Investigation of Mycobacterium tuberculosis and host responses through transcriptomic analysis of tuberculosis infection models

  • Jamie Medley

Student thesis: Doctoral Thesis


Tuberculosis is the leading cause of death by a single bacterial agent, causing 1.3 million deaths in 2021. Developing new multi-drug therapies and vaccines, necessitated by increasing antibiotic resistance and lack of current vaccine efficacy, requires further insights into Mycobacterium tuberculosis (MTB) and host environment interactions. Understanding pathways expressed by MTB in lung granulomata and the host immune response to infection will help highlight potential therapeutic targets and assess vaccine efficacy, identifying signatures associated with disease states, potentially acting as correlates of protection or disease progression.

This thesis begins by applying novel, targeted gene expression to reveal differences in the MTB transcriptome between acute and chronic murine models of infection using previously inaccessible quantities of RNA. qRT-PCR targeting 16S rRNA was then used to quantify concentration of RNA extractable from more representative animal models of infection including guinea pigs (GP) and non-human primates (NHP). Though concentrations were too low for downstream application of currently available transcriptomic methods, quantitative differences in bacterial load between stages of infection, types of granulomata, drug treatment and vaccine given were demonstrated.

Next, host immune response was investigated, applying targeted gene expression analysisto RNA extracted from formalin-fixed, paraffin embedded (FFPE) granulomatous NHP lung tissue. There were clear differences in expression of immunological genes and pathways between animals challenged with MTB after either BCG or MTBVAC vaccination. Gene expression-based cell profiling was also applied to measure cell type abundance of immune cells within our samples and confirmed prior investigation by immunohistochemical staining.

Requirements for in vivo models which result in sufficient MTB RNA to assess transcriptomic response post treatment led us to investigate the Galleria mellonella (GM) model of infection. After successful extraction of mycobacterial RNA and RNA-sequencing, differential gene expression between in vivo bacteria and in vitro log-phase culture, and between bacteria at different timepoints of infection was revealed. These differences included increased expression of genes associated with hypoxic response, cholesterol catabolism and metal ion regulation. The gene expression profile also showed significant overlap with other models of infection, including intracellular macrophage response and the acute murine model confirming similarities between GM and more representative models of infection.

Finally, we applied RNA-sequencing to MTB patient sputa to demonstrate current limitations, hurdles, and possible opportunities in determining MTB transcriptional response to human infection. These results will contribute to understanding of how both host and pathogen respond to infection.
Date of AwardJun 2024
Original languageEnglish
Awarding Institution
  • University of Brighton
SupervisorSimon Waddell (Supervisor)

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