LC-MS-QTof-analyzer

微生物生物技术教授职位的重点是开发和优化来自可再生原料的化学品和燃料的微生物生产过程，以及工业过程条件下微生物的系统级生理研究。为了开发工业生物技术的既定和微生物系统的潜力，我们应用代谢工程，系统生物学和合成生物学的方法。定制细胞工厂的建设是通过基因工程的现代方法进行的。在这种情况下，定量和系统地了解微生物平台，如产钠弧菌，恶臭假单胞菌，噬氢菌pseudoflava和谷氨酸棒杆菌的代谢性能是必不可少的。此外，我们还研究了模式植物拟南芥的代谢网络，特别是细胞色素P450酶的功能及其在微生物技术中的应用。使用所要求的LC-MS-QTof分析系统，可以使用不同的过程控制策略（例如，分批、补料分批、连续过程控制等）分析微生物或植物培养方法的样品。以及筛选和进化方法的样本。这是必要的，在一个详细的水平，目前是不可能的，在教授职位的微生物生物技术。拟建立的代谢组学分析应侧重于所谓的非靶向代谢组学，即特征分析和指纹分析方法，以及非参照或未知化合物的鉴定，从而用于阐明代谢途径和细胞调控机制以及优化生产系统等。

The focus of the professorship for microbial biotechnology is on the development and optimization of microbial production processes for chemicals and fuels from renewable raw materials and systems-level physiological studies of microbes under industrial process conditions. To exploit the potential of established and microbial systems for industrial biotechnology, we apply the methodology of metabolic engineering, systems biology and synthetic biology. The construction of tailor-made cell factories is carried out by modern methods of genetic engineering. The development of a quantitative and systemic understanding of the metabolic performance of microbial platforms such as Vibrio natriegens, Pseudomonas putida, Hydrogenophaga pseudoflava and Corynebacterium glutamicum is essential in this context. In addition, we investigate metabolic networks in the model plant Arabidopsis thaliana and in particular the functions of cytochrome P450 enzymes and their application for microbial biotechnology. With the requested LC-MS-QTof analysis system, samples from microbial or plant cultivation approaches are to be analyzed using different process control strategies (e.g. batch, fed-batch, continuous process control etc.) as well as samples from screening and evolution approaches. This is necessary in a level of detail that is currently not possible at the professorship for microbial biotechnology. The metabolome analysis to be established should focus on so-called untargeted metabolomics, i.e. profiling and fingerprinting approaches, as well as the identification of non-referenced or unknown compounds, and thus be used, for example, to elucidate metabolic pathways and cellular regulatory mechanisms as well as to optimize production systems.