Rapid Detection of Ethambutol-Resistant Mycobacterium tuberculosis from Sputum by High-Resolution Melting Analysis in Beijing, China

A precision overview of genomic resistance screening in Ecuadorian isolates of Mycobacterium tuberculosis using web-based bioinformatics tools

INTRODUCTION

Tuberculosis (TB) is among the deadliest diseases worldwide, and its impact is mainly due to the continuous emergence of resistant isolates during treatment due to the laborious process of resistance diagnosis, nonadherence to treatment and circulation of previously resistant isolates of Mycobacterium tuberculosis. In this study, we evaluated the performance and functionalities of web-based tools, including Mykrobe, TB-profiler, PhyResSE, KvarQ, and SAM-TB, for detecting resistance in 88 Ecuadorian isolates of Mycobacterium tuberculosis drug susceptibility tested previously. Statistical analysis was used to determine the correlation between genomic and phenotypic analysis. Our results showed that with the exception of KvarQ, all tools had the highest correlation with the conventional drug susceptibility test (DST) for global resistance detection (98% agreement and 0.941 Cohen's kappa), while SAM-TB, PhyResSE, TB-profiler and Mykrobe had better correlations with DST for first-line drug analysis individually. We also identified that in our study, only 50% of mutations characterized by the web-based tools in the rpoB, katG, embB, pncA, gyrA and rrs regions were canonical and included in the World Health Organization (WHO) catalogue. Our findings suggest that SAM-TB, PhyResSE, TB-profiler and Mykrobe were efficient in determining canonical resistance-related mutations, but more analysis is needed to improve second-line detection. Improving surveillance programs using whole-genome sequencing tools for first-line drugs, MDR-TB and XDR-TB is essential to understand the molecular epidemiology of TB in Ecuador.

IMPORTANCE

Tuberculosis, an infectious disease caused by Mycobacterium tuberculosis, most commonly affects the lungs and is often spread through the air when infected people cough, sneeze, or spit. However, despite the existence of effective drug treatment, patient adherence, long duration of treatment, and late diagnosis have reduced the effectiveness of therapy and increased drug resistance. The increase in resistant cases, added to the impact of the COVID-19 pandemic, has highlighted the importance of implementing efficient and timely diagnostic methodologies worldwide. The significance of our research is in evaluating and identifying a more efficient and user-friendly web-based tool to characterize resistance in Mycobacterium tuberculosis by whole-genome sequencing, which will allow more routine application to improve TB strain surveillance programs locally.

High resolution melting assay as a reliable method for diagnosing drug-resistant TB cases: a systematic review and meta-analysis

BACKGROUND

Tuberculosis (TB) is one of the most contagious infectious diseases worldwide. Currently, drug-resistant Mycobacterium tuberculosis (Mtb) isolates are considered as one of the main challenges in the global TB control strategy. Rapid detection of resistant strains effectively reduces morbidity and mortality of world's population. Although both culture and conventional antibiotic susceptibility testing are time-consuming, recent studies have shown that high resolution melting (HRM) assay can be used to determine the types of antibiotic resistance. In the present meta-analysis, we evaluated the discriminative power of HRM in detecting all drug-resistance cases of TB.

METHODS

A systematic search was performed using databases such as Cochrane Library, Scopus, PubMed, Web of Science, and Google Scholar. Related studies on the effect of HRM in the diagnosis of drug-resistant (DR) TB cases were retrieved by April 2021. We used Meta-Disc software to evaluate the pooled diagnostic sensitivity and specificity of HRM for the detection of each type of drug-resistant cases. Finally, diagnostic value of HRM was characterized by summary receiver operating characteristic (SROC) curve and the area under the curve (AUC) method.

RESULTS

Overall 47 studies (4,732 Mtb isolates) met our criteria and were included in the present meta-analysis. Sensitivity, specificity, and AUC of HRM were measured for antibiotics such as isoniazid (93%, 98%, 0.987), rifampin (94%, 97%, 0963), ethambutol (82%, 87%, 0.728), streptomycin (82%, 95%, 0.957), pyrazinamide (72%, 84%, 0.845), fluoroquinolones (86%, 99%, 0.997), MDR-TB (90%, 98%, 0.989), and pan-drug-resistant TB (89%, 95%, 0.973).

CONCLUSIONS

The HRM assay has high accuracy for the identification of drug-resistant TB, particularly firs-line anti-TB drugs. Therefore, this method is considered as an alternative option for the rapid diagnosis of DR-TB cases. However, due to heterogeneity of included studies, the results of HRM assays should be interpreted based on conventional drug susceptibility testing.