The ability to correlate the production of specialized metabolites to the genetic capacity of the organism that produces such molecules has become an invaluable tool in aiding the discovery of biotechnologically applicable molecules. Here, we accomplish this task by matching molecular families with gene cluster families, making these correlations to 60 microbes at one time instead of connecting one molecule to one organism at a time, such as how it is traditionally done. We can correlate these families through the use of nanospray desorption electrospray ionization MS/MS, an ambient pressure MS technique, in conjunction with MS/MS networking and peptidogenomics. We matched the molecular families of peptide natural products produced by 42 bacilli and 18 pseudomonads through the generation of amino acid sequence tags from MS/MS data of specific clusters found in the MS/MS network. These sequence tags were then linked to biosynthetic gene clusters in publicly accessible genomes, providing us with the ability to link particular molecules with the genes that produced them. As an example of its use, this approach was applied to two unsequenced Pseudoalteromonas species, leading to the discovery of the gene cluster for a molecular family, the bromoalterochromides, in the previously sequenced strain P. piscicida JCM 20779 T . The approach itself is not limited to 60 related strains, because spectral networking can be readily adopted to look at molecular family-gene cluster families of hundreds or more diverse organisms in one single MS/MS network.MS/MS molecular networking | mass spectrometry | microbial ecology T ens of thousands of sequenced microbial genomes or rough drafts of genomes are available at this time, and this number is predicted to grow into the millions over the next decades. This wealth of sequence data has the potential to be used for the discovery of small bioactive molecules through genome mining (1-6). Genome mining is a process in which small molecules are discovered by predicting what compound will be genetically encoded based on the sequences of biosynthetic gene clusters. However, the process of mining genetically encoded small molecules is not keeping pace with the rate by which genome sequences are being obtained. In general, genome mining is still done one gene cluster at a time and requires many person-years of effort to annotate a single molecule. The time and significant expertise that current genome mining requires also make genome mining very expensive. In light of this extensive effort and cost, alternative approaches to genome mining and annotating specialized metabolites must be developed that not only take advantage of the sequenced resources available and make it efficient to perform genome mining on a more global scale but also enable the molecular analysis of unsequenced organisms. Such methods will then significantly reduce the cost of genome mining by increasing the speed with which molecules are connected to candidate genes and using resources already available. Here, we put fo...

Hypothemycin is a macrolide protein kinase inhibitor from the fungus Hypomyces subiculosus. During biosynthesis, its carbon framework is assembled by two iterative polyketide synthases (PKSs), Hpm8 (highly reducing) and Hpm3 (non-reducing). These were heterologously expressed in Saccharomyces cerevisiae BJ5464-NpgA, purified to near homogeneity and reconstituted in vitro to produce (6′S, 10′S)-trans-7′,8′-dehydrozearalenol (1) from malonyl-CoA and NADPH. The structure of 1 was determined by x-ray crystallographic analysis. In the absence of functional Hpm3, the reducing PKS Hpm8 produces and offloads truncated pyrone products instead of the expected hexaketide. The non-reducing Hpm3 is able to accept an N-acetylcysteamine thioester of a correctly functionalized hexaketide to form 1, but it is unable to initiate polyketide formation from malonyl-CoA. We show that the starter unit acyltransferase (SAT) of Hpm3 is critical for crosstalk between the two enzymes and that the rate of biosynthesis of 1 is determined by the rate of hexaketide formation by Hpm8.