bioRxivBiochemistryPreprint
Quantitative profiling of JMJD6-catalysed lysine hydroxylation reveals a graded, residue-dependent readout of oxygen availability
Pallavi KesavaniD, Sophie M. StuermeriD, Katrin Räbel, Oliver PoppiD, Philipp MertinsiD, Matthew E. CockmaniD, Yoichiro SugimotoiD
Abstract
Enzyme-catalysed protein hydroxylation links cellular oxygen availability to protein function, as exemplified by the hydroxylation of hypoxia-inducible factor (HIF). Whereas HIF hydroxylation occurs at three specific residues, lysine hydroxylation catalysed by Jumonji domain-containing protein 6 (JMJD6) occurs at many residues within lysine-rich regions across the proteome. How this widespread modification signals oxygen availability has remained incompletely understood, in part because hydroxylation within lysine-rich regions is difficult to detect. Here we developed an analytical workflow for comprehensive, accurate, and quantitative analysis of lysine hydroxylation in proteomic data from lysine-derivatised samples: optimised database searching improved peptide coverage across lysine-rich regions, while diagnostic immonium ion filtering increased the accuracy of hydroxylysine residue assignment. We further showed that stoichiometry estimated from peptide precursor ion intensities enables reliable comparison across residues and conditions. Applied to bromodomain (BRD) proteins, epigenetic readers containing lysine-rich regions extensively hydroxylated by JMJD6, the workflow revealed marked heterogeneity in the apparent kinetics of hydroxylation among target lysines, with interdependence between neighbouring hydroxylation events. Hypoxia suppressed hydroxylation progressively with increasing severity, preferentially affecting residues with slower apparent kinetics. Together, these findings demonstrate that lysine-rich regions can encode a graded, residue-dependent readout of oxygen availability, providing a framework for investigating how cells calibrate their responses to changes in oxygen levels.
- organism: human
- assay: proteomics
- research focus: protein folding & dynamics
- approach: statistical model
- Citations
- 0
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