Capturing evolved small molecule natural product chemical space

天然小化学品，天然产品，具有广泛的活性，具有重要的工业和药用价值。在它们的自然环境中，这些分子已经进化为细胞之间的一种通信形式，并协助产生它们的生物体的生命。它们的进化状态体现在对生物分子靶点的选择性和对细胞的影响上。导致不同种类的天然产物（如萜烯、聚酮、非核糖体肽）的生物合成机制现在得到了很好的认识，它们的代码已经被破解，因此遗传指令和最终产物小分子之间的联系得到了认识。天然产物来源的基因组测序的出现打开了大量新的天然产物的缓存，等待发现和评估其工业和制药用途。该研究计划的目的是设计和实施强大的新工具和策略，以实现基因组信息与小分子天然产物的快速连接。拟议的研究计划将寻求制定强有力的策略，以选择性地识别和捕获这些进化的天然产物，使其成为现实进行测试。已证实的抗生素生产者和许多研究不足的微生物的基因组测序已经产生了对其代谢能力的深刻见解。随着下一代测序方法对微生物基因组测序的不断推进，这些基因组设想的微生物天然产物，或可称为“未知已知”天然产物的队列正在增加。为了有选择地识别这些未知的已知分子，而不首先重新研究（重新分离）已知的天然产物，将需要尖端的策略来将它们定位在复杂的代谢组中。技术需要足够敏感，以便在它们以微量存在时识别它们，并推动这些未知物质的生产，随着它们以消失的数量出现。该计划将创建强大的新平台技术，通过将多种形式的“组学”信息与化学信息学和生物信息学数据处理策略结合现代分析仪器，选择性地鉴定聚酮和非核糖体肽天然产物。该计划将在目前nserc支持的计划的基础上建立，该计划已经在开发天然产物的信息搜索（iSNAP）方面产生了几项创新工作。重要的是，这次更新将集中在这些技术的部署上，以选择性地分离新的生物活性聚酮和非核糖体肽，考虑到它们被发现的化学生态和系统。我希望提出这样的假设，即在生物活性引导下发现抗生素的早期黄金时代，只有一小部分抗生素是自然进化出来的。我的实验室将询问导致早期抗生素发现的开创性发现的早期生物体（已知抗生素的生产者），但不是随机评估这些生物体，我们将首先使用我的实验室新的CFI LOF基础设施（基因组测序仪和质谱仪）支持的仪器获得它们的基因组序列，然后利用基因组序列来预测和选择性地挖掘已知未知的天然产物。一旦分离出这些分子，我们将查询它们的生物活性，特别是这些未知的已知分子是否对耐药致病菌及其集体活性（协同作用）表现出有效的抗菌活性。

Natural small chemicals, natural products, exhibit a wide spectrum of activity with significant industrial and medicinal value. Within their natural context these molecules have been evolved as a form of communication between cells and to assist the life of the organisms that produce them. Their evolved status is evident in the selectivity to their bio-molecular targets and demonstrated impact on cells. Biosynthetic machinery leading to natural products of different categories (e.g. terpenes, polyketides, nonribosomal peptides) are now well appreciated and their codes have been cracked such that the connection between genetic instruction and end product small molecules is appreciated. The advent of genomic sequencing of natural product sources have opened up a large cache of new natural products that await discovery and evaluation for their industrial and pharmaceutical use. The purpose of the proposed research program will be to design and implement powerful new tools and strategies to enable the rapid connection of genomic information to small molecule natural products. The propose research program will seek to develop powerful strategies to selectively identify and capture these evolved natural products a reality for testing. Genomic sequencing of proven antibiotic producers and numerous poorly studied microorganisms has produced a deep view of their metabolic capability. These genomically-envisioned cohort of microbial natural products, or what can be referred to as ‘unknown known’ natural products, are increasing with the continued advance of microbial genome sequencing with next-generation sequencing approaches. To selectively identify these unknown known molecules, without first re-investigating (re-isolating) the known natural products will demand cutting-edge strategies to target them within the complex metabolomes in which they are found. Technologies will need to be sensitive enough to identify them when they are present in trace amounts and drive the production of these unknown agents with they are revealed in vanishing quantities. The proposed program will create powerful new platform technologies to selectively identify polyketide and nonribosomal peptide natural products by integrating numerous forms of ‘omic’ information with chemoinformatic and bioinformatic data processing strategies in conjunction with modern analytical instruments. The program will build significantly from the current NSERC-supported program that has produced several innovative works in developing an informatic search for natural products (iSNAP). Importantly this renewal will focus on the deployment of these technologies to selectively isolate new bioactive polyketide and nonribosomal peptides that considers the chemical ecology and systems in which they are found. I wish to advance the hypothesis, that the previous early golden age of antibiotic discovery driven by bioactivity guided activities revealed only a small fraction of the antibiotics that have been naturally evolved. My laboratory will interrogate the early organisms (producers of known antibiotics) that lead to the seminal discoveries in early antibiotic discovery, but instead of randomly assessing these organisms we will first obtain genomic sequences of them using instrumentation supported by my laboratories new CFI LOF infrastructure (genomic sequencers and mass spectrometers) and then leverage that genomic sequence to predict and selectively mine for known unknown natural products. Once these molecules are isolated we will then query their biological activities and specifically whether these unknown known molecules exhibit potent antimicrobial activities to drug resistant pathogenic bacteria and their collective activities (synergies).