Biophysical determinants of cell fate decisions in skin inflammatory diseases

PROJECT OVERVIEW

Epithelial tissues, such as the skin epidermis, provide an impermeable protective barrier against external insults. To ensure its maintenance, specialised cells located in its basal layer, known as stem cells, divide and differentiate to replace cells lost through exhaustion and damage. However, the mechanisms that control stem cell renewal and the pathways that lead to their dysregulation in disease remain controversial.

Through advances in genetic lineage tracing, statistical modelling approaches have begun to reveal the functional identity and fate behaviour of stem cells in cycling epithelial tissues. These studies have highlighted the role of stochastic renewal programmes, in which stem cells are not individually long-lived, but are constantly lost and replaced by neighbouring cells [1]. Nevertheless, the mechanisms governing cell fate decisions remain poorly understood. While some recent studies have emphasized the role of tissue mechanical properties in 'priming' epithelial stem cells for renewal or differentiation [2], other work on inflammatory diseases such as psoriasis or atopic dermatitis, where the balance between profliferation and differentiation is typically altered, has highlighted the role of 'niche' signals derived from immune [3] and neuro-glial cells [4] in modulating stem cell self-renewal potential and controlling tissue dynamics.

In this project, you will use the latest image-based spatial transcriptomics (10x Genomics Xenium, Bruker CosMx) and proteomics (Akoya Phenocycler, Leica Cell DIVE) platforms to characterise the tissue / ECM architecture, gene expression patterns, and cellular composition of skin at subcellular resolution. You will use tissue biopsies from patients with psoriasis or atopic dermatitis, as well as from mouse models of these conditions. You will also use a pioneering methodology, recently developed by the Hallou Lab (Kennedy Institute, University of Oxford) [5], to simultaneously profile the mechanical properties of the tissue at cellular resolution using atomic force microscopy (AFM) and image-based force inference. This will allow you to characterise the mechanical, biochemical and cellular niches of epidermal stem cells for the first time, and to investigate how their composition, mechanical properties and spatial organisation might be altered in inflammatory skin diseases.

Working alongside computational colleagues, you will use machine learning and advanced bioinformatics tools to contribute to the development of new spatial mechano-omics analysis modules, exploring the unique multimodal dataset that you will have generated in the lab. You will also have the opportunity to design and contribute to follow-up experiments and hypothesis testing using mouse models or epithelial organoids co-cultured with immune and/or neuro-gliall  cells. These experiments will be combined with advanced live imaging, genetic lineage tracing and functional genomics approaches, such as CRISPR-based gene editing.

Ultimately, the results of this research will transform our understanding of the biological and physical mechanisms that regulate that regulate stem cell self-renewal and differentiation in the skin epidermis and provide a rational basis for the development of more effective therapeutics that target the causes rather than the symptoms of psoriasis and atopic dermatitis.

KEYWORDS

Skin, inflammation, single cell and spatial genomics, mechanobiology.  

TRAINING OPPORTUNITIES

The project is supported by a supervisory team with complementary computational and experimental expertise. The Hallou lab, based at the Kennedy Institute in Oxford, combines wet and dry laboratory approaches to study the role of mechano-chemical interactions in cell fate decisions and tissue dynamics, and has expertise in the use of biophysical, machine learning and single cell/spatial omics methods applied to a variety of biological systems.  Also at the Kennedy, the Sansom lab is using genomic approaches to study immune mediated diseases and are expert with the use of data science approaches for the analysis and integration of single-cell and spatial transcriptomics data.

In addtion of the supervisory team, this project will be supported by a strong network of  collaborations, with the group of Professor Graham Ogg which has world-leading expertise with the experimental and clinical investigation of inflammatory diseases in skin, and the group of Dr Callioppe Dendrou who has expertise in computational analysis of single cell and spatial genomics data sets in immune-mediated and infectious diseases.

The ideal applicant will already have significant experience in the fields of human skin biology and skin inflammatory diseases, including patient tissue harvest and processing, and organoid/skin explant models, as well as experience in conducting single-cell and/or spatial transcriptomics experiments, alongside relevant data analysis, and coding experience in R and/or Python. Throughout this project, you will further develop your experimental research skills and become an expert in using ML /AI approaches to integrate and analyse spatial omics and mechanical data you will have generated in the lab.

You will be supervised on a day-to-day basis by Dr Hallou and there will be regular joint meetings with Dr Sansom and other collaborators. You will be expected to present your work regularly at the weekly Hallou group meetings and will have the opportunity to attend regular seminars within the Institute and relevant seminars at the wider University. You will also have the opportunity to present your research at  international meetings and conferences.

A core curriculum of lectures will be taken in the first term to provide a solid foundation in a broad range of subjects including tissue biology, inflammation, epigenetics, translational immunology, data analysis and single cell genomics. You will also have access to various courses run by the Medical Sciences Division Skills Training Team and other departments, and, like all students of the program, you will be required to attend a 2-day Statistical and Experimental Design course at NDORMS.

KEY PUBLICATIONS

[1] A.M. Klein and B.D. Simons. Universal patterns of stem cell fate in cycling adult tissues. Development 138, 3103(2011).

[2] J. McGinn, A. Hallou, S. Han, et al., B.D. Simons and M.P. Alcolea. A biomechanical switch regulates the transition towards homeostasis in oesophageal epithelium. Nature Cell Biology 23(5), 511-525 (2021).

[3] S. Park et al., V. Greco. Skin-resident immune cells actively coordinate their distribution with epidermal cells during homeostasis. Nature Cell Biology 23, 476–484 (2021).

[4] S. Huang et al., P. Rompolas. Lgr6 marks epidermal stem cells with a nerve-dependent role in wound re-epithelialization. Cell stem cell, 28(9), 1582–1596.e6. (2021)

[5] A. Hallou, et al. A computational pipeline for spatial mechano-transcriptomics. Nature Methods 22, 737–750 (2025). 

THEMES

Skin biology, inflammation, spatial and single cell genomics, mechanobiology.

CONTACT INFORMATION OF ALL SUPERVISORS

Please contact Dr. Adrien Hallou (adrien.hallou@kennedy.ox.ac.uk) or Dr Steve Sansom (stephen.sansom@kennedy.ox.ac.uk).

This project and studentship funding is linked to Reuben College.

We welcome applicants with home or overseas fee status.