دورية أكاديمية
Characterization of Citrullination Sites in Neutrophils and Mast Cells Activated by Ionomycin via Integration of Mass Spectrometry and Machine Learning.
| العنوان: | Characterization of Citrullination Sites in Neutrophils and Mast Cells Activated by Ionomycin via Integration of Mass Spectrometry and Machine Learning. |
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| المؤلفون: | Chaerkady R, Zhou Y, Delmar JA, Weng SHS, Wang J, Awasthi S, Sims D, Bowen MA; Antibody Discovery and Protein Engineering (ADPE), R&D AstraZeneca, Gaithersburg, Maryland 20878, United States., Yu W, Cazares LH, Sims GP, Hess S |
| المصدر: | Journal of proteome research [J Proteome Res] 2021 Jun 04; Vol. 20 (6), pp. 3150-3164. Date of Electronic Publication: 2021 May 19. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: American Chemical Society Country of Publication: United States NLM ID: 101128775 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1535-3907 (Electronic) Linking ISSN: 15353893 NLM ISO Abbreviation: J Proteome Res Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Washington, D.C. : American Chemical Society, c2002- |
| مواضيع طبية MeSH: | Citrullination* , Mast Cells*/metabolism, Citrulline/metabolism ; Ionomycin/pharmacology ; Machine Learning ; Mass Spectrometry ; Neutrophils/metabolism ; Protein-Arginine Deiminases/genetics |
| مستخلص: | 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. |
| فهرسة مساهمة: | Keywords: citrullination; deimination; ionomycin; machine learning; mass spectrometry; mast cell; neutral loss; neutrophil; protein-arginine deiminases |
| المشرفين على المادة: | 29VT07BGDA (Citrulline) 56092-81-0 (Ionomycin) EC 3.5.3.15 (Protein-Arginine Deiminases) |
| تواريخ الأحداث: | Date Created: 20210519 Date Completed: 20210617 Latest Revision: 20210617 |
| رمز التحديث: | 20240628 |
| DOI: | 10.1021/acs.jproteome.1c00028 |
| PMID: | 34008986 |
| قاعدة البيانات: | MEDLINE |
Find this issue from the American Chemical Society | تدمد: | 1535-3907 |
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| DOI: | 10.1021/acs.jproteome.1c00028 |