PDF(Pubmed)
Abstract：
BACKGROUND: Infectious meningitis/encephalitis (IM) is a severe neurological disease that can be caused by bacterial, viral, and fungal pathogens. IM suffers high morbidity, mortality, and sequelae in childhood. Metagenomic next-generation sequencing (mNGS) can potentially improve IM outcomes by sequencing both pathogen and host responses and increasing the diagnosis accuracy.
METHODS: Here we developed an optimized mNGS pipeline named comprehensive mNGS (c-mNGS) to monitor DNA/RNA pathogens and host responses simultaneously and applied it to 142 cerebrospinal fluid samples. According to retrospective diagnosis, these samples were classified into three categories: confirmed infectious meningitis/encephalitis (CIM), suspected infectious meningitis/encephalitis (SIM), and noninfectious controls (CTRL).
RESULTS: Our pipeline outperformed conventional methods and identified RNA viruses such as Echovirus E30 and etiologic pathogens such as HHV-7, which would not be clinically identified via conventional methods. Based on the results of the c-mNGS pipeline, we successfully detected antibiotic resistance genes related to common antibiotics for treating Escherichia coli, Acinetobacter baumannii, and Group B Streptococcus. Further, we identified differentially expressed genes in hosts of bacterial meningitis (BM) and viral meningitis/encephalitis (VM). We used these genes to build a machine-learning model to pinpoint sample contaminations. Similarly, we also built a model to predict poor prognosis in BM.
CONCLUSIONS: This study developed an mNGS-based pipeline for IM which measures both DNA/RNA pathogens and host gene expression in a single assay. The pipeline allows detecting more viruses, predicting antibiotic resistance, pinpointing contaminations, and evaluating prognosis. Given the comparable cost to conventional mNGS, our pipeline can become a routine test for IM.
METHODS: Here we developed an optimized mNGS pipeline named comprehensive mNGS (c-mNGS) to monitor DNA/RNA pathogens and host responses simultaneously and applied it to 142 cerebrospinal fluid samples. According to retrospective diagnosis, these samples were classified into three categories: confirmed infectious meningitis/encephalitis (CIM), suspected infectious meningitis/encephalitis (SIM), and noninfectious controls (CTRL).
RESULTS: Our pipeline outperformed conventional methods and identified RNA viruses such as Echovirus E30 and etiologic pathogens such as HHV-7, which would not be clinically identified via conventional methods. Based on the results of the c-mNGS pipeline, we successfully detected antibiotic resistance genes related to common antibiotics for treating Escherichia coli, Acinetobacter baumannii, and Group B Streptococcus. Further, we identified differentially expressed genes in hosts of bacterial meningitis (BM) and viral meningitis/encephalitis (VM). We used these genes to build a machine-learning model to pinpoint sample contaminations. Similarly, we also built a model to predict poor prognosis in BM.
CONCLUSIONS: This study developed an mNGS-based pipeline for IM which measures both DNA/RNA pathogens and host gene expression in a single assay. The pipeline allows detecting more viruses, predicting antibiotic resistance, pinpointing contaminations, and evaluating prognosis. Given the comparable cost to conventional mNGS, our pipeline can become a routine test for IM.
摘要：
背景：传染性脑膜炎/脑炎（IM）是一种严重的神经系统疾病，可由细菌引起，病毒，和真菌病原体。IM发病率高，死亡率,和童年的后遗症。宏基因组下一代测序（mNGS）可以通过对病原体和宿主反应进行测序并提高诊断准确性来潜在地改善IM结果。
方法：在这里，我们开发了一种优化的mNGS管道，称为综合mNGS（c-mNGS），以同时监测DNA/RNA病原体和宿主反应，并将其应用于142个脑脊液样品。根据回顾性诊断,这些样本分为三类:确诊的传染性脑膜炎/脑炎(CIM)，疑似传染性脑膜炎/脑炎（SIM），和非感染性对照（CTRL）。
结果：我们的管道优于常规方法，并鉴定了RNA病毒，如EchovirusE30和病原病原体，如HHV-7，这些病毒不能通过常规方法进行临床鉴定。根据c-mNGS管道的结果，我们成功检测到与治疗大肠杆菌的常用抗生素相关的抗生素耐药基因，鲍曼不动杆菌,和B组链球菌。Further,我们在细菌性脑膜炎(BM)和病毒性脑膜炎/脑炎(VM)宿主中鉴定了差异表达基因.我们使用这些基因来构建机器学习模型，以查明样本污染。同样，我们还建立了一个模型来预测BM的不良预后。
结论：这项研究开发了一种基于mNGS的IM管道，该管道可在单一测定中测量DNA/RNA病原体和宿主基因表达。管道允许检测更多的病毒，预测抗生素耐药性，精确定位污染物，并评估预后。考虑到与传统mNGS相当的成本，我们的管道可以成为IM的常规测试。
方法：在这里，我们开发了一种优化的mNGS管道，称为综合mNGS（c-mNGS），以同时监测DNA/RNA病原体和宿主反应，并将其应用于142个脑脊液样品。根据回顾性诊断,这些样本分为三类:确诊的传染性脑膜炎/脑炎(CIM)，疑似传染性脑膜炎/脑炎（SIM），和非感染性对照（CTRL）。
结果：我们的管道优于常规方法，并鉴定了RNA病毒，如EchovirusE30和病原病原体，如HHV-7，这些病毒不能通过常规方法进行临床鉴定。根据c-mNGS管道的结果，我们成功检测到与治疗大肠杆菌的常用抗生素相关的抗生素耐药基因，鲍曼不动杆菌,和B组链球菌。Further,我们在细菌性脑膜炎(BM)和病毒性脑膜炎/脑炎(VM)宿主中鉴定了差异表达基因.我们使用这些基因来构建机器学习模型，以查明样本污染。同样，我们还建立了一个模型来预测BM的不良预后。
结论：这项研究开发了一种基于mNGS的IM管道，该管道可在单一测定中测量DNA/RNA病原体和宿主基因表达。管道允许检测更多的病毒，预测抗生素耐药性，精确定位污染物，并评估预后。考虑到与传统mNGS相当的成本，我们的管道可以成为IM的常规测试。
