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Proteome discover version 1

Manufactured by Thermo Fisher Scientific
Sourced in United States

Proteome Discoverer version 1.4 is a software tool designed for the analysis and identification of proteins from mass spectrometry data. It provides a comprehensive platform for processing, visualizing, and interpreting proteomic data.

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3 protocols using proteome discover version 1

1

Peptide Identification in Enteroviruses

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For peptide identification, raw MS files were converted into mgf.files by Proteome Discover version 1.4 (Thermo Scientific) and processed using Sequest (Eng et al. 1994 (link)) (HT version 1.3) against a customized in-house built database with sequences from all enterovirus sequences in UniProt and the recombinant enterovirus sequence. A parent mass tolerance of 10 ppm, a fragment tolerance of 0.02 Da, a variable modification oxidation of M, a fixed modification with carbamidomethyl C and up to one missed cleavage for trypsin were used. Common MS contaminants, such as human keratin and pig trypsin were used as decoy.
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2

Comprehensive Maize Proteome Profiling

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Digested samples (1 μg/5 μL) were separated via UPLC-MS/MS system, in which the Ultimate 3000 UPLC system (Dionex, Thermo Scientific) and the Q Exactive Orbitrap mass spectrometer (Thermo Scientific, United States) were used according to Vanhove et al. (2015) (link). Data were obtained with Xcalibur 3.0.63 software (Thermo Scientific). Protein identification was realized with the conversion of the raw data by Proteome Discover version 1.4 (Thermo Scientific) into mgf files and processing with MASCOT version 2.2.06 (Matrix Science) against the Uniprot Zea mays database (99 371 proteins). Calculation of false discovery rate (FDR) was realized with Scaffold (Version: Scaffold 3.6.3; Proteome Software Inc., Portland, OR, United States). Quantification of peptides was determined using Progenesis LC-MS version 4.1 (Nonlinear Dynamics), with automatic alignment from a selected reference run. Abundance of proteins was based on sum of peptides quantification. Singular enrichment analysis (SEA) was performed for selected proteins using the AgriGO SEA tool1, with Zea mays background and significance level of 0.01. Promoter analysis was conducted using plantCARE (Lescot et al., 2002 (link)), up to 1,500 bp and using genotype B73 as the sequenced reference.
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3

Peptide Identification Pipeline for Oral Pathogens

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The peptide samples (5 µL of each sample) were digested and subsequently injected for UPLC separation by an Ultimate 3000 UPLC System (Dionex, Thermo Fisher Scientific, Waltham, USA), using an Acclaim PepMap100 pre-column (C18 3µm-100 Å, Thermo Fisher Scientific, Waltham, USA) and a C18 PepMap RSLC (2 μm, 50 μm-15 cm, Thermo Fisher Scientific, Waltham, USA) using a linear gradient (300 μL/min) of 0–4% buffer B (80% ACN, 0.08% FA) for 3 min, 4–10% B for 12 min, 10–35% for 20 min, 35–65% for 5 min, 65–95% for 1 min, 95% for 10 min, 95–5% for 1 min, and 5% for 10 min. The operational settings of the mass spectrometer and data acquisition procedure were identical to those described earlier by Khodaparast et al.55 (link). With the purpose of identification, all raw data were converted into mgf.files using Proteome Discover version 1.4 (Thermo Fisher Scientific, Waltham, USA) and processed with MASCOT version 2.2.06 (Matrix Science Ltd, London, UK) against the Uniprot A. actinomycetemcomitans, F. nucleatum, P. gingivalis or P. intermedia database. The parameters used to search with MASCOT are described elsewhere55 (link). MASCOT results were imported to Scaffold (version 3.6.3). The parameters used in Scaffold for protein identification were retaining proteins with 99% confidence and containing at least two identified peptides with a confidence level of 95%.
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