All organisms need energy for their survival, and an intricate network of proteins has evolved to harvest the available energy sources. However, energy availability and necessity intrinsically fluctuate throughout life history and between different tissues and cells and therefore not all available enzymes can be present at every given time. This would be too energy intensive, surpassing the very goal of obtaining more energy. Therefore, life had to evolve a mechanism to regulate protein expression in a fast and dynamic way in response to changes in resource availability. Possibly, such mechanism arose with the first Eukaryote merger, where a prokaryote provided the energy system and the Archaeal cell provided histones as an information management system.

Chemical modifications on histones are called histone posttranslational modifications (hPTMs) and they influence the degree of DNA compaction, making genes more or less accessible to the transcription machinery. This regulation of gene expression is what coordinates the production of proteins involved in the various metabolic processes. While still relatively new, the perception is growing that histones could potentially be reading out the energy need and availability in a cell by directly binding the metabolites as PTMs to allow more efficient energy harvesting through altering protein expression. In multicellular organisms, each cell thus can tap into its optimal energy source in this way. Yet, when this energy-information system is hacked, cells can start harvesting energy uncontrollably, potentially fueling disease and carcinogenesis.

Therefore, we have developed a workflow to directly measure the expression of over 4000 proteins and the abundance of over 100 histone PTMs and close to a 1000 metabolites from a single cell pellet, effectively allowing us to directly probe this energy-information axis. First, we use a human and mouse embryonic stem cell (ESC) model in an effort to correlate the metabolic conversion between naïve and primed ESCs to the changes in hPTMs. Next, we verify the potential implications in acute myeloid leukemia (AML), where recently a new "Mito-High" phenotype was discovered through proteomics, which is characterized by a high expression of mitochondrial proteins that could in turn affect the histone code.

Here, we present some of the most intricate reciprocal correlations between hPTMs and correlate them directly to protein expression in ESCs. Additionally, for 18 AML cell lines, we are in the process of supplementing a similar perspective with their respective metabolomics profile, allowing us to reflect on the available evidence for a direct energy-information axis in Eukaryote cells.