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Shotgun proteomics has been widely used to identify histone marks. Conventional database search methods rely on the “target-decoy” strategy to calculate the false discovery rate (FDR) and distinguish true peptide-spectrum matches (PSMs) from false ones. This strategy has a caveat of inaccurate FDR caused by the small data size of histone marks. To address this challenge, we developed a tailored database search strategy, named “Comprehensive Histone Mark Analysis (CHiMA).” Instead of target-decoy–based FDR, this method uses “50% matched fragment ions” as the key criterion to identify high-confidence PSMs. CHiMA identified twice as many histone modification sites as the conventional method in benchmark datasets. Reanalysis of our previous proteomics data using CHiMA led to the identification of 113 new histone marks for four types of lysine acylations, almost doubling the number of previously reported marks. This tool not only offers a valuable approach for identifying histone modifications but also greatly expands the repertoire of histone marks. 

Abstract Histone lysine crotonylation is a posttranslational modification with demonstrated functions in transcriptional regulation. Here we report the discovery of a new type of histone posttranslational modification, lysine methacrylation (Kmea), corresponding to a structural isomer of crotonyllysine. We validate the identity of this modification using diverse chemical approaches and further confirm the occurrence of this type of histone mark by pan specific and site-specific anti-methacryllysine antibodies. In total, we identify 27 Kmea modified histone sites in HeLa cells using affinity enrichment with a pan Kmea antibody and mass spectrometry. Subsequent biochemical studies show that histone Kmea is a dynamic mark, which is controlled by HAT1 as a methacryltransferase and SIRT2 as a de-methacrylase. Altogether, these investigations uncover a new type of enzyme-catalyzed histone modification and suggest that methacrylyl-CoA generating metabolism is part of a growing number of epigenome-associated metabolic pathways.