基于GC-MS的灰葡萄孢菌代谢组分析

对农作物重要病害灰霉病的致病菌——灰葡萄孢菌进行了代谢组提取溶剂、衍生化时间和温度等前处理条件以及内标物筛选优化。结果表明,以水杨苷作为内标物,试验条件下以甲醇-水(80∶20)为提取溶剂,按照4.0 m L/0.1 g菌丝的剂量进行提取,采用N,O-双(三甲基硅烷基)乙酰胺和甲氧基胺盐酸盐在37℃和6 h条件下进行衍生化,可实现多种代谢物衍生产物收率和稳定性的最优化。灰葡萄孢菌丝代谢组的检测获得了210个峰,其中50种代谢物与NIST 2008的匹配度达到80%以上,主要为氨基酸类、醇类、有机酸类、糖类等代谢物,并通过标准品对部分代谢物进行了定性。典型的17种代谢物在1.0~100μg/m L范围内线性关系良好,相关系数均大于0.98,检出限为0.02~10.0 ng/m L,定量下限为0.1~34.0 ng/m L。方法精密度分析结果显示89.05%代谢物的相对标准偏差为0.01%~16.8%。所建立的方法适合于丝状真菌的代谢组检测,可为农业和医学领域开展微生物代谢组研究提供参考。

Application of GC-MS in Botrytis cinerea Metabolome Analysis

The pretreatment conditions,including extraction solvent,derivatization time and temperature,as well as internal standard were optimized for metabolome analysis of Botrytis cinerea (B.cinerea),an important pathogenic fungus that could induce a severe grey mold on plants.The results showed that,using salicin as the internal standard,a mixture of methanol and water (80 ∶ 20) with a dosage of 4.0 mL for 0.1 g of mycelium as extraction reagent,a silylation of N,O-bis(trimethylsilyl) trifluoroacetamide with methoxylamine for 6 h of derivation at 37 ℃ was the optimal for most kinds of metabolites in derivatives yield and stability.In B.cinerea hypha metabolome,210 peaks were detected by GC-MS,and the metabolome was identified as a group of metabolites including mainly amino acids,alcohols,organic acids,sugars and others.Among the metabolites,50 of them were identified by NIST 2008 with a match quality of 80％ or more,and part of them by standards.As a result,typical 17 metabolites obtained good linearities in the range of 1.0-100 μg/mL with correlation coefficients more than 0.98.The limits of detection and limits of quantitation were in the range of 0.02-10.0 ng/mL and 0.1-34.0 ng/mL,respectively.Investigation on the reproducibility of the optimal method suggested that the RSD for 89.05％ metabolites detected were in the range of 0.01％-16.8％.The good reproducibility implied that the method established was suitable for the metabolome detection of mycelial fungi,and could provide a good reference for microorganism metabolomics research in the field of agricultural and medical science.