Abstract
Encapsulating antibiotics such as rifampicin in biodegradable nanoparticles provides several advantages compared to free drug administration, including reduced dosing due to localized targeting and sustained release. Consequently, these characteristics reduce systemic drug toxicity. However, new nanoformulations need to be tested in complex biological systems to fully characterize their potential for improved drug therapy. Tuberculosis, caused by infection with the bacterium Mycobacterium tuberculosis, requires lengthy and expensive treatment, and incomplete therapy contributes to an increasing incidence of drug resistance. Recent evidence suggests that standard therapy may be improved by combining antibiotics with bacterial efflux pump inhibitors, such as thioridazine. However, this drug is difficult to use clinically due to its toxicity. Here, we encapsulated thioridazine in poly(lactic-co-glycolic) acid nanoparticles and tested them alone and in combination with rifampicin nanoparticles, or free rifampicin in macrophages and in a zebrafish model of tuberculosis. Whereas free thioridazine was highly toxic in both cells and zebrafish embryos, after encapsulation in nanoparticles no toxicity was detected. When combined with rifampicin nanoparticles, the nanoparticles loaded with thioridazine gave a modest increase in killing of both Mycobacterium bovis BCG and M. tuberculosis in macrophages. In the zebrafish, the thioridazine nanoparticles showed a significant therapeutic effect in combination with rifampicin by enhancing embryo survival and reducing mycobacterial infection. Our results show that the zebrafish embryo is a highly sensitive indicator of drug toxicity and that thioridazine nanoparticle therapy can improve the antibacterial effect of rifampicin in vivo.
Acknowledgements
We would like to thank L. Ramakrishnan and members of her group for their generous contribution of Mycobacterium marinum strains and advice on zebrafish infection and treatment methods and training in fluorescent pixel count analysis. We would also like to thank M. Gutierrez for his assistance with optimizing our CFU method, and G. Koster for valuable advice on FPC analysis.
Declaration of interest
The authors report no conflict of interest. This work was funded by the Norwegian Research Council (Fripro 143686) and an EEA mobility grant (to V.B.).