High-throughput antibody microarrays for quantitative proteomic analysis

The antibody microarray is an intrinsically robust and quantitative system that delivers high-throughput and parallel measurements on particular sets of known proteins. It has become an important proteomics research tool, complementary to the conventional unbiased separation-based and mass spectrometry-based approaches. This review summarizes the technical aspects of production and the application for quantitative proteomic analysis with an emphasis on disease proteomics, especially the identification of biomarkers. Quality control, data analysis methods and the challenges for quantitative assays are also discussed.     

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.     

High-throughput antibody isolation

To define the proteome of an organism, there is a need for robust and reproducible methods for the quantitative detection of all the polypeptides in a cell. High-density arrays of receptors specific for each of the polypeptides in a complex sample hold great promise for the analysis of complex protein mixtures. Because of their high affinity, specificity and their ability to bind to virtually any protein, antibodies appear particularly promising as the receptor element in protein-detection arrays. For proteomic-scale analyses, the ability to isolate and produce antibodies en masse to large numbers of target molecules is critical. A variety of systems for the high-throughput isolation of antibodies from combinatorial libraries are being developed and are outlined in this review. However, there are several other important considerations to be borne in mind before such systems can realistically be applied on a large scale.     

Tissue microarrays as a platform for proteomic investigation

Tissue microarrays have become an essential tool in translational pathology. They are used to confirm results from other experimental platforms, such as expression microarrays, as well as a primary tool to explore the expression profile of proteins by immunohistochemical analysis. Tissue microarrays are routinely used molecular epidemiology, drug development and determining the diagnostic, prognostic and predictive value of new biomarkers. By applying traditional protein based assays, as well as novel assays to the platform, tissue microarrays have gained a new utility as a proteomic tool for both basic science as well as clinical investigation. This article will explore the new approaches that are being applied to tissue microarrays to, characterize the human proteome, and new technologies that allow tissue microarrays to function as a protein array. The U.S. Government's right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged     

High-throughput isotopic analysis of RNA microarrays to quantify microbial resource use

Most microorganisms remain uncultivated, and typically their ecological roles must be inferred from diversity and genomic studies. To directly measure functional roles of uncultivated microbes, we developed Chip-stable isotope probing (SIP), a high-sensitivity, high-throughput SIP method performed on a phylogenetic microarray (chip). This approach consists of microbial community incubations with isotopically labeled substrates, hybridization of the extracted community rRNA to a microarray and measurement of isotope incorporation—and therefore substrate use—by secondary ion mass spectrometer imaging (NanoSIMS). Laboratory experiments demonstrated that Chip-SIP can detect isotopic enrichment of 0.5 atom % ¹³C and 0.1 atom % ¹⁵N, thus permitting experiments with short incubation times and low substrate concentrations. We applied Chip-SIP analysis to a natural estuarine community and quantified amino acid, nucleic acid or fatty acid incorporation by 81 distinct microbial taxa, thus demonstrating that resource partitioning occurs with relatively simple organic substrates. The Chip-SIP approach expands the repertoire of stable isotope-enabled methods available to microbial ecologists and provides a means to test genomics-generated hypotheses about biogeochemical function in any natural environment.     

High-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue microarrays using MALDI imaging mass spectrometry

A novel method for high-throughput proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMA) is described using on-tissue tryptic digestion followed by MALDI imaging MS. A TMA section containing 112 needle core biopsies from lung-tumor patients was analyzed using MS and the data were correlated to a serial hematoxylin and eosin (H&E)-stained section having various histological regions marked, including cancer, non-cancer, and normal ones. By correlating each mass spectrum to a defined histological region, statistical classification models were generated that can sufficiently distinguish biopsies from adenocarcinoma from squamous cell carcinoma biopsies. These classification models were built using a training set of biopsies in the TMA and were then validated on the remaining biopsies. Peptide markers of interest were identified directly from the TMA section using MALDI MS/MS sequence analysis. The ability to detect and characterize tumor marker proteins for a large cohort of FFPE samples in a high-throughput approach will be of significant benefit not only to investigators studying tumor biology, but also to clinicians for diagnostic and prognostic purposes.     

Combining microarrays and genetic analysis

Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a study is not a matter of simply applying the existing and more-or-less standard computational tools for microarrays to a new type of experimental data. It is shown how to fully exploit the power of genetics through optimal experimental design and analysis for two major microarray technologies, cDNA two-colour arrays and Affymetrix short oligonucleotide arrays.     

Diagnostic and analytical applications of protein microarrays

DNA microarrays have changed the field of biomedical sciences over the past 10 years. For several reasons, antibody and other protein microarrays have not developed at the same rate. However, protein and antibody arrays have emerged as a powerful tool to complement DNA microarrays during the past 5 years. A genome-scale protein microarray has been demonstrated for identifying protein–protein interactions as well as for rapid identification of protein binding to a particular drug. Furthermore, protein microarrays have been shown as an efficient tool in cancer profiling, detection of bacteria and toxins, identification of allergen reactivity and autoantibodies. They have also demonstrated the ability to measure the absolute concentration of small molecules. Besides their capacity for parallel diagnostics, microarrays can be more sensitive than traditional methods such as enzyme-linked immunosorbent assay, mass spectrometry or high-performance liquid chromatography-based assays. However, for protein and antibody arrays to be successfully introduced into diagnostics, the biochemistry of immunomicroarrays must be better characterized and simplified, they must be validated in a clinical setting and be amenable to automation or integrated into easy-to-use systems, such as micrototal analysis systems or point-of-care devices.     

iTRAQ标记技术与差异蛋白质组学的生物标志物研究

结合多维液相色谱和串联质谱分析,iTRAQ技术已成为差异蛋白质组学定量研究的主要工具之一。而寻找和发现区别于正常生理状态下的疾病特异表达蛋白质,有利于阐明疾病的发病机理,对疾病的预防、诊断、预后和疗效监测具有重要作用,并有助于用作新靶点来开发临床治疗药物。本文重点就该技术在医学领域中进行差异蛋白质组分析并寻找标记蛋白质的研究进行综述。     

Improvement of protein stability in protein microarrays

Protein stability in microarrays was improved using protein stabilizers. PEG 200 at 30% (w/v) was the most efficient stabilizer giving over 4-fold improvement in protein stability compared to without the stabilizer. PEG 200 above 10% (w/v) in the array solution prevented the evaporation of water in the sample and thereby improved protein stability in the microarray. When the streptavidin-biotin binding reaction was performed under optimized conditions, biotin-BSA-fluorescein isothiocyanate (FITC) was detected from 1 ng ml^–1 to 5 g ml^–1 by fluorescence analysis.     

Allelic dosage analysis with genotyping microarrays

Genomic alternations, including dosage and allelic imbalance, constitute a major basis of neoplastic and other genetic disorders. Using oligonucleotide genotyping microarrays, here we report the development and usage of an algorithm, called genome imbalance map (GIM) algorithm, for allelic as well as total gene dosage analysis. Using the GIM algorithm, global genome imbalance status at over 100,000 loci was simultaneously analyzed with unprecedented accuracy and allelic discrimination.     

Protein microarrays and their applications

In recent years, the importance of proteomic works, such as protein expression, detection and identification, has grown in the fields of proteomic and diagnostic research. This is because complete genome sequences of humans, and other organisms, progress as cellular processing and controlling are performed by proteins as well as DNA or RNA. However, conventional protein analyses are time-consuming; therefore, high throughput protein analysis methods, which allow fast, direct and quantitative detection, are needed. These are so-called protein microarrays or protein chips, which have been developed to fulfill the need for high-throughput protein analyses. Although protein arrays are still in their infancy, technical development in immobilizing proteins in their native conformation on arrays, and the development of more sensitive detection methods, will facilitate the rapid deployment of protein arrays as high-throughput protein assay tools in proteomics and diagnostics. This review summarizes the basic technologies that are needed in the fabrication of protein arrays and their recent applications.     

Data merging for integrated microarray and proteomic analysis.

The functioning of even a simple biological system is much more complicated than the sum of its genes, proteins and metabolites. A premise of systems biology is that molecular profiling will facilitate the discovery and characterization of important disease pathways. However, as multiple levels of effector pathway regulation appear to be the norm rather than the exception, a significant challenge presented by high-throughput genomics and proteomics technologies is the extraction of the biological implications of complex data. Thus, integration of heterogeneous types of data generated from diverse global technology platforms represents the first challenge in developing the necessary foundational databases needed for predictive modelling of cell and tissue responses. Given the apparent difficulty in defining the correspondence between gene expression and protein abundance measured in several systems to date, how do we make sense of these data and design the next experiment? In this review, we highlight current approaches and challenges associated with integration and analysis of heterogeneous data sets, focusing on global analysis obtained from high-throughput technologies.     

Optimization of NMR analysis of biological fluids for quantitative accuracy

With the rising interest in the use of nuclear magnetic resonance (NMR) for the study of biological fluids such as urine and serum for metabonomic or diagnostic purposes, new challenges have arisen concerning the efficacy of NMR data acquisition and analysis. In particular the quantification of sample constituents such as metabolites is of great importance. This study compares five one-dimensional proton NMR pulse sequences using synthetic urine samples to determine appropriate acquisition parameters for reasonable sample throughput and accuracy. Each pulse sequence has its own advantages and limitations with respect to solvent suppression, stable baseline, exchangeable protons, and quantization of resonances near the residual water peak. Hardware issues such as low-pass filters, unique to each spectrometer, also impact quantitation accuracy. Metabolite concentrations were determined using integration referenced to an added internal standard, and using the Chenomx NMR Suite software package. Since nuclei in different metabolites and the internal standard all have different longitudinal relaxation rates (T ₁) we included a mathematical correction factor for quantitation.     

Chemically-blocked antibody microarray for multiplexed high-throughput profiling of specific protein glycosylation in complex samples

In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed.     

Development and standardization of multiplexed antibody microarrays for use in quantitative proteomics

BACKGROUND: Quantitative proteomics is an emerging field that encompasses multiplexed measurement of many known proteins in groups of experimental samples in order to identify differences between groups. Antibody arrays are a novel technology that is increasingly being used for quantitative proteomics studies due to highly multiplexed content, scalability, matrix flexibility and economy of sample consumption. Key applications of antibody arrays in quantitative proteomics studies are identification of novel diagnostic assays, biomarker discovery in trials of new drugs, and validation of qualitative proteomics discoveries. These applications require performance benchmarking, standardization and specification. RESULTS: Six dual-antibody, sandwich immunoassay arrays that measure 170 serum or plasma proteins were developed and experimental procedures refined in more than thirty quantitative proteomics studies. This report provides detailed information and specification for manufacture, qualification, assay automation, performance, assay validation and data processing for antibody arrays in large scale quantitative proteomics studies. CONCLUSION: The present report describes development of first generation standards for antibody arrays in quantitative proteomics. Specifically, it describes the requirements of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; provides the rationale for the application of standardized statistical approaches to manage the data output of highly replicated assays; defines design requirements for controls to normalize sample replicate measurements; emphasizes the importance of stringent quality control testing of reagents and antibody microarrays; recommends the use of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and presents survey procedures to reveal the significance of biomarker findings.     

Proteomic analysis of Saccharomyces cerevisiae

Nowadays, proteomics is recognized as one of the fastest growing tools in many areas of research. This is especially true for the study of Saccharomyces cerevisiae, as it is considered to be a model organism for eukaryotic cells. Proteomic analysis provides an insight into global protein expressions from identification to quantitation, from localization to function, and from individual to network systems. Moreover, many methods for identification and quantitation of proteins based on tandem mass spectrometry workflows have recently been developed and widely applied in S. cerevisiae. The current methods and issues in the proteomic analysis of S. cerevisiae are reviewed here.     

Transfected cell microarrays: an efficient tool for high-throughput functional analysis

Transfected cell microarrays are considered to be a breakthrough methodology for high-throughput and high-content functional genomics. Here, recent advances in the cell microarray field are reviewed, along with its potential to increase the speed of determining gene function. These advances, combined with an increasing number and diversity of gene perturbing systems, such as RNAi and ectopic gene expression, provide tools for expanding our understanding of biology at the systems level.     

The inflammatory side of human chondrocytes unveiled by antibody microarrays

Although being largely used for pathobiological models of cartilage diseases such as osteoarthritis (OA), human chondrocytes are still enigmatic cells, in as much as a large part of their secretome is unknown. We took advantage of the recent development of antibody-based microarrays to study multiple protein expression by human chondrocytes obtained from one healthy and five osteoarthritic joints, in unstimulated conditions or after stimulation by the proinflammatory cytokines interleukin-1 (IL-1) or tumour necrosis factor (TNF). The secretion media of chondrocytes were incubated with array membranes consisting of 79 antibodies directed against cytokines, chemokines, and angiogenic or growth factors. Several proteins were identified as new secretion products of chondrocytes, including the growth or angiogenic factors EGF, thrombopoietin, GDNF, NT-3 and -4, and PlGF, the chemokines ENA-78, MCP-2, IP-10, MIP-3alpha, NAP-2, PARC, and the cytokines MIF, IL-12, and IL-16. Most of the newly identified chemokines were increased intensely after stimulation by IL-1 or TNF, as for other proteins of the array, including GRO proteins, GM-CSF, IL-6, IL-8, MIP-1beta, GCP-2, and osteoprotegerin. The up-regulation by cytokines suggested that these proteins may participate in the destruction of cartilage and/or in the initiation of chemotactic events within the joint during OA. In conclusion, the microarray approach enabled to unveil part of an as yet unexplored chondrocyte secretome. Our findings demonstrated that chondrocytes were equipped with a proinflammatory arsenal of proteins which may play an important part in the pathogenesis of OA and/or its drift towards an inflammatory, rheumatoid phenotype.     

High-throughput screening for developability during early-stage antibody discovery using self-interaction nanoparticle spectroscopy

The discovery of monoclonal antibodies (mAbs) that bind to a particular molecular target is now regarded a routine exercise. However, the successful development of mAbs that (1) express well, (2) elicit a desirable biological effect upon binding, and (3) remain soluble and display low viscosity at high concentrations is often far more challenging. Therefore, high throughput screening assays that assess self-association and aggregation early in the selection process are likely to yield mAbs with superior biophysical properties. Here, we report an improved version of affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) that is capable of screening large panels of antibodies for their propensity to self-associate. AC-SINS is based on concentrating mAbs from dilute solutions around gold nanoparticles pre-coated with polyclonal capture (e.g., anti-Fc) antibodies. Interactions between immobilized mAbs lead to reduced inter-particle distances and increased plasmon wavelengths (wavelengths of maximum absorbance), which can be readily measured by optical means. This method is attractive because it is compatible with dilute and unpurified mAb solutions that are typical during early antibody discovery. In addition, we have improved multiple aspects of this assay for increased throughput and reproducibility. A data set comprising over 400 mAbs suggests that our modified assay yields self-interaction measurements that are well-correlated with other lower throughput assays such as cross-interaction chromatography. We expect that the simplicity and throughput of our improved AC-SINS method will lead to improved selection of mAbs with excellent biophysical properties during early antibody discovery.