When under stress, plants release molecules to activate their defense system. Detecting these stress-related molecules offers the possibility to address stress conditions and prevent the development of diseases. However, detecting endogenous signalling molecules in living plants remains challenging due to low concentrations of these analytes and interference with other compounds; additionally, many methods currently used are invasive and labour-intensive. Here we show a non-destructive surface-enhanced Raman scattering (SERS)-based nanoprobe for the real-time detection of multiple stress-related endogenous molecules in living plants. The nanoprobe, which is placed in the intercellular space, is optically active in the near-infrared region (785 nm) to avoid interferences from plant autofluorescence. It consists of a Si nanosphere surrounded by a corrugated Ag shell modified by a water-soluble cationic polymer poly(diallyldimethylammonium chloride), which can interact with multiple plant signalling molecules. We measure a SERS enhancement factor of 2.9 × 107 and a signal-to-noise ratio of up to 64 with an acquisition time of ~100 ms. To show quantitative multiplex detection, we adopted a binding model to interpret the SERS intensities of two different analytes bound to the SERS hot spot of the nanoprobe. Under either abiotic or biotic stress, our optical nanosensors can successfully monitor salicylic acid, extracellular adenosine triphosphate, cruciferous phytoalexin and glutathione in Nasturtium officinale, Triticum aestivum L. and Hordeum vulgare L.—all stress-related molecules indicating the possible onset of a plant disease. We believe that plasmonic nanosensor platforms can enable the early diagnosis of stress, contributing to a timely disease management of plants.
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The data that support the findings of this study are available within the Article and Supplementary Information. Raw data of the results reported in this study are available via figshare at https://figshare.com/articles/dataset/In_vivo_SERS_nanosensor_for_plant_signaling_molecules/21316554. All other relevant data and findings of this study are available from the corresponding authors upon reasonable request. Source data are provided with this paper.
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This research was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Crop Viruses and Pests Response Industry Technology Development Program, funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) (no. 321107-03), the National Research Foundation of Korea (NRF) grant funded by the Korean government (the Ministry of Science and ICT) (nos. 2021R1C1C1005691, 2020R1A4A1018017 and 2021R1A4A5031762) and the Creative-Pioneering Researchers Program through Seoul National University. We are grateful for the helpful discussion with Y.-S. Lee.
The authors declare no competing interests.
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Source Data Fig. 1
SERS spectrum and statistical source.
Source Data Fig. 2
SERS spectrum and false image matrix.
Source Data Fig. 3
SERS spectrum and curve fitting data.
Source Data Fig. 4
SERS spectrum and statistical source.
Source Data Fig. 5
SERS spectrum and statistical source.
Source Data Fig. 6
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Son, W.K., Choi, Y.S., Han, Y.W. et al. In vivo surface-enhanced Raman scattering nanosensor for the real-time monitoring of multiple stress signalling molecules in plants. Nat. Nanotechnol. 18, 205–216 (2023). https://doi.org/10.1038/s41565-022-01274-2
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