Gene expression regulation and protein complex assembly
Our group seeks to elucidate general principles of gene expression and protein complex assembly. We study protein complexes in terms of their 3D structure, structural evolution and the principles underlying protein-complex formation and organisation. We also explore the regulation of gene expression during switches in cell state, and use mouse T-helper cells as a model of cell differentiation. We combine computational and wet-lab approaches at both EMBL-EBI and the Wellcome Trust Sanger Institute
The wealth of genome-scale data now available for sequences, structures and interactions provides an unprecedented opportunity to investigate systematically principles of gene and protein interactions. We focus on the evolution and dynamics of regulatory and physical interaction networks, combining computational and mathematical approaches with genome-wide and gene/protein experiments. Our two main areas are transcription factors and the regulation of gene expression; and physical protein–protein interactions and protein complexes.
Differences in genes and their spatio-temporal expression patterns determine the physiology of an organism: its development, differentiation and behaviour. Transcription factors regulate this process by decoding DNA elements and binding to DNA in a sequence-specific manner. Our group has developed a prediction pipeline (transcriptionfactor.org) that identifies repertoires of transcription factors in genomes.
We are very interested in elucidating transcriptional regulatory networks that orchestrate T-helper-cell differentiation and plasticity. Using the T helper cell system, we explore the hierarchy and kinetics of molecular events that contribute to changes in gene expression, and whether the kinetics of these interactions graded or switch-like.
Our group also investigates the principles that govern the folding and assembly of protein complexes. Using the informative power of genomic, proteomic and structural data, we capture the critical changes in sequence and structure that distinguish protein-complex formation from the sea of functionally neutral changes. The 3DComplex.org database is a research tool for our work in this area. Our in silico, phylogeny-based methods predict critical ancestral mutations involved in changing protein complexes, and we test these using wet-lab biophysical and biochemical techniques.
- Charoensawan V, Janga SC, Bulyk ML, Babu MM, Teichmann SA. (2012) DNA sequence preferences of transcriptional activators correlate more strongly than repressors with nucleosomes. Mol. Cell, 47, 183-92.
- Perica, T., Chothia, C. and Teichmann, S.A. (2012) Evolution of oligomeric state through geometric coupling of interfaces. Proc. Natl. Acad. Sci. USA, 109, 8127-32.
- Hebenstreit, D., et al. (2011) RNA-sequencing reveals two major abundance classes of gene expression levels in metazoan cells. Mol. Sys. Biol., 7, 497.
- Teichmann, S.A. and Babu, M.M. (2004) Gene Regulatory Network Growth by Duplication. Nature Genet., 36, 492-496.
- Luscombe, N.M., et al. (2004) Genome-scale analysis of regulatory network dynamics. Nature, 431, 308-312.
- Apic, G., Gough, J. and Teichmann, S.A. (2001) Domain combinations in archaeal, eubacterial and eukaryotic proteomes. J. Mol. Biol., 310, 311-325.