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Discovery of the Tyrobetaine Natural Products and Their Biosynthetic Gene Cluster via Metabologenomics

机译:酪氨酸甜菜碱天然产物及其生物合成基因簇的发现通过代谢组学

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摘要

Natural products (NPs) are a rich source of medicines, but traditional discovery methods are often unsuccessful due to high rates of rediscovery. Genetic approaches for NP discovery are promising, but progress has been slow due to the difficulty of identifying unique biosynthetic gene clusters (BGCs) and poor gene expression. We previously developed the metabologenomics method, which combines genomic and metabolomic data to discover new NPs and their BGCs. Here, we utilize metabologenomics in combination with molecular networking to discover a novel class of NPs, the tyrobetaines: nonribosomal peptides with an unusual trimethylammonium tyrosine residue. The BGC for this unusual class of compounds was identified using metabologenomics and computational structure prediction data. Heterologous expression confirmed the BGC and suggests an unusual mechanism for trimethylammonium formation. Overall, the discovery of the tyrobetaines shows the great potential of metabologenomics combined with molecular networking and computational structure prediction for identifying interesting biosynthetic reactions and novel NPs.
机译:天然产物(NPs)是丰富的药物来源,但是由于发现率很高,传统的发现方法通常不成功。用于NP发现的遗传方法是有前途的,但是由于难以识别独特的生物合成基因簇(BGC)和不良的基因表达而进展缓慢。我们之前开发了代谢组学方法,该方法结合了基因组学和代谢组学数据,以发现新的NP及其BGC。在这里,我们利用代谢组学与分子网络相结合的方法来发现一类新型的NP,即酪氨酸甜菜碱:具有不常见的三甲基铵酪氨酸残基的非核糖体肽。使用代谢组学和计算结构预测数据确定了此异常类化合物的BGC。异源表达证实了BGC,并暗示了三甲基铵形成的异常机制。总体而言,酪氨酸甜菜碱的发现显示出代谢组学与分子网络和计算结构预测相结合的巨大潜力,可用于识别有趣的生物合成反应和新型NP。

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