Bing Zhao

Whole-genome sequencing (WGS) is an increasingly adopted platform for predicting drug resistance in Mycobacterium tuberculosis; however, diagnostic accuracy varies substantially across bioinformatic tools and analytical frameworks, generating considerable uncertainty for clinical laboratory implementation. We conducted a prospectively registered (PROSPERO: CRD420261342739), PRISMA-DTA-compliant systematic review and meta-analysis of diagnostic accuracy studies. PubMed (MEDLINE), Embase, Web of Science, and Cochrane CENTRAL were searched from 1 January 2000 through 28 January 2026. Primary overall sensitivity and specificity were estimated using a tool-level bivariate random-effects model. Exploratory subgroup analyses and meta-regression examined the association between algorithm category and diagnostic-performance heterogeneity. Twenty-eight drug-level evaluations from seven tools (rifampicin, isoniazid, ethambutol, and pyrazinamide for each tool) were compiled from the extracted 2 × 2 data. For the primary tool-level composite analysis, pooled sensitivity was 0.930 (95% CI: 0.907–0.948) and pooled specificity was 0.962 (95% CI: 0.929–0.981). In secondary drug-specific analyses, sensitivity was highest for rifampicin (0.960, 95% CI: 0.934–0.976) and isoniazid (0.933, 95% CI: 0.906–0.953), and lowest for pyrazinamide (0.860, 95% CI: 0.800–0.904). Exploratory tool-level comparisons produced pooled sensitivity estimates of 0.920 for rule-based tools, 0.899 for machine learning tools, and 0.951 for hybrid tools. These comparisons involved only seven tool-level analytic units and cannot disentangle algorithm type from individual tool identity, training data, mutation catalogue version, or validation population. WGS-based bioinformatic tools provide highly specific and generally sensitive predictions of Mycobacterium tuberculosis resistance for first-line drugs across diverse clinical settings. Exploratory differences between tool categories should not be interpreted as causal effects of algorithmic architecture. Future studies should use prospective head-to-head evaluations on shared, geographically diverse isolate collections, alongside continued improvement of resistance catalogues and external validation.

Objectives: To investigate epidemiological/drug-resistance characteristics and identify potential factors related to drug-resistant and clustered tuberculosis in Sichuan. Methods: A total of 295 Mycobacterium tuberculosis (MTB) isolates were collected from surveillance sites in Sichuan from 2019 to 2021. The minimum inhibitory concentrations (MICs) of 12 anti-TB drugs were acquired using the broth microdilution method, followed by whole-genome sequencing (WGS) analysis. Results: Of 268 MTB isolates with both WGS and drug-susceptibility testing (DST) results, 159 (59.3%, 159/268) strains belonged to the Beijing lineage (L2). Isoniazid had the highest resistance rate (15.3%, 41/268), followed by rifampicin (9.3%, 25/268). The sensitivity of WGS to predict drug resistance varied from 75% to 97.6%, and the specificity was above 96.0% for all. rpoB Ser450Leu (41.7%, 10/24) and katG Ser315Thr (70%, 28/40) were the most frequent mutations in rifampicin and isoniazid resistance isolates, respectively. The clustering rate in Sichuan was 9.3% (25/268), and patients ≤ 24 years old (aOR = 11.697; 95% CI: 0.817–167.463) had a greater risk of clustering. Conclusions: Our findings prove that WGS is a promising tool for predicting drug resistance to isoniazid, rifampicin, ethambutol, moxifloxacin and levofloxacin in Sichuan. The higher resistance rate to isoniazid emphasizes the urgent need for susceptibility testing surveillance and application management. Improving the diagnosis, treatment and management of patients ≤ 24 years old may reduce the transmission of MTB in Sichuan.

Background: Although several World Health Organization–endorsed targeted next-generation sequencing (tNGS) assays exist for tuberculosis (TB) drug-resistance detection, their target selection and diagnostic accuracy vary widely. In this study, we developed a novel tNGS workflow (the TB Pro assay) and evaluated its performance in identifying Mycobacterium species and predicting drug resistance.Methods: The TB Pro assay was validated for identifying 10 Mycobacterium tuberculosis complex (MTBC) and 39 nontuberculous mycobacterial (NTM) species, as well as predicting resistance to 4 first-line and 13 second-line anti-TB drugs. The limit of detection (LOD) was determined using 11 reference strains spiked in sputum. The prediction of resistance to anti-tuberculous drugs/drug classes was compared with phenotypic drug susceptibility testing (pDST) and whole-genome sequencing (WGS) using 435 clinical isolates.Results: The assay demonstrated high sensitivity with a calculated LOD of 3.0 CFU/ml for MTB and 1.4–16.2 CFU/ml for most NTMs, except for Mycobacterium intracellulare with 117.9 CFU/ml. Using pDST as the reference standard, the sensitivity of the TB Pro assay for the detection of resistance ranged from 74.3% (ethambutol) to 94.4% (rifampicin), with specificity values >98% for all drugs. Compared with WGS, the sensitivity of the TB Pro assay was over 98.0% for all drugs except pyrazinamide (66.7%), and the specificity values were all nearly 100.0%. Directly on sputum, the TB Pro assay showed 100% agreement with smear- and culture-positive sputum specimens.Conclusions: The TB Pro assay represents a sensitive and specific solution for simultaneous mycobacterial identification and comprehensive drug-resistance profiling, performing robustly on both cultured isolates and direct clinical specimens.

Mycobacterial membrane proteins play a pivotal role in the bacterial invasion of host cells; however, the precise mechanisms underlying certain membrane proteins remain elusive. Mycolicibacterium smegmatis (Ms) msmeg5257 is a hemolysin III family protein that is homologous to Mycobacterium tuberculosis (Mtb) Rv1085c, but it has an unclear function in growth. To address this issue, we utilized the CRISPR/Cas9 gene editor to construct Δmsmeg5257 strains and combined RNA transcription and LC-MS/MS protein profiling to determine the functional role of msmeg5257 in Ms growth. The correlative analysis showed that the deletion of msmeg5257 inhibits ABC transporters in the cytomembrane and inhibits the biosynthesis of amino acids in the cell wall. Corresponding to these results, we confirmed that MSMEG5257 localizes in the cytomembrane via subcellular fractionation and also plays a role in facilitating the transport of iron ions in environments with low iron levels. Our data provide insights that msmeg5257 plays a role in maintaining Ms metabolic homeostasis, and the deletion of msmeg5257 significantly impacts the growth rate of Ms. Furthermore, msmeg5257, a promising drug target, offers a direction for the development of novel therapeutic strategies against mycobacterial diseases.

Early diagnosis of drug susceptibility for tuberculosis (TB) patients could guide the timely initiation of effective treatment. We evaluated a novel multiplex xMAP TIER (Tuberculosis-Isoniazid-Ethambutol-Rifampicin) assay based on the Luminex xMAP system to detect first-line anti-tuberculous drug resistance. Deoxyribonucleic acid samples from 353 Mycobacterium tuberculosis clinical isolates were amplified by multiplex polymerase chain reaction, followed by hybridization and analysis through the xMAP system. Compared with the broth microdilution method, the sensitivity and specificity of the xMAP TIER assay for detecting resistance was 94.9% (95%CI, 90.0–99.8%) and 98.9% (95%CI, 97.7–100.0%) for rifampicin; 89.1% (95%CI, 83.9–94.3%) and 100.0% (95%CI, 100.0–100.0%) for isoniazid; 82.1% (95% CI, 68.0–96.3%) and 99.7% (95% CI, 99.0–100.0%) for ethambutol. With DNA sequencing as the reference standard, the sensitivity and specificity of xMAP TIER for detecting resistance were 95.0% (95% CI, 90.2–99.8%) and 99.6% (95% CI, 98.9–100.0%) for rifampicin; 96.9% (95% CI, 93.8–99.9%) and 100.0% (95% CI, 100.0–100.0%) for isoniazid; 86.1% (95% CI, 74.8–97.4%) and 100.0% (95% CI, 100.0–100.0%) for ethambutol. The results achieved showed that the xMAP TIER assay had good performance for detecting first-line anti-tuberculosis drug resistance, and it has the potential to diagnose drug-resistant tuberculosis more accurately due to the addition of more optimal design primers and probes on open architecture xMAP system.

Mycobacterium abscessus (M. abscessus) and Mycobacterium massiliense (M. massiliense) are major pathogens that cause post-surgical wound infection and chronic pulmonary disease. Although they are closely related subspecies of M. abscessus complex, their infections are associated with different drug-resistance and cure rate. In the present study, a loop-mediated isothermal amplification (LAMP) coupled with lateral flow dipstick (LFD) method was developed to simultaneous detect M. abscessus and M. massiliense, via specific erm(41) gene. The amplification was carried out at 65 °C for only 60 min, and the results could be visualized on a lateral flow strip. Positive results only occurred in M. abscessus and M. massiliense, no cross-reaction with other mycobacterial species was observed. Therefore, the cost-effective MABC (M. abscessus complex)–LAMP–LFD method developed here was able to correct the diagnose of M. abscessus and M. massiliense infection in a short time. Thus, this method could be used to guide clinicians in treatment of M. abscessus group infections.