HighlightsThiopurines are effective immunosuppressant drugs.Monitoring of thiopurines is needed for research and clinical use.A sensitive assay of DNA-incorporated deoxythioguanosine is described.This method assays thiopurine nucleotides in DNA from nucleated blood cells.

Objective: Investigate the endothelial cell phenotype (s) that causes Shock-Induced Endotheliopathy in trauma. Background: We have studied more than 2750 trauma patients and identified that patients with high circulating syndecan-1 (endothelial glycocalyx damage marker) in plasma have an increased mortality rate compared with patients with lower levels. Notably, we found that patients suffering from the same trauma severity could develop significantly different degrees of endothelial dysfunction as measured by syndecan-1. Methods: Prospective observational study of 20 trauma patients admitted to a Level 1 Trauma Centre and 20 healthy controls. Admission plasma syndecan-1 level and mass spectrometry were measured and analyzed by computational network analysis of our genome-scale metabolic model of the microvascular endothelial cell function. Results: Trauma patients had a significantly different endothelial metabolic profile compared with controls. Among the patients, 4 phenotypes were identified. Three phenotypes were independent of syndecan-1 levels. We developed genome-scale metabolic models representative of the observed phenotypes. Within these phenotypes, we observed differences in the cell fluxes from glucose and palmitate to produce Acetyl-CoA, and secretion of heparan sulfate proteoglycan (component of syndecan-1). Conclusions: We confirm that trauma patients have a significantly different metabolic profile compared with controls. A minimum of 4 shock-induced endotheliopathy phenotypes were identified, which were independent of syndecan-1level (except 1 phenotype) verifying that the endothelial response to trauma is heterogeneous and most likely driven by a genetic component. Moreover, we introduced a new research tool in trauma by using metabolic systems biology, laying the foundation for personalized medicine.

Endothelial dysfunction contributes to sepsis outcome. Metabolic phenotypes associated with endothelial dysfunction are not well characterised in part due to difficulties in assessing endothelial metabolism in situ. Here, we describe the construction of iEC2812, a genome scale metabolic reconstruction of endothelial cells and its application to describe metabolic changes that occur following endothelial dysfunction. Metabolic gene expression analysis of three endothelial subtypes using iEC2812 suggested their similar metabolism in culture. To mimic endothelial dysfunction, an in vitro sepsis endothelial cell culture model was established and the metabotypes associated with increased endothelial permeability and glycocalyx loss after inflammatory stimuli were quantitatively defined through metabolomics. These data and transcriptomic data were then used to parametrize iEC2812 and investigate the metabotypes of endothelial dysfunction. Glycan production and increased fatty acid metabolism accompany increased glycocalyx shedding and endothelial permeability after inflammatory stimulation. iEC2812 was then used to analyse sepsis patient plasma metabolome profiles and predict changes to endothelial derived biomarkers. These analyses revealed increased changes in glycan metabolism in sepsis non-survivors corresponding to metabolism of endothelial dysfunction in culture. The results show concordance between endothelial health and sepsis survival in particular between endothelial cell metabolism and the plasma metabolome in patients with sepsis.

Mesenchymal stem cells are a promising source for externally grown tissue replacements and patient-specific immunomodulatory treatments. This promise has not yet been fulfilled in part due to production scaling issues and the need to maintain the correct phenotype after re-implantation. One aspect of extracorporeal growth that may be manipulated to optimize cell growth and differentiation is metabolism. The metabolism of MSCs changes during and in response to differentiation and immunomodulatory changes. MSC metabolism may be linked to functional differences but how this occurs and influences MSC function remains unclear. Understanding how MSC metabolism relates to cell function is however important as metabolite availability and environmental circumstances in the body may affect the success of implantation. Genome-scale constraint based metabolic modeling can be used as a tool to fill gaps in knowledge of MSC metabolism, acting as a framework to integrate and understand various data types (e.g., genomic, transcriptomic and metabolomic). These approaches have long been used to optimize the growth and productivity of bacterial production systems and are being increasingly used to provide insights into human health research. Production of tissue for implantation using MSCs requires both optimized production of cell mass and the understanding of the patient and phenotype specific metabolic situation. This review considers the current knowledge of MSC metabolism and how it may be optimized along with the current and future uses of genome scale constraint based metabolic modeling to further this aim.