Exploring the Antifungal Potential of Arginine in Controlling Chestnut Rot Disease

Exploring the Antifungal Potential of Arginine in Controlling Chestnut Rot Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Exploring the Antifungal Potential of Arginine in Controlling Chestnut Rot Disease Shuang Zhou, Dong-Hui Yan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6207660/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Arginine (Arg) can induce plant resistance. However, few know about its direct effect on fungal pathogens.. This study found that arginine could inhibit the growth of the pathogenic fungus Diaporthe nobilis , a major causal agent of rot disease on edible nuts from Castanea trees, with an inhibition rate of at most 66.9%. After chestnuts were treated with Arg, the disease index of rot caused by D. nobilis decreased significantly, dropping from 91.67 to 20.83 at most. Transcriptome analysis showed that at least 225 differentially expressed genes (DEGs) in D. nobilis were inhibited by arginine. Among them, the expression of genes related to pathogenicity, such as transport proteins, secondary metabolites, degrading enzymes, and organic metabolism, was downregulated. These results provide novel insights into the potential antifungal mechanism of arginine and suggest that arginine could be a potential safe alternative for controlling rot diseases of postharvest foods. Biological sciences/Biological techniques Biological sciences/Plant sciences Scientific community and society/Agriculture Arg Diaporthe nobilis Postharvest storage Chestnuts Transcriptomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Chestnuts have historically served as a staple food in various cultures. In modern agricultural practices, chestnuts hold significant importance as a valuable nutritional source in both daily life and research. From a compositional perspective, chestnuts are abundant in starch, protein, fiber, essential lipids and some vitamins, minerals. [ 1 , 2 ] 。However, chestnut rot diseases pose a severe threat to the economic benefits and valuable food of chestnuts and outbreak typically peaks during the postharvest storage period. Although a diverse range of pathogens in chestnut fruit rots were identified such as Diaporthe , Alternaria , Botryosphearia , and Colletotrichum genera, the Diaporthe fungi always takes dominant abundance among these genera [ 3 ] . Furthermore, Diaporthe species are widely distributed and serve as fungal pathogens of many plants and even mammals besides being non-pathogenic endophytes (biotrophic fungi), saprobes [ 4 , 5 ] . Plant pathogenic Diaporthe spp. can cause wood cankers, wilts, dieback, and fruit rot in various economically valuable plant hosts, particularly recorded those affecting economically important crops such as soybeans, sunflowers, grapes, citrus, chestnuts, and ornamental trees [ 6 ] .Rot diseases caused by Diaporthe species are prevalent and highly destructive in postharvest fruits including chestnut fruit [ 7 – 11 ] . D. nobilis has recently been identified as major causal pathogen for fruit rots of Castanea mollissima var. Yanshanzaofen, which is the most economically profitable chestnut variety in the Yanshan region of northern China and recorded as a very susceptible variety to rot diseases, with a cultivation area exceeding 1 million mu and an export volume accounting for more than 50% of the total chestnut exports [ 12 ] . Consuming food containing pesticide residues can increase the risk of developing cancer, cardiovascular diseases, and respiratory diseases. [ 13 , 14 ] .Currently, chemical pesticides are commonly used to control Diaporthe -induced diseases [ 15 , 16 ] , However, the excessive use of chemical pesticides has led to serious issues such as food contamination, environmental pollution, and phytotoxicity [ 17 ] . Consequently, as consumer concern about food safety and environmental issues continues to rise, eco-friendly postharvest preservation technologies have developed rapidly [ 18 , 19 ] . Arginine is predominantly present as a structural amino acid in proteins, and it plays an essential role in protein synthesis and degradation. It is widely distributed in most prokaryotic and eukaryotic organisms [ 20 ] . In plants, arginine is involved in growth, development, and stress tolerance through its conversion to putrescine via ornithine, which is critical for root elongation and development. A reduction in putrescine inhibits root elongation, whereas exogenous putrescine (0.01–1 mM) promotes root growth and system development [ 21 – 25 ] . Arginine is also hydrolyzed by arginase to produce urea, which is integrated into the nitrogen recycling pathway, supporting plant development and responses to biotic and abiotic stresses [ 26 ] .In fungi, arginine supplementation enhances the production of perylenequinone in the endophytic fungus Beauveria bassiana by upregulating glycolysis-related genes and activating the NO-cGMP-PKG signaling pathway [ 27 ] . Similarly, arginine treatment in postharvest jujube fruit induces resistance to Alternaria alternata by balancing ROS metabolism and enhancing pathogenesis-related protein activity [ 28 ] . Additionally, arginine regulates microcycle conidiation in Metarhizium acridum by modulating NO levels, with disruption of MaAGA leading to reduced NO and altered sporulation patterns [ 29 ] . Chestnuts are rich in various nutrients, including carbohydrates, proteins, vitamins, potassium, magnesium, iron, dietary fiber, and a diverse range of amino acids [ 30 ] ‌, However, the potential impact of amino acids metabolized by chestnuts on nut rot disease remains largely unexplored. This study evaluates the inhibitory effect of exogenous arginine (Arg) on chestnut rot disease. It also investigates the impact of exogenous Arg on the growth of the pathogenic fungus D.nobilis and further explores the antifungal mechanisms of Arg through transcriptomic analysis. The objective of this research is to thoroughly analyze the direct inhibitory effects of Arg on Diaporthe and its potential pathways, providing theoretical support for the use of Arg as a possible therapeutic strategy to inhibit the growth of this pathogen and its pathogenic process. 2. Methods 2.1. Fruit, strains, and chemicals The chestnut variety used in this study is Yanshan Zaofeng 3113, harvested from Tangxian County in Tangshan City, Hebei Province, which is the core distribution area of Yanshan Zaofeng. Healthy chestnuts were stored in a 4°C refrigerator for preservation. The D. nobilis strain, which was isolated from rotting chestnuts, has been experimentally confirmed for its pathogenicity. It was cultured on PDA medium and used for subsequent experiments. Arginine (purity: 99%) was purchased from Beijing Zhongxing Weiye Biotechnology Co., Ltd. 2.2. Arg inhibits chestnut rot disease The chestnuts were first washed and soaked in 2% sodium hypochlorite and sterile water for 3 minutes, then soaked in 100 mL of sterilized arginine (Arg) solution for 24 hours. The concentrations of the Arg solution were 2.5 mM, 5.0 mM, 10 mM, 20 mM, and 30 mM, with sterile water used as a control group, which was also soaked for 24 hours. Using a 5 mm sterile punch, holes were made in the chestnut shells, ensuring that the inner seed coat detached without damaging the seed. Sterile tweezers were used to transfer D.nobilis agar plugs, with the mycelium facing the seed, into the holes for inoculation. The fruits were then placed into sterile 150 mm Petri dishes, sealed with cling film, and stored in a 25°C constant temperature incubator. After 15 days of dark incubation, the chestnuts were opened, and the disease condition of each group was examined. There were 24 chestnuts in each treatment group. All the required tools were sterilized in an autoclave at 121°C for 20 minutes. All operations were performed in a laminar flow hood. The disease severity of chestnut rot (disease grade) was classified based on the observed diseased area on the maximum longitudinal section of the chestnut at the inoculation site, using a 5-level scale: Level 0: The seed is healthy with no disease;Level 1: Disease at the inoculation site, with minimal spread; the lesion diameter ≤ 5 mm༛Level 2: Lesion has spread, and the diseased area is ≤ 25%༛Level 3: Lesion has spread, and the diseased area is > 25% but ≤ 50%༛Level 4: Lesion has spread, and the diseased area is > 50%. The disease index is calculated as: $$\:\text{D}\text{i}\text{s}\text{e}\text{a}\text{s}\text{e}\:\text{I}\text{n}\text{d}\text{e}\text{x}=\frac{{\Sigma\:}(\text{D}\text{i}\text{s}\text{e}\text{a}\text{s}\text{e}\:\text{G}\text{r}\text{a}\text{d}\text{e}\times\:\text{N}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{F}\text{r}\text{u}\text{i}\text{t}\text{s})}{\text{T}\text{o}\text{t}\text{a}\text{l}\:\text{N}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{F}\text{r}\text{u}\text{i}\text{t}\text{s}\times\:\text{H}\text{i}\text{g}\text{h}\text{e}\text{s}\text{t}\:\text{G}\text{r}\text{a}\text{d}\text{e}\:\text{V}\text{a}\text{l}\text{u}\text{e}}\times\:100$$ 2.3. Measurement of the mycelial growth inhibition rate of D. nobilis The Potato Dextrose Agar (PDA) medium was autoclaved at 121°C for 20 minutes, then cooled to 60°C. Sterile Arginine aqueous solution was added to achieve final concentrations of 2.5 mM, 5 mM, 10 mM, 20 mM, and 30 mM. An equal volume of sterile water was used as a control sample. A 5 mm mycelial disc of D. nobilis (the disc was obtained by punching from a PDA culture after 7 days of incubation) was cultured on the PDA medium containing Arg. The colony diameter was measured daily using a ruler. For each treatment group, 5 independent samples were measured, and each sample was measured 3 times, with the average value taken. The antifungal activity was determined by radial mycelial growth bioassay, and the inhibition rate was calculated as follows: $$\:\text{I}\text{n}\text{h}\text{i}\text{b}\text{i}\text{t}\text{i}\text{o}\text{n}\:\text{r}\text{a}\text{t}\text{e}=\frac{C-T}{C-5}\times\:100\%$$ C = the colony diameter of D. nobilis on the control plate; T = the colony diameter of D. nobilis on the treatment plate; 5 = the initial size of the D. nobilis mycelial block 2.4. Transcriptome analysis of D.nobilis treated with Arg 2.4.1. Transcriptome sequencing and cDNA library construction To investigate the effects of different Arg concentrations on D.nobilis , transcriptome analysis was performed on three groups of samples: the untreated control group (CK), the low concentration Arg treatment group (2.5 mM), and the high concentration Arg treatment group (30 mM). These three groups were selected based on preliminary experimental results showing significant differences in the inhibitory or promotional effects of low and high concentrations of Arg on chestnut disease severity and incidence. After filtering the data, the base composition and quality distribution were analyzed to visualize the data quality. Prepare PDA media with 2.5 mM and 30 mM Arg concentrations, and set up sterile water as the control. Sterile glass paper is placed on the surface of the medium, and 5 mm mycelial discs of D. nobilis are inoculated using a sterile puncher, followed by dark incubation at 25°C for 7 days. For each Arg concentration, mycelia from 5 petri dishes are pooled into one sample, with 3 repetitions. Mycelia from each treatment group are collected for RNA extraction, with normally growing D. nobilis used as the control.RNA extraction, quality control, PCR amplification, and sequencing were performed by Kangsheng Xuanyuan Biotechnology (Wuhan) Co., Ltd. 2.4.2. Transcriptome data processing The sequencing data underwent quality control by removing reads containing adapters and low-quality reads, including those with Ns or those with more than 50% of bases having a quality score (Q) ≤ 10 [ 31 ] . After obtaining high-quality sequencing data, sequence assembly and library construction were performed using Trinity [ 32 ] . To ensure the quality of the sequencing library, randomization tests, fragment length distribution, and saturation tests were conducted [ 33 , 34 ] .DIAMOND [ 35 ] software was used to align Unigene sequences with databases such as NR [ 36 ] 、Swiss-Prot [ 37 ] 、COG [ 38 ] 、KOG [ 39 ] 、eggNOG4.5 [ 40 ] 、KEGG [ 41 ] .KOBAS [ 42 ] was utilized to obtain KEGG Orthology results for Unigene in KEGG. InterProScan [ 43 ] integrated databases to analyze the Gene Ontology (GO) [ 44 ] annotations of the newly identified genes. After predicting the amino acid sequences of Unigene, HMMER [ 45 ] was used to align them with the Pfam [ 46 ] database to obtain annotation information for Unigene. 2.4.3. Differentially expressed genes (DEGs) analysis he sequencing reads were aligned to the Unigene database using Bowtie [ 47 ] , and expression levels were estimated using RSEM [ 48 ] based on the alignment results. The expression abundance of corresponding Unigenes was represented by FPKM values. Differential expression analysis was performed using a software tool based on gene counts across samples. or groups with biological replicates, differential analysis was conducted using the DESeq2 [ 49 ] software. In the differential expression gene detection process, a |Fold Change| ≥ 1 and FDR < 0.01 were used as the screening criteria. Differentially expressed genes were then subjected to functional annotation and gene count statistics using relevant databases [ 44 , 50 – 52 ] . 2.5. Real-time quantitative reverse transcription PCR (qRT-PCR) detection and data analysis Transcribe the RNA of the samples into cDNA. The mRNA expression of the target gene is detected by real-time PCR. cDNA is synthesized using the TRUEscript RT MasterMix kit (Aibosen, Beijing, China). The primers for the target gene are designed using Primer Premier 6, with actin selected as the internal reference gene. Then, 2xSybr Green qPCR Mix is used for qRT-PCR with the CFX96 real-time PCR detection system (Bio-Rad, USA). The qRT-PCR reaction mixture (total volume 25 µL) contains 12.5 µL of 2xSybr Green qPCR Mix, 0.5 µL of each primer (1 µM), 1 µL of cDNA, and 10.5 µL of ddH2O. The qRT-PCR reaction conditions are 95°C for 120 s; 95°C for 15 s, 60°C for 30 s, for 40 cycles. Gene expression is calculated using the 2 −ΔΔCt method. All qRT-PCR reactions are performed in triplicate. The primers are listed in Supplementary Table 1 (Table S1 ). Differentially expressed genes were analyzed for Gene Ontology (GO) enrichment using the hypergeometric test method in ClusterProfiler, focusing on biological processes, molecular functions, and cellular components. Based on the annotation results of KEGG for the differentially expressed genes from public databases [ 53 ] , the KEGG pathways were classified according to pathway types in KEGG. RT-qPCR data analysis was performed using the ANOVA function in GraphPad Prism 8.0 for physiological data analysis. 3. Results 3.1. The mycelial growth of D. nobilis is inhibited by Arg The Yanshan Zaofeng variety is rich in amino acids, including glutamic acid, aspartic acid, arginine, lysine, leucine, etc. [ 54 ] 。In addition, it has been reported that the naturally occurring non - protein amino acid γ - aminobutyric acid can effectively inhibit the growth of Alternaria alternata [ 55 ] 。Solutions of alanine, glycine, glutamic acid, aspartic acid, lysine, arginine, leucine, valine, and γ - aminobutyric acid with a concentration of 30 mM were respectively added to the culture medium to cultivate D. nobilis . The results showed that alanine had no effect on the growth of D. nobilis . Glycine, glutamic acid, aspartic acid, lysine, and arginine inhibited the growth of D. nobilis , with arginine showing the most significant inhibitory effect. On the sixth day, the average diameter of the fungal discs in the CK group grew to 80.04 mm, while the diameter of the fungal discs of D. nobilis in the Arg group was only 28.84 mm, which was significantly lower than that of the CK group (Fig. 1 A). Leucine, valine, and γ - aminobutyric acid promoted the growth of D. nobilis . On the fourth day, the diameters of the fungal discs in the leucine group, valine group, and γ - aminobutyric acid group were 51.73 mm, 55.16 mm, and 55.78 mm respectively, all of which were significantly higher than 50.12 mm of the CK group (Fig. 1 B). Based on these results, we will select arginine with the best inhibitory effect for subsequent research. Exogenous Arg affects the growth of D. nobilis . Treatment with different concentrations of Arg shows that the inhibitory effect on D. nobilis colony growth becomes more pronounced as the concentration increases, with noticeable inhibition at 2.5 mM, 5.0 mM, 10 mM, 20 mM, and 30 mM (Figs. 2 A-F). Over a 6-day period, higher concentrations of Arg lead to stronger inhibition of D. nobilis colony growth. At 2.5 mM, the mycelial diameter increased by 58.93 mm, while at 30 mM, it only increased by 22.56 mm (Fig. 2 G). In terms of growth rate, the colony growth rate was 13.23 mm/day at 2.5 mM, while at 30 mM, the growth rate was only 4.87 mm/day (Fig. 2 H). Compared to the CK growth(0 mM),the inhibitory effect of 30 mM Arg on colony growth reached 66.9%, while the inhibition at 2.5 mM was 9.65%, with the former being 6.9 times greater than the latter (Fig. 2 I). At high concentrations of Arg, not only is D. nobilis growth inhibited, but the colony color also deepens, indicating significant impacts on its metabolic processes (Fig. 2 F). 3.2. The ability of Arg to control chestnut rot disease According to the disease grading criteria in section 2.4 , the severity of chestnut fruit disease is classified into five levels: grade 0 (Figs. 3 A, B), grade 1 (Figs. 3 C, D), grade 2 (Figs. 3 E, F), grade 3 (Figs. 3 G, H), and grade 4 (Figs. 3 I, J). Grade 0 indicates completely asymptomatic and is considered healthy, while grade 4 represents severe decay. In the CK group, the incidence of disease was 100%, while it decreased to 50% at 2.5 mM Arg, 33.3% at both 5.0 mM and 10 mM, 16.7% at 20 mM, however returned to 100% at 30 mM. At lower Arg concentrations (2.5 mM, 5.0 mM, and 10 mM), the severity of chestnut rot was significantly reduced, primarily showing grade 0 or 1 symptoms, indicating effective disease suppression. As the Arg concentration increased, disease severity gradually declined, suggesting a dose-dependent inhibitory effect of Arg on the nut rot development. However, at 30 mM, the disease severity increased to grade 3 or 4, with larger lesions and more extensive decay, indicating that excessive Arg may instead promote disease progression (Fig. 3 K). In terms of disease severity index (Fig. 3 L), the CK group exhibited the highest index at 91.67, indicating the most severe infection in untreated chestnuts. As the Arg concentration increased, the disease index gradually decreased to 39.58, 20.83, and 22.92 for the 2.5 mM, 5.0 mM, and 10 mM treatment groups, respectively, suggesting that low concentrations of Arg effectively suppressed or mitigated the occurrence of decay. When the Arg concentration reached 20 mM, the disease index further dropped to 10.42, demonstrating a strong inhibitory effect of Arg at this concentration. However, when the Arg concentration reached 30 mM, the disease index rebounded to 89.58, approaching the level of the control group, indicating that an excessively high concentration of Arg had a negative impact on chestnuts and instead promoted disease development. This suggests that a moderate concentration of Arg can effectively mitigate chestnut decay, reducing both the incidence and severity of the disease, whereas an excessively high concentration may exacerbate the infection. 3.3. Mechanism of Arg Inhibition on the Growth and Development of D. nobilis 3.3.1. Differential Expression Gene (DEG) data analysis To understand the effects of different Arg concentrations on D. nobilis , transcriptome analysis was performed on three sample groups. As shown in Table S2, the sequencing data across all samples were relatively balanced, ranging from 9.27 Gb to 10.58 Gb, indicating sufficient data volume. The GC content of each sample was approximately 55%, suggesting stable nucleotide composition without AT or GC bias, and overall high sequencing quality. The Q30 scores were also high, ensuring the reliability of subsequent bioinformatics analyses. Correlation heatmap analysis (Figure S1 ) showed strong correlations among the samples, demonstrating high reproducibility across the three sample groups. Using | log2(FoldChange) | > 1 and FDR < 0.05, the gene expression differences among the three groups were compared. As shown in Table S3 and Fig. 3 , in the 2.5 mM treatment group, a total of 1112 differentially expressed genes (DEGs) were identified (Fig. 4 A), with 573 genes upregulated (Fig. 4 B) and 539 genes downregulated (Fig. 4 C). In the 30 mM treatment group, 3296 DEGs were found (Fig. 4 A), with 1851 genes upregulated (Fig. 4 B) and 1445 genes downregulated (Fig. 4 C). When comparing the 2.5 mM and 30 mM treatment groups, 3370 DEGs were identified (Fig. 4 A), with 1934 genes upregulated (Fig. 4 B) and 1436 genes downregulated (Fig. 4 C). A comparison of DEGs across the three groups revealed 253 common DEGs (Fig. 4 A), with 78 DEGs commonly upregulated (Fig. 4 B) and 98 DEGs commonly downregulated (Fig. 4 C). Moreover, a total of 172 DEGs exhibit a "decrease-then-increase" expression pattern, and 225 DEGs also display a "decrease-then-increase" expression pattern. This suggests that D. nobilis responds to Arg stress with at least 78 genes showing upregulated expression, 98 genes exhibiting downregulated expression, 172 genes demonstrating a decrease in expression levels under high concentrations of Arg stress, and 225 genes being upregulated under high concentrations of Arg stress. 3.3.2. GO Enrichment Analysis The DEGs were subjected to GO enrichment analysis and categorized into three categories: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF). In the 2.5 mM treatment group, 355 DEGs were annotated as "metabolic process" under BP category; 416 DEGs were annotated as "catalytic activity" under MF category; and 285 DEGs were annotated as "membrane" under CC category (Fig. 5 A). In the 30 mM treatment group, 178 DEGs were annotated as "membrane" under BP category; 212 DEGs were annotated as "catalytic activity" under MF category; and 310 DEGs were annotated as "cellular component: membrane part" under CC category (Fig. 5 B). Compared to the low concentration of Arg at 2.5 mM, the high concentration of 30 mM Arg treatment resulted in 166 DEGs annotated as "membrane" under BP category; 210 DEGs annotated as "catalytic activity" under MF category; and 311 DEGs annotated as "cellular component: membrane part" under CC category (Fig. 5 C). The high concentration of Arg likely exerts a more significant impact on membrane-associated functions and structures, which may further affect cellular metabolism, material transport, and signal transduction. This alteration may represent a stress response of cells to high concentrations of Arg. 3.3.3. KEGG Enrichment Analysis KEGG analysis of differentially expressed genes (DEGs) revealed that when treated with 2.5 mM Arg, 23 and 69 DEGs were annotated as being related to Glycine, serine and threonine metabolism, respectively, and 19 DEGs and 44 DEGs were annotated as being related to Arginine and proline metabolism (Fig. 6 A, B). Interestingly, compared with the low concentration of 2.5 mM Arg, under the treatment of high - concentration 30 mM Arg, more DEGs were annotated as being related to Glycine, serine and threonine metabolism rather than Arginine and proline metabolism, with a total of 60 (Fig. 6 C). This implies that there may be complex feedback regulatory mechanisms within the cell. High - concentration Arg may act as a signaling molecule, triggering a series of signal transduction pathways, which in turn affect gene expression regulation. These signal pathways may act directly or indirectly on the promoter regions of genes related to glycine, serine and threonine metabolism, as well as arginine and proline metabolism, or influence the expression levels of genes by regulating the activities of transcription factors. 3.3.4. Analysis of Genes Associated with D. nobilis Pathogenicity Inhibited by Arg Through GO and KEGG enrichment analyses, along with the different expression fold changes (log2FPKM) of genes at each time point, we further screened DEGs associated with the parasitic process of D. nobilis fungus. Our aim was to identify genes from the transcriptome that are involved in the suppression of D. nobilis by Arg. Therefore, we selected 12 DEGs related to transport proteins (GO:0005215, ko02010), secondary metabolites (GO:0046872, GO:0005576, ko03070), degrading enzymes (GO:0016787, GO:0008233, ko00520), and organic metabolism (GO:0071704, ko00230, ko00620) from the DEGs with decreased expression and those with an initial increase followed by a decrease(Figure 7 ). By annotating these DEGs using the nr (non-redundant protein) database, we attempted to assign gene names. Eleven of these DEGs could be named as follows: DN2161 as VM1G_02428 ; DN25300 as VMCG_05981 ; DN32410 as GCG54_00009088 ; DN14706 as CDD82_7343 ; DN5325 as M406DRAFT_345789 ; DN34630 as DHEL01_v201185 ; DN1223 as DHEL01_v209062 ; DN2657 as CORC01_12234 ; DN4632 as VSDG_07717 ; DN1799 as DHEL01_v202331 ; DN34620 as VMCG_08322 . Notably, DEGs with an initial increase followed by a decrease were only found in transport proteins and degrading enzymes. 3.3.5. The qRT-PCR validation experiment We randomly selected 15 DEGs for qRT-PCR analysis to further validate the reliability of the transcriptome data. The qRT-PCR analysis results showed that when D. nobilis was treated with Arg, the 15 selected genes were significantly differentially expressed, and the results were consistent with the transcriptome analysis (Fig. 8 ). This confirms that the results obtained from the transcriptome analysis are reliable. 4. Discussion In this study, we investigated the inhibitory effects of Arg on D. nobilis , a fungus that commonly infects fresh food nuts of chestnuts during harvesting and storage. The results demonstrated that Arg effectively inhibited the growth of D. nobilis mycelium and reduced the incidence and disease index of chestnut rot. However, high concentrations of Arg not only affected the pathogen but also exerted toxic effects on healthy fruit, which is consistent with previous findings on the use of amino acids like GABA in tomato treatment [ 55 ] . This highlights the importance of selecting an appropriate concentration of Arg for practical applications. The potential antifungal mechanisms of Arg were explored through transcriptomic analysis. After Arg treatment, the expression of genes related to transport proteins, secondary metabolites, degradative enzymes, and organic metabolism in D. nobilis decreased. Transport proteins play a crucial role in the absorption and efflux of various compounds across biological membranes [ 56 ] . The significant reduction in the expression of genes related to ABC transporters and MFS transporters, such as DN25300 (hypothetical protein VMCG_05981 ), DN1816 (putative high-affinity nicotinic acid transporter), and DN3090 (ABC-transporter), suggests that Arg can impede the normal growth of D.nobilis by inhibiting ATP transfer and transmembrane transport, similar to the effects of drug inhibition on fungal ATP transport [ 57 , 58 ] . Fungal secondary metabolites are associated with virulence [ 59 ] . The decreased expression of a large number of secondary metabolism - related genes in D. nobilis after Arg treatment, such as DN14447 (Dihydromonacolin L monooxygenase LovA), DN8089 (cytochrome P450), and DN1569 (putative d-amino-acid oxidase), indicates that the expression of virulence genes is reduced, thereby diminishing its harmful effects on fruits. D. nobilis is a species of the genus Diaporthe [ 60 ] , as a pathogen, it can secrete toxic substances, but arginine may inhibit the secretion of these toxins. Pathogens use cell wall - degrading enzymes (CWDEs) to break down plant cell walls [ 61 , 62 ] . The mycelia and spores of the pathogenic bacteria colonize in the intercellular spaces, and then the mycelia cover the entire surface of the tissues of Chinese chestnut, leading to the disappearance of the cell structure [ 63 ] . Arg significantly inhibited the synthesis of potential CWDEs in D. nobilis , and the expression of some CWDE - related genes, like DN34593 (glycosyl hydrolase, annotated as 3-hydroxybutyryl-CoA dehydrogenase) and DN6432 (hypothetical protein VPNG_02935 , annotated as Enoyl-Acyl carrier protein reductase), was affected by Arg concentration, which may be involved in the resistance and detoxification mechanisms of D. nobilis . There are reports suggesting that some fungal secreted degrading enzymes (such as oxidoreductases and peroxidases) can decompose or transform toxins, heavy metals, or metabolic byproducts in the environment, thereby reducing their toxic effects on fungal cells [ 64 , 65 ] . Moreover, the expression levels of certain transport proteins DN1536 (putative quinate permease), DN41907 (putative potassium transporter), DN22176 (putative quinate permease), DN7931 (putative mfs drug efflux)) and degradation enzymes ( DN34593 , DN6432 ) showed an increase followed by a decrease during Arg treatment. This may be due to a negative feedback regulation mechanism. At low Arg concentrations, the cell may increase the expression of these genes to cope with the stress, while at high concentrations, it may suppress the expression to avoid unnecessary energy consumption [ 66 ] . 5. Conclusions This study comprehensively investigated the inhibitory effects of Arg on D. nobilis and control chestnuts rot diseases using in vitro experiments and transcriptomics, presenting Arg very potential control on postharvest food diseases. Arg effects growth of plant pathogenic fungi by mediating pathways related to cell activity, toxin synthesis, and cell wall - degrading enzymes. However, the concentration - dependent effects of Arg must be carefully considered when to apply it into control diseases in practice, as higher concentrations do not always lead to better results. These findings not only provide valuable direct evidence firstly on the mediation and potential mechanisms of Arg to inhibits the growth of pathogenic fungi in plants but also offer a theoretical basis for its possible application in post - harvest preservation in the future. Further research is needed to optimize the application conditions of Arg and explore its broader application prospects in the field of agricultural product preservation. Declarations Funding This work was supported by the Fundamental Research Funds for CAF (CAFYBB2021ZF001). Conflict of interest The authors confirm that there are no known conflicts of interest associated with this publication and no significant financial support for this work that could have influenced its outcome. Author contributions Dong-Hui Yan : Conceptualization; Supervision; Funding acquisition; Writing–review and editing. Shuang Zhou : Data curation; Formal analysis; Investigation; Methodology; Project administration; Resources; Software; Validation; Visualization; Writing–original draft. References Li R, Sharma AK, Zhu J, et al. Nutritional biology of chestnuts: A perspective review [J]. 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Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6207660","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":441611363,"identity":"ac33b85f-287c-487e-b3df-bfaa83192cd1","order_by":0,"name":"Shuang Zhou","email":"","orcid":"","institution":"Chinese Academy of Forestry","correspondingAuthor":false,"prefix":"","firstName":"Shuang","middleName":"","lastName":"Zhou","suffix":""},{"id":441611364,"identity":"73b9d64c-3ede-4399-9df6-5a9fd667beae","order_by":1,"name":"Dong-Hui Yan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYJACaYYKBgb2BtK0nGFg4DlAkhbGNlK0GBw/e/B24Tw7eR4G5ocfGGruEKHlTF6y9cxtyYY9DGzGEgzHnhGh5UCOmTTvtgOM+xkYzBgYGw4ToeX8G6CWOQfsexjYvxGp5QbIloYDiT0MPETaInnjjbE1z7Hk5B5mnmKJhGNEaOE7n2N4m6fGzraHvX3jhw81RGhROABjMQNxAmENDAzyDcSoGgWjYBSMgpENABOcNWo9671zAAAAAElFTkSuQmCC","orcid":"","institution":"Chinese Academy of Forestry","correspondingAuthor":true,"prefix":"","firstName":"Dong-Hui","middleName":"","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2025-03-12 01:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6207660/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6207660/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80520229,"identity":"703384ed-db40-450e-9806-0ed1d553b157","added_by":"auto","created_at":"2025-04-14 08:58:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1277637,"visible":true,"origin":"","legend":"\u003cp\u003eInhibition of \u003cem\u003eD. nobilis\u003c/em\u003e growth by Arg. Growth of \u003cem\u003eD. nobilis\u003c/em\u003e on PDA plates with 0 mM(A),2.5 mM(B), 5.0 mM(C), 10 mM(D), 20 mM(E), and 30 mM(F) Arg concentrations . Mycelial diameter growth per day (G). Daily growth rate of mycelial diameter (H). Mycelial growth inhibition rate (I).\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/e21e0fb8ef0f8f476e3a1f18.png"},{"id":80520745,"identity":"b9382551-e8e3-4eb3-ad79-3e165345fb3a","added_by":"auto","created_at":"2025-04-14 09:06:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":22657555,"visible":true,"origin":"","legend":"\u003cp\u003eDisease incidence of chestnuts inoculated with \u003cem\u003eD. nobilis\u003c/em\u003e under Arg treatment.\u003c/p\u003e\n\u003cp\u003e(A, C, E, G, I) Disease severity on the chestnut surface. (B, D, F, H, J) Disease severity inside the chestnut. (K) Distribution of disease severity in chestnuts treated with different concentrations of Arg.(L) Disease index of chestnuts treated with different concentrations of Arg.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/884b3ed4c65e90902957185c.png"},{"id":80520231,"identity":"7bcf9a56-eaf5-430f-a799-0e9e5dec17fc","added_by":"auto","created_at":"2025-04-14 08:58:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":12600769,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram of DEGs. All DEGs (A). Upregulated DEGs (B). Downregulated DEGs (C). i: CK vs 2.5 mM; ii: CK vs 30 mM; iii: 2.5 mM vs 30 mM.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/c02d6d7f873d84bc6dbd6111.png"},{"id":80520238,"identity":"dba61dd6-06cb-4d73-a9b6-21321797c0cb","added_by":"auto","created_at":"2025-04-14 08:58:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":11675291,"visible":true,"origin":"","legend":"\u003cp\u003eGO Enrichment Analysis. Select the top 10 most significant terms for each category. (A) CK vs 2.5 mM;(B) CK vs 30 mM;(C) 2.5 mM vs 30 mM.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/b59eed224491dbc34d060cf4.png"},{"id":80520230,"identity":"b627e8ee-d932-4811-8f1f-0259f59c2607","added_by":"auto","created_at":"2025-04-14 08:58:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":189192,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG Enrichment Analysis. Screen the top 20 most significantly enriched pathways.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/a9a254efc4a78263812c1c75.png"},{"id":80520742,"identity":"eedf63cf-5185-4ded-9025-fafee890a94a","added_by":"auto","created_at":"2025-04-14 09:06:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":127393,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of Transport Proteins, Secondary Metabolites, Degrading Enzymes, and Organic substance Metabolism.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/094e6398e829b0df418bd260.png"},{"id":80520247,"identity":"93641f63-8a9e-4436-a280-8c2eaf73bde5","added_by":"auto","created_at":"2025-04-14 08:58:49","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1362226,"visible":true,"origin":"","legend":"\u003cp\u003eRT-qPCR validation. Fifteen randomly selected DEGs were validated by RT-qPCR and the results were compared with RNA-seq data.\u003c/p\u003e","description":"","filename":"figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/a11f1ac46dfb7b18503f4091.png"},{"id":80520239,"identity":"1e613d56-c9cb-449e-abd9-e2a65fbabd5c","added_by":"auto","created_at":"2025-04-14 08:58:49","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":158701,"visible":true,"origin":"","legend":"\u003cp\u003eRT-qPCR validation. Fifteen randomly selected DEGs were validated by RT-qPCR and the results were compared with RNA-seq data.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/e24bf8a85338ea45243a36ed.png"},{"id":80520233,"identity":"cdaef607-689d-467e-95de-0ccc2c7bfe38","added_by":"auto","created_at":"2025-04-14 08:58:48","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":141000,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-6207660/v1/d5afd7392d46e7c5b3f99459.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring the Antifungal Potential of Arginine in Controlling Chestnut Rot Disease","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eChestnuts have historically served as a staple food in various cultures. In modern agricultural practices, chestnuts hold significant importance as a valuable nutritional source in both daily life and research. From a compositional perspective, chestnuts are abundant in starch, protein, fiber, essential lipids and some vitamins, minerals. \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e。However, chestnut rot diseases pose a severe threat to the economic benefits and valuable food of chestnuts and outbreak typically peaks during the postharvest storage period. Although a diverse range of pathogens in chestnut fruit rots were identified such as \u003cem\u003eDiaporthe\u003c/em\u003e, \u003cem\u003eAlternaria\u003c/em\u003e, \u003cem\u003eBotryosphearia\u003c/em\u003e, and \u003cem\u003eColletotrichum\u003c/em\u003e genera, the \u003cem\u003eDiaporthe\u003c/em\u003e fungi always takes dominant abundance among these genera \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Furthermore, \u003cem\u003eDiaporthe\u003c/em\u003e species are widely distributed and serve as fungal pathogens of many plants and even mammals besides being non-pathogenic endophytes (biotrophic fungi), saprobes\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003ePlant pathogenic Diaporthe\u003c/em\u003e spp. can cause wood cankers, wilts, dieback, and fruit rot in various economically valuable plant hosts, particularly recorded those affecting economically important crops such as soybeans, sunflowers, grapes, citrus, chestnuts, and ornamental trees\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.Rot diseases caused by \u003cem\u003eDiaporthe\u003c/em\u003e species are prevalent and highly destructive in postharvest fruits including chestnut fruit\u003csup\u003e[\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003eD. nobilis\u003c/em\u003e has recently been identified as major causal pathogen for fruit rots of \u003cem\u003eCastanea mollissima\u003c/em\u003e var. Yanshanzaofen, which is the most economically profitable chestnut variety in the Yanshan region of northern China and recorded as a very susceptible variety to rot diseases, with a cultivation area exceeding 1\u0026nbsp;million mu and an export volume accounting for more than 50% of the total chestnut exports\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Consuming food containing pesticide residues can increase the risk of developing cancer, cardiovascular diseases, and respiratory diseases.\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.Currently, chemical pesticides are commonly used to control \u003cem\u003eDiaporthe\u003c/em\u003e-induced diseases\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, However, the excessive use of chemical pesticides has led to serious issues such as food contamination, environmental pollution, and phytotoxicity\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Consequently, as consumer concern about food safety and environmental issues continues to rise, eco-friendly postharvest preservation technologies have developed rapidly\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eArginine is predominantly present as a structural amino acid in proteins, and it plays an essential role in protein synthesis and degradation. It is widely distributed in most prokaryotic and eukaryotic organisms \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. In plants, arginine is involved in growth, development, and stress tolerance through its conversion to putrescine via ornithine, which is critical for root elongation and development. A reduction in putrescine inhibits root elongation, whereas exogenous putrescine (0.01\u0026ndash;1 mM) promotes root growth and system development\u003csup\u003e[\u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Arginine is also hydrolyzed by arginase to produce urea, which is integrated into the nitrogen recycling pathway, supporting plant development and responses to biotic and abiotic stresses\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e.In fungi, arginine supplementation enhances the production of perylenequinone in the endophytic fungus Beauveria bassiana by upregulating glycolysis-related genes and activating the NO-cGMP-PKG signaling pathway\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Similarly, arginine treatment in postharvest jujube fruit induces resistance to \u003cem\u003eAlternaria alternata\u003c/em\u003e by balancing ROS metabolism and enhancing pathogenesis-related protein activity\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Additionally, arginine regulates microcycle conidiation in \u003cem\u003eMetarhizium acridum\u003c/em\u003e by modulating NO levels, with disruption of MaAGA leading to reduced NO and altered sporulation patterns\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Chestnuts are rich in various nutrients, including carbohydrates, proteins, vitamins, potassium, magnesium, iron, dietary fiber, and a diverse range of amino acids\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e\u0026zwnj;, However, the potential impact of amino acids metabolized by chestnuts on nut rot disease remains largely unexplored.\u003c/p\u003e \u003cp\u003eThis study evaluates the inhibitory effect of exogenous arginine (Arg) on chestnut rot disease. It also investigates the impact of exogenous Arg on the growth of the pathogenic fungus \u003cem\u003eD.nobilis\u003c/em\u003e and further explores the antifungal mechanisms of Arg through transcriptomic analysis. The objective of this research is to thoroughly analyze the direct inhibitory effects of Arg on \u003cem\u003eDiaporthe\u003c/em\u003e and its potential pathways, providing theoretical support for the use of Arg as a possible therapeutic strategy to inhibit the growth of this pathogen and its pathogenic process.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Fruit, strains, and chemicals\u003c/h2\u003e \u003cp\u003eThe chestnut variety used in this study is Yanshan Zaofeng 3113, harvested from Tangxian County in Tangshan City, Hebei Province, which is the core distribution area of Yanshan Zaofeng. Healthy chestnuts were stored in a 4\u0026deg;C refrigerator for preservation.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eD. nobilis\u003c/em\u003e strain, which was isolated from rotting chestnuts, has been experimentally confirmed for its pathogenicity. It was cultured on PDA medium and used for subsequent experiments.\u003c/p\u003e \u003cp\u003eArginine (purity: 99%) was purchased from Beijing Zhongxing Weiye Biotechnology Co., Ltd.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Arg inhibits chestnut rot disease\u003c/h2\u003e \u003cp\u003eThe chestnuts were first washed and soaked in 2% sodium hypochlorite and sterile water for 3 minutes, then soaked in 100 mL of sterilized arginine (Arg) solution for 24 hours. The concentrations of the Arg solution were 2.5 mM, 5.0 mM, 10 mM, 20 mM, and 30 mM, with sterile water used as a control group, which was also soaked for 24 hours. Using a 5 mm sterile punch, holes were made in the chestnut shells, ensuring that the inner seed coat detached without damaging the seed. Sterile tweezers were used to transfer \u003cem\u003eD.nobilis\u003c/em\u003e agar plugs, with the mycelium facing the seed, into the holes for inoculation. The fruits were then placed into sterile 150 mm Petri dishes, sealed with cling film, and stored in a 25\u0026deg;C constant temperature incubator. After 15 days of dark incubation, the chestnuts were opened, and the disease condition of each group was examined. There were 24 chestnuts in each treatment group. All the required tools were sterilized in an autoclave at 121\u0026deg;C for 20 minutes. All operations were performed in a laminar flow hood.\u003c/p\u003e \u003cp\u003eThe disease severity of chestnut rot (disease grade) was classified based on the observed diseased area on the maximum longitudinal section of the chestnut at the inoculation site, using a 5-level scale: Level 0: The seed is healthy with no disease;Level 1: Disease at the inoculation site, with minimal spread; the lesion diameter\u0026thinsp;\u0026le;\u0026thinsp;5 mm༛Level 2: Lesion has spread, and the diseased area is \u0026le;\u0026thinsp;25%༛Level 3: Lesion has spread, and the diseased area is \u0026gt;\u0026thinsp;25% but \u0026le;\u0026thinsp;50%༛Level 4: Lesion has spread, and the diseased area is \u0026gt;\u0026thinsp;50%.\u003c/p\u003e \u003cp\u003eThe disease index is calculated as:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{D}\\text{i}\\text{s}\\text{e}\\text{a}\\text{s}\\text{e}\\:\\text{I}\\text{n}\\text{d}\\text{e}\\text{x}=\\frac{{\\Sigma\\:}(\\text{D}\\text{i}\\text{s}\\text{e}\\text{a}\\text{s}\\text{e}\\:\\text{G}\\text{r}\\text{a}\\text{d}\\text{e}\\times\\:\\text{N}\\text{u}\\text{m}\\text{b}\\text{e}\\text{r}\\:\\text{o}\\text{f}\\:\\text{F}\\text{r}\\text{u}\\text{i}\\text{t}\\text{s})}{\\text{T}\\text{o}\\text{t}\\text{a}\\text{l}\\:\\text{N}\\text{u}\\text{m}\\text{b}\\text{e}\\text{r}\\:\\text{o}\\text{f}\\:\\text{F}\\text{r}\\text{u}\\text{i}\\text{t}\\text{s}\\times\\:\\text{H}\\text{i}\\text{g}\\text{h}\\text{e}\\text{s}\\text{t}\\:\\text{G}\\text{r}\\text{a}\\text{d}\\text{e}\\:\\text{V}\\text{a}\\text{l}\\text{u}\\text{e}}\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Measurement of the mycelial growth inhibition rate of D. nobilis\u003c/h2\u003e \u003cp\u003eThe Potato Dextrose Agar (PDA) medium was autoclaved at 121\u0026deg;C for 20 minutes, then cooled to 60\u0026deg;C. Sterile Arginine aqueous solution was added to achieve final concentrations of 2.5 mM, 5 mM, 10 mM, 20 mM, and 30 mM. An equal volume of sterile water was used as a control sample. A 5 mm mycelial disc of \u003cem\u003eD. nobilis\u003c/em\u003e (the disc was obtained by punching from a PDA culture after 7 days of incubation) was cultured on the PDA medium containing Arg. The colony diameter was measured daily using a ruler. For each treatment group, 5 independent samples were measured, and each sample was measured 3 times, with the average value taken. The antifungal activity was determined by radial mycelial growth bioassay, and the inhibition rate was calculated as follows:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\text{I}\\text{n}\\text{h}\\text{i}\\text{b}\\text{i}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{r}\\text{a}\\text{t}\\text{e}=\\frac{C-T}{C-5}\\times\\:100\\%$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eC\u003c/em\u003e\u0026thinsp;=\u0026thinsp;the colony diameter of \u003cem\u003eD. nobilis\u003c/em\u003e on the control plate;\u003c/p\u003e \u003cp\u003e \u003cem\u003eT\u003c/em\u003e\u0026thinsp;=\u0026thinsp;the colony diameter of \u003cem\u003eD. nobilis\u003c/em\u003e on the treatment plate;\u003c/p\u003e \u003c/div\u003e\n\u003cdiv class=\"Heading\"\u003e5\u0026thinsp;=\u0026thinsp;the initial size of the \u003cem\u003eD. nobilis\u003c/em\u003e mycelial block\u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Transcriptome analysis of D.nobilis treated with Arg\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1. Transcriptome sequencing and cDNA library construction\u003c/h2\u003e \u003cp\u003eTo investigate the effects of different Arg concentrations on \u003cem\u003eD.nobilis\u003c/em\u003e, transcriptome analysis was performed on three groups of samples: the untreated control group (CK), the low concentration Arg treatment group (2.5 mM), and the high concentration Arg treatment group (30 mM). These three groups were selected based on preliminary experimental results showing significant differences in the inhibitory or promotional effects of low and high concentrations of Arg on chestnut disease severity and incidence. After filtering the data, the base composition and quality distribution were analyzed to visualize the data quality.\u003c/p\u003e \u003cp\u003ePrepare PDA media with 2.5 mM and 30 mM Arg concentrations, and set up sterile water as the control. Sterile glass paper is placed on the surface of the medium, and 5 mm mycelial discs of \u003cem\u003eD. nobilis\u003c/em\u003e are inoculated using a sterile puncher, followed by dark incubation at 25\u0026deg;C for 7 days. For each Arg concentration, mycelia from 5 petri dishes are pooled into one sample, with 3 repetitions. Mycelia from each treatment group are collected for RNA extraction, with normally growing \u003cem\u003eD. nobilis\u003c/em\u003e used as the control.RNA extraction, quality control, PCR amplification, and sequencing were performed by Kangsheng Xuanyuan Biotechnology (Wuhan) Co., Ltd.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2. Transcriptome data processing\u003c/h2\u003e \u003cp\u003eThe sequencing data underwent quality control by removing reads containing adapters and low-quality reads, including those with Ns or those with more than 50% of bases having a quality score (Q)\u0026thinsp;\u0026le;\u0026thinsp;10 \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. After obtaining high-quality sequencing data, sequence assembly and library construction were performed using Trinity\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. To ensure the quality of the sequencing library, randomization tests, fragment length distribution, and saturation tests were conducted\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e.DIAMOND\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e software was used to align Unigene sequences with databases such as NR\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e、Swiss-Prot\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e、COG\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e、KOG\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e、eggNOG4.5\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e、KEGG\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e.KOBAS\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e was utilized to obtain KEGG Orthology results for Unigene in KEGG. InterProScan\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e integrated databases to analyze the Gene Ontology (GO) \u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e annotations of the newly identified genes. After predicting the amino acid sequences of Unigene, HMMER\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e was used to align them with the Pfam\u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e database to obtain annotation information for Unigene.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3. Differentially expressed genes (DEGs) analysis\u003c/h2\u003e \u003cp\u003ehe sequencing reads were aligned to the Unigene database using Bowtie\u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e, and expression levels were estimated using RSEM\u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e based on the alignment results. The expression abundance of corresponding Unigenes was represented by FPKM values. Differential expression analysis was performed using a software tool based on gene counts across samples. or groups with biological replicates, differential analysis was conducted using the DESeq2\u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]\u003c/sup\u003e software. In the differential expression gene detection process, a |Fold Change| \u0026ge; 1 and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.01 were used as the screening criteria. Differentially expressed genes were then subjected to functional annotation and gene count statistics using relevant databases\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Real-time quantitative reverse transcription PCR (qRT-PCR) detection and data analysis\u003c/h2\u003e \u003cp\u003eTranscribe the RNA of the samples into cDNA. The mRNA expression of the target gene is detected by real-time PCR. cDNA is synthesized using the TRUEscript RT MasterMix kit (Aibosen, Beijing, China). The primers for the target gene are designed using Primer Premier 6, with actin selected as the internal reference gene. Then, 2xSybr Green qPCR Mix is used for qRT-PCR with the CFX96 real-time PCR detection system (Bio-Rad, USA). The qRT-PCR reaction mixture (total volume 25 \u0026micro;L) contains 12.5 \u0026micro;L of 2xSybr Green qPCR Mix, 0.5 \u0026micro;L of each primer (1 \u0026micro;M), 1 \u0026micro;L of cDNA, and 10.5 \u0026micro;L of ddH2O. The qRT-PCR reaction conditions are 95\u0026deg;C for 120 s; 95\u0026deg;C for 15 s, 60\u0026deg;C for 30 s, for 40 cycles. Gene expression is calculated using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. All qRT-PCR reactions are performed in triplicate. The primers are listed in Supplementary Table\u0026nbsp;1 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDifferentially expressed genes were analyzed for Gene Ontology (GO) enrichment using the hypergeometric test method in ClusterProfiler, focusing on biological processes, molecular functions, and cellular components. Based on the annotation results of KEGG for the differentially expressed genes from public databases\u003csup\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/sup\u003e, the KEGG pathways were classified according to pathway types in KEGG. RT-qPCR data analysis was performed using the ANOVA function in GraphPad Prism 8.0 for physiological data analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1. The mycelial growth of D. nobilis is inhibited by Arg\u003c/h2\u003e \u003cp\u003eThe Yanshan Zaofeng variety is rich in amino acids, including glutamic acid, aspartic acid, arginine, lysine, leucine, etc.\u003csup\u003e[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e。In addition, it has been reported that the naturally occurring non - protein amino acid γ - aminobutyric acid can effectively inhibit the growth of \u003cem\u003eAlternaria alternata\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e。Solutions of alanine, glycine, glutamic acid, aspartic acid, lysine, arginine, leucine, valine, and γ - aminobutyric acid with a concentration of 30 mM were respectively added to the culture medium to cultivate \u003cem\u003eD. nobilis\u003c/em\u003e. The results showed that alanine had no effect on the growth of \u003cem\u003eD. nobilis\u003c/em\u003e. Glycine, glutamic acid, aspartic acid, lysine, and arginine inhibited the growth of \u003cem\u003eD. nobilis\u003c/em\u003e, with arginine showing the most significant inhibitory effect. On the sixth day, the average diameter of the fungal discs in the CK group grew to 80.04 mm, while the diameter of the fungal discs of \u003cem\u003eD. nobilis\u003c/em\u003e in the Arg group was only 28.84 mm, which was significantly lower than that of the CK group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Leucine, valine, and γ - aminobutyric acid promoted the growth of \u003cem\u003eD. nobilis\u003c/em\u003e. On the fourth day, the diameters of the fungal discs in the leucine group, valine group, and γ - aminobutyric acid group were 51.73 mm, 55.16 mm, and 55.78 mm respectively, all of which were significantly higher than 50.12 mm of the CK group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Based on these results, we will select arginine with the best inhibitory effect for subsequent research.\u003c/p\u003e \u003cp\u003eExogenous Arg affects the growth of \u003cem\u003eD. nobilis\u003c/em\u003e. Treatment with different concentrations of Arg shows that the inhibitory effect on \u003cem\u003eD. nobilis\u003c/em\u003e colony growth becomes more pronounced as the concentration increases, with noticeable inhibition at 2.5 mM, 5.0 mM, 10 mM, 20 mM, and 30 mM (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-F). Over a 6-day period, higher concentrations of Arg lead to stronger inhibition of \u003cem\u003eD. nobilis\u003c/em\u003e colony growth. At 2.5 mM, the mycelial diameter increased by 58.93 mm, while at 30 mM, it only increased by 22.56 mm (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). In terms of growth rate, the colony growth rate was 13.23 mm/day at 2.5 mM, while at 30 mM, the growth rate was only 4.87 mm/day (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eH). Compared to the CK growth(0 mM),the inhibitory effect of 30 mM Arg on colony growth reached 66.9%, while the inhibition at 2.5 mM was 9.65%, with the former being 6.9 times greater than the latter (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eI). At high concentrations of Arg, not only is \u003cem\u003eD. nobilis\u003c/em\u003e growth inhibited, but the colony color also deepens, indicating significant impacts on its metabolic processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eF).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2. The ability of Arg to control chestnut rot disease\u003c/h2\u003e \u003cp\u003eAccording to the disease grading criteria in section \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e2.4\u003c/span\u003e, the severity of chestnut fruit disease is classified into five levels: grade 0 (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B), grade 1 (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, D), grade 2 (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, F), grade 3 (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eG, H), and grade 4 (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eI, J). Grade 0 indicates completely asymptomatic and is considered healthy, while grade 4 represents severe decay.\u003c/p\u003e \u003cp\u003eIn the CK group, the incidence of disease was 100%, while it decreased to 50% at 2.5 mM Arg, 33.3% at both 5.0 mM and 10 mM, 16.7% at 20 mM, however returned to 100% at 30 mM. At lower Arg concentrations (2.5 mM, 5.0 mM, and 10 mM), the severity of chestnut rot was significantly reduced, primarily showing grade 0 or 1 symptoms, indicating effective disease suppression. As the Arg concentration increased, disease severity gradually declined, suggesting a dose-dependent inhibitory effect of Arg on the nut rot development. However, at 30 mM, the disease severity increased to grade 3 or 4, with larger lesions and more extensive decay, indicating that excessive Arg may instead promote disease progression (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eK).\u003c/p\u003e \u003cp\u003eIn terms of disease severity index (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eL), the CK group exhibited the highest index at 91.67, indicating the most severe infection in untreated chestnuts. As the Arg concentration increased, the disease index gradually decreased to 39.58, 20.83, and 22.92 for the 2.5 mM, 5.0 mM, and 10 mM treatment groups, respectively, suggesting that low concentrations of Arg effectively suppressed or mitigated the occurrence of decay. When the Arg concentration reached 20 mM, the disease index further dropped to 10.42, demonstrating a strong inhibitory effect of Arg at this concentration.\u003c/p\u003e \u003cp\u003eHowever, when the Arg concentration reached 30 mM, the disease index rebounded to 89.58, approaching the level of the control group, indicating that an excessively high concentration of Arg had a negative impact on chestnuts and instead promoted disease development. This suggests that a moderate concentration of Arg can effectively mitigate chestnut decay, reducing both the incidence and severity of the disease, whereas an excessively high concentration may exacerbate the infection.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Mechanism of Arg Inhibition on the Growth and Development of D. nobilis\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1. Differential Expression Gene (DEG) data analysis\u003c/h2\u003e \u003cp\u003eTo understand the effects of different Arg concentrations on \u003cem\u003eD. nobilis\u003c/em\u003e, transcriptome analysis was performed on three sample groups. As shown in Table S2, the sequencing data across all samples were relatively balanced, ranging from 9.27 Gb to 10.58 Gb, indicating sufficient data volume. The GC content of each sample was approximately 55%, suggesting stable nucleotide composition without AT or GC bias, and overall high sequencing quality. The Q30 scores were also high, ensuring the reliability of subsequent bioinformatics analyses. Correlation heatmap analysis (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) showed strong correlations among the samples, demonstrating high reproducibility across the three sample groups.\u003c/p\u003e \u003cp\u003eUsing | log2(FoldChange) | \u0026gt; 1 and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, the gene expression differences among the three groups were compared. As shown in Table S3 and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e, in the 2.5 mM treatment group, a total of 1112 differentially expressed genes (DEGs) were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), with 573 genes upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) and 539 genes downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). In the 30 mM treatment group, 3296 DEGs were found (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), with 1851 genes upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) and 1445 genes downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). When comparing the 2.5 mM and 30 mM treatment groups, 3370 DEGs were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), with 1934 genes upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) and 1436 genes downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). A comparison of DEGs across the three groups revealed 253 common DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), with 78 DEGs commonly upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) and 98 DEGs commonly downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Moreover, a total of 172 DEGs exhibit a \"decrease-then-increase\" expression pattern, and 225 DEGs also display a \"decrease-then-increase\" expression pattern. This suggests that \u003cem\u003eD. nobilis\u003c/em\u003e responds to Arg stress with at least 78 genes showing upregulated expression, 98 genes exhibiting downregulated expression, 172 genes demonstrating a decrease in expression levels under high concentrations of Arg stress, and 225 genes being upregulated under high concentrations of Arg stress.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2. GO Enrichment Analysis\u003c/h2\u003e \u003cp\u003eThe DEGs were subjected to GO enrichment analysis and categorized into three categories: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF). In the 2.5 mM treatment group, 355 DEGs were annotated as \"metabolic process\" under BP category; 416 DEGs were annotated as \"catalytic activity\" under MF category; and 285 DEGs were annotated as \"membrane\" under CC category (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In the 30 mM treatment group, 178 DEGs were annotated as \"membrane\" under BP category; 212 DEGs were annotated as \"catalytic activity\" under MF category; and 310 DEGs were annotated as \"cellular component: membrane part\" under CC category (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Compared to the low concentration of Arg at 2.5 mM, the high concentration of 30 mM Arg treatment resulted in 166 DEGs annotated as \"membrane\" under BP category; 210 DEGs annotated as \"catalytic activity\" under MF category; and 311 DEGs annotated as \"cellular component: membrane part\" under CC category (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). The high concentration of Arg likely exerts a more significant impact on membrane-associated functions and structures, which may further affect cellular metabolism, material transport, and signal transduction. This alteration may represent a stress response of cells to high concentrations of Arg.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3. KEGG Enrichment Analysis\u003c/h2\u003e \u003cp\u003eKEGG analysis of differentially expressed genes (DEGs) revealed that when treated with 2.5 mM Arg, 23 and 69 DEGs were annotated as being related to Glycine, serine and threonine metabolism, respectively, and 19 DEGs and 44 DEGs were annotated as being related to Arginine and proline metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, B). Interestingly, compared with the low concentration of 2.5 mM Arg, under the treatment of high - concentration 30 mM Arg, more DEGs were annotated as being related to Glycine, serine and threonine metabolism rather than Arginine and proline metabolism, with a total of 60 (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). This implies that there may be complex feedback regulatory mechanisms within the cell. High - concentration Arg may act as a signaling molecule, triggering a series of signal transduction pathways, which in turn affect gene expression regulation. These signal pathways may act directly or indirectly on the promoter regions of genes related to glycine, serine and threonine metabolism, as well as arginine and proline metabolism, or influence the expression levels of genes by regulating the activities of transcription factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.3.4. Analysis of Genes Associated with D. nobilis Pathogenicity Inhibited by Arg\u003c/h2\u003e \u003cp\u003eThrough GO and KEGG enrichment analyses, along with the different expression fold changes (log2FPKM) of genes at each time point, we further screened DEGs associated with the parasitic process of \u003cem\u003eD. nobilis\u003c/em\u003e fungus. Our aim was to identify genes from the transcriptome that are involved in the suppression of \u003cem\u003eD. nobilis\u003c/em\u003e by Arg. Therefore, we selected 12 DEGs related to transport proteins (GO:0005215, ko02010), secondary metabolites (GO:0046872, GO:0005576, ko03070), degrading enzymes (GO:0016787, GO:0008233, ko00520), and organic metabolism (GO:0071704, ko00230, ko00620) from the DEGs with decreased expression and those with an initial increase followed by a decrease(Figure \u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBy annotating these DEGs using the nr (non-redundant protein) database, we attempted to assign gene names. Eleven of these DEGs could be named as follows: \u003cem\u003eDN2161\u003c/em\u003e as \u003cem\u003eVM1G_02428\u003c/em\u003e; \u003cem\u003eDN25300\u003c/em\u003e as \u003cem\u003eVMCG_05981\u003c/em\u003e; \u003cem\u003eDN32410\u003c/em\u003e as \u003cem\u003eGCG54_00009088\u003c/em\u003e; \u003cem\u003eDN14706\u003c/em\u003e as \u003cem\u003eCDD82_7343\u003c/em\u003e; \u003cem\u003eDN5325\u003c/em\u003e as \u003cem\u003eM406DRAFT_345789\u003c/em\u003e; \u003cem\u003eDN34630\u003c/em\u003e as \u003cem\u003eDHEL01_v201185\u003c/em\u003e; \u003cem\u003eDN1223\u003c/em\u003e as \u003cem\u003eDHEL01_v209062\u003c/em\u003e; \u003cem\u003eDN2657\u003c/em\u003e as \u003cem\u003eCORC01_12234\u003c/em\u003e; \u003cem\u003eDN4632\u003c/em\u003e as \u003cem\u003eVSDG_07717\u003c/em\u003e; \u003cem\u003eDN1799\u003c/em\u003e as \u003cem\u003eDHEL01_v202331\u003c/em\u003e; \u003cem\u003eDN34620\u003c/em\u003e as \u003cem\u003eVMCG_08322\u003c/em\u003e. Notably, DEGs with an initial increase followed by a decrease were only found in transport proteins and degrading enzymes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.3.5. The qRT-PCR validation experiment\u003c/h2\u003e \u003cp\u003eWe randomly selected 15 DEGs for qRT-PCR analysis to further validate the reliability of the transcriptome data. The qRT-PCR analysis results showed that when \u003cem\u003eD. nobilis\u003c/em\u003e was treated with Arg, the 15 selected genes were significantly differentially expressed, and the results were consistent with the transcriptome analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e8\u003c/span\u003e). This confirms that the results obtained from the transcriptome analysis are reliable.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, we investigated the inhibitory effects of Arg on \u003cem\u003eD. nobilis\u003c/em\u003e, a fungus that commonly infects fresh food nuts of chestnuts during harvesting and storage. The results demonstrated that Arg effectively inhibited the growth of \u003cem\u003eD. nobilis\u003c/em\u003e mycelium and reduced the incidence and disease index of chestnut rot. However, high concentrations of Arg not only affected the pathogen but also exerted toxic effects on healthy fruit, which is consistent with previous findings on the use of amino acids like GABA in tomato treatment\u003csup\u003e[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e. This highlights the importance of selecting an appropriate concentration of Arg for practical applications.\u003c/p\u003e \u003cp\u003eThe potential antifungal mechanisms of Arg were explored through transcriptomic analysis. After Arg treatment, the expression of genes related to transport proteins, secondary metabolites, degradative enzymes, and organic metabolism in \u003cem\u003eD. nobilis\u003c/em\u003e decreased. Transport proteins play a crucial role in the absorption and efflux of various compounds across biological membranes\u003csup\u003e[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe significant reduction in the expression of genes related to ABC transporters and MFS transporters, such as \u003cem\u003eDN25300\u003c/em\u003e (hypothetical protein \u003cem\u003eVMCG_05981\u003c/em\u003e), \u003cem\u003eDN1816\u003c/em\u003e (putative high-affinity nicotinic acid transporter), and \u003cem\u003eDN3090\u003c/em\u003e (ABC-transporter), suggests that Arg can impede the normal growth of \u003cem\u003eD.nobilis\u003c/em\u003e by inhibiting ATP transfer and transmembrane transport, similar to the effects of drug inhibition on fungal ATP transport\u003csup\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFungal secondary metabolites are associated with virulence\u003csup\u003e[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]\u003c/sup\u003e. The decreased expression of a large number of secondary metabolism - related genes in \u003cem\u003eD. nobilis\u003c/em\u003e after Arg treatment, such as \u003cem\u003eDN14447\u003c/em\u003e (Dihydromonacolin L monooxygenase LovA), \u003cem\u003eDN8089\u003c/em\u003e (cytochrome P450), and \u003cem\u003eDN1569\u003c/em\u003e (putative d-amino-acid oxidase), indicates that the expression of virulence genes is reduced, thereby diminishing its harmful effects on fruits. \u003cem\u003eD. nobilis\u003c/em\u003e is a species of the genus \u003cem\u003eDiaporthe\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/sup\u003e, as a pathogen, it can secrete toxic substances, but arginine may inhibit the secretion of these toxins. Pathogens use cell wall - degrading enzymes (CWDEs) to break down plant cell walls\u003csup\u003e[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]\u003c/sup\u003e. The mycelia and spores of the pathogenic bacteria colonize in the intercellular spaces, and then the mycelia cover the entire surface of the tissues of Chinese chestnut, leading to the disappearance of the cell structure\u003csup\u003e[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]\u003c/sup\u003e. Arg significantly inhibited the synthesis of potential CWDEs in \u003cem\u003eD. nobilis\u003c/em\u003e, and the expression of some CWDE - related genes, like \u003cem\u003eDN34593\u003c/em\u003e (glycosyl hydrolase, annotated as 3-hydroxybutyryl-CoA dehydrogenase) and \u003cem\u003eDN6432\u003c/em\u003e (hypothetical protein \u003cem\u003eVPNG_02935\u003c/em\u003e, annotated as Enoyl-Acyl carrier protein reductase), was affected by Arg concentration, which may be involved in the resistance and detoxification mechanisms of \u003cem\u003eD. nobilis\u003c/em\u003e. There are reports suggesting that some fungal secreted degrading enzymes (such as oxidoreductases and peroxidases) can decompose or transform toxins, heavy metals, or metabolic byproducts in the environment, thereby reducing their toxic effects on fungal cells\u003csup\u003e[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMoreover, the expression levels of certain transport proteins \u003cem\u003eDN1536\u003c/em\u003e (putative quinate permease), \u003cem\u003eDN41907\u003c/em\u003e (putative potassium transporter), \u003cem\u003eDN22176\u003c/em\u003e (putative quinate permease), \u003cem\u003eDN7931\u003c/em\u003e (putative mfs drug efflux)) and degradation enzymes (\u003cem\u003eDN34593\u003c/em\u003e, \u003cem\u003eDN6432\u003c/em\u003e) showed an increase followed by a decrease during Arg treatment. This may be due to a negative feedback regulation mechanism. At low Arg concentrations, the cell may increase the expression of these genes to cope with the stress, while at high concentrations, it may suppress the expression to avoid unnecessary energy consumption\u003csup\u003e[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study comprehensively investigated the inhibitory effects of Arg on \u003cem\u003eD. nobilis\u003c/em\u003e and control chestnuts rot diseases using in vitro experiments and transcriptomics, presenting Arg very potential control on postharvest food diseases. Arg effects growth of plant pathogenic fungi by mediating pathways related to cell activity, toxin synthesis, and cell wall - degrading enzymes. However, the concentration - dependent effects of Arg must be carefully considered when to apply it into control diseases in practice, as higher concentrations do not always lead to better results. These findings not only provide valuable direct evidence firstly on the mediation and potential mechanisms of Arg to inhibits the growth of pathogenic fungi in plants but also offer a theoretical basis for its possible application in post - harvest preservation in the future. Further research is needed to optimize the application conditions of Arg and explore its broader application prospects in the field of agricultural product preservation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Fundamental Research Funds for CAF (CAFYBB2021ZF001).\u003c/p\u003e\n\u003cp\u003eConflict of interest\u003c/p\u003e\n\u003cp\u003eThe authors confirm that there are no known conflicts of interest associated with this publication and no significant financial support for this work that could have influenced its outcome.\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDong-Hui Yan\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eConceptualization; Supervision; Funding acquisition; Writing\u0026ndash;review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShuang Zhou\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003eData curation; Formal analysis; Investigation; Methodology; Project administration; Resources; Software; Validation; Visualization; Writing\u0026ndash;original draft.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLi R, Sharma AK, Zhu J, et al. 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PLoS One, 2019, 14(6): e0218508.https://doi.org/10.1371/journal.pone.0218508\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":false,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Arg, Diaporthe nobilis, Postharvest storage, Chestnuts, Transcriptomics","lastPublishedDoi":"10.21203/rs.3.rs-6207660/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6207660/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eArginine (Arg) can induce plant resistance. However, few know about its direct effect on fungal pathogens.. This study found that arginine could inhibit the growth of the pathogenic fungus \u003cem\u003eDiaporthe nobilis\u003c/em\u003e, a major causal agent of rot disease on edible nuts from \u003cem\u003eCastanea\u003c/em\u003e trees, with an inhibition rate of at most 66.9%. After chestnuts were treated with Arg, the disease index of rot caused by \u003cem\u003eD. nobilis\u003c/em\u003e decreased significantly, dropping from 91.67 to 20.83 at most. Transcriptome analysis showed that at least 225 differentially expressed genes (DEGs) in \u003cem\u003eD. nobilis\u003c/em\u003e were inhibited by arginine. Among them, the expression of genes related to pathogenicity, such as transport proteins, secondary metabolites, degrading enzymes, and organic metabolism, was downregulated. These results provide novel insights into the potential antifungal mechanism of arginine and suggest that arginine could be a potential safe alternative for controlling rot diseases of postharvest foods.\u003c/p\u003e","manuscriptTitle":"Exploring the Antifungal Potential of Arginine in Controlling Chestnut Rot Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-14 08:58:43","doi":"10.21203/rs.3.rs-6207660/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a650141a-10f3-4b96-bc6c-b304bc87b791","owner":[],"postedDate":"April 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47023032,"name":"Biological sciences/Biological techniques"},{"id":47023033,"name":"Biological sciences/Plant sciences"},{"id":47023034,"name":"Scientific community and society/Agriculture"}],"tags":[],"updatedAt":"2025-07-04T11:23:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-14 08:58:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6207660","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6207660","identity":"rs-6207660","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}