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106 results for “Bacteroides”
Polysaccharide utilization loci in Bacteroides determine population fitness and community-level interactions
<p>Polysaccharide utilization loci (PULs) in the human gut microbiome have critical roles in shaping human health and ecological dynamics. We develop a CRISPR-FnCpf1-RecT genome-editing tool to study 23 PULs in the highly abundant species <em>B. uniformis</em> (BU). We identify the glycan-degrading functions of multiple PULs and elucidate transcriptional coordination between PULs that enables the population to adapt to the loss of PULs. Exploiting a pooled BU mutant barcoding strategy, we demonstrate that the <em>in vitro</em> fitness and the colonization ability of BU in the murine gut is enhanced by deletion of specific PULs and modulated by glycan availability. We show that BU PULs can mediate complex glycan-dependent interactions with butyrate producers that depend on the mechanism of degradation and the butyrate producer glycan utilizing ability. In sum, PULs are major determinants of community dynamics and butyrate production and can provide a selective advantage or disadvantage depending on the nutritional landscape. </p>
Chemoproteomic identification of a DPP4 homolog in Bacteroides thetaiotaomicron
<p>Serine hydrolases play important roles in signaling and human metabolism, yet little is known about their functions in gut commensal bacteria. Using bioinformatics and chemoproteomics, we identify serine hydrolases in the gut commensal <em>Bacteroides thetaiotaomicron</em> that are specific to the Bacteroidetes phylum. Two are predicted homologs of the human protease dipeptidyl peptidase 4 (hDPP4), a key enzyme that regulates insulin signaling. Functional studies reveal that BT4193 is a true homolog of hDPP4 that can be inhibited by FDA-approved type 2 diabetes medications targeting hDPP4, while the other is a misannotated proline-specific triaminopeptidase. We demonstrate that BT4193 is important for envelope integrity and that loss of BT4193 reduces <em>B. thetaiotaomicron</em> fitness during <em>in vitro</em> growth within a diverse community. However, neither function is dependent on BT4193 proteolytic activity, suggesting a scaffolding or signaling function for this bacterial protease.</p>
A Conserved Inhibitory Interdomain Interaction Regulates DNA-binding Activities of Hybrid Two-component Systems in Bacteroides
<p>The study reveals a highly conserved inhibitory mechanism to regulate the activities of hybrid two-component systems (HTCSs) in <em>Bacteroides</em>. HTCSs comprise a major class of transcription regulators of polysaccharide utilization genes in <em>Bacteroides</em>. A conserved sequence motif has been discovered to correlate with the interdomain arrangement of HTCS domains. Presence or absence of this motif is likely predictive of the regulatory mechanism evolved for utilization of different glycans.</p> <p> </p> <p>This dataset includes sequence analyses and structure predictions of HTCSs.</p> <p>List of files:</p> <p>· AlphaFold-HTCS-RR.zip AlphaFold results of all HTCS-RR fragments in <em>B. theta</em></p> <p>· AlphaFold-HTCS-cyto-dimer.zip AlphaFold results of all HTCS-cyto dimers in <em>B. theta</em></p> <p>· HTCSbacteroides-MAFFT-fasta Sequence alignment of 6908 HTCSs from <em>Bacteroides</em></p> <p>· HMM-AllHTCS.hmm HMM of HTCSs generated from the MAFFT alignment</p> <p>· HMM-DBD-PF12833 HMM of HTH18 (Pfam: PF12833) from Interpro</p> <p>· HMM-REC-PF00072 HMM of REC (Pfam: PF00072) from Interpro</p> <p>· B_theta_RR_fasta Sequence alignment of 32 HTCS-RRs in <em>B. theta</em></p> <p>· B_theta_RR-tree A neighbor-joining phylogenetic tree of 32 HTCS-RRs in <em>B. theta</em> </p>
Multicolor flow cytometry of monocultures and co-cultures of Bacteroides species
<p>Dataset of FCS (Flow Cytometry Standard) files, along with meta-data, related to a flow cytometry analysis of monocultures and co-cultures of <em>Bacteroides </em>species under several different conditions. </p> <p><strong>Data Collection. </strong>This<strong> </strong>dataset accompanies a journal artcle which was published in <em>Frontiers in Microbiology</em> (<a href="https://doi.org/10.3389/fmicb.2022.910390">https://doi.org/10.3389/fmicb.2022.910390</a>). The "Methods and Materials" section in this article fully describes the biological nature of these samples and how the samples were processed for flow analysis and analyzed with flow cytometry. </p> <p><strong>Data Organization. </strong>Dataset includes 1832 samples. See mapping.xlsx and mapping_key.xlsx for list of samples and their meta-data. Folders are formatted as {run_data}_{time_point} and contains only samples belonging to either a run performed on 2018/07/17 or 2018/07/21 for time points of either 0, 24, 48, 72, or 102 hours. </p> <p><strong>Data Analysis. </strong>Code used for manipulating and analyzing these samples is publicly available (<a href="https://github.com/firasmidani/BacteroidesFlowCytometry">https://github.com/firasmidani/BacteroidesFlowCytometry</a>).</p> <p><strong>Data Integrity</strong>. "hardac-hashes.txt" stores the MD5 hashes of the original folders created by the authors prior to uploading data to Zenodo.</p>
Construction and characterization of a genome-scale ordered mutant collection of Bacteroides thetaiotaomicron
<p>Ordered transposon-insertion collections, in which specific transposon-insertion mutants are stored as monocultures in a genome-scale collection, represent a promising tool for genetic dissection of human gut microbiota members. However, publicly available collections are scarce and the construction methodology remains in the early stages of development. This dataset contains the raw data associated with the statistics and figures reported in an accompanying paper which describes the assembly of a genome-scale ordered collection of transposon-insertion mutants in the model gut anaerobe <em>Bacteroides</em> <em>thetaiotaomicron</em> VPI-5482 that we created as a resource for the research community.</p>
Construction and characterization of a genome-scale ordered mutant collection of Bacteroides thetaiotaomicron
Open the record for dataset details and reuse information.
Data from: Fusobacterium nucleatum and Bacteroides fragilis detection in colorectal tumours: optimal target site and correlation with total bacterial load
<p>These data were generated to investigate detection of <em>Fusobacterium nucleatum </em>(<em>F. nucleatum</em>) and <em>Bacteroides fragilis</em> (<em>B. fragili</em>s) across different regions of human colorectal tumours. Relative abundance of each species in DNA extracted for clinical molecular mutation testing from formalin-fixed, paraffin-embedded (FFPE) tumour samples from 42 patients was assessed using targeted real-time PCR quantitative (qPCR) (the screening cohort). DNA was then freshly extracted from specific regions of tumours testing positive for one or both species (n = 20) and from 31 additional patients, and relative abundance of each species assessed using qPCR (site investigation cohort). Total bacterial load at the tumour luminal surface (where <em>F. nucleatum</em> and <em>B. fragilis</em> were most frequently detected) was also assessed by qPCR using primers targeting amplification of 16S rRNA. 16S sequencing was performed on tumour luminal surface DNA samples from five patients as an orthogonal method to confirm the ability to detect the targeted species by qPCR.</p>
Supplemental information for "Single-Molecule Dynamics of Surface Lipoproteins in Bacteroides Indicate Similarities and Cooperativity"
<p>Supplemental Movies 1 - 3</p> <p><strong>SI Movie S1 - Representative movie of SusG-HT dynamics in <em>Bt</em> cells grown in amylopectin.</strong> The <em>Bt</em> cell outlines (white) are determined from the corresponding phase-contrast image. The single-molecule localization fits (circles) and corresponding trajectories (lines) are overlaid with the same colors as in Figure 1c. Below the scale bar is the date of the experiment, the movie number, the number of the photo-activation pulse that the sequence follows (in parentheses), and the frame number. These indicators are displayed in green during the imaging frames and in red during the photo-activation pulse. Scale bar: 1 µm; imaging rate: 20 ms/frame.</p> <p><strong>SI Movie S2 - Representative movie of SusG-HT dynamics in <em>Bt</em> cells grown in maltose.</strong> The <em>Bt</em> cell outlines (white) are determined from the corresponding phase-contrast image. The single-molecule localization fits (circles) and corresponding trajectories (lines) are overlaid with the same colors as in Figure 1c. Below the scale bar is the date of the experiment, the movie number, the number of the photo-activation pulse that the sequence follows (in parentheses), and the frame number. These indicators are displayed in green during the imaging frames and in red during the photo-activation pulse. Scale bar: 1 µm; imaging rate: 20 ms/frame.</p> <p><strong>SI Movie S3 - Representative movie of SusG-HT dynamics in <em>Bt</em> cells grown in glucose.</strong> The <em>Bt</em> cell outlines (white) are determined from the corresponding phase-contrast image. The single-molecule localization fits (circles) and corresponding trajectories (lines) are overlaid with the same colors as in Figure 1c. Below the scale bar is the date of the experiment, the movie number, the number of the photo-activation pulse that the sequence follows (in parentheses), and the frame number. These indicators are displayed in green during the imaging frames and in red during the photo-activation pulse. Scale bar: 1 µm; imaging rate: 20 ms/frame.</p>
RNA-seq Data for Bacteroides fragilis Toxin Suppresses METTL3-Mediated m6A Modification in Macrophage to Promote Inflammatory Bowel Disease
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Genome assemblies of Bacteroides fragilis CCUG4856T(=ATCC25285=NCTC9343)
<p>Supplementary material for the manuscript <em>Insights from complete, circular genome assembly and plasmid identification of six clinical multidrug resistant Bacteroides fragilis isolates.</em></p> <p>141 genome assemblies of Bacteroides fragilis CCUG4856T(=ATCC25285=NCTC9343) using Illumina and Oxford Nanopore data with the following assemblers and polishing tools</p> <p>Wtdbg2 v2.3 (<a href="https://github.com/ruanjue/wtdbg2">https://github.com/ruanjue/wtdbg2</a>)</p> <p>Miniasm v0.3r179 (<a href="https://github.com/lh3/miniasm">https://github.com/lh3/miniasm</a>)</p> <p>Flye v2.3.7 (<a href="https://github.com/fenderglass/Flye">https://github.com/fenderglass/Flye</a>)</p> <p>Canu v1.8 (<a href="https://github.com/marbl/canu">https://github.com/marbl/canu</a>)</p> <p>Spades (including Hybridspades) v3.13.0 (<a href="https://github.com/ablab/spades">https://github.com/ablab/spades</a>)</p> <p>Skesa v2.3.0 (<a href="https://github.com/ncbi/SKESA">https://github.com/ncbi/SKESA</a>)</p> <p>Unicycler v0.4.7 (<a href="https://github.com/rrwick/Unicycler">https://github.com/rrwick/Unicycler</a>)</p> <p>Nanopolish v0.10.2 (<a href="https://github.com/jts/nanopolish">https://github.com/jts/nanopolish</a>)</p> <p>Racon v1.3.1 (<a href="https://github.com/isovic/racon">https://github.com/isovic/racon</a>)</p> <p>Pilon v1.22 (<a href="https://github.com/broadinstitute/pilon">https://github.com/broadinstitute/pilon</a>)</p> <p> </p> <p>Methods and source code are available in the manuscript and at <a href="https://github.com/thsyd/bfassembly">https://github.com/thsyd/bfassembly</a></p>
States of genome assembly supporting data for complete genome assembly of clinical multidrug resistant Bacteroides fragilis isolates enables comprehensive identification of antimicrobial resistance genes and plasmids.
<p>Assemblies for each isolate and assembly stage is in .gfa and .fasta format.</p> <p>the best SPAdes assembly is also included in the .zip files.</p> <p>1) Unicycler with illumina data and Nanopore data from the first sequencing run, filtered with FiltLong.<br> 2) Unicycler with illumina data and Nanopore data from the first sequencing run, filtered with FiltLong and error corrected with Canu<br> 3) Unicycler with illumina data and Nanopore data from the first and second sequencing run, filtered with FiltLong.<br> 4) manual finshing of assembly 3. <br> Methods are described in the paper and at the github repository (https://github.com/thsyd/bfassembly)</p> <p> </p>
Roving methyltransferases generate a mosaic epigenetic landscape and influence evolution in Bacteroides fragilis group
<p>This repository contains code and the data for reproducing results and figures in the associated manuscript:</p> <p>Roving methyltransferases generate a mosaic epigenetic landscape and influence evolution in Bacteroides fragilis group</p> <p> </p> <p><strong>BFG-Analysis-main/ </strong>includes scripts and data to process Nanopore and Illumina reads, assemble BFG genomes, polish those genomes, and correct out-of-frame ORFs for MLST alignment. This also includes GenBank reference genomes referred to in the manuscript.</p> <p><strong>tree_files/ </strong>includes pylogenetic tree files and aligned sequence files used in Figures 1, 5, and 6</p> <p><strong>acessory_regions/ </strong>includes a .fasta file of accessory regions in each genome from the study in which it was possible to calculate this (using Ppanggolin/panRGP)</p> <p><strong>genomes/ </strong>contains different versions of BFG genomes with and without different types of polishing and frame-correction:</p> <ul> <li><strong>genomes/pacbio_uncorrected/</strong> contains genomes sequenced with PacBio and assembled with PacBio software <ul> <li>Analyzed for MLST trees in Figures: 1, 5, 6</li> <li>Analyzed in Figures: 5, 6, S7, S9 - S16</li> </ul> </li> <li><strong>genomes/nanopore_racon_medaka/</strong> contains genomes sequenced with Nanopore, assembled with Flye, then polished with racon and medaka. <ul> <li>Analyzed in Figures: 5, 6, S7, S9 - S16</li> </ul> </li> <li><strong>genomes/nanopore_racon_medaka_pilon/</strong> contains genomes sequenced with Nanopore, assembled with Flye, polished with racon and medaka, then polished with Illumina reads with pilon. <ul> <li>Analyzed in Figures: 5, 6, S7, S9 - S16</li> </ul> </li> <li><strong>genomes/proovframe_BFG_genomes/</strong> contains genomes from the<em> pacbio_uncorrected/, nanopore_racon_medaka/, and nanopore_racon_medaka_pilon/ </em>directories that were frame-corrected with Proovframe. <ul> <li>Analyzed for Figures: 2, 3, 4, S2, S3, S4, S5, S6, S8</li> </ul> </li> <li><strong>genomes/nanopore_MEGAN_corrected/</strong> contains genomes from the <em>nanopore_racon_medaka/ and nanopore_racon_medaka_pilon/ </em>directories that were frame-corrected with MEGAN <ul> <li>Analyzed for MLST trees in Figures: 1, 5, 6</li> </ul> </li> </ul> <p><strong>nanodisco_difference_files/</strong> contains Nanodisco intermediate files reporting the difference in nanopore signal between native and PCR-generated gDNA at each genomic position. They refer to the genomes in directories <strong>genomes/nanopore_racon_medaka_pilon/, genomes/nanopore_racon_medaka/, genomes/pacbio_uncorrected/</strong>. Each isolate has a genome in only one of these directories.</p> <p><strong>acessory_regions/ </strong>has a .fasta file of accessory sequences (per methods in manuscript) of relevant genomes.</p> <p> </p>
Bacteroides cellulosilyticus-directed glycans relieve colitis
<p>Bacteroides cellulosilyticus correlates with inflammatory bowel disease (IBD). Targeting an increase in abundance of B. cellulosilyticus is a feasible approach to treating IBD. Although B. cellulosilyticus is responsive to dietary components, untargeted manipulation cannot focus on target microbe and can lead to an increase in harmful bacteria in the microbiota. Despite breakthroughs in methods for regulating specific microbes, the protocols are expensive, time-consuming, and difficult to follow. Glycans based on microbial-carbohydrate-active enzymes (CAZymes) that target a specific microbiota would provide a potential solution.</p>
Dataset for BtuB TonB-dependent transporters and BtuG surface lipoproteins form stable complexes for vitamin B12 uptake in gut Bacteroides.
<p>The dataset published here supports the work in the publication titled "BtuB TonB-dependent transporters and BtuG surface<br> lipoproteins form stable complexes for vitamin B12 uptake in gut Bacteroides." All the initial and final conformation files of the MD simulations are given along with the analyzed data presented in the manuscript.</p>
Study of Bacteroides Thetaiotaomicron in Young People Aged 16 to 18 Years With Stable Crohn's Disease
ClinicalTrials.gov study NCT02704728. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Fusobacterium nucleatum and Bacteroides fragilis detection in colorectal tumours: optimal target site and correlation with total bacterial load
Open the record for dataset details and reuse information.
scRNA-seq data for "Bacteroides fragilis toxin suppresses METTL3-Mediated m6A modification in macrophage to promote inflammatory bowel disease"
Open the record for dataset details and reuse information.
Stockholm sequence-structure alignments for 9 Bacteroides sRNAs
<p>Sequence alignment supporting the manuscript "Comparative genomics provides structural and functional insights into Bacteroides RNA biology".</p>
Nanodisco Files for Roving methyltransferases generate a mosaic epigenetic landscape and influence evolution in Bacteroides fragilis group
<p>This repository contains the data for reproducing results and figures in the associated manuscript:</p> <p>Roving methyltransferases generate a mosaic epigenetic landscape and influence evolution in Bacteroides fragilis group</p> <p>Specifically, these R data structures map to genome assemblies from this study, summarizing the difference in current disturbance between native and PCR-amplified genomic DNA through a nanopore.</p> <p>See https://doi.org/10.5281/zenodo.7407113 for corresponding genomes in sub-directories <strong>genomes/pacbio_uncorrected/, genomes/nanopore_racon_medaka/, genomes/nanopore_racon_medaka_pilon/.</strong></p>
Effects of Diet on Resource Utilization by a Model Human Gut Microbiota Containing Bacteroides cellulosilyticus WH2, a Symbiont with an Extensive Glycobiome
GEO Series GSE48537. Dorea longicatena DSM 13814; [Clostridium] scindens ATCC 35704; Faecalibacterium prausnitzii M21/2; Collinsella aerofaciens ATCC 25986; Thomasclavelia spiroformis DSM 1552; Bacteroides thetaiotaomicron VPI-5482; Blautia obeum ATCC 29174; [Ruminococcus] torques ATCC 27756; Bacteroides caccae ATCC 43185; Agathobacter rectalis ATCC 33656; Bacteria; Bacteroides ovatus ATCC 8483; Bacteroides uniformis ATCC 8492; Phocaeicola vulgatus ATCC 8482; Parabacteroides distasonis ATCC 8503; Bacteroides cellulosilyticus; Bacteroides sp. WH2. 895 samples. Type: Expression profiling by high throughput sequencing; Other; Expression profiling by array.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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