Frontiers in Cellular and Infection Microbiology · 2022 · 21 citations · 12 references
Life SciencesMicrobiologyPathologyDiagnostic MicrobiologyMedical MicrobiologyMetagenomicsMetagenomic AnalysisMicrobiology Of Musculoskeletal InfectionPathogen DiscoveryShotgun Metagenomic SequencingSpinal InfectionComparative Diagnostic PerformanceDiagnostic Performance MetricsHistopathological EvaluationHistopathological InterpretationMetagenomic DiagnosisMetagenomic DiagnosticsMetagenomic SequencingNext-generation Sequencing Diagnosis
Spinal infection is a rarely occurred pathology, whose diagnosis remains a major challenge due to the low sensitivity of culturing techniques. Metagenomic next-generation sequencing (mNGS) is a novel approach to identify the pathogenic organisms in infectious diseases. In this study, mNGS technology was adopted for pathogenic detection in spinal infection from the tissue and pus samples. Additionally, the diagnostic performance of mNGS for spinal infection was evaluated, by comparing it with that of the conventional microbial culture, with the histopathological results as the gold standard. Overall, 56 samples from 38 patients were enrolled for mNGS testing, and 69 samples were included for microbial culture. 30 patients (78.95%) were identified to be positive by the mNGS method, which was higher than that of microbial culture (17, 44.74%). The sensitivity and specificity of mNGS with pus samples were 84.2% and 100.0%, respectively, which outperformed those of microbial culture (42.1% and 100.0%). The pathogen identification results were applied to medication guidance, and all 38 patients experienced favorable outcomes at three months, followed-up post-treatment, without any adverse effects. These findings proved that mNGS was superior to microbial culture in pathogenic identification of the spinal infection, thereby showing great promise in guiding drug administration and improving clinical outcomes.
12
Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids
Wei Gu, Xianding Deng, Marco Lee et al. · Nature Medicine · 2020 · 687 citations · Full text