Probing the epitope signatures of IgG antibodies in human serum from patients with autoimmune disease

Applications of Peptide Microarrays in Autoantibody, Infection, and Cancer Detection

The diversity of the antigen-specific humoral immune response reflects the interaction of the immune system with pathogens and autoantigens. Peptide microarray analysis opens up new perspectives for the use of antibodies as diagnostic biomarkers and provides unique access to a more differentiated view on humoral responses to disease. This review focuses on the latest applications of peptide microarrays for the serologic medical diagnosis of autoimmunity, infectious diseases (including COVID-19), and cancer.

High-Density Peptide Microarray Analysis of IgG Autoantibody Reactivities in Serum and Cerebrospinal Fluid of Multiple Sclerosis Patients

Intrathecal immunoglobulin G (IgG) synthesis and oligoclonal IgG bands in cerebrospinal fluid (CSF) are hallmarks of multiple sclerosis (MS), but the antigen specificities remain enigmatic. Our study is the first investigating the autoantibody repertoire in paired serum and CSF samples from patients with relapsing-remitting MS (RRMS), primary progressive MS (PPMS), and other neurological diseases by the use of high-density peptide microarrays. Protein sequences of 45 presumed MS autoantigens (e.g.MOG, MBP, and MAG) were represented on the microarrays by overlapping 15mer peptides. IgG reactivities were screened against a total of 3991 peptides, including also selected viral epitopes. The measured antibody reactivities were highly individual but correlated for matched serum and CSF samples. We found 54 peptides to be recognized significantly more often by serum or CSF antibodies from MS patients compared with controls (pvalues <0.05). The results for RRMS and PPMS clearly overlapped. However, PPMS patients presented a broader peptide-antibody signature. The highest signals were detected for a peptide mapping to a region of the Epstein-Barr virus protein EBNA1 (amino acids 392-411), which is homologous to the N-terminal part of human crystallin alpha-B. Our data confirmed several known MS-associated antigens and epitopes, and they delivered additional potential linear epitopes, which await further validation. The peripheral and intrathecal humoral immune response in MS is polyspecific and includes antibodies that are also found in serum of patients with other diseases. Further studies are required to assess the pathogenic relevance of autoreactive and anti-EBNA1 antibodies as well as their combinatorial value as biomarkers for MS.

Peptide Microarrays for Medical Applications in Autoimmunity, Infection, and Cancer

The diversity of the antigen-specific humoral immune response reflects the interaction of the immune system with pathogens and autoantigens. Peptide microarray analysis opens up new perspectives for the use of antibodies as diagnostic biomarkers and provides unique access to a more differentiated serological diagnosis. This review focusses on latest applications of peptide microarrays for the serologic medical diagnosis of autoimmunity, infectious diseases, and cancer.

Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development

An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth of IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research.

Epitope predictions indicate the presence of two distinct types of epitope-antibody-reactivities determined by epitope profiling of intravenous immunoglobulins

Epitope-antibody-reactivities (EAR) of intravenous immunoglobulins (IVIGs) determined for 75,534 peptides by microarray analysis demonstrate that roughly 9% of peptides derived from 870 different human protein sequences react with antibodies present in IVIG. Computational prediction of linear B cell epitopes was conducted using machine learning with an ensemble of classifiers in combination with position weight matrix (PWM) analysis. Machine learning slightly outperformed PWM with area under the curve (AUC) of 0.884 vs. 0.849. Two different types of epitope-antibody recognition-modes (Type I EAR and Type II EAR) were found. Peptides of Type I EAR are high in tyrosine, tryptophan and phenylalanine, and low in asparagine, glutamine and glutamic acid residues, whereas for peptides of Type II EAR it is the other way around. Representative crystal structures present in the Protein Data Bank (PDB) of Type I EAR are PDB 1TZI and PDB 2DD8, while PDB 2FD6 and 2J4W are typical for Type II EAR. Type I EAR peptides share predicted propensities for being presented by MHC class I and class II complexes. The latter interaction possibly favors T cell-dependent antibody responses including IgG class switching. Peptides of Type II EAR are predicted not to be preferentially presented by MHC complexes, thus implying the involvement of T cell-independent IgG class switch mechanisms. The high extent of IgG immunoglobulin reactivity with human peptides implies that circulating IgG molecules are prone to bind to human protein/peptide structures under non-pathological, non-inflammatory conditions. A webserver for predicting EAR of peptide sequences is available at www.sysmed-immun.eu/EAR.

Mass spectrometric and peptide chip characterization of an assembled epitope: analysis of a polyclonal antibody model serum directed against the Sjøgren/systemic lupus erythematosus autoantigen TRIM21

We demonstrate the development of a mass spectrometry-based epitope-mapping procedure in combination with Western blot analysis that works also with antigens that are insoluble in nondenaturing buffers consuming minute amounts of antigen (approximately 200 pmol) and antibody (approximately 15 pmol), respectively. A polyclonal anti-TRIM21 rabbit antibody serum is applied as a model serum for future patient analyses to set up the system. The major epitope that is recognized by the anti-TRIM21 serum spans the central TRIM21 region LQ-ELEKDEREQLRILGE-KE, showing that immunization with a 139-amino acid residue long peptide resulted in a 'monospecific' polyclonal antibody repertoire. Protein structure investigations, secondary structure predictions, and surface area calculations revealed that the best matching partial sequence to fulfill all primary and secondary structure requirements was the four amino acid spanning motif 'L-E-Q-L', which is present in both the sequential and the α-helical peptide conformation. Peptide chip analyses confirmed the mass spectrometric results and showed that the peptide chip platform is an appropriate method for displaying secondary structure-relying epitope conformations. As the same secondary structures are present in vivo, patient antibody screening, e.g., to identify subgroups of patients according to distinct epitope antibody reactivities, is feasible.

Prediction of peptide reactivity with human IVIg through a knowledge-based approach

The prediction of antibody-protein (antigen) interactions is very difficult due to the huge variability that characterizes the structure of the antibodies. The region of the antigen bound to the antibodies is called epitope. Experimental data indicate that many antibodies react with a panel of distinct epitopes (positive reaction). The Challenge 1 of DREAM5 aims at understanding whether there exists rules for predicting the reactivity of a peptide/epitope, i.e., its capability to bind to human antibodies. DREAM 5 provided a training set of peptides with experimentally identified high and low reactivities to human antibodies. On the basis of this training set, the participants to the challenge were asked to develop a predictive model of reactivity. A test set was then provided to evaluate the performance of the model implemented so far.We developed a logistic regression model to predict the peptide reactivity, by facing the challenge as a machine learning problem. The initial features have been generated on the basis of the available knowledge and the information reported in the dataset. Our predictive model had the second best performance of the challenge. We also developed a method, based on a clustering approach, able to "in-silico" generate a list of positive and negative new peptide sequences, as requested by the DREAM5 "bonus round" additional challenge.The paper describes the developed model and its results in terms of reactivity prediction, and highlights some open issues concerning the propensity of a peptide to react with human antibodies.

Realizing individualized medicine: the road to translating proteomics from the laboratory to the clinic

The sequencing of the human genome has brought great promise and potential for the future of medicine, as well as providing a strong momentum for the burgeoning field of individualized medicine. Tests based on genetic information can be used to allow physicians to target therapies for those patients most likely to benefit from specific therapies and identify potential risk before the onset of disease. While advances in genomics-based molecular diagnostics are progressing, producing some useful US FDA-approved/-cleared diagnostic tests, protein-based molecular diagnostics have not met its promised potential. This article will provide an overview of protein-based analysis technologies, identify their strengths and limitations, discuss barriers to protein-based biomarker development and identify issues which must be addressed in order to successfully transfer the field of proteomics from the laboratory to the clinic.

Immunoprofiling using NAPPA protein microarrays

Protein microarrays provide an efficient method to immunoprofile patients in an effort to rapidly identify disease immunosignatures. The validity of using autoantibodies in diagnosis has been demonstrated in type 1 diabetes, rheumatoid arthritis, and systemic lupus, and is now being strongly considered in cancer. Several types of protein microarrays exist including antibody and antigen arrays. In this chapter, we describe the immunoprofiling application for one type of antigen array called NAPPA (nucleic acids programmable protein array). We provide a guideline for setting up the screening study and designing protein arrays to maximize the likelihood of obtaining quality data.

Long-lived plasma cells and memory B cells produce pathogenic anti-GAD65 autoantibodies in Stiff Person Syndrome

Stiff person syndrome (SPS) is a rare, neurological disorder characterized by sudden cramps and spasms. High titers of enzyme-inhibiting IgG autoantibodies against the 65 kD isoform of glutamic acid decarboxylase (GAD65) are a hallmark of SPS, implicating an autoimmune component in the pathology of the syndrome. Studying the B cell compartment and the anti-GAD65 B cell response in two monozygotic twins suffering from SPS, who were treated with the B cell-depleting monoclonal anti-CD20 antibody rituximab, we found that the humoral autoimmune response in SPS is composed of a rituximab-sensitive part that is rapidly cleared after treatment, and a rituximab-resistant component, which persists and acts as a reservoir for autoantibodies inhibiting GAD65 enzyme activity. Our data show that these potentially pathogenic anti-GAD65 autoantibodies are secreted by long-lived plasma cells, which may either be persistent or develop from rituximab-resistant memory B lymphocytes. Both subsets represent only a fraction of anti-GAD65 autoantibody secreting cells. Therefore, the identification and targeting of this compartment is a key factor for successful treatment planning of SPS and of similar autoimmune diseases.

Mass spectrometric and peptide chip epitope analysis on the RA33 autoantigen with sera from rheumatoid arthritis patients

As the potential of epitope chips for routine application in diagnostics relies on the careful selection of peptides, reliable epitope mapping results are of utmost interest to the medical community. Mass spectrometric epitope mapping in combination with peptide chip analysis showed that autoantibodies from patients who suffered from rheumatoid arthritis (RA) were directed against distinct surface structures on the full-length human autoantigen RA33 as well as against partial sequences. Using the combined mass spectrometric epitope extraction and peptide chip analysis approach, four sequence motifs on RA33 emerged as immuno-positive, showing that epitopes were not randomly distributed on the entire RA33 amino acid sequence. A sequential epitope motif ((245)GYGGG(249)) was determined on the C-terminal part of RA33 which matched with the Western blot patient screening results using the full-length protein and, thus, was regarded as a disease-associated epitope. Other epitope motifs were found on N-terminal partial sequences ((59)RSRGFGF(65), (111)KKLFVG(116)) and again on the C-terminal part ((266)NQQPSNYG(273)) of RA33. As recognition of these latter three motifs was also recorded by peptide chip analysis using control samples which were negative in the Western blot screening, these latter motifs were regarded as "cryptic epitopes". Knowledge of disease-associated epitopes is crucial for improving the design of a customized epitope peptide chip for RA and mass spectrometric epitope mapping pivotally assisted with selecting the most informative peptide(s) to be used for future diagnostic purposes.

Antibody signatures defined by high-content peptide microarray analysis

Circulating antibodies are highly selective binding reagents directed to a vast repertoire of antigens. Candidate antigens displayed as overlapping peptides on microarrays can be used to screen for recognition by serum antibodies from clinically well-defined patient populations. The methodology is robust and enables unbiased visualization of antigen-specific B-cell responses. Additionally, autoantibody signatures of diagnostic value could be detected using microarrays displaying thousands of human peptides.

Mass spectrometric and peptide chip epitope mapping of rheumatoid arthritis autoantigen RA33

The protein termed RA33 was determined to be one major autoantigen in rheumatoid arthritis (RA) patients and antiRA33 auto-antibodies were found to appear shortly after onset of RA. They are often detectable before a final diagnosis can be made in the clinic. The aim of our study is to characterise the epitope of a monoclonal antiRA33 antibody on recombinant RA33 using mass spectrometric epitope mapping. Recombinant RA33 has been subjected to BrCN cleavage and fragments were separated by sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Subsequent in-gel proteolytic digestion and mass spectrometric analysis determined the partial sequences in the protein bands. Western blotting of SDS-PAGE-separated protein fragments revealed immuno-positive, i.e. epitope-containing bands. BrCN-derived RA33 fragments were also separated by high- performance liquid chromatography (HPLC) and immuno-reactivity of peptides was measured by dot-blot analysis with the individual HPLC fractions after partial amino acid sequences were determined. The epitope region identified herewith was compared to data from peptide chip analysis with 15-meric synthetic peptides attached to a glass surface. Results from all three analyses consistently showed that the epitope of the monoclonal antiRA33 antibody is located in the aa79-84 region on recombinant RA33; the epitope sequence is MAARPHSIDGRVVEP. Sequence comparisons of the 15 best scoring peptides from the peptide chip analysis revealed that the epitope can be separated into two adjacent binding parts. The N-terminal binding parts comprise the amino acid residues "DGR", resembling the general physico-chemical properties "acidic/polar-small-basic". The C-terminal binding parts contain the amino acid residues "VVE", with the motif "hydrophobic-gap-acidic". The matching epitope region that emerged from our analysis on both the full-length protein and the 15-meric surface bound peptides suggests that peptide chips are indeed suitable tools for screening patterns of autoantibodies in patients suffering from autoimmune diseases.