Heux Stéphanie, Poinot Juliette, Massou Stéphane, Sokol Serguei, Portais Jean-Charles
Université de Toulouse; INSA, UPS, INP; LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France; INRA, UMR792, Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France; CNRS, UMR5504, F-31400 Toulouse, France.
Université de Toulouse; INSA, UPS, INP; LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France; INRA, UMR792, Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France; CNRS, UMR5504, F-31400 Toulouse, France.
Metab Eng. 2014 Sep;25:8-19. doi: 10.1016/j.ymben.2014.06.001. Epub 2014 Jun 12.
Advances in metabolic engineering are enabling the creation of a large number of cell factories. However, high-throughput platforms do not yet exist for rapidly analyzing the metabolic network of the engineered cells. To fill the gap, we developed an integrated solution for fluxome profiling of large sets of biological systems and conditions. This platform combines a robotic system for (13)C-labelling experiments and sampling of labelled material with NMR-based isotopic fingerprinting and automated data interpretation. As a proof-of-concept, this workflow was applied to discriminate between Escherichia coli mutants with gradual expression of the glucose-6-phosphate dehydrogenase. Metabolic variants were clearly discriminated while pathways that support metabolic flexibility towards modulation of a single enzyme were elucidating. By directly connecting the data flow between cell cultivation and flux quantification, considerable advances in throughput, robustness, release of resources and screening capacity were achieved. This will undoubtedly facilitate the development of efficient cell factories.
代谢工程的进展使得大量细胞工厂得以创建。然而,目前尚不存在用于快速分析工程细胞代谢网络的高通量平台。为了填补这一空白,我们开发了一种针对大量生物系统和条件进行通量组分析的综合解决方案。该平台将用于¹³C标记实验和标记材料采样的机器人系统与基于核磁共振的同位素指纹识别及自动数据解读相结合。作为概念验证,此工作流程被应用于区分具有逐步表达的6-磷酸葡萄糖脱氢酶的大肠杆菌突变体。代谢变体得到了清晰区分,同时阐明了支持对单一酶进行调节的代谢灵活性的途径。通过直接连接细胞培养和通量定量之间的数据流,在通量、稳健性、资源释放和筛选能力方面取得了显著进展。这无疑将促进高效细胞工厂的开发。