Diagnostic performance of metagenomic next-generation sequencing in Mycobacterium and non-Mycobacterium infection patients: a retrospective study at a large comprehensive medical center

Background Metagenomic next-generation sequencing (mNGS) has become a potentially valuable complementary test, if not an essential one, in some challenging clinical cases. This study comprehensively compared mNGS with other methods, including TB-IgG, TB-IGRA, TB-DNA, Xpert, culture, and AFS for the diagnosis of and differentiation between TB infection from NTM infection using multiple sample types, including BALF, CSF, blood, pus, tissue, hydrothorax, and ascites. Methods From 2021 to 2024, the clinical data, including imaging, laboratory results, and medical records, of 425 patients with suspected TB infection were retrospectively collected and classified as PTB [306 (72%)], EPTB [67 (15.76%)], and non-TB [52 (12.24%)], according to the final clinical diagnosis. Results Among the three groups, significant differences were observed in age, sex, cough, smoking history, hsCRP, IFN-γ, and hypertension ( P < 0.05). According to the final clinical diagnosis, the sensitivity and specificity of mNGS in all samples were 90.1% (95% CI: 0.866–0.927) and 75.0% (95% CI: 0.618–0.848), respectively. The sensitivity of mNGS was higher than that of TB-IGRA (79.1%), Xpert (72.4%), culture (52.3%), TB-DNA (45.6%), TB-IgG (36.4%), and AFS (10.7%). For distinguishing TB from non-TB, the sensitivity of mNGS was approximately 37.8% higher than that of standard test culture (90.1% vs 36.4%; P < 0.001). Further analysis also showed that MTB read counts from mNGS were highly correlated with MTB burden measured by other laboratory tests ( P < 0.05). Analysis of the ROC curve of mNGS reads showed that the AUC for MTB diagnosis was 0.9073, with a sensitivity of 73.19% and specificity of 96.15% when the recommended cutoff value of 4 reads (Youden’s index, 0.6934) was applied. Conclusions For patients with suspected TB or NTM infection, mNGS may serve as a helpful adjunctive tool, particularly when routine diagnostic tests are unrevealing or indeterminate. It has the potential to assist in distinguishing MTB from NTM and to provide additional evidence to guide appropriate treatment choices, though its results should always be interpreted alongside clinical findings and conventional microbiological testing.

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Journal
Frontiers in Cellular and Infection Microbiology
Published
2026-10-29
DOI
https://doi.org/10.3389/fcimb.2026.1935536
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

Diagnostic performance of metagenomic next-generation sequencing in Mycobacterium and non-Mycobacterium infection patients: a retrospective study at a large comprehensive medical center

Shengkun Peng, Kai Zhang, Honghua Hu, Xiaoli Zhou et al.
1 links
Frontiers in Cellular and Infection Microbiology
Tuberculosis Research and Epidemiology
article

Diagnostic performance of metagenomic next-generation sequencing in Mycobacterium and non-Mycobacterium infection patients: a retrospective study at a large comprehensive medical center

Shengkun Peng, Kai Zhang, Honghua Hu, Xiaoli Zhou, Jiaqiang Wang, Rui Tan, Aibo Liu
article en

Abstract

Background Metagenomic next-generation sequencing (mNGS) has become a potentially valuable complementary test, if not an essential one, in some challenging clinical cases. This study comprehensively compared mNGS with other methods, including TB-IgG, TB-IGRA, TB-DNA, Xpert, culture, and AFS for the diagnosis of and differentiation between TB infection from NTM infection using multiple sample types, including BALF, CSF, blood, pus, tissue, hydrothorax, and ascites. Methods From 2021 to 2024, the clinical data, including imaging, laboratory results, and medical records, of 425 patients with suspected TB infection were retrospectively collected and classified as PTB [306 (72%)], EPTB [67 (15.76%)], and non-TB [52 (12.24%)], according to the final clinical diagnosis. Results Among the three groups, significant differences were observed in age, sex, cough, smoking history, hsCRP, IFN-γ, and hypertension ( P < 0.05). According to the final clinical diagnosis, the sensitivity and specificity of mNGS in all samples were 90.1% (95% CI: 0.866–0.927) and 75.0% (95% CI: 0.618–0.848), respectively. The sensitivity of mNGS was higher than that of TB-IGRA (79.1%), Xpert (72.4%), culture (52.3%), TB-DNA (45.6%), TB-IgG (36.4%), and AFS (10.7%). For distinguishing TB from non-TB, the sensitivity of mNGS was approximately 37.8% higher than that of standard test culture (90.1% vs 36.4%; P < 0.001). Further analysis also showed that MTB read counts from mNGS were highly correlated with MTB burden measured by other laboratory tests ( P < 0.05). Analysis of the ROC curve of mNGS reads showed that the AUC for MTB diagnosis was 0.9073, with a sensitivity of 73.19% and specificity of 96.15% when the recommended cutoff value of 4 reads (Youden’s index, 0.6934) was applied. Conclusions For patients with suspected TB or NTM infection, mNGS may serve as a helpful adjunctive tool, particularly when routine diagnostic tests are unrevealing or indeterminate. It has the potential to assist in distinguishing MTB from NTM and to provide additional evidence to guide appropriate treatment choices, though its results should always be interpreted alongside clinical findings and conventional microbiological testing.

Frontiers in Cellular and Infection MicrobiologyVol. 16
University of Electronic Science and Technology of China (CN), Sichuan University (CN), Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (CN), Chengdu Second People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 12%
Tuberculosis Research and Epidemiology
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