Tuning the immune response in tuberculosis

Lead Research Organisation: University College London
Department Name: Infection

Abstract

Tuberculosis (TB) is an important infectious disease which affects nine million people and causes two million deaths every year. The human immune system can protect against TB but is also responsible for causing the tissue damage that may result from TB disease. I aim to increase our understanding of the parts of the immune system that influence the balance of beneficial and harmful responses to TB infection in order to identify new targets for more effective treatments and vaccines. To do this I will combine experiments in a fish model that closely resembles human TB with experiments in patients with active TB disease. Initially, I will focus on the role of a specific part of the immune system called interleukin (IL)10 because this is a key mediator that controls the immune system during its response to infections. Thus far the role of IL10 in TB has almost exclusively been evaluated in mouse models that provide incomplete information because they do not accurately reflect human TB disease. In addition, I will take advantage of the massive increase in genetic data that has become available, in order to discover new components of immune responses to TB which vary most between people. I postulate that variable immune responses cause differences in outcome of TB infection. I will test this theory by investigating the effects of deficiency or excess of potential new regulatory factors that I identify in people with TB, using the fish model of TB infection. I hope to gain new insights that help to develop novel interventions that will significantly shorten the length of anti-TB treatment, which will be important to reduce spread of TB and minimise development of drug resistance. I anticipate that my work may also lead to design of new vaccines that prevent TB disease altogether.

Technical Summary

Understanding the molecular determinants that tune immune responses to provide effective control of mycobacterial growth without immunopathology is a key priority in tuberculosis (TB) research. I will combine transcriptional profiling of the tuberculin skin test (TST) for molecular level assessment of human anti-mycobacterial immune responses, with studies using the genetically tractable zebrafish Mycobacterium marinum (Mm) infection model to evaluate the role of a key immunoregulatory cytokine, interleukin (IL)10, in tuning the immune response in TB. I will also adopt a genome-wide discovery approach to identify novel regulators of human immune responses to Mycobacterium tuberculosis (Mtb), on the basis that variability in anti-mycobacterial responses is responsible for differences in pathogenesis. I will cross-reference genes within the TST that exhibit highly variable expression levels between different individuals, with data from recent functional genomic studies that describe putative genetic interactions, in order to identify key regulatory hubs. Functional effects of potential master-regulators on anti-mycobacterial immune responses will be investigated by genetic manipulation in the zebrafish Mm model. By selecting candidates based on variable human anti-mycobacterial immune responses and testing them using the zebrafish, which has a successful track record for modelling human TB, this cutting-edge strategy promises to elucidate novel pathways that tune immune responses to determine clinical outcome in TB. Importantly, this will inform development of adjunctive host-directed therapies to significantly shorten duration of standard anti-tuberculous chemotherapy, risk stratification of active disease in latent TB infection and strategies for design of novel anti-TB vaccines.

Planned Impact

The principal impact of my proposed research will be to improve current understanding of immunological correlates of protection and pathogenesis in tuberculosis (TB). This work will be of broad interest to both the clinical and scientific community focussed on mycobacterial infection specifically, and infectious diseases more generally. Other investigators in the field will benefit from access to novel transcriptomic datasets incorporating immune responses to human and zebrafish mycobacterial infection, generated by my work to use for their own research.
Identifying pathways that can be targeted for personalised host directed therapy as an adjunct to standard chemotherapy in people with active TB is expected to significantly reduce morbidity and mortality associated with disease, by radically shortening treatment duration, preventing disease complications and improving efficacy of current antimicrobial regimens in those infected with drug resistant organisms. Short treatment regimens will promote better compliance with drug therapy, leading to reduced rates of drug resistance and TB transmission. Furthermore, my work will inform stratification of individuals who are latently infected for risk of developing active TB. This will ensure prophylactic therapy is only given to those at significant risk, for whom the benefits of treatment outweigh the risks of serious side effects, such as hepatotoxicity. This project will also potentially identify new vaccine targets that will facilitate rational design of much needed new, effective anti-TB vaccines to prevent disease altogether, which is particularly important in resource poor settings with high TB prevalence.
Infectious diseases impose a significant financial burden on the United Kingdom's economy. I anticipate that strategies to improve TB control that may arise as a result of my findings, will significantly reduce financial costs to both the health service and employers. Importantly, shorter treatment regimens will ensure less time lost from work and more rapid return to full productivity that will benefit both the national and global economy. In addition, minimising development of drug resistant TB will reduce the need for expensive, prolonged antibiotic courses and specialist inpatient care in this context.
My research will also form the scientific basis on which to update current guidelines for TB treatment. The ability to accurately predict progression to active disease in latently infected individuals will be of specific interest to policy makers with respect to developing evidence-based guidelines for treatment of latent TB.
Through my proposed programme of work and collaborations that I have recently initiated with Stephen Renshaw (Sheffield University) and Annemarie Meijer (Leiden University), I will acquire a broad range of new skills that will be invaluable in achieving my current and future research objectives. This fellowship will augment my transition to an independent investigator at the forefront of clinical and laboratory research in TB and respiratory tract inflammation and lays the foundations for obtaining a Senior Clinical Fellowship. In addition, the post-doctoral researcher appointed to work alongside me on this project will gain experience in a wide repertoire of laboratory techniques. They will also benefit from existing expertise in bioinformatic analysis within the host laboratory as well as frequent interactions with the dynamic academic community at UCL.

Publications

10 25 50
 
Description I have established the zebrafish larval Mycobacterium marinum infection model and generated two new CRISPR mutants for interleukin (IL)10 and one for interferon regulatory factor (IRF)5. I have also developed new image analysis software to measure the effects of genetic manipulation on disease severity. This work has been published in Scientific Reports (doi.org/10.1038/s41598-020-59932-1).
I evaluated the role of the key regulatory cytokine, IL10, in zebrafish larval M marinum infection using my new CRISPR mutants (il10u5028 and il10u5029) and an existing mutant (e46 allele, Sanger Zebrafish Mutation Project) to model gene deficiency and using mRNA injection to overexpress IL10. Manipulation of IL10 levels had no effect on disease severity or the inflammatory response to M marinum, suggesting that IL10 has no significant biological impact in this model. This line of investigation has therefore been discontinued.
My current zebrafish work is focused on my CRISPR mutant for IRF5 (irf5u5030), the key transcription factor that programmes macrophages to adopt a pro-inflammatory phenotype. Mutants show 10 fold higher bacterial burden compared to their wild type siblings and significantly greater spatial dispersion of bacteria, reflecting more severe disease. These exciting data suggest that IRF5 plays an important protective role in the host response in zebrafish larval M marinum infection. I am developing this work during a further 18 month extension of my current fellowship.
I have completed recruitment of a cohort of people with pulmonary tuberculosis undergoing gene expression profiling of biopsies taken from the site of tuberculin skin test challenge, which provides a surrogate for the immune response in the lungs. Data from my cohort formed the basis for a manuscript focused on the role of IL17 in TB pathogenesis published in Science Translational Medicine (doi: 10.1126/scitranslmed.abg7673). I have also selected genes associated with disease severity identified in my human TB data, for mechanistic studies using the zebrafish larval mycobacterial infection model.
I have established the system to generate CRISPant zebrafish larvae by injection of short guide RNA-Cas9 protein complexes into one cell stage zebrafish embryos to model gene deficiency. During my fellowship extension I will use this approach to validate whether putative drivers of disease severity selected from my human TB data impact disease phenotype experimentally in the zebrafish larval mycobacterial infection model.
Exploitation Route I will be developing my findings further during the further 18 month extension of my fellowship.
Sectors Healthcare

Pharmaceuticals and Medical Biotechnology

 
Description Costed extension to MRC Clinician Scientist Fellowship
Amount £174,488 (GBP)
Funding ID MR/N007727/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 03/2022 
End 08/2023
 
Description Costed extension to MRC Clinician Scientist Fellowship (MRC contribution)
Amount £58,306 (GBP)
Funding ID MR/N007727/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 03/2020 
End 02/2022
 
Description Costed extension to MRC Clinician Scientist Fellowship (UCL contribution)
Amount £58,306 (GBP)
Funding ID MR/N007727/1 
Organisation University College London 
Sector Academic/University
Country United Kingdom
Start 03/2020 
End 02/2022
 
Description MRC Contribution to Additional Clinical Research Costs (January 2021)
Amount £21,722 (GBP)
Funding ID MR/N007727/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 03/2021 
End 07/2022
 
Description Medical Research Council Clinician Scientist Fellowship
Amount £1,117,999 (GBP)
Funding ID MR/N007727/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 03/2016 
End 02/2020
 
Description UCL UKRI COVID-19 Grant Extension Allocation
Amount £34,040 (GBP)
Organisation United Kingdom Research and Innovation 
Sector Public
Country United Kingdom
Start 03/2021 
End 09/2021
 
Description UCL Wellcome Institutional Strategic Support Fund Restarting Research Award
Amount £19,997 (GBP)
Funding ID 204841/Z/16/Z 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 11/2021 
End 02/2022
 
Description UKRI GCRF and Newton Institutional Consolidated Impact Account (GNCA) allocation to University College London
Amount £49,391 (GBP)
Funding ID Added to MR/N007727/1 
Organisation United Kingdom Research and Innovation 
Sector Public
Country United Kingdom
Start 12/2022 
End 03/2023
 
Title QuantiFish 
Description We have developed new open source image analysis software called QuantiFish for quantitation of fluorescent foci in zebrafish larvae, to support infection research in this model. QuantiFish extends the conventional measurements of bacterial load and number of bacterial foci to quantify spatial distribution of pathology and the proportional distribution of the total disease burden between sites. Our novel measures of disease severity provide greater capacity to detect differences following experimental manipulation, that could be applied widely to any zebrafish model where spatial distribution of focal pathology is important. 
Type Of Material Physiological assessment or outcome measure 
Year Produced 2019 
Provided To Others? Yes  
Impact Our analysis tools provide novel methods to assess severity of infection; the spatial distribution of bacterial foci and the proportional distribution of total burden of pathology between foci. We show in our publication that these measures can reliably discriminate intravenous and hindbrain routes of Mycobacterium marinum infection, which are indistinguishable by measurement of bacterial load (the most widely used measure of disease severity) and not consistently differentiated by the number of bacterial foci. These tools are already being adopted by other investigators within the field (Mostowy Lab (London School of Hygiene and Tropical Medicine), Ellks Lab (Sheffield University), Meijer lab (Leiden University), Oehlers Lab (University of Sydney)). We anticipate that our tools could also be applied to other zebrafish models where spatial distribution of focal pathology is important, such as metastatic cancer. As such, these analysis methods represent an exciting advance, of considerable utility to a wide range of investigators engaged in zebrafish research. 
URL https://github.com/DavidStirling/QuantiFish
 
Description Collaboration with Professor Annemarie Meijer (University of Leiden) 
Organisation Leiden University
Department Institute of Biology Leiden
Country Netherlands 
Sector Academic/University 
PI Contribution I undertook a secondment to Professor Annemarie Meijer's lab (University of Leiden) for the first two months of my fellowship in order to gain technical competence in intravenous injection of zebrafish embryos and experience in fluorescence microscopy to quantify mycobacterial infection.
Collaborator Contribution Annemarie Meijer's group have provided a mutant zebrafish line for my project and stocks of fluorescent wild type and mutant Mycobacterium marinum for this work.
Impact The experience gained during my secondment to Leiden University has been invaluable in allowing me to establish the zebrafish mycobacterial infection model at UCL.
Start Year 2016
 
Title QuantiFish 
Description We have developed new open source image analysis software called QuantiFish for quantitation of fluorescent foci in zebrafish larvae, to support infection research in this model. QuantiFish extends the conventional measurements of bacterial load and number of bacterial foci to quantify spatial distribution of pathology and the proportional distribution of the total disease burden between sites. Our novel measures of disease severity provide greater capacity to detect differences following experimental manipulation, that could be applied widely to any zebrafish model where spatial distribution of focal pathology is important. 
Type Of Technology Software 
Year Produced 2019 
Open Source License? Yes  
Impact This software allows rapid, accurate quantitation of mycobacterial load and dissemination of infection by quantifying fluorescence in zebrafish embryos infected with fluorescent bacteria. Our analysis tools provide novel methods to assess severity of infection; the spatial distribution of bacterial foci and the proportional distribution of total burden of pathology between foci. We show in our publication that these measures can reliably discriminate intravenous and hindbrain routes of Mycobacterium marinum infection, which are indistinguishable by measurement of bacterial load (the most widely used measure of disease severity) and not consistently differentiated by the number of bacterial foci. These tools have already been adopted by several different European groups working on zebrafish infection and the Oehlers Lab (University of Sydney). We anticipate that our tools could also be applied to other zebrafish models where spatial distribution of focal pathology is important, such as metastatic cancer. As such, these analysis methods represent an exciting advance, of considerable utility to a wide range of investigators engaged in zebrafish research. 
URL https://github.com/DavidStirling/QuantiFish