A comprehensive assessment of metagenomic cfDNA sequencing for microbe detection

The Clinical Chemistry Journal Club allows readers to discuss key articles by using focused slides as teaching tools. Each month Clinical Chemistry posts the original article and slides online, and they are then distributed to individuals and university Journal Clubs.

Original Article: https://doi.org/10.1093/clinchem/hvaf044

Slides: Download ppt

Webinar (on demand), available through August 31, 2026: https://myadlm.org/education/all-webinars/webinars/2025/august/comprehensive-assessment-of-metagenomic-cfdna-sequencing-for-microbe-detection

Abstract

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.