Bloem Audrey, Rollero Stephanie, Seguinot Pauline, Crépin Lucie, Perez Marc, Picou Christian, Camarasa Carole
UMR SPO, INRA, SupAgroM, Université de Montpellier.
IWBT Stellenbosch University.
J Vis Exp. 2018 Jan 22(131):56393. doi: 10.3791/56393.
Studies in the field of microbiology rely on the implementation of a wide range of methodologies. In particular, the development of appropriate methods substantially contributes to providing extensive knowledge of the metabolism of microorganisms growing in chemically defined media containing unique nitrogen and carbon sources. In contrast, the management through metabolism of multiple nutrient sources, despite their broad presence in natural or industrial environments, remains virtually unexplored. This situation is mainly due to the lack of suitable methodologies, which hinders investigations. We report an experimental strategy to quantitatively and comprehensively explore how metabolism operates when a nutrient is provided as a mixture of different molecules, i.e., a complex resource. Here, we describe its application for assessing the partitioning of multiple nitrogen sources through the yeast metabolic network. The workflow combines information obtained during stable isotope tracer experiments using selected C- or N-labeled substrates. It first consists of parallel and reproducible fermentations in the same medium, which includes a mixture of N-containing molecules; however,a selected nitrogen source is labeled each time. A combination of analytical procedures (HPLC, GC-MS) is implemented to assess the labeling patterns of targeted compounds and to quantify the consumption and recovery of substrates in other metabolites. An integrated analysis of the complete dataset provides an overview of the fate of consumed substrates within cells. This approach requires an accurate protocol for the collection of samples-facilitated by a robot-assisted system for online monitoring of fermentations-and the achievement of numerous time-consuming analyses. Despite these constraints, it allowed understanding, for the first time, the partitioning of multiple nitrogen sources throughout the yeast metabolic network. We elucidated the redistribution of nitrogen from more abundant sources toward other N-compounds and determined the metabolic origins of volatile molecules and proteinogenic amino acids.
微生物学领域的研究依赖于多种方法的实施。特别是，合适方法的开发极大地有助于提供关于在含有独特氮源和碳源的化学限定培养基中生长的微生物代谢的广泛知识。相比之下，尽管多种营养源在自然或工业环境中广泛存在，但通过代谢对其进行管理实际上仍未得到探索。这种情况主要是由于缺乏合适的方法，这阻碍了研究。我们报告了一种实验策略，用于定量和全面地探索当一种营养物质以不同分子的混合物（即复杂资源）形式提供时，代谢是如何运作的。在这里，我们描述了其在通过酵母代谢网络评估多种氮源分配方面的应用。该工作流程结合了在使用选定的碳或氮标记底物的稳定同位素示踪实验中获得的信息。它首先包括在同一培养基中进行平行且可重复的发酵，该培养基包含含氮分子的混合物；然而，每次选择一种氮源进行标记。实施一系列分析程序（高效液相色谱法、气相色谱 - 质谱法）来评估目标化合物的标记模式，并量化其他代谢物中底物的消耗和回收情况。对完整数据集的综合分析提供了细胞内消耗底物去向的概述。这种方法需要一个精确的样本采集方案——由一个用于在线监测发酵的机器人辅助系统来辅助——以及完成大量耗时的分析。尽管有这些限制，但它首次使我们能够了解整个酵母代谢网络中多种氮源的分配情况。我们阐明了氮从较丰富的来源向其他含氮化合物的重新分配，并确定了挥发性分子和蛋白质ogenic氨基酸的代谢来源。 （注：“proteinogenic”可能有误，推测可能是“proteinogenic”，意为“生蛋白的”，这里暂按推测翻译）
