Bloemen Bram, Gand Mathieu, Ringenier Moniek, Bogaerts Bert, Vanneste Kevin, Marchal Kathleen, Roosens Nancy H C, Dewulf Jeroen, Boyen Filip, De Keersmaecker Sigrid C J
Transversal Activities in Applied Genomics, Sciensano, Elsene, Belgium.
Department of Plant Biotechnology and Bioinformatics, Ghent University, Zwijnaarde, Belgium.
Front Microbiol. 2025 Jul 23;16:1614301. doi: 10.3389/fmicb.2025.1614301. eCollection 2025.
Antimicrobial resistance is an alarming public health problem, and comprehensive surveillance across environments is required to reduce its impact. Phenotypic testing and whole-genome sequencing of isolates are efficient, but culture-free approaches like metagenomic sequencing potentially allow for broader investigation of resistance gene occurrence, evolution and spread. However, technical challenges such as difficulties in associating antimicrobial resistance genes with their bacterial hosts and the collapse of strain-level variation during metagenome assembly, hinder its implementation.
To illustrate how these challenges can be overcome, we applied Oxford Nanopore Technologies long-read metagenomic sequencing and novel bioinformatic methods to a case study focused on fluoroquinolone resistance in chicken fecal samples.
We demonstrate plasmid-host linking based on detecting common DNA methylation signatures. Additionally, we use new bioinformatic approaches for strain haplotyping, enabling phylogenomic comparison and uncovering fluoroquinolone resistance determining point mutations in metagenomic datasets.
We leverage long-read sequencing, including DNA methylation profiling and strain-level haplotyping, to identify antimicrobial resistance gene hosts, link plasmids to their bacterial carriers, and detect resistance-associated point mutations. Although some limitations remain, our work demonstrates how these improvements in metagenomic sequencing can enhance antimicrobial resistance surveillance.
抗菌药物耐药性是一个令人担忧的公共卫生问题,需要对各种环境进行全面监测以减少其影响。对分离株进行表型检测和全基因组测序是有效的,但像宏基因组测序这样的免培养方法有可能更广泛地研究耐药基因的出现、进化和传播。然而,诸如难以将抗菌药物耐药基因与其细菌宿主相关联以及宏基因组组装过程中菌株水平变异的崩溃等技术挑战,阻碍了其应用。
为了说明如何克服这些挑战,我们将牛津纳米孔技术的长读长宏基因组测序和新型生物信息学方法应用于一个聚焦于鸡粪便样本中氟喹诺酮耐药性的案例研究。
我们基于检测常见的DNA甲基化特征证明了质粒 - 宿主的关联。此外,我们使用新的生物信息学方法进行菌株单倍型分型,实现系统发育基因组比较并在宏基因组数据集中发现氟喹诺酮耐药性决定点突变。
我们利用长读长测序,包括DNA甲基化分析和菌株水平单倍型分型,来识别抗菌药物耐药基因宿主,将质粒与其细菌载体关联,并检测与耐药相关的点突变。尽管仍然存在一些局限性,但我们的工作展示了宏基因组测序中的这些改进如何能够加强抗菌药物耐药性监测。