Distinguishing Natural Infections of the Bovine Mammary Gland by Staphylococcus from Streptococcus spp. Using Quantitative Milk Proteomics

Author:

Rešetar Maslov Dina1ORCID,Thomas Funmilola Clara1,Beletić Anđelo1ORCID,Kuleš Josipa2ORCID,Rubić Ivana1,Benić Miroslav3,Bačić Goran4,Maćešić Nino4ORCID,Eraghi Vida1ORCID,Farkaš Vladimir1,Lenac Roviš Tihana5ORCID,Lisnić Berislav5,Žubčić Damir6,Potočnjak Dalibor6,Mrljak Vladimir16

Affiliation:

1. Laboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, Croatia

2. Department of Chemistry and Biochemistry, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, Croatia

3. Department of Bacteriology and Parasitology, Croatian Veterinary Institute, Savska Cesta, 143, 10000 Zagreb, Croatia

4. Reproduction and Obstetrics Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, Croatia

5. Center for Proteomics University of Rijeka, Faculty of Medicine, Brace Branchetta 20, 51000 Rijeka, Croatia

6. Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, Croatia

Abstract

Bovine mastitis is the most frequent disease on dairy farms, which leads to a decrease in the health welfare of the animals and great economic losses. This study was aimed at determining the quantitative variations in the milk proteome caused by natural infection by Staphylococcus and Streptococcus species in order to gain further understanding of any discrepancies in pathophysiology and host immune responses, independent of the mastitis level. After identification of Staphylococcus (N = 51) and Streptococcus (N = 67) spp., tandem mass tag (TMT)-labeled quantitative proteomic and liquid chromatography-mass spectrometry (LC-MS/MS) techniques on a modular Ultimate 3000 RSLCnano system coupled to a Q Exactive Plus was applied on aseptically sampled milk from Holstein cows. Proteome Discoverer was used for protein identification and quantitation through the SEQUEST algorithm. Statistical analysis employing R was used to identify differentially abundant proteins between the groups. Protein classes, functions and functional-association networks were determined using the PANTHER and STRING tools and pathway over-representation using the REACTOME. In total, 156 master bovine proteins were identified (two unique peptides, p < 0.05 and FDR < 0.001), and 20 proteins showed significantly discrepant abundance between the genera (p < 0.05 and FDR < 0.5). The most discriminatory proteins per group were odorant-binding protein (higher in staphylococci) and fibrinogen beta chain protein (higher in streptococci). The receiver operating characteristic (ROC) curve showed that protein kinase C-binding protein NELL2, thrombospondin-1, and complement factor I have diagnostic potential for differentiating staphylococci and streptococci intramammary infection and inflammation. Improved understanding of the host response mechanisms and recognition of potential biomarkers of specific-pathogen mastitis, which may aid prompt diagnosis for control implementation, are potential benefits of this study.

Funder

Republic of Croatia Ministry of Science and Education

Publisher

MDPI AG

Subject

General Veterinary,Animal Science and Zoology

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