LC-MS/MS Analysis and Database Search

Dried-down peptide mixtures were analyzed in a nanoAcquity liquid chromatographer (Waters) coupled to a LTQ-Orbitrap Velos (Thermo Scientific) mass spectrometer. Tryptic digests were resuspended in 1% FA solution and an aliquot was injected for chromatographic separation. Peptides were trapped on a Symmetry C18TM trap column (5 µm 180 µm x 20mm, Waters), and separated using a C18 reverse phase capillary column (ACQUITY UPLC M-Class Peptide BEH column; 130 Å, 1.7µm, 75 µm x 250mm, Waters). The gradient used for the elution of the peptides was 1 to 40% B in 20 min, followed by gradient from 40 to 60% during 5 min (A:0.1% FA; B: 100% CAN, 0.1% FA), with a flow rate of 250 nl/min. Eluted peptides were subjected to electrospray ionization in an emitter needle (PicoTipTM, New Objective) with an applied voltage of 2,000 V. Peptide masses (m/z 300–1,700) were analyzed in data dependent mode where a full Scan MS was acquired in the Orbitrap with a resolution of 60,000 FWHM at 400 m/z. Up to the 10th most abundant peptides (minimum intensity of 500 counts) were selected from each MS scan and then fragmented in the linear ion trap using CID (38% normalized collision energy) with helium as the collision gas. The scan time settings were: Full MS: 250 ms (1 microscan) and MSn: 120 ms. Generated.raw data files were collected with Thermo Xcalibur (v.2.2).

Files obtained from mass spectrometry analyses were used to search against the public database Uniprot Actinopterygii (v.23/3/17). A database containing common laboratory contaminant proteins was added to this database. The software used as Thermo Proteome Discoverer (v1.4.1.14) with Sequest HT as the search engine. The following search parameters were applied: two missed cleavage sites as well as fixed and variable modifications; carbamidomethyl of cysteine and oxidation of methionine, respectively. Peptide tolerance was 10 ppm and 0.6 Da for MS and MS/MS spectra, respectively. Both target and decoy databases were searched in order to obtain a false discovery rate (FDR), and thus, estimate the number of incorrect peptide-spectrum matches that exceeded a given threshold. The results were filtered so only proteins identified with at least two high confidence (FDR >1%) peptides were included in the lists. To sort the search results, proteins were ranked by a first criterion of the higher Score together with and a second criterion of the higher number of Sequence Coverage and Peptides matched. The principal component analysis (PCA) was used to check the quality of the data from each replicate and identify the subsets of samples that are associated with the two different groups under study. The protein intensity values (log2-expression ratios) were represented by a hierarchical clustering heatmap analysis using MeV software (v4.0), with Pearson distance and average linkage.