Literature DB >> 32768450

Clinical metagenomic sequencing for diagnosis of pulmonary tuberculosis.

Cui-Lin Shi1, Peng Han2, Pei-Jun Tang1, Meng-Meng Chen2, Zhi-Jian Ye1, Mei-Ying Wu1, Jie Shen1, Hai-Yan Wu1, Zhu-Qing Tan1, Xin Yu3, Guan-Hua Rao4, Jian-Ping Zhang5.   

Abstract

OBJECTIVES: The aim of this study is to investigate the clinical usefulness of metagenomic Next-generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) samples to discriminate pulmonary tuberculosis (PTB) from Non-TB community-acquired pneumonia (CAP) in PTB suspects.
METHODS: We investigate the performance of mNGS on BALF samples from 110 PTB suspects, in comparison with conventional microbiological testing (solid media culture, acid-fast bacilli staining (AFS), Xpert) of BALF or sputum samples and final clinical diagnosis.
RESULTS: We finally clinically diagnosed 48 cases of pulmonary tuberculosis patients and 62 cases of non-tuberculosis patients. Comparing to the final clinical diagnosis, mNGS produced a sensitivity of 47.92%, which was similar to that of Xpert (45.83%) and culture (46.81%), but much higher than that of AFS (29.17%) for TB diagnosis in BALF samples. Apart from detecting Mycobacterium tuberculosis, mNGS also identified mixed infections in PTB patients, including 3 fungal cases and 1 bacteria case. Meanwhile, mNGS efficiently identified 14 of 22 (63.63%) cases of non-tuberculous mycobacteria (NTM), 7 cases of fungi, 1 case of viral infection, and other common bacterial pathogens in Non-PTB group. Finally, mNGS identified 67.23% infection cases within 3 days, while the conventional methods identified 49.58% infection cases for over 90 days.
CONCLUSION: Our data show that mNGS of BALF represents a potentially effective tool for the rapid diagnosis of PTB suspects.
Copyright © 2020 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bronchoalveolar lavage fluid; Community-acquired pneumonia; GeneXpert; Metagenomic sequencing; NTM; Pulmonary tuberculosis

Mesh:

Year:  2020        PMID: 32768450     DOI: 10.1016/j.jinf.2020.08.004

Source DB:  PubMed          Journal:  J Infect        ISSN: 0163-4453            Impact factor:   6.072


  17 in total

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