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Keywords = 16S rDNA

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21 pages, 2105 KiB  
Article
Effects of Probiotic Supplementation on Body Weight, Growth Performance, Immune Function, Intestinal Microbiota and Metabolites in Fallow Deer
by Meihui Wang, Qingyun Guo, Yunfang Shan, Zhibin Cheng, Qingxun Zhang, Jiade Bai, Yulan Dong and Zhenyu Zhong
Biology 2024, 13(8), 603; https://doi.org/10.3390/biology13080603 (registering DOI) - 9 Aug 2024
Viewed by 122
Abstract
Intestinal diseases are one of the diseases that affect the growth and immunity of deer. Currently, more lactic acid bacteria (LAB) are available as feed additives to improve the intestinal ecological balance of ruminants in production practices. In this study, Enterococcus faecalis was [...] Read more.
Intestinal diseases are one of the diseases that affect the growth and immunity of deer. Currently, more lactic acid bacteria (LAB) are available as feed additives to improve the intestinal ecological balance of ruminants in production practices. In this study, Enterococcus faecalis was supplemented in the feed of fallow deer for 170 d, and body weights, blood indices and immune levels of fallow deer were counted at 35, 65 and 170 d. The effects of Enterococcus faecalis on the intestinal microbiota and the metabolism of fallow deer were analysed using 16S rDNA and UPLC-MS/MS methods. The results showed that the addition of Enterococcus faecalis to the diet improved body weight and immune function and increased the aggregation of gut microbiota in fallow deer. The addition of Enterococcus faecalis altered the community structure of intestinal microorganisms in fallow deer and increased the number of beneficial bacteria. In addition, combined with metabolomics analysis, it was found that supplementation with Enterococcus faecalis significantly altered the metabolites of fallow deer, mainly regulating lipid metabolism, carbohydrate metabolism and phospholipid metabolism. In conclusion, this study presents, for the first time, evidence that the LAB strain Enterococcus faecalis can be used as a potential probiotic for deer and points to a new direction for the treatment of intestinal disorders in the deer family. Full article
(This article belongs to the Section Zoology)
17 pages, 1947 KiB  
Article
Radiation-Tolerant Fibrivirga spp. from Rhizosphere Soil: Genome Insights and Potential in Agriculture
by Sathiyaraj Srinivasan
Genes 2024, 15(8), 1048; https://doi.org/10.3390/genes15081048 - 9 Aug 2024
Viewed by 192
Abstract
The rhizosphere of plants contains a wide range of microorganisms that can be cultivated and used for the benefit of agricultural practices. From garden soil near the rhizosphere region, Strain ES10-3-2-2 was isolated, and the cells were Gram-negative, aerobic, non-spore-forming rods that were [...] Read more.
The rhizosphere of plants contains a wide range of microorganisms that can be cultivated and used for the benefit of agricultural practices. From garden soil near the rhizosphere region, Strain ES10-3-2-2 was isolated, and the cells were Gram-negative, aerobic, non-spore-forming rods that were 0.3–0.8 µm in diameter and 1.5–2.5 µm in length. The neighbor-joining method on 16S rDNA similarity revealed that the strain exhibited the highest sequence similarities with “Fibrivirga algicola JA-25” (99.2%) and Fibrella forsythia HMF5405T (97.3%). To further explore its biotechnological potentialities, we sequenced the complete genome of this strain employing the PacBio RSII sequencing platform. The genome of Strain ES10-3-2-2 comprises a 6,408,035 bp circular chromosome with a 52.8% GC content, including 5038 protein-coding genes and 52 RNA genes. The sequencing also identified three plasmids measuring 212,574 bp, 175,683 bp, and 81,564 bp. Intriguingly, annotations derived from the NCBI-PGAP, eggnog, and KEGG databases indicated the presence of genes affiliated with radiation-resistance pathway genes and plant-growth promotor key/biofertilization-related genes regarding Fe acquisition, K and P assimilation, CO2 fixation, and Fe solubilization, with essential roles in agroecosystems, as well as genes related to siderophore regulation. Additionally, T1SS, T6SS, and T9SS secretion systems are present in this species, like plant-associated bacteria. The inoculation of Strain ES10-3-2-2 to Arabidopsis significantly increases the fresh shoot and root biomass, thereby maintaining the plant quality compared to uninoculated controls. This work represents a link between radiation tolerance and the plant-growth mechanism of Strain ES10-3-2-2 based on in vitro experiments and bioinformatic approaches. Overall, the radiation-tolerant bacteria might enable the development of microbiological preparations that are extremely effective at increasing plant biomass and soil fertility, both of which are crucial for sustainable agriculture. Full article
(This article belongs to the Special Issue Feature Papers in Microbial Genetics in 2024)
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Figure 1
<p>The genome-based phylogenetic tree of ES10-3-2-2 and its related type strains determined using data from the Type Strain Genome Server. The phylogenetic tree was constructed using the calculated intergenomic distances to infer a balanced minimum evolution tree. This analysis utilized the FASTME v.2.1.6.1 software, incorporating Subtree Pruning and Regrafting (SPR) post-processing [<a href="#B17-genes-15-01048" class="html-bibr">17</a>] to refine the tree topology. Branch support was determined through 100 pseudo-bootstrap replicates. The resulting trees were midpoint-rooted [<a href="#B18-genes-15-01048" class="html-bibr">18</a>] and visualized using MEGA (v.8.2) software.</p>
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<p>Circular map of the Strain ES10-3-2-2’s chromosome and plasmids. The outer circle shows the scale in metabases (Mb). The representations, from the outer to the inner circle, are forward- and reverse-strand CDSs.</p>
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<p>Predicted components of T9SS and the gliding motility genes used in the genome of ES10-3-2-2. The representative image illustrates the gene components associated with the Type IX secretion system (T9SS) and gliding motility, as predicted by T9GPred [<a href="#B26-genes-15-01048" class="html-bibr">26</a>].</p>
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<p>Effect of Strain ES10-3-2-2 on plant-growth parameters. (<b>A</b>) The surface of leaves detached from 20-day-old (20 DAT) grown plants. Control (no bacterial suspension), Fe-EDTA-treated plant and 2 × 10<sup>6</sup> cfu/mL bacterial suspension. (<b>B</b>) Graphical representation of the fresh weights of shoots and roots at 20 DAT. The median and SE were calculated with eight plants per treatment. Significant differences between the treated plants were *, <span class="html-italic">p</span> &lt; 0.02 and **, <span class="html-italic">p</span> &lt; 0.05.</p>
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11 pages, 9067 KiB  
Article
First Record of Summer Truffle (Tuber aestivum) in Portugal
by Celeste Santos-Silva and Clarisse Brígido
Microbiol. Res. 2024, 15(3), 1494-1504; https://doi.org/10.3390/microbiolres15030101 - 9 Aug 2024
Viewed by 328
Abstract
Tuber aestivum, commonly known as the summer truffle, is typically found in various parts of Europe where it grows naturally. However, its presence in Portugal was not confirmed until now. The first fruit bodies were collected in April 2024 at stone pine [...] Read more.
Tuber aestivum, commonly known as the summer truffle, is typically found in various parts of Europe where it grows naturally. However, its presence in Portugal was not confirmed until now. The first fruit bodies were collected in April 2024 at stone pine stands (Alenquer and Arruda dos Vinhos, Lisbon) and in June at holm oak stands (Salir, Faro). These specimens are characterized by hypogeous, subglobose, black ascomata with a peridium surface covered with pyramidal warts. Ascopores are subglobose-to-broadly ellipsoid, distinctively ornamented, usually 1–6 per asci. According to the results of the internal transcribed spacer (ITS) rDNA sequence analysis, these specimens form a well-supported group within the Aestivum clade, with T. aestivum being the closest phylogenetic taxon. This remarkable discovery opens up new opportunities for truffle exploitation in Portugal thanks to the summer truffle’s gastronomical value and high market prices. Full article
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<p>Countries with <span class="html-italic">Tuber aestivum</span> natural occurrence. Data retrieved from [<a href="#B15-microbiolres-15-00101" class="html-bibr">15</a>,<a href="#B16-microbiolres-15-00101" class="html-bibr">16</a>,<a href="#B17-microbiolres-15-00101" class="html-bibr">17</a>,<a href="#B18-microbiolres-15-00101" class="html-bibr">18</a>,<a href="#B19-microbiolres-15-00101" class="html-bibr">19</a>,<a href="#B20-microbiolres-15-00101" class="html-bibr">20</a>,<a href="#B21-microbiolres-15-00101" class="html-bibr">21</a>,<a href="#B22-microbiolres-15-00101" class="html-bibr">22</a>,<a href="#B23-microbiolres-15-00101" class="html-bibr">23</a>,<a href="#B24-microbiolres-15-00101" class="html-bibr">24</a>], and created with mapchart.net.</p>
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<p><span class="html-italic">Tuber aestivum</span> specimens collected in Portugal. (<b>A</b>) Left to right: Giovanni Longo, Pina (dog) and Tanka Sapkota, at 1016 sample location site (<a href="https://www.nit.pt/wp-content/uploads/2024/06/49bdcfdd344747a0f30a145d5f6625b1-e1717409790694.jpg" target="_blank">https://www.nit.pt/wp-content/uploads/2024/06/49bdcfdd344747a0f30a145d5f6625b1-e1717409790694.jpg</a>, accessed on 28 June 2024). (<b>B</b>) Left to right: Celeste Santos-Silva, Larissa Müller and Figo (dog) at 1022 sample location site (Algarve Truffle Group). (<b>C</b>) <span class="html-italic">T. aestivum</span> ascomata (Larissa Müller). (<b>D</b>). <span class="html-italic">T. aestivum</span> gleba (Celeste Santos-Silva). (<b>E</b>,<b>F</b>) <span class="html-italic">T. aestivum</span> asci and ascospores (Celeste Santos-Silva). Bars: (<b>C</b>,<b>D</b>) = 1 cm; (<b>E</b>,<b>F</b>). = 30 µm.</p>
Full article ">Figure 3
<p>Phylogenetic placement of <span class="html-italic">Tuber aestivum</span> specimens obtained in this study (bold) in the Aestivum clade. The consensus tree represents a Bayesian approximation with 1000 generations and a maximum likelihood analysis with 1000 bootstrap replicates. The tree is based on the ITS rDNA sequence alignment of 70 sequences assigned to 22 <span class="html-italic">Tuber taxa</span>. ITS rDNA sequences of <span class="html-italic">Choiromyces venosus</span> and <span class="html-italic">C. magnusii</span> were used as the outgroup. Bootstrap supports are shown at the nodes of the branches.</p>
Full article ">Figure 4
<p>Continental Portugal month precipitation (P) and the mean air temperature (Ta) from September 2023 to May 2024. Climatological standard normals (1941–2023) per month for precipitation (PN) and mean air temperature (TaN) (data from <a href="https://www.ipma.pt/pt/publicacoes/" target="_blank">https://www.ipma.pt/pt/publicacoes/</a>, accessed on 26 June 2024).</p>
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17 pages, 1851 KiB  
Article
Impacts of Excreta Exposure and Age on Ileal Microbial Communities, Intestinal Permeability, and Corticosterone in Hens Housed in Enriched Colonies and Cage-Free Housing Systems
by Benjamin J. Altendorf, Chiron J. Anderson, Isabella von Seggern, Maddison L. Wiersema, Stephan Schmitz-Esser and Dawn A. Koltes
Poultry 2024, 3(3), 267-283; https://doi.org/10.3390/poultry3030020 - 7 Aug 2024
Viewed by 400
Abstract
To tease apart differences between conventional cage (CC) and cage-free (CF) housing systems, this study focuses on the effects of excreta exposure and age by comparing microbial communities, intestinal permeability, and corticosterone in hens in enriched colonies (EC) and CF housing systems during [...] Read more.
To tease apart differences between conventional cage (CC) and cage-free (CF) housing systems, this study focuses on the effects of excreta exposure and age by comparing microbial communities, intestinal permeability, and corticosterone in hens in enriched colonies (EC) and CF housing systems during early- and late-lay. Hens were randomly selected from two rooms of CF (n = 20) and EC (n = 20) at 35 and 76 weeks of age. One hour following an oral gavage of fluorescein isothiocyanate dextran (FITC-D), hens were euthanized, and ileal contents and blood were collected. Serum FITC-D using a fluorescent spectrophotometer and corticosterone using a commercial competitive ELISA kit were analyzed. Following DNA isolation from the ileum contents, the V4 region of the 16S rRNA gene was sequenced. Sequence data were filtered in Mothur v1.43.0, followed by de novo operational taxonomic unit (OTU) clustering and classifying with the SILVA SSU v138 reference database. Serum FITC-D was altered by housing type, age of hens, and the interaction between housing type and age of hens (p < 0.001), with 76-week-old hens housed in EC having the highest FITC-D. Corticosterone increased with age (p = 0.023). Microbial community diversity measurements favored hens housed in the CF housing system as ileal contents tended to have increased species evenness (p = 0.008) and greater alpha diversity (p = 0.006). The majority of the over-representation of OTUs were associated with peak lay. Full article
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<p><span class="html-italic">Boxplots of the alpha diversity measurements of ileal microbiota from hens in late-lay and peak lay housed in cage-free (CF) and enriched colony (EC) systems.</span> Gold denotes the diversities from hens in late-lay, and red denotes the diversities from hens in peak lay. The parameters displayed are Observed which represents the number of different taxa observed in the sample, Chao1 which represents species richness within a sample, Shannon which represents the Shannon index or an estimate of both species richness and species evenness within a sample, and Simpson which represents species evenness within a sample.</p>
Full article ">Figure 2
<p><span class="html-italic">Principal coordinate analysis comparing the ileal microbiota of hens in cage-free (CF) and enriched colony (EC) systems as well as hens in late-lay and peak lay.</span> Gold denotes hens in late-lay, and red denotes hens in peak lay. Circles denote hens in CF systems, and triangles denote hens in EC systems.</p>
Full article ">Figure 3
<p><span class="html-italic">Relative abundance of phyla of ileal microbiota of hens in cage-free (CF) and enriched colony (EC) systems as well as hens in late-lay and peak lay.</span> (<b>A</b>) Percent of relative abundance of phyla for housing system. (<b>B</b>) Percent of relative abundance of phyla for late-lay and peak-lay hens.</p>
Full article ">Figure 4
<p><span class="html-italic">Relative abundance of top 15 genera of ileal microbiota of hens in cage-free (CF) and enriched colony (EC) systems as well as hens in late-lay and peak lay.</span> (<b>A</b>) Percent of relative abundance of genera for housing system. (<b>B</b>) Percent of relative abundance of genera for late-lay and peak-lay hens.</p>
Full article ">Figure 5
<p><span class="html-italic">Changes in ileal microbiota from hens in enriched colonies (EC) and cage-free (CF) systems across peak and late-lay.</span> Each graph depicts different significant (<span class="html-italic">p</span> &lt; 0.05, q &lt; 0.05) interaction for individual operational taxonomic unit (OTU). Gold lines represent average relative counts from ileal sample collected from enriched colonies. Red lines represent average relative counts from ileal sample collected from cage-free system.</p>
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16 pages, 6271 KiB  
Article
MicroRNA-148a Targets DNMT1 and PPARGC1A to Regulate the Viability, Proliferation, and Milk Fat Synthesis of Ovine Mammary Epithelial Cells
by Jiqing Wang, Na Ke, Xinmiao Wu, Huimin Zhen, Jiang Hu, Xiu Liu, Shaobin Li, Fangfang Zhao, Mingna Li, Bingang Shi, Zhidong Zhao, Chunyan Ren and Zhiyun Hao
Int. J. Mol. Sci. 2024, 25(16), 8558; https://doi.org/10.3390/ijms25168558 - 6 Aug 2024
Viewed by 253
Abstract
In this study, the expression profiles of miR-148a were constructed in eight different ovine tissues, including mammary gland tissue, during six different developmental periods. The effect of miR-148a on the viability, proliferation, and milk fat synthesis of ovine mammary epithelial cells (OMECs) was [...] Read more.
In this study, the expression profiles of miR-148a were constructed in eight different ovine tissues, including mammary gland tissue, during six different developmental periods. The effect of miR-148a on the viability, proliferation, and milk fat synthesis of ovine mammary epithelial cells (OMECs) was investigated, and the target relationship of miR-148a with two predicted target genes was verified. The expression of miR-148a exhibited obvious tissue-specific and temporal-specific patterns. miR-148a was expressed in all eight ovine tissues investigated, with the highest expression level in mammary gland tissue (p < 0.05). Additionally, miR-148a was expressed in ovine mammary gland tissue during each of the six developmental periods studied, with its highest level at peak lactation (p < 0.05). The overexpression of miR-148a increased the viability of OMECs, the number and percentage of Edu-labeled positive OMECs, and the expression levels of two cell-proliferation marker genes. miR-148a also increased the percentage of OMECs in the S phase. In contrast, transfection with an miR-148a inhibitor produced the opposite effect compared to the miR-148a mimic. These results indicate that miR-148a promotes the viability and proliferation of OMECs in Small-tailed Han sheep. The miR-148a mimic increased the triglyceride content by 37.78% (p < 0.01) and the expression levels of three milk fat synthesis marker genes in OMECs. However, the miR-148a inhibitor reduced the triglyceride level by 87.11% (p < 0.01). These results suggest that miR-148a promotes milk fat synthesis in OMECs. The dual-luciferase reporter assay showed that miR-148a reduced the luciferase activities of DNA methyltransferase 1 (DNMT1) and peroxisome proliferator-activated receptor gamma coactivator 1-A (PPARGC1A) in wild-type vectors, suggesting that they are target genes of miR-148a. The expression of miR-148a was highly negatively correlated with PPARGC1A (r = −0.789, p < 0.001) in ovine mammary gland tissue, while it had a moderate negative correlation with DNMT1 (r = −0.515, p = 0.029). This is the first study to reveal the molecular mechanisms of miR-148a underlying the viability, proliferation, and milk fat synthesis of OMECs in sheep. Full article
(This article belongs to the Section Biochemistry)
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<p>Expression levels of miR-148a in ovine eight different tissues (<b>A</b>), mammary gland tissue during different developmental periods (<b>B</b>) and mammary gland tissue at peak lactation of Small-tailed Han sheep and Gansu Alpine Merino sheep (<b>C</b>). Values with different lowercase letters above the bars are different (<span class="html-italic">p</span> &lt; 0.05). ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Transfection efficiency of miR-148a detected using RT-qPCR (<b>A</b>) and its effect on the viability of ovine mammary epithelial cells (<b>B</b>). ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 3
<p>Effect of miR-148a on the proliferation of ovine mammary epithelial cells (OMECs) when the miR-148a mimic and miR-148a inhibitor were transfected into OMECs. (<b>A</b>) Proliferation of OMECs detected using an Edu assay. (<b>B</b>) Percentage of Edu-labeled positive OMECs. (<b>C</b>) Relative expression levels of <span class="html-italic">CDK4</span> and <span class="html-italic">CDK2</span>. ** <span class="html-italic">p</span> &lt; 0.01 and * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 4
<p>Effects of the miR-148a mimic (<b>A</b>) and miR-148a inhibitor (<b>C</b>) on the cycle of ovine mammary epithelial cells (OMECs) when compared to the miR-148a mimic NC (<b>B</b>) and miR-148a inhibitor NC (<b>D</b>).</p>
Full article ">Figure 5
<p>Effect of miR-148a on the triglyceride level (<b>A</b>) and expression levels of <span class="html-italic">mTOR</span> (<b>B</b>), <span class="html-italic">DGAT1</span> (<b>C</b>), and <span class="html-italic">ABCG2</span> (<b>D</b>) in ovine mammary epithelial cells (OMECs). ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 5 Cont.
<p>Effect of miR-148a on the triglyceride level (<b>A</b>) and expression levels of <span class="html-italic">mTOR</span> (<b>B</b>), <span class="html-italic">DGAT1</span> (<b>C</b>), and <span class="html-italic">ABCG2</span> (<b>D</b>) in ovine mammary epithelial cells (OMECs). ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 6
<p>Construction and sequencing results of dual luciferase reporter vectors for two target genes. (<b>A</b>) The structural diagram of dual luciferase reporter vectors. (<b>B</b>) Sequence validation of the target gene <span class="html-italic">DNMT1</span> in wild-type (WT) and mutant-type (MUT) pmiR-RB-Report™ vectors by Sanger sequencing. (<b>C</b>) Sequence validation of the target gene <span class="html-italic">PPARGC1A</span> in WT and MUT pmiR-RB-Report™ vectors by Sanger sequencing.</p>
Full article ">Figure 6 Cont.
<p>Construction and sequencing results of dual luciferase reporter vectors for two target genes. (<b>A</b>) The structural diagram of dual luciferase reporter vectors. (<b>B</b>) Sequence validation of the target gene <span class="html-italic">DNMT1</span> in wild-type (WT) and mutant-type (MUT) pmiR-RB-Report™ vectors by Sanger sequencing. (<b>C</b>) Sequence validation of the target gene <span class="html-italic">PPARGC1A</span> in WT and MUT pmiR-RB-Report™ vectors by Sanger sequencing.</p>
Full article ">Figure 7
<p>Validation of miR-148a with the predicted target genes <span class="html-italic">DNMT1</span> and <span class="html-italic">PPARGC1A</span>. (<b>A</b>,<b>B</b>) The luciferase activities of the target genes <span class="html-italic">DNMT1</span> and <span class="html-italic">PPARGC1A</span> for miR-148a detected using a dual luciferase reporter assay. (<b>C</b>,<b>D</b>) Effect of miR-148a on the expression levels of the target genes <span class="html-italic">DNMT1</span> and <span class="html-italic">PPARGC1A</span>. ** <span class="html-italic">p</span> &lt; 0.01 and * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 8
<p>Expression levels of the target genes <span class="html-italic">DNMT1</span> (<b>A</b>) and <span class="html-italic">PPARGC1A</span> (<b>B</b>) for miR-148a in ovine mammary gland tissue during six different developmental periods. Values with different lowercase letters above the bars are different (<span class="html-italic">p</span> &lt; 0.05).</p>
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9 pages, 2107 KiB  
Article
Bacterial Communities Associated with the Leaves and the Roots of Salt Marsh Plants of Bayfront Beach, Mobile, Alabama, USA
by Aqsa Majeed, Jinbao Liu, Adelle J. Knight, Karolina M. Pajerowska-Mukhtar and M. Shahid Mukhtar
Microorganisms 2024, 12(8), 1595; https://doi.org/10.3390/microorganisms12081595 - 6 Aug 2024
Viewed by 347
Abstract
Salt marshes are highly dynamic and biologically diverse ecosystems that serve as natural habitats for numerous salt-tolerant plants (halophytes). We investigated the bacterial communities associated with the roots and leaves of plants growing in the coastal salt marshes of the Bayfront Beach, located [...] Read more.
Salt marshes are highly dynamic and biologically diverse ecosystems that serve as natural habitats for numerous salt-tolerant plants (halophytes). We investigated the bacterial communities associated with the roots and leaves of plants growing in the coastal salt marshes of the Bayfront Beach, located in Mobile, Alabama, United States. We compared external (epiphytic) and internal (endophytic) communities of both leaf and root plant organs. Using 16S rDNA amplicon sequencing methods, we identified 10 bacterial phyla and 59 different amplicon sequence variants (ASVs) at the genus level. Bacterial strains belonging to the phyla Proteobacteria, Bacteroidetes, and Firmicutes were highly abundant in both leaf and root samples. At the genus level, sequences of the genus Pseudomonas were common across all four sample types, with the highest abundance found in the leaf endophytic community. Additionally, Pantoea was found to be dominant in leaf tissue compared to roots. Our study revealed that plant habitat (internal vs. external for leaves and roots) was a determinant of the bacterial community structure. Co-occurrence network analyses enabled us to discern the intricate characteristics of bacterial taxa. Our network analysis revealed varied levels of ASV complexity in the epiphytic networks of roots and leaves compared to the endophytic networks. Overall, this study advances our understanding of the intricate composition of the bacterial microbiota in habitats (epiphytic and endophytic) and organs (leaf and root) of coastal salt marsh plants and suggests that plants might recruit habitat- and organ-specific bacteria to enhance their tolerance to salt stress. Full article
(This article belongs to the Section Plant Microbe Interactions)
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<p>Bacterial community composition and diversity salt-marsh plants. (<b>A</b>,<b>B</b>) Group-wise relative abundance of dominating phylum and genus of root and leaf endophytes and epiphytes. (<b>C</b>) Shared and unique ASVs between all four groups. (<b>D</b>) Principal Coordinates Analysis (PCoA) of all samples based on Jaccard’s index (binary data). (<b>E</b>,<b>F</b>) An increase in microbial richness and diversity was found in roots compared to leaves in epiphytic habitats, revealed by Chao 1 and Shannon index.</p>
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<p>Four groups each for endophytic (<b>A</b>) and epiphytic networks (<b>B</b>) are illustrated. Individual types of networks within each category are indicated. With the node size proportional to node connectivity, the node color represents various phyla, while the line color indicates positive (red) and negative (blue) correlation coefficients. Network construction employed Spearman’s correlation coefficient, with r &gt; 0.6 and <span class="html-italic">p</span> &lt; 0.05 as criteria.</p>
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20 pages, 57504 KiB  
Article
Protopine-Type Alkaloids Alleviate Lipopolysaccharide-Induced Intestinal Inflammation and Modulate the Gut Microbiota in Mice
by Jialu Huang, Meishan Yue, Yang Yang, Yisong Liu and Jianguo Zeng
Animals 2024, 14(15), 2273; https://doi.org/10.3390/ani14152273 - 5 Aug 2024
Viewed by 296
Abstract
In this study, we assessed the therapeutic effects of Macleaya cordata (Willd). R. Br.-derived protopine-type alkaloids (MPTAs) in a mouse model of lipopolysaccharide (LPS)-induced intestinal inflammation. The experimental design involved the allocation of mice into distinct groups, including a control group, a model [...] Read more.
In this study, we assessed the therapeutic effects of Macleaya cordata (Willd). R. Br.-derived protopine-type alkaloids (MPTAs) in a mouse model of lipopolysaccharide (LPS)-induced intestinal inflammation. The experimental design involved the allocation of mice into distinct groups, including a control group, a model group treated with 6 mg/kg LPS, a berberine group treated with 50 mg/kg berberine hydrochloride and low-, medium- and high-dose MPTA groups treated with 6, 12 and 24 mg/kg MPTAs, respectively. Histological analysis of the ileum, jejunum and duodenum was performed using Hematoxylin and Eosin (H&E) staining. Moreover, the quantification of intestinal goblet cells (GCs) was performed based on PAS staining. The serum levels of IL-1β, IL-6, IL-8 and TNF-α were quantified using an enzyme-linked immunosorbent assay (ELISA), while the mRNA levels of TLR4, NF-κB p65, NLRP3, IL-6 and IL-1β were assessed using quantitative PCR (qPCR). The protein levels of TLR4, Md-2, MyD88, NF-κB p65 and NLRP3 were determined using Western blotting. Furthermore, the 16S rDNA sequences of bacterial taxa were amplified and analysed to determine alterations in the gut microbiota of the mice following MPTA treatment. Different doses of MPTAs were found to elicit distinct therapeutic effects, leading to enhanced intestinal morphology and an increased abundance of intestinal GCs. A significant decrease was noted in the levels of pro-inflammatory cytokines (IL-1β, IL-6, IL-8 and TNF-α). Additionally, the protein levels of TLR4, MyD88, NLRP3 and p-p65/p65 were markedly reduced by MPTA treatment. Furthermore, 16S rDNA sequencing analysis revealed that the administration of 24 mg/kg MPTAs facilitated the restoration of microbial composition. Full article
(This article belongs to the Section Animal Nutrition)
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<p>The experimental grouping.</p>
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<p>Effects of MPTAs on the symptoms of LPS-induced mice. (<b>A</b>) Body weight of LPS-induced mice. (<b>B</b>) Weight changes [(final weight − initial weight)/initial weight × 100%] in LPS-induced mice. (<b>C</b>) Diarrhoea symptoms in LPS-induced mice. Red arrows indicate that the white intestine and the drained intestinal contents induced by acute diarrhea. (<b>D</b>) Diarrhoea index. Results are presented as the mean ± standard error of the mean (SEM). <span class="html-italic">p</span>-value &lt; 0.01 (##) versus the control group, and <span class="html-italic">p</span>-value &lt; 0.01 (**) versus the LPS group.</p>
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<p>Effects of MPTAs on the duodenal morphology in LPS-induced mice. (<b>A</b>) Duodenal morphology based on H&amp;E staining; Intestinal villi shortening, shedding (blue arrow), Villous epithelial cells separate from the lamina propria (black arrow) and inflammatory cell infiltrationin the epithelium of the intestine (yellow arrow); scale bar: 50 μm. (<b>B</b>) Statistical analysis of villus height (VH), crypt depth (CD) and VH/CD ratio. Results are presented as the mean ± standard error of the mean (SEM). <span class="html-italic">p</span>-value &lt; 0.01 (##) versus the control group, and <span class="html-italic">p</span>-value &lt; 0.01 (**) versus the LPS group.</p>
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<p>Effects of MPTAs on duodenal goblet cells (GCs) in LPS-induced mice. (<b>A</b>) Duodenal GCs assessed using PAS staining; scale bar: 50 μm. (<b>B</b>) Statistical analysis of the number of GCs. Results are presented as the mean ± standard error of the mean (SEM). <span class="html-italic">p</span>-value &lt; 0.01 (##) versus the control group, and <span class="html-italic">p</span>-value &lt; 0.05 (*) or 0.01 (**) versus the LPS group.</p>
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<p>Effects of MPTAs on serum cytokine levels in LPS-induced mice. Assessment of the levels of TNF-α (<b>A</b>), IL-8 (<b>B</b>), IL-1β (<b>C</b>) and IL-6 (<b>D</b>) using ELISA kits. Results are presented as the mean ± standard error of the mean (SEM). <span class="html-italic">p</span>-value &lt; 0.01 (##) versus the control group, and <span class="html-italic">p</span>-value &lt; 0.05 (*) or 0.01 (**) versus the LPS group.</p>
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<p>Effects of MPTAs on inflammatory response in LPS-induced mice. Assessment of relative mRNA levels of IL-1β, TLR4, NLRP3 and NF-κB in the duodenum (<b>A</b>) and colon (<b>B</b>) of mice. Results are presented as the mean ± standard error of the mean (SEM). <span class="html-italic">p</span>-value &lt; 0.05 (#) or 0.01 (##) versus the control group, and <span class="html-italic">p</span>-value &lt; 0.05 (*) or 0.01 (**) versus the LPS group.</p>
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<p>Effects of MPTAs on the NF-κB and NLRP3 pathways. (<b>A</b>) Assessment of protein levels of TLR4, MD-2, MyD88, NF-κB p65 and NF-κB p-p65 in the duodenum of mice. (<b>B</b>) Statistical analysis of relative expression levels of TLR-4, MD-2, MyD88 compared with internal control protein β-actin and NF-κB p-p65 compared with NF-κB p65. (<b>C</b>) Assessment of protein levels of NLPR3 and IL-18 in the duodenum of mice. (<b>D</b>) Statistical analysis of relative expression levels of NLPR3 and IL-18 compared with internal control protein β-actin. Results are presented as the mean ± standard error of the mean (SEM). <span class="html-italic">p</span>-value &lt; 0.05 (#) or 0.01 (##) versus the control group, and <span class="html-italic">p</span>-value &lt; 0.05 (*) or 0.01 (**) versus the LPS group.</p>
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<p>Number of bacterial OTUs in faecal samples of LPS-induced mice. OTU level (<b>A</b>) and sparse curve (<b>B</b>) of LPS-induced mouse faeces.</p>
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<p>α-diversity analysis of the intestinal microbiota of LPS-induced mice. Assessment of ACE (<b>A</b>), Chao1 (<b>B</b>), Shannon (<b>C</b>), Simpson (<b>D</b>) and Sobs (<b>E</b>) indices and coverage (<b>F</b>) in the faecal samples of LPS-induced mice. Results are presented as the mean ± standard error of the mean (SEM). <span class="html-italic">p</span>-value &lt; 0.05 (*), 0.01 (**) or 0.001 (***).</p>
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<p>β-diversity analysis of intestinal microbiota of LPS-induced mice. Principal coordinate analysis (PCoA) (<b>A</b>) and non-metric multi-dimensional scaling (NMDS) analysis (<b>B</b>) of the faecal samples of LPS-induced mice.</p>
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<p>Microbial community composition. (<b>A</b>) Composition analysis of each bacterial group at the phylum level. (<b>B</b>) Cladogram showing taxa with different abundance in LPS-induced mice. (<b>C</b>) Welch’s <span class="html-italic">t</span>-test bar plot comparing the microbiome between control and LPS groups at the genus level. (<b>D</b>) Welch’s <span class="html-italic">t</span>-test bar plot comparing the microbiome between LPS and LPS + H-MPTA groups at the genus level. <span class="html-italic">p</span>-value &lt; 0.05 (*) or 0.01 (**).</p>
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<p>Spearman correlation analysis. (<b>A</b>) Heatmap analysis of the gut microbiota. (<b>B</b>) Spearman correlation analysis assessing the correlation of inflammatory cytokines with 16 rDNA of the gut microbiota. <span class="html-italic">p</span>-value &lt; 0.05 (*), 0.01 (**) or 0.001 (***).</p>
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<p>Analysis of volatile acetic acids. Results are presented as the mean ± standard error of the mean (SEM). <span class="html-italic">p</span>-value &lt; 0.01 (##) versus the control group, and <span class="html-italic">p</span>-value &lt; 0.05 (*) or 0.01 (**) versus the LPS group.</p>
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<p>Graphical summary.</p>
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26 pages, 498 KiB  
Review
Structure and Evolution of Ribosomal Genes of Insect Chromosomes
by Vladimir E. Gokhman and Valentina G. Kuznetsova
Insects 2024, 15(8), 593; https://doi.org/10.3390/insects15080593 - 4 Aug 2024
Viewed by 445
Abstract
Currently, clusters of 45S and 5S ribosomal DNA (rDNA) have been studied in about 1000 and 100 species of the class Insecta, respectively. Although the number of insect species with known 45S rDNA clusters (also referred to as nucleolus-organizing regions, or NORs) constitutes [...] Read more.
Currently, clusters of 45S and 5S ribosomal DNA (rDNA) have been studied in about 1000 and 100 species of the class Insecta, respectively. Although the number of insect species with known 45S rDNA clusters (also referred to as nucleolus-organizing regions, or NORs) constitutes less than 0.1 percent of the described members of this enormous group, certain conclusions can already be drawn. Since haploid karyotypes with single 45S and 5S rDNA clusters predominate in both basal and derived insect groups, this character state is apparently ancestral for the class Insecta in general. Nevertheless, the number, chromosomal location, and other characteristics of both 45S and 5S rDNA sites substantially vary across different species, and sometimes even within the same species. There are several main factors and molecular mechanisms that either maintain these parameters or alter them on the short-term and/or long-term scale. Chromosome structure (i.e., monocentric vs. holokinetic chromosomes), excessive numbers of rRNA gene copies per cluster, interactions with transposable elements, pseudogenization, and meiotic recombination are perhaps the most important among them. Full article
(This article belongs to the Section Insect Molecular Biology and Genomics)
13 pages, 1250 KiB  
Article
Aquibium pacificus sp. nov., a Novel Mixotrophic Bacterium from Bathypelagic Seawater in the Western Pacific Ocean
by Fan Jiang, Xun Hao, Ding Li, Xuying Zhu, Jiamei Huang, Qiliang Lai, Jianning Wang, Liping Wang and Zongze Shao
Microorganisms 2024, 12(8), 1584; https://doi.org/10.3390/microorganisms12081584 - 4 Aug 2024
Viewed by 314
Abstract
A novel Gram-stain-negative, facultatively anaerobic, and mixotrophic bacterium, designated as strain LZ166T, was isolated from the bathypelagic seawater in the western Pacific Ocean. The cells were short rod-shaped, oxidase- and catalase-positive, and motile by means of lateral flagella. The growth of [...] Read more.
A novel Gram-stain-negative, facultatively anaerobic, and mixotrophic bacterium, designated as strain LZ166T, was isolated from the bathypelagic seawater in the western Pacific Ocean. The cells were short rod-shaped, oxidase- and catalase-positive, and motile by means of lateral flagella. The growth of strain LZ166T was observed at 10–45 °C (optimum 34–37 °C), at pH 5–10 (optimum 6–8), and in the presence of 0–5% NaCl (optimum 1–3%). A phylogenetic analysis based on the 16S rRNA gene showed that strain LZ166T shared the highest similarity (98.58%) with Aquibium oceanicum B7T and formed a distinct branch within the Aquibium genus. The genomic characterization, including average nucleotide identity (ANI, 90.73–76.79%), average amino identity (AAI, 88.50–79.03%), and digital DNA–DNA hybridization (dDDH, 36.1–22.2%) values between LZ166T and other species within the Aquibium genus, further substantiated its novelty. The genome of strain LZ166T was 6,119,659 bp in size with a 64.7 mol% DNA G+C content. The predominant fatty acid was summed feature 8 (C18:1ω7c and/or C18:1ω6c). The major polar lipids identified were diphosphatidylglycerol (DPG), phosphatidylethanolamine (PE), glycolipid (GL), and phosphatidylglycerol (PG), with ubiquinone-10 (Q-10) as the predominant respiratory quinone. The genomic annotation indicated the presence of genes for a diverse metabolic profile, including pathways for carbon fixation via the Calvin–Benson–Bassham cycle and inorganic sulfur oxidation. Based on the polyphasic taxonomic results, strain LZ166T represented a novel species of the genus Aquibium, for which the name Aquibium pacificus sp. nov. is proposed, with the type strain LZ166T (=MCCC M28807T = KACC 23148T = KCTC 82889T). Full article
(This article belongs to the Section Microbiomes)
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Figure 1
<p>Maximum likelihood phylogenetic tree based on 13 16S rRNA gene sequences showing the positions between strain LZ166<sup>T</sup> and other closely related phylogenetic neighbors. Bootstrap numbers (&gt;70%) were shown with 1000 calculations. The bold font represents the novel species identified in this study. <span class="html-italic">Bradyrhizobium japonicum</span> DSMZ_30131<sup>T</sup> (X87272) was used as the out group. Bar, 0.01 substitutions per nucleotide position.</p>
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<p>Phylogenomic tree of LZ166<sup>T</sup> and its functional genes involved in carbon, sulfur, and nitrogen metabolism in comparison with closely related species. The bold font represents the novel species identified in this study. <span class="html-italic">Bradyrhizobium japonicum</span> USDA 6<sup>T</sup> (GFC_000284375.1) was used as the out group. Bar, 0.05 substitutions per nucleotide position. Pink, green, and yellow blocks, presence of corresponding carbon, sulfur, and nitrogen functional genes, respectively. White blocks, absence or partial presence of corresponding functional genes. <span class="html-italic">rcbL</span>, ribulose-1,5-bisphosphate carboxylase/oxygenase gene large chain. <span class="html-italic">prk</span>, phosphoribulokinase gene. <span class="html-italic">CA</span>, carbonic anhydrase gene. <span class="html-italic">coxMSL</span>, carbon monoxide dehydrogenase (form I) gene. <span class="html-italic">coxSLM</span>, carbon monoxide dehydrogenase (form II) gene. <span class="html-italic">sox</span>, thiosulfate oxidation genes cluster (<span class="html-italic">soxABCDXYZ</span>). <span class="html-italic">fcc</span>, flavocytochrome c-sulfide dehydrogenase gene. <span class="html-italic">sqr</span>, sulfide:quinone oxidoreductases gene. <span class="html-italic">soe</span>, sulfite dehydrogenase (quinone) gene. <span class="html-italic">cys</span>, assimilatory sulfate reduction genes cluster (<span class="html-italic">cysNDCHJIK</span>). <span class="html-italic">sat</span>, sulfate adenylyltransferase gene. <span class="html-italic">aprAB</span>, adenylylsulfate reductase gene. <span class="html-italic">dsr</span>, dissimilatory sulfite reductase gene. <span class="html-italic">nifH</span>, nitrogenase gene. <span class="html-italic">nirK</span>, copper-containing nitrite reductase (denitrification) gene. <span class="html-italic">nosZ</span>, nitrous oxide reductase gene. <span class="html-italic">norB</span> nitric oxide reductase gene. <span class="html-italic">napA</span>, periplasmic dissimilatory nitrate reductase gene. <span class="html-italic">narG</span>, membrane-bound dissimilatory nitrate reductase gene. <span class="html-italic">nirBD</span>, dissimilatory nitrite reductase (NADH) gene. <span class="html-italic">nrfAH</span>, dissimilatory nitrite reductase (cytochrome c-552). <span class="html-italic">nasD</span>, assimilatory nitrite reductase gene. <span class="html-italic">nasA</span>, assimilatory nitrate reductase. <span class="html-italic">glnA</span>, glutamine synthase gene. <span class="html-italic">gltB</span>, glutamate synthase gene. <span class="html-italic">ure</span>, urease gene. <span class="html-italic">gdh</span>, glutamate dehydrogenase gene.</p>
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<p>Reconstructed carbon (pink), sulfur (green), and nitrogen (yellow) metabolism of strain LZ166<sup>T</sup> based on functional genes (corresponding enzymes are in red). ED, Entner–Doudoroff pathway. EMP, Embden–Meyerhof–Parnas pathway. HMP, hexose monophosphate pathway. CBB, Calvin–Benson–Bassham cycle. TCA, tricarboxylic acid cycle. GAP, glyceraldehyde 3–phosphate. RU–5–P, ribulose–5–phosphate. PRK, phosphoribulokinase. RUBP, ribulose–1,5–bisphosphate. RuBisCO, ribulose–1,5–bisphosphate carboxylase/oxygenase. 3–PGA, 3–phosphoglycerate. 1, 3–PGA, 1, 3–diphosphoglycerate. PAPS, phosphoadenosine phosphosulfate. APS, adenosine 5′–phosphosulfate. CA, carbonic anhydrase. Cox, carbon monoxide dehydrogenase. NirK, copper-containing nitrite reductase. NosZ, nitrous oxide reductase. NasD, assimilatory nitrite reductase. GlnA, glutamine synthase. GltB, glutamate synthase. Gdh, glutamate dehydrogenase. Ure, urease. CysK, cysteine synthase. CysI, sulfite reductase (NADPH) hemoprotein beta-component. CysJ, sulfite reductase (NADPH) flavoprotein alpha-component. CysH, PAPS reductase. CysC, adenylylsulfate kinase. CysN, sulfate adenylyltransferase subunit 1. CysD, sulfate adenylyltransferase subunit 2. SOX, thiosulfate oxidation enzymes. Soe sulfite dehydrogenase. Sqr, sulfide:quinone oxidoreductases. Fcc, flavocytochrome c-sulfide dehydrogenase.</p>
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15 pages, 4357 KiB  
Review
Species of the Sections Hedysarum and Multicaulia of the Genus Hedysarum (Fabaceae): Taxonomy, Distribution, Chromosomes, Genomes, and Phylogeny
by Olga Yu. Yurkevich, Tatiana E. Samatadze, Svyatoslav A. Zoshchuk, Alexandra V. Amosova and Olga V. Muravenko
Int. J. Mol. Sci. 2024, 25(15), 8489; https://doi.org/10.3390/ijms25158489 - 3 Aug 2024
Viewed by 337
Abstract
The genus Hedysarum L. (Fabaceae) includes about 200 species of annual and perennial herbs distributed in Asia, Europe, North Africa, and North America. Many species of this genus are valuable medicinal, melliferous, and forage resources. In this review, we consider the taxonomic history [...] Read more.
The genus Hedysarum L. (Fabaceae) includes about 200 species of annual and perennial herbs distributed in Asia, Europe, North Africa, and North America. Many species of this genus are valuable medicinal, melliferous, and forage resources. In this review, we consider the taxonomic history of the genus Hedysarum, the chromosomal organization of the species from the sections Hedysarum and Multicaulia, as well as phylogenetic relationships between these sections. According to morphological, genetic, and phylogenetic data, the genus Hedysarum is divided into three main sections: Hedysarum (= syn. Gamotion), Multicaulia, and Stracheya. In species of this genus, two basic chromosome numbers, x = 7 (section Hedysarum) and x = 8 (sections Multicaulia and Stracheya), were determined. The systematic positions of some species within the sections are still uncertain due to their morphological similarities. The patterns of distribution of molecular chromosomal markers (45S rDNA, 5S rDNA, and different satellite DNAs) in karyotypes of various Hedysarum species made it possible to determine their ploidy status and also specify genomic relationships within the sections Hedysarum and Multicaulia. Recent molecular phylogenetic studies clarified significantly the taxonomy and evolutionary development of the genus Hedysarum. Full article
(This article belongs to the Special Issue Plant Phylogenomics and Genetic Diversity (2nd Edition))
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<p>Plants growing on the trial plot (AIMAP, Moscow) and wild populations of some <span class="html-italic">Hedysarum</span> species. <span class="html-italic">H. alpinum</span> (the trial plot of AIMAP, Moscow, Russia) (<b>A</b>), <span class="html-italic">H. neglectum</span> (the Altai region, Russia) (<b>B</b>), <span class="html-italic">H. theinum</span> (Kazakhstan) (<b>C</b>), <span class="html-italic">H. flavescens</span> (the trial plot of AIMAP, Moscow, Russia) (<b>D</b>), <span class="html-italic">H. grandiflorum</span> (Volgograd region, Russia) (<b>E</b>), and <span class="html-italic">H. razoumovianum</span> (Volgograd region, Russia) (<b>F</b>). The figure is adapted from “Molecular Cytogenetics of Eurasian Species of the Genus <span class="html-italic">Hedysarum</span> L. (Fabaceae)” by Yurkevich et al., 2021, <span class="html-italic">Plants</span>, 10, 89 [<a href="#B29-ijms-25-08489" class="html-bibr">29</a>] and “Integration of Genomic and Cytogenetic Data on Tandem DNAs for Analyzing the Genome Diversity Within the Genus <span class="html-italic">Hedysarum</span> L. (Fabaceae)” by Yurkevich et al., 2022, <span class="html-italic">Frontiers in Plant Science</span>, <span class="html-italic">13</span>, 865958 [<a href="#B39-ijms-25-08489" class="html-bibr">39</a>].</p>
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<p>Karyotypes of the studied accessions of species from the sect. <span class="html-italic">Hedysarum</span>. Karyograms of <span class="html-italic">H. flavescens</span> (<b>a</b>), <span class="html-italic">H. hedysaroides</span> (<b>b</b>), <span class="html-italic">H. arcticum</span> (<b>c</b>), <span class="html-italic">H. austrosibiricum</span> (<b>d</b>), <span class="html-italic">H. theinum</span> (<b>e</b>), <span class="html-italic">H. alpinum</span> (<b>f</b>), <span class="html-italic">H. caucasicum</span> (<b>g</b>), and <span class="html-italic">H. neglectum</span> (<b>h</b>) after FISH with 45S rDNA (green) and 5S rDNA (red). Chromosome DAPI-staining—blue. The figure is adapted from “Molecular Cytogenetics of Eurasian Species of the Genus <span class="html-italic">Hedysarum</span> L. (Fabaceae)” by Yurkevich et al., 2021, <span class="html-italic">Plants</span>, 10, 89 [<a href="#B29-ijms-25-08489" class="html-bibr">29</a>].</p>
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<p>Karyotypes of the studied species accessions from the sect. <span class="html-italic">Multicaulia</span>. Karyograms of the studied accessions of diploid <span class="html-italic">H. grandiflorum</span> (<b>a</b>), <span class="html-italic">H. razoumovianum</span> (<b>b</b>), <span class="html-italic">H. zundukii</span> (<b>c</b>), <span class="html-italic">H. dahuricum</span> (<b>d</b>), and also tetraploid <span class="html-italic">H. gmelinii</span> (<b>e</b>), and <span class="html-italic">H. setigerum</span> (<b>f</b>) after FISH with 45S (green) and 5S (red) rDNA. B—B chromosomes. DAPI chromosome staining—blue. The figure is adapted from “Integration of Genomic and Cytogenetic Data on Tandem DNAs for Analyzing the Genome Diversity Within the Genus <span class="html-italic">Hedysarum</span> L. (Fabaceae)” by Yurkevich et al., 2022, <span class="html-italic">Frontiers in Plant Science</span>, <span class="html-italic">13</span>, 865958 [<a href="#B39-ijms-25-08489" class="html-bibr">39</a>].</p>
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<p>Genome proportion of most abundant DNA repeats in <span class="html-italic">H. grandiflorum</span>, <span class="html-italic">H. dahuricum</span>, and <span class="html-italic">H. zundukii</span>. The genome proportion of individual repeat types was obtained as a ratio of reads specific to individual repeat types to all reads used for clustering analyses by the RepeatExplorer pipelines. The figure is adapted from “Integration of Genomic and Cytogenetic Data on Tandem DNAs for Analyzing the Genome Diversity Within the Genus <span class="html-italic">Hedysarum</span> L. (Fabaceae)” by Yurkevich et al., 2022, <span class="html-italic">Frontiers in Plant Science</span>, <span class="html-italic">13</span>, 865958 [<a href="#B39-ijms-25-08489" class="html-bibr">39</a>].</p>
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<p>Generalized idiograms of <span class="html-italic">Hedysarum</span> chromosomes showing the chromosomal distribution of the examined markers: Hz 6 (green), 45S rDNA (blue), and 5S rDNA (red). Asterisks indicate polymorphic sites. The figure is adapted from “Integration of Genomic and Cytogenetic Data on Tandem DNAs for Analyzing the Genome Diversity Within the Genus <span class="html-italic">Hedysarum</span> L. (Fabaceae)” by Yurkevich et al., 2022, <span class="html-italic">Frontiers in Plant Science</span>, <span class="html-italic">13</span>, 865958 [<a href="#B39-ijms-25-08489" class="html-bibr">39</a>].</p>
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<p>Karyograms of the <span class="html-italic">H. flavescens</span> (<b>a</b>), <span class="html-italic">H. theinum</span> (<b>b</b>), <span class="html-italic">H. grandiflorum</span> (<b>c</b>), and <span class="html-italic">H. dahuricum</span> (<b>d</b>) after FISH with 45S rDNA (green) and 5S rDNA (red), and also rapidGISH with genomic DNA of <span class="html-italic">H. flavescens</span> and/or <span class="html-italic">H. alpinum</span> (red). Chromosome DAPI-staining—blue. The figure is adapted from “Comparative analysis of genomes of six species of <span class="html-italic">Hedysarum</span> L. (Fabaceae) by the rapidGISH technique” by Yurkevich et al., 2023, <span class="html-italic">Problems of Botany in Southern Siberia and Mongolia 22</span>, 436–440 [<a href="#B92-ijms-25-08489" class="html-bibr">92</a>].</p>
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16 pages, 2809 KiB  
Article
Early Detection of Food Safety and Spoilage Incidents Based on Live Microbiome Profiling and PMA-qPCR Monitoring of Indicators
by May Cohen Hakmon, Keren Buhnik-Rosenblau, Hila Hanani, Hila Korach-Rechtman, Dagan Mor, Erez Etkin and Yechezkel Kashi
Foods 2024, 13(15), 2459; https://doi.org/10.3390/foods13152459 - 3 Aug 2024
Viewed by 463
Abstract
The early detection of spoilage microorganisms and food pathogens is of paramount importance in food production systems. We propose a novel strategy for the early detection of food production defects, harnessing the product microbiome. We hypothesize that by establishing microbiome datasets of proper [...] Read more.
The early detection of spoilage microorganisms and food pathogens is of paramount importance in food production systems. We propose a novel strategy for the early detection of food production defects, harnessing the product microbiome. We hypothesize that by establishing microbiome datasets of proper and defective batches, indicator bacteria signaling production errors can be identified and targeted for rapid quantification as part of routine practice. Using the production process of pastrami as a model, we characterized its live microbiome profiles throughout the production stages and in the final product, using propidium monoazide treatment followed by 16S rDNA sequencing. Pastrami demonstrated product-specific and consistent microbiome profiles predominated by Serratia and Vibrionimonas, with distinct microbial signatures across the production stages. Based on the established microbiome dataset, we were able to detect shifts in the microbiome profile of a defective batch produced under lactate deficiency. The most substantial changes were observed as increased relative abundances of Vibrio and Lactobacillus, which were subsequently defined as potential lactate-deficiency indicators. PMA-qPCR efficiently detected increased levels of these species, thus proving useful in rapidly pinpointing the production defect. This approach offers the possibility of the in-house detection of defective production events with same-day results, promoting safer food production systems. Full article
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Figure 1
<p>Live microbiome profiling of different meat products and batches. Microbiome composition in the different meat products was assessed using PMA treatment followed by 16S rRNA gene sequencing. (<b>A</b>) Relative abundances displayed by taxa bar plots. Each column represents the live microbiome of a single sample with the eight most-abundant genera listed on the right side of the diagram. (<b>B</b>) Beta diversities of bacterial communities clustered using PCoA, based on weighted UniFrac measure; significant differences were observed among the microbiota profiles of the different products (ANOSIM R = 0.7).</p>
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<p>The live microbiome profiling of main stages along the BarBQ pastrami production chain. The microbiome composition of the live bacteria in the different production stages was assessed using 16S rRNA gene sequencing. (<b>A</b>) Relative abundances displayed by taxa bar plots. Each column represents the live microbiome of a single sample with the eight most-abundant genera listed on the right side of the diagram. (<b>B</b>) Beta diversities of bacterial communities clustered using PCoA, based on weighted UniFrac measure; ANOSIM R = 0.96; <span class="html-italic">p</span> &lt; 0.05 for comparison of every two stages. Raw material: raw chicken and turkey meat after defrosting and grinding. Brine: a mixture of water, spices and preservatives. Mixture: raw material mixed with the brine, incubated overnight at 4 °C. After cooking: mixture cooked for 3 h to an internal Tmax of 72 °C. After slicing: the final product sliced into thin slices and packed.</p>
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<p>The live microbiome profiling of main stages along the pastrami production chain and a long-term storage period, with and without potassium lactate. The microbiome composition in the different production stages of the properly produced batch (upper plot) and the lactate-deficient batch (lower plot) was assessed using 16S rRNA gene sequencing. Each column represents the live microbiome of a single sample with the 11 most-abundant genera listed on the right side of the diagram. Raw material: raw chicken and turkey meat after defrosting and grinding. Brine: a mixture of water, spices and preservatives. Mixture: raw material mixed with the brine, incubated overnight at 4 °C. After cooking: mixture cooked for 3 h to an internal Tmax of 72 °C. After slicing: the final product sliced into thin slices and packed. One/two/six weeks/three months in storage represent the long-term storage periods of the products at 4 °C.</p>
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<p>Highlighted <span class="html-italic">Vibrio</span> prevalence along different stages of the pastrami production process and a following long-term storage period, with and without potassium lactate. The relative abundance of <span class="html-italic">Vibrio</span> out of the entire microbiome composition, obtained for the different production stages of the properly produced batch (<b>upper plot</b>) and the lactate-deficient batch (<b>lower plot</b>), corresponds to the one presented in <a href="#foods-13-02459-f003" class="html-fig">Figure 3</a>.</p>
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<p>Highlighted <span class="html-italic">Lactobacillus</span> prevalence along different stages of the pastrami production process and a following long-term storage period, with and without potassium lactate. The relative abundance of <span class="html-italic">Lactobacillus</span> out of the entire microbiome composition, obtained for the different production stages of the properly produced batch (<b>upper plot</b>) and the lactate-deficient batch (<b>lower plot</b>), corresponds to the one presented in <a href="#foods-13-02459-f003" class="html-fig">Figure 3</a>.</p>
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17 pages, 8666 KiB  
Article
Effect of High Dietary Iron on Fat Deposition and Gut Microbiota in Chickens
by Ting Yang, Shihao Chen, Lingling Qiu, Qixin Guo, Zhixiu Wang, Yong Jiang, Hao Bai, Yulin Bi and Guobin Chang
Animals 2024, 14(15), 2254; https://doi.org/10.3390/ani14152254 - 3 Aug 2024
Viewed by 306
Abstract
To meet the demand of consumers for chicken products, poultry breeders have made improvements to chickens. However, this has led to a new problem in the modern poultry industry, namely excessive fat deposition. This study aims to understand the effects of dietary iron [...] Read more.
To meet the demand of consumers for chicken products, poultry breeders have made improvements to chickens. However, this has led to a new problem in the modern poultry industry, namely excessive fat deposition. This study aims to understand the effects of dietary iron supplementation on fat deposition and gut microbiota in chickens. In this study, we investigated the effects of iron on the growth performance, fat deposition, and gut microbiota of silky fowl black-bone chickens. A total of 75 7-week-old silky fowl black-bone chickens were randomly divided into three groups (five replicates per group, five chickens per replicate) and fed them for 28 days using a growing diet (control group), a growing diet + 10% tallow (high-fat diet group, HFD group), and a growing diet + 10% tallow + 500 mg/kg iron (HFDFe500 group), respectively. We detected the effects of iron on the growth performance, fat deposition, and gut microbiota of silky fowl black-bone chickens using the growth performance index test, oil red O staining, and HE staining, and found that the high-fat diet significantly increased liver and serum fat deposition and liver injury, while the addition of iron to the diet could reduce the fat deposition caused by the high-fat diet and alleviate liver injury. In addition, 16S rDNA sequencing was used to compare the relative abundance of gut microbiota in the cecal contents in different feeding groups. The results showed that the high-fat diet could induce gut microbiota imbalance in chickens, while the high-iron diet reversed the gut microbiota imbalance. PICRUSt functional prediction analysis showed that dietary iron supplementation affected amino acid metabolism, energy metabolism, cofactors, and vitamin metabolism pathways. In addition, correlation analysis showed that TG was significantly associated with Firmicutes and Actinobacteriota (p < 0.05). Overall, these results revealed high dietary iron (500 mg/kg) could reduce fat deposition and affect the gut microbiota of silky fowl black-bone chickens, suggesting that iron may regulate fat deposition by influencing the gut microbiota of chickens and provides a potential avenue that prevents excessive fat deposition in chickens by adding iron to the diet. Full article
(This article belongs to the Special Issue The Animal Microbiome in Health and Disease)
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<p>Effects of high iron diet on lipid metabolism in the different tissues. (<b>A</b>) Histological analysis of liver sections with oil red O staining. (<b>B</b>) Histological analysis of abdominal adipose tissue sections with hematoxylin and eosin staining (scale bar = 20 μm).</p>
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<p>Analysis of the amplicon sequence variant and α diversity of the gut microbiota in chickens. (<b>A</b>) Venny plots of amplicon sequence variant (ASV) in the cecum of chickens in the three groups. (<b>B</b>) α-diversity analyses based on the Chao1 index. (<b>C</b>) α-diversity analyses based on the Shannon index. (<b>D</b>) β-diversity analyses based on the PCoA plot about the cecal microbiota. (<b>E</b>) β-diversity analyses based on the PLS-DA sample plot with confidence ellipse plots.</p>
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<p>The differences between the cecal microbiota of different groups at the phylum level.</p>
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<p>The differences between the cecal microbiota of different groups at the genus level.</p>
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<p>Biomarkers of discriminative bacteria (from phylum to genus) in different groups identified by LEfSe analysis (LDA score &gt; 3.7). The length of the bars in the chart represents the influence sizes of the different species (i.e., LDA score).</p>
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<p>PICRUSt2 functional prediction analysis of the differential abundant bacterial communities between different groups.</p>
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<p>The correlation analysis of the growth performance and the relative abundances of cecal bacteria (phyla level).</p>
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<p>The correlation analysis of the serum biochemical parameters and the relative abundances of cecal bacteria (phyla level).</p>
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15 pages, 5311 KiB  
Article
Diversity of Endophytic Fungi and Bacteria Inhabiting the Roots of the Woodland Grass, Festuca gigantea (Poaceae)
by Izolda Pašakinskienė, Violeta Stakelienė, Saulė Matijošiūtė and Justas Martūnas
Diversity 2024, 16(8), 453; https://doi.org/10.3390/d16080453 - 1 Aug 2024
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Abstract
We studied the occurrence of endophytic fungi and bacteria in the roots of F. gigantea, a woodland perennial grass common throughout Europe and temperate Asia. The taxonomic assignment was carried out according to the isolate’s colony and cytological species morphotype characteristics and [...] Read more.
We studied the occurrence of endophytic fungi and bacteria in the roots of F. gigantea, a woodland perennial grass common throughout Europe and temperate Asia. The taxonomic assignment was carried out according to the isolate’s colony and cytological species morphotype characteristics and confirmed by the assessment of the standard DNA sequences, ITS, RPB2, SSU, and TEF1-a for fungi and 16S rDNA for bacteria. Our study has shown that F. gigantea roots are the habitat to a wide range of fungi and bacteria. The occurrence of fungal structures was determined in ~40% of the roots examined by Trypan Blue staining. In a surface-sterile root-cutting culture on PDA medium, we obtained isolates of six endophytic fungi species: four members of Ascomycota—Alternaria alternata, Cadophora fastigiata, Chaetomium funicola, and Microdochium bolleyi—and two of Basidiomycota—Coprinellus sp. and Sistotrema brinkmannii. In addition, we report bacteria co-occurring endophytically in the roots of this grass. The Firmicutes group was the most prevalent, consisting of four Gram-positive, endospore-forming bacteria taxa. The isolates were identified as Bacillus pumilus, Bacillus sp., Lysinibacillus sp., and Priestia aryabhattai. Moreover, two Gram-negative bacteria were detected—Kosakonia sp. (Proteobacteria) and Pedobacter sp. (Bacteroidetes). Thus, applying the isolate-culture approach, we identified a set of microorganisms in the roots of a typical grass native to the deciduous forest floor. The functional roles of these endophytes are diverse, and many of them, saprotrophs and decomposers of wood and plant debris, are linked to the decomposition of organic matter. This is the first detailed report on fungal and bacterial endophytes inhabiting the roots of F. gigantea. This study fills in a research gap on endophytes associated with the below-ground parts of Festuca spp., hitherto extensively studied for Epichloë/Neotyphodium associations in their foliar parts. Full article
(This article belongs to the Special Issue Microbial Diversity and Culture Collections Hotspots in 2024)
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<p>Cytological view of fungal and bacterial endophyte morphotypes in the root meristem of <span class="html-italic">F</span>. <span class="html-italic">gigantea</span>: (<b>A</b>–<b>E</b>) images of endophytic fungi hyphae; (<b>F</b>) <span class="html-italic">Alternaria</span>-type conidia; (<b>G</b>) agglomerates of fungal spores; (<b>H</b>,<b>I</b>) clusters of hyphae; (<b>J</b>) large bunches of Bacillus-type endophytic bacteria; (<b>K</b>) chains of filamentous bacteria. Scale bar = 10 µm.</p>
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<p>The 7–10-day isolate colonies on PDA medium from the roots of <span class="html-italic">F. gigantea</span> and cytomorphological images obtained from mycelium: (<b>A1</b>,<b>A2</b>) <span class="html-italic">Alternaria alternata</span> (isolate BSG001) top and reverse view, (<b>A3</b>) multicelled, obclavate conidia with short conical beaks, and (<b>A4</b>) segmented hyphae; (<b>B1</b>,<b>B2</b>) <span class="html-italic">Cadophora fastigiata</span> (BSG003) top and reverse views, (<b>B3</b>,<b>B5</b>) conidiophores (funnel-shaped collarette marked) and segmented hyphae, and (<b>B4</b>) conidia; (<b>C1</b>,<b>C2</b>) <span class="html-italic">Chaetomium funicola</span> (BSG039) front and reverse views, (<b>C3</b>) ascomata, and (<b>C4</b>) ascomata hair and ascospores sticking to it; (<b>D1</b>,<b>D2</b>) <span class="html-italic">Microdochium bolleyi</span> (BSG008) top and reverse, (<b>D3</b>) conidia on cylindrical conidiogenous cells; (<b>E1</b>,<b>E2</b>) <span class="html-italic">Coprinellus</span> sp. (BSG004) top and reverse view, and (<b>E3</b>,<b>E4</b>) segmented hyphae; (<b>F1</b>,<b>F2</b>) <span class="html-italic">Sistotrema brinkmannii</span> (BSG005) top and reverse view, (<b>F3</b>,<b>F5</b>) hyphae, and (<b>F4</b>) spores. Scale bar: (<b>A3</b>,<b>A4</b>,<b>B3</b>,<b>C3</b>,<b>E3</b>,<b>F3</b>) = 100 µm; (<b>B4</b>,<b>B5</b>,<b>C4</b>,<b>D3</b>,<b>E4</b>,<b>F4</b>,<b>F5</b>) = 10 µm.</p>
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26 pages, 5132 KiB  
Article
Microbial Diversity of Soil in a Mediterranean Biodiversity Hotspot: Parque Nacional La Campana, Chile
by Carolina Quinteros-Urquieta, Jean-Pierre Francois, Polette Aguilar-Muñoz, Roberto Orellana, Rodrigo Villaseñor, Andres Moreira-Muñoz and Verónica Molina
Microorganisms 2024, 12(8), 1569; https://doi.org/10.3390/microorganisms12081569 - 31 Jul 2024
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Abstract
Parque Nacional La Campana (PNLC) is recognized worldwide for its flora and fauna, rather than for its microbial richness. Our goal was to characterize the structure and composition of microbial communities (bacteria, archaea and fungi) and their relationship with the plant communities typical [...] Read more.
Parque Nacional La Campana (PNLC) is recognized worldwide for its flora and fauna, rather than for its microbial richness. Our goal was to characterize the structure and composition of microbial communities (bacteria, archaea and fungi) and their relationship with the plant communities typical of PNLC, such as sclerophyllous forest, xerophytic shrubland, hygrophilous forest and dry sclerophyllous forest, distributed along topoclimatic variables, namely, exposure, elevation and slope. The plant ecosystems, the physical and chemical properties of organic matter and the soil microbial composition were characterized by massive sequencing (iTag-16S rRNA, V4 and ITS1-5F) from the DNA extracted from the soil surface (5 cm, n = 16). A contribution of environmental variables, particularly related to each location, is observed. Proteobacteria (35.43%), Actinobacteria (32.86%), Acidobacteria (10.07%), Ascomycota (76.11%) and Basidiomycota (15.62%) were the dominant phyla. The beta diversity (~80% in its axes) indicates that bacteria and archaea are linked to their plant categories, where the xerophytic shrub stands out with the most particular microbial community. More specifically, Crenarchaeote, Humicola and Mortierella were dominant in the sclerophyllous forest; Chloroflexi, Cyanobacteria and Alternaria in the xerophytic shrubland; Solicoccozyma in the dry sclerophyllous forest; and Cladophialophora in the hygrophilous forest. In conclusion, the structure and composition of the microbial consortia is characteristic of PNLC’s vegetation, related to its topoclimatic variables, which suggests a strong association within the soil microbiome. Full article
(This article belongs to the Special Issue Advances in Soil Microbial Ecology)
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<p>Map that shows PNLC sampling locations (1, 2, 3, 4). Vegetation map, adapted from Hauck et al. [<a href="#B38-microorganisms-12-01569" class="html-bibr">38</a>].</p>
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<p>Graphical representation of the four sample sites characterized by their exposure and elevation.</p>
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<p>Physicochemical variables of the soil samples: (<b>a</b>) C/N. Significant C/N differences were observed between the hygrophilous forest and the xerophytic shrubland, and between the dry sclerophyllous forest and the xerophytic shrubland. (<b>b</b>) pH. No significant differences between locations were observed. (<b>c</b>) Dry density (g/cm<sup>3</sup>). Significant differences were observed between the hygrophilous forest and the xerophytic shrubland (<b>d</b>) d15N and d13C isotope content.</p>
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<p>Redundancy analysis (RDA) that shows the variability of the environmental conditions associated with the plant communities. (For further information, see <a href="#app1-microorganisms-12-01569" class="html-app">Supplementary Table S3</a>.)</p>
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<p>(<b>a</b>) Prokaryote and (<b>b</b>) fungi soil microorganism’s alpha diversity in PNLC plant communities. Grey dots correspond to replicate outliers.</p>
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<p>PCoA (PERMANOVA <span class="html-italic">p</span>-value &lt; 0.05) that illustrates the microbial variability of the soil of the plant communities at the phylum level of (<b>a</b>) prokaryotes and (<b>b</b>) fungi. The blue arrows represent the environmental parameters that significantly correlate with the microbial communities (envfit, <span class="html-italic">p</span>-value &lt; 0.05).</p>
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<p>PCoA (PERMANOVA <span class="html-italic">p</span>-value &lt; 0.05) that illustrates the microbial variability of the soil of the plant communities at the phylum level of (<b>a</b>) prokaryotes and (<b>b</b>) fungi. The blue arrows represent the environmental parameters that significantly correlate with the microbial communities (envfit, <span class="html-italic">p</span>-value &lt; 0.05).</p>
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<p>Venn diagram that shows the comparison of ASVs richness associated with (<b>a</b>) prokaryotes and (<b>b</b>) fungi, grouped on the basis of the soil of the plant communities. Sclerophilous forest—purple area, Xerophytic shrubland—yellow area, Hygrophilous forest—green area, Dry sclerophilous forest—orange area.</p>
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<p>The box plot shows the relative abundance of bacterial and archaeal phyla in the PNLC soil categorized by the different plant communities.</p>
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<p>The box plots show the relative abundance of the fungal phyla in the PNLC soil categorized by different plant communities.</p>
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<p>Heatmap of the 18 most abundant genera of prokaryotes in the soil (<span class="html-italic">n</span> = 16) analyzed in PNLC, categorized by plant communities.</p>
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<p>Heatmap for the 20 genera of fungi in the soil (<span class="html-italic">n</span> = 16) analyzed in PNLC categorized by plant communities.</p>
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<p>Volcano plot that shows the ASVs of microorganisms (bacteria, archaea and fungi) when comparing the xerophytic shrubland vs. sclerophyllous forest plant communities in PNLC. The red line indicates the significantly different ASVs (<span class="html-italic">p</span>-adj). Complete data in <a href="#app1-microorganisms-12-01569" class="html-app">Supplementary Table S4</a>.</p>
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<p>Volcano plot that shows the ASVs of microorganism when comparing the hygrophilous forest and dry sclerophyllous forest plant communities in PNLC. The red line indicates the significantly different ASVs (<span class="html-italic">p</span>-adj). Complete data in <a href="#app1-microorganisms-12-01569" class="html-app">Supplementary Table S5</a>.</p>
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<p>Predicted potential microbial function profile by comparison of the 4 study sites. (<b>a</b>) Prokaryotes, (<b>b</b>) fungi.</p>
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11 pages, 1225 KiB  
Article
Molecular and Morphological Identification of Sarocladium Species Causing Sheath Rot of Rice in Thailand and Their Division into Physiological Races
by Jintana Unartngam, Noppol Kopmoo, Umpawa Pinruan, Chatchai Kosawang and Hans Jørgen Lyngs Jørgensen
J. Fungi 2024, 10(8), 535; https://doi.org/10.3390/jof10080535 - 31 Jul 2024
Viewed by 439
Abstract
Sheath rot and dirty panicle are some of the major diseases of rice in Thailand. The diseases are traditionally considered to be caused by the pathogen Sarocladium oryzae and damage and lower both the quantity and quality of rice grain. In this study, [...] Read more.
Sheath rot and dirty panicle are some of the major diseases of rice in Thailand. The diseases are traditionally considered to be caused by the pathogen Sarocladium oryzae and damage and lower both the quantity and quality of rice grain. In this study, 32 fungal isolates collected from the central and northeastern regions of Thailand were analysed phylogenetically using three molecular markers (ITS, D1/D2 of 28S rDNA and ACT) and physiological races were determined on 10 differential rice cultivars. We found that S. oryzae is not the only causal agent of sheath rot in Thailand, but S. attenuatum was also found. Despite having similar morphological features, the phylogenetic analysis recognised 11 of 32 isolates as S. attenuatum and the remaining isolates as S. oryzae. This is the first report of S. attenuatum causing sheath rot of rice in Thailand in addition to S. oryzae. Evaluation of physiological races revealed high pathogenic diversity of the two species. Thus, 16 and 11 physiological races were recorded from 21 isolates of S. oryzae and 11 isolates of S. attenuatum, respectively. These results indicate that both S. oryzae and S. attenuatum are the causal agents of rice sheath rot and dirty panicle in Thailand and that they are pathologically diverse. Full article
(This article belongs to the Section Fungal Evolution, Biodiversity and Systematics)
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<p>Morphological characteristics of <span class="html-italic">S. oryzae</span> (<b>a</b>–<b>d</b>) and <span class="html-italic">S. attenuatum</span> (<b>e</b>–<b>h</b>) isolated from sheath rot and dirty panicle diseases of rice. (<b>a</b>,<b>b</b>,<b>e</b>,<b>f</b>): colonies were grown on (<b>a</b>) PDA and (<b>b</b>) oatmeal agar (left seen from above and right from below); (<b>c</b>,<b>d</b>,<b>g</b>,<b>h</b>): simple and branched conidiophores, phialide producing conidia in chains, cylindrical conidia. Scale bars (<b>a</b>,<b>b</b>,<b>e</b>,<b>f</b>) = 1 cm; (<b>c</b>,<b>d</b>,<b>g</b>,<b>h</b>) = 10 μm.</p>
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<p>Phylogenetic tree obtained from ITS rDNA, D1/D2 of 28S rDNA and <span class="html-italic">ACT</span> concatenated data of <span class="html-italic">S. oryzae</span>, <span class="html-italic">S. attenuatum</span> and other species from the GenBank database using maximum likelihood and Bayesian inference method. Bootstrap support values (1000 replications) above 50% are shown on the branches.</p>
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<p>Dirty panicle and sheath rot on panicles and flag leaf sheaths at 21 days after inoculation with a spore suspension of (<b>a</b>) <span class="html-italic">S. attenuatum</span> isolate KKN0225 and (<b>b</b>) <span class="html-italic">S. oryzae</span> isolate KKN0122 on 10 differential rice cultivars.</p>
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