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Zhang Z, Yao Y, Yang J, Jiang H, Meng Y, Cao W, Zhou F, Wang K, Yang Z, Yang C, Sun J, Yang Y. Assessment of adaptive immune responses of dairy cows with Burkholderia contaminans-induced mastitis. Front Microbiol 2023; 14:1099623. [PMID: 36960295 PMCID: PMC10028201 DOI: 10.3389/fmicb.2023.1099623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/15/2023] [Indexed: 03/09/2023] Open
Abstract
Burkholderia contaminans, an emerging pathogen related to cystic fibrosis, is known to cause potentially fatal infections in humans and ruminants, especially in immunocompromised individuals. However, the immune responses in cows following its infection have not been fully elucidated. In this study, T- and B-lymphocytes-mediated immune responses were evaluated in 15 B. contaminans-induced mastitis cows and 15 healthy cows with multi-parameter flow cytometry. The results showed that infection with B. contaminans was associated with a significant decrease in the number and percentage of B lymphocytes but with a significant increase in the proportion of IgG+CD27+ B lymphocytes. This indicated that humoral immune response may not be adequate to fight intracellular infection, which could contribute to the persistent bacterial infection. In addition, B. contaminans infection induced significant increase of γδ T cells and double positive (DP) CD4+CD8+ T cells but not CD4+ or CD8+ (single positive) T cells in blood. Phenotypic analysis showed that the percentages of activated WC1+ γδ T cells in peripheral blood were increased in the B. contaminans infected cows. Interestingly, intracellular cytokine staining showed that cattle naturally infected with B. contaminans exhibited multifunctional TNF-α+IFN-γ+IL-2+ B. contaminans-specific DP T cells. Our results, for the first time, revealed a potential role of IgG+CD27+ B cells, CD4+CD8+ T cells and WC1+ γδ T cells in the defense of B. contaminans-induced mastitis in cows.
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Affiliation(s)
- Zhipeng Zhang
- Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, College of Veterinary Medicine, Yangzhou University, Yangzhou, China
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Yiyang Yao
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Jiayu Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Hui Jiang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Ye Meng
- Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, College of Veterinary Medicine, Yangzhou University, Yangzhou, China
| | - Wenqiang Cao
- Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, College of Veterinary Medicine, Yangzhou University, Yangzhou, China
| | - Fuzhen Zhou
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Kun Wang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Zhangping Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou, China
| | - Chunhua Yang
- Institute of Biological Resources, Jiangxi Academy of Sciences, Nanchang, China
- *Correspondence: Chunhua Yang,
| | - Jie Sun
- Shenzhen Academy of Inspection and Quarantine Sciences, Shenzhen, China
- Jie Sun,
| | - Yi Yang
- Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, College of Veterinary Medicine, Yangzhou University, Yangzhou, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou, China
- Yi Yang,
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Neculai-Valeanu AS, Ariton AM. Udder Health Monitoring for Prevention of Bovine Mastitis and Improvement of Milk Quality. Bioengineering (Basel) 2022; 9:608. [PMID: 36354519 PMCID: PMC9687184 DOI: 10.3390/bioengineering9110608] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 08/05/2023] Open
Abstract
To maximize milk production, efficiency, and profits, modern dairy cows are genetically selected and bred to produce more and more milk and are fed copious quantities of high-energy feed to support ever-increasing milk volumes. As demands for increased milk yield and milking efficiency continue to rise to provide for the growing world population, more significant stress is placed on the dairy cow's productive capacity. In this climate, which is becoming increasingly hotter, millions of people depend on the capacity of cattle to respond to new environments and to cope with temperature shocks as well as additional stress factors such as solar radiation, animal crowding, insect pests, and poor ventilation, which are often associated with an increased risk of mastitis, resulting in lower milk quality and reduced production. This article reviews the impact of heat stress on milk production and quality and emphasizes the importance of udder health monitoring, with a focus on the use of emergent methods for monitoring udder health, such as infrared thermography, biosensors, and lab-on-chip devices, which may promote animal health and welfare, as well as the quality and safety of dairy products, without hindering the technological flow, while providing significant benefits to farmers, manufacturers, and consumers.
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Farschtschi S, Riedmaier-Sprenzel I, Phomvisith O, Gotoh T, Pfaffl MW. The successful use of -omic technologies to achieve the 'One Health' concept in meat producing animals. Meat Sci 2022; 193:108949. [PMID: 36029570 DOI: 10.1016/j.meatsci.2022.108949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/09/2022] [Accepted: 08/16/2022] [Indexed: 11/15/2022]
Abstract
Human health and wellbeing are closely linked to healthy domestic animals, a vital wildlife, and an intact ecosystem. This holistic concept is referred to as 'One Health'. In this review, we provide an overview of the potential and the challenges for the use of modern -omics technologies, especially transcriptomics and proteomics, to implement the 'One Health' idea for food-producing animals. These high-throughput studies offer opportunities to find new potential molecular biomarkers to monitor animal health, detect pharmacological interventions and evaluate the wellbeing of farm animals in modern intensive livestock systems.
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Affiliation(s)
- Sabine Farschtschi
- Division of Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Irmgard Riedmaier-Sprenzel
- Division of Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Eurofins Medigenomix Forensik GmbH, Anzinger Straße 7a, 85560 Ebersberg, Germany
| | - Ouanh Phomvisith
- Department of Agricultural Sciences and Natural Resources, Kagoshima University, Korimoto 1-21-24, Kagoshima 890-8580, Japan
| | - Takafumi Gotoh
- Department of Agricultural Sciences and Natural Resources, Kagoshima University, Korimoto 1-21-24, Kagoshima 890-8580, Japan
| | - Michael W Pfaffl
- Division of Animal Physiology and Immunology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
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Bausewein M, Mansfeld R, Doherr MG, Harms J, Sorge US. Sensitivity and Specificity for the Detection of Clinical Mastitis by Automatic Milking Systems in Bavarian Dairy Herds. Animals (Basel) 2022; 12:ani12162131. [PMID: 36009724 PMCID: PMC9405299 DOI: 10.3390/ani12162131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/11/2022] [Accepted: 08/14/2022] [Indexed: 11/20/2022] Open
Abstract
In automatic milking systems (AMSs), the detection of clinical mastitis (CM) and the subsequent separation of abnormal milk should be reliably performed by commercial AMSs. Therefore, the objectives of this cross-sectional study were (1) to determine the sensitivity (SN) and specificity (SP) of CM detection of AMS by the four most common manufacturers in Bavarian dairy farms, and (2) to identify routinely collected cow data (AMS and monthly test day data of the regional Dairy Herd Improvement Association (DHIA)) that could improve the SN and SP of clinical mastitis detection. Bavarian dairy farms with AMS from the manufacturers DeLaval, GEA Farm Technologies, Lely, and Lemmer-Fullwood were recruited with the aim of sampling at least 40 cows with clinical mastitis per AMS manufacturer in addition to clinically healthy ones. During a single farm visit, cow-level milking information was first electronically extracted from each AMS and then all lactating cows examined for their udder health status in the barn. Clinical mastitis was defined as at least the presence of visibly abnormal milk. In addition, available DHIA test results from the previous six months were collected. None of the manufacturers provided a definition for clinical mastitis (i.e., visually abnormal milk), therefore, the SN and SP of AMS warning lists for udder health were assessed for each manufacturer individually, based on the clinical evaluation results. Generalized linear mixed models (GLMMs) with herd as random effect were used to determine the potential influence of routinely recorded parameters on SN and SP. A total of 7411 cows on 114 farms were assessed; of these, 7096 cows could be matched to AMS data and were included in the analysis. The prevalence of clinical mastitis was 3.4% (239 cows). When considering the 95% confidence interval (95% CI), all but one manufacturer achieved the minimum SN limit of >80%: DeLaval (SN: 61.4% (95% CI: 49.0%−72.8%)), GEA (75.9% (62.4%−86.5%)), Lely (78.2% (67.4%−86.8%)), and Lemmer-Fullwood (67.6% (50.2%−82.0%)). However, none of the evaluated AMSs achieved the minimum SP limit of 99%: DeLaval (SP: 89.3% (95% CI: 87.7%−90.7%)), GEA (79.2% (77.1%−81.2%)), Lely (86.2% (84.6%−87.7%)), and Lemmer-Fullwood (92.2% (90.8%−93.5%)). All AMS manufacturers’ robots showed an association of SP with cow classification based on somatic cell count (SCC) measurement from the last two DHIA test results: cows that were above the threshold of 100,000 cells/mL for subclinical mastitis on both test days had lower chances of being classified as healthy by the AMS compared to cows that were below the threshold. In conclusion, the detection of clinical mastitis cases was satisfactory across AMS manufacturers. However, the low SP will lead to unnecessarily discarded milk and increased workload to assess potentially false-positive mastitis cases. Based on the results of our study, farmers must evaluate all available data (test day data, AMS data, and daily assessment of their cows in the barn) to make decisions about individual cows and to ultimately ensure animal welfare, food quality, and the economic viability of their farm.
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Affiliation(s)
- Mathias Bausewein
- Bavarian Animal Health Services, 85586 Poing-Grub, Germany
- Clinic for Ruminants with Ambulatory and Herd Health Services, Centre for Clinical Veterinary Medicine, LMU Munich, 85764 Oberschleissheim, Germany
- Correspondence:
| | - Rolf Mansfeld
- Clinic for Ruminants with Ambulatory and Herd Health Services, Centre for Clinical Veterinary Medicine, LMU Munich, 85764 Oberschleissheim, Germany
| | - Marcus G. Doherr
- Institute for Veterinary Epidemiology and Biostatistics, Freie Universität, 14163 Berlin, Germany
| | - Jan Harms
- Institute for Agricultural Engineering and Animal Husbandry, Bavarian State Research Centre for Agriculture, 85586 Poing-Grub, Germany
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