天蓝色链霉菌代谢物组测定方法优化及其代谢特征

Optimized sample preparation for metabolome studies on Streptomyces coelicolor

链霉菌能够产生多种抗生素,具有重要的研究与应用价值。代谢物组学能够定性和定量测定胞内外主要低分子量代谢产物。相对于其他组学,代谢物组学在监控胞内代谢状态、指导物种理性改造方面具有独特优势。本文旨在建立一种快速、准确的链霉菌胞内代谢物分析方法。以模式菌株天蓝色链霉菌为研究对象,基于GC-MS分析平台优化了代谢物组学样品制备流程中的细胞淬灭时间、菌体分离方法、代谢物提取及代谢物衍生化条件,并利用该方法对天蓝色链霉菌不同生长时期各代谢途径的相对活性进行了初步分析。采用"低温淬灭(–40℃,4 min)-快速过滤分离-反复冻融(45 s/3 min)-衍生化(40℃,90 min)"的流程能够鉴定出中心代谢途径(糖酵解、戊糖磷酸途径和TCA循环)、氨基酸代谢途径、脂肪酸代谢途径、核酸代谢途径及部分次级代谢途径中的103种主要代谢物。利用该流程测定发现天蓝色链霉菌细胞生长周期中存在显著的代谢时序差异,并且发现氨基酸与脂肪酸代谢在衔接初级代谢与次级代谢生物合成中具有重要作用。本研究建立的测定方法能够有效地用于天蓝色链霉胞内代谢物分析,该方法将有助于深入刻画链霉菌细胞代谢过程,为菌株代谢工程改造增加次级代谢产物产量提供理性指导。

Streptomycetes produce many antibiotics and are important model microorgansims for scientific research and antibiotic production. Metabolomics is an emerging technological platform to analyze low molecular weight metabolites in a given organism qualitatively and quantitatively. Compared to other Omits platform, metabolomics has greater advantage in monitoring metabolic flux distribution and thus identifying key metabolites related to target metabolic pathway. The present work aims at establishing a rapid, accurate sample preparation protocol for metabolomics analysis in streptomycetes. In the present work, several sample preparation steps, including cell quenching time, cell separation method, conditions for metabolite extraction and metabolite derivatization were optimized. Then, the metabolic profiles of Streptomyces coelicolor during different growth stages were analyzed by GC-MS. The optimal sample preparation conditions were as follows： time of low-temperature quenching 4 min, cell separation by fast filtration, time of freeze-thaw 45 s/3 min and the conditions of metabolite derivatization at 40 ℃ for 90 rain. By using this optimized protocol, 103 metabolites were finally identified from a sample of S. coelicolor, which distribute in central metabolic pathways （glycolysis, pentose phosphate pathway and citrate cycle）, amino acid, fatty acid, nucleotide metabolic pathways, etc. By comparing the temporal profiles of these metabolites, the amino acid and fatty acid metabolic pathways were found to stay at a high level during stationary phase, therefore, these pathways may play an important role during the transition between the primary and secondary metabolism. An optimized protocol of sample preparation was established and applied for metabolomics analysis of S. coelicolor, 103 metabolites were identified. The temporal profiles of metabolites reveal amino acid and fatty acid metabolic pathways may play an important role in the transition from primary to secondary metabolism in S. coelicolor.