Bioactivity-driven fungal metabologenomics identifies antiproliferative stemphone analogs and their biosynthetic gene cluster

生物活性驱动的真菌代谢基因组学识别抗增殖干细胞类似物及其生物合成基因簇

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作者:Navid J Ayon, Cody E Earp, Raveena Gupta, Fatma A Butun, Ashley E Clements, Alexa G Lee, David Dainko, Matthew T Robey, Manead Khin, Lina Mardiana, Alexandra Longcake, Manuel Rangel-Grimaldo, Michael J Hall, Michael R Probert, Joanna E Burdette, Nancy P Keller, Huzefa A Raja, Nicholas H Oberlies, Ne

Conclusions

This work demonstrates how the incorporation of biochemometrics as a third dimension into the metabologenomics workflow can identify bioactive metabolites and link them to their biosynthetic machinery.

Methods

The 110 fungi from our metabologenomics study were tested against multiple cancer cell lines to identify which strains produced antiproliferative natural products. Three strains were selected for further study, fractionated using flash chromatography, and subjected to an additional round of bioactivity testing and mass spectral analysis. Data were overlaid using biochemometrics analysis to predict active constituents early in the fractionation process following which their biosynthetic pathways were identified using metabologenomics.

Results

We isolated three new-to-nature stemphone analogs, 19-acetylstemphones G (1), B (2) and E (3), that demonstrated antiproliferative activity ranging from 3 to 5 µM against human melanoma (MDA-MB-435) and ovarian cancer (OVACR3) cells. We proposed a rational biosynthetic pathway for these compounds, highlighting the potential of using bioactivity as a filter for the analysis of integrated-Omics datasets. Conclusions: This work demonstrates how the incorporation of biochemometrics as a third dimension into the metabologenomics workflow can identify bioactive metabolites and link them to their biosynthetic machinery.

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