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175 results for “Lipidomics”
VOLUMETRIC ABSORPTIVE MICROSAMPLING OF BLOOD (VAMS) FOR UNTARGETED LIPIDOMICS
<p>In the present, proof-of-concept paper, we explore the potential of one common solid support for blood microsampling (dried blood spot, DBS) and a recently developed device (volumetric absorptive microsampling, VAMS) for the untargeted lipidomic profiling of human whole blood, performed by high-resolution LC-MS/MS. Dried blood microsamples obtained by means of DBS and VAMS were extracted with different solvent compositions and compared with fluid blood to evaluate their efficiency in profiling the lipid chemical space in the most wide way. Although more effort is needed to better characterize this approach, our results indicate that VAMS is a viable option for untargeted studies and its use will bring all the corresponding known advantages, like, for example, haematocrit independence, in the field of lipidomics. </p>
Examination of the effect of nocadazole treatment on lipidomics
<p>We conducted an analysis to investigate the impact of Nocodazole treatment on Caki-1, a human renal cell carcinoma cell line. Our preliminary lipidomics analysis revealed that Nocodazole induces the accumulation of triacylglycerides (TAGs) in Caki-1 cells. To gain further insights, we employed inhibitors of diacylglycerol acyltransferases (DGATs), including DGAT1 and DGAT2, which play a pivotal role in TAG synthesis by adding a fatty acyl group to the sn-3 position of diacylglycerol, ultimately forming TAGs.</p>
Nitrogen and sulfur for phosphorus: Lipidome adaptation for anaerobic sulfate-reducing bacteria in phosphorus-deprived conditions
<p><strong>Abstract </strong></p> <p>Understanding how microbial lipidomes adapt to environmental and nutrient stress is crucial for comprehending microbial survival and functionality. Certain anaerobic bacteria can synthesize glycerolipids with ether/ester bonds, yet the complexities of their lipidome remodeling under varying environmental and nutritional conditions remain largely unexplored. In this study, we thoroughly examined the lipidome adaptations of <em>Desulfatibacillum alkenivorans</em> strain PF2803<sup>T</sup>, a mesophilic anaerobic sulfate-reducing bacterium known for its n-alkene degradation capability, under various cultivation conditions including temperature, pH, salinity, and ammonium and phosphorous concentrations. Employing an extensive analytical and computational lipidomic methodology, we identified nearly 400 distinct lipids for the first time, including a range of glycerol ether/ester lipids and various polar head groups. Information theory-based analysis revealed that temperature fluctuations and phosphate scarcity profoundly influenced the lipidome's composition, leading to enhanced diversity and specificity of novel lipids. Notably, phosphorous limitation led to the creation of novel glucuronosylglycerols and sulfur-containing aminolipids, termed butyramide cysteine glycerols, featuring various ether/ester bonds. This suggests a novel adaptive strategy for anaerobic heterotrophs to thrive in phosphorus-depleted areas of the oceans, characterized by a diverse array of nitrogen- and sulfur-containing polar head groups, moving beyond a reliance on conventional non-phospholipid types.</p> <p><strong>Repository Contents</strong></p> <p><strong>1_SRB_lipidome.zip</strong>: includes all source data and code scripts used for figures in this study. Files are organized as follows and are associated with the corresponding parts of the manuscript: Figure 2A-F, Figure 4A-E, Figure 5A-B, Figure 6A-E, Supplementary Figures 7.</p> <p>Figure 2. The impact of culturing conditions on lipidomic variability. A) The number of intact polar lipid species in different lipid classes putatively identified in this study. B) Principal Component Analysis (PCA) based on peak intensity of intact polar lipid species, showcasing the variation in general lipidomic features across individual experimental conditions. C) Information theory analysis showing lipidome diversity and specificity based on the Shannon entropy of the lipidomic frequency distribution. D) Lipid species specificity across the various culturing conditions. E) Hierarchical clustering heatmap depicting the distribution of major lipid classes across all the culturing conditions. F) Cumulative variability of all intact polar lipid species within each range of growth conditions, calculated as the difference in mean abundance between the standard growth condition and the variable conditions. The variability analysis excludes phosphate 0.015 mM as it is under phosphorous-sufficient condition, which showed a similar lipidome composition as the standard growth condition. Each condition analysis is based on three biological replicates. Abbreviations: Polar head groups –phosphatidylethanolamines (PE), phosphatidylglycerols (PG), cardiolipins (CL), novel N-butyramide cysteine (BACys), glucuronosyl (GlcA); Core lipids – diacylglycerols (DAGs), acyl/ether glycerols (AEGs), dietherglycerols (DEGs), tetraetherglycerols (TetraEGs), triether/monoacyl glycerols (TriEGs), diether/diacyl glycerol (DiEGs), monoether/triacyl glycerol (MonoEGs), and tetraacylglycerols (TetraAGs), demethylmenaquinone (DMK).</p> <p>Figure 4. Variability of major lipid classes across different culturing conditions. A) PG with different ether/ester bond core lipids. B) PE with different ether/ester bond core lipids. C) CL with different ether/ester bond core lipids. D) GlcA with different ether/ester bond core lipids. E) Novel BACys with different ether/ester bond core lipids. Asterisks indicate significant differences between the last condition and the current condition (Student's t tests on pairwise differences, *P < 0.05, **P < 0.01 and ***P < 0.001). The numbers of treatments on the x-axis represent the parameters associated with each condition, ranging from low to high. These parameters include temperature (25°C, 30°C, 40°C), pH levels (6.4, 6.8, 7.8), NaCl concentration (3 g/L, 10 g/L, 25 g/L, 60 g/L), phosphate concentration (0.0005 mM, 0.0015 mM, 0.015 mM, 1.5 mM), and ammonium concentration (0.003 g/L, 0.03g/L, 0.3 g/L).</p> <p><span>Figure 5. Distribution of the relative abundance of major lipid classes and number of lipid species across different culturing conditions. </span><span>A) Relative abundance of major lipid classes. B) Number of lipid species with an abundance exceeding 0.5% of the total lipids. The numbers of treatments on the x-axis represent the parameters associated with each condition, ranging from low to high. These parameters include temperature (25°C, 30°C, 40°C), pH levels (6.4, 6.8, 7.8), NaCl concentration (3 g/L, 10 g/L, 25 g/L, 60 g/L), phosphate concentration (0.0005 mM, 0.0015 mM, 0.015 mM, 1.5 mM), and ammonium concentration (0.003 g/L, 0.03g/L, 0.3 g/L).</span></p> <p><span>Fig</span><span>ure</span><span> 6</span><span>. Adaptation of ether/ester bond lipids, polar headgroups, the averaged carbon chain length and double bond equivalents (DB) of the studied sulfur-reducing bacterial lipidome across different culturing conditions.</span><span> A) The ratio of phospholipids with dialkyl chains and tetraalkyl chains, or the ratio of (PE+PG)/CL, calculated as the summed core lipids within each class. B) The logarithmic ratio of phospholipids/non-phospholipids, phospholipids included both diglyceride phospholipids (PG and PE) and CL. C) The ratio of ether/ester bond lipids. The abundance of ethers in lipids with DEGs is calculated based on their inherent intensity, while the abundance of ethers in lipids containing both ether and ester chains is determined using the ratio of ether% multiplied by the intensity. For instance, in CL-TriEG, which has three ether-bond chains and one ester-bond chain, the abundance of the ether chain is calculated as 0.75 multiplied by the intensity. D) The average DBs of total lipids across different culturing conditions. E) The average chain length of two-chain lipids across different culturing conditions. Asterisks indicate significant differences between the last condition and the current condition (Student’s <em>t </em>tests on pairwise differences, *<em>P </em>< 0.05, **<em>P </em>< 0.01 and ***<em>P </em>< 0.001). These parameters include temperature (25°C, 30°C, 40°C), pH levels (6.4, 6.8, 7.8), NaCl concentration (3 g/L, 10 g/L, 25 g/L, 60 g/L), phosphate concentration (0.0005 mM, 0.0015 mM, 0.015 mM, 1.5 mM), and ammonium concentration (0.003 g/L, 0.03g/L, 0.3 g/L).</span></p> <p><span><span>Fig. S7. The fractional abundance of lipids with (A) different DBs (0-4) and (B) different carbon chain lengths (26-37, 56-68).</span></span><span> The numbers from 26 to 37 represent the summed two-chain carbon atoms, while the numbers from 56 to 68 represent the summed four-chain carbon atoms (from CL). The numbers of treatments </span><span>with different colors</span><span> represent the parameters associated with each condition, ranging from low to high. </span></p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Atomistic modelling of lysophospholipids from the Campylobacter jejuni lipidome
<p>Input files for and trajectory files from the modelling and simulation of lysophospholipids from the C. jejuni lipidome. </p>
Lipidomics and metabolomics datasets for "Adverse effects of arsenic uptake in rice metabolome and lipidome revealed by untargeted liquid chromatography coupled to mass spectrometry (LC-MS) and regions of interest multivariate curve resolution"
<p><strong>Files description</strong></p> <p>Raw files for lipidomics and metabolics studies on the impact of arsenic exposure on rice growth.</p> <p>File details on the worksheets lipids_files.xlsx and metabolomics_files.xlsx</p> <p>Files have been organized as follows:</p> <p><strong>Lipidomics</strong></p> <blockquote> <p>1) Control samples: lip_controls.rar<br> 2) Watering low As exposure: lip_water_1.rar<br> 3) Watering high As exposure: lip_water_1000.rar<br> 4) Soil low As exposure: lip_soil_5.rar<br> 5) Soil high As exposure: lip_soil_50.rar<br> 6) QC samples: lip_qcs.rar</p> </blockquote> <p><strong>Metabolomics (positive ionization mode)</strong></p> <blockquote> <p>1) Control samples: met_pos_controls.rar<br> 2) Watering low As exposure: met_pos_water_1.rar<br> 3) Watering high As exposure: met_pos_water_1000.rar<br> 4) Soil low As exposure: met_pos_soil_5.rar<br> 5) Soil high As exposure: met_pos_soil_50.rar<br> 6) QC samples: met_pos_qcs.rar</p> </blockquote> <p><strong>Metabolomics (negative ionization mode)</strong></p> <blockquote> <p>1) Control samples: met_neg_controls.rar<br> 2) Watering low As exposure: met_neg_water_1.rar<br> 3) Watering high As exposure: met_neg_water_1000.rar<br> 4) Soil low As exposure: met_neg_soil_5.rar<br> 5) Soil high As exposure: met_neg_soil_50.rar<br> 6) QC samples: met_neg_qcs.rar<br> </p> </blockquote> <p> </p> <p><strong>Experimental details</strong></p> <blockquote> <p><strong>Arsenic Exposure</strong></p> <p>Arsenic was supplied through two main routes: watering with contaminated water or soil containing arsenic. In addition, this new study includes metabolomic as well as lipidomic analysis, in order to have a more global overview of arsenic exposure.</p> <p>For the watering treatment, during the first 11 days, rice was irrigated with Milli-Q water. From that day until harvesting, plants were watered with 1 and 1000 μM of As (V) for the two concentration levels of exposure, and with Milli-Q water for control samples. The lowest concentration was established at 1 μM as it is the limit of the acceptable arsenic concentration in water by European legislation. The upper concentration was set at 1000 μM, a threshold established to ensure that the experiment was performed under sub-lethal arsenic concentration for the plant, based on previous studies.</p> <p>For the soil treatment, two containers were prepared with 1 kg of soil two days before planting. Soil from the container was exposed to two arsenic concentration levels (5 and 50 mg L<sup>-1</sup>). Once sowing, rice was irrigated the whole growth period with a solution containing 0.001 μM of As (V). The lowest arsenic limit in this treatment was set at 5 mg L<sup>-1</sup> as a maximum value of common arsenic leaches without toxic characteristics, although background soil content of arsenic varies between one and 40 ppm according to the US food and drug administration (FDA) report. The highest arsenic limit was established to 50 mg L<sup>-1</sup>, as a considerably high arsenic content in the soil, slightly above the maximum frequently encountered levels.</p> <p><strong>Lipidomic Analysis</strong></p> <p>The lipidomic analysis was performed using a Waters Acquity UPLC system (Waters Corporation, MA, USA), connected to a Waters LCT Premier orthogonal accelerated time of flight mass spectrometer (Waters), operated in both positive and negative electrospray (ESI) ionization modes. Full scan spectra were acquired from 50 to 1500 Da.</p> <p>The chromatographic column employed was a Kinetex C8 (100 x 2.1 mm, 1.7 μm) (Phenomenex) under the following conditions (already used in [47]): temperature at 30˚C, injection volume at 10 μL, and flow rate at 0.3 mL min<sup>-1</sup>. Mobile phases selected were (A) MeOH 1mM ammonium formate, and (B) H<sub>2</sub>O 2mM ammonium formate, both at 0.2% formic acid. The gradient started at 80% A, increased to 90% A in 3 min, from 3 to 6 min remained at 90% A, changed to 99 % A until minute 15, remained constant 1 min, and returned to initial conditions until minute 20.</p> <p><strong>Metabolomic analysis</strong></p> <p>The metabolomic analysis was performed using a Waters Acquity UPLC system connected to a Q-Exactive (Thermo Fisher Scientific, Hemel Hempstead, UK) equipped with a quadrupole-Orbitrap mass analyzer. Electrospray (ESI) was used as an ionization source in both positive and negative ion modes. Full scan mass range was set from <em>m/z</em> 90 to 1000, and all ion fragmentation (AIF) was performed with normalized collision energy (NCE) of 35 eV.</p> <p>The column employed was an HILIC TSK gel amide-80 column (250 x 2.0 mm i.d., 5 μm) provided by Tosoh Bioscience (Tokyo, Japan), under the following experimental conditions (already employed in [45]): flow rate at 0.15 mL min<sup>-1</sup>, at room temperature, and 5 μL injection volume. Mobile phases were (A) AcN, and (B) 5 mM ammonium acetate, adjusted at pH 5.5 with acetic acid. The gradient employed was: starting conditions at 25% B, then increased until 30% B in 8 min; a 60% B was reached at 10 min, held for 2 min more and then back to 25% B until minute 14 min; lastly, a re-equilibration step was added and from 14 to 20 min at 25% B.</p> </blockquote> <p> </p> <p><strong>Funding:</strong> This research was funded by the Spanish Ministry of Science and Innovation (MCI, Grant CTQ2017-82598-P) and Severo Ochoa Project CEX2018-000794-S (funded by MCIN/AEI/ 10.13039/501100011033), and supported from the Catalan Agency for Management of University and Research Grants (AGAUR, Grant 2017SGR753). MPC was funded by a predoctoral FPU 16/02640 scholarship from the Spanish Ministry of Education and Vocational Training (MEFP). </p> <p> </p>
Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions
<p>Lipidomics studies suffer from analytical and annotation challenges due to the great structural similarity of many of the lipid species. To improve lipid characterization and annotation capabilities beyond those afforded by traditional mass spectrometry (MS)-based methods, multidimensional separation methods such as those integrating liquid chromatography, ion mobility spectrometry, collision induced dissociation and MS (LC-IMS-CID-MS) may be employed. While LC-IMS-CID-MS and other multidimensional methods offer valuable hydrophobicity, structural and mass information, the files are also complex and difficult to assess. Thus, the development of software tools to rapidly process and facilitate confident lipid annotations is essential. In this Protocol Extension, we utilize the freely available, vendor-neutral, and open-source software Skyline to process and annotate the multidimensional lipidomic data. While Skyline was established for targeted processing of LC-MS-based proteomics data, it has since been extended such that it can be used to analyze small molecule data as well as data containing the IMS dimension. This protocol utilizes Skylines’ recently expanded capabilities, including small molecule spectral libraries, indexed retention time (iRT), and ion mobility filtering, and provides a step-by-step description for importing data, predicting retention times, validating lipid annotations, exporting results, and editing our manually validated 500+ lipid library. While the time required to complete the steps outlined here varies based on multiple factors such as dataset size and familiarity with Skyline, this protocol takes approximately 5.5 hours to complete when annotations are rigorously verified for maximum confidence.</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>
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>
Lipidomic profiling indicate protection of hypoxic-ischemic brain injury on neonatal rats ingesting Acer truncatum Bunge oil
<p>Hypoxic ischemic encephalopathy (HIE) has a serious effect on newborn growth and development, and there are currently no effective interventions. In this study, we discovered administering <em>Acer truncatum Bunge seed </em>oil (ASO) for 30 days reduces the damage caused by HIE and improves the learning and memory ability. Using lipidomics approaches to compare metabolite changes in HIE and sham rats, we discovered that glycerophospholipids, plasmalogen, unsaturated fatty acids decreased and lysophospholipids increased in HIE rats' brain. After 30 days of ASO treatment, glycerophospholipids, plasmalogen, and unsaturated fatty acids increased in serum and brain, while lysophospholipids and oxidized glycerophospholipids decreased. Based on cluster, correlation and attribution analysis, we find changes of glycerophospholipids, plasmalogen, w3/6/9 fatty acid, oxidized GP and lysophospholipids contributes to improvement of cognitive ability, indicated by eliminating the oxidative injury by HIE. Our findings suggest that ASO may be a potential special medical food for ischemic hypoxic newborns.</p>
Demonstration LC-IM-MS Lipidomics Data for mzapy
<p>LC-IM-MS lipidomics data, in MZA format, acquired from porcine brain total lipid extract. Used for demonstration of mzapy functionality. </p>
Experimental and Computational Evaluation of Lipidomic In-Source Fragmentation as a Result of Post-Ionization with Matrix-Assisted Laser Desorption/Ionization
<p>Supporting data for the manuscript 'Experimental and Computational Evaluation of Lipidomic In-Source Fragmentation as a Result of Post-Ionization with Matrix-Assisted Laser Desorption/Ionization.'</p>
Lipidomics data from knockin mice carrying a dominant negative mutation in LXRalpha (p.W441R)
<p>Lipidomics data from knockin mice carrying a dominant negative mutation in LXRalpha (p.W441R). Wildtype, heterozygous and homozygous mice were fed either a low fat, low cholesterol control diet (TD.05230, Inotiv) or a western diet (TD.88137, Inotiv) for 8 weeks. Mice were then sacrificed and livers flash frozen. Livers were homogenised, lipids extracted and lipid profile analysed by liquid chromatography and mass spectrometry as described in Lockhart, Muso et al., (https://www.biorxiv.org/content/10.1101/2024.04.28.591512v1). If a lipid could not be detected in a sample, or quality checks were failed, values were set to half the minimum reported value. The data was then log transformed prior to upload. </p>
Environmentally induced lipidome adaptation in the bacterial model organism M. extorquens
<p>Cells, from microbes to man, adapt their membranes in response to the environment to maintain functionality. How cells sense environmental change/stimuli and adapt their membrane accordingly is unclear. In particular, how lipid composition changes and what lipid structural features are necessary for homeostatic adaptation remains relatively undefined. Here, we examine the simple yet adaptive lipidome of the plant-associated Gram-negative bacterium <em>Methylobacterium extorquens </em>over<em> </em>a range of chemical and physical conditions. Using shotgun lipidomics, we explored adaptivity over varying temperature, hyperosmotic and detergent stress, carbon sources, and cell density. Globally, we observed that as few as 10 lipids, representing ca. 30% of the lipidome, characterized by 9 structural features account for 90% of the total changes. We revealed that variations in lipid structural features are not monotonic over a given range of conditions (e.g. temperature) and are not evenly distributed across lipid classes. Thus, despite the compositional simplicity of this lipidome, the patterns in lipidomic remodeling suggest a highly adaptive mechanism with many degrees of freedom. Our observations reveal constraints on the minimal lipidomic requirements for an adaptive membrane and provide a resource for unraveling the design principles of living membranes.</p>
Lipidomics of myelin from wild-type and Gltp cKO mice
<p>Myelin lipidome of <em><span>Gltp</span></em> cKO (<em><span>Cnp-Cre Gltp<sup>flox/flox</sup></span></em>) and Cre control (<em><span>Cnp-Cre</span></em>) mice at postnatal day 14 and 28 (P14 and P28). n=4 mice for each genotype/time point. Lipid species abundance is reported in mole %. </p> <p>The dataset is from the manuscript entitled "Nonvesicular lipid transfer drives myelin growth in the central nervous system"</p>
Lipidomic and fatty acid metabolism changes in pancreatic cancer upon ELOVL6 inhibition
<p>LC-MS data for the analysis of lipidomic and fatty acid metabolism changes in pancreatic cancer upon ELOVL6 inhibition and MYC deletion or overexpression</p>
Cell-Type Resolved Protein Atlas of Brain Lysosomes Identifies SLC45A1-Associated Disease as a Lysosomal Disorder: Untargeted Metabolomics and Lipidomics Data Deposition
<p>Raw data files used for untargeted metabolomics and lipidomics in the manuscript "Cell-Type Resolved Protein Atlas of Brain Lysosomes Identifies SLC45A1-Associated Disease as a Lysosomal Disorder".</p> <p>The PDF document <strong>(Data_Deposition_Naming_Info.pdf)</strong> contains information on the file naming system.</p>
Targeted lipidomics yields changes in both arachidonic acid and linoleic acid pathways observed in C57BL/6J mice compared to KitW-sh mice after nitrogen mustard exposure
<p>Sulfur mustard (SM) has been widely used as a chemical warfare agent including most recently in Syria. Mice exposed to SM exhibit an increase in pro-inflammatory cytokines followed by immune cell infiltration in the lung, however, the mechanisms leading to these inflammatory responses has not been completely elucidated. Mast cells are one of the first responding innate immune cells found at the mucosal surfaces of the lung and have been reported to be activated by SM in the skin. Therefore, we hypothesized that nitrogen mustard (NM: a surrogate for SM) exposure promotes activation of mast cells causing chronic respiratory inflammation. To assess the role of mast cells in NM-mediated pulmonary toxicity, we compared the effects of NM exposure between C57BL/6 and B6.Cg-KitW-sh/HNihrJaeBsmJ (Kit<sup><em>W-s</em></sup><sup>h</sup>; mast cell deficient) mice. Lung injury was observed in C57BL/6J mice following NM exposure (0.125 mg/kg) at 72 h, which was significantly abrogated in Kit<sup><em>W-s</em></sup><sup>h</sup> mice. Although both strains exhibited damage from NM, C57BL/6J mice had higher inflammatory cell infiltration and more elevated prostaglandin D<sub>2</sub> (PGD<sub>2</sub>) present in bronchoalveolar lavage fluid compared with Kit<sup><em>W-s</em></sup><sup>h</sup> mice. Additionally, we utilized murine bone marrow-derived mast cells to assess NM-inducedearly and late activation. Although NM exposure did not result in mast cell degranulation, we observed an upregulation in PGD<sub>2</sub> and IL-6 levels following exposure to NM. Results suggest that mast cells play a prominent role in lung injury induced by NM and may contribute to the acute and potentially long-term lung injury observed caused by SM.</p>
Lipidomic profiling of Mycobacterium tuberculosis treated with JCP276, BMB034, or THL
<p><span><span><span><span><span><span><span><span><span><span><span>The increasing incidence of antibiotic-resistant <i>Mycobacterium tuberculosis </i>infections is a growing global health threat necessitating the development of new antibiotics. Serine hydrolases (SHs) are a promising class of targets because of their importance for the synthesis of the mycobacterial cell envelope. We screened a library of small molecules containing serine-reactive electrophiles and identified a series of narrow spectrum inhibitors of <i>M. tuberculous </i>growth. Using these lead molecules we performed competitive activity-based protein profiling and identified SH targets, including enzymes with uncharacterized functions. Lipidomic analyses of compound-treated cultures revealed an accumulation of free lipids and a substantial decrease in lipooligosaccharides, linking SH inhibition to defects in cell envelope biogenesis. Mutant analysis revealed a path to resistance via the synthesis of mycocerates, but not through mutations to target enzymes. We conclude that simultaneous inhibition of multiple SH enzymes is likely to be an effective therapeutic strategy.</span></span></span></span></span></span></span></span></span></span></span></p>
Lipidomic analysis of bronchoalveolar lavage from mice exposed to ozone
<p>Exposure to ozone causes decrements in pulmonary function, a response associated with alterations in lung lipids. Pulmonary lipid homeostasis is dependent on the activity of peroxisome proliferator-activated receptor gamma (PPARγ), a nuclear receptor that regulates lipid uptake and catabolism by alveolar macrophages (AMs). Herein, we assessed the role of PPARγ in ozone-induced dyslipidemia and aberrant lung function in mice. Exposure of mice to ozone (0.8 ppm, 3 hr) resulted in a significant reduction in lung hysteresivity at 72 hr post-exposure; this correlated with increases in levels of total phospholipids, specifically cholesteryl esters, ceramides, phosphatidylcholines, phosphorylethanolamines, sphingomyelins, and di- and triacylglycerols in lung lining fluid. This was accompanied by a reduction in relative surfactant protein-B (SP-B) content, consistent with surfactant dysfunction. Administration of the PPARγ agonist, rosiglitazone (5 mg/kg/day, i.p.) reduced total lung lipids, increased relative amounts of SP-B, and normalized pulmonary function in ozone-exposed mice. This was associated with increases in lung macrophage expression of CD36, a scavenger receptor important in lipid uptake and a transcriptional target of PPARγ. These findings highlight the role of alveolar lipids as regulators of surfactant activity and pulmonary function following ozone exposure and suggest that targeting lipid uptake by lung macrophages may be an efficacious approach for treating altered respiratory mechanics.</p>
Lactobacillus johnsonii N6.2 total lipid and fractionated lipids profiling by qualitative lipidomic LC-MS/MS analysis
<p>Table presents both MS-1 (precursor mass-matched) and MS-2 (precursor mass- and spectral-matched) annotations. The values in the table represent the peak area. The column labels, RT: retention time; m/z: mass-to-charge ratio; SL (simple lipids), GL (glycolipids), and PL (phospholipids) represent lipid fractions and TL: total lipids. Table is provided as an xlsx file.</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.