Tuberculosis (TB) is a major health problem worldwide with 10.4 million new cases in 2015 and 1.4 million deaths. Over a person’s life-time 5-10% of those infected with Mycobacterium tuberculosis (MTB) will develop active disease, requiring a cocktail of at least 4 drugs for up to 6 months duration, often with complex side effects and toxicities. The emergence and spread of multi-drug resistant (MDR) and extreme-drug resistant TB (XDR) poses a serious threat to disease control; new drugs and combination regimens which are shorter, safer and more efficacious to target LTBI and active disease are an urgent priority.
Two new drugs, bedaquiline and delamanid, have recently been approved for MDR-TB, however the last first-line drug to be developed was rifampicin in 1967. Currently, there are only 12 new or repurposed drugs undergoing late phase clinical trials; few, if any may enter the clinic. Thus, it is crucial to maintain a constant pipeline of novel antimycobacterial compounds and have reliable, low-cost, high-throughput in vivo infection models to screen novel compounds.
A range of animal models have been widely used in TB research to understand the basic mechanisms of MTB and the host response and to evaluate novel anti-mycobacterial agents, immunotherapeutics and new vaccine candidates. MTB infection models have been described in non-human primates (e.g. macaques), guinea pigs, rabbits, cattle, pigs, mice and zebrafish, however all have limitations. For example in mice, the most commonly used species, granulomas and areas of hypoxia are not seen which are characteristic of LTBI. The animal model that more closely resembles human MTB infection is the macaque. However ethical, cost, and practical considerations limit widespread use. Furthermore novel drug candidates showing promising antimicrobial activity in vitro often have limited therapeutic effects in expensive and time-consuming animal models. To overcome these issues there is an urgent need for a rapid, well-characterised, low-cost, high-throughput model that mimics the key features of other models, and could be used to screen novel drug candidates at an early stage of development.
The larva of the insect, Galleria mellonella (GM), has been increasingly used as a surrogate to study host-pathogen interactions in a range of bacterial pathogens, and as a rapid model to screen novel antimicrobial drug candidates. Advantages to using GM larva as an infection model include: 1) that they have an innate cell mediated immune system that shares a high degree of structural similarity to that of vertebrates including phagocytosis by haemocytes, the production of antimicrobial peptides and reactive oxygen and nitrogen species; 2) the large size of the moth larva for easy manipulation and facilitation of tissue and haemolymph collection for analysis; 3) maintenance at 37 ̊C making them well-suited to study the temperature at which human pathogens cause disease; 4) precise infection; 5) efficacy of antimicrobial agents can be assessed; and 6) ethically more acceptable that the use of mammalian hosts.
In preliminary studies we have demonstrated that GM shows promise as an infection model for mycobacteria which may be used to evaluate novel therapeutic agents, potentially reducing the number of animals required in drug screening experiments by 70%. The aim of this proposal is to characterise MTB-GM interactions and (1) Establish an optimal, reproducible GM-mycobacteria infection model; (2) Characterise host-mycobacteria interactions using the GM model; and (3) Utilise the GM-mycobacteria infection model for the assessment of classic and novel antimicrobial agents. The research will advance knowledge in the 3Rs by the development of a GM-mycobacterial infection model which will incorporate the benefits of controlled challenge, multiple replicates, measurements of changes in host/pathogen structure, transcriptome and proteome and will be applicable to a range of other pathogens.
Status:Not yet active
Principal investigatorProfessor Paul Langford
InstitutionImperial College London
Co-InvestigatorDr Sandra Newton
Dr Brian Robertson