Costa Carina Pedrosa, Gonçalves Silva Diogo, Rudnitskaya Alisa, Almeida Adelaide, Rocha Sílvia M
Department of Biology, University of Aveiro, Aveiro, Portugal.
Department of Chemistry &QOPNA, University of Aveiro, Aveiro, Portugal.
Sci Rep. 2016 Jun 6;6:27441. doi: 10.1038/srep27441.
An in-depth exploration of the headspace content of Aspergillus niger cultures was performed upon different growth conditions, using a methodology based on advanced multidimensional gas chromatography. This volatile fraction comprises 428 putatively identified compounds distributed over several chemical families, being the major ones hydrocarbons, alcohols, esters, ketones and aldehydes. These metabolites may be related with different metabolic pathways, such as amino acid metabolism, biosynthesis and metabolism of fatty acids, degradation of aromatic compounds, mono and sesquiterpenoid synthesis and carotenoid cleavage. The A. niger molecular biomarkers pattern was established, comprising the 44 metabolites present in all studied conditions. This pattern was successfully used to distinguish A. niger from other fungi (Candida albicans and Penicillium chrysogenum) with 3 days of growth by using Partial Least Squares-Discriminant Analysis (PLS-DA). In addition, PLS-DA-Variable Importance in Projection was applied to highlight the metabolites playing major roles in fungi distinction; decreasing the initial dataset to only 16 metabolites. The data pre-processing time was substantially reduced, and an improvement of quality-of-fit value was achieved. This study goes a step further on A. niger metabolome construction and A. niger future detection may be proposed based on this molecular biomarkers pattern.
采用基于先进多维气相色谱的方法，在不同生长条件下对黑曲霉培养物的顶空成分进行了深入探索。该挥发性成分包含428种推定鉴定的化合物，分布在几个化学类别中，主要为烃类、醇类、酯类、酮类和醛类。这些代谢物可能与不同的代谢途径有关，如氨基酸代谢、脂肪酸的生物合成和代谢、芳香化合物的降解、单萜和倍半萜的合成以及类胡萝卜素的裂解。建立了黑曲霉分子生物标志物模式，包括在所有研究条件下均存在的44种代谢物。通过偏最小二乘判别分析（PLS-DA），该模式成功用于在3天生长时将黑曲霉与其他真菌（白色念珠菌和产黄青霉）区分开来。此外，应用投影中变量重要性的PLS-DA来突出在真菌区分中起主要作用的代谢物；将初始数据集减少到仅16种代谢物。数据预处理时间大幅减少，拟合优度值得到提高。本研究在黑曲霉代谢组构建方面更进一步，基于此分子生物标志物模式可提出黑曲霉未来的检测方法。
