基于GC-MS的灰葡萄孢菌代谢组分析

摘要

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.%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 mL/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6h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 ～ 100 μg/mL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/mL,定量下限为0.1～ 34.0 ng/mL.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.