To combat multidrug-resistant bacterial infections, novel classes of antibiotics with new mechanisms of action are desperately required. Genome mining for novel natural products is quickly replacing traditional approaches to antibiotic discovery. Warp Drive Bio has sequenced over 135,000 actinomycete strain genomes from diverse sources worldwide, and our proprietary genomic database contains approximately ~3,500,000 secondary metabolite gene clusters. Importantly ~75% of cluster families identified in our database have yet to be reported in the literature. Our vast microbial genomics-based approach is innovative because it provides an unprecedented opportunity to discover entirely novel antibiotics with new mechanisms of action (MOAs). The focus of this project will be to identify, express, and test biosynthetic gene clusters encoding new classes of antibiotics with novel MOAs to combat current and future drug-resistant pathogens, by combing our vast genomics resources and innovative bioinformatics search with our validated genomes-to-drugs platform for natural products discovery. First, we will harness our extensive, complementary genomic resources to identify and clone 10 candidate neomorph antibiotic clusters. We term biosynthetic clusters that are novel as neomorphs, and we have constructed a bioinformatic analysis pipeline of phylogenomic and chemoinformatic tools to assess novelty at the genetic and biosynthetic levels. We then will utilize our microbial genomic database to predict which neomorph clusters possess antibiotic activity, by searching for self-resistance genes within the neomorph cluster. Bacteria utilize a variety of self-resistance mechanisms to protect against the antibiotics they are actively producing, and this property can be exploited using genomic information. Our integrated bioinformatic analysis we will advance 10 candidate neomorph antibiotic clusters for expression and testing. A validated portfolio of synthetic biology techniques will be deployed for refactoring biosynthetic clusters to enhance the expression of clusters that are not expressed, or which are expressed at very low levels, to increase compound production. Finally we have developed a high throughput fermentation process, bioassay, and mass spectrometric infrastructure to analyze and identify neomorphs. Thus, by combing an innovative genomic search of novel biosynthetic clusters with embedded resistance genes, with our integrated genes-to-compound platform, we will identify, engineer, and screen candidate neomorph antibiotics to address the growing clinical need for new antibacterial agents with novel MOAs.
Public Health Relevance Statement: This project will take a microbial genomics-based approach to finding entirely novel, natural products with antibiotic properties and new mechanisms of action, to combat current and emerging drug resistant pathogens.
Project Terms: Address; Anti-Bacterial Agents; Antibiotic Resistance; Antibiotics; Bacteria; Bacterial Artificial Chromosomes; Bacterial Infections; bacterial resistance; Bioinformatics; Biological Assay; Candida albicans; Cells; Chemicals; Clinical; Cloning; Collection; Comb animal structure; combat; Cytology; Databases; Development; drug discovery; Drug resistance; Engineering; Family; Fermentation; Future; Gene Cluster; Genes; Genetic; genetic signature; Genetic Transcription; Genome; Genomics; Growth; Housekeeping Gene; Hybrids; innovation; Length; Libraries; Link; Literature; Measures; methicillin resistant Staphylococcus aureus; Methodology; Methods; microbial; Mining; Modification; Multi-Drug Resistance; Natural Products; novel; overexpression; pathogen; Pathogenicity; Pharmaceutical Preparations; Phenotype; polyketide synthase; Process; Production; promoter; Promoter Regions; Property; Pseudomonas aeruginosa; Reporting; Research Infrastructure; resistance gene; resistance mechanism; Resources; screening; Source; Streptomyces; synthetic biology; System; Techniques; Testing; tool; transcription factor
