Structural basis for VLDLR recognition by eastern equine encephalitis virus

Alphaviruses are arthropod-borne enveloped RNA viruses that include several important human pathogens with outbreak potential. Among them, eastern equine encephalitis virus (EEEV) is the most virulent, and many survivors develop neurological sequelae, including paralysis and intellectual disability. The spike proteins of alphaviruses comprise trimers of heterodimers of their envelope glycoproteins E2 and E1 that mediate binding to cellular receptors and fusion of virus and host cell membranes during entry. We recently identified very-low density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2), two closely related proteins that are expressed in the brain, as cellular receptors for EEEV and a distantly related alphavirus, Semliki forest virus (SFV) 1 . The EEEV and SFV spike glycoproteins have low sequence homology, and how they have evolved to bind the same cellular receptors is unknown. Here, we used single-particle cryo-electron microscopy (cryo-EM) to determine structures of the EEEV and SFV spike glycoproteins bound to the VLDLR ligand-binding domain. The structures reveal that EEEV and SFV use distinct surfaces to bind VLDLR; EEEV uses a cluster of basic residues on the E2 subunit of its spike glycoprotein, while SFV uses two basic residues at a remote site on its E1 glycoprotein. Our studies reveal that different alphaviruses interact with the same cellular receptor through divergent binding modes. They further suggest that the ability of LDLR-related proteins to interact with viral spike proteins through very small footprints with flexible binding modes results in a low evolutionary barrier to the acquisition of LDLR-related proteins as cellular receptors for diverse sets of viruses.

Structural basis for continued antibody evasion by the SARS-CoV-2 receptor binding domain

Many studies have examined the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants on neutralizing antibody activity after they have become dominant strains. Here, we evaluate the consequences of further viral evolution. We demonstrate mechanisms through which the SARS-CoV-2 receptor binding domain (RBD) can tolerate large numbers of simultaneous antibody escape mutations and show that pseudotypes containing up to seven mutations, as opposed to the one to three found in previously studied variants of concern, are more resistant to neutralization by therapeutic antibodies and serum from vaccine recipients. We identify an antibody that binds the RBD core to neutralize pseudotypes for all tested variants but show that the RBD can acquire an N-linked glycan to escape neutralization. Our findings portend continued emergence of escape variants as SARS-CoV-2 adapts to humans.

VLDLR and ApoER2 are receptors for multiple alphaviruses

Alphaviruses, like many other arthropod-borne viruses, infect vertebrate species and insect vectors separated by hundreds of millions of years of evolutionary history. Entry into evolutionarily divergent host cells can be accomplished by recognition of different cellular receptors in different species, or by binding to receptors that are highly conserved across species. Although multiple alphavirus receptors have been described^1–3, most are not shared among vertebrate and invertebrate hosts. Here we identify the very low-density lipoprotein receptor (VLDLR) as a receptor for the prototypic alphavirus Semliki forest virus. We show that the E2 and E1 glycoproteins (E2–E1) of Semliki forest virus, eastern equine encephalitis virus and Sindbis virus interact with the ligand-binding domains (LBDs) of VLDLR and apolipoprotein E receptor 2 (ApoER2), two closely related receptors. Ectopic expression of either protein facilitates cellular attachment, and internalization of virus-like particles, a VLDLR LBD–Fc fusion protein or a ligand-binding antagonist block Semliki forest virus E2–E1-mediated infection of human and mouse neurons in culture. The administration of a VLDLR LBD–Fc fusion protein has protective activity against rapidly fatal Semliki forest virus infection in mouse neonates. We further show that invertebrate receptor orthologues from mosquitoes and worms can serve as functional alphavirus receptors. We propose that the ability of some alphaviruses to infect a wide range of hosts is a result of their engagement of evolutionarily conserved lipoprotein receptors and contributes to their pathogenesis.

Studies using viral coat glycoproteins show that alphaviruses can enter cells via the very low-density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2), members of an evolutionarily conserved family of lipoprotein receptors.

Vesicular Stomatitis Virus Transcription Is Inhibited by TRIM69 in the Interferon-Induced Antiviral State

Interferons (IFNs) induce the expression of interferon-stimulated genes (ISGs), many of which are responsible for the cellular antiviral state in which the replication of numerous viruses is blocked. How the majority of individual ISGs inhibit the replication of particular viruses is unknown. We conducted a loss-of-function screen to identify genes required for the activity of alpha interferon (IFN-α) against vesicular stomatitis virus, Indiana serotype (VSVIND), a prototype negative-strand RNA virus. Our screen revealed that TRIM69, a member of the tripartite motif (TRIM) family of proteins, is a VSVIND inhibitor. TRIM69 potently inhibited VSVIND replication through a previously undescribed transcriptional inhibition mechanism. Specifically, TRIM69 physically associates with the VSVIND phosphoprotein (P), requiring a specific peptide target sequence encoded therein. P is a cofactor for the viral polymerase and is required for viral RNA synthesis, as well as the assembly of replication compartments. By targeting P, TRIM69 inhibits pioneer transcription of the incoming virion-associated minus-strand RNA, thereby preventing the synthesis of viral mRNAs, and consequently impedes all downstream events in the VSVIND replication cycle. Unlike some TRIM proteins, TRIM69 does not inhibit viral replication by inducing degradation of target viral proteins. Rather, higher-order TRIM69 multimerization is required for its antiviral activity, suggesting that TRIM69 functions by sequestration or anatomical disruption of the viral machinery required for VSVIND RNA synthesis.IMPORTANCE Interferons are important antiviral cytokines that work by inducing hundreds of host genes whose products inhibit the replication of many viruses. While the antiviral activity of interferon has long been known, the identities and mechanisms of action of most interferon-induced antiviral proteins remain to be discovered. We identified gene products that are important for the antiviral activity of interferon against vesicular stomatitis virus (VSV), a model virus that whose genome consists of a single RNA molecule with negative-sense polarity. We found that a particular antiviral protein, TRIM69, functions by a previously undescribed molecular mechanism. Specifically, TRIM69 interacts with and inhibits the function of a particular phosphoprotein (P) component of the viral transcription machinery, preventing the synthesis of viral messenger RNAs.

PO and ID BCG vaccination in humans induce distinct mucosal and systemic immune responses and CD4+ T cell transcriptomal molecular signatures

Protective efficacy of Bacillus Calmette-Guérin (BCG) may be affected by the methods and routes of vaccine administration. We have studied the safety and immunogenicity of oral (PO) and/or intradermal (ID) administration of BCG in healthy human subjects. No major safety concerns were detected in the 68 healthy adults vaccinated with PO and/or ID BCG. Although both PO and ID BCG could induce systemic Th1 responses capable of IFN-γ production, ID BCG more strongly induced systemic Th1 responses. In contrast, stronger mucosal responses (TB-specific secretory IgA and bronchoalveolar lavage T cells) were induced by PO BCG vaccination. To generate preliminary data comparing the early gene signatures induced by mucosal and systemic BCG vaccination, CD4⁺ memory T cells were isolated from subsets of BCG vaccinated subjects pre- (Day 0) and post-vaccination (Days 7 and 56), rested or stimulated with BCG infected dendritic cells, and then studied by Illumina BeadArray transcriptomal analysis. Notably, distinct gene expression profiles were identified both on Day 7 and Day 56 comparing the PO and ID BCG vaccinated groups by GSEA analysis. Future correlation analyses between specific gene expression patterns and distinct mucosal and systemic immune responses induced will be highly informative for TB vaccine development.

Repeatable Population Dynamics among Vesicular Stomatitis Virus Lineages Evolved under High Co-infection

Parasites and hosts can experience oscillatory cycles, where the densities of these interacting species dynamically fluctuate through time. Viruses with different replication strategies can also interact to produce cyclical dynamics. Frequent cellular co-infection can select for defective-interfering particles (DIPs): “cheater” viruses with shortened genomes that interfere with intracellular replication of full-length (ordinary) viruses. DIPs are positively selected when rare because they out-replicate ordinary viruses during co-infection, but DIPs are negatively selected when common because ordinary viruses become unavailable for intracellular exploitation via cheating. Here, we tested whether oscillatory dynamics of ordinary viruses were similar across independently evolved populations of vesicular stomatitis virus (VSV). Results showed identical cyclical dynamics across populations in the first 10 experimental passages, which transitioned to repeatable dampened oscillations by passage 20. Genomic analyses revealed parallel molecular substitutions across populations, particularly novel mutations that became dominant by passage 10. Our study showed that oscillatory dynamics and molecular evolution of interacting viruses were highly repeatable in VSV populations passaged under frequent co-infection. Furthermore, our data suggested that frequent co-infection with DIPs caused lowered performance of full-length viruses, by reducing their population densities by orders of magnitude compared to reproduction of ordinary viruses during strictly clonal infections.

Effects on Metal/Metal-Oxide Interface Adhesion Due to Electron and Ion Irradiation

The influence of electron and ion irradiation on the adhesion at chromium-copper thin film interfaces has been studied. The measurements were carried out with different types and thicknesses of well-characterized oxides at the interfaces. The electron energies were varied between 5 and 10 keV, with doses up to 1018cm−2. lons of He+Ne+and P+were used in the range of energies between 150 keVand 1.0 MeV, with fluences ranging from 1015cm−2to 6× 1016cm−2. Substantial improvement of the adhesion is observed in cases where the beam has a significant nuclear stopping power component. Electronic processes may also play a role in improving adhesion, although they are not dominant in the case of the present films.

Prediction of class I T-cell epitopes: evidence of presence of immunological hot spots inside antigens

Motivation: Processing and presentation of major histocompatibility complex class I antigens to cytotoxic T-lymphocytes is crucial for immune surveillance against intracellular bacteria, parasites, viruses and tumors. Identification of antigenic regions on pathogen proteins will play a pivotal role in designer vaccine immunotherapy. We have developed a system that not only identifies high binding T-cell antigenic epitopes, but also class I T-cell antigenic clusters termed immunological hot spots.

Methods: MULTIPRED, a computational system for promiscuous prediction of HLA class I binders, uses artificial neural networks (ANN) and hidden Markov models (HMM) as predictive engines. The models were rigorously trained, tested and validated using experimentally identified HLA class I T-cell epitopes from human melanoma related proteins and human papillomavirus proteins E6 and E7. We have developed a scoring scheme for identification of immunological hot spots for HLA class I molecules, which is the sum of the highest four predictions within a window of 30 amino acids.

Results: Our predictions against experimental data from four melanoma-related proteins showed that MULTIPRED ANN and HMM models could predict T-cell epitopes with high accuracy. The analysis of proteins E6 and E7 showed that ANN models appear to be more accurate for prediction of HLA-A3 hot spots and HMM models for HLA-A2 predictions. For illustration of its utility we applied MULTIPRED for prediction of promiscuous T-cell epitopes in all four SARS coronavirus structural proteins. MULTIPRED predicted HLA-A2 and HLA-A3 hot spots in each of these proteins.

Long-term T cell memory to human leucocyte antigen-A2 supertype epitopes in humans vaccinated against smallpox

Identification of human leucocyte antigen (HLA) class I-restricted T cell epitopes is important to develop methods to track the evolution of T cell memory to new generation smallpox vaccines and allow comparison to older vaccinia virus preparations known to induce protection against smallpox. We evaluated the relative predictive values of four computational algorithms to identify candidate 9-mer HLA-A2 supertype epitopes that were confirmed to stimulate preferentially T cell interferon (IFN)-gamma responses by subjects last vaccinated with Dryvax 27-54 years previously. Six peptides encoded by I4L, G1L, A8R, I8R, D12L and H3L open reading frames that were identical for Vaccinia (Copenhagen), Variola major (Bangledesh 1975) and modified vaccinia Ankara strain preferentially stimulated IFN-gamma responses by healthy HLA-A2 supertype adults last given Dryvax 27-49 years earlier relative to remotely vaccinated non-HLA-A2 supertype and unvaccinated HLA-A2 supertype adults. Combining results from at least two computational algorithms that use different strategies to predict peptide binding to HLA-A2 supertype molecules was optimal for selection of candidate peptides that were confirmed to be epitopes by recall of T cell IFN-gamma responses. These data will facilitate evaluation of the immunogenicity of replication incompetent smallpox vaccines such as modified vaccinia Ankara and contribute to knowledge of poxvirus epitopes that are associated with long-lived T cell memory.

The transcriptional landscape of the mammalian genome

This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.

Elevation of gamma-glutamyltransferase activity in 293 HEK cells constitutively expressing antisense glutaminase mRNA

Previous studies have shown that the use of dynamic nutrient feeding to maintain glutamine at low levels in fed-batch cultures reduced the overflow of glutamine metabolism. This strategy resulted in the shift of metabolism towards an energetically more efficient state signified by reduced lactate and ammonia production and thus achieving a higher cell density for enhanced productivity. In an effort to mimic the metabolic changes effected by this fed-batch strategy at the molecular level, 293 HEK cells were engineered via stable transfection with an antisense fragment of the rat phosphate-dependent glutaminase (PDG) gene. PDG is localized in the mitochondria and catalyzes the deamination of glutamine to glutamate with the release of ammonia. Stable single cell clones were isolated from the transfected populations. Characterization of these transfectants revealed indications of an altered glutamine metabolism affected by the antisense strategy. Contrary to our expectations, glutamine consumption and ammonia production in the antisense cells did not deviate significantly from that of untransfected cells. Glutamate was also observed to accumulate to high level extracellularly, as opposed to a consumption pattern normally observed in non-transfected cells. Subsequent analyses show that gamma-glutamyltransferase (gamma-GT) may be a significant pathway that resulted in the formation of glutamate and ammonia from glutamine catabolism extracellularly. gamma-GT has been widely investigated in renal glutamine metabolism, but has rarely been implicated in cultured cell metabolism. This study highlights the importance of this alternative glutamine metabolism pathway in cell culture.

ANTIMIC: a database of antimicrobial sequences

Antimicrobial peptides (AMPs) are important components of the innate immune system of many species. These peptides are found in eukaryotes, including mammals, amphibians, insects and plants, as well as in prokaryotes. Other than having pathogen-lytic properties, these peptides have other activities like antitumor activity, mitogen activity, or they may act as signaling molecules. Their short length, fast and efficient action against microbes and low toxicity to mammals have made them potential candidates as peptide drugs. In many cases they are effective against pathogens that are resistant to conventional antibiotics. They can serve as natural templates for the design of novel antimicrobial drugs. Although there are vast amounts of data on natural AMPs, they are not available through one central resource. We have developed a comprehensive database (ANTIMIC, http://research.i2r. a-star.edu.sg/Templar/DB/ANTIMIC/) of known and putative AMPs, which contains approximately 1700 of these peptides. The database is integrated with tools to facilitate efficient extraction of data and their analysis at molecular level, as well as search for new AMPs. These tools include BLAST, PDB structure viewer and the Antimic profile module.

Computational tools for the study of allergens

Allergy is a major cause of morbidity worldwide. The number of characterized allergens and related information is increasing rapidly creating demands for advanced information storage, retrieval and analysis. Bioinformatics provides useful tools for analysing allergens and these are complementary to traditional laboratory techniques for the study of allergens. Specific applications include structural analysis of allergens, identification of B- and T-cell epitopes, assessment of allergenicity and cross-reactivity, and genome analysis. In this paper, the most important bioinformatic tools and methods with relevance to the study of allergy have been reviewed.

Allergen databases

Allergies represent a significant medical and industrial problem. Molecular and clinical data on allergens are growing exponentially and in this article we have reviewed nine specialized allergen databases and identified data sources related to protein allergens contained in general purpose molecular databases. An analysis of allergens contained in public databases indicates a high level of redundancy of entries and a relatively low coverage of allergens by individual databases. From this analysis we identify current database needs for allergy research and, in particular, highlight the need for a centralized reference allergen database.

Molecular evolution and phylogeny of elapid snake venom three-finger toxins

Animal venom components are of considerable interest to researchers across a wide variety of disciplines, including molecular biology, biochemistry, medicine, and evolutionary genetics. The three-finger family of snake venom peptides is a particularly interesting and biochemically complex group of venom peptides, because they are encoded by a large multigene family and display a diverse array of functional activities. In addition, understanding how this complex and highly varied multigene family evolved is an interesting question to researchers investigating the biochemical diversity of these peptides and their impact on human health. Therefore, the purpose of our study was to investigate the long-term evolutionary patterns exhibited by these snake venom toxins to understand the mechanisms by which they diversified into a large, biochemically diverse, multigene family. Our results show a much greater diversity of family members than was previously known, including a number of subfamilies that did not fall within any previously identified groups with characterized activities. In addition, we found that the long-term evolutionary processes that gave rise to the diversity of three-finger toxins are consistent with the birth-and-death model of multigene family evolution. It is anticipated that this "three-finger toxin toolkit" will prove to be useful in providing a clearer picture of the diversity of investigational ligands or potential therapeutics available within this important family.

Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs

Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.

Efficient discovery of immune response targets by cyclical refinement of QSAR models of peptide binding

Peptides that induce and recall T-cell responses are called T-cell epitopes. T-cell epitopes may be useful in a subunit vaccine against malaria. Computer models that simulate peptide binding to MHC are useful for selecting candidate T-cell epitopes since they minimize the number of experiments required for their identification. We applied a combination of computational and immunological strategies to select candidate T-cell epitopes. A total of 86 experimental binding assays were performed in three rounds of identification of HLA-A11 binding peptides from the six preerythrocytic malaria antigens. Thirty-six peptides were experimentally confirmed as binders. We show that the cyclical refinement of the ANN models results in a significant improvement of the efficiency of identifying potential T-cell epitopes.

SCORPION, a molecular database of scorpion toxins

Increasing interest in the studies of toxins and the requirements for better structural and functional annotations have created a need for improved data management in the field of toxins. The molecular database, SCORPION, contains more than 200 entries of fully referenced scorpion toxin data including primary sequences, three-dimensional structures, structural and functional annotations of scorpion toxins along with relevant literature references. SCORPION has a set of search tools that allow users to extract data and perform specific queries. These entries have been compiled from public databases and literature, cleaned of errors and enriched with additional structural and functional information. The grouping of scorpion toxins provides a basis for extending and clarifying the existing structural and functional classifications. The bioinformatics modules in SCORPION facilitate analyses aimed at classification of scorpion toxins and identification of sequence patterns associated with specific structural or functional properties of scorpion toxins. The SCORPION database is accessible via the Internet at sdmc.krdl.org.sg:8080/scorpion.

gp100/pmel17 and tyrosinase encode multiple epitopes recognized by Th1-type CD4+T cells

CD4+ T cells modulate the magnitude and durability of CTL responses in vivo, and may serve as effector cells in the tumour microenvironment. In order to identify the tumour epitopes recognized by tumour-reactive human CD4+ T cells, we combined the use of an HLA-DR4/peptide binding algorithm with an IFN-gamma ELISPOT assay. Two known and three novel CD4+ T cell epitopes derived from the gp 100/pmel17 and tyrosinase melanocyte-associated antigens were confirmed or identified. Of major interest, we determined that freshly-isolated PBMC frequencies of Th1-type CD4+ T recognizing these peptides are frequently elevated in HLA-DR4+ melanoma patients (but not normal donors) that are currently disease-free as a result of therapeutic intervention. Epitope-specific CD4+ T cells from normal DR4+ donors could be induced, however, after in vitro stimulation with autologous dendritic cell pulsed with antigens (peptides or antigen-positive melanoma lysates) or infected with recombinant vaccinia virus encoding the relevant antigen. Peptide-reactive CD4+ T cells also recognized HLA-DR4+ melanoma cell lines that constitutively express the relevant antigen. Based on these data, these epitopes may serve as potent vaccine components to promote clinically-relevant Th1-type CD4+ T cell effector function in situ.

Characterization of a novel H2A(-)E+ transgenic model susceptible to heterologous but not self thyroglobulin in autoimmune thyroiditis: thyroiditis transfer with Vbeta8+ T cells

Recently we reported on a novel H2E transgenic, IA-negative model of experimental autoimmune thyroiditis (EAT) that excludes reactivity to self in its susceptibility pattern to heterologous thyroglobulin (Tg). In conventional, susceptible mouse strains, EAT is inducible with both homologous and heterologous Tg; e.g., human (h)Tg shares conserved thyroiditogenic epitopes with mouse (m)Tg. However, when an H2Ea(k) transgene is introduced into class II-negative B10.Ab(0) mice, which express neither surface IA (mutant Abeta-chain) nor surface IE (nonfunctional Ea gene), the resultant H2E(b) molecules are permissive for EAT induction by hTg, but not self mTg. Also, the hTg-primed cells do not cross-react with mTg. To explore this unique capacity of E+B10.Ab(0) mice to distinguish self from nonself Tg, we have developed T cell lines to examine the T cell receptor repertoire and observed a consistent Vbeta8+ component after repeated hTg stimulation. Enrichment and activation of Vbeta8+ T cells by either superantigen staphylococcal entertoxin B or anti-Vbeta8 in vitro enabled thyroiditis transfer to untreated A-E+ recipients, similar to hTg activation. Vbeta8+ T cells isolated by FACS from hTg-immunized mice also proliferated to hTg in vitro. These studies support the contribution of Vbeta8 genes to the pathogenicity of hTg in this H2A-E+ transgenic model.

A neural network model approach to the study of human TAP transporter

We used an artificial neural network (ANN) computer model to study peptide binding to the human transporter associated with antigen processing (TAP). After validation, an ANN model of TAP-peptide binding was used to mine a database of HLA-binding peptides to elucidate patterns of TAP binding. The affinity of HLA-binding peptides for TAP was found to differ according to the HLA supertype concerned: HLA-B27, -A3 or -A24 binding peptides had high, whereas HLA-A2, -B7 or -B8 binding peptides had low affinity for TAP. These results support the idea that TAP and particular HLA molecules may have co-evolved for efficient peptide processing and presentation. The strong similarity between the sets of peptides bound by TAP or HLA-B27 suggests functional co-evolution whereas the lack of a relationship between the sets of peptides bound by TAP or HLA-A2 is against these particular molecules having co-evolved. In support of these conclusions, the affinities of HLA-A2 and HLA-B7 binding peptides for TAP show similar distributions to that of randomly generated peptides. On the basis of these results we propose that HLA alleles constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3 and -A24) and those that are TAP-inefficient (HLA-A2, -B7 and -B8). Computer modelling can be used to complement laboratory experiments and thereby speed up knowledge discovery in biology. In particular, we provide evidence that large-scale experiments can be avoided by combining initial experimental data with limited laboratory experiments sufficient to develop and validate appropriate computer models. These models can then be used to perform large-scale simulated experiments the results of which can then be validated by further small-scale laboratory experiments.

NY-ESO-1 encodes DRB1*0401-restricted epitopes recognized by melanoma-reactive CD4+ T cells

The NY-ESO-1 gene is expressed by a range of human tumors and encodes HLA-A2-restricted melanoma peptides recognized by CD8+ CTLs. Here we report that the NY-ESO-1 gene also encodes two overlapping, but non-cross-reactive, HLA-DRB1*0401-presented peptides that are recognized by CD4+ T cells. The NY-ESO-1(119-143) peptide was able to induce specific CD4+ T cells in vitro from both an HLA-DRB1*0401+ normal donor and an HLA-DRB1*0401+ patient with melanoma. Bulk and cloned CD4+ T cells produced IFN-gamma specifically in response to, and also lysed, T2.DR4 cells pulsed with peptide NY-ESO-1(119-143) and the autologous tumor cell line, but not a DRB1*0401+ melanoma cell line that does not express NY-ESO-1. Interestingly, the NY-ESO119-143 peptide contains two overlapping putative "core" epitopes recognized by non-cross-reactive anti-NY-ESO-1(119-143) CD4+ T-cell clones. Taken together, these data support the use of this novel DR4-restricted tumor peptide, NY-ESO-1(119-143), or its two "sub-epitopes" in immunotherapeutic trials designed to generate or enhance specific CD4+ T-cell responses against tumors expressing NY-ESO-1 in vivo.

Data warehousing in molecular biology

In the business and healthcare sectors data warehousing has provided effective solutions for information usage and knowledge discovery from databases. However, data warehousing applications in the biological research and development (R&D) sector are lagging far behind. The fuzziness and complexity of biological data represent a major challenge in data warehousing for molecular biology. By combining experiences in other domains with our findings from building a model database, we have defined the requirements for data warehousing in molecular biology.

Molecular immunology databases and data repositories

Over recent years databases have become an extremely important resource for biomedical research. Immunology research is increasingly dependent on access to extensive biological databases to extract existing information, plan experiments, and analyse experimental results. This review describes 15 immunological databases that have appeared over the last 30 years. In addition, important issues regarding database design and the potential for misuse of information contained within these databases are discussed. Access pointers are provided for the major immunological databases and also for a number of other immunological resources accessible over the World Wide Web (WWW).

Melan-A/MART-1(51-73) represents an immunogenic HLA-DR4-restricted epitope recognized by melanoma-reactive CD4(+) T cells

The human Melan-A/MART-1 gene encodes an HLA-A2-restricted peptide epitope recognized by melanoma-reactive CD8(+) cytotoxic T lymphocytes. Here we report that this gene also encodes at least one HLA-DR4-presented peptide recognized by CD4(+) T cells. The Melan-A/MART-1(51-73) peptide was able to induce the in vitro expansion of specific CD4(+) T cells derived from normal DR4(+) donors or from DR4(+) patients with melanoma when pulsed onto autologous dendritic cells. CD4(+) responder T cells specifically produced IFN-gamma in response to, and also lysed, T2.DR4 cells pulsed with the Melan-A/MART-1(51-73) peptide and DR4(+) melanoma target cells naturally expressing the Melan-A/MART-1 gene product. Interestingly, CD4(+) T cell immunoreactivity against the Melan-A/MART-1(51-73) peptide typically coexisted with a high frequency of anti-Melan-A/MART-1(27-35) reactive CD8(+) T cells in freshly isolated blood harvested from HLA-A2(+)/DR4(+) patients with melanoma. Taken together, these data support the use of this Melan-A/MART-1 DR4-restricted melanoma epitope in future immunotherapeutic trials designed to generate, augment, and quantitate specific CD4(+) T cell responses against melanoma in vivo.

FIMM, a database of functional molecular immunology

FIMM database (http://sdmc.krdl.org.sg:8080/fimm ) contains data relevant to functional molecular immunology, focusing on cellular immunology. It contains fully referenced data on protein antigens, major histocompatibility complex (MHC) molecules, MHC-associated peptides and relevant disease associations. FIMM has a set of search tools for extraction of information and results are presented as lists or as reports.

Neural network-based prediction of candidate T-cell epitopes

Activation of T cells requires recognition by T-cell receptors of specific peptides bound to major histocompatibility complex (MHC) molecules on the surface of either antigen-presenting or target cells. These peptides, T-cell epitopes, have potential therapeutic applications, such as for use as vaccines. Their identification, however, usually requires that multiple overlapping synthetic peptides encompassing a protein antigen be assayed, which in humans, is limited by volume of donor blood. T-cell epitopes are a subset of peptides that bind to MHC molecules. We use an artificial neural network (ANN) model trained to predict peptides that bind to the MHC class II molecule HLA-DR4(*0401). Binding prediction facilitates identification of T-cell epitopes in tyrosine phosphatase IA-2, an autoantigen in DR4-associated type1 diabetes. Synthetic peptides encompassing IA-2 were tested experimentally for DR4 binding and T-cell proliferation in humans at risk for diabetes. ANN-based binding prediction was sensitive and specific, and reduced the number of peptides required for T-cell assay by more than half, with only a minor loss of epitopes. This strategy could expedite identification of candidate T-cell epitopes in diverse diseases.

Relationship between peptide selectivities of human transporters associated with antigen processing and HLA class I molecules

Efficiency of presentation of a peptide epitope by a MHC class I molecule depends on two parameters: its binding to the MHC molecule and its generation by intracellular Ag processing. In contrast to the former parameter, the mechanisms underlying peptide selection in Ag processing are poorly understood. Peptide translocation by the TAP transporter is required for presentation of most epitopes and may modulate peptide supply to MHC class I molecules. To study the role of human TAP for peptide presentation by individual HLA class I molecules, we generated artificial neural networks capable of predicting the affinity of TAP for random sequence 9-mer peptides. Using neural network-based predictions of TAP affinity, we found that peptides eluted from three different HLA class I molecules had higher TAP affinities than control peptides with equal binding affinities for the same HLA class I molecules, suggesting that human TAP may contribute to epitope selection. In simulated TAP binding experiments with 408 HLA class I binding peptides, HLA class I molecules differed significantly with respect to TAP affinities of their ligands. As a result, some class I molecules, especially HLA-B27, may be particularly efficient in presentation of cytosolic peptides with low concentrations, while most class I molecules may predominantly present abundant cytosolic peptides.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

MOTIVATION

Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules.

RESULTS

Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification . This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binders were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotherapeutic peptides.

AVAILABILITY

Software and data are available from the authors upon request.

CONTACT

vladimir@wehi.edu. au

MHCPEP, a database of MHC-binding peptides: update 1997

MHCPEP (http://wehih.wehi.edu.au/mhcpep/) is a curated database comprising over 13 000 peptide sequences known to bind MHC molecules. Entries are compiled from published reports as well as from direct submissions of experimental data. Each entry contains the peptide sequence, its MHC specificity and where available, experimental method, observed activity, binding affinity, source protein and anchor positions, as well as publication references. The present format of the database allows text string matching searches but can easily be converted for use in conjunction with sequence analysis packages. The database can be accessed via Internet using WWW or FTP.

MHCWeb: converting a WWW database into a knowledge-based collaborative environment

The World Wide Web (WWW) is useful for distributing scientific data. Most existing web data resources organize their information either in structured flat files or relational databases with basic retrieval capabilities. For databases with one or a few simple relations, these approaches are successful, but they can be cumbersome when there is a data model involving multiple relations between complex data. We believe that knowledge-based resources offer a solution in these cases. Knowledge bases have explicit declarations of the concepts in the domain, along with the relations between them. They are usually organized hierarchically, and provide a global data model with a controlled vocabulary. We have created the OWEB architecture for building online scientific data resources using knowledge bases. OWEB provides a shell for structuring data, providing secure and shared access, and creating computational modules for processing and displaying data. In this paper, we describe the translation of the online immunological database MHCPEP into an OWEB system called MHCWeb. This effort involved building a conceptual model for the data, creating a controlled terminology for the legal values for different types of data, and then translating the original data into the new structure. The OWEB environment allows for flexible access to the data by both users and computer programs.

Application of genetic search in derivation of matrix models of peptide binding to MHC molecules

T cells of the vertebrate immune system recognise peptides bound by major histocompatibility complex (MHC) molecules on the surface of host cells. Peptide binding to MHC molecules is necessary for immune recognition, but only a subset of peptides are capable of binding to a particular MHC molecule. Common amino acid patterns (binding motifs) have been observed in sets of peptides that bind to specific MHC molecules. Recently, matrix models for peptide/MHC interaction have been reported. These encode the rules of peptide/ MHC interactions for an individual MHC molecule as a 20 x 9 matrix where the contribution to binding of each amino acid at each position within a 9-mer peptide is quantified. The artificial intelligence techniques of genetic search and machine learning have proved to be very useful in the area of biological sequence analysis. The availability of peptide/MHC binding data can facilitate derivation of binding matrices using machine learning techniques. We performed a simulation study to determine the minimum number of peptide samples required to derive matrices, given the pre-defined accuracy of the matrix model. The matrices were derived using a genetic search. In addition, matrices for peptide binding to the human class I MHC molecules, HLA-B35 and -A24, were derived, validated by independent experimental data and compared to previously-reported matrices. The results indicate that at least 150 peptide samples are required to derive matrices of acceptable accuracy. This result is based on a maximum noise content of 5%, the availability of precise affinity measurements and that acceptable accuracy is determined by an area under the Relative Operating Characteristic curve (Aroc) of > 0.8. More than 600 peptide samples are required to derive matrices of excellent accuracy (Aroc > 0.9). Finally, we derived a human HLA-B27 binding matrix using a genetic search and 404 experimentally-tested peptides, and estimated its accuracy at Aroc > 0.88. The results of this study are expected to be of practical interest to immunologists for efficient identification of peptides as candidates for immunotherapy.

Strategies for identifying and predicting islet autoantigen T-cell epitopes in insulin-dependent diabetes mellitus

T cells recognize peptide epitopes bound to major histocompatibility complex molecules. Human T-cell epitopes have diagnostic and therapeutic applications in autoimmune diseases. However, their accurate definition within an autoantigen by T-cell bioassay, usually proliferation, involves many costly peptides and a large amount of blood. We have therefore developed a strategy to predict T-cell epitopes and applied it to tyrosine phosphatase IA-2, an autoantigen in IDDM, and HLA-DR4(*0401). First, the binding of synthetic overlapping peptides encompassing IA-2 was measured directly to purified DR4. Secondly, a large amount of HLA-DR4 binding data were analysed by alignment using a genetic algorithm and were used to train an artificial neural network to predict the affinity of binding. This bioinformatic prediction method was then validated experimentally and used to predict DR4 binding peptides in IA-2. The binding set encompassed 85% of experimentally determined T-cell epitopes. Both the experimental and bioinformatic methods had high negative predictive values, 92% and 95%, indicating that this strategy of combining experimental results with computer modelling should lead to a significant reduction in the amount of blood and the number of peptides required to define T-cell epitopes in humans.

Generation and phenotypic characterization of new human ovarian cancer cell lines with the identification of antigens potentially recognizable by HLA-restricted cytotoxic T cells

This study describes a simple method for long-term establishment of human ovarian tumor lines and prediction of T-cell epitopes that could be potentially useful in the generation of tumor-specific cytotoxic T lymphocytes (CTLs). Nine ovarian tumor lines (INT.Ov) were generated from solid primary or metastatic tumors as well as from ascitic fluid. Notably all lines expressed HLA class I, intercellular adhesion molecule-1 (ICAM-1), polymorphic epithelial mucin (PEM) and cytokeratin (CK), but not HLA class II, B7.1 (CD80) or BAGE. While of the 9 lines tested 4 (INT.Ov1, 2, 5 and 6) expressed the folate receptor (FR-alpha) and 6 (INT.Ov1, 2, 5, 6, 7 and 9) expressed the epidermal growth factor receptor (EGFR); MAGE-1 and p185HER-2/neu were only found in 2 lines (INT.Ov1 and 2) and GAGE-1 expression in 1 line (INT.Ov2). The identification of class I MHC ligands and T-cell epitopes within protein antigens was achieved by applying several theoretical methods including: 1) similarity or homology searches to MHCPEP; 2) BIMAS and 3) artificial neural network-based predictions of proteins MAGE, GAGE, EGFR, p185HER-2/neu and FR-alpha expressed in INT.Ov lines. Because of the high frequency of expression of some of these proteins in ovarian cancer and the ability to determine HLA binding peptides efficiently, it is expected that after appropriate screening, a large cohort of ovarian cancer patients may become candidates to receive peptide-based vaccines.

Direct evidence for the expression of multiple endogenous retroviruses in the synovial compartment in rheumatoid arthritis

OBJECTIVE

Circumstantial evidence links retroviruses (RVs) with human autoimmune diseases. The aim of the present study was to obtain direct evidence of RV gene expression in rheumatoid arthritis (RA).

METHODS

Synovial samples were obtained from patients with RA, patients with osteoarthritis (OA), and normal control subjects. Reverse transcription-polymerase chain reaction (RT-PCR) was performed using synovial RNA and primers to conserved sequences in the polymerase (pol) genes of known RVs.

RESULTS

PCR products (n = 857) were cloned and sequenced. Multiple pol transcripts, many with open reading frames, were expressed in every sample. Sequences were aligned and classified into 6 families (F1-F6) that contained 33 groups of known and unknown endogenous RVs (ERVs), each distinguished by a specific, deduced peptide motif. The frequency of sequences in each family was similar between RA, OA, and normal synovial tissue, but differed significantly in RA synovial fluid cells. F1 sequences (undefined, but related to murine and primate type C RVs) were lower in frequency, F2 (ERV-9-related), F4 (HERV-K-related), and F6 (HERV-L-related) sequences were higher in frequency, and F3 (RTVL-H-related) sequences were not detected, in the RA synovial fluid cells compared with the RA synovial tissues.

CONCLUSION

Multiple ERVs are expressed in normal and diseased synovial compartments, but specific transcripts can be differentially expressed in RA.

A peptide-binding motif for I-A(g7), the class II major histocompatibility complex (MHC) molecule of NOD and Biozzi AB/H mice

The class II major histocompatibility complex molecule I-A(g7) is strongly linked to the development of spontaneous insulin-dependent diabetes mellitus (IDDM) in non obese diabetic mice and to the induction of experimental allergic encephalomyelitis in Biozzi AB/H mice. Structurally, it resembles the HLA-DQ molecules associated with human IDDM, in having a non-Asp residue at position 57 in its beta chain. To identify the requirements for peptide binding to I-A(g7) and thereby potentially pathogenic T cell epitopes, we analyzed a known I-A(g7)-restricted T cell epitope, hen egg white lysozyme (HEL) amino acids 9-27. NH2- and COOH-terminal truncations demonstrated that the minimal epitope for activation of the T cell hybridoma 2D12.1 was M12-R21 and the minimum sequence for direct binding to purified I-A(g7) M12-Y20/K13-R21. Alanine (A) scanning revealed two primary anchors for binding at relative positions (p) 6 (L) and 9 (Y) in the HEL epitope. The critical role of both anchors was demonstrated by incorporating L and Y in poly(A) backbones at the same relative positions as in the HEL epitope. Well-tolerated, weakly tolerated, and nontolerated residues were identified by analyzing the binding of peptides containing multiple substitutions at individual positions. Optimally, p6 was a large, hydrophobic residue (L, I, V, M), whereas p9 was aromatic and hydrophobic (Y or F) or positively charged (K, R). Specific residues were not tolerated at these and some other positions. A motif for binding to I-A(g7) deduced from analysis of the model HEL epitope was present in 27/30 (90%) of peptides reported to be I-A(g7)-restricted T cell epitopes or eluted from I-A(g7). Scanning a set of overlapping peptides encompassing human proinsulin revealed the motif in 6/6 good binders (sensitivity = 100%) and 4/13 weak or non-binders (specificity = 70%). This motif should facilitate identification of autoantigenic epitopes relevant to the pathogenesis and immunotherapy of IDDM.

MHCPEP, a database of MHC-binding peptides: update 1996

MHCPEP is a curated database comprising over 9000 peptide sequences known to bind MHC molecules. Entries are compiled from published reports as well as from direct submissions of experimental data. Each entry contains the peptide sequence, its MHC specificity and, when available, experimental method, observed activity, binding affinity, source protein, anchor positions and publication references. The present format of the database allows text string matching searches but can easily be converted for use in conjunction with sequence analysis packages. The database can be accessed via Internet using WWW, FTP or Gopher.

MHCPEP--a database of MHC-binding peptides: update 1995

MHCPEP is a curated database comprising over 6000 peptide sequences known to bind MHC molecules. Entries are compiled from published reports as well as from direct submissions of experimental data. Each entry contains peptide sequence, MHC specificity and when available, experimental method, observed activity, binding affinity, source protein, anchor positions, as well as publication references. The present format of the database allows text string matching searches but can easily be converted for use in conjunction with sequence analysis packages. The database can be accessed via Internet using Gopher, FTP or WWW.

Similar peptides from two beta cell autoantigens, proinsulin and glutamic acid decarboxylase, stimulate T cells of individuals at risk for insulin-dependent diabetes

BACKGROUND

Insulin (1) and glutamic acid decarboxylase (GAD) (2) are both autoantigens in insulin-dependent diabetes mellitus (IDDM), but no molecular mechanism has been proposed for their association. We have identified a 13 amino acid peptide of proinsulin (amino acids 24-36) that bears marked similarity to a peptide of GAD65 (amino acids 506-518) (G. Rudy, unpublished). In order to test the hypothesis that this region of similarity is implicated in the pathogenesis of IDDM, we assayed T cell reactivity to these two peptides in subjects at risk for IDDM.

MATERIALS AND METHODS

Subjects at risk for IDDM were islet cell antibody (ICA)-positive, first degree relatives of people with insulin-dependent diabetes. Peripheral blood mononuclear cells from 10 pairs of at-risk and HLA-DR matched control subjects were tested in an in vitro proliferation assay.

RESULTS

Reactivity to both proinsulin and GAD peptides was significantly greater among at-risk subjects than controls (proinsulin; p < 0.008; GAD; p < 0.018). In contrast to reactivity to the GAD peptide, reactivity to the proinsulin peptide was almost entirely confined to the at-risk subjects.

CONCLUSIONS

This is the first demonstration of T cell reactivity to a proinsulin-specific peptide. In addition, it is the first example of reactivity to a minimal peptide region shared between two human autoimmune disease-associated self antigens. Mimicry between these similar peptides may provide a molecular basis for the conjoint autoantigenicity of proinsulin and GAD in IDDM.