寻找常见食源性致病菌间特征性代谢产物，是研发食品安全快速高效监控技术的基础。本文直接利用常见食源性致病菌发酵液冻干，经硅烷化试剂衍生，并采用气相色谱-质谱技术（GC-MS）对代谢产物进行分析，同时进行NIST11谱图库检索并分类，并对数据进行热图和主成分（PCA）分析。研究发现，发酵液中有大量有机酸、醇类和胺类等物质产生，且菌种间各代谢产物种类和相对含量差异显著；同时各菌间含有丰富的特有代谢产物，其中部分特有代谢产物在其他菌株中未见报道。通过热图和PCA分析各菌株胞外代谢轮廓可知，24 h时各菌株间能够明显区分，同时去除糖类和氨基酸后，PCA区分鉴定效果明显提高，尤其在24h时最好。研究表明，胞外代谢轮廓分析可以用于寻找常见食源性致病菌生物标志物和菌种区分鉴定，同时部分菌种间特有的代谢产物有望成为常见食源性致病菌潜在生物标志物。

This study aims to determine the characteristic metabolites of common food-borne pathogens and develop fast and efficient techniques for food safety monitoring. In this study, the zymotic fluid of food-borne pathogens was freeze-dried and derivatized with N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA), followed by analysis using gas chromatography mass spectrometry (GC-MS). An NIST11 database search and classification were also performed, and the acquired data were analyzed using heatmapping and principal component analysis (PCA). The results showed that there were a large number of substances, such as organic acids, alcohols, and amines that were formed in the culture broth. Significant differences were observed between different bacterial species based on the types and relative metabolic contents. Many specific metabolites for each bacterial species were found, some of twhich have never been reported in other strains. The extracellular metabolic profiles of all bacteria were analyzed by heatmapping and PCA, and the results showed that the strains could be differentiated at 24 h; the differentiation effect of PCA was significantly enhanced after the removal of amino acid and sugars, and the optimal effect was found at 24 h. Our results show that extracellular metabolic profile analysis can be used to determine the biomarkers of food-borne pathogenic bacteria and distinguish between bacterial species. Further, some of the characteristic metabolites may be potential biomarkers of common food-borne pathogens.

国家自然科学基金项目（U1031003， 31371780）；粤港关键领域重点突破项目（2011A011303001）