Biological and Molecular Components for Genetically Engineering Biosensors in Plants
Liu, Yang, Guoliang Yuan, MD Mahmudul Hassan, Paul E. Abraham, Julie C. Mitchell, Daniel Jacobson, Gerald A. Tuskan, Arjun Khakhar, June Medford, Cheng Zhao, Chang-Jun Liu, Carrie A. Eckert, Mitch J. Doktycz, Timothy J. Tschaplinski, and Xiaohan Yang.
November 9, 2022, Biodesign Research; DOI:10.34133/2022/9863496
Plants adapt to their changing environments by sensing and responding to physical, biological, and chemical stimuli. Due to their sessile lifestyles, plants experience a vast array of external stimuli and selectively perceive and respond to specific signals. By repurposing the logic circuitry and biological and molecular components used by plants in nature, genetically encoded plant-based biosensors (GEPBs) have been developed by directing signal recognition mechanisms into carefully assembled outcomes that are easily detected. GEPBs allow for in vivo monitoring of biological processes in plants to facilitate basic studies of plant growth and development. GEPBs are also useful for environmental monitoring, plant abiotic and biotic stress management, and accelerating design-build-test-learn cycles of plant bioengineering. With the advent of synthetic biology, biological and molecular components derived from alternate natural organisms (e.g., microbes) and/or de novo parts have been used to build GEPBs. In this review, we summarize the framework for engineering different types of GEPBs. We then highlight representative validated biological components for building plant-based biosensors, along with various applications of plant-based biosensors in basic and applied plant science research. Finally, we discuss challenges and strategies for the identification and design of biological components for plant-based biosensors.
Liu Y, Yuan G, Hassan MM, Abraham PE, Mitchell JC, Jacobson D, Tuskan GA, Khakhar A, Medford J, Zhao C, Liu C-J, Eckert CA, Doktycz MJ, Tschaplinski TJ, and Yang X. (2022). Biological and Molecular Components for Genetically Engineering Biosensors in Plants. BioDesign Research, 9863496. https://doi.org/10.34133/2022/9863496.