Innovative technologies to transform antibiotic discovery. Project 1 Genomic applications to transform Gram-negative Antibiotic discovery

改变抗生素发现的创新技术。

• 批准号: 10463688
• 负责人: DEBORAH T HUNG
• 金额: $ 185.21万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-07 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10463688
• 关键词: Antibiotic Resistance; Antibiotics; Bacterial Infections; Bar Codes; Binding; Biological; Biological Assay; Biological Availability; Biophysics; Cell membrane; Cells; Censuses; Centers for Disease Control and Prevention (U.S.); Cessation of life; Chemicals; Clinical; Collection; Complex; Coupled; Crystallization; Data Analyses; Dependence; Development; Drug Industry; Expression Profiling; Failure; Gene Expression Profiling; Genes; Genetic; Genetic Engineering; Genome; Genomics; Gram-Negative Bacteria; Health; Hospitals; Human; In Vitro; Infection; Intervention; Kinetics; Lead; Life; Machine Learning; Measures; Medical; Membrane Proteins; Modeling; Monitor; Mus; Natural Products; New Agents; Pathway interactions; Penicillins; Permeability; Persons; Pharmaceutical Preparations; Polysaccharides; Process; Property; Proteins; Pseudomonas aeruginosa; Resistance; Safety; Savings; Specificity; Structure; Structure-Activity Relationship; Technology; Testing; Therapeutic Index; Time; Triage; Xenobiotics; Zebrafish; bacterial resistance; base; biophysical properties; clinical candidate; combinatorial; cost; cytotoxicity; efflux pump; experience; genetic approach; genome sequencing; genome-wide; high throughput screening; improved; in vivo; inhibitor; innovative technologies; interest; knock-down; lead candidate; lead optimization; lead series; machine learning algorithm; mutant; next generation sequencing; novel; novel strategies; pathogen; peptidoglycan-associated lipoprotein; potency testing; promoter; protein expression; response; scaffold; screening; small molecule; small molecule libraries; success; targeted agent; transcriptomics; transposon sequencing; uptake; whole genome

Since Alexander Fleming's discovery of penicillin, antibiotics have been arguably the single medical intervention that has saved more lives than any other. However, this life saving intervention is now being threatened by the problem of antibiotic resistance that is outpacing the discovery of new antibiotics, resulting in the WHO and CDC declaring antibiotic resistance as one of the greatest threats to human health. Projections include the possibility of 10 million deaths per year by 2050 with tremendous impact on the global economy in the absence of a significant shift in the current antibiotic landscape We have developed novel strategies to interface genomics and high-throughput chemical screening technologies to transform antibiotic discovery, with a focus here on the major Gram-negative pathogen Pseudomonas aeruginosa (PsA), specifically targeting its essential outer membrane proteins (OMPs) and outer membrane associated proteins (OMAPs) in order to circumvent the need for xenobiotic cytoplasmic accumulation. We have performed chemical screening in a multiplexed fashion against a pool of bar-coded, genetically engineered target-specific strains in which each of the essential OMP/OMAP target genes has been knocked-down by promoter replacement. Next generation sequencing is used to enumerate amplified barcodes to measure the census of each mutant strain in the pool in response to a small molecule. Controlled low expression of the protein of interest in each of these strains hypersensitizes them to inhibitors of the corresponding target. Importantly, this strategy has allowed us (1) to expand the numbers of small molecule candidates by identifying small molecules that would have eluded discovery if screening simply against wild-type PsA, (2) to couple whole cell screening with target-based discovery, and (3) to target essential proteins of unknown function or lack a high-throughput assay. Using this approach to target 9 essential OMP/OMAP targets in a single screen, we have identified candidates targeting the outer membrane proteins LptD and OprL, proteins required for LPS transport and cell membrane integrity, respectively. Because these targets lack robust functional assays, we have developed a high-throughput transcriptomics-driven pipeline coupled with machine learning to identify and prioritize molecules with a high likelihood of specifically inhibiting these targets. We now propose to develop the hits with completely novel mechanisms of action to lead optimization and demonstrate in vivo proof of concept.

自从亚历山大·弗莱明发现青霉素以来，抗生素可以说是唯一的医疗手段。 比任何其他干预措施都挽救了更多的生命。然而，这种挽救生命的干预措施目前正在 受到抗生素耐药性问题的威胁，该问题的速度超过了新抗生素的发现，导致 世界卫生组织和疾病预防控制中心宣布抗生素耐药性是对人类健康的最大威胁之一。预测 到 2050 年，每年可能有 1000 万人死亡，这对全球经济产生巨大影响 目前的抗生素格局没有发生重大转变 我们开发了连接基因组学和高通量化学筛选的新策略 改变抗生素发现的技术，重点关注主要的革兰氏阴性病原体 铜绿假单胞菌 (PsA)，专门针对其必需的外膜蛋白 (OMP) 和外膜蛋白 膜相关蛋白（OMAP）以避免对异生细胞质的需求 积累。我们以多重方式对一组条形码进行了化学筛选， 基因工程的目标特异性菌株，其中每个必需的 OMP/OMAP 目标基因都已被 通过启动子替换而被击倒。下一代测序用于计数扩增的条形码 测量库中每个突变株对小分子反应的普查。控制低 这些菌株中感兴趣的蛋白质的表达使它们对这些菌株的抑制剂高度敏感。 相应的目标。重要的是，这一策略使我们能够（1）扩大小分子的数量 通过识别小分子来筛选候选者，如果仅针对野生型进行筛选，这些小分子将无法发现 PsA，(2) 将全细胞筛选与基于靶标的发现结合起来，(3) 靶向 功能未知或缺乏高通量检测。使用此方法来实现 9 个基本 OMP/OMAP 目标 在一次筛选中，我们已经确定了针对外膜蛋白 LptD 和 OprL 的候选蛋白 分别是 LPS 运输和细胞膜完整性所必需的。因为这些目标缺乏稳健性 功能分析，我们开发了一个高通量转录组驱动的管道与机器耦合 学习识别和优先考虑极有可能特异性抑制这些目标的分子。我们现在 建议开发具有全新作用机制的热门产品，以引导优化和论证 体内概念证明。