Chemical Injuries Research Center, Baqiyatallah University of Medical Sciences, 1477893855 Tehran, Iran.
Department of Pharmaceutics, School of Pharmacy, Baqiyatallah University of Medical Sciences, 1477893855 Tehran, Iran.
Molecules. 2017 Aug 14;22(8):1242. doi: 10.3390/molecules22081242.
Microbial remediation of nitroaromatic compounds (NACs) is a promising environmentally friendly and cost-effective approach to the removal of these life-threating agents. () has shown remarkable capability for the biotransformation of 2,4,6-trinitro-toluene (TNT). Efforts to develop as an efficient TNT degrading biocatalyst will benefit from holistic flux-level description of interactions between multiple TNT transforming pathways operating in the strain. To gain such an insight, we extended the genome-scale constraint-based model of to account for a curated version of major TNT transformation pathways known or evidently hypothesized to be active in in present of TNT. Using constraint-based analysis (CBA) methods, we then performed several series of in silico experiments to elucidate the contribution of these pathways individually or in combination to the TNT transformation capacity. Results of our analyses were validated by replicating several experimentally observed TNT degradation phenotypes in cultures. We further used the extended model to explore the influence of process parameters, including aeration regime, TNT concentration, cell density, and carbon source on TNT degradation efficiency. We also conducted an in silico metabolic engineering study to design a series of mutants capable of degrading TNT at higher yield compared with the wild-type strain. Our study, therefore, extends the application of CBA to bioremediation of nitroaromatics and demonstrates the usefulness of this approach to inform bioremediation research.
微生物修复硝基芳香族化合物 (NACs) 是一种很有前途的环保且经济有效的方法,可以去除这些危及生命的物质。()已显示出对 2,4,6-三硝基甲苯 (TNT) 生物转化的显著能力。开发()作为一种高效的 TNT 降解生物催化剂的努力将受益于对在该菌株中运行的多个 TNT 转化途径之间相互作用的整体通量水平描述。为了获得这种洞察力,我们扩展了()的基于基因组规模的约束模型,以解释在 TNT 存在下已知或明显假设在()中活跃的主要 TNT 转化途径的经过校对的版本。然后,我们使用基于约束的分析 (CBA) 方法进行了几系列的计算机模拟实验,以单独或组合方式阐明这些途径对()TNT 转化能力的贡献。我们的分析结果通过在()培养物中复制几个实验观察到的 TNT 降解表型得到了验证。我们还使用扩展模型来研究过程参数(包括通气方式、TNT 浓度、细胞密度和碳源)对 TNT 降解效率的影响。我们还进行了计算机代谢工程研究,设计了一系列与野生型菌株相比能够以更高产率降解 TNT 的()突变体。因此,我们的研究将 CBA 应用扩展到了硝基芳烃的生物修复,并证明了该方法在生物修复研究中的有用性。