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Li M, Wang Z, Fu S, Sun N, Li W, Xu Y, Han X, Zhang J, Miao J. Taurine reduction of injury from neutrophil infiltration ameliorates Streptococcus uberis-induced mastitis. Int Immunopharmacol 2023; 124:111028. [PMID: 37857121 DOI: 10.1016/j.intimp.2023.111028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/14/2023] [Accepted: 10/04/2023] [Indexed: 10/21/2023]
Abstract
Mastitis is a common disease of dairy cows characterized by infiltration of leukocytes, especially neutrophils, resulting in increased permeability of the blood-milk barrier (BMB). Taurine, a functional nutrient, has been shown to have anti-inflammatory and antioxidant effects. Here, we investigated the regulatory effects and mechanisms of taurine on the complex immune network of the mammary gland in Streptococcus uberis (S. uberis) infection. We found that taurine had no direct effect on CXCL2-mediated neutrophil chemotaxis. However, it inhibited MAPK and NF-κB signalings by modulating the activity of TAK1 downstream of TLR2, thereby reducing CXCL2 expression in macrophages to reduce neutrophil recruitment in S. uberis infection. Further, the AMPK/Nrf2 signaling pathway was activated by taurine to help mitigate oxidative damage, apoptosis and disruption of tight junctions in mammary epithelial cells caused by hypochlorous acid, a strong oxidant produced by neutrophils, thus protecting the integrity of the mammary epithelial barrier. Taurine protects the BMB from damage caused by neutrophils via blocking the macrophage-CXCL2-neutrophil signaling axis and increasing the antioxidant capacity of mammary epithelial cells.
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Affiliation(s)
- Ming Li
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Animal Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China; College of Veterinary Medicine, Yunnan Agricultural University, Kunming 650201, China
| | - Zhenglei Wang
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Animal Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Shaodong Fu
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Animal Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Naiyan Sun
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Animal Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Weizhen Li
- College of Veterinary Medicine, Yunnan Agricultural University, Kunming 650201, China
| | - Yuanyuan Xu
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Animal Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Xiangan Han
- Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, 200241, China
| | - Jinqiu Zhang
- National Research Center for Veterinary Vaccine Engineering and Technology of China, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China.
| | - Jinfeng Miao
- MOE Joint International Research Laboratory of Animal Health and Food Safety, Key Laboratory of Animal Physiology & Biochemistry, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China.
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Gaspa G, Correddu F, Cesarani A, Congiu M, Dimauro C, Pauciullo A, Macciotta NPP. Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed. FRONTIERS IN ANIMAL SCIENCE 2022. [DOI: 10.3389/fanim.2022.889797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Milk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Although the clotting properties of individual milk have been widely studied, little attention has been given to NCM and genomic dissection of this trait. Mid-infrared (MIR) spectra can be exploited both to predict cheese-making aptitude and to discriminate between coagulating milk and NCM. The main goals of this work were (i) to assess the predictivity of MIR spectra for NCM classification and (ii) to conduct a genome-wide association study on coagulation ability. Milk samples from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCPs) served as the training dataset. The validation dataset included 662 ewes. Three classical MCPs were measured: rennet coagulation time (RCT), curd firmness (a30), and curd firming time (k20). Moreover, MIR spectra were acquired and stored in the region between 925.92 and 5,011.54 cm−1. The probability of a sample to be NCM was modeled by step-wise logistic regression on milk spectral information (LR-W), logistic regression on principal component (LR-PC), and canonical discriminant analysis of spectral wave number (DA-W). About 9% of the samples did not coagulate at 30 min. The use of LR-W gave a poorer classification of NCM. The use of LR-PC improved the percentage of correct assignment (45 ± 9%). The DA-W method allows us to reach 75.1 ± 10.3 and 76.5 ± 18.4% of correct assignments of the inner and external validation datasets, respectively. As far as GWA of NCM, 458 SNP associations and 45 candidate genes were detected. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status, and a milk compound also known to affect the ability of milk to coagulate. In particular, the potential involvement of CAPNs deserves further investigation.
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Nielsen SS, Bicout DJ, Calistri P, Canali E, Drewe JA, Garin‐Bastuji B, Gonzales Rojas JL, Gortázar C, Herskin M, Michel V, Miranda Chueca MÁ, Padalino B, Pasquali P, Roberts HC, Spoolder H, Ståhl K, Velarde A, Viltrop A, Winckler C, Baldinelli F, Broglia A, Kohnle L, Alvarez J. Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): antimicrobial-resistant Staphylococcus aureus in cattle and horses. EFSA J 2022; 20:e07312. [PMID: 35582361 PMCID: PMC9087474 DOI: 10.2903/j.efsa.2022.7312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Staphylococcus aureus (S. aureus) was identified among the most relevant antimicrobial-resistant (AMR) bacteria in the EU for cattle and horses in previous scientific opinions. Thus, it has been assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7 on disease profile and impacts, Article 5 on its eligibility to be listed, Annex IV for its categorisation according to disease prevention and control rules as in Article 9, and Article 8 for listing animal species related to the bacterium. The assessment has been performed following a methodology previously published. The outcome is the median of the probability ranges provided by the experts, which indicates whether each criterion is fulfilled (lower bound ≥ 66%) or not (upper bound ≤ 33%), or whether there is uncertainty about fulfilment. Reasoning points are reported for criteria with uncertain outcome. According to the assessment here performed, it is uncertain whether AMR S. aureus can be considered eligible to be listed for Union intervention according to Article 5 of the AHL (60-90% probability). According to the criteria in Annex IV, for the purpose of categorisation related to the level of prevention and control as in Article 9 of the AHL, the AHAW Panel concluded that the bacterium does not meet the criteria in Sections 1, 2 and 4 (Categories A, B and D; 1-5%, 5-10% and 10-33% probability of meeting the criteria, respectively) and the AHAW Panel was uncertain whether it meets the criteria in Sections 3 and 5 (Categories C and E, 33-90% and 60-90% probability of meeting the criteria, respectively). The animal species to be listed for AMR S. aureus according to Article 8 criteria include mainly mammals, birds, reptiles and fish.
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Genetic Parameters of Somatic Cell Score in Florida Goats Using Single and Multiple Traits Models. Animals (Basel) 2022; 12:ani12081009. [PMID: 35454255 PMCID: PMC9025430 DOI: 10.3390/ani12081009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/29/2022] [Accepted: 04/04/2022] [Indexed: 12/10/2022] Open
Abstract
A total of 1,031,143 records of daily dairy control test of Spanish Florida goats were used for this study. The database was edited, and only the records of the first three lactations were kept. The final database contained 340,654 daily-test somatic cell counts from 27,749 daughters of 941 males and 16,243 goats. The evolution of this count in the last 14 years was analyzed following French and American international associations’ criteria for the risk of mastitis in goats, and confirmed the slight increase in SCS in the last years and the importance of this problem (50% of dairy control tests show a risk of suffering mastitis). For the genetic analysis, the SCS records were log-transformed to normalize this variable. Two strategies were used for the genetic analysis: a univariate animal model for the SCS assuming that SCS does not vary throughout the parities, and a multi-character animal model, where SCS is not considered as the same character in the different parities. The heritabilities (h2) were higher in the multiple traits models, showings an upward trend from the first to the third parity (h2 between 0.245 to 0.365). The genetic correlations of the same trait, as well as between breeding values (GVs) between different parities, were different from unity. The breeding values (EBVs) obtained for both models were subjected to a PCA: the first eigenvector (λ1) explained most of the variations (between 74% to 90%), while the second λ2 accounted for between 9% to 20% of the variance, which shows that the selection will be proportionally favorable but not equivalent in all parities and that there are some variations in the type of response.
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