Although the first bacterial genome sequence was published almost 20 years ago, there is still no generalizable method for automatically assigning natural products to their cognate biosynthetic gene clusters (BGCs). This thesis describes the development of a mass spectrometry-based parallel stable isotope labeling (SIL) platform, termed IsoAnalyst, which automatically associates metabolite stable isotope labeling patterns with BGC structure prediction in order to connect natural products to their cognate BGCs. The parallel SIL experiments were optimized for small scale and a custom tool written in Python was developed for the untargeted detection and interpretation of SIL labeling patterns. This approach was validated in the industrial production strains Saccharopolyspora erythraea and Amycolatopsis mediterranei demonstrating that the compounds erythromycin A and rifamycin SV respectively, could be associated with the proper BGCs based on the distribution of isotopomer labeling patterns. The method was further validated by connecting known biosynthetic intermediates of these compounds to their associated BGCs and the identification of various siderophores through a combination of SIL labeling patterns and MS/MS fragmentation data. Extension to environmental organisms using a sequenced Micromonospora sp. from our Actinobacterial isolate library led to the discovery of lobosamide D, a new member of the lobosamide family of natural products, and an update to the lobosamide BGC to include relevant tailoring enzymes. This discovery illustrates the power of the IsoAnalyst platform for identifying new compounds, linking molecules to BGCs, and generating new knowledge about biosynthesis
