This PhD opportunity is being offered as part of the LSTM and Lancaster University Doctoral Training Partnership. Find out more about the studentships and how to apply.
| Abstract | Non-tuberculous mycobacteria (NTM), including Mycobacterium abscessus and M. avium, are emerging pathogens causing significant morbidity, particularly in immunocompromised individuals such as those living with HIV or structural lung disease. While related to M. tuberculosis, the causative agent of TB, anti-TB drug regimens and vaccines do not work in NTM. Therapeutic regimens include multiple toxic, poorly effective antibiotics that must be taken for at least 12 months. Even if treatment is adhered to, ~50% of patients will fail to achieve a clinical cure. Treatment is complicated by intrinsic antimicrobial resistance (AMR) to most clinically used classes of antibiotics, yet the genomic determinants of AMR remain poorly understood. In addition, there is emerging evidence of horizontal gene transfer through plasmid acquisition but the role of plasmids in NTM also remains poorly understood. This project aims to define the resistome of clinically relevant NTM isolates from the UK and Malawi using an integrated genomic and functional approach. Isolates will undergo whole genome sequencing to identify known and novel resistance genes, which will be correlated with phenotypic drug susceptibility profiles, including intracellular infection models. Functional genomics will be employed to validate key resistance determinants through targeted gene knockouts, providing mechanistic insight into their roles in drug tolerance and virulence. By linking genomic data with functional outcomes, this project will provide a comprehensive understanding of AMR in NTM, informing the development of more effective therapeutic strategies and guiding global efforts to manage these challenging infections. |
| Where does this project lie in the translational pathway? | T1 - Basic Research |
| Methodological Aspects | This project will employ an integrated experimental and computational approach to define the resistome of NTM. Key methodologies include: Whole Genome Sequencing: Clinical isolates of M. abscessus and M. avium from the UK and Malawi will be sequenced to identify known and novel AMR genes and other genomic determinants of resistance. Quantitative comparative genomics and bioinformatics pipelines will be used to analyse sequence data, including gene presence/absence, single nucleotide polymorphisms, and phylogenetic relationships. Long read sequencing will be of particular focus to identify and map putative plasmids. Phenotypic Drug Susceptibility Assays: Standardised in vitro assays will measure minimum inhibitory concentrations across multiple antibiotics, generating quantitative datasets for correlation with genomic resistance determinants. Intracellular Infection Models: Host-pathogen interactions will be modelled using macrophage infection assays, allowing quantification of bacterial survival, replication, and drug efficacy in a physiologically relevant context. Functional Genomics: Targeted gene knockouts will validate candidate resistance determinants, linking specific genetic elements to phenotypic outcomes. Quantitative readouts of growth, survival, and intracellular replication will provide robust functional data. This combination of genomic, phenotypic, and functional analyses ensures a rigorous, quantitative framework for elucidating NTM resistance mechanisms. |
| Expected Outputs | Publications wise, I anticipate at least one high impact publication detailing the genomic and phenomic resistome of NTM. This has not been published to date and in particular the focus on isolates from UK and Sub-Saharan Africa will be transformational for the field. This work will likely be high scoring for REF, expected to be a 4*. I have a fellowship currently submitted on NTM, and am planning future submissions to BBSRC and MRC once the outcome of my fellowship in 2026 is known- this project underpins my work to date on NTM and so will be essential to future funding applications over the coming years. In particular, I aim to apply to Gates Foundation to develop NTM therapeutics and these data will be key to demonstrating we have the expertise and knowledge to develop new therapeutics. This project will advance understanding of NTM AMR, informing therapeutic strategies and guiding clinical management of these difficult-to-treat infections. Methodologically, it will demonstrate the value of integrating genomics, functional genomics, and host-pathogen models, creating transferable expertise in high-throughput and quantitative research. The student will acquire interdisciplinary skills across microbiology, bioinformatics, and functional genomics, preparing them for academic or industry careers addressing antimicrobial resistance globally. |
| Training Opportunities | Building on previous MRC DTP students’ experience, there will be a residential bioinformatics training course for one week offered, provided by the University of Birmingham. Full lab training will be provided covering wet lab and organoid work, supported by both Fabrice and Giancarlo. |
| Skills Required | Student must possess experience of working in a lab in either microbiology or tissue culture. A life sciences degree such as biochemistry, microbiology or genetics would be preferred as would a relevant masters but I would also be keen to consider students who have industry or research experience in lieu of a Masters. |
| Subject Areas | Lung health & tuberculosis; antimicrobial resistance |
| Key Publications associated with this project |
D Cantillon: Searching for new therapeutic options for the uncommon pathogen Mycobacterium chimaera: an open drug discovery approach: https://pubmed.ncbi.nlm.nih.gov/35544099/ D Cantillon: Three-dimensional low shear culture of Mycobacterium bovis BCG induces biofilm formation and antimicrobial drug tolerance: https://pubmed.ncbi.nlm.nih.gov/33526771/ D Cantillon: Dissecting the Mycobacterium bovis BCG Response to Macrophage Infection to Help Prioritize Targets for Anti-Tuberculosis Drug and Vaccine Discovery: https://pubmed.ncbi.nlm.nih.gov/35062774/ F Graf: A High-Throughput Method for Screening for Genes Controlling Bacterial Conjugation of Antibiotic Resistance: https://pubmed.ncbi.nlm.nih.gov/33361328/ G Biagini: Intracellular Pharmacodynamic Modeling Is Predictive of the Clinical Activity of Fluoroquinolones against Tuberculosis: https://pubmed.ncbi.nlm.nih.gov/31611354/ |