Placental dysfunction is central to many complications of human pregnancy including pre-eclampsia (PE), intra-uterine growth restriction (IUGR) and stillbirth. The precise molecular pathophysiology of placental dysfunction in these conditions is not known, although oxidative and nitrative stresses have been implicated. Metabolites are low molecular weight chemicals which play an important role in biological function, primarily through metabolism and regulation of biological processes. The holistic study of metabolites, defined as metabolomics or metabolic profiling, has the objective to detect and identify all, or a large complement of all metabolites. Metabolomics is applied to discover new knowledge regarding biological processes and systems. We hypothesised that a metabolomic strategy could (1) provide a reproducible technique to investigate the intracellular metabolism of placental tissue and also metabolites consumed from or secreted in to the extracellular 'metabolic footprint' of in vitro culture systems (2) identify metabolic related differences in placental tissue culture systems subjected to perturbations in oxygen tension and from pregnancies complicated by PE. We review our early studies which demonstrate that a reproducible experimental protocol is required, including the preparation of culture medium and the site of the placenta applied for sampling tissue. We have detected changes in the intracellular metabolome and metabolic footprint of placental tissue in response to altered oxygen tension and PE. We have demonstrated that placental tissue from uncomplicated pregnancies cultured in 1% oxygen (hypoxia) had metabolic similarities to explants from PE pregnancies cultured at 6% oxygen (normoxia). Metabolites requiring further study include lipids, glutamate and glutamine and metabolites related to tryptophan, leukotriene and prostaglandin metabolism. Metabolomics has the potential to identify changes in clinical conditions, such as PE, that are associated with placental molecular pathophysiology.
- Systems biology