Novel metabolomic strategies to understand phenotypic perturbations

对生理学和细胞生物学的分子机制的科学理解对于理解正常的人类生理学至关重要，这为理解扰动提供了最强大的手段。在心脏生理学和细胞生物学中，为了预防和了解不利的表型变化，发展这种认识的必要性尤为重要。了解心脏生理学和细胞生物学的高价值的有形证据是识别涉及到心电波形的关键离子通道。然而，除了关键细胞器之外，其他与心电图无关的心脏生理学和细胞生物学事件之间的分子联系，特别是心脏细胞生物学和形态的变化，知之甚少(Cross等人)。2015年；Laverty等人。2011年)。代谢组学为识别心肌细胞生物学和形态表型中的预测性和反射性扰动提供了机会，促进了定量翻译理解的发展。这些代谢组指纹整合并反映了基因组、转录组和蛋白质组的变化，提供了确凿的证据，表明代谢组指纹的变化将促进对心肌细胞生物学表型和表型扰动的影响的理解。此外，代谢改变与包括心力衰竭和心肌梗死在内的各种心血管疾病表型有关(Dunn等人。2011年；Kordalewska和Markuzewski，2015年)。这强烈地表明，利用代谢组学来理解心肌细胞生物学和形态表型变化期间的扰动是可行的。这将为发现可翻译的分子扰动提供一种不偏不倚的方法，这些扰动反过来可以用来产生生物学假说，用于更详细的研究。为了实现这一愿景，需要将更复杂的、因此具有生理相关性的先进模型系统(例如微组织和微生理系统(MPS))与来自临床前物种和临床样本的生物液/组织一起应用于代谢组学领域。然而，由于样本质量较小，这在分析方面提出了挑战。通过采用当代代谢组学技术，这些技术已经被优化用于临床应用，我们需要开发更高灵敏度的代谢组学方法，使代谢组学能够应用于这一前沿研究。最终，这将在模型系统和分析方面带来新的新方法，以加深对表型扰动的理解。最后，这些进展比心血管领域具有更广泛的适用性，一旦在这个领域发展起来，其他关键器官区域就可以被研究。

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.