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112 results for “Clostridioides difficile”
Gut microbiota inter-species interactions shape the response of Clostridioides difficile to clinically relevant antibiotics
<p>In the human gut, the growth of <em>Clostridioides difficile </em>is impacted by a complex web of inter-species interactions with members of human gut microbiota. We investigate the contribution of inter-species interactions on the antibiotic response of <em>C. difficile </em>to clinically relevant antibiotics using bottom-up assembly of human gut communities. We discover two classes of microbial interactions that alter <em>C. </em>difficile’s antibiotic susceptibility: infrequent increases in tolerance at high antibiotic concentrations and frequent growth enhancements at low antibiotic concentrations. Based on genome-wide transcriptional profiling data, we demonstrate that metal sequestration due to hydrogen sulfide production by the prevalent gut species <em>Desulfovibrio piger </em>increases metronidazole tolerance of <em>C. difficile</em>. Competition with species that display higher sensitivity to the antibiotic than <em>C. difficile </em>leads to enhanced growth of <em>C. difficile </em>at low antibiotic concentrations. A dynamic computational model identifies the ecological design principles driving this effect. Our results provide a deeper understanding of ecological and molecular principles shaping <em>C. difficile</em>’s response to antibiotics, which could inform therapeutic interventions.</p>
Gut microbiota inter-species interactions shape the response of Clostridioides difficile to clinically relevant antibiotics
<p>In the human gut, the growth of <em>Clostridioides difficile </em>is impacted by a complex web of inter-species interactions with members of human gut microbiota. We investigate the contribution of inter-species interactions on the antibiotic response of <em>C. difficile </em>to clinically relevant antibiotics using bottom-up assembly of human gut communities. We discover two classes of microbial interactions that alter <em>C. </em>difficile’s antibiotic susceptibility: infrequent increases in tolerance at high antibiotic concentrations and frequent growth enhancements at low antibiotic concentrations. Based on genome-wide transcriptional profiling data, we demonstrate that metal sequestration due to hydrogen sulfide production by the prevalent gut species <em>Desulfovibrio piger </em>increases metronidazole tolerance of <em>C. difficile</em>. Competition with species that display higher sensitivity to the antibiotic than <em>C. difficile </em>leads to enhanced growth of <em>C. difficile </em>at low antibiotic concentrations. A dynamic computational model identifies the ecological design principles driving this effect. Our results provide a deeper understanding of ecological and molecular principles shaping <em>C. difficile</em>’s response to antibiotics, which could inform therapeutic interventions.</p>
Illumina Sequencing Data for "Elucidating human gut microbiota interactions that robustly inhibit diverse Clostridioides difficile strains across different nutrient landscapes"
<p>Illumina Sequencing Data for Sulaiman et al., "Elucidating human gut microbiota interactions that robustly inhibit diverse Clostridioides difficile strains across different nutrient landscapes".</p>
Gut microbiota inter-species interactions shape the response of Clostridioides difficile to clinically relevant antibiotics
<p>In the human gut, the growth of <em>Clostridioides difficile </em>is impacted by a complex web of inter-species interactions with members of human gut microbiota. We investigate the contribution of inter-species interactions on the antibiotic response of <em>C. difficile </em>to clinically relevant antibiotics using bottom-up assembly of human gut communities. We discover two classes of microbial interactions that alter <em>C. </em>difficile’s antibiotic susceptibility: interactions resulting in increased <em>C. diffiicle </em>tolerance at high antibiotic concentrations (rare) and interactions resulting in <em>C. difficile </em>growth enhancement at low antibiotic concentrations (common). Based on genome-wide transcriptional profiling data, we demonstrate that metal sequestration due to hydrogen sulfide production by the prevalent gut species <em>Desulfovibrio piger </em>increases metronidazole tolerance of <em>C. difficile</em>. Competition with species that display higher sensitivity to the antibiotic than <em>C. difficile </em>leads to enhanced growth of <em>C. difficile </em>at low antibiotic concentrations. A dynamic computational model identifies the ecological design principles driving this effect. Our results provide a deeper understanding of ecological and molecular principles shaping <em>C. difficile</em>’s response to antibiotics, which could inform therapeutic interventions.In the human gut, the growth of <em>Clostridioides difficile </em>is impacted by a complex web of inter-species interactions with members of human gut microbiota. We investigate the contribution of inter-species interactions on the antibiotic response of <em>C. difficile </em>to clinically relevant antibiotics using bottom-up assembly of human gut communities. We discover two classes of microbial interactions that alter <em>C. </em>difficile’s antibiotic susceptibility: interactions resulting in increased <em>C. diffiicle </em>tolerance at high antibiotic concentrations (rare) and interactions resulting in <em>C. difficile </em>growth enhancement at low antibiotic concentrations (common). Based on genome-wide transcriptional profiling data, we demonstrate that metal sequestration due to hydrogen sulfide production by the prevalent gut species <em>Desulfovibrio piger </em>increases metronidazole tolerance of <em>C. difficile</em>. Competition with species that display higher sensitivity to the antibiotic than <em>C. difficile </em>leads to enhanced growth of <em>C. difficile </em>at low antibiotic concentrations. A dynamic computational model identifies the ecological design principles driving this effect. Our results provide a deeper understanding of ecological and molecular principles shaping <em>C. difficile</em>’s response to antibiotics, which could inform therapeutic interventions.</p>
Clostridioides difficile in Honduras: a genomic and phenotypic characterization of the persistent RT027 and emergent RT002 genotypes
<p>Supplementary dataset to the manuscript: Clostridioides difficile in Honduras: a genomic and phenotypic characterization of the persistent RT027 and emergent RT002 genotypes, by Mauricio Andino-Molina, Mostafa Abdel-Glil, Fanny Hidalgo-Villeda, Edgardo Tzoc, Gernot Schmoock, Mathias W. Pletz, Heinrich Neubauer & Christian Seyboldt. </p> <p>Dataset analysed with clostyper (https://gitlab.com/FLI_Bioinfo/clostyper)</p>
Exo-Metabolomics Data for "Phocaeicola vulgatus shapes the long-term growth dynamics and evolutionary adaptations of Clostridioides difficile"
<p>Exo-Metabolomics Data for "<em>Phocaeicola vulgatus</em> shapes the long-term growth dynamics and evolutionary adaptations of <em>Clostridioides difficile</em>"</p>
Illumina Sequencing Data for "Phocaeicola vulgatus shapes the long-term growth dynamics and evolutionary adaptations of Clostridioides difficile"
<p>Illumina Sequencing Data for "<em>Phocaeicola vulgatus</em> shapes the long-term growth dynamics and evolutionary adaptations of <em>Clostridioides difficile</em>"</p>
Emerging Clostridioides difficile ribotypes have divergent metabolic phenotypes
<p>Dataset of multi-well plate reader files related to the analysis of the growth of <em>C. difficile</em> isolates on differnet carbon substrates. </p> <p><strong>Data Collection. </strong>This<strong> </strong>dataset accompanies an <em>mSystems</em> article which is available at <a href="https://doi.org/10.1128/msystems.01075-24">https://doi.org/10.1128/msystems.01075-24</a>. The "Materials and Methods" section in this article fully describes the biological nature of these samples and how the samples were processed and analyzed. </p> <p><strong>Repository Content. </strong>The <em>amiga</em> folders contains both the raw data (see <em>data</em> and <em>mapping </em>sub-folders), intermediate outpus (see <em>dervied</em> sub-folders), and final outputs (see <em>figures</em> and <em>summary</em> sub-folders). Each <em>amiga </em>folder corresponds to a single working directory analyzed by the <a href="https://github.com/firasmidani/amiga"><em>AMiGA</em></a> software. For the <em>amiga-biolog</em> directory, the <em>notes</em> sub-folder also includes text files related to flagging plates and wells for quality issues.</p> <p><strong>Data Organization. </strong>Growth plate data are organized by the following experiments. </p> <ul> <li>biolog</li> <li>validation</li> <li>ribotype-255</li> <li>clade-5</li> <li>yeast-extract-biolog</li> <li>yeast-extract-validation</li> </ul> <p><strong>Data Analysis. </strong>Code used for manipulating and analyzing these samples is also publicly available on GitHub (<a href="https://github.com/firasmidani/cdiff-biolog-growth">https://github.com/firasmidani/cdiff-biolog-growth</a>) under the GNU GPL-3.0 license. The scripts in "analyze-code" can be used to analyze all data and the scripts in the "generate-figures" folder can be used to reproduce all figures included in the manuscript. See the GitHub repository for instructions on how to do so. </p> <p> </p>
Gut metabolites predict Clostridioides difficile recurrence
<p>This repository contains:</p> <p>1. Data used for analyses from:</p> <p>A) 16S rRNA gene amplicon analysis after paired-end Fastq files were truncated, filtered, denoised, and merged ["1-ASV_Counts.xlsx"]</p> <p>B) Untargeted metabolomics as provided by Metabolon ["2-UntargetedMetabolomics.xlsx"]</p> <p>C) Precision SCFA analysis ["3-PrecisionSCFA.xlsx"]</p> <p>D) Clincal demographic data of the study cohort ["Clinical Demographics.csv"]</p> <p> </p> <p>2. Detailed results of univariate analyses in sub-folder "Univariate analysis results" for clinical data, untargeted metabolomics data, SCFAs, and ASVs</p> <p> </p> <p>3. Detailed results of predictive analysis in subfolder "Predictive Analyses results", including per-fold performance results ("9-PredictiveResults.xlsx") and analysis of predictive features for ASVs ("10-ASVsPredictiveAnalysis.xlsx"), untargeted metabolites ("11-MetabsPredictiveAnalysis.xlsx"), targeted SCFAs ("12-SCFAPredictive Analysis.xlsx"), clinical data ("13-DemoPredictiveAnalysis.xlsx") and all data ("14-AllDataPredictiveAnalysis.xlsx")</p> <p>4. Data for generating all figures and analyses in the publication ("GenFigure&AnalysesData")</p>
Gut microbiota inter-species interactions shape the response of Clostridioides difficile to clinically relevant antibiotics
<p>In the human gut, the growth of <em>Clostridioides difficile </em>is impacted by a complex web of inter-species interactions with members of human gut microbiota. We investigate the contribution of inter-species interactions on the antibiotic response of <em>C. difficile </em>to clinically relevant antibiotics using bottom-up assembly of human gut communities. We discover two classes of microbial interactions that alter <em>C. </em>difficile’s antibiotic susceptibility: infrequent increases in tolerance at high antibiotic concentrations and frequent growth enhancements at low antibiotic concentrations. Based on genome-wide transcriptional profiling data, we demonstrate that metal sequestration due to hydrogen sulfide production by the prevalent gut species <em>Desulfovibrio piger </em>increases metronidazole tolerance of <em>C. difficile</em>. Competition with species that display higher sensitivity to the antibiotic than <em>C. difficile </em>leads to enhanced growth of <em>C. difficile </em>at low antibiotic concentrations. A dynamic computational model identifies the ecological design principles driving this effect. Our results provide a deeper understanding of ecological and molecular principles shaping <em>C. difficile</em>’s response to antibiotics, which could inform therapeutic interventions.</p>
Bezlotoxumab Yielded Outcomes by Addressing Personalized Needs in Clostridioides Difficile Infection
ClinicalTrials.gov study NCT05304715. IPD Sharing: NO. Countries: 1. Publications: 1.
A Multi-center, Single-arm Trial Exploring the Safety and Clinical Effectiveness of RBX2660 Administered by Colonoscopy to Adults With Recurrent Clostridioides Difficile Infection
ClinicalTrials.gov study NCT05831189. IPD Sharing: NO. Countries: 1. Publications: 3.
Primary or Recurrent Clostridioides Difficile Infection Treatment With Capsules of Lyophilised Faecal Microbiota vs Fidaxomicin
ClinicalTrials.gov study NCT05201079. IPD Sharing: Not stated. Countries: 1. Publications: 2.
ECOSPOR IV: An Open-Label Study Evaluating SER-109 in Recurrent Clostridioides Difficile Infection
ClinicalTrials.gov study NCT03183141. IPD Sharing: NO. Countries: 2. Publications: 2.
ACX-362E [Ibezapolstat] for Oral Treatment of Clostridioides Difficile Infection
ClinicalTrials.gov study NCT04247542. IPD Sharing: NO. Countries: 1. Publications: 5.
Phase 2 Study of VE303 for Prevention of Recurrent Clostridioides Difficile Infection
ClinicalTrials.gov study NCT03788434. IPD Sharing: NO. Countries: 2. Publications: 1.
Evaluation of CRS3123 vs. Oral Vancomycin in Adult Patients With Clostridioides Difficile Infection
ClinicalTrials.gov study NCT04781387. IPD Sharing: NO. Countries: 2. Publications: 1.
Data from: A multivalent mRNA-LNP vaccine protects against Clostridioides difficile infection
Open the record for dataset details and reuse information.
Volcano plot of Sigma B-dependent differential gene expression of Clostridioides difficile
<p>A customized whole-genome DNA microarray of <em>Clostridioides difficile </em>630∆<em>erm</em> was used (8x15K format, Agilent). Quadruplicate samples were analysed for the DNA microarray. Using the ULS fluorescent labelling kit for Agilent arrays (Kreatech), 1 µg of total RNA was used for labelling with either Cy3 (P<sub>tet</sub>-<em>sigB</em>) or Cy5 (P<sub>tet</sub>-<em>sLuc<sup>opt</sup></em>). After pooling and fragmentation, 300 ng of labelled RNA per sample was hybridized according to the two-color microarray protocol from Agilent. DNA microarrays were scanned with an Agilent C scanner and analysed. CDS_ID=GenBank identifier, gene_name=annotated gene name (when available), locus_tag= locus tag, protein=annotation of protein function (when available), log2FC= log 2 of the fold change (sigB overproduction/control), adj_Pvalue = adjusted P-value, significance = -10log(adj_Pvalue).</p>
Discordant Clostridioides difficile diagnostic assay and treatment practice: a cross-sectional study in a tertiary care hospital, Geneva, Switzerland
<p><b><span>Objectives:</span></b><span> </span><span><span>To determine the proportion of patients who received a treatment for </span><i><span>Clostridioides difficile</span></i><span> infection (CDI) among those presenting a discordant </span><i><span>Clostridioides difficile</span></i><span> diagnostic assay and to identify patient characteristics associated with the decision to treat CDI.</span></span></p> <p><b><span><span>Design: </span></span></b><span><span>Cross-sectional study.</span></span></p> <p><b><span><span>Setting: </span></span></b><span><span>Monocentric study in a tertiary care hospital, Geneva, Switzerland</span></span></p> <p><b><span>Participants: </span></b><span>Among 4562 adult patients tested for </span><i><span>C. difficile</span></i><span> between March 2017 and March 2019</span><span><span>, 208 patients with discordant tests' results</span></span><span> (positive nucleic acid amplification test [NAAT+]/negative enzyme immunoassay [EIA-]) were included.</span></p> <p><b><span>Main outcome measures:</span></b><span> </span><span><span>Treatment for CDI</span></span><span>.</span></p> <p><b><span>Results: </span></b><span><span>CDI treatment was administered in 147 (71%) cases</span></span><span>. In multivariate analysis, </span><span><span>an abdominal computed tomography scan</span></span><span> with signs of colitis (</span><span><span>OR 14.7; 95% CI 1.96-110.8) was the only factor associated with CDI treatment</span></span><span>.</span></p> <p><b><span>Conclusions:</span></b><span> The proportion of NAAT+/EIA- patients who received treatment questions the contribution of the EIA for the detection of toxin A/B after NAAT to limit </span><span><span>overtreatment</span></span><span>. Additional studies are needed to investigate if other factors are associated with the decision to treat.</span></p>
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