Identification from discovery data was performed using the Bos taurus proteome (UniProt proteome ID UP000009136, n23868, downloaded 08/06/2015) with Proteome Discoverer 2.3 software (ThermoFisher Scientific). The processing workflow consisted of the following nodes: Spectrum Selector for spectra pre-processing (precursor mass range: 350–5000 Da; S/N Threshold: 1.5), Sequest-HT search engine (Protein Database: see above; Enzyme: Trypsin; Max. missed cleavage sites: 2; Peptide length range 6–144 amino acids; Precursor mass tolerance: 10 ppm; Fragment mass tolerance: 0.02 Da; Static modification: cysteine carbamidomethylation; and Percolator for peptide validation (FDR < 1% based on peptide q-value). Results were filtered to keep only the Master protein with at least one unique peptide, and protein grouping was allowed according to the parsimony principle. For label-free quantification (LFQ), the sum of the top 3 peptides for each protein was taken to reflect the intensity of the protein. Peptide intensities were quantified using a proprietary algorithm developed in Proteome Discoverer 2.3 (ThermoFisher Scientific).
Proteome discoverer 2
Manufactured by Thermo Fisher Scientific
Sourced in United States, Germany, United Kingdom, China, France
Proteome Discoverer 2.2 is a software application designed for protein identification and quantification in mass spectrometry-based proteomics experiments. It provides a comprehensive platform for data processing, analysis, and workflow management.
Automatically generated - may contain errors
Lab products found in correlation
Sequest ht, by Thermo Fisher Scientific (33 mentions)
Mascot 2, by Matrix Science (23 mentions)
Mascot, by Matrix Science (17 mentions)
Q exactive mass spectrometer, by Thermo Fisher Scientific (14 mentions)
Trypsin, by Promega (13 mentions)
Easy nlc 1200, by Thermo Fisher Scientific (12 mentions)
Q exactive, by Thermo Fisher Scientific (12 mentions)
Q exactive plus, by Thermo Fisher Scientific (11 mentions)
Q exactive hf x mass spectrometer, by Thermo Fisher Scientific (11 mentions)
Q exactive hf mass spectrometer, by Thermo Fisher Scientific (10 mentions)
Orbitrap fusion, by Thermo Fisher Scientific (7 mentions)
Q exactive plus mass spectrometer, by Thermo Fisher Scientific (7 mentions)
Orbitrap fusion lumos mass spectrometer, by Thermo Fisher Scientific (7 mentions)
Easy nlc 1000, by Thermo Fisher Scientific (7 mentions)
Orbitrap exploris 480, by Thermo Fisher Scientific (7 mentions)
Orbitrap fusion mass spectrometer, by Thermo Fisher Scientific (6 mentions)
Ultimate 3000, by Thermo Fisher Scientific (6 mentions)
Easy nlc 1200 system, by Thermo Fisher Scientific (6 mentions)
Tmt reagent, by Thermo Fisher Scientific (5 mentions)
Easy nlc, by Thermo Fisher Scientific (5 mentions)
736 protocols using proteome discoverer 2
1
Bovine Proteome Identification and Quantification
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Proteomic Analysis of Skim Milk and MFGM Fractions
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Peptide Analysis of BM-MSC Secretome
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Peptide analysis of the culture media samples from BM-MSC under TNFα and C1 conditions (3 samples each condition) was carried out by quadrupole-orbitrap nano-HPLC-ESI-MS/MS. Culture media was lyophilized and dissolved in water. Gel-assisted proteolysis was performed for the proteins entrapped in a polyacrylamide gel matrix. Protein digestion and sample preparation were carried out using DigestPro MSI (INTAVIS Bioanalytical Instruments AG, Cologne, Germany). Peptides were purified and concentrated using C18 ZipTip (Merck Millipore) according to the manufacturer’s instructions. Samples were injected into an Easy nLC 1200 UHPLC system coupled to a Q Exactive™ HF-X Hybrid Quadrupole-Orbitrap Mass Spectrometer (ThermoFisher). Data was acquired using Tune 2.9 and Xcalibur 4.1.31.9 (ThermoFisher). Swiss-Prot database was used to identify Mus musculus proteins. These proteins were analyzed using Proteome Discoverer 2.2 (Thermo Fisher) and the tandem mass spectrometry data analysis program SEQUEST. The false discovery rate (FDR) was calculated using Percolator. Minora feature detector in Proteome Discoverer 2.2 (Thermo Fisher) was used for the label-free quantification.
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Proteomic Analysis of Skim Milk and MFGM Fractions
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For statistical analysis, PROC MIXED of SAS 9.4 (SAS Institute Inc., Cary, NC) was performed, including treatment (GLH vs. GLAH) as the fixed effect and milk parameter as the dependent variable. Treatment least squares means were compared using the probability of differences (PDIFF) option and included a Tukey adjustment test. Of the 76 proteins identified in the skim milk fraction and 367 proteins identified in the MFGM-associated fraction through Proteome Discoverer 2.2 (Thermo Fisher Scientific), 68 skim milk-associated proteins and 365 MFGM-associated proteins were present in enough samples to be statistically analyzed, and proteins that were included in statistical analysis were included in bioinformatic characterization. For bioinformatic analysis, proteins that were uncharacterized in Proteome Discoverer 2.2 (Thermo Fisher Scientific) were identified by obtaining their FASTA sequence through UniProt (Chen et al., 2017 (link)) and searching this sequence in BLAST (Camacho et al., 2009 (link)). Identified proteins were then annotated according to their biological processes, molecular functions, and cellular components through gene ontology (GO ) using the PANTHER classification system (Mi et al., 2017 (link)). All GO data presented are the percentage of gene hits against the total number of genes identified. Statistical differences were declared significant if P ≤ 0.05.
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Quantitative Proteomics Analysis Pipeline
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Processing of the raw data generated from LC-MS/MS analysis and protein identification and quantification were carried out using Proteome Discoverer 2.0 (Thermo Fisher Scientific, Bremen, Germany) and Sequest HT (Sequest HT algorithm, license Thermo Scientific, registered trademark University of Washington, USA). Protein label-free quantification was prepared according to the intensities of the precursor ions signal. For protein identification the following search parameters were used: peptide mass tolerance set to 10 ppm, MS/MS mass tolerance set to 0.02 Da, mass precision was set to 2 ppm, up to two missed cleavages allowed, minimal peptide length was set to six amino acids, cysteine carbamidomethylation, and carboxymethylation, methionine oxidation and 4-HNEcysteine/lysine/histidine adducts formation set as a dynamic modification [21] (link). For each protein, minimal number of identified unique peptides was set to two peptides. Input data were searched against the UniProtKB-SwissProt database (taxonomy: Homo sapiens, release 2017-08). Protein grouping was performed according to molecular function using the Gene Ontology (GO) database available in the Proteome Discoverer 2.0 (Thermo Fisher Scientific, Bremen, Germany).
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Differential Proteomic Analysis of Samples
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Each sample was analyzed on a Thermo Scientific Orbitrap Fusion Lumos MS via 3 technical replicate injections using data-dependent acquisition (DDA) HCD MS2 instrument method outlined in Table S1. The technical replicates were blocked, and each block was randomized. Pooled QCs, which are a mixture of all the samples being analyzed, were analyzed at the start, end, and in between each sample block. MS data were analyzed using Proteome Discoverer 2.4 (Thermo Fisher Scientific, Waltham, MA) platform, as outlined in Table S2. Protein identifications were filtered to include only those proteins identified by two or more unique peptides identified.
Differential expression calling was performed on normalized read count data generated by Proteome Discoverer 2.4 (Thermo Fisher Scientific, Waltham, MA) using integrated Differential Expression and Pathway (iDEP) analysis (http://bioinformatics.sdstate.edu/idep/ ) tool.28 (link) Box plots for data normalization and sample variance were assessed as part of quality control (Supplementary Figure 2 ). Gene enrichment analysis was subsequently performed on differentially expressed gene lists using ShinyGO 0.76 (http://bioinformatics.sdstate.edu/go/ ) to identify altered biological pathways between groups.
Differential expression calling was performed on normalized read count data generated by Proteome Discoverer 2.4 (Thermo Fisher Scientific, Waltham, MA) using integrated Differential Expression and Pathway (iDEP) analysis (
7
Quantitative Proteome Analysis of Irrigated and Rainfed Seeds
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Proteome Discoverer 2.4 (Thermo Fisher Scientific, Massachusetts, United States) was used to determine peptide and protein abundance. First, mass recalibration was performed with Sequest HT comparing database and identified proteins, getting a chromatography alignment of the samples with a tolerance of up to 10 min. Then, an alignment of the retention time of all samples was performed to quantify precursor ions (considering unique peptides that were present in, at least, two of the three replicates). Finally, the total protein amount was normalized among samples using peptide total abundance. Also, Proteome Discoverer 2.4 (Thermo Fisher Scientific, Massachusetts, United States) was used to represent the Principal Component Analysis (PCA) and the heat map with the common and exclusive proteins found in each biological replicate of the seeds harvested from irrigated and rainfed conditions (Supplementary Figures S2 and S3 ).
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Quantitative Deamidation Analysis by MS
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Protein identification was performed using the Homo sapiens taxonomy (20,200 sequences) setting of the Swiss-Prot database (SwissProt_2015_06) with Proteome Discoverer 2.1 (version 2.1.1.21, Thermo Scientific) as previously described (53 (link)). Quantification of MS1 precursor ions was analyzed using the Proteome Discoverer 2.1 (version 2.1.1.21, Thermo Scientific). A relative quantification approach was used for deamidation measurement as follows: The ratio of a deamidated peptide/total peptide was used to represent the abundance of the deamidated peptide. The ratio of a specific deamidated peptide across the samples was standardized (z score); the mean standardized values of the peptides derived from one protein were used to represent the level of deamidated protein abundance.
9
XRCC6-FOXL2 Interaction Analysis
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Equimolar (~100 μM) amounts of XRCC6 (aa 1-609) and the FH domain of FOXL2 (aa 46-158) were mixed in a buffer containing 20 mM HEPES pH 7.5 and 200 mM NaCl. BS3 (Thermo Fisher Scientific) was added to the protein mixture to a final concentration of 1 mM. The mixture was incubated for 30 min at room temperature with mild shaking (350 rpm) on a thermomixer (Eppendorf, Hamburg, Germany). The cross-linking reaction was quenched by adding 1 M Tris-HCl pH 7.5 to a final concentration of 50 mM. The crosslinked products were analysed by SDS-PAGE. Bands from the SDS-PAGE gels corresponding to crosslinked complexes were excised, and the proteins were reduced, alkylated, digested with trypsin (Thermo Fisher Scientific), and desalted using ZipTip C18 (Millipore, Burlington, MA, USA). Final eluates were resuspended in 0.1% (v/v) formic acid. Samples were analysed by LC-MS/MS analysis on a Q Exactive mass spectrometer (Thermo Fisher Scientific). Data analysis was performed by xQuest59 (link) and Proteome Discoverer 2.3 (Thermo Fisher Scientific), using a sequence database containing the two target proteins, and validated by xProphet60 (link). Crosslinks with deltaS < 0.95 were used for structural analysis.
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Proteome Discoverer 2.3 Peptide Identification
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