{"title":"纳米孔适应性采样可富集微生物群落中的抗菌药耐药性基因。","authors":"Danielle C Wrenn, Devin M Drown","doi":"10.46471/gigabyte.103","DOIUrl":null,"url":null,"abstract":"<p><p>Antimicrobial resistance (AMR) is a global public health threat. Environmental microbial communities act as reservoirs for AMR, containing genes associated with resistance, their precursors, and the selective pressures promoting their persistence. Genomic surveillance could provide insights into how these reservoirs change and impact public health. Enriching for AMR genomic signatures in complex microbial communities would strengthen surveillance efforts and reduce time-to-answer. Here, we tested the ability of nanopore sequencing and adaptive sampling to enrich for AMR genes in a mock community of environmental origin. Our setup implemented the MinION mk1B, an NVIDIA Jetson Xavier GPU, and Flongle flow cells. Using adaptive sampling, we observed consistent enrichment by composition. On average, adaptive sampling resulted in a target composition 4× higher than without adaptive sampling. Despite a decrease in total sequencing output, adaptive sampling increased target yield in most replicates. We also demonstrate enrichment in a diverse community using an environmental sample. This method enables rapid and flexible genomic surveillance.</p>","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2023 ","pages":"gigabyte103"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10726737/pdf/","citationCount":"0","resultStr":"{\"title\":\"Nanopore adaptive sampling enriches for antimicrobial resistance genes in microbial communities.\",\"authors\":\"Danielle C Wrenn, Devin M Drown\",\"doi\":\"10.46471/gigabyte.103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Antimicrobial resistance (AMR) is a global public health threat. Environmental microbial communities act as reservoirs for AMR, containing genes associated with resistance, their precursors, and the selective pressures promoting their persistence. Genomic surveillance could provide insights into how these reservoirs change and impact public health. Enriching for AMR genomic signatures in complex microbial communities would strengthen surveillance efforts and reduce time-to-answer. Here, we tested the ability of nanopore sequencing and adaptive sampling to enrich for AMR genes in a mock community of environmental origin. Our setup implemented the MinION mk1B, an NVIDIA Jetson Xavier GPU, and Flongle flow cells. Using adaptive sampling, we observed consistent enrichment by composition. On average, adaptive sampling resulted in a target composition 4× higher than without adaptive sampling. Despite a decrease in total sequencing output, adaptive sampling increased target yield in most replicates. We also demonstrate enrichment in a diverse community using an environmental sample. This method enables rapid and flexible genomic surveillance.</p>\",\"PeriodicalId\":73157,\"journal\":{\"name\":\"GigaByte (Hong Kong, China)\",\"volume\":\"2023 \",\"pages\":\"gigabyte103\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10726737/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GigaByte (Hong Kong, China)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46471/gigabyte.103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GigaByte (Hong Kong, China)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46471/gigabyte.103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
抗菌药耐药性(AMR)是对全球公共卫生的威胁。环境微生物群落是 AMR 的储存库,其中包含与耐药性相关的基因、其前体以及促进其持续存在的选择性压力。基因组监测可以帮助人们深入了解这些贮藏库是如何变化并影响公共卫生的。在复杂的微生物群落中丰富 AMR 基因组特征将加强监测工作并缩短回复时间。在这里,我们测试了纳米孔测序和自适应采样在环境源模拟群落中富集 AMR 基因的能力。我们的装置采用了 MinION mk1B、英伟达 Jetson Xavier GPU 和 Flongle 流动池。利用自适应采样,我们观察到了一致的成分富集。平均而言,自适应采样的目标成分比不使用自适应采样时高 4 倍。尽管测序总输出量有所下降,但在大多数重复中,自适应采样提高了目标产量。我们还利用环境样本展示了多样化群落的富集情况。这种方法可以实现快速灵活的基因组监测。
Nanopore adaptive sampling enriches for antimicrobial resistance genes in microbial communities.
Antimicrobial resistance (AMR) is a global public health threat. Environmental microbial communities act as reservoirs for AMR, containing genes associated with resistance, their precursors, and the selective pressures promoting their persistence. Genomic surveillance could provide insights into how these reservoirs change and impact public health. Enriching for AMR genomic signatures in complex microbial communities would strengthen surveillance efforts and reduce time-to-answer. Here, we tested the ability of nanopore sequencing and adaptive sampling to enrich for AMR genes in a mock community of environmental origin. Our setup implemented the MinION mk1B, an NVIDIA Jetson Xavier GPU, and Flongle flow cells. Using adaptive sampling, we observed consistent enrichment by composition. On average, adaptive sampling resulted in a target composition 4× higher than without adaptive sampling. Despite a decrease in total sequencing output, adaptive sampling increased target yield in most replicates. We also demonstrate enrichment in a diverse community using an environmental sample. This method enables rapid and flexible genomic surveillance.