In new research published in Molecular Biology and Evolution, Dr Thomas Shafee, Professor Anthony Bacic and Dr Kim Johnson at the La Trobe Institute for Agriculture and Food have developed a computational method to study the proteins that help plants to respond to challenges, such as disease.
“Plants are rooted in the earth and, over the course of evolution, they have developed a range of smart systems to adapt to changes in their environment,” explains Johnson. “They have the ability to sense and respond to changes in temperature and rainfall, and to fight disease. They can also change their growth patterns based on the information they receive from the world around them.”
“Understanding the molecular mechanisms that help plants to respond to challenges in their environment will help breeding programs that target enhanced biomass and seed production as well as resilience for a more sustainable future,” adds Shafee.
Proteins with sugars attached, also known as glycoproteins, help plants to adapt to their environment. They are involved in all aspects of plant growth, providing signals that are needed to create seeds, regulate flowering, promote stem development and fight disease. “These signals are about sense and response,” says Johnson. “If a person feels heat with their hand, for example, there is a message that goes to the brain which responds accordingly. It is the same for plants. They encounter the environment and glycoproteins help to process messages to initiate an appropriate response.”
While glycoproteins play a critical role in plant growth, their variability has made them a challenge to study.
“Most proteins fold down into a condensed, neatly packaged shape, which makes them easier to analyse,” explains Shafee. “Some glycoproteins belong to a group of disordered proteins that have other elements attached to them, such as sugars. While their disordered state makes them the quick and flexible responders of the protein world, their variability also makes them difficult to study because they don’t fit the mould of a neat, classical protein structure.”
Shafee, Bacic and Johnson have solved that problem, developing an innovative computational method that allows scientists to classify glycoproteins into groups and identify their function. “Now we can determine which group is responsible for stem growth, for example,” says Johnson.
“Our method will allow scientists to fast-track experimental approaches to improve plant growth, yield and disease resistance in agriculture, forestry and horticulture,” says Shafee. “Disordered proteins are surprisingly common and found in every kingdom of life, from viruses to humans. The method provides a powerful tool that can be used to understand proteins important for growth, defence and disease in all living things.”