Assessment of the GenoType MTBDRsl VER 2.0 compared to the phenotypic drug susceptibility testing and whole genome sequencing for the rapid detection of resistance to fluoroquinolone and second-line injectable drugs among rifampicin-resistant Mycobacterium tuberculosis isolates

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.

Evaluation of genetic mutations associated with phenotypic resistance to fluoroquinolones, bedaquiline, and linezolid in clinical Mycobacterium tuberculosis: A systematic review and meta-analysis

OBJECTIVES

The aim of the study was to update the classification of drugs used in multidrug-resistant tuberculosis (MDR-TB) regimens. Group A drugs (fluoroquinolones, bedaquiline (BDQ), and linezolid (LZD)) are crucial drugs for the control of MDR-TB. Molecular drug resistance assays could facilitate the effective use of Group A drugs.

METHODS

We summarised the evidence implicating specific genetic mutations in resistance to Group A drugs. We searched PubMed, Embase, MEDLINE, and the Cochrane Library for studies published from the inception of each database until July 1, 2022. Using a random-effects model, we calculated the odds ratios and 95% confidence intervals as our measures of association.

RESULTS

A total of 5001 clinical isolates were included in 47 studies. Mutations in gyrA A90V, D94G, D94N, and D94Y were significantly associated with an increased risk of a levofloxacin (LFX)-resistant phenotype. In addition, mutations in gyrA G88C, A90V, D94G, D94H, D94N, and D94Y were significantly associated with an increased risk of a moxifloxacin (MFX)-resistant phenotype. In only one study, the majority of gene loci (n = 126, 90.65%) in BDQ-resistant isolates were observed to have unique mutations in atpE, Rv0678, mmpL5, pepQ, and Rv1979c. The most common mutations occurred at four sites in the rrl gene (g2061t, g2270c, g2270t, and g2814t) and at one site in rplC (C154R) in LZD-resistant isolates. Our meta-analysis demonstrated that there were no mutations associated with BDQ- or LZD-resistant phenotypes.

CONCLUSION

The mutations detected by rapid molecular assay were correlated with phenotypic resistance to LFX and MFX. The absence of mutation-phenotype associations for BDQ and LZD hindered the development of a rapid molecular assay.

Metabolomic analysis of Mycobacterium tuberculosis reveals metabolic profiles for identification of drug-resistant tuberculosis

The detection of pre-extensively (pre-XDR) and extensively drug-resistant tuberculosis (XDR-TB) is challenging. Drug-susceptibility tests for some anti-TB drugs, especially ethambutol (ETH) and ethionamide (ETO), are problematic due to overlapping thresholds to differentiate between susceptible and resistant phenotypes. We aimed to identify possible metabolomic markers to detect Mycobacterium tuberculosis (Mtb) strains causing pre-XDR and XDR-TB. The metabolic patterns of ETH- and ETO-resistant Mtb isolates were also investigated. Metabolomics of 150 Mtb isolates (54 pre-XDR, 63 XDR-TB and 33 pan-susceptible; pan-S) were investigated. Metabolomics of ETH and ETO phenotypically resistant subgroups were analyzed using UHPLC-ESI-QTOF-MS/MS. Orthogonal partial least-squares discriminant analysis revealed distinct separation in all pairwise comparisons among groups. Two metabolites (meso-hydroxyheme and itaconic anhydride) were able to differentiate the pre-XDR and XDR-TB groups from the pan-S group with 100% sensitivity and 100% specificity. In comparisons of the ETH and ETO phenotypically resistant subsets, sets of increased (ETH = 15, ETO = 7) and decreased (ETH = 1, ETO = 6) metabolites specific for the resistance phenotype of each drug were found. We demonstrated the potential for metabolomics of Mtb to differentiate among types of DR-TB as well as between isolates that were phenotypically resistant to ETO and ETH. Thus, metabolomics might be further applied for DR-TB diagnosis and patient management.

Comparative genomics of drug-resistant strains of Mycobacterium tuberculosis in Ecuador

BACKGROUND

Tuberculosis is a serious infectious disease affecting millions of people. In spite of efforts to reduce the disease, increasing antibiotic resistance has contributed to persist in the top 10 causes of death worldwide. In fact, the increased cases of multi (MDR) and extreme drug resistance (XDR) worldwide remains the main challenge for tuberculosis control. Whole genome sequencing is a powerful tool for predicting drug resistance-related variants, studying lineages, tracking transmission, and defining outbreaks. This study presents the identification and characterization of resistant clinical isolates of Mycobacterium tuberculosis including a phylogenetic and molecular resistance profile study by sequencing the complete genome of 24 strains from different provinces of Ecuador.

RESULTS

Genomic sequencing was used to identify the variants causing resistance. A total of 15/21 isolates were identified as MDR, 4/21 as pre-XDR and 2/21 as XDR, with three isolates discarded due to low quality; the main sub-lineage was LAM (61.9%) and Haarlem (19%) but clades X, T and S were identified. Of the six pre-XDR and XDR strains, it is noteworthy that five come from females; four come from the LAM sub-lineage and two correspond to the X-class sub-lineage. A core genome of 3,750 genes, distributed in 295 subsystems, was determined. Among these, 64 proteins related to virulence and implicated in the pathogenicity of M. tuberculosis and 66 possible pharmacological targets stand out. Most variants result in nonsynonymous amino acid changes and the most frequent genotypes were identified as conferring resistance to rifampicin, isoniazid, ethambutol, para-aminosalicylic acid and streptomycin. However, an increase in the resistance to fluoroquinolones was detected.

CONCLUSION

This work shows for the first time the variability of circulating resistant strains between men and women in Ecuador, highlighting the usefulness of genomic sequencing for the identification of emerging resistance. In this regard, we found an increase in fluoroquinolone resistance. Further sampling effort is needed to determine the total variability and associations with the metadata obtained to generate better health policies.