<i>Galleria mellonella -</i> a novel infection model for the <i>Mycobacterium tuberculosis</i> complex

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Li, Yanwen;Spiropoulos, John;Cooley, William;Khara, Jasmeet Singh;Gladstone, Camilla A;Asai, Masanori;Bossé, Janine T;Robertson, Brian D;Newton, Sandra M;Langford, Paul R

Description

Animal models have long been used in tuberculosis research to understand disease pathogenesis and to evaluate novel vaccine candidates and anti-mycobacterial drugs. However, all have limitations and there is no single animal model which mimics all the aspects of mycobacterial pathogenesis seen in humans. Importantly mice, the most commonly used model, do not normally form granulomas, the hallmark of tuberculosis infection. Thus there is an urgent need for the development of new alternative in vivo models. The insect larvae, Galleria mellonella has been increasingly used as a successful, simple, widely available and cost-effective model to study microbial infections. Here we report for the first time that G. mellonella can be used as an infection model for members of the Mycobacterium tuberculosis complex. We demonstrate a dose-response for G. mellonella survival infected with different inocula of bioluminescent Mycobacterium bovis BCG lux, and demonstrate suppression of mycobacterial luminesence over 14 days. Histopathology staining and transmission electron microscopy of infected G. mellonella phagocytic haemocytes show internalization and aggregation of M. bovis BCG lux in granuloma-like structures, and increasing accumulation of lipid bodies within M. bovis BCG lux over time, characteristic of latent tuberculosis infection. Our results demonstrate that G. mellonella can act as a surrogate host to study the pathogenesis of mycobacterial infection and shed light on host-mycobacteria interactions, including latent tuberculosis infection.

Citations (1)

Mentions (0)

Metrics

Dataset Index

0.6

FAIR Score

85%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Taylor & Francis

Assigned Domain

Subfield

Infectious Diseases

Field

Medicine

Domain

Health Sciences

Confidence Score

84%

Source

Open Alex

Keywords

MedicineMicrobiologyFOS: Biological sciencesBiotechnologyEcologyImmunologyFOS: Clinical medicineBiological Sciences not elsewhere classifiedScience PolicyInfectious DiseasesFOS: Health sciencesVirologyComputational Biology

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00