Given the success of "Improving the Clinical Effectiveness of Metagenomic Next Generation Sequencing (mNGS) in Infection Disease Diagnosis and Treatment: Linking the NGS Specialists and Clinicians" series of article collections, and the rapidly evolving subject area, we are pleased to announce the launch of Volume III.
Rapid and accurate diagnosis is crucial for the effective treatment of infectious diseases. Metagenomics, using next-generation sequencing (NGS) or targeted NGS (tNGS) by enriching and sequencing specific regions of microbial genomes, can directly analyze mixed genomic materials from bacteria, viruses, fungi, parasites, and hosts in clinical samples. This provides immense potential for cost reduction and faster turnaround times, ranging from 12 to 24 hours, without the need for a clinical hypothesis. Although NGS still faces technical and practical challenges, it has been used in clinical practice, especially for critically ill patients in intensive care units who show no response to anti-infective therapies. At this stage, it is crucial to focus on the accuracy of pathogens identification in NGS reports for downstream clinical decision-making, such as adjusting anti-infective therapies or excluding infectious diseases in cases with negative reports. Therefore, the specificity of the reported pathogens should be comprehensively assessed by combining multiple clinical tests and processes.
The focus of this Research Topic is on the use of NGS, tNGS, and other rapid methods for pathogen detection. Our aim is to provide an overview of recent progress in the application of NGS and tNGS systems for the diagnosis of infectious diseases and to seek innovative solutions for addressing existing challenges, particularly in the area of specialty assessments of clinical NGS reports. We emphasize the robustness and repeatability of clinical NGS reports, including antibiotic resistance genes, virulence factor genes, and phylogeny information detection of reported causative pathogens. The exploration of the combination of NGS or tNGS with other conventional microbiological or molecular tests to confirm the accuracy of clinical diagnoses are also highly welcome. We welcome submissions of Review, Mini-Reviews, Original Research, and General Commentary covering a wide range of topics related to the application of NGS in pathogen detection. These topics include, but are not limited to:
1. The use of NGS in pathogen detection and diagnosis.
2. In-depth analysis of sequencing reads, including resistance genotyping, phylogeny analysis, and virulence factors.
3. The development of methodologies for NGS and other genomics-based applications in the diagnosis of infectious diseases.
Please note: All genomes (excluding human genomes) must be uploaded into the public genomic database for validation. And sample metadata should be clear and consistent, including sample name, sample type, sequencing instruments, sequencing strategy, data size, and the number of human genomes. For case reports, authors should focus on the confidence level of NGS.
Given the success of "Improving the Clinical Effectiveness of Metagenomic Next Generation Sequencing (mNGS) in Infection Disease Diagnosis and Treatment: Linking the NGS Specialists and Clinicians" series of article collections, and the rapidly evolving subject area, we are pleased to announce the launch of Volume III.
Rapid and accurate diagnosis is crucial for the effective treatment of infectious diseases. Metagenomics, using next-generation sequencing (NGS) or targeted NGS (tNGS) by enriching and sequencing specific regions of microbial genomes, can directly analyze mixed genomic materials from bacteria, viruses, fungi, parasites, and hosts in clinical samples. This provides immense potential for cost reduction and faster turnaround times, ranging from 12 to 24 hours, without the need for a clinical hypothesis. Although NGS still faces technical and practical challenges, it has been used in clinical practice, especially for critically ill patients in intensive care units who show no response to anti-infective therapies. At this stage, it is crucial to focus on the accuracy of pathogens identification in NGS reports for downstream clinical decision-making, such as adjusting anti-infective therapies or excluding infectious diseases in cases with negative reports. Therefore, the specificity of the reported pathogens should be comprehensively assessed by combining multiple clinical tests and processes.
The focus of this Research Topic is on the use of NGS, tNGS, and other rapid methods for pathogen detection. Our aim is to provide an overview of recent progress in the application of NGS and tNGS systems for the diagnosis of infectious diseases and to seek innovative solutions for addressing existing challenges, particularly in the area of specialty assessments of clinical NGS reports. We emphasize the robustness and repeatability of clinical NGS reports, including antibiotic resistance genes, virulence factor genes, and phylogeny information detection of reported causative pathogens. The exploration of the combination of NGS or tNGS with other conventional microbiological or molecular tests to confirm the accuracy of clinical diagnoses are also highly welcome. We welcome submissions of Review, Mini-Reviews, Original Research, and General Commentary covering a wide range of topics related to the application of NGS in pathogen detection. These topics include, but are not limited to:
1. The use of NGS in pathogen detection and diagnosis.
2. In-depth analysis of sequencing reads, including resistance genotyping, phylogeny analysis, and virulence factors.
3. The development of methodologies for NGS and other genomics-based applications in the diagnosis of infectious diseases.
Please note: All genomes (excluding human genomes) must be uploaded into the public genomic database for validation. And sample metadata should be clear and consistent, including sample name, sample type, sequencing instruments, sequencing strategy, data size, and the number of human genomes. For case reports, authors should focus on the confidence level of NGS.