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Mascot 2.2 search engine

Manufactured by Matrix Science
Sourced in United Kingdom, United States

The Mascot 2.2 search engine is a software tool designed for the identification and characterization of proteins from mass spectrometry data. It provides a fast and efficient way to search large protein sequence databases to find the most likely matches to the experimental data.

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3 protocols using mascot 2.2 search engine

1

Proteomic profiling of CKD stages

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The CARE FOR HOME study comprises stable patients with confirmed CKD recruited at the outpatient clinic of the Saarland University Medical Center. All patients in this study were from Europe and white. The ethnicity and socioeconomic status were not collected. The study was approved by the Saarland University Ethics Committee and all participants gave their written consent.
A total of 15 measurements were performed on 5 healthy controls, 5 chronic kidney disease (CKD) stage 2 patients, and 5 CKD stage 3 patients. Plasma was prepared as described before57 (link) and a MALDI–time of flight (TOF)/TOF MS (Ultraflex III; Bruker Daltonic, Bremen, Germany) MS was performed. A database search (Swiss-Prot) using the Mascot 2.2 search engine (Matrix Science Inc, Boston, MA) and Bruker Bio-Tool 3.2 software was performed with the calibrated and annotated spectra to calculate the peptide mass signal for each entry into the sequence database, to compare the experimental MALDI-MS and MALDI-MS/MS dataset, and to assign a statistical weight to each individual peptide match using empirically determined factors.56 (link)
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2

Comprehensive Multiomics Analysis Protocol

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Microarray hybridization, nanoLC-MS/MS analysis and qRT-PCR was done with reference to our previous articles [19 (link)]. Each slide was hybridized with 1.65μg Cy3-labeled cRNA using a Gene Expression Hybridization Kit (Agilent Technologies) and a hybridization oven (Agilent Technologies). After 17 hours of hybridization, the slides were washed with Gene Expression Wash Buffer Kit (Agilent Technologies) and scanned on Microarray Scanner (Agilent Technologies). RT-qPCR was operated by using the Applied Bio-systems 7500 Fast System (Life Technologies). The fold-change in differential expression for each gene was calculated using the comparative CT method (also known as the 2−∆∆CT method).
The samples separated via capillary high-performance liquid chromatography were subsequently analyzed using a Triple TOF 5600þ system (AbSciex, USA). Protein identification and proteome annotation were performed using the ProteinPilotTM software package 4.5 (Applied Biosystems) and searched against the SwissProt database (March 2013) using the Mascot 2.2 search engine (Matrix Science, London, UK).
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3

Proteomic Profiling of Activated CD4+ T Cells

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15 × 106 CD4+ T cells from healthy controls were treated with 10% HC/SF serum and incubated for 18 h. Total protein extraction was conducted using RIPA buffer with a 1× protease inhibitor cocktail. 40 µg of protein extract was separated on a 10% acrylamide gel at 100 V for 90 min. Samples were digested with 0.02 μg/μL trypsin and ammonium bicarbonate for 24 h at 37 °C. The peptides were then desalted and concentrated by ZipTipC18 technology (Millipore, Billerica, MA, USA) with double-distilled water containing 80% acetonitrile and 0.1% trifluoroacetic acid. The eluate was spread onto a matrix-assisted laser desorption/ionization (MALDI) target plate (MTP AnchorChip 400/384 target plate, Bruker Daltonic, Bremen, Germany) with α-cyano-4-hydroxycinnamic acid used as the matrix. Subsequently a MALDI–time of flight (TOF)/TOF MS (Ultraflex III; Bruker Daltonic) MS was performed.
A database search (Swiss-Prot) using the Mascot 2.2 search engine (Matrix Science Inc., Boston, MA, USA) and Bruker Bio-Tool 3.2 software (Bruker Daltonics, Bremen, Germany) was performed with the calibrated and annotated spectra to calculate the peptide mass signal for each entry into the sequence database, to compare the experimental MALDI-MS and MALDI-MS/MS dataset, and to assign a statistical weight to each individual peptide match using empirically determined factors. Adapted/rewritten from [31 (link)].
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