Abstract
Background
Tuberculosis (TB) is one of the deadliest bacterial infectious diseases worldwide, with rising cases of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains. Bedaquiline (BDQ)-containing regimens have become important for the treatment of MDR/XDR-TB, and resistance to BDQ is increasing. Understanding genetic mutations is crucial for early detection of BDQ-resistant strains and thus maintaining the effectiveness of these drugs. This study aimed to review mutations associated with BDQ-resistant TB globally.
Methods
This study systematically searched the keywords TB, XDR, MDR, BDQ, and genes in the PubMed, Scopus, Web of Science, and Embase databases for studies reporting BDQ-resistant TB and their associated genes globally from 2014 to 2025.
Results
This systematic review included 40 studies and 25,234 patient samples with MDR and XDR-TB from around the world. Results showed significant variation in BDQ resistance across the World Health Organization (WHO) regions, with the highest in the Eastern Mediterranean and the lowest in the Western Pacific. Furthermore, the data collected showed that, among the continents studied, resistance was highest in Africa and lowest in the Americas. The country distribution showed that resistance rates were higher in Iran (n = 24), Moldova (n = 26), and Armenia (n = 35), and lower in Italy (n = 1001) and the Philippines (n = 724) than in other countries in the analysis. Genetically, the most resistance-associated mutations were observed in the Rv0678, atpE, and pepQ genes, respectively.
Conclusion
Given the increasing BDQ resistance and regional variability, it is essential to develop early detection systems, genomic surveillance, robust drug policy enforcement, and rapid diagnostics to maintain treatment effectiveness and curb the spread of resistance. Future research should focus on elucidating resistance mechanisms and developing novel therapeutic strategies.
Keywords: Tuberculosis, Bedaquiline, XDR, MDR, Drug-resistant, Global mapping, Gene
Introduction
Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) can infect various parts of the body, but the most common site is the lungs [1, 2]. TB is divided into multidrug-resistant (MDR) and extensively drug-resistant (XDR) [3]. The spread and control of drug-resistant TB (DR) due to unsuccessful treatment is one of the severe international challenges that continues to increase despite many measures and has killed many people around the world [4]. Among the well-known factors contributing to antimicrobial resistance are rapid evolution, mutation, and transfer of resistant genes through horizontal gene transfer [4]. Poor treatment regimens and non-adherence to antibiotic regimens are the most important reasons for the emergence of DR-TB [4]. The quality of drugs, inconsistency in drug supply, poverty, aging, overcrowding, and having a history of TB, co-infection with HIV, diabetes, drinking problems, immunodeficiency, and the use of many other drugs are other reasons [4, 5].
Since 2013, the use of bedaquiline (BDQ) has increased as a new anti-TB drug that is more effective against DR-TB. However, cases of acquired and primary resistance to BDQ were reported soon after its introduction [6]. BDQ is a diarylquinoline that inhibits an ATP synthase of MTB, specifically, the subunit c encoded by the atpE gene (Rv1305) [7]. BDQ is most effective when MTB is grown on non-fermentable energy sources such as lipids (which prevent ATP synthesis through glycolysis). Also, MTB responds to BDQ by inducing dormancy, activating ATP-producing pathways, or disrupting drug binding, thereby maintaining its survival in the face of the drug [8, 9].
BDQ resistance is associated with mutations in atpE, which encodes the subunit c of the ATP synthase complex, and with off-target mutations in Rv0678, which derepress the transcription of the MmpL5MmpS5 efflux transporter, pepQ (Rv2535c), and Rv1979c [10]. Although some mutation patterns are common, more diverse genetic profiles have been identified in clinical isolates [11]. Rapid sequencing of resistant strains revealed significant differences in mutation rates across countries [12]. Investigating genetic variations is crucial for developing and accessing DR detection tools and for providing effective strategies to mitigate the TB epidemic [13].
So far, several studies have investigated genes associated with BDQ-resistant TB, but there is a lack of studies with a global perspective. For example, Nieto Ramirez LM. et al. [7] in 2020, presented a comprehensive panel of gene mutations associated with varying levels of drug resistance to BDQ and delamanid. Nimmo C. et al. [14] evaluated the prospects and challenges of genomics for diagnosing BDQ-resistant TB. An Q. et al. [15] updated the classification of fluoroquinolones, BDQ, and linezolid drugs used in MDR-TB regimens. Also, Ismail N. et al. [16] assessed the association between genomic variants with phenotypic resistance to BDQ by 2020. To effectively control DR-TB worldwide, a systematic study of genes linked to BDQ resistance was conducted using a gene-mapping approach.
Methods
Search strategy
This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Keywords include tuberculosis, Mycobacterium spp., Mycobacterium tuberculosis, Koch’s disease, antibiotic resistance, MDR, XDR, pre-XDR, bedaquiline, resistance, and genes. Besides, their MeSH terms were combined using AND and OR operators. These were searched in PubMed, Embase, Scopus, and Web of Science databases from 2014 to March 2025. All identified articles were imported into EndNote (version 9.0). Then, studies reporting genes associated with BDQ-resistant TB in countries that met the inclusion criteria were selected for the final analysis.
Inclusion and exclusion criteria
The following criteria were used in the systematic review: studies investigating BDQ-resistant TB genes in human lung tissue. In contrast, the following criteria led to the exclusion of identified articles: Nontuberculous mycobacteria (NTM), other mycobacteria, other drugs, review articles, systematic review, animal models, data paper, meeting, case reports, conference papers, books, generics, letters, comments, erratum, comparative studies, editorials, data papers, symposiums, meta-analysis studies, and non-English papers. Additionally, studies that did not report clear parameters relevant to our review were excluded.
Quality evaluation
A checklist appropriate for observational studies was chosen to assess the quality of the articles. In March 2025, a search for relevant literature was conducted, yielding 1,637 studies, of which 1,157 remained after duplicates were removed. The selection of studies followed PRISMA guidelines, which are summarized in Fig. 1.
Fig. 1.
PRISMA flow diagram for study selection
Study selection
First, duplicate articles were removed, leaving only one copy of each research article. Next, non-original articles were eliminated from the selection. Afterward, a preliminary review of the titles and abstracts was conducted to filter out articles that did not meet the established inclusion and exclusion criteria. Finally, the full texts of the remaining articles were examined, and any additional irrelevant articles were removed.
Data extraction
Data extraction was completed by three researchers using a different pre-prepared checklist. This checklist included the first author’s name, year, continent, country, WHO region, sample size, sex, BDQ resistance rate, gene, and mutations, including wild type (WT), codon, amino acid, and nucleotide.
Statistical analysis
Data from the selected studies were systematically organized and pre-processed using Microsoft Excel 2019 (Microsoft Corporation, Redmond, WA, USA). Tabulation involved listing sample sizes, resistance rates, and other related metrics for various WHO regions, continents, and countries into formatted spreadsheets. Simple descriptive measures, such as totals, maxima, minima, means, standard deviations (SD), and percentages, were listed using Excel’s built-in functions, including SUM, MAX, MIN, AVERAGE, STDEV, and special-purpose formulae for percentages and cumulative frequencies.
For more precise visualization and further analysis, the data were also loaded into GraphPad Prism version 9.0 (GraphPad Software, San Diego, CA, USA). Descriptive summaries were generated, including mean BDQ resistance rates ± SD by WHO region, continent, and country. Cumulative sample sizes were also generated, with subdivision by region, continent, and country.
Graphical presentations were created in Prism to display these results, including sample-size bar charts, error-bar graphs of resistance rates, and distributions of resistance rates by category. All analyses were performed according to mainstream tenets of descriptive statistics to ensure faithful representation and reproducibility of findings. However, due to inadequate and heterogeneous reporting of primary statistical data in the available studies, no inferential statistical analyses were performed, as the focus was on presenting worldwide BDQ resistance patterns based on aggregated published literature data.
Results
Search and selection process
In the initial search, 1,637 articles were identified after transfer to EndNote and initial screening. Four hundred eighty articles were removed due to duplication across databases. Then, 416 non-research articles (book sections, abstracts, reviews, systematic reviews, letters, comments, errata, case reports, meta-analyses, editorials, and data papers) were removed. Furthermore, 27 non-English articles were removed; based on the inclusion and exclusion criteria, 650 articles were excluded after title and abstract review, leaving 64 for further review. After reviewing the complete text, 24 articles were excluded because they did not fully meet the inclusion criteria. Finally, 40 articles on genes causing BDQ-resistant TB were examined globally (Fig. 1).
Study characteristics
Forty studies from 2014 to 2025 were included in the final review, with one article covering both China and Russia. Studies spanned Asia, Africa, Europe, and the Americas, but none from Oceania met the study objectives. Most studies are from the Western Pacific region, including China, Pakistan, and South Africa, while fewer are from Iran, Moldova, and Armenia. Gender breakdowns, where available, showed roughly 70% male and 30% female samples.
The mmpR (Rv0678) gene has been reported in about 75% [30] studies, and the most frequently identified mutations include nucleotide insertions or deletions such as 192_193insG, 141_142insC, 192insG, 193delG, 144dupC, and 198dupG. Also, amino acid point mutations such as Ile108Thr, Arg109Pro, Ala86Val, Ser53Leu, Gly11Gly, Thr33Ser, Arg123Lys, Ser31Arg, Asn98Asp, and Glu21Asp are common. Frameshift mutations and premature stop mutations have also been reported in some studies. Moreover, WT associated with this gene has been reported in 20% of studies [8]. The atpE gene has been reported in 15% of studies [6], most of which include the mutations Ala63Pro, E61D (Glu61Asp), and I66M (Ile66Met). Also, the pepQ gene has been reported in 15% [6] of studies, with the most frequently reported mutations being R7Q and 964delG. In addition, other genes, including efflux pump-related genes such as mmpL5 (Rv0676c) and mmpS5 (Rv0677c), were examined in 20% [8] of studies. The most common mutations reported in them include Gly41Asp, Arg72Trp, Val45fs, Pro48fs, Gly66fs, and Trp42*. Furthermore, WT associated with atpE and pepQ genes had been seen in 7.5% [3] and 5% [2] studies, respectively.
Full details of the included articles, including year of publication, country, continent, WHO region, sample size and type, percentage of males and females, rate of drug resistance, type and percentage of genes and mutations identified, are provided in Table 1.
Table 1.
The information extracted from articles
| First author/Year | WHO region | Continent | Country | Number of samples (Human) | Number of samples (Strain) | Male | Female | Resistance rate of BDQ | The resistance rate of the gene | The resistance rate of mutation | Gene | Change | Ref. | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mutation | Wild Type | Codon | Amino acid | Nucleotide | |||||||||||||
| Gary Napier et al.2022 | Eastern Mediterranean | Asia | Pakistan | NR | 535 | NR | NR | 0.20% | NR | NR | mmpR5 | NR | NR | NR | NR | 192_193insG | [17] |
| Cong Yao et al. 2021 | Western Pacific | Asia | China | NR | 425 | NR | NR | 2.40% | 40.00% | 60.00% | Rv0678 | NR | WT | NR | NR | NR | [18] |
| 10.00% | Rv0678 | NR | NR | NR | Ile108Thr | NR | |||||||||||
| 10.00% | Rv0678 | NR | NR | NR | Arg109Pro | NR | |||||||||||
| 10.00% | Rv0678 | NR | NR | NR | Ala86Val | NR | |||||||||||
| 10.00% | Rv0678 | NR | NR | NR | NR | 110delA | |||||||||||
| Brigitta Derendinger et al. 2023 | African | Africa | South Africa | 38 | NR | 73% | 28% | 8% | NR | NR | Rv0676c | NR | NR | NR | NR | NR | [19] |
| NR | NR | Rv0678-11 C/A | NR | NR | NR | NR | NR | ||||||||||
| 89% | NR | Rv0678 | NR | NR | NR | NR | NR | ||||||||||
| NR | NR | pepQ | NR | NR | NR | NR | NR | ||||||||||
| NR | NR | Rv0678 | NR | NR | NR | NR | IS6110ins | ||||||||||
| Zexuan Song et al. 2023 | Western Pacific | Asia | China | NR | 546 | NR | NR | 0.73% | NR | NR | Rv0678 | L117R | NR | NR | Leu117Arg | NR | [20] |
| Rv0678 | R134* | NR | NR | Arg134Ter | NR | ||||||||||||
| Dania Khalid Saeed et al. 2022 | Eastern Mediterranean | Asia | Pakistan | NR | 48 | NR | NR | 20.80% | 44.00% | NR | Rv0678 | G25fs | NR | NR | Gly25fs | NR | [21] |
| 44.00% | NR | Rv0678 | D64fs | NR | NR | Gly25fs | NR | ||||||||||
| 44.00% | NR | Rv0678 | D109fs | NR | NR | Asp109fs | NR | ||||||||||
| 44.00% | NR | Rv0678 | L40F | NR | NR | Leu40Phe | NR | ||||||||||
| 44.00% | NR | Rv0678 | R50Q | NR | NR | Arg50Gln | NR | ||||||||||
| 44.00% | NR | Rv0678 | R107C | NR | NR | Arg107Cys | NR | ||||||||||
| 44.00% | NR | Rv0678 | S63R | NR | NR | Ser63Arg | NR | ||||||||||
| 44.00% | NR | Rv0678 | S63G | NR | NR | Ser63Gly | NR | ||||||||||
| NR | NR | pepQ | R7Q | NR | NR | Arg7Gln | NR | ||||||||||
| NR | NR | atpE | A18A | NR | NR | Ala18= | NR | ||||||||||
| NR | NR | mmpL5 | I948V+T794I | NR | NR | Ile948Val+ Thr794Ile | NR | ||||||||||
| NR | NR | Rv1979c | F144* | NR | NR | Phe144Ter | NR | ||||||||||
| NR | NR | Rv0194c | M74T | NR | NR | Met74Thr | NR | ||||||||||
| NR | NR | Rv0450c | G93C | NR | NR | Gly93Cys | NR | ||||||||||
| NR | NR | Rv1273c | G462K | NR | NR | Gly462Lys | NR | ||||||||||
| NR | 55.60% | Rv1634c | E198R | NR | NR | Glu198Arg | NR | ||||||||||
| NR | NR | Rv2688c | P156T | NR | NR | Pro156Thr | NR | ||||||||||
| NR | NR | Rv1218c | Q243R | NR | NR | Gln243Arg | NR | ||||||||||
| NR | NR | Rv0507c | Y679* | NR | NR | Tyr679Ter | NR | ||||||||||
| NR | NR | Rv0507c | R426H | NR | NR | Arg426His | NR | ||||||||||
| NR | NR | Rv1877c | Q113* | NR | NR | Gln113Ter | NR | ||||||||||
| NR | NR | Rv3823c | G253R | NR | NR | Gly253Arg | NR | ||||||||||
| NR | NR | Rv1704c | S187D | NR | NR | Ser187Asp | NR | ||||||||||
| NR | NR | Rv1704c | R93L | NR | NR | Arg93Leu | NR | ||||||||||
| Andriansjah Rukmana et al. 2024 | South_East Asia | Asia | Indonesia | NR | 60 | NR | NR | 5% | NR | NR | Rv1979c | A→T (T1178A p.L393H) | NR | NR | NR | NR | [22] |
| Rv1979c | T C (c. A_129G) | NR | NR | NR | NR | ||||||||||||
| Rv1979c | T→C (A857G p.D286G) | NR | NR | NR | NR | ||||||||||||
| Rv1979c | NR | NR | NR | Asp286Gly | NR | ||||||||||||
| Rv1979c | NR | NR | NR | Leu393His | NR | ||||||||||||
| Yan Hu et al. 2023 | Western Pacific | Asia | China | 205 | 205 | 73.20% | 26.80% | 4.40% | NR | NR | Rv1979 | NR | WT | NR | NR | NR | [23] |
| 66.70% | 16.70% | Rv0678 | T56C | NR | NR | Phe19Ser | NR | ||||||||||
| 66.70% | 16.70% | Rv0678 | T56C | NR | NR | NR | GA492ins | ||||||||||
| 66.70% | 16.70% | Rv0678 | T56C | NR | NR | NR | A274ins | ||||||||||
| 66.70% | 50.00% | Rv0678 | A152G | NR | NR | Gln51Arg | NR | ||||||||||
| Tatiana Umpeleva et al. 2024 | European | Europe | Russia | 203 | 239 | NR | NR | 2.10% | NR | NR | atpE | NR | WT | NR | NR | NR | [24] |
| atpE | А63Р | NR | NR | Ala63Pro | NR | ||||||||||||
| atpE | I66M | NR | NR | Ile66Met | NR | ||||||||||||
| Rv0678 | A36T | NR | NR | Ala36Thr | NR | ||||||||||||
| Rv0678 | NR | WT | NR | NR | NR | ||||||||||||
| Rv0678 | S53P | NR | NR | Ser53Pro | NR | ||||||||||||
| pepQ | NR | NR | NR | NR | NR | ||||||||||||
| Huiwen Zheng et al. 2021 | Western Pacific | Asia | China | NR | 88 | NR | NR | 2.30% | NR | NR | Rv0678 | NR | NR | NR | NR | A152G | [25] |
| Rv0678 | NR | NR | NR | Gln31Arg | NR | ||||||||||||
| Jeong Seong Yang et al. 2018 | Western Pacific | Asia | Korea | NR | 420 | NR | NR | 11% | NR | NR | Rv0678 | NR | NR | NR | Arg90cys | C268T | [26] |
| Rv0678 | NR | NR | NR | Gly11Gly | C33T | ||||||||||||
| Rv0678 | NR | NR | NR | Phe79Ser | T236C | ||||||||||||
| Rv0678 | NR | NR | NR | Thr33Ser | C98G | ||||||||||||
| Rv0678 | NR | NR | NR | Arg123Lys | G368A | ||||||||||||
| Rv0678 | NR | NR | NR | Ser31Arg | A91C | ||||||||||||
| Rv0678 | NR | NR | NR | Asn98Asp | A292G | ||||||||||||
| Rv0678 | NR | NR | NR | Glu21Asp | A63C | ||||||||||||
| Angela Cannas et al. 2024 | European | Europe | Italy | 1056 | 1001 | NR | NR | 0.40% | NR | NR | mmpR (Rv0678) | NR | NR | NR | NR | NR | [27] |
| Sheng-Han Wu et al. 2021 | Western Pacific | Asia | Taiwan | 898 | 898 | 72.80% | 27.20% | 3.10% | NR | 75.30% | Rv0678 | NR | WT | NR | NR | NR | [28] |
| 3.20% | Rv0678 | Whole gene del | NR | NR | NR | ||||||||||||
| 1.10% | Rv0678 | NR | NR | NR | NR | 11_63del fs (29 stop) | |||||||||||
| 2.20% | Rv0678 | NR | NR | NR | NR | 181_182insG fs (80 stop) | |||||||||||
| 1.10% | Rv0678 | NR | NR | NR | NR | 274_275insA fs (92 stop) | |||||||||||
| 1.10% | Rv0678 | G14A | NR | NR | Gly14Ala | NR | |||||||||||
| 2.20% | Rv0678 | S53P | NR | NR | Ser53Pro | NR | |||||||||||
| 3.20% | Rv0678 | I80S | NR | NR | Ile80Ser | NR | |||||||||||
| 1.10% | Rv0678 | L83P | NR | NR | Leu83Pro | NR | |||||||||||
| 1.10% | Rv0678 | G87A | NR | NR | Gly87Ala | NR | |||||||||||
| 1.10% | Rv0678 | F100Y | NR | NR | Phe100Tyr | NR | |||||||||||
| 1.10% | Rv0678 | A102V | NR | NR | Ala102Val | NR | |||||||||||
| 1.10% | Rv0678 | L114P | NR | NR | Leu114Pro | NR | |||||||||||
| Guirong Wang et al. 2021 | Western Pacific | Asia | China | NR | 391 | NR | NR | 7.16% | NR | NR | atpE | NR | WT | NR | NR | [29] | |
| Rv0678 | NR | NR | NR | Ser63Asn | NR | ||||||||||||
| NR | NR | NR | Asn98Asp | NR | |||||||||||||
| NR | NR | NR | NR | NR | |||||||||||||
| NR | NR | NR | NR | NR | |||||||||||||
| Nazir A. Ismail et al. 2018 | African | Africa | South Africa | NR | 391 | NR | NR | 2.30% | 0.80% | NR | Rv0678 | NR | NR | NR | NR | NR | [30] |
| 1.10% | pepQ | NR | NR | NR | NR | NR | |||||||||||
| 25.90% | Rv1979 | NR | NR | NR | NR | NR | |||||||||||
| Svetlana Zhdanova et al. 2023 | European | Europe | Russia | 60 | NR | 65% | 35% | 1.66% | NR | NR | mmpR | M655T | NR | NR | Met655Thr | NR | [31] |
| Western Pacific | Asia | China | 137 | 59.20% | 40.80% | 1.45% | Rv1979c | V426I | NR | NR | Val426Ile | NR | |||||
| Rv1979c | A-130 C | NR | NR | NR | -130 A > C | ||||||||||||
| Aparna Bhanushali et al. 2024 | South-East Asia | Asia | India | 600 | NR | 51.50% | 48.50% | 1% | NR | NR | atpE | NR | NR | NR | Ala63Pro | NR | [32] |
| Rv0678 | NR | NR | NR | Asp15Gly | NR | ||||||||||||
| Rv0678 | NR | NR | NR | Leu142Arg | NR | ||||||||||||
| Rv0678 | NR | NR | NR | Ser53Leu | NR | ||||||||||||
| Simone Mok et al. 2023 | European | Europe | Ireland | NR | 195 | NR | NR | 2.05% | NR | NR | mmpR (Rv0678) | NR | NR | NR | Met146Thr | NR | [33] |
| Rv0678 upstream | NR | NR | NR | 21insTTC | |||||||||||||
| mmpR (Rv0678) | NR | NR | NR | Ala59Val | NR | ||||||||||||
| mmpL5 (Rv0676c) | NR | NR | NR | Val344Leu | NR | ||||||||||||
| Rubeshan Perumal et al. 2023 | African | Africa | South Africa | 5 | 15 | NR | NR | 20.00% | NR | NR | Rv1979c | R409Q | NR | NR | Arg409Gln | NR | [33] |
| Rv0678 | D165 fs | NR | NR | Asp165fs | NR | ||||||||||||
| Enyu Tong et al. 2023 | Western Pacific | Asia | China | 245 | NR | 75.50% | 24.50% | 2.04% | NR | NR | Rv0678 | NR | NR | NR | Phe79Cys | UUC237UGC | [34] |
| Rv0678 | NR | NR | NR | NR | 192insG | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 275dupA | ||||||||||||
| Rv0678 | NR | WT | NR | NR | NR | ||||||||||||
| Rv0678 | NR | NR | NR | Glu138Gly | GAA413GGA | ||||||||||||
| Rv0678 | NR | NR | NR | Ser63Arg | AGC187CGC | ||||||||||||
| Rv1979c | NR | WT | NR | NR | NR | ||||||||||||
| pepQ | NR | WT | NR | NR | NR | ||||||||||||
| pepQ | NR | NR | NR | NR | 131G > A | ||||||||||||
| Jian Yang et al. 2020 | Western Pacific | Asia | China | 518 | NR | 69.30% | 30.70% | 1.93% | NR | NR | atpE | NR | NR | NR | NR | NR | [35] |
| pepQ | NR | NR | NR | NR | NR | ||||||||||||
| Rv0678 | NR | NR | NR | Ser2Ile | G5T | ||||||||||||
| Rv0678 | NR | NR | NR | Ile88Val | A263G | ||||||||||||
| Rv0678 | NR | NR | NR | Ala62Val | C185T | ||||||||||||
| Rv0678 | NR | NR | NR | Phe89Phe | C265T | ||||||||||||
| Rv0678 | NR | NR | NR | Ile108Thr | T323C | ||||||||||||
| Rv0678 | Fs57C | NR | NR | Cys57fs | 19delG | ||||||||||||
| Shanshan Li et al. 2024 | Western Pacific | Asia | China | 1877 | NR | 64% | 36% | 0.20% | NR | NR | pepQ | NR | NR | Codon 97 | Gly→Phe | NR | [36] |
| Rv0678 | NR | NR | NR | NR | 156insC | ||||||||||||
| Wencong He et al. 2021 | Western Pacific | Asia | China | NR | 1603 | NR | NR | 0.40% | NR | NR | Rv0678 | NR | NR | NR | Ser63Arg | NR | [37] |
| Rv0678 | NR | NR | NR | Ser68Gly | NR | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 192insG | ||||||||||||
| Yu Pang et al. 2017 | Western Pacific | Asia | China | NR | 90 | NR | NR | 3.30% | NR | NR | Rv0678 | NR | NR | NR | Tyr157Asp | NR | [38] |
| Rv0678 | NR | NR | NR | Ser53Leu | NR | ||||||||||||
| 66.60% | Rv0678 | NR | NR | NR | Ser53Pro | NR | |||||||||||
| Bing Zhao et al. 2022 | Western Pacific | Asia | China | 200 | 187 | 74.00% | 26.00% | 1.50% | NR | NR | Rv0678 | NR | NR | NR | Arg134 | NR | [39] |
| Jian Xu et al. 2017 | Western Pacific | Asia | China | 90 | 90 | NR | NR | 4.40% | NR | NR | Rv0678 | T437C (M146T) | NR | NR | NR | NR | [40] |
| Rv0678 | G5T (S2I) | NR | NR | NR | NR | ||||||||||||
| Rv0678 | C158T (S53L) | NR | NR | NR | NR | ||||||||||||
| Rv0678 | T350G (L117R) | NR | NR | NR | NR | ||||||||||||
| Rv0678 | NR | WT | NR | NR | NR | ||||||||||||
| Cristina Villellas et al. 2016 | European | Europe | Belgium | 347 | NR | NR | NR | 2.30% | 6.30% | NR | Rv0678 | NR | NR | NR | NR | 11 A→C | [41] |
| 6.30% | Rv0678 | NR | NR | NR | NR | 472 A→G | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 44 A→G | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 49 A→T | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 116T→C | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 122G→C | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 124T→C | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 148 C→T | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 155 C→T | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 176 C→T | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 185 C→T | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 187 A→G | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 198_199insG | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 224_225insA | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 226delC | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 256G→A | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 259G→C | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 263 A→G | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 269G→T | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 274_275insA | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 280_281insT | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 301G→A | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 334G→C | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 346G→A | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 350T→G | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 416T→C | |||||||||||
| 6.30% | Rv0678 | NR | NR | NR | NR | 433T→A | |||||||||||
| NR | Mmp55- Rv0678 | NR | NR | NR | NR | -44T→C | |||||||||||
| NR | Mmp55- Rv0678 | NR | NR | NR | NR | -47T→C | |||||||||||
| NR | Mmp55- Rv0678 | (-13) IS6110 | NR | NR | NR | NR | |||||||||||
| NR | Mmp55- Rv0678 | NR | NR | NR | NR | -59T→C | |||||||||||
| NR | Mmp55- Rv0678 | NR | NR | NR | NR | -11 C→A | |||||||||||
| Yuhong Liu et al. 2020 | Western Pacific | Asia | China | 277 | NR | NR | NR | 2.20% | 50.00% | NR | Rv0678 | NR | NR | NR | NR | 121delG | [42] |
| Rv0678 | NR | NR | NR | NR | 49insC | ||||||||||||
| Rv0678 | NR | NR | NR | Arg96Gln | NR | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 46insG | ||||||||||||
| Rv0678 | NR | WT | NR | NR | NR | ||||||||||||
| Elena Chesov et al. 2022 | European | Europe | Republic of Moldova | 26 | NR | NR | NR | 15.30% | NR | NR | atpE | NR | WT | NR | NR | NR | [43] |
| atpE | E61D | NR | NR | Glu61Asp | NR | ||||||||||||
| atpE | I66M | NR | NR | Ile66Met | NR | ||||||||||||
| atpE | A63P | NR | NR | Ala63Pro | NR | ||||||||||||
| Rv0678 | S63fs | NR | NR | Ser63fs | NR | ||||||||||||
| Rv0678 | NR | WT | NR | NR | NR | ||||||||||||
| Rv0678 | S64fs | NR | NR | Ser64fs | NR | ||||||||||||
| Rv0678 | D5fs | NR | NR | Asp5fs | NR | ||||||||||||
| Rv0678 | G24D | NR | NR | Gly24Asp | NR | ||||||||||||
| Rv0678 | T58P | NR | NR | Thr58Pro | NR | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 193delG | ||||||||||||
| Rv0678 | S63G | NR | NR | Ser63Gly | NR | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 192insG | ||||||||||||
| Rv0678 | L142P | NR | NR | Leu142Pro | NR | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 136insG | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 141insC | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 195insT | ||||||||||||
| Rv0678 | G66W | NR | NR | Gly66Trp | NR | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 436insT | ||||||||||||
| Rv0678 | NR | NR | NR | NR | 16delG | ||||||||||||
| Rv0678 | R72W | NR | NR | Arg72Trp | NR | ||||||||||||
| Yousheng Peng et al. 2024 | Western Pacific | Asia | China | NR | 2136 | NR | NR | 9.70% | 10.10% | NR | atpE | V152A | NR | NR | Val152Ala | NR | [44] |
| Rv0678 | L141R | NR | NR | Leu141Arg | NR | ||||||||||||
| Rv0678 | S51F | NR | NR | Ser51Phe | NR | ||||||||||||
| Rv0678 | E112K | NR | NR | Glu112Lys | NR | ||||||||||||
| Rv0678 | S63R/G | NR | NR | Ser63Arg/ Gly | NR | ||||||||||||
| Rv0678 | R50Q | NR | NR | Arg50Gln | NR | ||||||||||||
| Rv0678 | R107C | NR | NR | Arg107Cys | NR | ||||||||||||
| Rv0678 | G77R | NR | NR | Gly77Arg | NR | ||||||||||||
| pepQ | G265T | NR | NR | NR | 265G > T | ||||||||||||
| pepQ | T157C | NR | NR | NR | 157T > C | ||||||||||||
| pepQ | R337L | NR | NR | Arg337Leu | NR | ||||||||||||
| pepQ | T222N | NR | NR | Thr222Asn | NR | ||||||||||||
| atpE | P62A | NR | NR | p. | NR | ||||||||||||
| atpE | D27G | NR | NR | Asp27Gly | NR | ||||||||||||
| atpE | V74L | NR | NR | Val74Leu | NR | ||||||||||||
| Harriet N. A. Blankson et al. 2024 | African | Africa | Sierra Leone | 238 | 238 | 43.00% | 17% | 2.52% | NR | 16.70% | Rv0678 | NR | NR | NR | NR | 138insG | [45] |
| 33.30% | Rv0678 | NR | NR | NR | NR | 193delG | |||||||||||
| 16.70% | Rv0678 | NR | NR | NR | NR | 95insGA | |||||||||||
| 16.70% | Rv0678 | C46R | NR | NR | Cys46Arg | NR | |||||||||||
| 16.70% | Rv0678 | R90C | NR | NR | Arg90Cys | NR | |||||||||||
| 16.70% | Rv0678 | Y92 | NR | NR | Tyr92fs | NR | |||||||||||
| 16.70% | Rv0678 | NR | NR | NR | NR | 141insC | |||||||||||
| Christian Utpatel et al. 2024 | the Americas | America | Peru | 2180 | 171 | 66.70% | 33.30% | 3.50% | NR | NR | Rv0678 | N98D | NR | NR | Asn98Asp | NR | [46] |
| Rv0678 | NR | NR | NR | NR | 192insG | ||||||||||||
| Aimei Liu et al. 2024 | Western Pacific | Asia | China | 184 | NR | 77.13% | 22.87% | 0.58% | NR | NR | Rv0678 | R94Q | NR | NR | Arg94Gln | 281G > A | [47] |
| Linfeng Wang | Western Pacific | Asia | Philippines | 671 | 724 | NR | NR | 0.40% | NR | NR | mmpR5 (Rv0678) | NR | NR | NR | NR | 144dupC | [48] |
| mmpR5 (Rv0678) | NR | NR | NR | NR | 198dupG | ||||||||||||
| mmpR5 (Rv0678) | NR | NR | NR | NR | 135delG | ||||||||||||
| Leah W Roberts et al. 2024 | African | Africa | South Africa | 461 | 505 | NR | NR | 8.60% | 75.00% | NR | mmpR5 | NR | NR | NR | Gly41Asp | NR | [49] |
| mmpR5 | NR | NR | NR | Arg72Trp | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Val45fs | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Pro48fs: RAAVL | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Gly66fs: DQHQC | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Cys46fs: GSRAA | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Cys46fs: VIPSG | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Trp42* | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Gly66fs: SAPMP | NR | ||||||||||||
| mmpR5 | IS6110:779045 | NR | NR | NR | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Gln76* | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Leu117Val | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Arg135* | NR | ||||||||||||
| mmpR5 | NR | NR | NR | Gly6fs | NR | ||||||||||||
| mmpR5 | 6110ins:779,168 | NR | NR | NR | NR | ||||||||||||
| mmpR5 | IS6110:778978 | NR | NR | NR | NR | ||||||||||||
| mmpR5 | 6110ins:778,945 | NR | NR | NR | NR | ||||||||||||
| Shaojun Pei et al. 2024 | Western Pacific | Asia | China | NR | 9071 | NR | NR | 0.50% | NR | NR | pepQ | NR | NR | NR | NR | NR | [50] |
| Rv0678 | NR | NR | NR | NR | NR | ||||||||||||
| mmpL5 | NR | NR | NR | NR | NR | ||||||||||||
| mmpS5 | NR | NR | NR | NR | NR | ||||||||||||
| atpE | NR | NR | NR | NR | NR | ||||||||||||
| Vijayalakshmi Jawaharlal Nehru et al. 2024 | South-East Asia | Asia | India | 1158 | 28 | 75.13% | 24.87% | 7.14% | NR | NR | Rv0678 | NR | NR | NR | E113K: Glu→ Lys | NR | [51] |
| G337A | NR | NR | Gly337Ala | NR | |||||||||||||
| Hasan Ghajavand et al. 2019 | Eastern Mediterranean | Asia | Iran | NR | 24 | NR | NR | 20.83% | NR | NR | mmpl5 | S602P | NR | NR | Ser602Pro | NR | [52] |
| mmpl5 | V344L | NR | NR | Val344Leu | NR | ||||||||||||
| rv1979c | M245L | NR | NR | Met245Leu | NR | ||||||||||||
| Emmanuel Rivière et al. 2022 | African | Africa | South African | 509 | 509 | NR | NR | 1.40% | 84.90% | 48.10% | Rv0676c (mmpL5) | NR | NR | NR | Ile794Thr | NR | [53] |
| 84.90% | 36% | Rv0676c (mmpL5) | NR | NR | NR | Asp767Asn | NR | ||||||||||
| 0.20% | 0.20% | Rv0677c (mmpS5) | NR | NR | NR | NR | 306 C.T | ||||||||||
| 20.80% | 0.19% | Rv0678 | NR | NR | NR | Glu104 | NR | ||||||||||
| 20.80% | 0.19% | Rv0678 | NR | NR | NR | Ile67fs | NR | ||||||||||
| 20.80% | 0.19% | Rv0678 | NR | NR | NR | Arg140Trp | NR | ||||||||||
| 20.80% | 20% | Rv0678 | NR | NR | NR | NR | -11 C.A | ||||||||||
| 23.40% | 4.70% | Rv1979c | NR | NR | NR | Tyr51Asn | NR | ||||||||||
| 23.40% | 4.10% | Rv1979c | NR | NR | NR | Asp286Gly | NR | ||||||||||
| 23.40% | 10.40% | Rv1979c | NR | NR | NR | Arg409Gln | NR | ||||||||||
| 0.20% | 0.19% | Rv1304 (atpB) | NR | NR | NR | His250Pro | NR | ||||||||||
| 0.20% | 0.20% | Rv0677c(mmpS5) | NR | NR | NR | Asn102Asn | 306 C > T | ||||||||||
| Yuanyuan Shang et al. 2023 | Western Pacific | Asia | China | 72 | 72 | 72.20% | 27.80% | 1.48% | 50% | NR | Rv0678 | NR | NR | NR | Arg38* | 112 C→T | [54] |
| 50% | Rv0678 | NR | NR | NR | Ala57Glu | 170 C→A | |||||||||||
| 50% | Rv0678 | NR | NR | NR | Ala59Val | 176 C→T | |||||||||||
| 50% | Rv0678 | NR | NR | NR | Arg82Pro | 245G→C | |||||||||||
| 50% | Rv0678 | NR | NR | NR | Ala86Val | 257 C→T | |||||||||||
| 50% | Rv0678 | NR | NR | NR | Asp88Gly | 263 A→G | |||||||||||
| 50% | Rv0678 | NR | NR | NR | Phe93Ser | 278T→C | |||||||||||
| 50% | Rv0678 | NR | NR | NR | Ile108Thr | 323T→C | |||||||||||
| 50% | Rv0678 | NR | NR | NR | Asp141His | 421G→C | |||||||||||
| 50% | Rv0678 | NR | NR | NR | NR | 144_145insC | |||||||||||
| 50% | Rv0678 | NR | NR | NR | NR | 198_199insG | |||||||||||
| 50% | Rv0678 | NR | NR | NR | NR | 437_438ins ATATAT | |||||||||||
| 50% | |||||||||||||||||
| 50% | Rv0678 | NR | NR | NR | NR | 466_477insC | |||||||||||
| 2.8% | Rv0678 + Rv1979c | NR | NR | NR | Ser31Arg | 93T→G+ 708_709 | |||||||||||
| 2.8% | Rv0678 + Rv1979c | NR | NR | NR | NR | insA | |||||||||||
| 2.8% | Rv0678 + Rv1979c | NR | NR | NR | gln76lys | 226 C→A+ | |||||||||||
| 2.8% | Rv0678 + Rv1979c | NR | NR | NR | NR | 705_706 insC | |||||||||||
| 50% | Rv0678 + Rv1453 | NR | NR | NR | Ile279Ile | 321_322insC | |||||||||||
| 50% | Rv0678 + Rv1453 | NR | NR | NR | NR | + 837 C →A | |||||||||||
| 50% | Rv0678 + Rv1453 | NR | NR | NR | Arg90cys | 268 C→T+ 79_80insG | |||||||||||
| 50% | |||||||||||||||||
| 8.3% | Rv0678 + Rv1453 | NR | NR | NR | Arg38* | 112 C → T + 1160 | |||||||||||
| 8.3% | Rv0678 + Rv1453 | NR | NR | NR | Asp387Gly | A→G | |||||||||||
| 8.3% | Rv0678 + Rv1453 | NR | NR | NR | Ala386Ala | 198_199insG+ | |||||||||||
| 8.3% | Rv0678 + Rv1979c + Rv1453 | NR | NR | NR | NR | 708_709 insA+ | |||||||||||
| 8.3% | Rv0678 + Rv1979c + Rv1453 | NR | NR | NR | NR | 1158 C →A | |||||||||||
| 5.60% | Rv0678 + Rv1979c + Rv1453 | NR | NR | NR | Gly27Ser | 79G→A+ 198_199 | |||||||||||
| 2.80% | atpE + Rv0678 + Rv1453 | NR | NR | NR | Leu381Leu | Gins+1141 C→T | |||||||||||
| 2.80% | Rv1979c | NR | NR | NR | Gln236Asp | NR | |||||||||||
| E. Ardizzoni et al. 2025 | European | Asia | Armenia | 62 | 35 | 95% | 5% | 12% | NR | pepQ | NR | NR | NR | NR | 964delG | [55] | |
| 3% | Rv0678 | R89L | NR | NR | Arg89Leu | NR | |||||||||||
| 3% | Rv0678 | NR | NR | NR | NR | 144dupC | |||||||||||
| 3% | Rv0678 | NR | NR | NR | NR | 140dupA | |||||||||||
| 3% | Rv0678 | NR | NR | NR | NR | 198dupG | |||||||||||
| 3% | Rv0678 | NR | NR | NR | NR | 19delG | |||||||||||
| 3% | Rv0678 | L60P | NR | NR | Leu60Pro | NR | |||||||||||
| 3% | Rv0678 | F100Y | NR | NR | Phe100Tyr | NR | |||||||||||
∗: Stop codon, fs: Frameshift, NR: Not reported
Results of sample size and BDQ resistance rate in each WHO region
A total of 25,234 samples were included in our study. The maximum sample was 20,184, and the minimum was 171, both from the Western Pacific and the Americas WHO regions, respectively. The details of each WHO region are illustrated in Fig. 2.
Fig. 2.
A total of samples from each WHO region
The average BDQ resistance rate across the WHO regions ranged from 2.91% ± 0.65% to 13.94% ± 6.87%, with the highest rates observed in the Western Pacific and Eastern Mediterranean regions. Furthermore, the average resistance rate of BDQ for the Eastern Mediterranean was 13.94% ± 6.87%, the African was 7.14% ± 2.86%, the European was 5% ± 2.25%, South-East Asia was 4% ± 1.80%, the Americas was 3.50%, and the Western Pacific was 2.91% ± 0.65%. The average resistance rate for each WHO region is illustrated in Fig. 3.
Fig. 3.
Resistance rate of BDQ (%) in each WHO region (Mean ± SD)
Result of the sample size and BDQ resistance rate in each continent
The number of samples for the American continent was 171, for the African continent was 1681,for the European continent was 1868, and for the Asian continent was 21,514 (Fig. 4).
Fig. 4.
The sample size of each continent
The average BDQ resistance rate across continents ranged from 3.5% to 7.14% ± 2.86%, with the highest rates in the Americas and Africa. Furthermore, the average BDQ resistance rate for the American continent was 3.5%, for the European continent was 3.97% ± 2.28%, for the Asian continent was 4.70% ± 1.07%, and for the African continent was 7.14% ± 2.86% (Fig. 5).
Fig. 5.
The average Resistance rate (%) of BDQ in each continent (Mean ± SD)
Results of the sample size and BDQ resistance rate in each country
The number of samples across countries ranged from 24 (Iran) to 18,142 (China). The maximum number of samples was 18,142, 1443, and 1001 for China, South Africa, and Italy. Additionally, the minimum number of samples was 24, 26, and 35 for Iran, the Republic of Moldova, and Armenia, respectively. More details for each county were shown in Fig. 6.
Fig. 6.
Sample size for each country
The average BDQ resistance rate across the reported countries ranged from 0.4% to 20.83%. The average minimum resistance rate of BDQ was reported by Italy and the Philippines (0.40%), Russia (1.88% ± 0.22%), and Ireland (2.05%). However, the average maximum resistance rate of BDQ was reported by Iran (20.83%), the Republic of Moldova (15.30%), and Armenia (12%). Figure 7 shows the distribution of BDQ resistance rates across the reported countries.
Fig. 7.
Distribution of the resistance rate of BDQ (%) for the reported countries (Mean ± SD)
Conclusion and future perspective
In recent years, the emergence of BDQ resistance has posed a significant challenge in the treatment of MDR and XDR-TB. A review of 40 studies involving 25,234 samples found that BDQ resistance prevalence varied widely across countries. To illustrate, across different WHO regions, it ranges from 2.91% to 13.94%, and across continents, it ranges from 3.5% to 7.14%. The highest resistance rate was observed in the Eastern Mediterranean region (13.94%) and the lowest in the Western Pacific region (2.91%). At the continental level, the highest resistance was observed in Africa (7.14%) and the lowest in the Americas (3.5%). By country, Iran (20.83%), Moldova (15.3%), and Armenia (12%) reported the highest resistance rates, while Italy and the Philippines reported the lowest at about 0.4%. This suggests the roles of epidemiological factors, different selection pressures, and differences in drug use across countries, differences in treatment quality, patient adherence to the drug regimen, and differences in laboratory diagnostic capacities across countries [56, 57]. Genetic resistance to BDQ has increased the challenges of treating MDR and XDR-TB. The emergence of resistant strains can reduce the effectiveness of combination regimens, lead to treatment failure, increase mortality, and spread resistance [41, 58]. A significant concern is that resistance to BDQ is spreading not only in patients with prior drug exposure but also in patients with MDR or XDR backgrounds. This suggests that even effective treatment regimens cannot wholly prevent the emergence of resistance and that drug, host, and microbial factors are all involved [56, 57]. Therefore, ongoing drug and treatment monitoring, genetic screening, and further functional studies are necessary to understand novel mechanisms for preventing this disease [58]. As emphasized by Hu Y. et al. (2023) [23], rapid identification of these mutations through genomic sequencing and the development of molecular diagnostic tests are essential for global TB control.
According to this study, mutations in the atpE, Rv0678, and pepQ genes were identified as causing resistance to BDQ. The mutation in Rv0678 is the most frequent and causes increased expression of efflux pumps (MmpL5-MmpS5) and increased drug efflux from the cell, which is a type of indirect resistance [10, 58]. In contrast, mutations in the atpE gene disrupt drug binding to the ATP synthase complex; although rare, these mutations confer higher levels of resistance [10]. Moreover, mutations in pepQ have been reported to enhance resistance, mainly associated with low-level resistance and concomitant resistance to clofazimine [10]. WT mutations indicate the absence of mutations in genes associated with BDQ resistance, as reported in some studies. This suggests that even in the absence of mutations, some samples may exhibit drug sensitivity or low resistance [10, 59]. Therefore, accurate analysis of WT mutations is essential, as they can help better understand the mechanisms of drug resistance and sensitivity and, consequently, improve diagnostic methods based on the identification of specific resistance mutations [10, 59]. The combination of BDQ resistance with resistance to clofazimine and other drugs results in treatment failure and increased mortality, underscoring the importance of personalized therapies and continuous monitoring [60]. The findings of this study are consistent with those of Ismail et al. (2021) [16], who showed that combinations of mutations can confer varying degrees of phenotypic resistance. Also, significant differences in mutation distribution across countries were observed. For example, in China, which has examined the most extensive collection of isolates, a wide range of mutations was observed. At the same time, in European countries such as Italy and Ireland, low-level resistance was shown. This discrepancy could be due to the broader use of BDQ in countries with a high TB burden, which exerts greater selective pressure for resistance. In addition, poor drug quality, non-adherence to treatment, concomitant use of other drugs, co-morbidities (HIV and diabetes), and demographic conditions (poverty and overcrowding) can increase the likelihood of resistant mutations [61–63]. Also, inappropriate use of BDQ or treatment without susceptibility testing can accelerate the emergence of resistance, which the WHO also emphasizes careful monitoring and principled use of this drug [56]. Future studies should likely conduct more extensive genomic surveillance at the global level to better understand the actual pattern of BDQ resistance [58].
Limitations of this systematic review include the inclusion of only English-language articles, potential language bias, insufficient data from some countries, and heterogeneity in study methods. For example, in some countries, such as Iran, Moldova, and Armenia, only one eligible study was included, with a small sample size (n = 24), while in others, such as China, more than 18,000 samples were included. Such a vast difference can lead to decreased accuracy in resistance rate estimates and bias the results, because studies with small sample sizes do not reflect the actual epidemiological situation, while those with large sample sizes may skew the global data. On the other hand, heterogeneity in the time period of the studies was another challenge, because some studies covered data for several years, while others were limited to only one year or less; this time difference cannot clearly show the trend of resistance change and make direct comparisons between studies difficult [64]. It was also impossible to systematically and uniformly calculate weighted estimates across regions, with 12 of the 17 countries (70.6%) included being represented by only a single study each. Therefore, combining weighted estimates for some countries with unweighted estimates for others would have impaired comparability across countries and regions and would have biased the interpretation of the results. This structure makes it impossible to conduct robust meta-analyses based on sample size across the entire data set and increases the potential impact of small study effects. Therefore, to maintain consistency, transparency, and comparability across analyses, the same descriptive approach (simple mean) was used for all countries. It is recommended that in future studies, researchers fully report sample sizes and other information necessary for weighted analyses. Moreover, to increase the accuracy and comparability of future studies, it is suggested that a general policy and global standard be established in research design, such as determining minimum and maximum sample sizes for each study, standard time frames for data collection, and independent reporting of data from each country [65]. Implementing such a policy could yield a more accurate and reliable global map, and health decisions at the national and international levels could be based on more reliable data [65]. Also, because the information on genes and mutations was incomplete, they could not be included in the analysis. Therefore, it is recommended that the percentage and type of mutations and genes associated with resistance be fully and accurately reported in a manner that allows for consistent and comparable analysis across studies. In addition, disclosing sequencing methods and providing genetic data in public databases are important for increasing transparency and reproducibility.
Therefore, to better understand BDQ resistance and, consequently, more effectively control and treat MDR and XDR-TB, it is important that future research provides more accurate and comprehensive genetic information and that global standards for data collection and reporting are developed to map more complete and reliable patterns of resistance worldwide.
Author contributions
HS and MM conducted investigations, analyzed data, wrote a draft of the manuscript, and performed the experiments. MSH: designed and supervised, contributed data or analysis tools, wrote, read, edited, and approved the manuscript.
Funding
There is no funding.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethical approval
Not applicable.
Declarations of Generative AI and AI-assisted technologies in the writing process
Artificial intelligence assistance (OpenAI ChatGPT, GPT-4) was used exclusively for language editing, translation, grammar refinement, and formatting. The authors reviewed and verified all content to ensure accuracy and integrity of the final manuscript.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Hanie Sakhi and Maryam Meskini are co-first authors.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.