PROJECT SUMMARY. The economic and social burden of the treatment of infectious and chronic diseases is enormous, >$300B annually. The ongoing COVID-19 pandemic alone will cost the U.S. economy roughly $8 trillion over the next decade without an effective drug to date. The emergence of drug resistant microbes, the diminishing supply of novel classes of antibiotics, and the dramatic reduction in R&D of anti-infective, anti-proliferation and anti-inflammatory agents have further amplified public health concerns. Fungi are prolific producers of anti- microbial secondary metabolites (SM) and since the turn of the century have provided 45% of bioactive molecules from all microbial sources. However, environmental filamentous fungi and fungal SM biosynthetic gene clusters (BGCs) remain largely untapped due to difficulties in efficiently handling and expressing these SM BGCs. This research proposal will advance the science of functional SM metagenomics, and will further advance our newly-developed fungal artificial chromosome (FAC) technology by integrating Next-Gen Sequencing (NGS), artificial intelligence (AI), FAC heterologous expression, and direct Nuclear Magnetic Resonance (NMR) analysis. Our methodologies enable precise capture of full-length SM BGCs from any fungus, and heterologous expression of large intact silent SM BGCs-containing FAC clones for high yields of natural products (NPs). Our goals are to improve the prediction of novel BGCs and their compound production, and to discover novel NPs for clinical development of novel antibiotics and other drug leads. In proof-concept research, we successfully predicted and captured the FAC-BGC of novel antibiotic berkeleylactone A and 136 BGCs from two different fungi by FAC-NGS. Phenomenally, we achieved at least 60% yields of discreet NP compounds as FAC crude extracts by heterologous expression of 5 of 17 BGC-FACs. We also elucidate the structures of 15 NP molecules with diverse activities, including TWO novel compounds by direct NMR analysis of FAC crude extracts, due to the high yield of some compounds. In this Phase II study, we will further improve our in-house FAC-NGS-AI pipeline to better predict novel fungal BGCs and their NPs, increasing the compound hit rate to 50~70% with high yield. We will completely dissect the berkeleylactone BGC and discover novel derivatives of this new antibiotic of homologous BGCs of other fungi. We will also study twelve fungi (ten fungi with no reference genomic sequences available) with an estimated 800 BGCs. This technology should improve fungal SM discovery 100~1000 fold and result in the discovery of at least five novel antibiotics, and other drug leads from un-studied/un-sequenced fungi of the toxic Berkeley Pit.

PROJECT NARRATIVE Unfortunately, we are losing the fight against both infectious and chronic diseases due to ongoing pandemics, the alarming increase in the number of multi-drug resistant microbes, and our inability to find drug leads with novel mechanisms of action. To assist in the ongoing search for new drugs and drug leads, this proposed research further develops Fungal Artificial Chromosomes (FACs) into an advanced FAC-NGS-AI technology and tool for drug discovery that allows access to the majority of fungal biosynthetic gene clusters for high yields of natural products from environment filamentous fungi. For this Phase II proposal, our functional metagenomic approach will be used to synthesize, identify and characterize novel antibiotics, and produce them in high yield from dedicated fungal FAC-transformants to aid in the fight against drug-resistant microorganisms.