Confident Identification of Citrullination and Carbamylation Assisted by Peptide Retention Time Prediction

Abstract

The chromatographic behavior of peptides carrying citrulline and homocitrulline residues in proteomic two-dimensional (2D) liquid chromatography−mass spectrometry (LC−MS) experiments has been investigated. The primary goal of this study was to determine the chromatographic conditions that allow differentiating between arginine citrullination and deamidation of asparagine based on retention data, improving the confidence of MS-based identifications. Carbamylation was used as a reference point due to a high degree of similarity between modification products and anticipated changes in chromatographic behavior. We applied 2D LC−MS/MS (a high-pH−low-pH reversed phase (RP), hydrophilic interaction liquid chromatography (HILIC)−low-pH RP, and strong cation exchange (SCX)−low-pH RP) to acquire retention data for modified−nonmodified peptide pairs in the four separation modes. Modifications of a standard protein mixture were induced enzymatically (PAD-2) or chemically (urea) for citrullination and carbamylation, respectively. Deamidation occurs spontaneously. Similar retention shifts were observed for all three modifications in a high-pH RP (decrease) and a low-pH RP (increase), thus limiting the applicability of this 2D LC combination. HILIC on bare silica and strong cation exchange separations have been probed to amplify the effect of charge loss upon citrullination, with SCX demonstrating the most differentiating power: the elimination of basic residues upon citrullination/carbamylation results in an ∼58 mM KCl retention decrease, while retention of deamidated products decreases slightly.

12-Plex DiLeu Isobaric Labeling Enabled High-Throughput Investigation of Citrullination Alterations in the DNA Damage Response

“…This is largely due to a very small mass increment induced by citrullination compared to its unmodified counterpart, which can be easily confused with deamidation or 13 C isotopic peaks in a mass spectrum. In addition, the signals of low-abundance citrullinated peptides in the analytes are largely suppressed by other high-intensity molecules without effective enrichment methods. , To deal with these difficulties, various directions have been explored such as carefully examining the mass spectra, , applying more restrictive criteria or novel algorithms during data searching, − and developing chemical derivatization , and enrichment methods of target molecules. − Unfortunately, very few studies have provided easy yet effective means to confidently characterize protein citrullination in a large-scale manner. In addition, dissecting the involvement of citrullination in disease onset and progression requires comparative analysis.…”

Enabling Global Analysis of Protein Citrullination via Biotin Thiol Tag-Assisted Mass Spectrometry

“…However, none of the reported methods have overcome all the difficulties so far. For example, direct MS analysis is possible but often requires high mass accuracy of the instrument and time-consuming manual examination of the spectra. ,, Delicate searching algorithms and statistical modeling have also been developed to aid in the direct analysis. − Chemical derivatization of the PTM prior to MS analysis is an alternative to enlarge the mass shift but usually suffers from incomplete reaction. − The above-mentioned strategies did not address the challenge associated with intrinsic low abundance of this PTM either. Alternative studies have sought the means of using chemical probes for simultaneous introduction of mass shift and enrichment groups .…”

Retention Time Prediction for TMT-Labeled Peptides in Proteomic LC-MS Experiments

“…The key element in this transfer is the accurate measurement of the retention value of TMT-labeled peptides and prediction of the retention time (RT) shift ΔRT expected upon labeling: RT NL = RT TM T – ΔRT. We used a similar approach for various post-translational modifications (PTMs), aiming at introducing peptide modifications into our sequence-specific retention calculator model. − Our protocol for predicting ΔRT uses the accurate assignment of retention values for pairs of modified/nonmodified peptides generated by chemical and enzymatic treatments or due to spontaneous degradation. − Well-developed, high-yield TMT modification chemistry fits extremely well into our standard workflow, targeting better understanding chromatographic behavior of PTM carrying peptides.…”