Nowadays, accurate pathogen detection is still the bottleneck of diagnosis and treatment of clinical microbial infection. A large number of infections caused by distinct etiological agents have similar clinical symptoms. Traditional diagnostic tests via culture-dependent isolation followed by identification are usually slow, specialized, and organism-specific. The rapid development of the clinical metagenomic next-generation sequencing (mNGS) technique has recently been becoming an alternative diagnostic test that can meet the needs of modern medical multidisciplinary diagnosis and treatment. Sequencing microbial cell-free DNA has enabled the detection of the pathogen in several infected body fluids, such as bronchoalveolar lavage fluid, cerebrospinal fluid, pleural fluid, and sputum. However, implementing mNGS as a routine microbiological use in the hospital setting still needs extensive clinical evaluation to address performance assessment, quality control, and verification strategy for diagnosing and identifying infectious diseases.
This Research Topic aims to improve our understanding of the diagnostic advantages and potential limitations of mNGS test using cfDNA compared with the other traditional diagnostic tests for pathogen detection in the clinical setting. These should include:
1) the advances of standardized wet and dry bench protocols of cell-free DNA mNGS created for the detection of etiological agents including bacteria, viruses, fungi, yeasts, and parasites;
2) Can microbial-derived cfDNA reveal pathogens' landscape and community composition in the clinical specimens collected from the infected patients? What are the differences in pathogen identification performance factors between the sequencing of total DNA and cfDNA of clinical specimens?
3) Can plasma cfDNA mNGS accurately reflect the occurrence of the pathogens in the distal lesions of infected patients?
4) can we develop better models and methodological approaches to support mNGS assay of cfDNA routine microbiological test for truly no-invasive and unbiased pathogen detection?
5) can we develop better methodological approaches to eliminate the effect of background microorganisms on the report interpretation?
6) the analysis of the population structure of clinically significant pathogens and the use of mNGS for molecular epidemiology.
For this research topic of mNGS of cfDNA, we welcome an original or method article related to infectious diseases' diagnosis and pathogen identification. Topic to the following scope, but not limited to:
• Clinical assessment of mNGS pathogen detection using cfDNA of different types of clinical specimens from infected patients
• Comparison of performance characteristics between cfDNA mNGS and other diagnostic assays, including accuracy, analytic sensitivity and specificity, reproducibility, and reportable range
• The development of standardized cfDNA mNGS protocols and quality metrics related to reference materials and bioinformatics pipelines that enable the validity of NGS test results
• The development of automated sequence interpretation tools for better identification and prioritization of the pathogenic organisms that are clinically relevant
• Machine-learning model and analytical approach for differentiating pathogens from commensals
• Other practical issues in implementing mNGS using cfDNA for pathogen identification in routine diagnostic microbiology
The guest editors declare that they have no conflicts of interest. Dr Xu reported being an employee of Genoxor Medical Science and Technology Inc.
Nowadays, accurate pathogen detection is still the bottleneck of diagnosis and treatment of clinical microbial infection. A large number of infections caused by distinct etiological agents have similar clinical symptoms. Traditional diagnostic tests via culture-dependent isolation followed by identification are usually slow, specialized, and organism-specific. The rapid development of the clinical metagenomic next-generation sequencing (mNGS) technique has recently been becoming an alternative diagnostic test that can meet the needs of modern medical multidisciplinary diagnosis and treatment. Sequencing microbial cell-free DNA has enabled the detection of the pathogen in several infected body fluids, such as bronchoalveolar lavage fluid, cerebrospinal fluid, pleural fluid, and sputum. However, implementing mNGS as a routine microbiological use in the hospital setting still needs extensive clinical evaluation to address performance assessment, quality control, and verification strategy for diagnosing and identifying infectious diseases.
This Research Topic aims to improve our understanding of the diagnostic advantages and potential limitations of mNGS test using cfDNA compared with the other traditional diagnostic tests for pathogen detection in the clinical setting. These should include:
1) the advances of standardized wet and dry bench protocols of cell-free DNA mNGS created for the detection of etiological agents including bacteria, viruses, fungi, yeasts, and parasites;
2) Can microbial-derived cfDNA reveal pathogens' landscape and community composition in the clinical specimens collected from the infected patients? What are the differences in pathogen identification performance factors between the sequencing of total DNA and cfDNA of clinical specimens?
3) Can plasma cfDNA mNGS accurately reflect the occurrence of the pathogens in the distal lesions of infected patients?
4) can we develop better models and methodological approaches to support mNGS assay of cfDNA routine microbiological test for truly no-invasive and unbiased pathogen detection?
5) can we develop better methodological approaches to eliminate the effect of background microorganisms on the report interpretation?
6) the analysis of the population structure of clinically significant pathogens and the use of mNGS for molecular epidemiology.
For this research topic of mNGS of cfDNA, we welcome an original or method article related to infectious diseases' diagnosis and pathogen identification. Topic to the following scope, but not limited to:
• Clinical assessment of mNGS pathogen detection using cfDNA of different types of clinical specimens from infected patients
• Comparison of performance characteristics between cfDNA mNGS and other diagnostic assays, including accuracy, analytic sensitivity and specificity, reproducibility, and reportable range
• The development of standardized cfDNA mNGS protocols and quality metrics related to reference materials and bioinformatics pipelines that enable the validity of NGS test results
• The development of automated sequence interpretation tools for better identification and prioritization of the pathogenic organisms that are clinically relevant
• Machine-learning model and analytical approach for differentiating pathogens from commensals
• Other practical issues in implementing mNGS using cfDNA for pathogen identification in routine diagnostic microbiology
The guest editors declare that they have no conflicts of interest. Dr Xu reported being an employee of Genoxor Medical Science and Technology Inc.
