Nucleic Acid programmable protein arrays: versatile tools for array-based functional protein studies

Epitope Mapping of Allergenic Lipid Transfer Proteins

Food allergy is becoming a great problem in industrialized countries. Thus, there is the need for a robust understanding of all aspects characterizing IgE response to allergens. The epitope mapping of B-cell epitopes has the potential to become a fundamental tool for food allergy diagnosis and prognosis and to lead to a better understanding of the pathogenesis. Using this approach, we have worked on epitope mapping of the most important plant food allergens identified in the Mediterranean area. The final aim of this study is to define the immune response regarding B epitopes and its clinical relevance in LTP allergy. This chapter describes the protocol to produce microarrays using a library of overlapping peptides corresponding to the primary sequences of allergenic lipid transfer proteins.

Applications of Protein Microarrays in Biomarker Discovery for Autoimmune Diseases

Dysregulated autoantibodies and cytokines were deemed to provide important cues for potential illnesses, such as various carcinomas and autoimmune diseases. Increasing biotechnological approaches have been applied to screen and identify the specific alterations of these biomolecules as distinctive biomarkers in diseases, especially autoimmune diseases. As a versatile and robust platform, protein microarray technology allows researchers to easily profile dysregulated autoantibodies and cytokines associated with autoimmune diseases using various biological specimens, mainly serum samples. Here, we summarize the applications of protein microarrays in biomarker discovery for autoimmune diseases. In addition, the key issues in the process of using this approach are presented for improving future studies.

Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies

Sequences of the genomes of all-important bacterial pathogens of man, plants, and animals have been completed. Still, it is not enough to achieve complete information of all the mechanisms controlling the biological processes of an organism. Along with all advances in different proteomics technologies, proteomics has completed our knowledge of biological processes all around the world. Proteomics is a valuable technique to explain the complement of proteins in any organism. One of the fields that has been notably benefited from other systems approaches is bacterial pathogenesis. An emerging field is to use proteomics to examine the infectious agents in terms of, among many, the response the host and pathogen to the infection process, which leads to a deeper knowledge of the mechanisms of bacterial virulence. This trend also enables us to identify quantitative measurements for proteins extracted from microorganisms. The present review study is an attempt to summarize a variety of different proteomic techniques and advances. The significant applications in bacterial pathogenesis studies are also covered. Moreover, the areas where proteomics may lead the future studies are introduced.

Next Generation Techniques for Determination of Protein-Protein Interactions: Beyond the Crystal Structure

PURPOSE OF REVIEW

We discuss recent advancements in structural biology methods for investigating sites of protein-protein interactions. We will inform readers outside the field of structural biology about techniques beyond crystallography, and how these different technologies can be utilized for drug development.

RECENT FINDINGS

Advancements in cryo-electron microscopy (cryoEM) and micro-electron diffraction (microED) may change how we view atomic resolution structural biology, such that well-ordered macrocrystals of protein complexes are not required for interface identification. However, some drug discovery applications, such as lead peptide compound generation, may not require atomic resolution; mass spectrometry techniques can provide an expedited path to generation of lead compounds. New crosslinking compounds, more user-friendly data analysis, and novel protocols such as protein painting can advance drug discovery programs, even in the absence of atomic resolution structural data. Finally, artificial intelligence and machine learning methods, while never truly replacing experimental methods, may provide rational ways to stratify potential druggable regions identified with mass spectrometry into higher and lower priority candidates.

SUMMARY

Electron diffraction of nanocrystals combines the benefits of both x-ray diffraction and cryoEM, and may prove to be the next generation of atomic resolution protein-protein interface identification. However, in situations such as peptide drug discovery, mass spectrometry techniques supported by advancements in computational methods will likely prove sufficient to support drug discovery efforts. In addition, these methods can be significantly faster than any crystallographic or cryoEM methods for identification of interacting regions.

PhIP-Seq characterization of serum antibodies using oligonucleotide-encoded peptidomes

The binding specificities of an individual's antibody repertoire contain a wealth of biological information. They harbor evidence of environmental exposures, allergies, ongoing or emerging autoimmune disease processes, and responses to immunomodulatory therapies, for example. Highly multiplexed methods to comprehensively interrogate antibody-binding specificities have therefore emerged in recent years as important molecular tools. Here, we provide a detailed protocol for performing 'phage immunoprecipitation sequencing' (PhIP-Seq), which is a powerful method for analyzing antibody-repertoire binding specificities with high throughput and at low cost. The methodology uses oligonucleotide library synthesis (OLS) to encode proteomic-scale peptide libraries for display on bacteriophage. These libraries are then immunoprecipitated, using an individual's antibodies, for subsequent analysis by high-throughput DNA sequencing. We have used PhIP-Seq to identify novel self-antigens associated with autoimmune disease, to characterize the self-reactivity of broadly neutralizing HIV antibodies, and in a large international cross-sectional study of exposure to hundreds of human viruses. Compared with alternative array-based techniques, PhIP-Seq is far more scalable in terms of sample throughput and cost per analysis. Cloning and expression of recombinant proteins are not required (versus protein microarrays), and peptide lengths are limited only by DNA synthesis chemistry (up to 90-aa (amino acid) peptides versus the typical 8- to 12-aa length limit of synthetic peptide arrays). Compared with protein microarrays, however, PhIP-Seq libraries lack discontinuous epitopes and post-translational modifications. To increase the accessibility of PhIP-Seq, we provide detailed instructions for the design of phage-displayed peptidome libraries, their immunoprecipitation using serum antibodies, deep sequencing-based measurement of peptide abundances, and statistical determination of peptide enrichments that reflect antibody-peptide interactions. Once a library has been constructed, PhIP-Seq data can be obtained for analysis within a week.

A decade of Nucleic Acid Programmable Protein Arrays (NAPPA) availability: News, actors, progress, prospects and access

Understanding the dynamic of the proteome is a critical challenge because it requires high sensitive methodologies in high-throughput formats in order to decipher its modifications and complexity. While molecular biology provides relevant information about cell physiology that may be reflected in post-translational changes, High-Throughput (HT) experimental proteomic techniques are essential to provide valuable functional information of the proteins, peptides and the interconnections between them. Hence, many methodological developments and innovations have been reported during the last decade. To study more dynamic protein networks and fine interactions, Nucleic Acid Programmable Protein Arrays (NAPPA) was introduced a decade ago. The tool is rapidly maturing and serving as a gateway to characterize biological systems and diseases thanks primarily to its accuracy, reproducibility, throughput and flexibility. Currently, NAPPA technology has proved successful in several research areas adding valuable information towards innovative diagnostic and therapeutic applications. Here, the basic and latest advances within this modern technology in basic, translational research are reviewed, in addition to presenting its exciting new directions. Our final goal is to encourage more scientists/researchers to incorporate this method, which can help to remove bottlenecks in their particular research or biomedical projects. SIGNIFICANCE: Nucleic Acid Programmable Protein Arrays (NAPPA) is becoming an essential tool for functional proteomics and protein-protein interaction studies. The technology impacts decisively on projects aiming massive screenings and the latest innovations like the multiplexing capability or printing consistency make this a promising method to be integrated in novel and combinatorial proteomic approaches.

Hub Protein Controversy: Taking a Closer Look at Plant Stress Response Hubs

Plant stress responses involve numerous changes at the molecular and cellular level and are regulated by highly complex signaling pathways. Studying protein-protein interactions (PPIs) and the resulting networks is therefore becoming increasingly important in understanding these responses. Crucial in PPI networks are the so-called hubs or hub proteins, commonly defined as the most highly connected central proteins in scale-free PPI networks. However, despite their importance, a growing amount of confusion and controversy seems to exist regarding hub protein identification, characterization and classification. In order to highlight these inconsistencies and stimulate further clarification, this review critically analyses the current knowledge on hub proteins in the plant interactome field. We focus on current hub protein definitions, including the properties generally seen as hub-defining, and the challenges and approaches associated with hub protein identification. Furthermore, we give an overview of the most important large-scale plant PPI studies of the last decade that identified hub proteins, pointing out the lack of overlap between different studies. As such, it appears that although major advances are being made in the plant interactome field, defining hub proteins is still heavily dependent on the quality, origin and interpretation of the acquired PPI data. Nevertheless, many hub proteins seem to have a reported role in the plant stress response, including transcription factors, protein kinases and phosphatases, ubiquitin proteasome system related proteins, (co-)chaperones and redox signaling proteins. A significant number of identified plant stress hubs are however still functionally uncharacterized, making them interesting targets for future research. This review clearly shows the ongoing improvements in the plant interactome field but also calls attention to the need for a more comprehensive and precise identification of hub proteins, allowing a more efficient systems biology driven unraveling of complex processes, including those involved in stress responses.

Discovering Protein-Protein Interactions Using Nucleic Acid Programmable Protein Arrays

We have developed a protocol enabling the study of protein-protein interactions (PPIs) at the proteome level using in vitro-synthesized proteins. Assay preparation requires molecular cloning of the query gene into a vector that supports in vitro transcription/translation (IVTT) and appends a HaloTag to the query protein of interest. In parallel, protein microarrays are prepared by printing plasmids encoding glutathione S-transferase (GST)-tagged target proteins onto a carrier matrix/glass slide coated with antibody directed against GST. At the time of the experiment, the query protein and the target protein are produced separately through IVTT. The query protein is then applied to nucleic acid programmable protein arrays (NAPPA) that display thousands of freshly produced target proteins captured by anti-GST antibody. Interactions between the query and immobilized target proteins are detected through addition of a fluorophore-labeled HaloTag ligand. Our protocol allows the elucidation of PPIs in a high-throughput fashion using proteins produced in vitro, obviating the scientific challenges, high cost, and laborious work, as well as concerns about protein stability, which are usually present in protocols using conventional protein arrays. © 2017 by John Wiley & Sons, Inc.

Proteomics Tracing the Footsteps of Infectious Disease

Every year, a major cause of human disease and death worldwide is infection with the various pathogens-viruses, bacteria, fungi, and protozoa-that are intrinsic to our ecosystem. In efforts to control the prevalence of infectious disease and develop improved therapies, the scientific community has focused on building a molecular picture of pathogen infection and spread. These studies have been aimed at defining the cellular mechanisms that allow pathogen entry into hosts cells, their replication and transmission, as well as the core mechanisms of host defense against pathogens. The past two decades have demonstrated the valuable implementation of proteomic methods in all these areas of infectious disease research. Here, we provide a perspective on the contributions of mass spectrometry and other proteomics approaches to understanding the molecular details of pathogen infection. Specifically, we highlight methods used for defining the composition of viral and bacterial pathogens and the dynamic interaction with their hosts in space and time. We discuss the promise of MS-based proteomics in supporting the development of diagnostics and therapies, and the growing need for multiomics strategies for gaining a systems view of pathogen infection.

Tracking the Antibody Immunome in Type 1 Diabetes Using Protein Arrays

We performed an unbiased proteome-scale profiling of humoral autoimmunity in recent-onset type 1 diabetes (T1D) patients and nondiabetic controls against ∼10 000 human proteins using a Nucleic Acid Programmable Protein Array (NAPPA) platform, complemented by a knowledge-based selection of proteins from genes enriched in human pancreas. Although the global response was similar between cases and controls, we identified and then validated six specific novel T1D-associated autoantibodies (AAbs) with sensitivities that ranged from 16 to 27% at 95% specificity. These included AAbs against PTPRN2, MLH1, MTIF3, PPIL2, NUP50 (from NAPPA screening), and QRFPR (by targeted ELISA). Immunohistochemistry demonstrated that NUP50 protein behaved differently in islet cells, where it stained both nucleus and cytoplasm, compared with only nuclear staining in exocrine pancreas. Conversely, PPIL2 staining was absent in islet cells, despite its presence in exocrine cells. The combination of anti-PTPRN2, -MLH1, -PPIL2, and -QRFPR had an AUC of 0.74 and 37.5% sensitivity at 95% specificity. These data indicate that these markers behave independently and support the use of unbiased screening to find biomarkers because the majority was not predicted based on predicted abundance. Our study enriches the knowledge of the "autoantibody-ome" in unprecedented breadth and width.

Bulked sample analysis in genetics, genomics and crop improvement

Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high-throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker-assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.

Immunoproteomic Profiling of Antiviral Antibodies in New-Onset Type 1 Diabetes Using Protein Arrays

The rapid rise in the incidence of type 1 diabetes (T1D) suggests the involvement of environmental factors including viral infections. We evaluated the association between viral infections and T1D by profiling antiviral antibodies using a high-throughput immunoproteomics approach in patients with new-onset T1D. We constructed a viral protein array comprising the complete proteomes of seven viruses associated with T1D and open reading frames from other common viruses. Antibody responses to 646 viral antigens were assessed in 42 patients with T1D and 42 age- and sex-matched healthy control subjects (mean age 12.7 years, 50% males). Prevalence of antiviral antibodies agreed with known infection rates for the corresponding virus based on epidemiological studies. Antibody responses to Epstein-Barr virus (EBV) were significantly higher in case than control subjects (odds ratio 6.6; 95% CI 2.0-25.7), whereas the other viruses showed no differences. The EBV and T1D association was significant in both sex and age subgroups (≤12 and >12 years), and there was a trend toward early EBV infections among the case subjects. These results suggest a potential role for EBV in T1D development. We believe our innovative immunoproteomics platform is useful for understanding the role of viral infections in T1D and other disorders where associations between viral infection and disease are unclear.

Antiviral antibody profiling by high-density protein arrays

Viral infections elicit antiviral antibodies and have been associated with various chronic diseases. Detection of these antibodies can facilitate diagnosis, treatment of infection, and understanding of the mechanisms of virus-associated diseases. In this work, we assayed antiviral antibodies using a novel high-density nucleic acid programmable protein array (HD-NAPPA) platform. Individual viral proteins were expressed in situ directly from plasmids encoding proteins in an array of microscopic reaction chambers. Quality of protein display and serum response was assured by comparing intra- and inter-array correlation within or between printing batches with average correlation coefficients of 0.91 and 0.96, respectively. HD-NAPPA showed higher signal-to-background ratio compared with standard NAPPA on planar glass slides and ELISA. Antibody responses to 761 antigens from 25 different viruses were profiled among patients with juvenile idiopathic arthritis and type 1 diabetes. Common and unique antibody reactivity patterns were detected between patients and healthy controls. We believe HD-viral-NAPPA will enable the study of host-pathogen interactions at unprecedented dimensions and elucidate the role of pathogen infections in disease development.

High-throughput identification of proteins with AMPylation using self-assembled human protein (NAPPA) microarrays

AMPylation (adenylylation) has been recognized as an important post-translational modification that is used by pathogens to regulate host cellular proteins and their associated signaling pathways. AMPylation has potential functions in various cellular processes, and it is widely conserved across both prokaryotes and eukaryotes. However, despite the identification of many AMPylators, relatively few candidate substrates of AMPylation are known. This is changing with the recent development of a robust and reliable method for identifying new substrates using protein microarrays, which can markedly expand the list of potential substrates. Here we describe procedures for detecting AMPylated and auto-AMPylated proteins in a sensitive, high-throughput and nonradioactive manner. The approach uses high-density protein microarrays fabricated using nucleic acid programmable protein array (NAPPA) technology, which enables the highly successful display of fresh recombinant human proteins in situ. The modification of target proteins is determined via copper-catalyzed azide-alkyne cycloaddition (CuAAC). The assay can be accomplished within 11 h.

Overview of cell-free protein synthesis: historic landmarks, commercial systems, and expanding applications

During the early days of molecular biology, cell-free protein synthesis played an essential role in deciphering the genetic code and contributed to our understanding of translation of protein from messenger RNA. Owing to several decades of major and incremental improvements, modern cell-free systems have achieved higher protein synthesis yields at lower production costs. Commercial cell-free systems are now available from a variety of material sources, ranging from "traditional" E. coli, rabbit reticulocyte lysate, and wheat germ extracts, to recent insect and human cell extracts, to defined systems reconstituted from purified recombinant components. Although each cell-free system has certain advantages and disadvantages, the diversity of the cell-free systems allows in vitro synthesis of a wide range of proteins for a variety of downstream applications. In the post-genomic era, cell-free protein synthesis has rapidly become the preferred approach for high-throughput functional and structural studies of proteins and a versatile tool for in vitro protein evolution and synthetic biology. This unit provides a brief history of cell-free protein synthesis and describes key advances in modern cell-free systems, practical differences between widely used commercial cell-free systems, and applications of this important technology.

Robust microarray production of freshly expressed proteins in a human milieu

PURPOSE

In vitro transcription/translation (IVTT) systems are widely used in proteomics. For clinical applications, mammalian systems are preferred for protein folding and activity; however, the level of protein obtained is low. A new system extracted from human cells (1-Step Human Coupled IVT (HCIVT)) has the potential to overcome this problem and deliver high yields of protein expressed in a human milieu.

EXPERIMENTAL DESIGN

Western blots and self-assembled protein microarrays were used to test the efficiency of protein synthesis by HCIVT compared to rabbit reticulocyte lysate (RRL). The arrays were also used to measure the immune response obtained from serum of patients exposed to pathogens or vaccine.

RESULTS

HCIVT performed better than RRL in all experiments. The yield of protein synthesized in HCIVT is more than ten times higher than RRL, in both Western blot and protein microarrays. Moreover, HCIVT showed a robust lot-to-lot reproducibility. In immune assays, the signals of many antigens were detected only in HCIVT-expressed arrays, mainly due to the reduction in the background signal and the increased levels of protein on the array.

CONCLUSION AND CLINICAL RELEVANCE

HCIVT is a robust in vitro transcription and translation system that yields high levels of protein produced in a human milieu. It can be used in applications where protein expression in a mammalian system and high yields are needed. The increased immunogenic response of HCIVT-expressed proteins will be critical for biomarker discovery in many diseases, including cancer.

High-throughput screening for native autoantigen-autoantibody complexes using antibody microarrays

We report on a novel, high-dimensional method to detect autoantibodies that are complexed with their natural autoantigens. Specifically, autoantibody-autoantigen complexes in serum or plasma are directly incubated onto a high-density antibody microarray. Detection of the bound autoantibody-antigen complex is made via fluorescently labeled antihuman immunoglobulin G or other immunoglobulin isotype secondary antibodies and quantification in a microarray scanner. Uncomplexed antibodies do not interfere with this assay. The whole process is very rapid and applicable for high-throughput screening without the need for production of proteins or immunoglobulin purification from the samples. Using these methods, we found that plasma from healthy individuals contains hundreds of autoantibodies complexed with cellular proteins. Thus, this highly sensitive, multiplex method is capable of discovering new autoantibody-antigen or circulating immune complexes, many of which will likely be useful for disease detection and characterization.

Personal genomes, quantitative dynamic omics and personalized medicine

The rapid technological developments following the Human Genome Project have made possible the availability of personalized genomes. As the focus now shifts from characterizing genomes to making personalized disease associations, in combination with the availability of other omics technologies, the next big push will be not only to obtain a personalized genome, but to quantitatively follow other omics. This will include transcriptomes, proteomes, metabolomes, antibodyomes, and new emerging technologies, enabling the profiling of thousands of molecular components in individuals. Furthermore, omics profiling performed longitudinally can probe the temporal patterns associated with both molecular changes and associated physiological health and disease states. Such data necessitates the development of computational methodology to not only handle and descriptively assess such data, but also construct quantitative biological models. Here we describe the availability of personal genomes and developing omics technologies that can be brought together for personalized implementations and how these novel integrated approaches may effectively provide a precise personalized medicine that focuses on not only characterization and treatment but ultimately the prevention of disease.

Interactome mapping for analysis of complex phenotypes: insights from benchmarking binary interaction assays

Protein interactions mediate essentially all biological processes and analysis of protein-protein interactions using both large-scale and small-scale approaches has contributed fundamental insights to the understanding of biological systems. In recent years, interactome network maps have emerged as an important tool for analyzing and interpreting genetic data of complex phenotypes. Complementary experimental approaches to test for binary, direct interactions, and for membership in protein complexes are used to explore the interactome. The two approaches are not redundant but yield orthogonal perspectives onto the complex network of physical interactions by which proteins mediate biological processes. In recent years, several publications have demonstrated that interactions from high-throughput experiments can be equally reliable as the high quality subset of interactions identified in small-scale studies. Critical for this insight was the introduction of standardized experimental benchmarking of interaction and validation assays using reference sets. The data obtained in these benchmarking experiments have resulted in greater appreciation of the limitations and the complementary strengths of different assays. Moreover, benchmarking is a central element of a conceptual framework to estimate interactome sizes and thereby measure progress toward near complete network maps. These estimates have revealed that current large-scale data sets, although often of high quality, cover only a small fraction of a given interactome. Here, I review the findings of assay benchmarking and discuss implications for quality control, and for strategies toward obtaining a near-complete map of the interactome of an organism.

Validation processes of protein biomarkers in serum--a cross platform comparison

Due to insufficient biomarker validation and poor performances in diagnostic assays, the candidate biomarker verification process has to be improved. Multi-analyte immunoassays are the tool of choice for the identification and detailed validation of protein biomarkers in serum. The process of identification and validation of serum biomarkers, as well as their implementation in diagnostic routine requires an application of independent immunoassay platforms with the possibility of high-throughput. This review will focus on three main multi-analyte immunoassay platforms: planar microarrays, multiplex bead systems and, array-based surface plasmon resonance (SPR) chips. Recent developments of each platform will be discussed for application in clinical proteomics, principles, detection methods, and performance strength. The requirements for specific surface functionalization of assay platforms are continuously increasing. The reasons for this increase is the demand for highly sensitive assays, as well as the reduction of non-specific adsorption from complex samples, and with it high signal-to-noise-ratios. To achieve this, different support materials were adapted to the immobilized biomarker/ligand, allowing a high binding capacity and immobilization efficiency. In the case of immunoassays, the immobilized ligands are proteins, antibodies or peptides, which exhibit a diversity of chemical properties (acidic/alkaline; hydrophobic/hydrophilic; secondary or tertiary structure/linear). Consequently it is more challenging to develop immobilization strategies necessary to ensure a homogenous covered surface and reliable assay in comparison to DNA immobilization. New developments concerning material support for each platform are discussed especially with regard to increase the immobilization efficiency and reducing the non-specific adsorption from complex samples like serum and cell lysates.

Protein microarrays, biosensors, and cell-based methods for secretome-wide extracellular protein-protein interaction mapping

Approximately one quarter of all human genes encode proteins that function in the extracellular space or serve to bridge the extracellular and intracellular environments. Physical associations between these secretome proteins serve to regulate a wide range of biological activities and consequently represent important therapeutic targets. Moreover, some extracellular proteins are targeted by pathogens to allow host access or immune evasion. Despite the importance of extracellular protein-protein interactions, our knowledge in this area has remained sparse. Weak affinities and low abundance have often hindered efforts to identify these interactions using traditional methods such as biochemical purification and cDNA library expression cloning. Moreover, current large-scale protein-protein interaction mapping techniques largely under represent extracellular protein-protein interactions. This review highlights emerging biosensor and protein microarray technology, along with more traditional cell-based techniques, that are compatible with secretome-wide screens for extracellular protein-protein interaction discovery. A combination of these approaches will serve to rapidly expand our knowledge of the extracellular protein-protein interactome.