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. 2025 Jun 16;48(10):7107–7122. doi: 10.1111/pce.70017

Cysteine Signalling in Plant Pathogen Response

Jannis Moormann 1, Björn Heinemann 1, Cecile Angermann 1, Anna Koprivova 1, Ute Armbruster 2, Stanislav Kopriva 1, Tatjana M Hildebrandt 1,✉
PMCID: PMC12415419  PMID: 40522078

ABSTRACT

The amino acid cysteine is the precursor for a wide range of sulfur‐containing functional molecules in plants, including enzyme cofactors and defence compounds. Due to its redox active thiol group cysteine is highly reactive. Synthesis and degradation pathways are present in several subcellular compartments to adjust the intracellular cysteine concentration. However, stress conditions can lead to a transient increase in local cysteine levels. Here we investigate links between cysteine homeostasis and metabolic signalling in Arabidopsis thaliana. The systemic proteome response to cysteine feeding strongly suggests that Arabidopsis seedlings interpret accumulation of cysteine above a certain threshold as a signal for a biotic threat. Cysteine supplementation of Arabidopsis plants via the roots increases their resistance to the hemibiotrophic bacterium Pseudomonas syringae confirming the protective function of the cysteine induced defence pathways. Analysis of mutant plants reveals that the balance of cysteine synthesis between the cytosol and organelles is crucial during Arabidopsis immune response to Pseudomonas syringae. The induction profile of pathogen responsive proteins by cysteine provides insight into potential modes of action. Our results highlight the role of cysteine as a metabolic signal in the plant immune response and add evidence to the emerging concept of intracellular organelles as important players in plant stress signalling.

Keywords: amino acid metabolism, immunometabolism, infochemicals, mitochondria, proteomics, sulfur signalling

Summary statement

Cysteine accumulation triggers immune responses and enhances pathogen resistance in Arabidopsis thaliana. The balance of cysteine synthesis in different cellular compartments is crucial for effective defence, highlighting cysteine's role as an infochemical in stress signalling.

Abbreviations

ABA

abscisic acid

AOX

alternative oxidase

APK

adenosine 5′‐phosphosulfate kinase

APS

adenosine‐5′‐phosphosulfate

BTH

benzothiadiazole

CAS‐C1

cyanoalanine synthase

DAMP

damage‐associated molecular pattern

DES1

l‐cysteine desulfhydrase

dpi

days past infection

ETHE1

sulfur dioxygenase

GLR

Glutamate receptor‐like calcium channels

GSH

reduced glutathione

GST

glutathione‐S‐transferases

hpi

hours past infection

JA

jasmonic acid

NFS1

cysteine desulfurase

OAS

O‐acetylserine

OASTL

O‐acetylserine (thiol)lyase

PAMP

pathogen‐associated molecular pattern

Pst

Pseudomonas syringae pv tomato DC3000

ROS

reactive oxygen species

SA

salicylic acid

SAR

systemic acquired resistance

SERAT

serine acetyltransferase

STR1

3‐mercaptopyruvate sulfurtransferase

UDP

uridine diphosphate

UGT

uridine diphosphate‐dependent glucosyltransferase

1. Introduction

Amino acids have multiple functions in plants. In addition to their role during protein biosynthesis, they are an integral part of several biosynthetic pathways and involved in signalling processes including plant stress responses (Heinemann and Hildebrandt 2021). Amino acids can serve as markers reflecting nutrient availability or as carbon source for alternative respiratory pathways under energy starvation (Pedrotti et al. 2018). Proline is known to function as an osmolyte during osmotic stress and as molecular chaperone preventing protein aggregation (Szabados and Savouré 2010). In addition, amino acids serve as precursors for various molecules involved in plant immunity. Perturbations in amino acid metabolism have been reported to affect plant immune responses in various ways (Moormann et al. 2022). The phloem‐mobile signalling molecule N‐hydroxypipecolic acid, required for establishing systemic acquired resistance (SAR), is synthesised from lysine (Gupta and Spenser 1969; Návarová et al. 2012). Aromatic amino acids are precursors for a broad range of specialised molecules that crucially shape the interaction between plants and microbes such as coumarins, phytoalexins and indolic glucosinolates (Glawischnig 2007; Harun et al. 2020; Maeda and Dudareva 2012; Pastorczyk et al. 2020). The thiazole ring of camalexin, the characteristic phytoalexin of Arabidopsis thaliana, originates from the cysteine residue of glutathione (Su et al. 2011).

Among amino acids, cysteine is unique as it occupies a central position in plant sulfur metabolism. It is the precursor for a wide range of sulfur‐containing molecules in the cell, including methionine, essential vitamins and cofactors such as thiamin, lipoic acid, biotin, Fe‐S clusters and molybdenum cofactor (Droux 2004; Giovanelli et al. 1985; Van Hoewyk et al. 2008). Furthermore, the tripeptide γ‐glutamyl‐cysteinyl‐glycine, also known as glutathione, relies on the incorporation of cysteine to function as the main determinant of cellular redox homeostasis (Foyer and Noctor 2011). Its antioxidant property is based on the redox potential of the thiol group. Next to oxidative stress protection, glutathione also acts in detoxification of heavy metals and xenobiotics as well as in the plant defence response (Noctor et al. 2024). In proteins, cysteine residues contribute to structure, stability and function. When located in the active sites of enzymes they are essential for catalysis of many enzymatic reactions as well as metal cofactor binding. Moreover, thiol groups can undergo oxidation to form covalent disulfide bridges, aiding protein folding and stability. Reversible oxidation/reduction of these disulfide bridges poses a mechanism for redox regulation of proteins (Buchanan and Balmer 2005). Another layer of regulation is added by posttranslational cysteine modifications such as glutathionylation, nitrosylation, sulfenylation and persulfidation (Begara‐Morales et al. 2016; Moseler et al. 2024).

Cysteine is the product of the plant sulfur assimilatory pathway. Sulfate is taken up from the soil by specific transporters and activated by ATP sulfurylase. The resulting adenosine‐5′‐phosphosulfate (APS) is reduced in a two‐step reaction via sulfite to sulfide by APS reductase and sulfite reductase. Sulfide is incorporated into O‐acetylserine (OAS) by OAS‐(thiol)lyase (OASTL) to produce cysteine (Takahashi 2010; Takahashi et al. 2011). The amino acid precursor OAS is synthesised by serine acetyltransferase (SERAT) from serine and acetyl‐CoA. OASTL and SERAT form a cysteine synthase complex which is required for regulating cysteine synthesis based on substrate availability (Droux 2003; Wirtz and Hell 2006). Both enzymes have isoforms localised in the cytosol (SERAT1;1, SERAT3;1, SERAT3;2, OASTL‐A), plastids (SERAT2;1, OASTL‐B) and mitochondria (SEART2;2, OASTL‐C) enabling OAS and cysteine synthesis in different subcellular locations (Hell and Wirtz 2011; Ruffet et al. 1995; Watanabe et al. 2008). Cysteine desulfurases, which transfer sulfur to Fe‐S cluster scaffold proteins, are present in plastids and mitochondria as well (Couturier et al. 2013). The cytosolic cysteine desulfurase ABA3 is required for molybdenum cofactor synthesis (Caubrière et al. 2023). Cysteine levels are tightly regulated and generally kept low within the cell requiring adequate rates of cysteine degradation (Hildebrandt et al. 2015). In the cytosol, the l‐cysteine desulfhydrase DES1 deaminates cysteine resulting in pyruvate, ammonia and sulfide (Álvarez et al. 2010). In mitochondria, a four‐step process catalysing the complete oxidation of cysteine to pyruvate and thiosulfate is facilitated by an unknown aminotransferase, the 3‐mercaptopyruvate sulfurtransferase STR1, and the sulfur dioxygenase ETHE1 (Höfler et al. 2016). Cysteine levels vary among cellular compartments and are highest in the cytosol which is known to be the main contributor of cysteine with concentrations around 300 µM (Heeg et al. 2008; Krüger et al. 2009). Accordingly, OASTL‐A together with OASTL‐B were found to account for 95% of OASTL activity in Arabidopsis protein extracts, while OASTL‐C contributed only 5% of the activity. However, all three major OASTL isoforms were shown to largely compensate for each other's absence in null mutant studies (Birke et al. 2013; Heeg et al. 2008).

Previous findings provide some insight into the relevance of compartment specific cysteine metabolic pathways. Cytochrome c oxidase, the last enzyme of the mitochondrial respiratory chain, is strongly inhibited by cyanide as well as by hydrogen sulfide (Cooper and Brown 2008). Biosynthesis of camalexin and the gaseous phytohormone ethylene both lead to the production of cyanide in non‐cyanogenic plants such as Arabidopsis thaliana (Böttcher et al. 2009; Peiser et al. 1984). Cyanide detoxification in the mitochondria is achieved by conversion of cysteine and cyanide to hydrogen sulfide and β‐cyanoalanine catalysed by cyanoalanine synthase (CAS‐C1) (Hatzfeld et al. 2000; Watanabe et al. 2008). Hydrogen sulfide in turn is detoxified via incorporation into cysteine by mitochondrial OASTL‐C, creating a cyclic detoxification pathway. OASTL‐C might also be involved the regulation of sulfur homeostasis since loss or decreased activity due to a single‐nucleotide polymorphism in Arabidopsis thaliana accessions leads to reduced sulfate uptake (Koprivova et al. 2023). In addition, cysteine synthesis was found to play a role during stomatal closure in response to drought stress. Upon soil drying, sulfate is transported to the guard cells via the xylem and is incorporated into cysteine (Ernst et al. 2010). Subsequently, cysteine mediates abscisic acid (ABA)‐dependent stomatal closure in multiple ways (Heinemann and Hildebrandt 2021). It is a substrate of the MoCo‐sulfurylase ABA3 involved in ABA synthesis (Caubrière et al. 2023). ABA induces the expression of DES1, which uses cysteine as a substrate to produce hydrogen sulfide in the cytosol (Chen et al. 2020). Hydrogen sulfide accumulation leads to persulfidation and activation of several proteins involved in ABA‐induced stomatal closure including kinases and transcription factors (Chen et al. 2020; Shen et al. 2020; M. Zhou et al. 2021). These findings illustrate the wide range of functions and different modes of action of cysteine and its related metabolism. Taken together, the versatile chemical nature of cysteine and the high degree of compartmentalisation of its metabolism further highlight its potential for multiple, yet unknown, regulatory functions.

To identify additional potential signalling functions of cysteine in Arabidopsis, we analysed the response of seedlings to an artificial increase in cysteine levels. The proteome signature of the cysteine treated seedlings indicated perception of the disturbance in cysteine homeostasis as a biotic threat. Thus, we further investigated the role of compartment specific cysteine metabolism in the interaction of Arabidopsis plants with the leaf pathogen Pseudomonas syringae pv tomato DC3000 (Pst) and identified cytosolic and mitochondrial cysteine synthesis as major contributors to pathogen resistance.

2. Results

2.1. The Seedling Proteome Response to Increased Cysteine Concentrations Indicates Biotic Stress Signalling

To understand the systemic response of Arabidopsis thaliana to an increased cysteine content we performed a feeding experiment. Six‐day‐old seedlings grown in liquid culture were supplemented with 1 mM l‐cysteine for 24 h (Figure 1A, Supporting Information S5: Figure S1A). This treatment led to a 7.6‐fold increase in the seedling cysteine content, and the glutathione content was also significantly higher (1.7‐fold) than in control seedlings (Figure 1B). The cysteine content in the medium continuously decreased most likely due to a combination of uptake by the plants and chemical oxidation processes in the medium and was completely depleted at the end of the 24‐h incubation time (Supporting Information S5: Figure S1B). To test, whether cysteine oxidation led to a depletion of oxygen in the medium or had an effect on seedling respiration we analysed the oxygen content of the medium as well as seedling oxygen consumption rates, but did not detect any significant differences between cysteine treatment and control (Supporting Information S5: Figure S1C).

Figure 1.

Figure 1

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Seedling proteome response to cysteine treatment. (A) An A. thaliana seedling culture was supplemented with 1 mM l‐cysteine for 24 h before harvest. (B) Seedling content of l‐cysteine and reduced glutathione (GSH) [µmol·g fresh weight−1] (n = 8–9). (C) Principal component analysis of shotgun proteomics dataset with control (black) and cysteine‐treated (yellow) seedlings. (D) Volcano plot illustrating differences in the proteome of cysteine treated seedlings vs. controls. Proteins of significantly higher or lower abundance after cysteine feeding are marked in red and blue, respectively (t‐test, FDR < 0.05). (E) Enrichment of functional categories in proteins that are significantly increased (top, red) or decreased (bottom, blue) in the presence of cysteine. (F) Enrichment of stress induced categories among proteins that are significantly increased in the presence of cysteine. ABA, abscisic acid; BCAA, branched‐chain amino acid; BTH, benzothiadiazole, DAMP, damage‐associated molecular pattern; JA, jasmonic acid; PAMP, pathogen‐associated molecular pattern; SAM, S‐adenosylmethionine; SAR, systemic acquired resistance. The complete proteomics dataset including the enrichment analysis is provided as Dataset S1. (G) Seedling camalexin content [nmol·g fresh weight−1] (n = 5). Mean (bars) and individual (dots) values ± SD are shown. Asterisks indicate statistically significant differences compared with control seedlings following students t‐test (**p < 0.01 > 0.001; ***p < 0.001 > 0.0001; ****p < 0.0001). Raw data is provided in Dataset S4.

Shotgun proteome analysis revealed a distinct effect of cysteine feeding on the composition of the seedling proteome (Figure 1C). A total of 479 of the 4613 detected protein groups were significantly increased and 670 significantly decreased in cysteine treated compared to control samples (Figure 1D). Among the strongly downregulated proteins were the transcriptional activator Hem1, kinases associated with ABA signalling, and proteins involved in sulfur assimilation whereas glutathione‐S‐transferases (GSTs) as well as UDP‐glucosyltransferases (UGTs) were most drastically increased (Dataset S1). To systematically identify major features of the proteome response to increased cysteine levels, we performed an enrichment analysis on functional annotations of the significantly changed proteins (Dataset S1). Enrichment of metabolic pathways was analysed based on a modified version of the MapMan annotation system (https://mapman.gabipd.org; Figure 1E). The results indicated a decrease in pathways related to photosynthesis including photophosphorylation, the Calvin‐Benson‐Bassham cycle and also tetrapyrrole and organellar protein synthesis (Figure 1E, blue). In contrast, pathways required for heterotrophic energy metabolism such as carbohydrate and lipid degradation as well as cellular respiration showed increased abundance after cysteine treatment (Figure 1E, red). The enrichment of stress‐related categories (glucosyltransferases, oxidoreductases, GSTs) among the significantly increased proteins prompted us to systematically probe our dataset for characteristic stress response profiles. To this end, we performed an additional enrichment analysis on the basis of published transcriptome profiles for diverse abiotic and biotic stress conditions as well as elicitor and hormone treatments focusing on the proteins significantly increased after cysteine feeding (Figure 1F, Dataset S1). Strikingly, six of the seven significantly enriched categories in cysteine treated seedlings were associated with pathogen response. Enriched categories of proteins were those induced by pathogen‐associated molecular patterns (PAMPs), damage‐associated molecular patterns (DAMPs), SAR, treatment with jasmonic acid (JA) or the salicylic acid (SA) analogon benzothiadiazole (BTH) strongly suggesting a role for cysteine during biotic stress signalling (Figure 1F). Indeed, the concentration of the phytoalexin camalexin was significantly (4.5‐fold) increased in the cysteine‐treated seedlings indicating a similarity to an active pathogen response (Figure 1G).

2.2. Cysteine Treatment Induces Pathogen Resistance

To test the physiological relevance of the observed induction of pathogen response pathways by cysteine feeding under physiological conditions we watered 6‐week‐old A. thaliana plants grown on soil with 10 mM cysteine 24 h before performing a pathogen assay using the hemibiotrophic bacterium Pseudomonas syringae pv. tomato DC3000 (Pst) (Figure 2A). Quantification of thiols confirmed that cysteine was taken up by the plants and transported to the leaves (Figure 2B). Cysteine accumulated in the rosette leaves to a similar extent as in the seedling culture in treated compared to control plants (7‐fold). The cysteine treated plants were significantly less susceptible to Pst indicated by reduced bacterial growth and less chlorosis after 3 days of infection (Figure 2C,D).

Figure 2.

Figure 2

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Cysteine treatment induces resistance to the virulent pathogen Pseudomonas syringae. (A) Schematic representation of the workflow: A. thaliana plants were grown for 6 weeks under short‐day conditions and incubated in 10 mM l‐cysteine for 24 h before further analysis. (B) Content of l‐cysteine and reduced glutathione (GSH) [nmol·g fresh weight−1] in the rosette leaves of mock treated (white bars) and cysteine treated (yellow bars) plants (n = 10) (C) Pst infection assay: Four leaves per plant were infiltrated with P. syringae DC3000 solution including 5 × 105 colony forming units (CFU) per mL using a needleless syringe and sampled at 0 and 3 days past infection (dpi) to quantify CFU per cm leaf area (n = 11). (D) Phenotype of four representative leaves per treatment at 3 days after inoculation. Mean (bars) and individual (dots) values ± SD are shown. Asterisks indicate statistically significant differences compared with mock‐treated plants (**p < 0.01 > 0.001; ***p < 0.001 > 0.0001). Raw data is provided in Dataset S4. [Color figure can be viewed at wileyonlinelibrary.com]

2.3. Pathogen Attack Induces Cysteine Synthesis, and Proteome Responses to Cysteine Treatment and Pathogen Interaction Overlap

To investigate the function of cysteine during plant‐pathogen interaction, we quantified thiols in Arabidopsis leaves infected with Pst. Cysteine levels were significantly increased already 12 h post‐infection (hpi), peaked at 24 hpi at 6.6‐fold level of the mock treated controls and remained constantly high until 48 hpi (Figure 3A). The proteome of the infected leaves showed clear differences to the mock treated samples (Figure 3B; Dataset S2). The pattern of changes in individual protein abundances was highly consistent between the two timepoints analysed with a stronger response at 48 hpi (Dataset S3; Supporting Information S5: Figure S2). A total of 697 proteins were significantly increased and 582 proteins significantly decreased at both timepoints. Highlighting proteins with significant changes in the cysteine‐treated seedlings in the Pst infection dataset illustrates that there is also a strong overlap between the Arabidopsis proteome response to increased cysteine contents and pathogen attack (Figure 3C; Supporting Information S5: Figure S2; Dataset S3). A total of 174 proteins were significantly increased and 268 proteins significantly decreased after cysteine feeding as well as after pathogen attack. Among the consistently highly induced proteins in both responses were several GSTs, UGTs, and ALTERNATIVE OXIDASE 1A (Dataset S3). Enrichment analysis of functional annotations identifies a repression of photosynthesis related pathways, coenzyme metabolism as well as organellar protein translation (Figure 3D, blue) and an induction of lipid catabolism (Figure 3D, red) as common effects of both treatments.

Figure 3.

Figure 3

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Cysteine accumulation and proteome response during pathogen interaction. Six‐week‐old A. thaliana plants were infiltrated with P. syringae DC3000 (Pst) (2.5 × 106 colony forming units per mL). Six leaves per plant were sampled at the indicated timepoints. (A) Content of l‐cysteine [nmol·g fresh weight−1] in infected vs. mock treated leaves (n = 4–9). Mean values ± SD are shown. Asterisks indicate statistically significant differences compared with mock‐treated plants (****p < 0.0001). (B) Principal component analysis of the proteome of Pst‐ and mock‐infected leaves (circles and squares, respectively) at 24 and 48 h after inoculation (black and grey, respectively) (C) Volcano plots illustrating differences in the proteome of Pst‐ vs. mock‐infected plants at 24 and 48 hpi. Proteins of significantly higher or lower abundance after treatment with 1 mM l‐cysteine (Figure 1C) are highlighted in red and blue, respectively. (D) Enrichment of functional categories in proteins that are significantly increased (top) or decreased (bottom) at 24 hpi with Pst. Red and blue fonts indicate significantly increased or decreased categories, respectively, that were also enriched after cysteine treatment (Figure 1E). (E) Effect of Pst infection on amino acid metabolic pathways. Relative protein abundances in infected vs. mock treated leaves at 48 h after inoculation Pst. Proteins significantly increasing or decreasing in abundance are indicated by red or blue squares, respectively. 2‐OB, 2‐oxobutyrate; 2‐OG, 2‐oxoglutarate; 3PG, 3‐phosphoglycerate; ACoA, Acetyl‐CoA; AdoMet, S‐Adenosylmethionin; C1, C1‐metabolism; CM, chorismate; ET, ethylene; FeS, iron‐sulfur cluster; FU, fumarate; GABA, γ‐aminobutyric acid; Glce, glycerate; Glco, glycolate; GX, glyoxylate; Hpyr, Hydroxypyruvate; MoCo, molybdenum cofactor; NHP, N‐hydroxypipecolic acid; OA, oxaloacetic acid; Pyr, pyruvate; R5P, ribose‐5‐phosphate; SSA, succinic semialdehyde. The complete proteomics dataset including the enrichment analysis is provided in Dataset S2. Additional raw data is provided in Dataset S4. [Color figure can be viewed at wileyonlinelibrary.com]

We performed additional experiments to validate these cysteine responses with potential relevance in immune signalling (Supporting Information S5: Figure S3). The chlorophyll content of the cysteine treated seedlings was significantly decreased by 10% compared to the control, which is in line with the repression of photosynthesis indicated by the proteome data (Supporting Information S5: Figure S3A). However, we did not detect any significant effect of cysteine supplementation via the roots on the photosynthetic performance of the leaves as determined by chlorophyll a fluorescence analysis (Supporting Information S5: Figure S3B). The overall seedling composition with respect to carbohydrates, lipids and proteins remained unchanged (Supporting Information S5: Figure S3C). The induction of several GSTs in response to cysteine treatment led to a 1.6‐fold increase in total GST abundance, which was also reflected in a 1.7‐fold higher GST activity (Supporting Information S5: Figure S3D). To evaluate, whether the trigger for the induction of GSTs and other stress related proteins such as alternative oxidase might be an accumulation of reactive oxygen species (ROS) we performed DAB staining with the seedlings (Supporting Information S5: Figure S3E). The results revealed that hydrogen peroxide levels in the cysteine treated seedlings were even lower than in the controls indicating that other signalling processes are involved.

Several aspects of the proteome response to Pst interaction such as a decrease in terpenoid synthesis and an increase in hormone metabolism or vesicle trafficking did not become apparent during cysteine feeding and thus might be unrelated to cysteine signalling. The general effect on amino acid metabolism included an increase in the catabolic pathways mainly localised in the mitochondria and a decrease in plastidic synthesis pathways. A clear exception were the synthesis pathway of serine and the aromatic amino acids, which were strongly induced together with downstream pathways required for their conversion to specialised metabolites (Figure 3E).

2.4. Compartment Specific Cysteine Synthesis Is Required for Pathogen Resistance

A focus on the proteins involved in cysteine metabolism illustrates that the cytosolic and the mitochondrial pathway for cysteine synthesis as well as plastidic GSH production increased in abundance after pathogen attack whereas sulfate reduction and cysteine synthesis in the chloroplasts decreased (Figure 4A). To estimate the contributions of the individual compartments to cellular cysteine production we compared the total abundance of O‐acetylserine lyase (OASTL) isoforms catalysing the last step in cysteine synthesis in the leaf proteome (Figure 4B). The cytosolic and plastidic isoforms OASTL‐A and OASTL‐B were of similar abundance, but OASTL‐C localised in the mitochondria represented only about 5% of the total OASTL leaf content. During pathogen interaction OASTL‐A and OASTL‐C significantly increased in abundance whereas OASTL‐B significantly decreased (Figure 4A). Next, we tested the response of knockout mutant lines for the individual OASTL isoforms during interaction with Pst (Figure 4C–G). The oastl‐c (mitochondrial) mutant was significantly more susceptible to Pst infection compared to the wild type and the oastl‐b (chloroplast) mutant (Figure 4C). The stronger infection was also visible in the phenotype of the infected leaves, which were shriveled up with necrotic tips (Figure 4D). The cytosolic oastl‐a mutant showed an intermediate level of bacterial growth rates between the wild type and oastl‐c (Figure 4C). We detected a significant decrease in leaf camalexin levels at 24 hpi in oastl‐a and b and the same tendency in oastl‐c. (Figure 4E). Total leaf cysteine levels were lower than in the wild type already under control conditions in oastl‐a (deficient in cytosolic cysteine synthesis) and also the cysteine increase during infection lagged behind in this line but not in the others (Figure 4F, grey bars). Glutathione levels showed a similar trend (Figure 4G).

Figure 4.

Figure 4

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Compartmentalisation of cysteine synthesis in pathogen resistance. (A) Effect of Pst infection on cysteine metabolic pathways: Relative protein abundances in infected vs. mock treated leaves at 24 and 48 h after inoculation with P. syringae DC3000 (Pst) (2.5 × 106 colony forming units [CFU] per mL). Proteins increasing or decreasing in abundance are indicated by red or blue squares, respectively (n.d., undetected proteins). Asterisks indicate statistically significant differences compared with mock treated plants following students t‐test (*p < 0.05). APS, adenosine 5′‐phophosulfate; ATPS, ATP sulfhydrase; APR, APS reductase; SiR, sulfite reductase; SERAT, serine acetyltransferase; OAS, O‐acetylserine; OAS‐A, O‐acetylserin(thiol)lyase; GSH, glutathione; GSH1, γ‐glutamyl‐cysteine synthetase; GSH2, GSH syntethase; SCS, S‐sulfocysteine synthase; DES1, l‐cysteine desulfhydrase; Pyr, Pyruvate; 3‐MP, 3‐mercaptopyruvate; STR1, 3‐MP sulfurtransferase; GSSH, GSH‐persulfide; ETHE1, sulfur dioxygenase; β‐CA, β‐cyanoalanine; CAS‐C1, CAS synthase. (B) Total abundance of O‐acetylserin(thiol)lyase isoforms in control, mock treated and Pst infected leaves of wild type A. thaliana plants calculated from quantitative iBAQ‐values (n = 4). (C) Pst infection assay: Four leaves per plant were infiltrated with P. syringae DC3000 solution including 5 × 105 colony forming units (CFU) per mL using a needleless syringe and sampled at 0 and 3 days past infection (dpi) to quantify CFU per cm leaf area. (n = 8). (D) Phenotype of four representative leaves per treatment at 3 days after inoculation. (E) Camalexin content [nmol·g fresh weight−1] in mock treated and Pst infected leaves of wild type A. thaliana plants and OASTL‐deficient mutant lines (n = 4–5). (F) Cysteine and (G) Glutathione content [nmol·g fresh weight−1] in control, mock treated, and Pst infected leaves of wild type A. thaliana plants and OASTL‐deficient mutant lines (n = 5–10). Mean (bars) and individual (dots) values ± SD are shown. Letters indicate statistically significant differences following ANOVA with Tukey's test (α = 0.05). Raw data is provided in Dataset S4. [Color figure can be viewed at wileyonlinelibrary.com]

3. Discussion

3.1. Links of Cysteine Homeostasis to Plant Immune Signalling

The systemic proteome response to cysteine treatment strongly suggests that Arabidopsis seedlings interpret accumulation of cysteine above a certain threshold as a signal for a biotic threat. In accordance with these results, artificially increasing the intracellular cysteine concentration in mature plants renders them significantly less susceptible to infection by the hemibiotrophic bacterium Pseudomonas syringae, confirming the protective function of the defence pathways activated in response to cysteine treatment. Cysteine strongly accumulated within the first 24 h of infection in control plants that had not been treated before inoculation showing that a disturbance in cysteine homeostasis is an integral feature of the interaction between plant and pathogen. These findings indicate that the results obtained using the artificial but also highly reproducible and homogenous seedling culture approach can provide valuable insight into physiologically relevant processes. Effects observed consistently in seedling cultures and in the plants grown on soil despite the differences in age, tissues, and cultivation style have the potential to reveal fundamental aspects of metabolic immune signalling.

Several proteins were strongly induced by both, cysteine feeding as well as infection with Pst and thus might provide some insight into potential links between cysteine homeostasis and immune signalling. The functional category with the strongest enrichment in cysteine induced proteins consisted of UGTs of the 73B subfamily annotated as flavonoid glycosidases. Several additional UGTs responded similarly to Pst infection and cysteine treatment, and among them UGT71C5, UGT74F2, and UGT87A2 showed the strongest consistent induction (Dataset S3). The multigene family of uridine diphosphate‐dependent glucosyltransferases catalyses the covalent addition of sugars from nucleotide UDP sugar donors to functional groups on a variety of compounds which can increase the solubility of lipophilic metabolites or inactivate hormones and signalling molecules (Lairson et al. 2008). A number of UGTs have already been linked to plant immunity. UGT74F2 and UGT76B1 glycosylate and thereby inactivate immune signals including SA and N‐hydroxypipecolic acid. Knockout lines develop an autoimmune phenotype indicating that this function is required for balancing and containing immune responses (Bauer et al. 2021; Lim et al. 2002). UGT71C5 uses the phytohormone ABA as a substrate and is involved in regulating ABA homeostasis (Liu et al. 2015). ABA mediates abiotic stress responses and acts antagonistically to SA induced immune signalling (De Torres Zabala et al. 2009; De torres‐Zabala et al. 2007). The induction of UGT71C5 by cysteine will therefore amplify the plant pathogen response by suppressing antagonistic signals. A modelling approach recently suggested that UGT71C5 is activated by persulfidation of a cysteine residue at the active site, which would add an additional post‐translational layer to sulfur signalling in pathogen response (M. Li et al. 2024). The strongly cysteine‐responsive UGTs of the 73B subfamily also seem to have a positive regulatory role in immune signalling since Arabidopsis mutant plants lacking functional UGT73B3 or UGT73B5 showed increased susceptibility to Pst avrRpm1 (Langlois‐Meurinne et al. 2005). However, the relevant substrate(s) and the mechanism behind this effect have not been identified yet.

Among the group of proteins accumulating in response to cysteine treatment as well as during pathogen infection were also several GSTs of the plant‐specific phi (GSTF) and tau (GSTU) classes. GSTs catalyse the conjugation of glutathione to various substrates, mostly for detoxification purposes, and several of them are induced by pathogen infection and SA (Cummins et al. 2011; Lieberherr et al. 2003; Sappl et al. 2004). An accumulation during pathogen response has also been found in previous proteome studies (Jones et al. 2006; Maldonado‐Alconada et al. 2011). However, very limited information is available on endogenous substrates or the exact metabolic functions of disease‐induced GST isoenzymes. GSTF2, GSTF8, GSTF10, and GSTF11 were shown to bind to SA, though the biological implications remain unclear (Tian et al. 2012). Also, GSTF2 interacts with camalexin and was suggested to translocate plant defence compounds (Dixon et al. 2011).

Alternative oxidase (AOX) is induced by Pst infection and has been proposed to modulate ROS signalling in the mitochondria (Colombatti et al. 2014; Maxwell et al. 1999; Simons et al. 1999). The balance between AOX and manganese superoxide dismutase activities seems to be relevant for the specificity of ROS signalling by either confining the signal to the mitochondrial matrix (O2 −) or spreading it to the rest of the cell (H2O2) (Cvetkoska and Vanlerberghe 2012). Our results indicate that induction of AOX can be triggered in response to cysteine accumulation before or independently of a pathogen‐induced ROS burst.

The general response of the Arabidopsis leaf proteome to pathogen attack revealed that microbe interaction induces profound changes in organelle metabolism. Mitochondria strongly increase their oxidative phosphorylation capacity and use amino acids as alternative respiratory substrates. In contrast, chloroplasts decrease most of their functions including photosynthesis as well as amino acid synthesis and focus on the production of precursors for specialised metabolites and immune signals. This general metabolic shift from growth to defence is also clearly visible in the proteome response of cysteine treated seedlings, which in addition had a slightly decreased chlorophyll content compared to the control. However, the macromolecular composition and respiration rate of the seedlings as well as the photosynthetic performance of the plants was unaffected 24 h after cysteine treatment indicating that the systemic induction of defence pathways was able to protect the plant without causing major growth restrictions at this stage.

Interestingly, the protein most decreased in response to cysteine was HEM1, which has recently been reported to act as a translational regulator involved in the attenuation of the immune response during effector‐triggered immunity (Y. Zhou et al. 2023). The loss of HEM1 caused exaggerated cell death and restricted bacterial growth. Thus, a major aspect of cysteine signalling during pathogen response might be the repression of antagonistic signals.

3.2. Compartment Specific Functions of Cysteine Synthesis in Immune Signalling

While most amino acid anabolic pathways are localised in the chloroplasts, cysteine can be synthesised in different subcellular compartments (Heeg et al. 2008; Watanabe et al. 2008). The total leaf cysteine content after pathogen attack was reduced only in oastl‐A mutant plants defective in cytosolic cysteine synthesis, but not in oastl‐B or oastl‐C indicating that the remaining isoforms can at least partially compensate for the defect. These finding confirm the quantitatively dominant role of the cytosol in cysteine production reported before (Heeg et al. 2008; Krüger et al. 2009). A previous study with a focus on cytosolic cysteine homeostasis had already demonstrated an increased susceptibility of oastl‐A plants to Botrytis cinerea and Pst in contrast to a constitutive systemic immune response with high resistance to biotrophic and necrotrophic pathogens in des1 mutants, which accumulate cysteine due to defects in the cytosolic degradation pathway (Álvarez et al. 2012). Our results are in good agreement with these finding. In addition, they clearly show that cysteine synthesis in the mitochondria is also crucial for Arabidopsis pathogen resistance. Lack of mitochondrial OASTL‐C, despite constituting only about 5% of the total OASTL leaf content, had the strongest impact on pathogen response as indicated by the highest bacterial colony counts and leaf chlorosis after infection with Pst. Mitochondria require cysteine as a precursor for the synthesis of iron‐sulfur clusters and the cofactors biotin and lipoate as well as for cyanide detoxification. It was previously reported that overexpression of the mitochondrial cysteine desulfurase NFS1, which provides inorganic sulfur for FeS‐cluster synthesis, results in constitutive upregulation of defence‐related genes and increased resistance against Pst (Fonseca et al. 2020). The mechanism behind this response is currently unknown and could be related to regulatory functions of FeS proteins. However, increased cysteine desulfurase activity would also potentially lead to an increase in the product sulfane sulfur, which, if produced in excess, can be reduced to hydrogen sulfide in the presence of a reductant like GSH (Frazzon et al. 2007). Hydrogen sulfide production by the mitochondrial β‐cyanoalanine synthase CAS‐C1 in turn has recently been shown to be crucial for stomatal closure in response to the PAMP flagellin (Pantaleno et al. 2025). NFS1 was significantly induced by cysteine treatment and during Pst infection. Thus, an increase in compartment specific cysteine production as well as additional downstream metabolic processes seem to be involved in cysteine signalling during pathogen response.

Sulfate metabolism in plants branches at the level of APS, which can either be reduced to sulfide and incorporated into cysteine or phosphorylated by APS kinase (APK) and used for sulfation reactions. Blocking the sulfatation branch leads to an increased flux through the reductive branch of the pathway resulting in fourfold increased leaf cysteine contents in apk1xapk2 double knockout mutant plants compared to the wild type (Mugford et al. 2009). Re‐evaluation of published datasets reveals that the expression profile of the apk1xapk2 mutant strongly overlaps with the characteristic transcriptional response of Arabidopsis plants to bacterial pathogens, which would be in line with cysteine acting as a metabolic signal (Supporting Information S5: Figure S4). Since the cytosolic and mitochondrial but not the plastidic isoform of OASTL were induced in the APK deficient plants, compartment specific effects might again be relevant.

3.3. Potential Mechanisms of Cysteine Immune Signalling

Signalling events can be mediated by receptor proteins coupled to either kinase cascades or ion channels, allosteric protein regulation or post‐translational modifications. Previous proteomic studies have already demonstrated an effect of Pseudomonas syringae infection on post‐translational modifications such as S‐nitrosylation in Arabidopsis leaves (Jones et al. 2006; Maldonado‐Alconada et al. 2011). However, the mechanism of cysteine sensing and signalling during pathogen response remains poorly understood. Emerging evidence suggests possible modes of action that warrant further investigation. Glutamate receptor‐like calcium channels (GLRs) are involved in long‐distance plant defence signalling in response to wounding (Toyota et al. 2018). GLR3.3 is activated by GSH and several amino acids and responds to l‐cysteine in physiologically relevant micromolar concentrations (Alfieri et al. 2020; Grenzi et al. 2023). Treatment of the leaves with GSH or cysteine suppressed Pst propagation in wild type but not glr3‐3 mutant plants indicating that induction of pathogen response in reaction to extracellular cysteine is associated with this signalling pathway (F. Li et al. 2013). Based on a detailed transcriptome study and subsequent experimental confirmation clade 2 GLRs have also been linked to immune signalling (Bjornson et al. 2021). Since GLRs are mostly localised in the plasma membrane, they can detect extracellular changes in cysteine and other amino acids due to cell damage or release by pathogens but are unlikely to be involved in intracellular signalling. The induction of proteins associated with a DAMP‐response in the cysteine treated seedlings indicates that extracellular receptors might be relevant.

Persulfidation of protein cysteine residues has been established as a post‐translational modification involved in ABA signalling during drought response (Chen et al. 2020; Shen et al. 2020). A function in plant microbe interactions has not been demonstrated yet. However, in Aspergillus fumigatus, a human fungal pathogen causing severe pulmonary infections, persulfidation levels have been linked to both, the pathogenic potential of the fungus as well as the antifungal potency of alveolar macrophages and epithelial cells of the host (Sueiro‐Olivares et al. 2021). Although the mechanisms of protein persulfidation and de‐persulfidation is not entirely clear yet, cysteine most likely serves as the sulfur donor either via desulfhydration producing hydrogen sulfide or via transamination to 3‐mercaptopyruvate and subsequent transsulfuration (Pedre et al. 2023; Shen et al. 2020). Thus, an increase in cysteine content might be translated to persulfidation signals. The cysteine desulfhydrase DES1 (AT5G28030), which has been previously associated with protein persulfidation in Arabidopsis (Aroca et al. 2017; Shen et al. 2020; M. Zhou et al. 2021), is not included in our proteomics dataset and 3‐mercaptopyruvate sulfurtransferase (AT1G79230), the Arabidopsis ortholog of a yeast protein persulfidase (Pedre et al. 2023), was slightly decreased during Pst infection (Dataset S2). Thus, there is currently no clear evidence for a role of protein persulfidation in cysteine signalling and this aspect requires further investigation. Another potential mechanism of cysteine signalling would be via protein cysteinylation, which has been demonstrated in animals (Martí‐Andrés et al. 2024). Downstream effects can include transcriptional or post‐translational regulation. According to our results, the modulation of phytohormones and defence compounds as well as the alteration of immune gene translation pose potential hubs for cysteine‐induced biotic stress signalling.

In conclusion, cysteine, an important precursor for defence compounds, was shown to elicit plant immune signalling and thus serve as an infochemical during plant microbe interactions. Compartmental cysteine synthesis appears to be vital for properly mounting a pathogen response. The specific signalling pathways still need to be identified including potential intracellular cysteine receptors as well as connections to hormonal crosstalk during stress response. A potential role in hypoxic signalling indicated by proteomics also deserves further investigation.

4. Materials and Methods

4.1. Plant Material and Growth Conditions

All experiments were performed with Arabidopsis thaliana ecotype Col‐0 as wild type control. All mutants are T‐DNA insertion lines deficient (knockout) of the respective genes and were derived from Col‐0. Homozygous seeds of oastl‐A (At4g14880; N572213; SALK_072213; aka oastl‐a1.1; characterised in López‐Martín et al. 2008) and oastl‐B (At2g43750; N521183; SALK_021183; characterised in Heeg et al. 2008) as well as of oastl‐C (At3g59760, N500860; SALK_000860; characterised in Heeg et al. 2008) were kindly provided by Stanislav Kopriva and Andreas Meyer, respectively. Stratified seeds were sown in pots containing soil and grown in a climate chamber under short‐day conditions with 8 h of light (120 µmol·m−2·s−1). The temperature during the day and night changed from 22°C to 18°C. Soil‐grown plants were kept under these conditions for 6 weeks until experiments were performed.

For seedling cultures, seeds were incubated in 100% (v/v) ethanol for 2 min followed by two consecutive incubation steps in 6% (v/v) sodium hypochlorite (Carl Roth, Germany) for 2 min each. Afterwards, seeds were washed five times using sterile ddH2O and transferred to liquid growth media containing 0.43% (w/v) Murashige & Skoog salt mixture (Merck, Germany), 3 mM MES; and 0.5% (w/v) sucrose at pH 5.8. Individual cultures consisting of approximately 3 mg seeds in 50 mL liquid growth media were cultivated under long day conditions with 16 h of light (120 µmol·m−2·s−1) shaking at 100 rpm. The temperature during the day and night changed from 22°C to 18°C. Seedlings cultures were kept under these conditions for 6 days until treatment.

4.2. Cysteine Treatment

For seedling cultures, 1 mM l‐cysteine (Merck, Germany) was supplemented after 6 days of growth. The cysteine content in the medium decreased to low µM concentrations within the 24 h treatment.

Conditions for cysteine feeding of plants grown on soil were optimised in preliminary experiments to achieve a similar increase in tissue cysteine levels as in the experiments performed with seedling culture. Pots were soaked in 1 mM MES pH 5.8 with or without 10 mM l‐cysteine (Merck, Germany) for 24 h starting at the beginning of the light period. Afterwards, plants were either harvested and flash frozen in liquid nitrogen immediately or follow‐up experiments were performed.

4.3. Quantification of Total Lipids

The total lipid content was determined using the sulpho‐phospho‐vanillin method described in (Park et al. 2016). Absorbance was measured at 530 nm using a spectrophotometer (Multiscan Sykhigh, Thermo Fisher Scientific, Germany).

4.4. Quantification of Total Carbohydrates

The total carbohydrate content was determined using the phenol‐sulphuric acid method described by Tamboli et al. (2020). A total of 5 mg of lyophilised plant powder was dissolved in 1 mL of 2.5 N HCl and incubated for 3 h at 95°C, shaking. The extracts were diluted (1:50) with demineralised water and 10 µL phenol and 1 mL concentrated sulphuric acid were added. After incubation (10 min, 95°C, shaking) the absorbance was measured at 490 nm with a spectrophotometer (Multiskan Skyhigh, Thermo Fisher Scientific, Germany).

4.5. Extraction and Quantification of Total Protein

A total of 5 mg lyophilised seedling powder was dissolved in 700 µL methanol (100% (v/v)) and incubated for 20 min shaking at 80°C. After centrifugation (10 min, 4°C, 18 800g) the pellet was washed twice in 1 mL ethanol (70% (v/v)) and resuspended in 400 µL NaOH (0.1 M). The solution was incubated for 1 h shaking at 95°C and centrifuged again. The protein content of the supernatant was quantified using Ready‐to‐use Coomassie Blue G‐250 Protein Assay Reagent (Thermo Fisher Scientific, Germany) and Albumin Standard 23209 (Thermo Fisher Scientific, Germany).

4.6. Quantification of Chlorophyll

The quantification of chlorophyll was carried out according to a modified version of the method described by (Lichtenthaler 1987). A total of 5 mg plant powder was dissolved in 700 µL methanol [100% (v/v)] and incubated for 20 min at 80°C with shaking. After centrifugation (10 min, 4°C, 18 800g), the chlorophyll content of the supernatant was quantified with a spectrophotometer (Multiskan Skyhigh, Thermo Fisher Scientific, Germany) (wavelengths: 470, 653, and 666 nm).

4.7. Analysis of Seedling Respiration

Respiration rates were measured at ambient conditions using a Clark type oxygen electrode (model DW1, Hansatech Instruments Ltd, United Kingdom). Measurements were performed on control seedlings and seedlings fed 1 mM l‐cysteine for 24 h in fresh, air‐saturated liquid growth medium under constant stirring. After equilibration, 1 mM l‐cysteine (Merck, Germany) was added. After respiration measurements, seedlings were lyophilised and oxygen consumption rates were calculated on the basis of dry weight.

4.8. ROS Staining

Seedlings were rinsed with distilled water and transferred to the staining solution. For 3,3’‐diaminobenzidine (DAB; Merck, Germany) staining, seedlings were incubated in DAB staining solution [50 mM sodium phosphate buffer pH 7.5; DAB 0.1% (w/v); Tween 20 0.05% (v/v)] for 7 h at 10 rpm. Afterwards, seedlings were rinsed with distilled water and incubated in destaining solution [ethanol 60% (v/v), glycerol 20% (v/v), acetic acid 20% (v/v)] for 15 min at 95°C to remove chlorophyll for proper visualisation of the stain. Stained seedlings were scanned using the Epson Perfection V850 Pro (Epson, Germany).

4.9. GST Activity Assay

GST activity in crude extracts of seedlings was determined using a 1‐chloro‐2,4‐dinitrobenzene (CDNB)‐based photometric assay and performed as stated in Koschmieder et al. (2022) if not mentioned otherwise. In short, 150 µL of cold extraction buffer [50 mM Tris‐HCl, pH 8, 50 mM NaCl, 1 mM EDTA and 1% (w/v) PVPP] was added to 50 mg of seedlings ground in liquid nitrogen. Samples were resuspended thoroughly, kept on ice for 5 min and centrifuged at 18 000g for 15 min at 4°C to obtain crude extracts. Protein concentration was determined using Bradford assay and 10–15 µg of enzyme was added to 200 µL GST assay (2 mM GSH, 1 mM CDNB in modified PBS). The increase in absorbance at 340 nm was monitored every 5 s for 10 min at room temperature and GST activity was calculated.

4.10. Analysis of Photosynthetic Performance

For Chl a fluorescence analyses, the HEXAGON IMAGING‐PAM (Walz, Effeltrich, Germany) was used. Saturation light pulses of 0.5 s were applied after 30 min dark treatment to determine Fm and Fm’ during the illumination with increasing actinic light intensities. Non‐photochemical quenching (NPQ) was calculated as (Fm − Fm′)/Fm′ and ΦPSII as (Fm′ − F’)/Fm (Baker 2008).

4.11. Pseudomonas Syringae Infection Assays

For bacterial growth curves, Pseudomonas syringea pv. tomato DC3000 (Pst), grown on Kings‐B Agar (KB) plates containing 50 µg·mL−1 Rifampicin, were resuspended in 10 mM MgCl2 to a final concentration of 5 × 105 colony forming units (cfu)·mL−1 (OD600 0.001). For shot‐gun proteomics analysis, 2.5 × 106 cfu·mL−1 (OD600 0.005) Pst DC3000 was prepared as described. Five to seven of the youngest, fully matured leaves per plant were hand‐infiltrated with the bacterial suspension using a needless syringe. For bacterial growth curves, leaf discs were cut from infected leaves 0 days past infection (dpi) and 3 dpi and ground in 200 µL sterile MilliQ water using a tissue lyser (Mill Retsch MM400, Retsch GmbH, Haan, Germany). Dilution series were plated on KB plates containing 50 µg·mL−1 Rifampicin and 50 µg·mL−1 Cycloheximide, and colony forming units were counted after 2 days of growth at 28°C. Students t‐tests were performed with 8 biological replicates per time point and genotype or treatment from two independent experiments showing similar results. For thiol quantification and shot‐gun proteomics, all infected leaves were harvested, flash frozen in liquid nitrogen and ground for further procedures.

4.12. Quantification of Sulfur Metabolites

Sulfur compounds in plant samples were derivatized using bromobimane and quantified by reverse phase high performance liquid chromatography (HPLC). Samples were solved in derivatisation buffer [1.5 mM bromobimane (Merck, Darmstadt, Germany); 32% (v/v) acetonitrile; 10.3 mM EDTA and 103 mM HEPES pH 8] and incubated at 1400 rpm for 30 min in darkness. Afterwards, 15.9 mM methanesulfonic acid was added, cell debris pelleted at 18 000g for 5 min and the supernatant filtered using Corning Costar Spin‐X (0.22 µm) centrifuge filter tubes (Merck, Darmstadt, Germany). Samples were diluted and measured using an Agilent 1260 Infinity II HPLC (Agilent Technologies, Waldbronn, Germany) by fluorescence detection (ex. 380 nm; em. 480 nm). Peaks were evaluated and quantified using OpenLabCDS software (Agilent, Santa Clara, United States).

4.13. Quantification of Camalexin

Camalexin was determined by HPLC as described in (Koprivova et al. 2019). In short, approximately 50 mg plant material were extracted in 150 µL of dimethlysulfoxide (DMSO) for 20 min with shaking and centrifuged. A total of 20 µL of extracts were injected into a HPLC system with a Spherisorb ODS‐2 column (250 mm × 4.6 mm, 5 µm) and resolved using a gradient of acetonitrile in 0.01% (v/v) formic acid. Camalexin was detected by a FLD detector with an excitation at 318 nm and emission at 368 nm as described in (Bednarek et al. 2011). For the quantification of camalexin external standards were used ranging from 1 pg to 1 ng per µL.

4.14. Protein Extraction, Digestion and Sample Preparation for Proteome Analysis via Mass Spectrometry

Protein extraction, purification and digestion was performed with an adapted single‐pot solid‐phase‐enhanced sample preparations (SP3) protocol from (Mikulášek et al. 2021) which originates from (Hughes et al. 2019). In short, 5 mg of lyophilised plant powder were solved in 500 µL SDT buffer (4% sodium dodecyl sulfate, 0.1 M dithiothreitol, 0.1 M Tris pH 7.6) and incubated at 60°C for 30 min. Thirty microliters of the supernatants were mixed with 7.5 µL iodoacetamide (0.1 M) and incubated for 30 min in the dark. Then 2 µL dithiothreitol (0.1 M) was added. Equal shares (v/v) of hydrophobic and hydrophilic carboxylate‐modified magnetic beads (Sera‐Mag: No. 441521050250, No. 241521050250, GE Healthcare) were prepared for protein binding. Here, 600 µg beads were used per sample. Washing steps with ethanol (80%) were performed on a magnetic rack as described in (Mikulášek et al. 2021). The bound proteins were digested for 18 h at 37°C with 0.5 µg trypsin (MS grade, Promega) per sample. The peptide‐containing supernatants were collected in tubes with low peptide binding properties. The beads were rinsed in 60 µL ammonium bicarbonate (50 mM) to recover the remaining peptides. The eluates were acidified with formic acid and desalted on 50 mg Sep‐Pak tC18 columns (Waters). Peptide concentrations were quantified using the Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher Scientific) and adjusted to the same concentration in 0.1% formic acid.

4.15. Shotgun Proteomics by Ion Mobility Mass Spectrometry (IMS‐MS/MS)

For proteome profiling of the cysteine treated seedlings, 200 ng of peptides were injected via a nanoElute 1 (Bruker Daltonic, Bremen, Germany), separated on an analytical reversed‐phase C18 column (Aurora Ultimate 25 cm × 75 µm, 1.6 µm, 120 Å; IonOpticks) and analysed with a timsTOF Pro 2 mass spectrometer (Bruker Daltonic, Bremen, Germany). Using a multi‐staged linear gradient (Eluent A: MS grade water containing 0.1% formic acid, Eluent B: acetonitrile containing 0.1% formic acid, gradient: 0 min, 2%; 54 min, 25%; 60 min, 37%; 62 min, 95%; 70 min, 95% eluent B), peptides were eluted and ionised by a CaptiveSpray 1 ion source with a flow of 300 nL min−1. The ionised peptides were analysed with a standard data‐dependent acquisition parallel accumulation–serial fragmentation application method (DDA‐PASEF) with the following settings: Ion mobility window: 0.6–1.6 V·s/cm², 10 PASEF ramps, target intensity of 20 000 (threshold 2500), and a cycle time of ~1.1 s.

For proteome analysis of plants infected with Pseudomonas syringae 400 ng of peptides were injected via a nanoElute 2 UHPLC (Bruker Daltonic) and separated on the same type of analytical column with the same multi‐staged gradient as above. Here, the eluting peptides were ionised by a CaptiveSpray 2 source and analysed with a timsTOF‐HT mass spectrometer (Bruker Daltonic, Bremen, Germany). It was programmed with the following DDA‐PASEF method parameters: Ion mobility window of 0.7–1.5 V·s/cm², 4 PASEF ramps, target intensity 14 500 (threshold 1200), and a cycle time of ~0.53 s.

4.16. Data Processing and Evaluation

The ion mobility spectrometry (IMS–MS/MS) spectra from both experiments were analysed with MaxQuant software (Cox and Mann 2008) using default search parameters and TAIR10 (Arabidopsis.org) as database for protein identification. The calculation of label‐free quantification (LFQ) values and intensity‐based absolute quantification (iBAQ) values were both enabled. Data evaluation was performed using Perseus software (Tyanova et al. 2016). Proteins were excluded from further analysis if they were not detected in at least n − 1 biological replicates in at least one of the sample groups. Subsequently, missing values were replaced with randomly chosen low values from a normal distribution. Significant changes were calculated from the LFQ values using Student's t‐tests (p = 0.05). Fisher exact tests were performed in Perseus to identify significantly enriched or depleted metabolic pathways as well as environmental response patterns. The metabolic pathway categories were based on a modified version of MapMan (see Datasets S1 and S2; mapman.gabipd.org). Several RNA‐seq datasets were used to annotate proteins that showed a response to different stimuli, including fungal PAMPs, DAMPs, bacterial PAMPs (Bjornson et al. 2021), hypoxia (Klecker et al. 2014), ABA treatment, JA treatment (Goda et al. 2008), BTH treatment (Wang et al. 2006), or SAR (Gruner et al. 2013). Transcriptomics datasets for additional abiotic stress conditions (heat, cold, drought, salt, darkness) were used as summarised in (Hildebrandt 2018).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supplementary Dataset S1.

PCE-48-7107-s004.xlsx (3.2MB, xlsx)

Supplementary Dataset S2.

PCE-48-7107-s005.xlsx (6.2MB, xlsx)

Supplementary Dataset S3.

PCE-48-7107-s001.xlsx (192.6KB, xlsx)

Supplementary Dataset S4.

PCE-48-7107-s003.xlsx (45.2KB, xlsx)

Supplementary Figures.

PCE-48-7107-s002.pdf (1.3MB, pdf)

Acknowledgements

We thank Christina Mack, Cosima Sies, and Dagmar Lewejohann for skilful technical assistance and Isabella Rotthäuser for thorough help with plant cultivation. Research in the labs of TMH, UA, and SK is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC‐2048/1 – project ID 390686111. The proteomics unit in TMH's lab (timsTOF‐HT, Bruker Daltonic) is funded via DFG‐INST 216/1290‐1 FUGG.

Data Availability Statement

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository (Perez‐Riverol et al. 2022) with the dataset identifier PXD054723.

References

  1. Alfieri, A. , Doccula F. G., Pederzoli R., et al. 2020. “The Structural Bases for Agonist Diversity in an Arabidopsis thaliana Glutamate Receptor‐Like Channel.” Proceedings of the National Academy of Sciences 117, no. 1: 752–760. 10.1073/pnas.1905142117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Álvarez, C. , Ángeles Bermúdez M., Romero L. C., Gotor C., and García I.. 2012. “Cysteine Homeostasis Plays an Essential Role in Plant Immunity.” New Phytologist 193, no. 1: 165–177. 10.1111/j.1469-8137.2011.03889.x. [DOI] [PubMed] [Google Scholar]
  3. Aroca, A. , Benito J. M., Gotor C., and Romero L. C.. 2017. “Persulfidation Proteome Reveals the Regulation of Protein Function by Hydrogen Sulfide in Diverse Biological Processes in Arabidopsis.” Journal of Experimental Botany 68, no. 17: 4915–4927. 10.1093/jxb/erx294. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Álvarez, C. , Calo L., Romero L. C., García I., and Gotor C.. 2010. “An O‐Acetylserine(Thiol)Lyase Homolog With L‐Cysteine Desulfhydrase Activity Regulates Cysteine Homeostasis in Arabidopsis.” Plant Physiology 152, no. 2: 656–669. 10.1104/pp.109.147975. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Baker, N. R. 2008. “Chlorophyll Fluorescence: A Probe of Photosynthesis In Vivo.” Annual Review of Plant Biology 59, no. Volume 59, 2008: 89–113. 10.1146/annurev.arplant.59.032607.092759. [DOI] [PubMed] [Google Scholar]
  6. Bauer, S. , Mekonnen D. W., Hartmann M., et al. 2021. “UGT76B1, a Promiscuous Hub of Small Molecule‐Based Immune Signaling, Glucosylates N‐Hydroxypipecolic Acid, and Balances Plant Immunity.” Plant Cell 33, no. 3: 714–734. 10.1093/plcell/koaa044. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bednarek, P. , Piślewska‐Bednarek M., Ver Loren van Themaat E., Maddula R. K., Svatoš A., and Schulze‐Lefert P.. 2011. “Conservation and Clade‐Specific Diversification of Pathogen‐Inducible Tryptophan and Indole Glucosinolate Metabolism in Arabidopsis thaliana Relatives.” New Phytologist 192, no. 3: 713–726. 10.1111/j.1469-8137.2011.03824.x. [DOI] [PubMed] [Google Scholar]
  8. Begara‐Morales, J. C. , Sánchez‐Calvo B., Chaki M., et al. 2016. “Protein S‐Nitrosylation and S‐Glutathionylation as Regulators of Redox Homeostasis During Abiotic Stress Response.” In Redox State as a Central Regulator of Plant‐Cell Stress Responses, edited by Gupta D. K., Palma J. M., Corpas F. J., 365–386. Springer International Publishing. 10.1007/978-3-319-44081-1_17. [DOI] [Google Scholar]
  9. Birke, H. , Heeg C., Wirtz M., and Hell R.. 2013. “Successful Fertilization Requires the Presence of at Least One Major O‐Acetylserine(Thiol)Lyase for Cysteine Synthesis in Pollen of Arabidopsis.” Plant Physiology 163, no. 2: 959–972. 10.1104/pp.113.221200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Bjornson, M. , Pimprikar P., Nürnberger T., and Zipfel C.. 2021. “The Transcriptional Landscape of Arabidopsis thaliana Pattern‐Triggered Immunity.” Nature Plants 7, no. 5: 579–586. 10.1038/s41477-021-00874-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Böttcher, C. , Westphal L., Schmotz C., Prade E., Scheel D., and Glawischnig E.. 2009. “The Multifunctional Enzyme CYP71B15 (PHYTOALEXIN DEFICIENT3) Converts Cysteine‐Indole‐3‐Acetonitrile to Camalexin in the Indole‐3‐Acetonitrile Metabolic Network of Arabidopsis thaliana .” Plant Cell 21, no. 6: 1830–1845. 10.1105/tpc.109.066670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Buchanan, B. B. , and Balmer Y.. 2005. “REDOX REGULATION: A Broadening Horizon.” Annual Review of Plant Biology 56, no. Volume 56, 2005: 187–220. 10.1146/annurev.arplant.56.032604.144246. [DOI] [PubMed] [Google Scholar]
  13. Caubrière, D. , Moseler A., Rouhier N., and Couturier J.. 2023. “Diversity and Roles of Cysteine Desulfurases in Photosynthetic Organisms.” Journal of Experimental Botany 74, no. 11: 3345–3360. 10.1093/jxb/erad065. [DOI] [PubMed] [Google Scholar]
  14. Chen, S. , Jia H., Wang X., et al. 2020. “Hydrogen Sulfide Positively Regulates Abscisic Acid Signaling Through Persulfidation of SnRK2.6 in Guard Cells.” Molecular Plant 13, no. 5: 732–744. 10.1016/j.molp.2020.01.004. [DOI] [PubMed] [Google Scholar]
  15. Colombatti, F. , Gonzalez D. H., and Welchen E.. 2014. “Plant Mitochondria Under Pathogen Attack: A Sigh of Relief or a Last Breath?” Mitochondrion 19: 238–244. 10.1016/j.mito.2014.03.006. [DOI] [PubMed] [Google Scholar]
  16. Cooper, C. E. , and Brown G. C.. 2008. “The Inhibition of Mitochondrial Cytochrome Oxidase by the Gases Carbon Monoxide, Nitric Oxide, Hydrogen Cyanide and Hydrogen Sulfide: Chemical Mechanism and Physiological Significance.” Journal of Bioenergetics and Biomembranes 40, no. 5: 533–539. 10.1007/s10863-008-9166-6. [DOI] [PubMed] [Google Scholar]
  17. Couturier, J. , Touraine B., Briat J. ‑F., Gaymard F., and Rouhier N.. 2013. “The Iron‐Sulfur Cluster Assembly Machineries in Plants: Current Knowledge and Open Questions.” Frontiers in Plant Science 4: 1–22. Retrieved from https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2013.00259. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Cox, J. , and Mann M.. 2008. “Maxquant Enables High Peptide Identification Rates, Individualized P.P.B.‐Range Mass Accuracies and Proteome‐Wide Protein Quantification.” Nature Biotechnology 26, no. 12: 1367–1372. 10.1038/nbt.1511. [DOI] [PubMed] [Google Scholar]
  19. Cummins, I. , Dixon D. P., Freitag‐Pohl S., Skipsey M., and Edwards R.. 2011. “Multiple Roles for Plant Glutathione Transferases in Xenobiotic Detoxification.” Drug Metabolism Reviews 43, no. 2: 266–280. 10.3109/03602532.2011.552910. [DOI] [PubMed] [Google Scholar]
  20. Cvetkoska, M. , and Vanlerberghe G. C.. 2012. “Coordination of a Mitochondrial Superoxide Burst During the Hypersensitive Response to Bacterial Pathogen In Nicotiana Tabacum .” Plant, Cell & Environment 35, no. 6: 1121–1136. 10.1111/j.1365-3040.2011.02477.x. [DOI] [PubMed] [Google Scholar]
  21. Dixon, D. P. , Sellars J. D., and Edwards R.. 2011. “The Arabidopsis Phi Class Glutathione Transferase AtGSTF2: Binding and Regulation by Biologically Active Heterocyclic Ligands.” Biochemical Journal 438, no. 1: 63–70. 10.1042/BJ20101884. [DOI] [PubMed] [Google Scholar]
  22. Droux, M. 2003. “Plant Serine Acetyltransferase: New Insights for Regulation of Sulphur Metabolism in Plant Cells.” Plant Physiology and Biochemistry 41, no. 6: 619–627. 10.1016/S0981-9428(03)00083-4. [DOI] [Google Scholar]
  23. Droux, M. 2004. “Sulfur Assimilation and the Role of Sulfur in Plant Metabolism: A Survey.” Photosynthesis Research 79, no. 3: 331–348. 10.1023/B:PRES.0000017196.95499.11. [DOI] [PubMed] [Google Scholar]
  24. Ernst, L. , Goodger J. Q. D., Alvarez S., et al. 2010. “Sulphate as a Xylem‐Borne Chemical Signal Precedes the Expression of ABA Biosynthetic Genes in Maize Roots.” Journal of Experimental Botany 61, no. 12: 3395–3405. 10.1093/jxb/erq160. [DOI] [PubMed] [Google Scholar]
  25. Fonseca, J. P. , Lee H. K., Boschiero C., et al. 2020. “Iron–Sulfur Cluster Protein NITROGEN FIXATION S‐LIKE1 and Its Interactor FRATAXIN Function in Plant Immunity.” Plant Physiology 184, no. 3: 1532–1548. 10.1104/pp.20.00950. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Foyer, C. H. , and Noctor G.. 2011. “Ascorbate and Glutathione: The Heart of the Redox Hub.” Plant Physiology 155, no. 1: 2–18. 10.1104/pp.110.167569. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Frazzon, A. P. G. , Ramirez M. V., Warek U., et al. 2007. “Functional Analysis of Arabidopsis Genes Involved in Mitochondrial Iron–Sulfur Cluster Assembly.” Plant Molecular Biology 64, no. 3: 225–240. 10.1007/s11103-007-9147-x. [DOI] [PubMed] [Google Scholar]
  28. Giovanelli, J. , Mudd S. H., and Datko A. H.. 1985. “Quantitative Analysis of Pathways of Methionine Metabolism and Their Regulation in Lemna.” Plant Physiology 78, no. 3: 555–560. 10.1104/pp.78.3.555. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Glawischnig, E. 2007. “Camalexin.” Phytochemistry 68, no. 4: 401–406. 10.1016/j.phytochem.2006.12.005. [DOI] [PubMed] [Google Scholar]
  30. Goda, H. , Sasaki E., Akiyama K., et al. 2008. “The AtGenExpress Hormone and Chemical Treatment Data Set: Experimental Design, Data Evaluation, Model Data Analysis and Data Access.” Plant Journal 55, no. 3: 526–542. 10.1111/j.1365-313X.2008.03510.x. [DOI] [PubMed] [Google Scholar]
  31. Grenzi, M. , Buratti S., Parmagnani A. S., et al. 2023. “Long‐Distance Turgor Pressure Changes Induce Local Activation of Plant Glutamate Receptor‐Like Channels.” Current Biology 33, no. 6: 1019–1035.e8. 10.1016/j.cub.2023.01.042. [DOI] [PubMed] [Google Scholar]
  32. Gruner, K. , Griebel T., Návarová H., Attaran E., and Zeier J.. 2013. “Reprogramming of Plants During Systemic Acquired Resistance.” Frontiers in Plant Science 4: 1–28. 10.3389/fpls.2013.00252. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Gupta, R. N. , and Spenser I. D.. 1969. “Biosynthesis of the Piperidine Nucleus.” Journal of Biological Chemistry 244, no. 1: 88–94. 10.1016/S0021-9258(19)78195-2. [DOI] [PubMed] [Google Scholar]
  34. Harun, S. , Abdullah‐Zawawi M. R., Goh H. H., and Mohamed‐Hussein Z. A.. 2020. “A Comprehensive Gene Inventory for Glucosinolate Biosynthetic Pathway in Arabidopsis thaliana .” Journal of Agricultural and Food Chemistry 68, no. 28: 7281–7297. 10.1021/acs.jafc.0c01916. [DOI] [PubMed] [Google Scholar]
  35. Hatzfeld, Y. , Maruyama A., Schmidt A., Noji M., Ishizawa K., and Saito K.. 2000. “β‐Cyanoalanine Synthase Is a Mitochondrial Cysteine Synthase‐Like Protein in Spinach and Arabidopsis.” Plant Physiology 123, no. 3: 1163–1172. 10.1104/pp.123.3.1163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Heeg, C. , Kruse C., Jost R., et al. 2008. “Analysis of the Arabidopsis O‐Acetylserine(Thiol)Lyase Gene Family Demonstrates Compartment‐Specific Differences in the Regulation of Cysteine Synthesis.” Plant Cell 20, no. 1: 168–185. 10.1105/tpc.107.056747. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Heinemann, B. , and Hildebrandt T. M.. 2021. “The Role of Amino Acid Metabolism in Signaling and Metabolic Adaptation to Stress‐Induced Energy Deficiency in Plants.” Journal of Experimental Botany 72, no. 13: 4634–4645. 10.1093/jxb/erab182. [DOI] [PubMed] [Google Scholar]
  38. Hell, R. , and Wirtz M.. 2011. “Molecular Biology, Biochemistry and Cellular Physiology of Cysteine Metabolism in Arabidopsis Thaliana .” Arabidopsis Book 2011, no. 9: e0154. 10.1199/tab.0154. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Hildebrandt, T. M. 2018. “Synthesis Versus Degradation: Directions of Amino Acid Metabolism During Arabidopsis Abiotic Stress Response.” Plant Molecular Biology 98, no. 1: 121–135. 10.1007/s11103-018-0767-0. [DOI] [PubMed] [Google Scholar]
  40. Hildebrandt, T. M. , Nunes Nesi A., Araújo W. L., and Braun H. P.. 2015. “Amino Acid Catabolism in Plants.” Molecular Plant 8, no. 11: 1563–1579. 10.1016/j.molp.2015.09.005. [DOI] [PubMed] [Google Scholar]
  41. Van Hoewyk, D. , Pilon M., and Pilon‐Smits E. A. H.. 2008. “The Functions of Nifs‐Like Proteins in Plant Sulfur and Selenium Metabolism.” Plant Science 174, no. 2: 117–123. 10.1016/j.plantsci.2007.10.004. [DOI] [Google Scholar]
  42. Höfler, S. , Lorenz C., Busch T., et al. 2016. “Dealing With the Sulfur Part of Cysteine: Four Enzymatic Steps Degrade L‐Cysteine to Pyruvate and Thiosulfate in Arabidopsis Mitochondria.” Physiologia Plantarum 157, no. 3: 352–366. 10.1111/ppl.12454. [DOI] [PubMed] [Google Scholar]
  43. Hughes, C. S. , Moggridge S., Müller T., Sorensen P. H., Morin G. B., and Krijgsveld J.. 2019. “Single‐Pot, Solid‐Phase‐Enhanced Sample Preparation for Proteomics Experiments.” Nature Protocols 14, no. 1: 68–85. 10.1038/s41596-018-0082-x. [DOI] [PubMed] [Google Scholar]
  44. Jones, A. M. E. , Thomas V., Bennett M. H., Mansfield J., and Grant M.. 2006. “Modifications to the Arabidopsis Defense Proteome Occur Prior to Significant Transcriptional Change in Response to Inoculation With Pseudomonas Syringae.” Plant Physiology 142, no. 4: 1603–1620. 10.1104/pp.106.086231. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Klecker, M. , Gasch P., Peisker H., et al. 2014. “A Shoot‐Specific Hypoxic Response of Arabidopsis Sheds Light on the Role of the Phosphate‐Responsive Transcription Factor PHOSPHATE STARVATION RESPONSE1.” Plant Physiology 165, no. 2: 774–790. 10.1104/pp.114.237990. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Koprivova, A. , Elkatmis B., Gerlich S. C., et al. 2023. “Natural Variation in OASC Gene for Mitochondrial O‐Acetylserine Thiollyase Affects Sulfate Levels in Arabidopsis.” Plants 12, no. 1: 35. 10.3390/plants12010035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Koprivova, A. , Schuck S., Jacoby R. P., et al. 2019. “Root‐Specific Camalexin Biosynthesis Controls the Plant Growth‐Promoting Effects of Multiple Bacterial Strains.” Proceedings of the National Academy of Sciences 116, no. 31: 15735–15744. 10.1073/pnas.1818604116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Koschmieder, J. , Alseekh S., Shabani M., et al. 2022. “Color Recycling: Metabolization of Apocarotenoid Degradation Products Suggests Carbon Regeneration via Primary Metabolic Pathways.” Plant Cell Reports 41, no. 4: 961–977. 10.1007/s00299-022-02831-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Krüger, S. , Niehl A., Lopez Martin M. C., et al. 2009. “Analysis of Cytosolic and Plastidic Serine Acetyltransferase Mutants and Subcellular Metabolite Distributions Suggests Interplay of the Cellular Compartments for Cysteine Biosynthesis in Arabidopsis.” Plant, Cell & Environment 32, no. 4: 349–367. 10.1111/j.1365-3040.2009.01928.x. [DOI] [PubMed] [Google Scholar]
  50. Lairson, L. L. , Henrissat B., Davies G. J., and Withers S. G.. 2008. “Glycosyltransferases: Structures, Functions, and Mechanisms.” Annual Review of Biochemistry 77, no. Volume 77, 2008: 521–555. 10.1146/annurev.biochem.76.061005.092322. [DOI] [PubMed] [Google Scholar]
  51. Langlois‐Meurinne, M. , Gachon C. M. M., and Saindrenan P.. 2005. “Pathogen‐Responsive Expression of Glycosyltransferase Genes UGT73B3 and UGT73B5 Is Necessary for Resistance to Pseudomonas Syringae pv Tomato in Arabidopsis.” Plant Physiology 139, no. 4: 1890–1901. 10.1104/pp.105.067223. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Li, F. , Wang J., Ma C., et al. 2013. “Glutamate Receptor‐Like Channel3.3 Is Involved in Mediating Glutathione‐Triggered Cytosolic Calcium Transients, Transcriptional Changes, and Innate Immunity Responses in Arabidopsis.” Plant Physiology 162, no. 3: 1497–1509. 10.1104/pp.113.217208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Li, M. , Xiao L., Sun K., et al. 2024. “Insights From Structure‐Based Simulations Into the Persulfidation of Uridine Diphosphate‐Glycosyltransferase71c5 Facilitating the Reversible Inactivation of Abscisic Acid.” International Journal of Molecular Sciences 25, no. 17: 9679. 10.3390/ijms25179679. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Lichtenthaler, H. K. 1987. “[34] Chlorophylls and Carotenoids: Pigments of Photosynthetic Biomembranes.” In Methods in Enzymology. Plant Cell Membranes (148, 350–382. Elsevier. 10.1016/0076-6879(87)48036-1. [DOI] [Google Scholar]
  55. Lieberherr, D. , Wagner U., Dubuis P. H., Métraux J. P., and Mauch F.. 2003. “The Rapid Induction of Glutathione S‐Transferases AtGSTF2 and AtGSTF6 by Avirulent Pseudomonas Syringae Is the Result of Combined Salicylic Acid and Ethylene Signaling.” Plant and Cell Physiology 44, no. 7: 750–757. 10.1093/pcp/pcg093. [DOI] [PubMed] [Google Scholar]
  56. Lim, E. K. , Doucet C. J., Li Y., et al. 2002. “The Activity of Arabidopsisglycosyltransferases Toward Salicylic Acid, 4‐Hydroxybenzoic Acid, and Other Benzoates.” Journal of Biological Chemistry 277, no. 1: 586–592. 10.1074/jbc.M109287200. [DOI] [PubMed] [Google Scholar]
  57. Liu, Z. , Yan J. P., Li D. K., et al. 2015. “UDP‐Glucosyltransferase71C5, a Major Glucosyltransferase, Mediates Abscisic Acid Homeostasis in Arabidopsis.” Plant Physiology 167, no. 4: 1659–1670. 10.1104/pp.15.00053. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. López‐Martín, M. C. , Becana M., Romero L. C., and Gotor C.. 2008. “Knocking Out Cytosolic Cysteine Synthesis Compromises the Antioxidant Capacity of the Cytosol to Maintain Discrete Concentrations of Hydrogen Peroxide in Arabidopsis.” Plant Physiology 147, no. 2: 562–572. 10.1104/pp.108.117408. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Maeda, H. , and Dudareva N.. 2012. “The Shikimate Pathway and Aromatic Amino Acid Biosynthesis in Plants.” Annual Review of Plant Biology 63, no. Volume 63, 2012: 73–105. 10.1146/annurev-arplant-042811-105439. [DOI] [PubMed] [Google Scholar]
  60. Maldonado‐Alconada, A. M. , Echevarría‐Zomeño S., Lindermayr C., Redondo‐López I., Durner J., and Jorrín‐Novo J. V.. 2011. “Proteomic Analysis of Arabidopsis Protein S‐Nitrosylation in Response to Inoculation With Pseudomonas Syringae.” Acta Physiologiae Plantarum 33, no. 4: 1493–1514. 10.1007/s11738-010-0688-2. [DOI] [Google Scholar]
  61. Martí‐Andrés, P. , Finamor I., Torres‐Cuevas I., et al. 2024. “Trp14 Is the Rate‐Limiting Enzyme for Intracellular Cystine Reduction and Regulates Proteome Cysteinylation.” EMBO Journal 43, no. 13: 2789–2812. 10.1038/s44318-024-00117-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Maxwell, D. P. , Wang Y., and McIntosh L.. 1999. “The Alternative Oxidase Lowers Mitochondrial Reactive Oxygen Production in Plant Cells.” Proceedings of the National Academy of Sciences 96, no. 14: 8271–8276. 10.1073/pnas.96.14.8271. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Mikulášek, K. , Konečná H., Potěšil D., Holánková R., Havliš J., and Zdráhal Z.. 2021. “SP3 Protocol for Proteomic Plant Sample Preparation Prior LC‐MS/MS.” Frontiers in Plant Science 12: 1–12. Retrieved from https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2021.635550. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Moormann, J. , Heinemann B., and Hildebrandt T. M.. 2022. “News about Amino Acid Metabolism in Plant–Microbe Interactions.” Trends in Biochemical Sciences 47, no. 10: 839–850. 10.1016/j.tibs.2022.07.001. [DOI] [PubMed] [Google Scholar]
  65. Moseler, A. , Wagner S., and Meyer A. J.. 2024. “Protein Persulfidation in Plants: Mechanisms and Functions Beyond a Simple Stress Response.” Biological Chemistry 405, no. 9–10: 547–566. 10.1515/hsz-2024-0038. [DOI] [PubMed] [Google Scholar]
  66. Mugford, S. G. , Yoshimoto N., Reichelt M., et al. 2009. “Disruption of Adenosine‐5′‐Phosphosulfate Kinase in Arabidopsis Reduces Levels of Sulfated Secondary Metabolites.” Plant Cell 21, no. 3: 910–927. 10.1105/tpc.109.065581. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Návarová, H. , Bernsdorff F., Döring A. C., and Zeier J.. 2012. “Pipecolic Acid, an Endogenous Mediator of Defense Amplification and Priming, Is a Critical Regulator of Inducible Plant Immunity.” Plant Cell 24, no. 12: 5123–5141. 10.1105/tpc.112.103564. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Noctor, G. , Cohen M., Trémulot L., Châtel‐Innocenti G., van Breusegem F., and Mhamdi A.. 2024. “Glutathione: A Key Modulator of Plant Defence and Metabolism Through Multiple Mechanisms.” Journal of Experimental Botany 75, no. 15: 4549–4572. 10.1093/jxb/erae194. [DOI] [PubMed] [Google Scholar]
  69. Pantaleno, R. , Scuffi D., Schiel P., Schwarzländer M., Costa A., and García‐Mata C.. 2025. “Mitochondrial ß‐Cyanoalanine Synthase Participates in flg22‐Induced Stomatal Immunity.” Plant, Cell & Environment 48, no. 1: 537–552. 10.1111/pce.15155. [DOI] [PubMed] [Google Scholar]
  70. Park, J. , Jeong H. J., Yoon E. Y., and Moon S. J.. 2016. “Easy and Rapid Quantification of Lipid Contents of Marine Dinoflagellates Using the Sulpho‐Phospho‐Vanillin Method.” Algae 31, no. 4: 391–401. 10.4490/algae.2016.31.12.7. [DOI] [Google Scholar]
  71. Pastorczyk, M. , Kosaka A., Piślewska‐Bednarek M., et al. 2020. “The Role of CYP71A12 Monooxygenase in Pathogen‐Triggered Tryptophan Metabolism and Arabidopsis Immunity.” New Phytologist 225, no. 1: 400–412. 10.1111/nph.16118. [DOI] [PubMed] [Google Scholar]
  72. Pedre, B. , Talwar D., Barayeu U., et al. 2023. “3‐Mercaptopyruvate Sulfur Transferase Is a Protein Persulfidase.” Nature Chemical Biology 19, no. 4: 507–517. 10.1038/s41589-022-01244-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Pedrotti, L. , Weiste C., Nägele T., et al. 2018. “Snf1‐RELATED KINASE1‐Controlled C/S1‐bZIP Signaling Activates Alternative Mitochondrial Metabolic Pathways to Ensure Plant Survival in Extended Darkness.” Plant Cell 30, no. 2: 495–509. 10.1105/tpc.17.00414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Peiser, G. D. , Wang T. T., Hoffman N. E., Yang S. F., Liu H., and Walsh C. T.. 1984. “Formation of Cyanide From Carbon 1 of 1‐Aminocyclopropane‐1‐Carboxylic Acid During Its Conversion to Ethylene.” Proceedings of the National Academy of Sciences 81, no. 10: 3059–3063. 10.1073/pnas.81.10.3059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Perez‐Riverol, Y. , Bai J., Bandla C., et al. 2022. “The PRIDE Database Resources in 2022: A Hub for Mass Spectrometry‐Based Proteomics Evidences.” Nucleic Acids Research 50, no. D1: D543–D552. 10.1093/nar/gkab1038. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Ruffet, M. L. , Lebrun M., Droux M., and Douce R.. 1995. “Subcellular Distribution of Serine Acetyltransferase From Pisum Sativum and Characterization of an Arabidopsis thaliana Putative Cytosolic Isoform.” European Journal of Biochemistry 227, no. 1–2: 500–509. 10.1111/j.1432-1033.1995.tb20416.x. [DOI] [PubMed] [Google Scholar]
  77. Sappl, P. G. , Oñate‐Sánchez L., Singh K. B., and Millar A. H.. 2004. “Proteomic Analysis of Glutathione S‐Transferases of Arabidopsis thaliana Reveals Differential Salicylic Acid‐Induced Expression of the Plant‐Specific Phi and Tau Classes.” Plant Molecular Biology 54, no. 2: 205–219. 10.1023/B:PLAN.0000028786.57439.b3. [DOI] [PubMed] [Google Scholar]
  78. Shen, J. , Zhang J., Zhou M., et al. 2020. “Persulfidation‐Based Modification of Cysteine Desulfhydrase and the NADPH Oxidase RBOHD Controls Guard Cell Abscisic Acid Signaling.” Plant Cell 32, no. 4: 1000–1017. 10.1105/tpc.19.00826. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Simons, B. H. , Millenaar F. F., Mulder L., van Loon L. C., and Lambers H.. 1999. “Enhanced Expression and Activation of the Alternative Oxidase During Infection of Arabidopsis Withpseudomonas Syringae pv Tomato1.” Plant Physiology 120, no. 2: 529–538. 10.1104/pp.120.2.529. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Su, T. , Xu J., Li Y., et al. 2011. “Glutathione‐Indole‐3‐Acetonitrile Is Required for Camalexin Biosynthesis in Arabidopsis thaliana .” Plant Cell 23, no. 1: 364–380. 10.1105/tpc.110.079145. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Sueiro‐Olivares, M. , Scott J., Gago S., et al. 2021. “Fungal and Host Protein Persulfidation Are Functionally Correlated and Modulate Both Virulence and Antifungal Response.” PLoS Biology 19, no. 6: e3001247. 10.1371/journal.pbio.3001247. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Szabados, L. , and Savouré A.. 2010. “Proline: A Multifunctional Amino Acid.” Trends in Plant Science 15, no. 2: 89–97. 10.1016/j.tplants.2009.11.009. [DOI] [PubMed] [Google Scholar]
  83. Takahashi, H. , Kopriva S., Giordano M., Saito K., and Hell R.. 2011. “Sulfur Assimilation in Photosynthetic Organisms: Molecular Functions and Regulations of Transporters and Assimilatory Enzymes.” Annual Review of Plant Biology 62, no. Volume 62, 2011: 157–184. 10.1146/annurev-arplant-042110-103921. [DOI] [PubMed] [Google Scholar]
  84. Takahashi, H. 2010. “Chapter 4 ‐ Regulation of Sulfate Transport and Assimilation in Plants.” In International Review of Cell and Molecular Biology, edited by Jeon K. W., 281, 129–159. Academic Press. 10.1016/S1937-6448(10)81004-4. [DOI] [PubMed] [Google Scholar]
  85. Tamboli, F. A. , More H. N., Bhandugare S. S., Patil A. S., Jadhav N. R., and Killedar S. G.. 2020. “Estimation of Total Carbohydrate Content by Phenol Sulphuric Acid Method From Eichhornia Crassipes (Mart.) Solms.” Asian Journal of Research in Chemistry 13, no. 5: 357–359. 10.5958/0974-4150.2020.00067.X. [DOI] [Google Scholar]
  86. Tian, M. , von Dahl C. C., Liu P. P., Friso G., van Wijk K. J., and Klessig D. F.. 2012. “The Combined Use of Photoaffinity Labeling and Surface Plasmon Resonance‐Based Technology Identifies Multiple Salicylic Acid‐Binding Proteins.” Plant Journal 72, no. 6: 1027–1038. 10.1111/tpj.12016. [DOI] [PubMed] [Google Scholar]
  87. De Torres Zabala, M. , Bennett M. H., Truman W. H., and Grant M. R.. 2009. “Antagonism Between Salicylic and Abscisic Acid Reflects Early Host–Pathogen Conflict and Moulds Plant Defence Responses.” Plant Journal 59, no. 3: 375–386. 10.1111/j.1365-313X.2009.03875.x. [DOI] [PubMed] [Google Scholar]
  88. De torres‐Zabala, M. , Truman W., Bennett M. H., et al. 2007. “ Pseudomonas syringae pv. tomato Hijacks the Arabidopsis Abscisic Acid Signalling Pathway to Cause Disease.” EMBO Journal 26, no. 5: 1434–1443. 10.1038/sj.emboj.7601575. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Toyota, M. , Spencer D., Sawai‐Toyota S., et al. 2018. “Glutamate Triggers Long‐Distance, Calcium‐Based Plant Defense Signaling.” Science 361, no. 6407: 1112–1115. 10.1126/science.aat7744. [DOI] [PubMed] [Google Scholar]
  90. Tyanova, S. , Temu T., Sinitcyn P., et al. 2016. “The Perseus Computational Platform for Comprehensive Analysis of (Prote)Omics Data.” Nature Methods 13, no. 9: 731–740. 10.1038/nmeth.3901. [DOI] [PubMed] [Google Scholar]
  91. Wang, D. , Amornsiripanitch N., and Dong X.. 2006. “A Genomic Approach to Identify Regulatory Nodes in the Transcriptional Network of Systemic Acquired Resistance in Plants.” PLoS Pathogens 2, no. 11: e123. 10.1371/journal.ppat.0020123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Watanabe, M. , Kusano M., Oikawa A., Fukushima A., Noji M., and Saito K.. 2008. “Physiological Roles of the β‐Substituted Alanine Synthase Gene Family in Arabidopsis.” Plant Physiology 146, no. 1: 310–320. 10.1104/pp.107.106831. [DOI] [PMC free article] [PubMed] [Google Scholar]
  93. Wirtz, M. , and Hell R.. 2006. “Functional Analysis of the Cysteine Synthase Protein Complex From Plants: Structural, Biochemical and Regulatory Properties.” Journal of Plant Physiology 163, no. 3: 273–286. 10.1016/j.jplph.2005.11.013. [DOI] [PubMed] [Google Scholar]
  94. Zhou, M. , Zhang J., Shen J., et al. 2021. “Hydrogen Sulfide‐Linked Persulfidation of ABI4 Controls ABA Responses Through the Transactivation of MAPKKK18 in Arabidopsis.” Molecular Plant 14, no. 6: 921–936. 10.1016/j.molp.2021.03.007. [DOI] [PubMed] [Google Scholar]
  95. Zhou, Y. , Niu R., Tang Z., et al. 2023. “Plant HEM1 Specifies a Condensation Domain to Control Immune Gene Translation.” Nature Plants 9, no. 2: 289–301. 10.1038/s41477-023-01355-7. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Dataset S1.

PCE-48-7107-s004.xlsx (3.2MB, xlsx)

Supplementary Dataset S2.

PCE-48-7107-s005.xlsx (6.2MB, xlsx)

Supplementary Dataset S3.

PCE-48-7107-s001.xlsx (192.6KB, xlsx)

Supplementary Dataset S4.

PCE-48-7107-s003.xlsx (45.2KB, xlsx)

Supplementary Figures.

PCE-48-7107-s002.pdf (1.3MB, pdf)

Data Availability Statement

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository (Perez‐Riverol et al. 2022) with the dataset identifier PXD054723.

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