A Comprehensive Assessment of Metagenomic cfDNA Sequencing for Microbe Detection.

Background Metagenomic cell-free DNA (cfDNA) sequencing provides a new avenue for diagnosing infectious diseases. Owing to the low concentration and highly fragmented nature of microbial cfDNA in plasma, coupled with methodological complexity, ensuring accurate and comparable metagenomic cfDNA seque...

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Published in:Clinical Chemistry Vol. 71; no. 7; pp. 763 - 775
Main Authors: Diao, Zhenli, Zhao, Zihong, Han, Yanxi, Chen, Yuqing, Huang, Tao, Feng, Lei, Ma, Yu, Li, Jinming, Zhang, Rui
Format: Journal Article
Published: Oxford University Press / USA Jul2025
Online Access:View this record in EBSCOhost
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      pub: Oxford University Press / USA
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        atl: A Comprehensive Assessment of Metagenomic cfDNA Sequencing for Microbe Detection.
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          Diao, Zhenli
          Zhao, Zihong
          Han, Yanxi
          Chen, Yuqing
          Huang, Tao
          Feng, Lei
          Ma, Yu
          Li, Jinming
          Zhang, Rui
        affil: National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology, Beijing, P. R. China
      sug:
      ab: Background Metagenomic cell-free DNA (cfDNA) sequencing provides a new avenue for diagnosing infectious diseases. Owing to the low concentration and highly fragmented nature of microbial cfDNA in plasma, coupled with methodological complexity, ensuring accurate and comparable metagenomic cfDNA sequencing results has proved challenging. This study aims to evaluate the performance of metagenomic cfDNA sequencing for detecting microorganisms in plasma across various laboratories and to examine factors affecting accuracy. Methods A reference panel consisting of 18 microbial cfDNA communities was designed and used to investigate the performance of metagenomic cfDNA sequencing across 130 laboratories. We comprehensively assessed the accuracy, repeatability, anti-interference, limit of detection (LoD), and linear correlation. Results The results showed that the performance of most laboratories was excellent, with an average F1 score of 0.98. Most contamination in metagenomic cfDNA sequencing originated from "wet labs," as 68.25% (475/696) of the false-positive sequences matched reported microorganisms. The chief cause (74.24%, 49/66) of false-negative errors in metagenomic cfDNA sequencing was from "dry labs." Laboratories showed favorable reproducibility, LoD, and linearity. Interference from elevated human cfDNA concentrations was minimal, whereas interference from genetically similar microorganisms was more pronounced. Overall, viral cfDNA detection showed weaker performance compared to bacterial and fungal detection. Conclusions This study presented the performance of metagenomic cfDNA sequencing in real-world settings, identifying key factors critical for its development and optimization. These findings provide valuable guidance for accurate pathogen detection in infectious diseases and promote the adoption of metagenomic cfDNA sequencing in diagnostics.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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