Suppr超能文献

利用碱基组成分析鉴定和表征致病性及其他基因组岛

Identification and characterization of pathogenicity and other genomic islands using base composition analyses.

作者信息

Guy Lionel

机构信息

Département de Microbiologie Fondamentale, Faculté de Biologie et Médecine, Université de Lausanne, Switzerland.

出版信息

Future Microbiol. 2006 Oct;1(3):309-16. doi: 10.2217/17460913.1.3.309.

Abstract

Pathogenicity islands (PAIs) are major factors contributing to the pathogenicity of bacteria and to their resistance to antibiotics. In general, genomic islands (GIs), of which PAIs are a subset, increase the fitness of their hosts by providing new functions. With the number of available whole genome sequences growing exponentially, in silico methods have been developed to detect putative PAIs and GIs within them. Compositional methods rely on G+C content differences, codon usage and oligonucleotide biases. Other methods detect the presence of functional elements such as tRNA and mobility genes. Future availability of fast, high-throughput, inexpensive genome sequencing emphasizes the need for user-friendly applications able to detect, characterize and analyze putative GIs and PAIs. It may uncover new aspects of pathogenicity and provide better understanding of the evolution of pathogenic bacteria. These methods will be highly requested when whole genome sequencing technologies will be used by physicians for personal diagnosis.

摘要

致病岛(PAIs)是导致细菌致病性及其对抗生素耐药性的主要因素。一般来说,基因组岛(GIs)(PAIs是其一个子集)通过提供新功能来提高宿主的适应性。随着可用全基因组序列数量呈指数增长,已开发出计算机方法来检测其中假定的PAIs和GIs。组成方法依赖于G+C含量差异、密码子使用和寡核苷酸偏好。其他方法则检测tRNA和移动基因等功能元件的存在。未来快速、高通量、低成本的基因组测序技术的应用,凸显了对能够检测、表征和分析假定的GIs和PAIs的用户友好型应用程序的需求。这可能会揭示致病性的新方面,并更好地理解病原菌的进化。当医生将全基因组测序技术用于个人诊断时,这些方法将有很高的需求。

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