The rise of antimicrobial-resistant Neisseria gonorrhoeae is a significant public health concern. Against this background, rapid culture-independent diagnostics may allow targeted treatment and prevent onward transmission. We have previously shown metagenomic sequencing of urine samples from men with urethral gonorrhea can recover near-complete N. gonorrhoeae genomes. However, disentangling the N. gonorrhoeae genome from metagenomic samples and robustly identifying antimicrobial resistance determinants from error-prone Nanopore sequencing is a substantial bioinformatics challenge. Here, we show an N. gonorrhoeae diagnostic workflow for analysis of metagenomic sequencing data obtained from clinical samples using R9.4.1 Nanopore sequencing. We compared results from simulated and clinical infections with data from known reference strains and Illumina sequencing of isolates cultured from the same patients. We evaluated three Nanopore variant callers and developed a random forest classifier to filter called SNPs. Clair was the most suitable variant caller after SNP filtering. A minimum depth of 20× reads was required to confidently identify resistant determinants over the entire genome. Our findings show that metagenomic Nanopore sequencing can provide reliable diagnostic information in N. gonorrhoeae infection.

中文翻译：

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宏基因组纳米孔测序的高精度淋病奈瑟菌变异和抗菌素耐药性调用。

耐药性淋病奈瑟菌的兴起是一个重大的公共卫生问题。在此背景下，不依赖培养的快速诊断可能允许有针对性的治疗并防止进一步传播。我们之前已经表明，对患有尿道淋病的男性尿液样本进行宏基因组测序可以恢复近乎完整的淋病奈瑟菌基因组。然而，从宏基因组样本中解开淋病奈瑟菌基因组并从容易出错的纳米孔测序中可靠地识别抗菌素耐药性决定因素是一项重大的生物信息学挑战。在这里，我们展示了淋病奈瑟菌使用 R9.4.1 纳米孔测序分析从临床样本中获得的宏基因组测序数据的诊断工作流程。我们将模拟和临床感染的结果与已知参考菌株的数据和从同一患者培养的分离株的 Illumina 测序数据进行了比较。我们评估了三个 Nanopore 变体调用者并开发了一个随机森林分类器来过滤称为 SNP。Clair 是 SNP 过滤后最合适的变异调用者。需要至少 20 倍读数的深度才能自信地识别整个基因组的抗性决定簇。我们的研究结果表明宏基因组纳米孔测序可以为淋病奈瑟菌感染提供可靠的诊断信息。