Suppr超能文献

SYN-View:一种基于系统发育的基因共线性探索工具,用于鉴定与抗生素耐药性相关的基因簇。

SYN-View: A Phylogeny-Based Synteny Exploration Tool for the Identification of Gene Clusters Linked to Antibiotic Resistance.

机构信息

Interfaculty Institute of Microbiology and Infection Medicine, University of Tübingen, Auf der Morgenstelle 28, 72076 Tübingen, Germany.

German Centre for Infection Research (DZIF), Partner Site Tübingen, 38124 Tübingen, Germany.

出版信息

Molecules. 2020 Dec 31;26(1):144. doi: 10.3390/molecules26010144.

Abstract

The development of new antibacterial drugs has become one of the most important tasks of the century in order to overcome the posing threat of drug resistance in pathogenic bacteria. Many antibiotics originate from natural products produced by various microorganisms. Over the last decades, bioinformatical approaches have facilitated the discovery and characterization of these small compounds using genome mining methodologies. A key part of this process is the identification of the most promising biosynthetic gene clusters (BGCs), which encode novel natural products. In 2017, the Antibiotic Resistant Target Seeker (ARTS) was developed in order to enable an automated target-directed genome mining approach. ARTS identifies possible resistant target genes within antibiotic gene clusters, in order to detect promising BGCs encoding antibiotics with novel modes of action. Although ARTS can predict promising targets based on multiple criteria, it provides little information about the cluster structures of possible resistant genes. Here, we present SYN-view. Based on a phylogenetic approach, SYN-view allows for easy comparison of gene clusters of interest and distinguishing genes with regular housekeeping functions from genes functioning as antibiotic resistant targets. Our aim is to implement our proposed method into the ARTS web-server, further improving the target-directed genome mining strategy of the ARTS pipeline.

摘要

为了克服病原菌耐药性带来的威胁,开发新的抗菌药物已成为本世纪最重要的任务之一。许多抗生素源自各种微生物产生的天然产物。在过去的几十年中,生物信息学方法通过基因组挖掘方法促进了这些小分子化合物的发现和特性描述。该过程的一个关键部分是确定最有前途的生物合成基因簇(BGCs),这些基因簇编码新型天然产物。为了实现自动化的靶向基因组挖掘方法,2017 年开发了抗生素耐药性靶标搜索器(ARTS)。ARTS 确定抗生素基因簇内可能的耐药靶基因,以检测具有新型作用模式的有前途的 BGCs 编码的抗生素。尽管 ARTS 可以根据多个标准预测有前途的靶标,但它几乎没有提供有关可能的耐药基因簇结构的信息。在这里,我们介绍了 SYN-view。基于系统发育方法,SYN-view 允许轻松比较感兴趣的基因簇,并区分具有常规管家功能的基因和作为抗生素耐药性靶标的基因。我们的目标是将我们提出的方法集成到 ARTS 网络服务器中,进一步改进 ARTS 管道的靶向基因组挖掘策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8814/7795190/eedf7b4681de/molecules-26-00144-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验