Validation of serum protein profiles by a dual antibody array approach

In recent years, affinity-based technologies have become important tools for serum profiling to uncover protein expression patterns linked to disease state or therapeutic effects. In this study, we describe a path towards the production of an antibody microarray to allow protein profiling of biotinylated human serum samples with reproducible sensitivity in the picomolar range. With the availability of growing numbers of affinity reagents, protein profiles are to be validated in efficient manners and we describe a cross-platform strategy based on data concordance with a suspension bead array to interrogate the identical set of antibodies with the same cohort of serum samples. Comparative analysis enabled to screen for high-performing antibodies, which were displaying consistent results across the two platforms and targeting known serum components. Moreover, data processing methods such as sample referencing and normalization were evaluated for their effects on inter-platform agreement. Our work suggests that mutual validation of protein expression profiles using alternative microarray platforms holds great potential in becoming an important and valuable component in affinity-based high-throughput proteomic screenings as it allows to narrow down the number of discovered targets prior to orthogonal, uniplexed validation approaches.     

Optimized normalization for antibody microarrays and application to serum-protein profiling

The measurements of coordinated patterns of protein abundance using antibody microarrays could be used to gain insight into disease biology and to probe the use of combinations of proteins for disease classification. The correct use and interpretation of antibody microarray data requires proper normalization of the data, which has not yet been systematically studied. Therefore we undertook a study to determine the optimal normalization of data from antibody microarray profiling of proteins in human serum specimens. Forty-three serum samples collected from patients with pancreatic cancer and from control subjects were probed in triplicate on microarrays containing 48 different antibodies, using a direct labeling, two-color comparative fluorescence detection format. Seven different normalization methods representing major classes of normalization for antibody microarray data were compared by their effects on reproducibility, accuracy, and trends in the data set. Normalization with ELISA-determined concentrations of IgM resulted in the most accurate, reproducible, and reliable data. The other normalization methods were deficient in at least one of the criteria. Multiparametric classification of the samples based on the combined measurement of seven of the proteins demonstrated the potential for increased classification accuracy compared with the use of individual measurements. This study establishes reliable normalization for antibody microarray data, criteria for assessing normalization performance, and the capability of antibody microarrays for serum-protein profiling and multiparametric sample classification.     

Design of recombinant antibody microarrays for complex proteome analysis: choice of sample labeling-tag and solid support

Antibody-based microarray is a novel technology with great potential within high-throughput proteomics. The process of designing high-performing antibody (protein) microarrays has, however, turned out to be a challenging process. In this study, we have developed further our human recombinant single-chain variable-fragment (scFv) antibody microarray methodology by addressing two crucial technological issues, choice of sample labeling-tag and solid support. We examined the performance of a range of dyes in a one- or two-color approach on a selection of solid supports providing different surface and coupling chemistries, and surface structures. The set-ups were evaluated in terms of sensitivity, specificity, and selectivity. The results showed that a one-color approach, based on NHS-biotin (or ULS-biotin) labeling, on black polymer Maxisorb slides (or Nexterion slide H) was the superior approach for targeting low-abundant (pg/mL) analytes in nonfractionated, complex proteomes, such as human serum or crude cell supernatants. Notably, microarrays displaying adequate spot morphologies, high S/Ns, minimized nonspecific binding, and most importantly a high selectivity, specificity, and sensitivity (>or=fM range) were obtained. Taken together, we have designed the first generation of a high-performing recombinant scFv antibody microarray technology platform on black polymer Maxisorb slides for sensitive profiling of low-abundant analytes in nonfractionated biotinylated complex proteomes.     

A novel four-dimensional strategy combining protein and peptide separation methods enables detection of low-abundance proteins in human plasma and serum proteomes

A novel strategy, termed protein array pixelation, is described for comprehensive profiling of human plasma and serum proteomes. This strategy consists of three sequential high-resolution protein prefractionation methods (major protein depletion, solution isoelectrofocusing, and 1-DE) followed by nanocapillary RP tryptic peptide separation prior to MS/MS analysis. The analysis generates a 2-D protein array where each pixel in the array contains a group of proteins with known pI and molecular weight range. Analysis of the HUPO samples using this strategy resulted in 575 and 2890 protein identifications from plasma and serum, respectively, based on HUPO-approved criteria for high-confidence protein assignments. Most importantly, a substantial number of low-abundance proteins (low ng/mL - pg/mL range) were identified. Although larger volumes were used in initial prefractionation steps, the protein identifications were derived from fractions equivalent to approximately 0.6 microL (45 microg) of plasma and 2.4 microL (204 microg) of serum. The time required for analyzing the entire protein array for each sample is comparable to some published shotgun analyses of plasma and serum proteomes. Therefore, protein array pixelation is a highly sensitive method capable of detecting proteins differing in abundance by up to nine orders of magnitude. With further refinement, this method has the potential for even higher capacity and higher throughput.     

脱-R-羧基凝血酶原的Ba- 蛋白芯片法的建立和应用

目的：研发建立一种快速、特异性高、低成本的检测血清中脱-r- 羧基凝血酶原（DCP）的蛋白芯片,并通过检测DCP 阳性肝 细胞肝癌（HCC）血清临床样本对其进行评价。方法：首先采用柠檬酸钡吸附沉淀法去除血清中正常凝血酶原,然后通过双抗体夹 心法蛋白芯片检测血清中DCP 含量。通过Ba- 蛋白芯片法检测41 例DCP阳性HCC患者血清和66 例健康人血清,进行盲法验 证。结果：通过Ecarin- 显色多肽底物法证实柠檬酸钡吸附沉淀法能够完全除血清中正常凝血酶原,根据" 平均数+3× 标准差" 公式设置蛋白芯片的Cut-off值作为阳性判定标准,Ba-蛋白芯片法检测DCP阳性HCC血清的灵敏度为95.1 %（39/41）,特异度 为100 %（66/66）。结论：成功建立检测血清中DCP浓度的Ba- 蛋白芯片法,为多种标志物联合检测HCC 的蛋白芯片的研发提供 候选血清标志物。     

Development of a "reverse capture" autoantibody microarray for studies of antigen-autoantibody profiling

Diagnosing cancers based on serum profiling is a particularly attractive concept. However, the technical challenges to analysis of the serum proteome arise from the dynamic range of protein amounts. Cancer sera contain antibodies that react with a unique group of autologous cellular antigens, which affords a dramatic amplification of signal in the form of antibodies relative to the amount of the corresponding antigens. The serum autoantibody repertoire from cancer patients might, therefore, be exploited for antigen-antibody profiling. To date, studies of antigen-antibody reactivity using microarrays have relied on recombinant proteins or synthetic peptides as arrayed features. However, recombinant proteins and/or synthetic peptides may fail to accurately detect autoantibody binding due to the lack of proper PTMs. Here we describe the development and use of a "reverse capture" autoantibody microarray. Our "reverse capture" autoantibody microarray is based on the dual-antibody sandwich immunoassay platform of ELISA, which allows the antigens to be immobilized in their native configuration. As "proof-of-principle", we demonstrate its use for antigen-autoantibody profiling with sera from patients with prostate cancer and benign prostate hyperplasia.     

Immunoassay and antibody microarray analysis of the HUPO Plasma Proteome Project reference specimens: systematic variation between sample types and calibration of mass spectrometry data

Four different immunoassay and antibody microarray methods performed at four different sites were used to measure the levels of a broad range of proteins (N = 323 assays; 39, 88, 168, and 28 assays at the respective sites; 237 unique analytes) in the human serum and plasma reference specimens distributed by the Plasma Proteome Project (PPP) of the HUPO. The methods provided a means to (1) assess the level of systematic variation in protein abundances associated with blood preparation methods (serum, citrate-anticoagulated-plasma, EDTA-anticoagulated-plasma, or heparin-anticoagulated-plasma) and (2) evaluate the dependence on concentration of MS-based protein identifications from data sets using the HUPO specimens. Some proteins, particularly cytokines, had highly variable concentrations between the different sample preparations, suggesting specific effects of certain anticoagulants on the stability or availability of these proteins. The linkage of antibody-based measurements from 66 different analytes with the combined MS/MS data from 18 different laboratories showed that protein detection and the quality of MS data increased with analyte concentration. The conclusions from these initial analyses are that the optimal blood preparation method is variable between analytes and that the discovery of blood proteins by MS can be extended to concentrations below the ng/mL range under certain circumstances. Continued developments in antibody-based methods will further advance the scientific goals of the PPP.     

Dissecting the human plasma proteome and inflammatory response biomarkers

A central focus of clinical proteomics is to search for biomarkers in plasma for diagnostic and therapeutic use. We studied a set of plasma proteins accessed from the Healthy Human Individual's Integrated Plasma Proteome (HIP²) database, a larger set of curated human proteins, and a subset of inflammatory proteins, for overlap with sets of known protein biomarkers, drug targets, and secreted proteins. Most inflammatory proteins were found to occur in plasma, and over three times the level of biomarkers were found in inflammatory plasma proteins and their interacting protein neighbors compared to the sets of plasma and curated human proteins. Percentage overlaps with Gene Ontology terms were similar between the curated human set and plasma protein set, yet the set of inflammatory plasma proteins had a distinct ontology‐based profile. Most of the major hub proteins within protein‐protein interaction networks of tissue‐specific sets of inflammatory proteins were found to occur in disease pathways. The present study presents a systematic approach for profiling a plasma subproteome's relationship to both its potential range of clinical application and its overlap with complex disease.     

SRWD: a novel WD40 protein subfamily regulated by salt stress in rice (OryzasativaL.)

By analysis with microarray data, we found that a gene encoding a novel protein containing five WD40 repeats, was regulated by salt stress in rice and named as SRWD1 (Salt responsive WD40 protein 1). By database searching, additional four SRWD1-like genes (SRWD2-SRWD5) were found in rice genome, and these five SRWD genes formed a novel WD40 subfamily. Phylogenetic analysis showed that plant SRWD proteins divided into four groups. The significant functional divergences during SRWD evolution were found. The tissue-specific and salt responsive expression profiling for SRWD genes was investigated based on microarray data. It was found that all five SRWD genes in rice were regulated by salt stress. Further, we found that SRWD1 was regulated with different patterns by salt stress in two rice cultivars responding differently to salt stress. Our study correlates WD40 proteins with salt stress in plants and provides fundamental information for the further investigation of plant SRWD proteins.     

A well‐characterised peak identification list of MALDI MS profile peaks for human blood serum

MALDI MS profiling, using easily available body fluids such as blood serum, has attracted considerable interest for its potential in clinical applications. Despite the numerous reports on MALDI MS profiling of human serum, there is only scarce information on the identity of the species making up these profiles, particularly in the mass range of larger peptides. Here, we provide a list of more than 90 entries of MALDI MS profile peak identities up to 10 kDa obtained from human blood serum. Various modifications such as phosphorylation were detected among the peptide identifications. The overlap with the few other MALDI MS peak lists published so far was found to be limited and hence our list significantly extends the number of identified peaks commonly found in MALDI MS profiling of human blood serum.     

Evaluation of a protocol for metabolic profiling studies on human blood plasma by combined ultra-performance liquid chromatography/mass spectrometry: From extraction to data analysis

The investigation presented here describes a protocol designed to perform high-throughput metabolic profiling analysis on human blood plasma by ultra-performance liquid chromatography/mass spectrometry (UPLC/MS). To address whether a previous extraction protocol for gas chromatography (GC)/MS-based metabolic profiling of plasma could be used for UPLC/MS-based analysis, the original protocol was compared with similar methods for extraction of low-molecular-weight compounds from plasma via protein precipitation. Differences between extraction methods could be observed, but the previously published extraction method was considered the best. UPLC columns with three different stationary phases (C8, C18, and phenyl) were used in identical experimental runs consisting of a total of 60 injections of extracted male and female plasma samples. The C8 column was determined to be the best for metabolic profiling analysis on plasma. The acquired UPLC/MS data of extracted male and female plasma samples was subjected to principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA). Furthermore, a strategy for compound identification was applied here, demonstrating the strength of high-mass-accuracy time-of-flight (TOF)/MS analysis in metabolic profiling.     

Time series proteome profiling to study endoplasmic reticulum stress response

Time series profiling is a powerful approach for obtaining information on protein expression dynamics and prevailing biochemical pathways. To date, such information could only be obtained at the mRNA level using mature and highly parallel technologies such as microarray gene expression profiling. The generation of time series data at the protein level has lagged due to the lack of robust and highly reproducible methodologies. Using a combination of SILAC strategy, SDS-PAGE and LC-MS/MS, we demonstrate successful monitoring of expression levels of the same set of proteins across different time points within the ER compartment of human primary fibroblast cells when exposed to ER stress inducers tunicamycin and thapsigargin. Data visualization was facilitated using GeneSpring GX analysis platform that was designed to process Affymetrix microarray data. This software also facilitated the generation of important parameters such as data normalization, calculation of statistical values to extract significant changes in protein expression, and the cross comparison of data sets.     

Antibody microarray profiling of human prostate cancer sera: antibody screening and identification of potential biomarkers

We developed a practical strategy for serum protein profiling using antibody microarrays and applied the method to the identification of potential biomarkers in prostate cancer serum. Protein abundances from 33 prostate cancer and 20 control serum samples were compared to abundances from a common reference pool using a two-color fluorescence assay. Robotically spotted microarrays containing 184 unique antibodies were prepared on two different substrates: polyacrylamide based hydrogels on glass and poly-1-lysine coated glass with a photoreactive cross-linking layer. The hydrogel substrate yielded an average six-fold higher signal-to-noise ratio than the other substrate, and detection of protein binding was possible from a greater number of antibodies using the hydrogels. A statistical filter based on the correlation of data from "reverse-labeled" experiment sets accurately predicted the agreement between the microarray measurements and enzyme-linked immunosorbent assay measurements, showing that this parameter can serve to screen for antibodies that are functional on microarrays. Having defined a set of reliable microarray measurements, we identified five proteins (von Willebrand Factor, immunoglobulinM, Alpha1-antichymotrypsin, Villin and immunoglobulinG) that had significantly different levels between the prostate cancer samples and the controls. These developments enable the immediate use of high-density antibody and protein microarrays in biomarker discovery studies.     

Quantitative serum proteomics from surface plasmon resonance imaging

The detection and quantification of specific proteins in complex mixtures is a major challenge for proteomics. For example, the development of disease-related biomarker panels will require fast and efficient methods for obtaining multiparameter protein profiles. We established a high throughput, label-free method for analyzing serum using surface plasmon resonance imaging of antibody microarrays. Microarrays were fabricated using standard pin spotting on bare gold substrates, and samples were applied for binding analysis using a camera-based surface plasmon resonance system. We validated the system by measuring the concentrations of four serum proteins using part of a 792-feature microarray. Transferrin concentrations were measured to be 2.1 mg/ml in human serum and 1.2 mg/ml in murine serum, which closely matched ELISA determinations of 2.6 and 1.2 mg/ml, respectively. In agreement with expected values, human and mouse albumin levels were measured to be 24.3 and 23.6 mg/ml, respectively. The lower limits of detection for the four measurements ranged from 14 to 58 ng/ml or 175 to 755 pm. Where purified target proteins are not available for calibration, the microarrays can be used for relative protein quantification. We used the antibody microarray to compare the serum protein profiles from three liver cancer patients and three non-liver cancer patients. Hierarchical clustering of the serum protein levels clearly distinguished two distinct profiles. Thirty-nine significant protein changes were detected (p < 0.05), 10 of which have been observed previously in serum. alpha-Fetoprotein, a known liver cancer marker, was observed to increase. These results demonstrate the feasibility of this high throughput approach for both absolute and relative protein expression profiling.     

Depletion of multiple high-abundance proteins improves protein profiling capacities of human serum and plasma

Systematic detection of low-abundance proteins in human blood that may be putative disease biomarkers is complicated by an extremely wide range of protein abundances. Hence, depletion of major proteins is one potential strategy for enhancing detection sensitivity in serum or plasma. This study compared a recently commercialized HPLC column containing antibodies to six of the most abundant blood proteins ("Top-6 depletion") with either older Cibacron blue/Protein A or G depletion methods or no depletion. In addition, a prototype spin column version of the HPLC column and an alternative prototype two antibody spin column were evaluated. The HPLC polyclonal antibody column and its spin column version are very promising methods for substantially simplifying human serum or plasma samples. These columns show the lowest nonspecific binding of the depletion methods tested. In contrast other affinity methods, particularly dye-based resins, yielded many proteins in the bound fractions in addition to the targeted proteins. Depletion of six abundant proteins removed about 85% of the total protein from human serum or plasma, and this enabled 10- to 20-fold higher amounts of depleted serum or plasma samples to be applied to 2-D gels or alternative protein profiling methods such as protein array pixelation. However, the number of new spots detected on 2-D gels was modest, and most newly visualized spots were minor forms of relatively abundant proteins. The inability to detect low-abundance proteins near expected 2-D staining limits was probably due to both the highly heterogeneous nature of most plasma or serum proteins and masking of many low-abundance proteins by the next series of most abundant proteins. Hence, non2-D methods such as protein array pixelation are more promising strategies for detecting lower abundance proteins after depleting the six abundant proteins.     

Eph/ephrin profiling in human breast cancer reveals significant associations between expression level and clinical outcome

Pre-clinical studies provide compelling evidence that Eph family receptor tyrosine kinases (RTKs) and ligands promote cancer growth, neovascularization, invasion, and metastasis. Tumor suppressive roles have also been reported for the receptors, however, creating a potential barrier for clinical application. Determining how these observations relate to clinical outcome is a crucial step for translating the biological and mechanistic data into new molecularly targeted therapies. We investigated eph and ephrin expression in human breast cancer relative to endpoints of overall and/or recurrence-free survival in large microarray datasets. We also investigated protein expression in commercial human breast tissue microarrays (TMA) and Stage I prognostic TMAs linked to recurrence outcome data. We found significant correlations between ephA2, ephA4, ephA7, ephB4, and ephB6 and overall and/or recurrence-free survival in large microarray datasets. Protein expression in TMAs supported these trends. While observed no correlation between ephrin ligand expression and clinical outcome in microarray datasets, ephrin-A1 and EphA2 protein co-expression was significantly associated with recurrence in Stage I prognostic breast cancer TMAs. Our data suggest that several Eph family members are clinically relevant and tractable targets for intervention in human breast cancer. Moreover, profiling Eph receptor expression patterns in the context of relevant ligands and in the context of stage may be valuable in terms of diagnostics and treatment.     

Intact-protein-based high-resolution three-dimensional quantitative analysis system for proteome profiling of biological fluids

The substantial complexity and vast dynamic range of protein abundance in biological fluids, notably serum and plasma, present a formidable challenge for comprehensive protein analysis. Integration of multiple technologies is required to achieve high-resolution and high-sensitivity proteomics analysis of biological fluids. We have implemented an orthogonal three-dimensional intact-protein analysis system (IPAS), coupled with protein tagging and immunodepletion of abundant proteins, to quantitatively profile the human plasma proteome. Following immunodepletion, plasma proteins in each of paired samples are concentrated and labeled with a different Cy dye, before mixing. Proteins are subsequently separated in three dimensions according to their charge, hydrophobicity, and molecular mass. Differences in the abundance of resolved proteins are determined based on Cy dye ratios. We have applied this strategy to profile the plasma proteome for changes that occur with acute graft-versus-host disease (GVHD), following allogeneic bone marrow transplantation (BMT). Using capillary HPLC ESI Q-TOF MS, we identified 75 proteins in the micromolar to femtomolar range that exhibited quantitative differences between the pre- and post-GVHD samples. These proteins included serum amyloid A, apolipoproteins A-I/A-IV, and complement C3 that are well-known acute-phase reactants likely reflecting the post-BMT inflammatory state. In addition, we identified some potentially interesting immunologically relevant molecules including vitamin D-binding protein, fetuin, vitronectin, proline-rich protein 3 and 4, integrin-alpha, and leukocyte antigen CD97. IPAS provides a combination of comprehensive profiling and quantitative analysis, with a substantial dynamic range, for disease-related applications.