Nothing Special   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (841)

Search Parameters:
Keywords = polyketide

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
12 pages, 4407 KiB  
Article
New PKS/NRPS Tenuazamines A–H from the Endophytic Fungus Alternaria alternata FL7 Isolated from Huperzia serrata
by Hao Zhang, Zhibin Zhang, Yiwen Xiao, Wen Wang, Boliang Gao, Yuhao Xie, Jiahao Xie, Xinhua Gao and Du Zhu
J. Fungi 2024, 10(12), 809; https://doi.org/10.3390/jof10120809 - 21 Nov 2024
Viewed by 251
Abstract
In this paper, we present a novel class of hybrid polyketides, tenuazamines A–H (18), which exhibit a unique tautomeric equilibrium from Alternaria alternata FL7. The elucidation of the structures was achieved through a diverse combination of NMR, HR-ESIMS, and [...] Read more.
In this paper, we present a novel class of hybrid polyketides, tenuazamines A–H (18), which exhibit a unique tautomeric equilibrium from Alternaria alternata FL7. The elucidation of the structures was achieved through a diverse combination of NMR, HR-ESIMS, and ECD methods, with a focus on extensive spectroscopic data analysis. Notably, compounds 1, 4, 89 exhibited potent toxic effects on the growth of Arabidopsis thaliana. This research expands the structural diversity of tenuazonic acid compounds derived from endophytic fungi and provides potential hit compounds for the development of herbicides. Full article
Show Figures

Figure 1

Figure 1
<p>Chemical structures of <b>1</b>–<b>8</b> derived from <span class="html-italic">A. alternata</span> FL7.</p>
Full article ">Figure 2
<p>The key COSY (bond lines) and HMBC (blue arrows) correlations of compounds <b>1</b>–<b>8</b>.</p>
Full article ">Figure 3
<p>Experimental and calculated ECD spectra of compounds <b>1</b>–<b>2</b>.</p>
Full article ">Figure 4
<p>Toxicity of compounds <b>1</b>–<b>9</b> to <span class="html-italic">Arabidopsis thaliana</span>. (Note. the Chinese characters in the picture means “compound”).</p>
Full article ">
34 pages, 6063 KiB  
Article
Exploring the Genome of the Endophytic Fungus Botrytis deweyae: Prediction of Novel Secondary Metabolites Gene Clusters: Terpenes and Polyketides
by Victor Coca-Ruiz, Josefina Aleu, Carlos Garrido and Isidro G. Collado
Agronomy 2024, 14(11), 2747; https://doi.org/10.3390/agronomy14112747 - 20 Nov 2024
Viewed by 227
Abstract
Fungi have played a pivotal role in human history, from the dangers of fungal toxins to the revolutionary discovery of penicillin. Fungal secondary metabolites (SMs), such as polyketides (PKs) and terpenes, have attracted considerable interest due to their diverse biological activities. Botrytis deweyae [...] Read more.
Fungi have played a pivotal role in human history, from the dangers of fungal toxins to the revolutionary discovery of penicillin. Fungal secondary metabolites (SMs), such as polyketides (PKs) and terpenes, have attracted considerable interest due to their diverse biological activities. Botrytis deweyae, an endophytic fungus, exhibits behaviors that are notably distinct from those of its necrotrophic relatives within the genus Botrytis. This study explores the importance of terpenes and PK gene clusters and their conservation between species. In addition, new putative biosynthetic gene clusters corresponding to those families were identified. Consequently, the new PKS BdPKS22-26 were also identified in other Botrytis species and other fungi. In addition, those new gene clusters identified in this work show differences in the degree of conservation and are phylogenetically closely related to some of the 21 PKSs previously described in the reference strain Botrytis cinerea B05.10. Moreover, a new gene cluster related to terpenes in B. deweyae B1 and B. cinerea B05.10 was also identified that had never been detected before. This new gene cluster is well conserved among other Botrytis species in many phylogenetically distant fungal lineages. Understanding the genetic basis and conservation of these putative biosynthetic gene clusters sheds light on the metabolic potential and ecological roles of B. deweyae and related fungal species. Full article
Show Figures

Figure 1

Figure 1
<p>Distribution of different secondary metabolite gene clusters identified in <span class="html-italic">B. deweyae</span> and <span class="html-italic">B. cinerea</span>.</p>
Full article ">Figure 2
<p>Phylogenetic tree of the amino acid sequences of terpenes from <span class="html-italic">B. deweyae</span> B1 together with the amino acid sequences from <span class="html-italic">B. cinerea</span> B05.10 that contains the IPR008949 domain. The phylogenetic tree was inferred using the maximum likelihood method via MEGA 11 software and bootstrap values from 500 trials are indicated at each branch node.</p>
Full article ">Figure 3
<p>Gene cluster predicted by the AntiSMASH tool for the unannotated terpene EAE08_008016 in <span class="html-italic">B. deweyae</span> B1 (<a href="#agronomy-14-02747-t001" class="html-table">Table 1</a>).</p>
Full article ">Figure 4
<p>Phylogenetic tree of XP_038807933 protein from <span class="html-italic">B. deweyae</span> B1 and homologous protein sequences of other fungal species. The phylogenetic tree was inferred using the maximum likelihood method via MEGA 11 software, with bootstrap values from 500 trials indicated at each branch node. Protein sequences were selected after running similarity search by BlastP using XP_038807933 as query sequence, excluding the <span class="html-italic">Botrytis</span> and <span class="html-italic">Botryotinia</span> taxids (33196 and 40558, respectively), and filtering the results based on percent identity &gt; 50%, coverage &gt; 70%, and bit-score &gt; 50. The top 55 hits were retrieved for sequence alignment and phylogenetic analysis. The NCBI accession number of each sequence is shown. Actin (CAA04009.1) of <span class="html-italic">B. cinerea</span> was used as outgroup. Different clades and subclades are indicated by colored branches (red, green, or violet).</p>
Full article ">Figure 5
<p>Representation of the gene cluster from BdPKS22-26 in <span class="html-italic">B. deweyae</span> predicted by the antiSMASH fungal version tool.</p>
Full article ">Figure 6
<p>Phylogenetic tree of all the <span class="html-italic">B. cinerea</span> genes that showed polyketide domain together with the new putative polyketide synthases identified in <span class="html-italic">B. deweyae</span> B1. The evolutionary history was inferred using the maximum likelihood [<a href="#B60-agronomy-14-02747" class="html-bibr">60</a>]. The bootstrap consensus tree inferred from 500 replicates [<a href="#B60-agronomy-14-02747" class="html-bibr">60</a>] is taken to represent the evolutionary history of the taxa analyzed [<a href="#B60-agronomy-14-02747" class="html-bibr">60</a>]. Branches corresponding to partitions reproduced in less than 50% bootstrap replicates are collapsed. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1000 replicates) are shown next to the branches [<a href="#B60-agronomy-14-02747" class="html-bibr">60</a>]. The evolutionary distances were computed using the Poisson correction method [<a href="#B60-agronomy-14-02747" class="html-bibr">60</a>] and are in the units of the number of amino acid substitutions per site. This analysis included 27 amino acid sequences where in the phylogenetic tree were identified in yellow the polyketide synthases previously described in <span class="html-italic">B. cinerea</span>, in blue the polyketide synthases of <span class="html-italic">B. deweyae</span> and in green the new polyketide synthases identified in <span class="html-italic">B. cinerea</span>. All ambiguous positions were removed for each sequence pair (pairwise deletion option). There were a total of 4970 positions in the final dataset. Evolutionary analyses were conducted in MEGA 11 [<a href="#B61-agronomy-14-02747" class="html-bibr">61</a>].</p>
Full article ">Figure 7
<p>Phylogenetic tree of XP_038813652.1 protein (BdPKS22) from <span class="html-italic">B. deweyae</span> and homologous protein sequences from other fungal species. The phylogenetic tree was inferred using the maximum likelihood method via MEGA 11 software, and bootstrap values from 1000 trials are indicated at each branch node. Protein sequences were selected after running a similarity search by BLASTP using XP_038813652.1 as the query sequence, excluding the <span class="html-italic">Botrytis</span> and <span class="html-italic">Botryotinia</span> taxids (33196 and 40558, respectively), and filtering the results based on percent identity &gt; 50%, coverage &gt; 70%, and bit-score &gt; 50. The top 18 hits were retrieved for sequence alignment and phylogenetic analysis. NCBI accession numbers of each sequence are shown. Actin (CAA04009.1) of <span class="html-italic">B. cinerea</span> was used as the outgroup. Taxonomic distribution is highlighted by different colors: <span class="html-italic">Sordariomycetes</span> (blue), <span class="html-italic">Dothideomycetes</span> (red), and <span class="html-italic">Leotiomycetes</span> (violet).</p>
Full article ">Figure 8
<p>Phylogenetic tree of XP_038807018.1 protein from <span class="html-italic">B. deweyae</span> and homologous protein sequences from other fungal species. The phylogenetic tree was inferred using the maximum likelihood method via MEGA 11 software, and bootstrap values from 1000 trials are indicated at each branch node. Protein sequences were selected after running similarity search by BLASTP using XP_038807018.1 as query sequence, excluding the <span class="html-italic">Botrytis</span> and <span class="html-italic">Botryotinia</span> taxids (33196 and 40558, respectively), and filtering the results based on percent identity &gt; 50%, coverage &gt; 70%, and bit-score &gt; 50. The top 51 hits were retrieved for sequence alignment and phylogenetic analysis. NCBI accession number of each sequence is shown. Actin (CAA04009.1) of <span class="html-italic">B. cinerea</span> was used as outgroup. Different clades and subclades are delimited by color of the branches: <span class="html-italic">Sordariomycetes</span> (blue), <span class="html-italic">Dothideomycetes</span> (red), <span class="html-italic">Leotiomycetes</span> (violet).</p>
Full article ">Figure 9
<p>Phylogenetic tree of XP_038806877.1 protein (BdPKS24) from <span class="html-italic">B. deweyae</span> and homologous protein sequences from other fungal species. The phylogenetic tree was inferred using the maximum likelihood method via MEGA 11 software, and bootstrap values from 500 trials are indicated at each branch node. Protein sequences were selected after running a similarity search by BLASTP using XP_038806877.1 as the query sequence, excluding the <span class="html-italic">Botrytis</span> and <span class="html-italic">Botryotinia</span> taxids (33196 and 40558, respectively), and filtering the results based on percent identity &gt; 50%, coverage &gt; 70%, and bit-score &gt; 50. The top 4 hits were retrieved for sequence alignment and phylogenetic analysis. NCBI accession numbers of each sequence are shown. Actin (CAA04009.1) of <span class="html-italic">B. cinerea</span> was used as the outgroup. Taxonomic distribution is highlighted by different colors: <span class="html-italic">Sordariomycetes</span> (blue) and <span class="html-italic">Leotiomycetes</span> (violet).</p>
Full article ">Figure 10
<p>Phylogenetic tree of XP_038805042.1 protein (BdPKS25) from <span class="html-italic">B. deweyae</span> and homologous protein sequences from other fungal species. The phylogenetic tree was inferred using the maximum likelihood method via MEGA 11 software, and bootstrap values from 1000 trials are indicated at each branch node. Protein sequences were selected after running a similarity search by BLASTP using XP_038805042.1 as the query sequence, excluding the <span class="html-italic">Botrytis</span> and <span class="html-italic">Botryotinia</span> taxids (33196 and 40558, respectively), and filtering the results based on percent identity &gt; 50%, coverage &gt; 70%, and bit-score &gt; 50. The top 25 hits were retrieved for sequence alignment and phylogenetic analysis. NCBI accession numbers of each sequence are shown. Actin (CAA04009.1) of <span class="html-italic">B. cinerea</span> was used as the outgroup. Taxonomic distribution is highlighted by different colors: <span class="html-italic">Sordariomycetes</span> (blue) and <span class="html-italic">Leotiomycetes</span> (violet) and <span class="html-italic">Dothideomycetes</span> (red).</p>
Full article ">Figure 11
<p>Phylogenetic tree of XP_038805079.1 protein (BdPKS26) from <span class="html-italic">B. deweyae</span> and homologous protein sequences from other fungal species. The phylogenetic tree was inferred using the maximum likelihood method via MEGA 11 software, and bootstrap values from 500 trials are indicated at each branch node. Protein sequences were selected after running a similarity search by BLASTP using XP_038805079.1 as the query sequence, excluding the <span class="html-italic">Botrytis</span> and <span class="html-italic">Botryotinia</span> taxids (33196 and 40558, respectively), and filtering the results based on percent identity &gt; 50%, coverage &gt; 70%, and bit-score &gt; 50. The top 55 hits were retrieved for sequence alignment and phylogenetic analysis. NCBI accession numbers of each sequence are shown. Actin (CAA04009.1) of <span class="html-italic">B. cinerea</span> was used as the outgroup. Taxonomic distribution is highlighted by different colors: <span class="html-italic">Sordariomycetes</span> (blue) and <span class="html-italic">Leotiomycetes</span> (violet) and <span class="html-italic">Dothideomycetes</span> (red).</p>
Full article ">
17 pages, 5375 KiB  
Article
Streptomyces hygroscopicus and rapamycinicus Evaluated from a U.S. Marine Sanctuary: Biosynthetic Gene Clusters Encode Antibiotic and Chemotherapeutic Secondary Metabolites
by Hannah R. Flaherty, Semra A. Aytur and John P. Bucci
J. Mar. Sci. Eng. 2024, 12(11), 2076; https://doi.org/10.3390/jmse12112076 - 17 Nov 2024
Viewed by 689
Abstract
Cancer remains a leading cause of death worldwide. Also threatening the public is the emergence of antibiotic resistance to existing medicines. Despite the challenge to produce viable natural products to market, there continues to be a need within public health to provide new [...] Read more.
Cancer remains a leading cause of death worldwide. Also threatening the public is the emergence of antibiotic resistance to existing medicines. Despite the challenge to produce viable natural products to market, there continues to be a need within public health to provide new chemotherapeutic drugs such as those exhibiting cytotoxicity and tumor cell growth-inhibitory properties. As marine genomic research advances, it is apparent that marine-derived sediment harbors uniquely potent bioactive compounds compared to their terrestrial counterparts. The Streptomyces genus in particular produces more than 30% of all secondary metabolites currently approved for human health, thus harboring unexplored reservoirs of chemotherapeutic and antibiotic agents to combat emerging disease. The present study identifies the presence of Streptomyces hygroscopicus and rapamycinicus in environmental sediment at locations within the U.S. Stellwagen Bank National Marine Sanctuary (SBNMS) from 2017 to 2022. Sequencing and bioinformatics methods catalogued biosynthetic gene clusters (BGCs) that drive cytotoxic and antibiotic biochemical processes in samples collected from sites permittable and protected to fishing activity. Poisson regression models confirmed that Sites 1 and 3 had significantly higher occurrences of rapamycinicus than other sites (p < 0.01). Poisson regression models confirmed that Sites 1, 2 and 3 had significantly higher occurrence for Streptomyces hygroscopicus across sites (p < 0.05). Interestingly, permitted fishing sites showed a greater prevalence of both species. Statistical analyses showed a significant difference in aligned hits with polyketide synthases (PKSs) and non-ribosomal peptide synthetases (NRPSs) by site and between species with hygroscopicus showing a greater quantity than rapamycinicus among Streptomyces spp. (p < 0.05; F = 4.7 > F crit). Full article
(This article belongs to the Section Marine Biology)
Show Figures

Figure 1

Figure 1
<p>Study site map (1–9) of the Gulf of Maine within the Massachusetts Bay area. Included are the borders of the Stellwagen Bank National Marine Sanctuary (black) with sample sites labeled with red (open to fishing) and black (closed to fishing) circles. The Western Gulf of Maine Closure area is marked with dashed markings. Note: Site 5 was retired in 2019 and is not shown on the map.</p>
Full article ">Figure 2
<p>Metagenomic sequenced hits were quantified and matched by <span class="html-italic">Streptomyces</span> species sampled at locations within the SBNMS.</p>
Full article ">Figure 3
<p>Metagenomic sequences (hit-counts) aligned with <span class="html-italic">Streptomyces hygroscopicus</span> and <span class="html-italic">rapamycinicus</span> were quantified according to the UniPRot output.</p>
Full article ">Figure 4
<p>Contiguous hits for <span class="html-italic">S. hygroscopicus</span>, <span class="html-italic">S. rapamycinicus,</span> and all <span class="html-italic">Streptomyces</span> spp. corresponding to core BGCs and predicted by AntiSMASH<sup>™</sup> analysis. Each sampling site is expressed for all years (8, 9 n/a). The Poisson data analysis was generated using SAS software, Version 9.4, SAS Institute Inc., Cary, NC, USA.</p>
Full article ">Figure 5
<p>The number of secondary metabolites were quantified using the AntiSMASH<sup>™</sup> bioinformatics program predictions. All sample collection years and site locations were combined in this diagram (<a href="#app1-jmse-12-02076" class="html-app">Table S2</a>).</p>
Full article ">Figure 6
<p>Map of study sites (1–9 black numbers) show total number of secondary metabolites identified in relation to surface to sediment depth (meters) as a heatmap corresponding to <span class="html-italic">S. hygroscopicus</span> and <span class="html-italic">S. rapamycinicus</span> by site. Spherical symbols: sparse to dense scale 0–100. Site 5 was retired in 2019 and is not shown on the map.</p>
Full article ">Figure 7
<p>Diagram of an <span class="html-italic">S. hygroscopicus</span> spp. (NCBI accession number NC_020895.1) identified by antiSMASH<sup>™</sup> in study samples depicting prevalence of PKS and NRPS regions within BGGs aligned. This unique protein sequence record was identified in approximately 18% of all <span class="html-italic">S. hygroscopicus</span> and <span class="html-italic">S. rapamycinicus</span> contig samples analyzed.</p>
Full article ">Figure 8
<p>Identified secondary metabolite region of BGC search according to AntiSMASH output of multiple <span class="html-italic">S. hygroscopicus</span> strains (NZ_CP018627–Region 13; Location 1,553,101–1,683,344 nt). The select region within shows core BGCs (dark red) that encode for cytotoxic compounds such as Nigericin related and Type I Polyketides.</p>
Full article ">
23 pages, 6586 KiB  
Article
Studies Regarding Antimicrobial Properties of Some Microbial Polyketides Derived from Monascus Strains
by Daniela Albisoru, Nicoleta Radu, Lucia Camelia Pirvu, Amalia Stefaniu, Narcisa Băbeanu, Rusandica Stoica and Dragos Paul Mihai
Antibiotics 2024, 13(11), 1092; https://doi.org/10.3390/antibiotics13111092 - 16 Nov 2024
Viewed by 649
Abstract
Finding new molecules to prevent the growth of antimicrobial resistance is a hot topic for scientists worldwide. It has been reported that some raw bioproducts containing Monascus polyketides have antimicrobial activities, but extensive studies on this effect have not been conducted. In this [...] Read more.
Finding new molecules to prevent the growth of antimicrobial resistance is a hot topic for scientists worldwide. It has been reported that some raw bioproducts containing Monascus polyketides have antimicrobial activities, but extensive studies on this effect have not been conducted. In this context, our studies aimed to evaluate the antimicrobial properties of six raw bioproducts containing three classes of microbial polyketides biosynthesized by three Monascus strains through solid-state biosynthesis. As a methodology, we performed in silico predictions using programs such as PyMOL v3.0.4 and employed ESI-MS techniques to provide evidence of the presence of the six studied compounds in our bioproducts. The results obtained in silico were validated through in vitro studies using the Kirby-Bauer diffusion method on bacteria and fungi. The test performed in silico showed that Monascorubramine has the highest affinity for both Gram-positive and Gram-negative bacteria, followed by yellow polyketides such as Ankaflavin and Monascin. The estimated pharmacokinetic parameters indicated high gastrointestinal absorption and the potential to cross the blood-brain barrier for all studied compounds. However, the compounds also inhibit most enzymes involved in drug metabolism, presenting some level of toxicity. The best in vitro results were obtained for S. aureus, with an extract containing yellow Monascus polyketides. Predictions made for E. coli were validated in vitro for P. aeruginosa, S. enterica, and S. marcescens, as well as for fungi. Significant antibacterial properties were observed during this study for C. albicans, S. aureus, and fungal dermatophytes for crude bioproducts containing Monascus polyketides. In conclusion, the antimicrobial properties of Monascus polyketides were validated both in silico and in vitro. However, due to their potential toxicity, these bioproducts would be safer to use as topical formulations. Full article
Show Figures

Figure 1

Figure 1
<p>Experimental study design.</p>
Full article ">Figure 2
<p>Molecular docking validation—superposition of predicted poses (pink) of co-crystallized inhibitors on initial conformations (green): (<b>a</b>) trimethoprim in saDHFR binding site (PDB ID: 2w9s, RMSD 0.6535 Å); (<b>b</b>) trimethoprim in ecDHFR binding site (PDB ID: 7mym, RMSD 0.3521 Å); (<b>c</b>) UCP11E in caDHFR binding site (PDB ID: 4hoe, RMSD 0.4389 Å); (<b>d</b>) trimethoprim in hDHFR binding site (PDB ID: 2w3a, RMSD 0.9559 Å).</p>
Full article ">Figure 3
<p>Predicted binding poses of Monascorubramine in DHFR active sites. (<b>a</b>) saDHFR; (<b>b</b>) ecDHFR; (<b>c</b>) caDHFR; (<b>d</b>) hDHFR.</p>
Full article ">Figure 4
<p>2D diagrams of predicted molecular interactions between Monascorubramine and active sites of DHFR homologues. (<b>a</b>) saDHFR; (<b>b</b>) ecDHFR; (<b>c</b>) caDHFR; (<b>d</b>) hDHFR.</p>
Full article ">Figure 5
<p>“Boiled egg” diagram illustrating the distribution of the investigated compounds in the chemical space of molecules that are absorbed in the gastrointestinal (GI) tract or passively permeate the blood–brain barrier (BBB) based on calculated WlogP (octanol/water partition coefficient) and TPSA (topological polar surface area) values. Molecules located in the “egg yolk” are predicted to passively permeate through the BBB. Molecules located in the white area are predicted to be passively absorbed in the GI tract.</p>
Full article ">Figure 6
<p>ESI-MS analysis of a total alcoholic extract of the following: (<b>a</b>) <span class="html-italic">Monascus purpureus</span>; (<b>b</b>) <span class="html-italic">Monascus ruber</span>; (<b>c</b>) <span class="html-italic">Monascus</span> sp. 3 <span class="html-italic">(Monascus ruber</span>; highly productive).</p>
Full article ">Figure 7
<p>Antibacterial properties of polyketides obtained from Monascus-derived bioproducts: (<b>a</b>) antibacterial properties for <span class="html-italic">S. aureus</span> (yellow polyketides exhibit the best activities); (<b>b</b>) antibacterial properties for <span class="html-italic">S. aureus</span> MRSA (yellow polyketides exhibit moderate activities); (<b>c</b>) antibacterial properties for <span class="html-italic">S. marcescens</span> (red polyketides exhibit the best activities); (<b>d</b>) antibacterial properties for <span class="html-italic">P. aeruginosa</span> (red polyketides exhibit moderate antimicrobial activities); (<b>e</b>) antibacterial properties for <span class="html-italic">S. enterica</span> (red polyketides exhibit local-moderate antimicrobial activities).</p>
Full article ">Figure 7 Cont.
<p>Antibacterial properties of polyketides obtained from Monascus-derived bioproducts: (<b>a</b>) antibacterial properties for <span class="html-italic">S. aureus</span> (yellow polyketides exhibit the best activities); (<b>b</b>) antibacterial properties for <span class="html-italic">S. aureus</span> MRSA (yellow polyketides exhibit moderate activities); (<b>c</b>) antibacterial properties for <span class="html-italic">S. marcescens</span> (red polyketides exhibit the best activities); (<b>d</b>) antibacterial properties for <span class="html-italic">P. aeruginosa</span> (red polyketides exhibit moderate antimicrobial activities); (<b>e</b>) antibacterial properties for <span class="html-italic">S. enterica</span> (red polyketides exhibit local-moderate antimicrobial activities).</p>
Full article ">Figure 8
<p>Antifungal properties of polyketides obtained from Monascus-derived bioproducts for the following: (<b>a</b>) <span class="html-italic">Candida albicans</span>; (<b>b</b>) <span class="html-italic">S. brevicaulis</span>, (<b>c</b>) <span class="html-italic">M. gypseum</span>; (<b>d</b>) <span class="html-italic">T. mentagrophytes</span>.</p>
Full article ">Figure 9
<p>Flow diagram used to obtain enhanced extracts of yellow, orange, and red polyketides: (<b>a</b>) Solid-state biosynthesis of <span class="html-italic">Monascus</span> bioproducts (RYR); (<b>b</b>) Sample preparation of <span class="html-italic">Monascus</span> bioproducts for analysis; (<b>c</b>) Obtaining <span class="html-italic">Monascus</span> extract with yellow polyketides; (<b>d</b>) Obtaining <span class="html-italic">Monascus</span> extract with orange polyketides; (<b>e</b>) Obtaining <span class="html-italic">Monascus</span> extract with red polyketides.</p>
Full article ">Figure 9 Cont.
<p>Flow diagram used to obtain enhanced extracts of yellow, orange, and red polyketides: (<b>a</b>) Solid-state biosynthesis of <span class="html-italic">Monascus</span> bioproducts (RYR); (<b>b</b>) Sample preparation of <span class="html-italic">Monascus</span> bioproducts for analysis; (<b>c</b>) Obtaining <span class="html-italic">Monascus</span> extract with yellow polyketides; (<b>d</b>) Obtaining <span class="html-italic">Monascus</span> extract with orange polyketides; (<b>e</b>) Obtaining <span class="html-italic">Monascus</span> extract with red polyketides.</p>
Full article ">
15 pages, 5974 KiB  
Article
Biological Characteristics of a Novel Bibenzyl Synthase (DoBS1) Gene from Dendrobium officinale Catalyzing Dihydroresveratrol Synthesis
by Shao-Guo Zhou, Ke Zhong, Feng-Xia Yan, Fan Tian, Chang-Sha Luo, Hang-Cheng Yu, Zai-Qi Luo and Xi-Min Zhang
Molecules 2024, 29(22), 5320; https://doi.org/10.3390/molecules29225320 - 12 Nov 2024
Viewed by 408
Abstract
Bibenzyl compounds are one of the most important bioactive components of natural medicine. However, Dendrobium officinale as a traditional herbal medicine is rich in bibenzyl compounds and performs functions such as acting as an antioxidant, inhibiting cancer cell growth, and assisting in neuro-protection. [...] Read more.
Bibenzyl compounds are one of the most important bioactive components of natural medicine. However, Dendrobium officinale as a traditional herbal medicine is rich in bibenzyl compounds and performs functions such as acting as an antioxidant, inhibiting cancer cell growth, and assisting in neuro-protection. The biosynthesis of bibenzyl products is regulated by bibenzyl synthase (BBS). In this study, we have cloned the cDNA gene of the bibenzyl synthase (DoBS1) from D. officinale using PCR with degenerate primers, and we have identified a novel type III polyketide synthase (PKS) gene by phylogenetic analyses. In a series of perfect experiments, DoBS1 was expressed in Escherichia coli, purified and some catalytic properties of the recombinant protein were investigated. The molecular weight of the recombinant protein was verified to be approximately 42.7 kDa. An enzyme activity analysis indicated that the recombinant DoBS1-HisTag protein was capable of using 4-coumaryol-CoA and 3 malonyl-CoA as substrates for dihydroresveratrol (DHR) in vitro. The Vmax and Km of the recombinant protein for DHR were 3.57 ± 0.23 nmol·min−1·mg−1 and 0.30 ± 0.08 mmol, respectively. The present study provides further insights into the catalytic mechanism of the active site in the biosynthetic pathway for the catalytic production of dihydroresveratrol by bibenzylase in D. officinale. The results can be used to optimize a novel biosynthetic pathway for the industrial synthesis of DHR. Full article
Show Figures

Figure 1

Figure 1
<p>The proposed biosynthetic pathway for bibenzyls. PAL: phenylalanine ammonia-lyase; C4H: cinnamic-4-hydroxylase; 4CL: 4-coumaryl-CoA ligase; DBR: double-bond reductases; BBS: bibenzyl synthase.</p>
Full article ">Figure 2
<p>Amino acid sequence comparison of six type III PKSs of plant origin. A multiple sequence alignment was calculated with the DNAMAN package. Black shading indicates the homology of amino acids, while red and blue shading indicates amino acids with different similarity. The conserved catalytic residues in plant type III PKS (Cys164, His304 and Asn337, DoBS1 numbers) are represented by diamonds. Additionally, the highly conserved sequence G373FGPG (DoBS1 number) is indicated by red boxes.</p>
Full article ">Figure 3
<p>The phylogenetic relationship of type III PKS. The numbers at the nodes represent the bootstrap. Source data are provided in the <a href="#app1-molecules-29-05320" class="html-app">Supplementary Material</a> titled “Construct Phylogenetic Tree Source Files”.</p>
Full article ">Figure 4
<p>Figure of the pET-28a-DoBS1 recombinant plasmid construction and protein purification results. (<b>a</b>) Electrophoresis pattern of double-enzyme-digested recombinant plasmid. M: DNA marker (250–12,000 bp); Lane 1: results of double digestion of XbaI-XhoI empty vector; Lane 2: Results of double digestion of the pET-28a-DoBS1 recombinant plasmid. (<b>b</b>) DoBS1 was purified with the Ni<sup>2+</sup>-NTA column. M: 180 kDa Prestained Protein Marker; Lane 1: supernatant crude protein; Lane 2: the effluent obtained after incubating the supernatant crude protein with the equilibrated column packing for 1 h; Lane 3: equilibrate with 20 mM imidazole; Lane 4: washed with 50 mM imidazole; Lane 5: elution with 500 mM imidazole.</p>
Full article ">Figure 5
<p>The results of the target protein verification. (<b>a</b>) Western blot analysis of the final puri-fied protein. M: 180 kDa predicted protein marker; Lane 1: Target protein. (<b>b</b>) The coverage of the identified peptides on the protein. (<b>c</b>) MS/MS analysis of peptide ion 1 (ATT-GEGLEWGVLFGFGPGLTVETVVLR). (<b>d</b>) MS/MS analysis of peptide ion 2 (NVEKCLEE-AFTPFGISDWNSIFWVPHPGGR).</p>
Full article ">Figure 6
<p>Analysis of the enzymatic reaction products of the DoBS1 protein. (<b>a</b>) HPLC chromatograms of the catalytic reaction standard mix. (<b>b</b>) Blank group. (<b>c</b>) HPLC chromatogram of the reaction product.</p>
Full article ">Figure 7
<p>Kinetic analysis of DoBS1 toward p-coumaroyl-CoA. The Michaelis-Menten equation, expressed as V = Vmax[S]/(Km + [S]). The calculated values for Vmax and Km of the DoBS1 pro-tein were obtained. An adjusted R-squared value of 0.99787 indicates an excellent fit of the curve to the observed value.</p>
Full article ">
38 pages, 5296 KiB  
Review
Recent Updates on the Secondary Metabolites from Fusarium Fungi and Their Biological Activities (Covering 2019 to 2024)
by Prosper Amuzu, Xiaoqian Pan, Xuwen Hou, Jiahang Sun, Muhammad Abubakar Jakada, Eromosele Odigie, Dan Xu, Daowan Lai and Ligang Zhou
J. Fungi 2024, 10(11), 778; https://doi.org/10.3390/jof10110778 - 9 Nov 2024
Viewed by 487
Abstract
Fusarium species are commonly found in soil, water, plants, and animals. A variety of secondary metabolites with multiple biological activities have been recently isolated from Fusarium species, making Fusarium fungi a treasure trove of bioactive compounds. This mini-review comprehensively highlights the newly isolated [...] Read more.
Fusarium species are commonly found in soil, water, plants, and animals. A variety of secondary metabolites with multiple biological activities have been recently isolated from Fusarium species, making Fusarium fungi a treasure trove of bioactive compounds. This mini-review comprehensively highlights the newly isolated secondary metabolites produced by Fusarium species and their various biological activities reported from 2019 to October 2024. About 276 novel metabolites were revealed from at least 21 Fusarium species in this period. The main metabolites were nitrogen-containing compounds, polyketides, terpenoids, steroids, and phenolics. The Fusarium species mostly belonged to plant endophytic, plant pathogenic, soil-derived, and marine-derived fungi. The metabolites mainly displayed antibacterial, antifungal, phytotoxic, antimalarial, anti-inflammatory, and cytotoxic activities, suggesting their medicinal and agricultural applications. This mini-review aims to increase the diversity of Fusarium metabolites and their biological activities in order to accelerate their development and applications. Full article
(This article belongs to the Section Fungal Cell Biology, Metabolism and Physiology)
Show Figures

Figure 1

Figure 1
<p>Structures of the amines (<b>1</b>–<b>4</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 2
<p>Structures of the amides (<b>5</b>–<b>35</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 2 Cont.
<p>Structures of the amides (<b>5</b>–<b>35</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 3
<p>Structures of the cyclic peptides (<b>36</b>–<b>51</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 3 Cont.
<p>Structures of the cyclic peptides (<b>36</b>–<b>51</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 4
<p>Structures of the pyridines (<b>52</b>–<b>58</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 5
<p>Structures of the pyridines (<b>59</b>–<b>62</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 6
<p>Structures of the indole analogs (<b>63</b>–<b>77</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 7
<p>Structures of the imidazole analogs (<b>78</b>–<b>94</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 8
<p>Structures of the other nitrogen-containing metabolites (<b>95</b>–<b>97</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 9
<p>Structures of the α-pyrones (<b>98</b>–<b>122</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 9 Cont.
<p>Structures of the α-pyrones (<b>98</b>–<b>122</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 10
<p>Structures of the γ-pyrones (<b>123</b>–<b>132</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 11
<p>Structures of the furanones (<b>133</b>–<b>154</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 11 Cont.
<p>Structures of the furanones (<b>133</b>–<b>154</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 12
<p>Structures of the quinones (<b>155</b>–<b>165</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 12 Cont.
<p>Structures of the quinones (<b>155</b>–<b>165</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 13
<p>Structures of the other polyketides (<b>166</b>–<b>190</b> and <b>193</b>–<b>207</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 13 Cont.
<p>Structures of the other polyketides (<b>166</b>–<b>190</b> and <b>193</b>–<b>207</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 13 Cont.
<p>Structures of the other polyketides (<b>166</b>–<b>190</b> and <b>193</b>–<b>207</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 14
<p>Structures of the sesquiterpenoids (<b>208</b>–<b>248</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 14 Cont.
<p>Structures of the sesquiterpenoids (<b>208</b>–<b>248</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 14 Cont.
<p>Structures of the sesquiterpenoids (<b>208</b>–<b>248</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 15
<p>Structures of the diterpenoids (<b>249</b>–<b>260</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 16
<p>Structures of the triterpenoids (<b>261</b> and <b>262</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 17
<p>Structures of the other terpenoids (<b>263</b>–<b>265</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 18
<p>Structures of the steroids (<b>266</b>–<b>273</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">Figure 19
<p>Structures of the phenolic metabolites (<b>274</b>–<b>276</b>) isolated from <span class="html-italic">Fusarium</span> fungi.</p>
Full article ">
11 pages, 3130 KiB  
Communication
Aeruginosin 525 (AER525) from Cyanobacterium Aphanizomenon Sp. (KUCC C2): A New Serine Proteases Inhibitor
by Donata Overlingė, Marta Cegłowska, Robert Konkel and Hanna Mazur-Marzec
Mar. Drugs 2024, 22(11), 506; https://doi.org/10.3390/md22110506 - 8 Nov 2024
Viewed by 590
Abstract
Aeruginosins (AERs) are one of the most common classes of cyanobacterial peptides synthesised through a hybrid non-ribosomal peptide synthase/polyketide synthase pathway. They have been found in Microcystis, Nodularia spumigena, Oscillatoria/Plantothrix, and Nostoc. The presence of AER in Aphanizomenon [...] Read more.
Aeruginosins (AERs) are one of the most common classes of cyanobacterial peptides synthesised through a hybrid non-ribosomal peptide synthase/polyketide synthase pathway. They have been found in Microcystis, Nodularia spumigena, Oscillatoria/Plantothrix, and Nostoc. The presence of AER in Aphanizomenon isolated from the Curonian Lagoon was reported for the first time in our previous work. Here, the structure of aeruginosin 525 (AER525), isolated from Aphanizomenon sp. KUCC C2, was characterised based on high-resolution mass spectrometry. This new AER variant shows potent activity against thrombin. It also inhibits trypsin and carboxypeptidase A but has no effect on elastase and chymotrypsin. In terms of the N-terminal residue and biological activity, AER525 displaces some similarity to dysinosins, which belongs to the most potent inhibitors of thrombin among AERs. The findings underline the potential of AER525 as a new anticoagulant agent. Full article
Show Figures

Figure 1

Figure 1
<p>Mass fragmentation spectra of AER525 collected using QTRAP5500.</p>
Full article ">Figure 2
<p>Mass fragmentation spectra of AER525 collected using HRMS SYNAPT XS QTOF systems.</p>
Full article ">Figure 3
<p>The activity of <span class="html-italic">Aphanizomenon</span> sp. KUCC C2 fractions against trypsin (tested at a concentration of 45 µg mL<sup>−1</sup>).</p>
Full article ">Figure 4
<p>The activity of <span class="html-italic">Aphanizomenon</span> sp. KUCC C2 fractions against thrombin (tested at a concentration of 45 µg mL<sup>−1</sup>).</p>
Full article ">
24 pages, 4971 KiB  
Article
Unraveling Whole-Genome Sequence and Functional Characterization of P. megaterium PH3
by Xiaohan Zhang, Junbo Liang, Dong Zhang, Liang Wang and Shuhong Ye
Foods 2024, 13(22), 3555; https://doi.org/10.3390/foods13223555 - 7 Nov 2024
Viewed by 605
Abstract
Priestia megaterium (P. megaterium PH3) is an endophytic bacterium isolated from peanuts. It has natural resveratrol production ability and shows potential application value. This study analyzed its genetic function and metabolic mechanism through whole-genome sequencing and found that the genome size is [...] Read more.
Priestia megaterium (P. megaterium PH3) is an endophytic bacterium isolated from peanuts. It has natural resveratrol production ability and shows potential application value. This study analyzed its genetic function and metabolic mechanism through whole-genome sequencing and found that the genome size is 5,960,365 bp, the GC content is 37.62%, and 6132 genes are annotated. Functional analysis showed that this strain contained 149 carbohydrate active enzyme genes, 7 secondary metabolite synthesis gene clusters, 509 virulence genes, and 273 drug-resistance genes. At the same time, this strain has the ability to regulate salt stress, low temperature, and hypoxia. Genomic analysis reveals a stilbene-synthase-containing type III polyketide synthase gene cluster that contributes to resveratrol synthesis. A safety assessment showed that the strain is non-hemolytic, does not produce amino acid decarboxylase, and is not resistant to multiple antibiotics. In the mouse model, P. megaterium PH3 did not have significant effects on body weight, behavior, or physiological indicators. These results provide important basic data and theoretical support for its industrial application and the research and development of plant protection agents. Full article
(This article belongs to the Section Food Biotechnology)
Show Figures

Figure 1

Figure 1
<p>Genomic evaluation. (<b>A</b>) GC depth distribution analysis (Depth of staining indicates enrichment); (<b>B</b>) K-mer frequency distribution analysis.</p>
Full article ">Figure 2
<p><span class="html-italic">P. megaterium</span> PH3 genome circle map (note: the outermost circle, genome size; the second circle, coding sequence (CDS) on the positive chain; the third circle, CDS on the negative chain; the fourth circle, rRNA and tRNA; the fifth circle, GC content; the innermost circle, GC skew value).</p>
Full article ">Figure 3
<p>Gene annotation. (<b>A</b>) Gene base annotation analysis; (<b>B</b>) Non-Redundant Protein Database (COG) annotations; (<b>C</b>) Gene Ontology (GO) annotation; (<b>D</b>) Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation.</p>
Full article ">Figure 4
<p>Analysis of the metabolic system of <span class="html-italic">P. megaterium</span> PH3 genome. (<b>A</b>) Carbohydrate-active enzymes (CAZy) functional classification map; (<b>B</b>) Type III Polyketide Synthase (T3PKS) gene cluster; (<b>C</b>) terpene gene cluster.</p>
Full article ">Figure 5
<p>System analysis of pathogenic disease. (<b>A</b>) Virulence factor statistic; (<b>B</b>) antibiotic-resistance gene.</p>
Full article ">Figure 6
<p>Intracellular regulation and functional protein analysis. (<b>A</b>) Two-component regulatory system analysis; (<b>B</b>) transporter protein analysis; (<b>C</b>) mutual analysis of pathogenic bacteria hosts.</p>
Full article ">Figure 7
<p>Safety evaluation. (<b>A</b>) Hemolysis experiment; (<b>B</b>) Indo matrix experimental tests; (<b>C</b>) biogenic amines experiment; (<b>D</b>) visualization of drug-sensitivity tests.</p>
Full article ">Figure 8
<p>Results of <span class="html-italic">P. megaterium</span> PH3 on basal indices in mice. (<b>A</b>) Organ tissues of mice; (<b>B</b>) body weight of mice (low-dose group (1.5 × 10<sup>5</sup> CFU/mL, LC), and high-dose group (1.5 × 10<sup>10</sup> CFU/mL, HC)).</p>
Full article ">Figure 9
<p>Mice organ index analysis (LC stands for low-dose group (1.5 × 10<sup>5</sup> CFU/mL) and HC stands for high-dose group (1.5 × 10<sup>10</sup> CFU/mL)).</p>
Full article ">Figure 10
<p>Pathological analysis of <span class="html-italic">P. megaterium</span> PH3 on mice. (<b>A</b>) Organ slices; (<b>B</b>) oxidative stress analysis in serum (LC stands for low-dose group (1.5 × 10<sup>5</sup> CFU/mL) and HC stands for high-dose group (1.5 × 10<sup>10</sup> CFU/mL)).</p>
Full article ">
15 pages, 6319 KiB  
Article
Biocontrol Agents Inhibit Banana Fusarium Wilt and Alter the Rooted Soil Bacterial Community in the Field
by Chanjuan Du, Di Yang, Shangbo Jiang, Jin Zhang, Yunfeng Ye, Lianfu Pan and Gang Fu
J. Fungi 2024, 10(11), 771; https://doi.org/10.3390/jof10110771 - 6 Nov 2024
Viewed by 606
Abstract
Banana is an important fruit and food crop in tropical and subtropical regions worldwide. Banana production is seriously threatened by Fusarium wilt of banana (FWB), a disease caused by Fusarium oxysporum f. sp. cubense, and biological control is an important means of [...] Read more.
Banana is an important fruit and food crop in tropical and subtropical regions worldwide. Banana production is seriously threatened by Fusarium wilt of banana (FWB), a disease caused by Fusarium oxysporum f. sp. cubense, and biological control is an important means of curbing this soil-borne disease. To reveal the effects of biocontrol agents on inhibiting FWB and altering the soil bacterial community under natural ecosystems, we conducted experiments at a banana plantation. The control efficiency of a compound microbial agent (CM), Paenibacillus polymyxa (PP), Trichoderma harzianum (TH), and carbendazim (CA) on this disease were compared in the field. Meanwhile, the alterations in structure and function of the rooted soil bacterial community in different treatments during the vigorous growth and fruit development stages of banana were analyzed by microbiomics method. The results confirmed that the different biocontrol agents could effectively control FWB. In particular, CM significantly reduced the incidence of the disease and showed a field control efficiency of 60.53%. In terms of bacterial community, there were no significant differences in the richness and diversity of banana rooted soil bacteria among the different treatments at either growth stage, but their relative abundances differed substantially. CM treatment significantly increased the ratios of Bacillus, Bryobacter, Pseudomonas, Jatrophihabitans, Hathewaya, and Chujaibacter in the vigorous growth stage and Jatrophihabitans, Occallatibacter, Cupriavidus, and 1921-3 in the fruit development stage. Furthermore, bacterial community function in the banana rooted soil was affected differently by the various biocontrol agents. CM application increased the relative abundance of multiple soil bacterial functions, including carbohydrate metabolism, xenobiotic biodegradation and metabolism, terpenoid and polyketide metabolism, lipid metabolism, and metabolism of other amino acids. In summary, our results suggest that the tested biocontrol agents can effectively inhibit the occurrence of banana Fusarium wilt and alter the soil bacterial community in the field. They mainly modified the relative abundance of bacterial taxa and the metabolic functions rather than the richness and diversity. These findings provide a scientific basis for the use of biocontrol agents to control banana Fusarium wilt under field conditions, which serves as a reference for the study of the soil microbiological mechanisms of other biocontrol agents. Full article
(This article belongs to the Special Issue Current Research in Soil Borne Plant Pathogens)
Show Figures

Figure 1

Figure 1
<p>Experimental design of the field trial. The banana plant with yellow leaves shows symptoms of banana wilt. Samples were collected at the seedling, vigorous growth, and fruit development stages as shown. Biocontrol agent treatments were applied approximately every 30 days during the vigorous growth stage, for a total of four treatments.</p>
Full article ">Figure 2
<p>Effects of different inoculation treatments on the disease incidence and control efficiency of banana Fusarium wilt. CM, compound microbial agent; PP, <span class="html-italic">Paenibacillus polymyxa</span>; TH, <span class="html-italic">Trichoderma harzianum</span>; CA, carbendazim. Significant differences (<span class="html-italic">p</span> &lt; 0.05) among treatments are indicated by different letters.</p>
Full article ">Figure 3
<p>Bacterial richness and diversity of banana rooted soils at the seedling, vigorous growth, and fruit development stages. (<b>a</b>) Sob rarefaction curve; (<b>b</b>) Number of operational taxonomic units (OTUs); (<b>c</b>) Chao index; (<b>d</b>) Ace index; (<b>e</b>) Shannon index; (<b>f</b>) Simpson index. CM, compound microbial agent; PP, <span class="html-italic">Paenibacillus polymyxa</span>; TH, <span class="html-italic">Trichoderma harzianum</span>; CA, carbendazim; BCK, before treatment; CK, control. Letters a and b indicate the vigorous growth and fruit development stages, respectively. Values are the means ± standard deviations (SD) (<span class="html-italic">n</span> = 3). Different letters indicate significant differences among the treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4
<p>Bacterial composition of banana rooted soil from different treatments. (<b>a</b>,<b>b</b>) Bacterial composition at the phylum level (<b>a</b>) and genus level (<b>b</b>). (<b>c</b>,<b>d</b>) Venn diagrams showing shared and unique bacterial genera in the five treatments at the vigorous growth stage (<b>c</b>) and fruit development stage (<b>d</b>). CM, compound microbial agent; PP, <span class="html-italic">Paenibacillus polymyxa</span>; TH, <span class="html-italic">Trichoderma harzianum</span>; CA, carbendazim; BCK, before treatment; CK, control. Letters a and b indicate the vigorous growth and fruit development stages, respectively. “Other” indicates the relative abundance of all phylum-level or genus-level classifications other than the top 10 presented and named in the lists (<b>a</b>,<b>b</b>).</p>
Full article ">Figure 5
<p>Weighted UniFrac principal coordinate analysis (PCoA) of the soil bacterial communities of banana under different treatments. (<b>a</b>) Vigorous growth stage; (<b>b</b>) Fruit development stage. CM, compound microbial agent; PP, <span class="html-italic">Paenibacillus polymyxa</span>; TH, <span class="html-italic">Trichoderma harzianum</span>; CA, carbendazim; CK, control. Letters a and b indicate the vigorous growth and fruit development stages, respectively.</p>
Full article ">Figure 6
<p>Differences in the abundance of bacterial taxa and identification of biomarkers associated with the compound microbial agent (CM) and control (CK) treatments. (<b>a</b>,<b>b</b>) LEfSe analysis of the bacterial community (<b>a</b>) and Welch’s <span class="html-italic">t</span>-tests of bacterial abundance at the genus level (<b>b</b>) at the vigorous growth stage. (<b>c</b>,<b>d</b>) LEfSe analysis of the bacterial community (<b>c</b>) and Welch’s <span class="html-italic">t</span>-tests of bacterial abundance at the genus level (<b>d</b>) at the fruit development stage. In (<b>a</b>,<b>c</b>), tracks from inside to outside represent classification levels from phylum to genus. Each small solid circle represents a taxon at that level, and the size of the circle is proportional to the relative abundance of the taxon. Taxa with an LDA score &gt; 3.0 and <span class="html-italic">p</span> &lt; 0.05 are shown. In (<b>b</b>,<b>d</b>), <span class="html-italic">n</span> = 3 and <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 7
<p>Metabolic functions of bacterial communities of banana rooted soil predicted by Tax4Fun. (<b>a</b>) Clustered heatmap showing the relative abundance of the top 20 KEGG metabolic pathways across all samples; red indicates higher abundance and blue indicates lower abundance. CM, compound microbial agent; PP, <span class="html-italic">Paenibacillus polymyxa</span>; TH, <span class="html-italic">Trichoderma harzianum</span>; CA, carbendazim; CK, control. The letters a and b indicate the vigorous growth stage and fruit development stage, respectively. (<b>b</b>) Significant differences in the abundance of different functions between the CM and CK treatments were analyzed with Welch’s <span class="html-italic">t</span>-test (<span class="html-italic">n</span> = 3, <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">
16 pages, 3210 KiB  
Article
Widely Targeted Metabolomics Method Reveals Differences in Volatile and Nonvolatile Metabolites in Three Different Varieties of Raw Peanut by GC–MS and HPLC–MS
by Jiantao Fu, Yuxing An, Dao Yao, Lijun Chen, Liwen Zhou, Dachun Shen, Sixing Dai, Yinglin Lu and Donglei Sun
Molecules 2024, 29(22), 5230; https://doi.org/10.3390/molecules29225230 - 5 Nov 2024
Viewed by 455
Abstract
The aim of the present study was to comprehensively analyze and identify the metabolites of different varieties of raw peanut, as well as provide a reference for the utilization of different varieties of peanuts. In this study, three varieties of peanuts, namely ZKH1H, [...] Read more.
The aim of the present study was to comprehensively analyze and identify the metabolites of different varieties of raw peanut, as well as provide a reference for the utilization of different varieties of peanuts. In this study, three varieties of peanuts, namely ZKH1H, ZKH13H, and CFD, were investigated via ultrahigh-performance liquid chromatography (UPLC) and widely targeted metabolomics methods based on tandem mass spectrometry (MS) and solid-phase microextraction-gas chromatography–mass spectrometry (SPME-GC–MS). In total, 417 nonvolatile and 55 volatile substances were detected. The nonvolatile substances were classified into the following 10 categories: organic acids and derivatives (28.9%); organic oxygen compounds (21.9%); lipids and lipid-like molecules (12.6%); organoheterocyclic compounds (9.9%); nucleosides, nucleotides, and analogues (9.4%); benzenoids (7.8%); phenylpropanoids and polyketides (6.1%); organic nitrogen compounds (2.7%); lignans, neolignans, and related compounds (0.5%); and alkaloids and their derivatives (0.3%). The volatile compounds (VOCs) were classified into the following eight categories: organic oxygen compounds (24.1%); organic cyclic compounds (20.4%); organic nitrogen compounds (13%); organic acids and their derivatives (13%); lipids and lipid-like molecules (11.2%); benzenoids (11.1%); hydrocarbons (3.7%); and homogeneous non-metallic compounds (3.7%). Differentially abundant metabolites among the different peanut varieties (ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H) were investigated via multivariate statistical analyses, which identified 213, 204, and 157 nonvolatile differentially abundant metabolites, respectively, and 12, 11, and 10 volatile differentially abundant metabolites, respectively. KEGG metabolic pathway analyses of the differential non-VOCs revealed that the most significant metabolic pathways among ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H were galactose metabolism, purine metabolism, and aminoacyl-tRNA, while the nitrogen metabolism pathway was identified as a significant metabolic pathway for the VOCs. The present findings provide a theoretical foundation for the development and utilization of these three peanut species, as well as for the breeding of new peanut varieties. Full article
Show Figures

Figure 1

Figure 1
<p>The appearance (<b>A</b>), length (<b>B</b>), width (<b>C</b>), and length/width ratio (<b>D</b>) of the three varieties of peanuts. The data are presented as the mean ± standard deviation (SD).</p>
Full article ">Figure 2
<p>Different main nonvolatile metabolites in the three varieties of peanut samples were identified through a widely targeted metabolic method and method reliability evaluation. (<b>A</b>) Classification of the 417 nonvolatile metabolites detected in the three varieties of peanut samples. (<b>B</b>) PCA score plot. (<b>C</b>) Heatmap analysis.</p>
Full article ">Figure 3
<p>K-means clustering analysis of all nonvolatile metabolites of the three varieties of peanut samples.</p>
Full article ">Figure 4
<p>Differential nonvolatile metabolites obtained by comparison of each pair of varieties. Score plots of OPLS-DA pairwise comparisons of differentially abundant metabolites in (<b>A</b>) ZKH1H vs. CFD, (<b>D</b>) ZKH1H vs. ZKH13H, and (<b>G</b>) ZKH13H vs. CFD. Volcano plots showing the differential nonvolatile metabolite expression levels in (<b>B</b>) ZKH1H vs. CFD, (<b>E</b>) ZKH1H vs. ZKH13H, and (<b>H</b>) ZKH13H vs. CFD. Classification of the differential nonvolatile metabolites obtained by comparison of each pair of varieties in (<b>C</b>) ZKH1H vs. CFD, (<b>F</b>) ZKH1H vs. ZKH13H, and (<b>I</b>) ZKH13H vs. CFD.</p>
Full article ">Figure 5
<p>KEGG pathway annotation of the differential nonvolatile metabolites obtained by comparing each of the two groups in (<b>A</b>) ZKH1H vs. CFD, (<b>B</b>) ZKH1H vs. ZKH13H, and (<b>C</b>) ZKH13H vs. CFD. (<b>D</b>) Intersection of the 5 pathways with the most significant differences in the 3 comparison groups.</p>
Full article ">Figure 6
<p>Multivariate statistical analysis of VOCs in the three varieties of peanut samples. (<b>A</b>) Classification of the 55 nonvolatile metabolites detected in the three varieties of peanut samples. (<b>B</b>) PCA score plot. (<b>C</b>) Heatmap analysis.</p>
Full article ">Figure 7
<p>Differential VOCs obtained by comparison of each pair of varieties. Score plots of OPLS-DA pairwise comparisons of differentially abundant metabolites in (<b>A</b>) ZKH1H vs. CFD, (<b>D</b>) ZKH1H vs. ZKH13H, and (<b>G</b>) ZKH13H vs. CFD. Volcano plots showing the differential nonvolatile metabolite expression levels in (<b>B</b>) ZKH1H vs. CFD, (<b>E</b>) ZKH1H vs. ZKH13H, and (<b>H</b>) ZKH13H vs. CFD. Correlation analysis of differential volatile metabolites in (<b>C</b>) ZKH1H vs. CFD, (<b>F</b>) ZKH1H vs. ZKH13H, and (<b>I</b>) ZKH13H vs. CFD.</p>
Full article ">Figure 8
<p>Differential VOCs from GC-MS were enriched in distinct KEGG pathways by comparing each of the two groups. (<b>A</b>) ZKH1H vs. CFD, (<b>B</b>) ZKH1H vs. ZKH13H.</p>
Full article ">
20 pages, 4483 KiB  
Article
Metabolomic Analysis of Elymus sibiricus Exposed to UV-B Radiation Stress
by Fei Zhang, Ming Sun, Daxu Li, Minghong You, Jiajun Yan and Shiqie Bai
Molecules 2024, 29(21), 5133; https://doi.org/10.3390/molecules29215133 - 30 Oct 2024
Viewed by 456
Abstract
Plants cultivated on the Qinghai-Tibet Plateau (QTP) are exposed to high ultraviolet radiation intensities, so they require effective mechanisms to adapt to these stress conditions. UV-B radiation is an abiotic stress factor that affects plant growth, development, and environmental adaptation. Elymus sibiricus is [...] Read more.
Plants cultivated on the Qinghai-Tibet Plateau (QTP) are exposed to high ultraviolet radiation intensities, so they require effective mechanisms to adapt to these stress conditions. UV-B radiation is an abiotic stress factor that affects plant growth, development, and environmental adaptation. Elymus sibiricus is a common species in the alpine meadows of the QTP, with high-stress resistance, large biomass, and high nutritional value. This species plays an important role in establishing artificial grasslands and improving degraded grasslands. In this study, UV-B radiation-tolerant and UV-B radiation-sensitive E. sibiricus genotypes were subjected to simulated short-term (5 days, 10 days) and long-term (15 days, 20 days) UV-B radiation stress and the metabolite profiles evaluated to explore the mechanism underlying UV-B radiation resistance in E. sibiricus. A total of 699 metabolites were identified, including 11 primary metabolites such as lipids and lipid-like molecules, phenylpropanoids and polyketides, organic acids and their derivatives, and organic oxygen compounds. Principal component analysis distinctly clustered the samples according to the cultivar, indicating that the two genotypes exhibit distinct response mechanisms to UV-B radiation stress. The results showed that 14 metabolites, including linoleic acid, LPC 18:2, xanthosine, and 23 metabolites, including 2-one heptamethoxyflavone, glycyrrhizin, and caffeic acid were differentially expressed under short-term and long-term UV-B radiation stress, respectively. Therefore, these compounds are potential biomarkers for evaluating E. sibiricus response to UV-B radiation stress. Allantoin specific and consistent expression was up-regulated in the UV-B radiation-tolerant genotype, thereby it can be used to identify varieties resistant to UV-B radiation. Different metabolic profiles and UV-B radiation response mechanisms were observed between the UV-B radiation-tolerant and UV-B radiation-sensitive E. sibiricus genotypes. A model for the metabolic pathways and metabolic profiles was constructed for the two genotypes. This metabolomic study on the E. sibiricus response to UV-B radiation stress provides a reference for the breeding of new UV-B radiation-tolerant E. sibiricus cultivars. Full article
Show Figures

Figure 1

Figure 1
<p>Screening of UV-B radiation-tolerant and sensitive genotypes of <span class="html-italic">E. sibiricus</span>. (<b>A</b>) Hierarchical clustering diagram of the 18 <span class="html-italic">E. sibiricus</span> samples; (<b>B</b>) phenotypic changes of the SC genotype and XJ genotype at days 0, 5, 10, 15, and 20 of UV-B radiation, respectively. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiation-sensitive genotype.</p>
Full article ">Figure 2
<p>Physiological indicators of SC and XJ genotypes. (<b>A</b>) Proanthocyanidin content; (<b>B</b>) flavonoid content. Different lower-case letters indicate the significant difference at different UV-B radiation stress time for the same <span class="html-italic">E. sibiricus</span> variety at 0.05 levels. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiatio-sensitive genotype.</p>
Full article ">Figure 3
<p>Metabolite profiles of the SC and XJ genotypes under different UV-B radiation stress times as determined by HCA and PCA. (<b>A</b>) Cluster analysis of the metabolites present in the SC and XJ genotypes. Red indicates high abundance, whereas blue indicates low abundance. Metabolites were clustered into four distinct clusters (group 1, group 2, group 3, group 4). (<b>B</b>) The PCA plot illustrating the metabolites in the different samples. Each point represents one metabolite profiling experiment, that is, the numbers 1 to 6 represent samples from day 0 of XJ radiation stress (XJ_0), 7 to 12 represent samples from 5 days of XJ radiation stress (XJ_5), 13 to 18 represent samples from 10 days of XJ radiation stress (XJ_10), 19 to 24 represent samples from 15 days of XJ radiation stress (XJ_15), 25 to 30 represent samples from 20 days of XJ radiation stress (XJ_20), similarly, numbers 31 to 60 represent samples of SC in different UV stress days (SC_0, SC_5, SC_10, SC_15, SC_20). Six biological replicates were set per UV-B radiation time point. (<b>C</b>) Pearson’s correlation heatmap of 60 samples. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiation-sensitive genotype.</p>
Full article ">Figure 4
<p>Metabolite classes and quantities. (<b>A</b>) Primary metabolite classes; (<b>B</b>) red represents all metabolite classes and their quantities, blue represents the quantities and classes of DAMs; (<b>C</b>) differentially expressed metabolites across the 25 comparison groups, up-regulated metabolites are shown in red and down-regulated metabolites are indicated in blue. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiation-sensitive genotype.</p>
Full article ">Figure 5
<p>(<b>A</b>) A Venn diagram of the differentially expressed metabolites in the SC and XJ genotypes under UV-B radiation exposure; (<b>B</b>) significantly enriched KEGG pathways associated with the common DAMs between the two genotypes. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiation-sensitive genotype.</p>
Full article ">Figure 6
<p>Metabolic profiles of the SC and XJ genotypes. A Venn diagram showing the number of up-regulated metabolites for the SC genotype (<b>A</b>) and XJ genotype (<b>C</b>). The number of down-regulated metabolites for the SC genotype (<b>B</b>) and XJ genotype (<b>D</b>). (<b>E</b>,<b>F</b>) Trend analysis of DAMs in the SC and XJ genotypes; (<b>G</b>) significantly enriched KEGG pathways associated with the DAMs unique to the SC genotype. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiation-sensitive genotype.</p>
Full article ">Figure 6 Cont.
<p>Metabolic profiles of the SC and XJ genotypes. A Venn diagram showing the number of up-regulated metabolites for the SC genotype (<b>A</b>) and XJ genotype (<b>C</b>). The number of down-regulated metabolites for the SC genotype (<b>B</b>) and XJ genotype (<b>D</b>). (<b>E</b>,<b>F</b>) Trend analysis of DAMs in the SC and XJ genotypes; (<b>G</b>) significantly enriched KEGG pathways associated with the DAMs unique to the SC genotype. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiation-sensitive genotype.</p>
Full article ">Figure 7
<p>The metabolic network in <span class="html-italic">E. sibiricus</span> under UV-B radiation stress. The proposed metabolic pathways are based on a literature review and KEGG database analysis. Red indicates a significant up-regulation, blue indicates a significant down-regulation, and gray indicates no significant change in expression. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiation-sensitive genotype.</p>
Full article ">Figure 8
<p>Metabolite profiles in the SC and XJ genotypes in response to UV-B radiation stress. The red font indicates increased expression, whereas the blue font indicates decreased expression. SC represents the UV-B radiation-tolerant genotype and XJ represents the UV-B radiation-sensitive genotype.</p>
Full article ">
18 pages, 1544 KiB  
Article
Genomic Characterization of Lactiplantibacillus plantarum Strains: Potential Probiotics from Ethiopian Traditional Fermented Cottage Cheese
by Seyoum Gizachew and Ephrem Engidawork
Genes 2024, 15(11), 1389; https://doi.org/10.3390/genes15111389 - 29 Oct 2024
Viewed by 736
Abstract
Background: Lactiplantibacillus plantarum is a species found in a wide range of ecological niches, including vegetables and dairy products, and it may occur naturally in the human gastrointestinal tract. The precise mechanisms underlying the beneficial properties of these microbes to their host remain obscure. [...] Read more.
Background: Lactiplantibacillus plantarum is a species found in a wide range of ecological niches, including vegetables and dairy products, and it may occur naturally in the human gastrointestinal tract. The precise mechanisms underlying the beneficial properties of these microbes to their host remain obscure. Although Lactic acid bacteria are generally regarded as safe, there are rare cases of the emergence of infections and antibiotic resistance by certain probiotics. Objective: An in silico whole genome sequence analysis of putative probiotic bacteria was set up to identify strains, predict desirable functional properties, and identify potentially detrimental antibiotic resistance and virulence genes. Methods: We characterized the genomes of three L. plantarum strains (54B, 54C, and 55A) isolated from Ethiopian traditional cottage cheese. Whole-genome sequencing was performed using Illumina MiSeq sequencing. The completeness and quality of the genome of L. plantarum strains were assessed through CheckM. Results: Analyses results showed that L. plantarum 54B and 54C are closely related but different strains. The genomes studied did not harbor resistance and virulence factors. They had five classes of carbohydrate-active enzymes with several important functions. Cyclic lactone autoinducer, terpenes, Type III polyketide synthases, ribosomally synthesized and post-translationally modified peptides-like gene clusters, sactipeptides, and all genes required for riboflavin biosynthesis were identified, evidencing their promising probiotic properties. Six bacteriocin-like structures encoding genes were found in the genome of L. plantarum 55A. Conclusions: The lack of resistome and virulome and their previous functional capabilities suggest the potential applicability of these strains in food industries as bio-preservatives and in the prevention and/or treatment of infectious diseases. The results also provide insights into the probiotic potential and safety of these three strains and indicate avenues for further mechanistic studies using these isolates. Full article
(This article belongs to the Section Microbial Genetics and Genomics)
Show Figures

Figure 1

Figure 1
<p>Phylogenetic analysis of <span class="html-italic">L. plantarum</span> 54B, 54C, and 55A with 23 other <span class="html-italic">L. plantarum</span> genomes. This phylogenetic tree was generated in the BV-BRC using the “Bacterial Genome Tree” tool for the 23 representative <span class="html-italic">L. plantarum</span> genomes (6 human isolates, 6 dairy isolates, 4 meat products isolates, and 7 isolates from different sources) and the 3 genomes under study. Parameters: Max allowed deletions = 0; Max allowed duplications = 0; Single-copy genes found = 100; Number of protein alignments = 100; Alignment program = mafft; Number of aligned amino acids = 39,007; Number of CDS alignments = 100; Number of aligned nucleotides = 117,021; Best protein model found by RAxML = DUMMY2; Branch support method = RAxML Fast Bootstrapping; RAxML likelihood = −329,039.7462.</p>
Full article ">Figure 2
<p>Analysis of the presence of probiotic marker genes from the cloud genome proposed by Carpi et al. [<a href="#B40-genes-15-01389" class="html-bibr">40</a>] for the species <span class="html-italic">L. plantarum</span>. Numeric values refer to the number of gene copies.</p>
Full article ">Figure 3
<p>The antiSMASH system predicted bacteriocins and secondary metabolite-producing regions in the genome of <span class="html-italic">L. plantarum</span> 55A: Red (core biosynthetic genes), pink (additional biosynthetic genes), blue (transport-related genes), green (regulatory genes), grey (other genes), and black (resistance). (<b>A</b>) Cyclic lactone autoinducer; (<b>B</b>) RiPP-like; (<b>C</b>) Type III PKS; (<b>D</b>) Terpene.</p>
Full article ">Figure 4
<p>Identification of chromosomal gene clusters of the <span class="html-italic">L. plantarum</span> 55A containing genes encoding sactipeptides (<b>A</b>), plantaricin-like proteins (<b>B</b>), and chromosomal gene clusters of the <span class="html-italic">L. plantarum</span> 54B containing genes encoding sactipeptides (<b>C</b>) using BAGEL v5 software.</p>
Full article ">
15 pages, 1996 KiB  
Article
New Polyketide Congeners with Antibacterial Activities from an Endophytic Fungus Stemphylium globuliferum 17035 (China General Microbiological Culture Collection Center No. 40666)
by Yingying Li, Guoliang Zhu, Jing Wang, Junjie Yu, Ke Ye, Cuiping Xing, Biao Ren, Bin Zhu, Simin Chen, Lijun Lai, Yue Li, Tom Hsiang, Lixin Zhang, Xueting Liu and Jingyu Zhang
J. Fungi 2024, 10(11), 737; https://doi.org/10.3390/jof10110737 - 24 Oct 2024
Viewed by 641
Abstract
Four new polyketides, heterocornol Y (1), stemphyindan (2), pestalospirane C (3), and stemphyspyrane (4), along with five known ones (59) were isolated from the endophytic fungus Stemphylium globuliferum 17035 (SG17035) based [...] Read more.
Four new polyketides, heterocornol Y (1), stemphyindan (2), pestalospirane C (3), and stemphyspyrane (4), along with five known ones (59) were isolated from the endophytic fungus Stemphylium globuliferum 17035 (SG17035) based on the One Strain Many Compounds (OSMAC) strategy allied with an LC-MS approach. These structures were elucidated through extensive spectroscopic analyses, single-crystal X-ray diffraction, and 13C NMR-DP4 analysis. Pestalospirane C (3) and stemphyspyrane (4) featured unprecedented spiroketal skeletons. In addition, the putative biosynthetic logic for compounds 14 was proposed. Antibacterial and cytotoxic activities of compounds 19 were evaluated. Stemphyspyrane (4) displayed promising antibacterial activity against different pathogens, especially against Staphylococcus aureus, Porphyromonas gingivalis, and methicillin-resistant Staphylococcus aureus (MRSA) with MIC values of 3.125 μM, 6.25 μM, and 12.5 μM, respectively. It is promising as an antibacterial agent for further optimization. Full article
(This article belongs to the Special Issue Advances in Fungal Endophyte Research)
Show Figures

Figure 1

Figure 1
<p>The structures of compounds <b>1</b>–<b>9</b>.</p>
Full article ">Figure 2
<p>Identifying the species of strain SG17035. (<b>a</b>) SG17035’s conidiation morphology after 14 days of culture on a PDA plate at 28 °C. (<b>b</b>) The SG17035 phylogenetic tree constructed using ITS sequences. Numbers for NCBI accession are provided in parenthesis. Based on 1000 resampled datasets, numbers at nodes represent bootstrap support levels (percentages); only values &gt; 50% are shown. The selected out-group was <span class="html-italic">Asteromyces cruciatus</span>. (<b>c</b>,<b>d</b>) Microscopic morphology of mycelium and conidium. Scale bars: 10 µm and 2 µm.</p>
Full article ">Figure 3
<p>Key 2D NMR correlations of compounds <b>1</b>–<b>4</b>.</p>
Full article ">Figure 4
<p>ORTEP plot (50% probability level) of single-crystal X-ray structures of <b>1</b>–<b>3</b> (red line circle: oxygen atom; black line circle: carbon atom; hollow circle: hydrogen atom).</p>
Full article ">Figure 5
<p>Putative biosynthetic pathway of compounds <b>1</b>–<b>4</b>.</p>
Full article ">
15 pages, 2401 KiB  
Article
Diversity and Anti-Infectious Components of Cultivable Rhizosphere Fungi Derived from Three Species of Astragalus Plants in Northwestern Yunnan, China
by Guo-Jun Zhou, Wei-Jia Xiong, Wei Xu, Zheng-Rong Dou, Bo-Chao Liu, Xue-Li Li, Hao Du, Hai-Feng Li, Yong-Zeng Zhang, Bei Jiang and Kai-Ling Wang
J. Fungi 2024, 10(11), 736; https://doi.org/10.3390/jof10110736 - 24 Oct 2024
Viewed by 476
Abstract
Astragalus, a group of legume plants, has a pronounced rhizosphere effect. Many species of Astragalus with limited resource reserves are distributed in the high-altitude area of northern Yunnan, China. Although some of these plants have high medicinal value, the recognition of them [...] Read more.
Astragalus, a group of legume plants, has a pronounced rhizosphere effect. Many species of Astragalus with limited resource reserves are distributed in the high-altitude area of northern Yunnan, China. Although some of these plants have high medicinal value, the recognition of them is still at a low level. The aim of this research is to explore the species diversity of cultivable rhizofungi derived from Astragalus acaulis, A. forrestii and A. ernestii growing in a special high–cold environment of northwest Yunnan and discover anti-infective components from these fungi. A total of 93 fungal strains belonging to 38 species in 18 genera were isolated and identified. Antibacterial and antimalarial screening yielded 10 target strains. Among them, the ethyl acetate crude extract of the fermented substrate of the rhizofungus Aspergillus calidoustus AA12 derived from the plant A. acaulis showed broad-spectrum antibacterial activity and the best antimalarial activity. Further chemical investigation led to the first discovery of seven compounds from the species A. calidoustus, including sesterterpine 6-epi-ophiobolin G; three sesquiterpenes, penicisochroman A, pergillin and 7-methyl-2-(1-methylethylethlidene)-furo [3,2-H]isoquinoline-3-one; and three polyketides, trypacidin, 1,2-seco-trypacidin and questin. Among them, the compound 6-epi-ophiobolin G exhibited moderate to strong antibacterial activity against six Gram-positive pathogens with the minimum inhibitory concentration (MIC) ranging from 25 to 6.25 μg/mL and a prominent inhibitory effect on the biofilm of Streptococcus agalactiae at an MIC value of 3.125 μg/mL. This compound also displayed potent antimalarial activity against Plasmodium falciparum strains 3D7 and chloroquine-resistant Dd2 at the half-maximal inhibitory concentration (IC50) values of 3.319 and 4.340 µmol/L at 72 h, respectively. This study contributed to our understanding of the cultivable rhizofungi from characteristic Astragalus plants in special high–cold environments and further increased the library of fungi available for natural anti-infectious product screening. Full article
(This article belongs to the Section Fungal Evolution, Biodiversity and Systematics)
Show Figures

Figure 1

Figure 1
<p>Venn diagram showing the number of fungi at genus (<b>A</b>) and species (<b>B</b>) level in the rhizosphere soil samples of <span class="html-italic">Astragalus acaulis</span> (Aa), <span class="html-italic">A. forrestii</span> (Af) and <span class="html-italic">A. ernestii</span> (Ae). Each circle, with a different color in the diagram, represents the number of genera and species specific to the corresponding subgroup. Middle core numbers represent the number of genera and species commonly to all groups.</p>
Full article ">Figure 2
<p>Chemical structures of the compounds <b>1</b>–<b>7</b>.</p>
Full article ">Figure 3
<p>Scanning electron micrographs (SEM) ×15,000 of 24 h preformed <span class="html-italic">Streptococcus agalactiae</span> ATCC 13813 biofilms treated with different concentrations of 6-epi-ophiobolin G (<b>1</b>). (<b>A</b>–<b>C</b>) Different treatment groups ((<b>A</b>), DMSO control; (<b>B</b>), treated with 1/2 × MIC = 3.125 μg/mL of the compound <b>1</b>; (<b>C</b>), treated with MIC = 6.25 μg/mL of the compound <b>1</b>).</p>
Full article ">Figure 4
<p>Determination of the antimalarial activity of 6-epi-ophiobolin G (<b>1</b>) at 72 h against <span class="html-italic">Plasmodium falciparum</span> 3D7 (<b>A</b>) and chloroquine-resistant <span class="html-italic">P. falciparum</span> Dd2 (<b>B</b>).</p>
Full article ">Figure 5
<p>Blood smear of <span class="html-italic">Plasmodium falciparum</span> 3D7 and chloroquine-resistant <span class="html-italic">P. falciparum</span> Dd2 treated by different concentrations of 6-epi-ophiobolin G (<b>1</b>). The pictures of A1–A3 belong to the <span class="html-italic">P. falciparum</span> 3D7 tested group including a DMSO control (<b>A</b>) and treated with 50 µmol/L (<b>B</b>) and 25 µmol/L (<b>C</b>) of the compound <b>1</b>. The pictures of (<b>D</b>–<b>F</b>) belong to the chloroquine-resistant <span class="html-italic">P. falciparum</span> Dd2 tested group including a DMSO control (<b>D</b>) and treated with 50 µmol/L (<b>E</b>) and 25 µmol/L (<b>F</b>) of the compound <b>1</b>. I and II represent the periods of the trophozoite and schizont of <span class="html-italic">Plasmodium</span> parasites, respectively.</p>
Full article ">
13 pages, 2230 KiB  
Article
Goondapyrones A–J: Polyketide α and γ Pyrone Anthelmintics from an Australian Soil-Derived Streptomyces sp.
by Shengbin Jin, David F. Bruhn, Cynthia T. Childs, Erica Burkman, Yovany Moreno, Angela A. Salim, Zeinab G. Khalil and Robert J. Capon
Antibiotics 2024, 13(10), 989; https://doi.org/10.3390/antibiotics13100989 - 18 Oct 2024
Viewed by 816
Abstract
An investigation of ×19 soil samples collected under the auspices of the Australian citizen science initiative, Soils for Science, returned ×559 chemically dereplicated microbial isolates, of which ×54 exhibited noteworthy anthelmintic activity against either the heartworm Dirofilaria immitis microfilaria and/or the gastrointestinal parasite [...] Read more.
An investigation of ×19 soil samples collected under the auspices of the Australian citizen science initiative, Soils for Science, returned ×559 chemically dereplicated microbial isolates, of which ×54 exhibited noteworthy anthelmintic activity against either the heartworm Dirofilaria immitis microfilaria and/or the gastrointestinal parasite Haemonchus contortus L1–L3 larvae. Chemical (GNPS and UPLC-DAD) and cultivation (MATRIX) profiling prompted a detailed chemical investigation of Streptomyces sp. S4S-00196A10, which yielded new anthelmintic polyketide goondapyrones A–J (110), together with the known actinopyrones A (11) and C (12). Structures for 112 were assigned on the basis of detailed spectroscopic and chemical analysis, with preliminary structure activity relationship analysis revealing selected γ-pyrones >50-fold and >13-fold more potent than isomeric α-pyrones against D. immitis mf motility (e.g., EC50 0.05 μM for 1; EC50 2.7 μM for 5) and H. contortus L1–L3 larvae development (e.g., EC50 0.58 μM for 1; EC50 8.2 μM for 5), respectively. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p><span class="html-italic">Streptomyces</span> sp. S4S-00196A10 metabolites <b>1</b>–<b>12</b>.</p>
Full article ">Figure 2
<p>Selected 2D NMR (DMSO-<span class="html-italic">d</span><sub>6</sub>) correlations for <b>1</b>–<b>4</b>.</p>
Full article ">Figure 3
<p>Mosher analysis of <b>3</b>. Δ<span class="html-italic">δ</span> (<span class="html-italic">δ<sub>S</sub></span> − <span class="html-italic">δ<sub>R</sub></span>) data for the <span class="html-italic">S</span>-MTPA (<b>3a</b>) and <span class="html-italic">R</span>-MTPA (<b>3b</b>).</p>
Full article ">Figure 4
<p>Selected 2D NMR (DMSO-<span class="html-italic">d</span><sub>6</sub>) correlations for <b>5</b>–<b>8</b>.</p>
Full article ">Figure 5
<p>Selected 2D NMR (DMSO-<span class="html-italic">d</span><sub>6</sub>) correlations for <b>9</b>–<b>10</b>.</p>
Full article ">Figure 6
<p>Piericidin B (<b>13</b>). Colour highlights—similarities with actinopyrone A (<b>11</b>) (green).</p>
Full article ">
Back to TopTop