max2, d14, and ccd7 plants, but not kai2 plants, produce more branches with stems that accumulate higher levels of anthocyanins

To explore the role of SL and KAR signaling in the plant’s resistance to stem-boring herbivores, we first characterized MAX2, the coreceptor of both SL and KAR signaling, in N. attenuata. The two homologues of MAX2, NaMAX2a, and NaMAX2b, were found to be localized to the nucleus (S1A and S1B Fig), and both proteins interacted with NaD14 in the presence of GR24 (S1C Fig). A virus-induced gene silencing (VIGS) experiment that independently silenced the two homologues, albeit relatively weakly (with 61% of MAX2a and 63% of MAX2b silencing efficiency, respectively) suggested functional redundancy of the two homologues, as the characteristic branching phenotype of SL-deficient lines (Fig 1A and 1B) was not observed. Given that both proteins interacted with D14, we next generated a stable transgenic line expressing an RNAi construct, inverted repeat max2, which silenced both MAX2a and MAX2b with a single inverted repeat tandem construct (S1D Fig). Two independent homozygous transgenic lines, max2#1 and max2#2 (Fig 1A), each harboring single, complete insertions, as verified by several NanoString probes (S1E Fig), were selected. As the silencing efficiency of MAX2a/b was generally low (50%–70% silencing efficiency) (Fig 1C), phenotyping assays in addition to the stem/branch number assays (Fig 1B) were conducted to characterize the max2 lines in greater depth: in addition to increased branching, both lines of max2 plants showed attenuated responses to GR24 and KAR treatments in assays that measured hypocotyl elongation and seed germination (S1F and S1G Fig). Three additional suites of transgenic lines in which the key components of the SL and KAR signaling pathways, including D14, CCD7, and KAI2 genes (S2A and S2B Fig), were silenced by RNAi were generated (Fig 1A and 1C). For each silencing construct, we selected two independent transgenic lines, which harbored a single complete insertion of the inverted repeat RNAi construct, as verified by several NanoString probes (S2C–S2E Fig) [42]. A transgenic line transformed with an empty vector (EV) was used as control plants [11]. All lines of SL-insensitive (max2 and d14) and SL-deficient (ccd7) plants displayed increased numbers of primary branches and shorter plant heights; two kai2 lines did not differ from control plants in these parameters (Fig 1A and 1B). Consistent with a negative-feedback loop controlling SL production, transcripts of two SL biosynthetic genes, NaCCD7 and NaCCD8, were up-regulated in roots of max2 and d14 plants (S3A and S3B Fig). When plants were grown under low phosphate supply rates, the levels of (±)2′-epi-orobanchol, the active form of SL in N. attenuata, were approximately 20- to 50-fold higher in the root exudates of d14 and max2 plants (S3C–S3F Fig); in contrast, this compound was nearly undetectable in the root exudates of ccd7 plants (S3F Fig).

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Fig 1. SL-RNAi plants have more branches.

(A) Representative branching phenotypes of EV, two independent transgenic lines in which the target genes were individually silenced: max2#1 and max2#2, d14#1 and d14#2, ccd7#1 and ccd7#2, and kai2#1 and kai2#2 plants. Scale bar, 5 cm. (B) Plant height and primary branch numbers per plant of indicated plants (±SE, n = 12). Branches longer than 5 cm were counted. (C) Silencing efficiency of target genes. Relative transcript abundance of MAX2a and MAX2b in axillary buds of EV, max2#1, and max2#2 plants; D14 in axillary buds of EV, d14#1, and d14#2 plants; CCD7 in seedlings of EV, ccd7#1, and ccd7#2 plants; KAI2a and KAI2b in leaves of EV, kai2#1, and kai2#2 plants (±SE, n = 3–4) (***P < 0.001; two-tailed Student t test). Values for graphs (B) and (C) are listed in S1 Data. ccd, carotenoid cleavage dioxygenase; d14, dwarf 14; EV, empty vector; kai2, karrikin insensitive 2; max2, more axillary growth 2; n.s., not significant; RNAi, RNA interference; SL, strigolactone.

https://doi.org/10.1371/journal.pbio.3000830.g001

Interestingly, the stems of max2, d14, and ccd7 plants turned red at the later developmental stages of flowering (Fig 2A), a phenotype not previously reported in other SL-related studies. Accordingly, the anthocyanin levels were significantly higher (2-fold) in these three SL-RNAi plants (Fig 2B). Given the role of JAs and auxin in the regulation of anthocyanin accumulations in N. attenuata [5], the constitutive levels of JAs (JA and JA-Ile) and IAA were quantified. Both JA and IAA levels were significantly increased in the stems of max2, d14, and ccd7 plants, but the fold change of IAA was overall greater than that of JAs (Fig 2C). However, neither stem color and anthocyanin content nor JA and IAA levels in kai2 plants differed significantly from those of EV control plants (Fig 2).

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Fig 2. Anthocyanin accumulations in stems of max2, d14, ccd7, and kai2 plants.

(A) Representative stem phenotypes of 75-day-old EV, max2, d14, ccd7, and kai2 plants. (B) Relative anthocyanin levels in epidermis of stems of indicated plants (±SE, n = 8). (C) Levels of JA, JA-Ile, and IAA in stems of indicated plants (±SE, n = 6) (*P < 0.05; **P < 0.01; ***P < 0.001; two-tailed Student t test). Values for graphs (B) and (C) are listed in S1 Data. ccd, carotenoid cleavage dioxygenase; d14, dwarf 14; EV, empty vector; IAA, indole-3-acetic acid; JA, jasmonate; JA-Ile, jasmonic acid-isoleucine; kai2, karrikin insensitive 2; max2, more axillary growth 2; n.s. not significant.

https://doi.org/10.1371/journal.pbio.3000830.g002

max2, d14, and ccd7 plants, but not kai2 plants, are more susceptible to the larvae of the stem-boring weevil, T. mucorea

The greater anthocyanin contents of the stems and the higher JA levels of the SL-RNAi plants suggested alterations in plant defense in these lines [1,43]. To explore this inference, we investigated the role of SL signaling in herbivore defense with an ecologically relevant herbivore, the neonate larvae of the N. attenuata specialist T. mucorea weevil, which enter the RSJ of N. attenuata plants to feed on the pith of stems (Fig 3A) and elicit anthocyanin accumulations in the epidermal layers of the RSJ and stems (Fig 3B). We performed larval performance assays with a previously characterized method [11]: to mimic how T. mucorea attacks plants in nature, freshly collected eggs were inoculated into the petioles of rosette leaves, the natural oviposition sites of T. mucorea adults. Neonate larvae then burrow through the petioles into the pith of the RSJ, where they feed endophytically inside stems. At 2 or 3 weeks postinoculation (wpi), when larvae in wild-type (WT) stems are typically in the penultimate instar [44], stems were carefully split open, larvae were retrieved, and larval biomass was quantified. To first investigate the direct role of JAs in defense against T. mucorea, a transgenic line deficient in JA signaling, resulting from the silencing the JA biosynthetic gene, allene oxide cyclase (aoc) plants [45], was used for the larval performance assay. In contrast to EV plants, aoc plants did not show any red-stem phenotype after T. mucorea attack (Fig 3B), and the larvae performed much better in aoc plants (Fig 3C), indicating that JA positively regulates stem anthocyanin accumulation and defense against T. mucorea attack, as previously reported [11].

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Fig 3. max2, d14, and ccd7 plants are more susceptible to T. m. attack.

(A) Schematic diagram of a T. m.–attacked plant. Stem pith and RSJ part used in this study are marked. (B) Representative pictures of EV, max2, and aoc plants after 3 weeks of T. m. attack; red pigmentation occurred along stems after attack or in max2 plants regardless of attack as indicated by red arrows. (C) Biomass of T. m. larvae after attacking EV and aoc plants for 2 weeks (n = 8–15). (D) Representative pictures of T. m. larvae after attacking EV, max2#1, and max2#2 plants for 2 weeks and biomass of T. m. larvae after attacking EV, max2#1, and max2#2 plants for 2 weeks (n = 15). Kinetic analysis of T. m. larvae biomass accumulations after 1, 2, and 3 wpi (n = 10–18). Scale bar, 2 mm. (E) Biomass of T. m. larvae after attacking EV, d14#1, and d14#2 plants for 2 weeks (n = 16). (F) Representative pictures and biomass of T. m. larvae after attacking EV, ccd7#1, and ccd7#2 plants for 2 weeks (n = 20). (G) Biomass of T. m. larvae after attacking EV, kai2#1, and kai2#2 plants for 3 weeks (n = 20). (H) Relative transcript abundance of BRC1a and CCD8 in stem pith of EV plants without (Control) or with T. m. attack (T. m.) for 2 weeks (±SE, n = 4). Levels of (±)-2′-epi-orobanchol in roots with indicated treatments (±SE, n = 8). (I) Levels of JA and JA-Ile in piths of EV and max2 plants without or with T. m. attack for 3 weeks (±SE, n = 6–10). (J) Levels of JA, JA-Ile, and IAA in piths of EV, max2, and ccd7 plants with T. m. attack for 2 weeks (±SE, n = 6–10) (two-tailed Student t test). Values for graphs (C–J) are listed in S1 Data. aoc, allene oxide cyclase; BRC1, branched 1, ccd, carotenoid cleavage dioxygenase; d14, dwarf14; EV, empty vector; IAA, indole-3-acetic acid; JA, jasmonate; JA-Ile, jasmonic acid-isoleucine; kai2, karrikin insensitive 2; max2, more axillary growth 2; n.s. not significant; RSJ, root–shoot junction; T. m., T. mucorea; wpi, weeks postinoculation.

https://doi.org/10.1371/journal.pbio.3000830.g003

To evaluate the role of MAX2 in defense against T. mucorea, we measured the growth and timing of instar transitions of larvae feeding in stems of max2 plants. Larvae were significantly larger when feeding on max2 (#1 and #2) plants than on EV plants (Fig 3D). Furthermore, T. mucorea larvae consistently performed better in max2#2 plants than in EV plants regardless of the feeding period (approximately 1–3 wpi) (Fig 3D, S4A Fig), which implied constitutive (rather than induced) differences between EV and max2 plants in herbivore resistance. After insect infestation, both EV and max2 plants showed no differences in stem diameter, plant height, and numbers of primary branches compared with those of uninfested plants (S4B Fig). These results, consistent with field observations [44], suggest that T. mucorea attack does not morphologically alter plant structures. In addition, larvae were also found most frequently (approximately 80%) feeding on the pith of max2 stems in larvae choice assays (S4C Fig). Considering the involvement of MAX2 in both SL and KAR signaling pathways, d14, ccd7, and kai2 plants were additionally used in feeding assays to more precisely dissect the effects of SL and KAR signaling on herbivore resistance. The larvae feeding in the stems of both d14 and ccd7 plants were heavier than those feeding in the stems of EV plants (Fig 3E and 3F), demonstrating that SL signaling is positively correlated with larval performance. However, the performance of larvae feeding in EV or kai2 plants did not differ significantly (Fig 3G), indicating that KAR signaling is not involved in defensive responses against T. mucorea.

We identified SL-mediated phytohormonal responses to T. mucorea attack and changes in SL-reporter genes and SL levels in EV plants. In response to larval feeding, transcript abundances of BRC1a and CCD8 were significantly reduced to about 25% of those in unattacked EV plants, and the levels of (±)-2′-epi-orobanchol in roots decreased by 50% after attack (Fig 3H), indicating that T. mucorea attack leads to the down-regulation of SL responses. JA contents were dramatically elevated in an AOC-dependent manner upon T. mucorea attack (Fig 3I). In addition to the constitutive responses of IAA and JAs of max2 plants (Fig 2C), the inducibilities of JA (rather than JA-Ile) and IAA levels in the stems of max2 and ccd7 plants in response to T. mucorea feeding were also consistently higher than those of EV plants (Fig 3J).

To comprehensively illuminate the mechanisms responsible for the attenuated resistance of SL-insensitive plants to T. mucorea, we conducted a microarray assay to compare constitutive transcriptional changes in the pith of the RSJs of EV and max2 plants. Multidimensional scaling (MDS) analysis grouped max2#1 and max2#2 together and clearly separated them from the EV samples (S5A Fig). Differentially expressed genes (DEGs) included 1,160 up-regulated DEGs and 435 down-regulated DEGs (|log2FC| ≥ 1, false discovery rate (FDR) ≤ 0.05) (S5B and S5C Fig), and these were further used to compute the enrichment of Gene Ontology (GO) terms. The GO terms were highly enriched in processes associated with the regulation of meristem development, signaling, hormone metabolism, and transport. Among these, phenylpropanoid metabolism, response to wounding, and auxin transport and response have previously been reported to be involved in plant defense (S5D Fig) [2,5]. Consistently, transcript levels of the wounding-associated genes NaOPR2a, NaOPR2b, and JASMONIC ACID RESISTANT 4 (NaJAR4) and auxin-related genes of NaPIN7, NaPIN6, NaPIN1, YUCCA 6 (NaYUC6), and AUXIN RESISTANT 1 (NaAUX1) were up-regulated in max2 samples (S5E Fig). The changes of these genes were consistently observed in the RSJs of d14 and ccd7 plants, but not in those of kai2 plants (S5F Fig). To summarize, SL-RNAi plants are more susceptible to T. mucorea attack and display amplified JAs and IAA responses in both transcriptional and metabolic layers, regardless of herbivore attack. Given the commonly held knowledge that plant defenses are positively regulated by JA signaling, this apparent disconnect was particularly intriguing.

Untargeted metabolic profiling revealed changes in specific sectors of specialized metabolism in the RSJs of max2 plants

The apparent disconnect between the observed higher JA/JA-Ile levels and the greater susceptibility to herbivore attack in max2, d14, and ccd7 plants led to the prediction that particular sectors of defense metabolism in SL-RNAi plants were not primarily regulated by JA signaling. To better understand the underlying metabolic basis of resistance to T. mucorea attack, two batches of RSJ samples from EV, max2#1, max2#2, and aoc plants (41 in total) were analyzed by untargeted metabolome profiling using liquid chromatography (LC) coupled to quadrupole time-of-flight mass spectrometry (qTOF-MS). This analysis resulted in a concatenated data matrix consisting of 5,975 mass features (m/z signals detected at particular retention times). A supervised principal components analysis using partial least squares discriminant analysis (PLS-DA) clearly separated the max2 samples, which nicely grouped together (Fig 4A). For each batch, Student t tests with Benjamin–Hochberg corrections among comparisons with EV samples were performed. This analysis identified 226 up-regulated and 309 down-regulated mass features, which were further used for coexpression analyses with the following significance requirements: |log2FC| > 0.58, FDR < 0.05 (Fig 4B, S1 Table).

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Fig 4. Untargeted metabolic profiling reveals the JA regulation of specific sectors of specialized metabolism in the RSJ of max2 plants with JA-deficient aoc plants as reference.

(A) PLS-DA of metabolomes of EV, aoc, and max2 plants in two independent experiments (batch 1 and 2). (B) Number of up-regulated and down-regulated features in total after statistical filtering. (C) TOM plot for visualizing coexpression outcome by WGCNA. (D and E) Extracted subnetworks visualized by Cytoscape (left panels) and correlations with JA contents with each subnetwork were calculated as PCC and their P values. Bar charts display the representative compounds from each subnetwork across all samples from two batches (dark gray: first batch; purple: second batch). Values for graphs (D) and (E) are listed in S1 Table. aoc, allene oxide cyclase; CP, N′-caffeoylputrescine; DCS, N′, N″-decaffeospermidine; EV, empty vector; JA, jasmonate; JDC, JA-dependent cluster; JIC, JA-independent cluster; max2, more axillary growth 2; PCC, Pearson’s correlation coefficient; PLS-DA, partial least squares discriminant analysis; RSJ, root–shoot junction; TOM, topological overlap matrix; WGCNA, weighted correlation network analysis.

https://doi.org/10.1371/journal.pbio.3000830.g004

A well-developed coexpression pipeline, the weighted correlation network analysis (WGCNA) [46], was employed, and six modules were obtained (power = 10) (Fig 4C). Samples of the RSJs of aoc plants were used to identify JA/JA-Ile–independent/–dependent subnetworks. Based on this, coexpression networks were constructed (topological overlap matrix [TOM] > 0.3) (Fig 4D and 4E and S6 Fig), and JA-independent clusters (JICs)/JA-dependent clusters (JDCs) were defined depending on whether subnetworks were significantly correlated with the JA/JA-Ile contents of the samples. As indicated in S6 Fig, O-acyl sugars were nicely clustered in the blue module and tightly associated with a similar enrichment pattern across all groups, revealing the robustness of network construction. However, in this large subnetwork, variable expression patterns correlated with JA/JA-Ile contents. In the cluster JIC#1, all features decreased consistently in max2 and aoc groups regardless of JA/JA-Ile contents (P = 0.156) (Fig 4D). Interestingly, in JIC#1 cluster annotated as alkaloids, we found the levels of nicotine to be significantly decreased in max2 and aoc samples (Fig 4D). On the other hand, we found compounds with significant negative correlations with JA/JA-Ile contents in unknown clusters JDC#1 (PCC = −0.41, P = 0.021) (S6B Fig) and JDC#2 (PCC = −0.76, P < 0.0001) (S6C Fig) and compounds with positive correlations with JA/JA-Ile contents in JDC#3 (PCC = 0.70, P < 0.0001) (Fig 4E), which were mainly populated by known phenolamide structures. After these analyses, the associated features in the largest subnetwork from JIC#1 and JDC#3 were captured for further analysis.

Increased phenolamide accumulations in SL-RNAi RSJ are positively related to JA signaling

Levels of phenolamides located in cluster JDC#3 were increased in the RSJs of max2 plants, which is consistent with the presence of significant GO enrichment in phenylpropanoid biosynthetic genes (S5D Fig). Importantly, the signature compounds of phenolamides, N′-caffeoylputrescine (CP) and N′, N″-decaffeospermidine (DCS), were also increased in ccd7 and d14 plants, but not in kai2 plants (Fig 5A). Because phenolamides are known to play essential roles in defense against leaf feeding lepidopteran herbivores [12,13,47], we performed a T. mucorea larval performance assay with a transgenic line silenced in MYB DOMAIN PROTEIN 8 (MYB8) expression, a key transcriptional factor regulating phenolamide biosynthesis in N. attenuata [13], to clarify whether increased CP and DCS in pith of SL-RNAi plants contribute to altered resistance against the stem-boring weevil. However, even though the levels of CP and DCS were much lower in the RSJs of myb8 plants (Fig 5B), larval performance in mby8 plants was similar to that in EV plants (Fig 5C). These results indicate that phenolamides do not function as defenses against T. mucorea larvae.

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Fig 5. Increased phenolamide accumulations in SL-RNAi RSJ are positively related to JA signaling via MYB8.

(A) Relative contents of phenolamides such as CP and DCS in the RSJs of indicated plants (±SE, n = 6). (B) Relative contents of CP and DCS in RSJs of EV and myb8 plants after attack. (C) Biomass of T. m. larvae after attacking EV and myb8 plants for 2 weeks (n = 15). (D) Relative transcript abundance of MYB8 and DH29 in RSJ of EV and aoc plants (±SE, n = 4). (E) Relative contents of CP and DCS in the pith of EV and aoc plants without (Control) or with T. m. attack for 2 weeks. (F) Relative transcript abundance of MYB8 and DH29 in the RSJs of indicated plants (±SE, n = 4). (G) Relative content of CP and DCS in the pith of EV and max2#2 plants without (Control) or with T. m. attack for 2 weeks (±SE, n = 6–10) (*P < 0.05; **P < 0.01; ***P < 0.001; two-tailed Student t test). Values for graphs (A–G) are listed in S1 Data. aoc, allene oxide cyclase; ccd, carotenoid cleavage dioxygenase; CP, N′-caffeoylputrescine; d14, dwarf14; DCS, N′, N″-decaffeospermidine; DH29, ACYLTRANSFERASE DH29; EV, empty vector; JA, jasmonate; kai2, karrikin insensitive 2; max2, more axillary growth 2; n.s., not significant; RNAi, RNA interference; RSJ, root–shoot junction; SL, strigolactone; T. m., T. mucorea.

https://doi.org/10.1371/journal.pbio.3000830.g005

Consistent with previous findings in leaves [47], transcript abundances of key genes in phenolamide biosynthesis, including MYB8 and acyltransferase DH29 (DH29), were dramatically lower in the pith of aoc plants (Fig 5D); and the increases in CP and DCS levels after T. mucorea attack were completely lacking in aoc plants (Fig 5E), suggesting that the decreased JA/JA-Ile levels lower the production of phenolamides by down-regulating the expression of MYB8 and DH29 genes. In SL-insensitive and SL-deficient max2, d14, and ccd7 lines, the transcript abundances of MYB8 and DH29 were up-regulated in the pith (Fig 5F). CP and DCS levels were also higher in the pith of max2 plants compared with those of EV plants after T. mucorea attack (Fig 5G). Taken together, the elevated JA levels may account for the increases in phenolamides via the up-regulation MYB8 and DH29 in SL-RNAi lines; this inference allowed us to disentangle the potential cross talk among SL and JA signaling pathways through the crossing of different RNAi lines that targeted key genes in these signaling pathways.

Phenolamide and anthocyanin accumulations are regulated by SL signaling via JA signaling

As shown in Figs. 2 and 5, anthocyanin, phenolamides, and JAs all overaccumulate in the stems of SL-RNAi plants, whereas in aoc plants, extremely low JA levels are associated with low anthocyanin and phenolamide levels (Fig 3B, Fig 5E). To further examine this interplay of JA-SL signaling, a set of genetic hybridizations were designed. d14 and max2 plants with their high JA levels were crossed with the JA-deficient aoc plant. We quantified anthocyanin and phenolamide levels in all crosses. The anthocyanin levels in the stems of EV×d14 and EV×max2 plants were significantly higher than those in aoc×d14 and aoc×max2 plants, a result consistent with the higher JA levels in both EV×d14 and EV×max2 plants (Fig 6A and 6B) and clearly demonstrating that JA signaling functions downstream of SLs to regulate anthocyanin and phenolamide accumulations. Notably, although the increases in anthocyanin levels in d14 and max2 stems were attenuated in crosses with aoc plants, the levels of anthocyanins in aoc×d14 and aoc×max2 stems were still significantly higher than those in EV×aoc stems (Fig 6A and 6B), suggesting that another additional factor regulates anthocyanin accumulations. As auxin is known to regulate anthocyanin levels in N. attenuata [5] and occurs in higher concentrations in the stems of SL-RNAi plants, we inferred that auxin would positively contribute to the anthocyanin accumulations in SL-RNAi stems. In contrast to the results that both JA and IAA likely regulate anthocyanin accumulation, SL regulates phenolamide production primarily through JA signaling, as the phenolamide contents were almost undetectable in EV×aoc, aoc×d14, and aoc×max2 piths, whereas the levels of phenolamides were dramatically increased in EV×d14 and EV×max2 piths after T. mucorea attack (Fig 6C). Taken together, by crossing SL- and JA-RNAi plants, we dissected the functional consequences of accumulated JA levels in SL-insensitive plants to reveal that the concentrations of anthocyanin and phenolamides in stems of SL-insensitive plants increase in a JA-dependent manner. This insight motivated a deeper exploration of the molecular mechanism involved in this cross talk.

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Fig 6. Phenolamide and anthocyanin accumulations are regulated by SL signaling via JA signaling.

(A) Representative pictures of stems of EV, EV×d14#1, aoc×d14#1, EV×max2#2, and aoc×max2#2 plants. (B) Relative anthocyanin levels in epidermis of stems of indicated plants (n = 8). (C) Relative contents of CP and DCS in stem pith of indicated plants after 2 weeks of T. mucorea attack (n = 8) (two-tailed Student t test). Values for graphs (B) and (C) are listed in S1 Data. aoc, allene oxide cyclase; CP, N′-caffeoylputrescine; d14, dwarf 14; DCS, N′, N″-decaffeospermidine; EV, empty vector; max2, more axillary growth 2; JA, jasmonate; SL, strigolactone.

https://doi.org/10.1371/journal.pbio.3000830.g006

Interplay of SL and JA signaling through SMXL6/7-JAZ interactions

Based on the crossing results, we inferred that SL tunes the responses of the JA signaling pathway through an unknown mechanism to regulate anthocyanin and phenolamide production through COI1/JAZ and transcriptional factors such as MYB8 (Fig 7A). Given that the direct interaction of JAZs with DELLA proteins contributes to the cross talk between JA and GA signaling [48], we hypothesized that physical interactions among the suppressors of SL and JA signaling could account for the interplay between SL and JA signaling (Fig 7A). After BLAST N. attenuata genome searches with published sequences of suppressors of MAX2, SMXL6/7/8 from Arabidopsis, two orthologues (NaSMXL6 and NaSMXL7) were identified (Fig 7B and S7A Fig). NaSMXLs were localized to the nucleus and found to directly interact with NaD14 in the presence of the synthetic SL analogue rac-GR24 (5 μM) (Fig 7C and 7D, S7B and S7C Fig).

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Fig 7. Interplay of SL and JA signaling through SMXL6/7-JAZ interactions.

(A) Schematic diagram of amplified JA signaling resulting from silenced SL signaling that leads to accumulations of anthocyanins and phenolamides. (B) Phylogenetic analysis of NaSMXL gene family from N. attenuata. (C) Interactions between NaSMXL6/7 and NaD14 proteins in the presence of rac-GR24 by Y2H assays. GAL4 DNA-BD-D14 and AD-SMXL6/7 were cotransformed into yeast. The transformants were grown on QDO (SD−Ade/−His/−Leu/−Trp). (D) The interactions of NaSMXL6 /7 and NaD14 in the presence of 20 μM rac-GR24 by pull-down assays. NaSMXL6/7-YFP was transiently expressed in N. benthamiana leaves. Purified GST-D14 was used. Input of GST-D14 is shown at the second panel. (E) Interaction between NaSMXL6/7 and NaJAZs proteins by Y2H assays. GAL4 DNA-BD-SMXL6/7 and AD-JAZs were cotransformed into yeast. The transformants were grown on QDO (SD −Ade/−His/−Leu/−Trp with 40 μg/mL X-α-gal). (F) Relative transcript abundance of SMXL6, SMXL7, and those JAZs that encode JAZ proteins that interact with SMXL in different tissues. Expression levels were analyzed from microarray data. (G) Interactions of SMXL6/7-YFP and MYC-JAZb by in vivo Co-IP. (H) JAZb degradation in EV and max2 (#1, #2) crude proteins. Purified His-JAZb was incubated in EV or max2 crude proteins extracted from stem pith for the indicated times. His-JAZb was detected by anti-His. The CBB staining represented protein loading levels. (I-J) JAZb degradation in EV, d14#1, or kai2#1 crude proteins, with the same condition mentioned in (H). (K) Interference of SMXL6/7 on interaction of JAZb and MYC2a/b by Y3H assay. The expression of SMXL6/7 was gradually induced by the addition of decreasing amounts of Met. The transformants were grown on QDO (SD−Leu/−His/−Trp/−Met with 40 μg/mL X-α-gal). Raw images for blots are listed in S1 Raw Images. AD, activation domain; ANT, anther; BD, binding domain; CBB, Coomassie Brilliant Blue; COI1, coronatine insensitive 1; Co-IP, co-immunoprecipitation; COL, corolla late; d14, dwarf 14; EV, empty vector; FLB, flower bud; GST, glutathione S-transferase; JA, jasmonate; JAR4/6, JASMONIC ACID RESISTANT 4/6; JAZ, JASMONATE ZIM-DOMAIN; kai2, karrikin insensitive 2; LDOX, LEUCOANTHOCYANIDIN DIOXYGENASE; LEA, leaf; LT, Leu and Trp; LTHA, Leu, Trp, His, and Ade; max2, more axillary growth 2; Met, methionine; MYB8, MYB DOMAIN PROTEIN 8; OFL, opening flower; OVA, ovary; PED, pedicel; QDO, quadruple dropout medium; ROT, root; SD, synthetic defined medium; SED, seed; SL, strigolactone; SMXL, suppressor of max2-like; STE, stem; STI, stigma; Y2H, yeast two-hybrid; Y3H, yeast three-hybrid; YFP, yellow fluorescent protein.

https://doi.org/10.1371/journal.pbio.3000830.g007

To test whether the SL repressors, NaSMXLs, interact with the JA repressors, NaJAZs, we conducted yeast two-hybrid (Y2H) assays. The results suggested that both SMXL6 and SMXL7 interacted with JAZa, JAZb, JAZd, JAZj, and JAZl, whereas JAZe only interacted with SMXL7 (Fig 7E). Coexpression analysis was performed using RNA-seq data across different tissues [49] to identify patterns among genes, including SMXLs and the JAZs (a/b/d/j/l/e). The stem-abundant SMXL7 was found to be highly coexpressed with JAZb (Fig 7F), and JAZb was used for further studies. We further confirmed the interaction of SMXL6/7 and JAZb in vivo using coimmunoprecipitation (Co-IP) assays. MYC-JAZb physically interacted with SMXL6/7-YFP when transiently expressed in N. benthamiana leaves (Fig 7G).

In max2 plants, SMXL6 protein was found to accumulate to higher levels than in EV plants, as determined by immunoblots with anti-SMXL6 (S7D Fig). According to the degradation mechanisms elucidated in Arabidopsis and rice [26,50], a greater accumulation of SMXL7 was predicted; however, because of a lack of antibody against SMXL7, this was not determined. To determine whether larger accumulations of SMXL6/7 proteins in max2 plants influence JAZb degradation, we performed an in vitro degradation assay by adding recombinant His-JAZb to crude protein extracted from the pith of EV or max2 plants and quantified the degradation of JAZb after incubation for the indicated time points. His-JAZb degraded more rapidly in max2 crude protein relative to that in EV (Fig 7H). As reported in rice, more D53 protein was found to accumulate in both d14 and max2 plants [50]; hence, we performed degradation assays with d14 crude protein. As expected, JAZb was degraded more rapidly in d14 crude protein extracts (Fig 7I). Because of the close phylogenetic relationships between D14 and KAI2, kai2 lines were also included in the tests of the stability of the His-JAZb complex. The pattern of His-JAZb degradation in kai2 crude protein extracts was found to be similar to its degradation in EV crude protein extracts (Fig 7J). In contrast to the more rapid degradation of JAZb when interacting with SMXL6/7, His-JAZk, one of the JAZs not interacting with SMXL6/7 in the Y2H assays, degraded at a similar rate in EV and max2 crude protein extracts (S7E Fig).

Additional Y3H assays were performed to explore the effect of SMXL6/7 on the interaction of JAZb and MYC2a/b. With decreasing methionine (Met) concentrations in the media, the abundance of SMXL6 or SMXL7 was experimentally increased, and the binding capacity of JAZb-MYC2 was gradually weakened until completely abolished, when no Met was added to the media (Fig 7K and S7F Fig). This result indicates that overaccumulated SMXL6/7 dampens the binding between MYC2 and JAZb.

In summary, the enhanced SMXL6/7 protein in SL-RNAi plants physically interacts with JAZs to trigger the degradation of JAZ protein; excessive SMXL6/7 protein production interferes with the interactions of JAZs and MYC2, which both facilitate the release of MYC2 to activate the downstream JA signaling cascade, which results in enhanced anthocyanin and phenolamide accumulations in SL-RNAi plants.

Decreased nicotine mediated by increased auxin accounts for the susceptibility of SL-RNAi plants to T. mucorea attack

Even though the enhanced phenolamides do not account for the susceptibility of SL-RNAi plants to T. mucorea attack (Fig 5B and 5C), we noticed that another essential defense compound in the JIC#1 module, nicotine, was decreased in the RSJs of max2 samples from the untargeted metabolome analysis Fig 4D. Nicotine levels were consistently lower in the pith of max2 plants compared with those of EV plants regardless of T. mucorea infestation (S8A Fig); they were also significantly lower in the roots of max2 plants after attack (S8B Fig). JA and IAA levels were higher in the roots of max2 plants (S8C Fig), consistent with their levels in pith (Fig 2C). Further analysis revealed that nicotine levels were significantly decreased in the RSJs of max2, d14, and ccd7 plants, but not in those of kai2 plants (Fig 8A). To evaluate whether nicotine, which is synthesized in roots, is essential for plant defense against T. mucorea larvae, we performed feeding assays using a nicotine-deficient transgenic line, putrescine n‐methyltransferase (pmt) plants (Fig 8B) [51]. T. mucorea larvae inoculated into pmt plants gained higher biomass compared with those that fed on EV plants (Fig 8C). It is known that JA signaling stimulates nicotine biosynthesis and accumulation [8,52]; however, in the RSJs of SL-RNAi plants, low nicotine levels coincide with high JA/JA-Ile levels (Fig 8D). Auxin signaling is known to suppress nicotine levels [52,53], which suggests that the high IAA contents cause the low nicotine levels in SL-RNAi plants (Fig 8E).

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Fig 8. Decreased nicotine mediated by increased auxin accounts for the susceptibility of SL-RNAi plants to T. mucorea attack.

(A) Relative contents of nicotine in the RSJs of indicated plants (±SE, n = 6). (B) Relative levels of nicotine in the pith of EV and pmt plants (n = 6). (C) Representative pictures and biomass of T. mucorea larvae after attacking EV and pmt plants for 2 weeks (n = 15). Scale bar, 2 mm. (D) Relationship of JA and nicotine levels in RSJ of aoc, EV, and SL-RNAi (max2, d14, and ccd7) plants. Data collected from same samples are indicated by gray lines. (E) Relationship of IAA and nicotine levels in RSJ of EV and SL-RNAi (max2, d14, and ccd7) plants. Data collected from the same sample are connected with a gray line. (F) Schematic diagram of nicotine biosynthesis regulated by auxin and JA-Ile. (G) Levels of JA-Ile, JA, and IAA in roots of EV plants without (Control) or with decapitation treatment for 3 days (n = 6–8). Nicotine content in the RSJs of EV plants with or without decapitation treatments for 3 days (n = 5–6). Biomass of larvae that had attacked intact or decapitated EV plants for 2 weeks (n = 12). (H) Levels of JA-Ile, JA, and IAA in roots of EV plants without (Control) or with treatments with the IAA transport inhibitor CFM for 3 days (n = 6). Nicotine levels in RSJ of EV without or with CFM treatment for 3 days (n = 6). Pith-preference bioassay with T. mucorea larvae between EV stem halves EV (Control)-EV (Control), EV (Control)-EV (CFM treatment) (±SE, 3 replicates, each replicate includes 8–10 plants). (I) Relative transcript abundance of nicotine biosynthetic genes BBL and A622 in EV and aoc seedlings without (Mock) or with 10 μM IAA treatment for 8 hours (±SE, n = 4). (J) Nicotine contents in RSJ of aoc plants without (Control) or with decapitation treatment (n = 6). Biomass of larvae that had attacked aoc control plants or decapitated plants for 2 weeks (n = 12) (two-tailed Student t test). Values for graphs (A–E and G–J) are listed in S1 Data. A622, ISOFLAVONE REDUCTASE-LIKE PROTEIN; aoc, allene oxide cyclase; BBL, BERBERINE BRIDGE ENZYME-LIKE; ccd, carotenoid cleavage dioxygenase; CFM, methyl-2-chloro-9-hydroxyfluorene-9-carboxylate; COI1, CORONATINE INSENSITIVE 1; d14, dwarf14; EV, empty vector; IAA, indole-3-acetic acid; JA, jasmonate; JA-Ile, jasmonic acid-isoleucine; JAR, JASMONIC ACID RESISTANT; kai2, karrikin insensitive 2; max2, more axillary growth 2; n.s., not significant; OPR, OPDA reductase; pmt, putrescine n-methyltransferase; RNAi, RNA interference; RSJ, root–shoot junction; SL, strigolactone.

https://doi.org/10.1371/journal.pbio.3000830.g008

To test whether the decreased amount of nicotine in max2 plants resulted from increased IAA levels, we manipulated auxin levels by decapitation or using the auxin transport inhibitor methyl-2-chloro-9-hydroxyfluorene-9-carboxylate (CFM) (Fig 8F). Three days after decapitating EV plants, there were no significant changes in JA and JA-Ile levels, whereas IAA decreased about 2-fold (Fig 8G). The amount of nicotine significantly increased in the RSJs in decapitated EV plants (Fig 8G). Moreover, T. mucorea larvae performed worse in decapitated EV plants compared with those in intact plants (Fig 8G). Next, after using CFM to block IAA transport from shoot to root, IAA levels decreased in EV plants without altering JA or JA-Ile levels (Fig 8H). The amount of nicotine in the RSJs of EV plants after CFM treatment was higher than in control plants (Fig 8H). In pith-preference assays, more than 70% of the larvae preferred to feed on pith from plants subjected to the CFM treatment than from control pith (Fig 8H). To further evaluate whether auxin regulates nicotine levels independently of JA signaling, we treated aoc seedlings with IAA for 8 hours. Transcript levels of the nicotine biosynthetic genes BBL and A622 decreased to similar degrees (approximately 30%) in both EV and aoc seedlings (Fig 8I). Furthermore, aoc plants still accumulated more nicotine in their RSJs after decapitation, again leading to a lower larval biomass gain (Fig 8J).

To better understand the role of the increased auxin levels in max2 plants in T. mucorea resistance, we studied the nicotine biosynthesis response of max2 plants to auxin. Transcripts of BBL and A622 were lower in max2#2 than in EV seedlings (S8D Fig), suggesting that the biosynthesis of nicotine in max2 plants was decreased. After auxin treatment, the expression of BBL and A622 was still decreased in max2 plants, as in EV plants (S8D Fig). Upon decapitation, the amount of nicotine was enhanced in the RSJs of max2#2 plants, resulting in significantly lower larval performance compared with undecapitated plants (S8E Fig). These results demonstrate that max2’s nicotine biosynthesis machinery still responds to changes in auxin levels.

In summary, these results reveal that the inhibitory effect of auxin on nicotine accumulation is at least partially independent of JA signaling, and it is the change in nicotine levels associated with SL silencing that most profoundly determine larval performance.

SL signaling balances the metabolic output of specialized sectors via its interaction with JA and auxin

We returned to the JDC and JIC metabolite modules to understand the ternary regulatory relationship dissected by the d14, aoc, and d14×aoc lines. As previously mentioned, the pith of d14 displayed increased auxin and JA levels, aoc pith had lower JA but normal auxin levels, and d14×aoc pith exhibited higher auxin but lower JA levels. As indicated in Fig 4E, JDC#3 (phenolamide sector) was dominantly correlated with JA levels, and anthocyanin production was also mainly correlated with JA levels, although IAA was also involved in this regulation (Fig 9A). The JIC#1 module (alkaloid sector) included nicotine and clustered with aoc largely because of the inhibition effect of higher auxin levels from the d14 background. The JDC#1 and JDC#2 modules negatively correlated with JA levels (S6B and S6C Fig) and clustered distinctly because of the larger repression effect of higher JA levels in d14 plants (Fig 9A). This analysis clearly illustrated that the metabolic profiles of the pith reflect the balance amongst several regulators, and this balance is tuned by additional factors such as SL signaling.

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Fig 9. SL signaling regulates anthocyanin accumulations and plant defense against T. mucorea larval attack via its interaction with JA and auxin signaling.

(A) A ternary analysis illustrating metabolite distributions across three genotypes: aoc, d14, and aoc×d14 plants. For JIC#1 and JDC#1–3, see Fig 4 and S6 Fig. (B) A model of the role of SLs as regulators that fine-tune resistance to endophytic stem-feeding weevils by disrupting the SL-mediated homeostasis between auxin and JA signaling. In N. attenuata, SL-deficient (d14, max2, and ccd7) plants produce more branches (right panel) relative to EV (left panel), have lower pith nicotine levels and higher anthocyanin and phenolamine levels, and are more susceptible to T. mucorea attack. In EV plants, SL levels maintain auxin and JA homeostasis, but once SL signaling is impaired, auxin and JA levels increase and become unbalanced, decreasing pith nicotine levels and increasing susceptibility to larval attack. Values for the graph (A) are listed in S1 Data. aoc, allene oxide cyclase; CP, N′-caffeoylputrescine; d14, dwarf14; DCS, N′, N″-decaffeospermidine; EV, empty vector; JA, jasmonate; IAA, indole-3-acetic acid; JDC, JA-dependent cluster; JIC, JA-independent cluster; max2, more axillary growth 2; SL, strigolactone.

https://doi.org/10.1371/journal.pbio.3000830.g009

As summarized in the proposed model (Fig 9B), the RSJs of SL-RNAi plants accumulate SL repressors SMXL6 and SMXL7, which directly interact with JAZs, accelerating JAZ degradation, releasing the inhibition of MYC2 from JAZ to amplify JA signaling, and increasing the production of phenolamides and anthocyanin through MYB8-mediated regulation. Meanwhile, auxin may contribute to the anthocyanin production as well [5]. However, these increases in defense responses do not attenuate the growth of the stem-boring larvae. Even though SL-RNAi lines (max2/d14/ccd7) exhibited enhanced JA responses, which positively regulated nicotine biosynthesis, the simultaneous increases in IAA levels completely neutralized JA’s effects to decrease nicotine levels in the pith, which accounted for the greater larval performance.

Plant material and growing conditions

In all experiments, WT N. attenuata Torr. Ex Watts seeds of the 31st generation inbred line were used. Seed germination and plant growth were performed as described [81]. NaMAX2/D14/KAI2-silenced lines were produced by the published Agrobacterium tumefaciens–mediated transformation method [81] using pRESC8 binary vector containing the inverted repeat (ir) fragment of the NaMAX2 (NIATv7_g10118, NIATv7_g01142) sequences, NaD14 (NIATv7_g26688, NIATv7_g08776) sequences, or KAI2 (NIATv7_g33099, NIATv7_g21279) sequences. CCD7-silenced lines were constructed by using pSOL8 vector with NaCCD7 (NIATv7_g01914) sequences. T₂ plants were used in all experiments. The number of insertion copies as well as the fidelity of the insertion (over-reads and truncations) were evaluated by NanoString [42]. In brief, DNA extracted from individual transgenic plants was used for NanoString to detect the content of inserted fragments according to the designed probes. To validate the single-copy-number insertions inferred from the segregation rates, a published single-copy insertion stably transformed line, ago8 (871-8-8), was used as a positive control [82]. The following three previously characterized transgenic lines were also used in this study: myb8 (A-07-810-2) plants silenced in the expression of MYB8 gene [47]; pmt (A-03-108-3) plants silenced in the expression of putrescine N-methyltransferase, a key nicotine biosynthetic enzyme [51]; and aoc (A-07-457-1) plants silenced in the expression of AOC, a single-copy key biosynthetic enzyme in JA biosynthesis [45].

All experiments were performed in the glasshouse. N. attenuata plants were grown with a day/night cycle of 16 hours (26–28°C)/8 hours (22–24°C). For decapitation experiments and CFM treatments, plants with eight leaf nodes on the stem were used. The top two nodes with unexpanded small leaves were removed in the decapitation experiment, and eggs of T. mucorea were inoculated on the same day. Plants treated with CFM (1 μg/mL) on the second node (from bottom to above) for 3 days were used in pith-preference assays.

Anthocyanin measurement

The epidermis of stems of 75-day-old plants (Fig 2) and 90-day-old plants (Fig 6) was removed, and anthocyanin levels were measured by Dualex (FORCE-A).

T. mucorea performance and pith-preference assays

T. mucorea eggs were inoculated into N. attenuata plants as described [11]. In brief, freshly collected eggs were inoculated into the petiole of a healthy rosette leaf located at the basal stem (RSJ) of a plant in the early elongation stage of growth. After the indicated inoculation period (approximately 1–3 weeks), egg-inoculated stems were split to harvest plant material or collect larvae for weighing or pith-preference assays, as previously described [41]. Approximately 5 cm of pith section above the area attacked by T. mucorea larvae and control samples consisting of a 5-cm pith section just above the RSJ were harvested for analysis and immediately frozen in the liquid nitrogen.

For pith-preference bioassays, the stems of the different genotypes were split lengthwise and paired with size-matched halves of stems from EV plants in the same stage of growth. Larvae harvested from 2-week-inoculated max2 plants were individually placed into an approximately 1-mm³ hole excavated in the pith of the RSJ on both halves of the stem “sandwich.” The two halves were wrapped with M3 tape to hold the two halves together. Stems were kept hydrated and held in a vertical position by covering them with wet tissues. After 36 hours, the tape wrapping was removed, and both stem halves were inspected for feeding damage. The volume of the consumed pith area was scored as a criterion for the feeding choice of larvae.

Total RNA extraction and transcript abundance analysis

For transcript abundance analysis, RNA was extracted from the indicated tissues using the RNAeasy Plant Mini Kit (Qiagen) or NucleoSpin RNA Plant (Macherey-Nagel) according to the manufacturer’s instructions. Isolated RNA was used for microarray or reverse transcription. cDNA was prepared by using the PrimeScript RT-qPCR Kit (TaKaRa). For microarray analysis, extracted RNA was labeled and hybridized according to the protocol of the Quick Amp labeling kit (Agilent, http://www.agilent.com/home). Agilent single-color technology arrays (60 k) were used for the hybridizations. Raw intensity data were normalized with the quantile method, and subsequently, the low expression probes were discarded after log2 transformation. Differentially expressed probes were filtered after pairwise comparisons (|log2FC| ≥ 1, FDR ≤ 0.05).

RT-qPCR was performed on a Stratagene Mx3005P qPCR machine using a SYBR Green containing reaction mix (Eurogentec, qPCR Core kit for SYBR Green I No ROX). For all qPCR analysis, N. attenuata IF-5A housekeeping gene was used as internal reference. Primer sequences were listed in the S2 Table.

Primary and secondary metabolites extractions and analysis

For primary and secondary metabolites extraction, ground plant material was aliquoted into Eppendorf tubes, and their masses were recorded for normalization. Per 100 mg of plant tissues, 800 μL of extraction buffer (0.2 N formic acid in 80% MeOH with internal standards) was pipetted into the samples before being shaken in a GenoGrinder 2000 (SPEX SamplePrep) for 60 seconds at 1,150 strokes. After two centrifugations, the supernatant was collected, and 100 μL was aliquoted for secondary metabolites analysis. The remaining supernatant was used for further hormonal extraction and analyzed following the procedures described by Schäfer and colleagues [83].

For root exudate collections and SL measurements, 20-day-old N. attenuata plants were transferred individually to 1-L pots containing hydroponic solution. After 20 days, the hydroponic solutions were replaced by solutions depleted in inorganic Pi for a week for max2 and d14 plants and 10 days for ccd7 plants. Then 200 mL of hydroponic solution was collected and acidified by adding 200 μL of formic acid. The collected volume of hydroponic solution was passed through an HR-X column (Macherey-Nagel). The column was subsequently washed with 2 mL of water and finally eluted with 2 mL of 100% MeOH. Before chromatographic measurement, the dehydrated precipitate was resuspended with 200 μL of 80% MeOH.

For chromatographic separations, UHPLC (Dionex UltiMate 3000) equipped with a reverse phase column (Agilent ZORBAX Eclipse XDB C18, 50 × 3.0 mm, 1.8 μm) as the stationary phase was used. Mass spectrum (MS) detection for primary metabolites analysis was performed on a Bruker Elite EvoQ triple-quadrupole MS equipped with a heated electrospray ionization (HESI) ion source; MS detection for secondary metabolites analysis was performed on a microTOF-Q II MS system (Bruker Daltonics) equipped with an electrospray ionization (ESI) source operating in positive ion mode. Additionally, for nicotine quantification, samples were measured by microTOF-Q II MS described previously [46]. For 2′-epi-orobanchol quantification, purchased standards including strigol, orobanchol, and 2′-epi-orobanchol from OlChemIn (www.olchemin.cz) together with concentrated root exudates were analyzed by microTOF-Q II MS, and the retention times of extracted ion chromatograms (m/z 347.15 ± 0.05) were compared. For the fragmentation of the proposed daughter ions via pseudo-MS³, we applied a 20-eV in-source-CID transfer energy, which produced spectra reflecting the loss of the butenolide moieties.

Metabolome analysis

Raw data collected from the LC-MS instrument were preprocessed with R packages “XCMS” and “CAMERA” without fillPeak function. A missing value (MV) filtering rule was applied across individual samples or single peaks (cutoff: 0.5, 0.5), and 5,649 mass features were retained. An MV imputation with a minimum value across samples for each feature was implemented, after which a 75% percentile normalization and log2 transformation scaling was followed. “NA” were MVs, which were filtered by applying the following rules: if the proportion of MV was greater than 50% in each row (features) or column (samples), such features or samples were removed from the analysis, and 5,649 mass features were retained. Remaining “NA" MVs were replaced with the minimum value of each row. A 75% percentile normalization process was conducted, and log2 transformation was followed for the WGCNA pipeline. PLS-DA methods were applied for PCA analysis to classify batch and genotype effects. Prior to WGCNA processing, statistical filtering was performed according to comparisons of any group relative to EV as a reference group in the same batch. Significant differences were defined as (|log2FC| > 0.58, FDR < 0.05). Eventually, 535 features were used for the WGCNA pipeline (S1 Table), which used the following parameters: signed as TOMType = “unsigned”, power = 10, minModuleSize = 30, and corType = “bicor” and then output TOM > 0.3 nodes and edges as Cytoscape network visualization input. Correlations were computed between pith JA contents and extracted subnetworks, respectively; means of Pearson’s correlation coefficients and P values are reported. For ternary analysis, medians of features from each genotype were extracted and scaled as input variables, and the R packages “VCD” and “ggtern” were used for plotting.

Phylogeny analysis

Protein sequences of indicated genes were downloaded from NCBI or SGN (https://solgenomics.net) and N. attenuata Data Hub (http://nadh.ice.mpg.de/NaDH/others/genes). MEGA5 was used for phylogenic analysis; in brief, after alignment by using MUSCLE algorithm, a maximum likelihood tree was generated with default parameters (JTT algorithms).

Cloning

For transient expression experiments, SMXL6 and SMXL7 were cloned into pBA-YFP; MAX2a and MAX2b were cloned into p1302SNB to generate C-terminal YFP and eGFP fused genes. JAZb was cloned into pEarleyGate 203 to generate N-terminal myc fused gene. Constructs were transformed into A. tumefaciens GV3101. For Y2H assay, SMXL6, SMXL7, and D14 were cloned into pGBKT7 to generate BD fused constructs; each JAZ was cloned into pGADT7 to generate AD fused genes. MAX2a and MAX2b genes were cloned into pGADT7, respectively, to generate AD fused genes via NdeI/SmalI digest; ASK1 (NIATv7_g32726) was then cloned into AD-MAX2a and AD-MAX2b vectors to generate AD-ASK1-MAX2a and AD-NSK1-MAX2b vectors via NdeI digest. For prokaryotic expression, JAZb, JAZk, and D14 were cloned into pDEST–N112–MBP and pDEST15 to generate HIS–MBP and GST fused gene, respectively. Constructs were transformed into Escherichia coli BL21 (DE3).

Subcellular localization

Agrobacterium containing 35S: SMXL6-YFP, 35S: SMXL7-YFP, 35S: D14-YFP, 35S: MAX2a-eGFP, 35S: MAX2b-eGFP, or nuclei-localized marker 35S: SV40-CFP construct was infiltrated into N. benthamiana leaves. Three days after incubation, fluorescence was analyzed by confocal microscopy.

Y2H and Y3H assays

Y2H assay was performed by using Matchmaker Gold Yeast Two-Hybrid System (Clontech) under the manufacturer’s instruction. In brief, AD and BD fusions constructed along with their own EVs as control were cotransformed into freshly made Y2H gold competent cells and plated on selective dropout medium (SD-Leu/-Trp). The transformations grew on QDO (SD-Leu/-Ade/-His/-Trp) medium in the presence of X-α-gal (40 μg/mL) and 2 mM 3AT or rac-GR24 (5 μM) if needed at 30°C for 5–7 days after incubation for recording.

In Y3H assays, pBridge-JAZb-Promoter (met)-SMXL6/7 and pGADT7-MYC2a/b were used. The expression of SMXL6/7 was induced by adding decreasing amounts of Met as indicated. Transformed yeast were grown on selective dropout medium (SD-Leu/-Trp) with AbA (70 μg/mL). The transformations grew on QDO (SD-Leu/-His/-Trp/-Met) medium in the presence of X-α-gal (40 μg/mL) and AbA (70 μg/mL) with the addition of different amounts of Met. After incubating at 30°C for 5 days, the growth of yeast was recorded.

Purification of recombinant protein

Single clone of His-MBP-JAZb, His-MBP-JAZk, and D14-GST was respectively cultured in 1 mL Luria–Bertani (LB) at 37°C for 24 hours, and then 10 μL of the culture was transferred to 500 mL LB medium for amplification, and then 0.5 mM isopropyl-β-thiogalactopyranoside (IPTG) was added when OD₆₀₀ reached around 0.4 for an additional 3 hours at 37°C. HIS-tagged protein was purified using Ni-NTA agarose (Qiagen), and GST-tagged protein was purified using Glutathione Sepharose 4B (GE Healthcare) according to the respective manufacturer’s manual.

Pull-down assays

N. benthamiana leaves were infiltrated with Agrobacterium containing either 35S: SMXL6-YFP or 35S: SMXL7-YFP. Leaves were harvested after 72 hours of incubation in climate chambers at 20–22°C. Approximately 3 g of leaf material was extracted in 2.4 mL of extraction buffer (50 mM Tris-Cl [pH 6.7], 100 mM NaCl, 10% [v/v] glycerol, 0.1% [v/v] Tween 20, 20 mM 2-mercapto-ethanol, and 10 μM MG132), and 0.8-mL extracts were added into 25-μL GFP-Trap-A beads (Chromotek) and incubated at 4°C for 1 hour. Supernatant was then removed after short spin, and these steps were repeated several times. A three-times washing step was followed by using pull-down binding buffer (50 mM Tris-Cl [pH 7.0], 150 mM NaCl, 0.5% Tween 20), and then 1 μg of purified D14-GST was added into the reaction system containing protease inhibitor mixture and 10 μM MG132 with/without 20 μM rac-GR24, and incubation was performed at 22°C for an additional hour. After washing five times by using pull-down washing buffer (50 mM Tris-Cl [pH 7.0], 300 mM NaCl, 0.5% Tween 20) and carefully removing supernatant, 100 μL 2× SDS loading buffer was pipetted into it and boiled at 95°C for 5 minutes. Then, 20 μL was used by SDS-PAGE and immunoblotted using anti-GST antibody (Sigma).

Co-IP assay

N. benthamiana leaves were coinfiltrated with Agrobacterium containing genes encoding 35S: MYC-JAZb along with either 35S: SMXL6-YFP or 35S: SMXL7-YFP. Leaves were harvested after 72 hours of incubation at 20–22°C. Approximately 5 g of leaf material was extracted in 4 mL of extraction buffer, and 50-μL GFP-Trap-A beads were added into 1-mL extracts; the incubation and sample preparation process was the same as described in the pull-down assay and immunoblotted using anti-myc antibody (Sigma).

In vitro JAZ degradation assay

Pith material just above RSJ was harvested from adult plants at flowering stage of EV and max2 plants; around 200 mg of plant materials was used for total protein extraction. Crude protein was adjusted to the same concentration (0.5 μg/μL). Recombinant His-MBP-JAZb (5 μg) was added into crude protein from indicated plants and incubated at 22°C for the indicated times. Samples were harvested at each time point for western blot using anti-His antibody.

Accession numbers

Sequence data from this article can be found in the N. attenuata Data Hub under the following accession numbers: JAZa (NIATv7_g42021), JAZb (NIATv7_g23423), JAZc (NIATv7_g08281), JAZd (NIATv7_g10090), JAZe (NIATv7_g17159), JAZf (NIATv7_g25875), JAZg (NIATv7_g36100), JAZh (NIATv7_g26197), JAZi (NIATv7_g29371), JAZj (NIATv7_g27995), JAZk (NIATv7_g32564), JAZl (NIATv7_g38280), JAZm (NIATv7_g34582), SMXL6 (NIATv7_g27847), SMXL7 (NIATv7_g37691), MAX2a (NIATv7_g10118), MAX2b (NIATv7_g01142), D14(NIATv7_g26688), CCD7 (NIATv7_g01914), CCD8 (NIATv7_g12116), BBL (NIATv7_g17187), A622 (NIATv7_g09977), MYB8 (NIATv7_g41919) and DH29 (NIATv7_g06682).