Computational protocol: QuaNCAT: quantitating proteome dynamics in primary cells

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Protocol publication

[…] Samples were analysed on an Ultimate 3000 RSLCnano (Dionex) system run in direct injection coupled to a QExactive mass spectrometer (Thermo Scientific). Samples were resolved on a NanoEASY (Thermo Scientific) C18-reversed phase column (50 cm long, 75 μm internal diameter, 2 μm beads) at a flow rate of 300 nL min−1 using a linear gradient of 5–44% buffer B (80% acetonitrile/0.1% formic acid) over 190 min. The mass spectrometer was operated in a “Top 10” data-dependent acquisition mode with dynamic exclusion enabled (40 s). Survey scans (mass range 300-1650 Th) were acquired at a resolution of 70,000 at 200 Th with the ten most abundant multiply charged (z ≥ 2) ions selected with a 3-Th isolation window for HCD fragmentation. MS/MS scans were acquired at a resolution of 17,500 at 200 Th.Raw data were processed using MaxQuant and Proteome Discoverer 1.3 (Thermo Scientific). Searches against the UniProt human database were performed using Andromeda and Mascot respectively. Search parameters were two missed trypsin cleavage sites, cysteine carbamidomethylation fixed modification, methionine oxidation and N-terminal protein acetylation variable modifications. Peptide results were filtered to 1% false discovery rate by MaxQuant and Proteome Discoverer.Protein and peptide quantitation information were extracted from MaxQuant and Proteome Discoverer and imported into R 2.15.1. Protein extracted ion chromatograms (XICs) were used from MaxQuant without further modification. For Proteome Discoverer, “Medium” and “Heavy” protein XICs were calculated from the sum of the individual unique peptides XICs in R. Peptides with zero Medium and Heavy XICs were not considered for the calculation.Proteins that were not reproducibly quantified across replicates were removed from downstream analysis. We required proteins to have a minimum of three quantifiable unique peptides in at least two of the three biological replicates.Differential protein expression analysis was performed with LIMMA 3.14.1/Bioconductor. After protein area distributions were quantile normalized, a linear model was fitted and a moderated t-test used to assess the statistical significance of Heavy-to-Medium Protein fold changes. Proteins with a corresponding fold-change P value (adjusted for multiple hypothesis testing with the Benjamini-Hochberg method) lower than 0.05 were accepted as differentially expressed. […]

Pipeline specifications

Software tools MaxQuant, Proteome Discoverer, Andromeda, limma
Application MS-based untargeted proteomics
Chemicals Amino Acids