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1,108 results for “metabolome”
Data from: Metabolomic and transcriptomic responses of ticks during recovery from cold shock reveal mechanisms of survival
<p>Ticks are blood-feeding ectoparasites but spend most of their life off-host where they may have to tolerate low winter temperatures. Rapid cold-hardening (RCH) is a process commonly used by arthropods, including ticks, to improve survival of acute low temperature exposure. However, little is known about the underlying mechanisms in ticks associated with RCH, cold shock, and recovery from these stresses. In the present study, we investigated the extent to which RCH influences gene expression and metabolism during recovery from cold stress in Dermacentor variabilis, the American dog tick, using a combined transcriptomics and metabolomics approach. Following recovery from RCH, 1,860 genes were differentially expressed in ticks, whereas only 99 genes responded during recovery to direct cold shock. Recovery from RCH resulted in an upregulation of various pathways associated with ion binding, transport, metabolism, and cellular structures seen in the response of other arthropods to cold. The accumulation of various metabolites, including several amino acids and betaine, corresponded to transcriptional shifts in the pathways associated with these molecules, suggesting congruent metabolome and transcriptome changes. Ticks receiving exogenous betaine and valine demonstrated enhanced cold tolerance, suggesting cryoprotective effects of these metabolites. Overall, many of the responses during recovery from cold shock in ticks were similar to those observed in other arthropods, but several adjustments may be distinct from other currently examined taxa.</p>
Supplemental Analysis of metabolomics data for the lipidome of fat body and heart HS fed W118 or CG4625 RNAi flies
<p>Full metabolomics of normalized peak height for fat body tissue from w1118 background and <em>CG4625</em> knockdown (via RNAi) flies fed a high-sugar diet for three weeks.</p>
Complementary hepatic metabolomics and proteomics reveal the adaptive mechanisms of dairy cows to the transition period
<p>Gas chromatography quadrupole-time-of-flight mass spectrometry-based metabolomics and data-independent acquisition-based quantitative proteomics methods were used to analyze liver tissues collected from eight healthy multiparous Holstein dairy cows on 21 days before and after calving.</p>
Supplement DataLongitudinal metabolomics and lipidomics analyses reveal markers of envenoming by Bothrops asper and Daboia russelii in an experimental murine model
<p>Longitudinal metablolomic and lipidomics analyses were carried out on the blood plasma of mice injected with venoms of the viperid species Northrop's asper and Daboia russelii.</p>
Supplementary Data for the Project Multiomics and quantitative modelling disentangle diet, host, and microbiota contributions to the host metabolome
<p><strong>Supplementary Tables for the Project "Multiomics and quantitative modelling disentangle diet, host, and microbiota contributions to the host metabolome"</strong></p> <p>Supplementary Table 1. List of 18 genome-sequenced human gut bacteria with metabolic characteristics that were used for community assembly.</p> <p>Supplementary Table 2. Diet composition.</p> <p>Supplementary Table 3. Species relative abundance.</p> <p>Supplementary Table 4. Gene abundance and expression changes.</p> <p>Supplementary Table 5. Gene pathway enrichment results.</p> <p>Supplementary Table 6. Metabolomics data.</p> <p>Supplementary Table 7. Metabolite fold changes, clustering and model parameters.</p> <p>Supplementary Table 8. Description of the intestinal flux model.</p> <p>Supplementary Table 9. Enzymatic paths between substrates and products.</p> <p>Supplementary Table 10. Pearson's correlation coefficients between potential substrates and products, and metagenomics and metatranscriptomic measurements.</p>
Information of indentified metabolites in metabolomic analysis and summary of the major mass-spectrometry-based studies performed on the syphilis patients or neurosyphilis patients to date
<p>Supplementary Table S1. Information of indentified metabolites in metabolomic analysis. <br> Supplementary Table S2. Summary of the major mass-spectrometry-based studies performed on the syphilis patients or neurosyphilis patients to date. Table includes details about the numbers of sample, the analysis method, and the type of mass spectrometer used and biomarkers identified in previous study.eng</p>
Supporting information: VISA Metabolomics Profiling Metadata
<p> Metadata for metabolomics profiling of vancomycin-intermediate S. aureus (VISA) strains: Mu50Ω (VSSA), Mu50Ω-<em>vraS</em>m (VISA) and Mu50Ω-<em>vraS</em>m-<em>graR</em>m (VISA)</p>
Spatial metabolomics reveal upregulation of several pyrophosphate-producing pathways in cortical bone of Hyp mice
<p>Imaging mass spectrometry data (.imzML format) from bones of <em>Hyp </em>(hypophosphatemia) mice and wild-type controls. Detailed information is given in the publication by Buck & Prade et al. "Spatial metabolomics reveal upregulation of several pyrophosphate-producing pathways in cortical bone of <em>Hyp</em> mice" in JCI Insight.</p>
Data from: Metabolomic profiling reveals shifts in defenses of an invasive plant
<p><strong>Abstract</strong>. The Shifting Defense Hypothesis predicts that introduced exotic plants evolve increased defenses against generalist herbivores and decreased defenses against specialists that are often absent in the introduced range. This hypothesis has received mixed evidence, and there is limited insight in its chemical basis from targeted analysis. Here, we provide an untargeted metabolomic analysis of native and invasive Purple Loosestrife populations and we experimentally test if admixture between introduced populations provides a basis for rapid defense chemistry evolution. Invasive populations showed improved growth and generalist herbivore resistance, but lower resistance to a specialist weevil. Metabolomic profiling revealed large shifts in chemistry between native and invasive populations, including differences in alkaloids and flavonoids. Experimental admixture increased chemical diversity and plant growth in the native populations, indicating its potential to fuel rapid evolution, but admixture did not affect generalist and specialist herbivory. Our comprehensive untargeted metabolomics results provide strong support for the Shifting Defense Hypothesis.</p> <p> </p> <p><strong>Data sets description:</strong></p> <p> </p> <ul> <li>Metabolite data: <strong>LCMS_pos.xlsx</strong> and <strong>LCMS_neg.xlsx</strong></li> </ul> <p>Metabolites were extracted from the 3rd to 4th pairs of leaves (from top to bottom) of experimental <em>Lythrum salicaria</em> plants, which originated from three regions in Europe and three regions in North America, and were analyzed by LC-MS. Electrospray ionization was carried in in positive mode (LCMS_pos.xlsx) and in negative mode (LCMS_neg.xlsx). The LC-MS profiles were analyzed by software SIMCA v13.0, and the number of metabolites and their unique compounds were also classified and analyzed. The data sets show retention times and mass-over-charge ratios (in rows) organized by individual plant samples (in columns). Plant samples were analyzed in four batches (two each for positive and negative mode), and are labeled by their population of origin and cross type:</p> <p>IALS: Iowa – Little South Storm Lake</p> <p>IML: Idaho – Middleton</p> <p>NJS1: New Jersey – Site 1</p> <p>NW: Netherlands – Wageningen</p> <p>PG: Potsdam – Geltow</p> <p>TR: Tübingen – Reusten</p> <p>Intra: sample from intra-population cross</p> <p>Pop: sample from cross between populations from the same region</p> <p>Reg: sample from cross between populations from different regions</p> <p> </p> <ul> <li>Herbivory and plant trait data: <strong>Phenotypes.xlsx</strong></li> </ul> <p>The plant height, main stem width, generalist and specialist feeding results of <em>L. salicaria</em> plants used in the experiments. Data are from individual plants, which are characterized by origin (North America or Europe), Region (three regions per origin), Sample site (three sites per region) and cross type (experimental plant derived from either ‘intrapop’ cross (cross within sample site) or ‘interregion’ cross (cross between sample sites from different regions)).</p> <p>Height: plant height in cm</p> <p>Diameter: main stem diameter in mm</p> <p>Specialist: number of holes eaten on the tested leaf</p> <p>Generalist: total leaf surface area consumed by herboivores (cm2)</p>
Met4DX: A mass spectrum-oriented computational framework for ion mobility-resolved untargeted metabolomics
<p><strong>Raw LC-IM-MS data</strong> to run Met4DX and <strong>RT recalibration table</strong> for multi-dimensional match</p> <p>Each dataset was archieved into a zip, containing raw LC-IM-MS data (.d format) and corresponding RT recalibration table (.csv format).</p>
VISA metabolomics: supporting tables and figures
<p><strong>Supporting information for the manuscript "Metabolic profiling reveals importance of arginine metabolism via arginine deiminase pathway in vancomycin-intermediate S. aureus"</strong></p> <p><strong>Figure S1:</strong> Stepwise transformation of VISA from VSSA in Mu50 lineage through VraSR and GraSR regulons.</p> <p><strong>Figure S2:</strong> Distribution of QCs in PCA score plot</p> <p><strong>Figure S3:</strong> Distribution of samples in PCA score plot</p> <p><strong>Figure S4:</strong> PLS-DA of samples</p> <p><strong>Table S1:</strong> Number of total, significantly different and annotated MFs</p> <p><strong>Table S2:</strong> Pathway analysis.</p>
Proteomic and Metabolomic Profiling of Plasma Predict Immune-related Adverse Events in Older Patients with Advanced Non-small Cell Lung Cancer
Open the record for dataset details and reuse information.
Labile Carbon Triggers Microbial Priming of Deep Peat Carbon Breakdown Unveiled by Coupled DNA SIP-Metabolomics : NMR raw data
<p>METHODS:</p> <p>180 µL of each DOM sample (two depths, 3 treatments (control, labeled glucose, unlabeled glucose,) and 6 times points (7, 14, 28, 42, 56, and 70 days); n=36) were combined with 2,2-dimethyl-2-silapentane- 5-sulfonate-d6 (DSS-d6) in D2O (20 µL, 5 mM) and thoroughly mixed prior to transfer to 3mm NMR tubes. NMR spectra were acquired on a Varian 600 MHz VNMRS spectrometer equipped with a 5-mm triple-resonance (HCN) cold probe at a regulated temperature of 298K. The 90° 1H pulse was calibrated prior to the measurement of each sample. The one-dimensional (1D) 1H spectra were acquired using a nuclear Overhauser effect spectroscopy (NOESY) pulse sequence with a spectral width of 12 ppm and 512 transients. The NOESY mixing time was 100ms, and the acquisition time was 4s, followed by a relaxation delay of 1.5s during which pre-saturation of the water signal was applied. Time-domain free induction decays (57,472 total points) were zero filled to 131,072 total points prior to Fourier transform. Chemical shifts were referenced to the 1H methyl signal in DSS-d6 at 0 ppm. The 1D 1H spectra were manually processed, assigned metabolite identification, and quantified using Chenomx NMR Suite 8.3. Metabolite identification was based on matching the chemical shift, J-coupling, and the intensity of experimental signals to compound signals in the Chenomx and custom in-house databases. Quantification was based on fitted metabolite signals relative to the internal standard (DSS-d6). Signal-to-noise ratios (S/N) were measured using MestReNova 14 with the limit of quantification equal to an S/N of 10 and the limit of detection equal to an S/N of 3. 13C labeling was assessed by 13C satellite analysis from the 1D spectra described above or from a 1D-(13C-edited) HSQC experiment. In several cases further corroboration of metabolite identity was made using standard 2-D experiments such as 1H / 13C - heteronuclear correlation (HSQC) experiments or 2-D 1H/ 1H Total Correlation spectroscopy (TOCSY).</p> <p> </p> <p>FUNDING:</p> <p>This research was supported by U.S. Department of Energy Office of Science, Office of Biological and Environmental Research (BER), grant no. DE-SC0023297.</p>
Supplemental files associated with the the manuscript "Genetic screening and metabolomics identify glial adenosine metabolism as a therapeutic target in Parkinson's disease"
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LC-HRMS study of Arabidopsis root metabolome in wild-type Col-0 and npr1 mutant upon in vitro inoculation with Streptomyces sp. AgN23.
<p>This archive compiles datasets related to studies of <em>Streptomyces</em> sp. AgN23 interaction with <em>Arabidopsis thaliana</em>. Ultra-high-performance liquid chromatography-high-resolution MS (UHPLC-HRMS) analyses were performed on a Q Exactive Plus quadrupole (Orbitrap) mass spectrometer, equipped with a heated electrospray probe (HESI II) coupled to a U-HPLC Ultimate 3000 RSLC system (Thermo Fisher Scientific, Hemel Hempstead, United Kigdom). For each biological sample, the RAW file obtained in ESI+ and ESI- mode were retrieved from the Xcalibur version 4.4 software and are deposited in separate sub-folders termed "RawPos" and "RawNeg". Each folder contains all the data relative to the cohort comprising "Blank" samples (n=13), Quality Check samples (pool of all samples from the cohort) "QC" (n=8), Control Col-0 plant samples "Col0CTRL" (n=6), Col-0 plant inoculated with AgN23 samples "Col0AgN23WT" (n=6), Control npr1 plant samples"NPR1CTRL" (n=6), npr1 plant inoculated with AgN23 samples "NPR1AgN23WT" (n=6). The files belonging to Negative mode bare the "neg" suffix and those belonging to Positive mode "pos" suffix, i.e. "Col0AgN23WT1_neg" and Col0AgN23WT1_pos". The details regarding samples preparation, analytic parameters and mass spectrometry, statistical treatment and visualization of the data will be made available in the publication relating to this archive. </p>
FERMO 1.0.0 example dataset: metabolomics data from Planomonospora - data subset
<p>A subset of the <em>Planomonospora</em> dataset published under <a href="https://doi.org/10.1021/acs.jnatprod.0c00807" target="_blank" rel="noopener">Zdouc et al 2021</a> and available under <a href="https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?accession=MSV000085376">MSV000085376</a>. This subset encompasses strains from different phylogroups, all grown in the same medium. A medium blank is provided as well. This data is referenced in the <em>FERMO</em> 1.0.0 Documentation and made available for convenient access.</p>
Single and few cell analysis for correlative light microscopy, metabolomics, and targeted proteomics (Data)
<p>Combined data for the manuscript `Single and few cell analysis for correlative light microscopy, metabolomics, and targeted proteomics` for all manuscript and supplemental information figures.</p> <p>Every folder contains the raw data and Jupyter notebook (python) for graph creation.</p> <p>Images are not enclosed but are shown in the manuscript.</p> <p> </p>
Metabolome analyses of oncogene-induced senescent IMR-90 cells
<p><strong>Methods</strong></p> <p><strong>Cell culture</strong></p> <p>IMR-90 ER:Ras (H-RasG12V) cells were maintained in Dulbecco’s modified Eagle’s medium supplemented with 200 mM L-glutamine, 1 mM sodium pyruvate, 10% (v/v) heat-inactivated fetal bovine serum (FBS), and penicillin/streptomycin (P/S). To induce quiescence, IMR-90 ER:Ras cells were cultured in the above medium containing 0.1% FBS for 2 days. For oncogene-induced senescence, IMR-90 ER:Ras cells were treated with 100 nM 4-hydroxytamoxifen (4-OHT) for 6 days.</p> <p><strong>Metabolite extraction</strong></p> <p>Culture medium was aspirated from the dishes and the cells were washed twice with 5% mannitol solution (10 mL and 2 mL for the first and second washes, respectively). The cells were then treated with 800 µL of methanol and incubated at room temperature for 30 sec to suppress enzyme activity. Next, 550 µL of Milli-Q water containing internal standards (H3304-1002, Human Metabolome Technologies, Inc. (HMT), Tsuruoka, Yamagata, Japan) was added to the cell extract, followed by further incubation at room temperature for 30 sec. The cell extract was then centrifuged at 2,300 × <em>g</em> and 4ºC for 5 min, after which 700 µL of the supernatant was centrifugally filtered through a Millipore 5-kDa cut-off filter (UltrafreeMC-PLHCC, HMT) at 9,100 × <em>g</em> and 4ºC for 120 min to remove macromolecules. Subsequently, the filtrate was evaporated to dryness under vacuum and reconstituted in 50 µL of Milli-Q water for metabolome analysis at HMT.</p> <p><strong>Metabolome analysis</strong></p> <p>Metabolome analysis was conducted using HMT’s Basic Scan package, capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), and the previously described method <sup>1</sup>. Briefly, CE-TOFMS analysis was carried out using an Agilent CE capillary electrophoresis system equipped with an Agilent 6210 time-of-flight mass spectrometer (Agilent Technologies, Inc., Santa Clara, CA, USA). The systems were controlled by Agilent G2201AA ChemStation software version B.03.01 (Agilent Technologies) and connected by a fused silica capillary (50 μm internal diameter × 80 cm total length) containing commercial electrophoresis buffer (H3301-1001 and I3302-1023 for cation and anion analyses, respectively, HMT) as the electrolyte. The spectrometer scanned from m/z 50 to 1,000 and peaks were identified using MasterHands automatic integration software (Keio University, Tsuruoka, Yamagata, Japan) in order to obtain peak information, including m/z, peak area, and migration time (MT) <sup>2</sup>. Signal peaks corresponding to isotopomers, adduct ions, and other product ions corresponding to known metabolites were excluded, and the remaining peaks were annotated according to HMT’s metabolite database, based on their m/z values and MTs. The areas of the annotated peaks were then normalized to those for internal standards and the amounts of the samples in order to obtain the relative quantity for each metabolite. The absolute quantities of 110 primary metabolites were quantified on the basis of one-point calibrations using their respective standards.</p> <ol> <li>Ohashi, Y., Hirayama, A., Ishikawa, T., Nakamura, S., Shimizu, K., Ueno, Y., Tomita, M., and Soga, T. (2008). Depiction of metabolome changes in histidine-starved Escherichia coli by CE-TOFMS. Mol Biosyst <em>4</em>, 135–147. 10.1039/b714176a.</li> <li> <p>Sugimoto, M., Wong, D.T., Hirayama, A., Soga, T., and Tomita, M. (2010). Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles. Metabolomics <em>6</em>, 78–95. 10.1007/s11306-009-0178-y.</p> </li> </ol>
Datasets for the manuscript: "Metabolic disruption of zebrafish (Danio rerio) embryos by bisphenol A. An integrated metabolomic and transcriptomic approach"
<h1>Metabolomics datasets for the manuscript: Metabolic disruption of zebrafish (Danio rerio) embryos by bisphenol A. An integrated metabolomic and transcriptomic approach</h1> <h2><em>Instrumental conditions</em></h2> <p>LC-MS analyses were carried out using an Agilent Infinity 1200 series LC system coupled with an orthogonal G1385-44300 interface (Agilent Technologies, Waldbronn, Germany) to a 6220 oa-TOF LC/MS mass spectrometer (Agilent Technologies). LC control and separation data acquisition were performed using ChemStation software (Agilent Technologies) that was running in combination with the MassHunter workstation software (Agilent Technologies) for control and data acquisition of the TOF mass spectrometer. For the chromatographic separations, an HILIC TSK Gel Amide-80 column (250 mm length, 2.1 mm inner diameter and 5 μm particle size, Tosoh Bioscience, Tokyo, Japan) was used at 25 °C with gradient elution at a flow rate of 0.15 mL·min<sup>−1</sup>. Elution gradient was performed using solvent A (acetonitrile) and solvent B (5 mM of ammonium acetate adjusted to pH 5.5 with acetic acid) as follows: 0–8 min, linear gradient from 25 to 30% B; 8–12 min, from 30 to 60% B; 12–17 min, 60% B; 17–20 min, back linearly from 60% to 25% B; and from 20 to 27 min, 25% B. Solvents were degassed for 15 min by sonication before use. Sample injection was performed with an autosampler at 4 °C, and the injection volume was 5 μL. All samples (six replicates per treatment: control, 4.4 μM BPA, 8.8 μM BPA and 17.5 μM BPA) were randomly injected. Several blank samples and calibration standards were also randomly injected to further assess the stability of the instrument among runs.</p> <p>The TOF mass spectrometer operated both in positive and negative mode using the following parameters: capillary voltage 4000 V, drying gas temperature 350 °C, drying gas flow rate 8 L·min<sup>−1</sup>, nebulizer gas 32 psi, fragmentor voltage 150 V, skimmer voltage 65 V and OCT 1 RF Vpp voltage 300 V. Data were collected in profile mode at 1 spectrum/s (approximately 10 000 transients/spectrum) with an <em>m/z</em> range of 85–1000 working in the extended dynamic range mode (2 GHz) with the mass range set to standard.</p> <h2><em>List of files</em></h2> <h3>Negative ionization</h3> <ul> <li>Control x 12 samples - 6 x 2 replicates</li> <li>BPA 1 ppm x 12 samples - 6 x 2 replicates</li> <li>BPA 2 ppm x 12 samples - 6 x 2 replicates</li> <li>BPA 4 ppm x 12 samples - 6 x 2 replicates</li> </ul> <h3>Positive ionization</h3> <ul> <li>Control x 12 samples - 6 x 2 replicates</li> <li>BPA 1 ppm x 12 samples - 6 x 2 replicates</li> <li>BPA 2 ppm x 12 samples - 6 x 2 replicates</li> <li>BPA 4 ppm x 12 samples - 6 x 2 replicates</li> </ul>
Plasma metabolomic signatures for copy number variants and COVID-19 risk loci in Northern Finland Populations
<p>A MySQL database for metabolomic signatures for The Northern Finland Birth Cohorts, <strong>NFBC1966 </strong>and <strong>NFBC1986</strong>, a longitudinal research program based at the Medical Faculty, University of Oulu, Finland. This dataset is a supplement to the manuscript titlted "Plasma metabolomic signatures for copy number variants and COVID-19 risk loci in Northern Finland Populations"</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
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
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.