Apex3d

Shotgun quantitative label-free proteomics was performed in a nanoACQUITY UPLC system (Waters, Milford, MA, USA) coupled with a Xevo Q-TOF G2 mass spectrometer (Waters, Milford, MA, USA), as previously described [23 (link)]. Spectra were processed, and proteins were identified and quantified with Progenesis QI for Proteomics^® (Nonlinear Dynamics; Waters Corporation; version 4.0) using Apex3D (Waters) for peak detection and searching the Swiss-Prot Human proteomic database, using all the peptides for relative quantification. In order to obtain the preliminary protein dataset, the following parameters were considered: trypsin digestion with a maximum of one missed cleavage; variable modification via oxidation (M) and fixed modification via carbamidomethyl (C); false discovery rate (FDR) less than 4%; and mass error less than 20 ppm. In addition, ion-matching requirements were established to select proteins with at least one ion per peptide, three ions per protein, and one peptide per protein. Then, the final list of proteins was reduced to selected proteins identified by at least two unique peptides and proteins whose presence was detected in at least 60% of the samples.
The software CYTOSCAPE version 3.9.0 was used to build networks of molecular interactions between the identified proteins with the aid of the ClueGo and String applications.

For spectra processing and database search we used Progenesis QI for Proteomics software package with Apex3D, peptide 3D, and ion accounting informatics (Waters Corporation). The software loads LC-MS data, followed by chromatogram alignment and peak detection. A list of curated ions (peptides) are explored within Peptide Ion Stats by multivariate statistical methods; next, relative intensities for all ions are normalized among runs through total ion current. Finally, peptides are searched against a human proteome database (UniProt Human Reference Proteome, version 2015/11; 70,225 entries) for protein identification employing default parameters for ion accounting and quantitation 4. Protin database was reversed “on the fly” during the database queries and appended to the original database to assess the false-positive identification rate. The following parameters were considered for identifying peptides: 1) Digestion by trypsin with one missed cleavage allowed; 2) Methionine oxidation as variable modifications and carbamidomethyl (C) as fixed modification; 3) false discovery rate (FDR) lower than 1%. The protein identified with the highest score is chosen automatically as reference. Its intensity is used as a normalization factor for the relative quantification of all other proteins across the conditions analyzed (normalized abundance).

MS/MS spectra were aligned and analyzed with Progenesis^® QI for Proteomics (version 3.1) with Apex3D, peptide 3D, and ion accounting informatics (Waters). Proteins were identified using the reviewed Uniprot Homo sapiens database (obtained 12/2020) and quantified using the default Top3 method. The following parameters were used in the identification of peptides/proteins: digestion by trypsin with a maximum of one missed cleavage; maximum protein mass of 600 kDa; false discovery rate (FDR) less than 1% (as calculated by a reverse sequence database generated on-the-fly by Progenesis); at least two fragments per peptide, one peptide per protein, and five or more fragments per protein; at least one unique peptide per protein for quantitation; and a mass error ≤20 ppm. Proteins were considered differentially expressed when the one-way analysis of variance (ANOVA) returned a p-value < 0.05.