Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.
J Clin Microbiol. 2020 Dec 17;59(1). doi: 10.1128/JCM.02142-20.
Broad testing for respiratory viruses among persons under investigation (PUIs) for SARS-CoV-2 has been performed inconsistently, limiting our understanding of alternative viral infections and coinfections in these patients. RNA metagenomic next-generation sequencing (mNGS) offers an agnostic tool for the detection of both SARS-CoV-2 and other RNA respiratory viruses in PUIs. Here, we used RNA mNGS to assess the frequencies of alternative viral infections in SARS-CoV-2 RT-PCR-negative PUIs ( = 30) and viral coinfections in SARS-CoV-2 RT-PCR-positive PUIs ( = 45). mNGS identified all viruses detected by routine clinical testing (influenza A [= 3], human metapneumovirus [2], and human coronavirus OC43 [2], and human coronavirus HKU1 [1]). mNGS also identified both coinfections (1, 2.2%) and alternative viral infections (4, 13.3%) that were not detected by routine clinical workup (respiratory syncytial virus [3], human metapneumovirus [1], and human coronavirus NL63 [1]). Among SARS-CoV-2 RT-PCR-positive PUIs, lower cycle threshold ( ) values correlated with greater SARS-CoV-2 read recovery by mNGS (, 0.65; < 0.001). Our results suggest that current broad-spectrum molecular testing algorithms identify most respiratory viral infections among SARS-CoV-2 PUIs, when available and implemented consistently.
对疑似 SARS-CoV-2 感染患者(PUI)进行广泛的呼吸道病毒检测一直不一致,这限制了我们对这些患者中其他病毒感染和合并感染的了解。RNA 宏基因组下一代测序(mNGS)为检测 PUI 中的 SARS-CoV-2 和其他 RNA 呼吸道病毒提供了一种无偏倚的工具。在这里,我们使用 RNA mNGS 来评估 SARS-CoV-2 RT-PCR 阴性 PUI(n=30)中替代病毒感染的频率和 SARS-CoV-2 RT-PCR 阳性 PUI(n=45)中的病毒合并感染。mNGS 鉴定了常规临床检测(甲型流感[=3]、人偏肺病毒[2]、OC43 冠状病毒[2]和 HKU1 冠状病毒[1])检测到的所有病毒。mNGS 还鉴定了常规临床检查未检测到的合并感染(1 例,2.2%)和替代病毒感染(4 例,13.3%)(呼吸道合胞病毒[3]、人偏肺病毒[1]和 NL63 冠状病毒[1])。在 SARS-CoV-2 RT-PCR 阳性 PUI 中,较低的循环阈值(Ct 值)与 mNGS 检测到更高的 SARS-CoV-2 读码恢复相关(r=0.65;P<0.001)。我们的研究结果表明,当前广泛的分子检测算法可以识别大多数 SARS-CoV-2 PUI 中的呼吸道病毒感染,当可用且一致实施时。