Comparative analysis of whey protein in goat milk throughout the lactation cycle using data-independent acquisition and data-dependent acquisition based proteomics methods

Published: 19 April 2022| Version 1 | DOI: 10.17632/s7nxbzy32p.1
Contributor:
Rongwei Han

Description

We have investigated whey proteome of goat milk at 1, 3, 30, 90, 150, and 240 d using data-independent acquisition and data-dependent acquisition quantitative proteomics approaches. The clustering and principal component analysis revealed that the protein components in goat milk was associated with specific lactation stages. Protein-protein interaction showed that fibronectin had more interaction with other proteins and was considered as a central node. Our results can provide a better understanding of the whey proteome during the lactation cycle of dairy goats and indicate which proteins are important for the development of newborns and mammary gland.

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For DIA analysis, The mass spectrometry was performed in the positive ion mode with a parent ion scanning range of 395–1205 m/z. The parameters of mass spectrometry were set as follows: (1) MS: resolution: 60,000; AGC target: 2e6; maximum injection time: 100 ms; (2) HCD-MS/MS: resolution: 15,000; AGC target: 1e6; collision energy: 30 eV. (3) DIA using an isolation width of 26 Da (containing 1 Da for the window overlap) and 32 overlapping windows were constructed covering the precursor mass range of 400–1200 Da for DIA acquisition. Protein identification and quantification The DDA raw files were analyzed using MaxQuant software (Version 2.0.3.0) to search against the database downloaded from the Uniprot database (46,754 entries of Bos taurus; 35,479 entries of Capra hircus; downloaded in December 2020). The relevant parameters were set as follows: The digestion mode was set to the Trypsin/P specificity, maximum missed cleavages at 2, fixed carbamidomethyl modification of cysteine, and variable modifications of protein N-terminal acetylation and methionine oxidation. Protein and peptide identifications were achieved at a false discovery rate and PSM of 0.01. The conditions for match between runs were set as 0.7 match time window, 0.05 ion mobility, 20 alignment time window, and 1 alignment ion mobility. The identified proteins were quantified according to the abundances of razor and unique peptides using the label-free quantitation (LFQ) workflow. The DIA raw files were also searched against the downloaded database using MaxQuant software as above-mentioned. In addition, the spectral library was established by DDA and the other parameter settings were the same as applied in the DDA procedure. Bioinformatics and statistical analysis

Institutions

Qingdao Agricultural University

Categories

Proteomics

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