Universal Characterization of Natural Product Libraries

有机分子在许多生物过程中发挥着核心作用，从昆虫使用的信号分子到治疗人类疾病的下一代药物的开发。这些自然产生的有机分子被称为天然产品。为了有效地研究这些化合物，科学家必须能够从生物样本提取物中通常发现的复杂混合物中分离出单独的分子，并识别这些单独的成分。这笔赠款的主要目标是为这一鉴定步骤开发新的分析化学工具，并使用这些新工具来探索细菌中自然存在的化合物的分布、来源和功能。*目前细菌世界中约有30,000种已知的天然产物，这使得对这些化合物的确定成为一项艰巨的分析挑战。这笔赠款旨在分四个步骤解决这一问题。首先，我们将创建一个所有已知细菌天然产物的通用数据库，并分析它们结构之间的异同，以产生一个描述这些天然化合物占据的化学景观的天然产品图谱。其次，我们将使用核磁共振波谱来定义我们内部天然产物库中存在的分子的所有诊断核磁共振信号。第三，我们将结合这些核磁共振数据和质谱学(MS)数据来确定描述库中每种化合物的唯一的一组核磁共振和MS特征。最后，我们将开发新的计算工具，利用这套核磁共振和MS特征将化学成分与天然产品图谱中的个别化合物联系起来，从而定义天然产品库中每一种提取物的完整组成。*除了解决这一突出的分析化学挑战之外，我们的实验室还对这些天然产品的生化来源感兴趣。为了解决这个问题，我们将使用同位素标记的前体来跟踪在细菌细胞生长过程中前体加入到天然产品中的情况。使用一组独特的标记前体与上述分析平台相结合，我们将开发一种方法，系统地确定给定细菌菌株的所有天然产物的生化来源，并创建计算工具，将这些分子与其来自全基因组序列的生产基因联系起来。*最后，我们将使用该分析平台来探索一类新的和未被研究的细菌的化学多样性，来自伯克霍尔德氏菌属。这项工作的目标是检验这些生物体产生的化学多样性，并检验这样一个假设，即新的微生物多样性可以帮助我们在未来的基础科学和药物开发应用中发现独特的天然产品。**

Organic molecules play a central role in many biological processes, from signaling molecules used by insects, to the development of the next generation of drugs for human diseases. These naturally occurring organic molecules are known as natural products'. To study these compounds effectively, scientists must be able to separate individual molecules from the complex mixtures typically found in extracts from biological samples, and identify each of these individual constituents. The main objectives of this grant are to develop new analytical chemistry tools for this identification step, and to use these new tools to explore the distributions, origins and functions of naturally occurring compounds in bacteria. ***Currently there are approximately 30,000 known natural products in the bacterial world, making confident identification of these compounds a daunting analytical challenge. This grant aims to address this issue in four steps. Firstly we will create a universal database of all known bacterial natural products, and analyze the similarities and differences between their structures to produce a natural products Atlas' that describes the chemical landscape occupied by these naturally occurring compounds. Secondly, we will use nuclear magnetic resonance (NMR) spectroscopy to define all the diagnostic NMR signals for molecules present in our in-house natural products library. Thirdly, we will use these NMR data in conjunction with mass spectrometric (MS) data to determine the unique set of NMR and MS features that describe each compound in the library. Finally, we will develop new computational tools that use this set of NMR and MS features to connect chemical constituents to individual compounds in the natural products Atlas, therefore defining the complete composition of every extract in the natural products library.***In addition to solving this outstanding analytical chemistry challenge, our laboratory is also interested in the biochemical origin of these natural products. To address this question we will use isotopically labeled precursors to track the incorporation of precursors into natural products during bacterial cell growth. Using a unique set of labeled precursors in conjunction with the analytical platform described above we will develop a method for the systematic determination of the biochemical origin of all natural products from a given bacteria strain, and create computational tools to link these molecules to their producing genes from whole genome sequences.***Finally, we will use the analytical platform to explore the chemical diversity of a new and understudied class of bacteria, from the genus Burkholderia. The goal of this work is to examine the chemical diversity produced by these organisms, and to test the hypothesis that novel microbial diversity can help us discover unique natural products with future basic science and drug development applications.**