Antimicrobial resistance (AMR) poses a global human and animal health threat, and predicting AMR persistence and transmission remains an intractable challenge. Shotgun metagenomic sequencing can help overcome this by enabling characterization of AMR genes within all bacterial taxa, most of which are uncultivatable in laboratory settings. Shotgun sequencing, therefore, provides a more comprehensive glance at AMR “potential” within samples, i.e., the “resistome.” However, the risk inherent within a given resistome is predicated on the genomic context of various AMR genes, including their presence within mobile genetic elements (MGEs). Therefore, resistome risk stratification can be advanced if AMR profiles are considered in light of the flanking mobilizable genomic milieu (e.g., plasmids, integrative conjugative elements (ICEs), phages, and other MGEs). Because such mediators of horizontal gene transfer (HGT) are involved in uptake by pathogens, investigators are increasingly interested in characterizing that resistome fraction in genomic proximity to HGT mediators, i.e., the “mobilome”; we term this “colocalization.” We explored the utility of common colocalization approaches using alignment- and assembly-based techniques, on clinical (human) and agricultural (cattle) fecal metagenomes, obtained from antimicrobial use trials. Ordination revealed that tulathromycin-treated cattle experienced a shift in ICE and plasmid composition versus untreated animals, though the resistome was unaffected during the monitoring period. Contrarily, the human resistome and mobilome composition both shifted shortly after antimicrobial administration, though this rebounded to pre-treatment status. Bayesian networks revealed statistical AMR-MGE co-occurrence in 19 and 2% of edges from the cattle and human networks, respectively, suggesting a putatively greater mobility potential of AMR in cattle feces. Conversely, using Mobility Index (MI) and overlap analysis, abundance of de novo-assembled contigs supporting resistomes flanked by MGE increased shortly post-exposure within human metagenomes, though > 40 days after peak dose such contigs were rare (∼2%). MI was not substantially altered by antimicrobial exposure across all cattle metagenomes, ranging 0.5–4.0%. We highlight that current alignment- and assembly-based methods estimating resistome mobility yield contradictory and incomplete results, likely constrained by approach-specific data inputs, and bioinformatic limitations. We discuss recent laboratory and computational advancements that may enhance resistome risk analysis in clinical, regulatory, and commercial applications.

抗菌素耐药性（AMR）构成了全球人类和动物健康的威胁，预测AMR的持久性和传播仍然是一个棘手的挑战。gun弹枪宏基因组测序可通过表征所有细菌类群中的AMR基因来帮助克服这一问题，其中大多数细菌在实验室环境中无法培养。因此，弹枪测序可以更全面地浏览样品中的AMR“电势”，即“电阻组”。但是，给定抵抗系统固有的风险取决于各种AMR基因的基因组背景，包括它们在移动遗传元件（MGE）中的存在。因此，如果根据侧面可动员的基因组环境（例如质粒，整合结合元件（ICE），噬菌体，和其他MGE）。由于这种水平基因转移（HGT）介体参与病原体的吸收，因此研究人员越来越感兴趣的是表征抗基因组片段在基因组上与HGT介体（即“运动组”）相近。我们称之为“共本地化”。我们探索了使用基于比对和组装的技术在临床（人类）和农业（牛）粪便的基因组学中常见的共定位方法的实用性，这些方法是从抗菌药物使用试验中获得的。整理显示，与未处理的动物相比，经图拉霉素处理的牛的ICE和质粒组成发生了变化，尽管在监测期内电阻组未受影响。相反，在服用抗微生物剂后不久，人体抵抗力和运动能力的组成都发生了变化，尽管这种作用反弹到了治疗前的状态。贝叶斯网络揭示了牛和人网络中分别有19％和2％的边缘发生统计性AMR-MGE共存，这表明AMR在牛粪中的潜在移动性更大。相反，使用移动性指数（MI）和重叠分析，从头虽然在峰值剂量后> 40天，这种重叠群很少见（〜2％），但在人的基因组中暴露后不久，支持MGE侧翼的反汇编的重叠群就增加了。在所有牛的基因组中，抗菌素暴露并未显着改变心梗，幅度在0.5％至4.0％之间。我们着重指出，当前基于对准和组装的估计电阻组活动性的方法产生矛盾和不完整的结果，这可能受到特定于方法的数据输入和生物信息学限制的约束。我们讨论了最新的实验室和计算进展，这些进展可能会增强在临床，法规和商业应用中的抵抗力风险分析。