A novel approach to protein expression profiling using antibody microarrays combined with surface plasmon resonance technology

We have previously described our systems for the high-throughput production of antibodies against mouse KIAA proteins and their validation (Proteomics 2004, 4, 1412-1416). Using our "libraries" of antibodies, we established a novel antibody microarray system in which surface plasmon resonance (SPR) technology is utilized for signal detection. Up to 400 real-time antibody-target bindings could be measured simultaneously within a single hour. This rapid detection was achieved by direct readout of the bindings using SPR technology. To evaluate our system, we assessed the reproducibility on crude protein samples and obtained satisfactorily reproducible results, exhibiting correlation values >0.92. Using this SPR-based antibody microarray system, we examined mKIAA protein expression in five different adult mouse tissues and identified the specific tissue expression patterns of several mKIAA proteins.     

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.     

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.     

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.     

Protein profiling in human sera for identification of potential lung cancer biomarkers using antibody microarray

To identify potential biomarkers of lung cancer (LC), profiling of proteins in sera obtained from healthy and LC patients was determined using an antibody microarray. Based on our previous study on mRNA expression profiles between patients with LC and healthy persons, 19 proteins of interest were selected as targets for fabrication of an antibody microarray. Antibody to each protein and five nonspecific control antibodies were spotted onto a hydrogel‐coated glass slide and used for profiling of proteins in sera of LC patients in a two‐color fluorescence assay. Forty‐eight human sera samples were analyzed, and expression profiling of proteins were represented by the internally normalized ratio method. Six proteins were distinctly down‐regulated in sera of LC patients; this observation was validated by Wilcoxon test, false discovery rate, and Western blotting. Blind test of other 32 human sera using the antibody microarray followed by hierarchical clustering analysis revealed an approximate sensitivity of 88%, specificity of 80%, and an accuracy of 84%, respectively, in classifying the sera, which supports the potential of the six identified proteins as biomarkers for the prognosis of lung cancer.     

Protein microarrays for gene expression and antibody screening.

Proteins translate genomic sequence information into function, enabling biological processes. As a complementary approach to gene expression profiling on cDNA microarrays, we have developed a technique for high-throughput gene expression and antibody screening on chip-size protein microarrays. Using a picking/spotting robot equipped with a new transfer stamp, protein solutions were gridded onto polyvinylidene difluoride filters at high density. Specific purified protein was detected on the filters with high sensitivity (250 amol or 10 pg of a test protein). On a microarray made from bacterial lysates of 92 human cDNA clones expressed in a microtiter plate, putative protein expressors could be reliably identified. The rate of false-positive clones, expressing proteins in incorrect reading frames, was low. Product specificity of selected clones was confirmed on identical microarrays using monoclonal antibodies. Cross-reactivities of some antibodies with unrelated proteins imply the use of protein microarrays for antibody specificity screening against whole libraries of proteins. Because this application would not be restricted to antigen-antibody systems, protein microarrays should provide a general resource for high-throughput screens of gene expression and receptor-ligand interactions.     

Protein expression profiling of breast cancer cells by dissociable antibody microarray (DAMA) staining

Dissociable antibody microarray (DAMA) staining is a technology that combines protein microarrays with traditional immunostaining techniques. It can simultaneously determine the expression and subcellular location of hundreds of proteins in cultured cells and tissue samples. We developed this technology and demonstrated its application in identifying potential biomarkers for breast cancer. We compared the expression profiles of 312 proteins among three normal breast cell lines and seven breast cancer cell lines and identified 10 differentially expressed proteins by the data analysis program DAMAPEP (DAMA protein expression profiling). Among those proteins, RAIDD, Rb p107, Rb p130, SRF, and Tyk2 were confirmed by Western blot and statistical analysis to have higher expression levels in breast cancer cells than in normal breast cells. These proteins could be potential biomarkers for the diagnosis of breast cancer.     

Evaluation of surface chemistries for antibody microarrays

Antibody microarrays are an emerging technology that promises to be a powerful tool for the detection of disease biomarkers. The current technology for protein microarrays has been derived primarily from DNA microarrays and is not fully characterized for use with proteins. For example, there are a myriad of surface chemistries that are commercially available for antibody microarrays, but there are no rigorous studies that compare these different surfaces. Therefore, we have used a sandwich enzyme-linked immunosorbent assay (ELISA) microarray platform to analyze 17 different commercially available slide types. Full standard curves were generated for 23 different assays. We found that this approach provides a rigorous and quantitative system for comparing the different slide types based on spot size and morphology, slide noise, spot background, lower limit of detection, and reproducibility. These studies demonstrate that the properties of the slide surface affect the activity of immobilized antibodies and the quality of data produced. Although many slide types produce useful data, glass slides coated with aldehyde silane, poly-l-lysine, or aminosilane (with or without activation with a crosslinker) consistently produce superior results in the sandwich ELISA microarray analyses we performed.     

Development of an internally controlled antibody microarray

Antibody microarrays are a high throughput technology used to concurrently screen for protein expression. Most antibody arrays currently used are based on the ELISA sandwich approach that uses two antibodies to screen for the expression of a limited number of proteins. Also because antigen-antibody interactions are concentration-dependent, antibody microarrays need to normalize the amount of antibody that is used. In response to the limitations with the currently existing technology we have developed a single antibody-based microarray where the quantity of antibody spotted is used to standardize the antigen concentration. In addition, this new array utilizes an internally controlled system where one color represents the amount of antibody spotted, and the other color represents the amount of the antigen that is used to quantify the level of protein expression. When compared with median fluorescence intensity alone, normalization for antibody spot intensity decreased variability and lowered the limits of detection. This new antibody array was tested using standard cytokine proteins and also cell lysates obtained from mouse macrophages stimulated in vitro and evaluated for the expression of the cytokine proteins interleukin (IL)-1beta, IL-5, IL-6, and macrophage inflammatory proteins 1alpha and 1beta. The levels of protein expression seen with the antibody microarray was compared with that obtained with Western blot analysis, and the magnitude of protein expression observed was similar with both technologies with the antibody array actually showing a greater degree of sensitivity. In summary, we have developed a new type of antibody microarray to screen for protein expression that utilizes a single antibody and controls for the amount of antibody spotted. This type of array appears at least as sensitive as Western blot analysis, and the technology can be scaled up for high throughput screening for hundreds of proteins in complex biofluids such as blood.     

Design of recombinant antibody microarrays for serum protein profiling: targeting of complement proteins

Antibody-based microarrays is a novel technology with great promise for high-throughput proteomics. The process of designing high-performing arrays has, however, turned out to be challenging. Here, we have designed the next generation of a human recombinant scFv antibody microarray platform for protein expression profiling of nonfractionated biotinylated human plasma and serum proteomes. The setup, based on black polymer Maxisorb slides interfaced with a fluorescent-based read-out system, was found to provide specific, sensitive (subpicomolar (pM) range) and reproducible means for protein profiling. Further, a chip-to-chip normalization protocol critical for comparing data generated on different chips was devised. Finally, the microarray data were found to correlate well with clinical laboratory data obtained using conventional methods, as demonstrated for a set of medium abundant (micromolar (microM) to nanomolar (nM) range) protein analytes in serum and plasma samples derived from healthy and complement-deficient individuals.     

Quorum sensing affects virulence-associated proteins F1, LcrV, KatY and pH6 etc. of Yersinia pestis as revealed by protein microarray-based antibody profiling

Protein microarray that consists of virulence-associated proteins of Yersinia pestis is used to compare antibody profiles elicited by the wild-type and quorum sensing (QS) mutant strain of this bacterium to define the immunogens that are impacted by QS. The results will lead the way for future functional proteomics studies. The antibody profile that was induced by the QS mutant differed from that of the parent strain. Detailed comparison of the antibody profiles, according to the proteins' functional annotations, showed that QS affects the expression of many virulence-associated proteins of Y. pestis. The antibodies to many virulence-associated proteins were not detected or lower titers of antibodies to many proteins were detected in the sera of rabbits immunized with the QS mutant, relative to those of the wild type, which indicated that these proteins were not expressed or expressed at relatively lower levels in the QS mutant. The results demonstrated that antibody profiling by protein microarrays is a promising high-throughput method for revealing the interactions between pathogens and the host immune system.     

Microarray profiling of skeletal muscle sarcoplasmic reticulum proteins

Microarrays were developed to profile the level of proteins associated with calcium regulation in sarcoplasmic reticulum (SR) isolated from porcine Longissimus muscle. The microarrays consisted of SR preparations printed onto to glass slides and probed with monoclonal antibodies to 7 target proteins. Proteins investigated included: ryanodine receptor, (RyR), dihydropyridine receptor, (DHPR), triadin (TRI), calsequestrin (CSQ), 90 kDa junctional protein (JSR90), and fast-twitch and slow-twitch SR calcium ATPases (SERCA1 and SERCA2). Signal from a fluorescently-labeled detection antibody was measured and quantitated using a slide reader. The microarray developed was also employed to profile Longissimus muscle SR proteins from halothane genotyped animals. Significant (P<0.05) reductions in levels of several proteins were found including: RyR, CSQ, TRI, DHPR and SERCA2 in SR samples from halothane positive animals. The results illustrate the potential of microarrays as a tool for profiling SR proteins and aiding investigations of calcium regulation.     

Multiplexed analysis of glycan variation on native proteins captured by antibody microarrays

Carbohydrate post-translational modifications on proteins are important determinants of protein function in both normal and disease biology. We have developed a method to allow the efficient, multiplexed study of glycans on individual proteins from complex mixtures, using antibody microarray capture of multiple proteins followed by detection with lectins or glycan-binding antibodies. Chemical derivatization of the glycans on the spotted antibodies prevented lectin binding to those glycans. Multiple lectins could be used as detection probes, each targeting different glycan groups, to build up lectin binding profiles of captured proteins. By profiling both protein and glycan variation in multiple samples using parallel sandwich and glycan-detection assays, we found cancer-associated glycan alteration on the proteins MUC1 and CEA in the serum of pancreatic cancer patients. Antibody arrays for glycan detection are highly effective for profiling variation in specific glycans on multiple proteins and should be useful in diverse areas of glycobiology research.     

Profiling of differential protein expression in angiogenin-induced HUVECs using antibody-arrayed ProteoChip

ProteoChip has been developed as a novel protein microarray technology. So far it has been applied in new lead screening and molecular diagnostics and we expect its role to grow in the field of biology. Here, we investigated the application of ProteoChip for the study of differential protein expression profiles in angiogenin-induced human umbilical vein endothelial cells (HUVECs). Antibody microarrays constructed by immobilizing 60 distinct antibodies against signal-transducing proteins on ProteoChip base plates were used to analyze the expression pattern of cell-signaling proteins in HUVECs treated with angiogenin. The antibody microarray approach showed that angiogenin induced the up- and down-regulation of several cellular regulators related with cell proliferation. Changes in the expression of signaling proteins determined by antibody microarray were validated by Western blot analysis. In this experiment, ten up-regulated proteins and six down-regulated proteins were identified and confirmed by immunoblot analysis. Taken together, these data suggest that antibody microarrays using ProteoChip technology can be a powerful tool for high-throughput analysis of proteomes in biological samples.     

Sensitive single-molecule protein quantification and protein complex detection in a microarray format

Single-molecule protein analysis provides sensitive protein quantitation with a digital read-out and is promising for studying biological systems and detecting biomarkers clinically. However, current single-molecule platforms rely on the quantification of one protein at a time. Conventional antibody microarrays are scalable to detect many proteins simultaneously, but they rely on less sensitive and less quantitative quantification by the ensemble averaging of fluorescent molecules. Here, we demonstrate a single-molecule protein assay in a microarray format enabled by an ultra-low background surface and single-molecule imaging. The digital read-out provides a highly sensitive, low femtomolar limit of detection and four orders of magnitude of dynamic range through the use of hybrid digital-analog quantification. From crude cell lysate, we measured levels of p53 and MDM2 in parallel, proving the concept of a digital antibody microarray for use in proteomic profiling. We also applied the single-molecule microarray to detect the p53-MDM2 protein complex in cell lysate. Our study is promising for development and application of single-molecule protein methods because it represents a technological bridge between single-plex and highly multiplex studies.     

Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries

A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC.     

An Integrated Peptide-Antigen Microarray on Plasmonic Gold Films for Sensitive Human Antibody Profiling

High-throughput screening for interactions of peptides with a variety of antibody targets could greatly facilitate proteomic analysis for epitope mapping, enzyme profiling, drug discovery and biomarker identification. Peptide microarrays are suited for such undertaking because of their high-throughput capability. However, existing peptide microarrays lack the sensitivity needed for detecting low abundance proteins or low affinity peptide-protein interactions. This work presents a new peptide microarray platform constructed on nanostructured plasmonic gold substrates capable of metal enhanced NIR fluorescence enhancement (NIR-FE) by hundreds of folds for screening peptide-antibody interactions with ultrahigh sensitivity. Further, an integrated histone peptide and whole antigen array is developed on the same plasmonic gold chip for profiling human antibodies in the sera of systemic lupus erythematosus (SLE) patients, revealing that collectively a panel of biomarkers against unmodified and post-translationally modified histone peptides and several whole antigens allow more accurate differentiation of SLE patients from healthy individuals than profiling biomarkers against peptides or whole antigens alone.     

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.     

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.