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SalaryApplications are invited for a British Heart Foundation-funded position of Post-Doctoral Research Associate to investigate the complex process of systemic metabolic adaptation during the initiation and development of pulmonary hypertension (PH). You will join the Hypoxia and Inflammation research group, led by Dr Andrew Cowburn in the National Heart and Lung Institute (NHLI). Dr Cowburn works with a team of basic and clinician scientists challenging our understanding of oxygen sensing in the pathophysiology of inflammation and disease.
The research brings together the major disciplines of metabolomics, hypoxia signalling and cardiopulmonary biology, and follows the seminal discovery by Group Cowburn that HIF2a signalling forms a key component in the development of pulmonary hypertension in pre-clinical models (Cowburn et al, PNAS 2016; Macias et el, ERJ 2021).This is vital to understand critical systemic metabolic reprogramming events associated with pulmonary arterial hypertension (PAH), and how these maladaptive processes in distal tissues contribute to increased patient morbidity and mortality. The combined analysis of metabolic data with tissue-specific respirometry and gene expression profiles will determine whether cardiopulmonary and systemic tissues follow comparable metabolic dysregulation and identify the tissue origin of metabolic dysfunction during PH development. This detailed longitudinal analysis of metabolic homeostasis throughout the progression of PH will help to identify novel biomarkers/pathways related to disease development and thus identify novel therapeutic opportunities targeting metabolic dysfunction; thus the project has significant translational potential.
We will use two pre-clinical models (Sugen5416/hypoxia and monocrotaline) to longitudinally follow metabolic adaptation process from the point of disease initiation through to end-stage right ventricle maladaptation. We will use a drug intervention strategy to question the role of HIFa signalling in these metabolic processes. We will determine PAH disease severity by cardiac ultrasound using the Fuji-sonics vevo3100 before analysis of whole-body metabolism using the Columbus instruments CLAMS and collection of breath samples to determine exhaled metabolites. We will collect multiple tissues at set time points throughout the PH disease cycle to identify organ specific metabolic adaptation using high resolution respirometry, RNA-seq, histology and lipidomics. These model systems combined with whole-body and breath metabolic profiles from PAH patients will allow us to validate patient metabolic status and disease severity.
These methodologies are eminently clinically translatable as non-invasive procedures to monitor: i) disease progression, ii) metabolic target engagement during clinical intervention studies or iii) response to established treatments in PAH patients.
Duties and responsibilities
You will work in a multidisciplinary collaborative team of researchers with expertise ranging from pre-clinical models and PH patient clinical service to bioinformatics and metabolism. The environment is ideal for a candidate who is keen to work in a team, learn new techniques and bring new exciting ideas that span multiple approaches and disciplines.
You will be responsible for generating and monitoring the rat PAH pre-clinical models. Both monocrotaline and Sugen5416/hypoxia models will be used during these investigations. You will determine PAH disease severity by cardiac ultrasound using the Fuji-sonics vevo3100 before analysis of whole-body metabolism using the Columbus instruments CLAMS and collection of breath samples to determine exhaled metabolites. You will collect multiple tissues at set time points throughout the PAH disease cycle to identify organ specific metabolic adaptation using high resolution respirometry, RNA-seq, histology and lipidomics.
You will collaborate with the Hammersmith Hospital PH clinical team to collect patient metabolic data and with bioinformaticians to analysis and integrate data from both in vivo model systems and PAH patients.
The environment is ideal for a candidate who is keen to work in a team, develop pre-clinical model skills and bring new ideas spanning multiple disciplines.
Essential requirements
- You should have (or be about to obtain) a PhD in a relevant biological discipline. A strong background in metabolomics, in vivo model systems and hypoxia signalling is essential.
- Previous experience in metabolite analysis and RNASeq, including data analysis and validation is essential. Familiarity with basic molecular biology and protein biochemistry techniques is essential.
- The post will require collaboration with groups within and outside the department and outside the College. Enthusiasm, drive, and a passion for science are essential.
Further information
This role is a Full-time and Fixed term contract for 36 months based at Hammersmith Campus (East Acton).
Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £40,694 - £43,888 per annum.
You will be part of Dr Cowburn’s group, in the Vascular Science section, which includes >10 research groups interested in cardiopulmonary diseases and vascular biology. (https://www.imperial.ac.uk/nhli/research/research-sections/vascular-science/). The Section is part of the NHLI at Imperial College London, with over 300 scientists leading basic and translational research in the cardiovascular and pulmonary areas. The wider Imperial College environment offers opportunities for collaborations with bioengineers and chemists. The Imperial Vascular Network (https://www.imperial.ac.uk/vascular-science-network) captures interdisciplinary vascular research across the College and facilitates networking and collaboration.
Candidates need to complete an online application.
Should you require any further details on the role please contact Dr Andrew Cowburn: a.cowburn@imperial.ac.uk
For technical issues when applying online please emailrecruitment@imperial.ac.uk
Documents
- Job Description - Research Associate.pdf
