Label-free quantification of proteins and data analysis
The LC-MS analysis of peptides was performed using a Q-TOF Premier MS device coupled to a NanoAcquity system device (Waters Corporation, Eschborn, Germany) as described elsewhere (Jozefowicz et al., 2017). Two technical repetitions were run for the three independent experiments. Protein identification was performed using the ProteinLynx Global SERVER v2.5.3 software (Waters Corp.). The following parameters were used: automatic mass tolerance and fragment mass tolerance, one missed cleavage and variable modification: oxidation (Met), carbamidomethyl (Cys). MS data were searched against a potato database, based on the sequences from Solanum tuberosum group Phureja DM1-3 (PGSC_DM_v3.4_pep_representative, 39,031 entries) (X. Xu et al., 2011) annotated by means of the Blast2GO software (09.2014) (Conesa & Gotz, 2008) and supplemented with sequences of human keratin and trypsin. Additional annotation using the UniProt database (http://www.uniprot.org/) was performed for the proteins of interest. Protein quantification was carried out using Progenesis QI for proteomics software (Nonlinear Dynamics, Newcastle, UK). Only proteins with more than one unique peptide were included in the analysis and those with ANOVA p-values < 0.05 and a fold change > 1.5 were considered as showing a significant degree of variation. Transmembrane regions were predicted by reference to the TMHMM Server v.2.0 (http://www.cbs.dtu.dk/services/TMHMM/) (Krogh, Larsson, von Heijne, & Sonnhammer, 2001). Principal component analysis (PCA), Z-score normalization and hierarchical clustering based on the Euclidean distance method were carried out using the Perseus Framework (Tyanova et al., 2016). A full listing of the differentially expressed proteins has been placed, together with the raw data, in the IPK Gatersleben system e!DAL (Arend et al., 2014), available at: https://doi.ipk-gatersleben.de/DOI/15c49da1-7f23-4c8f-9227-5695c1218b6a/2a5bce80-0e3b-484f-8878-0a4f3afe62b9/2/1847940088.