Volume 5, Issue 1 2000792
Review

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

Na Li

Na Li

Department of Infectious Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032 China

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Qingqing Cai

Qingqing Cai

Genoxor Medical Science and Technology Inc., Zhejiang, 317317 China

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Qing Miao

Qing Miao

Department of Infectious Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032 China

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Zeshi Song

Zeshi Song

Genoxor Medical Science and Technology Inc., Zhejiang, 317317 China

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Yuan Fang

Yuan Fang

Genoxor Medical Science and Technology Inc., Zhejiang, 317317 China

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Bijie Hu

Corresponding Author

Bijie Hu

Department of Infectious Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032 China

E-mail: [email protected]

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First published: 13 December 2020
Citations: 52

Abstract

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Conflict of Interest

The authors declare no conflict of interest.

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