Induced resistance in maize is based on organ-specific defence responses


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To obtain further insight into the intricate inter-play between maize (Zea mays) and the fungal pathogen Colletotrichum graminicola, the local and systemic molecular and chemical defence responses of maize leaves and roots were simultaneously investigated and compared. Similar gene expression and hormonal patterns were detected in both above- and below-ground organs; however, roots responded more rapidly and accumulated higher levels of defence-related hormones than leaves. Leaf and root infection with C. graminicola triggered systemic resistance in the foliage against the same fungus. This systemic defence response was associated with systemic transcriptional adaptations, and elevated levels of salicylic acid and abscisic acid. Metabolomic profiling revealed significant differences in the composition of secondary metabolites in leaves and roots, indicating that these organs employ distinct chemical defence systems. In addition, higher basal levels of antimicrobial flavonoids suggest an enhanced basal defensive state of roots. Our findings reveal tissue-specific local and systemic antifungal defence mechanisms in maize.


Members of the genus Colletotrichum, which cause anthracnose and blights, and also devastating post-harvest rot, belong to the top 10 fungal plant pathogens attacking economically important crops (Dean et al., 2012). As a hemi-biotrophic pathogen, Colletotrichum grows first biotrophically but soon switches to a necrotrophic lifestyle (Wharton et al., 2001; Mims and Vaillancourt, 2002). A comparative genomic analysis of fungal lifestyle transitions is now possible due to the availability of the recently published genome sequences of Colletotrichum (O'Connell et al., 2012).

Maize (Zea mays) anthracnose, caused by Colletotrichum graminicola, has a worldwide impact on corn production, affecting all parts of the crop plant at every growth stage (Bergstrom and Nicholson, 1999), and leading to annual losses of up to 1 billion dollars in the USA (Frey et al., 2011). Leaf blight and stalk rot are the predominant symptoms, but C. graminicola is also able to infect maize roots (Sukno et al., 2008). Root infections differ from leaf infections, as both rhizodermal and cortical cells are infected in a mosaic pattern that is distinct from the typical cell-to-cell spread observed in leaves (Sukno et al., 2008). In contrast to leaf infections, where initial symptoms appear after a few days, roots may remain symptomless for up to 42 days post-infection (dpi) (Sukno et al., 2008). Interestingly, root infections may also result in systemic infections of aerial parts (Sukno et al., 2008), suggesting an important role for root infections in the disease cycle.

Compared to above-ground defences, knowledge on root defences is more elusive, and comparative analyses of above- and below-ground defences are scarce (Rasmann and Agrawal, 2008). Arabidopsis roots exposed to salicylic acid (SA) showed a significant difference in the SA-dependent transcriptome compared with SA-treated leaves (Badri et al., 2008). Similarly, roots and leaves are known to differ in the concentration of various defensive compounds. In Nicotiana sylvestris, the levels of alkaloids are up to six times higher in roots than in leaves (Rasmann and Agrawal, 2008). During the past few years, extensive studies of root herbivore defences revealed a pronounced role for roots as part of local and systemic plant defensive systems (Erb et al., 2009c). For example, roots may act as reservoir of secondary metabolites that are translocated to distal plant parts during biotic attacks. In tobacco plants, nicotine is predominantly synthesized in roots and transported to the shoots (Dawson and Solt, 1959), and below-ground herbivory in maize triggers systemic induction of the antibiotic compound DIMBOA (2,4–dihydroxy-7–methoxy-1,4–benzoxazin-3–one) in above-ground parts (Erb et al., 2009a).

Colletotrichum has a tradition as fungal model organism. Colletotrichum lagenarium infection studies on L. Cucumis sativus contributed to the initial characterization of systemic acquired resistance (SAR) (Hammerschmidt et al., 1982), which is usually induced upon local attack by necrotizing or hypersensitive response-triggering pathogens (Vlot et al., 2008). Such attacks lead to the generation of mobile alarm signals that are translocated through the vascular system or airborne to distal as yet uninfected plant parts, where they lead to SAR. SAR may also be triggered by application of SAR-inducing chemicals (Oostendorp et al., 2001). Induced resistance has been extensively investigated in the model plants Arabidopsis and Nicotiana tabacum, leading to identification of a set of critical long-distance signals (Dempsey and Klessig, 2012), such as glycerol-3–phosphate (Chanda et al., 2011), azelaic acid (Jung et al., 2009), the volatile methyl salicylate (Park et al., 2007) or dehydroabietinal (Chaturvedi et al., 2012). However, less is known about SAR mechanisms in monocots (Balmer et al., 2012). Although there is solid evidence that chemical SAR inducers such as benzothiadiazole (BTH) and probenazole (Görlach et al., 1996; Nakashita et al., 2002) are active in monocots, data describing biologically induced SAR are scarce. In rice (Oryza sativa), Pseudomonas syringae pv. syringae infections were shown to trigger SAR against Magnaporthe grisea (Smith and Métraux, 1991). Similarly, SAR against leaf rust has been reported in Triticum aestivum (Barna et al., 1998). It remains to be shown whether the systemic signals described for dicots also play a role in monocots. Moreover, classical SAR research has mainly focussed on events in above-ground parts, thereby neglecting the root system.

Little is known about local and systemic defence responses of maize upon above- and below-ground fungal attack. In this study, we simultaneously investigated both local and systemic organ-specific above- and below-ground maize defence responses during C. graminicola attack, providing an insight into a multi-layered defence system. Our studies on metabolomic responses to C. graminicola attack in shoots and roots show that these organs employ different chemical defence strategies. We also present evidence that the systemic transcriptional, hormonal and metabolomic adaptations that occur after local leaf and root infections are correlated with expression of SAR against C. graminicola in systemic leaf tissues.


Disease progress in leaves and roots

To compare both C. graminicola leaf and root infections under identical experimental conditions and time points, 12-day-old maize plants were inoculated with C. graminicola-gGFP (Erb et al., 2011), and fungal development was documented at 36, 48 and 96 h post-infection (hpi) using confocal microscopy (Figure S1). The chosen time points correspond to the known lifestyle transitions of C. graminicola during hemi-biotrophic growth on leaves (Vargas et al., 2012). The disease progress differed between leaves and roots. In leaves, characteristic biotrophic structures such as bulbous biotrophic hyphae were present at 36 hpi (Figure S1a), whereas, in roots, thin runner hyphae were observed at the surface (Figure S1b). At 48 hpi, the first necrotic symptoms on leaves marked the transition to necrotrophy. At this time, thin secondary hyphae grew without specific orientation inside leaf tissue (Figure S1c), while, in the roots, the hyphae grew parallel to the longitudinal axis of epidermal cells (Figure S1d). At 96 hpi, leaf tissues were colonized by a dense hyphal network (Figure S1e). In contrast, roots were infected in a mosaic pattern, consisting of a few colonized cells that were often packed with falcate conidia, while neighbouring cells remained uninfected (Figure S1d). Thus, compared to the extensive colonization of leaves, fungal growth is restricted in roots. Selective inoculation of the various root types, namely primary, seminal and crown roots (Hochholdinger and Tuberosa, 2009), showed that they were all susceptible to C. graminicola (Figure S2).

The transcriptional state of infected leaves and roots differs

The organ-specific defence responses at the molecular level were investigated by quantitative real-time PCR. Based on a marker system for biotic and abiotic stress responses (Erb et al., 2009a), primers for 44 defence- and stress-related genes were designed (Table S1). The local and systemic transcriptional response of leaves and roots at distinct time points, including lifestyle transition points, was compared (Figure 1). With a few exceptions, both leaves and roots showed a similar local expression pattern (Figure 1a). The pathogenesis related gene PR2 was up-regulated at later time points (96 hpi) only in infected roots. Similarly, CHS C2, which encodes a chalcone synthase that is important in flavonoid synthesis, was exclusively induced in infected roots. Moreover, the lipoxygenase (LOX) pathway was found to be involved more in leaf infection than in roots; for example, LOX1 was only up-regulated in leaves. Although the transcriptional pattern was similar, roots responded faster than leaves. Even at 12 hpi, PR genes, as well as BB, a Bowman–Birk serine trypsin inhibitor, a potential antimicrobial protein, were up-regulated in the roots. In contrast, Bx1 and IGL, both of which encode enzymes involved in benzoxazinoid synthesis, were down-regulated at early leaf infection stages. Notably, in contrast to the rapid induction of defence genes in roots, leaves generally responded later (see Table S2 for induction levels). For example, there was a slight induction of PR1 at early time points in roots. In contrast, PR1 levels in leaves increased up to 800-fold at 48 and 96 hpi (Figure 2).

Figure 1.

Comparative analysis of defence genes.(a) Colletotrichum graminicola -infected leaves (inf. leaf) and roots (inf. root) at 12, 24, 48 and 96 hpi.(b) Systemic gene expression profiles: systemic leaves of leaf-infected plants (LA sys. L), roots of leaf-infected plants (LA sys. R), and leaves of root-infected plants (RA sys. L) at 24, 48 and 96 hpi.Gene expression is indicated as fold induction compared to mock-treated plants; blue = down-regulated genes, yellow = up-regulated genes. SA, salicylic acid; Aux, auxin; JA, jasmonic acid; ET, ethylene; ABA, abscisic acid.

Figure 2.

Expression level of PR1 in Colletotrichum graminicola -infected roots (inf. root) and infected leaves (inf. leaf).Expression is indicated as fold change relative to mock-treated plants.

The transcriptional state of the various maize root types was assessed at six dpi (Figure S3), with the highest response seen in seminal roots, whereas a smaller number of genes were induced in crown roots. However, the general gene expression pattern was similar, with a few exceptions. For example, CHS C2 was down-regulated in crown roots, and PR2 was only induced in seminal roots.

Leaf and root infections influence hormone levels

To elucidate the contribution of plant hormones to above- and below-ground defence responses against C. graminicola SA, jasmonic acid (JA) and abscisic acid (ABA) levels were quantified by UHPLC-MS/MS during biotrophic (36 hpi) and necrotrophic (96 hpi) infection stages (Figure 3). While no significant differences in hormone levels between control and infected leaves were observed at 36 hpi (Figure 3a), levels of SA and ABA were significantly higher in roots at 36 hpi, and JA levels were lower in roots (Figure 3b). However, a significant increase in the levels of SA, JA and ABA was observed in both leaves and roots at 96 hpi (Figure 3c,d). Interestingly, the concentration of all three hormones was higher in infected roots compared to infected leaves.

Figure 3.

SA (salicylic acid), JA (jasmonic acid) and ABA (abscisic acid) quantification in Colletotrichum graminicola local and systemic infection assays.(a) Infected leaves at 36 hpi.(b) Infected roots at 36 hpi.(c) Infected leaves at 96 hpi.(d) Infected roots at 96 hpi.(e) Quantification of SA, JA and ABA in systemic tissues upon local C. graminicola leaf and root infection at 36 hpi. (f) Systemic leaves of leaf-infected plants at 96 hpi.(g, h) Systemic roots at 36 hpi (g) and 96 hpi (h) from leaf-infected plants.(i, j) Systemic leaves of root-infected plants at 36 hpi (i) and 96 hpi (j). LA, leaf assay; RA, root assay; sys., systemic. Control (Ctrl) and infected (inf.) plants were compared using Tukey's range test; asterisks indicate statistically significant differences (< 0.05).

Local infections induce systemic transcriptional responses

Systemic transcriptional changes were analysed by quantitative real-time PCR using the same defence marker system as described above (Figure 1b). Changes were assessed in a leaf assay, whereby a single leaf was infected and non-infected systemic leaf and root tissues were analysed. Additionally, in a root assay, the root system was infected and gene expression was quantified in non-infected leaves. Systemic transcriptional adaptations were observed over a time course of 96 h, starting at 24 hpi. In systemic leaves, the majority of up-regulated genes, such as PR1, PR5, PR10 and PAL1, were SA-associated. CHS C2, Bx1 and IGL were also induced, whereas terpene synthase genes such as TPS10 and TPS23 were down-regulated at 96 hpi. In contrast to systemic leaves, only two genes with significantly different expression pattern were detected at 96 hpi in systemic roots, namely OPR2 and LOX1. Interestingly, the transcriptional response of systemic leaves after root infection was much faster and stronger than after leaf infection. Even at 24 hpi, pathogenesis-related genes such as PR1 and PR10 were highly induced, in addition to Bx1, LOX1 and WIP1. The gene encoding 9-cis-epoxycarotenoid dioxygenase, a key enzyme in ABA synthesis, was also rapidly induced, suggesting a contribution of ABA to defence responses of systemic leaves. In contrast to local leaf infections, root infections also triggered the up-regulation of PR3, CytP450, LOX5, AOS and BB. To test for possible root-to-root signalling, primary roots were infected and the expression of selected defence-related genes was analysed in systemic seminal and crown roots at 4 dpi (Figure S4). PR genes were induced in both systemic seminal and crown roots. However, seminal roots had a higher number of induced genes compared to systemic crown roots, in which only PR1 was induced. Nevertheless, this provides evidence of systemic root–root signalling.

Local leaf and root infection with Colletotrichum graminicola induces SAR in the systemic foliage

To determine the impact of local infection on the resistance of distal tissues, either one leaf per plant (leaf assay) or the root system (root assay), were subjected to an induction treatment by inoculation with C. graminicola. 6 days later, systemic leaves were challenged with the same fungus. C. graminicola-induced plants are referred to as SAR+ plants and mock-treated plants are referred to as SAR plants. In both the leaf assay and the root assay, fungal growth was quantified 3 days after challenge, and compared to infections on SAR plants. Fungal growth was significantly reduced in the systemic leaves of SAR+ plants compared to SAR plants (Figure 4). Induced resistance was observed in both the leaf above the initially induced leaf (Figure 4a) and the one below it (Figure 4b), indicating a bi-directional systemic response. Interestingly, root infection also induced foliar systemic resistance against C. graminicola (Figure 4c).

Figure 4.

Local Colletotrichum graminicola leaf and root infection triggers systemic resistance against the same fungus. SAR + plants received an initial fungal infection, SAR plants were mock-treated.(a) Pre-infection of second leaves induces resistance in the younger third leaves.(b) Pre-infection of third leaves induces resistance in the older second leaves.(c) Leaves of root-infected plants are more resistant against C. graminicola compared to SAR plants that received a root mock treatment.

Plant hormones are implicated in systemic defence responses

To assess the contribution of plant hormones in establishment of the resistant state, SA, JA and ABA levels were quantified in systemic tissues of both locally infected leaves (leaf assay) and roots (root assay) at 36 and 96 hpi by UHPLC-MS/MS (Figure 3e–j). There was no significant change in hormone levels in the systemic foliage at 36 hpi after local infection of leaves (Figure 3e); however, at 96 hpi, SA had significantly accumulated in systemic leaves (Figure 3f). There were no statistically significant differences in SA, JA and ABA levels between roots from control and infected plants following infection at the above-ground level (leaf assay) (Figure 3g,h). Induction treatment of the root system (root assay) led to a significant accumulation of ABA in the foliage at 36 hpi (Figure 3i) and increased levels of both SA and ABA at 96 hpi (Figure 3j). Thus, while only SA levels increased during leaf-to-leaf SAR, both SA and predominantly ABA accumulated to a higher extent during root-to-leaf SAR.

The below-ground-induced SAR against Colletotrichum graminicola is mediated by ABA

The up-regulation of ABA-related genes and the elevated ABA levels in systemic leaves following root inoculation suggested that ABA may act as chemical regulator of root-to-shoot SAR. To investigate this possibility, roots were treated with ABA and leaves were challenge-inoculated 6 days later with C. graminicola (Figure 5). ABA treatment of roots resulted in significantly reduced fungal growth on leaves compared to control plants. Thus, application of ABA to the root system of maize mimics biological SAR induction and leads to protection of the leaves against anthracnose. Moreover, root application of the functional SA analogue BTH resulted in a similar resistance level (Figure 5), suggesting an involvement of both ABA and SA in the induction of systemic resistance.

Figure 5.

ABA and BTH treatment of roots triggers systemic resistance against Colletotrichum graminicola in the foliage, similar to the resistance on leaves of root-infected plants.Different letters indicate statistically significant differences (= 20, three independent observations; one-way anova,< 0.05).

Colletotrichum graminicola induces organ-specific local and systemic host metabolomic adaptations

To determine the plant reactions at the metabolomic level, an UHPLC-QTOF-based analysis of secondary metabolites in local and systemic C. graminicola-infected maize roots and leaves was performed at six dpi. The goal was to obtain a general overview of metabolomic adaptations during maize/C. graminicola interactions, and to identify organ/tissue-specific markers of antifungal defence responses, using the identical experimental set-up as for gene expression and hormone analysis.

In a first step, the metabolomic profile of local leaf and root infections was investigated. Principal component analysis (PCA) allowed separation of control and infected leaves and roots into various groups (Figure 6), showing a distinct profile for both leaf and root control tissue as well as infected versus control tissues. Of the 100 compounds most highly induced during local C. graminicola infection, only 25 were common to infected roots and leaves. Using high-resolution tandem mass spectra (HRMS/MS) and/or chemical standards, 17 distinctive, significantly up-regulated, metabolites in either infected leaves or roots were identified (Table 1). In both organs, high amounts of flavonoids such as naringenin chalcone, apigenin or genkwanin were present. In contrast, lysophosphatidic acid was only induced in roots, whereas 3–caffeoyl-quinic acid (chlorogenic acid) was not detected in roots. In general, leaves responded to infection with increased accumulation of the compounds compared to roots. However, the basal levels of flavonoids detected were higher in roots (Table S3). In contrast to the local metabolomic profiling, the profiles of systemic organs could not be separated by PCA. However, a supervised partial least squares discriminant analysis (PLS-DA) model (Figure S5) separated control and systemic parts, suggesting minor adaptations of the secondary metabolome in systemic tissues during local infection. As the generated dataset was complex, the putative presence of co-regulated clusters was investigated by analysing the sets using the filtering and clustering tool MarVis (Kaever et al., 2009, 2012). Eight hundred and 86 compounds clustered for local conditions (Table S4), and 583 candidates clustered for systemic conditions in negative mode (Table S5), identifying marker candidates with different intensity profiles (Figure 7). Clusters with higher intensities in control leaves and large clusters that were induced in infected leaves were observed (Figure 7a). Interestingly, these clusters showed a low intensity for both control and infected roots. Moreover, some clusters showed prominent induction in infected roots only. Some small clusters of markers induced in systemic leaves upon leaf infection were also distinguished (Figure 7b). These clusters contained markers distinct from the ones with high intensity in leaves upon root infection. Ascorbic acid (m/z 175.02407) was among the clustered putative compounds induced in systemic leaves upon leaf infection. Moreover, the secondary metabolite maysin (m/z 575.1401) and the isoscoparin rhamnoside (m/z 607.1663) (as yet uncharacterized, to our knowledge) also showed higher concentrations. In contrast, a different situation was present in systemic leaves after root infection. The amino acids phenylalanine (m/z 166.0869), tryptophan (m/z 205.0979) and isoleucine/leucine (m/z 132.1034) as well as feruloyl-feruloyl-glycerol (m/z 443.1341) and a hexose (m/z 179.0556) were induced in systemic leaves after root infection. Interestingly, feruloyl-feruloyl-glycerol was also induced locally in infected roots and leaves (Table 1). In addition, selected markers showed higher expression in systemic roots upon leaf infection, suggesting leaf-to-root signalling.

Table 1. Metabolites induced in maize leaves and roots upon Colletotrichum graminicola infection
CompoundMassMF (M-H)-FragmentsP(1)IDLeaf FIRoot FI
  1. MF, molecular formula; (M-H)-, negative ion mode; P(1), PCA ranking; ID, identification; HRMS/MS, high-resolution tandem mass spectra; FI, fold induction (infected versus control); ND, not determined. Asterisks indicate P value (infected versus control, Mann–Whitney U test) (***< 0.001, **< 0.01, *< 0.05).

Naringenin chalcone271.0609C15H11O5151.0031, 119.0500−0.187914Standard 57** 9.6**
Lysophosphatidic acid (18:2)447.2508C22H40O7P279.2327−0.176749HRMS/MS0.47.4***
Acyl sugar819.2335C38H43O20175.0397−0.140926HRMS/MS8.5** 2.9***
Eryodictiol287.0559C15H11O6-−0.135599HRMS/MS36.1** 6.9***
3–caffeoyl-quinic acid353.0872C16H17O9191.0559−0.135461Standard3468.5** 4.6***
N–p–coumaroyltryptamine305.1293C19H17N2O2119.0500, 159.0924−0.129356HRMS/MS101.2** 120.5**
Feruloyl-feruloyl-glycerol443.1341C23H23O9193.0505, 134.0373−0.126652HRMS/MS16.3** 9**
Citric acid191.0197C6H7O7111.0082, 87.0081−0.110255Standard3.4* 2.8*
Coumaroyl-tyramine282.1133C17H16NO3119.0496, 162.0563−0.110089Standard53.9** 7.2***
3–caffeoyl-quinic acid (dimer)707.1817 −0.0856772 154.1** ND
N–feruloyl-tryptamine335.1397C20H19N2O3119.0498−0.079998HRMS/MS68.1** 6.5***
Apigenin269.0455C15H9O5117.0340, 151.0032−0.0665907Standard20.9** 12.4***
Genkwanin283.0607C16H11O5268.0373−0.065281Standard78.2** 6.1***
5–feruloyl-quinic acid367.1029C17H19O9191.056−0.0635136HRMS/MS28.9** 5.8***
Coumaroyl-feruloyl-glycerol413.1234C22H21O8193.0500, 163.0392−0.0525341HRMS/MS3.4* 7.4**
Feruloyl-tyramine312.1236C18H18NO4−0.0514736HRMS/MS89.7** 4.8**
Homoeryodictyol301.0712C16H13O6117.0341−0.0466089HRMS/MS12.7** 7.6***
Figure 6.

Principal component analysis (PCA) score plot of Colletotrichum graminicola infected and control leaves and roots. ctr, control; inf, infected.

Figure 7.

Cluster plot of local (a) and systemic (b) metabolomic fingerprinting upon Colletotrichum graminicola infection.(a) Control (ctr) and infected (inf) leaves and roots are compared in clusters 1–20.(b) Leaves from control plants (LA ctr sys leaf) were compared with systemic leaves from leaf-infected plants (LA sys leaf), systemic leaves from mock-treated (RA ctr sys leaf) and infected roots (RA sys leaf), systemic roots from mock-treated leaves (LA ctr sys root) and systemic roots from infected leaves (LA sys root).

Leaf and root metabolites contribute to antifungal defence

The role of inducible secondary metabolites identified during local C. graminicola leaf and root infection was assessed by testing the in vitro antifungal activity of selected compounds (Figure S7). Apigenin, genkwanin and chlorogenic acid all led to a dose-dependent reduction of radial growth of C. graminicola on medium containing the corresponding chemicals, suggesting that induction of these compounds is part of the inducible chemical arsenal that maize uses to counteract C. graminicola infection.


Breeding programs are generally focused on yield improvement, and mechanisms related to stress management by the plant are often neglected and not routinely selected for. Here, we investigated the capacity of maize to express local and induced resistance at both the above- and below-ground level against the maize anthracnose fungus C. graminicola. We assessed the reactions of the plants to inducing and challenge treatments at the phenotypic, transcriptional and metabolomic level.

Local and systemic adaptations at the transcriptomic level upon infection

The interaction between maize and C. graminicola is characterized by a change in lifestyle of the fungus at a certain developmental stage, as defined by Vargas et al. (2012). After an initial biotrophic phase in leaves, it becomes more invasive and switches to a necrotrophic lifestyle. In roots (Figure S1), there was no obviously necrotrophic behaviour, and growth was much restricted compared to leaves. However, most tested defence marker genes were similarly up- or down-regulated in both organ types (Figure 1a). Generally, infection by C. graminicola appears to trigger the SA-dependent defence pathway. However, the root system responded faster to fungal ingress than leaves did (Figure 1a), but transcript levels of defence genes such as PR1 reached up to 100 times higher levels in leaves than in roots (Figure 2 and Table S2). This may either be the consequence of a constitutively elevated basal defence state of the root system blocking pathogen ingress so rapidly that no major induction of defence transcripts is possible, and/or the defence response may be actively suppressed by the pathogen in the roots. Similarly, Magnaporthe grisea infections in rice show distinct disease progress in leaves and roots associated with different transcriptional patterns (Marcel et al., 2010). The authors concluded that M. grisea utilizes a biotrophic lifestyle strategy during root infections. There was no down-regulation of the defence gene transcriptome in C. graminicola-infected roots during at least 6 days following inoculation, suggesting that C. graminicola employs an infection strategy that is different from the biotrophic one of M. grisea. Recent findings also suggest that C. graminicola does not suppress host defence mechanisms during biotrophic phases of leaf infections (Vargas et al., 2012), in contrast to other biotrophs (Doehlemann et al., 2008; Djamei et al., 2011). Thus, the biotrophic phase of C. graminicola is not comparable with the lifestyle of true biotrophs. Nonetheless, certain defence-related genes, for example Bx1, IGL or CHS C2, were down-regulated during early leaf infection phases in the maize/C. graminicola interaction (Figure 1). Bx1 and IGL both encode enzymes that convert indole-3–glycerole phosphate into indole, which is the first step in the synthesis of benzoxazinoids (Glauser et al., 2011). As benzoxazinoids play an important role in the immunity of maize plants against fungi and aphids, and benzoxazinoid-deficient mutants are impaired in penetration resistance against a necrotrophic fungus (Ahmad et al., 2011), down-regulation of Bx1 and IGL early in the interaction may facilitate the development of C. graminicola in leaves. In contrast, the early transient up-regulation of Bx1 in roots is in agreement with the higher basal resistance of roots to C. graminicola.

Metabolomic above-and below-ground changes in Colletotrichum graminicola -infected maize

In contrast to the minor differences at the transcriptomic level between C. graminicola infections of roots and leaves, respectively, the metabolomic fingerprinting yielded major organ-specific differences. This suggests that leaves and roots employ distinct chemical arsenals of secondary metabolites during antifungal defence. Common to both organs was an increase in flavonoid levels in response to fungal infection. However, the constitutive levels of flavonoids were generally higher in control roots compared to control leaves. Interestingly, infection of leaf cells was accompanied by strong autofluorescence, including aggregation of fluorescent vesicles around the penetration peg (Figure S6) early during infection. As anthocyanins and hydroxycinnamic acid derivatives accumulate at the cell wall of C. graminicola-attacked maize leaf cells (Vargas et al., 2012), flavonoids and additional defence compounds may be directed towards the penetration site by vesicles (Kwon et al., 2008). Flavonoids play an important role in both above- and below-ground plant–microbe interactions. In Sorghum bicolour, Colletotrichum sublineolum foliar infection is associated with higher levels of phlobaphenes (Ibraheem et al., 2010). In the roots, flavonoids such as naringenin and quercetin are implicated in mycorrhization, nodulation, root development or nematode repulsion (Hassan and Mathesius, 2012). Interestingly, C. graminicola encodes a putative quercetinase that cleaves quercetin (Krijger et al., 2008), indicating that the fungus has the potential to counteract flavonoid-based chemical defences. Flavonoids induced in both leaves and roots in response to C. graminicola attack also have an antagonistic effect on fungal growth (Figure S7).

The elevated basal level of flavonoids and other defensive compounds in roots (Table S3) suggests an enhanced defensive state of this organ, as suggested by the fact that roots adapt their transcriptome more rapidly to defence situations (Figure 1a) and also generate higher levels of defence-associated plant hormones (Figure 3). Maize crown roots are richer in defensive compounds compared to other root types (Robert et al., 2012), and, as they are vital in early development, it has been suggested that this helps in defence of maize roots against herbivory. Similarly, roots may employ an enhanced basal resistance against fungal infections. In addition, roots may act as chemical arsenal. In Arabidopsis, flavonoids are transported from roots to distal tissues (Buer et al., 2008). Colletotrichum graminicola leaf infection may induce the translocation of flavonoids from root to shoot, which may explain why there was no significant up-regulation of CHS C2 in infected leaves although flavonoids were clearly present.

The role of plant hormones in maize defence against Colletotrichum graminicola

Plant hormones and numerous other compounds with biological activity are of utmost importance for the control of targeted reactions of plants during stress situations (Erb and Glauser, 2010). The pattern of hormonal adaptations during leaf and root infections of maize with C. graminicola is in accordance with the transcriptome data: infected roots reacted faster than leaves and exhibited significant changes in SA, JA and ABA levels compared to control plants. The early down-regulation of JA in infected roots is reminiscent of the observed inter-play between SA and JA during biotrophic interactions (Pieterse et al., 2009), although, at later stages, SA, JA and ABA all accumulated to higher levels. The hormone levels were higher in infected roots compared to infected leaves. This fits the attenuated and symptomless disease progress observed for C. graminicola in roots, suggesting that the hormones really contribute to a more effective defence. Only little is actually known about their importance in root defence (Gutjahr and Paszkowski, 2009). JA inhibits nodule initiation by Sinorhizobium meliloti on Medicago truncatula (Sun et al., 2006). Similarly, Nicotiana tabacum with reduced levels of SA showed elevated mycorrhizal colonization at early time points (Herrera Medina et al., 2003), indicating that SA is involved in the control of biotrophic plant–microbe interactions at the root level. Thus, the strong up-regulation of SA in C.  graminicola-infected maize roots suggests a chemical defence strategy that is similar to that found in biotrophic interactions. In rice, brassinosteroids have been shown to suppress gibberellin- and SA-mediated root defences against Pythium graminicola, indicating that SA-mediated root resistance is strongly regulated by a hormonal network (De Vleesschauwer et al., 2012). Recently, ABA has been found to act as negative regulator of SA, JA and ethylene-mediated defence against root nematodes in rice (Nahar et al., 2011). ABA has also been shown to be induced in maize roots upon herbivore attack (Erb et al., 2009a). As ABA has no negative effect on C. graminicola in vitro growth (Vargas et al., 2012), root-induced ABA may play a role in fine-tuning hormonal pathways as observed during foliar herbivore defence mechanisms in Arabidopsis (Bodenhausen and Reymond, 2007). Furthermore, local ABA application on maize leaves led to enhanced C. graminicola disease progress by faster transition to necrotrophy (Vargas et al., 2012). The contrast between our observations showing increased resistance following ABA treatment and the results obtained by Vargas et al. (2012), who observed an increased susceptibility of maize towards C. graminicola after ABA treatment, may be due to changes of the role of ABA during disease progress, as described for several plant–pathogen interactions (Ton et al., 2009). ABA induced or applied early in an interaction stimulates host resistance, but, during later phases, when the pathogen has penetrated the host tissue, ABA may interfere with ROS production and hence cause an increase in susceptibility. As some pathogens are known to produce ABA (Mauch-Mani and Mauch, 2005), the effect of the presence of ABA on C. graminicola growing in liquid cultures was tested. ABA levels in these cultures were near the detection limit (Figure S8), and supplementing the culture medium with crude plant extracts did not induce ABA accumulation, suggesting that C. graminicola does not produce ABA specifically during the interaction with its host.

SAR in maize

Both maize leaves and roots possess the ability to trigger systemic antifungal resistance in distal tissues (Figure 4). Colletotrichum graminicola leaf infection led to systemic changes at the transcriptomic level, higher accumulation of SA, and elevated resistance against this fungus. Similarly, root inoculation activated massive gene expression changes in systemic leaves, increased accumulation of SA and ABA in systemic leaves, and systemic resistance against C. graminicola infection. SA appears to play a role in both leaf–leaf and root–leaf systemic resistance in maize against C. graminicola. In contrast, infection does not result in higher SA levels in rice (Silverman et al., 1995), probably due to the already constitutively high basal levels of SA. However, resistance in general as well as SAR mechanisms are highly dependent on the environmental conditions. This is illustrated by the fact that, during infection of Arabidopsis with P.  syringae pv. maculicola, strong light triggers SAR in the absence of either SA or PR1 induction in systemic leaves (Zeier et al., 2004).

Systemic acquired resistance requires the generation of mobile alarm signals. The clustering of systemic metabolomic data (Figure 7b) indicates systemic metabolomic changes; however, these are much less prominent than during local C. graminicola attack. At present, it is not possible to determine which compounds act as mobile signals. Some of the systemically induced compounds identified in this study are known to play a role in plant defence. For instance, the C–glycosyl flavone maysin has been associated with resistance to the corn earworm Helicoverpa zea (Byrne et al., 1998), and sugars are known to act as priming molecules during plant immune responses (Bolouri Moghaddam and Van den Ende, 2012). However, further involvement of these compounds in the SAR of maize remains to be investigated. Interestingly, SAR induced by a below-ground infection resulted in a stronger resistance than SAR induced above-ground. This observation supports the idea that roots are better protected than leaves and may act as a defence arsenal. Fungal root infections led to higher levels of ABA in leaves, similar to observations during root herbivory (Erb et al., 2009a). ABA application on maize roots triggers foliar resistance against Spodoptera littoralis, as well as the necrotrophic fungus Setosphaeria turcica (Erb et al., 2009a). As ABA root treatment also induces foliar resistance against C. graminicola (Figure 5), it may act as general root–shoot systemic resistance signal. Nonetheless, it remains to be determined whether ABA translocates from roots to shoots during SAR, or whether ABA is also induced in systemic tissues. ABA probably also modulates other systemic defence pathways, as root treatment with ABA in maize primes the foliage for enhanced DIMBOA and chlorogenic acid accumulation (Erb et al., 2009b).

Despite an absence of major systemic changes at the transcriptome and hormone level in roots following leaf infection, metabolomic fingerprinting uncovered clusters of metabolites that show higher intensities in systemic roots. This may be due to the higher defensive state of roots, which would dilute a systemic defence response. However, induction of SAR from the second to the third leaf and vice versa suggests the possibility of bi-directional signalling as previously demonstrated for herbivore resistance. In caterpillar-resistant maize, foliar caterpillar attack induces accumulation of the cysteine protease Mir1–CP in roots (Lopez et al., 2007). Mir1–CP is highly toxic for caterpillars as it damages the insect mid-gut. Root-derived Mir1–CP is translocated to the shoot, confirming the crucial role of roots in both local and systemic defence systems (Luthe et al., 2011).

In conclusion, this study demonstrates that both maize leaves and roots apply specific defence strategies to counteract C. graminicola infection. Remarkably, C. graminicola is able to deal with these various strategies, and is capable of infecting a variety of tissues, including different root types. This ability of C. graminicola may explain its success as a serious maize pathogen. Recent advances in C. graminicola genomics (O'Connell et al., 2012) may be further applied to assess tissue-specific physiological adaptations of the fungus. Maize roots contain higher basal levels of defensive compounds such as flavonoids, which may be a valuable target for future crop enhancement programs. Similarly, our study also shows that local C. graminicola infection triggers systemic resistance in as yet uninfected tissues. Although both SA and ABA appear to be implicated in this defence mechanism, further studies are required to identify putative long-distance mobile signals. Given the existence of climate change and the growing demand for maize as a high-value crop, C. graminicola is an emerging agricultural threat. Thus, understanding plant and fungal behaviour in both above- and below-ground tissues is crucial to develop novel anthracnose disease control strategies.

Experimental procedures

Plants and fungi

Maize plants (Zea mays, variety Jubilee, West Coast Seeds, were grown in a soil-free system (Planchamp et al., 2012) in a growth chamber at 25°C day/22°C night temperature with 16 h light (400 μE m−2 sec−1) and 60% relative humidity. Colletotrichum graminicola (M1.001, obtained from Lisa Vaillancourt, University of Kentucky, Department of Plant Pathology, Lexington, KY), and its transgenic GFP-expressing derivative C. graminicola-gGFP (Erb et al., 2009a) were maintained at 25°C on potato dextrose agar (Difco PDA, Becton Dickinson, under continuous illumination (70 μE m−2 sec−1).

Fungal infections

Leaves were locally inoculated by spreading 20 μl of C. graminicola conidia suspension (6 × 105 spores ml−1 sterile water containing 0.01% Silwet L–77, Lehle Seeds, on the surface using a paintbrush. Inoculated plants were kept in the dark (100% relative humidity, 25°C, 16 h), before transfer to the growth chamber. Roots were inoculated by dipping for 30 min in a similar spore suspension, then transferred back to the soil-free growth system. Infections were performed at the end of the day period.

Inhibition of fungal radial growth was tested by applying 3 μl of conidia suspension (3 × 105 spores ml−1) to the centre of each well in 12-well culture plates (Millipore, containing potato dextrose agar plus the test compounds. Growth was measured after 2 days. Chlorogenic acid (A.R. Collins, Ecology and Evolution Department, University of Fribourg, Switzerland), apigenin and genkwanin (both Extrasynthese, were dissolved in EtOH (99.9%, Merck, and further diluted in sterile water.


Light microscopy was performed using a Nikon Eclipse E800 microscope (" ). Colletotrichum graminicola -gGFP disease progress was observed using a Leica TCS SP5 II confocal laser scanning microscope (; digital images were acquired using Leica Application Suite Advanced Fluorescence (version 2.0.0, build 1934). To assess and quantify fungal colonization of plants, C. graminicola-gGFP infection spots were photographed using a Nikon dissecting microscope C–BD230 with blue light excitation; the images were further processed as described previously (Erb et al., 2011).

RNA extraction and gene expression analysis

Plant RNA isolation was performed according to manufacturer's instructions using an RNeasy plant mini kit (Qiagen, RNA was treated with DNase (Qiagen), and reverse-transcribed into cDNA using SuperScript III reverse transcriptase (Invitrogen, Primers for quantitative real-time PCR were designed using the universal probe library assay design tool from Roche ( The primers used in this study are listed in Table S1. Primer efficiency was determined by performing a quantitative real-time PCR with serial diluted cDNA; the minimal accepted efficiency for the primers was set to 0.8. The quantitative real-time PCR was performed using the SensiMix SYBR kit (Bioline, on a Rotor Gene 6000 cycler (Qiagen). The reaction volume was 10 μl, consisting of 2.5 μl nuclease-free water, 5 μl SensiMix SYBR Master Mix (Bioline), 0.25 μl forward and reverse primer (each 10 μm) and 2 μl cDNA. PCRs were performed using three independent biological replicates per sample, each replicate consisting of a pool of six plants. PCR reactions were performed using technical duplicates as a three-step reaction (initial hold step, 95°C for 10 min; 40 cycles of amplification comprising 95°C for 15 sec, 60°C for 20 sec and 72°C for 20 sec), with a final melting curve analysis (68–95°C). Melting curve and cycle threshold (C t) analysis were performed using rotor gene 6000 software version 1.7. Gene expression of infected tissue was calculated relative to control plants and relative to the expression of the two housekeeping genes ZmGAPc and ZmActin, and the specific primer efficiencies were determined using REST 2009 (Qiagen). The statistical outputs of the analysis using rest 2009 are summarized in Table S5. The gene expression data were further visualized using the software MeV viewer (

Biological and chemical systemic resistance assays

To investigate SAR on the foliage, the second or third leaf of 12-day-old plants was inoculated with C. graminicola as described above (= 30 plants, minimum of three independent observations). Three 50 μl drops were applied and distributed over the whole leaf area (SAR+ plants); in parallel, control plants were mock-treated with water containing 0.01% Silwet L-77 (SAR plants). Challenge infection was performed at six dpi using a C. graminicola-gGFP spore suspension as described above. Infection was quantified at 3 days after challenge infection as described previously (Erb et al., 2011). Fungal growth between treatments was compared using the Mann–Whitney U test. SAR induction via roots (12-day-old plants; = 30, five independent observations) was performed by dip inoculation with C. graminicola (6 × 105 conidia ml−1) as described above. Challenge infections were performed 6 days after the inducing treatment on the second leaf of root-infected (SAR+) and root mock-treated (SAR) plants, and quantified as described previously (Erb et al., 2011). ABA (300 μ± –ABA; Sigma, was sprayed directly on roots (= 30 plants, three replicates) of 12-day-old plants that were challenged 6 days later with C. graminicola-gGFP as described above. BTH (Bion, 1.5 mm, Syngenta, was applied in the same way.

Hormone quantification

Salicylic acid, JA and ABA were quantified simultaneously in single samples using UHPLC-MS/MS (Glauser et al., 2012). In brief, hormones from 100 mg fresh weight tissue were extracted using EtOAc/formic acid (99.5/0.5 v/v). Before extraction, an internal standard solution containing isotopically labelled SA, JA and ABA (10 ng/ml) was added to the samples. The extracts were evaporated to dryness and resuspended in 100 μl aqueous methanol (70%). After centrifugation at 5000  g for 2 min at 20°C, 5 μl of the supernatant were subjected to UHPLC-MS/MS. The hormones were quantified using a calibration equation obtained by linear regression from five calibration points for each analyte. Peak areas of the hormones measured in the samples were normalized to the internal standard before applying the calibration equation.

Metabolomic profiling

For metabolomic analysis, 12-day-old maize plants were infected with C. graminicola as described above. At 6 dpi, metabolites were isolated from 100 mg flash-frozen and ground tissue using 500 μl extraction solvent (80% MeOH, 19.5% H2O, 0.5% formic acid). Three biological replicates (six pooled plants per treatment) were analysed in technical duplicates using UHPLC-QTOF. Separation was performed using an Acquity UPLC (Waters, at a flow rate of 400 μl min−1 using an Acquity BEH C18 column (length 50 mm, 2.1 mm internal diameter, 1.7 μm particle size) at 30°C. Solvent A consisted of water and 0.05% formic acid, and solvent B consisted of acetonitrile and 0.05% formic acid. The following linear gradient was employed: 0–6 min, 5–100% B; 6–8 min holding at 100% B; 8–10 min re-equilibration at 5% B. The QTOF parameters (Synapt G2, Waters) were applied as described by Glauser et al. (2011). The mass spectrometry data were further processed using the MarkerLynx application of the MassLynx software (Waters). PCA and PLS–DA were performed using EZinfo (Umetrics, In order to identify selected markers, co-elution with available reference standards and/or a positive match with MS2 fragmentation spectra were requested. The toolbox MarVis (http://marvis.gobics.de33) was used for filtering and ranking the local and systemic metabolomic data. Raw data were converted into.CDF files that were extracted using the Bioconductor ( packages ‘xcms’ (Smith et al., 2006; Tautenhahn et al., 2008) and ‘multtest’ ( in R (R Development Core Team, 2008). To filter a subset of high-quality markers, a Kruskal–Wallis one-way anova was applied. A P value <0.01 was considered significant. Clustering of the high-quality markers was based on m/z value ranking and visualized using a MarVis colormap.

Statistical analysis

Variances of quantified levels of metabolites and fungal growth for multiple groups were analysed by a one-way anova; a P value <0.05 was considered significant. The Mann–Whitney U test was used to compare significant differences between two sample groups. All statistical analysis was performed using Sigma Plot 11.0 ( The significance of gene expression data was calculated using the software rest 2009 (Qiagen), which applies the Pfaffl mathematical model for relative quantification of quantitative real-time PCR data (Pfaffl, 2001).


We are grateful to Armelle Vallat (Chemical Analytical Service, University of Neuchâtel, Switzerland) for providing the tools for UHPLC-MS/MS analysis. We thank Lisa Vaillancourt (Department of Plant Pathology, University of Kentucky, Lexington, KY) for providing the wild-type C. graminicola M1.001 strain, Sanaa Ayachi (Department of Biology, University of Neuchâtel, Switzerland) for technical help with confocal microscopy, and Jordi Gamir Felip (Department CAMN, Universitat Jaume I, Castellón, Spain) for advice on using MarVis. Financial support from the National Centre of Competence in Research ‘Plant Survival’ and grant number 31003A-120197, both research programs of the Swiss National Science Foundation, is gratefully acknowledged.