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Lipid profiling of barley root in interaction with Fusarium macroconidia
Environmental and Experimental Botany 166 (2019) 103788
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Lipid profiling of barley root in interaction with Fusarium macroconidia Matias Reyna, Micaela Peppino Margutti, Ana Laura Villasuso
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Dpto. de Biología Molecular, FCEFQN, Universidad Nacional de Río Cuarto, X5804BYA Río Cuarto, Córdoba, Argentina
A R T I C LE I N FO
A B S T R A C T
Keywords: Barley Electrospray ionization tandem mass spectrometry Fusarium graminearum Lipid remodelling Phosphatidic acid
Fusarium is the major causal agent of Fusarium head blight (FHB) in several cereal crops. Macroconidia, the asexual form of Fusarium, can infect the roots and aerial parts of plants. The response of cereal to attacks by Fusarium has been investigated at transcriptomic and metabolomic level, but there are no reports of root lipidomic assays carried out during Fusarium-root interaction. In order to determine how root phospholipids contribute to that interaction, we performed a lipidomics-based ESI-MS/MS assay coupled with a statistical analysis. It was found that phospholipid and galactolipid levels were not modified during early pathogen response, although some individual phospholipid molecular species did undergo significant changes. In plants exposed to macroconidia there was a rapid and transient increase in the phosphatidylcholine (36:4-PC) molecular species, in comparison with the control. By contrast, there was a decrease in lysophosphatidylcholine (16:0-, 18:2- and 18:3-LPC) levels. Furthermore, a phospholipase assay and the measurement of endogenous phytohormone levels through the use of fluorescent lipids and liquid chromatography-tandem mass spectrometry, revealed an increase in phospholipase A (PLA) activity, as well as in the endogenous amounts of Jasmonic acid (JA) and Salicylic acid (SA). The results indicate that barley root is able to modulate the glycerolipid fatty acid composition during the early response to Fusarium, suggesting a particular pathogen-sensing mechanism that could be useful to understand the role of lipids in plant-pathogen interactions.
1. Introduction Plants are continuously challenged by invading microorganisms, some of which are pathogens that affect plant survival and produce a negative effect on crop production. In general, the perception of pathogens relies on transmembrane pattern recognition receptors that specifically recognize highly conserved pathogen-derived molecules called PAMPs/MAMPs (pathogen-/microbial-associated molecular patterns), such as bacterial flagellin or chitosan (Jones and Dangl, 2006). These elicitors are signal-inducing compounds recognised by the innate immune system. A second layer of defence is based on pathogen-derived molecules that are specifically recognized by the corresponding plant resistance protein and induce effector-triggered immunity (Thomma et al., 2011). The activation of plant immunity involves a variety of early signalling events, including rapid accumulation of reactive oxygen species (ROS), changes in cellular ion fluxes, activation of protein kinase cascades, and changes in gene expression (Lamb and Dixon, 1997; Durrant and Dong, 2004; Truman et al., 2007). Membrane lipids are also key
players during the perception of and response to a pathogen attack. Accumulating evidence suggests that the metabolism of plant lipids is modulated mainly by the activity of lipases (Siebers et al., 2016; Li and Wang, 2019). However, these studies generally focus on the phosphatidic acid (PA) signal. This minor phospholipid is produced by enzymatic activation of phospholipase C in concerted action with diacylgycerol kinase (PLC/DGK), or by activation of phospholipase D (PLD) (Testerink and Munnik, 2011). This PA-based lipid signalling has been described as one of the earliest plant responses upon treatment with several elicitors. The MAMPs xylanase, chitotetraose, chitosan and N-acetylchitooligosaccharides, produced by fungi, cryptogein, from the oomycete Phyotophtora cryptogea, botrydial from Botrytis cinerea and the bacterial flagellin-derived peptide flg22, induce PA production via PLC/ DGK and/or PLD (Yamaguchi et al., 2003; Bargmann et al., 2006; Laxalt et al., 2007; Raho et al., 2011; Cacas et al., 2017; D’Ambrosio et al., 2018). In most of these reports, PA was determined by labelling the cell/ tissue with 32 P, monitoring the phospho-transfer from 32 P-γ-ATP to the respective substrate, and then measuring the enzymatic activity
Abbreviations: DGDG, digalactosyldiacylglycerol; JA, jasmonic acid; LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; LPG, lysophosphatidylglycerol; MGDG, monogalactosyldiacylglycerol; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PI, phosphatidylinositol; PG, phosphatidylglycerol; PS, phosphatidylserine PLA phospholipase A; PLC, phospholipase C; PLD, phospholipase D; SA, salicylic acid; TLC, thin layer chromatography ⁎ Corresponding author. E-mail address: [email protected] (A.L. Villasuso). https://doi.org/10.1016/j.envexpbot.2019.06.001 Received 27 February 2019; Received in revised form 31 May 2019; Accepted 5 June 2019 Available online 09 July 2019 0098-8472/ © 2019 Elsevier B.V. All rights reserved.
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For the chitosan assay, chitosan was prepared from crab shells (Sigma, St. Louis, MO, USA) following Raho et al. (2011). Briefly, barley roots were treated with 100 μg mL-1 chitosan at the times indicated. For inactivated macroconidia, a 1 × 107 macroconidia mL-1 suspension was deactivated with autoclave.
(Testerink and Munnik, 2011). However, PA derived from the aforementioned two pathways may possess structural diversity (in terms of fatty acyl chain length and degree of saturation), as well as distinct spatio-temporal characteristics in the assessed tissue (Pokotylo et al., 2018). Additionally, the perception of and response to a pathogen attack might not be limited only to this minor phospholipid (Siebers et al., 2016). On the other hand, our knowledge about the role lipids play in different cellular responses in plants has improved ever since highly sensitive analytical technologies, including mass spectrometry, have been made available (Lam et al., 2017). Lipidomic analysis has made it possible to detect lipids in relatively narrow mass ranges which can often suffer from isobaric interferences, as well as when the high concentration of certain lipids supresses the detection of low abundance lipids (Lam et al., 2017). Moreover, it has also shown how global changes in membrane lipid composition or specific lipid remodelling contribute to the physiological response to abiotic stress, such as high or low temperature, salinity, availability of nutrients, and so on (Welti et al., 2002; Wang et al., 2006; Narasimhan et al., 2013; Narayanan et al., 2016, 2018). In contrast, lipid profiling has not been extensively performed in connection with plant pathogen response in cereal (Hammann et al., 2019), especially when it comes to crops of considerable economic importance, like barley. The present study investigates glycerolipid molecular species in barley roots, with the aim of determining how they are quantitatively and qualitatively modulated by their interaction with macroconidia, the asexual form of Fusarium graminearum. Furthermore, we analysed other downstream events of PAMP-triggered immunity, like the generation of reactive oxygen species, hormonal changes and phospholipase activity, in order to elucidate how the steady-state membrane lipid composition is modified in connection with other aspects of barley root defence.
2.2. Lipid extraction and separation Total lipids were extracted from barley roots (80 mg) by adding 0.8 mL of methanol/chloroform/ formic acid (20:10:1, v/v/v), and shaken vigorously for 5 min. After that, 0.4 mL of 0.2 M H3PO4/1 M KCl was added to obtain a lower chloroform phase and an upper phase. Centrifugation at 13,000×g for 1 min made it easier to separate the lower organic phase containing the lipid, which was transferred to a new glass vial. The solvent was evaporated under an N2 stream. Phospholipids and galactolipids were separated by TLC. Chromatograms were developed with a solvent system made up of acetone/acetic acid/H2O (100:2:1, v/v/v) or acetone/acetic acid/H2O (91:30:7.5, v/v/v) (Wang and Benning, 2011), and stained with iodine or α-naphthol. The positions of lipids on the chromatograms were determined by comparing migration with commercial standards. Before being used, TLC plates were briefly submerged in an ammonium sulfate solution and dried for at least 2 days in a place protected from dust. The plate was activated at 120 °C to convert (NH4)2SO4 into NH3 and H2SO4. This treatment led to the evaporation of ammonia and the acidification of the silica material by sulfuric acid. Thus, anionic lipids altered their migration, and the separation of the phospho- and glycolipids was improved (Wewer et al., 2013). 2.3. Lipid profiling Lipid extraction was performed as described by (Welti et al., 2002). For each sample, roots (approximately 200 mg) were immersed in 3 ml of isopropanol (0.01% w/v 2,6-Di-tert-butyl-4-methylphenol) at 75 °C for 15 min. These conditions prevent the lipid from being modified by degrading enzymes such as phospholipases (Lam et al., 2017). Then, 1.5 ml of chloroform and 0.6 ml of distilled water were added. The tubes were shaken for 1 h at room temperature, and then the extract was removed. The tissues were re-extracted with chloroform/methanol (2:1) with 0.01% 2,6-Di-tert-butyl-4-methylphenol five times, with 30 min of agitation each time, until all the remaining plant tissue appeared white. The combined extracts were washed once with 1 ml of 1 M KCl and once with 2 ml of water. The organic phase was recovered, and the solvent was evaporated under a nitrogen stream. The lipid extracts were sealed in a glass tube with a Teflon tape screw cap (2.0 mL clear vial. SUPELCO, SIGMA-ALDRICH) and stored at −20 °C until the analysis. The remaining plant tissues were heated overnight at 105 °C and weighed. These weights are listed as plant “dry weight”. Lipid samples were analysed on a triple quadrupole MS/MS equipped for ESI. The lipid analyses described here were performed at the Kansas Lipidomics Research Center's Analytical Laboratory. Data processing was performed as previously described by (Li et al., 2008). Phospholipid and galactolipid molecular species were quantified in comparison to the two internal standards. The quantity of each lipid was determined as a normalized mass spectral signal (i.e., normalized to the two internal standards (Maatta et al., 2012). The normalized signal was divided by extracted dry mass (to produce normalized mass spectral (MS) signal/mg extracted dry mass). This approach makes it possible to compare lipid species quantities and classes between samples (Narasimhan et al., 2013).
2. Materials and methods 2.1. Pathogen growth and inoculation Barley plants (Hordeum vulgare L. cv. ‘scarlett’) were grown from seeds (INTA Bordenave, Argentina). To avoid microbial contamination, seeds were surface-sterilized by incubation in H2SO4 (50% v ⁄ v) for 1 h and then washed five times in sterile bi-distilled water to remove the remaining sulphuric acid. Seeds were subsequently shaken in AgNO3 (1% w ⁄ v), at 200 rpm on an orbital platform for 20 min and rinsed successively with NaCl (1% w ⁄ v), sterile bi-distilled water, NaCl (1% w ⁄ v), and five times in sterile bi-distilled water to remove the AgNO3 completely. Seeds were placed on a Petri plate, germinated in sterilized water and grown for 4 d in the dark at 25 ± 2 °C until roots and shoots emerged (Lanoue et al., 2010; Peppino Margutti et al., 2017). To obtain Fusarium graminearum macroconidia, an active culture of the fungus grown on solid Spezielier Nährstoffarmer (SNA) medium (g L−1: 1 KH2PO4, 1 KNO3, 0.5 MgSO4-7H2O, 0.5 KCl, 0.2 glucose, 0.2 sucrose, 20 Agar, at pH 5.4) was transferred by cutting the medium into small agar pieces that were placed in liquid SNA medium at 28 °C, with 150 rpm shaking. After 7 d, the culture was passed through a 0.5 mm polyester filter. Then, macroconidia were harvested by centrifugation (11,000×g, 15 min) and resuspended in a minimal volume of sterile glycerol 15% v / v. To infect the plant root system, a suspension of macroconidia was prepared at a concentration of 1 × 107 conidia mL−1 in a Neubauer chamber. Finally, 4 day-old seedlings were placed in a sterile Petri plate, inoculated with the macroconidia suspension and harvested after the times indicated (Lanoue et al., 2010). We chose these inoculation times to analyse the early response of barley root, prior to macroconidia germination. For the control samples, sterile water was used and the treatment was alternatively stopped and started for 30 s intervals. Afterwards, roots were separated and washed five times in sterile bi-distilled water.
2.4. Unsaturation index The unsaturation index is a calculation that determines the number of double bonds in a lipid. For each lipid molecular species in barley roots, this was calculated as indicated by (Narayanan et al., 2018). 2
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were identified by comparison to standards (Avanti Polar Lipids, Inc – Alabama-USA) and visualized with iodine vapor. The difference in relative mobilities between NBD-labelled and unlabelled standards was less than 5%. A standard curve was constructed using a range of phosphatidylcholine (PC) concentrations (Peppino Margutti et al., 2019b). The relationship between the amount of standard PC and the fluorescence measured was linear throughout the range 6 ng–50 ng. These values could be used to express the results as enzymatic activity in μKat (microkatal).
Briefly, it was estimated as the product of the amount of that lipid molecular species and the average number of double bonds per acyl chain, where the average number of double bonds per acyl chain was calculated as the number of double bonds in the lipid molecular species divided by the number of acyl chains. Finally, the unsaturation index of a lipid head group class was calculated as the sum of the unsaturation indices of individual lipid molecular species in that class (Narayanan et al., 2016). 2.5. Heat map and correlation map
2.7. Detection of reactive oxygen species Utilities of the MetaboAnalyst web server (metabolanalyst.ca) were used to obtain the normalized data by median (Table S2) of lipid data (Table S1) to produce heat maps (Vu et al., 2014; Narayanan et al., 2018). Individual values contained in a matrix (Table S2) are represented with colours on the map. The features are colour-coded by row, with red indicating high intensity and blue indicating low intensity. Correlation analyses between selected lipids (PC and LPC, Table S3) based on Pearson correlation were also conducted using the software package MetaboAnalyst (Table S4).
ROS levels were determined by staining with 2',7'-dichlorofluorescin diacetate (DCFH-DA; Molecular Probes, Invitrogen) as described by (Peppino Margutti et al., 2017). Roots were treated with 10 mM DCFH-DA for 5 min and then examined with an epifluorescence microscope (Axio Lab; Zeiss) with a 492–495 excitation filter and a 517–527 emission filter. Images were taken with a Canon G10 camera and quantified with the ImageJ densitometry software. 2.8. Extraction and quantification of JA and SA
2.6. Phospholipase assay SA and JA levels were analysed simultaneously by electrospray ionization/tandem mass spectrometry (LC-ESI–MS-MS), essentially as described by Durgbanshi et al. (2005). In brief, 200 mg of barley roots were ground in liquid nitrogen, extracted with acetone/water/acetic acid (80: 19: 1, v/v/ v), added with 5 mL of a mixture of internal standards (50 ng/sample of 2H6-JA and 2H4-SA), and centrifuged at 500 g for 15 min. The resulting supernatant was collected and evaporated, and the solid residue was dissolved in 500 mL of methanol and evaporated. The resulting residue was dissolved in methanol/1% acetic acid (99:1, v/v), and then passed through a DEAE Sephadex A-25 column. Aliquots of the resulting solution were injected directly into the LC-ESI-MS-MS system. MS/MS experiments were performed on a Micromass Quatro Ultima Pt double quadrupole mass spectrometer (Micromass, Manchester, UK).
PLD and PLA activities were measured by observing phosphatidyl butanol (NBD-PBut) and free fatty acid (NBD-FFA) production from NBD-PC, mainly as described by (Yang et al., 2007; Peppino Margutti et al., 2017). Briefly, PLD activity was determined by TLC as the synthesis of phosphatidylbutanol (NBD-PtdBut) in relation to NBD-PA and NBD-PC levels. NBD-PC (Avanti Polar Lipids, Inc-Alabama, USA) was stored at −80 °C in chloroform (1 mg mL-1), dried under an N2 stream before its use, resuspended in Hepes (50 mM, pH 7.4), and added to the PLD assay mixture as a liposome. The standard PLD assay mixture consisted of 20 mM Mes-NaOH (pH 6.5), 50 mM CaCl2, 0.25 mM SDS, 1.5 μL fluorescent substrate (NBD-PC, 10–50 μg), 1% (v/ v) 1-butanol, and 40 μg protein, in a total volume of 40 μL. The reaction was initiated by addition of the substrate. Incubation continued for 30 min at 30 °C with shaking (100 rpm), and the reaction was stopped by addition of 150 μL chloroform/methanol (1:2, v/v), 40 μL chloroform, and 40 μL 2 M KCl. The mixture was centrifuged at 15,000×g for 2 min, and the phases were separated. 100 μL chloroform were added to the aqueous phase, which was then centrifuged at 15,000×g for 2 min. The lower chloroform phases from each step were pooled. Samples were dried under an N2 stream, resuspended in a minimal volume of chloroform/methanol (95:5, v/v), spotted on TLC plates (silica gel G; Fisher Scientific), and developed with 2,2,4-trimethylpentane/acetic acid/H2O/ethyl acetate (2:3:10:13, v/v). For the PLA assay, protein (100 μg) was incubated with 3 μL of liposomes (NBD-PC, (Avanti Polar Lipids, Inc-Alabama,USA)) in a total volume of 100 μL of MES-KOH, pH 6.8, and 1 mM CaCl2 at 33 °C for 30 min. Reactions were stopped by adding 2 volumes of the stopping solution (methanol:chloroform 2:1, v/v). One volume of 0.1 M KCl was subsequently added, and incubation at −20 °C for 20 min followed. After centrifugation for 30 s at 10,000×g, the organic phase was evaporated under an N2 stream and redissolved in 10 μL chloroform for TLC on silica gel 60 (Merck, Darmstadt, Germany) in a solvent of chloroform:methanol:H2O (65:25:4, v/v). Plates were dried and scanned. Fluorescence from lipids (excitation 460 nm, emission 534 nm) was measured with a fluorescence spectrophotometer (Image Station 4000 MM PRO-Carestream Molecular Imaging). Fluorescently labelled lipids were visualized with a UV light box (FBTIV-88, Fisher Scientific), and the regions corresponding to NBD-PC, -PA, -PtdBut, and -FFA were marked. The spots marked were scraped from the plates, placed in 600 μL chloroform: methanol: H2O (5:5:1, v/v/v), vortexed and centrifuged for 5 min at 15,000×g. Fluorescence from the eluted lipids (excitation 460 nm, emission 534 nm) was measured with a fluorescence spectrofluorometer (Horiba-Fluoromax-3). Lipid spots
2.9. Statistical analysis For lipidomic analysis, five replicates of each treatment were processed and analysed. Paired values were subjected to the one-way ANOVA with Tukey’s test to determine the statistical significance, and graphics were created with Origin Pro 8 Copyright 1991–2008. Principal Component Analysis (PCA) was performed as an exploratory multivariate analysis tool to reduce the dimensionality of the large datasets generated by ESI-MS/MS. The dataset scores and the specific weight with which each glycerolipid molecular species contributed to the first two principal components are visualized in the scores and loading plots, respectively. Both biplots (scores and loading plots) based on the correlation matrices were made using the software package MetaboAnalyst (Table S6 and S7). For others assay, statistical analyses were carried out by using the software package with Origin Pro 8 Copyright 1991–2008. At least, five replicates of each treatment were analysed using Analysis of Variance (ANOVA) and Tukey’s test pairwise comparisons. All tests were subjected to a 95% confidence limit. 3. Results Lipidomic analysis based on electrospray ionization-triple quadrupole mass spectrometry (ESI-MS/MS) allows for the rapid and sensitive profiling, quantification, and characterization of plastidic and extraplastidic lipids in barley tissues (Peppino Margutti et al., 2018, 2019a). However, to the best of our knowledge, there are no lipidomics data available for biotic stress in barley roots, since the interaction between F. graminearum and barley tissues has been explored at the 3
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Fig. 1. Changes associated with lipid class and glycerolipid molecular species from barley roots during F. graminearum macroconidia treatment. A) Separation of plastidic and extraplastidic lipids from barley roots. Lipids were isolated from barley roots with a CHCl3/methanol/formic acid solution, separated by TLC and stained with iodine (left panel) or α-naphthol (right panel). B) The total polar glycerolipid amounts are expressed as percentage of total normalized mass spectra. The values are the mean ± SEM; n = 5. Means with different letters are significantly different according to Tukey test at P < 0.05. C) Heat map showing F. graminearum effect on lipid profiling: Each colored bar within a column represents a lipid molecular species in the indicated class lipid and treatment. The colour of each bar represents the levels of corresponding lipid species (% of total normalized intensity). A total of 156 lipid species in the indicated lipid classes were organized using class (as indicated), total acyl carbons (in ascending order within a class), and total double bonds (in ascending order within class and total acyl carbons).
(∼40%). The next most abundant class was PI (∼15%), followed by PE and PA (∼10% to 15%). The least abundant classes were PS and LPC (∼0.5%; Figs. 1B and 3 D). Although total phospholipid content remained unchanged, some phospholipid species were significantly different under pathogen treatment. Analysis of the specific contribution of every lipid class to the total amount of measured glycerolipids showed an important difference between zwitterionic glycerolipids like PC and monoacyl molecular species LPC (Figs. 1B and 4 A). An overview of the data based on ESI-MS/MS, which is shown in Fig. 1(B and C), revealed complex and considerable changes in lipid molecular species during the interaction between F. graminearum and barley roots. Changes in the lipid profile during pathogen treatment were more significant 30 min after macroconidia inoculation than those after 60 min. The level of most lipids tended to increase or remain unchanged except for that of LPC, which declined.
transcriptomic and metabolomic level (Kazan and Gardiner, 2018). This is despite the great opportunity that barley tissue analysis offers in terms of deciphering how the metabolism of lipids in roots specifically contributes to the physiology of barley response to fungal pathogens such as F. graminearum.
3.1. Lipid class changes in barley roots after inoculation with macroconidia of F. graminearum From a TLC analysis we learned that phospholipids and glycolipids are the most abundant lipids in barley roots (Fig. 1A). In order to determine the specific contribution of lipids in the response to the pathogen, it was necessary to use a powerful strategy to fully characterize lipid molecular species. Approaches based on electrospray ionization tandem mass spectrometry have been developed to comprehensively analyse lipid composition in plant tissues. We used a lipidomic approach to explore the modulation of lipid composition in barley roots after inoculation with macroconidia of F. graminearum. Lipids from roots either grown under control conditions (seedlings incubated at 25 °C) or submitted to the pathogen (seedlings incubated at 25 °C for 30 and 60 min with macroconidia) were quantitatively profiled using ESIMS/MS. The data provided information on phospholipids and glycolipids at the level of the head group and the number of carbon atoms and double bonds present in the acyl chains. We identified 156 glycerolipid molecular species, present in all five biological replicates from control and F. graminearum-inoculated barley roots (Fig. 1C). The lipids identified fitted into most major glycerolipid classes, including galactolipids (monogalactosyldiacylglycerol, MGDG‐; digalactosyldiacylglycerol, DGDG‐), and phospholipids (PL, PC‐; PA‐; PE‐; PG‐; PI‐; PS‐; including the monoacyl molecular species LPC‐, LPG-, LPE) (Fig. 1B). When comparing the proportions within PL classes, PC was the most abundant
3.2. Glycerolipid molecular species changes in barley roots after inoculation with macroconidia of F. graminearum When barley roots were exposed to macroconidia, the phospholipids/galactolipids ratio was not modified. The fatty acid composition of all lipid classes was analysed to identify any modifications. In lipid profiling studies, each molecular species was identified in relation to the total number of acyl carbon atoms and double bonds. The interaction between F. graminearum macroconidia and barley roots resulted in significant changes in the diacyl lipid species composition of extraplastidic classes PC, PE, PI and PA (Fig. 2). The amount of most unsaturated species, such as 34:2- (16:0/18:2), 36:4- (18:2/18:2), 36:3(18:1/18:2), and 36:2- (18:1/18:1 or 18:0/18:2) -PC, -PE, and/or -PI, tended to increase after pathogen inoculation (Fig. 2). In contrast, 4
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Fig. 2. Changes in lipid molecular species during F. graminearum macroconidia treatment. Left panel, phosphatidylcholine and phosphatidic acid; right panel, phosphatidylethanolamine and phosphatidylinositol. Black bars represent plants grown at 25 °C, grey and white bars represent plants incubated at 25 °C for 30 min and 60 min with F. graminearum macroconidia, respectively. Means with different letters are significantly different according to Tukey test at P < 0.05.
3.3. Analysis of correlation between PC and LPC species levels in response to F. graminearum
34:2-, 34:3- 36:4- and 36:5- PA tended to decrease significantly. Compared with control barley roots, 34:2-, 34:3- 36:4- and 36:5- PC noticeably increased in response to F. graminearum. On the other hand, lipid species containing two polyunsaturated acyl chains, such as 36:6 (which is a di18:3 combination) PC, PE, and PA, remained unchanged or slight increased, and they decreased only in plastidic lipids such as DGDG (Fig. 3B). The regulation of the saturation level and the constitution of glycerolipids are important for plants to maintain the integrity and fluidity of their membranes under stressful conditions. In order to evaluate modifications in the saturated/ unsaturated ratio, the unsaturation index was calculated. Thus, lipid species that had 16:0, 18:0, 18:1, and/or 18:2 acyl chains (e.g., 34:2, 36:4 species) were frankly modified in the course of treatment with F. graminearum. This led to a slight modification in the unsaturation index of PE, PC, PI, PA, and PS (although the changes were not statistically significant, Fig. 3D). Interestingly, 34:3- (16:0/18:3) PC and PA were markedly modified during interaction with the pathogen (Fig. 2 A and B). This might have contributed to the unsaturation index showing opposite behaviours during pathogen response (Fig. 3D). Future studies should look into whether the 34:3 species containing 18:3 contributes to a unique mechanism for F. graminearum response in barley root. The level of lysophospholipids remained similar to that of untreated tissues in LPG and LPE (Fig. 4A). However, the F. graminearum treatment caused a significant decrease in 16:0-, 18:2- and 18:3-LPC (Fig. 4B).
The autoscaled lipid levels of individual samples are displayed as a heat map in Fig. 5A and B. The concomitant increase in PC and decrease in LPC could suggest that LPC is partly being converted to PC by acylation. In order to determine the degree to which these variables are associated, the coefficient of correlation generated by the Pearson matrix was calculated. Pearson’s correlation coefficient, q, was calculated for each lipid analyte with each other lipid analyte across all 25 lipid samples, including 15 samples subjected to each treatment (untreated, treated with Fusarium and harvested after 30 and 60 min). The coefficient can range from -1 (perfect negative correlation) to 1 (perfect positive correlation), with 0 indicating no correlation. In Fig. 5A the heat map showed that PC and LPC species were positively correlated in untreated barley roots. Out of 300 total pairs analyzed, 36 resulted in significant correlation coefficients (P < 0.05) in untreated roots. Of these correlating pairs approximately 90% were positive (Fig. 5A). In addition, the pairs LPC-18:3/LPC-18:0, PC-34:1/ PC-36:1 and PC-38:3/PC36:1 were negatively correlated. While that of out of 300 pairs analyzed in treated with Fusarium and harvested after 30 and 60 min, 78 resulted in significant correlation coefficients (P < 0.05). Of these correlating pairs approximately 90% were positive but with values close 0, i.e. they are not strongly correlated (Fig. 5B). In addition, a significant increase in the PC:LPC ratio was observed during the response to the pathogen (Fig. 5C). The unsaturation index
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Fig. 3. Changes in lipid molecular species during F. graminearum macroconidia treatment on plastidic lipids. Left panel, monogalactosyldiacylglycerol and digalactosyldiacylglycerol; right upper panel, phosphatidylglycerol. Black bars represent plants grown at 25 °C, grey and white bars represent plants incubated at 25 °C for 30 min and 60 min with F. graminearum macroconidia, respectively. Means with different letters are significantly different according to Tukey test at P < 0.05. D) Effect of F. graminearum macroconidia treatment on unsaturation index of plastidic and extraplastidic lipids from barley roots. The unsaturation index of each lipid molecular species was calculated as indicated in Material and Methods section.
3.5. Biochemical changes associated with F. graminearum perception by barley roots
shows that this parameter increased in PC and slightly decreased in LPC (Fig. 5D).
Plants have developed an array of defensive response mechanisms against attacks by pathogens. These responses are usually associated with a rapid and transient production of ROS, a modification in phospholipase activity and an increase in SA and JA levels. To test whether phospholipases are involved in the early response to F. graminearum, PLD activity was assessed by incubating protein extract with fluorescent substrate NBD-PC in the presence of 1-butanol (Peppino Margutti et al., 2017). Phospholipids were extracted, separated by ethyl acetate TLC, and analysed based on fluorescence intensity. Fig. 7A shows there were no changes in NBD- PtdBut in response to treatment with F. graminearum. In order to determine whether the treatment induced ROS changes in barley roots, we studied ROS localization using a membranepermeable fluorescent probe. In agreement with what was observed for PLD activity, DCFH-DA staining of the root showed no significant ROS production in response to the pathogen at all studied times (inset Fig. 7A). PLA is also involved in plant immunity through its role in JA biosynthesis (Siebers et al., 2016). When assayed with NBD-PC and NBD-PE, PLA activity increased rapidly and transiently in response to the pathogen (Fig. 7B). The enzyme was more active with NBD-PC. We also evaluated whether heating-deactivated macroconidia and the chitosan elicitor were able to modulate PLA activity. TLC images in Fig. 7C show that both chitosan and deactivated macroconidia had a similar response, although the latter was faster (Fig. 7C, left image) in comparison with chitosan (Fig. 7C, right image). Finally, it was
3.4. Differences associated with PC revealed by Principal Component Analysis To check whether the differences in lipid composition after exposure to Fusarium were related with the duration of the exposure, the data obtained from targeted lipidomics were subjected to multivariate analysis. Fig. 6A shows the scores plot for the dataset of lipid species isolated both from untreated and F. graminearum-treated plants, for the first two principal components. As can be observed, the samples are separated into two distinct groups, according to how molecular species responded with respect to the duration of F. graminearum macroconidia exposure. The first principal component (PC1) accounted for the greatest variance (89.5%) across the data and separated the samples based on PC behavior. The specific weight with which each glycerolipid molecular species contributed to the first two principal components is visualized in the loading plot (Fig. 5B). The PC1 factor of the biplot described around 90% of the overall variance in PC. This revealed that mostly C34:2- and C36:4-PC contributed to cluster separation, represented by 30-min pathogen exposure (Fig. 6A and B).
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Fig. 4. Changes in lysophospholipid molecular species during F. graminearum macroconidia treatment. Effects of pathogen treatment on content of LPG, LPC and LPE and on molecular species of indicated lysophospholipids.
phospholipids such as PC, with acyl chains (34:2 (18:2–16:0), 34:3 (16:0/18:3), 36:4 (di18:2 or 18:1–18:2), 36:5 containing 18:2 and 18:3, and lyso-glycerolipids such as LPC. In plastidic lipids like DGDG, a decrease in 36:6 (18:3–18:3) was also evidenced. This phenomenon regarding acyl chain composition and remodelling was not observed in response to abiotic stresses like chilling, so certain sorts of phospholipids seem to be more responsive to variations in the environment, such as the presence of pathogens (Peppino Margutti et al., 2018, 2019a). An analysis of the pathogen-barley root interaction showed that PC tended to increase. This phospholipid is the main glycerophospholipid present at significant levels in the membrane of barley tissues. It has been shown that it can be synthesized through the cytidine diphosphate-choline pathway or the phosphatidylethanolamine N-methyltransferase pathway, which convert PE into PC. Another possible route is through the activation of a phospholipase that generates DAG, which is subsequently converted into PC (Larsson et al., 2007). However, no variation in the PC-PE ratio was observed in this work. On the other hand, we found a decrease in LPC concomitantly with an increase in PC. Therefore, we propose that part of the lyso-glycerolipid might be converted into PC (Larsson et al., 2007). Moreover, we wondered why the level of PC tended to increase in response to Fusarium. This might be an adaptive mechanism to minimize some of the effects caused by a previous hydrolysis of PC by lypolitic enzymes. Thus, phospholipase activity was evaluated to test our hypothesis. First, PLD was assayed as a contributor to the variations in PA levels. PA is a phospholipid mediator in the response to the pathogen (Li and Wang, 2019). Several metabolic pathways could be implied in the modulation of PA levels. Treating plants with a fungal pathogen or elicitors has been reported to induce PA production (van der Luit et al., 2000; Raho et al., 2011). Recent
determined that SA increased rapidly but transiently in response to the pathogen, while the increase in JA was both rapid and sustained (Fig. 8). 4. Discussion We found that some molecular species of barley root lipids were altered in response to F. graminearum. Phospholipids and galactolipids are the major lipids found in roots. An analysis of lipid classes showed that the phospholipid/galactolipid ratio remained unchanged in response to the pathogen, which suggests membrane stability, was not altered during the assay. Unlike the case with leaves, the lipidomic study of barley roots from plants grown at 25°C demonstrated that the composition of extraplastidic phospholipids at this site was dominated by 34:2 (18:2–16:0) and 36:4 (di18:2 or 18:1–18:2) species, which contain linolenic acid (18:2). The higher proportion of palmitic (16:0) and linoleic acid (18:2) in the lipidome of barley roots might be important for their functioning under optimum and stressful conditions. Supporting that, barley root spatial metabolite profiling revealed differences in response to short-term salt (Shelden et al., 2016) The alteration in the composition and unsaturation levels of extraplastidic phospholipids in barley roots suggests that lipid remodelling and the modification in lipid unsaturation levels are early responses to the fungal pathogen. Thus, this study shows that barley roots respond to the fungal pathogen by altering to levels of lipid species in a tissuespecific manner. Lipid remodelling refers to the decrease in the amounts of certain lipids and the increase in others. In the present study, lipid remodelling in terms of increase and decrease involved different classes of 7
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Fig. 5. Heat map showing the correlation between PC and LPC species based on Pearson’s correlation coefficient, P (Table S5). (A) Correlation between PC and LPC species in control barley roots. (B) Correlation between PC and LPC species in barley roots after F. graminearum treatment. Blue and red colours on the heat map indicate negative and positive correlation, respectively. (C–D) Effect of F. graminearum on PC-LPC ratio and on unsaturation index of PC and LPC.
The effects of these PLDs were interpreted through PA effectors, since PA was shown to bind to NADPH oxidase and to regulate H2O2 production and oxidative stress (Li and Wang, 2019). PLD has been characterized in different types of barley tissues as having diverse roles in
studies with a knockout of PLDβ1 have described a decrease in the production of PA induced by Botritis cinerea, which supports the idea that this PLD isoform is responsible for a major portion of the PA generated during the attack by the fungal pathogen (Zhao et al., 2013).
Fig. 6. Principal component analysis of the lipid composition in barley roots after F. graminearum treatment. A Biplot from the first and second principal components showing score (A) and principal components loading (B) of relationships between intensities of main glycerolipids classes and time of exposure to F. graminearum from barley root. 8
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Fig. 7. Effect of F. graminearum on phospholipase activities and ROS generation of barley roots. (A) PLD activity was assayed with NBD-PC. After reaction, lipids were extracted and separated by ethyl acetate TLC system. Inset of Fig. 1A: Epifluorescence microscopy images of qualitative distribution of ROS in roots treated with F. graminearum macroconidia for 0 (a), 5 (b), 15 (c), 30 (d) and 60 min (e). Images were taken with a Canon G10 camera and quantified (optical density in arbitrary units) using the ImageJ program, with the optical density of control roots defined as 39.07 AU (arbitrary units). (B) Effects of F. graminearum on PLA activity assayed with NBD-PC and NBD-PE. (C) Representative TLC blots are shown for: (left panel) effect of desnaturated macroconidia on PLA activity measured with NBD-PC as fluorescent substrate; (right panel) effect of chitosan on PLA activity. Fluorescent lipids were separated by solvent system containing chloroform:methanol:H2O (65:25:4, v/v).
with this, H2O2 production mediated by PLD/PA was also not observed in barley treated with the pathogen, while PA levels appeared to decrease. By contrast, when PLA activity was tested, a rapid and transient increase was observed in response to F. graminearum, as well as to the elicitor chitosan and the presence of inactivated macroconidia. A major PA pool in barley comes from PLD-dependent hydrolysis of the structural phospholipid PC (Villasuso et al., 2013; Peppino Margutti et al., 2018). Therefore, it is possible that PLA competes with PLD for PC availability and directly affects PLD activity and PA accumulation (Kirik and Mudgett, 2009). In consistency with this hypothesis, PLA was frankly more active than PLD in response to F. graminearum when they were assayed with vesicles containing fluorescent NBD-labelled PC analogues. This could also explain what was observed in terms of H2O2 accumulation. On the other hand, PLA plays an important role in regulating oxylipin biosynthesis in plants. To explore lipid remodelling in relation with the defence response, we tested JA production. It was observed that F. graminearum triggered JA accumulation. Several pathways could contribute to this. A profile of the lipid species that were altered in response to F. graminearum revealed decreases in the levels of DGDG (enriched in 18:3-18:3), which suggests that the hydrolysis of plastidic lipids might provide precursors for pathogen-induced JA production (Yang et al., 2007). Accordingly, free linoleic acid decreased after 30 min of F. graminearum treatment (data not shown), in such a way that more than one pathway could regulate JA synthesis (Yang et al., 2007). Taken together, the data indicate that PLA is modulated in
Fig. 8. Levels of SA and JA were analysed simultaneously by electrospray ionization/tandem mass spectrometry (LC-ESI-MS-MS), essentially as described by Meringer et al. (2016). Results are expressed as ng/dry weight of barley root, they correspond to n=3. Means with different letters are significantly different according to Tukey test at P < 0.05.
lipid metabolism and cellular regulation (Villasuso et al., 2013) and environmental stress responses (Meringer et al., 2016; Peppino Margutti et al., 2017). The response found in the PLD of roots inoculated with F. graminearum is an apparently contradictory behaviour that takes place during plant response to the pathogen. In agreement 9
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barley root in response to F. graminearum. In addition, the results suggest that lipid remodelling may contribute to JA production. In summary, our results suggest early lipid signalling activation when barley is responding to a pathogen attack, and open new insights into the role of lipids in plant-pathogen interactions. Further studies are needed to fully characterize the involvement of lipids in this pathosystem.
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Author contributions Conceived and designed the experiments: MR, ALV. Performed the experiments: MPM, MR. Analyzed the data: MPM, MR, ALV. Contributed reagents/materials/analysis tools: ALV. Result discussion ALV. Wrote the paper: ALV. Acknowledgements This work was supported by Universidad Nacional de Río Cuarto (SECyT-UNRC, grant number 18/C426); PPI-CONICET (grant number 11220150100206CO), Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT, grant number PICT 1108/15Préstamo BID, Argentina. INTA-Bordenave generously provided seeds. ALV is a Career Investigator of CONICET. MPM and MR are CONICET fellowship holders. The authors are grateful to Florencia Sgarlatta for language/ editing assistance. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.envexpbot.2019.06. 001. References Bargmann, B.O., Laxalt, A.M., Riet, B.T., Schouten, E., Van Leeuwen, W., Dekker, H.L., De Koster, C.G., Haring, M.A., Munnik, T., 2006. LePLDbeta1 activation and relocalization in suspension-cultured tomato cells treated with xylanase. Plant J. 45, 358–368. https://doi.org/10.1111/j.1365-313X.2005.02631.x. Cacas, J.L., Gerbeau-Pissot, P., Fromentin, J., Cantrel, C., Thomas, D., Jeannette, E., Kalachova, T., Mongrand, S., Simon-Plas, F., Ruelland, E., 2017. Diacylglycerol kinases activate tobacco NADPH oxidase-dependent oxidative burst in response to cryptogein. Plant Cell Environ. 40, 585–598. https://doi.org/10.1111/pce.12771. D’ambrosio, J.M., Gonorazky, G., Sueldo, D.J., Moraga, J., Di Palma, A.A., Lamattina, L., Collado, I.G., Laxalt, A.M., 2018. The sesquiterpene botrydial from Botrytis cinerea induces phosphatidic acid production in tomato cell suspensions. Planta 247, 1001–1009. https://doi.org/10.1007/s00425-018-2843-8. Durgbanshi, A., Arbona, V., Pozo, O., Miersch, O., Sancho, J.V., Gómez-Cadenas, A., 2005. Simultaneous determination of multiple phytohormones in plant extracts by liquid chromatography−electrospray tandem mass spectrometry. J. Agric. Food Chem. 53, 8437–8442. https://doi.org/10.1021/jf050884b. Durrant, W.E., Dong, X., 2004. Systemic acquired resistance. Annu. Rev. Phytopathol. 42, 185–209. https://doi.org/10.1146/annurev.phyto.42.040803.140421. Hammann, S., Korf, A., Bull, I.D., Hayen, H., Cramp, L.J.E., 2019. Lipid profiling and analytical discrimination of seven cereals using high temperature gas chromatography coupled to high resolution quadrupole time-of-flight mass spectrometry. Food Chem. 282, 27–35. https://doi.org/10.1016/j.foodchem.2018.12.109. Jones, J.D.G., Dangl, J.L., 2006. The plant immune system. Nature 444, 323. https://doi. org/10.1038/nature05286. Kazan, K., Gardiner, D.M., 2018. Transcriptomics of cereal–Fusarium graminearum interactions: what we have learned so far. Mol. Plant Pathol. 19, 764–778. https://doi. org/10.1111/mpp.12561. Kirik, A., Mudgett, M.B., 2009. SOBER1 phospholipase activity suppresses phosphatidic acid accumulation and plant immunity in response to bacterial effector AvrBsT. Proc. Natl. Acad. Sci. U. S. A. 106, 20532–20537. https://doi.org/10.1073/pnas. 0903859106. Lam, S.M., Tian, H., Shui, G., 2017. Lipidomics, en route to accurate quantitation. Biochim. Biophys. Acta Mol. Cell Biol. Lipids 1862, 752–761. https://doi.org/10. 1016/j.bbalip.2017.02.008. Lamb, C., Dixon, R., 1997. The OXIDATIVE BURST IN PLANT DISEASE RESISTANCE. Annu. Rev. Plant Physiol. Plant Mol. Biol. 48, 251–275. https://doi.org/10.1146/ annurev.arplant.48.1.251. Lanoue, A., Burlat, V., Henkes, G.J., Koch, I., Schurr, U., Rose, U.S., 2010. De novo biosynthesis of defense root exudates in response to Fusarium attack in barley. New Phytol. 185, 577–588. https://doi.org/10.1111/j.1469-8137.2009.03066.x. Larsson, K.E., Kjellberg, J.M., Tjellstrom, H., Sandelius, A.S., 2007. LysoPC
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oxygen generation. Physiol. Plant. 118, 361–370. https://doi.org/10.1034/j.13993054.2003.00131.x. Yang, W., Devaiah, S.P., Pan, X., Isaac, G., Welti, R., Wang, X., 2007. AtPLAI is an acyl hydrolase involved in basal jasmonic acid production and Arabidopsis resistance to Botrytis cinerea. J. Biol. Chem. 282, 18116–18128. https://doi.org/10.1074/jbc. M700405200. Zhao, J., Devaiah, S.P., Wang, C., Li, M., Welti, R., Wang, X., 2013. Arabidopsis phospholipase Dβ1 modulates defense responses to bacterial and fungal pathogens. New Phytol. 199, 228–240. https://doi.org/10.1111/nph.12256.
Welti, R., Li, W., Li, M., Sang, Y., Biesiada, H., Zhou, H.E., Rajashekar, C.B., Williams, T.D., Wang, X., 2002. Profiling membrane lipids in plant stress responses. Role of phospholipase D alpha in freezing-induced lipid changes in Arabidopsis. J. Biol. Chem. 277, 31994–32002. https://doi.org/10.1074/jbc.M205375200. Wewer, V., Dörmann, P., Hölzl, G., 2013. Analysis and quantification of plant membrane lipids by thin-layer chromatography and gas chromatography. In: Munnik, T., Heilmann, I. (Eds.), Plant Lipid Signaling Protocols. Methods in Molecular Biology (Methods and Protocols). Humana Press, Totowa, NJ, pp. 1009. Yamaguchi, T., Minami, E., Shibuya, N., 2003. Activation of phospholipases by N-acetylchitooligosaccharide elicitor in suspension-cultured rice cells mediates reactive
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Lipid profiling of barley root in interaction with Fusarium macroconidia Matias Reyna, Micaela Peppino Margutti, Ana Laura Villasuso
⁎
T
Dpto. de Biología Molecular, FCEFQN, Universidad Nacional de Río Cuarto, X5804BYA Río Cuarto, Córdoba, Argentina
A R T I C LE I N FO
A B S T R A C T
Keywords: Barley Electrospray ionization tandem mass spectrometry Fusarium graminearum Lipid remodelling Phosphatidic acid
Fusarium is the major causal agent of Fusarium head blight (FHB) in several cereal crops. Macroconidia, the asexual form of Fusarium, can infect the roots and aerial parts of plants. The response of cereal to attacks by Fusarium has been investigated at transcriptomic and metabolomic level, but there are no reports of root lipidomic assays carried out during Fusarium-root interaction. In order to determine how root phospholipids contribute to that interaction, we performed a lipidomics-based ESI-MS/MS assay coupled with a statistical analysis. It was found that phospholipid and galactolipid levels were not modified during early pathogen response, although some individual phospholipid molecular species did undergo significant changes. In plants exposed to macroconidia there was a rapid and transient increase in the phosphatidylcholine (36:4-PC) molecular species, in comparison with the control. By contrast, there was a decrease in lysophosphatidylcholine (16:0-, 18:2- and 18:3-LPC) levels. Furthermore, a phospholipase assay and the measurement of endogenous phytohormone levels through the use of fluorescent lipids and liquid chromatography-tandem mass spectrometry, revealed an increase in phospholipase A (PLA) activity, as well as in the endogenous amounts of Jasmonic acid (JA) and Salicylic acid (SA). The results indicate that barley root is able to modulate the glycerolipid fatty acid composition during the early response to Fusarium, suggesting a particular pathogen-sensing mechanism that could be useful to understand the role of lipids in plant-pathogen interactions.
1. Introduction Plants are continuously challenged by invading microorganisms, some of which are pathogens that affect plant survival and produce a negative effect on crop production. In general, the perception of pathogens relies on transmembrane pattern recognition receptors that specifically recognize highly conserved pathogen-derived molecules called PAMPs/MAMPs (pathogen-/microbial-associated molecular patterns), such as bacterial flagellin or chitosan (Jones and Dangl, 2006). These elicitors are signal-inducing compounds recognised by the innate immune system. A second layer of defence is based on pathogen-derived molecules that are specifically recognized by the corresponding plant resistance protein and induce effector-triggered immunity (Thomma et al., 2011). The activation of plant immunity involves a variety of early signalling events, including rapid accumulation of reactive oxygen species (ROS), changes in cellular ion fluxes, activation of protein kinase cascades, and changes in gene expression (Lamb and Dixon, 1997; Durrant and Dong, 2004; Truman et al., 2007). Membrane lipids are also key
players during the perception of and response to a pathogen attack. Accumulating evidence suggests that the metabolism of plant lipids is modulated mainly by the activity of lipases (Siebers et al., 2016; Li and Wang, 2019). However, these studies generally focus on the phosphatidic acid (PA) signal. This minor phospholipid is produced by enzymatic activation of phospholipase C in concerted action with diacylgycerol kinase (PLC/DGK), or by activation of phospholipase D (PLD) (Testerink and Munnik, 2011). This PA-based lipid signalling has been described as one of the earliest plant responses upon treatment with several elicitors. The MAMPs xylanase, chitotetraose, chitosan and N-acetylchitooligosaccharides, produced by fungi, cryptogein, from the oomycete Phyotophtora cryptogea, botrydial from Botrytis cinerea and the bacterial flagellin-derived peptide flg22, induce PA production via PLC/ DGK and/or PLD (Yamaguchi et al., 2003; Bargmann et al., 2006; Laxalt et al., 2007; Raho et al., 2011; Cacas et al., 2017; D’Ambrosio et al., 2018). In most of these reports, PA was determined by labelling the cell/ tissue with 32 P, monitoring the phospho-transfer from 32 P-γ-ATP to the respective substrate, and then measuring the enzymatic activity
Abbreviations: DGDG, digalactosyldiacylglycerol; JA, jasmonic acid; LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; LPG, lysophosphatidylglycerol; MGDG, monogalactosyldiacylglycerol; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PI, phosphatidylinositol; PG, phosphatidylglycerol; PS, phosphatidylserine PLA phospholipase A; PLC, phospholipase C; PLD, phospholipase D; SA, salicylic acid; TLC, thin layer chromatography ⁎ Corresponding author. E-mail address: [email protected] (A.L. Villasuso). https://doi.org/10.1016/j.envexpbot.2019.06.001 Received 27 February 2019; Received in revised form 31 May 2019; Accepted 5 June 2019 Available online 09 July 2019 0098-8472/ © 2019 Elsevier B.V. All rights reserved.
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For the chitosan assay, chitosan was prepared from crab shells (Sigma, St. Louis, MO, USA) following Raho et al. (2011). Briefly, barley roots were treated with 100 μg mL-1 chitosan at the times indicated. For inactivated macroconidia, a 1 × 107 macroconidia mL-1 suspension was deactivated with autoclave.
(Testerink and Munnik, 2011). However, PA derived from the aforementioned two pathways may possess structural diversity (in terms of fatty acyl chain length and degree of saturation), as well as distinct spatio-temporal characteristics in the assessed tissue (Pokotylo et al., 2018). Additionally, the perception of and response to a pathogen attack might not be limited only to this minor phospholipid (Siebers et al., 2016). On the other hand, our knowledge about the role lipids play in different cellular responses in plants has improved ever since highly sensitive analytical technologies, including mass spectrometry, have been made available (Lam et al., 2017). Lipidomic analysis has made it possible to detect lipids in relatively narrow mass ranges which can often suffer from isobaric interferences, as well as when the high concentration of certain lipids supresses the detection of low abundance lipids (Lam et al., 2017). Moreover, it has also shown how global changes in membrane lipid composition or specific lipid remodelling contribute to the physiological response to abiotic stress, such as high or low temperature, salinity, availability of nutrients, and so on (Welti et al., 2002; Wang et al., 2006; Narasimhan et al., 2013; Narayanan et al., 2016, 2018). In contrast, lipid profiling has not been extensively performed in connection with plant pathogen response in cereal (Hammann et al., 2019), especially when it comes to crops of considerable economic importance, like barley. The present study investigates glycerolipid molecular species in barley roots, with the aim of determining how they are quantitatively and qualitatively modulated by their interaction with macroconidia, the asexual form of Fusarium graminearum. Furthermore, we analysed other downstream events of PAMP-triggered immunity, like the generation of reactive oxygen species, hormonal changes and phospholipase activity, in order to elucidate how the steady-state membrane lipid composition is modified in connection with other aspects of barley root defence.
2.2. Lipid extraction and separation Total lipids were extracted from barley roots (80 mg) by adding 0.8 mL of methanol/chloroform/ formic acid (20:10:1, v/v/v), and shaken vigorously for 5 min. After that, 0.4 mL of 0.2 M H3PO4/1 M KCl was added to obtain a lower chloroform phase and an upper phase. Centrifugation at 13,000×g for 1 min made it easier to separate the lower organic phase containing the lipid, which was transferred to a new glass vial. The solvent was evaporated under an N2 stream. Phospholipids and galactolipids were separated by TLC. Chromatograms were developed with a solvent system made up of acetone/acetic acid/H2O (100:2:1, v/v/v) or acetone/acetic acid/H2O (91:30:7.5, v/v/v) (Wang and Benning, 2011), and stained with iodine or α-naphthol. The positions of lipids on the chromatograms were determined by comparing migration with commercial standards. Before being used, TLC plates were briefly submerged in an ammonium sulfate solution and dried for at least 2 days in a place protected from dust. The plate was activated at 120 °C to convert (NH4)2SO4 into NH3 and H2SO4. This treatment led to the evaporation of ammonia and the acidification of the silica material by sulfuric acid. Thus, anionic lipids altered their migration, and the separation of the phospho- and glycolipids was improved (Wewer et al., 2013). 2.3. Lipid profiling Lipid extraction was performed as described by (Welti et al., 2002). For each sample, roots (approximately 200 mg) were immersed in 3 ml of isopropanol (0.01% w/v 2,6-Di-tert-butyl-4-methylphenol) at 75 °C for 15 min. These conditions prevent the lipid from being modified by degrading enzymes such as phospholipases (Lam et al., 2017). Then, 1.5 ml of chloroform and 0.6 ml of distilled water were added. The tubes were shaken for 1 h at room temperature, and then the extract was removed. The tissues were re-extracted with chloroform/methanol (2:1) with 0.01% 2,6-Di-tert-butyl-4-methylphenol five times, with 30 min of agitation each time, until all the remaining plant tissue appeared white. The combined extracts were washed once with 1 ml of 1 M KCl and once with 2 ml of water. The organic phase was recovered, and the solvent was evaporated under a nitrogen stream. The lipid extracts were sealed in a glass tube with a Teflon tape screw cap (2.0 mL clear vial. SUPELCO, SIGMA-ALDRICH) and stored at −20 °C until the analysis. The remaining plant tissues were heated overnight at 105 °C and weighed. These weights are listed as plant “dry weight”. Lipid samples were analysed on a triple quadrupole MS/MS equipped for ESI. The lipid analyses described here were performed at the Kansas Lipidomics Research Center's Analytical Laboratory. Data processing was performed as previously described by (Li et al., 2008). Phospholipid and galactolipid molecular species were quantified in comparison to the two internal standards. The quantity of each lipid was determined as a normalized mass spectral signal (i.e., normalized to the two internal standards (Maatta et al., 2012). The normalized signal was divided by extracted dry mass (to produce normalized mass spectral (MS) signal/mg extracted dry mass). This approach makes it possible to compare lipid species quantities and classes between samples (Narasimhan et al., 2013).
2. Materials and methods 2.1. Pathogen growth and inoculation Barley plants (Hordeum vulgare L. cv. ‘scarlett’) were grown from seeds (INTA Bordenave, Argentina). To avoid microbial contamination, seeds were surface-sterilized by incubation in H2SO4 (50% v ⁄ v) for 1 h and then washed five times in sterile bi-distilled water to remove the remaining sulphuric acid. Seeds were subsequently shaken in AgNO3 (1% w ⁄ v), at 200 rpm on an orbital platform for 20 min and rinsed successively with NaCl (1% w ⁄ v), sterile bi-distilled water, NaCl (1% w ⁄ v), and five times in sterile bi-distilled water to remove the AgNO3 completely. Seeds were placed on a Petri plate, germinated in sterilized water and grown for 4 d in the dark at 25 ± 2 °C until roots and shoots emerged (Lanoue et al., 2010; Peppino Margutti et al., 2017). To obtain Fusarium graminearum macroconidia, an active culture of the fungus grown on solid Spezielier Nährstoffarmer (SNA) medium (g L−1: 1 KH2PO4, 1 KNO3, 0.5 MgSO4-7H2O, 0.5 KCl, 0.2 glucose, 0.2 sucrose, 20 Agar, at pH 5.4) was transferred by cutting the medium into small agar pieces that were placed in liquid SNA medium at 28 °C, with 150 rpm shaking. After 7 d, the culture was passed through a 0.5 mm polyester filter. Then, macroconidia were harvested by centrifugation (11,000×g, 15 min) and resuspended in a minimal volume of sterile glycerol 15% v / v. To infect the plant root system, a suspension of macroconidia was prepared at a concentration of 1 × 107 conidia mL−1 in a Neubauer chamber. Finally, 4 day-old seedlings were placed in a sterile Petri plate, inoculated with the macroconidia suspension and harvested after the times indicated (Lanoue et al., 2010). We chose these inoculation times to analyse the early response of barley root, prior to macroconidia germination. For the control samples, sterile water was used and the treatment was alternatively stopped and started for 30 s intervals. Afterwards, roots were separated and washed five times in sterile bi-distilled water.
2.4. Unsaturation index The unsaturation index is a calculation that determines the number of double bonds in a lipid. For each lipid molecular species in barley roots, this was calculated as indicated by (Narayanan et al., 2018). 2
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were identified by comparison to standards (Avanti Polar Lipids, Inc – Alabama-USA) and visualized with iodine vapor. The difference in relative mobilities between NBD-labelled and unlabelled standards was less than 5%. A standard curve was constructed using a range of phosphatidylcholine (PC) concentrations (Peppino Margutti et al., 2019b). The relationship between the amount of standard PC and the fluorescence measured was linear throughout the range 6 ng–50 ng. These values could be used to express the results as enzymatic activity in μKat (microkatal).
Briefly, it was estimated as the product of the amount of that lipid molecular species and the average number of double bonds per acyl chain, where the average number of double bonds per acyl chain was calculated as the number of double bonds in the lipid molecular species divided by the number of acyl chains. Finally, the unsaturation index of a lipid head group class was calculated as the sum of the unsaturation indices of individual lipid molecular species in that class (Narayanan et al., 2016). 2.5. Heat map and correlation map
2.7. Detection of reactive oxygen species Utilities of the MetaboAnalyst web server (metabolanalyst.ca) were used to obtain the normalized data by median (Table S2) of lipid data (Table S1) to produce heat maps (Vu et al., 2014; Narayanan et al., 2018). Individual values contained in a matrix (Table S2) are represented with colours on the map. The features are colour-coded by row, with red indicating high intensity and blue indicating low intensity. Correlation analyses between selected lipids (PC and LPC, Table S3) based on Pearson correlation were also conducted using the software package MetaboAnalyst (Table S4).
ROS levels were determined by staining with 2',7'-dichlorofluorescin diacetate (DCFH-DA; Molecular Probes, Invitrogen) as described by (Peppino Margutti et al., 2017). Roots were treated with 10 mM DCFH-DA for 5 min and then examined with an epifluorescence microscope (Axio Lab; Zeiss) with a 492–495 excitation filter and a 517–527 emission filter. Images were taken with a Canon G10 camera and quantified with the ImageJ densitometry software. 2.8. Extraction and quantification of JA and SA
2.6. Phospholipase assay SA and JA levels were analysed simultaneously by electrospray ionization/tandem mass spectrometry (LC-ESI–MS-MS), essentially as described by Durgbanshi et al. (2005). In brief, 200 mg of barley roots were ground in liquid nitrogen, extracted with acetone/water/acetic acid (80: 19: 1, v/v/ v), added with 5 mL of a mixture of internal standards (50 ng/sample of 2H6-JA and 2H4-SA), and centrifuged at 500 g for 15 min. The resulting supernatant was collected and evaporated, and the solid residue was dissolved in 500 mL of methanol and evaporated. The resulting residue was dissolved in methanol/1% acetic acid (99:1, v/v), and then passed through a DEAE Sephadex A-25 column. Aliquots of the resulting solution were injected directly into the LC-ESI-MS-MS system. MS/MS experiments were performed on a Micromass Quatro Ultima Pt double quadrupole mass spectrometer (Micromass, Manchester, UK).
PLD and PLA activities were measured by observing phosphatidyl butanol (NBD-PBut) and free fatty acid (NBD-FFA) production from NBD-PC, mainly as described by (Yang et al., 2007; Peppino Margutti et al., 2017). Briefly, PLD activity was determined by TLC as the synthesis of phosphatidylbutanol (NBD-PtdBut) in relation to NBD-PA and NBD-PC levels. NBD-PC (Avanti Polar Lipids, Inc-Alabama, USA) was stored at −80 °C in chloroform (1 mg mL-1), dried under an N2 stream before its use, resuspended in Hepes (50 mM, pH 7.4), and added to the PLD assay mixture as a liposome. The standard PLD assay mixture consisted of 20 mM Mes-NaOH (pH 6.5), 50 mM CaCl2, 0.25 mM SDS, 1.5 μL fluorescent substrate (NBD-PC, 10–50 μg), 1% (v/ v) 1-butanol, and 40 μg protein, in a total volume of 40 μL. The reaction was initiated by addition of the substrate. Incubation continued for 30 min at 30 °C with shaking (100 rpm), and the reaction was stopped by addition of 150 μL chloroform/methanol (1:2, v/v), 40 μL chloroform, and 40 μL 2 M KCl. The mixture was centrifuged at 15,000×g for 2 min, and the phases were separated. 100 μL chloroform were added to the aqueous phase, which was then centrifuged at 15,000×g for 2 min. The lower chloroform phases from each step were pooled. Samples were dried under an N2 stream, resuspended in a minimal volume of chloroform/methanol (95:5, v/v), spotted on TLC plates (silica gel G; Fisher Scientific), and developed with 2,2,4-trimethylpentane/acetic acid/H2O/ethyl acetate (2:3:10:13, v/v). For the PLA assay, protein (100 μg) was incubated with 3 μL of liposomes (NBD-PC, (Avanti Polar Lipids, Inc-Alabama,USA)) in a total volume of 100 μL of MES-KOH, pH 6.8, and 1 mM CaCl2 at 33 °C for 30 min. Reactions were stopped by adding 2 volumes of the stopping solution (methanol:chloroform 2:1, v/v). One volume of 0.1 M KCl was subsequently added, and incubation at −20 °C for 20 min followed. After centrifugation for 30 s at 10,000×g, the organic phase was evaporated under an N2 stream and redissolved in 10 μL chloroform for TLC on silica gel 60 (Merck, Darmstadt, Germany) in a solvent of chloroform:methanol:H2O (65:25:4, v/v). Plates were dried and scanned. Fluorescence from lipids (excitation 460 nm, emission 534 nm) was measured with a fluorescence spectrophotometer (Image Station 4000 MM PRO-Carestream Molecular Imaging). Fluorescently labelled lipids were visualized with a UV light box (FBTIV-88, Fisher Scientific), and the regions corresponding to NBD-PC, -PA, -PtdBut, and -FFA were marked. The spots marked were scraped from the plates, placed in 600 μL chloroform: methanol: H2O (5:5:1, v/v/v), vortexed and centrifuged for 5 min at 15,000×g. Fluorescence from the eluted lipids (excitation 460 nm, emission 534 nm) was measured with a fluorescence spectrofluorometer (Horiba-Fluoromax-3). Lipid spots
2.9. Statistical analysis For lipidomic analysis, five replicates of each treatment were processed and analysed. Paired values were subjected to the one-way ANOVA with Tukey’s test to determine the statistical significance, and graphics were created with Origin Pro 8 Copyright 1991–2008. Principal Component Analysis (PCA) was performed as an exploratory multivariate analysis tool to reduce the dimensionality of the large datasets generated by ESI-MS/MS. The dataset scores and the specific weight with which each glycerolipid molecular species contributed to the first two principal components are visualized in the scores and loading plots, respectively. Both biplots (scores and loading plots) based on the correlation matrices were made using the software package MetaboAnalyst (Table S6 and S7). For others assay, statistical analyses were carried out by using the software package with Origin Pro 8 Copyright 1991–2008. At least, five replicates of each treatment were analysed using Analysis of Variance (ANOVA) and Tukey’s test pairwise comparisons. All tests were subjected to a 95% confidence limit. 3. Results Lipidomic analysis based on electrospray ionization-triple quadrupole mass spectrometry (ESI-MS/MS) allows for the rapid and sensitive profiling, quantification, and characterization of plastidic and extraplastidic lipids in barley tissues (Peppino Margutti et al., 2018, 2019a). However, to the best of our knowledge, there are no lipidomics data available for biotic stress in barley roots, since the interaction between F. graminearum and barley tissues has been explored at the 3
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Fig. 1. Changes associated with lipid class and glycerolipid molecular species from barley roots during F. graminearum macroconidia treatment. A) Separation of plastidic and extraplastidic lipids from barley roots. Lipids were isolated from barley roots with a CHCl3/methanol/formic acid solution, separated by TLC and stained with iodine (left panel) or α-naphthol (right panel). B) The total polar glycerolipid amounts are expressed as percentage of total normalized mass spectra. The values are the mean ± SEM; n = 5. Means with different letters are significantly different according to Tukey test at P < 0.05. C) Heat map showing F. graminearum effect on lipid profiling: Each colored bar within a column represents a lipid molecular species in the indicated class lipid and treatment. The colour of each bar represents the levels of corresponding lipid species (% of total normalized intensity). A total of 156 lipid species in the indicated lipid classes were organized using class (as indicated), total acyl carbons (in ascending order within a class), and total double bonds (in ascending order within class and total acyl carbons).
(∼40%). The next most abundant class was PI (∼15%), followed by PE and PA (∼10% to 15%). The least abundant classes were PS and LPC (∼0.5%; Figs. 1B and 3 D). Although total phospholipid content remained unchanged, some phospholipid species were significantly different under pathogen treatment. Analysis of the specific contribution of every lipid class to the total amount of measured glycerolipids showed an important difference between zwitterionic glycerolipids like PC and monoacyl molecular species LPC (Figs. 1B and 4 A). An overview of the data based on ESI-MS/MS, which is shown in Fig. 1(B and C), revealed complex and considerable changes in lipid molecular species during the interaction between F. graminearum and barley roots. Changes in the lipid profile during pathogen treatment were more significant 30 min after macroconidia inoculation than those after 60 min. The level of most lipids tended to increase or remain unchanged except for that of LPC, which declined.
transcriptomic and metabolomic level (Kazan and Gardiner, 2018). This is despite the great opportunity that barley tissue analysis offers in terms of deciphering how the metabolism of lipids in roots specifically contributes to the physiology of barley response to fungal pathogens such as F. graminearum.
3.1. Lipid class changes in barley roots after inoculation with macroconidia of F. graminearum From a TLC analysis we learned that phospholipids and glycolipids are the most abundant lipids in barley roots (Fig. 1A). In order to determine the specific contribution of lipids in the response to the pathogen, it was necessary to use a powerful strategy to fully characterize lipid molecular species. Approaches based on electrospray ionization tandem mass spectrometry have been developed to comprehensively analyse lipid composition in plant tissues. We used a lipidomic approach to explore the modulation of lipid composition in barley roots after inoculation with macroconidia of F. graminearum. Lipids from roots either grown under control conditions (seedlings incubated at 25 °C) or submitted to the pathogen (seedlings incubated at 25 °C for 30 and 60 min with macroconidia) were quantitatively profiled using ESIMS/MS. The data provided information on phospholipids and glycolipids at the level of the head group and the number of carbon atoms and double bonds present in the acyl chains. We identified 156 glycerolipid molecular species, present in all five biological replicates from control and F. graminearum-inoculated barley roots (Fig. 1C). The lipids identified fitted into most major glycerolipid classes, including galactolipids (monogalactosyldiacylglycerol, MGDG‐; digalactosyldiacylglycerol, DGDG‐), and phospholipids (PL, PC‐; PA‐; PE‐; PG‐; PI‐; PS‐; including the monoacyl molecular species LPC‐, LPG-, LPE) (Fig. 1B). When comparing the proportions within PL classes, PC was the most abundant
3.2. Glycerolipid molecular species changes in barley roots after inoculation with macroconidia of F. graminearum When barley roots were exposed to macroconidia, the phospholipids/galactolipids ratio was not modified. The fatty acid composition of all lipid classes was analysed to identify any modifications. In lipid profiling studies, each molecular species was identified in relation to the total number of acyl carbon atoms and double bonds. The interaction between F. graminearum macroconidia and barley roots resulted in significant changes in the diacyl lipid species composition of extraplastidic classes PC, PE, PI and PA (Fig. 2). The amount of most unsaturated species, such as 34:2- (16:0/18:2), 36:4- (18:2/18:2), 36:3(18:1/18:2), and 36:2- (18:1/18:1 or 18:0/18:2) -PC, -PE, and/or -PI, tended to increase after pathogen inoculation (Fig. 2). In contrast, 4
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Fig. 2. Changes in lipid molecular species during F. graminearum macroconidia treatment. Left panel, phosphatidylcholine and phosphatidic acid; right panel, phosphatidylethanolamine and phosphatidylinositol. Black bars represent plants grown at 25 °C, grey and white bars represent plants incubated at 25 °C for 30 min and 60 min with F. graminearum macroconidia, respectively. Means with different letters are significantly different according to Tukey test at P < 0.05.
3.3. Analysis of correlation between PC and LPC species levels in response to F. graminearum
34:2-, 34:3- 36:4- and 36:5- PA tended to decrease significantly. Compared with control barley roots, 34:2-, 34:3- 36:4- and 36:5- PC noticeably increased in response to F. graminearum. On the other hand, lipid species containing two polyunsaturated acyl chains, such as 36:6 (which is a di18:3 combination) PC, PE, and PA, remained unchanged or slight increased, and they decreased only in plastidic lipids such as DGDG (Fig. 3B). The regulation of the saturation level and the constitution of glycerolipids are important for plants to maintain the integrity and fluidity of their membranes under stressful conditions. In order to evaluate modifications in the saturated/ unsaturated ratio, the unsaturation index was calculated. Thus, lipid species that had 16:0, 18:0, 18:1, and/or 18:2 acyl chains (e.g., 34:2, 36:4 species) were frankly modified in the course of treatment with F. graminearum. This led to a slight modification in the unsaturation index of PE, PC, PI, PA, and PS (although the changes were not statistically significant, Fig. 3D). Interestingly, 34:3- (16:0/18:3) PC and PA were markedly modified during interaction with the pathogen (Fig. 2 A and B). This might have contributed to the unsaturation index showing opposite behaviours during pathogen response (Fig. 3D). Future studies should look into whether the 34:3 species containing 18:3 contributes to a unique mechanism for F. graminearum response in barley root. The level of lysophospholipids remained similar to that of untreated tissues in LPG and LPE (Fig. 4A). However, the F. graminearum treatment caused a significant decrease in 16:0-, 18:2- and 18:3-LPC (Fig. 4B).
The autoscaled lipid levels of individual samples are displayed as a heat map in Fig. 5A and B. The concomitant increase in PC and decrease in LPC could suggest that LPC is partly being converted to PC by acylation. In order to determine the degree to which these variables are associated, the coefficient of correlation generated by the Pearson matrix was calculated. Pearson’s correlation coefficient, q, was calculated for each lipid analyte with each other lipid analyte across all 25 lipid samples, including 15 samples subjected to each treatment (untreated, treated with Fusarium and harvested after 30 and 60 min). The coefficient can range from -1 (perfect negative correlation) to 1 (perfect positive correlation), with 0 indicating no correlation. In Fig. 5A the heat map showed that PC and LPC species were positively correlated in untreated barley roots. Out of 300 total pairs analyzed, 36 resulted in significant correlation coefficients (P < 0.05) in untreated roots. Of these correlating pairs approximately 90% were positive (Fig. 5A). In addition, the pairs LPC-18:3/LPC-18:0, PC-34:1/ PC-36:1 and PC-38:3/PC36:1 were negatively correlated. While that of out of 300 pairs analyzed in treated with Fusarium and harvested after 30 and 60 min, 78 resulted in significant correlation coefficients (P < 0.05). Of these correlating pairs approximately 90% were positive but with values close 0, i.e. they are not strongly correlated (Fig. 5B). In addition, a significant increase in the PC:LPC ratio was observed during the response to the pathogen (Fig. 5C). The unsaturation index
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Fig. 3. Changes in lipid molecular species during F. graminearum macroconidia treatment on plastidic lipids. Left panel, monogalactosyldiacylglycerol and digalactosyldiacylglycerol; right upper panel, phosphatidylglycerol. Black bars represent plants grown at 25 °C, grey and white bars represent plants incubated at 25 °C for 30 min and 60 min with F. graminearum macroconidia, respectively. Means with different letters are significantly different according to Tukey test at P < 0.05. D) Effect of F. graminearum macroconidia treatment on unsaturation index of plastidic and extraplastidic lipids from barley roots. The unsaturation index of each lipid molecular species was calculated as indicated in Material and Methods section.
3.5. Biochemical changes associated with F. graminearum perception by barley roots
shows that this parameter increased in PC and slightly decreased in LPC (Fig. 5D).
Plants have developed an array of defensive response mechanisms against attacks by pathogens. These responses are usually associated with a rapid and transient production of ROS, a modification in phospholipase activity and an increase in SA and JA levels. To test whether phospholipases are involved in the early response to F. graminearum, PLD activity was assessed by incubating protein extract with fluorescent substrate NBD-PC in the presence of 1-butanol (Peppino Margutti et al., 2017). Phospholipids were extracted, separated by ethyl acetate TLC, and analysed based on fluorescence intensity. Fig. 7A shows there were no changes in NBD- PtdBut in response to treatment with F. graminearum. In order to determine whether the treatment induced ROS changes in barley roots, we studied ROS localization using a membranepermeable fluorescent probe. In agreement with what was observed for PLD activity, DCFH-DA staining of the root showed no significant ROS production in response to the pathogen at all studied times (inset Fig. 7A). PLA is also involved in plant immunity through its role in JA biosynthesis (Siebers et al., 2016). When assayed with NBD-PC and NBD-PE, PLA activity increased rapidly and transiently in response to the pathogen (Fig. 7B). The enzyme was more active with NBD-PC. We also evaluated whether heating-deactivated macroconidia and the chitosan elicitor were able to modulate PLA activity. TLC images in Fig. 7C show that both chitosan and deactivated macroconidia had a similar response, although the latter was faster (Fig. 7C, left image) in comparison with chitosan (Fig. 7C, right image). Finally, it was
3.4. Differences associated with PC revealed by Principal Component Analysis To check whether the differences in lipid composition after exposure to Fusarium were related with the duration of the exposure, the data obtained from targeted lipidomics were subjected to multivariate analysis. Fig. 6A shows the scores plot for the dataset of lipid species isolated both from untreated and F. graminearum-treated plants, for the first two principal components. As can be observed, the samples are separated into two distinct groups, according to how molecular species responded with respect to the duration of F. graminearum macroconidia exposure. The first principal component (PC1) accounted for the greatest variance (89.5%) across the data and separated the samples based on PC behavior. The specific weight with which each glycerolipid molecular species contributed to the first two principal components is visualized in the loading plot (Fig. 5B). The PC1 factor of the biplot described around 90% of the overall variance in PC. This revealed that mostly C34:2- and C36:4-PC contributed to cluster separation, represented by 30-min pathogen exposure (Fig. 6A and B).
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Fig. 4. Changes in lysophospholipid molecular species during F. graminearum macroconidia treatment. Effects of pathogen treatment on content of LPG, LPC and LPE and on molecular species of indicated lysophospholipids.
phospholipids such as PC, with acyl chains (34:2 (18:2–16:0), 34:3 (16:0/18:3), 36:4 (di18:2 or 18:1–18:2), 36:5 containing 18:2 and 18:3, and lyso-glycerolipids such as LPC. In plastidic lipids like DGDG, a decrease in 36:6 (18:3–18:3) was also evidenced. This phenomenon regarding acyl chain composition and remodelling was not observed in response to abiotic stresses like chilling, so certain sorts of phospholipids seem to be more responsive to variations in the environment, such as the presence of pathogens (Peppino Margutti et al., 2018, 2019a). An analysis of the pathogen-barley root interaction showed that PC tended to increase. This phospholipid is the main glycerophospholipid present at significant levels in the membrane of barley tissues. It has been shown that it can be synthesized through the cytidine diphosphate-choline pathway or the phosphatidylethanolamine N-methyltransferase pathway, which convert PE into PC. Another possible route is through the activation of a phospholipase that generates DAG, which is subsequently converted into PC (Larsson et al., 2007). However, no variation in the PC-PE ratio was observed in this work. On the other hand, we found a decrease in LPC concomitantly with an increase in PC. Therefore, we propose that part of the lyso-glycerolipid might be converted into PC (Larsson et al., 2007). Moreover, we wondered why the level of PC tended to increase in response to Fusarium. This might be an adaptive mechanism to minimize some of the effects caused by a previous hydrolysis of PC by lypolitic enzymes. Thus, phospholipase activity was evaluated to test our hypothesis. First, PLD was assayed as a contributor to the variations in PA levels. PA is a phospholipid mediator in the response to the pathogen (Li and Wang, 2019). Several metabolic pathways could be implied in the modulation of PA levels. Treating plants with a fungal pathogen or elicitors has been reported to induce PA production (van der Luit et al., 2000; Raho et al., 2011). Recent
determined that SA increased rapidly but transiently in response to the pathogen, while the increase in JA was both rapid and sustained (Fig. 8). 4. Discussion We found that some molecular species of barley root lipids were altered in response to F. graminearum. Phospholipids and galactolipids are the major lipids found in roots. An analysis of lipid classes showed that the phospholipid/galactolipid ratio remained unchanged in response to the pathogen, which suggests membrane stability, was not altered during the assay. Unlike the case with leaves, the lipidomic study of barley roots from plants grown at 25°C demonstrated that the composition of extraplastidic phospholipids at this site was dominated by 34:2 (18:2–16:0) and 36:4 (di18:2 or 18:1–18:2) species, which contain linolenic acid (18:2). The higher proportion of palmitic (16:0) and linoleic acid (18:2) in the lipidome of barley roots might be important for their functioning under optimum and stressful conditions. Supporting that, barley root spatial metabolite profiling revealed differences in response to short-term salt (Shelden et al., 2016) The alteration in the composition and unsaturation levels of extraplastidic phospholipids in barley roots suggests that lipid remodelling and the modification in lipid unsaturation levels are early responses to the fungal pathogen. Thus, this study shows that barley roots respond to the fungal pathogen by altering to levels of lipid species in a tissuespecific manner. Lipid remodelling refers to the decrease in the amounts of certain lipids and the increase in others. In the present study, lipid remodelling in terms of increase and decrease involved different classes of 7
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Fig. 5. Heat map showing the correlation between PC and LPC species based on Pearson’s correlation coefficient, P (Table S5). (A) Correlation between PC and LPC species in control barley roots. (B) Correlation between PC and LPC species in barley roots after F. graminearum treatment. Blue and red colours on the heat map indicate negative and positive correlation, respectively. (C–D) Effect of F. graminearum on PC-LPC ratio and on unsaturation index of PC and LPC.
The effects of these PLDs were interpreted through PA effectors, since PA was shown to bind to NADPH oxidase and to regulate H2O2 production and oxidative stress (Li and Wang, 2019). PLD has been characterized in different types of barley tissues as having diverse roles in
studies with a knockout of PLDβ1 have described a decrease in the production of PA induced by Botritis cinerea, which supports the idea that this PLD isoform is responsible for a major portion of the PA generated during the attack by the fungal pathogen (Zhao et al., 2013).
Fig. 6. Principal component analysis of the lipid composition in barley roots after F. graminearum treatment. A Biplot from the first and second principal components showing score (A) and principal components loading (B) of relationships between intensities of main glycerolipids classes and time of exposure to F. graminearum from barley root. 8
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Fig. 7. Effect of F. graminearum on phospholipase activities and ROS generation of barley roots. (A) PLD activity was assayed with NBD-PC. After reaction, lipids were extracted and separated by ethyl acetate TLC system. Inset of Fig. 1A: Epifluorescence microscopy images of qualitative distribution of ROS in roots treated with F. graminearum macroconidia for 0 (a), 5 (b), 15 (c), 30 (d) and 60 min (e). Images were taken with a Canon G10 camera and quantified (optical density in arbitrary units) using the ImageJ program, with the optical density of control roots defined as 39.07 AU (arbitrary units). (B) Effects of F. graminearum on PLA activity assayed with NBD-PC and NBD-PE. (C) Representative TLC blots are shown for: (left panel) effect of desnaturated macroconidia on PLA activity measured with NBD-PC as fluorescent substrate; (right panel) effect of chitosan on PLA activity. Fluorescent lipids were separated by solvent system containing chloroform:methanol:H2O (65:25:4, v/v).
with this, H2O2 production mediated by PLD/PA was also not observed in barley treated with the pathogen, while PA levels appeared to decrease. By contrast, when PLA activity was tested, a rapid and transient increase was observed in response to F. graminearum, as well as to the elicitor chitosan and the presence of inactivated macroconidia. A major PA pool in barley comes from PLD-dependent hydrolysis of the structural phospholipid PC (Villasuso et al., 2013; Peppino Margutti et al., 2018). Therefore, it is possible that PLA competes with PLD for PC availability and directly affects PLD activity and PA accumulation (Kirik and Mudgett, 2009). In consistency with this hypothesis, PLA was frankly more active than PLD in response to F. graminearum when they were assayed with vesicles containing fluorescent NBD-labelled PC analogues. This could also explain what was observed in terms of H2O2 accumulation. On the other hand, PLA plays an important role in regulating oxylipin biosynthesis in plants. To explore lipid remodelling in relation with the defence response, we tested JA production. It was observed that F. graminearum triggered JA accumulation. Several pathways could contribute to this. A profile of the lipid species that were altered in response to F. graminearum revealed decreases in the levels of DGDG (enriched in 18:3-18:3), which suggests that the hydrolysis of plastidic lipids might provide precursors for pathogen-induced JA production (Yang et al., 2007). Accordingly, free linoleic acid decreased after 30 min of F. graminearum treatment (data not shown), in such a way that more than one pathway could regulate JA synthesis (Yang et al., 2007). Taken together, the data indicate that PLA is modulated in
Fig. 8. Levels of SA and JA were analysed simultaneously by electrospray ionization/tandem mass spectrometry (LC-ESI-MS-MS), essentially as described by Meringer et al. (2016). Results are expressed as ng/dry weight of barley root, they correspond to n=3. Means with different letters are significantly different according to Tukey test at P < 0.05.
lipid metabolism and cellular regulation (Villasuso et al., 2013) and environmental stress responses (Meringer et al., 2016; Peppino Margutti et al., 2017). The response found in the PLD of roots inoculated with F. graminearum is an apparently contradictory behaviour that takes place during plant response to the pathogen. In agreement 9
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barley root in response to F. graminearum. In addition, the results suggest that lipid remodelling may contribute to JA production. In summary, our results suggest early lipid signalling activation when barley is responding to a pathogen attack, and open new insights into the role of lipids in plant-pathogen interactions. Further studies are needed to fully characterize the involvement of lipids in this pathosystem.
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Author contributions Conceived and designed the experiments: MR, ALV. Performed the experiments: MPM, MR. Analyzed the data: MPM, MR, ALV. Contributed reagents/materials/analysis tools: ALV. Result discussion ALV. Wrote the paper: ALV. Acknowledgements This work was supported by Universidad Nacional de Río Cuarto (SECyT-UNRC, grant number 18/C426); PPI-CONICET (grant number 11220150100206CO), Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT, grant number PICT 1108/15Préstamo BID, Argentina. INTA-Bordenave generously provided seeds. ALV is a Career Investigator of CONICET. MPM and MR are CONICET fellowship holders. The authors are grateful to Florencia Sgarlatta for language/ editing assistance. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.envexpbot.2019.06. 001. References Bargmann, B.O., Laxalt, A.M., Riet, B.T., Schouten, E., Van Leeuwen, W., Dekker, H.L., De Koster, C.G., Haring, M.A., Munnik, T., 2006. LePLDbeta1 activation and relocalization in suspension-cultured tomato cells treated with xylanase. Plant J. 45, 358–368. https://doi.org/10.1111/j.1365-313X.2005.02631.x. Cacas, J.L., Gerbeau-Pissot, P., Fromentin, J., Cantrel, C., Thomas, D., Jeannette, E., Kalachova, T., Mongrand, S., Simon-Plas, F., Ruelland, E., 2017. Diacylglycerol kinases activate tobacco NADPH oxidase-dependent oxidative burst in response to cryptogein. Plant Cell Environ. 40, 585–598. https://doi.org/10.1111/pce.12771. D’ambrosio, J.M., Gonorazky, G., Sueldo, D.J., Moraga, J., Di Palma, A.A., Lamattina, L., Collado, I.G., Laxalt, A.M., 2018. The sesquiterpene botrydial from Botrytis cinerea induces phosphatidic acid production in tomato cell suspensions. Planta 247, 1001–1009. https://doi.org/10.1007/s00425-018-2843-8. Durgbanshi, A., Arbona, V., Pozo, O., Miersch, O., Sancho, J.V., Gómez-Cadenas, A., 2005. Simultaneous determination of multiple phytohormones in plant extracts by liquid chromatography−electrospray tandem mass spectrometry. J. Agric. Food Chem. 53, 8437–8442. https://doi.org/10.1021/jf050884b. Durrant, W.E., Dong, X., 2004. Systemic acquired resistance. Annu. Rev. Phytopathol. 42, 185–209. https://doi.org/10.1146/annurev.phyto.42.040803.140421. Hammann, S., Korf, A., Bull, I.D., Hayen, H., Cramp, L.J.E., 2019. Lipid profiling and analytical discrimination of seven cereals using high temperature gas chromatography coupled to high resolution quadrupole time-of-flight mass spectrometry. Food Chem. 282, 27–35. https://doi.org/10.1016/j.foodchem.2018.12.109. Jones, J.D.G., Dangl, J.L., 2006. The plant immune system. Nature 444, 323. https://doi. org/10.1038/nature05286. Kazan, K., Gardiner, D.M., 2018. Transcriptomics of cereal–Fusarium graminearum interactions: what we have learned so far. Mol. Plant Pathol. 19, 764–778. https://doi. org/10.1111/mpp.12561. Kirik, A., Mudgett, M.B., 2009. SOBER1 phospholipase activity suppresses phosphatidic acid accumulation and plant immunity in response to bacterial effector AvrBsT. Proc. Natl. Acad. Sci. U. S. A. 106, 20532–20537. https://doi.org/10.1073/pnas. 0903859106. Lam, S.M., Tian, H., Shui, G., 2017. Lipidomics, en route to accurate quantitation. Biochim. Biophys. Acta Mol. Cell Biol. Lipids 1862, 752–761. https://doi.org/10. 1016/j.bbalip.2017.02.008. Lamb, C., Dixon, R., 1997. The OXIDATIVE BURST IN PLANT DISEASE RESISTANCE. Annu. Rev. Plant Physiol. Plant Mol. Biol. 48, 251–275. https://doi.org/10.1146/ annurev.arplant.48.1.251. Lanoue, A., Burlat, V., Henkes, G.J., Koch, I., Schurr, U., Rose, U.S., 2010. De novo biosynthesis of defense root exudates in response to Fusarium attack in barley. New Phytol. 185, 577–588. https://doi.org/10.1111/j.1469-8137.2009.03066.x. Larsson, K.E., Kjellberg, J.M., Tjellstrom, H., Sandelius, A.S., 2007. LysoPC
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