Assessment of current diagnostic algorithm for detection of mixed infection with Mycobacterium tuberculosis and nontuberculous mycobacteria
Background: The increasing pulmonary diseases are reported to be affected by mixed infection of Mycobacterium tuberculosis (MTB) and nontuberculous mycobacteria (NTM). In this study, our objective was to assess the efficiency of mycobacterial culture plus DNA sequencing to detect the mixed infection...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2020-12-01
|
Series: | Journal of Infection and Public Health |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1876034120304305 |
_version_ | 1818725374385717248 |
---|---|
author | Qian Liang Yuanyuan Shang Fengmin Huo Yi Xue Yunxu Li Lingling Dong Shanshan Li Yu Pang |
author_facet | Qian Liang Yuanyuan Shang Fengmin Huo Yi Xue Yunxu Li Lingling Dong Shanshan Li Yu Pang |
author_sort | Qian Liang |
collection | DOAJ |
description | Background: The increasing pulmonary diseases are reported to be affected by mixed infection of Mycobacterium tuberculosis (MTB) and nontuberculous mycobacteria (NTM). In this study, our objective was to assess the efficiency of mycobacterial culture plus DNA sequencing to detect the mixed infections with MTB and various NTM organisms. We also aimed to investigate how efficiently GeneXpert detected MTB in mixed infections with NTM in in vitro models. Methods: A serial of mixed infection samples was generated by combining suspensions of MTB and five NTM bacteria, respectively. The mixed suspensions were further detected with GeneXpert and liquid culture plus DNA sequencing. Results: Overall, the GeneXpert assay exhibited promising capability to identify the presence of MTB at different proportions ranging from 1% to 99%. For the liquid culture, the subsequent DNA sequencing only detected the presence of NTM bacteria in the mixed samples, which the proportion of NTM ranged from 1% to 99%, including M. intracellulare, M. kansasii, M. abscessus, and M. fortuitum. For M. avium, DNA sequencing was able to identify the mixtures as M. avium infection in suspensions with no less than 10% M. avium bacteria, whereas only MTB was found in the other suspensions with less M. avium bacteria. Conclusions: Our data demonstrate that the current diagnostic algorithm cannot yield a precise detection of mixed infections with MTB and NTM bacteria. The GeneXpert assay only identify MTB in the mixed samples, while the subculture plus DNA sequencing prefers to identify the NTM species with the higher growth rate. Further targeted molecular analysis by specific capture of multiple loci of mycobacterial species from specimens is urgently required to solve this diagnostic dilemma. |
first_indexed | 2024-12-17T21:41:18Z |
format | Article |
id | doaj.art-1ed6005b42724f09bc149c96dcefde38 |
institution | Directory Open Access Journal |
issn | 1876-0341 |
language | English |
last_indexed | 2024-12-17T21:41:18Z |
publishDate | 2020-12-01 |
publisher | Elsevier |
record_format | Article |
series | Journal of Infection and Public Health |
spelling | doaj.art-1ed6005b42724f09bc149c96dcefde382022-12-21T21:31:37ZengElsevierJournal of Infection and Public Health1876-03412020-12-01131219671971Assessment of current diagnostic algorithm for detection of mixed infection with Mycobacterium tuberculosis and nontuberculous mycobacteriaQian Liang0Yuanyuan Shang1Fengmin Huo2Yi Xue3Yunxu Li4Lingling Dong5Shanshan Li6Yu Pang7National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, Beijing, ChinaNational Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, Beijing, ChinaNational Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, Beijing, ChinaNational Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, Beijing, ChinaNational Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, Beijing, ChinaNational Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, Beijing, ChinaCorresponding author at: Beijing Chest Hospital, Capital Medical University, No. 97, Machang, Tongzhou District, Beijing 101149, China.; National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, Beijing, ChinaCorresponding author at: Beijing Chest Hospital, Capital Medical University, No. 97, Machang, Tongzhou District, Beijing 101149, China.; National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory on Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, Beijing, ChinaBackground: The increasing pulmonary diseases are reported to be affected by mixed infection of Mycobacterium tuberculosis (MTB) and nontuberculous mycobacteria (NTM). In this study, our objective was to assess the efficiency of mycobacterial culture plus DNA sequencing to detect the mixed infections with MTB and various NTM organisms. We also aimed to investigate how efficiently GeneXpert detected MTB in mixed infections with NTM in in vitro models. Methods: A serial of mixed infection samples was generated by combining suspensions of MTB and five NTM bacteria, respectively. The mixed suspensions were further detected with GeneXpert and liquid culture plus DNA sequencing. Results: Overall, the GeneXpert assay exhibited promising capability to identify the presence of MTB at different proportions ranging from 1% to 99%. For the liquid culture, the subsequent DNA sequencing only detected the presence of NTM bacteria in the mixed samples, which the proportion of NTM ranged from 1% to 99%, including M. intracellulare, M. kansasii, M. abscessus, and M. fortuitum. For M. avium, DNA sequencing was able to identify the mixtures as M. avium infection in suspensions with no less than 10% M. avium bacteria, whereas only MTB was found in the other suspensions with less M. avium bacteria. Conclusions: Our data demonstrate that the current diagnostic algorithm cannot yield a precise detection of mixed infections with MTB and NTM bacteria. The GeneXpert assay only identify MTB in the mixed samples, while the subculture plus DNA sequencing prefers to identify the NTM species with the higher growth rate. Further targeted molecular analysis by specific capture of multiple loci of mycobacterial species from specimens is urgently required to solve this diagnostic dilemma.http://www.sciencedirect.com/science/article/pii/S1876034120304305Mycobacterium tuberculosisNontuberculous mycobacteriaMixed infection |
spellingShingle | Qian Liang Yuanyuan Shang Fengmin Huo Yi Xue Yunxu Li Lingling Dong Shanshan Li Yu Pang Assessment of current diagnostic algorithm for detection of mixed infection with Mycobacterium tuberculosis and nontuberculous mycobacteria Journal of Infection and Public Health Mycobacterium tuberculosis Nontuberculous mycobacteria Mixed infection |
title | Assessment of current diagnostic algorithm for detection of mixed infection with Mycobacterium tuberculosis and nontuberculous mycobacteria |
title_full | Assessment of current diagnostic algorithm for detection of mixed infection with Mycobacterium tuberculosis and nontuberculous mycobacteria |
title_fullStr | Assessment of current diagnostic algorithm for detection of mixed infection with Mycobacterium tuberculosis and nontuberculous mycobacteria |
title_full_unstemmed | Assessment of current diagnostic algorithm for detection of mixed infection with Mycobacterium tuberculosis and nontuberculous mycobacteria |
title_short | Assessment of current diagnostic algorithm for detection of mixed infection with Mycobacterium tuberculosis and nontuberculous mycobacteria |
title_sort | assessment of current diagnostic algorithm for detection of mixed infection with mycobacterium tuberculosis and nontuberculous mycobacteria |
topic | Mycobacterium tuberculosis Nontuberculous mycobacteria Mixed infection |
url | http://www.sciencedirect.com/science/article/pii/S1876034120304305 |
work_keys_str_mv | AT qianliang assessmentofcurrentdiagnosticalgorithmfordetectionofmixedinfectionwithmycobacteriumtuberculosisandnontuberculousmycobacteria AT yuanyuanshang assessmentofcurrentdiagnosticalgorithmfordetectionofmixedinfectionwithmycobacteriumtuberculosisandnontuberculousmycobacteria AT fengminhuo assessmentofcurrentdiagnosticalgorithmfordetectionofmixedinfectionwithmycobacteriumtuberculosisandnontuberculousmycobacteria AT yixue assessmentofcurrentdiagnosticalgorithmfordetectionofmixedinfectionwithmycobacteriumtuberculosisandnontuberculousmycobacteria AT yunxuli assessmentofcurrentdiagnosticalgorithmfordetectionofmixedinfectionwithmycobacteriumtuberculosisandnontuberculousmycobacteria AT linglingdong assessmentofcurrentdiagnosticalgorithmfordetectionofmixedinfectionwithmycobacteriumtuberculosisandnontuberculousmycobacteria AT shanshanli assessmentofcurrentdiagnosticalgorithmfordetectionofmixedinfectionwithmycobacteriumtuberculosisandnontuberculousmycobacteria AT yupang assessmentofcurrentdiagnosticalgorithmfordetectionofmixedinfectionwithmycobacteriumtuberculosisandnontuberculousmycobacteria |