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. 2021 Dec 30;10(2):307-316.
doi: 10.1002/fsn3.2300. eCollection 2022 Feb.

Investigating changes of proteome in the bovine milk serum after retort processing using proteomics techniques

Zikai Wei  1 , Jiaxin Kang  1 , Minhe Liao  1 , Huanhuan Ju  1 , Rong Fan  1 , Jiaqi Shang  1 , Xuenan Ning  1 , Meng Li  1   2
Affiliations

Investigating changes of proteome in the bovine milk serum after retort processing using proteomics techniques

Zikai Wei et al. Food Sci Nutr. .

Abstract

The objective of this study was to investigate the changes of the proteins in bovine milk serum after retort processing by label-free quantification proteomics techniques. A total of 96 and 106 proteins were quantified in control group (CG) and retort group (RG), respectively. Hierarchical clustering analysis of the identified milk serum proteins showed a decrease in the abundance of most proteins, such as serum albumin, lactoperoxidase, lactotransferrin, and complement C3, and an increase in the abundance of other proteins such as κ-casein, lipocalin 2, and Perilipin. Student's t-test showed 21 proteins significantly differential abundance between CG and RG (p < .05), of which intensity-based absolute quantification (iBAQ) of five proteins decreased and iBAQ of 16 proteins increased. Bioinformatics analysis demonstrated that retort processing increased the digestibility of proteins, but this improvement was offset by a decrease in the digestibility of proteins caused by protein modification. Our results provide insight into the proteome of retort sterilized milk for the first time. Given the extremely high security of retort sterilized milk, the proteome of bovine milk serum changes after retort sterilization exposed in this study will contribute to the formula design of retort sterilized milk products.

Keywords: LFQ; bioinformatics; bovine milk; proteomics; retort sterilized milk.

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Conflict of interest statement

The authors declare that they do not have any conflict of interest.

Figures

FIGURE 1
FIGURE 1
Protein concentration (a) and SDS‐PAGE (b) of milk serum proteins in CG and RG. CG represents unheated bovine milk serum proteins, RG represents bovine milk proteins heat‐treated by retort. The presentation of the values (a) is indicated by mean ± standard deviation (SD) of triplicate samples
FIGURE 2
FIGURE 2
Venn diagram of quantified milk serum proteins (a) and summed iBAQ (b) in CG and RG. The Venn diagram shows the number and overlap of proteins identified in CG versus RG. The summed iBAQ represents the amount of protein abundance in the CG and RG. The presentation of the values (b) is indicated by mean ± standard deviation (SD) of triplicate samples
FIGURE 3
FIGURE 3
Hierarchical clustering of quantified milk serum proteins in CG and RG. Clustering according to protein abundance (iBAQ value by LC‐MS analysis) in CG and RG. Bar color represents a logarithmic scale from −2.50 to 2.50
FIGURE 4
FIGURE 4
GO analysis for biological process (a), cellular component (b), and molecular function (c) of differential milk serum proteins. The color in the graph represents the high or low p‐value, the redder the color the larger the value; the size of the dot represents the gene number, the larger the dot the larger the value
FIGURE 5
FIGURE 5
Schematic diagram of β‐lactoglobulin determined by ELISA and LC/MS. The presentation of the values is indicated by mean ± standard deviation (SD) of triplicate samples
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