5 DISCUSSION
Assessing interactions between biotic stressors and plants in food webs
is critical to understand the dynamics of these interactions. Plant
responses to stressors are often specific to the attacker, and both
phytochemical responses and plant nutritional status can affect
susceptibility to specific stressors (van Geem, Gols, Raaijmakers, &
Harvey, 2016; Shikano, 2017). We show plants responded in complex
ways to unique biotic stressors, including a piercing-sucking herbivore
(A. pisum ), a chewing herbivore (S. lineatus ), and a virus
(PEMV). Our study is among the first to assess how the order of attack,
and diversity of stressors, mediate the defensive responses of plants
and plant nutritional status (see also Vos, Moritz, Pieterse, & Van
Wees, 2015). Our results show that plants traits varied in response to
the type of attacker, the number of stressors, and their order of
arrival. Moreover, we show that assessment of multiple gene transcripts,
phytohormones, and plant nutrients provides a more comprehensive
perspective on mechanisms driving plant-insect-pathogen interactions
than any isolated response.
We found PEMV caused broad defensive responses in P. sativum by
inducing specific gene transcripts and phytohormones (Figs. 2, 3 & 4).
Biotropic pathogens such as PEMV are known to activate salicylic acid
signaling (Singh, Swain, Singh, & Nandi, 2018; Chisholm, Sertsuvalkul,
Casteel, & Crowder, 2018). This was reflected by increased expression
of the ICS1 biosynthesis gene, increased salicylic acid hormone
levels, and increased expression of the downstream defensive transcriptPR1 when PEMV was present. However, effects of PEMV were not
limited to salicylic acid, as PEMV induced gene transcripts often
associated with biosynthesis of abscisic acid (AO3 ), and
giberrellic acid (GA2ox ), while also affecting defense response
genes that occur downstream from induction of these hormones (PR1,
DRR230 , PsLectin ). However, PEMV alone can not induce gene
transcript associated with biosynthesis of JA (LOX2 ), but PEMV
infection after weevil herbivory induced LOX2 accumulation.
Similar results in P. sativum have been observed in response to
fungal infection by Mycosphaerella pinodes and Phoma
koolunga , where infections induce defense related genes across multiple
signaling pathways (Fondevilla et al., 2011; Tran, You, & Barbetti,
2018). However, increased expression of LOX2 and AO3 gene
transcripts (Fig. 2) were not reflected by increased levels of jasmonic
acid or abscisic acid (Fig. 4). This suggests that measuring
phytohormones, or gene transcripts, in isolation may fail to reveal more
complex pathways by which plants respond to stress (Kazan & Lyons,
2014).
While PEMV had broad effects on plants, S. lineatus attenuated
these responses. When S. lineatus was present, before or after
PEMV, the expression of three out of four biosynthesis gene transcripts
(with the exception of LOX2 ) in response to infectious aphids
were comparatively weaker (Fig. 2). Increased expression of LOX2may be due to S. lineatus inducing expression of defensive
transcripts associated with JA-mediated chewing herbivore attack and the
effect was further enhanced by PEMV infection after S. lineatusfeeding (Fig. 2). Effects of PEMV on plant defense genes (PR1 ,DDR230 , PsLectin ) were also affected by S.
lineatus , but varied with attack order. Overall, in this study the
order of attack seemed to have stronger effects on downstream plant
defense gene transcripts than on hormone biosynthesis gene transcripts.
While S. lineatus increased expression of two (LOX2 andGA2ox ) of the four biosynthesis gene transcripts studied when
PEMV was not present, expression of LOX2 was enhanced when PEMV
was also present (Fig. 2). In contrast, PEMV caused decreased expression
of two genes (PR1 , DRR230 ) that were induced by S.
lineatus was present alone (Fig. 2). For plants attacked first by
either PEMV or S. lineatus , we observed the strongest evidence
for mutual antagonism at the gene transcript level rather than for
phytohormones (Figs. 2-4). Our study shows interactions among a set of
stressors can vary based on attack order. Here, we found that S.
lineatus feeding following PEMV infection inhibited plant defense
(mutual antagonism), while LOX2 expression was enhanced when PEMV
infection followed S. lineatus feeding (synergistic effect).
While the first effect is in line with studies showing “mutual
antagonism” between chewing herbivores and biotropic pathogens (Thaler,
Agrawal, & Halitschke, 2010; Vos et al., 2015), our study suggests the
order of attack can lead to variation along a spectrum from antagonism
to enhancement.
Our results provide evidence that the order of arrival of biotic
stressors on plants can play a crucial role in determining plants’
response to these attackers. While mutual antagonism between S.
lineatus and PEMV was common, for some genes these effects only
occurred when S. lineatus attacked first, and for others whenS. lineatus attacked second (Figs. 2-4). Mutual antagonism has
most often been studied as effects of a prior attacker affecting a
subsequent attacker, such as when a herbivore alters gene activation or
phytohormones in ways that attenuate performance of subsequent attackers
(Kessler & Halitschke, 2007; Erb, Robert, Hibbard, & Turlings, 2011;
Stam, Mantelin, McLellan, & Thilliez, 2014; Huang et al., 2017).
However, our results suggest that a second attacker may also mitigate
defensive responses against the first attacker in ways that might affect
plant defense and propagation of pathogens. For example, we show that
plants infected by PEMV had decreased defenses when subsequently
attacked by S. lineatus (Fig. 3), which should promote PEMV
replication. Moreover, our results suggest that, PEMV infection induces
pathogen defense and S. lineatus inhibits that if they appear on
plants after the infection has been established. This may be more
strongly expressed as variation in gene transcripts rather than hormone
levels, a result that has similarly been seen in Arabidopsis in
response to pathogen infection (Anderson et al., 2004).
Mutual antagonism in plant signaling pathways has most commonly been
examined in regard to tradeoffs between jasmonic acid and salicylic
acid. Our results show these tradeoffs extend to other signaling
pathways. For example, jasmonic acid exhibits antagonism with abscisic
acid in Arabidopsis following attack from Fusarium
oxysporum (Anderson et al., 2004). Mutual antagonism between jasmonic
acid and gibberellic acid, and jasmonic acid and abscisic acid, have
also been reported (Yang, Yang, & He, 2013; Okada et al., 2015;
Liu & Hou, 2018). For example, jasmonic acid facilitates defense over
growth by repressing degradation of DELLA protein in rice andArabidopsis , but elevated DELLA proteins interfere with the
gibberellic acid pathway by binding to growth promoting transcription
factors associated with gibberellic acid signaling (Yang et al., 2012,
2013; Okada et al., 2015). Antagonistic relationships between giberellic
acid and abscisic acid have also been reported in both mono and dicot
plants and regulated by various transcription factor regulators in
response to diverse environmental cues (Liu & Hou, 2018). However,
antagonisms between salicylic acid and abscisic acid may actually lead
to synergism between jasmonic acid and abscisic acid, where elevated
abscisic acid levels following infection with Pseudomonas
syringae induce jasmonic acid in Arabidopsis , which in turn
limits the levels of salicylic acid (Fan, Hill, Crooks, Doerner, &
Lamb, 2009). Overall, these results suggest that a broad examination of
genes and hormones are needed to elucidate pathways underlying
plant-insect-pathogen interactions in P. sativum and other
plants.
Our results suggest mutual antagonism may also occur among defense gene
transcripts that are associated with a single signaling pathway. For
example, the induction of PR1, a salicylic acid-responsive gene,
was mitigated by S. lineatus attack after PEMV infection, as may
be expected with antagonism between jasmonic acid and salicylic acid.
However, the expression of ICS1, another gene associated with the
biosynthesis of salicylic acid, was not responsive to S.
lineatus . This has been seen in other studies where ICS1 was not
induced by caterpillar feeding although other genes associated with
salicylic acid were (Onkokesung, Reichelt, van Doorn, Schuurink, &
Dicke 2016). These results suggest that a plant’s response to multiple
stressors is unlikely to result from simple crosstalk but rather from
interactions among multiple signaling pathways that may exhibit complex
responses.
In addition to affecting plant gene expression and phytohormones, plant
pathogens such as viruses can also alter nutritional quality of their
host plants in ways that affect vectors (Mauck, Bosque‐Pérez,
Eigenbrode, Moraes, & Mescher, 2012; Wang, Senthil-Kumar, Ryu, Kang, &
Mysore, 2012; Patton et al., 2019). Similarly, non-vector herbivores may
strongly affect the quantity and quality of plant nutrients
(Ángeles-López, Rivera-Bustamante, & Heil, 2016). For example,pepper golden mosaic virus (PGMV) infection in Capsicum
annuum increased levels of the amino acids proline, tyrosine, valine
but decreased levels of histidine and alanine. In the same system, the
greenhouse whitefly, Trialeurodes vaporarioum , reversed the
levels of these amino acids (Ángeles-López et al., 2016). Arrival
of S. lineatus before PEMV infection suppressed the amount of
total amino acids in peas, while enhanced amino acid level was
detected if S. lineatus damaged peas after PEMV infected was
established. This suggests the intriguing possibility that antagonism
between a pathogen and non-vector herbivore can occur at the level of
amino acid production in plants.
Overall, our study provides example of complex interactions between a
vector-borne plant pathogen and a non-vector herbivore that varies from
antagonism to enhancement and manifest as changes in plant gene
transcripts, phytohormones levels, and plant nutrients. However, we show
that assessing the order of attack is necessary to best understand the
complexity and mechanisms of plant-insect-pathogen interactions.
Moreover, our study suggests complete pathways must be characterized as
differences are evident even when a few transcripts and metabolites are
analyzed., often measured with associated gene transcripts (Bedini,
Mercy, Schneider, Franken, & Lucic-Mercy, 2018; Ángeles-López el al.,
2016; Shi et al., 2019), may fail to capture mechanisms by which plants
interact with multiple stressors. Our results demonstrate both the order
of arrival, and the diversity of interactions, determine plant responses
to stress through the combined action of defense gene activation,
phytohormone accumulation, and modification of plant nutrients.
Characterizing the pathways by which plants respond to single and
multiple stressors, with varying attack order, can shed light on the
mechanisms that shape food web interactions among plants, herbivores,
and pathogens.