AUTHOR=Qian Yi-Yi , Wang Hong-Yu , Zhou Yang , Zhang Hao-Cheng , Zhu Yi-Min , Zhou Xian , Ying Yue , Cui Peng , Wu Hong-Long , Zhang Wen-Hong , Jin Jia-Lin , Ai Jing-Wen TITLE=Improving Pulmonary Infection Diagnosis with Metagenomic Next Generation Sequencing JOURNAL=Frontiers in Cellular and Infection Microbiology VOLUME=10 YEAR=2021 URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2020.567615 DOI=10.3389/fcimb.2020.567615 ISSN=2235-2988 ABSTRACT=

Pulmonary infections are among the most common and important infectious diseases due to their high morbidity and mortality, especially in older and immunocompromised individuals. However, due to the limitations in sensitivity and the long turn-around time (TAT) of conventional diagnostic methods, pathogen detection and identification methods for pulmonary infection with greater diagnostic efficiency are urgently needed. In recent years, unbiased metagenomic next generation sequencing (mNGS) has been widely used to detect different types of infectious pathogens, and is especially useful for the detection of rare and newly emergent pathogens, showing better diagnostic performance than traditional methods. There has been limited research exploring the application of mNGS for the diagnosis of pulmonary infections. In this study we evaluated the diagnostic efficiency and clinical impact of mNGS on pulmonary infections. A total of 100 respiratory samples were collected from patients diagnosed with pulmonary infection in Shanghai, China. Conventional methods, including culture and standard polymerase chain reaction (PCR) panel analysis for respiratory tract viruses, and mNGS were used for the pathogen detection in respiratory samples. The difference in the diagnostic yield between conventional methods and mNGS demonstrated that mNGS had higher sensitivity than traditional culture for the detection of pathogenic bacteria and fungi (95% vs 54%; p<0.001). Although mNGS had lower sensitivity than PCR for diagnosing viral infections, it identified 14 viral species that were not detected using conventional methods, including multiple subtypes of human herpesvirus. mNGS detected viruses with a genome coverage >95% and a sequencing depth >100× and provided reliable phylogenetic and epidemiological information. mNGS offered extra benefits, including a shorter TAT. As a complementary approach to conventional methods, mNGS could help improving the identification of respiratory infection agents. We recommend the timely use of mNGS when infection of mixed or rare pathogens is suspected, especially in immunocompromised individuals and or individuals with severe conditions that require urgent treatment.