Eleni Papachristoforou

Thesis title: Defining Therapeutic Targets for Human Liver Fibrosis using Single -Cell Transcriptomics

Background

I am an MRC DTP Precision Medicine PhD Student at the Centre for Inflammation Research, at the University of Edinburgh. My research focuses on the heterogeneity and single-cell transcriptomics of macrophage in the disease, liver fibrosis.

I have also completed my undergraduate and postgraduate studies in Medical Sciences and Bioinformatics respectively.  During my studies, I was involved with research regarding acute liver disease by analysing the effect of therapeutic administration of Interleukin-4 (IL-4)  in hepatocyte proliferation with Dr SteveJenkins. Similarly, I was engaged with research in regenerative medicine by investigating the transcriptomic and epigenetic changes of reprogrammed mouse embryonic fibroblasts (MEFs) to induced pluripotent stem cells (iPSCs) and totipotent stem cells (iTSCs)  via the induction of several combinations of transcription factors (TFs) while working along with Dr Abdenour Soufi.

Qualifications

2013-2017: BSc (Hons) Medical Sciences |The University of Edinburgh

2018-2019: MSc Bioinformatics |The University of Edinburgh

 

Postgraduate teaching

Lab Demonstrating and Marking 

1. Next Generation Genomics, [SEM2], 2020-2021

2. Biotechnology 2, [SEM2], 2020-2021

3. Bioinformatics Programming and Systems Management, [SEM1], 2020-2021

 

Research summary

The purpose of my research is to uncover any unknown heterogeneity of macrophages in both human and mouse liver disease. This would further assist to map corollary populations and ‘core’ fibrogenic pathways across species. Once those populations and pathway are defined, their functional relevance will be studied via ant-ifibrotic interventional studies in mouse both in vitro and in vivo. My ultimate research goal is to define tractable therapeutic targets for human liver fibrosis.

Current research interests

Liver Fibrosis, Macrophage Heterogeneity, Single Cell Genomics, Big Data, Neural Networks, Unsupervised learning

Past research interests

Transcriptomic and Epigenomic Data Analysis, Regenerative Medicine

Project activity

PhD Title:  'Defining therapeutic targets for human liver fibrosis using single-cell transcriptomics'. 

My currently work involves the analysis of single-cell transcriptomic data to define therapeutic targets for human liver fibrosis. Liver macrophages are key regulators of fibrosis and represent an attractive therapeutic target. However, macrophages are multifunctional and heterogeneous, meaning the accurate definition of the pathogenic subpopulations is needed to enable specific targeting. Macrophages in rodent models of liver fibrosis mirror several the features of those identified in human liver disease. The precise corollary subpopulations between rodent models and human liver disease have not yet been defined. Recent studies using single-cell RNA-sequencing (scRNAseq) have defined the pathogenic macrophages in human liver fibrosis. Therefore, to define and test strategies to modulate these macrophages in vivo, in this study we aim to identify corollary macrophages in a relevant preclinical liver fibrosis model. By generating data from murine models of liver fibrosis (i.e. carbon tetrachloride, bile duct ligation, dietary models), comprising simultaneous scRNA-seq, 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. This will facilitate the identification of corollary populations and “core” pathways regulating liver fibrosis across species and define tractable therapeutic targets for liver fibrosis.

Current project grants

Medical Research Council (MRC) PhD Studentship (Precision Medicine), awarded 2019 until 2024
Medical Research Council (MRC) Flexible Supplement Funds, awarded 2020
Medical Research Council (MRC) Flexible Supplement Funds, awarded 2021

Conference details

Conference Prizes

1. BSI Congress, Liverpool, December 2022 - Poster Presentation Prize 

2. 'Mononuclear phagocytes in health and disease' BSI London Immunology Group Meeting, October 2022, Poster Presentation First Prize 

3. Next Generation Genomics Symposium, University of Edinburgh, March 2022 - Presentation First Prize 

 

Participant

  1. British Society for Immunology (BSI) Congress, Liverpool, December 2022,  Poster Presentation Title: 'Single-cell transcriptomics defines pathogenic macrophages in murine liver fibrosis'
  2. Single Cell Genomics, Utrecht, October 2022, Poster Presentation Title: 'Single-cell Multiomics Defines Pathogenic Macrophages in Murine Liver Fibrosis'
  3. 'Mononuclear phagocytes in health and disease' BSI London Immunology Group Meeting, London, October 2022, Poster Presentation Title: 'Single-cell transcriptomics defines pathogenic macrophages in murine liver fibrosis'
  4. Single Cell Biology conference (Hybrid), June 2022
  5. The Next Generation Sequencing Symposium, Edinburgh, May 2022, Presentation Title: 'Single-cell transcriptomics defines pathogenic macrophages in murine liver fibrosis'
  6. British Society for Immunology (BSI) Congress, Edinburgh, November 2021
  7. Single Cell Biology conference (Virtual edition), November 2020
  8. Emerging Technologies in Single Cell Research (Virtual edition), November 2020
  9. Dealing with Data 2019: Collaboration Across the Nations: Managing, sharing, and securing research data across space and time, Informatics Forum University of Edinburgh, January 2020
  10. A Cell for all Seasons: Macrophages in Health and Disease- 5th Annual Symposium, QMRI University of Edinburgh, October 2019

University of Edinburgh Training:

1. CMVM Light Microscopy Course (Jun 2021)

2. Introductory Applied Machine Learning  (2019-2020) [SEM1]

3. Introductory Probability and Statistics (2019-2020) [SEM1]

4. Biomedical Data Science (2019-2020) [SEM2]

5. Innovation-driven Entrepreneurship (2019-2020) [SEM2]

6. One Day Flow Cytometry Course: SSC in association with 'The Francis Crick Institute, QMRI, February 2020

External Training:

1. SysMIC: Online Course in Coding, Modelling & Data Analysis for Bioscience Researchers-Module 1 (Oct 2020-Jul 2021)

2. Bioinformatics training course: Analysis of single-cell RNA-seq data, University of Cambridge Training  (Dec 2019)

3. DATAETHICS Summer School, one-week (35hours) course: 'Big Data, Big Implications: Data Protection in Biomedicine', University of Barcelona (July 2022)

1. Macrophages as key regulators of liver health and disease

2022 | Book chapter

DOI: 10.1016/bs.ircmb.2022.04.006

CONTRIBUTORS: Eleni Papachristoforou; Prakash Ramachandran

 

2. CRIg on liver macrophages clears pathobionts and protects against alcoholic liver disease

Nature Communications

2021-12-09 | Journal article

DOI: 10.1038/s41467-021-27385-3

Part of ISSN: 2041-1723