A KINETIC-MODEL FOR PRODUCT FORMATION IN UNSTABLE RECOMBINANT POPULATIONS
A KINETIC-MODEL FOR PRODUCT FORMATION IN UNSTABLE RECOMBINANT POPULATIONS
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DOI：
10.1002/bit.260271211
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发表时间：
1985-01-01
影响因子：
3.8
通讯作者：
BAILEY, JE
中科院分区：
文献类型：
--
作者：
LEE, SB;SERESSIOTIS, A;BAILEY, JE
建立了间歇和连续流动反应器中不稳定重组生物生成产物的数学模型。根据质粒的存在(分离不稳定性)和活性克隆基因的存在(结构不稳定性)，细胞群体具有3种不同的基因类型。由质粒和产物蛋白引起的经验生长抑制因子被分配给相应的菌株。产物形成动力学基于准稳态转录-翻译表达模型。这些基于机理的产物形成动力学的近似形式与传统的、基于经验的Leudeking-Piret公式相同。提出了基于总产物浓度和基于胞内产物浓度考虑抑制的替代模型，并比较了它们的含义。基于这些模型的模拟结果表明：(1)质粒的整体稳定性取决于产物的表达和反应器的操作条件以及固有的分离和突变率参数；(2)存在一个最优的质粒拷贝数和克隆基因转录和翻译效率的组合来最大化反应器的生产率；(3)连续的反应器稀释率影响生产细胞的比例。从模型模拟得到的总体趋势和底物、产物和细胞浓度时间轨迹与当前可用的实验信息定性地吻合。
A mathematical model has been formulated for product formation by unstable recombinant organisms in batch and in continuous flow reactors. The cell population is characterized by 3 different genotypes according to the absence or presence of plasmids (segregational instability) and of active cloned gene (structural instability). Empirical growth inhibition factors due to plasmids and to product protein are assigned to the corresponding strains. Product formation kinetics are based upon a quasisteady-state transcription-translation expression model. An approximate form of these mechanism-based product formation kinetics is identical to the traditional, empirically based Leudeking-Piret formula. Alternative models which consider inhibition based on overall product concentration and based on intracellular product concentration are posed, and their implications are compared. Simulation results based on these models indicate (1) overall plasmid stability depends on product expression and reactor operating conditions as well as on intrinsic segregation and mutation rate parameters; (2) there exists an optimum combination of plasmid copy number and cloned-gene transcription and translation efficiencies to maximize reactor productivity; and (3) continuous reactor dilution rate influences the fraction of productive cells. General trends and substrate, product, and cell concentration time trajectories obtained from model simulation agree well qualitatively with currently available experimental information.