A host immune hormone modifies parasite species interactions and epidemics: insights from a field manipulation

Abstract

Parasite epidemics can depend on priority effects, and parasite priority effects can result from the host immune response to prior infection. Yet we lack experimental evidence that such immune-mediated priority effects influence epidemics. To address this research gap, we manipulated key host immune hormones, then measured the consequences for within-host parasite interactions, and ultimately parasite epidemics in the field. Specifically, we applied plant immune-signalling hormones to sentinel plants, embedded into a wild host population, and tracked foliar infections caused by two common fungal parasites. Within-host individuals, priority effects were altered by the immune-signalling hormone, salicylic acid (SA). Scaling up from within-host interactions, hosts treated with SA experienced a lower prevalence of a less aggressive parasite, increased burden of infection by a more aggressive parasite, and experienced fewer co-infections. Together, these results indicate that by altering within-host priority effects, host immune hormones can drive parasite epidemics. This study therefore experimentally links host immune hormones to within-host priority effects and parasite epidemics, advancing a more mechanistic understanding of how interactions among parasites alter their epidemics.

1. Introduction

Interactions among parasites and pathogens (hereafter, parasites) may alter host health and parasite epidemics [1,2]. Some of these interactions depend on the sequence in which parasites infect host individuals, generating priority effects among co-occurring parasites [3,4]. This contingency of interactions may result from host immune responses to prior parasite infection [2,3]. Yet determining the effect of host immunity on interacting parasites under field conditions remains a frontier in disease ecology, likely due to the joint challenge of reliably manipulating host immunity and measuring within-host interactions in the field ([2,3,5–7], but see [8]). This study experimentally tests whether host immune-signalling hormones alter interactions among parasites, and measures the consequences for parasite epidemics in the field.

Parasites that are able to establish in a given host are often subjected to interactions with the resident community during simultaneous infections, known as co-infections [2,9,10]. One potential mechanism of interaction among co-infecting parasites occurs when host immune responses to one parasite alter host susceptibility to secondary infections of another parasite [11–13]. This mechanism can result in either antagonism or facilitation among co-infecting parasites, and ultimately can alter parasite epidemics [2,14]. Specifically, immune-mediated interactions among parasites can decrease or increase peak parasite prevalence [4,15,16], among-host transmission [17], or within-host parasite burdens [8]. Within-host interactions can also decrease or increase the frequency of co-infections within hosts [18], which can further influence transmission [19–21] and parasite burdens [22]. Furthermore, co-infection and parasite burdens can influence host performance, which may alter among-host transmission and parasite prevalence [19].

Some interactions among parasites may be contingent on the sequence of past events, generating priority effects within hosts (e.g. [3]). Within hosts, priority effects occur when the per capita strength of antagonism or facilitation among parasites is altered by their sequence of arrival [3,23]. For parasites, priority effects may occur when prior parasite infection alters susceptibility to secondary parasite infection. By altering host susceptibility to secondary infection, priority effects that occur within hosts can alter the magnitude of parasite epidemics across hosts [4]. Priority effects are expected to occur most commonly when species exhibit high niche overlap and when early arriving species have large impacts on the availability of that niche [24]. A host comprises the entire niche available to parasites during infection [1,25], and thus co-infecting parasites often exhibit high niche overlap [26–28]. By activating immune responses that alter host susceptibility, early arriving parasites can determine the availability of that shared niche [26,29]. Thus, the immune response to prior infection may drive priority effects within hosts.

The immune response to prior infection can result in antagonism or facilitation of secondary infection, resulting in priority effects within hosts. Immune-mediated antagonism (also referred to as cross-protection, induced resistance, or cross-immunity) occurs when the immune response to infection by one parasite confers immunity to another [30–32]; this can decrease the frequency of co-infection [33]. Immune-mediated antagonism occurs most commonly when parasites respond to similar immune-signalling pathways (e.g. [34]). Immune-mediated facilitation (also referred to as crosstalk) occurs when up-regulation of one immune-signalling pathway leads to down-regulation of another [35], facilitating subsequent infection; this can increase the frequency of co-infection [15,36]. Immune-mediated facilitation occurs most commonly when parasites respond to distinct immune-signalling pathways [9,35,37], as is often the case among parasites that exhibit different feeding strategies. Both mechanisms of immune-mediated interactions among parasites have been reported in plant and animal hosts [15,31,37].

In plant hosts, immune-mediated interactions among parasites are thought to chiefly occur through the salicylic acid (SA) and jasmonic acid (JA) pathways [38,39]. These interactions may depend on parasite feeding strategies [36,37]. Plant parasite feeding strategies occupy a continuum, from biotrophic parasites, which feed and reproduce in living host tissue, to necrotrophic parasites, which kill living cells and extract resources from the dead tissue [40–42]. The SA pathway is thought to confer resistance to biotrophic parasites, while the JA pathway is thought to confer resistance against necrotrophic parasites and insect herbivores [36,37,43]. Consequently, parasites that share the same feeding strategy (e.g. two biotrophs) may suffer from immune-mediated antagonism, while parasites that differ in feeding strategies may benefit from immune-mediated facilitation between the two pathways [35,37,44]—a relationship that bears some analogy to the well-known mutual inhibition between the Th1 and Th2 immune responses in vertebrates [15,26]. In addition to down-regulating JA, SA signalling activates defence genes linked to systemic acquired resistance and host cell death [43], thereby further facilitating infections by necrotrophic parasites [37].

Host immunity may alter parasite interactions and epidemics [2,11,26], but we lack studies that experimentally manipulate host immunity and measure the consequences for parasites outside of the laboratory [7,8,45]. This experiment begins to address this research gap by manipulating two key host immune hormones, SA and JA, then measuring the consequences for within-host interactions, and ultimately parasite epidemics in the field. Using the host plant, tall fescue, and two co-occurring foliar parasites, we show that experimentally manipulating host immune hormones can alter within-host priority effects, leading to shifts in parasite prevalence, the frequency of co-infection, and the burden of parasite infection experienced by hosts.

2. Methods

This experiment was carried out at Widener Farm, an old field in Duke Forest Teaching and Research Laboratory (Orange County, NC, USA) that produced row crops until 1996. Since 1996, the site has been mowed to produce hay. It is dominated by the cool-season grass tall fescue (Lolium arundinaceum). The study focused on two common fungal parasites of tall fescue: Colletotrichum cereale and Rhizoctonia solani AG1-1A.

Colletotrichum causes anthracnose of cool-season grasses. It is a hemibiotrophic parasite, meaning that it initially infects its host and extracts resources from living cells (a biotrophic feeding strategy), but then it switches its mode of parasitism to kill living cells and extract resources from the dead tissue (a necrotrophic feeding strategy). It is transmitted by mucilaginous spores that are dispersed primarily by rain splash. In this system, Colletotrichum prevalence and disease severity are relatively constant throughout the growing season [4].

Rhizoctonia is the cause of many diseases, including brown patch of tall fescue. It is a facultative necrotrophic parasite, meaning that it can survive in the soil as a saprobe, and when it infects plants, it kills living cells and extracts resources from the dead tissue. It is transmitted almost exclusively by hyphae (growth and fragmentation), not spores. In this system, Rhizoctonia is best characterized by a single epidemic, beginning between late June and early July, after the emergence of Colletotrichum, and peaking in mid to late September, after which prevalence and severity decline [4].

Many potential mechanisms of within-host interactions among fungal parasites have been tested experimentally, leading to specific predictions based on parasite feeding strategies [4]. Specifically, biotrophs often facilitate necrotrophs via immune-mediated crosstalk, while necrotrophs inhibit biotrophs via competition for host resources [36,38,46,47]. Colletotrichum, a hemibiotroph, initially infects hosts as a biotroph. During this biotrophic phase, we expected Rhizoctonia to antagonize Colletotrichum via competition for resources (figure 1a path a), and Colletotrichum to facilitate Rhizoctonia via immune-mediated crosstalk (figure 1a path b). When Colletotrichum switches to a necrotrophic feeding strategy, we expected Rhizoctonia to still antagonize Colletotrichum, but Colletotrichum to also antagonize Rhizoctonia via a combination of competition for resources and cross-resistance (figure 1a path c).

Figure 1.

Hypothetical interactions between Rhizoctonia (a necrotroph) and Colletotrichum (a hemibiotroph) under (a) natural conditions, (b) experimental application of SA, and (c) experimental application of JA. Blue arrows represent positive interactions (e.g. facilitation). Red clubs represent negative interactions (e.g. inhibition). (a) Under natural conditions, previous infection by Rhizoctonia is expected to inhibit subsequent Colletotrichum infection via resource competition (path a). In the biotrophic phase of growth, previous infection by Colletotrichum is expected to facilitate subsequent Rhizoctonia infection via the SA pathway (path b), while in the necrotrophic phase of growth, previous infection by Colletotrichum is expected to inhibit subsequent Rhizoctonia infection via the JA pathway and via resource competition (path c). (b) Following predictions from (a), experimental application of SA is expected to facilitate Rhizoctonia infection (path d) and inhibit Colletotrichum infection (path e), while eliminating JA-mediated cross-resistance (path c). (c) Experimental application of jasmonic acid is expected to inhibit Rhizoctonia infection (path f), but to have no net effect on Colletotrichum infection (path g), while eliminating SA-mediated facilitation (path b). (Online version in colour.)

(a). Experimental design

To measure within-host priority effects and their effects on parasite epidemics, we placed individual sentinel outplants into the existing vegetation on 21 September 2015, at the peak of the Rhizoctonia epidemic (concurrent with Cohort 3 in [4], electronic supplementary material, figure S1). The sequence of infection in the field is highly variable, allowing us to detect priority effects without using inoculations, and instead using longitudinal surveys to observe the sequence of infection on individual leaves [4]. To measure the effects of immune-mediated interactions on parasite epidemics, we experimentally added two key immune-signalling hormones to individual sentinel outplants.

Following Schweiger et al. [48], each plant was randomly assigned to one of three treatments: the JA treatment received an aqueous solution of jasmonic acid (J-2500, Sigma-Aldrich, St. Louis) diluted to a 0.5 mM solution. The SA treatment received an aqueous solution of salicylic acid (S-7401, Sigma-Aldrich) diluted to 0.5 mM, and the control treatment (control) received distilled water, with half of those plants receiving distilled water adjusted to pH 3.1. These hormone concentrations were similar to those used in other studies [49–51], which experimentally applied immune hormones in the laboratory and measured downstream effects within the plants, including resistance to disease and herbivory. Once per month, beginning the day the plants were first deployed, 1 ml of solution was applied evenly across the aboveground surface of each plant using a handheld atomizer.

Each treatment consisted of 20 plants that were propagated from endophyte-free seed in a greenhouse for 33 days, then treated with the systemic insecticide, Marathon (Imidacloprid 1% granular, OHP Inc, Mainland, PA), to prevent insect herbivory, and transplanted into the field by burying each plant in its individual pot in a hole within an approximately 16 m² area that was fenced to exclude vertebrate herbivores. The location of individual plants in the field was randomized, and plant locations were rearranged weekly to homogenize exposure to fungal parasites. Plants that failed to establish or that resulted from seed contamination by the wrong species were excluded from analyses. This resulted in a total of 19 plants in the SA treatment group, 18 plants in the JA group, and 17 plants in the control group (comprising the 17 endophyte-free plants of Cohort 3 in [4], electronic supplementary material, figure S1). All plants were harvested on 29 October 2015.

(b). Survey

All leaves on one focal tiller (ramet) of each plant (genet) were surveyed longitudinally for infection by foliar parasites (following [4]). Each leaf was surveyed weekly from emergence to senescence, or until the end of the study. This yielded 107 total leaves in the SA group, 102 leaves in the JA group, and 98 leaves in the control group. To detect priority effects, we recorded the order of infection on each leaf. Specifically, on each leaf, the initial date of symptomatic infection by each parasite was recorded, and the per cent of leaf area infected by that parasite (infection severity) was estimated during each survey of that leaf by visually comparing the leaf to reference images of leaves of known infection severity [52,53].

Leaf age was used as a proxy for exposure to parasite propagules. When plants were transplanted into the field and initially surveyed, pre-existing leaves were assigned age 0. Each subsequent survey, newly emerged leaves were recorded as age 0, and previously surveyed leaves were individually identified based on their vertical order on the tiller, with their age recorded as the days since age 0.

To evaluate the effects of experimental treatments on parasite prevalence, all leaves of each plant (genet), including leaves of the focal tiller, were surveyed for infection by foliar parasites at the conclusion of the experiment. This yielded 503 total leaves in the SA group, 536 leaves in the JA group, and 434 leaves in the control group. On each plant, the total number of leaves and the number of leaves infected by each parasite were recorded.

(c). Disease metrics

To evaluate the magnitude of parasite epidemics, we used parasite prevalence, co-infection, and parasite burden. Parasite prevalence represents a snapshot in time of the parasite epidemic across all host leaves, while the estimated frequency of leaves becoming co-infected with parasites captures the outcome of interactions among parasites, including competitive exclusion, facilitation, and priority effects among parasites [4,23,54], and parasite burden integrates across all interactions that take place within a leaf.

Parasite prevalence was calculated as the proportion of host leaves infected by each parasite across an entire host plant. Co-infection was calculated on each longitudinally surveyed leaf and coded one if that leaf became co-infected by both parasites, and zero if that leaf was never co-infected. Parasite burden was derived from infection severity, and calculated individually on each longitudinally surveyed leaf as the area under the disease progress stairs [55] using the agricolae package [56]. This measurement includes the period of time that the leaf is uninfected, integrating the development of disease progress experienced by each leaf over the course of the experiment [57]. Consequently, this measurement provides a single value of disease burden that includes the effects of all within-host interactions, including priority effects.

(d). Data analysis

Data analysis was performed using R version 3.2.3 [58]. Leaves were analysed as hosts because each parasite infection is restricted to a single leaf. SA and JA were applied to host plants, and individual leaves are nested on host plants, so host plant was treated as a random intercept in each model.

To analyse the magnitude of epidemics, we evaluated the prevalence of each parasite, the burden of each parasite, and co-infection as a function of the experimental treatment. Parasite prevalence was modelled as a grouped binomial response, using a logit link, with leaves grouped by host plant, using the lme4 package for generalized linear mixed effects models, version 1.1-12 [59]. Parasite burden was modelled as a linear response, with leaves nested in host plants using the lme4 package. The frequency of leaves that became co-infected was modelled as a binomial response, using a logit link, with leaves nested in host plants, using the lme4 package.

For each parasite species, we assessed the treatment effects on each measure of parasite epidemics with the two control treatments separated (four levels: acid control, water control, JA, SA) and with the two control treatments combined (three levels: control, JA, SA). In each case, there was no detectable difference in support based on the Akaike information criterion (ΔAICc < 2.5) between the models with the control treatments separated and with them combined. We, therefore, combined the two control treatments into a single variable for all subsequent analyses to facilitate comparisons among the treatments of interest (JA versus control, SA versus control).

Parasite prevalence, parasite burden, and co-infection represent potential outcomes of within-host interactions, including priority effects. To model within-host priority effects, we constructed a series of models following Halliday et al. [4]. These models explicitly measure priority effects by testing whether the sequence of infection on an individual leaf influences the rate of infection by each parasite. Each model included one dependent variable pertaining to one parasite species (the focal parasite) and accounted for nestedness (leaves nested within host plants). To explicitly model priority effects, we used Cox-proportional hazards mixed models from the R package, coxme [60], to estimate the probability of a leaf transitioning from uninfected to infected. Specifically, the dependent variable in each model was time to infection, modelled as the transition rate from uninfected to infected as a function of leaf age. We modelled time to infection resulting from a baseline rate of infection shared by all individuals and modified by a linear combination of the experimental treatment, the infection status of the leaf by the other parasite during the previous survey (treated as a time-varying coefficient), and their interaction. A third parasite, Puccinia coronata, commonly co-occurs with Colletotrichum and Rhizoctonia in this system, but was not considered as a focal parasite in this study, as only seven leaves became infected with Puccinia prior to becoming infected by other parasites. However, because Puccinia can generate within-host priority effects [4], the previous infection by Puccinia was included as a fixed effect in each model. Leaves that did not become infected were right-censored, meaning that time to infection is assumed to be greater than the time of observation.

Exponentiated fixed-effect coefficients are interpreted as multiplicative changes in infection rate. Pairwise comparisons of the fixed coefficients were performed using the lsmeans package [61]. Non-significant interactions make pairwise comparisons of the fixed coefficients difficult to interpret, and were therefore removed using analysis of deviance tests (following [62]) before performing pairwise comparison tests. To limit the number of comparisons, only pairwise comparisons of ecological relevance were conducted. Specifically, two sets of pairwise comparisons were conducted: differences between each treatment and the control were assessed in leaves that were not previously infected by other parasites using the contrast function, and the effect of previous infection by other parasites was assessed separately for each treatment group using the pairs function.

3. Results

Across all responses, we found no significant effect of JA application. These results, therefore, focus almost exclusively on the effects of SA application on parasite interactions and epidemics.

(a). Does host immunity alter within-host priority effects?

Across all hosts, healthy leaves became infected with Rhizoctonia more commonly than with Colletotrichum. In untreated hosts, 71% of leaves were infected with Rhizoctonia first, while 12% were infected with Colletotrichum first and 17% were simultaneously co-infected. JA did not alter this infection sequence: 71% of leaves were infected with Rhizoctonia first, 9% were infected with Colletotrichum first, and 20% were simultaneously co-infected. Whereas JA did not alter infection sequence, experimental application of SA may have favoured early infection by Rhizoctonia. In SA-treated hosts, 89% of leaves were infected with Rhizoctonia first, while only 7% of leaves were infected with Colletotrichum first and only 4% were simultaneously co-infected.

To test whether the sequence of infection altered infection risk (i.e. whether parasites exhibited priority effects), we constructed a series of Cox-mixed models, following Halliday et al. [4]. Neither SA nor JA altered the risk of a Colletotrichum-free leaf becoming infected by Rhizoctonia (p = 0.89 and 0.62, respectively; figure 2a; electronic supplementary material, table S1A and table S2A). However, SA did reduce the risk of Rhizoctonia infection via its interaction with previous Colletotrichum infection (p = 0.048). A pairwise comparison of this effect revealed that Colletotrichum exhibited a priority effect over Rhizoctonia, reducing host risk of infection by Rhizoctonia by 94%, but only in SA-treated hosts (p = 0.033). This result is counter to the expectation that SA would strengthen the facilitative effect of hemibiotrophic Colletotrichum on necrotrophic Rhizoctonia.

Figure 2.

Model-estimated relative risk of infection. Plots are results of the reduced Cox-mixed models and are on a logarithmic scale. Points represent the treatment mean and error bars represent the 95% confidence interval. The dashed, horizontal line at y = 0 indicates no effect. Purple circles show leaves that, if they became infected, were infected with Rhizoctonia before Colletotrichum. Green triangles show leaves where, if they became infected, were infected with Colletotrichum before Rhizoctonia. Leaves that never became infected were right-censored. (a) Rhizoctonia infection risk. (b) Colletotrichum infection risk. (Online version in colour.)

This within-host priority effect of Colletotrichum on Rhizoctonia among SA-treated leaves was precluded, in some individuals, by an effect of the experimental treatment on Colletotrichum infection risk (p = 0.049; figure 2b; electronic supplementary material tables S1B and S2B). Specifically, as expected, SA treatment reduced the Colletotrichum infection risk by 67%, although this was only marginally significant in a pairwise comparison (p = 0.057). By reducing Colletotrichum infection risk, SA treatment indirectly precluded the priority effect of Colletotrichum on Rhizoctonia by reducing the fraction of host individuals becoming infected by Colletotrichum. In addition to SA, Colletotrichum infection risk was also reduced 60% by previous Rhizoctonia infection (p = 0.01). There was no interaction between this priority effect of Rhizoctonia over Colletotrichum and the experimental treatment (p = 0.78). This lack of interaction is consistent with the priority effect of necrotrophic Rhizoctonia over hemibiotrophic Colletotrichum being driven by competition for within-host resources (e.g. [47]). Putting these results together, even though Colletotrichum exhibited a priority effect over Rhizoctonia in SA-treated hosts, the negative effect of SA on Colletotrichum infection limited the degree to which this within-host priority effect could scale up to alter the Rhizoctonia epidemic.

(b). What are the consequences of immune-mediated parasite interactions for parasite epidemics?

To evaluate the outcome of immune-mediated within-host priority effects on parasite epidemics, we analysed effects on parasite prevalence, the frequency of parasite co-infection, and the burden of each parasite (calculated as the area under the disease progress stairs). Parasite prevalence represents a snapshot of the parasite epidemic, the estimated frequency of co-infection captures the outcome of interactions among parasites, and parasite burden integrates across all interactions that take place within a leaf.

The Cox-mixed models indicated that JA did not alter within-host priority effects. Similarly, we found no significant effect of JA application on parasite prevalence, the frequency of parasite co-infection, or the burden of each parasite (p > 0.05; electronic supplementary material, tables S3–S5).

SA did not significantly influence Rhizoctonia prevalence (z-test comparing SA to control; p_z = 0.166; electronic supplementary material, table S3, figure 3), contrasting with the negative effect of prior Colletotrichum infection on Rhizoctonia infection risk in SA-treated hosts. Consistent with the effects of SA on Colletotrichum infection risk, SA application reduced Colletotrichum prevalence by 57% relative to control, although this effect was only marginally significant (z-test comparing SA to control; p_z = 0.055, figure 3). Thus, even though previous Colletotrichum infection reduced Rhizoctonia infection risk in SA-treated hosts, the negative effect of SA on Colletotrichum risk appears to have offset this effect, resulting in no net effect of SA on Rhizoctonia prevalence.

Figure 3.

Model-estimated effects of experimental treatments (black = control, blue = JA, orange = SA) on parasite infection prevalence across all leaves at the end of the experiment. Empty circles show the raw data. Filled circles represent means and error bars represent 95% confidence intervals. (Online version in colour.)

SA significantly influenced the frequency of co-infection, and SA significantly influenced the parasite burden of both Rhizoctonia and Colletotrichum (p = 0.016, p < 0.001, and p < 0.001, respectively; electronic supplementary material, tables S4 and S5). Specifically, SA increased Rhizoctonia burden by 44% compared to control (z-test comparing SA to control; p_z = 0.01; figure 4). SA also reduced Colletotrichum burden by 77% compared to control (z-test comparing SA to control; p_z = 0.008; figure 4), and reduced the frequency of leaves that became co-infected with Colletotrichum and Rhizoctonia by 72% compared to control (z-test comparing SA to control; p_z = 0.032; figure 5). Together, these results indicate that by altering within-host interactions among parasites, SA can dramatically alter parasite epidemics.

Figure 4.

Model-estimated effects of experimental treatments (black = control, blue = JA, orange = SA) on parasite burden, an indicator of disease severity integrated over the life of a leaf. Empty circles show the raw data. Filled circles represent means and error bars represent 95% confidence intervals. (Online version in colour.)

Figure 5.

Model-estimated effects of experimental treatments (black = control, blue = JA, orange = SA) on the frequency of co-infection by Colletotrichum and Rhizoctonia on longitudinally surveyed leaves. Filled circles represent means and error bars represent 95% confidence intervals. (Online version in colour.)

4. Discussion

This study aimed to test the hypothesis that host immune hormones can drive within-host priority effects among parasites. Vannete & Fukami [24] posited that priority effects are most likely to occur when species exhibit high niche overlap. This may occur when species require similar resources, share natural enemies, or for parasites, respond to the same within-host immune processes. Additionally, priority effects should be more common when the early arriving species have large impacts on that niche and when the late-arriving species are highly sensitive to the availability of that niche [24]. These requirements may be commonly fulfilled for parasites sharing a host. Parasites require host resources for survival, growth, and reproduction [63], and may, therefore, exhibit some niche overlap and high sensitivity to the availability of that niche when they co-infect the same host individual. Early arriving parasites may further influence the success of later arriving parasites by altering host immunity and consequently susceptibility to secondary infection [26,29]. This study advances this hypothesis by experimentally measuring the consequences of immune hormone-mediated priority effects on parasite epidemics in the field. Specifically, immune hormone-mediated interactions altered parasite prevalence, co-infection frequency, and parasite burdens.

Immune-mediated interactions may depend on niche overlap between parasites, including in parasite feeding strategy. Specifically, immune-mediated antagonism, which can reduce the frequency of co-infection, is expected to occur more commonly among parasites with similar feeding strategies and therefore higher niche overlap, while immune-mediated facilitation, which can increase the frequency of co-infection, may be more common among parasites with distinct feeding strategies and lower niche overlap [33,36,37,64]. This dependence of host-mediated interactions on parasite feeding strategies may explain the effect of SA on interactions among Colletotrichum, a hemibiotroph, and Rhizoctonia, a necrotroph. Host immunity altered the effect of previous Colletotrichum infection on Rhizoctonia. However, this interaction did not occur in the direction that we hypothesized. We hypothesized that Colletotrichum would facilitate Rhizoctonia by up-regulating the SA pathway, thereby down-regulating the JA pathway, which predicts that the experimental application of SA will strengthen the facilitative effect of Colletotrichum on Rhizoctonia. However, we instead observed evidence of immune-mediated antagonism: Colletotrichum inhibited Rhizoctonia, but only among SA-treated hosts. Because antagonism is expected more commonly among parasites with similar feeding strategies [34], and Colletotrichum is only expected to antagonize Rhizoctonia during the necrotrophic phase of growth [4], this result may indicate that SA hastened the switch in Colletotrichum from biotrophy to necrotrophy.

Experimental application of JA had no effect on any measured response. This lack of an effect may be related to defence priming in host plants. Specifically, some hosts are primed to express and respond more strongly to JA [65,66]. Such defence priming is systemic, can persist long after exposure to microbial symbionts [31], and can be passed from one generation to the next [66]. A possible explanation for our observed lack of effects of JA is that hosts may have both experienced defence priming, and already expressed JA at relatively high levels before the experimental application of JA.

A limitation of this study is a lack of data on the physiological and transcriptional responses of the experimental host individuals to the experimental treatments. Thus, a caveat to this study's conclusions is that we could not assess whether the application of the immune hormone, SA, produced the observed effects via the hypothesized within-host immune mechanism. Future field studies could overcome this limitation, as prior laboratory studies have, by directly measuring hormone production and gene expression in healthy and infected host plants [49–51]. Furthermore, although SA and JA do play a key role in the immune responses to the focal pathogens of this study, we cannot rule out effects that may have resulted from other processes such as growth, development, photosynthesis, and ion exchange [64]. This issue could be similarly addressed in future studies by integrating experimental approaches in the field, like those used in this study, with measurements of hormone levels and gene expression.

Plant hosts face many trade-offs when responding to natural enemies, including immune-mediated trade-offs driven by parasites [67]. One type of immune-mediated trade-off likely depends on exposure to parasites of different feeding strategies. The SA pathway activates pathogen resistance genes, leading to a resistance response of host cell death and systemic acquired resistance to biotrophic parasites [44]. However, this resistance comes at a cost: maintaining and activating pathogen resistance genes can negatively affect plant performance in the absence of infection by biotrophs [68]. This may result in selection against activation of the SA pathway under many ecological conditions. Consequently, immune-mediated trade-offs may underlie interactions among parasites that infect those hosts. Activation of the SA pathway by (hemi)biotrophic parasites can also potentially increase host susceptibility to necrotrophic parasites via immune-mediated facilitation [33,36,37,64], leading to a second type of immune-mediated trade-off, driven by within-host interactions. The results of this study indicate a third potential type of immune-mediated trade-off, driven by within-host priority effects and parasite epidemics. SA reduced the prevalence of Colletotrichum, a parasite that is common throughout the growing season, apparently less aggressive than Rhizoctonia, and that can reduce Rhizoctonia prevalence by infecting hosts prior to the Rhizoctonia epidemic [4]. By reducing Colletotrichum prevalence, SA thus reduced the protective effect of Colletotrichum over its host, resulting in increased burdens of the necrotrophic parasite, Rhizoctonia.

Together, these results underscore the complexity involved in understanding interactions and epidemics of co-occurring parasites. Epidemics of co-occurring parasites may be influenced by their interactions [4,19], and these interactions may result from host immunity [9,11]. Each host's immune system commonly includes multiple components that respond to different parasite feeding strategies [37], and that can be limited by host requirements for growth and reproduction [69,70]. Beyond co-occurring parasites, predicting the magnitude of historical contingency in species interactions remains a challenge for ecologists in general, largely because the mechanisms that generate priority effects are difficult to test [24]. Understanding the mechanisms that generate priority effects may, therefore, advance a more general understanding of interactions among species. This study indicates that for plant parasites, host immune hormones may influence within-host priority effects, altering parasite epidemics.

Data accessibility

The data and code supporting the results are available at the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.k455v5c [71].

Authors' contributions

F.W.H. and C.E.M. designed the experiment. F.W.H. and J.U. analysed the data. F.W.H. performed the study and wrote the first draft. All authors contributed substantially to revising the manuscript.

Competing interests

We have no competing interests.

Funding

This work was supported by the NSF-USDA joint program in Ecology and Evolution of Infectious Diseases (NSF grant no. DEB-1015909 and USDA-NIFA AFRI grant no. 2016-67013-25762). F.W.H. was supported by the NSF Graduate Research Fellowship, the UNC Dissertation Completion Fellowship, and the UNC Dr Coker Botany Fellowship.