Líffræðifélag Íslands - biologia.is
Líffræðiráðstefnan 2017

Erindi/veggspjald / Talk/poster E32

Endotheliomics: The metabolic response of the endothelium to LPS

Höfundar / Authors: Sarah McGarrity, Ósk Anuforo, Haraldur Halldórsson, Óttar Rolfsson, Pär Johansson

Starfsvettvangur / Affiliations: Center for Systems Biology University of Iceland/ University of Reykjavik, Center for Systems Biology University of Iceland, Biomedical Center University of Iceland, Center for Systems Biology University of Iceland/Biomedical Center University of Iceland, Rigshospitalet, University of Copenhagen

Kynnir / Presenter: Sarah McGarrity

Endothelial cells line blood vessels and their dysfunction plays a key role in many diseases including sepsis. Sepsis is a complex systemic condition, difficult to treat. Context specific genome scale metabolic models (GEMs) have been built to explore metabolic changes in human umblical vein endothelial cells (HUVECs) when grown with lipopolysaccharide (LPS). These models combine existing transcriptomic data with novel metabolomic data.
RECON1 was constrained to produce cell type specific GEMs related to HUVECs using transcriptomic data. The HUVEC model was further constrained to reflect HUVECs grown with LPS. Metabolomic data from HUVECs with and without LPS was collected using mass spectrometry and applied to further constrain the model. Comparisons between models were made for example MOMA to analyse growth rates. These differences were related to functional changes in endothelial cells in culture including permeability, in static conditions and under flow. Comparisons of model predictions with published metabolomics data from sepsis patients will also be made to establish the endothelial contribution to the metabolic disruption seen in this condition.
Analysis of context specific GEMs shows differences in reactive oxygen species production and processing, nucleotide metabolism and pyruvate metabolism appear between HUVECs with and without LPS.
Combining metabolomics analysis with models based on transcriptomics data highlights context specific differences in endothelial cell metabolism that may have functional implications. This project has laid the biochemical foundations required to understand metabolic endothelial dysfunction will be capitalised on in the clinic.