摘要

       我们的目的是比较Bowtie2，bwa mem，blastn和blastx在将细菌基因组与综合抗药性数据库（CARD）比对时的表现。在以下四个性能标准下，使用模拟读取来评估每个对齐器的性能：正确映射、误报、多读取和部分读取。将优化的比对方法应用于两个污水处理厂的样品，利用下一代测序法检测抗生素耐药基因。在Bowtie2所考虑的四种序列比对方法中，blastn映射的精度更高。blastx在与卡对齐时产生最多的误报和多次读取。使用无错误读取对每种对准工具的性能进行了研究。尽管与Illumina错误读取相比，每个校准器映射了更多的无错误读取，但通常，在与卡对齐时，引入排序错误对对齐结果的影响很小。考虑到每种性能标准，blastn被认为是最有利的比对工具，因此被用于评估污水样本中的抗性基因。在每个样本中，β-内酰胺和氨基糖苷是最丰富的抗生素耐药基因。
        研究的意义和影响：
        抗生素抗性基因（ARGs）是已知存在于污水处理厂等环境中的污染物，因此检测这些基因的方法变得越来越重要。下一代测序带来了一系列的序列比对工具，可以全面调查环境样品中的抗微生物性。然而，精氨酸亚基因组研究中的标准化实践具有挑战性，因为校准工具产生的结果可能有很大差异。我们的研究提供了合成的、真实的细菌基因组的序列比对结果，并使用多种比对工具对ARG数据库进行了比对，同时也提供了检测环境样品中ARG的最佳实践。

We aim to compare the performance of Bowtie2, bwa-mem, blastn and blastx when aligning bacterial metagenomes against the Comprehensive Antibiotic Resistance Database (CARD). Simulated reads were used to evaluate the performance of each aligner under the following four performance criteria: correctly mapped, false positives, multi-reads and partials. The optimal alignment approach was applied to samples from two wastewater treatment plants to detect antibiotic resistance genes using next generation sequencing. blastn mapped with greater accuracy among the four sequence alignment approaches considered followed by Bowtie2. blastx generated the greatest number of false positives and multi-reads when aligned against the CARD. The performance of each alignment tool was also investigated using error-free reads. Although each aligner mapped a greater number of error-free reads as compared to Illumina-error reads, in general, the introduction of sequencing errors had little effect on alignment results when aligning against the CARD. Given each performance criteria, blastn was found to be the most favourable alignment tool and was therefore used to assess resistance genes in sewage samples. Beta-lactam and aminoglycoside were found to be the most abundant classes of antibiotic resistance genes in each sample.

SIGNIFICANCE AND IMPACT OF THE STUDY:

Antibiotic resistance genes (ARGs) are pollutants known to persist in wastewater treatment plants among other environments, thus methods for detecting these genes have become increasingly relevant. Next generation sequencing has brought about a host of sequence alignment tools that provide a comprehensive look into antimicrobial resistance in environmental samples. However, standardizing practices in ARG metagenomic studies is challenging since results produced from alignment tools can vary significantly. Our study provides sequence alignment results of synthetic, and authentic bacterial metagenomes mapped against an ARG database using multiple alignment tools, and the best practice for detecting ARGs in environmental samples.

       https://sfamjournals.onlinelibrary.wiley.com/doi/abs/10.1111/lam.12842