A Human Erythrocyte-based Haemolysis Assay for the Evaluation of Human Complement Activity.

The complement system consists of at least 50 proteins that serve as one of the first lines of defence against foreign, or damaged, cells and invading microorganisms. Its dysregulation underlies the pathophysiology of many different diseases, which makes functional assays of complement activity crucial; they are, however, underutilised. Standard haemolysis assays for the analysis of complement function employ sensitised non-human erythrocytes (e.g. from the sheep, guinea-pig or rabbit), the use of which raises animal welfare concerns. To provide an alternative to the use of such animal-derived products for complement function assays, we developed a method that employs modified human erythrocytes to evaluate the activity of complement pathways. Human erythrocytes were subjected to various chemical and/or proteolytic treatments involving 2,4,6-trinitrobenzene sulphonate (TNBS) and pancreatin. Haemolysis assays demonstrated that sequential treatment with TNBS and pancreatin resulted in significantly greater complement-mediated haemolysis, as compared to TNBS or pancreatin treatment alone. Evidence that lysis of the modified erythrocytes was complement-mediated was provided by the chelation and subsequent restoration of calcium in the plasma. Thus, such modified human erythrocytes could be used as an alternative to animal-derived erythrocytes in haemolysis assays, in order to evaluate complement activity in human plasma during, for example, the screening of patients for complement deficiencies and other abnormalities in a clinical setting.

Delineating Surface Epitopes of Lyme Disease Pathogen Targeted by Highly Protective Antibodies of New Zealand White Rabbits.

Lyme disease (LD), the most prevalent vector-borne illness in the United States and Europe, is caused by Borreliella burgdorferi No vaccine is available for humans. Dogmatically, B. burgdorferi can establish a persistent infection in the mammalian host (e.g., mice) due to a surface antigen, VlsE. This antigenically variable protein allows the spirochete to continually evade borreliacidal antibodies. However, our recent study has shown that the B. burgdorferi spirochete is effectively cleared by anti-B. burgdorferi antibodies of New Zealand White rabbits, despite the surface expression of VlsE. Besides homologous protection, the rabbit antibodies also cross-protect against heterologous B. burgdorferi spirochetes and significantly reduce the pathology of LD arthritis in persistently infected mice. Thus, this finding that NZW rabbits develop a unique repertoire of very potent antibodies targeting the protective surface epitopes, despite abundant VlsE, prompted us to identify the specificities of the protective rabbit antibodies and their respective targets. By applying subtractive reverse vaccinology, which involved the use of random peptide phage display libraries coupled with next-generation sequencing and our computational algorithms, repertoires of nonprotective (early) and protective (late) rabbit antibodies were identified and directly compared. Consequently, putative surface epitopes that are unique to the protective rabbit sera were mapped. Importantly, the relevance of newly identified protection-associated epitopes for their surface exposure has been strongly supported by prior empirical studies. This study is significant because it now allows us to systematically test the putative epitopes for their protective efficacy with an ultimate goal of selecting the most efficacious targets for development of a long-awaited LD vaccine.

Identification of Surface Epitopes Associated with Protection against Highly Immune-Evasive VlsE-Expressing Lyme Disease Spirochetes.

The tick-borne pathogen Borrelia burgdorferi is responsible for approximately 300,000 Lyme disease (LD) cases per year in the United States. Recent increases in the number of LD cases, in addition to the spread of the tick vector and a lack of a vaccine, highlight an urgent need for designing and developing an efficacious LD vaccine. Identification of protective epitopes that could be used to develop a second-generation (subunit) vaccine is therefore imperative. Despite the antigenicity of several lipoproteins and integral outer membrane proteins (OMPs) on the B. burgdorferi surface, the spirochetes successfully evade antibodies primarily due to the VlsE-mediated antigenic variation. VlsE is thought to sterically block antibody access to protective epitopes of B. burgdorferi However, it is highly unlikely that VlsE shields the entire surface epitome. Thus, identification of subdominant epitope targets that induce protection when they are made dominant is necessary to generate an efficacious vaccine. Toward the identification, we repeatedly immunized immunocompetent mice with live-attenuated VlsE-deleted B. burgdorferi and then challenged the animals with the VlsE-expressing (host-adapted) wild type. Passive immunization and Western blotting data suggested that the protection of 50% of repeatedly immunized animals against the highly immune-evasive B. burgdorferi was antibody mediated. Comparison of serum antibody repertoires identified in protected and nonprotected animals permitted the identification of several putative epitopes significantly associated with the protection. Most linear putative epitopes were conserved between the main pathogenic Borrelia genospecies and found within known subdominant regions of OMPs. Currently, we are performing immunization studies to test whether the identified protection-associated epitopes are protective for mice.

B-Cell Epitope Prediction for Antipeptide Paratopes with the HAPTIC2/HEPTAD User Toolkit (HUT).

B-cell epitope prediction is key to developing peptide-based vaccines and immunodiagnostics along with antibodies for prophylactic, therapeutic and/or diagnostic use. This entails estimating paratope binding affinity for variable-length peptidic sequences subject to constraints on both paratope accessibility and antigen conformational flexibility, as described herein for the HAPTIC2/HEPTAD User Toolkit (HUT). HUT comprises the Heuristic Affinity Prediction Tool for Immune Complexes 2 (HAPTIC2), the HAPTIC2-like Epitope Prediction Tool for Antigen with Disulfide (HEPTAD) and the HAPTIC2/HEPTAD Input Preprocessor (HIP). HIP enables tagging of residues (e.g., in hydrophobic blobs, ordered regions and glycosylation motifs) for exclusion from downstream analyses by HAPTIC2 and HEPTAD. HAPTIC2 estimates paratope binding affinity for disulfide-free disordered peptidic antigens (by analogy between flexible-ligand docking and protein folding), from terms attributed to compaction (in view of sequence length, charge and temperature-dependent polyproline-II helical propensity), collapse (disfavored by residue bulkiness) and contact (with glycine and proline regarded as polar residues that hydrogen bond with paratopes). HEPTAD analyzes antigen sequences that each contain two cysteine residues for which the impact of disulfide pairing is estimated as a correction to the free-energy penalty of compaction. All of HUT is freely accessible online ( https://freeshell.de/~badong/hut.htm ).

Immunologic, genetic, and ecological interplay of factors involved in allergic diseases.

An allergic or type I hypersensitivity reaction involves a misdirected immune overreaction to innocuous environmental and dietary antigens called allergens. The genetic predisposition to allergic disease, referred to as atopy, can be expressed as a variety of manifestations-e.g., allergic rhinitis, allergic conjunctivitis, atopic dermatitis, allergic asthma, anaphylaxis. Globally, allergic diseases are one the most common types of chronic conditions. Several factors have been identified to contribute to the pathogenesis and progression of the disease, leading to distinctively variable clinical symptoms. The factors which can attenuate or exacerbate allergic reactions can range from genetic heterozygosity, the prominence of various comorbid infections, and other factors such as pollution, climate, and interactions with other organisms and organism-derived products, and the surrounding environment. As a result, the effective prevention and control of allergies remains to be one of the most prominent public health problems. Therefore, to contextualize the current knowledge about allergic reactions, this review paper attempts to synthesize different aspects of an allergic response to describe its significance in the global health scheme. Specifically, the review shall characterize the biomolecular mechanisms of the pathophysiology of the disease based on underlying disease theories and current findings on ecologic interactions and describe prevention and control strategies being utilized. An integrated perspective that considers the underlying genetic, immunologic, and ecologic aspects of the disease would enable the development of more effective and targeted diagnostic tools and therapeutic strategies for the management and control of allergic diseases.

Beyond B-Cell Epitopes: Curating Positive Data on Antipeptide Paratope Binding to Support Peptide-Based Vaccine Design.

BACKGROUND: B-cell epitope prediction is a computational approach originally developed to support the design of peptide-based vaccines for inducing protective antibody-mediated immunity, as exemplified by neutralization of biological activity (e.g., pathogen infectivity). Said approach is benchmarked against experimentally obtained data on paratope-epitope binding; but such data are curated primarily on the basis of immune-complex structure, obscuring the role of antigen conformational disorder in the underlying immune recognition process. OBJECTIVE: This work aimed to critically analyze the curation of epitope-paratope binding data that are relevant to B-cell epitope prediction for peptide-based vaccine design. METHODS: Database records on neutralizing monoclonal antipeptide antibody immune-complex structure were retrieved from the Immune Epitope Database (IEDB) and analyzed in relation to other data from both IEDB and external sources including the Protein Data Bank (PDB) and published literature, with special attention to data on conformational disorder among paratope-bound and unbound peptidic antigens. RESULTS: Data analysis revealed key examples of antipeptide antibodies that recognize conformationally disordered B-cell epitopes and thereby neutralize the biological activity of cognate targets (e.g., proteins and pathogens), with inconsistency noted in the mapping of some epitopes due to reliance on immune-complex structural details, which vary even among experiments utilizing the same paratope-epitope combination (e.g., with the epitope forming part of a peptide or a protein). CONCLUSION: The results suggest an alternative approach to curating paratope-epitope binding data based on neutralization of biological activity by polyclonal antipeptide antibodies, with reference to immunogenic peptide sequences and their conformational disorder in unbound antigen structures.

Benchmarking B-cell epitope prediction for the design of peptide-based vaccines: problems and prospects.

To better support the design of peptide-based vaccines, refinement of methods to predict B-cell epitopes necessitates meaningful benchmarking against empirical data on the cross-reactivity of polyclonal antipeptide antibodies with proteins, such that the positive data reflect functionally relevant cross-reactivity (which is consistent with antibody-mediated change in protein function) and the negative data reflect genuine absence of cross-reactivity (rather than apparent absence of cross-reactivity due to artifactual masking of B-cell epitopes in immunoassays). These data are heterogeneous in view of multiple factors that complicate B-cell epitope prediction, notably physicochemical factors that define key structural differences between immunizing peptides and their cognate proteins (e.g., unmatched electrical charges along the peptide-protein sequence alignments). If the data are partitioned with respect to these factors, iterative parallel benchmarking against the resulting subsets of data provides a basis for systematically identifying and addressing the limitations of methods for B-cell epitope prediction as applied to vaccine design.

Development and Characterization of Polymeric Peptides for Antibody Tagging of Bacterial Targets.

BACKGROUND: Microbe-Binding Peptides (MBPs) are currently being investigated to address the problem of antimicrobial resistance. Strategies enhancing their antimicrobial activity have been developed, including peptide dimerization. Here, we present an alternative approach based on peptide polymerization, yielding hapten-labelled polymeric MBPs that mediate tagging of bacteria with anti-hapten antibodies, for enhanced immune recognition by host phagocytes. METHODS: C-terminally amidated analogs of the bacterial-binding peptide IIGGR were synthesized, with or without addition of cysteine residues at both N- and C-termini. Peptides were subjected to oxidizing conditions in a dimethyl-sulfoxide/water solvent system, and polymerization was demonstrated using SDS-PAGE. Peptides were then N-terminally labelled with a trinitrophenyl (TNP) group using trinitrobenzene sulfonate (TNBS). Binding to representative bacteria was demonstrated by ELISA using anti-TNP antibodies and was quantified as half-maximal effective concentration (EC50). Minimum Inhibitory Concentration (MIC) and concentration yielding 50% hemolysis (H50) were estimated. Neutrophil phagocytic index was determined for TNP-labelled polymeric bacterial- binding peptide (Pbac) with anti-TNP antibodies and/or serum complement. RESULTS: Polydisperse Pbac was synthesized. EC50 was lower for Pbac than for the corresponding monomeric form (Mbac), for both Staphylococcus aureus ATCC 29213 and Escherichia coli ATCC 25922. MIC and H50 were >250µg/mL for both Pbac and Mbac. A complement-independent increase in neutrophil phagocytic index was observed for E. coli treated with TNP-labelled Pbac in conjunction with anti-TNP antibodies. CONCLUSION: Our data suggest that hapten-labelled polymeric bacterial-binding peptides may easily be produced from even crude synthetic oligopeptide precursors, and that such bacterial-binding peptides in conjunction with cognate anti-hapten antibodies can enhance immune recognition of bacteria by host phagocytes.

Functional analysis of GALT variants found in classic galactosemia patients using a novel cell-free translation method.

Classic galactosemia is an autosomal recessive disorder caused by deleterious variants in the galactose-1-phosphate uridylyltransferase (GALT) gene. GALT enzyme deficiency leads to an increase in the levels of galactose and its metabolites in the blood causing neurodevelopmental and other clinical complications in affected individuals. Two GALT variants NM_000155.3:c.347T>C (p.Leu116Pro) and NM_000155.3:c.533T>G (p.Met178Arg) were previously detected in Filipino patients. Here, we determine their functional effects on the GALT enzyme through in silico analysis and a novel experimental approach using a HeLa-based cell-free protein expression system. Enzyme activity was not detected for the p.Leu116Pro protein variant, while only 4.5% of wild-type activity was detected for the p.Met178Arg protein variant. Computational analysis of the variants revealed destabilizing structural effects and suggested protein misfolding as the potential mechanism of enzymological impairment. Biochemical and computational data support the classification of p.Leu116Pro and p.Met178Arg variants as pathogenic. Moreover, the protein expression method developed has utility for future studies of GALT variants.

A structural-energetic basis for B-cell epitope prediction.

Structural-energetic analysis of peptide and protein antigens in the context of binding to antibody reveals fundamental differences between the cross-reactions of antipeptide antibody with protein and antiprotein antibody with peptide, providing a physicochemical basis for B-cell epitope prediction as applied to the development of peptide-based vaccines and immunodiagnostics.

Expressing Redundancy among Linear-Epitope Sequence Data Based on Residue-Level Physicochemical Similarity in the Context of Antigenic Cross-Reaction.

Epitope-based design of vaccines, immunotherapeutics, and immunodiagnostics is complicated by structural changes that radically alter immunological outcomes. This is obscured by expressing redundancy among linear-epitope data as fractional sequence-alignment identity, which fails to account for potentially drastic loss of binding affinity due to single-residue substitutions even where these might be considered conservative in the context of classical sequence analysis. From the perspective of immune function based on molecular recognition of epitopes, functional redundancy of epitope data (FRED) thus may be defined in a biologically more meaningful way based on residue-level physicochemical similarity in the context of antigenic cross-reaction, with functional similarity between epitopes expressed as the Shannon information entropy for differential epitope binding. Such similarity may be estimated in terms of structural differences between an immunogen epitope and an antigen epitope with reference to an idealized binding site of high complementarity to the immunogen epitope, by analogy between protein folding and ligand-receptor binding; but this underestimates potential for cross-reactivity, suggesting that epitope-binding site complementarity is typically suboptimal as regards immunologic specificity. The apparently suboptimal complementarity may reflect a tradeoff to attain optimal immune function that favors generation of immune-system components each having potential for cross-reactivity with a variety of epitopes.

An integrative structure-based framework for predicting biological effects mediated by antipeptide antibodies.

A general framework is presented for predicting quantitative biological effects mediated by antipeptide antibodies, primarily on the basis of antigen structure (possibly featuring intrinsic disorder) analyzed to estimate epitope-paratope binding affinities, which in turn is considered within the context of dose-response relationships as regards antibody concentration. This is illustrated mainly using an approach based on protein structural energetics, whereby expected amounts of solvent-accessible surface area buried upon epitope-paratope binding are related to the corresponding binding affinity, which is estimated from putative B-cell epitope structure with implicit treatment of paratope structure, for antipeptide antibodies either reacting with peptides or cross-reacting with cognate protein antigens. Key methods described are implemented in SAPPHIRE/SUITE (Structural-energetic Analysis Program for Predicting Humoral Immune Response Epitopes/SAPPHIRE User Interface Tool Ensemble; publicly accessible via http://freeshell.de/~badong/suite.htm). Representative results thus obtained are compared with published experimental data on binding affinities and quantitative biological effects, with special attention to loss of paratope sidechain conformational entropy (neglected in previous analyses) and in light of key in-vivo constraints on antigen-antibody binding affinity and antibody-mediated effects. Implications for further refinement of B-cell epitope prediction methods are discussed as regards envisioned biomedical applications including the development of prophylactic and therapeutic antibodies, peptide-based vaccines and immunodiagnostics.

Hybrid methods for B-cell epitope prediction.

Many computational approaches to B-cell epitope prediction have been published, including combinations of previously proposed methods, which complicates the tasks of further developing such computational approaches and of selecting those most appropriate for practical applications (e.g., the design of novel immunodiagnostics and vaccines). These tasks are considered together herein to clarify their close but often overlooked interrelationship, thereby providing a guide to their performance in mutual support of one another, with emphasis on key physicochemical and biological considerations that are relevant from an applications perspective. This aims to assist investigators in performing either or both tasks, with the overall goals of successfully applying computational tools towards practical ends and of generating informative new data towards iterative improvement of the tools, particularly as regards the design of peptide-based immunogens for eliciting the production of antipeptide antibodies that modulate biological activity of protein targets via functionally relevant cross-reactivity in relation to the phenomena of protein folding and protein disorder.

Beyond new chemical entities: advancing drug development based on functional versatility of antibodies.

Antibody-type agents (i.e., antibodies and derivatives thereof) may be produced as clinically valuable antidotes, which conceivably could be developed in tandem with prospective new pharmaceutical products so as to render the risks of clinical trials more acceptable from a regulatory standpoint. Yet, this is but a relatively narrow view of the full potential utility associated with antibody-type agents, the significance of which is appreciated upon reconsidering key aspects of early modern biomedical research (notably major contributions thereto by Nobel Laureate Paul Ehrlich) in light of much more recent advances (e.g., application of immunity-oriented approaches to diseases in general, epitope-specific targeting, abzyme-mediated catalysis, antibody-mediated sustained-release buffering of unbound-ligand concentrations, and enhanced thermal and metabolic stability of deuterated chemical species via the kinetic isotope effect), as conditioned by health-related concerns (e.g., current and anticipated epidemiologic transitions vis-a-vis environmental changes) especially with regard to sustainable development (e.g., emphasizing more efficient resource utilization toward increased global resilience based on greater independence from high-maintenance technological infrastructure). The broader view that thus emerges highlights the urgent need to rebalance the health-research agenda, which presently reflect an overemphasis on small-molecule candidate-drug discovery, in order to advance health based on a comprehensive fundamental synthesis of immunity and pharmacology.

Benchmarking B-cell epitope prediction with quantitative dose-response data on antipeptide antibodies: towards novel pharmaceutical product development.

B-cell epitope prediction can enable novel pharmaceutical product development. However, a mechanistically framed consensus has yet to emerge on benchmarking such prediction, thus presenting an opportunity to establish standards of practice that circumvent epistemic inconsistencies of casting the epitope prediction task as a binary-classification problem. As an alternative to conventional dichotomous qualitative benchmark data, quantitative dose-response data on antibody-mediated biological effects are more meaningful from an information-theoretic perspective in the sense that such effects may be expressed as probabilities (e.g., of functional inhibition by antibody) for which the Shannon information entropy (SIE) can be evaluated as a measure of informativeness. Accordingly, half-maximal biological effects (e.g., at median inhibitory concentrations of antibody) correspond to maximally informative data while undetectable and maximal biological effects correspond to minimally informative data. This applies to benchmarking B-cell epitope prediction for the design of peptide-based immunogens that elicit antipeptide antibodies with functionally relevant cross-reactivity. Presently, the Immune Epitope Database (IEDB) contains relatively few quantitative dose-response data on such cross-reactivity. Only a small fraction of these IEDB data is maximally informative, and many more of them are minimally informative (i.e., with zero SIE). Nevertheless, the numerous qualitative data in IEDB suggest how to overcome the paucity of informative benchmark data.

Antidotes, antibody-mediated immunity and the future of pharmaceutical product development.

If new scientific knowledge is to be more efficiently generated and applied toward the advancement of health, human safety must be more effectively addressed in the conduct of research. Given the present difficulties of accurately predicting biological outcomes of novel interventions in vivo, the imperative of human safety suggests the development of novel pharmaceutical products in tandem with their prospective antidotes in anticipation of possible adverse events, to render the risks of initial clinical trials more acceptable from a regulatory standpoint. Antibody-mediated immunity provides a generally applicable mechanistic basis for developing antidotes to both biologicals and small-molecule drugs (such that antibodies may serve as antidotes to pharmaceutical agents as a class including other antibodies) and also for the control and prevention of both infectious and noninfectious diseases via passive or active immunization. Accordingly, the development of prophylactic or therapeutic passive-immunization strategies using antipeptide antibodies is a plausible prelude to the development of corresponding active-immunization strategies using peptide-based vaccines. In line with this scheme, global proliferation of antibody- and vaccine-production technologies, especially those that obviate dependence on the cold chain for storage and transport of finished products, could provide geographically distributed breakout capability against emerging and future health challenges.

On the meaning of affinity limits in B-cell epitope prediction for antipeptide antibody-mediated immunity.

B-cell epitope prediction aims to aid the design of peptide-based immunogens (e.g., vaccines) for eliciting antipeptide antibodies that protect against disease, but such antibodies fail to confer protection and even promote disease if they bind with low affinity. Hence, the Immune Epitope Database (IEDB) was searched to obtain published thermodynamic and kinetic data on binding interactions of antipeptide antibodies. The data suggest that the affinity of the antibodies for their immunizing peptides appears to be limited in a manner consistent with previously proposed kinetic constraints on affinity maturation in vivo and that cross-reaction of the antibodies with proteins tends to occur with lower affinity than the corresponding reaction of the antibodies with their immunizing peptides. These observations better inform B-cell epitope prediction to avoid overestimating the affinity for both active and passive immunization; whereas active immunization is subject to limitations of affinity maturation in vivo and of the capacity to accumulate endogenous antibodies, passive immunization may transcend such limitations, possibly with the aid of artificial affinity-selection processes and of protein engineering. Additionally, protein disorder warrants further investigation as a possible supplementary criterion for B-cell epitope prediction, where such disorder obviates thermodynamically unfavorable protein structural adjustments in cross-reactions between antipeptide antibodies and proteins.

Immunization with peptide-protein conjugates: impact on benchmarking B-cell epitope prediction for vaccine design.

Benchmarking B-cell epitope prediction for vaccine design is meaningful if based on empirical reference data pertaining to cross-reactivities of antipeptide antibodies with native protein antigens; yet it is complicated by such data acquired using antibodies raised against peptide-protein conjugates, as peptide-protein conjugation can differentially suppress antibody responses to peptide epitopes.