Abstract
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.