Abstract：
An engineered Synechococcus elongatus UTEX 2973-IspS.IDI is used to enhance isoprene production through geranyl diphosphate synthase (CrtE) inhibition and process parameters (light intensity, NaHCO3 and growth temperature) optimization approach. A cumulative isoprene production of 1.21 mg/gDCW was achieved with productivity of 12.6 μg/gDCW/h in culture supplemented with 20 μg/mL alendronate. This inhibition strategy improvises the cumulative isoprene production 5.76-fold in presence of alendronate. The maximum cumulative production of isoprene is observed to be 5.22 and 6.20 mg/gDCW (54.4 and 64.6 μg/gDCW/h) at statistical and artificial neural network genetic algorithm (ANN-GA) optimized conditions, respectively. The overall increase of isoprene production is found to be 29.52-fold using an integrated approach of inhibition and ANN-GA optimization in comparison to unoptimized cultures without alendronate. This study reveals that alendronate use as a potential inhibitor and machine learning based optimization is a better approach in comparison to statistical optimization to enhance the isoprene production.
摘要：
一种工程改造的长神经球菌UTEX2973-IspS。IDI用于通过香叶二磷酸合酶（CrtE）抑制和工艺参数（光强度，NaHCO3和生长温度)的优化方法。在补充有20μg/mL阿仑膦酸盐的培养物中，以12.6μg/gDCW/h的生产率实现了1.21mg/gDCW的累积异戊二烯产量。这种抑制策略使在阿仑膦酸盐存在下的累积异戊二烯产量为5.76倍。在统计和人工神经网络遗传算法（ANN-GA）优化的条件下，观察到异戊二烯的最大累积产量为5.22和6.20mg/gDCW（54.4和64.6μg/gDCW/h），分别。与没有阿仑膦酸盐的未优化培养物相比，使用抑制和ANN-GA优化的综合方法发现异戊二烯产量的总体增加是29.52倍。这项研究表明，阿仑膦酸盐作为潜在的抑制剂和基于机器学习的优化是一个更好的方法相比，统计优化，以提高异戊二烯的生产。
