MRC Precision Medicine DTP: Defining Therapeutic Targets for Human Liver Fibrosis using Single-cell Transcriptomics

Background
Chronic liver disease is estimated to affect 844 million people worldwide, with over 2 million deaths per year. Liver fibrosis (or scarring) is a feature of advanced chronic liver disease of any aetiology and predicts adverse patient outcomes. Despite this significant burden of disease, there are currently no effective antifibrotic treatments available for patients with liver disease. This is in part due to the lack of a precision medicine-based approach, with a dearth of comparative data exploring the links between human disease and pre-clinical models. Hence, potential antifibrotic interventions have not been adequately targeted to pathways known to be active in fibrotic human liver tissue.
Macrophages are key regulators of liver fibrosis and represent an attractive therapeutic target[1]. Recently, we have used a single-cell RNA-seq approach, to define the pathogenic macrophage population in human liver cirrhosis for the first time (Ramachandran et al., under review at Nature). We proceeded to define molecular interactions between these macrophages and other key cell types within the fibrotic niche. These data provide a unique opportunity, enabling the rational testing of antifibrotic therapies on pathways known to be present in human liver disease.

Macrophages in rodent models of liver fibrosis mirror a number of the features of those identified in human liver disease. However, macrophages are highly heterogeneous and dynamic cells, meaning the precise corollary subpopulations between rodent models and human liver disease have not yet been defined. By generating data from murine models of liver fibrosis, comprising simultaneous single-cell RNA-seq (scRNA-seq) and multiplex protein marker detection (using CITE-seq[2]), we will resolve fibrogenic macrophage subpopulations. We will proceed to map the transcriptomes of these cells to those identified in human cirrhotic liver tissue using cutting edge computational approaches[3]. This will facilitate the identification of “core” pathways regulating liver fibrosis across species and define tractable therapeutic targets for liver fibrosis.

Aims
1) Dissect human and mouse liver macrophage heterogeneity and activation states using scRNA-seq and CITE-seq approaches. Computational methodologies will include unsupervised clustering, transcriptomic network analysis, pseudotemporal dynamics and RNA velocity analyses[4].
2) Integrate murine and human liver scRNA-seq data. This will facilitate the identification of corollary populations and “core” fibrogenic pathways[3].
3) Therapeutic targeting of selected fibrogenic pathways in murine models of liver fibrosis.

Training outcomes
1) Training in cutting-edge computational and statistical tools to allow the analysis and interpretation of single cell transcriptomic data, mapping across species and identifying conserved pathways.
2) Performing and analysing murine models of liver fibrosis: carbon tetrachloride, bile duct ligation, dietary models.
3) Phenotyping and spatially resolving macrophage subpopulations from murine models of liver fibrosis: multiparameter flow cytometry, histology, imaging and ex vivo cell culture analyses.
4) Designing, analysing and interpreting antifibrotic interventional studies in mouse models.
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This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.

All applications should be made via the University of Edinburgh, irrespective of project location:

http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=919

Please note, you must apply to one of the projects and you should contact the primary supervisor prior to making your application. Additional information on the application process if available from the link above.

For more information about Precision Medicine visit:

http://www.ed.ac.uk/usher/precision-medicine