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Optimized Autoantibody Profiling on Protein Arrays
Abstract
Profiling the autoantibody (AAb) repertoire in serum has been routinely used for many years for the diagnosis of autoimmune diseases, including rheumatoid arthritis, scleroderma, and lupus. In recent years, AAb profiling of cancers has become a prominent field in oncology research. Protein arrays enable high-throughput screening of clinical samples, characterising the serum profile using low volumes of samples. This chapter describes the use of a protein array comprising 37,200 redundant proteins (containing over 10,000 non-redundant human recombinant proteins) for identification of the proteins bound by the antibodies in human sera using a test set of serum samples. The proteins identified have the potential to be candidate biomarkers. These recombinant proteins are expressed, purified, and robotically spotted on microarrays or chips to facilitate the screening of additional serum samples with the aim of identifying a candidate biomarker or panel of potential biomarkers for applications in disease diagnosis, stage, progression, or response to therapy.
... Generally, protein microarrays have been grouped into functional protein microarrays and analytic (protein-detecting) protein microarrays [121,122]. They can be fabricated using reverse capture of native proteins [121][122][123][124], recombinant proteins [120,125], cDNA expression libraries [126][127][128], and in-situ expression techniques [129][130][131][132]. Detailed information about how protein arrays work can be found elsewhere [120,133,134]. Despite the immense potential of this proteomics method in elucidating the pathogenesis of several autoimmune hair and skin conditions in humans [135], there is a paucity of studies that have employed it in human hair proteomics. ...
The use of non-invasive human substrates to interrogate pathophysiological conditions has become essential in the post- Human Genome Project (HGP) era. Due to its high turnover rate, and its long term capability to incorporate exogenous and endogenous substances from the circulation; hair testing is emerging a key player in monitoring long term drug compliance, chronic alcohol abuse, forensic toxicology, and biomarker discovery, among other things. Novel high throughput ‘omics based approaches like proteomics have been underutilized globally in comprehending human hair morphology and its evolving use as a diagnostic testing substrate in the era of precision medicine. There is paucity of scientific evidence that evaluates the difference in drug incorporation into hair based on lipid content; and very few studies have addressed hair growth rates, hair forms and the biological consequences hair grooming or bleaching. It is apparent that protein-based identification using the human hair proteome would play a major role in understanding these parameters akin to deoxyribonucleic acid (DNA) single nucleotide polymorphism (SNP) profiling, up to single amino acid polymorphism (SAP) resolution. Hence, this work seeks to identify and discuss the progress made thus far in the field of molecular hair testing using proteomic approaches, and identify ways in which proteomics would improve the field of hair research, considering that the human hair is mostly composed of proteins. Gaps in hair proteomics research were identified; and the potential of hair proteomics in establishing a historic medical repository of normal and disease-specific proteome was also discussed. This article is protected by copyright. All rights reserved
Objective:
Protein microarrays provide a high-throughput platform to measure protein interactions and associated functions, and can aid in the discovery of cancer biomarkers. The resulting protein microarray data can however be subject to systematic bias and noise, thus requiring a robust data processing, normalization and analysis pipeline to ensure high quality and robust results. To date, a comprehensive data processing pipeline is yet to be developed. Furthermore, a lack of analysis consistency is evident amongst different research groups, thereby impeding collaborative data consolidation and comparison. Thus, we sought to develop an accessible data processing tool using methods that are generalizable to the protein microarray field and which can be adapted to individual array layouts with minimal software engineering expertise.
Results:
We developed an improved version of a previously developed pipeline of protein microarray data processing and implemented it as an open source software tool, with particular focus on widening its use and applicability. The Protein Microarray Analyser software presented here includes the following tools: (1) neighbourhood background correction, (2) net intensity correction, (3) user-defined noise threshold, (4) user-defined CV threshold amongst replicates and (5) assay controls, (6) composite 'pin-to-pin' normalization amongst sub-arrays, and (7) 'array-to-array' normalization amongst whole arrays.
Objective:
Anti-ribosomal-phosphoprotein antibodies (anti-Ribos.P Abs) are detected in 10-45% of NPSLE patients. Intracerebroventricular administration of anti-ribosomal-P Abs induces depression-like behaviour in mice. We aimed to discern the mechanism by which anti-Ribos.P Abs induce behavioural changes in mice.
Methods:
Anti-Ribos.P Abs were exposed to human and rat neuronal cell cultures, as well as to human umbilical vein endothelial cell cultures for a control. The cellular localization of anti-Ribo.P Abs was found by an immunofluorescent technique using a confocal microscope. Identification of the target molecules was undertaken using a cDNA library. Immunohistochemistry and an inhibition assay were carried out to confirm the identity of the target molecules. Neuronal cell proliferation was measured by bromodeoxyuridine, and Akt and Erk expression by immunoblot.
Results:
Human anti-Ribos.P Abs penetrated into human neuronal cells and rat hippocampal cell cultures in vitro, but not to endothelial cells as examined. Screening a high-content human cDNA-library with anti-Ribos.P Abs identified neuronal growth-associated protein (GAP43) as a target for anti-Ribos.P Abs. Ex vivo anti-Ribos.P Abs bind to mouse brain sections of hippocampus, dentate and amygdala. Anti-Ribos.P Abs brain-binding was prevented by GAP43 protein. Interestingly, GAP43 inhibited in a dose-dependent manner the anti-Ribos.P Abs binding to recombinant-ribosomal-P0, indicating mimicry between the ribosomal-P0 protein and GAP43. Furthermore, anti-Ribos.P Abs reduced neuronal cell proliferation activity in vitro (P < 0.001), whereas GAP43 decreased this inhibitory activity by a factor of 7.6. The last was related to Akt and Erk dephosphorylation.
Conclusion:
Anti-Ribos.P Abs penetrate neuronal cells in vitro by targeting GAP43. Anti -Ribos.P Abs inhibit neuronal-cell proliferation via inhibition of Akt and Erk. Our data contribute to deciphering the mechanism for anti-Ribos.P Abs' pathogenic activity in NPSLE.
The cancer-testis antigens are a group of unrelated proteins aberrantly expressed in various cancers in adult somatic tissues. This aberrant expression can trigger spontaneous immune responses, a phenomenon exploited for the development of disease markers and therapeutic vaccines. However, expression levels often vary amongst patients presenting the same cancer type, and these antigens are therefore unlikely to be individually viable as diagnostic or prognostic markers. Nevertheless, patterns of antigen expression may provide correlates of specific cancer types and disease progression. Here we describe the development of a novel, readily customizable cancer-testis antigen microarray platform together with robust bioinformatics tools, with which to quantify anti-cancer testis antigen autoantibody profiles in patient sera. By exploiting the high affinity between autoantibodies and tumor antigens, we achieved linearity of response and an autoantibody quantitation limit in the pg/ml range - equating to a million-fold serum dilution. By utilizing oriented attachment of folded, recombinant antigens and a polyethylene glycol microarray surface coating, we attained minimal non-specific antibody binding. Unlike other proteomics methods, which typically use lower affinity interactions between monoclonal antibodies and tumor antigens for detection, the high sensitivity and specificity realized using our autoantibody-based approach may facilitate the development of better cancer biomarkers, as well as potentially enabling pre-symptomatic diagnosis. We illustrated the utility of our platform by monitoring the response of a melanoma patient cohort to an experimental therapeutic NY-ESO-1-based cancer vaccine; inter alia, we found evidence of determinant spreading in individual patients, as well as differential CT antigen expression and epitope utilization. © 2014 Wiley Periodicals, Inc.
Effective management of Rheumatoid Arthritis (RA) is being hampered by the difficulties for its early diagnosis and the heterogeneity of the disease. Although early intervention can result in disease remission, it requires early diagnosis, and current diagnostic tests are not sufficiently accurate or sensitive in the early stages of RA. Therefore, research efforts are increasingly focused on gaining knowledge about RA pathogenesis, and also on the discovery of novel biological markers that enable early diagnosis and stratification of the disease, and thus the implementation of targeted therapies. Ongoing research includes the emergence of novel approaches for the characterization of molecules that play a role in RA, such as genomic, proteomic and metabolomic technologies. These techniques, coupled with sophisticated statistical methods, permit the simultaneous analysis of multiple targets, and have become very powerful tools in RA research both for etiopathogenesis studies and biomarker discovery. It is believed that proteomics will soon provide a much-needed novel therapeutic approach to treating RA. This chapter will focus on the utility of Proteomics in RA research to enable a better understanding of the disease process, and to provide novel protein biomarkers useful for early diagnosis, prognosis and the application of tailored treatments.
Affinity proteomics is the field of proteome analysis based on the use of antibodies and other binding reagents as protein-specific detection probes. In this review, the particular strengths of affinity methods for determination of protein localization, functional characterization, biomarker discovery and intracellular applications, and their resulting impact in basic and clinical research are highlighted. An additional focus is on the requirements for systematic binder generation and current large-scale binder projects, including bioinformatic frameworks for epitope selection and for documentation of available binding reagents and their performance. In addition to current affinity proteomics methods and applications, including arrays of proteins, binders, lysates and tissues, approaches coupling mass spectrometry-based proteomics and affinity proteomics are reviewed.
The Overnight Express Autoinduction Systems enable regulated protein expression in Escherichia coli without the need to monitor the culture or add inducer during cell growth and are marketed exclusively through the Novagen brand of EMD Biosciences, Inc. (EMD Biosciences). EMD Biosciences is a major supplier of premium tools for proteomics and disease pathway analysis known through its global brands Calbiochem, Novabiochem and Novagen and is part of the Life Science and Analytics (LSA) division of Merck KGaA (Darmstadt, Germany). The company operates as EMD Biosciences, Inc. in North America and as Merck Biosciences outside North America.
We have developed a technique to establish catalogues of protein products of arrayed cDNA clones identified by DNA hybridisation
or sequencing. A human fetal brain cDNA library was directionally cloned in a bacterial vector that allows IPTG-inducible
expression of His6-tagged fusion proteins. Using robot technology, the library was arrayed in microtitre plates and gridded
onto high-density in situ filters. A monoclonal antibody recognising the N-terminal RGSH6 sequence of expressed proteins (RGS·His antibody, Qiagen) detected 20% of the library as putative expression clones. Two
example genes, GAPDH and HSP90α, were identified on high-density filters using DNA probes and antibodies against their proteins.
The choice of probes is an important feature of hybridisation experiments. In this paper we present an algorithm that optimises probes with respect to a training set of sequences based on Shannon entropy as a quality criterion. The practical motivation for our algorithm is oligonucleotide fingerprinting, a method for the simultaneous identification of sequences (cDNA or genomic DNA) by their hybridisation tags according to a set of short probes such as octamers, although the algorithm is of course not restricted to that application.
We can show that our method is superior to the selection of probes according to their frequencies, which is a widely used strategy, and to randomly chosen probe sets. The quality of probe sets is assessed by a simulation pipeline that entails the set of probes as a simulation parameter. The performance of probe sets trained on sequences from different organisms shows additionally that probes should be chosen with regard to the organism under analysis. Case studies are presented on how constraints (G+C-content, complexity of the individual probes) influence the selection process.
A description of the oligonucleotide fingerprinting pipeline is published on our web-page http://www.molgen.mpg.de/ approximately ag_onf/met.htm. An executable of the algorithm and probe lists designed for human and rodents can be downloaded from the ftp-site ftp://ftp.molgen.mpg.de/pub/mpimg/probe_design/.
There is burgeoning interest in protein microarrays, but a source of thousands of nonredundant, purified proteins was not previously available. Here we show a glass chip containing 2413 nonredundant purified human fusion proteins on a polymer surface, where densities up to 1600 proteins/cm(2) on a microscope slide can be realized. In addition, the polymer coating of the glass slide enables screening of protein interactions under nondenaturing conditions. Such screenings require only 200-microl sample volumes, illustrating their potential for high-throughput applications. Here we demonstrate two applications: the characterization of antibody binding, specificity, and cross-reactivity; and profiling the antibody repertoire in body fluids, such as serum from patients with autoimmune diseases. For the first application, we have incubated these protein chips with anti-RGSHis(6), anti-GAPDH, and anti-HSP90beta antibodies. In an initial proof of principle study for the second application, we have screened serum from alopecia and arthritis patients. With analysis of large sample numbers, identification of disease-associated proteins to generate novel diagnostic markers may be possible.
Protein biochips have a great potential in future parallel processing of complex samples as a research tool and in diagnostics. For the generation of protein biochips, highly automated technologies have been developed for cDNA expression library production, high throughput protein expression, large scale analysis of proteins, and protein microarray generation. Using this technology, we present here a strategy to identify potential autoantigens involved in the pathogenesis of alopecia areata, an often chronic disease leading to the rapid loss of scalp hair. Only little is known about the putative autoantigen(s) involved in this process. By combining protein microarray technology with the use of large cDNA expression libraries, we profiled the autoantibody repertoire of sera from alopecia areata patients against a human protein array consisting of 37,200 redundant, recombinant human proteins. The data sets obtained from incubations with patient sera were compared with control sera from clinically healthy persons and to background incubations with anti-human IgG antibodies. From these results, a smaller protein subset was generated and subjected to qualitative and quantitative validation on highly sensitive protein microarrays to identify novel alopecia areata-associated autoantigens. Eight autoantigens were identified by protein chip technology and were successfully confirmed by Western blot analysis. These autoantigens were arrayed on protein microarrays to generate a disease-associated protein chip. To confirm the specificity of the results obtained, sera from patients with psoriasis or hand and foot eczema as well as skin allergy were additionally examined on the disease-associated protein chip. By using alopecia areata as a model for an autoimmune disease, our investigations show that the protein microarray technology has potential for the identification and evaluation of autoantigens as well as in diagnosis such as to differentiate alopecia areata from other skin diseases.
A serum pool from 800 healthy donors and individual samples from three healthy donors were passed through tubulin, actin, thyroglobulin, myoglobin, fetuin, transferrin, albumin, cytochrome c, and collagen immunoadsorbent columns. Proteins were eluted from all the immunoadsorbents and were found to be essentially composed of the three major Ig classes and albumin. Isolated Ig fractions were studied by competitive and noncompetitive enzyme immunoassays and were shown to bind specifically to the antigens via their Fab fragment. When the isolated antibodies were tested by a noncompetitive assay, anti-tubulin antibodies were found to bind exclusively to tubulin, whereas the others bound mainly to their respective homologous antigens and to a lesser extent to one or more other antigens. When the isolated antibodies were examined by a competitive assay, they fell into three groups: the first group, consisting of anti-tubulin and anti-thyroglobulin, was only inhibited by their respective antigens. The second group was comprised of anti-actin, anti-myoglobin, and anti-fetuin; antibodies mainly inhibited by their respective antigens, but also to a significant degree by two or three additional antigens; thus, the reaction between anti-actin antibodies and immobilized actin was chiefly inhibited by actin, but tubulin and tyroglobulin also inhibited to some extent. The third antibody group consisted of anti-albumin, anti-transferrin, anti-collagen, and anti-cytochrome c, which bound specifically to the antigens but were only inhibited slightly or not at all by their respective antigens. Finally, immunocytologic staining showed antibody binding to constituents present in normal human cells. These results strongly suggest that natural antibodies against the nine antigens examined are present in normal human serum, and indicate that natural antibodies directed against a great variety of antigens - often self antigens - might be present in normal serum.
The evolution of the immune system has provided a multilevel system that interconnects the innate and adaptive immune systems to serve at least three central purposes: the defense from microbial pathogens, the capacity for discrimination of self- from non-self necessary for the prevention of autoimmune disease, and essential effector roles in wound repair and tissue remodeling. In recent studies, we have elucidated an unsuspected role for a class of naturally occurring autoreactive antibodies from the most primitive tier of B lymphocytes, which regulates fundamental functions of the innate immune system. Our findings also throw light onto long unresolved mysteries regarding the origins of the earliest waves of B lymphocyte development.
Immunoblotting of platelets that have been subjected to SDS-PAGE has revealed that sera from normal individuals contain IgG which binds to many platelet components. This binding was seen with autologous and heterologous platelets using serum of males and of nulliparous females who had not received blood transfusions. Although binding patterns of different sera were not identical, almost all sera caused IgG binding to platelet components of 87-90 kD, 140 kD (identified as vinculin) and 220-240 kD (tentatively identified as talin and actin-binding protein). Purified IgG showed the same binding pattern as whole serum and F(ab')2 fragments retained their ability to bind to many components. The titre of IgG binding in serum was 1:50-1600 while that of alloantibodies to the PlA1 antigen was 1:3200. IgG binding components were not secreted when platelets were stimulated and were rarely associated with isolated membranes, but were located either in platelet cytoplasm or cytoskeletons. IgG binding was decreased by absorbing sera with lysed platelets or isolated cytoskeletons, but only slightly with intact platelets. Microaffinity purification of IgG which formed a major band on immunoblots showed that it was antibody with specificity for vinculin or its degradation products. These findings suggest that normal sera contain naturally occurring IgG antibodies with specificity for intracellular platelet antigens and that in some cases their titre approaches that of antibodies of pathological significance.
There is strong preclinical evidence that cancer, including breast cancer, undergoes immune surveillance. This continual monitoring, by both the innate and the adaptive immune systems, recognizes changes in protein expression, mutation, folding, glycosylation, and degradation. Local immune responses to tumor antigens are amplified in draining lymph nodes, and then enter the systemic circulation. The antibody response to tumor antigens, such as p53 protein, are robust, stable, and easily detected in serum; may exist in greater concentrations than their cognate antigens; and are potential highly specific biomarkers for cancer. However, antibodies have limited sensitivities as single analytes, and differences in protein purification and assay characteristics have limited their clinical application. For example, p53 autoantibodies in the sera are highly specific for cancer patients, but are only detected in the sera of 10-20% of patients with breast cancer. Detection of p53 autoantibodies is dependent on tumor burden, p53 mutation, rapidly decreases with effective therapy, but is relatively independent of breast cancer subtype. Although antibodies to hundreds of other tumor antigens have been identified in the sera of breast cancer patients, very little is known about the specificity and clinical impact of the antibody immune repertoire to breast cancer. Recent advances in proteomic technologies have the potential for rapid identification of immune response signatures for breast cancer diagnosis and monitoring. We have adapted programmable protein microarrays for the specific detection of autoantibodies in breast cancer. Here, we present the first demonstration of the application of programmable protein microarray ELISAs for the rapid identification of breast cancer autoantibodies.
Protein domains are independently folded regions of proteins that are often involved in protein-protein interactions. They are good candidates for the generation of protein microarrays because of their small size, their globular structures, and the fact that they are the protein-interacting workhorses of the cell. In addition, arrayed recombinant protein domains retain much of their binding specificity. Such microarrays can be probed with other recombinant proteins or fluorescently labeled peptides to identify potential binding partners and also determine how posttranslational modifications influence specific interactions. Thus, protein domains provide us with a system-oriented array that is focused on elucidating signal transduction pathway specificity and regulation.
A nonredundant human protein chip for antibody screening and serum profiling
- Lueking A
- A Possling
- O Huber
- A Beveridge
- M Horn
- H Eickhoff
- J Schuchardt
- H Lebrach
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Naturally occurring antibodies against nine common antigens in human sera. I. Detection, isolation and characterization
- B Guilbert
- G Dighiero
- B. Guilbert
Natural Autoantibodies to Apoptotic Cell Membranes Regulate Fundamental Innate Immune Functions and Suppress Inflammation
- G J Silverman
- C Gronwall
- J Vas
- GJ Silverman