A dual-process of targeted and unbiased Nanopore sequencing enables accurate and rapid diagnosis of lower respiratory infections

Background: Nanopore metagenomics has been used for infectious disease diagnosis for bacterial pathogens. However, this technology currently lacks comprehensive performance studies in clinical settings for simultaneous detection of bacteria, fungi, and viruses.

Methods: We developed a dual-process of Nanopore sequencing for one sample, with unbiased metagenomics in Meta process and target enrichment in Panel process (Nanopore Meta-Panel process, NanoMP) and prospectively enrolled 450 respiratory specimens from multiple centers. The filter system of pathogen detection was established with machine learning and receiver operator characteristic (ROC) curve to optimize the detection accuracy based on orthogonal test of 21 species. Antimicrobial resistance (AMR) genes were identified based on the Comprehensive Antibiotic Resistance Database (CARD) and single-nucleotide polymorphism matrix.

Findings: Our approach showed high sensitivity in Meta process, with 82.9%, 88.7%, and 75.0% for bacteria, fungi (except Aspergillus), and Mycobacterium tuberculosis groups, respectively. Moreover, target amplification improved the sensitivity of virus (>80.0% vs. 39.4%) and Aspergillus (81.8% vs. 42.3%) groups in Panel process compared with Meta process. Overall, NanoMP achieved 80.2% sensitivity and 98.8% specificity compared with the composite reference standard, and we were able to accurately detect AMR genes including bla_KPC-2, bla_OXA-23 and mecA and distinguish their parent organisms in patients with mixed infections.

Interpretation: We combined metagenomic and enriched Nanopore sequencing for one sample in parallel. Our NanoMP approach simultaneously covered bacteria, viruses and fungi in respiratory specimens and demonstrated good diagnostic performance in real clinical settings.

Funding: National Key Research and Development Program of China and National Natural Science Foundation of China.