ACS Publications. Most Trusted. Most Cited. Most Read
Hormesis-Inducing Essential Oil Nanodelivery System Protects Plants against Broad Host-Range Necrotrophs
My Activity
  • Open Access
Article

Hormesis-Inducing Essential Oil Nanodelivery System Protects Plants against Broad Host-Range Necrotrophs
Click to copy article linkArticle link copied!

  • Pablo Vega-Vásquez
    Pablo Vega-Vásquez
    Laboratory of Renewable Resources Engineering (LORRE), Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United States
    Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United States
  • Nathan S. Mosier
    Nathan S. Mosier
    Laboratory of Renewable Resources Engineering (LORRE), Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United States
    Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United States
  • Joseph Irudayaraj*
    Joseph Irudayaraj
    Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United States
    Department of Bioengineering, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States
    *Email: [email protected]
Open PDFSupporting Information (1)

ACS Nano

Cite this: ACS Nano 2021, 15, 5, 8338–8349
Click to copy citationCitation copied!
https://doi.org/10.1021/acsnano.0c09759
Published April 21, 2021

Copyright © 2021 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY-NC-ND 4.0 .

Abstract

Click to copy section linkSection link copied!

Botrytis cinerea, a broad host-range necrotrophic (BHN) phytopathogen, establishes compatible interactions with hosts by deploying multigene infection strategies, rendering simply inherited resistance ineffective to fight off this pathogen. Since essential oils (EOs) serve as intermediators during phytobiome communication, we hypothesize that they have the potential to enhance the quantitative disease resistance against BHN by eliciting the adaptive stress response (hormesis) in plants. However, using EOs is challenging due to their poor solubility in water. Nanoemulsification of EOs enhances not only the solubility of EOs but also their potency and stability. Here, we demonstrate the potential use of essential oil nanoemulsions (EONEs) to control infections caused by BHN. Using basic engineering principles of nanocarrier design, we demonstrate the efficacy of a robust EONEs design for controlling B. cinerea infection in a model plant, Arabidopsis thaliana. Our nanoemulsion delivery system significantly enhanced the disease resistance of the host by reducing the necrotic area by up to 50% compared to untreated plants. RNA-seq analysis indicated that successful treatments upregulated autophagy, ROS scavenging, and activation of the jasmonic acid signaling pathway.

This publication is licensed under

CC-BY-NC-ND 4.0 .
  • cc licence
  • by licence
  • nc licence
  • nd licence
Copyright © 2021 The Authors. Published by American Chemical Society
Truly resistant plants to broad host-range necrotrophic pathogens (BHN) expressing simply inherited traits that result in incompatible interactions cannot be bred, since the infection mechanisms deployed by these pathogens are complex. Rather than being mediated on a gene-by-gene basis, the compatible interactions of BHNs are driven by multiple strategies that require the intervention of several genes, prompting successful infection. (1)Botrytis cinerea, the causal agent of gray mold, one of the most devastating plant diseases, (2) produces cell wall degrading enzymes, nonhost specific toxins (botrydial), high levels of ROS, necrosis-inducing factors, and an array of secondary metabolites. (3,4) The economic losses caused by this pathogen in crops worldwide are estimated to be up to $100 billion per year. (4,5) Synthetic fungicide application still remains the most common method to control this disease, (2) although this practice is becoming restricted due to not only concerns on sustainability but also the increasing resistance to synthetic chemical fungicides. (6−8)
Both the impossibility of relying on plant breeding approaches to combat BHN and the high risks posed by synthetic fungicides on the environment, on the health of humans and off-target ecosystem, bring about the challenge of finding eco-compatible solutions to combat BHN pathogens.In this context, the use of eco-friendly nanomaterials in agriculture is highly relevant, due to the inherent properties when interacting with host plant systems. The potential benefits and cautions to be exercised from an environmental perspective and the bioengineering challenges involved in translating drug-delivery nanosystems from medicine to agriculture should be noted elsewhere. (9,10) Here, we lay the foundation for the design of a versatile essential oil (EO) nanodelivery system and demonstrate its efficacy in treating the disease caused by BHN.
It is well documented that the biological role of the compounds in EOs are beneficial to the plant’s defense response, either by direct antimicrobial activity against pathogens or repelling off insects. A major challenge in using EOs as is may stem from the fact that they are poorly soluble in water. Surfactant-assisted emulsification is a process commonly carried out to produce homogeneous blends of oil and water. However, the diameter of oil droplets in traditional emulsions is micrometric, therefore their bioactivity is low. Nanoemulsions, in contrast, are more stable than traditional emulsions (11) and more potent due to their enhanced bioavailability because of their increased membrane permeation. (12)
In nature, some of the molecules present in EOs serve as intermediators during plant-to-plant communication (allelopathy), (13) triggering a specific response in defense to an ongoing infection or insect attack. (14) During stressful conditions, a metabolic reprogramming occurs in plants that results in the switching from the salicylic acid (SA) to the jasmonic acid (JA) hormone signaling. Thus, volatile organic compounds (VOCs) carry the “alert” message between plants and their surrounding phytobiome, (15) whereas JA carries the message from local to distal parts within the stressed plant. There is evidence that VOCs, the main constituents of EO, trigger the oxylipin pathway (16) which is critical for JA formation. (17)
We hypothesized that exposure of plants to nanoemulsified EOs may result in the activation of the JA hormone signaling pathway that is normally triggered upon insect or herbivore attack or necrotrophic pathogen infection. Moreover, there is evidence that EOs participate in a feedback loop by activating the plant defense mechanism known as pathogen/damage associated molecular pattern (PAMP/DAMP) which, in turn, results in enhanced production of secondary metabolites stored in the form of EO. (18,19) Using the plant-pathogen model system Arabidopsis thaliana (Col-0) challenged with the necrotrophic fungi B. cinerea, we predict that the quantitative disease resistance (QDR) of treated plants with nanoemulsified EO delivery system would be enhanced, and therefore, the rot produced by the pathogen could be significantly mitigated by this treatment approach. In this context, QDR refers to the extent of susceptibility reduction from the plant to the disease caused by the pathogen. (20)
The objective of our work is two-fold: First, to develop a rational formulation for the production of concentrated, translucent, EO-based nanoemulsions under low-energy conditions and validate the method for a range of EO encapsulation such as cinnamon, clove, coriander, geranium, oregano, peppermint, and red thyme. Second, to explore the systemic hormetic effect of the developed nanoemulsions on the QDR in A. thaliana (Col-0) infected with the necrotrophic fungal pathogen B. cinerea.

Results and Discussion

Click to copy section linkSection link copied!

The effect of stress on biological systems can be debilitating or restorative, depending on the dosage. High-dose or continuous exposure to stress factors results in cellular failure. In contrast, low-dose or intermittent exposure to stressors activates a complex signal/receptor mechanism that counterbalances the noxious effects, restoring homeostasis. This biphasic physiological resilience phenomenon is known as hormesis. (21,22) Hormetins are chemical elicitors of the hormetic response. In plants, the secondary metabolites, such as those present in EOs, are termed as hormetins, (23) which act as intermediators in a feedback loop system. Secondary metabolites are produced in plants by the immune system upon perception of environmental cues, including secondary metabolites.
The motivation for our work is to investigate alternative formulations for a nanodrug-delivery system utilizing plant-derived EO as an eco-compatible and safe alternative to synthetic fungicides to control BHN. Factoring in the limitations of using EO in large scale, given its poor solubility in water and related low potency, we investigated the main drivers of isothermal formation of nanoemulsions under low-energy conditions (Figure 2a), with the primary goal to simplify the formulation and fabrication process. Our fabrication approach, based on the viscosity differential fine-tuning, along with the use of hydrophilic–lipophilic difference (HLD) (Supplementary Figure S2) yielded highly stable and translucent essential oil nanoemulsions (EONEs) (Supplementary Table 1).
Due to their opposing polarity, oil and water do not naturally form a homogeneous blend and tend to separate spontaneously when mixed. Surfactants slow down this separation process. Emulsions can destabilize via coalescence, flocculation, creaming, and Ostwald ripening. Ostwald ripening is the most common process of nanoemulsion failure. This occurs when oil droplets become larger at the expense of smaller droplets, driven by the pressure difference between two oil droplets of different diameters. (24) The process accelerates as the difference in diameter increases. Nanoemulsions are more resistant to Ostwald ripening, therefore kinetically stable. (24) The increased viscosity in the continuous phase may help to increase the stability of the emulsion by reducing the droplet mobility and, therefore, reducing the probability of collision between particles, which may result in coalescence or aggregation and further phase separation.
Another phenomena that could explain the high stability of the formulated EONEs is related to compositional ripening. (25) A phenomenon where the molecules in EOs with high water affinity are transferred from small to larger droplets, driven by the Laplace pressure (Ostwald ripening) creating a concentration gradient in the system. The difference in oil phase composition between varying sized oil droplets induces a thermodynamically unfavorable environment due to the entropy of mixing effect, (26,68) resulting in the buildup of osmotic pressure between droplets of different sizes as a result of the concentration gradient. Such a process can favor the movement of hydrophobic molecules from larger to small droplets through the continuous phase to counterbalance the Ostwald ripening. With time, the Ostwald ripening and compositional ripening processes balance each other out, and droplet growth is inhibited. (27)
High-resolution images in Figure 2c,d show that the droplet size of the undiluted EONEs (dilution effect is provided in Supplementary Figure S3) are stable even after 9 months (extended stability testing over time is presented in Supplementary Figure S1). The growing body of evidence suggests that plants can deter BHN infection by preventing the accumulation of ROS intracellularly, by upregulating the autophagocytic process, and by enhancing JA production. (3,28−30)

Assessment of Dose-Dependent Response of EONEs via Image-Based Phenotyping

Although the mechanisms pertaining to volatiles involved in plant to plant interactions have yet to be fully elucidated, evidence suggests that these molecules not only prime the immune system upon perception by eliciting the expression of defense related genes (18) but also induce their de novo biosynthesis, which comes at a cost. (31) Under adverse conditions, plants face a trade-off between growth and defense. Stressed plants shift their physiological status to the secondary metabolism, by diverting energy and resources that are used to sustain growth and development under adverse conditions, to favor defense mechanisms to endure adversity and trigger survival responses. Therefore, a phenotypical hallmark displayed by plants under such stressful circumstances signals the halt of growth. (32) The flow of experiments on treatment and quantitative image-based phenotyping is presented in Scheme 1. The systemic effect of EONEs was assessed by measuring the response in infected leaves from plants previously treated in the roots.

Scheme 1

Scheme 1. Evaluation of EONEs via Quantitative Image-Based Phenotypinga

aThe workflow presented is a representation of a multispectral image analysis system to assess the hormetic effect of EONEs on the QDR in the plant-pathogen model system A. thaliana-B. cinerea. Roots of 4-week-old A. thaliana (Col-0) are treated by dissolving the tested EONE in the basal nutrient solution, and the leaves are infected with the inoculum 24 h after treatment. Plants left untreated and uninfected are used as the control group. Images are collected daily for 3 days. During image acquisition, the automated system with the focused light beam on the plant rosettes collects information at different wavelengths. Chlorophyll absorbs short wavelength light (blue), and the longer (NIR) wavelength reflected light is filtered through a LP696 filter that blocks the ultraviolet (UV) and visible (vis) light. Collected images are automatically segmented based on their chlorophyll fluorescence. Lack of fluorescence from necrotic tissue is not displayed in the processed image.

Figure 1 shows the effect over time of EONEs from cinnamon, clove, coriander, geranium, peppermint, oregano and red thyme on the mean growth rate of A. thaliana rosette upon exposure of the root to EONEs at two different concentrations (50 and 500 μg/mL). The growth behavior from untreated plants under the same incubation condition are also presented for each of the two concentrations. We found that although the experimental conditions were kept identical, the negative control group (untreated plants) showed a slight difference (p = 0.0243) between the two concentration levels (continuous vs broken line in Figure 1) over time. Specifically, the mean relative growth on day 3, where the difference between the two groups was the strongest (p = 0.0014). This indicates that there is some variation that could not be explained by the experimental conditions. Hence, a lower value was used to test the statistical significance (α = 0.01) of the interaction between the two concentration levels over time in subsequent treatments. However, the relative growth of A. thaliana seedlings, measured as the relative difference in the area of the rosette compared to its initial size, was significantly different for both groups after day 2, indicating that the image-based phenotyping approach using a chlorophyll-derived fluorescence for image treatment and analysis, is sensitive enough to discern statistical noise from biological signal (Supplementary Figures S4 and S5).

Figure 1

Figure 1. Assessment of the hormetic dose-dependent response of A. thaliana to various EO nanoemulsions. The least-squares mean plots from the two-way ANOVA conducted for each of the concentrations under study represent the mean relative growth of the rosettes from a set of nine independently grown seedlings under identical hydroponic conditions. A set of nine untreated independently grown seedlings under identical hydroponic conditions were used as control group, per test concentration. Error bars represent 95% confidence interval of the LS means. To test the differences between LS means, the pairwise comparison Tukey HSD test was employed at alpha (α) = 0.01 to determine the statistical significance. Levels not connected by the same letter symbol (A, B, C, D) are significantly different.

The image-based phenotyping analysis of the EONEs previously mentioned demonstrates a concentration-dependent response on the growth of A. thaliana plants under investigation. Figure 1 shows the interaction plots from the full set of EONEs at the two tested concentrations. In general, none of the EOs used in the nanoemulsions negatively altered the relative growth of A. thaliana over time when treating its roots with 50 μg/mL. However, by increasing the concentration to 500 μg/mL, the mean growth rate of the rosettes from the A. thaliana seedlings significantly reduced. This is true for all of the EONEs tested, although to a different extent as expected. For instance, nanoemulsion formulations with cinnamon, clove, oregano, and red thyme completely halted the growth of treated plants in <24 hr, whereas nanoemulsions from coriander, geranium, and peppermint, although equally effective, were not as effective. On an average, none of the treated plants with 500 μg/mL EONEs grew over 20% as noted from the measured rosette area. Since we exposed the roots to the EONEs, we measured the effects on the rosette (see Supplementary Figure S4), to note that the nanoemulsified EO carriers triggered a systemic immune response via root signal transduction. Normally, the signaling transduction phenomena provoked by VOCs from EOs is associated with leaves, rather than roots. Here, we demonstrated that cells from roots can also participate in the biological response primed by EOs. The biological effect of the EONEs here tested is most likely due to the VOCs present in the EOs, and not from unintended effects from other components from the emulsion, such as the PG used as viscosity modulator in the continuous phase. Strong evidence exists supporting the nontoxic nature of PG for animals and plants. (33)
A key element in the transition between growing status to a systemic defense response status is the plant hormone JA which counterbalances the SA hormone signaling system that prevails under optimal growing conditions. (34) The biosynthesis and role of jasmonates in the plant immune response have been extensively described in the literature. (35−38) Briefly, JA is synthesized from polyunsaturated fatty acids (PUFAs), such as α-linolenic acid, of membranes through the octadecanoid pathway that involves the translocation of lipid intermediates from the chloroplast membranes to the cytoplasm and later on into peroxisomes. Given that the nanoemulsion formulation comprises of a blend of soybean oil (rich in PUFAs) and EO (rich in VOCs), it is feasible that the change in growth upon treatment with EONEs is a consequence of activation of the JA signaling system.
JA undergoes intracellular methylation to form methyl jasmonate (MeJA). MeJA induces metabolic reprogramming that contributes to the regulation of the trade-off between defense mode and plant growth by inhibiting cell proliferation and halting cell expansion while enhancing the defense response. (39) MeJA is also responsible for the induction of biosynthesis and subsequent accumulation of secondary metabolites (such as volatile organic compounds in EO). (40) It is well established that ethylene (ET) and JA are the main contributors to the defense response of plants against necroptrophs, whereas SA primarily regulates the defense resistance to biotrophic and hemibiotrophic pathogens. (41)

Figure 2

Figure 2. Formation and characterization of stable EONEs under low-energy conditions by modulation of the viscosity differential with propylene glycol and soybean oil. (a) Schematic representation of the nanoemulsion formation process via spontaneous emulsification driven by modulation of the viscosity in continuous phase under mild conditions. (b) Effect of EONEs on the QDR in the plant-pathogen model system A. thaliana-B. cinerea assessed by automated phenotyping with chlorophyll fluorescence-based segmentation. Bars represent the mean and standard error of a nested model measuring necrotic areas from four leaves per plant and five plants per treatment. A set of five untreated and uninfected independently grown seedlings under identical hydroponic conditions were used as the control group. Statistical differences were evaluated per the nested ANOVA followed by a pairwise comparison with a Dunnett’s adjustment relative to the control group. Asterisks on top of the bars indicate a significant difference between the treatment and the control group (*p < 0.05 and **p < 0.001). Images in the bottom depict treatments. Images with mask and without mask (RGB) show image segmentation based on fluorescence emitted by chlorophyll upon excitation with blue light. Gaps in the leaves indicate areas of no fluorescence (i.e., necrotic areas). (c, d) Transmission electron micrographs from 9 month-old cinnamon nanoemulsion.

Systemic Effect of EONEs on Quantitative Disease Resistance

Due to the necrotrophic lifestyle of B. cinerea, the restriction of HR from plants is a paramount strategy employed by plants to prevent disease progression once infected. Although information on the genetic control of HR is scarce, there are a number of potential mechanisms that plant cells may employ to achieve it. A growing body of evidence suggests that plants can deter BHN infection by preventing the accumulation of ROS intracellularly, by upregulating the autophagocytic process and by enhancing JA production. (3,28−30) We hypothesized that exposure of plant roots to EONEs may trigger these biological processes, resulting in enhanced QDR against BHN (a potential mode of action is illustrated in Figure 3a). In order to test this, RNA-seq analysis was performed from plants treated with cinnamon nanoemulsion, because this treatment resulted in the most enhanced quantitative defense response compared to untreated plants. RNA-seq analysis showed that a total of 1405 differentially expressed genes (DEGs) were only expressed by the treated plants, compared to the 1073 genes in control. Figure 3b shows the gene ontologies for differentially expressed biological functions from treated vs untreated plants.

Figure 3

Figure 3. Mode of action of EONEs as hormetins. (a) Schematic representation of the mode of action of cinnamon EONEs in the activation of hormesis leads to enhanced QDR against BHNs in the plant-pathogen system A. thaliana-B. cinerea. (b) List of biological targets upregulated and downregulated upon exposure to cinnamon oil nanoemulsion relative to the control group. The control group consisted of a set of three untreated and independently grown plants under identical hydroponic conditions.

As shown in Figure 2b nanoemulsions from cinnamon, clove, coriander, and red thyme showed a significant effect on the QDR of A. thaliana against B. cinerea. The strongest effect was produced by cinnamon nanoemulsion, with a mean necrotic area of 10%, which is ca. 50% less than the untreated plants. The necrotic area observed in plants treated with coriander, clove, and red thyme EONEs was, on an average, between one-third to a half of the necrotic area observed in the control group. The EO extracted from cinnamon bark contains mainly cinnamaldehyde (65.00–80.00%) and eugenol (5.00–10.00%). (42) Eugenol is also present in the EO from clove buds, as its main constituent (70–95%) along with eugenol citrate (up to 20%) and β-caryophyllene (12–17%). (43) The relative composition of the EO extracted from coriander seeds is mainly linalool (72.7%) followed by λ-terpinene (8.8%), α-pinene (5.5%), camphor (3.7%), limonene (2.3%), geranyl acetate (1.9%), and p-cymene (1.5%), although the oil composition may change depending on the maturity of the seed. (44) The major components in the EOs from red thyme have been identified as thymol (48%), γ-terpinene (31%), and p-cymene (8%). (45) Our results on the compositional analyses of the EOs used are presented in Supporting Information Figure S6, which are consistent with the literature.
The role of cinnamaldehyde, (46) eugenol, (47) thymol, (48) linalool, (49) and terpinene (50) in the defense response of plants was studied. In general, VOCs from EO induce the JA defense response in plants. (49) For instance, there is evidence that cinnamaldehyde elicits a defense response in plants that result in significantly less accumulation of SA, signifying upregulation of the JA/ET pathway. (51) The ability to transduce infection signals from focal points into a systemic response in a coordinated and timely manner is imperative for effective plant defense. The intricacies of the transcriptional dynamics related to plant immunity are noted in the literature (52) as well as a description of the major transcription regulators during the plant immune response against necrotrophic pathogens. (2)
As mentioned before, the mechanisms involved in the cross-communication mediated by VOCs is not completely understood, but evidence suggests that some of the mechanisms involved in the translocation of these molecules from its source to where they accumulate may involve simple diffusion, vesicle-mediated transport, and transporter-mediated membrane transport. (53) Several genes have been identified as JA-responsive transporters which are involved in the membrane transport of various secondary metabolites including the families: ATP-binding cassette (ABC) transporter, nitrate-peptide transporter (NRT), multidrug and toxic compound extrusion (MATE), and purine permease (PUP). (54) In A. thaliana, there are around 120 genes for ABC proteins, 53 for NRT, 56 for MATE, and 21 PUP genes. (53) GSEA-GO (55) showed that exposure of roots to cinnamon NE resulted in enhanced transporter activity (see Table 1). Specifically, nucleotide transmembrane transporter activity (GO:0000295, GO:0051503, GO:0015215, and GO:0005347) (see Supplementary data set 2: Functional analysis of DEG-GSEA-GO-Cinnamon NE vs Control). The transcriptome of A. thaliana plants treated with cinnamon oil NE was analyzed to elucidate the biological mechanisms involved in the enhanced QDR caused by this treatment in our plant-pathogen model system. Our results are consistent with prior studies on the pathways involved in the defense resistance against necrotrophic pathogens previously discussed. (31−34)
Table 1. Comparison of Significantly Enriched GO Terms from Plants Treated with Cinnamon EONE
cinnamon NE treated groupcontrol group
adenine nucleotide transmembrane transporter activityAT DNA binding
adenine nucleotide transportcarbonate dehydratase activity
alkali metal ion bindingcell cycle phase transition
ATP transmembrane transporter activitycellular response to brassinosteroid stimulus
ATP transportcellular response to cytokinin stimulus
Energy reserve metabolic processcondensed chromosome centromeric region
glycogen metabolic processCondensed chromosome kinetochore
jasmonic acid biosynthetic processcytokinin activated signaling pathway
jasmonic acid metabolic processfluid transport
nucleotide transmembrane transporter activitymeiosis II
nucleotide transportmeiosis II cell cycle process
positive regulation of transcription from RNA polymerase II promoter in response to heat stressprenyltransferase activity
positive regulation of transcription from RNA polymerase II promoter in response to stresspurine nucleoside biosynthetic process
potassium ion bindingpurine ribonucleoside biosynthetic process
purine nucleotide transmembrane transporter activityresponse to cytokinin
purine nucleotide transportresponse to gibberellin
pyruvate kinase activityvoltage gated cation channel activity
toxin biosynthetic processwater transmembrane transporter activity
The gene ontology (GO) functional analysis on the DEGs in Table 1 indicates that, after 3 days of post treatment, the set of genes that were significantly upregulated compared to untreated plants were those involved in the biological functions controlling the major defense responses, including the responses to heat, water deprivation, oxidative stress and toxic compounds. Further, the genes that control the activation of secondary metabolism were upregulated, including those responsible for the biosynthesis of sulfur compounds. VOCs from the EO are rich in such type of compounds. (56,57) In contrast, the GO annotations from genes controlling major biological functions related to growth and development were downregulated.
The JA-mediated defense is vital for the plants to enhance resistance to B. cinerea. (58) As discussed, activation of the JA-mediated defense response shifts the physiological status of the plant, halting growth and activation of the defense-associated mechanism. Ontologies associated with JA-based physiology were shown to be significantly enriched in plants treated with cinnamon EONE, including biomarkers such as farnesoic acid carboxyl-O-methyltransferase (FAMT), plant defensin 1.2 (PDF1.2), vegetative storage protein (VSP2), and WRKY transcription factors, among others. (3,59,60) These findings suggest that the enhanced systemic QDR, observed in the phenotyping assays is most likely due to molecules from the cinnamon nanoemulsion.
KEGG functional annotations on the DEGs from plants treated with cinnamon NE indicate that among the main upregulated metabolic pathways were the ribosome and the proteasome biogenesis (see Table 2). This is most likely due to an attempt from cells to maintain homeostasis since ribosomes, ER, and proteasomes are substrates for selective degradation (i.e., selective autophagy) through complex mechanisms that are only recently beginning to emerge, especially under conditions of cellular stress. (61) GO terms for biomarkers of autophagy were significantly upregulated in plants treated with cinnamon NE, including gene members of the families ATG, BAG, RAPTOR, VTI, RING, and ATI (Supplementary data set 1: Functional analysis of DEG-GO-Cinnamon NE vs Control), for instance, the atBAG4 gene that appears to inhibit apoptotic-like plant cell death (i.e., HR). Inhibitors of cell death domains, such as BIR1 (BAK1-interacting receptor-like kinase aka BAK1) and BAG cochaperone 6, are thought to be implicated in endoplasmic reticulum stress-induced cell death via regulation of apoptosis-inducing factor. (62) We also found that the stress-induced protein KIN2 gene was significantly enriched in plants treated with cinnamon oil NE. KIN genes promote phosphorylation of ATG genes and the target of rapamycin (TOR) complex subunit RAPTOR which inhibits TOR activity and initiate autophagy. (63)
Table 2. Comparison of Significantly Enriched KEGG Annotations from Plants Treated with Cinnamon EONE
cinnamon NE treated groupcontrol group
α-linoleic acid metabolismaminoacyl tRNA biosynthesis
arachidonic acid metabolismbutanoate metabolism
ascorbate and aldarate metabolismcarbon fixation in photosynthetic organisms
biosynthesis of amino acidscarbon metabolism
circadian rhythm – plantDNA replication
cysteine and methionine metabolismfructose and mannose metabolism
fatty acid degradationglyoxylate and dicarboxylate metabolism
folate biosynthesisnicotinate and nicotinamide metabolism
glutathione metabolismnitrogen metabolism
glycine, serine, and threonine metabolismone carbon pool by folate
histidine metabolismother glycan degradation
lysine degradationpentose and glucuronate interconversions
peroxisomepentose phosphate pathway
phenylalanine, tyrosine, and tryptophan biosynthesisphagosome
protein processing in endoplasmic reticulumphotosynthesis
purine metabolismphotosynthesis antenna proteins
RNA degradationplant hormone signal transduction
spliceosomesteroid biosynthesis
sulfur metabolismterpenoid backbone biosynthesis
valine, leucine, and isoleucine degradationvarious types of N-glycan biosynthesis
There is evidence that botrytis susceptible 1 (BOS1) and botrytis susceptible interactor (BOI) seem to restrict pathogen-induced necrosis. (3) Our GSEA results show that the BOI gene is overrepresented in plants treated with cinnamon NE. This gene has E3 ubiquitin ligase activity and interacts with ubiquitinates BOS1, preventing caspase activation resulting in attenuation of cell death. (29) Gene biomarker VTI11, encoding a member of soluble N-ethylmaleimide-sensitive-factor attachment protein receptor (SNARE) gene family was also significantly enriched. Components of the SNARE machinery are required for the fusion process and autophagosome membrane expansion. (64) This may explain the reason why KEGG annotations for the GSEA of DEGs indicate that the snare interaction in vesicular transport (ath04130) was significantly enriched (Supplementary data set 3: Functional analysis of DEG-GSEA-KEGG-Cinnamon NE vs Control).
Figure 3b indicates that, in general, biological processes involved in carbon and energy metabolism were significantly downregulated. This is consistent with the fact that tight linkages between autophagy and energy metabolism, particularly sugar signaling, exist. (62) One of the overrepresented GO terms in the plants treated with cinnamon NE was the ATI2 gene. This gene encodes an Atg8-interacting protein. This interaction contributes to the selective autophagy, targeting mitochondria, protein aggregates, chloroplasts, and invading pathogens that are critical for stress tolerance. (62)
KEGG notations from the GSEA indicate that the most significantly enriched pathway from the treated plants correspond to the control of the α-linoleic acid metabolism (Supplementary Data set 3: Functional analysis of DEG-GSEA-KEGG-Cinnamon NE vs Control). As discussed before, linolenic acid is a precursor for the biosynthesis of JA via β-oxidation. A key element in the formulation of EONEs is the addition of soybean oil as a viscosity modulator. Hence, the function of SBO in the EONEs is dual: It facilitates the formation of EO nanosized droplets and promotes the JA response in plants, resulting in enhanced QDR. Gene ontologies related to the biosynthesis of JA (see Table 2) support this conclusion.
Finally, the glutathione metabolism and the cysteine and methionine metabolism were among the major metabolic pathways that were significantly enriched in the treated plants (see Table 2). In plants, glutathione, a paramount hallmark of stress-related response, was involved in the cell detoxification of ROS. (65,66) Cysteine is the metabolic precursor of glutathione and other key components involved in signal transduction in plants under stress. (67)

Conclusions

Click to copy section linkSection link copied!

The nascent field of phytobiome research attempts to overcome the challenge of reconciling our understanding in the fields of agriculture and ecology while helping to engineer strategies for better crop and ecosystem management. (15) Similarly, the concepts of “hormesis” and “biphasic mechanism” are generally considered as two independent forms of biological response, ergo, the research efforts and literature describing these were historically diverted into the fields of toxicology and pharmacology. And last, through this work, we show that drug delivery concepts traditionally restricted to biomedical applications can be brought into the realm of agriculture. (10)
We noted that EONEs from cinnamon, clove, coriander, and red thyme significantly enhanced the QDR in the model plant-pathogen system, A. thaliana-B. cinerea, under controlled experimental conditions. Given the enhanced effect of cinnamon nanoemulsions, RNA-seq analyses with cinnamon nanocarrier treated plants show that the main physiological processes enabling the enhancement of QDR are related to the upregulation of autophagy, JA-dependent cell-to-cell communication, and ROS scavenging detoxification. These combined processes allowed the tight control of hypersensitive response, hindering disease progression. Further work under real field conditions comparing the effectiveness of EONEs against a gold standard, for the control of B. cinerea or other broad host-range necrotrophic pathogens, will provide additional data on field efficacy.

Methods

Click to copy section linkSection link copied!

Nanoemulsion Formulation and Fabrication

Materials

Commercially available 100% pure EO from cinnamon (Cinnamomum cassia) and peppermint (Mentha piperita) (Now Foods, Bloomingdale, IL, USA), clove bud, oregano, coriander seed, geranium, and red thyme (Aura Acacia, Urbana, IA, USA) were used for the preparation of nanoemulsions. Commercially available soybean oil (The J.M. Smucker Co., Orrville, OH, USA) was used to modulate the viscosity of the organic phase of nanoemulsion (NE). Propylene glycol (Ward’s Science, West Henrietta, NY, USA) and polyethylene glycol (PEG) 4000 (ref 95904 Fluka, Thermo Fisher Scientific; Waltham, MA, USA) were used to modulate the viscosity of the aqueous phase of NE. Tween80 (P4780, Sigma-Aldrich, St. Louis, MO, USA) was used as a surfactant agent during the emulsification process. All materials/reagents were used as received.

Viscosity Measurements

Dynamic viscosity was measured from 5 different blends of EOs and soybean oil at a ratio of 95:5, 90:10, 80:20, 75:25, 50:50, and 5:95 (percentage weight), respectively. PEG4000 and propylene glycol were used as models of aqueous phase viscosity modulators. The dynamic viscosity was measured from 4 different concentrations of each of the polymers: 75%, 50%, 25%, and 10% (w/w). Viscosity measurements were performed in triplicate (Model SVM3001 Anton Paar) at 25 °C.

Surface Tension Measurements

50 g of PEG400 and propylene glycol in dH2O were prepared at 75%, 50%, 25%, and 10% (w/w). For measuring the surface tension, the Wilhelmy method was performed with a platinum plate using force tensiometer K100MKII goniometer K100 (Krüss Hamburg, Germany). The surface tension measurements from each sample were conducted at room temperature for 60 s recording data every 10 s. Experiments were performed in triplicate per sample. Results are expressed as an average between replicas (n = 3). The aluminum plate was torched–cleaned before each new measurement.

Characterization of Essential Oils Used in Bioactive Nanoemulsions via GC-MS

The component identification was achieved by gas chromatography (7890B, Agilent, Santa Clara, CA, USA) and mass spectrometry (Micromass GCT Premier, Waters, Milford, MA, USA). DB-5 GC column (Agilent) was used for GC. Essential oil samples were diluted with hexane. The instrument setting were adjusted such that the flow was kept constant at a rate of 1 mL/min using helium as carrier gas, and the injection had a split of 60:1 ratio. The column temperature was set to increase from 40 to 250 °C at a rate of 6 °C/min, with a 2 min plateau at the beginning and end of the ramp. The temperature for MS analysis was set at 180 °C and an electron energy of 70 eV. MassLynx (Waters) software was used to perform MS analysis.

Nanoemulsion Formation

The spontaneous emulsification method is explained by Komaiko and McClements. (26) In our work, the organic phase consisted of 5% (w/w) of a 95:5 (% w/w) blend of EO:SBO thoroughly mixed with Tween80 at a weight ratio of 3:1. The surfactant and the oil phase were mixed under magnetic stirring at room temperature for 2–3 min. The freshly formed organic phase was then titrated at a rate of 0.5 mL/min into 95% (w/w) of aqueous phase containing either propylene glycol or PEG4000 at one of the previously mentioned concentrations (i.e., 75, 50, 25, and 10 (% w/w)). The aqueous phase was kept at a constant magnetic stirring speed of 500 rpm at room temperature. The formed nanoemulsion was kept under magnetic stirring for 2–3 min after the organic phase was fully added into the aqueous phase.

Nanoemulsion Particle Size Characterization

Dynamic Light Scattering

Only translucent emulsions were selected for particle size distribution analysis. Nanoemulsion particle size distribution was measured with dynamic light scattering (Nano ZS, Malvern, Worcestershire, UK) at a scattering angle of 173° using a 633 nm laser with each measurement at an average of 11 runs, each of 10 s duration. Undiluted freshly prepared samples were measured at 25 °C, and results are reported as an average of two measurements. The average emulsion droplet size diameter and polydispersity of each sample were obtained from the cumulative analysis of the sample correlation function.

Transmission Electron Microscopy

Formvar carbon film 400 mesh copper TEM grids were negatively charged using a PELCO easiGlow discharge flow at 10 mA for 1 min in order to allow aqueous solutions to spread easily on the grid’s surface. After glow discharge, 1.5 μL of translucent, freshly prepared undiluted nanoemulsion sample was placed onto the TEM grid surface along with 1.5 μL of 1% uranyle acetate 1 N in water in order increase image contrast. The TEM grid containing the nanoemulsion sample and the negative stain was allowed to rest for 1 min. TEM images were acquired using a Tecnai T12 (120 kV) transmission electron microscope.

Dynamic Morpho-Physiological Assessment of the Systemic Effect of Nanoemulsions on the Plants’ Defense Immune System in Wild-Type A. thaliana (Col-0)

Plant Material and Growing Conditions

In order to assess the systemic effect of EONEs on the innate immune mechanism of plants, a system to grow plants hydroponically was adopted (69) using A. thaliana wild type (Col-0) as a biological model. In this approach, access to the radicular system of the plant is enabled without compromising the integrity of plants.
Briefly, two to three individual seeds were carefully placed on a seed holder (pierced black microcentrifuge lid) containing germination medium agar. Seed holders loaded with seeds were placed in germination boxes containing germination nutrient solution, and then seeds were stratified at 4 °C for 48 h in darkness. After the stratification period, germination boxes were incubated under a 12 h:12 h day/night photoperiod with an irradiance of 150 μmol photons m2/s at the plant level, at 24 °C and 55% atmospheric relative humidity. On day 4 postgermination, extra seedlings were carefully removed from seed holders to guarantee one plant per holder only. After 7 days of germination, the germination solution was gradually replaced with basal nutrient solution (BNS) daily for 3 days, replacing 33%, 50%, and 100%, respectively. A week later, 14-day old seedlings were individually transferred to 50 mL plant holders containing BNS and further incubated for two more weeks. Four-week old plants were used for further experimentation.

Multispectral Image-Based Phenotype Assessment of Treated Plants

Roots from 4-week old plants were treated with freshly prepared EONEs at two different concentrations (50 and 500 μg/mL) under hydroponic conditions. BNS was leveled up to 50 mL after dissolution of each treatment. A set of nine individual plants were used for each of the experimental condition, whereas a set of nine untreated, independently grown seedlings under identical hydroponic conditions were used as control group, per tested concentration. Image-based phenotyping analysis was performed using an ARIS B.V automatic top-view imaging machine vision system equipped with a multispectral light source (Aris, Eindhoven, Netherlands). The chlorophyll-based masking segmentation was used to measure the area of the plant rosette immediately after treatment (t = 0) and then every 24 h for three consecutive days. The treated plants were kept under controlled conditions, previously described. On day 3, plants were flash-frozen with liquid nitrogen and stored at −80 °C. A two-way ANOVA was performed to assess the interaction between each of the concentration levels under investigation every 24 h, over a 72 h time period, for each treatment.

Assessment of Systemic Effect of Treatments on the QDR against B. cinereavia Image-Based Phenotyping

The roots from 4-week old plants were treated as previously described on image-based phenotyping of treated plants (see Scheme 1). Fungal disease was evaluated as previously described. (70) Briefly, for the B. cinerea disease assay, four leaves per plant from five pretreated 4-week old plants were drop inoculated with a conidial suspension (2.5 × 105 spores/mL) of B. cinerea strain B05.10 in 1% Sabouraud maltose broth and maintained under a transparent cover at high humidity for 72 h. Four leaves per plant from a set of five untreated, independently grown seedlings under identical hydroponic conditions, were infected as previously described to be used as control group. The lesion area size per leaf was measured via image-based phenotyping analysis using an ARIS B.V. automatic top-view imaging machine equipped with a multispectral light source (Aris, Eindhoven, Netherlands). The chlorophyll-based masking segmentation was used to distinguish necrotic tissue in leaves. The statistical analysis was carried out by conducting a balanced nested ANOVA on the necrotic area of the infected leaves per plant for each of the treatments (n = 20).

Physiological Assessment of Treated Plants via RNA-seq

Plant tissue was grounded with pestle and mortar with liquid nitrogen, and total RNA was extracted with Trizol reagent according to the manufacturer’s instructions (Sigma-Aldrich). Three independent biological replicates per condition were used to quantitatively assess the differential gene expression between treated plants against untreated plants (control) with RNA-seq. Illumina sequencing was carried out by Novogene Bioinformatics Technology Co., Ltd., in Beijing, China.

Statistical Analysis

Multispectral Image-Based Phenotype Assessment of Treated Plants

For statistical analysis, an orthogonal model was used with nine independent plants for each of the concentrations of EONEs under study. A two-way ANOVA was conducted to evaluate the effect of each of the different levels of tested concentrations on the relative rosette area growth over three time points, per treatment. A pairwise comparison using Tukey HSD test was conducted to compare differences between LS-means for each of the levels in the model. A value for α = 0.01 was set to establish statistical significance.

Phenotypical and Physiological Assessment of the Systemic Effect of EONEs on QDR of A. thaliana (Col-0) against B. cinereavia Image-Based Phenotyping

Phenotyping assessment of the effect of EONEs was quantitatively assessed by measuring the resulting necrotic area 72 h postinfection, from four different leaves per plant. Five independent plants were used as biological replicates per treatment. A nested ANOVA model was carried out to assess the effect of treatments on the QDR in the plant-pathogen model system under study. (72) Statistical significance was set at α = 0.01.

Differential Gene Expression Analysis

The gene expression levels between two different experimental conditions (treatment vs Control) were compared. The experimental groups consisted of three biological replicates. The differential expression analysis between the two experimental conditions was performed using the DESeq2 R package according to Anders, 2010. (71) The DESeq2 R package provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. Therefore, if the read count of the i-th gene in j-th sample is Kij, and the resulting p-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate:

Functional Analysis

GO and KEGG enrichment analyses were conducted with adjusted p-value <0.05 to assess statistical significance. Significantly enriched metabolic or signal transduction pathways associated with DEGs, compared to the whole genome background from the KEEG analysis, was conducted as described by Kanehisa, 200072:
where N is the number of all the genes with a KEGG annotation, n is the number of DEGs in N, M is number of all genes annotated to specific pathways, and m is the number of DEGs in M.

Supporting Information

Click to copy section linkSection link copied!

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsnano.0c09759.

  • EONEs formulation, production, and characterization; assessment of the dose-dependent response of EONEs in the plant-pathogen model system A. thaliana (Col-0)-B.cinerea via image-based phenotyping; systemic effect of EONEs on the QDR in the pathosystem used in this study (PDF)

Terms & Conditions

Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

Click to copy section linkSection link copied!

  • Corresponding Author
    • Joseph Irudayaraj - Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United StatesDepartment of Bioengineering, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United StatesOrcidhttp://orcid.org/0000-0002-0630-1520 Email: [email protected]
  • Authors
    • Pablo Vega-Vásquez - Laboratory of Renewable Resources Engineering (LORRE), Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United StatesDepartment of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United States
    • Nathan S. Mosier - Laboratory of Renewable Resources Engineering (LORRE), Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United StatesDepartment of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana 47907, United StatesOrcidhttp://orcid.org/0000-0003-0258-644X
  • Author Contributions

    P.V.-V. and J.I. conceived the idea. P.V.-V. designed and carried out the experiments, analyzed the data, and wrote the initial manuscript. N.M. and J.I. supervised the findings of this work and discussed experiments and results. All authors contributed to writing the manuscript.

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

Click to copy section linkSection link copied!

The authors thank Prof. Tesfaye Mengiste and Dr. Chao-Jan Liao from the department of Botany and plant pathology at Purdue University (West Lafayette, IN, USA) for providing the B. cinerea strain B05.10 and A. thaliana (Col-0) seed and technical support for the plant-pathogen interaction experiments. Partial funding from the Colombian Ministry of Science and Technology is appreciated. The authors thank Yi Wen from the Department of Bioengineering at UIUC, for the GC/MS analysis.

References

Click to copy section linkSection link copied!

This article references 72 other publications.

  1. 1
    Lai, Z.; Mengiste, T. Genetic and Cellular Mechanisms Regulating Plant Responses to Necrotrophic Pathogens. Curr. Opin. Plant Biol. 2013, 16 (4), 505512,  DOI: 10.1016/j.pbi.2013.06.014
  2. 2
    Dean, R.; Van Kan, J. A. L.; Pretorius, Z. A.; Hammond-kosack, K. E.; Di Pietro, A.; Spanu, P. D.; Rudd, J. J.; Dickman, M.; Kahmann, R.; Ellis, J.; Foster, G. D. The Top 10 Fungal Pathogens in Molecular Plant Pathology. Mol. Plant Pathol. 2012, 13 (4), 414430,  DOI: 10.1111/j.1364-3703.2011.00783.x
  3. 3
    Mengiste, T. Plant Immunity to Necrotrophs. Annu. Rev. Phytopathol. 2012, 50 (1), 267294,  DOI: 10.1146/annurev-phyto-081211-172955
  4. 4
    Laluk, K.; Mengiste, T. Necrotroph Attacks on Plants: Wanton Destruction or Covert Extortion?. Arabidopsis Book 2010, 8, 134,  DOI: 10.1199/tab.0136
  5. 5
    Hua, L.; Yong, C.; Zhanquan, Z.; Boqiang, L.; Guozheng, Q.; Shiping, T. Pathogenic Mechanisms and Control Strategies of Botrytis cinerea Causing Post-Harvest Decay in Fruits and Vegetables. Food Qual. Saf. 2018, 2, 111119,  DOI: 10.1093/fqsafe/fyy016
  6. 6
    Fernandez-Ortuno, D.; Grabke, A.; Li, X.; Schnabel, G. Independent Emergence of Resistance to Seven Chemical Classes of Fungicides in Botrytis cinerea. Phytopathology 2015, 105 (13), 424432,  DOI: 10.1094/PHYTO-06-14-0161-R
  7. 7
    Leroux, P. Chemical Control of Botrytis and Its Resistance to Chemical Fungicides. In Botrytis: Biology, Pathology and Control; Fillinger, S., Elad, Y., Eds.; Springer: Dordrecht, 2007; pp 195222.
  8. 8
    Hu, M.; Cox, K. D.; Schnabel, G. Resistance to Increasing Chemical Classes of Fungicides by Virtue of “ Selection by Association ” in Botrytis cinerea. Phytopathology 2016, 106 (12), 15131520,  DOI: 10.1094/PHYTO-04-16-0161-R
  9. 9
    Gilbertson, L. M.; Pourzahedi, L.; Laughton, S.; Gao, X.; Zimmerman, J. B.; Theis, T. L.; Westerhoff, P.; Lowry, G. V. Guiding the Design Space for Nanotechnology to Advance Sustainable Crop Production. Nat. Nanotechnol. 2020, 15 (9), 801810,  DOI: 10.1038/s41565-020-0706-5
  10. 10
    Vega-Vásquez, P.; Mosier, N. S.; Irudayaraj, J. Nanoscale Drug Delivery Systems: From Medicine to Agriculture. Front. Bioeng. Biotechnol. 2020, 8, 116,  DOI: 10.3389/fbioe.2020.00079
  11. 11
    Jansen, K. M. B.; Agterof, W. G. M.; Mellema, J. Droplet Breakup in Concentrated Emulsions. J. Rheol. (Melville, NY, U. S.) 2001, 45 (1), 227236,  DOI: 10.1122/1.1333001
  12. 12
    Wooster, T. J.; Moore, S. C.; Chen, W.; Andrews, H.; Addepalli, R.; Seymour, R. B.; Osborne, S. A. Biological Fate of Food Nanoemulsions and the Nutrients They Carry - Internalisation, Transport and Cytotoxicity of Edible Nanoemulsions in Caco-2 Intestinal Cells. RSC Adv. 2017, 7 (64), 4005340066,  DOI: 10.1039/C7RA07804H
  13. 13
    Sakai, A.; Yoshimura, H. Monoterpenes of Salvia leucophylla. Curr. Bioact. Compd. 2012, 8 (1), 90100,  DOI: 10.2174/157340712799828205
  14. 14
    Cheng, F.; Cheng, Z. Research Progress on the Use of Plant Allelopathy in Agriculture and the Physiological and Ecological Mechanisms of Allelopathy. Front. Plant Sci. 2015, 6, 116,  DOI: 10.3389/fpls.2015.01020
  15. 15
    Leach, J. E.; Triplett, L. R.; Argueso, C. T.; Trivedi, P. Communication in the Phytobiome. Cell 2017, 169 (4), 587596,  DOI: 10.1016/j.cell.2017.04.025
  16. 16
    Song, G. C.; Ryu, C. Two Volatile Organic Compounds Trigger Plant Self-Defense against a Bacterial Pathogen and a Sucking Insect in Cucumber under Open Field Conditions. Int. J. Mol. Sci. 2013, 14, 98039819,  DOI: 10.3390/ijms14059803
  17. 17
    Dave, A.; Graham, I. A. Oxylipin Signaling: A Distinct Role for the Jasmonic Acid Precursor Cis-(+)-12-Oxo-Phytodienoic Acid (Cis-OPDA). Front. Plant Sci. 2012, 3 (MAR), 16,  DOI: 10.3389/fpls.2012.00042
  18. 18
    Holopainen, J. K.; Blande, J. D. Where Do Herbivore-Induced Plant Volatiles Go?. Front. Plant Sci. 2013, 4, 113,  DOI: 10.3389/fpls.2013.00185
  19. 19
    Jones, J. D. G.; Vance, R. E.; Dangl, J. L. Intracellular Innate Immune Surveillance Devices in Plants and Animals. Science 2016, 354, 11171125,  DOI: 10.1126/science.aaf6395
  20. 20
    Kushalappa, A. C.; Yogendra, K. N.; Karre, S. Plant Innate Immune Response: Qualitative and Quantitative Resistance. Crit. Rev. Plant Sci. 2016, 35 (1), 3855,  DOI: 10.1080/07352689.2016.1148980
  21. 21
    Mattson, M. P. Hormesis Defined. Ageing Res. Rev. 2008, 7 (1), 17,  DOI: 10.1016/j.arr.2007.08.007
  22. 22
    Calabrese, E. J.; Mattson, M. P. How Does Hormesis Impact Biology, Toxicology, and Medicine?. npj Aging Mech. Dis. 2017, 3 (1), 18,  DOI: 10.1038/s41514-017-0013-z
  23. 23
    Vargas-Hernandez, M.; Macias-Bobadilla, I.; Guevara-Gonzalez, R. G.; Romero-Gomez, S. de J.; Rico-Garcia, E.; Ocampo-Velazquez, R. V.; Alvarez-Arquieta, L. de L.; Torres-Pacheco, I. Plant Hormesis Management with Biostimulants of Biotic Origin in Agriculture. Front. Plant Sci. 2017, 8, 111,  DOI: 10.3389/fpls.2017.01762
  24. 24
    Wooster, T. J.; Golding, M.; Sanguansri, P. Impact of Oil Type on Nanoemulsion Formation and Ostwald Ripening Stability. Langmuir 2008, 24 (22), 1275812765,  DOI: 10.1021/la801685v
  25. 25
    Rao, J.; McClements, D. J. Impact of Lemon Oil Composition on Formation and Stability of Model Food and Beverage Emulsions. Food Chem. 2012, 134 (2), 749757,  DOI: 10.1016/j.foodchem.2012.02.174
  26. 26
    Komaiko, J. S.; McClements, D. J. Formation of Food-Grade Nanoemulsions Using Low-Energy Preparation Methods: A Review of Available Methods. Compr. Rev. Food Sci. Food Saf. 2016, 15, 331352,  DOI: 10.1111/1541-4337.12189
  27. 27
    Park, J.; Lee, J.; McClements, D. J.; Choi, S. J. Inhibition of Droplet Growth in Model Beverage Emulsions Stabilized Using Poly (ethylene glycol) Alkyl Ether Surfactants Having Various Hydrophilic Head Sizes: Impact of Ester Gum. Appl. Sci. 2020, 10, 5588,  DOI: 10.3390/app10165588
  28. 28
    De Coninck, B.; Timmermans, P.; Vos, C.; Cammue, B. P.A.; Kazan, K. What Lies Beneath: Belowground Defense Strategies in Plants. Trends Plant Sci. 2015, 20 (2), 91101,  DOI: 10.1016/j.tplants.2014.09.007
  29. 29
    Luo, H.; Laluk, K.; Lai, Z.; Veronese, P.; Song, F.; Mengiste, T. The Arabidopsis Botrytis Susceptible1 Interactor Defines a Subclass of RING E3 Ligases That Regulate Pathogen and Stress Responses. Plant Physiol. 2010, 154 (4), 17661782,  DOI: 10.1104/pp.110.163915
  30. 30
    Abuqamar, S.; Moustafa, K.; Tran, L. S. Mechanisms and Strategies of Plant Defense against Botrytis cinerea. Crit. Rev. Biotechnol. 2017, 37 (2), 262274,  DOI: 10.1080/07388551.2016.1271767
  31. 31
    Sharifi-Rad, J.; Sureda, A.; Tenore, G. C.; Daglia, M.; Sharifi-Rad, M.; Valussi, M.; Tundis, R.; Sharifi-Rad, M.; Loizzo, M. R.; Oluwaseun Ademiluyi, A.; Sharifi-Rad, R.; Ayatollahi, S. A.; Iriti, M. Biological Activities of Essential Oils: From Plant Chemoecology to Traditional Healing Systems. Molecules 2017, 22 (1), 155,  DOI: 10.3390/molecules22010070
  32. 32
    Huang, H.; Liu, B.; Liu, L.; Song, S. Jasmonate Action in Plant Growth and Development. J. Exp. Bot. 2017, 68 (6), 13491359,  DOI: 10.1093/jxb/erw495
  33. 33
    West, R.; Banton, M.; Hu, J.; Klapacz, J.; Whitacre, D. The Distribution, Fate, and Effects of Propylene Glycol Substances in the Environment. Rev. Environ. Contam. Toxicol. 2014, 232, 107138,  DOI: 10.1007/978-3-319-06746-9_5
  34. 34
    Jones, J. D. G.; Dangl, J. L. The Plant Immune System. Nature 2006, 444 (7117), 323329,  DOI: 10.1038/nature05286
  35. 35
    Wasternack, C.; Hause, B. The Missing Link in Jasmonic Acid Biosynthesis. Nat. Plants 2019, 5 (8), 776777,  DOI: 10.1038/s41477-019-0492-y
  36. 36
    Wasternack, C.; Strnad, M. Jasmonates: News on Occurrence, Biosynthesis, Metabolism and Action of an Ancient Group of Signaling Compounds. Int. J. Mol. Sci. 2018, 19, 2539,  DOI: 10.3390/ijms19092539
  37. 37
    Ruan, J.; Zhou, Y.; Zhou, M.; Yan, J.; Khurshid, M.; Weng, W.; Cheng, J.; Zhang, K. Jasmonic Acid Signaling Pathway in Plants. Int. J. Mol. Sci. 2019, 20, 2479,  DOI: 10.3390/ijms20102479
  38. 38
    Ahmad, P.; Rasool, S.; Gul, A.; Sheikh, S. A.; Akram, N. A.; Ashraf, M.; Kazi, A. M.; Gucel, S. Jasmonates: Multifunctional Roles in Stress Tolerance. Front. Plant Sci. 2016, 7, 115,  DOI: 10.3389/fpls.2016.00813
  39. 39
    Huot, B.; Yao, J.; Montgomery, B. L.; He, S. Y. Growth-Defense Tradeoffs in Plants: A Balancing Act to Optimize Fitness. Mol. Plant 2014, 7 (8), 12671287,  DOI: 10.1093/mp/ssu049
  40. 40
    Ho, T. T.; Murthy, H. N.; Park, S. Y. Methyl Jasmonate Induced Oxidative Stress and Accumulation of Secondary Metabolites in Plant Cell and Organ Cultures. Int. J. Mol. Sci. 2020, 21, 716,  DOI: 10.3390/ijms21030716
  41. 41
    Glazebrook, J. Contrasting Mechanisms of Defense against Biotrophic and Necrotrophic Pathogens. Annu. Rev. Phytopathol. 2005, 43, 205227,  DOI: 10.1146/annurev.phyto.43.040204.135923
  42. 42
    Rao, P. V.; Gan, S. H. Cinnamon: A Multifaceted Medicinal Plant. Evidence-based Complement. Altern. Med. 2014, 2014, 112,  DOI: 10.1155/2014/642942
  43. 43
    Nurdjannah, N.; Bermawie, N. Cloves. In Handbook of Herbs and Spices, 2nd ed.; Peter, K. V., Ed.; Woodhead Publishing Ltd: London, 2012; Vol. 1, pp 197215.
  44. 44
    Mandal, S.; Mandal, M. Coriander (Coriandrum sativum L.) Essential Oil: Chemistry and Biological Activity. Asian Pac. J. Trop. Biomed. 2015, 5 (6), 421428,  DOI: 10.1016/j.apjtb.2015.04.001
  45. 45
    Borugă, O.; Jianu, C.; Mişcă, C.; Goleţ, I.; Gruia, A. T.; Horhat, F. G. Thymus vulgaris Essential Oil: Chemical Composition and Antimicrobial Activity. J. Med. Life 2014, 7, 5660
  46. 46
    Yoon, M. Y.; Cha, B.; Kim, J. C. Recent Trends in Studies on Botanical Fungicides in Agriculture. Plant Pathol. J. 2013, 29 (1), 19,  DOI: 10.5423/PPJ.RW.05.2012.0072
  47. 47
    Wang, C.; Fan, Y. Eugenol Enhances the Resistance of Tomato against Tomato Yellow Leaf Curl Virus. J. Sci. Food Agric. 2014, 94 (4), 677682,  DOI: 10.1002/jsfa.6304
  48. 48
    Banani, H.; Olivieri, L.; Santoro, K.; Garibaldi, A.; Gullino, M. L.; Spadaro, D. Thyme and Savory Essential Oil Efficacy and Induction of Resistance against Botrytis cinerea through Priming of Defense Responses in Apple. Foods 2018, 7 (2), 11,  DOI: 10.3390/foods7020011
  49. 49
    Tanaka, K.; Taniguchi, S.; Tamaoki, D.; Yoshitomi, K.; Akimitsu, K.; Gomi, K. Multiple Roles of Plant Volatiles in Jasmonate-Induced Defense Response in Rice. Plant Signaling Behav. 2014, 9, e29247,  DOI: 10.4161/psb.29247
  50. 50
    Rienth, M.; Crovadore, J.; Ghaffari, S.; Lefort, F. Oregano Essential Oil Vapour Prevents Plasmopara viticola Infection in Grapevine (Vitis vinifera) and Primes Plant Immunity Mechanisms. PLoS One 2019, 14 (9), e0222854,  DOI: 10.1371/journal.pone.0222854
  51. 51
    Alvarez, A.; Montesano, M.; Schmelz, E.; Ponce de León, I. Activation of Shikimate, Phenylpropanoid, Oxylipins, and Auxin Pathways in Pectobacterium carotovorum Elicitors-Treated Moss. Front. Plant Sci. 2016, 7 (328), 114,  DOI: 10.3389/fpls.2016.00328
  52. 52
    Moore, J. W.; Loake, G. J.; Spoel, S. H. Transcription Dynamics in Plant Immunity. Plant Cell 2011, 23 (8), 28092820,  DOI: 10.1105/tpc.111.087346
  53. 53
    Shitan, N. Secondary Metabolites in Plants: Transport and Self-Tolerance Mechanisms. Biosci., Biotechnol., Biochem. 2016, 80, 12831293,  DOI: 10.1080/09168451.2016.1151344
  54. 54
    Shitan, N.; Sugiyama, A.; Yazaki, K. Functional Analysis of Jasmonic Acid-Responsive Secondary Metabolite Transporters. Methods Mol. Biol. 2013, 1011, 241250,  DOI: 10.1007/978-1-62703-414-2_19
  55. 55
    Subramanian, A.; Tamayo, P.; Mootha, V. K.; Mukherjee, S.; Ebert, B. L.; Gillette, M. A.; Paulovich, A.; Pomeroy, S. L.; Golub, T. R.; Lander, E. S.; Mesirov, J. P. Gene Set Enrichment Analysis: A Knowledge-Based Approach for Interpreting Genome-Wide Expression Profiles. Proc. Natl. Acad. Sci. U. S. A. 2005, 102 (43), 1554515550,  DOI: 10.1073/pnas.0506580102
  56. 56
    Ikram, R.; Low, K. H.; Hashim, N. B.; Ahmad, W.; Nasharuddin, M. N. A. Characterization of Sulfur-Compounds as Chemotaxonomic Markers in the Essential Oils of Allium Species by Solvent-Free Microwave Extraction and Gas Chromatography-Mass Spectrometry. Anal. Lett. 2019, 52 (4), 563574,  DOI: 10.1080/00032719.2018.1479411
  57. 57
    Kasaian, J.; Asili, J.; Iranshahi, M. Sulphur-Containing Compounds in the Essential Oil of Ferula alliacea Roots and Their Mass Spectral Fragmentation Patterns. Pharm. Biol. 2016, 54 (10), 22642268,  DOI: 10.3109/13880209.2016.1152279
  58. 58
    Zhang, N.; Zhou, S.; Yang, D.; Fan, Z. Revealing Shared and Distinct Genes Responding to JA and SA Signaling in Arabidopsis by Meta-Analysis. Front. Plant Sci. 2020, 11 (908), 117,  DOI: 10.3389/fpls.2020.00908
  59. 59
    Qi, J.; Li, J.; Han, X.; Li, R.; Wu, J.; Yu, H.; Hu, L.; Xiao, Y.; Lu, J.; Lou, Y. Jasmonic Acid Carboxyl Methyltransferase Regulates Development and Herbivory-Induced Defense Response in Rice. J. Integr. Plant Biol. 2016, 58 (6), 564576,  DOI: 10.1111/jipb.12436
  60. 60
    Lai, Z.; Wang, F.; Zheng, Z.; Fan, B.; Chen, Z. A Critical Role of Autophagy in Plant Resistance to Necrotrophic Fungal Pathogens. Plant J. 2011, 66 (6), 953968,  DOI: 10.1111/j.1365-313X.2011.04553.x
  61. 61
    Beese, C. J.; Brynjólfsdóttir, S. H.; Frankel, L. B. Selective Autophagy of the Protein Homeostasis Machinery: Ribophagy, Proteaphagy and ER-Phagy. Front. Cell Dev. Biol. 2020, 7 (373), 112,  DOI: 10.3389/fcell.2019.00373
  62. 62
    Kabbage, M.; Kessens, R.; Bartholomay, L. C.; Williams, B. The Life and Death of a Plant Cell. Annu. Rev. Plant Biol. 2017, 68 (1), 375404,  DOI: 10.1146/annurev-arplant-043015-111655
  63. 63
    Su, T.; Li, X.; Yang, M.; Shao, Q.; Zhao, Y.; Ma, C.; Wang, P. Autophagy: An Intracellular Degradation Pathway Regulating Plant Survival and Stress Response. Front. Plant Sci. 2020, 11 (164), 116,  DOI: 10.3389/fpls.2020.00164
  64. 64
    Liu, Y.; Bassham, D. C. Autophagy: Pathways for Self-Eating in Plant Cells. Annu. Rev. Plant Biol. 2012, 63 (1), 215237,  DOI: 10.1146/annurev-arplant-042811-105441
  65. 65
    Hasanuzzaman, M.; Nahar, K.; Anee, T. I.; Fujita, M. Glutathione in Plants: Biosynthesis and Physiological Role in Environmental Stress Tolerance. Physiol. Mol. Biol. Plants 2017, 23 (2), 249268,  DOI: 10.1007/s12298-017-0422-2
  66. 66
    Hameed, A.; Sharma, I.; Kumar, A.; Azooz, M. M.; Ahmad, H. Glutathione Metabolism in Plants under Environmental Stress. In Oxidative Damage to Plants; Ahmad, P., Ed.; Elsevier Inc.: Amsterdam, 2014; pp 183200.
  67. 67
    Romero, L. C.; Aroca, M. Á.; Laureano-Marín, A. M.; Moreno, I.; García, I.; Gotor, C. Cysteine and Cysteine-Related Signaling Pathways in Arabidopsis thaliana. Mol. Plant 2014, 7 (2), 264276,  DOI: 10.1093/mp/sst168
  68. 68
    Gupta, A.; Badruddoza, A. Z. M.; Doyle, P. S. A General Route for Nanoemulsion Synthesis Using Low-Energy Methods at Constant Temperature. Langmuir 2017, 33 (28), 71187123,  DOI: 10.1021/acs.langmuir.7b01104
  69. 69
    Conn, S. J.; Hocking, B.; Dayod, M.; Xu, B.; Athman, A.; Henderson, S.; Aukett, L.; Conn, V.; Shearer, M. K.; Fuentes, S.; Tyerman, S. D.; Gilliham, M. Protocol: Optimising Hydroponic Growth Systems for Nutritional and Physiological Analysis of Arabidopsis thaliana and Other Plants. Plant Methods 2013, 9 (4), 111,  DOI: 10.1186/1746-4811-9-4
  70. 70
    Liao, C. J.; Lai, Z.; Lee, S.; Yun, D. J.; Mengiste, T. Arabidopsis HOOKLESS1 Regulates Responses to Pathogens and Abscisic Acid through Interaction with MED18 and Acetylation of WRKY33 and ABI5 Chromatin. Plant Cell 2016, 28 (7), 16621681,  DOI: 10.1105/tpc.16.00105
  71. 71
    Roberts, A.; Trapnell, C.; Donaghey, J.; Rinn, J. L.; Pachter, L. Improving RNA-Seq Expression Estimates by Correcting for Fragment Bias. Genome Biol. 2011, 12, R22,  DOI: 10.1186/gb-2011-12-3-r22
  72. 72
    Kanehisa, M.; Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research 2000, 28 (1), 2730,  DOI: 10.1093/nar/28.1.27

Cited By

Click to copy section linkSection link copied!
Citation Statements
Explore this article's citation statements on scite.ai

This article is cited by 11 publications.

  1. Pablo Vega-Vásquez, Nathan S. Mosier, Joseph Irudayaraj. Nanovaccine for Plants from Organic Waste: d-Limonene-Loaded Chitosan Nanocarriers Protect Plants against Botrytis cinerea. ACS Sustainable Chemistry & Engineering 2021, 9 (29) , 9903-9914. https://doi.org/10.1021/acssuschemeng.1c02818
  2. Peng Yu, Xu Peng, Hui Sun, Qiangwei Xin, Han Kang, Peng Wang, Yao Zhao, Xinyuan Xu, Guangwu Zhou, Jing Xie, Jianshu Li. Inspired by lubricin: a tailored cartilage-armor with durable lubricity and autophagy-activated antioxidation for targeted therapy of osteoarthritis. Materials Horizons 2024, 11 (21) , 5352-5365. https://doi.org/10.1039/D4MH00812J
  3. Jindi Wang, Fangyuan Zhao, Jinglin Huang, Qianyu Li, Qingli Yang, Jian Ju. Application of essential oils as slow-release antimicrobial agents in food preservation: Preparation strategies, release mechanisms and application cases. Critical Reviews in Food Science and Nutrition 2024, 64 (18) , 6272-6297. https://doi.org/10.1080/10408398.2023.2167066
  4. Sinem Karakus. Enhancing Post-Harvest Resilience: Investigating the Synergistic Effects of Essential Oil Combinations on Biochemical Profiles in Botrytis cinerea-Infected Apples. Horticulturae 2024, 10 (4) , 341. https://doi.org/10.3390/horticulturae10040341
  5. Maojie Zhang, Qiang Cao, Yuming Yuan, Xiaohan Guo, Dawei Pan, Rui Xie, Xiaojie Ju, Zhuang Liu, Wei Wang, Liangyin Chu. Functional nanoemulsions: Controllable low-energy nanoemulsification and advanced biomedical application. Chinese Chemical Letters 2024, 35 (2) , 108710. https://doi.org/10.1016/j.cclet.2023.108710
  6. Jianshu Li, Peng Yu, Xu Peng, Hui Sun, Qiangwei Xin, Han Kang, Peng Wang, Yao Zhao, Xinyuan Xu, Guangwu Zhou, Jing Xie. Cartilage–targeting and Autophagy–activating of A Lubricin–inspired Polyzwitterion for Osteoarthritis Therapy. 2023https://doi.org/10.21203/rs.3.rs-3708815/v1
  7. Pablo L. Godínez-Mendoza, Amanda K. Rico-Chávez, Noelia I. Ferrusquía-Jimenez, Ireri A. Carbajal-Valenzuela, Ana L. Villagómez-Aranda, Irineo Torres-Pacheco, Ramon G. Guevara-González. Plant hormesis: Revising of the concepts of biostimulation, elicitation and their application in a sustainable agricultural production. Science of The Total Environment 2023, 894 , 164883. https://doi.org/10.1016/j.scitotenv.2023.164883
  8. Chen Wang, Jinhui Wang, Dai Zhang, Jianing Cheng, Jiehua Zhu, Zhihui Yang, . Identification and functional analysis of protein secreted by Alternaria solani. PLOS ONE 2023, 18 (3) , e0281530. https://doi.org/10.1371/journal.pone.0281530
  9. Ved Prakash Giri, Pallavi Shukla, Ashutosh Tripathi, Priya Verma, Navinit Kumar, Shipra Pandey, Christian O. Dimkpa, Aradhana Mishra. A Review of Sustainable Use of Biogenic Nanoscale Agro-Materials to Enhance Stress Tolerance and Nutritional Value of Plants. Plants 2023, 12 (4) , 815. https://doi.org/10.3390/plants12040815
  10. Jun Ma, Yi Zhou, Jiaying Li, Zhiyong Song, Heyou Han. Novel approach to enhance Bradyrhizobium diazoefficiens nodulation through continuous induction of ROS by manganese ferrite nanomaterials in soybean. Journal of Nanobiotechnology 2022, 20 (1) https://doi.org/10.1186/s12951-022-01372-2
  11. Jelena Marinković, Biljana Nikolić, Tatjana Marković, Božana Petrović, Snežana Pašalić, Mohan Lal, Dejan Marković. Essential Oils as Adjuvants in Endodontic Therapy: Myth Or Reality?. Future Microbiology 2022, 17 (18) , 1487-1499. https://doi.org/10.2217/fmb-2022-0115
  12. Edward J. Calabrese, Evgenios Agathokleous, Vittorio Calabrese. Ferulic acid and hormesis: Biomedical and environmental implications. Mechanisms of Ageing and Development 2021, 198 , 111544. https://doi.org/10.1016/j.mad.2021.111544

ACS Nano

Cite this: ACS Nano 2021, 15, 5, 8338–8349
Click to copy citationCitation copied!
https://doi.org/10.1021/acsnano.0c09759
Published April 21, 2021

Copyright © 2021 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY-NC-ND 4.0 .

Article Views

1981

Altmetric

-

Citations

Learn about these metrics

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.

  • Abstract

    Scheme 1

    Scheme 1. Evaluation of EONEs via Quantitative Image-Based Phenotypinga

    aThe workflow presented is a representation of a multispectral image analysis system to assess the hormetic effect of EONEs on the QDR in the plant-pathogen model system A. thaliana-B. cinerea. Roots of 4-week-old A. thaliana (Col-0) are treated by dissolving the tested EONE in the basal nutrient solution, and the leaves are infected with the inoculum 24 h after treatment. Plants left untreated and uninfected are used as the control group. Images are collected daily for 3 days. During image acquisition, the automated system with the focused light beam on the plant rosettes collects information at different wavelengths. Chlorophyll absorbs short wavelength light (blue), and the longer (NIR) wavelength reflected light is filtered through a LP696 filter that blocks the ultraviolet (UV) and visible (vis) light. Collected images are automatically segmented based on their chlorophyll fluorescence. Lack of fluorescence from necrotic tissue is not displayed in the processed image.

    Figure 1

    Figure 1. Assessment of the hormetic dose-dependent response of A. thaliana to various EO nanoemulsions. The least-squares mean plots from the two-way ANOVA conducted for each of the concentrations under study represent the mean relative growth of the rosettes from a set of nine independently grown seedlings under identical hydroponic conditions. A set of nine untreated independently grown seedlings under identical hydroponic conditions were used as control group, per test concentration. Error bars represent 95% confidence interval of the LS means. To test the differences between LS means, the pairwise comparison Tukey HSD test was employed at alpha (α) = 0.01 to determine the statistical significance. Levels not connected by the same letter symbol (A, B, C, D) are significantly different.

    Figure 2

    Figure 2. Formation and characterization of stable EONEs under low-energy conditions by modulation of the viscosity differential with propylene glycol and soybean oil. (a) Schematic representation of the nanoemulsion formation process via spontaneous emulsification driven by modulation of the viscosity in continuous phase under mild conditions. (b) Effect of EONEs on the QDR in the plant-pathogen model system A. thaliana-B. cinerea assessed by automated phenotyping with chlorophyll fluorescence-based segmentation. Bars represent the mean and standard error of a nested model measuring necrotic areas from four leaves per plant and five plants per treatment. A set of five untreated and uninfected independently grown seedlings under identical hydroponic conditions were used as the control group. Statistical differences were evaluated per the nested ANOVA followed by a pairwise comparison with a Dunnett’s adjustment relative to the control group. Asterisks on top of the bars indicate a significant difference between the treatment and the control group (*p < 0.05 and **p < 0.001). Images in the bottom depict treatments. Images with mask and without mask (RGB) show image segmentation based on fluorescence emitted by chlorophyll upon excitation with blue light. Gaps in the leaves indicate areas of no fluorescence (i.e., necrotic areas). (c, d) Transmission electron micrographs from 9 month-old cinnamon nanoemulsion.

    Figure 3

    Figure 3. Mode of action of EONEs as hormetins. (a) Schematic representation of the mode of action of cinnamon EONEs in the activation of hormesis leads to enhanced QDR against BHNs in the plant-pathogen system A. thaliana-B. cinerea. (b) List of biological targets upregulated and downregulated upon exposure to cinnamon oil nanoemulsion relative to the control group. The control group consisted of a set of three untreated and independently grown plants under identical hydroponic conditions.

  • References


    This article references 72 other publications.

    1. 1
      Lai, Z.; Mengiste, T. Genetic and Cellular Mechanisms Regulating Plant Responses to Necrotrophic Pathogens. Curr. Opin. Plant Biol. 2013, 16 (4), 505512,  DOI: 10.1016/j.pbi.2013.06.014
    2. 2
      Dean, R.; Van Kan, J. A. L.; Pretorius, Z. A.; Hammond-kosack, K. E.; Di Pietro, A.; Spanu, P. D.; Rudd, J. J.; Dickman, M.; Kahmann, R.; Ellis, J.; Foster, G. D. The Top 10 Fungal Pathogens in Molecular Plant Pathology. Mol. Plant Pathol. 2012, 13 (4), 414430,  DOI: 10.1111/j.1364-3703.2011.00783.x
    3. 3
      Mengiste, T. Plant Immunity to Necrotrophs. Annu. Rev. Phytopathol. 2012, 50 (1), 267294,  DOI: 10.1146/annurev-phyto-081211-172955
    4. 4
      Laluk, K.; Mengiste, T. Necrotroph Attacks on Plants: Wanton Destruction or Covert Extortion?. Arabidopsis Book 2010, 8, 134,  DOI: 10.1199/tab.0136
    5. 5
      Hua, L.; Yong, C.; Zhanquan, Z.; Boqiang, L.; Guozheng, Q.; Shiping, T. Pathogenic Mechanisms and Control Strategies of Botrytis cinerea Causing Post-Harvest Decay in Fruits and Vegetables. Food Qual. Saf. 2018, 2, 111119,  DOI: 10.1093/fqsafe/fyy016
    6. 6
      Fernandez-Ortuno, D.; Grabke, A.; Li, X.; Schnabel, G. Independent Emergence of Resistance to Seven Chemical Classes of Fungicides in Botrytis cinerea. Phytopathology 2015, 105 (13), 424432,  DOI: 10.1094/PHYTO-06-14-0161-R
    7. 7
      Leroux, P. Chemical Control of Botrytis and Its Resistance to Chemical Fungicides. In Botrytis: Biology, Pathology and Control; Fillinger, S., Elad, Y., Eds.; Springer: Dordrecht, 2007; pp 195222.
    8. 8
      Hu, M.; Cox, K. D.; Schnabel, G. Resistance to Increasing Chemical Classes of Fungicides by Virtue of “ Selection by Association ” in Botrytis cinerea. Phytopathology 2016, 106 (12), 15131520,  DOI: 10.1094/PHYTO-04-16-0161-R
    9. 9
      Gilbertson, L. M.; Pourzahedi, L.; Laughton, S.; Gao, X.; Zimmerman, J. B.; Theis, T. L.; Westerhoff, P.; Lowry, G. V. Guiding the Design Space for Nanotechnology to Advance Sustainable Crop Production. Nat. Nanotechnol. 2020, 15 (9), 801810,  DOI: 10.1038/s41565-020-0706-5
    10. 10
      Vega-Vásquez, P.; Mosier, N. S.; Irudayaraj, J. Nanoscale Drug Delivery Systems: From Medicine to Agriculture. Front. Bioeng. Biotechnol. 2020, 8, 116,  DOI: 10.3389/fbioe.2020.00079
    11. 11
      Jansen, K. M. B.; Agterof, W. G. M.; Mellema, J. Droplet Breakup in Concentrated Emulsions. J. Rheol. (Melville, NY, U. S.) 2001, 45 (1), 227236,  DOI: 10.1122/1.1333001
    12. 12
      Wooster, T. J.; Moore, S. C.; Chen, W.; Andrews, H.; Addepalli, R.; Seymour, R. B.; Osborne, S. A. Biological Fate of Food Nanoemulsions and the Nutrients They Carry - Internalisation, Transport and Cytotoxicity of Edible Nanoemulsions in Caco-2 Intestinal Cells. RSC Adv. 2017, 7 (64), 4005340066,  DOI: 10.1039/C7RA07804H
    13. 13
      Sakai, A.; Yoshimura, H. Monoterpenes of Salvia leucophylla. Curr. Bioact. Compd. 2012, 8 (1), 90100,  DOI: 10.2174/157340712799828205
    14. 14
      Cheng, F.; Cheng, Z. Research Progress on the Use of Plant Allelopathy in Agriculture and the Physiological and Ecological Mechanisms of Allelopathy. Front. Plant Sci. 2015, 6, 116,  DOI: 10.3389/fpls.2015.01020
    15. 15
      Leach, J. E.; Triplett, L. R.; Argueso, C. T.; Trivedi, P. Communication in the Phytobiome. Cell 2017, 169 (4), 587596,  DOI: 10.1016/j.cell.2017.04.025
    16. 16
      Song, G. C.; Ryu, C. Two Volatile Organic Compounds Trigger Plant Self-Defense against a Bacterial Pathogen and a Sucking Insect in Cucumber under Open Field Conditions. Int. J. Mol. Sci. 2013, 14, 98039819,  DOI: 10.3390/ijms14059803
    17. 17
      Dave, A.; Graham, I. A. Oxylipin Signaling: A Distinct Role for the Jasmonic Acid Precursor Cis-(+)-12-Oxo-Phytodienoic Acid (Cis-OPDA). Front. Plant Sci. 2012, 3 (MAR), 16,  DOI: 10.3389/fpls.2012.00042
    18. 18
      Holopainen, J. K.; Blande, J. D. Where Do Herbivore-Induced Plant Volatiles Go?. Front. Plant Sci. 2013, 4, 113,  DOI: 10.3389/fpls.2013.00185
    19. 19
      Jones, J. D. G.; Vance, R. E.; Dangl, J. L. Intracellular Innate Immune Surveillance Devices in Plants and Animals. Science 2016, 354, 11171125,  DOI: 10.1126/science.aaf6395
    20. 20
      Kushalappa, A. C.; Yogendra, K. N.; Karre, S. Plant Innate Immune Response: Qualitative and Quantitative Resistance. Crit. Rev. Plant Sci. 2016, 35 (1), 3855,  DOI: 10.1080/07352689.2016.1148980
    21. 21
      Mattson, M. P. Hormesis Defined. Ageing Res. Rev. 2008, 7 (1), 17,  DOI: 10.1016/j.arr.2007.08.007
    22. 22
      Calabrese, E. J.; Mattson, M. P. How Does Hormesis Impact Biology, Toxicology, and Medicine?. npj Aging Mech. Dis. 2017, 3 (1), 18,  DOI: 10.1038/s41514-017-0013-z
    23. 23
      Vargas-Hernandez, M.; Macias-Bobadilla, I.; Guevara-Gonzalez, R. G.; Romero-Gomez, S. de J.; Rico-Garcia, E.; Ocampo-Velazquez, R. V.; Alvarez-Arquieta, L. de L.; Torres-Pacheco, I. Plant Hormesis Management with Biostimulants of Biotic Origin in Agriculture. Front. Plant Sci. 2017, 8, 111,  DOI: 10.3389/fpls.2017.01762
    24. 24
      Wooster, T. J.; Golding, M.; Sanguansri, P. Impact of Oil Type on Nanoemulsion Formation and Ostwald Ripening Stability. Langmuir 2008, 24 (22), 1275812765,  DOI: 10.1021/la801685v
    25. 25
      Rao, J.; McClements, D. J. Impact of Lemon Oil Composition on Formation and Stability of Model Food and Beverage Emulsions. Food Chem. 2012, 134 (2), 749757,  DOI: 10.1016/j.foodchem.2012.02.174
    26. 26
      Komaiko, J. S.; McClements, D. J. Formation of Food-Grade Nanoemulsions Using Low-Energy Preparation Methods: A Review of Available Methods. Compr. Rev. Food Sci. Food Saf. 2016, 15, 331352,  DOI: 10.1111/1541-4337.12189
    27. 27
      Park, J.; Lee, J.; McClements, D. J.; Choi, S. J. Inhibition of Droplet Growth in Model Beverage Emulsions Stabilized Using Poly (ethylene glycol) Alkyl Ether Surfactants Having Various Hydrophilic Head Sizes: Impact of Ester Gum. Appl. Sci. 2020, 10, 5588,  DOI: 10.3390/app10165588
    28. 28
      De Coninck, B.; Timmermans, P.; Vos, C.; Cammue, B. P.A.; Kazan, K. What Lies Beneath: Belowground Defense Strategies in Plants. Trends Plant Sci. 2015, 20 (2), 91101,  DOI: 10.1016/j.tplants.2014.09.007
    29. 29
      Luo, H.; Laluk, K.; Lai, Z.; Veronese, P.; Song, F.; Mengiste, T. The Arabidopsis Botrytis Susceptible1 Interactor Defines a Subclass of RING E3 Ligases That Regulate Pathogen and Stress Responses. Plant Physiol. 2010, 154 (4), 17661782,  DOI: 10.1104/pp.110.163915
    30. 30
      Abuqamar, S.; Moustafa, K.; Tran, L. S. Mechanisms and Strategies of Plant Defense against Botrytis cinerea. Crit. Rev. Biotechnol. 2017, 37 (2), 262274,  DOI: 10.1080/07388551.2016.1271767
    31. 31
      Sharifi-Rad, J.; Sureda, A.; Tenore, G. C.; Daglia, M.; Sharifi-Rad, M.; Valussi, M.; Tundis, R.; Sharifi-Rad, M.; Loizzo, M. R.; Oluwaseun Ademiluyi, A.; Sharifi-Rad, R.; Ayatollahi, S. A.; Iriti, M. Biological Activities of Essential Oils: From Plant Chemoecology to Traditional Healing Systems. Molecules 2017, 22 (1), 155,  DOI: 10.3390/molecules22010070
    32. 32
      Huang, H.; Liu, B.; Liu, L.; Song, S. Jasmonate Action in Plant Growth and Development. J. Exp. Bot. 2017, 68 (6), 13491359,  DOI: 10.1093/jxb/erw495
    33. 33
      West, R.; Banton, M.; Hu, J.; Klapacz, J.; Whitacre, D. The Distribution, Fate, and Effects of Propylene Glycol Substances in the Environment. Rev. Environ. Contam. Toxicol. 2014, 232, 107138,  DOI: 10.1007/978-3-319-06746-9_5
    34. 34
      Jones, J. D. G.; Dangl, J. L. The Plant Immune System. Nature 2006, 444 (7117), 323329,  DOI: 10.1038/nature05286
    35. 35
      Wasternack, C.; Hause, B. The Missing Link in Jasmonic Acid Biosynthesis. Nat. Plants 2019, 5 (8), 776777,  DOI: 10.1038/s41477-019-0492-y
    36. 36
      Wasternack, C.; Strnad, M. Jasmonates: News on Occurrence, Biosynthesis, Metabolism and Action of an Ancient Group of Signaling Compounds. Int. J. Mol. Sci. 2018, 19, 2539,  DOI: 10.3390/ijms19092539
    37. 37
      Ruan, J.; Zhou, Y.; Zhou, M.; Yan, J.; Khurshid, M.; Weng, W.; Cheng, J.; Zhang, K. Jasmonic Acid Signaling Pathway in Plants. Int. J. Mol. Sci. 2019, 20, 2479,  DOI: 10.3390/ijms20102479
    38. 38
      Ahmad, P.; Rasool, S.; Gul, A.; Sheikh, S. A.; Akram, N. A.; Ashraf, M.; Kazi, A. M.; Gucel, S. Jasmonates: Multifunctional Roles in Stress Tolerance. Front. Plant Sci. 2016, 7, 115,  DOI: 10.3389/fpls.2016.00813
    39. 39
      Huot, B.; Yao, J.; Montgomery, B. L.; He, S. Y. Growth-Defense Tradeoffs in Plants: A Balancing Act to Optimize Fitness. Mol. Plant 2014, 7 (8), 12671287,  DOI: 10.1093/mp/ssu049
    40. 40
      Ho, T. T.; Murthy, H. N.; Park, S. Y. Methyl Jasmonate Induced Oxidative Stress and Accumulation of Secondary Metabolites in Plant Cell and Organ Cultures. Int. J. Mol. Sci. 2020, 21, 716,  DOI: 10.3390/ijms21030716
    41. 41
      Glazebrook, J. Contrasting Mechanisms of Defense against Biotrophic and Necrotrophic Pathogens. Annu. Rev. Phytopathol. 2005, 43, 205227,  DOI: 10.1146/annurev.phyto.43.040204.135923
    42. 42
      Rao, P. V.; Gan, S. H. Cinnamon: A Multifaceted Medicinal Plant. Evidence-based Complement. Altern. Med. 2014, 2014, 112,  DOI: 10.1155/2014/642942
    43. 43
      Nurdjannah, N.; Bermawie, N. Cloves. In Handbook of Herbs and Spices, 2nd ed.; Peter, K. V., Ed.; Woodhead Publishing Ltd: London, 2012; Vol. 1, pp 197215.
    44. 44
      Mandal, S.; Mandal, M. Coriander (Coriandrum sativum L.) Essential Oil: Chemistry and Biological Activity. Asian Pac. J. Trop. Biomed. 2015, 5 (6), 421428,  DOI: 10.1016/j.apjtb.2015.04.001
    45. 45
      Borugă, O.; Jianu, C.; Mişcă, C.; Goleţ, I.; Gruia, A. T.; Horhat, F. G. Thymus vulgaris Essential Oil: Chemical Composition and Antimicrobial Activity. J. Med. Life 2014, 7, 5660
    46. 46
      Yoon, M. Y.; Cha, B.; Kim, J. C. Recent Trends in Studies on Botanical Fungicides in Agriculture. Plant Pathol. J. 2013, 29 (1), 19,  DOI: 10.5423/PPJ.RW.05.2012.0072
    47. 47
      Wang, C.; Fan, Y. Eugenol Enhances the Resistance of Tomato against Tomato Yellow Leaf Curl Virus. J. Sci. Food Agric. 2014, 94 (4), 677682,  DOI: 10.1002/jsfa.6304
    48. 48
      Banani, H.; Olivieri, L.; Santoro, K.; Garibaldi, A.; Gullino, M. L.; Spadaro, D. Thyme and Savory Essential Oil Efficacy and Induction of Resistance against Botrytis cinerea through Priming of Defense Responses in Apple. Foods 2018, 7 (2), 11,  DOI: 10.3390/foods7020011
    49. 49
      Tanaka, K.; Taniguchi, S.; Tamaoki, D.; Yoshitomi, K.; Akimitsu, K.; Gomi, K. Multiple Roles of Plant Volatiles in Jasmonate-Induced Defense Response in Rice. Plant Signaling Behav. 2014, 9, e29247,  DOI: 10.4161/psb.29247
    50. 50
      Rienth, M.; Crovadore, J.; Ghaffari, S.; Lefort, F. Oregano Essential Oil Vapour Prevents Plasmopara viticola Infection in Grapevine (Vitis vinifera) and Primes Plant Immunity Mechanisms. PLoS One 2019, 14 (9), e0222854,  DOI: 10.1371/journal.pone.0222854
    51. 51
      Alvarez, A.; Montesano, M.; Schmelz, E.; Ponce de León, I. Activation of Shikimate, Phenylpropanoid, Oxylipins, and Auxin Pathways in Pectobacterium carotovorum Elicitors-Treated Moss. Front. Plant Sci. 2016, 7 (328), 114,  DOI: 10.3389/fpls.2016.00328
    52. 52
      Moore, J. W.; Loake, G. J.; Spoel, S. H. Transcription Dynamics in Plant Immunity. Plant Cell 2011, 23 (8), 28092820,  DOI: 10.1105/tpc.111.087346
    53. 53
      Shitan, N. Secondary Metabolites in Plants: Transport and Self-Tolerance Mechanisms. Biosci., Biotechnol., Biochem. 2016, 80, 12831293,  DOI: 10.1080/09168451.2016.1151344
    54. 54
      Shitan, N.; Sugiyama, A.; Yazaki, K. Functional Analysis of Jasmonic Acid-Responsive Secondary Metabolite Transporters. Methods Mol. Biol. 2013, 1011, 241250,  DOI: 10.1007/978-1-62703-414-2_19
    55. 55
      Subramanian, A.; Tamayo, P.; Mootha, V. K.; Mukherjee, S.; Ebert, B. L.; Gillette, M. A.; Paulovich, A.; Pomeroy, S. L.; Golub, T. R.; Lander, E. S.; Mesirov, J. P. Gene Set Enrichment Analysis: A Knowledge-Based Approach for Interpreting Genome-Wide Expression Profiles. Proc. Natl. Acad. Sci. U. S. A. 2005, 102 (43), 1554515550,  DOI: 10.1073/pnas.0506580102
    56. 56
      Ikram, R.; Low, K. H.; Hashim, N. B.; Ahmad, W.; Nasharuddin, M. N. A. Characterization of Sulfur-Compounds as Chemotaxonomic Markers in the Essential Oils of Allium Species by Solvent-Free Microwave Extraction and Gas Chromatography-Mass Spectrometry. Anal. Lett. 2019, 52 (4), 563574,  DOI: 10.1080/00032719.2018.1479411
    57. 57
      Kasaian, J.; Asili, J.; Iranshahi, M. Sulphur-Containing Compounds in the Essential Oil of Ferula alliacea Roots and Their Mass Spectral Fragmentation Patterns. Pharm. Biol. 2016, 54 (10), 22642268,  DOI: 10.3109/13880209.2016.1152279
    58. 58
      Zhang, N.; Zhou, S.; Yang, D.; Fan, Z. Revealing Shared and Distinct Genes Responding to JA and SA Signaling in Arabidopsis by Meta-Analysis. Front. Plant Sci. 2020, 11 (908), 117,  DOI: 10.3389/fpls.2020.00908
    59. 59
      Qi, J.; Li, J.; Han, X.; Li, R.; Wu, J.; Yu, H.; Hu, L.; Xiao, Y.; Lu, J.; Lou, Y. Jasmonic Acid Carboxyl Methyltransferase Regulates Development and Herbivory-Induced Defense Response in Rice. J. Integr. Plant Biol. 2016, 58 (6), 564576,  DOI: 10.1111/jipb.12436
    60. 60
      Lai, Z.; Wang, F.; Zheng, Z.; Fan, B.; Chen, Z. A Critical Role of Autophagy in Plant Resistance to Necrotrophic Fungal Pathogens. Plant J. 2011, 66 (6), 953968,  DOI: 10.1111/j.1365-313X.2011.04553.x
    61. 61
      Beese, C. J.; Brynjólfsdóttir, S. H.; Frankel, L. B. Selective Autophagy of the Protein Homeostasis Machinery: Ribophagy, Proteaphagy and ER-Phagy. Front. Cell Dev. Biol. 2020, 7 (373), 112,  DOI: 10.3389/fcell.2019.00373
    62. 62
      Kabbage, M.; Kessens, R.; Bartholomay, L. C.; Williams, B. The Life and Death of a Plant Cell. Annu. Rev. Plant Biol. 2017, 68 (1), 375404,  DOI: 10.1146/annurev-arplant-043015-111655
    63. 63
      Su, T.; Li, X.; Yang, M.; Shao, Q.; Zhao, Y.; Ma, C.; Wang, P. Autophagy: An Intracellular Degradation Pathway Regulating Plant Survival and Stress Response. Front. Plant Sci. 2020, 11 (164), 116,  DOI: 10.3389/fpls.2020.00164
    64. 64
      Liu, Y.; Bassham, D. C. Autophagy: Pathways for Self-Eating in Plant Cells. Annu. Rev. Plant Biol. 2012, 63 (1), 215237,  DOI: 10.1146/annurev-arplant-042811-105441
    65. 65
      Hasanuzzaman, M.; Nahar, K.; Anee, T. I.; Fujita, M. Glutathione in Plants: Biosynthesis and Physiological Role in Environmental Stress Tolerance. Physiol. Mol. Biol. Plants 2017, 23 (2), 249268,  DOI: 10.1007/s12298-017-0422-2
    66. 66
      Hameed, A.; Sharma, I.; Kumar, A.; Azooz, M. M.; Ahmad, H. Glutathione Metabolism in Plants under Environmental Stress. In Oxidative Damage to Plants; Ahmad, P., Ed.; Elsevier Inc.: Amsterdam, 2014; pp 183200.
    67. 67
      Romero, L. C.; Aroca, M. Á.; Laureano-Marín, A. M.; Moreno, I.; García, I.; Gotor, C. Cysteine and Cysteine-Related Signaling Pathways in Arabidopsis thaliana. Mol. Plant 2014, 7 (2), 264276,  DOI: 10.1093/mp/sst168
    68. 68
      Gupta, A.; Badruddoza, A. Z. M.; Doyle, P. S. A General Route for Nanoemulsion Synthesis Using Low-Energy Methods at Constant Temperature. Langmuir 2017, 33 (28), 71187123,  DOI: 10.1021/acs.langmuir.7b01104
    69. 69
      Conn, S. J.; Hocking, B.; Dayod, M.; Xu, B.; Athman, A.; Henderson, S.; Aukett, L.; Conn, V.; Shearer, M. K.; Fuentes, S.; Tyerman, S. D.; Gilliham, M. Protocol: Optimising Hydroponic Growth Systems for Nutritional and Physiological Analysis of Arabidopsis thaliana and Other Plants. Plant Methods 2013, 9 (4), 111,  DOI: 10.1186/1746-4811-9-4
    70. 70
      Liao, C. J.; Lai, Z.; Lee, S.; Yun, D. J.; Mengiste, T. Arabidopsis HOOKLESS1 Regulates Responses to Pathogens and Abscisic Acid through Interaction with MED18 and Acetylation of WRKY33 and ABI5 Chromatin. Plant Cell 2016, 28 (7), 16621681,  DOI: 10.1105/tpc.16.00105
    71. 71
      Roberts, A.; Trapnell, C.; Donaghey, J.; Rinn, J. L.; Pachter, L. Improving RNA-Seq Expression Estimates by Correcting for Fragment Bias. Genome Biol. 2011, 12, R22,  DOI: 10.1186/gb-2011-12-3-r22
    72. 72
      Kanehisa, M.; Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research 2000, 28 (1), 2730,  DOI: 10.1093/nar/28.1.27
  • Supporting Information

    Supporting Information


    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsnano.0c09759.

    • EONEs formulation, production, and characterization; assessment of the dose-dependent response of EONEs in the plant-pathogen model system A. thaliana (Col-0)-B.cinerea via image-based phenotyping; systemic effect of EONEs on the QDR in the pathosystem used in this study (PDF)


    Terms & Conditions

    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.