Resolving the bottleneck in antibiotic discovery

摘要 大多数抗生素产生于Waxman平台，筛选土壤微生物，但这种资源有限 到了60年代末就被破坏了。在没有平台的情况下，化合物的引入速度比 病原体产生抗药性，结果是人类健康危机。最近总统的行政命令 “打击抗药性细菌”强调了这个问题的重要性。在本节目中，我们将 开发基于利用未培养细菌的有效发现计划，以解决 抗菌药物的发现。 未培养的细菌是尚未开发的次生代谢物来源，我们开发了方法来 为了发现抗生素而种植它们和我的。到目前为止，我们从这个来源发现了25种新化合物， 其中包括一种新的化合物--拉索霉素，该化合物具有抗M。 结核病；以及teixobactin，一种基本上没有耐药性的新型肽聚糖合成抑制剂 发展。然而，未培养细菌的真正潜力仍未实现--背景 即使对于这种尚未开发的化学来源，已知和有毒化合物也一直是主要的瓶颈 多样性。我们建议通过引入转录组分析作为快速识别的工具来解决这个问题 从未培养的细菌中提取的有希望的化合物。影响同一目标的化合物产生不同的 聚集在一起的转录配置文件。这种方法使我们能够将化合物归类为已知的；新奇的 击中已知的目标；新奇地击中新的有价值的目标；击中不受欢迎的目标；或讨厌的目标 缺乏特异性的化合物。在一项初步研究中，我们确定产生菌株的粗提物可以 用于在测试有机体中生成转录组图谱以识别靶标，并推断存在 有潜在价值的化合物。在提议的项目中，我们将创建一个转录配置文件数据库 已知的抗菌素，开发有效的转录组分析计算工具，并将审问 来自大量提取物的转录本及其来自未培养细菌的馏分。铅分子 将在体外和动物疗效模型中进行验证。该项目的最终结果将是一项新的发现 药物开发的平台、新靶点和先导化合物。该项目是金姆与 Lewis，PD/Pi(Nu)，抗微生物药物发现和耐药性专家；Karen Nelson，联合调查员 (JCVI)，基因组学、元组学方法和计算生物学专家；艾米·斯波林，Co- 研究员(新生物)，从未培养的细菌中发现药物的专家。这些专家在 为本计划制作初步数据。

Abstract Most antibiotics resulted from the Waxman platform, screening of soil microorganisms, but this limited resource was overmined by the late 60s. In the absence of a platform, compounds are introduced slower than pathogens acquire resistance, and the result is a human health crisis. The recent President's executive order “Combating Antibiotic-Resistant Bacteria” underscores the significance of this problem. In this Program, we will develop an effective discovery program based on exploiting uncultured bacteria to resolve the bottleneck of antimicrobial drug discovery. Uncultured bacteria are an untapped source of secondary metabolites, and we developed methods to grow them and mine for antibiotic discovery. We discovered 25 new compounds from this source so far, including lassomycin, a novel compound with specific activity against the ClpP1P2C1 protease of M. tuberculosis; and teixobactin, a novel inhibitor of peptidoglycan synthesis which is essentially free of resistance development. However, the real potential of uncultured bacteria remains unrealized - the background of knowns and toxic compounds has been the main bottleneck even for this untapped source of chemical diversity. We propose to solve this problem by introducing transcriptome analysis as a rapid tool to identify promising compounds from uncultured bacteria. Compounds affecting the same target produce distinct transcription profiles that cluster together. This approach allows us to classify compounds as known; novel hitting a known target; novel hitting a new valuable target; hitting an undesirable target; or a nuisance compound lacking specificity. In a pilot study, we determined that crude extracts from producing strains can be used to generate transcriptome profiles in a test organism to identify targets, and deduce the presence of a potentially valuable compound. In the proposed project, we will create a database of transcription profiles from known antimicrobials, develop effective computational tools for transcriptome analysis, and will interrogate transcriptomes from a large number of extracts and their fractions from uncultured bacteria. Lead molecules will be validated in vitro and in an animal efficacy model. The end result of the project will be a novel discovery platform, new targets, and lead compounds for drug development. The project is a collaboration between Kim Lewis, PD/PI (NU), an expert in antimicrobial drug discovery and resistance; Karen Nelson, Co-Investigator (JCVI), an expert in genomics, meta-omics approaches and computational biology; and Amy Spoering, Co- Investigator (NovoBiotic), an expert in drug discovery from uncultured bacteria. These experts collaborated on producing preliminary data for this Program.