Tomàs-Gamisans Màrius, Ferrer Pau, Albiol Joan
Departament d'Enginyeria Química, Biològica i Ambiental, Universitat Autònoma de Barcelona, 08193 Bellaterra (Cerdanyola del Vallès), Barcelona, Spain.
PLoS One. 2016 Jan 26;11(1):e0148031. doi: 10.1371/journal.pone.0148031. eCollection 2016.
Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented.
In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the iMT1026 model has shown a better performance than the previous existing models.
基因组规模代谢模型（GEMs）是能够在特定环境条件下根据基因型预测表型的工具。在过去十年中，已针对多种生物开发了GEMs，并用于多种目的，例如发现代谢网络的新特性、预测代谢工程的新靶点，以及优化生化制品或重组蛋白生产的培养条件。巴斯德毕赤酵母是最广泛用于异源蛋白表达的生物之一。针对这种甲基营养型酵母有不同的GEMs，其中已发表文献中最相关且最完整的是iPP668、PpaMBEL1254和iLC915。然而，这三个模型在某些途径、代谢物和反应的术语以及注释方面存在差异。此外，某些物种的GEMs通常基于相关模式生物的重建模型构建。在这些情况下，一些特定于生物体的途径可能缺失或表述错误。
为了提供一个更新且更全面的巴斯德毕赤酵母GEM，我们重建并验证了一个整合并合并所有三个现有模型的共识模型。在这一步骤中，对这三个版本中每个版本所包含的代谢途径进行了全面审查和整合。此外，所得的iMT1026模型包含了一些代谢过程的新描述。特别纳入了最近发表文献中描述的新信息，主要涉及脂肪酸和鞘脂代谢、糖基化和细胞能量学。最后，通过将模拟结果与从广泛实验条件（如不同碳源、不同氧气供应条件以及两种不同重组蛋白的生产）获得的可用经验生理数据集结果进行比较，对重建模型进行了测试和验证。在这些模拟中，iMT1026模型表现出比先前现有模型更好的性能。
