Peptide Antibody Reactivity to Homologous Regions in Glutamate Decarboxylase Isoforms and Coxsackievirus B4 P2C.

Two isoforms of the glutamate decarboxylase (GAD) enzyme exist, GAD65 and GAD67, which are associated with type 1 diabetes (T1D) and stiff-person syndrome (SPS), respectively. Interestingly, it has been reported that T1D patients seldom develop SPS, whereas patients with SPS occasionally develop T1D. In addition, coxsackievirus B4 (CVB4) has previously been proposed to be involved in the onset of T1D through molecular mimicry. On this basis, we aimed to examine antibody cross-reactivity between a specific region of GAD65 and GAD67, which has high sequence homology to the nonstructural P2C protein of CVB4 to determine potential correlations at antibody level. Monoclonal peptide antibodies generated in mice specific for a region with high similarity in all three proteins were screened for reactivity along with human sera in immunoassays. In total, six antibodies were generated. Two of the antibodies reacted to both GAD isoforms. However, none of the antibodies were cross-reactive to CVB, suggesting that antibody cross-reactivity between GAD65 and CVB, and GAD67 and CVB may not contribute to the onset of T1D and SPS, respectively.

HLA Class II Specificity Assessed by High-Density Peptide Microarray Interactions.

The ability to predict and/or identify MHC binding peptides is an essential component of T cell epitope discovery, something that ultimately should benefit the development of vaccines and immunotherapies. In particular, MHC class I prediction tools have matured to a point where accurate selection of optimal peptide epitopes is possible for virtually all MHC class I allotypes; in comparison, current MHC class II (MHC-II) predictors are less mature. Because MHC-II restricted CD4+ T cells control and orchestrated most immune responses, this shortcoming severely hampers the development of effective immunotherapies. The ability to generate large panels of peptides and subsequently large bodies of peptide-MHC-II interaction data are key to the solution of this problem, a solution that also will support the improvement of bioinformatics predictors, which critically relies on the availability of large amounts of accurate, diverse, and representative data. In this study, we have used rHLA-DRB1*01:01 and HLA-DRB1*03:01 molecules to interrogate high-density peptide arrays, in casu containing 70,000 random peptides in triplicates. We demonstrate that the binding data acquired contains systematic and interpretable information reflecting the specificity of the HLA-DR molecules investigated, suitable of training predictors able to predict T cell epitopes and peptides eluted from human EBV-transformed B cells. Collectively, with a cost per peptide reduced to a few cents, combined with the flexibility of rHLA technology, this poses an attractive strategy to generate vast bodies of MHC-II binding data at an unprecedented speed and for the benefit of generating peptide-MHC-II binding data as well as improving MHC-II prediction tools.

A novel approach to probe host-pathogen interactions of bovine digital dermatitis, a model of a complex polymicrobial infection.

BACKGROUND: Polymicrobial infections represent a great challenge for the clarification of disease etiology and the development of comprehensive diagnostic or therapeutic tools, particularly for fastidious and difficult-to-cultivate bacteria. Using bovine digital dermatitis (DD) as a disease model, we introduce a novel strategy to study the pathogenesis of complex infections. RESULTS: The strategy combines meta-transcriptomics with high-density peptide-microarray technology to screen for in vivo-expressed microbial genes and the host antibody response at the site of infection. Bacterial expression patterns supported the assumption that treponemes were the major DD pathogens but also indicated the active involvement of other phyla (primarily Bacteroidetes). Bacterial genes involved in chemotaxis, flagellar synthesis and protection against oxidative and acidic stress were among the major factors defining the disease. CONCLUSIONS: The extraordinary diversity observed in bacterial expression, antigens and host antibody responses between individual cows pointed toward microbial variability as a hallmark of DD. Persistence of infection and DD reinfection in the same individual is common; thus, high microbial diversity may undermine the host's capacity to mount an efficient immune response and maintain immunological memory towards DD. The common antigenic markers identified here using a high-density peptide microarray address this issue and may be useful for future preventive measures against DD.

Towards High-throughput Immunomics for Infectious Diseases: Use of Next-generation Peptide Microarrays for Rapid Discovery and Mapping of Antigenic Determinants.

Complete characterization of antibody specificities associated to natural infections is expected to provide a rich source of serologic biomarkers with potential applications in molecular diagnosis, follow-up of chemotherapeutic treatments, and prioritization of targets for vaccine development. Here, we developed a highly-multiplexed platform based on next-generation high-density peptide microarrays to map these specificities in Chagas Disease, an exemplar of a human infectious disease caused by the protozoan Trypanosoma cruzi. We designed a high-density peptide microarray containing more than 175,000 overlapping 15 mer peptides derived from T. cruzi proteins. Peptides were synthesized in situ on microarray slides, spanning the complete length of 457 parasite proteins with fully overlapped 15 mers (1 residue shift). Screening of these slides with antibodies purified from infected patients and healthy donors demonstrated both a high technical reproducibility as well as epitope mapping consistency when compared with earlier low-throughput technologies. Using a conservative signal threshold to classify positive (reactive) peptides we identified 2,031 disease-specific peptides and 97 novel parasite antigens, effectively doubling the number of known antigens and providing a 10-fold increase in the number of fine mapped antigenic determinants for this disease. Finally, further analysis of the chip data showed that optimizing the amount of sequence overlap of displayed peptides can increase the protein space covered in a single chip by at least ∼ threefold without sacrificing sensitivity. In conclusion, we show the power of high-density peptide chips for the discovery of pathogen-specific linear B-cell epitopes from clinical samples, thus setting the stage for high-throughput biomarker discovery screenings and proteome-wide studies of immune responses against pathogens.

Identification and mapping of linear antibody epitopes in human serum albumin using high-density Peptide arrays.

We have recently developed a high-density photolithographic, peptide array technology with a theoretical upper limit of 2 million different peptides per array of 2 cm(2). Here, we have used this to perform complete and exhaustive analyses of linear B cell epitopes of a medium sized protein target using human serum albumin (HSA) as an example. All possible overlapping 15-mers from HSA were synthesized and probed with a commercially available polyclonal rabbit anti-HSA antibody preparation. To allow for identification of even the weakest epitopes and at the same time perform a detailed characterization of key residues involved in antibody binding, the array also included complete single substitution scans (i.e. including each of the 20 common amino acids) at each position of each 15-mer peptide. As specificity controls, all possible 15-mer peptides from bovine serum albumin (BSA) and from rabbit serum albumin (RSA) were included as well. The resulting layout contained more than 200.000 peptide fields and could be synthesized in a single array on a microscope slide. More than 20 linear epitope candidates were identified and characterized at high resolution i.e. identifying which amino acids in which positions were needed, or not needed, for antibody interaction. As expected, moderate cross-reaction with some peptides in BSA was identified whereas no cross-reaction was observed with peptides from RSA. We conclude that high-density peptide microarrays are a very powerful methodology to identify and characterize linear antibody epitopes, and should advance detailed description of individual specificities at the single antibody level as well as serologic analysis at the proteome-wide level.

High-resolution mapping of linear antibody epitopes using ultrahigh-density peptide microarrays.

Antibodies empower numerous important scientific, clinical, diagnostic, and industrial applications. Ideally, the epitope(s) targeted by an antibody should be identified and characterized, thereby establishing antibody reactivity, highlighting possible cross-reactivities, and perhaps even warning against unwanted (e.g. autoimmune) reactivities. Antibodies target proteins as either conformational or linear epitopes. The latter are typically probed with peptides, but the cost of peptide screening programs tends to prohibit comprehensive specificity analysis. To perform high-throughput, high-resolution mapping of linear antibody epitopes, we have used ultrahigh-density peptide microarrays generating several hundred thousand different peptides per array. Using exhaustive length and substitution analysis, we have successfully examined the specificity of a panel of polyclonal antibodies raised against linear epitopes of the human proteome and obtained very detailed descriptions of the involved specificities. The epitopes identified ranged from 4 to 12 amino acids in size. In general, the antibodies were of exquisite specificity, frequently disallowing even single conservative substitutions. In several cases, multiple distinct epitopes could be identified for the same target protein, suggesting an efficient approach to the generation of paired antibodies. Two alternative epitope mapping approaches identified similar, although not necessarily identical, epitopes. These results show that ultrahigh-density peptide microarrays can be used for linear epitope mapping. With an upper theoretical limit of 2,000,000 individual peptides per array, these peptide microarrays may even be used for a systematic validation of antibodies at the proteomic level.

NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide data.

Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new "omics"-based approaches towards the analysis of complex biological processes. However, the amount and complexity of data that even a single experiment can produce seriously challenges researchers with limited bioinformatics expertise, who need to handle, analyze and interpret the data before it can be understood in a biological context. Thus, there is an unmet need for tools allowing non-bioinformatics users to interpret large data sets. We have recently developed a method, NNAlign, which is generally applicable to any biological problem where quantitative peptide data is available. This method efficiently identifies underlying sequence patterns by simultaneously aligning peptide sequences and identifying motifs associated with quantitative readouts. Here, we provide a web-based implementation of NNAlign allowing non-expert end-users to submit their data (optionally adjusting method parameters), and in return receive a trained method (including a visual representation of the identified motif) that subsequently can be used as prediction method and applied to unknown proteins/peptides. We have successfully applied this method to several different data sets including peptide microarray-derived sets containing more than 100,000 data points. NNAlign is available online at http://www.cbs.dtu.dk/services/NNAlign.

Binding of the receptor tyrosine kinase TrkB to the neural cell adhesion molecule (NCAM) regulates phosphorylation of NCAM and NCAM-dependent neurite outgrowth.

Recognition molecules and neurotrophins play important roles during development and maintenance of nervous system functions. In this study, we provide evidence that the neural cell adhesion molecule (NCAM) and the neurotrophin receptor TrkB directly interact via sequences in their intracellular domains. Stimulation of TrkB by brain-derived neurotrophic factor leads to tyrosine phosphorylation of NCAM at position 734. Mutation of this tyrosine to phenylalanine completely abolishes tyrosine phosphorylation of NCAM by TrkB. Moreover, the knockdown of TrkB in hippocampal neurons leads to a reduction of NCAM-induced neurite outgrowth. Transfection of NCAM-deficient hippocampal neurons with mutated NCAM carrying an exchange of tyrosine by phenylalanine at position 734 leads to promotion of NCAM-induced neurite outgrowth in comparison with that observed after transfection with wild-type NCAM, whereas a reduction of neurite outgrowth was observed after transfection with mutated NCAM, which carries an exchange of tyrosine by glutamate that mimics the phosphorylated tyrosine. Our observations indicate a functional relationship between TrkB and NCAM.

Functional consequences of the interactions among the neural cell adhesion molecule NCAM, the receptor tyrosine kinase TrkB, and the inwardly rectifying K+ channel KIR3.3.

Cell adhesion molecules and neurotrophin receptors are crucial for the development and the function of the nervous system. Among downstream effectors of neurotrophin receptors and recognition molecules are ion channels. Here, we provide evidence that G protein-coupled inwardly rectifying K(+) channel Kir3.3 directly binds to the neural cell adhesion molecule (NCAM) and neurotrophin receptor TrkB. We identified the binding sites for NCAM and TrkB at the C-terminal intracellular domain of Kir3.3. The interaction between NCAM, TrkB, and Kir3.3 was supported by immunocytochemical co-localization of Kir3.3, NCAM, and/or TrkB at the surface of hippocampal neurons. Co-expression of TrkB and Kir3.1/3.3 in Xenopus oocytes increased the K(+) currents evoked by Kir3.1/3.3 channels. This current enhancement was reduced by the concomitant co-expression with NCAM. Both surface fluorescence measurements of microinjected oocytes and cell surface biotinylation of transfected CHO cells indicated that the cell membrane localization of Kir3.3 is regulated by TrkB and NCAM. Furthermore, the level of Kir3.3, but not of Kir3.2, at the plasma membranes was reduced in TrkB-deficient mice, supporting the notion that TrkB regulates the cell surface expression of Kir3.3. The premature expression of developmentally late appearing Kir3.1/3.3 in hippocampal neurons led to a reduction of NCAM-induced neurite outgrowth. Our observations indicate a decisive role for the neuronal K(+) channel in regulating NCAM-dependent neurite outgrowth and attribute a physiologically meaningful role to the functional interplay of Kir3.3, NCAM, and TrkB in ontogeny.

The outermost N-terminal region of tapasin facilitates folding of major histocompatibility complex class I.

Tapasin (Tpn) is an ER chaperone that is uniquely dedicated to MHC-I biosynthesis. It binds MHC-I molecules, integrates them into peptide-loading complexes, and exerts quality control of the bound peptides; only when an "optimal peptide" is bound will the MHC-I be released and exported to the cell surface for presentation to T cells. The exact mechanisms of Tpn quality control and the criteria for being an optimal peptide are still unknown. Here, we have generated a recombinant fragment of human Tpn, Tpn(1-87) (representing the 87 N-terminal and ER-luminal amino acids of the mature Tpn protein). Using a biochemical peptide-MHC-I-binding assay, recombinant Tpn(1-87) was found to specifically facilitate peptide-dependent folding of HLA-A*0201. Furthermore, we used Tpn(1-87) to generate a monoclonal antibody, alphaTpn(1-87)/80, specific for natural human Tpn and capable of cellular staining of ER localized Tpn. Using overlapping peptides, the epitope of alphaTpn(1-87)/80 was located to Tpn(40-44), which maps to a surface-exposed loop on the Tpn structure. Together, these results demonstrate that the N-terminal region of Tpn can be recombinantly expressed and adopt a structure, which at least partially resembles that of WT Tpn, and that this region of Tpn features chaperone activity facilitating peptide binding of MHC-I.

Recombinant chymosin used for exact and complete removal of a prochymosin derived fusion tag releasing intact native target protein.

Fusion tags add desirable properties to recombinant proteins, but they are not necessarily acceptable in the final products. Ideally, fusion tags should be removed releasing the intact native protein with no trace of the tag. Unique endoproteinases with the ability to cleave outside their own recognition sequence can potentially cleave at the boundary of any native protein. Chymosin was recently shown to cleave a pro-chymosin derived fusion tag releasing native target proteins. In our hands, however, not all proteins are chymosin-resistant under the acidic cleavage conditions (pH 4.5) used in this system. Here, we have modified the pro-chymosin fusion tag and demonstrated that chymosin can remove this tag at more neutral pH (pH 6.2); conditions, that are less prone to compromise the integrity of target proteins. Chymosin was successfully used to produce intact native target protein both at the level of small and large-scale preparations. Using short peptide substrates, we further examined the influence of P1' amino acid (the N-terminus of the native target protein) and found that chymosin accepts many different, although not all, amino acids. We conclude that chymosin has several appealing characteristics for the exact removal of fusion tags. It is readily available in highly purified recombinant versions approved by the FDA for preparation of food for human consumption. We suggest that one should consider extending the use of chymosin to the preparation of pharmaceutical proteins.

The peptide-binding specificity of HLA-A*3001 demonstrates membership of the HLA-A3 supertype.

Human leukocyte antigen class I (HLA-I) molecules are highly polymorphic peptide receptors, which select and present endogenously derived peptide epitopes to CD8+ cytotoxic T cells (CTL). The specificity of the HLA-I system is an important component of the overall specificity of the CTL immune system. Unfortunately, the large and rapidly increasing number of known HLA-I molecules seriously complicates a comprehensive analysis of the specificities of the entire HLA-I system (as of June 2008, the international HLA registry holds >1,650 unique HLA-I protein entries). In an attempt to reduce this complexity, it has been suggested to cluster the different HLA-I molecules into "supertypes" of largely overlapping peptide-binding specificities. Obviously, the HLA supertype concept is only valuable if membership can be assigned with reasonable accuracy. The supertype assignment of HLA-A*3001, a common HLA haplotype in populations of African descent, has variously been assigned to the A1, A3, or A24 supertypes. Using a biochemical HLA-A*3001 binding assay, and a large panel of nonamer peptides and peptide libraries, we here demonstrate that the specificity of HLA-A*3001 most closely resembles that of the HLA-A3 supertype. We discuss approaches to supertype assignment and underscore the importance of experimental verification.