畜牧兽医学报 ›› 2025, Vol. 56 ›› Issue (3): 1076-1088.doi: 10.11843/j.issn.0366-6964.2025.03.010
范曼婷1(), 黄若婷1, 佘远航1, 郭建超2,3, 刘建营2,3,*(
), 郭勇庆1,*(
)
收稿日期:
2024-04-30
出版日期:
2025-03-23
发布日期:
2025-04-02
通讯作者:
刘建营,郭勇庆
E-mail:3107259655@qq.com;59069847@qq.com;lyongqing@scau.edu.cn
作者简介:
范曼婷(2004-),女,广东陆丰人,本科生,主要从事动物健康养殖与安全生产研究,E-mail: 3107259655@qq.com
基金资助:
FAN Manting1(), HUANG Ruoting1, SHE Yuanhang1, GUO Jianchao2,3, LIU Jianying2,3,*(
), GUO Yongqing1,*(
)
Received:
2024-04-30
Online:
2025-03-23
Published:
2025-04-02
Contact:
LIU Jianying, GUO Yongqing
E-mail:3107259655@qq.com;59069847@qq.com;lyongqing@scau.edu.cn
摘要:
乳腺炎是奶牛养殖中危害较大的疾病之一,严重影响奶牛健康和乳品安全,因此需要及时采取预防和控制措施。目前,奶牛乳腺炎存在诊断效率不高和发病机制解释不清晰等问题。随着高通量测序技术的快速发展,基因组学、表观基因组学、转录组学、蛋白质组学等组学技术已被逐步应用于奶牛乳腺炎相关研究上,推动了对该疾病的深入认知。本文综述了组学技术在奶牛乳腺炎发病机制和诊断上的应用现状及研究进展,旨在为科学认识和降低乳腺炎发病率提供参考。通过解析奶牛乳腺炎的多层面机制,揭示了关键调控通路、潜在生物标志物,如CHI3L1、LBP、GSN、GCLC、C4等蛋白质及乳酸、酪氨酸等代谢物,可为乳腺炎发病机制的解析提供指导,也为干预治疗提供了新的途径。但是,在生产中应用时,组学技术仍面临着成本和技术门槛高等挑战。随着多组学技术的深入整合和成本降低,将有助于发现更精确的生物标志物,深入了解特定信号通路,为奶牛乳腺炎的预防、诊断和治疗提供更为科学的依据。
中图分类号:
范曼婷, 黄若婷, 佘远航, 郭建超, 刘建营, 郭勇庆. 组学技术在奶牛乳腺炎发病机制和诊断上应用研究进展[J]. 畜牧兽医学报, 2025, 56(3): 1076-1088.
FAN Manting, HUANG Ruoting, SHE Yuanhang, GUO Jianchao, LIU Jianying, GUO Yongqing. Research Progress on the Application of Omics Technology in the Pathogenesis and Diagnosis of Mastitis in Dairy Cows[J]. Acta Veterinaria et Zootechnica Sinica, 2025, 56(3): 1076-1088.
表 1
组学技术在奶牛乳腺炎的应用与展望"
组学技术 Omics techniques | 已破解的问题 Cracked issues | 存在的问题 Existing issues | 未来发展方向 Development direction |
基因组学 Genomics | 鉴定出与乳腺炎相关的候选基因,如PKD2、KCNAB1等 | 候选基因的功能验证复杂,转化为实际应用的技术尚不成熟 | 现场快速识别致病菌技术 |
表观基因组学 Epigenomics | 揭示了DNA甲基化在乳腺炎免疫调控中的作用 | 缺乏系统性的分子调控网络理解,表观遗传调控产品尚未市场化 | 深入研究表观遗传标记与乳腺炎的关系,开发表观遗传调控工具 |
转录组学 Transcriptomics | 揭示了乳腺炎状态下基因表达的差异,发现关键调控通路 | 高通量数据的解析和转化应用成本较高 | 优化数据处理算法,降低成本,加速研究成果的临床转化 |
蛋白质组学 Proteomics | 鉴定出如CHI3L1、LBP等乳腺炎的潜在生物标志物 | 生物标志物的临床验证和应用门槛较高 | 筛选并验证更精确的生物标志物,降低检测成本 |
代谢组学 Metabonomics | 发现乳酸、酪氨酸等代谢物与乳腺炎状态的关联 | 代谢组学数据复杂,现场快速检测技术不足 | 开发快速、低成本的代谢物检测技术,建立标准化代谢物数据库 |
微生物组学 Microbiomics | 揭示乳腺炎与乳腺微生物群落结构的关联,发现病原菌和耐药基因 | 现场快速识别致病菌的技术有限,微生物组数据转化难 | 优化微生物检测技术,建立标准化数据库,促进数据在乳腺炎防治中的应用 |
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