Photosystem II Repair Cycle in Faba Bean May Play a Role in Its Resistance to Botrytis fabae Infection

Abstract

Chocolate spot, which is caused by the necrotrophic fungus Botrytis fabae, is a major foliar disease occurring worldwide and dramatically reducing crop yields in faba bean (Vicia faba). Although chemical control of this disease is an option, it has serious economic and environmental drawbacks that make resistant cultivars a more sensible choice. The molecular mechanisms behind the defense against B. fabae are poorly understood. In this work, we studied the leave proteome in two faba bean genotypes that respond differently to B. fabae in order to expand the available knowledge on such mechanisms. For this purpose, we used two-dimensional gel electrophoresis (2DE) in combination with Matrix-Assisted Laser Desorption/Ionization (MALDI-TOF/TOF). Univariate statistical analysis of the gels revealed 194 differential protein spots, 102 of which were identified by mass spectrometry. Most of the spots belonged to proteins in the energy and primary metabolism, degradation, redox or response to stress functional groups. The MS results were validated with assays of protease activity in gels. Overall, they suggest that the two genotypes may respond to B. fabae with a different PSII protein repair cycle mechanism in the chloroplast. The differences in resistance to B. fabae may be the result of a metabolic imbalance in the susceptible genotype and of a more efficient chloroplast detoxification system in the resistant genotype at the early stages of infection.

1. Introduction

By virtue of its high nutritional value, faba bean (Vicia faba L.) is an important food legume for human consumption and livestock feeding [1]. In fact, it is regarded as an excellent protein crop on the basis of its ability to provide nitrogen inputs into temperate agricultural systems, and also because of its increased yield potential and nitrogen-fixing capacity relative to other grain legumes [2,3]. Faba bean is the fourth most widely grown cool season grain legume (pulse) globally after pea (Pisum sativum), chickpea (Cicer arietinum) and lentil (Lens culinaris) (FAOSTAT 2019; https://www.fao.org, accessed on 15 September 2021). However, its yield is greatly affected by some environmental conditions, including biotic and abiotic stresses [3,4].

The necrotrophic fungus Botrytis fabae Sard. (teleomorph: Botryotinia fabae Lu & Wu) causes chocolate spot, which is one of the most destructive diseases for faba bean plants worldwide [5,6]. Infected plants exhibit chocolate-colored lesions on aboveground parts and, especially, on leaves. The disease, which starts in bean crops where inoculum is present in residues from previous years or in contaminated seeds [7], may be especially aggressive under high humidity and temperature conditions. Such conditions can lead to extensive necrosis of plant tissues and severe damage, and can also favor the spread of the pathogen to other plants [8]. Prolonged favorable conditions for B. fabae growth can result in considerable economic crop losses through reduced grain yields and quality [9]. The severity of chocolate spot epidemics can be mitigated with integrated disease management strategies, such as the use of clean seeds, crop rotations, lower planting densities, application of fungicides and selection of more resistant plant varieties [6,10]. Although some germplasm accessions have shown moderate to high levels of resistance [11], resistant cultivars adapted to different cultivation areas are scarcely available.

As a necrotrophic pathogen, B. fabae must kill and decompose host cells in order to feed on them. The fungus can infect plants via a variety of mechanisms mediated by lytic enzymes, toxins, stress-induced reactive oxygen species (ROS), necrosis-secreted proteins and a wide variety of secondary metabolites [12,13,14,15,16]. On the other hand, plants can stop the progression of the fungus by using constitutive or infection-induced mechanisms. Such mechanisms can be of the physical (cuticle and cell wall) [17,18] or chemical type (phytoanticipins and phytoalexins) [19], but can also involve induction of pathogenesis-related proteins or defensins, or accumulation of antimicrobial compounds [20,21].

Plants are known to accumulate ROS in response to necrotrophic fungi [22,23,24,25,26,27] and faba bean cultivars have been found to respond to B. fabae with differential ROS accumulation, lipid peroxidation and enzymatic ROS scavenging activity [28]. Recently, enhanced functionality in photosystem II (PSII), probably resulting from ROS accumulation in response to short-time exposure to B. cinerea, was reported in tomato plants [27]. However, little is known about the specific molecular mechanisms by which plants respond to B. fabae. A transcription factor (TF) analysis of the response of M. truncatula to B. fabae and B. cinerea [29] revealed some TFs to be involved in differential responses and others to be responsible for resistance to the two pathogens.

To our knowledge, few omics studies have focused on plant responses to Botrytis. As confirmed by using mutants at the transcriptomic level, Arabidopsis thaliana and tomato possess some genes whose expression is related to B. cinerea resistance. Such defense-related genes include some encoding PR protein 1 (PR1), β-1,3-glucanase and subtilisin-like protease, and other proteins involved in secondary metabolite synthesis (reviewed in 15), but still others are involved in responses to abiotic stresses, such as signaling hormone pathways, which affect photosynthesis, and protein synthesis and transport [15,30,31]. Even fewer proteomics studies have addressed plant–Botrytis interactions [32,33] and most have focused on the pathogen B. cinerea (reviewed in 15). Thus, Marra et al. used 2DE coupled to Matrix-Assisted Laser Desorption/Ionization (MALDI-TOF) analysis [32] to examine the interaction of beans with B. cinerea and Trichoderma. They found pathogenesis-related proteins and other disease-related factors, such as potential resistance genes, to be seemingly associated with interactions with both the pathogen and Trichoderma. In addition, a shotgun proteomic study of B. cinerea-infected tomato fruit at different ripening stages identified a substantial number of proteins responsible for pathogenicity (mainly PR and disease resistance proteins, proteases and peroxidases), as well as others protecting the fruit from the oxidative stress response by the host [33].

In the absence of a reference genome assembly for Vicia faba owing to its enormous size (13 Gbp) and complexity (e.g., abundance of transposable elements), high-throughput methods, such as transcriptome analysis, have proved efficient for enriching genomic resources (reviewed in 1). However, only limited DNA sequence data from reported transcriptome datasets have been made available on public databases [34]. Using high-throughput omic technology can no doubt help expand existing knowledge of the plant–pathogen interaction and provide a basis for developing improved crop breeding programs. The main aim of this work was to go deeper into the knowledge of the molecular mechanisms underlying the defense against B. fabae in faba bean. For this purpose, we studied the leave proteome in two faba bean genotypes that respond differently to B. fabae by using two-dimensional gel electrophoresis (2DE) in combination with (MALDI-TOF/TOF) mass spectrometry (MS). Some results of the MS analysis were validated by assays of protease activity in gels. Overall, the results suggest that the key to stopping the spread of the pathogen onto leaves is mainly a regulatory ROS production mechanism occurring in the chloroplast.

2. Materials and Methods

2.1. Plant Material and Sample Collection

Two faba bean genotypes known to exhibit a contrasting response to B. fabae were used, namely: Baraca as susceptible genotype and BPL710 as resistant genotype [10,35]. Seeds of the two genotypes were grown in 1 L pots filled with a (1:1) sand–peat mixture under controlled conditions: (20 ± 2) °C, 12 h dark/12 h light photoperiod and a photon flux density of 150 μmol m⁻² s⁻¹.

A total 27 plants per genotype were used, with leaves being sampled from 12 inoculated plants and 12 uninoculated (control) plants of each. Three other plants were inoculated and were used to score disease symptoms. Plants were inoculated according to Villegas-Fernandez et al. [35], with B. fabae local monosporic isolate (Bf-CO-05) being grown on Petri dishes containing V8 medium and spores suspended at a 4.5 × 10⁵ spores/mL concentration in a glucose/water solution (1.2% w/v). Three-week-old plants were then sprayed with the suspension at a rate of 1.5 mL/plant and incubated in a growth chamber at a relative humidity above 95% in the dark. By contrast, control (uninoculated) plants were sprayed with a glucose solution containing no spores. Disease symptoms were evaluated after restoring the photoperiod 24 h later but keeping the relative humidity above 90%. Evaluations were done two and six days after inoculation (dai). Disease severity (DS) was calculated by visual estimation of the proportion of plant surface covered with chocolate spots, with estimates being corrected by increasing the weight of the aggressive lesions by 50% with the formula DS = (% nonaggressive lesions) + 1.5 × (% aggressive lesions). The results thus obtained were analyzed statistically with the software Statistix 8 (Analytical Software, Tallahassee, FL, USA). Data were subjected to the arcsin √x transformation in order to offset evaluation bias and to increase normality in their distribution prior to analysis of variance (ANOVA).

Faba leaves for proteomic analyses were collected at two different times while both control and inoculated plants were still under incubation in the dark [35]. Sampling was done 6 h post-inoculation (hpi)—an early time at which no symptoms were apparent—and then 12 hpi—when the earliest symptoms of chocolate spots became macroscopically visible. All of the leaves from six individual plants (three biological replicates from two plants each) per condition (treatment and sampling time) were collected, frozen in liquid nitrogen and stored at −80 °C until protein extraction.

2.2. Protein Extraction and Gel Electrophoresis

Faba leaves samples (ca. 0.5 g fresh weight) from three independent replicates per treatment, sampling time and genotype were crushed with liquid nitrogen in a precooled mortar to obtain a fine powder. Proteins were extracted into TCA–phenol [36] and the resulting pellets were resuspended in a solubilization buffer containing 7 M urea (Merck, Kenilworth, NJ, USA), 2 M thiourea (Sigma–Aldrich, St. Louis, MI, USA), 2% (w/v) CHAPS (Sigma–Aldrich), 2% (v/v) Bio-Lyte 3–10 carrier ampholytes (BioRad, Hercules, CA, USA), 2% (w/v) DTT (Sigma–Aldrich) and Bromophenol Blue traces (Sigma–Aldrich). Protein concentrations were determined with the Bradford assay (BioRad) and proteins were then separated in 2D electrophoresis gels.

For 2DE analysis, 18-cm IPG DryStrips (Amersham Biosciences, Amersham, UK) were used with nonlinear pH gradients over the range 3–10. Strips were rehydrated passively for 6 h and then actively at 50 V for a further 6 h with 300 µL of sample buffer containing an amount of 400 µg of protein. Strips were loaded onto a PROTEAN IEF System (BioRad), focused at 20 °C with an increasing linear voltage and equilibrated according to Castillejo et al. [37]. They were then transferred onto vertical slabs of 10% SDS polyacrylamide gels. Electrophoresis runs were done at 30 V at 15 °C for 30 min, and then at 60 V for about 14 h until the dye front reached the bottom of the gel. The gels were loaded with broad-range molecular markers (Bio-Rad) and, after electrophoresis, stained with Coomassie Brilliant Blue G-250 [38].

2.3. Image Acquisition and Statistical Analysis

Gels were scanned with the Molecular imager FX ProPlus Multi-imager system (BioRad) and the images thus obtained (Supplementary Figure S1) were analyzed with the software PDQuest Advanced v. 8.0.1 (BioRad), using 10 times the background signal as the presence threshold for spots. The quantitative data gathered from the spots in each gel (viz., normalized spot volumes given as individual spot intensity/normalization factor) were used to designate differences when comparing gel images. A multivariate statistical analysis of the entire data set was performed by using the web-based software tool NIA array [39]. Those spots showing significant differences (p ≤ 0.05) in intensity, exhibiting a minimum change of ±2 and being consistently present among replicates were selected for further MS/MS analysis.

2.4. Protein Identification by Mass Spectrometry (MALDI-TOF/TOF)

Differential gel spots were excised for digestion with trypsin [40] and peptide fragments from digested proteins were analyzed by mass spectrometry. For that purpose, peptides were crystallized in an α-cyano-4-hydroxycinnamic acid matrix and subjected to MALDI-TOF/TOF analysis over the m/z range 800–4000 by using a 4800 Proteomics Analyzer (Applied Biosystems, Foster City, CA, USA) at an accelerating voltage of 20 kV. Spectra were internally calibrated against peptides from trypsin autolysis (M + H⁺ = 842.509, M + H⁺ = 2211.104) and the five most abundant peptide ions in each spectrum were used for fragmentation analysis to elucidate peptide sequences. A combined peptide mass fingerprinting (PMF)/tandem mass spectrometry (MS + MSMS) search was performed by using the software GPS Explorer™.5 (Applied Biosystems) over the nonredundant NCBInr database restricted to Viridiplantae taxonomy in combination with the MASCOT search engine (Matrix Science, London; http://www.matrixscience.com accessed on 15 September 2019). The following parameters were allowed: a minimum of two peptides matches and a single trypsin miscleavage, and peptide modifications by carbamidomethylcysteine and methionine oxidation. The maximum tolerance for peptide mass matching was limited to 20 ppm. The score level and a minimum of four peptides per protein were chosen as PMF confidence parameters. Proteins were characterized in functional terms against the NCBInr database (https://www.ncbi.nlm.nih.gov/guide/proteins/, accessed on 15 October 2021). In addition, BLAST analysis (tblastn) was performed for all the identified proteins using the reference transcriptome Vicia faba RefTrans v2 (2017), with 37,378 sequences deposited in Pulse Crops Database (https://www.pulsedb.org/, accessed on 15 October 2021). Only matches with an expectation (E) value of ≤ 1 × 10⁻⁶ were considered. Mass spectrometry analyses were conducted at the Proteomics Facility of the Central Research Support Service (SCAI) of the University of Córdoba (Spain).

2.5. Zymography

Proteins from leaves (200 mg of frozen powdered tissue) were extracted with a mixture of 200 mM TrisHCl at pH 7.4, 3% (w/v) insoluble polyvinylpolypyrrolidone (PVPP), 10% (v/v) glycerol, 5 mM diethiothreitol (DTT) and 0.25% (v/v) Triton X-100. Samples were allowed to stand on ice for at least 10 min and were then centrifuged at 16,000× g at 4 °C for 30 min, with the proteins present in the supernatant then being quantified with the Bradford assay [41].

SDS-PAGE slabs containing 0.1% gelatin and 9% acrylamide were analyzed according to Heussen and Dowdle [42]. Thus, samples containing 100 µg of protein were diluted with a nondenaturing Laemmli buffer [62.5 mM TrisHCl, 10% (v/v) glycerol, 0.001% (w/v) Bromophenol Blue] and loaded onto 1 mm thick gel slabs for electrophoresis at 50 V at 4 °C for 30 min, with the voltage being raised to 80 V until the front reached the end of the gel. The gels were loaded with Spectra Multicolor Broad Range Protein Ladder (Thermo Scientific). After electrophoresis, gels were incubated in 2.5% (v/v) Triton X-100 at room temperature under constant agitation for 30 min to remove SDS. They were then washed with distilled water three times to remove Triton X-100 and incubated in a proteolysis buffer (100 mM citrate buffer, Na₂HPO₄/citric acid pH 6.8, 4 mM DTT and 10 mM cysteine) under constant agitation at 35 °C overnight. Proteolysis was stopped by transferring the gels to a solution containing 0.1% (w/v) Coomassie Brilliant Blue R-250 [43]. Finally, the gels were destained in a solution containing 40% methanol and 10% acetic acid until clear bands formed over a dark blue background.

3. Results

3.1. Disease Assessment

As can be seen in Figure 1, twelve hpi symptoms of B. fabae infection were already visible in the susceptible genotype (Baraca), but not in the resistant genotype (BPL710). Analyses of variance of the DS results revealed that the Baraca genotype was strongly affected both 2 and 6 dpi (average DS 23.9 and 52.5, respectively). On the other hand, the BPL710 genotype was highly resistant (ANOVA p ≤ 0.05) in both samplings (average DS 11.6 and 14.6, respectively) (Figure 1; Supplementary Figure S2).

3.2. Two-Dimensional Gel Electrophoresis and MSMS Analysis

Image analysis with the software PDQuest allowed, on average, 224 individual protein spots to be detected (Figure 2a; Supplementary Table S1). In addition, a hierarchical clustering analysis clearly separated the genotypes into two clusters (Figure 2b), thus confirming the reproducibility of the experiment. Principal component analysis (PCA) allowed 194 differential protein spots from the entire dataset to be identified by comparing genotypes (susceptible and resistant) and treatments (uninoculated and inoculated) in both samplings (6 and 12 hpi) (Figure 2c). The first two principal components (PCs) jointly explained 70% of the total variability in the data, PC1 separating genotypes. The PCs for individual genotypes explained 74% and 86% of variability in the susceptible and resistant genotype, respectively (Figure 2d,e). In both cases, samples clustered by sampling times.

Spots were classified as variable if they met the following criteria: (a) being consistently present or absent in the three replicates under each set of experimental conditions; (b) exhibiting at least a two-fold change in abundance ratio; and (c) exhibiting statistically significant differences (p ≤ 0.05) between genotypes or treatments. A total of 129 protein spots were thus selected for MALDI-TOF/TOF analysis.

3.3. Protein Identification and Abundance Pattern Analysis

A protein search against the Viridiplantae index in the nonredundant NCBI database was performed and a total of 102 proteins were thus identified with high confidence (

Table 1. Proteins identified by MALDI-TOF MS analysis.

SSP a	Protein Name (% Identity to V. faba Transcriptome Entry) b	NCBI Accession	Score c	Species	PM c/ Coverage %	Mr/pI Experimental (Theoretical) d	Functional Category		More/Less Abundance Change Ratio (FDR) e
								S1	S2	R1	R2	$\frac{\mathit{R}}{\mathit{S}}1$	$\frac{\mathit{R}}{\mathit{S}}2$
3504	Enolase (93.3% Vf_0033189)	gi|42521309	261	Glycine max	10/28	57.2/5.7 (48.0/5.3)	Carbohydrate met.	3.0	6.3	1.0	1.0	0.0	0.0
6302	Isocitrate dehydrogenase [NADP], chloroplastic (88.1% Vf_0028303)	gi|2497259	153	Medicago sativa	17/40	44.9/6.2 (48.7/6.2)	Carbohydrate met.	0.4	9.0	0.8	0.6	1.2	0.6
2204	Fructose-1,6-bisphosphatase (93.2% Vf_0032848)	gi|5305145	109	Pisum sativum	4/14	40.0/5.5 (36.3/6.3)	Carbohydrate met.	16.4	6.7	1.7	0.2	0.4	0.9
6203	Fructose-bisphosphate aldolase, cytoplasmic isozyme 1 (77.9% Vf_0020212)	gi|1168408	352	Pisum sativum	15/54	39.4/6.5 (38.7/6.4)	Carbohydrate met.	1.1	3.8	1.5	1.5	0.3	0.1
4104	Fructose-bisphosphate aldolase 2, chloroplastic (80.6% Vf_0020212)	gi|461501	183	Pisum sativum	10/37	38.4/5.8 (38.0/5.5)	Carbohydrate met.	0.6	1.2	27.6	0.2	0.5	1.6
5103	Fructose-bisphosphate aldolase 2, chloroplastic (80.6% Vf_0020212)	gi|461501	474	Pisum sativum	17/51	36.8/6.3 (38.0/5.5)	Carbohydrate met.	3.8	1.9	27.7	0.0	0.3	1.5
105	N-glyceraldehyde-2-phosphotransferase-like (84.2% Vf_0017868)	gi|8885622	133	Arabidopsis thaliana	7/22	33.4/5.2 (32.0/5.1)	Carbohydrate met.	6.4	0.8	0.5	1.0	0.2	0.0
1007	Triose-phosphate isomerase (75.1% Vf_0012679)	gi|15226479	205	Arabidopsis thaliana	9/25	29.5/5.6 (33.6/7.7)	Carbohydrate met.	3.6	2.3	1.1	1.2	0.5	0.2
2002	Triose-phosphate isomerase (75.1% Vf_0012679)	gi|15226479	292	Arabidopsis thaliana	11/29	29.1/5.8 (33.6/7.7)	Carbohydrate met.	10.4	5.1	1.9	1.1	0.5	0.2
3004	Triose-phosphate isomerase (89.1% Vf_0024793)	gi|57283985	165	Phaseolus vulgaris	7/31	21.9/5.6 (27.4/5.9)	Carbohydrate met.	2.2	4.7	1.0	0.4	0.0	1.6
2705	Phosphoglucomutase, cytoplasmic (97.9% Vf_0002214)	gi|12585296	109	Pisum sativum	10/8	74.3/5.6 (63.5/5.5)	Carbohydrate met.	9.5	0.0	1.0	1.0	0.0	0.0
3702	Phosphoglucomutase, cytoplasmic (97.9% Vf_0002214)	gi|12585296	222	Pisum sativum	10/23	70.8/5.7 (63.5/5.5)	Carbohydrate met.	6.3	19.0	0.4	0.9	2.3	8.8
603	Beta-amylase (88.5% Vf_0019893)	gi|3913031	149	Medicago sativa	7/17	61.3/5.0 (56.5/5.3)	Major CHO met.	3.1	8.2	1.0	0.5	1.0	1.6
4808	Methionine synthase/Cobalamin- independent synthase family protein (94.5% Vf_0005324)	gi|219522337	104	Cicer arietinum	12/19	92.8/5.9 (84.6/6.0)	Amino acid met.	6.9	190.5	1.5	0.7	3.4	20.1
5805	Methionine synthase/Cobalamin- independent synthase family protein (94.5% Vf_0005324)	gi|219522337	312	Cicer arietinum	15/26	93.2/6.0 (84.6/6.0)	Amino acid met.	20.8	50.3	0.5	0.7	5.2	4.0
5808	Methionine synthase/Cobalamin- independent synthase family protein (94.5% Vf_0005324)	gi|219522337	344	Cicer arietinum	20/31	92.2/6.1 (84.6/6.0)	Amino acid met.	3.2	25.4	0.3	2.3	3.9	1.0
2402	Alanine aminotransferase (82.2% Vf_0008300)	gi|29569153	140	Oryza sativa	8/17	54.1/5.6 (54.0/8.0)	Amino acid met.	8.1	17.6	0.7	2.9	2.4	0.8
3402	Alanine aminotransferase 2 (82.2% Vf_0008300)	gi|29569153	104	Oryza sativa	4/9	54.1/5.7 (54.0/8.0)	Amino acid met.	63.4	0.0	1.3	1.4	51.7	11.9
1402	5-enolpyruvylshikimate 3-phosphate synthase (79.5% Vf_0032499)	gi|55740769	73	Camptotheca acuminate	8/14	52.1/5.2 (56.1/8.2)	Amino acid met.	0.0	1.0	1.0	1.0	0.0	1.0
3613	Ketol-acid reductoisomerase chloroplastic (97.3% Vf_0004275)	gi|6225542	560	Pisum sativum	23/43	61.5/5.7 (63.2/6.6)	Amino acid met.	12.0	0.5	0.7	0.4	2.2	0.4
7501	Serine hydroxymethyltransferase 2 (91.7% Vf_0037308)	gi|222142531	203	Glycine max	13/29	57.1/6.9 (55.0/8.2)	Amino acid met.	2.1	1.7	1.6	1.0	0.3	0.0
1104	Putative lactoylglutathione lyase (78.0% Vf_0028431)	gi|15810219	183	Arabidopsis thaliana	8/26	33.4/5.3 (32.0/5.1)	Amino acid met.	3.7	1.2	0.6	0.4	0.5	0.4
7602	Chain A, Dihydrolipoamide Dehydrogenase (99.6% Vf_0005095)	gi|9955321	337	Pisum sativum	22/62	57.4/6.4 (50.0/6.1)	Lipid metabolism	51.2	25.1	0.9	0.8	7.7	1.9
2102	Pyruvate dehydrogenase E1 component subunit beta, mitochondrial (96.1% Vf_0005095)	gi|1709454	171	Pisum sativum	6/18	39.3/5.5 (39.0/5.9)	Lipid metabolism	0.7	6.7	1.0	1.0	0.0	0.0
3705	Zeaxanthin epoxidase, chloroplastic (72.1% Vf_0030326)	gi|5902706	92	Solanum lycopersicum	5/9	74.3/5.8 (73.6/6.2)	Hormone met.	1.0	1.0	0.6	1.1	∞	∞
5601	Polyphenol oxidase A1, chloroplastic (98.5% Vf_0006701)	gi|1172586	254	Vicia faba	8/8	64.9/6.0 (68.9/7.0)	Pigment biosynt.	0.0	1.0	1.0	1.0	0.0	1.0
5603	Polyphenol oxidase A1, chloroplastic (98.5% Vf_0006701)	gi|1172586	253	Vicia faba	9/13	64.7/6.0 (68.9/7.0)	Pigment biosynt.	9.5	0.0	1.0	1.0	0.0	0.0
4607	Polyphenol oxidase A1, chloroplastic (98.5% Vf_0006701)	gi|1172586	274	Vicia faba	9/12	64.4/5.9 (68.9/7.0)	Pigment biosynt.	1.0	1.0	0.0	1.0	∞	1.0
4605	Polyphenol oxidase A1, chloroplastic (98.5% Vf_0006701)	gi|1172586	151	Vicia faba	11/13	61.8/5.8 (68.9/7.0)	Pigment biosynt.	8.7	0.6	1.0	1.0	0.0	0.0
2103	Coproporphyrinogen-III oxidase, chloroplastic (70.9% Vf_0022525)	gi|2493810	148	Nicotiana tabacum	4/11	38.6/5.6 (45.3/7.6)	Co-factor and vitamine met.	7.7	1.2	1.0	1.0	0.0	0.0
2601	ATP synthase CF1 alpha subunit (96.7% Vf_0021629)	gi|219673973	546	Trifolium subterraneum	19/36	59.9/5.4 (55.7/5.1)	Energy metabolism	2.1	2.7	28.2	0.0	1.5	4.6
1601	ATP synthase CF1 alpha subunit (95.3% Vf_0021629)	gi|139387459	126	Phaseolus vulgaris	9/20	57.0/5.3 (55.7/5.2)	Energy metabolism	0.6	1.2	1.5	1.3	22.4	2.3
604	ATP synthase CF1 beta subunit ATP synthase alpha/beta family protein (97.6% Vf_0007913)	gi|295136979	572	Pisum sativum	18/48	58.9/5.2 (53.2/5.1)	Energy metabolism	0.7	2.7	1.0	1.6	9.0	2.3
505	ATP synthase CF1 beta subunit ATP synthase alpha/beta family protein (97.6% Vf_0007913)	gi|295136979	882	Pisum sativum	26/65	57.9/5.2 (53.2/5.1)	Energy metabolism	2.0	17.9	1.2	1.9	5.8	9.5
1503	ATP synthase CF1 alpha subunit (95.4% Vf_0021629)	gi|295137014	573	Pisum sativum	21/38	56.5/5.3 (54.7/5.7)	Energy metabolism	4.5	3.2	1.2	0.9	3.9	2.7
1501	ATP synthase CF1 beta subunit ATP synthase alpha/beta family protein (97.6% Vf_0007913)	gi|295136979	755	Pisum sativum	21/51	56.2/5.2 (53.2/5.1)	Energy metabolism	2.4	1.5	1.3	1.2	1.5	1.2
9701	Sulfite reductase (96.4% Vf_0029426)	gi|119225844	129	Pisum sativum	17/25	75.6/8.8 (77.3/9.1)	S metabolism	∞	1.0	1.0	1.0	1.0	1.0
3704	Transketolase (95.5% Vf_0028016)	gi|4586600	214	Cicer arietinum	3/30	82.8/5.8 (17.1/5.8)	Photosynthesis	11.3	7.0	1.2	1.0	35.9	3.2
3706	Transketolase (95.5% Vf_0028016)	gi|4586600	91	Cicer arietinum	4/44	82.7/5.8 (17.1/5.8)	Photosynthesis	4.0	4.0	1.0	0.5	18.0	2.8
4704	Transketolase (95.5% Vf_0028016)	gi|4586600	86	Cicer arietinum	4/44	82.5/5.9 (17.1/5.8)	Photosynthesis	3.8	17.1	0.6	0.7	6.4	1.7
4702	Transketolase (95.5% Vf_0028016)	gi|4586600	189	Cicer arietinum	5/48	81.6/5.8 (17.1/5.8)	Photosynthesis	3.8	3.1	1.0	1.1	8.1	1.5
1604	RuBisCO large subunit-binding protein subunit beta chloroplastic/chaperonin subunit beta (96.3% Vf_0035079)	gi|2506277	423	Pisum sativum	16/39	67.8/5.5 (63.3/5.8)	Photosynthesis	19.1	30.5	0.9	0.4	11.5	9.4
2602	RuBisCO large subunit-binding protein subunit beta chloroplastic/chaperonin subunit beta (96.3% Vf_0035079)	gi|2506277	72	Pisum sativum	11/27	66.8/5.6 (63.3/5.8)	Photosynthesis	1.8	2.4	2.2	0.5	1.9	1.5
1606	RuBisCO large subunit-binding protein subunit beta chloroplastic/chaperonin subunit beta (96.3% Vf_0035079)	gi|2506277	257	Pisum sativum	10/26	65.7/5.5 (63.3/5.8)	Photosynthesis	0.9	3.7	1.5	0.5	5.9	4.1
601	RuBisCO large subunit-binding protein subunit alpha chloroplastic /chaperonin-60alpha (98.4% Vf_0031659)	gi|1710807	480	Pisum sativum	19/36	65.8/5.0 (62.0/5.2)	Photosynthesis	2.4	5.2	0.7	0.2	1.0	3.3
4501	Ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (95.9% Vf_0007913)	gi|825737	556	Carya illinoinensis	20/40	57.1/5.8 (51.6/6.1)	Photosynthesis	26.5	7.5	0.5	37.7	4.3	2.8
4505	Ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (96.5% Vf_0007913)	gi|33113311	584	Carya ovate	23/42	55.8/5.9 (51.4/6.1)	Photosynthesis	5.1	1.7	6.2	1.4	41.3	3.3
4406	Ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (95.6% Vf_0007913)	gi|21634071	485	Cressa depressa	23/44	55.5/5.8 (50.6/6.7)	Photosynthesis	3.3	4.3	0.1	17.6	38.4	17.3
5507	Ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (96.4% Vf_0007913)	gi|225544093	709	Caragana camilli-schneideri	25/45	54.4/6.0 (52.8/6.3)	Photosynthesis	1.9	1.4	0.8	2.4	41.8	2.0
5408	Ribulose-1,5-bisphosphate carboxylase/ oxygenase (95.7% Vf_0007913)	gi|74179244	619	Aristolochia arborea	23/44	52.5/6.1 (52.0/6.1)	Photosynthesis	14.6	1.3	0.9	0.7	21.7	7.2
5407	Ribulose-1,5-bisphosphate carboxylase/ oxygenase large subunit (95.3% Vf_0007913)	gi|62861204	759	Paracroton zeylanicus	25/50	50.8/6.2 (52.0/6.0)	Photosynthesis	14.1	0.9	0.6	0.9	11.2	3.7
2304	Phosphoglycerate kinase chloroplastic (86.1% Vf_0006851)	gi|129915	192	Triticum aestivum	9/19	49.6/5.6 (50.0/6.6)	Photosynthesis	96.2	2.6	1.0	1.0	0.0	0.0
2301	Phosphoglycerate kinase chloroplastic (86.1% Vf_0006851)	gi|129915	254	Triticum aestivum	7/16	46.1/5.6 (50.0/6.6)	Photosynthesis	12.8	3.9	6.9	0.8	6.3	4.6
2303	Phosphoglycerate kinase chloroplastic (85.6% Vf_0006851)	gi|2499497	571	Nicotiana tabacum	15/33	44.5/5.6 (50.3/8.5)	Photosynthesis	3.2	3.7	2.5	1.5	3.7	1.7
7503	Ribulose-1,5-bisphosphate carboxylase/ oxygenase large (95.9% Vf_0007913)	gi|825737	372	Carya illinoinensis	21/42	56.2/6.7 (51.6/6.1)	Photosynthesis	3.5	6.8	0.9	1.8	98.3	3.2
6418	Ribulose-1,5-bisphosphate carboxylase/ oxygenase (95.7% Vf_0007913)	gi|74179244	589	Aristolochia arborea	24/42	53.7/6.3 (52.0/6.1)	Photosynthesis	15.2	1.7	0.8	1.4	1.3	2.5
8308	Geranylgeranyl hydrogenase (91.3% Vf_0032793)	gi|19749359	267	Glycine max	18/38	48.6/8.7 (51.7/9.1)	Photosynthesis	1.7	5.0	0.9	0.4	2.1	5.9
203	Sedoheptulose-1,7-bisphosphatase (81.8% Vf_0007079)	gi|229597543	230	Cucumis sativus	9/21	42.8/5.2 (42.5/5.9)	Photosynthesis	2.4	3.2	1.0	0.7	1.6	1.4
3202	Sedoheptulose-1,7-bisphosphatase (81.8% Vf_0007079)	gi|229597543	215	Cucumis sativus	12/34	42.6/5.6 (42.5/5.9)	Photosynthesis	5.5	11.2	1.5	3.3	1.7	1.5
1204	Phosphoribulokinase (99.1% Vf_0003052)	gi|1885326	350	Pisum sativum	14/46	41.4/5.4 (39.2/5.4)	Photosynthesis	2.4	2.5	4.8	0.9	2.3	2.7
2202	Phosphoribulokinase (99.1% _0003052)	gi|1885326	160	Pisum sativum	7/27	41.1/5.5 (39.2/5.4)	Photosynthesis	1.2	1.5	1.2	0.8	3.4	2.0
1201	Photosystem II stability/assembly factor HCF136, chloroplast precursor (78.8% Vf_0033934)	gi|255559812	237	Ricinus communis	8/20	41.1/5.3 (43.4/7.1)	Photosynthesis	1.3	2.2	1.8	2.0	0.5	0.3
3107	Aldolase (80.8% Vf_0017749)	gi|169039	137	Pisum sativum	9/27	38.5/5.6 (38.0/5.5)	Photosynthesis	2.3	1.6	5.3	1.2	0.3	1.7
3105	Aldolase (80.8% Vf_0017749)	gi|169039	88	Pisum sativum	8/29	38.0/5.6 (38.0/5.5)	Photosynthesis	0.0	0.1	∞	0.8	0.0	0.1
1001	Chloroplast chlorophyll a/b binding protein (99.2% Vf_0037012)	gi|157786302	265	Pisum sativum	10/34	30.3/5.2 (28.4/5.5)	Photosynthesis	0.9	0.8	6.8	0.9	0.3	1.4
4306	Transaminase mtnE, putative (80.9% Vf_0021772)	gi|255562088	159	Ricinus communis	5/11	46.2/5.9 (50.9/6.9)	Photosynthesis	1.2	4.4	1.0	1.0	0.0	0.0
401	Chloroplast ribulose-1,5-bisphosphate carboxylase activase (81.0% Vf_0005564)	gi|115392208	122	Triticum aestivum	6/21	51.7/5.1 (40.3/6.5)	Photosynthesis	0.9	0.0	1.0	1.0	0.0	0.0
1502	UDP-glucose pyrophosphorylase (89.7% Vf_0034269)	gi|12585472	271	Astragalus penduliflorus	12/29	54.1/5.3 (51.6/5.9)	Protein synthesis	1.1	2.3	1.0	1.0	0.0	0.0
2801	ClpC protease (92.1% Vf_0007069)	gi|4105131	70	Spinacia oleracea	12/16	96.6/5.6 (99.6/8.8)	Protein degrad.	6.7	8.8	0.5	0.4	8.9	2.7
2804	ClpC protease (98.5% Vf_0007069)	gi|461753	145	Pisum sativum	19/26	96.1/5.6 (102.8/6.6)	Protein degrad.	5.3	1.6	0.3	1.4	20.0	1.2
1802	ATP-dependent Clp protease (98.5% Vf_0007069)	gi|461753	383	Pisum sativum	26/33	95.3/5.3 (102.8/6.6)	Protein degrad.	2.3	6.4	1.5	1.2	1.1	1.7
2703	Cell division protease ftsH homolog, chloroplastic (91.1% Vf_0034616)	gi|17865463	262	Medicago sativa	16/30	75.4/5.6 (75.8/5.6)	Protein degrad.	5.9	7.0	1.1	1.6	0.9	0.2
2707	Cell division protease ftsH homolog chloroplastic (91.1% Vf_0034616)	gi|17865463	140	Medicago sativa	10/19	74.8/5.7 (75.8/5.6)	Protein degrad.	14.1	60.9	0.6	0.8	4.0	3.5
2706	Cell division protease ftsH homolog, chloroplastic (91.1% Vf_0034616)	gi|17865463	315	Medicago sativa	21/38	70.9/5.7 (75.8/5.6)	Protein degrad.	2.9	6.0	0.6	1.2	2.7	0.9
1702	Putative zinc dependent protease/FTSH protease 8 (87.0% Vf_0002195)	gi|84468324	206	Trifolium pretense	11/22	74.5/5.3 (75.4/5.5)	Protein degrad.	∞	8.0	0.7	1.6	∞	1.2
2101	Serine-type endopeptidase (96.5% Vf_0035526)	gi|270342123	70	Phaseolus vulgaris	5/15	39.5/5.4 (45.2/7.7)	Protein degrad.	∞	1.0	1.0	1.0	1.0	1.0
2802	Ubiquitin-specific-processing protease 8 (62.7% Vf_0023012)	gi|257050978	61	Arabidopsis thaliana	13/27	99.1/5.2 (90.7/5.5)	Protein degrad.	1.0	10.4	1.0	1.0	1.0	0.0
3803	ATP-dependent Clp protease/CLPC homologue 1 (98.5% Vf_0007069)	gi|461753	308	Pisum sativum	19/26	83.8/5.7 (102.8/6.6)	Protein degrad.	7.3	13.4	1.7	1.6	8.2	3.0
702	Chaperone DnaK (stromal 70 kDa heat shock-related protein, chloroplastic) (93.7% Vf_0024557)	gi|92870233	955	Medicago truncatula	27/38	81.5/5.0 (75.8/5.2)	Stress response	3.5	4.5	1.6	0.6	4.2	3.0
1701	Heat shock protein 70 (92.1% Vf_0006213)	gi|56554972	562	Medicago sativa	23/40	81.8/5.3 (71.4/5.1)	Stress response	3.6	4.5	2.1	0.8	1.7	5.3
2701	Heat shock 70 kDa protein mitochondrial (93.1% Vf_0016658)	gi|585272	216	Pisum sativum	14/26	76.2/5.6 (72.4/5.8)	Stress response	13.1	11.1	1.0	1.0	0.0	0.0
4302	Monodehydroascorbate reductase I (92.0% Vf_0006284)	gi|51860738	167	Pisum sativum	10/24	47.9/5.8 (47.4/5.8)	Stress response	3.7	2.2	6.4	1.0	1.4	0.3
3001	L-ascorbate peroxidase, cytosolic (60.9% Vf_0035596)	gi|1351963	171	Pisum sativum	8/34	31.0/6.1 (27.2/5.5)	Stress response	1.9	0.5	1.1	0.6	0.5	2.1
3103	CDSP32 protein (Chloroplast Drought-induced Stress Protein of 32 kDa) (69.4% Vf_0033087)	gi|2582822	133	Solanum tuberosum	4/14	33.8/6.0 (33.8/8.1)	Stress response	0.9	0.8	0.3	0.2	0.4	0.7
1206	NADPH-dependent alkenal/one oxidoreductase, chloroplastic (85.3% Vf_0022282)	XP_003532009.1	190	Glycine max	6/28	40.6/5.4 (31.2/9.2)	Redox	1.0	1.0	1.0	∞	1.0	1.0
11	Thioredoxin peroxidase (80.1% Vf_0034677)	gi|21912927	108	Nicotiana tabacum	3/16	21.6/5.2 (30.1/8.2)	Redox	2.4	0.3	16.3	0.6	0.0	0.7
5305	GDP-D-Mannose 3′,5′-Epimerase (90.2% Vf_0021019)	gi|15241945	108	Arabidopsis thaliana	8/26	49.6/6.0 (43.1/5.8)	Cell wall	8.0	19.0	1.0	1.0	0.0	0.0
502	Hydroxyproline-rich glycoprotein family protein	gi|18411523	147	Arabidopsis thaliana	9/13	60.7/4.8 (49.4/5.2)	Cell wall	3.8	2.0	0.8	0.7	0.8	0.6
4404	Gdp-Mannose-3′, 5′-Epimerase (89.9% Vf_0021019)	gi|83754656	112	Arabidopsis thaliana	9/22	50.6/5.9 (43.2/5.8)	Cell wall	0.5	3.7	1.0	1.0	0.0	0.0
101	PAP fibrillin (84.1% Vf_0025094)	gi|87240799	268	Medicago truncatula	8/18	34.4/4.9 (34.1/4.9)	Cell organization	1.4	1.7	1.8	0.5	0.2	1.5
1308	Actin (99.7% Vf_0005527)	gi|34541966	560	Trifolium pretense	16/51	47.9/5.5 (41.9/5.3)	Cell organization	0.7	12.9	0.4	7.7	3.1	0.5
1404	Actin (99.1% Vf_0028038)	gi|1498334	113	Glycine max	8/39	49.3/5.3 (37.3/5.5)	Cell organization	2.6	11.5	1.0	1.0	0.0	0.0
1304	Actin (99.7% Vf_0005527)	gi|34541966	431	Trifolium pretense	16/53	49.0/5.3 (41.9/5.3)	Cell organization	0.8	8.7	1.0	1.8	0.5	0.6
3205	Actin (94.3% Vf_0008358)	gi|1498384	172	Zea mays	5/19	39.7/5.6 (37.3/5.5)	Cell organization	0.0	6.4	1.0	1.0	0.0	0.0
3302	Elongation factor Tu (97.5% Vf_0005994)	gi|6015084	284	Pisum sativum	17/35	48.1/5.6 (53.1/6.6)	Transcription/ Translation	∞	2.8	2.5	1.2	∞	0.8
3309	Elongation factor Tu (97.5% Vf_0005994)	gi|6015084	480	Pisum sativum	22/43	47.9/5.7 (53.1/6.6)	Transcription/ Translation	0.3	13.0	11.7	2.2	1.7	1.4
3307	Elongation factor Tu (97.5% Vf_0005994)	gi|6015084	584	Pisum sativum	22/46	47.7/5.7 (53.1/6.6)	Transcription/ Translation	7.6	7.5	1.0	0.9	11.6	8.2
9401	Elongation factor 1 alpha (96.9% Vf_0022300)	gi|61741088	201	Actinidia deliciosa	16/37	54.0/9.0 (49.6/9.2)	Transcription/ Translation	4.4	4.8	1.3	2.4	7.0	4.9
3603	Tic62 protein (89.8% Vf_0007594)	gi|21616072	99	Pisum sativum	7/24	61.8/5.7 (57.1/8.8)	Signaling	1.0	0.0	1.0	1.0	1.0	0.0
1708	V-type proton ATPase catalytic subunit A (95.9% Vf_0002956)	gi|12585490	146	Citrus unshiu	17/42	74.4/5.5 (68.9/5.3)	Transport	8.9	54.4	0.7	1.2	3.8	5.3
5002	Carbonate dehydratase (64.2% Vf_0022150)	gi|47606728	105	Flaveria bidentis	3/17	30.3/6.2 (35.9/5.8)	Miscellaneous	1.3	5.8	1.3	0.6	0.5	3.1
6003	Carbonic anhydrase (85.8% Vf_0022150)	gi|270342124	153	Phaseolus vulgaris	7/34	29.0/6.5 (35.9/8.1)	Miscellaneous	0.9	0.5	3.3	∞	0.2	0.0

^a Standard spot number assigned to each spot protein (SSP) by PDQuest software (BioRad). ^b Percentages of identity to V. faba transcriptome entries [Vicia faba RefTrans V2 (2017) (https://www.pulsedb.org/, accessed on 15 October 2021)] obtained by Blast (tblastn) analysis are displayed in brackets. The coding “v.faba_CSFL_reftransV2_number” has been simplified by “Vf_number” for each transcript. ^c PM: number of peptides matched (from peptide mass fingerprinting) with the homologous protein from the database. Some of these peptides were automatically MSMS fragmented. ^d Experimental mass (Mr, kDa) and pI were calculated with PDQuest software and standard molecular mass markers. Theoretical values were retrieved from the protein database (NCBInr). ^e Values are given as normalized volume (calculated with PDQuest software) and represent change ratios in response to B. fabae inoculation of each genotype (S: Baraca; R: BPL710), and between uninoculated genotypes (R/S) at both sampling times (1: 6 hpi; 2: 12 hpi).

; Supplementary Figure S3), 70% of which matched legume species. Most of the proteins met the confidence identification criteria [viz., a score higher than 70 and at least four peptides per protein except for three spot proteins (viz., SSP 2802, 5002 and 11, which should be considered with caution)]. The proteins thus identified belonged to the main functional groups of energy and primary metabolism [photosynthesis (30) and other energy metabolism (6), carbohydrate (12) and amino acid metabolism (9)], followed by proteins of degradation (10), redox and response to stress groups (8) (Figure 3a).

Figure 3b compares treatments, genotypes and sampling times. The susceptible genotype (S) showed the largest number of changes in proteins in response to inoculation, but mainly in those of the primary and energy metabolism groups (Figure 3b). In fact, a strikingly large number of degradation proteins showed changes in S genotype in response to inoculation that were not observed in the resistant genotype (R). The group of degradation proteins comprised ten proteases, namely: three cell division proteases ftsH chloroplastic (gi|17865463), two ATP-dependent Clp proteases (gi|461753), two Clp proteases (gi|4105131, gi|461753), one ubiquitin-specific protease 5 (gi|257050978), one zinc dependent protease/FTSH protease 8 (gi|84468324) and one serine-type endopeptidase (gi|270342123). Interestingly, most of the identified proteases were significantly increased in response to inoculation in the susceptible genotype but, as revealed by the heat map (Figure 4a, Table 1), none was in the resistant genotype. A comparison of the uninoculated leaf proteome revealed a much greater number of proteins of the energy metabolism and protein degradation groups in R than in S, mainly in the first sampling (Figure 3b and Figure 4a). In addition, these functional groups were increased in control S plants in the second sampling.

3.4. Protease Gel Activity

The results of the protease gel activity assay confirmed those previously obtained by MS. Protease bands corresponding to high molecular weights (~90 to 120 kDa) were stronger in inoculated plants of the susceptible genotype in both samplings, coinciding with the molecular weight of some proteases identified by MALDI-TOF (viz., Clp proteases, SSPs 1802, 2801, 2804, 3803; and Ubiquitin-specific-processing protease 8, SSP 2802) (Figure 4b; Supplementary Figure S4). Gel activity assay also exposed a strong band at 40 kDa not changing substantially with the specific conditions and potentially corresponded to the serine-type endopeptidase identified by MS analysis (SSP 2101). In any case, the most striking result was the presence of two well-defined protease bands at high molecular weights (140–250 kDa) that were especially strong in the resistant genotype (and, particularly, in the second sampling). The area of the protease activity bands were estimated using ImageJ software (ImageJ.JS (imjoy.io)), and the data are presented in Supplemental Figure S5. Since activity gels were used under native conditions and 2DE-MS analyses conducted under denaturing conditions, these bands may well correspond to protein complexes not identified with the denaturing gels.

4. Discussion

Botrytis fabae is a necrotrophic plant pathogen causing chocolate spot, which is one of the most devastating diseases for faba bean production worldwide [5,6]. The mechanism by which plants counteract infection by this pathogen is of great agronomic interest. ROS production (especially H₂O₂ induction by Botrytis) is known to occur in a wide variety of plants [23,25,26,27] and to be one of the earliest plant responses to fungal infection [22,24]. Botrytis fabae reportedly increases lipid peroxidation, and the levels of ROS and antioxidant enzymes (superoxide dismutase, catalase and ascorbate peroxidase), substantially in faba bean [28]. In fact, ROS were found to accumulate rapidly in leaf tissue of a resistant cultivar at early stages of infection, but more markedly and over longer periods at later stages in its susceptible counterpart [28].

4.1. The Role of Chloroplasts as Redox Sensors Eliciting an Acclimatory Response to Stressing Conditions

ROS accumulation at an early stage of infection is triggered by plasma membrane-bound NADPH oxidases and typically occurs in the apoplast [44]. However, chloroplastic and peroxisomal ROS production have been reported to contribute to plant immunity as well [45,46]. Although ROS can also be produced by other organelles (notably peroxisomes and mitochondria), the chloroplast is possibly a major source. Some proteins in the chloroplast are involved in cross-talk with the cytosol and nucleus to govern the outcome of defense signaling [47]. Besides triggering ROS signals, chloroplasts can perceive, mediate or even amplify ROS signals originating in the apoplast [48]. In addition, there is evidence that the role of chloroplastic ROS production in coordinating cell death or modulating defense outputs is highly specific in targeting various types of invading pathogens. Thus, some chloroplastic components may be specific targets for microbial effector molecules, which suggest that chloroplasts communicate through these target molecules to elicit ROS production in the apoplast, presumably to contain spread of the lesion [49].

Chloroplast-derived ROS has been shown to play a role in plant resistance against B. cinerea [27,50]. Thus, histochemical analysis revealed ROS accumulation in tomato leaves 24 h after application of B. cinerea spores. A defense response accompanied by an improvement in photosystem II (PSII), possibly triggered by ROS upon short-time exposure, was observed. However, the relatively increased time of exposure to these molecules made them harmful to PSII functionality [27,51]. In addition, H₂O₂ levels in strawberry leaves were found to correlate positively with disease severity, and to be influenced by both leaf age and light quality [52].

Through photosynthesis, chloroplasts play a central role as redox sensors of environmental conditions by eliciting acclimatory or stress-defense responses [53,54]. In chloroplasts, chaperone systems refold proteins after stress, while proteases degrade misfolded and aggregated proteins that cannot be refolded [55]. A study on Arabidopsis thaliana demonstrated a major role of Hsp70 chaperones and Clp proteases in the folding and degradation of misfolded or damaged proteins under variable stress conditions in the chloroplast [55]. Caseinolytic proteases (Clps) function as molecular chaperones and confer thermotolerance to plants. The results of a differential gene expression analysis of Clps in wheat suggest a potential role in cold, salt and biotic stresses, and confirm the previously reported role in thermotolerance [56]. ClpATPases class I (ClpB/HSP100 and ClpC) function in assembly and disassembly with protein complexes, acting together with the HSP70/DnaK chaperone system to remodel denatured protein aggregates [57]. On the other hand, plant ClpC proteins act as stromal molecular chaperones in importing and protecting unfolded newly synthesized proteins, which are responsible for maintaining homeostasis [58,59,60,61].

In the present work two ATP-dependent Clp, two ClpC proteases and three Hsp70 (one as Chaperone DnaK) were found to be considerably increased in the susceptible genotype in response to inoculation. This result suggests that the chloroplast may respond to B. fabae inoculation by triggering a mechanism to repair damaged proteins. The previous proteins were highly represented at the constitutive level in resistant uninoculated plants, which may represent a temporary advantage in response to the pathogen.

4.2. Homeostatic Control as a Dynamic Regulation Mechanism for Energy and Redox Status in Response to Botrytis fabae

Enhanced photosystem II (PSII) functionality at the early stages of pathogen infection may be responsible for the increased sugar production required to strengthen the response by inducing defense genes [27,62]. However, B. cinerea has been reported to use large amounts of soluble sugars to grow on tomato leaves [63].

Nonphotochemical chlorophyll fluorescence quenching (NPQ) is the key photoprotective process used by plants to dissipate excess light energy as heat and preserve photosynthesis as a result [64,65,66,67]. A substantial increase in NPQ was observed in tomato leaflets up to 6 h after application of a B. cinerea spore suspension; the increase, however, was followed by a decrease down to control levels [27]. This outcome suggests an imbalance between energy supply and demand, resulting in increased ROS production similarly as in photoinhibition, causing damage in chloroplast and eventual cell death (necrosis) [68].

On physiological grounds, Clp and FtsH proteases are believed to play major roles in chloroplast protein homeostasis. Thus, FtsH (filamentation temperature sensitive H) proteases are membrane-bound ATP-dependent zinc metalloproteases involved in the biogenesis of thylakoid membranes and quality control in the PSII repair cycle [69]. ROS production and PSII photodamage are linked to the high turnover rate of the D1 reaction center protein, which is degraded and replaced with de novo synthesized protein in the so-called “PSII repair cycle” [70]. FtsH proteases are among the many components mediating coordinated turnover in D1. In addition, there is evidence that programmed inhibition of the PSII repair cycle through specific downregulation of protease activity may provide plants with a mechanism to elicit ROS production and cell death upon infection [71].

In parallel to the recognition of ROS as key signaling molecules, antioxidant enzymes and ROS scavenging, scientists have accepted their potential involvement in fine-tuning defense reactions. In chloroplasts, the antioxidants ascorbate and glutathione contribute chemically to ROS quenching. In addition, H₂O₂ can be detoxified by ascorbate peroxidases (APX), peroxiredoxine (PRX) or glutathione peroxidase (GPX), reviewed in [72], as confirmed by a study on Gentiana triflora which suggested that PRXQ plays a role in mediating responses against the necrotrophic fungus B. cinerea [73].

The proteomic analysis conducted in this work revealed that three proteins identified as chloroplastic cell division protease FtsH, and a zinc dependent protease/FTSH protease 8, were highly represented in the susceptible genotype in response to B. fabae inoculation. The same proteins were better represented constitutively in the resistant genotype in the first sampling. In addition, a monodehydroascorbate reductase I, an L-ascorbate peroxidase and a thioredoxin peroxidase were also better represented in both genotypes in response to inoculation in the first sampling. Zymogram analysis confirmed the results of the MS analysis, where differences in the activity bands at the molecular weights of the proteins identified by 2DE-MS were observed. In addition, inoculated and uninoculated plants of the resistant genotype exhibited some activity bands at very high molecular weights (140–250 kDa) that were not clearly observed in the susceptible genotype. This result can be ascribed to differences in the experimental conditions, which were native in the zymograms and denaturing in the 2DE-MS analysis.

Consistent with the results obtained in this work, a recent study on tomato plants revealed H₂O₂ production and enhanced photosystem II functionality 30 min after B. cinerea inoculation. The effect, which lasted 4 h, was suggestive of a tolerant response; however, increasing the length of exposure led to plant damage [27] by fully inhibiting PSII functionality at the application spot and nearby. This was probably a time-dependent hormetic response, suggesting a positive biological response whose effect might be reversed upon extended exposure [27,67].

5. Conclusions

Based on the proteins identified in this study (Clp and Hsp70, together with FstH proteases and ROS proteins) and their increased levels upon inoculation with B. fabae, a signaling response mechanism based on ROS production in the chloroplast may be elicited by the fungus. This mechanism appears to be harmful to PSII in the susceptible genotype by effect of its being associated with lengthy exposures to high ROS levels. The differential response of the two genotypes can be ascribed to a metabolic imbalance in the susceptible genotype not observed in the resistant genotype and confirming that the latter retains normal metabolism under stress. On the other hand, there is evidence that the two genotypes differ in chloroplast detoxification system, the resistant genotype exhibiting a more efficient PSII repair mechanism at the early stages of infection. Further research is required in any case to ascertain whether the ROS dose or exposure time (hormesis) is associated with the differential V. faba phenotypes.