A team of scientists from the NTU School of Biological Sciences have carried out research into how plants react to stressful conditions and devised a computational method that allows scientists to predict how plants will respond to complex environmental stresses. Their paper discussing their research and new computational method was recently accepted into the prestigious scientific journal, Nature Communications.
The work was performed by PhD student Qiao Wen Tan (right), who received support from Peng Ken Lim (left). Both were supervised by Assoc. Prof. Marek Mutwil (center).
Limited knowledge of combined stresses on plants
All living things experience stress, whether animal, human, or plant, and a plethora of research into how animals and humans are affected by stress have been conducted over the years.
While there has been plenty of research into how plants react to stress as well, with the earliest experiments dating back to the late 19th century when scientists studied the influence of light intensity and osmotic stress on plants, our knowledge of how plants react to combined stresses in nature is still limited.
Our need to understand how plants react to combined stresses in nature has become more pressing due to the increasing threats brought about by climate change.
Plants are constantly challenged by abiotic stresses, which refer to environmental factors that are not caused by living organisms and can involve anything from changes in temperature to salinity levels. Climate change will only increase the frequency and intensity of these abiotic stresses, resulting in plants having to face a lack of water from more droughts, oxygen deprivation and poor nutrient uptake caused by flooding, and heat stress from high temperatures, amongst other things. This increased severity and frequency of abiotic stresses will negatively affect our ecosystems as well as our crop yields, threatening our survival.
Marchantia polymorpha
In order to better understand how plants react to a combination of stresses present in nature, a team of scientists from the NTU School of Biological Sciences, led by Associate Professor Marek Mutwil, investigated how plants reacted to seven abiotic stresses, both as singular stresses and in 18 pairwise stress combinations.
A specimen of Marchantia polymorpha
The team used the liverwort, Marchantia polymorpha, as part of their experiments. Liverworts are among the oldest land plants, with a fossil record dating back millions of years. They are a valuable model in the study of plant biology due to their small genome size, fast growth time, and the ability to grow in a variety of environmental conditions.
Marchantia is also favoured by scientists due to its minimal gene regulatory network redundancy. Gene regulatory networks in some organisms have many genes that act as a backup should their usual regulatory pathways fail, which is also known as having a redundancy. An organism that has minimal network redundancy in its biological system has little to no backup plans for a failure in its biological pathways. This means that their biological systems are more streamlined and easier to study, but at the cost of robustness towards deleterious gene mutations. With its minimal network redundancy, Marchantia polymorpha allows for a more straightforward investigation and identification of key regulatory elements by scientists.
Plant Stresses
For their study, the team wished to better understand how plants modulated the expression of genes and biological pathways in response to environmental stresses. They constructed an abiotic stress gene expression atlas of Marchantia that captured gene expression changes to single and combined stresses for the liverwort, using stresses of darkness, high amounts of light, hot and cold temperatures, salt levels, nitrogen deficiency, and osmotic stress. The gene expression atlas helped the team to see which genes and biological pathways were activated or supressed during the stresses.
When exposed to the different stresses and their various combinations, Marchantia would react by generating responses through the production of transcription factors, which are genes that regulate the expression of other genes. By monitoring the level of activation or repression of these transcription factors, the team was able to identify a hierarchy of stresses.
Based on their findings, the team ranked the strength of dominance of the different abiotic stresses. Darkness was the most dominant stress, followed by heat, light, nitrogen deficiency and cold temperatures, and finally with salt and osmotic stress as the least dominant. The team also inferred the gene regulatory network that controls the differentially expressed genes (DEGs), paving a way to engineer how Marchantia responds to stresses.
Predicting the expression level of genes during combined stress
The team’s analysis also showed that it is possible to predict Marchantia’s gene expression that resulted from combined stresses with a simple linear regression model that employs log2fc (log2 fold change) values, where the magnitude of the log2fc values indicate the gene expression level. The model showed that Marchantia integrated cues from multiple environmental stresses and developed its responses via arithmetic multiplication. This surprising finding should now enable us to calculate the gene expression and, ultimately, the behaviour of plants in complex environments.
Future studies
The team’s revelation of the hierarchy of stress responses in Marchantia, as well as their demonstration that one can predict the gene expressions of a plant reacting to combined stresses through a linear regression model, paves the way for the development of more complex and better-performing models that can help to predict gene stress expression in other plants in various environments.
There is a growing need to be able to better understand how plants react to a multitude of combined stresses, which are frequently occurring in nature, as climate change will increasingly bring challenges for our ecosystems and for the crops we grow. With more studies such as these, we can work towards strengthening our ecosystems and ensuring our plant-based food supplies remain robust in the face of climate change.
On the team’s research moving forward, Associate Professor Marek Mutwil said, “Now that we begin to understand how plants respond to combined stresses, we can start to build more complex models that integrate gene expression, metabolite and protein levels and phenotypic data, to breed, select and engineer more robust crops, and protect our environment. When successful, these models may be what is needed to bring about the next green revolution, for current breeding and selection methods are laborious and time intensive.”
Read their paper here.