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Microorganisms, Volume 12, Issue 12 (December 2024) – 290 articles

Cover Story (view full-size image): Viral respiratory infections (VRIs) are a leading cause of morbidity and mortality worldwide, making them a significant public health concern. During infection, respiratory viruses, including Influenza virus, SARS-CoV-2, and respiratory syncytial virus (RSV), trigger an antiviral immune response, specifically boosting the inflammatory response that plays a critical role in their pathogenesis. The inflammatory response induced by respiratory viruses can be a double-edged sword, since it can be initially induced to be antiviral and protective/reparative in terms of virus-induced injuries. Still, it can also be detrimental to host cells and tissues. However, the mechanisms that differentiate the complex crosstalk between favorable host inflammatory responses and harmful inflammatory responses are poorly understood. View this paper
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24 pages, 1704 KiB  
Article
In Vitro Antioxidant and Antibacterial Activities of Ethyl Acetate Extracts of Ziziphus lotus Leaves and Five Associated Endophytic Fungi
by Amel Ghazi-Yaker, Bart Kraak, Jos Houbraken, El-hafid Nabti, Cristina Cruz, Noria Saadoun and Karim Houali
Microorganisms 2024, 12(12), 2671; https://doi.org/10.3390/microorganisms12122671 - 23 Dec 2024
Viewed by 650
Abstract
The exploration of new pharmacological compounds from endophytic fungi offers infinite possibilities. The aim of this study was to evaluate the antibacterial and antioxidant activities of extracts from the leaves of Ziziphus lotus and five of its endophytic fungi and investigate the chemical [...] Read more.
The exploration of new pharmacological compounds from endophytic fungi offers infinite possibilities. The aim of this study was to evaluate the antibacterial and antioxidant activities of extracts from the leaves of Ziziphus lotus and five of its endophytic fungi and investigate the chemical diversity of the secondary metabolites produced. Isolated, purified, and molecularly identified endophytes and plant leaves were subjected to ethyl acetate extraction. The antibacterial potential of the extracts was assessed by the disc diffusion method against five bacterial strains: Staphylococcus aureus ATCC 25923; Staphylococcus aureus MU50; Enterococcus faecalis WDCM00009; Escherichia coli ATCC 25922; and Pseudomonas aeruginosa ATCC 27853. DPPH and reducing power tests were performed to assess antioxidant potential. GC–MS analysis was used to identify volatile compounds in extracts. Fungal endophytes were identified as Aspergillus cavernicola, Aspergillus persii, Alternaria alternata, Cladosporium asperlatum, and Fusarium incarnatum–equiseti complex, with respective accession numbers DTO 412-G6, DTO 412-I5, DTO 413-E7, DTO 412-G4, and DTO 414-I2. GC–MS analysis revealed a large number of bioactive compounds. All extracts showed antibacterial activity against at least two of the bacteria tested, and most showed antioxidant activity. The Aspergillus cavernicola extract stood out for its higher phenolic content and higher antioxidant and antibacterial activities in all tests. Full article
(This article belongs to the Special Issue Endophytic Fungus as Producers of New and/or Bioactive Substances)
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Figure 1
<p>Antibacterial activity of ethyl acetate extracts (<b>A</b>) <span class="html-italic">S. aureus</span> ATCC 25923, (<b>B</b>) <span class="html-italic">S. aureus</span> MU50, (<b>C</b>) <span class="html-italic">E. faecalis</span> WDCM00009 (<b>D</b>) <span class="html-italic">E. coli</span> ATCC 25922, and (<b>E</b>) <span class="html-italic">P. aerugenosa</span> ATCC 27853 (F.iec: <span class="html-italic">Fusarium incarnatum–equiseti</span> complex; <span class="html-italic">A.c: Aspergillus cavernicola</span>; <span class="html-italic">A.p: Aspergillus persii</span>; C.a: <span class="html-italic">Cladosporium asperlatum</span>; A.a: <span class="html-italic">Alternaria alternata</span>; Z.l: <span class="html-italic">Ziziphus lotus</span>; DMSO: Dimethylsulfoxide; AT: antibiotic Chloramphenicol).</p>
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<p>DPPH radical scavenging activities of endophytic fungi and <span class="html-italic">Z. lotus</span> leaves ethyl acetate extracts in comparison with ascorbic acid.</p>
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<p>Reducing power activity of samples and ascorbic acid at 1 mg/mL.</p>
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<p>Total phenolic contents in <span class="html-italic">Z. lotus</span> and its endophytic fungi.</p>
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29 pages, 7062 KiB  
Article
Gram Negative Biofilms: Structural and Functional Responses to Destruction by Antibiotic-Loaded Mixed Polymeric Micelles
by Tsvetozara Damyanova, Rumena Stancheva, Milena N. Leseva, Petya A. Dimitrova, Tsvetelina Paunova-Krasteva, Dayana Borisova, Katya Kamenova, Petar D. Petrov, Ralitsa Veleva, Ivelina Zhivkova, Tanya Topouzova-Hristova, Emi Haladjova and Stoyanka Stoitsova
Microorganisms 2024, 12(12), 2670; https://doi.org/10.3390/microorganisms12122670 - 23 Dec 2024
Viewed by 547
Abstract
Biofilms are a well-known multifactorial virulence factor with a pivotal role in chronic bacterial infections. Their pathogenicity is determined by the combination of strain-specific mechanisms of virulence and the biofilm extracellular matrix (ECM) protecting the bacteria from the host immune defense and the [...] Read more.
Biofilms are a well-known multifactorial virulence factor with a pivotal role in chronic bacterial infections. Their pathogenicity is determined by the combination of strain-specific mechanisms of virulence and the biofilm extracellular matrix (ECM) protecting the bacteria from the host immune defense and the action of antibacterials. The successful antibiofilm agents should combine antibacterial activity and good biocompatibility with the capacity to penetrate through the ECM. The objective of the study is the elaboration of biofilm-ECM-destructive drug delivery systems: mixed polymeric micelles (MPMs) based on a cationic poly(2-(dimethylamino)ethyl methacrylate)-b-poly(ε-caprolactone)-b-poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA35-b-PCL70-b-PDMAEMA35) and a non-ionic poly(ethylene oxide)-b-poly(propylene oxide)-b-poly(ethylene oxide) (PEO100-b-PPO65-b-PEO100) triblock copolymers, loaded with ciprofloxacin or azithromycin. The MPMs were applied on 24 h pre-formed biofilms of Escherichia coli and Pseudomonas aeruginosa (laboratory strains and clinical isolates). The results showed that the MPMs were able to destruct the biofilms, and the viability experiments supported drug delivery. The biofilm response to the MPMs loaded with the two antibiotics revealed two distinct patterns of action. These were registered on the level of both bacterial cell-structural alterations (demonstrated by scanning electron microscopy) and the interaction with host tissues (ex vivo biofilm infection model on skin samples with tests on nitric oxide and interleukin (IL)-17A production). Full article
(This article belongs to the Special Issue Contemporary Perspectives on Bacterial Virulence Factors)
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<p>(<b>a</b>) Hydrodynamic diameter, D<sub>h</sub>, and (<b>b</b>) ζ-potential variations as a function of the micellar concentration of SCPMs and MPMs based on PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers. (<b>c</b>) Size distribution curves (<b>d</b>) DLS correlation functions and (<b>e</b>) representative AFM micrograph of MPMs prepared from PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers at a molar ratio of 1:1 in the concentration range of 1 to 0.125 mg mL<sup>−1</sup>. The PDI values ranged in the 0.11–0.19 interval. All DLS measurements were performed at 25 °C.</p>
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<p>Variations of encapsulation efficiency (<b>a</b>) and drug loading content (<b>b</b>) as a function of the composition of SCPMs and MPMs based on PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers. The loading was performed at polymer-to-drug mass ratio of 10:1.</p>
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<p>Hydrodynamic diameter, Dh, (<b>a</b>,<b>c</b>,<b>e</b>) and ζ potential (<b>b</b>,<b>d</b>,<b>f</b>) of empty or loaded with antibiotics MPMs based on PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers in the concentration range of 1 to 0.125 mg mL<sup>−1</sup>. Measurements were performed at 25 °C at pH 7. Each data point represents the arithmetic mean ± SD of three separate experiments.</p>
Full article ">Figure 3 Cont.
<p>Hydrodynamic diameter, Dh, (<b>a</b>,<b>c</b>,<b>e</b>) and ζ potential (<b>b</b>,<b>d</b>,<b>f</b>) of empty or loaded with antibiotics MPMs based on PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers in the concentration range of 1 to 0.125 mg mL<sup>−1</sup>. Measurements were performed at 25 °C at pH 7. Each data point represents the arithmetic mean ± SD of three separate experiments.</p>
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<p>Drug release profiles of MPMs based on PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers, prepared at a 10:1 polymer-to-drug mass ratio, determined by HPLC. MPMs were formed at molar ratios of 3:1 (<b>a</b>), 1:1 (<b>b</b>), and 1:3 (<b>c</b>). The release was performed at 37 °C in phosphate buffer pH 7.4. Each data point represents the arithmetic mean ± SD of three separate experiments.</p>
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<p>Cytotoxicity of the SCPMs and MPMs based on PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers loaded with CF (<b>a</b>) or AZ (<b>b</b>) at a 10:1 polymer-to-drug mass ratio. The micelles were applied for 4 h in concentrations of 0.5, 0.25, and 0.125 mg mL<sup>−1</sup> onto confluent cultured HaCaT. The results are presented as percentage of the control—cells cultivated parallelly in DMEM. The data are the means of four repeats and are presented as the mean ± SD. Differences between control (DMEM) and treated with micelles cells are accepted as statistically significant (*) when <span class="html-italic">p</span> &lt; 0.05 and (**) when <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Reduction of the biomass of mature 24 h biofilms as a result of treatment for 4 or 24 h with 0.25 mg mL<sup>−1</sup> of empty or antibiotics-loaded MPMs based on PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers. The results were calculated as percentage of the biofilm at the start of each experiment. (<b>a</b>) <span class="html-italic">E. coli</span> 25922; (<b>b</b>) <span class="html-italic">P. aeruginosa</span> PAO1. Results for biofilms treated with dH<sub>2</sub>O are included since the micelles were dispersed in dH<sub>2</sub>O. Each data point represents the mean ± SD of six repeats.</p>
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<p>Viability of the biofilms after treatment for 24 h with 0.25 mg mL<sup>−1</sup> of empty or antibiotics-loaded MPMs based on PDMAEMA<sub>35</sub>-PCL<sub>70</sub>-PDMAEMA<sub>35</sub> and Pluronic F127 triblock copolymers. Viability was estimated by the reduction of resazurin using the Alamar Blue reagent (Invitrogen). The results were calculated as percentage of the untreated control (biofilm cultivated parallelly in M63 medium in the absence of the tested agents). dH<sub>2</sub>O bars are included to show the effect of treatment with dH<sub>2</sub>O alone_ the medium in which the micelles were dispersed. (<b>a</b>) <span class="html-italic">E. coli</span> 25922; (<b>b</b>) <span class="html-italic">P. aeruginosa</span> PAO1. Each data point represents the mean ± SD of six repeats. <span class="html-italic">p</span> &lt; 0.05 (*); <span class="html-italic">p</span> &lt; 0.001 (***), ANOVA test.</p>
Full article ">Figure 8
<p>Reduction of biofilms of pathogenic strains of <span class="html-italic">E. coli</span> treated with empty or antibiotic-loaded MPMs 3:1 (<b>a</b>) and of <span class="html-italic">P. aeruginosa</span> treated with empty or antibiotic-loaded MPMs 1:1 (<b>b</b>). The results were calculated as percentage of the “0” controls, i.e., the amount of biofilms of the strains before the start of the treatments. Each data point represents the mean ± SD of six repeats.</p>
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<p>Scanning electron microscopy of biofilms of <span class="html-italic">E. coli</span> 25922 (<b>A</b>–<b>H</b>) and <span class="html-italic">P. aeruginosa</span> PAO1 (<b>I</b>–<b>P</b>). Arrows: white—infolds of the cell wall; yellow—outer membrane vesicles; red—tunneling nanotubules. (<b>A</b>) <span class="html-italic">E. coli</span> 48 h control biofilm; (<b>B</b>,<b>E</b>,<b>F</b>,<b>F1</b>) <span class="html-italic">E. coli</span> 24 h biofilm treated for a further 24 h with empty MPMs 3:1; yellow asterisk mark slimy covering of cells in some areas of the treated biofilm. (<b>G</b>,<b>G1</b>) <span class="html-italic">E. coli</span> 24 h biofilm treated for a further 24 h with CF-loaded MPMs 3:1; (<b>H</b>,<b>H1</b>) <span class="html-italic">E. coli</span> 24 h biofilm treated for a further 24 h with AZ-loaded MPMs 3:1. (<b>I</b>,<b>M</b>) <span class="html-italic">P. aeruginosa</span> 48 h control biofilm; (<b>J</b>,<b>N</b>) <span class="html-italic">P. aeruginosa</span> 24 h biofilm treated for a further 24 h with empty MPMs 1:1; (<b>K</b>,<b>O</b>) <span class="html-italic">P. aeruginosa</span> 24 h biofilm treated for a further 24 h with CF-loaded MPMs 1:1; (<b>L</b>,<b>P</b>,<b>P1</b>) <span class="html-italic">P. aeruginosa</span> 24 h biofilm treated for a further 24 h with AZ-loaded MPMs 1:1; white asterisks, cells with extensively blebbed surfaces.</p>
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<p>Histological sections of skin explants infected with <span class="html-italic">P. aeruginosa</span> PAO1 biofilm. (<b>A</b>) Untreated 24 h ex vivo biofilm. (<b>B</b>,<b>C</b>) Mature 24 h biofilms on skin explants were treated for 24 h with 0.25 mg mL<sup>−1</sup> of MPMs 1:1 loaded with CF (<b>B</b>) or AZ (<b>C</b>). Bar = 10 µm.</p>
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<p>Effect of MPMs loaded with CF or AZ on NO (<b>a</b>) and IL-17A (<b>b</b>) production in ex vivo murine skin explant <span class="html-italic">P. aeruginosa</span> PAO1 biofilm model. Murine skin explants were infected with <span class="html-italic">P. aeruginosa</span> for 24 h for the development of biofilm. Afterwards the skin explants were treated with 50 µL of either 0.5 or 0.25 mg mL<sup>−1</sup> MPMs loaded with CF or AZ. Control samples, infected or uninfected with <span class="html-italic">P. aeruginosa</span> biofilm, were treated in parallel with either PBS or dH<sub>2</sub>O (the solvent for the MPM samples). Data represents mean ± SD from 3 samples/group * <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 when comparing the biofilm groups to the control PBS one, ANOVA test; ## <span class="html-italic">p</span> &lt; 0.05 when comparing the non-biofilm groups to the control PBS one, ANOVA test.</p>
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26 pages, 1262 KiB  
Review
Campylobacter jejuni/coli Infection: Is It Still a Concern?
by Piero Veronese and Icilio Dodi
Microorganisms 2024, 12(12), 2669; https://doi.org/10.3390/microorganisms12122669 - 23 Dec 2024
Viewed by 483
Abstract
Campylobacteriosis is a leading cause of infectious diarrhea and foodborne illness worldwide. Campylobacter infection is primarily transmitted through the consumption of contaminated food, especially uncooked meat, or untreated water; contact with infected animals or contaminated environments; poultry is the primary reservoir and source [...] Read more.
Campylobacteriosis is a leading cause of infectious diarrhea and foodborne illness worldwide. Campylobacter infection is primarily transmitted through the consumption of contaminated food, especially uncooked meat, or untreated water; contact with infected animals or contaminated environments; poultry is the primary reservoir and source of human transmission. The clinical spectrum of Campylobacter jejuni/coli infection can be classified into two distinct categories: gastrointestinal and extraintestinal manifestations. Late complications are reactive arthritis, Guillain–Barré syndrome, and Miller Fisher syndrome. In the pediatric population, the 0–4 age group has the highest incidence of campylobacteriosis. Regarding the use of specific antimicrobial therapy, international guidelines agree in recommending it for severe intestinal infections. Host factors, including malnutrition, immunodeficiency, and malignancy, can also influence the decision to treat. The Centers for Disease Control and Prevention (CDC) has identified antibiotic resistance in Campylobacter as a ‘significant public health threat’ due to increasing resistance to FQs or macrolides. Although numerous vaccines have been proposed in recent years to reduce the intestinal colonization of poultry, none have shown sufficient efficacy to provide a definitive solution. Full article
(This article belongs to the Special Issue Epidemiology, Prevention and Control of Foodborne Microbial Pathogens)
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<p>Transmission, environmental reservoirs, and risk factors for human <span class="html-italic">Campylobacteriosis</span>. As a zoonotic disease, poultry is the primary reservoir for <span class="html-italic">Campylobacter</span>. In non-endemic regions, consuming raw or undercooked poultry meat and direct contact with animals are the primary risk factors. However, in endemic areas, environmental contamination, including water sources, along with poultry contact, increased meat consumption, and inadequate hygienic practices contribute to the widespread persistence of the bacterium.</p>
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<p><span class="html-italic">Campylobacter jejuni/coli</span> virulence factors. The main pathogenic factors of <span class="html-italic">Campylobacter</span> have been categorized into four broad groups in this image: motility and chemotaxis, adhesion and translocation, invasion and evasion of the host immune system, and survival and biofilm formation. The flagellar apparatus, encoded by the <span class="html-italic">FlgA</span> gene, is the factor that confers motility to the bacterium, counteracting peristaltic movements. Additionally, it is involved in the secretion of effector molecules (<span class="html-italic">Campylobacter</span> invasion antigens, Cia), in the evasion of TLR5-mediated immunity, and in the biofilm formation. CiaB, CiaC, and CiaD facilitate bacterial uptake by and invasion of host cells. The type 3 secretion system (T3SS), a key virulence factor in many Gram-negative pathogens, is primarily responsible for the secretion of Cia effectors. Despite T4SS presence in <span class="html-italic">Campylobacter</span> remaining unclear, T6SS plays a clear role in host invasion, mediating both invasion and adhesion to colon cells. During invasion, <span class="html-italic">Campylobacter jejuni</span> cytolethal distending toxin (Cj-CDT). Capsular polysaccharide (CPS) and <span class="html-italic">Campylobacter</span>-containing vacuoles (CCVs) act as an immune shield, allowing the bacterium to persist within the host.</p>
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<p>Clinical manifestations and late complications of <span class="html-italic">Campylobacter</span> infection. While uncommon, bacteremia is a key factor in the systemic spread of the bacteria following intestinal infection, leading to potential complications in distant organs. Molecular mimicry underlies the pathogenesis of late complications.</p>
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22 pages, 5914 KiB  
Article
The Effect of Oral Care Product Ingredients on Oral Pathogenic Bacteria Transcriptomics Through RNA-Seq
by Ping Hu, Sancai Xie, Baochen Shi, Cheryl S. Tansky, Benjamin Circello, Paul A. Sagel, Eva Schneiderman and Aaron R. Biesbrock
Microorganisms 2024, 12(12), 2668; https://doi.org/10.3390/microorganisms12122668 - 23 Dec 2024
Viewed by 562
Abstract
Various ingredients are utilized to inhibit the growth of harmful bacteria associated with cavities, gum disease, and bad breath. However, the precise mechanisms by which these ingredients affect the oral microbiome have not been fully understood at the molecular level. To elucidate the [...] Read more.
Various ingredients are utilized to inhibit the growth of harmful bacteria associated with cavities, gum disease, and bad breath. However, the precise mechanisms by which these ingredients affect the oral microbiome have not been fully understood at the molecular level. To elucidate the molecular mechanisms, a high-throughput bacterial transcriptomics study was conducted, and the gene expression profiles of six common oral bacteria, including two Gram-positive bacteria (Actinomyces viscosus, Streptococcus mutans) and four Gram-negative bacteria (Porphyromonas gingivalis, Tannerella forsythia, Fusobacterium nucleatum, and Prevotella pallens), were analyzed. The bacteria were exposed to nine common ingredients in toothpaste and mouthwash at different concentrations (stannous fluoride, stannous chloride, arginine bicarbonate, cetylpyridinium chloride, sodium monofluorophosphate, sodium fluoride, potassium nitrate, zinc phosphate, and hydrogen peroxide). Across 78 ingredient–microorganism pairs with 360 treatment–control combinations, significant and reproducible ingredient-based transcriptional response profiles were observed, providing valuable insights into the effects of these ingredients on the oral microbiome at the molecular level. This research shows that oral care product ingredients applied at biologically relevant concentrations manifest differential effects on the transcriptomics of bacterial genes in a variety of oral periodontal pathogenic bacteria. Stannous fluoride, stannous chloride, and cetylpyridinium chloride showed the most robust efficacy in inhibiting the growth or gene expression of various bacteria and pathogenic pathways. Combining multiple ingredients targeting different mechanisms might be more efficient than single ingredients in complex oral microbiomes. Full article
(This article belongs to the Special Issue Oral Microbiomes and One Health Approach)
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Figure 1
<p>Heatmap of treatment-induced total bacterial RNA yield fold change compared to untreated control indicated that stannous and hydrogen peroxide down-regulated RNA synthesis in all tested oral bacteria.</p>
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<p>Heatmap of treatment-induced differential expressed gene ratio (DEGR) showed stannous compounds induced strong gene expression changes in all tested oral bacteria.</p>
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<p>Microbial transcriptomics response to oral hygiene product ingredients is used to evaluate and rank material for treatment effect, indicating that stannous is the top treatment for these groups of tested bacteria. (<b>a</b>) Heatmap of log2 fold change of all the 12,546 genes from the six tested bacteria strains. (<b>b</b>) PCA plot of the combined gene expression data from all the 12,546 genes, showing all the tested materials and their relative distance to the control samples. (<b>c</b>) The rank treatment effect of different materials based on the normalized distance to control based on the PCA plot indicated that the stannous compounds are a top treatment for disturbing microbial gene expression, and the color matches the PCA plot.</p>
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<p>Treatment-induced transcriptomics changes in genes involved in LPS biosynthesis. (<b>a</b>) Heatmap of log2 fold change of <span class="html-italic">P. gingivalis</span> genes involved in LPS biosynthesis (Lipid A, Core, O-Antigen, or APS biosynthesis) and LPS export compared to no-treatment controls. (<b>b</b>) KEGG pathway mapping of the first four genes of <span class="html-italic">P. gingivalis</span> LPS biosynthesis pathway highlights gene expression changes induced by ArgB, H<sub>2</sub>O<sub>2</sub>, SnCl<sub>2</sub>_L, and SnF<sub>2</sub>_L, showing that stannous compounds down-regulated LPS biosynthesis. ArgB up-regulated LPS biosynthesis. (<b>c</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis LpxA</span> gene, the first step for Lipid A biosynthesis, a critical component for LPS biosynthesis. (<b>d</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis LpxC</span> gene, which is a rate-limiting gene for the LPS biosynthesis pathway. (<b>e</b>) Heat map of log2 fold change of <span class="html-italic">LpxA</span> and <span class="html-italic">LpxC</span> genes from all four tested Gram-negative bacteria. The standard error is shown as an error bar in all bar figures; a single star indicates <span class="html-italic">p</span>-value ≤ 0.05, and double stars indicate fdr-adjusted <span class="html-italic">p</span>-value ≤ 0.05.</p>
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<p>Treatment-induced transcriptomics changes in genes involved in <span class="html-italic">P. gingivalis</span> toxin translocation, secretion system, and infection (<b>a</b>) Heatmap of Log2 fold change of <span class="html-italic">P. gingivalis</span> genes involved in toxin translocation, secretion system, and infection (including Type 9 Secretion System (T9SS), <span class="html-italic">PPAD</span>, <span class="html-italic">gingipain</span>, <span class="html-italic">frimbrium</span>, <span class="html-italic">humY</span>-<span class="html-italic">tonB</span>, <span class="html-italic">VIM</span>, quorum sensing gene <span class="html-italic">LuxS</span>, <span class="html-italic">LuxR</span>, NO stress-associated gene <span class="html-italic">cdrH</span>, and infection-associated gene <span class="html-italic">hflX</span>) compared to untreated control from all tested bacteria strains. (<b>b</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis</span> Type 9 Secretion System gene <span class="html-italic">PorQ</span> encoded by pgi:PG_0602. (<b>c</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis fimbrium subunit C (fimC)</span> gene encoded by pgi:PG_1881. (<b>d</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis VimF Glycosyltransferase</span> gene encoded by pgi:PG_0884, a key virulence modulating component. (<b>e</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis hflX</span> gene encoded by pgi:PG_1886, a key virulence factor for infection and invasion. (<b>f</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis peptidylarginine deiminase (PPAD)</span> gene encoded by pgi:PG_1424. (<b>g</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis cdhR</span> gene encoded by pgi:PG_1237, also named <span class="html-italic">luxR</span> as a component of quorum sensing, regulating NO stress resistance. The standard error is shown as an error bar in all bar figures; a single star indicates <span class="html-italic">p</span>-value ≤ 0.05, and double stars indicate fdr-adjusted <span class="html-italic">p</span>-value ≤ 0.05.</p>
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<p>Treatment-induced transcriptomic responses of degradative enzymes including proteases, peptidases, and hemolysins. (<b>a</b>) Heatmap of log2 fold change of degradative enzymes, such as proteases, peptidases, and hemolysins, from all the tested bacteria strains compared to the no-treatment controls. (<b>b</b>) Gene number of the degradation enzymes in each bacteria genome and representational ratio towards all the genes encoded in the genome. (<b>c</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis gingipain A</span> gene encoded by pgi:PG_2024. (<b>d</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis gingipain B</span> gene encoded by pgi:PG_0506. (<b>e</b>) Bar plot of the log2 fold change of <span class="html-italic">P. gingivalis hemolysin</span> gene encoded by pgi:PG_1875. (<b>f</b>) Bar plot of the log2 fold change of <span class="html-italic">F. nucleatum</span> prtC <span class="html-italic">collagenase</span> gene encoded by PKHDFLHN_00556 [<a href="#B73-microorganisms-12-02668" class="html-bibr">73</a>]. The standard error is shown as an error bar in all bar figures; a single star indicates <span class="html-italic">p</span>-value ≤ 0.05, and double stars indicate fdr-adjusted <span class="html-italic">p</span>-value ≤ 0.05.</p>
Full article ">Figure 7
<p>Transcriptomic changes in genes that are regulated by major oral care ingredients and involved in biofilm development, adhesion to, and infection of host cells. (<b>a</b>). Genes in biofilm development and survival. (<b>b</b>). Genes in attachment to and initial interaction with host cells, such as gingival keratinocytes. (<b>c</b>). Genes encoding products that directly degrade the cellular structure of gingiva and facilitate bacterial survival and infection. The directions of gene expression changes are based on the results observed with SnF<sub>2</sub>, SnCl<sub>2</sub>, and CPC, which had the strongest activity. Blue arrows designate down-regulation, and red arrows designate up-regulation.</p>
Full article ">
13 pages, 3058 KiB  
Article
Characteristics of the Stool, Blood and Skin Microbiome in Rosacea Patients
by Marie Isolde Joura, Antal Jobbágy, Zsuzsanna A. Dunai, Nóra Makra, András Bánvölgyi, Norbert Kiss, Miklós Sárdy, Sarolta Eszter Sándor, Péter Holló and Eszter Ostorházi
Microorganisms 2024, 12(12), 2667; https://doi.org/10.3390/microorganisms12122667 - 23 Dec 2024
Viewed by 476
Abstract
Several research groups have confirmed that in the pathogenesis of the chronic inflammatory skin disorder rosacea, the composition of the skin and fecal microbiome of affected patients differs from that of healthy individuals. We studied the stool, blood and skin microbiomes of rosacea [...] Read more.
Several research groups have confirmed that in the pathogenesis of the chronic inflammatory skin disorder rosacea, the composition of the skin and fecal microbiome of affected patients differs from that of healthy individuals. We studied the stool, blood and skin microbiomes of rosacea and control patients using 16S rRNA sequencing. Our goals were to determine 1. whether the microbiome characteristics of rosacea patients differ from that of healthy individuals, 2. whether the change experienced on the skin can be confirmed by alterations in the stool microbiome through the mediation of the blood and 3. whether the metabolic activity of the changed skin, blood or fecal microbiome can play a role in the pathogenesis of rosacea. The rosacea skin microbiome differed significantly from the healthy skin microbiome in both alpha and beta diversity, as well as in the abundance of the genera. Only a few genera abundances differed significantly in stool and blood samples. The most significant representatives of the rosacea skin microbiome, Staphylococcus, Cutibacterium, Corynebacterium and Neisseria, cannot be derived from the feces or blood. The metabolic pathways associated with healthy fecal microbiome contributed to the production of anti-inflammatory short-chain fatty acids. While the increased production of adenosylcobalamin, L-isoleucine and thiazole by the microbiome of healthy skin appeared to have a protective effect, the excessive heme and H2S production experienced in rosacea skin likely contribute to the deterioration of the pathology. Full article
(This article belongs to the Special Issue Human Skin Microbiota, 2nd Edition)
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<p>Principal component analysis (<b>A</b>) and heatmap (<b>B</b>) of bacterial abundance of stool, blood and skin samples of the rosacea patients and control healthy volunteers.</p>
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<p>Comparison of Chao1 alpha diversity (<b>A</b>) or Bray–Curtis beta diversity (<b>B</b>) of stool, blood and skin samples from the rosacea patients and control patients.</p>
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<p>The genus relative abundance in the composition of the skin microbiome of rosacea patients and control individuals, aggregated by cohort (<b>A</b>) and individual data (<b>B</b>) by stacked bar representation.</p>
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<p>Abundance distribution of <span class="html-italic">Bacteroides</span>, <span class="html-italic">Faecalibacterium</span>, <span class="html-italic">Blautia</span>, <span class="html-italic">Prevotella</span>, <span class="html-italic">Ruminococcus</span> and <span class="html-italic">Subdoligranulum</span> genera among the different sample types.</p>
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<p>LEfSe bar chart; visual representation of discriminative features of genera abundances among the control and rosacea blood and stool samples (<b>A</b>), and discriminative biochemical pathways in stool samples (<b>B</b>). LDA is the linear discriminant analysis score.</p>
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<p>LefSe analysis of metabolic pathways of the rosacea and control skin microbiome. LDA is the linear discriminant analysis score.</p>
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14 pages, 1014 KiB  
Article
Haemophilus influenzae Invasive Infections in Children in Vaccine Era: Phenotypic and Genotypic Characterization Tunis, Tunisia
by Yasmine Chelbi, Khaoula Meftah, Ala-Eddine Deghmane, Samar Mhimdi, Firas Aloui, Aida Bouafsoun, Eva Hong, Khaled Menif, Khadija Boussetta, Monia Khemiri, Samir Boukthir, Mehdi Trifa, Said Jlidi, Riadh Jouini, Zohra Fitouri, Mohamed-Nabil Nessib, Muhamed-Kheir Taha and Hanen Smaoui
Microorganisms 2024, 12(12), 2666; https://doi.org/10.3390/microorganisms12122666 - 23 Dec 2024
Viewed by 649
Abstract
The changing epidemiological profile of invasive Haemophilus influenzae infections (IIHi) is noted in the post-vaccination era. The aim of this study was to characterize phenotypically and genotypically invasive Haemophilus influenzae (Hi) isolates detected in Tunisian pediatric patients. A retrospective study was conducted in [...] Read more.
The changing epidemiological profile of invasive Haemophilus influenzae infections (IIHi) is noted in the post-vaccination era. The aim of this study was to characterize phenotypically and genotypically invasive Haemophilus influenzae (Hi) isolates detected in Tunisian pediatric patients. A retrospective study was conducted in the microbiology laboratory of the Children’s Hospital of Tunis over ten years (2013–2023). All IIHi cases were included. Molecular identification and serotyping were conducted through qPCR. Molecular typing and analysis of resistance genes were extracted from whole genome sequencing data. Fifty-three IIHi cases were collected. Children under five years old were the most affected (81%). Non-typable isolates (NTHi) were predominant (79%) followed by serotype b (17%) and serotype a (4%). Genetic diversity was observed, essentially among NTHi isolates. Resistance of Hi isolates to ampicillin, amoxicillin–clavulanic acid and cefotaxime (CTX) were 42%, 20% and 4%, respectively. Thirteen isolates (29%) produced a beta-lactamase and 14 carried the blaTEM-1 gene (kappa = 0.95). For non-enzymatic resistance, group 3 (n = 12) showed resistance to ampicillin. Groupe 4 (n = 9, NTHi) showed discordances with resistance to CTX. The emergence of resistance to CTX is concerning. Continuous surveillance through molecular tools in conjunction with phenotypic and clinical data is necessary to ensure better management of these infections. Full article
(This article belongs to the Section Antimicrobial Agents and Resistance)
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<p>Flowchart of the study. WGS: Whole genome sequencing; CNSPP: culture-negative samples, positive PCR.</p>
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<p>GrapeTree based on allelic profile of the cgMLST loci of invasive <span class="html-italic">Haemophilus influenzae</span> isolates. Isolates were indicated as in the <a href="#app1-microorganisms-12-02666" class="html-app">Supplementary Table S1</a> and were colored according to their serotypes. The number between the neighboring isolates indicated the number of different alleles of genes included in the cgMLST scheme (numbers refer to isolates references); encapsulated isolates were homogenously grouped compared to non-typeable <span class="html-italic">Haemophilus influenzae</span> isolates.</p>
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<p>Phylogenetic tree of the <span class="html-italic">ftsI</span> based on the sequence CLUSTALW multiple alignment of amino-acid sequences deduced of the DNA sequences of all <span class="html-italic">ftsI</span> alleles defined among the isolates of this study (Numbers refer to <span class="html-italic">ftsI</span> alleles); Group 1 and Group 2 were known to be correlated with a susceptible phenotype to beta-lactams, Group 3 to resistance to amoxicillin but not to cefotaxime and Group 4 to resistance to cefotaxime; these alleles are grouped homogenously on the phylogenetic tree according to their <span class="html-italic">ftsI</span> group.</p>
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15 pages, 4536 KiB  
Article
Transcriptome Analysis of the Harmful Dinoflagellate Heterocapsa bohaiensis Under Varied Nutrient Stress Conditions
by Peng Peng, Fangxin Han, Xue Gong, Xiangyuan Guo, Ying Su, Yiwen Zhang and Jingjing Zhan
Microorganisms 2024, 12(12), 2665; https://doi.org/10.3390/microorganisms12122665 - 22 Dec 2024
Viewed by 864
Abstract
The increasing prevalence of harmful algal blooms (HABs) driven by eutrophication, particularly in China’s nearshore waters, is a growing concern. Dinoflagellate Heterocapsa bohaiensis blooms have caused significant ecological and economic damage, as well as mass mortality, in cultivated species. Nutrients are one of [...] Read more.
The increasing prevalence of harmful algal blooms (HABs) driven by eutrophication, particularly in China’s nearshore waters, is a growing concern. Dinoflagellate Heterocapsa bohaiensis blooms have caused significant ecological and economic damage, as well as mass mortality, in cultivated species. Nutrients are one of the primary inducers of H. bohaiensis blooms. However, the transcriptomic studies of H. bohaiensis remain sparse, and its metabolic pathways are unknown. This study analyzed the transcriptome of H. bohaiensis under varying nutrient conditions (nitrogen at 128, 512, and 880 μM; phosphate at 8, 6, and 32 μM), focusing on differential gene expression. The results indicated that deviations in nutrient conditions (higher or lower N:P ratios) led to a higher number of differentially expressed genes compared to the control (N:P ratios = 27.5), thereby underscoring their pivotal role in growth. Gene Ontology (GO) enrichment analyses showed that nutrient limitation upregulated the biosynthesis and catabolism processes while downregulating the cell cycle and division functions. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that, under nitrogen limitation, the proteasome pathways were upregulated, while photosynthesis and carbon fixation were downregulated; under phosphorus limitation, the proteasome pathways were upregulated and nitrogen metabolism was downregulated. These findings suggest that H. bohaiensis adapts to nutrient stress by adjusting its metabolic processes. Full article
(This article belongs to the Special Issue Research on Biology of Dinoflagellates)
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<p>(<b>a</b>) Gene Ontology (GO) assignment and (<b>b</b>) KEGG assignment of assembled unigenes of <span class="html-italic">H. bohaiensis</span>.</p>
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<p>Differential genetic volcanoes of <span class="html-italic">H. bohaiensis</span> under different nitrogen concentration conditions ((<b>A</b>) LNP vs. NP; (<b>B</b>) LLNP vs. NP).</p>
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<p>GO enrichment of differential genes under nitrogen-limited conditions in <span class="html-italic">H. bohaiensis</span>: (<b>A</b>) upregulated; (<b>B</b>) downregulated.</p>
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<p>Differential genetic volcanoes of <span class="html-italic">H. bohaiensis</span> under different phosphorus concentration conditions ((<b>A</b>) HNP vs. NP; (<b>B</b>) HHNP vs. NP).</p>
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<p>GO enrichment of differential genes under phosphorus-limited conditions in <span class="html-italic">H. bohaiensis</span> ((<b>A</b>) upregulated; (<b>B</b>) downregulated).</p>
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<p>Different nitrogen (LLNP) and phosphorus (HHNP) conditions on photosynthesis enrichment pathway of <span class="html-italic">H. bohaiensis</span>. The red and green squares in the figure represent gene expression that is either up- or downregulated. The yellow squares represent gene expression that exhibits both up- and downregulation.</p>
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<p>Different nitrogen (LLNP) and phosphorus (HHNP) conditions on carbon fixation in photosynthetic organism enrichment pathway of <span class="html-italic">H. bohaiensis.</span> The red and green squares in the figure represent gene expression that is either up- or downregulated. The yellow squares represent gene expression that exhibits both up- and downregulation.</p>
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<p>Different nitrogen (LLNP) and phosphorus (HHNP) conditions on proteasome enrichment pathway of <span class="html-italic">H. bohaiensis</span>. The red squares in the figure represent gene expression that is upregulated. The yellow squares represent gene expression that exhibits both up- and downregulation.</p>
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<p>Different nitrogen (LLNP) and phosphorus (HHNP) conditions on nitrogen metabolism enrichment pathway of <span class="html-italic">H. bohaiensis</span>. The red and green squares in the figure represent gene expression that is either up- or downregulated. The yellow squares represent gene expression that exhibits both up- and downregulation.</p>
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19 pages, 1244 KiB  
Article
Phytochemical Analysis and Antimicrobial Activity of Terminalia bellirica (Gaertn.) Roxb. and Terminalia chebula Retz. Fruit Extracts Against Gastrointestinal Pathogens: Enhancing Antibiotic Efficacy
by Gagan Tiwana, Ian Edwin Cock and Matthew James Cheesman
Microorganisms 2024, 12(12), 2664; https://doi.org/10.3390/microorganisms12122664 - 22 Dec 2024
Viewed by 751
Abstract
Terminalia bellirica (Gaertn) Roxb. and Terminalia chebula Retz. are significant botanicals in ancient Ayurvedic medicine. They are renowned for their therapeutic properties, notably in addressing gastrointestinal (GI) diseases. These plants have undergone thorough examination related to their antibacterial, anti-inflammatory, and antioxidant properties, which [...] Read more.
Terminalia bellirica (Gaertn) Roxb. and Terminalia chebula Retz. are significant botanicals in ancient Ayurvedic medicine. They are renowned for their therapeutic properties, notably in addressing gastrointestinal (GI) diseases. These plants have undergone thorough examination related to their antibacterial, anti-inflammatory, and antioxidant properties, which make them highly efficient natural treatments for controlling gastrointestinal infections. The current research demonstrated the antibacterial efficacy of fruit extracts of Terminalia bellirica and Terminalia chebula against Bacillus cereus, Shigella sonnei, Shigella flexneri, and Salmonella typhimurium. We performed disc diffusion and liquid microdilution experiments to evaluate the antibacterial efficacy. All extracts of Terminalia bellirica and Terminalia chebula showed good antibacterial effects against B. cereus and S. flexneri. The minimum inhibitory concentration (MIC) values ranged from 94 µg/mL to 556 µg/mL. The methanolic extracts from both plants also showed noteworthy antibacterial activity against S. sonnei and S. typhimurium, with MIC values of 755 µg/mL for both. Fractional inhibitory concentration studies revealed additive interactions between some conventional antibiotics and the plant extracts when used concurrently. Liquid chromatography–mass spectrometry (LC-MS) analyses revealed that the T. bellirica and T. chebula extracts contained various tannins including methyl gallate, propyl gallate, gallic acid, and ellagic acid. Lethality assays conducted using Artemia franciscana Kellogg nauplii indicated that all the plant extracts are non-toxic. The antibacterial properties and absence of toxicity in T. bellirica and T. chebula fruit extracts indicate their potential for antibiotic development, warranting additional mechanistic and phytochemical studies. Full article
(This article belongs to the Special Issue Plant Extracts and Antimicrobials, Second Edition)
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<p>Antimicrobial activity of <span class="html-italic">T. bellirica</span> and <span class="html-italic">T. chebula</span> fruit extracts in the disc diffusion assays against (<b>A</b>) <span class="html-italic">B. cereus</span>, (<b>B</b>) <span class="html-italic">S. flexneri</span>, (<b>C</b>) <span class="html-italic">S. sonnei</span>, (<b>D</b>) <span class="html-italic">S. typhimurium</span>. TB-AQ = <span class="html-italic">T. bellirica</span> aqueous (50.2 mg/mL); TB-MeOH = <span class="html-italic">T. bellirica</span> methanolic (48.3 mg/mL); TB-EtOAc = <span class="html-italic">T. bellirica</span> ethyl acetate (4.9 mg/mL). TCh-AQ = <span class="html-italic">T. chebula</span> aqueous (35.6 mg/mL); TCh-MeOH = <span class="html-italic">T. chebula</span> methanol (48.3 mg/mL); TCh-EtOAc = <span class="html-italic">T. chebula</span> ethyl acetate (4.9 mg/mL). Negative controls = 1% DMSO and blank = sterile water. Reference antibiotics: PEN G = penicillin G (10 IU), ERY = erythromycin (10 µg), TET = tetracycline (30 µg), CHL = chloramphenicol (30 µg), CIP = ciprofloxacin (1 µg), POL B = polymyxin B (300IU), OXA = oxacillin (1 µg), AMX = amoxycillin (10 µL of 0.01 mg/mL stock solution), GEN = gentamicin (10 µg), VAN = vancomycin (30 µg), AUG = Augmentin<sup>®</sup> (15 µg), CEF = cefoxitin (30 µg). Horizontal red lines on the <span class="html-italic">y</span>-axis at 6 mm indicate the disc diameter used in the assay. Mean values (±SEM) are reported from three independent studies. <span class="html-italic">p</span>-values &lt; 0.05 are represented with a single asterisk symbol (*), while <span class="html-italic">p</span>-values &lt; 0.01 are represented with a double asterisk symbol (**).</p>
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<p>Structures of noteworthy compounds identified in the fruit extracts of <span class="html-italic">T. bellirica</span> and <span class="html-italic">T. chebula</span>. Methyl gallate (<b>A</b>), propyl gallate (<b>B</b>), gallic acid (<b>C</b>), ellagic acid (<b>D</b>), hamamelitannin (<b>E</b>), pyrogallol (<b>F</b>), quercetin (<b>G</b>), 6-galloylglucose (<b>H</b>), gallic acid 3-O-(6-galloylglucoside) (<b>I</b>), 1,2,6-trigalloyl-β-D-glucopyranose (<b>J</b>), 1,3,6-tri-O-galloyl-β-D-glucose (<b>K</b>), 1,6-bis-O-(3,4,5-trihydroxybenzoyl) hexopyranose (<b>L</b>), chebulic acid (<b>M</b>), and chebuloside II (<b>N</b>). Structures were prepared using Chemsketch Version 2024.</p>
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17 pages, 4623 KiB  
Article
Development of a TaqMan qPCR for the Simultaneous Detection of the TuMV and BBWV2 Viruses Responsible for the Viral Disease in Pseudostellaria heterophylla
by Li Gu, Chensi Liu, Shuting Yao, Jiaxin Wu, Lianghong Wang, Jing Mu, Yankun Wang, Jianming Wang, Zhongyi Zhang and Mingjie Li
Microorganisms 2024, 12(12), 2663; https://doi.org/10.3390/microorganisms12122663 - 22 Dec 2024
Viewed by 467
Abstract
Pseudostellaria heterophylla (Miq.) Pax, a highly valued Chinese medicinal plant, is experiencing a notable decline in yield and quality due to viral diseases, particularly caused those by TuMV and BBWV2. Currently, the absence of a quantitative detection method for these viruses in P. [...] Read more.
Pseudostellaria heterophylla (Miq.) Pax, a highly valued Chinese medicinal plant, is experiencing a notable decline in yield and quality due to viral diseases, particularly caused those by TuMV and BBWV2. Currently, the absence of a quantitative detection method for these viruses in P. heterophylla impedes the accurate diagnosis. The development of an accurate quantitative detection method is thus essential for effectively managing viral diseases in this plant. In this study, singleplex and duplex TaqMan qPCR were developed for the detection of the two viruses, based on two viral cloning vectors. Concurrently, the levels of both viruses were examined in the main produced regions of P. heterophylla. Furthermore, the levels of BBWV2 were examined during its infection of P. heterophylla. The optimal singleplex qPCR employed 0.1 μM of hydrolysis probe and 0.1 μM of primer for TuMV, while 0.2 μM of hydrolysis probe and 0.1 μM of primer were utilised for BBWV2. In contrast, the duplex qPCR employed the use of 0.1 μM of the upstream/downstream primer from each primer pair, with 0.2 μM of the respective hydrolysis probes. The 95% limit of detection (LOD) for singleplex qPCR was 734 copies for TuMV and 20 copies for BBWV2, while the 95% LOD for duplex qPCR was 945 copies for TuMV and 47 copies for BBWV2. Furthermore, the intra- and inter-assay coefficients of variation were found to be less than 1.2% for both singleplex and duplex qPCR. Of the P. heterophylla sampled 60 sites, 96% were found to be infected by one of two viruses. The levels of BBWV2 in N. benthamiana and P. heterophylla demonstrated an initial increase, followed by a subsequent decrease. The TaqMan qPCR methods provide a technical foundation for the monitoring of virus infections in P. heterophylla. Full article
(This article belongs to the Section Virology)
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<p>The construction process of the <span class="html-italic">P. heterophylla</span> BBWV2 cloning vector and infectious cloning vector. The RNA1 and RNA2 genomes from the BBWV2 virus were transferred into the pSMART (Lucigen)-E cloning vector, respectively (<b>A</b>). Subsequently, the RNA1 and RNA2 genomes of the BBWV2 virus in the pSMART-E vector were further transferred into the pCB301 expression vector, thereby forming the BBWV2 infectious clone vector (<b>B</b>,<b>C</b>).</p>
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<p>The evaluation for the initial detection range of singleplex (<b>A</b>,<b>B</b>) and duplex (<b>C</b>,<b>D</b>) TaqMan qPCR by using virus standard plasmid with a range of 10<sup>5</sup> to 10<sup>0</sup> copies/μL.</p>
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<p>The standard curve of singleplex and duplex TaqMan qPCR. The standard curve for TaqMan qPCR, used for the singleplex (<b>A</b>) and duplex detection (<b>B</b>) of the BBWV2 or TuMV virus, was identified using the concentrations of virus standard plasmid ranging from 10<sup>9</sup> to 10<sup>3</sup>. The linear equations between Cq values and virus concentration were obtained by utilising the qPCR Cq values of two viruses as the independent variable (y) and the corresponding plasmid concentration (Log x) as the dependent variable.</p>
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<p>The symptoms of the viral disease of <span class="html-italic">P. heterophylla</span> for partial samples from the main cultivation region of <span class="html-italic">P. heterophylla</span>. The figure illustrates the infection levels of the TuMV and BBWV2 viruses, as determined via duplex TaqMan qPCR. Detailed infection level data across the various samples can be found in <a href="#app1-microorganisms-12-02663" class="html-app">Table S4</a>, which provides a summary of the infection levels in <span class="html-italic">P. heterophylla</span> at 60 sampling sites. It should be noted that the present study has only identified <span class="html-italic">P. heterophylla</span> TuMV and BBWV2. However, <span class="html-italic">P. heterophylla</span> has previously been shown to harbour a variety of viruses and their subtypes. Consequently, the virus symptoms displayed in the figure may not wholly be attributable to the presence of these two viruses. It is more probable that the observed disease results from a combination of multiple viral infections.</p>
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<p>The phenotypic characteristics and BBWV2 levels of <span class="html-italic">N. benthamiana</span> following infection with BBWV2 infectious clones. The external characteristics <span class="html-italic">N. benthamiana</span> following infection with BBWV2 infectious clones were observed (<b>A</b>). The presence of the BBWV2 infectious clone in <span class="html-italic">N. benthamiana</span> was determined through the use of PCR methods (<b>B</b>). The singleplex qPCR was employed to detect BBWV2 levels during its process of infecting <span class="html-italic">N. benthamiana</span> (<b>C</b>).</p>
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<p>The phenotypic characteristics and BBWV2 levels of <span class="html-italic">P. heterophylla</span> following the infection with BBWV2 infections clones. The phenotypic characteristics of <span class="html-italic">P. heterophylla</span> at varying stages after injection with BBWV2 infectious clones were observed (<b>A</b>). BBWV2 levels in the leaves and roots of these <span class="html-italic">P. heterophylla</span> were identified through singleplex TaqMan qPCR for BBWV2 detection (<b>B</b>,<b>C</b>).</p>
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18 pages, 7731 KiB  
Article
Identification, Characterization, and Ultrastructure Analysis of the Phenol-Degrading Rhodococcus erythropolis 7Ba and Its Viable but Nonculturable Forms
by Valentina N. Polivtseva, Anton N. Zvonarev, Olesya I. Sazonova, Yanina A. Delegan, Yulia N. Kocharovskaya, Alexander G. Bogun and Nataliya E. Suzina
Microorganisms 2024, 12(12), 2662; https://doi.org/10.3390/microorganisms12122662 - 22 Dec 2024
Viewed by 538
Abstract
Phenol and its chlorinated derivatives are introduced into the environment with wastewater effluents from various industries, becoming toxic pollutants. Phenol-degrading bacteria are important objects of research; among them, representatives of the genus Rhodoccocus are often highlighted as promising. Strain 7Ba was isolated by [...] Read more.
Phenol and its chlorinated derivatives are introduced into the environment with wastewater effluents from various industries, becoming toxic pollutants. Phenol-degrading bacteria are important objects of research; among them, representatives of the genus Rhodoccocus are often highlighted as promising. Strain 7Ba was isolated by enrichment culture. A new isolate was characterized using culturing, biochemistry, high-throughput sequencing, microscopy (including electron microscopy), and functional genome analysis. Rhodococcus erythropolis strain 7Ba is able to grow on phenol and chlorophenols without losing its properties during long-term storage. It was shown that strain 7Ba is able to form viable but nonculturable (VBNC) forms during long-term storage under nutrient limitation, preserving both cell viability and the ability to degrade phenols. The ultrastructural organization of the vegetative forms of cells and VBNC forms was characterized. The following distinctive features were found: modifications (thickening) of cell membranes, cell size reduction, nucleoid condensation. Functional analysis of the genome showed the presence of genes for the degradation of alkanes, and two branches of the β-ketoadipate pathway for the degradation of aromatic compounds. Also, the genome of strain 7Ba contains several copies of Rpf (resuscitation promoting factor) genes, a resuscitation factor of resting bacterial forms. The new isolate strain 7Ba is a promising biotechnological agent that can not only utilize toxic aromatic compounds but also remain viable during long-term storage. For this reason, its further application as an agent for bioremediation can be successful under changing conditions of climate and given the deficiency of nutrient compounds in nature. Minor biostimulation will allow the strain to recover its metabolic activity and effectively degrade pollution. Full article
(This article belongs to the Section Environmental Microbiology)
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<p>Growth of strain 7Ba on phenol: (<b>a</b>) vegetative cells 7Ba from the reseeded culture, phenol 0.5 g/L, (<b>b</b>) vegetative cells 7Ba from the reseeded culture, phenol 1 g/L, (<b>c</b>) 7Ba(24) cells (vegetative cells of strain 7Ba after dormancy at 24 °C), phenol 0.5 g/L, (<b>d</b>) 7Ba(24) cells (vegetative cells of strain 7Ba after dormancy at 24 °C), phenol 1 g/L, (<b>e</b>) 7Ba(24) cells (vegetative cells of strain 7Ba after dormancy at 24 °C), phenol up to 2 g/L.</p>
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<p>Degradation level of phenol by 7Ba and 7Ba (24). Values are mean ± SD of triplicate sets, * <span class="html-italic">p</span>-value ≤ 0.05 and ** <span class="html-italic">p</span>-value = less than 0.001 represent the significant difference between variants.</p>
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<p>Cell morphology of strain 7Ba: (<b>a</b>) vegetative cells 7Ba from the reseeded culture grown on LB medium for 48 h, (<b>b</b>) VBNC cells of the 7Ba(4), (<b>c</b>) VBNC cells of the 7Ba(24). Phase-contrast microscopy. Scale bar—10 μm.</p>
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<p>Ultrastructural organization of cells of strain 7Ba: (<b>a</b>) vegetative cells 7Ba from the reseeded culture, (<b>b</b>) VBNC cells of 7Ba(4), (<b>c</b>) VBNC 7Ba(24), (<b>d</b>) VBNC 7Ba(24) after 3.5 years of storage. Transmission electron microscopy. Designations: CM—cytoplasm membrane, CW—cell wall, Inc—inclusions, M—murein, MlOL—“membrane-like limiting outer layer”, Mls—myeline-like structures, N—nucleoid, IM—inner space between cytoplasm membrane and peptidoglycan layer.</p>
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<p>Cells of strain 7Ba stained with Live/Dead dye. (<b>a</b>) vegetative cells 7Ba from the reseeded culture, (<b>b</b>) VBNC cells of the 7Ba(24) after 3.5 years of storage. Cells that are green in color are live cells, dead cells are red in color. Fluorescence microscopy.</p>
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<p>Phylogenetic tree showing the position of strain 7Ba within the genus <span class="html-italic">Rhodococcus</span>. The genomes of only type strains were used in the construction of the tree. The strain under study is labeled in red.</p>
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<p>Genomic fingerprint of strain <span class="html-italic">Rhodococcus</span> sp. 7Ba with primers BoxA1R and (GTG)<sub>5</sub>. The figure demonstrates changes in the genome by the presence of Box A1R (circles) and (GTG)<sub>5</sub> (index line) sequence amplification products for different samples. M—GeneRuler 1 kb Plus DNA Ladder, 1—vegetative cells of the 7Ba(4) (vegetative cells of strain 7Ba after dormancy at 4 °C), 2—VBNC cells of the 7Ba(24), 3—vegetative cells of the 7Ba(24) (vegetative cells of strain 7Ba after dormancy at 24 °C), 4—vegetative cells of the 7Ba routinely reseed into laboratory culture.</p>
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12 pages, 577 KiB  
Article
Correlation of Geographic Variables with the Incidence Rate of Dengue Fever in Mexico: A 38-Year Study
by Porfirio Felipe Hernández Bautista, David Alejandro Cabrera Gaytán, Alfonso Vallejos Parás, Olga María Alejo Martínez, Lumumba Arriaga Nieto, Brenda Leticia Rocha Reyes, Carmen Alicia Ruíz Valdez, Leticia Jaimes Betancourt, Gabriel Valle Alvarado, Yadira Pérez Andrade and Alejandro Moctezuma Paz
Microorganisms 2024, 12(12), 2661; https://doi.org/10.3390/microorganisms12122661 - 22 Dec 2024
Viewed by 520
Abstract
Background: Dengue is a viral disease transmitted by the mosquitoes Aedes, which is characterized by fever, myalgia and arthralgia. In some cases, it can be fatal. For many years, dengue fever has been endemic to Mexico; however, few studies have investigated the [...] Read more.
Background: Dengue is a viral disease transmitted by the mosquitoes Aedes, which is characterized by fever, myalgia and arthralgia. In some cases, it can be fatal. For many years, dengue fever has been endemic to Mexico; however, few studies have investigated the historical and current extents of dengue fever at the national level or considered the effects of variables such as temperature, precipitation and elevation on its occurrence. Methods: An ecological study was carried out to compare the incidence rates of different types of dengue fever per hundred thousand inhabitants with temperature, precipitation and elevation between 1985 and 2023 in Mexico. The sources of information were the public records of the Ministry of Health and the National Meteorological Service. Multiple linear regression analysis was performed with Pearson and Spearman correlation coefficients at an alpha of <0.05. Results: The global linear regression presented an R2 of 0.68 between the mean temperature and the cases of haemorrhagic dengue/severe/with warning signs. The degree of rainfall was not strongly correlated with the incidence rate, except in the eastern part of the country, where average temperature was also strongly correlated with the incidence rate. Nonsevere/classic dengue was most common from 1501 to 2000 m elevation, whereas severe forms of the disease were more prevalent at elevations greater than 2000 m. Full article
(This article belongs to the Special Issue Climate Change and Emerging Arboviruses)
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<p>Dengue incidence rate by type and temperature in Mexico, 1985—2023.</p>
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<p>Haemorrhagic dengue/severe dengue and average temperature in the Eastern Region of Mexico.</p>
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9 pages, 273 KiB  
Case Report
Trypanosoma cruzi DNA Identification in Breast Milk from Mexican Women with Chagas Disease
by María del Pilar Crisóstomo-Vázquez, Griselda Rodríguez-Martínez, Verónica Jiménez-Rojas, Leticia Eligio-García, Alfonso Reyes-López, María Hernández-Ramírez, Francisco Hernández-Juárez, José Luis Romero-Zamora, Silvia Guadalupe Vivanco-Tellez, Fortino Solorzano-Santos, Victor M. Luna-Pineda and Guillermina Campos-Valdez
Microorganisms 2024, 12(12), 2660; https://doi.org/10.3390/microorganisms12122660 - 21 Dec 2024
Viewed by 761
Abstract
(1) Background: Chagas disease is a public health problem affecting nearly 2 million women of reproductive age in Latin America. From these, 4–8% can transmit the infection to the foetus through the vertical route, whereas horizontal transmission through milk during breastfeeding remains controversial. [...] Read more.
(1) Background: Chagas disease is a public health problem affecting nearly 2 million women of reproductive age in Latin America. From these, 4–8% can transmit the infection to the foetus through the vertical route, whereas horizontal transmission through milk during breastfeeding remains controversial. Therefore, the presence of Trypanosoma cruzi (T. cruzi) DNA in the milk of women seropositive for Chagas disease was analysed to determine whether a relationship with the infection of their children can exist. (2) Methods: 260 pairs (mother–child) from four hospitals located in rural areas endemic to T. cruzi (state of Oaxaca) were studied. The presence of anti-T. cruzi antibodies in the serum of lactating women were determined by ELISA, whereas parasitic DNA in either breast milk or newborn’s blood was identified by PCR; (3) Results: The seroprevalence of infection in lactating women was 5.76%, and the frequency of infection detected by PCR in breast milk was 1.92%, while the frequency of infection in the blood of newborns was 1.92%. Pochutla-Oaxaca presented the highest number of positive cases in both breast milk and blood. The only risk factor found was the presence of the vector in the geographical area analysed, favouring the parasite’s transmission. Overall, the results suggest a probable transmission of T. cruzi, although whether it was through breastfeeding or through the blood during delivery could not be determined. (4) Conclusions: T. cruzi DNA was identified in lactating women’s milk and newborn blood, which is probable evidence of transmission through breastfeeding; nevertheless, future studies must be performed to confirm the presence of the parasite, alive or dead. Full article
(This article belongs to the Special Issue Parasitic Infection and Host Immunity, 2nd Edition)
14 pages, 3946 KiB  
Systematic Review
White Coats at a Crossroads: Hygiene, Infection Risk, and Patient Trust in Healthcare Attire—An Umbrella Review with Quantitative Synthesis and Stress, Weaknesses, Opportunities, and Threats Analysis
by Christos Tsagkaris, Matthias Rueger, Samuel B. Tschudi and Thomas Dreher
Microorganisms 2024, 12(12), 2659; https://doi.org/10.3390/microorganisms12122659 - 21 Dec 2024
Viewed by 583
Abstract
White coats, traditionally symbols of physicians’ hygiene and professionalism, are now scrutinized for potential infection risks during patient interactions. This review investigates whether wearing white coats is linked to microbial contamination, infection transmission, and patient expectations. An umbrella review of peer-reviewed studies and [...] Read more.
White coats, traditionally symbols of physicians’ hygiene and professionalism, are now scrutinized for potential infection risks during patient interactions. This review investigates whether wearing white coats is linked to microbial contamination, infection transmission, and patient expectations. An umbrella review of peer-reviewed studies and guidelines was conducted, with searches in PubMed/Medline and Scopus using terms related to medical attire, infection control, patient perceptions, and discrimination. Ten records were included, and a bibliometric analysis was performed with VOS Viewer. Bias appraisal was conducted using the JBI Bias Assessment Toolset, and a SWOT analysis was developed to support evidence-based decision-making. Findings indicate that white coats may harbor pathogens such as Staphylococcus aureus, Gram-positive cocci, Gram-negative rods, and MRSA. To mitigate contamination risks, it is recommended that physicians roll up coat sleeves during examinations and that the coats receive daily laundering in healthcare settings. However, evidence supporting a coatless policy is yet to be published. Patients tend to expect physicians to wear identifiable attire, like white coats or scrubs for surgeons. Recent research in this field shifts the focus from infection control to the impact of attire on patient trust and physician–patient relationships. Full article
(This article belongs to the Collection Feature Papers in Public Health Microbiology)
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<p>PRISMA flowchart.</p>
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<p>Thematic connection of keywords in research related to use of white coats. Interrelated thematic areas are marked with the same color. The shortened terms “amb” and “p” refer to “ambulatory” (blood pressure monitoring) and practices, in the frame of “health knowledge, attitudes, practices” (KAP) framework.</p>
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<p>Evolution of keywords used to describe research on white coats in time. The shortened terms “amb” and “p” refer to “ambulatory” (blood pressure monitoring) and practices, in the frame of “health knowledge, attitudes, practices” (KAP) framework.</p>
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<p>Thematic density of keywords used to describe research on white coats. Yellow marks the highest thematic density, followed by shades of green in declining intensity. The shortened terms “amb” and “p” refer to “ambulatory” (blood pressure monitoring) and practices, in the frame of “health knowledge, attitudes, practices” (KAP) framework.</p>
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18 pages, 4133 KiB  
Article
Differential Immunological Responses of Adult Domestic and Bighorn Sheep to Inoculation with Mycoplasma ovipneumoniae Type Strain Y98
by Sally A. Madsen-Bouterse, David R. Herndon, Paige C. Grossman, Alejandra A. Rivolta, Lindsay M. Fry, Brenda M. Murdoch and Lindsay M. W. Piel
Microorganisms 2024, 12(12), 2658; https://doi.org/10.3390/microorganisms12122658 - 21 Dec 2024
Viewed by 484
Abstract
Bighorn sheep (BHS) populations have been reported to experience high levels of morbidity and mortality following infection with Mycoplasma ovipneumoniae. This contrasts with the subclinical presentation in domestic sheep (DS). Understanding this difference requires baseline knowledge of pre- and post-infection immune responses [...] Read more.
Bighorn sheep (BHS) populations have been reported to experience high levels of morbidity and mortality following infection with Mycoplasma ovipneumoniae. This contrasts with the subclinical presentation in domestic sheep (DS). Understanding this difference requires baseline knowledge of pre- and post-infection immune responses of both species. The present study identifies differences in leukocyte phenotypes between adult BHS and DS before and after intranasal inoculation with 1 × 108 Mycoplasma ovipneumoniae. Prior to inoculation, BHS were confirmed to have a higher abundance of leukocyte CD14 and serum concentrations of IL-36RA. In contrast, DS had a higher leukocyte abundance of CD16 in addition to previously observed integrin markers and CD172a, as well as greater serum TNF-α concentrations. Within 15 days of inoculation, BHS displayed signs of mild respiratory disease and M. ovipneumoniae DNA was detected on nasal swabs using a quantitative PCR; meanwhile, DS exhibited few to no clinical signs and had levels of M. ovipneumoniae DNA below the standard curve threshold. Immunologic markers remained relatively consistent pre- and post-inoculation in DS, while BHS demonstrated changes in the peripheral leukocyte expression of CD172a and CD14. Circulating serum IL-36RA decreased and CXCL10 increased within BHS. These findings highlight significant differences in cellular immunity between BHS and DS, raised and housed under similar conditions, prior to and following inoculation with M. ovipneumoniae. Full article
(This article belongs to the Special Issue Advances in Mycoplasma Research)
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<p><span class="html-italic">M. ovipneumoniae</span> detected on nasal swabs using a quantitative PCR in DS and BHS. (<b>A</b>) Cycle thresholds (Cq) measured from DNA extracted from nasal swabs. BHS are represented by open circles (○) and DS are represented by open triangles (Δ). The solid line is the standard curve limit of quantification (33.52 Cq) associated with ten copies of genomic equivalents. (<b>B</b>) Bacterial genomic equivalents calculated on a per-nasal-swab basis. The line indicates the limit of quantification (500 copies per swab) at the standard which measures ten bacterial copies. Fractions in DS bars indicate the number of subjects detected per the five animals enrolled in the study. Asterisks indicate a <span class="html-italic">p</span>-value &lt; 0.05 and error bars represent the standard error.</p>
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<p>Clinical signs noted in bighorn and domestic sheep following inoculation with <span class="html-italic">M. ovipneumoniae</span>. Coughing was scored daily based on presence (1) or absence (0). The weekly clinical score was calculated by summing the daily scores for the week. In contrast, nasal discharge severity was observed twice a day and marked as a 0 to 5, where 0 = no discharge, 1 = mild discharge, 2 = moderate discharge, 3 = moderately severe discharge, 4 = severe discharge, and 5 = excessive discharge. Each animal’s weekly nasal discharge score was calculated by averaging the week’s scores and dividing by the number of times the animal was observed. Each point represents an individual animal enrolled in the study and asterisks indicate a <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Peripheral leukocyte profiles in BHS and DS. (<b>A</b>) Percent of resting cellular populations calculated by observing 100 cells during manual differentials. Open bars are BHS and closed bars are DS. (<b>B</b>) Mean percent of neutrophils (black), lymphocytes (blue), and monocytes (orange) from the total leukocyte population for each species over the course of observation using flow cytometry. Bighorn sheep are represented by open circles (○) and domestic sheep are represented by solid circles (●). Both graphs have standard error incorporated and a <span class="html-italic">p</span>-value &lt; 0.05 indicated by an * or &lt;0.005 indicated by **. Significance in (<b>B</b>) is a comparison between the labeled day and day minus seven.</p>
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<p>Gating strategies for leukocyte cell type and adhesin markers. Each density dot plot is from seven days prior to inoculation and is based on the total leukocyte population. Side-scatter (SSC) and autofluorescence were used to differentiate between neutrophils, eosinophils, and peripheral blood mononuclear cells (PBMCs) in the left-hand image for each cluster of differentiation. The right-hand image for either marker shows the gating used to distinguish dim and bright populations of CD172a, as well as upper right and lower right populations of CD62L-positive lymphocytes.</p>
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<p>CD11b MFI in PBMCs following inoculation with <span class="html-italic">M. ovipneumoniae</span>. The asterisk indicates a <span class="html-italic">p</span>-value &lt; 0.05 and is comparing the day marked to day minus seven.</p>
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<p>Adhesin expression changes in neutrophils and PBMCs following inoculation. CD172a is blue and CD62L is black, with UR having solid lines and LR having dashed lines. (<b>A</b>) The median fluorescence intensity for either marker in neutrophils, (<b>B</b>) the MFI for CD62L UR and LR measured in PBMCs, and (<b>C</b>) the MFI for CD172a+ in PBMCs. Significance is marked to the upper right of the graphed data point, where points that overlap are indicated by either DS or BHS. A <span class="html-italic">p</span>-value &lt; 0.05 is indicated by * and &lt;0.005 indicated by **, where the labeled day is compared to day minus seven.</p>
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<p>CD14 abundance in neutrophil and PBMC populations following inoculation. Solid lines are neutrophils and dashed lines are PBMCs. Asterisks mark the day in question for comparison to day minus seven, where * is a <span class="html-italic">p</span>-value &lt; 0.05 and ** is a <span class="html-italic">p</span>-value &lt; 0.005.</p>
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<p>Pre-inoculation serum cytokine concentrations. (<b>A</b>) Cytokines with values below 1000 pg/mL and (<b>B</b>) those with values above 1000 pg/mL. A <span class="html-italic">p</span>-value &lt; 0.05 is marked with an asterisk.</p>
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<p>Serum cytokine fold change relative to day one post-inoculation. Serum concentrations measured each week were divided by day one cytokine concentrations to achieve a relative fold change. BHS are represented by open black circles, while DS are represented by open blue triangles. A <span class="html-italic">p</span>-value &lt; 0.05 is labeled with an asterisk and represents significant difference to day one or between species.</p>
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<p>BHS and DS serum antibodies to Mycoplasma ovipneumoniae pre-inoculation and 28-days post-inoculation. The ladder and associated kDa values are in the first sample lane. Thereafter, the pre-sample is in the first lane for each animal in the inoculation study and is followed by the 28-day post-inoculation (dPI) serum sample.</p>
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20 pages, 8907 KiB  
Article
Proline Improves Pullulan Biosynthesis Under High Sugar Stress Condition
by Keyi Liu, Junqing Wang, Feng Li, Ruiming Wang, Qingming Zeng, Zhenxing Zhang, Hongwei Liu and Piwu Li
Microorganisms 2024, 12(12), 2657; https://doi.org/10.3390/microorganisms12122657 - 21 Dec 2024
Viewed by 480
Abstract
Pullulan is an extracellular polysaccharide produced via the fermentation of Aureobasidium pullulans. However, high sugar concentrations and hyperosmotic stress limit pullulan biosynthesis during the fermentation process. Therefore, we investigated the effects of proline supplementation on A. pullulans growth and pullulan biosynthesis [...] Read more.
Pullulan is an extracellular polysaccharide produced via the fermentation of Aureobasidium pullulans. However, high sugar concentrations and hyperosmotic stress limit pullulan biosynthesis during the fermentation process. Therefore, we investigated the effects of proline supplementation on A. pullulans growth and pullulan biosynthesis under high sugar and hyperosmotic stress using physiological, biochemical, and transcriptomic analyses. High sugar concentrations significantly inhibited A. pullulans growth and pullulan biosynthesis. High sugar and hyperosmotic stress conditions significantly increased intracellular proline content in A. pullulans. However, treatment with proline (400 mg/L proline) significantly increased biomass and pullulan yield by 10.75% and 30.06% (174.8 g/L), respectively, compared with those in the control group. To further investigate the effect of proline on the fermentation process, we performed scanning electron microscopy and examined the activities of key fermentation enzymes. Proline treatment preserved cell integrity and upregulated the activities of key enzymes involved in pullulan biosynthesis. Transcriptome analysis revealed that most differentially expressed genes in the proline group were associated with metabolic pathways, including glycolysis/gluconeogenesis, pyruvate metabolism, and sulfur metabolism. Conclusively, proline supplementation protects A. pullulans against high sugar and hyperosmotic stress, providing a new theoretical basis and strategy for the efficient industrial production of pullulans. Full article
(This article belongs to the Special Issue Advances in Metabolic Engineering of Industrial Microorganisms)
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<p>Effect of different sugar concentrations on pullulan production and <span class="html-italic">Aureobasidium pullulans</span> growth: Pullulan yield (<b>a</b>); cell biomass (<b>b</b>).</p>
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<p>Changes in the contents of glutamic acid, glycine, and proline under different sucrose concentrations were evaluated. Significant differences (<span class="html-italic">p</span> &lt; 0.05) were determined using a one-way analysis of variance with Duncan’s test and represented using different letters.</p>
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<p>Effects of exogenous supplementation of glutamic acid, glycine, and proline on biomass (<b>a</b>) and pullulan yield (<b>b</b>) under high sugar conditions (200 g/L) and on biomass (<b>c</b>) and pullulan yield (<b>d</b>) under low sugar conditions (100 g/L). Significant differences (<span class="html-italic">p</span> &lt; 0.05) were determined using a one-way analysis of variance with Duncan’s test and represented using different letters.</p>
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<p>Effect of exogenous proline on proline (<b>a</b>) and glycerol (<b>b</b>) concentration in <span class="html-italic">Aureobasidium pullulans</span> cells at different sucrose concentrations (100 and 200 g/L).</p>
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<p>Comparative analysis of scanning electron microscopy images of the experimental and control groups in the absence of proline: (<b>a</b>) Control cells, magnification: 10,000×. (<b>b</b>) Control cells, magnification: 2500×. (<b>c</b>) Cells in the experimental group, magnification: 10,000×. (<b>d</b>) Cells in the experimental group, magnification: 2500×.</p>
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<p>Activities of pullulan biosynthetic and degrading enzymes in the experimental and control groups in the presence or absence of proline at different fermentation stages. UGP: UDP–glucose pyrophosphorylase (<b>a</b>); PGM: α-phosphoglucomutase (<b>b</b>); UGT: UDP–glucosyltransferase (<b>c</b>); AMY: α-amylase (<b>d</b>); IPU: isopullulanase (<b>e</b>). Asterisks indicate the level of significance using the Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span>  &lt;  0.05; ** <span class="html-italic">p</span>  &lt;  0.01) in comparison to the control without proline addition.</p>
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<p>Sample correlation heat map (<b>a</b>). Statistics of differentially expressed genes (DEGs) (<b>b</b>). Volcano plot (<b>c</b>) and heatmap (<b>d</b>) showing gene expression patterns in the control (CK) and proline (CP) groups. CK: <span class="html-italic">Aureobasidium pullulans</span> cultivated for 24 h in the initial fermentation medium; CP: <span class="html-italic">A</span>. <span class="html-italic">pullulans</span> cultivated for 24 h in the fermentation medium containing proline. In the volcano plot of differential genes, each point represents a gene, with red representing upregulation and blue representing downregulation. In the differential comparison clustering heat map, the expression levels of genes in different samples are represented by different colors.</p>
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<p>Gene ontology (GO) enrichment circle diagram (<b>a</b>): The first circle represents the top 20 enriched GO terms, the second circle represents the number and Q value of the GO term in the background of differential genes, and the third circle represents the proportion of upregulated and downregulated DEGs. GO enrichment difference bubble chart (<b>b</b>): The ordinate is -log10 (Q value), and the abscissa is the z-score value. GO enrichment classification histogram (<b>c</b>): abscissa is the secondary GO term, ordinate is the number of differential genes in the term, and different colors represent different types of GO terms.</p>
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<p>Gene ontology (GO) enrichment circle diagram (<b>a</b>): The first circle represents the top 20 enriched GO terms, the second circle represents the number and Q value of the GO term in the background of differential genes, and the third circle represents the proportion of upregulated and downregulated DEGs. GO enrichment difference bubble chart (<b>b</b>): The ordinate is -log10 (Q value), and the abscissa is the z-score value. GO enrichment classification histogram (<b>c</b>): abscissa is the secondary GO term, ordinate is the number of differential genes in the term, and different colors represent different types of GO terms.</p>
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<p>Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment circle diagram (<b>a</b>): The first circle represents the top 20 enriched pathways, the second circle represents the number and Q value of the pathway, and the third circle represents the proportion of upregulated and downregulated DEGs. KEGG enrichment difference bubble chart (<b>b</b>): The ordinate is −log10 (Q value), and the abscissa is the z-score value. KEGG enrichment secondary classification histogram (<b>c</b>): the top 20 KEGG enriched pathways.</p>
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<p>Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment circle diagram (<b>a</b>): The first circle represents the top 20 enriched pathways, the second circle represents the number and Q value of the pathway, and the third circle represents the proportion of upregulated and downregulated DEGs. KEGG enrichment difference bubble chart (<b>b</b>): The ordinate is −log10 (Q value), and the abscissa is the z-score value. KEGG enrichment secondary classification histogram (<b>c</b>): the top 20 KEGG enriched pathways.</p>
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16 pages, 946 KiB  
Review
Host Long Noncoding RNAs as Key Players in Mycobacteria–Host Interactions
by Stephen K. Kotey, Xuejuan Tan, Audrey L. Kinser, Lin Liu and Yong Cheng
Microorganisms 2024, 12(12), 2656; https://doi.org/10.3390/microorganisms12122656 - 21 Dec 2024
Viewed by 645
Abstract
Mycobacterial infections, caused by various species within the Mycobacterium genus, remain one of the main challenges to global health across the world. Understanding the complex interplay between the host and mycobacterial pathogens is essential for developing effective diagnostic and therapeutic strategies. Host long [...] Read more.
Mycobacterial infections, caused by various species within the Mycobacterium genus, remain one of the main challenges to global health across the world. Understanding the complex interplay between the host and mycobacterial pathogens is essential for developing effective diagnostic and therapeutic strategies. Host long noncoding RNAs (lncRNAs) have emerged as key regulators in cellular response to bacterial infections within host cells. This review provides an overview of the intricate relationship between mycobacterial infections and host lncRNAs in the context of Mycobacterium tuberculosis and non-tuberculous mycobacterium (NTM) infections. Accumulation of evidence indicates that host lncRNAs play a critical role in regulating cellular response to mycobacterial infection within host cells, such as macrophages, the primary host cells for mycobacterial intracellular survival. The expression of specific host lncRNAs has been implicated in the pathogenesis of mycobacterial infections, providing potential targets for the development of novel host-directed therapies and biomarkers for TB diagnosis. In summary, this review aims to highlight the current state of knowledge regarding the involvement of host lncRNAs in mycobacterial infections. It also emphasizes their potential application as novel diagnostic biomarkers and therapeutic targets. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Bacterial Infection)
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<p>Host lncRNAs in mycobacterial infections. PRC2: Polycomb repressive complex 2; DUSP4: Dual-specificity protein phosphatase 4; SATB1: Special AT-rich sequence-binding protein-1; NF-κβ: Nuclear factor kappa B; STAT3: Signal transducer and activator of transcription 3; LC3: Microtubule-associated protein 1A/1B-light chain 3 (MAP1LC3B); RHEB: Ras homolog enriched in brain; A20: TNF alpha induced protein 3 (TNFAIP3); hnRNPA2/B1: Heterogeneous nuclear ribonucleoproteins A2/B1; FUBP3: Far upstream element-binding protein 3; ULK1: Unc-51-like autophagy-activating kinases 1; mTOR: Mammalian target of rapamycin; TGF-β: Transforming growth factor beta; TRAF6: TNF receptor-associated factor 6.</p>
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21 pages, 15157 KiB  
Article
Microbial Dynamics: Assessing Skincare Regimens’ Impact on the Facial Skin Microbiome and Skin Health Parameters
by Nicole Wagner, Valerie Diane Valeriano, Samuel Diou-Hirtz, Evelina Björninen, Ulf Åkerström, Lars Engstrand, Ina Schuppe-Koistinen and Johanna Maria Gillbro
Microorganisms 2024, 12(12), 2655; https://doi.org/10.3390/microorganisms12122655 - 21 Dec 2024
Viewed by 710
Abstract
The human skin microbiome, a complex ecosystem of microbes, plays a pivotal role in skin health. This study aimed to investigate the impact of two skincare regimens, with preservatives (CSPs) and preservative-free (PFPs), on the skin microbiome in correlation to skin quality. double-blind [...] Read more.
The human skin microbiome, a complex ecosystem of microbes, plays a pivotal role in skin health. This study aimed to investigate the impact of two skincare regimens, with preservatives (CSPs) and preservative-free (PFPs), on the skin microbiome in correlation to skin quality. double-blind randomized cosmetic studywith a split-face design was conducted on 26 female participants. Microbial diversity and abundance were analyzed using 16S rRNA amplicon sequence data and skin quality utilizing the Antera 3D skin camera. We confirmed earlier studies on the identification of major skin microbial taxa at the genus level, including Cutibacterium acnes, Corynebacterium, and Neisseriaceae as a predominant part of the facial skin microbiome. Furthermore, microbiome profile-based subgrouping was employed, which revealed that the cluster, characterized by the Neisseriaceae family as its predominant organism, exhibited significant reduction in folds count, fine lines, and redness after application of PFP compared to CSP. A Spearman correlation analysis highlighted the correlation between changes in specific bacteria and skin quality parameters such as redness, pores, and texture in the context of comparing PFP and CSP. Overall, the PFP treatment demonstrated a greater number of significant correlations between bacterial changes and skin quality compared to the CSP treatment, suggesting a distinct impact of the preservative-free skincare regimen on the skin microbiome and skin quality. Our study provides insights into different microbiome-centered approaches to improve our understanding of the skin microbiome’s interplay with skin quality but also highlights the need for larger, comprehensive research to further understand the microbiome’s role in dermatology. Full article
(This article belongs to the Special Issue Feature Papers in Microbiomes)
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<p>Taxonomic profile of all samples, including the top 20 samples, with the remaining being denoted as “other species”.</p>
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<p>NMDS profile of the different clusters of samples showing that the separation can be seen clearly with cluster D, representing sample 23 as being farthest from the other samples.</p>
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<p>Taxonomic profile of the top 20 species, along with “other species” in each cluster.</p>
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<p>Alpha diversity between time point 1 and time point 2 for each treatment.</p>
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<p>Shannon diversity between clusters at different points in the treatment.</p>
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<p>Shannon diversity difference values for each of the samples.</p>
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<p>Heatmaps depicting the delta CLR (the lighter color indicates a decrease after treatment, and the darker color indicates an increase after treatment).</p>
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<p>Jensen–Shannon Distance between the samples.</p>
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<p>ANCOMBC2 volcano plot indicating the log-fold change on the <span class="html-italic">x</span>-axis and log10 of FDR-corrected <span class="html-italic">p</span>-value (q-value) on the <span class="html-italic">y</span>-axis. Black dots represent organisms with a significantly different log fold change of value greater than absolute value of 2.</p>
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<p>Significant changes observed in cluster 2 between the amounts of change in the two treatments for the variables.</p>
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<p>Significant Spearman correlation between taxa and Antera variables for the PFP treatment. Purple dots signify a positive correlation, while blue ones signify a negative correlation.</p>
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<p>Significant Spearman correlation between taxa and Antera variables for the CSP treatment. Purple dots signify a positive correlation, while blue ones signify a negative correlation.</p>
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23 pages, 7582 KiB  
Article
Endophytic Bacteria from the Desiccation-Tolerant Plant Selaginella lepidophylla and Their Potential as Plant Growth-Promoting Microorganisms
by Maria Guadalupe Castillo-Texta, José Augusto Ramírez-Trujillo, Edgar Dantán-González, Mario Ramírez-Yáñez and Ramón Suárez-Rodríguez
Microorganisms 2024, 12(12), 2654; https://doi.org/10.3390/microorganisms12122654 - 21 Dec 2024
Viewed by 700
Abstract
Bacteria associated with plants, whether rhizospheric, epiphytic, or endophytic, play a crucial role in plant productivity and health by promoting growth through complex mechanisms known as plant growth promoters. This study aimed to isolate, characterize, identify, and evaluate the potential of endophytic bacteria [...] Read more.
Bacteria associated with plants, whether rhizospheric, epiphytic, or endophytic, play a crucial role in plant productivity and health by promoting growth through complex mechanisms known as plant growth promoters. This study aimed to isolate, characterize, identify, and evaluate the potential of endophytic bacteria from the resurrection plant Selaginella lepidophylla in enhancing plant growth, using Arabidopsis thaliana ecotype Col. 0 as a model system. Plant growth-promotion parameters were assessed on the bacterial isolates; this assessment included the quantification of indole-3-acetic acid, phosphate solubilization, and biological nitrogen fixation, a trehalose quantification, and the siderophore production from 163 endophytic bacteria isolated from S. lepidophylla. The bacterial genera identified included Agrobacterium, Burkholderia, Curtobacterium, Enterobacter, Erwinia, Pantoea, Pseudomonas, and Rhizobium. The plant growth promotion in A. thaliana was evaluated both in Murashige Skoog medium, agar-water, and direct seed inoculation. The results showed that the bacterial isolates enhanced primary root elongation and lateral root and root hair development, and increased the fresh and dry biomass. Notably, three isolates promoted early flowering in A. thaliana. Based on these findings, we propose the S. lepidophylla bacterial isolates as ideal candidates for promoting growth in other agriculturally important plants. Full article
(This article belongs to the Section Plant Microbe Interactions)
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<p>Scheme of inoculation of <span class="html-italic">Arabidopsis thaliana</span> plants in MS 50% and AW culture medium with endophytic bacteria.</p>
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<p>Representative image of the in vitro plant growth-promotion parameters. (<b>A</b>) Solubilization of phosphates. AB, <span class="html-italic">A. brasilense</span> Cd; <span class="html-italic">Pseudomonas</span> sp. SlL121, higher PS for rainy season; <span class="html-italic">Pantoea</span> sp. SlL46, lower PS for rainy season; <span class="html-italic">Erwinia</span> sp. SlS1, higher PS for drought season; <span class="html-italic">Pseudomonas</span> sp. SlS14, lower PS for drought season. (<b>B</b>) Production of siderophores. AC, <span class="html-italic">A. chlorophenolicus</span> 30.16; AB, <span class="html-italic">A. brasilense</span> Cd; <span class="html-italic">Pseudomonas</span> sp. SlL121 is a major producer of rainy season hydroxamate-type siderophores; <span class="html-italic">Burkholderia</span> sp. SlL91 is the largest producer of rainy season catechol-type siderophores; <span class="html-italic">Pseudomonas</span> sp. SlS14 is a major producer of hydroxamate-type siderophores for drought season; <span class="html-italic">Pseudomonas</span> sp. SlS1 is a major producer of catechol-type siderophores for drought season.</p>
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<p>Promotion of plant growth of <span class="html-italic">A. thaliana</span> in MS 50% culture medium. (<b>A</b>) Length of the plant, rainy season. (<b>B</b>) Biomass in fresh and dry weight, rainy season. (<b>C</b>) Length of the plant, dry season. (<b>D</b>) Biomass in fresh and dry weight, dry season. The bars represent the mean value. Differences statistically significant with respect to the control bacteria were determined with a completely randomized ANOVA (Pr &gt; F =&lt; 0.0001), followed by a Tukey analysis (α = 0.05); the means with the same letter are not significantly different, and the error bars indicate the standard deviation of three repetitions. The biomass only represents the value of a replicate with 30 plants for each bacterial isolate.</p>
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<p>Appearance of <span class="html-italic">A. thaliana</span> plants inoculated with the different bacterial isolates in MS 50% culture medium.</p>
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<p>Promotion of plant growth of <span class="html-italic">A. thaliana</span> in AW culture medium. (<b>A</b>) Length of the plant, rainy season. (<b>B</b>) Biomass in fresh and dry weight, rainy season. (<b>C</b>) Length of the plant, dry season. (<b>D</b>) Biomass in fresh and dry weight, dry season. The bars represent the mean value. Differences that were statistically significant with respect to the control bacteria were determined with a completely randomized ANOVA (Pr &gt; F = &lt; 0.0001), followed by a Tukey analysis (α = 0.05); the means with the same letter are not significantly different, and the error bars indicate the standard deviation of three repetitions. The biomass represents the value of a replicate with 30 plants for each bacterial isolate.</p>
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<p>Appearance of <span class="html-italic">A. thaliana</span> plants inoculated with different bacterial isolates in AW culture medium.</p>
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<p>Promotion of plant growth of <span class="html-italic">A. thaliana</span> in AW culture medium. (<b>A</b>) Length of the plant, both seasons. (<b>B</b>) Biomass in fresh and dry weight, both seasons. (<b>C</b>) The germination percentage on days 1, 4, 7 and 10. (<b>D</b>) The germination speed on day 10. (<b>E</b>) The germination speed of <span class="html-italic">A. thaliana</span> seeds. The bars represent the mean value, and the statistically significant differences with respect to the control bacteria were determined with a completely randomized ANOVA (Pr &gt; F = &lt; 0.0001), followed by a Tukey analysis (α = 0.05); the means with the same letter are not significantly different, and the error bars indicate the standard deviation of three repetitions.</p>
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<p>Appearance of <span class="html-italic">A. thaliana</span> plants inoculated directly on the seeds with different bacterial isolates in AW culture medium.</p>
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18 pages, 1578 KiB  
Review
Respiratory Flora Intervention: A New Strategy for the Prevention and Treatment of Occupationally Related Respiratory Allergy in Healthcare Workers
by Linglin Gao, Xi Chen, Ziyi Jiang, Jie Zhu and Qiang Wang
Microorganisms 2024, 12(12), 2653; https://doi.org/10.3390/microorganisms12122653 - 20 Dec 2024
Viewed by 519
Abstract
Occupational allergic respiratory disease in healthcare workers due to occupational exposure has received widespread attention. At the same time, evidence of altered respiratory flora associated with the development of allergy has been found in relevant epidemiologic studies. It is of concern that the [...] Read more.
Occupational allergic respiratory disease in healthcare workers due to occupational exposure has received widespread attention. At the same time, evidence of altered respiratory flora associated with the development of allergy has been found in relevant epidemiologic studies. It is of concern that the composition of nasopharyngeal flora in healthcare workers differs significantly from that of non-healthcare workers due to occupational factors, with a particularly high prevalence of carriage of pathogenic and drug-resistant bacteria. Recent studies have found that interventions with upper respiratory tract probiotics can significantly reduce the incidence of respiratory allergies and infections. We searched PubMed and other databases to describe the burden of allergic respiratory disease and altered respiratory flora in healthcare workers in this narrative review, and we summarize the mechanisms and current state of clinical research on the use of flora interventions to ameliorate respiratory allergy, with the aim of providing a new direction for protecting the respiratory health of healthcare workers. Full article
(This article belongs to the Section Medical Microbiology)
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<p>Dysbiosis of the nasal flora can induce allergic respiratory diseases. In dysbiosis, pathogenic bacteria cause airway inflammation and, together with respiratory viruses, lower respiratory tract infections. Occupational allergen exposure increases the body’s susceptibility to pathogens, and continued exposure can lead to airway inflammation or even induce respiratory allergies.</p>
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<p>Differences in the composition of the upper respiratory tract flora in asthmatics and healthy individuals. In the upper airways of healthy individuals, all genera were at normal levels; in the upper airways of asthmatics, <span class="html-italic">Haemophilus</span> and <span class="html-italic">Moraxella</span> were elevated, whereas the levels of commensal bacteria were reduced, such as <span class="html-italic">Mogibacteriaceae</span>.</p>
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<p>Mechanisms of probiotic-assisted treatment of respiratory allergy. Firstly, probiotics directly compete with pathogens for nutrients and space and inhibit pathogen colonization of epithelial cells. Secondly, it regulates mucosal immunity and promotes secretion of antimicrobial peptides and interferon by immune cells. Thirdly, it enhances innate and adaptive immunity in the lungs.</p>
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16 pages, 3242 KiB  
Article
The Nitrogen Removal Characteristics of a Novel Salt-Tolerant Bacterium, Enterobacter quasihormaechei DGFC5, Isolated from Municipal Sludge
by Bingguo Wang, Huanlong Peng and Wei Liu
Microorganisms 2024, 12(12), 2652; https://doi.org/10.3390/microorganisms12122652 - 20 Dec 2024
Viewed by 472
Abstract
A novel bacterial strain, Enterobacter quasihormaechei DGFC5, was isolated from a municipal sewage disposal system. It efficiently removed ammonium, nitrate, and nitrite under conditions of 5% salinity, without intermediate accumulation. Provided with a mixed nitrogen source, DGFC5 showed a higher utilization priority for [...] Read more.
A novel bacterial strain, Enterobacter quasihormaechei DGFC5, was isolated from a municipal sewage disposal system. It efficiently removed ammonium, nitrate, and nitrite under conditions of 5% salinity, without intermediate accumulation. Provided with a mixed nitrogen source, DGFC5 showed a higher utilization priority for NH4+-N. Whole-genome sequencing and nitrogen balance experiments revealed that DGFC5 can simultaneously consume NH4+-N in the liquid phase through assimilation and heterotrophic nitrification, and effectively remove nitrate via aerobic denitrification and dissimilatory reduction reactions. Single-factor experiments were conducted to determine the optimal nitrogen removal conditions, which were as follows: a carbon-to-nitrogen ratio of 15, a shaking speed of 200 rpm, a pH of 7, C4H4Na2O4 as the carbon source, and a temperature of 30 °C. DGFC5 showed efficient nitrogen purification capabilities under a wide range of environmental conditions, indicating its potential for disposing of nitrogenous wastewater with high salinity. Full article
(This article belongs to the Section Environmental Microbiology)
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<p>(<b>a</b>) The heterotrophic nitrification and (<b>b</b>) aerobic denitrification performances of the nine preliminarily selected strains within 48 h. The letters above the columns are used to show the significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>a</b>) A scanning electron micrograph of DGFC5, (<b>b</b>) the Gram staining results, and (<b>c</b>) the neighbor-joining phylogenetic tree of DGFC5 and its related bacteria. The number of bootstrap replications is 1000 and the bootstrap values are indicated at the branch nodes. The scale bar represents a 0.1% sequence divergence.</p>
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<p>Nitrogen removal and growth characteristics of DGFC5 under 5% salinity conditions. (<b>a</b>) Nitrogen source corresponding to ammonium, (<b>b</b>) nitrogen source corresponding to nitrite, (<b>c</b>) nitrogen source corresponding to nitrate, and (<b>d</b>) ammonium, nitrite, and nitrate as mixed nitrogen sources.</p>
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<p>(<b>a</b>) A genetic map of DGFC5, (<b>b</b>) a nitrogen metabolism pathway map, (<b>c</b>) the KEGG pathway analysis, and (<b>d</b>) a schematic diagram of the nitrogen removal process. The green boxes indicate the genes present in the nitrogen metabolism pathway, and the numbers inside are the EC numbers of the key enzymes.</p>
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<p>(<b>a</b>,<b>b</b>) The influences of different carbon sources, (<b>c</b>,<b>d</b>) C/N ratios, (<b>e</b>,<b>f</b>) rotation speeds, (<b>g</b>,<b>h</b>) temperatures, and (<b>i</b>,<b>j</b>) pH values on the heterotrophic nitrification performance of DGFC5 at 5% salinity. The values are the mean ± SD (error bars) of three replicates.</p>
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13 pages, 561 KiB  
Article
Elimination of Methicillin-Resistant Staphylococcus aureus from Mammary Glands of Dairy Cows by an Additional Antibiotic Treatment Prior to Dry Cow Treatment
by Bernd-Alois Tenhagen, Mirka Elisabeth Wörmann, Anja Gretzschel, Mirjam Grobbel, Sven Maurischat and Tobias Lienen
Microorganisms 2024, 12(12), 2651; https://doi.org/10.3390/microorganisms12122651 - 20 Dec 2024
Viewed by 505
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) have been isolated from quarter milk samples of dairy cows, raising concerns over transmission to consumers of raw milk. This study investigates whether pre-treatment before dry-off can increase the success rate of dry cow treatment against MRSA. MRSA positive [...] Read more.
Methicillin-resistant Staphylococcus aureus (MRSA) have been isolated from quarter milk samples of dairy cows, raising concerns over transmission to consumers of raw milk. This study investigates whether pre-treatment before dry-off can increase the success rate of dry cow treatment against MRSA. MRSA positive cows were assigned to two treatment groups. Both groups received dry cow treatment with a licensed product. The test group was additionally treated intramammarily with pirlimycin over seven days prior to the dry-off treatment. The use of pirlimycin increased the elimination of MRSA from previously MRSA positive udder quarters significantly (96.0 vs. 53.3%). However, MRSA were still present in noses and udder clefts of cows in MRSA negative quarter milk samples. New infections were observed in some quarters in both groups. Quarters that remained positive carried the same strain as prior to treatment. All MRSA isolates were associated with clonal complex CC398. Resistance to pirlimycin associated with the genes erm(C) or lnu(B) was observed in one isolate each from new infections after calving. Pretreatment supported the elimination of MRSA from the udder but did not eliminate MRSA from other body sites. Using the treatment will not eliminate the bacteria from the herd. Full article
(This article belongs to the Special Issue Bacterial Infections and Antimicrobial Resistance in Animals)
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<p>Status of udder quarters before dry-off and their respective diagnosis after parturition. More than half of the udder quarters were negative for MRSA prior to dry-off and after calving. Therefore, only the percentage range above 50% is displayed. neg-neg, negative prior to treatment and after calving; neg-pos, negative prior to treatment and positive after calving; pos-neg, positive prior to treatment and negative after calving; pos-pos, positive prior to treatment and after calving.</p>
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<p>Genomic comparison (SNP analysis) of MRSA obtained from quarter milk samples of different cows (C), quarters (Q) and time points (S1, S2, S3, S4). S1 and S2 represent sampling before dry-off. Collection of S3 and S4 was carried out after calving. Cow C15 was affected by mastitis during the trial.</p>
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25 pages, 4800 KiB  
Article
Innovative Methodology for Antimicrobial Susceptibility Determination in Mycoplasma Biofilms
by B. Tegner Jacobson, Jessica DeWit-Dibbert, Eli T. Selong, McKenna Quirk, Michael Throolin, Chris Corona, Sobha Sonar, LaShae Zanca, Erika R. Schwarz and Diane Bimczok
Microorganisms 2024, 12(12), 2650; https://doi.org/10.3390/microorganisms12122650 - 20 Dec 2024
Viewed by 732
Abstract
Mycoplasma spp. are facultative pathogens that contribute to the pathogenesis of multiple bovine diseases, including the bovine respiratory disease complex, and have been shown to form biofilms. Biofilm formation is associated with increased antibiotic resistance in many organisms, but accurate determination of antimicrobial [...] Read more.
Mycoplasma spp. are facultative pathogens that contribute to the pathogenesis of multiple bovine diseases, including the bovine respiratory disease complex, and have been shown to form biofilms. Biofilm formation is associated with increased antibiotic resistance in many organisms, but accurate determination of antimicrobial susceptibility in biofilms is challenging. In Mycoplasma spp., antimicrobial susceptibility is routinely determined using metabolic pH-dependent color change. However, biofilm formation can lead to reduced metabolism, making interpretation of metabolic readouts difficult. Therefore, we developed and optimized a new flow cytometry-based method for antimicrobial susceptibility testing in biofilm-forming Mycoplasma, termed the live/dead antimicrobial susceptibility test (LD-AST). The LD-AST measures the proportion of live bacteria upon exposure to antibiotics, works robustly with both planktonic and biofilm cultures, and enables the determination of the minimum bactericidal concentration (MBC) for a given antibiotic. We used two strains of Mycoplasma bovis (Donetta PG45 and Madison) and two clinical Mycoplasma bovoculi isolates (MVDL1 and MVDL2) to determine the impact of biofilm growth on antimicrobial susceptibility for gentamicin, enrofloxacin, or tetracycline. All Mycoplasma strains were susceptible to all antibiotics when cultured as planktonic cells, with MBCs in the expected range. However, three out of four strains (Donetta PG45, MVDL1, and MVDL2) were completely resistant to all three antibiotics when newly adhered biofilms were analyzed, whereas M. bovis Madison gave variable results. For mature biofilms that were cultured for 4–5 days before antibiotic exposure, results also were variable, with some strains showing an increased resistance with certain antibiotics and a decreased resistance with others. Overall, these results are consistent with earlier reports that biofilms can exhibit increased antimicrobial resistance. Full article
(This article belongs to the Special Issue Detection, Diagnosis, and Host Interactions of Animal Mycoplasmas)
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<p><b>Representative FACS dot plots of live and dead <span class="html-italic">M. bovis</span> samples</b>. The live/dead stain was visualized as the log intensity of SYTO9 versus the log intensity of the PI (<b>A</b>) Live cells were gated as SYTO9-positive, PI-negative cells in gate R2. (<b>B</b>) TritonX-100 treatment was used to kill a proportion of the M. bovis to create a positive control. Dead cells are found as SYTO9-positive, PI-positive cells in gate R3. Representative data from one experiment.</p>
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<p>Brightfield images of Mycoplasma biofilm formation on glass-bottom plates over 6 d. Top rows: phase contrast images; bottom rows: thresholded images used to estimate the percent confluence of the biofilm in the field of view. Data are representative of one experiment with 18 technical replicates.</p>
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<p><b>Maturation of <span class="html-italic">M. bovis</span> PG45 biofilms over time</b>. Biofilm maturity was assessed based on the percent confluence of the cells and the largest structure diameter observed. (<b>A</b>) Biofilm confluence peaked at 4 d, which showed strong evidence of a difference (Wald’s Test, <span class="html-italic">p</span> &lt; 0.01) compared to all other days post-inoculation. (<b>B</b>) The diameter of the largest biofilm structure did not vary across the different days (Wald’s test, <span class="html-italic">p</span> &gt; 0.05). The boxplot displays the median and quartiles of the population, the grey point indicates the mean. Representative of two experiments, each with 16–18 technical replicates. * <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.</p>
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<p><b>Standard color change assay is inappropriate for measuring <span class="html-italic">Mycoplasma</span> spp. biofilm growth</b>. (<b>A</b>) A color change due to acid production is visible for planktonic cells (top, grown for 2 d on a clear polystyrene plate), but not for mature biofilms (bottom, incubated with new media for 2 d after biofilm formation on a glass-bottom plate with black polystyrene wells). (<b>B</b>) Quantification of medium pH for M. bovis PG45 grown as a biofilm for 6 d. No significant difference in pH between the media control and PG45 (Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> &gt; 0.05). Representative of one experiment with 60 technical replicates.</p>
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<p><b>Impact of biofilm disruption treatment on <span class="html-italic">M. bovis</span> particle size</b>. Particle size of disrupted <span class="html-italic">M. bovis</span> biofilms was determined using SYTO9 stained cells with an imaging cytometer. (<b>A</b>) Two populations for the planktonic cells were noted, with a natural division observed at 1.75 × 105 RFU, which corresponds with a particle diameter of approximately 5 µm. (<b>B</b>) For the disrupted biofilms, the 10 min sonication had strong evidence (Wald’s test, <span class="html-italic">p</span> = 0.015) for an increase in small particles compared to the untreated biofilms The percentage of particles above and below 5 µm was calculated for each treatment and compared. Representative of one experiment with two replicate cultures, each with two technical replicates (represented by different colored lines). Each technical replicate had ~5 × 10<sup>4</sup>–8 × 10<sup>4</sup> particles/biofilm replicate and ~8 × 10<sup>3</sup>–16 × 10<sup>3</sup> particles/planktonic replicate.</p>
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<p><b>Impact of 10 min of sonication on the particle size of <span class="html-italic">M. bovis</span> PG45 biofilms.</b> The particle size of disrupted biofilms was further analyzed by observing the forward scatter from a 405 nm small particle laser and comparing it to size calibration beads. (<b>A</b>) Planktonic <span class="html-italic">M. bovis</span> PG45 culture. (<b>B</b>) Untreated <span class="html-italic">M. bovis</span> PG45 biofilm. (<b>C</b>) <span class="html-italic">M. bovis</span> PG45 biofilm after 10 min sonication. Representative graphs were generated by randomly selecting and concatenating 1 × 10<sup>6</sup> particles from each technical replicate. Representative of one experiment with 4 technical replicates.</p>
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<p><b>Impact of 10 min of sonication on the mean fluorescence of the <span class="html-italic">M. bovis</span> PG45 particles</b>. There was a 9.37 ± 0.57% decrease (Wald’s Test, <span class="html-italic">p</span> &lt; 0.001) in mean particle size between the untreated biofilm and the 10 min sonicated biofilm. The point is the estimated mean and the 95% confidence interval from the separate means model. Representative of one experiment with four technical replicates.</p>
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<p><b>Analysis of cell viability and density for the LD-AST.</b> (<b>A</b>) The survival of filtered cells exposed to 10 min of sonication and the rate of cell adherence was assessed. Filtered planktonic cells were sonicated for 10 min to determine if the treatment would lead to a decrease in live cells. The imaging and flow cytometry results were compared. Representative of one experiment with six technical replicates. (<b>B</b>) Cells inoculated at 2 × 10<sup>4</sup>/mL were imaged at 1, 2.5, and 4 h intervals to determine the rate of adhesion to the glass-bottom plate. The line represents the inoculum concentration while the shaded area represents the 103–105 cells/mL target range. Representative of one experiment with three technical replicates.</p>
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<p><b>The LD-AST reveals increased MBCs for <span class="html-italic">M. bovis</span> PG45 biofilms compared to planktonic bacteria.</b> Minimum bactericidal concentration of a decrease in live cells ≥ 5% (MBC ≥ 5%) data showing the percentage of live cells compared to (<b>A</b>) enrofloxacin, (<b>B</b>) gentamicin, and (<b>C</b>) tetracycline concentrations for each of the organism states. The colored boxes correspond to the lowest antibiotic concentration that resulted in a significant drop in the percentage of live cells. The mean and SEM are shown for each group. Representative of three independent experiments with 2 technical replicates.</p>
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24 pages, 1561 KiB  
Review
Association Between Diabetes Mellitus–Tuberculosis and the Generation of Drug Resistance
by Axhell Aleid Cornejo-Báez, Roberto Zenteno-Cuevas and Julieta Luna-Herrera
Microorganisms 2024, 12(12), 2649; https://doi.org/10.3390/microorganisms12122649 - 20 Dec 2024
Viewed by 1018
Abstract
Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains one of the leading infectious causes of death globally, with drug resistance presenting a significant challenge to control efforts. The interplay between type 2 diabetes mellitus (T2DM) and TB introduces additional complexity, as [...] Read more.
Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains one of the leading infectious causes of death globally, with drug resistance presenting a significant challenge to control efforts. The interplay between type 2 diabetes mellitus (T2DM) and TB introduces additional complexity, as T2DM triples the risk of active TB and exacerbates drug resistance development. This review explores how T2DM-induced metabolic and immune dysregulation fosters the survival of Mtb, promoting persistence and the emergence of multidrug-resistant strains. Mechanisms such as efflux pump activation and the subtherapeutic levels of isoniazid and rifampicin in T2DM patients are highlighted as key contributors to resistance. We discuss the dual syndemics of T2DM–TB, emphasizing the role of glycemic control and innovative therapeutic strategies, including efflux pump inhibitors and host-directed therapies like metformin. This review underscores the need for integrated diagnostic, treatment, and management approaches to address the global impact of T2DM–TB comorbidity and drug resistance. Full article
(This article belongs to the Special Issue Prevention, Treatment and Diagnosis of Tuberculosis, 2nd Edition)
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<p>The image presents three cases: one of a person with T2DM, another with TB, and a third with both T2DM–TB simultaneously. This figure illustrates how the immune response is altered in each condition, showing changes in the concentration of immune response cells and cytokines. These changes are represented with blue arrows for increases and red arrows for decreases. Additionally, it highlights that the presence of the T2DM–TB comorbidity promotes the development of DR, which worsens the clinical condition of patients.</p>
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23 pages, 8712 KiB  
Article
A Tachyplesin Antimicrobial Peptide from Theraphosidae Spiders with Potent Antifungal Activity Against Cryptococcus neoformans
by Brenda B. Michira, Yi Wang, James Mwangi, Kexin Wang, Demeke Asmamaw, Dawit Adisu Tadese, Jinai Gao, Mehwish Khalid, Qiu-Min Lu, Ren Lai and Juan Li
Microorganisms 2024, 12(12), 2648; https://doi.org/10.3390/microorganisms12122648 - 20 Dec 2024
Viewed by 674
Abstract
The venoms of Theraphosidae spiders have evolved into diverse natural pharmacopeias through selective pressures. Cryptococcus neoformans is a global health threat that frequently causes life-threatening meningitis and fungemia, particularly in immunocompromised patients. In this study, we identify a novel anti-C. neoformans peptide, [...] Read more.
The venoms of Theraphosidae spiders have evolved into diverse natural pharmacopeias through selective pressures. Cryptococcus neoformans is a global health threat that frequently causes life-threatening meningitis and fungemia, particularly in immunocompromised patients. In this study, we identify a novel anti-C. neoformans peptide, QS18 (QCFKVCFRKRCFTKCSRS), from the venom gland of China’s native spider species Chilobrachys liboensis by utilizing bioinformatic tools. QS18 shares over 50% sequence similarity with tachyplesin peptides, previously identified only in horseshoe crab hemocytes, expanding the known repertoire of the tachyplesin family to terrestrial arachnids. The oxidative folding of QS18 notably enhances its antifungal activity and stability, resulting in a minimum inhibitory concentration of 1.4 µM. The antimicrobial mechanism of QS18 involves cell membrane disruption. QS18 exhibits less than 5% hemolysis in human erythrocytes, indicating microbial selectivity and a favorable safety profile for therapeutic use. Furthermore, mouse model studies highlight QS18’s ability as an antifungal agent with notable anti-inflammatory activity. Our study demonstrates QS18 as both a promising template for spider venom peptide research and a novel candidate for the development of peptide antifungals. Full article
(This article belongs to the Special Issue Advances in Antimicrobial Peptides)
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<p>Sequence alignment and phylogenetic analysis for QS18: (<b>A</b>) The complete amino acid sequence of QS18. Color-coded regions represent the three typical sections of a toxin peptide sequence: blue for the signal peptide, red for the mature peptide (QS18), and green for the propeptide; (<b>B</b>) Sequence alignment utilizing Clustal W software (<a href="https://www.genome.jp/tools-bin/clustalw" target="_blank">https://www.genome.jp/tools-bin/clustalw</a>). The amino acid identity is represented in different color codes; (<b>C</b>) Phylogenetic analysis maximum likelihood tree generated using RAxML and visualized in the ITOL website. The branch length and bootstrap replications (branch reliability) are represented in black and blue numbers, respectively. The higher the branch length value, the farther the branch. Gomesin (P82358), an antimicrobial peptide from <span class="html-italic">Acanthoscurria gomesiana</span> [<a href="#B20-microorganisms-12-02648" class="html-bibr">20</a>]; gomesin-like peptide (A0A1D0BZI2), an antibacterial peptide from <span class="html-italic">Hadronyche infensa</span> [<a href="#B17-microorganisms-12-02648" class="html-bibr">17</a>]; Tachyplesin-2 (P14214), from <span class="html-italic">Tachypleus tridentatus</span> [<a href="#B39-microorganisms-12-02648" class="html-bibr">39</a>]; Tachyplesin-1 (P14213), from <span class="html-italic">Tachypleus tridentatus</span> [<a href="#B39-microorganisms-12-02648" class="html-bibr">39</a>,<a href="#B40-microorganisms-12-02648" class="html-bibr">40</a>]; Tachyplesin-1 (P69135) and Tachyplesin-3 (P18252) from <span class="html-italic">Tachypleus gigas</span> [<a href="#B41-microorganisms-12-02648" class="html-bibr">41</a>]; Phosphoinositide phospholipase C 3 (Q56W08), an enzyme involved in signal transduction from <span class="html-italic">Arabidopsis thaliana</span> [<a href="#B42-microorganisms-12-02648" class="html-bibr">42</a>]; the protein associated with UVRAG as autophagy enhancer (protein Rubicon-like) (A7E316.1), a regulator of autophagy from Bos taurus; and Polyphemusin-1 (P14215) and Polyphemusin-2 (P14216), AMPs from <span class="html-italic">Limulus polyphemus</span> [<a href="#B43-microorganisms-12-02648" class="html-bibr">43</a>]; (<b>D</b>) The venom gland of <span class="html-italic">Chilobrachys liboensis;</span> (<b>E</b>) A silhouette image of a horseshoe crab obtained from PhyloPic (<a href="https://www.phylopic.org/" target="_blank">https://www.phylopic.org/</a>); and (<b>F</b>) A photograph of the tarantula species <span class="html-italic">C. liboensis</span>.</p>
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<p>Mass spectrometry analysis: (<b>A</b>) Mass spectra of reduced linear QS18 (QS18red). The spectrum shows the mass-to-charge (m/z) ratio distribution, with the highest peak labeled. (<b>B</b>) Mass spectra of the oxidized QS18 (QS18). These data confirmed molecular mass and purity of the synthesized QS18 peptide before and after the oxidative folding process. Comparison with the linear peptide spectrum allowed the verification of successful folding and formation of disulfide bonds, as indicated by the decrease in molecular mass.</p>
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<p>Structural analysis of QS18: (<b>A</b>) Helical wheel projections showing QS18’s amphipathic nature. The arrow indicates a hydrophobic moment. Indicated in yellow are the hydrophobic residues, whereas the purple color shows serine and threonine, and blue and pink show the basic residues and glutamine, respectively. C and N are the C- and N-termini represented in red. (<b>B</b>) The secondary α-helix structure of QS18 predicted using PEP-FOLD3 software. (<b>C</b>) The primary structure of the linear QS18 generated by pepSMI software (<a href="https://www.novoprolabs.com/tools/convert-peptide-to-smiles-string" target="_blank">https://www.novoprolabs.com/tools/convert-peptide-to-smiles-string</a>). The structure shows amino acids’ sequence connected by peptide bonds. (<b>D</b>,<b>E</b>) Circular dichroism spectra displaying the secondary helical structure of QS18 and QS18red, respectively, in membrane-mimicking and aqueous solutions: trifluoroethanol (TFE) and sodium dodecyl-sulfate (SDS). [θ]M represents the mean residue ellipticity. Results are expressed as the mean ± standard deviation (SD) of three technical replicates.</p>
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<p>Proteolytic resistance: (<b>A</b>) SDS-PAGE evaluation of the proteolytic stability of QS18, QS18red, LL37, and colistin following incubation with chymotrypsin or trypsin from 0 to 12 h. Besides colistin, LL37 human cathelicidin AMP served as a positive control due to its known susceptibility to serine proteases. L represents the protein ladder, and S represents peptide samples without enzymes. (<b>B</b>) The effect of proteolytic enzymes on the antifungal effect of QS18. Two hours post-incubation, QS18 appeared to maintain its antimicrobial property in chymotrypsin, which corresponds with the SDS-PAGE analysis results, displaying resistance even up to 12 h. Data represent the mean ± SD of three independent experiments, each performed in technical triplicates.</p>
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<p>Antifungal activity of QS18 against <span class="html-italic">C. neoformans</span> BNCC225501 cells: (<b>A</b>) Time-dependent fungicidal activity. QS18 exhibits potent effects with complete growth inhibition at 10× the MIC within 60 min and at 5× the MIC after 120 min. (<b>B</b>) Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) micrographs showing the effect of QS18 treatment at 1× and 10× the MIC. SEM and TEM scale bars are 2 µm and 200 µm, respectively. The arrows highlight key areas of membrane disruption, including visible perforations, thus providing visual evidence of QS18’s membrane-targeting mechanism. (<b>C</b>) The fluorescence intensity of DiSC3(5) in <span class="html-italic">C. neoformans</span> cell suspension. Abbreviations: FCZ represents fluconazole, and AMB represents amphotericin B. The results are expressed as the mean ± SD of three independent experiments, each conducted in technical triplicates.</p>
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<p>Antibiofilm activity of QS18 against <span class="html-italic">C. neoformans</span> BNCC225501 cells: (<b>A</b>) Dose–response inhibition of biofilm formation in 96-well plates. (<b>B</b>) Dose–response eradication of preformed biofilms in 96-well plates. Data expressed as mean OD600 values of solubilized crystal violet dye ± SEM. (<b>C</b>) Quantification of the red (PI) and green (FDA) fluorescence. The percentage area of fluorescence is expressed relative to the negative control (NC). (<b>D</b>) Two-photon laser microscopy analysis of the peptide’s effect on <span class="html-italic">C. neoformans</span> biofilms: Propidium iodide (PI) and Fluorescein diacetate (FDA) dyes were used to stain the dead and live cells, respectively. Imaging of the differential interference contrast (DIC) under white light was also assessed. Abbreviations: FCZ, fluconazole; and AMB, amphotericin B. Treated <span class="html-italic">C. neoformans</span> populations demonstrated a higher proportion of dead cells (red fluorescence) compared to untreated cells (green fluorescence). This color intensity shift indicates significant antibiofilm activity in the presence of QS18. These observations further corroborate the membrane-targeting mechanism of QS18. Scale bar, 50 µm. The data are presented as the mean ± SEM of three independent experiments. A one-way ANOVA was conducted for statistical analysis. Statistical significance: *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>QS18 treatment of mice infected with <span class="html-italic">C. neoformans</span>: (<b>A</b>) Evaluation of the number of colony-forming units (CFUs) (<span class="html-italic">C. neoformans</span>-8 × 10<sup>6</sup> CFU/mouse, n = 4) per gram of tissue and per mL in blood. Results demonstrate a substantial dose-dependent decrease in fungal burden in treated groups across all examined tissues and blood. (<b>B</b>) Histopathological analysis of inflammatory responses. Tissue sections from the lung, liver, spleen and kidney were subjected to hematoxylin and eosin (H&amp;E) staining. Compared to untreated negative controls (NC), QS18-treated sections exhibited dose-dependent reduction in infiltrating inflammatory cells and overall architectural disruption. The 4 mg/kg QS18-treated group shows near-normal tissue morphology, indicating the significant alleviation of infection-induced inflammation. Scale bar, 50 µm. Results are expressed as the mean ± SD of four biological replicates per dose group. A one-way ANOVA was performed. Statistical significance: * <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.</p>
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<p>Quantification of pro-inflammatory cytokines: (<b>A</b>–<b>D</b>) Plasma was analyzed for concentrations of interleukin--1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and monocyte chemoattractant protein-1 (MCP-1), respectively, using the enzyme-linked immunosorbent assay (ELISA). QS18-treated groups demonstrated dose-dependent reductions in these inflammatory markers compared to the untreated group. Data represent the mean ± SD of four biological replicates per dose group. Statistical significance was assessed using one-way ANOVA; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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24 pages, 4556 KiB  
Article
Mosla Chinensis Extract Enhances Growth Performance, Antioxidant Capacity, and Intestinal Health in Broilers by Modulating Gut Microbiota
by Wei Wang, Yuyu Wang, Peng Huang, Junjuan Zhou, Guifeng Tan, Jianguo Zeng and Wei Liu
Microorganisms 2024, 12(12), 2647; https://doi.org/10.3390/microorganisms12122647 - 20 Dec 2024
Viewed by 523
Abstract
This study aimed to evaluate the effects of Mosla chinensis extract (MCE) on broiler intestinal health. A total of 240 1-day-old Arbor Acres (AA) broilers (balanced for sex) were randomly allocated into four treatment groups, each with six replicates of 10 chickens. The [...] Read more.
This study aimed to evaluate the effects of Mosla chinensis extract (MCE) on broiler intestinal health. A total of 240 1-day-old Arbor Acres (AA) broilers (balanced for sex) were randomly allocated into four treatment groups, each with six replicates of 10 chickens. The study comprised a starter phase (days 1–21) and a grower phase (days 22–42). The control group (C) received a basal diet, while the experimental groups were supplemented with low (S1, 500 mg/kg), medium (S2, 1000 mg/kg), and high doses (S3, 2000 mg/kg) of MCE. The results showed that MCE supplementation significantly improved average daily gain in broilers (p < 0.05) and reduced the feed-to-gain ratio in broilers. Additionally, MCE enhanced the anti-inflammatory and antioxidant capacity of broilers. In the duodenum and cecum, MCE significantly upregulated the expression of tight junction proteins Claudin-1, and Occludin, with the high-dose group showing the strongest effect on intestinal barrier protection (p < 0.05). There was no significant difference in ZO-1 in dudenum (p > 0.05). Microbial analysis indicated that MCE supplementation significantly reduced the Chao and Sobs indices in both the small and large intestines (p < 0.05). At the same time, the Coverage index of the small intestine increased, with the high-dose group demonstrating the most pronounced effect. Beta diversity analysis revealed that MCE had a significant modulatory effect on the microbial composition in the large intestine (p < 0.05), with a comparatively smaller impact on the small intestine. Furthermore, MCE supplementation significantly increased the relative abundance of Ruminococcaceae and Alistipes in the large intestine, along with beneficial genera that promote short-chain fatty acid (SCFA) production, thus optimizing the gut microecological environment. Correlation analysis of SCFAs further confirmed a significant association between the enriched microbiota and the production of acetate, propionate, and butyrate (p < 0.05). In conclusion, dietary supplementation with MCE promotes healthy growth and feed intake in broilers and exhibits anti-inflammatory and antioxidant effects. By optimizing gut microbiota composition, enhancing intestinal barrier function, and promoting SCFA production, MCE effectively maintains gut microecological balance, supporting broiler intestinal health. Full article
(This article belongs to the Special Issue Advances in Diet–Host–Gut Microbiome Interactions)
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<p>Experimental grouping of broiler chickens. This figure illustrates the randomized allocation of 240 Arbor Acres (AA) broiler chicks into four treatment groups, with each group containing six replicates of 10 chicks each. The dosing levels of M. chinensis extract for each group were based on established experimental protocols. The design ensures a balanced distribution of subjects to examine the effects on growth performance, serum biochemistry, antioxidant capacity, immune function, and gut microbiota over a 42-day period.</p>
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<p>Effects of M. chinensis extract on antioxidant activity in serum and liver of white feather broilers: (<b>A</b>) total antioxidant capacity (T-AOC) in the liver; (<b>B</b>) glutathione peroxidase (GSH-PX) activity in the liver; (<b>C</b>) superoxide dismutase (SOD) activity in the liver; (<b>D</b>) catalase (CAT) activity in the liver; (<b>E</b>) malondialdehyde (MDA) levels in the liver; (<b>F</b>) glutathione peroxidase (GSH-PX) activity in the serum; (<b>G</b>) malondialdehyde (MDA) levels in the serum; (<b>H</b>) nitric oxide (NO) levels in the serum. * <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.</p>
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<p>Effects of M. chinensis extract on the immune performance of white feather broilers: (<b>A</b>) serum IgA levels; (<b>B</b>) serum IgM levels; (<b>C</b>) serum IgG levels; (<b>D</b>) serum IL-4 levels; (<b>E</b>) serum IL-10 levels; (<b>F</b>) serum IFN-γ levels * <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, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Effects of MCE on intestinal tight junction protein gene expression in white feather broilers: (<b>A</b>) ZO-1 expression in the duodenum; (<b>B</b>) Claudin-1 expression in the duodenum; (<b>C</b>) Occludin expression in the duodenum; (<b>D</b>) ZO-1 expression in the cecum; (<b>E</b>) Claudin-1 expression in the cecum. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effects of MCE on short-chain fatty acid production in intestinal contents of white feather broilers: (<b>A</b>) acetic acid in the large intestine; (<b>B</b>) propionic acid in the large intestine; (<b>C</b>) butyric acid in the large intestine; (<b>D</b>) valeric acid in the large intestine; (<b>E</b>) acetic acid in the small intestine; (<b>F</b>) propionic acid in the small intestine. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Microbial composition analysis of intestinal contents: (<b>A</b>) gate level composition analysis of colonic contents; (<b>B</b>) gate level composition analysis of small intestine contents; (<b>C</b>) analysis of the genus level composition of the contents of the large intestine; (<b>D</b>) analysis of genus level composition of small intestine contents.</p>
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<p>Effects of dietary MCE on OTU counts in the intestinal microbiota of broilers: (<b>A</b>) OTU count changes in large intestinal contents; (<b>B</b>) OTU count changes in small intestinal contents.</p>
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<p>Effects of dietary MCE on alpha diversity of intestinal microbiota in broilers: (<b>A</b>) Chao index for large intestinal contents; (<b>B</b>) coverage index for large intestinal contents; (<b>C</b>) Simpson index for large intestinal contents; (<b>D</b>) Sobs index for large intestinal contents; (<b>E</b>) Chao index for small intestinal contents; (<b>F</b>) coverage index for small intestinal contents; (<b>G</b>) Simpson index for small intestinal contents; (<b>H</b>) Sobs index for small intestinal contents. * <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.</p>
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<p>Principal component analysis of intestinal microbiota at the genus level in broilers supplemented with MCE: (<b>A</b>) PCA plot of large intestinal microbiota; (<b>B</b>) PCoA plot of large intestinal microbiota; (<b>C</b>) PCA plot of small intestinal microbiota; (<b>D</b>) PCoA plot of small intestinal microbiota.</p>
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<p>Differential analysis of intestinal microbiota at the genus level in broilers supplemented with MCE: (<b>A</b>) bar chart of the large intestinal microbial community composition; (<b>B</b>) inter-group differential analysis of large intestinal microbiota; (<b>C</b>) bar chart of the small intestinal microbial community composition; (<b>D</b>) inter-group differential analysis of small intestinal microbiota. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Correlation analysis between short-chain fatty acids and microbiota in the large intestine. This figure presents the Spearman correlation analysis between short-chain fatty acids (SCFAs) and the microbial genera in the large intestine. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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13 pages, 4837 KiB  
Article
Genetic Characterization, Transmission Pattern and Health Risk Analysis of Intestinal Colonization ESBL-Producing Escherichia coli in Vegetable Farming Population
by Fanghui Yao, Qian Zhao, Di Wang and Xuewen Li
Microorganisms 2024, 12(12), 2646; https://doi.org/10.3390/microorganisms12122646 - 20 Dec 2024
Viewed by 481
Abstract
The surging prevalence rates of ESBL-producing Escherichia coli (ESBL-Ec) pose a serious threat to public health. To date, most research on drug-resistant bacteria and genes has focused on livestock and poultry breeding areas, hospital clinical areas, natural water environments, and wastewater treatment plants. [...] Read more.
The surging prevalence rates of ESBL-producing Escherichia coli (ESBL-Ec) pose a serious threat to public health. To date, most research on drug-resistant bacteria and genes has focused on livestock and poultry breeding areas, hospital clinical areas, natural water environments, and wastewater treatment plants. However, few studies have been conducted on drug-resistant bacteria in vegetable cultivation. In this study, a total of vegetable farmers (n = 59) from six villages were surveyed. Fecal samples were collected from vegetable farmers; we also collected environmental samples, including river water, well water, soil, river sediment, vegetable surface swabs, and fish intestinal tracts. The ESBL-Ec intestinal colonization rate in vegetable farmers was 76.27%. PFGE results indicated two patterns of ESBL-Ec transmission within the vegetable cultivation area: among vegetable farmers, and among river water, river sediments, and vegetable farmers. Based on the phylogenetic analysis, three transmission patterns of ESBL-Ec outside the vegetable cultivation area were inferred: human–human, human–animal–human, and human–animal–environment. Twelve of the isolates carried closely related or identical IncF plasmids carrying blaCTX-M. Whole genome sequencing (WGS) analysis showed that ST569-B2-O134:H31 and ST38-D-O50:H30 were associated with high disease risk. We assessed the health risks of the farming population and provided a reference basis for public health surveillance and environmental management by monitoring the prevalence and transmission of ESBL-Ec in vegetable areas. Full article
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<p>Vegetable cultivation area sampling map (white dots are greenhouse locations).</p>
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<p>Clustering by phylogenetic group, MLST type and serotype to analyze the status of resistance genes carried by intestinal colonized ESBL-Ec isolates (red is carrying the resistance gene; blue is not carrying the resistance gene).</p>
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<p>Different subtypes of CTX-M resistance gene skeletons (red arrows are CTX-M resistance genes, blue arrows are mobile genetic elements, yellow arrows are other resistance genes, and orange arrows are other genes): (<b>a</b>) gene skeleton of <span class="html-italic">bla<sub>CTX-M-65</sub></span>; (<b>b</b>) gene skeleton of <span class="html-italic">bla<sub>CTX-M-</sub><sub>14</sub></span>; (<b>c</b>) gene skeleton of <span class="html-italic">bla<sub>CTX-M-</sub><sub>5</sub><sub>5</sub></span>; (<b>d</b>) gene skeleton of <span class="html-italic">bla<sub>CTX-M-</sub><sub>3</sub></span>; (<b>e</b>) gene skeleton of <span class="html-italic">bla<sub>CTX-M-</sub><sub>1</sub><sub>5</sub></span>; (<b>f</b>) gene skeleton of <span class="html-italic">bla<sub>CTX-M-</sub><sub>27</sub></span>.</p>
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<p>Phylogenetic clusters, MLST typing and serotype correlation analysis of intestinal colonized ESBL-Ec (right side is labeled as carrying the virulence gene).</p>
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<p>PFGE fingerprints of different samples of ESBL-Ec isolates within the vegetable cultivation area.</p>
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<p>Transmission patterns of ESBL-Ec in vegetable cultivation environments identified based on PFGE analysis (F: cultivator feces; R: river water; D: river sediment).</p>
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<p>SNP phylogenetic analysis of ESBL-Ec isolates from different times and sources with farmer gut-colonized ESBL-Ec in Shandong Province, October 2012–March 2024 (labels outside the phylogenetic tree are labeled for strains (SNP &lt; 10) for time, source, ST type, serotype, and resistance genes).</p>
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13 pages, 872 KiB  
Article
Molecular Analysis of Escherichia coli and Correlations Between Phylogroups and Sequence Types from Different Sources
by João Gabriel Material Soncini, Vanessa Lumi Koga, Bruna Fuga, Zuleica Naomi Tano, Gerson Nakazato, Renata Katsuko Takayama Kobayashi, Nilton Lincopan and Eliana Carolina Vespero
Microorganisms 2024, 12(12), 2645; https://doi.org/10.3390/microorganisms12122645 - 20 Dec 2024
Viewed by 672
Abstract
Escherichia coli is a significant pathogen responsible for infections in both humans and livestock, possessing various virulence mechanisms and antimicrobial resistance that make it even more concerning. In this study, several internationally recognized clones of E. coli were identified, such as ST131, ST38, [...] Read more.
Escherichia coli is a significant pathogen responsible for infections in both humans and livestock, possessing various virulence mechanisms and antimicrobial resistance that make it even more concerning. In this study, several internationally recognized clones of E. coli were identified, such as ST131, ST38, ST648, and ST354, from chicken meat, pork, and human infection samples. Notably, ST131, belonging to phylogroup B2, was the dominant sequence type (ST) in human samples, while ST38, belonging to phylogroup D, was the most prevalent in meat samples. Several antibiotic resistance genes were identified: the gyrA gene mutation was the most prevalent, and CTX-M-55 was the most common extended-spectrum beta-lactamases (ESBLs), with significant differences noted for CTX-M-2 and CTX-M-15. Virulence-associated genes (VAGs) such as gad and iss were frequently found, especially in human isolates. These findings highlight the complex epidemiology of antibiotic-resistant E. coli in community settings and the potential risks associated with commercial meat. Full article
(This article belongs to the Special Issue Antimicrobial Resistance in Enterobacteriaceae and Enterococci)
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<p>Heatmap. A visual scheme displaying the sample codes, sources, STs, phylogroups, ESBLs, quinolone resistance genes (QRGs), quinolone resistance-determining regions (QRDRs), VAGs, and serotypes. Color legend: In the source column, the yellow and green icons represent isolates derived from chicken and pork meat, respectively, while the blue icon represents those of human origin. The presence of ESBLs, QRGs, and QRDRs is represented by the colors brown, golden yellow and yellow, respectively. In the VAGs section, each color represents the classification of the gene: purple—effector delivery system; dark blue—adhesins; teal—exotoxin; blue—nutritional/metabolic factor; blue-green—capsule; light blue—other. The symbols ** represent <span class="html-italic">E. coli</span> scheme sequence type II (Institut Pasteur).</p>
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13 pages, 783 KiB  
Article
Molecular Testing of Zoonotic Bacteria in Cattle, Sheep, and Goat Abortion Cases in Botswana
by Boitumelo M. Modise-Tlotleng, Sununguko W. Mpoloka, Tirumala B. K. Settypalli, Joseph Hyera, Tebogo Kgotlele, Kago Kumile, Mosarwa E. Sechele, Obuile O. Raboloko, Chandapiwa Marobela-Raborokgwe, Gerrit J. Viljoen, Giovanni Cattoli and Charles E. Lamien
Microorganisms 2024, 12(12), 2644; https://doi.org/10.3390/microorganisms12122644 - 20 Dec 2024
Viewed by 742
Abstract
Abortion is one of the major causes of economic losses in livestock production worldwide. Because several factors can lead to abortion in cattle, sheep and goats, laboratory diagnosis, including the molecular detection of pathogens causing abortion, is often necessary. Bacterial zoonotic diseases such [...] Read more.
Abortion is one of the major causes of economic losses in livestock production worldwide. Because several factors can lead to abortion in cattle, sheep and goats, laboratory diagnosis, including the molecular detection of pathogens causing abortion, is often necessary. Bacterial zoonotic diseases such as brucellosis, coxiellosis, leptospirosis, and listeriosis have been implicated in livestock abortion, but they are under diagnosed and under-reported in most developing countries, including Botswana. This study applied a recently developed multiplex high-resolution melting analysis technique, coupled with singleplex qPCR assays, to investigate abortions in livestock in Botswana, using 152 samples from cattle, sheep, and goat abortion cases. Brucella spp. were the most frequent pathogen detected, with an overall frequency of 21.1%, followed by Coxiella burnetii with 19.1%. Listeria monocytogenes and Leptospira spp. were not detected in any of specimens samples investigated. Mixed infections with Brucella spp. and C. burnetii were observed in 35% specimes examined. There was a good agreement between the multiplex qPCR-HRM and singleplex qPCR for detecting Brucella spp. and C. burnetii. This study is the first report on the syndromic testing of abortion-causing pathogens in Botswana. It shows the importance of molecular methods in the differential diagnosis of abortion-causing diseases in domestic ruminants. Full article
(This article belongs to the Section Veterinary Microbiology)
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<p>Distribution of <span class="html-italic">Brucella-</span> and <span class="html-italic">Coxiella</span>-positive cases from 2014 to 2021.</p>
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<p>Map of Botswana showing distribution of pathogens per location.</p>
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15 pages, 694 KiB  
Article
Subclinical Mastitis in Small-Holder Dairy Herds of Gansu Province, Northwest China: Prevalence, Bacterial Pathogens, Antimicrobial Susceptibility, and Risk Factor Analysis
by Ling Wang, Shahbaz Ul Haq, Muhammad Shoaib, Jiongjie He, Wenzhu Guo, Xiaojuan Wei and Xiaohong Zheng
Microorganisms 2024, 12(12), 2643; https://doi.org/10.3390/microorganisms12122643 - 20 Dec 2024
Viewed by 458
Abstract
This cross-sectional study assessed the prevalence, bacterial distribution, antimicrobial susceptibility, and potential risk factors associated with subclinical mastitis (SCM) in small-holder dairy herds in Gansu Province, Northwest China. Forty small-holder cow farms were randomly selected from eight cities/counties in six districts of Gansu [...] Read more.
This cross-sectional study assessed the prevalence, bacterial distribution, antimicrobial susceptibility, and potential risk factors associated with subclinical mastitis (SCM) in small-holder dairy herds in Gansu Province, Northwest China. Forty small-holder cow farms were randomly selected from eight cities/counties in six districts of Gansu Province, and a total of n = 530 lactating cows were included in this study. SCM prevalence was noted at 38.87% and 9.72% at the cow and quarter levels, respectively, based on the California Mastitis Test (CMT). The prevalence of the recovered bacterial species was noted as follows: S. agalactiae (36.02%), S. aureus (19.43%), coagulase-negative staphylococci (CNS) (16.11%), S. dysgalactiae (12.80%), E. coli (9.00%), and S. uberis (6.64%). All isolated bacteria were 100% multi-drug-resistant (MDR) except S. aureus (87.8% MDR). Antimicrobial susceptibility profiles revealed the increased resistance (>85%) of these pathogens to penicillin, streptomycin, trimethoprim–sulfamethoxazole, vancomycin, and erythromycin. However, these pathogens showed increased susceptibility to ampicillin, amoxicillin–sulbactam, ceftazidime, neomycin, kanamycin, spectinomycin, norfloxacin, ciprofloxacin, and doxycycline. The multivariate regression analysis demonstrated that old age, high parity, late lactation, lesions on teats, previous history of clinical mastitis, higher milk yield, and milking training were found to be potential risk factors (p < 0.001) associated with developing SCM in small-holder dairy cows in Gansu Province, China. These findings highlight the need for routine surveillance, antimicrobial stewardship, and effective preventive strategies to mitigate SCM in small-holder dairy production and their possible impacts, i.e., increased antimicrobial resistance and infection, on public health. Full article
(This article belongs to the Special Issue Antimicrobial Testing (AMT), Third Edition)
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<p>(<b>a</b>) Number of positive cases of subclinical mastitis (SCM) (<span class="html-italic">n</span> = 206) in small-holder dairy cows based on California Mastitis Test (CMT) scores. (<b>b</b>) Distribution of major SCM-associated bacteria (<span class="html-italic">n</span> = 211) isolated from milk of small-holder dairy cows.</p>
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<p>Percentage of multi-drug resistant (MDR) bacterial strains isolated from milk of small-holder dairy cows with SCM in Gansu Province, China.</p>
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14 pages, 4221 KiB  
Article
Differences in the Microbial Composition and Function of the Arundo donax Rhizosphere Under Different Cultivation Conditions
by Fan Yang, Miaomiao Liu, Xin Wang, Yuting Hong, Qiuju Yao, Xiaoke Chang, Gongyao Shi, Weiwei Chen, Baoming Tian and Abeer Hegazy
Microorganisms 2024, 12(12), 2642; https://doi.org/10.3390/microorganisms12122642 - 19 Dec 2024
Viewed by 502
Abstract
Rhizosphere microorganisms play an important role in the health and development of root systems. Investigating the microbial composition of the rhizosphere is central to understanding the inter-root microbial function of Arundo donax under various cultivation conditions. To complement the metagenomic study of the [...] Read more.
Rhizosphere microorganisms play an important role in the health and development of root systems. Investigating the microbial composition of the rhizosphere is central to understanding the inter-root microbial function of Arundo donax under various cultivation conditions. To complement the metagenomic study of the Arundo donax rhizosphere, here, an amplicon-based metagenomic survey of bacteria and fungi was selected as a practical approach to analyzing the abundance, diversity index, and community structure of rhizosphere bacteria and fungi, as well as to study the effects of different cultivation methods on rhizosphere microbial diversity. Next-generation sequencing and QIIME2 analysis were used. The results indicated that microbial community richness, diversity, and evenness of the hydroponic samples were lower than those of soil samples when examining the α diversity indices of bacteria and fungi using Chao1, ACE, and Shannon metrics. In particular, the relative abundances of Proteobacteria, Rhizobiales, and Incertae sedis in hydroponic materials were higher, while Basidiomycota, Ascomycota, and Actinobacteriota dominated the flora in soil materials when comparing the numbers of OTUs and the ACE community richness estimator. Furthermore, the rhizosphere of hydroponic A. donax contained a higher abundance of nitrogen-fixing bacteria and photosynthetic bacteria, which contribute to root formation. Additionally, there was a significant presence of Basidiomycota, Ascomycota, and Actinobacteriota in soil A. donax, which can form hyphae. This reveals that the microbial community composition of the A. donax rhizosphere is significantly different under various cultivation conditions, suggesting that employing two distinct culturing techniques for Arundo donax may alter the microbiome. Furthermore, it provides technical support for the synergistic interaction between Arundo donax and rhizosphere microorganisms so as to better use the relationship between Arundo donax and basic microorganisms to solve the problems of Arundo donax growth and ecological restoration. Full article
(This article belongs to the Section Plant Microbe Interactions)
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<p>Alpha diversity index box plots. Box plots show the variations in Chao1 (<b>A</b>), ACE (<b>B</b>), Shannon (<b>C</b>), and Simpson (<b>D</b>) indices for bacteria (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Bacterial community composition and relative abundance in the rhizosphere of <span class="html-italic">Arundo donax</span> under different cultivation methods at the phylum (<b>A</b>), class (<b>B</b>), order (<b>C</b>), and genus (<b>D</b>) levels (top 30). The horizontal coordinate is the sample name, and the vertical coordinate is the relative abundance of the species in the sample. The figure shows information for species with a relative abundance of more than 1%.</p>
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<p>Krona sample illustration (<b>A</b>). The circles represent the different classification levels from the inside to the outside, and the fan size represents the relative proportion of different OTU annotation results. Analysis of differences between samples. PCoA analysis diagram (<b>B</b>). The first principal component and its contribution to the difference in samples are shown in the horizontal coordinates, and the second principal component and its contribution to the difference in samples are shown in the vertical coordinates. Based on the Bray–Curtis multi-sample clustering tree (<b>C</b>). The length of the branches represents the distance between the samples, and the more similar the samples, the more likely they are to be clustered together.</p>
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<p>Functional metabolism prediction. Column chart of functional abundance (<b>A</b>): horizontal coordinate is the sample name, and vertical coordinate is the proportion. Functional abundance cluster heatmap (<b>B</b>,<b>C</b>). Horizontal coordinates for different samples; vertical coordinates for the first 50 abundances of the function.</p>
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<p>Alpha diversity index box plot. Box plots show the variation in Chao1 (<b>A</b>), ACE (<b>B</b>), Shannon (<b>C</b>), and Simpson (<b>D</b>) indices for fungi (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The composition and relative abundance of fungal communities in the rhizosphere of <span class="html-italic">Arundo donax</span> were assessed under various cultivation methods at the phylum (<b>A</b>), class (<b>B</b>), order (<b>C</b>), family (<b>D</b>), genus (<b>E</b>), and species (<b>F</b>) levels. The horizontal coordinate is the sample name, and the vertical coordinate is the relative abundance of the species in the sample. The figure shows species information with a relative abundance of more than 1%.</p>
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<p>Heatmap of OTUs and their corresponding taxonomic levels presented for the phylum (<b>A</b>), class (<b>B</b>), order (<b>C</b>), family (<b>D</b>), genus (<b>E</b>), and species (<b>F</b>).</p>
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<p>Analysis of differences between samples illustrated through a PCoA analysis diagram (<b>A</b>) and a Bray–Curtis multi-sample clustering tree (<b>B</b>). The points indicate the species composition of each sample: the horizontal coordinates indicate the first principal component and its contribution to the difference in samples; the vertical coordinates indicate the second principal component and its contribution to the difference in samples. The length of the branches represents the distance between the samples, and the more similar the samples, the more likely they are to be clustered together.</p>
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<p>Column chart illustrating functional abundance (<b>A</b>) and cladogram presenting the distribution and cladistics of LDA values for various species (<b>B</b>). The circles radiating from the inside to the outside of the branching graph represent the taxonomic level from phylum to genus (or species). Each small circle at a different classification level represents a classification at that level, and the diameter of the small circle is proportional to the relative abundance. The non-significantly different species are uniformly colored in yellow, with red nodes representing the microbiota playing an important role in the red group and green nodes representing the microbiota playing an important role in the green group. The other circle colors have the same meaning.</p>
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<p>Illustration of the rhizosphere microorganism mechanism and its effect on <span class="html-italic">Arundo donax</span>.</p>
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