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Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing
BACKGROUND: Community-acquired central nervous system infections (CA-CNS infections) have the characteristics of acute onset and rapid progression, and are associated with high levels of morbidity and mortality worldwide. However, there have been only limited studies on the etiology of this infectio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9549810/ https://www.ncbi.nlm.nih.gov/pubmed/36225235 http://dx.doi.org/10.3389/fcimb.2022.979086 |
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author | Zhang, Shanshan Wu, Gang Shi, Yuru Liu, Ting Xu, Liangfei Dai, Yuanyuan Chang, Wenjiao Ma, Xiaoling |
author_facet | Zhang, Shanshan Wu, Gang Shi, Yuru Liu, Ting Xu, Liangfei Dai, Yuanyuan Chang, Wenjiao Ma, Xiaoling |
author_sort | Zhang, Shanshan |
collection | PubMed |
description | BACKGROUND: Community-acquired central nervous system infections (CA-CNS infections) have the characteristics of acute onset and rapid progression, and are associated with high levels of morbidity and mortality worldwide. However, there have been only limited studies on the etiology of this infections. Here, metagenomic next-generation sequencing (mNGS), a comprehensive diagnosis method, facilitated us to better understand the etiology of CA-CNS infections. METHODS: We conducted a single-center retrospective study between September 2018 and July 2021 in which 606 cerebrospinal fluid (CSF) samples were collected from suspected CNS infectious patients for mNGS testing, and all positive samples were included in this analysis RESULTS: After the exclusion criteria, a total of 131 mNGS-positive samples were finally enrolled. Bacterial, viral, fungal, parasitic, specific pathogen and mixed infections were accounted for 32.82% (43/131), 13.74% (18/131), 0.76% (1/131), 2.29% (3/131) and 6.87% (9/131), respectively. A total of 41 different pathogens were identified, including 16 bacteria, 12 viruses, 10 fungi, and 1 parasite and 3 specific pathogens. The most frequent infecting pathogens are Epstein-Barr virus (n = 14), Herpes simplex virus 1 (n = 14), Mycobacterium tuberculosis (n = 13), Streptococcus pneumoniae (n = 13), and Cryptococcus neoformans (n = 8). Some difficult-to-diagnose pathogen infections were also detected by mNGS, such as Streptococcus suis, Pseudorabies virus, Bunyavirus, Orientia tsutsugamushi and Toxoplasma gondii. CONCLUSION: In this study, mNGS identified a wide variety of pathogens of CA-CNS infections and many of which could not be detected by conventional methods. Our data provide a better understanding of the etiology of CA-CNS infections and show that mNGS represents a comparative screening of CSF in an unbiased manner for a broad range of human pathogens. |
format | Online Article Text |
id | pubmed-9549810 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95498102022-10-11 Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing Zhang, Shanshan Wu, Gang Shi, Yuru Liu, Ting Xu, Liangfei Dai, Yuanyuan Chang, Wenjiao Ma, Xiaoling Front Cell Infect Microbiol Cellular and Infection Microbiology BACKGROUND: Community-acquired central nervous system infections (CA-CNS infections) have the characteristics of acute onset and rapid progression, and are associated with high levels of morbidity and mortality worldwide. However, there have been only limited studies on the etiology of this infections. Here, metagenomic next-generation sequencing (mNGS), a comprehensive diagnosis method, facilitated us to better understand the etiology of CA-CNS infections. METHODS: We conducted a single-center retrospective study between September 2018 and July 2021 in which 606 cerebrospinal fluid (CSF) samples were collected from suspected CNS infectious patients for mNGS testing, and all positive samples were included in this analysis RESULTS: After the exclusion criteria, a total of 131 mNGS-positive samples were finally enrolled. Bacterial, viral, fungal, parasitic, specific pathogen and mixed infections were accounted for 32.82% (43/131), 13.74% (18/131), 0.76% (1/131), 2.29% (3/131) and 6.87% (9/131), respectively. A total of 41 different pathogens were identified, including 16 bacteria, 12 viruses, 10 fungi, and 1 parasite and 3 specific pathogens. The most frequent infecting pathogens are Epstein-Barr virus (n = 14), Herpes simplex virus 1 (n = 14), Mycobacterium tuberculosis (n = 13), Streptococcus pneumoniae (n = 13), and Cryptococcus neoformans (n = 8). Some difficult-to-diagnose pathogen infections were also detected by mNGS, such as Streptococcus suis, Pseudorabies virus, Bunyavirus, Orientia tsutsugamushi and Toxoplasma gondii. CONCLUSION: In this study, mNGS identified a wide variety of pathogens of CA-CNS infections and many of which could not be detected by conventional methods. Our data provide a better understanding of the etiology of CA-CNS infections and show that mNGS represents a comparative screening of CSF in an unbiased manner for a broad range of human pathogens. Frontiers Media S.A. 2022-09-26 /pmc/articles/PMC9549810/ /pubmed/36225235 http://dx.doi.org/10.3389/fcimb.2022.979086 Text en Copyright © 2022 Zhang, Wu, Shi, Liu, Xu, Dai, Chang and Ma https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cellular and Infection Microbiology Zhang, Shanshan Wu, Gang Shi, Yuru Liu, Ting Xu, Liangfei Dai, Yuanyuan Chang, Wenjiao Ma, Xiaoling Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing |
title | Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing |
title_full | Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing |
title_fullStr | Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing |
title_full_unstemmed | Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing |
title_short | Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing |
title_sort | understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing |
topic | Cellular and Infection Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9549810/ https://www.ncbi.nlm.nih.gov/pubmed/36225235 http://dx.doi.org/10.3389/fcimb.2022.979086 |
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