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opencc-by-4.0Dec 2019View details →

Effects of Lactobacillus plantarum Q180 on blood lipid levels and intestinal microbiota : a double-blind, randomized, placebo-controlled, parallel trial

<p>Probiotics can improve the intestinal environment by enhancing beneficial bacteria to potentially regulate lipid levels; however, the underlying mechanisms remain unclear. The aim of this study was to investigate the effect of <em>Lactobacillus plantarum</em> Q180 (LPQ180) on blood lipid levels and the intestinal microbiome environment from a clinical perspective. A double-blind, randomized, placebo-controlled study was conducted including 70 participants of both sexes, 20 years of age and older, with blood triacylglyceride (TG) levels below 200 mg/dL. Treatment with LPQ180 for 12 weeks significantly decreased LDL-cholesterol (<em>p</em> = 0.042) and apolipoprotein (Apo)B-100 (<em>p</em> = 0.003) levels, and decreased postprandial maximum concentrations (C<sub>max</sub>) and areas under the curve (AUC) of TG, chylomicron TG, ApoB-48, and ApoB-100. LPQ180 treatment significantly decreased total indole and phenol levels (<em>p</em> = 0.019). In addition, there was a negative correlation between baseline microbiota abundance and lipid marker change, which was negatively correlated with metabolites related to harmful bacteria. LPQ180 treatment may help prevent hypertriglyceridemia by improving fasting and postprandial blood lipid levels. In addition, LPQ180 effectively prevented the growth of harmful bacteria, particularly in subjects with higher baseline levels of harmful gut microbiota. Probiotics can improve the intestinal environment by enhancing beneficial bacteria to potentially regulate lipid levels; however, the underlying mechanisms remain unclear. The aim of this study was to investigate the effect of <em>Lactobacillus plantarum</em> Q180 (LPQ180) on blood lipid levels and the intestinal microbiome environment from a clinical perspective. A double-blind, randomized, placebo-controlled study was conducted including 70 participants of both sexes, 20 years of age and older, with blood triacylglyceride (TG) levels below 200 mg/dL. Treatment with LPQ180 for 12 weeks significantly decreased LDL-cholesterol (<em>p</em> = 0.042) and apolipoprotein (Apo)B-100 (<em>p</em> = 0.003) levels, and decreased postprandial maximum concentrations (C<sub>max</sub>) and areas under the curve (AUC) of TG, chylomicron TG, ApoB-48, and ApoB-100. LPQ180 treatment significantly decreased total indole and phenol levels (<em>p</em> = 0.019). In addition, there was a negative correlation between baseline microbiota abundance and lipid marker change, which was negatively correlated with metabolites related to harmful bacteria. LPQ180 treatment may help prevent hypertriglyceridemia by improving fasting and postprandial blood lipid levels. In addition, LPQ180 effectively prevented the growth of harmful bacteria, particularly in subjects with higher baseline levels of harmful gut microbiota.</p>

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Data from: Aquatic animals promote antibiotic resistance gene dissemination in water via conjugation: role of different regions within the zebra fish intestinal tract, and impact on fish intestinal microbiota

The aqueous environment is one of many reservoirs of antibiotic resistance genes (ARGs). Fish, as important aquatic animals which possess ideal intestinal niches for bacteria to grow and multiply, may ingest antibiotic resistance bacteria from aqueous environment. The fish gut would be a suitable environment for conjugal gene transfer including those encoding antibiotic resistance. However, little is known in relation to the impact of ingested ARGs or antibiotic resistance bacteria (ARB) on gut microbiota. Here, we applied the cultivation method, qPCR, nuclear molecular genetic marker and 16S rDNA amplicon sequencing technologies to develop a plasmid-mediated ARG transfer model of zebrafish. Furthermore, we aimed to investigate the dissemination of ARGs in microbial communities of zebrafish guts after donors carrying self-transferring plasmids that encode ARGs were introduced in aquaria. On average, 15% of faecal bacteria obtained ARGs through RP4-mediated conjugal transfer. The hindgut was the most important intestinal region supporting ARG dissemination, with concentrations of donor and transconjugant cells almost 25 times higher than those of other intestinal segments. Furthermore, in the hindgut where conjugal transfer occurred most actively, there was remarkable upregulation of the mRNA expression of the RP4 plasmid regulatory genes, trbBp and trfAp. Exogenous bacteria seem to alter bacterial communities by increasing Escherichia and Bacteroides species, while decreasing Aeromonas compared with control groups. We identified the composition of transconjugants and abundance of both cultivable and uncultivable bacteria (the latter accounted for 90.4%–97.2% of total transconjugants). Our study suggests that aquatic animal guts contribute to the spread of ARGs in water environments.

opencc-zeroDec 2016View details →

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Data from: Intestinal microbiota is influenced by gender and body mass index

Intestinal microbiota changes are associated with the development of obesity. However, studies in humans have generated conflicting results due to high inter-individual heterogeneity in terms of diet, age, and hormonal factors, and the largely unexplored influence of gender. In this work, we aimed to identify differential gut microbiota signatures associated with obesity, as a function of gender and changes in body mass index (BMI). Differences in the bacterial community structure were analyzed by 16S sequencing in 39 men and 36 post-menopausal women, who had similar dietary background, matched by age and stratified according to the BMI. We observed that the abundance of the Bacteroides genus was lower in men than in women (P<0.001, Q = 0.002) when BMI was > 33. In fact, the abundance of this genus decreased in men with an increase in BMI (P<0.001, Q<0.001). However, in women, it remained unchanged within the different ranges of BMI. We observed a higher presence of Veillonella (84.6% vs. 47.2%; X2 test P = 0.001, Q = 0.019) and Methanobrevibacter genera (84.6% vs. 47.2%; X2 test P = 0.002, Q = 0.026) in fecal samples in men compared to women. We also observed that the abundance of Bilophila was lower in men compared to women regardless of BMI (P = 0.002, Q = 0.041). Additionally, after correcting for age and sex, 66 bacterial taxa at the genus level were found to be associated with BMI and plasma lipids. Microbiota explained at P = 0.001, 31.17% variation in BMI, 29.04% in triglycerides, 33.70% in high-density lipoproteins, 46.86% in low-density lipoproteins, and 28.55% in total cholesterol. Our results suggest that gut microbiota may differ between men and women, and that these differences may be influenced by the grade of obesity. The divergence in gut microbiota observed between men and women might have a dominant role in the definition of gender differences in the prevalence of metabolic and intestinal inflammatory diseases.

opencc-zeroDec 2015View details →

opencc-zeroFeb 2024View details →

A catalog of genes, genomes and species of the dog (Canis lupus familiaris) intestinal microbiota

<p></p><h1>Data sources</h1><br>This dataset was constructed using metagenomic sequencing data from the bioproject PRJEB20308 from Coelho et al. 2018 (129 samples)<br><h1>Metagenomic assembly</h1><br>First, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (ROS_Cfam_1.0 GCF_014441545.1) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes. Contigs of less than 1500 bp were removed.<br><h1>MAGs recovery</h1><br>MAGs were generated with COMEBin (multi-coverage mode) and MAGs quality was assessed with CheckM2. MAGs with completeness < 70% or contamination > 5% or N50 < 5Kb were discarded. Pairwise Average Nucleotide Identity (ANI) was computed for all recovered MAGs with fastANI and dereplication at species level (ANI cutoff = 95%).<br><h1>Non-redundant gene catalog</h1><br>Genes were predicted on all contigs from metagenomic assemblies with Prodigal (parameters : -m -p meta). Genes were pooled and clustered with cd-hit-est (parameters -c 0.95 -aS 0.90 -G 0 -d 0 -M 0 -T 0) by choosing those from the longest contigs as representatives.<br><h1>MSPs recovery</h1><br>Reads were aligned against the non-redundant gene catalog with the Meteor software suite to produce a raw gene abundance table (1,0M genes quantified in 129 samples). Then, co-abundant genes were binned in 234 Metagenomic Species Pan-genomes (MSPs, i.e. gene clusters that likely belong to the same microbial species) using MSPminer.<br><h1>MAGs and MSPs taxonomic annotation</h1><br>Dereplicated MAGs were annotated with GTDB-Tk based on GTDB r220. Then, MAGs taxonomic annotation was propagated to the corresponding MSPs.<br><h1>Construction of the phylogenetic tree</h1><br>39 universal phylogenetic markers genes were extracted from the dereplicated MAGs with fetchMGs. Then, the markers were separately aligned with MUSCLE. The 40 alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni).<h1>Mapping rate distribution across public cohorts</h1>We generated mapping rate distribution plots using Meteor2 (default parameters), comparing performance between: PRJEB20308 (cohort used in catalogue assembly) and PRNJNA714112 (independent cohort not used in assembly).<p></p>

opencc-zeroDec 2020View details →

MIMIC2: Murine Intestinal Microbiota Integrated Catalog v2

<p></p><h1>Dataset overview</h1><br>The MIMIC2 dataset provides:<br>a non-redundant high-quality catalog of 5.0 million genes<br>6,967 Metagenome-Assembled Genomes (MAGs)<br>1,252 Metagenomic Species Pangenomes (MSPs)<br>This dataset can be used to analyze shotgun sequencing data of the murine gut microbiota.<br><h1>Methods</h1><br><h2>Data sources</h2><br>The MIMIC2 dataset was constructed using two different data sources:<br>Source 1: the Mouse Gastrointestinal Bacterial Catalogue (MGBC) which is a compilation of 276 genomes from cultured isolates and 45,218 metagenome-assembled genomes (MAGs) from 1,960 publicly available mouse metagenomes<br>Source 2: 68 samples of Messaoudene et al. (PRJNA783624) and 85 deeply sequenced samples from bioproject CNP0000619 published by Xiao et al.<br><h2>Metagenomic assembly</h2><br>De novo metagenomic assembly was performed on the 153 samples from the data Source 2. First, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes. Contigs of less than 1500 bp were removed.<br><h2>MAGs recovery</h2><br>Reads of each sample from the data Source 2 were aligned to their respective assembly with bowtie2 and results were indexed in sorted bam files with samtools. Then, contigs coverage was computed in each sample with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and MAGs quality was assessed with checkM. MAGs with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.<br><h2>Non-redundant gene catalog</h2><br>Genes were predicted on all contigs from the data Source 2 with Prodigal (parameters : -m -p meta ). Likewise, genes were predicted on all genomes from the data Source 1 (MGBC) with Prodigal (parameters : -m -p single ). Genes from the two data sources were pooled and those shorter than 90 bp or incomplete were discarded. Finally, genes were clustered with cd-hit-est (parameters -c 0.95 -aS 0.90 -G 0 -d 0 -M 0 -T 0 ) by choosing those from the longest contigs as representatives.<br><h2>MSPs recovery</h2><br>Samples from 19 cohorts (see below) were aligned against the non-redundant gene catalog with the Meteor software suite to produce a raw gene abundance table (5M genes quantified in 1374 samples). Then, co-abundant genes were binned in 1,252 Metagenomic Species Pan-genomes (MSPs, i.e. clusters of > 500 co-abundant genes that likely belong to the same microbial species) using MSPminer.<br><br>The 19 cohorts used to recover the MSPs are:<br>PRJNA783624<br>CNP0000619<br>PRJEB15095<br>PRJEB22007<br>PRJEB22710<br>PRJEB31298<br>PRJEB32790<br>PRJEB32890<br>PRJEB3374<br>PRJEB36943<br>PRJEB44286<br>PRJEB7759<br>PRJNA293255<br>PRJNA390686<br>PRJNA397886<br>PRJNA515074<br>PRJNA540893<br>PRJNA549182<br>PRJEB40719<br><h2>MSPs taxonomic annotation</h2><br>Representative genomes of the MMGC collection were annotated with GTDB-Tk based on GTDB r202. Then, taxonomic annotation of MMGC genomes was propagated to the corresponding MSPs.<br><br>For the MSPs without any corresponding MAG, taxonomic annotation was performed by alignment of all core and accessory genes against representative genomes of the GTDB database (release r202) using blastn (version 2.7.1, task = megablast, word_size = 16). A species-level assignment was given if > 50% of the genes matched the representative genome of a given species, with a mean nucleotide identity ≥ 95% and mean gene length coverage ≥ 90%. The remaining MSPs were assigned to a higher taxonomic level (genus to superkingdom), if more than 50% of their genes had the same annotation.<br><h2>Construction of the phylogenetic tree</h2><br>39 universal phylogenetic markers genes were extracted from the 1,252 MSPs (or the corresponding MAGs if available) with fetchMGs. Then, the markers were separately aligned with MUSCLE. The 40 alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni).<h1>Mapping rate distribution across public cohorts</h1>We generated mapping rate distribution plots using Meteor2 (default parameters), comparing performance between: CNP0000619, PRJEB15095, PRJEB22007, PRJNA783624 (cohort used in catalogue assembly) and PRJNA760892 (independent cohort not used in assembly).<p></p>

opencc-by-4.0Nov 2024View details →

IMPACT OF TEBIPENEM-PIVOXIL ON THE INTESTINAL MICROBIOTA AND ON ESTABLISHMENT OF COLONIZATION WITH CARBAPENEM-RESISTANT KLEBSIELLA PNEUMONIAE IN MICE

<p><span>Antimicrobial therapy has the</span><span> potential to cause unintended adverse effects by promoting antibiotic-resistant bacteria. Therefore, as new antibiotics are developed there is a need to understand their potential to disrupt the indigenous microbiota of the colon and promote colonization by pathogens. Tebipenem pivoxil (Teb-piv), the first oral carbapenem, has potent <em>in vitro</em> activity against <em>Enterobacterales</em> pathogens, but requires combination with an appropriate β-lactamase inhibitor to achieve activity against <em>Klebsiella pneumoniae</em> carbapenemase and metallo-β-lactamase (MBL)-producing carbapenem-resistant <em>Enterobacterales</em></span></p>

opencc-by-4.0May 2022View details →

Crosstalk between imbalanced gut microbiota caused by antibiotics and rotavirus replication in the intestine

<p>In this manuscript, we discover that 10% of young adults are asymptomatic rotavirus infected. Imbalanced gut microbiota caused by veterinary antibiotics and preferred as veterinary antibiotics play an important role in this situation. High level of lipopolysaccharide produced by gram-negative bacteria promote rotavirus replication. Our results demonstrated that patients have a disrupted gut microbiota following rotavirus infection, and therefore may be at risk for long-term health complications. We believe that our findings widen the knowledge about the infection of rotavirus.</p>

opencc-by-4.0Jun 2021View details →

Dataset of intestinal microbiota in mice model of bronchopulmonary dysplasia

<p>This is a database of the gut microbiota of mice, mainly to compare the difference in gut microbiota between bronchopulmonary dysplasia mice and healthy mice. The "BPD" in the file name represents mice with bronchopulmonary dysplasia, "Control" represents normal mice, and "Day *" refers to the time to obtain the sample.</p>

opencc-by-4.0Aug 2023View details →

Ceftriaxone and Cefotaxime Have Similar Effects on the Intestinal Microbiota in Human Volunteers

<p><strong>Pour ce TP, nous allons déterminer l’impact d’un traitement à la ceftriaxone sur la flore intestinale (<a href="https://aac.asm.org/content/63/6/e02244-18.abstract">https://aac.asm.org/content/63/6/e02244-18.abstract</a>). 22 volontaires sains ont reçu par intraveineuse de la ceftriaxone (1g / 24 h) ou de la cefotaxime ( 1g / 8h) pendant 3 jours. Le consortium CEREMI a collecté des échantillons de selles de ces volontaires et réalisé une étude de métagénomique ciblée sur le gène 16S rRNA. En raison des limitations de vos machines, nous allons analyser les échantillons du groupe B uniquement à 2 temps: Jm1 (un jour avant le traitement) et J4</strong></p>

closedIPD-NOFeb 2026View details →

Rescue Fecal Microbiota Transplantation for National Refractory Intestinal Infections

ClinicalTrials.gov study NCT03895593. IPD Sharing: NO. Countries: 1. Publications: 8.

The Effect of Intestinal Microbiota Transplantation for Inflammatory Bowel Diseases

ClinicalTrials.gov study NCT03426683. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.

Impact of Consumption of Beta-glucans on the Intestinal Microbiota and Glucose and Lipid Metabolism

ClinicalTrials.gov study NCT02041104. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Impact of the Choice of 3rd Generation Cephalosporins on the Emergence of Resistance in the Microbiota Intestinal.

ClinicalTrials.gov study NCT02659033. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.

Evolution of Proteomic Profiles of Intestinal Microbiota in Patients With Locally Advanced or Metastatic Urothelial Carcinomas

ClinicalTrials.gov study NCT04566029. IPD Sharing: Not stated. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →

Establishment of the Human Intestinal and Salivary Microbiota Biobank - Kidney Diseases

ClinicalTrials.gov study NCT04689074. IPD Sharing: NO. Countries: 1. Publications: 5.

controlledIPD-YESFeb 2026View details →

Clinical Trial to Demonstrate the Effectiveness of Fecal Microbiota Transplantation for Selective Intestinal Decolonization of Patients Colonized by Carbapenemase-producing Klebsiella Pneumoniae

ClinicalTrials.gov study NCT04760665. IPD Sharing: YES. Countries: 1. Publications: 1.