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24 pages, 2369 KiB  
Article
Diversity and Functional Roles of Root-Associated Endophytic Fungi in Two Dominant Pioneer Trees Reclaimed from a Metal Mine Slag Heap in Southwest China
by Bo Bi, Yuqing Xiao, Xiaonan Xu, Qianqian Chen, Haiyan Li, Zhiwei Zhao and Tao Li
Microorganisms 2024, 12(10), 2067; https://doi.org/10.3390/microorganisms12102067 (registering DOI) - 15 Oct 2024
Viewed by 303
Abstract
The utilization of fast-growing, economically valuable woody plants with strong stress resistance, such as poplar and willow, to revegetate severely metal-contaminated mine tailings not only offers a productive and profitable use of abandoned polluted soil resources but also facilitates the phytoremediation of these [...] Read more.
The utilization of fast-growing, economically valuable woody plants with strong stress resistance, such as poplar and willow, to revegetate severely metal-contaminated mine tailings not only offers a productive and profitable use of abandoned polluted soil resources but also facilitates the phytoremediation of these polluted soils. This study examines the diversity and functional roles of endophytic fungi naturally colonizing the roots of an artificially established Populus yunnanensis forest and the naturally reclaimed pioneer species Coriaria sinica on an abandoned tailing dam in southwest China. Culture-independent analyses revealed that the root systems of both plant species were abundantly colonized by arbuscular mycorrhizal fungi and endophytic fungi, forming rich and diverse endophytic fungal communities predominantly represented by the genera Ilyonectria, Tetracladium, Auricularia, and unclassified members of Helotiales. However, the composition of root endophytic fungal communities differed significantly between the two plant species. Using a culture-dependent approach, a total of 192 culturable endophytic fungal strains were isolated from the roots. The dominant genera included Cadophora, Cladosporium, Cyphellophora, and Paraphoma, most of which were previously identified as dark septate endophytes (DSE). Six representative DSE strains were selected for further study, and significant cadmium tolerance and various plant growth-promoting traits were observed, including the solubilization of insoluble inorganic and organic phosphorus, indole-3-acetic acid (IAA) production, and siderophore synthesis. In greenhouse experiments, inoculating two DSE strains mitigated the inhibitory effects of metal-polluted tailing soil on the growth of P. yunnanensis. This was achieved by reducing heavy metal uptake in roots and limiting metal translocation to the above-ground tissues, thereby promoting plant growth and adaptability. Our findings suggest that as plants reclaim metal-polluted tailings, root-associated endophytic fungal communities also undergo natural succession, playing a critical role in enhancing the host plant’s tolerance to stress. Therefore, these restored root-associated fungi, particularly DSE, are essential functional components of the root systems in plants used for tailing reclamation. Full article
(This article belongs to the Special Issue Biotechnology for Environmental Remediation)
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Figure 1

Figure 1
<p>Relative abundance of fungal genera colonizing the roots of <span class="html-italic">P. yunnanensis</span> (Py) and <span class="html-italic">C. sinica</span> (Cn) in the abandoned tailing area of Huangmaoshan, Yunnan Province, southwest China.</p>
Full article ">Figure 2
<p>PCoA (unweighted UniFrac) analysis of fungi colonizing the roots of <span class="html-italic">P. yunnanensis</span> and <span class="html-italic">C. sinica</span> in the abandoned tailing area of Huangmaoshan, Yunnan Province, southwest China.</p>
Full article ">Figure 3
<p>Heatmap showing the correlation between 14 environmental factors and the top 35 most abundant fungal genera colonizing the roots of <span class="html-italic">P. yunnanensis</span> and <span class="html-italic">C. sinica</span> in the abandoned tailing area of Huangmaoshan, Yunnan Province, Southwest China. Environmental factors include pH, soil organic matter (SOM), total nitrogen (tN), total phosphorus (tP), total potassium (tK), available N (aN), available phosphorus (aP), available potassium (aK), total lead (tPb), total zinc (tZn), total cadmium (tCd), and extractable metals (ePb, eZn, eCd). Spearman’s correlation coefficient was deemed statistically significant at the levels of 0.05 (*), 0.01 (**), and 0.001 (***), respectively.</p>
Full article ">Figure 4
<p>Tolerance of DSE strains colonizing the roots of <span class="html-italic">P. yunnanensis</span> (<b>a</b>) and <span class="html-italic">C. sinica</span> (<b>b</b>) to Cd<sup>2+</sup> as determined by the minimum inhibitory concentration (MIC) range in the abandoned tailing area of Huangmaoshan, Yunnan Province, southwest China.</p>
Full article ">Figure 5
<p>Phosphorus solubilizing capacity of the six representative DSE strains isolated from the roots of <span class="html-italic">P. yunnanensis</span> and <span class="html-italic">C. sinica</span> in the abandoned tailing area of Huangmaoshan, Yunnan Province, Southwest China. The strains were cultured in a PVK liquid medium supplemented with tricalcium phosphate (<b>a</b>–<b>c</b>) and Phytin (TCP) (<b>d</b>–<b>f</b>) as the sole phosphorus source for 10 days. (<b>a</b>,<b>d</b>) Dry weight of DSE strains; (<b>b</b>,<b>e</b>) concentration of soluble P in PVK liquid medium; (<b>c</b>,<b>f</b>) pH value in PVK liquid medium. Different lowercase letters indicate significant differences among different DSE strains (one-way ANOVA, Duncan’s multiple range test, <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 6
<p>Indole-3-acetic acid (IAA) concentrations in the culture filtrates of six representative DSE strains after 10 days of incubation with L-tryptophan. Different lowercase letters indicate significant differences among the different DSE strains (one-way ANOVA, Duncan’s multiple range test, <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 7
<p>Effects of inoculation by the two fungal strains (FE) on the growth and heavy metal concentrations (Cd, Zn, and Pb) accumulated in the roots, stems, and leaves, as well as on the translocation factors (TF) and bioconcentration factors (BCF) of <span class="html-italic">P. yunnanensis</span> inoculated with different DSE strains, compared to non-inoculated controls after 60 days of cultivation. Different lowercase letters indicate significant differences among the different treatments (one-way ANOVA, Duncan’s multiple range test, <span class="html-italic">p</span> &lt; 0.05). Asterisks indicate significant differences between the DSE inoculation treatments and their respective uninoculated controls (* <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">t</span>-test).</p>
Full article ">Figure 8
<p>Concentrations of HCl-extractable metals in the rhizosphere soil after 60 days of cultivation of <span class="html-italic">P. yunnanensis.</span> Different letters within the same heavy metal group indicate significant differences between the treatment groups (one-way ANOVA, Duncan’s multiple range test, <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">
21 pages, 15596 KiB  
Article
Assessing the Pathogenicity of Berkeleyomyces rouxiae and Fusarium oxysporum f. sp. vasinfectum on Cotton (Gossypium hirsutum) Using a Rapid and Robust Seedling Screening Method
by Andrew Chen, Duy P. Le, Linda J. Smith, Dinesh Kafle, Elizabeth A. B. Aitken and Donald M. Gardiner
J. Fungi 2024, 10(10), 715; https://doi.org/10.3390/jof10100715 - 15 Oct 2024
Viewed by 327
Abstract
Cotton (Gossypium spp.) is the most important fibre crop worldwide. Black root rot and Fusarium wilt are two major diseases of cotton caused by soil-borne Berkeleyomyces rouxiae and Fusarium oxysporum f. sp. vasinfectum (Fov), respectively. Phenotyping plant symptoms caused by [...] Read more.
Cotton (Gossypium spp.) is the most important fibre crop worldwide. Black root rot and Fusarium wilt are two major diseases of cotton caused by soil-borne Berkeleyomyces rouxiae and Fusarium oxysporum f. sp. vasinfectum (Fov), respectively. Phenotyping plant symptoms caused by soil-borne pathogens has always been a challenge. To increase the uniformity of infection, we adapted a seedling screening method that directly uses liquid cultures to inoculate the plant roots and the soil. Four isolates, each of B. rouxiae and Fov, were collected from cotton fields in Australia and were characterised for virulence on cotton under controlled plant growth conditions. While the identities of all four B. rouxiae isolates were confirmed by multilocus sequencing, only two of them were found to be pathogenic on cotton, suggesting variability in the ability of isolates of this species to cause disease. The four Fov isolates were phylogenetically clustered together with the other Australian Fov isolates and displayed both external and internal symptoms characteristic of Fusarium wilt on cotton plants. Furthermore, the isolates appeared to induce varied levels of plant disease severity indicating differences in their virulence on cotton. To contrast the virulence of the Fov isolates, four putatively non-pathogenic Fusarium oxysporum (Fo) isolates collected from cotton seedlings exhibiting atypical wilt symptoms were assessed for their ability to colonise cotton host. Despite the absence of Secreted in Xylem genes (SIX6, SIX11, SIX13 and SIX14) characteristic of Fov, all four Fo isolates retained the ability to colonise cotton and induce wilt symptoms. This suggests that slightly virulent strains of Fo may contribute to the overall occurrence of Fusarium wilt in cotton fields. Findings from this study will allow better distinction to be made between plant pathogens and endophytes and allow fungal effectors underpinning pathogenicity to be explored. Full article
(This article belongs to the Special Issue Current Research in Soil Borne Plant Pathogens)
Show Figures

Figure 1

Figure 1
<p>Colony morphology of <span class="html-italic">Berkeleyomyces rouxiae</span> and <span class="html-italic">Fusarium oxysporum</span> isolates used in this study. (<b>A</b>) <span class="html-italic">B. rouxiae</span> isolates RVB4.1, BRR4, 22BRR77, and StrB22 grown for 2 weeks on 10% carrot agar. (<b>B</b>) <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">vasinfectum</span> isolates <span class="html-italic">Fov</span> SG1, <span class="html-italic">Fov</span> SG26, <span class="html-italic">Fov</span> SG55, and <span class="html-italic">Fov</span> TH1 grown for 2 weeks on half-strength potato dextrose agar (PDA). (<b>C</b>) <span class="html-italic">Fusarium oxsporum</span> isolates <span class="html-italic">Fo</span> BRF1, <span class="html-italic">Fo</span> BRF2, <span class="html-italic">Fo</span> WRF2, and <span class="html-italic">Fo</span> SHF6 grown for 2 weeks on half-strength PDA.</p>
Full article ">Figure 2
<p>Compound microscopic images of <span class="html-italic">Berkeleyomyces rouxiae</span> and <span class="html-italic">Fusarium oxysporum</span> isolates used in this study. (<b>A</b>,<b>B</b>) <span class="html-italic">B. rouxiae</span> isolate RVB4.1. (<b>C</b>,<b>D</b>) <span class="html-italic">B. rouxiae</span> isolate 22BRR77. (<b>E</b>,<b>F</b>) <span class="html-italic">B. rouxiae</span> isolate BRR4. (<b>G</b>,<b>H</b>) <span class="html-italic">B. rouxiae</span> isolate StrB22. (<b>I</b>) <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">Vasinfectum</span> isolate (<span class="html-italic">Fov</span>) SG1. (<b>J</b>) <span class="html-italic">Fov</span> isolate SG26. (<b>K</b>) <span class="html-italic">Fov</span> isolate SG55. (<b>L</b>) <span class="html-italic">Fov</span> isolate TH1. (<b>M</b>) <span class="html-italic">Fusarium oxsporum</span> (<span class="html-italic">Fo</span>) isolate BRF1. Inset: a cluster of conidia. (<b>N</b>) <span class="html-italic">Fo</span> isolate BRF2. Inset: microconidia. (<b>O</b>) <span class="html-italic">Fo</span> isolate SHF6. Inset: a cluster of macroconidia. (<b>P</b>) <span class="html-italic">Fo</span> isolate WRF2. Inset: microconidia. e = endoconidia; ec = endoconidia chains; a = aleuriospores; c = microconidia; ma = macroconidia. Bars indicate a scale of 15 µm.</p>
Full article ">Figure 3
<p>Phylogenetic positions of <span class="html-italic">Berkeleyomyces rouxiae</span> isolates within the genus <span class="html-italic">Berkeleyomyces</span> determined using Bayesian inference. Phylogenetic relationships were reconstructed using concatenated sequences of <span class="html-italic">MCM7</span> and <span class="html-italic">RPB2</span> genes. Isolates examined in this study are highlighted in red. Orange circles indicate accessions that were used to define the genus <span class="html-italic">Berkeleyomyces</span> [<a href="#B4-jof-10-00715" class="html-bibr">4</a>]. The bar indicates a scale range of 0.1. Node values show the posterior probability. Genus is abbreviated as Ch. for <span class="html-italic">Chalaropsis</span>, C. for <span class="html-italic">Ceratocystis</span>, B. for <span class="html-italic">Berkeleyomyces</span>, and L. for <span class="html-italic">Lignincola</span>.</p>
Full article ">Figure 4
<p>Bayesian phylogeny of the <span class="html-italic">Fusarium oxysporum</span> isolates inferred from combined analysis of translation elongation factor, mitochondrial small subunit rDNA, nitrate reductase, and phosphate permease gene sequences. <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">vasinfectum</span> isolates are classified into lineages I–V [<a href="#B7-jof-10-00715" class="html-bibr">7</a>,<a href="#B9-jof-10-00715" class="html-bibr">9</a>]. Isolates examined in this study are highlighted in red. The endophytic and slightly pathogenic <span class="html-italic">F. oxysporum</span> isolates from cotton were classified as a distinct lineage [<a href="#B18-jof-10-00715" class="html-bibr">18</a>], and these isolates were characterised to be either non-pathogenic (green circle) or slightly pathogenic (orange circles) on cotton plants. VCG01111 and VCG01112 are abbreviated as VCG11 and VCG12, respectively. The bar indicates a scale range of 0.001. Node values show the posterior probability.</p>
Full article ">Figure 5
<p>Bayesian inference phylogenetic reconstruction of <span class="html-italic">Secreted in Xylem 6</span> gene (<span class="html-italic">SIX6</span>) in <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">vasinfectum</span> isolates and isolates from other <span class="html-italic">formae speciales</span> of <span class="html-italic">Fusarium oxysporum</span>. Isolates examined in this study are highlighted in red. <span class="html-italic">Focuc</span> = <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">cucumerinum</span>; <span class="html-italic">Fol</span> = <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">lycopersici</span>; <span class="html-italic">Fopas</span> = <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">passiflora</span>; <span class="html-italic">Fon</span> = <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">niveum</span>; <span class="html-italic">Fop</span> = <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">pisi</span>; <span class="html-italic">Foradc</span> = <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">radicis-cucumerinum</span>; <span class="html-italic">Foses</span> = <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">sesami</span>. Bars indicate a scale range of 0.05. Node values show the posterior probability.</p>
Full article ">Figure 6
<p>Virulence testing of <span class="html-italic">Berkeleyomyces rouxiae</span> isolates on cotton cv. Sicot746 B3F. (<b>A</b>) Plants at harvest (15–20 days post inoculation). (<b>B</b>) Total (above and below ground) plant weight. (<b>C</b>) Plant height. (<b>D</b>) Percentage of roots discoloured. (<b>E</b>) Total stem discoloured. (<b>F</b>) Percentage of leaves wilted or dropped. (<b>G</b>) Reisolations of <span class="html-italic">B. rouxiae</span>-like colonies on half-strength potato dextrose agar from the roots, stems, and petioles of uninoculated plants and plants inoculated with the <span class="html-italic">B. rouxiae</span> isolates. Numbers indicate the number of samples assayed per tissue type. Letters indicate a significant separation of means by Tukey’s range test at <span class="html-italic">p</span> = 0.05. Error bars indicate a 95% confidence interval.</p>
Full article ">Figure 7
<p>Symptomatology of <span class="html-italic">Berkeleyomyces rouxiae</span> and <span class="html-italic">Fusarium oxysporum</span> isolates on cotton cv. Sicot746 B3F at harvest. (<b>A</b>) Stem and root symptomatology of Sicot746 B3F plants inoculated with <span class="html-italic">B. rouxiae</span> isolates StrB22, BRR4, RVB4.1 and 22BRR77. (<b>B</b>) Stem and root symptomatology of Sicot746 B3F plants inoculated with <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">vasinfectum</span> (<span class="html-italic">Fov</span>) isolates <span class="html-italic">Fov</span> SG26, <span class="html-italic">Fov</span> TH1, <span class="html-italic">Fov</span> SG55 and <span class="html-italic">Fov</span> SG1. (<b>C</b>) Stem and root symptomatology of Sicot746 B3F plants inoculated with <span class="html-italic">F. oxysporum</span> (<span class="html-italic">Fo</span>) isolates <span class="html-italic">Fo</span> SHF6, <span class="html-italic">Fo</span> BRF2, <span class="html-italic">Fo</span> WRF2, <span class="html-italic">Fo</span> BRF1 and <span class="html-italic">Fov</span> SG1 (positive control). Plants inoculated with water served as a negative control. Red vertical bars indicate a scale of 10 cm.</p>
Full article ">Figure 8
<p>Virulence testing of <span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">vasinfectum</span> (<span class="html-italic">Fov</span>) isolates on cotton cv. Sicot746 B3F. (<b>A</b>) Plants at harvest (27–34 days post inoculation). (<b>B</b>) Total (above and below ground) plant weight. (<b>C</b>) Plant height. (<b>D</b>) Percentage of roots discoloured. (<b>E</b>) Total stem discoloured. (<b>F</b>) Percentage of leaves wilted or dropped. (<b>G</b>) Reisolations of <span class="html-italic">F. oxysporum</span>-like colonies on half-strength potato dextrose agar from the roots, stems, and petioles of uninoculated plants and plants inoculated with the <span class="html-italic">Fov</span> isolates. Numbers indicate the number of samples assayed per tissue type. Letters indicate a significant separation of means by Tukey’s range test at <span class="html-italic">p</span> = 0.05. Error bars indicate a 95% confidence interval.</p>
Full article ">Figure 9
<p>Virulence testing of <span class="html-italic">Fusarium oxysporum</span> (<span class="html-italic">Fo</span>) isolates on cotton cv. Sicot746 B3F. (<b>A</b>) Plants at harvest (17–22 days post inoculation). (<b>B</b>) Total (above and below ground) plant weight. (<b>C</b>) Plant height. (<b>D</b>) Percentage of roots discoloured. (<b>E</b>) Total stem discoloured. (<b>F</b>) Percentage of leaves wilted or dropped. (<b>G</b>) Reisolations of <span class="html-italic">F. oxysporum</span>-like colonies on half-strength potato dextrose agar from the roots, stems, and petioles of uninoculated plants and plants inoculated with the <span class="html-italic">Fov</span> isolates. Numbers indicate the number of samples assayed per tissue type. Letters indicate a significant separation of means by Tukey’s range test at <span class="html-italic">p</span> = 0.05. Error bars indicate a 95% confidence interval.</p>
Full article ">
16 pages, 3646 KiB  
Article
Improving Inoculum Production of Arbuscular Mycorrhizal Fungi in Zea mays L. Using Light-Emitting Diode (LED) Technology
by Sutee Kiddee, Niramon Lakkasorn, Jenjira Wongdee, Pongdet Piromyou, Pongpan Songwattana, Teerana Greetatorn, Kamonluck Teamtisong, Nantakorn Boonkerd, Katsuharu Saito, Neung Teaumroong and Panlada Tittabutr
Agronomy 2024, 14(10), 2342; https://doi.org/10.3390/agronomy14102342 - 11 Oct 2024
Viewed by 352
Abstract
A substrate-based production system is a simple and low-cost method for arbuscular mycorrhizal (AM) fungal inoculum production. However, it is time-consuming and typically yields low numbers of AM fungal spores due to several factors affecting plant growth efficiency. Our study investigated the use [...] Read more.
A substrate-based production system is a simple and low-cost method for arbuscular mycorrhizal (AM) fungal inoculum production. However, it is time-consuming and typically yields low numbers of AM fungal spores due to several factors affecting plant growth efficiency. Our study investigated the use of light-emitting diode (LED) technology to expedite AM fungal spore production in planta. We performed experiments with Rhizophagus irregularis inoculated in maize (Zea mays L.), contrasting LED light with greenhouse (GH) conditions. Our results exhibited a significant improvement in AM fungal colonization and spore production, as well as a reduction in the production period from 120 to 90 days under the LED light condition. This was achieved using a red-and-blue light ratio of 60:40 with a total light intensity of 300 µmol m−2 s−1. The LED light treatments improved maize growth by increasing nitrogen (N) and phosphorus (P) concentrations in shoots and roots, respectively. Our gene expression analyses revealed that in AMF-inoculated plants, genes related to photosynthesis were significantly upregulated under LED light compared to the GH condition. Moreover, LED increased the expression of marker genes linked to the AM fungi-related cell cycle, indicating enhanced AM fungal growth during symbiosis. These findings advance our comprehension of LED applications in agriculture, offering promising prospects for acceleration of AM fungal spore production. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
Show Figures

Figure 1

Figure 1
<p>Evaluating the impact of red–blue (R:B) light ratios on the growth of maize (<span class="html-italic">Zea mays</span> L.) cultivar Suawan-5 at (<b>A</b>) 7 and (<b>B</b>) 14 days after exposure (DAE), with a total light intensity of 300 µmol m<sup>−2</sup> s<sup>−1</sup>.</p>
Full article ">Figure 2
<p>Impact of LED light on AM fungal colonization, vesicle size, and spore number of <span class="html-italic">R. irregularis</span> in maize roots at 45 DAIs. (<b>A</b>) The AM fungal abundance in roots of maize grown under greenhouse (GH) condition and red–blue (R:B) light ratio of 60:40 at different light intensities of 200, 300, and 400 µmol m<sup>−2</sup> s<sup>−1</sup> conditions, with scale bars of 100 μm. (<b>B</b>) The average vesicle size, with the vesicles (<span class="html-italic">n</span> = 52) from 10 root fragments randomly measured for each treatment, and (<b>C</b>) the number of AM fungal spores per pot. Values are represented as means ± s.e.m (<span class="html-italic">n</span> = 3). Bars with different letters indicate significant differences at a <span class="html-italic">p</span>-value &lt; 0.05 based on Tukey’s HSD test. n.s., not significant.</p>
Full article ">Figure 3
<p>Plant physiology of Suwan-5 maize, showing growth at 45 days after inoculation (DAIs) under greenhouse (GH) and LED light conditions. (<b>A</b>) Plants were grown without <span class="html-italic">R. irregularis</span> (non-AMF) and with <span class="html-italic">R. irregularis</span> (AMF) inoculation. (<b>B</b>) Plant height and (<b>C</b>) chlorophyll content of maize were measured. Significant differences among all groups, including LED light and GH conditions within both non-AMF and AMF inoculations, were analyzed using one-way ANOVA. Standard error bars (s.e.m.) were calculated with <span class="html-italic">n</span> = 3. Groups that share the same letter show no significant difference, as determined by Tukey’s post hoc test at <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 4
<p>The data of (<b>A</b>) dry biomass and (<b>B</b>) plant tissue nitrogen (N) and phosphorus (P) concentrations at 45 days after inoculation (DAIs). Average concentrations of nitrogen (N) and phosphorus (P) (mg g<sup>−1</sup> dry weight) in the shoot and root of Suwan-5 maize are presented with standard error bars (± s.e.m; <span class="html-italic">n</span> = 3). The analysis of shoot and root biomass was conducted separately, and different letters indicate significant differences based on Tukey’s HSD test. Student’s <span class="html-italic">t</span>-test was performed to analyze nitrogen (N) and phosphorus (P) concentrations (n.s., not significant; *, <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>The abundance of <span class="html-italic">R. irregularis</span> at 45 days after inoculation (DAIs). Maize was inoculated with <span class="html-italic">R. irregularis</span> (AMF) under the greenhouse (GH) and LED light conditions. (<b>A</b>) AMF colonization in maize roots. F(%), the frequency of mycorrhiza in the root system; M(%), the intensity of mycorrhizal colonization in the root system; m(%), the intensity of mycorrhizal colonization in the root fragments; a(%), the arbuscule abundance in the mycorrhizal parts of the root fragments; and A(%), the arbuscule abundance in the root system. (<b>B</b>) The number of <span class="html-italic">R. irregularis</span> spores produced in the soil at 45 DAIs and (<b>C</b>) 90 DAIs. Values are represented as means ± s.e.m. (<span class="html-italic">n</span> = 3). Student’s <span class="html-italic">t</span>-test (n.s., not significant; * <span class="html-italic">p</span> &lt; 0.05) was conducted in (<b>A</b>–<b>C</b>).</p>
Full article ">Figure 6
<p>The expression of maize photosynthesis-related genes at 45 days after inoculation (DAIs). Chloroplast-encoded photosynthetic genes: <span class="html-italic">rbcL</span>: RuBisCO (large subunit); <span class="html-italic">psaA</span> and <span class="html-italic">psbA</span>: electron transport (photosystems I and II); <span class="html-italic">petA</span> and <span class="html-italic">petD</span>: electron transport (cytochrome ƒ and subunit IV of cytochrome <span class="html-italic">b<sub>6</sub>f</span> complex); and <span class="html-italic">atpB</span> and <span class="html-italic">atpE</span>: ATP synthesis. There are three replications, and the letter above the bar indicates significant difference at <span class="html-italic">p</span>-value &lt; 0.05 using Student’s <span class="html-italic">t</span>-test.</p>
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<p>The gene expression profiles of maize (<b>A</b>) and <span class="html-italic">R. irregularis</span> (<b>B</b>) at 45 days after inoculation (DAIs). Plants were inoculated with <span class="html-italic">R. irregularis</span> (AMF) and grown under the greenhouse (GH) and LED light conditions. <span class="html-italic">P</span>-values were calculated based on Student’s <span class="html-italic">t</span>-test (*, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ****, <span class="html-italic">p</span> &lt; 0.0001). (<b>A</b>) maize genes, including <span class="html-italic">RAM1</span>: GRAS transcription factor; <span class="html-italic">Pht6</span>: phosphate transporter; <span class="html-italic">AMT3</span>: ammonium transporter; <span class="html-italic">FatM</span>: acyl–acyl carrier protein thioesterase; and <span class="html-italic">RAM2</span>: glycerol-3-phosphate acyltransferase. (<b>B</b>) <span class="html-italic">R. irregularis</span> genes, including <span class="html-italic">H2</span> and <span class="html-italic">H3</span>: histones; <span class="html-italic">Polδ</span>: DNA polymerase delta subunit 4; <span class="html-italic">CDK1</span>: cyclin-dependent kinase; <span class="html-italic">PCNA</span>: proliferating cell nuclear antigen; <span class="html-italic">RNR</span>: ribonucleotide reductase; <span class="html-italic">KIF</span>: kinesin; <span class="html-italic">PPN1</span>-<span class="html-italic">PPN4</span>: endopolyphosphatases; <span class="html-italic">VTC1</span>, <span class="html-italic">VTC2</span>, and <span class="html-italic">VTC4</span>: vacuolar transporter chaperones; and <span class="html-italic">MST2</span>: monosaccharide transporter.</p>
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14 pages, 820 KiB  
Article
Fungal Biostarter and Bacterial Occurrence of Dry-Aged Beef: The Sensory Quality and Volatile Aroma Compounds after 21 Days of Aging
by Wiesław Przybylski, Danuta Jaworska, Paweł Kresa, Grzegorz Ostrowski, Magdalena Płecha, Dorota Korsak, Dorota Derewiaka, Lech Adamczak, Urszula Siekierko and Julia Pawłowska
Appl. Sci. 2024, 14(19), 9053; https://doi.org/10.3390/app14199053 - 7 Oct 2024
Viewed by 944
Abstract
In this study, we decided to test the hypothesis that the fungal biostarter M. flavus used during a 21-day beef dry-aging process significantly impacts the composition of other microorganisms, the profile of volatile compounds, meat hardness characteristics, and, consequently, the sensory quality. The [...] Read more.
In this study, we decided to test the hypothesis that the fungal biostarter M. flavus used during a 21-day beef dry-aging process significantly impacts the composition of other microorganisms, the profile of volatile compounds, meat hardness characteristics, and, consequently, the sensory quality. The experiments were performed on samples derived from animals crossbred between Holstein–Fresian cows and meat breed bulls. Two groups of samples were studied, including the control group, without biostarter, and a group inoculated with the M. flavus biostarter. Both sample groups were seasoned for 21 days in the dry-aging fridge. The physicochemical parameters (pH, color parameters), the chemical composition of muscle, the determination of the shear force, the profile of volatile compounds (VOCs), and the sensory quality were evaluated after aging. During this study, classical microbiological methods were used to investigate the influence of fungal biostarters on the growth and survival of bacteria and other fungi (e.g., yeasts) during the dry-aging process of beef (DAB). The M. flavus biostarter improved the sensory quality of DAB, allowing high sensory quality to be achieved after just 21 days. This is likely due to the diverse VOCs produced by the fungus, including 1-tetradecanol, 2-nonenal, trans-2-undecenoic acid, and the following esters: formic acid hexyl ester, 10-undecenoic acid methyl ester, and 4-methylpentanoic acid methyl ester. The presence of the biostarter had no significant effect on the number of the bacteria or the survivability of the L. monocytogenes on the meat’s surface in laboratory conditions. Full article
(This article belongs to the Special Issue State of the Art in Food Science: Food Processing and Preservation)
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<p>Comparison of sensory liking (40 consumers) control and biostarter samples after 21 days of dry aging. Odor A—raw material (after 21 days of dry-aging; before heat treatment), Odor B—after heat treatment. Different letters (a, b) indicate means that are significantly different at the level of <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Volatile aroma compound groups [%] found in dry-aged beef samples with biostarter (<span class="html-italic">M. Flavus</span>) and without it (control beef samples) over 21 days. <sup>a.b</sup>—values within a bar of a specific compound group with different letters are significantly different (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Mean number of bacterial colony-forming units (CFUs) developed on the surface of dry-aged beef over time, during the 21 days of the dry-aging process, when seasoned with <span class="html-italic">M. flavus</span> biostarter (<span class="html-italic">Mf)</span> and without it (control).</p>
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16 pages, 4288 KiB  
Article
Bacillus subtilis Strain YJ-15, Isolated from the Rhizosphere of Wheat Grown under Saline Conditions, Increases Soil Fertility and Modifies Microbial Community Structure
by Junkang Sui, Chenyu Wang, Pengfei Chu, Changqing Ren, Feifan Hou, Yuxuan Zhang, Xueting Shang, Qiqi Zhao, Xuewen Hua and Hengjia Zhang
Microorganisms 2024, 12(10), 2023; https://doi.org/10.3390/microorganisms12102023 - 6 Oct 2024
Viewed by 571
Abstract
Soil salinization during wheat cultivation considerably diminishes soil fertility and impedes wheat growth, primarily due to rhizosphere microbial community changes. Our study investigates the application of Bacillus subtilis YJ-15, a strain isolated from the rhizosphere of wheat cultivated in salinized soil, as a [...] Read more.
Soil salinization during wheat cultivation considerably diminishes soil fertility and impedes wheat growth, primarily due to rhizosphere microbial community changes. Our study investigates the application of Bacillus subtilis YJ-15, a strain isolated from the rhizosphere of wheat cultivated in salinized soil, as a soil remediation agent. This strain has demonstrated significant salt tolerance, disease suppression capabilities, and growth-promoting attributes in previous studies. The wheat rhizosphere was examined to assess the impact of Bacillus subtilis YJ-15 on microbial community composition and soil fertility. Fertility of soil in saline soil was significantly increased by inoculating wheat with YJ-15. The microbial community structure within the wheat rhizosphere inoculated with Bacillus subtilis YJ-15 was analyzed through sequencing on the Illumina MiSeq platform. Phyla Proteobacteria and Acidobacteria were identified as the dominant bacteria. Basidiomycota, Mortierellomycota, and Ascomycota dominated the fungal phyla. Among the bacterial genera, Pseudomonas, Arthrobacter, and Bacillus were predominant. The predominant fungal genera included Alternaria, Cephalotrichum, Mortierella, and Chaetomium. A significant increase in Gaiella and Haliangium levels was observed in the YJ group compared to the control group. Additionally, the fungal genera Epicoccum, Sporidiobolus, and Lecythophora have significantly increased in YJ abundance. One of the potential benefits of Bacillus subtilis YJ-15 in the cultivation of wheat on salinized land is its ability to enhance the rhizosphere microbial community structure and improve soil fertility. Full article
(This article belongs to the Special Issue Rhizosphere Microbial Community, 3rd Edition)
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<p>The bacterial (<b>a</b>) and fungal (<b>b</b>) species sobs curves were analyzed to evaluate the effect of a 3% dissimilarity threshold on the identification of unobserved OTUs. “YJ” represents the treated group with the bacterial agent, whereas “CK” represents the control group without the bacterial agent applied.</p>
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<p>Shannon curves for bacteria (<b>a</b>) and fungi (<b>b</b>). “YJ” represents the treated group with the bacterial agent, whereas “CK” represents the control group without the bacterial agent applied.</p>
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<p>NMDS analysis and ANOSIM analysis of rhizosphere soil microbes from non-deep tillage and deep tillage wheat cultivation. (<b>a</b>) Bacterial NMDS analysis on OTU level, (<b>b</b>) Bacterial ANOSIM analysis on OTU level, (<b>c</b>) Fungal NMDS analysis on OTU level, (<b>d</b>) Fungal ANOSIM analysis on OTU level. “YJ” represents the treated group with the bacterial agent, whereas “CK” represents the control group without the bacterial agent applied.</p>
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<p>Bacterial and fungal communities’ composition. (<b>a</b>) Phylum level of bacterial composition. (<b>b</b>) Genus level of bacterial composition. (<b>c</b>) Phylum level of fungal composition. (<b>d</b>) Genus level of fungal composition. Major genera are represented by stacked bar graphs. “YJ” represents the treated group with the bacterial agent, whereas “CK” represents the control group without the bacterial agent applied.</p>
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<p>Distributions of bacteria and fungi grouped hierarchically. (<b>a</b>) Phylum level of bacterial taxonomic composition. (<b>b</b>) Genus level of bacterial taxonomic composition. (<b>c</b>) Phylum level of fungal taxonomic composition. (<b>d</b>) Genus level of fungal taxonomic composition. “YJ” represents the treated group with the bacterial agent, whereas “CK” represents the control group without the bacterial agent applied.</p>
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<p>Venn diagram with unique and shared genera for (<b>a</b>) bacteria and (<b>b</b>) fungi. “YJ” represents the treated group with the bacterial agent, whereas “CK” represents the control group without the bacterial agent applied.</p>
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<p>Significant test of differences between two groups. (<b>a</b>) Phylum-level bacterial significant differences (<b>b</b>) Genus-level bacterial significant differences (<b>c</b>) Phylum-level fungal significant differences (<b>d</b>) Genus-level fungal significant differences. “YJ” represents the treated group with the bacterial agent, whereas “CK” represents the control group without applied the bacterial agent.</p>
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<p>Multilevel species differences evaluated through LEfSe analysis. (<b>a</b>) Bacterial multi-level species differences. (<b>b</b>) Fungal multi-level species differences. Nodes of different colors signify microbial communities that are significantly enriched in their respective groups and contribute notably to inter-group differences.</p>
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20 pages, 4083 KiB  
Article
Prevalence and Antimicrobial Susceptibility Patterns of Wound and Pus Bacterial Pathogens at a Tertiary Care Hospital in Central Riyadh, Saudi Arabia
by Fizza Khalid, Christy Poulose, Dalal Farah Mousa Farah, Abid Mahmood, Azza Elsheikh and Osamah T. Khojah
Microbiol. Res. 2024, 15(4), 2015-2034; https://doi.org/10.3390/microbiolres15040135 - 2 Oct 2024
Viewed by 748
Abstract
The long history and extensive use of antibiotics have caused resistant bacterial pathogens to emerge, increasing mortality and morbidity. The current study was designed to see the prevalence of aerobic bacterial isolates with their antimicrobial resistance pattern from out- and inpatients requested for [...] Read more.
The long history and extensive use of antibiotics have caused resistant bacterial pathogens to emerge, increasing mortality and morbidity. The current study was designed to see the prevalence of aerobic bacterial isolates with their antimicrobial resistance pattern from out- and inpatients requested for wound or pus culture. Retrospective study conducted at a tertiary care hospital in central Riyadh from January 2023 to December 2023. Samples were collected and inoculated onto the appropriate media following standard guidelines. Bacterial pathogens were identified by the Vitek2 compact system. Antimicrobial susceptibility was tested using the Kirby–Bauer disk diffusion method as well as by MIC determination through the Vitek2 compact. A total of 1186 subjects were included in the study with a bacterial isolation rate of 691 (58.3%). Out of these, 155 positive cultures had incomplete information or anaerobic or fungal growth and were excluded from the study. With a slight female predominance (54.9%), the majority of subjects (72.2%) were outpatients, and over half of the isolates (55.2%) were Gram-positive. The most common isolate was Staphylococcus spp. (44.4%), followed by E. coli (13.6%) and P. aeruginosa (12.9%). The highest resistance was reported against penicillin followed by fusidic acid against Gram-positive bacteria. Methicillin-resistant Staphylococcus aureus (MRSA) was detected in 40.5% of Staphylococcus aureus (S. aureus) isolates. Amikacin was the most susceptible antibiotic against all Gram-negative isolates. MDR Gram-negative bacteria accounted for 51.9% of wound infection isolates (95% CI: 45.95 to 58.33) while 6.3% (95% CI: 4.39 to 8.86) were XDR (nonsusceptibility to at least one agent in all but two or fewer antimicrobial categories). A high prevalence of bacterial isolates, with S. aureus as the predominant pathogen, showed high rates of multidrug resistance. This highlights the importance of monitoring antibiotic choices for prophylaxis and treatment in the study area. Full article
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<p>Prevalence of bacterial isolates from different types of wound infections. Percentage was calculated out of the number of samples for each type of wound. Drainage * (from ear/bile).</p>
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<p>Antimicrobial resistance of <span class="html-italic">S. aureus</span> (n = 205) and CoNS (n = 33). P: penicillin, OX: oxacillin, E: erythromycin, DA: clindamycin, CN: gentamicin, TS: co-trimoxazole, CIP: ciprofloxacin, LEV: levofloxacin, TE: tetracycline, VA: vancomycin, LZD: linezolid, FD: fusidic acid.</p>
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<p>Antimicrobial resistance of <span class="html-italic">E. faecalis</span> (n = 58). AMP: ampicillin, P: penicillin, LZD: linezolid, TE: tetracycline, VA: vancomycin.</p>
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<p>Antimicrobial resistance of Enterobacteriaceae (n = 167). AMC: augmentin, CEFAL: cefalothin, CXM: cefuroxime, CFM: cefixime, CPD: cefpodoxime, CRO: ceftriaxone, FEP: cefepime, TS: co-trimoxazole, CIP: ciprofloxacin, LEV: levofloxacin, OFX: ofloxacin, TZP: piperacillin–tazobactam, IMP: imipenem, MEM: meropenem, AK: amikacin, CN: gentamicin.</p>
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<p>Antimicrobial resistance of Pseudomonas (n = 69). CAZ: ceftazidime, FEP: cefepime, CIP: ciprofloxacin, LEV: levofloxacin, OFX: ofloxacin, TZP: piperacillin–tazobactam, IMP: imipenem, MEM: meropenem, AK: amikacin, CN: gentamicin, ATM: aztreonam.</p>
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19 pages, 1618 KiB  
Article
Assessment of Chemical and Biological Fungicides for the Control of Diplodia mutila Causing Wood Necrosis in Hazelnut
by Verónica Retamal, Juan San Martín, Braulio Ruíz, Richard M. Bastías, Eugenio Sanfuentes, María José Lisperguer, Tommaso De Gregorio, Matteo Maspero and Ernesto Moya-Elizondo
Plants 2024, 13(19), 2753; https://doi.org/10.3390/plants13192753 - 30 Sep 2024
Viewed by 413
Abstract
Fungal trunk disease (FTD) poses a significant threat to hazelnut (Corylus avellana L.) production worldwide. In Chile, the fungus Diplodia mutila, from the Botryosphaeriaceae family, has been frequently identified causing this disease in the Maule and Ñuble Regions. However, control measures [...] Read more.
Fungal trunk disease (FTD) poses a significant threat to hazelnut (Corylus avellana L.) production worldwide. In Chile, the fungus Diplodia mutila, from the Botryosphaeriaceae family, has been frequently identified causing this disease in the Maule and Ñuble Regions. However, control measures for D. mutila remain limited. This research aimed to evaluate the effectiveness of chemical and biological fungicides against D. mutila under in vitro, controlled pot experiment, and field conditions. An in vitro screening of 30 fungicides was conducted. The effectiveness was assessed by measuring the length of vascular lesions in hazelnut branches inoculated with D. mutila mycelium disks under controlled and field conditions. Field trials were conducted in a hazelnut orchard in Ñiquén, Ñuble Region, Chile. The results showed that three biological and five chemical fungicides were selected in vitro with >31% inhibition after 14 days. In pot experiments, all fungicides reduced necrotic lesions on branches by 32% to 61%. In field experiments, the most effective systemic fungicides were fluopyram/tebuconazole, fluxapyroxad/pyraclostrobin, and tebuconazole, while the effectiveness of antagonists Pseudomonas protegens ChC7 and Bacillus subtilis QST713 varied with seasonal temperatures. Effective conventional and biological fungicides against D. mutila could be integrated into disease management programs to protect hazelnut wounds from infections. Full article
(This article belongs to the Special Issue Pathogens and Disease Management of Horticultural Crops)
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<p>Pre-selection assay of antagonist microorganisms against <span class="html-italic">Diplodia mutila</span> after 7 days of incubation. (<b>a</b>) Control: <span class="html-italic">D. mutila</span>; (<b>b</b>) <span class="html-italic">Trichoderma</span> spp. and <span class="html-italic">Bacillus</span> spp. (Puelche-VTO, Bio Insumos Nativa SpA); (<b>c</b>) <span class="html-italic">Bionectria ochroleuca</span> Mitique, <span class="html-italic">Trichoderma gamsii</span> Volqui, <span class="html-italic">Hypocrea virens</span> Ñire (Mamull, Bio Insumos Nativa SpA); (<b>d</b>) <span class="html-italic">Bacillus subtilis</span> QST 713 (Serenade ASO, Bayer de México, S.A, Tiaxcala, Mexico); (<b>e</b>) <span class="html-italic">Pantoea</span> sp. AP113; (<b>f</b>) <span class="html-italic">Pseudomonas protegens</span> Ca2 + Ca6 + ChC7; (<b>g</b>) <span class="html-italic">P. protegens</span> Ca2; (<b>h</b>) <span class="html-italic">P. protegens</span> Ca6; and (<b>i</b>) <span class="html-italic">P. protegens</span> ChC7.</p>
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<p>Mean length values of necrotic lesions caused by the fungus <span class="html-italic">Diplodia mutila</span> on branches of hazelnut cv. Tonda di Giffoni, inoculated the same day and 24 h after the application of biological control agents, under field conditions during the 2020–2021 season. Bars with different letters indicate statistical differences between treatments according to Fisher’s LSD test (α = 0.05).</p>
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<p>(<b>A</b>) Mean length values of necrotic lesions caused by the fungus <span class="html-italic">Diplodia mutila</span> on branches of hazelnut cv. Tonda di Giffoni; (<b>B</b>) inoculations on the same day (first inoculation) and 24 h later (second inoculation) after the application of biological control agents, under field conditions in the 2021–2022 season. Bars with different letters indicate statistical differences between treatments (<b>A</b>) and inoculation times (<b>B</b>) according to Fisher’s LSD test (α = 0.05).</p>
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18 pages, 2899 KiB  
Article
Green Alternatives for the Control of Fungal Diseases in Strawberry: In-Field Optimization of the Use of Elicitors, Botanical Extracts and Essential Oils
by Sebastian Soppelsa, Antonio Cellini, Irene Donati, Giampaolo Buriani, Francesco Spinelli and Carlo Andreotti
Horticulturae 2024, 10(10), 1044; https://doi.org/10.3390/horticulturae10101044 - 30 Sep 2024
Viewed by 335
Abstract
Finding safe and reliable alternatives to fungicides is currently one of the biggest challenges in agriculture. In this regard, this experiment investigated the effectiveness of different elicitors, botanical extracts and essential oils to control grey mold (Botrytis cinerea) and powdery mildew [...] Read more.
Finding safe and reliable alternatives to fungicides is currently one of the biggest challenges in agriculture. In this regard, this experiment investigated the effectiveness of different elicitors, botanical extracts and essential oils to control grey mold (Botrytis cinerea) and powdery mildew (Podosphaera aphanis) on strawberry plants. This trial was conducted in field conditions under a plastic tunnel with strawberry plants ‘Elsanta’. A first group of strawberry plants was treated before flowering with elicitors [acibenzolar-S-Methyl–(BTH), chitosan], botanical extracts (seaweed extract, alfalfa hydrolysate) and essential oils (thyme and juniper), and grey mold incidence on flowers was evaluated (Experiment 1). Furthermore, a second group of plants was treated before (Experiment 2) and after (Experiment 3) controlled inoculation with P. aphanis. The results indicated that the incidence of flower infected by B. cinerea was reduced by approximately 50% with thyme and juniper essential oils’ applications compared to the untreated control, with no significant difference observed compared to the commercial fungicide penconazole (positive control). As a consequence, the final yield of essential-oil-treated plants was +27% higher than that of non-treated plants. No significant differences emerged for other tested products against grey mold. However, gene expression analysis showed an up-regulation (>2 ÷ 5 folds as compared to control 4 days after application) of FaEDS1, FaLOX and PR gene expression (FaPR1, FaPR5, FaPR10) in leaves treated with BTH. The other natural substances tested also induced defense-related genes, albeit at a lower level than BTH. In Experiment 2, all treatments applied prior to inoculation significantly reduced the incidence and severity of powdery mildew as compared to control. At 28 days after inoculation, chitosan and thyme essential oil applications performed similarly to their positive controls (BTH and penconazole, respectively), showing a significant reduction in disease incidence (by −84 and −92%) as compared to control. Post-inoculum application of essential oils (Experiment 3) showed an efficacy similar to that of penconazole against powdery mildew. These results indicated that the tested substances could be used as alternatives to fungicides for the control of grey mold and powdery mildew in strawberry, therefore representing a valuable tool for the control of these fungal diseases under the framework of sustainable agriculture. Full article
(This article belongs to the Special Issue New Challenge of Fungal Pathogens of Horticultural Crops)
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<p>Climatic conditions: average daily temperature (T °C) and relative humidity (RH %) in the greenhouse during the experimental period.</p>
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<p>Incidence of flowers affected by natural infections by <span class="html-italic">Botrytis cinerea</span> at the end of harvest (56 days after flowering; Experiment 1). Different letters at the top of each bar indicate significant differences among treatments according to LSD test at <span class="html-italic">p</span> &lt; 0.05 (mean ± SE, <span class="html-italic">n</span> = 4). Treatments’ legend: CON, control; FUN, fungicide; BTH, benzothiadiazole; CHI, chitosan; SEA, seaweed extract; APH, alfalfa protein hydrolysate; THY, thyme essential oil; JUN, juniper essential oil.</p>
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<p>Powdery mildew incidence on strawberry leaves after inoculation (<b>A</b>) and severity at 56 days after inoculation (<b>B</b>). Tested products were applied 7 days before inoculation at BBCH 71 (Experiment 2). Different letters at the top of each bar indicate significant differences among treatments according to LSD test at <span class="html-italic">p</span> &lt; 0.05 (mean ± SE, <span class="html-italic">n</span> = 8). ns: not significant.</p>
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<p>Powdery mildew incidence on strawberry leaves after inoculation (<b>A</b>) and severity at 56 days after inoculation (<b>B</b>). Tested products were applied 24 h after inoculation at BBCH 73 (Experiment 3). Different letters at the top of each bar indicate significant differences among treatments according to LSD test at <span class="html-italic">p</span> &lt; 0.05 (mean ± SE, <span class="html-italic">n</span> = 8). ns: not significant.</p>
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<p>Expression of defense-related genes (<span class="html-italic">FaPR1</span> (<b>A</b>), <span class="html-italic">FaPR5</span> (<b>B</b>), <span class="html-italic">FaPR10</span> (<b>C</b>), <span class="html-italic">FaEDS1</span> (<b>D</b>) and <span class="html-italic">FaLOX</span> (<b>E</b>)) in strawberry leaves treated with benzothiadiazole, seaweed extracts, chitosan and thyme essential oil. RT-qPCR was performed using FaGPDH2 as housekeeping gene. For gene expression, we adopted the 2<sup>(−DDCT)</sup> method, in which a ‘0’ fold change corresponds to ‘no change’. Values were normalized to the control at each time point. Data are expressed as mean ± SE.</p>
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<p>Expression of defense-related genes (<span class="html-italic">FaPR1</span> (<b>A</b>), <span class="html-italic">FaPR5</span> (<b>B</b>), <span class="html-italic">FaPR10</span> (<b>C</b>), <span class="html-italic">FaEDS1</span> (<b>D</b>) and <span class="html-italic">FaLOX</span> (<b>E</b>)) in strawberry leaves treated with benzothiadiazole, seaweed extracts, chitosan and thyme essential oil. RT-qPCR was performed using FaGPDH2 as housekeeping gene. For gene expression, we adopted the 2<sup>(−DDCT)</sup> method, in which a ‘0’ fold change corresponds to ‘no change’. Values were normalized to the control at each time point. Data are expressed as mean ± SE.</p>
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<p>Expression of defense-related genes (<span class="html-italic">FaPR1</span> (<b>A</b>), <span class="html-italic">FaPR5</span> (<b>B</b>), <span class="html-italic">FaPR10</span> (<b>C</b>), <span class="html-italic">FaEDS1</span> (<b>D</b>) and <span class="html-italic">FaLOX</span> (<b>E</b>)) in strawberry leaves treated with benzothiadiazole, seaweed extracts, chitosan and thyme essential oil. RT-qPCR was performed using FaGPDH2 as housekeeping gene. For gene expression, we adopted the 2<sup>(−DDCT)</sup> method, in which a ‘0’ fold change corresponds to ‘no change’. Values were normalized to the control at each time point. Data are expressed as mean ± SE.</p>
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20 pages, 3790 KiB  
Article
Effect of Harvest Maturity and Lactiplantibacillus plantarum Inoculant on Dynamics of Fermentation Characteristics and Bacterial and Fungal Community of Triticale Silage
by Run Gao, Yi Liu, Bo Wu, Chunlin Jia, Zhu Yu and Guoliang Wang
Agriculture 2024, 14(10), 1707; https://doi.org/10.3390/agriculture14101707 - 29 Sep 2024
Viewed by 307
Abstract
(1) Background: Suitable harvest maturity stage selection and microbial inoculation during anaerobic fermentation are effective strategies for improving the quality of triticale (×Triticosecale) silage for ruminant nutrition. (2) Methods: In the present study, the fermentation characteristics, microbial communities, and their correlations [...] Read more.
(1) Background: Suitable harvest maturity stage selection and microbial inoculation during anaerobic fermentation are effective strategies for improving the quality of triticale (×Triticosecale) silage for ruminant nutrition. (2) Methods: In the present study, the fermentation characteristics, microbial communities, and their correlations were evaluated for triticale silages, as affected by Lactiplantibacillus plantarum (LP) inoculation at the heading, flowering, filling, milk-ripening, and wax-ripening stages. (3) Results: The results indicate that the filling and milk-ripening stages without LP inoculation resulted in lower pH and higher lactic acid than other harvest maturity stages (p < 0.05). Inoculating with LP decreased the pH at each harvest maturity stage, except for the filling stage, and increased the lactic acid concentration at the heading and filling stages (p < 0.05). The bacterial dynamics indicated that the abundances of Lactiplantebacilli and Monascus of the triticale silages without the LP inoculation were different between the harvest maturity stages (p < 0.05), and the abundance of Enterobacters was different between the harvest maturity stages in the triticale silage (p < 0.05). Remarkably, negative correlations were found between the Lactiplantebacillus, Monascus, and pH and positive correlations were found between the Lactiplantebacillus, Monascus, and lactic acid content (p < 0.05). (4) Conclusions: The filling and milk-ripening stages were the most suitable harvest maturity stages for the triticale silage. Inoculation with LP could enhance the fermentation quality, increase the abundances of beneficial microorganisms, and inhibit harmful microorganisms in triticale silage. Full article
(This article belongs to the Section Farm Animal Production)
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<p>PCoA (principal co-ordinates) results based on OTU levels of the bacteria (<b>A</b>) and fungi (<b>B</b>) in the triticale silage (<span class="html-italic">n</span> = 3). PC1, principal co-ordinate 1; PC2, principal co-ordinate 2; CK, group with same volume of distilled water added; LP, group with <span class="html-italic">Lactiplantibacillus plantarum</span> added; H, heading stage; F, flowering stage; F1, filling stage; M, milk-ripening stage; W, wax-ripening stage.</p>
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<p>Petal chart of common and unique bacteria (<b>A</b>) and fungi (<b>B</b>) populations in the triticale silage at different harvest maturity stages. Different colors represent different treatments, with petals representing the number of species unique to the corresponding treatment and the center representing the number of species common to all treatments. CK, group with the same volume of distilled water added; LP, group with <span class="html-italic">Lactiplantibacillus plantarum</span> added; H, heading stage; F, flowering stage; F1, filling stage; M, milk-ripening stage; W, wax-ripening stage.</p>
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<p>Relative abundances of the bacterial community proportions at the phylum (<b>A</b>) and genus (<b>B</b>) levels and in the triticale silage at different harvesting stages. HCK, control (CK) in the heading period; HLP, <span class="html-italic">Lactiplantibacillus plantarum</span> (LP) added in the heading period; FCK, CK in the flowering period; FLP, LP added in the flowering period; F1CK, CK in the filling period; F1LP, LP added in the filling period; MCK, CK in the milk-ripening period; MLP, LP added in the milk-ripening period; WCK, CK in the wax-ripening period; WLP, LP added in the wax-ripening period.</p>
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<p>The differential bacterial species of the triticale silage at the phylum and genus (among the top 10 bacterial genera) levels during the different harvest maturity stages of the CK group. * means 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05, ** means 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, *** means <span class="html-italic">p</span> ≤ 0.001.</p>
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<p>The different bacterial species of the triticale silage at the genus (among the top 10 bacterial genera) level during the different harvest maturity stages of the LP group. * means 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05, ** means 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, *** means <span class="html-italic">p</span> ≤ 0.001.</p>
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<p>Spearman correlation heatmaps for the fermentation characteristics with the top 10 enriched bacteria (<b>A</b>) and fungi (<b>B</b>) at the genus level. Positive correlations are shown in purple and negative correlations are shown in orange. * means 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05, ** means 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, *** means <span class="html-italic">p</span> ≤ 0.001.</p>
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<p>Relative abundances of fungal community proportions at the phylum (<b>A</b>) and genus (<b>B</b>) levels and in triticale silage at different harvesting stages. HCK, control (CK) in the heading period; HLP, <span class="html-italic">Lactiplantibacillus plantarum</span> (LP) added in the heading period; FCK, CK in the flowering period; FLP, LP added in the flowering period; F1CK, CK in the filling period; F1LP, LP added in the filling period; MCK, CK in the milk-ripening period; MLP, LP added in the milk-ripening period; WCK, CK in the wax-ripening period; WLP, LP added in the wax-ripening period.</p>
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<p>The different fungal species of the triticale silage at the phylum (no different fungal species were found) and genus (among the top 10 bacterial genera) level during the different harvest maturity stages of the CK group. * means 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05, ** means 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, *** means <span class="html-italic">p</span> ≤ 0.001.</p>
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<p>The different fungal species of the triticale silage at the phylum and genus (among the top 10 bacterial genera) levels during the different harvest maturity stages of the LP group. * means 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05, ** means 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, *** means <span class="html-italic">p</span> ≤ 0.001.</p>
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17 pages, 3309 KiB  
Article
Exploring the Synergistic Secretome: Insights from Co-Cultivation of Aspergillus brasiliensis and Trichoderma reesei RUT-C30
by Guilherme Bento Sperandio, Reynaldo Magalhães Melo, Taísa Godoy Gomes, Robert Neil Gerard Miller, Luis Henrique Ferreira do Vale, Marcelo Valle de Sousa, Carlos André Ornelas Ricart and Edivaldo Ximenes Ferreira Filho
J. Fungi 2024, 10(10), 677; https://doi.org/10.3390/jof10100677 - 28 Sep 2024
Viewed by 439
Abstract
The spectrum of enzymes required for complete lignocellulosic waste hydrolysis is too diverse to be secreted by a single organism. An alternative is to employ fungal co-cultures to obtain more diverse and complete enzymatic cocktails without the need to mix enzymes during downstream [...] Read more.
The spectrum of enzymes required for complete lignocellulosic waste hydrolysis is too diverse to be secreted by a single organism. An alternative is to employ fungal co-cultures to obtain more diverse and complete enzymatic cocktails without the need to mix enzymes during downstream processing. This study evaluated the co-cultivation of Aspergillus brasiliensis and Trichoderma reesei RUT-C30 in different conditions using sugarcane bagasse as the carbon source. The resulting enzymatic cocktails were characterized according to the impact of strain inoculation time on enzymatic activities and proteome composition. Data revealed that the profile of each enzymatic extract was highly dependent on the order in which the participating fungi were inoculated. Some of the co-cultures exhibited higher enzyme activities compared to their respective monocultures for enzymes such as CMCase, pectinase, β-glucosidase, and β-xylosidase. Analysis of the T. reesei RUT-C30 and A. brasiliensis co-culture secretome resulted in the identification of 167 proteins, with 78 from T. reesei and 89 from A. brasiliensis. In agreement with the enzymatic results, proteome analysis also revealed that the timing of inoculation greatly influences the overall secretome, with a predominance of T. reesei RUT-C30 proteins when first inoculated or in simultaneous inoculation. Full article
(This article belongs to the Special Issue Fungal-Related Proteomics in Biotechnology and Health)
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<p>Enzymatic activity profiles tested on natural substrates obtained over 9 days in mono- and co-cultures of <span class="html-italic">A. brasiliensis</span> and <span class="html-italic">T. reesei</span> RUT-C30 grown in liquid medium with sugarcane bagasse as sole carbon source, as described in <a href="#jof-10-00677-t001" class="html-table">Table 1</a>. The substrates used in the enzymatic assays were Panel (<b>A</b>) = carboxymethyl cellulose; Panel (<b>B</b>) = oat spelt xylan; Panel (<b>C</b>) = pectin and Panel (<b>D</b>) = mannan. Error bars represent the standard deviation between three biological replicates. All experiments showed <span class="html-italic">p</span> &lt; 0.05 (ANOVA).</p>
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<p>Enzymatic activity profiles tested on synthetic substrates, obtained over 9 days in mono- and co-cultures of <span class="html-italic">A. brasiliensis</span> and <span class="html-italic">T. reesei</span> RUT-C30 grown in liquid medium with sugarcane bagasse as sole carbon source, as described in <a href="#jof-10-00677-t001" class="html-table">Table 1</a>. The substrates used in the enzymatic assays were: Panel (<b>A</b>) = p-nitrophenyl-β-D-glucopyranoside, Panel (<b>B</b>) = p-nitrophenyl-β-D-xylopyranoside, Panel (<b>C</b>) = p-nitrophenyl-β-D-mannopyranoside, Panel (<b>D</b>) = p-nitrophenyl-β-D-galactopyranoside. Error bars represent the standard deviation between three biological replicates. All experiments showed <span class="html-italic">p</span> &lt; 0.05 (ANOVA).</p>
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<p>Influence of temperature on the enzymatic activity of crude extracts from monocultures of <span class="html-italic">A. brasiliensis</span> and <span class="html-italic">T. reesei</span> RUT-C30 and their simultaneous co-cultures and with different inoculation times, as described in <a href="#jof-10-00677-t001" class="html-table">Table 1</a>. Panel (<b>A</b>) = CMCase activity, Panel (<b>B</b>) = Xylanase activity, Panel (<b>C</b>) = Pectinase activity, Panel (<b>D</b>) = Mannanase activity, Panel (<b>E</b>) = β-glucosidase activity, Panel (<b>F</b>) = β-Xylosidase activity and Panel (<b>G</b>) = β-galactosidase activity. The error bars represent the standard deviation between three biological replicates. All experiments showed <span class="html-italic">p</span> &lt; 0.05 (ANOVA).</p>
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<p>Influence of pH on the CMCase activity of different mono- and co-cultures of <span class="html-italic">A. brasiliensis</span> and <span class="html-italic">T. reesei</span> RUT-C30, as described in <a href="#jof-10-00677-t001" class="html-table">Table 1</a>. The error bars represent the standard deviation between three biological replicates. All experiments showed <span class="html-italic">p</span> &lt; 0.05 (ANOVA).</p>
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<p>The identification percentage of proteins belonging to either <span class="html-italic">T. reesei</span> RUT-C30 or <span class="html-italic">A. brasiliensis</span> in mono- and co-cultures. The ratio of identified proteins from each organism was calculated, providing insights into the relative abundance of proteins from each organism under different experimental setups as described in <a href="#jof-10-00677-t001" class="html-table">Table 1</a>.</p>
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<p>Venn diagram of shared and exclusive proteins identified in the secretomes of different co-culture experimental setups (see <a href="#jof-10-00677-t001" class="html-table">Table 1</a>) and monocultures of AB and C30. Panel (<b>A</b>) = AB + C30 0 h vs. AB vs. C30; Panel (<b>B</b>) = C30 + AB 24 h vs. AB vs. C30; Panel (<b>C</b>) = C30 + AB 24 h vs. AB vs. C30. Panel (<b>D</b>) = list of proteins identified exclusively in the co-cultures. AB—<span class="html-italic">A. brasiliensis</span>; C30 = <span class="html-italic">T. reesei</span> RUT-C30.</p>
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<p>Probabilistic principal component analysis (PPCA) was used to assess similarities among replicates within each group and to identify differences between conditions. Dimension reductions considered both normalized abundance values and number of missing values.</p>
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13 pages, 1656 KiB  
Article
Pathogenicity and Metabolomic Characterization of Fusarium graminearum and Fusarium poae Challenge in Barley under Controlled Conditions
by Raja Khanal, Kerin Hudson, Adam Foster, Xiben Wang, Elizabeth K. Brauer, Thomas E. Witte and David P. Overy
J. Fungi 2024, 10(10), 670; https://doi.org/10.3390/jof10100670 - 26 Sep 2024
Viewed by 417
Abstract
Barley is the third most important cereal crop in terms of production in Canada, and Fusarium head blight (FHB) is one of the main fungal diseases of barley. FHB is caused by a species complex of Fusaria, of which Fusarium graminearum Schwabe is [...] Read more.
Barley is the third most important cereal crop in terms of production in Canada, and Fusarium head blight (FHB) is one of the main fungal diseases of barley. FHB is caused by a species complex of Fusaria, of which Fusarium graminearum Schwabe is the main causal species of FHB epidemics in Canada. Field surveys show that two or more Fusarium species often co-exist within the same field or grain sample, and F. poae is reported as another important species in barley. This study aimed to determine the pathogenicity of F. graminearum, F. poae, and a co-inoculation of both species causing FHB in barley. Two susceptible barley cultivars were spray-inoculated at 10 to 14 days after heading. Phenotypic disease severity was rated on a scale of 0–9 at 4, 7, 14, 21, and 28 days after inoculation. There was a significant difference in FHB severity between F. graminearum and F. poae, where infection with F. graminearum produced more severe disease ratings. F. poae generated lower disease ratings and was not statistically different from the control. When heads were co-inoculated with both Fusarium species, the resulting FHB severity was unchanged relative to heads inoculated with F. graminearum only. The ratio of F. graminearum to F. poae genomic DNA was also no different than when heads were inoculated with F. graminearum alone, as quantified with ddPCR using markers specific to each species. The metabolomic analysis of sample extracts showed that F. graminearum-associated metabolites dominated the mycotoxin profile of co-inoculated samples, which corroborated our other findings where F. graminearum appeared to outcompete F. poae in barley. No significant effect on visual FHB disease ratings or fungal DNA detection was observed between the cultivars tested. However, there were some metabolome differences between cultivars in response to the challenge by both F. graminearum and F. poae. Full article
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<p>Mean observed Fusarium head blight (FHB) disease severity on Stander and CDC Bold barley cultivars in the growth chamber experiment. The disease was assessed as described by Xue et al. [<a href="#B25-jof-10-00670" class="html-bibr">25</a>].</p>
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<p>Gene expression of the <span class="html-italic">Fusarium</span> secondary metabolite biosynthetic genes <span class="html-italic">GRA1</span> and <span class="html-italic">APS1</span> in infected barley spikes. Expression was measured by ddPCR on ground tissue inoculated with single-species or co-inoculation treatments. Heads were harvested at 28 days post-inoculation (dpi). *** <span class="html-italic">p</span> &lt; 0.0001. Error bars represent standard error of mean.</p>
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<p>Results from PCA analysis of barley cultivar Stander, comparing <span class="html-italic">F. graminearum</span> and <span class="html-italic">F. poae</span> secondary metabolite mass feature associations between monoculture and co-culture pathogen challenges. (<b>A</b>) PC1-2 score plot (red dots = mock control samples; green dots = <span class="html-italic">F. graminearum</span> monoculture samples; dark-blue dots = <span class="html-italic">F. poae</span> monoculture samples; light-blue dots = <span class="html-italic">F. graminearum</span> and <span class="html-italic">F. poae</span> co-culture samples). (<b>B</b>) PC1-2 loading plot representing mass feature variables (<span class="html-italic">Fp</span> = <span class="html-italic">F. poae</span>).</p>
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<p>Heatmap demonstrating difference in scaled (4 to −4) relative abundance of mass feature intensities observed in in planta challenge experiments using Stander and CDC Bold barley cultivars (red colour reflects greater abundance; black reflects low abundance; green reflects absence). Protonated pseudomolecular ion ([M + H]<sup>+</sup>) mass features are used to represent the various metabolites, unless otherwise specified.</p>
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17 pages, 6508 KiB  
Article
RNA-Seq Analysis and Candidate Gene Mining of Gossypium hirsutum Stressed by Verticillium dahliae Cultured at Different Temperatures
by Ni Yang, Zhaolong Gong, Yajun Liang, Shiwei Geng, Fenglei Sun, Xueyuan Li, Shuaishuai Qian, Chengxia Lai, Mayila Yusuyin, Junduo Wang and Juyun Zheng
Plants 2024, 13(19), 2688; https://doi.org/10.3390/plants13192688 - 25 Sep 2024
Viewed by 358
Abstract
The occurrence and spread of Verticillium dahliae (V. dahliae) in cotton depends on the combined effects of pathogens, host plants, and the environment, among which temperature is one of the most important environmental factors. Studying how temperature impacts the occurrence of [...] Read more.
The occurrence and spread of Verticillium dahliae (V. dahliae) in cotton depends on the combined effects of pathogens, host plants, and the environment, among which temperature is one of the most important environmental factors. Studying how temperature impacts the occurrence of V. dahliae in cotton and the mechanisms governing host defense responses is crucial for disease prevention and control. Understanding the dual effects of temperature on both pathogens and hosts can provide valuable insights for developing effective strategies to manage this destructive fungal infection in cotton. This study was based on the deciduous V. dahliae Vd-3. Through cultivation at different temperatures, Vd-3 formed the most microsclerotia and had the largest colony diameter at 25 °C. Endospore toxins were extracted, and 48 h was determined to be the best pathogenic time point for endotoxins to infect cotton leaves through a chlorophyll fluorescence imaging system and phenotypic evaluation. Transcriptome sequencing was performed on cotton leaves infected with Vd-3 endotoxins for 48 h at different culture temperatures. A total of 34,955 differentially expressed genes (DEGs) were identified between each temperature and CK (no pathogen inoculation), including 17,422 common DEGs. The results of the enrichment analysis revealed that all the DEGs were involved mainly in photosynthesis and sugar metabolism. Among the 34,955 DEGs, genes in the biosynthesis and signal transduction pathways of jasmonic acid (JA), salicylic acid (SA), and ethylene (ET) were identified, and their expression patterns were determined. A total of 5652 unique DEGs were clustered into six clusters using the k-means clustering algorithm, and the functions and main transcription factors (TFs) of each cluster were subsequently annotated. In addition, we constructed a gene regulatory network via weighted correlation network analysis (WGCNA) and identified twelve key genes related to cotton defense against V. dahliae at different temperatures, including four genes encoding transcription factors. These findings provide a theoretical foundation for investigating temperature regulation in V. dahliae infecting cotton and introduce novel genetic resources for enhancing resistance to this disease in cotton plants. Full article
(This article belongs to the Section Plant Genetics, Genomics and Biotechnology)
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<p>(<b>a</b>) Phenotype and colony diameter of Vd-3 colonies after 14 days of culture at different temperatures, bar = 1 cm. Different letters indicate the significance level of difference in colony diameter at different temperatures (<span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Phenotype and chlorophyll fluorescence imaging of cotton leaves infected with the spore toxin protein at different times under normal conditions; bar = 1 cm. (<b>c</b>) Phenotype and chlorophyll fluorescence imaging of cotton leaves infected with spore toxin protein at different temperatures for 48 h; bar = 1 cm.</p>
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<p>(<b>a</b>) Correlation analysis of RNA-seq data from cotton leaves infected with the spore toxin protein at different temperatures. (<b>b</b>) PCA of RNA-seq data from cotton leaves infected with the spore toxin protein at different temperatures.</p>
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<p>(<b>a</b>) Numbers of upregulated and downregulated DEGs at different temperatures. (<b>b</b>) Numbers of common and unique DEGs at different temperatures. (<b>c</b>) GO enrichment analysis of DEGs. (<b>d</b>) KEGG enrichment analysis of DEGs.</p>
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<p>Line graph of the cluster analysis of DEGs. The green numbers represent the numbers of DEGs and TFs in each cluster.</p>
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<p>(<b>a</b>) Line graph of the cluster analysis of unique DEGs. (<b>b</b>) Heatmap of TF proportions in each cluster. (<b>c</b>) Heatmap of the KEGG enrichment analysis results for each cluster.</p>
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<p>(<b>a</b>) Calorimetry of JA biosynthesis and signaling-related DEGs. (<b>b</b>) Calorimetry of SA biosynthesis and signaling-related DEGs. (<b>c</b>) Calorimetry of ET biosynthesis and signaling-related DEGs.</p>
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<p>(<b>a</b>) WGCNA module hierarchical clustering tree diagram; different modules are represented by different colors. (<b>b</b>) Correlation and significance heatmaps between samples and modules. (<b>c</b>) Red module gene interaction network diagram. (<b>d</b>) Turquoise module gene interaction network diagram. (<b>e</b>) Yellow module gene interaction network diagram. (<b>f</b>) Black module gene interaction network diagram.</p>
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<p>Analysis of the expression patterns of candidate genes under different temperature conditions (error bars represent the means ± SEs of three replicates, * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01).</p>
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22 pages, 21927 KiB  
Article
Antimicrobial, Optical, and Mechanical Properties of Saliva-Contaminated Silver–Zeolite Nanoparticle-Incorporated Dental Acrylic Resins
by Çisel Kısa Yaman, Necla Demir, Uğur Arslan and Nurullah Çiftçi
Inorganics 2024, 12(10), 258; https://doi.org/10.3390/inorganics12100258 - 25 Sep 2024
Viewed by 417
Abstract
Background and Purpose: This study aimed to evaluate the flexural strength, color change and antimicrobial effect of silver–zeolite nanoparticles (NPs) in acrylic resin materials. Methods: Fifty-six disc-shaped acrylic resin samples were divided into four groups (n = 7) according to concentrations of [...] Read more.
Background and Purpose: This study aimed to evaluate the flexural strength, color change and antimicrobial effect of silver–zeolite nanoparticles (NPs) in acrylic resin materials. Methods: Fifty-six disc-shaped acrylic resin samples were divided into four groups (n = 7) according to concentrations of silver–zeolite NPs (0%, 2%, 4%, 5%). Discs were contaminated with C. albicans and S. mutans. The antimicrobial effect was tested by inoculating contaminated discs on Tryptic soy agar (TSA), Sabouraud Dextrose Agar (SDA), Tryptic soy broth (TSB), and Sabouraud dextrose broth (SDB). Forty rectangular 65 × 10 × 2.5 mm acrylic resin specimens were also classified into four groups (n = 10) according to concentrations of silver–zeolite NPs. For the color change, L, a, and b values of rectangular specimens were examined with a spectrophotometer. A three-point bending test was also performed using a Devotrans device to determine the flexural bond strength of rectangular specimens. Scanning electron microscope analysis (SEM/EDX analysis) was also performed. Results: In this study, the antimicrobial effect increased with the concentration of silver–zeolite NPs added to acrylic resin discs. In our study, adding 2% silver–zeolite NPs was more effective against C. albicans. The antimicrobial effect against S. mutans increased with concentration of silver–zeolite NPs (<0.001). The colonization of C. albicans was significantly reduced by silver–zeolite NPs. A significant increase was observed in the color change as the nanoparticle percentage ratio increased (p < 0.001). The flexural strength values of the groups containing 2% and 4% nanoparticles were found to be clinically acceptable. Conclusions: The study showed that bacterial and fungal colonization is significantly reduced by adding silver–zeolite nanoparticles to acrylic resin discs. Based on its antimicrobial, physical, and mechanical properties, we recommend adding 2% silver–zeolite nanoparticles to the acrylic resin material for optimal results. Full article
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<p>Surface topography of the discs by SEM images. (<b>A</b>) Control group surface topography (from left to right 300×/500×/1000× magnification); (<b>B</b>) 2% NPs added discs surface topography (from left to right 300×/500×/1000× magnification); (<b>C</b>) 4% NPs added discs surface topography (from left to right 300×/500×/1000× magnification); (<b>D</b>) 5% NPs added discs surface topography (from left to right 300×/500×/1000× magnification).</p>
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<p>Ag Images with SEM/EDX in the (<b>A</b>) 2%, (<b>B</b>) 4%, and (<b>C</b>) 5% (respectively, up to down) groups.</p>
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<p>ΔE2000 color change of the groups.</p>
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<p>Flexural strength values of three-point bending strength test.</p>
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<p>SEM Images of Fracture Surface of Control Group 300×/500×/1.00K× magnification: (<b>a</b>) Mist zone, (<b>b</b>) Hackle zone, (<b>c</b>) Nano-crack.</p>
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<p>SEM Images of Fracture Surface of 2% Group 300×/500×/1.00K× Magnification: (<b>a</b>) 2% Ag/Z group agglomeration, (<b>b</b>) 2% Ag/Z group agglomeration, (<b>c</b>) Increase in the number of nano-cracks.</p>
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<p>4% Group Fracture Surface SEM Images 300×/500×/1.00K× Magnification: (<b>a</b>) Increase in the number of nano-fractures, (<b>b</b>) 4% Ag/Z group agglomeration, (<b>c</b>) Increase in the size of nano-fractures.</p>
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<p>5% Group Fracture Surface SEM Images 300×/500×/1.00K× Magnification: (<b>a</b>,<b>b</b>) 5% Ag/Z group agglomeration, (<b>c</b>) Hackle zone expansion, nano-crack length increase.</p>
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<p>The color differences after XTT and PMS added.</p>
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<p>Differences in <span class="html-italic">C. albicans and S. mutans</span> concentrations.</p>
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<p>Inoculation of contaminated discs with <span class="html-italic">S. mutans</span> and <span class="html-italic">C. albicans. (</span><b>a</b>) <span class="html-italic">S. mutans</span>, a<sup>1</sup> no silver–zeolite NPs added, a<sup>2</sup> discs with 2% silver–zeolite NPs, a<sup>3</sup> discs with 4% silver–zeolite NPs, a<sup>4</sup> discs with 5% silver–zeolite NPs; (<b>b</b>) <span class="html-italic">C. albicans</span>, b<sup>1</sup> no silver–zeolite NPs added, b<sup>2</sup> discs with 2% silver–zeolite NPs, b<sup>3</sup> discs with 4% silver–zeolite NPs, b<sup>4</sup> discs with 5% silver–zeolite NPs.</p>
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<p>Colony count of <span class="html-italic">C. albicans</span> strains. 1: no silver–zeolite NPs added (Control group), 2: discs with 2% silver–zeolite NPs, 3: discs with 4% silver–zeolite NPs, 4: discs with 5% silver–zeolite NPs.</p>
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<p>Colony count of <span class="html-italic">S. mutans</span> strains; 1: no silver–zeolite NPs added (Control group), 2: discs with 2% silver–zeolite NPs, 3: discs with 4% silver–zeolite NPs, 4: discs with 5% silver–zeolite NPs.</p>
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13 pages, 5564 KiB  
Article
Identification of a Fomitopsis pinicola from Xiaoxing’an Mountains and Optimization of Cellulase Activity
by Jing Sun, Hong Yang, Shangjie Ge-Zhang, Yujie Chi and Dawei Qi
Forests 2024, 15(9), 1673; https://doi.org/10.3390/f15091673 - 23 Sep 2024
Viewed by 462
Abstract
Brown-rot fungi are large fungi that can decompose the cell walls of wood; they are notable for their secretion of diverse and complex enzymes that synergistically hydrolyze natural wood cellulose molecules. Fomitopsis pinicola (F. pinicola) is a brown-rot fungus of interest [...] Read more.
Brown-rot fungi are large fungi that can decompose the cell walls of wood; they are notable for their secretion of diverse and complex enzymes that synergistically hydrolyze natural wood cellulose molecules. Fomitopsis pinicola (F. pinicola) is a brown-rot fungus of interest for its ability to break down the cellulose in wood efficiently. In this study, through a combination of rDNA-ITS analysis and morphological observation, the wood decay pathogen infecting Korean pine (Pinus koraiensis Siebold and Zucc.) was identified. Endoglucanase (CMCase) and β-glucosidase were quantified using the DNS (3,5-Dinitrosalicylic acid) method, and the cellulase activity was optimized using a single-factor method and orthogonal test. The results revealed that the wood-decaying fungus NE1 identified was Fomitopsis pinicola with the ITS accession number OQ880566.1. The highest cellulase activity of the strain reached 116.94 U/mL under the condition of an initial pH of 6.0, lactose 15 g·L−1, KH2PO4 0.5 g·L−1, NH4NO3 15 g·L−1, MgSO4 0.5 g·L−1, VB1 0.4 g·L−1, inoculated two 5 mm fungal cakes in 80 mL medium volume cultured 28 °C for 5 days. This laid a foundation for improving the degradation rate of cellulose and biotransformation research, as well as exploring the degradation of cellulose by brown rot fungi. Full article
(This article belongs to the Special Issue Fungal Biodiversity, Systematics, and Evolution)
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<p>Phylogenetic tree of the NE1.</p>
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<p>Observation of morphological characteristics. (<b>a</b>) Front; (<b>b</b>) Back.</p>
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<p>Hyphal growth of NE1 strain on PDA medium. (<b>a</b>) Front; (<b>b</b>) Back.</p>
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<p>Photo of hyphae of wood-decaying fungi NE1 observed with optical microscope.</p>
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<p>Different initial pH on cellulase activity by NE1 (<span class="html-italic">p</span> &lt; 0.05). (a, b, c, d indicate significant differences between groups. Different letters indicate significant differences between groups, while the same letters indicate no significant differences between groups.)</p>
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<p>Different carbon sources on cellulase activity by NE1 (<span class="html-italic">p</span> &lt; 0.05). (a, b, c, d, e indicate significant differences between groups. Different letters indicate significant differences between groups, while the same letters indicate no significant differences between groups).</p>
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<p>Different nitrogen sources on cellulase activity by NE1 (<span class="html-italic">p</span> &lt; 0.05). Different letters indicate significant differences between groups, while the same letters indicate no significant differences between groups.</p>
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15 pages, 6972 KiB  
Article
Metabolomics Revealed the Tolerance and Growth Dynamics of Arbuscular Mycorrhizal Fungi (AMF) to Soil Salinity in Licorice
by Li Fan, Chen Zhang, Jiafeng Li, Zhongtao Zhao and Yan Liu
Plants 2024, 13(18), 2652; https://doi.org/10.3390/plants13182652 - 22 Sep 2024
Viewed by 412
Abstract
Several studies have been devoted to seeking some beneficial plant-related microorganisms for a long time, and on this basis, it has been found that arbuscular mycorrhizal fungi (AMF) have a considerable positive impact on plant health as a biological fungal agent. In this [...] Read more.
Several studies have been devoted to seeking some beneficial plant-related microorganisms for a long time, and on this basis, it has been found that arbuscular mycorrhizal fungi (AMF) have a considerable positive impact on plant health as a biological fungal agent. In this study, we focused on the effects of different AMF on the growth dynamics and root configuration of licorice under saline and alkali conditions. The metabolites of licorice under different AMF were assessed using liquid chromatography–tandem mass spectrometry (LC-MS/MS). Funneliformis mosseae (Fm) and Rhizophagus intraradices (Ri) were added as different AMF treatments, while the sterilized saline–alkali soil was treated as a control. Samples were taken in the R1 period (15 d after AMF treatment) and the R2 period (45 d after AMF treatment). The results showed that the application of AMF significantly increased the root growth of licorice and significantly increased the biomass of both shoot and root. A total of 978 metabolites were detected and divided into 12 groups including lipids, which accounted for 15.44%; organic acids and their derivatives, at 5.83%; benzene compounds and organic heterocyclic compounds, at 5.42%; organic oxides, at 3.78%; and ketones, accounting for 3.17%. Compared with the control, there were significant changes in the differential metabolites with treatment inoculated with AMF; the metabolic pathways and biosynthesis of secondary metabolites were the main differential metabolite enrichment pathways in the R1 period, and those in the R2 period were microbial metabolism in diverse environments and the degradation of aromatic compounds. In conclusion, the use of AMF as biofertilizer can effectively improve the growth of licorice, especially in terms of the root development and metabolites, in saline–alkali soil conditions. Full article
(This article belongs to the Special Issue Role of Microbes in Alleviating Abiotic Stress in Plants)
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Figure 1

Figure 1
<p>Changes in plant growth performance for R1 period (<b>a</b>) and R2 period (<b>b</b>); shoot (<b>c</b>) and root (<b>d</b>) biomass production; and root mycorrhizal colonization rate (<b>e</b>). Data followed by different letters above the bars indicate significant (<span class="html-italic">p</span> &lt; 0.05) differences. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Changes in root system architecture in R1 period (<b>a</b>) and R2 period (<b>b</b>). Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Classification statistics of compounds in the root of licorice.</p>
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<p>Number of differential metabolites in roots of licorice in R1 period for CK_vs._Fm (<b>a</b>) and CK_vs._Ri (<b>b</b>) treatments, and in R2 period for CK_vs._Fm (<b>c</b>) and CK_vs._Ri (<b>d</b>) treatments. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Number of differential metabolites in roots of licorice in R1 period for CK_vs._Fm (<b>a</b>) and CK_vs._Ri (<b>b</b>) treatments, and in R2 period for CK_vs._Fm (<b>c</b>) and CK_vs._Ri (<b>d</b>) treatments. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Heatmap of metabolites in licorice root in R1 period for CK_vs._Fm_vs._Ri (<b>a</b>) treatment, and in R2 period for CK_vs._Fm_vs._Ri (<b>b</b>) treatment. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Heatmap of metabolites in licorice root in R1 period for CK_vs._Fm_vs._Ri (<b>a</b>) treatment, and in R2 period for CK_vs._Fm_vs._Ri (<b>b</b>) treatment. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Top 20 differential metabolites in roots of licorice in R1 period for CK_vs._Fm (<b>a</b>) and CK_vs._Ri (<b>b</b>) treatments, and in R2 period for CK_vs._Fm (<b>c</b>) and CK_vs._Ri (<b>d</b>) treatments. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Top 20 differential metabolites in roots of licorice in R1 period for CK_vs._Fm (<b>a</b>) and CK_vs._Ri (<b>b</b>) treatments, and in R2 period for CK_vs._Fm (<b>c</b>) and CK_vs._Ri (<b>d</b>) treatments. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Top 20 metabolic pathways of differential metabolites annotated by KEEG in roots of licorice between R1 period for CK_vs._Fm (<b>a</b>) and CK_vs._Ri (<b>b</b>) treatments and R2 period for CK_vs._Fm (<b>c</b>) and CK_vs._Ri (<b>d</b>) treatments. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Top 20 metabolic pathways of differential metabolites annotated by KEEG in roots of licorice between R1 period for CK_vs._Fm (<b>a</b>) and CK_vs._Ri (<b>b</b>) treatments and R2 period for CK_vs._Fm (<b>c</b>) and CK_vs._Ri (<b>d</b>) treatments. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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<p>Top 20 metabolic pathways of differential metabolites annotated by KEEG in roots of licorice between R1 period for CK_vs._Fm (<b>a</b>) and CK_vs._Ri (<b>b</b>) treatments and R2 period for CK_vs._Fm (<b>c</b>) and CK_vs._Ri (<b>d</b>) treatments. Abbreviations: R1 and R2, the different periods; CK, treatment with no inoculation; Fm, treatment with <span class="html-italic">Funneliformis mosseae</span> inoculation; Ri, treatment with <span class="html-italic">Rhizophagus intraradices</span> inoculation.</p>
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