Research

Improving photosynthesis

Increasing crop productivity is essential for global food security - our research focuses on finding novel ways to deal with this challenge (Yang et al., 2020; Krose et al., 2024). One major limitation of productivity is the low efficiency of photosynthetic CO2 assimilation. We are currently exploring several approaches to understand and overcome this problem:

Engineering pyrenoid-based CO2-concentrating mechanisms into higher plants


Chlamydomonas reinhardtii

 

Most plants rely on passive diffusion for photosynthetic CO2 assimilation. We are investigating whether the pyrenoid-based CO2-concentrating mechanism (pCCM) from green algae (e.g. Chlamydomonas and Chlorella)  can be utilised to increase photoassimilation rates and hence productivity (Adler et al. 2022; Catherall et al. 2024). In collaboration with members of the Combining Algal and Plant Photosynthesis (CAPP) consortium, we are investigating the compatability of pCCM components with plant chloroplasts (Atkinson et al., 2016; 2017) and working towards the assembly of a functional pCCM in the model C3 plant species Arabidopsis thaliana (Atkinson et al., 2019; 2020; 2024; Barret et al., 2024;  Itakura et al., 2020;  He et al., 2020; Hennacy et al. 2024) (funded by the BBSRC, Leverhulme Trust and Carbon Technology Research Foundation).

Characteristics of Rubisco

 


Arabidopsis thaliana

Photosynthetic CO2 assimilation is limited by the properties of the primary assimilating enzyme, Rubisco. We employ precision genome editing approaches to change the properties and expression of the Rubisco holoenzyme in model plants, such as Arabidopsis (Khumsupan et al., 2019) and tobacco . We are focusing  on the role of the small subunit of Rubisco (Khumsupan et al., 2020; Donovan et al., 2020; Mao et al., 2022), with the aim of gaining a better understanding of how the Rubisco complex might be modified to design more appropriate Rubiscos for crop plants (funded by the BBSRC). 


Arabidopsis Rubisco mutants

Photosynthetic microorganisms

Phycobilisome mutants

 

The Edinburgh Genome Foundry

Cyanobacteria are central to several emerging biotechnologies that use light and photosynthesis to drive the production of high value biofuels and biochemicals. We have developed a standardised Modular Cloning toolkit called CyanoGate (available on Addgene) to generate novel strains for studying cyanobacterial photobiology and producing high value chemicals (Vasudevan et al., 2019; Gale et al., 2021). In collaboration with our industrial partners ScotBio and CyanoCapture, we are interested in utilising cyanobacteria for the production and downstream processing of high value products, such as the phycobiliprotein C-phycocyanin (Puzorjov et al., 2020; 2022a; 2022b; Simon et al., 2020; Scorza et al., 2021), and developing fast growing strains as a bio-based capture utilisation and storage (CCUS) technology for reducing CO2 emissions (Victoria et al., 2024; 2024)

Working with the Edinburgh Genome Foundry and the Lea-Smith Lab (University of East Anglia), we have also expanded the CyanoGate toolkit to generate the first full genome knockout library of the model cyanobacterium Synechocystis sp. 6803 called CyanoSource (Gale et al., 2019b; Mills et al., 2020; Zielinski et al., 2022). This work is funded by the BBSRC, BBSRC NIBB Algae-UK, IBioIC and Carbon Technology Research Foundation.

The CyanoGate system

 

 

Synechocystis sp. 6803 mutant library 
Cyanobacterial biofilm Previous work with the Howe Lab (University of Cambridge) includes the development of novel photosynthetic microbial fuel cells ("biophotovoltaic" devices) that utilise unicellular species, such as Synechocystis sp. PCC 6803, to produce electricity (McCormick et al., 2011) and drive hydrogen production (McCormick et al., 2013). We have released a broad review of biophotovoltaic research (McCormick et al., 2015).

BPV device

 

Dynamic capture of plant growth

Reconstruction of Arabidopsis rosette 

We are working with the Centre for Machine Vision (Bristol Robotics Lab, UWE) to develop low-cost hardware and software tools to track plants throughout the growth period. With the Halliday Lab (UoE), we are developing computer vision algorithms to extract important traits and models to predict growth and productivity (funded by the BBSRC). We have developed low-cost 2D imaging system for tracking plant growth (Dobrescu et al. 2017), and a 3D imaging system based on an imaging technique called photometric stereo (Bernotas et al., 2019).

Photometric stereo rigs imaging Arabidopsis

Growth under fluctuating conditions

In the natural environment, plants need to adapt quickly to prevailing conditions. They achieve this, in part, by dynamically co-ordinating photosynthesis and the allocation of newly fixed carbon to ensure optimal rates of growth and fitness. The cytosolic regulatory metabolite fructose 2,6-bisphosphate (Fru-2,6-P2) is central to this process. With the Kruger lab (University of Oxford) we have shown that, under fluctuating environments, Fru-2,6-P2 rapidly modulates the partitioning of photassimilate to buffer photosynthetic capacity (McCormick & Kruger, 2015). We are interested in expanding this work to explore the interactions of light and temperature signalling with primary metabolism.