Meet the team

If you're interested in joining the LMS
We use spatial single-cell genomics (Slide-tags) to capture DNA mutations, epigenetic states, and gene expression in single nuclei, together with their precise spatial coordinates within intact tissue. Barcoded nuclei are compatible with virtually any established single-cell sequencing workflow, making the platform broadly applicable. We also incorporate fluorescent and histological imaging of tissues to enrich datasets for computational modelling, diagnostic development, and cross-modal integration.
Traditional toxicology studies are costly, slow, and test compounds individually, yet real-world exposures involve complex mixtures. We are developing high-throughput in vitro and in vivo screening platforms designed to enable dose- and time-resolved single-cell multiomic readouts across thousands of exposures simultaneously.
Individual cells accumulate somatic mutations as tissues age, yet how these vary across cell types, spatial locations, and microenvironments remains poorly understood. We use spatial single-cell DNA and RNA sequencing to construct cell-type-resolved mutational atlases of normal ageing tissues, establishing the baseline landscape against which exposure-driven changes can be detected and understood. Using somatic mutations as natural barcodes, we can also reconstruct clonal lineage histories of human tissues with unprecedented spatial and temporal resolution.
The multimodal datasets generated by our experimental platforms - spanning the genome, epigenome, transcriptome, and spatial context - require new computational approaches to interpret. We are developing frameworks to integrate these data modalities, model exposure-driven tissue evolution, and identify vulnerable cell states. A key goal is building predictive models trained on characterised exposures that generalise to unseen chemicals, enabling in silico risk assessment at scale.

Tissue Biology research

Every day we encounter thousands of chemicals in the air, food, and products we use. Some can damage our health by altering how our cells behave, contributing to cancer, fertility problems, and other diseases. But for most chemicals, we don’t yet know exactly how or why this happens inside the body. Our group develops technologies to read the molecular state of individual cells within their precise location in tissue, building detailed maps of how chemical exposures alter us from the inside out. Ultimately, we want to identify which chemicals are harmful and why, in order to help remove and replace them before they cause widespread disease.

We develop and apply spatial single-cell multiomic technologies to characterise the cellular mechanisms by which environmental exposures (e.g. carcinogens, endocrine disruptors, and PFAS) perturb tissue homeostasis. Using Slide-tags, a spatial barcoding platform, we simultaneously profile somatic mutations, epigenetic state, and the transcriptome in single nuclei at spatial resolution in tissues with diverse exposure profiles and distinct disease outcomes (e.g. liver and reproductive tissues). We complement this with high-throughput in vitro screening platforms using oligonucleotide-barcoded exposures, and are exploring organoid models as a scalable alternative to in vivo experiments. Computational frameworks integrate these multimodal datasets to model exposure-driven tissue evolution, identify vulnerable cell states, and predict the effects of unseen exposures. 

Environmental exposures contribute to nearly a quarter of all global deaths, yet health effects remain uncharacterised for the majority of the >350,000 chemicals in current use. By mapping the cellular consequences of specific chemical exposures at high resolution, our work will generate evidence to inform regulation and removal of harmful compounds before they cause widespread disease, including cancers, reproductive disorders, metabolic disease, and neurodevelopmental conditions. Our datasets and predictive models will support novel diagnostics identifying early cellular signatures of tissue damage. By linking chemical structure to biological effect, we also aim to inform the rational design of safer alternatives and therapeutic interventions. 
 

Our research is supported by

Selected publications

Slide-tags enables single-nucleus barcoding for multimodal spatial genomics. Russell AJC, Weir JA, Nadaf NM, Shabet M, Kumar V, Kambhampati S, Raichur R, Marrero GJ, Liu S, Balderrama KS, Vanderburg CR, Shanmugam V, Tian L, Iorgulescu JB, Yoon CH, Wu CJ, Macosko EZ, Chen F. Nature·2024·:101-109·DOI: 10.1038/s41586-023-06837-4·PubMed 

 Spatial multiomic landscape of the human placenta at molecular resolution. Ounadjela JR, Zhang K, Kobayashi-Kirschvink KJ, Jin K, J C Russell A, Lackner AI, Callahan C, Viggiani F, Dey KK, Jagadeesh K, Maxian T, Prandstetter AM, Nadaf N, Gong Q, Raichur R, Zvezdov ML, Hui M, Simpson M, Liu X, Min W, Knöfler M, Chen F, Haider S, Shu J. Nature medicine·2024·:3495-3508·DOI: 10.1038/s41591-024-03073-9·PubMed

Regulators of male and female sexual development are critical for the transmission of a malaria parasite. Russell AJC, Sanderson T, Bushell E, Talman AM, Anar B, Girling G, Hunziker M, Kent RS, Martin JS, Metcalf T, Montandon R, Pandey V, Pardo M, Roberts AB, Sayers C, Schwach F, Choudhary JS, Rayner JC, Voet T, Modrzynska KK, Waters AP, Lawniczak MKN, Billker O. Cell host & microbe·2023·:305-319.e10·DOI: 10.1016/j.chom.2022.12.011·PubMed

The Malaria Cell Atlas: Single parasite transcriptomes across the complete Plasmodium life cycle. Howick VM, Russell AJC, Andrews T, Heaton H, Reid AJ, Natarajan K, Butungi H, Metcalf T, Verzier LH, Rayner JC, Berriman M, Herren JK, Billker O, Hemberg M, Talman AM, Lawniczak MKN. Science·2019·:eaaw2619·DOI: 10.1126/science.aaw2619·PubMed