Related Experiment Video
Updated: Jul 15, 2025

04:56
An Efficient Single—Person Technique for Milk Sampling from Laboratory Mice
Published on: March 28, 2025
683
Differences in Milk Proteomic Profiles between Estrous and Non-Estrous Dairy Cows
Chao Du1,2, Liangkang Nan2, Chunfang Li2,3
1College of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, China.
Animals : an Open Access Journal From MDPI
|September 28, 2023
Summary
Accurate estrus identification in dairy cows is crucial for efficient reproduction. This study identified 89 differentially expressed milk proteins, including ACACA and APOB, as potential biomarkers for estrus detection.
Area of Science:
- Animal Science
- Biochemistry
- Reproductive Biology
Background:
- Accurate estrus identification is vital for dairy cow reproductive efficiency.
- Current methods like visual observation are unreliable, necessitating novel biomarker discovery.
- Proteomics offers a promising approach for identifying non-invasive biomarkers in milk.
Purpose of the Study:
- To identify potential protein biomarkers in milk for reliable estrus detection in dairy cows.
- To utilize proteomics to compare milk protein profiles between estrus and non-estrus states.
Main Methods:
- Milk samples were collected from pregnant dairy cows on estrus (day 0) and non-estrus (day -3) days.
- Tandem mass tags (TMT) proteomics approach was employed for protein analysis.
- Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed.
Main Results:
- A total of 89 differentially expressed proteins were identified between estrus and non-estrus milk.
- 33 proteins were upregulated, and 56 were downregulated in estrus milk.
- Key proteins involved in lipid metabolism, such as ACACA, APOB, and PLIN2, were identified and linked to estrus regulation.
Conclusions:
- Specific milk proteins, particularly those involved in lipid metabolism, show potential as biomarkers for estrus detection in dairy cows.
- Further validation in larger populations is required to confirm the utility of these proposed biomarkers.

