Genome Mining the Full Diversity of the Actinomycete Biosynthetic Universe for Neomorph Antibiotic Discovery

摘要 为了对抗多重耐药细菌感染，具有新作用机制的新型抗生素 是迫切需要的。新天然产物的基因组挖掘正在迅速取代传统方法 到抗生素的发现。Warp Drive Bio已经对来自不同地区的135，000多个放线菌菌株基因组进行了测序， 我们的专有基因组数据库包含约3，500，000个次级基因组， 代谢物基因簇。重要的是，在我们的数据库中确定的聚类家族中，有75%尚未被确定。 在文献中有报道。我们的基于微生物基因组学的方法是创新的，因为它提供了一个 这是一个前所未有的机会，可以发现具有新作用机制（MOAs）的全新抗生素。 这个项目的重点将是识别、表达和测试编码新类别的生物合成基因簇 抗生素与新型MOA对抗当前和未来的耐药病原体，通过梳理我们庞大的 基因组学资源和创新的生物信息学搜索与我们的验证基因组药物平台， 天然产物的发现首先，我们将利用我们广泛的、互补的基因组资源， 并克隆10个候选新变体抗生素簇。我们把新颖的生物合成簇称为 “neomorphs”，我们已经建立了一个生物信息学分析管道， 在基因和生物合成水平上评估新奇的工具。然后我们将利用我们的微生物基因组 数据库，通过搜索自身抗性基因来预测哪些新变体簇具有抗生素活性 在新形态群中。细菌利用各种自我抗性机制来保护免受 它们正在积极生产抗生素，并且可以利用基因组信息来利用这种特性。我们 综合生物信息学分析，我们将提出10个候选新形态抗生素簇用于表达， 试验.一个经过验证的合成生物学技术组合将被部署用于重构生物合成 簇以增强不表达的簇或以非常低的水平表达的簇的表达。 水平，以增加化合物的产量。最后，我们开发了一种高通量发酵方法， 生物测定和质谱基础设施来分析和鉴定neomorphs。因此，通过梳理 创新的基因组搜索新的生物合成集群与嵌入式抗性基因，与我们的集成 基因到化合物平台，我们将确定，工程师，并筛选候选新形态抗生素，以解决 对具有新型MOA的新型抗菌剂的临床需求不断增长。

ABSTRACT To combat multidrug-resistant bacterial infections, novel classes of antibiotics with new mechanisms of action are desperately required. Genome mining for novel natural products is quickly replacing traditional approaches to antibiotic discovery. Warp Drive Bio has sequenced over 135,000 actinomycete strain genomes from diverse sources worldwide, and our proprietary genomic database contains approximately ~3,500,000 secondary metabolite gene clusters. Importantly ~75% of cluster families identified in our database have yet to be reported in the literature. Our vast microbial genomics-based approach is innovative because it provides an unprecedented opportunity to discover entirely novel antibiotics with new mechanisms of action (MOAs). The focus of this project will be to identify, express, and test biosynthetic gene clusters encoding new classes of antibiotics with novel MOAs to combat current and future drug-resistant pathogens, by combing our vast genomics resources and innovative bioinformatics search with our validated genomes-to-drugs platform for natural products discovery. First, we will harness our extensive, complementary genomic resources to identify and clone 10 candidate neomorph antibiotic clusters. We term biosynthetic clusters that are novel as “neomorphs,” and we have constructed a bioinformatic analysis pipeline of phylogenomic and chemoinformatic tools to assess novelty at the genetic and biosynthetic levels. We then will utilize our microbial genomic database to predict which neomorph clusters possess antibiotic activity, by searching for self-resistance genes within the neomorph cluster. Bacteria utilize a variety of self-resistance mechanisms to protect against the antibiotics they are actively producing, and this property can be exploited using genomic information. Our integrated bioinformatic analysis we will advance 10 candidate neomorph antibiotic clusters for expression and testing. A validated portfolio of synthetic biology techniques will be deployed for refactoring biosynthetic clusters to enhance the expression of clusters that are not expressed, or which are expressed at very low levels, to increase compound production. Finally we have developed a high throughput fermentation process, bioassay, and mass spectrometric infrastructure to analyze and identify neomorphs. Thus, by combing an innovative genomic search of novel biosynthetic clusters with embedded resistance genes, with our integrated genes-to-compound platform, we will identify, engineer, and screen candidate neomorph antibiotics to address the growing clinical need for new antibacterial agents with novel MOAs.