Periodic Reporting for period 1 - MECHSYS (Mechanistic Systems modelling of plant environmental adaptation and CAM photosynthesis engineering)
Período documentado: 2022-11-01 hasta 2025-04-30
Plants have evolved remarkable ways to survive in challenging environments, from deserts to tropical rainforests. Some plants use a special form of photosynthesis called CAM (Crassulacean Acid Metabolism) that allows them to conserve water by capturing carbon dioxide at night rather than during hot days. This adaptation makes CAM plants extremely water-efficient and able to thrive with very little water, such as in deserts or when growing on other plants or on rocks.
The MechSys project aims to develop a comprehensive computer model that can predict how plants adapt to different environments. Combining principles from physics, biochemistry, and plant biology, the model simulates how plants optimize their anatomy and internal processes - from photosynthesis to water transport - to survive and grow in varying conditions. Of particular interest is understanding how some plants evolved to become succulent (having thick, fleshy leaves) and developed CAM photosynthesis, adaptations that have emerged independently multiple times in desert plants and plants that grow on other plants (epiphytes).
The project has four main objectives:
1. Create a detailed mathematical model that captures the key biological and physical processes in plants
2. Predict optimal plant characteristics for different environments
3. Understand how plants evolved various survival strategies
4. Develop blueprints for engineering drought-resistant versions of important crops like rice
The insights from this project could help address food security challenges in a warming world by showing how to engineer crops that are more resilient to drought while maintaining high productivity. This is particularly important as droughts already cause significant crop losses globally, and climate change is expected to make many regions hotter and drier in the future.
The research combines cutting-edge computational methods, including artificial intelligence, with experimental data to create a powerful new framework for understanding plant adaptation. This interdisciplinary approach, bridging physics, computer science, and biology, could revolutionize our ability to predict and engineer plant responses to environmental challenges.
The MechSys project aims to develop a comprehensive computer model that can predict how plants adapt to different environments. Combining principles from physics, biochemistry, and plant biology, the model simulates how plants optimize their anatomy and internal processes - from photosynthesis to water transport - to survive and grow in varying conditions. Of particular interest is understanding how some plants evolved to become succulent (having thick, fleshy leaves) and developed CAM photosynthesis, adaptations that have emerged independently multiple times in desert plants and plants that grow on other plants (epiphytes).
The project has four main objectives:
1. Create a detailed mathematical model that captures the key biological and physical processes in plants
2. Predict optimal plant characteristics for different environments
3. Understand how plants evolved various survival strategies
4. Develop blueprints for engineering drought-resistant versions of important crops like rice
The insights from this project could help address food security challenges in a warming world by showing how to engineer crops that are more resilient to drought while maintaining high productivity. This is particularly important as droughts already cause significant crop losses globally, and climate change is expected to make many regions hotter and drier in the future.
The research combines cutting-edge computational methods, including artificial intelligence, with experimental data to create a powerful new framework for understanding plant adaptation. This interdisciplinary approach, bridging physics, computer science, and biology, could revolutionize our ability to predict and engineer plant responses to environmental challenges.
The MechSys team has developed a comprehensive computer model simulating how plants adapt to different environments. This model integrates three key systems that determine plant survival and growth: the biochemical network handling photosynthesis inside plant cells, the hydraulic network managing water movement from soil through the plant to the atmosphere, and the thermal mechanics controlling heat exchange between the plant and its environment.
For plants performing CAM photosynthesis (taking in carbon dioxide at night), the team also modeled the special malic acid cycle enabling this adaptation. By modeling these systems together, the researchers discovered that plant biochemistry, water transport, and heat exchange are much more tightly connected than previously appreciated.
Using fundamental physics and chemistry principles, the model is starting to reveal new insights about poorly understood aspects of CAM plants, including how malate accumulation affects water movement, why water-storing tissues are important for CAM photosynthesis, and why this efficient form of photosynthesis is mainly found in harsh environments.
Through computer simulations of plant evolution, the team demonstrated that both thin-leaved C3 plants and succulent CAM plants represent optimal solutions under specific conditions. In warmer, drier environments with low CO2 levels, CAM photosynthesis becomes more advantageous, matching real-world observations. Preliminary results help explain several puzzling aspects of CAM plants, including their strong connection to succulence, their presence in some aquatic plants, and the role of photorespiration in their metabolism.
These findings reveal which combinations of plant traits work together effectively under different conditions, crucial knowledge for engineering drought-resistant crops. The team is now refining their model with the help of artificial intelligence to facilitate quantitative predictions that can be validated experimentally.
For plants performing CAM photosynthesis (taking in carbon dioxide at night), the team also modeled the special malic acid cycle enabling this adaptation. By modeling these systems together, the researchers discovered that plant biochemistry, water transport, and heat exchange are much more tightly connected than previously appreciated.
Using fundamental physics and chemistry principles, the model is starting to reveal new insights about poorly understood aspects of CAM plants, including how malate accumulation affects water movement, why water-storing tissues are important for CAM photosynthesis, and why this efficient form of photosynthesis is mainly found in harsh environments.
Through computer simulations of plant evolution, the team demonstrated that both thin-leaved C3 plants and succulent CAM plants represent optimal solutions under specific conditions. In warmer, drier environments with low CO2 levels, CAM photosynthesis becomes more advantageous, matching real-world observations. Preliminary results help explain several puzzling aspects of CAM plants, including their strong connection to succulence, their presence in some aquatic plants, and the role of photorespiration in their metabolism.
These findings reveal which combinations of plant traits work together effectively under different conditions, crucial knowledge for engineering drought-resistant crops. The team is now refining their model with the help of artificial intelligence to facilitate quantitative predictions that can be validated experimentally.
The project represents several major advances over existing approaches to understanding plant adaptation. While previous models treated different plant processes separately, this is the first to integrate cellular biochemistry, water transport, and thermal dynamics into a single mechanistic framework. Even with the preliminary model, this integration has already revealed previously unknown interactions between these systems.
The model's ability to predict optimal plant characteristics for different environments, supported by evolutionary simulations, provides a novel theoretical foundation for understanding plant adaptation. This goes beyond traditional descriptive approaches to offer a predictive framework that could guide future crop engineering efforts.
The model's ability to predict optimal plant characteristics for different environments, supported by evolutionary simulations, provides a novel theoretical foundation for understanding plant adaptation. This goes beyond traditional descriptive approaches to offer a predictive framework that could guide future crop engineering efforts.