High-throughput proteomics using antibody microarrays

Antibody-based microarrays are a novel technology that hold great promise in proteomics. Microarrays can be printed with thousands of recombinant antibodies carrying the desired specificities, the biologic sample (e.g., an entire proteome) and any specifically bound analytes detected. The microarray patterns that are generated can then be converted into proteomic maps, or molecular fingerprints, revealing the composition of the proteome. Using this tool, global proteome analysis and protein expression profiling will thus provide new opportunities for biomarker discovery, drug target identification and disease diagnostics, as well as providing insights into disease biology. Intense work is currently underway to develop this novel technology platform into the high-throughput proteomic tool required by the research community.     

Antibody microarrays: current status and key technological advances

Antibody-based microarrays are among the novel classes of rapidly evolving proteomic technologies that holds great promise in biomedicine. Miniaturized microarrays (< 1 cm2) can be printed with thousands of individual antibodies carrying the desired specificities, and with biological sample (e.g., an entire proteome) added, virtually any specifically bound analytes can be detected. While consuming only minute amounts (< microL scale) of reagents, ultra- sensitive assays (zeptomol range) can readily be performed in a highly multiplexed manner. The microarray patterns generated can then be transformed into proteomic maps, or detailed molecular fingerprints, revealing the composition of the proteome. Thus, protein expression profiling and global proteome analysis using this tool will offer new opportunities for drug target and biomarker discovery, disease diagnostics, and insights into disease biology. Adopting the antibody microarray technology platform, several biomedical applications, ranging from focused assays to proteome-scale analysis will be rapidly emerging in the coming years. This review will discuss the current status of the antibody microarray technology focusing on recent technological advances and key issues in the process of evolving the methodology into a high-performing proteomic research tool.     

Use of proteomics for the identification of novel drug targets in brain diseases

In spite of the rapid advances in the development of the new proteomic technologies, there are, to date, relatively fewer studies aiming to explore the neuronal proteome. One of the reasons is the complexity of the brain, which presents high cellular heterogeneity and a unique subcellular compartmentalization. Therefore, tissue fractionation of the brain to enrich proteins of interest will reduce the complexity of the proteomics approach leading to the production of manageable and meaningful results. In this review, general considerations and strategies of proteomics, the advantages and challenges to exploring the neuronal proteome are described and summarized. In addition, this article presents an overview of recent advances of proteomic technologies and shows that proteomics can serve as a valuable tool to globally explore the changes in brain proteome during various disease states. Understanding the molecular basis of brain function will be extremely useful in identifying novel targets for the treatment of brain diseases.     

Design of recombinant antibody microarrays for cell surface membrane proteomics

Generating proteomic maps of membrane proteins, common targets for therapeutic interventions and disease diagnostics, has turned out to be a major challenge. Antibody-based microarrays are among the novel rapidly evolving proteomic technologies that may enable global proteome analysis to be performed. Here, we have designed the first generation of a scaleable human recombinant scFv antibody microarray technology platform for cell surface membrane proteomics as well as glycomics targeting intact cells. The results showed that rapid and multiplexed profiling of the cell surface proteome (and glycome) could be performed in a highly specific and sensitive manner and that differential expression patterns due to external stimuli could be monitored.     

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

ABSTRACT

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

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

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

GelMap-a novel software tool for building and presenting proteome reference maps

Protein separation by two-dimensional gel electrophoresis is of central importance for proteomics. Upon combination with systematic protein identifications by mass spectrometry, large data sets are routinely generated in several proteome laboratories which can be used as "reference maps" for future analyses of analogous biochemical fractions. Here we present GelMap, a novel software tool for the building presentation and evaluation of proteomic reference maps. Variable frames are introduced in order to group proteins into functional categories on three levels or into categories according to differential abundance during comparative proteome analyses. The software is easy to handle as it only requires uploading two digital files to a web site. An additional file including detailed information on all proteins can be combined with the primary map. Two different gel-based projects are presented to illustrate the capacity of GelMap for proteome annotation and evaluation.     

Design of high-density antibody microarrays for disease proteomics: Key technological issues

Antibody-based microarray is a novel proteomic technology setting a new standard for molecular profiling of non-fractionated complex proteomes. The first generation of antibody microarrays has already demonstrated its potential for generating detailed protein expression profiles, or protein atlases, of human body fluids in health and disease, paving the way for new discoveries within the field of disease proteomics. The process of designing highly miniaturized, high-density and high-performing antibody microarray set-ups have, however, proven to be challenging. In this mini-review we discuss key technological issues that must be addressed in a cross-disciplinary manner before true global proteome analysis can be performed using antibody microarrays.     

Proteomic signatures in antibiotic research

Antibiotics disturb the physiological homeostasis of bacterial cells by interfering with essential cellular functions or structures. The bacterial proteome adjusts quickly in response to antibiotic challenge. This physiological response is specifically tailored to overcome the inflicted damage and, thus, closely linked to the antibiotic target and mechanism of action. In a way, the proteome mirrors the antibiotic insult. This connection can be exploited to guide the development of novel antibiotics. By using structurally different antibiotics, which cause the same physiological disturbance, proteomic signatures diagnostic of the mechanism of action can be defined. These proteomic signatures inform about mechanism-related differential protein expression as well as about protein modifications. This review recapitulates how antibiotic proteomic signatures are established and highlights areas of antibiotic research benefiting most from proteomic signatures. Antibacterial research programs designed to structurally advance existing antibiotic classes profit from rapid in vivo mechanism of action confirmation. What is more, a comprehensive reference compendium of antibiotic proteomic signatures allows rapid mechanism of action identification of those structurally novel compounds that inhibit known targets. Finally, novel proteomic response profiles indicate unprecedented mechanisms. Here, the proteome profile provides evidence on the nature of the antibiotic-caused physiological disturbance leading to testable hypotheses on the mechanism of action.     

Proteomic Approaches to Decipher Mechanisms Underlying Pathogenesis in Multiple Sclerosis Patients

Multiple sclerosis (MS) is a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system (CNS). The cause of MS is unknown, with no effective therapies available to halt the progressive neurological disability. Development of new and improvement of existing therapeutic strategies therefore require a better understanding of MS pathogenesis, especially during the progressive phase of the disease. This can be achieved through development of biomarkers that can help to identify disease pathophysiology and monitor disease progression. Proteomics is a powerful and promising tool to accelerate biomarker detection and contribute to novel therapeutics. In this review, an overview of how proteomic technology using CNS tissues and biofluids from MS patients has provided important clues to the pathogenesis of MS is provided. Current publications, pitfalls, as well as directions of future research involving proteomic approaches to understand the pathogenesis of MS are discussed.     

Challenges in translating plasma proteomics from bench to bedside: update from the NHLBI Clinical Proteomics Programs

The emerging scientific field of proteomics encompasses the identification, characterization, and quantification of the protein content or proteome of whole cells, tissues, or body fluids. The potential for proteomic technologies to identify and quantify novel proteins in the plasma that can function as biomarkers of the presence or severity of clinical disease states holds great promise for clinical use. However, there are many challenges in translating plasma proteomics from bench to bedside, and relatively few plasma biomarkers have successfully transitioned from proteomic discovery to routine clinical use. Key barriers to this translation include the need for "orthogonal" biomarkers (i.e., uncorrelated with existing markers), the complexity of the proteome in biological samples, the presence of high abundance proteins such as albumin in biological samples that hinder detection of low abundance proteins, false positive associations that occur with analysis of high dimensional datasets, and the limited understanding of the effects of growth, development, and age on the normal plasma proteome. Strategies to overcome these challenges are discussed.     

Proteomic analysis of human blood serum using peptide library beads

Human serum is thought to contain key information for diagnostics of human disease. However, no single technology is currently nor might ever be available to cope with the complexity and dynamic range of the serum proteome. We here report a large-scale proteomic study of human blood serum using peptide library beads and mass spectrometry. Serum proteins are adsorbed onto polymeric beads coated with a combinatorial library composed of millions of hexameric peptide baits. Analysis of the eluates from this combinatorial library (as obtained with 3 eluants of different strength, able to release 99% of the retentate) via liquid chromatography coupled to high-resolution mass spectrometry resulted in the identification of 1559 proteins or 3869 proteins, respectively, depending on how 95% confidence was estimated. In either case, the analysis showed that ligand beads are able to capture a large number of proteins in a single operation. The ligand bead bound fraction appeared to have a lower dynamic range when compared to the starting material, due to a "normalization" of the protein concentrations in the original mixture. We find that extensive information on the protein composition of complex samples such as serum can be obtained using ligand beads and that these beads enrich the proteomic tool box.     

Integrating intracellular and extracellular proteomic profiling for in-depth investigations of cellular communication in a model of prostate cancer

Cellular communication is essential for cell-cell interactions, maintaining homeostasis and progression of certain disease states. While many studies examine extracellular proteins, the holistic extracellular proteome is often left uncaptured, leaving gaps in our understanding of how all extracellular proteins may impact communication and interaction. We used a cellular-based proteomics approach to more holistically profile both the intracellular and extracellular proteome of prostate cancer. Our workflow was generated in such a manner that multiple experimental conditions can be observed with the opportunity for high throughput integration. Additionally, this workflow is not limited to a proteomic aspect, as metabolomic and lipidomic studies can be integrated for a multi-omics workflow. Our analysis showed coverage of over 8000 proteins while also garnering insights into cellular communication in the context of prostate cancer development and progression. Identified proteins covered a variety of cellular processes and pathways, allowing for the investigation of multiple aspects into cellular biology. This workflow demonstrates advantages for integrating intra- and extracellular proteomic analyses as well as potential for multi-omics researchers. This approach possesses great value for future investigations into the systems biology aspects of disease development and progression.     

Characterization of the human myocardial proteome in inflammatory dilated cardiomyopathy by label-free quantitative shotgun proteomics of heart biopsies

Dilated cardiomyopathy (DCM) is characterized by contractile dysfunction leading to heart failure. The molecular changes in the human heart associated with this disease have so far mostly been addressed at the gene expression level and only a few studies have analyzed global changes in the myocardial proteome. Therefore, our objective was to investigate the changes in the proteome in patients suffering from inflammatory DCM (iDCM) and chronic viral infection by a comprehensive quantitative approach. Comparative proteomic profiling of endomyocardial biopsies (EMB) from 10 patients with iDCM (left ventricular ejection fraction <40%, symptoms of heart failure) as well as 7 controls with normal left ventricular function and histology was performed by label-free proteome analysis (LC-MS/MS). Mass spectrometric data were analyzed with the Rosetta Elucidator software package. The analysis covered a total of 485 proteins. Among the 174 proteins displaying at least a 1.3-fold change in intensity (p < 0.05), major changes were observed for mitochondrial and cytoskeletal proteins, but also metabolic pathways were affected in iDCM compared to controls. In iDCM patients, we observed decreased levels of mitochondrial proteins involved in oxidative phosphorylation and tricarboxylic acid cycle. Furthermore, deregulation of proteins of carbohydrate metabolism, the actin cytoskeleton, and extracellular matrix remodeling was observed. Proteomic observations were confirmed by gene expression data and immunohistochemistry (e.g. collagen I and VI). This study demonstrates that label-free, mass spectrometry-centered approaches can identify disease dependent alterations in the proteome from small tissue samples such as endomyocardial biopsies. Thus, this technique might allow better disease characterization and may be a valuable tool in potential clinical proteomic studies.     

Proteomics applied to exercise physiology: a cutting-edge technology

Exercise research has always drawn the attention of the scientific community because it can be widely applied to sport training, health improvement, and disease prevention. For many years numerous tools have been used to investigate the several physiological adaptations induced by exercise stimuli. Nowadays a closer look at the molecular mechanisms underlying metabolic pathways and muscular and cardiovascular adaptation to exercise are among the new trends in exercise physiology research. Considering this, to further understand these adaptations as well as pathology attenuation by exercise, several studies have been conducted using molecular investigations, and this trend looks set to continue. Through enormous biotechnological advances, proteomic tools have facilitated protein analysis within complex biological samples such as plasma and tissue, commonly used in exercise research. Until now, classic proteomic tools such as one- and two-dimensional polyacrylamide gel electrophoresis have been used as standard approaches to investigate proteome modulation by exercise. Furthermore, other recently developed in gel tools such as differential gel electrophoresis (DIGE) and gel-free techniques such as the protein labeling methods (ICAT, SILAC, and iTRAQ) have empowered proteomic quantitative analysis, which may successfully benefit exercise proteomic research. However, despite the three decades of 2-DE development, neither classic nor novel proteomic tools have been convincingly explored by exercise researchers. To this end, this review gives an overview of the directions in which exercise-proteome research is moving and examines the main tools that can be used as a novel strategy in exercise physiology investigation.     

Analysing signalling networks by mass spectrometry

Sequence analysis of the human genome and the association of genetic aberrations with diseases have provided a rough framework whereby the impact of individual genotypes can be assessed. To fully understand the effect of individual and co-occurring genetic aberrations, as well as their individual and collected contribution to the development of diseases, it is critical to analyse the matching proteome and to determine how the organisation, expression level and function of protein networks are affected. Sensitive mass spectrometric platforms in combination with innovative workflows allow qualitative and quantitative analyses of the cellular as well as the extracellular proteome. Importantly, in addition to specifically identifying the content of the proteome, several aspects of the proteomic organisation can be analysed including protein complexes, protein modifications, enzymatic activities and subcellular/organelle localisation. Together, these measurements will provide novel insight into the biological effect of disease-causing mutations ultimately coupling genotype and phenotype.     

Current perspectives in cancer proteomics

Proteome technology has been used widely in cancer research and is a useful tool for the identification of new cancer markers and treatment-related changes in cancer. This article details the use of proteome technology in cancer research, and laboratory-based and clinical cancer research studies are described. New developments in proteome technology that enable higher sample-throughput are evaluated and methods for enhancing conventional proteome analysis (based on two-dimensional electrophoresis) discussed. The need to couple laboratory-based proteomics research with clinically relevant models of the disease is also considered, as this remains the next main challenge of cancer-related proteome research.     

Neuroproteomics: Expression Profiling of the Brain's Proteomes in Health and Disease

The term "proteome" describes the protein complement of a genome. Proteomes of cells are dynamic and are directly affected by environmental factors, such as stress and/or drug treatment, or as a result of aging and disease. One of the distinct advantages of proteomic analysis, not attainable with RNA expression data, is the ability to fractionate the cell's proteins into various subpopulations. In neuroscience, "neuromics" (proteomics in the central nervous system) is in its infancy, with a paucity of studies in the context of the brain. One of the objectives of this review is to illustrate the potential of neuromics to profile differences in the distribution of thousands of proteins as a function of disease markers. We have previously used this approach to determine the effects of varied postmortem interval in examining human brain tissue and to identify biomarkers. Here we review proteomic studies of schizophrenia, Alzheimer's disease, and Parkinson's disease. Experimental results regarding Parkinson's disease are presented to illustrate the potential of neuromics to identify pathways of pathogenesis and novel therapeutic targets.