To study complex biological systems, multi-omics methods have become an important tool. They integrate data from multiple biological layers, such as the metabolome and the proteome, to gain better insights of the processes happening. However, challenges remain both in sample preparation for measurements of different types of analytes as well as in the integration of different data types. Post-translational modifications such as acetylation of proteins are an example of a highly dynamic, reversible process that combines core metabolism with protein function. Histones are small proteins binding DNA that are highly acetylated in their N-terminal region. In this study, we utilise a simultaneous extraction method for acetyl-CoA and histones in combination with combined metabolic and chemical acetylation (CoMetChem) to track metabolic label incorporation into both acetyl-CoA and histones. Acetyl-CoA formation rates as well as histone acetylation- and deacetyation rates are modelled by ordinary differential equation, allowing the combination of data from acetyl-CoA and histone acetylation measurements into a unified model. We find that correcting for acetyl-CoA formation is necessary to accurately determine histone acetylation rates, particularly in systems with changes in upstream metabolism.