Background Bedaquiline is a crucial drug for control of rifampicin-resistant tuberculosis. Molecular drug resistance assays could facilitate effective use of bedaquiline and surveillance of drug resistance emergence. To facilitate molecular assay development, we aimed to identify genomic markers of bedaquiline resistance.Methods In this systematic review and individual isolate analysis, we searched Europe PubMed Central and Scopus for studies published from the inception of each database until Oct 19, 2020, that assessed genotypic and phenotypic bedaquiline resistance in clinical or non-clinical Mycobacterium tuberculosis isolates. All studies reporting on the assessment of variants in the four genes of interest (Rv0678, atpE, pepQ, and Rv1979c) and phenotypic bedaquiline data in both clinical and non-clinical samples were included. We collated individual isolate data from eligible studies to assess the association between genomic variants with phenotypic bedaquiline resistance, using a standardised method endorsed by WHO. Risk of bias of the extracted data was independently assessed by two authors using the Quality Assessment of Diagnostic Accuracy Studies tool for clinical studies and Systematic Review Center for Laboratory Animal Experimentation tool for animal studies. The primary outcome was to identify mutations associated with resistance in four genes of interest (Rv0678, atpE, pepQ, and Rv1979c); for each genomic variant, the odds ratio (OR), 95% CI, and p value were calculated to identify resistance markers associated with bedaquiline resistance. This study is registered with PROSPERO, CRD42020221498. FindingsOf 1367 studies identified, 41 published between 2007 and 2020 were eligible for inclusion. We extracted data on 1708 isolates: 1569 (91•9%) clinical isolates and 139 (8•1%) non-clinical isolates. We identified 237 unique variants in Rv0678, 14 in atpE, 28 in pepQ, and 11 in Rv1979c. Most clinical isolates with a single variant reported in Rv0678 (229 [79%] of 287 variants), atpE (14 [88%] of 16 variants), pepQ (32 [100%] of 32 variants), or Rv1979c (115 [98%] of 119 variants) were phenotypically susceptible to bedaquiline. Except for the atpE 187G→C (OR ∞, [95% CI 13•28-∞]; p<0•0001) and Rv0678 138_139insG (OR 6•91 [95% CI 1•16-47•38]; p=0•016) variants, phenotypic-genotypic associations were not significant (p≥0•05) for any single variant in Rv0678, atpE, pepQ, and Rv1979c. Interpretation Absence of clear genotypic-phenotypic associations for bedaquiline complicates the development of molecular drug susceptibility tests. A concerted global effort is urgently needed to assess the genotypic and phenotypic drug susceptibility of M tuberculosis isolates, especially in patients who have received unsuccessful bedaquilinecontaining regimens. Treatment regimens should be designed to prevent emergence of bedaquiline resistance and phenotypic drug susceptibility tests should be used to guide and monitor treatment.
Objectives: Effective use of antibiotics is critical to control the global tuberculosis pandemic. High-dose isoniazid (INH) can be effective in the presence of low-level resistance. We performed a systematic literature review to improve our understanding of the differential impact of genomic Mycobacterium tuberculosis (Mtb) variants on the level of INH resistance. The following online databases were searched: PubMed, Web of Science and Embase. Articles reporting on clinical Mtb isolates with linked genotypic and phenotypic data and reporting INH resistance levels were eligible for inclusion. Methods: All genomic regions reported in the eligible studies were included in the analysis, including: katG, inhA, ahpC, oxyR-ahpC, furA, fabG1, kasA, rv1592c, iniA, iniB, iniC, rv0340, rv2242 and nat. The level of INH resistance was determined by MIC: low-level resistance was defined as 0.1e0.4 mg/mL on liquid and 0.2e1.0 mg/mL on solid media, high-level resistance as >0.4mg/mL on liquid and >1.0 mg/mL on solid media. Results: A total of 1212 records were retrieved of which 46 were included. These 46 studies reported 1697 isolates of which 21% (n ¼ 362) were INH susceptible, 17% (n ¼ 287) had low-level, and 62% (n ¼ 1048) high-level INH resistance. Overall, 24% (n ¼ 402) of isolates were reported as wild type and 76% (n ¼ 1295) had 1 relevant genetic variant. Among 1295 isolates with 1 variant, 78% (n ¼ 1011) had a mutation in the katG gene. Of the 867 isolates with a katG mutation in codon 315, 93% (n ¼ 810) had high-level INH resistance. In contrast, only 50% (n ¼ 72) of the 144 isolates with a katG variant not in the 315-position had high-level resistance. Of the 284 isolates with 1 relevant genetic variant and wild type katG gene, 40% (n ¼ 114) had high-level INH resistance. Conclusions: Presence of a variant in the katG gene is a good marker of high-level INH resistance only if located in codon 315.
The ability of clinical algorithms to identify tuberculosis disease and the impact of empiric treatment on survival in people with a negative Xpert MTB/RIF (Xpert) result remains poorly documented. Methods: Hospitalized Xpert-negative patients (125 initiated on empiric tuberculosis treatment based on a clinical algorithm and 125 in whom tuberculosis treatment was not started) were enrolled. Sputum samples were evaluated for Mycobacterium tuberculosis by culture. All study participants were followed up for 6 months. Results: Xpert-negative inpatients in whom empiric tuberculosis treatment was initiated were more likely to have microbiological confirmed tuberculosis compared to those in whom empiric tuberculosis treatment was not started (24.8% vs 6.4%, p = 0.0001). Six-month risk of death was 5.2%, but the risk was twice as high in people with bacteriological confirmation of TB (10.3% vs 4.3%, p = 0.12). Cardinal symptoms of TB were associated with bacteriological confirmation and a decision to start empiric treatment. The positive predictive value of the clinical algorithm was 24.8% and empiric treatment did not affect 6-month risk of death (5.6% vs 4.8%, p = 0.78). Conclusions: Clinical algorithm identifies the majority of confirmed tuberculosis cases among Xpertnegative inpatients. Empiric treatment did not impact survival and resulted in substantial overtreatment. The more sensitive Xpert Ultra assay should be used to eliminate the need for empiric tuberculosis treatment.
Background Whole genome sequencing (WGS) is increasingly used for Mycobacterium tuberculosis (Mtb) research. Countries with the highest tuberculosis (TB) burden face important challenges to integrate WGS into surveillance and research. Methods We assessed the global status of Mtb WGS and developed a 3-week training course coupled with long-term mentoring and WGS infrastructure building. Training focused on genome sequencing, bioinformatics and development of a locally relevant WGS research project. The aim of the long-term mentoring was to support trainees in project implementation and funding acquisition. The focus of WGS infrastructure building was on the DNA extraction process and bioinformatics. Findings Compared to their TB burden, Asia and Africa are grossly underrepresented in Mtb WGS research. Challenges faced resulted in adaptations to the training, mentoring and infrastructure building. Out-of-date laptop hardware and operating systems were overcome by using online tools and a Galaxy WGS analysis pipeline. A case studies approach created a safe atmosphere for students to formulate and defend opinions. Because quality DNA extraction is paramount for WGS, a biosafety level 3 and general laboratory skill training session were added, use of commercial DNA extraction kits was introduced and a 2-week training in a highly equipped laboratory was combined with a 1-week training in the local setting. Interpretation By developing and sharing the components of and experiences with a sequencing and bioinformatics training program, we hope to stimulate capacity building programs for Mtb WGS and empower high-burden countries to play an important role in WGS-based TB surveillance and research.
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