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1,108 results for “Metabolomics”
Non-Targeted Metabolomics of a Phytoplankton Bloom in the California Current Ecosystem 1706
<p>Non-Targeted LC-MS/MS based Metabolomics of SPE (PPL) extracts of a Phytoplankton Bloom in the California Current Ecosystem 1706</p>
Spatiotemporal metabolome data from Bacillus subtilis swarm development
<p>Metabolome data and associated Matlab code used in the scientific article "Simultaneous spatiotemporal transcriptomics and microscopy of <em>Bacillus subtilis</em> swarm development reveal cooperation across generations" by the following authors: Hannah Jeckel*, Kazuki Nosho*, Konstantin Neuhaus, Alasdair D. Hastewell, Dominic J. Skinner, Dibya Saha, Niklas Netter, Nicole Paczia, Jörn Dunkel, Knut Drescher. The symbol "*" indicates an equal contribution.</p> <p>The Excel files AminoAcidResults.xslx and OrganicAcidResults.xlsx list raw data containing the positon and timepoints of sampling as well as metabolite concentrations given in µM. More details about these files are given in a ReadMe.txt file.</p> <p>The Excel file nSamples.xlsx summarizes the number of samples for each mean calculated during plotting.</p> <p>There are two m-files with Matlab code, which are used for plotting the metabolite data. To plot metabolite concentrations over time, open "displayData.m" and select the raw data file in lines 5 and 6. Then choose a path to save your data in line 9. Execute the Matlab script to obtain graphs.</p>
Metabolomic Profile of Cerebral Tissue After Blood-Brain Barrier Opening using Microbubble-Assisted Ultrasound: A Focus on Contralateral Side.
<p>Microbubble (MB)-assisted ultrasound (US) is an innovative modality for the non-invasive, targeted and efficient delivery of the therapeutic molecules into the brain. Previously, we reported the first metabolomic signature of blood-brain barrier opening (BBBO) induced by MB-assisted US. In the present study, the neurometabolic consequences of acoustically mediated BBBO on cerebral tissue using multimodal metabolomics approaches. Sinusoid US waves (1 MHz, peak negative pressure 0.6 MPa, burst length 10 ms, total treatment time 30 s, MB bolus dose 0.7 10<sup>5</sup> MBs/g) were applied on the right striatum (ipsilateral side). Brain was collected and both striata were then dissected 3 h, 2 days and 1 week after BBBO. After tissue preparation, the samples were analyzed using nuclear magnetic resonance spectrometry (NMRS) and high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS). Our findings showed a slight disruption of metabolic pathways in contralateral striata of animals. Analyses of metabolic pathways indicated change of amino acid metabolisms. In addition, tryptophan derivate dosages revealed the perturbation of a central metabolite of the kynurenin pathway (<em>i.e.</em>, 3-hydroxykynurenin). In conclusion, the acoustically mediated BBBO of the ipsilateral cerebral hemisphere induced significant change in metabolism of contralateral one.</p>
1H NMR based metabolomics from: <em>Citrus sinensis</em> leaves in response to Diaphorina citri infestation and Huanglongbing disease
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Part 2: Kiss and spit metabolomics highlight the role of host purine metabolism during pathogen infection
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Part 1: Kiss and spit metabolomics highlight the role of host purine metabolism during pathogen infection
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Proteomic and metabolomic analysis of COVID-19 nasal swabs
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Longitudinal analysis of the microbiome and metabolome in the 5xfAD mouse model of Alzheimer's disease
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Modulation of the Tomato Fruit Metabolome by LED Light (GCMS and LCMS datasets)
<p>Metabolic profiles of tomatoes change during ripening and light can modulate the activity of relevant biochemical pathways. We investigated the effects of light directly supplied to the fruits, on the metabolome of the fruit pericarp during ripening. Mature green tomatoes were exposed to well-controlled conditions with light as the only varying factor; control fruits were kept in darkness. In Experiment 1 the fruits were exposed to either white light or darkness for 15 days. In Experiment 2 fruits were exposed to different light spectra (blue, green, red, far-red, white) added to white background light for 7 days. Changes in the global metabolome of the fruit pericarp were monitored using LCMS and GCMS (554 compounds in total). Health-beneficial compounds (carotenoids, flavonoids, tocopherols and phenolic acids) accumulated faster under white light compared to darkness, while alkaloids and chlorophylls decreased faster. Light also changed the levels of taste-related metabolites including glutamate and malate. The light spectrum treatments indicated that the addition of blue light was the most effective treatment in altering the fruit metabolome. We conclude that light during ripening of tomatoes can have various effects on the metabolome and may help shaping the levels of key compounds involved in various fruit quality characteristics.</p>
Data from Nicolle et al. LC-HRMS study of Streptomyces sp. AgN23 Culture Media Extract. Study of AgN23 exometabolome and analysis of Arabidopsis metabolomic responses to the bacteria
<p>This archive compiles several datasets related to studies of <i>Streptomyces</i> sp. AgN23 interaction with <i>Arabidopsis thaliana</i>. 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 experimental cohort is grouped in a folder where the biological repeats can be retrieved, as well as QC (Quality Check, pool of all samples from the cohort), Blank samples and eventual alternative control such as Bennett, the mock control media of <i>Streptomyces</i> sp. AgN23. 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. The folder " AgN23-WT_AgN23-pSC004" contains chromatograms related to metabolomic study of Wild-type and pSC004-1, pSC004-10, pSC004-16 and pSC004-22 mutants of <i>Streptomyces</i> sp. AgN23. The folder " Col-0_AgN23" contains chromatograms related to metabolomic study of <i>Arabidopsis thaliana</i> Col-0 responses to colonization by <i>Streptomyces</i> sp. AgN23-WT. The folder " Col-0_pad3-1_AgN23" contains chromatograms related to metabolomic study of <i>Arabidopsis thaliana</i> Col-0 and the <i>Arabidopsis</i> pad3-1 mutant responses to colonization by <i>Streptomyces</i> sp. AgN23-WT. The folder " Col-0_pSC004" contains chromatograms related to metabolomic study of <i>Arabidopsis thaliana</i> Col-0 responses to colonization by <i>Streptomyces</i> sp. AgN23-WT and the AgN23 mutants pSC004-10 and pSC004-22. It should be noted that in the publication associated with this archive, the pSC004-1, pSC004-10, pSC004-16 and pSC004-22 mutants are referred to as ΔgbnB-1, ΔgbnB-2, ΔgbnB-3 and ΔgbnB-4, respectively.</p>
Metabolomic Expertiment_Exposition of M.tuberculosis to garlic essential oil
<p>The data contain the results of metabolomic exteriment. M. tuberculosis exposed to garlic essential oil in two doses: lower and higher. Levels of lipids were calculated in relation to control samples. Expression results were calculated in relation to reference standard.</p>
Metabolomics of KP mouse LUAD cell lines
<p>The goal of the experiment was to characterize the changes in metabolic pathway flux in these cells in response to HDAC and glutaminase inhibition. This dataset includes metabolomics of U-C13 glucose tracing (1h and 24h) and U-C13 glutamine (8h) of mouse LUAD cell lines with Kras overexpression and p53 knock-out (KP), carrying empty vector (EV) or overexpression of NRF2dNeh2 (NRF2) and treated with DMSO, Romidepsin or CB-839. 3 technical replicates were done per condition. The full methodology is described in the accompanying text file.</p>
Identifying biomarkers for chronic obstructive pulmonary disease in the salivary metabolome.
<p><strong><span>Background:</span></strong><span> The lack of specificity in spirometry and accuracy in ‘pre-disease states’, and elderly indicates the need for other accurate, inexpensive and non-invasive tests for diagnosis, triage severity and particularly for choosing and monitoring response to treatments in chronic obstructive pulmonary disease (COPD). We compared salivary metabolomic signatures from patients with COPD and controls across a range of severity of airflow obstruction. </span></p> <p><a name="_61k4y1plsv5"></a><strong><span>Methods</span></strong></p> <p><span>45 people with COPD (mean age 66.1 ± 23 years, forced expiratory volume [FEV<sub>1</sub>] 47<u>+</u>15% predicted) and 48 healthy controls (mean age 56.0 <u>+</u>16.2 years, FEV<sub>1</sub> 90<u>+</u>23 % predicted) provided saliva that was assessed by flow infusion electrospray mass spectrometry (FIE-MS). Spectra were interrogated using an online library package. Data (patient data and metabolomic outputs) are available from this site. </span></p> <p><a name="_j99pcjszp0an"></a><strong><span>Results</span></strong></p> <p><span>Four potential biomarkers identified the presence of COPD with a sensitivity of 73%, specificity of 72%.<span> </span>Six metabolites predicted FEV1 % in the COPD cohort (<em>P </em>< 0.001, R<sup>2</sup> > 0.3, AUC > 0.7) whilst a range of multivariate approaches targeted six metabolites linked to GOLD stage (<em>P </em>< 0.001, AUC > 0.7). Identification of the metabolites suggested changes in pterin biosynthesis, lipid processing, nucleotide metabolism and melatonin in COPD patients. </span></p> <p><a name="_2n4ucvxs4l1n"></a><strong><span>Conclusions</span></strong></p> <p><span>Metabolic fingerprinting of saliva samples could differentiate COPD from age matched controls and inform COPD severity of airflow obstruction. Potential biomarkers are suggested which could inform the diagnosis and monitoring of COPD.</span></p> <p><span> </span></p> <h2><span> </span></h2>
Analysis of Metabolomics Data to Assess Interactions in Microalgal Co-culture of Skeletonema marinoi and Prymnesium parvum
<p>This dataset refers to the metabolomics results from Metabolome Annotation QWorkflow on a co-culture of two microalgae: <em>Skeletonema marinoi </em>and <em>Prymnesium parvum</em>. The metabolomics data was acquired from endometabolome and exometabolome in both positive and negative MS modes. These will be referred as conditions. The files ms2_spectra_condition.mzML files have the MS2 combined from different MS2 files found on Zenodo with DOI: 10.5281/zenodo.10143233. The MS1 files are available on Zenodo as well with the DOI: 10.5281/zenodo.10143127</p> <p>The first section is about the results from the MS1 analysis. For the code used to generate these files, please refer to the code: <a href="https://github.com/zmahnoor14/MAW/tree/main/co-culture">https://github.com/zmahnoor14/MAW/tree/main/co-culture</a> </p> <ol> <li>Feature_info_condition.csv refers to the list of features with IDS, m/z, rt and intensity values. <ul> <li>The feature list is used to link the MS1 features to the features extracted from MS2 spectra.</li> </ul> </li> <li>Feature_list_condition.csv refers to the list of mzML origin file (samples) and the intensity of the features in those samples.</li> </ol> <p>The second section relates to the MS2 results. For source code please refer to: <a href="https://github.com/zmahnoor14/MAW/tree/main/Docker">https://github.com/zmahnoor14/MAW/tree/main/Docker</a></p> <ol> <li>SL_MAW_Coculture.csv contains list of metabolic features that were annotated and found to be present in the suspect list of either of the two organisms or both. The suspect lists for Skeletonema marinoi can be found at 10.5281/zenodo.5772755, and for Prymnesium parvum can be found at 10.5281/zenodo.7864506. </li> <li>unique_MAW_SMILES_coculture.csv file contains all information on unique SMILES.</li> <li>onlyDAF.csv contains differentially abundant features in either of the conditions: <em>S. marinoi </em>co-culture, <em>S. marinoi</em> mono-culture and similar conditions for <em>P. parvum</em>.</li> <li>condition_mergedResults-with-one-Candidates_sig_feat_for_only_inclusion.csv files contain all MS2 features and annotations together with the information on whether these features were found in the inclusion list (List provided for generating MS2 spectra in orbitrap), and whether these features were differential.</li> </ol>
Data from: Metabolomic profiles of acute and chronic ambient hydrogen sulfide exposure in a mouse model
<p>Hydrogen sulfide (H<sub>2</sub>S) is an environmental toxicant of health concern following acute or chronic human exposures. Male 6-8 week-old C57BL/6J mice were exposed by whole-body inhalation to 1000 ppm H<sub>2</sub>S for 45 min and euthanized at 5 min and 72 h for acute exposure. For subchronic study, mice were exposed to 5 ppm H<sub>2</sub>S 2 h/day, 5 days/week for 5 weeks. The brainstem was removed for metabolomic analysis. The metabolomics analyses consisted of three assays, (1) primary metabolism by GC-TOF MS, (2) biogenic amines (hydrophilic compounds) by HILIC-MS/MS and (3) lipidomics by RPLC-MS/MS. Metabolomics were performed in West Coast Metabolomics Center, University of California at Davis, CA, USA. 348, 311, and 565 known metabolites were detected and analyzed by primary metabolism, biogenic amines, and lipidomic metabolomics assays. 33, 19, and 46 metabolites were increased at 5 min and 72 h post acute H<sub>2</sub>S exposures and subchronic ambient H<sub>2</sub>S exposures, respectively, compared to room air control group. 22, 17, and 32 metabolites were decreased at 5 min and 72 h post acute H<sub>2</sub>S exposures and subchronic ambient H<sub>2</sub>S exposures, respectively, compared to room air control group. Acute H<sub>2</sub>S exposure decreased excitatory neurotransmitters aspartate and glutamate concentrations while the inhibitory neurotransmitter serotonin was increased. Glutamate and serotonin were also decreased after ambient H<sub>2</sub>S exposure. Branched-chain amino acids, fructose, and glucose were increased by acute H<sub>2</sub>S exposure. In ambient H<sub>2</sub>S exposure, glucose was decreased while MUFAs, PUFAs, inosine, and hypoxanthine were increased. Collectively, these results provide important mechanistic clues of acute and subchronic ambient H<sub>2</sub>S poisonings and show that H<sub>2</sub>S alters neurotransmission homeostasis.</p>
Tandem Mass Spectrometry Dataset for Machine Learning in Metabolomics
<p>This dataset contains tandem mass spectrometry data cleaned and processed from the publicly available GNPS Spectral Library. We aim to continuously update this dataset with new data points as the spectral libraries expand.</p>
Examples for running TraceGroomer: format and normalise your labeled metabolomics data for DIMet analysis
<p>Examples to test our tool <a href="https://github.com/cbib/TraceGroomer">TraceGroomer</a>, to prepare your files for DIMet (Differential analysis of Isotope-labeled Metabolomics data).</p> <p>Each example represents one type of input supported by TraceGroomer. Please download the entire .zip and find inside the example that best suits your case.</p> <p>The new version v2 contains four types of input:</p> <ol> <li>IsoCor .tsv generated file: <em>example-isocor_data</em></li> <li>The rule of "three .tsv files" , i.e. sampleMetadata, variableMetadata and dataMatrix: <em>example-ruletsv_data</em></li> <li>custom or generic .xlsx file: <em>example-sheet_data</em></li> <li>VIB MEC .xlsx file: <em>example-vib_data</em></li> </ol> <p>Visit the <a href="https://github.com/cbib/TraceGroomer/wiki">TraceGroomer Wiki page</a> for further information and how to run the tool on the provided examples. </p> <p><strong>For users of the Galaxy </strong>version of Tracegroomer: please only use the 'data/' folder (ignore the 'groom_files/' folder)</p>
Data from: Nutrient composition and functional constituents of daylily from different producing areas based on widely targeted metabolomics
<p>Daylily is a functional food with high nutritional value in China. Datong (DT) in Shanxi Province is one of the four main production areas of daylily. Therefore, Linfen (LF), Lvliang (LL), and Yangquan (YQ) in Shanxi Province have also introduced daylily from DT. However, geographical and climatic conditions and producing patterns cause variations in the vegetable quality. In the present study, we determined the quality of daylilies from different producing areas and found that the nutrient composition of daylilies from different producing areas varied. The widely targeted metabolomics was performed, and the results showed that 1642 metabolites were found in daylily. The differential metabolites between DT and YQ, LL and LF were 557, 667, and 359, respectively. Notably, 9 metabolic pathways and 76 metabolite markers could be associated with daylily from different areas. This study provides a theoretical basis for the quality maintenance and health efficacy research of daylily.</p>
Data for: Salivary metabolomics in the family environment: A large-scale study investigating oral metabolomes in children and their parental caregivers
<p>Human metabolism is complex and dynamic and is impacted by genetics, diet, health, and countless inputs from the environment. Beyond the genetics shared by family members, cohabitation leads to shared microbial and environmental exposures. Furthermore, metabolism is affected by factors such as inflammation, antibiotic potential, environmental tobacco smoke (ETS) exposure, metabolic regulation, and environmental exposure to heavy metals within the home. Metabolomics represents a useful analytical method to assay the metabolism of individuals to find potential biomarkers for metabolic conditions that may not be phenotypically obvious or represent unknown physiological processes. As such, we applied untargeted LC-MS metabolomics to archived saliva samples from a racially diverse group of elementary school-aged children and their caregivers collected during the "90-month" assessment of the Family Life Project. We assayed a total of 1,425 saliva samples of which 1,344 were paired into 672 caregiver/child dyads. We compared the metabolomes of children (N = 719) and caregivers (N = 706) within and between homes, performed population-wide "metabotype" analyses, and measured associations between metabolites and salivary biomeasures of inflammation, antioxidant potential, ETS exposure, metabolic regulation, and heavy metals. Dyadic analyses revealed that children and their caregivers have largely similar salivary metabolomes. Although there were differences between the dyads at the individual levels of analysis, dyads explained most (62%) of the metabolome variation. At a population level of analysis, our data clustered into two large groups, indicating that people likely share most of their metabolomes, but that there are distinct "metabotypes" across large sample sets. Lastly, individual differences in several metabolites – which were putative oxidative damage-associated or pathological markers – were significantly correlated with salivary measures indexing inflammation, antioxidant potential, ETS exposure, metabolic regulation, and heavy metals. Implications of the effects of family environment on metabolomic variation at the population, dyadic, and individual levels of analyses for health and human development are discussed.</p>
MetaVision3D: Automated Framework for the Generation of Spatial Metabolome Atlas in 3D | MALDI Data
<p>This repository contains MALDI data related to the Ma et al. study "<strong>MetaVision3D: Automated Framework for the Generation of Spatial Metabolome Atlas in 3D</strong>". Processed MALDI pixel-by-pixel .csv files for both metabolomics and lipidomics for two Wild-type samples, one 5xFAD sample and one GAA sample. If you use this dataset in your research, please consider citing the above study.</p> <p>The content of the files are:<br>wt.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for wild-type sample.</p> <p>5x.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for 5xFAD sample.</p> <p>gaa.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for GAA sample.</p> <p>wt2.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for wild-type2 sample.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.