Natural product antibiotics targeting Gram-negative MDR pathogens

目前迫切需要新的抗生素来对抗多重耐药性（MDR）的上升，而目前最紧迫的是鉴定抑制MDR革兰氏阴性病原体的化合物，其中几种病原体的治疗选择已经严重受限。Demuris是一家SME，拥有世界领先的放线菌细菌集合，这些放线菌细菌非常多样化，几乎没有复制品。该集合被用于识别和开发抗生素和抗真菌剂，以对抗抗菌素耐药性（AMR）的上升。通过从收集的7000多个不同的和去复制的放线菌中筛选，Demuris已经鉴定出100多个具有广谱抗菌活性的菌株，这些菌株可以抑制一组多重抗生素耐药的E。在这个项目中，Demuris将致力于对所有这些广谱抗生素生产菌株的基因组进行测序。这将使用来自Oxford-Nanopore的长读取单分子测序快速且廉价地进行。我们将创建一个内部技术平台，使用现有软件以低成本对抗生素生产细菌的基因组进行测序和生物信息学筛选。在生物信息学上预测会产生已知广谱抗生素化合物的菌株将从发现管道中删除，从而大大加快去复制过程，并迅速放大产生新型抗生素化合物的菌株。将对新型抗生素进行结构表征，并生成由微生物学和细胞毒性组成的数据包。这些数据将足以进行临床开发评价。这种基于“数据优先”的方法有望提高效率，并将允许所有资源优先用于具有最佳临床成功机会的化合物。

New antibiotics are urgently needed to combat the rise of Multi-Drug Resistance (MDR), and by far the most pressing is the identification of compounds to inhibit MDR-Gram-negative pathogens, where the treatment options for several pathogens have become severely limited.Demuris is an SME with a world-leading collection of actinomycete bacteria which are both extremely diverse and almost devoid of replicates. The collection is being used to identify and develop antibiotic and antifungal agents to combat the rise of antimicrobial resistance (AMR). Through screening >7000 diverse and dereplicated actinomycetes from the collection, Demuris has identified over 100 strains with broad-spectrum antibacterial activity that inhibit a panel of multiply antibiotic resistant E. coli strains.In this project Demuris will aim to sequence the genomes of all of these broad spectrum antibiotic producer strains. This will be performed rapidly and cheaply using long read, single molecule sequencing from Oxford-Nanopore. We will create an in-house technology platform to sequence and then bioinformatically screen the genomes of antibiotic producing bacteria at low cost using existing software. Strains bioinformatically predicted to produce known broad spectrum antibiotic compounds will be removed from the discovery pipeline, dramatically speeding up the dereplication process and zooming in rapidly on strains producing novel antibiotic compounds. Novel antibiotics will be structurally characterised and a data package consisting of microbiology and cytotoxicity will be generated. These data will be sufficient to enable evaluation for clinical development. This "data first" based approach promises to improve efficiency and will allow all resources to be prioritised on the compounds with the best chance of clinical success.