An improved catalogue for whole-genome sequencing prediction of bedaquiline resistance in M. tuberculosis using a reproducible algorithmic approach

Objectives: Bedaquiline (BDQ) has only been approved for use for a little over a decade yet is a key drug for treating multi-drug resistant tuberculosis. Rising levels of resistance threaten, however, to reduce its effectiveness. Catalogues of mutations associated with resistance to bedaquiline are...

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Vydáno v:bioRxiv
Hlavní autoři: Adlard, Dylan, Lavania, Joseph, Webster, Hermione, O'reilly, Ailva, Knaggs, Jeff, Peto, Timothy Ea, Crook, Derrick W, Shaheed Vally Omar, Fowler, Philip W
Médium: Paper
Jazyk:angličtina
Vydáno: Cold Spring Harbor Cold Spring Harbor Laboratory Press 25.02.2025
Cold Spring Harbor Laboratory
Vydání:3.1
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ISSN:2692-8205, 2692-8205
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Shrnutí:Objectives: Bedaquiline (BDQ) has only been approved for use for a little over a decade yet is a key drug for treating multi-drug resistant tuberculosis. Rising levels of resistance threaten, however, to reduce its effectiveness. Catalogues of mutations associated with resistance to bedaquiline are key to detecting resistance genetically for either diagnosis or surveillance. At present building catalogues requires considerable expert knowledge, often requires the use of complex grading rules, and is an irreproducible process. We propose an algorithmic approach (catomatic) which requires minimal expertise and can be used to automatically and reproducibily build accurate catalogues. Methods: We developed an automated method that associates genetic variants with resistance (or susceptibility) using a two-tailed binomial test with a stated background rate and applied it to a dataset of 11,867 Mycobacterium tuberculosis samples with whole genome and bedaquline susceptibility testing data. Using this framework we investigated how to best classify variants and the phenotypic significance of minor alleles. Results: The genes mmpS5 and mmpL5 are not directly associated with bedaquline resistance. Our catalogue of Rv0678, atpE, and pepQ variants attains a cross-validated sensitivity and specificity of 79.4 ± 1.8 % and 98.5 ± 0.3%, respectively, for 94 ± 0.4% of samples. Identifying samples with subpopulations containing Rv0678 variants improves sensitivity, and detection thresholds in bioinformatic pipelines should therefore be lowered. Conclusion: By using a more permissive and deterministic algorithm trained on a sufficient number of resistant samples we have reproducibly constructed an AMR catalogue for BDQ resistance-associated variants that is comprehensive and accurate.Competing Interest StatementTEAP, DWC, and PWF receive consultancy fees from the Ellison Institute of Technology, Oxford.Footnotes* Fig 4F has been updated (and the corresponding equivalents in the Supplement). Also the key software package now has a DOI and is cited as such.* https://github.com/fowler-lab/tb-bdq-cat/
Bibliografie:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
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Competing Interest Statement: DWC, and PWF receive consultancy fees from the Ellison Institute of Technology, Oxford Ltd.
ISSN:2692-8205
2692-8205
DOI:10.1101/2025.01.30.635633