An artificial metalloenzyme biosensor can detect ethylene gas in fruits and Arabidopsis leaves

Kenward Vong; Shohei Eda; Yasuhiro Kadota; Igor Nasibullin; Takanori Wakatake; Satoshi Yokoshima; Ken Shirasu; Katsunori Tanaka

doi:10.1038/s41467-019-13758-2

. 2019 Dec 17;10:5746. doi: 10.1038/s41467-019-13758-2

An artificial metalloenzyme biosensor can detect ethylene gas in fruits and Arabidopsis leaves

Kenward Vong ^1,^#, Shohei Eda ^1,^2,^#, Yasuhiro Kadota ³, Igor Nasibullin ¹, Takanori Wakatake ³, Satoshi Yokoshima ⁴, Ken Shirasu ³, Katsunori Tanaka ^1,^2,^5,^6,^✉

PMCID: PMC6917813 PMID: 31848337

Abstract

Enzyme biosensors are useful tools that can monitor rapid changes in metabolite levels in real-time. However, current approaches are largely constrained to metabolites within a limited chemical space. With the rising development of artificial metalloenzymes (ArM), a unique opportunity exists to design biosensors from the ground-up for metabolites that are difficult to detect using current technologies. Here we present the design and development of the ArM ethylene probe (AEP), where an albumin scaffold is used to solubilize and protect a quenched ruthenium catalyst. In the presence of the phytohormone ethylene, cross metathesis can occur to produce fluorescence. The probe can be used to detect both exogenous- and endogenous-induced changes to ethylene biosynthesis in fruits and leaves. Overall, this work represents an example of an ArM biosensor, designed specifically for the spatial and temporal detection of a biological metabolite previously not accessible using enzyme biosensors.

Subject terms: Biocatalysis, Sensors and probes, Plant biotechnology, Plant hormones

Existing methods to detect ethylene in plant tissue typically require gas chromatography or use ethylene-dependent gene expression as a proxy. Here Vong et al. show that an artificial metalloenzyme-based ethylene probe can be used to detect ethylene in plants with improved spatiotemporal resolution.

Introduction

Enzyme-based chemical biosensors for diagnostic purposes still remains an underdeveloped research area. One of the major issues impeding progress is that most, if not all, enzyme biosensors are derived from existing natural enzymes, rather than methodically designed. As such, there is still a large chemical space that remains inaccessible based on current developmental approaches to enzyme biosensors.

One challenging metabolite to detect is ethylene (IUPAC name: ethene), a well-characterized phytohormone that plays a major role in regulating many aspects of plant growth, immunity, development, and senescence^1,2. In literature, two systems are known to control ethylene biosynthesis in plants³. System 1 production, which is ethylene autoinhibitory⁴, is applicable to all plants and is mainly responsible for controlling basal ethylene levels for normal vegetative growth. Under environmental or developmental stimuli, ethylene levels in climacteric fruit can dramatically increase via system 2 production, which is an ethylene autocatalytic process^5–7. In literature, exogenous sources of ethylene have been shown to greatly accelerate the processes of abscission and ripening^8–11.

Given its biological importance, improved diagnostic tools for ethylene gas would be invaluable to agricultural research to help better study ethylene-dependent pathways during stress response, hormone treatment, and different developmental stages in plants. However, since ethylene is a small gaseous olefin that freely diffuses between membranes under physiological conditions, there are many obstacles to overcome in order to develop working systems. Current methods to assay ethylene in plants have largely employed analytical techniques (such as gas chromatography, electrochemical sensors, and laser-based techniques¹²), or have utilized plants genetically encoded with ethylene-inducible reporters (such as EBS:GUS^13,14). As an alternative method for ethylene detection, interest has recently begun to shift towards developing chemical-based probes. Through this approach, topical application onto plant tissues should in theory allow ethylene levels to be monitored in a spatiotemporal manner.

In one of the earliest examples of a chemical-based ethylene probe, the Burstyn group developed poly(vinyl phenyl ketone) (PVPK) polymer films. In the presence of ethylene, coordination with impregnated silver ions could lead to the proportional decrease of photoluminescence¹⁵. Later, the Swager group developed an alternative system where the quenched fluorescence of conjugated polymers by copper(I) scorpionate complexes could be revived by displacement with ethylene¹⁶. Another notable example is from the Kodera group, where a silver(I)–anthracene complex was constructed around a crucial metal–arene interaction. Upon exposure to ethylene, interconversion from a metal–arene to metal–ethylene interaction led to a change in the anthracene absorption and fluorescence spectra¹⁷. Finally, during the preparation of this manuscript, two reports were published highlighting an elegant strategy using profluorescent ruthenium metal complexes^18,19. In the presence of ethylene, turn-on fluorescence can be triggered via cross metathesis to release a BODIPY-based dye. In particular, the Michel group showed the detection of diffused ethylene from live cell cultures incubated with ripening fruit¹⁸. Although a clear upgrade in terms of biocompatibility compared to previous strategies, the direct imaging of fruits or plants was not shown in this report.

Among all current examples of ethylene-sensing probes, one common theme is the use of water-insoluble metal catalysts. For instance, besides the Michel report, all studies have heavily relied on the use of organic solvent. Furthermore, none of these methods have been able to test ethylene directly from plant tissue; instead relying on exogenous ethylene sources. It can be surmised that in the presence of water-based plant samples, metal complexes may aggregate, potentially lowering their reactivity. In addition, metal quenching in complex biological environments is also an issue. Numerous reports in literature have identified high concentrations of glutathione in plants²⁰. As a result, for metals like ruthenium, inactivation by low molecular weight thiols becomes an added challenge. In order to overcome these practical limitations, what is currently lacking is a means to confer biocompatibility to metal complex catalysts.

Artificial metalloenzymes (ArM) are the result of incorporating abiotic metals complexes into a protein scaffold, which can often impart enhanced biofunctionality to the anchored metal catalysts. In current literature, a host of different protein scaffolds have been adapted as ArMs, some of which include streptavidin^21–26, prolyl oligopeptidase^27,28, myoglobin^29,30, CeuE³¹, ADORA2A³², nitrobindin³³, among many others. Recently, our group explored the use of human serum albumin-based ArMs, which was found to impart two important biological effects for the anchored metal catalyst³⁴. First, the typically insoluble ruthenium complex catalyst (linked to a coumarin-ligand anchor) can become soluble in aqueous conditions with the addition of albumin. This is likely the effect of the hydrophobic-binding pocket on albumin, which is well known to bind to many hydrophobic drug molecules³⁵. And second, due to the negatively charged surface of albumin at physiological pH³⁶, charged metabolites were found to be prevented from entering the hydrophobic-binding pocket. As such, metal catalysts (e.g. ruthenium) bound inside the hydrophobic-binding pocket could be resistant to inactivation from biological thiols (i.e. glutathione). To highlight the biocompatibility of albumin-based ArMs bound with ruthenium (alb–Ru), investigations were then further done to develop an anticancer prodrug therapy based on activation via ring-closing metastasis (RCM)³⁴. In this case, alb–Ru was furnished with cancer cell-targeting complex N-glycans^37–41, which was then used to successfully activate a RCM-drug precursor against various cancer lines (e.g. HeLa, A549, SW620).

Not only restricted to drug therapy, the chemoselective nature of abiotic metal-containing ArMs can also open the door for enzyme biosensor applications. Although metal-based diagnostic probes have been well studied in literature, many of them do not directly engaged with water-based specimens under organic solvent-free conditions. As such, one promising approach is to develop enzyme biosensors based on albumin ArMs to confer water solubility and biocompatibility to metal complexes used for diagnostic purposes.

The principal goal of this paper is to demonstrate that ArMs can be adapted as enzyme biosensors to detect ethylene produced from real world biological samples. The significance of this work is that when compared to current metal-based ethylene probes, it would be one of the first to show applicability with samples directly obtained from fruits and leaves. And when compared to other ethylene detection methods (e.g. GC, electrochemical sensors), it presents a better way to analyze samples in a spatiotemporal manner.

The strategy to develop the ArM ethylene probe (AEP) is outlined in Fig. 1. Using the hydrophobic-binding pocket of albumin, the bound metal complex is composed of three key components: the fluorophore 7-diethylaminocoumarin (DEAC), the second generation Hoveyda–Grubbs catalyst, and the olefin-containing DABCYL quencher. In its normal state, the DABCYL quencher suppresses DEAC fluorescence via Förster resonance energy transfer (FRET) interactions. However, in the presence of ethylene gas, Hoveyda–Grubbs catalyzed cross metathesis will occur, thereby releasing the olefin-containing DABCYL quencher. As a result, detectable levels of fluorescence can be produced. To test this hypothesis, the following study investigates the ability of AEP to detect ethylene in biological samples that include fruits and plant leaves.

Results

Preparation of ethylene-sensing ArM

The steps to prepare AEP are outlined in Fig. 2a. Previously in the construction of the albumin ArM (alb–Ru), a DEAC–Ru complex was utilized where a DEAC moiety was used as a ligand anchor to direct the second generation Hoveyda–Grubbs catalyst towards the hydrophobic-binding pocket of albumin. The fluorescence emitted by DEAC itself is highly sensitive to the polarity of the surrounding solvent. As shown in Fig. 2b, the quantum yield of DEAC–Ru increases by roughly 20-fold in the transition from a polar environment (10% dioxane/H₂O) to a non-polar environment (60% dioxane/H₂O). As such, alb–Ru generally exists as a fluorescent and water-soluble ArM, prepared as described in the “Methods” section.

In literature, DEAC and DABCYL have previously been identified as a FRET donor pair⁴². Therefore, the approach undertaken in this study to prepare the AEP probe is based on reacting alb–Ru with the olefin-containing DABCYL quencher, as described in the “Methods” section. The resulting RuQ complex found inside the albumin-binding pocket exhibits significantly lower levels of fluorescence due to quenching, which is evident when comparing the observed fluorescence between alb–Ru and the AEP probe in Fig. 2c. Furthermore, no major structural changes to the protein complexes were identified during preparation since their circular dichroism (CD) spectra overlapped perfectly (Fig. 2d).

Ethylene-reactivity studies

The theory behind AEP is that biosynthesized ethylene produced by plants will react with the bound ruthenium catalyst, thereby displacing the DABCYL quencher to activate a fluorescent signal. Given the competition with the more reactive ethylene substrate, and the added obstacle of re-entering the albumin-binding pocket under biological conditions, it is surmised that reversible reactivity of the DABCYL quencher will only have a mild influence during bioimaging.

To investigate AEP reactivity, a series of in vitro studies were performed. First, dose-dependent response curves were obtained for RuQ only (Fig. 2e). These experiments were done by injecting varying volumes of ethylene gas (50–1000 μl) into an airtight cuvette. After incubation for 1 min, the change in fluorescence was quantified. For experiments where RuQ was dissolved in pure organic solvent (100% THF), reactivity was shown to be comparable to contemporary examples of ruthenium-based ethylene probes^18,19. The limit of detection (LOD) was calculated to be 34.4 μl of injected ethylene, which corresponds to about 27 ppm in air. It should be noted that since physiological levels of ethylene produced during ripening are typically <1 ppm, incubation periods for these probes would thus need to exceed times generally analogous with “real-time” detection (within 1 min). In the case where experiments were performed for RuQ in an aqueous environment, reactivity was instead observed to become greatly diminished due to two main factors. First, it is an expected occurrence that olefin metathesis using the Hoveyda–Grubbs catalyst proceeds with lower reactivities under aqueous conditions. And second, a limitation of the experimental setup does not properly account for the poor solubility of ethylene in water. To highlight this, NMR studies were done using similar air-to-liquid volume ratios (Supplementary Fig. 1). With 1 ml of ethylene injected into pure solvent (100% THF-d8), the dissolved concentration was calculated to be roughly 1 mM. However, under aqueous conditions (25% or 10% THF-d8/D₂O), no peaks corresponding to ethylene could be detected.

In order to design an experimental setup that can ensure an adequate level of ethylene is present under aqueous conditions to test AEP reactivity, the following assumptions were made. According to Henry’s gas law, the amount of dissolved gas in a liquid is proportional to its partial pressure above the liquid. As such, one setup could see a closed system (with the cuvette) containing water that is purged and fitted with a balloon-containing ethylene gas. In this manner, it can be assumed that the only gas present is ethylene. Since the pressure of a balloon does not significantly deviate from 1 atm, it can be assumed that the total pressure of ethylene gas present is equivalent to its partial pressure. Using a Henry’s law constant of 5.98 × 10⁻³ M atm⁻¹, the calculated concentration of dissolved ethylene in water would thus be approximately 6 mM, or 167 ppm. To initiate time-dependent reactivity studies, AEP was then injected into the ethylene-filled cuvette and monitored over time. Shown in Fig. 2f, a significant time-dependent increase in fluorescence was thus observed in the AEP/ethylene mixture compared to controls (RuQ/ethylene and AEP only).

Not only does ethylene has one of the highest reactivities for olefin metathesis⁴³, but its smaller molecular size should allow it to enter the albumin-binding pocket with better ease compared to other plant metabolites, such as unsaturated molecules known as terpenes. To determine whether there is a chance for significant cross-reactivity with AEP, various terpenes (e.g. pinene, limonene, terpinolene, myrcene, citronellol, and farnesol) were tested utilizing similar conditions to the previous ethylene experiments (final terpene concentration of 6 mM). Shown in Fig. 2g, the overall reactivities of the tested terpenes were found to be significantly lower than with ethylene gas. However, it should be noted that in cases containing terminal unsaturated alkenes (such as myrcene and limonene), moderate activity was observed. As such, additional controls may be required when testing samples like cannabis (myrcene-abundant) and citrus fruits (limonene-abundant).

Spatial detection of ethylene in fruits

Climacteric fruits typically undergo autocatalytic ethylene (system 2) production during endogenous processes, such as ripening, and also in response to exogenous stimuli, such as wounding stress and pathogen infection^44,45. In this study, the spatial capabilities of the AEP probe was first investigated in response to endogenous ethylene. During ripening, studies have observed that kiwifruit exhibit an increase in ethylene production primarily through upregulation of ACS isogenes in the outer pericarp⁴⁶. As shown in Fig. 3a and Supplementary Figs. 2–9, imaging experiments in kiwifruits using AEP focused on observing changes in ethylene expression of various organelles (outer pericarp, locule, and columella) at different stages of development (unripe vs. ripening). Summarized in Fig. 3b, a significant increase in fluorescence was detected in the outer pericarp from the transition of unripe to ripe fruit. On the other hand, fluorescent changes in the locule and columella of the kiwifruits did not occur at significant levels. As a note, it was observed that the tissues between individual locules generally exhibited an increase in fluorescence. Since literature has shown that kiwifruit seeds or surrounding tissues may play a role in ethylene biosynthesis (parthenocarpic kiwifruit are shown to have decreased levels of ethylene production due to suppressed expression of ACS⁴⁷), a more thorough analysis may be of interest for future studies. Overall, with these results, the use of AEP presents itself as a promising tool to monitor the spatial expression of ethylene for fruits during ripening and development.

Fig. 3 — a Fluorescent imaging of a ripening kiwi fruit, which was sectioned to display the outer pericarp, locules, and part of the columella. Multiple images were obtained at ×4 magnification and were joined together via image stitching. b The measured change in fluorescence of the pericarp, locule, and the columella of kiwifruit (unripe or ripe) was taken between the 1 and 24 h timepoints. As shown, a significant increase in **AEP**-detected ethylene can be observed in the pericarp during the process of ripening. For each condition (unripe or ripe), two whole fruits were used to provide four different sections for investigation. Replicates values for the outer pericarp (n = 24), locule (n = 12), and the columella (n = 4) were obtained. Statistical analysis was performed using a paired sample t-test. *P < 0.03, **P < 0.002, ***P < 0.0002, ****P < 0.0001, ns = not significant. Source data are provided as a Source Data file.

The ethylene biosynthetic pathway in plants (Fig. 4a) is mainly composed of three enzymes that convert methionine into ethylene: SAM synthetase (SAMS), ACC synthase (ACS), and ACC oxidase (ACO)⁴⁸. Although ACS is often regarded as the rate-limiting step of ethylene biosynthesis⁴⁹, recent research has indicated that ACO may also be rate limiting during post-climacteric ripening of tomatoes (and likely other climacteric fruit)^50,51. Of relative importance to this study, pyrazinamide (PZA) was recently found to be an inhibitor of ethylene biosynthesis through inhibition of ACO⁵². With consideration of this pathway, this study generally relied on using ACC as a stimulant of ethylene production, and PZA as a repressor of ethylene production.

In another investigation, the ability of AEP to respond to changes in ethylene biosynthesis due to external stimuli was carried out. Cotton balls soaked in either a solution of ACC or PZA were topically applied to sections of fruit flesh (hypanthium) from Asian pears. In order to ensure uniform hydration of the sample, water-infused cotton balls were placed in an equally spaced arrangement depicted in Fig. 4b. Following a 5 h incubation period, cotton balls were removed and the samples were then placed on plates preloaded with AEP. Fluorescence microscopy-imaging results obtained after 18 h are shown in Fig. 4c, d and Supplementary Figs. 10 and 11. In this study, the inner area is defined as the tissue roughly within a 15 mm radius from the origin of stimulant (ACC or PZA) application. On the other hand, the outer area is the tissue area exposed to water (as a control). As summarized in Fig. 4e, results clearly show differences in inner area fluorescence compared to outer area fluorescence. For example, exposure to ACC was shown to moderately increase inner area fluorescence by about 20%. Alternatively, exposure to PZA gave the opposite effect by greatly decreasing inner area fluorescence by up to 60%. Although promising, it should be noted that there are major experimental challenges associated with studying spatial changes in ethylene biosynthesis due to external stimuli; the main culprit being the issue of diffusion. Without a strong external inducer, diffusion of the stimulant greatly decreases spatial resolution. This is especially problematic for samples with smaller surface areas, as similar experiments could not be reproduced with smaller plant leaves.

Temporal detection of ethylene in fruits

To investigate the temporal detection capabilities of the AEP probe across a variety of different fruits, the general protocol outlined in Fig. 5a was followed. To begin, small sections of fruit measuring roughly 10 mm × 8 mm in size were prepared. These samples were then incubated with varying concentrations of ACC or PZA for 3 h at room temperature, before being placed onto chamber slides pre-loaded with AEP. Fluorescence analysis was then carried out at specific time intervals.

Fig. 5 — a In general, samples were prepared from slices of fruit flesh cut into ~10 mm × 8 mm segments. Following a 3 h incubation either in solutions of ACC, PZA, or water (as a control), samples were then removed and placed onto chamber slides preloaded with **AEP** probe (10 µl of a 400 µM solution). Using an inverted microscope, samples were monitored at specific time intervals. To examine the difference in ethylene production across different apple cultivars, fluorescence was monitored over time for Golden Delicious, Jazz, and Fuji apples b. A summary and statistical comparison between the 1 and 20 h timepoints for each apple cultivar are also shown c–e, as well as samples images of Golden Delicious apples (water-control) over various timepoints f. Statistical analysis was performed using a one-way ANOVA with Tukey’s multiple comparisons test. *P < 0.03, **P < 0.002, ***P < 0.0002, ****P < 0.0001, ns = not significant. Error is represented as s.d. of three independent experiments. Source data are provided as a Source Data file.

In literature, internal ethylene levels have been shown to vary among different types of apple cultivars^53–55. For instance, Fuji apples are known to produce lower levels of ethylene gas compared to other cultivars⁵⁵. To test the capacity of AEP to detect these differences, time-based studies were carried out using apple cultivars that included Golden Delicious, Jazz, and Fuji apples (Fig. 5b–f and Supplementary Figs. 12–26). As summarized in Fig. 5b, data clearly shows that Fuji apples produce lower levels of ethylene compared to other cultivars over time. Furthermore, this trend was also observed during supplementation studies using ACC or PZA (Fig. 5c–e).

Additionally, other fruits were also examined in this study using the AEP probe, which included kiwifruit, Asian pears, and Muscat grapes (Fig. 6 and Supplementary Figs. 27–41). For climacteric fruits like kiwifruit and Asian pears^56,57, both displayed time-dependent ethylene production as expected. Interestingly, samples from Muscat grapes were also tested and produced ethylene in a time-dependent manner. Although generally classified as non-climacteric, studies have shown grapes have the capacity to produce ethylene gas; reaching its peak during grape maturation⁵⁸. Furthermore, detectable levels of ACS and ACO gene expression can be found long after development and ripening⁵⁹. As a step to further check AEP sensitivity, negative controls were carried out with ethylene non-producing vegetables like carrots and red bell peppers (Supplementary Figs. 42–52). As expected, these cases produced non-significant levels of ethylene over similar time periods.

Ethylene detection in plants

To investigate the efficacy of AEP detection in plants, the small flowering plant Arabidopsis thaliana (Brassicaceae family) was chosen as the model organism. Focusing specifically on imaging of clear epidermal peels, comparative studies were carried out using a wide range of small molecules and plant mutants (Fig. 7 and Supplementary Figs. 53 and 54).

For this study, the Col-0 ecotype of A. thaliana served as the model wild-type plant. Also used were various mutants; acs1/2/6/4/5/9/7/11 and eto1-1. The mutant acs1/2/6/4/5/9/7/11, which contains knock outs of eight functional ACS genes, was chosen because it exhibits dramatically reduced levels of ethylene that persist even during pathogen invasion^60,61. This is due to the key role that ACS plays in the ethylene biosynthetic pathway (Fig. 4a). Another of the chosen mutants is eto1-1, which is characterized by ethylene overproduction⁶². In this case, the eto1-1 mutation results in the stabilization of type II ACS, thereby preventing proteasomal degradation of ACS⁶³.

Shown in Fig. 7b are the images obtained for Col-0 incubated with and without AEP at room temperature. As quantified in Fig. 7e, a significant increase in fluorescence was observed, thereby validating the use of AEP for ethylene detection in A. thaliana epidermal peels. As a positive control, ethylene production was contrasted with Col-0 exogenously stimulated by ACC incubation. As expected, AEP-based ethylene detection showed a significantly higher increase in detected fluorescence compared to the wild type Col-0.

To further evaluate the sensitivity of the AEP probe to detect endogenous differences in ethylene production, comparative studies were then carried out using mutants acting as either a positive ethylene control (eto1-1) or a negative ethylene control (acs1/2/6/4/5/9/7/11). Shown in Fig. 7c, imaging for the ethylene overproducer, eto1-1, showed a significant increase in fluorescence compared to the wild type Col-0, as expected. In contrast, with the acs1/2/6/4/5/9/7/11 mutant that naturally lacks the ability to produce ethylene, there was no discernible fluorescent change with AEP addition (Fig. 7d). When compared with the wild-type Col-0, the acs knockout plant thus exhibited significantly lower levels of fluorescence.

In the next part of this study, AEP probe sensitivity was tested in response to environmental stress factors, namely the immunogenic response to pathogen invasion in A. thaliana. Focus will be given to changes in ethylene production caused by two separate plant immunity pathways: PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI).

PTI-based ethylene detection

Pathogenic bacteria attempting to invade plant cells initially must contend with the first tier of plant’s defense mechanism—PTI. Depicted in Fig. 8a, this system is triggered by the recognition of pathogen-derived molecules known as pathogen-associated molecular pattern (PAMP) through pattern recognition receptors (PRRs) on the plasma membrane. Once triggered, a signaling cascade then commences to upregulate genes associated with the defense response. Among the upregulated genes, studies have shown that ethylene biosynthesis plays an integral role in PTI⁶⁴, possibly due to its regulatory role for innate immune receptors⁶⁵.

Fig. 8 — a Depiction of the general pathway that leads to PTI response. b List of *A. thaliana* plants used in this experiment. Fluorescence and brightfield imaging (×40 magnification) of epidermal peels applied with **AEP** (100 µM) for wild-type Col-0 c, PRR-deficient *fls2/efr/cerk1* d, and the ethylene biosynthesis defected *acs1/2/6/4/5/9/7/11* e. Additionally, supplementation studies were performed using the PAMPs, flg22, and elf18 (4.8 µM), which were applied to all plants. f Summary of the measured fluorescence between the various conditions studied. Statistical analysis was performed using a one-way ANOVA with Tukey’s multiple comparisons test. If not indicated, comparisons were made between the mutants and wild-type under the same treatment conditions. *P < 0.03, **P < 0.002, ***P < 0.0002, ****P < 0.0001, ns = not significant. Error is represented as s.d. of three independent experiments. Source data are provided as a Source Data file.

Two well-studied PAMPs used in this study are the flg22 and elf18 bacterial PAMPs. Flagellin is a globular protein found in the filament that composes the bacterial flagellum. On the conserved N-terminus of flagellin, a 22-amino acid sequence known as flg22 has been found to activate plant defense mechanisms^66,67. It does this by first binding to the PRR known as FLS2, which then leads to the activation of MAPK-signaling cascades and the production of reactive oxygen species (ROS) to confer pathogen resistance⁶⁸. For the bacterial protein EF-Tu (elongation factor thermo unstable), an 18-amino acid sequence, termed elf18, is known to be important for post-invasive immunity and capable of eliciting PTI⁶⁹. In this case, perception instead acts through the PRR known as EFR (EF-TU receptor), followed by downstream MAPK signaling and ROS production⁷⁰.

In this study, epidermal peels from A. thaliana Col-0 were first incubated for 6 h with either PAMP (flg22 or elf18) or a blank control. Incubation with AEP was then carried out, followed by imaging and quantification (Fig. 8c–e and Supplementary Figs. 55–60). As shown in Fig. 8c, significant increases in fluorescence could be detected with tissues incubated with either PAMP compared to the blank control. This data correlates well with literature reports that have shown consistently high levels of ethylene gas generated after flg22 or elf18 exposure⁶¹.

As a further investigation, control studies were also carried out using the mutant plants fls2/efr/cerk1 and acs1/2/6/4/5/9/7/11. For the A. thaliana mutant known as fls2/efr/cerk1, the two PAMP-sensing PRR genes FLS2 and EFR are knocked out, leaving these plants unable to sense and respond to the presence of extracellular PAMP. With the images shown in Fig. 8d, fluorescence levels in the mutants incubated with either flg22 or elf18 falls to levels on par with the blank controls, thereby representing a significant decrease compared to the corresponding wild type Col-0. With the acs1/2/6/4/5/9/7/11 mutant, no discernible difference in fluorescence with epidermal peels incubated with or without PAMPs was found (Fig. 8e). Consistent with the fact that this mutant is unable to biosynthesize ethylene^60,61, observed fluorescence was again significantly reduced compared to the corresponding wild type Col-0.

ETI-based ethylene detection

In case the first defense system (PTI) is defeated, innate resistance mechanisms in plants initiate a second defense system known as ETI. As depicted in Fig. 9a, the basis behind this immune response relies on the fact that bacterial pathogens are known to infect eukaryotic cells using an appendage to secrete toxins or effectors into the host cells by type III secretion system (or injectisome). These secreted effectors have the ability to exert a number of effects that promote pathogen virulence. Examples of well-studied effectors are AvrRpm1 and AvrRpt2, which can be produced by Pseudomonas syringae pv. tomato (Pst) to interfere with the PTI-regulating membrane protein RPM1-interacting protein 4 (RIN4)⁷¹. To combat this, resistant plants have resistance (R) proteins that recognize directly or indirectly some of these effectors (known as avirulent effectors), leading to a signaling cascade that upregulates genes associated with the defense response. For AvrRpm1, once associated with RIN4, phosphorylation of RIN4 is induced, followed by activation of the R protein known as RPM1⁷². In the case of AvrRpt2, degradation of RIN4 occurs instead. Since the R-protein RPS2 also associates with RIN4, its degradation essentially frees RPS2 to interact and be activated by AvrRpt2^73,74.

Fig. 9 — a Depiction of the general pathway that leads to ETI response. b List of *A. thaliana* plants used in this experiment. Fluorescence and brightfield imaging (×40 magnification) of epidermal peels applied with **AEP** (100 µM) for wild-type Col-0 c, R-protein-deficient *rpm1rps2* d, and the ethylene biosynthesis-defected *acs1/2/6/4/5/9/7/11* e. Additionally, supplementation studies were also performed using *Pst* AvrRpm1 or *Pst* AvrRpt2 (bacterial solution OD₆₀₀ = 0.02), which was applied to all plants. f Summary of the measured fluorescence between the various conditions studied. Statistical analysis was performed using a one-way ANOVA with Tukey’s multiple comparisons test. If not indicated, comparisons were made between the mutants and wild-type under the same treatment conditions. *P < 0.03, **P < 0.002, ***P < 0.0002, ****P < 0.0001, ns = not significant. Error is represented as s.d. of three independent experiments. Source data are provided as a Source Data file.

In this study, ETI-induced ethylene production was monitored in A. thaliana via exposure to two different bacterial strains known to produce either the AvrRpm1 or AvrRpt2 avirulence proteins. To carry out this study, inoculation of epidermal peels with Pst AvrRpm1, Pst AvrRpt2, or a 10 mM MgCl₂ solution was first done 12 h before detection. Incubation with AEP was then carried out, followed by imaging and quantification (Fig. 9c–e and Supplementary Figs. 61–66). As shown in Fig. 9c, the Col-0 epidermal peels that were exposed to Pseudomonas producing either AvrRpm1 or AvrRpt2 showed significantly increased levels of fluorescence compared to the MgCl₂ control.

Again, as a comparative study, A. thaliana mutants were also tested as controls to highlight the robustness of the AEP probe. One of the mutants used was rpm1rps2, which has both the R proteins, RPM1 and RPS2, knocked out. In this regard, the rpm1rps2 mutant is unable to properly activate ETI even after infection with Pseudomonas bacteria carrying AvrRpm1 or AvrRpt2. Shown in Fig. 9d, imaging results clearly show that fluorescence levels in the mutant plant exposed to either AvrRpm1 or AvrRpt2 did not have elevated levels of ethylene production. Instead, fluorescence levels remain on par with the MgCl₂ controls. In comparison to the corresponding wild type Col-0, this signifies a dramatic reduction in detected ethylene. Finally, in the case with the acs1/2/6/4/5/9/7/11 mutant, no discernible differences in fluorescence was found with exposure to AvrRpm1 or AvrRpt2 (Fig. 9e), which agrees well with literature⁶¹.

Limitations

Through testing numerous different samples in this study, some limitations of the AEP probe were gradually noted. First, one key issue is absorption. Given that the exterior scaffold of AEP is human serum albumin (~66 kDa protein), the probe is unlikely to passively penetrate across the cell membrane and into plant cells. It is assumed that the AEP probe exists extracellularly, rather than intracellularly. Due to this, the texture of a sample becomes a limiting factor. When used with absorbent samples, such as the flesh of fruits, the AEP probe was observed to sufficiently remain on sample surfaces. However, when testing with samples of waxy nature (i.e. plant cuticles), it was noted that the AEP probe tends to get pushed off over time.

Another issue is related to the aspect of “real-time” detection. Due to its poor water solubility, ethylene rapidly transitions from solution into the atmosphere. As such, any (water-based) bioimaging reagent used to directly measure this phytohormone in “real-time” must react under a very short period of time. At its current state, however, AEP probe reactivity is not fast enough to measure “real-time”. Conceivable approaches to improve upon this area could see changes made to (1) increase ruthenium reactivity by altering the metal–ligand complex, (2) change the protein scaffold for one with a shallow-binding pocket to allow easier access, or (3) adopt the use of a stronger FRET donor–acceptor pair.

Discussion

Overall, the work conducted in this study should have a significant impact for the advancement of two separate research fields, namely in the areas of enzyme biosensor development and also research focused on ethylene detection in plants.

Given the biocompatible nature of enzyme biosensors, their usage for biomedical applications not only has implications from a scientific perspective, but also from a commercial standpoint. Currently, numerous examples of enzyme biosensors are applied commercially, such as arylacylamidase, β-hydroxybutyrate dehydrogenase, salicylate hydroxylase, and uricase, which are used for the serum determination of metabolites like acetaminophen, ketone bodies, salicylate, and uric acid, respectively. However, since enzyme biosensors are mainly derived from naturally occurring enzymes, recent progress in this field has largely appeared to stall. In parallel, a rapid rise of interest is now being directed towards the use of biosensors composed of abiotic metal complexes, where the bioorthogonality of certain transition metals can help to target metabolites typically found in difficult-to-access chemical spaces.

With the advent of ArMs, a highly unique opportunity exists for the development of “artificial” enzyme biosensors, where metabolite detection can be driven via abiotic metal catalytic reactions. To the best of our knowledge, this study represents a leading example of an ArM being developed into an enzyme biosensor that has shown robust application with real world biological samples, such as fruits and leaves. Given its ease of preparation, there is the added benefit that this work can help pioneer the field of ArM biosensors, where different transition metals (e.g. palladium, rhodium, ruthenium, etc.) can be exploited for the chemoselective detection and quantification of other important biological metabolites.

Another significant aspect of this work is related to the development of the ethylene-sensing AEP probe, which has proven to be capable of detecting changes (both induced endogenously and exogenously) in biological concentrations of ethylene in various fruits and A. thaliana plants. Given the physiological importance of ethylene for plants, numerous studies have been conducted to understand ethylene-dependent pathways. However, one limitation of current detection methods (e.g. gas chromatography) is that typically only the average ethylene gas released into the surrounding environment can be measured. Without a proper bioimaging technique that can spatially detect ethylene on a cellular level, it is presently a challenge for scientists to determine the location and source of ethylene production. Despite some restrictions, this study has developed an ethylene-sensing bioimaging technique shown to be capable of measuring ethylene in a spatiotemporal manner for cross-sections of various fruits and leaves.

Methods

General materials

Reagents and buffer components were purchased from Sigma-Aldrich, Fisher Scientific, Alfa Aesar, TCI, or Wako Chemicals without further purification. Human serum albumin (lyophilized powder, essentially fatty acid free) was purchased from Sigma-Aldrich (Prod# A1887). All experiments dealing with air-sensitive and moisture-sensitive compounds were conducted under an atmosphere of dry nitrogen. Anhydrous solvents were used as received, which include THF (anhydrous; Fujifilm Wako Pure Chemical), dichloromethane (anhydrous; Fijifilm Wako Pure Chemical) and benzene (anhydrous; Fujifilm Wako Pure Chemical). TLC analyses (F-254) were performed with 60 Å silica gel from Merck. ¹H and ¹³C NMR spectra were measured on either a JEOL JNM-AL300 (300 MHz), JNM-ECZ400R/S1 (400 MHz), or JNM-ECA500 (500 MHz) instrument with the solvent peaks as internal standards: δH 0.00 (tetramethylsilane) and δC 77.0 for CDCl₃. For chemical synthesis, high-resolution mass spectra (HRMS) were obtained on a Bruker MicroTOF-QIII spectrometer® by electron spray ionization time-of-flight (ESI-TOF-MS). Ultrapure water used for all experiments was obtained from a Milli-Q Advantage® A10 Water Purification System sold by Merck Millipore (Burlington, USA). In addition, Amicon® Ultra Centrifugal Filters (10 and 30 kDa) and Durapore PVDF 0.45 µm® filters were also purchased from by Merck Millipore (Burlington, USA). All fruit and vegetable samples were purchased from a local grocery store. Previously published A. thaliana mutants were: rpm1rps2 (rpm1-3/rps2-101C)⁷², eto1-1⁶², acs1/2/6/4/5/9/7/11⁶⁰, and fls2/efr/cerk1^66,70. The following bacterial strains were used in this study: P. syringae pv. tomato DC3000 transformed with pVSP61-AvrRpt2 (Pst AvrRpt2) and pVSP61-AvrRpm1 (Pst AvrRpm1)⁷⁵. Bacteria were propagated on LB media containing selection antibiotics and suspended with a 10 mM MgCl₂ solution at a concentration of OD₆₀₀ = 1.0.

Preparation of AEP

As previously described³⁴, alb–Ru was prepared first by mixing 30 μM of human serum albumin (50 nmol, 167 μl from 300 μM stock solution in H₂O) and 37 μM of DEAC-Ru (62 nmol, 167 μl from 370 μM stock solution in dioxane). The total reaction volume was adjusted to 1670 μl of 10% dioxane in PBS buffer pH 7.4. Following initiation by HSA addition, reaction mixtures were mildly mixed and incubated at 37 °C for 1 h. The reaction mixture was then concentrated and washed with PBS buffer (3×) using Amicon® ultra centrifugal filters (30 kDa). The concentrated alb–Ru solution was then diluted in H₂O to 50 μl to obtain a 1 mM stock solution. To prepare the AEP solution, a mixture of 100 μM of alb–Ru (50 nmol, 50 μl from 1 mM stock solution in H₂O) and 500 μM DABCYL quencher (250 nmol, 450 μl from 555 μM stock solution in 1:8 DMSO in H₂O) was made. Solutions were mildly mixed and incubated at 37 °C for 5 min. The reaction mixture was then concentrated and washed with H₂O (3×) using Amicon® ultra centrifugal filters (30 kDa). The concentrated AEP solution was then diluted in H₂O to 500 μl to obtain a 100 μM stock solution. Following preparation, AEP was characterized via fluorescence spectroscopy and CD.

Protein complex fluorescence

For the protein complexes used in this study (alb–Ru, AEP), fluorescence was determined via spectrofluorometric analysis using a JASCO FP-6500 Spectrofluorometer equipped with a JASCO FMP-963 microplate reader. For sample preparations, both alb–Ru and AEP were adjusted to a concentration of 10 µM in H₂O. Samples were then aliquoted (100 µl) into 96-well microtiter plates, and monitored at λ_EX = 420 nm/λ_EM = 463 nm. All measurements were taken in triplicate from distinct samples.

CD experiments

In order to identify major structural changes to the various protein complexes used in this study (alb–Ru, AEP), CD analysis was done. CD spectra were measured on a J-1500 CD spectrometer (JASCO, Tokyo, Japan) using a 0.1 cm cell. A solution of 10% dioxane in water was used as a blank and automatically subtracted from the samples during scanning. Data was recorded from 200 to 250 nm with a scan speed of 100 nm/min. The concentration of each protein complex was maintained at 2.3 μM.

Ethylene concentration by NMR analysis

As an internal standard, a 100 mM stock solution of 1,3-propanediol in THF-d8 was first prepared. For the 100% THF condition, an NMR tube was filled with 60 μl of the internal standard solution and 540 μl of THF-d8. For the 25% THF/H₂O condition, an NMR tube was filled with 60 μl of the internal standard solution, 90 μl of THF-d8, and 450 μl of D₂O. For the 10% THF/H₂O condition, an NMR tube was filled with 60 μl of the internal standard solution and 540 μl of D₂O. Tubes were gastight sealed, before 1 ml of ethylene gas was injected into each NMR tube. Following an incubation period of 5 min, the ¹H NMR spectra was obtained. Ethylene concentrations in solution were determined through integration and comparison with the internal standard.

Dose-dependent reactivity of RuQ with ethylene gas

For dose-dependent reactivity experiments, a 100 μM solution of RuQ in solvent (either 100% THF or 10% THF in H₂O) was prepared in a septum-sealed cuvette. Before injection, a measurement was recorded (t = 0 min). A specific volume of ethylene gas (1000, 500, 250, 100, 50 μl) was then quickly bubbled into solution. The cuvette was incubated for 1 min before another measurement was recorded (t = 1 min). Fluorescence measurements were made using a JASCO FP-6500 spectrofluorometer (λ_EX = 420 nm/λ_EM = 463 nm). All reactivity studies were performed in duplicate from distinct samples.

Time-based reactivity of AEP with ethylene gas

For time-based monitoring of AEP reactivity, water (1425 µl) was added to a septum-sealed cuvette and purged with a balloon of ethylene gas. A solution of AEP (75 µl from 2 mM stock solution in H₂O) was then added via syringe. The cuvette was then incubated at r.t. and monitored at set time intervals (10, 30, 60, 120, and 180 min). Fluorescence measurements were made using a JASCO FP-6500 spectrofluorometer (λ_EX = 420 nm/λ_EM = 463 nm). All reactivity studies were performed in triplicate from distinct samples.

AEP-selectivity assay

To investigate AEP reactivity with various terpenes, water (1275 µl) was first added to a cuvette, followed by a solution of AEP (75 µl from 2 mM stock solution in H₂O) and various terpenes (150 µl from 60 mM stock solution in THF). The cuvette was then incubated at r.t. and monitored at 60 min. Fluorescence measurements were made using a JASCO FP-6500 spectrofluorometer (λ_EX = 420 nm/λ_EM = 463 nm). All reactivity studies were performed in triplicate from distinct samples.

Spatial imaging with kiwifruit

Unripe and ripening kiwifruit were obtained from the local supermarket. Sections of kiwifruit were prepared using a kitchen knife at rough dimensions of about 2.0 cm × 4.5 cm, where the aim was to obtain slices that included the outer pericarp, locules, and the columella of the fruit. To monitor ethylene production, 170 μl of AEP (400 μM solution) was first applied to the center of a 10 cm Petri dish. Samples were then gently placed on top of the AEP solution to ensure even exposure. Samples were left to incubate at r.t., where imaging was carried at certain time intervals (1, 24 h) using a Keyence BZ-X710 All-in-one Fluorescence Microscope® equipped with a ET-EBFP2/Coumarin/Attenuated DAPI Filter Set Cat#49021 (Chroma Technology Corp., Vermont, USA). Brightfield images (color) were obtained at a 1/25 s exposure setting and fluorescent images were obtained at a 1/3.5 s exposure setting. Multiple images were obtained at ×4 magnification, where image stitching and analysis was performed using BZ-X Analyzer software (Keyence, Japan).

Spatial imaging with Asian pears

Asian pears were obtained from the local supermarket. Sections of flesh (hypanthium tissue) were prepared using a kitchen slicer, at rough dimensions of about 4.8 cm × 4.8 cm. Samples were then positioned in the center of a 10 cm Petri dish, where cotton balls were placed on the sample surface and allowed to incubate for 5 h at r.t. Four of the five cotton balls are soaked with water, while the remaining cotton ball is soaked with either 10 mM ACC or 10 mM PZA. To monitor ethylene production, 300 μl of AEP (400 μM solution) was first applied to the center of another 10 cm Petri dish. Samples were then gently placed on top of the AEP solution to ensure even exposure. Samples were left to incubate at r.t., where imaging was carried out after 18 h using a Keyence BZ-X710 All-in-one Fluorescence Microscope® equipped with a ET-EBFP2/Coumarin/Attenuated DAPI Filter Set Cat#49021 (Chroma Technology Corp., Vermont, USA). Brightfield images (color) were obtained at a 1/25 s exposure setting and fluorescent images were obtained at a 1/3.5 s exposure setting. Multiple images were obtained at ×4 magnification, where image stitching and analysis was performed using BZ-X Analyzer software (Keyence, Japan).

Time-dependent imaging with fruits

Apples (Golden Delicious, Jazz, and Fuji cultivars), Asian pears, kiwifruit, and Muscat grapes, carrots, and red bell peppers were obtained from the local supermarket. Samples of tissue (small rectangles of ~10 mm × 8 mm) were prepared using a kitchen slicer and knife. Samples were then incubated in either water, ACC (1 or 10 mM), or PZA (1 or 10 mM) for 3 h at r.t. To monitor ethylene production, 10 μl of AEP (400 μM solution) was first applied to the center of individual wells of a chamber slide (ibidi µ-Slide eight-well chamber slides). Samples were then gently placed on top of the AEP solution to ensure even exposure. Samples were left to incubate at r.t., where imaging was carried at certain time intervals (0, 1, 2, 4, 8, 20 h) using a Keyence BZ-X710 All-in-one Fluorescence Microscope® equipped with a ET-EBFP2/Coumarin/Attenuated DAPI Filter Set Cat#49021 (Chroma Technology Corp., Vermont, USA). Brightfield images (color) were obtained at a 1/80 s exposure setting and fluorescent images were obtained at a 1/6 s exposure setting. Multiple images were obtained at ×4 magnification, where image stitching and analysis was performed using BZ-X Analyzer software (Keyence, Japan).

Imaging with A. thaliana plants

A. thaliana plants were grown on soil at 23 °C and a light intensity of 85 μmol m⁻² s⁻¹. A 10 h light and 14 h dark photoperiod was applied. To monitor ethylene production, leaves were first harvested from 4 to 6 weeks old plants. Using forceps, clear epidermal peels were then removed from leaves and placed into 96-well clear bottom plates. Following the addition of H₂O (100 μl), the samples were then incubated for 12 h at r.t. to cancel wound stress. Depending on the conditions under study, various solutions were added as necessary: 1 mM of ACC (2 μl of 55 mM stock solution in H₂O); 4.8 μM of flg22 or elf18 (5 μl of 100 μM stock solution in H₂O); or OD₆₀₀ = 0.02 solution of Pseudomonas bacteria (2 μl of OD₆₀₀ = 1.0 stock solution). For studies involved with ACC and Pseudomonas bacteria, an incubation period of 12 h at r.t. was applied. For studies involved with PAMPs, an incubation period of 6 h at r.t. was instead applied. The solutions were then completely removed from the epidermal peel samples, followed by the addition of 100 μM AEP (50 μl stock solution). After 30 min, solutions were completely removed, washed with H₂O, and then imaged on a Keyence BZ-X710 All-in-one Fluorescence Microscope® equipped with a ET-EBFP2/Coumarin/Attenuated DAPI Filter Set Cat#49021 (Chroma Technology Corp., Vermont, USA). Images were obtained at ×20 and ×40 magnification, where brightfield images (monochrome) were obtained at a 1/400 s exposure setting and fluorescent images were obtained at a 1/30 s exposure setting. Analysis was performed using BZ-X Analyzer software (Keyence, Japan).

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Supplementary information

Supplementary Information^{(20.5MB, pdf)}

Peer Review File^{(172.1KB, pdf)}

Reporting Summary^{(164.8KB, pdf)}

Acknowledgements

Kind acknowledgement is given to GlyTech Inc. for supporting this research. CD spectral measurements were acquired by the Molecular Structure Characterization Unit, RIKEN Center for Sustainable Resource Science (CSRS). This work was financially supported by the MEXT/JSPS KAKENHI Grant Numbers JP16H03287, JP18K19154, JP15H05843 (to K.T.), JP16H06186 (to Y.K.), JP15H05959 (to K. S.), and JP18K14347 (to K.V.). This work was also supported by a RIKEN Incentive Research Project grant to I.N. and Y.K., as well as the Russian Government Program for Competitive Growth (granted to Kazan Federal University).

Source data

Source Data^{(77.4KB, xlsx)}

Author contributions

Preparation of reagents was done by S.E., K.V., and I.N. Preparation of plant and bacterial strains were carried out by Y.K. Fruit-imaging studies were carried out by K.V., while plant-imaging studies were done by S.E. and T.W. Reactivity and spectroscopic studies were performed by K.V. and S.E. The manuscript was written by K.V. and K.T., and checked by S.Y. and K.S. This research was directed and supervised by K.T.

Data availability

All data supporting the findings of this study are available with the article, and can also be obtained from the corresponding author upon reasonable request. The source data underlying Figs. 2b–g; 3b; 4e; 5b–e; 6a–b, d–e, g–h; 7e; 8f; 9f, and Supplementary Figs. 42a, b, d, e are provided as a Source Data file.

Competing interests

The authors declare no competing interests.

Footnotes

Peer review information Nature Communications thanks Bram Van de Poel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Kenward Vong, Shohei Eda.

Supplementary information

Supplementary information is available for this paper at 10.1038/s41467-019-13758-2.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Information^{(20.5MB, pdf)}

Peer Review File^{(172.1KB, pdf)}

Reporting Summary^{(164.8KB, pdf)}

Data Availability Statement

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PERMALINK

An artificial metalloenzyme biosensor can detect ethylene gas in fruits and Arabidopsis leaves

Kenward Vong

Shohei Eda

Yasuhiro Kadota

Igor Nasibullin

Takanori Wakatake

Satoshi Yokoshima

Ken Shirasu

Katsunori Tanaka

Abstract

Introduction

Fig. 1. The versatility of albumin artificial metalloenzymes allows for its usage in areas such as drug therapy and diagnostics.

Results

Preparation of ethylene-sensing ArM

Fig. 2. Preparation and characterization of the AEP probe.

Ethylene-reactivity studies

Spatial detection of ethylene in fruits

Fig. 3. Spatial-based detection of ethylene in ripening and unripe kiwifruit.

Fig. 4. Spatial-based detection of ethylene in sections of Asian pears induced with either an ethylene-stimulating or ethylene-inhibiting additive.

Temporal detection of ethylene in fruits

Fig. 5. Time-dependent detection of ethylene in apples.

Fig. 6. Time-dependent detection of ethylene in other ethylene-producing fruits.

Ethylene detection in plants

Fig. 7. Detection of ethylene produced in A. thaliana plants.

PTI-based ethylene detection

Fig. 8. Detection of ethylene produced as a result of PAMP-triggered immunity in A. thaliana plants.

ETI-based ethylene detection

Fig. 9. Detection of ethylene produced as a result of effector-triggered immunity in A. thaliana plants.

Limitations

Discussion

Methods

General materials

Preparation of AEP

Protein complex fluorescence

CD experiments

Ethylene concentration by NMR analysis

Dose-dependent reactivity of RuQ with ethylene gas

Time-based reactivity of AEP with ethylene gas

AEP-selectivity assay

Spatial imaging with kiwifruit

Spatial imaging with Asian pears

Time-dependent imaging with fruits

Imaging with A. thaliana plants

Reporting summary

Supplementary information

Acknowledgements

Source data

Author contributions

Data availability

Competing interests

Footnotes

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