Exploring the Spectrum of Microbiota in Central Nervous System Infections Through Metagenomic Next-Generation Sequencing.
Jun-Mei Wang, Yu-Ying Pan, Jian-Chen Hong, Zai-Jie Jiang, Shi-Ying Zhang, Rui-Jie Fan, Bi-Hui Yang, Zhi-Qiang Wang, et al. (10 authors)
Infection and drug resistance · 2025-01
Abstract
PURPOSE: This study leveraged CSF metagenomic next-generation sequencing (mNGS) to bridge this knowledge gap and elucidate the microbiota spectrum of CNS infections.
PATIENTS AND METHODS: We retrospectively analyzed CSF mNGS reports and clinical data from 264 patients with suspected CNS infections, who were enrolled from September 2019 to November 2023.
RESULTS: According to diagnostic criteria, 145 patients were diagnosed with CNS infections, including bacterial (27 cases, 18.6%),(30, 20.7%), fungal (23, 15.9%), and viral (65, 44.8%) infections. The mNGS positive detection rate was 46.2% (67/145), with significant differences among groups (< 0.001). A total of 22 pathogens were identified, most commonly(16, 23.9%),(10, 14.9%), and Epstein-Barr virus (9, 13.4%). The most frequent background microorganisms detected by mNGS were(58.6%),(29.0%), and(26.2%).
CONCLUSION: High-throughput sequencing using mNGS revealed the microbial compositions in CSF samples from patients with CNS infections. This approach may enhance our understanding of pathogens and assist clinicians in making effective therapeutic decisions.