Laboratory of Synthetic Microbiology, School of Chemical Engineering & Technology, and Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin University , Tianjin 300072, P. R. China.
J Proteome Res. 2013 Nov 1;12(11):5302-12. doi: 10.1021/pr400640u. Epub 2013 Sep 24.
Although synthetic biology progress has made it possible to produce various biofuels in more user-friendly hosts, such as Escherichia coli, the large-scale biofuel production in these non-native systems is still challenging, mostly due to the very low tolerance of these non-native hosts to the biofuel toxicity. To address the issues, in this study we determined the metabolic responses of E. coli induced by three major biofuel products, ethanol, butanol, and isobutanol, using a gas chromatography-mass spectrometry (GC-MS) approach. A metabolomic data set of 65 metabolites identified in all samples was then subjected to principal component analysis (PCA) to compare their effects and a weighted correlation network analysis (WGCNA) to identify the metabolic modules specifically responsive to each of the biofuel stresses, respectively. The PCA analysis showed that cellular responses caused by the biofuel stress were in general similar to aging cells at stationary phase, inconsistent with early studies showing a high degree of dissimilarity between metabolite responses during growth cessation as induced through stationary phases or through various environmental stress applications. The WGCNA analysis allowed identification of 2, 4, and 2 metabolic modules specifically associated with ethanol, butanol, and isobutanol treatments, respectively. The biofuel-associated modules included amino acids and osmoprotectants, such as isoleucine, valine, glycine, glutamate, and trehalose, suggesting amino acid metabolism and osmoregulation are among the key protection mechanisms against biofuel stresses in E. coli. Interestingly, no module was found associated with all three biofuel products, suggesting differential effects of each biofuel on E. coli. The findings enhanced our understanding of E. coli responses to exogenous biofuels and also demonstrated the effectiveness of the metabolomic and network analysis in identifying key targets for biofuel tolerance.
尽管合成生物学的进展使得在更易于使用的宿主（如大肠杆菌）中生产各种生物燃料成为可能，但在这些非天然系统中大规模生产生物燃料仍然具有挑战性，这主要是由于这些非天然宿主对生物燃料毒性的耐受性非常低。为了解决这些问题，本研究使用气相色谱-质谱（GC-MS）方法确定了大肠杆菌对三种主要生物燃料产品（乙醇、丁醇和异丁醇）的代谢反应。然后，对所有样品中鉴定出的 65 种代谢物的代谢组学数据集进行主成分分析（PCA），以比较它们的影响，并进行加权相关网络分析（WGCNA），以分别鉴定对每种生物燃料胁迫特异响应的代谢模块。PCA 分析表明，生物燃料胁迫引起的细胞反应与处于静止期的衰老细胞大致相似，与早期研究结果不一致，早期研究表明，在通过静止期或通过各种环境胁迫应用诱导的生长停止期间，代谢物反应具有高度的差异性。WGCNA 分析允许分别鉴定与乙醇、丁醇和异丁醇处理特异性相关的 2、4 和 2 个代谢模块。与生物燃料相关的模块包括氨基酸和渗透调节剂，如异亮氨酸、缬氨酸、甘氨酸、谷氨酸和海藻糖，这表明氨基酸代谢和渗透压调节是大肠杆菌抵御生物燃料胁迫的关键保护机制之一。有趣的是，没有发现与所有三种生物燃料产品相关的模块，这表明每种生物燃料对大肠杆菌的影响不同。这些发现增强了我们对大肠杆菌对外源生物燃料的反应的理解，也证明了代谢组学和网络分析在鉴定生物燃料耐受性的关键靶标方面的有效性。
