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Bovine TB: Reconstructing the molecular evolution of Mycobacterium bovis

Project Description

Bovine tuberculosis (TB) is an infectious mycobacterial disease caused by Mycobacterium tuberculosis var. bovis, a pathogenic member of the M. tuberculosis complex bacteria. It is the most costly, problematic and controversial endemic zoonosis currently facing government, the farming industry and veterinarians in the UK and Ireland with annual control costs estimated currently at £40M for N Ireland and €84M for Ireland. The epidemiology of bovine TB is notoriously complex and still lacking in detail, with current evidence indicating both cattle and wildlife sources. Additional information that would guide the use of control management strategies on a more science- and evidence-based footing would be of great value to policy-makers and stakeholders.

DAFM (Ireland) and DAERA (N Ireland) have co-funded the UCD-led project: BTBGENIE (Bovine TuBerculosis GENomics IrEland): The project, which focuses on the development of genomic epidemiology systems for tracking and eradicating Mycobacterium bovis in Ireland will benefit from recent advances in genomics methodologies and parallel bioinformatics pipelines. Whole-genome sequencing (WGS) now provides a step-change in our ability to characterize pathogens. BTBGENIE aims to integrate pathogen WGS more fully into the TB control programmes and to investigate the transmission, epidemiology and evolution of M. bovis in Ireland. This PhD project is integral to the BTBGENIE project. The student will have access to an unprecedented bio-bank of M. bovis isolates, collected on the island of Ireland over years and from various hosts and ~1,000 M. bovis whole-genome sequences.

Available infrastructure resources:
The student will have in-house access to both genome NGS sequencing platforms (Illumina MiSeq, HiSeq and NovaSeq) and dedicated High Performance Computer infrastructure in AFBI, QUB and UCD. Professor Prodohl’s laboratory in QUB also provides direct access to state of the art medium- high- throughput automated SNP genotyping technology that will be used to screen multiple bacterial isolates for clade-defining markers identified by WGS, thereby permitting high-resolution phylogeographic analyses of M. bovis diversity.

General PhD objectives are:
1) To construct a phylogeny for M. bovis in Ireland for comparison with other areas in Britain and elsewhere.
2) To investigate potential signatures of selection within identified evolutionary lineages.
3) To identify and map M. bovis genetic structure and diversity in Ireland; investigating phylogeographic distribution of sequence / strain types and their wider dispersal.
4) Use genomic data, to detect and estimate the relative importance of bi-directional, cross border dissemination of bovine TB in Ireland.


The student will be trained in collection and management of large genomics datasets, state of the art phylogenetic comparative approaches in R and mathematical models of evolution (including detecting potential signatures of genomic selection), and will capitalise on the availability of Queen’s University High Performance Computing resources (KELVIN). The student will also have the opportunity to interact with researchers of the wider BTBGENIE team at QUB, AFBI and UCD.

In addition to addressing discovery and translational research questions on a topic of national and international significance, the student will gain a valuable set of interdisciplinary skills that increase employability, including cutting-edge statistical and mathematical modelling, data management, numeracy, evaluating risk and uncertainty, as well as gaining an in-depth understanding of fundamental principles in microbial evolution, pathogen genomics and epidemiology. Through interactions with AFBI researchers,the student will also gain a better understanding of disease surveillance and management and some of the skills required to inform policy.

Start date:

1 March 2020


36 months

This project will be supervised by Professor Paulo Prodohl and Dr Rosaleen Hynes (QUB) and Dr Adrian Allen and Professor Robin Skuce (AFBI). The project advisor is Professor Stephen Gordon of UCD.

Academic Eligibility:

Candidates should have (or expect to achieve) a minimum of a 2.1 Honours degree in a relevant subject (e.g. Biological subject or Computer Sciences). Applicants with a minimum of a 2.2 Honours degree may be considered providing they have a Distinction at Master’s level.

Application Procedure:

• Apply for Degree of Doctor of Philosophy in Biological Sciences at Queen’s University Belfast
• State name of the lead supervisor as ‘Name of Proposed Supervisor’ on application
• State DAFM/DAERA Intended Source of Funding
• Select ‘Visit Website’ to apply now

Funding Notes

This project is funded by a DAFM/DAERA Partnership to support collaborative research in agreed priority areas across both jurisdictions. The studentship provides funding for tuition fees, stipend and research training and support grant subject to eligibility.

Please note that the studentship will cover a maximum of €6,000 per annum of the QUB tuition fees for non-EEA students. Non-EEA students may also be required to apply for a visa in order to travel from the UK to the Republic of Ireland.


Brites D, Loiseau C, Menardo F, et al. A New Phylogenetic Framework for the Animal-Adapted Mycobacterium tuberculosis Complex. Front Microbiol. 2018;9:2820. Published 2018 Nov 27. doi:10.3389/fmicb.2018.02820

Chiner-Oms Á, Sánchez-Busó L, Corander J, et al. Genomic determinants of speciation and spread of the Mycobacterium tuberculosis complex. Sci Adv. 2019;5(6):eaaw3307. Published 2019 Jun 12. doi:10.1126/sciadv.aaw3307

Crispell J, Benton CH, Balaz D, et al. Combining genomics and epidemiology to analyse bi-directional transmission of Mycobacterium bovis in a multi-host system. Elife. 2019;8:e45833. Published 2019 Dec 17. doi:10.7554/eLife.45833

Smith NH, Gordon SV, de la Rua-Domenech R, Clifton-Hadley RS, Hewinson RG. Bottlenecks and broomsticks: the molecular evolution of Mycobacterium bovis. Nat Rev Microbiol. 2006;4(9):670–681. doi:10.1038/nrmicro1472

How good is research at Queen’s University Belfast in Agriculture, Veterinary and Food Science?

FTE Category A staff submitted: 33.40

Research output data provided by the Research Excellence Framework (REF)

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