Arabidopsis leaf cells, stained to visualise the cell wall and Botrytis cinerea mycelia
Today’s highlighted paper demonstrates the scale of the pathogen response in greater detail than has been published previously. Windram et al. (2012) profiled gene expression in Arabidopsis thaliana leaves every two hours after infection with Botrytis cinerea, until the fungus was truly established 48 hours after infection.
On the whole, until now research into the pathogen response has been at the pathway-level. Many details are known about the plant pathogen response, for example it is possible to identify loci responsible for resistance, as highlighted on this blog last week, and the intricacies of the oxidative burst are being discovered. When we understand these kinds of details, it is possible to make aphid-repellant crops, and harness the TALE tools used by Xanthomonas spp. to make disease resistant rice. On the other hand, they are just details – a close-up, zoomed in fraction of the whole, and broadly speaking it is luck if a piece of research provides anything of commercial worth.
A systems biology approach allows us to see the whole picture rather than the details of a close-up. From the data in Windram et al., we now know that a third of the Arabidopsis genome is differentially expressed in leaves infected with Botrytis compared to mock-inoculated controls. This represents a huge chunk of defence-related pathways, not previously studied, which could be affected by any attempts to improve pathogen resistance in plants.
This experiment was a timecourse, which allowed the team to record the timings of defence response pathways to two-hour time slots, like ethylene synthesis at 14 hours and response to jasmonic acid at 16 hours post-infection. Additionally, it showed that pathways including translation, photosynthesis, and protein phosphorylation were all down-regulated, and the order and timing in which they occurred. The ability to assign each process a time is important for modelling and predicting regulatory mechanisms. (more…)
GARNet needs your help to assess the uptake, influence and future of systems biology in the plant science community. This is the second time GARNet has conducted a survey about systems biology, as in 2006 the BBSRC commissioned GARNet to produce a report on how systems biology could best be approached in UK Arabidopsis research. We believe that report and the various activities that accompanied it helped the Arabidopsis community get its foot on the ‘System Biology Ladder’ – and to win some of the associated grants.
Now, six years later, systems biology is supporting systems biology and the digital organism efforts. We feel it is time to write a follow up report to the 2006 Systems Biology report in order to advise the BBSRC and other funders on the community’s capabilities, current needs, and readiness for future initiatives that build on Systems Biology.
Please help us collect data and information for this report by filling in a questionnaire, which will take about 20 minutes of your time. Please click here to go to the questionnaire. Please contribute your ideas before the 5th November.
Video credit: Pacific Biosciences.
Highighted article: Michaël Bekaert, Patrick P. Edger, Corey M. Hudson, J.Chris Pires, Gavin C. Conant (2012) Metabolic and evolutionary costs of herbivory defense: systems biology of glucosinolate synthesis. New Phytologist 196:596–605.
Research published in a current New Phytologist paper uses a systems biology approach to demonstrate the metabolic and evolutionary costs of producing glucosinolates for defence. Bekart et al. used AraGEM (Oliveira Dal’Molin et al., 2010) as a starting point. They collected data on Arabidopsis glucosinolate genes by scouring published papers and downloading their expression patterns from AtGenExpress. This information was integrated into the basic dataset from AraGEM. The complete list of genes involved in glucosinolate reactions, including references, is in Supplementary Table S1 of the paper.
The team performed flux balance analysis on the integrated database to estimate metabolic and energy flux through reactions in the system both with glucosinolate biosynthesis activity and with none. They found that glucosinolate biosynthesis affected flux incidentally through 241 reactions in addition to the 196 reactions which are only active when glucosinolates are being produced.
The main finding of the research is the heavy cost of glucosinolate biosynthesis. Sulphur import dramatically increased when glucosinolates were being synthesised, and demand for water, carbon dioxide, ammonia, and photons increased too. Despite the increase in substrate import, biomass synthesis fell by around 15% during glucosinolate production. This cost is reflected in other studies demonstrating that the evolutionary competitive edge glucosinolates give to plants is a disadvantage when there are no predators around (Mauricio, 1997), and reduces the number of seeds and flowers produced per plant compared to non-producers (Stowe and Marquis, 2011). (more…)
It’s time for another guest post today – Katherine Denby writes about the SEB 2012 conference.
Warwick Systems Biology Centre was well represented at the recent SEB conference in Salzburg, with 4 presentations in sessions on Biotic Stress, Environmental Control of Development and Generating New Biological Insights from Complex Data.
Arabidopsis leaf cells, stained to visualise the cell wall and Botrytis cinerea mycelia. Credit: Katherine Denby
First up was Katherine Denby who presented analysis of a gene expression time series from Arabidopsis leaves infected with the fungal pathogen Botrytis cinerea generated in the PRESTA project. Using a variety of network inference algorithms, the group has generated models of the gene regulatory networks underlying the Arabidopsis response to this pathogen. These network models have highlighted specific regulatory interactions, and led to identification of transcription factors with a novel role in defence. Modelling using gene expression time series from other biotic and abiotic stresses has predicted a core regulatory network underlying multiple stress responses with differential flux through the network under different environmental conditions. Katherine also described a novel tool, Wigwams, to identify groups of genes significantly co-expressed across multiple stresses. Integrating this with the network models enables prediction of the upstream regulators of these groups. (more…)