Stefan Thorsten, Wu Xu Na, Zhang Youjun, Fernie Alisdair, Schulze Waltraud X
Department of Plant Systems Biology, University of Hohenheim, Stuttgart, Germany.
College for Life Science, Yunnan University, Kunming, China.
Front Plant Sci. 2022 May 19;13:891405. doi: 10.3389/fpls.2022.891405. eCollection 2022.
Multi-omics data sets are increasingly being used for the interpretation of cellular processes in response to environmental cues. Especially, the posttranslational modification of proteins by phosphorylation is an important regulatory process affecting protein activity and/or localization, which, in turn, can have effects on metabolic processes and metabolite levels. Despite this importance, relationships between protein phosphorylation status and metabolite abundance remain largely underexplored. Here, we used a phosphoproteomics-metabolomics data set collected at the end of day and night in shoots and roots of Arabidopsis to propose regulatory relationships between protein phosphorylation and accumulation or allocation of metabolites. For this purpose, we introduced a novel, robust co-expression measure suited to the structure of our data sets, and we used this measure to construct metabolite-phosphopeptide networks. These networks were compared between wild type and plants with perturbations in key processes of sugar metabolism, namely, sucrose export ( mutant) and starch synthesis ( mutant). The phosphopeptide-metabolite network turned out to be highly sensitive to perturbations in sugar metabolism. Specifically, KING1, the regulatory subunit of SnRK1, was identified as a primary candidate connecting protein phosphorylation status with metabolism. We additionally identified strong changes in the fatty acid network of the mutant, potentially resulting from a combination of fatty acid signaling and metabolic overflow reactions in response to high internal sucrose concentrations. Our results further suggest novel protein-metabolite relationships as candidates for future targeted research.
多组学数据集越来越多地用于解释细胞对环境信号的响应过程。特别是，蛋白质磷酸化的翻译后修饰是影响蛋白质活性和/或定位的重要调控过程，进而可能对代谢过程和代谢物水平产生影响。尽管这一过程很重要，但蛋白质磷酸化状态与代谢物丰度之间的关系在很大程度上仍未得到充分探索。在这里，我们使用了拟南芥地上部和根部在白天和黑夜结束时收集的磷酸化蛋白质组学-代谢组学数据集，来提出蛋白质磷酸化与代谢物积累或分配之间的调控关系。为此，我们引入了一种适用于我们数据集结构的新型、稳健的共表达测量方法，并使用该方法构建代谢物-磷酸肽网络。我们比较了野生型和糖代谢关键过程（即蔗糖输出（突变体）和淀粉合成（突变体））受到扰动的植物之间的这些网络。结果表明，磷酸肽-代谢物网络对糖代谢的扰动高度敏感。具体而言，SnRK1的调节亚基KING1被确定为连接蛋白质磷酸化状态与代谢的主要候选者。我们还发现突变体的脂肪酸网络发生了显著变化，这可能是由于脂肪酸信号传导和对高内部蔗糖浓度的代谢溢流反应共同作用的结果。我们的结果进一步表明了新的蛋白质-代谢物关系，作为未来靶向研究的候选对象。
