Background The fungus Aspergillus niger is an important industrial organism for citric acid fermentation; one of the most efficient biotechnological processes. Previously we introduced a dynamic model that captures this process in the industrially relevant batch fermentation setting, providing a more accurate predictive platform to guide targeted engineering. In this article we exploit this dynamic modelling framework, coupled with a robust genetic algorithm for the in silico evolution of A. niger organic acid production, to provide solutions to complex evolutionary goals involving a multiplicity of targets and beyond the reach of simple Boolean gene deletions. We base this work on the latest metabolic models of the parent citric acid producing strain ATCC1015 dedicated to organic acid production with the required exhaustive genomic coverage needed to perform exploratory in silico evolution. Results With the use of our informed evolutionary framework, we demonstrate targeted changes that induce a complete switch of acid output from citric to numerous different commercially valuable target organic acids including succinic acid. We highlight the key changes in flux patterns that occur in each case, suggesting potentially valuable targets for engineering. We also show that optimum acid productivity is achieved through a balance of organic acid and biomass production, requiring finely tuned flux constraints that give a growth rate optimal for productivity. Conclusions This study shows how a genome-scale metabolic model can be integrated with dynamic modelling and metaheuristic algorithms to provide solutions to complex metabolic engineering goals of industrial importance. This framework for in silico guided engineering, based on the dynamic batch growth relevant to industrial processes, offers considerable potential for future endeavours focused on the engineering of organisms to produce valuable products.

中文翻译：

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黑曲霉有机酸生产的计算机模拟进化提出了切换酸输出的策略。


背景真菌黑曲霉(Aspergillus niger)是柠檬酸发酵的重要工业微生物。最有效的生物技术过程之一。之前我们介绍了一个动态模型，该模型可以在工业相关的批量发酵设置中捕获此过程，从而提供更准确的预测平台来指导有针对性的工程。在本文中，我们利用这种动态建模框架，结合用于黑曲霉有机酸生产的计算机进化的强大遗传算法，为涉及多个目标且超出简单布尔基因删除范围的复杂进化目标提供解决方案。我们的这项工作基于专用于有机酸生产的柠檬酸生产亲本菌株 ATCC1015 的最新代谢模型，具有进行计算机进化探索所需的详尽基因组覆盖范围。结果通过使用我们知情的进化框架，我们展示了有针对性的变化，导致酸输出从柠檬酸完全转变为包括琥珀酸在内的许多不同的具有商业价值的目标有机酸。我们强调了每种情况下发生的通量模式的关键变化，为工程提出了潜在有价值的目标。我们还表明，最佳的酸生产率是通过有机酸和生物质生产的平衡来实现的，需要精细调整通量限制，以提供最佳的生产率增长率。结论本研究展示了如何将基因组规模的代谢模型与动态建模和元启发式算法相结合，为具有工业重要性的复杂代谢工程目标提供解决方案。 这种计算机引导工程框架基于与工业过程相关的动态批量增长，为未来专注于生物工程以生产有价值产品的努力提供了巨大的潜力。