Nathan A. Magarvey

Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM)

Microbial natural products are an invaluable source of evolved bioactive small molecules and pharmaceutical agents. Next-generation and metagenomic sequencing indicates untapped genomic potential, yet high rediscovery rates of known metabolites increasingly frustrate conventional natural product screening programs. New methods to connect biosynthetic gene clusters to novel chemical scaffolds are therefore critical to enable the targeted discovery of genetically encoded natural products. Here, we present PRISM, a computational resource for the identification of biosynthetic gene clusters, prediction of genetically encoded nonribosomal peptides and type I and II polyketides, and bio- and cheminformatic dereplication of known natural products. PRISM implements novel algorithms which render it uniquely capable of predicting type II polyketides, deoxygenated sugars, and starter units, making it a comprehensive genome-guided chemical structure prediction engine. A library of 57 tailoring reactions is leveraged for combinatorial scaffold library generation when multiple potential substrates are consistent with biosynthetic logic. We compare the accuracy of PRISM to existing genomic analysis platforms. PRISM is an open-source, user-friendly web application available at http://magarveylab.ca/prism/.

Gold biomineralization by a metallophore from a gold-associated microbe

Microorganisms produce and secrete secondary metabolites to assist in their survival. We report that the gold resident bacterium Delftia acidovorans produces a secondary metabolite that protects from soluble gold through the generation of solid gold forms. This finding is the first demonstration that a secreted metabolite can protect against toxic gold and cause gold biomineralization.

Staphylococcus aureus Nonribosomal Peptide Secondary Metabolites Regulate Virulence

Golden Regulator Staphylococcus aureus is a common cause of intractable infections that are exacerbated by an array of toxins and virulence factors. The agr pheromone has been thought to represent the master regulator of virulence in this pathogen, but it is not always expressed and is also found in many nonpathogenic cocci. A strictly conserved, nonribosomal peptide synthetase has now been found by Wyatt et al. (p. 294, published online 3 June) by genome mining. The enzyme assembles valine and tyrosine into cyclic dipeptides called aureusimines that are expressed by all sequenced strains of S. aureus, including the “superbug” MRSA (Methicillin-resistant Staphylococcus aureus). Microarray analysis showed a striking effect of mutation in the synthetase locus on the production of immunomodulators, hemolysins, and other exotoxins by the pathogen. Indeed, mice infected systemically with the mutant strain showed a restricted spread of infection compared with the wild type. Dipeptides produced by a major bacterial pathogen are essential for successful infection. Staphylococcus aureus is a major human pathogen that is resistant to numerous antibiotics in clinical use. We found two nonribosomal peptide secondary metabolites—the aureusimines, made by S. aureus—that are not antibiotics, but function as regulators of virulence factor expression and are necessary for productive infections. In vivo mouse models of bacteremia showed that strains of S. aureus unable to produce aureusimines were attenuated and/or cleared from major organs, including the spleen, liver, and heart. Targeting aureusimine synthesis may offer novel leads for anti-infective drugs.

Dereplicating nonribosomal peptides using an informatic search algorithm for natural products (iSNAP) discovery

Nonribosomal peptides are highly sought after for their therapeutic applications. As with other natural products, dereplication of known compounds and focused discovery of new agents within this class are central concerns of modern natural product-based drug discovery. Development of a chemoinformatic library-based and informatic search strategy for natural products (iSNAP) has been constructed and applied to nonribosomal peptides and proved useful for true nontargeted dereplication across a spectrum of nonribosomal peptides and within natural product extracts.

An automated Genomes-to-Natural Products platform (GNP) for the discovery of modular natural products.

Bacterial natural products are a diverse and valuable group of small molecules, and genome sequencing indicates that the vast majority remain undiscovered. The prediction of natural product structures from biosynthetic assembly lines can facilitate their discovery, but highly automated, accurate, and integrated systems are required to mine the broad spectrum of sequenced bacterial genomes. Here we present a genome-guided natural products discovery tool to automatically predict, combinatorialize and identify polyketides and nonribosomal peptides from biosynthetic assembly lines using LC–MS/MS data of crude extracts in a high-throughput manner. We detail the directed identification and isolation of six genetically predicted polyketides and nonribosomal peptides using our Genome-to-Natural Products platform. This highly automated, user-friendly programme provides a means of realizing the potential of genetically encoded natural products.

Assembly and clustering of natural antibiotics guides target identification

Antibiotics are essential for numerous medical procedures, including the treatment of bacterial infections, but their widespread use has led to the accumulation of resistance, prompting calls for the discovery of antibacterial agents with new targets. A majority of clinically approved antibacterial scaffolds are derived from microbial natural products, but these valuable molecules are not well annotated or organized, limiting the efficacy of modern informatic analyses. Here, we provide a comprehensive resource defining the targets, chemical origins and families of the natural antibacterial collective through a retrobiosynthetic algorithm. From this we also detail the directed mining of biosynthetic scaffolds and resistance determinants to reveal structures with a high likelihood of having previously unknown modes of action. Implementing this pipeline led to investigations of the telomycin family of natural products from Streptomyces canus, revealing that these bactericidal molecules possess a new antibacterial mode of action dependent on the bacterial phospholipid cardiolipin.

Molecular mechanisms of membrane targeting antibiotics

The bacterial membrane provides a target for antimicrobial peptides. There are two groups of bacteria that have characteristically different surface membranes. One is the Gram-negative bacteria that have an outer membrane rich in lipopolysaccharide. Several antimicrobials have been found to inhibit the synthesis of this lipid, and it is expected that more will be developed. In addition, antimicrobial peptides can bind to the outer membrane of Gram-negative bacteria and block passage of solutes between the periplasm and the cell exterior, resulting in bacterial toxicity. In Gram-positive bacteria, the major bacterial lipid component, phosphatidylglycerol can be chemically modified by bacterial enzymes to convert the lipid from anionic to cationic or zwitterionic form. This process leads to increased levels of resistance of the bacteria against polycationic antimicrobial agents. Inhibitors of this enzyme would provide protection against the development of bacterial resistance. There are antimicrobial agents that directly target a component of bacterial cytoplasmic membranes that can act on both Gram-negative as well as Gram-positive bacteria. Many of these are cyclic peptides with a rigid binding site capable of binding a lipid component. This binding targets antimicrobial agents to bacteria, rather than being toxic to host cells. This article is part of a Special Issue entitled: Antimicrobial peptides edited by Karl Lohner and Kai Hilpert.

Polyketide and nonribosomal peptide retro-biosynthesis and global gene cluster matching

Polyketides (PKs) and nonribosomal peptides (NRPs) are profoundly important natural products, forming the foundations of many therapeutic regimes. Decades of research have revealed over 11,000 PK and NRP structures, and genome sequencing is uncovering new PK and NRP gene clusters at an unprecedented rate. However, only ∼10% of PK and NRPs are currently associated with gene clusters, and it is unclear how many of these orphan gene clusters encode previously isolated molecules. Therefore, to efficiently guide the discovery of new molecules, we must first systematically de-orphan emergent gene clusters from genomes. Here we provide to our knowledge the first comprehensive retro-biosynthetic program, generalized retro-biosynthetic assembly prediction engine (GRAPE), for PK and NRP families and introduce a computational pipeline, global alignment for natural products cheminformatics (GARLIC), to uncover how observed biosynthetic gene clusters relate to known molecules, leading to the identification of gene clusters that encode new molecules.

Genomic charting of ribosomally synthesized natural product chemical space facilitates targeted mining

Significance Natural products and their derivatives are essential to the treatment of many diseases. Ribosomally synthesized and posttranslationally modified peptides (RiPPs) are a class of natural products noted for their bioactivities. Genome sequencing has revealed that most natural products remain undiscovered, but the complexity and diversity of RiPPs has challenged the systematic identification of these molecules from genomic data. Here, we present an algorithm for RiPP structure prediction from prokaryotic genomes and systematically investigate the chemical space occupied by genetically encoded RiPPs. We reveal widespread biosynthesis of RiPPs by prokaryotes, identify candidates for targeted discovery, and isolate a RiPP from a rare family. Microbial natural products are an evolved resource of bioactive small molecules, which form the foundation of many modern therapeutic regimes. Ribosomally synthesized and posttranslationally modified peptides (RiPPs) represent a class of natural products which have attracted extensive interest for their diverse chemical structures and potent biological activities. Genome sequencing has revealed that the vast majority of genetically encoded natural products remain unknown. Many bioinformatic resources have therefore been developed to predict the chemical structures of natural products, particularly nonribosomal peptides and polyketides, from sequence data. However, the diversity and complexity of RiPPs have challenged systematic investigation of RiPP diversity, and consequently the vast majority of genetically encoded RiPPs remain chemical “dark matter.” Here, we introduce an algorithm to catalog RiPP biosynthetic gene clusters and chart genetically encoded RiPP chemical space. A global analysis of 65,421 prokaryotic genomes revealed 30,261 RiPP clusters, encoding 2,231 unique products. We further leverage the structure predictions generated by our algorithm to facilitate the genome-guided discovery of a molecule from a rare family of RiPPs. Our results provide the systematic investigation of RiPP genetic and chemical space, revealing the widespread distribution of RiPP biosynthesis throughout the prokaryotic tree of life, and provide a platform for the targeted discovery of RiPPs based on genome sequencing.

Heterologous Expression and Structural Characterisation of a Pyrazinone Natural Product Assembly Line

Through a number of strategies nonribosomal peptide assembly lines give rise to a metabolic diversity not possible by ribosomal synthesis. One distinction within nonribosomal assembly is that products are elaborated on an enzyme‐tethered substrate, and their release is enzyme catalysed. Reductive release by NAD(P)H‐dependent catalysts is one observed nonribosomal termination and release strategy. Here we probed the selectivity of a terminal reductase domain by using a full‐length heterologously expressed nonribosomal peptide synthetase for the dipeptide aureusimine and were able to generate 17 new analogues. Further, we generated an X‐ray structure of aureusimine terminal reductase to gain insight into the structural details associated with this enzymatic domain.