Quantitative protein profiling and database searches were completed as previously mentioned [43 (link)]. Briefly, MS/MS spectra corresponding to peptide peaks were applied to the Uniprot database using Mascot™ 2.3 (Matrix Science, London, UK). The search parameters were set as follows: enzyme, trypsin; missed cleavage sites allowed, 3; fixed modification, carbamidomethyl; variable modifications, oxidation of methionine; precursor mass tolerance, 2 Da; fragment mass tolerance, 1 Da. The peptide identifications were subject to DeCyder MS software. For quantitative profiling, we selected proteins that were identified by multiple peptides with a significant Mascot score (p < 0.05) [44 (link)]. To validate MS/MS-based peptide and protein identifications, we used the Scaffold 3.06 software (Proteome Software Inc., Portland, OR, USA) and MS/MS samples were analyzed using Mascot™ 2.3 (Matrix Science, London, UK). The parameters used were as follows: peptide identification probability of >95%, protein identification probability of > 99%, and a minimum of 2 peptides.
Mascot 2
Manufactured by Matrix Science
Sourced in United Kingdom, United States, Germany
The Mascot 2.4 is a high-performance liquid chromatography (HPLC) system designed for analytical and preparative applications. It features a modular design, allowing for the configuration of various components to meet specific research or analytical needs. The Mascot 2.4 is capable of delivering a wide range of flow rates and pressure capabilities to accommodate a variety of HPLC column sizes and applications.
Automatically generated - may contain errors
Lab products found in correlation
Proteome discoverer 1, by Thermo Fisher Scientific (56 mentions)
Proteome discoverer 2, by Thermo Fisher Scientific (23 mentions)
Q exactive mass spectrometer, by Thermo Fisher Scientific (17 mentions)
Proteome discoverer, by Thermo Fisher Scientific (15 mentions)
Proteome discoverer 1, by Matrix Science (12 mentions)
Scaffold 4, by Proteome Software (11 mentions)
Q exactive plus, by Thermo Fisher Scientific (6 mentions)
Flexanalysis 3, by Bruker (6 mentions)
Dataanalysis 4, by Bruker (5 mentions)
Sequest ht, by Thermo Fisher Scientific (5 mentions)
Q exactive hf mass spectrometer, by Thermo Fisher Scientific (5 mentions)
Orbitrap elite, by Thermo Fisher Scientific (5 mentions)
Q exactive hf orbitrap, by Thermo Fisher Scientific (4 mentions)
Trypsin, by Promega (4 mentions)
Easy nlc 1200, by Thermo Fisher Scientific (4 mentions)
Bca protein assay kit, by Thermo Fisher Scientific (4 mentions)
Proteinscape 3, by Bruker (4 mentions)
Proteome discoverer, by Matrix Science (4 mentions)
Gps 3, by Thermo Fisher Scientific (4 mentions)
Proteome discoverer version 1, by Thermo Fisher Scientific (3 mentions)
358 protocols using mascot 2
1
Quantitative Proteomic Profiling and Validation
2
Quantitative Proteome Analysis of C. elegans
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Identification and relative quantification were performed using Proteome Discoverer version 2.2 (Thermo Fisher Scientific). The search was performed by matching against Caenorhabditis elegans Uniprot Database (November 2018) using Mascot 2.5.1 (Matrix Science) with a precursor mass tolerance of 5 ppm and fragment mass tolerance of 0.6 Da. Tryptic peptides were accepted with zero missed cleavage; methionine oxidation was set as a variable modification; cysteine alkylation, TMT-modification on lysine and peptide N-termini were set as fixed modifications. A percolator was used for the validation of identified proteins. TMT reporter ions were identified in the MS3 HCD spectra with 3 mmu mass tolerance, and the TMT reporter intensity values for each sample were normalized on the total peptide amount. Only peptides unique to a given protein were considered for protein quantification. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD038504 .
3
Mass Spectrometry Analysis of Akt1 Interactors
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For mass spectrometry analysis, anti-HA immunoprecipitations (IP) were performed with the whole cell lysates derived from three 10 cm dishes of HEK293 cells co-transfected with Flag-SETDB1 and HA-Akt1. The IP proteins were resolved by SDS-PAGE, and identified by Coomassie staining. The band containing Akt1 was reduced with 10 mM DTT for 30 minutes, alkylated with 55 mM iodoacetamide for 45 minutes, and in-gel-digested with trypsin enzymes. The resulting peptides were extracted from the gel and analyzed by microcapillary reversed-phase (C18) liquid chromatography-tandem mass spectrometry (LC-MS/MS), using a high resolution QExactive HF Orbitrap (Thermo Fisher Scientific) in positive ion DDA mode (Top 8) via higher energy collisional dissociation (HCD) coupled to a Proxeon EASY-nLc II nano-HPLC 60 (link). MS/MS data were searched against the Uniprot Human protein database (version 20151209 containing 21,024 entries) using Mascot 2.5.1 (Matrix Science) and data analysis was performed using the Scaffold 4.4.8 software (Proteome Software). Peptides and modified peptides were accepted if they passed a 1% FDR threshold.
4
Proteomic Analysis of Human Proteome
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Data analysis was performed with the Swissprot Homo sapiens database using Proteome Discoverer version 2.2 (Thermo Fisher Scientific, Waltham, MA). Mascot 2.5.1 (Matrix Science, London, UK) was used as the search tool with precursor mass tolerance of 10 ppm and fragment mass tolerance of 0.6 Da. One missed cleavage was accepted, mono-oxidation on methionine was set as a variable modification, and methylthiolation on cysteine was set as a fixed modification. Percolator was used for the validation of the identification results with a strict target false discovery rate of 1%, and proteins were only considered when they were identified in all replicates. The Panther classification system was used for protein class analysis and pathway classification (http://pantherdb.org/ ). Gene ontology (GO) analysis was performed using DAVID (https://david.ncifcrf.gov/ ) and the Funrich analysis tool. The mass spectrometry data were deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD033512.
5
Quantitative Proteomic Analysis of C. elegans
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Peptide and protein identification and quantification were performed using Proteome Discoverer version 2.4 (Thermo Fisher Scientific). The LC-MS files were matched against the C. elegans reference Uniprot database (May 2020) supplemented with common proteomic contaminants (26924 proteins in total) using Mascot 2.5.1 (Matrix Science, London, United Kingdom) as a database search engine with trypsin and one allowed missed cleavage as an enzyme rule, with the precursor tolerance of 10 ppm and fragment tolerance of 0.03 Da; methionine oxidation was set as a variable modification, and methylthiolation on cysteine was set as a fixed modification. Fixed Value PSM validator was used to assess the quality of peptide matches. Precursor ion quantification was accomplished via the Minora feature detection node in Proteome Discoverer 2.4, with the maximum peak intensity values used for quantification. Transfer of identifications between the runs was disabled. Abundance values for all unique peptides were used to calculate the protein abundances, and the intensity normalization was disabled.
6
Quantitative Mitochondrial Proteomics Analysis
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The raw data files were directly loaded in Proteome Discoverer v2.2 and searched against mouse or human SwissProt protein databases (42,793 and 21,008 entries, respectively) using the Mascot 2.5.1 search engine (Matrix Science Ltd.). Parameters were chosen as follows: up to two missed cleavage sites for trypsin, precursor mass tolerance 10 ppm, and 0.05 Da for the HCD fragment ions. Dynamic modifications of oxidation on methionine, deamidation of asparagine and glutamine, and acetylation of N‐termini were set. For quantification, both unique and razor peptides were requested. The final quantitative data analysis was performed with an in‐house developed R‐studio script. Submitochondrial localization was based on the data extracted from (Vögtle et al, 2017 (link)). Human homologs were mapped with DIOPT v.8.0 (Hu et al, 2011 (link)) and filtered for proteins in human MitoCarta 2.0 (Calvo et al, 2016 (link)).
7
Proteomic analysis of Pseudomonas aeruginosa
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Data were analyzed with Proteome Discoverer version 1.4 (Thermo Fisher Scientific). The database search was performed against the Swissprot P. aeruginosa database. Mascot 2.5.1 (Matrix Science, London, UK) was used as the search engine with a precursor mass tolerance of 5 ppm and fragment mass tolerance of 0.5 Da, and one missed cleavage was recognized, mono-oxidation on methionine was set as a variable modification, and methylthiolation on cysteine was set as a fixed modification. Percolator was used for the validation of the identification results with the strict target false discovery rate of 1%, and proteins were only accepted when identified in all replicates. Gene ontology analysis was performed using the Funrich analysis tool, and principal component analysis and hierarchical cluster analysis were performed with the ClustVis software. The mass spectrometry data has been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD033690.
8
Comparative Proteomic Analysis of Homo sapiens
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Data analysis was performed using Proteome Discoverer version 2.2 (Thermo Fisher Scientific, Waltham, MA). The database search was performed against the Swissprot Homo sapiens database. Mascot 2.5.1 (Matrix Science, London, UK) was used as a search engine with precursor mass tolerance of 10 ppm and fragment mass tolerance of 0.6 Da; one missed cleavage was accepted, mono-oxidation on methionine was set as a variable modification, and methylthiolation on cysteine was set as a fixed modification. Percolator was used for the validation of identification results with the strict target false discovery rate of 1%, and proteins were only considered when identified in all three replicates. For protein class analysis and pathway classification, Panther classification system was used (http://pantherdb.org/ ). Gene ontology (GO) analysis was obtained using DAVID (https://david.ncifcrf.gov/ ) and Funrich analysis tool.
9
Mass Spectrometry-based Protein Quantification
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Data analysis was performed using Proteome Discoverer version 1.4 (Thermo Fisher Scientific, Waltham, USA). The protein database for Mus musculus (February 2017, 16854 sequences) was downloaded from Swissprot. Mascot 2.5.1 (Matrix Science) was used as a search engine with precursor mass tolerance of 10 ppm and fragment mass tolerance of 0.02 Da, one missed tryptic cleavage was accepted. Mono-oxidation on methionine was set as a variable modification, methylthiolation on cysteine and TMT-6 reagent modification on lysine and peptide N-terminus were set as a fixed modification. Percolator was used for the validation of identificated results; target false discovery rate of 1% was used as a threshold to filter confident peptide identifications.
Reporter ion intensities were quantified in MS3 spectra using Proteome Discoverer 1.4 at 0.003 Da mass tolerances with reporter absolute intensity threshold of 2000. The resulting ratios were normalized on the median protein value of 1.0 in each sample.
Reporter ion intensities were quantified in MS3 spectra using Proteome Discoverer 1.4 at 0.003 Da mass tolerances with reporter absolute intensity threshold of 2000. The resulting ratios were normalized on the median protein value of 1.0 in each sample.
10
Proteomic Profiling of Extracellular Matrix
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The peak list was generated using Proteome Discoverer (Version 1.4. Thermo Fisher Scientific). The MS/MS spectra were searched with the Mascot 2.5.1 (Matrix Science, MA, USA) search algorithm using the Human UniProt Database. The following parameters were used: precursor mass tolerance (MS) 20 ppm, IT-MS/MS 0.6 Da, 3 missed cleavages; Variable modifications: Oxidation (M), Deamidated (NQ), Acetyl N-terminal protein, Static modifications: Carboamidomethyl (C). Forward/decoy search was used for false discovery rate (FDR) estimations on peptide/PSM level, and were set at high confidence, FDR 1% and medium confidence, FDR 5%. The generated protein list was curated using the Matrisome24 (link) database.
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