Discovering novel natural products from fungal species

Project Summary.
Antibiotic resistance is becoming a major public health problem worldwide, with antibiotic resistant pathogens
infecting hundreds of millions and killing over a million patients worldwide each year. Infections such as
pneumonia, tuberculosis, blood poisoning, gonorrhoea, and foodborne diseases are becoming harder or
impossible to treat with the existing medicine. Majority of antibiotics currently in clinical use are natural products
or their derivatives. However, recently discovery of natural products with novel mechanisms to kill pathogens
have become more challenging due to the high rate of rediscovery of known molecules, as the traditional
technologies only capture the highest abundant molecular products of microbial isolates. The introduction of
modern sequencing technologies and genome mining in early 2000 has revolutionized the field of natural product
discovery. While these technologies have revealed millions of biosynthetic gene clusters (BGCs, clusters of
genes that encode for natural products) in microbial genomes, currently these methods cannot predict the
precise action of enzymes in BGCs, and therefore fail to correctly predict the final molecular product of BGCs.
Chemia Biosciences is developing technologies to predict the molecular product of these BGCs based on high-
throughput mass spectrometry data collected on extracts of microbial cultures. In the past, the PI and co-PI have
developed techniques for identifying known and discovering novel bacterial natural products by a computational
analysis of mass spectrometry data. The main goal of this proposal is to develop methods for discovering novel
fungal natural products, a biomedically important class of natural products that include antibacterial penicillin,
antifungal echinocandin, anticancer paclitaxel, immunosuppressant cyclosporin, and cholesterol-lowering
medication lovastatin. The software developed in the course of this proposal will be available to partners as a
cloud service.

Grant Number: 1R43GM154504-01
NIH Institute/Center: NIH
Principal Investigator: Bahar Behsaz