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Reprogramming stomatal behaviour to reduce water use in crops


Project Description

Future food security will depend on developing crop plants that are as efficient as possible in their utilisation of finite resources such as water. A promising avenue is to engineer more water-use-efficient photosynthetic modes such as Crassulacean acid metabolism (CAM) into crops. While the biochemical cycle of CAM is straightforward to introduce in transgenic plants, with the first steps already taken, reprogramming stomata so that they stay shut during the day and open at night is a major challenge that will require new understanding of the regulation of stomatal opening. It is known that a signal from leaf mesophyll cells is a major factor in regulating stomatal opening, linking stomatal aperture to the requirement of the photosynthetic leaf for CO2. This signal could be manipulated to alter the temporal pattern of stomatal opening but its identity has remained elusive despite decades of research. This project will initially use a computational model to propose novel candidates for this signal molecule. The model, previously developed in the Sweetlove and Ratcliffe labs, captures the entirety of primary metabolism in leaves and will be adapted in the project to account for the transport of mesophyll metabolites into the extracellular space where they can diffuse to guard cells and affect stomatal behaviour. The project could develop in an experimental direction (e.g. testing the candidate signals in transgenic plants) or continue in a computational direction (e.g. connecting the model with a more detailed model of guard cell function [1]) or could consist of a mixture of computational and experimental work.

[1] Vialet-Chabrand S, Hills A, Wang Y, Griffiths H, Lew VL, Lawson T, Blatt MR, Rogers S. (2017) Global sensitivity analysis of OnGuard models identifies key hubs for transport interaction in stomatal dynamics. Plant Physiol 174:680-8.

STUDENT PROFILE

Interested in food security.
Interested in computational biology.
Interested in plant metabolism and metabolic engineering.

No prior experience in computational modelling or programming necessary.


Funding Notes

There are two main routes into the Department of Plant Sciences Graduate Programme dictated by different funding mechanisms: If, after discussion with a potential supervisor, you decide that one of these programmes is right for you, you will need to apply directly to the relevant programme.

Option 1: Applying via a Doctoral Training Programme
Option 2: Applying directly to the Plant Sciences DPhil research programme

In depth guidance is available here: View Website

References

[1] Shameer, S., Ratcliffe, R.G. and Sweetlove, L.J., (2019). Leaf energy balance requires mitochondrial respiration and export of chloroplast NADPH in the light. Plant Physiol, 180:1947-61

[2] Shameer, S., Baghalian, K., Cheung, C.Y.M., Ratcliffe, R.G. and Sweetlove, L.J. (2018) Computational analysis of the productivity-potential of CAM. Nature Plants 4: 165-171 doi:10.1038/s41477-018-0112-2

How good is research at University of Oxford in Biological Sciences?

FTE Category A staff submitted: 223.80

Research output data provided by the Research Excellence Framework (REF)

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