Abstract
Plants release Volatile Organic Compounds (VOCs) in response to insect attacks. VOC facilitates communication with neighboring, undamaged plants. In response to VOC from insect damaged plants, neighboring undamaged plants upregulate their own defenses as if they were being attacked themselves. To date, Green Leaf Volatiles (GLVs) within VOC have been widely considered a primary mediator for plant communication. GLV is a six-carbon compound which all land plants emit immediately and in large quantities after wounding. We hypothesized that GLVs’ lack of specificity and abundance is unlikely to account for key aspects of plant communication like increased sensitivity between closely related plants. To test our hypothesis, we used an Arabidopsis accession which does not produce GLVs. We also developed a non-invasive imaging technique to visualize plant communication utilizing expressions of insect stress marker gene VSP1. Our analysis confirmed that plant communication occurs even without GLVs. Cytosolic calcium ion concentration increased before this timing, and moved towards the tip of the leaf in undamaged plants. Additionally, when plants were damaged by insects, acetophenone and alkanes accumulated the experiment’s enclosed space. This suggests that plants communicate independently of GLV using alkanes and acetophenone, which are known to attract natural enemies of herbivore insects like parasitoid wasps.
Introduction
Plants release smell, or Volatile Organic Compounds (VOC), when insects attack (; ; ; ). Nearby undamaged plants recognize this smell and activate their own defenses accordingly (; ; ; ; ; ; ).
For the purposes of this paper, plants releasing VOC as they are being attacked by herbivore insects are Emitter plants.
Undamaged plants detecting VOC released from their neighboring plants under herbivore insect attack are Receiver plants.
In Emitter plants, cytosolic calcium ion concentration ([Ca2+]cyt) elevates at the site-of-injury and propagates throughout their vascular system. When calcium waves reach distant tissues within a plant, they activate defense responses by inducing the expression of enzymes involved in jasmonic acid (JA) biosynthesis, a critical phytohormone that mediates resistance to insect attack (; ; ). The resulting increase in JA promotes the expression of defense related genes like JAZ10 and VEGETATIVE STORAGE PROTEIN1 (VSP1), an established marker gene for insect stress (; ). These long-distance calcium and defense signaling processes are dependent on ion channel encoding GLUTAMATE RECEPTOR-LIKE (GLR) (; ).
In Receiver plants, exposure to VOC from nearby, insect damaged plants triggers the activation of their own JA biosynthesis and JA-dependent defense pathways. For example, when leaves of lima bean Emitter plants (Phaseolus lunatus cv. Sieva) were infested with spider mites (Tetranychus urticae), neighboring lima bean Receiver plants upregulated mRNA level of LIPOXYGENASE, a key enzyme in JA biosynthesis (Arimura et al., 2000). Similarly, when lima bean Emitter plants were attacked by leafminers (Liriomyza huidobrensis), adjacent Arabidopsis Receiver plants exhibited increased VSP1 transcripts, which suggests a corresponding boost in their defense responses ().
The current view on communication between Emitter and Receiver plants is that communication facilitated primarily by Green Leaf Volatiles (GLVs) (). GLVs are six-carbon volatile compounds, including aldehydes, alcohols and their corresponding esters. They are produced by all terrestrial green plants in large quantities when plants are damaged. It is also known that plants with closer genetic relationships communicate with higher sensitivity (). Therefore we explored whether plants could communicate effectively without GLVs. Our findings indicate that GLVs are not a primary determinant of plant communication. This suggests that additional, more specific volatile cues underlie the facilitation of plant communication.
Results and discussion
VOC emitted from mutants lacking GLV activates insect defenses in nearby plants
We developed a noninvasive experimental setup to visualize VOC-mediated plant communication. Petri dishes were separated in half using a porous barrier which enables air to move freely within the petri dish. Insects were only able to eat plants on one side of the dish. On half of the dish, we grew five Emitter plants for two weeks. Insects were added at the time of the experiment. On the other half of the dish, we grew two Receiver plants (Figure 1a). Fluorescence was analyzed continuously using time-lapse imaging.
Figure 1
To visualize VOC-mediated communication between plants, we used insect infested Wild-type (WT) Arabidopsis as Emitter plants. For Receiver plants, we used transgenic Arabidopsis containing Yellow Fluorescent Protein (YFP) fused to the promoter of VSP1 (VSP1-Receiver) (; ; ). Arabidopsis Columbia accession (Col-0) for both Emitter and Receiver plants were used. Col-0 accessions do not produce detectable amounts of GLVs because of their lack of functional HYDROPEROXIDE LYASE (HPL), a key enzyme in GLV synthesis ().
When Emitter plants were infested with diamondback moth (DB moth) (Plutella xylostella), a specialist caterpillar for the Brassicaceae family which includes Arabidopsis, VSP1-Receiver displayed an intense fluorescent signal (Figures 1b-d; Supplementary Figure 1; Supplementary Movies S1, S2). Fluorescence was detectable at the onset of an insect attack indicated by initial decline of surface area exhibiting chlorophyll autofluorescence (Figures 1b, c; Supplementary Figure 2). For example, one hour after DB moth infestation, less than five percent of Arabidopsis-Emitter leaves were damaged (Figure 1c). Surprisingly, VSP1-Receiver displayed approximately 30% of peak fluorescence at this early timing (Figure 1b-c). There was also greater VSP1-Receiver signal intensity when the number of intact plants increased suggesting signaling amplification within groups of plants (Figure 1e).
Fluorescent intensities were measured and plotted along the horizontal section of the leaf base to analyze signal distribution within VSP1-Receiver. Fluorescence declined around the midvein but was highly expressed in the tissue surrounding the midvein (Figures 1f, g). This suggested that insect defense in the lamina tissue surrounding midvein was activated within Receiver plants via the detection of VOC (). In a parallel experiment, WT Arabidopsis was subjected to polyphagous oriental armyworm (armyworm) (Mythimna separata). This was done to demonstrate whether the VSP-1 expression pattern we observed using DB moth was specific to specialist herbivore insects.
We found that while VSP1-Receiver plants displayed an increase of fluorescence when exposed to armyworm-infested Emitter plants, its signal was weaker when compared to the DB moth experiments (Figures 1d, h, i; Supplementary Figure 1; Supplementary Movie S3). It is likely that relatively large armyworms consumed Emitter plants faster than they could release sufficient quantities of VOC. In any case, the signal followed a similar pattern to that of DB Moth. To ensure that these signals were not caused by the respiration of insects, we verified that neither carbon dioxide nor extra humidity induced a clear fluorescent signal (Figure 1h). There was a slight decrease of fluorescence in response to increased carbon dioxide. Insect respiration likely dampens rather than induces signal. We also confirmed that fluorescent signals are detected even when holes were made in the Petri dish to accelerate ventilation (Supplementary Figure 3).
GLRs in damaged Emitter plant trigger insect defenses in Receiver plants
GLUTAMATE RECEPTOR-LIKE proteins (GLRs) are necessary to express JA-inducible anti-herbivory genes in plants under insect attack (; ). So, we sought to test whether GLR genes in Emitter plants are required to release VOC.
When double mutant glr3.3glr3.6 was used as an Emitter plant, VSP1-Receiver plants exhibited reduced fluorescence when compared to the WT Emitter experiments (Figures 1d, i; Supplementary Figure 1). Fluorescent signal from VSP1-Receiver did not elevate when exposed to the scent of herbivore insects by itself (Figure 1i). Emitter genes GLR3.3 and GLR3.6 were required to communicate with Receiver plants.
Calcium ion movement in Receiver is triggered by VOC blends lacking GLVs
Prior studies demonstrate that plants increase their [Ca2+]cyt levels after exposure to terpenoids and Green Leaf Volatiles, GLVs (; ; ). We examined whether natural VOC without GLV from plants under herbivore insect stress increase calcium waves in Receiver plants. Using time-lapse imaging, we visualized [Ca2+]cyt increase in Receiver using Arabidopsis expressing GCaMP3 (Gcamp3-Receiver), a protein-based fluorescent calcium sensor (). Fluorescent signal was detectable in the midvein and extended toward the tip of the leaf in Receiver plants (Figures 2a, b). For both DB moth and armyworm, this corresponded with previous findings that [Ca2+]cyt travels through the Emitter plant’s vascular system (). Receiver plants appear to mirror the Emitter response to insect damage without being physically damaged.
Figure 2
We quantified the speed of [Ca2+]cyt increase by measuring length of the signal increase along the midvein from the base of the leaf. [Ca2+]cyt increase moved markedly (more than two orders of magnitude) more slowly than what was observed in Emitter plants. The peak speed of [Ca2+]cyt increase was 118 ± 15 μm/min. within a Receiver plant’s leaf in response to DB Moth damaged Emitter plants (Figure 2b). In Emitter plants, [Ca2+]cyt increase moved approximately 6 mm/min when Arabidopsis was damaged by another lepidopteran insect, cabbage butterfly (Pieris rapae) (). Emitter plants appear to respond faster than Receiver plants to warn its own leaves of imminent insect threats.
Receiver-GLRs are required for calcium signaling in Receiver plants
Emitter-GLRs are required for the upregulation of fluorescent signal in VSP1-Receiver (Figure 1i) as well as the production of calcium signals in Emitter plants (; ). VOC from infested Wild-type (WT) Emitter plants did not increase fluorescent signal around the midvein of Gcamp3-Receiver/glr3.3glr3.6 (Figure 2c; Supplementary Figure 4). This confirms that Receiver GLR3.3 and GLR3.6 are necessary to activate calcium signaling in the Receiver plants. GLR is localized within vascular bundles (). It is likely that VOCs enter plants through the stomata (), and diffuse across mesophyll cells which encase vascular bundles where GLRs are expressed (). Additionally, VOC likely interacts with proteins expressed in guard and/or mesophyll cells. These proteins activate GLR expressed in contact cells in xylem parenchyma and phloem where calcium signals originate (). For instance, an analog of the terpene caryophyllene interacts with the transcriptional repressor TOPLESS (TPL) (). Accordingly, TPL and TPR4 (TPL RELATED 4) are highly expressed in stomata guard and mesophyll cells ().
Emitter GLRs are necessary for Receiver plant calcium signaling
Emitter GLRs are necessary to upregulate VSP1 expression in Receiver plants (Figures 1b, h, i). When Emitter plants contained glr3.3 and glr3.6 mutations, the region of [Ca2+]cyt increase in Receiver plants did not extend toward the tip of the leaf when compared to WT Emitter (Figure 2d, Supplementary Figure 5). Emitter GLRs are therefore necessary to produce calcium waves in Receiver plants.
Acetophenone and alkanes are mediators of VOC-mediated communication
We analyzed how plant communication occurs without GLVs by isolating chemical compounds found in VOC using gas chromatography mass spectrometry (GC-MS). The median number of detected compounds was 22 (range 14–24) in damaged Emitter plants, compared to 10 (range 6–13) in undamaged controls. Principal component analysis clarified that biological replicates clustered tightly (Figures 3a, b). Volcano plot analysis identified chemical compounds whose levels changed significantly in close proximity to damaged Emitter plants (Figure 3c). Among these, 23-chemical components increased significantly when plants were infested with DB moth (Supplementary Table 1). GLVs like (E)-2-hexenal, (Z)-3-hexenal, and (Z)-3-hexenyl acetate were absent due to their lack of functional Hydroperoxide Lyase (HPL), the enzyme responsible for GLV synthesis ().
Figure 3
Octanal, an aldehyde known to attract the natural enemies of herbivore insects, was detected in our analysis (Figure 3c). For example, octanal is released by cabbage when infested with pierid butterfly larvae (). Hydrocarbons like tridecane, pentadecane, dodecane, cyclohexadecane were also found (Figure 3c). These hydrocarbons were detected as a part of VOC emissions in various plant species, inclusive of rice and tomato (; ; ; ). While these VOC were detected in other plant species, their significance was likely missed in terms of their function as a facilitator of plant communication under duress from herbivore insects.
Notably, acetophenone, a major compound found in Alyssum (Lobularia maritima) (Brassicaceae) was identified (Figure 3c). Volatiles from Alyssum attract Cotesia vestalis, a parasitoid wasp and natural enemy of DB moth (). Acetophenone is known to extend C. vestalis’ lifespan, and increase C. vestalis’ parasitism rate (). Acetophonone enables Brassicaceae plants to provide an important benefit to Cotesia vestalis without extending these same benefits to DB moths. Further investigation is needed to clarify whether these compounds play a direct role in triggering the GCaMP3 calcium waves and VSP1-YFP expression.
Emission of octanal, four aforementioned hydrocarbons, and acetophenone required GLRs. Volcano plot analysis using GLR mutants did not detect significant differences between Emitter plants with and without DB moth samples (p < 0.05, fold change ≥ 2, Supplementary Table 2). Although relationships between alkane biosynthesis and GLR remain unclear, acetophenone is produced via β-oxidative pathway (). Octanal is derived from lipid oxidation (). At the same time, GLR triggers jasmonic acid biosynthesis and this requires both LOX-mediated lipid oxidation and subsequent β-oxidation steps (; ). It is plausible that GLR-dependent signaling promotes the accumulation of both compounds by modulating these metabolic activities although direct regulatory links are not yet established.
Conclusion
We established a technique to analyze VOC mediated plant-to-plant communication by using non-invasive time-lapse imaging. Even under conditions where Green Leaf Volatiles (GLVs) are absent, VOCs emitted from Emitter plants are sufficient to activate defense responses in Receiver plants (Figure 4). GLRs in Emitter plants are necessary to emit specific VOCs, including hydrocarbons, and acetophenone, as well as for the subsequent upregulation of defense-related molecular markers in Receiver plants. In sum, basic assumptions about how plant communication works at a molecular level may be fruitfully examined as new techniques make it possible to do so. As our knowledge about the molecular mechanisms of plant communication increase, so might our understanding of how plants organize, communicate and thrive in stressful environments.
Figure 4
Materials and methods
Plant materials
Arabidopsis thaliana ecotype Columbia-0, which is publicly available from Arabidopsis Biological Resource Center (https://abrc.osu.edu/) was used as Wild type (WT). Transgenic lines GCamp3 and GCamp3/glr3.3glr3.6 were described by Toyota et al (). Transgenic line VSP1-YFP was previously documented (; ; ). Columbia-0 ecotype was graciously provided by Dr. Tohru Ariizumi, University of Tsukuba.
Growth
Surface sterilized Arabidopsis seeds were grown for three weeks in Murashige and Skoog (MS) media consisting of half-strength MS, 0.5% sucrose, and 0.6% Phytagel (). Plants were grown at 22°C under 16-h/8-h light/dark cycle. After one week, seven seedlings were transferred to media inside a Petri dish divided in half by a plastic divider and grown for two additional weeks. For Figure 1e, 22 seedlings were transferred. Three-week-old seedlings were used in the experiments. This divider had 1 mm holes. The plastic divider in the Petri dish was manufactured at the University of Tsukuba Engineering Workshop Division.
Insects
Armyworm (Mythimna separata) was reared according to Kuramitsu et al (). Silkmate (Ehime Sanshu) was used as an artificial diet. Diamondback moths (Plutella xylostella) were reared using komatsuna leaves. Second and third instar armyworm larvae and fourth instar diamondback moth larvae were used.
Microscopy
M205FA automated stereomicroscope (Leica Microsystems) with a motorized stage and DFC7000T color CCD camera (Leica Microsystems) was used to acquire images. Apparatus was controlled by LasX software (Leica Microsystems). A metal halide bulb (Leica EL6000) was used as an excitation light source. Chlorophyll auto fluorescence and YFP signals were detected using Texas Red and YFP filters respectively (both from Leica Microsystems) (; ). Excitation emission wavelengths of YFP and Texas Red filters were 510/20–560/40 nm and 560/40–610 LP nm respectively.
In all analyzes, except Figures 1b, c, the first cycle was recorded without insects. Six DB moth larvae or two armyworm larvae were used in each experiment (with the exception of Figure 1e). Equal numbers of insects were used for control without Emitter (Figures 1i, 2d). For the carbon dioxide control experiments, a Petri dish with Receiver was opened and placed in a plastic box containing approximately 800 ppm of carbon dioxide (Figure 1h). This environment was created by placing dry ice in the plastic box. The Petri dish was left open for one minute before being sealed and analyzed using time-lapse microscopy. To measure the effect of moisture on control experiments, we placed a cotton ball with 40 μl of ultra-pure water, which is the approximate weight of six DB moths, into a Petri dish with Receiver and analyzed them using time-lapse microscopy (Figure 1h). For experiments using our automatic fluorescent signal quantification method (), diamondback moth was added at the beginning of recordings (Figure 1b, c). In the experiment regarding ventilation, we used a 0.6 mm drill to drill three holes on the Emitter side and five holes on the Receiver side of the lid of the petri dish (Supplementary Figure 3).
Experimental research using plants and insects in our study complies with relevant international, national, and institutional rules and guidelines.
Image processing
Red channel images from Texas Red filter and white light images were exported from LasX (Leica Microsystems). Green channel images from the YFP filter were exported and analyzed using FIJI (NIH) by superposing binarized Texas Red images to define plant shapes. These superposed images were used to extract plant-specific signals. Shadows in merged images at the intersection of the adjacent frames were adjusted using the BaSic tool ().
Quantification
For Figure 1c, the “Analysis” function of LasX was used to calculate the Texas Red area from red channel images. Mean YFP signal intensity from the whole plant was analyzed using green channel images (). To prevent the leaves from growing upward in the dark, 300 milliseconds of white light was applied for every YFP image taken on a single tile. As for the overlap between leaves or insects, 20 millisecond exposure for Texas Red imaging immediately followed five seconds of YFP exposure.
The remaining YFP signal intensity was quantified using images from the green channel with FIJI (NIH) software. For Figures 1h, i, fluorescent signal intensities of fully developed, non-overlapped whole leaves were measured. For Figures 1f, g, signal intensity at the time of Fmax was analyzed at the leaf blade closest to the petiole. Signal intensity was plotted along the horizontal orientation of a leaf using FIJI. Relative positions were used: the center of the leaf was 0.5. The edges on both ends were 0 and 1. Timing of maximum mean fluorescent signal was used for Figures 1e, i. For Figure 2c, mean signal intensity for the increased fluorescent region within midvein was compared against the rest of the leaf. For Figures 2b, d, length of the region of signal increase along the midvein from base of the leaf was measured using threshold of 6-94. For Figure 2b, data for 1.5 hours was used, for Figure 2d, data at 0.5 hours was used. For Figure 1e, acrylic box of 193 mm (W) x 103 mm (H) x 25 mm (D) was used. Box was separated into three sections using a porous divider. The first section contained five WT Emitters, the second section contained 15 WT Arabidopsis plants, and the third section contained two VSP1-Receivers. Twenty DM moths were added to the Emitter section after the first frame was recorded. Recording was conducted for 20-hours in one-hour intervals. Fluorescent signal intensities of fully developed, non-overlapped whole leaves were measured. The brightest two leaves were analyzed for each plant. Statistics and graphs were done using and R package ().
Gas chromatography mass spectrometry
Volatile components were collected via passive absorption onto a Monotrap (RGC18 TD, GL-Science, Tokyo, Japan) for three hours at room temperature. After the volatiles were absorbed, samples were transferred to a 1.5-ml vial and stored at − 20 °C until analysis. Headspace volatiles collected using the Monotrap were analyzed by gas chromatography-mass spectrometry (GC–MS, GC: Agilent 7890A/MS5977B MSD, Agilent Technologies, CA, USA) with an HP-5MS UI capillary column (30 m, 0.25-mm ID, 0.25-μm film thickness; Agilent Technologies) equipped with a thermal-desorption system, cooled injection, and cold trap (Gerstel). The GC was maintained at 40 °C for 3 min., increased to 150 °C at a rate of 10 °C/min., then to 280 °C at 20 °C/min., and held at this temperature for five minutes. Helium was the carrier gas at a constant flow of 1.1 ml/min. The compounds were tentatively identified using data contained in the NIST Mass Spectral Library, 2017 release. GC-MS data were deconvoluted using Unknowns Analysis software (ver. B.09.00, Agilent Technologies) and aligned using Mass Profinder Professional (ver. 14.9, Agilent Technologies). Only entities present in at least 60% of replicates from one condition were included in subsequent analyzes. To determine changes in components in each condition, the data was subjected to principal component analysis using software R (version 4.1.0). To determine which components varied between conditions, we performed volcano plot analysis to compare with and without infested Emitter (P value 0.05, fold change 2) in the Mass Profinder Professional software. Compound identification was performed by comparing mass spectra to the NIST 2017 Library.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
NK: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Visualization, Writing – original draft, Writing – review & editing. MH: Data curation, Formal analysis, Methodology, Visualization, Writing – review & editing, Writing – original draft. TU: Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. BL: Conceptualization, Writing – original draft, Writing – review & editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. Supported by: Canon Foundation; KAKENHI (C) 21K05593; KAKENHI Grant-in-Aid for Exploratory Research 24K21862; Takahashi Industrial and Economic Research Foundation; Ichimura Foundation for New Technology; Fuji Foundation for Protein Research; Murata Science Foundation; Amano Institute of Technology; Asahi Glass Foundation; KDDI Foundation; Hitachi Global Foundation, and the Toyota Physical and Chemical Research Institute; Konno &Lester Foundation; Iijima Memorial Foundation for the Promotion of Food Science and Technology; University-Industry Cooperation Strengthening in Tsukuba; Tateisi Science and Technology Foundation; Terumo Life Science Foundation; Suzuken Memorial Foundation; Kobayashi Foundation.
Acknowledgments
We thank Shigeyuki Betsuyaku (Ryukoku University) for providing VSP1-YFP seeds, Masatsugu Toyota (Saitama University) for providing Gcamp3 and Gcamp3/glr3.3glr3.6 seeds, and Takumi Higaki (Kumamoto University) for advice on imaging analysis. Tatsuji Morishita and Kosuke Sugahara (Leica Microsystems) assisted with microscopy. The Engineering Workshop Division (University of Tsukuba) assisted with materials. Aki Sugita assisted with research. Keiko Koda and Ayako Inada (Kinoshita Lab) provided invaluable support.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2026.1829872/full#supplementary-material
Supplementary Figure 1Fluorescent signals from VSP1-Receiver were dependent on insect damage and GLR genes. VSP1-Receiver failed to emit a clear fluorescent signal without insects (top). Armyworm-infested Emitter with glr3.3/glr3.6 mutations did not induce distinct fluorescent signals in VSP1-Receiver (bottom). Scale bar, 5 mm.
Supplementary Figure 2Insect damage in Emitter was measured using auto fluorescent imaging. Insect damage was visualized using chlorophyll autofluorescence using a Texas Red filter. Auto fluorescent images were used to quantify insect damage (Figure 1b). Scale bar, 1 cm.
Supplementary Figure 3Plant communication under DB moth attack is detected under ventilated conditions. Left, Fluorescence from VSP1-Receiver without ventilation. Right, Fluorescence from VSP1-Receiver with ventilation.
Supplementary Figure 4GLR mutant Gcamp3-Receiver did not respond to WT Emitter. Gcamp3-Receiver with glr3.3 and glr3.6 mutations was exposed to WT Emitter infested with diamondback moth (DB moth) and armyworm. Receivers with double mutations failed to display noticeable fluorescent signals. Scale bar, 1 mm.
Supplementary Figure 5Gcamp3-Receiver does not display an increase of [Ca2+lcyt area in the midvein when exposed to infested Emitter with glr3.3/glr3.6 mutations scale bar, 1 mm.
Movie S1Exposure to DB moth-damaged Emitter triggers fluorescent signal in VSP1-Receiver. Scale bar, 5 mm. (corresponding to Figure 1b top panel).
Movie S2Exposure to DB moth-damaged Emitter triggers fluorescent signal in VSP1-Receiver. first frame is recorded without DB moth. Scale bar: 5 mm. (corresponding to Figure 1d).
Movie S3Exposure to armyworm-damaged Emitter triggers fluorescent signal in VSP1-Receiver. first frame is recorded without armyworm. Scale bar: 5 mm. (corresponding to Figure 1d).
Movie S4Movement of [Ca2+]cyt increase extends toward the tip of the leaf after exposure to DB moth-damaged Emitter. Receiver [Ca2+]cyt was visualized using transgenic Arabidopsis expressing GCaMP3, a protein-based fluorescent calcium sensor. Scale bar: 5 mm. (corresponding to Figure 2a).
Movie S5Movement of [Ca2+]cyt increase extends toward the tip of the leaf after exposure to armyworm-damaged Emitter. Receiver [Ca2+]cyt was visualized using transgenic Arabidopsis expressing GCaMP3, a protein-based fluorescent calcium sensor. Scale bar: 5 mm. (corresponding to Figure 2a).
References
1
ArataniY.UemuraT.HagiharaT.MatsuiK.ToyotaM. (2023). Green leaf volatile sensory calcium transduction in Arabidopsis. Nat. Commun.14, 6236. doi: 10.1038/s41467-023-41589-9
2
ArimuraG.OzawaR.ShimodaT.NishiokaT.BolandW.TakabayashiJ. (2000). Herbivory-induced volatiles elicit defence genes in lima bean leaves. Nature406(6795), 512–515.
3
ArimuraG.UemuraT. (2024). Cracking the plant VOC sensing code and its practical applications. Trends Plant Sci. doi: 10.1016/j.tplants.2024.09.005
4
BergerS.Mitchell-OldsT.StotzH. U. (2002). Local and differential control of vegetative storage protein expression in response to herbivore damage in Arabidopsis thaliana. Physiol. Plant114, 85–91. doi: 10.1046/j.0031-9317.2001.1140112.x
5
BetsuyakuS.KatouS.TakebayashiY.SakakibaraH.NomuraN.FukudaH. (2018). Salicylic acid and jasmonic acid pathways are activated in spatially different domains around the infection site during effector-triggered immunity in Arabidopsis thaliana. Plant Cell Physiol.59, 439. doi: 10.1093/pcp/pcx181
6
BirkettM. A.ChamberlainK.GuerrieriE.PickettJ. A.WadhamsL. J.YasudaT. (2003). Volatiles from whitefly-infested plants elicit a host-locating response in the parasitoid, Encarsia formosa. J. Chem. Ecol.29, 1589–1600. doi: 10.1023/a:1024218729423
7
BrossetA.BlandeJ. D. (2021). Volatile-mediated plant–plant interactions: volatile organic compounds as modulators of receiver plant defence, growth, and reproduction. J. Exp. Bot.73, 511–528. doi: 10.1093/jxb/erab487
8
CaldwellE.ReadJ.SansonG. D. (2015). Which leaf mechanical traits correlate with insect herbivory among feeding guilds? Ann. Bot.117, 349–361. doi: 10.1093/aob/mcv178
9
ChenY.MaoJ.ReynoldsO. L.ChenW.HeW.YouM.et al. (2020). Alyssum (Lobularia maritima) selectively attracts and enhances the performance of Cotesia vestalis, a parasitoid of Plutella xylostella. Sci. Rep.10, 6447. doi: 10.1038/s41598-020-62021-y
10
DuanH.HuangM. Y.PalacioK.SchulerM. A. (2005). Variations in CYP74B2 (hydroperoxide lyase) gene expression differentially affect hexenal signaling in the Columbia and Landsberg erecta ecotypes of Arabidopsis. Plant Physiol.139, 1529–1544. doi: 10.1104/pp.105.067249
11
ErbM.ReymondP. (2019). Molecular interactions between plants and insect herbivores. Annu. Rev. Plant Biol.70. doi: 10.1146/annurev-arplant-050718-095910
12
ErrardA.UlrichsC.KühneS.MewisI.DrungowskiM.SchreinerM.et al. (2015). Single- versus multiple-pest infestation affects differently the biochemistry of tomato (Solanum lycopersicum 'Ailsa Craig'). J. Agric. Food. Chem.63, 10103–10111. doi: 10.1021/acs.jafc.5b03884
13
GokilaG.PremalathaK.ShanmugamP. S.Suganya KannaS.PradeepS. (2024). Herbivore-induced plant volatiles in rice: a natural defense mechanism shaping arthropod community. Appl. Ecol. Environ. Res.22, 3047–3058. doi: 10.15666/aeer/2204_30473058
14
GongQ.WangY.HeL.HuangF.ZhangD.WangY.et al. (2023). Molecular basis of methyl-salicylate-mediated plant airborne defence. Nature622, 139–148. doi: 10.1038/s41586-023-06533-3
15
HuL.YeM.ErbM. (2019). Integration of two herbivore-induced plant volatiles results in synergistic effects on plant defence and resistance. Plant Cell Environ.42, 959–971. doi: 10.1111/pce.13443
16
KarbanR. (2021). Plant communication. Annu. Rev. Ecol. Evol. Syst.52, 1–24. doi: 10.1146/annurev-ecolsys-010421-020045
17
KarbanR.ShiojiriK.HuntzingerM.McCallA. C. (2006). Damage-induced resistance in sagebrush: volatiles are key to intra- and interplant communication. Ecology87, 922–930. doi: 10.1890/0012-9658(2006)87[922:drisva]2.0.co;2
18
KarbanR.ShiojiriK.IshizakiS.WetzelW. C.EvansR. Y. (2013). Kin recognition affects plant communication and defence. Proc. Biol. Sci.280, 20123062. doi: 10.1098/rspb.2012.3062
19
KarbanR.YangL. H.EdwardsK. F. (2014). Volatile communication between plants that affects herbivory: a meta-analysis. Ecol. Lett.17, 44–52. doi: 10.1111/ele.12205
20
KinoshitaN.BetsuyakuS. (2018). The effects of Lepidopteran oral secretion on plant wounds: a case study on the interaction between. Plant Bio/Technol. (Tokyo).35, 237–242. doi: 10.5511/plantbiotechnology.18.0528a
21
KinoshitaN.WangH.KasaharaH.LiuJ.MacphersonC.MachidaK.et al. (2012). IAA-Ala Resistant3, an evolutionarily conserved target of miR167, mediates Arabidopsis root architecture changes during high osmotic stress. Plant Cell24, 3590–3602. doi: 10.1105/tpc.112.097006
22
KinoshitaN.SugitaA.LustigB.BetsuyakuS.FujikawaT.MorishitaT. (2019). Automating measurements of fluorescent signals in freely moving plant leaf specimens. Plant Bio/Technol. (Tokyo).36, 7–11. doi: 10.5511/plantbiotechnology.18.1002a
23
KuramitsuK.VicencioE. J. M.KainohY. (2019). Differences in food plant species of the polyphagous herbivore Mythimna separata (Lepidoptera: Noctuidae) influence host searching behavior of its larval parasitoid, Cotesia kariyai (Hymenoptera: Braconidae). Arthropod-Plant. Interact.13, 49–55. doi: 10.1007/s11829-018-9659-0
24
LiC.SchilmillerA. L.LiuG.LeeG. I.JayantyS.SagemanC.et al. (2005). Role of beta-oxidation in jasmonate biosynthesis and systemic wound signaling in tomato. Plant Cell17, 971–986. doi: 10.1105/tpc.104.029108
25
LiangX.QianR.WangD.LiuL.SunC.LinX. (2022). Lipid-derived aldehydes: new key mediators of plant growth and stress responses. Biology11, 1590. doi: 10.3390/biology11111590
26
MousaviS. A.ChauvinA.PascaudF.KellenbergerS.FarmerE. E. (2013). GLUTAMATE RECEPTOR-LIKE genes mediate leaf-to-leaf wound signalling. Nature500, 422–426. doi: 10.1038/nature12478
27
NagashimaA.et al. (2019). Transcriptional regulators involved in responses to volatile organic compounds in plants. J. Biol. Chem.294, 2256–2266. doi: 10.1074/jbc.ra118.005843
28
NguyenC. T.KurendaA.StolzS.ChételatA.FarmerE. E. (2018). Identification of cell populations necessary for leaf-to-leaf electrical signaling in a wounded plant. Proc. Natl. Acad. Sci. U.S.A.115, 10178–10183. doi: 10.1073/pnas.1807049115
29
PengT.ThornK.SchroederT.WangL.TheisF. J.MarrC.et al. (2017). A BaSiC tool for background and shading correction of optical microscopy images. Nat. Commun.8, 14836. doi: 10.1038/ncomms14836
30
SchumanM. C.BaldwinI. T. (2016). The layers of plant responses to insect herbivores. Annu. Rev. Entomol.61, 373–394. doi: 10.1146/annurev-ento-010715-023851
31
SpitzerM.WildenhainJ.RappsilberJ.TyersM. (2014). BoxPlotR: a web tool for generation of box plots. Nat. Methods11, 121–122. doi: 10.1038/nmeth.2811
32
Team, R.C. (2019). R: Language and environment for statistical computing (Vienna, Australia: Foundation for Statistical Computing). Available online at: https://www.R-project.org/ (Accessed May 28, 2018).
33
ToyotaM.SpencerD.Sawai-ToyotaS.JiaqiW.ZhangT.KooA. J.et al. (2018). Glutamate triggers long-distance, calcium-based plant defense signaling. Science361, 1112–1115. doi: 10.1126/science.aat7744
34
TurlingsT. C. J.ErbM. (2018). Tritrophic interactions mediated by herbivore-induced plant volatiles: mechanisms, ecological relevance, and application potential. Annu. Rev. Entomol.63, 433–452. doi: 10.1146/annurev-ento-020117-043507
35
WangL.ErbM. (2022). Volatile uptake, transport, perception, and signaling shape a plant's nose. Essays. Biochem. doi: 10.1042/ebc20210092
36
WinterD.VinegarB.NahalH.AmmarR.WilsonG. V.ProvartN. J. (2007). An "Electronic Fluorescent Pictograph" browser for exploring and analyzing large-scale biological data sets. PloS One2, e718. doi: 10.1371/journal.pone.0000718
37
YasaV.SurosheS. S.NebapureS. M. (2024). Behavioral response of zigzag ladybird beetle Cheilomenes sexmaculata to the HIPVs induced by cotton aphid, Aphis gossypii. Arthropod-Plant. Interact.18, 771–780. doi: 10.1007/s11829-024-10087-0
38
YiC.TengD.XieJ.TangH.ZhaoD.LiuX.et al. (2023). Volatiles from cotton aphid (Aphis gossypii) infested plants attract the natural enemy Hippodamia variegata. Front. Plant Sci.14. doi: 10.3389/fpls.2023.1326630
39
ZhaiR.ZhangH.XieY.ZhangS.ZhouF.DuX.et al. (2025). Naturally impaired side-chain shortening of aromatic 3-ketoacyl-CoAs reveals the biosynthetic pathway of plant acetophenones. Nat. Plants11, 1903–1919. doi: 10.1038/s41477-025-02082-x
40
ZhangL.ZhangF.MelottoM.YaoJ.HeS. Y. (2017). Jasmonate signaling and manipulation by pathogens and insects. J. Exp. Bot.68, 1371–1385. doi: 10.1093/jxb/erw478
41
ZubkovF. I.KouznetsovV. V. (2023). Traveling across life sciences with acetophenone-a simple ketone that has special multipurpose missions. Molecules28. doi: 10.3390/molecules28010370
Summary
Keywords
wide-field non-invasive real-time fluorescent imaging, plant communication, green leaf volatile (GLV), volatile organic compound (VOC), herbivore-induced plant volatile (HIPV), calcium signal, anti-herbivory insect stress responsive gene expression, Arabidopsis
Citation
Kinoshita N, Hirakawa MS, Uehara T and Lustig B (2026) Revisiting volatile organic compounds’ role in plant communication using real-time bioimaging. Front. Plant Sci. 17:1829872. doi: 10.3389/fpls.2026.1829872
Received
13 March 2026
Revised
18 April 2026
Accepted
23 April 2026
Published
18 June 2026
Volume
17 - 2026
Edited by
Tuo Zeng, Guizhou Normal University, China
Reviewed by
Jiang Shi, Chinese Academy of Agricultural Sciences, China
Mukesh Kumar Meena, National Institute of Plant Genome Research (NIPGR), India
Updates
Copyright
© 2026 Kinoshita, Hirakawa, Uehara and Lustig.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Natsuko Kinoshita, kinoshita.natsuko.gf@u.tsukuba.ac.jp
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.