Abstract
Lower respiratory tract infection (LRTI) is a serious global public health issue and poses significant challenges for detection and diagnosis. We validated the detection performance of targeted next-generation sequencing (tNGS) based on multiplex PCR using simulated microbial sample panels and clinical samples, providing a theoretical basis for promoting and applying tNGS in clinical diagnosis. We used a series of simulated microbial sample panels to validate the analytical validity of tNGS comprehensively. We also use tNGS to test respiratory specimens from 108 diagnosed or suspected LRTI patients to validate its clinical validity in diagnosing LRTI. Finally, we summarize the drug-resistance genes obtained from tNGS, the detection cost, and the turnaround time. tNGS has good analytical specificity, sensitivity, and precision. It has good stability when stored under low-temperature conditions. Using the composite diagnostic criteria as the gold standard, our internal tNGS platform has a sensitivity of 84.38%, specificity of 91.67%, positive predictive value of 98.78%, and negative predictive value of 42.31%. In terms of turnaround time, tNGS (about 16 h) and metagenomic next-generation sequencing (about 24 h) are similar, both significantly superior to traditional microbial detection methods (3-5 days). The cost of tNGS is approximately one-fourth of metagenomic next-generation sequencing. As a novel method with acceptable performance and cost, tNGS can compensate for the shortcomings of commonly used pathogen detection schemes in clinical practice, and its application prospects are worth looking forward to. IMPORTANCE: Lower respiratory tract infection (LRTI) is a serious global public health problem, and detecting its pathogenic microorganisms is difficult. Targeted next-generation sequencing (tNGS) is a rising star in microbial detection, with enormous potential. To understand the detection performance of tNGS and provide a theoretical basis for promoting its application in clinical diagnosis, this study prepared simulated microbial sample panels using reference materials to evaluate the analytical and clinical validity of tNGS. Our research suggests that tNGS has good analytical specificity and sensitivity, precision, and stability. Additionally, it can reliably detect common LRTI pathogens. It has advantages in identifying co-infections and atypical pathogens. Moreover, tNGS significantly reduces turnaround time, allowing faster treatment. In summary, tNGS is expected to be used in clinical practice to diagnose and manage LRTI.