Structural investigation of ribosomally synthesized natural products by hypothetical structure enumeration and evaluation using tandem MS

Ribosomally synthesized and posttranslationally modified peptides (RiPPs) are a growing class of natural products that are found in all domains of life. These compounds possess vast structural diversity and have a wide range of biological activities, promising a fertile ground for exploring novel natural products. One challenging aspect of RiPP research is the difficulty of structure determination due to their architectural complexity. We here describe a method for automated structural characterization of RiPPs by tandem mass spectrometry. This method is based on the combined analysis of multiple mass spectra and evaluation of a collection of hypothetical structures predicted based on the biosynthetic gene cluster and molecular weight. We show that this method is effective in structural characterization of complex RiPPs, including lanthipeptides, glycopeptides, and azole-containing peptides. Using this method, we have determined the structure of a previously structurally uncharacterized lanthipeptide, prochlorosin 1.2, and investigated the order of the posttranslational modifications in three biosynthetic systems.Ribosomally synthesized and posttranslationally modified peptides (RiPPs) are a major class of natural products as revealed by the genome-sequencing efforts of the past decade (1). RiPPs are biosynthesized from genetically encoded and ribosomally produced precursor peptides, which typically consist of a core peptide that is transformed to the final product and an N-terminal extension called the leader peptide that is usually important for recognition by the posttranslational modification (PTM) enzymes (1). Because of the highly diverse PTMs, these compounds possess vast structural diversity and have a wide range of biological activities, thus representing a fertile ground for exploration. Furthermore, the ribosomal origin of RiPPs makes them particularly well suited for genome mining efforts. By using genome mining to explicitly avoid species harboring biosynthetic gene clusters identical to those that produce known compounds, a combination of strain prioritization and mass spectrometry (MS)-based analysis offers a new route to discovering natural products that can overcome the burden of rediscovery that has increasingly hampered discovery efforts (2, 3). One challenging aspect of high-throughput genome mining for new natural products is the difficulty to determine their molecular structures in high throughput. We present here a method that allows automated RiPP structure elucidation.In contrast to nonribosomal peptides that have an average molecular weight of less than 1,000 Da, as documented in the NORINE database (4), RiPPs in many cases have molecular weights larger than 2,500 Da. Molecules of this size are difficult to rapidly analyze by NMR spectroscopy, rendering MS the most convenient tool for RiPP structural characterization. Even when the precursor peptide sequences are known and the types of PTMs can be predicted based on the sequences of the biosynthetic enzymes (5–8), multiple possible PTM sites on the precursor peptide typically result in a myriad of structures that are often difficult to differentiate. This challenge is further exacerbated by the frequent occurrence of one or more cross-links in RiPPs, which complicates traditional tandem MS-based structure elucidation. One of the main difficulties is that the spectra only contain a small fraction of informative signals among a large number of less diagnostic signals that cloud spectrum interpretation. As the spectra often also vary significantly with different instrument settings (9), selection of the most suitable spectra for drawing conclusions is time consuming and sometimes introduces bias. Indeed, a number of incorrect structural assignments of RiPPs have been reported based on insufficient information content of tandem MS data (10–15). Here, we report use of hypothetical structure enumeration and evaluation (HSEE) for automated and unbiased interpretation of tandem MS data. The method is based on the prediction of a collection of hypothetical structures for a RiPP of certain mass and known biosynthetic information. By listing all of the theoretical daughter ions from this enumeration and automated evaluation of their matches with one or several experimental spectra, the most probable RiPP structure can be determined. We demonstrate here for multiple classes of known RiPPs with complex structures that HSEE is highly effective in analyzing tandem MS data and predicting the correct structure. In addition, we used HSEE to characterize a lanthipeptide whose structure was elusive despite our previous efforts, and to determine the directionality of thiazole-forming enzymes and lanthipeptide synthetases.