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19 pages, 8887 KiB  
Article
LPA3: Pharmacodynamic Differences Between Lysophosphatidic Acid and Oleoyl-Methoxy Glycerophosphothionate: Biased Agonism, Two Sites
by K. Helivier Solís, M. Teresa Romero-Ávila, Ruth Rincón-Heredia, Juan Carlos Martínez-Morales and J. Adolfo García-Sáinz
Receptors 2024, 3(4), 555-573; https://doi.org/10.3390/receptors3040029 - 20 Dec 2024
Viewed by 553
Abstract
Background: Lysophosphatidic acid (LPA) receptor 3 (LPA3) is involved in many physiological and pathophysiological actions of this bioactive lipid, particularly in cancer. The actions of LPA and oleoyl-methoxy glycerophosphothionate (OMPT) were compared in LPA3-transfected HEK 293 cells. Methods: [...] Read more.
Background: Lysophosphatidic acid (LPA) receptor 3 (LPA3) is involved in many physiological and pathophysiological actions of this bioactive lipid, particularly in cancer. The actions of LPA and oleoyl-methoxy glycerophosphothionate (OMPT) were compared in LPA3-transfected HEK 293 cells. Methods: Receptor phosphorylation, ERK 1/2 activation, LPA3-β-arrestin 2 interaction, and changes in intracellular calcium were analyzed. Results: Our data indicate that LPA and OMPT increased LPA3 phosphorylation, OMPT being considerably more potent than LPA. OMPT was also more potent than LPA to activate ERK 1/2. In contrast, OMPT was less effective in increasing intracellular calcium than LPA. The LPA-induced LPA3-β-arrestin 2 interaction was fast and robust, whereas that induced by OMPT was only detected at 60 min of incubation. LPA- and OMPT-induced receptor internalization was fast, but that induced by OMPT was more marked. LPA-induced internalization was blocked by Pitstop 2, whereas OMPT-induced receptor internalization was partially inhibited by Pitstop 2 and Filipin and entirely by the combination of both. When LPA-stimulated cells were rechallenged with 1 µM LPA, hardly any response was detected, i.e., a “refractory” state was induced. However, a conspicuous and robust response was observed if OMPT was used as the second stimulus. Conclusions: The differences in these agents’ actions suggest that OMPT is a biased agonist. These findings suggest that two binding sites for these agonists might exist in the LPA3 receptor, one showing a very high affinity for OMPT and another likely shared by LPA and OMPT (structural analogs) with lower affinity. Full article
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Figure 1

Figure 1
<p>Concentration–response curves for LPA- and OMPT-induced LPA<sub>3</sub> receptor phosphorylation. Cells were incubated with the indicated concentrations of the agonists for 15 min. Receptor phosphorylation is expressed as the percentage of the baseline value. The means are plotted, and vertical lines indicate the SEM of 10 experiments performed on different days. Representative autoradiographs (<sup>32</sup>P) and Western blots (WBs) are presented above the graph.</p>
Full article ">Figure 2
<p>Concentration–response curves for LPA- and OMPT-induced ERK 1/2 phosphorylation. Cells were incubated with the indicated concentrations of the agonists for 2 min. ERK 1/2 phosphorylation is expressed as the percentage of the baseline value. The means are plotted, and vertical lines indicate the SEM of 6 experiments performed on different days. Representative Western blots for phosphorylated (pERK) and total (ERK) kinase are presented above the graph.</p>
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<p>Time course of LPA- and OMPT-induced ERK 1/2 phosphorylation. Cells were incubated for the times indicated with 1 µM of each agonist. ERK 1/2 phosphorylation is expressed as the percentage of the baseline value. The means are plotted, and vertical lines indicate the SEM of 6 experiments performed on different days. Representative Western blots for phosphorylated (pERK) and total (ERK) kinase are presented above the graph. <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 LPA vs. OMPT.</p>
Full article ">Figure 4
<p>Time-course of LPA- and OMPT-induced LPA<sub>3</sub>-β-arrestin interaction (FRET). Cells were incubated for the times indicated with 1 µM LPA (black symbols and line) or 1 µM OMPT (red symbols and line). The baseline WT FRET index was considered as 100%. The means are plotted, and vertical lines indicate the SEM of 9–10 experiments performed on different days; 10–14 cells were analyzed for each experimental condition in all the experiments. Representative FRET index images are presented above the graph. Bars, 10 µm. *** <span class="html-italic">p</span> &lt; 0.001 vs. baseline, ** <span class="html-italic">p</span> &lt; 0.005 vs. baseline, * <span class="html-italic">p</span> &lt; 0.05 vs. baseline (color coded).</p>
Full article ">Figure 5
<p>Time course of 1µM LPA- and 1µM OMPT-induced changes in intracellular (panel (<b>A</b>)) and plasma membrane (panel (<b>B</b>)) fluorescence. In both cases, data are presented as the percentage of the baseline values. The means are plotted, and vertical lines indicate the SEM of 4–5 experiments in which 10–14 images were taken for each condition. Representative images (fluorescence, confocal microscopy) are presented above the graph. Bars, 10 µm. *** <span class="html-italic">p</span> &lt; 0.001 vs. baseline, ** <span class="html-italic">p</span> &lt; 0.005 vs. baseline, * <span class="html-italic">p</span> &lt; 0.05 vs. baseline, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 LPA vs. OMPT.</p>
Full article ">Figure 6
<p>Effect of Pitstop 2 on LPA and OMPT-induced internalization. Cells were preincubated for 15 min without (gray or pale red symbols and lines) or with Pitstop 2 (PIT) (black or bright red symbols and lines) before being stimulated with 1 µM LPA (panel (<b>A</b>)) or 1 µM OMPT (panel (<b>B</b>)). The means are plotted, and vertical lines indicate the SEM of 4–5 experiments in which 10–14 images were taken for each condition. Representative images (fluorescence, confocal microscopy) are presented above the graphs. <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 LPA vs. OMPT.</p>
Full article ">Figure 7
<p>Effects of Pitstop 2 and Filipin on LPA-, OMPT-, and PMA-induced internalization. Cells were preincubated without any internalization inhibitor or with Pitstop 2 (PIT, 15 min, blue columns), Filipin (FIL, 60 min, yellow columns), or both agents (PIT + FIL, purple columns). After the preincubation, the cells were challenged with the agent and for the time indicated: vehicle (B, baseline, 5 min), 1 µM LPA (5 min), 1 µM OMPT (30 min), and 1 µM PMA (30 min). The baseline intracellular fluorescence was considered as 100%. The means are plotted, and vertical lines indicate the SEM of 5 experiments in which 10–14 images were taken for each condition. Representative images (fluorescence, confocal microscopy) are presented above the graphs. *** <span class="html-italic">p</span> &lt; 0.001 vs. baseline, ** <span class="html-italic">p</span> &lt; 0.01 vs. baseline; <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001, indicated conditions.</p>
Full article ">Figure 8
<p>Cell proliferation as reflected by the MTT and crystal violet staining assays. Proliferation was studied without any agent (none) or with the following stimuli: 10% serum, 1 µM LPA, 1 µM PMA, 1 µM OMPT, or 100 ng/mL EGF. ** <span class="html-italic">p</span> &lt; 0.01 vs. none, *** <span class="html-italic">p</span> &lt; 0.001 vs. none; <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001, comparing indicated conditions.</p>
Full article ">Figure 9
<p>Increases in intracellular calcium in response to LPA and OMPT. Representative calcium tracings of cells incubated with distinct concentrations (color coded) of LPA (panel (<b>A</b>)) or OMPT (panel (<b>B</b>)). The concentration–response curves for LPA- and OMPT-induced intracellular calcium increases are presented in panel (<b>C</b>). The means are plotted, and vertical lines indicate the SEM of 5–8 distinct curves.</p>
Full article ">Figure 10
<p>Response to a second stimulation without or with an intermediate washing step. In the first two columns, cells were incubated with the vehicle, followed by a challenge with LPA or OMPT (control responses). In the second group of columns, cells were stimulated with the agonist indicated (first), and when the response vanished, the second stimulus was applied. In the third group of columns, after the cells were stimulated with the first agonist, they were extensively washed to eliminate the agent and rechallenged with the second stimulus. The concentration of LPA and OMPT was 1 µM in all cases. The means are plotted, and vertical lines indicate the SEM of 8–10 determination with cells from distinct cultures. <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. vehicle+LPA, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 vs. vehicle+OMPT, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.001 vs. vehicle+OMPT. Agonist stimulation was for 100 s (sec = seconds). Cell washing procedure took approximately 10 min and cells were challenged after washing.</p>
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<p>Representative calcium tracings of data that are presented in <a href="#receptors-03-00029-f010" class="html-fig">Figure 10</a>. Agonist stimulation was for 100 s (sec = seconds). Panels (<b>A</b>–<b>F</b>), continuous tracings without washing. Panels (<b>G</b>–<b>J</b>), cells were washed and the response to the second stimulus is shown. Cell washing procedure took approximately 10 min and cells were challenged after washing.</p>
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16 pages, 1768 KiB  
Article
A Health Threat from Farm to Fork: Shiga Toxin-Producing Escherichia coli Co-Harboring blaNDM-1 and mcr-1 in Various Sources of the Food Supply Chain
by Ayesha Sarwar, Bilal Aslam, Muhammad Hidayat Rasool, Mounir M. Salem Bekhit and James Sasanya
Pathogens 2024, 13(8), 659; https://doi.org/10.3390/pathogens13080659 - 6 Aug 2024
Cited by 1 | Viewed by 1069
Abstract
The dissemination of resistant pathogens through food supply chains poses a significant public health risk, spanning from farm to fork. This study analyzed the distribution of Shiga toxin-producing Escherichia coli (STEC) across various sources within the animal-based food supply chain. A total of [...] Read more.
The dissemination of resistant pathogens through food supply chains poses a significant public health risk, spanning from farm to fork. This study analyzed the distribution of Shiga toxin-producing Escherichia coli (STEC) across various sources within the animal-based food supply chain. A total of 500 samples were collected from livestock, poultry, the environment, fisheries, and dairy. Standard microbiological procedures were employed to isolate and identify E. coli isolates, which were further confirmed using MALDI-TOF and virulence-associated genes (VAGs) such as stx1, stx2, ompT, hylF, iutA, fimH, and iss. The phenotypic resistance patterns of the isolates were determined using the disc diffusion method, followed by molecular identification of antibiotic resistance genes (ARGs) through PCR. STEC were subjected to PCR-based O typing using specific primers for different O types. Overall, 154 (30.5%) samples were confirmed as E. coli, of which 77 (50%) were multidrug-resistant (MDR) E. coli. Among these, 52 (67.53%) isolates exhibited an array of VAGs, and 21 (40.38%) were confirmed as STEC based on the presence of stx1 and stx2. Additionally, 12 out of 52 (23.07%) isolates were identified as non-O157 STEC co-harbouring mcr-1 and blaNDM-1. O26 STEC was found to be the most prevalent among the non-O157 types. The results suggest that the detection of STEC in food supply chains may lead to serious health consequences, particularly in developing countries with limited healthcare resources. Full article
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Figure 1
<p>Heat map showing the distribution of antibiotic resistance gene (ARGs), virulence resistance genes (VRGs), and co-existence of NDM-1 and <span class="html-italic">mcr</span>-1 associated with VRGs-based <span class="html-italic">E. coli</span> detection from various sources.</p>
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<p>Showing the circular cluster heat map illustrated the Resistance pattern of various standard antibiotics against VRGs based confirmed <span class="html-italic">E. coli</span> isolates co-harboring NDM-1 and <span class="html-italic">mcr-1</span>. The resistance pattern among <span class="html-italic">E. coli</span> isolates harboring NDM-1 and <span class="html-italic">mcr-1</span> represented by color and cluster showing overall resistance percentages against antibiotics (AMP, CMP, COL, LVX, MEM, IMI, CIP, TRI, TOC, and FOS).</p>
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<p>Stacked bar showcasing the prevalence of various VRGs in <span class="html-italic">E. coli</span> isolates from various food sources. This stalked bar describes the detection of various VRGs (<span class="html-italic">stx1</span>, <span class="html-italic">stx2</span>, <span class="html-italic">eae</span>, <span class="html-italic">hylA</span>, <span class="html-italic">iss</span>, <span class="html-italic">pap A</span>. <span class="html-italic">papC</span>, <span class="html-italic">papG</span>, <span class="html-italic">fimH</span>, <span class="html-italic">traT</span>, <span class="html-italic">ompT</span>, and <span class="html-italic">ampC</span>) shown in various colors set against selected food sources from livestock. It shows poultry, dairy, and environmental sample categories. The highest prevalence rates were <span class="html-italic">stx1</span> in cheese, followed by <span class="html-italic">stx2</span> in slaughterhouse samples. The chicken meat carried more <span class="html-italic">hylA</span>, <span class="html-italic">iss</span>, <span class="html-italic">traT</span>, <span class="html-italic">ompT</span>, and <span class="html-italic">papC</span>, whereas <span class="html-italic">papA</span> and <span class="html-italic">fimH</span> were more prevalent in beef. This was followed by <span class="html-italic">ampC</span>, which was high in various transport means from environment samples.</p>
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<p>The chord diagram (<a href="https://www.everviz.com/" target="_blank">https://www.everviz.com/</a>, accessed on 18 March 2024) represented the flow between various studied sample sources i.e., nodes. Each source is displayed with an alphabet on the outer circle and arcs between different sources showing the connection and relevance with adjacent sources.</p>
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<p>Scatter plot describing the sample sources against different VRGs from different food origins. Scatter plot showing the sample sources and ARGs in the form of numerical value. The <span class="html-italic">Y</span>-axis shows the sample source. 0–9 depicts beef, mutton, veal, chicken, cloacal/anal swabs, droppings, environmental samples (slaughterhouse, open market, and transport waste, dairy and poultry waste), fish, shrimps, market waste, transport means, and dairy (raw milk, yogurt, dairy cream, cheese, and outlet waste) and <span class="html-italic">x</span>-axis showing ARGs (<span class="html-italic">ESBLs</span>, <span class="html-italic">MBLs</span>, <span class="html-italic">qnrs</span>, <span class="html-italic">tet</span>, and <span class="html-italic">sul</span>).</p>
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13 pages, 1159 KiB  
Article
Evaluation of the Humoral Response after Immunization with a Chimeric Subunit Vaccine against Shiga Toxin-Producing Escherichia coli in Pregnant Sows and Their Offspring
by Roberto M. Vidal, David A. Montero, Adriana Bentancor, Carolina Arellano, Alhejandra Alvarez, Cecilia Cundon, Ximena Blanco Crivelli, Felipe Del Canto, Juan C. Salazar and Angel A. Oñate
Vaccines 2024, 12(7), 726; https://doi.org/10.3390/vaccines12070726 - 29 Jun 2024
Cited by 1 | Viewed by 1566
Abstract
Shiga toxin-producing Escherichia coli (STEC) poses a significant public health risk due to its zoonotic potential and association with severe human diseases, such as hemorrhagic colitis and hemolytic uremic syndrome. Ruminants are recognized as primary reservoirs for STEC, but swine also contribute to [...] Read more.
Shiga toxin-producing Escherichia coli (STEC) poses a significant public health risk due to its zoonotic potential and association with severe human diseases, such as hemorrhagic colitis and hemolytic uremic syndrome. Ruminants are recognized as primary reservoirs for STEC, but swine also contribute to the epidemiology of this pathogen, highlighting the need for effective prevention strategies across species. Notably, a subgroup of STEC that produces Shiga toxin type 2e (Stx2e) causes edema disease (ED) in newborn piglets, economically affecting pig production. This study evaluates the immunogenicity of a chimeric protein-based vaccine candidate against STEC in pregnant sows and the subsequent transfer of immunity to their offspring. This vaccine candidate, which includes chimeric proteins displaying selected epitopes from the proteins Cah, OmpT, and Hes, was previously proven to be immunogenic in pregnant cows. Our analysis revealed a broad diversity of STEC serotypes within swine populations, with the cah and ompT genes being prevalent, validating them as suitable antigens for vaccine development. Although the hes gene was detected less frequently, the presence of at least one of these three genes in a significant proportion of STEC suggests the potential of this vaccine to target a wide range of strains. The vaccination of pregnant sows led to an increase in specific IgG and IgA antibodies against the chimeric proteins, indicating successful immunization. Additionally, our results demonstrated the effective passive transfer of maternal antibodies to piglets, providing them with immediate, albeit temporary, humoral immunity against STEC. These humoral responses demonstrate the immunogenicity of the vaccine candidate and are preliminary indicators of its potential efficacy. However, further research is needed to conclusively evaluate its impact on STEC colonization and shedding. This study highlights the potential of maternal vaccination to protect piglets from ED and contributes to the development of vaccination strategies to reduce the prevalence of STEC in various animal reservoirs. Full article
(This article belongs to the Special Issue Vaccines and Animal Health)
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Figure 1
<p>Overview of the experimental design used in this study. This figure presents the experimental design utilized to evaluate the immunogenicity of a chimeric protein-based vaccine against STEC in pregnant sows and the subsequent transfer of passive immunity to their offspring. The study involved nine pregnant sows, divided into two immunized and one control group. The immunization schedule consisted of the intramuscular administration of the vaccine, with the prime dose administered in the 8th week of gestation, followed by two booster doses at the 10th and 12th weeks. After parturition, 28 of the 45 piglets from the vaccinated and control groups were selected to assess lactogenic immunity. Sample collection for analysis included blood and feces, as detailed in the key legend.</p>
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<p>Serum antibody response in immunized swine. Sera samples were analyzed in duplicate, and the results are presented as means ± SEM of absorbance values at 405 nm for each serum dilution, n = 3 animals per group. (<b>A</b>) Anti-Chi1/Chi2 IgG antibodies. (<b>B</b>) Anti-Chi1/Chi2 IgA antibodies. Levels of specific antibodies in groups are depicted and categorized according to the color and symbol key.</p>
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<p>Passive transfer of maternal antibodies. Levels of specific antibodies in groups of piglets born to and nursed by each sow are depicted and categorized according to the color and symbol key. (<b>A</b>,<b>B</b>) Serum levels of specific IgG at days 15 and 30, respectively. ELISA results are shown with a serum dilution of 1/250 and with various serum dilutions. (<b>C</b>,<b>D</b>) Serum levels of specific IgA at days 15 and 30, respectively. ELISA results are shown with a serum dilution of 1/50 and with various serum dilutions. The results are expressed as absorbance values at 405 nm for each serum dilution. A successful transfer of maternal antibodies from vaccinated sows to piglets was observed, showing a natural decline as piglet age increases. Statistical analysis was performed using the Kruskal–Wallis test, followed by Dunn’s multiple comparison test. <span class="html-italic">p</span> &lt; 0.05 was considered significant.</p>
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13 pages, 2072 KiB  
Article
Lysophosphatidic Acid Receptor 3 Activation Is Involved in the Regulation of Ferroptosis
by Yi-Xun Huang, Kuan-Hung Lin, Jui-Chung Chiang, Wei-Min Chen and Hsinyu Lee
Int. J. Mol. Sci. 2024, 25(4), 2315; https://doi.org/10.3390/ijms25042315 - 15 Feb 2024
Cited by 1 | Viewed by 2123
Abstract
Ferroptosis, a unique form of programmed cell death trigged by lipid peroxidation and iron accumulation, has been implicated in embryonic erythropoiesis and aging. Our previous research demonstrated that lysophosphatidic acid receptor 3 (LPA3) activation mitigated oxidative stress in progeria cells and [...] Read more.
Ferroptosis, a unique form of programmed cell death trigged by lipid peroxidation and iron accumulation, has been implicated in embryonic erythropoiesis and aging. Our previous research demonstrated that lysophosphatidic acid receptor 3 (LPA3) activation mitigated oxidative stress in progeria cells and accelerated the recovery of acute anemia in mice. Given that both processes involve iron metabolism, we hypothesized that LPA3 activation might mediate cellular ferroptosis. In this study, we used an LPA3 agonist, 1-Oleoyl-2-O-methyl-rac-glycerophosphothionate (OMPT), to activate LPA3 and examine its effects on the ferroptosis process. OMPT treatment elevated anti-ferroptosis gene protein expression, including solute carrier family 7 member 11 (SLC7A11), glutathione peroxidase 4 (GPX4), heme oxygenase-1 (HO-1), and ferritin heavy chain (FTH1), in erastin-induced cells. Furthermore, OMPT reduced lipid peroxidation and intracellular ferrous iron accumulation, as evidenced by C11 BODIPY™ 581/591 Lipid Peroxidation Sensor and FerroOrange staining. These observations were validated by applying LPAR3 siRNA in the experiments mentioned above. In addition, the protein expression level of nuclear factor erythroid 2-related factor (NRF2), a key regulator of oxidative stress, was also enhanced in OMPT-treated cells. Lastly, we verified that LPA3 plays a critical role in erastin-induced ferroptotic human erythroleukemia K562 cells. OMPT rescued the erythropoiesis defect caused by erastin in K562 cells based on a Gly A promoter luciferase assay. Taken together, our findings suggest that LPA3 activation inhibits cell ferroptosis by suppressing lipid oxidation and iron accumulation, indicating that ferroptosis could potentially serve as a link among LPA3, erythropoiesis, and aging. Full article
(This article belongs to the Special Issue Lysophosphatidic Acid Signaling in Health and Disease)
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Figure 1
<p>An LPA<sub>3</sub> agonist mitigates erastin-induced ferroptotic death. (<b>A</b>) Cell viability of HT-1080 cells was measured via a CCK-8 assay after treatment with erastin at various concentrations (0 to 10 μM) for 12 or 24 h (<span class="html-italic">N</span> = 3). (<b>B</b>) Intracellular Fe<sup>2+</sup> was measured using the FerroOrange Fluorescent probe after treatment with erastin at various concentrations (0 to 10 μM) for 12 or 24 h (<span class="html-italic">N</span> = 3). (<b>C</b>) HT-1080 cells were starved 4 h before reagent treatment and pre-treated with vehicle or erastin (5 μM) for 2 h, followed by treatment with or without OMPT (10 μM) for an additional 22 h (<span class="html-italic">N</span> = 3). Red arrows indicate cells undergo ferroptosis. (<b>D</b>) Cell viability was assessed by performing a CCK-8 assay. HT-1080 cells were starved 4 h before reagent treatment and pre-treated with vehicle or erastin (5 μM) for 2 h, followed by treatment with or without OMPT, DFO (200 μM), NAC (1 M), or Fer-1 (2 μM) for an additional 22 h (<span class="html-italic">N</span> = 3). Statistical analysis was performed using Student’s <span class="html-italic">t</span>-test and one-way ANOVA; ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>An LPA<sub>3</sub> agonist mitigates erastin-induced lipid peroxidation in HT-1080 cells. (<b>A</b>) HT-1080 cells were starved 4 h before reagent treatment and pre-treated with erastin for 2 h, followed by treatment with or without OMPT for an additional 22 h. The fluorescence intensity of C11 BODIPY was measured via FACS, and the results showed that ROS levels decreased after OMPT treatment in erastin-induced cells. (<b>B</b>) HT-1080 cells were starved 4 h before reagent treatment and pre-treated with erastin for 2 h, followed by incubation with or without OMPT for 22 h. Western blots revealed that OMPT treatment increased the protein level of SCL7A11 (<span class="html-italic">N</span> = 3) and GPX4 (<span class="html-italic">N</span> = 3) in erastin-induced cells. (<b>C</b>) Real-time PCR results showed the knockdown of <span class="html-italic">LPAR3</span> mediated by siRNA (siLPA<sub>3</sub>) for 48 h (<span class="html-italic">N</span> = 3). (<b>D</b>) The knockdown of <span class="html-italic">LPAR3</span> mediated by siRNA (siLPA<sub>3</sub>) for 48 h decreased the protein level of SLC7A11 (<span class="html-italic">N</span> = 4) and GPX4 (<span class="html-italic">N</span> = 3) and mRNA (<span class="html-italic">N</span> = 3) levels. Statistical analysis was performed using one-way ANOVA and 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, *** <span class="html-italic">p</span> &lt; 0.001, n.s. not significant.</p>
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<p>An LPA<sub>3</sub> agonist stabilizes iron homeostasis in erastin-induced HT-1080 cells. (<b>A</b>) Intracellular Fe<sup>2+</sup> was measured using the FerroOrange Fluorescent probe. HT-1080 cells were starved 4 h before reagent treatment and pre-treated with vehicle or erastin (5 μM) for 2 h, followed by treatment with or without OMPT, DFO (200 μM), NAC (1 M), or Fer-1 (2 μM) for 22 h (<span class="html-italic">N</span> = 3). (<b>B</b>) HT-1080 cells were starved 4 h before reagent treatment and pre-treated with erastin for 2 h, followed by treatment with or without OMPT for 22 h. Western blot analysis revealed that OMPT treatment increased the protein levels of HO-1 (<span class="html-italic">N</span> = 3) and FTH1 (<span class="html-italic">N</span> = 3) in erastin-induced cells. (<b>C</b>) The knockdown of <span class="html-italic">LPAR3</span> mediated by siRNA (siLPA<sub>3</sub>) for 48 h decreased HO-1 (<span class="html-italic">N</span> = 5) and FTH1 (<span class="html-italic">N</span> = 5) protein levels and the FTH1 (<span class="html-italic">N</span> = 3) mRNA level. (<b>D</b>) HT-1080 cells were starved 4 h before reagent treatment and pre-treated with erastin for 24 h, followed by treatment with or without OMPT for 5 min. Western blot analysis revealed that OMPT treatment increased p-MEK (<span class="html-italic">N</span> = 3) and p-ERK (<span class="html-italic">N</span> = 4) protein levels. HT-1080 cells were pre-treated with erastin for 2 h, followed by treatment with or without OMPT for an additional 22 h. Western blot analysis revealed that OMPT treatment increased the protein level of NRF2 (<span class="html-italic">N</span> = 4) in erastin-induced cells. Statistical analysis was performed using one-way ANOVA and 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, *** <span class="html-italic">p</span> &lt; 0.001, n.s. not significant.</p>
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<p>LPA<sub>3</sub> promotes erythropoiesis in erastin-induced K562 cells. (<b>A</b>) Construction a luciferase-based screening system. (<b>B</b>) K562 cells were starved 4 h before reagent treatment and pre-treated with vehicle or erastin (5 μM) for 2 h, followed by treatment with or without hemin (200 nM) or OMPT (10 μM) for 22 h. The transcriptional activity of <span class="html-italic">Gly A</span> was decreased under erastin treatment, but was increased after OMPT treatment (<span class="html-italic">N</span> = 3). (<b>C</b>) Knockdown of <span class="html-italic">LPAR3</span> mediated by siRNA for 48 h resulted in a decreased expression level of <span class="html-italic">Gly A</span> (<span class="html-italic">N</span> = 4). (<b>D</b>) <span class="html-italic">LPAR3</span> knockdown mediated by siRNA lasted for 48 h, followed by starvation for 4 h before pre-treatment with erastin for 2 h, and then treatment with or without OMPT for 22 h in K562 cells. <span class="html-italic">Gly A</span> expression level did not respond to OMPT under <span class="html-italic">LPAR3</span>-knockdown conditions in K562 cells (<span class="html-italic">N</span> = 4). Statistical analysis was performed using one-way ANOVA; ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, n.s. not significant.</p>
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14 pages, 1398 KiB  
Article
Resistance and Virulence Surveillance in Escherichia coli Isolated from Commercial Meat Samples: A One Health Approach
by Maísa Fabiana Menck-Costa, Ana Angelita Sampaio Baptista, Matheus Silva Sanches, Beatriz Queiroz dos Santos, Claudinéia Emidio Cicero, Hellen Yukari Kitagawa, Larissa Justino, Leonardo Pinto Medeiros, Marielen de Souza, Sergio Paulo Dejato Rocha, Gerson Nakazato and Renata Katsuko Takayama Kobayashi
Microorganisms 2023, 11(11), 2712; https://doi.org/10.3390/microorganisms11112712 - 6 Nov 2023
Cited by 2 | Viewed by 2382
Abstract
Escherichia coli is a key indicator of food hygiene, and its monitoring in meat samples points to the potential presence of antimicrobial-resistant strains capable of causing infections in humans, encompassing resistance profiles categorized as serious threats by the Centers for Disease Control and [...] Read more.
Escherichia coli is a key indicator of food hygiene, and its monitoring in meat samples points to the potential presence of antimicrobial-resistant strains capable of causing infections in humans, encompassing resistance profiles categorized as serious threats by the Centers for Disease Control and Prevention (CDC), such as Extended-Spectrum Beta-Lactamase (ESBL)—a problem with consequences for animal, human, and environmental health. The objective of the present work was to isolate and characterize ESBL-producing E. coli strains from poultry, pork, and beef meat samples, with a characterization of their virulence and antimicrobial resistance profiles. A total of 450 meat samples (150 chicken, 150 beef, and 150 pork) were obtained from supermarkets and subsequently cultured in medium supplemented with cefotaxime. The isolated colonies were characterized biochemically, followed by antibiogram testing using the disk diffusion technique. Further classification involved biofilm formation and the presence of antimicrobial resistance genes (blaCTX-M, AmpC-type, mcr-1, and fosA3), and virulence genes (eaeA, st, bfpA, lt, stx1, stx2, aggR, iss, ompT, hlyF, iutA, iroN, fyuA, cvaC, and hylA). Statistical analysis was performed via the likelihood-ratio test. In total, 168 strains were obtained, with 73% originating from chicken, 22% from pork, and 17% from beef samples. Notably, strains exhibited greater resistance to tetracycline (51%), ciprofloxacin (46%), and fosfomycin (38%), apart from β-lactams. The detection of antimicrobial resistance in food-isolated strains is noteworthy, underscoring the significance of antimicrobial resistance as a global concern. More than 90% of the strains were biofilm producers, and strains carrying many ExPEC genes were more likely to be biofilm formers (OR 2.42), which increases the problem since the microorganisms have a greater chance of environment persistence and genetic exchange. Regarding molecular characterization, bovine samples showed a higher prevalence of blaCTX-M-1 (OR 6.52), while chicken strains were more likely to carry the fosA3 gene (OR 2.43, CI 1.17–5.05) and presented between 6 to 8 ExPEC genes (OR 2.5, CI 1.33–5.01) compared to other meat samples. Concerning diarrheagenic E. coli genes, two strains harbored eae. It is important to highlight these strains, as they exhibited both biofilm-forming capacities and multidrug resistance (MDR), potentially enabling colonization in diverse environments and causing infections. In conclusion, this study underscores the presence of β-lactamase-producing E. coli strains, mainly in poultry samples, compared to beef and pork samples. Furthermore, all meat sample strains exhibited many virulence-associated extraintestinal genes, with some strains harboring diarrheagenic E. coli (DEC) genes. Full article
(This article belongs to the Special Issue Resistant Bacteria: What Course to Follow?)
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<p>Comparative antimicrobial susceptibility profile across beef, chicken, and pork samples. On the left a figure relating to the number of isolates per meat sample and on the right a figure relating to the percentage of resistance per meat sample. FOT—fosfomycin-trometamol; TET—tetracycline; SXT—trimethoprim-sulfamethoxazole; C—chloramphenicol; CN—gentamicin; CIP—ciprofloxacin; AMC—amoxicillin-clavulanic acid; AMP—ampicillin; CFZ—cefazolin; CFO—cefoxitin; CRO—ceftriaxone; CAZ—ceftazidime; ATM—aztreonam.</p>
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<p>Molecular identification of resistance gene percentage across beef, chicken, and pork strains.</p>
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<p>Percentage of virulence genes detected in beef, chicken, and pork strains.</p>
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13 pages, 4096 KiB  
Article
Virulence Potential, Biofilm Formation, and Disinfectants Control of Escherichia coli from Raw Milk Bulk Tanks in the Southeast of Brazil
by Sâmea Joaquim Aguiar Soares, Felipe de Freitas Guimarães, Gabriel Augusto Marques Rossi, Simony Trevizan Guerra, Felipe Morales Dalanezi, Bruna Churocof Lopes, Mateus de Souza Ribeiro Mioni, Ana Carolina Yamakawa, Evelyn Cristine da Silva, Gustavo Nunes de Moraes, Amanda Bezerra Bertolini, Márcio Garcia Ribeiro, José Carlos de Figueiredo Pantoja, Simone Baldini Lucheis, Vera Lucia Mores Rall, Rodrigo Tavanelli Hernandes, Domingos da Silva Leite and Helio Langoni
Dairy 2023, 4(4), 541-553; https://doi.org/10.3390/dairy4040037 - 3 Oct 2023
Cited by 1 | Viewed by 2023
Abstract
Escherichia coli is a major player in foodborne illnesses, capable of forming biofilms on dairy facilities, leading to milk contamination. Thus, we examined the capacity of E. coli strains from raw milk bulk tanks to form biofilms on surfaces made of polystyrene, stainless [...] Read more.
Escherichia coli is a major player in foodborne illnesses, capable of forming biofilms on dairy facilities, leading to milk contamination. Thus, we examined the capacity of E. coli strains from raw milk bulk tanks to form biofilms on surfaces made of polystyrene, stainless steel, and silicone; the potential links between biofilm formation with genes responsible for fimbriae and virulence factors of extra-intestinal E. coli (ExPEC); and the susceptibility of biofilm-forming isolates to iodine and chlorhexidine digluconate. Out of 149 E. coli strains, 42.28% (63/149) formed biofilm on polystyrene, 56.38% (84/149) on silicone, and 21.48% (32/149) on stainless steel. The frequency of genes was: fimH (100%), hlyA (5.4%), irp2 (2.7%), sitA (10.7%), ompT (43.6%), and traT (98%). No biofilm developed when disinfectants were used prior to biofilm formation. However, iodine and chlorhexidine digluconate allowed 25.40% (16/63) of isolates displaying growth after a mature biofilm was formed. The presence of biofilm on different surfaces emphasizes the vital need for thorough equipment cleaning, both in farms and in industrial dairy settings. Rapid disinfection is crucial, given the reduced susceptibility of potentially pathogenic E. coli after biofilm maturity. Full article
(This article belongs to the Special Issue Microbial Safety of Milk and Dairy Products)
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<p>Location of the 10 (ten) dairy farms sampled in the study, which are located in the states of São Paulo and Minas Gerais, Brazil.</p>
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14 pages, 2457 KiB  
Article
New Insights and Evidence on “Food Intolerances”: Non-Celiac Gluten Sensitivity and Nickel Allergic Contact Mucositis
by Nicoletta Greco, Annalinda Pisano, Laura Mezzatesta, Marta Pettinelli, Arianna Meacci, Maria Gemma Pignataro, Carla Giordano and Antonio Picarelli
Nutrients 2023, 15(10), 2353; https://doi.org/10.3390/nu15102353 - 17 May 2023
Cited by 4 | Viewed by 3046
Abstract
The clinical examination of patients often includes the observation of the existence of a close relationship between the ingestion of certain foods and the appearance of various symptoms. Until now, the occurrence of these events has been loosely defined as food intolerance. Instead, [...] Read more.
The clinical examination of patients often includes the observation of the existence of a close relationship between the ingestion of certain foods and the appearance of various symptoms. Until now, the occurrence of these events has been loosely defined as food intolerance. Instead, these conditions should be more properly defined as adverse food reactions (AFRs), which can consist of the presentation of a wide variety of symptoms which are commonly identified as irritable bowel syndrome (IBS). In addition, systemic manifestations such as neurological, dermatological, joint, and respiratory disorders may also occur in affected patients. Although the etiology and pathogenesis of some of them are already known, others, such as non-celiac gluten sensitivity and adverse reactions to nickel-containing foods, are not yet fully defined. The study aimed to evaluate the relationship between the ingestion of some foods and the appearance of some symptoms and clinical improvements and detectable immunohistochemical alterations after a specific exclusion diet. One hundred and six consecutive patients suffering from meteorism, dyspepsia, and nausea following the ingestion of foods containing gluten or nickel were subjected to the GSRS questionnaire which was modified according to the “Salerno experts’ criteria”. All patients underwent detection of IgA antibodies to tissue transglutaminase, oral mucosal patch tests with gluten and nickel (OMPT), and EGDS, including biopsies. Our data show that GSRS and OMPT, the use of APERIO CS2 software, and the endothelial marker CD34 could be suggested as useful tools in the diagnostic procedure of these new pathologies. Larger, multi-center clinical trials could be helpful in defining these emerging clinical problems. Full article
(This article belongs to the Special Issue Hot Topics in Clinical Nutrition (2nd Edition))
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<p>The intensity of symptoms according to the GSRS questionnaire based on the patients’ regular diet (Time 1). The bar graphs represent the mean ± SEM of the GSRS score for each symptom. The black bars indicate the symptoms that exceeded the score ≥5.</p>
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<p>Patients and study design. GOMPT: oral mucosa patch test to gluten; Ni-OMPT: oral mucosa patch test to nickel; NCGS: non-celiac gluten sensitivity; Ni-ACM: nickel allergic contact mucositis.</p>
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<p>GSRS questionnaire results in anti-tTG-IgA, GOMPT, and Ni-OMPT positive patients on their regular diet (Time 1). The bar graphs represent the mean ±SEM of the GSRS score for each symptom. The GSRS questionnaire is considered positive if at least 3 of the 27 symptoms considered have a score ≥5. The dashed line indicates the cut-off point. GOMPT: oral mucosa patch test to gluten; Ni-OMPT: oral mucosa patch test to nickel. * <span class="html-italic">p</span> &lt; 0.05 for GOMPT positive versus anti-tTG-IgA positive patients; § <span class="html-italic">p</span> &lt; 0.05 for Ni-OMPT positive patients versus anti-tTG IgA positive patients (ANOVA).</p>
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<p>Comparison of GSRS questionnaire results at Time 1 and Time 2 in GOMPT and NI-OMPT positive patients. The bar graphs represent the mean ±SEM of the GSRS score for each symptom. The GSRS questionnaire is considered positive if at least 3 of the 27 symptoms considered have a score ≥5. The dashed line indicates the cut-off point. GOMPT: oral mucosa patch test to gluten; Ni-OMPT: oral mucosa patch test to nickel. * <span class="html-italic">p</span>-value &lt; 0.05 for Time 2 (after their specific diet) versus Time 1 (on their regular diet).</p>
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<p>Duodenal biopsies from NCGS (<b>A</b>) and Ni-ACM (<b>B</b>) immuno-stained with anti-CD3 antibodies. The linear disposition of T lymphocytes in the deeper part of the mucosa is indicated by arrows (original magnification 4×). Higher magnification of a villus from NCGS (<b>C</b>), Ni-ACM (<b>D</b>), and a control patient who underwent endoscopy for cancer screening (<b>E</b>). An asterisk highlights a cluster of intraepithelial T lymphocytes in NCGS (original magnification 20×). NCGS: non-celiac gluten sensitivity; Ni-ACM: nickel allergic contact mucositis.</p>
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<p>Histomorphometric quantification of IEL (<b>A</b>), CD3 (<b>B</b>), CD4 (<b>C</b>), and CD8 (<b>D</b>) positive T lymphocytes and eosinophils (<b>E</b>) in the mucosa of duodenal biopsies. IEL: the number of CD3 positive intraepithelial lymphocytes/100 enterocytes; CD-Rem: celiac disease in remission; CD-Act: active celiac disease, NCGS: non-celiac gluten sensitivity; Ni-ACM: nickel allergic contact mucositis. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005, *** <span class="html-italic">p</span> &lt; 0.0005 for NCGS, Ni-ACM, and CD-Act versus CD-Rem; § <span class="html-italic">p</span> &lt; 0.05 and §§§§ <span class="html-italic">p</span> &lt; 0.0001 for all groups versus CD-Act; °°°° <span class="html-italic">p</span> &lt; 0.0001 for all groups versus CD-Act (ANOVA).</p>
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<p>Histomorphometric evaluation of capillary density on duodenal biopsy, including a representative image of a villus immuno-stained with an antibody specific for endothelial cells (CD34) (<b>A</b>) and the measurement of capillary (green) and villous (red) areas (<b>B</b>). The bar graphs represent the number of intra-villous capillaries/villus area (μm<sup>2</sup>) × 100 (<b>C</b>) and the ratio between the total area of the lumen of intra-villous capillaries/total villous area × 100 (<b>D</b>). CD-Rem: celiac disease in remission; NCGS: non-celiac gluten sensitivity; Ni-ACM: nickel allergic contact mucositis; CD-Act: active celiac disease; CTR: controls. * <span class="html-italic">p</span> &lt; 0.05 for Ni-ACM versus CD-Rem (ANOVA).</p>
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13 pages, 1386 KiB  
Article
Co-Occurrence of mcr-1 and Carbapenem Resistance in Avian Pathogenic E. coli Serogroup O78 ST95 from Colibacillosis-Infected Broiler Chickens
by Muhammad Usman, Muhammad Hidayat Rasool, Mohsin Khurshid, Bilal Aslam and Zulqarnain Baloch
Antibiotics 2023, 12(5), 812; https://doi.org/10.3390/antibiotics12050812 - 26 Apr 2023
Cited by 4 | Viewed by 2238
Abstract
Avian pathogenic Escherichia coli (APEC) is responsible for significant economic losses in the poultry industry. This study aimed to molecularly detect carbapenem-resistant co-harboring mcr-1 avian pathogenic E. coli in broiler chickens infected with colibacillosis. A total of 750 samples were collected from colibacillosis-infected [...] Read more.
Avian pathogenic Escherichia coli (APEC) is responsible for significant economic losses in the poultry industry. This study aimed to molecularly detect carbapenem-resistant co-harboring mcr-1 avian pathogenic E. coli in broiler chickens infected with colibacillosis. A total of 750 samples were collected from colibacillosis-infected broilers, and conventional microbiological techniques were used to isolate and identify APEC. MALDI-TOF and virulence-associated genes (VAGs) were used for further identification. Phenotypic carbapenem resistance profiling was followed by molecular detection of carbapenem resistance genes (CRGs) and other resistance genes through PCR using specific primers. Isolates were also subjected to PCR for O typing, followed by allele-specific PCR to detect sequence type (ST) 95. Results showed that 154 (37%) isolates were confirmed as APEC, with 13 (8.4%) isolates found to be carbapenem-resistant (CR)-APEC. Among CR-APEC isolates, 5 (38%) were observed to co-harbor mcr-1. All CR-APEC showed the presence of five markers (ompT, hylF, iutA, iroN, and iss) APEC VAGs, and 89% of CR-APEC isolates displayed O78 type. Furthermore, 7 (54%) CR-APEC isolates were observed with ST95, all displaying O78 type. These results suggest that the improper use of antibiotics in poultry production systems is contributing to the emergence of pathogens such as CR-APEC co-harboring the mcr-1 gene. Full article
(This article belongs to the Special Issue Antibiotic Resistance in Companion and Food-Producing Animals)
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<p>The detection rate of VAGs in CR-APEC and CR-APEC co-harboring <span class="html-italic">mcr-1</span> isolates.</p>
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<p>Sample-based detection of carbapenem-resistant genes (CRGs) among CR-APEC isolates.</p>
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<p>(<b>A</b>) Sampled broiler showing a typical gross lesion of colibacillosis, i.e., perihepatitis (<b>B</b>) Sampled broiler showing a typical gross lesion of colibacillosis, pericarditis, and perihepatitis (<b>C</b>) EMB agar plate showing metallic sheen colonies of <span class="html-italic">E. coli</span>.</p>
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11 pages, 1425 KiB  
Article
Safety and Immunogenicity of a Chimeric Subunit Vaccine against Shiga Toxin-Producing Escherichia coli in Pregnant Cows
by Roberto M. Vidal, David A. Montero, Felipe Del Canto, Juan C. Salazar, Carolina Arellano, Alhejandra Alvarez, Nora L. Padola, Hernán Moscuzza, Analía Etcheverría, Daniel Fernández, Victoria Velez, Mauro García, Rocío Colello, Marcelo Sanz and Angel Oñate
Int. J. Mol. Sci. 2023, 24(3), 2771; https://doi.org/10.3390/ijms24032771 - 1 Feb 2023
Cited by 3 | Viewed by 2608
Abstract
Shiga toxin-producing Escherichia coli (STEC) is a zoonotic pathogen that causes gastroenteritis and Hemolytic Uremic Syndrome. Cattle are the main animal reservoir, excreting the bacteria in their feces and contaminating the environment. In addition, meat can be contaminated by releasing the intestinal content [...] Read more.
Shiga toxin-producing Escherichia coli (STEC) is a zoonotic pathogen that causes gastroenteritis and Hemolytic Uremic Syndrome. Cattle are the main animal reservoir, excreting the bacteria in their feces and contaminating the environment. In addition, meat can be contaminated by releasing the intestinal content during slaughtering. Here, we evaluated the safety and immunogenicity of a vaccine candidate against STEC that was formulated with two chimeric proteins (Chi1 and Chi2), which contain epitopes of the OmpT, Cah and Hes proteins. Thirty pregnant cows in their third trimester of gestation were included and distributed into six groups (n = 5 per group): four groups were administered intramuscularly with three doses of the formulation containing 40 µg or 100 µg of each protein plus the Quil-A or Montanide™ Gel adjuvants, while two control groups were administered with placebos. No local or systemic adverse effects were observed during the study, and hematological parameters and values of blood biochemical indicators were similar among all groups. Furthermore, all vaccine formulations triggered systemic anti-Chi1/Chi2 IgG antibody levels that were significantly higher than the control groups. However, specific IgA levels were generally low and without significant differences among groups. Notably, anti-Chi1/Chi2 IgG antibody levels in the serum of newborn calves fed with colostrum from their immunized dams were significantly higher compared to newborn calves fed with colostrum from control cows, suggesting a passive immunization through colostrum. These results demonstrate that this vaccine is safe and immunogenic when applied to pregnant cows during the third trimester of gestation. Full article
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<p>Experimental design of this field trial. The different groups of animals, vaccine formulations and placebos and immunization schedule are shown.</p>
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<p>Serum antibody response in cows immunized with the vaccine formulations. Sera obtained before the first immunization and after the last immunization were used for the determination of anti-Chi1/Chi2 IgG and IgA antibodies. Samples were analyzed in duplicate, and the results are expressed as means ± SEM of absorbance values at 405 nm for each serum dilution, <span class="html-italic">n</span> = 5 animals per group. Anti-Chi1/Chi2 IgG (<b>a</b>) and IgA (<b>c</b>) antibodies from P1, P2 and P3 groups. Anti-Chi1/Chi2 IgG (<b>b</b>) and IgA (<b>d</b>) antibodies from P4, P5 and P6 groups. Statistical analysis was performed using a two-way ANOVA, followed by Tukey’s multiple comparison test. <span class="html-italic">p</span> &lt; 0.05 was considered significant. Asterisks (*) indicate significant differences between the group immunized with the formulation containing 40 µg of each chimeric protein and the control group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005, *** <span class="html-italic">p</span> &lt; 0.0005. Number signs (#) indicate significant differences between the group immunized with the formulation containing 100 µg of each chimeric protein and the control group. # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.005, ### <span class="html-italic">p</span> &lt; 0.0005.</p>
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<p>Chi1/Chi2—specific antibody levels in colostrum. (<b>a</b>) Colostrum from P1, P2 and P3 groups. (<b>b</b>) Colostrum from P4, P5 and P6 groups. Data analysis was by Kruskal−Wallis test, followed by Dunn’s multiple comparison test. <span class="html-italic">p</span> &lt; 0.05 was considered significant. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Chi1/Chi2—specific antibody levels present in the serum of newborn calves. (<b>a</b>) Newborn calves from groups P1, P2 and P3. (<b>b</b>) Newborn calves from groups P4, P5 and P6. Data analysis was by a two-way ANOVA, followed by Tukey’s multiple comparison test. <span class="html-italic">p</span> &lt; 0.05 was considered significant. Asterisks (*) indicate significant differences between the group immunized with the formulation containing 40 µg of each chimeric antigen and the control group (adjuvant alone). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.005, *** <span class="html-italic">p</span> &lt; 0.0005. Number signs (#) indicate significant differences between the group immunized with the formulation containing 100 µg of each chimeric antigen and the control group (adjuvant alone). # <span class="html-italic">p</span> &lt; 0.05, ### <span class="html-italic">p</span> &lt; 0.0005.</p>
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16 pages, 1359 KiB  
Article
Characterization of Avian Pathogenic Escherichia coli Isolated from Broiler Breeders with Colibacillosis in Mississippi
by Jiddu Joseph, Madalyn Jennings, Nicolle Barbieri, Li Zhang, Pratima Adhikari and Reshma Ramachandran
Poultry 2023, 2(1), 24-39; https://doi.org/10.3390/poultry2010004 - 27 Jan 2023
Cited by 6 | Viewed by 4021
Abstract
Avian pathogenic Escherichia coli (APEC) causes colibacillosis in poultry, a leading cause of poultry mortality worldwide. It is crucial to control APEC in broiler breeders as it is vertically transferred to progeny via eggs. However, there is only limited knowledge on the current [...] Read more.
Avian pathogenic Escherichia coli (APEC) causes colibacillosis in poultry, a leading cause of poultry mortality worldwide. It is crucial to control APEC in broiler breeders as it is vertically transferred to progeny via eggs. However, there is only limited knowledge on the current APEC population in breeders. This study characterized 28 APEC strains isolated from broiler breeders with colibacillosis. The genotypic-virulence characteristics as well as antimicrobial and heavy-metal resistance patterns of the isolates were determined. Results showed that O88 is the most prevalent serogroup and B2 is the predominant phylogenetic group. Among virulence genes, genes for iron acquisition (iroN and iutA), protectins (iss and ompT), and toxin production (hlyF) exhibited the highest prevalence. Further, 93% of the isolates carried at least one antimicrobial resistance gene with highest prevalence for tetracycline gene tetA. Among the isolates, 10.71% exhibited multidrug resistance. All isolates carried at least one heavy-metal resistance gene with the highest prevalence for arsenic gene arsC and the highest resistance towards silver. Our findings provide insight into the characteristics of current APEC populations in broiler breeders in Mississippi. This will help future research on the pathogenesis of APEC and the development of effective prevention and control strategies against APEC in broiler breeders. Full article
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<p>Pie charts showing the prevalence of O and H serogroups among the broiler breeder APEC isolates. (<bold>a</bold>) The O-serogroups identified among the typed isolates were O88, O8, O25, O115, O166, O161, and O1. (<bold>b</bold>) The H serogroups identified among the typed isolates were H4, H7, H8, H9, H21, H32, and H34. Data represented as the percentage of prevalence.</p>
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<p>Pie chart showing phylogenetic classification of broiler breeder APEC isolates. The phylogenetic groups identified among the 28 isolates were B2, D, and B1; and each segment represent the percentage prevalence.</p>
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<p>Prevalence of virulence-associated genes among broiler breeder APEC isolates. <italic>papC</italic> and <italic>tsh</italic> code for adhesins; <italic>ibeA</italic> for invasin; <italic>iutA</italic> and <italic>iroN</italic> indicate iron acquisition systems; <italic>iss</italic> and <italic>ompT</italic> for protectins; <italic>astA</italic> and <italic>hylF</italic> indicate toxins; and <italic>cva/cvi</italic> is part of the colicin V plasmid.</p>
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<p>Prevalence of antimicrobial and heavy-metal resistance genes among broiler breeder APEC isolates. (<bold>a</bold>) Antimicrobial resistance genes tested in the 28 isolates. <italic>tetA</italic> confers resistance to tetracycline; <italic>aac3Vla</italic>, <italic>aph3IA</italic>, and <italic>aadA</italic> to aminoglycosides; <italic>qacEΔ</italic> to quaternary ammonium compounds; <italic>blaTEM</italic> to β-lactamase; <italic>blaCTX-M</italic> to cephalosporins; <italic>dfr7</italic> and <italic>sul1</italic> to sulfonamides; <italic>qnr</italic> to quinolones; and <italic>cat1</italic> to phenicols. (<bold>b</bold>) <italic>arsC</italic> confers resistance to arsenic; <italic>pcoA, pcoD, pcoE</italic> to copper; <italic>silE, silP</italic> to silver; <italic>merA</italic> to mercury; and <italic>terD</italic>, <italic>terF</italic>, <italic>terX</italic>, and <italic>terY3</italic> to tellurium.</p>
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<p>Results of phenotypic antimicrobial and heavy-metal resistance pattern of broiler breeder APEC isolates. (<bold>a</bold>) Antibiotic-resistance patterns towards ten antibiotics were tested using Kirby–Bauer disk diffusion assay. TET: tetracycline, STM: streptomycin, KAN: kanamycin, GEN: gentamicin, SXT: sulphamethoxazole-trimethoprim, AMP/SUL: ampicillin/ sulbactam, CTX: cefotaxime, CPFX: ciprofloxacin, CAP: chloramphenicol, NAL: nalidixic acid, MDR: multi- drug resistance (<bold>b</bold>) Quaternary ammonium compound (QAC) and heavy-metal resistance patterns were tested using a broth microdilution assay.</p>
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18 pages, 3233 KiB  
Article
Molecular Insights into Substrate Binding of the Outer Membrane Enzyme OmpT
by Yubo Zhang and Marc Baaden
Catalysts 2023, 13(2), 214; https://doi.org/10.3390/catal13020214 - 17 Jan 2023
Cited by 2 | Viewed by 2583
Abstract
The enzyme OmpT of the outer membrane of Escherichia coli shows proteolytic activity and cleaves peptides and proteins. Using molecular dynamics simulations in a fully hydrated lipid bilayer on a time scale of hundreds of nanoseconds, we draw a detailed atomic picture of [...] Read more.
The enzyme OmpT of the outer membrane of Escherichia coli shows proteolytic activity and cleaves peptides and proteins. Using molecular dynamics simulations in a fully hydrated lipid bilayer on a time scale of hundreds of nanoseconds, we draw a detailed atomic picture of substrate recognition in the OmpT-holo enzyme complex. Hydrogen bonds and salt bridges are essential for maintaining the integrity of the active site and play a central role for OmpT in recognizing its substrate. Electrostatic interactions are critical at all stages from approaching the substrate to docking at the active site. Computational alanine scanning based on the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) approach confirms the importance of multiple residues in the active site that form salt bridges. The substrate fluctuates along the axis of the β-barrel, which is associated with oscillations of the binding cleft formed by the residue pairs D210-H212 and D83-D85. Principal component analysis suggests that substrate and protein movements are correlated. We observe the transient presence of putative catalytic water molecules near the active site, which may be involved in the nucleophilic attack on the cleavable peptide bond of the substrate. Full article
(This article belongs to the Topic Advances in Enzymes and Protein Engineering)
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<p>(<b>A</b>) The root mean square carbon alpha fluctuations (RMSF) and (<b>B</b>) the solvent accessible surface area (SASA) as a function of the residue number for the ARRA-OmpT complex. A structural snapshot highlights the position of the L1, L2, and L3 loops on the secondary structure of the enzyme, as seen from above the membrane. The numbers of the residues are given for reference.</p>
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<p>(<b>A</b>) Superposition of two conformations of the R301 residue of the ARRA-OmpT complex at 0 ns (brown) and at 100 ns (blue). The neighboring residues D85 and D97 of OmpT are in close contact with R301 and are highlighted in red. (<b>B</b>) The two-dimensional free energy landscape as a function of distances s1 and s2 (defined in the text) for the 100 ns simulation. The asterisk (*) and cross (+) indicate the distances for the first and last simulation snapshots, respectively. (<b>C</b>) Time series of the number of hydrogen bonds between selected active site residues (E27 and D208) of OmpT and basic residue R300 of the ARRA peptide. Hydrogen bonds were calculated with a donor-acceptor distance of 3.5 Å and an angle of 35° between donor-H-acceptor positions. (<b>D</b>) Time series of closest contact distances of salt bridges between selected active site residues (D97 and D85) of OmpT and basic residue R301 of the ARRA peptide. The distance of salt bridges was calculated using the smallest native distance between two residues.</p>
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<p>Temporal evolution of the distances δ (<b>A</b>) and ε (<b>B</b>) defined in the text. The boundaries of these oscillating values are given as lines δ1, δ2, ε1, and ε2. (<b>C</b>) Boltzman-weighted 2D energy plot of the eigenvector of the first principal component XV1 (vertical) against the ε-distance distribution (horizontal). The two observed minima are labeled according to their correspondence with the ε1- (*) and ε2-distance (+) limits. The porcupine diagram of the first eigenvector for the simulation of ARRA-OmpT. The model is shown as a backbone trace. The arrows at each backbone atom indicate the direction of the eigenvector.</p>
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<p>(<b>A</b>) The major active site residues in the extracellular part of OmpT. (<b>B</b>) Number of hydrogen bonds between active site residues plotted against time for the <span class="html-italic">holo</span>–protein system. Hydrogen bonds were calculated using a donor–acceptor distance of 3.5 Å and an angle of 35° between donor–H–acceptor positions. (<b>C</b>) Salt bridge interactions between active site residues (H212-D210, R300-E27, and R300-D210) plotted against time. Salt bridge distance was calculated using the smallest native distance between two residues.</p>
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<p>Binding affinities estimated by computer-assisted alanine scanning for mutations of the ARRA-OmpT complex (<math display="inline"><semantics> <mrow> <mo>Δ</mo> <mo>Δ</mo> <msubsup> <mi>G</mi> <mrow> <mi>b</mi> <mi>i</mi> <mi>n</mi> <mi>d</mi> <mi>i</mi> <mi>n</mi> <mi>g</mi> </mrow> <mo>*</mo> </msubsup> <mo>=</mo> <mo>Δ</mo> <msubsup> <mi>G</mi> <mrow> <mi>b</mi> <mi>i</mi> <mi>n</mi> <mi>d</mi> <mi>i</mi> <mi>n</mi> <mi>g</mi> <mfenced> <mrow> <mi>m</mi> <mi>u</mi> <mi>t</mi> <mi>a</mi> <mi>n</mi> <mi>t</mi> </mrow> </mfenced> </mrow> <mo>*</mo> </msubsup> <mo>−</mo> <mo>Δ</mo> <msubsup> <mi>G</mi> <mrow> <mi>b</mi> <mi>i</mi> <mi>n</mi> <mi>d</mi> <mi>i</mi> <mi>n</mi> <mi>g</mi> <mfenced> <mrow> <mi>w</mi> <mi>i</mi> <mi>l</mi> <mi>d</mi> <mtext>-</mtext> <mi>t</mi> <mi>y</mi> <mi>p</mi> <mi>e</mi> </mrow> </mfenced> </mrow> <mo>*</mo> </msubsup> </mrow> </semantics></math>). <math display="inline"><semantics> <mrow> <mo>Δ</mo> <mo>Δ</mo> <msubsup> <mi>G</mi> <mrow> <mi>b</mi> <mi>i</mi> <mi>n</mi> <mi>d</mi> <mi>i</mi> <mi>n</mi> <mi>g</mi> </mrow> <mo>*</mo> </msubsup> </mrow> </semantics></math> results for 10 single mutations in either OmpT or ARRA in the initial structure at 0 ns (black) and averaged over 10 structures at the end of the 100 ns simulation (shaded; error bars represent standard deviations). For D85, D97, and D83, there was no interaction at 0 ns. The corresponding bars with the value zero are not displayed.</p>
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<p>(<b>A</b>) The reference group and the pull group are used for umbrella sampling. The ligand backbone is shown as tube in red and blue, representing the initial and final positions of the ligand moving away from OmpT in the z-direction, shown next to the free energy landscape for binding of the ARRA and AKKA ligands to OmpT. (<b>B</b>) Three different snapshots were selected for umbrella sampling with the COM distance between the reference and pull groups being 2.8, 3.7, and 4.4 nm, respectively.</p>
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<p>Two putative water molecules possibly involved in the catalytic mechanism (<b>A</b>). The black arrow describes the direction of a nucleophilic attack on the cleavable peptide bond of substrate residue R300. (<b>B</b>) The occupancy of the two types of “catalytic” water position, W1 and W2 (defined in the text), is indicated by a colored bar as a function of simulation time.</p>
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<p>(<b>A</b>) Root mean square deviation (RMSD) of the ARRA-OmpT complex with respect to the initial structure for the carbon alpha atoms of all residues (red), the coil and turn structural elements (blue), and the β-barrel (green) during the 100 ns production simulation. (<b>B</b>) Temporal evolution of the secondary structure elements. The beta sheets, turns, and coil regions are shown in yellow, green, and white, respectively. Markers β1 to β10 represent the ten different beta sheets of OmpT.</p>
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<p>Projection of the free energy landscape representing free energy basins as a function of key distances d1 and d2 characterizing the active site center. The landscape’s free energy basin is concentrated around a narrow conformation of the active site.</p>
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17 pages, 1387 KiB  
Article
High Virulence and Multidrug Resistance of Escherichia coli Isolated in Periodontal Disease
by Tania Hernández-Jaimes, Eric Monroy-Pérez, Javier Garzón, Rosario Morales-Espinosa, Armando Navarro-Ocaña, Luis Rey García-Cortés, Nancy Nolasco-Alonso, Fátima Korina Gaytán-Núñez, Moisés Moreno-Noguez, Felipe Vaca-Paniagua, Ernesto Arturo Rojas-Jiménez and Gloria Luz Paniagua-Contreras
Microorganisms 2023, 11(1), 45; https://doi.org/10.3390/microorganisms11010045 - 23 Dec 2022
Cited by 3 | Viewed by 2370
Abstract
Periodontal disease is caused by different gram-negative anaerobic bacteria; however, Escherichia coli has also been isolated from periodontitis and its role in periodontitis is less known. This study aimed to determine the variability in virulence genotype, antibiotic resistance phenotype, biofilm formation, phylogroups, and [...] Read more.
Periodontal disease is caused by different gram-negative anaerobic bacteria; however, Escherichia coli has also been isolated from periodontitis and its role in periodontitis is less known. This study aimed to determine the variability in virulence genotype, antibiotic resistance phenotype, biofilm formation, phylogroups, and serotypes in different emerging periodontal strains of Escherichia coli, isolated from patients with periodontal disease and healthy controls. E. coli, virulence genes, and phylogroups, were identified by PCR, antibiotic susceptibility by the Kirby-Bauer method, biofilm formation was quantified using polystyrene microtiter plates, and serotypes were determined by serotyping. Although E. coli was not detected in the controls (n = 70), it was isolated in 14.7% (100/678) of the patients. Most of the strains (n = 81/100) were multidrug-resistance. The most frequent adhesion genes among the strains were fimH and iha, toxin genes were usp and hlyA, iron-acquisition genes were fyuA and irp2, and protectin genes were ompT, and KpsMT. Phylogroup B2 and serotype O25:H4 were the most predominant among the strains. These findings suggest that E. coli may be involved in periodontal disease due to its high virulence, multidrug-resistance, and a wide distribution of phylogroups and serotypes. Full article
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<p>Hierarchical clustering of <span class="html-italic">E. coli</span> strains according to the virulence genotype profile and its relationship with biofilm production, phylogroups, serotypes, and diagnoses. Positivity and negativity for a given genotype are represented by a red and gray “rectangle” respectively. Genetic functions, biofilm production, phylogroups, serotypes, and diagnostics are color-coded as indicated in the key below. Cladograms of the strains and genes are shown along the top and “left” respectively. Upper axis: ID of the strains. Left axis: name of the virulence genes. Right blue bars: detection percentage of each virulence gene. Lower blue bars: number of virulence genes detected in each strain. Lower axis: serotypes identified in each strain.</p>
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26 pages, 4787 KiB  
Article
High-Resolution Small RNAs Landscape Provides Insights into Alkane Adaptation in the Marine Alkane-Degrader Alcanivorax dieselolei B-5
by Guangshan Wei, Sujie Li, Sida Ye, Zining Wang, Kourosh Zarringhalam, Jianguo He, Wanpeng Wang and Zongze Shao
Int. J. Mol. Sci. 2022, 23(24), 15995; https://doi.org/10.3390/ijms232415995 - 15 Dec 2022
Cited by 1 | Viewed by 2131
Abstract
Alkanes are widespread in the ocean, and Alcanivorax is one of the most ubiquitous alkane-degrading bacteria in the marine ecosystem. Small RNAs (sRNAs) are usually at the heart of regulatory pathways, but sRNA-mediated alkane metabolic adaptability still remains largely unknown due to the [...] Read more.
Alkanes are widespread in the ocean, and Alcanivorax is one of the most ubiquitous alkane-degrading bacteria in the marine ecosystem. Small RNAs (sRNAs) are usually at the heart of regulatory pathways, but sRNA-mediated alkane metabolic adaptability still remains largely unknown due to the difficulties of identification. Here, differential RNA sequencing (dRNA-seq) modified with a size selection (~50-nt to 500-nt) strategy was used to generate high-resolution sRNAs profiling in the model species Alcanivorax dieselolei B-5 under alkane (n-hexadecane) and non-alkane (acetate) conditions. As a result, we identified 549 sRNA candidates at single-nucleotide resolution of 5′-ends, 63.4% of which are with transcription start sites (TSSs), and 36.6% of which are with processing sites (PSSs) at the 5′-ends. These sRNAs originate from almost any location in the genome, regardless of intragenic (65.8%), antisense (20.6%) and intergenic (6.2%) regions, and RNase E may function in the maturation of sRNAs. Most sRNAs locally distribute across the 15 reference genomes of Alcanivorax, and only 7.5% of sRNAs are broadly conserved in this genus. Expression responses to the alkane of several core conserved sRNAs, including 6S RNA, M1 RNA and tmRNA, indicate that they may participate in alkane metabolisms and result in more actively global transcription, RNA processing and stresses mitigation. Two novel CsrA-related sRNAs are identified, which may be involved in the translational activation of alkane metabolism-related genes by sequestering the global repressor CsrA. The relationships of sRNAs with the characterized genes of alkane sensing (ompS), chemotaxis (mcp, cheR, cheW2), transporting (ompT1, ompT2, ompT3) and hydroxylation (alkB1, alkB2, almA) were created based on the genome-wide predicted sRNA–mRNA interactions. Overall, the sRNA landscape lays the ground for uncovering cryptic regulations in critical marine bacterium, among which both the core and species-specific sRNAs are implicated in the alkane adaptive metabolisms. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>Genome-wide sRNAs landscape of A. dieselolei B-5. (<b>A</b>) Diagram shows the distributions of sRNAs, TSSs and PSSs across the B-5 whole genome. From outside to inside, the rings represent the distributions of CDSs, sRNAs, TSSs, PSSs and the GC content, respectively, and the values in brackets show corresponding numbers or percentages in the genome. The orientations of each ring are clockwise for the plus (+) strand and counterclockwise for the minus (−) strand. The relatively conserved sRNAs are red marked on the corresponding rings, and their annotated names are displayed on the outermost edges of the plot; black fonts for Rfam families and grey for identified CsrA-related sRNAs. Circos plot was created by using Proksee (<a href="https://proksee.ca/" target="_blank">https://proksee.ca/</a>, accessed on 23 March 2022). (<b>B</b>) The size distribution of sRNAs. (<b>C</b>) Comparison of the distributing proportions of CDSs and sRNAs in two strands (+/−) of the genome.</p>
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<p>Origin and location patterns of sRNAs. (<b>A</b>) Distribution of sRNAs classified by the origins of 5′-ends. (<b>B</b>,<b>C</b>) show the sequence logos of neighboring regions of TSSs and PSSs, respectively. The “−” and “+” before the numbers represent the upstream and downstream positions, respectively, and the featured positions are shown with bold and red fonts. (<b>D</b>,<b>E</b>) show the distributions of sRNAs classified by their locations relative to the genomic annotations. The percentage represents the ratio of one type of sRNA in the total, and the following number in the bracket shows the corresponding amount. The relationships between (<b>A</b>) and (<b>D</b>) are connected by a Sankey diagram created by using the SankeyMATIC (<a href="https://sankeymatic.com/build/" target="_blank">https://sankeymatic.com/build/</a>, accessed on 28 February 2022).</p>
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<p>Sequence and structure features of sRNAs with different classifications. (<b>A</b>) Boxplot shows the length distributions of different types of sRNAs. The grey stripes in the background shows the overall length distributions. (<b>B</b>) GC contents and (<b>C</b>) NMFEs of classified sRNAs, CDSs, rRNAs and tRNAs.</p>
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<p>Rfam-annotated sRNAs of <span class="html-italic">A. dieselolei</span> and their distributions in genus <span class="html-italic">Alcanivorax</span>. (<b>A</b>) IGV views on the read coverages of Rfam-annotated sRNAs. Tracks display the different experimental conditions (i.e., C for C16 (hexadecane) and N for NaAc (sodium acetate) carbon sources) and RNA-seq strategies (i.e., TEX+ and TEX- for dRNA-seq and FRG for ssRNA-seq). The reads mapped on the plus (P) and minus (M) strands of the genome are in red and black colours, respectively. (<b>B</b>) The homologs of Rfam-annotated sRNAs in Alcanivorax. The left part shows the 16S rRNA gene-based maximum-likelihood phylogenic tree of representative <span class="html-italic">Alcanivorax</span> species constructed using MEGA6 (<a href="http://www.megasoftware.net" target="_blank">www.megasoftware.net</a>, accessed on 19 May 2022), the bootstrap values that are more than 50 are presented on the related branches. The middle part shows the distributions and identities (%) of sRNAs in different species, and the names of broadly conserved sRNAs are in red. The right part shows the names of corresponding species. (<b>C</b>) Neighboring gene synteny of highly conserved sRNAs. The red arrows in the middle represent the sRNAs, black for the highly conserved nearby genes and grey for the less conserved genes. The arrow direction to the left indicates genes on the minus-strand and to the right for the plus-strand. The details of the nearby genes are listed in <a href="#app1-ijms-23-15995" class="html-app">Table S12</a>. (<b>D</b>) Secondary structures and conserved features of the core sRNAs.</p>
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<p>Distribution of sRNA homologs across different species of <span class="html-italic">Alcanivorax</span>. (<b>A</b>) The number (percentage) distribution of sRNA homologs across one (<span class="html-italic">A. dieselole</span>i-specific) to all 15 (broadly conserved) species of <span class="html-italic">Alcanivorax</span>. The bar with broadly conserved sRNAs is marked in red. (<b>B</b>) The sequence identity distribution of the 41 conserved sRNAs across different <span class="html-italic">Alcanivorax</span> species and their classifications in the reference strain B-5. The different sequence identities are shown using color gradients from yellow to red. The number (2 or 3) in the grid represents the copy number of the related sRNA in corresponding species, and the average identity of multiple copies is shown. The classifications of sRNAs are also displayed by distinct colors.</p>
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<p>Expression of the top 50 sRNAs in alkane and non-alkane conditions. From left to right, the heatmap and colored bar charts show the expression levels in each sample of NaAc (non-alkane) or C16 (alkane) as carbon source, the differential expression of alkane vs. non-alkane conditions, the distribution of the top 50 highly expressed sRNAs in the two conditions and the classifications based on sRNA origins and locations. The sRNA names are listed behind, and the broadly conserved ones are in red.</p>
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<p>CsrA-related sRNAs and proposed regulation mechanisms in <span class="html-italic">A. dieselolei</span>. (<b>A</b>,<b>B</b>) show the secondary structures of the CsrR1 and CsrR2 conserved regions, respectively. (<b>C</b>) The alignments of CsrR2 homologous sequences in different species of <span class="html-italic">Alcanivorax</span>. The potential GGA motifs are marked using asterisks with different colors, red for motifs in loops, black for motifs in single-strand regions and blue for motifs at the junctions of the stem-loop. Secondary structures were calculated using RNAfold, and sequences were aligned with DNAMAN (version 8.0). (<b>D</b>) The proposed regulation mechanisms of the two CsrA-related sRNAs in alkane metabolism. The detailed notes are on the bottom right corner. Abbreviations: <span class="html-italic">miaA</span>, tRNA dimethylallyltransferase (B5T_00773); <span class="html-italic">hfq</span>/Hfq, Host factor (B5T_00774); RubA, Rubredoxin-NAD(+) reductase (B5T_04349); AldH, Aldehyde dehydrogenase (B5T_00039); ExaA, PQQ-dependent dehydrogenase (B5T_01640); <span class="html-italic">fdx</span>/Fdx, Ferredoxin (B5T_03135); <span class="html-italic">hpt</span>, Hpt domain-containing protein (B5T_03136). The mRNA/protein related to alkane metabolism is underlined. The question mark represents unknown effects.</p>
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<p>Putative relationships between the key genes in alkane metabolism and directly related sRNAs. (<b>A</b>) The three criteria to determine the directly related sRNAs with key genes of alkane metabolism. (<b>B</b>) Putative relationships between sRNAs and key genes. Each square represents a unique sRNA, and the sRNA identifiers are shown near the corresponding squares; the squares are colored according to the sRNA location-based classification. The ‘i, ii, iii’ in the squares correspond to the three criteria above. The ovals denote the mRNAs of key genes and are colored according to functions in alkane metabolism, and the related gene names are shown inside. The lines without an arrow show the matching relationships between sRNA and their targets, and the lines with arrows represent the sRNAs derived from the parental mRNAs. The <span class="html-italic">cis</span>-acting relationships (showing with wider lines) were deduced in terms of direct base-pairing for the asRNA and intra&amp;asRNA, and the <span class="html-italic">trans</span>-acting relationships (showing with narrow lines) were inferred by IntaRNA prediction. The key genes in the top 10 most likely targets are shown with solid lines, and dotted lines show the potential targets beyond that range (top 20 to 100). The colors of lines or arrows indicate the correlationships of both of the connected ends based on Spearman correlation analyses of ssRNA-seq expression values in two carbon sources (n = 6).</p>
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<p>Hypothesized sRNA-mediated alkane metabolic regulations in <span class="html-italic">A. dieselolei</span> B-5. The key related sRNAs (red and largest font) and their potential regulating mechanisms are shown in each dotted box. The significant expression changed sRNAs responding to the alkane, which are marked with up and down arrows before them, representing up- and down-regulated expressions, respectively. The possible regulating effects of the sRNAs are indicated above each dotted box (black and bold font). Abbreviations: RNAP, RNA polymerase; Hfq, Host factor; Fdx, Ferredoxin; RBS, ribosome binding site.</p>
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12 pages, 658 KiB  
Article
Genetic and Antimicrobial Resistance Profiles of Mammary Pathogenic E. coli (MPEC) Isolates from Bovine Clinical Mastitis
by Fernanda C. Campos, Ivana G. Castilho, Bruna F. Rossi, Érika C. R. Bonsaglia, Stéfani T. A. Dantas, Regiane C. B. Dias, Ary Fernandes Júnior, Rodrigo T. Hernandes, Carlos H. Camargo, Márcio G. Ribeiro, José C. F. Pantoja, Hélio Langoni and Vera L. M. Rall
Pathogens 2022, 11(12), 1435; https://doi.org/10.3390/pathogens11121435 - 28 Nov 2022
Cited by 7 | Viewed by 2541
Abstract
Mammary pathogenic E. coli (MPEC) is one of the main pathogens of environmental origin responsible for causing clinical mastitis worldwide. Even though E. coli are strongly associated with transient or persistent mastitis and the economic impacts of this disease, the virulence factors involved [...] Read more.
Mammary pathogenic E. coli (MPEC) is one of the main pathogens of environmental origin responsible for causing clinical mastitis worldwide. Even though E. coli are strongly associated with transient or persistent mastitis and the economic impacts of this disease, the virulence factors involved in the pathogenesis of MPEC remain unknown. Our aim was to characterize 110 MPEC isolates obtained from the milk of cows with clinical mastitis, regarding the virulence factor-encoding genes present, adherence patterns on HeLa cells, and antimicrobial resistance profile. The MPEC isolates were classified mainly in phylogroups A (50.9%) and B1 (38.2%). None of the isolates harbored genes used for diarrheagenic E. coli classification, but 26 (23.6%) and 4 (3.6%) isolates produced the aggregative or diffuse adherence pattern, respectively. Among the 22 genes investigated, encoding virulence factors associated with extraintestinal pathogenic E. coli pathogenesis, fimH (93.6%) was the most frequent, followed by traT (77.3%) and ompT (68.2%). Pulsed-field gel electrophoresis analysis revealed six pulse-types with isolates obtained over time, thus indicating persistent intramammary infections. The genes encoding beta-lactamases detected were as follows: blaTEM (35/31.8%); blaCTX-M-2/blaCTX-M-8 (2/1.8%); blaCTX-M-15 and blaCMY-2 (1/0.9%); five isolates were classified as extended spectrum beta-lactamase (ESBL) producers. As far as we know, papA, shf, ireA, sat and blaCTX-M-8 were detected for the first time in MPEC. In summary, the genetic profile of the MPEC studied was highly heterogeneous, making it impossible to establish a common genetic profile useful for molecular MPEC classification. Moreover, the detection of ESBL-producing isolates is a serious public health concern. Full article
(This article belongs to the Special Issue Pathogens in Ruminant Mastitis)
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<p>Dendrogram of PFGE patterns with &gt;95% similarity coefficients for <span class="html-italic">E. coli</span> isolates obtained from the milk of cows with clinical mastitis. (*): 100% similarity between phylogroups A and unknown; (**), and between phylogroups A and C.</p>
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11 pages, 721 KiB  
Article
Distribution of CRISPR in Escherichia coli Isolated from Bulk Tank Milk and Its Potential Relationship with Virulence
by Hyo-Jung Kang and Young-Ju Lee
Animals 2022, 12(4), 503; https://doi.org/10.3390/ani12040503 - 17 Feb 2022
Cited by 3 | Viewed by 2380
Abstract
Escherichia coli is one of the most common causes of mastitis on dairy farms around the world, but its clinical severity is determined by a combination of virulence factors. Recently, clustered regularly interspaced short palindromic repeat (CRISPR) arrays have been reported as a [...] Read more.
Escherichia coli is one of the most common causes of mastitis on dairy farms around the world, but its clinical severity is determined by a combination of virulence factors. Recently, clustered regularly interspaced short palindromic repeat (CRISPR) arrays have been reported as a novel typing method because of their usefulness in discriminating pathogenic bacterial isolates. Therefore, this study aimed to investigate the virulence potential of E. coli isolated from bulk tank milk, not from mastitis, and to analyze its pathogenic characterization using the CRISPR typing method. In total, 164 (89.6%) out of 183 E. coli isolated from the bulk tank milk of 290 farms carried one or more of eighteen virulence genes. The most prevalent virulence gene was fimH (80.9%), followed by iss (38.3%), traT (26.8%), ompT (25.7%), afa/draBC (24.0%), and univcnf (21.9%). Moreover, the phylogenetic group with the highest prevalence was B1 (64.0%), followed by A (20.1%), D (8.5%), and C (7.3%) (p < 0.05). Among the four CRISPR loci, only two, CRISPR 1 and CRISPR 2, were found. Interestingly, the distribution of CRISPR 1 was significantly higher in groups A and B1 compared to that of CRISPR 2 (p < 0.05), but there were no significant differences in groups C and D. The prevalence of CRISPR 1 by virulence gene ranged from 91.8% to 100%, whereas that of CRISPR 2 ranged from 57.5% to 93.9%. The distribution of CRISPR 1 was significantly higher in fimH, ompT, afa/draBC, and univcnf genes than that of CRISPR 2 (p < 0.05). The most prevalent E. coli sequence types (EST) among 26 ESTs was EST 22 (45.1%), followed by EST 4 (23.2%), EST 16 (20.1%), EST 25 (19.5%), and EST 24 (18.3%). Interestingly, four genes, fimH, ompT, afa/draBC, and univcnf, had a significantly higher prevalence in both EST 4 and EST 22 (p < 0.05). Among the seven protospacers derived from CRISPR 1, protospacer 163 had the highest prevalence (20.4%), and it only existed in EST 4 and EST 22. This study suggests that the CRISPR sequence-typing approach can help to clarify and trace virulence potential, although the E. coli isolates were from normal bulk tank milk and not from mastitis. Full article
(This article belongs to the Section Cattle)
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<p>Distribution of CRISPR 1 and CRISPR 2 by phylogenetic group in 164 <span class="html-italic">E. coli</span> possessing virulence genes, isolated from bulk tank milk. The asterisk indicates that there were significant differences between CRISPR 1 and CRISPR 2 (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Distribution of CRISPR1 and CRISPR2 by virulence gene in 164 <span class="html-italic">E. coli</span> possessing virulence genes, isolated from bulk tank milk. The asterisk indicates that there were significant differences between CRISPR 1 and CRISPR 2 (<span class="html-italic">p</span> &lt; 0.05).</p>
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