Fürtauer Lisa, Weckwerth Wolfram, Nägele Thomas
Department of Ecogenomics and Systems Biology, University of Vienna Vienna, Austria.
Department of Ecogenomics and Systems Biology, University of ViennaVienna, Austria; Vienna Metabolomics Center, University of ViennaVienna, Austria.
Front Plant Sci. 2016 Dec 22;7:1912. doi: 10.3389/fpls.2016.01912. eCollection 2016.
Although compartmentation is a key feature of eukaryotic cells, biological research is frequently limited by methods allowing for the comprehensive subcellular resolution of the metabolome. It has been widely accepted that such a resolution would be necessary in order to approximate cellular biochemistry and metabolic regulation, yet technical challenges still limit both the reproducible subcellular fractionation and the sample throughput being necessary for a statistically robust analysis. Here, we present a method and a detailed protocol which is based on the non-aqueous fractionation technique enabling the assignment of metabolites to their subcellular localization. The presented benchtop method aims at unraveling subcellular metabolome dynamics in a precise and statistically robust manner using a relatively small amount of tissue material. The method is based on the separation of cellular fractions via density gradients consisting of organic, non-aqueous solvents. By determining the relative distribution of compartment-specific marker enzymes together with metabolite profiles over the density gradient it is possible to estimate compartment-specific metabolite concentrations by correlation. To support this correlation analysis, a spreadsheet is provided executing a calculation algorithm to determine the distribution of metabolites over subcellular compartments. The calculation algorithm performs correlation of marker enzyme activity and metabolite abundance accounting for technical errors, reproducibility and the resulting error propagation. The method was developed, tested and validated in three natural accessions of showing different ability to acclimate to low temperature. Particularly, amino acids were strongly shuffled between subcellular compartments in a cold-sensitive accession while a cold-tolerant accession was characterized by a stable subcellular metabolic homeostasis. Finally, we conclude that subcellular metabolome analysis is essential to unambiguously unravel regulatory strategies being involved in plant-environment interactions.
尽管区室化是真核细胞的一个关键特征，但生物学研究常常受到能实现代谢组全面亚细胞分辨率方法的限制。人们普遍认为，为了近似细胞生物化学和代谢调控，这种分辨率是必要的，但技术挑战仍然限制了可重复的亚细胞分级分离以及进行统计稳健分析所需的样本通量。在此，我们提出一种基于非水相分级分离技术的方法及详细方案，该技术能够将代谢物定位到其亚细胞位置。所展示的台式方法旨在使用相对少量的组织材料，以精确且统计稳健的方式揭示亚细胞代谢组动态。该方法基于通过由有机非水溶剂组成的密度梯度分离细胞组分。通过确定区室特异性标记酶的相对分布以及代谢物谱在密度梯度上的分布，可以通过相关性估计区室特异性代谢物浓度。为支持这种相关性分析，提供了一个电子表格，执行一种计算算法来确定代谢物在亚细胞区室中的分布。该计算算法在考虑技术误差、可重复性和由此产生的误差传播的情况下，对标记酶活性和代谢物丰度进行相关性分析。该方法在三种自然材料中进行了开发、测试和验证，这些材料对低温的适应能力不同。特别是，在对冷敏感的材料中，氨基酸在亚细胞区室之间强烈重排，而耐寒材料的特征是亚细胞代谢稳态稳定。最后，我们得出结论，亚细胞代谢组分析对于明确揭示参与植物 - 环境相互作用的调控策略至关重要。
