Erratum for Research Article "Synovial fibroblast-neutrophil interactions promote pathogenic adaptive immunity in rheumatoid arthritis" by C. Carmona-Rivera, P. M. Carlucci, E. Moore, N. Lingampalli, H. Uchtenhagen, E. James, Y. Liu, K. L. Bicker, H. Wahamma, V. Hoffman, A. I. Catrina, P. Thompson, J. H. Buckner, W. H. Robinson, D. A. Fox, M. J. Kaplan

Recent advances in characterization of citrullination and its implication in human disease research: From method development to network integration

Post-translational modifications (PTM) of proteins increase the functional diversity of the proteome and have been implicated in the pathogenesis of numerous diseases. The most widely understood modifications include phosphorylation, methylation, acetylation, O-linked/N-linked glycosylation, and ubiquitination, all of which have been extensively studied and documented. Citrullination is a historically less explored, yet increasingly studied, protein PTM which has profound effects on protein conformation and protein-protein interactions. Dysregulation of protein citrullination has been associated with disease development and progression. Identification and characterization of citrullinated proteins is highly challenging, complicated by the low cellular abundance of citrullinated proteins, making it difficult to identify and quantify the extent of citrullination in samples, coupled with challenges associated with development of mass spectrometry (MS)-based methods, as the corresponding mass shift is relatively small, +0.984 Da, and identical to the mass shift of deamidation. The focus of this review is to discuss recent advancements of citrullination-specific MS approaches and integration of the potential methodology for improved citrullination identification and characterization. In addition, the association of citrullination in disease networks is also highlighted.

Characterization of Citrullination Sites in Neutrophils and Mast Cells Activated by Ionomycin via Integration of Mass Spectrometry and Machine Learning

Citrullination is an important post-translational modification implicated in many diseases including rheumatoid arthritis (RA), Alzheimer's disease, and cancer. Neutrophil and mast cells have different expression profiles for protein-arginine deiminases (PADs), and ionomycin-induced activation makes them an ideal cellular model to study proteins susceptible to citrullination. We performed high-resolution mass spectrometry and stringent data filtration to identify citrullination sites in neutrophil and mast cells treated with and without ionomycin. We identified a total of 833 validated citrullination sites on 395 proteins. Several of these citrullinated proteins are important components of pathways involved in innate immune responses. Using this benchmark primary sequence data set, we developed machine learning models to predict citrullination in neutrophil and mast cell proteins. We show that our models predict citrullination likelihood with 0.735 and 0.766 AUCs (area under the receiver operating characteristic curves), respectively, on independent validation sets. In summary, this study provides the largest number of validated citrullination sites in neutrophil and mast cell proteins. The use of our novel motif analysis approach to predict citrullination sites will facilitate the discovery of novel protein substrates of protein-arginine deiminases (PADs), which may be key to understanding immunopathologies of various diseases.