University of Cambridge > > Evolution and Development Seminar Series > Studying stem cells and differentiation in regenerating animals using single cell transcriptomics

Studying stem cells and differentiation in regenerating animals using single cell transcriptomics

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Humans and mammals in general have extremely limited regeneration capacities, and so do most well-established lab models. However, animals such as planarians, annelids and amphibians have amazing regenerative powers. These differences can be explained by the stem cells that exist in the adult bodies, but these are largely uncharacterised across the tree of life. Among regenerative animals, the planarian Schmidtea mediterranea is a convenient lab model that regenerates any body part in a matter of days. A pluripotent stem cell population – the so-called neoblasts – underlies the process. To study regeneration in planarians and other animals we are using novel methods of single cell analysis. We have developed ACME (ACetic-MEthanol) dissociation. ACME fixes the cells while they are being dissociated, preventing the stress that a trypsin live dissociation imposes on the cells and freezes the biology of the cell in the moment of capture. ACME is based on affordable reagents, can be done in most laboratories and even in the field, and thus will accelerate our knowledge of cell types across the tree of life. Using ACME , we have also optimised SPLiT-seq, one of the latest scRNA-seq approaches. SPLiT-seq is cost efficient, highly scalable and allows multiplexing several samples on one experiment, avoiding batch effects. With this approach we can obtain cell type atlases, but also investigate differences in cell type composition as well as finer differences in gene expression patterns. This has allowed us to characterise cell types, including stem cells, of planarians, cnidarians, annelids and ascidians. We now aim at investigating stem cells and regeneration across animal evolution.

This talk is part of the Evolution and Development Seminar Series series.

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