The dynamics of gene regulatory networks induced by Notch activation

Lead Research Organisation: University of Cambridge
Department Name: Physiology Development and Neuroscience


Cells communicate with each other and receive information about their environments through molecular signalling pathways. One such signalling pathway involves the Notch receptor. This pathway is highly conserved, is important for many aspects of building multicellular animals and is disrupted in several human diseases, including cancers. If we are to understand how Notch is able to alter the behaviour of cells we need to understand how its activity changes the expression of genes in the cell. New technologies, such as DNA microarrays, allow us to simultaneously analyse all of the genes encoded by an animal's genome. Thus we can ask how many genes are switched on or off when a cell receives the Notch signal. By looking at different times after Notch activation we can further find out how quickly and in what order different genes are switched on. We propose investigating these questions using cells from the fruit-fly Drosophila as our model. Not only was this the animal where Notch was first discovered (a slight defect in gene activity causes a 'notch' in the fly wing), but also it has a smaller and more simple genome than mammals (for example humans have multiple Notch-like receptors whereas Drosophila has one). However, even using Drosophila, our experiments will produce a very complicated set of data and to fully analyse and understand the relationship between the genes that are turned on at different times we will need to use mathematical approaches. Indeed we propose to go beyond this and use our data to build mathematical models of the network of gene responses to Notch activation. The hope is that, as the models become more sophisticated and accurate, we will be able to predict, from first principal, the behaviour of this biological system. Thus we hope to be able to simulate in the computer what would happen if the system is defective (for example if a gene is mutant) or if it is treated with a particular drug. We will be able to verify these predictions through experiments, to see how accurate our models are, and to improve them. This approach requires that biologists and mathematicians collaborate to bring together their expertise as we propose here. Our long term goal therefore is to develop an understanding of Notch signalling by building predictive mathematical models; models that will be constructed by analysing the data we generate in this study, and that can subsequently be useful for further studies, for drug design and for application to other signalling pathways.

Technical Summary

Our goals are (1) to elucidate the temporal characteristics of the transcriptional response to Notch signalling and (2) to develop predictive models from these data that will inform our understanding of the intrinsic regulatory circuits. Characterising the regulatory circuits underpinning genomic responses to signalling and developing the computational tools necessary for the predictive modelling of these circuits requires experimentally tractable systems with well-developed genomics resources. Drosophila offers an excellent system for quantitative analysis of metazoan genomes because it is comparatively simple and has less genome complexity than vertebrate models. We therefore propose to exploit an ex vivo model in Drosophila cells for generating quantitative data on the cellular responses to Notch signalling. In our analysis of these data we will identify temporal relationships and patterns within the responding genes, which will be tested to validate these networks.
Description Signaling via the Notch pathway conveys important information that helps to shape tissues and, when misused, contributes to diseases. Cells respond to the Notch signal by changing which genes are transcribed. Most previous studies have looked at changes in gene activity at a single time point, long after the start of signaling. By looking at carefully timed intervals immediately after Notch pathway activation, we have been able to follow the dynamic changes in transcription of all the genes and have found that they exhibit different patterns of activity. Our investigations into the underlying mechanisms revealed that cross-regulatory interactions driven by the early responding HES family of genes are required to shape the timing of later responding genes. This feed-forward mechanism explains the pivotal role played by the HES genes in the Notch response, despite the fact that many other genes are regulated by the signal. These findings are valuable (i) for understanding the contribution of Hes genes in diseases associated with altered Notch (ii) as paradigm to illustrate how a signal leads to dynamic changes in transcription (iii) because they stimulated the development of new analytical methods.
Exploitation Route the conclusions will be tested in other contexts
the hypothesis will be exploited in further studies
the computational methods will be used by others studying transcriptional changes
Sectors Digital/Communication/Information Technologies (including Software),Pharmaceuticals and Medical Biotechnology

Description Project Grant (Mechanisms of gene regulation by CSL-Notch)
Amount £842,000 (GBP)
Funding ID BB/J008842/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 06/2012 
End 05/2015
Description Royal Society Travelling Grant
Amount £4,000 (GBP)
Organisation The Royal Society 
Sector Charity/Non Profit
Country United Kingdom
Start 10/2010 
End 12/2010
Title Time course model 
Description Method analyzing time course data of Notch regulated genes that generated a model for feedback regulation 
Type Of Material Model of mechanisms or symptoms - non-mammalian in vivo 
Year Produced 2011 
Provided To Others? Yes  
Impact Has led to reconsideration of prevailing paradigms. 
Title Genome-wide Changes in RNA expression levels, CSL binding profiles and Pol II occupancy over time course 
Description Expression arrays were used to measure the levels of mRNA in cells after notch stimulation Genomic tiling arrays were used to emasure CSL binding and Polymerse II binding over the same time-course. Data has been submitted to GEO. GEO Series record GSE35557 
Type Of Material Database/Collection of data 
Year Produced 2012 
Provided To Others? No  
Impact No actual impacts realised to date 
URL http://GEO
Title DIRECT: Gene clustering package 
Description R-Package that uses Bayesian clustering, with the Dirichlet-process prior, to look for and group related patterns in the expression array data, while estimating the number of clusters directly from the data 
Type Of Technology Software 
Year Produced 2012 
Impact No actual Impacts realised to date