Proteo-Molecular Investigation of Cultivated Rice, Wild Rice, and Barley Provides Clues of Defense Responses against Rhizoctonia solani Infection

Rhizoctonia solani is a soil-borne fungus causing sheath blight disease in cereal crops including rice. Genetic resistance to sheath blight disease in cereal crops is not well understood in most of the host(s). Aside from this, a comparative study on the different hosts at the biochemical and proteomic level upon R. solani infection was not reported earlier. Here, we performed proteomic based analysis and studied defense pathways among cultivated rice (cv. Pusa Basmati-1), wild rice accession (Oryza grandiglumis), and barley (cv. NDB-1445) after inoculation with R. solani. Increased levels of phenol, peroxidase, and β-1, 3-glucanase were observed in infected tissue as compared to the control in all of the hosts. Wild rice accession O. grandiglumis showed a higher level of biochemical signals than barley cv. NDB 1445 and cultivated rice cv. Pusa Basmati-1. Using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS), differently expressed proteins were also studied in control and after inoculation with R. solani. Wild rice accession O. grandiglumis induced a cysteine protease inhibitor and zinc finger proteins, which have defense functions and resistance against fungal pathogens. On the other hand, barley cv. NDB-1445 and cultivated rice cv. Pusa Basmati-1 mainly induce energy metabolism-related proteins/signals after inoculation with R. solani in comparison to wild rice accession O. grandiglumis. The present comprehensive study of R. solani interaction using three hosts, namely, Pusa Basmati-1 (cultivated rice), O. grandiglumis (wild rice), and NDB-1445 (barley) would interpret wider possibilities in the dissection of the protein(s) induced during the infection process. These proteins may further be correlated to the gene(s) and other related molecular tools that will help for the marker-assisted breeding and/or gene editing for this distressing disease among the major cereal crops.


Introduction
The fungal pathogen Rhizoctonia solani has pathogenicity over a broad range of host plants. R. solani causes sheath blight (ShB) in rice and is responsible for up to 25% of yield losses [1]. This necrotic fungal pathogen has a considerable effect on the production of an extensive range of plants imperative to humanity, including the 15 largest food crops worldwide, and causes root rot disease in wheat and barley [2]. Despite cost-effective treatments and the large impact of the pathogen, very little is known about how it causes disease in the cereal crops. ShB disease management has been largely achieved through systemic fungicides and certain non-systemic fungicides, namely, captaf, mancozeb, pencycuron [1-(4-chlorobenzyl)-1-cyclopentyl3-phenylurea], etc. However, these chemical fungicides harshly affect environmental conditions as pertains to beneficial microorganisms and others present in the atmosphere [3]. Uses of the chemical fungicides raise the cultivation outlay of the crops. Resistance to R solani varied among cereal crop species [4], thus, the information on resistant host cultivars and the defense mechanisms studied against ShB have become an essential concern in the present scenario. Several genetic loci have been identified that can confer minor resistance against R. solani [5]. Therefore, identification of tolerant or resistant genotypes is of prime importance for categorizing the crops for susceptibility and resistance to this necrotic disease [6].
Few studies identified that farm soil type can also influence the severity of the disease. There are several reports where resistance has been identified in the wild rice and other hosts against different diseases [7]; further, it was also reported that the wild relative of rice has not only an agronomically important gene, but also superior genetic diversity in resistant genes as compared to cultivated rice. In cereal crops, resistance against R. solani is governed by quantitative traits [8], and these traits might be associated with broadspectrum resistance. Up to 50-60% of defense-related alleles are lost in cultivated rice in resemblance to wild rice [9]. The researchers' intentions are to sort new rice genotypes with improved disease resistance and to improve yield potential using genomic and molecular information to shatter the rice yield plateau [10]. Few early studies attempted to look for the detail of the mode of rice infection by sheath blight pathogen, which can be further utilized for the conception of resistance mechanisms against R. solani [1]. R. solani isolates produce hydrolytic enzymes such as cellular cellulase, pectolytic, and protease enzymes which help in the invasion of the host's primary line of defense [11]. These induced toxins produced by R. solani have corresponded with sheath susceptibility in rice. Several mechanisms, including redox regulation, reactive oxygen species (ROS) formation, signal transmission, and metabolic alterations, were involved in the defensive routes against the R. solani pathogen in cereals [12]. The biomolecules which were induced after R. solani infection have been linked to basal resistance in several crops including rice [13].
Rice resistance to ShB is a typical quantitative attribute governed by many genes or quantitative trait loci (QTLs) [14]. No rice variety has been reported to be completely resistant to R. solani, despite the discovery of more than 60 SB resistance quantitative traits (QTLs). Additionally, no SB resistance QTLs have been cloned [8]. Thus, there is a need to investigate the molecular as well as the proteomic approaches in the wide host range to confer resistance sources against the ShB pathogen. Researchers also provide proteomicsbased tools, which serve as an effectual method for investigating the molecular responses of plants to various biotic stresses [15]. Lee et al. [16] recognized a precise 3-β HSD protein in resistant cultivated rice varieties. LSBR-5 connected with a response to infection by R. solani using 2-D and mass spectrometry (ESI Q-TOF MS). Similarly, a set of 319 differentially accumulated proteins (DAPs) after R. solani [13] was also studied for the investigation of resistance. A study of comparative metabolome and proteome profiles of the rice lines (wild-type and AtNPR1-transgenic) before and after R. solani infection [17] also revealed the host-pathogen interaction.
R. solani infects a broad range of cereal crops (rice, wheat, maize, barley, etc.) and no proper evidence has been found on how this necrotic fungal pathogen infects the host. The comparative defense response of different hosts has also been lacking until now, and effort should be put into exploring molecular targets for sheath blight-resistance which can be used for introgression to the rice and other cereals. Therefore, differential proteomic analysis of infected hosts in cereals (i.e., rice, wild rice, barley) may play an important role in finding resistance to ShB. Thus, the present study was carried out in order to determine the proteomic and biochemical signals that occur during the cultivated rice-R. solani, wild rice-R. solani, and barley-R. solani interactions for the purpose of searching for resistance possibilities in cereal crops.

R. solani Isolate, Plant Materials and Inoculation Procedure
Seeds of cultivated rice cv. Pusa Basmati-1, wild rice accession O. grandiglumis, and barley cv. NDB-1445 were collected from N.B.P.G.R., New Delhi, I.R.R.I., Philippines, and the Department of Genetics and Plant Breeding, A.N.D. University of Agriculture and Technology, Kumarganj, Ayodhya, U.P., India, respectively. They were sterilized with 5% bleach for 10 min and thoroughly rinsed with distilled water. Germinated seeds were placed in petri dishes at 28 • C for three days under dark conditions and further grown in pots (45 cm × 60 cm) filled with autoclaved pot mixture (30 mg N, 9.7 mg P, and 18.5 mg K per kilogram of soil in the form of urea, single superphosphate, and muriate of potash, respectively). All host plants were grown in a greenhouse at 25 ± 3 • C (14 h light/10 h dark cycle). The R. solani strain D-14, belonging to the AG1-IA anastomosis group, was collected from the Rice Pathology Laboratory, G. B. Pant University of Agriculture and Technology, Pantnagar, India. It was grown on potato dextrose agar at 28 ± 1 • C for 6 days and utilized for the inoculation. Approximately 0.2 mg of a 4-day-old immature sclerotium of R. solani grown on a PDA (potato dextrose agar) medium was used as inoculum. The sclerotium includes agar plugs embedded beneath the six-week-old host plants. The inoculated host plants' sheaths were covered with sterilized absorbent cotton to maintain humidity. The host plants without R. solani inoculation were maintained as healthy controls. The experimentation employed a completely randomized block design. Each treatment had three replications with three pots in each replication, and the experiments were repeated twice. After inoculation, all plants were transferred for 24 h. at 28 • C in complete darkness and up to 100% humidity, then transferred at 20 • C for 14 h in the light, and finally, for 10 h in the dark at 60% humidity. The relative lesion height (RLH = lesion height/plant height × 100) was recorded as described by Singh et al. [18]. The disease severity was calculated based on the RLH percentage. The data of RLH was converted into a disease index based on a disease score with a 0 to 9 rating scale. For the biochemical and proteomic analysis, leaf sheath tissue of~3 cm was harvested above the 2 cm lesion with R. solani in the inoculated hosts, as described by Lee et al. [16], in order to avoid contamination.

Estimation of Total Phenol Content, Peroxidase (PO) and β-1, 3-Glucanase
For biochemical assays, infected and mock leaf samples were collected from rice, wild rice, and barley at 24, 48, 72, and 96 hpi (hours post-infection). For phenol estimation in samples, 100 mg of freshly collected infected and control samples were ground in liquid N 2 . The homogenized sheath was collected in 10 mL of solvent (80% aqueous acetone) for 1 min, and transferred in test tubes and centrifuged for 15 min at 1000× g (REMI C-224 Centrifuge). After centrifugation, a clear supernatant was collected. The amount of total phenolics in the leaves in both the control and inoculated conditions were determined according to the Folin-Ciocalteu procedure [19]. Next, 2 mL samples in three replicates were transferred into test tubes; 1.0 mL of Folin-Ciocalteu's reagent and 0.8 mL of sodium carbonate (7.5%) were added in each replicate. The tubes were assorted thoroughly and permitted to stand for 30 min. Absorption at 765 nm was measured (Systronics UV-vis spectrophotometer, Ahmedabad, Gujarat, India). The total phenolic content was stated as gallic acid equivalents (GAE) in milligrams per gram of the sample dry material. The phenol content of the extract was expressed as µg, and the phenol equivalent released g −1 of leaf tissue. For peroxidase activity assay, 100 mg of both freshly infected and control samples were ground in liquid N 2 . The ground powder was used for the estimation of peroxidase activity by adopting the method described by Srivastava [20] and scoring the absorbance at 420 nm. The enzyme activity in the tissue sample was represented by the ktkatg −1 . Similarly, 100 mg of freshly ground tissue of infected and control samples were used to estimate β-1, 3-glucanase activity by the laminarin-dinitrosalicylic acid method [21]. The enzyme activity was expressed as µg, and glucose released min −1 mg −1 proteins. All of the biochemical analyses were repeated thrice in this experiment.

Protein Extraction for 2D Analysis
Leaf-sheaths from both inoculated and non-inoculated (control) plants of different hosts (rice, wild rice, and barley) were collected after 48 hpi. Fresh leaf samples (1 g of control and inoculated) were crushed into a fine powder using liquid nitrogen. The ground homogenate was extracted in 10% TCA in acetone containing 0.07% DTT and then kept at −20 • C for 1 h, followed by centrifugation for 15 min at 35,000× g. The pellets were centrifuged once for 15 min at 35,000× g, kept at 20 • C for an hour, and then given a second wash with ice-cold acetone containing 0.07% DTT. When the supernatant was clear, the washing procedure was repeated four or five times. The final precipitated pellets were lyophilized using the Freeze Dryer lyophilizer (Sew, New Delhi, India). Proteins from the leaves were extracted as described by Koller et al. [22]. The experiments were repeated thrice from the three replicate samples.

Isoelectric Focusing (IEF) and Polyacrylamide Gel Electrophoresis (PAGE)
A total of 10 mg of the dried powder (control and treated) was suspended in 350 µL of buffer, containing 7 M urea, 2 M thiourea, 4% CHAPS ((3-cholamidopropyl) (dimethy lammonio)-1-propanesulfonate) detergent, 0.5% ampholytes (pH 3-10), and 0.7% DTT. The supernatant was distributed in 100 µL aliquots and kept at −80 • C for further use. In order to determine optimum 2-DE gel conditions, a broad range (pH 3-10) IPG strip for the first dimension and a 12% linear polyacrylamide gel for the second dimension were carried out. The preponderance of the protein spots was perceived in the center of the gel, thus, the 2-DE gel with a pH 4-7 range and a 12% linear polyacrylamide gel were used. A total of 500 µg of protein, assayed by the Bradford method [23], was loaded onto a 17 cm (pH range 4-7) linear IPG (immobilized pH gradient) strip (BIO-RAD, Hercules, CA, USA) into the rehydration/equilibration tray with slight modification (Kumar et al. [24]). The rehydration tray containing the IPG strips was covered by 2 to 3 mL of mineral oil to avoid evaporation during the rehydration process. The first-dimensional electrophoresis (isoelectric focusing) was carried out with a PROTEAN IEF Cell (BIO-RAD, Hercules, CA, USA) at 250 volts for 20 min in linear mode, followed by 8000 volts for 2.5 h in linear mode, followed by 8000 volts at~30,000 volt-hour mode in rapid mode. The IPG strips were subjected to second-dimensional electrophoresis after 10 min in equilibration buffer 1 (6 M urea, 0.375 M tris, pH 8.8, 2% sodium dodecyl sulphate (SDS), 20% glycerol, and 2% (w/v) DTT), followed by 10 min in equilibration buffer 2 (6 M urea, 0.375 M tris, pH 8.8, 2% SDS, 20% glycerol and 2.5% iodoacetamide). The equilibrated IPG strips were washed in sterile, distilled water, and then placed on top of a 12% non-gradient and 18 cm × 20 cm polyacrylamide-bisacrylamide gel. No stacking gel was used [24]. Bromophenol bluecontaining 1% agarose was used to seal the IPG strip. The following operating conditions were used for the second electrophoresis: 30 min of constant 16 mA at 6 • C, followed by constant 30 mA in a vertical electrophoretic dual gel unit PROTEAN II XI (BIO-RAD, Hercules, CA, USA). Coomassie Brilliant Blue R250 was used to stain the gels of all the tested samples.

Image Acquisition, Spot Digestion and Identification
Images of the stained gels were obtained by Chemidoc (BIO-RAD, Segrate (Milan), Italy) using Quantity One software version 4.6.3 (BIO-RAD, Hercules, CA, USA). Spot detection and matching analyses were conducted first with the PDQuest Advanced software Gel images were analyzed using stepwise spot detection and spot matching followed by differential expression analysis. Protein spots among the gels showed increased/decreased intensities with more than 1.5-fold selected for identification. PDQuest employs a Student t-test and enumerates spots with a differential intensity of significant levels. Differentially expressed protein spots of interest were excised from gels using the spot picker 'Investigator ProPic' (Genomic Solutions, Huntingdon, UK) and collected in 96-well PCR plates. The digestion of protein and spotting of peptides on the MALDI-TOF target plate was carried out using the protein digester 'Investigator ProPrep' (Genomic Solutions, Huntingdon, UK) as described by Shevchenko et al. [25] with slight modifications. The gel plugs were de-stained and dehydrated by washing three times (~10 min) with 25 mM NH 4 HCO 3 -50% acetonitrile (ACN) (1:1). Dried gel plugs were treated with freshly prepared 10 mM DTT in 50 mM NH 4 HCO 3 for 45 min at 56 • C. After incubation, the DTT was replaced quickly by 55 mM iodoacetamide (freshly prepared) at the same volume in 50 mM NH 4 HCO 3 for 30 min and, finally, dehydrated with 100% ACN. The dried gel pieces were incubated for 12 h at 37 • C with 25 mM NH 4 HCO 3 containing 0.02 µg/µL of mass spectrometry grade trypsin (Promega, Madison, WI, USA). The resulting peptides were extracted twice from the gel pieces, using a peptide extraction buffer.
The digested protein samples were analyzed by mass spectrometry in the same manner that was described earlier [25]. According to the instructions provided by the manufacturer, digested protein samples were desalted and concentrated using C-18 ZipTips (Millipore, Billerica, MA, USA). The ZipTips were eluted from the MTP 384 target plate using 2 L of a saturated solution of a-cyano-4-hydroxycinnamic acid (HCCA) (Sigma-Aldrich, St. Louis, MO, USA) dissolved in 50% aqueous cyanohydrin and 0.2% trifluoroacetic acid. The Autoflex II TOF/TOF 50 mass spectrometer from Bruker Daltonik GmbH in Leipzig, Germany was used to acquire mass spectra of digested proteins. The instrument was set to the positive reflectron mode, and the detection range was 500-3000 m/z. Before the acquisition, an external calibration to a spectrum was carried out, with the spectrum being acquired for a mixture of peptides whose masses ranged from 1046 to 2465 Da. After that, the proteolytic masses which were obtained were put through the Flex Analysis v.2.4 program so that peak detection could take place. In order to identify the proteins contained in the rice database (O. sativa and other green plant data, EMBL/GenBank/DDBJ), peak list submissions were made to the UniProtKB and Swiss-Prot databases through the use of the Mascot search engine found at http://www.matrixscience.com (accessed on 9 and 27 November 2019).

Co-Expression Network and Gene Ontology Analysis
For the purpose of mapping, the co-expression network of differentially expressed proteins in cultivated rice cv. Pusa Basmati-1, wild rice accession O. grandiglumis, and barley cv. NDB-1445 under R. solani inoculation were considered individually as input in the STRING 11.0 version (https://string-db.org/ accessed on 27 November 2019) and repeated twice [26]. For this, protein ids/protein sequences were used to obtain the co-expressing primary interactors, considering the maximum number of primary interactors was set to 500 and the interaction score cut off value was set at ≥0.700. Then, a complete list of primary interactors and differentially expressed proteins was used as input to construct the co-expression network and gain insight into a functional classification for R. solani-induced proteins in cultivated rice cv. Pusa Basmati-1, wild rice accession O. grandiglumis, and barley cv. NDB-1445. For enrichment analysis, gene ontology was performed using STRING 11.0 to obtain insight into the enriched category (FDR corrected p-value ≤ 0.05).

Data Analysis
The SAS (Statistical Analysis Systems) software (version 7.0, SAS Institute, Cary, NC, USA) [27] was utilized for the data analysis in the experiment, which was laid out in a complete randomized design (CRD) with 3 replications. In the disease scoring experiment, cultivated rice cv. Pusa Basmati-1 was used as a susceptible check and wild rice accession O. grandiglumis was used as a resistance check. The protein spots in the gels were captured by PDQuest software, which employs a Student t-test analysis.

Results
The Oryza spp. (cultivated rice cv. Pusa Basmati-1 and wild rice accession O. grandiglumis) and barley cv. NDB-1445 ranged from very susceptible to mildly resistant to sheath blight. The cultivated rice cv. Pusa Basmati-1 showed the highest visual rating in terms of infection under field and the detached leaf method, but O. grandiglumis was found to have the lowest infection across all tested hosts. In field conditions, the average lesion number was also largest in Pusa Basmati-1, but it was lower in O. grandiglumis than in the barley cv. NDB-1445 and the other tested hosts (Figure 1a-c).

Biochemical Assay
Biochemical assays of total phenol, peroxidase, and β-1,3-glucanase were performed in order to assess the R. solani infection in cultivated rice cv. Pusa Basmati-1, wild rice accession O. grandiglumis, and barley cv. NDB-1445 on different time intervals, such as at 24 hpi, 48 hpi, 72 hpi, 96 hpi, 120 hpi, separately and in control condition. The hosts' plants show variation in phenol, peroxidase, and β-1,3-glucanase accumulation at different time intervals on R. solani inoculation (Figure 2a-c). The accumulation of total phenol content

Biochemical Assay
Biochemical assays of total phenol, peroxidase, and β-1,3-glucanase were performed in order to assess the R. solani infection in cultivated rice cv. Pusa Basmati-1, wild rice accession O. grandiglumis, and barley cv. NDB-1445 on different time intervals, such as at 24 hpi, 48 hpi, 72 hpi, 96 hpi, 120 hpi, separately and in control condition. The hosts' plants show variation in phenol, peroxidase, and β-1,3-glucanase accumulation at different time intervals on R. solani inoculation (Figure 2a-c). The accumulation of total phenol content increased after inoculation with R. solani in Pusa Basmati-1, O. grandiglumis, and NDB-1445 as compared to the control condition (Figure 2a , 72 hpi [3], 96 hpi [4], and 120 hpi [5]). (a) Fold change in enzymatic activity of total phenol content. (b) Fold change in enzymatic activity of total peroxidase content. (c) Fold change in enzymatic activity of total β-1,3glucanase content. Mean differences were significant at ≤0.05% level.

R. solani Induced Proteome Shift in Cultivated Rice, Wild Rice, and Barley
In the 2-DE maps, more than 1840 protein spots and an average of 613 protein spots were viewed with Coomassie brilliant blue staining across all the hosts. A total of 672 spots were identified, of which 605 were matched among the gels. In a comparison analysis between inoculated and non-inoculated rice cv. Pusa Basmati-1, 67 spots were differentially expressed on R. solani inoculated gel. After 48 hpi of inoculation, 15 distinct pro- , 96 hpi [4], and 120 hpi [5]). (a) Fold change in enzymatic activity of total phenol content. (b) Fold change in enzymatic activity of total peroxidase content. (c) Fold change in enzymatic activity of total β-1,3-glucanase content. Mean differences were significant at ≤0.05% level.

R. solani Induced Proteome Shift in Cultivated Rice, Wild Rice, and Barley
In the 2-DE maps, more than 1840 protein spots and an average of 613 protein spots were viewed with Coomassie brilliant blue staining across all the hosts. A total of 672 spots were identified, of which 605 were matched among the gels. In a comparison analysis between inoculated and non-inoculated rice cv. Pusa Basmati-1, 67 spots were differentially expressed on R. solani inoculated gel. After 48 hpi of inoculation, 15 distinct protein spots were found with significant differential accumulation in response to pathogen infection. Spots were considered to be differentially accumulated when a fold change of 2 in their relative volume was observed on all three experimental repeats (Figure 3a,b; Table 1). A total of eight up-regulated and four down-regulated protein spots were selected based on high percent reduction and induction of the protein for the MALDI-TOF analysis (Figure 3c,d).
The up-regulated proteins were identified as ribulose bisphosphate carboxylase large chain, thioredoxin peroxidase, alcohol dehydrogenase, fructose-1, 6-bisphosphatase, Omethylthiopentene, OsClp1-putative protease homologue, thioredoxin, and hypothetical protein OsJNBa0069E14). The four down-regulated proteins were identified as magnesiumchelatase subunit chlI, alcohol dehydrogenase, catalase domain-containing protein, and ribulose bisphosphate carboxylase large chain precursor ( In the comparative analysis of wild rice O. grandiglumis, 559 spots were detected, out of which 515 spots were matched to all the gels and 44 protein spots were perceived to have a different relative expression. Among 44 protein spots, 32 spots were up-regulated and 12 protein spots were down-regulated. The comparative protein profiles of wild rice accession O. grandiglumis showed that 14 protein spots were differentially accumulated between the control and R. solani treated samples (Figure 4a,b). Finally, nine up-regulated and three down-regulated protein spots were selected for the MALDI-TOF analysis. In the up-regulated spots, putative cysteine proteinase inhibitor, proteinase inhibitor type-2, kinesin motor domain-containing protein, chlorophyll a-b binding protein, kinesin motor domain-containing protein, ZOS5-12 C2H2 zinc finger protein, acyl carrier protein desaturase, and down-regulated speckle-type POZ protein were identified (Figure 4c,d; Table 2). Induced genes and their respective ORFs are mentioned in Supplementary Table S2.
In barley cv. NDB-1445, comparative analysis revealed 609 protein spots, of which 570 spots were matched to all of the treatment gels, and 39 spots which significantly varied in their expressions. Among the 39 spots detected, 30 spots were up-regulated and 9 spots were down-regulated (Figure 5a,b). Further protein spots showing more than twofold increased intensities were further processed for identification purposes. The up-regulated spots were identified as a heat shock factor, peptidase ClA papain, PhotosystemII PbsO, and ribonucleoside-diphosphate reductase small chain. Down-regulated spots were identified as chlorophyll a-b binding protein 3C and a hypothetical protein (Figure 5c,d, Table  3). Induced genes and their respective ORFs are mentioned in Supplementary Table S3. solani. The spots which were more intense in the control are shown with a downward arrow (↓), and the spots which were more intense in the stressed cells are shown with an upward arrow (↑). After image analysis, 67 spots were found to be differentially expressed quantitatively between the two situations. In panels (c,d) are some of the representative differentially expressed enlarged regions solani. The spots which were more intense in the control are shown with a downward arrow (↓), and the spots which were more intense in the stressed cells are shown with an upward arrow (↑). After image analysis, 67 spots were found to be differentially expressed quantitatively between the two situations. In panels (c,d) are some of the representative differentially expressed enlarged regions of the protein profile from panels (a,b). Here, URP and DRP represent the up-regulated and down-regulated protein spots, respectively. In the comparative analysis of wild rice O. grandiglumis, 559 spots were detected, out of which 515 spots were matched to all the gels and 44 protein spots were perceived to have a different relative expression. Among 44 protein spots, 32 spots were up-regulated and 12 protein spots were down-regulated. The comparative protein profiles of wild rice accession O. grandiglumis showed that 14 protein spots were differentially accumulated between the control and R. solani treated samples (Figure 4a,b). Finally, nine up-regulated and three down-regulated protein spots were selected for the MALDI-TOF analysis. In the upregulated spots, putative cysteine proteinase inhibitor, proteinase inhibitor type-2, kinesin motor domain-containing protein, chlorophyll a-b binding protein, kinesin motor domaincontaining protein, ZOS5-12 C 2 H 2 zinc finger protein, acyl carrier protein desaturase, and down-regulated speckle-type POZ protein were identified (Figure 4c,d; Table 2). Induced genes and their respective ORFs are mentioned in Supplementary Table S2.
In barley cv. NDB-1445, comparative analysis revealed 609 protein spots, of which 570 spots were matched to all of the treatment gels, and 39 spots which significantly varied in their expressions. Among the 39 spots detected, 30 spots were up-regulated and 9 spots were down-regulated (Figure 5a,b). Further protein spots showing more than twofold increased intensities were further processed for identification purposes. The up-regulated spots were identified as a heat shock factor, peptidase ClA papain, PhotosystemII PbsO, and ribonucleoside-diphosphate reductase small chain. Down-regulated spots were identified as chlorophyll a-b binding protein 3C and a hypothetical protein (Figure 5c,d, Table 3). Induced genes and their respective ORFs are mentioned in Supplementary Table S3.   The spots which were more intense in the control are shown with a downward arrow (↓), and the spots which were more intense in the stressed cells are shown with an upward arrow (↑). After image analysis, 44 protein spots were found to be differentially expressed quantitatively between the two situations. In panels (c,d): some of the representative differentially expressed enlarged regions of the protein profile from panels (a,b). Here, URP and DRP represent the up-regulated and down-regulated protein spots, respectively.  R. solani. The spots which were more intense in the control are shown with a downward arrow (↓), and the spots which were more intense in the stressed cells are shown with an upward arrow (↑). After image analysis, 44 protein spots were found to be differentially expressed quantitatively between the two situations. In panels (c,d): some of the representative differentially expressed enlarged regions of the protein profile from panels (a,b). Here, URP and DRP represent the up-regulated and down-regulated protein spots, respectively.

Chromosome Location of Differentially Expressed Protein on the Chromosomes
Genes encoding fifteen of the differentially expressed proteins from Pusa Basmati-1, nine proteins from wild rice accession O. grandiglumis (Supplementary Figure S1), and six from barley cv. NDB-1445 (Supplementary Figure S2) were located on their respective chromosomes. Four proteins of cultivated rice and one from wild rice were found to be located on rice chromosome 3, followed by two proteins from cultivated and one from wild rice which were located on chromosome 10, two proteins located on chromosome 7 and chromosome 12, and one each on chromosomes 2, 4, 5, 6, 8, and 11. Additionally, genes encoding the highest no. of differentially expressed proteins were assigned to chromosome 3. In barley cv. NDB-1445, the maximum no. of differentially expressed proteins was found on chromosome 7, followed by chromosome 2, whereas one differentially expressed protein was seen on chromosome 5 (Supplementary Figure S2).

Co-Expression Networks and Gene Ontology
In order to understand the biological significance of differentially expressed proteins upon R. solani infection, identified proteins were screened for their co-expression network and gene ontology using the STRING 11.0 version. The co-expression network was mapped using differentially expressed proteins along with their primary interactors. Primary interactors were extracted, and the co-expression interaction network was individually mapped for differentially expressed proteins of Pusa Basmati-1 (Figure 6a), O. grandiglumis (Figure 7a), and barley cv. NDB-1445 (Figure 8a). The gene ontology enrichment analysis of Pusa Basmati-1 identified that the differential proteins are majorly localized in the cytoplasm (GO:0005737), intracellular membrane-bounded organelle (GO:0043231), and chloroplast (GO:0009507). The significantly enriched biological process was related to the oxidation-reduction process (GO:0055114) and photosynthesis (GO:0015979). The result of significantly overrepresented terms for molecular functions lies majorly in catalytic activity (GO: 0003824) and oxidoreductase activity terms (GO:0016491) (Figure 6b, Supplementary  Table S4). A similar analysis of differentially expressed proteins in O. grandiglumis showed a highly connected co-expression network, suggesting their association with biological function (Figure 7b). Gene ontology enrichment identified that differentially expressed proteins and primary interactors were majorly localized in the intracellular part (GO:0044424) and in the cytoplasm (GO:0005737). Similarly, an enriched biological process lies in the nitrogen compound metabolic process (GO:0006807), gene expression (GO:0010467), and translation (GO:0006412) terms. The molecular function category showed enriched terms such as organic cyclic compound binding (GO:0097159), nucleic acid binding (GO:0003676), and chlorophyll binding (GO:0016168) (Figure 7b, Supplementary Table S5). Using a similar strategy, differentially expressed proteins from barley were also screened for primary interactors, co-expression network analysis, and GO enrichment analysis (Figure 8a). The significantly enriched cellular components belong to the chloroplast (GO:0009507) and the photosynthetic membrane (GO:0034357), whereas the significantly enriched biological process involves photosynthesis (GO:0015979) as well as the generation of precursor metabolites and energy (GO:0006091). The enriched molecular function GO terms for the co-expression network for barley involve metal ion binding (GO:0046872) and cofactor binding (GO:0048037) (Figure 8b, Supplementary Table S6). Intriguingly, R. solani induced differentially expressed proteins, co-expressed with cellular proteins that majorly determine photosynthesis and primary metabolic processes, showing enrichment of common GO terms. A pathway analysis of biological processes and protein class was conducted, in which differently abundant proteins after R. solani inoculation with the hosts were involved, as depicted in Figure 9a,b. As a whole, seven functional groups based on molecular process are most clearly affected by the R. solani infection, including protein binding (03), enzyme regulator activity (03), transferase activity (03), lyasese activity (04), hydrolase activity (07), and protein binding (18). With regard to the cellular components' function, the key groups containing intracellular (32), cell periphery (13), plasma membrane (10), protein complex (8), endomembrane system (7), intracellular organelle part (5), external encapsulating structure (4), non-membrane bounded organelle (4), and organelle lumen (3) were found (Figure 9b). The present investigation suggests that R. solani inoculation in cereal crops induced conserved signals which affect vital processes of the inoculated hosts' growth and survival. periphery (13), plasma membrane (10), protein complex (8), endomembrane system (7), intracellular organelle part (5), external encapsulating structure (4), non-membrane bounded organelle (4), and organelle lumen (3) were found (Figure 9b). The present investigation suggests that R. solani inoculation in cereal crops induced conserved signals which affect vital processes of the inoculated hosts' growth and survival.   Figure 6. (a,b). Protein interaction network analysis of differentially expressed proteins (including primary interactors) in cultivated rice cv. Pusa Basmati-1 using STRING v.11.0. (a) Network was constructed at an interaction score cut off value of ≥0.700 with maximum number of primary interactors set to 500, including experimental evidence (pink lines), gene fusion (red lines), and coexpression (black lines). (b) Graph showing GO enrichment analysis of interaction network representing the no. of genes classified in respective GO categories (FDR corrected p value ≤ 0.01).

Figure 7.
Protein interaction network analysis of differentially expressed proteins (including primary interactors) in wild rice accession O. grandiglumis using STRING v.11.0. (a) Network was constructed at an interaction score cut off value of ≥0.700 with maximum number of primary interactors set to 500, including experimental evidence (pink lines), gene fusion (red lines), and co-expression

Discussion
Application of fungicide in rice cultivation is a common practice, and if it is not applied precisely, it could adversely impact the environment as well as human beings and other living organisms [28]. Studies on the rice sheath blight resistance mechanism are limited due to the lack of resistant donors in cultivated cultivars [29]. So far, interaction between the fungus and the plant has been studied [30], but there have been only a few reports on R. solani interactions with a wide range of hosts. Thus, for the identification of the differentially expressed biochemical signals and proteins among the three hosts of R. Solani, a comparative proteomics study has been performed. Similarly, studies on ShB resistance genes in rice and their processes have primarily utilized cultivated rice as a host for a long time [31]. However, due to the polygenic nature of ShB resistance, no significant ShB resistance genes or rice cultivars demonstrating complete resistance to R. solani have been reported [32]. Thus, in the present study, three hosts (namely, cultivated rice cv. Pusa Basmati-1, wild rice accession O. grandiglumis, and barley cv. NDB-1445) have been selected for the resistance response against the R. solani pathogen.

Discussion
Application of fungicide in rice cultivation is a common practice, and if it is not applied precisely, it could adversely impact the environment as well as human beings and other living organisms [28]. Studies on the rice sheath blight resistance mechanism are limited due to the lack of resistant donors in cultivated cultivars [29]. So far, interaction between the fungus and the plant has been studied [30], but there have been only a few reports on R. solani interactions with a wide range of hosts. Thus, for the identification of the differentially expressed biochemical signals and proteins among the three hosts of R. Solani, a comparative proteomics study has been performed. Similarly, studies on ShB resistance genes in rice and their processes have primarily utilized cultivated rice as a host for a long time [31]. However, due to the polygenic nature of ShB resistance, no significant ShB resistance genes or rice cultivars demonstrating complete resistance to R. solani have been reported [32]. Thus, in the present study, three hosts (namely, cultivated rice cv. Pusa Basmati-1, wild rice accession O. grandiglumis, and barley cv. NDB-1445) have been selected for the resistance response against the R. solani pathogen.
Recently, significant developments in proteomics have made substantial progress in understanding the physiological process governing rice resistance, associated signaling networks, and their function in triggering defense responses [16]. For the assessment of the biochemical response, we performed a comprehensive biochemical (total phenol content, peroxidase activities, and β-1, 3-glucanase), and proteomic analysis of the different hosts (cultivated rice cv. Pusa Basmati 1, wild rice accession O. grandiglumis, and barley cv. NDB-1445) after R. solani infection in order to comprehend how host-pathogen interactions work in rice sheath blight resistance. The host plants show variation in phenol, peroxidase, and β-1,3-glucanase accumulation at different time intervals after R. solani inoculation [33]. From the biochemical analysis, it is clear that accumulation of phenol, peroxidase, and β-1,3-glucanase was generally higher in infected samples as compared to the control. With regard to pathogen attacks, plants generally produce and accumulate defense-related compounds such as phenols, peroxidases, β-1,3-glucanases, chitinases, etc. Phenol and peroxidase activities in wild rice accession and barley cv. NDB-1445 showed significant induction after R. solani inoculation. Both enzymes showed maximum activity at 72 hpi in wild rice accession, compared with susceptible cultivated rice cv. Pusa Basmati-1. Plant phenolic compounds work as a structural barrier against pathogen attacks [34]. Plant peroxidases play an essential role in catalyzing the oxidation of different reductants in cells. These enzymes are active regulators of auxin metabolism, lignin and suberin synthesis, cell wall component cross-linking, phytoalexin synthesis, ROS (reactive oxygen species) metabolism, and RNS reactive nitrogen species), and are involved in disease resistance in plants [35]. The activities of these enzymes were found to be altered after fungal infection [35]. According to the earlier reports, the activity of peroxidase was significantly enhanced in rice leaves after artificial inoculation with M. oryzae and R. solani [36]. A similar report of high concentrations of defense enzymes such as 1,3-glucanase, phenylalanine ammonia lyase (PAL), peroxidase (POX), polyphenol oxidase (PPO), lipoxygenase (LOX), and defense protein hydroxyproline-rich glycoproteins (HRGPs) positively correlated with increased downy mildew resistance in pearl millet (Pennisetum glaucum (L.) after Sclerospora graminicola (Sacc.) inoculation [37]. These results are consistent with our current inquiry.
Similarly, the induction of β-1, 3-glucanase is highest at 72 hpi in the wild rice accession O. grandiglumis, and increased consistently up to 120 hpi in comparison to other hosts. The β-1,3-glucanase enzyme plays a crucial part in the breakdown of fungal cell walls by hydrolyzing chitin, where it has been demonstrated that cell wall fragments cause plants to mount a defense response [37]. Similarly, a study showed that β-1,3-glucanase enzyme activity significantly increased following a pathogen challenge in Taipei (TP) 309 containing the pi54 gene at 120 hpi, but were significantly lower in other rice genotypes [38].
In cultivated rice cv. Pusa Basmati-1, upon R solani infection, upregulation of eight proteins was identified: ribulose bisphosphate carboxylase large chain, thioredoxin peroxidase, alcohol dehydrogenase, fructose-1,6-bisphosphatase, O-methylthiopentene, OsClp1putative protease homologue, thioredoxin, and the hypothetical protein OsJNBa0069E14. In previous studies, it has been reported that Rubisco (ribulose bisphosphate carboxylase) is inactivated by ROS after biotic stress and is mostly downregulated [17,39]. However, Wu et al. [40] reported that the sugarcane mosaic virus (SCMV) infection affects photosynthesisrelated proteins, which were down-regulated in maize (Zea mays) seedlings, with the exception of the Rubisco large subunit as well as the ferredoxin-NADP reductase and its isoforms. Induction of the ribulose bisphosphate carboxylase large chain precursor was also observed, and similar observations have been reported with abiotic and biotic stresses in rice. Similarly, the upregulation of Thioredoxin peroxidase might be due to its ability to mitigate oxidative stress along with thioredoxin reductase [13,41].
The photosynthetic protein ribulose bisphosphate carboxylase large chain was upregulated, and the role of Rubisco is well studied in photorespiratory carbon oxidation and photosynthetic CO 2 assimilation. It has also been reported that after biotic stress, Rubisco is destroyed during senescence and oxidative stressors, and inactivated by ROS. Induction of another protein, namely, thioredoxin peroxidase, again showed the defense mechanism in rice after R. solani infection [13]. Thioredoxin reductase and thioredoxin peroxidase work together to mitigate oxidative stress [13,41]. Generally, fungal infections create hypoxia/anoxia conditions in their host plant according to which plants adapt mechanisms to compensate for the energy crisis. Alcohol dehydrogenase (ADH) is an important component in the maintenance of a primary energy metabolism in higher plants, and seems to be engaged in aerobic metabolism under specific stress situations [42] such as low temperature, water stress, or ozone exposure. In several studies, alcohol dehydrogenase (ADH) and pyruvate carboxylase are central enzymes in fermentative metabolism, and were reported after biotic stress [43]. Inoculation of R. solani to the rice cv. Pusa Basmati-1 induces the accumulation of O-methyltransferases (OMT). Plant O-methyltransferases (OMT) play an important role in lignin biosynthesis and stress tolerance in plants [44]. A greater accumulation of OMT was also observed in barley after infection with the fungus Blumeria graminis [45].
After R. solani inoculation, rice cv. Pusa Basmati-1 also showed down-regulation in proteins, namely, magnesium-chelatase subunit chlI, alcohol dehydrogenase, catalase domain-containing protein, and ribulose bisphosphate carboxylase large chain precursor. An increased relative abundance of anaerobic metabolisms under salt stress was reported by the increased relative abundance of FBP aldolase, other glycolytic enzymes, and enzymes involved in ethanolic fermentation and glycolate metabolism in rice seedlings. After inoculation with R. solani OsClp10, a putative Clp protease homolog protein showed downregulation. The important function of the chloroplast Clp protease has been proven in earlier research employing several transgenic plants. Plants with lower levels of the plastomic ClpP1 or other Clp proteolytic core elements have a reduced ability to differentiate their chloroplasts, generate shoots, and maintain overall plant viability. The Rubisco small chain protein ribulose bisphosphate carboxylase also showed down-regulation after inoculation with R. solani. It is well known that infected plant cells have lower levels of the Rubisco protein, a vital photosynthesis enzyme, as a result of pathogens attacking chloroplasts and causing their destruction [46].
Wild rice accession O. grandiglumis showed induction of a cysteine-type endopeptidase inhibitor. The induced proteinase inhibitors (PIs) are categorized under the PR6 family, which plays an important role in plant defense. Additionally, it has been found that plant PIs influence plant immunity by inhibiting pathogen proteases or controlling endogenous plant proteases [47]. The majority of cysteines found in plants are found in tiny proteins that act as inhibitors of the C1A papain-like family of cysteine proteases (CysProt). It has been assumed that PhyCys has a defense function against viruses and pests based on its up-regulation in response to biotic, stress-related signals. It has been demonstrated that the A. thaliana serine protease inhibitor (UPI) aids in defense against the necrotrophic fungi Alternaria brassicicola and Botrytis cinerea [48]. Recently, Zhang et al. [49] also reported a novel host defense mechanism in rice, where an NLR receptor protects a host protease inhibitor that is targeted by rice fungus Magnaporthe oryzae and promotes resistance against it.
The chlorophyll a/b-binding protein (CAB), related to metabolism and energy, showed up-regulation after R. solani inoculation at 48 hpi by the cultivated rice cv. Pusa Basmati-1 and wild rice accession O. grandiglumis. The CAB protein has a role in regulating the expression of sugar-related genes in plants. Following pathogen infection, several genes for chlorophyll a/b binding proteins were down-regulated, slowing photosynthesis and limiting the availability of food resources such as sugar [50]. The transcription of photosynthetic genes, including ribulose 1,5-diphosphate carboxylase and genes that bind chlorophyll a/b, was also found to be inhibited in an interaction between rice and R. solani, in both the susceptible and resistant interactions. However, wild rice accession O. grandiglumis induced the chlorophyll a/b-binding protein, probably due to the availability of food under stress.
The kinesin motor domain-containing protein was up-regulated after R. solani inoculation. It has been reported that plant stress tolerance depends on many factors, including signals generated by mitogen-activated protein-kinase modules, which play a crucial role under stress. After inoculation with R. solani, wild rice accession O. grandiglumis showed a high level of expression of C 2 H 2 zinc finger (C 2 H 2 -ZF) proteins. Zinc finger transcription factors (TFs) had already been discovered in other plants, and it has been reported that these TFs contribute to vital biological functions during vegetative growth, reproductive development, and stress responses [13]. Several studies identified that a CCCH-type zinc finger protein regulates the interaction of pathogens in cotton as well as in rice [51]. The zinc finger protein (ZFP) (N2), which is associated with defense-related transcriptional factors, was induced in a MoHrip2 elicitor and treated plants as compared to controls. Similarly, acyl carrier protein desaturases and speckle-type POZ showed down-regulation after R. solani inoculation in O. grandiglumis. The vital roles that stearoyl-acyl carrier protein desaturases play in UFA production in response to biotic and abiotic stressors are well documented [52].
The barley cv. NDB-1445 showed up-regulation of the heat shock transcription factor after R. solani inoculation. There is evidence to support the importance of heat shock factors (Hsfs) in stress sensing and signaling of various environmental stresses. Induced reactive oxygen species (ROS) in plants, particularly H 2 O 2 , are important components in biotic and abiotic stress responses and signaling mechanisms [53]. The heat shock protein-encoding gene OsHsf23 was induced after interaction with R. solani via activation of OsHsf23. Similarly, Bechtold et al. [54] also confirmed HSFA1b's additional function in sustaining baseline disease resistance, which was not dependent on stress hormones, but did include H 2 O 2 signaling.
A protease (namely, peptidase CIA (MLOC_751664) papain) was also induced after R. solani inoculation by barley cv. NDB-1445. Proteases also appear to play key roles in plant pathogenesis [47,55]. With the genetic identification of RCR3, a secreted papain-like protease (C1) of tomato, the function of papain-like proteases has caused interest. The function of the resistance gene Cf-2, which mediates recognition of the Avr2 avirulence gene of the fungus Cladosporium fulvum, depends on RCR3 [55]. The role of cysteine proteinases from different plants has also been associated with disease resistance [47].
The R. solani interaction with barley cv. NDB-1445 induced protein photosystem II PsbO. Through the creation of ROS, which not only harms the elements of the photosynthetic electron transfer chain but also serves as an essential retrograde signaling molecule, photosystem II (PSII) plays a significant role in plant immunology. An interaction between tobacco leaf PSII repair and the control of cell death was also reported after infections by tobacco mosaic virus had been established in tobacco plants [56].
Proteins (namely, ribonucleotide reductase small subunit and the CAB protein) showed reduced expression after R. solani inoculation. In yeast, humans, and, probably, higher plants, ribonucleotide reductase (RNR) is known to be a significant target of DNA damage checkpoint mechanisms [57]. There is also a report that upon Septoria tritici (filamentous fungus) infection, a large number of proteins, including chloroplast CAB proteins, ribulose bisphosphate carboxylase, fructose-bisphosphate aldolase, etc., show a decrease in abundance and/or changed in phosphorylation status in wheat cultivars from 3 to 11 dpi. This finding suggests suppression of photosynthesis, changes in sugar metabolism, and an increase in sugar content [58]. It has been reported that high sugar levels decrease photosynthetic gene expression and increase mobilization and sugar transport [58], and that fungal diseases can target sugar transporters and activate the expression of the relevant genes for nutritional gain [59]. According to the findings of this research, the reaction of cultivated rice and other hosts (wild rice and barley) to R. solani can be explained in terms of the physiological state of the infected cultivated rice and the energy needed to induce a defense, which is supplied by proteins involved in energy metabolism (GAPDH, Rubisco). On the other hand, wild rice and barley were inducted into the defense modes of other, different proteins. A number of photosynthesis-related proteins underwent changes, indicating the dynamic impact of SA on photosynthesis. A decrease in the photosynthetic rate has occurred after treatment, as evidenced by the down-regulation of proteins such as Rubisco large subunit, phosphoenolpyruvate carboxylase, ADP-glucose pyrophosphorylase large subunit, and Rubisco small subunit in control condition only.
Results analyzed from the present study conclude that stress-related proteins, including defense, carbon metabolism, and energy synthesis, have been significantly affected in the selected cereal crops after R. solani infection, i.e., in cultivated rice cv. Pusa Basmati-1, and together dictate transition to a 'defense mode.' Some common stress response systems appeared to be activated in both resistant and susceptible lines, but the resistant wild rice accession O. grandiglumis produced significantly more defense-related proteins than barley cv. NDB-1445. From the different protein expression patterns detected in this study, it is hypothesized that the resistance of wild rice accession O. grandiglumis resulted from its ability to produce more defense proteins than the more susceptible rice and barley cv. NDB-1445. This ability was, possibly, a loss in the cultivated rice variety.

Conclusions
The present study reveals a complex response of R. solani interaction in three cereal hosts showing simultaneous induction of key proteins, their biochemical profile, and chromosomal and physiological mapping. Here, we propose that defense pathways involved in R. solani interaction are due to some key regulated pathways at the translational levels, such as pathogenesis-related protein, resistance gene/protein domains, signal transduction, proteins involved in energy metabolism, and protein synthesis, which were induced in different hosts. In field conditions, wild relatives of rice accession O. grandiglumis showed high resistance as compared to barley cv. NDB-1445 (moderately resistant) and cultivated rice cv. Pusa Basmati-1 (susceptible). The identified sources could be dissected and engineered in order to develop novel sheath blight resistance rice cultivars through breeding programs.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/bioengineering9100589/s1, Figure S1: Chromosomal location of genes encoding differentially expressed proteins of cultivated rice cv. Pusa Basmati-1 (black colour) and wild rice accession O. grandiglumis (red colour). The proteins were mapped to the rice genome according to the locus of the markers, Figure S2: Chromosomal location of genes encoding differentially expressed proteins of barley cv. NDB-1445. The proteins were mapped to the barley genome according to the locus of the markers; Table S1: Genes and their various ORFs of Pusa Basmati-1,

Data Availability Statement:
The original data were available from the corresponding author upon an appropriate request.