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- W2940451323 abstract "Animal infection models are vital as drug screens for novel therapeutics to tackle the global tuberculosis (TB) epidemic. However, all pre-existing models have limitations which include ethical constraints. Therefore, efforts to reduce and/or replace conventional animal models in TB research are warranted. Previously, we reported the use of Galleria mellonella (greater wax moth, GM) as a novel infection model for the Mycobacterium tuberculosis (MTB) complex, using Mycobacterium bovis BCG lux, a bioluminescent mutant which allows for the rapid quantification of bacterial burden in vivo. Here we investigated the drug screening potential of GM infected with a lethal dose of BCG lux, treated with first or second-line antimycobacterial drugs over a 96 h period; where drug efficacy was determined every 24 h through bioluminescent measurement of larval homogenates. Improved survival outcome was observed in all larvae treated with antimycobacterials when compared to untreated controls. Furthermore, all drug treatments except pyrazinamide resulted in a significant reduction in bioluminescence of BCG lux in vivo. Isoniazid and rifampicin displayed the highest survival outcome and greatest in vivo drug efficacy, in line with observations reported in mice. However, combined or multiple dosing of either drug showed little to no difference over single dose mono-therapy. Our results demonstrate that GM is a promising infection model for members of the MTB complex, with significant potential for its use in the drug development pipeline as a pre-screening model for novel therapeutics, thereby reducing experimental usage of animals in TB research. Supported by the NC3R’s (NC/R001596/1)" @default.
- W2940451323 created "2019-05-03" @default.
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- W2940451323 date "2019-03-01" @default.
- W2940451323 modified "2023-10-16" @default.
- W2940451323 title "Galleria mellonella: a novel infection model for screening potential anti-mycobacterial compounds against members of the Mycobacterium tuberculosis complex" @default.
- W2940451323 doi "https://doi.org/10.1099/acmi.ac2019.po0172" @default.
- W2940451323 hasPublicationYear "2019" @default.
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