We are interested in the molecular mechanisms that control cell-to-cell heterogeneity. Work in our group focuses on yeast and mammalian cells. Our group exploits a range of techniques in single-cell (RNA-FISH and DNA-FISH) to understand more about when genes are expressed and how the relative position of the DNA changes. We complement our experimental data with mathematical modelling, in this case using histograms of single RNA distributions in the nucleus and cytoplasm of cells to derive the underlying principles of transcription by comparing WT and mutant strains. More recently we have used the idea of modelling shapes of signal distributions to nascent transcription to extend our experimental observations on the effect of transcription on gene expression, particularly the fate of transcripts (e.g. stability, subcellular localization). We have a wide range of high-resolution next-generation-sequencing (NGS)-based approaches in the lab including HiC, Capture-C, TT-seq, SNU-seq, NET-seq, TEF-seq, ChIP-mentation, RNA-seq, ATAC-seq, ChIP-seq, ribosome profiling, polysome profiling, complemented by proteomics and metabolomics which enable us to relate variations in gene expression to protein levels and changes in key metabolic intermediates such as Acetyl-CoA and NAD that influence PTMs on chromatin-associated proteins. Using these approaches, we are beginning to understand how the variation in single cells in populations arises. One system we have extensive data on is the yeast metabolic cycle, a system in which cells growing in a constant environment in a chemostat become synchronized and show cycling gene expression and metabolism, similar to other biological rhythms.

Transcription, gene expression, chromatin and genome architecture, metabolism, single-cell biology, mammalian cell lines

Saccharomyces cerevisiae (budding yeast)