Chronic lung diseases like COPD affect millions of people in the UK and worldwide, and are increasing in prevalence. COPD is characterised by progressive, irreversible airflow limitation, lung damage and respiratory symptoms with periods of acute worsening of symptoms (exacerbations) which are often treated with antibiotics. Culture independent studies have shown that the lungs harbour a diverse community (microbiome) of bacteria. Work we, and others, have published has shown that a loss of lung microbiome diversity (dysbiosis) is associated with increasing disease severity in COPD. The role of antibiotics, in driving the development of lung microbiome dysbiosis in COPD is not fully understood. There is a need to develop novel strategies to personalise treatment of COPD exacerbations to minimise unnecessary antibiotic prescriptions.
This project will provide the data needed to develop personalised treatment strategies for exacerbations of COPD, by determining if antibiotic prescribing patterns have an impact on lung microbiome dysbiosis, and whether defined microbiome dysbiosis characteristics are able to predict long term outcomes for COPD patients. 16S rRNA sequencing of additional sputum samples will be performed to supplement the existing microbiome sequencing data from COPD patients. Bioinformatic and statistical analysis of the sequencing data obtained in this project will be carried out on a high-performance computing cluster using specialised data analysis methods based on R computing packages. This data will be compared to anonymised patient prescribing records held by the Health Informatics Centre to identify antibiotic prescribing patterns associated with microbiome dysbiosis.
The student will join the respiratory infection research group at the School of Medicine, University of Dundee, which includes 3 principle investigators, post-docs, PhD students, technicians and a bioinformatician. The student will join an extremely productive and supportive environment dedicated to high quality research training, whose microbiome sequencing and data analysis work stream is a core part of large research grants and has resulted in several high impact publications. The student will be actively encouraged to engage with the wider respiratory research, university and patient communities including attending and presenting at major international conferences. Mentorship is individualized to students needs and we encourage flexible working and policies to encourage diversity and a positive working environment.
We are looking for a team orientated individual with a background in biology or medical science wishing to perform cutting edge translational research to start in January 2022. Experience of bioinformatics/ analysis of large datasets will be an advantage but full training in all methodologies will be provided.
For informal enquiries - please contact Dr Alison Dicker [Email Address Removed]
To apply - please send a covering letter and CV to Dr Alison Dicker [Email Address Removed]
Closing date - 12 November 2021
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