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.