High-content Peptide Microarrays Research Articles

Linear epitopes of bony fish β-parvalbumins.

Fish β-parvalbumins are common targets of allergy-causing immunity. The nature of antibody responses to such allergens determines the biological outcome following exposure to fish. Specific epitopes on these allergens recognised by antibodies are incompletely characterised. High-content peptide microarrays offer a solution to the identification of linear epitopes recognised by antibodies. We characterized IgG and IgG4 recognition of linear epitopes of fish β-parvalbumins defined in the WHO/IUIS allergen database as such responses hold the potential to counter an allergic reaction to these allergens. Peripheral blood samples, collected over three years, of 15 atopic but not fish-allergic subjects were investigated using a microarray platform that carried every possible 16-mer peptide of known isoforms and isoallergens of these and other allergens. Interindividual differences in epitope recognition patterns were observed. In contrast, reactivity patterns in a given individual were by comparison more stable during the 3 years-course of the study. Nevertheless, evidence of the induction of novel specificities over time was identified across multiple regions of the allergens. Particularly reactive epitopes were identified in the D helix of Cyp c 1 and in the C-terminus of Gad c 1 and Gad m 1.02. Residues important for the recognition of certain linear epitopes were identified. Patterns of differential recognition of isoallergens were observed in some subjects. Altogether, comprehensive analysis of antibody recognition of linear epitopes of multiple allergens enables characterisation of the nature of the antibody responses targeting this important set of food allergens.

Abstract A16: Combinatorial drug testing using 3D microtumors derived from GBM PDX reveals cytotoxic synergisms in pharmacokinomics-informed pathway interactions

Abstract Introduction: Drug testing of Glioblastoma multiforme (GBM) has revealed that many promising preclinical therapies fail when translated to the clinic. Serious limitations in preclinical models (often monolayer, serum-treated immortalized cell models) likely contribute to this translational failure. Although patient-derived xenografts (PDX), in which patient tumors are serially passaged in immunocompromised mice, are potentially superior model systems of human disease, high throughput drug studies in GBM PDX tumors are not feasible due to time, cost and throughput. To overcome these challenges, we have developed a GBM PDX MicroTumor system in which GBM PDX cells are grown in a novel 3D extracellular matrix material (HuBiogel™, Vivo Biosciences Inc., Birmingham, AL). We hypothesized that this 3D MicroTumor system would better emulate in vivo PDX tumor growth while providing a high throughput assay system for drug combination studies that can be performed in a more rapid timeframe. Methods: Six GBM PDX tumor “xenolines” were selected from the UAB Brain Tumor Animal Model Core to represent the 4 known molecular subtypes of GBM: Classical (JX10, X1016, X1046); Proneural (XD456); Neural (JX10) and Mesenchymal (JX22P). Tumor cells were prepared as single cell suspensions from subcutaneously passaged tumors and embedded in HuBiogel™ beads to form MicroTumors using Neuro-basal media devoid of serum. Single and combinatorial drug cytotoxicity studies were performed using MTT mitochondrial viability assays and Calcein AM imaging. Small molecule inhibitors selected for drug testing were: 1) selumetinib-targeting MEK1/2; 2) crizotinib-targeting c-MET and ALK; 3) cediranib-targeting VEGFR, FLT-1, FLT-4, c-KIT, and PDGFR; and 4) WP1066-targeting JAK2/STAT3. Combinatorial interactions were determined by Chou-Talalay combination index (CI) calculation using Calcusyn software. Global kinase signaling (kinomic profiling) was assessed using paired total cell lysates of GBM-PDX from orthotopic tumors grown in athymic nu/nu mice and as 3D MicroTumors. Testing was performed on the PamStation12 high content peptide microarray platform within the UAB Kinome Core. Results: Following optimization of model system conditions, 4 drugs were tested at multiple concentrations to identify effective dose ranges. While crizotinib, cediranib and WP1066 demonstrated significant cytotoxicity in at least 1 of the GBM-PDX MicroTumors tested, selumetinib was ineffective in producing cytotoxicity as a monotherapy. However, in combinatorial drug testing, selumetinib was effective in promoting synergistic activity (CI<1.0) when combined with each of the other drugs in several of the GBM-PDX tested. Conversely, WP1066 demonstrated some antagonistic interactions with the other drugs in certain tumors. Overall, cediranib and crizotinib demonstrated the most consistent level of efficacy both as monotherapies and combinatorial therapies across the GBM-PDX MicroTumors. Kinomic profiles were compared between GBM-PDX MicroTumors and matched GBM-PDX tumor xenolines grown as orthotopic intracranial tumors to confirm kinase signaling fidelity between the model systems. Paired t-test of kinomic phosphopeptide probes revealed only 20 of 246 peptides significantly differed (FDR<0.05) between the model systems suggesting a high level of signaling preservation within the MicroTumors. Conclusions: The GBM-PDX 3D MicroTumor provides a relatively high throughput drug screening model system that displays similar kinase signaling pathway activation as compared to their in vivo intracranial counterpart. Specific synergistic drug combinations were identified through MicroTumor testing. Ongoing drug combination testing of intracranially implanted GBM-PDX will determine how robustly the MicroTumor system predicts in vivo efficacy. Citation Format: Christopher D. Willey, Ashley N. Gilbert, Rachael Shevin, Catherine P. Langford, Christine W. Duarte, Raj Singh, Joshua C. Anderson, G. Yancey Gillespie. Combinatorial drug testing using 3D microtumors derived from GBM PDX reveals cytotoxic synergisms in pharmacokinomics-informed pathway interactions. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr A16.

Autoantibodies to chromogranin A are potential diagnostic biomarkers for non-small cell lung cancer

Cancer-associated autoantibodies show promise as sensitive biomarkers for the early detection of cancer. To test the immunogenicity of chromogranin A (ChgA) as a B cell autoantigen and to assess the potential applications of ChgA autoantibodies as novel biomarkers for the diagnosis of non-small cell lung cancer (NSCLC), we developed a high-content peptide microarray using ChgA peptides. Autoantibody profiling was carried out using sera from 168 individuals with NSCLC and 97 healthy controls. We present evidence for the occurrence of autoantibodies to ChgA peptides in patient sera and identified five highly responsive peptides in the NSCLC group using significance analysis of microarray (SAM). Receiver operating characteristic analyses showed that ChgA autoantibodies are valuable in the predictive diagnosis of NSCLC, suggesting that serum autoantibodies to ChgA-derived peptides are promising novel markers of NSCLC. Moreover, the high-content peptide microarray antibody profiling reported in this work provides a powerful tool to visualize the overall B cell response to ChgA peptides and should enable the rapid development of in-depth research into ChgA.

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

BackgroundPertussis (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).MethodsSera 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.Results367/3,085 (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.ConclusionWe 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 materialThe online version of this article (doi:10.1186/s12865-015-0090-3) contains supplementary material, which is available to authorized users.

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.

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.

Markus Maeurer on the LifeGene project

This year will see the full-scale roll-out of the LifeGene study. Coordinated by the Karolinska Institutet (Stockholm, Sweden), the project looks set to be one of the largest health studies performed in the world, aiming to enroll 500,000 Swedes in order to determine the relationship between disease and environmental, lifestyle and hereditary factors. International experts from a broad spectrum of scientific fields will collaborate on this project, including Mark Maeurer, Chair of the infections working group in LifeGene (www.lifegene.se). Maeurer leads the additional study on influenza-like illnesses, which is currently being run within the LifeGene project. Maeurer studied medicine in Germany, Switzerland and the USA. He is board-certified in medical microbiology, has served as Assistant Professor of Surgery at the University of Pittsburgh Medical School (PA, USA) in the Department of Surgical Oncology and Immunotherapy, as Professor of Medical Microbiology at the University of Mainz, Germany, and is now Professor of Clinical Immunology at the Microbiology and Tumor Cell Biology Center at the Karolinska Institutet. Maeurer has conducted experiments with nonhuman primate models to study TB vaccine take, with the aim to profile markers of immune protection. His general interests are in the field of immune reconstitution and memory immune responses, with a particular focus on gauging protective T-cell responses and antibody immune signatures using high-content peptide microarrays. He has published more than 100 original articles, ten book chapters and serves as a reviewer for a number of international scientific journals.

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 PepStar™ peptide 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.

Pattern Recognition in Pulmonary Tuberculosis Defined by High Content Peptide Microarray Chip Analysis Representing 61 Proteins from M. tuberculosis

BackgroundSerum antibody-based target identification has been used to identify tumor-associated antigens (TAAs) for development of anti-cancer vaccines. A similar approach can be helpful to identify biologically relevant and clinically meaningful targets in M.tuberculosis (MTB) infection for diagnosis or TB vaccine development in clinically well defined populations.MethodWe constructed a high-content peptide microarray with 61 M.tuberculosis proteins as linear 15 aa peptide stretches with 12 aa overlaps resulting in 7446 individual peptide epitopes. Antibody profiling was carried with serum from 34 individuals with active pulmonary TB and 35 healthy individuals in order to obtain an unbiased view of the MTB epitope pattern recognition pattern. Quality data extraction was performed, data sets were analyzed for significant differences and patterns predictive of TB+/−.FindingsThree distinct patterns of IgG reactivity were identified: 89/7446 peptides were differentially recognized (in 34/34 TB+ patients and in 35/35 healthy individuals) and are highly predictive of the division into TB+ and TB−, other targets were exclusively recognized in all patients with TB (e.g. sigmaF) but not in any of the healthy individuals, and a third peptide set was recognized exclusively in healthy individuals (35/35) but no in TB+ patients. The segregation between TB+ and TB− does not cluster into specific recognition of distinct MTB proteins, but into specific peptide epitope ‘hotspots’ at different locations within the same protein. Antigen recognition pattern profiles in serum from TB+ patients from Armenia vs. patients recruited in Sweden showed that IgG-defined MTB epitopes are very similar in individuals with different genetic background.ConclusionsA uniform target MTB IgG-epitope recognition pattern exists in pulmonary tuberculosis. Unbiased, high-content peptide microarray chip-based testing of clinically well-defined populations allows to visualize biologically relevant targets useful for development of novel TB diagnostics and vaccines.