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.     

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.     

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.     

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.     

A cancer protein microarray platform using antibody fragments and its clinical applications

Antibody microarrays have shown great potential for measurement of either a spectrum of target proteins in proteomics or disease-associated antigens in molecular diagnostics. Despite its importance, the applications of antibody microarrays are still limited by a variety of fundamental problems. Among them, cross-reactivity significantly limits the multiplexing ability in parallel sandwich immunoassays. As a result, it is very important to design new capture probes in order to incorporate a universal label into the assay configuration. In this report, an antibody fragments (F(ab')2) microarray platform for serum tumor markers was developed. Each antigen was detected at different concentrations to assemble its calibration curve, and combinations of different markers were tested to examine the specificity of simultaneous detection based on the F(ab')2 microarrays. Diagnostics of serum samples with this cancer antibody microarray platform and immunoradiometric assays (IRMA) were also performed. Wide range calibration curves (0-1280 U mL(-1)) were obtained for each tumor marker. Comparative studies demonstrated that such F(ab')2 microarrays exhibited both moderately improved sensitivity and better specificity than full-sized monoclonal antibody microarrays. It is also demonstrated that this microarray platform is quantitative, highly specific and reasonably sensitive. More importantly, clinical applications of our F(ab')2 microarray platform for upwards of 100 patient serum samples clearly show its potential in cancer diagnostics.     

A novel antibody microarray format using non-covalent antibody immobilization with chemiluminescent detection

To date, protein and antibody microarrays have been used in reverse-phase and sandwich-based methods in order to detect known proteins such as biomarkers in samples. Our group developed "libraries" of antibodies against unknown proteins, referred to as mKIAA proteins, and we attempted to discover candidate novel biomarkers by protein expression profiling.To profile mKIAA protein expression using these antibodies, we established an antibody microarray system using chemiluminescent detection. A number of techniques for protein-antibody microarrays have been reported; however, no entirely suitable protocol for crude protein samples has been established. To address this issue, we immobilized purified antibodies on hydrophilic surface polymer slides (Maxisorp, Nunc). Although our system is based on the direct labeling of crude protein samples, we achieved sufficient sensitivity (detection limit: 50 pg mL(-1)) and low backgrounds. This sensitivity is on a level with the sandwich immunoassay-based antibody array system. Using our protocol, we developed an antibody microarray spotted with 960 anti-mKIAA antibodies (total: 3888 spots for quadruplicate assessments), and we carried out protein expression profiling of mKIAA proteins. In this study, we generated an expression profile of 960 mKIAA proteins and compared the present results with those obtained via cDNA microarray.     

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.     

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.     

Methods and applications of antibody microarrays in cancer research

Antibody microarrays have great potential for significant value in biological research. Cancer research in particular could benefit from the unique experimental capabilities of this technology. This article examines the current state of antibody microarray technological developments and assay formats, along with a review of the demonstrated applications to cancer research. Work is ongoing in the refinement of various aspects of the protocols and the development of robust methods for routine use. Antibody microarray experimental formats can be broadly categorized into two classes: (1) direct labeling experiments, and (2) dual antibody sandwich assays. In the direct labeling method, the covalent labeling of all proteins in a complex mixture provides a means for detecting bound proteins after incubation on an antibody microarray. If proteins are labeled with a tag, such as biotin, the signal from bound proteins can be amplified. In the sandwich assay, proteins captured on an antibody microarray are detected by a cocktail of detection antibodies, each antibody matched to one of the spotted antibodies. Each format has distinct advantages and disadvantages. Several applications of antibody arrays to cancer research have been reported, including the analysis of proteins in blood serum, resected frozen tumors, cell lines, and on membranes of blood cells. These demonstrations clearly show the utility of antibody microarrays for cancer research and signal the imminent expansion of this platform to many areas of biological research.     

Microarrays of tumor cell derived proteins uncover a distinct pattern of prostate cancer serum immunoreactivity

The broad characterization of the immune responses elicited by tumors has valuable applications in diagnostics and basic research. We present here the use of microarrays of tumor-derived proteins to profile the antibody repertoire in the sera of prostate cancer patients and controls. Two-dimensional liquid chromatography was used to separate proteins from the prostate cancer cell line LNCaP into 1760 fractions. These fractions were spotted in microarrays on coated microscope slides, and the microarrays were incubated individually with serum samples from 25 men with prostate cancer and 25 male controls. The amount of immunoglobulin bound to each fraction by each serum sample was quantified. Statistical analysis revealed that 38 of the fractions had significantly higher levels of immunoglobulin binding in the prostate cancer samples compared to the controls. Two fractions showed higher binding in the control samples. The significantly higher immunoglobulin reactivity from the prostate cancer samples may reflect a strong immune response to the tumors in the prostate cancer patients. We used multivariate analysis to classify the samples as either prostate cancer or control. In a cross-validation study, recursive partitioning classified the samples with 84% accuracy. A decision tree with two levels of partitioning classified the samples with 98% accuracy. Additional studies will allow further characterization of tumor antigens in prostate cancer and their significance for diagnosis. These results suggest that microarrays of fractionated proteins could be a powerful tool for tumor antigen discovery and cancer diagnosis.     

Antibody suspension bead arrays within serum proteomics

Antibody microarrays offer a powerful tool to screen for target proteins in complex samples. Here, we describe an approach for systematic analysis of serum, based on antibodies and using color-coded beads for the creation of antibody arrays in suspension. This method, adapted from planar antibody arrays, offers a fast, flexible, and multiplexed procedure to screen larger numbers of serum samples, and no purification steps are required to remove excess labeling substance. The assay system detected proteins down to lower picomolar levels with dynamic ranges over 3 orders of magnitude. The feasibility of this workflow was shown in a study with more than 200 clinical serum samples tested for 20 serum proteins.     

Integral protein microarrays for the identification of lung cancer antigens in sera that induce a humoral immune response

The identification of biomarkers (both molecules and profiles) in patient sera offers enormous interest for the diagnosis of cancers. In this context, the detection of antibodies to tumor cell autologous antigens possesses great potential. The humoral immune response represents a form of biological amplification of signals that are otherwise weak because of very low concentrations of antigen, especially in the early stages of cancers. Herein we present the use of integral microarrays spotted with tumor-derived proteins to investigate the antibody repertoire in the sera of lung cancer patients and controls. The use of two-dimensional liquid chromatography allowed us to separate proteins from the lung adenocarcinoma cell line A549 into 1760 fractions, which were printed in duplicate, along with various controls, onto nitrocellulose coated slides. The sensitivity and specificity of the microarrays to detect singular antibodies in fluids were first validated through the recognition of fractions containing a lung marker antigen by antibody probing. Twenty fractions were initially selected as highly reactive against the anti-PGP9.5 antibody, and subsequent mass spectrometry analyses confirmed the identity of PGP9.5 protein in four of them. As a result, the importance of neighboring fractions in microarray detection was revealed due to the spreading of proteins during the separation process. Next, the microarrays were individually incubated with 14 serum samples from patients with lung cancer patients, 14 sera from colon cancer patients, and 14 control sera from normal subjects. The reactivity of the selected fractions was analyzed, and the level of immunoglobulin bound to each fraction by each serum sample was quantified. Eight of the 20 fractions offered p values < 0.01 and were recognized by an average of four reacting patients, whereas no serum from normal individuals was positive for those fractions. Protein microarrays from tumor-derived fractions hold the diagnostic potential of uncovering antigens that induce an immune response in patients with certain types of cancers.     

A high-performance, small-scale microarray for expression profiling of many samples in Arabidopsis-pathogen studies

Studies of the behavior of biological systems often require monitoring of the expression of many genes in a large number of samples. While whole-genome arrays provide high-quality gene-expression profiles, their high cost generally limits the number of samples that can be studied. Although inexpensive small-scale arrays representing genes of interest could be used for many applications, it is challenging to obtain accurate measurements with conventional small-scale microarrays. We have developed a small-scale microarray system that yields highly accurate and reproducible expression measurements. This was achieved by implementing a stable gene-based quantile normalization method for array-to-array normalization, and a probe-printing design that allows use of a statistical model to correct for effects of print tips and uneven hybridization. The array measures expression values in a single sample, rather than ratios between two samples. This allows accurate comparisons among many samples. The array typically yielded correlation coefficients higher than 0.99 between technically duplicated samples. Accuracy was demonstrated by a correlation coefficient of 0.88 between expression ratios determined from this array and an Affymetrix GeneChip, by quantitative RT-PCR, and by spiking known amounts of specific RNAs into the RNA samples used for profiling. The array was used to compare the responses of wild-type, rps2 and ndr1 mutant plants to infection by a Pseudomonas syringae strain expressing avrRpt2. The results suggest that ndr1 affects a defense-signaling pathway(s) in addition to the RPS2-dependent pathway, and indicate that the microarray is a powerful tool for systems analyses of the Arabidopsis disease-signaling network.     

A pre-processing pipeline to quantify,visualize, and reduce technical variation in protein microarray studies

Technical variation, or variation from non-biological sources, is present in most laboratory assays. Correcting for this variation enables analysts to extract a biological signal that informs questions of interest. However, each assay has different sources and levels of technical variation, and the choice of correction methods can impact downstream analyses. Compared to similar assays such as DNA microarrays, relatively few methods have been developed and evaluated for protein microarrays, a versatile tool for measuring levels of various proteins in serum samples. Here, we propose a pre-processing pipeline to correct for some common sources of technical variation in protein microarrays. The pipeline builds upon an existing normalization method by using controls to reduce technical variation. We evaluate our method using data from two protein microarray studies and by simulation. We demonstrate that pre-processing choices impact the fluorescent-intensity based ranks of proteins, which in turn, impact downstream analysis.     

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.     

In vitro gene expression dissected: chemostat surgery for mycobacterium tuberculosis

A unique approach, combining defined and reproducible in vitro models with DNA microarrays, has been developed to study environmental modulation of mycobacterial gene expression. The gene expression profiles of samples of Mycobacterium tuberculosis, from independent chemostat cultures grown under defined and reproducible conditions, were found to be highly correlated. This approach is now being used to study the effect of relevant stimuli, such as limited oxygen availability, on mycobacterial gene expression. A modification of the chemostat culture system, enabling largevolume controlled batch culture, has been developed to study starvation survival. Cultures of M. tuberculosis have been maintained under nutrient-starved conditions for extended periods, with 10(6) - 10(7) bacilli surviving in a culturable state after 100 days. The design of the culture system has made it possible to control the environment and collect multiple time-course samples to study patterns of gene expression. These studies demonstrate that it is possible to perform long-term studies and obtain reproducible expression data using controlled and defined in vitro models.     

High-throughput protein arrays: prospects for molecular diagnostics

High-throughput protein arrays allow the miniaturized and parallel analysis of large numbers of diagnostic markers in complex samples. Using automated colony picking and gridding, cDNA or antibody libraries can be expressed and screened as clone arrays. Protein microarrays are constructed from recombinantly expressed, purified, and yet functional proteins, entailing a range of optimized expression systems. Antibody microarrays are becoming a robust format for expression profiling of whole genomes. Alternative systems, such as aptamer, PROfusion, nano- and microfluidic arrays are all at proof-of-concept stage. Differential protein profiles have been used as molecular diagnostics for cancer and autoimmune diseases and might ultimately be applied to screening of high-risk and general populations.