Human substantia nigra proteome dataset

Quantitative proteomic analysis of human post-mortem substantia nigra from patients with Parkinson’s disease (n=3) versus controls (n=3) based on sixplex TMT (TMT6) isobaric labeling which allowed protein simultaneous identification and quantification. Samples were digested and pooled after TMT6 labeling. Peptides were fractionated by OFFGEL electrophoresis (24 fractions). Each peptidic fraction was analyzed in two technical replicates by LC−MS/MS analysis on a LTQ Orbitrap XL mass spectrometer equipped with a NanoAcquity HPLC system. MS data were processed using EasyProtConv (v. 1.21). Peak lists were generated from raw data combining CID and HCD spectra, and submitted to Easyprot (v2.2) which uses Phenyx (GeneBio, Geneva, Switzerland) for protein identification [1]. Searches were conducted against UniProt Swiss-Prot database (08-Feb-2011, 525’207 entries) specifying Homo sapiens taxonomy. Trypsin was selected as the proteolytic enzyme, one missed cleavage was allowed, cysteines carbamidomethylation, TMT6 amino terminus and TMT6 lysine were set as a fixed modification whereas oxidized methionine as variable. The minimum peptide length was five amino acids and precursor error tolerance was 10 ppm. False positive ratios were estimated using a reverse decoy database [3]. Peptide z-scores were set to maintain a false positive peptide ratio below 1%. Proteins with at least two unique distinct peptide sequences were selected and clustered based on shared peptides indistinguishable by MS [4] using Isobar (v 1.3.1) package. The protein entry containing the most peptides was selected as the group reporter. For protein quantification, TMT6 reporter ion intensities were extracted, corrected for isotopic impurities as provided by the manufacturer and each channel was normalized imposing equal median intensity. Only spectra from protein specific peptides not eliminated after outlier filtering were used for quantification. Isobar R package (v 1.3.1.) was used to calculate protein ratios and select statistically significant differentially regulated proteins between the two states.