Biological and Molecular Components for Genetically Engineering Biosensors in Plants

Abstract

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.

Figure 1

Conceptual framework of genetically encoded plant-based biosensors (GEPBs) design. GEPBs contain a Sensory Module and a Reporter Module. Five different mechanisms of Sensory Modules are presented in the gray gear, and two types of Reporters Module are presented in the yellow gear. The Sensory Module detects the environmental, chemical, or internal stimuli, and the Reporter Module provides the detectable signal.

Figure 2

A dichotomous decision tree for the selection of appropriate genetically encoded plant-based biosensors.

Figure 3

Design of direct plant biosensors. (a) Working principle for intrinsic direct plant biosensors where florescent proteins (FP) respond to an environmental change and induce a spectral change in the FP. (b) Illustration of the construct design and readout of pHusion in plants. Figures are redrawn from the publication of pHusion [51]. Pro indicates promoter and ter represents terminator. (c) Working principle for extrinsic direct plant biosensors, where the conformational change of the sensory module caused by binding activity leads to the FRET change. Figure is designed based on the strategy of FRET-based biosensors. (d) Illustration of working principle and application of G-GECO in plants. Figures are redesigned from the results in Populus [68].

Figure 4

Design of transcriptional regulation-based plant biosensors. (a) Working principle for transcriptional regulation-based biosensors with responsive promoters as the sensory module, where the turquoise cylinder presents an optical signal from a florescent protein. (b) Illustration of the construct design and readout of SS16::GFP biosensor. Figures were redrawn from the results in Populus protoplasts [33]. Pro indicates promoter, and ter represents terminator. (c) Working principle for transcriptional regulation-based biosensors with synthetic TFs as the sensory module. (d) Illustration of constructs design and readout of TNT plant-based biosensor. Figures were adopted from phenotypic data of Arabidopsis [38].

Figure 5

Design of posttranslational modification-based plant biosensors. (a) Working principle for posttranslational modification-based biosensors consisting of a conditionally stable ligand binding domain (LBD) fused with a reporter, where the turquoise cylinder presents an optical signal from a florescent protein. (b) Illustration of constructs design and application of digoxin plant-based biosensor. Figures were redrawn from results in Arabidopsis [35]. Pro indicates promoter and ter represents terminator. (c) Working principle for posttranslational modification-based biosensors consisting of a degron motif fused with a reporter. (d) Illustration of constructs design and application of DII-VENUS for mapping Auxin distribution. Figures were redrawn from results in Arabidopsis [6]. Pro indicates promoter, and ter represents terminator.

Figure 6

Design of translocation-based biosensors. (a) Illustration of translocation-based biosensors for brassinosteroid signaling pathway. (b) Illustration of the construct design and readout of BZR1-YFP biosensor. Yellow dots represent the accumulation of BZR1-YFP in nucleus, whereas the gradient yellow area represents the cytoplasmic BZR1-YFP signals. Figures were adopted from a study in Arabidopsis [42]. Pro indicates promoter, and ter represents terminator. (c) Illustration of translocation-based biosensors for phosphorylation activity. (d) Illustration of the construct design and readout of the KLR-MKP1 biosensor. Solid green spots represent the accumulation of KLR-MKP1 signals in the nucleus, whereas the green circle with gradient color change indicates the decrease fluorescence intensity in the nucleus. Figures were adopted from the results in Arabidopsis [96]. Pro indicates promoter, and ter represents terminator.