Frontiers in cellular and infection microbiology · 2022
Metagenomic next-generation sequencing of cell-free and whole-cell DNA in diagnosing central nervous system infections.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Yu Lili, Zhang Ye, Zhou Jiemin, Zhang Yu, Qi Xuejiao, Bai Kaixuan, Lou Zheng, Li Yi, Xia Han, Bu Hui
Аннотация
BACKGROUND: Central nervous system (CNS) infections pose a fatal risk to patients. However, the limited sample volumes of cerebrospinal fluid (CSF) and low detection efficiency seriously hinder the accurate detection of pathogens using conventional methods.
METHODS: We evaluated the performance of metagenomics next-generation sequencing (mNGS) in diagnosing CNS infections. CSF samples from 390 patients clinically diagnosed with CNS infections were used for the mNGS of cell-free DNA (cfDNA) (n =394) and whole-cell DNA (wcDNA) (n =150).
RESULTS: The sensitivity of mNGS using cfDNA was 60.2% (237/394, 95% confidence interval [CI] 55.1%-65.0%), higher than that of mNGS using wcDNA (32.0%, 95% [CI] 24.8%-40.2%, 48/150) and conventional methods (20.9%, 95% [CI] 16.2%-26.5%, 54/258) (P < 0.01, respectively). The accuracy of mNGS using cfDNA in positive samples was 82.6%. Most of viral (72.6%) and mycobacterial (68.8%) pathogens were only detected by the mNGS of cfDNA. Meningitis and encephalitis with Streptococcus pneumoniae infection might be more likely to result in critically ill diseases, while Human alphaherpesvirus 3 was prone to cause non-critically ill diseases.
CONCLUSIONS: This is the first report on evaluating and emphasizing the importance of mNGS using CSF cfDNA in diagnosing CNS infections, and its extensive application in diagnosing CNS infections could be expected, especially for viral and mycobacterial CNS infections.
METHODS: We evaluated the performance of metagenomics next-generation sequencing (mNGS) in diagnosing CNS infections. CSF samples from 390 patients clinically diagnosed with CNS infections were used for the mNGS of cell-free DNA (cfDNA) (n =394) and whole-cell DNA (wcDNA) (n =150).
RESULTS: The sensitivity of mNGS using cfDNA was 60.2% (237/394, 95% confidence interval [CI] 55.1%-65.0%), higher than that of mNGS using wcDNA (32.0%, 95% [CI] 24.8%-40.2%, 48/150) and conventional methods (20.9%, 95% [CI] 16.2%-26.5%, 54/258) (P < 0.01, respectively). The accuracy of mNGS using cfDNA in positive samples was 82.6%. Most of viral (72.6%) and mycobacterial (68.8%) pathogens were only detected by the mNGS of cfDNA. Meningitis and encephalitis with Streptococcus pneumoniae infection might be more likely to result in critically ill diseases, while Human alphaherpesvirus 3 was prone to cause non-critically ill diseases.
CONCLUSIONS: This is the first report on evaluating and emphasizing the importance of mNGS using CSF cfDNA in diagnosing CNS infections, and its extensive application in diagnosing CNS infections could be expected, especially for viral and mycobacterial CNS infections.