Distinguishing Natural Infections of the Bovine Mammary Gland by <i>Staphylococcus</i> from <i>Streptococcus</i> spp. Using Quantitative Milk Proteomics
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 <i>Staphylococcus</i>...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
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MDPI AG
2023-05-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/13/11/1829 |
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| author | Dina Rešetar Maslov Funmilola Clara Thomas Anđelo Beletić Josipa Kuleš Ivana Rubić Miroslav Benić Goran Bačić Nino Maćešić Vida Eraghi Vladimir Farkaš Tihana Lenac Roviš Berislav Lisnić Damir Žubčić Dalibor Potočnjak Vladimir Mrljak |
| author_facet | Dina Rešetar Maslov Funmilola Clara Thomas Anđelo Beletić Josipa Kuleš Ivana Rubić Miroslav Benić Goran Bačić Nino Maćešić Vida Eraghi Vladimir Farkaš Tihana Lenac Roviš Berislav Lisnić Damir Žubčić Dalibor Potočnjak Vladimir Mrljak |
| author_sort | Dina Rešetar Maslov |
| collection | DOAJ |
| description | 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 <i>Staphylococcus</i> and <i>Streptococcus</i> species in order to gain further understanding of any discrepancies in pathophysiology and host immune responses, independent of the mastitis level. After identification of <i>Staphylococcus</i> (N = 51) and <i>Streptococcus</i> (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, <i>p</i> < 0.05 and FDR < 0.001), and 20 proteins showed significantly discrepant abundance between the genera (<i>p</i> < 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. |
| first_indexed | 2024-03-11T03:12:42Z |
| format | Article |
| id | doaj.art-a5dad8207ef44ef9a48f25aeb2c48ac1 |
| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-03-11T03:12:42Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj.art-a5dad8207ef44ef9a48f25aeb2c48ac12023-11-18T07:30:16ZengMDPI AGAnimals2076-26152023-05-011311182910.3390/ani13111829Distinguishing Natural Infections of the Bovine Mammary Gland by <i>Staphylococcus</i> from <i>Streptococcus</i> spp. Using Quantitative Milk ProteomicsDina Rešetar Maslov0Funmilola Clara Thomas1Anđelo Beletić2Josipa Kuleš3Ivana Rubić4Miroslav Benić5Goran Bačić6Nino Maćešić7Vida Eraghi8Vladimir Farkaš9Tihana Lenac Roviš10Berislav Lisnić11Damir Žubčić12Dalibor Potočnjak13Vladimir Mrljak14Laboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaLaboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaLaboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaDepartment of Chemistry and Biochemistry, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaLaboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaDepartment of Bacteriology and Parasitology, Croatian Veterinary Institute, Savska Cesta, 143, 10000 Zagreb, CroatiaReproduction and Obstetrics Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaReproduction and Obstetrics Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaLaboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaLaboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaCenter for Proteomics University of Rijeka, Faculty of Medicine, Brace Branchetta 20, 51000 Rijeka, CroatiaCenter for Proteomics University of Rijeka, Faculty of Medicine, Brace Branchetta 20, 51000 Rijeka, CroatiaInternal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaInternal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaLaboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, CroatiaBovine 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 <i>Staphylococcus</i> and <i>Streptococcus</i> species in order to gain further understanding of any discrepancies in pathophysiology and host immune responses, independent of the mastitis level. After identification of <i>Staphylococcus</i> (N = 51) and <i>Streptococcus</i> (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, <i>p</i> < 0.05 and FDR < 0.001), and 20 proteins showed significantly discrepant abundance between the genera (<i>p</i> < 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.https://www.mdpi.com/2076-2615/13/11/1829<i>Staphylococcus</i><i>Streptococcus</i>bovine mastitisproteomicsmarkersbacterial intramammary infection |
| spellingShingle | Dina Rešetar Maslov Funmilola Clara Thomas Anđelo Beletić Josipa Kuleš Ivana Rubić Miroslav Benić Goran Bačić Nino Maćešić Vida Eraghi Vladimir Farkaš Tihana Lenac Roviš Berislav Lisnić Damir Žubčić Dalibor Potočnjak Vladimir Mrljak Distinguishing Natural Infections of the Bovine Mammary Gland by <i>Staphylococcus</i> from <i>Streptococcus</i> spp. Using Quantitative Milk Proteomics Animals <i>Staphylococcus</i> <i>Streptococcus</i> bovine mastitis proteomics markers bacterial intramammary infection |
| title | Distinguishing Natural Infections of the Bovine Mammary Gland by <i>Staphylococcus</i> from <i>Streptococcus</i> spp. Using Quantitative Milk Proteomics |
| title_full | Distinguishing Natural Infections of the Bovine Mammary Gland by <i>Staphylococcus</i> from <i>Streptococcus</i> spp. Using Quantitative Milk Proteomics |
| title_fullStr | Distinguishing Natural Infections of the Bovine Mammary Gland by <i>Staphylococcus</i> from <i>Streptococcus</i> spp. Using Quantitative Milk Proteomics |
| title_full_unstemmed | Distinguishing Natural Infections of the Bovine Mammary Gland by <i>Staphylococcus</i> from <i>Streptococcus</i> spp. Using Quantitative Milk Proteomics |
| title_short | Distinguishing Natural Infections of the Bovine Mammary Gland by <i>Staphylococcus</i> from <i>Streptococcus</i> spp. Using Quantitative Milk Proteomics |
| title_sort | distinguishing natural infections of the bovine mammary gland by i staphylococcus i from i streptococcus i spp using quantitative milk proteomics |
| topic | <i>Staphylococcus</i> <i>Streptococcus</i> bovine mastitis proteomics markers bacterial intramammary infection |
| url | https://www.mdpi.com/2076-2615/13/11/1829 |
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