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MAP  >  Studies in Fungi
2024 Volume 9
Article Contents
Abstract
Introduction
Materials and methods
Plant materials
Protein extraction
Trypsin digestion
Affinity enrichment of ubiquitinated peptides
LC-MS/MS and data analysis
Bioinformatics methods
Results
Overview of the ubiquitomic analysis
Properties of ubiquitinated proteins and motifs
A temperature-regulated rice endosperm ubiquitome
Functions for differentially expressed ubiquitinated proteins
Discussion
Ubiquitination of heat shock proteins and transcription factors under high-temperature stress
Sucrose and starch metabolism are modified by ubiquitination under high-temperature stress
Ubiquitination affects sucrose hydrolysis
Ubiquitination of ADP-glucose pyrophosphorylase (AGPase)
Ubiquitination regulates amylose biosynthesis
Ubiquitination regulates amylopectin biosynthesis
Ubiquitination affects ribosomal systems under high-temperature stress
Author contributions
Data availability
Acknowledgments
Conflict of interest
Rights and permissions
References
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ARTICLE   Open Access    

Identification and fungicide sensitivity of the blue mold pathogen in postharvest-stored elephant garlic bulbs in Thailand

  • 1.

    Office of Research Administration, Chiang Mai University, Chiang Mai 50200, Thailand

  • 2.

    Center of Excellence in Microbial Diversity and Sustainable Utilization, Chiang Mai University, Chiang Mai 50200, Thailand

  • 3.

    Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand

  • 4.

    Department of Microbiology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand

  • 5.

    School of Agriculture and Natural Resources, University of Phayao, Phayao 56000, Thailand

More Information
  • Received: 05 November 2024
    Revised: 25 November 2024
    Accepted: 26 November 2024
    Published online: 20 December 2024
    Studies in Fungi  9,  Article number: e015 (2024)  |  Cite this article
  • Blue mold disease is one of the most important postharvest diseases affecting garlic bulbs. In 2023, this disease was found on bulbs of elephant garlic [Allium ampeloprasum var. ampeloprasum (Borrer) Syme] in Chiang Mai Province, Thailand, during the postharvest storage period. Three fungal isolates were obtained and identified as Penicillium allii based on morphological characteristics and phylogenetic analysis of combined sequences of the internal transcribed spacer (ITS) of ribosomal DNA, β-tubulin (BenA), calmodulin (CaM), and RNA polymerase II second largest subunit (rpb2) genes. In the pathogenicity test, garlic bulbs inoculated with the isolated fungi exhibited symptoms similar to those observed during the postharvest storage period. In the fungicide screening test, carbendazim, difenoconazole + azoxystrobin, and difenoconazole effectively completely inhibited this fungus at both half and recommended dosages, while the fungus showed insensitivity to captan and mancozeb. Additionally, double-recommended dosages of carbendazim, copper oxychloride, difenoconazole combined with azoxystrobin, and difenoconazole alone exhibited complete inhibition of the fungus. To the best of our knowledge, this is the first report of postharvest blue mold disease on elephant garlic bulbs caused by P. allii in Thailand. Furthermore, the results of the fungicide sensitivity screening could help in developing effective management strategies for controlling postharvest blue mold disease on elephant garlic bulbs caused by P. allii.

  • Introduction

    Rice (Oryza sativa L.) is a world staple crop that feeds over half of the world's population[1,2]. In recent years, high-temperature events are becoming more frequent and intensive as a result of global warming, which can severely affect rice grain yield and quality[3,4]. During flowering and grain filling stages, high-temperature stress can result in a significant reduction in seed setting rate and influence amylose content, starch fine structure, functional properties and chalkiness degree of rice[5−7]. Transcriptome and proteome analysis in rice endosperm have also been used to demonstrate the differences in high-temperature environments at gene and protein expression levels[8−10]. In addition, as an important post-translational modification, protein phosphorylation has proven to be involved in the regulation of starch metabolism in response to high-temperature stress[11]. However, little is known about whether protein ubiquitination regulates seed development under high-temperature stress.

    Ubiquitination is another form of post-translational modification that plays key roles in diverse cellular processes[12]. Several reports have described the functions of ubiquitination in rice defense responses based on ubiquitome analysis. Liu et al.[13] investigated relationships between ubiquitination and salt-stress responses in rice seedlings using a gel-based shotgun proteomic analysis and revealed the potential important role of protein ubiquitination in salt tolerance in rice. Xie et al.[14] identified 861 peptides with ubiquitinated lysines in 464 proteins in rice leaf cells by combining highly sensitive immune affinity purification and high resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS). These ubiquitinated proteins regulated a wide range of processes, including response to stress stimuli. A later study revealed the relationships between ubiquitination status and activation of rice defense responses, and generated an in-depth quantitative proteomic catalog of ubiquitination in rice seedlings after chitin and flg22 treatments, providing useful information for understanding how the ubiquitination system regulates the defense responses upon pathogen attack[15]. Although many studies have shown that ubiquitination plays improtant roles in the heat response of plant[16,17], there has been little systematic discussion on the ubiquitome of rice endosperm in the context of global climate change.

    In this study, we examine the high-temperature induced ubiquitination change in two rice varieties with different starch qualities, through a label-free quantitative ubiquitome analysis. This study provides a comprehensive view of the function of ubiquitination in high-temperature response of rice developing seed, which will shed new light on the improvement of rice grain quality under heat stress.

    Materials and methods

    Plant materials

    Two indica rice varieties with different starch quality, 9311 and Guangluai4 (GLA4), were used as materials. 9311 is a heat-sensitive variety, which displays low amylose content with good starch quality; while GLA4 is known to be the parental variety of HT54, an indica breeding line with heat tolerance, and thus GLA4 is possibly heat tolerant, which shows high amylose content with poor starch quality[18,19]. Rice growth conditions, sample treatment and collection were conducted as previously described[11].

    Protein extraction

    Husk, pericarp and embryo were detached from immature rice grains on ice[20]. Rice endosperm was then ground with liquid nitrogen, and the cell powder was sonicated 10 rounds of 10 s sonication and 15 s off-sonication on ice in lysis buffer (6 M Guanidine hydrochloride, pH 7.8−8.0, 0.1% Protease Inhibitor Cocktail) using a high intensity ultrasonic processor. Following lysis, the suspension was centrifuged at 14,000 g for 40 min at 4 °C to remove the debris. The supernatant was collected, and the protein concentration was estimated using BCA assay (Pierce BCA Protein assay kit, Thermo Fisher Scientific, Waltham, MA, USA) before further analysis.

    Trypsin digestion

    The protein mixture was reduced by DTT with the final concentration of 10 mM at 37 °C for 1 h, alkylated by iodoacetamide with a final concentration of 50 mM at room temperature in the dark for 0.5 h, and digested by trypsin (1:50) at 37 °C for 16 h. Then the sample was diluted by adding trifluoroacetic acid (TFA) to the final concentration of 0.1%. The enzymatic peptides were desalted on a Sep-Pak C18 cartridge (Waters, Milford, MA, USA), concentrated by lyophilization and reconstituted in precooled IAP buffer (50 mM MOPS-NaOH PH 7.2, 10 mM Na2HPO4, 50 mM NaCl) for further analysis.

    Affinity enrichment of ubiquitinated peptides

    The peptides solution was incubated with prewashed K-ε-GG antibody beads (PTMScan Ubiquitin Remnant Motif (K-ε-GG) Kit), and gently shaken at 4 °C for 1.5 h. The suspension was centrifuged at 2,000 g for 30 s, and the supernatant was removed. The Anti-K-ε-GG antibody beads were washed with IAP Buffer three times and with ddH2O three times. The peptides were eluted from the beads with 0.15% trifluoroacetic acid (TFA). Finally, the eluted fractions were combined and desalted with C18 Stage Tips.

    LC-MS/MS and data analysis

    LC-MS/MS analysis were performed using the methods of Pang et al.[11]. Raw mass spectrometric data were analyzed with MaxQuant software (version 1.3.0.5) and were compared with the indica rice protein sequence database (Oryza sativa subsp. indica-ASM465v1). Parameters were set according to Pang et al.[11]. All measurements were obtained from three separate biological replicates.

    Bioinformatics methods

    Quantification of the modified peptides was performed using the label-free quantification (LFQ) algorithm[11]. Differentially ubiquitinated sites (proteins) in response to high-temperature were identified by Student's t-test (p < 0.05, log2(fold-change) > 1) with at least two valid values in any condition or the ubiquitination sites that exhibited valid values in one condition (at least two of three replicates) and none in the other.

    Subcellular localization was performed using CELLO database (http://cello.life.nctu.edu.tw). Gene Ontology (GO) annotation proteome was derived from the AgriGO (http://bioinfo.cau.edu.cn/agriGO/). The differential metabolic profiles were visualized with MapMan software (version 3.6.0RC1). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation was performed by using KEGG Automatic Annotation Server (KAAS) software. A p-value of < 0.05 was used as the threshold of significant enrichment. SWISS-MODEL was used to generate the tertiary structure of GBSSI (SWISS-MODEL, http://swissmodel.expasy.org/). The figures were annotated with Adobe Illustrator (Adobe Systems, San Jose, CA, USA).

    Results

    Overview of the ubiquitomic analysis

    To elucidate how high-temperature stress influences rice developing endosperm at the ubiquitination level, a label-free analysis was performed to quantify ubiquitome from two indica rice varieties under normal (9311-C and GLA4-C) and high-temperature conditions (9311-H and GLA4-H). The distribution of mass error of all the identified peptides was near zero and most of them (71.5%) were between -1 and 1 ppm, suggesting that the mass accuracy of the MS data fits the requirement (Fig. 1a). Meanwhile, the length of most peptides distributed between 8 and 42, ensuring that sample preparation reached standard conditions (Fig. 1b).

    Figure 1.  Characteristics of the ubiquitinated proteome of rice endosperm and QC validation of MS data. (a) Mass error distribution of all identified ubiquitinated peptides. (b) Peptide length distribution. (c) Frequency distribution of ubiquitinated proteins according to the number of ubiquitination sites identified.
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    In all endosperm samples, a total of 437 ubiquitinated peptides were identified from 246 ubiquitinated proteins, covering 488 quantifiable ubiquitinated sites (Supplemental Table S1). Among the ubiquitinated proteins, 60.6% had only one ubiquitinated lysine site, and 18.7%, 8.1%, 5.3%, or 7.3% had two, three, four, or five and more ubiquitinated sites, respectively. In addition, four proteins (1.6%, BGIOSGA004052, BGIOSGA006533, BGIOSGA006780, BGIOSGA022241) were ubiquitinated at 10 or more lysine sites (Fig. 1c, Supplemental Table S1). The proteins BGIOSGA008317 had the most ubiquitination sites with the number of 16. It was noted that besides ubiquitin, two related ubiquitin-like proteins NEDD8 and ISG15 also contain C-terminal di-Gly motifs generated by trypsin cleavage, and the modifications of these three proteins cannot be distinguished by MS[21]. Here, the di-Gly-modified proteome therefore represents a composite of proteins modified by these three proteins. However, the sites from NEDD8 or ISG15 modifications were limited because they mediate only a few reactions in cells[21].

    Properties of ubiquitinated proteins and motifs

    To better understand the lysine ubiquitome changes in rice endosperm induced by high-temperature, we performed a Gene Ontology (GO) functional annotation analysis on all identified ubiquitinated proteins (Fig. 2a). In the biological process GO category, 'metabolic process' and 'cellular process' were mainly enriched, accounting for 75.1% and 74.1% of ubiquitinated proteins, respectively. In addition, 34.6% proteins were associated with 'response to stimulu', emphasizing the regulatory role of ubiquitination modification in response to high-temperature stress. From the cellular component perspective, ubiquitinated proteins were mainly associated with 'cellular anatomical entity' (99.4%), 'intracellular' (84.4%) and 'protein-containing complex' (29.9%). The molecular function category result suggested that these proteins were largely involved in 'binding' (62.7%), 'catalytic activity' (43.4%) and 'structural molecule activity' (16.5%). Furthermore, subcellular location annotation information indicated that 34.7%−39.4% proteins were located in the cytoplasm, and other were mostly located in the nucleus (23.5%−27.7%), plasma membrane (9.4%−11.4%), and chloroplast (9.6%−12.8%) (Fig. 2b). It is noteworthy that the ubiquitinated proteins located in the cytoplasm were decreased in high-temperature environments in both varieties.

    Figure 2.  Analysis of ubiquitinated proteins and motifs. (a) Gene ontology (GO) functional characterization of ubiquitinated proteins. (b) Subcellular localization of ubiquitinated proteins. From the inside out, the ring represents 9311-C, 9311-H, GLA4-C and GLA4-H, respectively. (c) Motif enrichment analysis of ubiquitinated proteins.
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    The following two significantly enriched motifs from all of the identified ubiquitinated sites were identified using MoDL analysis: [A/S]xKub and Kubxx[E/Q/R/V]x[E/G/L/P/Q/R/Y], which covered 84 and 100 sequences, respectively (Fig. 2c). Further analysis showed that the conserved alanine (A) and glutamic acid (E) were included in upstream and downstream of the ubiquitinated lysine sites in rice endosperm. A similar phenomenon also occurred in rice leaf[14], wheat leaf[22], and petunia[23], indicating that alanine (A) and glutamic acid (E) were likely to be the specific amino acids in conserved ubiquitination motifs in plants. Additionally, serine (S) was enriched at the position -2 (upstream) of the ubiquitinated lysine, while various amino acids such as arginine (R), glutamic acid (E), glutamine (Q), valine (V) were found at positions +3 and +5 (downstream).

    A temperature-regulated rice endosperm ubiquitome

    To detect possible changes in rice endosperm ubiquitome attributable to high-temperature stress, we then performed LFQ analysis on all quantifiable ubiquitination sites within our dataset. As shown in Fig. 3a, more ubiquitinated proteins, peptides and sites were detected in the treatment groups (9311-H and GLA4-H), suggesting that exposure to high-temperature stress may increase the ubiquitination events in rice endosperm. Only 282 common ubiquitinated sites in 158 proteins were quantifiable for all sample groups due to reversible ubiquitination induced by high-temperature (Fig. 3b). Principal component analysis (PCA) showed that three repeats of each sample clustered together, and four groups were clearly separated (Fig. 3c). Furthermore, the differentially expression profiles of ubiquitination sites (proteins) in 9311 and GLA4 under high-temperature stress were depicted to further understand the possible changes (Fig. 3d). Where LFQ values were missing, the data were filtered to identify those ubiquitination sites with a consistent presence/absence expression pattern. These analyses yielded 89 ubiquitination sites that were only present in 9311-H and six that were only present in 9311-C (Fig. 3d, Supplemental Table S2). Similarly, 51 differentially expressed ubiquitination sites were present in GLA4-H and 13 ubiquitination sites only occurred in GLA4-C (Fig. 3d & Supplemental Table S3). Beyond that, a total of 113 and 50 significantly changed ubiquitination sites (p < 0.05, log2(fold-change) >1) were screened out in 9311 and GLA4, respectively (Fig. 3d, Supplemental Tables S4 & S5). For subsequent comparative analysis, the ubiquitination expression profiles with consistent presence/absence and ubiquitination sites with significant differences in statistical testing were combined and named as 9311-Up, 9311-Down, GLA4-Up, and GLA4-Down, respectively (Fig. 3d). The number of significantly up-regulated ubiquitination sites was far greater than down-regulated ubiquitination sites in both 9311 and GLA4 varieties. These findings indicated that high temperature not only induced the occurrence of ubiquitination sites, but also significantly upregulated the intensity of ubiquitination. Beyond that, the magnitude of the up-regulation in 9311 was higher than that in GLA4 (Fig. 3b & d), indicating that the ubiquitination modification of heat-sensitive varieties was more active than heat-resistant varieties in response to high-temperature stress.

    Figure 3.  A temperature regulated rice endosperm ubiquitome. (a) The number of ubiquitinated proteins, peptides and sites detected in four group samples. (b) Venn diagram of ubiquitination sites (proteins) detected in four group samples. (c) PCA based on ubiquitination intensity across all four sample groups with three biological repetitions. (d) Differentially expression profiles of ubiquitination sites (proteins) in 9311 and GLA4 under high-temperature stress. The expression profiles of selected ubiquitination sites (p < 0.05, log2(fold-change) >1) were normalized using the Z-score and presented in a heatmap.
    DownLoad: Full-Size Img PowerPoint

    To further investigate the ubiquitination regulatory pattern under high temperature stress in two varieties, four groups with significantly regulated sites were analyzed. There were 37 ubiquitination sites showed the same regulatory trend in 9311 and GLA4, accounting for 17.8% and 32.5% of the total differentially expressed sites in 9311 and GLA4, respectively. Among them, 36 ubiquitination sites were upregulated and one site was downregulated (Fig. 4a). In addition, 159 upregulated ubiquitination sites and three downregulated sites were only present in 9311, while 53 upregulated sites and 15 downregulated sites were only present in GLA4. Moreover, nine ubiquitination sites showed opposite regulatory trends in 9311 and GLA4. A similar regulatory trend of ubiquitination proteins is shown in Fig. 4b. It is noted that some proteins had both upregulated and downregulated ubiquitination sites (Supplemental Tables S6 & S7), indicating that significant differences in ubiquitination were, to some extent, independent of protein abundance.

    Figure 4.  Comparison of differentially ubiquitinated sites and proteins in 9311 and GLA4 under high-temperature stress.
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    Functions for differentially expressed ubiquitinated proteins

    To understand the function of ubiquitination in response to the high-temperature stress of rice endosperm, we conducted GO enrichment-based clustering analysis of the differentially ubiquitinated proteins in 9311 and GLA4 at high temperature, respectively (Fig. 5). In the biological process category of 9311, proteins were relatively enriched in the carbohydrate metabolic process, polysaccharide metabolic process, starch biosynthetic process, cellular macromolecule localization, protein localization, intracellular transport, and phosphorylation (Fig. 5). For the molecular function analysis, we found that the proteins related to kinase activity, nucleotidyltransferase activity, phosphotransferase activity, and nutrient reservoir activity were enriched (Fig. 5). The two principal cellular components were intrinsic component of membrane and integral component of membrane (Fig. 5). There was no significantly enriched GO term in the GLA4 group due to the dataset containing relatively few proteins, and thus, further enrichment analysis was conducted on the proteins that were common to both varieties. The results showed that proteins were over-represented in carbon metabolism, including starch biosynthesis and metabolism, glucan biosynthesis and metabolism, and polysaccharide biosynthesis and metabolism (Fig. 5), indicating the importance of carbohydrate synthesis and metabolism in the ubiquitination regulatory network.

    Figure 5.  Enrichment analysis of differentially expressed ubiquitinated proteins based on Gene Ontology (GO) terms.
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    To identify pathways which were differentially ubiquitinated under high-temperature stress, the KEGG pathway-based clustering analysis was conducted. The results showed that the differentially ubiquitinated proteins in both 9311 and GLA4 were mostly abundant in the pathways of carbohydrate metabolism, starch and sucrose metabolism, folding, sorting and degradation, translation, ribosome, and protein processing in endoplasmic reticulum (Fig. 6a). In the 9311 group, the pathways of carbohydrate metabolism, starch and sucrose metabolism, glycosyltransferases, glycolysis, and energy metabolism were enriched in the differentially ubiquitinated proteins (Fig. 6b); while there was no significantly enriched KEGG pathway in the GLA4 group. We further found the proteins that were common to both varieties were only significantly enriched in the starch and sucrose metabolism pathways (p = 0.04). The ubiquitination proteins involved in the starch and sucrose metabolism mainly include: sucrose hydrolysis (SUS, FK, UGPase), and starch synthesis (AGPase, GBSSI, BEI, BEIIb, PUL, PHO1), which are discussed below.

    Figure 6.  KEGG classification and enrichment analysis of differentially ubiquitinated proteins. (a) Number of differentially ubiquitinated proteins based on KEGG classification in 9311 and GLA4. (b) KEGG enrichment analysis of differentially ubiquitinated proteins in 9311.
    DownLoad: Full-Size Img PowerPoint

    Discussion

    Although many reports have described specific examples of ubiquitination in rice defense responses[13,15,16], our knowledge on global changes in the developing endosperm ubiquitome under high-temperature stress is still lacking. In this study, a label-free quantitative proteomic analysis of ubiquitination was applied to examine the high-temperature induced ubiquitination change of two indica rice varieties (9311 and GLA4) with distinct starch quality. We identified many new lysine modification sites on proteins involved in various pathways, highlighting the complexity of the ubiquitination-mediated regulatory system in high-temperature stress responses in rice.

    Ubiquitination of heat shock proteins and transcription factors under high-temperature stress

    Heat shock proteins accumulate under various stresses and play important roles in plant defenses against abiotic stresses[24,25]. Research has shown that a number of heat shock proteins were prominent in the rice ubiquitome network, of which OsHSP71.1, and OsHSP82A showed increased ubiquitination levels under chitin and flg22 treatment[15]. Here, seven lysine residues on five heat shock proteins possessed ubiquitination modification in rice endosperm. Three sites (BGIOSGA011420-K78, BGIOSGA026764-K99, BGIOSGA029594-K106) showed significant up-regulation in 9311 under high-temperature stress, while in GLA4, the ubiquitination level of BGIOSGA011420-K78 was down-regulated. This differential ubiquitination of heat-tolerant and heat-sensitive varieties provided a basis for studying the regulation of post-translational modification of heat shock proteins under high-temperature stress, despite the regulatory role of those heat shock proteins being still unclear.

    Transcription factors (TFs) play an essential role in the regulation of gene expression. A total of three transcription factors were identified in the ubiquitination dataset, of which two were NAC family members. As one of the largest plant-specific TF families, NAC is involved in the responses to abiotic and biotic stresses[26]. The ubiquitination modification of K173 in BGIOSGA018048 was specifically expressed in the 9311-H group, which may affect the stress resistance level in high-temperature environments. In addition, two sites K148 and K149 of ERF TF family member BGIOSGA024035 was downregulated in GLA4 under high-temperature stress. This differential ubiquitination was likely to affect the expression of related genes regulated by this transcription factor.

    Sucrose and starch metabolism are modified by ubiquitination under high-temperature stress

    Ubiquitination affects sucrose hydrolysis

    The results of GO and KEGG enrichment analysis of differential ubiquitination proteins indicated that the sucrose and starch metabolic pathway was largely affected by ubiquitination regulation under high-temperature stress (Figs 5 & 6). The ubiquitination sites involved in sucrose and starch metabolism are listed in Table 1. To assess how high-temperature stress affects the crucial pathway, the significantly differential ubiquitination sites in 9311 and GLA4 were displayed in the heatmap of specific proteins (Fig. 7).

    Table 1.  Ubiquitination sites related to sucrose and starch metabolism in rice endosperm.
    Gene nameAnnotationProtein entryModification site(s)
    SUS1Sucrose synthase 1BGIOSGA010570K172, K177
    SUS2Sucrose synthase 2BGIOSGA021739K160, K165, K176, K804
    SUS3Sucrose synthase 3BGIOSGA026140K172, K177, K541, K544, K588
    FKFructokinaseBGIOSGA027875K143
    UGPaseUDP-glucose pyrophosphorylaseBGIOSGA031231K27, K150, K303, K306
    AGPS1ADP-glucose pyrophosphorylase small subunit 1BGIOSGA030039K94, K464, K484
    AGPS2ADP-glucose pyrophosphorylase small subunit 2BGIOSGA027135K106, K132, K385, K403, K406, K476, K496
    AGPL2ADP-glucose pyrophosphorylase large subunit 2BGIOSGA004052K41, K78, K134, K191, K227, K254, K316, K338, K394, K396, K463, K508, K513
    AGPL3ADP-glucose pyrophosphorylase large subunit 3BGIOSGA017490K509
    GBSSIGranule bound starch synthase IBGIOSGA022241K130, K173, K177, K181, K192, K258, K371, K381, K385, K399, K462, K517, K530, K549, K571, K575
    BEIStarch branching enzyme IBGIOSGA020506K103, K108, K122
    BEIIbStarch branching enzyme IIbBGIOSGA006344K134
    PULStarch debranching enzyme:PullulanaseBGIOSGA015875K230, K330, K431, K736, K884
    PHO1Plastidial phosphorylaseBGIOSGA009780K277, K445, K941
     | Show Table
    DownLoad: CSV
    Figure 7.  Sucrose and starch pathway at the ubiquitination levels in rice endosperm under high-temperature stress.
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    In cereal endosperm, sucrose is the substrate for the biosynthesis of starch. The formation of glucose 1-phosphate (G1P, used in starch synthesis, see below) from sucrose requires a series of enzymes[27]. Here, we found that sucrose synthase 1 (SUS1), SUS2, SUS3, fructokinase (FK), and UDP-glucose pyrophosphorylase (UGPase) were ubiquitinated among all sample groups (Table 1, Fig. 7). In the ubiquitome of seedling and leaf in japonica rice, ubiquitination sites have been found in SUS1, SUS2, UGPase, and FK, which were related to sucrose hydrolysis[14,15]. SUS catalyzed the process of cleaving sucrose into UDP-glucose (UDPG) and fructose. Two ubiquitination sites, K172 and K177, were identified in SUS1 in rice endosperm, which were also found in rice leaves[14]. A total of four ubiquitination sites were identified in SUS2, two of which were also reported in rice seedling and leaf, indicating the conservation of the lysine residues in different rice tissues. It was noted that all four ubiquitination sites in SUS2 were upregulated in high-temperature environments, although the regulated sites of 9311 and GLA4 were different. In 9311, the ubiquitination levels of K160, K174, and K804 were increased, while GLA4 was only upregulated in K176. The ubiquitination sites K541, K544, and K588 in SUS3 were screened from developing rice seeds for the first time. In addition, SUS3 had two completely overlapping sites K172 and K177 with SUS1, and it was difficult to determine which enzymes the two sites belonged to. The ubiquitination levels of SUS3-K541 and SUS3-K544 in 9311 significantly increased in high-temperature environments, while there was no significant difference in the ubiquitination level of SUS3 in GLA4. Overall, the ubiquitination sites of SUS in rice endosperm were located in the functional domain except for SUS2-K804, reflecting the importance of ubiquitination regulation in SUS.

    UGPase catalyses the conversion of glucose 1-phosphate and UTP into UDPG[28]. Research has shown that the mutation of UGPase gene lead to chalky endosperm[29]. As shown in Table 1, four ubiquitination sites K27, K150, K303, and K306 were identified in rice endosperm, which were completely inconsistent with the seven ubiquitination sites in rice seedlings and two in leaves[14,15], reflecting the tissue specificity. We speculated that the UGPase with different modification sites may play different regulatory roles in metabolic pathways in different tissues. Under high-temperature stress, the ubiquitination level of UGPase-K27 was 8.1-fold up-regulated. Liao et al.[10] demonstrated that the expression of UDPase was down-regulated in both heat-tolerant and heat-sensitive rice lines under high temperature conditions, which could reasonably explain the significant up-regulation of UGPase-K27 ubiquitination level. The ubiquitination site K143 of FK was also reported in seedling tissues[15].

    Ubiquitination of ADP-glucose pyrophosphorylase (AGPase)

    The AGPase reaction represents the first committed step of starch biosynthesis[27]. A total of 22 lysine ubiquitination sites were identified in four AGPase subunits (AGPL2, AGPL3, AGPS1, AGPS2). AGPL2 had 13 ubiquitination sites, of which six were located in NTP_transferase domain, including K254, K338, K191, K134, K227, and K316. High-temperature stress resulted in an increase in the ubiquitination level of K254 in both 9311 and GLA4, and significant upregulation of K508 and K513 in 9311, as well as K191, K227, and K316 in GLA4. In contrast, AGPL2-K394 were significantly downregulated in GLA4. AGPL3 contained one ubiquitination site K509, and the modification level of AGPL3-K509 was up-regulated in high-temperature environments in 9311. AGPS1 had one specific ubiquitination site K464 and another two sites K94 and K484 that completely overlapped with AGPS2-K106 and AGPS2-K496, respectively. The modification levels of K464 and K484 significantly increased in high-temperature environments in 9311, and K94 was significantly up-regulated in both varieties. There were seven ubiquitination sites in AGPS2 in rice endosperm, which were different with the sites found in rice leaves[14]. In addition to the two sites that overlapped with AGPS1, AGPS2 had another two ubiquitination sites (K406 and K132) that upregulated in high-temperature environments.

    Ubiquitination regulates amylose biosynthesis

    Amylose content is one of the key determinants that strongly influence rice grain quality[30]. The biosynthesis of amylose requires the catalytic effect of granule-bound starch synthase I (GBSSI)[30,31]. Here, a total of 16 ubiquitination sites were identified in GBSSI (Table 1, Fig. 8a). Among these ubiquitination sites, six lysine residues (K130, K173, K177, K181, K192, K258) were located in glycosyltransferase 5 (GT5) domain, and three sites (K399, K462, K517) were located in GT1 domain (Fig. 6), indicating the important role of ubiquitination regulation of GBSSI. Under high-temperature stress, the ubiquitination levels of six sites (K130, K177, K399, K381, K385, K549) increased in two indica rice varieties, while one sites (K258) showed downregulation in 9311 (Fig. 8a). Numerous studies had described that the amylose content was reduced under high-temperature stress in rice[5,7], which might be due to the degradation of GBSSI proteins caused by the increased significantly up-regulated ubiquitination sites. These ubiquitination sites identified in rice GBSSI with significant differences under high-temperature stress were expected to become a new breakthrough point for the improvement of starch quality.

    Figure 8.  Structure of GBSSI. (a) Domain structure of GBSSI and ubiquitination sites with significant differences in response to high-temperature stress. (b) 3D model of GBSSI and the relationship between ubiquitination sites K462 and ADP, SO4 (salt bridge or hydrogen bond).
    DownLoad: Full-Size Img PowerPoint

    To further determine the regulatory role of the ubiquitination sites in GBSSI, SWISS-MODEL was used to predict 3D structural model. As shown in Fig. 8b, GBSSI had three SO4 (sulfate ions) and one ADP ligand. These ligands interact with GBSSI through hydrogen bonds and salt bridges. Three sites, K447, R458, and K462, were associated with SO4 through salt bridges, while G100, N265, Q412, K462, and Q493 interact with the hydrogen bonds of ADP in GBSSI[32,33]. Based on this finding, it can be reasonably inferred that the K462 site with ubiquitination modification located in the GT1 domain played an important role in the interaction between GBSSI, SO4, and ADP. An in-depth investigation was necessary to gain a more comprehensive understanding of the regulatory function of ubiquitination modification at GBSSI-K462, although there was no significant difference in the ubiquitination level under high-temperature stress.

    Ubiquitination regulates amylopectin biosynthesis

    Amylopectin, the major component of starch, is synthesized by the coordinated action of multiple enzymes including soluble starch synthase (SSs), starch branching enzyme (BEs), starch debranching enzyme (DBEs), and phosphorylases (PHOs or Phos) with ADPG as a substrate. In this study, ubiquitination sites were detected in BEs, DBEs, and Phos.

    BEs, covering two isoforms, BEI and BEII, are responsible for catalyzing the formation of α-1,6-glucosidic linkages of amylopectin[34]. There were three ubiquitination sites (K103, K108, and K122) identified in BEI (Fig. 9a). K122 was the first amino acid in the carbohydrate-binding module 48 (CBM48) domain. Sequence alignment analyses of BEs from eight plants revealed K122 was conserved among all plants' BEI (Fig. 9a), suggesting a high probability of the functional effects of ubiquitination modification at this site. In high-temperature environments, ubiquitination levels of K108 and K122 were significantly up-regulated in 9311, while no significantly regulated ubiquitination sites of BEI were observed in GLA4. Only one ubiquitination site, K134, was found in BEIIb (Fig. 9a). The ubiquitination levels showed a slightly upward trend with no significant differences in high-temperature environments in both varieties. These changes could be one of the reasons for increased gelatinization temperature and relative crystallinity of rice starch in response to high-temperature[5].

    Figure 9.  Domain structure of (a) BEs, (b) PUL and (c) Pho1 as well as their ubiquitination sites with significant differences in response to heat stress. Residues in red indicate the ubiquitination site. Non-ubiquitinated residues are shown in dark grey.
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    DBEs consists of isoamylase (ISA) and pullulanase (PUL) with catalytic function for hydrolyzing α-1,6-glucosic linkages[35]. In the present study, we found that only PUL was ubiquitinated in rice endosperm (Fig. 9b). Among five ubiquitination sites (K230, K330, K432, K736, and K884) identified in PUL, K230 was located in the PULN2 domain, while K330 was in the CBM48 domain. Under high-temperature stress, K330 showed completely opposite regulatory trends in two cultivars. In addition, the ubiquitination level of K884, located in the DUF3372 domain, was significantly up-regulated in 9311. Previous study has reported that the expression of PUL was significantly up-regulated in 9311 under high-temperature stress, while GLA4 showed down-regulation in PUL abundance[11]. Consequently, there might be two possible functions of these ubiquitination sites. One possibility is that ubiquitination sites were unrelated to protein degradation; instead, they regulated the biosynthesis of amylopectin by affecting other functions of the protein. Secondly, ubiquitination sites were associated with protein degradation, and the levels of ubiquitination modification were based on protein abundance, resulting in a completely consistent regulation of ubiquitination modification and protein abundance under high-temperature stress.

    PHOs, including two types, Pho1/PHO1 and Pho2/PHO2, are responsible for the transfer of glucosyl units from Glc-1-P to the non-reducing end of a-1,4-linked glucan chains[36]. Pho1 is a temperature-dependent enzyme and considered crucial not only during the maturation of amylopectin but also in the initiation process of starch synthesis[37,38]. The three ubiquitination sites (K277, K445, K941) identified in Pho1 were located in two phosphorylase domains. We found that two sites, Pho1-K277 and Pho1-K445, were only ubiquitinated in high-temperature environments in 9311 and GLA4, respectively. Pang et al.[11] has demonstrated that the protein abundance of Pho1 decreased under high-temperature stress, especially in GLA4. Satoh et al.[38] reported that the functional activity of Pho1 was weakened under conditions of high temperature and its function might be complement by one or more other factors. Hence, these ubiquitination modifications that specifically occurred in high-temperature environments might be related to the degradation of Pho1 proteins.

    Ubiquitination affects ribosomal systems under high-temperature stress

    As a factory for protein synthesis in cells, the ribosome is an extremely crucial structure in the cell[39]. It has been proven that multiple ribosomal subunits were abundantly ubiquitinated in Arabidopsis and wheat[22]. In the present study, 57 ubiquitination sites involving 33 ribosome subunits were identified in 40S and 60S ribosome complexes in rice. Under high-temperature stress, the ubiquitination levels of some sites were significantly upregulated or downregulated, implying that ubiquitination of ribosomal proteins is likely to be an important regulatory mechanism in high-temperature response in rice endosperm. The results of GO and KEGG enrichment analysis indicated that the ribosome system was one of the most active systems for ubiquitination regulation under high-temperature stress. We speculated that the ubiquitin-proteasome system might be involved in the removal of subunits or entire ribosomes that were improperly folded in high-temperature environments. As shown in Fig. 10, the S10e, L18Ae, S27Ae, L9e, S3e, S28e, S20e, and S2e subunits were significantly up-regulated in 9311, while L13e subunits showed a completely opposite regulatory trend at the ubiquitination sites K81 and K88. In GLA4, the ubiquitination levels of S10e, S27Ae, L10Ae, L9e, S3e, S2e, and L4e showed a significant increase, while the ubiquitination level of L17e was significantly down-regulated under high-temperature stress. A total of seven ubiquitination sites involving S10e, S27Ae, L9e, S3e, and S2e subunits were jointly up-regulated in both two varieties. These sites might be related to the degradation of improperly folded ribosome subunits under high-temperature stress, while other ubiquitination sites with variety specificity might be associated with ribosomal function.

    Figure 10.  Ribosome system at the ubiquitination levels in rice endosperm under high-temperature stress. Grey shadings represent ubiquitinated proteins with no significant differences under heat stress. Red and blue shadings indicate up-regulated and down-regulated ubiquitinated proteins, respectively. Orange shading displays a combination of up- and down-regulated ubiquitinated sites in the same ubiquitinated protein.
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    In conclusion, this study provides the first comprehensive view of the ubiquitome in rice developing endosperm, and demonstrated that ubiquitination has diverse functions in the high-temperature response of rice endosperm by modulating various cellular processes, especially the sucrose and starch metabolism. Comparative analysis of the temperature-induced ubiquitination status revealed some similarities and more interesting differences between 9311 and GLA4. These differences might be the reason for the different qualities formation of the two indica rice varieties, which could provide potential genetic resources for the improvement of the heat resistance in rice. Considering the diversity of ubiquitination modification, it is worthwhile to further validate and explore the function and regulatory mechanism of the key targets and key pathways. The findings provide valuable insights into the role of ubiquitination in response to high-temperature stress and lay a foundation for further functional analysis of lysine ubiquitination in rice.

    Author contributions

    The authors confirm contribution to the paper as follows: study conception and design: Bao J, Pang Y; data collection: Pang Y; analysis and interpretation of results: Pang Y; draft manuscript preparation: Ying Y; Revised manuscript preparation: Ying Y, Pang Y, Bao J. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

    Acknowledgments

    This work was financially supported by the AgroST Project (NK2022050102) and Zhejiang Provincial Natural Science Foundation (LZ21C130003).

  • The authors declare that they have no conflict of interest.

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  • Cite this article

    Suwannarach N, Khuna S, Chaiwong K, Senwanna C, Nuangmek W, et al. 2024. Identification and fungicide sensitivity of the blue mold pathogen in postharvest-stored elephant garlic bulbs in Thailand. Studies in Fungi 9: e015 doi: 10.48130/sif-0024-0015
    Suwannarach N, Khuna S, Chaiwong K, Senwanna C, Nuangmek W, et al. 2024. Identification and fungicide sensitivity of the blue mold pathogen in postharvest-stored elephant garlic bulbs in Thailand. Studies in Fungi 9: e015 doi: 10.48130/sif-0024-0015
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Identification and fungicide sensitivity of the blue mold pathogen in postharvest-stored elephant garlic bulbs in Thailand

  • 1.

    Office of Research Administration, Chiang Mai University, Chiang Mai 50200, Thailand

  • 2.

    Center of Excellence in Microbial Diversity and Sustainable Utilization, Chiang Mai University, Chiang Mai 50200, Thailand

  • 3.

    Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand

  • 4.

    Department of Microbiology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand

  • 5.

    School of Agriculture and Natural Resources, University of Phayao, Phayao 56000, Thailand

  • Received: 05 November 2024
  • Revised: 25 November 2024
  • Accepted: 26 November 2024
  • Published online: 20 December 2024
Studies in Fungi  9,  Article number: e015  (2024)  |  Cite this article

Abstract: Blue mold disease is one of the most important postharvest diseases affecting garlic bulbs. In 2023, this disease was found on bulbs of elephant garlic [Allium ampeloprasum var. ampeloprasum (Borrer) Syme] in Chiang Mai Province, Thailand, during the postharvest storage period. Three fungal isolates were obtained and identified as Penicillium allii based on morphological characteristics and phylogenetic analysis of combined sequences of the internal transcribed spacer (ITS) of ribosomal DNA, β-tubulin (BenA), calmodulin (CaM), and RNA polymerase II second largest subunit (rpb2) genes. In the pathogenicity test, garlic bulbs inoculated with the isolated fungi exhibited symptoms similar to those observed during the postharvest storage period. In the fungicide screening test, carbendazim, difenoconazole + azoxystrobin, and difenoconazole effectively completely inhibited this fungus at both half and recommended dosages, while the fungus showed insensitivity to captan and mancozeb. Additionally, double-recommended dosages of carbendazim, copper oxychloride, difenoconazole combined with azoxystrobin, and difenoconazole alone exhibited complete inhibition of the fungus. To the best of our knowledge, this is the first report of postharvest blue mold disease on elephant garlic bulbs caused by P. allii in Thailand. Furthermore, the results of the fungicide sensitivity screening could help in developing effective management strategies for controlling postharvest blue mold disease on elephant garlic bulbs caused by P. allii.

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    Introduction

    • Garlic (Allium spp.), especially the bulb, is commonly consumed and valued for both culinary and medicinal purposes due to its nutritional richness and numerous beneficial bioactive compounds essential for human health[1−3]. Elephant garlic [Allium ampeloprasum var. ampeloprasum (Borrer) Syme], hardneck garlic [A. sativum var. ophioscorodon (Link) Döll], and softneck garlic (A. sativum var. sativum L.) are popular varieties that have been cultivated worldwide[4,5]. In 2022, global garlic production reached 2.91 million tons, valued at 3.43 billion USD. China was the largest producer, contributing 2.13 million tons (73% of world production), followed by India with 0.3 million tons, Bangladesh with 0.05 million tons, and Egypt with 0.03 million tons[6]. Myanmar is the top garlic producer in Southeast Asia followed by Thailand and Indonesia[6]. At every stage of growth, harvesting, and post-harvest storage, garlic is susceptible to various diseases caused by bacteria, fungi, and viruses[7−9]. Diseases can significantly damage garlic bulb production and quality[9,10]. Blue mold disease, caused by Penicillium species, is a common issue affecting garlic bulbs during both the cultivation process and postharvest storage[9,11−14]. This disease can lead to significant customer dissatisfaction and economic losses in garlic production worldwide[9,11,14,15].

      In Thailand, the northern part is the main region for garlic cultivation[16]. Nowadays, elephant garlic is a significant vegetable crop extensively cultivated in Thailand. Thus, the area of plantations used for growing garlic has significantly increased in Thailand. However, the incidence and severity of diseases have also increased when plants are grown in sub-optimal areas and unsuitable storage conditions. In 2023, blue mold disease caused by fungi was observed on elephant garlic bulbs during the storage period in Chiang Mai Province in Thailand, with a degree of incidence within the range of 20% to 30%. Importantly, there had been no prior reports of blue mold disease on elephant garlic bulbs in Thailand. Therefore, the objective of this study was to isolate the causal fungal agents of this disease. The isolated fungi were identified using both morphological and molecular data. Pathogenicity tests were conducted, and Koch's postulates were applied to assess the effects of the isolated fungi on asymptomatic elephant garlic bulbs. Moreover, the sensitivity of the isolated fungi to several commercial fungicides was investigated using solid culture techniques.

    Materials and methods

      Sample collection

    • Blue mold disease was observed on elephant garlic bulbs (A. ampeloprasum var. ampeloprasum) throughout the postharvest storage at 25 to 30 °C and 65% to 75% relative humidity over a period of 7 to 14 d in Chiang Mai Province, northern Thailand in 2023 (March to April). Garlic bulbs exhibiting typical symptoms were collected from postharvest storage stores and shipped to the laboratory within 24 h. After being transferred to the laboratory, symptomatic bulbs were examined using a stereo microscope (Nikon H55OS, Tokyo, Japan) and stored in a plastic container with moist filter paper to promote fungal sporulation.

      Fungal isolation and morphological study

    • Samples of bulb disease were processed to isolate the fungal causal agents. The single conidial isolation method described by Choi et al.[17] was used to isolate the causal fungi from the lesions. This process was conducted on 1.0% water agar containing 0.5 mg/L streptomycin. The individual germinated conidia were observed after incubation at 25 °C for 24–48 h and then transferred directly onto potato dextrose agar (PDA; CONDA, Madrid, Spain) supplemented with 0.5 mg/L streptomycin under a stereo microscope. Pure cultures were deposited in the Culture Collection of Sustainable Development of Biological Resources (SDBR) Laboratory, Faculty of Science, Chiang Mai University, Thailand. The characteristics of the fungal colonies, including colony morphology, pigmentation, and odor, were examined on PDA, Czapek yeast extract agar (CYA), and malt extract agar (MEA; Difco, France) after incubation in the dark for 7 d at 25 °C. Micromorphological characteristics were assessed using a light microscope (Nikon Eclipse Ni-U, Tokyo, Japan). The Tarosoft® Image Frame Work software was used to measure at least 50 samples for each anatomical structure (such as conidiophores, phialides, and conidia).

      DNA extraction, PCR amplification, and sequencing

    • Genomic DNA was extracted from the fungal cultures of each isolate that grew on PDA at 25 °C for 5 d, using a Fungal DNA Extraction Kit (FAVORGEN, Ping-Tung, Taiwan) according to the manufacturer's protocol. Amplification of the internal transcribed spacer (ITS) of ribosomal DNA, β-tubulin (BenA), calmodulin (CaM), and RNA polymerase II second largest subunit (rpb2) genes using ITS5/ITS4[18], Bt2a/Bt2b[19], CF1/CF4[20], and RPB2-5F/RPB2-7CR[21], respectively. The PCR for these four genes was conducted in separate PCR reactions and consisted of an initial denaturation at 95 °C for 3 min, followed by 35 cycles of denaturation at 95 °C for 30 s, annealing at 52 °C for 30 s (ITS and BenA); 51 °C for 1 min (CaM) and 52 °C for 1 min (rpb2), extension at 72 °C for 1 min, and final extension at 72 °C for 10 min on a peqSTAR thermal cycler (PEQLAB Ltd., Fareham, UK). PCR products were checked on 1% agarose gel electrophoresis and purified using a PCR clean-up Gel Extraction NucleoSpin® Gel and a PCR Clean-up Kit (Macherey-Nagel, Düren, Germany), according to the manufacturer's instructions. The purified PCR products were directly sequenced. Sequencing reactions were performed, and the above-mentioned PCR primers were employed to automatically determine the sequences in the Genetic Analyzer at the 1st Base Company (Kembangan, Malaysia).

      Sequence alignment and phylogenetic analyses

    • The analysis of the ITS, BenA, CaM, and rpb2 sequences was conducted with the use of similarity searches employing the BLAST program available at NCBI (http://blast.ddbj.nig.ac.jp/top-e.html, accessed on 10 July 2024). The sequences from this study and those obtained from previous studies, together with sequences downloaded from the nucleotide GenBank database are listed in Table 1. Multiple sequence alignment was performed with MUSCLE[22] and improved where necessary using BioEdit v. 6.0.7[23]. Finally, the combination datasets of ITS, BenA, CaM, and rpb2 sequences were performed.

      Table 1.  Details of sequences in Penicillium section Fasciculata used in molecular phylogenetic analysis.

      Penicillium species Strain/isolate GenBank accession number
      ITS BenA CaM rpb2
      P. albocoremium CBS 472.84T AJ004819 AY674326 KUJ896819 KU904344
      P. allii CBS 131.89T ‒ AY674331 KU896820 KU904345
      P. allii SDBR-CMU499 PP998350 PQ032853 PQ032856 PQ032859
      P. allii SDBR-CMU500 PP998351 PQ032854 PQ032857 PQ032860
      P. allii SDBR-CMU501 PP998352 PQ032855 PQ032858 PQ032861
      P. aurantiogriseum CBS 324.89 AF033476 AY674296 KU896822 JN406573
      P. camemberti MUCL 29790T AB479314 FJ930956 KU896825 JN121484
      P. cavernicola CBS 100540T MH862709 KJ834439 KU896827 KU904348
      P. caseifulvum CBS 101134T MH862722 AY674372 KU896826 KU904347
      P. commune CBS 311.48T AY213672 AY674366 KU896829 KU904350
      P. concentricum CBS 477.75T KC411763 AY674413 DQ911131 KT900575
      P. coprobium CBS 561.90T DQ339559 AY674425 KU896830 KT900576
      P. discolor CBS 474.84T OW986149 AY674348 KU896834 KU904351
      P. echinulatum CBS 317.48T MH856364 AY674341 DQ911133 KU904352
      P. freii CBS 476.84T MH861769 KU896813 KU896836 KU904353
      P. gladioli CBS 332.48T AF033480 AY674287 KU896837 JN406567
      P. glandicola CBS 498.75T AB479308 AY674415 KU896838 KU904354
      P. griseofulvum CBS 185.27T AF033468 AY674432 JX996966 JN121449
      P. hirsutum CBS 135.41T AY373918 AF003243 KU896840 JN406629
      P. hordei CBS 701.68T MN431391 AY674347 KU896841 KU904355
      P. italicum CBS 339.48T KJ834509 AY674398 DQ911135 ‒
      P. melanoconidium CV1331 JX091410 JX091545 JX141587 KU904358
      P. neoechinulatum CBS 101135T JN942722 AF003237 KU896844 JN985406
      P. nordicum DTO 098-F7 KJ834513 KJ834476 KU896845 KU904359
      P. palitans CBS 107.11T KJ834514 KJ834480 KU896847 KU904360
      P. polonicum CBS 222.28T AF033475 AY674305 KU896848 JN406609
      P. solitum CBS 424.89T AY373932 AY674354 KU896851 KU904363
      P. thymicola CBS 111225T KJ834518 AY674321 FJ530990 KU904364
      P. tricolor CBS 635.93T MH862450 AY674313 KU896852 JN985422
      P. ulaiense CBS 210.92T KC411695 AY674408 KUB96854 KU904365
      P. verrucosum CBS 603.74T AY373938 AY674323 DQ911138 JN121539
      P. vulpinum CBS 126.23T AF506012 KJ834501 KU896857 KU904367
      Ex-type species are indicated by the superscript letters as 'T'. '−' indicates the absence of sequencing information in GenBank. The fungal isolates and sequences obtained in this study are in bold.

      For phylogenetic analyses, Penicillium italicum (CBS 339.48) and P. ulaiense (CBS 210.92) were selected as the outgroup. The maximum likelihood (ML) analysis was carried out using RAxML-HPC2 version 8.2.12 on the GTRCAT model with 25 categories and 1000 bootstrap (BS) replications[24,25] via the CIPRES web portal. Bayesian inference (BI) analysis was performed with MrBayes v. 3.2.6 software for Windows[26]. The best substitution model for BI analysis was estimated using the jModelTest 2.1.10[27] by employing the Akaike information criterion (AIC). Bayesian posterior probability (PP) was determined by Markov Chain Monte Carlo Sampling (MCMC). Four simultaneous Markov chains were run for a million generations with random initial trees, wherein every 100 generations were sampled. The first 25% of generated trees representing the burn-in phase of the analysis were eliminated, while the remaining trees were used for calculating PP in the majority-rule consensus tree. The phylogenetic trees were visualized using FigTree v1.4.0[28].

      Pathogenicity tests

    • Conidia from fungal isolates cultivated for two weeks on PDA were used in this experiment. Healthy commercial elephant garlic bulbs were washed thoroughly, and then their surfaces were sterilized by soaking them for 5 min in a sterile sodium hypochlorite solution with a concentration of 1.5% (v/v). Following that, sterile distilled water was used to wash them three times. The bulbs were allowed to air-dry at room temperature (25 ± 2 °C) for 10 min after surface disinfection. Following the air-drying process, a quantity of 10 μL of a conidial suspension (1 × 106 conidia/mL) in sterile water from each fungal isolate was dropped onto each bulb. Consequently, sterile distilled water was used as an inoculant for the control. The inoculated bulbs were placed in individual 4 L sterile plastic boxes maintained at 80% relative humidity. These containers were kept in a growth chamber at a temperature of 25 °C under a 12-h light cycle for one week. A total of ten replicates were used for each treatment, which was repeated twice under the same conditions. The disease symptoms were observed. Confirmation of Koch's postulates was achieved by re-isolating the fungi through the isolation method from any lesions that occurred on the inoculated bulbs.

      Screening of commercial fungicides against the causal agent

    • Seven commercially available fungicides, including benalaxyl-M (4%) + mancozeb (65%) (Fantic M WG®, Thailand), captan (Captan 50®, Thailand), carbendazim (Dazine®, Thailand), copper oxychloride (Copina 85 WP®, Thailand), difenoconazole (12.5%) + azoxystrobin (20%) (Ortiva®, Thailand), difenoconazole (Score®, Thailand), and mancozeb (Newthane M-80®, Thailand), were examined in this study according to the approach indicated through previous studies[29,30]. The fungicides used in this study were available commercially in Thailand and were approved for usage. The in vitro applications of benalaxyl-M + mancozeb, captan, carbendazim, copper oxychloride, difenoconazole + azoxystrobin, difenoconazole, and mancozeb were recommended at dosages of 1,380, 750, 750, 1,700, 243.75, 187.5, and 1,200 ppm, respectively, according to the labels for each fungicide. The final concentration was obtained by preparing each fungicide and adding it to an autoclaved PDA. Each fungicide was used in three different dosages: half-recommended, recommended, and double-recommended. The test media were inoculated with mycelial plugs (5 mm in diameter) that had been cultivated on PDA in the dark at 25 °C for one week. The control did not add any fungicide. The plates were maintained in darkness at a temperature of 25 °C. Following one week of incubation, the mycelial growth of each isolate was evaluated on individual plates and a comparison was made between the growth in PDA supplemented with fungicides and the growth observed in the control. The calculation of the percentage growth inhibition for each isolate was performed using the formula provided by Pandey et al.[31]. Each isolate was classified as sensitive (> 50% inhibition), insensitive (< 50% inhibition), or totally inhibited (100% inhibition) based on their growth inhibition rates[30,31]. Five replicates were conducted for each fungicide and fungal isolate, and the experiments were independently repeated twice under the same biological conditions.

      Statistical analysis

    • The Shapiro-Wilk test in SPSS software version 26 was used to examine data from the two repeated fungicide sensitivity experiments at a significant level of p < 0.05 to perform the normality test. The results indicated non-significant findings, so the data from these repeated experiments were assessed for the assumptions of one-way analysis of variance (ANOVA). Duncan's Multiple Range Test (DMRT) was then used to identify significant differences at p ≤ 0.05.

    Results

      Disease symptoms

    • Initial symptoms, water-soaked areas on the outer surface of scales were observed. Later, white mycelium and blue powdery mold develop on the surface of the lesions (Fig. 1a). These lesions appear as brown, tan, or grey colored areas when the bulbs are cut. In advanced stages, infected bulbs disintegrated into a watery rot.

      Figure 1. 

      (a) Natural symptoms of blue mold disease on bulbs of elephant garlic by Penicillium allii . Colonies of Penicillium allii SDBR-CMU499 after incubation at 25 °C for one week. (b) PDA. (c) CYA. (d) MEA. (e)–(g) Conidiophores. (h) Conidia. Scale bars: (a)–(d) = 10 mm, (e)–(h) = 10 μm.

      Fungal isolation and morphological characteristics

    • Three fungal isolates (CMU499, CMU500, and CMU501) with similar morphology were obtained and deposited at the SDBR-CMU under accession numbers SDBR-CMU499, SDBR-CMU500, and SDBR-CMU501, respectively. Colonies PDA, CYA, and MEA were 29–32, 32–37, and 33–37 mm in diameter, respectively after incubation for one week at 25 °C (Fig. 1b–d). Colonies on PDA and MEA were white, flat with entire edges, conidium turquoise, white in the center, dull green at the margins; reverse pale yellow for PDA and yellow-brown for MEA. Colonies on CYA were white, flat with entire edges, conidium dull green; reverse white. All fungal isolates could produce conidiophores, and phialides, and sporulate in all of the agar media. Conidiophores terverticillate (Fig. 1e–g). Stipes rough-walled, 13.2–181.2 × 2.3–3.9 μm. Rami one or two, rough-walled and appressed or divergent, 8.4–24.7 × 2.5–4.6 μm. Metulae divergent, in verticils of 2–4, 8–19.1 × 2.3–4.6 μm. Phialides ampulliform, in verticils of 3 to 9, 6–17.9 × 1.7–6.9 μm. Conidia globose, 2.6–4.3 μm in diameter, smooth-walled, dull green (Fig. 1h). Based on these morphological characteristics, all fungal isolates were initially identified as belonging to Penicillium[32−35]. Fungal identification was then further confirmed using multi-gene phylogenetic analyses.

      Phylogenetic analysis

    • The ITS, BenA, CaM, and rpb2 sequences obtained from three fungal isolates in this study have been deposited in GenBank (Table 1). According to the BLAST results, all fungal isolates were identified as members of the Penicillium section Fasciculata. The combined ITS, BenA, CaM, and rpb2 sequences dataset consists of 32 taxa, and the aligned dataset includes 2,399 characters comprising gaps (ITS: 1–553, BenA: 554–927, CaM: 928–1,442, and rpb2: 1,443–2,399). The best-scoring RAxML tree was established with a final ML optimization likelihood value of –9,279.455311. Accordingly, the matrix contained 612 distinct alignment patterns with 5.04% undetermined characters or gaps. The estimated base frequencies were found to be: A = 0.235164, C = 0.269054, G = 0.262373, and T = 0.233408; substitution rates AC = 1.298254, AG = 4.466196, AT = 1.340638, CG = 0.787838, CT = 9.362594, and GT = 1.00000. The values of the gamma distribution shape parameter alpha and the Tree-Length were 0.580385 and 0.524602, respectively. Additionally, BI analysis yielded a final average standard deviation of 0.002257 for the split frequencies at the end of all MCMC generations. Regarding topology, the phylogenetic trees generated from both ML and BI analyses were similar. Consequently, the phylogenetic tree obtained from the ML analysis was selected and is displayed in Fig. 2. The results indicated that three fungal isolates SDBR-CMU499, SDBR-CMU500, and SDBR-CMU501 clustered with P. allii CBS 131.89 (ex-type strain) with strong statistical (100% BS and 1.0 PP) supports. Therefore, all fungal isolates obtained in this were identified as P. allii based on morphological and molecular data.

      Figure 2. 

      Phylogram derived from maximum likelihood analysis of the combined ITS, BenA, CaM, and rpb2 sequences of 30 taxa in the Penicillium section Fasciculata and two taxa in the Penicillium section Penicillium. Penicillium italicum CBS 339.48 and P. ulaiense CBS 210.92 were used as outgroups. Bootstrap values ≥ 50% (left) and Bayesian posterior probabilities ≥ 0.90 (right) are displayed above nodes. The scale bar represents the expected number of nucleotide substitutions per site. The sequences of fungal species obtained in this study are in red. The ex-type strain are in bold.

      Pathogenicity tests

    • The initial symptoms appeared on bulbs of elephant garlic 3 d after being inoculated. After 7 d, all inoculated bulbs displayed powdery mold at their centers, surrounded by orange-brown water-soaked lesions (Fig. 3b‒d). Whereas, control bulbs were asymptomatic (Fig. 3a). Penicillium allii was consistently reisolated from the inoculated bulbs on PDA to complete Koch's postulates.

      Figure 3. 

      Pathogenicity test using Penicillium allii SDBR-CMU499, SDBR-CMU500, and SDBR-CMU501 on bulbs of elephant garlic after one week inoculation at 25 °C. (a) Control bulbs treated with sterile distilled water instead of inoculum. Blue mold disease on bulbs of elephant garlic after inoculation of isolate (b) SDBR-CMU499, (c) SDBR-CMU500, and (d) SDBR-CMU501. Scale bar: 10 mm.

      Reactions of commercial fungicides against Penicillium allii

    • Seven commercially available fungicides in Thailand were tested in this study. After one week, the mycelial growths in response to the fungicides at three different dosages, including half-recommended (1/2RD), recommended (RD), and double-recommended (2RD) were calculated and presented in Table 2. The results revealed that the growth inhibition values varied across different fungicides, dosages, and fungal isolates. Data on the percentage of mycelial inhibition for each fungal isolate, related to the fungicides, passed the normality test (Shapiro-Wilk test, p < 0.001), thereby assuming normal distributions. Therefore, ANOVA followed by DMRT (p ≤ 0.05) was used to identify significant differences. The findings indicated that all fungal isolates were completely inhibited by carbendazim, difenoconazole + azoxystrobin, and difenoconazole at all tested dosages (Table 2). In the tests for captan and mancozeb, all isolates demonstrated sensitivity to 2RD. Therefore, based on the recommended dosages, carbendazim, difenoconazole + azoxystrobin, and difenoconazole could be effectively applied to control this pathogen.

      Table 2.  Percentage of mycelial inhibition and reactions of three isolates of Penicillium allii against fungicides.

      Fungicides Dosages Inhibition of mycelial growth (%)* Reaction
      SDBR-CMU499 SDBR-CMU500 SDBR-CMU501
      Benalaxyl-M + mancozeb 1/2RD 30.08 ± 1.41 c 29.27 ± 2.25 c 30.08 ± 2.53 c Insensitive
      RD 55.28 ± 1.41 b 56.10 ± 3.62 b 60.16 ± 1.67 b Sensitive
      2RD 82.11 ± 2.82 a 83.74 ± 1.41 a 83.74 ± 3.45 a Sensitive
      Captan 1/2RD 2.44 ± 3.50 c 1.63 ± 2.41 c 2.44 ± 1.25 c Insensitive
      RD 4.88 ± 2.25 b 4.88 ± 2.23 b 5.69 ± 2.30 b Insensitive
      2RD 72.36 ± 1.60 a 73.93 ± 3.45 a 73.98 ± 2.82 a Sensitive
      Carbendazim 1/2RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      2RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      Copper oxychloride 1/2RD 61.79 ± 1.60 c 58.54 ± 1.05 c 56.91 ± 1.41 f Sensitive
      RD 68.29 ± 1.20 b 68.29 ± 2.05 b 68.29 ± 2.54 d Sensitive
      2RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      Difenoconazole + azoxystrobin 1/2RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      2RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      Difenoconazole 1/2RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      2RD 100 ± 0 a 100 ± 0 a 100 ± 0 a Inhibition
      Mancozeb 1/2RD 19.51 ± 2.44 c 22.76 ± 3.73 c 21.14 ± 1.41 c Insensitive
      RD 47.15 ± 1.45 b 47.15 ± 2.82 b 43.90 ± 2.44 b Insensitive
      2RD 58.54 ± 2.44 a 54.47 ± 1.42 a 55.28 ± 1.45 a Sensitive
      * Results are means of five replicates ± standard deviation with the independently repeated twice. Data with different letters within the same column for each fungal isolate and fungicide indicate a significant difference at p ≤ 0.05 according to Duncan's multiple range test. 1/2RD, RD, and 2RD indicate half of the recommended dosage, recommended dosage, and double the recommended dosage, respectively.
    Discussion

    • Penicillium species are widely recognized as one of the most significant genera, known to cause major diseases in numerous economically valuable crops cultivated worldwide, including garlic[9,10,12,13,36]. Traditionally, Penicillium species have been identified using both macromorphological and micromorphological characteristics. However, morphological traits alone are insufficient to differentiate closely related Penicillium species due to the extensive range of morphological variations. Therefore, molecular techniques are crucial for accurately identifying Penicillium at the species level. Several previous studies have utilized a combination of ribosomal DNA (ITS) and protein-coding genes (BenA, CaM, rpb1, and rpb2) as powerful tools to identify Penicillium species since species-level identification remained unresolved when used solely on the ribosomal DNA gene[32,34,35,37]. In this study, three isolates of P. allii were obtained from the rot lesions of blue mold disease on elephant garlic bulbs in northern Thailand. The identification of this fungal species followed methods similar to those used for identifying Penicillium, which involve combining phylogenetic analysis of multiple genes with their morphological characteristics.

      In this study, Koch's postulates were fulfilled by conducting pathogenicity tests on all isolates of P. allii. The findings demonstrate that postharvest blue mold disease on elephant garlic bulbs in northern Thailand, caused by P. allii identified in this study resembles the disease caused by previously identified Penicillium pathogens, particularly P. hirsutum, which affects garlic bulbs worldwide[11−13,36]. Penicillium polonicum has been reported as a causal agent of blue mold on stored garlic bulbs in Pakistan[38]. Penicillium allii was known to cause postharvest blue mold disease on garlic bulbs in Argentina[15,39,40]. In the USA, P. albocoremium, P. expansum, P. glabrum, P. paraherquei, and P. radicicola can cause blue mold on garlic bulbs[13]. In Korea, blue mold disease on garlic bulbs caused by P. hirsutum has been reported[41]. Five Penicillium species, namely P. allii, P. glabrum, P. italicum, P. polonicum, and P. psychrotrophicum were identified and confirmed as postharvest pathogens causing blue mold rot of garlic in Serbia[42]. Recently, P. allii was the most virulent pathogen causing blue mold disease of elephant garlic bulbs in Italy, accounting for 95% of cases, followed by P. citrinum (4%) and P. brevicompactum (1%)[43]. Before this study, there were no reports of blue mold disease on elephant garlic bulbs in Thailand. Thus, this represents the first report of postharvest blue mold disease on elephant garlic bulbs caused by P. allii in Thailand.

      To manage and control fungal-caused plant diseases, a variety of fungicides have been used. Several studies have documented the effectiveness of fungicides in affecting sensitive, resistant strains of plant pathogenic fungi, particularly those in the Penicillium species, on their in vitro mycelial growth[44−46]. In this study, the sensitivity and inhibition of P. allii to fungicides varied among different fungicides and dosages. These findings are consistent with previous studies, which reported that the sensitivity and inhibition of Penicillium species to fungicides varies based on the type and dosage of the fungicide, as well as fungal species[46−48]. Before this study, prochloraz had been used against P. allii to control diseases related to sprouting germination in Europe[49]. In this study, carbendazim, difenoconazole + azoxystrobin, and difenoconazole at both half and recommended dosages exhibited complete inhibition of P. allii. The information on the in vitro inhibition, sensitivity, and resistance of fungicides against P. allii, which causes postharvest blue mold disease on elephant garlic bulbs, would be beneficial for in vivo applications and for managing this disease in Thailand and globally. However, environmental factors and the fungicide's metabolism in the plant can cause the results of in vitro fungicide testing to differ from in vivo responses. Therefore, further studies are required to conduct in vivo fungicide sensitivity and disease inhibition assays based on the in vitro findings. Additionally, several previous studies have established that fungicide-resistant strains are a result of both excessive and prolonged fungicide treatment[50−52]. Utilizing biological control agents, rotating crops, adhering to fungicide treatment guidelines, and maintaining cleanliness in fields, equipment, and storage spaces are all essential components of a comprehensive strategy to reduce fungicide resistance in fungi[9,50,53,54].

    Conclusions

    • Garlic blue mold disease, caused by Penicillium species, leads to significant economic losses during postharvest storage worldwide. In the present study, P. allii was isolated from infected bulbs of elephant garlic in northern Thailand. The identification of this fungi involved the analysis of their morphological characteristics and conducting multi-gene phylogenetic analyses. The assessment of pathogenicity for P. allii showed similar symptoms throughout the artificial inoculation process, as observed during the postharvest storage period. Therefore, this study represents the first report of elephant garlic blue mold disease caused by P. allii in Thailand. In the fungicide screening test, carbendazim, difenoconazole + azoxystrobin, and difenoconazole were found to effectively control this pathogen at both half and full recommended dosages. Thus, half of the recommended dosages can be used in managing this disease, serving as a guideline for prevention and helping to reduce pathogen resistance to fungicides. The findings of this study will enhance our understanding of postharvest blue mold disease in elephant garlic bulbs and provide insights for developing effective management strategies and prevention methods to minimize significant economic losses. Further research on the epidemiology of this disease would be required for effective monitoring, prevention, and control.

      Acknowledgments

      • The authors sincerely appreciate the financial support provided by Chiang Mai University, Thailand and the University of Phayao Innovation Fund [Fundamental Fund 2024 (227/2567)], Thailand.

      Author contributions

      • The authors confirm contribution to the paper as follows: conceptualization: Suwannarach N, Khuna S; formal analysis: Suwannarach N, Khuna S, Chaiwong K, Senwanna C, Kumla J; investigation, methodology: Suwannarach N, Khuna S, Chaiwong K; resources: Suwannarach N, Khuna S, Chaiwong K; software: Khuna S, Chaiwong K, Senwanna C, Kumla J; validation: Suwannarach N, Khuna S, Senwanna C, Nuangmek W; data curation: Khuna S, Senwanna C, Nuangmek W, Kumla J; visualization: Khuna S, Chaiwong K; writing–original draft: Suwannarach N, Khuna S, Nuangmek W, Kumla J; writing–review & editing: Suwannarach N, Khuna S, Chaiwong K, Senwanna C, Nuangmek W, Kumla J; supervision, project administration: Suwannarach N; funding acquisition: Suwannarach N, Nuangmek W. All authors have read and agreed to the published version of the manuscript.

      Data availability

      • The DNA sequences generated in this study have been submitted to GenBank and can be accessed through the accession numbers provided in the paper.

      Conflict of interest

      • The authors declare that they have no conflict of interest. Nakarin Suwannarach and Jaturong Kumla are the Editorial Board members of Studies in Fungi who are blinded from reviewing or making decisions on the manuscript. The article was subject to the journal's standard procedures, with peer review handled independently of these Editorial Board members and the research groups.

      Rights and permissions
      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (3)  Table (2) References (54)
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    Cite this article
    Suwannarach N, Khuna S, Chaiwong K, Senwanna C, Nuangmek W, et al. 2024. Identification and fungicide sensitivity of the blue mold pathogen in postharvest-stored elephant garlic bulbs in Thailand. Studies in Fungi 9: e015 doi: 10.48130/sif-0024-0015
    Suwannarach N, Khuna S, Chaiwong K, Senwanna C, Nuangmek W, et al. 2024. Identification and fungicide sensitivity of the blue mold pathogen in postharvest-stored elephant garlic bulbs in Thailand. Studies in Fungi 9: e015 doi: 10.48130/sif-0024-0015
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  • Introduction
  • Materials and methods

  • Sample collection

  • Fungal isolation and morphological study

  • DNA extraction, PCR amplification, and sequencing

  • Sequence alignment and phylogenetic analyses

  • Pathogenicity tests

  • Screening of commercial fungicides against the causal agent

  • Statistical analysis

  • Results

  • Disease symptoms

  • Fungal isolation and morphological characteristics

  • Phylogenetic analysis

  • Pathogenicity tests

  • Reactions of commercial fungicides against Penicillium allii

  • Discussion
  • Conclusions
  • Acknowledgments
  • Author contributions
  • Data availability
  • Conflict of interest
  • Rights and permissions
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