Abstract
Background Bacterial meningitis remains one of the major challenges in infectious diseases, leading to sequel in many cases. A prompt diagnosis of the causative microorganism is critical to significantly improve outcome of bacterial meningitis. Although various targeted tests for cerebrospinal fluid (CSF) samples are available, it is a big problem for the identification of etiology of bacterial meningitis.
Methods Here we describe the use of unbiased sequence analyses by next-generation sequencing (NGS) technology for the identification of infectious microorganisms from CSF samples of pediatric bacterial meningitis patients in the Department of Infectious Diseases from Beijing Children’s Hospital.
Results In total, we had 99 bacterial meningitis patients in our study, 55 (55.6%) of these were etiologically confirmed by clinical microbiology methods. Combined with NGS, 68 cases (68.7%) were etiologically confirmed. The main pathogens identified in this study were Streptococcus pneumoniae (n=29), group B streptococcus (n=15), Staphylococcus aureus (n=7), Escherichia coli (n=7). In addition, two cases with cytomegalovirus infection and one with Taenia saginata asiatica were confirmed by NGS.
Conclusions NGS could be a promising alternative diagnostic approach for critically ill patients suffering from bacterial meningitis in pediatric population.
Summary We conducted the study for the identification of microorganisms by next-generation sequencing directly from CSF samples of pediatric bacterial meningitis patients. And the study showed that NGS could be a promising alternative diagnostic approach for bacterial meningitis in pediatric population.
