Poster
Meiqi Ding
The Institute of Microbiology of the Chinese Academy of Sciences
Beijing, Beijing, China (People's Republic)
Yang Zhou
zhengzhou university
Zheng zhou, Henan, China (People's Republic)
Dirk Becker
University of Wuerzburg
Wuerzburg, Bayern, Germany
Shang Yang
University of Wuerzburg
Wuerzburg, Bayern, Germany
Rainer Hedrich
University of Wuerzburg
Wuerzburg, Bayern, Germany
Georg Nagel
University of Wuerzburg
Wuerzburg, Bayern, Germany
Shiqiang Gao
University of Wuerzburg
Wuerzburg, Bayern, Germany
Kai Konrad
University of Wuerzburg
Wuerzburg, Bayern, Germany
When threatened, sessile plants trigger a complex defense signaling network including cytosolic Ca2+ ([Ca2+]cyt) increases, plasma membrane depolarization, reactive oxygen species (ROS) signals. The mechanisms by which specific signaling elements dictate defined physiological outcomes remain poorly understood. Our recently established methodology employed an optogenetic approach to elicit individual of those signaling elements and explore specific physiological responses encoded. Here a genetically engineered Channelrhodopsin-2 variant XXM 2.0 with high Ca2+ conductivity was functionally expressed in Nicotiana tabacum to orchestrate Ca2+ signals. Together with XXM 2.0, a light-gated anion channel ACR1 2.0 was utilized to simultaneously induce plasma membrane depolarization and facilitate anion effluxes.Both channels triggered comparable membrane depolarizations, yet they led to markedly different physiological responses. Our optogenetic approach unveiled that sustained plasma membrane depolarization alone is insufficient to elicit specific physiological outcomes. Similar to the immune response triggered by Pseudomonas syringae, the XXM 2.0-induced [Ca2+]cyt elevations stimulated immune responses, including ROS production, salicylic acid accumulation, and transcriptional reprogramming. This minimal-invasive optogenetics approach offers the potential to precisely manipulate particular point (e.g., pH, ROS, etc.) when study the complex defense signaling network.