AUTHOR=Li Xiaoqiang , Du Hui , Song Zhibin , Wang Hui , Long xiong TITLE=Polymicrobial Anaerobic Meningitis Detected by Next-Generation Sequencing: Case Report and Review of the Literature JOURNAL=Frontiers in Medicine VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.840910 DOI=10.3389/fmed.2022.840910 ISSN=2296-858X ABSTRACT=Background

Anaerobic meningitis is a severe central nervous system infection associated with significant neurological sequelae and high mortality. However, the precise detection of causative pathogen(s) remains difficult because anaerobic bacteria are difficult to culture. Next-generation sequencing is a technology that was developed recently and has been applied in many fields. To the best of our knowledge, the use of next-generation sequencing for cerebrospinal fluid analysis in the diagnosis of anaerobic meningitis has been rarely reported.

Case presentation

Here, we report a case of polymicrobial anaerobic meningitis diagnosed using next-generation sequencing of cerebrospinal fluid in a 16-year-old girl. Five species of anaerobic bacteria (Porphyromonas gingivalis, Prevotella enoeca, Campylobacter rectus, Fusobacterium uncleatum, and Actinomyces israelii) were detected by next-generation sequencing and treated with antibacterial agents (ceftriaxone, vancomycin, and metronidazole). The patient responded well to antibacterial treatment. Further inspection revealed bone destruction at the base of the skull, which further confirmed that these bacteria had originated from the oral cavity. One month later, the patient's condition improved significantly. At the same time, we performed a literature review on anaerobic meningitis using studies published in the last 20 years.

Conclusions

This case emphasizes the importance of applying metagenomic next-generation sequencing to clinch the clinical diagnosis for patients with central nervous system infection. Metagenomic next-generation sequencing has been reported to be an important diagnostic modality for identifying uncommon pathogens.