Peaks studio version 10

Since ginger protease hydrolyzed gelatin more efficiently when compared with other proteases, we characterized and identified the peptides in detail. GPH was submitted to nano-liquid chromatography using EASY-nLC 1200 (Thermo Scientific, San Jose, CA, USA) coupled with Q Exactive™ Hybrid Quadrupole-Orbitrap™ Mass Spectrometer (Thermo Scientific, San Jose, CA, USA). The analysis conditions were as follows: pre-column—Acclaim PepMap RPLC C18 300 µm × 5 mm (5 µm, 100 Å; Thermo Scientific, San Jose, CA, USA); analytical column—Acclaim PepMap RPLC C18 150 µm × 150 mm (1.9 µm, 100 Å; Thermo Scientific, San Jose, CA, USA); mobile phase A was 0.1% TFA in 2% ACN (v/v) and mobile phase B was 0.1% TFA in 80% ACN (v/v); gradient—0–2 min at 4–8% B, 2–45 min at 8–28% B, 45–55 min at 28–40% B, 55–56 min at 40–95% B and 56–66 min at 95% B; and flow rate—600 nL/min. Data analysis and de novo sequencing were performed using PEAKS studio version 10.6 (Bioinformatics Solutions Inc., Waterloo, ON, Canada).

In brief, 50 µL of lyse buffer was added and heated at 95 °C for 10 min at 1000 rpm with agitation. After cooling the sample to room temperature, trypsin digestion buffer was added and the sample was incubated at 37 °C for 2 h at 500 rpm with shaking. The digestion process was stopped with a stop buffer. Sample clean-up and desalting was carried out in the iST cartridge using the recommended wash buffers. Peptides were eluted with elution buffer (2 × 100 µL) and then lyophilized via SpeedVac. The peptides were re-dissolved in solvent A (A: 0.1% formic acid in water) and analyzed via Q-Exactive Plus coupled to an EASY-nanoLC 1200 system (Thermo Fisher Scientific, Waltham, MA, USA). The mass spectrometer was run under data-dependent acquisition (DDA) mode and automatically switched between MS and MS/MS mode. The survey of full-scan MS spectra (m/z 350–1800) was acquired in the Orbitrap with 70,000 resolution. The automatic gain control (AGC) target was 3e6 and the maximum injection time was 50 ms. Tandem mass spectra were processed using PEAKS Studio version 10.6 (Bioinformatics Solutions Inc., Waterloo, ON, Canada).

Tandem mass spectra were processed by PEAKS Studio version 10.6 (Bioinformatics Solutions Inc., Waterloo, ON, Canada). PEAKS DB was set up to search the database of targets assuming trypsin as the digestion enzyme. The DB was searched with a fragment ion mass tolerance of 0.02 Da and a parent ion tolerance of 7 ppm. Carbamidomethyl on cysteine was specified as the fixed modification. Oxidation on methionine, deamination on asparagine and glutamine, and acetylation on the protein-N term on serine were specified as the variable modifications. Those peptides with no more than 1% FDR (false discovery rate) and those proteins with less than 1% FDR and containing at least 1 unique peptide were filtered for further analysis.

Peptide identification and quantification were conducted using nanoLC-MS/MS, following the method described by Osório et al. (2021) [54 (link)]. Tandem mass spectra were processed with PEAKS Studio version 10.6 (Bioinformatics Solutions Inc., Waterloo, ON, Canada). The DENOVO analysis was configured assuming no digestion enzyme, with a fragment ion mass tolerance of 0.02 Da, a parent ion tolerance of 10.0 ppm, and a maximum of 3 variable PTMs per peptide.
The identified peptide sequences were categorized based on their potential antimicrobial activity, filtering out those not expected to possess such activity. To predict the bioactivity in silico, all identified peptides were analyzed using the CAMP_R3 (Collection of Antimicrobial Peptides) [55 ] with Support Vector Machine (SVM) classifier, Random Forest (RF) classifier, Artificial Neural Network (ANN) classifier, and Discriminant Analysis classifier.
The potentially antimicrobial sequences were further analyzed to estimate their overall bioactive potential. For in silico bioactivity prediction of each peptide, a ranking was initially performed using PeptideRanker [56 ], a server that predicts bioactive peptides based on a novel N-to-1 neural network [57 (link)]. Subsequently, all these peptides were analyzed using the BIOPEP-UWM database [58 ] to estimate potential bioactivities [59 (link),60 (link)].

The PEAKS Studio version 10.6 (Bioinformatics Solutions Inc.) was employed to process tandem mass spectra. Trypsin was assumed to be a digestive enzyme when PEAKS DB was set up to search the GDP21120524 database. PEAKS DB was searched with a parent ion tolerance of 10 ppm and a fragment ion mass tolerance of 0.02 Da. TMT-11Plex (K, N-term) and Carbamidomethylation (C) were specified as the fixed modification, whereas, Acetylation (Protein N-term) and Oxidation (M) were specified as the variable modifications. Filtration of peptides was carried out using 1% FDR and proteins were filtered by means of one unique peptide. Reporter ions were used to evaluate the ratio of quantification among various samples, and normalization was derived from the total intensity of every label in each quantifiable peptide.

The peptide sequences in CPHs were identified by Shanghai Omicsolution Co., Ltd. (Shanghai, China). The desalted CPHs were dissolved in solvent A (0.1% formic acid aqueous solution). The reaction process was analyzed by Q Exactive^TM coupled to the EASY-nanoLC 1200 system (Thermo Fisher Scientific, Waltham, MA, USA). Tandem mass spectra were analyzed by PEAKS Studio version 10.6 (Bioinformatics Solutions Inc., Waterloo, ON Canada). PEAKS DB was built to search the database of uniprot_Cicer arietinum (version 202112, 24812 entries) assuming none as the digestion enzyme. The filtered proteins had −10 lgP ≥ 0, and the peptides had −10 lgP ≥ 20 and contained at least one unique peptide.