Single amino acid fingerprinting of the human antibody repertoire with high density peptide arrays

Serum antibody fingerprinting of SARS-CoV-2 variants in infected and vaccinated subjects by label-free microarray biosensor

Both viral infection and vaccination affect the antibody repertoire of a person. Here, we demonstrate that the analysis of serum antibodies generates information not only on the virus type that caused the infection but also on the specific virus variant. We developed a rapid multiplex assay providing a fingerprint of serum antibodies against five different SARS-CoV-2 variants based on a microarray of virus antigens immobilized on the surface of a label-free reflectometric biosensor. We analyzed serum from the plasma of convalescent subjects and vaccinated volunteers and extracted individual antibody profiles of both total immunoglobulin Ig and IgA fractions. We found that Ig level profiles were strongly correlated with the specific variant of infection or vaccination and that vaccinated subjects displayed a larger quantity of total Ig and a lower fraction of IgA relative to the population of convalescent unvaccinated subjects.

Highly heterogenous humoral immune response in Lyme disease patients revealed by broad machine learning-assisted antibody binding profiling with random peptide arrays

Introduction

Lyme disease (LD), a rapidly growing public health problem in the US, represents a formidable challenge due to the lack of detailed understanding about how the human immune system responds to its pathogen, the Borrelia burgdorferi bacterium. Despite significant advances in gaining deeper insight into mechanisms the pathogen uses to evade immune response, substantial gaps remain. As a result, molecular tools for the disease diagnosis are lacking with the currently available tests showing poor performance. High interpersonal variability in immune response combined with the ability of the pathogen to use a number of immune evasive tactics have been implicated as underlying factors for the limited test performance.

Methods

This study was designed to perform a broad profiling of the entire repertoire of circulating antibodies in human sera at the single-individual level using planar arrays of short linear peptides with random sequences. The peptides sample sparsely, but uniformly the entire combinatorial sequence space of the same length peptides for profiling the humoral immune response to a B.burg. infection and compare them with other diseases with etiology similar to LD and healthy controls.

Results

The study revealed substantial variability in antibody binding profiles between individual LD patients even to the same antigen (VlsE protein) and strong similarity between individuals diagnosed with Lyme disease and healthy controls from the areas endemic to LD suggesting a high prevalence of seropositivity in endemic healthy control.

Discussion

This work demonstrates the utility of the approach as a valuable analytical tool for agnostic profiling of humoral immune response to a pathogen.

Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping and sequence analysis

Here, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses. Applying a high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses allowed identification of B cell epitopes and relate them to their evolutionary and structural properties. We identify hotspots of pre-existing immunity and identify cross-reactive epitopes that contribute to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves, and SARS-CoV-2 variants. Lastly, we show that mutations in spike and nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.

Modeling the sequence dependence of differential antibody binding in the immune response to infectious disease

Past studies have shown that incubation of human serum samples on high density peptide arrays followed by measurement of total antibody bound to each peptide sequence allows detection and discrimination of humoral immune responses to a variety of infectious diseases. This is true even though these arrays consist of peptides with near-random amino acid sequences that were not designed to mimic biological antigens. This "immunosignature" approach, is based on a statistical evaluation of the binding pattern for each sample but it ignores the information contained in the amino acid sequences that the antibodies are binding to. Here, similar array-based antibody profiles are instead used to train a neural network to model the sequence dependence of molecular recognition involved in the immune response of each sample. The binding profiles used resulted from incubating serum from 5 infectious disease cohorts (Hepatitis B and C, Dengue Fever, West Nile Virus and Chagas disease) and an uninfected cohort with 122,926 peptide sequences on an array. These sequences were selected quasi-randomly to represent an even but sparse sample of the entire possible combinatorial sequence space (~1012). This very sparse sampling of combinatorial sequence space was sufficient to capture a statistically accurate representation of the humoral immune response across the entire space. Processing array data using the neural network not only captures the disease-specific sequence-binding information but aggregates binding information with respect to sequence, removing sequence-independent noise and improving the accuracy of array-based classification of disease compared with the raw binding data. Because the neural network model is trained on all samples simultaneously, a highly condensed representation of the differential information between samples resides in the output layer of the model, and the column vectors from this layer can be used to represent each sample for classification or unsupervised clustering applications.

Resemblance-Ranking Peptide Library to Screen for Binders to Antibodies on a Peptidomic Scale

A novel resemblance-ranking peptide library with 160,000 10-meric peptides was designed to search for selective binders to antibodies. The resemblance-ranking principle enabled the selection of sequences that are most similar to the human peptidome. The library was synthesized with ultra-high-density peptide arrays. As proof of principle, screens for selective binders were performed for the therapeutic anti-CD20 antibody rituximab. Several features in the amino acid composition of antibody-binding peptides were identified. The selective affinity of rituximab increased with an increase in the number of hydrophobic amino acids in a peptide, mainly tryptophan and phenylalanine, while a total charge of the peptide remained relatively small. Peptides with a higher affinity exhibited a lower sum helix propensity. For the 30 strongest peptide binders, a substitutional analysis was performed to determine dissociation constants and the invariant amino acids for binding to rituximab. The strongest selective peptides had a dissociation constant in the hundreds of the nano-molar range. The substitutional analysis revealed a specific hydrophobic epitope for rituximab. To show that conformational binders can, in principle, be detected in array format, cyclic peptide substitutions that are similar to the target of rituximab were investigated. Since the specific binders selected via the resemblance-ranking peptide library were based on the hydrophobic interactions that are widespread in the world of biomolecules, the library can be used to screen for potential linear epitopes that may provide information about the cross-reactivity of antibodies.

Scoping review of the applications of peptide microarrays on the fight against human infections

INTRODUCTION

This scoping review explores the use of peptide microarrays in the fight against infectious diseases. The research domains explored included the use of peptide microarrays in the mapping of linear B-cell and T cell epitopes, antimicrobial peptide discovery, immunosignature characterisation and disease immunodiagnostics. This review also provides a short overview of peptide microarray synthesis.

METHODS

Electronic databases were systematically searched to identify relevant studies. The review was conducted using the Joanna Briggs Institute methodology for scoping reviews and data charting was performed using a predefined form. The results were reported by narrative synthesis in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews guidelines.

RESULTS

Ninety-five articles from 103 studies were included in the final data charting process. The majority (92. 0%) of the articles were published during 2010-2020 and were mostly from Europe (44.2%) and North America (34.7%). The findings were from the investigation of viral (45.6%), bacterial (32. 0%), parasitic (23.3%) and fungal (2. 0%) infections. Out of the serological studies, IgG was the most reported antibody type followed by IgM. The largest portion of the studies (77.7%) were related to mapping B-cell linear epitopes, 5.8% were on diagnostics, 5.8% reported on immunosignature characterisation and 8.7% reported on viral and bacterial cell binding assays. Two studies reported on T-cell epitope profiling.

CONCLUSION

The most important application of peptide microarrays was found to be B-cell epitope mapping or antibody profiling to identify diagnostic and vaccine targets. Immunosignatures identified by random peptide microarrays were found to be applied in the diagnosis of infections and interrogation of vaccine responses. The analysis of the interactions of random peptide microarrays with bacterial and viral cells using binding assays enabled the identification of antimicrobial peptides. Peptide microarray arrays were also used for T-cell linear epitope mapping which may provide more information for the design of peptide-based vaccines and for the development of diagnostic reagents.

Mapping antibody binding using multiplexed epitope substitution analysis

A more complete understanding of antibody epitopes would aid the development of diagnostics, therapeutic antibodies, and vaccines. However, current methods for mapping antibody binding to epitopes require a targeted experimental approach, which limits throughput. To address these limitations, we developed Multiplexed Epitope Substitution Analysis (MESA) which can rapidly characterize various distinct epitopes using millions of antibody-binding peptides. We screened peptides from a random 12-mer library that bound to human serum antibody repertoires and determined their sequences using next-generation sequencing (NGS). Computationally, we divided target epitope sequences into overlapping k-mer subsequences and substituted the positions in each k-mer with all 20 amino acids, mimicking a saturation mutagenesis. We then determined enrichments of the substituted k-mers in the screened peptide dataset and used these enrichments to identify substitutions favored for binding at each position in the target epitope, ultimately revealing the precise binding motif. To validate MESA, we determined binding motifs for monoclonal antibodies spiked into serum, recovering the expected binding positions and amino acid preferences. To characterize epitopes bound by a population, we analyzed 50 serum specimens to determine the binding motifs within various target epitopes from common pathogens. Additionally, by analyzing various HSV-1 glycoprotein epitopes, MESA revealed unique binding signatures for HSV-1 seropositive specimens and demonstrated the variability of binding signatures within a population. These results demonstrate that MESA can rapidly identify and characterize binding motifs for an unlimited number of epitopes from a single experiment, accelerating discoveries and enhancing our understanding of antibody-epitope interactions.

Identification of a Zika NS2B epitope as a biomarker for severe clinical phenotypes

The identification of specific biomarkers for Zika infection and its clinical complications is fundamental to mitigate the infection spread, which has been associated with a broad range of neurological sequelae. We present the characterization of antibody responses in serum samples from individuals infected with Zika, presenting non-severe (classical) and severe (neurological disease) phenotypes, with high-density peptide arrays comprising the Zika NS1 and NS2B proteins. The data pinpoints one strongly IgG-targeted NS2B epitope in non-severe infections, which is absent in Zika patients, where infection progressed to the severe phenotype. This differential IgG profile between the studied groups was confirmed by multivariate data analysis. Molecular dynamics simulations and circular dichroism have shown that the peptide in solution presents itself in a sub-optimal conformation for antibody recognition, which led us to computationally engineer an artificial protein able to stabilize the NS2B epitope structure. The engineered protein was used to interrogate paired samples from mothers and their babies presenting Zika-associated microcephaly and confirmed the absence of NS2B IgG response in those samples. These findings suggest that the assessment of antibody responses to the herein identified NS2B epitope is a strong candidate biomarker for the diagnosis and prognosis of Zika-associated neurological disease.

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.

Production of high-complexity frameshift neoantigen peptide microarrays

Parallel measurement of large numbers of antigen-antibody interactions are increasingly enabled by peptide microarray technologies. Our group has developed an in situ synthesized peptide microarray of >400 000 frameshift neoantigens using mask-based photolithographic peptide synthesis, to profile patient specific neoantigen reactive antibodies in a single assay. The system produces 208 replicate mircoarrays per wafer and is capable of producing multiple wafers per synthetic lot to routinely synthesize over 300 million peptides simultaneously. In this report, we demonstrate the feasibility of the system for detecting peripheral-blood antibody binding to frameshift neoantigens across multiple synthetic lots.

Epitopes of Naturally Acquired and Vaccine-Induced Anti-Ebola Virus Glycoprotein Antibodies in Single Amino Acid Resolution

The Ebola virus (EBOV) can cause severe infections in humans, leading to a fatal outcome in a high percentage of cases. Neutralizing antibodies against the EBOV surface glycoprotein (GP) can prevent infections, demonstrating a straightforward way for an efficient vaccination strategy. Meanwhile, many different anti-EBOV antibodies have been identified, whereas the exact binding epitopes are often unknown. Here, the analysis of serum samples from an EBOV vaccine trial with the recombinant vesicular stomatitis virus-Zaire ebolavirus (rVSV-ZEBOV) and an Ebola virus disease survivor, using high-density peptide arrays, is presented. In this proof-of-principle study, distinct IgG and IgM antibodies binding to different epitopes of EBOV GP is detected: By mapping the whole GP as overlapping peptide fragments, new epitopes and confirmed epitopes from the literature are found. Furthermore, the highly selective binding epitope of a neutralizing monoclonal anti-EBOV GP antibody could be validated. This shows that peptide arrays can be a valuable tool to study the humoral immune response to vaccines in patients and to support Ebola vaccine development.

Multivalent glycan arrays

Glycan microarrays have become a powerful technology to study biological processes, such as cell-cell interaction, inflammation, and infections. Yet, several challenges, especially in multivalent display, remain. In this introductory lecture we discuss the state-of-the-art glycan microarray technology, with emphasis on novel approaches to access collections of pure glycans and their immobilization on surfaces. Future directions to mimic the natural glycan presentation on an array format, as well as in situ generation of combinatorial glycan collections, are discussed.

Diagnostic Profiling of the Human Public IgM Repertoire With Scalable Mimotope Libraries

Specific antibody reactivities are routinely used as biomarkers, but the antibody repertoire reactivity (igome) profiles are still neglected. Here, we propose rationally designed peptide arrays as efficient probes for these system level biomarkers. Most IgM antibodies are characterized by few somatic mutations, polyspecificity, and physiological autoreactivity with housekeeping function. Previously, probing this repertoire with a set of immunodominant self-proteins provided a coarse analysis of the respective repertoire profiles. In contrast, here, we describe the generation of a peptide mimotope library that reflects the common IgM repertoire of 10,000 healthy donors. In addition, an appropriately sized subset of this quasi-complete mimotope library was further designed as a potential diagnostic tool. A 7-mer random peptide phage display library was panned on pooled human IgM. Next-generation sequencing of the selected phage yielded 224,087 sequences, which clustered in 790 sequence clusters. A set of 594 mimotopes, representative of the most significant sequence clusters, was shown to probe symmetrically the space of IgM reactivities in patients' sera. This set of mimotopes can be easily scaled including a greater proportion of the mimotope library. The trade-off between the array size and the resolution can be explored while preserving the symmetric sampling of the mimotope sequence and reactivity spaces. BLAST search of the non-redundant protein database with the mimotopes sequences yielded significantly more immunoglobulin J region hits than random peptides, indicating a considerable idiotypic connectivity of the targeted igome. The proof of principle predictors for random diagnoses was represented by profiles of mimotopes. The number of potential reactivity profiles that can be extracted from this library is estimated at more than 10⁷⁰. Thus, a quasi-complete IgM mimotope library and a scalable representative subset thereof are found to address very efficiently the dynamic diversity of the human public IgM repertoire, providing informationally dense and structurally interpretable IgM reactivity profiles.

A general approach for predicting protein epitopes targeted by antibody repertoires using whole proteomes

Antibodies are essential to functional immunity, yet the epitopes targeted by antibody repertoires remain largely uncharacterized. To aid in characterization, we developed a generalizable strategy to predict antibody-binding epitopes within individual proteins and entire proteomes. Specifically, we selected antibody-binding peptides for 273 distinct sera out of a random library and identified the peptides using next-generation sequencing. To predict antibody-binding epitopes and the antigens from which these epitopes were derived, we tiled the sequences of candidate antigens into short overlapping subsequences of length k (k-mers). We used the enrichment over background of these k-mers in the antibody-binding peptide dataset to predict antibody-binding epitopes. As a positive control, we used this approach, termed K-mer Tiling of Protein Epitopes (K-TOPE), to predict epitopes targeted by monoclonal and polyclonal antibodies of well-characterized specificity, accurately recovering their known epitopes. K-TOPE characterized a commonly targeted antigen from Rhinovirus A, predicting four epitopes recognized by antibodies present in 87% of sera (n = 250). An analysis of 2,908 proteins from 400 viral taxa that infect humans predicted seven enterovirus epitopes and five Epstein-Barr virus epitopes recognized by >30% of specimens. Analysis of Staphylococcus and Streptococcus proteomes similarly predicted 22 epitopes recognized by >30% of specimens. Twelve of these common viral and bacterial epitopes agreed with previously mapped epitopes with p-values < 0.05. Additionally, we predicted 30 HSV2-specific epitopes that were 100% specific against HSV1 in novel and previously reported antigens. Experimentally validating these candidate epitopes could help identify diagnostic biomarkers, vaccine components, and therapeutic targets. The K-TOPE approach thus provides a powerful new tool to elucidate the organisms, antigens, and epitopes targeted by human antibody repertoires.

Renaissance Distribution for Statistically Failed Experiments

Much of the experimental data, especially in life sciences, is considered to be useless if it demonstrates a large standard deviation from the mean value. The Renaissance distribution, as presented in this study, allows one to extract true values from such statistical data with large noise. To obtain proof of the Renaissance distribution, high-throughput synthesis of deep substitutions for a target amino acid sequence was performed, and the known epitope was identified in assay with human serum antibodies. In addition, the Renaissance distribution was shown to approach the epitope affinity maturation by the deep alanine substitution. The Renaissance distribution may have an impact in the development of novel specific drugs.

High-density Peptide Arrays Help to Identify Linear Immunogenic B-cell Epitopes in Individuals Naturally Exposed to Malaria Infection

High-density peptide arrays are an excellent means to profile anti-plasmodial antibody responses. Different protein intrinsic epitopes can be distinguished, and additional insights are gained, when compared with assays involving the full-length protein. Distinct reactivities to specific epitopes within one protein may explain differences in published results, regarding immunity or susceptibility to malaria. We pursued three approaches to find specific epitopes within important plasmodial proteins, (1) twelve leading vaccine candidates were mapped as overlapping 15-mer peptides, (2) a bioinformatical approach served to predict immunogenic malaria epitopes which were subsequently validated in the assay, and (3) randomly selected peptides from the malaria proteome were screened as a control. Several peptide array replicas were prepared, employing particle-based laser printing, and were used to screen 27 serum samples from a malaria-endemic area in Burkina Faso, West Africa. The immunological status of the individuals was classified as "protected" or "unprotected" based on clinical symptoms, parasite density, and age. The vaccine candidate screening approach resulted in significant hits in all twelve proteins and allowed us (1) to verify many known immunogenic structures, (2) to map B-cell epitopes across the entire sequence of each antigen and (3) to uncover novel immunogenic epitopes. Predicting immunogenic regions in the proteome of the human malaria parasite Plasmodium falciparum, via the bioinformatics approach and subsequent array screening, confirmed known immunogenic sequences, such as in the leading malaria vaccine candidate CSP and discovered immunogenic epitopes derived from hypothetical or unknown proteins.

Vertical Scanning Interferometry for Label-Free Detection of Peptide-Antibody Interactions

Peptide microarrays are a fast-developing field enabling the mapping of linear epitopes in the immune response to vaccinations or diseases and high throughput studying of protein-protein interactions. In this respect, a rapid label-free measurement of protein layer topographies in the array format is of great interest but is also a great challenge due to the extremely low aspect ratios of the peptide spots. We have demonstrated the potential of vertical scanning interferometry (VSI) for a detailed morphological analysis of peptide arrays and binding antibodies. The VSI technique is shown to scan an array area of 5.1 square millimeters within 3–4 min at a resolution of 1.4 μm lateral and 0.1 nm vertical in the full automation mode. Topographies obtained by VSI do match the one obtained by AFM measurements, demonstrating the accuracy of the technique. A detailed topology of peptide-antibody layers on single spots was measured. Two different measurement regions are distinguished according to the antibody concentration. In the case of weakly diluted serum, the thickness of the antibody layer is independent of the serum dilution and corresponds to the physical thickness of the accumulated antibody layer. In strongly diluted serum, the thickness measured via VSI is linearly proportional to the serum dilution.

Elastic reversible valves on centrifugal microfluidic platforms

Reversible valves on centrifugal microfluidic platforms facilitate the automation of bioanalytical assays, especially of those requiring a series of steps (such as incubation) in a single reaction chamber. In this study, we present fixed elastic reversible (FER) valves and tunable elastic reversible (TER) valves that are easy to fabricate, implement and control. In the FER valve the compression of an elastic barrier/patch against a microchamber's outlet prevents the release of liquid. The valve sealing pressure was determined by adjusting the engraving depth of the valve-seat at which the elastic patch was located, this allows to set the sealing pressure during disc fabrication. In the TER valve, the patch compression value and sealing pressure is controlled by the penetration depth of a plastic screw into the valve-seat. The ER valves prevent liquid flow until the centrifugal force overcomes their sealing pressure. Moreover, at a constant spin speed, turning the screw of a TER valve reduces its sealing pressure and opens the valve. Therefore, the TER valve allows for controlling of the liquid transfer volume at various spin speeds. The FER and TER valves' behavior is mathematically described and equations for the prediction of their operation under centrifugal forces are provided. As a point-of-care (POC) application of ER valves, we have developed a microfluidic disc with a series of TER valves and peptide microarrays for automated multiplexed detection of five different proteins from a single serum sample.

Serological Number for Characterization of Circulating Antibodies

The dissociation constant of the circulating IgG antibodies is suggested to be proportional to the partial concentrations of these antibodies in blood serum in equilibrium. This coefficient, called serological number, is a dimensionless parameter and may be equal for all antibodies in a serum. Based on the serological number, we derived the equilibrium equation of the humoral immune system which allows estimating the number of different binding motifs in a serum. This equation also allows estimating the number of binding motifs of posttranslational and conformational nature. The feasibility of measuring the serological number via peptide arrays was demonstrated. Fifteen peptides with unique binding motifs were incubated and stained with the blood serum of a healthy adult at different dilutions. From these experiments, the serological number was determined. The serological number may explain the pre-existing antibody response after vaccination.

Development of Neutralizing and Non-neutralizing Antibodies Targeting Known and Novel Epitopes of TcdB of Clostridioides difficile

Clostridioides difficile is the causative bacterium in 15-20% of all antibiotic associated diarrheas. The symptoms associated with C. difficile infection (CDI) are primarily induced by the two large exotoxins TcdA and TcdB. Both toxins enter target cells by receptor-mediated endocytosis. Although different toxin receptors have been identified, it is no valid therapeutic option to prevent receptor endocytosis. Therapeutics, such as neutralizing antibodies, directly targeting both toxins are in development. Interestingly, only the anti-TcdB antibody bezlotoxumab but not the anti-TcdA antibody actoxumab prevented recurrence of CDI in clinical trials. In this work, 31 human antibody fragments against TcdB were selected by antibody phage display from the human naive antibody gene libraries HAL9/10. These antibody fragments were further characterized by in vitro neutralization assays. The epitopes of the neutralizing and non-neutralizing antibody fragments were analyzed by domain mapping, TcdB fragment phage display, and peptide arrays, to identify neutralizing and non-neutralizing epitopes. A new neutralizing epitope within the glucosyltransferase domain of TcdB was identified, providing new insights into the relevance of different toxin regions in respect of neutralization and toxicity.

Phage display peptide libraries: deviations from randomness and correctives

Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications.

Enhancing the Microparticle Deposition Stability and Homogeneity on Planer for Synthesis of Self-Assembly Monolayer

The deposition stability and homogeneity of microparticles improved with mask, lengthened nozzle and flow rate adjustment. The microparticles can be used to encapsulate monomers, before the monomers in the microparticles can be deposited onto a substrate for nanoscale self-assembly. For the uniformity of the synthesized nanofilm, the homogeneity of the deposited microparticles becomes an important issue. Based on the ANSYS simulation results, the effects of secondary flow were minimized with a lengthened nozzle. The ANSYS simulation was also used to investigate the ring-vortex generation and why the ring vortex can be eliminated by adding a mask with an aperture between the nozzle and deposition substrate. The experimental results also showed that particle deposition with a lengthened nozzle was more stable, while adding the mask stabilized deposition and diminished the ring-vortex contamination. The effects of flow rate and pressure were also investigated. Hence, the deposition stability and homogeneity of microparticles was improved.

Peptide array functionalization via the Ugi four-component reaction

The Ugi four-component reaction was investigated as a tool for the functionalization of peptide arrays via post-synthetic side-chain modification, mimicking post-translational processes. Additionally, as a proof of concept for the synthesis of peptidomimetics on arrays, the integration of an Ugi unit into a growing peptide chain was demonstrated.

Identification of a Tetanus Toxin Specific Epitope in Single Amino Acid Resolution

Vaccinations are among the most potent tools to fight infectious diseases. However, cross-reactions are an ongoing problem and there is an urgent need to fully understand the mechanisms of the immune response. For the development of a methodological workflow, the linear epitopes in the immune response to the tetanus toxin is investigated in sera of 19 vaccinated Europeans applying epitope mapping with peptide arrays. The most prominent epitope, appearing in nine different sera (₉₂₃ IHLVNNESSEVIVHK₉₃₇ ), is investigated in a substitution analysis to identify the amino acids that are crucial for the binding of the corresponding antibody species - the antibody fingerprint. The antibody fingerprints of different individuals are compared and found to be strongly conserved (₉₂₉ ExxEVIVxK₉₃₇ ), which is astonishing considering the randomness of their development. Additionally, the corresponding antibody species is isolated from one serum with batch chromatography using the amino acid sequence of the identified epitope and the tetanus specificity of the isolated antibody is verified by ELISA. Studying antibody fingerprints with peptide arrays should be transferable to any kind of humoral immune response toward protein antigens. Furthermore, antibody fingerprints have shown to be highly disease-specific and, therefore, can be employed as reliable biomarkers enabling the study of cross-reacting antigens.

Rare, high-affinity mouse anti-PD-1 antibodies that function in checkpoint blockade, discovered using microfluidics and molecular genomics

Conventionally, mouse hybridomas or well-plate screening are used to identify therapeutic monoclonal antibody candidates. In this study, we present an alternative to hybridoma-based discovery that combines microfluidics, yeast single-chain variable fragment (scFv) display, and deep sequencing to rapidly interrogate and screen mouse antibody repertoires. We used our approach on six wild-type mice to identify 269 molecules that bind to programmed cell death protein 1 (PD-1), which were present at an average of 1 in 2,000 in the pre-sort scFv libraries. Two rounds of fluorescence-activated cell sorting (FACS) produced populations of PD-1-binding scFv with a mean enrichment of 800-fold, whereas most scFv present in the pre-sort mouse repertoires were de-enriched. Therefore, our work suggests that most of the antibodies present in the repertoires of immunized mice are not strong binders to PD-1. We observed clusters of related antibody sequences in each mouse following FACS, suggesting evolution of clonal lineages. In the pre-sort repertoires, these putative clonal lineages varied in both the complementary-determining region (CDR)3K and CDR3H, while the FACS-selected PD-1-binding subsets varied primarily in the CDR3H. PD-1 binders were generally not highly diverged from germline, showing 98% identity on average with germline V-genes. Some CDR3 sequences were discovered in more than one animal, even across different mouse strains, suggesting convergent evolution. We synthesized 17 of the anti-PD-1 binders as full-length monoclonal antibodies. All 17 full-length antibodies bound recombinant PD-1 with K_D < 500 nM (average = 62 nM). Fifteen of the 17 full-length antibodies specifically bound surface-expressed PD-1 in a FACS assay, and nine of the antibodies functioned as checkpoint inhibitors in a cellular assay. We conclude that our method is a viable alternative to hybridomas, with key advantages in comprehensiveness and turnaround time.

Antibody fingerprints in lyme disease deciphered with high density peptide arrays

Lyme disease is the most common tick-borne infectious disease in Europe and North America. Previous studies discovered the immunogenic role of a surface-exposed lipoprotein (VlsE) of Borreliella burgdorferi. We employed high density peptide arrays to investigate the antibody response to the VlsE protein in VlsE-positive patients by mapping the protein as overlapping peptides and subsequent in-depth epitope substitution analyses. These investigations led to the identification of antibody fingerprints represented by a number of key residues that are indispensable for the binding of the respective antibody. This approach allows us to compare the antibody specificities of different patients to the resolution of single amino acids. Our study revealed that the sera of VlsE-positive patients recognize different epitopes on the protein. Remarkably, in those cases where the same epitope is targeted, the antibody fingerprint is almost identical. Furthermore, we could correlate two fingerprints with human autoantigens and an Epstein-Barr virus epitope; yet, the link to autoimmune disorders seems unlikely and must be investigated in further studies. The other three fingerprints are much more specific for B. burgdorferi. Since antibody fingerprints of longer sequences have proven to be highly disease specific, our findings suggest that the fingerprints could function as diagnostic markers that can reduce false positive test results.