24 January 2024 | Aljuboori M. Nafea, Yuer Wang, Duanyang Wang, Ahmed M. Salama, Manal A. Aziz, Shan Xu, Yigang Tong
Next-generation sequencing (NGS) has become a crucial tool for identifying various pathogens, including bacteria, fungi, and viruses. Traditional methods such as culture-based techniques and molecular testing are limited in their application and time-consuming. NGS offers high-throughput sequencing capabilities, enabling the rapid identification of pathogens with high accuracy. This review discusses the application of NGS in pathogen identification, including whole-genome sequencing (WGS), targeted next-generation sequencing (tNGS), and metagenomic next-generation sequencing (mNGS). It also highlights the challenges and future prospects of using NGS for clinical pathogen detection.
Sanger sequencing, a first-generation sequencing method, is still widely used for small DNA sequences due to its high-quality results. However, NGS has revolutionized pathogen detection by allowing the simultaneous sequencing of millions of DNA fragments, providing a more comprehensive view of genetic material. NGS technologies, such as Illumina, 454 Roche, and SOLiD, have enabled the rapid and accurate identification of pathogens, including viruses like HIV and hepatitis C virus (HCV). NGS has also been used to detect and track the spread of pathogens such as Mycobacterium tuberculosis and Klebsiella pneumoniae.
The application of NGS in clinical settings has shown significant benefits, including faster diagnosis, improved treatment outcomes, and better understanding of antimicrobial resistance. However, challenges remain, such as the need for robust bioinformatics pipelines, standardization of methods, and the high cost of NGS. Despite these challenges, NGS is increasingly being adopted in clinical laboratories for pathogen detection, offering a more efficient and accurate alternative to traditional methods. The future of NGS in pathogen identification lies in further advancements in sequencing technologies, data analysis tools, and collaboration between researchers, clinicians, and public health agencies to improve diagnostics, surveillance, and control of infectious diseases.Next-generation sequencing (NGS) has become a crucial tool for identifying various pathogens, including bacteria, fungi, and viruses. Traditional methods such as culture-based techniques and molecular testing are limited in their application and time-consuming. NGS offers high-throughput sequencing capabilities, enabling the rapid identification of pathogens with high accuracy. This review discusses the application of NGS in pathogen identification, including whole-genome sequencing (WGS), targeted next-generation sequencing (tNGS), and metagenomic next-generation sequencing (mNGS). It also highlights the challenges and future prospects of using NGS for clinical pathogen detection.
Sanger sequencing, a first-generation sequencing method, is still widely used for small DNA sequences due to its high-quality results. However, NGS has revolutionized pathogen detection by allowing the simultaneous sequencing of millions of DNA fragments, providing a more comprehensive view of genetic material. NGS technologies, such as Illumina, 454 Roche, and SOLiD, have enabled the rapid and accurate identification of pathogens, including viruses like HIV and hepatitis C virus (HCV). NGS has also been used to detect and track the spread of pathogens such as Mycobacterium tuberculosis and Klebsiella pneumoniae.
The application of NGS in clinical settings has shown significant benefits, including faster diagnosis, improved treatment outcomes, and better understanding of antimicrobial resistance. However, challenges remain, such as the need for robust bioinformatics pipelines, standardization of methods, and the high cost of NGS. Despite these challenges, NGS is increasingly being adopted in clinical laboratories for pathogen detection, offering a more efficient and accurate alternative to traditional methods. The future of NGS in pathogen identification lies in further advancements in sequencing technologies, data analysis tools, and collaboration between researchers, clinicians, and public health agencies to improve diagnostics, surveillance, and control of infectious diseases.