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377 results for “Mass spectrometry”
Liquid chromatography tandem mass spectrometry of AMPA receptor containing vesicles
<p>Regulated delivery of AMPA receptors (AMPARs) to the postsynaptic membrane is an essential step in synaptic strength modification, and in particular, long-term potentiation (LTP). While LTP has been extensively studied using electrophysiology and light microscopy, several questions regarding the molecular mechanisms of AMPAR delivery via trafficking vesicles remain outstanding, including the gross molecular make up of AMPAR trafficking organelles and identification and location of calcium sensors required for SNARE complex-dependent membrane fusion of such trafficking vesicles with the plasma membrane. Here, we isolated AMPAR containing vesicles (ACVs) from whole mouse brains via immunoisolation and characterized them using immunoelectron microscopy, immunoblotting, and liquid chromatography tandem mass spectrometry (LC-MS/MS). We identified several proteins on ACVs that were previously found to play a role in AMPAR trafficking, including synaptobrevin-2, Rabs, the SM protein Munc18-1, the calcium-sensor synaptotagmin-1, as well as several new candidates, including synaptophysin and synaptogyrin on ACV membranes. Here, we present three biological replicates of liquid chromatography tandem mass spectrometry of AMPA receptor containing vesicles.</p>
Supplementary data Quantitative elemental mapping of chondritic meteorites using laser ablation-inductively coupled plasma-time of flight-mass spectrometry (LA-ICP-TOF-MS)
<p>Supplementary data Quantitative elemental mapping of chondritic meteorites using laser ablation-inductively coupled plasma-time of flight-mass spectrometry (LA-ICP-TOF-MS)English</p>
Supporting Information for Complementary Elucidation of the Molecular Characteristics of Groundwater Dissolved Organic Matter using Ultrahigh-Resolution Mass Spectrometry Coupled with Negative and Positive-Ion Electrospray Ionization
<p>These four spreadsheets are Table S1, Table S2, Table S3 and Table S4 of the Supporting information for the ES&T manuscript entitled "<strong>Complementary Elucidation of the Molecular Characteristics of Groundwater Dissolved Organic Matter using Ultrahigh-Resolution Mass Spectrometry Coupled with Negative and Positive-Ion Electrospray Ionization</strong>".</p>
Structural characterization of the protein-material interfacial interactions by using lysine reactivity profiling-mass spectrometry
<p>The exploration of interfacial molecular interactions of protein-material integrations and how material modulate the protein structure and activity are essential to the safety evaluation of biomedical micro/nanomaterials, toxicity estimation and design of nano-drugs, and catalytic activity improvement of bio-inorganic functional hybrids. However, characterizing the interfacial molecular details of protein-micro/nanomaterial hybrids remains a great challenge. Herein, we introduce the protocol of lysine reactivity profiling-mass spectrometry (LRP-MS) strategy for probing the interfacial molecular structures between proteins and micro/nanomaterials. LRP-MS utilizes lysine residues as the endogenous probes to characterize the protein localization orientation, interaction sequence regions, binding sites, and modulated protein structures in the protein-material hybrids, which cannot be achieved by traditional spectroscopy methods. We describe the optimized heavy and light two-step isotope dimethyl labeling strategy for protein-material hybrids under their native and denaturing conditions in sequence. The comparative quantification results of lysine reactivity (referred as NLE) are only dependent on the native microenvironments of lysine local structures. We also highlight other critical steps including protein digestion, elution from materials, data processing, and interfacial structure analysis. The two-step isotope labeling steps need about 5 h, and the whole protocol including digestion, liquid chromatography-tandem mass spectrometry, data processing, and structure analysis needs about 3-5 days.</p>
Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics
<p>Protein glycosylation — a complex and heterogeneous post-translational modification frequently dysregulated in disease — has been difficult to analyse at scale. Here we report a data-independent-acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named ‘OxoScan-MS’, identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive, untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from COVID-19 patients and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.</p>
Fig. 2 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 2. Workflow for sample preparation and injection. Culture samples were filtered and dried (A–B). Dried filter papers were placed in clean vials (C) and then resuspended in methanol (D) before being extracted with Chloroform (E). Water was added (F) and subsequently, the chloroform layer was aliquotted into GC vials (G) for further sample preparation. Extracts were dried (H) and then derivatized using a two-step methoximation/silylation process to yield derivatized extracts (I). 9-μL aliquots of derivatized extracts were automatically transferred to microvial inserts in thermal desorption tubes for injection (J) using an initial solvent vent step to remove excess solvent and derivatisation reagents (K), followed by thermal desorption to a cooled PTV inlet and subsequent splitless injection to the GC × GC-TOFMS system. Non-volatile residues from the extracts remained in the microvial insert for subsequent disposal (L). See text for details.
Fig. 4 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 4. From left to right: results of principal component analysis of the raw data (autoscaled), similarly scaled data normalised to class-specific TUPA, and the normalised, scaled data using the selected features from the FS-CR routine. Quality control samples were not included in the feature selection routine, and are displayed as filled icons connected to their corresponding replicate with a straight line, following projection into the optimised principal component space. Confidence ellipses were drawn about each sample class for a confidence interval of 0.95. Note the convention: DUN refers to D. tertiolecta samples, CO refers to co-culture samples, and BAC refers to P. italicus R11 samples.
Fig. 5 in Molecular differentiation of Panax notoginseng grown under different conditions by internal extractive electrospray ionization mass spectrometry and multivariate analysis
Fig. 5. Multivariate statistical analysis results of 9 different types of Panax notoginseng samples. (a) Score scatter plot of 2D PCA model, (b) Score scatter plot of 3D PCA model, (c) Score scatter plot of OPLS-DA model, (d) Bar plot with OPLS-DA model of VIP.
Fig. 4 in Molecular differentiation of Panax notoginseng grown under different conditions by internal extractive electrospray ionization mass spectrometry and multivariate analysis
Fig. 4. Tandem MS analysis of characteristic ions in Panax notoginseng samples. (a) MS3 spectrum of m/z 1143 → 1107→, (b) MS3 spectrum of m/z 1193 → 1149→, (c) MS3 spectrum of m/z 885 → 841, (d) MS3 spectrum of m/z 1031 → 987, (e) MS3 spectrum of m/z 1245 → 1209, (f) MS3 spectrum of m/z 968 → 931.
Fig. 3 in Molecular differentiation of Panax notoginseng grown under different conditions by internal extractive electrospray ionization mass spectrometry and multivariate analysis
Fig. 3. Mass spectra of different types of Panax notoginseng samples analyzed by iEESI-MS. (a) Mass spectrum of Panax notoginseng from Kunming, (b) Mass spectrum of Panax notoginseng from Qujing, (c) Mass spectrum of Panax notoginseng from Hongjiaozhou, (d) Mass spectrum of Panax notoginseng from Wenshan (1 year), (e) Mass spectrum of Panax notoginseng from Wenshan (2 year), (f) Mass spectrum of Panax notoginseng from Wenshan (3 year), (g) Mass spectrum of Panax notoginseng from Hongjiaozhou (black soil), (h) Mass spectrum of Panax notoginseng from Hongjiaozhou (white soil), (i) Mass spectrum of Panax notoginseng from Hongjiaozhou (red soil). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Molecular differentiation of Panax notoginseng grown under different conditions by internal extractive electrospray ionization mass spectrometry and multivariate analysis
Fig. 2. Chemical structures of eight ginsenosides used in this study as reference standards. G, ginsenoside; NG, notoginsenoside; glc, glucoside; rha, rhamnoside; xyl, xyloside; ara, arabinoside.
Fig. 1 in Molecular differentiation of Panax notoginseng grown under different conditions by internal extractive electrospray ionization mass spectrometry and multivariate analysis
Fig. 1. Schematic illustration of iEESI-MS for direct analysis of Panax notoginseng samples. (a) Analytical procedure of Panax notoginseng analysis by iEESI-MS. Approximately 0.1 mg of Panax notoginseng tissue was loaded into the sample chamber by punching without sample pretreatment, (b) Disposable iEESI device and its components, (c) Photo of iEESI-MS interface.
Fig. 4 in Distribution of 5,6-dihydro-α-pyrones by electrospray ionization ion trap mass spectrometry in different aerial parts of Hyptis monticola
Fig. 4. UHPLC base peak ion chromatogram of CH2Cl2-soluble extract from leaves of Hyptis monticola. UHPLC-ESI-MS instrumental conditions: column C-18 (2.1 × 150 mm, 2 μm); mobile phase, gradient CH3CN:H2O; flow rate, 0.25 mL/min. Peaks assignments: tR 36.7 min =monticolide A (1); tR 27.6 min = monticolide B (2), tR 23.6 min = monticolide C (3); tR 29.6 min = monticolide D (4); tR 31.1 min = monticolide E (5); tR 19.1 min = monticolide F (6).
Fig. 6 in Distribution of 5,6-dihydro-α-pyrones by electrospray ionization ion trap mass spectrometry in different aerial parts of Hyptis monticola
Fig. 6. Average for the relative quantification of monticolides A-F (1–6) in different plant organs (n = 15, mean with SD).
Fig. 3 in Distribution of 5,6-dihydro-α-pyrones by electrospray ionization ion trap mass spectrometry in different aerial parts of Hyptis monticola
Fig. 3. Comparison of leaves extracts base peak chromatograms obtained with different solvents by UHPLC-ESI(+)-IT-MS. Analytical conditions: gradient mobile phase of CH3CN and 0.1% (v/v) aqueous formic acid; flow rate 0.25 mL/min; column C-18, 2.1 × 150 mm, 2 μm; sample concentration 0.5 mg/mL; mass spectrometry detection with ESI ionization in positive mode in the range of m/z 200 to 500. Peaks assignments: monticolides A-F, compounds 1–6.
Fig. 2 in Distribution of 5,6-dihydro-α-pyrones by electrospray ionization ion trap mass spectrometry in different aerial parts of Hyptis monticola
Fig. 2. Recycling HPLC chromatogram for the separation of diacetylated monticolides B (2) and C (3) from the CCC fractions 8–12 (see, Fig. S1). Chromatographic conditions: mobile phase CH3CN; flow rate, 4.7 mL/min; NH2 column, 19 × 150 mm, 10 μm, DAD detector (290 nm); sample concentration, 30 mg/mL.
Fig. 5 in Distribution of 5,6-dihydro-α-pyrones by electrospray ionization ion trap mass spectrometry in different aerial parts of Hyptis monticola
Fig. 5. PCA score plot of different extracts based on the relative abundances of total diagnostic ions for the distribution of monticolides A-F (1–6), which were registered by UHPLC-ESI(+)-IT-MS. Extracts prepared from flowers (HFL), leaves (HFO) and branches (HG). Codes were assigned according to the corresponding season and altitude as follows: HFL1, HFO1 and HG1-Spring collected at a low-altitude (1229 m) in 2013; HFL2, HFGO2 and HG2-winter collected at a low-altitude (1245 m) in 2017; HFL3, HFO3 and HG3-winter collected at a high-altitude (1310 m) in 2017; HFL4, HFO4 and HG4-summer collected at a low-altitude (1245 m) in 2018; and HFL5, HFO5 and HG5-summer collected at a high-altitude (1310 m) in 2018.
Fig. 5 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 5. DESI-MS/MSI of OPDA and OPC-8 in the developing Phaseolus vulgaris seeds. (a) Optical image of the seed section for OPDA analysis. (b) MS/MS spectrum of precursor ion at m/z 291.1966 ± 1 Da obtained at the target enhanced mode for m/z 165.1. (c) Ion image at m/z 165.1300. (d) Optical image of the seed section for OPC-8:0 analysis. (e) MS/MS spectrum of precursor ion at m/z 293.2122 ± 1 Da obtained at the target enhanced mode for m/z 225.1. Ion images at m/z (f) 223.1400 and (g) 231.2142. Scale bar = 2 mm. Compound names are defined in Table 1.
Fig. 4 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 4. LC-ESI-MS/MS analysis of JA-related compounds in the extracts from the radicle and seed coat of developing Phaseolus vulgaris seeds. MS/MS spectra of peaks at (a) 5.3 min in Fig. 3c, (b) 5.3 min in Fig. 3d, (c) 6.5 min in Fig. 3c and (d) 6.5 min in Fig. 3d and (e) 6.3 min in Fig. 3e and (f) 6.3 min in Fig. 3f and (g) 6.4 min in Fig. 3e, (h) 6.4 min in Fig. 3f, (i) 6.7 min in Fig. 3e, and (j) 6.7 min in Fig. 3f. Compound names are defined in Table 1.
Fig. 2 in Unique localization of jasmonic acid-related compounds in developing Phaseolus vulgaris L. (common bean) seeds revealed through desorption electrospray ionization-mass spectrometry imaging
Fig. 2. LC-ESI-MS/MS analysis of JA-related compound standards. Spectra of (a) OPDA, (b) OPC-8:0, and (c) JA standards. Compound names are defined in Table 1.
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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.