Citrullination by peptidylarginine deiminase in rheumatoid arthritis

Mechanisms of immune tolerance breakdown in paraneoplastic neurological syndromes

Paraneoplastic neurological syndromes (PNS) are rare autoimmune disorders triggered by the presence of a cancer. The autoimmunity is herein directed against proteins expressed both in the tumor and in the nervous system, namely the onconeural antigens, against which are directed specific autoantibodies, each of them characterizing a neurological syndrome. The mechanisms of the immune tolerance breakdown in PNS leading to the production of specific autoantibodies directed against the nervous system and leading to the immune attack begins to be explained. Each syndrome is associated with a specific histo-molecular subtype of tumor suggesting a link between the PNS genesis and oncogenesis. The expression of the onconeural antigen by these tumors is insufficient to explain the immune tolerance breakdown. In some PNS tumors, alterations of the antigen have been identified: mutations, gene copy number variation and overexpression of transcript and protein. But in others PNS, no such molecular alterations of the onconeural antigens have been demonstrated. In these cases, other mechanisms of neoantigen generation that may be involved remain to be deciphered. Cancer outcomes of PNS tumors are also characterized by the high frequency of lymph node metastasis at diagnosis. At the primary tumor site, the antitumor immune reaction seems to be particularly intense and characterized by a prominence of B-cell and Ig-secreting plasma cells that may generate the autoantibody secretion. The immune control mechanisms leading to such organization of the immune attack are not known to date. Renewed research efforts are thus needed to better understand the mechanism of immune tolerance breakdown in each PNS and determine potential targets to meet the therapeutic challenges posed by these rare disorders.

DeepPRMS: advanced deep learning model to predict protein arginine methylation sites

Protein methylation is a form of post-translational modifications of protein, which is crucial for various cellular processes, including transcription activity and DNA repair. Correctly predicting protein methylation sites is fundamental for research and drug discovery. Some experimental techniques, such as methyl-specific antibodies, chromatin immune precipitation and mass spectrometry, exist for predicting protein methylation sites, but these techniques are time-consuming and costly. The ability to predict methylation sites using in silico techniques may help researchers identify potential candidate sites for future examination and make it easier to carry out site-specific investigations and downstream characterizations. In this research, we proposed a novel deep learning-based predictor, named DeepPRMS, to identify protein methylation sites in primary sequences. The DeepPRMS utilizes the gated recurrent unit (GRU) and convolutional neural network (CNN) algorithms to extract the sequential and spatial information from the primary sequences. GRU is used to extract sequential information, while CNN is used for spatial information. We combined the latent representation of GRU and CNN models to have a better interaction among them. Based on the independent test data set, DeepPRMS obtained an accuracy of 85.32%, a specificity of 84.94%, Matthew's correlation coefficient of 0.71 and a sensitivity of 85.80%. The results indicate that DeepPRMS can predict protein methylation sites with high accuracy and outperform the state-of-the-art models. The DeepPRMS is expected to effectively guide future research experiments for identifying potential methylated protein sites. The web server is available at http://deepprms.nitsri.ac.in/.

Co-expression of PADI isoforms during progenitor differentiation enables functional diversity

Protein isoforms, generated through alternative splicing or promoter usage, contribute to tissue function. Here, we characterize the expression of predicted Padi3α and Padi3β isoforms in hair follicles and describe expression of Padi2β, a hitherto unknown PADI2 isoform, in the oligodendrocyte lineage. Padi2β transcription is initiated from a downstream intronic promoter, generating an N-terminally truncated, unstable, PADI2β. By contrast to the established role of the canonical PADI2 (PADI2α) (Falcao et al. 2019 Cell Rep. 27, 1090-1102.e10. (doi:10.1016/j.celrep.2019.03.108)), PADI2β inhibits oligodendrocyte differentiation, suggesting that PADI2 isoforms exert opposing effects on oligodendrocyte lineage progression. We localize Padi3α and Padi3β to developing hair follicles and find that both transcripts are expressed at low levels in progenitor cells, only to increase in expression concomitant with differentiation. When expressed in vitro, PADI3α and PADI3β are enriched in the cytoplasm and precipitate together. Whereas PADI3β protein stability is low and PADI3β fails to induce protein citrullination, we find that the enzymatic activity and protein stability of PADI3α is reduced in the presence of PADI3β. We propose that PADI3β modulates PADI3α activity by direct binding and heterodimer formation. Here, we establish expression and function of Padi2 and Padi3 isoforms, expanding on the mechanisms in place to regulate citrullination in complex tissues. This article is part of the Theo Murphy meeting issue 'The virtues and vices of protein citrullination'.

PRMxAI: protein arginine methylation sites prediction based on amino acid spatial distribution using explainable artificial intelligence

BACKGROUND

Protein methylation, a post-translational modification, is crucial in regulating various cellular functions. Arginine methylation is required to understand crucial biochemical activities and biological functions, like gene regulation, signal transduction, etc. However, some experimental methods, including Chip-Chip, mass spectrometry, and methylation-specific antibodies, exist for the prediction of methylated proteins. These experimental methods are expensive and tedious. As a result, computational methods based on machine learning play an efficient role in predicting arginine methylation sites.

RESULTS

In this research, a novel method called PRMxAI has been proposed to predict arginine methylation sites. The proposed PRMxAI extract sequence-based features, such as dipeptide composition, physicochemical properties, amino acid composition, and information theory-based features (Arimoto, Havrda-Charvat, Renyi, and Shannon entropy), to represent the protein sequences into numerical format. Various machine learning algorithms are implemented to select the better classifier, such as Decision trees, Naive Bayes, Random Forest, Support vector machines, and K-nearest neighbors. The random forest algorithm is selected as the underlying classifier for the PRMxAI model. The performance of PRMxAI is evaluated by employing 10-fold cross-validation, and it yields 87.17% and 90.40% accuracy on mono-methylarginine and di-methylarginine data sets, respectively. This research also examines the impact of various features on both data sets using explainable artificial intelligence.

CONCLUSIONS

The proposed PRMxAI shows the effectiveness of the features for predicting arginine methylation sites. Additionally, the SHapley Additive exPlanation method is used to interpret the predictive mechanism of the proposed model. The results indicate that the proposed PRMxAI model outperforms other state-of-the-art predictors.

Role of non-canonical post-translational modifications in gastrointestinal tumors

Post-translational modifications (PTMs) of proteins contribute to the occurrence and development of tumors. Previous studies have suggested that canonical PTMs such as ubiquitination, glycosylation, and phosphorylation are closely implicated in different aspects of gastrointestinal tumors. Recently, emerging evidence showed that non-canonical PTMs play an essential role in the carcinogenesis, metastasis and treatment of gastrointestinal tumors. Therefore, we summarized recent advances in sumoylation, neddylation, isoprenylation, succinylation and other non-canonical PTMs in gastrointestinal tumors, which comprehensively describe the mechanisms and functions of non-classical PTMs in gastrointestinal tumors. It is anticipated that targeting specific PTMs could benefit the treatment as well as improve the prognosis of gastrointestinal tumors.

The Role of Autophagy as a Trigger of Post-Translational Modifications of Proteins and Extracellular Vesicles in the Pathogenesis of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease, characterized by persistent joint inflammation, leading to cartilage and bone destruction. Autoantibody production is directed to post-translational modified (PTM) proteins, i.e., citrullinated or carbamylated. Autophagy may be the common feature in several types of stress (smoking, joint injury, and infections) and may be involved in post-translational modifications (PTMs) in proteins and the generation of citrullinated and carbamylated peptides recognized by the immune system in RA patients, with a consequent breakage of tolerance. Interestingly, autophagy actively provides information to neighboring cells via a process called secretory autophagy. Secretory autophagy combines the autophagy machinery with the secretion of cellular content via extracellular vesicles (EVs). A role for exosomes in RA pathogenesis has been recently demonstrated. Exosomes are involved in intercellular communications, and upregulated proteins and RNAs may contribute to the development of inflammatory arthritis and the progression of RA. In RA, most of the exosomes are produced by leukocytes and synoviocytes, which are loaded with PTM proteins, mainly citrullinated proteins, inflammatory molecules, and enzymes that are implicated in RA pathogenesis. Microvesicles derived from cell plasma membrane may also be loaded with PTM proteins, playing a role in the immunopathogenesis of RA. An analysis of changes in EV profiles, including PTM proteins, could be a useful tool for the prevention of inflammation in RA patients and help in the discovery of personalized medicine.

Increased risk of periodontitis in patients with rheumatoid arthritis: A nationwide register study in Norway

AIM

To investigate the risk of periodontitis in rheumatoid arthritis (RA) patients in a nationwide register-based study.

MATERIALS AND METHODS

Patients and controls were defined using ICD-10 codes registered in the Norwegian Patient Registry (NPR), from 2011 to 2017. The 324,232 included subjects had at least one registered diagnostic code for RA (33,040 patients) or diagnostic codes for non-osteoporotic fractures or hip or knee replacement due to osteoarthritis (controls). The outcome was periodontitis, defined by codes for periodontal treatment from the Norwegian Control and Payment of Health Reimbursements Database (KUHR). Hazard ratios (HRs) were calculated for periodontitis in RA patients compared to controls. Generalized additive model in Cox regressions was estimated to visualize periodontitis occurrences as a function of number of RA visits.

RESULTS

The risk of periodontitis increased with increasing number of RA visits. RA patients having 10 or more visits during the 7-year period had a 50% increased risk of periodontitis compared to controls (HR = 1.48, 95% confidence interval [CI]: 1.39-1.59); also, in patients with assumed new RA, an even higher risk estimate was seen (HR = 1.82, 95% CI: 1.53-2.17).

CONCLUSIONS

In this register-based study in which periodontal treatment was used as a surrogate marker for periodontitis, we found an increased risk of periodontitis in RA patients, particularly those with active disease and new RA.

MLysPRED: graph-based multi-view clustering and multi-dimensional normal distribution resampling techniques to predict multiple lysine sites

Posttranslational modification of lysine residues, K-PTM, is one of the most popular PTMs. Some lysine residues in proteins can be continuously or cascaded covalently modified, such as acetylation, crotonylation, methylation and succinylation modification. The covalent modification of lysine residues may have some special functions in basic research and drug development. Although many computational methods have been developed to predict lysine PTMs, up to now, the K-PTM prediction methods have been modeled and learned a single class of K-PTM modification. In view of this, this study aims to fill this gap by building a multi-label computational model that can be directly used to predict multiple K-PTMs in proteins. In this study, a multi-label prediction model, MLysPRED, is proposed to identify multiple lysine sites using features generated from human protein sequences. In MLysPRED, three kinds of multi-label sequence encoding algorithms (MLDBPB, MLPSDAAP, MLPSTAAP) are proposed and combined with three encoding strategies (CHHAA, DR and Kmer) to convert preprocessed lysine sequences into effective numerical features. A multidimensional normal distribution oversampling technique and graph-based multi-view clustering under-sampling algorithm were first proposed and incorporated to reduce the proportion of the original training samples, and multi-label nearest neighbor algorithm is used for classification. It is observed that MLysPRED achieved an Aiming of 92.21%, Coverage of 94.98%, Accuracy of 89.63%, Absolute-True of 81.46% and Absolute-False of 0.0682 on the independent datasets. Additionally, comparison of results with five existing predictors also indicated that MLysPRED is very promising and encouraging to predict multiple K-PTMs in proteins. For the convenience of the experimental scientists, 'MLysPRED' has been deployed as a user-friendly web-server at http://47.100.136.41:8181.

Syndecan-2 regulates PAD2 to exert antifibrotic effects on RA-ILD fibroblasts

Rheumatoid arthritis (RA)-associated interstitial lung disease (RA-ILD) is the most common pulmonary complication of RA, increasing morbidity and mortality. Anti-citrullinated protein antibodies have been associated with the development and progression of both RA and fibrotic lung disease; however, the role of protein citrullination in RA-ILD remains unclear. Here, we demonstrate that the expression of peptidylarginine deiminase 2 (PAD2), an enzyme that catalyzes protein citrullination, is increased in lung homogenates from subjects with RA-ILD and their lung fibroblasts. Chemical inhibition or genetic knockdown of PAD2 in RA-ILD fibroblasts attenuated their activation, marked by decreased myofibroblast differentiation, gel contraction, and extracellular matrix gene expression. Treatment of RA-ILD fibroblasts with the proteoglycan syndecan-2 (SDC2) yielded similar antifibrotic effects through regulation of PAD2 expression, phosphoinositide 3-kinase/Akt signaling, and Sp1 activation in a CD148-dependent manner. Furthermore, SDC2-transgenic mice exposed to bleomycin-induced lung injury in an inflammatory arthritis model expressed lower levels of PAD2 and were protected from the development of pulmonary fibrosis. Together, our results support a SDC2-sensitive profibrotic role for PAD2 in RA-ILD fibroblasts and identify PAD2 as a promising therapeutic target of RA-ILD.

Systematic Characterization of Lysine Post-translational Modification Sites Using MUscADEL

Among various types of protein post-translational modifications (PTMs), lysine PTMs play an important role in regulating a wide range of functions and biological processes. Due to the generation and accumulation of enormous amount of protein sequence data by ongoing whole-genome sequencing projects, systematic identification of different types of lysine PTM substrates and their specific PTM sites in the entire proteome is increasingly important and has therefore received much attention. Accordingly, a variety of computational methods for lysine PTM identification have been developed based on the combination of various handcrafted sequence features and machine-learning techniques. In this chapter, we first briefly review existing computational methods for lysine PTM identification and then introduce a recently developed deep learning-based method, termed MUscADEL (Multiple Scalable Accurate Deep Learner for lysine PTMs). Specifically, MUscADEL employs bidirectional long short-term memory (BiLSTM) recurrent neural networks and is capable of predicting eight major types of lysine PTMs in both the human and mouse proteomes. The web server of MUscADEL is publicly available at http://muscadel.erc.monash.edu/ for the research community to use.

Anti-citrullinated protein antibodies are associated with neutrophil extracellular trap formation in rheumatoid arthritis

Objectives

We evaluated the associations of anti‐citrullinated protein antibodies (ACPAs) and serological and cytological levels of neutrophil extracellular trap (NET) formation in rheumatoid arthritis (RA) patients.

Methods

Serum levels of myeloperoxidase‐DNA and elastase‐DNA complexes (NET remnants) were examined in 51 patients with RA and 40 healthy controls using a modified enzyme‐linked immunosorbent assay. Neutrophils were isolated by density gradient centrifugation. IgG antibodies were purified by affinity chromatography. NET formation in RA and control neutrophils was assessed by microscopy in vitro. NETs were purified and co‐incubated with fibroblast‐like synoviocyte (FLS) cells. Interleukin (IL)‐6 and IL‐8 mRNA expression and protein levels in FLS cells were determined by real‐time polymerase chain reaction and enzyme‐linked immunosorbent assay, respectively.

Results

In RA patients, NET remnants in the peripheral circulation were higher in extremely high ACPA titers when compared to in moderate ACPA titers. And IgG antibodies containing ACPA can stimulate neutrophils to form NETs in a concentration‐dependent manner. Furthermore, significantly higher expression of the pro‐inflammatory cytokines IL‐6 and IL‐8 is detected after FLS cells interacted with NETs which derived from neutrophils stimulated with ACPA‐containing IgG antibodies.

Conclusions

Anti‐citrullinated protein antibodies may enhance NET formation and contribute to inflammation development in RA by stimulating NET formation, such as by subsequent activation of FLS cells by NETs.

Computational Prediction of Protein Arginine Methylation Based on Composition-Transition-Distribution Features

Arginine methylation is one of the most essential protein post-translational modifications. Identifying the site of arginine methylation is a critical problem in biology research. Unfortunately, biological experiments such as mass spectrometry are expensive and time-consuming. Hence, predicting arginine methylation by machine learning is an alternative fast and efficient way. In this paper, we focus on the systematic characterization of arginine methylation with composition-transition-distribution (CTD) features. The presented framework consists of three stages. In the first stage, we extract CTD features from 1750 samples and exploit decision tree to generate accurate prediction. The accuracy of prediction can reach 96%. In the second stage, the support vector machine can predict the number of arginine methylation sites with 0.36 R-squared. In the third stage, experiments carried out with the updated arginine methylation site data set show that utilizing CTD features and adopting random forest as the classifier outperform previous methods. The accuracy of identification can reach 82.1 and 82.5% in single methylarginine and double methylarginine data sets, respectively. The discovery presented in this paper can be helpful for future research on arginine methylation.

Uncovering a Shared Epitope-Activated Protein Citrullination Pathway

Rheumatoid arthritis (RA) is closely associated with shared epitope (SE)-coding HLA-DRB1 alleles and circulating anticitrullinated protein Abs (ACPA), but neither the respective pathogenic roles of SE and ACPA in RA nor the mechanisms underlying their coassociation are known. It was recently shown that the SE functions as a signal transduction ligand that activates a cell surface calreticulin-mediated, proarthritogenic, bone erosive pathway in an experimental model of RA. In this study, we demonstrate that stimulation of murine macrophages with LPS or DTT facilitated cell surface translocation of calreticulin, which in turn enabled increased SE-activated calcium signaling and activation of peptidylarginine deiminase with the resultant increased cellular abundance of citrullinated proteins. The i.p. administration of LPS to transgenic mice carrying a human SE-coding HLA-DRB1 allele lead to increased serum levels of TNF-α and anticitrullinated cyclic peptide Abs, along with terminal phalanx bone destruction. These data uncover a previously unknown signal transduction pathway by which the SE facilitates protein citrullination, ACPA production, and bone destruction.

Large-scale comparative assessment of computational predictors for lysine post-translational modification sites

Lysine post-translational modifications (PTMs) play a crucial role in regulating diverse functions and biological processes of proteins. However, because of the large volumes of sequencing data generated from genome-sequencing projects, systematic identification of different types of lysine PTM substrates and PTM sites in the entire proteome remains a major challenge. In recent years, a number of computational methods for lysine PTM identification have been developed. These methods show high diversity in their core algorithms, features extracted and feature selection techniques and evaluation strategies. There is therefore an urgent need to revisit these methods and summarize their methodologies, to improve and further develop computational techniques to identify and characterize lysine PTMs from the large amounts of sequence data. With this goal in mind, we first provide a comprehensive survey on a large collection of 49 state-of-the-art approaches for lysine PTM prediction. We cover a variety of important aspects that are crucial for the development of successful predictors, including operating algorithms, sequence and structural features, feature selection, model performance evaluation and software utility. We further provide our thoughts on potential strategies to improve the model performance. Second, in order to examine the feasibility of using deep learning for lysine PTM prediction, we propose a novel computational framework, termed MUscADEL (Multiple Scalable Accurate Deep Learner for lysine PTMs), using deep, bidirectional, long short-term memory recurrent neural networks for accurate and systematic mapping of eight major types of lysine PTMs in the human and mouse proteomes. Extensive benchmarking tests show that MUscADEL outperforms current methods for lysine PTM characterization, demonstrating the potential and power of deep learning techniques in protein PTM prediction. The web server of MUscADEL, together with all the data sets assembled in this study, is freely available at http://muscadel.erc.monash.edu/. We anticipate this comprehensive review and the application of deep learning will provide practical guide and useful insights into PTM prediction and inspire future bioinformatics studies in the related fields.

Peptidylarginine deiminase 4 (PAD4) activity in early rheumatoid arthritis

Objectives: Peptidylarginine deiminases (PADs) are a family of calcium-dependent enzymes catalysing the conversion of arginine residues to citrulline, which may constitute a risk factor in rheumatoid arthritis (RA) pathogenesis. We investigated PAD activation by serum (PAD_Act) in early RA, and the associations between PAD activation and disease characteristics, treatment response, and progression of radiographic damage.Method: Sera from disease-modifying anti-rheumatic drug (DMARD)-naïve early RA patients (n = 225), classified according to the 2010 American College of Rheumatology/European League Against Rheumatism criteria, and healthy controls (n = 63) were analysed for PAD4 activating capacity at 0, 3, 12, and 24 months using a high-performance liquid chromatography fluorometric method. Associations for PAD_Act were evaluated by Mann-Whitney U and chi-squared tests. Changes in PAD_Act levels were compared using the Wilcoxon signed-rank test.Results: PAD_Act positivity occurred in 42% (n = 95) of the patients and was more prevalent in anti-citrullinated protein antibody (ACPA)-positive vs ACPA-negative patients (47% vs 20%, p = 0.002), but not in rheumatoid factor (RF)-positive vs RF-negative patients (44% vs 38%, p = 0.49). PAD_Act-positive were younger than PAD_Act-negative patients [mean ± sd 48.7 ± 13.5 vs 53.2 ± 13.7 years, p = 0.011]. Median [25th, 75th percentile] PAD_Act levels were higher in patients than in controls (8768 [7491, 11 393] vs 7046 [6347, 7906], p < 0.0001) and decreased after initiation of DMARD treatment, but were not associated with treatment response or progression of radiographic damage after 2 years of follow-up.Conclusion: Serum capacity to activate PAD4 was associated with ACPA and RF positivity and earlier disease onset in early RA patients, and decreased after initiation of DMARD treatment, indicating that anti-PAD treatment could potentially be beneficial in RA.

Expanding the citrullinome of synovial fibrinogen from rheumatoid arthritis patients

Citrullination is a post-translational protein modification, which is associated with inflammation in general and is thought to play an important pathogenic role in rheumatoid arthritis (RA). Here a mass spectrometry-based proteomics approach was applied to identify citrullination sites in synovial fluid fibrinogen from four RA patients. In general, high disease activity correlated with increased number of identified citrullination sites and higher relative citrulline occupancy. Altogether, 23 sites were identified, of which 9 have not been previously reported to be citrullinated in vivo. Citrullination at site α84, α123, α129, α547, α573, α591, β334 and γ134 was identified in more than one patient, and these positions were therefore regarded as hotspots. Following citrullination of fibrinogen in vitro using human recombinant peptidylarginine deiminase 2 (PAD2), a total of 46 citrullination sites were identified, including 6 hitherto unreported in vitro citrullination sites. Twenty-two out of the 23 citrullination sites identified in vivo were also detected in vitro, supporting the validity of the identifications. SIGNIFICANCE: This work provides information about previously uncharacterized citrullination sites in synovial fluid fibrinogen from rheumatoid arthritis patients. Detection of these novel citrullination sites may prove to have diagnostic or prognostic value in RA and enhance our understanding of the immune pathogenesis.

Fast Prediction of Protein Methylation Sites Using a Sequence-Based Feature Selection Technique

Protein methylation, an important post-translational modification, plays crucial roles in many cellular processes. The accurate prediction of protein methylation sites is fundamentally important for revealing the molecular mechanisms undergoing methylation. In recent years, computational prediction based on machine learning algorithms has emerged as a powerful and robust approach for identifying methylation sites, and much progress has been made in predictive performance improvement. However, the predictive performance of existing methods is not satisfactory in terms of overall accuracy. Motivated by this, we propose a novel random-forest-based predictor called MePred-RF, integrating several discriminative sequence-based feature descriptors and improving feature representation capability using a powerful feature selection technique. Importantly, unlike other methods based on multiple, complex information inputs, our proposed MePred-RF is based on sequence information alone. Comparative studies on benchmark datasets via vigorous jackknife tests indicate that our proposed MePred-RF method remarkably outperforms other state-of-the-art predictors, leading by a 4.5 percent average in terms of overall accuracy. A user-friendly webserver that implements the proposed method has been established for researchers' convenience, and is now freely available for public use through http://server.malab.cn/MePred-RF. We anticipate our research tool to be useful for the large-scale prediction and analysis of protein methylation sites.

Humanized Mouse Models of Rheumatoid Arthritis for Studies on Immunopathogenesis and Preclinical Testing of Cell-Based Therapies

Rodent models of rheumatoid arthritis (RA) have been used over decades to study the immunopathogenesis of the disease and to explore intervention strategies. Nevertheless, mouse models of RA reach their limit when it comes to testing of new therapeutic approaches such as cell-based therapies. Differences between the human and the murine immune system make it difficult to draw reliable conclusions about the success of immunotherapies. To overcome this issue, humanized mouse models have been established that mimic components of the human immune system in mice. Two main strategies have been pursued for humanization: the introduction of human transgenes such as human leukocyte antigen molecules or specific T cell receptors, and the generation of mouse/human chimera by transferring human cells or tissues into immunodeficient mice. Recently, both approaches have been combined to achieve more sophisticated humanized models of autoimmune diseases. This review discusses limitations of conventional mouse models of RA-like disease and provides a closer look into studies in humanized mice exploring their usefulness and necessity as preclinical models for testing of cell-based therapies in autoimmune diseases such as RA.

Peptidyl arginine deiminase 2 (Padi2) is expressed in Sertoli cells in a specific manner and regulated by SOX9 during testicular development

Peptidyl arginine deiminases (PADIs) are enzymes that change the charge of proteins through citrullination. We recently found Padi2 was expressed exclusively in fetal Sertoli cells. In this study, we analyzed the transcriptional regulation of Padi2 and the role of PADI2 in testicular development. We showed SOX9 positively regulated Padi2 transcription and FOXL2 antagonized it in TM3 cells, a model of Sertoli cells. The responsive region to SOX9 and FOXL2 was identified within the Padi2 sequence by reporter assay. In fetal testes from Sox9 knockout (AMH-Cre:Sox9^flox/flox) mice, Padi2 expression was greatly reduced, indicating SOX9 regulates Padi2 in vivo. In vitro analysis using siRNA suggested PADI2 modified transcriptional regulation by SOX9. However, Padi2^−/− XY mice were fertile and showed no apparent reproductive anomalies. Although, PADI2 is known as an epigenetic transcriptional regulator through H3 citrullination, no significant difference in H3 citrullination between wildtype and Padi2^−/− XY gonads was observed. These results suggest Padi2 is a novel gene involved in testis development that is specifically expressed in Sertoli cells through the regulation by SOX9 and FOXL2 and PADI2 supports regulation of target genes by SOX9. Analysis of the Padi2^−/− XY phenotype suggested a redundant factor compensated for PADI2 function in testicular development.

Citrullination as a plausible link to periodontitis, rheumatoid arthritis, atherosclerosis and Alzheimer's disease

Periodontitis, rheumatoid arthritis (RA), atherosclerosis (AS), and Alzheimer’s disease (AD) are examples of complex human diseases with chronic inflammatory components in their etiologies. The initial trigger of inflammation that progresses to these diseases remains unresolved. Porphyromonas gingivalis is unique in its ability to secrete the P. gingivalis-derived peptidyl arginine deiminase (PPAD) and consequently offers a plausible and exclusive link to these diseases through enzymatic conversion of arginine to citrulline. Citrullination is a post-translational enzymatic modification of arginine residues in proteins formed as part of normal physiological processes. However, PPAD has the potential to modify self (bacterial) and host proteins by deimination of arginine amino acid residues, preferentially at the C-terminus. Migration of P. gingivalis and/or its secreted PPAD into the bloodstream opens up the possibility that this enzyme will citrullinate proteins at disparate body sites. Citrullination is associated with the pathogenesis of multifactorial diseases such as RA and AD, which have an elusive external perpetrator as they show epidemiological associations with periodontitis. Therefore, PPAD deserves some prominence as an external antigen, in at least, a subset of RA and AD cases, with as yet unidentified, immune/genetic vulnerabilities.

Human Leukocyte Antigen-Disease Associations in Rheumatoid Arthritis

The cause and pathogenesis of rheumatoid arthritis (RA) are influenced by environmental and genetic risk factors. Shared epitope-coding human leukocyte antigen (HLA)-DRB1 alleles increase RA risk and severity; however, the underlying mechanisms of action remain unclear. In contrast, several other DRB1 alleles protect against RA. Additionally, genome-wide association studies suggest that RA associates with other, HLA and non-HLA, genes; but the relative contributions of such risk loci to RA are incompletely understood. Future research challenges include integrating the epidemiologic and genomic data into validated arthritogenic pathways and determining the mechanisms of interaction between RA risk genes and environmental influences.

A Novel Biological Role for Peptidyl-Arginine Deiminases: Citrullination of Cathelicidin LL-37 Controls the Immunostimulatory Potential of Cell-Free DNA

LL-37, the only human cathelicidin that is released during inflammation, is a potent regulator of immune responses by facilitating delivery of oligonucleotides to intracellular TLR-9, thereby enhancing the response of human plasmacytoid dendritic cells (pDCs) to extracellular DNA. Although important for pathogen recognition, this mechanism may facilitate development of autoimmune diseases. In this article, we show that citrullination of LL-37 by peptidyl-arginine deiminases (PADs) hindered peptide-dependent DNA uptake and sensing by pDCs. In contrast, carbamylation of the peptide (homocitrullination of Lys residues) had no effect. The efficiency of LL-37 binding to oligonucleotides and activation of pDCs was found to be inversely proportional to the number of citrullinated residues in the peptide. Similarly, preincubation of carbamylated LL-37 with PAD2 abrogated the peptide's ability to bind DNA. Conversely, LL-37 with Arg residues substituted by homoarginine, which cannot be deiminated, elicited full activity of native LL-37 regardless of PAD2 treatment. Taken together, the data showed that citrullination abolished LL-37 ability to bind DNA and altered the immunomodulatory function of the peptide. Both activities were dependent on the proper distribution of guanidinium side chains in the native peptide sequence. Moreover, our data suggest that cathelicidin/LL-37 is citrullinated by PADs during NET formation, thus affecting the inflammatory potential of NETs. Together this may represent a novel mechanism for preventing the breakdown of immunotolerance, which is dependent on the response of APCs to self-molecules (including cell-free DNA); overactivation may facilitate development of autoimmunity.

Novel furan-containing peptide-based inhibitors of protein arginine deiminase type IV (PAD4)

Protein arginine deiminase type IV (PAD4) is responsible for the posttranslational conversion of peptidylarginine to peptidylcitrulline. Citrullinated protein is the autoantigen in rheumatoid arthritis, and therefore, PAD4 is currently a promising therapeutic target for the disease. Recently, we reported the importance of the furan ring in the structure of PAD4 inhibitors. In this study, the furan ring was incorporated into peptides to act as the "warhead" of the inhibitors for PAD4. IC₅₀ studies showed that the furan-containing peptide-based inhibitors were able to inhibit PAD4 to a better extent than the furan-containing small molecules that were previously reported. The best peptide-based inhibitor inhibited PAD4 reversibly and competitively with an IC₅₀ value of 243.2 ± 2.4 μm. NMR spectroscopy and NMR-restrained molecular dynamic simulations revealed that the peptide-based inhibitor had a random structure. Molecular docking studies showed that the peptide-based inhibitor entered the binding site and interacted with the essential amino acids involved in the catalytic activity. The peptide-based inhibitor could be further developed into a therapeutic drug for rheumatoid arthritis.

Porphyromonas gingivalis and its LPS differentially regulate the expression of peptidyl arginine deiminases in human chondrocytes

Periodontitis, an inflammatory disease initiated by Gram-negative bacteria such as Porphyromonas gingivalis ( Pg), is considered as a risk factor for rheumatoid arthritis (RA). Our study aimed to determine the effect of Pg and its LPS on the expression of peptidyl arginine deiminase isotypes (PADs) in human primary chondrocytes (HC). HCs were infected with Pg and activated by its LPS (LPS- Pg). The mRNA expression levels of human PADs (1, 2, 3, 4 and 6) and bacterial enzyme (PADPg) were quantified by RT-qPCR. Cellular extracts served to measure the enzymatic activities of PADs and PADPg and to visualize the profiles of citrullinated proteins/peptides by Western blotting. Our data showed significant inhibitions of mRNA expressions of human PAD-2, PAD-3 and PAD-4 during infection of HC with live Pg. Activation of HC by LPS- Pg increased mRNA expressions of human PAD-2 and PAD-3. The PADPg enzymatic activity was significantly increased in only infected HC. Analysis of citrullinated proteins/peptides profiles revealed the occurrence of low molecular bands only in cellular extracts from HC infected with Pg. Our data showed that Pg and its LPS differentially regulate the expression of PADs in human chondrocytes and that Pg favors the apparition of new citrullinated proteins/peptides.

PADI4 Epigenetically Suppresses p21 Transcription and Inhibits Cell Apoptosis in Fibroblast-like Synoviocytes from Rheumatoid Arthritis Patients

Rheumatoid arthritis (RA) is characterized by synovial lining hyperplasia, which involves abnormal growth of fibroblast-like synoviocytes (FLSs). This study aimed to investigate the function and molecular mechanism of peptidylarginine deiminase type 4 (PADI4) in FLSs isolated from RA patients (RA-FLSs). FLSs were isolated from RA patients and transfected with small interfering RNAs (siRNAs) or PADI4 overexpression plasmid. FLSs were treated by Adriamycin (ADR) to induce apoptosis, and apoptotic cells were detected by flow cytometry. The expression of PADI4, p53 and p21 was detected by qRT-PCR and Western blot analysis. The recruitment of PADI4 and histone H3 arginine modifications to p21 promoter was measured by chromatin immunoprecipitation. The results showed that knockdown of PADI4 promoted the apoptosis of RA-FLSs and the expression of p53 and p21. Ectopic expression of PADI4 inhibited ADR-induced apoptosis of RA-FLSs, and down-regulated the expression of p53 and p21. In RA-FLSs, global H3 citrullination (CitH3) and H3 arginine 17 methylation levels were dynamically changed by PADI4 and ADR treatment. PADI4 and H3 could bind p21 promoter region to regulate p21 expression. In conclusion, PADI4 contributes to the pathogenesis of RA by protecting FLSs from apoptosis. PADI4 suppresses p21 transcription through altering histone H3 arginine modifications on p21 promoter region. Our study provides new insight into the anti-apoptotic role of PADI4 in RA development.

Human Deiminases: Isoforms, Substrate Specificities, Kinetics, and Detection

Peptidylarginine deiminase (PAD) enzymes are of enormous interest in biomedicine. They catalyze the conversion of a positively-charged guanidinium at an arginine side chain into a neutral ureido group. As a result of this conversion, proteins acquire the non-ribosomally encoded amino acid "citrulline". This imposes critical influences on the structure and function of the target molecules. In multiple sclerosis, myelin hyper-citrullination promotes demyelination by reducing its compaction and triggers auto-antibody production. Immune responses to citrulline-containing proteins play a central role in the pathogenesis of autoimmune diseases. Moreover, auto-antibodies, specific to citrullinated proteins, such as collagen type I and II and filaggrin, are early detectable in rheumatoid arthritis, serving as diagnostic markers of the disease. Despite their significance, little is understood about the role in demyelinating disorders, diversified cancers, and auto-immune diseases. To impart their biological and pathological effects, it is crucial to better understand the reaction mechanism, kinetic properties, substrate selection, and specificities of peptidylarginine deiminase isoforms.Many aspects of PAD biochemistry and physiology have been ignored in past, but, herein is presented a comprehensive survey to improve our current understandings of the underlying mechanism and regulation of PAD enzymes.

Microvesicles in Autoimmune Diseases

During apoptosis or activation, cells can release a subcellular structure, called a membrane microvesicle (also known as microparticle) into the extracellular environment. Microvesicles bud-off as a portion of cell membrane with its associated proteins and lipids surrounding a cytosolic core that contains intracellular proteins, lipids, and nucleic acids (DNA, RNA, siRNA, microRNA, lncRNA). Biologically active molecules on the microvesicle surface and encapsulated within can act on recipient cells as a novel mode of intercellular communication. Apoptosis has long been known to be involved in the development of diseases of autoimmunity. Abnormally persistent microvesicles, particularly apoptotic microvesicles, can accelerate autoimmune responses locally in specific organs and tissues as well as systemically. In this review, we focus on studies implicating microvesicles in the pathogenesis of autoimmune diseases and their complications.

Accurate in silico prediction of species-specific methylation sites based on information gain feature optimization

As one of the most important reversible types of post-translational modification, protein methylation catalyzed by methyltransferases carries many pivotal biological functions as well as many essential biological processes. Identification of methylation sites is prerequisite for decoding methylation regulatory networks in living cells and understanding their physiological roles. Experimental methods are limitations of labor-intensive and time-consuming. While in silicon approaches are cost-effective and high-throughput manner to predict potential methylation sites, but those previous predictors only have a mixed model and their prediction performances are not fully satisfactory now. Recently, with increasing availability of quantitative methylation datasets in diverse species (especially in eukaryotes), there is a growing need to develop a species-specific predictor. Here, we designed a tool named PSSMe based on information gain (IG) feature optimization method for species-specific methylation site prediction. The IG method was adopted to analyze the importance and contribution of each feature, then select the valuable dimension feature vectors to reconstitute a new orderly feature, which was applied to build the finally prediction model. Finally, our method improves prediction performance of accuracy about 15% comparing with single features. Furthermore, our species-specific model significantly improves the predictive performance compare with other general methylation prediction tools. Hence, our prediction results serve as useful resources to elucidate the mechanism of arginine or lysine methylation and facilitate hypothesis-driven experimental design and validation.

AVAILABILITY AND IMPLEMENTATION

The tool online service is implemented by C# language and freely available at http://bioinfo.ncu.edu.cn/PSSMe.aspx CONTACT: jdqiu@ncu.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.

Autophagy generates citrullinated peptides in human synoviocytes: a possible trigger for anti-citrullinated peptide antibodies

OBJECTIVES

Autophagy may represent a functional processing event that creates a substrate for autoreactivity. In particular, autophagy may play a role in the pathogenesis of RA, since autophagy is a key cellular event involved in the generation of citrullinated peptides, with consequent breakage of tolerance. Thus, in RA, autophagy may be the common feature in several situations (including smoking, joint injury and infection) that may drive the adaptive responses to citrullinated self-proteins. The aim of this study was the analysis, in vitro, of the role of autophagy in the generation of citrullinated peptides and, in vivo, of the relationship between autophagy and the production of anti-CCP antibodies (Abs).

METHODS

For autophagy induction, fibroblast-like synoviocytes, primary fibroblasts and monocytes were stimulated with tunicamycin or rapamycin. Peptidyl arginine deiminase activity was tested by enzyme-linked immunosorbent assay, and protein citrullination was evaluated by western blotting. The main citrullinated RA candidate antigens, vimentin, α-enolase and filaggrin, were demonstrated by immunoprecipitation. The relationship between autophagy and anti-CCP Abs was analysed in 30 early-active RA patients.

RESULTS

Our results demonstrated in vitro a role for autophagy in the citrullination process. Cells treated with tunicamycin or rapamycin showed peptidyl arginine deiminase 4 activation, with consequent protein citrullination. Immunoblotting and immunoprecipitation experiments, using specific Abs, identified the main citrullinated proteins: vimentin, α-enolase and filaggrin. In vivo, a significant association between levels of autophagy and anti-CCP Abs was observed in treatment-naïve early-active RA patients.

CONCLUSION

These findings support the view that the processing of proteins in autophagy generates citrullinated peptides recognized by the immune system in RA.

Soluble alpha-enolase activates monocytes by CD14-dependent TLR4 signalling pathway and exhibits a dual function

Rheumatoid arthritis (RA) is the most common form of chronic inflammatory rheumatism. Identifying auto-antigens targeted by RA auto-antibodies is of major interest. Alpha-enolase (ENO1) is considered to be a pivotal auto-antigen in early RA but its pathophysiologic role remains unknown. The main objective of this study was to investigate the in vitro effects of soluble ENO1 on peripheral blood mononuclear cells (PBMC) from healthy donors and RA patients in order to determine the potential pathogenic role of ENO1. ELISA, transcriptomic analysis, experiments of receptor inhibition and flow cytometry analysis were performed to determine the effect, the target cell population and the receptor of ENO1. We showed that ENO1 has the ability to induce early production of pro-inflammatory cytokines and chemokines with delayed production of IL-10 and to activate the innate immune system. We demonstrated that ENO1 binds mainly to monocytes and activates the CD14-dependent TLR4 pathway both in healthy subjects and in RA patients. Our results establish for the first time that ENO1 is able to activate in vitro the CD14-dependent TLR4 pathway on monocytes involving a dual mechanism firstly pro-inflammatory and secondly anti-inflammatory. These results contribute to elucidating the role of this auto-antigen in the pathophysiologic mechanisms of RA.

Epidemiology: Then and Now

Twenty-five years ago, on the 75th anniversary of the Johns Hopkins Bloomberg School of Public Health, I noted that epidemiologic research was moving away from the traditional approaches used to investigate "epidemics" and their close relationship with preventive medicine. Twenty-five years later, the role of epidemiology as an important contribution to human population research, preventive medicine, and public health is under substantial pressure because of the emphasis on "big data," phenomenology, and personalized medical therapies. Epidemiology is the study of epidemics. The primary role of epidemiology is to identify the epidemics and parameters of interest of host, agent, and environment and to generate and test hypotheses in search of causal pathways. Almost all diseases have a specific distribution in relation to time, place, and person and specific "causes" with high effect sizes. Epidemiology then uses such information to develop interventions and test (through clinical trials and natural experiments) their efficacy and effectiveness. Epidemiology is dependent on new technologies to evaluate improved measurements of host (genomics), epigenetics, identification of agents (metabolomics, proteomics), new technology to evaluate both physical and social environment, and modern methods of data collection. Epidemiology does poorly in studying anything other than epidemics and collections of numerators and denominators without specific hypotheses even with improved statistical methodologies.

Understanding the Complexity of Epigenetic Target Space

The purpose of this review is to provide an overview of the complexity of the epigenetic target space. Chemical modifications of histones and nucleic acids constitute a key epigenetic mechanism. Whereas modifications such as methylation and acetylation are well-known, there are many additional, less explored modifications described here. The writers, readers and erasers of such diverse modifications, which constitute a major portion of the potential epigenetic target space, are discussed, in addition to the various other protein families that do not fall under these three categories. Finally, disease relevance and druggability of epigenetic targets are discussed with concluding remarks about the richness and diversity they will provide for future targeted therapies.

The association between rheumatoid arthritis and periodontitis

The relationship between rheumatoid arthritis and poor oral health has been recognised for many decades. The association between periodontal infection and the risk of developing RA has been the subject of epidemiological, clinical and basic science research in recent times. Converging and reproducible evidence now makes a clear case for the role of specific periodontal infective pathogens in initiating, amplifying and perpetuating rheumatoid arthritis. The unique enzymatic properties of the periodontal pathogen Porphyromonas gingivalis and its contribution to the burden of citrullinated peptides is now well established. The impact of localized infection such as periodontitis in shaping specific anti-citrullinated peptide immune responses highlights a key area for treatment, prevention and risk assessment in rheumatoid arthritis.

Design, synthesis, and biological evaluation of tetrazole analogs of Cl-amidine as protein arginine deiminase inhibitors

Protein arginine deiminases (PADs) catalyze the post-translational hydrolysis of arginine residues to form citrulline. This once obscure modification is now known to play a key role in the etiology of multiple autoimmune diseases (e.g., rheumatoid arthritis, multiple sclerosis, lupus, and ulcerative colitis) and in some forms of cancer. Among the five human PADs (PAD1, -2, -3, -4, and -6), it is unclear which isozyme contributes to disease pathogenesis. Toward the identification of potent, selective, and bioavailable PAD inhibitors that can be used to elucidate the specific roles of each isozyme, we describe tetrazole analogs as suitable backbone amide bond bioisosteres for the parent pan PAD inhibitor Cl-amidine. These tetrazole based analogs are highly potent and show selectivity toward particular isozymes. Importantly, one of the compounds, biphenyl tetrazole tert-butyl Cl-amidine (compound 13), exhibits enhanced cell killing in a PAD4 expressing osteosarcoma bone marrow (U2OS) cell line and can also block the formation of neutrophil extracellular traps. These bioisosteres represent an important step in our efforts to develop stable, bioavailable, and selective inhibitors for the PADs.

iMethyl-PseAAC: identification of protein methylation sites via a pseudo amino acid composition approach

Before becoming the native proteins during the biosynthesis, their polypeptide chains created by ribosome's translating mRNA will undergo a series of “product-forming” steps, such as cutting, folding, and posttranslational modification (PTM). Knowledge of PTMs in proteins is crucial for dynamic proteome analysis of various human diseases and epigenetic inheritance. One of the most important PTMs is the Arg- or Lys-methylation that occurs on arginine or lysine, respectively. Given a protein, which site of its Arg (or Lys) can be methylated, and which site cannot? This is the first important problem for understanding the methylation mechanism and drug development in depth. With the avalanche of protein sequences generated in the postgenomic age, its urgency has become self-evident. To address this problem, we proposed a new predictor, called iMethyl-PseAAC. In the prediction system, a peptide sample was formulated by a 346-dimensional vector, formed by incorporating its physicochemical, sequence evolution, biochemical, and structural disorder information into the general form of pseudo amino acid composition. It was observed by the rigorous jackknife test and independent dataset test that iMethyl-PseAAC was superior to any of the existing predictors in this area.

Rheumatoid arthritis in the Women's Health Initiative: methods and baseline evaluation

Second-generation assays for anti-cyclic citrullinated peptide (anti-CCP), a highly sensitive and specific marker for rheumatoid arthritis (RA), have redefined the epidemiology of RA. In the Women's Health Initiative (WHI) RA study (2009-2011), we evaluated the prevalence of anti-CCP positivity among 15,691 (10.2% of 161,808) WHI participants aged 50-79 years who reported RA. Using stored baseline specimens, we measured serum anti-CCP, rheumatoid factor (RF), and antinuclear antibody in a defined sample of 9,988 of black, white, and Hispanic women. In a subset of women, we measured plasma cytokine levels and number of copies of the human leukocyte antigen (HLA)-DRB1 (HLA-DRB1) shared epitope in DNA by means of Luminex polymerase chain reaction typing (Luminex Corporation, Austin, Texas). We validated classification of probable clinical RA in 2 clinics as anti-CCP positivity or self-reported validated use of disease-modifying antirheumatic drugs (DMARDs). The prevalence of anti-CCP positivity was 8.1%, and the prevalence of RF positivity was approximately 16.0%. DMARD use including prednisone was reported by 1,140 (11.4%) participants (841 excluding prednisone) but by 57.5% of anti-CCP-positive women. The prevalence of 2 shared epitopes was also much higher for anti-CCP-positive women (18.2%, as opposed to only 5.5% for women with anti-CCP-negative DMARD-positive RA and 6.6% for anti-CCP-negative, RF-negative DMARD nonusers). Median cytokine levels were much higher for anti-CCP-positive/RF-positive women. Women with anti-CCP-positive RA and anti-CCP-negative RA had different characteristics with regard to HLA shared epitope, cigarette smoking, and inflammation (cytokines).