Centro Nacional de Biotecnología, CSIC, Darwin 3, Madrid, Spain.
Servicio de Microbiología, Hospital Universitario Ramón y Cajal (IRYCIS), Madrid, Spain.
Ann N Y Acad Sci. 2017 Jan;1388(1):26-41. doi: 10.1111/nyas.13282. Epub 2016 Nov 10.
Antibiotic resistance is a relevant problem for human health that requires global approaches to establish a deep understanding of the processes of acquisition, stabilization, and spread of resistance among human bacterial pathogens. Since natural (nonclinical) ecosystems are reservoirs of resistance genes, a health-integrated study of the epidemiology of antibiotic resistance requires the exploration of such ecosystems with the aim of determining the role they may play in the selection, evolution, and spread of antibiotic resistance genes, involving the so-called resistance mobilome. High-throughput sequencing techniques allow an unprecedented opportunity to describe the genetic composition of a given microbiome without the need to subculture the organisms present inside. However, bioinformatic methods for analyzing this bulk of data, mainly with respect to binning each resistance gene with the organism hosting it, are still in their infancy. Here, we discuss how current genomic methodologies can serve to analyze the resistance mobilome and its linkage with different bacterial genomes and metagenomes. In addition, we describe the drawbacks of current methodologies for analyzing the resistance mobilome, mainly in cases of complex microbiotas, and discuss the possibility of implementing novel tools to improve our current metagenomic toolbox.
抗生素耐药性是一个与人类健康相关的问题,需要全球采取措施,以深入了解人类细菌病原体获得、稳定和传播耐药性的过程。由于自然(非临床)生态系统是耐药基因的储库,因此将抗生素耐药性的流行病学纳入健康研究需要对这些生态系统进行探索,目的是确定它们在选择、进化和传播抗生素耐药基因方面可能发挥的作用,其中涉及所谓的耐药移动组。高通量测序技术为描述给定微生物组的遗传组成提供了前所未有的机会,而无需对存在于其中的生物体进行培养。然而,用于分析这些大量数据的生物信息学方法,主要是关于将每个耐药基因与宿主生物体进行分类,仍处于起步阶段。在这里,我们讨论了当前的基因组方法如何用于分析耐药移动组及其与不同细菌基因组和宏基因组的联系。此外,我们还描述了分析耐药移动组的当前方法的缺点,主要是在复杂微生物群的情况下,并讨论了实施新工具以改进我们当前宏基因组工具包的可能性。