Pierce Amanda A, de Man Tom J B
Department of Biology, University of North Carolina, Chapel Hill, NC 27599 USA.
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
J Biol Educ. 2019;53(2):150-156. doi: 10.1080/00219266.2018.1447003. Epub 2018 Mar 9.
The evolution of resistance to antibiotics provides a timely and relevant topic for teaching undergraduate students evolutionary biology. Here, we present a module incorporating modified sequencing data from eight antibiotic resistant pathogen outbreaks in hospital settings with bioinformatics and phylogenetic analyses. This module uses whole genome sequencing data from hospital outbreaks investigated by the Centers for Disease Control and Prevention to provide examples of antibiotic resistance spread. Students work in groups to analyze outbreak data to identify the bacterial species and antibiotic resistance genes, to infer a phylogenetic tree examining relatedness among isolates, and to determine a possible source of the outbreak. Students then compile their results in individual reports and provide recommendations for preventing the further spread of antibiotic resistant organisms. In addition to providing genomic outbreak data, we include a teaching concepts guide discussing three integral components of the module: how evolutionary biology concepts of natural selection and competition impact antibiotic resistance; outbreak investigation information to aid in phylogenetic analysis and creation of recommendations; and instructions for the bioinformatics protocol. Completion of this module provides students an opportunity to think critically about the evolution of resistance, practice bioinformatics techniques, and relate evolutionary biology to current events.
抗生素耐药性的演变是为本科生教授进化生物学的一个适时且相关的主题。在此,我们展示一个模块,该模块将来自医院环境中八起抗生素耐药病原体爆发事件的经过修改的测序数据与生物信息学及系统发育分析相结合。这个模块使用了疾病控制与预防中心调查的医院爆发事件的全基因组测序数据,以提供抗生素耐药性传播的实例。学生们分组分析爆发数据,以识别细菌种类和抗生素耐药基因,推断一棵考察分离株之间亲缘关系的系统发育树,并确定爆发的可能源头。然后,学生们将他们的结果整理成个人报告,并为防止抗生素耐药生物的进一步传播提供建议。除了提供基因组爆发数据外,我们还包括一份教学概念指南,讨论该模块的三个重要组成部分:自然选择和竞争的进化生物学概念如何影响抗生素耐药性;有助于系统发育分析和提出建议的爆发调查信息;以及生物信息学方案的说明。完成这个模块为学生提供了一个批判性思考耐药性进化、实践生物信息学技术以及将进化生物学与当前事件联系起来的机会。