Acetyllsine Pulse Programs

As Described In: Fraser OA, Dewing SM, Usher ET, George C, and Showalter SA (2022), A direct nuclear magnetic resonance method to investigate lysine acetylation of intrinsically disordered proteins. Front. Mol. Biosci. 9:1074743. doi: 10.3389/fmolb.2022.1074743

Abstract: Intrinsically disordered proteins are frequent targets for functional regulation through post-translational modification due to their high accessibility to modifying enzymes and the strong influence of changes in primary structure on their chemical properties. While lysine N-acetylation was first observed as a common modification of histone tails, proteomic data suggest that lysine acetylation is ubiquitous among both nuclear and cytosolic proteins. However, compared with our biophysical understanding of the other common post-translational modifications, mechanistic studies to document how lysine N-acetyl marks are placed, utilized to transduce signals, and eliminated when signals need to be turned off, have not kept pace with proteomic discoveries. Herein we report a nuclear magnetic resonance method to monitor N-lysine acetylation through enzymatic installation of a 13C-acetyl probe on a protein substrate, followed by detection through 13C direct-detect spectroscopy. We demonstrate the ease and utility of this method using histone H3 tail acetylation as a model. The clearest advantage to this method is that it requires no exogenous tags that would otherwise add steric bulk, change the chemical properties of the modified lysine, or generally interfere with downstream biochemical processes. The non-perturbing nature of this tagging method is beneficial for application in any system where changes to local structure and chemical properties beyond those imparted by lysine modification are unacceptable, including intrinsically disordered proteins, bromodomain containing protein complexes, and lysine deacetylase enzyme assays.



Work Title Acetyllsine Pulse Programs
Open Access
License CC BY 4.0 (Attribution)
Work Type Dataset
Publication Date 2022
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Deposited December 29, 2022




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