Kotze Helen L, Armitage Emily G, Sharkey Kieran J, Allwood James W, Dunn Warwick B, Williams Kaye J, Goodacre Royston
School of Chemistry, Manchester Institute of Biotechnology, University of Manchester, Manchester M1 7DN, UK.
BMC Syst Biol. 2013 Oct 23;7:107. doi: 10.1186/1752-0509-7-107.
Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments.
Correlation analysis has revealed statistically significant connections between metabolites, where differences in correlations between cells exposed to different oxygen levels have been highlighted as markers of hypoxic metabolism in cancer. Network mapping onto reconstructed human metabolic models is a novel addition to correlation analysis. Correlated metabolites have been mapped onto the Edinburgh human metabolic network (EHMN) with the aim of interlinking metabolites found to be regulated in a similar fashion in response to oxygen. This revealed novel pathways within the metabolic network that may be key to tumour cell survival at low oxygen. Results show that the metabolic responses to lowering oxygen availability can be conserved or specific to a particular cell line. Network-based correlation analysis identified conserved metabolites including malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate. In this way, this method has revealed metabolites not previously linked, or less well recognised, with respect to hypoxia before. Lactate fermentation is one of the key themes discussed in the field of hypoxia; however, malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate, which are connected by a single pathway, may provide a more significant marker of hypoxia in cancer.
Metabolic networks generated for each cell line were compared to identify conserved metabolite pathway responses to low oxygen environments. Furthermore, we believe this methodology will have general application within metabolomics.
代谢组学在疾病表型和分子病理生理学研究中越来越受欢迎。代谢组学的一个分支是代谢谱分析,它涵盖了细胞代谢的高通量筛选。在本研究中,将来自结直肠癌和乳腺腺癌的不同肿瘤细胞的代谢谱暴露于缺氧和常氧条件下,并进行比较,以揭示缺氧对肿瘤细胞生物化学的潜在代谢影响;这可能有助于它们在氧含量受限的环境中存活。为了分析代谢物之间超出常规单变量和多变量数据分析方法的复杂相互作用,将相关性分析与人类代谢重建相结合,以揭示与常氧或缺氧环境相关的代谢途径之间的联系。
相关性分析揭示了代谢物之间具有统计学意义的联系,其中暴露于不同氧水平的细胞之间相关性的差异被突出显示为癌症缺氧代谢的标志物。将网络映射到重建的人类代谢模型上是相关性分析的一项新内容。已将相关代谢物映射到爱丁堡人类代谢网络(EHMN)上,目的是将发现以类似方式响应氧气而受到调节的代谢物相互联系起来。这揭示了代谢网络中的新途径,这些途径可能是肿瘤细胞在低氧条件下存活的关键。结果表明,对降低氧可用性的代谢反应可能是保守的,也可能是特定于某一细胞系的。基于网络的相关性分析确定了保守的代谢物,包括苹果酸、丙酮酸、2-氧代戊二酸、谷氨酸和6-磷酸果糖。通过这种方式,该方法揭示了以前未与缺氧相关联或认识较少的代谢物。乳酸发酵是缺氧领域讨论的关键主题之一;然而,通过单一途径连接的苹果酸、丙酮酸、2-氧代戊二酸、谷氨酸和6-磷酸果糖可能是癌症中缺氧的更重要标志物。
比较为每个细胞系生成的代谢网络,以确定对低氧环境的保守代谢物途径反应。此外,我们认为这种方法将在代谢组学中得到广泛应用。