Citrullination of a phage-displayed human peptidome library reveals the fine specificities of rheumatoid arthritis-associated autoantibodies

A quantitative and site-specific atlas of the citrullinome reveals widespread existence of citrullination and insights into PADI4 substrates

Despite the importance of citrullination in physiology and disease, global identification of citrullinated proteins, and the precise targeted sites, has remained challenging. Here we employed quantitative-mass-spectrometry-based proteomics to generate a comprehensive atlas of citrullination sites within the HL60 leukemia cell line following differentiation into neutrophil-like cells. We identified 14,056 citrullination sites within 4,008 proteins and quantified their regulation upon inhibition of the citrullinating enzyme PADI4. With this resource, we provide quantitative and site-specific information on thousands of PADI4 substrates, including signature histone marks and transcriptional regulators. Additionally, using peptide microarrays, we demonstrate the potential clinical relevance of certain identified sites, through distinct reactivities of antibodies contained in synovial fluid from anti-CCP-positive and anti-CCP-negative people with rheumatoid arthritis. Collectively, we describe the human citrullinome at a systems-wide level, provide a resource for understanding citrullination at the mechanistic level and link the identified targeted sites to rheumatoid arthritis.

Breaking tolerance: autoantibodies can target protein posttranslational modifications

Autoantibodies (AAb) are an immunological resource ripe for exploitation in cancer detection and treatment. Key to this translation is a better understanding of the self-epitope that AAb target in tumor tissue, but do not bind to in normal tissue. Posttranslational modifications (PTMs) on self-proteins are known to break tolerance in many autoimmune diseases and have also recently been described in cancer. This scope of possible autoantigens is quite broad and new high-dimensional and -throughput technologies to probe this repertoire will be necessary to fully exploit their potential. Here, we discuss the strengths and weaknesses of existing high-throughput platforms to detect AAb, review the current methods for characterizing immunogenic PTMs, describe the main challenges to identifying disease-relevant antigens and suggest the properties of future technologies that may be able to address these challenges. We conclude that exploiting the evolutionary power of the immune system to distinguish between self and nonself has great potential to be translated into antibody-based clinical applications.

Phage Immunoprecipitation Sequencing (PhIP-Seq) for Analyzing Antibody Epitope Repertoires Against Food Antigens

While thousands of food and environmental allergens have been reported, conventional methods for allergy testing typically rely on measuring immunoglobulin E (IgE) binding against panels of dozens to hundreds of antigens. Beyond IgE, also the specificity of other Ig (sub-)classes such as IgG4, has gained interest because of a potential protective role toward allergy.Phage immunoprecipitation sequencing (PhIP-Seq) allows to study hundreds of thousands of rationally selected peptide antigens and to resolve binding specificities of different Ig classes. This technology combines synthetic DNA libraries encoding antigens, with the display on the surface of T7 bacteriophages and next-generation sequencing (NGS) for quantitative readouts. Thereby binding of entire Ig repertoires can be measured to detect the exact epitopes of food allergens and to study potential cross-reactivity.In this chapter, we provide a summary of both the key experimental steps and various strategies for analyzing PhIP-Seq datasets, as well as comparing the advantages and disadvantages of this methodology for measuring antibody responses against food antigens.

Exploring Immunome and Microbiome Interplay in Reproductive Health: Current Knowledge, Challenges, and Novel Diagnostic Tools

The dynamic interplay between the immunome and microbiome in reproductive health is a complex and rapidly advancing research field, holding tremendously vast possibilities for the development of reproductive medicine. This immunome-microbiome relationship influences the innate and adaptive immune responses, thereby affecting the onset and progression of reproductive disorders. However, the mechanisms governing these interactions remain elusive and require innovative approaches to gather more understanding. This comprehensive review examines the current knowledge on reproductive microbiomes across various parts of female reproductive tract, with special consideration of bidirectional interactions between microbiomes and the immune system. Additionally, it explores innate and adaptive immunity, focusing on immunoglobulin (Ig) A and IgM antibodies, their regulation, self-antigen tolerance mechanisms, and their roles in immune homeostasis. This review also highlights ongoing technological innovations in microbiota research, emphasizing the need for standardized detection and analysis methods. For instance, we evaluate the clinical utility of innovative technologies such as Phage ImmunoPrecipitation Sequencing (PhIP-Seq) and Microbial Flow Cytometry coupled to Next-Generation Sequencing (mFLOW-Seq). Despite ongoing advancements, we emphasize the need for further exploration in this field, as a deeper understanding of immunome-microbiome interactions holds promise for innovative diagnostic and therapeutic strategies for reproductive health, like infertility treatment and management of pregnancy.

Phage display sequencing reveals that genetic, environmental, and intrinsic factors influence variation of human antibody epitope repertoire

Phage-displayed immunoprecipitation sequencing (PhIP-seq) has enabled high-throughput profiling of human antibody repertoires. However, a comprehensive overview of environmental and genetic determinants shaping human adaptive immunity is lacking. In this study, we investigated the effects of genetic, environmental, and intrinsic factors on the variation in human antibody repertoires. We characterized serological antibody repertoires against 344,000 peptides using PhIP-seq libraries from a wide range of microbial and environmental antigens in 1,443 participants from a population cohort. We detected individual-specificity, temporal consistency, and co-housing similarities in antibody repertoires. Genetic analyses showed the involvement of the HLA, IGHV, and FUT2 gene regions in antibody-bound peptide reactivity. Furthermore, we uncovered associations between phenotypic factors (including age, cell counts, sex, smoking behavior, and allergies, among others) and particular antibody-bound peptides. Our results indicate that human antibody epitope repertoires are shaped by both genetics and environmental exposures and highlight specific signatures of distinct phenotypes and genotypes.

Citrullination modulates antigen processing and presentation by revealing cryptic epitopes in rheumatoid arthritis

Cryptic peptides, hidden from the immune system under physiologic conditions, are revealed by changes to MHC class II processing and hypothesized to drive the loss of immune tolerance to self-antigens in autoimmunity. Rheumatoid arthritis (RA) is an autoimmune disease characterized by immune responses to citrullinated self-antigens, in which arginine residues are converted to citrullines. Here, we investigate the hypothesis that citrullination exposes cryptic peptides by modifying protein structure and proteolytic cleavage. We show that citrullination alters processing and presentation of autoantigens, resulting in the generation of a unique citrullination-dependent repertoire composed primarily of native sequences. This repertoire stimulates T cells from RA patients with anti-citrullinated protein antibodies more robustly than controls. The generation of this unique repertoire is achieved through altered protease cleavage and protein destabilization, rather than direct presentation of citrulline-containing epitopes, suggesting a novel paradigm for the role of protein citrullination in the breach of immune tolerance in RA.

Autoantibody discovery across monogenic, acquired, and COVID-19-associated autoimmunity with scalable PhIP-seq

Phage immunoprecipitation sequencing (PhIP-seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-seq for autoantigen discovery, including our previous work (Vazquez et al., 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), and finally, mild and severe forms of COVID-19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as prodynorphin (PDYN) in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in two patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID-19, including the endosomal protein EEA1. Together, scaled PhIP-seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.

Unbiased discovery of autoantibodies associated with severe COVID-19 via genome-scale self-assembled DNA-barcoded protein libraries

Pathogenic autoreactive antibodies that may be associated with life-threatening coronavirus disease 2019 (COVID-19) remain to be identified. Here, we show that self-assembled genome-scale libraries of full-length proteins covalently coupled to unique DNA barcodes for analysis by sequencing can be used for the unbiased identification of autoreactive antibodies in plasma samples. By screening 11,076 DNA-barcoded proteins expressed from a sequence-verified human ORFeome library, the method, which we named MIPSA (for Molecular Indexing of Proteins by Self-Assembly), allowed us to detect circulating neutralizing type-I and type-III interferon (IFN) autoantibodies in five plasma samples from 55 patients with life-threatening COVID-19. In addition to identifying neutralizing type-I IFN-α and IFN-ω autoantibodies and other previously known autoreactive antibodies in patient plasma, MIPSA enabled the detection of as yet unidentified neutralizing type-III anti-IFN-λ3 autoantibodies that were not seen in healthy plasma samples or in convalescent plasma from ten non-hospitalized individuals with COVID-19. The low cost and simple workflow of MIPSA will facilitate unbiased high-throughput analyses of protein-antibody, protein-protein and protein-small-molecule interactions.

Phage ImmunoPrecipitation Sequencing (PhIP-Seq): The Promise of High Throughput Serology

Simple Summary

Determining the exposure or infection history of a person to a multitude of viruses is not an easy task. Typically, antibody tests detect antibodies against proteins (antigens) to only one or a few viruses. Here, we review an emerging technology called Phage ImmunoPrecipitation Sequencing (PhIP-Seq), that allows us to study the infection history of individuals to large numbers of viruses simultaneously. This technology uses bacteriophages to express and display viral antigens of choice, which are then bound by antigen-specific antibodies in patient samples. Antibody-bound bacteriophages are pulled down and identified through molecular techniques. This technology has been used in various infectious disease scenarios, including assessing exposure to different viruses, studying vaccine responses, and identifying viral cause of diseases. Despite inherent limitations in presenting only peptides, this technology holds great promise for future application in identifying novel pathogens, one health and pandemic preparedness.

Abstract

Phage ImmunoPrecipitation Sequencing (PhIP-Seq) is a high throughput serological technology that is revolutionizing the manner in which we track antibody profiles. In this review, we mainly focus on its application to viral infectious diseases. Through the pull-down of patient antibodies using peptide-tile-expressing T7 bacteriophages and detection using next-generation sequencing (NGS), PhIP-Seq allows the determination of antibody repertoires against peptide targets from hundreds of proteins and pathogens. It differs from conventional serological techniques in that PhIP-Seq does not require protein expression and purification. It also allows for the testing of many samples against the whole virome. PhIP-Seq has been successfully applied in many infectious disease investigations concerning seroprevalence, risk factors, time trends, etiology of disease, vaccinology, and emerging pathogens. Despite the inherent limitations of this technology, we foresee the future expansion of PhIP-Seq in both investigative studies and tracking of current, emerging, and novel viruses. Following the review of PhIP-Seq technology, its limitations, and applications, we recommend that PhIP-Seq be integrated into national surveillance programs and be used in conjunction with molecular techniques to support both One Health and pandemic preparedness efforts.

Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq.. [PMID: 35350199 PMCID: PMC8963698 DOI: 10.1101/2022.03.23.485509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Phage Immunoprecipitation-Sequencing (PhIP-Seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-Seq for autoantigen discovery, including our previous work (Vazquez et al. 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), and finally, mild and severe forms of COVID19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as PDYN in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in 2 patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-Seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID19, including the endosomal protein EEA1. Together, scaled PhIP-Seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.