Integration of transcriptomics and metabolomics data specifies the metabolic response of Chlamydomonas to rapamycin treatment
Integration of transcriptomics and metabolomics data specifies the metabolic response of Chlamydomonas to rapamycin treatment
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DOI：
10.1111/tpj.12763
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发表时间：
2015-03-01
期刊：
影响因子：
7.2
通讯作者：
Nikoloski, Zoran
中科院分区：
文献类型：
--
作者：
Kleessen, Sabrina;Irgang, Susann;Nikoloski, Zoran
通量表型预测的约束为基础的方法，可以细化包括异质性数据。虽然最近的进展促进了转录组学和蛋白质组学数据的整合，但缺乏通过考虑代谢组学数据来预测通量表型的纯粹基于化学计量的方法。在这里，我们提出了一种基于约束的方法，称为TREM-Flux，用于整合时间分辨代谢组学和转录组学数据。我们证明了TREM-Flux的适用性，在解剖的代谢反应的莱茵衣藻雷帕霉素治疗整合的表达水平的982个基因和45个代谢产物的含量从两个生长条件。研究结果指出，半胱氨酸和蛋氨酸代谢受雷帕霉素治疗的影响最大。我们的研究表明，除了转录组学数据的时间分辨未标记的代谢组学数据的整合可以指定参与系统的响应所研究的treatment.Significance StatementIntegration的代谢途径转录组学和代谢组学的时间序列数据在大规模的生化反应模型是用来获得代表性通量表型。通量表型的比较分析，从衣原体针最受影响的代谢功能，在不同的生长条件下的雷帕霉素治疗。
Flux phenotypes predicted by constraint-based methods can be refined by the inclusion of heterogeneous data. While recent advances facilitate the integration of transcriptomics and proteomics data, purely stoichiometry-based approaches for the prediction of flux phenotypes by considering metabolomics data are lacking. Here we propose a constraint-based method, termed TREM-Flux, for integrating time-resolved metabolomics and transcriptomics data. We demonstrate the applicability of TREM-Flux in the dissection of the metabolic response of Chlamydomonas reinhardtii to rapamycin treatment by integrating the expression levels of 982 genes and the content of 45 metabolites obtained from two growth conditions. The findings pinpoint cysteine and methionine metabolism to be most affected by the rapamycin treatment. Our study shows that the integration of time-resolved unlabeled metabolomics data in addition to transcriptomics data can specify the metabolic pathways involved in the system's response to a studied treatment.Significance StatementIntegration of transcriptomics and metabolomics time-series data in large-scale models of biochemical reactions is used to derive representative flux phenotypes. Comparative analysis of the flux phenotypes from Chlamydomonas pinpoints the most affected metabolic functions in response to the rapamycin treatment under different growth conditions.