ProteinPilot Software 5.0 (AB Sciex, Concord, Ontario, Canada) was used to search the database HUMAN_uniProt to identify the differentially expressed proteins. Gene Ontology (GO) annotations (http://www.geneontology.org ) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis (http://www.kegg.jp/kegg/pathway.html ) were conducted to analyze differentially abundant proteins, functional classifications, or signal transduction pathways.
Proteinpilot software 5
Manufactured by AB Sciex
Sourced in United States
ProteinPilot Software 5.0 is a bioinformatics software program designed for the analysis of mass spectrometry data. The software's core function is to facilitate the identification and quantification of proteins in complex samples.
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16 protocols using proteinpilot software 5
1
Protein Profiling and Pathway Analysis
2
Quantitative Proteomic Analysis of Endothelial Cells
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ProteinPilot Software 5.0 (ABSciex, Redwood City, CA, USA) was used to identify and quantify differentially expressed proteins (DEPs) from the LC-MS/MS data. To further understand the impact of DEPs on endothelial cells and to investigate relationships between the DEPs, gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interaction (PPI) analyses were performed. GO enrichment was performed for biological process, molecular function, and cellular component, and was applied based on Fisher’s exact test considering the whole quantified protein annotations as the background dataset. The Benjamini-Hochberg correction for multiple testing was further applied to adjust the derived P values. In our iTRAQ proteomic analysis, the screening was based on the following criteria: P<0.05 and fold change (FC) ratio ≥1.3 or ≤0.76. GO terms with P<0.05 and false discovery rate (FDR) <0.05 were considered significantly enriched. KEGG pathway enrichment was performed using the clusterProfiler package in R software (version 3.6.0) based on the KEGG pathway database (http://www.kegg.jp/kegg/pathway.html ). PPI network analysis was performed according to the STRING database (http://string-db.org/ ). Then, the results were imported into CytoScape software for visualization.
3
Protein Identification and Quantification
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ProteinPilot Software 5.0 (AB SCIEX) was used for identification of proteins and relative iTRAQ quantification. ProteinPilot utilizes Paragon™ database search algorithm (5.0.0.0.4767) and non-linear fitting method to determine the integrated false discovery rate (FDR) for peptide identification and quantification (Shilov et al., 2007 (link); Tang et al., 2008 (link)). For FDR calculation, an automatic decoy database search strategy (Choi and Nesvizhskii, 2008 (link)) was used to estimate FDR using the PSPEP (Proteomics System Performance Evaluation Pipeline Software) algorithm. Only proteins with at least one unique peptide and unused value more than 1.3 were considered for further analysis. Protein lists were interpreted according to fold change in expression. The cut-off for high abundance (> 1.5-fold over normal, P < 0.05) and low abundance (< 0.67-fold over normal, P < 0.05) proteins were selected to identify differentially abundant proteins (DAPs) based on biological replicate method.
4
Proteomic Analysis of Differential Protein Expression
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Protein Pilot Software 5.0 (AB SCIEX, USA) was used to analyze peptide data. Proteins with ≥1 unique peptide and unused value >2 were selected for subsequent assessments. Log2 FC (fold change) > 2.0, p < 0.01, and CV < 0.5 were used to establish significantly differentially expressed proteins. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted using the DAVID (http://david.abcc.ncifcrf.gov ) tool to determine the functions of selected proteins. Protein-protein interaction network (PPI) analysis was conducted using the STRING tool (www.string-db.org ).
5
Quantitative Proteomic Profiling Protocol
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Protein identification and quantification was achieved using the ProteinPilot Software 5.0 (AB SCIEX) which employs the Paragon™ database search algorithm (5.0.0.0.4767) and non-linear fitting method to determine the integrated false discovery rate (FDR) for peptide identification and quantification 21 (link). An automatic decoy database search strategy 22 (link) was used to estimate FDR using the PSPEP (Proteomics System Performance Evaluation Pipeline Software) algorithm. Proteins of at least one unique peptide and an FDR value greater than 1.3 were selected for further analysis. Proteomic data were interpreted according to fold change in expression. The cut-off for high abundance (> 1.2-fold over normal, P < 0.05) and low abundance (< 0.8-fold over normal, P < 0.05) proteins were selected to identify differentially expressed proteins based on biological replicate method.
6
Mass Spectrometry Data Analysis Protocol
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The processing, retrieval and analysis of the original .wiff file data collected by mass spectrometry was conducted with Protein Pilot Software 5.0 (AB SCIEX) using the following parameters: No trypsin digestion and no cysteine modification. Variable modifications included deamidation (NQ), oxidation (M), glutamic acid (Pyro-glu), glutamine (Pyro-gln), acetylation (protein N-terminal), maximum variable modification/peptide set to 3 and no fixed posttranslational modifications. The search method was a thorough search analysis: The mass tolerance of mass spectrometry was 20 ppm, mass spectrometry was 0.1 Da, false positive rate was controlled at 1% false discovery rate and protein search unused score >1.3 was regarded as a reliable result. A peptide with confidence >95% was deemed a reliable sequence.
7
Affinity Purification and Mass Spectrometry
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For the pull-down and co-immunoprecipitation assays with magnetic beads conjugated with anti-HA antibody, lysates of the plasmid-transfected HEK-293T cells were incubated with anti-HA magnetic beads (ChemCruz, sc-500773A) at 4 °C overnight. Following intensive washing, the elution samples were analyzed by mass spectrometry and western-blotting, respectively. For mass spectrometry analysis, the pull-down samples were subjected to in-gel digestion with trypsin, following SDS-PAGE for validation. The digested peptides were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) using the nano-LC-equipped TripleTOF 5600 system (AB SCIEX). Raw tandem spectra were searched against Unified Protein database (UniProt) with the ProteinPilot Software 5.0 (AB SCIEX). The data selected for further analysis were based on the false discovery rate (FDR) of ≤ 1% for protein identification.
8
Protein Identification Using ProteinPilot
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The protein identification was carried out using the ParagonTM algorithm as the search engine in the ProteinPilotTM software (version 5.0; Applied Biosystems). Each of the RAW files created from the MS system was converted to a ProteinPilot compatible Mascot Generic Format (MGF) with preselected iTRAQ reporter ions. The MGF files were searched against the Homo sapiens database in UniProt along with contaminant protein sequences in December 2015 using ProteinPilot™ Software 5.0 (AB Sciex) and the following search parameters: Sample Type: iTRAQ 6-plex (Peptide Labeled); Cys-alkylation: MMTS; Digestion: Trypsin; ID focus: Biological modification; Use FDR analysis; Thorough search and an Unused Protscore (Conf)): ≥1.3%.
9
Proteomic Analysis of Differential Protein Expression
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Protein identification and quantification results were analyzed by ProteinPilot™ Software 5.0 (AB SCIEX) using the Paragon™ Algorithm (5.0.0.0, 4767). Each MS/MS spectrum was searched against the Uniprot/Swiss-Prot Database for Homo sapiens. Parameters for searching were as follows: (1) Detected Protein Threshold: 0.05; (2) Competitor Error Margin: 2.00; (3) Revision Number: 4769; (4) Instrument: Orbi MS (1−3 ppm), Orbi MS/MS; (5) Sample Type: iTRAQ 8 plex (Peptide Labeled); (6) Cysteine Alkylation: MMTS; (7) Digestion: Trypsin; (8) Special Factors: none; (9) ID Focus: biological modifications; (10) Search Effort: thorough ID; (11) FDR Analysis: yes; (12) User Modified Parameter Files: no. Qualification criteria for peptides were unused confidence score ≥ 1.3 and confidence level ≥ 95%. Proteins containing at least one peptide and false discovery rate (FDR) < 1% were accepted. Proteins with poor repeatability (coefficient of variation > 0.5) or no quantitative information were removed. For qualifying proteins, average fold change ≥ 1.5 was classified as upregulated and average fold change ≤ 0.67 was defined as downregulated.
10
Quantitative Proteomics of Rubber Tree
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Two independent iTRAQ experiments were carried out on the Triple TOF 6600 system (AB SCIEX). The vacuum dried peptides were labeled with the eight iTRAQ tags named 113 (D24), 114 (E24), 115 (D48), 116 (E48), 117 (D24-2), 118 (E24-2), 119 (D48-2) and 121 (E48-2), respectively. The MS analysis was performed in Information Dependent Mode. Protein identification from the rubber tree genome as described above and relative iTRAQ quantification was performed with ProteinPilot™ Software 5.0 (AB SCIEX). A strict unused confidence score >2.0 was used. The identified proteins with at least two matched peptides, confidence higher than 95%, and an FDR value ≤ 1% were used to perform protein quantification. Subsequently, proteins with 2.0-fold change (p < 0.01) were termed as DAPs in SRPs from the four biological replicates.
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