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Application of Next Generation Sequencing in identifying different pathogens
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  • Shan Xu,
  • Aljuboori M. Nafea,
  • Duanyang Wang,
  • Ahmed M. Salama,
  • Manal A. Aziz,
  • Yuer Wang,
  • Yigang Tong
Shan Xu
Beijing University of Chemical Technology College of Life Science and Technology

Corresponding Author:[email protected]

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Aljuboori M. Nafea
Beijing University of Chemical Technology College of Life Science and Technology
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Duanyang Wang
Beijing University of Chemical Technology College of Life Science and Technology
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Ahmed M. Salama
Beijing University of Chemical Technology Department of Chemical Engineering and Technology
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Manal A. Aziz
Ibn Sina University for Medical and Pharmaceutical Sciences
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Yuer Wang
Beijing University of Chemical Technology College of Life Science and Technology
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Yigang Tong
Beijing University of Chemical Technology College of Life Science and Technology
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Abstract

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing clinical infectious diseases. Currently, available pathogen detection techniques, which include mass spectrometry, biochemical tests (metabolic fingerprinting), molecular testing (usually PCR), and culture-based procedures, are limited in application and time-consuming to produce results. Next Generation Sequencing (NGS) have emerged as an essential technology for identifying clinical pathogens. NGS is a cutting-edge DNA sequencing method with high throughput, which can create massive volumes of sequences with a wide range of potential uses in research and diagnostic settings. NGS presents a revolutionary way to overcome the issues above with fast speed, available application in unknown pathogens detection, improved sensitivity, as well as efficient data interpretation. This review introduces the NGS technology in detail and summarizes the application of the NGS in detecting different pathogens, including bacteria, fungi, and viruses, and analyzing the challenges and the outlook for using NGS to detect clinical pathogens. Therefore, this work provides theoretical basis for NGS study and promotes the application of NGS in diagnosing various clinical pathogens.