New insights into defense responses against Verticillium dahliae infection revealed by a quantitative proteomic analysis in Arabidopsis thaliana

Keywords: Arabidopsis, camalexin, cyanogenic biosynthesis, exosome, iTRAQ, plant immunity, proteome, Verticillium dahliae.

Verticillium wilt (causal organism Verticillium dahliae) is a highly destructive fungal disease that affects a broad range of major crops, vegetables, and other plants, such as cotton (Gossyium hirsutum L.), potato (Solanum tuberosum L.), tomato (Solanum lycopersicum L.), alfalfa (Medicago sativa L.), sunflower (Helianthus annuus L.), strawberry (Fragaria spp.), rape (Brassica napus L.), lettuce (Lactuca sativa L.), maple (Acer spp.) and smoke-tree (Cotinus coggria Scop.) (Pegg and Brady 2002; Deketelaere et al. 2017). The disease is difficult to control owing to the long-term survival of fungal resting structures in the soil, the lack of resistant germplasms, and environmental pollution caused by the abuse of fungicides. The best strategy for preventing Verticillium wilt is the use of Verticillium-resistant cultivars, which was genetically modified (Gao et al. 2011). To establish a theoretical or practical basis for genetically controlling Verticillium wilt, functional dissection of genes/proteins, and omics-based approaches, including transcriptomic, proteomic, and metabolomic analyses, have been performed over the past decade to identify resistance-related genes/proteins and reveal the defence mechanism (Schenke and Cai 2020; Song et al. 2020). The first resistant gene (Ve1) cloned in tomato, encodes a cell surface receptor protein which was responsible for race-specific resistance against race 1 strains of V. dahliae (Kawchuk et al. 2001). To date, host resistance to V. dahliae has often been recognised as quantitative, and few cultivars with high resistance have been identified (Antanaviciute et al. 2015). To study the resistance mechanisms, Ve1 and its downstream actors (Fradin et al. 2009, 2011), signalling molecules (Gao et al. 2011; Su et al. 2014), transcription factors (Cheng et al. 2016; Qin et al. 2018), oxygen scavengers (Li et al. 2019), defence regulators (Han et al. 2019), anti-fungal proteins (Wang et al. 2016) have been functionally characterised. In addition, omics-based studies were performed to provide more information about the dynamic regulation of cellular processes and the complicated transduction signals involved in Verticillium wilt defence from a global perspective (Iven et al. 2012; Gao et al. 2013; Su et al. 2018; Xiong et al. 2021). Among the omics-based approaches, proteomics analysis is a powerful tool that can be employed to study proteins implicated in various biological processes, which represents the actual contributors for immunity response. In cotton, proteomic studies based on 2D, 2D-DIGE, label-free methods and isobaric tags for relative and absolute quantification (iTRAQ) have been reported since 2011 and the results revealed that various biological processes are involved in plant immunity to V. dahliae, including reduction balance, phenylpropanoid biosynthesis, and hormones (salicylic acid, gibberellic acid, ethylene, brassinolide) signalling (Wang et al. 2011; Gao et al. 2013; Li et al. 2016; Yang et al. 2020). In tomato and hop (Humulus lupulus L.), three proteomic analyses have been conducted based on 2D-DIGE or label-free technologies (Mandelc et al. 2013; Witzel et al. 2017; Hu et al. 2019). To the model plant Arabidopsis thaliana L., there were some research work related to transcriptomic or metabolomic analysis on host immunity against V. dahliae, but the related proteomics studies are seldom reported (Scholz et al. 2018; Su et al. 2018). Previously, a proteomic analysis to dissect autophagy-mediated plant immunity was performed as autophagy directly affects protein abundance as an intracellular degradation pathway (Wang et al. 2018). Nevertheless, a global view of plant immunity responses against V. dahliae based on proteomic approaches was still need to be conducted in Arabidopsis. Importantly, the research could possibly provide new insights compared with other crops due to the small and clear genetic background of this model plant.

In this study, we attempted to determine the immune responses of Arabidopsis toward V. dahliae infection based on proteome changes between mock and infected plants, with special attention to new findings that have not been reported in other studies. The bioinformatics analysis combined with molecular cell biology investigations showed exosome formation, tryptophan-derived camalexin and cyanogenic biosynthesis, various new members involved in hub immunity responses, and ‘Growth-defense tradeoffs’ appeared in plant immunity to V. dahliae. Our research provides new insights into plant defence against V. dahliae infection, thus improving the recognition of host immunity against this important pathogen.

Arabidopsis thaliana L. seeds (Columbia, Col-0) were obtained from the Arabidopsis Biological Resource Centre at Ohio State University. The seeds were surface sterilised, germinated on agar plates, and vernalised at 4°C for 3 days. Seedlings were then grown in an illuminated growth chamber under 16 h/8 h light/dark (after vernalisation for 1 week) or 8 h/16 h light/dark conditions (in vermiculite for resistance analysis) at 22°C. Verticillium dahliae isolate V592 was used as the inoculum, and conidia were produced by growing the fungus on Czapek medium at 26°C for 4 days. A conidial suspension (1 × 10⁶ conidia/mL) in distilled and deionised water (DDW) was prepared for inoculation. For qRT-PCR experiment, 2 mL of DDW or conidial suspension was inoculated onto the roots of 2-week-old plants on vertical plates for 15 min and then cultivated until sampling. For transmission electron microscopy (TEM) analysis, 5-day-old wild-type (WT) seedlings were dip-inoculated with DDW or conidial suspension for 5 min and then placed on vertical plates before sampling. For tolerance evaluation, 1-week-old seedlings were grown in vermiculite under 8 h/16 h light/dark conditions for 3 weeks, then the plants were uprooted from vermiculite and the roots were dip-inoculated in either the DDW (mock treatment) or conidial suspension for 5 min, replanted and grew other 3-weeks before disease survey.

The DAPs used in this study were sourced from a previous iTRAQ experiment, plant growth conditions, V. dahliae inoculum preparation and inoculation, protein extraction, digestion, the iTRAQ-8plex labelling, LC-MS/MS database search, and the quantitative proteome analysis methods have been described previously (Wang et al. 2018). Briefly, mock or V592 inoculated-roots on vertical plates were sampled at 24, 48, and 72 h post-inoculation (hpi). After protein extraction in PBS buffer following methanol–chloroform precipitation, the samples were then reduced, alkylated, trypsin-digested, and labelled with the iTRAQ Reagents 8-plex kit (AB Sciex, Framingham, MA, USA, 4390812). The mixed iTRAQ-labelled peptides were fractionated by strong-cation exchange (SCX) chromatography on an Ekspert TM ultraLC 100 system (AB Sciex). Then, the samples were separated on a Thermo Scientific EASY-Spray PepMap C18 column with a Thermo Scientific EASY-nLC 1000 HPLC system (San Jose, CA, USA) and analysed using a high-resolution Orbitrap Fusion mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). After database search using MASCOT Distiller ver. 2.5.1., Scaffold (Scaffold 4.4.5) was used to validate and quantify the MS/MS-based peptide and protein identifications. In this study, DAPs at 24, 48, and 72 hpi with a log₂-fold change ≥0.38 or ≤−0.38 compared with the control in WT were selected, and Mann–Whitney Test results with P ≤ 0.05 were chosen as significantly changed proteins.

The functional enrichment analysis including biological process (BP), cellular component (CC), and molecular function (MF) of the increased and decreased DAPs were conducted using the SEA tool (http://systemsbiology.cau.edu.cn/agriGOv2/index.php) based on the Arabidopsis TAIR 10 database (Du et al. 2010). The enriched GO terms (P ≤ 0.05) and the number of proteins in the same enriched GO terms were then compared, and similar GO terms were grouped whenever necessary. The KEGG encyclopaedia was used to identify pathways by analysing the increased and decreased DAPs, which were then compared (http://www.genome.jp/kegg) (Kanehisa et al. 2012).

Heatmaps were constructed and visualised using the Multi-Experiment Viewer (MeV) ver. 4.8.1 package.

The protein–protein interaction assay was performed using Search Tool for the Retrieval of Interacting Genes (STRING database, ver. 11; https://www.string-db.org; Szklarczyk et al. 2019).

TEM analysis was used to visualise the exosomes. The maturation zone (0.5 cm away from the root tip, 1 cm sections) of Arabidopsis primary roots was fixed in 2.0% paraformaldehyde and 2.5% glutaraldehyde in 0.1 M phosphate buffer (pH 7.0) overnight at 4°C. After washing in phosphate buffer, the sections were post-fixed for 2 h in 1% OsO₄ at room temperature, washed, dehydrated using a series of ethanol and acetone solutions, and then embedded in Spurr resin using an SPI-Chem low viscosity kit (SPI, 02690-AB). Thin sections (60–80 nm) were cut using an ultramicrotome (Leica EM UC7, Wetzlar, Germany), stained with uranyl acetate and lead citrate, and observed and photographed under a JEM-1400 transmission electron microscope (Jeol, Japan). Quantification of exosome-like structures in the TEM sections was performed following the method for quantitation of autolysosome and autophagosome structures as described by Liu et al. (2005).

The transcript levels of the tested genes in the roots (100 mg powder in nitrogen) were measured by isolating the total RNA using a plant total RNA purification kit (GeneMark, TR02-150) according to the manufacturer’s protocol. The quantity and purity of RNA was measured by a Nanodrop instrument ND-1000 (NanoDrop Technologies, Wilmington, USA). Two micrograms of total RNA were used for first-strand cDNA synthesis by TransScript One-Step gDNA Removal and cDNA synthesis SuperMix (TransGen Biotech, AT311-03). The qRT-PCR experiments were conducted using SYBR Green Real-Time PCR Master Mix (Toyobo, QPK-201) and the DNA Engine Opticon 2 Real-Time PCR Detection System (MJ Research). The AT1G50010/TUA2 gene was amplified as an internal control to normalise qRT-PCR data. The primer sequences are listed in Supplementary Table S1. Mock-inoculated samples from the WT plants (pooled with equal amounts of samples at 12, 24, 36, 48, 60, and 72 hpi) were used as mock controls. Three biological replicates, each with three technical repeats, were conducted for each sample.

After inoculation, tryptophan (Trp) amino acid solution in different concentration (0.1, 0.25 and 0.5 g/L) was used to spray the aboveground parts of the plants every 5 days. Symptoms, disease index, and fungal biomass of the mock and inoculated plants were investigated at 21 days post-inoculation (dpi).

The disease index of Arabidopsis plants was calculated according to a previous study (Cheng et al. 2016). Briefly, five disease grades (grade 0, 1, 2, 3, and 4) were established based on the percentage of infected leaves in the plants. Disease index was then calculated by a formula: [(∑disease grades × number of infected plants)/(total checked plants × 4)] × 100.

V. dahliae biomass quantified as described previously (Ellendorff et al. 2009). In brief, five V. dahliae-inoculated plants from each treatment were harvested, pooled and ground to a powder in liquid nitrogen, an aliquot of 100 mg was used for DNA isolation. The primers used for measure V. dahliae biomass (ITS1-F and R) or sample equilibration (At-RuBisCo-F3 and -R3) were the same as Ellendorff et al. (2009) described. The real-time quantification experiment was also conducted by SYBR Green Real-Time PCR Master Mix (Toyobo, QPK-201) and the DNA Engine Opticon 2 Real-Time PCR Detection System (MJ Research).

For statistical significance analyses, the mean and s.d. were calculated by Microsoft Excel (Office 2010 edition), and the P-value (0.05 or 0.01) was determined by a two tailed Student’s t-test. All data are from the representatives of three independent experiments.

Previously, DAPs in response to V. dahilae infection were identified in WT and an autophagy mutant (atg10–1) plants to study the roles and functional mechanisms of autophagy-mediated plant immunity (Wang et al. 2018). As the study only focused on autophagy-mediated immunity, hundreds of DAPs representing immunity responses against V. dahilae infection needed to be further investigated. To explore the obtained proteomics data and look for new clues related to immune responses against V. dahilae infection, we extracted the record and listed a total of 515 DAPs, which contained 301 increased and 214 decreased DAPs between the mock and V. dahliae-infected WT Arabidopsis plants at 24, 48, and 72 hpi with log₂ ratios of either (≥0.38, Table S2a) or (≤0.38, Table S2b). To investigate the time course of the proteome changes, we analysed the number of identified proteins at three different time points. The number of proteins identified at 24, 48, and 72 hpi was 121, 198, and 361, respectively (Fig. 1a). The number of DAPs increased dramatically over time, indicating that the proteome changes in response to pathogen infection accelerated over 72 hpi. We also compared the number of increased and decreased DAPs at all three time points, as shown in the Venn diagram (Fig. 1b, c). The significant difference in protein number between increased and decreased DAPs (more than three-fold) at all three time points indicated that the increased abundance of some proteins was vital during all the infection stages. Meanwhile, a more than two-fold difference between increased and decreased DAPs identified at only one time point at the early infection stage (24 hpi) suggested that increased abundance of some proteins occurred during the early infection stage, but some responses only lasted a short period of time. The reduced difference between the number of increased and decreased DAPs identified at two time points and one time point at 48 or 72 hpi indicated that the changes in the proteome included the activation of some proteins as well as repression following pathogen propagation. A heatmap was generated to show the abundance changes of the increased and decreased DAPs at the different infection stages (Fig. S1).

Fig. 1.  Number distribution analysis of differentially abundant proteins (DAPs) at different infection stages. (a) Number distributions of increased and decreased abundant proteins; (b) and (c) Venn diagram showing the overlap of increased (b) and decreased (c) abundant proteins identified at 24, 48, and 72 hpi.

The increased and decreased DAPs in response to V. dahliae infection were annotated by a plant Gene Ontology (GO) analysis using the agriGO Single Enrichment Analysis (SEA) tool (http://bioinfo.cau.edu.cn/agriGO) (P ≤ 0.05). For GO terms enriched for increased and decreased DAPs, there were 151 and 31 for biological processes (BP), 32 and 43 for cellular components (CC), and 49 and 11 for molecular functions (MF), respectively (Table S3a–f).

For the BP annotation, 131 GO terms were only enriched from increased DAPs (Table S3g), which could be categorised into three groups: (1) metabolism (Fig. 2a); (2) defence response and hormone signalling (Fig. 2b); and (3) stress response (Fig. 2c). Eleven GO terms were only enriched from decreased DAPs, which were related to biological processes involved in carbohydrate metabolism, cell growth and redox homeostasis, and cytoskeleton proteins associated with ‘cytokinesis’ (Fig. 2d, Table S3g). Twenty GO terms were enriched from both increased and decreased DAPs, which were related to biological processes involved in stress response (osmotic/oxidative/water/inorganic substance/chemical/karrikin), cellular metabolism (hydrogen peroxide/reactive oxygen species), and cell wall organisation or biogenesis. (Fig. 2e, Table S3g).

Fig. 2.  GO annotation of the identified DAPs. (a–c) GO terms only enriched with increased DAPs; (a) metabolism, BP, biosynthetic process; MP, metabolic process; CP, catabolic process, (b) defence response and hormones signalling and (c) stress response, roman numbers indicate the sub-groups presented in Table S3g. (d) GO terms only enriched with decreased DAPs; (e) GO terms enriched with both increased and decreased DAPs.

For the MF annotation, a total of 41 GO terms were only enriched from increased DAPs. They mainly included proteins that function as transferases, hydrolases, or ATPases. Three GO terms were only enriched from decreased DAPs, which comprised proteins that function as water transporters or structural constituents of ribosomes. A total of eight GO terms were enriched from both increased and decreased DAPs, eight GO terms contain overwhelming number of increased DAPs that function as oxidoreductases or peroxidases, or have binding activity to heme and tetrapyrroler (Table S3h).

For the CC annotation, a total 14 CC GO terms were only enriched from increased DAPs. They mainly located in the plasma membrane, apoplast, chloroplast stroma, endomembrane system, or the vacuolar membrane. A total of 25 GO terms were only enriched from decreased DAPs, mainly located in macromolecular complex, intracellular non-membrane-bounded organelle, cytosolic ribosomes, intrinsic components of the plasma membrane, etc. A total of 18 GO terms were enriched from both increased and decreased DAPs, four of them contained overwhelming number of increased DAPs, which mainly included proteins located on the cell periphery and in the cytoplasm, five of them were enriched from overwhelming number of decreased DAPs, which included proteins located in the plant-type cell wall, cell junction plasmodesma, and symplast (Table S3i).

To further investigate the function of the identified DAPs, the increased and decreased DAPs were annotated according to the KEGG pathways, and the enriched pathways involving at least four proteins were compared. Table S4a showed that the KEGG pathways that only enriched from increased DAPs were glutathione metabolism, biosynthesis of amino acids, amino sugar and nucleotide sugar metabolism, carbon metabolism, tryptophan metabolism, sulfur metabolism, plant–pathogen interaction, MAPK signalling pathway, glycolysis/gluconeogenesis, and nitrogen metabolism; while only ribosome was enriched with decreased DAPs. Additionally, there was also a KEGG pathway (phenylpropanoid biosynthesis) enriched with both increased and decreased DAPs.

Next, we compared the KEGG brite hierarchy enriched with the increased and decreased DAPs. As shown in Table S4b, cytochrome P450, membrane trafficking, glycosyltransferases, mitochondrial biogenesis, and ribosome biogenesis were enriched with increased DAPs, while ribosome, photosynthesis proteins, chaperones, and folding catalysts were enriched with decreased DAPs. In addition, transporters, exosome, chromosome and associated proteins, and messenger RNA biogenesis were enriched in the KEGG brite hierarchy with both increased and decreased DAPs.

According to the GO and KEGG annotations enriched with increased DAPs, many biological processes were activated to impede V. dahliae infection or enhance plant tolerance in Arabidopsis. The biological processes activated could be grouped as carbohydrate derivative metabolism, defence response to biotic stress, amino acid metabolism, and response to abiotic stimulus (Fig. 2, Table S3a, b, Table S4a, b). Group members involved in processes such as phenylpropanoid metabolism, stress responses, and oxygen reduction were repeatedly found to be activated against V. dahliae infection. Remarkably, we also found some new clues to further understand the defence mechanism revealed by the proteome changes in response to the pathogen infection, we analyse the number, the temporal changes and the functional roles of the identified proteins in the biological processes.

Exosomes, subcellular bodies containing antifungal peptides and small RNAs under pathogen attack, play an essential role in blocking fungal growth (Rutter and Innes 2017; Cai et al. 2018; Rutter and Innes 2018). In our study, the KEGG brite analysis showed that 16 increased DAPs were exosomal proteins (Fig. 3a), which indicated that exosomes could be induced by V. dahliae infection and might play a vital role in plant defence. Transcriptional level changes of four selected exosome proteins involved in vesicle trafficking indicated that all of them highly accumulated in response to pathogen infection, with a peak at 48 hpi, and a lower expression at 36 hpi, suggesting the possible activation of exosome formation (Fig. 3b–e). TEM confirmed the presence of exosomes and clearly showed the morphology of V. dahliae-infected epidermis and cortex cells in Arabidopsis roots. As shown in Fig. 3f, exosome-like structures with a diameter of approximately 20–100 nm were frequently observed in the apoplast area between the cell wall and membrane in the root cells, while there were far fewer of them in the control (mock) plants. The quantitative data for exosomes in the two types of cells from mock- and V592-inoculated roots at 48 hpi in WT and V. dahliae plants are shown in Fig. 3g.

Fig. 3.  Exosome secretion was activated after V. dahliae infection in Arabidopsis. (a) Heat map showing the accumulation change pattern for proteins that were located in the exsomes. Blank spaces show a protein that was identified but did not show a significant change in accumulation relative to the mock control. (b–e) RT-PCR analysis of the transcription levels of four selected proteins involving in exosomes formation. The vertical axis in the panels indicates the relative expression change vs the mock control. The standard deviation (n = 3) was estimated. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 vs the mock control as measured by Student’s t-test. (f) TEM analysis of exosomes in mock and V. dahliae-infected Arabidopsis root cells. Bar = 0.2 μm. (g) Quantification of exosome-like structures observed in TEM images of mock or V592 inoculated root cells. E/C, epidermis and cortex; P-V, perivascular. Mean and s.e. were calculated from 10 independent areas of 100 μm².

Tryptophan is a precursor of auxin and some secondary metabolites, such as camalexin and glucosinolates, and cyanogenic compounds, which are usually found in Brassicales and can inhibit the infection by fungus, bacterial, and herbivore (Barth and Jander 2006; Bednarek et al. 2009; Rajniak et al. 2015). Bioinformatics analysis indicated 9 out of the 22 increased DAPs identified at all infection stages were key enzymes involved in tryptophan-derived secondary metabolite biosynthesis (Fig. 4a). As shown in Fig. 4b, the two synthesis steps catalysed by TSA1 and CYP79B2 generated L-Trp and IAOx, and IAOx was the branch point for the two pathways involved in tryptophan-derived secondary metabolite biosynthesis. The camalexin synthesis pathway included four sequential enzymes (CYP71A13, GSTF6 and 7, CYP71B15), while three enzymes (FOX1, CYP71A12 and CYP82C2) were involved in cyanogenic metabolite (4-OH-ICN) synthesis. We chose six genes for RT-PCR quantification analysis to test whether the transcriptional expression of these synthetic enzymes was also activated in response to pathogen infection. Fig. 4c–h show that the transcriptional levels of enzymes for L-Trp and IAOx synthesis (TSA1 and CYP79B2), camalexin synthesis (CYP71A13 and CYP71B15), and 4-OH-ICN synthesis (CYP71A12 and CYP82C2) were increased at almost all the infection stages, with differential statistical significance levels (P-value ≤0.05, 0.01 or 0.001). The high number and durable activation of these enzymes suggested that activation of the two pathways is vital for Arabidopsis defence against V. dahliae infection. Since compound synthesis in the two pathways originates from tryptophan, we speculated that tryptophan is a key component that might influence Arabidopsis resistance. To verify this, we treated Arabidopsis seedlings with tryptophan solution every 5 days after inoculation. The results showed that spraying tryptophan in a saturated solution (0.5 g/L) dramatically enhanced the disease tolerance, indicated by disease symptom, disease index and fungal biomass amount. Spraying Arabidopsis seedlings with lower concentration of tryptophan solution (0.25, 0.1 g/L) could also enhance the disease tolerance of the plants, but the effect was obviously reduced (Fig. 4i–k).

Fig. 4.  Tryptophan-derived camalexin and cyanogenic biosynthesis play a vital role for plant tolerance to V. dahliae infection. (a) Heat map showing the accumulation change pattern for proteins that were durably activated during tryptophan-derived camalexin and cyanogenic biosynthesis. Blank spaces show a protein that was identified but did not show a significant change in accumulation relative to the mock control. (b) Biosynthetic pathway for tryptophan-derived camalexin and cyanogenic biosynthesis, with enzymes identified as increased DAPs in response to V. dahliae infection at each step. (c–h) RT-PCR analysis of the transcription levels of some selected proteins in the tryptophan-derived camalexin and cyanogenic biosynthesis pathway. Vertical axis in the panels indicates the relative expression change vs the mock control, standard deviation (n = 3) was estimated. (i–k) Exogenous tryptophan enhances plant tolerance to V. dahliae in Arabidopsis, disease symptoms (i), disease index (j) and fungal biomass (k) were measured in mock and V592 infected plants with or without spraying tryptophan solutions, standard deviation (n = 3) was estimated. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 vs the mock control as measured by Student’s t-test.

The defence response to biotic stress and hormone signalling directly reflects the character of the immune response caused by the pathogen. Therefore, we investigated this characteristic, which is provoked by V. dahliae infection. There were 108 proteins in the GO term related to defence response to biotic stress or KEGG pathway ‘plant–pathogen interaction’ and ‘hormone synthesis’ (Table S5a). They accounted for more than one-third of the increased DAPs identified. The majority of them belonged to the subgroups for defence signalling, hormone synthesis, regulation and signalling, phytoalexins, oxidation–reduction, PR proteins, and lignin biosynthesis (Fig. 5a, Table S5a). Among them, a total of 39 proteins appeared at multiple time points and 69 proteins appeared at only one time point (5 at 24 hpi, 18 at 48 hpi, and 46 at 72 hpi), which indicated durable or temporal activation of responsive proteins during V. dahliae infection (Fig. 5b, c, Table S5a). The interactions between the 108 proteins were identified using STRING analysis (Fig. S2) and the protein accession number and descriptions corresponding to the string names shown in the figure are illustrated in Table S5b. After database and literature searching of the 108 proteins individually, we found 54 proteins that were core components for plant immunity response with distinct signalling routes against V. dahliae infection. The accession number, expression profile, description, and classification of these 54 proteins were shown in Table S5a, the functional cascade and subcellular localisation of these proteins were illustrated and various novel V. dahliae responsive proteins were shown by a schematic representation (Fig. 5d).

Fig. 5.  Analysis of the identified proteins in GO terms related to defence responses, biotic stress and hormone signalling. (a) Functional classification. (b–c) Heat maps showing the increased DAPs identified at multiple time points (b) or at only one time point (c) after V. dahliae infection. Blank spaces show a protein that was identified but did not show a significant change in accumulation relative to the mock control. (d) Schematic representation of the functional cascade and subcellular localisation of the key proteins. After pathogen infection, inhibition of fungal cell growth (chitinase) and infection (PGIP1) occurred in the cell wall; PAMP- and DAMP-immunity were activated by signalling components (chitinase/LYK5/NHL3, PEPR1/PEP7, ABCG36, Ca²⁺, RBOHD, H₂O₂, and NHL10) in the apoplast and membrane; MAPK/SA/JA/ET function in signalling transduction from cytoplasm to nucleus; proteins related to key downstream immunity responses (in dashed square), including tryptophan synthesis, lignin synthesis, glucosinolate biosynthesis, detoxin, cyanogenic metabolism, and cell wall reinforcement were translated and delivered to different locations in the cell to form multiple baselines for defence. ‘*’ in red shown the newly identified V. dahliae responsive proteins in this study.

In this study, we found GO terms of ‘cellular component organisation/biogenesis’ and ‘cytokinesis’ were specifically enriched from decreased DAPs. The proteins involved and their temporal expression are in Fig. 6a and Table S6a. We then classified these proteins into seven groups according to their functional roles (Fig. 6b, Table S6b), which were cell wall organisation (10, 21.74%), redox homeostasis (9, 19.57%), ribosome biogenesis (6, 13.04%), chromatin organisation (5, 10.87%), microtubule formation (4, 8.70%), signalling (2, 4.35%), and unclassified (10, 21.47%). Next, we selected six proteins from three groups with larger protein number to test whether their transcriptional expression was decreased. As shown in Fig. 6c–h, expression of the tested encoding genes decreased at all the infection stages, including cell wall organisation-related genes (PME24, PME2 and CESA3), inhibitor of tubulin polymerisation for cytokinesis (PLP3A and PLP3B), and ribosome constitute protein (60S), suggested the repression of corresponding processes. The repression of cell wall/components organisation and cytokinesis coincided with plant growth inhibition caused by V. dahliae infection, which is widely known in various hosts. In addition, the abundance of a chaperone for importing mitochondrial inner membrane proteins decreased at all the infection stages (TIM10), which suggested the normal biogenesis of energy producer (mitochondrial) could be also repressed by V. dahliae.

Fig. 6.  Analysis of the identified proteins that were annotated as GO terms related to cellular component organisation/biogenesis, cytokinesis, and cytoskeleton organisation. (a) Heat map showing the accumulation change pattern. Blank spaces show a protein that was identified but did not show a significant change in accumulation relative to the mock control. (b) Functional classification. (c–h) RT-PCR analysis of the transcription levels for selected proteins. Vertical axis in the panels indicates the relative expression change vs the mock control. Standard deviation (n = 3) was estimated. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 vs the mock control as measured by Student’s t-test.

Exosomes were first dissected in mammalian cells. They originate as intraluminal vesicles (ILVs) in multivesicular bodies (MVBs) and are formed in plants by release into the space between the plasma membrane and cell wall after the fusion of the cell membrane and MVBs (Harding et al. 1983; An et al. 2006a, 2006b). Exosomes contain lipids, RNA, cell wall-related proteins, defense-related proteins, and compounds that mediate cell-to-cell communication (Cui et al. 2020). These compounds inhibit pathogen growth, decrease pathogen virulence, and participate in plant cell wall remodelling (Schorey et al. 2015). In our study, proteomic data combined with cellular analysis showed that exosome formation increased dramatically after V. dahliae infection (Fig. 3). Considering the complexity of plant immunity responses against V. dahliae and the knowledge obtained to date, we expected to see several types of components that could be released through exosomes. These were: (1) proteins or compounds that inhibit fungal growth, including chitinase, inhibitors of cell wall-degrading enzymes, lectins, and anti-pathogenic compounds; (2) cell wall-related proteins that form a physical barrier to restrict fungal infections, such as TCH4 and XTH24. The abundance of these two types of molecules or their related synthases increased in this study and we speculated that exosome packaging and delivery might account for their apoplast location in the cell; and (3) RNA targeting fungi. Previously, host-induced gene silencing (HIGS) was successfully applied to silence target genes in fungal cells to construct transgenic cotton with V. dahliae resistance (Zhang et al. 2016). The trans-kingdom movement of RNAs is thought to be mediated by exosomes, together with several actions associated with other plant–pathogen interactions (Rutter and Innes 2017). Thus, exosomes seem to mediate various plant immunity responses after V. dahliae infection, so further research on the delivery mechanisms and their possible use for disease control should be conducted.

Phytoalexins, antimicrobial compounds with low molecular weights, are produced in plants upon pathogen infection or abiotic stress, and the major phytoalexin in Arabidopsis is camalexin (3-thiazol-2′-yl-indole) (Tsuji et al. 1992; Hammerschmidt 1999; Su et al. 2011). Many cytochrome P450 enzymes and glutathione S-transferases function in the camalexin synthesis pathway derived from Trp and are co-regulated by CPK5/CPK6, MAPK, and WRKY33 (Zhou et al. 1999, 2020; Su et al. 2011; He et al. 2019). Another Trp-derived phytoalexin is indole glucosinolate metabolite (IGS), which has been reported to be a mediator of fungal defence (Bednarek et al. 2009, 2011). In 2015, a new Trp-derived compound, 4-hydroxyindole-3-carbonyl nitrile (4-OH-ICN), was discovered to be a cyanogenic metabolite that is required by inducible pathogens in Arabidopsis (Rajniak et al. 2015). Through a transcriptome analysis, Iven et al. (2012) reported that Trp-derived compounds including IGSs, indole-3-carboxylic acid (I3CA) and camalexin were simultaneously activated in response to Verticillium longisporum infection in Arabidopsis. In this study, we found that nearly all the enzymes in the camalexin and 4-OH-ICN pathways were increased DAPs and this was verified at the transcriptional level, but no enzymes for IGS or I3CA synthesis were altered in response to V. dahliae infection (Fig. 4a–h). These results suggest that the 4-OH-ICN pathways are very important for plant defence against V. dahliae infection, which is different from V. longisporum. The suppression of tryptophan synthase and the production of camalexin, promoted by spermine, have been found to contribute to plant resistance against V. dahliae in cotton (Mo et al. 2015; Miao et al. 2019). These two studies highlight the significance of plant immunity through the regulation of Trp and camalexin synthesis after V. dahliae infection, but the affected pathways are distinct. The exact roles of Trp synthesis and Trp-derived metabolites in different plant hosts in response to V. dahliae, including the newly identified 4-OH-ICN, need to be studied further, and could provide a theoretical basis for controlling V. dahliae. Significantly, we found that spraying Trp on leaves dramatically enhanced disease tolerance in Arabidopsis (Fig. 4i–k), which could be directly used to design convenient and environmentally friendly foliar spraying agents for V. dahliae control in similar host plant species.

Knowledge about plant immunity against V. dahliae infection has gradually accumulated over the past decade. Many studies concerning single gene characterisation and the immune responses by various biological processes have been performed in different hosts, especially cotton, and the key findings and critical components of immunity have been summarised as a theoretical basis for understanding the molecular mechanisms underlying plant resistance to V. dahliae (Shaban et al. 2018; Song et al. 2020). In this study, we found some immune responses against V. dahliae infection that were consistent with previous studies, such as chitin-triggered immunity, RBOHD-mediated HR-PCD, complex hormone signalling, and lignin synthesis (Fig. 5, Table S5a). More importantly, we found unreported components that were actors for immunity activation and signalling as well as downstream immune responses against V. dahliae (Fig. 5d). For instance, nine activators and regulators of HR-PCD (NHL10, KTI1, NUDT7, SYP122, PAP1, SAG13, DLO1, BCS1, and MSS1), and 10 enzymes for cyanogenic metabolism (ASA1, TSA2, CYP79B2, CYP71A13, CYP71B15, CYP71A12, FOX1, NIT1, CYP81D1, and CYSC1) were found. These newly identified components or response processes related to plant immunity against V. dahliae infection will provide important supporting data that could improve our understanding about the molecular mechanisms underlying plant resistance against V. dahliae, and these findings are expected to serve as a theoretical and applied basis for developing new strategies for controlling Verticillium wilt disease.

After analysing the decrease DAPs in response to V. dahliae attack, we found that the biological processes related to normal cell growth were seriously repressed (Fig. 6, Table S6b). A comparison with the highly activated defence status, including HR-PCD, ROS regulation, immunity signalling activation, anti-microbial compound production, and cell wall reinforcement, showed that there may be a remodelling process after pathogen infection. It is called the ‘Growth-defense tradeoffs’ process, which means that defence activation for plant survival comes at the expense of plant growth (Huot et al. 2014). In general, the number of the decreased DAPs was less or almost equal to the increased DAPs and increased along with the pathogen infection, and often classified as functional enzymes related to primary metabolism or oxidative stress (Wang et al. 2011; Gao et al. 2013; Fang et al. 2015). Recently, a study has also shown the decreased DAPs were highly related to plant growth and development during V. dahliae–cotton interaction by monitoring the proteome changes of cotton xylem sap (Yang et al. 2020). Detail studies need to be performed on spatially and temporally changed character of the decreased DAPs to further unravel their functional roles. The molecular basis of ‘Growth-defense tradeoffs’ remains largely unknown. Hormone crosstalk and Ca²⁺ sensor-mediated ROS scavenging have ever been found to play important roles in regulating trade-offs to maintain balance (Karasov et al. 2017; Gao et al. 2021). Coincidently, various growth and defence hormones and ROS related responses were all found in our study (Figs 5, 6), which also indicated that ‘Growth-defense tradeoffs’ appeared in plants challenged with V. dahliae. Our study monitored whole proteome changes due to pathogen recognition, infection, defense-triggering and growth alterations, which could lead to the potential identification of proteins involved in ‘Growth-defense tradeoffs’ after pathogen infection. As maintaining the balance between resistance with the least growth reduction is very important when designing resistant crops using transgenic engineering (Karasov et al. 2017), further determination of the functional roles played by V. dahliae-responsive proteins that also play a role in plant growth might be necessary.

Through bioinformatics combined with experimental validation, we investigated defence responses against V. dahliae infection in Arabidopsis based on the original proteomic data from a previous study. Notably, we verified several new clues for understanding the defence responses against V. dahliae except for the already reported findings in other studies. Indeed, activation of exosomes formation at the early infection stages, durably and extensively increasement of both transcriptional and protein abundance of tryptophan-derived compound biosynthesis related enzymes, the possible trade-off between defence and growth, and the participation of some newly found hub immunity components were critical and necessary for plant immunity against V. dahliae infection. Collectively, our results provide new evidence demonstrating the native immunity in response to V. dahliae invasion, thus supplementing the current knowledge about the molecular basis of plant defence against the vascular pathogens.

Supplementary material is available online.

The data that support the findings of this study are available from the corresponding author upon reasonable request.

The authors declare no conflicts of interest.

This work was supported by the National Natural Science Foundation of China (Grant Number 31871225 and 32170303), the Natural Science Foundation of Hebei Province (Grant Number C2021201031) and Advanced Talents Incubation Program of the Hebei University (Grant Number 521100221014).