Rumi Monjura Afrin, Oh Min, Davis Benjamin C, Brown Connor L, Juvekar Adheesh, Vikesland Peter J, Pruden Amy, Zhang Liqing
Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, USA.
Microsoft Research, Redmond, 98052 WA, USA.
FEMS Microbiol Ecol. 2024 Nov 23;100(12). doi: 10.1093/femsec/fiae155.
While numerous environmental factors contribute to the spread of antibiotic resistance genes (ARGs), quantifying their relative contributions remains a fundamental challenge. Similarly, it is important to differentiate acute human health risks from environmental exposure, versus broader ecological risk of ARG evolution and spread across microbial taxa. Recent studies have proposed various methods for achieving such aims. Here, we introduce MetaCompare 2.0, which improves upon original MetaCompare pipeline by differentiating indicators of human health resistome risk (potential for human pathogens of acute resistance concern to acquire ARGs) from ecological resistome risk (overall mobility of ARGs and potential for pathogen acquisition). The updated pipeline's sensitivity was demonstrated by analyzing diverse publicly-available metagenomes from wastewater, surface water, soil, sediment, human gut, and synthetic microbial communities. MetaCompare 2.0 provided distinct rankings of the metagenomes according to both human health resistome risk and ecological resistome risk, with both scores trending higher when influenced by anthropogenic impact or other stress. We evaluated the robustness of the pipeline to sequence assembly methods, sequencing depth, contig count, and metagenomic library coverage bias. The risk scores were remarkably consistent despite variations in these technological aspects. We packaged the improved pipeline into a publicly-available web service (http://metacompare.cs.vt.edu/) that provides an easy-to-use interface for computing resistome risk scores and visualizing results.
虽然众多环境因素促成了抗生素抗性基因（ARGs）的传播，但量化它们的相对贡献仍然是一项根本性挑战。同样，区分环境暴露对人类健康的急性风险与ARGs在微生物类群中进化和传播的更广泛生态风险也很重要。最近的研究提出了各种方法来实现这些目标。在此，我们介绍MetaCompare 2.0，它在原始MetaCompare流程的基础上进行了改进，区分了人类健康抗性组风险指标（急性抗性相关人类病原体获取ARGs的可能性）和生态抗性组风险指标（ARGs的整体移动性以及病原体获取的可能性）。通过分析来自废水、地表水、土壤、沉积物、人类肠道和合成微生物群落的各种公开可用宏基因组，证明了更新后流程的敏感性。MetaCompare 2.0根据人类健康抗性组风险和生态抗性组风险对宏基因组给出了不同的排名，当受到人为影响或其他压力时，这两个分数都呈上升趋势。我们评估了该流程对序列组装方法、测序深度、重叠群数量和宏基因组文库覆盖偏差的稳健性。尽管在这些技术方面存在差异，但风险评分非常一致。我们将改进后的流程打包成一个公开可用的网络服务（http://metacompare.cs.vt.edu/），该服务提供了一个易于使用的界面来计算抗性组风险评分并可视化结果。
