Chad W. Johnston

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.

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.

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.

PRISM 3: expanded prediction of natural product chemical structures from microbial genomes

Abstract Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/.

Structural and Chemical Characterization of Placer Gold Grains: Implications for Bacterial Contributions to Grain Formation

Gold grains collected from the Rio Saldaña River, Colombia were hundreds of micrometers in size and discoid-ellipse in shape. Fourteen of 63 grains contained an iron oxyhydroxide coating that occurred as ca. 50 to 100 nm thick lamina while thicker coatings were comprised of colloids 200 nm to 4 μm in diameter. Bacterial-size casts were observed throughout the thicker iron oxyhydroxide coating and intuitively represent relic impressions of bacterial cells. The surface textures of gold grains were generally smooth with surficial depressions or crevices containing detrital material colonized by bacteria. Focus Ion Beam (FIB) milled cross-sections demonstrated that the detrital material contained nanophase gold particles. Biofilm attached to this detrital material contained ca. 2 to 3 nm colloidal gold attached to exopolymeric substances. Cross sections of grains revealed solid cores with vesicular voids near the grain edge including a bacterial-size cast interpreted to be a permineralized bacterial cell. Synchrotron-based elemental mapping indicated that grains contained heterogenously distributed Ag and Cu. While strong Ag and Cu signals (relative to Au) were detected in the core, a stronger Au signal occurred at the edge of grains demonstrating enriched rims of secondary gold. The preservation of bacterial casts and biofilms associated with secondary gold structures at the surface of grains suggest that bacteria may contribute to gold enrichment and growth in this placer environment. Bacteria, occurring on the surface of 13 of 25 gold grains, were enriched by “inoculating” individual grains into separate test tubes containing R2B growth medium. Enriched growth of bacteria on gold grain surfaces demonstrated preferential attachment onto detrital material within creviced regions. The dominant bacteria from these enrichments were transferred to solid R2A medium to obtain pure isolates. The isolates were identified as one of four bacterial species: Nitrobacter sp. 263, Shewanella sp. YM-8, Sediminibacterium sp. B2-10-2 and sp. I-32 based on 16S ribosomal DNA sequencing.

Nonribosomal Assembly of Natural Lipocyclocarbamate Lipoprotein-Associated Phospholipase Inhibitors

EXPANDING OUR KNOWLEDGE: Natural lipocyclocarbamate natural products have provided the inspiration for the first-in-class synthetic phospholipase inhibitor darapladib, currently in phase III clinical trials for the treatment of atherosclerosis. Here, we discuss their biosynthesis by a nonribosomal peptide synthetase.