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1,017 results for “antimicrobials”
Datasets for Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar
<p>These datasets accompany the analyses conducted under the study title "<span>Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar</span>"</p> <p>Accompanying R scripts with commentary to run these data can be found in the Github repository under release v1.0.0: https://github.com/bmtalbot/Humans_and_Lemurs_2017</p>
When does antimicrobial resistance increase bacterial fitness? Effects of dosing, social interactions and frequency dependence on the benefits of AmpC β-lactamases in broth, biofilms and a gut infection model.
<p><span>One of the longstanding puzzles of antimicrobial resistance is why the frequency of resistance persists at intermediate levels.<span> </span>Theoretical explanations for the lack of fixation of resistance include cryptic costs of resistance or negative frequency-dependence but are seldom explored experimentally. <span> </span><em>β</em>-lactamases, which detoxify penicillin-related antibiotics, have well-characterized frequency-dependent dynamics driven by cheating and cooperation.<span> </span>However, bacterial physiology determines whether <em>β</em>-lactamases are cooperative and we know little about the sociality or fitness of <em>β</em>-lactamase producers in infections.<span> </span>Moreover, media-based experiments constrain how we measure fitness, and ignore important parameters such as infectivity and transmission among hosts.<span> </span>Here, we investigated the fitness effects of broad-spectrum AmpC <em>β</em>-lactamases in <em>Enterobacter cloacae</em> in broth, biofilms and gut infections in a model insect. <span> </span>We quantified frequency- and dose-dependent fitness using cefotaxime, a third-generation cephalosporin.<span> </span>We predicted that infection dynamics would be similar to those observed in biofilms, with social protection extending over a wide dose range.<span> </span>We found evidence for the sociality of <em>β</em>-lactamases in all contexts with negative frequency-dependent selection ensuring the persistence of wild-type bacteria although cooperation was less prevalent in biofilms, contrary to predictions.<span> </span>While competitive fitness in gut infections and broth had similar dynamics, incorporating infectivity into measurements of fitness in infections<em> </em>significantly affected conclusions. <span> </span>Resistant bacteria had reduced infectivity which limited the fitness benefits of resistance to infections challenged with low antibiotic doses and having low initial frequencies of resistance. <span> </span>The fitness of resistant bacteria in more physiologically tolerant states (in biofilms, in infections) could be constrained by the presence of wild-type bacteria, high antibiotic doses and limited availability of <em>β</em>-lactamases.<span> </span>One conclusion is that increased tolerance of <em>β</em> -lactams does not necessarily increase selection pressure for resistance.<span> </span>Overall, both cryptic fitness costs and frequency-dependence curtailed the fitness benefits of resistance in this study.<span> </span></span></p> <p><span> </span></p>
A Multiplexed Cell-Free Assay to Screen for Antimicrobial Peptides in Double Emulsion Droplets
<p>Data underlying the figures in the publication “A Multiplexed Cell-Free Assay to Screen for Antimicrobial Peptides in Double Emulsion Droplets”, published in <em>Angew. </em><em>Chem. Int. Ed.,</em> <strong>2022</strong>, e202114632.</p> <p><a href="https://onlinelibrary.wiley.com/doi/10.1002/anie.202114632">https://onlinelibrary.wiley.com/doi/10.1002/anie.202114632</a></p> <p> </p> <p>Table of contents:</p> <p><strong>1. Figure 1b</strong>: Bright-field image of the double emulsions droplets produced on the microfluidic chip (scale bar 40 μm).</p> <p><strong>2. Figure 1c</strong>: Source video of the image in <em>Figure 1c</em>. Overlaid fluorescence and bright-field image of a double emulsion in a hydrodynamic trap, containing LUVs loaded with a self-quenching concentration of SRB in the cell-free extract, showing background fluorescence (scale bar 20 μm).</p> <p><strong>3. Figure 2a</strong>: Excel file containing the experimental data for <em>Figure 2a</em>. Cell-free protein production. Cell-free production of sfGFP in double emulsion (DE) droplets. The expression and folding of sfGFP was confirmed by the increase of fluorescence at 516 nm (ex. 488 nm). The dashed ribbon represents standard deviation (n=150).</p> <p><strong>4. Figure 2c</strong>: Excel files containing the experimental data for <em>Figure 2c</em>. Mean fluorescence intensities of b) after incubation at room temperature for 16 hours. no DNA: DEs without any alpha-hemolys in plasmid DNA(n=107), α-HL:DEs with the alpha-hemolys in plasmid DNA(n=258), SDS: double emulsions without any alpha-hemolys in plasmid DNA, exposed to a solution of 0.5% SDS in buffer throughout the incubation (n=204).</p> <p><strong>5. Figure 2d</strong>: Excel file containing the experimental data for <em>Figure 2d</em>. Fluorophore leakage kinetics from mammalian-like LUVs with SRB and from bacteria-like LUVs with 6-FAM, induced by the cell-free expression of pneumolysin in a 384 well-plate, starting at time 0. Fractional fluorescence (fF) is calculated by setting the zero level to the vesicle fluorescence in the absence of DNA, and the maximum level of fluorescence, scaled to a value of 1, to the value obtained by lysing the vesicles with 0.5% SDS. Solid lines represent the average of three independent reactions visible below.</p> <p><strong>6. Figures 2e and 2f</strong>: FACS data for <em>Figures 2e</em> and <em>2f</em>.</p> <p><strong>7. Figure 3a</strong>: Excel file containing the experimental data for <em>Figure 3a</em>. Fluorophore leakage kinetics from mammalian-like LUVs with SRB and bacteria-like LUVs with 6-FAM, induced by the cell-free expression of meucin-25 in a 384 well-plate. Each well contained 8 nM of plasmid (Supporting Information Table 1). Solid lines represent the average of three technical replicates displayed as well (the lines are overlapping, thus not visible).</p> <p><strong>8. Figure 3c</strong>: Excel file containing the experimental data for <em>Figure 3c</em>. Bacterial viability assay with increasing meucin-25 concentrations, measured by flow cytometry. Propidium iodide (PI) cannot pass intact bacterial membranes and only intercalates the DNA of permeabilized dead bacteria (“PI positive”). Constitutively expressed sfGFP proteins normally efficiently retained in intact bacterial cells (“GFPpositive”) but lost in suitably permeabilized cells. Error bars indicate standard deviation (n=10000).</p> <p><strong>9. Figure SI_2</strong>: Excel files containing the experimental data for <em>Supplementary Figure 2</em>.</p> <p><strong>10. Figure SI_3</strong>: Excel file containing the experimental data for <em>Supplementary Figure 3</em>.</p> <p><strong>11. Figure SI_4a</strong>: Excel files containing the experimental data for <em>Supplementary Figure 4a</em>.</p> <p><strong>12. Figure SI_4b</strong>: Excel files containing the experimental data for <em>Supplementary Figure 4b</em>.</p> <p><strong>13. Figure SI_5</strong>: Excel files containing the experimental data for <em>Supplementary Figure 5</em>.</p> <p><strong>14. Figure SI_6</strong>: Excel files containing the experimental data for <em>Supplementary Figure 6</em>.</p> <p> </p> <p> </p>
Alterations of antimicrobial resistance genes in the clinical multi-drug resistance Acinetobacter baumannii isolates in Vietnam
<p><strong>FIGURE 1 </strong>List of antibiotic resistance gene expression.</p> <p><strong>TABLE 1 </strong>Primers used in this study.</p> <p><strong>TABLE 2 </strong>Clinical characteristics of 30 patients with <em>A. baumannii </em>isolates.</p> <p><strong>TABLE 3 </strong>Antimicrobial resistance values of <em>A. baumannii</em> isolated during 2017 to 2019 year in the Military Hospital 103.</p> <p><strong>TABLE 4 </strong>Relationship between genotype and phenotype antimicrobial resistance of isolates in this study.</p> <p><strong>TABLE 5 </strong>List of altered antibiotic resistance genes expression in isolates of <em>A. baumannii</em> (up or down two-fold changes of related genes compare with <em>16S rRNA</em> gene).</p> <p><strong>TABLE 6 </strong>The multiple antimicrobial resistance gene profile of 30 <em>A. baumannii</em> isolates.</p> <p> </p>
Code and Additional Files for the Manuscript "The Impact of Farming Practices on Resistance to Critically Important Antimicrobials in ESBL or AmpC-producing Escherichia coli in Thailand"
<p>These scripts were used in the"The Impact of Farming Practices on Resistance to Critically Important Antimicrobials in ESBL or AmpC-producing Escherichia coli in Thailand" manuscript. The scripts are ordered for ease of use. It also contains intermediate files and files necessary for the mapping. Table S1 containing the metadata is available in the supplementary information of the manuscript.</p>
ArMoR Cluster: 5 research projects fight Antimicrobial Resistance in livestock farming
<p>Within Horizon Results Booster programme (HRB), 4 Horizon 2020 projects (AVANT, DISARM, HealthyLivestock and ROADMAP) and 1 BBSRC funded project (AMRILS) have formed the "ArMoR Cluster" to develop a conceptual framework to improve understanding of AMR in livestock systems.</p> <p>Supported by the European Commission, Horizon Dissemination Booster (HRB) contributes to an effective transfer of research and innovation project results to policy makers, industry and society by offering various services as dissemination, exploitation strategy and business plan development to projects.</p> <p>The video is available on YouTube: <strong><a href="https://www.youtube.com/watch?v=rnU35ytdEuM">https://www.youtube.com/watch?v=rnU35ytdEuM</a></strong></p> <p>For any further questions please contact us at:</p> <ul> <li><strong><a href="https://zenodo.org/record/avant@rtds-group.com">avant@rtds-group.com</a></strong> (project AVANT),</li> <li><strong><a href="https://zenodo.org/record/info@disarmproject.eu">info@disarmproject.eu</a></strong> (project DISARM),</li> <li><strong><a href="https://zenodo.org/record/healthylivestockproject@yahoo.com">healthylivestockproject@yahoo.com</a></strong> (project Healthy Livestock) or</li> <li><strong><a href="mailto:roadmap.communication@gmail.com">roadmap.communication@gmail.com</a></strong> (project ROADMAP). </li> </ul>
Data and code for: Dihydrothiazolo ring-fused 2-pyridone antimicrobial compounds effectively treat Streptococcus pyogenes skin and soft tissue infection
<p>We have developed GmPcides from a peptidomimetic dihydrothiazolo ring-fused 2-pyridone scaffold that have antimicrobial activities against a broad-spectrum of Gram-positive pathogens. Here we examine the treatment efficacy of GmPcides using skin and soft tissue infection (SSTI) and biofilm formation models by <em>Streptococcus pyogenes</em>. Screening our compound library for minimal inhibitory (MIC) and minimal bactericidal (MBC) concentrations identified GmPcide PS757 as highly active against <em>S. pyogenes</em> . Treatment of <em>S. pyogenes</em> biofilm with PS757 revealed robust efficacy against all phases of biofilm formation by preventing initial biofilm development, ceasing biofilm maturation and eradicating mature biofilm. In a murine model of <em>S. pyogenes</em> SSTI, subcutaneous delivery of PS757 resulted in reduced levels of tissue damage, decreased bacterial burdens and accelerated rates of wound-healing, which were associated with down-regulation of key virulence factors, including M protein and the SpeB cysteine protease. These data demonstrate that GmPcides show considerable promise for treating <em>S. pyogenes</em> infections.</p>
The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is severely constrained by random peptide mixtures
<p><span>The prevalence of antibiotic-resistant pathogens has become a major threat to public health, requiring swift initiatives for discovering new strategies to control bacterial infections. Hence, antibiotic stewardship and rapid diagnostics, but also the development, and prudent use, of novel effective antimicrobial agents are paramount. Ideally, these agents should be less likely to select for resistance in pathogens than currently available conventional antimicrobials. The usage of antimicrobial Peptides (AMPs), key components of the innate immune response, and combination therapies, have been proposed as strategies to diminish the emergence of resistance.</span></p> <p><span>Herein, we investigated whether newly developed random antimicrobial peptide mixtures (RPMs) can significantly reduce the risk of resistance evolution <em>in vitro</em> to that of single sequence AMPs, using the ESKAPE pathogen <em>Pseudomonas aeruginosa</em> (<em>P. aeruginosa</em>) as a model Gram-negative bacterium. Infections of this pathogen are difficult to treat due the inherent resistance to many drug classes, enhanced by the capacity to</span><span> form biofilms. </span><em><span>P. aeruginosa</span></em><span> was experimentally evolved in the presence of AMPs or RPMs, subsequentially assessing the extent of resistance evolution and cross-resistance/collateral sensitivity between treatments. Furthermore, the fitness costs of resistance on bacterial growth were studied, and whole-genome sequencing used to investigate which mutations could be candidates for causing resistant phenotypes. Lastly, changes in the pharmacodynamics of the evolved bacterial strains were examined.</span></p> <p><span>Our findings suggest that using RPMs bears a much lower risk of resistance evolution compared to AMPs and mostly prevents cross-resistance development to other treatments, while maintaining (or even improving) drug sensitivity. This strengthens the case for using random cocktails of AMPs in favour of single AMPs, against which resistance evolved <em>in vitro</em>, providing an alternative to classic antibiotics worth pursuing.</span></p>
Figure 3 in Microbial source tracking and antimicrobial resistance in one river system of a rural community in Bahia, Brazil
Figure 3. Locations and copy numbers for human- and ruminant-indicative Bacteroides spp. DNA extracted from the material retained from filtration of 500 ml was used for qPCR determination of rDNA copy number. The size of the indicated shapes in the figure is proportional to the copy number/ml at that point as indicated in the legend. Inset shows points 12 and 13 at the same scale as the main figure.
Figure 2 in Microbial source tracking and antimicrobial resistance in one river system of a rural community in Bahia, Brazil
Figure 2. Locations and concentrations of coliforms and E. coli at water collection points. A volume of water (100 µl – 1 ml) collected mid-stream was plated using the Coliscan culture system. Colonies were identified and counted at 48h. The size of the indicated shapes in the figure is proportional to the number of colonies/ml cultured as indicated in the legend. Inset shows points 12 and 13 at the same scale as the main figure.
Figure 1 in Microbial source tracking and antimicrobial resistance in one river system of a rural community in Bahia, Brazil
Figure 1. Study area, rivers and water collection sites. The collection points on the Jiquiriçá River are P1-5; collection points on the Brejões P6-8. P3 is at the junction of the 2 rivers, and P9 and P10 are from the water treatment plant and an outside faucet, respectively. Left inset – Location of Bahia state, Salvador and Jenipapo within Brazil based on Wikimedia Commons (2011). Right inset – relationship of P12 and P13 to Jenipapo. These 2 points represent the source of piped water for the community and the furthest point upstream for collection on the Brejões River, respectively. Inset modified from Wikimedia Commons (2011).
Fig. 2 — Chromatogram for A in Antimicrobial activity of the crude peptide extracts from Blackfin sea catfish Arius jella Day, 1877
Fig. 2 — Chromatogram for A. jella peptide extract using FPLC: a) 5 % Sep-Pak fraction, b) 40 % Sep-Pak fraction, and c) 80 % Sep-Pak fraction
Figure 1. Standard curve for gallic acid y in Effect of extraction solvent system on the antimicrobial, antioxidant and total polyphenol content of the bark of Pistacia chinensis
Figure 1. Standard curve for gallic acid y = absorbance, x = concentration of Gallic Acid, R2 = correlation coefficient.
Figure 1 in Antimicrobial resistance profile of Aeromonas spp. isolated from asymptomatic Colossoma macropomum cultured in the Amazonas State, Brazil
Figure 1. Records of Aeromonas spp. isolated from tambaqui (Colossoma macropomum) by fish farms in the rainy season (bars with stripes) and the dry season (bars with dots).
Figure 2 in In vitro study of antimicrobial activity of some plant seeds against bacterial strains causing food poisoning diseases
Figure 2. MIC's of the effective plant seeds powder against S. aureus and K. pneumonia, ± standard error.
Tables and Figures complementing the European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2016
<p>All tables, figures and maps produced for the European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2016 are provided.</p>
Tables and Figures complementing the European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2017
<p>All tables, figures and maps produced for the European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2017 are provided.</p>
Figure 4 in Antimicrobial activity of noni fruit essential oil on Escherichia coli O157:H7 and Salmonella Enteritidis
Figure 4. The GC chromatogram of noni EO: 1. α-pinene; 2. camphene; 3. Methyl ester; 4. 2- heptanone; 5. Caprylic acid.
Figure 1 in Antimicrobial activity of noni fruit essential oil on Escherichia coli O157:H7 and Salmonella Enteritidis
Figure 1. The effect of noni EO on E. coli O157:H7 and S. Enteritidis using the direct spreading- plate method on the MIC value of noni EO towards both pathogens.
Figure 3 in Antimicrobial activity of noni fruit essential oil on Escherichia coli O157:H7 and Salmonella Enteritidis
Figure 3. The survival of E. coli O157:H7 and S. Enteritidis as affected by noni EO in TBS after a treatment for 16 hours.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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