SILAC sample preparation and quantitative proteomics

MCF7 cells were grown in DMEM containing heavy (¹³C, ¹⁵N) or light (¹²C, ¹⁴N) lysine and arginine supplemented with 5% dialyzed FBS for 2 weeks. Cells labeled with heavy amino acids were subjected to the heat shock and recovery treatments indicated in the figures. Control cells were maintained in standard (light) media. Cells were collected and lysed in RIPA buffer (50 mM Tris, 150 mM NaCl, 1% NP‐40, 0.25% SDS, 1 mM EDTA, and 1× Pierce™ protease inhibitor cocktail). Protein concentrations were determined by BCA assay, and experimental samples (“heavy”) were mixed with the untreated control sample (“light”) at a ratio of 1:1. 200 μg of protein samples were applied for LC‐MS/MS. Filter aided sample preparation (FASP) for LC‐MS/MS was done as described (Wiśniewski et al, 2009). The digested peptide mixtures were re‐dissolved in 0.1% formic acid in ultrapure water prior to LC‐MS/MS, and the LC‐MS/MS was performed as described (Lin et al, 2020). Protein identification and quantitation were performed by Thermo Proteome Discoverer (PD 2.1.1.2.) software against UniProt human protein database release 2016_09. Precursor ion mass tolerance was 10 ppm; fragment ion mass tolerance was 0.5 Da. The FDR of protein and peptide was 0.01. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (Perez‐Riverol et al, 2019) with the dataset identifier PXD020140.

Differentially expressed proteins were defined as those proteins that were quantified based on replicate H/L ratios with a relative standard deviation of less than 30% (RSD < 0.3) and that differed from the mean with a Z factor > 1 or < −1. Enrichment of functional terms in the proteomic datasets was done with Metascape (Zhou et al, 2019). For each protein list, pathway and process enrichment analysis has been carried out with the following ontology sources: GO Biological Processes and GO Cellular Components. The set of 5,491 human proteins detected in all combined proteomic analyses carried out was used as the enrichment background. Terms with a P value < 0.01, a minimum count of 3, and an enrichment factor > 1.5 (the enrichment factor is the ratio between the observed counts and the counts expected by chance) were collected and grouped into clusters based on their membership similarities.