Enhancing Antibody Serodiagnosis Using a Controlled Peptide Coimmobilization Strategy

Two-dimensional high-throughput on-cell screening of immunoglobulins against broad antigen repertoires

Identifying high-affinity antibodies in human serum is challenging due to extremely low number of circulating B cells specific to the desired antigens. Delays caused by a lack of information on the immunogenic proteins of viral origin hamper the development of therapeutic antibodies. We propose an efficient approach allowing for enrichment of high-affinity antibodies against pathogen proteins with simultaneous epitope mapping, even in the absence of structural information about the pathogenic immunogens. To screen therapeutic antibodies from blood of recovered donors, only pathogen transcriptome is required to design an antigen polypeptide library, representing pathogen proteins, exposed on the bacteriophage surface. We developed a two-dimensional screening approach enriching lentiviral immunoglobulin libraries from the convalescent or vaccinated donors against bacteriophage library expressing the overlapping set of polypeptides covering the spike protein of SARS-CoV-2. This platform is suitable for pathogen-specific immunoglobulin enrichment and allows high-throughput selection of therapeutic human antibodies.

Optimization of Functional Group Concentration of N, N-Dimethylacrylamide-based Polymeric Coatings and Probe Immobilization for DNA and Protein Microarray Applications

We report here a deep investigation into the effect of the concentration of a polymeric coating's functional groups on probe density immobilization with the aim of establishing the optimal formulation to be implemented in specific microarray applications. It is widely known that the ideal performance of a microarray strictly depends on the way probes are tethered to the surface since it influences the way they interact with the complementary target. The N, N-dimethylacrylamide-based polymeric coating introduced by our research group in 2004 has already proven to offer great flexibility for the customization of surface properties; here, we demonstrate that it also represents the perfect scaffold for the modulation of probe grafting. With this aim in mind, polymers with increasing concentrations of N-acryloyloxysuccinimide (NAS) were synthesized and the coating procedure optimized accordingly. These were then tested not only in DNA microarray assays, but also using protein probes (with different MWs) to establish which formulation improves the assay performance in specific applications. The flexibility of this polymeric platform allowed us also to investigate a different immobilization chemistry-specifically, click chemistry reactions, thanks to the insertion of azide groups into the polymer chains-and to evaluate possible differences generated by this modification.

Computational Epitope Prediction and Design for Antibody Development and Detection

The design of optimized protein antigens is a fundamental step in the development of new vaccine candidates and in the detection of therapeutic antibodies. A fundamental prerequisite is the identification of antigenic regions that are most prone to interact with antibodies, namely, B-cell epitopes. Here, we describe an efficient structure-based computational method for epitope prediction, called MLCE. In this approach, all that is required is the 3D structure of the antigen of interest. MLCE can be applied to glycosylated proteins, facilitating the identification of immunoreactive versus immune-shielding carbohydrates.

Membrane-Sensing Peptides for Extracellular Vesicle Analysis

Analytical platforms for small extracellular vesicle (sEV) high-throughput analysis are highly desirable. These bionanoparticles present fairly distinctive lipid membrane features including high curvature, lipid-packing defects, and a relative abundance in lipids. sEV membrane could be considered as a "universal" marker, complementary or alternative to traditional surface-associated proteins. Here, we describe the use of membrane-sensing peptides as a new, highly efficient ligand to directly integrate sEV capturing and analysis on a microarray platform.

Peptide Microarrays for Studying Autoantibodies in Neurological Disease

Antibody-mediated neurological diseases constitute an emerging clinical entity that remains to be fully explored. Recent studies identified autoantibodies that directly confer pathogenicity, and it was shown that in these cases immunotherapies can result in profound positive patient responses. These advances highlight the urgent need for improved means to effectively screen patient samples for novel autoantibodies (aAbs) and their subsequent characterization. Here, we discuss challenges and opportunities for peptide microarrays to contribute to the identification, mapping, and characterization of the underlying monospecific disease-defining binding surfaces. We outline control experiments, workflow modifications and bioinformatic filtering methods that enhance the predictive power of array-based studies. Further, we highlight experimental and computer-based display approaches that have the potential to expand the use of synthetic microarrays over the detection of discontinuous epitopes. Knowledge over the autoantibody epitopes in neurological disease will enhance our understanding of the pathological mechanisms and thereby potentially contribute to novel diagnostic approaches or even innovative antigen-specific treatments that avoid the serious adverse effects seen with currently used immunosuppressive therapies.

Peptide Microarrays for Flavivirus Diagnosis

Flavivirus are the most alarming prevalent viruses worldwide due to its vast impact on public health. Most early symptoms of diseases caused by Flavivirus are similar among each other and to other febrile illnesses making the clinical differential diagnosis challenging. In addition, due to cross-reactivity and a relatively limited persistence of viral RNA in infected individuals, the current available diagnosis strategies fail to efficiently provide a differential viral identification. In this context, virus-specific tests are essential to improve patient care, as well as to facilitate disease surveillance and the effective control of transmission. Here, we describe the use of protein microarrays as an effective tool for screening peptides differentially recognized by anti-Yellow Fever virus antibodies induced by vaccination or by natural viral infection.

Epitope Mapping on Microarrays Highlights a Sequence on the N Protein with Strong Immune Response in SARS-CoV-2 Patients

In SARS-CoV-2 pandemic scenario, the identification of rapid methods to detect antibodies against coronavirus has been a wide and urgent issue. Epitope mapping on peptide microarrays is a rapid way to identify sequences with a high immunoreactivity. The process begins with a proteome-wide screening, based on immune affinity; the use of a high-density microarray is followed by a validation phase, where a restricted panel of probes is tested using peptide microarrays; peptide sequences are immobilized through a click-based strategy.COVID-19-positive sera are tested and immuno-domains regions are identified on SARS-CoV-2 spike (S), nucleocapsid (N) protein, and Orf1ab polyprotein. An epitope on N protein (region 155-171) provided good diagnostic performance in discriminating COVID-19-positive vs. healthy individuals. Using this sequence, 92% sensitivity and 100% specificity are reached for IgG detection in COVID-19 samples, and no cross-reactivity with common cold coronaviruses is detected. Overall, epitope 155-171 from N protein represents a promising candidate for further development and rapid implementation in serological tests.

Evaluation of docking procedures reliability in affitins-partners interactions

Affitins constitute a class of small proteins belonging to Sul7d family, which, in microorganisms such as Sulfolobus acidocaldarius, bind DNA preventing its denaturation. Thanks to their stability and small size (60–66 residues in length) they have been considered as ideal candidates for engineering and have been used for more than 10 years now, for different applications. The individuation of a mutant able to recognize a specific target does not imply the knowledge of the binding geometry between the two proteins. However, its identification is of undoubted importance but not always experimentally accessible. For this reason, computational approaches such as protein-protein docking can be helpful for an initial structural characterization of the complex. This method, which produces tens of putative binding geometries ordered according to a binding score, needs to be followed by a further reranking procedure for finding the most plausible one. In the present paper, we use the server ClusPro for generating docking models of affitins with different protein partners whose experimental structures are available in the Protein Data Bank. Then, we apply two protocols for reranking the docking models. The first one investigates their stability by means of Molecular Dynamics simulations; the second one, instead, compares the docking models with the interacting residues predicted by the Matrix of Local Coupling Energies method. Results show that the more efficient way to deal with the reranking problem is to consider the information given by the two protocols together, i.e. employing a consensus approach.

Elucidating the 3D Structure of a Surface Membrane Antigen from Trypanosoma cruzi as a Serodiagnostic Biomarker of Chagas Disease

Chagas disease (CD) is a vector-borne parasitosis, caused by the protozoan parasite Trypanosoma cruzi, that affects millions of people worldwide. Although endemic in South America, CD is emerging throughout the world due to climate change and increased immigratory flux of infected people to non-endemic regions. Containing of the diffusion of CD is challenged by the asymptomatic nature of the disease in early infection stages and by the lack of a rapid and effective diagnostic test. With the aim of designing new serodiagnostic molecules to be implemented in a microarray-based diagnostic set-up for early screening of CD, herein, we report the recombinant production of the extracellular domain of a surface membrane antigen from T. cruzi (TcSMP) and confirm its ability to detect plasma antibodies from infected patients. Moreover, we describe its high-resolution (1.62 Å) crystal structure, to which in silico epitope predictions were applied in order to locate the most immunoreactive regions of TcSMP in order to guide the design of epitopes that may be used as an alternative to the full-length antigen for CD diagnosis. Two putative, linear epitopes, belonging to the same immunogenic region, were synthesized as free peptides, and their immunological properties were tested in vitro. Although both peptides were shown to adopt a structural conformation that allowed their recognition by polyclonal antibodies raised against the recombinant protein, they were not serodiagnostic for T. cruzi infections. Nevertheless, they represent good starting points for further iterative structure-based (re)design cycles.

SARS-CoV-2 Spike Protein Mutations and Escape from Antibodies: A Computational Model of Epitope Loss in Variants of Concern

The SARS-CoV-2 spike (S) protein is exposed on the viral surface and is the first point of contact between the virus and the host. For these reasons it represents the prime target for Covid-19 vaccines. In recent months, variants of this protein have started to emerge. Their ability to reduce or evade recognition by S-targeting antibodies poses a threat to immunological treatments and raises concerns for their consequences on vaccine efficacy. To develop a model able to predict the potential impact of S-protein mutations on antibody binding sites, we performed unbiased multi-microsecond molecular dynamics of several glycosylated S-protein variants and applied a straightforward structure-dynamics-energy based strategy to predict potential changes in immunogenic regions on each variant. We recover known epitopes on the reference D614G sequence. By comparing our results, obtained on isolated S-proteins in solution, to recently published data on antibody binding and reactivity in new S variants, we directly show that modifications in the S-protein consistently translate into the loss of potentially immunoreactive regions. Our findings can thus be qualitatively reconnected to the experimentally characterized decreased ability of some of the Abs elicited against the dominant S-sequence to recognize variants. While based on the study of SARS-CoV-2 spike variants, our computational epitope-prediction strategy is portable and could be applied to study immunoreactivity in mutants of proteins of interest whose structures have been characterized, helping the development/selection of vaccines and antibodies able to control emerging variants.

Recent progresses and remaining challenges for the detection of Zika virus

Zika virus (ZIKV) has emerged as a particularly notorious mosquito-borne flavivirus, which can lead to a devastating congenital syndrome in the fetuses of pregnant mothers (e.g., microcephaly, spasticity, craniofacial disproportion, miscarriage, and ocular abnormalities) and cause the autoimmune disorder Guillain-Barre' syndrome of adults. Due to its severity and rapid dispersal over several continents, ZIKV has been acknowledged to be a global health concern by the World Health Organization. Unfortunately, the ZIKV has recently resurged in India with the potential for devastating effects. Researchers from all around the world have worked tirelessly to develop effective detection strategies and vaccines for the prevention and control of ZIKV infection. In this review, we comprehensively summarize the most recent research into ZIKV, including the structural biology and evolution, historical overview, pathogenesis, symptoms, and transmission. We then focus on the detection strategies for ZIKV, including viral isolation, serological assays, molecular assays, sensing methods, reverse transcription loop mediated isothermal amplification, transcription-mediated amplification technology, reverse transcription strand invasion based amplification, bioplasmonic paper-based device, and reverse transcription isothermal recombinase polymerase amplification. To conclude, we examine the limitations of currently available strategies for the detection of ZIKV, and outline future opportunities and research challenges.

SARS-CoV-2 Epitope Mapping on Microarrays Highlights Strong Immune-Response to N Protein Region

A workflow for rapid SARS-CoV-2 epitope discovery on peptide microarrays is herein reported. The process started with a proteome-wide screening of immunoreactivity based on the use of a high-density microarray followed by a refinement and validation phase on a restricted panel of probes using microarrays with tailored peptide immobilization through a click-based strategy. Progressively larger, independent cohorts of Covid-19 positive sera were tested in the refinement processes, leading to the identification of immunodominant regions on SARS-CoV-2 spike (S), nucleocapsid (N) protein and Orf1ab polyprotein. A summary study testing 50 serum samples highlighted an epitope of the N protein (region 155-71) providing good diagnostic performance in discriminating Covid-19 positive vs. healthy individuals. Using this epitope, 92% sensitivity and 100% specificity were reached for IgG detection in Covid-19 samples, and no cross-reactivity with common cold coronaviruses was detected. Likewise, IgM immunoreactivity in samples collected within the first month after symptoms onset showed discrimination ability. Overall, epitope 155-171 from N protein represents a promising candidate for further development and rapid implementation in serological tests.

Rapid Response to Pandemic Threats: Immunogenic Epitope Detection of Pandemic Pathogens for Diagnostics and Vaccine Development Using Peptide Microarrays

Emergence and re-emergence of pathogens bearing the risk of becoming a pandemic threat are on the rise. Increased travel and trade, growing population density, changes in urbanization, and climate have a critical impact on infectious disease spread. Currently, the world is confronted with the emergence of a novel coronavirus SARS-CoV-2, responsible for yet more than 800 000 deaths globally. Outbreaks caused by viruses, such as SARS-CoV-2, HIV, Ebola, influenza, and Zika, have increased over the past decade, underlining the need for a rapid development of diagnostics and vaccines. Hence, the rational identification of biomarkers for diagnostic measures on the one hand, and antigenic targets for vaccine development on the other, are of utmost importance. Peptide microarrays can display large numbers of putative target proteins translated into overlapping linear (and cyclic) peptides for a multiplexed, high-throughput antibody analysis. This enabled for example the identification of discriminant/diagnostic epitopes in Zika or influenza and mapping epitope evolution in natural infections versus vaccinations. In this review, we highlight synthesis platforms that facilitate fast and flexible generation of high-density peptide microarrays. We further outline the multifaceted applications of these peptide array platforms for the development of serological tests and vaccines to quickly encounter pandemic threats.

The Answer Lies in the Energy: How Simple Atomistic Molecular Dynamics Simulations May Hold the Key to Epitope Prediction on the Fully Glycosylated SARS-CoV-2 Spike Protein

SARS-CoV-2 is a health threat with dire socioeconomical consequences. As the crucial mediator of infection, the viral glycosylated spike protein (S) has attracted the most attention and is at the center of efforts to develop therapeutics and diagnostics. Herein, we use an original decomposition approach to identify energetically uncoupled substructures as antibody binding sites on the fully glycosylated S. Crucially, all that is required are unbiased MD simulations; no prior knowledge of binding properties or ad hoc parameter combinations is needed. Our results are validated by experimentally confirmed structures of S in complex with anti- or nanobodies. We identify poorly coupled subdomains that are poised to host (several) epitopes and potentially involved in large functional conformational transitions. Moreover, we detect two distinct behaviors for glycans: those with stronger energetic coupling are structurally relevant and protect underlying peptidic epitopes, and those with weaker coupling could themselves be prone to antibody recognition.

Clickable cellulosic surfaces for peptide-based bioassays

The use of peptides in paper-based analytics is a highly appealing field, yet it suffers from severe limitations. This is mostly due to the loss of effective target recognition properties of this relatively small probes upon nonspecific adsorption onto cellulose substrates. Here we address this issue by introducing a simple polymer-based strategy to obtain clickable cellulose surfaces, that we exploited for the chemoselective bioconjugation of peptide bioprobes. Our method largely outperformed standard adsorption-based immobilization strategy in a challenging, real case immunoassay, namely the diagnostic discrimination of Zika + individuals from healthy controls. Of note, the clickable polymeric coating not only allows efficient peptides bioconjugation, but it provides favorable anti-fouling properties to the cellulosic support. We envisage our strategy to broaden the repertoire of cellulosic materials manipulation and promote a renewed interest in peptide-based paper bioassays.

Computational Analysis of Dengue Virus Envelope Protein (E) Reveals an Epitope with Flavivirus Immunodiagnostic Potential in Peptide Microarrays

The mosquito-borne viral disease caused by the Dengue virus is an expanding global threat. Diagnosis in low-resource-settings and epidemiological surveillance urgently requires new immunoprobes for serological tests. Structure-based epitope prediction is an efficient method to design diagnostic peptidic probes able to reveal specific antibodies elicited in response to infections in patients’ sera. In this study, we focused on the Dengue viral envelope protein (E); computational analyses ranging from extensive Molecular Dynamics (MD) simulations and energy-decomposition-based prediction of potentially immunoreactive regions identified putative epitope sequences. Interestingly, one such epitope showed internal dynamic and energetic properties markedly different from those of other predicted sequences. The epitope was thus synthesized as a linear peptide, modified for chemoselective immobilization on microarrays and used in a serological assay to discriminate Dengue-infected individuals from healthy controls. The synthetic epitope probe showed a diagnostic performance comparable to that of the full antigen in terms of specificity and sensitivity. Given the high level of sequence identity among different flaviviruses, the epitope was immune-reactive towards Zika-infected sera as well. The results are discussed in the context of the quest for new possible structure-dynamics-based rules for the prediction of the immunoreactivity of selected antigenic regions with potential pan-flavivirus immunodiagnostic capacity.

Peptides for Infectious Diseases: From Probe Design to Diagnostic Microarrays

Peptides and peptidomimetics have attracted revived interest regarding their applications in chemical biology over the last few years. Their chemical versatility, synthetic accessibility and the ease of storage and management compared to full proteins have made peptides particularly interesting in diagnostic applications, where they proved to efficiently recapitulate the molecular recognition properties of larger protein antigens, and were proven to be able to capture antibodies circulating in the plasma and serum of patients previously exposed to bacterial or viral infections. Here, we describe the development, integration and application of strategies for computational prediction and design, advanced chemical synthesis, and diagnostic deployment in multiplexed assays of peptide-based materials which are able to bind antibodies of diagnostic as well as therapeutic interest. By presenting successful applications of such an integrated strategy, we argue that they will have an ever-increasing role in both basic and clinical realms of research, where important advances can be expected in the next few years.

Towards precision medicine: the role and potential of protein and peptide microarrays

Techniques to comprehensively analyze protein signatures are pivotal to unravel disease mechanisms, develop novel biomarkers and targeted therapies. In this frame, protein and peptide microarrays can play a major role in fuelling precision medicine.

Targeting Difficult Protein-Protein Interactions with Plain and General Computational Approaches

Investigating protein-protein interactions (PPIs) holds great potential for therapeutic applications, since they mediate intricate cell signaling networks in physiological and disease states. However, their complex and multifaceted nature poses a major challenge for biochemistry and medicinal chemistry, thereby limiting the druggability of biological partners participating in PPIs. Molecular Dynamics (MD) provides a solid framework to study the reciprocal shaping of proteins’ interacting surfaces. Here, we review successful applications of MD-based methods developed in our group to predict interfacial areas involved in PPIs of pharmaceutical interest. We report two interesting examples of how structural, dynamic and energetic information can be combined into efficient strategies which, complemented by experiments, can lead to the design of new small molecules with promising activities against cancer and infections. Our advances in targeting key PPIs in angiogenic pathways and antigen-antibody recognition events will be discussed for their role in drug discovery and chemical biology.