A google maps for biology: single cell genetic characterization goes spatial

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• Dario Bressan, University of Cambridge
• Thursday 01 February 2018, 13:10-14:00
• The Richard King Room, Darwin College.

If you have a question about this talk, please contact Lorena Escudero.

Location matters in biology. Both the inner workings of tissues and organs and their dysregulation, which leads to disease, depend on the tight web of relationships between different cell populations, and on the concerted regulation of their function mediated by genetic and environmental effects. In the last 10 years and more, it has become clear that many biological phenomena cannot be studied by analyzing cells in bulk and outside of their natural environment, but their underlying mechanisms can only be mechanistically investigated if observed both at the single-cell level and in situ. While technologies allowing either the former or the latter of these features are now available, combining both is extremely challenging, at least with the throughput necessary to obtain reliable results.
In our laboratory, we have recently launched a project, named IMAXT (Imaging and Molecular Annotation of Xenografts and Tumours), that aims to produce a comprehensive tri-dimensional map of breast tumours in which each cell is annotated by measuring the expression of hundreds of different genes and proteins. We are doing this by combining several microscope-based techniques with automated image analysis and mass spectrometry. The results are used to build an integrated computer model of the tumour, which can be explored using a natural interface in a virtual reality environment, literally “immersing oneself” into the tissue and observing its features. While the project is still in its early phases, early results on tumour samples are showing how powerful this method could be not only for cancer biology, but for many other fields as well, such as developmental biology.

This talk is part of the Darwin College Science Seminars series.

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• AUB_Cambridge Seminars
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• Neurons, Fake News, DNA and your iPhone: The Mathematics of Information
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