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\title{Social networking in crop plants: Wire and wireless cross-phytobiome
communications}



\author[1]{Rouhallah Sharifi}%
\author[2]{Choong Min Ryu}%
\affil[1]{Razi University}%
\affil[2]{KRIBB}%


\vspace{-1em}



  
  \date{April 25, 2026}


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\selectlanguage{english}
\begin{abstract}
ants share the phytobiome with other members of the ecological community
by sharing their physiology. The phytobiome is a collective ecological
entity that senses external and internal stimuli via its member's
sensing apparatus (senome). The activated senome generates
intercellular, and intra- and inter-organismal signals that induce
genetically and epigenetically dependent modifications of phytobiome
member transcriptomes. Ultimately, these genetic modifications alter the
phenotypes of the collective phytobiome members. Mycorrhiza, epiphytic
fungi, and dodder can physically transfer signals between kin and
non-kin plants. Phytobiome members can release infochemicals by
themselves, or modify plant volatile emissions and root exudates to act
as signals for plant--plant interactions. These signals can change plant
physiology and induce holobiont updates in receiver plants via a
facilitative or competitive mechanism. Receiver plants eavesdrop on
phytobiome cues and signals to anticipate responses to unfolding
challenges. An emerging body of information in plant--plant interactions
through inter-kingdom communication can be exploited in integrated crop
management under field conditions. However, a holistic view is crucial
for the manipulation of complex systems, such as the phytobiome, to
avoid potential butterfly effects.%
\end{abstract}%



\sloppy


Social networking in crop plants: Wired and wireless cross-plant
communications

Rouhallah Sharifi\textsuperscript{1} and Choong-Min
Ryu\textsuperscript{2,3}

\textsuperscript{1}Department of Plant Protection, College of
Agriculture and Natural Resources, Razi University, Kermanshah, Iran

\textsuperscript{2}Molecular Phytobacteriology Laboratory, Infectious
Disease Research Center, KRIBB, Daejeon 34141, South Korea

\textsuperscript{3}Biosystem and Bioengineering Program, University of
Science and Technology (UST), Daejeon 34141, South Korea

\textbf{*Corresponding author:} Choong-Min Ryu; Fax: +82 (42) 860 4422;
Phone: +82 (42) 879 8229; Email: cmryu@kribb.re.kr

\textbf{Running head} : Disclosed social life in phytobiome

\textbf{Manuscript information}

Word count: 7535 words excluding Summary and References

The manuscript includes three Figures and one Table.

\textbf{Abstract}

The plant-associated microbial community (microbiome) has an important
role in plant--plant communications. Plants decipher their complex
habitat situations by sensing the environmental stimuli and molecular
patterns and associated with microbes, herbivores, and dangers.
Perception of these cues generates inter/intracellular signals that
induce modifications of plant metabolism and physiology. Signals can
also be transferred between plants via different mechanisms, which we
classify as wired- and wireless communications. Wired communications
involve direct signal transfers between plants mediated by mycorrhizal
hyphae and parasitic plant stems. Wireless communications involve plant
volatile emissions and root exudates elicited by microbes/insects, which
enable inter-plant signaling without physical contact. These
producer-plant signals induce microbiome adaptation in receiver plants
via a facilitative or competitive mechanisms. Receiver plants eavesdrop
to anticipate responses to improve fitness against stresses. An emerging
body of information in plant--plant communication can be leveraged to
improve integrated crop management under field conditions.

\textbf{KEYWORDS:} dodder, herbivore-induced plant volatiles (HIPVs),
holobiont, microbiome adaptation, microbe-induced plant volatiles
(MIPVs), mycorrhiza

\textbf{1 ? INTRODUCTION}

Plants adapt to stress via sensor elicitation, signaling cascade
activation, gene expression, and phenotype modification (Glazebrook,
2005, Jung, Tschaplinski, Wang, Glazebrook \& Greenberg, 2009). Signal
processing time is critical for success or failure in stress responses.
Plants acquired the ability to anticipate and respond to imminent
dangers, which conferred ecological competence in highly dynamic
ecosystems. This system is known as defense priming (Conrath, Beckers,
Langenbach \& Jaskiewicz, 2015, Jung \emph{et al.} , 2009).

Plants can acquire early warning information through their microbiome
and plant--plant signals (Gilbert \& Johnson, 2017, Vahabi, Reichelt,
Scholz, Furch, Matsuo, Johnson, Sherameti, Gershenzon \& Oelmuller,
2018, Yi, Heil, Adame-Alvarez, Ballhorn \& Ryu, 2009). The plant can
exploit the unique capabilities of its symbionts including the
mycorrhizal network, dodder (\emph{Cuscuta} spp.), and endophytic fungi,
which directly prime plant defense responses or transfer inter-plant
signals (da Trindade, Almeida, Xavier, Lins, Andrade, Maia, Mello,
Setzer, Ramos \& da Silva, 2019, Hettenhausen, Li, Zhuang, Sun, Xu, Qi,
Zhang, Lei, Qin, Sun, Wang, Baldwin \& Wu, 2017, Vahabi \emph{et al.} ,
2018). The plant microbiome and macrobiomecan modify plant-derived
inter-plant signals such as volatiles and root exudates (Figure 1)
(Sharifi, Lee \& Ryu, 2018, Song, Sim, Kim \& Ryu, 2016).
Herbivore-induced plant volatiles (HIPVs) and microbe-induced plant
volatiles (MIPVs) are good examples of inter-plant signals (Heil \&
Bueno, 2014, Sharifi \emph{et al.} , 2018).\selectlanguage{english}
\begin{longtable}[]{@{}l@{}}
\toprule
Box 1\tabularnewline
\midrule
\endhead
Definitions: holobiont, holobiome, microbiome Recent reports proposed
that multicellular organisms (e.g., animals and plants) and their
associated unicellular organisms (e.g., microbes) could be considered as
super-organisms, or holobionts (in ancient Greek, holos means whole and
biont means unit of life) (Gilbert, 2019, Suarez \& Stencel, 2020).
However, the definition and concept of a holobiont is still debated. We
consider a holobiont as an ecological unit (assembly) of a group of
organisms that gather together based on their evolutionary capability to
achieve a common purpose, which is the survival of the holobiont. The
holobiome includes all living organisms, their genetic materials, and
their primary and secondary metabolites, as well as the molecules
produced within a particular habitat (Berg, Rybakova, Fischer, Cernava,
Verg\selectlanguage{ngerman}ès, Charles, Chen, Cocolin, Eversole \& Corral, 2020, Sharifi \&
Ryu, 2017). The microbiome includes the microbial community living in a
particular habitat and their metabolites, mobile genetic elements, and
relic DNA (Berg \emph{et al.}, 2020). The microbiome helps the holobiont
survive during biotic and abiotic stresses. The presence and abundance
of specific microbial species in the microbiome change during successive
phases of plant ontogeny and during biotic/abiotic stresses (Carrión,
Perez-Jaramillo, Cordovez, Tracanna, de Hollander, Ruiz-Buck, Mendes,
van Ijcken, Medema \& Raaijmakers, 2019, Cotton, Petriacq, Cameron,
Meselmani, Schwarzenbacher, Rolfe \& Ton, 2019, Edwards,
Santos-Medell\selectlanguage{polish}ı\selectlanguage{english}n, Liechty, Nguyen, Lurie \& Eason, 2018, Gu, Wei, Wang,
Friman, Huang, Wang, Mei, Xu, Shen \& Jousset, 2016).\tabularnewline
\bottomrule
\end{longtable}

Here, we review plant--plant communications that improve plant defense
against pathogenic microbes. From multiple layers of plant--plant
communications, we distinguished two distinct types: wired and wireless
communications. Wired communication involves one plant sending a signal
to another plant though direct contact via microbial structures and
hyper-parasitic plant organs. This can be considered as an information
highway mediating plant--plant communication. Wireless communication
involves signal transfer across the space separating two plants. We
investigated how wired and wireless communications affect plant defense
responses. We determined that these signal transduction pathways
proceeded via the following three steps: signal input (extracellular
signal perception generates an endogenous signal cascade); transferring
signal (direct connection from signal producer to receiver through
mycorrhizal network and parasitic plants, and indirect signal
translocation via plant volatile compounds and exudates); and signal
output (receiver plant responses to biotic and abiotic stresses).

\textbf{2 ? WIRED COMMUNICATION}

\textbf{2.1 ? Wired connections between clonal plants via rhizomes and
stolons}

Some plants produce genetically identical but independent plants
(clones) through specific organs such as rhizome and stolon (Bittebiere,
Benot \& Mony, 2020, Vannier, Mony, Bittebiere, Theis, Rosenberg \&
Vandenkoornhuyse, 2019). These clonal plants are two functionally
independent plants that share vascular connections and physiological
integration. Clones have similar microbiomes, and represent unique
models in plant--plant interaction studies (Vannier \emph{et al.} ,
2019). Clones communicate and enhance each other's survival during
biotic/abiotic stress (Karban, Wetzel, Shiojiri, Ishizaki, Ramirez \&
Blande, 2014, Qian, Li, Han \& Sun, 2010, Semchenko, John \& Hutchings,
2007).

Physical connections via stolon and rhizome can mitigate abiotic stress
by facilitating the transfer/exchange of nutrients and metabolites, or
by modulating resource use efficiency (Figure 1) (Roiloa, Antelo \&
Retuerto, 2014). Defense signals can be transferred via phloem from
older to younger ramets to induce systemic resistance in young ramets.
Older ramets do not receive defense signals from younger clones due to
the direction of source-sink gradient flow (G\selectlanguage{ngerman}ómez \& Stuefer, 2006).
In\emph{Trifolium repens} , a defense signal against \emph{Mamestra
brassicae} larvae can be transferred to younger ramets within 35--51 h
depending on genotypic variation. Induced but undamaged ramets lose
their resistance after 28 days (Gómez, Van Dijk \& Stuefer, 2010).
Besides direct plant-plant links via plant parts, higher parasitic
plants are also an important link in wired communications that enhance
plant fitness.

\selectlanguage{english}\textbf{2.2 ? Wired connections between independent plants via
Dodder-mediated interspecific signaling}

Dodders (\emph{Cuscuta} spp.) are plant holoparasites that acquire water
and nutrients from host plants via the haustorium, which physically
connects the parasite to its host. Dodder species have broad host range,
and can interconnect several plant species or clusters of the same
species (Figure 1) to generate a common dodder network. The common
dodder network can be considered as an inter-plant highway that
translocates large numbers of proteins, RNA, metabolites, and plant
viruses over a distance of at least 100 cm (Hettenhausen \emph{et al.} ,
2017, Zhuang, Li, Song, Hettenhausen, Schuman, Sun, Zhang, Li, Song \&
Wu, 2018). The common dodder network can translocate more than 1,500
proteins between soybean and Arabidopsis, and some of these proteins can
localize in dodder seeds. Approximately 15--30\% of dodder proteins have
host origin, including transcription factors and R proteins that may
function in signal transaction. Dodder proteins can transfer to host
plant cells.

Plants can anticipate future threats by receiving neighboring plant
signals transferred through the common dodder network. Although there
are few reports on the role of the common dodder network in inter-plant
signaling, the results indicate that these transferred signals are
important in biotic/abiotic stress responses. When a host of the dodder
plant is under abiotic stress such high salinity, dodder transfers
salinity stress signals through a cluster of plants at a rate of 1.2 cm
per min, which prime salt tolerance in neighboring receiver plants. This
receiver plant priming changes the transcriptome, proline levels, and
stomatal conduction, so that the receiver plant stress response becomes
similar to that of the donor plant (Li, Zhang, Liu, Liu, Shen, Zhuang \&
Wu, 2020b).

Plants infected with different herbivorous insects transfer relatively
long-distance signals to conspecific and heterospecific neighbors via
the common dodder network (Hettenhausen \emph{et al.} , 2017,
Zhuang\emph{et al.} , 2018). \emph{Myzus persica} infestation reduces
the contents of salicylic acid (SA) and jasmonic acid (JA) in dodder
(\emph{Cuscuta australis} ) by up to 58\% and 41\%, respectively. Aphids
can modulate hormonal signaling by injecting effector proteins into
dodder plants (Rodriguez \& Bos, 2013). Aphid-infested dodder induce JA
but not SA in soybean hosts, and subsequent phloem sap feeding
by\emph{M. persica} and chewing by \emph{Spodoptera litura} causes 41\%
and 20\% less damage, respectively, in dodder-infected plants than in
control plants. Dodder transfers signals from insect-damaged soybean to
conspecific or heterospecific plants, such as tomato and Arabidopsis.
Gene expression and RNA-seq analyses reveal intense transcriptome
modification in receiver plants. An unknown signal can translocate
between common dodder network--connected Arabidopsis plants at a rate of
1 cm/min. A wave of signal transduction propagated between connected
Arabidopsis plants, as intracellular WRKY 40 and WRKY53 transcription
factors reached maximum expression at 45 and 90 min after donor plant
damage in the second and fourth plants in the cluster, respectively
(Zhuang \emph{et al.} , 2018).

\selectlanguage{english}\textbf{2.3 ? Wired connections between plants via fungal hyphae of the
mycorrhizal or endophytic fungal network}

Fungi can act as messengers to transfer information between independent
plants. Plant-mycorrhiza symbiosis is an ancient system that arose more
than 450 million years ago (Waters, Gutjahr, Bennett \& Nelson, 2017).
This symbiosis had a crucial role in land colonization by plants.
Different fungal phyla have evolved different types of plant-mycorrhiza
symbiosis (Tedersoo, Bahram \& Zobel, 2020). Some \emph{Brassicaceae}and
\emph{Proteaceae} plants do not participate in mycorrhizal
relationships, and are considered to be non-mycorrhizal symbiotic plants
(Tedersoo \emph{et al.} , 2020). These plants can interfere in the
mycorrhizal establishment of other plants (Cipollini, Rigsby \& Barto,
2012). For example, \emph{Alliaria petiolata} produces
glucosinolate-derived exudate that suppresses the mycorrhizae of
neighboring plants (Cipollini \emph{et al.} , 2012).

Mycorrhizae have important roles in inter-plant nutrient transfer
(especially carbon, phosphorus, and nitrogen), allelochemicals, and
signal molecules. Mycorrhizae are common in soil, as 1 g of soil
contains 10--100 meters of mycorrhizal fungi (Gilbert \& Johnson, 2017).
These fungi have broad host ranges and can connect several plants from
different taxa. Closely-related mycorrhiza fungi can perform anastomosis
to generate a network (Figure 1), which is called a common mycorrhiza
network (Deja-Sikora, Mercy, Baum \& Hrynkiewicz, 2019). Some plant
species exploit the common mycorrhiza network, especially EcM, to
transfer nutrients and signals and promote the establishment and
survival of conspecific seedlings (Bennett, Cahill \& van der Heijden,
2016, Hortal, Lozano, Bastida, Armas, Moreno, Garcia \& Pugnaire, 2017).

Plants exploit mycorrhizae fungi for long-distance transfer of plant
signals and allelochemicals. \emph{Tagetes tenuifolia} secretes the
lipophilic allelopathic compound thiophene and the hydrophilic
allelopathic compound imazamox, which can diffuse more than 12 cm via
the common mycorrhiza network (Barto, Hilker, Muller, Mohney,
Weidenhamer \& Rillig, 2011). Mycorrhizae fungi can translocate defense
signals to neighboring unstressed plants, similar to dodder. Tomato
plants infected with the nectrotrophic pathogenic fungus\emph{Alternaria
solani} transfer a signal to non-infected neighbors at 18 h
post-inoculation via mycorrhizae hypha. In the receiver plants, the
relative expression levels of defense-related genes such as
phenylalanine ammonia-lyase (PAL), lipoxygenase, polyphenol oxidase, and
pathogenesis-related proteins (PR1, PR2, and PR4) were the same as those
in the donor plants (Song, Zeng, Xu, Li, Shen \& Yihdego, 2010). Alaux,
Naveau, Declerck and Cranenbrouck (2020) also set up a
sophisticated\emph{in vitro} experiment to confirm the role of
mycorrhizae in plant-plant signal transduction. The results showed that
a\emph{Phytophthora infestans} infected tomato plant could transfer a
signal to healthy neighbors via mycorrhizae hypha to activate the
transient expression of JA related genes. Signal transduction via the
common mycorrhiza network also has been detected for herbivore-damaged
plants (Babikova, Gilbert, Bruce, Birkett, Caulfield, Woodcock, Pickett
\& Johnson, 2013, Song, Ye, Li, He, Zhu-Salzman, Wang, Su, Luo \& Zeng,
2014).

Fungal signal transduction is not exclusive to mycorrhizae. Other mutual
and pathogenic fungi with long-term endophytic relationships with plants
have the potential to transfer signals between plants. Some soil fungi
can serve as a bridge between host plants. For
example,\emph{Piriformospora indica} transfers signals from
infected\emph{Arabidopsis} to neighboring \emph{Arabidopsis}
plants.\emph{Alternaria brassicae} activates JA pathways in infected
focal plants. By contrast, endophytic fungi convert a specific JA signal
to generate an ABA signal in neighboring (receiver) plants (Vahabi
\emph{et al.} , 2018).

Fungi serve as vectors for the transfer of plant viruses among plants.
Although plants and fungi are not phylogenetically related, they can be
infected by phylogenetically-related viruses (Roossinck, 2019). Some
plant viruses propagate in the fungal cytosol and transfer between host
plants based on the host range of both fungi and viruses. A virus from
the saprophytic endophyte \emph{Penicillium aurantiogriseum} replicates
in the host plant (Nerva, Varese, Falk \& Turina, 2017). \emph{Cucumber
mosaic virus} is a broad-range virus that can survive in the pathogenic
fungus \emph{Rhizoctonia solani} , which has a broad host range.
\emph{R. solani} transfers this virus to a neighboring host (Andika,
Wei, Cao, Salaipeth, Kondo \& Sun, 2017). There is evidence that plant
virus enters fungal spores and achieves long-distance dissemination via
wind dispersal of the fungal spores. \emph{Cryphonectria}
transfer\emph{Cryphonectria hypovirus 1} to tobacco, which subsequently
propagates and spreads systemically throughout the plant with the help
of \emph{Tobacco mosaic virus} (TMV) movement protein. TMV also enters
fungi and propagates with the help of \emph{Cryphonectria hypovirus 1} ,
which can spread to other hosts via fungal spores (Bian, Andika, Pang,
Lian, Wei, Niu, Wu, Kondo, Liu \& Sun, 2020).

\selectlanguage{english}\textbf{3 ? WIRELESS COMMUNICATION: SIGNAL INPUT-TRANSFER-OUTPUT MODEL}

Plants normally release volatile and non-volatile chemicals that can be
exploited by other plants as a source of signal molecules
(infochemicals). Here, we discuss how these plant infochemicals can be
induced by microbes, insects, and environmental stimuli. Infochemicals
diffuse via air and soil pores to reach neighbor plants. Receiver plants
can amplify the released infochemical signals to expand the effective
infochemical signaling zone. Infochemicals perceived by the receiver
plants can act as kin recognition signals, growth inhibitors
(allelopathy), growth stimulators, and defense signals (Karban,
Shiojiri, Ishizaki, Wetzel \& Evans, 2013, Kong, Zhang, Li, Xia, Yang,
Meiners \& Wang, 2018a, Kong, Zhang, Li, Xia, Yang, Meiners \& Wang,
2018b, Sharifi \emph{et al.} , 2018, Sharifi \& Ryu, 2018b).
Infochemicals can directly change the transcriptome and physiology of
receiver plants to prime for imminent threats, or they may indirectly
change the plant microbiome in neighboring plants through a facilitative
or competitive mechanism (Carvalhais, Dennis, Badri, Kidd, Vivanco \&
Schenk, 2015, Li, Zhao \& Kong, 2020a, Mannaa, Han, Jeon, Kim, Kim,
Park, Kim \& Seo, 2020, Vannier, Bittebiere, Mony \& Vandenkoornhuyse,
2020).

\selectlanguage{english}\textbf{3.1 ? Wireless signal input}

\selectlanguage{english}\textbf{3.1.1 ? Constitutive release of infochemicals as information
sources}

Plants continuously release a profile of volatile organic compounds
(VOCs) and non-VOCs to the root and atmosphere. These chemical profiles,
concentrations, and release time courses function as signals of plant
presence and health status. Constitutive release of specific chemical
signatures can be exploited by neighbor organisms to determine the
presence and identity of neighboring plants. Receiver plants recognize
the degree of phylogenetical relationship of neighbor plants to
discriminate kin and non-kin plants (Biedrzycki, Jilany, Dudley \& Bais,
2010, Yang, Li, Xu \& Kong, 2018). In most cases, signals from healthy
plants can affect neighboring plants by modifying biomass allocation,
lateral root formation, and chlorophyll and phenolic compound
biosynthesis, or directly inhibiting seed germination (Delory,
Delaplace, Fauconnier \& du Jardin, 2016, Takigahira \& Yamawo, 2019) .
The sagebrush volatile compounds methyl jasmonate, camphor, 1,8-cineol,
\selectlanguage{greek}α-\selectlanguage{english}thujone, and nerol inhibit the germination of \emph{Nicotiana
attenuate} seeds (Jassbi, Zamanizadehnajari \& Baldwin, 2010). Exposing
potato to healthy onion changes the profile of potato volatiles is
repellent to an aphid pest and attractive to the aphid predator ladybird
beetle (Ninkovic, Dahlin, Vucetic, Petrovic-Obradovic, Glinwood \&
Webster, 2013, Vucetic, Dahlin, Petrovic-Obradovic, Glinwood, Webster \&
Ninkovic, 2014). (\emph{E} )-nerolidol and (3\emph{E} ,7\emph{E}
)-4,8,12-trimethyl-1,3,7,11-tridecatetraene were the primary effective
volatiles released by exposed potato plants (Vucetic\emph{et al.} ,
2014).

Some plant infochemicals are released primarily by healthy plants and
can be considered as a marker of plant health status. Isoprene emission
levels are linked to plant health and photosynthetic efficiency. The
reduction of isoprene emission after pest and disease attacks is
considered as a marker for plant stress (Copolovici, Kannaste, Pazouki
\& Niinemets, 2012, Jiang, Ye, Veromann \& Niinemets, 2016, Toome,
Randj\selectlanguage{ngerman}ärv, Copolovici, Niinemets, Heinsoo \& Luik, 2010). Isoprene
alleviates plant oxidative stress (van Doorn, Merl-Pham, Ghirardo, Fink,
Polle, Schnitzler \& Rosenkranz, 2020).

\selectlanguage{english}\textbf{3.1.2 ? Microbes and insects induce the emission of specific
plant volatiles}

Microbes and insects modulate plant volatile emission dynamics by
decreasing some VOCs and increasing others, or by inducing \emph{de
novo} VOC synthesis. Plant volatiles are produced by several metabolic
pathways, including plastidic methylerythritol phosphate and cytosolic
mevalonic acid pathways (terpenoid compounds), shikimic acid pathways
(benzoid and phenylpropanoid compounds), and oxylipin pathways {[}green
leaf volatiles (GLVs){]} (Bouwmeester, Schuurink, Bleeker \& Schiestl,
2019). The emitted VOC profile is related to the plant genotype, organ,
and type of biotic/abiotic trigger. Different comparative triggers
(e.g., chewing vs. sucking/piercing, biotroph vs. necrotroph, host vs.
non-host pathogens, and saprophytic beneficial vs. parasitic pathogenic
microbes) elicit distinct bouquets of VOCs, including the quantity and
quality of each compound and its emission time course (Castelyn,
Appelgryn, Mafa, Pretorius \& Visser, 2014, Klimm, Weinhold \& Volf,
2020, Qawasmeh, Raman \& Wheatley, 2015, Quintana-Rodriguez,
Morales-Vargas, Molina-Torres, Adame-Alvarez, Acosta-Gallegos, Heil \&
Flynn, 2015, Sharifi \emph{et al.} , 2018).

VOC profiles are conventionally defined based on what triggers their
emission. They include herbivore-induced plant volatiles (HIPVs),
oviposition-induced plant volatiles, microbe-induced plant volatiles
(MIPVs), and stress-induced plant volatiles (Kessler \& Heil, 2011,
Sharifi \emph{et al.} , 2018). These categories normally contain all of
the above-mentioned VOC groups, but the quantity/quality and emission
time course for each compound carries specific information. Green leaf
volatiles (GLVs) are categorized as HIPVs, especially for chewing
insects, but GLVs also are emitted from microbial pathogen-infected
plants (Ameye, Allmann, Verwaeren, Smagghe, Haesaert, Schuurink \&
Audenaert, 2018). Rust disease disrupts the epidermis and induces the
release of high amounts of GLVs (Jiang \emph{et al.} , 2016). By
contrast, chewing insects feeding on maize root did not elicit the
emission of GLVs, and maize root did not respond to GLVs (van Doan,
Zust, Maurer, Zhang, Machado, Mateo, Ye, Schimmel, Glauser \& Robert,
2020).

Plants emit VOCs in response to signaling between plants and Invaders.
Plant VOC profiles were altered by pathogen-associated molecular
patterns (PAMPs), herbivore-associated molecular patterns (HAMPs),
damage-associated molecular patterns (DAMPs), effector proteins, and
microbial volatile compounds (Figure 2) (Ameye \emph{et al.} , 2018,
Bouwmeester \emph{et al.} , 2019, Rybakova, Rack-Wetzlinger, Cernava,
Schaefer, Schmuck \& Berg, 2017, Sharifi \emph{et al.} , 2018, Wu, Qi,
Li, Tian, Gao, Wang, Ge, Yao, Ren, Wang, Liu, Kang, Ding \& Xie, 2017).
These elicitors activate defense-related hormones (e.g., JA, SA, and
their cross-talk), which in turn activate metabolic pathways that
produce the main VOC groups.

HAMPs such as volicitin, caeliferins, and \selectlanguage{greek}β-\selectlanguage{english}glucosidase modify the
volatile profiles in several plants (Alborn, Turlings, Jones, Stenhagen,
Loughrin \& Tumlinson, 1997, Alborn, Hansen, Jones, Bennett, Tumlinson,
Schmelz \& Teal, 2007, Hopke, Donath, Blechert \& Boland, 1994). These
compounds can induce or suppress specific groups of volatiles to attract
or repel parasitoids to host plants. Well-adapted maize caterpillars
(\emph{Spodoptera frugiperda} ) suppress HIPVs in maize, but not in
cotton (De Lange, Laplanche, Guo, Xu, Vlimant, Erb, Ton \& Turlings,
2020).

In some plant pathogens, PAMPs (e.g., flg22, laminarin, and glucan) and
effector proteins (e.g., 2b) can modify plant VOCs (Chalal, Winkler,
Gourrat, Trouvelot, Adrian, Schnitzler, Jamois \& Daire, 2015, Leitner,
Kaiser, Rasmussen, Driguez, Boland \& Mith\selectlanguage{ngerman}öfer, 2008, Sobhy, Bruce \&
Turlings, 2018, Tu, Yang, Xu, Chen, Luo, Zhu, Chen \& Yan, 2017,
Tungadi, Groen, Murphy, Pate, Iqbal, Bruce, Cunniffe \& Carr, 2017).
PAMPs, HAMPs, and effector proteins are perceived by pattern recognition
receptors and R proteins in plants, and subsequently activate basal and
effector-triggered plant immune responses (Bonaventure, VanDoorn \&
Baldwin, 2011, Glazebrook, 2005). Insertion of single R protein and its
position in the genome can significantly change the emission of
volatiles (Figure 2) (Lazebnik, Tibboel, Dicke \& van Loon, 2017).

Signaling pathways (e.g., SA- and JA-dependent pathways) leading to
systemic resistance in inoculated and neighboring plants have important
roles in volatile biosynthesis (Orlovskis \& Reymond, 2020, Wenig,
Ghirardo, Sales, Pabst, Breitenbach, Antritter, Weber, Lange, Lenk,
Cameron, Schnitzler \& Vlot, 2019). ENHANCED DISEASE SUSCEPTIBILITY1
(EDS1) and AvrRpm1 are essential factors in systemic acquired resistance
and important regulators of VOCs synthesis in Arabidopsis (Bichlmeier,
2017). Monoterpenes such as \selectlanguage{greek}α- \selectlanguage{english}and \selectlanguage{greek}β-\selectlanguage{english}pinene also induce systemic
resistance through EDS1, SA INDUCTION--DEFICIENT 2 (SID2), and
NONEXPRESSOR OF PR GENES 1 (NPR1) proteins (Figure 3) (Bichlmeier,
2017). Thus, any biological and chemical modulator of plant resistance
can change the VOC profile or prime VOC release in response to
stress.\emph{Pseudomonas protegens} strain CHA0 did not change
\selectlanguage{greek}β-\selectlanguage{english}caryophyllene emission or expression of the \selectlanguage{greek}β-\selectlanguage{english}caryophyllene synthase
gene, but primed them in response to maize beetle \emph{Diabrotica
balteata} (Chiriboga, Guo, Campos-Herrera, R\selectlanguage{ngerman}öder, Imperiali, Keel,
Maurhofer \& Turlings, 2018). Bacterial pathogens \emph{Pseudomonas
syringae} directly induce the emission of 1-undecanol and (\emph{Z}
)-3-hexenol volatiles in common bean, which repel spider mite
(\emph{Tetranychus urticae} ) (Karamanoli, Kokalas, Koveos, Junker \&
Farré-Armengol, 2020). Thus, signal cross-talk during simultaneous plant
infestation with herbivores and pathogens (Eberl, Hammerbacher,
Gershenzon \& Unsicker, 2018, Lazebnik\emph{et al.} , 2017, Peñaflor \&
Bento, 2019) or co-infestation with two pests (Kroes, Weldegergis,
Cappai, Dicke \& van Loon, 2017, Zhang, Broekgaarden, Zheng, Snoeren,
van Loon, Gols \& Dicke, 2013) can modulate VOC emissions and attract
pests and their parasitoids.

\selectlanguage{english}\textbf{3.1.3 ? Root exudates as interplant signals}

Plant release large amounts of root exudates into the soil where they
act as carbon and nitrogen sources or cues for rhizosphere organisms.
The profile of root exudates can be affected by biotic and abiotic
stimuli. Soil dwelling organisms and roots of neighboring plants use
some of these root exudates as a source of information (Bais, 2006,
Biedrzycki \emph{et al.} , 2010, Carvalhais \emph{et al.} , 2015, Khashi
u Rahman, Zhou \& Wu, 2019, Sharifi \& Ryu, 2017). Plants employ root
exudates to discriminate between kin and non-kin neighbor plants. Rice
use allantoin as a cue to recognize kin cultivars and respond to it by
shifting root biomass allocation and increasing grain yield
(Yang\emph{et al.} , 2018). An allantoin mutant of Arabidopsis was
reported to be susceptible to \emph{Pseudomonas syringae} and
\emph{Pectobacterium carotovorum} . Exogenous application of allantoin
also induces JA-responsive genes, such as MYC2 (Table 1) (Takagi,
Ishiga, Watanabe, Konishi, Egusa, Akiyoshi, Matsuura, Mori, Hirayama,
Kaminaka, Shimada \& Sakamoto, 2016). Root exudates such as
(--)-loliolide, jasmonic acid and salicylic acid act as interplant
signals and plant defense inducers (Cheol Song, Sim, Kim \& Ryu, 2016,
Kong \emph{et al.} , 2018b, Li\emph{et al.} , 2020a). (--)-loliolide
from barnyardgrass (\emph{Echinochloa crus-galli} ) root exudates
induces the biosynthesis of the rice allelochemicals momilactone B and
tricin (Li \emph{et al.} , 2020a), which can reduce the disease severity
of several rice pathogens, such as \emph{Piricularia oryzae} ,
\emph{Rhizoctonia solani} and\emph{Fusarium oxysporum} (Table 1) (Kong,
Xu, Zhang \& Zhang, 2010, Zhao, Cheng, Guo, Duan \& Che, 2018).

\selectlanguage{english}\textbf{3.2 ? Wireless signal transfer}

Plant infochemicals can diffuse around the elicited plant (producer),
and are amplified by receiver plants to expand their effective zone.
Infochemicals can diffuse distances of a few centimeters to several
meters according to their chemical structure and vectors such as
mycorrhiza and dodder. Wheat infected by \emph{Fusarium
culmorum}transfers signals to neighbor plants located 1--3 meters
distant. However, there is a negative correlation between distance and
response intensity in the receiver plant. Several studies show that
receiver plants also propagate signals and act as nodes in inter-plant
signaling (Chen, Yang, Chen, Luo, Cui, Yan \& Gerwick, 2019a, Piesik,
Pa\selectlanguage{polish}ń\selectlanguage{english}ka, Jeske, Wenda-Piesik, Delaney \& Weaver, 2013, Wenig \emph{et al.}
, 2019). Thus, neighboring plants amplify signals in clusters of
receiver plants. However, the regulation of induced signaling pathways
involved in infochemical synthesis in receiver plants requires time,
which results in a wave of infochemical synthesis and metabolic
responses in receiver plants. Falik, Mordoch, Ben-Natan, Vanunu,
Goldstein and Novoplansky (2012) observed that osmotic stress in
\emph{Pisum sativum}activated stomatal closure in the focal plant and
the next three plants in the cluster within 1 h, whereas more distant
plants responded after 1 h. In this study, focal plant stomata remained
closed for 24 h, whereas receiver plants opened their stomatal apertures
because they did not directly encounter osmotic stress. Receiver plants
did prepare for imminent osmotic stress, with the ability to return to a
naive state if the stress was resolved. Weed plants use stress signals
from \emph{P. sativum} neighbors to improve their acclimation (Falik
\emph{et al.} , 2012).

Wenig \emph{et al.} (2019) showed that monoterpenes such as \selectlanguage{greek}α- \selectlanguage{english}and
\selectlanguage{greek}β-\selectlanguage{english}pinene act as immunity-inducing signals between plants (Figure 3).
Systemic acquired resistance (SAR) is an SA-mediated induced resistance
in systemic plant tissues that is effective against a broad range of
plant pathogens (Wenig \emph{et al.} , 2019). LEGUME LECTIN-LIKE
PROTEIN1 (LLP1) is a predicted lectin that acts in the recognition of
SAR signals, which also regulate intra- and inter-plant monoterpene
synthesis. In the non-vascular marine alga \emph{Pyropia haitanensis} ,
the 1-octone-3-ol plant--plant defense signal can self-stimulate in
receiver plants and activate SA hormones (Chen \emph{et al.} , 2019a).

\textbf{3.3 ? Wireless signal output: Receiver plant response to
biotic/abiotic stresses}

The transferred signal is perceived by neighboring (receiver) plants and
augments biotic/abiotic stress resistance responses. VOC-mediated plant
stress responses have been demonstrated in numerous studies, although
the ethylene receptor ETR1 is the only plant VOC receptor identified to
date (Chang, Kwok, Bleecker \& Meyerowitz, 1993). Future research may
lead to the discovery of additional receptors for plant volatile organic
compounds (VOCs).

Recent studies identified different mechanisms whereby receiver plants
perceive VOCs from neighbor plants. VOCs can be absorbed by a wax layer
on the epidermal cell, which traps VOCs and slowly releases them to
attract or repel herbivores and their parasitoids and entomopathogens
(Camacho-Coronel, Molina-Torres \& Heil, 2020, Lin, Hussain, Avery,
Qasim, Fang \& Wang, 2016).

Some trapped volatiles such as methyl salicylate (MeSA), MeJA, and
indole can be converted to the active plant hormones SA, JA, and
indole-3-acetic acid (IAA), respectively (Figure 2,3) (Bailly,
Groenhagen, Schulz, Geisler, Eberl \& Weisskopf, 2014, Rivas-San Vicente
\& Plasencia, 2011). Some enzymes metabolize trapped volatiles such as
(\emph{Z} )-3-hexenol to the more active derivative (\emph{Z}
)-3-hexenylvicianoside (Sugimoto, Matsui, Iijima, Akakabe, Muramoto,
Ozawa, Uefune, Sasaki, Alamgir \& Akitake, 2014). Some GLVs induce
plasma membrane potential depolarization in receiver plants, thereby
activating reactive oxygen species (ROS) and calcium signaling (Figure
2) (Zebelo, Matsui, Ozawa \& Maffei, 2012).

The perception of VOCs modifies the transcriptome, proteome, and
metabolome in receiver plants (Kwon, Ryu, Lee, Park, Han, Lee, Lee,
Chung, Jeong, Kim \& Bae, 2010, van Dam \& Bouwmeester, 2016, Zhang,
Kim, Krishnamachari, Payton, Sun, Grimson, Farag, Ryu, Allen, Melo \&
Pare, 2007). In some cases, VOCs do not significantly change gene
expression profiles and metabolic activity, but prime the plant to
respond more rapidly and robustly to upcoming threats (Paschold,
Halitschke \& Baldwin, 2006, Quintana-Rodriguez \emph{et al.} , 2015).
Plant volatile (\emph{Z} )-3-hexenyl acetate directly induces JA- and
abscisic acid--related gene expression, whereas indole primes these
genes in maize against \emph{Spodoptera littoralis} (Hu, Ye \& Erb,
2019). Several studies report that primed plants activate
defense-related pathways based on the attacker identity rather than the
inducer (Moreira, Nell, Katsanis, Rasmann \& Mooney, 2018, Sharifi \&
Ryu, 2017). For example, VOCs from plants infested with general or
specialized herbivores activate similar defense pathways and VOC
emission profiles in healthy neighbors. By contrast, primed receiver
plants mount a specific set of defense mechanisms based on the type of
attacker (Moreira \emph{et al.} , 2018).

Infochemicals from neighbor plants can activate master regulatory
systems involved in plant innate immunity, including leucine-rich
repeat-receptor-like kinase, mitogen-activated protein kinases, WRKY
transcription factors, and systemic acquired resistance (Figure 2, 3)
(Dombrowski, Kronmiller, Hollenbeck, Rhodes, Henning \& Martin, 2019,
Dombrowski \& Martin, 2018, Lee, Kim, Lee, Ahn \& Ryu, 2020, Mirabella,
Rauwerda, Allmann, Scala, Spyropoulou, Vries, Boersma, Breit, Haring \&
Schuurink, 2015, Wenig \emph{et al.} , 2019, Ye, Glauser, Lou, Erb \&
Hu, 2019). D-Lactic acid secreted by the microalga \emph{Chlorella
fusca}primed defense in \emph{Arabidopsis thaliana} against
\emph{Pseudomonas syringae} pv. tomato DC3000 by increasing the
expression of WRKY transcription factors and cysteine-rich receptor-like
kinases, and induced both SA- and JA-dependent pathways (Lee \emph{et
al.} , 2020).

In inter-plant communication, volatile organic compounds (VOCs) modulate
receiver plant physiology and directly or indirectly affect other plant
holobiome members. VOCs captured by receiver plant wax display
fungicidal and bactericidal activity for several days
(Camacho-Coronel\emph{et al.} , 2020). GLVs and terpenoid volatiles have
strong fungicidal and bactericidal activity \emph{in vitro} and \emph{in
planta} (Huang, Sanchez-Moreiras, Abel, Sohrabi, Lee, Gershenzon \&
Tholl, 2012, Pontin, Bottini, Burba \& Piccoli, 2015,
Quintana-Rodriguez\emph{et al.} , 2015). VOCs can alter parasitoid
attraction and entomopathogenic fungi performance in both donor and
receiver plants (Desurmont, Xu \& Turlings, 2016, Lin \emph{et al.} ,
2016, Xu, Desurmont, Degen, Zhou, Laplanche, Henryk \& Turlings, 2016).
VOC emission in aboveground and below-ground parts may attract or repel
herbivores and plant pathogenic nematodes (Ali, Alborn \& Stelinski,
2011, D'Alessandro, Erb, Ton, Brandenburg, Karlen, Zopfi \& Turlings,
2014, Rasmann, Kollner, Degenhardt, Hiltpold, Toepfer, Kuhlmann,
Gershenzon \& Turlings, 2005).

Root exudates act as critical triggers to activate resistance in
neighboring plants by diffusing through the soil to neighboring roots.
Root exudates such as SA transfer the SAR signal to neighboring plants
and synchronize their microbiomes (Kong, Song, Sim \& Ryu, 2020,
Orlovskis \& Reymond, 2020, Song \emph{et al.} , 2016). Plants exploit
microbiome adaptation to facilitate conspecific survival according to
kin selection theory, or to compete for heterospecificity. Airborne
signals from wound-damaged plants regulated the ALMT1 transporter in
receiver Arabidopsis plants to release malic acid into the rhizosphere
(Figure 3). Malic acid recruits \emph{B. subtilis} to colonize
Arabidopsis roots and induce systemic resistance to different stresses
(Rudrappa, Czymmek, Pare \& Bais, 2008, Sweeney, Lakshmanan \& Bais,
2017).

A (--)-loliolide root exudate at a physiological concentration of 5 nmol
g\textsuperscript{-1} soil induces the release of the benzoxazinoid
compound 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) exudate
from wheat roots (Kong \emph{et al.} , 2018b). DIMBOA is a putative
allelochemical with several other roles in the rhizosphere. DIMBOA
regulates the root metabolome and exudation, which have important roles
in shaping the root microbiome (Cotton \emph{et al.} , 2019, Kudjordjie,
Sapkota, Steffensen, Fomsgaard \& Nicolaisen, 2019). DIMBOA-treated
plants recruit specific bacterial families and species such
as\emph{Pseudomonas putida} , thereby increasing plant resistance to
several stresses (Neal \& Ton, 2013). \emph{P. fluorescens} increases
DIMBOA and primed resistance against the fungal
pathogen\emph{Setosphaeria turcica} in maize (Zhou, Ma, Lu, Zhu \& Yan,
2020). The populations of bacterial plant pathogens such as
Xanthomonadaceae and \emph{Agrobacterium tumefaciens} decreased in
benzoxazinoid-treated plants (Cotton \emph{et al.} , 2019, Kudjordjie
\emph{et al.} , 2019).

Any change in cumarin, sesquiterpenes, and diadzein by airborne signals
and root exudates will change plant microbiomes (Chen, Jiang, Liu, Liu,
Zhao, Liu, Gan, Hallab, Wang, He, Ma, Zhang, Jin, Schranz, Wang, Bai \&
Wang, 2019b, Okutani, Hamamoto, Aoki, Nakayasu, Nihei, Nishimura, Yazaki
\& Sugiyama, 2020, Stringlis, Proietti, Hickman, Van Verk, Zamioudis \&
Pieterse, 2018). Activation of defense hormones (e.g., JA and SA) by
airborne signals (e.g., MeSA, 3-pentanol, or effectors of aphid/whitefly
pest) induces microbiome adaptation in plants (Lee, Lee \& Ryu, 2012,
Mannaa \emph{et al.} , 2020, Song, Choi \& Ryu, 2015, Yang, Yi, Kim,
Lee, Lee, Ghim \& Ryu, 2011). Microbiome adaptation in these examples
reduces disease severity caused by several plant pathogens and pests,
probably by recruiting beneficial bacteria such as \emph{B. subtilis}
(Lee\emph{et al.} , 2012, Song \emph{et al.} , 2015). The rhizosphere
microbiome also modulates root metabolism and exudation by azelaic acid
as a potential signal molecule (Figure 3) (Korenblum, Dong, Szymanski,
Panda, Jozwiak, Massalha, Meir, Rogachev \& Aharoni, 2020). Activation
of the two JA pathway branches differentially shape the root microbiome.
The Arabidopsis mutants \emph{myc2} and \emph{med25} alter root exudate
(Figure 3). Similar changes in some categories of root exudate were
observed in mutants of both branches, but some root exudates were
differentially synthesized. Clostridiales were abundant but declined in
mutants of both branches. \emph{Bacillus} , \emph{Lysinibacillus} ,
and\emph{Streptomyces} populations increased in the \emph{med25} mutant,
whereas the Enterobacteriaceae population increased in the
\emph{myc2}mutant (Carvalhais \emph{et al.} , 2015). Med25 has an
important role in regulating density recognition in Arabidopsis and
changing root architecture by increasing root response to auxin
(Munoz-Parra, Pelagio-Flores, Raya-Gonzalez, Salmeron-Barrera,
Ruiz-Herrera, Valencia-Cantero \& Lopez-Bucio, 2017).

\textbf{3.4 ? Acoustic and electric signals}

Plants utilize acoustic and electric signals as internal and inter-plant
signals. A sound vibration signal can be generated by a herbivore
walking on the plant, breaking trichomes, chewing the plant, and even by
water stress (Caicedo-Lopez, Contreras-Medina, Guevara-Gonzaleza,
Perez-Matzumotob \& Ruiz-Ruedab, 2020, Kollasch, Abdul-Kaf, Body, Pinto,
Appel \& Cocroft, 2020). Pest species might be discriminated based on
the vibration frequency they produce (Kollasch \emph{et al.} , 2020).

Perception of a sound vibration signal modifies plant epigenetics,
transcriptome, proteome, and metabolome (Ghosh, Mishra, Choi, Kwon, Won
Bae, Park \& Bae, 2016, Jung, Kim, Jung, Jeong \& Ryu, 2020). Sound
vibration signal perception modulates defense hormones such as SA,
leading to activation of MAPKs, MYBs, and transcription factors (Body,
Neer, C., Lin, Vu \& Cocroft, 2019, Ghosh \emph{et al.} , 2016). This
upregulation of key enzymes and secondary metabolites, including
catalase and PAL, increases the biosynthesis of phenols, alkaloids,
terpenes, and oxylipin-derivative volatile organic compounds (VOCs)
(Body \emph{et al.} , 2019, Ghosh \emph{et al.} , 2016, Kollasch
\emph{et al.} , 2020). These metabolites enhance plant resistance or act
as signals in plant--plant communication. Jung \emph{et al.} (2020)
reported that sound vibration induces resistance against the root
pathogen \emph{Ralstonia solanacearum} by modulating cytokinin
signaling, increasing aliphatic glucosinolate biosynthesis through
epigenetic DNA methylation by H3K27me3, and improving cell wall
reinforcement by downregulating miR397b suppression of lignin
accumulation--related transcripts. Vibration sensing is an
evolutionarily ancient system that arose before vascular plants emerged,
as microalga also have mechanosensory proteins that respond to vibration
(Paika, Jinb, Simc \& N.L., 2018).

Electric signals, primarily Ca\textsuperscript{2+} signaling, have
important roles in intra- and inter-plant signaling (Choi, Miller,
Wallace, Harper, Mittler \& Gilroy, 2017, de Toledo, Parise, Simmi,
Costa, Senko, Debono \& Souza, 2019, Simmi, Dallagnol, Ferreira, Pereira
\& Souza, 2020). The oomycete pathogen \emph{Pythium
aphanidermatum}exploits electric signals to target host roots (Van West,
Morris, Reid, Appiah, Osborne, Campbell, Shepherd \& Gow, 2002). Both
acoustic and electric signals have high transmission speed and good
potential for use in precision agriculture (Choi \emph{et al.} , 2017,
Kollasch \emph{et al.} , 2020).

\textbf{3.5 ? Field applications}

Although these previous studies have increased our understanding of the
signals and mechanisms involved in plant--plant communication, the
ultimate goal is to transfer this knowledge to the agricultural field.
Field applications can leverage the intrinsic potential of inter-plant
signaling by intercropping or rotating crops according to lab results,
or by eliciting plant--plant communication with biological and chemical
elicitors. Plant defense inducers can be applied to induce volatile
emission and trigger plant immunity against insect pests and microbial
pathogens. MIPVs and HIPVs contain VOCs that inhibit pathogen growth and
prime resistance in neighboring plants (Quintana-Rodriguez \emph{et al.}
, 2015, Sharifi \emph{et al.} , 2018). Inoculating some plant rows in a
field with non-pathogenic strains of plant pathogens, microbe-associated
molecular patterns (MAMPs), or herbivore-associated molecular patterns
(HAMPs) can induce VOC release and reduce disease severity in all plants
in the field. Grapevine inoculation with a sulfated laminarin MAMP
increases the emission of terpenes such as (\emph{E,E} )-\selectlanguage{greek}α-\selectlanguage{english}farnesene,
\selectlanguage{greek}β-\selectlanguage{english}caryophyllene, and trans-\selectlanguage{greek}β-\selectlanguage{english}ocimene, and subsequently increases
resistance to downy mildew disease. VOCs release and disease resistance
are significantly positively correlated (Chalal\emph{et al.} , 2015),
and the inter-plant signaling activity of these compounds on neighboring
plants has been reported elsewhere (Lazazzara, Bueschl, Parich, Pertot,
Schuhmacher \& Perazzolli, 2018, Quintana-Rodriguez \emph{et al.} ,
2015). The flg22 MAMP significantly induces the oxylipin volatiles
nonanal, heptanal, and hendecanal (Tu\emph{et al.} , 2017). Nonanal is
an inter-plant signal that induces systemic resistance against plant
pathogens (Yi \emph{et al.} , 2009).

Inter-plant infochemicals can alter volatile emission profiles and
trigger immune responses (Ameye, Audenaert, De Zutter, Steppe, Van
Meulebroek, Vanhaecke, De Vleesschauwer, Haesaert \& Smagghe, 2015).
(\emph{Z} )-3-hexenyl acetate GLV primes JA-dependent signaling
against\emph{Fusarium graminearum} in wheat (Ameye \emph{et al.} ,
2015). Indole primes the expression of JA-dependent genes and increases
JA synthesis against fall armyworm (\emph{Spodoptera frugiperda} ) in
rice (Ye\emph{et al.} , 2019). Some infochemicals may induce disease
susceptibility depending on the pathosystem. Green leaf volatiles (GLVs)
induce maize susceptibility against \emph{Colletotrichum graminicola} by
suppressing SA-dependent pathways (Gorman, Christensen, Yan, He, Borrego
\& Kolomiets, 2020). Plant growth--promoting and endophytic bacteria can
induce plant volatile synthesis to attract parasitoids and
entomopathogens (Bell, Naranjo-Guevara, Santos, Meadow \& Bento, 2020,
Disi, Mohammad, Lawrence, Kloepper \& Fadamiro, 2019, Maggini, Bandeira
Reidel, De Leo, Mengoni, Rosaria Gallo, Miceli, Biffi, Fani, Firenzuoli,
Bogani \& Pistelli, 2020). By contrast, there has been one report
showing that endophytic microbes do not have a significant effect on
plant VOC profiles and the behavior of herbivores and their parasitoids
(Moisan, Lucas-Barbosa, Villela, Greenberg, Cordovez, Raaijmakers \&
Dicke, 2020).

Plant--plant communication can be enhanced by introducing fungal
networks into the soil between plants and by triggering fungal spore
germination and root colonization with strigolactones and beneficial
bacteria. Mycorrhiza and endophytic fungi such as \emph{Piriformospora
indica} can transfer infochemical signals between plant species
(Song\emph{et al.} , 2014, Vahabi \emph{et al.} , 2018). Soil
inoculation with these fungi or promoting their populations by
conservative and organic agriculture can improve inter-plant signaling
and plant priming for imminent challenges. Soil disturbance in intense
tillage systems negatively affects mycorrhizae communities (Wang, Li,
Li, Zhao \& Liao, 2020). Mycorrhiza colonization is controlled by
strigolactones and phosphorus availability (Lopez-Raez, Shirasu \& Foo,
2017, Waters\emph{et al.} , 2017). Thus, reduced application of
phosphorus fertilizers and increased application of
phosphate-solubilizing bacteria and mycorrhiza can improve plant
colonization by mycorrhiza. Beneficial microbes can also promote root
colonization by mycorrhiza even in non-mycorrhiza plants (Poveda,
Hermosa, Monte \& Nicol\selectlanguage{ngerman}ás, 2019).

Plant--plant communication can be maximized by managed intercropping to
locate aboveground and below-ground plant parts in close proximity to
chemicals released by neighbor plants, which can directly inhibit the
germination and growth of pathogenic fungi and bacteria or repel
herbivores from fields (Lazazzara \emph{et al.} , 2018,
Quintana-Rodriguez \emph{et al.} , 2015, Yang, Zhang, Qi, Mei, Liao,
Ding, Deng, Fan, He, Vivanco, Li, Zhu \& Zhu, 2014, Zhou, Cen, Tian,
Wang \& Zhang, 2019). Volatiles from resistant cultivars contain
volatiles that can directly inhibit pathogen growth or induce systemic
resistance in neighbor susceptible cultivars (Lazazzara \emph{et al.} ,
2018, Quintana-Rodriguez \emph{et al.} , 2015). Inter-plant signals can
suppress plant pathogens directly or indirectly through microbiome
adaptation. Intercropping of aerobic rice and watermelon reduces disease
severity of \emph{Fusarium oxysporum} in watermelon (Ren, Su, Yang, Xu,
Huang \& Shen, 2008). Rice root exudates reduce pathogen spore
germination up to 41\% and alter the root microbiome community structure
in favor of \emph{Actinomycetes} . Similarly, corn can act as a
biological wall between pepper rows to inhibit \emph{Phytophthora
capsici} growth and promote the root microbiome (Yang \emph{et al.} ,
2014). DIMBOA is a density-dependent allelochemical that suppresses
plant pathogens in densely cropped maize rows. Intercropped plants can
emit infochemicals that alter the transcriptomes of neighboring plants
to cope with pathogens. RNA-seq results suggest that tall fescue root
exudate containing putrescine and cyclohexane-1,2-diol stimulates the
expression of genes related to defense hormones and pathogenesis-related
proteins in tomato, and reduces stem rot disease (Zhou \emph{et al.} ,
2019).

Plant debris functions as a modulator and infochemical for the next
plant generation and rhizosphere microbiome. Infochemicals can remain in
the ecosystem after plant death or harvest and act as signals for the
next crop generation. Infochemicals have different chemical stabilities
under different conditions. Plant debris in minimum-tillage and
no-tillage systems may enhance slow-release of infochemicals. Plant
debris can affect the next crop by modifying the soil microbiome
community and activity, by increasing soil fertility, or by acting as an
infochemical source (Veen, Fry, ten Hooven, Kardol, Morriën \& De Long,
2019, Wang, Wu, Wang, Alabady, Parson, Molumo \& Fankhauser, 2020).

Plant debris from root and aerial parts contains information about plant
identity, life history, and memory of biotic/abiotic
stresses.\emph{Medicago truncatula} growth and endophytic fungi are
affected by neighboring plants and by plants from the previous season.
Thus, both intercropping and crop rotation affect the ecological
performance of alfalfa as the holobiome (Vannier \emph{et al.} , 2020).

Rotation in hydroponic systems also affects the next crop's
performance.\emph{Vicia faba} plants infested by \emph{Acyrthosiphon
pisum} release soluble chemicals that increase the attractiveness of the
next plant parasitoid \emph{Aphidius ervi} . Similarly, lima bean
infested by\emph{Tetranychus urticae} increase the next season plant's
attraction of the predatory mite \emph{Phytoseiulus persimilis} (Delory
\emph{et al.} , 2016, Guerrieri, Dong \& Bouwmeester, 2019).

Large-scale formulation and application of inter-plant infochemicals is
a promising approach in integrated crop management. These compounds can
be considered as synthetic pesticide alternatives and can reduce their
application dose by combining synthetic pesticides and pest lure
volatiles to attract and kill pest (Martel, Alford \& Dickens, 2007).
However, infochemicals are highly reactive compounds with short
half-lives under natural conditions. Plant should be treated with these
compounds at the proper time under optimum conditions to avoid neutral
or negative effects on plant growth and defense. Micro- and
nano-encapsulation of infochemicals in natural and synthetic polymers
for slow- or controlled-release improves their effects on plant health
and volatile emission (Oliveira, Varanda \& Félix, 2016, Wang, Liu, Zhan
\& Liu, 2019). Plant virus particles can be used to deliver
infochemicals into the rhizosphere (Chariou, Dogan, Welsh, Saidel,
Baskaran \& Steinmetz, 2019). The formulation technologies and field
applications of infochemicals is reviewed elsewhere (Sharifi \& Ryu,
2018a, Sharifi \& Ryu, 2020).

\selectlanguage{english}\textbf{4 ? CONCLUDING REMARKS}

Plants have adapted to growth in complex and competitive ecosystems
during their evolutionary history. They need to compete with
interspecific and conspecific plants for light, water, and nutrients,
and communicate with neighboring plants to anticipate upcoming
biotic/abiotic challenges (Ballare \& Austin, 2019, Effah, Holopainen \&
McCormick, 2019, Hodge, Fitter \& Robinson, 2013, Hortal \emph{et al.} ,
2017). However, only some of the competition and communication
mechanisms rely on the plant genome. Plant microbiota have pivotal roles
in nutrient solubility and uptake, especially nitrogen, phosphorus, and
iron (Adesemoye, Torbert \& Kloepper, 2008, Sharifi, Ahmadzadeh,
Sharifi-Tehrani \& Talebi-Jahromi, 2010). Microbiota also improve water
use efficiency and osmotic stress response (Fan, Hu, Huang, Huang, Li \&
Palta, 2015, Sharifi \& Ryu, 2018c). The plant holobiome leverages the
collection of its member genes to optimize performance and survival.
Plants have spatiotemporal layers of defense consisting of rhizosphere
microbes, endophytes, pattern-triggered immunity, effector-triggered
immunity, and recruited natural enemies; each of these can efficiently
suppress specific groups of attackers (Carrion \emph{et al.} , 2019,
Sharifi \& Ryu, 2017). Because of these advantages conferred by
microbiota, plants donate 10--30\% of their carbon and nitrogen to the
rhizosphere to organize their microbiota.

Information and signal transferring systems play important roles in
plant growth and survival. Plants decipher their complex habitat
situations by perceiving physical and chemical cues and signals, either
directly from neighboring plants or indirectly from their symbionts such
as mycorrhiza, endophytic fungi and dodder. Previous research has
characterized the signal types and signal mediators involved in plant
interactions with other members of the ecosystem and revealed that deaf
and mute mutants of plants have reduced ecological competence. However,
plants may lose some of their communication abilities during
domestication and plant breeding programs. Therefore, plant breeders and
genetic engineers should have a holistic view of plants as members of
the holobiome. Otherwise, small changes in key ecology-related genes may
substantially affect plant performance, a phenomenon called the
butterfly effect.

Agricultural practices also affect plant-plant communication. As we
mentioned above, no-tillage and minimum tillage systems preserve common
mycorrhizal networks and endophytic fungi as mediators of wired
plant-plant communication. Moreover, Information can transfer between
plants during intercropping or from crop to crop in the next season.
Thus, recent advances in our understanding of plant-plant communication
can help manage agricultural practices so that they utilize the
abilities of plants to exploit ecological interactions, and survive in
competitive environments.

\textbf{ACKNOWLEDGMENTS}

We appreciate Ms. Meeae Hwang and Hanhee Na for drawing Figure 1. This
research was supported by grants from the BioNano Health-Guard Research
Center funded by the Ministry of Science, ICT, and Future Planning of
Korea as a Global Frontier Project (Grant H-GUARD\_2013M3A6B2078953),
the Strategic Initiative for Microbiomes in Agriculture and Food,
Ministry of Agriculture, Food and Rural Affairs, Republic of Korea {[}as
part of the (multiministerial) Genome Technology to Business Translation
Program 918017\selectlanguage{english}-4{]}, and the KRIBB Initiative Program, South Korea.

\textbf{CONFLICT OF INTEREST}

The authors declare no conflicts of interest.

\textbf{Table 1.} Effect of plant--plant communication via volatile
organic compounds and root exudates on the suppression of plant
pathogens.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Donor plant}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Receiver plant}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Signal molecule}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Target pathogen}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Reference}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{Volatile organic compounds}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{Volatile organic compounds}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Lima bean\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Lima bean\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
VOC, nonanal\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Pseudomonas syringae} pv\emph{.} syringae PR-2\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(Yi \emph{et al.}, 2009)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Tomato\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Tomato\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(\emph{Z})-3-hexenyl propionate (\emph{Z})-3-hexenyl butyrate\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Pseudomonas syringae} pv\emph{.} tomato stomatal closure\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(Lopez-Gresa, Paya, Ozaez, Rodrigo, Conejero, Klee, Belles \& Lison,
2018)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Maize\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Maize\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(\emph{Z})-3-hexen-1-yl acetate, (\emph{Z})-3-hexenal, linalool and
\selectlanguage{greek}β-\selectlanguage{english}caryophyllene\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Fusarium} spp.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Piesik, Lemnczyk, Skoczek, Lamparski, Bocianowski, Kotwica \& Delaney,
2011)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Barley and wheat\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Barley and wheat\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
GLV, (\emph{Z})-b-ocimene and linalool\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Fusarium} spp.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Piesik \emph{et al.}, 2013)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Wheat\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Wheat\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
GLVs, fatty acid derivatives, benzenoids, and terpenoid\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Puccinia triticina}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Castelyn \emph{et al.}, 2014)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Lima bean\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Lima bean\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Limonene, linalool, nonanal, methyl salicylate, and methyl
jasmonate\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Colletortichum lindemuthianum}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Quintana-Rodriguez \emph{et al.}, 2015)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Tobacco\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Tobacco\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Methyl salicylate\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Tobacco mosaic virus (TMV)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Shulaev, Silverman \& Raskin, 1997)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Tea (\emph{Camellia sinensis})\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Tea\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(\emph{E})-nerolidol\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Colletotrichum fructicola}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Chen, Zhang, Cai, Li, Bian, Luo, Li, Chen \& Xin, 2020)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Arabidopsis thaliana}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{A. thaliana}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\selectlanguage{greek}α\selectlanguage{english}- \selectlanguage{english}and \selectlanguage{greek}β\selectlanguage{english}-\selectlanguage{english}pinene\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{P. syringae} pv. \emph{tomato}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Riedlmeier, Ghirardo, Wenig, Knappe, Koch, Georgii, Dey, Parker,
Schnitzler \& Vlot, 2017)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Maize\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Maize\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
GLVs , terpenes Shikimic acid pathway derivatives\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Pantoea ananatis}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(Delaney, Breza-Boruta, Lema\selectlanguage{polish}ń\selectlanguage{english}czyk, Bocianowski, Wrzesi\selectlanguage{polish}ń\selectlanguage{english}ska, Kalka \&
Piesik, 2015)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textbf{Root exudates}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Poncirus trifoliata}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{P. trifoliata}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Salicylic acid (SA)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Xanthomonas axonopodis} pv. \emph{citri}\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Zhang, Zou, Liu \& Wu, 2019)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Maize\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Pepper\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
2,4-Dihydroxy-7-methoxy-2H-1,4- benzoxazin-3(4H)-one,
6-methoxy-2-benzoxazolinone, benzothiazole, and
2-(methylthio)-benzothiazole\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Phytophthora capsici}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(Yang \emph{et al.}, 2014)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Tobacco\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Tobacco\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
SA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{Ralstonia solanacearum} and \emph{P. syringae} pv. tabaci\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Cheol Song \emph{et al.}, 2016)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Arabidopsis thaliana}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{A. thaliana}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Root-derived signal(s)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Pseudomonas syringae pv.} tomato\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(Orlovskis \& Reymond, 2020)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Echinochloa crus-galli}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Rice\textsuperscript{*}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(--)-loliolide\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Piricularia oryzae} \emph{Fusarium oxysporum} \emph{Rhizoctonia
solani}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(Kong \emph{et al.}, 2010, Li \emph{et al.}, 2020a, Zhao \emph{et al.},
2018)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Rice\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Rice\textsuperscript{*}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Allantoin\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
\emph{Pseudomonas syringae} \emph{Pectobacterium carotovorum}\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(Takagi \emph{et al.}, 2016, Yang \emph{et al.}, 2018)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{*} This information was obtained from several reports, some of
which reported these chemicals as interplant signals and others as their
effects on plant pathogens.

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\textbf{Figure Legends}

\textbf{Figure 1. Wired and wireless phytobiome communication.} Clonal
plants (right) communicate via physical connections (e.g., stolons and
rhizomes) or VOCs. Plants also communicate via dodder and mycorrhiza
(left). Reciver plants can act as nodes to transfer defense signals
against pests and pathogens to neighboring conspecific and
heterospecific plants. Volatiles and root exudates recived by
neighboring plants modulate receiver plant defense systems, attract
parasitoids and entemopathogens, and induce plant microbiome remodeling
to protect plants against imminent stress conditions.

\textbf{Figure 2. Illustration of the signal input-transfer-output model
in plant} --\textbf{plant communication.} Molecular patterns, volatiles,
and effector proteins of pests and pathogens elicit plant signaling
pathways that promote volatiles emission and root exudation. Plant
signals can be delivered to neighboring plants through the atmosphere or
soil (wireless communication), or transferred through mycorrhiza, fungi,
and odder (wired communication). Signals can be converted to their
active form by receiver plant proteins. Signal perception by neighbor
plants activates signaling pathways and phosphorylation cascades, which
subsequently induce the expression of defense-related proteins and
metabolites. Signal perception also changes the root exudate and
recruits beneficial microbes. MAMPs, microbe-associated molecular
patterns; HAMPs, herbivore-associated molecular patterns; VOCs, volatile
organic compounds; GLVs, green leaf volatiles; BZ, benzoxazinoid; SA,
salicylic acid; MeSA, methyl salicylate; JA, jasmonic acid; MEP,
methylerythritol phosphate; MVA, mevalonic acid; MAPKs,
mitogen-activated protein kinases; TFs, transcription factors.

\textbf{Figure 3. Signals from neighboring plants modulate signaling
pathways in receiver plants and induce microbiome remodeling.} Signals
can be sensed by reciver proteins (e.g., ETR1 sensor for ethylene) or
coverted to active signals {[}e.g., SABP2 for salicylic acid (SA){]}.
Signals are transmitted through well-characterized downstream pathways
that may cross-talk with each other. These signaling pathways regulate
defense mechanisms against different groups of attackers and induce
plant microbiome remodeling by changing root exudation, thereby adapting
the plant holobiome to respond to imminent threats. MeSA, methyl
salicylate; SABP\textsubscript{2}, SA-BINDING PROTEINS 2; NPR,
NON-EXPRESSER OF PR genes; G3P, glycerol-3-phosphate; ETR1, ETHYLENE
RESPONSE 1; EIN2, ETHYLENE INSENSITIVE 2; CTR1, CONSTITUTIVE TRIPLE
RESPONSE 1; ORA59, OCTADECANOID-RESPONSIVE ARABIDOPSIS 59; MeJA, methyl
jasmonate; Med25, Mediator 25; JAZ, JASMONATE ZIM DOMAIN protein;
SCF\textsuperscript{COI1}, Skp1-Cul1-F-box protein CORONATINE
INSENSITIVE 1; FIT1, FE-DEFICIENCY-INDUCING TRANSCRIPTION FACTOR1; FRO2,
FERRIC REDUCTASE OXIDASE 2; IRT1, IRON-REGULATED TRANSPORTER 1; IAA,
indole-3-acetic acid; AUX1/LAX, AUXIN RESISTANT 1/LIKE AUX1; ALMT1,
ALUMINUM-ACTIVATED MALATE TRANSPORTER; CDPK,
Ca\textsuperscript{2+}-dependent proteinkinases; CIPK, calcineurin B
like proteins (CBL)-interacting protein kinase.\selectlanguage{english}
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