Mining fragmented microbial DNA identifies candidates for anticancer testing
Researchers have developed a practical strategy for recovering biosynthetic information from fragmented metagenomic data. Through this work, the researchers identified and prioritized promising natural-product candidates with potential antibacterial or anticancer activity.
Researchers have developed a new strategy for identifying promising natural-product candidates with potential anticancer activity by analyzing fragmented microbial DNA. The study, published in Microbiology Spectrum, involved using known biosynthetic gene clusters (BGCs) as reference maps to reconstruct missing pathway information from metagenomic data.
By chemically synthesizing and testing selected predicted compounds, the researchers found that fragmented metagenomic data can contain valuable biosynthetic information that would otherwise be missed. The approach prioritizes computational mining of metagenomic data with experimental validation, identifying compounds D and E as showing notable cytotoxic activity in seven cancer cell lines.
This method offers a route for turning incomplete or fragmented biosynthetic gene clusters into testable natural-product hypotheses.
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