomarker individuation and drug discovery and/or testing are also discussed.

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There has been considerable interest in recent years in the development of miniaturized and parallelized array technology for protein-protein interaction analysis and protein profiling, namely 'protein-detecting microarrays'. Protein-detecting microarrays utilize a wide variety of capture agents (antibodies, fusion proteins, DNA/RNA aptamers, synthetic peptides, carbohydrates, and small molecules) immobilized at high spatial density on a solid surface. Each capture agent binds selectively to its target protein in a complex mixture, such as serum or cell lysate samples. Captured proteins are subsequently detected and quantified in a high-throughput fashion, with minimal sample consumption. Protein-detecting microarrays were first described by MacBeath and Schreiber in 2000, and the number of publications involving this technology is rapidly increasing. Furthermore, the first multiplex immunoassay systems have been cleared by the US Food and Drug Administration, signaling recognition of the usefulness of miniaturized and parallelized array technology for protein detection in predictive/early diagnosis. Although genetic tests still predominate, with further development protein-based diagnosis will become common in clinical use within a few years.
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The use of proteomics to profile biological fluids and identify therein biomarkers for cancer and other diseases was initially received with considerable excitement. However, results have fallen short of the expectations. Traditionally, protein biomarkers have been identified by measurement of relative expression changes between case and control samples from which differentially expressed proteins are then considered to represent biomarker candidates. We argue that current individual proteomics-based biomarker discovery studies lack the statistical strength for the identification of high-confidence biomarkers. Instead, multi-group efforts are necessary to facilitate the generation of sufficient sample sizes. This is contingent on the ability to collate and cross-compare data from different studies, which will require the use of a common metric or standards. Though profound, the technical challenges for absolute protein quantification can be overcome. The use of matrix specific, shared standards for absolute quantitation presents an opportunity to facilitate the much needed, but currently impossible, comparisons of different studies. In addition to community-wide approaches to standardize pre-analytical biomarker research studies, it is also important to establish means to integrate experimental data from different studies in order to assess the usefulness of proposed biomarkers with sufficient statistical certainty.
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We employed stereotactic microdialysis to sample extracellular fluid intracranially from glioblastoma patients, before and during the first five days of conventional radiotherapy treatment. Microdialysis catheters were implanted in the contrast enhancing tumor as well as in the brain adjacent to tumor (BAT). Reference samples were collected subcutaneously from the patients' abdomen. The samples were analyzed by gas chromatography-time-of-flight mass spectrometry (GC-TOF MS), and the acquired data was processed by hierarchical multivariate curve resolution (H-MCR) and analyzed with orthogonal partial least-squares (OPLS). To enable detection of treatment-induced alterations, the data was processed by individual treatment over time (ITOT) normalization. One-hundred fifty-one metabolites were reliably detected, of which 67 were identified. We found distinct metabolic differences between the intracranially collected samples from tumor and the BAT region. There was also a marked difference between the intracranially and the subcutaneously collected samples. Furthermore, we observed systematic metabolic changes induced by radiotherapy treatment among both tumor and BAT samples. The metabolite patterns affected by treatment were different between tumor and BAT, both containing highly discriminating information, ROC values of 0.896 and 0.821, respectively. Our findings contribute to increased molecular knowledge of basic glioblastoma pathophysiology and point to the possibility of detecting metabolic marker patterns associated to early treatment response.
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New biomarkers are urgently needed to accelerate efforts in developing new drugs and treatments of known diseases. New clinical and translational proteomics studies emerge almost every day. However, discovery of new diagnostic biomarkers lags behind because of variability at every step in proteomics studies (e.g., assembly of a cohort of patients, sample preparation and the nature of body fluids, selection of a profiling method and uniform protocols for data analysis).Quite often, the validation step that follows the discovery phase does not reach desired levels of sensitivity and specificity or reproducibility between laboratories. Mass spectrometry and gel-based methods do not provide enough throughput for screening thousands of clinical samples. Further development of protein arrays may address this issue.Despite many obstacles, proteomics delivers vast amounts of information useful for understanding the molecular mechanisms underlying diseases.
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The analysis of proteins in biological membranes forms a major challenge in proteomics. Despite continuous improvements and the development of more sensitive analytical methods, the analysis of membrane proteins has always been hampered by their hydrophobic properties and relatively low abundance. In this review, we describe recent successful strategies that have led to in-depth analyses of the membrane proteome. To facilitate membrane proteome analysis, it is essential that biochemical enrichment procedures are combined with special analytical workflows that are all optimized to cope with hydrophobic polypeptides. These include techniques for protein solubilization, and also well-matched developments in protein separation and protein digestion procedures. Finally, we discuss approaches to target membrane-protein complexes and lipid-protein interactions, as such approaches offer unique insights into function and architecture of cellular membranes.
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Combinatorial peptide ligand libraries have recently allowed considerable advances in the mapping of chicken egg yolk and white proteomics. Data from literature have been regrouped and elaborated for network and pathway analyses in order to convey a unified view of these proteomes. Redundant proteins were excluded, while isoforms of the same proteins were maintained to reach a total of 260 distinct gene products for egg yolk and 148 for egg white having a match in the database. From these analyses, a role for proteins involved in cell development, proliferation and migration, cell-to-cell interaction and hematological system development emerged. Although it might turn out that, notwithstanding the extensive mapping, the currently available datasets might be still incomplete, a valuable insight could still be obtained about specific proteins playing a crucial role in antimicrobial responses, mainly histones, lysozyme and vitamin-binding proteins. In particular, SERPINB3 (ovalbumin Y, or Squamous Cell Carcinoma Antigen, SCCA1) was individuated in 8 out of 10 top score pathways in egg yolk and in 6 out 10 in egg white. SERPINB3 is a member of the ov-serpin family, participating in coagulation and inflammation responses. However, it is yet to be assessed how these observations could correlate with previous analyses about the role of egg yolk derived proteins in counteracting blood coagulation.
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Advances in proteomics technologies, in particular the parallel development of highly sensitive mass spectrometers and accurate protein quantitation technologies, have allowed the detection and accurate measurement of low abundance proteins in bodily fluids and tissues. Furthermore, the application of these technologies in biomedical research has led to the identification of proteins and genes with expression patterns that change as a consequence of disease; detection and quantitation of these proteins and genes could provide valuable information for disease diagnosis and prognosis. For example, cell-surface protein expression can change in diseased cells. These proteins may then be secreted or shed from the cell surface; the levels of these proteins in blood or urine could provide valuable information for the diagnosis of disease and disease severity. The focus of this review is the methods by which proteomics-based technologies can be applied to characterize cell-surface proteins and to measure changes to expression levels in diseased states; the review also discusses the soluble counterparts of these surface proteins in the blood; these proteins could be important diagnostic and/or prognostic indicators of disease.
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Although a preliminary portrait of the red blood cell proteome and interactome has already been provided, the recent identification of 1578 gene products from the erythrocyte cytosol asks for an updated and improved view. In this paper, we exploit data available from recent literature to compile a nonredundant list of 1989 proteins and elaborate it with pathway and network analyses. Upon network analysis, it is intuitively confirmed that red blood cells likely suffer of exacerbated oxidative stress and continuously strive against protein and cytoskeletal damage. It also emerges that erythrocyte interaction networks display a high degree of maturity. Indeed, a series of core proteins were individuated to play a central role. A catalytic ring of proteins counteracting oxidative stress was individuated as well. In parallel, pathway analysis confirmed the validity of observations about the SEC23B gene role in CDA II in a fast and unbiased way.
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The low-molecular weight fraction (LMF) of the human plasma proteome is an invaluable source of biological information, especially in the context of identifying plasma-based biomarkers of disease. In this study, a separation and enrichment strategy based on centrifugal ultrafiltration was developed for the LMF (i.e., <or=25K) of plasma routinely prepared from normal, healthy volunteers. Four commercially-available filter membranes of similar nominal molecular weight cut-off (NMWC), but differing membrane chemistries and filter orientations (Microcon, Millipore; Centrisart, Sartorius; Amicon Ultra, Millipore; Vivaspin, Sartorius), were evaluated. Of these filtration devices, only the Sartorius Vivaspin tangential membrane, NMWC 20K was effective in the non-retention of M(r)>50K, and recovery and enrichment of low-M(r) components from human plasma. This filter membrane device was further optimized with respect to plasma buffer composition, centrifugal force, duration and temperature. Optimal ultrafiltration conditions were obtained using 100 microL of normal plasma in 10% acetonitrile, and a centrifugation force of 4000x g for 35 min at 20 degrees C. In this LMF, 44 proteins (from 266 unique peptides) were identified using a combination of 1D-SDS-PAGE / nano-LC-MS/MS and a stringent level of identification (FDR <1%). We report the identification of several proteins (e.g., protein KIAA0649 (Q9Y4D3), rheumatoid factor D5, serine protease inhibitor A3, and transmembrane adapter protein PAG) previously not reported in extant high-confidence Human Proteome Organization (HUPO) Plasma Proteome Project datasets. When compared with the low-M(r) human plasma/serum proteome datasets of Zhou et al. (Electrophoresis, 2004. 25, 1289-98), Gundry et al. (Proteomics Clin. Appl., 2007. 1, 73-88) and Villanueva et al. (Anal Chem, 2004. 76, 1560-70), 64% of our identifications (28 proteins) were novel; these include cofilin-1, PPIase A, and the SH3 domain-binding glutamic acid-rich-like protein 3. In addition to intact proteins, many peptide fragments from high-abundance proteins (e.g., fibrinogen, clusterin, Factor XIIIa, transferrin, kinogen-1, and inter-alpha-trypsin inhibitor), presumably derived by ex vivo proteolysis, were observed.
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Here we review the use of informatics in structural interactomics, with particular emphasis on understanding interfacial contacts in the development of novel therapeutics and the interpretation of genetic variation. We describe the availability and applicability of structural databases of protein interactions which facilitate this endeavour. We demonstrate the applicability of a structural interactomics approach to the study of the fibroblast growth factor (FGF)-stimulated mitogen-activated protein kinase (MAPK) pathway.
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Biomarkers are decision-making tools at the basis of clinical diagnostics and essential for guiding therapeutic treatments. In this context, autoimmune diseases represent a class of disorders that need early diagnosis and steady monitoring. These diseases are usually associated with humoral or cell-mediated immune reactions against one or more of the body's own constituents. Autoantibodies fluctuating in biological fluids can be used as disease biomarkers and they can be, thus, detected by diagnostic immunoassays using native autoantigens. However, it is now accepted that post-translational modifications may affect the immunogenicity of self-protein antigens, triggering an autoimmune response and creating neo-antigens. In this case, post-translationally modified peptides represent a more valuable tool with respect to isolated or recombinant proteins. In fact, synthetic peptides can be specifically modified to mimic neo-antigens and to selectively detect autoantibodies as disease biomarkers. A 'chemical reverse approach' to select synthetic peptides, bearing specific post-translational modifications, able to fishing out autoantibodies from patients' biological fluids, can be successfully applied for the development of specific in vitro diagnostic/prognostic assays of autoimmune diseases. Herein, we report the successful application of this approach to the identification of biomarkers in different autoimmune diseases, such as systemic lupus erythematosus, rheumatoid arthritis and multiple sclerosis.
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Blood-related proteomics is an emerging field, recently gaining momentum. Indeed, a wealth of data is now available and a plethora of groups has contributed to add pieces to the jigsaw puzzle of protein complexity within plasma and blood cells. In this review article we purported to sail across the mare magnum of the actual knowledge in this research endeavour. The main strides in proteomic investigations on red blood cells, platelets, plasma and white blood cells are hereby presented in a chronological order. Moreover, a glance is given at prospective studies which promise to shift the focus of attention from the end product to its provider, the donor, in a sort of Kantian "Copernican revolution". A well-rounded portrait of the usefulness of proteomics in blood-related research is accurately given. In particular, proteomic tools could be adopted to follow the main steps of the blood-banking production processes (a comparison of collection methods, pathogen inactivation techniques, storage protocols). Thus proteomics has been recently transformed from a mere basic-research extremely-expensive toy into a dramatically-sensitive and efficient eye-lens to either delve into the depths of the molecular mechanisms of blood and blood components or to establish quality parameters in the blood-banking production chain totally anew.
Article
The use of combinatorial peptide ligand libraries, containing hexapeptides terminating with a primary amine, or modified with a terminal carboxyl group, allowed discovering and identifying a large number of previously unreported proteins in cow's whey. Whereas comprehensive whey protein lists progressively increased in the last 6 years from 17 unique gene products to more than 100, our findings have considerably expanded this list to a total of 149 unique protein species, of which 100 were not described in previous proteomics studies. As an additional interesting result, a polymorphic alkaline protein was observed with a strong positive signal when blotted from an isoelectric focusing separation in gel and tested with sera of allergic patients. This polymorphic protein, found only after treatment with the peptide library, was identified as an immunoglobulin (Ig), a minor allergen that had been largely amplified. The list of cow's whey components here reported is by far the most comprehensive at present and could serve as a starting point for the functional characterization of low-abundance proteins possibly having novel pharmaceutical, diagnostic, and biomedical applications.
Article
Despite continued increase in global Pharma R & D expenditure, the number of innovative drugs obtaining market approval has declined since 1994. The pharmaceutical industry is now entering a crucial juncture where increasing rates of attrition in clinical drug development as well as increasing development timelines are impacted by external factors such as intense regulatory pricing and safety pressures, increasing sales erosion due to generics, as well as exponential increases in the costs of bringing a drug to market. Despite these difficulties, numerous opportunities exist such as multiple unmet medical needs, the increasing incidence of certain diseases such as Alzheimer's disease, cancer, diabetes and obesity due to demographic changes, as well as the emergence of evolving markets such as China, India, and Eastern Europe. Consequently, Pharma is now responding to this challenge by improving both the productivity and the innovation in its drug discovery and development pipelines. In this regard, the advent of new technologies and expertise such as genomics, proteomics, structural biology, and molecular informatics in an integrated systems biology approach also provides a powerful opportunity for Pharma to address some of these difficulties. The key features behind this new strategy imply a discovery process based on an improved understanding of the molecular mechanism of diseases and drugs, translational research that places the patient at the center of the research process, and the application of biomarkers throughout the discovery and development phases. Moreover, new paradigms are required to improve target validation and develop more predictive cellular and animal models of human pathologies, a greater capacity in informatics-based analysis, and, consequently, a greater access to the vast sources of accumulating biological data and its integrated analysis. In the present review, we will address some of these issues and in particular emphasize how the application of biomarkers could potentially lead to improved productivity, quality, and innovation in drug discovery and ultimately better and safer medicines with improved therapeutic efficacy in specific pathologies for targeted patients.
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The HUPO Plasma Proteome Project new phase, PPP-2, held its initial workshop on 17 August, 2008, at the 7(th) World Congress of Proteomics in Amsterdam. Technology platforms, data repositories, informatics, and engagement of research groups for the submission of major datasets were key topics. Plasma is expected to be the common pathway for biomarker development and application through collaboration and integration with other HUPO initiatives.
Article
In plasma proteomics, before a proteome analysis, it is essential to prepare protein samples without high-abundance proteins, including albumin, via specific preparation techniques, such as immunoaffinity capture. However, our preliminary experiments suggested that functional changes with use alter the ability of the immunoaffinity column. Thus, in this study, to evaluate the changes of the removal ability of abundant proteins from plasma by the immunoaffinity column, plasma proteome analysis was performed for the long-term test for the reproducibility of the affinity column using the fluorogenic derivatization-liquid chromatography-tandem mass spectrometry method combined with an IgY column. The specific adsorption for albumin decreased with an increase in the number of the column usage before its expiration date. Moreover, it was demonstrated that hydrophobic high molecular weight compounds in plasma adsorbed onto the column materials surface contributed to the functional changes from specific immunoaffinity adsorption into hydrophobic interaction. These results suggested that, in quantitative plasma proteomics studies, it is important to keep in mind the risk of not only the nonselective loss but also the changes in the adsorption ability of the immunoafinity column.
Article
The most abundant proteins in serum, such as albumin and IgG, act as molecular sponges that bind and transport low molecular weight proteins/peptides and drugs. In the near future, pharmacoproteomics, the use of proteomic technologies in the field of drug discovery and development, and interactomics, the branch of proteomics which is concerned with identifying interactions between proteins, will allow researchers to (i) know the specific protein changes that occur in biological compartments in response to drug administration; (ii) design small novel therapeutic molecules that can have extended half-lives if carried by plasma protein in the blood stream. Advances in these fields will open new avenues of tailor-made molecular therapy, reducing present limitations on treatment arising from toxicity and inefficiency. In this short review we report and discuss the most recent developments arising from the use of proteomic tools in blood plasma protein research, looking at the identification of proteins found in plasma as well as their interactions with small molecules such as drugs, peptides, organic chemicals and metals. We believe this research demonstrates that proteomic technologies, and in particular pharmacoproteomics, interactomics and post-translational modification analysis, could be instrumental in the design of new tailor-made drugs leading to substantial improvements in molecular therapy.
Article
Metastasis is a common phenomenon and the major lethal cause of lung adenocarcinoma (AdC). To discover novel potential biomarkers associated with lymph node metastasis and prognosis in lung AdC, we assessed differences in protein expression between primary lung AdC with (LNM AdC) and without lymph node metastasis (non-LNM AdC) using a quantitative proteomic approach. Laser capture microdissection was performed to purify the cancer cells from primary lung AdC tissues. The differential proteins between the pooled microdissected non-LNM AdC and LNM AdC tissues were identified by two-dimensional difference gel electrophoresis (2D-DIGE) coupled with mass spectrometry (MS). In this study, twenty proteins were found to be differentially expressed in two types of lung AdC. ANXA3, significantly up-regulated in LNM AdC compared with non-LNM AdC, was validated by western blotting. Immunohistochemistry showed that ANXA3 over-expression was frequently observed in LNM AdCs and matched lymph node metastases compared with non-LNM AdCs. ANXA3 over-expression was significantly associated with advanced clinical stage (p < 0.001) and lymph node metastasis (p < 0.001) and increased relapse rate (p < 0.001) and decreased overall survival (p < 0.001) in lung AdCs. Cox regression analysis indicated ANXA3 over-expression was an independent prognostic factor. Our results indicate that ANXA3 might serve as a novel biomarker for lymph node metastasis and prognosis in lung AdC, and play an important role in lung AdC progression.
Article
Biological membranes form an essential barrier between living cells and their external environments, as well as serve to compartmentalize intracellular organelles within eukaryotes. The latter includes membranes that envelope the nucleus, the outer and inner membranes of the mitochondria, membrane cisternae complex of the ER, Golgi apparatus, as well as lysosomes and secretory vesicles. Depending on their localizations in the whole organism and also within the cell, these membranes have different, highly specialized functions. Although 30% of naturally occurring proteins are predicted to be embedded in biological membranes, membrane proteomics is traditionally understudied due to difficulties in solubilizing, separating, and identifying membrane proteins. Given the importance of membrane proteins in the various cellular processes listed in this review, as well as the roles they play in diseases and their potential as drug targets, it is imperative that this class of proteins be better studied. With the recent advancement in technology, it is expected that some of the difficulties in membrane proteomics will be overcome, yielding new data on membrane proteins.
Article
We present here the estimation of the upper limit of the number of molecular targets in the human genome that represent an opportunity for further therapeutic treatment. We select around approximately 6300 human proteins that are similar to sequences of known protein targets collected from DrugBank database. Our bioinformatics study estimates the size of 'druggable' human genome to be around 20% of human proteome, i.e. the number of the possible protein targets for small-molecule drug design in medicinal chemistry. We do not take into account any toxicity prediction, the three-dimensional characteristics of the active site in the predicted 'druggable' protein families, or detailed chemical analysis of known inhibitors/drugs. Instead we rely on remote homology detection method Meta-BASIC, which is based on sequence and structural similarity. The prepared dataset of all predicted protein targets from human genome presents the unique opportunity for developing and benchmarking various in silico chemo/bio-informatics methods in the context of the virtual high throughput screening.
Article
A discontinuous electrophoretic system for the isolation of membrane proteins from acrylamide gels has been developed using equipment for sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Coomassie dyes were introduced to induce a charge shift on the proteins and aminocaproic acid served to improve solubilization of membrane proteins. Solubilized mitochondria or extracts of heart muscle tissue, lymphoblasts, yeast, and bacteria were applied to the gels. From cells containing mitochondria, all the multiprotein complexes of the oxidative phosphorylation system were separated within one gel. The complexes were resolved into the individual polypeptides by second-dimension Tricine-SDS-PAGE or extracted without SDS for functional studies. The recovery of all respiratory chain complexes was almost quantitative. The percentage recovery of functional activity depended on the respective protein complex studied and was zero for some complexes, but almost quantitative for others. The system is especially useful for small scale purposes, e.g., separation of radioactively labeled membrane proteins, N-terminal protein sequencing, preparation of proteins for immunization, and diagnostic studies of inborn neuromuscular diseases.
Article
Peptides play a central role in many physiological processes. In order to comprehensively analyze all peptides and small proteins of a whole organism or a subsystem (peptidome), technologies other than 2-D gel electrophoresis are required. Although systematic efforts directed at peptides and peptidomes, comparable to the numerous proteomics projects, are largely lacking to date, a number that employ liquid chromatography or affinity purification and mass spectrometric identification have now been developed and applied successfully to the analysis of a variety of different peptide sources. Furthermore, distinct peptide classes, such as antimicrobial peptides or peptides related to metabolic diseases such as diabetes/obesity, are once again receiving attention. Here we discuss peptides in terms of their applicability to serve as diagnostic markers (or more generally as biomarkers), as well as therapeutic targets or lead compounds. There are also a number of technological challenges that need to be overcome in the study of potent animal venoms and plant toxins, both of which are generally peptides and which are discussed as potential lead compounds for therapeutic intervention in diseases such as cancer.
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Imaging sciences have grown exponentially during the past three decades, and many techniques, such as magnetic resonance imaging, nuclear tomographic imaging and X-ray computed tomography, have become indispensable in clinical use. Advances in imaging technologies and imaging probes for humans and for small animals are now extending the applications of imaging further into drug discovery and development, and have the potential to considerably accelerate the process. This review summarizes some of the recent developments in conventional and molecular imaging, and highlights their impact on drug discovery.
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Cataloging the proteomes of single-celled microorganisms, cells, biological fluids, tissue and whole organisms is being undertaken at a rapid pace as advances are made in protein and peptide separation, detection and identification. For metazoans, subcellular organelles represent attractive targets for global proteome analysis because they represent discrete functional units, their complexity in protein composition is reduced relative to whole cells and, when abundant cytoskeletal proteins are removed, lower abundance proteins specific to the organelle are revealed. Here, we review recent literature on the global analysis of subcellular organelles and briefly discuss how that information is being used to elucidate basic biological processes that range from cellular signaling pathways through protein-protein interactions to differential expression of proteins in response to external stimuli. We assess the relative merits of the different methods used and discuss issues and future directions in the field.
Article
The genomic era has brought with it a basic change in experimentation, enabling researchers to look more comprehensively at biological systems. The sequencing of the human genome coupled with advances in automation and parallelization technologies have afforded a fundamental transformation in the drug target discovery paradigm, towards systematic whole genome and proteome analyses. In conjunction with novel proteomic techniques, genome-wide annotation of function in cellular models is possible. Overlaying data derived from whole genome sequence, expression and functional analysis will facilitate the identification of causal genes in disease and significantly streamline the target validation process. Moreover, several parallel technological advances in small molecule screening have resulted in the development of expeditious and powerful platforms for elucidating inhibitors of protein or pathway function. Conversely, high-throughput and automated systems are currently being used to identify targets of orphan small molecules. The consolidation of these emerging functional genomics and drug discovery technologies promises to reap the fruits of the genomic revolution.
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An increasing number of proteomic strategies rely on liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect and identify constituent peptides of enzymatically digested proteins obtained from various organisms and cell types. However, sample preparation methods for isolating membrane proteins typically involve the use of detergents and chaotropes that often interfere with chromatographic separation and/or electrospray ionization. To address this problem, a sample preparation method combining carbonate extraction, surfactant-free organic solvent-assisted solubilization, and proteolysis was developed and demonstrated to target the membrane subproteome of Deinococcus radiodurans. Out of 503 proteins identified, 135 were recognized as hydrophobic on the basis of their calculated hydropathy values (GRAVY index), corresponding to coverage of 15% of the predicted hydrophobic proteome. Using the PSORT algorithm, 53 of the proteins identified were classified as integral outer membrane proteins and 215 were classified as integral cytoplasmic membrane proteins. All identified integral cytoplasmic membrane proteins had from 1 to 16 mapped transmembrane domains (TMDs), and 65% of those containing four or more mapped TMDs were identified by at least one hydrophobic membrane spanning peptide. The extensive coverage of the membrane subproteome (24%) by identification of highly hydrophobic proteins containing multiple TMDs validates the efficacy of the described sample preparation technique to isolate and solubilize hydrophobic integral membrane proteins from complex protein mixtures.
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The emerging field of biomarkers has applications in the diagnosis, staging, prognosis and monitoring of disease progression, as well as in the monitoring of clinical responses to a therapeutic intervention and the development and delivery of personalized treatments to reduce attrition in clinical trials. Moreover, biomarkers have a positive impact on health economics. The word "biomarker" has been used extensively across therapeutic areas and many disciplines, and its nature takes into consideration clinical, physiological, biochemical, developmental, morphological and molecular measures. In drug trials, biomarkers have been proposed for use in efficacy determination and patient population stratification, in deducing pharmacokinetic-pharmacodynamic relationships and in safety monitoring. The interfacing and integration of different technologies for data collection and analysis are pivotal to biomarker identification, characterization, validation and application. "Integrative functional informatics" represents a novel direction in such technology integration.
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Separation of complex protein mixtures that have a wide dynamic range of concentration, such as plasma or serum, is a challenge for proteomic analysis. Sample preparation to remove high-abundant proteins is essential for proteomics analysis. Immunoglobulin yolk (IgY) antibodies have unique and advantageous features that enable specific protein removal to aid in the detection of low-abundant proteins and biomarker discovery. This report describes the efficiency and effectiveness of IgY microbeads in separating 12 abundant proteins from plasma with an immunoaffinity spin column or LC column. The protein separation and sample preparation process was monitored via SDS-PAGE, 2-DE, LC-MS/MS, or clinical protein assays. The data demonstrate the high specificity of the protein separation, with removal of 95-99.5% of the abundant proteins. IgY microbeads against human proteins can also selectively remove orthologous proteins of other mammals such as mouse, rat, etc. Besides the specificity and reproducibility of the IgY microbeads, the report discusses the factors that may cause potential variations in protein separation such as protein-protein interactions (known as "Interactome"), binding and washing conditions of immunoaffinity reagents, etc. A novel concept of Seppromics is introduced to address methodologies and science of protein separation in a context of proteomics.
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There is a substantial list of pre-analytical variables that can alter the analysis of blood-derived samples. We have undertaken studies on some of these issues including choice of sample type, stability during storage, use of protease inhibitors, and clinical standardization. As there is a wide range of sample variables and a broad spectrum of analytical techniques in the HUPO PPP effort, it is not possible to define a single list of pre-analytical standards for samples or their processing. We present here a compendium of observations, drawing on actual results and sound clinical theories and practices. Based on our data, we find that (1) platelet-depleted plasma is preferable to serum for certain peptidomic studies; (2) samples should be aliquoted and stored preferably in liquid nitrogen; (3) the addition of protease inhibitors is recommended, but should be incorporated early and used judiciously, as some form non specific protein adducts and others interfere with peptide studies. Further, (4) the diligent tracking of pre-analytical variables and (5) the use of reference materials for quality control and quality assurance, are recommended. These findings help provide guidance on sample handling issues, with the overall suggestion being to be conscious of all possible pre-analytical variables as a prerequisite of any proteomic study.
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The human urinary proteome has been reassessed and re-evaluated via a novel concentration/equalization technique, exploiting beads coated with hexameric peptide ligand libraries. These beads act by capturing the whole protein spectra contained in the sample, by drastically reducing the level of the most abundant species, while strongly concentrating the more dilute and rare ones. In a control urine sample, 134 unique proteins could be identified. The first bead eluate (in thiourea, urea, and CHAPS) permitted the identification of 317 gene products, whereas the second eluate (in 9 M urea, pH 3.8) allowed the identification of another 95 unique proteins. By eliminating redundancies, a total of 383 unique gene products could be identified in human urines. This represents a major increment as compared to data reported in recent literature. By comparing our data with those reported to the present, an additional 251 proteins could be added to the list, thus bringing the total unique gene products so far identified in human urines to ca. 800 species.