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16 pages, 2701 KiB  
Article
Effects of Reclaimed Water Irrigation on Soil Properties and the Composition and Diversity of Microbial Communities in Northwest China
by Wenmin Wang, Zhen Wang, Hongbo Ling, Xu Zheng, Chaoqun Chen, Jiaping Wang and Zhibo Cheng
Sustainability 2025, 17(1), 308; https://doi.org/10.3390/su17010308 - 3 Jan 2025
Abstract
Reasonably using reclaimed water (RW) for irrigation can help to alleviate water scarcity, while also providing both environmental and economic benefits. However, there is limited information regarding the potential impact of RW irrigation on the nutrients of saline–alkali soils and their microbial communities. [...] Read more.
Reasonably using reclaimed water (RW) for irrigation can help to alleviate water scarcity, while also providing both environmental and economic benefits. However, there is limited information regarding the potential impact of RW irrigation on the nutrients of saline–alkali soils and their microbial communities. This study investigates the effects of RW irrigation on saline–alkali soil properties and microbial communities using a 16S rRNA sequence analysis. The results show that the pH and electrical conductivity (EC) are significantly lower in RW treatment (p < 0.05). Compared to the saline–alkali soil that was not irrigated with RW (CK), the EC value decreased by 42.15–45.76%, in both 0–20 cm and 40–60 cm depth. RW exhibited a significant increase in the abundance of Actinobacteria (32.32–33.42%), Chloroflexi (7.63–15.79%), Firmicutes (9.27–10.42%), and Ascomycota (89.85–95.95%). Bacterial richness and diversity were significantly enhanced after RW irrigation (p < 0.05). At the genus level, the dominant bacterial genera included Bacillus, Penicillium, Aspergillus, and Talaromyces. Differences in the microbial community were observed between the two treatments and among soil depths within each treatment (p < 0.05). A network analysis indicated that the internal relationships among bacterial communities become more complex following RW irrigation, whereas the internal connections within fungal communities tend to become more simplified. A redundancy analysis (RDA) showed that soil microbial communities were directly influenced by EC, total nitrogen (TN), and available potassium (AK). Partial least squares path modeling (PLS-PM) results indicated that soil salinity and available nutrients were the most significant factors influencing the microbial community structure. Together, these results indicate that RW irrigation has a positive impact on ameliorating soil salinity and enhancing microbial community diversity in saline–alkali soils. These findings provide valuable insights for the future agricultural utilization of saline–alkali land. Full article
(This article belongs to the Special Issue Soil Pollution, Soil Ecology and Sustainable Land Use)
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<p>Changes in operational taxonomic units (OTUs) and the relative abundance of soil microbial communities among the treatments: CK (saline–alkali soil not irrigated with reclaimed water) and RW (saline–alkali soil irrigated with reclaimed water). The Venn diagram illustrates the unique and shared OTUs of bacterial (<b>A</b>) and fungal (<b>B</b>) communities. Relative abundance is shown for (<b>C</b>) bacterial and (<b>D</b>) fungal communities at the phylum level. Additionally, the changes in bacterial (<b>E</b>) and fungal (<b>F</b>) communities are presented at the genus levels. Asterisks show statistically significant differences among the treatments (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Network of co-occurring bacterial genera based on correlation analysis for intercropping cultivations and cucumber monoculture. CK, saline–alkali soil not irrigated with reclaimed water; RW, saline–alkali soil irrigated with reclaimed water.</p>
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<p>Alpha and beta diversity in soil microbial communities across the different treatments. Alpha diversity of bacterial (<b>A</b>) and fungal (<b>B</b>) community among the two treatments, (<b>C</b>,<b>D</b>) represent the beta diversity of bacterial and fungal communities, respectively. CK: saline–alkali soil not irrigated with reclaimed water, RW: saline–alkali soil irrigated with reclaimed water. These indices were calculated for community richness, diversity, and coverage. <span class="html-italic">p</span>-values were analyzed using Kruskal-Wallis <span class="html-italic">H</span> test. Different lowercase letters show statistically significant differences.</p>
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<p>Ordination biplots from the redundancy analysis (RDA) were utilized to identify the relationships between soil bacterial and fungal communities (blue arrows) and soil properties (red arrows). (<b>A</b>) illustrates the relations between soil properties and bacterial communities at the phylum level; (<b>B</b>) presents the relations between soil properties and fungal communities, also at the phylum level. Mantel tests were conducted to examine the correlations between microbial community composition and diversity with soil properties. (<b>C</b>) shows how soil properties influence the composition and diversity of the soil bacterial community, while (<b>D</b>) depicts the relationships between soil properties and the fungal community. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. CK: saline–alkali soil not irrigated with reclaimed water, and RW: saline–alkali soil irrigated with reclaimed water.</p>
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<p>Partial least squares path modeling (PLS-PM) demonstrates the impact of reclaimed water irrigation, soil salinity (EC), available nutrients (AP, AN, and AK), total nutrients (TP, TN, and TK), and stoichiometry (C/N, C/P) on the soil microbial community. The path coefficients and coefficients of determination (<span class="html-italic">R</span><sup>2</sup>) were calculated following 999 bootstrap iterations. The blue lines indicate negative effects, while the red lines represent positive effects; the numbers on the lines denote the respective path coefficients. Models with different compositions were evaluated using the goodness of fit statistic. Data for evaluating bacterial and fungal communities were selected based on their relative abundance at the phylum level. The ACE and Shannon indices were employed to analyze microbial diversity. Statistical significance is indicated as follows: * <span class="html-italic">p</span> &lt; 0.05, and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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29 pages, 2633 KiB  
Review
Current Approaches for Genetic Manipulation of Streptomyces spp.—Key Bacteria for Biotechnology and Environment
by Sergii Krysenko
BioTech 2025, 14(1), 3; https://doi.org/10.3390/biotech14010003 - 2 Jan 2025
Viewed by 229
Abstract
Organisms from the genus Streptomyces feature actinobacteria with complex developmental cycles and a great ability to produce a variety of natural products. These soil bacteria produce more than 2/3 of antibiotics used in medicine, and a large variety of bioactive compounds for industrial, [...] Read more.
Organisms from the genus Streptomyces feature actinobacteria with complex developmental cycles and a great ability to produce a variety of natural products. These soil bacteria produce more than 2/3 of antibiotics used in medicine, and a large variety of bioactive compounds for industrial, medical and agricultural use. Although Streptomyces spp. have been studied for decades, the engineering of these bacteria remains challenging, and the available genetic tools are rather limited. Furthermore, most biosynthetic gene clusters in these bacteria are silent and require strategies to activate them and exploit their production potential. In order to explore, understand and manipulate the capabilities of Streptomyces spp. as a key bacterial for biotechnology, synthetic biology strategies emerged as a valuable component of Streptomyces research. Recent advancements in strategies for genetic manipulation of Streptomyces involving proposals of a large variety of synthetic components for the genetic toolbox, as well as new approaches for genome mining, assembly of genetic constructs and their delivery into the cell, allowed facilitation of the turnaround time of strain engineering and efficient production of new natural products at an industrial scale, but still have strain- and design-dependent limitations. A new perspective offered recently by technical advances in DNA sequencing, analysis and editing proposed strategies to overcome strain- and construct-specific difficulties in the engineering of Streptomyces. In this review, challenges and recent developments of approaches for Streptomyces engineering are discussed, an overview of novel synthetic biology strategies is provided and examples of successful application of new technologies in molecular genetic engineering of Streptomyces are highlighted. Full article
(This article belongs to the Section Industrial Biotechnology)
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<p>A scheme of the main interconnections of primary metabolic pathways in <span class="html-italic">Streptomyces</span>. Arrows indicate positive effects; dashed arrows indicate negative effects. The dotted lines indicate an uncharacterized or indirect regulation. Rectangles and orange color represent parts of the carbon metabolism; ovals and green color—nitrogen metabolism; diamond shape and blue color—phosphate metabolism. Glucose as the main carbon source in <span class="html-italic">Streptomyces</span> influences all three main components of the primary metabolism.</p>
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<p>Schematic representation of an actinobacterial cell with potential barriers to genetic manipulation. Many difficulties in <span class="html-italic">Streptomyces</span> engineering are connected to general challenges, such as lack of tools for DNA delivery, lack of suitable host strains and complex and multilayered cell-wall barrier. However, many challenges appear in the cell after the DNA transfer, such as degradation of introduced DNA, low recombination rates between the host chromosome and mobile genetic elements (plasmids), as well as different codon usage among strains.</p>
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<p>Overview of the DNA transfer systems in <span class="html-italic">Streptomyces</span>, including the parameters to be evaluated when applied to genetically manipulating strains. Due to the complex actinobacterial developmental cycle, difficulties in DNA transfer and stability may appear at different stages depending on the target (germinating spores or developed mycelium). Optimization steps that may be undertaken depend on the selected method.</p>
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<p>The modified Gibson assembly method for <span class="html-italic">Streptomyces</span>. Initially, three DNA fragments are assembled using a BAC vector. In the first step, the complementary overlaps between DNA inserts are 30 bp. Subsequently, the left, middle, and right assembled products from the first step are digested by <span class="html-italic">Nhe</span>I, <span class="html-italic">Nhe</span>I/<span class="html-italic">Nde</span>I, and <span class="html-italic">Nde</span>I, respectively. In the second step, the overlaps between DNA inserts are 45 bp.</p>
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<p>Schematic representation of the Cas-nuclease mediated generation of DNA double-strand breaks with subsequent endogenous DNA repair machinery. The guide RNA (sgRNA) contains a spacer/matching sequence that directs the Cas endonuclease to the complementary sequence. When the help of the protospacer adjacent motif (PAM), the Cas protein induces double-strand DNA breaks (DSB) in the target genome. During the non-homologous end-joining (NHEJ) pathway, repair proteins introduce insertions or Indels (deletions) because of the lack of a homolog repair template. If a homolog DNA segment is present (donor DNA), proteins of the homology-directed repair (HDR) system facilitate genomic recombination, enabling precise gene modifications.</p>
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<p>Design and strategy of TAR-based cloning and expression. Plasmid vectors should contain genetic elements for <span class="html-italic">Saccharomyces</span> (blue), <span class="html-italic">Escherichia coli</span> (green) and <span class="html-italic">Streptomyces</span> (red). In a three-step process, plasmid vectors are first introduced into yeast, where recombination events with the target BGC result in generation of Yeast Artificial Chromosomes (YACs). Afterwards, the genetic construct is transferred into the <span class="html-italic">Streptomyces</span> host through an intermediate yeast or <span class="html-italic">E. coli</span> host.</p>
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20 pages, 3377 KiB  
Article
Response of Soil Bacteria to Short-Term Nitrogen Addition in Nutrient-Poor Areas
by Hongbin Yin, Mingyi Xu, Qingyang Huang, Lihong Xie, Fan Yang, Chao Zhang, Gang Sha and Hongjie Cao
Microorganisms 2025, 13(1), 56; https://doi.org/10.3390/microorganisms13010056 - 1 Jan 2025
Viewed by 299
Abstract
Increasing nitrogen (N) addition induces soil nutrient imbalances and is recognized as a major regulator of soil microbial communities. However, how soil bacterial abundance, diversity, and community composition respond to exogenous N addition in nutrient-poor and generally N-limited regions remains understudied. In this [...] Read more.
Increasing nitrogen (N) addition induces soil nutrient imbalances and is recognized as a major regulator of soil microbial communities. However, how soil bacterial abundance, diversity, and community composition respond to exogenous N addition in nutrient-poor and generally N-limited regions remains understudied. In this study, we investigated the effects of short-term exogenous N additions on soil bacterial communities using quantitative polymerase chain reaction (PCR) and Illumina Miseq sequencing in an in situ N addition field experiment. The results showed that a low nitrogen addition increased the observed species (Sobs) of the bacterial community, and with the increased nitrogen addition, the Sobs of bacteria gradually decreased, especially the unique OTUs. The relative abundance of Proteobacteria, Actinobacteria, and Gemmatimonadetes increased with increasing nitrogen addition, whereas the relative abundance of Chloroflexi and Firmicutes decreased. Soil properties play an important role in bacterial community structure at phylum or genus levels. Short-term nitrogen addition increased the proportion of nodes from Actinobacteria and Proteobacteria in the co-occurrence network and enhanced the stability of the microbial network. Actinobacteria may play an important role in constructing the network. Our study aims to explore the effects of nitrogen addition on the diversity, composition, and structure of soil bacterial communities in nutrient-poor areas caused by ecological disturbances. Full article
(This article belongs to the Special Issue Microbial Communities and Nitrogen Cycling)
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<p>A map of the study area and its overview.</p>
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<p>Composition of bacteria of different nitrogen addition treatments on phyla level (<b>a</b>) and genera level (<b>b</b>).</p>
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<p>PCoA of bacterial communtiies at different nitrogen addition treatment on OTUs.</p>
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<p>Redundancy analysis (RDA) of relationship between soil properties and bacterial community structures at phylum level (<b>a</b>)and genus level (<b>b</b>)<b>.</b></p>
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<p>The taxonomy analysis of the threshold indicators (TITAN) showed that the relative abundance of the genera increased with the amount of nitrogen addition. In the figure, the positions of the black short lines in the red peak patterns are the change points observed by the index taxa of the screening criteria. The red peak patterns intersecting the black short lines are the 5th and 95th quantiles of the bootstrap distribution of the change points for each taxon, i.e., confidence or variability bands such as those illustrated in <a href="#microorganisms-13-00056-f005" class="html-fig">Figure 5</a>. In the figure, the color depth of the peak pattern is proportional to the indicator <span class="html-italic">z</span> value, so darker peak patterns are taxa with stronger relative responses to the nitrogen gradient.</p>
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<p>The taxonomy analysis of the threshold indicators (TITAN) showed that the relative abundance of the genera decreased with the amount of nitrogen addition. In the figure, the positions of the black short lines in the blue peak patterns are the change points observed by the index taxa of the screening criteria. The blue peak patterns intersecting the black short lines are the 5th and 95th quantiles of the bootstrap distribution of the change points for each taxon, i.e., confidence or variability bands such as those illustrated in the figure. In the figure, the color depth of the peak pattern is proportional to the indicator <span class="html-italic">z</span> value, so darker peak patterns are taxa with stronger relative responses to the nitrogen gradient.</p>
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<p>The co-occurrence networks and topological properties of the soil microorganisms in CK (<b>a</b>), N1 (<b>b</b>), N2 (<b>c</b>), N3 (<b>d</b>) and N4 (<b>e</b>), respectively. The size of each node was proportional to the number of degrees. The classification levels of the microorganisms in the co-occurrence network was phylum. The phyla with an average abundance of less than 1% were classified as “others”.</p>
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<p>A <span class="html-italic">Zi-Pi</span> plot showing the distribution of OTUs based on their topological roles in the bacteria networks under CK (<b>a</b>), N1 (<b>b</b>), N2 (<b>c</b>), N3 (<b>d</b>) and N4 (<b>e</b>), respectively. The threshold values of <span class="html-italic">Zi</span> and <span class="html-italic">Pi</span> for categorizing the OTUs were 2.5 and 0.62, respectively.</p>
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16 pages, 7312 KiB  
Article
Spatial Distribution and Driving Factors of Nitrogen Cycle Genes in Urban Landscape Lake
by Hua Zhong, Peng Li, Xin Xu, Maoting Ma, Chengjun Zhang, Lianfeng Du and Xuan Guo
Sustainability 2025, 17(1), 186; https://doi.org/10.3390/su17010186 - 30 Dec 2024
Viewed by 353
Abstract
Urban landscape lakes are increasingly at risk of nitrogen-induced eutrophication. Microbial nitrogen transformation plays a crucial role in reducing nitrogen levels in these lakes. However, the relationships between microbial communities, nitrogen functional genes, and nitrogen dynamics in water and sediment, along with their [...] Read more.
Urban landscape lakes are increasingly at risk of nitrogen-induced eutrophication. Microbial nitrogen transformation plays a crucial role in reducing nitrogen levels in these lakes. However, the relationships between microbial communities, nitrogen functional genes, and nitrogen dynamics in water and sediment, along with their underlying mechanisms, remain unclear. In this study, we systemically investigated the spatial distributions of physicochemical indicators in the overlying water and sediment in a typical urban landscape lake, Zizhuyuan Park, and the microbial communities and nitrogen cycling genes in the surface sediments of the lake connection (CO), side (SI), and center (CE) were evaluated via macrogenetic sequencing technology to analyze their relationships with environmental factors. The results revealed that the concentrations of TN, NO3, and NH4+ in the lake water were within the ranges of 1.36~2.84, 0.98~1.92, and 0.01~0.29 mg·L−1, respectively. The concentrations of TN, NO3, and NH4+ in the sediments ranged from 1.17~3.47 g·kg−1, 0.88~1.94 mg·kg−1, and 5.61~10.09 mg·kg−1, respectively. The contents of NH4+ in water, TN and NO3 in sediments were significantly different in spatial distribution (p < 0.05). At the CE site, the Shannon diversity index was the highest and differed significantly from the values at the SI and CO sites (p < 0.01).The sediments of Central Lake contained a total of 36 phyla and 1303 genera of microorganisms. Proteobacteria (62.88–64.83%) and Actinobacteria (24.84–26.62%) accounted for more than 85% of the microorganisms. Nitrospirae, Ignavibacteriae, and Bacteroidetes were significantly different (p < 0.05) at the CE, and Planctomycetes were significantly different (p < 0.05) at the CO. The functional gene nrfA exhibited the highest abundance, followed by napA, nosZ, nirS, hao, ureC, norB, nifH, nirK, hdhA, nifB, and amoA. The abundances of hao and nifH differed significantly at various locations in Central Lake (p < 0.05). The key nitrogen transformation processes in the sediments, ranked by contribution rate, were DNRA, denitrification, nitrification, ammoniation, nitrogen fixation, and anammox. The six nitrogen processes showed significant differences (p < 0.01) in spatial distribution. The pH, TN, NO3, NH4+, C/N ratio of the sediment, and NH4+ in the lake water impact the microbial community and nitrogen conversion process. The sediment should be cleaned regularly, and the water cycle should be strengthened in urban landscape lakes to regulate microorganisms and genes and ultimately reduce nitrogen and control eutrophic water. This study can provide a reference for improving and managing lake water environments in urban landscapes. Full article
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<p>(<b>a</b>) Location of Central Lake in Zizhuyuan Park with respect to Beijing, (<b>b</b>) collection sites for samples from Central Lake in Zizhuyuan Park, and (<b>c</b>) surrounding environment map of Central Lake in Zizhuyuan Park.</p>
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<p>Comparison of water and sediment physicochemical properties in the three locations (CE, CO, and SI) in Central Lake. Significance is indicated by * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001, NS: no significant difference. (<b>a</b>) TN contents of water, (<b>b</b>) NH<sub>4</sub><sup>+</sup> contents of water, (<b>c</b>) NO<sub>3</sub><sup>−</sup> contents of water, (<b>d</b>) NO<sub>2</sub><sup>−</sup> contents of water, (<b>e</b>) pH of water, (<b>f</b>) TN contents of sediment, (<b>g</b>) NH<sub>4</sub><sup>+</sup> contents of sediment, (<b>h</b>) NO<sub>3</sub><sup>−</sup> contents of sediment, (<b>i</b>) C/N ratio of sediment, and (<b>j</b>) pH of sediment. Abbreviations: W.TN, total nitrogen contents of water; W.NH<sub>4</sub><sup>+</sup>, NH<sub>4</sub><sup>+</sup> contents of water; W.NO<sub>3</sub><sup>−</sup>, NO<sub>3</sub><sup>−</sup> contents of water; W.NO<sub>2</sub><sup>−</sup>, NO<sub>2</sub><sup>−</sup> contents of water; W.pH, pH of water; S.TN, total nitrogen contents of sediment; S. NH<sub>4</sub><sup>+</sup>, NH<sub>4</sub><sup>+</sup> contents of sediment; S.NO<sub>3</sub><sup>−</sup>, NO<sub>3</sub><sup>−</sup> contents of sediment; S.C/N, total organic carbon/total nitrogen ratio of sediment; S.pH, pH of sediment.</p>
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<p>Distributions of bacterial species in sediment samples: (<b>a</b>) The abundance of bacteria in the bacterial community structure at the phylum level. (<b>b</b>) The 50 genera with the highest abundance among the bacterial community structures in the sediment samples. (<b>c</b>) The relative abundance of bacteria in the bacterial community structure at the phylum level.</p>
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<p>NMDS analysis of the microbial community in three different areas, namely CO, SI, and CE.</p>
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<p>Different bacterial distributions in sediments at different locations.</p>
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<p>Mantel test for microbial community structure and environmental factors. (Abbreviations: S, sediment; W, water.).</p>
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<p>Average relative abundance of each type of nitrogen functional gene (<b>a</b>) and the contribution of each nitrogen transformation process (<b>b</b>).</p>
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<p>PCoA of the relative abundances of nitrogen functional genes in sediment samples.</p>
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<p>Mantel test for nitrogen transformation process and environmental factors.</p>
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29 pages, 16155 KiB  
Article
The Positive Effects of Training and Time-Restricted Eating in Gut Microbiota Biodiversity in Patients with Multiple Myeloma
by Olga Czerwińska-Ledwig, Alicja Nowak-Zaleska, Małgorzata Żychowska, Katarzyna Meyza, Tomasz Pałka, Adrianna Dzidek, Agata Szlachetka, Artur Jurczyszyn and Anna Piotrowska
Nutrients 2025, 17(1), 61; https://doi.org/10.3390/nu17010061 - 27 Dec 2024
Viewed by 239
Abstract
Background: The physical activity of different groups of individuals results in the rearrangement of microbiota composition toward a symbiotic microbiota profile. This applies to both healthy and diseased individuals. Multiple myeloma (MM), one of the more common hematological malignancies, predominantly affects older adults. [...] Read more.
Background: The physical activity of different groups of individuals results in the rearrangement of microbiota composition toward a symbiotic microbiota profile. This applies to both healthy and diseased individuals. Multiple myeloma (MM), one of the more common hematological malignancies, predominantly affects older adults. Identifying an appropriate form of physical activity for this patient group remains a challenge. The aim of this study was to investigate the impact of a 6-week Nordic walking (NW) training program combined with a 10/14 time-restricted eating regimen on the gut microbiota composition of multiple myeloma patients. Methods: This study included healthy individuals as the control group (n = 16; mean age: 62.19 ± 5.4) and patients with multiple myeloma in remission (MM group; n = 16; mean age: 65.00 ± 5.13; mean disease duration: 57 months). The training intervention was applied to the patient group and consisted of three moderate-intensity sessions per week, individually tailored to the estimated physical capacity of each participant. The taxonomic composition was determined via 16S rRNA sequencing (V3–V9 regions). The microbiota composition was compared between the patient group and the control group. Results: The alpha and beta diversity metrics for species and genus levels differed significantly between the control and patient groups before the implementation of the NW program. In contrast, no differences were observed between the control and patient groups after the training cycle, indicating that the patients’ microbiota changed toward the pattern of the control group. This is confirmed by the lowest values of average dissimilarity between the MMB groups and the control at all taxonomic levels, as well as the highest one between the control group and the MMA patient group. The gut microbiota of the patients was predominantly represented by the phyla Firmicutes, Actinobacteria, Verrucomicrobia, Proteobacteria, and Bacteroidetes. Conclusions: The training, combined with time-restricted eating, stimulated an increase in the biodiversity and taxonomic rearrangement of the gut microbiota species. Full article
(This article belongs to the Collection Connection between Microbiome, Lifestyle and Diet)
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<p>Patient diagram flow.</p>
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<p>Graph for the studied alpha-diversity metrics: Simpson’s Index (1-D), Shannon Index, and Fisher-alpha parameter (median) considering the taxonomic levels of the microbiota and the division of the study sample into groups (MyelomaA—group of patients before starting the NW program; MyelomaB—group of patients after completing the Nordic walking program; control).</p>
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<p>Graph for the studied alpha-diversity metrics: Simpson’s Index (1-D), Shannon Index, and Fisher-alpha parameter (median) considering the taxonomic levels of the microbiota and the division of the study sample into groups (MyelomaA—group of patients before starting the NW program; MyelomaB—group of patients after completing the Nordic walking program; control).</p>
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<p>Mean divergence between the study groups (MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program at the phylum level.</p>
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<p>Mean divergence between the study groups (MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program) at the class level.</p>
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<p>Mean divergence between the study groups (MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program) at the family level.</p>
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<p>Mean divergence between the study groups (MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program) at the order level.</p>
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<p>Mean divergence between the study groups (MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program) at the genus level.</p>
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<p>Mean divergence between the study groups (MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program) at the species level.</p>
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<p>Average abundance of taxa for phyla group MMA and MMB expressed as percentage (outer circle—MMB; inner circle—MMA). MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program.</p>
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<p>Average abundance for classes group MMA and MMB expressed as percentage (outer circle—MMB; inner circle—MMA). MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program.</p>
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<p>Average abundance for families group MMA and MMB expressed as percentage (outer circle—MMB; inner circle—MMA). MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program.</p>
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<p>Average abundance for orders group MMA and MMB expressed as percentage (outer circle—MMB; inner circle—MMA). MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program.</p>
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<p>Average abundance within genus for group MMA and MMB expressed as percentage (outer circle—MMB; inner circle—MMA). MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program.</p>
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<p>Average abundance for species group MMA and MMB expressed as percentage (outer circle—MMB; inner circle—MMA). MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program.</p>
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<p>The percentage contribution of taxa within the taxonomic ranks (Phylum, Class, Family, Order, Genus, Species) with respect to the group divisions: MMA, MMB, Control. Phylum level based on the microbiota analysis of all studied samples (<b>A</b>); phylum level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>B</b>). Class level based on the microbiota analysis of all studied samples (<b>C</b>); class level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>D</b>). Family level based on the microbiota analysis of all studied samples (<b>E</b>); family level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>F</b>). Order level based on the microbiota analysis of all studied samples (<b>G</b>); order level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>H</b>). Genus level based on the microbiota analysis of all studied samples (<b>I</b>); genus level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>J</b>). Species level based on the microbiota analysis of all studied samples (<b>K</b>); species level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>L</b>).</p>
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<p>The percentage contribution of taxa within the taxonomic ranks (Phylum, Class, Family, Order, Genus, Species) with respect to the group divisions: MMA, MMB, Control. Phylum level based on the microbiota analysis of all studied samples (<b>A</b>); phylum level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>B</b>). Class level based on the microbiota analysis of all studied samples (<b>C</b>); class level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>D</b>). Family level based on the microbiota analysis of all studied samples (<b>E</b>); family level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>F</b>). Order level based on the microbiota analysis of all studied samples (<b>G</b>); order level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>H</b>). Genus level based on the microbiota analysis of all studied samples (<b>I</b>); genus level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>J</b>). Species level based on the microbiota analysis of all studied samples (<b>K</b>); species level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>L</b>).</p>
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<p>The percentage contribution of taxa within the taxonomic ranks (Phylum, Class, Family, Order, Genus, Species) with respect to the group divisions: MMA, MMB, Control. Phylum level based on the microbiota analysis of all studied samples (<b>A</b>); phylum level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>B</b>). Class level based on the microbiota analysis of all studied samples (<b>C</b>); class level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>D</b>). Family level based on the microbiota analysis of all studied samples (<b>E</b>); family level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>F</b>). Order level based on the microbiota analysis of all studied samples (<b>G</b>); order level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>H</b>). Genus level based on the microbiota analysis of all studied samples (<b>I</b>); genus level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>J</b>). Species level based on the microbiota analysis of all studied samples (<b>K</b>); species level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>L</b>).</p>
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<p>The percentage contribution of taxa within the taxonomic ranks (Phylum, Class, Family, Order, Genus, Species) with respect to the group divisions: MMA, MMB, Control. Phylum level based on the microbiota analysis of all studied samples (<b>A</b>); phylum level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>B</b>). Class level based on the microbiota analysis of all studied samples (<b>C</b>); class level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>D</b>). Family level based on the microbiota analysis of all studied samples (<b>E</b>); family level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>F</b>). Order level based on the microbiota analysis of all studied samples (<b>G</b>); order level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>H</b>). Genus level based on the microbiota analysis of all studied samples (<b>I</b>); genus level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>J</b>). Species level based on the microbiota analysis of all studied samples (<b>K</b>); species level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>L</b>).</p>
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<p>The percentage contribution of taxa within the taxonomic ranks (Phylum, Class, Family, Order, Genus, Species) with respect to the group divisions: MMA, MMB, Control. Phylum level based on the microbiota analysis of all studied samples (<b>A</b>); phylum level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>B</b>). Class level based on the microbiota analysis of all studied samples (<b>C</b>); class level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>D</b>). Family level based on the microbiota analysis of all studied samples (<b>E</b>); family level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>F</b>). Order level based on the microbiota analysis of all studied samples (<b>G</b>); order level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>H</b>). Genus level based on the microbiota analysis of all studied samples (<b>I</b>); genus level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>J</b>). Species level based on the microbiota analysis of all studied samples (<b>K</b>); species level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>L</b>).</p>
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<p>The percentage contribution of taxa within the taxonomic ranks (Phylum, Class, Family, Order, Genus, Species) with respect to the group divisions: MMA, MMB, Control. Phylum level based on the microbiota analysis of all studied samples (<b>A</b>); phylum level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>B</b>). Class level based on the microbiota analysis of all studied samples (<b>C</b>); class level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>D</b>). Family level based on the microbiota analysis of all studied samples (<b>E</b>); family level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>F</b>). Order level based on the microbiota analysis of all studied samples (<b>G</b>); order level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>H</b>). Genus level based on the microbiota analysis of all studied samples (<b>I</b>); genus level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>J</b>). Species level based on the microbiota analysis of all studied samples (<b>K</b>); species level based on the microbiota analysis of the studied groups: MMA/MMB, MMA/Control, MMB/Control (<b>L</b>).</p>
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<p>UMAP analysis performed based on Bray–Curtis metric for particular taxonomic ranks (MMA—blue plus; MMB—pink square; Control—violet triangle). The area where 95% of the population points are expected to be found (95% ellipses) was circled in the same colors. (MMA—group of patients before starting the NW program; MMB—group of patients after completing the Nordic walking program).</p>
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23 pages, 8548 KiB  
Article
Comparative Analysis of Meat Quality and Hindgut Microbiota of Cultured and Wild Bighead Carp (Hypophthalmichthys nobilis, Richardson 1845) from the Yangtze River Area
by Abdullateef Mukhtar Muhammad, Chang Yang, Bo Liu, Cunxin Sun, Linghong Miao, Xiaochuan Zheng, Liangkun Pan, Dong Xia and Qun-Lan Zhou
Microorganisms 2025, 13(1), 20; https://doi.org/10.3390/microorganisms13010020 - 25 Dec 2024
Viewed by 298
Abstract
Wild fish are often considered more nutritionally valuable than cultured fish. This study aimed to elucidate the relationship between the gut microbiota and meat quality through the gut–muscle axis. Therefore, cultured and wild bighead carp (Hypophthalmichthys nobilis, Richardson 1845) from the [...] Read more.
Wild fish are often considered more nutritionally valuable than cultured fish. This study aimed to elucidate the relationship between the gut microbiota and meat quality through the gut–muscle axis. Therefore, cultured and wild bighead carp (Hypophthalmichthys nobilis, Richardson 1845) from the Yangtze River were investigated to compare the differences in the meat quality and gut microbiota composition. Cultured bighead carp were collected from four intensive ponds along the Yangtze River area, while wild bighead carp were obtained from three different sites in the Yangtze River. The results showed that wild bighead carp muscle had significantly higher total saturated fatty acid (∑SFA) and total ω − 3 polyunsaturated fatty acid (∑n − 3 PUFA) content and water-holding capacity and lower lipid, histidine, and total ω − 6 polyunsaturated fatty acid (∑n − 6 PUFA) content than cultured bighead carp, while the muscle texture was not significantly different between the two groups, with the exception of the resilience. Moreover, the hindgut microbiota was analyzed using 16S rRNA high-throughput sequencing. The alpha and beta diversity differences between the cultured and wild groups were significant. The LEfSe analysis revealed Mycobacterium, Longivirga, and Acetobacteroides as biomarkers in cultured bighead carp, while Clostridium_T and other Firmicutes-associated genera were predominant in wild bighead carp. Regarding the relationship between the hindgut microbiota and meat quality, Mycobacterium exhibited a positive correlation with the muscle n-6 PUFA content and a negative correlation with muscle n − 3 PUFAs, while Clostridium_T exhibited the opposite pattern. According to the ecological network, the abundance of Actinobacteria could serve as a significant indicator of variations in the abundance of Mycobacterium and Clostridium_T. Consequently, differences in meat quality, particularly in the fatty acid composition, were observed between wild and cultured bighead carp. These differences may be associated with variations in the hindgut microbiota, shedding light on the gut–muscle axis. Full article
(This article belongs to the Section Veterinary Microbiology)
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<p>Sampling locations of cultured and wild bighead carp.</p>
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<p>E-nose analysis of flavor of cultured and wild bighead carp from the Yangtze River area. (<b>A</b>) Radar chart. (<b>B</b>) Principal component analysis (cultured <span class="html-italic">n</span> = 12, wild <span class="html-italic">n</span> = 9).</p>
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<p>Hindgut microbiota composition in bighead carp between cultured and wild environments at the phylum and genus levels (<span class="html-italic">n</span> = 9). (<b>A</b>) Stacked column chart representing the phylum composition with top 15 abundance. (<b>B</b>) Stacked column chart representing the genus composition with top 15 abundance. (<b>C</b>) Bar chart of phyla with significant differences between two groups. (<b>D</b>) Bar chart of genera with significant differences between two groups. * and rectangles in red indicate high abundance in wild bighead carp, while * and rectangles in blue indicate high abundance in cultured bighead carp.</p>
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<p>Disparities in alpha and beta diversity of bighead carp hindgut microbiota between cultured and wild environments (<span class="html-italic">n</span> = 9). (<b>A</b>) Calculation of Chao1, Good’s coverage, Faith’s pd, Shannon, and the observed species for bighead carp with varying dietary habits in cultured and wild environments; (<b>B</b>) PCoA plot illustrating the gut microbial structure of bighead carp growing in different environments. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Linear discriminant effect size (LEfSe) analysis of gut microbiota composition of bighead carp between cultured and wild environments (LDA &gt; 4) (<span class="html-italic">n</span> = 9).</p>
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<p>Metabolic functional profiles of bighead carp gut microbiota between cultured and wild environments (<span class="html-italic">n</span> = 9). (<b>A</b>,<b>B</b>) Metabolic functional profiles of bighead carp gut microbiota between cultured and wild environments at MetaCyc level 1 and level 2; (<b>C</b>) PCoA plot for functional units of bighead carp gut microbiota between cultured and wild environments.</p>
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<p>The correlations of the key gut bacteria and fish meat quality components (amino acids, fatty acids, texture, and water-holding capacity) with significant changes (<span class="html-italic">n</span> = 18). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p &lt;</span> 0.001.</p>
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<p>Correlation-based network analysis of hindgut microbiota community (<span class="html-italic">n</span> = 18). (<b>A</b>) Interspecies interaction network of bighead carp hindgut microbiota in cultured and wild bighead carp. Each node represents a genus. Node colors indicate genus affiliated with different major phyla. The green edge indicates a negative interaction between two individual nodes, whereas the red edge indicates a positive interaction. (<b>B</b>) Topological properties of hindgut microbiota community network.</p>
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16 pages, 2216 KiB  
Article
Exploring the Effects of Imidacloprid on Liver Health and the Microbiome in Rats: A Comprehensive Study
by Alaa T. Qumsani
Microorganisms 2025, 13(1), 15; https://doi.org/10.3390/microorganisms13010015 - 25 Dec 2024
Viewed by 246
Abstract
The current study investigates the systemic effects of imidacloprid, one of the most widely used neonicotinoid insecticides, on the liver and gut microbiome of rats in detail. With consideration of recent discussions on the potential harmfulness of imidacloprid to environmental and human health, [...] Read more.
The current study investigates the systemic effects of imidacloprid, one of the most widely used neonicotinoid insecticides, on the liver and gut microbiome of rats in detail. With consideration of recent discussions on the potential harmfulness of imidacloprid to environmental and human health, the aim was to investigate the influence of this compound in the framework of controlled exposure at different dosages, namely, IMI-5, IMI-10, and IMI-30. Histopathological examination showed that liver morphology changed significantly with the dose, including in terms of cellular disorganization and signs of stress, with an alteration in the hepatic architecture. Morphological changes were related to disturbances in the activity of liver enzymes, reflecting deteriorating liver function with increased imidacloprid exposure. In parallel with this, a deep analysis of the gut microbiome revealed dramatic changes in microbial diversity and composition. Alpha diversity, represented by the Chao1 and Shannon indices, was significantly reduced with an increased dosage of imidacloprid. Subsequent beta diversity analysis, as visualized by principal component analysis, showed distinct clustering among the microbial communities, separated well between control and imidacloprid-treated groups, especially at higher dosages. Taxonomic analysis revealed an increase in the Firmicutes/Bacteroidetes ratio and a change in key phyla including Actinobacteria, Bacteroidetes, and Verrucomicrobia. A heatmap and bar charts further confirmed dose-dependent changes in microbial abundance. These changes point toward imidacloprid-induced dysbiosis, a reduction in microbial diversity, and an imbalance in the F/B ratio, usually associated with metabolic disorders. Overall, given these findings, it would seem that imidacloprid does indeed impose serious negative impacts on both liver function and gut microbiota composition and may have further impacts on health and ecological safety. Full article
(This article belongs to the Section Microbiomes)
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<p>This figure illustrates the effects of imidacloprid (IMI) on body weight gain in various groups of rats. The groups are designated as follows: C for the control group, IMI5 for the group exposed to 5 mg/L of imidacloprid, IMI10 for the group exposed to 10 mg/L, and IMI30 for the group exposed to 30 mg/L. <a href="#microorganisms-13-00015-f001" class="html-fig">Figure 1</a> shows how body weight fluctuated in the rats throughout the experiment. Data are expressed as mean ± standard deviation (n = 8–10), with significant differences noted at <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 0.01, and <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>(<b>A</b>–<b>E</b>). The impact of imidacloprid on various oxidative stress markers and antioxidant defense parameters in rats exposed to the compound. The subplots show the following indicators: (<b>A</b>) catalase (CAT), (<b>B</b>) superoxide dismutase (SOD), (<b>C</b>) glutathione-S-transferase (GST) activity (measured in U/g tissue), (<b>D</b>) glutathione peroxidase (GPx), and (<b>E</b>) malondialdehyde (MDA) (expressed as nmol/g tissue). The data are presented as the mean ± standard deviation (n = 10). Statistical significance is marked as * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to the control group.</p>
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<p>(<b>A</b>–<b>E</b>). The results of serum lipid analysis in rats exposed to different concentrations of imidacloprid. The subplots illustrate the concentrations of key lipid markers, including low-density lipoprotein (LDL) (<b>A</b>)—LDL levels were significantly elevated in imidacloprid-treated groups compared to the control group, with the increase becoming more pronounced at higher doses. Free Fatty Acids (FFA) (<b>B</b>)—a dose-dependent rise in FFA concentrations was observed, with the highest levels recorded in the group receiving the IMI-30 dose. Triglycerides (TG) (<b>C</b>)—similar to LDL and FFA levels, TG levels were also significantly elevated in a dose-dependent manner, indicating that imidacloprid influences lipid metabolism. Total cholesterol (TC) (<b>D</b>)—imidacloprid exposure resulted in increased TC levels, with the highest concentrations found in the IMI-30 group. High-density lipoprotein (HDL) (<b>E</b>)—in contrast to the other lipid parameters, HDL levels showed a reduction with increasing doses of imidacloprid. All data are presented as mean ± standard deviation (n = 10), with statistical significance indicated at * <span class="html-italic">p</span> &lt; 0.05 compared to the control group. The results suggest that imidacloprid alters lipid metabolism, leading to elevated LDL, FFA, TG, and TC levels along with a reduction in HDL, which may have implications for cardiovascular health.</p>
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<p>((<b>1</b>–<b>4</b>) and (<b>A</b>–<b>C</b>)). The hepatotoxic effects of imidacloprid (IMI) on rat liver tissue, showing a clear dose-dependent impact. In the control group, liver tissue appeared healthy with intact hepatocytes and a well-defined central vein. At a low dose (IMI-5), only minor alterations were seen, while the IMI-10 group showed slight disorganization and sinusoidal dilation, indicating early signs of liver stress. The most severe changes occurred at the IMI-30 dose, where a significant disruption to cellular structure and signs of liver damage were evident. Additionally, there was a marked increase in the liver-to-body weight ratio (<b>A</b>), increased liver congestion (<b>B</b>), and higher levels of inflammation (<b>C</b>) as the dose increased, with the IMI-30 group showing the most pronounced effects. These findings suggest that imidacloprid causes progressive liver damage, inflammation, and congestion, with an increase in severity at higher doses. Statistical significance is denoted as * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>(<b>A</b>–<b>I</b>). The significant effects of imidacloprid on the gut microbiota across different treatment groups, with adjusted labels for clarity: (<b>A</b>) The bacterial phyla proportions, with labels rotated for easier reading, display notable shifts across the control and imidacloprid-treated groups. Increased proportions of <span class="html-italic">Firmicutes</span> and <span class="html-italic">Verrucomicrobia</span> were observed in the IMI-10 and IMI-30 groups, while Bacteroidetes proportions decreased. (<b>B</b>) The Shannon diversity index shows a clear decrease in microbial diversity as imidacloprid concentrations increase. The control group maintained the highest diversity, while IMI-30 exhibited the lowest, reflecting the dose-dependent reduction in microbial diversity. (<b>C</b>) The <span class="html-italic">Firmicutes</span>/<span class="html-italic">Bacteroidetes</span> (F/B) ratio shows a clear increase with higher imidacloprid doses, with proper spacing between labels. This shift suggests an alteration in gut microbial composition that may have health implications. (<b>D</b>) The heatmap highlights bacterial abundance across the different treatment groups, showing a clear increase in <span class="html-italic">Verrucomicrobia</span> and a decrease in Bacteroidetes with higher imidacloprid doses. (<b>E</b>) The Chao1 diversity index, with ordered and clear labels, shows a decrease in species richness with increasing imidacloprid exposure. This reduction was most evident in the IMI-30 group. (<b>F</b>) The PCoA plot demonstrates the distinct separation of microbial communities across treatment groups, with proper spacing between labels. The control group was clearly separated from IMI-treated groups, particularly at higher doses. (<b>G</b>) Microbial characteristics are shown with rotated labels for clarity, depicting changes in the proportions of Gram-positive, Gram-negative, aerobic, and anaerobic bacteria across the groups. (<b>H</b>) The <span class="html-italic">Firmicutes</span>/<span class="html-italic">Bacteroidetes</span> proportions, with rotated labels for clarity, illustrate the increasing dominance of Firmicutes and decreasing Bacteroidetes with higher imidacloprid doses. (<b>I</b>) Gel electrophoresis analysis of an 16S rRNA gene amplification of microbial DNA extracted from fecal samples of rats treated with imidacloprid at different doses (5 mg/L, 10 mg/L, and 30 mg/L). The DNA ladder is present in lane 1, and microbial DNA samples from the control and treated groups are visible in lanes 2–11. Clear bands indicate the successful amplification of the V3–V4 region of the 16S rRNA gene, used for subsequent bioinformatics analysis.</p>
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<p>(<b>A</b>–<b>E</b>). The impact of IMI treatment on the microbial community, showing a decline in the Simpson diversity index as the IMI dosage increased, indicating reduced microbial diversity. The proportion of Gram-positive bacteria increased with higher IMI doses, while Gram-negative bacteria decreased. Additionally, the treatment led to a shift from aerobic to anaerobic bacteria, with anaerobes becoming more dominant in the higher-dose groups. These results suggest that IMI treatments significantly alter the structure and dynamics of the microbial community.</p>
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14 pages, 679 KiB  
Review
Biocontrol of Mycotoxigenic Fungi by Actinobacteria
by Louise Maud, Nathalie Barakat, Julie Bornot, Selma P. Snini and Florence Mathieu
J. Fungi 2025, 11(1), 4; https://doi.org/10.3390/jof11010004 - 24 Dec 2024
Viewed by 380
Abstract
Actinobacteria are well known for their production of metabolites of interest. They have been previously studied to identify new antibiotics in medical research and for their ability to stimulate plant growth in agronomic research. Actinobacteria represents a real source of potential biocontrol agents [...] Read more.
Actinobacteria are well known for their production of metabolites of interest. They have been previously studied to identify new antibiotics in medical research and for their ability to stimulate plant growth in agronomic research. Actinobacteria represents a real source of potential biocontrol agents (BCAs) today. With the aim of reducing the use of phytosanitary products by 50% with the different Ecophyto plans, a possible application is the fight against mycotoxin-producing fungi in food matrices and crops using BCAs. To deal with this problem, the use of actinobacteria, notably belonging to the Streptomyces genus, or their specialized metabolites seems to be a solution. In this review, we focused on the impact of actinobacteria or their metabolites on the development of mycotoxigenic fungi and mycotoxin production on the one hand, and on the other hand on their ability to detoxify food matrices contaminated by mycotoxins. Full article
(This article belongs to the Special Issue Mycotoxin Contamination and Control in Food)
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<p>Example of flowchart to determine the mode of action of actinobacteria.</p>
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19 pages, 7580 KiB  
Article
Terpinen-4-ol Improves the Intestinal Barrier Function of the Colon in Immune-Stressed Weaning Piglets
by Lihuai Yu, Guangzhi Qiu, Xiaomu Yu, Jianwei Zhao, Jun Liu, Hongrong Wang and Li Dong
Animals 2025, 15(1), 9; https://doi.org/10.3390/ani15010009 - 24 Dec 2024
Viewed by 249
Abstract
The aim of this study was to investigate the effects of terpinen-4-ol (TER) supplementation on the intestinal barrier function of pigs. Five groups of fifty 28-day-old piglets with comparable body weights were randomly assigned to the following groups: the control group (CON), the [...] Read more.
The aim of this study was to investigate the effects of terpinen-4-ol (TER) supplementation on the intestinal barrier function of pigs. Five groups of fifty 28-day-old piglets with comparable body weights were randomly assigned to the following groups: the control group (CON), the lipopolysaccharide group (LPS), the low TER group (PLT), the middle TER group (PMT), and the high TER group (PHT). The basal diet was given to the CON and LPS groups, and 30, 60, or 90 mg/kg TER was added to the basal diet for the TER groups. After the 21-day trial period, piglets in the LPS and TER groups received an intraperitoneal injection of 100 μg/kg body weight of LPS, whereas the piglets in the CON group received an injection of 0.9% normal saline solution. The results showed that LPS stimulation resulted in a decrease (p < 0.05) in the depth of colonic crypts in piglets, which was greater (p < 0.05) in the TER group. Compared with those in the CON group, the number of goblet cells and MUC2 expression were decreased in the colon of piglets in the LPS group, while these parameters were increased in the PMT group (p < 0.05). The malondialdehyde (MDA) content was greater in the colon of the LPS group than in that of the CON group, while the activities of glutathione peroxidase (GSH-Px), superoxide dismutase (SOD), and catalase (CAT) were lower in the colon of the LPS group; conversely, the MDA content was lower in the colons of the PLT and PMT groups than in those of the LPS group (p < 0.05). TER also reduced (p < 0.05) LPS-induced upregulation of IL-1β and TNF-α expression, along with the relative gene expression of NLRP3, ASC, and caspase-1 in the colon of piglets (p < 0.05). Compared with those in the CON group, the abundances of Firmicutes and UCG-005 in the LPS group were lower (p < 0.05), and those in the TER group were significantly greater than those in the LPS group. Compared with those in the CON group, the abundance of Proteobacteria in the LPS group increased (p < 0.05), while the abundance of Actinobacteria and Phascolarctobacterium increased (p < 0.05) in the colon of the PHT group compared with that in the LPS group. In conclusion, TER effectively improved the intestinal barrier function of the colon in weaning piglets. Based on the results of this study, the appropriate dose of TER in the diets of weaning piglets was 60 mg/kg. Full article
(This article belongs to the Section Pigs)
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<p>The effect of terpinen-4-ol on the colon morphology and structure of immune-stressed piglets. (<b>A</b>) Colon tissue HE, PAS, and immunohistochemical staining (100× magnification). (<b>B</b>) Depth of crypt. (<b>C</b>) Number of goblet cells. (<b>D</b>) MUC2 positive area. The data are represented as mean ± SD, n = 8. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The effect of terpinen-4-ol on the activity and gene expression of antioxidant enzymes in the colon of immune-stressed piglets. (<b>A</b>) <span class="html-italic">SOD</span> enzyme activity. (<b>B</b>) <span class="html-italic">GSH-Px</span> enzyme activity. (<b>C</b>) <span class="html-italic">CAT</span> enzyme activity. (<b>D</b>) MDA enzyme activity. (<b>E</b>) T-AOC enzyme activity. (<b>F</b>) <span class="html-italic">SOD</span> gene expression. (<b>G</b>) <span class="html-italic">GSH-Px</span> gene expression. (<b>H</b>) <span class="html-italic">CAT</span> gene expression. The data are represented as mean ± SD, n = 8. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The effect of terpinen-4-ol on the content and gene expression of colitis factors in immune-stressed piglets. (<b>A</b>) <span class="html-italic">TNF-a</span> content. (<b>B</b>) <span class="html-italic">IL-1β</span> content. (<b>C</b>) <span class="html-italic">IL-10</span> content. (<b>D</b>) <span class="html-italic">TNF-a</span> gene expression and (<b>E</b>) <span class="html-italic">IL-18</span> gene expression. (<b>F</b>) <span class="html-italic">IL-1 β</span> gene expression. The data are represented as mean ± SD, n = 8. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The effect of terpinen-4-ol on the expression of colitis-related genes in immune-stressed piglets. (<b>A</b>) <span class="html-italic">NLRP3</span> gene expression. (<b>B</b>) <span class="html-italic">ASC</span> gene expression. (<b>C</b>) <span class="html-italic">Caspase-1</span> gene expression. The data are represented as mean ± SD, n = 8. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Terpinen-4-ol on the colon microbiota α and β. The impact of diversity analysis. (<b>A</b>) Chao1 index. (<b>B</b>) Shannon index. (<b>C</b>) Simpson index. (<b>D</b>) ACE index. (<b>E</b>) Principal component analysis. The data are represented as mean ± SD, n = 8. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The effect of terpinen-4-ol on the gut microbiota of immune-stressed piglets. (<b>A</b>) Bacterial taxonomy analysis of gut microbiota at the phylum level. (<b>B</b>) Relative abundance of <span class="html-italic">Firmicutes</span>. (<b>C</b>) Relative abundance of <span class="html-italic">Bacteroidota</span>. (<b>D</b>) Relative abundance of <span class="html-italic">Proteobacteria</span>. (<b>E</b>) Relative abundance of <span class="html-italic">Desulfobacteriota</span>. (<b>F</b>) Relative abundance of <span class="html-italic">Actinobacteriota.</span> The data are represented as mean ± SD, n = 8. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The effect of terpinen-4-ol on the gut microbiota of immune-stressed piglets. (<b>A</b>) Taxonomic analysis of gut microbiota at the genus level. (<b>B</b>) <span class="html-italic">UCG_ 005</span> relative abundance. (<b>C</b>) Relative abundance of <span class="html-italic">Alloprevotella</span>. (<b>D</b>) <span class="html-italic">Muribaculaceae</span> unclassified relative abundance. (<b>E</b>) <span class="html-italic">Lactobacillus</span> relative abundance. (<b>F</b>) <span class="html-italic">Lachnospiraceae</span> unclassified relative abundance. (<b>G</b>) <span class="html-italic">Prevotella</span> relative abundance. (<b>H</b>) <span class="html-italic">Phascolarium</span> relative abundance. (<b>I</b>) <span class="html-italic">Christensenaceae R-7_group</span> relative abundance. (<b>J</b>) <span class="html-italic">UCG-002</span> relative abundance. The data are represented as mean ± SD, n = 8. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The effect of terpinen-4-ol on the gut microbiota of immune-stressed piglets. (<b>A</b>) Taxonomic analysis of gut microbiota at the genus level. (<b>B</b>) <span class="html-italic">UCG_ 005</span> relative abundance. (<b>C</b>) Relative abundance of <span class="html-italic">Alloprevotella</span>. (<b>D</b>) <span class="html-italic">Muribaculaceae</span> unclassified relative abundance. (<b>E</b>) <span class="html-italic">Lactobacillus</span> relative abundance. (<b>F</b>) <span class="html-italic">Lachnospiraceae</span> unclassified relative abundance. (<b>G</b>) <span class="html-italic">Prevotella</span> relative abundance. (<b>H</b>) <span class="html-italic">Phascolarium</span> relative abundance. (<b>I</b>) <span class="html-italic">Christensenaceae R-7_group</span> relative abundance. (<b>J</b>) <span class="html-italic">UCG-002</span> relative abundance. The data are represented as mean ± SD, n = 8. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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27 pages, 3169 KiB  
Article
GC/MS Fatty Acid Profile of Marine-Derived Actinomycetes from Extreme Environments: Chemotaxonomic Insights and Biotechnological Potential
by Marlene B. Cunha, André F. Jorge, Maria João Nunes, Joana R. Sousa, Maria João Lança, Marco Gomes da Silva and Susana P. Gaudêncio
Mar. Drugs 2025, 23(1), 1; https://doi.org/10.3390/md23010001 - 24 Dec 2024
Viewed by 496
Abstract
This study investigated the fatty acids (FA) profile of 54 actinomycete strains isolated from marine sediments collected off the Portugal continental coast, specifically from the Estremadura Spur pockmarks field, by GC/MS. Fatty acid methyl esters (FAMEs) were prepared from the ethyl acetate lipidic [...] Read more.
This study investigated the fatty acids (FA) profile of 54 actinomycete strains isolated from marine sediments collected off the Portugal continental coast, specifically from the Estremadura Spur pockmarks field, by GC/MS. Fatty acid methyl esters (FAMEs) were prepared from the ethyl acetate lipidic extracts of these strains and analyzed by gas chromatography–mass spectrometry (GC/MS), with FA identification performed using the NIST library. The identified FAs varied from C12:0 to C20:0, where 32 distinct FAs were identified, including 7 branched-chain fatty acids (BCFAs), 9 odd-chain fatty acids (OCFAs), 8 monounsaturated fatty acids (MUFAs), 6 saturated fatty acids (SFAs), 1 polyunsaturated fatty acid (PUFA), and 1 cyclic chain fatty acid (CCFA). The average expressed content was BCFA (47.54%), MUFA (28.49%), OCFA (26.93%), and SFA (22.16%), of which i-C16:0, C18:1ω9, and C16:0 were predominant, while PUFA (3.58%) and CCFA (0.41%) were identified as minor components. The identified BCFA were i-C16:0, a-C15:0, i-C15:0, i-C15:1ω6, a-C16:0, a-C14:0, and i-C17:0, which include combined branching and unsaturation and branching and odd. SFAs were present in all species, with C16:0 and C18:0 being the most representative. Rare OCFAs C19:1ω9, C17:1ω7, C15:0, and C17:0 were expressed. PUFA C18:1ω9 was detected; within this class, omega families ω9, ω7, ω6, and ω5 were identified, and no ω3 was detected. The only CCFA was benzene-butanoic acid (benzene-C4:0). These findings highlight the metabolic versatility of actinomycetes, providing valuable insights into microbial chemotaxonomy and offering promising biochemical leads for the development of biofuel, nutraceutical, and antifungal agents. Furthermore, these results underline the diversity and biotechnological potential of FAs in actinomycetes, uncovering their potential to be used as microbial cell factories, and paving the way for innovations in biofuels, pharmaceuticals, and eco-friendly industrial products. Full article
(This article belongs to the Special Issue Marine Omics for Drug Discovery and Development)
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<p>Profile of fatty acids’ main classes (expressed in %) from the ethyl acetate lipid extracts of the actinomycetes species isolated from marine sediments of the Estremadura Spur pockmarks.</p>
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<p>Individual SFA profile of the total SFAs (%) identified in ethyl acetate lipid extracts by actinomycetes species isolated from marine sediments of the Estremadura Spur pockmarks.</p>
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<p>MUFA content in the total profile of FAMEs in actinomycete species isolated from marine sediments of the Estremadura Spur, with emphasis on C18:1ω9. Values expressed in % in relation to the total identified FA.</p>
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<p>Omega families (ω9, ω7, ω6, and ω5) present in the FAME profile of marine actinobacteria species isolated from marine sediments of the Estremadura Spur.</p>
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<p>BCFAs comprising the FAME profile identified in the actinomycetes species.</p>
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<p>Profiling of the FA classes produced by the actinomycetes genera.</p>
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<p>PCA illustrating the FA classes profile according to the actinomycetes genera. The colors correspond to the genera of the actinomycetes.</p>
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17 pages, 3077 KiB  
Article
Effects of Acute Salinity Stress on the Histological and Bacterial Community Structure and Function in Intestine of Stichopus monotuberculatus
by Lianghua Huang, Hui Wang, Chuanyan Pan, Xueming Yang, Guoqing Deng, Yaowen Meng, Yongxiang Yu, Xiuli Chen and Shengping Zhong
Mar. Drugs 2024, 22(12), 576; https://doi.org/10.3390/md22120576 - 23 Dec 2024
Viewed by 458
Abstract
This study focused on Stichopus monotuberculatus and conducted stress experiments at salinity levels of 20‰ and 40‰. Intestinal histological changes and the structural characteristics of the intestinal flora of S. monotuberculatus under salinity stress were analyzed. The results show that acute salinity stress [...] Read more.
This study focused on Stichopus monotuberculatus and conducted stress experiments at salinity levels of 20‰ and 40‰. Intestinal histological changes and the structural characteristics of the intestinal flora of S. monotuberculatus under salinity stress were analyzed. The results show that acute salinity stress inflicts varying degrees of damage to the intestinal tissues of S. monotuberculatus. Salinity stress enhances the species diversity of intestinal flora in S. monotuberculatus. Eight phyla of bacteria are detected in the intestine of S. monotuberculatus. Dominant phyla include Proteobacteria, Firmicutes, and Actinobacteria. Furthermore, functional prediction reveals that acute salinity stress can significantly modify the abundance of pathways associated with nutrient and energy metabolism mediated by the intestinal flora of S. monotuberculatus. These results indicate that acute salinity stress induces pathological damage to the intestinal tissues of S. monotuberculatus, compromising the microbial habitat and leading to alterations in the intestinal flora composition. Additionally, S. monotuberculatus can mitigate salinity stress by adjusting the composition of its intestinal flora and the corresponding functional pathways. Full article
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<p>Transverse sections of intestinal tissues (foregut) HE staining of <span class="html-italic">S. monotuberculatus</span> under different salinity. LSG: low-salinity group; CG: control group; HSG: high-salinity group. IV: intestinal villi; L: lumen; IC: crypt; M: mucosa; SMC: submucosa; MM: muscularis layer; S: serosa layer; BB: brush border; GC: goblet cell; CSMM: circular smooth muscle; LSMM: longitudinal smooth muscle. The blue arrow indicates the presence of vacuolation in the intestine; the red arrow indicates death to epithelial cell of the intestine.</p>
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<p>Sample dilution curve.</p>
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<p>Venn diagrams of OTUs.</p>
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<p>Beta diversity analysis index based on PCA analysis. Note: (<b>a</b>–<b>c</b>) respectively represent the PCA diagram of intestinal flora in <span class="html-italic">S. monotuberculatus</span> treated with different salinity for 24 h, 48 h and 96 h; (<b>d</b>–<b>f</b>) respectively represent the PCA diagram of intestinal flora in <span class="html-italic">S. monotuberculatus</span> treated with the same salinity and different treatment time, (<b>d</b>): low-salinity group; (<b>e</b>): control group; (<b>f</b>): high-salinity group.</p>
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<p>Relative abundance of bacterial community in the gut of <span class="html-italic">S. monotuberculatus</span> at the level of phylum.</p>
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<p>Relative abundance of bacterial community in the gut of <span class="html-italic">S. monotuberculatus</span> at the level of genus.</p>
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<p>Heatmap showing the abundance distribution of potential functional pathways of gut bacterial communities in <span class="html-italic">S. monotuberculatus</span> under different salinity and different stress times. Note: The color from blue to red represents an increase in the abundance of the corresponding functional pathway; samples under different salinity stress were clustered according to functional pathways.</p>
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20 pages, 1382 KiB  
Review
The Daunomycin: Biosynthesis, Actions, and the Search for New Solutions to Enhance Production
by Baveesh Pudhuvai, Karel Beneš, Vladislav Čurn, Andrea Bohata, Jana Lencova, Radka Vrzalova, Jan Barta and Vladimir Matha
Microorganisms 2024, 12(12), 2639; https://doi.org/10.3390/microorganisms12122639 - 19 Dec 2024
Viewed by 503
Abstract
Daunorubicin (DNR) is an anthracycline antibiotic originating from soil-dwelling actinobacteria extensively used to treat malignant tumors. Over the decades, extensive attempts were made to enhance the production of anthracyclines by introducing genetic modifications and mutations in combination with media optimization, but the target [...] Read more.
Daunorubicin (DNR) is an anthracycline antibiotic originating from soil-dwelling actinobacteria extensively used to treat malignant tumors. Over the decades, extensive attempts were made to enhance the production of anthracyclines by introducing genetic modifications and mutations in combination with media optimization, but the target production levels remain comparatively low. Developing an appropriate culture medium to maximize the yield of DNR and preventing autotoxicity for the producing organism remains a challenge. Our prospective review sheds light on a method involving perturbation that enhances the precursors to regulate the type II PKS pathway, enhancing cells’ capacity to increase secondary metabolite production. The suggested method also entails the preparation of culture media for the cultivation of Streptomyces sp. and enhanced yield of DNR, as well as making it inactive with iron or its reduced forms following efflux from the producer. The iron or iron–DNR complex is encapsulated by oleic acid or lipid micelle layers in the culture media, finally resulting in the generated inactive DNR and the DNR–iron–oil complex. This idea has the potential to protect the producer organism from autotoxicity and prevent the inhibition of metabolite production. The approach of substituting sugar with oil in culture media has a dual role wherein it promotes Streptomyces growth by utilizing lipids as an energy source and encapsulating the generated DNR–iron complex in the medium. In this review, we discussed aspects like anthracycline producers, biosynthesis pathways, and gene regulation; side effects of DNR; mechanisms for autotoxicity evasion; and culture media components for the enhancement of DNR production in Streptomyces sp. We anticipate that our work will help researchers working with secondary metabolites production and decipher a methodology that would enhance DNR yield and facilitate the extraction of the resulting DNR by lowering costs in large-scale fermentation. Full article
(This article belongs to the Section Microbial Biotechnology)
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<p>Structure of daunorubicin (DNR) and doxorubicin (DOX) with the aglycone sugar moieties.</p>
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<p>Biosynthesis pathway and involved genes of daunorubicin (DNR) and doxorubicin (DOX) in <span class="html-italic">Streptomyces</span> with (<b>a</b>) the aglycone moiety synthesis, (<b>b</b>) the sugar moiety, and (<b>c</b>) the glycosylation and post-modification steps in DNR/DOX synthesis.</p>
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16 pages, 2304 KiB  
Article
Genomic and Phenotypic Characterization of Streptomyces sirii sp. nov., Amicetin-Producing Actinobacteria Isolated from Bamboo Rhizospheric Soil
by Yuliya V. Zakalyukina, Vera A. Alferova, Arina A. Nikandrova, Albina R. Kiriy, Alisa P. Chernyshova, Marsel R. Kabilov, Olga A. Baturina, Mikhail V. Biryukov, Petr V. Sergiev and Dmitrii A. Lukianov
Microorganisms 2024, 12(12), 2628; https://doi.org/10.3390/microorganisms12122628 - 19 Dec 2024
Viewed by 579
Abstract
In our large-scale search for antimicrobial-producing bacteria, we isolated an actinomycete strain from rhizospheric soil of Bambusa vulgaris. The strain designated BP-8 showed noticeable antibacterial activity. BP-8 was subjected to a whole-genome analysis via a polyphasic taxonomy approach, and its antibacterial metabolite [...] Read more.
In our large-scale search for antimicrobial-producing bacteria, we isolated an actinomycete strain from rhizospheric soil of Bambusa vulgaris. The strain designated BP-8 showed noticeable antibacterial activity. BP-8 was subjected to a whole-genome analysis via a polyphasic taxonomy approach, and its antibacterial metabolite was identified by HRLS-MS. The results of the physiological and morphological analyses indicated that BP-8 is an aerobic, neutrophilic, mesophilic organism that is tolerant to 8% NaCl and can use a wide range of carbohydrates. It forms curly sporophores with a warty surface. The results of the phylogenetic and average nucleotide identity analyses and in silico DNA–DNA hybridization calculation indicated that BP-8 represents the type strain of a novel Streptomyces species. A comparative in silico analysis of the genome sequences of BP-8 and its closest related strains revealed the presence of genes encoding chemotaxonomic markers characteristic of Streptomyces. The antibacterial compound was identified as amicetin. Genomic mining also revealed more than 10 biosynthetic gene clusters that have not been described previously and may lead to the discovery of new valuable compounds. On the basis of these results, strain BP-8T (=VKM Ac-3066T = CCTCC AA 2024094T) is proposed as the type strain of the novel species Streptomyces sirii sp. nov. Full article
(This article belongs to the Section Environmental Microbiology)
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<p>Phylogenetic trees of <span class="html-italic">Streptomyces</span> sp. BP-8<sup>T</sup> and type strains of the related species: (<b>a</b>) tree inferred with FastME 2.1.6.1 [<a href="#B5-microorganisms-12-02628" class="html-bibr">5</a>] from GBDP distances calculated from genome sequences. The branch lengths are scaled in terms of GBDP distance formula d5. The numbers above branches are GBDP pseudo-bootstrap support values &gt; 60% from 100 replications, with an average branch support of 91.5%. The tree is rooted at the midpoint. (<b>b</b>) Part of phylogenomic tree for <span class="html-italic">Streptomyces</span> genera constructed with de novo workflow of GTDB-tk.</p>
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<p>Cultural and morphological properties of BP-8<sup>T</sup> on ISP3 media after 10 days at 28 °C: (<b>a</b>) color of aerial mycelium, (<b>b</b>) color of substrate mycelium, (<b>c</b>) spiral chains of spores (×1000 magnification).</p>
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<p>Scanning electron micrographs of strain BP-8<sup>T</sup> on ISP3 agar for 12 days at 28 °C: (<b>a</b>) spiral chains of spores; (<b>b</b>) warty surface of non-mature spore chain among smooth aerial hyphae.</p>
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<p>Induction of a two-color reporter system sensitive to inhibitors of ribosome progression and DNA replication. Erythromycin (Ery), levofloxacin (Lev), and the compounds obtained during the broth culture purification via solid-phase extraction were placed on an agar plate with <span class="html-italic">E. coli</span> ΔtolC cells transformed with a pDualrep2 plasmid. The fluorescence of the <span class="html-italic">E. coli</span> lawn was scanned at 553/574 nm for RFP fluorescence and 588/633 nm for Katushka2S. The induction of Katushka2S expression is triggered by translation inhibitors, and RFP is regulated by the SOS response to DNA damage. BC—broth culture of BP-8<sup>T</sup>; 0, 10, 20, 25, 30, 35, 40, and 50%—elution with acetonitrile solutions in water of indicated volume concentrations.</p>
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<p>Analysis of bioactive metabolites from the strain BP-8<sup>T</sup>: (<b>a</b>) a comparison of amicetin BGC (BGC0000953) with region 7 in the BP-8<sup>T</sup> complete genome sequence, generated using clinker tool [<a href="#B46-microorganisms-12-02628" class="html-bibr">46</a>]. Homologous genes are highlighted with colors, and labels indicate identity of the genes. (<b>b</b>) MS2 fragmentation spectrum of [M+H]<sup>+</sup> ion (<span class="html-italic">m</span>/<span class="html-italic">z</span> 619.3078) of the isolated compound; structure of amicetin and characteristic [<a href="#B45-microorganisms-12-02628" class="html-bibr">45</a>] fragmentation patterns.</p>
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13 pages, 2658 KiB  
Article
Role of Bioavailability in Compost Maturity During Aerobic Composting of Chicken Manure
by Jiahuan Tang, Shuqun Zhang, Guannan Zheng, Zhuoya Han, Dingmei Wang and Hao Lin
Sustainability 2024, 16(24), 11122; https://doi.org/10.3390/su162411122 - 18 Dec 2024
Viewed by 404
Abstract
To evaluate the effects of the type and proportion of bulking agents on compost maturity, chicken manure feedstock (J) was selected as the main raw material for aerobic composting, and wood chips (M), straw (S), and cornmeal (Y) were used as bulking agents. [...] Read more.
To evaluate the effects of the type and proportion of bulking agents on compost maturity, chicken manure feedstock (J) was selected as the main raw material for aerobic composting, and wood chips (M), straw (S), and cornmeal (Y) were used as bulking agents. The ratios of chicken manure feedstock to the three bulking agents were set at 1:3, 1:1, and 3:1, respectively. The compost mixture composed of wood chips (M) and feedstock (J) in a 1:1 ratio exhibited the highest temperature (75 °C). The treatment with a bulking-agent-to-feedstock ratio of 3:1 exhibited the lowest temperature (52 °C) and the longest high-temperature period (about 10 days). Moreover, the compost mixture composed of wood chips (M) and feedstock (J) in a 3:1 ratio exhibited the highest seed germination index (1.32), while the GI values for all cornmeal treatments did not meet the standard requirements (0.4). The predominant microorganisms in all three treatments included Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria. The total carbon transformation-related microorganism abundance in MJ31, SJ31, and YJ31 was 1.65%, 10.69%, and 3%, respectively. Further analysis showed that the bioavailability of feedstock was strongly correlated with compost maturity. The treatment with a bulking-agent-to-feedstock ratio of 3:1, with the highest GI, also exhibited the highest bioavailability. These results can guide the selection of the appropriate bulking agent and the optimal bulking-agent-to-feedstock ratio, offering a new direction for the optimization of the composting process. Full article
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<p>Basic physicochemical properties of raw materials before composting. (<b>A</b>) Carbon source concentration with different degrees of degradation (RCP and LCP); (<b>B</b>) degradable carbon source concentration (LCP1 and LCP2); (<b>C</b>) nitrogen source concentrations with different degrees of degradation (RNP and LNP); (<b>D</b>) degradable carbon source concentration (LCP1 and LCP2); (<b>E</b>) different amounts of water content in raw materials; (<b>F</b>) relative density of raw materials.</p>
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<p>Dynamic changes in physicochemical indexes during composting (<b>A</b>–<b>C</b>); temperature; (<b>D</b>–<b>F</b>) moisture content; (<b>G</b>–<b>I</b>) total-carbon-to-total-nitrogen ratio (C/N).</p>
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<p>(<b>A</b>–<b>I</b>) Three-dimensional fluorescence spectroscopy of the different samples at the end of composting and (<b>J</b>–<b>L</b>) the germination index (GI) during composting.</p>
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<p>The relative abundance changes in the top 20 bacterial communities related to genus-level carbon source metabolism on the 3rd and 50th days of composting. (<b>A</b>) The material ratio between the bulk agent and the chicken manual was 1 to 3. (<b>B</b>) The material ratio between the bulk agent and the chicken manual was 1 to 1. (<b>C</b>) The material ratio between the bulk agent and the chicken manual was 3 to 1.</p>
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<p>The Mantel test was used to analyze the correlation between the density, moisture content, and carbon and nitrogen sources of compost raw materials and key physicochemical properties and microorganisms. (<b>A</b>) The material ratio between the bulking agent and chicken manure was 1 to 3. (<b>B</b>) The material ratio between the bulking agent and chicken manure was 1 to 1. (<b>C</b>) The material ratio between the bulking agent and chicken manure was 3 to 1. (<b>D</b>) The co-occurrence networks among all treatments.</p>
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17 pages, 3153 KiB  
Article
Role of Climate and Edaphic Factors on the Community Composition of Biocrusts Along an Elevation Gradient in the High Arctic
by Isabel Mas Martinez, Ekaterina Pushkareva, Leonie Agnes Keilholz, Karl-Heinz Linne von Berg, Ulf Karsten, Sandra Kammann and Burkhard Becker
Microorganisms 2024, 12(12), 2606; https://doi.org/10.3390/microorganisms12122606 - 17 Dec 2024
Viewed by 439
Abstract
Biological soil crusts are integral to Arctic ecosystems, playing a crucial role in primary production, nitrogen fixation and nutrient cycling, as well as maintaining soil stability. However, the composition and complex relationships between the diverse organisms within these biocrusts are not well studied. [...] Read more.
Biological soil crusts are integral to Arctic ecosystems, playing a crucial role in primary production, nitrogen fixation and nutrient cycling, as well as maintaining soil stability. However, the composition and complex relationships between the diverse organisms within these biocrusts are not well studied. This study investigates how the microbial community composition within Arctic biocrusts is influenced by environmental factors along an altitudinal gradient (101 m to 314 m). Metagenomic analyses were used to provide insights into the community composition, revealing that temperature, pH, and nutrient availability significantly shaped the community. In contrast, altitude did not directly influence the microbial composition significantly. Eukaryotic communities were dominated by Chloroplastida and fungi, while Proteobacteria and Actinobacteria prevailed among prokaryotes. Cyanobacteria, particularly orders such as Pseudoanabaenales, Pleurocapsales, and Nostocales, emerged as the most abundant photoautotrophic organisms. Our findings highlight the impact of environmental gradients on microbial diversity and the functional dynamics of biocrusts, emphasizing their critical role in Arctic tundra ecosystems. Arctic biocrusts are intricate micro-ecosystems, whose structure is strongly shaped by local physicochemical parameters, likely affecting essential ecological functions. Full article
(This article belongs to the Special Issue Molecular Ecology of Microalgae and Cyanobacteria)
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<p>Geographical location of sampling sites on Ossian Sarsfjellet, Svalbard. (<b>A</b>)—The red arrow indicates the location of Ossian Sarsfjellet and the red star indicates the location of the weather station in Ny-Ålesund in the Kongsfjorden area. (<b>B</b>)—The red circles indicate the sampling sites. Maps based on TopoSvalbard, courtesy of the Norwegian Polar Institute.</p>
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<p>Temperature data from 13 July 2023 to 4 August 2023 at the three different measurement points across the four sites. T1 = measured 6 cm below the soil surface; T2 = measured at the soil surface; T3 = measured 15 cm above the soil surface; measured every 15 min; measured with TOMST<sup>®</sup> data loggers.</p>
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<p>Soil moisture data from 13 July 2023 to 20 August 2023 across the sites. Measured every 15 min; measured with TOMST<sup>®</sup> data loggers; significant differences observed between all four sites; <span class="html-italic">p</span>-value &lt; 0.05. Data used for statistical analysis are from 13 July 2023 to 4 August 2023 only.</p>
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<p>Non-Metric Multidimensional Scaling (NMDS) plot based on the vegetation analysis conducted at the sites. T1 = temperature measured 6 cm below the soil surface; T2 = temperature measured at the soil surface; T3 = temperature measured 15 cm above the soil surface; C.N = carbon to nitrogen ratio; parameters which did not show significant differences between the sites are not included, <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Overall community composition across sites. Metagenomic 16/18 S rRNA dataset analysed using Silva software; taxonomic groups with total abundance below the 0.5% threshold are grouped as ‘low abundance’; * indicates significant differences between sites based on a one-way ANOVA, <span class="html-italic">p</span>-value * &lt; 0.05, ** &lt; 0.01).</p>
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<p>Relative abundance of fungal taxa and fungal functional guilds across sites. Metagenomic 16/18S rRNA dataset analysed using Silva software. (<b>A</b>)—fungal phyla. (<b>B</b>)—functional guilds; * indicates significant differences between sites based on a one-way ANOVA, <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Relative abundance of photoautotrophic taxa across sites. Metagenomic 16/18S rRNA dataset analysed using Silva software; no significant differences were observed between the taxa, based on a one-way ANOVA, <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Relative abundance of cyanobacterial orders across sites. Metagenomic 16 S rRNA dataset analysed using Silva software; filamentous orders shown in orange/red; heterocystous order shown in green; unicellular orders shown in blue; * indicates significant differences between sites based on a one-way ANOVA, <span class="html-italic">p</span>-value &lt; 0.05.</p>
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