Antanaviciute Group - Characterising spatial tissue niches in human immune system development and disease using computational biology, machine learning and multi-omics approaches

ABOUT THE RESEARCH

Our research group interests lie at the intersection of computational biology and human immunology, in particular in the applications of ‘omics, single cell and spatial technologies for the better understanding of tissue microenvironment, local tissue dynamics and cellular interactions, how they are established during development, and the molecular perturbations and tissue remodelling that occurs in disease states, in particular in autoimmune and autoinflammatory conditions. In order to address these types of questions, our group focuses on inter-disciplinary expertise in both biology and computational biology to both to extract relevant biological insights from complex datasets and to develop domain-tailored machine learning models and novel computational methods for high-dimensional sequencing data analysis.

In recent years, the development of cutting-edge multi-modal single cell technologies have enabled diverse molecular read-outs of gene and protein expression, epigenetic states, T-cell and B-cell receptor sequences or even antigen specificity of thousands of individual cells at a time. These approaches generate vast amounts of high-dimensional sequencing data that require the application of advanced computational biology approaches and machine learning techniques. More recently, the emergence of spatial transcriptomics technologies has added further complexity to these datasets with the addition of spatial dimensionality and imaging data. While potentially incredibly powerful, due to the nascency of these experimental approaches, many challenges in computational data analysis are largely unaddressed and finding patterns in spatial gene expression remains one of the biggest challenges in single cell ‘omics today. Understanding the mechanisms by which gene activity in individual cells guides complex cellular spatial arrangements in tissues has far-reaching implications in human biomedical research. Cellular organisation in tissues is ultimately linked to specific biological functions – cancer, infectious and inflammatory disease processes often lead to drastic spatial tissue remodelling and cellular re-arrangements. 

Various research opportunities are currently available within the group, broadly focusing either on: a) Computational method and model development in the area of spatial transcriptomics and integrative approaches with single cell multi-omics data; or b) applying multi-omics and spatial technologies to explore human intestinal immune system development and early childhood diseases at single cell resolution. 

More specifically, these include: 

Topological modelling of spatial cellular signalling networks during human immune system development - In tissues, cells engage in complex cross-talk via secreted and cell surface molecules that coordinates their fate and behaviour from early developmental to mature tissue and pathological tissue remodelling in disease conditions. The emergence of single cell ‘omics technologies has contributed greatly to unravelling cellular interactions in a variety of biological contexts; however, extending these approaches to spatially resolved data remains challenging. This project will aim to first to reconstruct 3D tissue architecture using consecutive-cut spatial transcriptomics sections from cutting edge MERFISH technologies and focus on developing methodology to reconstruct 3D spatial cellular signalling networks and analyse network topology and patterns. This method will be applied to better characterise early paediatric human gut development and quantify spatial morphogen gradients that are established during this time, with a focus on immune cell colonisation of the colon. 

Interplay between molecular, cellular and epigenetic determinants of early gut immune system colonisation, immune maturation and gut aging- Small intestine is colonised by immune cells and forms lymphoid associated tissue in utero but the colonic immune system, the primary site of microbial symbiosis, is less developed at birth. This project aims to better our understanding of how human gut immune system develops and establishes the delicate balance between immunity towards pathogens and tolerance towards commensals in the early neonatal developmental period, priming the immune system of the infant for healthy life-long immunity.  Disruption of this process can lead to debilitating childhood diseases, such as necrotising enterocolitis, an inflammatory intestinal disease that one of the leading causes of morbidity in pre-term neonates.  This project will utilise data from single cell multi-omics technologies, bringing together epigenetic and transcriptomics read-outs from the same cells and applying advanced data analysis methods. Students interested in both fully computational or half-dry half-wet lab project are encouraged to reach out. 

Machine learning for predicting disease-associated features using spatial transcriptomics-Spatially resolved ‘omics often generates paired image data, which is often underutilized but can be used to extract high-resolution information. This project will focus on developing machine learning models for prediction of transcriptomics derived features from histology image data. This will enable quantifying spatial tissue niches across large numbers of tissue sections in order to assess structural, cellular and co-localisation changes, with the aim of applying this to in-house transcriptomics and image data of inflammatory bowel disease samples and generate insights into disease pathology.

Each project will enable the student to work in collaboration with world-leading immunologists within the MRC Human Immunology Unit at the WIMM. Interested candidates are encouraged to reach out for an informal discussion (agne.antanaviciute@ndm.ox.ac.uk).

Additional supervision will be provided by Professor Alison Simmons and Professor Hashem Koohy.

TRAINING OPPORTUNITIES

Our projects and work are mostly multidisciplinary, and usually lie at the intersection of data science (machine-learning and statical inference) and immunology and developmental biology and therefore motivated students from both computer science and biology backgrounds are encouraged to apply. In addition to computational-based projects, there are further opportunities for half-wet half-dry lab inter-disciplinary projects. 

Each project is supervised by a minimum of two supervisor (one from each discipline) to ensure proper training and supervision. Students will additionally have access to a wide variety of training and courses within Oxford University teaching and training schemes.  Specifically within the group, the successful applicant will have access to training in the following dry lab techniques: spatial ‘omics and imaging data analysis, NGS data analysis, single cell multi-omics data analysis, including scRNA-Seq, CITE-Seq, scATAC-Seq, TCR/BCR repertoire analysis, statistical inference and machine learning. 

Students will be enrolled on the MRC Weatherall Institute of Molecular Medicine DPhil Course, which takes place in the autumn of their first year. Running over several days, this course helps students to develop basic research and presentation skills, as well as introducing them to a wide range of scientific techniques and principles, ensuring that students have the opportunity to build a broad-based understanding of differing research methodologies.

Generic skills training is offered through the Medical Sciences Division's Skills Training Programme. This programme offers a comprehensive range of courses covering many important areas of researcher development: knowledge and intellectual abilities, personal effectiveness, research governance and organisation, and engagement, influence, and impact. Students are actively encouraged to take advantage of the training opportunities available to them.

As well as the specific training detailed above, students will have access to a wide range of seminars and training opportunities through the many research institutes and centres based in Oxford.

The Department has a successful mentoring scheme, open to graduate students, which provides an additional possible channel for personal and professional development outside the regular supervisory framework. We hold an Athena SWAN Silver Award in recognition of our efforts to build a happy and rewarding environment where all staff and students are supported to achieve their full potential.

PUBLICATIONS