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。治疗传染病和结核病的经济和社会负担 慢性病是巨大的，每年超过3000亿美元。仅持续的COVID-19大流行就将 到目前为止，在没有有效药物的情况下，美国经济在未来十年内损失了大约8万亿美元。 抗药性微生物的出现，新型抗生素的供应减少， 以及抗感染、抗增殖和抗炎药物的研发大幅减少 代理商进一步加剧了公众健康问题。真菌是抗- 微生物次级代谢产物（SM），自世纪以来， 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）由于在 有效地处理和表达这些SM BGC。这项研究计划将推动 科学的功能SM宏基因组学，并将进一步推进我们新开发的真菌 人工染色体（FAC）技术通过整合下一代测序（NGS），人工 人工智能（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， 和含有大的完整沉默SM BGC的FAC克隆的异源表达，用于高表达。 天然产物（NPs）的产量。我们的目标是提高新的BGC的预测， 它们的化合物生产，并发现新的NP用于新的临床开发。 抗生素和其他药物。在概念验证研究中，我们成功地预测了 捕获了新型抗生素berkeleylactone A的FAC-BGC和来自两个不同的 真菌FAC-NGS。显然，我们实现了至少60%的离散NP化合物的产率 作为FAC粗提取物，通过异源表达17个BGC-FAC中的5个。我们还阐明了 15个具有不同活性的NP分子的结构，包括两个新化合物， FAC粗提物的NMR分析，由于某些化合物的高产率。在第二阶段 研究，我们将进一步改善我们的内部FAC-NGS-AI管道，以更好地预测新的真菌 BGC及其NP，使复合命中率提高到50~70%，产量高。我们将 彻底剖析伯克力内酯BGC，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12种真菌（10种真菌没有参考 基因组序列），估计有800个BGC。这项技术应该改进 真菌SM发现100~1000倍，并导致至少5种新抗生素的发现， 和其他药物线索从未研究/未测序的真菌有毒伯克利坑。