Optimizing Metagenomic Next-Generation Sequencing with Co-Library Preparation:  Improved Detection of Low-Load RNA Viruses
Introduction: Metagenomic next-generation sequencing (mNGS) has emerged as a cornerstone in clinical diagnostics for pathogen detection, renowned for its unbiased and culture-independent approach. However, mNGS faces challenges in identifying low-load RNA viruses, especially when libraries are constructed from samples containing both RNA and DNA pathogens.Objectives: This study aimed to enhance the method for co-constructing DNA and RNA libraries in mNGS. Our goal was to improve the detection of low-load viral pathogens while preserving the ability to detect DNA-based pathogens.Methods: We utilized a combination of random and specific primers to amplify RNA through the transcription-mediated amplification (TMA) technique. Using these amplified nucleic acids, we developed a library for mNGS that is capable of detecting a spectrum of both RNA and DNA pathogens, and investigated its detection performance using simulated samples and clinical samples.Results: Traditional mNGS struggled with detecting low-load viruses when human nucleic acids are abundant. However, the novel TMA-mNGS approach significantly improved detection, even in the presence of high concentrations of human DNA. Moreover, TMA-mNGS has demonstrated its effectiveness in detecting DNA pathogens and has shown superior performance over traditional mNGS in the analysis of clinical samples.Conclusion: Integrating TMA into the mNGS library construction process significantly enhances the sensitivity for detecting low-load RNA viruses while maintaining effective detection of DNA pathogens. This advancement represents a critical development in pathogen diagnostics, providing a powerful tool for the simultaneous detection of both RNA and DNA pathogens.