
Most of my work in the last few years was computational, either looking at the evolution of protein-protein interactions or at the prediction of domain-peptide interactions. The nice thing of working on a lab were a lot of people were doing wet lab experiments was that I had the oportunity to, once in a while, grab some pipettes and participate in some of the work that was going on. One project that worked out well was published today (not open access sorry). My contribution to this project was small but it was a lot of fun and I am very interested in the topic that we worked on. We called it the shuffle project in lab.
The main objective of this work was to study how the addition of gene regulatory interactions impacts on a cell's fitness. We introduced different combinations of existing E.coli promoters and transcription/sigma factors either as plasmids or integrated in the genome. In effect, each construct mimics a duplication of one of the E.coli's sigma factors or transcription factors with a change in its promoter. We then tested the impact on fitness by measuring growth curves under different conditions or performing competition assays.
There were a couple of interesting findings but the two the I found most interesting were:
- The vast majority of the constructs had no measurable impact on growth even by testing different experimental conditions.
- A few constructs could out-compete the control in competition assays (stationary phase survival or passaging experiments in rich medium).
Both of these suggest that the gene regulatory network of E. coli is very tolerant to the addition of novel regulatory interactions. This is important because it tells us that regulatory networks are free to explore new interactions given that there is a limited impact on fitness. From this we could also argue that if there are many equivalent (nearly neutral) ways of regulating gene expression we can't expect to see individual gene regulatory interactions conserved across different species. There are a several recent studies, particularly in eukaryotic species, showing that there is in fact a fast divergence of transcription factor binding sites (see recent review by Brian B. Tuch and colleagues) and many other examples that show that although the selectable phenotype is found to be conserved the underlying interactions or regulations have diverged in different species. (see Tsong et al. and Lars Juhl Jensen et al.)
There are a couple of questions that come from these and other related works. What is the fractions of cellular interactions that are simple biologically irrelevant ? Is it possible to predict to what degree purifying selection restricts changes at different levels of cellular organization ? What is the extent of change in protein-protein interactions ?
Having previously worked on the evolution of protein-protein interactions this is the direction that most interests me. This is why I am currently looking at the evolution of phospho-regulation and signaling in eukaryotic species.
4 comments:
Wow, congratulations, sounds like a revolutionary work. Were you be able to redefine robustness somehow? Have you got any operational definition for robustness in a gene network before starting the work?
It is only possible to define robustness for a set of experimental conditions. In this case we were defining robustness as the impact on the cell's growth under defined experimental conditions. We tried rich medium, defined carbon sources, anaerobic and survival under heat stress or starvation. The fitness was measured by comparing the growth curve with the control in a 96 well plate reader or in same cases by performing passaging experiments over many days to detect small differences in fitness.
Robustness ends up being a very vague and hard to define concept. Very small differences in fitness, depending on the population size, might still be large enough to be either positively selected or purified away from the population.
One think that I am trying to work on right now is methods that are able to detect small differences in fitness (under some condition) but are still amenable to high-throughout studies.
So coming back to your questions, we did have a definition of robustness to work with and no I don't think this redefines robustness. There is still the question of why is the cell's growth curve is so tolerable to these additions of regulatory interactions but that requires some more work.
Congrats! It's on my papers-to-read-this-weekend list! Great stuff.
I wrote about this for my latest column at Wired.com: http://www.wired.com/science/discoveries/commentary/dissection/2008/04/dissection_0418
Fascinating stuff.
The headline's not my choice, fyi...
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