Investigating the spatial organisation of pathogenic cell niches in chronic inflammatory diseases

PROJECT OVERVIEW

Are you interested in understanding how the spatial arrangement of cells shapes tissue inflammation? The immune system functions within highly organised tissue environments, where interactions between immune, stromal and structural cells are essential for maintaining health. Increasing evidence suggests that disruption of healthy cellular neighbourhoods and development of aberrant, pathogenic cell niches is a common feature of chronic inflammatory diseases, but the mechanisms governing their organisation and function remain poorly understood.

Recent breakthroughs in spatial transcriptomics have enabled the direct and unbiased study of the cells, genes and signalling pathways in intact tissue. The ability to precisely map the spatial relationships between cells promises to unlock our understanding of how cell-cell interactions contribute to disease. In this primarily computational project, you will apply and develop bioinformatic pipelines and methods for spatial omics data analysis, using them to co-lead investigations of the cellular basis of inflammatory bowel disease (IBD) and atherosclerosis. These chronic immune-mediated diseases affect distinct organs but share common pathological features, including persistent inflammation, tissue remodelling and complex interactions between immune and resident cells.

IBD is a heterogeneous condition, and although effective therapies exist, finding the right drug for each patient is currently a slow and expensive trial-and-error process. To address this, we are working to identify tissue pathotypes in IBD and to link these with therapy outcomes1. In this project, spatial multiomics approaches will be used to help define the aberrant cell niches and interactions associated with different tissue pathotypes. Atherosclerosis involves the progressive build-up of lipid-rich plaques within arterial walls and is a major underlying cause of heart attacks and strokes. These plaques are dynamic, immunologically active lesions in which poorly understood interactions between immune and stromal cells take place in a highly spatially organised microenvironment2. Work in this project will contribute to construction of a precise cellular map of this pathogenic niche to help identify mechanisms driving plaque progression and instability.

In this interdisciplinary project, you will use cutting-edge spatial transcriptomics platforms, including Bruker CosMx and 10x Xenium, together with advanced computational approaches to study human tissues from patients with IBD and atherosclerosis. These data will be integrated with clinical information and complementary single-cell datasets to map cellular niches and determine how these differ between patients and disease subtypes. The resulting findings are expected to help underpin the stratification of inflammatory disease by cellular mechanism and hence to inform drug selection on a case-by-case basis.

For this DPhil you will join a multidisciplinary team of computational biologists, immunologists and clinician scientists. The project offers opportunities to work closely with experimental collaborators to validate computational findings using complementary approaches, including advanced tissue imaging, functional genomics and experimental models where appropriate. Training in computational biology, spatial omics and systems immunology will be provided, with the opportunity to develop skills across the full pipeline from tissue to biological insight in an internationally recognised research environment.

KEYWORDS

Spatial transcriptomics

Bioinformatics

Computational biology

Atherosclerosis

IBD

TRAINING OPPORTUNITIES

The project is supported by a strong supervisory team at the University of Oxford that has complementary computational, experimental and clinical expertise.

Based at the Kennedy Institute, the Sansom lab has state of the art single-cell and spatial transcriptomic platforms and is highly experienced with the use of computational genomics and data science approaches for the study of inflammatory diseases.1,2,3,4

The Friedrich group is expert with the use of AI and spatial transcriptomics for the study of IBD1.

The Monaco lab has world-leading expertise with the experimental and cellular investigation of atherosclerosis.2

The Hallou lab are developing novel interdisciplinary approaches for machine learning-based analysis of spatial transcriptomics and mechanical force data.5

You will work closely with researchers across the labs of the supervisory team to gain the skills needed to undertake your studies.

Whilst undertaking this DPhil, you will develop strong data science skills, learning how to program and to perform statistical data analysis and visualisation with Python and R. You will become expert with the use of machine learning approaches to analyse spatial transcriptomics data. Working closely with clinical colleagues, you will gain an expert understanding of chronic inflammatory disease. You will develop a close understanding of experimental research, including the generation of single-cell and spatial genomics data, through regular attendance of wet-lab group meetings.

A core curriculum of lectures will be taken in the first term to provide a solid foundation in a broad range of subjects including musculoskeletal biology, inflammation, epigenetics, translational immunology, data analysis and the microbiome. Students will attend regular seminars within the department and those relevant in the wider University. Students will be expected to present data regularly in the departmental PGR seminars, Sansom and Monaco group meetings. You will have the opportunity to present your research in local, national and international meetings and conferences.

Students will have access to various courses run by the Medical Sciences Division Skills Training Team and other departments. All students are required to attend a two-day Statistical and Experimental Design course at NDORMS.

KEY PUBLICATIONS

1. Friedrich et al. IL-1-driven stromal-neutrophil interactions define a subset of patients with inflammatory bowel disease that does not respond to therapies. Nature Medicine 2021 (https://doi.org/10.1038/s41591-021-01520-5).

2. Dib L et al. Lipid-associated macrophages transition to an inflammatory state in human atherosclerosis, increasing the risk of cerebrovascular complications. Nature Cardiovascular Research 2023 (https://doi.org/10.1038/s44161-023-00295-x).

3. Croft AP et al. Distinct fibroblast subsets drive inflammation and damage in arthritis. Nature 2019. (https://doi.org/10.1038/s41586-019-1263-7).

4. Cross AR et al. Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury. JCI Insight 2023 (https://doi.org/10.1172/jci.insight.157837).

5. Hallou A, et al. A computational pipeline for spatial mechano-transcriptomics. Nature Methods 2025 (https://doi.org/10.1038/s41592-025-02618-1).

THEMES

Immunology

Immune mediated inflammatory disease

Systems Biology

Translational Medicine

CONTACT INFORMATION OF ALL SUPERVISORS

Stephen Sansom

Claudia Monaco

Matthias Friedrich

Adrien Hallou