Biosynthesis-guided discovery reveals enteropeptins as alternative sactipeptides containing N-methylornithine.

The combination of next-generation DNA sequencing technologies and bioinformatics has revitalized natural product discovery. Using a bioinformatic search strategy, we recently identified ∼600 gene clusters in otherwise overlooked streptococci that code for ribosomal peptide natural products synthesized by radical S-adenosylmethionine enzymes. These grouped into 16 subfamilies and pointed to an unexplored microbiome biosynthetic landscape.

Vitamin B3 Triggers Biosynthesis of Secondary Metabolite Dormancy Signals in .

Human-associated streptococci have not been viewed as productive sources of natural products. Against expectation, bioinformatic searches recently revealed a large collection of diverse biosynthetic gene clusters coding for ribosomally synthesized and post-translationally modified peptides (RiPPs) in streptococcal genomes. The most abundant of these, the gene cluster, is specific to , a burdensome agricultural pathogen and zoonotic agent.

Bicyclostreptins are radical SAM enzyme-modified peptides with unique cyclization motifs.

Microbial natural products comprise diverse architectures that are generated by equally diverse biosynthetic strategies. In peptide natural products, amino acid sidechains are frequently used as sites of modification to generate macrocyclic motifs. Backbone amide groups, among the most stable of biological moieties, are rarely used for this purpose.

Guidelines for metabolomics-guided transposon mutagenesis for microbial natural product discovery.

There is a great discrepancy between the natural product output of cultured microorganisms and their bioinformatically predicted biosynthetic potential, such that most of the molecular diversity contained within microbial reservoirs has yet to be discovered. One of the primary reasons is insufficient expression of natural product biosynthetic gene clusters (BGCs) under standard laboratory conditions. Several methods have been developed to increase production from such "cryptic" BGCs.

MetEx, a Metabolomics Explorer Application for Natural Product Discovery.

Advances in next-generation DNA sequencing technologies, bioinformatics, and mass spectrometry-based metabolite detection have ushered in a new era of natural product discovery. Microbial secondary metabolomes are complex, especially when otherwise silent biosynthetic genes are activated, and there is therefore a need for data analysis software to explore and map the resulting multidimensional datasets. To that end, we herein report the Metabolomics Explorer (MetEx), a publicly available web application for the analysis of parallel liquid chromatography-coupled mass spectrometry (LC-MS)-based metabolomics data.

A Natural Product Chemist's Guide to Unlocking Silent Biosynthetic Gene Clusters.

Microbial natural products have provided an important source of therapeutic leads and motivated research and innovation in diverse scientific disciplines. In recent years, it has become evident that bacteria harbor a large, hidden reservoir of potential natural products in the form of silent or cryptic biosynthetic gene clusters (BGCs). These can be readily identified in microbial genome sequences but do not give rise to detectable levels of a natural product.

Quorum Sensing in Streptococcus mutans Regulates Production of Tryglysin, a Novel RaS-RiPP Antimicrobial Compound.

The genus encompasses a large bacterial taxon that commonly colonizes mucosal surfaces of vertebrates and is capable of disease etiologies originating from diverse body sites, including the respiratory, digestive, and reproductive tracts. Identifying new modes of treating infections is of increasing importance, as antibiotic resistance has escalated. is an important opportunistic pathogen that is an agent of dental caries and is capable of systemic diseases such as endocarditis.

Discovery and Biosynthesis of Streptosactin, a Sactipeptide with an Alternative Topology Encoded by Commensal Bacteria in the Human Microbiome.

Mammalian microbiomes encode thousands of biosynthetic gene clusters (BGCs) and represent a new frontier in natural product research. We recently found an abundance of quorum sensing-regulated BGCs in mammalian microbiome streptococci that code for ribosomally synthesized and post-translationally modified peptides (RiPPs) and contain one or more radical S-adenosylmethionine (RaS) enzymes, a versatile superfamily known to catalyze some of the most unusual reactions in biology. In the current work, we target a widespread group of streptococcal RiPP BGCs and elucidate both the reaction carried out by its encoded RaS enzyme and identify its peptide natural product, which we name streptosactin.

Unlocking Cryptic Metabolites with Mass Spectrometry-Guided Transposon Mutant Selection.

The products of most secondary metabolite biosynthetic gene clusters (BGCs) have yet to be discovered, in part due to low expression levels in laboratory cultures. Reporter-guided mutant selection (RGMS) has recently been developed for this purpose: a mutant library is generated and screened, using genetic reporters to a chosen BGC, to select transcriptionally active mutants that then enable the characterization of the "cryptic" metabolite. The requirement for genetic reporters limits the approach to a single pathway within genetically tractable microorganisms.

Total Synthesis and Stereochemical Assignment of Streptide.

Streptide () is a peptide-derived macrocyclic natural product that has attracted considerable attention since its discovery in 2015. It contains an unprecedented post-translational modification that intramolecularly links the β-carbon (C3) of a residue 2 lysine with the C7 of a residue 6 tryptophan, thereby forming a 20-membered cyclic peptide. Herein, we report the first total synthesis of streptide that confirms the regiochemistry of the lysine-tryptophan cross-link and provides an unambiguous assignment of the stereochemistry (3 vs 3) of the lysine-2 C3 center.

Comparative mass spectrometry-based metabolomics strategies for the investigation of microbial secondary metabolites.

Covering: 2000 to 2016The labor-intensive process of microbial natural product discovery is contingent upon identifying discrete secondary metabolites of interest within complex biological extracts, which contain inventories of all extractable small molecules produced by an organism or consortium. Historically, compound isolation prioritization has been driven by observed biological activity and/or relative metabolite abundance and followed by dereplication via accurate mass analysis. Decades of discovery using variants of these methods has generated the natural pharmacopeia but also contributes to recent high rediscovery rates.

Metabolic model for diversity-generating biosynthesis.

A conventional metabolic pathway leads to a specific product. In stark contrast, there are diversity-generating metabolic pathways that naturally produce different chemicals, sometimes of great diversity. We demonstrate that for one such pathway, tru, each ensuing metabolic step is slower, in parallel with the increasing potential chemical divergence generated as the pathway proceeds.

Mapping Microbial Response Metabolomes for Induced Natural Product Discovery.

Intergeneric microbial interactions may originate a significant fraction of secondary metabolic gene regulation in nature. Herein, we expose a genomically characterized Nocardiopsis strain, with untapped polyketide biosynthetic potential, to intergeneric interactions via coculture with low inoculum exposure to Escherichia, Bacillus, Tsukamurella, and Rhodococcus. The challenge-induced responses of extracted metabolites were characterized via multivariate statistical and self-organizing map (SOM) analyses, revealing the magnitude and selectivity engendered by the limiting case of low inoculum exposure.

Structuring Microbial Metabolic Responses to Multiplexed Stimuli via Self-Organizing Metabolomics Maps.

Secondary metabolite biosynthesis in microorganisms responds to discrete chemical and biological stimuli; however, untargeted identification of these responses presents a significant challenge. Herein we apply multiplexed stimuli to Streptomyces coelicolor and collect the resulting response metabolomes via ion mobility-mass spectrometric analysis. Self-organizing map (SOM) analytics adapted for metabolomic data demonstrate efficient characterization of the subsets of primary and secondary metabolites that respond similarly across stimuli.