Building Natural Product Libraries Using Quantitative Clade-Based and Chemical Clustering Strategies

The success of natural product-based drug discovery is predicated on hav -ing chemical collections that offer broad coverage of metabolite diversity. We propose a simple set of tools combining genetic barcoding and metabolomics to help investiga-tors build natural product libraries aimed at achieving predetermined levels of chemical coverage. It was found that such tools aided in identifying overlooked pockets of chemical diversity within taxa, which could be useful for refocusing collection strat-egies. We have used fungal isolates identified as Alternaria from a citizen-science-based soil collection to demonstrate the application of these tools for assessing and carrying out predictive measurements of chemical diversity in a natural product collection. Within Alternaria, different subclades were found to contain nonequivalent levels of chemical diversity. It was also determined that a surprisingly modest number of isolates (195 isolates) was sufficient to afford nearly 99% of Alternaria chemical features in the data set. However, this result must be considered in the context that 17.9% of chemical features appeared in single isolates, suggesting that fungi like Alternaria might be engaged in an ongoing process of actively exploring nature's metabolic landscape. Our results demonstrate that combining modest investments in securing internal tran-scribed spacer (ITS)-based sequence information (i.e., establishing gene-based clades) with data from liquid chromatography-mass spectrometry (i.e., generating feature accu-mulation curves) offers a useful route to obtaining actionable insights into chemical di-versity coverage trends in a natural product library. It is anticipated that these out-comes could be used to improve opportunities for accessing bioactive molecules that serve as the cornerstone of natural product-based drug discovery. IMPORTANCE Natural product drug discovery efforts rely on libraries of organisms to provide access to diverse pools of compounds. Actionable strategies to ration-ally maximize chemical diversity, rather than relying on serendipity, can add value to such efforts. Readily implementable biological (i.e., ITS sequence analysis) and chemical (i.e., mass spectrometry-based feature and scaffold measurements) diver-sity assessment tools can be employed to monitor and adjust library development tactics in real time. In summary, metabolomics-driven technologies and simple gene-based specimen barcoding approaches have broad applicability to building chemically diverse natural product libraries.