Validation of peptide epitope microarray experiments and extraction of quality data

Antibody landscape of C57BL/6 mice cured of B78 melanoma via a combined radiation and immunocytokine immunotherapy regimen

Sera of immune mice that were previously cured of their melanoma through a combined radiation and immunocytokine immunotherapy regimen consisting of 12 Gy of external beam radiation and the intratumoral administration of an immunocytokine (anti-GD2 mAb coupled to IL-2) with long-term immunological memory showed strong antibody-binding against melanoma tumor cell lines via flow cytometric analysis. Using a high-density whole-proteome peptide array (of 6.090.593 unique peptides), we assessed potential protein-targets for antibodies found in immune sera. Sera from 6 of these cured mice were analyzed with this high-density, whole-proteome peptide array to determine specific antibody-binding sites and their linear peptide sequence. We identified thousands of peptides that were targeted by these 6 mice and exhibited strong antibody binding only by immune (after successful cure and rechallenge), not naïve (before tumor implantation) sera and developed a robust method to detect these differentially targeted peptides. Confirmatory studies were done to validate these results using 2 separate systems, a peptide ELISA and a smaller scale peptide array utilizing a slightly different technology. To the best of our knowledge, this is the first study of the full set of germline encoded linear peptide-based proteome epitopes that are recognized by immune sera from mice cured of cancer via radio-immunotherapy. We furthermore found that although the generation of B-cell repertoire in immune development is vastly variable, and numerous epitopes are identified uniquely by immune serum from each of these 6 immune mice evaluated, there are still several epitopes and proteins that are commonly recognized by at least half of the mice studied. This suggests that every mouse has a unique set of antibodies produced in response to the curative therapy, creating an individual "fingerprint." Additionally, certain epitopes and proteins stand out as more immunogenic, as they are recognized by multiple mice in the immune group.

Development of a Cell-based Neutralizing Antibody Assay for Zinpentraxin Alfa: Challenges and Mitigation Strategies

Therapeutic protein drugs can potentially induce immune responses in patients and result in the production of anti-drug antibodies (ADAs), including a subset of ADAs called neutralizing antibodies (NAbs) that might cause loss of efficacy by inhibiting clinical activities of the drug. Herein, we describe the unique challenges encountered during the development of a fit-for-purpose cell-based NAb assay for a new protein modality, zinpentraxin alfa, including our strategies for assay design to overcome various matrix interferences and improve assay drug tolerance. We demonstrated that a typical biotin-drug extraction with acid dissociation (BEAD) approach alone was not sufficient to eliminate matrix interferences in this assay. Instead, the combination of the BEAD and ZebaTM spin size exclusion plate (SEP) was required to achieve the desirable assay performance. We also demonstrated that appropriate acidic buffers were critical in sample pretreatment to improve assay drug tolerance, which not only dissociated the drug/NAb immune complex but also effectively and irreversibly denatured the free drug. The final assay performed well with confirmed assay robustness and suitability for the clinical applications.

Antibody landscape of C57BL/6 mice cured of B78 melanoma via immunotherapy

Hoefges et al. utilized a whole-proteome peptide array approach to show that C57BL/6 mice develop a large repertoire of antibodies against linear peptide sequences of their melanoma after receiving a curative immunotherapy regimen consisting of radiation and an immunocytokine. Antibodies can play an important role in innate and adaptive immune responses against cancer, and in preventing infectious disease. Flow cytometry analysis of sera of immune mice that were previously cured of their melanoma through a combined immunotherapy regimen with long-term memory showed strong antibody-binding against melanoma tumor cell lines. Using a high-density whole-proteome peptide array, we assessed potential protein-targets for antibodies found in immune sera. Sera from 6 of these cured mice were analyzed with this high-density, whole-proteome peptide array to determine specific antibody-binding sites and their linear peptide sequence. We identified thousands of peptides that were targeted by 2 or more of these 6 mice and exhibited strong antibody binding only by immune, not naive sera. Confirmatory studies were done to validate these results using 2 separate ELISA-based systems. To the best of our knowledge, this is the first study of the "immunome" of protein-based epitopes that are recognized by immune sera from mice cured of cancer via immunotherapy.

Ranking Antibody Binding Epitopes and Proteins Across Samples from Whole Proteome Tiled Linear Peptides

Ultradense peptide binding arrays that can probe millions of linear peptides comprising the entire proteomes or immunomes of human or mouse, or numerous microbes, are powerful tools for studying the abundance of different antibody repertoire in serum samples to understand adaptive immune responses. There are few statistical analysis tools for exploring high-dimensional, significant and reproducible antibody targets for ultradense peptide binding arrays at the linear peptide, epitope (grouping of adjacent peptides), and protein level across multiple samples/subjects (I.e. epitope spread or immunogenic regions within each protein) for understanding the heterogeneity of immune responses. We developed HERON (Hierarchical antibody binding Epitopes and pROteins from liNear peptides), an R package, which allows users to identify immunogenic epitopes using meta-analyses and spatial clustering techniques to explore antibody targets at various resolution and confidence levels, that can be found consistently across a specified number of samples through the entire proteome to study antibody responses for diagnostics or treatment. Our approach estimates significance values at the linear peptide (probe), epitope, and protein level to identify top candidates for validation. We test the performance of predictions on all three levels using correlation between technical replicates and comparison of epitope calls on 2 datasets, which shows HERON's competitiveness in estimating false discovery rates and finding general and sample-level regions of interest for antibody binding. The code is available as an R package downloadable from http://github.com/Ong-Research/HERON.

Epitope and affinity determination of recombinant Mycobacterium tuberculosis Ag85B antigen towards anti-Ag85 antibodies using proteolytic affinity-mass spectrometry and biosensor analysis

Tuberculosis (TB) is the first cause of death from infectious diseases worldwide. Only a single anti-TB vaccine is currently available for clinical use, but its efficacy is not achieved with certainty. The aim of this work is to provide a basis for the rational design of a neo-glycoconjugate vaccine against TB. Structural characterization of recombinant antigenic proteins from Mycobacterium tuberculosis (MTB) Ag85B (rAg85B, variants, and semi-synthetic glycoconjugates) was initially carried out. Identification of antibody epitope analyses by proteolytic affinity-mass spectrometry and surface plasmon resonance (SPR) biosensor analyses were performed in order to qualitatively identify and quantitatively characterize interaction structures of the antigens with antibodies from different sources. A commercial monoclonal antibody and polyclonal antibodies from different sources (patients with active TB, vaccinated individuals, and a healthy control) were employed to analyze antigen-antibody interactions. These combined approaches provided the identification of different assembled epitope regions on the recombinant MTB antigens, their affinity binding constants in the interactions with specific antibodies, and revealed the importance of protection from excessive glycosylation. The identified epitope peptides should constitute a suitable basis for the design of new specific target vaccines. Graphical abstract ᅟ.

Similar Epitope Specificities of IgG and IgA Antibodies Elicited by Ad26 Vector Prime, Env Protein Boost Immunizations in Rhesus Monkeys

Vaccine-elicited immunoglobulin G (IgG) has been shown to be important for protection against simian-human immunodeficiency virus (SHIV) infection in rhesus monkeys. However, it remains unclear whether vaccine-elicited IgA responses are beneficial or detrimental for protection. In this study, we evaluated the kinetics, magnitude, breadth, and linear epitope specificities of vaccine-elicited IgG and IgA responses in serum and mucosal secretions following intramuscular immunization with adenovirus 26 (Ad26) prime, Env protein boost vaccination regimens. The systemic and mucosal antibody responses exhibited kinetics similar to those of the serum antibody responses but lower titers than the serum antibody responses. Moreover, the IgG and IgA responses were correlated, both in terms of the magnitude of the responses and in terms of the antibody specificities against linear human immunodeficiency virus type 1 (HIV-1) Env, Gag, and Pol epitopes. These data suggest that IgG and IgA responses are highly coordinated in both peripheral blood and mucosal compartments following Ad26/Env vaccination in rhesus monkeys.IMPORTANCE Vaccine-elicited IgG responses are important for protection against simian-human immunodeficiency virus (SHIV) infection in nonhuman primates. However, much less is known about the role and function of IgA, despite it being the predominant antibody in mucosal sites. There is debate as to whether HIV-1-specific IgA responses are beneficial or detrimental, since serum anti-Env IgA titers were shown to be inversely correlated with protection in the RV144 clinical trial. We thus assessed vaccine-elicited IgG and IgA antibody responses in peripheral blood and mucosal secretions following vaccination with the Ad26/Env vaccine.

Importance of serological cross-reactivity among Toxoplasma gondii, Hammondia spp., Neospora spp., Sarcocystis spp. and Besnoitia besnoiti

Toxoplasma gondii, Neospora spp., Sarcocystis spp., Hammondia spp. and Besnoitia besnoiti are genetically related cyst-forming coccidia. Serology is frequently used for the identification of T. gondii, Neospora spp. and B. besnoiti-exposed individuals. Serologic cross-reactions occur in different tests among animals infected with T. gondii and H. hammondi, as well as among animals infected by T. gondii and N. caninum. Infections caused by N. caninum and N. hughesi are almost indistinguishable by serology. Neospora caninum, B. besnoiti and Sarcocystis spp. infections in cattle show some degree of serologic cross-reactivity. Antibody cross-reactivity between Neospora spp. and H. heydorni-infected animals is suspected, but not proven to occur. We review serologic cross-reactivity among animals and/or humans infected with T. gondii, Neospora spp., Sarcocystis spp., Hammondia spp. and B. besnoiti. Emphasis is laid upon antigens and serological methods for N. caninum diagnosis which were tested for cross-reactivity with related protozoa. Species-specific antigens, as well as stage-specific proteins have been identified in some of these parasites and have promising use for diagnosis and epidemiological surveys.

Peptide microarray-based characterization of antibody responses to host proteins after bacille Calmette-Guérin vaccination

BACKGROUND

Bacille Calmette-Guérin (BCG) is the world's most widely distributed vaccine, used against tuberculosis (TB), in cancer immunotherapy, and in autoimmune diseases due to its immunomodulatory properties. To date, the effect of BCG vaccination on antibody responses to host proteins has not been reported. High-content peptide microarrays (HCPM) offer a unique opportunity to gauge specific humoral immune responses.

METHODS

The sera of BCG-vaccinated healthy adults were tested on a human HCPM platform (4953 randomly selected epitopes of human proteins) to detect specific immunoglobulin gamma (IgG) responses. Samples were obtained at 56, 112, and 252 days after vaccination. Immunohistology was performed on lymph node tissue from patients with TB lymphadenitis. Results were analysed with a combination of existing and novel statistical methods.

RESULTS

IgG recognition of host peptides exhibited a peak at day 56 post BCG vaccination in all study subjects tested, which diminished over time. Primarily, IgG responses exhibited increased reactivity to ion transporters (sodium, calcium channels), cytokine receptors (interleukin 2 receptor β (IL2Rβ), fibroblast growth factor receptor 1 (FGFR1)), other cell surface receptors (inositol, somatostatin, angiopoeitin), ribonucleoprotein, and enzymes (tyrosine kinases, phospholipase) on day 56. There was decreased IgG reactivity to transforming growth factor-beta type 1 receptor (TGFβR1) and, in agreement with the peptide microarray findings, immunohistochemical analysis of TB-infected lymph node samples revealed an overexpression of TGFβR in granulomatous lesions. Moreover, the vesicular monoamine transporter (VMAT2) showed increased reactivity on days 112 and 252, but not on day 56 post-vaccination. IgG to interleukin 4 receptor (IL4R) showed increased reactivity at 112 days post-vaccination, while IgG to IL2Rβ and FGFR1 showed decreased reactivity on days 112 and 252 as compared to day 56 post BCG vaccination.

CONCLUSIONS

BCG vaccination modifies the host's immune landscape after 56 days, but this imprint changes over time. This may influence the establishment of immunological memory in BCG-vaccinated individuals.

Humoral immune profiling of mycobacterial antigen recognition in sarcoidosis and Löfgren's syndrome using high-content peptide microarrays

INTRODUCTION

Sarcoidosis is considered an idiopathic granulomatous disease, although similar immunological and clinical features with tuberculosis (TB) suggest mycobacterial involvement in its pathogenesis. High-content peptide microarrays (HCPM) may help to decipher mycobacteria-specific antibody reactivity in sarcoidosis.

METHODS

Serum samples from patients with sarcoidosis, Löfgren's syndrome, and TB, as well as from healthy individuals (12/group), were tested on HCPM containing 5964 individual peptides spanning 154 Mycobacterium tuberculosis proteins displayed as 15-amino acid stretches. Inclusion/exclusion and significance analyses were performed according to published methods.

RESULTS

Each study group recognized 68-78% M. tuberculosis peptides at least once. M. tuberculosis epitope recognition by sarcoidosis patient sera was 42.7%, and by TB patient sera was 39.1%. Seven and 16 peptides were recognized in 9/12 (75%) and 8/12 (67%) sarcoidosis patient sera but not in TB patient sera, respectively. Nine (75%) and eight (67%) out of twelve TB patient sera, respectively recognized M. tuberculosis peptides that were not recognized in sarcoidosis patient sera.

CONCLUSIONS

Specific IgG recognition patterns for M. tuberculosis antigens in sarcoidosis patients re-affirm mycobacterial involvement in sarcoidosis, providing biologically relevant targets for future studies pertaining to diagnostics and immunotherapy.

Antibody Responses After Analytic Treatment Interruption in Human Immunodeficiency Virus-1-Infected Individuals on Early Initiated Antiretroviral Therapy

The examination of antibody responses in human immunodeficiency virus (HIV)-1-infected individuals in the setting of antiretroviral treatment (ART) interruption can provide insight into the evolution of antibody responses during viral rebound. In this study, we assessed antibody responses in 20 subjects in AIDS Clinical Trials Group A5187, wherein subjects were treated with antiretroviral therapy during acute/early HIV-1 infection, underwent analytic treatment interruption, and subsequently demonstrated viral rebound. Our data suggest that early initiation of ART arrests the maturation of HIV-1-specific antibody responses, preventing epitope diversification of antibody binding and the development of functional neutralizing capacity. Antibody responses do not appear permanently blunted, however, because viral rebound triggered the resumption of antibody maturation in our study. We also found that antibody responses measured by these assays did not predict imminent viral rebound. These data have important implications for the HIV-1 vaccine and eradication fields.

A statistical approach to determining responses to individual peptides from pooled-peptide ELISpot data

To investigate in detail the effect of infection or vaccination on the human immune system, ELISpot assays are used to simultaneously test the immune response to a large number of peptides of interest. Scientists commonly use "peptide pools", where, instead of an individual peptide, a test well contains a group of peptides. Since the response from a well may be due to any or many of the peptides in the pool, pooled assays usually need to be followed by confirmatory assays of a number of individual peptides. We present a statistical method that enables estimation of individual peptide responses from pool responses using the Expectation Maximization (EM) algorithm for "incomplete data". We demonstrate the accuracy and precision of these estimates in simulation studies of ELISpot plates with 90 pools of 6 or 7 peptides arranged in three dimensions and three Mock wells for the estimation of background. In analysis of real pooled data from 6 subjects in a HIV-1 vaccine trial, where 199 peptides were arranged in 80 pools if size 9 or 10, our estimates were in very good agreement with the results from individual-peptide confirmatory assays. Compared to the classical approach, we could identify almost all the same peptides with high or moderate response, with less than half the number of confirmatory tests. Our method facilitates efficient use of the information available in pooled ELISpot data to avoid or reduce the need for confirmatory testing. We provide an easy-to-use free online application for implementing the method, where on uploading two spreadsheets with the pool design and pool responses, the user obtains the estimates of the individual peptide responses.

Bayesian hierarchical modeling for subject-level response classification in peptide microarray immunoassays

The peptide microarray immunoassay simultaneously screens sample serum against thousands of peptides, determining the presence of antibodies bound to array probes. Peptide microarrays tiling immunogenic regions of pathogens (e.g., envelope proteins of a virus) are an important high throughput tool for querying and mapping antibody binding. Because of the assay's many steps, from probe synthesis to incubation, peptide microarray data can be noisy with extreme outliers. In addition, subjects may produce different antibody profiles in response to an identical vaccine stimulus or infection, due to variability among subjects' immune systems. We present a robust Bayesian hierarchical model for peptide microarray experiments, pepBayes, to estimate the probability of antibody response for each subject/peptide combination. Heavy-tailed error distributions accommodate outliers and extreme responses, and tailored random effect terms automatically incorporate technical effects prevalent in the assay. We apply our model to two vaccine trial data sets to demonstrate model performance. Our approach enjoys high sensitivity and specificity when detecting vaccine induced antibody responses. A simulation study shows an adaptive thresholding classification method has appropriate false discovery rate control with high sensitivity, and receiver operating characteristics generated on vaccine trial data suggest that pepBayes clearly separates responses from non-responses.

Analyzing Peptide Microarray Data with the R pepStat Package

In this chapter we demonstrate the use of R Bioconductor packages pepStat and Pviz on a set of paired peptide microarrays generated from vaccine trial data. Data import, background correction, normalization, and summarization techniques are presented. We introduce a sliding mean method for amplifying signal and reducing noise in the data, and show the value of gathering paired samples from subjects. Useful visual summaries are presented, and we introduce a simple method for setting a decision rule for subject/peptide responses that can be used with a set of control peptides or placebo subjects.

Chimeric peptide constructs comprising linear B-cell epitopes: application to the serodiagnosis of infectious diseases

Linear B-cell epitopes are ideal biomarkers for the serodiagnosis of infectious diseases. However, the long-predicted diagnostic value of epitopes has not been realized. Here, we demonstrated a method, diagnostic epitopes in four steps (DEIFS), that delivers a combination of epitopes for the serodiagnosis of infectious diseases with a high success rate. Using DEIFS for malaria, we identified 6 epitopes from 8 peptides and combined them into 3 chimeric peptide constructs. Along with 4 other peptides, we developed a rapid diagnostic test (RDT), which is able to differentiate Plasmodium falciparum (P. falciparum) from Plasmodium vivax (P. vivax) infections with 95.6% overall sensitivity and 99.1% overall specificity. In addition to applications in diagnosis, DEIFS could also be used in the diagnosis of virus and bacterium infections, discovery of vaccine candidates, evaluation of vaccine potency, and study of disease progression.

Serum reactome induced by Bordetella pertussis infection and Pertussis vaccines: qualitative differences in serum antibody recognition patterns revealed by peptide microarray analysis

Background

Pertussis (whooping cough) remains a public health problem despite extensive vaccination strategies. Better understanding of the host-pathogen interaction and the detailed B. pertussis (Bp) target recognition pattern will help in guided vaccine design. We characterized the specific epitope antigen recognition profiles of serum antibodies (‘the reactome’) induced by whooping cough and B. pertussis (Bp) vaccines from a case–control study conducted in 1996 in infants enrolled in a Bp vaccine trial in Sweden (Gustafsson, NEJM, 1996, 334, 349–355).

Methods

Sera from children with whooping cough, vaccinated with Diphtheria Tetanus Pertussis (DTP) whole-cell (wc), acellular 5 (DPTa5), or with the 2 component (a2) vaccines and from infants receiving only DT (n = 10 for each group) were tested with high-content peptide microarrays containing 17 Bp proteins displayed as linear (n = 3175) peptide stretches. Slides were incubated with serum and peptide-IgG complexes detected with Cy5-labeled goat anti-human IgG and analyzed using a GenePix 4000B microarray scanner, followed by statistical analysis, using PAM (Prediction Analysis for Microarrays) and the identification of uniquely recognized peptide epitopes.

Results

367/3,085 (11.9%) peptides were recognized in 10/10 sera from children with whooping cough, 239 (7.7%) in DTPwc, 259 (8.4%) in DTPa5, 105 (3.4%) DTPa2, 179 (5.8%) in the DT groups. Recognition of strongly recognized peptides was similar between whooping cough and DPTwc, but statistically different between whooping cough vs. DTPa5 (p < 0.05), DTPa2 and DT (p < 0.001 vs. both) vaccines. 6/3,085 and 2/3,085 peptides were exclusively recognized in (10/10) sera from children with whooping cough and DTPa2 vaccination, respectively. DTPwc resembles more closely the whooping cough reactome as compared to acellular vaccines.

Conclusion

We could identify a unique recognition signature common for each vaccination group (10/10 children). Peptide microarray technology allows detection of subtle differences in epitope signature responses and may help to guide rational vaccine development by the objective description of a clinically relevant immune response that confers protection against infectious pathogens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12865-015-0090-3) contains supplementary material, which is available to authorized users.

Fusion of selected regions of mycobacterial antigens for enhancing sensitivity in serodiagnosis of tuberculosis

Serodiagnosis of tuberculosis requires detection of antibodies against multiple antigens of Mycobacterium tuberculosis, because antibody profiles differ among the patients. Using fusion proteins with epitopes from two or more antigens would facilitate in the detection of multiple antibodies. Fusion constructs tn1FbpC1-tnPstS1 and tn2FbpC1-tnPstS1 were produced by linking truncated regions of variable lengths from FbpC1 to the N-terminus of the truncated PstS1. Similarly a truncated fragment of HSP was linked to the N-terminus of a truncated fragment from FbpC1 to produce tnHSP-tn1FbpC1. ELISA analysis of the plasma samples of TB patients against tn2FbpC1-tnPstS1 showed 72.2% sensitivity which is nearly the same as the expected combined value for the two individual antigens. However, the sensitivity of tn1FbpC1-tnPstS1 was lowered to 60%. tnHSP-tn1FbpC1 showed 67.7% sensitivity which is slightly less than the expected combined value for the two individual antigens, but still significantly higher than that of each of the individual antigen. Data for secondary structure analysis by CD spectrometry was in reasonable agreement with the X-ray crystallographic data of the native proteins and the predicted structure of the fusion proteins. Comparative molecular modeling suggests that the epitopes of the constituent proteins are better exposed in tn2FbpC1-tnPstS1 as compared to those in tn1FbpC1-tnPstS1. Therefore, removal of the N-terminal non-epitopic region of FbpC1 from 34-96 amino acids seems to have unmasked at least some of the epitopes, resulting in greater sensitivity. The high level of sensitivity of tn2FbpC1-tnPstS1 and tnHSP-tn1FbpC1, not reported before, shows that these fusion proteins have great potential for use in serodiagnosis of tuberculosis.

A Novel Multipeptide Microarray for the Specific and Sensitive Mapping of Linear IgE-Binding Epitopes of Food Allergens

BACKGROUND

The identification of B-cell epitopes of food allergens can possibly lead to novel diagnostic tools and therapeutic reagents for food allergy. We sought to develop a flexible, low-tech, cost-effective and reproducible multipeptide microarray for the research environment to enable large-scale screening of IgE epitopes of food allergens.

METHODS

Overlapping peptides (15-mer, 4 amino acid offset) covering the primary sequence of either peanut allergen Ara h 1 or all 3 subunits of the soybean allergen Gly m 5 were simultaneously synthesized in-house on a porous cellulose matrix. Identical peptide microarrays created with up to 384 duplicate peptide-cellulose microspots each were investigated for specificity and sensitivity in IgE immunodetection and in direct experimental comparison to the formerly established SPOT™ membrane technique.

RESULTS

The in-house microarray identified with 98% reproducibility the same IgE-binding peptides as the SPOT™ membrane technique. Additional IgE-binding peptides were identified using the microarray. While the sensitivity was increased between 2- and 20-fold, the amount of human serum required was reduced by at least two thirds over the SPOT™ membrane technique using the microarray. After subtraction of the potential background, we did not observe non-specific binding to the presented peptides on microarray.

CONCLUSIONS

The novel peptide microarray allows simple and cost-effective screening for potential epitopes of large allergenic legume seed storage proteins, and it could be adapted for other food allergens as well, to study allergenic epitopes at the individual subject level in large paediatric and adult study groups of food allergic subjects.

H1N1 viral proteome peptide microarray predicts individuals at risk for H1N1 infection and segregates infection versus Pandemrix(®) vaccination

A high content peptide microarray containing the entire influenza A virus [A/California/08/2009(H1N1)] proteome and haemagglutinin proteins from 12 other influenza A subtypes, including the haemagglutinin from the [A/South Carolina/1/1918(H1N1)] strain, was used to gauge serum IgG epitope signatures before and after Pandemrix® vaccination or H1N1 infection in a Swedish cohort during the pandemic influenza season 2009. A very narrow pattern of pandemic flu-specific IgG epitope recognition was observed in the serum from individuals who later contracted H1N1 infection. Moreover, the pandemic influenza infection generated IgG reactivity to two adjacent epitopes of the neuraminidase protein. The differential serum IgG recognition was focused on haemagglutinin 1 (H1) and restricted to classical antigenic sites (Cb) in both the vaccinated controls and individuals with flu infections. We further identified a novel epitope VEPGDKITFEATGNL on the Ca antigenic site (251–265) of the pandemic flu haemagglutinin, which was exclusively recognized in serum from individuals with previous vaccinations and never in serum from individuals with H1N1 infection (confirmed by RNA PCR analysis from nasal swabs). This epitope was mapped to the receptor-binding domain of the influenza haemagglutinin and could serve as a correlate of immune protection in the context of pandemic flu. The study shows that unbiased epitope mapping using peptide microarray technology leads to the identification of biologically and clinically relevant target structures. Most significantly an H1N1 infection induced a different footprint of IgG epitope recognition patterns compared with the pandemic H1N1 vaccine.

The pre-analytical processing of blood samples for detecting biomarkers on protein microarrays

Specimen collection method and quality insurance are pivotal in biomarker discovery. Pre-analytical variables concerning blood collection and sample handling might affect analytical results and should be standardised prior application. In this study, we examine pre-analytical characteristics of blood samples using protein microarray. The influences of 1) standby times until centrifugation (1 h, 4 h, 24 h and 48 h), 2) four blood collection methods, and 3) IgG purified from those samples on differentially reactive antigens between samples ("DIRAGs") were investigated. Spearman correlation analyses of intra-individual arrays demonstrated remarkable differences (0.75-0.98 vs. 0.5-0.75) of antibody reactivities within and between serum and plasma samples. Class comparison showed that reactive antigen profiles were best preserved using IgG purified samples of serum tubes without separation gel as after 24h 83% of the 1h baseline DIRAGs were re-found. Testing dilution series with protein microarrays and Luminex xMap® Technology, we found linear correlations (R(2) = 0.94-0.99) between IgG concentration and read-out when using purified IgG instead of serum. Therefore, we highly recommend standardising pre-analytics and proposing the use of purified IgG for autoantibody immune-profiling with protein microarrays to reduce potential unspecific binding of matrix proteins abundant in serum and plasma samples.

SIGNIFICANCE

Although purified IgG cannot completely compensate the influence of pre-analytics, in highly parallel immune-profiling IgG enables reduction of unspecific effects, which occur when using serum or plasma for analysis on protein microarrays. Reproducibility problems due to pre-analytical processing of blood samples might explain discrepant results reported in various biomarker studies.

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.

Common features of mucosal and peripheral antibody responses elicited by candidate HIV-1 vaccines in rhesus monkeys

Human immunodeficiency virus type 1 (HIV-1) vaccines that elicit protective antibody responses at mucosal sites would be highly desirable. Here, we report that intramuscular immunization of candidate HIV-1 vaccine vectors and purified Env proteins elicited potent and durable humoral immune responses in colorectal mucosa in rhesus monkeys. The kinetics, isotypes, functionality, and epitope specificity of these mucosal antibody responses were similar to those of peripheral responses in serum. These data suggest a close immunological relationship between mucosal and systemic antibody responses following vaccination in primates.

Whole CMV proteome pattern recognition analysis after HSCT identifies unique epitope targets associated with the CMV status

Cytomegalovirus (CMV) infection represents a vital complication after Hematopoietic Stem Cell Transplantation (HSCT). We screened the entire CMV proteome to visualize the humoral target epitope-focus profile in serum after HSCT. IgG profiling from four patient groups (donor and/or recipient +/− for CMV) was performed at 6, 12 and 24 months after HSCT using microarray slides containing 17174 of 15mer-peptides overlapping by 4 aa covering 214 proteins from CMV. Data were analyzed using maSigPro, PAM and the ‘exclusive recognition analysis (ERA)’ to identify unique CMV epitope responses for each patient group. The ‘exclusive recognition analysis’ of serum epitope patterns segregated best 12 months after HSCT for the D+/R+ group (versus D−/R−). Epitopes were derived from UL123 (IE1), UL99 (pp28), UL32 (pp150), this changed at 24 months to 2 strongly recognized peptides provided from UL123 and UL100. Strongly (IgG) recognized CMV targets elicited also robust cytokine production in T-cells from patients after HSCT defined by intracellular cytokine staining (IL-2, TNF, IFN and IL-17). High-content peptide microarrays allow epitope profiling of entire viral proteomes; this approach can be useful to map relevant targets for diagnostics and therapy in patients with well defined clinical endpoints. Peptide microarray analysis visualizes the breadth of B-cell immune reconstitution after HSCT and provides a useful tool to gauge immune reconstitution.

Immunoinformatics: a brief review

A large volume of data relevant to immunology research has accumulated due to sequencing of genomes of the human and other model organisms. At the same time, huge amounts of clinical and epidemiologic data are being deposited in various scientific literature and clinical records. This accumulation of the information is like a goldmine for researchers looking for mechanisms of immune function and disease pathogenesis. Thus the need to handle this rapidly growing immunological resource has given rise to the field known as immunoinformatics. Immunoinformatics, otherwise known as computational immunology, is the interface between computer science and experimental immunology. It represents the use of computational methods and resources for the understanding of immunological information. It not only helps in dealing with huge amount of data but also plays a great role in defining new hypotheses related to immune responses. This chapter reviews classical immunology, different databases, and prediction tool. Further, it briefly describes applications of immunoinformatics in reverse vaccinology, immune system modeling, and cancer diagnosis and therapy. It also explores the idea of integrating immunoinformatics with systems biology for the development of personalized medicine. All these efforts save time and cost to a great extent.

Serotyping of Toxoplasma gondii in cats (Felis domesticus) reveals predominance of type II infections in Germany

Background

Cats are definitive hosts of Toxoplasma gondii and play an essential role in the epidemiology of this parasite. The study aims at clarifying whether cats are able to develop specific antibodies against different clonal types of T. gondii and to determine by serotyping the T. gondii clonal types prevailing in cats as intermediate hosts in Germany.

Methodology

To establish a peptide-microarray serotyping test, we identified 24 suitable peptides using serological T. gondii positive (n=21) and negative cat sera (n=52). To determine the clonal type-specific antibody response of cats in Germany, 86 field sera from T. gondii seropositive naturally infected cats were tested. In addition, we analyzed the antibody response in cats experimentally infected with non-canonical T. gondii types (n=7).

Findings

Positive cat reference sera reacted predominantly with peptides harbouring amino acid sequences specific for the clonal T. gondii type the cats were infected with. When the array was applied to field sera from Germany, 98.8% (85/86) of naturally-infected cats recognized similar peptide patterns as T. gondii type II reference sera and showed the strongest reaction intensities with clonal type II-specific peptides. In addition, naturally infected cats recognized type II-specific peptides significantly more frequently than peptides of other type-specificities. Cats infected with non-canonical types showed the strongest reactivity with peptides presenting amino-acid sequences specific for both, type I and type III.

Conclusions

Cats are able to mount a clonal type-specific antibody response against T. gondii. Serotyping revealed for most seropositive field sera patterns resembling those observed after clonal type II-T. gondii infection. This finding is in accord with our previous results on the occurrence of T. gondii clonal types in oocysts shed by cats in Germany.

A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling

We present an integrated analytical method for analyzing peptide microarray antibody binding data, from normalization through subject-specific positivity calls and data integration and visualization. Current techniques for the normalization of such data sets do not account for non-specific binding activity. A novel normalization technique based on peptide sequence information quickly and effectively reduced systematic biases. We also employed a sliding mean window technique that borrows strength from peptides sharing similar sequences, resulting in reduced signal variability. A smoothed signal aided in the detection of weak antibody binding hotspots. A new principled FDR method of setting positivity thresholds struck a balance between sensitivity and specificity. In addition, we demonstrate the utility and importance of using baseline control measurements when making subject-specific positivity calls. Data sets from two human clinical trials of candidate HIV-1 vaccines were used to validate the effectiveness of our overall computational framework.

A novel B-cell epitope identified within Mycobacterium tuberculosis CFP10/ESAT-6 protein

Background

The 10-kDa culture filtrate protein (CFP10) and 6-kDa early-secreted target antigen (ESAT-6) play important roles in mycobacterial virulence and pathogenesis through a 1∶1 complex formation (CFP10/ESAT-6 protein, CE protein), which have been used in discriminating TB patients from BCG-vaccinated individuals. The B-cell epitopes of CFP10 and ESAT-6 separately have been analyzed before, however, the epitopes of the CE protein are unclear and the precise epitope in the positions 40 to 62 of ESAT-6 is still unknown.

Methods

In the present study, we searched for the B-cell epitopes of CE protein by using phage-display library biopanning with the anti-CE polyclonal antibodies. The epitopes were identified by sequence alignment, binding affinity and specificity detection, generation of polyclonal mouse sera and detection of TB patient sera.

Results

One linear B-cell epitope (KWDAT) consistent with the 162^nd–166^th sequence of CE and the 57^th–61^st sequence of ESAT-6 protein was selected and identified. Significantly higher titers of E5 peptide-binding antibodies were found in the sera of TB patients compared with those of healthy individuals.

Conclusion

There was a B-cell epitope for CE and ESAT-6 protein in the position 40 to 62 of ESAT-6. E5 peptide may be useful in the serodiagnosis of tuberculosis, which need to be further confirmed by more sera samples.

Normalization and statistical analysis of multiplexed bead-based immunoassay data using mixed-effects modeling

Multiplexed bead-based flow cytometric immunoassays are a powerful experimental tool for investigating cellular communication networks, yet their widespread adoption is limited in part by challenges in robust quantitative analysis of the measurements. Here we report our application of mixed-effects modeling for the normalization and statistical analysis of bead-based immunoassay data. Our data set consisted of bead-based immunoassay measurements of 16 phospho-proteins in lysates of HepG2 cells treated with ligands that regulate acute-phase protein secretion. Mixed-effects modeling provided estimates for the effects of both the technical and biological sources of variance, and normalization was achieved by subtracting the technical effects from the measured values. This approach allowed us to detect ligand effects on signaling with greater precision and sensitivity and to more accurately characterize the HepG2 cell signaling network using constrained fuzzy logic. Mixed-effects modeling analysis of our data was vital for ascertaining that IL-1α and TGF-α treatment increased the activities of more pathways than IL-6 and TNF-α and that TGF-α and TNF-α increased p38 MAPK and c-Jun N-terminal kinase (JNK) phospho-protein levels in a synergistic manner. Moreover, we used mixed-effects modeling-based technical effect estimates to reveal the substantial variance contributed by batch effects along with the absence of loading order and assay plate position effects. We conclude that mixed-effects modeling enabled additional insights to be gained from our data than would otherwise be possible and we discuss how this methodology can play an important role in enhancing the value of experiments employing multiplexed bead-based immunoassays.

Validation processes of protein biomarkers in serum--a cross platform comparison

Due to insufficient biomarker validation and poor performances in diagnostic assays, the candidate biomarker verification process has to be improved. Multi-analyte immunoassays are the tool of choice for the identification and detailed validation of protein biomarkers in serum. The process of identification and validation of serum biomarkers, as well as their implementation in diagnostic routine requires an application of independent immunoassay platforms with the possibility of high-throughput. This review will focus on three main multi-analyte immunoassay platforms: planar microarrays, multiplex bead systems and, array-based surface plasmon resonance (SPR) chips. Recent developments of each platform will be discussed for application in clinical proteomics, principles, detection methods, and performance strength. The requirements for specific surface functionalization of assay platforms are continuously increasing. The reasons for this increase is the demand for highly sensitive assays, as well as the reduction of non-specific adsorption from complex samples, and with it high signal-to-noise-ratios. To achieve this, different support materials were adapted to the immobilized biomarker/ligand, allowing a high binding capacity and immobilization efficiency. In the case of immunoassays, the immobilized ligands are proteins, antibodies or peptides, which exhibit a diversity of chemical properties (acidic/alkaline; hydrophobic/hydrophilic; secondary or tertiary structure/linear). Consequently it is more challenging to develop immobilization strategies necessary to ensure a homogenous covered surface and reliable assay in comparison to DNA immobilization. New developments concerning material support for each platform are discussed especially with regard to increase the immobilization efficiency and reducing the non-specific adsorption from complex samples like serum and cell lysates.

Comparative study of classification algorithms for immunosignaturing data

BACKGROUND

High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data.

RESULTS

We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found 'Naïve Bayes' far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy.

CONCLUSIONS

'Naïve Bayes' algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties.

Peptide microarray analysis of in silico-predicted epitopes for serological diagnosis of Toxoplasma gondii infection in humans

Toxoplasma gondii infections occur worldwide in humans and animals. In immunocompromised or prenatally infected humans, T. gondii can cause severe clinical symptoms. The identification of specific epitopes on T. gondii antigens is essential for the improvement and standardization of the serological diagnosis of toxoplasmosis. We selected 20 peptides mimicking linear epitopes on GRA1, GRA2, GRA4, and MIC3 antigenic T. gondii proteins in silico using the software ABCpred. A further 18 peptides representing previously published epitopes derived from GRA1, SAG1, NTPase1, and NTPase2 antigens were added to the panel. A peptide microarray assay was established to prove the diagnostic performance of the selected peptides with human serum samples. Seropositive human serum samples (n = 184) were collected from patients presenting with acute toxoplasmosis (n = 21), latent T. gondii infection (n = 53), and inactive ocular toxoplasmosis (n = 10) and from seropositive forest workers (n = 100). To adjust the cutoff values for each peptide, sera from seronegative forest workers (n = 75) and patients (n = 65) were used. Univariate logistic regression suggested the significant diagnostic potential of eight novel and two previously published peptides. A test based on these peptides had an overall diagnostic sensitivity of 69% (100% in ocular toxoplasmosis patients, 86% in acutely infected patients, 81% in latently infected patients, and 57% in seropositive forest workers). The analysis of seronegative sera performed with these peptides revealed a diagnostic specificity of 84%. The results of our study suggest that the use of a bioinformatic approach for epitope prediction in combination with peptide microarray testing is a powerful method for the selection of T. gondii epitopes as candidate antigens for serological diagnosis.

Analysis of clonal type-specific antibody reactions in Toxoplasma gondii seropositive humans from Germany by peptide-microarray

Background

Different clonal types of Toxoplasma gondii are thought to be associated with distinct clinical manifestations of infections. Serotyping is a novel technique which may allow to determine the clonal type of T. gondii humans are infected with and to extend typing studies to larger populations which include infected but non-diseased individuals.

Methodology

A peptide-microarray test for T. gondii serotyping was established with 54 previously published synthetic peptides, which mimic clonal type-specific epitopes. The test was applied to human sera (n = 174) collected from individuals with an acute T. gondii infection (n = 21), a latent T. gondii infection (n = 53) and from T. gondii-seropositive forest workers (n = 100).

Findings

The majority (n = 124; 71%) of all T. gondii seropositive human sera showed reactions against synthetic peptides with sequences specific for clonal type II (type II peptides). Type I and type III peptides were recognized by 42% (n = 73) or 16% (n = 28) of the human sera, respectively, while type II–III, type I–III or type I–II peptides were recognized by 49% (n = 85), 36% (n = 62) or 14% (n = 25) of the sera, respectively. Highest reaction intensities were observed with synthetic peptides mimicking type II-specific epitopes. A proportion of the sera (n = 22; 13%) showed no reaction with type-specific peptides. Individuals with acute toxoplasmosis reacted with a statistically significantly higher number of peptides as compared to individuals with latent T. gondii infection or seropositive forest workers.

Conclusions

Type II-specific reactions were overrepresented and higher in intensity in the study population, which was in accord with genotyping studies on T. gondii oocysts previously conducted in the same area. There were also individuals with type I- or type III-specific reactions. Well-characterized reference sera and further specific peptide markers are needed to establish and to perform future serotyping approaches with higher resolution.

Peptide microarrays to interrogate the "histone code"

Histone posttranslational modifications (PTMs) play a pivotal role in regulating the dynamics and function of chromatin. Supported by an increasing body of literature, histone PTMs such as methylation and acetylation function together in the context of a "histone code," which is read, or interpreted, by effector proteins that then drive a functional output in chromatin (e.g., gene transcription). A growing number of domains that interact with histones and/or their PTMs have been identified. While significant advances have been made in our understanding of how these domains interact with histones, a wide number of putative histone-binding motifs have yet to be characterized, and undoubtedly, novel domains will continue to be discovered. In this chapter, we provide a detailed method for the construction of combinatorially modified histone peptides, microarray fabrication using these peptides, and methods to characterize the interaction of effector proteins, antibodies, and the substrate specificity of histone-modifying enzymes. We discuss these methods in the context of other available technologies and provide a user-friendly approach to enable the exploration of histone-protein-enzyme interactions and function.

rapmad: Robust analysis of peptide microarray data

BACKGROUND

Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel analysis of thousands of peptides in a single run they are suitable for high-throughput settings. Since data characteristics of peptide microarrays differ from DNA oligonucleotide microarrays, computational methods need to be tailored to these specifications to allow a robust and automated data analysis. While follow-up experiments can ensure the specificity of results, sensitivity cannot be recovered in later steps. Providing sensitivity is thus a primary goal of data analysis procedures. To this end we created rapmad (Robust Alignment of Peptide MicroArray Data), a novel computational tool implemented in R.

RESULTS

We evaluated rapmad in antibody reactivity experiments for several thousand peptide spots and compared it to two existing algorithms for the analysis of peptide microarrays. rapmad displays competitive and superior behavior to existing software solutions. Particularly, it shows substantially improved sensitivity for low intensity settings without sacrificing specificity. It thereby contributes to increasing the effectiveness of high throughput screening experiments.

CONCLUSIONS

rapmad allows the robust and sensitive, automated analysis of high-throughput peptide array data. The rapmad R-package as well as the data sets are available from http://www.tron-mz.de/compmed.

Mapping mouse IL-13 binding regions using structure modeling, molecular docking, and high-density peptide microarray analysis

Interleukin-13 is a Th2-associated cytokine responsible for many pathological responses in allergic asthma including mucus production, inflammation, and extracellular matrix remodeling. In addition, IL-13 is required for immunity to many helminth infections. IL-13 signals via the type-II IL-4 receptor, a heterodimeric receptor of IL-13Rα1 and IL-4Rα, which is also used by IL-4. IL-13 also binds to IL-13Rα2, but with much higher affinity than the type-II IL-4 receptor. Binding of IL-13 to IL-13Rα2 has been shown to attenuate IL-13 signaling through the type-II IL-4 receptor. However, molecular determinants that dictate the specificity and affinity of mouse IL-13 for the different receptors are largely unknown. Here, we used high-density overlapping peptide arrays, structural modeling, and molecular docking methods to map IL-13 binding sequences on its receptors. Predicted binding sequences on mouse IL-13Rα1 and IL-13Rα2 were in agreement with the reported human IL-13 receptor complex structures and site-directed mutational analysis. Novel structural differences were identified between IL-13 receptors, particularly at the IL-13 binding interface. Notably, additional binding sites were observed for IL-13 on IL-13Rα2. In addition, the identification of peptide sequences that are unique to IL-13Rα1 allowed us to generate a monoclonal antibody that selectively binds IL-13Rα1. Thus, high-density peptide arrays combined with molecular docking studies provide a novel, rapid, and reliable method to map cytokine-receptor interactions that may be used to generate signaling and decoy receptor-specific antagonists.

Immunoinformatics: an integrated scenario

Genome sequencing of humans and other organisms has led to the accumulation of huge amounts of data, which include immunologically relevant data. A large volume of clinical data has been deposited in several immunological databases and as a result immunoinformatics has emerged as an important field which acts as an intersection between experimental immunology and computational approaches. It not only helps in dealing with the huge amount of data but also plays a role in defining new hypotheses related to immune responses. This article reviews classical immunology, different databases and prediction tools. It also describes applications of immunoinformatics in designing in silico vaccination and immune system modelling. All these efforts save time and reduce cost.

High throughput T epitope mapping and vaccine development

Mapping of antigenic peptide sequences from proteins of relevant pathogens recognized by T helper (Th) and by cytolytic T lymphocytes (CTL) is crucial for vaccine development. In fact, mapping of T-cell epitopes provides useful information for the design of peptide-based vaccines and of peptide libraries to monitor specific cellular immunity in protected individuals, patients and vaccinees. Nevertheless, epitope mapping is a challenging task. In fact, large panels of overlapping peptides need to be tested with lymphocytes to identify the sequences that induce a T-cell response. Since numerous peptide panels from antigenic proteins are to be screened, lymphocytes available from human subjects are a limiting factor. To overcome this limitation, high throughput (HTP) approaches based on miniaturization and automation of T-cell assays are needed. Here we consider the most recent applications of the HTP approach to T epitope mapping. The alternative or complementary use of in silico prediction and experimental epitope definition is discussed in the context of the recent literature. The currently used methods are described with special reference to the possibility of applying the HTP concept to make epitope mapping an easier procedure in terms of time, workload, reagents, cells and overall cost.

Visualisation and pre-processing of peptide microarray data

The data files produced by digitising peptide microarray images contain detailed information on the location, feature, response parameters and quality of each spot on each array. In this chapter, we will describe how such peptide microarray data can be read into the R statistical package and pre-processed in preparation for subsequent comparative or predictive analysis. We illustrate how the information in the data can be visualised using images and graphical displays that highlight the main features, enabling the quality of the data to be assessed and invalid data points to be identified and excluded. The log-ratio of the foreground to background signal is used as a response index. Negative control responses serve as a reference against which "detectable" responses can be defined, and slides incubated with only buffer and secondary antibody help identify false-positive responses from peptides. For peptides that have a detectable response on at least one subarray, and no false-positive response, we use linear mixed models to remove artefacts due to the arrays and their architecture. The resulting normalized responses provide the input data for further analysis.

Qualitative and quantitative analysis of peptide microarray binding experiments using SVM-PEPARRAY

A main objective of analyzing peptide array-based binding experiments is to uncover the relationship between a peptide sequence and the binding outcome. Limited by the peptide array technologies available for applications, few attempts have been made to construct qualitative or quantitative models that depict the peptide sequence:binding strength relationships in peptide microarray-based binding studies. There has been a long history of similar modeling efforts based on low-throughput binding data in the areas of T-cell epitope screening and kinase substrate mapping, however. The keen needs in peptide array applications and the success of the modeling efforts in related fields have prompted us to develop SVM-PEPARRAY, a Web-based program capable of constructing qualitative and quantitative models based on peptide microarray binding datasets using support vector machine (SVM) modeling methods. We expect that such modeling analysis will allow researchers to quickly extract sequence-based biological information from improved peptide array binding results and provide more precise and accurate information about the biological systems investigated.

Exploring and profiling protein function with peptide arrays

Development of array technologies started in the late 1980s and was first extensively applied to DNA arrays especially in the genomic field. Today this technique has become a powerful tool for high-throughput approaches in biology and chemistry. Progresses were mainly driven by the human genome project and were associated with the development of several new technologies, which led to the onset of additional "omic" topics like proteomics, glycomics, antibodyomics or lipidomics. The main characteristics of the array technology are (i) spatially addressable immobilization of a huge number of different capture molecules; (ii) probing the array in a simultaneous and highly parallel manner with a biological sample; (iii) tendency towards miniaturization of the arrays; and (iv) software-supported read-out and data analysis. We review some general concepts about peptide arrays on planar supports and point out technical aspects concerning the generation of peptide microarrays. Finally, we discuss recent applications by describing relevant literature.

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.

Antibody-based protein multiplex platforms: technical and operational challenges

BACKGROUND

The measurement of multiple protein biomarkers may refine risk stratification in clinical settings. This concept has stimulated development of multiplexed immunoassay platforms that provide multiple, parallel protein measurements on the same specimen.

CONTENT

We provide an overview of antibody-based multiplexed immunoassay platforms and discuss technical and operational challenges. Multiplexed immunoassays use traditional immunoassay principles in which high-affinity capture ligands are immobilized in parallel arrays in either planar format or on microspheres in suspension. Development of multiplexed immunoassays requires rigorous validation of assay configuration and analytical performance to minimize assay imprecision and inaccuracy. Challenges associated with multiplex configuration include selection and immobilization of capture ligands, calibration, interference between antibodies and proteins and assay diluents, and compatibility of assay limits of quantification. We discuss potential solutions to these challenges. Criteria for assessing analytical multiplex assay performance include the range of linearity, analytical specificity, recovery, and comparison to a quality reference method. Quality control materials are not well developed for multiplexed protein immunoassays, and algorithms for interpreting multiplex quality control data are needed.

SUMMARY

Technical and operational challenges have hindered implementation of multiplexed assays in clinical settings. Formal procedures that guide multiplex assay configuration, analytical validation, and quality control are needed before broad application of multiplexed arrays can occur in the in vitro diagnostic market.