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2,697 results for “Lipids”
Raw data to accompany the manuscript 'Data for Engineering Lipid Metabolism of Chinese Hamster Ovary (CHO) Cells for Enhanced Recombinant Protein Production' published in the Journal Data in Brief
<p>This repository consists of the raw western blot, microscopy and mass spectrometry data to accompany the manuscript 'Data for Engineering Lipid Metabolism of Chinese Hamster Ovary (CHO) Cells for Enhanced Recombinant Protein Production' published in the Journal Data in Brief and associated with the article '<a href="https://www.ncbi.nlm.nih.gov/pubmed/31805379">Engineering of Chinese hamster ovary cell lipid metabolism results in an expanded ER and enhanced recombinant biotherapeutic protein production</a>' published in the journal Metabolic Engineering (see DOI: 10.1016/j.ymben.2019.11.007). </p> <p>The western blot raw file is associated with Figure 1a and 1b of the Data in Brief manuscript.</p> <p>The confocal microscopy raw image files (x3) are associated with Figure 1c of the Data in Brief manuscript.</p> <p>The mass spectrometry files are the raw data that refers to the samples presented in Figure 5 of the Data in Brief manuscript. Files are labelled as in the Data in Brief and Metabolic Engineering manuscripts. The file name structures is as follows;</p> <p>CHO-Controlpoolai</p> <p>Where 'a' represents replicate 'a' of three biological replicates and 'i' refers to mass spectrometry technical analysis 1 of 3 technical analyses of each replicate (thus for each cell pool or line there are three biological replicates that are each analysed in triplicate such that there are 9 raw mass spectrometry files for each cell pool or line).</p> <p>All the mass spectrometry files are found in the compressed (zip) file named mass_spectrometry_raw_files_archive.zip</p>
Raw band intensity values for ATG3 WT or Mutants in vitro LC3 lipidation
<p>Raw band intensity values used for the quantification of in vitro LC3 lipidation results (Fig4C) in Three-step docking by WIPI2, ATG16L1 and ATG3 delivers LC3 to the phagophore.</p>
LIPID MAPS® Structure Database (LMSD) formatted for MetFrag
<p>This repository contains the LIPID MAPS® Structure Database (<a href="https://www.lipidmaps.org/databases/lmsd/overview">LMSD</a>) formatted for use in <a href="https://msbi.ipb-halle.de/MetFrag/">MetFrag</a> (and other workflows).</p> <p><em>LIPID MAPS® Lipidomics Gateway is a free, comprehensive website for researchers interested in lipid biology. Use <a href="https://www.lipidmaps.org"> https://www.lipidmaps.org</a> to stay abreast of developments each month from across the field, and explore the rich information collections, tools and resources from the LIPID Metabolites And Pathways Strategy (LIPID MAPS®) Consortium. </em><br> </p> <p>The workflow used to create this file (by B. Talavera Andújar) can be found here: <a href="https://gitlab.lcsb.uni.lu/eci/simple-utilities/sdf2csv">https://gitlab.lcsb.uni.lu/eci/simple-utilities/sdf2csv</a></p> <p><strong>Reference:</strong> LMSD: LIPID MAPS® structure database, Sud M., Fahy E., Cotter D., Brown A., Dennis E., Glass C., Murphy R., Raetz C., Russell D., and Subramaniam S., Nucleic Acids Research, 2006, DOI: <a href="https://doi.org/10.1093/nar/gkl838"> 10.1093/nar/gkl838 </a></p>
Adsorption free energies and potentials of mean-force for interactions between amino acids, lipid fragments, and nanoparticles
<p>This dataset contains tabulated potentials of mean force (PMFs) and associated adsorption (binding) free energies for interactions of amino acids side chain analogues and lipid fragments (LF) with a range of materials: titanium dioxide, iron oxide, amorphous silica, quartz, and a range of carbon-based materials including amorphous carbon, graphene and carbon nanotubes both in a pristine form and functionalized by certain chemical groups. All data were computed from atomistic molecular dynamics simulations as a part of the SmartNanoTox project 2016-2020. Version 2 of the dataset includes additional materials: zink oxide, zink sulfate in pristine and PMMA-coated forms computed within NanoSolveIt project (2019-2023). The data are intended to be used in coarse-grained models describing interactions of nanomaterials with nanoparticles, for the prediction of the binding affinity of proteins and lipids to nanoparticles, and as biological "fingerprints" of nanomaterials characterizing behavior of the nanomaterials in biological environments. </p>
Supplementary Information for "Biocatalytic Ether Lipid Synthesis by an Archaeal Glycerolprenylase" - Experimental Data
<p>This is the external Supplementary Information for our publication "Biocatalytic Ether Lipid Synthesis by an Archaeal Glycerolprenylase", freely available as a preprint from <em>ChemRxiv </em>(<a href="https://doi.org/10.26434/chemrxiv-2024-2lmv8-v2">https://doi.org/10.26434/chemrxiv-2024-2lmv8-v2</a>) and as a peer-reviewed publication from <em>Angewandte Chemie</em> (<a href="https://doi.org/10.1002/anie.202412597">https://doi.org/10.1002/anie.202412597</a>).</p> <p>The .zip files contain the raw data and metadata for all items (supplementary and main text) as well as the calculation results underlying each figure panel. This includes UV, fluorescence and NMR data. The zip files below also contain the ChimeraX session used to prepare all figure panels, the results of crystallization screens and reports on all MPLC runs used for the purification of pyrophosphate substrates. The <strong>NMR data for the synthesized compounds</strong> are described in the un-zipped metadata sheet which is separately stored below.</p> <p>The <strong>computational results</strong> contributed by Sangwar Wadtey Oung are stored in a separate zenodo entry (<a href="../doi/10.5281/zenodo.10635216">https://zenodo.org/doi/10.5281/zenodo.10635216</a>).</p> <p>This work was enabled by our previous studies on continuous reaction monitoring of phosphate-releasing transformations (<a href="https://doi.org/10.1021/acs.analchem.1c05356">https://doi.org/10.1021/acs.analchem.1c05356</a>), which itself builds on principles of spectral unmixing (<a href="https://doi.org/10.1002/cbic.202000204">https://doi.org/10.1002/cbic.202000204</a>), isosbestic normalization (<a href="https://doi.org/10.1002/cbic.202200744">https://doi.org/10.1002/cbic.202200744</a>) and thermodynamic reaction control in enzymatic equilibrium systems (<a href="https://doi.org/10.1021/acscatal.1c02589">https://doi.org/10.1021/acscatal.1c02589</a> & <a href="https://doi.org/10.1002/anie.202218492">https://doi.org/10.1002/anie.202218492</a> & <a href="https://doi.org/10.1002/adsc.201901230">https://doi.org/10.1002/adsc.201901230</a>).</p>
Activity of antioxidant enzymes and lipid peroxidation of soybean plants treated with five Diaporthe species
<p>Absorbance data from spectrophotometric measurements of catalase, reduced glutathion, lipid peroxidation and superoxide-dismutase of soybean cv. Sava plants infected with five <em>Diaporthe</em> species (i.e. <em>D. aspalathi</em>, <em>D. caulivora</em>, <em>D. eres</em>, <em>D. gulyae</em>, <em>D. longicolla</em>).</p> <p>Supplementary data to the publication Petrovic et al. (2023) The biochemical response of soybean cultivars infected by <em>Diaporthe</em> species complex. Plants 12, 2896. https://doi.org/10.3390/plants12162896</p>
SCALIBUR video 2: From retail food waste to protein, lipids, and chitin
<p>This video is part of a 3 part series explaining the innovative technologies being developed in the SCALIBUR project.</p> <p>The script is as follows: </p> <p>Eyes bigger than your stomach? Hotels and restaurants make a big contribution to the 100 million tonnes of organic waste produced each year in the EU. The SCALIBUR project is developing innovative technologies to convert waste from the food service industry into valuable products. Where we see waste SCALIBUR partners see a resource. Insects like black soldier flies love leftovers, efficiently converting food scraps into a rich biomass. New processes are being developed to extract the valuable materials like proteins, lipids and chitin: raw materials for bioplastics, and food and feed products. These technologies will help cities manage waste in a more sustainable and cost efficient way. And contribute to the creation of a truly circular bio-economy in Europe.</p>
Biogenic supported lipid bilayers as a tool to investigate nano-bio interfaces
<p>Colorimentric Nanoplasmonic Assay (CONAN) assay of EVs from TRAMP cells. UV/VIS spectrophotometer analysis of samples of EVs from TRAMP cell line incubated with gold nanoparticles, following the protocol described in Montis et al. <a href="https://doi.org/10.1016/j.jcis.2020.03.014">https://doi.org/10.1016/j.jcis.2020.03.014</a></p>
Stability characterization of microfluidic lipid-stabilized double emulsions under physiologically-relevant conditions
<p>Double emulsions (DEs) are water-in-oil-in-water (or oil-in-water-in-oil) droplets with the potential to deliver combinatory therapies due to their ability to co-localize hydrophilic and hydrophobic molecules in the same carrier. However, DEs are thermodynamically unstable and only kinetically trapped. Extending this transitory state, rendering DEs more stable, would widen the possibilities of real-world applications, yet characterization of their stability in physiologically-relevant conditions is lacking. In this work, we used microfluidics to produce lipid-stabilized DEs with reproducible monodispersity and high encapsulation efficiency. We investigated DE stability under a range of physico-chemical parameters such as temperature, pH and mechanical stimulus. Stability through time was inversely proportional to temperature. DEs were significantly stable up to 8 days at 4 oC, 5 days at RT and 2 days at 37 oC. When encapsulating a cargo, DE stability decreased significantly. When exposed to a pH change, unloaded DEs were only significantly unstable at the extremes (pH 1 and 13), largely outside physiological ranges. When exposed to flow, unloaded DEs behaved similarly regardless of the mechanical stimulus applied, with approximately 70% remaining after 100 flow cycles of 10s. These results indicate that lipid-stabilized DEs produced via microfluidics could be tailored to endure physiologically-relevant conditions and act as carriers for drug delivery. Special attention should be given to the composition of the solutions, e.g. osmolarity ratio between inner and outer solutions, and the interaction of the molecules, e.g. carrier and cargo, involved in the final formulation.</p>
Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% DOPS with Na+ counterions using ff99 Ions
<p><strong>System: </strong>Symmetric bilayer of anionic DOPS (1,2-Dioleoyl-<em>sn</em>-glycero-3-phosphoserine 100 mol-%) lipids with sodium (Na<sup>+</sup>) counter ions.</p> <p><strong>Number of DOPS:</strong> 128.<br> <strong>Number of Na<sup>+</sup>-ions:</strong> 128.<br> <strong>Number of waters:</strong> 4480.</p> <p><strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].</p> <p><strong>Ion models: </strong> Amber ff99 [J Åqvist <em>J. Phys. Chem.</em> <strong>94</strong> 8021 (1990)].</p> <p><strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].</p> <p><strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].</p> <p><strong>Number of independent repeats per setup: </strong>2.<br> <strong>Trajectory lengths per repeat:</strong> 400 ns + 100 ns.<br> <strong>Previously equilibrated for:</strong> 100 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Langevin' at T = 303 K.<br> <strong>Pressure coupling: '</strong>Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys.</em> <strong>103</strong> 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension.</p> <p><strong>Electrostatics: </strong>PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993);<em> J. Chem. Theory Comput.</em> <strong>9</strong> 3878 (2013)].<br> <strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.</p> <p><strong>Constraints: </strong>Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem. </em><strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications: </strong>OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).</p>
Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% POPS with Na+ counterions using Joung-Cheatham Ions
<p><strong>System:</strong> Symmetric bilayer of anionic POPS (palmitoyl-oleoyl-phosphatidylserine 100 mol-%) lipids with sodium (Na<sup>+</sup>) counter ions.</p> <p><strong>Number of POPS:</strong> 128.<br> <strong>Number of Na<sup>+</sup>-ions:</strong> 128.<br> <strong>Number of waters:</strong> 4480.</p> <p><strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].</p> <p><strong>Ion model:</strong> Joung–Cheatham [IS Joung, TE Cheatham III <em>J. Phys. Chem. B</em> <strong>112</strong> 9020 (2008)].</p> <p><strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].</p> <p><strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].</p> <p><strong>Number of independent repeats per setup:</strong> 2.<br> <strong>Trajectory lengths per repeat:</strong> 400 ns + 100 ns.<br> <strong>Previously equilibrated for:</strong> 100 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Langevin' at T = 298 K.<br> <strong>Pressure coupling:</strong> 'Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys</em>. <strong>103</strong> 10252 (1995)] with <em>xy</em> and <em>z</em> coupled separately at p = 1.0 bar with no surface tension.</p> <p><strong>Electrostatics:</strong> PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993); <em>J. Chem. Theory Comput. </em><strong>9</strong> 3878 (2013)].<br> <strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.</p> <p><strong>Constraints:</strong> Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem.</em> <strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications:</strong> OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).</p>
Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% POPS with Na+ counterions using ff99 ions
<p><strong>System: </strong>Symmetric bilayer of anionic POPS (palmitoyl-oleoyl-phosphatidylserine 100 mol-%) lipids with sodium (Na<sup>+</sup>) counter ions.</p> <p><strong>Number of POPS:</strong> 128.<br> <strong>Number of Na<sup>+</sup>-ions:</strong> 128.<br> <strong>Number of waters:</strong> 4480.</p> <p><strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].</p> <p><strong>Ion model:</strong> Amber ff99 [J Åqvist <em>J. Phys. Chem.</em> <strong>94</strong> 8021 (1990)].</p> <p><strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].</p> <p><strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].</p> <p><strong>Number of independent repeats per setup: </strong>2.<br> <strong>Trajectory lengths per repeat:</strong> 400 ns + 100 ns.<br> <strong>Previously equilibrated for:</strong> 100 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Langevin' at T = 298 K.<br> <strong>Pressure coupling: '</strong>Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys.</em> <strong>103</strong> 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension.</p> <p><strong>Electrostatics: </strong>PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993);<em> J. Chem. Theory Comput.</em> <strong>9</strong> 3878 (2013)].<br> <strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.</p> <p><strong>Constraints: </strong>Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem. </em><strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications: </strong>OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).</p>
Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% DOPS with Na+ counterions using Joung-Cheetham Ions
<p><strong>System: </strong>Symmetric bilayer of anionic DOPS (1,2-Dioleoyl-<em>sn</em>-glycero-3-phosphoserine 100 mol-%) lipids with sodium (Na<sup>+</sup>) counter ions.</p> <p><strong>Number of DOPS:</strong> 128.<br> <strong>Number of Na<sup>+</sup>-ions:</strong> 128.<br> <strong>Number of waters:</strong> 4480.</p> <p><strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].</p> <p><strong>Ion models: </strong>Joung–Cheatham [IS Joung, TE Cheatham III <em>J. Phys. Chem. B </em><strong>112</strong> 9020 (2008)].</p> <p><strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].</p> <p><strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].</p> <p><strong>Number of independent repeats per setup: </strong>2.<br> <strong>Trajectory lengths per repeat:</strong> 400 ns + 100 ns.<br> <strong>Previously equilibrated for:</strong> 100 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Langevin' at T = 303 K.<br> <strong>Pressure coupling: '</strong>Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys.</em> <strong>103</strong> 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension.</p> <p><strong>Electrostatics: </strong>PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993);<em> J. Chem. Theory Comput.</em> <strong>9</strong> 3878 (2013)].<br> <strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.</p> <p><strong>Constraints: </strong>Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem. </em><strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications: </strong>OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).</p>
Input files for "Faster Simulations with a 5 fs Time Step for Lipids in the CHARMM Force Field"
<p>The performance of all-atom molecular dynamics simulations is limited by an integration time step of 2 fs, which is needed to resolve the fastest degrees of freedom in the system, namely, the vibration of bonds and angles involving hydrogen atoms. The virtual interaction sites (VIS) method replaces hydrogen atoms by massless virtual interaction sites to eliminate these degrees of freedom while keeping intact nonbonded interactions and the explicit treatment of hydrogen atoms. We have modified the existing VIS algorithm for most lipids in the popular CHARMM36 force field by increasing the hydrogen atom masses at regular intervals in the lipid acyl chains and obtained lipid properties and pore formation free energies in very good agreement with those calculated in simulations without VIS. Our modified VIS scheme enables a 5 fs time step resulting in a significant performance gain for all-atom simulations of membranes. The method has the potential to make longer time and length scales accessible in all-atom simulations of membrane–protein complexes.</p> <p>The file set contains individual lipid topologies for virtual interaction sites for standard CHARMM lipids, as well as a README file with instructions on how to implement the VIS algorithm for membranes or membrane-protein complexes</p> <p>Please Cite: <a href="//pubs.acs.org/doi/10.1021/acs.jctc.8b00267">10.1021/acs.jctc.8b00267</a></p> <p> </p>
Lipidomic Data of Mycoplasma mycoides and JCVI-Syn3A grown on defined lipid diets
<p>Shotgun Lipidomics of four conditions: Mycoplasma mycoides grown on a 2FA + Cholesterol diet, a POPC + Cholesterol diet, a Diether PC + Cholesterol diet, and JCVI-Syn3A grown on a Diether PC + Cholesterol diet. All data made with three biological replicates. Lipids extracted from cells using the Bligh-Dyer protocol. Lipids analyzed by Lipotype with mass spectrometry based analysis. </p>
Escape from NK cell tumor surveillance by NGFR-induced lipid remodeling in melanoma
<p>Metabolomics Data used in the publication</p> <p>1) raw files obtained by the FGCZ (<a href="https://fgcz.ch/">Functional Genomics Center Zurich</a>):</p> <p>QCpools (technical replicate of all sample pooled: p2947_o5292_SOP3_DDA5_pos_QCpool_cells</p> <p>Sample of M010817 CMVTOEV cells not induced: p2947_o5292_SOP3_DDA5_pos_EV_cells_noninduced_sample</p> <p>Sample of M010817 CMVTOEV cells induced: p2947_o5292_SOP3_DDA5_pos_EV_cells_induced_sample</p> <p>Sample of M010817 CMVTONGFR cells not induced: p2947_o5292_SOP3_DDA5_pos_p75_cells_noninduced_sample</p> <p>Sample of M010817 CMVTONGFR cells induced: p2947_o5292_SOP3_DDA5_pos_p75_cells_induced_sample</p> <p>2) method description LC-MS</p> <p>LC-MS-based lipidomic analysis was performed with M010817 CMVTOEV and CMVTONGFR cells pretreated with 1 μg/ml doxycycline for 24 h. Cells were detached with PBS 2 mM EDTA, washed and resuspended in 1-butanol/methanol (1:1). Cells were vortexed for 15 sec and subsequently sonicated on ice with a pulse of 3x 10 sec and 1x 30 sec at an amplitude of 15% using a SONOPULS HD 2070 Ultrasonic Homogenizer (Bandelin). Cell extracts were centrifuged at 16’000 g, 20°C for 10 min to remove macromolecules and subsequently diluted (1:3) with water/methanol (1:2) solution. The dilution was vortexed and centrifuged (16,000 x g, 20 °C, 10 min). 100 μl of the supernatant was transferred to a glass vial with narrowed bottom (Total Recovery Vials, Waters) for LC-MS injection. <br> Lipids were separated on a nanoAcquity UPLC (Waters) equipped with a HSS T3 capillary column (150 μm x30mm, 1.8 μm particle size, Waters), applying a gradient of 5 mM ammonium acetate in water/acetonitrile 95:5 (A) and 5 mM ammonium acetate in isopropanol/acetonitrile 90:10 (B) from 5% B to 100% B over 10 min. The following 5 min conditions were kept at 100% B, followed by 5 min reequilibration to 5% B. The injection volume was 1 μL. The flow rate was constant at 2.5 μl/min. The UPLC was coupled to QExactive mass spectrometer (Thermo) by a nanoESI source. MS data was acquired using positive polarization and data-dependent acquisition (DDA). Full scan MS spectra were acquired in profile mode from 80-1200 m/z with an automatic gain control target of 1e6, an Orbitrap resolution of 70`000, and a maximum injection time of 200 ms. The 5 most intense charged (z = +1 or +2) precursor ions from each full scan were selected for collision induced dissociation fragmentation. Precursor was accumulated with an isolation window of 0.4 Da, an automatic gain control value of 5e4, a resolution of 17`500, a maximum injection time of 50 ms and fragmented with a normalized collision energy of 20, 30 and 40 (arbitrary unit). Generated fragment ions were scanned in the linear trap. Minimal signal intensity for MS2 selection was set to 500.</p> <p> </p> <p>3) csv result files were generated by the FGCZ (<a href="https://fgcz.ch/">Functional Genomics Center Zurich</a>)</p> <p>adducts found: adducts_p2947_o5292_new_10K_20210910</p> <p>identifications found: identifications_p2947_o5292_new_10K_20210910</p> <p>abundances of features: measurements_p2947_o5292_new_10K_20210910</p> <p>Metaboanalyst file statistics: Metabo_p2947_o5292_10k_cells_CVcleaned_20210916</p> <p>Metaboanalyst file enrichment: Metabo_Enrichment_p2947_o5292_10k_cells_20210910 _p75</p> <p>4) method description data analysis</p> <p>Data sets were evaluated with Progenesis QI software (Nonlinear Dynamics), which aligns the ion intensity maps based on a reference data set, followed by a peak picking on an aggregated ion intensity map. Detected ions were identified based on accurate mass, detected adduct patterns and isotope patterns by comparing with entries in the LipidMaps Data Base (LM) and KEGG database. Considered adducts were M+H, M+NH4, 2M+H M+H-H2O. A mass accuracy tolerance of 5 ppm was set for the searches. Fragmentation patterns were considered for 600 the identifications of metabolites. Putative identifications were further ranked based on Mass error (observed mass – exact mass), isotope similarity (observed versus theoretical).</p> <p> </p>
raw data of Gut microbiota remodeling and intestinal adaptation to lipid malabsorption after enteroendocrine cell loss in adult mice
<p>Microbiome dataset for "Gut microbiota remodeling and intestinal adaptation to lipid malabsorption after enteroendocrine cell loss in adult mice" publication</p> <p>https://doi.org/10.1016/j.jcmgh.2023.02.013</p> <p> </p>
Data for: Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease.
<p>Summary of Bivariate GWAS scan results reported in:<br> <a href="https://pubmed.ncbi.nlm.nih.gov/30525989/">Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease. </a>Siewert KM, Voight BF. Circ Genom Precis Med. 2018 Dec;11(12):e002239. doi: 10.1161/CIRCGEN.118.002239.</p> <p>PMID: 30525989 </p>
Light and confocal micrographs on the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, the accumulation of lipid droplets, and the heterologous expression and localisation of signature LD protein homologs to tobacco pollen tubes
<p>These micrographs accompany the work "Environmental gradients reveal stress hubs predating plant terrestrialization", posted as a pre-print on bioRxiv https://doi.org/10.1101/2022.10.17.512551 </p> <p>The light and confocal micrographs show the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, especially their accumulation of lipid droplets (LDs); in confocal micrographs, LDs appeared as distinct structures upon staining with BODIPY.</p> <p>Further confocal micrographs show the heterologous expression and localisation of signature LD protein homologs detected in Mesotaenium endlicherianum SAG 12.97; heterologous expression was carried out in tobacco pollen tubes were also stained with BODIPY and proteins were tagged with mCherry.</p>
Concentrations of methane, sulfate and lipid biomarkers and carbon isotope values oof lipids in the sediments from the outer Laptev Sea
<p>The dataset contains the concentrations of methane, sulfate and microbial lipid biomarkers, and the carbon isotope composition of lipids in the sediment collected from the SWERUS-C3 expedition in 2014. The core sediment samples were from stations 13, 14 and 23 in the outer Laptev Sea. The field investigation reveals it is a methane seep area. </p>
ScienceDex guides
Understand access before you commit
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.