Anderson Victoria M, Wendt Karen L, Najar Fares Z, McCall Laura-Isobel, Cichewicz Robert H
Natural Products Discovery Group, University of Oklahomagrid.266900.b, Norman, Oklahoma, USA.
Institute for Natural Products Applications and Research Technologies, University of Oklahomagrid.266900.b, Norman, Oklahoma, USA.
mSystems. 2021 Oct 26;6(5):e0064421. doi: 10.1128/mSystems.00644-21.
The 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 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 , 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 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 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. 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.
基于天然产物的药物发现的成功取决于拥有能够广泛涵盖代谢物多样性的化学文库。我们提出了一套简单的工具,将基因条形码技术和代谢组学相结合,以帮助研究人员构建旨在实现预定化学覆盖水平的天然产物文库。结果发现,这些工具有助于识别分类群中被忽视的化学多样性区域,这对于重新调整采集策略可能很有用。我们使用了从基于公民科学的土壤采集样本中鉴定出的真菌分离株,来证明这些工具在评估天然产物文库中的化学多样性以及进行预测性测量方面的应用。在这些分离株中,发现不同的亚分支包含不等量的化学多样性。还确定了数量惊人少的分离株(195个分离株)足以提供数据集中近99%的化学特征。然而,必须在这样的背景下考虑这一结果,即17.9%的化学特征出现在单个分离株中,这表明像这样的真菌可能正在积极探索自然界代谢景观的持续过程中。我们的结果表明,将获取基于内转录间隔区(ITS)序列信息(即建立基于基因的分支)的适度投入与液相色谱 - 质谱数据(即生成特征积累曲线)相结合,为获得关于天然产物文库中化学多样性覆盖趋势的可操作见解提供了一条有用途径。预计这些结果可用于改善获取作为基于天然产物的药物发现基石的生物活性分子的机会。天然产物药物发现工作依赖于生物体文库来获取多样的化合物库。合理最大化化学多样性而不是依赖偶然性的可操作策略,可以为这些工作增添价值。易于实施的生物学(即ITS序列分析)和化学(即基于质谱的特征和骨架测量)多样性评估工具可用于实时监测和调整文库开发策略。总之,代谢组学驱动的技术和简单的基于基因的样本条形码方法在构建化学多样的天然产物文库方面具有广泛的适用性。