Peptide based diagnostics: Are random-sequence peptides more useful than tiling proteome sequences?

A Peptide Microarray Platform Approach for Discovery of Immunodominant Antibody Epitopes

Immunodominant epitope discovery platforms play an important role in identifying novel biomarkers for effective immunotherapies and diagnostics. Methods to analyze the B-cell repertoire have been improved both experimentally and computationally. We developed an enhanced peptide microarray platform to discover and subsequently screen immunodominant epitopes. We utilized SARS-Cov-2 IgG positive and negative samples as a proof-of-concept to demonstrate the power of these improved peptide microarrays. The method identified significantly discriminant epitopes that classify positive and negative samples with good performance both as single peptides and in combination. We provide the assay conditions and parameters that justify the use of peptide microarrays in the selection of high-affinity epitopes, and we directly compare peptide performance against proteins. The results suggest that this platform can be used to confidently identify immunodominant antiviral epitopes while also serving as a useful tool for high-volume screening.

An Optimized Protocol for the Synthesis of Peptides Containing trans-Cyclooctene and Bicyclononyne Dienophiles as Useful Multifunctional Bioorthogonal Probes

Despite the great advances in solid-phase peptide synthesis (SPPS), the incorporation of certain functional groups into peptide sequences is restricted by the compatibility of the building blocks with conditions used during SPPS. In particular, the introduction of highly reactive groups used in modern bioorthogonal reactions into peptides remains elusive. Here, we present an optimized synthetic protocol enabling installation of two strained dienophiles, trans-cyclooctene (TCO) and bicyclononyne (BCN), into different peptide sequences. The two groups enable fast and modular post-synthetic functionalization of peptides, as we demonstrate in preparation of peptide-peptide and peptide-drug conjugates. Due to the excellent biocompatibility, the click-functionalization of the peptides can be performed directly in live cells. We further show that the introduction of both clickable groups into peptides enables construction of smart, multifunctional probes that can streamline complex chemical biology experiments such as visualization and pull-down of metabolically labeled glycoconjugates. The presented strategy will find utility in construction of peptides for diverse applications, where high reactivity, efficiency and biocompatibility of the modification step is critical.

Investigating Complex Samples with Molograms of Low-Affinity Binders

In vitro diagnostics relies on the quantification of minute amounts of a specific biomolecule, called biomarker, from a biological sample. The majority of clinically relevant biomarkers for conditions beyond infectious diseases are detected by means of binding assays, where target biomarkers bind to a solid phase and are detected by biochemical or physical means. Nonspecifically bound biomolecules, the main source of variation in such assays, need to be washed away in a laborious process, restricting the development of widespread point-of-care diagnostics. Here, we show that a diffractometric assay provides a new, label-free possibility to investigate complex samples, such as blood plasma. A coherently arranged sub-micron pattern, that is, a peptide mologram, is created to demonstrate the insensitivity of this diffractometric assay to the unwanted masking effect of nonspecific interactions. In addition, using an array of low-affinity binders, we also demonstrate the feasibility of molecular profiling of blood plasma in real time and show that individual patients can be differentiated based on the binding kinetics of circulating proteins.

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.

Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens

The 2019 novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak has caused a large number of deaths, with thousands of confirmed cases worldwide. The present study followed computational approaches to identify B- and T-cell epitopes for the spike (S) glycoprotein of SARS-CoV-2 by its interactions with the human leukocyte antigen alleles. We identified 24 peptide stretches on the SARS-CoV-2 S protein that are well conserved among the reported strains. The S protein structure further validated the presence of predicted peptides on the surface, of which 20 are surface exposed and predicted to have reasonable epitope binding efficiency. The work could be useful for understanding the immunodominant regions in the surface protein of SARS-CoV-2 and could potentially help in designing some peptide-based diagnostics. Also, identified T-cell epitopes might be considered for incorporation in vaccine designs.

•

Determination of variability and average solvent accessibility.

•

Identification of the B- and T-cell epitopes for spike glycoprotein of SARS-CoV-2.

•

Interactions of B and T cell epitopes with the human leukocyte antigen alleles.

Antibody characterization using immunosignatures

Therapeutic monoclonal antibodies have the potential to work as biological therapeutics. OKT3, Herceptin, Keytruda and others have positively impacted healthcare. Antibodies evolved naturally to provide high specificity and high affinity once mature. These characteristics can make them useful as therapeutics. However, we may be missing characteristics that are not obvious. We present a means of measuring antibodies in an unbiased manner that may highlight therapeutic activity. We propose using a microarray of random peptides to assess antibody properties. We tested twenty-four different commercial antibodies to gain some perspective about how much information can be derived from binding antibodies to random peptide libraries. Some monoclonals preferred to bind shorter peptides, some longer, some preferred motifs closer to the C-term, some nearer the N-term. We tested some antibodies with clinical activity but whose function was blinded to us at the time. We were provided with twenty-one different monoclonal antibodies, thirteen mouse and eight human IgM. These antibodies produced a variety of binding patterns on the random peptide arrays. When unblinded, the antibodies with polyspecific binding were the ones with the greatest therapeutic activity. The protein target to these therapeutic monoclonals is still unknown but using common sequence motifs from the peptides we predicted several human and mouse proteins. The same five highest proteins appeared in both mouse and human lists.

A synthetic peptide analog of in silico-predicted immunogenic epitope unique to dengue virus serotype 2 NS1 antigen specifically binds immunoglobulin G antibodies raised in rabbits

Development of a serotyping-capable dengue detection test is hampered by the absence of an identified unique marker that can detect specific dengue virus (DENV) serotype. In the current commercially available antibody-capture diagnostic methods, immobilized nonstructural 1 (NS1) antigen indiscriminately binds and detects immunoglobulin M or immunoglobulin G against any serotype, thus limiting its capability to distinguish existing serotypes of dengue. Identification of dengue serotype is important because certain serotypes are associated with severe forms of dengue as well as dengue hemorrhagic fever. In this study, we aimed to identify an immunogenic epitope unique to DENV2 NS1 antigen and determine the binding specificity of its synthetic peptide mimotope to antibodies raised in animal models. Selection of a putative B-cell epitope from the reported DENV2 NS1 antigen was done using Kolaskar and Tongaonkar Antigenicity prediction, Emini surface accessibility prediction, and Parker hydrophilicity prediction available at the immune epitope database and analysis resource. Uniqueness of the B-cell epitope to DENV2 was analyzed by BLASTp. Immunogenicity of the synthetic peptide analog of the predicted immunogenic epitope was tested in rabbits. The binding specificity of the antibodies raised in animals and the synthetic peptide mimotope was tested by indirect ELISA. A synthetic peptide analog comprising the unique epitope of DENV2 located at the 170th-183rd position of DENV2 NS1 was found to be immunogenic in animal models. The antipeptide antibody produced in rabbits showed specific binding to the synthetic peptide mimotope of the predicted unique DENV2 NS1 immunogenic epitope.

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.

Selection of Specific Peptides for Coccidioides spp. Obtained from Antigenic Fractions through SDS-PAGE and Western Blot Methods by the Recognition of Sera from Patients with Coccidioidomycosis

Antigenic fractions of 100, 50, 37, and 28 kDa obtained through the SDS-PAGE method that were more frequently recognized by anti-Coccidioides antibodies in the sera of coccidioidomycosis patients were selected using western blotting. Subsequently, these bands were sequenced, and the obtained proteins were analysed by BLAST to choose peptides specific for Coccidioides spp. from among the shared aligned sequences of related fungi. A peptide specific for C. immitis was selected from the "GPI anchored serine-threonine rich protein OS C. immitis", while from the "uncharacterized protein of C. immitis", we selected a peptide for C. immitis and C. posadasii. These proteins arose from the 100 kDa antigenic fraction. From the protein "fatty acid amide hydrolase 1 of C. posadasii" that was identified from the 50 kDa antigenic fraction, a peptide was selected that recognized C. immitis and C. posadasii. In addition, the analysis of all the peptides (353) of each of the assembled proteins showed that only 35 had 100% identity with proteins of C. immitis and C. posadasii, one had 100% identity with only C. immitis, and one had 100% identity with only C. posadasii. These peptides can be used as diagnostic reagents, vaccines, and antifungals.

Entropy is a Simple Measure of the Antibody Profile and is an Indicator of Health Status: A Proof of Concept

We have previously shown that the diversity of antibodies in an individual can be displayed on chips on which 130,000 peptides chosen from random sequence space have been synthesized. This immunosignature technology is unbiased in displaying antibody diversity relative to natural sequence space, and has been shown to have diagnostic and prognostic potential for a wide variety of diseases and vaccines. Here we show that a global measure such as Shannon's entropy can be calculated for each immunosignature. The immune entropy was measured across a diverse set of 800 people and in 5 individuals over 3 months. The immune entropy is affected by some population characteristics and varies widely across individuals. We find that people with infections or breast cancer, generally have higher entropy values than non-diseased individuals. We propose that the immune entropy as measured from immunosignatures may be a simple method to monitor health in individuals and populations.

Identification of non-random sequence properties in groups of signature peptides obtained in random sequence peptide microarray experiments

Immunosignaturing is an emerging experimental technique that uses random sequence peptide microarrays to detect antibodies produced by the immune system in response to a particular disease. Two important questions regarding immunosignaturing are "Do microarray peptides that exhibit a strong affinity to a given type of antibodies share common sequence properties?" and "If so, what are those properties?" In this work, three statistical tests designed to detect non-random patterns in the amino acid makeup of a group of microarray peptides are presented. One test detects patterns of significantly biased amino acid usage, whereas the other two detect patterns of significant bias in the biochemical properties. These tests do not require a large number of peptides per group. The tests were applied to analyze 19 groups of peptides identified in immunosignaturing experiments as being specific for antibodies produced in response to various types of cancer and other diseases. The positional distribution of the biochemical properties of the amino acids in these 19 peptide groups was also studied. Remarkably, despite the random nature of the sequence libraries used to design the microarrays, a unique group-specific non-random pattern was identified in the majority of the peptide groups studied. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 318-329, 2016.

General Assessment of Humoral Activity in Healthy Humans

The humoral immune system is network of biological molecules designed to maintain a healthy homeostatic equilibrium. Because antibodies are an abundant and highly specific effector of immunological action, they are also an important reservoir of previous host exposures. Antibodies may play a major role in early detection of host challenge. Unfortunately, few practical methods exist for interpreting the information stored in antibody variable regions. Immunosignatures use a microarray of thousands of random sequence peptides to interrogate antibodies in a broad and unbiased fashion. The pattern of binding between antibody and peptide is reproducible. Once the system has been trained on a disease cohort, blinded samples can be reliably predicted. Although immunosignatures of both chronic and infectious disease have been extensively tested, less has been done to demonstrate how healthy immunosignatures change over time or between individuals. Here, we report the results of a study of immunosignatures of healthy persons over brief (12 h sampled once per hour), intermediate (32 days sampled once per day), and long (5 years sampled once every year) time spans. Using this information, we were also able to detect intentional and unintentional immunological perturbations in the form of a vaccine and an infection, respectively. Our findings suggest that, even with the variability inherent in healthy immunosignatures, a single person's immunosignature will remain constant over time. Over this healthy signature, vaccines and infections create subsignatures that are common across multiple people, even subsuming healthy fluctuations. These findings have implications for disease monitoring and early diagnosis.

Use of computational and recombinant technologies for developing novel influenza vaccines

Influenza vaccine design has changed considerably with advancements in bioinformatics and computational biology. Improved surveillance efforts provide up-to-date information about influenza sequence diversity and assist with monitoring the spread of epidemics and vaccine efficacy rates. The advent of next-generation sequencing, epitope scanning and high-throughput analysis all help decipher influenza-associated protein interactions as well as predict immune responsiveness based on host genetic diversity. Computational approaches are utilized in nearly all aspects of vaccine design, from modeling, compatibility predictions, and optimization of antigens in various platforms. This overview discusses how computational techniques strengthen vaccine efforts against highly diverse influenza species.

Serology in the 21st century: the molecular-level analysis of the serum antibody repertoire

The ensemble of antibodies found in serum and secretions represents the key adaptive component of B-cell mediated humoral immunity. The antibody repertoire is shaped by the historical record of exposure to exogenous factors such as pathogens and vaccines, as well as by endogenous host-intrinsic factors such as genetics, self-antigens, and age. Thanks to very recent technology advancements it is now becoming possible to identify and quantify the individual antibodies comprising the serological repertoire. In parallel, the advent of high throughput methods for antigen and immunosignature discovery opens up unprecedented opportunities to transform our understanding of numerous key questions in adaptive humoral immunity, including the nature and dynamics of serological memory, the role of polyspecific antibodies in health and disease and how protective responses to infections or vaccine challenge arise. Additionally, these technologies also hold great promise for therapeutic antibody and biomarker discovery in a variety of settings.

Time-Frequency Analysis of Peptide Microarray Data: Application to Brain Cancer Immunosignatures

One of the gravest dangers facing cancer patients is an extended symptom-free lull between tumor initiation and the first diagnosis. Detection of tumors is critical for effective intervention. Using the body’s immune system to detect and amplify tumor-specific signals may enable detection of cancer using an inexpensive immunoassay. Immunosignatures are one such assay: they provide a map of antibody interactions with random-sequence peptides. They enable detection of disease-specific patterns using classic train/test methods. However, to date, very little effort has gone into extracting information from the sequence of peptides that interact with disease-specific antibodies. Because it is difficult to represent all possible antigen peptides in a microarray format, we chose to synthesize only 330,000 peptides on a single immunosignature microarray. The 330,000 random-sequence peptides on the microarray represent 83% of all tetramers and 27% of all pentamers, creating an unbiased but substantial gap in the coverage of total sequence space. We therefore chose to examine many relatively short motifs from these random-sequence peptides. Time-variant analysis of recurrent subsequences provided a means to dissect amino acid sequences from the peptides while simultaneously retaining the antibody–peptide binding intensities. We first used a simple experiment in which monoclonal antibodies with known linear epitopes were exposed to these random-sequence peptides, and their binding intensities were used to create our algorithm. We then demonstrated the performance of the proposed algorithm by examining immunosignatures from patients with Glioblastoma multiformae (GBM), an aggressive form of brain cancer. Eight different frameshift targets were identified from the random-sequence peptides using this technique. If immune-reactive antigens can be identified using a relatively simple immune assay, it might enable a diagnostic test with sufficient sensitivity to detect tumors in a clinically useful way.