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: 10546657
• 负责人: Chengcang Charles Wu
• 金额: $ 100万
• 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/10546657
• 关键词: Address; Anabolism; Anti-Infective Agents; Anti-Inflammatory Agents; Antibiotics; Antifungal Antibiotics; Applications Grants; Artificial Chromosomes; Artificial Intelligence; Bacterial Artificial Chromosomes; Bioinformatics; Biological Assay; Businesses; COVID-19 pandemic; Chronic Disease; Coculture Techniques; Communicable Diseases; Coupled; Crude Extracts; DNA; Data; 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 Products; Nuclear Magnetic Resonance; Pathway interactions; Pharmaceutical Preparations; Phase; Preparation; Production; Public Health; Publishing; Research; Research Proposals; Science; Services; Small Business Innovation Research Grant; Source; Structure; Technology; Therapeutic; Universities; Work; Workplace; antimicrobial; bioinformatics pipeline; chemical genetics; clinical development; cost; drug discovery; drug resistant microorganism; fight against; 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; 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。治疗传染病和传染病的经济和社会负担 慢性疾病是巨大的，每年>$300B。仅当前的 COVID-19 大流行就将 迄今为止，如果没有有效的药物，未来十年将给美国经济造成约 8 万亿美元的损失。 耐药微生物的出现、新型抗生素供应的减少、 抗感染、抗增殖、抗炎等药物研发大幅减少 特工进一步加剧了公众对健康的担忧。真菌是抗微生物物质的多产者 微生物次生代谢物 (SM) 自世纪之交以来提供了 45% 来自所有微生物来源的生物活性分子。然而，环境丝状真菌和 真菌 SM 生物合成基因簇 (BGC) 由于难以开发而在很大程度上尚未开发。 有效地处理和表达这些 SM BGC。该研究计划将推动 功能性 SM 宏基因组学科学，并将进一步推进我们新开发的真菌 人工染色体（FAC）技术通过集成下一代测序（NGS）、人工 智力 (AI)、FAC 异源表达和直接核磁共振 (NMR) 分析。我们的方法能够从任何真菌中精确捕获全长 SM BGC， 和含有 FAC 克隆的大型完整沉默 SM BGC 的异源表达，以实现高 天然产物（NP）的产量。我们的目标是改进新型 BGC 的预测， 他们的化合物生产，并发现新的纳米粒子用于新药物的临床开发 抗生素和其他药物先导物。在概念验证研究中，我们成功预测并 捕获了新型抗生素 Berkeleylactone A 的 FAC-BGC 和来自两种不同的 136 个 BGC 通过 FAC-NGS 检测真菌。令人惊奇的是，我们实现了至少 60% 的离散 NP 化合物产率 通过异源表达 17 个 BGC-FAC 中的 5 个作为 FAC 粗提物。我们还阐明了 15 个具有不同活性的 NP 分子的结构，包括两种通过直接方法获得的新型化合物 由于某些化合物的产率较高，因此对 FAC 粗提物进行 NMR 分析。在本次第二阶段 研究中，我们将进一步改进我们内部的 FAC-NGS-AI 流程，以更好地预测新型真菌 BGCs及其NPs，将化合物命中率提高到50~70%，且产量高。我们将 彻底剖析伯克利内酯 BGC 并发现这种新抗生素的新衍生物 其他真菌的同源 BGC。我们还将研究十二种真菌（十种真菌没有参考文献） 可用的基因组序列），估计有 800 个 BGC。这项技术应该改进 真菌 SM 发现提高 100~1000 倍，并导致至少五种新型抗生素的发现， 以及来自有毒的伯克利坑中未经研究/未测序的真菌的其他药物先导物。