Sensl: a synthetic biology sensor for tracking strigolactone signaling in rice

Abstract

Strigolactones (SLs), a special class of plant hormones and rhizosphere signals, play an indispensable role in regulating important agronomic traits of rice (Oryza sativa), one of the most important crops in the world (Wang et al., 2018; Chen et al., 2022). Genetically or chemically modifying the SL pathway could significantly alter plant architecture and crop yield of rice through the regulation of shoot branching (Zou et al., 2006; Arite et al., 2007; Lin et al., 2009; Wang et al., 2020). SLs can also coordinate with other plant hormones, such as auxin, brassinosteroid, gibberellin, and abscisic acid (ABA), to regulate rice growth and metabolic processes (Sang et al., 2014; Fang et al., 2020; Liu et al., 2020; Sun et al., 2023). Moreover, SLs have been shown to participate in integrating N, Pi, as well as sucrose signals to influence rice development and environmental adaptation (Shi et al., 2021; Patil et al., 2022; Barbier et al., 2023). In light of the pivotal role of SLs in rice breeding, it is necessary to develop precise molecular tools for real-time monitoring of SL signaling dynamics in rice.

Up to now, strategies for in vivo and in situ tracking of SLs have been limited. Researchers largely depend on mass spectrometry (MS) to quantify SLs in plant cell lysate (Xie et al., 2013; Halouzka et al., 2020; Yoneyama et al., 2022), which is often compromised by SLs' limited stability, high MS costs, and scarce analytical standards (Floková et al., 2020). Recent advances in genetically encoded ratiometric reporter systems, such as StrigoQuant (Samodelov et al., 2016) and pRATIO (Khosla et al., 2020; White et al., 2022), along with engineered fluorescent biosensors utilizing SL receptors (Chesterfield et al., 2020), provide promising alternatives. However, the above-mentioned sensors are only successfully applied in transient expression systems, of which the application in intact plants has not been achieved. Although the fluorescent biosensor Strigo-D2 enables SL signaling monitoring in Arabidopsis seedlings (Song et al., 2022), there remains a critical gap in high-throughput, noninvasive tools for SL signaling detection in vital crops like rice, where SLs are essential for regulating several important agronomic traits.

We first demonstrated that Sensl's response is dependent on bioactive SLs and proteasome activity. Next, we validated Sensl's ability to detect fluctuations in endogenous SL levels in intact living rice. We also pursued extensive Sensl exploration in distinguishing SL stereochemistry and detecting cross talk between SLs and other phytohormones. Additionally, we developed a streamlined in vitro method for assessing OsD53 degradation using Sensl. Collectively, our results highlight the significant value of Sensl as a versatile instrument for unraveling SL signaling in rice by combining species specificity, ratiometric precision, and in vivo–in vitro dual-mode compatibility.

The development of Sensl, the first ratiometric sensor for real-time monitoring of SL signaling dynamics in rice, represents a significant advancement in the field of plant hormone research. Unlike previous SL signaling biosensors, which are largely limited to transient expression systems (Samodelov et al., 2016; Chesterfield et al., 2020), Sensl enables noninvasive, high-throughput tracking of SL signaling dynamics in intact rice plants within native habitats, filling a critical technical gap, especially for crop research. Compared with Strigo-D2, which uses mVenus to monitor SL signaling in Arabidopsis (Song et al., 2022), Sensl employing FLUC bioluminescent indicator exhibits a better performance in plant materials, where Chl autofluorescence often interferes with signal detection. Moreover, Sensl's ratiometric design, incorporating both FLUC and RLUC, enhances the accuracy and reliability of SL signal quantification, making it a versatile tool for both in vivo and in vitro applications.

Despite its advantages, Sensl is not without limitations. As an indirect, degron-based sensor, Sensl relies on SL-induced degradation of the OsD53 protein to report SL signaling dynamics, rather than directly detecting the SL molecule itself. While this design provides high sensitivity and specificity, it also raises concerns about orthogonality, as the constitutive expression of OsD53 may interfere with endogenous SL signaling. We can effectively evaluate the effects of different plant mutants as well as small molecules on SL signaling by performing hybridization experiments between mutants and wild-type Sensl or by comparative analysis of the same line before and after small molecule treatment. Therefore, Sensl still holds significant potential for studying SL signaling.

Moreover, while the reversibility of Sensl is theoretically plausible due to the dynamic nature of protein degradation, it has not been explicitly validated through high-resolution, real-time monitoring experiments. Future studies could address these limitations by engineering OsD53 variants with minimized interference or creating synthetic biosensors that operate independently of the host's SL signaling machinery. Insights from structural biology and computational modeling could further enhance the design of such biosensors, improving their binding affinity, signal-to-noise ratio, and functional independence from host systems.

Looking ahead, combining Sensl with genetic tools, such as mutants or overexpression lines of OsD53-interacting proteins, could open new avenues for studying the regulatory mechanisms of SL signaling. For example, our analysis of the PPI network specific to OsD53 revealed its involvement in SL-dependent processes and identified novel molecular chaperones associated with OsD53 stability (Fig. S9). These findings establish a basis for future investigations into the molecular mechanisms underlying SL signaling. Furthermore, the use of sophisticated computational techniques, such as homology modeling, virtual screening, and artificial intelligence-aided protein engineering, could expedite the creation of next-generation biosensors with higher affinity, lower noise, and minimal interference with host signaling pathways (Vázquez Torres et al., 2024). Implementing these innovative approaches in plant biosensor design may yield unexpected innovations and discoveries.

None declared.

XS, JY, DX and YL designed the experimental strategy and wrote the manuscript. YL performed most of the experiments. FW and RD assisted in some experiments and revised the manuscript. All authors read and approved the final manuscript.

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