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/.
Novel antibiotics are urgently needed to address the looming global crisis of antibiotic resistance. Historically, the primary source of clinically used antibiotics has been microbial secondary ...metabolism. Microbial genome sequencing has revealed a plethora of uncharacterized natural antibiotics that remain to be discovered. However, the isolation of these molecules is hindered by the challenge of linking sequence information to the chemical structures of the encoded molecules. Here, we present PRISM 4, a comprehensive platform for prediction of the chemical structures of genomically encoded antibiotics, including all classes of bacterial antibiotics currently in clinical use. The accuracy of chemical structure prediction enables the development of machine-learning methods to predict the likely biological activity of encoded molecules. We apply PRISM 4 to chart secondary metabolite biosynthesis in a collection of over 10,000 bacterial genomes from both cultured isolates and metagenomic datasets, revealing thousands of encoded antibiotics. PRISM 4 is freely available as an interactive web application at http://prism.adapsyn.com .
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/.
Abstract
Antibiotic biosynthetic gene clusters (BGCs) produce bioactive metabolites that impart a fitness advantage to their producer, providing a mechanism for natural selection. This selection ...drives antibiotic evolution and adapts BGCs for expression in different organisms, potentially providing clues to improve heterologous expression of antibiotics. Here, we use phage-assisted continuous evolution (PACE) to achieve bioactivity-dependent adaptation of the BGC for the antibiotic bicyclomycin (BCM), facilitating improved production in a heterologous host. This proof-of-principle study demonstrates that features of natural bioactivity-dependent evolution can be engineered to access unforeseen routes of improving metabolic pathways and product yields.
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.
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.
Antibiotics are essential weapons in our fight against infectious disease, yet the consequences of broad-spectrum antibiotic use on microbiome stability and pathogen resistance are prompting ...investigations into more selective alternatives. Echoing the advent of precision medicine in oncology, precision antibiotics with focused activities are emerging as a means of addressing infections without damaging microbiomes or incentivizing resistance. Historically, antibiotic design principles have been gleaned from Nature, and reinvestigation of overlooked antibacterials is now providing scaffolds and targets for the design of pathogen-specific drugs. In this perspective, we summarize the biosynthetic and antibacterial mechanisms used to access these activities, and discuss how such strategies may be co-opted through engineering approaches to afford precision antibiotics.
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.
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.
Background & Aims Partially degraded gluten peptides from cereals trigger celiac disease (CD), an autoimmune enteropathy occurring in genetically susceptible persons. Susceptibility genes are ...necessary but not sufficient to induce CD, and additional environmental factors related to unfavorable alterations in the microbiota have been proposed. We investigated gluten metabolism by opportunistic pathogens and commensal duodenal bacteria and characterized the capacity of the produced peptides to activate gluten-specific T-cells from CD patients. Methods We colonized germ-free C57BL/6 mice with bacteria isolated from the small intestine of CD patients or healthy controls, selected for their in vitro gluten-degrading capacity. After gluten gavage, gliadin amount and proteolytic activities were measured in intestinal contents. Peptides produced by bacteria used in mouse colonizations from the immunogenic 33-mer gluten peptide were characterized by liquid chromatography tandem mass spectrometry and their immunogenic potential was evaluated using peripheral blood mononuclear cells from celiac patients after receiving a 3-day gluten challenge. Results Bacterial colonizations produced distinct gluten-degradation patterns in the mouse small intestine. Pseudomonas aeruginosa , an opportunistic pathogen from CD patients, exhibited elastase activity and produced peptides that better translocated the mouse intestinal barrier. P aeruginosa −modified gluten peptides activated gluten-specific T-cells from CD patients. In contrast, Lactobacillus spp. from the duodenum of non-CD controls degraded gluten peptides produced by human and P aeruginosa proteases, reducing their immunogenicity. Conclusions Small intestinal bacteria exhibit distinct gluten metabolic patterns in vivo, increasing or reducing gluten peptide immunogenicity. This microbe−gluten−host interaction may modulate autoimmune risk in genetically susceptible persons and may underlie the reported association of dysbiosis and CD.
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