Integrated Omics Technologies for Natural Products Discovery

自然界中的许多相互作用都是由化学控制的。例如，细菌利用小分子进行交流、隔离营养物质、占领领土和保护自己免受攻击。了解这些“天然产物”的分布和作用对我们理解全球微生物生态至关重要。这反过来又对社会的许多领域产生影响，包括农业、生态、人类健康和生物安全。尽管化学在这些领域很重要，但我们仍然无法回答许多关于微生物天然产物的基本问题。例如，在一个单一的培养条件下，识别一个有机体产生的所有分子仍然是非常困难的。如果我们希望识别微生物文库中产生的所有分子，并确定哪些生物有能力制造哪些产品，那么这一挑战就会被放大。该提案旨在创造新的工具来回答天然产物科学中的三个基本问题：“这种混合物中有多少化合物？”、“这些化合物的结构是什么？”以及“这些化合物是如何在自然界中产生的？”要回答第一个问题（这个混合物中有多少种化合物？）’)我们将整合我的实验室最近开发的核磁共振（NMR）分析平台和质谱（MS）的化学分析数据。这个新的混合工具将结合有机化学中两种最强大的分析方法（核磁共振和质谱）的信息，创建一个能够描述复杂混合物的化学景观的单一平台。要回答第二个问题(“这些化合物的结构是什么？”’)，我们将利用我们最近创建的微生物化学数据库——天然产物图谱（Natural Products Atlas）中的信息，创建新的算法，从质谱数据中直接预测化合物的类别。通过发展对自然界中化学类分布的全球理解，我们可以预测大型细菌文库中的结构多样性。要回答最后一个问题（“这些化合物是如何在自然界中产生的？”）’)，我们将使用基因组测序和平行稳定同位素标记相结合的方法，将天然产物与负责其产生的基因（生物合成基因簇）进行匹配。通过对100个测序菌株的大型文库进行分析，我们可以开始评估自然界的化学能力，并了解自然界化学多样性的范围和局限性。这项工作的核心成果将是一套新的工具，旨在使人们更详细地了解自然界的化学。这对加拿大未来有潜在的好处，包括发现农作物疾病的新疗法，更清楚地了解我们自己的微生物组如何影响人类健康，甚至可能发现下一代疗法。

Many interactions in the natural world are governed by chemistry. For example, bacteria use small molecules to communicate, sequester nutrients, take over territory, and defend themselves from attack. Understanding the distribution and roles of these 'natural products' is essential to our understanding of global microbial ecology. This in turn has implications for many areas of society including agriculture, ecology, human health and biosecurity. Despite the importance of chemistry in these areas, we are still poorly equipped to answer many basic questions about microbial natural products. For example, it remains very difficult to identify all of the molecules produced by a single organism under a single culture condition. This challenge is amplified if we wish to identify all of the molecules made by libraries of microorganisms, and to determine which organisms have the capability of making which products. This proposal aims to create new tools to answer three basic questions in natural products science: 'how many compounds are in this mixture?', 'what are the structures of these compounds?', and 'how are these compounds made in Nature?'. To answer the first question ('how many compounds are in this mixture?') we will integrate a recently developed nuclear magnetic resonance (NMR) analysis platform from my laboratory with chemical profiling data from mass spectrometry (MS). This new hybrid tool will combine information from two of the most powerful profiling methods in organic chemistry (NMR and MS) to create a single platform capable of describing the chemical landscape of complex mixtures of products. To answer the second question ('what are the structures of these compounds?') we will use the information in our recently created database of microbial chemistry, the Natural Products Atlas, to create new algorithms for the direct prediction of compound class identity from mass spectrometry data. By developing a global understanding of the distribution of chemical classes in the natural world we can predict structural diversity within large bacterial libraries. To answer the final question ('how are these compounds made in Nature?') we will use a combination of genome sequencing and parallel stable isotope labeling to match natural products to the genes responsible for their production (biosynthetic gene clusters). By performing this analysis on a large library of 100 sequenced bacterial strains, we can begin to evaluate the chemical capacity of the natural world, and to understand the scope and limitations of chemical diversity in Nature. The central outcome of this work will be a suite of new tools designed to enable a more detailed understanding of the chemistry of the natural world. This has potential future benefit to Canada in the discovery of new treatments for crop diseases, development of a clearer understanding of how our own microbiomes influence human health, end even perhaps the discovery of the next generation of therapeutics.