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Search Results (3,167)

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Keywords = secondary metabolism

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13 pages, 1683 KiB  
Review
Unveiling the Power of Flax Lignans: From Plant Biosynthesis to Human Health Benefits
by Zhan Gao, Qinglei Cao and Zhongyuan Deng
Nutrients 2024, 16(20), 3520; https://doi.org/10.3390/nu16203520 (registering DOI) - 17 Oct 2024
Abstract
Background: Flax (Linum usitatissimum L.) is the richest plant source of lignin secondary metabolites. Lignans from flax have been applied in the fields of food, medicine, and health due to their significant physiological activities. The most abundant lignan is secoisolariciresinol, which exists [...] Read more.
Background: Flax (Linum usitatissimum L.) is the richest plant source of lignin secondary metabolites. Lignans from flax have been applied in the fields of food, medicine, and health due to their significant physiological activities. The most abundant lignan is secoisolariciresinol, which exists in a glycosylated form in plants. Results: After ingestion, it is converted by human intestinal flora into enterodiol and enterolactone, which both have physiological roles. Here, the basic structures, contents, synthesis, regulatory, and metabolic pathways, as well as extraction and isolation methods, of flax lignans were reviewed. Additionally, the physiological activity-related mechanisms and their impacts on human health, from the biosynthesis of lignans in plants to the physiological activity effects observed in animal metabolites, were examined. Conclusions: The review elucidates that lignans, as phenolic compounds, not only function as active substances in plants but also offer significant nutritional values and health benefits when flax is consumed. Full article
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Figure 1
<p>Example compounds of lignans in plants. PINO, SYRI, LARI, and Ses are furans, MAT is a dibenzyl butyrolactone, SECO is a 9,9′-dihydroxy dibenzylbutane, and isolariciresinol is a 9,9′-dihydroxyaryltetrahydronaphthalene.</p>
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<p>Lignan synthesis and regulation. The text on the green background represents the phenylpropanoid biosynthesis pathway. The text on the blue background represents the lignan biosynthetic pathway.</p>
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<p>Lignan metabolic processes in humans.</p>
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<p>Functions of lignans in humans and their use.</p>
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14 pages, 7220 KiB  
Article
Transcriptome Remodeling in Arabidopsis: A Response to Heterologous Poplar MSL-lncRNAs Overexpression
by Jinyan Mao, Qianhua Tang, Huaitong Wu and Yingnan Chen
Plants 2024, 13(20), 2906; https://doi.org/10.3390/plants13202906 (registering DOI) - 17 Oct 2024
Abstract
Stamens are vital reproductive organs in angiosperms, essential for plant growth, reproduction, and development. The genetic regulation and molecular mechanisms underlying stamen development are, however, complex and varied among different plant species. MSL-lncRNAs, a gene specific to the Y chromosome of Populus deltoides [...] Read more.
Stamens are vital reproductive organs in angiosperms, essential for plant growth, reproduction, and development. The genetic regulation and molecular mechanisms underlying stamen development are, however, complex and varied among different plant species. MSL-lncRNAs, a gene specific to the Y chromosome of Populus deltoides, is predominantly expressed in male flower buds. Heterologous expression of MSL-lncRNAs in Arabidopsis thaliana resulted in an increase in both stamen and anther count, without affecting pistil development or seed set. To reveal the molecular regulatory network influenced by MSL-lncRNAs on stamen development, we conducted transcriptome sequencing of flowers from both wild-type and MSL-lncRNAs-overexpressing Arabidopsis. A total of 678 differentially expressed genes were identified between wild-type and transgenic Arabidopsis. Among these, 20 were classified as transcription factors, suggesting a role for these regulatory proteins in stamen development. GO enrichment analysis revealed that the differentially expressed genes were significantly associated with processes such as pollen formation, polysaccharide catabolic processes, and secondary metabolism. KEGG pathway analysis indicated that MSL-lncRNAs might promote stamen development by upregulating genes involved in the phenylpropanoid biosynthesis pathway. The top three upregulated genes, all featuring the DUF295 domain, were found to harbor an F-box motif at their N-termini, which is implicated in stamen development. Additionally, in transgenic Arabidopsis flowers, genes implicated in tapetum formation and anther development were also observed to be upregulated, implying a potential role for MSL-lncRNAs in modulating pollen development through the positive regulation of these genes. The findings from this study establish a theoretical framework for elucidating the genetic control exerted by MSL-lncRNAs over stamen and pollen development. Full article
(This article belongs to the Section Plant Molecular Biology)
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<p>Transcriptome data analysis. (<b>a</b>) Correlation analysis among six samples. (<b>b</b>) Bar Chart of the number of differentially expressed genes. (<b>c</b>) Cluster analysis of DEGs collected in six samples. The normalized FPKM expression is indicated by the row Z-score, where red represents upregulated genes and blue represents downregulated genes in every sample.</p>
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<p>Bar chart displaying the top three upregulated and bottom three downregulated genes based on log-fold change (logFC) values.</p>
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<p>Validation of RNA-seq results using qRT-PCR analysis. The top three histograms depict the relative expression levels from qRT-PCR, with fold change values shown as the mean ± standard deviation across three independent experiments. The bottom three histograms illustrate the FPKM values derived from RNA-seq data.</p>
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<p>Heatmap of differentially expressed transcription factors based on FPKM values. Normalized transcription factor expression is indicated by the row Z-score where red represents upregulated genes and blue represents downregulated genes.</p>
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<p>GO enrichment analysis of DEGs. (<b>a</b>) Biological process enrichment analysis. (<b>b</b>) Cellular component enrichment analysis. (<b>c</b>) Molecular function enrichment analysis.</p>
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<p>KEGG enrichment analysis of DEGs. The <span class="html-italic">X</span>-axis represents the number of DEGs enriched in specific metabolic pathways. The color gradient from red to blue denotes adjusted <span class="html-italic">p</span>-values: red for the smallest (0.00), purple for moderate (0.10), and blue for the largest (0.20).</p>
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<p>Differential expression levels of genes related to phenylpropanoid biosynthesis identified by KEGG annotation. The enzymes marked with the red boxes are associated with the upregulation of proteins, while those marked with the green boxes are associated with the downregulation of proteins.</p>
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<p>Protein–protein interaction network in <span class="html-italic">Arabidopsis</span>. Each node represents a protein, with the protein name displayed inside. Arcs denote interactions between proteins, and color coding reflects interaction strength: red for high, orange for moderate, and yellow for low interaction degrees.</p>
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20 pages, 5099 KiB  
Article
Proteomics and EPS Compositional Analysis Reveals Desulfovibrio bisertensis SY-1 Induced Corrosion on Q235 Steel by Biofilm Formation
by Yanan Wang, Ruiyong Zhang, Krishnamurthy Mathivanan, Yimeng Zhang, Luhua Yang, Fang Guan and Jizhou Duan
Materials 2024, 17(20), 5060; https://doi.org/10.3390/ma17205060 - 17 Oct 2024
Viewed by 108
Abstract
Microorganisms that exist in the seawater form microbial biofilms on materials used in marine construction, especially on metal surfaces submerged in seawater, where they form biofilms and cause severe corrosion. Biofilms are mainly composed of bacteria and their secreted polymeric substances. In order [...] Read more.
Microorganisms that exist in the seawater form microbial biofilms on materials used in marine construction, especially on metal surfaces submerged in seawater, where they form biofilms and cause severe corrosion. Biofilms are mainly composed of bacteria and their secreted polymeric substances. In order to understand how biofilms promote metal corrosion, planktonic and biofilm cells of Desulfovibrio bizertensis SY-1 (D. bizertensis) from Q235 steel were collected and analyzed as to their intracellular proteome and extracellular polymeric substances (EPS). The intracellular proteome analysis showed that the cellular proteins were strongly regulated in biofilm cells compared to planktonic cells, e.g., along with flagellar proteins, signaling-related proteins were significantly increased, whereas energy production and conversion proteins and DNA replication proteins were significantly regulated. The up-and-down regulation of proteins revealed that biofilm formation by bacteria on metal surfaces is affected by flagellar and signaling proteins. A significant decrease in DNA replication proteins indicated that DNA is no longer replicated and transcribed in mature biofilms, thus reducing energy consumption. Quantitative analysis and lectin staining of the biofilm on the metal’s surface revealed that the bacteria secreted a substantial amount of EPS when they began to attach to the surface, and proteins dominated the main components of EPS. Further, the infrared analysis showed that the secondary structure of the proteins in the EPS of the biofilm was mainly dominated by β-sheet and 3-turn helix, which may help to enhance the adhesion of EPS. The functional groups of EPS analyzed using XPS showed that the C element of EPS in the biofilm mainly existed in the form of combinations with N. Furthermore, the hydroxyl structure in the EPS extracted from the biofilm had a stronger hydrogen bonding effect, which could maintain the stability of the EPS structure and biofilm. The study results revealed that D. bizertensis regulates the metabolic pathways and their secreted EPS structure to affect biofilm formation and cause metal corrosion, which has a certain reference significance for the study of the microbially influenced corrosion (MIC) mechanism. Full article
(This article belongs to the Special Issue Future Trend of Marine Corrosion and Protection)
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Figure 1
<p>Scanning electron microscopy (SEM) micrograph images of the Q235 surface from (<b>a</b>) control and (<b>b</b>) <span class="html-italic">D. bizertensis</span>-containing medium. Confocal laser scanning microscopy images of the biofilm cells on the Q235 surface after 15 days immersion, stained with the LIVE/DEAD Biofilm Viability kit (<b>c</b>), and EPS distribution ((<b>d</b>) proteins stained with FITC, (<b>e</b>) polysaccharides stained with Concanavalin A-TRITC, and (<b>f</b>) lipids stained with Nile red). Green coloring indicates live cells, red coloring indicates dead cells, and yellow coloring indicates partially damaged/dead cells.</p>
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<p>(<b>a</b>) XRD of surface products of Q235 steel from control and <span class="html-italic">D. bizertensis</span>-containing medium, and (<b>b</b>) annual corrosion rates of Q235 steel after 15 days incubation. (<b>c</b>,<b>d</b>) The pits and their depths on the Q235 steel coupons from control and <span class="html-italic">D. bizertensis</span>-inoculated media after 15 days.</p>
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<p>(<b>a</b>) Summary of detectable protein contents and functions. (<b>b</b>) Volcano plots representing the results of the proteome analysis in biofilm vs. planktonic cells.</p>
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<p>Up- and down-regulated flagellum-related DEPs in biofilm and planktonic cells.</p>
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<p>Functional category distribution of differentially expressed proteins by GO in biofilm and planktonic cells.</p>
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<p>Differentially expressed proteins in KEEG pathway biofilm cells on the Q235 surface and planktonic cells, (<b>a</b>) biofilm.vs. plankton_up, (<b>b</b>) biofilm.vs.plankton_down.</p>
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<p>Intermittent protein restriction of differentially expressed proteins in biofilm cells on the Q235 surface and in planktonic cells.</p>
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<p>Growth curve (<b>a</b>) and EPS concentration of plankton cell and biofilm cell: (<b>b</b>) total, (<b>c</b>) protein, (<b>d</b>) polysaccharide, and (<b>e</b>) DNA.</p>
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<p>Deconvoluted C 1s and O 1s: High-resolution XPS spectra of EPS of biofilm and planktonic cells. (<b>a</b>) EPS of planktonic cells C 1s, (<b>b</b>) EPS of biofilm cells C 1s, (<b>c</b>) EPS of planktonic cells O 1s, (<b>d</b>) EPS of biofilm cells O 1s.</p>
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<p>FTIR spectra of the amide I region in the EPS: (<b>a</b>) biofilm cells and (<b>b</b>) planktonic cells.</p>
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17 pages, 4853 KiB  
Article
The Aspergillus flavus hacA Gene in the Unfolded Protein Response Pathway Is a Candidate Target for Host-Induced Gene Silencing
by Perng-Kuang Chang
J. Fungi 2024, 10(10), 719; https://doi.org/10.3390/jof10100719 - 16 Oct 2024
Viewed by 265
Abstract
Fungal HacA/Hac1 transcription factors play a crucial role in regulating the unfolded protein response (UPR). The UPR helps cells to maintain endoplasmic reticulum (ER) protein homeostasis, which is critical for growth, development, and virulence. The Aspergillus flavus hacA gene encodes a domain rich [...] Read more.
Fungal HacA/Hac1 transcription factors play a crucial role in regulating the unfolded protein response (UPR). The UPR helps cells to maintain endoplasmic reticulum (ER) protein homeostasis, which is critical for growth, development, and virulence. The Aspergillus flavus hacA gene encodes a domain rich in basic and acidic amino acids (Bsc) and a basic leucine zipper (bZip) domain, and features a non-conventional intron (Nt20). In this study, CRISPR/Cas9 was utilized to dissect the Bsc-coding, bZip-coding, and Nt20 sequences to elucidate the relationship between genotype and phenotype. In the Bsc and bZip experimental sets, all observed mutations in both coding sequences were in frame, suggesting that out-of-frame mutations are lethal. The survival rate of transformants in the Nt20 experiment set was low, at approximately 7%. Mutations in the intron primarily consisted of out-of-frame insertions and deletions. In addition to the wild-type-like conidial morphology, the mutants exhibited varied colony morphologies, including sclerotial, mixed (conidial and sclerotial), and mycelial morphologies. An ER stress test using dithiothreitol revealed that the sclerotial and mycelial mutants were much more sensitive than the conidial mutants. Additionally, the mycelial mutants were unable to produce aflatoxin but still produced aspergillic acid and kojic acid. RNAi experiments targeting the region encompassing Bsc and bZip indicated that transformant survival rates generally decreased, with a small number of transformants displaying phenotypic changes. Defects in the hacA gene at the DNA and transcript levels affected the survival, growth, and development of A. flavus. Thus, this gene may serve as a promising target for future host-induced gene-silencing strategies aimed at controlling infection and reducing aflatoxin contamination in crops. Full article
(This article belongs to the Special Issue Mycotoxin Contamination and Control in Food)
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<p>The <span class="html-italic">A. flavus hacA</span> gene. (<b>A</b>) Schematic representation of the functional domain-coding regions and introns. Gray and black areas indicate the single conventional intron (I54) and the non-conventional intron (I20 = Nt20). BA indicates the coding region rich in basic and acidic amino acids, which is interrupted by the conventional intron. bZip denotes the basic leucine zipper coding region. (<b>B</b>) Comparison of the 20-nucleotide non-conventional introns of <span class="html-italic">A. flavus</span>, <span class="html-italic">A. parasiticus</span>, <span class="html-italic">A. oryzae</span>, <span class="html-italic">A. fumigatus</span>, <span class="html-italic">A. nidulans</span>, <span class="html-italic">A. niger</span>, <span class="html-italic">T. reesei</span>, and <span class="html-italic">V. dahlia</span>. The hexanucleotide repeat, which is the <span class="html-italic">Pst</span>I restriction site sequence, is underlined. Single nucleotide polymorphisms are highlighted. (<b>C</b>) The 3D models of HacA and HacA<sup>∆</sup>. The amino acid sequence from residues 83 to 146 is the bZip domain, which is the long α-helical structure in both forms. AlphaFold produced a colored confidence score for each residue in the α-helical structure. The score range of each color is blue &gt; 90, light blue &gt; 70 but &lt;90, yellow &gt; 50 but &lt;70, orange &lt; 50. Refer to <a href="#app1-jof-10-00719" class="html-app">Figure S3A</a> for both amino acid sequences.</p>
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<p>Phenotypic changes resulting from sequence mutations in the <span class="html-italic">hacA</span> functional domain-coding regions and the nonconventional intron. (<b>A</b>) The basic/acidic domain: K (lysine) and R (arginine) are basic amino acids, while E (glutamic acid) and D (aspartic acid) are acidic amino acids. The three target regions are underlined. (<b>B</b>) The bZip domain: The domain forms an α-helix (see <a href="#jof-10-00719-f002" class="html-fig">Figure 2</a>) with leucine (L) residues highlighted in blue. The three target regions are underlined. The wild-type (WT) CA14 strain is shown alongside the CS mutant for visual comparison and consistency in presentation. (<b>C</b>) The non-conventional intron: Both amino acid sequences of the wild-type CA14 strain before and after the removal of the 20-nucleotide intron are shown. Only the predicted amino acid sequences before the removal of the respective introns from the mutants with single-nucleotide insertion or deletion are shown; the removal of these introns yielded amino acid sequences identical to that of the truncated HacA<sup>∆</sup>. Single amino acid changes are highlighted in yellow. Missing amino acids are indicated by dashes, and inserted amino acids are highlighted in grey. A star indicates the end of an amino acid sequence. In the three panels, open triangles and solid inverted triangles followed by numbers indicate deleted and inserted nucleotides, respectively. The double-headed arrow indicates nucleotide substitution. The numbers after the equals signs are the number of sequenced transformants with the same mutation. The following designations are used for colony morphology: C, conidial; S, sclerotial; CS, a roughly equal mix of conidial and sclerotial, Cs, more conidial than sclerotia, Sc, more sclerotial than conidial, and M, mycelial. Mycelial mats barely contained conidiophores. The powdery-looking sectors in panels (<b>A</b>–<b>C</b>) when examined under a dissecting microscope, were found to contain aggregations of hyphae, which appeared to be white sclerotia initials.</p>
Full article ">Figure 2 Cont.
<p>Phenotypic changes resulting from sequence mutations in the <span class="html-italic">hacA</span> functional domain-coding regions and the nonconventional intron. (<b>A</b>) The basic/acidic domain: K (lysine) and R (arginine) are basic amino acids, while E (glutamic acid) and D (aspartic acid) are acidic amino acids. The three target regions are underlined. (<b>B</b>) The bZip domain: The domain forms an α-helix (see <a href="#jof-10-00719-f002" class="html-fig">Figure 2</a>) with leucine (L) residues highlighted in blue. The three target regions are underlined. The wild-type (WT) CA14 strain is shown alongside the CS mutant for visual comparison and consistency in presentation. (<b>C</b>) The non-conventional intron: Both amino acid sequences of the wild-type CA14 strain before and after the removal of the 20-nucleotide intron are shown. Only the predicted amino acid sequences before the removal of the respective introns from the mutants with single-nucleotide insertion or deletion are shown; the removal of these introns yielded amino acid sequences identical to that of the truncated HacA<sup>∆</sup>. Single amino acid changes are highlighted in yellow. Missing amino acids are indicated by dashes, and inserted amino acids are highlighted in grey. A star indicates the end of an amino acid sequence. In the three panels, open triangles and solid inverted triangles followed by numbers indicate deleted and inserted nucleotides, respectively. The double-headed arrow indicates nucleotide substitution. The numbers after the equals signs are the number of sequenced transformants with the same mutation. The following designations are used for colony morphology: C, conidial; S, sclerotial; CS, a roughly equal mix of conidial and sclerotial, Cs, more conidial than sclerotia, Sc, more sclerotial than conidial, and M, mycelial. Mycelial mats barely contained conidiophores. The powdery-looking sectors in panels (<b>A</b>–<b>C</b>) when examined under a dissecting microscope, were found to contain aggregations of hyphae, which appeared to be white sclerotia initials.</p>
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<p>DTT induced ER stress on the growth and development of the wild-type CA14 strain and the <span class="html-italic">hacA</span> mutants. Open triangles and solid inverted triangles followed by numbers indicate deleted and inserted nucleotides, respectively. Bsc, bZip, and Nt20 have been added to strain designations in reference to the mutated regions. For details regarding the morphologies (C, CS, S, Cs, Sc, and M) of the Bsc, bZip, Nt20 mutants, refer to the legend for <a href="#jof-10-00719-f003" class="html-fig">Figure 3</a>. Conidia from wild-type CA14 and various types of the <span class="html-italic">hacA</span> mutants were inoculated onto PDA and CZ plates, both with and without the addition of 10 mM DTT. Plates were incubated at 30 °C for four days in the dark.</p>
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<p>Production of aspergillic acid, anthraquinones, and kojic acid by the <span class="html-italic">hacA</span> mutants. Colony morphologies and pigmentation were examined on ADM, CAM, and KAM plates. F, top view; R, reverse side; W, white light; UV, longwave ultraviolet light. Pigmentation in ADM was restricted to the edge of the colony, while pigmentation on KAM (complex formed by diffusible kojic acid with ferric ion) was distributed throughout the plate. WT, wild-type CA14; KO, respective gene knockout mutants. Open triangles and solid inverted triangles followed by numbers indicate deleted and inserted nucleotides, respectively. Bsc, bZip, and Nt20 added to strain designations for reference to the mutated regions. Refer to the legend for <a href="#jof-10-00719-f003" class="html-fig">Figure 3</a> for strain details and designations of morphologies.</p>
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<p>Semi-quantitative TLC analysis of aflatoxin production by selected <span class="html-italic">hacA</span> mutants with varying colony morphologies. (<b>A</b>) The designations Bsc, bZip, and Nt20 refer to mutants with defects in their HacA functional domains and the non-conventional intron. WT denotes the wild-type CA14 strain. Open triangles and solid inverted triangles followed by numbers indicate deleted and inserted nucleotides, respectively. Refer to the legend for <a href="#jof-10-00719-f003" class="html-fig">Figure 3</a> for strain details and designations of morphologies. (<b>B</b>) Lack of aflatoxin production by the fifth transfered <span class="html-italic">hacA</span> mutant of bZip∆42/M. The mutant was serially transferred onto PDA. A small piece of mycelia-containing agar from the fourth culture (circled red) was transferred onto a PDA plate. Two agar plugs from the fifth culture were cored and analyzed using semi-quantitative TLC. Bsc∆21/M, a mycelial mutant that does not produce aflatoxin, served as a negative control.</p>
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<p>Colony morphology of <span class="html-italic">hacA</span>i transformants on PDA plates. Transformants exhibiting sclerotial, green and velvet-like, or retarded growth morphologies are indicated by arrows. L and R denote transformants from the L_bZip and R_bZip control sets. Cultures were incubated at 30 °C for five days in the dark.</p>
Full article ">
9 pages, 213 KiB  
Article
One-Year Effect of Elexacaftor/Tezacaftor/Ivacaftor Therapy on HbA1c Levels and Insulin Requirement in Patients with Insulin-Dependent Cystic Fibrosis-Related Diabetes: A Retrospective Observational Study
by Marta Bassi, Marina Francesca Strati, Gaia Spiandorello, Marta Scalas, Federico Cresta, Maria Grazia Calevo, Giuseppe d’Annunzio, Carlo Castellani, Nicola Minuto, Mohamad Maghnie and Rosaria Casciaro
Life 2024, 14(10), 1309; https://doi.org/10.3390/life14101309 - 16 Oct 2024
Viewed by 220
Abstract
Introduction: The impact of ETI therapy on pulmonary function and nutritional status has been widely studied; the literature on the possible outcomes on glycemic control and insulin requirement in patients affected by CFRD is controversial. Aim: The main objective of our study was [...] Read more.
Introduction: The impact of ETI therapy on pulmonary function and nutritional status has been widely studied; the literature on the possible outcomes on glycemic control and insulin requirement in patients affected by CFRD is controversial. Aim: The main objective of our study was to evaluate HbA1c levels in patients with cystic fibrosis-related diabetes (CFRD) after one year of therapy with elexacaftor/tezacaftor/ivacaftor (ETI). The secondary objective was to study the changes in the total daily insulin dose (TDD), pulmonary function and metabolism in this population. Materials and methods: A retrospective single-center observational study was conducted at the Regional Cystic Fibrosis Centre and Diabetology Centre of IRCCS Istituto Giannina Gaslini. The observation period was divided into four different time points: initiation (T0), 3 months (T3mo), 6 months (T6mo) and 12 months (T12mo) of ETI therapy. Demographic and clinical data were collected. The results were then stratified by genotype (homozygous or heterozygous F508del). Results: Twenty-eight patients with CFRD undergoing insulin therapy were included. TDD (IU) significantly decreased at T3mo and T6mo, but not at T12mo, whereas HbA1c decreased significantly at all three times. The number of hospitalizations and pulmonary exacerbations decreased significantly. Conclusion: We demonstrated both improvement in glycemic control (by means of HbA1c) and insulin requirement in insulin-dependent CFRD patients after one year of ETI treatment. Full article
(This article belongs to the Special Issue Cystic Fibrosis: A Disease with a New Face)
16 pages, 2295 KiB  
Review
The Influence of Different Factors on the Metabolism of Capsaicinoids in Pepper (Capsicum annuum L.)
by Yuanling Yang, Chengan Gao, Qingjing Ye, Chenxu Liu, Hongjian Wan, Meiying Ruan, Guozhi Zhou, Rongqing Wang, Zhimiao Li, Ming Diao and Yuan Cheng
Plants 2024, 13(20), 2887; https://doi.org/10.3390/plants13202887 (registering DOI) - 15 Oct 2024
Viewed by 339
Abstract
Pepper is a globally cultivated vegetable known for its distinct pungent flavor, which is derived from the presence of capsaicinoids, a class of unique secondary metabolites that accumulate specifically in pepper fruits. Since the accumulation of capsaicinoids is influenced by various factors, it [...] Read more.
Pepper is a globally cultivated vegetable known for its distinct pungent flavor, which is derived from the presence of capsaicinoids, a class of unique secondary metabolites that accumulate specifically in pepper fruits. Since the accumulation of capsaicinoids is influenced by various factors, it is imperative to comprehend the metabolic regulatory mechanisms governing capsaicinoids production. This review offers a thorough examination of the factors that govern the metabolism of capsaicinoids in pepper fruit, with a specific focus on three primary facets: (1) the impact of genotype and developmental stage on capsaicinoids metabolism, (2) the influence of environmental factors on capsaicinoids metabolism, and (3) exogenous substances like methyl jasmonate, chlorophenoxyacetic acid, gibberellic acid, and salicylic acid regulate capsaicinoid metabolism. The findings of this study are expected to enhance comprehension of capsaicinoids metabolism and aid in the improvement of breeding and cultivation practices for high-quality pepper in the future. Full article
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Figure 1
<p>Capsaicinoid biosynthetic pathway. (<b>A</b>): Cross-section of chili fruit; (<b>B</b>): schematic diagram of capsaicin biosynthesis pathway and regulatory genes. Abbreviations: PAL, phenylalanine ammonia lyase; C4H, coumarate 4-hydroxylase; 4CL, 4-coumaroyl-CoA ligase; HCT, hydroxycinnamoyl transferase; C3H, coumarate 3-hydroxylase; COMT, caffeoyl-CoA 3-O-methyltransferase; HCHL, hydroxycinnamoyl-coenzyme A hydratase lyase; pAMT, Putative aminotransferase; BCAT, branched-chain amino acid aminotransferase; KAS, ketoacyl-ACP synthetase; ACL, acyl carrier protein; FatA, acyl-ACP-thiesterase; ACS, acyl-CoA synthetase; CS, capsaicinoid synthase; WRKY (WRKY9, 25), bHLH (bHLH7, 9, 26, 63 and 86), MYB (MYB4, 24, 31, 37 and 48) are the genes that have been shown in current studies to be involved in the capsaicin regulatory pathway, adapted from Naves et al. [<a href="#B20-plants-13-02887" class="html-bibr">20</a>] and QIN et al. [<a href="#B68-plants-13-02887" class="html-bibr">68</a>]. Note: Refer to Aza-Gonzalez et al. [<a href="#B12-plants-13-02887" class="html-bibr">12</a>] for the chemical structure of capsaicin synthesis pathway-related substances. Refer to Zhang et al. [<a href="#B69-plants-13-02887" class="html-bibr">69</a>]and Naves et al. [<a href="#B20-plants-13-02887" class="html-bibr">20</a>] for the pictures of germplasm resources of different varieties.</p>
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<p>Effect of different environmental factors on capsaicinoids. Note: CPA: chlorophenoxyacetic acid; GA3: Gibberellic acid; SA: salicylic acid. Red arrows indicate different conditions promoting the synthesis of capsaicinoids, where the arrow in the pathogen module indicates that capsaicin improves disease resistance in chili.</p>
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19 pages, 8261 KiB  
Article
The Critical Role of Phenylpropanoid Biosynthesis Pathway in Lily Resistance Against Gray Mold
by Qi Cui, Xinran Li, Shanshan Hu, Dongfeng Yang, Ann Abozeid, Zongqi Yang, Junhao Jiang, Ziming Ren, Danqing Li, Dongze Li, Liqun Zheng and Anhua Qin
Int. J. Mol. Sci. 2024, 25(20), 11068; https://doi.org/10.3390/ijms252011068 (registering DOI) - 15 Oct 2024
Viewed by 245
Abstract
Gray mold caused by Botrytis elliptica is one of the most determinative factors of lily growth and has become a major threat to lily productivity. However, the nature of the lily B. elliptica interaction remains largely unknown. Here, comparative transcriptomic and metabolomic were [...] Read more.
Gray mold caused by Botrytis elliptica is one of the most determinative factors of lily growth and has become a major threat to lily productivity. However, the nature of the lily B. elliptica interaction remains largely unknown. Here, comparative transcriptomic and metabolomic were used to investigate the defense responses of resistant (‘Sorbonne’) and susceptible (‘Tresor’) lily cultivars to B. elliptica infection at 24 hpi. In total, 1326 metabolites were identified in ‘Sorbonne’ and ‘Tresor’ after infection, including a large number of phenylpropanoids. Specifically, the accumulation of four phenylpropanes, including eriodictyol, hesperetin, ferulic acid, and sinapyl alcohol, was significantly upregulated in the B. elliptica-infected ‘Sorbonne’ compared with the infected ‘Tresor’, and these phenylpropanes could significantly inhibit B. elliptica growth. At the transcript level, higher expression levels of F3′M, COMT, and CAD led to a higher content of resistance-related phenylpropanes (eriodictyol, ferulic acid, and sinapyl alcohol) in ‘Sorbonne’ following B. elliptica infection. It can be assumed that these phenylpropanes cause the resistance difference between ‘Sorbonne’ and ‘Tresor’, and could be the potential marker metabolites for gray mold resistance in the lily. Further transcriptional regulatory network analysis suggested that members of the AP2/ERF, WRKY, Trihelix, and MADS-M-type families positively regulated the biosynthesis of resistance-related phenylpropanes. Additionally, the expression patterns of genes involved in phenylpropanoid biosynthesis were confirmed using qRT-PCR. Therefore, we speculate that the degree of gray mold resistance in the lily is closely related to the contents of phenylpropanes and the transcript levels of the genes in the phenylpropanoid biosynthesis pathway. Our results not only improve our understanding of the lily’s resistance mechanisms against B. elliptica, but also facilitate the genetic improvement of lily cultivars with gray mold resistance. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>(<b>A</b>) Oriental hybrid ‘Sorbonne’ and Asiatic hybrid ‘Tresor’. (<b>B</b>) Leaf phenotype of ‘Sorbonne’ and ‘Tresor’ after infection with <span class="html-italic">B. elliptica</span>, scale bar = 1 cm. (<b>C</b>) Leaf lesion size over time of ‘Sorbonne’ and ‘Tresor’ after infection with <span class="html-italic">B. elliptica</span>, n = 12. The lesion areas are shown as the means of the three biological replicates ± SD. Asterisks indicate statistically significant differences between resistant and susceptible cultivars according to Student’s <span class="html-italic">t</span>-test (** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>(<b>A</b>) Identification and functional enrichment analysis of DEGs in lily. (<b>A</b>) Volcanic plots of DEGs. Red and blue points represent the up-regulated and down-regulated DEGs, respectively. RD and SD represent <span class="html-italic">B. elliptica</span>-inoculated samples of ‘Sorbonne’ and ‘Tresor’, respectively. RH and SH represent the controls of ‘Sorbonne’ and ‘Tresor’, respectively. (<b>B</b>) GO enrichment analysis of the DEGs detected in <span class="html-italic">B. elliptica</span>-infected ‘Sorbonne’ compared with its control. Red texts represent four defense-related terms that were specifically enriched in ‘Sorbonne’ after infection relative to ‘Tresor’. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. (<b>C</b>) The ridge plot of KEGG enrichment analysis for the DEGs. The average log<sub>2</sub>FoldChange value of each gene in the pathway is shown in the ridge plot. If the value is greater than 0, the gene is the upregulated (right), and the gene is downregulated (left) if its value is less than 0. Three biological replicates were used for transcriptomic analysis.</p>
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<p>Classification of metabolites and identification of DAMs in ‘Sorbonne’ and ‘Tresor’ after infection with <span class="html-italic">B. elliptica</span>. (<b>A</b>) Classification and composition of identified metabolites. (<b>B</b>) Principal component analysis (PCA) of the samples based on the identified metabolites. (<b>C</b>) Numbers of DAMs identified in different pairwise comparisons. (<b>D</b>) Venn diagram of DAMs identified in ‘Sorbonne’ and ‘Tresor’ after infection with <span class="html-italic">B. elliptica</span>. Six biological replicates were used for metabolomic analysis.</p>
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<p>KEGG enrichment analysis of DAMs and in-depth analysis of key metabolites. (<b>A</b>) Six DAMs (a–f) with opposite accumulation patterns in ‘Sorbonne’ and ‘Tresor’ after infection with <span class="html-italic">B. elliptica</span> and three DAMs (g–i) were particularly accumulated in ‘Sorbonne’ or ‘Tresor’ after infection with <span class="html-italic">B. elliptica</span>. The horizontal axis indicates the value of log<sub>2</sub>FoldChange. Orange bars represent up-regulated DAMs, and blue bars represent the down-regulated DAMs. (<b>B</b>) KEGG enrichment analysis for DAMs.</p>
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<p>Integrated analysis of transcriptome and metabolome. (<b>A</b>) Venn diagram of KEGG pathways enriched in DEGs and DAMs in ‘Sorbonne’ and ‘Tresor’. MRD and MSD represent <span class="html-italic">B. elliptica</span>-inoculated samples of ‘Sorbonne’ and ‘Tresor’ metabolomes, respectively. MRH and MSH represent the controls of ‘Sorbonne’ and ‘Tresor’ metabolomes, respectively. TRD and TSD represent <span class="html-italic">B. elliptica</span>-inoculated samples of ‘Sorbonne’ and ‘Tresor’ transcriptomes, respectively. TRH and TSH represent the controls of ‘Sorbonne’ and ‘Tresor’ transcriptomes, respectively. (<b>B</b>) Diagram of partial phenylpropanoid biosynthesis pathway. The values of log<sub>2</sub>FoldChange for key DEGs are marked. (<b>C</b>) Comparison of the metabolite relative contents (represented as peak areas) between control and <span class="html-italic">B. elliptica</span>-infected ‘Sorbonne’ and ‘Tresor’. Data are presented as the means of the three biological replicates ± SD. Different letters above the bars indicate significant differences between treatments or genotypes according to Duncan’s multiple range test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Transcription regulatory network analysis of phenylpropanes in lily after infection with <span class="html-italic">B. elliptica</span>. (<b>A</b>) Specifically expressed DETFs in ‘Sorbonne’ or ‘Tresor’. The values of log<sub>2</sub>FoldChange for DETFs are marked. (<b>B</b>) Transcription regulator network of phenylpropanes according to integrated analysis of transcriptome and metabolome. Red and orange circles represent the DETFs and DAMs, respectively.</p>
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<p>qRT-PCR validation of key candidate DEGs associated with phenylpropanoids metabolism in lily. The relative expression levels are shown as the means of the three biological replicates ± SD. RD and SD represent <span class="html-italic">B. elliptica</span>-inoculated transcriptomic samples of ‘Sorbonne’ and ‘Tresor’, respectively. RH and SH represent the controls of ‘Sorbonne’ and ‘Tresor’, respectively.</p>
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<p>Inhibition effect of the phenylpropanes on <span class="html-italic">B. elliptica</span> growth. (<b>A</b>) Hesperetin, sinapyl alcohol, eriodictyol, and ferulic acid inhibited the growth of <span class="html-italic">B. elliptica</span>. DMSO was used as the solvent control. Scale bar = 1 cm. (<b>B</b>) The inhibition area of <span class="html-italic">B. elliptica</span> after treatment with hesperetin, sinapyl alcohol, eriodictyol, and ferulic acid, respectively. The inhibition areas are shown as the means of the three biological replicates ± SD. Different letters above the bars indicate significant differences among various treatments according to Duncan’s multiple range test (<span class="html-italic">p</span> &lt; 0.01).</p>
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19 pages, 5544 KiB  
Article
Comprehensive Transcriptomic Analysis Reveals Defense-Related Genes and Pathways of Rice Plants in Response to Fall Armyworm (Spodoptera frugiperda) Infestation
by Xueyan Zhang, Xihao Wang and Tao Wang
Plants 2024, 13(20), 2879; https://doi.org/10.3390/plants13202879 (registering DOI) - 15 Oct 2024
Viewed by 391
Abstract
Rice (Oryza sativa L.) serves as a substitute for bread and is a staple food for half of the world’s population, but it is heavily affected by insect pests. The fall armyworm (Spodoptera frugiperda) is a highly destructive pest, threatening [...] Read more.
Rice (Oryza sativa L.) serves as a substitute for bread and is a staple food for half of the world’s population, but it is heavily affected by insect pests. The fall armyworm (Spodoptera frugiperda) is a highly destructive pest, threatening rice and other crops in tropical regions. Despite its significance, little is known about the molecular mechanisms underlying rice’s response to fall armyworm infestation. In this study, we used transcriptome analysis to explore the global changes in gene expression in rice leaves during a 1 h and 12 h fall armyworm feeding. The results reveal 2695 and 6264 differentially expressed genes (DEGs) at 1 and 12 h post-infestation, respectively. Gene Ontology (GO) and KEGG enrichment analyses provide insights into biological processes and pathways affected by fall armyworm feeding. Key genes associated with hormone regulation, defense metabolic pathways, and antioxidant and detoxification processes were upregulated, suggesting the involvement of jasmonic acid (JA) signaling, salicylic acid biosynthesis pathways, auxin response, and heat shock proteins in defense during 1 h and 12 h after fall armyworm infestation. Similarly, key genes involved in transcriptional regulation and defense mechanisms reveal the activation of calmodulins, transcription factors (TFs), and genes related to secondary metabolite biosynthesis. Additionally, MYB, WRKY, and ethylene-responsive factors (ERFs) are identified as crucial TF families in rice’s defense response. This study provides a comprehensive understanding of the molecular dynamics in rice responding to fall armyworm infestation, offering valuable insights for developing pest-resistant rice varieties and enhancing global food security. The identified genes and pathways provide an extensive array of genomic resources that can be used for further genetic investigation into rice herbivore resistance. This also suggests that rice plants may have evolved strategies against herbivorous insects. It also lays the groundwork for novel pest-resistance techniques for rice. Full article
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<p>Showing the layout of experimental design: (<b>A</b>) infestation of rice plants with FAW larvae for 1 h and 12 h and control; (<b>B</b>) larvae were collected from infested host plants for RNA extraction and cDNA synthesis; (<b>C</b>) high-throughput sequencing and raw data; (<b>D</b>) biological insights; and (<b>E</b>) RTq-PCR analysis for the verification of DEGs data obtained from transcriptome analysis.</p>
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<p>Bar graph showing a total number of up- and downregulated differentially expressed genes (DEGs) in transcriptome analysis of Rice-1h vs. control and Rice-12h vs. control after FAW larvae infestation.</p>
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<p>Gene Ontology (GO) classification of transcripts. The number of significantly up- and downregulated unigenes in Rice-1h vs. control (<b>A</b>) and Rice-12h vs. control (<b>B</b>) after FAW larvae infestation.</p>
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<p>Gene Ontology (GO)-enriched terms of differentially expressed genes (DEGs) and unigenes in Rice-1h vs. control (<b>A</b>) and Rice-12h vs. control (<b>B</b>) after FAW larvae infestation. The <span class="html-italic">x</span>-axis lists the sub-GO terms under categories of biological process, cellular component, and molecular function. The <span class="html-italic">y</span>-axis is the number of DEGs involved in each term.</p>
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<p>Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation and pathways of in Rice-1h vs. control (<b>A</b>) and Rice-12h vs. control (<b>B</b>) after FAW larvae infestation.</p>
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<p>The expression patterns of defensive–responsive genes in in Rice-1h vs. control (<b>A</b>) and Rice-12h vs. control (<b>B</b>) after FAW larvae infestation. Hierarchical clustering heat map depicting overall results of the FPKM clustering using log2 (FPKM + 1) values. The red and blue squares indicate genes with high or low gene expression levels, respectively.</p>
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<p>A number of upregulated genes related to secondary metabolism (<b>A</b>) and transcriptional regulation in Rice-1h vs. control (<b>A</b>) and Rice-12h vs. control (<b>B</b>) after FAW larvae infestation.</p>
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<p>A number of upregulated genes related to hormone regulation (<b>A</b>) and antioxidant and detoxification processes in Rice-1h vs. control (<b>A</b>) and Rice-12h vs. control (<b>B</b>) after FAW larvae infestation.</p>
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<p>(<b>A</b>–<b>F</b>). Results for the qRT-PCR confirmation of the DEGs library. qRT-PCR analysis of ten upregulated genes of detoxification genes: transcriptional regulation (<b>A</b>–<b>F</b>) and hormone regulation (<b>G</b>–<b>L</b>) in Rice-1h vs. control and Rice-12h vs. control after FAW larvae infestation. Different letters a and b indicate significant differences.</p>
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<p>(<b>A</b>–<b>H</b>) Results for the qRT-PCR confirmation of the DEGs library and qRT-PCR analysis of upregulated genes of antioxidants and detoxification genes: Hormone regulation (<b>A</b>–<b>D</b>). Antioxidant and detoxification processes (<b>E</b>–<b>H</b>) in Rice-1h vs. control and Rice-12h vs. control after FAW larvae infestation.</p>
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<p>A working model diagram of molecular insights into the rice plant defense mechanism in response to an insect-attacked plant. Insect-derived elicitors are perceived by unidentified receptors on the plasma membranes, triggering rapid activation of MAPKs followed by biosynthesis of phytohormones, JA, JA-Ile, and ethylene. After several steps of signaling transduction, transcription factors (MYC2 and ERFs, for instance) regulate the accumulation of non-volatile secondary metabolites (such as TPIs in rice), which function as direct defenses against herbivores.</p>
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14 pages, 5169 KiB  
Article
Biochemical and Transcriptomic Analyses Reveal Key Salinity and Alkalinity Stress Response and Tolerance Pathways in Salix linearistipularis Inoculated with Trichoderma
by Zhouqing Han, Lili Chen, Wenyi Wang, Xueting Guan, Junjie Song and Shurong Ma
Agronomy 2024, 14(10), 2358; https://doi.org/10.3390/agronomy14102358 - 13 Oct 2024
Viewed by 488
Abstract
Soil salinization and alkalinization are pervasive environmental issues that severely restrict plant growth and crop yield. Utilizing plant growth-promoting rhizobacteria (PGPR) is an effective strategy to enhance plant tolerance to saline–alkaline stress, though the regulatory mechanisms remain unclear. This study employed biochemical and [...] Read more.
Soil salinization and alkalinization are pervasive environmental issues that severely restrict plant growth and crop yield. Utilizing plant growth-promoting rhizobacteria (PGPR) is an effective strategy to enhance plant tolerance to saline–alkaline stress, though the regulatory mechanisms remain unclear. This study employed biochemical and RNA-Seq methods to uncover the critical growth-promoting effects of Trichoderma spp. on Salix linearistipularis under saline–alkaline stress. The results showed that, during saline–alkaline stress, inoculation with Trichoderma sp. M4 and M5 significantly increased the proline and soluble sugar contents in Salix linearistipularis, enhanced the activities of SOD, POD, CAT, and APX, and reduced lipid peroxidation levels, with M4 exhibiting more pronounced effects than M5. RNA-Seq analysis of revealed that 11,051 genes were upregulated after Trichoderma sp. M4 inoculation under stress conditions, with 3532 genes primarily involved in carbon metabolism, amino acid biosynthesis, and oxidative phosphorylation—processes that alleviate saline–alkaline stress. Additionally, 7519 genes were uniquely upregulated by M4 under stress, mainly enriched in secondary metabolite biosynthesis, amino acid metabolism, cyanamide metabolism, and phenylpropanoid biosynthesis. M4 mitigates saline–alkaline stress-induced damage in Salix linearistipularis seedlings by reducing oxidative damage, enhancing organic acid and amino acid metabolism, and activating phenylpropanoid biosynthesis pathways to eliminate harmful ROS. This enhances the seedlings’ tolerance to saline–alkaline stress, providing a basis for studying fungi–plant interactions under such conditions. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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<p><span class="html-italic">Trichoderma</span> enhances the tolerance of <span class="html-italic">Salix linearistipularis</span> to saline–alkaline stress. (<b>a</b>–<b>c</b>) Phenotypes of <span class="html-italic">Salix linearistipularis</span> inoculated or uninoculated with <span class="html-italic">Trichoderma</span> under normal or saline–alkaline stress conditions. (<b>d</b>) MDA content: malondialdehyde content. (<b>e</b>) Proline content. (<b>f</b>) Soluble sugar content. (<b>g</b>) APX activity: aseorbateperoxidase activity. (<b>h</b>) CAT activity: catalase activity. (<b>i</b>) POD activity: peroxidase activity. (<b>j</b>) SOD activity: superoxide dismutase activity. CK: uninoculated with <span class="html-italic">Trichoderma</span>, M4: inoculated with <span class="html-italic">Trichoderma</span> M4, M5: inoculated with <span class="html-italic">Trichoderma</span> M5. 0 mM, 50 mM, and 200 mM: saline–alkaline stress (0, 50, 200 mM) induced by NaCl:Na<sub>2</sub>SO<sub>4</sub>:NaHCO<sub>3</sub>:Na<sub>2</sub>CO<sub>3</sub> at a ratio of 1:9:9:1. Data are from three biological repetitions (<span class="html-italic">n</span> = 3), means ± standard error (SE). Different lowercase letters indicate significant differences among different treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Colony morphology and root colonization of <span class="html-italic">Trichoderma</span> transformants. (<b>a</b>,<b>d</b>) Colony morphology of M4-GFP and M5-GFP after 3 days on PDA medium. (<b>b</b>,<b>e</b>) Morphology of M4-GFP and M5-GFP under a fluorescence microscope. (<b>c</b>,<b>f</b>) Colonization of M4-GFP in <span class="html-italic">Salix linearistipularis</span> roots under normal conditions.</p>
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<p>The number of DEGs (differentially expressed genes) in different comparison groups. (<b>a</b>) Volcano plot of DEGs in CK-0 vs. CK-50. (<b>b</b>) Volcano plot of DEGs in CK-0 vs. M4-0. (<b>c</b>) Volcano plot of DEGs in CK-50 vs. M4-50. (<b>d</b>) Volcano plot of DEGs in CK-0 vs. M4-50.</p>
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<p>RNA-Seq analysis of <span class="html-italic">Salix linearistipularis</span> seedlings inoculated with or without M4 under normal or saline–alkaline stress conditions. (<b>b</b>) GO analysis of 11,051 upregulated genes in CK-50 vs. M4-50. (<b>c</b>) KEGG enrichment analysis of genes in the overlapping portion of the Venn diagram described in (<b>a</b>). (<b>d</b>) KEGG enrichment pathways of 7519 uniquely upregulated DEGs in CK-50 vs. M4-50. KEGG: Kyoto Encyclopedia of Genes and Genomes.</p>
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<p>Effects of M4 inoculation on photosynthetic characteristics and expression of Calvin cycle-related genes in <span class="html-italic">Salix linearistipularis</span> leaves under saline–alkaline stress. (<b>a</b>) Net photosynthetic rate (Photo); (<b>b</b>) transpiration rate (Trmmol); (<b>c</b>) conductance to H<sub>2</sub>O (Cond); (<b>d</b>) intercellular CO<sub>2</sub> concentration (Ci); (<b>e</b>) qRT-PCR analysis of Calvin cycle-associated genes in mock-inoculated or M4-inoculated seedlings under saline–alkaline stress. (<b>f</b>) Calvin cycle-related genes transcriptional heat map. RuBP: Ribulose-1,5-bisphosphate, Rubisco: ribulose-1,5-bisphosphate carboxylase/oxygenase, PG: 2,3-phosphoglycerate, ATP: adenosine triphosphate, ADP: adenosine diphosphate; PGK: phosphogly-cerate kinase, BPG: 1,3-phosphoglycerate, GAPD: glyceraldehyde-3-phosphate dehydrogenase, NADPH: reduced nicotinamide adenine dinucleotide phosphate, NADP<sup>+</sup>: oxidation nicotinamide adenine dinucleotide phosphate, G3P: glyceraldehyde 3-phosphate, TPI: triosephosphate isomerase, DHAP: dihydroxyacetone phosphate, ALDO: fructose-bisphosphate aldolase, SBP: sedoheptulose-1,7-bisphosphate, SBPase: sedoheptulose-1,7-bisphosphatase, S7P: sedoheptulose7-phosphate, TK: transketolase, R5P: ribose 5-phosphate, R5PI: ribose-5-phosphate isomerase, RU5P: ribulose-5-phosphate, PRK: ribulose-5-bisphosphate kinase. Note: The data in <a href="#agronomy-14-02358-f005" class="html-fig">Figure 5</a> are from three replicates (n = 3) and are shown as means ± standard error (SE). Different lowercase letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Expression of genes related to lysine metabolic pathways in M4-inoculated <span class="html-italic">Salix linearistipularis</span> leaves under saline–alkaline stress. (<b>a</b>) Lysine metabolism-related genes transcriptional heat map; (<b>b</b>) qRT-PCR analysis of lysine metabolism-associated genes in mock-inoculated or M4-inoculated seedlings under saline–alkaline stress. AK: Aspartate kinase, ASD: aspartate-semialdehyde dehydrogenase, 4HTS: 4-hydroxy-tetrahydrodipicolinate synthase, 4HTR: 4-hydroxy-tetrahydrodipicolinate reductase, LLDA: LL-diaminopimelate aminotransferase, DE: diaminopimelate epimerase, DD: diaminopimelate decarboxylase. Note: The data in <a href="#agronomy-14-02358-f006" class="html-fig">Figure 6</a> are from three replicates (n = 3) and are shown as means ± standard error (SE). Different lowercase letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Expression profiles of genes related to the antioxidant system. SOD: Superoxide dismutase, CAT: catalase, APX: ascorbate peroxidase, MDHAR: monodehydroascorbate reductase, DHAR: dehydroascorbate reductase, GR: glutathione reductase. Note: The data in <a href="#agronomy-14-02358-f007" class="html-fig">Figure 7</a> are from three replicates (n = 3) and represent means ± standard error (SE).</p>
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25 pages, 4909 KiB  
Article
Genomic Diversity of Streptomyces clavuligerus: Implications for Clavulanic Acid Biosynthesis and Industrial Hyperproduction
by Paula Ríos-Fernández, Carlos Caicedo-Montoya and Rigoberto Ríos-Estepa
Int. J. Mol. Sci. 2024, 25(20), 10992; https://doi.org/10.3390/ijms252010992 - 12 Oct 2024
Viewed by 484
Abstract
Streptomyces clavuligerus is a species used worldwide to industrially produce clavulanic acid (CA), a molecule that enhances antibiotic effectiveness against β-lactamase-producing bacterial strains. Despite its low inherent CA production, hyper-producing strains have been developed. However, genomic analyses specific to S. clavuligerus and CA biosynthesis [...] Read more.
Streptomyces clavuligerus is a species used worldwide to industrially produce clavulanic acid (CA), a molecule that enhances antibiotic effectiveness against β-lactamase-producing bacterial strains. Despite its low inherent CA production, hyper-producing strains have been developed. However, genomic analyses specific to S. clavuligerus and CA biosynthesis are limited. Genomic variations that may influence CA yield were explored using S. clavuligerus strain genomes from diverse sources. Despite the slight differences obtained by similarity index calculation, pan-genome estimation revealed that only half of the genes identified were present in all strains. As expected, core genes were associated with primary metabolism, while the remaining genes were linked to secondary metabolism. Differences at the sequence level were more likely to be found in regions close to the tips of the linear chromosome. Wild-type strains preserved larger chromosomal and plasmid regions compared to industrial and/or hyper-producing strains; such a grouping pattern was also found through refined phylogenetic analyses. These results provide essential insights for the development of hyper-producing S. clavuligerus strains, attending to the critical demand for this antibiotic enhancer and contributing to future strategies for CA production optimization. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>Pan-genome composition and rarefaction curves by Panaroo (<b>left</b>) and BPGA (<b>right</b>). According to Panaroo results, the pan-genome of <span class="html-italic">S. clavuligerus</span> contains 8821 clusters (4641 core genes, 233 soft-core genes, 3135 shell genes, and 813 cloud genes). The pan-genome was shown to be closed in both cases (α &gt; 1) by performing 1000 permutations of genomes and fitting a power law to pan-genome counts.</p>
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<p>Evolutionary relationships of <span class="html-italic">S. clavuligerus</span> strains. Phylogenetic tree of concatenated sequences of 3760 core genes from <span class="html-italic">S. clavuligerus</span>. Wild-type, industrial, hyper-producing, and others strain types are depicted. Strain categories were defined as follows. Wild-type: strains reported by the literature to be wild-type. Industrial: strains known to be used in industrial CA production. Hyper-producing: industrial strains for which CA produced has been published and significantly exceeds that produced by a wild-type strain. Others: include strains known to have genetic modifications and/or whose relationship with wild-type strains is unclear and level of CA produced has not been published. Bootstrap values are used as branch support and highlighted in colored boxes. Additional information on CA produced per strain category can be found in <a href="#app1-ijms-25-10992" class="html-app">Supplementary Table S1</a>.</p>
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<p>Functional annotation of <span class="html-italic">S. clavuligerus</span> pan-genome. Annotation of core (inner), soft-core, shell, and cloud genes (Outer) of <span class="html-italic">S. clavuligerus</span> pan-genome based on (<b>A</b>) KEGG Prokaryote database and (<b>B</b>) COG database.</p>
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<p>CRISPR-Cas systems identified in <span class="html-italic">S. clavuligerus</span> genomes. Complete genomes of <span class="html-italic">S. clavuligerus</span> strains were analyzed. The grey line represents positions within a hypothetical genome whose length is the maximum among genomes considered. Relative positions of Cas operons and CRISPR arrays identified in all genomes are represented as blue and red lines, respectively. Dotted lines indicate the average starting point of some subgroups.</p>
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<p>CAZyme families and subfamilies present in <span class="html-italic">S. clavuligerus</span> genomes. CAZyme families are displayed as stacked bars containing subfamilies (code numbers in legend). The counts per family are shown on y-axis.</p>
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<p>Type and relative position of BGCs found in the chromosome of <span class="html-italic">S. clavuligerus</span> genomes.</p>
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<p>Biosynthetic gene clusters (BGCs) present in 30 <span class="html-italic">S. clavuligerus</span> genomes. BGCs annotated by BiG-SCAPE (<b>A</b>) and MIBiG (<b>B</b>), with each BGC type showcased in a different color. Annotation of BGCs by antiSMASH is also shown (<b>C</b>), with more specific categories.</p>
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<p>Presence/absence of genes within BGCs associated with CA biosynthesis of 30 <span class="html-italic">S. clavuligerus</span> genomes. AAC: Hypothetical protein, EA: Homoserine/homoserine lactone efflux protein, EAB: Flavin reductase, EAC: Aldo-keto reductase IolS, EAD: Clavaminate synthase 1, EAE: Homoserine O-acetyltransferase, EAF: 3,6-diketocamphane 1,6-monooxygenase, EAG: Putrescine--pyruvate aminotransferase, EAH: Serine/threonine-protein kinase PknD, LAR: Protein-glutamate methylesterase/protein-glutamine glutaminase, DAP: Glutamate N-acetyltransferase 2, LAS: Agmatinase, DAM: Carboxyethyl-arginine beta-lactam-synthase, DAL:N(2)-(2-carboxyethyl)arginine synthase, LAT: Fluorothreonine transaldolase, LAU:2-iminobutanoate/2-iminopropanoate deaminase, LAV: Methionine aminotransferase, LAW:L-threo-3-hydroxyaspartate ammonia-lyase, NAI:Vitamin B6 salvage pathway transcriptional repressor PtsJ, QAQ: Histidinol-phosphate aminotransferase, QAR: Putative N-acetyl-LL-diaminopimelate aminotransferase, QAS: Sugar efflux transporter, QAT:Adenosylmethionine-8-amino-7-oxononanoate aminotransferase, DAF: Transcriptional regulatory protein MoaR1, DAG: Beta-lactamase inhibitory protein, DAH:L-lysine-epsilon aminotransferase, DAI: Tyrocidine synthase 2, DAK: Peptidoglycan D,D-transpeptidase MrdA, DAN: Proclavaminate amidinohydrolase, DAO: Clavaminate synthase 2, DAQ: Heme-binding protein A, DAR: HTH-type transcriptional regulator ArgP, DAS: Putative oxidoreductase, DAT: Cytochrome P450-SU2, DAU:Ferredoxin-2, and NAJ: Putative amino-acid metabolite efflux pump.</p>
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<p>Diagram of the methodology displaying the tools, inputs, and output flow per step. The results can be categorized in Annotation analyses, Biosynthetic Gene Cluster analyses (BGCs), and Pan-genome analyses. The numbers correspond to the number of genomes used as input data for a given tool; no number is displayed in steps where input data were not genomes.</p>
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20 pages, 3394 KiB  
Article
Metagenomic Analysis: Alterations of Soil Microbial Community and Function due to the Disturbance of Collecting Cordyceps sinensis
by Yangyang Chen, Zhenjiang Chen, Xiuzhang Li, Kamran Malik and Chunjie Li
Int. J. Mol. Sci. 2024, 25(20), 10961; https://doi.org/10.3390/ijms252010961 - 11 Oct 2024
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Abstract
Soil microorganisms are critical to the occurrence of Cordyceps sinensis (Chinese Cordyceps), a medicinal fungi used in Traditional Chinese Medicine. The over-collection of Chinese Cordyceps has caused vegetation degradation and impacted the sustainable occurrence of Cordyceps. The effects of Chinese Cordyceps [...] Read more.
Soil microorganisms are critical to the occurrence of Cordyceps sinensis (Chinese Cordyceps), a medicinal fungi used in Traditional Chinese Medicine. The over-collection of Chinese Cordyceps has caused vegetation degradation and impacted the sustainable occurrence of Cordyceps. The effects of Chinese Cordyceps collection on soil microorganisms have not been reported. Metagenomic analysis was performed on the soil of collecting and non-collecting areas of production and non-production areas, respectively. C. sinensis collection showed no alteration in alpha-diversity but significantly affected beta-diversity and the community composition of soil microorganisms. In Cordyceps production, Thaumarchaeota and Crenarchaeota were identified as the dominant archaeal phyla. DNA repair, flagellar assembly, propionate metabolism, and sulfur metabolism were affected in archaea, reducing the tolerance of archaea in extreme habitats. Proteobacteria, Actinobacteria, Acidobacteria, Verrucomicrobia, and Nitrospirae were identified as the dominant bacterial phyla. The collection of Chinese Cordyceps enhanced the bacterial biosynthesis of secondary metabolites and suppressed ribosome and carbon metabolism pathways in bacteria. A more complex microbial community relationship network in the Chinese Cordyceps production area was found. The changes in the microbial community structure were closely related to C, N, P and enzyme activities. This study clarified soil microbial community composition and function in the Cordyceps production area and established that collection clearly affects the microbial community function by altering microbial community structure. Therefore, it would be important to balance the relationship between cordyceps production and microbiology. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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<p>(<b>A</b>) Soil physicochemical properties and (<b>B</b>) several enzyme activities in the C, Nc and Np of the five regions. Collecting areas of Chinese Cordyceps-producing areas (C); non-collecting areas of Chinese <span class="html-italic">Cordyceps</span>-producing areas (Nc); Chinese <span class="html-italic">Cordyceps</span> non-producing areas (Np). Zaduo (ZD), Yushu (YS), Maqin (MQ), Henan (HN)n, and Hualong (HL) in Qinghai Province. Different lowercase letters denote significance differences (<span class="html-italic">p</span> &lt; 0.05) between the C, Nc and Np, and uppercase letters denote significance differences (<span class="html-italic">p</span> &lt; 0.05) between the origins of Chinese <span class="html-italic">Cordyceps</span> in Qinghai Province.</p>
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<p>Microbial community α- and β-diversity. Shared and unique microorganisms and PCoA of the soil bacterial community (<b>A</b>); Chao1 and Shannon index values of archaea, bacteria, and fungi (<b>B</b>,<b>C</b>). TOG1 clustering contains all samples from ZD and YS, and TOG2 contains all samples from HL and HN. Collecting areas of Chinese <span class="html-italic">Cordyceps</span>-producing areas (C); non-collecting areas of Chinese <span class="html-italic">Cordyceps</span>-producing areas (Nc); Chinese <span class="html-italic">Cordyceps</span> non-producing areas (Np). Zaduo (ZD), Yushu (YS), Maqin (MQ), Henan (HN), and Hualong (HL) in the Qinghai Province. Different lowercase letters denote significance differences (<span class="html-italic">p</span> &lt; 0.05) between C, Nc, and Np.</p>
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<p>Bacterial community composition and structure at the phylum (<b>A</b>) and genus level (<b>B</b>). All unidentified microbes in the top 15 relative abundances were categorized as “Unidentified”, and all after 15 relative scores were categorized as “Other”. Collecting areas (C); non-collecting areas (Nc); non-producing areas (Np). Collecting areas of Chinese Cordyceps-producing areas (C); non-collecting areas of Chinese Cordyceps-producing areas (Nc); Chinese Cordyceps non-producing areas (Np). Zaduo (ZD), Yushu (YS), Maqin (MQ), Henan (HN)n, and Hualong (HL) in Qinghai Province.</p>
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<p>The correlation network analysis of bacterial community (top 50 abundance) in C (<b>A</b>), Nc (<b>B</b>), and Np (<b>C</b>). Each node represents a species, and species of the same class are set to the same color when visualized. The node size in the graph signifies the species abundance, with larger nodes corresponding to greater abundance. Line color signifies correlation: red represents a positive correlation between species, while gray denotes a negative correlation. Line thickness corresponds to the magnitude of the correlation coefficient; a thicker line signifies a stronger correlation between species. The number of lines illustrates the interconnectedness among species, with a higher line count indicating closer connections. Collecting areas of Chinese <span class="html-italic">Cordyceps</span>-producing areas (C); non-collecting areas of Chinese <span class="html-italic">Cordyceps</span>-producing areas (Nc); Chinese <span class="html-italic">Cordyceps</span> non-producing areas (Np).</p>
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<p>KEGG functional pathways (<b>A</b>), modules (<b>B</b>), and enzymes (<b>C</b>) of bacteria that differentially restrict the collection region. The correlation of enzymes (<b>D</b>) and nutrient characteristics (<b>E</b>) with the relative abundances of the top fifteen bacterial phyla. Collecting areas of Chinese Cordyceps-producing areas (C); non-collecting areas of Chinese <span class="html-italic">Cordyceps</span>-producing areas (Nc); Chinese <span class="html-italic">Cordyceps</span> non-producing areas (Np). * significant difference stands at <span class="html-italic">p</span> &lt; 0.05; ** significant difference stands at <span class="html-italic">p</span> &lt; 0.01; *** significant difference stands at <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Soil sample collection sites in Qinghai Province. The color gradient corresponds to the elevation information. Zaduo (ZD), Yushu (YS), Maqin (MQ), Henan (HN), and Hualong (HL) in Qinghai Province. These five regions are important <span class="html-italic">Cordyceps</span> production areas.</p>
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26 pages, 4186 KiB  
Review
Research Progress on the Mechanism for Improving Glucose and Lipid Metabolism Disorders Using Phenolic Acid Components from Medicinal and Edible Homologous Plants
by Miao Sun, Zhimin Zhang, Jingchen Xie, Jiahui Yu, Suhui Xiong, Feng Xiang, Xinyi Ma, Chen Yang and Limei Lin
Molecules 2024, 29(20), 4790; https://doi.org/10.3390/molecules29204790 - 10 Oct 2024
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Abstract
Glucose and lipid metabolism disorders are the core pathological mechanism of a variety of metabolic diseases, and the incidence of related diseases is increasing year by year, which seriously threatens human life and health. Traditional Chinese medicine with medicinal and edible properties refers [...] Read more.
Glucose and lipid metabolism disorders are the core pathological mechanism of a variety of metabolic diseases, and the incidence of related diseases is increasing year by year, which seriously threatens human life and health. Traditional Chinese medicine with medicinal and edible properties refers to Chinese medicinal resources that have both medicinal and edible characteristics. Due to its safety and its health-promoting and medicinal functions, traditional Chinese medicine has received increasing attention in the development of functional health foods. Phenolic acids are important secondary metabolites that are ubiquitous in medicinal and edible homologous plants, and the regulation of glycolipid metabolism is an important activity and plays a key role in many diseases. In this paper, we focus on the alleviation of glycolipid disorders using MEHH phenolic acids, which regulate glucose metabolism and lipid metabolism, improve insulin resistance, inhibit inflammatory responses, alleviate oxidative stress, and regulate intestinal flora; additionally, we summarize the mechanism in order to provide a reference for MEHH phenolic acids in the treatment of glycolipid metabolism diseases. Full article
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<p>The structure of phenolic acid compounds in MEHHs.</p>
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<p>A demonstration of MEHHs’ phenolic acids regulating pathways in glucose metabolism. The arrow (→) indicates enhancement, while the barred line (┤) signifies inhibition. Glucose metabolism encompasses the synthesis, cleavage, transport, and storage of glucose in living organisms, involving critical pathways such as glycolysis, the tricarboxylic acid cycle, and the processes of glycogen synthesis and breakdown, along with gluconeogenesis. MEHHs’ phenolic acids facilitate glucose uptake, inhibit gluconeogenesis, and enhance glycogen synthesis by increasing the expression or translocation of glucose transporters GLUT4 and GLUT2, thereby balancing blood glucose levels.</p>
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<p>Illustration of MEHHs’ phenolic acids regulating lipid metabolism pathways. The arrow (→) indicates enhancement, while the barred line (┤) signifies inhibition. Lipid metabolism, a complex process, involves the synthesis, cleavage, transport, and storage of fats in living organisms. It includes the β-oxidation of fatty acids, cholesterol production, and lipoprotein metabolism, all finely regulated by hormones such as insulin and glucagon. These are crucial for maintaining energy balance, cellular structure, and function. The dysregulation of these pathways can lead to obesity, non-alcoholic fatty liver disease, and other metabolic disorders.</p>
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<p>Depiction of how MEHHs phenolic acids regulate the insulin pathway. The arrow (→) indicates enhancement. The insulin signaling pathway plays a crucial role in regulating glucose and lipid metabolism within the body. MEHHs’ phenolic acids lower blood sugar levels by enhancing pancreatic β-cell secretion and promoting glucose uptake, glycogen synthesis, fatty acid synthesis, and storage. In the liver, muscle, and adipose tissue, these phenolic acids facilitate glucose utilization and glycogen synthesis through the activation of specific signal transduction pathways, such as the PI3K-Akt pathway, while concurrently inhibiting gluconeogenesis.</p>
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<p>Illustration of MEHHs’ phenolic acids mitigating the inflammatory response by modulating various pathways. The arrow (→) indicates enhancement, while the barred line (┤) signifies inhibition. Disruptions in glycolipid metabolism can result in the accumulation of advanced glycation end products (AGEs) and free fatty acids, which may bind directly to cellular receptors and activate inflammatory signaling cascades. In conditions of insulin resistance, insulin signaling is compromised; however, insulin levels remain elevated, promoting hyperinsulinemia, which can further stimulate the production and release of inflammatory mediators. MEHHs’ phenolic acids counteract inflammatory responses and improve glucose and lipid metabolism disorders by inhibiting signaling pathways such as TLRs, NF-κB, NLRP3, and MAPK.</p>
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<p>Illustration of MEHH phenolic acids mitigating oxidative stress by modulating various pathways. The arrow (→) indicates enhancement. Oxidative stress denotes the physiological and pathological responses of cells and tissues to the accumulation of reactive oxygen species (ROS) and reactive nitrogen radicals (RNS) stimulated by harmful internal and external environmental factors. MEHHs phenolic acids counteract oxidative stress and improve disorders in glucose and lipid metabolism by activating Nrf2, reducing ER stress, and regulating associated oxidative factors.</p>
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<p>Illustration of the primary mechanisms through which MEHHs phenolic acids modulate intestinal microbiota. The arrow (→) indicates enhancement, while the barred line (┤) signifies inhibition. SCFAs activate GPR41 and GPR43 protein-coupled receptors in intestinal epithelial cells, inducing the production of YY peptide and GLP-1, and promoting the expression of intestinal tight junction proteins such as Zo-1 and occludin. By suppressing LPS expression, MEHHs phenolic acids increase the expression of ZO-1 and GLP-1, enhance the intestinal mucosal barrier, and mitigate disorders in glucose and lipid metabolism.</p>
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77 pages, 5194 KiB  
Review
A Comprehensive Review of Moroccan Medicinal Plants for Diabetes Management
by Hanane Boutaj
Diseases 2024, 12(10), 246; https://doi.org/10.3390/diseases12100246 - 9 Oct 2024
Viewed by 728
Abstract
Moroccan flora, renowned for its diverse medicinal plant species, has long been used in traditional medicine to manage diabetes. This review synthesizes ethnobotanical surveys conducted during the last two decades. Among these plants, 10 prominent Moroccan medicinal plants are evaluated for their phytochemical [...] Read more.
Moroccan flora, renowned for its diverse medicinal plant species, has long been used in traditional medicine to manage diabetes. This review synthesizes ethnobotanical surveys conducted during the last two decades. Among these plants, 10 prominent Moroccan medicinal plants are evaluated for their phytochemical composition and antidiabetic properties through both in vitro and in vivo studies. The review encompasses a comprehensive analysis of the bioactive compounds identified in these plants, including flavonoids, phenolic acids, terpenoids, and alkaloids. Phytochemical investigations revealed a broad spectrum of secondary metabolites contributing to their therapeutic efficacy. In vitro assays demonstrated the significant inhibition of key enzymes α-amylase and α-glucosidase, while in vivo studies highlighted their potential in reducing blood glucose levels and enhancing insulin secretion. Among the ten plants, notable examples include Trigonella foenum-graecum, Nigella Sativa, and Artemisia herba-alba, each showcasing distinct mechanisms of action, such as enzymatic inhibition and the modulation of glucose metabolism pathways. This review underscores the necessity for further chemical, pharmacological, and clinical research to validate the antidiabetic efficacy of these plants and their active compounds, with a view toward their potential integration into therapeutic practices. Full article
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<p>The botanical families used for diabetes management in Morocco.</p>
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<p>The distribution of plants species families per Moroccan regions.</p>
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<p>The distribution of plants species per Moroccan regions.</p>
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<p>The distribution of plants species origin per Moroccan regions.</p>
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<p>The distribution of the percentage of different parts used for diabetes management in Morocco.</p>
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<p>The distribution of the percentage of different preparation methods used for diabetes management in Morocco.</p>
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<p>Most useful medicinal plants for diabetes management. (<bold>A</bold>) <italic>T. foenum-graecum</italic>, (<bold>B</bold>) <italic>N. oleander</italic>, (<bold>C</bold>) <italic>S. officinalis</italic>, (<bold>D</bold>) <italic>O. europeae</italic>, (<bold>E</bold>) <italic>N. sativa</italic>, and (<bold>F</bold>) <italic>M. vulgare</italic>.</p>
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<p>Chemical structures of the known natural compounds useful against diabetes.</p>
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14 pages, 2284 KiB  
Article
The Effect of Lacticaseibacillus paracasei LPC100 and Lactiplantibacillus plantarum LP140 on Bone Mineral Density in Postmenopausal Women: A Multicenter, Randomized, Placebo-Controlled Study
by Joanna Głogowska-Szeląg, Ilona Palka-Kisielowska, Wiesława Porawska, Joanna B. Bierła, Agnieszka K. Szczepankowska, Tamara Aleksandrzak-Piekarczyk and Bożena Cukrowska
J. Clin. Med. 2024, 13(19), 5977; https://doi.org/10.3390/jcm13195977 - 8 Oct 2024
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Abstract
Objectives: modulation of gut microbiota by probiotics has been proposed as a target for intervention to reduce bone mineral density (BMD) loss in the postmenopausal period. This study aims to evaluate the effect of Lacticaseibacillus (L.) paracasei LPC100 and Lactiplantibacillus (L.) plantarum LP140 [...] Read more.
Objectives: modulation of gut microbiota by probiotics has been proposed as a target for intervention to reduce bone mineral density (BMD) loss in the postmenopausal period. This study aims to evaluate the effect of Lacticaseibacillus (L.) paracasei LPC100 and Lactiplantibacillus (L.) plantarum LP140 on BMD in postmenopausal women in a multicenter, randomized, double-blind, placebo-controlled trial. Methods: the primary outcome was the change in T-score of the lumbar spine measured by dual-energy X-ray absorptiometry assessed after twelve-month probiotic supplementation. Secondary outcomes included changes in serological markers of inflammation and calcium–phosphate metabolism, body mass index, gastrointestinal symptoms, and satisfaction with the intervention. Results: a decrease in T-score indicating the progressive bone demineralization reached a statistically significant difference in the placebo group (from mean values of 0.06 ± 1.04 to −0.28 ± 1.12, p = 0.041) but not in the probiotic group (0.19 ± 0.99 and −0.08 ± 1.05, respectively, p = 0.125) with a p-value = 0.089 between the groups. No significant differences were found in secondary outcomes with the exception of vitamin D concentration and a significant reduction in some gastrointestinal symptoms in the probiotic group. A significant decrease in vitamin D level was observed only in the placebo group (p = 0.014). Probiotics were safe and well tolerated. Conclusions: this study suggests that the oral administration of L. paracasei LPC100 and L. plantarum LP140 may be a viable strategy to prevent BMD loss and vitamin D deficiency in postmenopausal women, but further research is necessary to confirm clinical benefits and to know the mechanism of action [ClinicalTrial.gov NCT06375668]. Full article
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<p>The study flowchart.</p>
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<p>The effect of probiotic intervention on selected serological markers. * <span class="html-italic">p</span> &lt; 0.05 in comparison with baseline levels within the group.</p>
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<p>The effect of intervention on BMI and gastrointestinal symptoms. Results for BMI, number of stools per day, and Bristol Stool Scale are presented as mean ± standard deviation. The remaining parameters are presented as a percentage of patients reporting each symptom. * <span class="html-italic">p</span> &lt; 0.05 compared to baseline within the group. # <span class="html-italic">p</span> &lt; 0.05 between probiotic and placebo groups.</p>
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<p>Intervention satisfaction assessment using the Treatment Satisfaction Questionnaire (TSQ). Results are presented as mean ± standard deviation. Satisfaction was assessed after 2 (2 m), 6 (6 m), 10 (10 m), and 12 (12 m) months. Subjects answered 6 questions (Q1–Q6) using a 5-point scale. The <span class="html-italic">Y</span>-axis presents scores.</p>
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<p>Percentage of patients without adverse events during the 12-month intervention.</p>
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18 pages, 921 KiB  
Review
Oncological Aspects of Lysosomal Storage Diseases
by Agnieszka Ługowska
Cells 2024, 13(19), 1664; https://doi.org/10.3390/cells13191664 - 8 Oct 2024
Viewed by 401
Abstract
Lysosomal storage diseases (LSDs) are caused by the deficient activity of a lysosomal hydrolase or the lack of a functional membrane protein, transporter, activator, or other protein. Lysosomal enzymes break down macromolecular compounds, which contribute to metabolic homeostasis. Stored, undegraded materials have multiple [...] Read more.
Lysosomal storage diseases (LSDs) are caused by the deficient activity of a lysosomal hydrolase or the lack of a functional membrane protein, transporter, activator, or other protein. Lysosomal enzymes break down macromolecular compounds, which contribute to metabolic homeostasis. Stored, undegraded materials have multiple effects on cells that lead to the activation of autophagy and apoptosis, including the toxic effects of lyso-lipids, the disruption of intracellular Ca2+ ion homeostasis, the secondary storage of macromolecular compounds, the activation of signal transduction, apoptosis, inflammatory processes, deficiencies of intermediate compounds, and many other pathways. Clinical observations have shown that carriers of potentially pathogenic variants in LSD-associated genes and patients affected with some LSDs are at a higher risk of cancer, although the results of studies on the frequency of oncological diseases in LSD patients are controversial. Cancer is found in individuals affected with Gaucher disease, Fabry disease, Niemann-Pick type A and B diseases, alfa-mannosidosis, and sialidosis. Increased cancer prevalence has also been reported in carriers of a potentially pathogenic variant of an LSD gene, namely CLN3, SGSH, GUSB, NEU1, and, to a lesser extent, in other genes. In this review, LSDs in which oncological events can be observed are described. Full article
(This article belongs to the Collection The Lysosome in Cancer: From Pathogenesis to Therapy)
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<p>Bioactive properties of sphingolipids (GlcCer and its derivatives). GlcCer—glucocerebroside (glucosylceramide); GCase—glucocerebrosidase (lysosomal beta-glucosidase deficient in Gaucher disease); Glu—glucose; Cer—ceramide; Cer-1-P—ceramide-1-phosphate; S-1-P—sphingosine-1-phosphate.</p>
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<p>Consequences of elevated <span class="html-italic">MAN2B1</span> gene expression in glioma cells. TIICs—tumor-infiltrating immune cells.</p>
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<p>Possible correlation between renal cell carcinoma and sphingolipids stored in Fabry disease. Gb3—globotriaosylceramide; IF-6—interleukin 6; TNF-α—tumor necrosis factor-α; VHL/HIF pathway—von Hippel-Lindau/hypoxia-inducible factor 1α; RCC—renal cell carcinoma; lysoGb3—globotriaosylsphingosine; TGF-β1—transforming growth factor-β1; MIF—macrophage migration inhibitory factor; FD—Fabry disease.</p>
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