Puchałka Jacek, Oberhardt Matthew A, Godinho Miguel, Bielecka Agata, Regenhardt Daniela, Timmis Kenneth N, Papin Jason A, Martins dos Santos Vítor A P
Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.
PLoS Comput Biol. 2008 Oct;4(10):e1000210. doi: 10.1371/journal.pcbi.1000210. Epub 2008 Oct 31.
A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, (13)C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype-phenotype relationships and provides a sound framework to explore this versatile bacterium and to capitalize on its vast biotechnological potential.
生物技术的一个基石是利用微生物高效生产化学品并消除有害废物。恶臭假单胞菌是这类微生物的一个典型代表，因其代谢的多功能性、抗逆性、易于进行基因改造以及在环境和工业应用方面的巨大潜力。为了阐明恶臭假单胞菌的代谢途径及其在生物催化中的应用，特别是用于生产与生长无关的生化物质，我们开发并在此展示了恶臭假单胞菌KT2440代谢的全基因组规模基于约束的模型。网络重建和通量平衡分析（FBA）能够定义代谢网络的结构、识别知识空白并确定关键的代谢功能，从而有助于完善基因注释。FBA和通量变异性分析用于分析该模型的特性、潜力和局限性。这些分析允许在各种条件下识别代谢的关键特征，如生长产量、资源分配、网络稳健性和基因必需性。该模型通过连续细胞培养数据、高通量表型数据、内部通量分布的（13）C测量以及专门生成的基因敲除突变体进行了验证。在75%的情况下，营养缺陷型被正确预测。这些系统分析表明，代谢网络结构是决定预测准确性的主要因素，而生物质组成的影响可以忽略不计。最后，我们利用该模型设计代谢工程策略，以提高聚羟基脂肪酸酯的产量，聚羟基脂肪酸酯是一类在生物技术上有用的化合物，其合成与细胞存活不相关。经过充分验证的模型对基因型 - 表型关系提供了有价值的见解，并为探索这种多功能细菌及其利用其巨大的生物技术潜力提供了一个可靠的框架。
