Research
Acyl-CoA metabolism and histone acylation:
Acyl-CoAs are an ancient and critical family of metabolic intermediates comprised of an acyl (R) group linked by a thioester bond to coenzyme A.
Acyl-CoAs serve as useful indicators of metabolic status. They are generated in diverse metabolic processes, including lipid metabolism, ketone body metabolism, amino acid catabolism, and metabolism of short chain fatty acids derived from intestinal microbiota.
Acyl groups are transferred not only within metabolic pathways but are also used to modify amino acid side chains, such as cysteine and lysine. Thus acyl-CoAs have the potential to exert signalling functions through post-translational protein modifications.
The availability of the central metabolite acetyl-CoA directly affects histone lysine acetylation, which exerts powerful effects on chromatin regulation and gene expression in multiple contexts including development, cancer, metabolic diseases, immune function, stem cell biology, and ageing.
The relatively recent discovery of at least 9 alternative histone lysine acylations (some of which are illustrated on the right) offers the possibility of numerous previously unrecognised modes of communication between cellular metabolism and chromatin modification potentially fine-tuning metabolic control of chromatin in a manner responsive to diverse metabolic processes.
We aim to understand the metabolic regulation of diverse acyl-CoA species and their relationship to epigenetic responses.
Reference:
Trefely S, Lovell CD, Snyder NW, Wellen KE.
Mol Metab. 2020 Aug;38:100941. doi: 10.1016/j.molmet.2020.01.005.
Epub 2020 Feb 14.PMID: 32199817
Metabolic compartmentalisation:
Metabolic pathways are highly compartmentalised and many acyl-CoAs are generated within mitochondria and cannot directly cross mitochondrial membranes. This raises the question of how these metabolites access the nucleus to participate in chromatin modification.
In the case of acetyl-CoA, the mechanism allowing transport out of mitochondria is well established, occurring through citrate export via the mitochondrial citrate transporter and subsequent cleavage by the enzyme ATP-citrate lyase (ACLY). For most histone acylations, however, the mechanisms of acyl-CoA generation in the nuclear-cytoplasmic compartment remain very poorly understood. And further questions remain about the potential for on-site metabolic regulation within the nucleus.
Nuclear metabolism:
We developed a technique to determine acyl-CoA abundance in different sub-cellular organelles termed stable isotope labelling of essential nutrients in cell culture – subcellular fractionation (SILEC-SF). This is a significant advance since we can detect different regulation of metabolites within specific organelles, which cannot be inferred from typical methods that use whole cell analysis.
Intriguingly, application of SILEC-SF to analysis of the nuclear compartment revealed a nuclear acyl-CoA profile distinct from that of the cytosol, with notable nuclear enrichment of propionyl-CoA. Using isotope tracing, we identified the branched chain amino acid isoleucine as a major metabolic source of nuclear propionyl-CoA and histone propionylation, thus revealing a new mechanism of crosstalk between metabolism and the epigenome.
See here:
Trefely S, Huber K, Liu J, Noji M, Stransky S, Singh J, Doan MT, Lovell CD, von Krusenstiern E, Jiang H, Bostwick A, Pepper HL, Izzo L, Zhao S, Xu JP, Bedi KC Jr, Rame JE, Bogner-Strauss JG, Mesaros C, Sidoli S, Wellen KE, Snyder NW
Mol Cell. 2022 Jan 20;82(2):447-462.e6. doi: 10.1016/j.molcel.2021.11.006. Epub 2021 Dec 1. PMID: 34856123
We aim to understand nuclear-specific metabolic regulation and the potential roles of propionyl-CoA and histone propionylation in processes associated with altered branched chain amino acid catabolism including cancer and type 2 diabetes.
Tools:
Isotope tracing:
Isotopic tracer analysis by mass spectrometry is a core technique for the study of metabolism. Isotopically labeled atoms from substrates, such as [13C]-labeled glucose, can be traced by their incorporation over time into specific metabolic products. Isotopologues of each metabolite of interest can be detected and differentiated by high resolution mass spectrometry.
Subcellular isotope tracing:
Analysis of compartmentalised metabolism and the dynamic interplay between compartments can potentially be achieved by stable isotope tracing followed by subcellular fractionation. However, the potential for artifactual metabolic activity during sample processing has previously limited this kind of analysis.
We designed a stable isotope tracing strategy to directly interrogate post-harvest metabolic activity during subcellular fractionation using liquid chromatography-mass spectrometry (LC-MS). We showed that post-harvest metabolic activity occurs rapidly (within seconds) upon cell harvest. This is significant for the interpretation of metabolomic data in general since it shows that post-harvest metabolism affects most metabolite measurements - even ‘rapid’ cell harvest protocols often take more than 30 seconds.
With further characterization we revealed that post-harvest metabolism is enzymatic and reflects the metabolic capacity of the sub-cellular compartment analyzed, but it is limited in the extent of its propagation into downstream metabolites in metabolic pathways. We took advantage of this insight to develop a strategy to account and correct for artifactual post-harvest metabolism and determine kinetic relationships between metabolic pathways in different compartments.
See here for the details:
Trefely, S., Liu, J., Huber, K., Doan, M.T., Jiang, H., Singh, J., von Krusenstiern, E., Bostwick, A., Xu, P., Bogner-Strauss, J.G., et al. (2019)
Mol. Metab. 30, 61–71.
FluxFix:
For meaningful interpretation, mass spectrometry data from metabolic tracer experiments must be corrected to account for the naturally occurring isotopologue distribution. We created FluxFix (), an application freely available on the internet and hosted by the º£½ÇÉçÇøÂÛ̳, that quickly and reliably transforms signal intensity values into percent mole enrichment for each isotopologue measured.
See the accompanying paper for full details and to reference:
Trefely, S., Ashwell, P., and Snyder, N.W. (2016).
BMC Bioinformatics 17, 485.