Scalable high-density peptide arrays for comprehensive health monitoring

Solid-phase peptide synthesis in 384-well plates

Newer solid-phase peptide synthesis and release strategies enable the production of short peptides with high purity, allowing direct screening for desired bioactivity without prior chromatographic purification. However, the maximum number of peptides that can currently be synthesized per microplate reactor is 96, allowing the parallel synthesis of 384 peptides in modern devices that have space for 4 microplate reactors. To synthesize larger numbers of peptides, we modified a commercially available peptide synthesizer to enable the production of peptides in 384-well plates, which allows the synthesis of 1,536 peptides in one run (4 × 384 peptides). We report new hardware components and customized software that allowed for the synthesis of 1,536 short peptides in good quantity (average > 0.5 μmol), at high concentration (average > 10 mM), and decent purity without purification (average > 80%). The high-throughput peptide synthesis, which we developed with peptide drug development in mind, may be widely used for peptide library synthesis and screening, antibody epitope scanning, epitope mimetic development, or protease/kinase substrate screening.

Towards a comprehensive understanding of the muscle proteome in Schizothorax labiatus: Insights from seasonal variations, metabolic responses, and reproductive signatures in the River Jhelum

Proteomics is a very advanced technique used for defining correlations, compositions and activities of hundreds of proteins from organisms as well as effectively used in identifying particular proteins with varying peptide lengths and amino acid counts. In the present study, an endeavour has been put forth to create muscle proteome expression of snow trout, Schizothorax labiatus. Liquid chromatography-mass spectrometry (LC-MS) using label free quantification (LFQ) technique has extensively been carried out to explore changes in protein metabolism and its composition to discriminate across species, clarify functions and pinpoint protein biomarkers from organisms. In LFQ technique, the abundances of proteins are determined based on the signal intensities of their corresponding peptides in mass spectrometry. The main benefit of using this method is that it doesn't require pre-labelling proteins with isotopic tags, which streamlines the experimental procedure and gets rid of any bias that might have been caused by the labelling process. LFQ techniques frequently offer a wider dynamic range, making it possible to detect and quantify proteins over a broad range of abundances obtained from the complex biological materials including fish muscle. The results of proteomic analysis could provide an insight in understanding about how various proteins are expressed in response to environmental challenges. For proteomic study, two different weight groups of S. labiatus were taken from River Jhelum based on biological, physiological and logistical factors. These groups corresponded to different life stages, such as younger size and adults/brooders in order to capture potential variations in the muscle proteome related to growth and development. The proteomic analysis of S. labiatus depicted that an overall of 220 proteins in male and 228 in female fish of group 1 were noted. However, when male and female S. labiatus were examined based on spectral count and peptide abundance using ProteinLynx Global Software, a total of 10 downregulated and 32 upregulated proteins were found. In group 2 of S. labiatus, a total of 249 proteins in male and 301 in female fish were documented. When the two genders of S. labiatus were likened to one another by LFQ technique, a total of 41 downregulated and 06 upregulated proteins were identified. The variability in the protein numbers between two fish weight groups reflected biological differences, influenced by factors such as age, developmental stages, physiological condition and reproductive activities. During the study, it was observed that S. labiatus exhibited downregulated levels of proteins that were involved in feeding and growth. The contributing factors to this manifestation could be explained by lower feeding and metabolic activity of fish and decreased food availability during winter in River Jhelum. Contrarily, the fish immune response proteins were found to be significantly over-expressed in S. labiatus, indicating that the environment was more likely to undergo increased microbial infection, pollution load and anthropogenic activities. In addition, it was also discovered that there was an upregulated expression of the reproductive proteins in S. labiatus, which could be linked to the fish's pre-spawning time as the fish used in this study was collected in the winter season which is the pre-spawning period of the fish. Therefore, the present study would be useful in obtaining new insights regarding the molecular makeup of species, methods of adaptation and reactions to environmental stresses. This information contributes to our understanding of basic science and may have applications in environmental monitoring, conservation and preservation of fish species.

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.

Crohn's patients and healthy infants share immunodominant B cell response to commensal flagellin peptide epitopes

About half of patients with Crohn's disease (CD) develop selective serum IgG response to flagellin proteins of the Lachnospiraceae family. Here, we identified a dominant B cell peptide epitope in CD, locating in the highly conserved "hinge region" between the D0 and D1 domains at the amino-terminus of Lachnospiraceae flagellins. Serum IgG reactive to this epitope is present at an elevated level in adult CD patients and in pediatric CD patients at diagnosis. Most importantly, high levels of serum IgG to the hinge epitope were found in most infants from 3 different geographic regions (Uganda, Sweden, and the USA) at one year of age. This vigorous homeostatic response decrements with age as it is not present in healthy adults. These data identify a distinct subset of CD patients, united by a shared reactivity to this dominant flagellin epitope that may represent failure of a homeostatic response beginning in infancy.

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.

The next wave of interactomics: Mapping the SLiM-based interactions of the intrinsically disordered proteome

Short linear motifs (SLiMs) are a unique and ubiquitous class of protein interaction modules that perform key regulatory functions and drive dynamic complex formation. For decades, interactions mediated by SLiMs have accumulated through detailed low-throughput experiments. Recent methodological advances have opened this previously underexplored area of the human interactome to high-throughput protein-protein interaction discovery. In this article, we discuss that SLiM-based interactions represent a significant blind spot in the current interactomics data, introduce the key methods that are illuminating the elusive SLiM-mediated interactome of the human cell on a large scale, and discuss the implications for the field.

The Trypanosoma cruzi Antigen and Epitope Atlas: antibody specificities in Chagas disease patients across the Americas

During an infection the immune system produces pathogen-specific antibodies. These antibody repertoires become specific to the history of infections and represent a rich source of diagnostic markers. However, the specificities of these antibodies are mostly unknown. Here, using high-density peptide arrays we examined the human antibody repertoires of Chagas disease patients. Chagas disease is a neglected disease caused by Trypanosoma cruzi, a protozoan parasite that evades immune mediated elimination and mounts long-lasting chronic infections. We describe a proteome-wide search for antigens, characterised their linear epitopes, and show their reactivity on 71 individuals from diverse human populations. Using single-residue mutagenesis we revealed the core functional residues for 232 of these epitopes. Finally, we show the diagnostic performance of identified antigens on challenging samples. These datasets enable the study of the Chagas antibody repertoire at an unprecedented depth and granularity, while also providing a rich source of serological biomarkers.

Droplet Microarray as a Powerful Platform for Seeking New Antibiotics Against Multidrug-Resistant Bacteria

Multidrug-resistant (MDR) bacteria is a severe threat to public health. Therefore, it is urgent to establish effective screening systems for identifying novel antibacterial compounds. In this study, a highly miniaturized droplet microarray (DMA) based high-throughput screening system is established to screen over 2000 compounds for their antimicrobial properties against carbapenem-resistant Klebsiella pneumoniae and methicillin resistant Staphylococcus aureus (MRSA). The DMA consists of an array of hydrophilic spots divided by superhydrophobic borders. Due to the differences in the surface wettability between the spots and the borders, arrays of hundreds of nanoliter-sized droplets containing bacteria and different drugs can be generated for screening applications. A simple colorimetric viability readout utilizing a conventional photo scanner is developed for fast single-step detection of the inhibitory effect of the compounds on bacterial growth on the whole array. Six hit compounds, including coumarins and structurally simplified estrogen analogs are identified in the primary screening and validated with minimum inhibition concentration assay for their antibacterial effect. This study demonstrates that the DMA-based high-throughput screening system enables the identification of potential antibiotics from novel synthetic compound libraries, offering opportunities for development of new treatments against multidrug-resistant bacteria.

Proteomic Applications in Aquatic Environment Studies

Genome determines the unique individualities of organisms; however, proteins play significant roles in the generation of the colorful life forms below water. Aquatic systems are usually complex and multifaceted and can take on unique modifications and adaptations to environmental changes by altering proteins at the cellular level. Proteomics is an essential strategy for exploring aquatic ecosystems due to the diverse involvement of proteins, proteoforms, and their complexity in basic and advanced cellular functions. Proteomics can expedite the analysis of molecular mechanisms underlying biological processes in an aquatic environment. Previous proteomic studies on aquatic environments have mainly focused on pollution assessments, ecotoxicology, their role in the food industry, and extraction and identification of natural products. Aquatic protein biomarkers have been comprehensively reported and are currently extensively applied in the pharmaceutical and medical industries. Cellular- and molecular-level responses of organisms can be used as indicators of environmental changes and stresses. Conversely, environmental changes are expedient in predicting aquatic health and productivity, which are crucial for ecosystem management and conservation. Recent advances in proteomics have contributed to the development of sustainable aquaculture, seafood safety, and high aquatic food production. Proteomic approaches have expanded to other aspects of the aquatic environment, such as protein fingerprinting for species identification. In this review, we encapsulated current proteomic applications and evaluated the potential strengths, weaknesses, opportunities, and threats of proteomics for future aquatic environmental studies. The review identifies both pros and cons of aquatic proteomics and projects potential challenges and recommendations. We postulate that proteomics is an emerging, powerful, and integrated omics approach for aquatic environmental studies.

Protective antigenic epitopes revealed by immunosignatures after three doses of inactivated SARS-CoV-2 vaccine

Background

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has infected millions of people around the world. Vaccination is a pillar in the strategy to control transmission of the SARS-CoV-2 spread. Immune responses to vaccination require elucidation.

Methods

The immune responses to vaccination with three doses of inactivated SARS-CoV-2 vaccine were followed in a cohort of 37 healthy adults (18–59 years old). Blood samples were collected at multiple time points and submitted to peptide array, machine learning modeling, and sequence alignment analyses, the results of which were used to generate vaccine-induced antibody-binding region (VIABR) immunosignatures (Registration number: ChiCTR2200058571).

Results

Antibody spectrum signals showed vaccination stimulated antibody production. Sequence alignment analyses revealed that a third vaccine dose generated a new highly represented VIABR near the A570D mutation, and the whole process of inoculation enhanced the VIABR near the N501Y mutation. In addition, the antigen conformational epitopes varied between short- and long-term samples. The amino acids with the highest scores in the short-term samples were distributed primarily in the receptor binding domain (RBD) and N-terminal domain regions of spike (S) protein, while in the long-term samples (12 weeks after the 2^nd dose), some new conformational epitopes (CEs) were localized to crevices within the head of the S protein trimer.

Conclusion

Protective antigenic epitopes were revealed by immunosignatures after three doses of inactivated SARS-CoV-2 vaccine inoculation. A third dose results in a new top-10 VIABR near the A570D mutation site of S protein, and the whole process of inoculation enhanced the VIABR near the N501Y mutation, thus potentially providing protection from strains that have gained invasion and immune escape abilities through these mutation.

High-Throughput Screening Identifies Synthetic Peptides with Antibacterial Activity against Mycobacterium abscessus and Serum Stability

The rise in antibiotic resistance in bacteria has spawned new technological approaches for identifying novel antimicrobials with narrow specificity. Current antibiotic treatment regimens and antituberculosis drugs are not effective in treating Mycobacterium abscessus. Meanwhile, antimicrobial peptides are gaining prominence as alternative antimicrobials due to their specificity toward anionic bacterial membranes, rapid action, and limited development of resistance. To rapidly identify antimicrobial peptide candidates, our group has developed a high-density peptide microarray consisting of 125,000 random synthetic peptides screened for interaction with the mycobacterial cell surface of M. abscessus morphotypes. From the array screening, peptides positive for interaction were synthesized and their antimicrobial activity was validated. Overall, six peptides inhibited the M. abscessus smooth morphotype (IC₅₀ = 1.7 μM for all peptides) and had reduced activity against the M. abscessus rough morphotype (IC₅₀ range: 13-82 μM). Peptides ASU2056 and ASU2060 had minimum inhibitory concentration values of 32 and 8 μM, respectively, against the M. abscessus smooth morphotype. Additionally, ASU2060 (8 μM) was active against Escherichia coli, including multidrug-resistant E. coli clinical isolates, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus. ASU2056 and ASU2060 exhibited no significant hemolytic activity at biologically relevant concentrations, further supporting these peptides as promising therapeutic candidates. Moreover, ASU2060 retained antibacterial activity after preincubation in human serum for 24 h. With antimicrobial resistance on the rise, methods such as those presented here will streamline the peptide discovery process for targeted antimicrobial peptides.

Automated Laser-Transfer Synthesis of High-Density Microarrays for Infectious Disease Screening

Laser-induced forward transfer (LIFT) is a rapid laser-patterning technique for high-throughput combinatorial synthesis directly on glass slides. A lack of automation and precision limits LIFT applications to simple proof-of-concept syntheses of fewer than 100 compounds. Here, an automated synthesis instrument is reported that combines laser transfer and robotics for parallel synthesis in a microarray format with up to 10 000 individual reactions cm^{- 2} . An optimized pipeline for amide bond formation is the basis for preparing complex peptide microarrays with thousands of different sequences in high yield with high reproducibility. The resulting peptide arrays are of higher quality than commercial peptide arrays. More than 4800 15-residue peptides resembling the entire Ebola virus proteome on a microarray are synthesized to study the antibody response of an Ebola virus infection survivor. Known and unknown epitopes that serve now as a basis for Ebola diagnostic development are identified. The versatility and precision of the synthesizer is demonstrated by in situ synthesis of fluorescent molecules via Schiff base reaction and multi-step patterning of precisely definable amounts of fluorophores. This automated laser transfer synthesis approach opens new avenues for high-throughput chemical synthesis and biological screening.

Restriction of the Global IgM Repertoire in Antiphospholipid Syndrome

The typical anti-phospholipid antibodies (APLA) in the anti-phospholipid syndrome (APS) are reactive with the phospholipid-binding protein β2GPI as well as a growing list of other protein targets. The relation of APLA to natural antibodies and the fuzzy set of autoantigens involved provoked us to study the changes in the IgM repertoire in APS. To this end, peptides selected by serum IgM from a 7-residue linear peptide phage display library (PDL) were deep sequenced. The analysis was aided by a novel formal representation of the Igome (the mimotope set reflecting the IgM specificities) in the form of a sequence graph. The study involved women with APLA and habitual abortions (n=24) compared to age-matched clinically healthy pregnant women (n=20). Their pooled Igomes (297 028 mimotope sequences) were compared also to the global public repertoire Igome of pooled donor plasma IgM (n=2 796 484) and a set of 7-mer sequences found in the J regions of human immunoglobulins (n=4 433 252). The pooled Igome was represented as a graph connecting the sequences as similar as the mimotopes of the same monoclonal antibody. The criterion was based on previously published data. In the resulting graph, identifiable clusters of vertices were considered related to the footprints of overlapping antibody cross-reactivities. A subgraph based on the clusters with a significant differential expression of APS patients’ mimotopes contained predominantly specificities underrepresented in APS. The differentially expressed IgM footprints showed also an increased cross-reactivity with immunoglobulin J regions. The specificities underexpressed in APS had a higher correlation with public specificities than those overexpressed. The APS associated specificities were strongly related also to the human peptidome with 1 072 mimotope sequences found in 7 519 human proteins. These regions were characterized by low complexity. Thus, the IgM repertoire of the APS patients was found to be characterized by a significant reduction of certain public specificities found in the healthy controls with targets representing low complexity linear self-epitopes homologous to human antibody J regions.

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.

Reduction of Promiscuous Peptides-Enzyme Inhibition and Aggregation by Negatively Charged Biopolymers

In this work, peptides selected from a microarray were found to inhibit β-gal with promiscuous mechanisms. Peptides inhibited the enzyme in a noncompetitive kinetics, and the inhibition of enzyme activities was reduced under high enzyme concentrations and the addition of detergent. Dynamic light scattering and atomic force microscope revealed that peptide/enzyme aggregation was related to inhibited enzyme activities. Positively charged residues of arginine and lysine were critical for the enzyme inhibition. The preincubation of peptide inhibitors with negatively charged biopolymers of polyphosphates, ssDNA, and low pI peptides could increase the residual activity of peptide-inhibited enzyme, possibly due to the disruption of the electrostatic interaction between positively charged peptide residues and the β-gal surface. Further, negative biopolymers were able to recover the activity of the aggregated peptide/β-gal complex. Negatively charged biopolymers could be used in high-throughput screening assays to reduce peptides/protein aggregation and thereby minimize promiscuous inhibitions.

Challenge of diagnosing acute infections in poor resource settings in Africa

Frequent disease outbreaks and acute infections occur in rural and low-income urban areas of Africa, with many health systems unprepared to diagnose and control diseases that are recurrent, endemic or have extended their geographic zone. In this review, we focus on acute infections that can be characterized by sudden onset, rapid progression, severe symptoms and poor prognosis. Consequently, these infections require early diagnosis and intervention. While effective vaccines have been developed against some of these diseases, lack of compliance and accessibility, and the need for repeated or multiple vaccinations mean large populations can remain vulnerable to infection. It follows that there is a need for enhancement of national surveillance and diagnostic capacity to avert morbidity and mortality from acute infections. We discuss the limitations of traditional diagnostic methods and explore the relative merits and applicability of protein-, carbohydrate- and nucleic acid-based rapid diagnostic tests that have been trialled for some infectious diseases. We also discuss the utility and limitations of antibody-based serological diagnostics and explore how systems biology approaches can better inform diagnosis. Lastly, given the complexity and high cost associated with after-service support of emerging technologies, we propose that, for resource-limited settings in Africa, multiplex point-of-care diagnostic tools be tailor-made to detect both recurrent acute infections and endemic infections.

Peptide Blocking CTLA-4 and B7-1 Interaction

Discovery of the B7 family immune checkpoints such as CTLA-4 (CD152), PD-1 (CD279), as well as their ligands B7-1 (CD80), B7-2 (CD86), B7-H1 (PD-L1, CD274), and B7-DC (PD-L2, CD273), has opened new possibilities for cancer immunotherapy using monoclonal antibodies (mAb). The blockade of inhibitory receptors (CTLA-4 and PD-1) with specific mAb results in the activation of cancer patients' T lymphocytes and tumor rejection. However, the use of mAb in clinics has several limitations including side effects and cost of treatment. The development of new low-molecular compounds that block immune checkpoints' functional activity can help to overcome some of these limitations. In this paper, we describe a synthetic peptide (p344) containing 14 amino acids that specifically interact with CTLA-4 protein. A 3D computer model suggests that this peptide binds to the ⁹⁹MYPPPY¹⁰⁴ loop of CTLA-4 protein and potentially blocks the contact of CTLA-4 receptor with B7-1 ligand. Experimental data confirm the peptide-specific interaction with CTLA-4 and its ability to partially block CTLA-4/B7-1 binding. The identified synthetic peptide can be used for the development of novel immune checkpoint inhibitors that can block CTLA-4 functional activity for cancer immunotherapy.

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.

Comprehensive Prediction of Molecular Recognition in a Combinatorial Chemical Space Using Machine Learning

In combinatorial chemical approaches, optimizing the composition and arrangement of building blocks toward a particular function has been done using a number of methods, including high throughput molecular screening, molecular evolution, and computational prescreening. Here, a different approach is considered that uses sparse measurements of library molecules as the input to a machine learning algorithm which generates a comprehensive, quantitative relationship between covalent molecular structure and function that can then be used to predict the function of any molecule in the possible combinatorial space. To test the feasibility of the approach, a defined combinatorial chemical space consisting of ∼10¹² possible linear combinations of 16 different amino acids was used. The binding of a very sparse, but nearly random, sampling of this amino acid sequence space to 9 different protein targets is measured and used to generate a general relationship between peptide sequence and binding for each target. Surprisingly, measuring as little as a few hundred to a few thousand of the ∼10¹² possible molecules provides sufficient training to be highly predictive of the binding of the remaining molecules in the combinatorial space. Furthermore, measuring only amino acid sequences that bind weakly to a target allows the accurate prediction of which sequences will bind 10-100 times more strongly. Thus, the molecular recognition information contained in a tiny fraction of molecules in this combinatorial space is sufficient to characterize any set of molecules randomly selected from the entire space, a fact that potentially has significant implications for the design of new chemical function using combinatorial chemical libraries.

Recent progress in creating complex and multiplexed surface-grafted macromolecular architectures

Surface-grafted macromolecules, including polymers, DNA, peptides, etc., are versatile modifications to tailor the interfacial functions in a wide range of fields. In this review, we aim to provide an overview of the most recent progress in engineering surface-grafted chains for the creation of complex and multiplexed surface architectures over micro- to macro-scopic areas. A brief introduction to surface grafting is given first. Then the fabrication of complex surface architectures is summarized with a focus on controlled chain conformations, grafting densities and three-dimensional structures. Furthermore, recent advances are highlighted for the generation of multiplexed arrays with designed chemical composition in both horizontal and vertical dimensions. The applications of such complicated macromolecular architectures are then briefly discussed. Finally, some perspective outlooks for future studies and challenges are suggested. We hope that this review will be helpful to those just entering this field and those in the field requiring quick access to useful reference information about the progress in the properties, processing, performance, and applications of functional surface-grafted architectures.

Computational assessment of the feasibility of protonation-based protein sequencing

Recent advances in DNA sequencing methods revolutionized biology by providing highly accurate reads, with high throughput or high read length. These read data are being used in many biological and medical applications. Modern DNA sequencing methods have no equivalent in protein sequencing, severely limiting the widespread application of protein data. Recently, several optical protein sequencing methods have been proposed that rely on the fluorescent labeling of amino acids. Here, we introduce the reprotonation-deprotonation protein sequencing method. Unlike other methods, this proposed technique relies on the measurement of an electrical signal and requires no fluorescent labeling. In reprotonation-deprotonation protein sequencing, the terminal amino acid is identified through its unique protonation signal, and by repeatedly cleaving the terminal amino acids one-by-one, each amino acid in the peptide is measured. By means of simulations, we show that, given a reference database of known proteins, reprotonation-deprotonation sequencing has the potential to correctly identify proteins in a sample. Our simulations provide target values for the signal-to-noise ratios that sensor devices need to attain in order to detect reprotonation-deprotonation events, as well as suitable pH values and required measurement times per amino acid. For instance, an SNR of 10 is required for a 61.71% proteome recovery rate with 100 ms measurement time per amino acid.

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.

Advances in Sweat Wearables: Sample Extraction, Real-Time Biosensing, and Flexible Platforms

Wearable biosensors for sweat-based analysis are gaining wide attention due to their potential use in personal health monitoring. Flexible wearable devices enable sweat analysis at the molecular level, facilitating noninvasive monitoring of physiological states via real-time monitoring of chemical biomarkers. Advances in sweat extraction technology, real-time biosensors, stretchable materials, device integration, and wireless digital technologies have led to the development of wearable sweat-biosensing devices that are light, flexible, comfortable, aesthetic, affordable, and informative. Herein, we summarize recent advances of sweat wearables from the aspects of sweat extraction, fabrication of stretchable biomaterials, and design of biosensing modules to enable continuous biochemical monitoring, which are essential for a biosensing device. Key chemical components of sweat, sweat capture methodologies, and considerations of flexible substrates for integrating real-time biosensors with electronics to bring innovations in the art of wearables are elaborated. The strategies and challenges involved in improving the wearable biosensing performance and the perspectives for designing sweat-based wearable biosensing devices are discussed.

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.

Comparison of motif-based and whole-unique-sequence-based analyses of phage display library datasets generated by biopanning of anti-Borrelia burgdorferi immune sera

Detection of protection-associated epitopes via reverse vaccinology is the first step for development of subunit vaccines against microbial pathogens. Mapping subunit vaccine targets requires high throughput methods, which would allow delineation of epitopes recognized by protective antibodies on a large scale. Phage displayed random peptide library coupled to Next Generation Sequencing (PDRPL/NGS) is the universal platform that enables high-yield identification of peptides that mimic epitopes (mimotopes). Despite being unsurpassed as a tool for discovery of polyclonal serum mimotopes, the PDRPL/NGS is far inferior as a quantitative method of immune response. Difficult-to-control fluctuations in amounts of antibody-bound phages after rounds of selection and amplification diminish the quantitative capacity of the PDRPL/NGS. In an attempt to improve the accuracy of the PDRPL/NGS method, we compared the discriminating capacity of two approaches for PDRPL/NGS data analysis. The whole-unique-sequence-based analysis (WUSA) involved generation of 7-mer peptide profiles and comparison of the numbers of sequencing reads for unique peptide sequences between serum samples. The motif-based analysis (MA) included identification of 4-mer consensus motifs unifying unique 7-mer sequences and comparison of motifs between serum samples. The motif comparison was based not on the numbers of sequencing reads, but on the numbers of distinct 7-mers constituting the motifs. Our PDRPL/NGS datasets generated from biopanning of protective and non-protective anti-Borrelia burgdorferi sera of New Zealand rabbits were used to contrast the two approaches. As a result, the principle component analyses (PCA) showed that the discriminating powers of the WUSA and MA were similar. In contrast, the unsupervised hierarchical clustering obtained via the MA classified the preimmune, non-protective, and protective sera better than the WUSA-based clustering. Also, a total number of discriminating motifs was higher than that of discriminating 7-mers. In sum, our results indicate that MA approach improves the accuracy and quantitative capacity of the PDRPL/NGS method.

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.

Stochastic deposition of amino acids into microcavities via microparticles

All known methods for solid-phase synthesis of molecular arrays exploit positioning techniques to deposit monomers on a substrate preferably high densely. In this paper, stochastic patterning of molecule spots (250 000 spots monomers/cm²) via random allocation of the microbeads on a microstructured glass is presented. The size and shape of the microbeads and the microcavities are selected in such a way so that only one microbead can fit into the respective microcavity. Each microbead can be loaded with a certain type of molecule e.g. amino acids and is brought in the microcavities stochastically. Applying solvent vapor and heating the substrate, the molecules are released from the microbeads and coupled to the functionalized substrate. To differentiate between the microbeads carrying different molecules, quantum dot labels are preliminary introduced into the microbeads. Fluorescence imaging and subsequent data analysis enable decoding of the molecule deposition patterns. After the coupling step is completed, the microbeads are mechanically removed from the microwells. The composition of the monomer microbeads, their deposition and the conditions of the monomer extraction are studied. The stochastic monomer patterning may be used to design novel molecular arrays.

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.

Serological Analysis of Herpes B Virus at Individual Epitope Resolution: From Two-Dimensional Peptide Arrays to Multiplex Bead Flow Assays

Macacine herpesvirus or B Virus (BV) is a zoonotic agent that leads to high mortality rates in humans if transmitted and untreated. Here, BV is used as a test case to establish a two-step procedure for developing high throughput serological assays based on synthetic peptides. In step 1, peptide microarray analysis of 42 monkey sera (30 of them tested BV positive by ELISA) revealed 1148 responses against 369 different peptides. The latter could be grouped into 142 different antibody target regions (ATRs) in six different glycoproteins (gB, gC, gD, gG, gH, and gL) of BV. The high number of newly detected ATRs was made possible inter alia by a new preanalytical protocol that reduced unspecific binding of serum components to the cellulose-based matrix of the microarray. In step 2, soluble peptides corresponding to eight ATRs of particularly high antigenicity were synthesized and coupled to fluorescently labeled beads, which were subsequently employed in immunochemical bead flow assays. Their outcome mirrored the ELISA results used as reference. Hence, convenient, fast, and economical screening of arbitrarily large macaque colonies for BV infection is now possible. The study demonstrates that a technology platform switch from two-dimensional high-resolution peptide arrays used for epitope discovery to a readily available bead array platform for serology applications is feasible.

High-Throughput Profiling of Circulating Antibody Signatures for Stroke Diagnosis Using Small Volumes of Whole Blood

Accurate stroke recognition during triage can streamline care and afford patients earlier access to life-saving interventions. However, the tools currently available to clinicians for prehospital and early in-hospital identification of stroke are limited. The peripheral immune system is intricately involved in stroke pathology and thus may be targetable for the development of immunodiagnostics. In this preliminary study, we sought to determine whether the circulating antibody pool is altered early in stroke, and whether such alterations could be leveraged for diagnosis. One hundred microliters of peripheral whole blood was sampled from 19 ischemic stroke patients, 17 hemorrhagic stroke patients, and 20 stroke mimics in the acute phase of care. A custom-fabricated high-density peptide array comprising 125,000 unique probes was used to assess the binding characteristics of blood-borne antibodies, and a random forest-based approach was used to select a parsimonious set of probes with an optimal ability to discriminate between groups. The coordinate antibody binding intensities of the top 17 probes identified in our analysis displayed an ability to differentiate the total pool of stroke patients from stroke mimics with 92% sensitivity and 90% specificity, as well as detect hemorrhage with 88% sensitivity and 87% specificity, as determined using a same-set cross-validation. These preliminary findings suggest that stroke-associated alterations in the circulating antibody pool may have clinical utility for diagnosis during triage, and that such a possibility warrants further investigation.

Large-Scale, Quantitative Protein Assays on a High-Throughput DNA Sequencing Chip

High-throughput DNA sequencing techniques have enabled diverse approaches for linking DNA sequence to biochemical function. In contrast, assays of protein function have substantial limitations in terms of throughput, automation, and widespread availability. We have adapted an Illumina high-throughput sequencing chip to display an immense diversity of ribosomally translated proteins and peptides and then carried out fluorescence-based functional assays directly on this flow cell, demonstrating that a single, widely available high-throughput platform can perform both sequencing-by-synthesis and protein assays. We quantified the binding of the M2 anti-FLAG antibody to a library of 1.3 × 10⁴ variant FLAG peptides, exploring non-additive effects of combinations of mutations and discovering a "superFLAG" epitope variant. We also measured the enzymatic activity of 1.56 × 10⁵ molecular variants of full-length human O⁶-alkylguanine-DNA alkyltransferase (SNAP-tag). This comprehensive corpus of catalytic rates revealed amino acid interaction networks and cooperativity, linked positive cooperativity to structural proximity, and revealed ubiquitous positively cooperative interactions with histidine residues.

Miniaturized and Automated Synthesis of Biomolecules-Overview and Perspectives

Chemical synthesis is performed by reacting different chemical building blocks with defined stoichiometry, while meeting additional conditions, such as temperature and reaction time. Such a procedure is especially suited for automation and miniaturization. Life sciences lead the way to synthesizing millions of different oligonucleotides in extremely miniaturized reaction sites, e.g., pinpointing active genes in whole genomes, while chemistry advances different types of automation. Recent progress in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) imaging could match miniaturized chemical synthesis with a powerful analytical tool to validate the outcome of many different synthesis pathways beyond applications in the life sciences. Thereby, due to the radical miniaturization of chemical synthesis, thousands of molecules can be synthesized. This in turn should allow ambitious research, e.g., finding novel synthesis routes or directly screening for photocatalysts. Herein, different technologies are discussed that might be involved in this endeavor. A special emphasis is given to the obstacles that need to be tackled when depositing tiny amounts of materials to many different extremely miniaturized reaction sites.

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.

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.

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.

Identification of B cell epitopes enhanced by protein unfolding and aggregation

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Aggregation of an exemplar therapeutic antibody fragment (scFv) enhances immunogenicity in vivo.

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Epitope mapping reveals immunogenicity is directed to a specific epitope in aggregate species.

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Molecular simulation demonstrates biophysical stress enhances epitope presentation.

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Protein aggregates have distinct immunological profiles to their native counterparts.

Aggregation of therapeutic proteins is a key factor in the generation of unwanted immunogenicity, and can result in reduced serum half-life, neutralization of function and adverse health effects. There is currently little information regarding how aggregates interact with B-cell receptors or cognate antibodies at the protein sequence level, or whether non-native, aggregate-induced epitopes predominate in these interactions. Using an antibody fragment (single chain antibody variable fragment; scFv) that forms aggregates readily at low temperature, anti-scFv IgG antibody responses were generated by intraperitoneal injection of BALB/c strain mice with monomer or aggregate preparations. Aggregate-specific immunosignatures were identified by oligo-peptide microarray fine epitope mapping, using overlapping 15mer peptides based on the linear sequence of scFv, printed onto glass slides. IgG antibodies from mice immunized with aggregated scFv preferentially recognized a patch of overlapping peptides. This region mapped to a β-strand located at the interface between the V_H and V_L domains. Molecular dynamics simulations indicated that the V_L domain is less stable than the V_H domain, suggesting the interface region between the two domains becomes exposed during partial unfolding of the scFv during aggregate formation. These data are consistent with the hypothesis that epitopes from partially unfolded states are revealed, or are more fully exposed, in the aggregated state, and that this can augment the IgG antibody response. This observation offers the theoretical possibility that epitopes preferentially associated with aggregates can be identified from the anti-drug antibody serum IgG response which may, in turn, lead to better methods for detection of anti-drug antibody responses, and improved design of therapeutic proteins to control immunogenicity.

High-Density Redox Amplified Coulostatic Discharge-Based Biosensor Array

High-density biosensor arrays are essential for many cutting-edge biomedical applications including point-of-care vaccination screening to detect multiple highly-contagious diseases. Typical electrochemical biosensing techniques are based on the measurement of sub-pA currents for micron-sized sensors requiring highly-sensitive readout circuits. Such circuits are often too complex to scale down for high-density arrays. In this paper, a high-density 4,096-pixel electrochemical biosensor array in 180 nm CMOS is presented. It uses a coulostatic discharge sensing technique and interdigitated electrode geometry to reduce both the complexity and size of the readout circuitry. Each biopixel contains an interdigitated microelectrode with a 13 aA low-leakage readout circuit directly underneath. Compared to standard planar electrodes, the implemented interdigitated electrodes achieve a maximum amplification factor of 10.5× from redox cycling. The array's sensor density is comparable to state-of-the-art arrays, all without augmenting the sensors with complex post-processing. The detection of anti-Rubella and anti-Mumps antibodies in human serum is demonstrated.

Immunosignature Differentiation of Non-Infectious Meningoencephalomyelitis and Intracranial Neoplasia in Dogs

A variety of inflammatory conditions of unknown cause (meningoencephalomyelitis of unknown etiology-MUE) and neoplastic diseases can affect the central nervous system (CNS) of dogs. MUE can mimic intracranial neoplasia both clinically, radiologically and even in some cases, histologically. Serum immunosignature protein microarray assays have been used in humans to identify CNS diseases such as Alzheimer's and neoplasia, and in dogs, to detect lymphoma and its progression. This study evaluated the effectiveness of immunosignature profiles for distinguishing between three cohorts of dogs: healthy, intracranial neoplasia, and MUE. Using the learned peptide patterns for these three cohorts, classification prediction was evaluated for the same groups using a 10-fold cross validation methodology. Accuracy for classification was 100%, as well as 100% specific and 100% sensitive. This pilot study demonstrates that immunosignature profiles may help serve as a minimally invasive tool to distinguish between MUE and intracranial neoplasia in dogs.

Non-natural amino acid peptide microarrays to discover Ebola virus glycoprotein ligands

We demonstrate a platform to screen a virus pseudotyped with Ebola virus glycoprotein (GP) against a library of peptides that contain non-natural amino acids to develop GP affinity ligands. This system could be used for rapid development of peptide-based antivirals for other emerging or neglected tropical infectious diseases.

Utility of dominant epitopes derived from cell-wall protein LppZ for immunodiagnostic of pulmonary tuberculosis

Background

Serological antibodies tests for tuberculosis (TB) are widely used in developing countries. They appear to have some advantages- faster, simple and could be used for extrapulmonary TB. However, most of current commercial TB serological tests are failed to provide sufficient sensitivity and specificity. Improved serological biomarkers were essential. In this study, we present an approach using peptide array to discover new immunodiagnostic biomarkers based on immunodominant epitopes of TB antigens.

Results

The Probable conserved lipoprotein LppZ, which is difficult to express and purify in vivo was selected as the model antigen. We use two-step screening for dominant epitope selection. Based on peptide array data from 170 TB patients and 41 control samples, two dominant epitopes were identified to have diagnostic value for TB patients. Truncation assay was used to identify the core reactive sequence. Peptide- based ELISA was used to evaluate the diagnostic ability of pep-LppZ-1 and pep-LppZ-13. Pep-LppZ-1 has a sensitivity of 49.2% and a specificity of 83.3% in TB diagnose. Pep-LppZ-13 has a sensitivity of 43.3% and a specificity of 88.5% in TB diagnose.

Conclusions

Our result demonstrated that peptide array screening would be an advantage strategy of screening TB diagnostic peptides.

Electronic supplementary material

The online version of this article (10.1186/s12865-018-0243-2) contains supplementary material, which is available to authorized users.

High-titer antibody depletion enhances discovery of diverse serum antibody specificities

The human antibody repertoire is a unique repository of information regarding infection, inflammation, and autoimmunity of the past, present, and future. However, antibodies can span vast ranges of concentrations with varying affinities and the repertoire is often heavily polarized by a few species. These complexities lead to difficulties detecting and characterizing low abundance antibody species that may be relevant to disease. We therefore developed a method to selectively remove antibodies from a sample in proportion to the titer of the species prior to analysis, referred to as high-titer depletion (HTD). Peptides from a large random peptide display library were enriched towards binding high-titer antibody species and utilized as binding reagents to deplete the corresponding species from the specimen. HTD enabled the discovery of antibody binding specificities using random peptide library screening with reduced cross-reactivity and background signal and improved coverage of low abundance species. With HTD, three monoclonal antibody species were detected at concentrations at least an order of magnitude lower than without HTD. Additionally, 92 serum antibody specificities were readily discovered from an individual specimen using HTD compared to only 25 specificities without HTD. Parameters affecting the extent of depletion such as the concentration of depleted serum were also adjusted to reproducibly improve the coverage of antibody specificities. These results demonstrate that HTD could be employed for the discovery of rare specificities related to disease and enable extensive characterization of the antibody repertoire. Moreover, the strategy of depletion in proportion to titer could be extended to other applications with complex biological samples to improve discovery.

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.

Peptide Sequencing Directly on Solid Surfaces Using MALDI Mass Spectrometry

There are an increasing variety of applications in which peptides are both synthesized and used attached to solid surfaces. This has created a need for high throughput sequence analysis directly on surfaces. However, common sequencing approaches that can be adapted to surface bound peptides lack the throughput often needed in library-based applications. Here we describe a simple approach for sequence analysis directly on solid surfaces that is both high speed and high throughput, utilizing equipment available in most protein analysis facilities. In this approach, surface bound peptides, selectively labeled at their N-termini with a positive charge-bearing group, are subjected to controlled degradation in ammonia gas, resulting in a set of fragments differing by a single amino acid that remain spatially confined on the surface they were bound to. These fragments can then be analyzed by MALDI mass spectrometry, and the peptide sequences read directly from the resulting spectra.