Institute of Biology, Leiden University, the Netherlands.
Verily Life Sciences, South San Francisco, CA, United States of America.
PLoS Biol. 2020 Dec 22;18(12):e3001026. doi: 10.1371/journal.pbio.3001026. eCollection 2020 Dec.
Microbial natural products constitute a wide variety of chemical compounds, many which can have antibiotic, antiviral, or anticancer properties that make them interesting for clinical purposes. Natural product classes include polyketides (PKs), nonribosomal peptides (NRPs), and ribosomally synthesized and post-translationally modified peptides (RiPPs). While variants of biosynthetic gene clusters (BGCs) for known classes of natural products are easy to identify in genome sequences, BGCs for new compound classes escape attention. In particular, evidence is accumulating that for RiPPs, subclasses known thus far may only represent the tip of an iceberg. Here, we present decRiPPter (Data-driven Exploratory Class-independent RiPP TrackER), a RiPP genome mining algorithm aimed at the discovery of novel RiPP classes. DecRiPPter combines a Support Vector Machine (SVM) that identifies candidate RiPP precursors with pan-genomic analyses to identify which of these are encoded within operon-like structures that are part of the accessory genome of a genus. Subsequently, it prioritizes such regions based on the presence of new enzymology and based on patterns of gene cluster and precursor peptide conservation across species. We then applied decRiPPter to mine 1,295 Streptomyces genomes, which led to the identification of 42 new candidate RiPP families that could not be found by existing programs. One of these was studied further and elucidated as a representative of a novel subfamily of lanthipeptides, which we designate class V. The 2D structure of the new RiPP, which we name pristinin A3 (1), was solved using nuclear magnetic resonance (NMR), tandem mass spectrometry (MS/MS) data, and chemical labeling. Two previously unidentified modifying enzymes are proposed to create the hallmark lanthionine bridges. Taken together, our work highlights how novel natural product families can be discovered by methods going beyond sequence similarity searches to integrate multiple pathway discovery criteria.
微生物天然产物包含了多种多样的化合物，其中许多具有抗生素、抗病毒或抗癌特性，因此在临床应用方面具有重要意义。天然产物的类别包括聚酮化合物（PKs）、非核糖体肽（NRPs）和核糖体合成及翻译后修饰肽（RiPPs）。虽然已知天然产物类别的生物合成基因簇（BGCs）变体在基因组序列中很容易识别，但新化合物类别的 BGCs 则容易被忽视。特别是，越来越多的证据表明，对于 RiPPs 而言，迄今为止已知的亚类可能只是冰山一角。在这里，我们提出了 decRiPPter（基于数据的探索性独立 RiPP 追踪器），这是一种用于发现新型 RiPP 类别的 RiPP 基因组挖掘算法。decRiPPter 将支持向量机（SVM）与泛基因组分析相结合，用于识别候选 RiPP 前体，并确定这些前体是否编码在与属的辅助基因组相关的操纵子样结构中。随后，它根据新酶学的存在以及跨物种的基因簇和前体肽保守性模式对这些区域进行优先级排序。然后，我们将 decRiPPter 应用于挖掘 1,295 个链霉菌基因组，从中鉴定出 42 种无法通过现有程序找到的新型候选 RiPP 家族。其中一个家族被进一步研究，并阐明为一种新型的硫肽亚家族，我们将其指定为 V 类。使用核磁共振（NMR）、串联质谱（MS/MS）数据和化学标记解决了新 RiPP 的 2D 结构，我们将其命名为 pristinin A3（1）。提出了两个以前未鉴定的修饰酶来生成标志性的硫醚键。总之，我们的工作强调了如何通过超越序列相似性搜索的方法，整合多种途径发现标准来发现新型天然产物家族。
