Streamlining the defense mechanism involving miRNA/mRNA and phytohormones during mycorrhiza-fusarium infecting tomato roots

Simplificando o mecanismo de defesa envolvendo miRNA/mRNA e fito-hormônios durante infecção por micorriza-Fusarium em raízes de tomateiro

Abstract

This study was carried out to identify the relationship between miRNAs/ targets and phytohormone-related genes associated with Rhizophagus irregularis/ F. oxysporum f. sp. lycopersici (Fol) interaction through post-infection of tomato roots at different stages. Furthermore, to address the role of miRNA-mediated families in regulating plant hormone crosstalk during plant-microbe interactions, including salicylic acid (SA), jasmonic acid (JA), abscisic acid (ABA), auxin (AUX) and 5 ethylene (ET). In this study, Expression levels of ethylene-responsive genes reflect antagonism between arbuscular mycorrhizal fungi (AMF) and ET, re-modulating immunoregulatory capacity in tomato. On the other hand, our data reinforce that overexpression of AP2 and ERF1 delay senescence in Fol-infected tomato plants by downregulating the expression level of SPL3. Moreover, a balance between TCP4, miR164, and miR319b transcript levels suggests that their interaction attenuates senescence under AMF infection.

Measurements of phytohormone production under AMF/Fol infection at 30 days post-inoculation (dpi) showed significantly lower hormone production in the resistant genotype (Heinz 'Hz') compared to the susceptible genotype (Castle Rock 'CR') by 36, 17, and 14% for ET, ABA, and JA, respectively. These findings potentially imply that modifications in Heinz’s hormonal signaling are prompting host changes, which lead to decreased phytohormone levels. This study provides an applied basis for further research on the molecular mechanism and challenges associated with the continuous cropping of tomato by R. irregulari under the deleterious effects of Fusarium on late stages of root infection.

Keywords:
Rhizophagus irregulari; Fusarium oxysporum; small RNAs (miRNAs); jasmonic acid; salicylic acid; Solananum lycopersicum

Resumo

Este estudo foi realizado para identificar a relação entre miRNAs/alvos e genes relacionados a fito-hormônios associados à interação Rhizophagus irregularis/F. oxysporum f. sp. lycopersici (Fol) através da pós-infecção de raízes de tomateiro em diferentes fases. Além disso, para abordar o papel das famílias mediadas por miRNA na regulação da comunicação cruzada de hormônios vegetais durante as interações planta-microrganismo, incluindo ácido salicílico (SA), ácido jasmônico (JA), ácido abscísico (ABA), auxina (AUX) e etileno (ET). Neste estudo, os níveis de expressão de genes responsivos ao etileno refletem o antagonismo entre fungos micorrízicos arbusculares (FMA) e ET, remodulando a capacidade imunorreguladora no tomate. Por outro lado, nossos dados reforçam que a superexpressão de AP2 e ERF1 atrasa a senescência em tomateiros infectados com Fol, regulando negativamente o nível de expressão de SPL3. Além disso, um equilíbrio entre os níveis de transcrição de TCP4, miR164 e miR319b sugere que sua interação atenua a senescência sob infecção por FMA.

Medições da produção de fito-hormônios sob infecção por FMA/Fol aos 30 dias pós-inoculação (dpi) mostraram produção hormonal significativamente menor no genótipo resistente (Heinz 'Hz') em comparação ao genótipo suscetível (Castle Rock 'CR') em 36%, 17% e 14% para ET, ABA e JA, respectivamente. Estas descobertas implicam potencialmente que modificações na sinalização hormonal de Heinz estão provocando alterações no hospedeiro, o que leva à diminuição dos níveis de fito-hormônios. Este estudo fornece uma base aplicada para futuras pesquisas sobre o mecanismo molecular e os desafios associados ao cultivo contínuo de tomate por R. irregularis sob os efeitos deletérios do Fusarium nos estágios finais da infecção radicular.

Palavras-chave:
Rhizophagus irregularis; Fusarium oxysporum; pequenos RNAs (miRNAs); ácido jasmônico; ácido salicílico; Solananum lycopersicum

1. Introduction

Signaling pathways are triggered through a wide range of pathogens to activate several redundant mechanisms through different associated molecular patterns leading to changes in the levels of immune-related hormones (Pozo et al., 2015). These include SA, JA, ET, ABA, and AUX. In turn, these hormones activate transcription factors that regulate the expression of defense genes (Aerts et al., 2021). F. oxysporum f. sp. lycopersici (Fol) (Sacc.) W. C. Snyder is a xylem-colonizing fungus that causes fusarium wilt in tomato (S. lycopersicum) (Fravel et al. 2003). One of the early management systems for controlling Fusarium infection is through planting resistant cultivars in the previously infected fields (Jones et al., 1991). Furthermore, plant symbiotic microorganisms may influence the consequences of pathogen infection, promoting the growth of host plants and enhancing their tolerance to biotic and abiotic stresses (Smith and Read, 2008). Nevertheless, arbuscular mycorrhizal fungi (AMF) form a symbiotic relationship with plant roots to trigger defense responses in a manner similar to that triggered by biotrophic and hemibiotrophic pathogens (García-Garrido and Ocampo, 2002; Pozo and Azcón-Aguilar, 2007). Establishing a successful symbiosis requires suppressing the initial defense response against AMF (Jung et al., 2012). Moreover, mycorrhizal symbiosis provides protection against a number of soilborne fun-gal pathogens (St-Arnaud and Vujanovic, 2007). Hormone levels in plants change during the establishment of AMF colonization, whereas SA levels in plants increase during the early stages of colonization, resulting in increased expression of plant defense genes (Pradhan and Requena, 2022). Systemic acquired resistance (SAR) and induced systemic resistance (ISR) are triggered by pathogen infection and root colonization by non-pathogenic mycorrhizal infection (Dreischhoff et al., 2020; Vlot et al., 2021). Moreover, there are various phytohormones that have been integrated as potential signals for SAR and ISR activation, e.g., SA, JA, and ET (Dreischhoff et al., 2020). One of the most important SA-associated genes is NPR1, a master transcription factor in the SA pathway that mediates the resistance of tomato plants to biotrophic pathogens. Nonexpressor of pathogenesis-related genes 1 (NPR1), which triggers the accumulation of pathogenesis-related proteins such as LRRs, PR1, PR2, and chitinase3 (PR3) (Zhang et al., 2015; Constantin et al., 2019; Alsamman et al., 2023). JA/ET-responsive defense genes such as lipoxygenaze (LOX), coronatine-insensitive1 (COI1), jasmonate ZIM-domain (JAZ), basic-helix-loop-helix (bHLH) transcription factor (TF) MYC2, NAC domain protein 1 (NAC1), ethylene response factors (ERF), plant defensin 1.2 (PDF1.2), ethylene insensitive2 (EIN2) and ethylene insensitive3 (EIN3) have been implicated in the JA/ET crosstalk (Hayashi et al., 2023). More recent studies indicate that AUX such as TIR1 and ARF6 greatly affect the plant defense system during fungal infection and crosstalk with SA (Han and Hwang, 2018; Caruana et al., 2020). Moreover, it is believed that 9-cis-epoxycarotenoid dioxygenase (NCED) as an ABA-biosynthesis gene and its responsive gene (RD22) play a role in regulating plant-pathogen interaction (Du et al., 2014; Purohit et al., 2019). However, successful AMF colonization requires suppressing them during the latter stages (Paszkowski et al., 2006; Hause et al., 2007; Kapoor et al., 2008; Axtell and Meyers, 2018). Plant microRNAs (miRNAs) are a class of short non-coding RNAs (21-24 nt), that regulate the transcriptional and post-transcriptional level of target genes (Jones-Rhoades et al., 2006; Wu et al., 2016). Moreover, miRNAs are required to control hormone signaling, nutrient signaling, and plant development to trigger plant resistance to abiotic and biotic stresses (Pant et al., 2008; Li and Zhang, 2016). Nevertheless, studies have reported that miRNAs play vital roles in plant-microbe symbiosis (Zeng et al., 2023). Plant and AMF symbiosis is the most interesting plant–microbe interaction (Oldroyd, 2013). Moreover, the mechanisms of resistance to vascular pathogen and its interaction with mycorrhizal infection have been reported to be mediated by SA and/or JA/ET/AUX/ABA pathways and miRNA families that mediate the defense hormone pathway (Zeng et al., 2023). There are several miRNA families that exhibit regulatory links with SA, JA, ET, ABA, and AUX and play a role in manipulating these hormones during root development, phase transition, senescence, disease, and symbiosis. These families include miR156, miR159, miR172, miR393, miR319, miR164, miR482, and miR5300 (Gu et al., 2010; Curaba et al., 2014; Ouyang et al., 2014; Pavitra et al., 2017; Ye et al., 2020; Xu et al., 2021). In this work, we investigated the expression levels of miRNAs and their target genes and some immune-response genes that could be potentially integrated into R. irregularis colonized plants against the vascular pathogen Fol.

2. Materials and Methods

2.1. Greenhouse experiment

Tomato Solanum lycopersicum L. cultivar Heinz “Hz” was selected as tolerant cultivar as indicated by the manufacturer company (Heinz,) and Castle Rock “CR” cultivar was selected as susceptible to Fol, as indicated in the previous literature (Wahid et al., 2001). Tomato seeds were sterilized with sodium hypochlorite (NaOCl, 5%, v/v). Then, the sterilized seeds were washed three times with distilled water followed by sowing in trays containing a sterilized mixture of peat, perlite, and sand (1:1:1, v/v/v) under controlled environmental conditions (day/night temperature of 28/16°C; relative humidity, 56%). Four-week-old tomato seedlings were transplanted in 1-liter pots containing a mixture of sterilized loam soil, sand, and peat moss (1:1:1, v/v/v). The experiment was carried out in the bio-containment greenhouse facility at the Agricultural Genetic Engineering Research Institute (AGERI), Agricultural Research Center (ARC), Giza, Egypt. Plantlets were grown under controlled conditions (30.0 ± 5.0^◦C; 56.0 ± 14.2% RV; 20.0 klux). Four trials were performed; (1) plantlets (control), (2) plantlets inoculated with AMF, (3) plantlets inoculated with Fol, (4) plantlets inoculated with Fol and AMF (AMF+Fol).

2.2. Fungal culture

F. oxysporum f. sp. lycopersici (Fol) (ON870803) was isolated from the infected tomato roots cultivated at Dakahlia Governorate, Egypt. Fol was cultivated for 15 -21 days 25±1ºC darkness on potato dextrose agar (PDA) mixed with 50 mg.L^-1 of antibiotic tetracycline to inhibit the growth of bacteria. The microconidia were collected by flooding the Fusarium medium with sterile, distilled water and gently rubbing with an alginate spatula. Fol was multiplied in sand maize medium and incubated for 15 days (28 ± 2 °C) for maximum multiplication. After 10 days the number of colony-forming unit (cfu)/ 1 mg were determined in the pathogenic culture. Inocula were adjusted to contain 106 cfu /gm by adding only sterilized media and mixing thoroughly. Inocula F. oxysporum was added to clean soil at a rate of 10 gm/kg soil. R. irregularis (ON869380) belongs to the Plant Pathology Research Institute (PPATHRI), ARC, Giza, Egypt. R. irregularis was propagated on Sudan grass (Sorghum Sudanese trap plant) grown for 4 months (Graham et al., 1982). During transplantation, 10 g/pot (1 clay: 2 sand) of the respective AMF inoculum (230 spores/ 50 gm) were added per plant. Ten pots (three plants per pot/ experiment) were used as replicates. Pots were arranged in a completely randomized design and kept under greenhouse conditions (30.0 ± 5.0 °C; 56.0 ± 14.2% RV; 20.0 klux). Thirty days after sowing, the soil was infested by mixing the R. irregularis inoculum at 2.5% (w/w). The root samples for analysis were collected 7, 14 and 30 days post inoculation (dpi) and immediately frozen at -80 °C.

2.3. Genomic DNA extraction

Frozen tomato roots were ground in liquid nitrogen and genomic DNA was extracted using the DNeasy Plant Mini Kit (Qiagen, Hilden, Germany), according to the manufacturer’s instructions. To isolate the DNA from AMF and Fol, QIAprep Spin Miniprep Kit (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. Genomic DNA quality and quantity were measured using NanoDrop™ 2000 (Thermo Fisher Scientific, Waltham, MA, USA).

2.4. Fungi quantification detection using qPCR

AMF- and Fol- colonization were quantified using qPCR (Bodenhausen et al., 2014). Briefly, the R. irregularis and F. oxysporum were quantified based on the GiAM and Fef genes, respectively (Casan et al., 2004; Haegi et al., 2013). In brief, GiAM was designed for the 28S RNA region, demonstrating high specificity and fidelity for R. irregularis. On the other hand, Fef gene, was designed through the comparison of EF-1α gene sequences, generated by amplification with the EF1/EF2 primer pair, from Fusarium spp. Both genes were normalized using the tomato-specific Actin gene, without matching of the genome background. The PCR amplifications were performed in total volumes of 20 µl: 1 µl (10 ng/µl) of diluted DNA, 10 µl of 2×BioEasy SYBR Green Master Mix (BIOER, Hangzhou, China), 1 L (10 M) each of GiAM-F and GiAM-R primers, as well as Fef1-F and Fef2-R primers.

qPCRs with SYBR Green Master Mix were carried out on Mx3000P QPCR System (Agilent Technologies, Inc., Santa Clara, CA, USA); starting cycle of 95°C for 2 min, 35 cycles of 95°C for 5 s and 60°C for 40 sec. The GiAM and Fef genes signal from AMF and Fol, respectively, was normalized to the plant gene signal and calculated as follows: AMF ^{or Fol genes (GiAM or Fef) / plant gene (Actin) = E}_ActinCt−Actin ^/E_{GiAM or Fe f} Ct−GiAM or Fef^{, Ct} is the mean of three technical replicates and E is the mean for all reactions with a particular primer pair for each run (Bodenhausen et al., 2014).

2.5. cDNA synthesis

Total RNA was isolated using TRI-reagent (Sigma-Aldrich Inc., MO, USA) according to the manufacturer’s instructions. RNA concentrations were quantified using a NanoDrop™ 2000 (Thermo Fisher Scientific, Waltham, MA). Total RNA was treated with RQ1 DNase (Promega, USA) according to the manufacturer’s protocols. The miRNAs were reverse-transcribed to cDNAs by MMLV reverse transcriptase (Promega, USA) using stem-loop primers (Supplementary Tables S1 and S2) that were designed according to Varkonyi-Gasic et al. (2007). For the expression analyses of mRNA genes, total RNAs were reverse-transcribed into first-strand cDNA using MMLV reverse transcriptase (Promega, USA). PrimerQuest Tool was used to design the specific primers (Supplementary Table S1).

2.6. Validation of miRNAs and mRNA genes

To evaluate the level of miRNAs expression and mRNAs, qPCRs were carried out on an Agilent Stratagene Mx3005p real-time PCR detection system using the BioEasy SYBR Green Master Mix (BIOER, Hangzhou, China) according to the manufacturer’s instructions. miRNAs expression analyses were performed in a total volume of 20 µl containing 1 µl of cDNA template (1:10 dilution),10 µl of 2×SYBR Green Master Mix, 1 µl of 10 µM miRNA- specific forward primer, 1 µl of 10 µM universal reverse primer, and 7 µl RNase-free water. On the other hand, miRNA-target genes and other genes were performed in a total volume of 20 µl containing (1 µl of diluted cDNA, 10 µl of 2×SYBR Green Master Mix,0.3 µl of each forward and reverse Primer (10 µM). The PCR program was as follows: 95°C for 60 s followed by 35 cycles at 95°C for 5 s and 60°C for 60 s. Then, the melting curve analysis of qPCR product amplicons was carried out to check the amplification of a product as a single peak. As an endogenous reference gene for normalization, U6-specific primer was used for miRNAs and Actin-specific primer for mRNA genes (Supplementary Tables S1 and S2). Reactions were performed in three biological and technical replicates and the relative expression levels were calculated using the 2^−△△Ct method (Schmittgen and Livak, 2008). Heatmap analysis was performed in Heatmapper online server, as described by Babicki et al. (2016).

2.7. SA, JA, ET, ABA and AUX assays

Thirty grams of the tomato roots from 30 dpi samples were used to quantify the following phytohormones; SA, JA, ET, ABA, and AUX. Ten milligrams of freeze-dried roots were ground into a fine powder. The ground samples were washed three times with a mixture containing 80% methanol (v/v) and 2, 6-bis (1, 1-dimethyl ethyl)-4-methylphenol at 5^◦C in darkness. The extract was centrifuged at 12,000 ×g for 20 min and the supernatant was decanted and adjusted to pH 8.5. The residues were extracted three times using the equivalent volume of pure ethyl acetate. The extracts were filtered after being dehydrated over anhydrous sodium sulphate. The filtrated supernatant was lyophilized using Savant Speedvac (Thermo Fisher Scientific) and redissolved in 1 ml methanol. ABA and AUX were quantified according to Furniss (1989). SA was quantified using the method described by Forcat et al. (2008). Moreover, the concentration of ET was quantified according to Iwai et al. (2006). JA content in tomato roots was determined according to the method of Wang et al. (2016).

2.8. Statistical analysis

Data were statistically analyzed by SPSS v23.0 (Chicago, IL, USA). The statistical analysis was performed using one-way analysis of variance (ANOVA) and the significant differences between means were compared using Duncan’s multiple range test at P<0.05. The correlation matrix was computed and visualized in R with the package corrplot.

3. Results

3.1. Mycorrhizal colonization

In Hz cultivar, qPCR quantification of AMF root colonization with GiAM as a specific gene showed that AMF colonization was more abundant at 30- and 14- dpi by 2.5 and 1-fold compared to 7 dpi. Moreover, the level of root colonization increased with increasing Fol-infestation at 30- and 14- dpi by 2 and 4-fold. Also, Fol-infested roots were confirmed by Fef as a specific gene to be abundantly infected by Fol throughout all stages. On the contrary, Fol-infested roots were significantly affected when interacting with AMF-colonization by 4.2 and 1.5-fold at 30- and 14- dpi (Figure 1A). On the other hand, in the CR cultivar, AMF-inoculated roots were abundantly colonized by AMF; however, its colonization did not affect Fol-infestation by 8-fold at 30 dpi. (Figure 1B).

Figure 1
Quantification of AMF and Fol interaction in different cultivars of Hz and CR at 7-, 14- and 30- dpi. Data are mean ± SEM (n = 3 independent trials with six to eight plants per treatment per trial). Each cultivar was analyzed separately. Different letters represent the significant differences (P < 0.05) for 7-, 14-, and 30- dpi followed by small, capital, and capital primed letters based on Duncan’s multiple range test.

3.2. Salicylic acid-integrated genes and miRNAs are expressed in AMF-infested and Fol-infected roots

The up-regulation of the expression level of the SA-integrated genes of the resistant tomato genotype reached a highest of 313-, 133-, and 43-fold change for PR2, LRR1, and I-2 at 30 dpi. Nevertheless, in spite of recording lower expression levels of NPR1, PR1, PR2, CHI3, and LRR1 at 30 dpi in the susceptible tomato genotype, a peak of 258-fold change was recorded at 30 dpi for the I-2 (Figure 2A-F). In the resistant genotype “Heinz”, the expression level of miR482f of AMF+Fol at 30 dpi, did not attain any response compared to the control at 7 dpi but peaked sharply at 14 dpi by 23-fold and decreased at 30 dpi by 3.4-fold. Moreover, in the CR cultivar, miR482f transcript at 30 dpi was up-regulated in AMF+Fol by 2-fold (Figure 3A). In the resistant genotype, miR5300 in AMF+Fol exhibited an intermediate transcriptional level between Fol and AMF in which its transcript level at 7 dpi was up-regulated by 2.6-fold, increased at 14 dpi by 4- fold, and down-regulated at 30 dpi. In contrast, miR5300 transcript level in the susceptible cultivar was down-regulated in Fol-infected and AMF+Fol at 7 dpi. Interestingly, its expression level increased at 30 dpi in Fol and AMF by 5- and 2- fold, respectively with no change in its expression level in AMF+Fol compared to the control (Figure 3B).

Figure 2
Expression level of the selected gene-markers involved in salicylic acid signaling pathway and plant immunity. Each cultivar was analyzed separately. Different letters represent significant difference (P < 0.05) for 7-, 14-, and 30- dpi are followed by small, capital, and capital primed letters based on Duncan’s multiple range test.

Figure 3
Expression level of the selected miRNA-markers controlled in the hormonal pathways. Each cultivar was analyzed separately. Different letters represent significant difference (P < 0.05) for 7-, 14-, and 30- dpi are followed by small, capital, and capital primed letters based on Duncan’s multiple range test.

3.3. miRNA and JA/ET-integrated genes are expressed in AMF-infested and Fol-infected Roots

The expression level of JA/ET-integrated genes in AMF+Fol the susceptible genotype followed different trends. MYB33, PDF1.2, and GRF4 showed no significant differences in the expression level between 7 and 30 dpi. LOX1 and MYC2 showed a noticeable increase from 7 to 30 dpi. However, the expression level of DELLA, EIN2, EIN3, and COI1 decreased over time. Nevertheless, a significant increase in the level of expression was recorded between 7 and 30 dpi by JAZ1 (16- to 0.3- fold) and ERF1 (11.3- to 0.8- fold). On the other hand, a significant increase was recorded by NAC1 (0.4- to 4.0- fold) in the expression level of JA/ET-integrated genes in the AMF+Fol resistant tomato genotype, which decreased for COI1, EIN2, and GRF4. Four genes showed a highly significant decrease from 7 to 30 dpi; MYB33 (5.5- to 0.3- fold); MYC2 (50- to 3- fold); EIN3 (25.6- to 2.3- fold) and ERF1 (78.5- to 1.7- fold). On the other hand, LOX1, JAZ1, NAC1, and PDF1.2 (1.1- to 7-fold; 2 to 6.5-fold; 240- to 3-fold, respectively). Interestingly, DELLA showed a peak of 331- fold at 30 dpi rising from 4- fold at 7 dpi (Figure 4A-L). In the CR cultivar, the expression level of miR159a was up-regulated at 14 and 30 dpi by 2.8- and 2.4-fold, respectively, in AMF+Fol. In contrast, the Hz cultivar showed lower levels of expression at 14 dpi, and baseline expression at 30 dpi was recorded in AMF+Fol (Figure 3C). In the Hz cultivar, miR164 exhibited remarkable up-regulation at 7 and 30 dpi throughout all treatments. On the contrary, in the susceptible cultivar, there was a significant down-regulation at 30 dpi in AMF and AMF+Fol (Figure 3D). The transcriptional level of miR396a in CR and Hz cultivars increased at 14 dpi by 7- and 2-fold, respectively in AMF+Fol. Nevertheless, it peaked up to 14-fold at 30 dpi. Interestingly, in the CR cultivar, its expression level sharply down-regulated at 30 dpi (Figure 3E).

Figure 4
Expression level of the selected of gene-markers involved in jasmonic acid, gibberellic acid and Ethylene signaling pathways. Each cultivar was analyzed separately. Different letters represent significant difference (P < 0.05) for 7-, 14-, and 30- dpi are followed by small, capital, and capital primed letters based on Duncan’s multiple range test.

3.4. miRNA and AUX/ABA-integrated genes are expressed in AMF-infested and Fol-infected roots

In the resistant cultivar, the expression level of miR393 up-regulated at 30 dpi by 3-fold in AMF+Fol. On the contrary, the expression level of miR393 in the susceptible cultivar was down-regulated at 30 dpi for the AMF+Fol (Figure 3F). In the resistant cultivar, the expression level of ARF6 was not significantly affected by the AMF+Fol infection. Also, the expression levels of TIR1 and RD22 were significantly affected by AMF+Fol from 7 to 30 dpi (41- to 1.2- fold; 102- to 17- fold, respectively). The expression level of NCED1 was down-regulated from 25-fold at 7 dpi to 19.5-fold at 30 dpi. The expression level of SPL3 showed no significant differences upon infection with AMF+Fol. In the susceptible genotype, the expression level of NCED1 was up-regulated at 7 and 30 dpi (2.29- to 76- fold, respectively). Nevertheless, TIR1, ARF6, and RD22 were down-regulated from 1.5-, 1.7- and 30- fold at 7 dpi to 0.02-, 0.7- and 9- fold at 30 dpi, respectively (Figure 5).

Figure 5
Expression level of the selected of gene-markers involved in ABA, Auxin synthesis and plant development pathway. Each cultivar was analyzed separately. Different letters represent significant difference (P < 0.05) for 7-, 14-, and 30- dpi are followed by small, capital, and capital primed letters based on Duncan’s multiple range test.

3.5. Major players miRNAs crosstalk to control plant development and senescence

In the resistant cultivar, the expression level of miR156a was significantly up-regulated at 30 dpi by 35.3- fold in AMF+Fol compared to the susceptible cultivar that up-regulated in AMF+Fol by 5- fold (Figure 3G). In the resistant cultivar, the expression level of AP2 was significantly affected by AMF+Fol from 7 to 30 dpi (3.5- to 34- fold). In contrast, the expression level of SPL3 showed no significant differences upon infection with AMF+Fol at 7 and 30 dpi. In the susceptible genotype, the expression level of SPL3 was up-regulated from 7 to 30 dpi (0.03- and 2.3- fold, respectively) (Figure 5E). The expression level of miR172a in the susceptible cultivar exhibited a sharp up-regulation at 7 dpi by 5.6-fold in AMF+Fol. Conversely, in the resistant cultivar, the expression level of miR172a did not exhibit noticeable changes compared to the control through the three time points in AMF+Fol (Figure 3H). In the Hz cultivar, in AMF+Fol, miR319b did not reveal changes compared to the control at 7 dpi. However, its expression level was significantly up-regulated by 15-fold at 30 dpi. On the other hand, in the CR cultivar, the expression level of miR319b was significantly up-regulated at 14 dpi in AMF+Fol by 6-fold compared to the third stage (30 dpi) where it was down-regulated (Figure 3I). In the Hz cultivar, the expression level of TCP4 was significantly up-regulated in AMF+Fol by 3.7- and 8.5- fold at 14 and 30 dpi, respectively. On the other hand, the expression level of TCP4 of the CR cultivar was significantly down-regulated in AMF+Fol at 7 and 14 dpi, but its expression was significantly up-regulated by 6-fold at 30 dpi (Figure 5G).

3.6. miR171 and miR171g as AMF symbiosis regulators in R. irregularis

In the Hz cultivar, the transcript level of miR171 was up-regulated by 6-fold at 7 dpi and decreased by 1.7-fold at 30 dpi in AMF+Fol. On the contrary, in the CR cultivar, the transcript level of miR171 did not exhibit obvious up-regulation throughout all treatments and stages; except in AMF-inoculated roots, its expression was moderately up-regulated by 1.5- fold at 30 dpi (Figure 3J). In Hz cultivar, the transcript level of miR171g showed the opposite expression manner compared to miR171 in which its expression remained stable at 14- and 30- dpi by 3- and 2.6- fold in AMF+Fol, respectively. On the other hand, in CR cultivar, its expression level was significantly down-regulated in AMF+Fol at 14 and 30 dpi (Figure 3K).

3.7. Heatmap analysis

To summarize our gene expression results obtained by qPCR experiment, all infection- related genes and miRNAs and their target genes were visualized as heatmaps. The overall or combined effects of AMF with Fol lead to different expression patterns over the time stage of each treatment. In the resistant genotype, CHI3, DELLA, EIN2, EIN3, ERF1, ARF6, MYC2, RD22, and NCED1 were early induced at 7 dpi in AMF+Fol, whereas gene expression activity remained stable at 14 dpi; except ERF1 and MYC2, they did not exhibit gene expression response. On the other hand, at 30 dpi, the gene expression activities of ERF1, ARF6, JAZ1, LOX1, PR1, PR2, PDF1.2, RD22, and COI1 were highly expressed in the resistant genotype compared to the susceptible genotype (Figure 6A). Moreover, at 7 dpi, miRNAs and their target genes; MYB33, AP2a, NAC1, TIR1, GRF4, and LRR1 were among the top differentially expressed genes. In addition, we can discriminate an alternative pattern including miRNAs-targets miR159a, miR172a, miR194, miR393, miR396, miR319b, and miR482f at 7 dpi. Interestingly, the activity of miRNAs and their target genes decreased at 14 dpi, except AP2a, LRR1, and miR482f. While at 30 dpi, miR156a were activated later, and the rest of the genes including AP2a, NAC1, GRF4, TCP4, and LRR1 remained highly expressed to the end of the treatment (Figure 6B). On the other hand, in the susceptible genotype, most of the miRNAs and their target genes; miR172a/AP2a, miR164/NAC1, miR393/TIR, and miR396a/GRF4 their expression patterns were completely suppressed during the interaction of AMF and Fol at 7 and 30 dpi. Nevertheless, miR156a was highly expressed at 7 dpi, in addition, SPL3, miR159a, NAC1, and TCP4 also highly expressed.

Figure 6
(a) Heatmap of infection-related genes expressed in Hz vs. CR root tomato plants under the AMF- and Fol-infected plants and their interaction (AMF+Fol) at 7-, 14- and 30- dpi. The log-transformed expression values range from − 2 to 2. Red and blue bands represent up and down gene expression levels, respectively. (b) Heatmap of infection-related miRNAs and their target genes differentially expressed in Hz vs. CR root tomato plants under the AMF- and Fol-infected plants and their interaction (AMF+Fol) at 7-, 14- and 30- dpi. The log-transformed expression values range from − 2 to 2. Red and blue bands represent up and down gene expression levels, respectively.

3.8. AMF and Fol alter phytohormones of tomato roots

Fol-infection induced JA, SA, ET, and ABA in both genotypes by 60, 45, 43, and 37% for Hz and by 52, 33, 49, and 35% for CR, respectively. Nevertheless, AMF infestation caused a reduction of 22, 32, 37, and 25% in the SA, JA, ET, and ABA content in the Hz and by 32, 53, 23, and 35% in SA, JA, ET, and ABA content of CR, respectively. Interestingly, Fol-infection caused a 68% reduction in AUX content for Hz and a 70% reduction for CR. However, the AMF infestation managed to restore the AUX content to levels comparable to the control (Figure 7). In general, the concentrations of SA, JA, ABA, AUX, and ET in the roots of the infected tomato plants were significantly reduced in the resistant cultivar compared to the susceptible one.

Figure 7
Hormone analysis of SA, JA, ET, ABA and AUX in Hz (a, b, c, d and e, respectively) vs. CR (f, g, h, i and j, respectively) tomato roots under the AMF- and Fol-infected plants and their interaction (AMF+Fol) at 30 dpi.

3.9. Correlation analysis between the gene expression of miRNAs and mRNA-genes through stages under the interaction between AMF and Fol

In the resistance genotype (Hz), ARF6, PDF1.2a, TIR1, PR1, PR2, NPR1, I-2, NCED1, ERF1, RD22, LOX1, JAZ1, EIN3, MYB33, LRR1, NAC1, AP2a, and SPL3 genes exhibited a significant positive correlation at 7 dpi and 30 dpi. This is in contrast to the second stage (14 dpi), which revealed a weak positive correlation (Figure 8A; Supplementary Figure S1 and S2). However, in the susceptible genotype (CR), these genes showed a significant positive correlation at 7 dpi compared to 14 dpi and 30 dpi (Figure 7B). At 30 dpi, miR482f exhibited a positive correlation with I-2, LRR1, NPR1, PR1, and PR2 in the resistance genotype (Hz). Conversely, in the susceptible genotype (CR), miR482f showed a negative correlation with I-2, LRR1, and NPR1. In contrast, at 30 dpi, miR164 and miR319a were positively correlated with LOX1, TCP4, EIN3, JAZ1, NCED1, ERF1, NAC1, PDF1.2, and SCOI1 in the resistance genotype (Hz). Conversely, in the susceptible genotype (CR), miR164 displayed a negative correlation with miR319a, LOX1, TCP4, NCED1, RD22, NAC1, PDF1.2, SCOI1, and MYC2. Additionally, at 30 dpi, a positive correlation was observed between CHI3, miR159a, and miR393 with JA, SA, ET, and ABA in the resistance genotype (Hz). Interestingly, in the resistant genotype (Hz), the correlation data revealed a positive relationship between miR482f and miR5300, which appeared to be mediated by phytohormones (JA, SA, ET, and ABA). However, in the susceptible genotype (CR), a moderate negative correlation was observed between miR482f and JA, as well as a positive correlation between miR5300 and SA, ET, and ABA.

Figure 8
Correlation analysis illustrates interaction between the expression level of miRNAs and their phytohormones mRNA and JA, SA, ET, ABA, and AUX to represent strength of co-expression under AMF, Fol, and AMF+Fol conditions at 30 dpi in Hz (a) and CR (b) tomato genotypes. The increasing color intensities elucidate a higher Pearson’s correlation coefficients.

4. Discussion

AMF has the potential to alleviate the pathogenicity of Fol, leading to a cascade of signaling events involving SA-related genes such as NPR1, PR1, PR2, and CHI3 (Dreischhoff et al., 2020; Yu et al., 2022). The presence of accumulated SA in both resistant and susceptible cultivars following AMF inoculation at 30 dpi indicates that the induction of SA was unaffected by prolonged inoculation. Notably, even though miRNA families miR482f and miR5300 were previously identified as negative regulators of LRR expression (Ouyang et al., 2014; Téllez Valerio et al., 2022), their expression levels were higher in the CR cultivar compared to the Hz cultivar during AMF+Fol treatment (at 14 and 30 dpi). This could be attributed to the role of miR482f and miR5300 in inhibiting AMF colonization. Consequently, a subsequent shutdown of SA signaling might be necessary to facilitate mycorrhizal colonization once again. Intriguingly, the increase in SA-responsive genes seemed to function as a control mechanism for the elevation of AMF levels in tomato roots. The dynamic interaction between COI and JAZ1 serves a fascinating dual purpose in the plant response. It not only supports the successful colonization of AMF but also enhances the plant defense mechanisms against Fusarium infection. This interplay between JAZ1 and COI1 acts as a safeguard, effectively preventing plant mortality by boosting the plant’s capacity for JA synthesis. Moreover, our study reveals the pivotal role of NPR1 in facilitating the crosstalk between the SA and JA signaling pathways. The expression of NPR1 orchestrates the regulation of key JA-related genes, such as JAZ1 and MYC2. Particularly intriguing is that, despite AMF being an autotrophic fungus, the expression level of NPR1 did not suppress JAZ1 throughout the three stages we examined. This suggests that the role of NPR1 extends beyond simple repression and likely involves the induction of immunity, which arises from the complex and often antagonistic interactions between autotrophic and necrotrophic fungi. During our study, we made a noteworthy observation regarding the hormonal balance in tomato plants during the later stages of Fol-infection. This observation revealed that the hormonal balance played a pivotal role in triggering an immune response against Fol. It is important to highlight that the expression of JA-related genes exhibited some variations during the early stages of infection. However, by the time we reached 30 days post-inoculation (dpi) and compared the gene expression to the control plants in the context of AMF inoculation, we noticed a significant change. This discrepancy in gene expression was intriguing, but even more compelling is that it was mitigated, ultimately restoring a normal gene expression state for both JA and SA pathways at 30 dpi (Wasternack, 2007). The antagonism between AMF and Fol was evident in the intricate interaction between JA and SA, finely tuning their balance to enhance resistance against invading organisms (Gimenez-Ibanez and Solano, 2013). The up-regulation of the JA-biosynthesis gene LOX1 in the Hz cultivar suggested that AMF+Fol activation induced JA expression at 14- and 30-dpi in the infected tomato roots. Consequently, JA played a significant role in the plant response to Fusarium infection, with its expression elevated in the presence of AMF. Consistent with our result, Garrido et al. (2010) demonstrated the substantial role of LOX1 in establishing G. mosseae-colonized roots. Furthermore, Zhang et al. (2018) reported an increased expression level of LOX1, leading to enhanced resistance to cotton Verticillium wilt. In this study, we propose that miR159a and JAZ1 may play a crucial role in controlling Fol-infection by down-regulating MYB33 in the presence of AMF+Fol at 30 dpi, thereby promoting the JA and SA signaling pathway. Previous research by Pavitra et al. (2017) has suggested that the expression level of miR159 decreases in response to F. oxysporum infection in banana roots. Interestingly, the CR cultivar exhibits heightened levels of miR159a expression during the later stages of infection when compared to the Hz cultivar. This distinction in expression patterns could be indicative of the complex and imbalanced defense response triggered by Fol-infection. In our study, DELLA may have a crucial role in neutralizing the expression of miR159a and its target gene MYB33, as indicated by previous research (Waheed and Zeng, 2020). This, in turn, can influence the delicate balance of the JA and SA signaling pathways (Liao et al., 2018; Su et al., 2022). Furthermore, our investigation revealed that the expression levels of ET-responsive genes, including EIN2, EIN3, ERF1, and PDF1.2, exhibited a negative impact on AMF-colonization. This observation agrees with the findings of Riedel et al (2008), who reported the involvement of ET-signaling in the interaction between plants and AMF. The antagonistic interplay between AMF and ET appears to recalibrate the capacity of ET-biosynthesis to regulate tomato immunity. Of particular interest, ERF1, a key gene in the ET pathway, exhibited a notable stability in gene expression during the late stage of infestation involving AMF and Fol. This stability could be attributed to the fact that ET is typically associated with accelerated plant senescence. The potentially detrimental effects of senescence induced by ET were seemingly counteracted by the presence of Fol-infestation. This pattern in gene expression is consistent with the results reported by Casarrubias-Castillo et al. (2020), who documented a down-regulation of ERF1 expression levels at 32- and 45- dpi, followed by an up-regulation at 50 dpi in tomato roots subjected to AMF inoculation. These findings collectively shed light on the intricate dynamics of hormone signaling pathways during plant-pathogen interactions, emphasizing the role of ET in Influencing plant responses to both AMF and pathogenic fungi. At 30 dpi, the presence of AMF significantly improved the adverse impact of Fol by elevating AUX content to match the expression levels observed in the control group. Additionally, the AUX content exhibited a striking resemblance to the control levels in the case of AMF at 30 dpi, suggesting that AUX may not be crucial for post-infection development, contrary to its essential role in normal AMF infection. It is worth mentioning that the expression level of miR393 was equivalent to that of the control at 7 dpi. Consequently, the down-regulation of miR393 led to an increase in the transcriptional level of TIR1, resulting in reduced auxin sensitivity. Conversely, down-regulation of TIR1 led to auxin resistance. Consistent with our result, Chen et al. (2011) indicated that miR393 functions as a negative regulator of auxin perception, thus confirming our results. The inoculation of AMF during Fol-infection provided further evidence for the correlation in expression levels between the two genes, with NAC1 exerting significant influence over the expression level of TIR1. This modulation resulted in an enhanced tomato defense response to Fol-infection. In support of our findings, Lin et al. (2021) documented that the expression level of TIR1 triggered a robust defense response against various biotrophic and necrotrophic pathogens. This strengthens the validity and relevance of our study to the scientific community. ARF6 played a role in bolstering the defense response in the presence of AMF, allowing for precise adjustments of AUX concentration during the later stages, ultimately returning it to baseline levels. We propose that the elevated AUX levels observed in the CR cultivar, induced by Fusarium infection, could potentially stimulate the host plant to reach its maximum capacity for AUX production. This heightened AUX level may contribute significantly to enhancing virulence and the survival rate, as suggested by Gilroy and Breen (2022). AP2 was up-regulated due to the role of AMF in inducing root development, in contrast to Fol-infected roots that displayed clear down-regulation during the 7- and 14- dpi. Curiously, Kaushal et al. (2021) documented that the expression levels of transcription factor (TF) families, including AP2, were down-regulated in response to Fol-infection in banana plants (Kaushal et al., 2021). Furthermore, the overexpression of AP2 at the final stage (30 dpi) could be linked to distinct responses in different tomato cultivars. Consequently, we can infer that the interplay between AP2 and miR156a plays a pivotal role in enhancing plant immunity against F. oxysporum in tomato roots, providing a noteworthy contrast to the interactions involving miR172/SPL3. As a result, the heightened expression of AP2 and ERF1 likely contributes to delaying aging by reducing SPL3 expression, thus mitigating the response to age acceleration during infection in the study’s later stages. Notably, a study conducted by Ye et al. (2020) sheds light on the gradual decrease in root development as plants age, with AP2 playing a role in this process, in addition to its involvement in AUX induction. Additionally, they proposed that SPL acts as a repressor of root development by inhibiting wound-induced AUX biosynthesis. These insights collectively reinforce the coherence and significance of our findings in the context of this study. The observed down-regulation of SPL3 expression by DELLA at 7 dpi presents an intriguing contrast to the patterns seen at 14 dpi and 30 dpi. This variation can be explained by the intrinsic role of SPL3 in transitional phases within plant development. Our speculation regarding the normalization of SPL3 expression by DELLA at 30 dpi presents a promising opportunity for further investigation into regulatory mechanisms., as suggested by a previous study by Waheed and Zeng (2020). This insight suggests a dynamic interplay between DELLA and SPL3, which could have significant implications for plant development and responses to environmental cues. In this study, ABA emerged as a pivotal player, particularly in the context of its involvement with the ABA-biosynthesis gene, NCED1. Intriguingly, we observed distinct patterns in the expression of NCED1 when examining its presence in both AMF and Fol-infected tomato roots. This divergence in expression levels is a notable departure from the findings of Martín-Rodríguez et al. (2016), who reported no noticeable differences in expression between AMF-infested and non-AMF-infested roots. This intriguing variation in results might be ascribed to the nuanced function of NCED1 in orchestrating resistance against Fol. Furthermore, as we delved deeper into the study, we uncovered a fascinating phenomenon: the overexpression of NCED1 led to a substantial accumulation of ABA, thereby intensifying the susceptibility of tomato plants to AMF infection. Notably, our observations revealed a striking 5-fold up-regulation of NCED1 during the later stages of the experiment. This finding underscores the dynamic nature of ABA involvement in the intricate interplay of plant-microbe interactions. In this study, the infection rate of AMF had a negative impact on the transcript level of miR396a, which subsequently led to an increase in the expression level of its target gene, GRF4. Consequently, AMF played a crucial role in maintaining the gene expression of GRF4 under the influence of AMF+Fol at all stages. Additionally, the balanced gene expression of both miR396a and GRF4 at 14- and 30- dpi points to a reciprocal feedback loop between them that helps stabilize their transcript abundance (Hewezi, 2020). This investigation yields a series of intriguing observations that deepen our understanding of the complex interplay between arbuscular mycorrhizal fungi (AMF), Fusarium oxysporum (Fol) infection, and key regulatory elements in tomato roots. Notably, at the crucial 30 days post-inoculation (dpi) time point, we uncovered a remarkable counteraction by AMF against the detrimental effects induced by Fol infection. This counteraction mechanism was associated with a significant increase in the concentration of AUX in tomato roots, effectively restoring it to normal expression levels. This remarkable discovery underscores the pivotal role of AUX in the context of AMF/Fol interactions. Furthermore, our study unveiled a fascinating down-regulation of miR393, a microRNA known for its control over AUX translocation by targeting the TIR1 gene. This observation highlights the central importance of TIR1 in modulating AUX content, offering a valuable piece of the puzzle in understanding how AUX is intricately regulated in response to fungal infection. In essence, AUX appears to play a multifaceted role in suppressing senescence and fine-tuning the latter stages of Fol infection in the presence of AMF. Adding depth to our understanding, we also explored the involvement of TCP4, a transcription factor known to activate AUX biosynthetic genes (Challa et al., 2016). This connection further elucidates the complex regulatory network at play, where TCP4’s role in AUX biosynthesis could be a key factor in mitigating the effects of Fol infection. Additionally, our findings shed light on the cooperative actions of miR164, TCP4, and miR319b in mitigating the senescence process induced by AMF infection. This intricate interplay between microRNAs and transcription factors underscores the nuanced regulatory mechanisms that plants employ to respond to and cope with symbiotic interactions. Furthermore, in the correlation study, several genes associated with defense responses in the resistance genotype (Hz), including ARF6, PDF1.2a, TIR1, PR1, PR2, NPR1, I-2, NCED1, ERF1, RD22, LOX1, JAZ1, EIN3, MYB33, LRR1, NAC1, AP2a, and SPL3, exhibited significant positive correlations at both early (7 dpi) and late (30 dpi) stages of infection. This suggests a consistent and robust activation of these defense-related genes in response to both AMF and Fol over the course of the infection. However, at the intermediate stage (14 dpi), these correlations weakened, indicating potential regulatory shifts during this period. Conversely, in the susceptible genotype (CR), the positive correlations among these genes were more prominent at the early stage (7 dpi) and declined at later time points (14 dpi and 30 dpi). This contrasting pattern suggests that the susceptible genotype may activate its defense mechanisms earlier during infection but fails to sustain this response over time, potentially contributing to its susceptibility. At 30 dpi, miR482f exhibited interesting correlations with key defense- related genes in the resistance genotype (Hz), such as I-2, LRR1, NPR1, PR1, and PR2. This positive correlation suggests that miR482f may play a role in fine-tuning the expression of these genes to optimize the defense response. In contrast, in the susceptible genotype (CR), miR482f displayed a negative correlation with some of the same genes (I-2, LRR1, and NPR1), indicating a different regulatory relationship that may contribute to the susceptibility of this genotype. Additionally, miR164 and miR319a showed positive correlations with several defense-related genes in the resistance genotype (Hz) at 30 dpi, suggesting their involvement in coordinating defense responses. In contrast, the susceptible genotype (CR) exhibited negative correlations involving miR164 and miR319a, indicating potential dysregulation of these microRNAs in the defense response. Furthermore, the correlation analysis unveiled compelling interactions between microRNAs (miR482f and miR5300) and phytohormones (JA, SA, ET, and ABA) in the resistant genotype (Hz). This suggests a complex crosstalk between microRNA regulation and hormonal signaling, potentially fine-tuning the defense response. In the susceptible genotype (CR), different correlation patterns suggest distinct hormonal regulation mechanisms. These findings highlight the genotype-specific and dynamic nature of molecular responses to AMF and Fol infections. The interplay between microRNA regulation, gene expression, and phytohormone signaling underscores the complexity of the defense mechanisms involved. Understanding these intricate interactions is crucial for unraveling the molecular basis of resistance and susceptibility in tomato genotypes and may have implications for plant breeding and disease management strategies. Lastly, our study corroborates the consistent regulation of AMF symbiosis by miR171 and miR171g across various developmental stages of tomato roots under Fol infection, as previously reported by Zhou et al. (2020). This reinforces the notion that these microRNAs play pivotal roles in maintaining the delicate balance of AMF interactions throughout different stages of plant development (Figure 9; Supplementary Figures S3 and S4).

Figure 9
Schematic representation of root defense genes activation in response to AMF and Fol-infection at 30 dpi.

5. Conclusions

The results from our study indicated enhancements in plant immune system-related genes responsible for the defense mechanism, evident in both the resistant (Hz) and susceptible (CR) tomato cultivars. However, the immune response observed in the resistant cultivar, Hz, surpassed that in the susceptible cultivar, CR. Furthermore, our findings strongly suggest that the presence of AMF facilitates crosstalk between various phytohormone-related genes and miRNA signaling pathways, effectively governing the delicate balance between plant defense and Fol-infection. In this context, AMF appears to modulate the expression of SA and JA-dependent defense genes in Fol-infected tomato roots, leading to the establishment of a compatible and defensive mechanism. This nuanced interaction between AMF and the plant’s immune response contributes to a more comprehensive understanding of how plants defend themselves against pathogenic invaders.

Supplementary Material

Supplementary material accompanies this paper.

Supplementary Figure S1.

Correlation analysis illustrates the interaction between the expression level of miRNAs and mRNA and JA, SA, ET, ABA, and AUX to represent the strength of co-expression under AMF, Fol, and AMF+Fol conditions at 7 dpi in Hz (A) and CR (B) tomato genotypes. The increasing color intensities elucidate a higher Pearson’s correlation coefficient.

Supplementary Figure S2.

Correlation analysis illustrates the interaction between the expression level of miRNAs and mRNA and JA, SA, ET, ABA, and AUX to represent the strength of co-expression under AMF, Fol, and AMF+Fol conditions at 14 dpi in Hz (A) and CR (B) tomato genotypes. The increasing color intensities elucidate a higher Pearson’s correlation coefficient.

Supplementary Figure S3.

Schematic representation of root defense genes activation in response to AMF and Fol-infection at 7 dpi.

Supplementary Figure S4.

Schematic representation of root defense genes activation in response to AMF and Fol-infection at 14 dpi.

Supplementary Table S1.

Names, sequences, Accession numbers and sources for the primers used for mRNA detection.

Supplementary Table S2.

Names, sequences, Accession numbers, and sources for the primers used for miRNA detection.

This material is available as part of the online article from https://doi.org/10.1590/1519-6984.280450

Acknowledgements

We are grateful to Dr. Dina S.S. Ibrahim, Nematology and Biotechnology at Plant Pathology Institute (PPI), Agricultural Research Center (ARC) for technical assistance. This work was funded by the Young Researcher Grant, Science and Technology Development Fund (STDF), Academy of Scientific Research and Technology (ASRT), Ministry for Scientific Research, Egypt [33497].

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Publication Dates

• Publication in this collection
  04 Apr 2025
• Date of issue
  2024

History

• Received
  14 Nov 2023
• Accepted
  08 Jan 2024