Systems biology has long been interested in models capturing both metabolism and expression in a cell. We propose here an implementation of the metabolism and expression model formalism (ME-models), which we call ETFL, for Expression and Thermodynamics Flux models. ETFL is a hierarchical model formulation, from metabolism to RNA synthesis, that allows simulating thermodynamics-compliant intracellular fluxes as well as enzyme and mRNA concentration levels. ETFL formulates a mixed-integer linear problem (MILP) that enables both relative and absolute metabolite, protein, and mRNA concentration integration. ETFL is compatible with standard MILP solvers and does not require a non-linear solver, unlike the previous state of the art. It also accounts for growth-dependent parameters, such as relative protein or mRNA content. We present ETFL along with its validation using results obtained from a well-characterized E. coli model. We show that ETFL is able to reproduce proteome-limited growth. We also subject it to several analyses, including the prediction of feasible mRNA and enzyme concentrations and gene essentiality.

中文翻译：

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ETFL配方可将多组学整合到符合热力学的代谢和表达模型中。

长期以来，系统生物学一直对捕获细胞中新陈代谢和表达的模型感兴趣。我们在此提出用于表达和热力学通量模型的新陈代谢和表达模型形式主义（ME-model）（我们称为ETFL）的实现。ETFL是一种从代谢到RNA合成的分层模型，可模拟符合热力学的细胞内通量以及酶和mRNA的浓度水平。ETFL制定了一个混合整数线性问题（MILP），可以实现相对和绝对代谢物，蛋白质和mRNA浓度的整合。ETFL与标准MILP求解器兼容，并且与现有技术不同，它不需要非线性求解器。它还考虑了依赖于生长的参数，例如相对蛋白质或mRNA含量。我们使用从特征明确的大肠杆菌模型获得的结果来展示ETFL及其验证。我们证明ETFL能够复制蛋白质组受限的增长。我们还对其进行了一些分析，包括对可行的mRNA和酶浓度以及基因必需性的预测。