Metagenomic diagnosis of bloodstream infection

Bloodstream infections remain a major challenge in hospital settings, with high mortality rates due to the lack of quick and accurate methods to identify pathogens. Recently, metagenomic next-generation sequencing (mNGS) has emerged as a promising diagnostic technology that enables universal pathogen detection, noninvasive sampling, and earlier diagnosis. However, a significant limitation of current mNGS assays is the high rate of false-positive results due to contamination. We constructed three novel control groups - 1) external negative controls under long-term surveillance, 2) samples with a negative result in convectional tests, and 3) a group of healthy people - dedicated to distinguishing contaminants arising from specimen collection, sample processing, and human normal flora. This workflow was applied to 209 clinical plasma samples from patients with suspected bloodstream infections.