Optimisation and clinical validation of a metagenomic third-generation sequencing approach for aetiological diagnosis in bronchoalveolar lavage fluid of patients with pneumonia

Background Metagenomic Third Generation Sequencing (mTGS), based on nanopore technology, has emerged as a promising tool for the rapid diagnosis of pneumonia pathogens. However, this technology currently lacks standardised technical protocols, quality control measures, and comprehensive performance evaluations for the simultaneous detection of bacteria, fungi, and viruses in clinical settings. Methods We optimised the mTGS workflow by refining key parameters (cell wall lysis, fragment size selection, host DNA depletion, and sequencing depth) using reference samples and bronchoalveolar lavage fluid (BALF) from eight patients with pneumonia. These optimisations formed the basis for a standardised mTGS protocol. To assess the clinical diagnostic value of the optimised mTGS, a multicentre prospective cohort study involving 313 pneumonia-suspected patients was conducted. Each BALF sample was tested using conventional microbiological testing (CMTs), metagenomic next-generation sequencing (mNGS), pre-optimised mTGS, and optimised mTGS. Findings The optimised mTGS protocol, based on the refined cell wall lysis, fragment size selection, no host DNA depletion, and 800 MB sequencing depth, achieved a tenfold increase in sensitivity compared with pre-optimised mTGS for detecting the species of Bacillus subtilis, Mycobacterium tuberculosis, Mycobacterium avium, Cryptococcus neoformans, and Human papillomavirus in reference samples. In the prospective cohort, 274 patients with a confirmed diagnosis of pneumonia were identified, yielding 376 distinct microbes. The mTGS identified more microbes than CMTs (314 vs. 115), with a 45.30% increase in sensitivity (84.70% vs. 39.40%, P Interpretation We optimised and validated a standardised mTGS protocol that significantly improved the ability to detect pathogens in the BALF of patients with pneumonia. Optimised mTGS demonstrated comparable performance to mNGS, making it a promising tool for the aetiological diagnosis of pneumonia. Funding The Research and Development Programme of Zhejiang Province (2023C03068, 2024C03187), the National Natural Science Foundation of China (82272338), the Key R&D Plan of the Ministry of Science and Technology (China) of China (2022YFC2504502).