Nucleus of Bioassays, Biosynthesis, and Ecophysiology of Natural Products (NuBBE), Institute of Chemistry, São Paulo State University, Araraquara, SP, Brazil.
Zimmermann Group, Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
Metabolomics. 2022 May 24;18(6):33. doi: 10.1007/s11306-022-01896-6.
In microbial metabolomics, the use of multivariate data analysis (MDVA) has not been comprehensively explored regarding the different techniques available and the information that each gives about the metabolome. To overcome these limitations, here we show the use of Fusarium oxysporum cultured in the presence of exogenous alkaloids as a model system to demonstrate a comprehensive strategy for metabolic profiling.
F. oxysporum was harvested on different days of incubation after alkaloidal addition, and the chemical profiles were compared using LC-MS data and MDVA. We show significant innovation to evaluate the chemical production of microbes during their life cycle by utilizing the full capabilities of Partial Least Square (PLS) with microbial-specific modeling that considers incubation days, media culture availability, and growth rate in solid media.
Results showed that the treatment of the Y-data and the use of both PLS regression and discrimination (PLSr and PLS-DA) inferred complemental chemical information. PLSr revealed the metabolites that are produced/consumed during fungal growth, whereas PLS-DA focused on metabolites that are only consumed/produced at a specific period. Both regression and classificatory analysis were equally important to identify compounds that are regulated and/or selectively produced as a response to the presence of the alkaloids. Lastly, we report the annotation of analogs from the piperidine alkaloids biotransformed by F. oxysporum as a defense response to the toxic plant metabolites. These molecules do not show the antimicrobial potential of their precursors in the fungal extracts and were rapidly produced and consumed within 4 days of microbial growth.
在微生物代谢组学中，尽管多元数据分析（MDVA）已经得到了广泛应用，但针对不同的可用技术以及每种技术对代谢组提供的信息，其应用仍有待进一步探索。为了克服这些局限性，我们以存在外源生物碱的尖孢镰刀菌（Fusarium oxysporum）培养物作为模型系统，展示了一种全面的代谢轮廓分析策略。
在添加生物碱后，在不同的培养天数收获尖孢镰刀菌，并使用 LC-MS 数据和 MDVA 对化学图谱进行比较。我们展示了一项重大创新，即通过利用偏最小二乘（PLS）的全部功能，结合微生物特异性建模，考虑培养天数、培养基可用性以及固体培养基中的生长速率，来评估微生物在其生命周期中的化学产物生成情况。
结果表明，处理 Y 数据并同时使用 PLS 回归和判别（PLSr 和 PLS-DA）推断互补的化学信息。PLSr 揭示了真菌生长过程中产生/消耗的代谢物，而 PLS-DA 则侧重于在特定时期内仅消耗/产生的代谢物。回归和分类分析对于识别受调控的化合物以及作为对生物碱存在的响应而选择性产生的化合物都同样重要。最后，我们报告了由尖孢镰刀菌生物转化的哌啶生物碱类似物的注释，这是作为对植物毒性代谢物的防御反应。这些分子在真菌提取物中没有表现出其前体的抗菌潜力，并且在微生物生长的 4 天内迅速产生和消耗。
