Identification of Metabolic Engineering Targets through Analysis of Optimal and Sub-Optimal Routes

Identification of optimal genetic manipulation strategies for redirecting substrate uptake towards a desired product is a challenging task owing to the complexity of metabolic networks, esp. in terms of large number of routes leading to the desired product. Algorithms that can exploit the whole range of optimal and suboptimal routes for product formation while respecting the biological objective of the cell are therefore much needed. Towards addressing this need, we here introduce the notion of structural flux, which is derived from the enumeration of all pathways in the metabolic network in question and accounts for the contribution towards a given biological objective function. We show that the theoretically estimated structural fluxes are good predictors of experimentally measured intra-cellular fluxes in two model organisms, namely, Escherichia coli and Saccharomyces cerevisiae. For a small number of fluxes for which the predictions were poor, the corresponding enzyme-coding transcripts were also found to be distinctly regulated, showing the ability of structural fluxes in capturing the underlying regulatory principles. Exploiting the observed correspondence between in vivo fluxes and structural fluxes, we propose an in silico metabolic engineering approach, iStruF, which enables the identification of gene deletion strategies that couple the cellular biological objective with the product flux while considering optimal as well as sub-optimal routes and their efficiency.由于代谢网络的复杂特性，尤其是通往目标产物的代谢途径数量繁多，识别可将底物摄取重定向至目标产物的最优遗传操作策略，是一项极具挑战性的工作。因此，亟需能够兼顾细胞自身生物学目标，同时充分利用产物合成的全部最优与次优代谢途径的算法。为解决这一需求，本文提出了结构通量（structural flux）的概念：该指标源自对目标代谢网络中所有代谢途径的枚举，可量化其对特定生物学目标函数的贡献程度。研究表明，在大肠杆菌（Escherichia coli）和酿酒酵母（Saccharomyces cerevisiae）这两种模式生物中，理论估算得到的结构通量可较好地预测实验测得的胞内通量。对于少数预测效果不佳的通量，其对应的编码酶的转录本也呈现出显著的调控差异，这印证了结构通量能够捕捉潜在调控机制的能力。基于上述体内通量与结构通量之间的对应关系，本文提出了一种计算机模拟（in silico）代谢工程方法iStruF：该方法可在考量最优与次优途径及其效率的前提下，识别出可将细胞生物学目标与产物通量相耦合的基因敲除策略。