BPSL1626: Reverse and Structural Vaccinology Reveal a Novel Candidate for Vaccine Design against Burkholderia pseudomallei.

Due to significant advances in computational biology, protein prediction, together with antigen and epitope design, have rapidly moved from conventional methods, based on experimental approaches, to in silico-based bioinformatics methods. In this context, we report a reverse vaccinology study that identified a panel of 104 candidate antigens from the Gram-negative bacterial pathogen Burkholderia pseudomallei, which is responsible for the disease melioidosis. B. pseudomallei can cause fatal sepsis in endemic populations in the tropical regions of the world and treatment with antibiotics is mostly ineffective. With the aim of identifying potential vaccine candidates, we report the experimental validation of predicted antigen and type I fimbrial subunit, BPSL1626, which we show is able to recognize and bind human antibodies from the sera of Burkholderia infected patients and to stimulate T-lymphocytes in vitro. The prerequisite for a melioidosis vaccine, in fact, is that both antibody- and cell-mediated immune responses must be triggered. In order to reveal potential antigenic regions of the protein that may aid immunogen re-design, we also report the crystal structure of BPSL1626 at 1.9 Å resolution on which structure-based epitope predictions were based. Overall, our data suggest that BPSL1626 and three epitope regions here-identified can represent viable candidates as potential antigenic molecules.

Designing Probes for Immunodiagnostics: Structural Insights into an Epitope Targeting Burkholderia Infections.

Structure-based epitope prediction drives the design of diagnostic peptidic probes to reveal specific antibodies elicited in response to infections. We previously identified a highly immunoreactive epitope from the peptidoglycan-associated lipoprotein (Pal) antigen from Burkholderia pseudomallei, which could also diagnose Burkholderia cepacia infections. Here, considering the high phylogenetic conservation within Burkholderia species, we ask whether cross-reactivity can be reciprocally displayed by the synthetic epitope from B. cenocepacia. We perform comparative analyses of the conformational preferences and diagnostic performances of the corresponding epitopes from the two Burkholderia species when presented in the context of the full-length proteins or as isolated peptides. The effects of conformation on the diagnostic potential and cross-reactivity of Pal peptide epitopes are rationalized on the basis of the 1.8 Å crystal structure of B. cenocepacia Pal and through computational analyses. Our results are discussed in the context of designing new diagnostic molecules for the early detection of infectious diseases.

Structure and Computation in Immunoreagent Design: From Diagnostics to Vaccines.

Novel immunological tools for efficient diagnosis and treatment of emerging infections are urgently required. Advances in the diagnostic and vaccine development fields are continuously progressing, with reverse vaccinology and structural vaccinology (SV) methods for antigen identification and structure-based antigen (re)design playing increasingly relevant roles. SV, in particular, is predicted to be the front-runner in the future development of diagnostics and vaccines targeting challenging diseases such as AIDS and cancer. We review state-of-the-art methodologies for structure-based epitope identification and antigen design, with specific applicative examples. We highlight the implications of such methods for the engineering of biomolecules with improved immunological properties, potential diagnostic and/or therapeutic uses, and discuss the perspectives of structure-based rational design for the production of advanced immunoreagents.

Screening Complex Biological Samples with Peptide Microarrays: The Favorable Impact of Probe Orientation via Chemoselective Immobilization Strategies on Clickable Polymeric Coatings.

The generation of robust analytical data using microarray platforms strictly relies on optimal ligand-target interaction at the sensor surface, which, in turn, is inherently bound to the correct immobilization scheme of the interrogated bioprobes. In the present work, we performed a rigorous comparative analysis of the impact of peptide ligands immobilization strategy in the screening of Burkholderia cepacia complex (BCC) infections in patients affected by cystic fibrosis (CF). We generated arrays of previously validated Burkholderia derived peptide probes that were selectively oriented on polymeric coatings by means of different click-type reactions including thiol maleimide, copper-catalyzed azide-alkyne cycloaddition (CuAAC), and strain-promoted azide-alkyne cycloaddition (SPAAC). We compared immobilization efficiency among the different chemoselective reactions, and we evaluated diagnostic performances at a statistically significant level, also in contrast to random immobilization strategies. Our findings clearly support the favorable role of correct bioprobe orientation in discriminating seronegative from infected individuals and, in the last analysis, in generating more-reliable and more-reproducible data. Spacing biomolecules from the sensor surface by means of small hydrophilic linkers also positively affects the analytical performance and leads to increased statistical significance of data. Overall, all of the click immobilization strategies that were considered displayed a good efficiency. Interestingly, SPAAC-mediated conjugation using DBCO cyclooctyne for some peptides resulted in sequence-dependent autofluorescence in the Cy5 emission range wavelength, which could be circumvented by using a different fluorescence detection channel. On the basis of our results, we critically discuss the immobilization parameters that need to be carefully considered for peptide ligand immobilization purposes.

Flexible vs Rigid Epitope Conformations for Diagnostic- and Vaccine-Oriented Applications: Novel Insights from the Burkholderia pseudomallei BPSL2765 Pal3 Epitope.

Peptides seldom retain stable conformations if separated from their native protein structure. In an immunological context, this potentially affects the development of selective peptide-based bioprobes and, from a vaccine perspective, poses inherent limits in the elicitation of cross-reactive antibodies by candidate epitopes. Here, a 1,4-disubstituted-1,2,3-triazole-mediated stapling strategy was used to stabilize the native α-helical fold of the Pal3 peptidic epitope from the protein antigen PalBp (BPSL2765) from Burkholderia pseudomallei, the etiological agent of melioidosis. Whereas Pal3 shows no propensity to fold outside its native protein context, the engineered peptide (Pal3H) forms a stable α-helix, as assessed by MD, NMR, and CD structural analyses. Importantly, Pal3H shows an enhanced ability to discriminate between melioidosis patient subclasses in immune sera reactivity tests, demonstrating the potential of the stapled peptide for diagnostic purposes. With regard to antibody elicitation and related bactericidal activities, the linear peptide is shown to elicit a higher response. On these bases, we critically discuss the implications of epitope structure engineering for diagnostic- and vaccine-oriented applications.

Evolving serodiagnostics by rationally designed peptide arrays: the Burkholderia paradigm in Cystic Fibrosis.

Efficient diagnosis of emerging and novel bacterial infections is fundamental to guide decisions on therapeutic treatments. Here, we engineered a novel rational strategy to design peptide microarray platforms, which combines structural and genomic analyses to predict the binding interfaces between diverse protein antigens and antibodies against Burkholderia cepacia complex infections present in the sera of Cystic Fibrosis (CF) patients. The predicted binding interfaces on the antigens are synthesized in the form of isolated peptides and chemically optimized for controlled orientation on the surface. Our platform displays multiple Burkholderia-related epitopes and is shown to diagnose infected individuals even in presence of superinfections caused by other prevalent CF pathogens, with limited cost and time requirements. Moreover, our data point out that the specific patterns determined by combined probe responses might provide a characterization of Burkholderia infections even at the subtype level (genomovars). The method is general and immediately applicable to other bacteria.

Surface energetics and protein-protein interactions: analysis and mechanistic implications.

Understanding protein-protein interactions (PPI) at the molecular level is a fundamental task in the design of new drugs, the prediction of protein function and the clarification of the mechanisms of (dis)regulation of biochemical pathways. In this study, we use a novel computational approach to investigate the energetics of aminoacid networks located on the surface of proteins, isolated and in complex with their respective partners. Interestingly, the analysis of individual proteins identifies patches of surface residues that, when mapped on the structure of their respective complexes, reveal regions of residue-pair couplings that extend across the binding interfaces, forming continuous motifs. An enhanced effect is visible across the proteins of the dataset forming larger quaternary assemblies. The method indicates the presence of energetic signatures in the isolated proteins that are retained in the bound form, which we hypothesize to determine binding orientation upon complex formation. We propose our method, BLUEPRINT, as a complement to different approaches ranging from the ab-initio characterization of PPIs, to protein-protein docking algorithms, for the physico-chemical and functional investigation of protein-protein interactions.

Prediction of Antigenic B and T Cell Epitopes via Energy Decomposition Analysis: Description of the Web-Based Prediction Tool BEPPE.

Unraveling the molecular basis of immune recognition still represents a challenging task for current biological sciences, both in terms of theoretical knowledge and practical implications. Here, we describe the physical-chemistry methods and computational protocols for the prediction of antibody-binding epitopes and MHC-II loaded epitopes, starting from the atomic coordinates of antigenic proteins (PDB file). These concepts are the base of the Web tool BEPPE (Binding Epitope Prediction from Protein Energetics), a free service that returns a list of putative epitope sequences and related blast searches against the Uniprot human complete proteome. BEPPE can be employed for the study of the biophysical processes at the basis of the immune recognition, as well as for immunological purposes such as the rational design of biomarkers and targets for diagnostics, therapeutics, and vaccine discovery.

Sequence- and Structure-Based Immunoreactive Epitope Discovery for Burkholderia pseudomallei Flagellin.

Burkholderia pseudomallei is a Gram-negative bacterium responsible for melioidosis, a serious and often fatal infectious disease that is poorly controlled by existing treatments. Due to its inherent resistance to the major antibiotic classes and its facultative intracellular pathogenicity, an effective vaccine would be extremely desirable, along with appropriate prevention and therapeutic management. One of the main subunit vaccine candidates is flagellin of Burkholderia pseudomallei (FliCBp). Here, we present the high resolution crystal structure of FliCBp and report the synthesis and characterization of three peptides predicted to be both B and T cell FliCBp epitopes, by both structure-based in silico methods, and sequence-based epitope prediction tools. All three epitopes were shown to be immunoreactive against human IgG antibodies and to elicit cytokine production from human peripheral blood mononuclear cells. Furthermore, two of the peptides (F51-69 and F270-288) were found to be dominant immunoreactive epitopes, and their antibodies enhanced the bactericidal activities of purified human neutrophils. The epitopes derived from this study may represent potential melioidosis vaccine components.

From crystal structure to in silico epitope discovery in the Burkholderia pseudomallei flagellar hook-associated protein FlgK.

Melioidosis, caused by the Gram-negative bacterium Burkholderia pseudomallei, is a potentially fatal infection that is endemic in Southeast Asia and Northern Australia that is poorly controlled by antibiotics. Research efforts to identify antigenic components for a melioidosis vaccine have led to the identification of several proteins, including subunits forming the flagella that mediate bacterial motility, host colonization, and virulence. This study focuses on the B. pseudomallei flagellar hook-associated protein (FlgK(Bp)), and provides the first insights into the 3D structure of FlgK proteins as targets for structure-based antigen engineering. The FlgK(Bp) crystal structure (presented here at 1.8-Å resolution) reveals a multidomain fold, comprising two small ß-domains protruding from a large elongated α-helical bundle core. The evident structural similarity to flagellin, the flagellar filament subunit protein, suggests that, depending on the bacterial species, flagellar hook-associated proteins are likely to show a conserved, elongated α-helical bundle scaffold coupled to a variable number of smaller domains. Furthermore, we present immune serum recognition data confirming, in agreement with previous findings, that recovered melioidosis patients produce elevated levels of antibodies against FlgK(Bp), in comparison with seronegative and seropositive healthy subjects. Moreover, we show that FlgK(Bp) has cytotoxic effects on cultured murine macrophages, suggesting an important role in bacterial pathogenesis. Finally, computational epitope prediction methods applied to the FlgK(Bp) crystal structure, coupled with in vitro mapping, allowed us to predict three antigenic regions that locate to discrete protein domains. Taken together, our results point to FlgK(Bp) as a candidate for the design and production of epitope-containing subunits/domains as potential vaccine components.

Structure-based design of a B cell antigen from B. pseudomallei.

Burkholderia pseudomallei is the etiological agent of melioidosis, a severe endemic disease in South-East Asia, causing septicemia and organ failure with high mortality rates. Current treatments and diagnostic approaches are largely ineffective. The development of new diagnostic tools and vaccines toward effective therapeutic opportunities against B. pseudomallei is therefore an urgent priority. In the framework of a multidisciplinary project tackling melioidosis through reverse and structural vaccinology, BPSL1050 was identified as a candidate for immunodiagnostic and vaccine development based on its reactivity against the sera of melioidosis patients. We determined its NMR solution structure and dynamics, and by novel computational methods we predicted immunogenic epitopes that once synthesized were able to elicit the production of antibodies inducing the agglutination of the bacterium and recognizing both BPSL1050 and B. pseudomallei crude extracts. Overall, these results hold promise for novel chemical biology approaches in the discovery of new diagnostic and prophylactic tools against melioidosis.

Exploiting the Burkholderia pseudomallei acute phase antigen BPSL2765 for structure-based epitope discovery/design in structural vaccinology.

We solved the crystal structure of Burkholderia pseudomallei acute phase antigen BPSL2765 in the context of a structural vaccinology study, in the area of melioidosis vaccine development. Based on the structure, we applied a recently developed method for epitope design that combines computational epitope predictions with in vitro mapping experiments and successfully identified a consensus sequence within the antigen that, when engineered as a synthetic peptide, was selectively immunorecognized to the same extent as the recombinant protein in sera from melioidosis-affected subjects. Antibodies raised against the consensus peptide were successfully tested in opsonization bacterial killing experiments and antibody-dependent agglutination tests of B. pseudomallei. Our strategy represents a step in the development of immunodiagnostics, in the production of specific antibodies and in the optimization of antigens for vaccine development, starting from structural and physicochemical principles.

Peptides for immunological purposes: design, strategies and applications.

The development of new vaccines remains an attractive goal for disease prevention and therapy, in combination or alternative to drug-based treatment. In parallel, a growing awareness of the importance of early diagnosis in successful disease management is driving the demand for new reliable diagnostic tools. As a consequence, over the last decades an impressive amount of work has been directed toward the search for new solutions to address vaccine design and biomarker discovery. In this context, peptides have generated considerable interest thanks to their general accessibility and ease of manipulation. The aim of this review is to provide the reader a general picture of the traditional peptide-based strategies adopted in immunology and to report on recent advances made in this field, highlighting advantages and limitations of classic versus innovative approaches. Case studies are described to provide illustrative examples, and cross references to more topic-focused and exhaustive reviews are proposed throughout the text.

A structure-based strategy for epitope discovery in Burkholderia pseudomallei OppA antigen.

We present an approach integrating structural and computational biology with immunological tests to identify epitopes in the OppA antigen from the Gram-negative pathogen Burkholderia pseudomallei, the etiological agent of melioidosis. The crystal structure of OppA(Bp), reported here at 2.1 Å resolution, was the basis for a computational analysis that identified three potential epitopes. In parallel, antigen proteolysis and immunocapturing allowed us to identify three additional peptides. All six potential epitopes were synthesized as free peptides and tested for their immunoreactivity against sera from healthy seronegative, healthy seropositive, and recovered melioidosis patients. Three synthetic peptides allowed the different patient groups to be distinguished, underlining the potential of this approach. Extension of the computational analysis, including energy-based decomposition methods, allowed rationalizing results of the predictive analyses and the immunocapture epitope mapping. Our results illustrate a structure-based epitope discovery process, whose application may expand our perspectives in the diagnostic and vaccine design fields.

Rational epitope design for protein targeting.

We present a new multidisciplinary strategy integrating computational biology with high-throughput microarray analysis aimed to translate molecular understanding of protein-antibody recognition into the design of efficient and selective protein-based analytical and diagnostic tools. The structures of two proteins with different folds and secondary structure contents, namely, the beta-barrel FABP and the α-helical S100B, were used as the basis for the prediction and design of potential antibody-binding epitopes using the recently developed MLCE computational method. Starting from the idea that the structure, dynamics, and stability of a protein-antigen play a key role in the interaction with antibodies, MLCE integrates the analysis of the dynamical and energetic properties of proteins to identify nonoptimized, low-intensity energetic interaction-networks on the surface of the isolated antigens, which correspond to substructures that can aptly be recognized by a binding partner. The identified epitopes were next synthesized as free peptides and used to elicit specific antibodies in rabbits. Importantly, the resulting antibodies were proven to specifically and selectively recognize the original, full-length proteins in microarray-based tests. Competition experiments further demonstrated the specificity of the molecular recognition between the target immobilized proteins and the generated antibodies. Our integrated computational and microarray-based results demonstrate the possibility to rationally discover and design synthetic epitopes able to elicit antibodies specific for full-length proteins starting only from three-dimensional structural information on the target. We discuss implications for diagnosis and vaccine development purposes.