Ogunleye Akinlabi Oladele, Ghosh Prakash, Gueye Adja Bousso, Jemilehin Foluke Olajumoke, Okunlade Adelekan Oluseyi, Ogunleye Veronica Olatimbo, Kobialka Rea Maja, Rausch Finja, Tanneberger Franziska, Ajuwape Adebowale Titilayo Philip, Sow Ousmane, Ademowo George Olusegun, Binsker Ulrike, Abd El Wahed Ahmed, Truyen Uwe, Dieye Yakhya, Fall Cheikh
Department of Veterinary Microbiology, Faculty of Veterinary Medicine, University of Ibadan, Ibadan 200001, Nigeria.
Institute for Animal Hygiene and Veterinary Public Health, Leipzig University, 04103 Leipzig, Germany.
Antibiotics (Basel). 2025 Aug 14;14(8):827. doi: 10.3390/antibiotics14080827.
Despite the huge burden of deaths associated with or attributable to antimicrobial resistance, studies on sequencing based antimicrobial resistance (AMR) monitoring in Africa are scarce, specifically in the animal sector. Objective and Methods: With a view to deploy rapid AMR monitoring through leveraging advanced technologies, in the current study, nanopore sequencing was performed with 10 strains isolated from rectal swabs of pigs and poultry layers in Nigeria. Two sequence analysis methods including command line, where bacterial genomes were assembled, and subsequently antimicrobial resistance genes (ARGs) were detected through online databases, and EPI2ME, an integrated cloud-based data analysis platform with MinION, was used to detect ARGs. A total of 95 ARGs were identified and most of the genes are known to be expressed in the chromosome. Interestingly, few genes including , , , , , , and were identified which were previously reported as transferred through Mobile Genetic Elements (MGEs). The antibiotic susceptibility assay determined that the isolates were resistant to Penicillin (100%), Ciprofloxacin (70%), tetracycline (50%) and Ampicillin (40%). The accuracies of the command line and EPI2ME methods have been found to be 57.14% and 32.14%, respectively, in predicting AMR. Moreover, the analysis methods showed 62.5% agreement in predicting AMR for the isolates. Conclusions: Considering the multiple advantages of nanopore sequencing, the application of this rapid and field-feasible sequencing technique holds promise for rapid AMR monitoring in low- and middle-income countries (LMICs), including Nigeria. However, the development of a robust sequence analysis pipeline and the optimization of the existing analysis tools are crucial to streamline the deployment of nanopore sequencing in LMICs for AMR monitoring both in animal and human sectors.
尽管与抗菌药物耐药性相关或可归因于抗菌药物耐药性的死亡负担巨大，但在非洲，特别是在动物领域，基于测序的抗菌药物耐药性（AMR）监测研究却很少。目的和方法：为了通过利用先进技术进行快速AMR监测，在本研究中，对从尼日利亚猪和蛋鸡直肠拭子中分离出的10株菌株进行了纳米孔测序。使用了两种序列分析方法，包括命令行方法（其中组装细菌基因组，随后通过在线数据库检测抗菌药物耐药基因（ARGs））和EPI2ME（一个与MinION集成的基于云的数据分析平台）来检测ARGs。共鉴定出95个ARGs，其中大多数基因已知在染色体中表达。有趣的是，鉴定出了少数几个基因，包括[此处原文缺失具体基因名称]，这些基因先前被报道是通过移动遗传元件（MGEs）转移的。抗生素敏感性试验确定这些分离株对青霉素（100%）、环丙沙星（70%）、四环素（50%）和氨苄青霉素（40%）耐药。在预测AMR方面，已发现命令行方法和EPI2ME方法的准确率分别为57.14%和32.14%。此外，分析方法在预测这些分离株的AMR方面显示出62.5%的一致性。结论：考虑到纳米孔测序的多重优势，这种快速且适用于现场的测序技术在包括尼日利亚在内的低收入和中等收入国家（LMICs）进行快速AMR监测方面具有前景。然而，如果要在LMICs的动物和人类领域简化纳米孔测序用于AMR监测的部署，开发强大的序列分析流程和优化现有分析工具至关重要。
