Francesca Vianello

A novel computational tool to reveal the all-scale structural organisation and design principles underpinning the activity of the enzyme responsible for the majority of global atmospheric CO2 fixation

Francesca Vianello - 3rd year PhD


Food Security and Climate Change: Agriculture is under worldwide pressure to increase crop productivity to cater for society’s growing requirements. Such increased requirements have to be considered within the context of global climate change, which will mean that many regions of the world will experience higher temperatures, and erratic weather patterns. Understanding how different plants and crops can be adapted to this changing landscape will be a defining factor if we are to increase food production over the coming decades.
CO2 concentrations in the atmosphere: The concentration of CO2 in the atmosphere is dependent upon a single enzyme, Rubisco, which is responsible for the fixation of the majority of CO2 in the atmosphere. Interestingly, this enzyme is highly inefficient, suffering from both a slow catalytic rate and lack of substrate specificity. Models that describe CO2 flux to predict the impact that climate change will have on, for example, crop yields and water usage, are currently limited by a lack of a quantitative understanding at a molecular level of CO2 uptake and how this can be enhanced. This means that we are currently in the somewhat uncomfortable position of relying on plant biomass for food, fuel and bio-products, without a clear understanding of the interaction between photosynthetic efficiency and changing CO2 concentrations, water levels and temperature fluctuations due to climate change.

Project Aim: WE aim to address this problem at the molecular level, by gaining a greater understanding of Rubisco and its role in CO2 uptake by investigating: (i) the effect of increasing CO2 levels on Rubisco’s activity, and (ii) the structure-function relationship that dictate this enzyme’s inefficiency based on the comparison across different plant species. The results from this study will provide the foundation for work focused on enhancing Rubisco’s efficiency at removing CO2 from the atmosphere, and increasing the yield potential of crops.

Combining Theory and Experiment: Rubisco is a large multi-heteromeric enzyme, exhibiting highly complex multiscale dynamics, which may explain the limited success to date in optimising Rubisco’s catalytic activity through genetic engineering. This studentship will focus on the development of a computational tool for the analysis of Rubisco structures based upon a novel multiscale graph-theoretical methodology for community detection. The tool uses biophysical, structural and biochemical data and will be employed to reveal the time-dependent hierarchical community substructures present in Rubisco, thus providing a relationship between Rubisco’s structural dynamics across time and length scales. This study will help establish links between structure and function, and to identify targetable hotspots that can be used by the student to chemically and/or genetically modify the activity of the enzyme and to enhance/diminish cooperativity. A comparison across species using methods from geometric graphs and dimensionality reduction will also be used. Thus there will be an iterative interaction between the theoretical and experimental aspects of this project.