Lysine acetylation is a widespread posttranslational modification affecting many biological pathways. Recent studies indicate that acetylated lysine residues mainly exhibit low acetylation occupancy, but challenges in sample preparation and analysis make it difficult to confidently assign these numbers, limiting understanding of their biological significance. Here, we tested three common sample preparation methods to determine their suitability for assessing acetylation stoichiometry in three human cell lines, identifying the acetylation occupancy in more than 1,300 proteins from each cell line. The stoichiometric analysis in combination with quantitative proteomics also enabled us to explore their functional roles. We found that higher abundance of the deacetylase sirtuin 1 (SIRT1) correlated with lower acetylation occupancy and lower levels of ribosomal proteins, including those involved in ribosome biogenesis and rRNA processing. Treatment with the SIRT1 inhibitor EX-527 confirmed SIRT1's role in the regulation of pre-rRNA synthesis and processing. Specifically, proteins involved in pre-rRNA transcription, including subunits of the polymerase I and SL1 complexes and the RNA polymerase I-specific transcription initiation factor RRN3, were up-regulated after SIRT1 inhibition. Moreover, many protein effectors and regulators of pre-rRNA processing needed for rRNA maturation were also up-regulated after EX-527 treatment with the outcome that pre-rRNA and 28S rRNA levels also increased. More generally, we found that SIRT1 inhibition down-regulates metabolic pathways, including glycolysis and pyruvate metabolism. Together, these results provide the largest data set thus far of lysine acetylation stoichiometry (available via ProteomeXchange with identifier PXD005903) and set the stage for further biological investigations of this central posttranslational modification.

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Abstract. Representing and reasoning over mereotopological relations (parthood and location) in an ontology is a well-known challenge, because there are many relations to choose from and OWL has limited expressiveness in this regard. To address these issues, we structure mereotopological relations based on the KGEMT mereotopological theory. A correctly chosen relation counterbalances some weaknesses in OWL's representation and reasoning services. To achieve effortless selection of the appropriate relation, we hide the complexities of the underlying theory through automation of modelling guidelines in the new tool OntoPartS. It uses, mainly, the categories from DOLCE [17], which avoids lengthy question sessions, and it includes examples and verbalizations. OntoPartS was experimentally evaluated, which demonstrated that selecting and representing the desired relation was done efficiently and more accurately with OntoPartS.

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