摘要

       了解哪些/如何抗生素抗性基因 (ARG) 有助于增加水生环境中病原体获得的抗性是具有深远意义的挑战。我们探讨了市政污水污泥消化器中 ARG 和人类细菌病原体 (HBP) 的共存和去除与富集。我们将广泛的 323 个 ARG 和 83 个 HBP 的宏基因组检测与基于相关性的统计方法相结合，并绘制了它们共现关系的网络。结果表明，大多数 ARGs 和一小部分 HBPs（主要是产气柯林斯菌、唾液链球菌和支气管高登菌）不能通过厌氧消化去除，揭示了消化后污泥传播抗生素耐药性和致病性的生物风险。此外，在一种 ARG 类型（例如，多药、β-内酰胺和氨基糖苷类）内和两种不同的 ARG 类型（即，氨基糖苷类和 β-内酰胺）之间，优先共现模式是明显的，这可能暗示抗生素选择压力的共同作用和协同抗性形成污水污泥中的抗生素抗性组。与β-内酰胺抗性基因不同，多药和大环内酯-林可酰胺-链球菌素的ARGs倾向于与HBPs更多地同时发生。引人注目的是，我们提供了证据表明 ARG 物种共发生事件的最直接的生物学起源是宿主关系。此外，显着且稳健的 HBP 物种共生相关性为提名 HBP 指标提供了适当的场景（例如，双歧杆菌属是 C. aerofaciens 的完美指标；r = 0.92–0.99 和 P 值 < 0.01）。结合起来，这项研究展示了一种创造性和有效的基于网络的宏基因组方法，用于探索 ARG 宿主和 HBP 指标，并评估 HBP 在 ARG 和 HBP 可能共同繁荣的人类影响环境中获得的 ARG。

       Understanding which/how antibiotic resistance genes (ARGs) contribute to increased acquisition of resistance by pathogens in aquatic environments are challenges of profound significance. We explored the co-occurrence and removal versus enrichment of ARGs and human bacterial pathogens (HBPs) in municipal sewage sludge digesters. We combined metagenomic detection of a wide spectrum of 323 ARGs and 83 HBPs with a correlation-based statistical approach and charted a network of their co-occurrence relationships. The results indicate that most ARGs and a minor proportion of HBPs (mainly Collinsella aerofaciens, Streptococcus salivarius and Gordonia bronchialis) could not be removed by anaerobic digestion, revealing a biological risk of post-digestion sludge in disseminating antibiotic resistance and pathogenicity. Moreover, preferential co-occurrence patterns were evident within one ARG type (e.g., multidrug, beta-lactam, and aminoglycoside) and between two different ARG types (i.e., aminoglycoside and beta-lactam), possibly implicating co-effects of antibiotic selection pressure and co-resistance on shaping antibiotic resistome in sewage sludge. Unlike beta-lactam resistance genes, ARGs of multidrug and macrolide-lincosamide-streptogramin tended to co-occur more with HBPs. Strikingly, we presented evidence that the most straightforward biological origin of an ARG-species co-occurring event is a hosting relationship. Furthermore, a significant and robust HBP-species co-occurrence correlation provides a proper scenario for nominating HBP indicators (e.g., Bifidobacterium spp. are perfect indicators of C. aerofaciens; r = 0.92–0.99 and P-values < 0.01). Combined, this study demonstrates a creative and effective network-based metagenomic approach for exploring ARG hosts and HBP indicators and assessing ARGs acquisition by HBPs in human-impacted environments where ARGs and HBPs may co-thrive.

https://www.sciencedirect.com/science/article/abs/pii/S0043135415303973