Evolution of Cellular Networks Group at EMBL-EBI
Our group is interested in understanding how novel cellular functions arise and diverge during evolution. What are the molecular sources of phenotypic novelties, or in other words, how genetic variability that is introduced at the level of the DNA is propagated through protein structures and interaction networks to give rise to phenotypic variability. Within the broad scope of this evolutionary problem, our team is currently focused in two related areas: 1) the function and evolution of post-translational regulatory networks; and 2) the evolution of genetic and chemical-genetic interactions. These studies are required not just to understand the evolutionary process but should also help us to understand the differences between different individuals (i.e. individual genomics) and improve our capacity to devise combinatorial therapeutic strategies.
Our group is interested in understanding how novel cellular functions arise and diverge during evolution. What are the molecular sources of phenotypic novelties, or in other words, how genetic variability that is introduced at the level of the DNA is propagated through protein structures and interaction networks to give rise to phenotypic variability. Within the broad scope of this evolutionary problem, our team is currently focused in two related areas: 1) the function and evolution of post-translational regulatory networks; and 2) the evolution of genetic and chemical-genetic interactions. These studies are required not just to understand the evolutionary process but should also help us to understand the differences between different individuals (i.e. individual genomics) and improve our capacity to devise combinatorial therapeutic strategies.
In order to study the evolutionary
dynamics and functional importance of post-translational regulatory
networks we are developing a resource of experimentally derived
post-translational modifications (PTMs) for different species in
collaboration with mass-spectrometry groups. This data is being used
to develop novel computational methods to predict PTM function and
regulatory interactions. The combination of these resources will
allow us to understand how genetic variation results in changes in
PTM interactions and function.
Changes in cellular interaction
networks underlie the variation in the cellular responses and
sensitivity to environmental perturbations or small-molecules. As we
model and study the evolution of cellular interaction networks, we
expect to gain an understanding about how different individuals or
species diverge in their response to drugs. We aim to study this
relationship and to develop methods to predict how genetic changes
result in specific sensitivity to drug combinations.
Current Projects
Function and Evolution of Post-translational networks
In collaboration with mass-spectrometry
groups we are using a growing resource of PTMs from different species
(PTMfunc.com) to study the functional relevance and evolutionary
properties of post-translational networks. Current projects in this
area include: the study and prediction of enzyme specificity and PTM
interaction networks; using information on conditional changes of PTM
abundance to study signalling specificity and functional
co-regulation of PTMs; development of novel methods to prioritize
functionally relevant PTMs within large-scale datasets. (related publication 1 and 2)
 |
| Predicting regulatory regions within the HSP70 domain family by measuring the conservation of PTMs. |
Evolution of chemical-genetic and genetic-interaction networks
The group is also interested in
understanding the genetic architecture of cells. How disrupting
simultaneously combinations of parts can have effects on fitness that
deviate from a neutral expectation. Studying these
genetic-interactions and how they change during evolution should
allow us also to understand how combinations of drugs can have
synergistic effects that are specific to a given species. Ongoing
efforts in this area aim to: integrate different data types such as
structural and chemical-genetic information to predict drug targets;
develop predictors for the combinatorial effects of small-molecules; (related publication).
 |
| Predicting drug interactions using comparative chemical-genetics data |
Individual genomics
With the recent improvements in
high-throughput methodologies it is becoming feasible to perform
large-scale characterization of different individuals of the same
species. Ultimately this information will allow us to better
understand how the genetic variation in a population relates to the
variations in phenotypes. In this area of research we are developing
methods to predict phenotypic variation in different strains of S.
cerevisiae from complete genome sequences making use of the
accumulated knowledge for the well characterized lab strain. We plan
also to apply these approaches to study the variation in individuals
of other species. (see post for example)
The group is at EMBL-EBI within the Wellcome trust Genome Campus in Cambridge, UK