At scientists have developed rapid methods for identifying Ralstonia solanacearum. This soil-borne pathogen is the cause of bacterial wilt, a bacterium that researchers are actively seeking to eliminate the impact of. This novel research taps the power of artificial intelligence to enhance plants’ innate alarm systems. Because of this work, we now understand how plants recognize and mount defenses against this lethal adversary. UCDavis Professor Gitta Coaker from the Department of Plant Pathology led a terrific study. It was just released in the journal Nature Plants.
Ralstonia solancearum has long been recognized a significant threat to agriculture worldwide. It is capable of infecting more than 200 species of plants, putting important staple crops such as tomatoes and potatoes at risk. The pathogen’s ability to spread bacterial wilt has caused catastrophic losses for farmers around the globe. Yet the incidence of these diseases continues to increase. Funded by the Foundation for Food & Agricultural Research, this research seeks to provide a scientific breakthrough that can transform crop protection.
Understanding Ralstonia solanacearum
Ralstonia solanacearum, found ubiquitously in soil, is known for its virulent infection forms. With potential devastation on key staple crops, the pathogen threatens their yields and ability to provide for themselves financially. This future bacterium represents a real danger not just to our food supply, but to global food security.
The researchers focused on FLS2, a key receptor that allows plants to sense flagellin. This protein is associated with the flagella of Ralstonia solanacearum. They improved the overall recognition system’s accuracy with artificial intelligence. This enhancement enables facilities to detect a greater variety of bacterial hazards and fortify their preparedness and response capabilities.
“Bacteria are in an arms race with their plant hosts, and they can change the underlying amino acids in flagellin to evade detection.” – Gitta Coaker
Innovative Approaches with Artificial Intelligence
This is the first time artificial intelligence has been used to make such a definitive impact on agricultural science, and especially plant pathology. Through studying large datasets, the scientists were able to find approaches that help plants detect pathogens sooner and more efficiently. This strategy doesn’t just focus on Ralstonia solanacearum — it encompasses other future bacterial enemies that lurk.
The resulting authors of the study worked intimately with one another to create this pioneering method. They are Tianrun Li, Esteban Jarquin Bolaños, Danielle M. Stevens and Hanxu Sha—of UC Davis, and Daniil M. Prigozhin of Lawrence Berkeley National Laboratory. Their work shows that we can improve plant recognition technologies and make our crops more robust.
“We were able to resurrect a defeated receptor, one where the pathogen has won, and enable the plant to have a chance to resist infection in a much more targeted and precise way.” – Gitta Coaker
Implications for Agriculture
The findings have exciting implications in agriculture, especially as the world grapples with the challenge of feeding a growing global population. By preventing damage from Ralstonia solanacearum and other pathogens through improving plants’ internal alarm systems, scientists hope to make those dangers obsolete. This breakthrough is paving the way for more effective and ecologically sustainable crop protection methods.
Farmers will be able to develop more resilient crops, better able to resist bacterial wilt and other diseases. Our researchers are working hard to determine how artificial intelligence can be used to revolutionize farming. One particularly promising direction that they are pursuing is creating disease-resistant crop varieties.