Physiological Responses of Phaseolus vulgaris to Damping-Off Disease Control Using Mutant Trichoderma spp.

doi:10.21203/rs.3.rs-7169291/v1

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Physiological Responses of Phaseolus vulgaris to Damping-Off Disease Control Using Mutant Trichoderma spp.

https://doi.org/10.21203/rs.3.rs-7169291/v1

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The effectiveness of biological control agents is increasingly recognized in sustainable agriculture, particularly in combating soil-borne pathogens such as Rhizoctonia solani, which causes damping-off disease in beans. This study investigates the potential of mutant Trichoderma species to enhance plant resistance and improve physiological responses in Phaseolus vulgaris. Five species of Trichoderma (T. harzianum NAS110, T. aureoviride NAS106, T. atroviride NAS112, T. afroharzianum NAS107, and T. lixii NAS114) were subjected to gamma irradiation to induce mutations, and their effects on the growth of R. solani were assessed. The experimental design included a completely randomized setup with statistical analyses to determine the significance of differences in disease incidence. Key physiological parameters, including peroxidase enzyme (POD) and polyphenol oxidase (PPO) activities, chlorophyll a and b levels, carotenoid concentrations, proline content, and lipid peroxidation were meticulously measured. The analysis revealed that treatment with mutant Trichoderma significantly increased POD and PPO activities compared to controls, indicating a heightened defense response. Moreover, treated plants exhibited higher chlorophyll and carotenoid levels, along with increased proline accumulation, which collectively contribute to enhanced photosynthetic efficiency and stress tolerance. Notably, the reduction in malondialdehyde (MDA) levels and lipid peroxidation in mutant-treated plants suggests decreased oxidative damage and improved cellular integrity. The evaluations showed that the mutant isolates decreased disease incidence (DI) more than the corresponding wild-type Trichoderma species, and the use of a mixture of Trichoderma spores (mutant or wild type) showed better efficacy. Overall, mutant Trichoderma species effectively suppress R. solani growth and enhance beneficial physiological changes in bean plants, supporting their use as biocontrol agents for managing damping-off disease sustainably.

Phaseolus vulgaris

Rhizoctonia solani

Gamma irradiation

Trichoderma

Biological control

Physiological parameters

The common bean, scientifically known as Phaseolus vulgaris L., is one of the most important leguminous crops globally, cultivated for its high nutritional value and adaptability to various environmental conditions (Jiménez 2019; Uebersax et al. 2023; Lisciani et al. 2024). Beans are a significant source of protein, fiber, and essential nutrients, making them a staple food in many developing countries. They play a crucial role in food security and are integral to sustainable agricultural practices due to their ability to fix atmospheric nitrogen, thus improving soil fertility (Ahanger et al., 2022). However, the cultivation of common beans is often threatened by various pathogens, among which Rhizoctonia solani is particularly notorious. R.solani is a soil-borne necrotrophic fungal pathogen that affects a wide range of plant species, including many economically important crops. This pathogen is responsible for several diseases, including damping-off, root rot, and crown rot, which can lead to significant yield losses in bean crops (Haque et al., 2021; Eken, 2024). The disease caused by R. solani can manifest at various stages of plant development, from pre-emergence damping-off of seedlings to post-emergence root rot, which severely impacts plant health and productivity (Haque et al., 2021). The pathogen's ability to survive in soil without a host for extended periods complicates its management, as it can persist in the environment and infect crops under favorable conditions (Rashed et al., 2021). The pathogenicity of R. solani is influenced by several factors, including environmental conditions such as temperature and humidity, which can enhance its virulence (CV et al., 2021). The fungus is known to produce a variety of enzymes that degrade plant cell walls, facilitating its invasion and colonization of host tissues (Adejuwon et al., 2021). Moreover, R. solani exhibits a high degree of genetic diversity, classified into multiple anastomosis groups (AGs), each with distinct pathogenic characteristics and host ranges (Razali et al., 2021; AL-Ezerjawi, 2017).

Trichoderma fungus has been well studied as an effective biological control agent for most plant pathogenic fungi (Abbasi et al., 2014; Abbasi et al., 2016; Goharzad et al., 2020; Orojnia et al., 2021; Alizadeh et al. 2024) and has been used as a biocontrol agent against damping-off in bean plants (Naima et al., 2004) and other crops (Lava et al., 2021). Competition for nutrient resources and space, antibiosis, rhizosphere modification, mycoparasitism, promotion of plant growth, and stimulation of defence mechanisms are common mechanisms of action in Trichoderma spp. that work synergistically to control disease (Soufi et al., 2021). Finding a suitable strain of Trichoderma to reduce the effects of pathogens and increase plant growth is the first step in biological control. One limiting factor for the use of Trichoderma species as biofungicides is their relatively low level of biocompatibility under farm conditions (compared with chemical fungicides) (Elad et al., 1983). Therefore, genetic manipulation using mutagenic agents on biological control agents can promote the development of improved biological control products (Abbasi et al., 2016; Haggag and Mohamed, 2002; Naseripour et al., 2014).

One method used to increase the ability of antagonists is to induce random mutations through physical mutagens such as electromagnetic waves, UV, X-rays, gamma rays, or chemical mutagens such as ethylmethane sulfonate. Several studies have been conducted to enhance the antagonistic potential of T. harzianum using genetic engineering techniques and direct mutations in the fungal genome (through mutagenic chemicals, ultraviolet light, and gamma rays) (Mba, 2013; Ghasemi et al., 2020; Mohamadi et al., 2014; Abbasi et al., 2014; Goharzad et al., 2020; Sahampoor et al., 2020; Orojnia et al., 2021; Lava et al., 2021). Accordingly, many researchers have explored ways to induce mutations using physical mutagens to obtain mutants with enhanced antagonistic activity or improved antifungal metabolite production capabilities (Mohamadi et al., 2014; Abbasi et al., 2014; Goharzad et al., 2020; Sahampoor et al., 2020; Orojnia et al., 2021; Lava et al., 2021).

Gamma radiation has emerged as a significant tool in enhancing the biocontrol potential of Trichoderma species, a genus of fungi widely recognized for their efficacy against various plant pathogens (Askari et al. 2024). The application of gamma radiation serves as a mutagenic agent, facilitating the generation of genetic variability within Trichoderma strains (El-Bialy et al. 2019). This variability is crucial for developing new microbial variants that exhibit improved biocontrol traits, such as enhanced antagonistic activity against specific pathogens, increased stability, and safety in agricultural applications (Soufi et al. 2021). The process of mutagenesis through gamma radiation can lead to the selection of strains that not only maintain their biocontrol capabilities but also adapt to changing environmental conditions, thereby ensuring their effectiveness in diverse agricultural settings (Diep et al., 2020). The safety and stability of gamma-irradiated Trichoderma strains are also of paramount importance in their application as biocontrol agents. The regulatory frameworks governing the use of genetically modified organisms (GMOs) necessitate thorough assessments of the ecological impact and safety of these modified strains (Diep et al., 2020). Research has indicated that gamma radiation does not significantly alter the non-pathogenic nature of Trichoderma, making it a suitable candidate for biocontrol applications in organic farming systems (Diep et al., 2020; Rostami et al. 2024). Gamma irradiation is a useful method that increases the antagonistic activity of Trichoderma species against soil-borne plant pathogens (Ghasemi et al., 2019).

In this research, we aimed to present a new approach involving a mixture of mutants of T. harzianum, T. aureoviride, T. lixii, T. atroviride, and T. afroharzianum for biological treatments and their biofungicidal properties by studying priming treatments alongside biological agents and their effects on yield, physiological components, and control of R. solani damping-off disease in bean plants.

2.1. Plant materials and treatments

Fungi (T. harzianum NAS110, T. aureoviride NAS106, T. atroviride NAS112, T. afroharzianum NAS107, and T. lixii NAS114) were obtained from the Nuclear Agriculture Research Institute. R. solani was obtained from the National Seed and Improvement Research Institute (NSIR). This experiment was conducted in a completely randomised design with four replications in a greenhouse. Pinto bean (Phaseolus vulgaris), Talash variety, was selected for this experiment. Seeds were sourced from the Karaj Seed and Plant Reproduction Institute. Several indices, including yield, malondialdehyde concentration, proline, chlorophyll a and b, carotenoids, and protein, were evaluated to determine the stimulation of the bean's defence response to the R. solani pathogen. Plant yield was assessed when 70% of the pods were dried, and for plant physiology, leaf samples were taken at the pre-flowering stage.

2.2. Seed treatments by Trichoderma spores

2.2.1 Mixture of spores for seed treatment

The spores were separated, and their population was adjusted in a carboxymethyl cellulose (CMC) solution to 1×10^8. Arabic gum (40% w/v) was then added.

2.2.2. Suspension of isolates (talc based)

For this biofungicide, a modified method was used. The Trichoderma fungi were cultured on wheat, dried at ambient temperature, and milled. The spores were then collected. The isolates were added to talc powder until the final population in the talc powder reached 1×10^8 spores per gram. The moisture content of the talc powder was reduced to 8% (Jeyarajan & Nakkeeran, 2000).

2.2.3. Treatment of spore mixture in soil

The production of this biofungicide was carried out according to Fravel et al. (1999) with a few modifications. The base composition of the granules contained a CMC solution of spores with Trichoderma fungi (1×10^8) mixed with 50% kaolin and 2% sodium alginate. The mixture was added dropwise into a CaCl2 solution (0.1M, pH 4.8) to form spherical beads. All materials were sterilized before the test, and the spherical beads were dried after being rinsed with distilled water at ambient temperature and stored before use at 4°C (Fravel et al., 1999). Mutant and wild-type spores were added to the soil fourteen days before planting.

2.3. Seeds biopriming

Seeds were surface sterilized in 70% ethanol for 1 minute and in 2% sodium hypochlorite for 40 seconds, then rinsed four times with sterile distilled water. Each of the biofungicides had two types (wild type and mutant). Treatments are shown in full in the following table with an acronym (Table 1).

Table 1

Used treatments and their abbreviation
abbreviations	Treatments	abbreviations	Treatments
pathogen	pathogen without fungicide	control	-
SWP	Mixture of spores for seed treatment by wild type strain + pathogen	SW	Mixture of spores for seed treatment by wild type strain
SMP	Mixture of spores for seed treatment by mutant strain + pathogen	SM	Mixture of spores for seed treatment by mutant strain
TWP	Suspension of isolates (talc based) containing of wild type strain + pathogen	TW	Suspension of isolates (talc based) containing of wild type strain
TMP	Suspension of isolates (talc based) containing of mutant strain + pathogen	TM	Suspension of isolates (talc based) containing of mutant strain
KWP	Spores mixture in soil containing of wild type strain + pathogen	KW	Spores mixture in soil containing of wild type strain
KMP	Spores mixture in soil containing of mutant strain	KM	Spores mixture in soil containing of mutant strain
chemical	pathogen + benomyl

The required soil for the pots was placed in a bag for 1 hour at a pressure of 50 pounds and a temperature of 121°C in an autoclave. The mixture was then blended in a ratio of 1:1:1 with perlite, soil, and peat moss. The seeds were planted in pots containing biofungicides, with two kilograms of soil added on the same day as seeding. The temperature in the greenhouse was maintained at 23–24°C, and the humidity was close to saturation. Irrigation of the pots was carried out immediately after seeding through a flower bed. The control treatment did not contain biofungicides.

In the pre-flowering stage, leaf samples were taken for enzymatic and protein analyses, then crushed in liquid nitrogen and stored at -70°C. For soil inoculation, 3 grams of fungi cultured on a wheat substrate were used. One-third of the fresh soil was blended with R. solani. The disease was assessed on a scale of 1 to 5 using a modified method (Kim et al., 1997) as follows:

0 = Healthy plants without any signs of contamination.

1 = Less than 20 percent of the plants are infected, with at least one large brown spot.

2 = About 50% of the plant has typical spots.

3 = More than 60–70% of the plant has spots.

4 = Seedlings die after emergence from the soil (post-emergence), with seedling lengths of less than 5 cm.

5 = Pre-emergence damping-off or seed rot (pre-emergence).

The disease index was calculated as 100% using the following equation.

$$\:DI\%=\frac{{\sum\:}_{i=1}^{n}\left(Contamination\:scale\:\times\:\:Seedling\:treatment\right)}{Total\:number\:of\:plants\:\times\:\:5}\times\:\:100$$

The denominator is the maximum contamination scale multiplied by the number of cultivated seedlings, resulting in the maximum severity of the disease.

2.4. Biochemical analysis of fresh leaf

2.4.1. Soluble protein extraction of leaf

To generalize enzyme activity to protein units per unit of plant tissue, the total protein content of the leaf extract was determined using the Bradford method (Bradford, 1976). The absorbance was measured at a maximum wavelength of 595 nm, using Bradford Reagent and Protein Bovine Serum Albumin (BSA) as reagents, with a standard curve. The standard range was between 0 and 750 µg/g. The total amount of soluble protein per plant sample was calculated as milligrams of protein per gram of fresh leaf.

2.4.2. Peroxidase enzyme (POD)

Guaiacol substrate, a phenolic compound, was used. The final volume of the reaction was 1 cc, containing 800 µl of 10 mM guaiacol solution in 50 mM phosphate buffer with pH 6, 100 µl of enzyme extract diluted 1:20 in protein extraction buffer, and 100 µM H2O2 at 35 mM. The changes in absorbance were measured at 25°C at 470 nm every 10 seconds for 2 minutes (Dazy et al., 2008).

2.4.3. Polyphenol oxidase (PPO)

A pyrogalol substrate (900 µl) was prepared in 10 mM phosphate buffer at pH 6.5, along with 100 µl of extract at a dilution of 1:2 in protein buffer. The absorbance was measured at 420 nm to remove zeroes from pyrogalol. The enzyme extract was then added, and changes were recorded over 2 minutes and 10 seconds (Raymond et al., 1993).

2.4.4. Chlorophyll a, b and carotenoids

0.5 g of fresh leaf tissue was homogenised with 20 ml of 80% acetone and then centrifuged at 6000 rpm for 10 minutes. Absorbance was read at 663 nm for chlorophyll a, 465 nm for chlorophyll b, and 470 nm for carotenoids using a spectrophotometer. Finally, the chlorophyll content and carotenoids were calculated in mg/g using the following formulas (Arnon, 1973).

$$\:chl\:a=\frac{\left(19.3*A663-0.8*A645\right)v}{100w}$$

$$\:chl\:b=\frac{\left(19.3*A645-3.6*A663\right)v}{100w}$$

$$\:caretenoides=\frac{100\left(A470\right)-3.27\left(mg\:chl\:a\right)-104\:\left(mg\:chl\:b\right)}{227}$$

v = volume of filtered solution (upper solution obtained from centrifugation)

a = absorption of light at wavelengths of 663, 654 and 470 nm

w = sample fresh weight in grams

2.4.5. Proline content

For the extraction and measurement of proline, the method described by Bates et al. (1973) was used. To prepare the ninhydrin reagent, 25.1 g of ninhydrin was dissolved in 30 ml of glacial acetic acid with mild heat, followed by the addition of 20 ml of 6 M phosphoric acid. For the determination of proline content, 0.05 g of tissue was extracted in 10 ml of 3% sulfosalicylic acid. 2 ml of the extract was diluted with 2 ml of ninhydrin solution and mixed with 2 ml of glacial acetic acid, then placed in a water bath at 100°C for 1 hour. After this, 4 ml of toluene was added to the contents of each tube. The supernatant phase, which contained toluene and proline, was separated from the aqueous phase and measured with a spectrophotometer at 520 nm. The standard proline range was 1 to 120 µg/g.

2.4.6. Lipid peroxidation, Malondialdehyde (MDA (

According to this method, 0.2 g of fresh leaf tissue was weighed and pulverized with 5 ml of 0.1% Trichloroacetic acid (TCA). The extract was then centrifuged for 5 minutes, and 1 ml of the centrifuged solution was mixed with 4.5 ml of a 20% TCA solution containing 5 grams of thiobarbituric acid (TBA) per 100 grams. The resulting mixture was centrifuged, and the absorbance was measured using a spectrophotometer at 532 nm and 600 nm. The absorbance of the remaining non-specific pigments at 600 nm was determined, and this value was deducted (Health and Packer, 1968).

2.4.7. SDS-PAGE

The soluble proteins were subjected to SDS-PAGE in gel slabs with a thickness of 1 mm (4% stacking and 12% resolving gels), as described by Laemmli (1970). Electrophoresis was performed using a discontinuous buffer system in a UVP Vertical Electrophoresis Unit (Cambridge, UK). The gel was run at 20 mA until the bromophenol blue marker reached the bottom of the gel. Protein molecular masses were calculated based on comparisons with the following standards (PageRuler™ Protein Ladder SDS-PAGE Standards, Fermentas, molecular weight range 10–200 kDa). After electrophoresis, the gels were rinsed for 20 minutes in an isopropanol-acetic acid-water (1:3:6) solution, followed by 5 minutes in a methanol-acetic acid-water (3:1:6) solution. The gels were then stained for 6 hours in 0.01% (w/v) Coomassie Brilliant Blue R-250. Subsequently, the gels were destained in a methanol-acetic acid-water (3:1:6) mixture until the protein bands became clearly visible.

2.4.8 Protein profile analysis: The gels were scanned and the molecular weight of each band was determined.

2.4.9. Extraction and Assay of Peroxidase (POD)

Peroxidase activity was measured according to the method of Kar and Mishra (1976), using pyrogallol as the substrate. The activity of the enzyme (Enzyme Unit, i.e. E.U.) was calculated. Peroxidase isoenzymes were analysed from the bean leaf.

2.4.10. Polyphenol oxidase zymogram

To develop the polyphenoloxidase enzyme bands on the polyacrylamide gel, the method by Van Loon (1971) was employed.

2.4.11. Data analyze

Data were analysed using SPSS software. The comparison of means was conducted using Duncan's multiple range test at a probability level of 5%. Charts were created with Excel.

3.1. Function of bean plants in the greenhouse

The yield of plants in the presence of Trichoderma (wild type and mutant) was significantly improved compared to the control and showed a significant difference from the control. The increase in grain yield compared to the control was 62.9% in the Trichoderma treatment and 58.2% in the Trichoderma mutant treatment (Fig. 1). Additionally, the roots from the soil showed significant differences; the roots of the control plants were very small, weak, and without nodes. The roots from the chemical treatment were also small. In contrast, the roots of the plants treated with Trichoderma bio-fungicides were bulky, full of nodules, and weighed more.

3.2. Biocontrol R. solani with biological fungicide

The comparison of the mean disease incidence index showed that in the absence of the pathogen (control), the percentage of root and crown rot was less than 1% (due to environmental factors). In contrast, in other treatments with R. solani, different control methods exhibited a significant difference in disease incidence compared to the control (pathogen). In plants grown in soil contaminated with R. solani, 90% of the plants were affected by root and crown rot. The incidence of disease with the chemical fungicide (Benomyl at a concentration of two per thousand) was 58%. Compared to the chemical control, all plants treated with the bio-fungicide at a 5% level had a significantly lower percentage of disease incidence, indicating that R. solani biocontrol was more effective than the chemical method. The PMP showed 18% disease incidence, while the weakest biocontrol in the KWP was 30%. No significant difference was found between the bio-fungicides at the 5% level in reducing the incidence of disease. However, a comparison of averages indicated that the bio-fungicides composed of a mixture of spores in the soil were less effective than other bio-fungicides, which reduced the incidence of disease. On the other hand, in each bio-fungicide treatment, the use of Trichoderma mutant spores was more effective in reducing the occurrence of the disease than the bio-fungicides derived from wild Trichoderma (Fig. 2).

3.3. Biochemical analysis of fresh leaf

3.3.1. Soluble protein

By plotting the regression relationship between BSA and absorbance, the amount of protein extracted from the aerial parts of bean plants (40 days after treatment) was measured. A comparison of groupings performed for the measured proteins showed that treatments were significant at the 5% level. Comparing the mean soluble protein across all treatments (Table 2), the protein content was highest in all treatments involving wild-type Trichoderma, followed by the benomyl chemical treatment. In other bio-fungicides prepared from both wild-type and mutant Trichoderma, the amount of protein accumulated in the plant cells treated with them was lower than that of the mixture of spores used for seed treatment and did not show any significant difference compared to the control plants. In the presence of the pathogen, the average protein content in all bio-fungicide treatments was higher than in the absence of the pathogen. However, in plants infected with pathogens, the protein levels were significantly lower in those seeds treated with granules produced by the mutant strain. Further enzymatic analyses can help interpret the extent to which this accumulation is associated with the proteins involved in the response to the pathogen and which bio-fungicides were able to accumulate effective proteins that enhance resistance in the plant.

Table 2
Comparison of the amount of protein measured in Trichoderma, pathogenic, and non-pathogenic treatments using Duncan's multiple range test.
Treatment	Soluble protein (µg/g fw)
control	2225.53 gh
SW	4138.78 a
KW	2355.64 fg
TW	2411.35 gh
SM	2127.26 fg
KM	2251.46 h
TM	2476.53 f
SWP	2867.69 de
KWP	2949.97 de
TWP	2776.69 e
SMP	2994.89 d
KMP	1859.84 i
TMP	3286.76 c
CHEM	3757.12 b

3.3.2. Molecular weight estimation of proteins and zymogram of enzymes

All treatments and control plants (without Trichoderma, wild type, and mutant fungi) exhibited different protein bands with molecular weights ranging from 10 to 180 kDa (Fig. 3). Additionally, in the protein profile of small red beans, bands with molecular weights of 80 and 74 kDa were observed (Rui et al., 2012).

All specimens, except for the seeds treated with the granules of the mutant isolates, exhibited a sharp band at a molecular weight of 62 to 66 kDa (Fig. 3). The seed samples treated with mutant isolate granules (KM), which had a molecular weight of 62.7 kDa, also displayed a protein band, but it appeared fainter compared to the other treatments. In terms of the presence of other sharp bands (with molecular weights from 36 to 40 kDa, 25 to 29 kDa, and 20 to 23 kDa), there was no difference between the samples of treated seeds with different Trichoderma fungal bio-fungicides and the control plant samples (Fig. 3). However, the highest levels of the aforementioned bands were observed in the SW, TM, and KW treatments (Fig. 3).

The highest intensity of the enzyme band at a molecular weight of 65–68 kDa was observed in the sample treated with the PM, as well as in the samples treated with the SM and the TW. The strongest band was observed at a molecular weight of 43 to 45 kDa in the samples treated with the TM, followed by the SM (Fig. 4). All specimens exhibited different protein bands in the molecular weight range of 10 to 180 kDa. The lowest band strength was observed in the control protein sample. The KMP samples differed in terms of the diversity of existing protein bands compared to the other treatments. A sharp band at a molecular weight of about 62 to 66 kDa was observed across the different treatments, while the KMP sample was noted to have this band as very weak. Additionally, the protein band at a molecular weight of 30–40 kDa was also very weak in this treatment. The sharpest bands were visible in the TMP, and after this treatment, the SMP and the TWP exhibited greater band strength than the other treatments.

The protein profiles of pinto beans, bright red beans, and dark red beans showed a molecular weight of 63 kDa (Rui et al., 2012). Beans of the variety's navy, pink, pinto, big northern, and small red bean exhibited bands at less than 60 kDa (Rui et al., 2012). Pinto beans, bright red beans, and dark red beans had bands at a molecular weight of 17 kDa, while the cultivars had bands at 18 kDa (Rui et al., 2012). The sharp bands in red beans were observed at about 35 kDa (Rui et al., 2012). All treatments and control plants had different bands in the molecular weight range of 290 to 35 kDa (Fig. 5 and a5). The presence of different molecular weight bands in the zymogram of the peroxidase demonstrates the various subunits of this enzyme in the plant leaf samples. The molecular weight of 265 to 210 kDa showed the highest band in the KM samples, followed by the KW and TM samples (Fig. 5 and a5). The highest intensity of the enzyme band at a molecular weight of 65–68 kDa was observed in the samples treated with the TM, as well as in the samples treated with the CM and TW. The strongest band was observed at a molecular weight of 43 to 45 kDa in the samples treated with the TM, followed by the SM (Fig. 5 and a5). The molecular weight of peroxidase is reported to be 44 kDa (Arredondo and Escamilla, 1993). A clear band of peroxidase was observed between 35 and 50 kDa, with the specified molecular weight for peroxidase being 45 kDa when compared to standard molecular weight markers (Nar et al., 2013; Akıncıoğlu et al., 1992; Köktepe et al., 2017).

All treatments and control plants exhibited peroxidase enzyme bands at molecular weights ranging from 35 to 223 kDa. The presence of different molecular weight bands in the zymogram of the enzyme peroxidase indicates the various subunits of this enzyme in the plant leaf samples. A sharp band at a molecular weight of 231 kDa was observed in the SMP. This enzyme band was found to have a molecular weight of 232 kDa with less intensity in KMP and very weakly in KWP. Other treatments lacked this enzyme band. In all treatments, the enzyme band at a molecular weight of 60 kDa (ranging from 58 to 62 kDa) varied between samples, with the highest activity of this enzyme observed in the KMP sample, followed by the KWP. Other treatments showed a very weak band for this enzyme. Another sharper band was observed in the treatments of KWP, KMP, and SMP, respectively, at molecular weights of 43, 46, and 43 kDa. Other treatments showed weak bands in this molecular weight range. The molecular weight of most peroxidases is reported to be between 30 and 60 kDa, which may be due to differences in the amino acid sequence or the degree of glycosylation (Welinder, 1992).

All treatments and control plants exhibited different bands with molecular weights ranging from 35 to 245 kDa (Fig. 7; a and b). The presence of different molecular weight bands in the zymogram of the polyphenol oxidase enzyme indicates the various subunits of this enzyme in the plant leaf samples (Fig. 3 and a3). The control, KW, and PM samples exhibited a change in colour due to enzyme activity at a molecular weight of 228 to 245 kDa (Fig. 7; a and b). In the control plants, staining caused by enzyme activity was observed at molecular weights of 44.7 kDa and 42.85 kDa (Fig. 7; a and b). In the SW sample, no colour change was observed due to enzyme activity (Fig. 3 and a3). The highest activity of the polyphenol oxidase enzyme, with molecular weights of 41 and 44 kDa, was observed in the TM and SM samples (Fig. 7; a and b). Other treatments, including KW, KM, and TW, showed very small bands due to the activity of the polyphenol oxidase enzyme (Fig. 7; a and b). Similar results were reported for the polyphenol oxidase enzyme in velvet beans (Zenin and Park, 1978). The molecular weight of four isoforms of polyphenol oxidase, ranging from 39.0 to 57.5 kDa, was based on SDS-PAGE (Guo et al., 2009).

The highest activity of the polyphenol oxidase enzyme, with molecular weights of 41 and 44 kDa, was observed in the TM and SM treatments (Fig. 7; a and b). Other treatments, including KW, KM, and TW, showed only very small bands due to the activity of the polyphenol oxidase enzyme (Fig. 3).

All treatments and control plants had a polyphenol oxidase enzyme band within the molecular weight range of 25 to 35 kDa (Fig. 8). The presence of various molecular weight bands in the zymogram of the enzyme peroxidase indicates the different subunits of this enzyme in the plant leaf samples. The sharpest band at a molecular weight of 245 kDa was visible in the SMP sample, followed by KMP and partially in KWP. Other treatments did not exhibit this enzyme subunit. The SMP sample was more diverse than the other treatments in terms of variety, owing to the presence of different subunits of the polyphenol oxidase enzyme in this plant sample, with visible molecular weights of 76, 60, 44, and 42 kDa. The 76 kDa enzyme subunit was only visible in this treatment, and other treatments lacked this enzyme band. The enzyme bands of 58 to 61 kDa were visible in the SMP, KMP, and KWP samples. The control, SWP, and SMP exhibited both subunits of 44 and 42 kDa. The control and SWP displayed this enzyme band very weakly. The most abundant enzyme band of 42 kDa was observed in KWP. KMP lacked this molecular weight of enzyme subunits and instead had an enzymatic subunit of 45 kDa. The samples from TWP and TMP, along with chemical treatments, showed the weakest activity of the polyphenol oxidase enzyme.

3.3.3. Results of measurement of chlorophyll a, b and carotenoids

Compared to the mean chlorophyll measurement (Fig. 9), SW exhibited higher chlorophyll levels than the rest of the treatments, followed by KM. SM was in the next group. The comparison of the mean chlorophyll a level in the presence of a significant amount of R. solani pathogens (Fig. 9) indicated that benomyl was the most effective. The control, SWP, and TMP were at a significant level, while KMP and KWP were in the lowest category and were together at a significant level. However, the pathogen treatment without the presence of the Trichoderma biological fungicide was completely eliminated. The comparison of the mean chlorophyll b measurements (Fig. 9) showed that the chlorophyll b content in SW was higher than in the other treatments, followed by KM and TW. The grouping of the mean chlorophyll b measurements (Fig. 9) indicated that KMP and KWP were in the last group. The comparison of the mean carotenoid measurements (Fig. 9) revealed that SW was most likely to contain the highest levels of carotenoids, with KM and TW both in the same group. Among the different treatments of Trichoderma, the control group had the least amount of carotenoids. The results of the groupings for carotenoid measurements (Fig. 9) indicated that the levels of carotenoids in the chemical treatments, SWP, and control were at a significant level, while TMP and SWP treatments were also at a significant level.

Lipid peroxidation:

Regarding the increase in malondialdehyde concentration in plant cells under stress conditions, the analysis of variance for the malondialdehyde data showed that the highest amount of MDA (ignoring the non-pathogenic treatments) was observed in the treatment with benomyl combined with the pathogen and TW (Fig. 10). It can be concluded that the chemical fungicide has the least control over pathogen effects. It should also be noted that KW and KM had higher MDA levels than the control, but the other bio-fungicides were more effective at controlling pathogen-induced stress. TW, SWP, TM, KM, and TWP, TMP, respectively, exhibited the lowest amounts of MDA across all treatments and did not differ statistically. Boroujerdnia et al. showed that MDA levels increase with higher stress (Boroujerdnia et al., 2016). An increase in malondialdehyde indicates significant destruction of the cell membrane in this variety under the stress of the disease. Gunez et al. reported higher concentrations of malondialdehyde in leaves under stress in corn (Gunez et al., 2007).

3.3.4. Proline:

The average results of the treatments indicated that proline concentration was higher in most pathogenic treatments than in the control. The lowest amount of proline was observed in TM, which showed a significant difference compared to the other treatments. Proline levels were highest in KMP and KWP (Fig. 11). In comparison to the averages, the effects of TMP and TWP were greater than those of the control. Low levels of proline indicate effective control by the bio-fungicides derived from the Trichoderma fungus. Additionally, the benomyl chemical fungicide was significantly higher than TMP and TWP in terms of proline concentration.

The study indicated that Trichoderma-based bio-fungicides provide better disease control than chemical fungicides and could be tested in greenhouse conditions exposed to pathogens. Protein expression changes were observed in the presence of Trichoderma in bean plants, alongside a significant reduction in lipid peroxidation and variations in proline accumulation, which aids in water absorption. Furthermore, inducing mutations in the Trichoderma genome enhances the secretion of extracellular enzymes in the rhizosphere, aiding nutrient release and absorption, strengthen roots, and promoting systemic resistance in plants. This biological fungicide not only boosts the effectiveness of Trichoderma but also improves the interaction between beans and pathogens, leading to increased protein content and heightened enzyme activity, ultimately enhancing plant resistance to diseases. Overall, the utilization of mutant Trichoderma species in the rhizosphere represents a promising strategy for sustainable agriculture, providing an eco-friendly alternative to chemical pesticides while enhancing plant resilience against soil-borne pathogens. These results are consistent with Begum et al. (2010), supporting the efficacy of soybean seed bioprimed treatment with Trichoderma for controlling Colletotrichum truncatum, as well as Abuamsha et al. (2011), who demonstrated control of Leptosphaeria maculans through biopriming with Pseudomonas bacteria. Some species of Trichoderma, such as T. harzianum and T. viride, possess properties such as mycoparasitism, antibiotic production, and saprophytic competition, which can significantly reduce the pathogenic fungal population (Soltani, 2008). However, under natural conditions, their low proliferation units in the soil are not effective in controlling fungal diseases (Cavalcante et al., 2008).

The interaction between Trichoderma species and the plant pathogen R. solani has garnered significant attention due to the potential of these fungi as biocontrol agents (Verma et al. 2025). Different species of Trichoderma have been shown to inhibit rotting caused by R. solani in the seeds of cotton, sugar beet, and soybeans (Vasanthakumari and Shivanna, 2013). Many previous reports have emphasised the use of T. harzianum and T. viride to control root rot and to prevent the growth of root rot fungi using T. polysporum as a biocontrol agent (Rajput and Shahzad, 2015). The impact of mutant Trichoderma species in the rhizosphere on inducing resistance in beans against soil-borne pathogens is a multifaceted phenomenon that underscores the potential of these fungi as biocontrol agents. Mutant strains of Trichoderma exhibit enhanced capabilities to colonize plant roots, thereby establishing a beneficial relationship that promotes plant health and resilience against pathogens. Trichoderma species, particularly T. harzianum and T. viride, exhibit various mechanisms of antagonism against R. solani, including mycoparasitism, competition for resources, and the production of bioactive compounds. These interactions can lead to significant changes in plant physiological parameters, including the activity of peroxidase (POD) and polyphenol oxidase (PPO), as well as alterations in chlorophyll content, carotenoid levels, proline accumulation, lipid peroxidation, and malondialdehyde (MDA) levels. Trichoderma species are known for their mycoparasitic behavior, which allows them to effectively suppress the growth of R. solani. For instance, studies have shown that T. harzianum and T. viride can parasitize the mycelial growth of R. solani, leading to a reduction in the pathogen's viability (Huma, 2022). The antagonistic activity of these Trichoderma species is not uniform; different isolates exhibit varying degrees of effectiveness against R. solani, which can be attributed to their genetic and biochemical diversity (Abbas & Fu, 2017). This variability underscores the importance of selecting specific Trichoderma strains for effective biocontrol applications. The efficacy of Trichoderma spp. in controlling R. solani is also linked to their ability to induce systemic resistance in host plants. This induction is often accompanied by an increase in the activity of antioxidant enzymes such as POD and PPO, which play crucial roles in mitigating oxidative stress caused by pathogen attack (Ahmad et al., 2015; Yasmeen & Siddiqui, 2017). Enhanced POD activity, in particular, has been associated with the detoxification of reactive oxygen species (ROS) generated during pathogen infection, thereby protecting plant tissues from damage (Çam & Küçük, 2020). Furthermore, the application of Trichoderma can lead to increased chlorophyll a and b levels, as well as carotenoid content, which are vital for photosynthesis and overall plant health (Prisa, 2019). In addition to enhancing antioxidant enzyme activity, Trichoderma spp. can influence proline metabolism in plants. Proline is an important osmoprotectant that accumulates in response to stress conditions, including pathogen infection. The presence of Trichoderma has been shown to elevate proline levels in host plants, which helps in maintaining cellular integrity and function under stress (Çam & Küçük, 2020). This accumulation of proline is often correlated with reduced lipid peroxidation and lower MDA levels, indicating decreased membrane damage and improved cellular stability (Ahmad et al., 2015; Yasmeen & Siddiqui, 2017). The interaction between Trichoderma and R. solani also affects the lipid peroxidation process in plants. Lipid peroxidation is a key indicator of oxidative stress, and its byproduct, MDA, is often used as a marker for cellular damage. Studies have demonstrated that the application of Trichoderma can significantly reduce lipid peroxidation levels in infected plants, thereby lowering MDA concentrations and enhancing plant resilience against R. solani (Yasmeen & Siddiqui, 2017; Prisa, 2019). This reduction in oxidative damage is critical for maintaining plant health and productivity, especially in agricultural systems where R. solani poses a significant threat. Moreover, the production of volatile organic compounds (VOCs) by Trichoderma species has been implicated in the suppression of R. solani. These VOCs can inhibit the growth of the pathogen and stimulate plant defense mechanisms, further enhancing the protective effects of Trichoderma (Jong et al., 2023). Also, the species T. harzianum, T. aureoviride, T. lixii, T. atroviride, and T. afroharzianum have been verified that mutation via gamma radiation enhanced biological activity against R. solani (Rezaloo et al., 2019).

The impact of mutant Trichoderma species on various physiological and biochemical parameters in beans, particularly in relation to their interaction with soil-borne pathogens such as R. solani, is a critical area of research in sustainable agriculture. Mutant strains of Trichoderma have been shown to enhance the activity of key enzymes such as peroxidase (POD) and polyphenol oxidase (PPO), which are integral to the plant's defense mechanisms against pathogens. Increased POD and PPO activities are associated with the plant's ability to detoxify reactive oxygen species generated during pathogen attack, thereby mitigating oxidative stress and promoting plant resilience (Ghoniem et al., 2021). Furthermore, the presence of Trichoderma species has been linked to elevated levels of chlorophyll a, b, and carotenoids in bean plants, which not only enhances photosynthetic efficiency but also contributes to the overall vigor of the plants under pathogen pressure (Mahmoodian et al., 2022). The modulation of proline content, a well-known osmoprotectant, is another significant effect observed with Trichoderma inoculation; elevated proline levels help in osmoregulation and protect cellular structures from damage during stress conditions (Vukelić et al., 2020). Additionally, the reduction of lipid peroxidation and malondialdehyde (MDA) levels in plants treated with mutant Trichoderma indicates a decrease in membrane lipid degradation, reflecting improved cellular integrity and reduced oxidative damage (Rush et al., 2021). This comprehensive enhancement of physiological traits not only improves the plants' defense against R. solani but also promotes overall growth and yield, highlighting the potential of utilizing mutant Trichoderma species as effective biocontrol agents in agricultural practices (Wang, 2024).

In conclusion, the application of gamma radiation to enhance the biocontrol potential of Trichoderma species represents a promising avenue for sustainable agriculture. By generating genetically diverse strains with improved antagonistic capabilities and resilience, researchers can develop effective biocontrol agents that contribute to the management of plant diseases while minimizing reliance on chemical pesticides. The profound impact of Trichoderma species on Rhizoctonia solani highlights their ability to influence various physiological parameters in host plants, including changes in POD and PPO activities, chlorophyll and carotenoid levels, proline content, lipid peroxidation, and MDA levels. These mechanisms of action, which include mycoparasitism, competition for resources, and the production of bioactive compounds, underscore Trichoderma's potential as a biocontrol agent and its role in enhancing plant resilience against pathogenic threats. The advancements in mutagenesis techniques pave the way for innovative solutions to combat the challenges posed by phytopathogens in modern agriculture. Future research should focus on elucidating the specific molecular pathways involved in these interactions to optimize the use of Trichoderma species in sustainable agricultural practices.

Acknowledgements

This article is part of the project "Production of biological materials for the control of soil borne pathogens -200-96-3A-PCR"

Authors’ contributions

S.S. designed the study. S.S., Z.R. A.A.A. and H.A. performed experiments.

All authors analyzed the data, wrote the manuscript, provided technical assistance, read and approved the final manuscript.

Funding

This work was supported by Nuclear Science and Technology Research Institute.

Data availability

All data generated or analyzed during this study are included in this article.

Ethics approval and consent to participate

All authors consent to participate.

Consent for publication

All authors consent for publication.

Competing interests

The authors confirm that there are no competing interests related to this study.

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You are reading this latest preprint version

Physiological Responses of Phaseolus vulgaris to Damping-Off Disease Control Using Mutant Trichoderma spp.

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Abstract

Figures

1. Introduction

2. Material and methods

2.1. Plant materials and treatments

2.2. Seed treatments by Trichoderma spores

2.2.1 Mixture of spores for seed treatment

2.2.2. Suspension of isolates (talc based)

2.2.3. Treatment of spore mixture in soil

2.3. Seeds biopriming

2.4. Biochemical analysis of fresh leaf

2.4.1. Soluble protein extraction of leaf

2.4.2. Peroxidase enzyme (POD)

2.4.3. Polyphenol oxidase (PPO)

2.4.4. Chlorophyll a, b and carotenoids

2.4.5. Proline content

2.4.6. Lipid peroxidation, Malondialdehyde (MDA (

2.4.7. SDS-PAGE

2.4.9. Extraction and Assay of Peroxidase (POD)

2.4.10. Polyphenol oxidase zymogram

2.4.11. Data analyze

3. Results

3.1. Function of bean plants in the greenhouse

3.2. Biocontrol R. solani with biological fungicide

3.3. Biochemical analysis of fresh leaf

3.3.1. Soluble protein

3.3.2. Molecular weight estimation of proteins and zymogram of enzymes

3.3.3. Results of measurement of chlorophyll a, b and carotenoids

3.3.4. Proline:

4. Discussion

5. Conclusion

Declarations

References

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