iTRAQ proteomics dataset on ceramide-dependent exosomal cargoes from SW480 and SW620 cells

Cancer metastasis is largely influenced by cell–cell communication, to which exosomes play a vital role. Exosomes are small extracellular vesicles (sEVs) that originate as intraluminal vesicles (ILVs) within multivesicular bodies (MVBs) during endosome maturation. ILV formation depends on several pathways, including that of ceramide synthesis by neutral sphingomyelinase 2 [nSMase2]. Colorectal cancer (CRC)-derived sEVs are reported to carry a diverse range of metastatic cargo proteins; however, segregation of them in the ceramide-dependent sEV pool (sEVCer) remains unexplored. The current study aimed to identify the metastatic proteins that are secreted through sEVCer, from CRC cells of variable metastatic potentials. Primary (SW480) and metastatic (SW620) CRC cells were treated with nSMase2 blocker and sEVs were isolated, followed by extraction of the sEV proteins for a quantitative proteomic profiling using isobaric tags for relative and absolute quantitation (iTRAQ). In total, 1781 proteins were identified with unused protein score >1.3. Of these identified proteins, 22.8% and 17.01% were found to be depleted within sEVs of the treated SW480 and SW620 cells, respectively. These depleted protein pools represented the cargo that are preferentially secreted through sEVCer in respective cell types (CargoCer-SW480 and CargoCer-SW620). CargoCer-SW480 overrepresented integrin signalling pathway members and CargoCer-SW620 overrepresented integrin as well as platelet-derived growth factor (PDGF) signalling pathway members. Interestingly, the uniquely overrepresented CargoCer-SW480 and CargoCer-SW620 were biologically connected, rendering possible transfer of metastatic cues via sEVCer. Overall, this study identified CargoCer and their dynamics over progressive CRC stages, and thereby opens up a new research direction for exploring the flow of metastatic cues through uptake and release of sEVCer.

Methods
The dataset was generated using 2D LC followed by tandem MS.

The tandem MS analysis was performed using a 5600 Triple TOF system (SCIEX) under Information Dependent Mode. The mass range of 400–1800 m/z and accumulation times of 250 ms per spectrum were chosen for precursor ion selections. MS/MS spectra were recorded in high sensitivity mode (resolution≥ 15 000) with rolling collision energy. In each cycle, a maximum of 20 precursors were selected for fragmentation.

Peptide and Protein Identification

Protein identification and relative iTRAQ quantification were performed with ProteinPilot™ Software 5.0 (AB SCIEX, revision number 4769) using the Paragon™ Algorithm (5.0.0.0, 4767) for the peptide identification, which was further processed by Pro GroupTM algorithm where isoform-specific quantification was adopted to trace the differences between expressions of various isoforms. The Pro Group Algorithm calculates protein ratios using only ratios from the spectra that are distinct to each protein or protein form and thus eliminates any masking of changes in expression because of peptides that are shared between proteins. User-defined search parameters were as follows: (1) Sample Type: iTRAQ 8plex (Peptide Labeled); (2) Cysteine Alkylation: MMTS; (3) Digestion: Trypsin; (4) Instrument: TripleTOF 5600; (5) Special Factors: None; (6) Species: Homo sapiens; (7) ID Focus: Biological modifications; (8) Database: 20190919_SwissProt_human_20659_plus crap.fasta; (9) Search Effort: Thorough; (10) FDR Analysis: Yes, using reverse database search strategy; (11) User Modified Parameter Files: Yes. For iTRAQ quantitation, the peptide for quantification was automatically selected by the Pro GroupTM algorithm to calculate the reporter peak area, error factor (EF), and p-value. The resulting data set was auto-bias-corrected and background corrected to remove any variations imparted because of the unequal mixing during the combination of different labelled samples. This software counts each modified peptide as a unique one. The peak areas and the S/N ratios are extracted from the database by ProteinPilotTM to process the raw data to yield quantification data.

A reverse database search strategy was adopted to estimate the false discovery rate (FDR) for peptide identification. For both of our iTRAQ studies, a strict unused confidence score of 1.3 was used as the qualification criteria, which corresponds to a peptide confidence level of 95% and a global FDR of 0.6%. The results were then exported into Microsoft Excel for manual data interpretation. Subsequently, the meaningful cutoff for up-regulation (iTRAQ ratio >1.3) and down-regulation (iTRAQ ratio <0.77) of proteins was finalized at 1.3 fold as previously reported [1-4]

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