Abstract

ABSTRACTThe success of natural product-based drug discovery is predicated on having chemical collections that offer broad coverage of metabolite diversity. We propose a simple set of tools combining genetic barcoding and metabolomics to help investigators 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 strategies. 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 transcribed spacer (ITS)-based sequence information (i.e., establishing gene-based clades) with data from liquid chromatography-mass spectrometry (i.e., generating feature accumulation curves) offers a useful route to obtaining actionable insights into chemical diversity coverage trends in a natural product library. It is anticipated that these outcomes 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 rationally 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) diversity 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.

Highlights

  • The success of natural product-based drug discovery is predicated on having chemical collections that offer broad coverage of metabolite diversity

  • The Alternaria isolates used in this study were obtained through the University of Oklahoma, Citizen Science Soil Collection Program [38, 39], which to date has received 9,670 soil samples from across the United States, yielding 78,581 fungal isolates identified by single-read internal transcribed spacer (ITS) sequencing data

  • A query performed on the ITS barcode data yielded an initial set of 219 candidate Alternaria isolates, which was refined to a subset of 198 samples having .90% ITS sequence similarity [40,41,42] to Alternaria type strain data available in GenBank and defined by Woudenberg et al [31]

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Summary

Introduction

The success of natural product-based drug discovery is predicated on having chemical collections that offer broad coverage of metabolite diversity. To monitor and better understand how feature diversity could be used to make informed decisions about constructing natural product libraries, feature accumulation curves were constructed from the metabolomics data (Fig. 4A).

Results
Conclusion
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