1
|
Gao J, Zhao L, Chen G, Huang C, Kong W, Feng Y, Zhen G. The value of metagenomic next-generation sequencing for the diagnosis of pulmonary tuberculosis using bronchoalveolar lavage fluid. Lab Med 2024; 55:96-102. [PMID: 37267076 PMCID: PMC10771034 DOI: 10.1093/labmed/lmad041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023] Open
Abstract
OBJECTIVE The aim of this study was to compare metagenomic next-generation sequencing (mNGS) with other methods, including Xpert MTB/RIF, Mycobacterium tuberculosis (MTB) culture, and acid-fast bacillus (AFB) staining in the diagnosis of pulmonary tuberculosis (PTB) using bronchoalveolar lavage fluid (BALF). METHODS The data of 186 patients with suspected PTB were retrospectively collected from January 2020 to May 2021 at Tongji Hospital. BALF samples were collected from all patients and analyzed using AFB staining, MTB culture, Xpert MTB/RIF, and mNGS. RESULTS Of the 186 patients, 38 patients were ultimately diagnosed as PTB. Metagenomic next-generation sequencing exhibited a sensitivity of 78.95%, which was higher than AFB staining (27.59%) and MTB culture (44.12%) but similar to Xpert MTB/RIF (72.73%). Utilization of combined methods demonstrates improvement for PTB diagnosis. In support of this, the area under the receiver operating characteristic curve for the combination of mNGS and MTB culture (0.933, 95% CI: 0.871, 0.995) was larger than those of mNGS, Xpert MTB/RIF, MTB culture, and the combination of Xpert MTB/RIF and MTB culture. CONCLUSION The sensitivity of mNGS in the diagnosis of PTB using BALF specimen is similar to Xpert MTB/RIF. Metagenomic next-generation sequencing in combination with MTB culture may further improve the diagnosis of pulmonary tuberculosis.
Collapse
Affiliation(s)
- Jiali Gao
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Respiratory Diseases, National Health Commission of the People’s Republic of China, and National Clinical Research Center for Respiratory Diseases, Wuhan, China
| | - Lu Zhao
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Respiratory Diseases, National Health Commission of the People’s Republic of China, and National Clinical Research Center for Respiratory Diseases, Wuhan, China
| | - Gongqi Chen
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Respiratory Diseases, National Health Commission of the People’s Republic of China, and National Clinical Research Center for Respiratory Diseases, Wuhan, China
| | - Chunli Huang
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Respiratory Diseases, National Health Commission of the People’s Republic of China, and National Clinical Research Center for Respiratory Diseases, Wuhan, China
| | - Weiqiang Kong
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Respiratory Diseases, National Health Commission of the People’s Republic of China, and National Clinical Research Center for Respiratory Diseases, Wuhan, China
| | - Yuchen Feng
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Respiratory Diseases, National Health Commission of the People’s Republic of China, and National Clinical Research Center for Respiratory Diseases, Wuhan, China
| | - Guohua Zhen
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Respiratory Diseases, National Health Commission of the People’s Republic of China, and National Clinical Research Center for Respiratory Diseases, Wuhan, China
| |
Collapse
|
2
|
Liu J, Zhang Q, Dong YQ, Yin J, Qiu YQ. Diagnostic accuracy of metagenomic next-generation sequencing in diagnosing infectious diseases: a meta-analysis. Sci Rep 2022; 12:21032. [PMID: 36470909 PMCID: PMC9723114 DOI: 10.1038/s41598-022-25314-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 11/28/2022] [Indexed: 12/12/2022] Open
Abstract
Many common pathogens are difficult or impossible to detect using conventional microbiological tests. However, the rapid and untargeted nature of metagenomic next-generation sequencing (mNGS) appears to be a promising alternative. To perform a systematic review and meta-analysis of evidence regarding the diagnostic accuracy of mNGS in patients with infectious diseases. An electronic literature search of Embase, PubMed and Scopus databases was performed. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Summary receiver operating characteristics (sROC) and the area under the curve (AUC) were calculated; A random-effects model was used in cases of heterogeneity. A total of 20 papers were eligible for inclusion and synthesis. The sensitivity and specificity of diagnostic mNGS were 75% and 68%, respectively. The AUC from the SROC was 85%, corresponding to excellent performance. mNGS demonstrated satisfactory diagnostic performance for infections and yielded an overall detection rate superior to conventional methods.
Collapse
Affiliation(s)
- Jian Liu
- grid.13402.340000 0004 1759 700XDepartment of Intensive Care Unit, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang China
| | - Qiao Zhang
- grid.13402.340000 0004 1759 700XDepartment of Clinical Pharmacy, Zhejiang Provincial Key Laboratory for Drug Evaluation and Clinical Research, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang China
| | - Yong-Quan Dong
- Department of Respiratory Disease, Yinzhou No.2 Hospital, Ningbo, Zhejiang China
| | - Jie Yin
- grid.9227.e0000000119573309Department of Colorectal Medicine, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang China
| | - Yun-Qing Qiu
- grid.13402.340000 0004 1759 700XDepartment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang China
| |
Collapse
|
3
|
Kalchev Y, Murdjeva M. Current methods for microbiological diagnosis of acute central nervous system infections. Folia Med (Plovdiv) 2022; 64:709-715. [PMID: 36876544 DOI: 10.3897/folmed.64.e72257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 10/04/2021] [Indexed: 11/06/2022] Open
Abstract
The incidence of infections affecting the central nervous system has increased in recent years, making neuroinfections a current global health problem. The central nervous system is quite well protected from the external and internal environments, although it is susceptible to infection by a wide variety of pathogens. The etiological diversity further complicates the management of such infections because it is important to identify correctly the specific cause in order to choose the most appropriate antimicrobial therapy. Diagnosis is made not only based on clinical and epidemiological data but also on the results of clinical laboratory and microbiological examination of cerebrospinal fluid. This article aims to review current microbiological methods in the diagnosis of acute central nervous system infections and help healthcare providers to recognize their advantages and limitations in order to manage their patients appropriately.
Collapse
|
4
|
A Retrospective Analysis of Metagenomic Next Generation Sequencing (mNGS) of Cerebrospinal Fluid from Patients with Suspected Encephalitis or Meningitis Infections. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:5641609. [PMID: 35494515 PMCID: PMC9050255 DOI: 10.1155/2022/5641609] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/28/2022] [Accepted: 03/31/2022] [Indexed: 11/18/2022]
Abstract
We determined the clinical value of metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) for the diagnosis of patients with suspected encephalitis or meningitis infection. Clinical data were collected and retrospectively analyzed from patients with suspected cases of encephalitis or meningitis who presented at four hospitals in Ningbo from January 1st, 2019 to December 31st, 2020. Of a total of 66 suspected cases, 41 (62.12%) were diagnosed with central nervous system infections, which included 18 cases (27.27%) of viral infection, 13 cases (19.70%) of bacterial infection, 3 cases (4.55%) of Mycobacterium tuberculosis, 5 cases (7.58%) of fungal infection, and 2 cases (3.03%) of Rickettsia infection. From these cases, mNGS identified 25 (37.88%) true-positive cases, 8 (12.12%) false-positive cases, 20 (30.30%) true-negative cases, and 13 (19.70%) false-negative cases. The sensitivity of mNGS was 65.79% with a specificity of 71.43%. The positive rate was higher compared with traditional methods (37.88% vs. 24.39%). The results indicate that mNGS technology is a more sensitive method for detecting suspected infectious encephalitis or meningitis compared with traditional pathogen detection methods.
Collapse
|
5
|
Shi CL, Han P, Tang PJ, Chen MM, Ye ZJ, Wu MY, Shen J, Wu HY, Tan ZQ, Yu X, Rao GH, Zhang JP. Clinical metagenomic sequencing for diagnosis of pulmonary tuberculosis. J Infect 2020; 81:567-574. [PMID: 32768450 DOI: 10.1016/j.jinf.2020.08.004] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 07/29/2020] [Accepted: 08/02/2020] [Indexed: 01/09/2023]
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.
Collapse
Affiliation(s)
- Cui-Lin Shi
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China
| | - Peng Han
- Genskey Medical Technology Co., Ltd, Beijing, China
| | - Pei-Jun Tang
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China
| | | | - Zhi-Jian Ye
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China
| | - Mei-Ying Wu
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China
| | - Jie Shen
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China
| | - Hai-Yan Wu
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China
| | - Zhu-Qing Tan
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China
| | - Xin Yu
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China.
| | - Guan-Hua Rao
- Genskey Medical Technology Co., Ltd, Beijing, China.
| | - Jian-Ping Zhang
- The Affiliated Infectious Hospital of Soochow University, 10 Guangqian Road, Suzhou, Suzhou, Jiangsu 215131, China; The Fifth People's Hospital of Suzhou, Suzhou, China.
| |
Collapse
|
6
|
Abstract
Infectious meningitis can be caused by viral, bacterial or fungal pathogens. Despite widely available treatments, many types of infectious meningitis are still associated with significant morbidity and mortality. Delay in diagnosis contributes to poor outcomes. Cerebrospinal fluid cultures have been used traditionally but are time intensive and sensitivity is decreased by empiric treatment prior to culture. More rapid techniques such as the cryptococcal lateral flow assay (IMMY), GeneXpert MTB/Rif Ultra (Cepheid) and FilmArray multiplex-PCR (Biofire) are three examples that have drastically changed meningitis diagnostics. This review will discuss a holistic approach to diagnosing bacterial, mycobacterial, viral and fungal meningitis.
Collapse
Affiliation(s)
- Victoria Poplin
- Department of Medicine, University of Kansas, Kansas City, KS 66160, USA
| | - David R Boulware
- Division of Infectious Diseases & International Medicine, Department of Medicine, University of Minnesota, Minneapolis, MN 55455, USA
| | - Nathan C Bahr
- Division of Infectious Diseases, Department of Medicine, University of Kansas, Kansas City, KS 66160, USA
| |
Collapse
|
7
|
Challenges to develop an equine herpesvirus vaccine in China. J Infect 2020; 80:578-606. [PMID: 32017972 DOI: 10.1016/j.jinf.2020.01.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 01/18/2020] [Indexed: 11/20/2022]
|
8
|
Hong NTT, Nghia HDT, Thanh TT, Lan NPH, Ny NTH, Ngoc NM, Hang VTT, Chau LTM, Quynh VX, Diem LT, Hanh BTB, Hanh NHH, Duc DT, Man DNH, Campbell J, Oanh PKN, Day J, Phu NH, Chau NVV, Thwaites G, Tan LV. Cerebrospinal fluid MinION sequencing of 16S rRNA gene for rapid and accurate diagnosis of bacterial meningitis. J Infect 2019; 80:469-496. [PMID: 31891725 PMCID: PMC7113840 DOI: 10.1016/j.jinf.2019.12.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 12/23/2019] [Indexed: 11/30/2022]
Affiliation(s)
| | - Ho Dang Trung Nghia
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam; Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Tran Tan Thanh
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | | | | | - Nghiem My Ngoc
- Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Vu Thi Ty Hang
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Le Thi My Chau
- Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Van Xuan Quynh
- Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Le Thi Diem
- Department of Medicine, Vietnam National University, Ho Chi Minh City, Vietnam
| | | | - Nguyen Ho Hong Hanh
- Department of Medicine, Vietnam National University, Ho Chi Minh City, Vietnam
| | - Du Trong Duc
- Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam
| | | | - James Campbell
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | | | - Jeremy Day
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Nguyen Hoan Phu
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Department of Medicine, Vietnam National University, Ho Chi Minh City, Vietnam
| | | | - Guy Thwaites
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Le Van Tan
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam.
| |
Collapse
|