Benchmarking of Antimicrobial Resistance Gene Detection Tools in Assembled Bacterial Whole Genomes

E. Abdelrazik, Mariam Oweda, M. El-Hadidi
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引用次数: 1

Abstract

Antimicrobial resistance (AMR) is one of the ten dangers threatening our world, according to the world health organization (WHO). Nowadays, there are plenty of electronic microbial genomics and metagenomics data records that represent host-associated microbiomes. These data introduce new insights and a comprehensive understanding of the current antibiotic resistance threats and the upcoming resistance outbreak. Many bioinformatics tools have been developed to detect the AMR genes based on different annotated databases of bacterial whole genome sequences (WGS). The number and structure of databases used may affect prediction quality. Herein, we aim to check the performance of four AMR gene detection tools and characterize the detection quality by comparing predicted results to reference antibiotic susceptibility test (AST) data. This may enhance the precise in-silico prediction of resistance phenotype and reduce false-positive predictions, which lead to more biologically relevant results. Four AMR gene detection tools; AMRFinder, ABRicate, ResFinder, and SraX are used for the benchmarking using Salmonella enterica isolates (n=104) retrieved from National Center for Biotechnology Information (NCBI) Assembly Database in July 2021. Performance is checked in terms of accuracy, precision, and specificity for each tool. Pearson x2 test is used to compare predicted results with antibiotic susceptibility testing (true results). All performance measures are assessed via scikit-learn package 0.21.3 and R software V 4.0.3. The highest accuracy was achieved by AMRFinder (0.89), while ResFinder had the highest precision score (0.93) and ABRicate has the lowest time and memory consumption. On the other hand, ResFinder's results confirmed the null hypothesis of the Pearson x2 test. We conclude that ResFinder is the best tool where its results have the tiniest difference compared to the phenotypic antibiotic susceptibility (true results).
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组装细菌全基因组耐药基因检测工具的标杆研究
根据世界卫生组织(WHO)的报告,抗菌素耐药性(AMR)是威胁我们世界的十大危险之一。目前,已有大量代表宿主相关微生物组的电子微生物基因组学和宏基因组学数据记录。这些数据提供了对当前抗生素耐药性威胁和即将发生的耐药性暴发的新见解和全面理解。基于不同的细菌全基因组序列(WGS)注释数据库,已经开发了许多生物信息学工具来检测AMR基因。所用数据库的数量和结构可能会影响预测质量。在此,我们的目的是检查四种AMR基因检测工具的性能,并通过将预测结果与参考抗生素敏感性试验(AST)数据进行比较来表征检测质量。这可能会提高耐药表型的精确计算机预测,减少假阳性预测,从而导致更多生物学相关的结果。四种AMR基因检测工具;使用AMRFinder、ABRicate、ResFinder和SraX对2021年7月从国家生物技术信息中心(NCBI)组装数据库检索的肠沙门氏菌分离株(n=104)进行基准测试。根据每个工具的准确性、精密度和特异性来检查性能。使用Pearson x2检验比较预测结果与抗生素药敏试验(真实结果)。所有性能指标均通过scikit-learn软件包0.21.3和R软件v4.0.3进行评估。AMRFinder的准确率最高(0.89),ResFinder的准确率最高(0.93),ABRicate的时间和内存消耗最低。另一方面,ResFinder的结果证实了Pearson x2检验的零假设。我们的结论是,ResFinder是最好的工具,其结果与表型抗生素敏感性(真实结果)相比差异最小。
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