Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Aug 8:9:980963.
doi: 10.3389/fvets.2022.980963. eCollection 2022.

DIA proteomics identified the potential targets associated with angiogenesis in the mammary glands of dairy cows with hemorrhagic mastitis

Quanwei Zhang  1   2   3 , Xu Bai  1   3 , Jun Shi  1   3 , Xueying Wang  2   3 , Bohao Zhang  2   3 , Lijun Dai  1   3 , Ting Lin  1   3 , Yuan Gao  1   3 , Yong Zhang  1   2   3 , Xingxu Zhao  1   2   3
Affiliations

DIA proteomics identified the potential targets associated with angiogenesis in the mammary glands of dairy cows with hemorrhagic mastitis

Quanwei Zhang et al. Front Vet Sci. .

Abstract

Hemorrhagic mastitis (HM) in dairy cows caused great economic losses in the dairy industry due to decreased milk production and increased costs associated with cattle management and treatment. However, the pathological and molecular mechanisms of HM are not well-understood. The present study aimed to investigate differentially expressed proteins (DEPs) associated with HM according to data-independent acquisition (DIA) proteomics. Compared to the mammary glands of healthylactating Holstein cows (Control, C group), the pathology of the HM group displayed massive alveolar infiltration of hemocytes and neutrophils, and the blood vessels, including arteriole, venules and capillaries were incomplete and damaged, with a loss of endothelial cells. DIA proteomics results showed that a total of 3,739 DEPs and 819 biological process terms were screened in the HM group. We focused on the blood, permeability of blood vessel, vascular and angiogenesis of mammary glands, and a total of 99 candidate DEPs, including 60 up- and 39 down-regulated DEPs, were obtained from the Gene Ontology (GO) and Pathway enrichment analyses. Phenotype prediction and function analysis of the DEPs revealed that three DEPs, particularly Caveolin-1(CAV1), were participated in the regulation of angiogenesis. Immunohistochemical and immunofluorescence staining showed that the CAV1 protein was present mainly in the mammary epithelial cells, vascular endothelial cells and vascular smooth muscle cells. The expression level of CAV1 mRNA and protein in the HM group was significantly down-regulated. The results will be helpful to the further understanding of the pathological and molecular mechanisms of HM in dairy cows.

Keywords: CAV1; DIA proteomics; angiogenesis; blood and cow; hemorrhagic mastitis.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Pathological observation of the mammary glands in the Holstein cows. (A,B) Pathological variations of the alveoli in the mammary glands of the C and HM groups (100 ×). (C–H) Pathological variations of the arterioles (C,D), venules (E,F), and caillaries (G,H) in the mammary glands of the C and HM, respectively (100 ×). MEC, mammary epithelial cells; MA, mammary gland alveolar; RBC, red blood cell; NEUT, neutrophil; LY, lymphocytes; VEC, vascular endothelial cell; VSMC, vascular smooth muscle cell; Con, control group; HM, hemorrhagic mastitis group. Scale bar of 50, 100, and 20 μm represents 400×, 200 x, and 800 × magnification, respectively.
Figure 2
Figure 2
Summary of the proteome analysis, protein identification and annotation in DIA data. (A) statistics for the peptides and proteins identification. (B) peptides number distribution analysis. The percentage represents the proportion of the number of peptides constituting the proteins. (C) statistics for the DEPs compared to the C group. (D) statistics for the GO terms including BP, MF, and CC, and pathway annotation. BP, biological process; MF, molecular function; CC, cellular component. (E,F) The top 20 biological process in GO annotation and the top 20 pathways in pathway annotation, respectively. Con, control group; HM, hemorrhagic mastitis group; GO, gene Ontology terms.
Figure 3
Figure 3
The candidate DEPs selected from the 3,739 DEPs and GO terms related to angiogenesis. (A) the GO terms selected from the 819 significantly different biological processes related to blood, vascular or vasculature, and angiogenesis in the DIA data. (B) Venn diagram of the 59 DEPs related to blood and vasculature or vascular development. (C) Volcano plots of the 24 co-expressed DEPs. (D) Heat-map of the representative 24 co-expressed DEPs. Con, control group; HM, hemorrhagic mastitis group.
Figure 4
Figure 4
PPI network of the 59 candidate DEPs and 25 GO terms related to blood, vascular and angiogenesis.
Figure 5
Figure 5
The candidate DEPs and pathways related to blood, vascular or vasculature, and angiogenesis. (A) the candidate pathways related to blood, vascular or vasculature, and angiogenesis selected from the 68 significantly different pathways according to KEGG annotation of the 3,739 DEPs. (B) heat-map of the 49 DEPs selected from the four significantly different pathways. (C) Volcano plots of the 49 DEPs including 10 down-regulated and 39 up-regulated proteins. (D) Upset Venn diagram of the 49 DEPs and the four pathways. Con, control group; HM, hemorrhagic mastitis group.
Figure 6
Figure 6
Identification and functional analysis of DEPs related to blood, vascular or vasculature, and angiogenesis selected from the GO terms and KEGG pathways. (A) Venn diagram of the DEPs related to blood, and vasculature or vascular selected from the GO terms and KEGG pathways. (B) Heat-map of the nine shared DEPs selected from the GO terms and KEGG pathways. (C) the relative expression levels of the nine shared DEPs quantified by DIA proteomics using log2 (FC) values. (D) PPI network of the 99 DEPs after overlapping GO terms and KEGG pathways. (E) phenotype prediction and functional analysis of the nine representative DEPs. Con, Control group; HM, Hemorrhagic mastitis.
Figure 7
Figure 7
The subcellular location, mRNA and protein analysis of CAV1 in the mammary glands of healthy Holstein cows with hemorrhagic mastitis. (A1–D1,A2–D2) the subcellular location of CAV1 protein in the alveolus, arteriole venules and capillaries of the mammary glands in the C and HM groups, respectively. (A3–D3,A4–D4) the negative control mammary glands of Holstein cow, respectively. (E,F) the relative expression of CAV1 mRNA and protein in the C and HM groups, respectively. MEC, mammary epithelial cells; MA, mammary gland alveolus; VEC, vascular endothelial cell; VSMC, vascular smooth muscle cell; NEUT, neutrophil; VV, venous valve; Con or C, control group, the mammary gland of healthy Holstein cow; HM, hemorrhagic mastitis group, the mammary gland of Holstein cow with hemorrhagic mastitis. Scale bar of 50 and 20 μm represents 400 × and 800 × magnification, respectively. *, significant difference; **, extremely significant difference.
Figure 8
Figure 8
Co-localization analysis, via immunofluorescent staining, of CAV1 protein in the mammary gland tissues of healthy and hemorrhagic mastitis Holstein cows. (A1–A6) the nuclei of different types of cells labeled with DAPI. (B1–B6) CD31 protein in the VECs of blood vessels. (C1–C6) α-SMA protein in VSMCs of blood vessels. (D1–D6) localization analysis of CAV1 protein in the mammary gland tissues. (E1–E6), Co-localization analysis of CAV1, CD31, and α-SMA proteins in blood vessels of the mammary gland tissues in healthy and experimental Holstein cows. VEC, vascular endothelial cell; VSMC, vascular smooth muscle cell; NEUT, neutrophil; VV, venous valve; Con or C, Control group; HM, Hemorrhagic mastitis group. Scale bar of 50 and 20 μm represents 400 × and 800 × magnification, respectively.
See this image and copyright information in PMC

References

    1. Kurt S, Funda EK. Pathogen isolation and antibiogram analysis in dairy cows with clinical mastitis in adana region, Turkey. Etlik Vet Mikrob Dergisi. (2021) 32:20–26. 10.35864/evmd.906990 - DOI
    1. Rainard P, Gilbert FB, Germon P, Foucras G. Invited review: a critical appraisal of mastitis vaccines for dairy cows. J Dairy Sci. (2021) 104:10427–48. 10.3168/jds.2021-20434 - DOI - PubMed
    1. Kabera F, Roy JP, Afifi M, Godden S, Dufour S. Comparing blanket vs. selective dry cow treatment approaches for elimination and prevention of intramammary infections during the dry period: a systematic review and meta-analysis. Front Vet Sci. (2021) 8:688450. 10.3389/fvets.2021.688450 - DOI - PMC - PubMed
    1. Xu M, Deng J, Xu K, Zhu T, Han L, Yan Y, et al. . In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine. Theranostics. (2019) 9:2475–88. 10.7150/thno.31144 - DOI - PMC - PubMed
    1. Cifrian E, Guidry AJ, Bramley AJ, Norcross NL, Bastida-Corcuera FD, Marquardt WW. Effect of staphylococcal beta toxin on the cytotoxicity, proliferation and adherence of Staphylococcus aureus to bovine mammary epithelial cells. Vet Microbiol. (1996) 48:187–98. 10.1016/0378-1135(95)00159-X - DOI - PubMed

LinkOut - more resources