Novel metabolomic strategies to understand phenotypic perturbations

Scientific understanding of molecular mechanisms underlying physiology and cell biology is critical in understanding normal human physiology, providing the most powerful means of understanding perturbations. The need to develop such an understanding is particularly important in cardiac physiology and cell biology in order to prevent and understand adverse phenotypic changes. Tangible evidence for the high value of understanding cardiac physiology and cell biology is the identification of the key ion channels involved in the ECG waveform. However the molecular links between other, non ECG-related cardiac physiology and cell biology events, in particular changes in cardiac cell biology and morphology, are poorly understood beyond the implication of key organelles (Cross et al. 2015; Laverty et al. 2011).

Metabolomics offers the opportunity for the identification of prognostic and reflective perturbations in cardiac cell biology and morphology phenotypes facilitating the development of quantitative translational understanding. These metabolomic fingerprints integrate and reflect changes in the genome, transcriptome and proteome, providing tangible evidence that changes in the metabolomic fingerprint will generate understanding of cardiac cell biology phenotypes and the impact of phenotypic perturbations. In addition, metabolomic alterations have been linked to various cardiovascular disease phenotypes including heart failure and myocardial infarction (Dunn et al. 2011; Kordalewska and Markuzewski 2015). This strongly suggests that using metabolomics to understand perturbations during phenotypic changes in cardiac cell biology and morphology would be feasible. This would provide an unbiased approach for discovering translatable molecular perturbations that can in turn be used to generate biological hypotheses for more detailed investigations.

In order for this vision to be realised, advanced model systems with greater complexity and thus physiological relevance (e.g. microtissues and microphysiological systems (MPS)) need to be applied to the metabolomics field in conjunction with biofluids/tissue from preclinical species and clinical samples. However, this presents challenges in terms of the analytics, due to the small sample masses. By adapting contemporary metabolomics technologies that have been optimised for clinical applications we need to develop much higher sensitivity metabolomics methods to enable the application of metabolomics to this cutting edge research. Ultimately this will bring together new novel approaches in terms of model systems and analytics to develop deep understanding of phenotypic perturbations.

Finally, these advancements have wider applicability than the cardiovascular area, once developed in this space other key organ areas could be investigated.