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.

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/.

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/.

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.

Several nonribosomal peptide natural products are composites of alpha-hydroxy acid and alpha-amino acid monomers. Cereulide, the emetic toxin from the human pathogen Bacillus cereus, and valinomycin, from Streptomyces spp., are closely related macrocyclic K+ ionophores. The macrocyclic core of each natural product contains alternating peptide (six) and ester (six) bonds, and their cyclododecadepsipeptide structures consist of a tetradepsipeptide unit repeated three times. Here we overexpress the cereulide NRPS alpha-hydroxy acid specifying modules from CesA and CesB and demonstrate that each contains an alpha-keto acid activating adenylation domain and a chiral alpha-ketoacyl-S-carrier protein reductase (alpha-KR). The logic used by the cereulide NRPS is likely at work in the valinomycin NRPS and may be the general strategy used in bacterial NRPSs to form alpha-hydroxy acid containing natural products.