AUTHOR=Zhang Shanshan , Wu Gang , Shi Yuru , Liu Ting , Xu Liangfei , Dai Yuanyuan , Chang Wenjiao , Ma Xiaoling TITLE=Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing JOURNAL=Frontiers in Cellular and Infection Microbiology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2022.979086 DOI=10.3389/fcimb.2022.979086 ISSN=2235-2988 ABSTRACT=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.