Octreotide-induced changes in the saliva proteome
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Orbitrap Exploris 480
ORGANISM(S): Streptococcus Mitis (ncbitaxon:28037) Gamella Haemolysans Homo Sapiens (ncbitaxon:9606) Granulicatella Adiacens (ncbitaxon:46124)
SUBMITTER: 
Walter T. Lee
PROVIDER: MSV000089053 | MassIVE | Sun Mar 13 21:33:00 GMT 2022
SECONDARY ACCESSION(S): PXD032249
REPOSITORIES: MassIVE
Similar Datasets
Project description:RAW 264.7 cells were stimulated with KDO (100 ng/ml), IFN-β (300 pM) and/or 8-Br 100 μM. These ligands were applied individually or in combination with KDO for 60 min and 120 min. Total RNA was extracted using TriPure (Roche) following its protocol. Keywords: designed
2008-06-28 | GSE11449 | GEO
Project description:2 mL of preserved urine samples were precipitated overnight with 5 mL of ice-cold acetone, pellets were washed 70% acetone resuspended in 5% SDS followed by trypsin digestion of up to 100 ugs of each sample using an S-trap. One-third of tryptic peptides were microflow LC-MS/MS using an ACQUITY UPLC interfaced to an Exploris 480 high resolution mass spectrometer. After direct injection, peptides were separated on a 1 mm x 10 mm 1.7 micron ACQUITY Premier charged surface hybrid (CSH) C18 column (Waters Corp) using a flow rate of 100 microliters/min, and the DIA analysis was performed using a staggered, overlapping window method with a MS2 mass range of 400-1000, 30,000 resolution and 45 x 28 m/z windows. Direct-DIA searches and peptide/protein quantification was performed using Spectronaut 15.
2022-10-11 | MSV000090513 | MassIVE
Project description:As a pooled donor blood product, cryoprecipitate carries higher risks of pathogen transmission. Pathogen inactivation (PI) improves the safety of cryoprecipitate, but its effects on hemostatic properties remain unclear. This study investigated protein expression in samples of pathogen inactivated cryoprecipitate (PI-cryo) using non-targeted quantitative proteomics. Specifically, cryoprecipitate samples were reduced and alkylated and digested with trypsin. Approximately 50 micrograms of tryptic digests were analyzed by microflowLC-MS/MS. The LC separation used a Waters ACQUITY UPLC and a 1 mm x 150 mm 1.7 micron CSH C18 column using a flow rate of 100 microliters/min, a column temperature of 55C and a gradient of 3-28% (v/v) MeCN:H2O containing 0.1% formic acid over 60 minutes. The LC was interfaced to a Thermo Q-Exactive HF-X using the HESI-II source. The MS analysis used data-independent acquisition (DIA)-MS with a 120,000 resolution precursor ion (MS1) scan from 375-1500 m/z, AGC target of 3E6 and maximum injection time (IT) of 20 ms. DIA-MS/MS was performed using 30,000 resolution, AGC target of 3e6 and maximum IT of 60 ms, and 27 V NCE. The DIA windows included 15 x 37 m/z windows spanning 400-941 m/z with 1 m/z overlaps; as well as 3 x 87 m/z windows spanning 941-1200 m/z. Data was analyzed using Spectronaut Pulsar X
2020-05-04 | MSV000085374 | MassIVE
Project description:We reported that the microRNA profiling of exosome isolated from 58 cerebrospinal fluid (CSF) of 38 medulloblastoma (MBL) patient with or without letomeningeal metastases (LM). CSF exosome was precipitated using Exo2DTM for RNA assay (EXOSOME plus, Suwon, South Korea) according to the manufacture’s protocol (Kim, et al. 2017). 2 ml of CSF were added to Exo2DTM reagent B following mixing by inverting, and incubated at room temperature for 30 min. The supernatant was discarded and the exosome containing pellet was resuspended in 100 ul of PBS to further RNA isolation. Total RNA was extracted from the CSF exosome fraction using a microRNA purification kit (Norgen Biotek corp., Thorold, Canada) according to the manufacture’s protocol. Briefly, samples were mixed with lysis buffer, and the lysate was added to absolute ethanol. The lysate was applied up to the column and centrifuged at 8,000 rpm for 1 min. The column was washed with wash solution and centrifuged at 14,000 rpm for 1 min. Finally, the column was applied to 20 ul of elution solution and centrifuged at 14,000 rpm for 2 min, and the flow-through was stored at –80 ℃ for storage. RNA precipitates were quantified and qualified with Bioanalyzer Pico 6000 Chip (Agilent Technologies, Santa Clara, CA). The 10 ng of total RNA was provided to the cDNA library generation using SMARTer smRNA-Seq kit (Illumina Inc., San Diego, CA), according to the user manual. The cDNA library was subjected to sequencing using Truseq SBS Kit and HiSeq 2500 System (Illumina Inc., San Diego, CA), according to user guide.
2020-09-15 | GSE157916 | GEO
Project description:Abstract Background: One of the approaches for conducting genomics research in organisms that do not yet have a proper microarray template is to profile their expression patterns by using cross-species hybridization (CSH). Several different studies using spotted microarray for CSH resulted with contradicting conclusions as to the ability of CSH to reflect biological processes. Results: We used a tomato spotted cDNA microarray to examine the ability of CSH to reflect species specific hybridization (SSH) data. Potato RNA was hybridized to spotted cDNA tomato and potato microarrays to generate heterologous and homologous hybridization data, respectively. The results revealed difficulties in obtaining transcriptomics data from CSH that reflected those obtained from SSH. Nevertheless, once the data was filtered for those corresponding to matching probe sets, by restricting proper cutoffs of probe homology, the CSH transcriptomics data better reflected those of the SSH, to an extent that was quantitated by identification of differentially regulated genes. Conclusions: This study enabled us to outline some considerations regarding evaluation of a microarray as candidate platform for CSH study, performance of CSH and proper data analysis that may allow CSH to reflect to some extent a biological process. Keywords: cross-species hybridization; heterologous hybridization
2006-05-30 | GSE3584 | GEO
Project description:Immortalized mouse macrophages (IMMs) were stimulated with 100 ng/ml lipopolysaccharide (LPS) for 0, 30, and 60 min. The samples were analyzed using LC-MS for global proteomics.
2024-02-27 | PXD046656 | Pride
Project description:Proteome quantification using TMT reagents and off-line basic peptide fractionation was done as described previously in Grand, 2021, with the exception that the isolated nuclei were used as a starting material rather than whole cells to enable detection of transcription factors which are generally less abundant proteins in the cell, and that nine channels from a TMTpro16 reagent kit were used. Briefly, mESCs, NGN2 24h induced cells and MyoD1 24h induced cells were harvested in triplicates of 10 million per sample. Nuclei were isolated by suspending in 4 ml of nuclear extraction buffer (10 mM HEPES pH 7.9, 10 mM KCl, 10 mM EDTA, 0.5% NP-40, 1 mM DTT and complete protease inhibitor (Roche)) and incubating on ice for 10 min with vortexing every 2 minutes. Nuclei were collected by centrifugation (800g, 10 min, 4 °C), washed with ice cold PBS and suspended in 1% sodium deoxycholate in 50 mM HEPES buffer (pH 8.5). The nuclear lysate was disrupted with sonication. Proteins were reduced, alkylated and Lys-C/trypsin digested. Fifty micrograms of peptides from each biological replicate were labelled using channels 128C-131C from a TMT 16plex isobaric labelling reagents kit (Lot# VJ313476, Thermo Fisher Scientific). Dried TMT-labeled peptides were dissolved in 20 μL of 10 mM ammonium formate (pH 10, high pH Buffer A), and high-pH reversed-phase chromatography was employed using an Agilent 1100 HPLC system with an autosampler, a YMC Triart C18 0.5 x 250 mm column, and a fraction collector. The peptides were separated using the following binary buffer system: high-pH Buffer A (20 mM ammonium formate in water, pH 10) and high-pH Buffer B (20 mM ammonium formate pH 10 in 90% acetonitrile) at a flow rate of 12 μL/minute. The gradient duration was a total of 115 min, with mobile phase compositions in %B as follows: 0-5 min at 2%-15%, 5-15 min at 15%-25%, 15-80 min at 25%-45%, 80-85 min at 45%-65%, 85-95 min at 65%-100%, 95-100 min at 100%, 100-101 min at 100%-2%, and 101-115 min at 2%, resulting in 48 fractions after sample concatenation. Samples were acidified with 1% TFA and dried in a speed vac. Peptides reconstituted in 2% acetonitrile, 0.1% formic acid were on-line separated on a C18 50 cm μPAC column using a EASYnLC-1000 system (all Thermo Fisher Scientific) mounted on a Digital PicoView nanospray source (New Objective), connected to an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific). Peptide elution was achieved using a linear gradient of increasing concentration of acetonitrile in 0.1% formic acid at a flow rate of 500 nl/min: 0-2 min: 2%, 2-8 min: 2-6%, 8-89 min 6-22%, 89-107 min: 22-40%, 107-111 min: 40-80%, 111-115 min: 80% (washing), 115-116 min: 80-2%, 116-120 min: 2% (equilibration). For MS data acquisition in a data-dependent mode, ions for survey MS1 scans were recorded in profile mode in the Orbitrap detector at a resolution of 120,000 in the range of 400-1400 m/z every 3 seconds for a maximum of 100 ms to reach the normalized AGC target of 50%. The most abundant precursors were selected in the quadrupole within an isolation window of 0.7 m/z for MS2 HCD fragmentation based on advanced peak determination, monoisotopic peak determination set to peptides, within charge states 2-8, dynamic exclusion of 60 s within +/-10 ppm tolerance for isotopes and different charge states, with a minimum intensity of 5e4, with normalized collision energy 34% for a maximum injection time of 200 ms to reach the normalized AGC target of 80%. MS2 HCD spectra were and recorded in the “normal” range, starting at 100 m/z at 50,000 resolution in the Orbitrap analyzer in centroid mode.
2025-08-21 | PXD054143 | Pride
Project description:Expression data from NIH-3T3 cells treated with mock, 100 U/ml IFN alpha or 100 U/ml gamma for 1 or 3h on nt-RNA labeled for 30-60 min at different times of interferon treatment Differential gene expression caused by IFN alpha or gamma was analyzed in newly transcribed RNA (nt-RNA) of NIH-3T3 cells treated for 1 or 3 h. RNA was labeled for 30 to 60 min and separated from total cellular RNA (tc-RNA) following Trizol RNA preparation and thiol-specific biotinylation We used microarrays to analyze the effects of IFNalpha and gamma treatment in newly transcribed RNA (nt-RNA) Keywords: time course
2009-09-30 | GSE9975 | GEO
Project description:The metabolome changes of Campylobacter jejuni with resistant gene ermB remain unclear. Here, we described an untargeted metabolomic workflow based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry to investigate the metabolites perturbations mediated by ermB in C. jejuni. After optimization of extractants and chromatographic conditions, the combination of 100% methanol extraction with a 12 min gradient by C18 column was adopted for untargeted metabolomic profiling in reversed phase separation. Meanwhile, 60% methanol extraction followed by a 14 min separation using hydrophilic interaction chromatography column was suitable to complementally expand the metabolite coverage of C. jejuni. Multivariate statistical analysis was performed by means of orthogonal projection to latent structures-discriminant analysis to select metabolic features. The selected features were further confirmed by ultra-high performance liquid chromatography-tandem quadrupole mass spectrometry. A total of thirty-six differential metabolites between the susceptible strain (C. jejuni NCTC 11168) and resistant stain (C. jejuni NCTC 11168 with ermB) were identified. These pivotal metabolites were primarily participated in biological processes as cell signaling, membrane integrity/stability, fuel and energy source/storage and nutrient. The biofilm formation capability of resistant strain was inferior to that of susceptible strain, confirming the influence of ermB on membrane integrity/stability of C. jejuni. Our findings revealed important metabolic regulatory pathways associated with resistant C. jejuni with ermB.
2018-08-07 | MTBLS496 | MetaboLights