Stoichiometric genome-scale metabolic network models (GEMs) have been widely used to predict metabolic phenotypes. In addition to stoichiometric ratios, other constraints such as enzyme availability and thermodynamic feasibility can also limit the phenotype solution space. Extended GEM models considering either enzymatic or thermodynamic constraints have been shown to improve prediction accuracy. In this paper, we propose a novel method that integrates both enzymatic and thermodynamic constraints in a single Pyomo modeling framework (ETGEMs). We applied this method to construct the EcoETM (E. coli metabolic model with enzymatic and thermodynamic constraints). Using this model, we calculated the optimal pathways for cellular growth and the production of 22 metabolites. When comparing the results with those of iML1515 and models with one of the two constraints, we observed that many thermodynamically unfavorable and/or high enzyme cost pathways were excluded from EcoETM. For example, the synthesis pathway of carbamoyl-phosphate (Cbp) from iML1515 is both thermodynamically unfavorable and enzymatically costly. After introducing the new constraints, the production pathways and yields of several Cbp-derived products (e.g. L-arginine, orotate) calculated using EcoETM were more realistic. The results of this study demonstrate the great application potential of metabolic models with multiple constraints for pathway analysis and phenotype prediction.

化学计量基因组规模代谢网络模型 (GEM) 已被广泛用于预测代谢表型。除了化学计量比之外，酶的可用性和热力学可行性等其他限制条件也会限制表型解决方案空间。已证明考虑酶促或热力学约束的扩展 GEM 模型可以提高预测精度。在本文中，我们提出了一种在单个 Pyomo 建模框架 (ETGEM) 中集成酶促和热力学约束的新方法。我们应用这种方法构建了 EcoETM（具有酶促和热力学约束的大肠杆菌代谢模型）。使用该模型，我们计算了细胞生长和 22 种代谢物产生的最佳途径。当将结果与i ML1515 和具有两个约束之一的模型，我们观察到许多热力学不利和/或酶成本高的途径被排除在 EcoETM 之外。例如，从i ML1515合成氨基甲酰磷酸 (Cbp) 的途径在热力学上是不利的，而且酶促成本很高。引入新的限制条件后，使用 EcoETM 计算的几种 Cbp 衍生产品（例如L-精氨酸、乳清酸）的生产途径和产量更加现实。这项研究的结果证明了具有多种约束条件的代谢模型在通路分析和表型预测方面的巨大应用潜力。