About this Research Topic
Rapid microbiological diagnosis of pulmonary infections facilitates the timely application of antimicrobial therapies. Conventional microbiological methods were relatively insensitive and cultures were time-consuming. Rapid advances in sequencing technologies and bioinformatics have made metagenomic sequencing (mNGS) a fertile area for the development of clinical diagnostics. Culture-independent screening for pathogens with mNGS only requires a small amount of DNA and RNA directly taken from the sample, and a bioinformatic tool, which identifies pathogens by linking sequencing reads to an accurate reference genome (or marker) database. Eventually, if the sequencing depth is sufficient, the antibiotic susceptibility can be inferred. Metagenomics and microbiome discoveries have revealed a new appreciation for the role of microbes in health and disease. Recent work has highlighted the current interest in using mNGS for the identification and antibiotic susceptibility testing of pathogens in the diagnosis of viral acute encephalitis, infective endocarditis, bacterial meningitis, prosthetic joint infections and pneumonia amongst others.
mNGS enables simultaneous detection of RNA and DNA in one sample, and a comprehensive analysis of pathogens from the transcriptome and genome-level may be able to distinguish infections and colonization of microorganisms in respiratory samples. Furthermore, mNGS can also simultaneously analyze the host immune responses, which could provide some information for the diagnosis of infectious diseases.
However, the mNGS approach is not without its limitations in respiratory infection diagnostics. mNGS could provide a wide range of organisms and microbial profiles, which were difficult to interpret for infectious pathogens. The lung microbiome should be considered when interpreting mNGS results, but only a few studies are available. The lung microbiome has been particularly difficult to characterize due to prior assumptions about the community composition of the lung, the diversity of pathogens causing diseases, and sampling concerns. As clinical microbiology laboratories move towards accreditation of mNGS for routine clinical use, we should turn our attention towards standardization by developing standard operating procedures for reproducible sample handling, sequencing, quality control, and downstream bioinformatic analyses.
This Research Topic welcomes articles highlighting advances from basic data management pipeline research to clinical applications of mNGS in respiratory infections. More specifically, topics of interest include, but are not limited to:
1. Methodological evaluation of respiratory sample processing before mNGS.
2. Novel insights into the effects of lung microbiome changes on pulmonary infection by mNGS.
3. Diagnosis of respiratory tract infections using mNGS.
mNGS enables simultaneous detection of RNA and DNA in one sample, and a comprehensive analysis of pathogens from the transcriptome and genome-level may be able to distinguish infections and colonization of microorganisms in respiratory samples. Furthermore, mNGS can also simultaneously analyze the host immune responses, which could provide some information for the diagnosis of infectious diseases.
However, the mNGS approach is not without its limitations in respiratory infection diagnostics. mNGS could provide a wide range of organisms and microbial profiles, which were difficult to interpret for infectious pathogens. The lung microbiome should be considered when interpreting mNGS results, but only a few studies are available. The lung microbiome has been particularly difficult to characterize due to prior assumptions about the community composition of the lung, the diversity of pathogens causing diseases, and sampling concerns. As clinical microbiology laboratories move towards accreditation of mNGS for routine clinical use, we should turn our attention towards standardization by developing standard operating procedures for reproducible sample handling, sequencing, quality control, and downstream bioinformatic analyses.
This Research Topic welcomes articles highlighting advances from basic data management pipeline research to clinical applications of mNGS in respiratory infections. More specifically, topics of interest include, but are not limited to:
1. Methodological evaluation of respiratory sample processing before mNGS.
2. Novel insights into the effects of lung microbiome changes on pulmonary infection by mNGS.
3. Diagnosis of respiratory tract infections using mNGS.
Keywords: Metagenomic Sequencing, Diagnosis of Pulmonary Infections, Lung Microbiome
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