Department of Chemistry, Boston College, Chestnut Hill, Massachusetts 02467, United States.
Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, LRB 826, 364 Plantation Street, Worcester, Massachusetts 01605, United States.
Biochemistry. 2021 Sep 28;60(38):2902-2914. doi: 10.1021/acs.biochem.1c00369. Epub 2021 Sep 7.
Citrullination is an enzyme-catalyzed post-translational modification (PTM) that is essential for a host of biological processes, including gene regulation, programmed cell death, and organ development. While this PTM is required for normal cellular functions, aberrant citrullination is a hallmark of autoimmune disorders as well as cancer. Although aberrant citrullination is linked to human pathology, the exact role of citrullination in disease remains poorly characterized, in part because of the challenges associated with identifying the specific arginine residues that are citrullinated. Tandem mass spectrometry is the most precise method for uncovering sites of citrullination; however, due to the small mass shift (+0.984 Da) that results from citrullination, current database search algorithms commonly misannotate spectra, leading to a high number of false-positive assignments. To address this challenge, we developed an automated workflow to rigorously and rapidly mine proteomic data to unambiguously identify the sites of citrullination from complex peptide mixtures. The crux of this streamlined workflow is the ionFinder software program, which classifies citrullination sites with high confidence on the basis of the presence of diagnostic fragment ions. These diagnostic ions include the neutral loss of isocyanic acid, which is a dissociative event that is unique to citrulline residues. Using the ionFinder program, we have mapped the sites of autocitrullination on purified protein arginine deiminases (PAD1-4) and mapped the global citrullinome in a PAD2-overexpressing cell line. The ionFinder algorithm is a highly versatile, user-friendly, and open-source program that is agnostic to the type of instrument and mode of fragmentation that are used.
瓜氨酸化是一种酶催化的翻译后修饰(PTM),对于许多生物过程至关重要,包括基因调控、程序性细胞死亡和器官发育。虽然这种 PTM 是正常细胞功能所必需的,但异常的瓜氨酸化是自身免疫性疾病以及癌症的标志。尽管异常的瓜氨酸化与人类病理学有关,但瓜氨酸化在疾病中的确切作用仍未得到很好的描述,部分原因是识别被瓜氨酸化的特定精氨酸残基存在挑战。串联质谱是揭示瓜氨酸化位点的最精确方法;然而,由于瓜氨酸化导致的质量偏移较小(+0.984 Da),当前的数据库搜索算法通常错误注释谱,导致大量假阳性分配。为了解决这个挑战,我们开发了一种自动化工作流程,以严格和快速地挖掘蛋白质组学数据,从复杂的肽混合物中明确鉴定瓜氨酸化位点。这个简化工作流程的核心是 ionFinder 软件程序,它基于存在诊断性片段离子,高度自信地分类瓜氨酸化位点。这些诊断性离子包括异氰酸的中性损失,这是瓜氨酸残基特有的离解事件。使用 ionFinder 程序,我们已经绘制了纯化蛋白精氨酸脱亚氨酶(PAD1-4)上的自身瓜氨酸化位点,并在 PAD2 过表达细胞系中绘制了全局瓜氨酸组。ionFinder 算法是一种高度通用、用户友好且开源的程序,它与使用的仪器类型和碎片化模式无关。