Rapid dissection of the biosynthesis of antiMRSA antibiotics produced in co-culture by extremophilic fungi through the development of Fungal Artificial Chromosomes

通过真菌人工染色体的发育，快速剖析嗜极真菌共培养中产生的抗 MRSA 抗生素的生物合成

• 批准号: 10657805
• 负责人: Chengcang Charles Wu
• 金额: $ 98.27万
• 依托单位: INTACT GENOMICS, INC.
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10657805
• 关键词: Address; Anabolism; Anti-Infective Agents; Anti-Inflammatory Agents; Antibiotics; Antifungal Agents; Applications Grants; Artificial Chromosomes; Artificial Intelligence; Bacterial Artificial Chromosomes; Bioinformatics; Biological Assay; Businesses; COVID-19 pandemic; Chemicals; Chronic Disease; Coculture Techniques; Communicable Diseases; Coupled; Crude Extracts; DNA; Data; Dedications; Development; Dissection; Economics; Engineering; Environment; Fermentation; Gene Cluster; Genetic Variation; Genomics; Goals; High Pressure Liquid Chromatography; Length; Libraries; Metagenomics; Methodology; Molds; Montana; Multi-Drug Resistance; Natural Compound; Natural Products; Nuclear Magnetic Resonance; Pathway interactions; Pharmaceutical Preparations; Phase; Preparation; Production; Proliferating; Public Health; Publishing; Research; Research Proposals; Science; Services; Small Business Innovation Research Grant; Source; Structure; Technology; Therapeutic; Universities; Work; Workplace; antimicrobial; bioinformatics pipeline; clinical development; cost; drug discovery; drug resistant microorganism; fighting; fungus; improved; in silico; infectious disease treatment; innovation; microbial; next generation sequencing; novel; novel antibiotic class; novel therapeutics; pandemic disease; phase 2 study; research and development; secondary metabolite; social; tool; vector; virtual

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.

项目摘要。治疗传染性和的经济和社会负担 慢性疾病是巨大的，每年> $ 300B。仅在进行的共同19-19大流行就会 迄今为止，未来十年没有有效的药物，美国经济损失了约8万亿美元。 耐药微生物的出现，新型抗生素的供应减少， 以及反感染，抗增殖和抗炎的R＆D的急剧减少 代理商进一步扩大了公共卫生问题。真菌是抗抗菌的生产者 自世纪之交以来，微生物次生代谢物（SM）提供了45％ 来自所有微生物来源的生物活性分子。但是，环境丝状真菌和 真菌SM生物合成基因簇（BGC）由于困难而在很大程度上尚未开发 有效处理和表达这些SM BGC。这项研究建议将推动 功能性SM元基因组学科学，并将进一步推进我们新开发的真菌 人造染色体（FAC）技术通过整合下一代测序（NGS），人造 智能（AI），FAC异源表达和直接核磁共振（NMR） 分析。我们的方法可以从任何真菌中精确捕获全长SM BGC， 和含有大量无静音SM BGC的FACE克隆的异源表达高 天然产物的产量（NP）。我们的目标是改善新型BGC的预测和 它们的复合生产，并发现新颖的NP用于新颖的临床开发 抗生素和其他药物铅。在证明概念研究中，我们成功预测了 从两个不同的 FAC-NGS真菌。在惊人的情况下，我们至少达到了至少60％的谨慎NP化合物的收率 作为FAC的原油提取物，通过17 BGC-FAC中的5个异源表达。我们还阐明了 具有不同活性的15个NP分子的结构，包括直接的两种新型化合物 由于某些化合物的高产量，对FAC原油提取物的NMR分析。在这个阶段II 研究，我们将进一步改善内部fac-ngs-ai管道，以更好地预测新型真菌 BGC及其NP，以高收益率将复合命中率提高到50〜70％。我们将 完全剖析伯克莱酮BGC并发现这种新抗生素的新颖衍生物 其他真菌的同源BGC。我们还将研究十二种真菌（十种真菌，没有参考 可用的基因组序列），估计为800 bgcs。该技术应该改进 真菌SM发现100〜1000倍，并发现至少五种新型抗生素， 其他药物来自有毒伯克利坑的未经研究/未序列的真菌。