摘要

随着多重抗药性病原体的出现以及开发中潜在的新抗生素数量的减少，迫切需要重振天然产品发现渠道。大多数抗生素来源于微生物和植物产生的次生代谢产物。为了避免自杀，抗生素生产者携带通常在负责生产抗生素的相同生物合成基因簇（BGC）内发现的抗性基因。现有的挖掘工具在检测BGCs或抗性基因方面非常出色，但对优先和识别针对特定和新靶点的化合物的基因簇没有多大帮助。在这里，我们介绍https://arts.ziemertlab.com上提供的“抗生素抗性目标搜索者”（ARTS）。 ARTS允许针对具有有趣和新颖目标的抗生素进行特异性和高效的基因组挖掘。这个网络服务器的目的是自动筛选大量的序列数据，并将重点放在以最新的作用模式生产抗生素的最有希望的菌株上。 ARTS整合了靶向定向基因组挖掘方法，抗生素基因簇预测和'基本基因筛选'，为快速识别BGC中已知和假定的靶点提供了交互式页面。

With the rise of multi-drug resistant pathogens and the decline in number of potential new antibiotics in development there is a fervent need to reinvigorate the natural products discovery pipeline. Most antibiotics are derived from secondary metabolites produced by microorganisms and plants. To avoid suicide, an antibiotic producer harbors resistance genes often found within the same biosynthetic gene cluster (BGC) responsible for manufacturing the antibiotic. Existing mining tools are excellent at detecting BGCs or resistant genes in general, but provide little help in prioritizing and identifying gene clusters for compounds active against specific and novel targets. Here we introduce the ‘Antibiotic Resistant Target Seeker’ (ARTS) available athttps://arts.ziemertlab.com. ARTS allows for specific and efficient genome mining for antibiotics with interesting and novel targets. The aim of this web server is to automate the screening of large amounts of sequence data and to focus on the most promising strains that produce antibiotics with new modes of action. ARTS integrates target directed genome mining methods, antibiotic gene cluster predictions and ‘essential gene screening’ to provide an interactive page for rapid identification of known and putative targets in BGCs.