Multi Omics Reveals Biomarkers of Metabolic and Microbial Alterations in Subclinical Mastitis

Subclinical mastitis (SCM) in dairy cows has a significant impact on both milk quality and overall animal health, often going undetected in the early stages. This study employs a multi-omics approach, integrating metabolomics and microbiome analyses across blood, milk, fecal, and rumen fluid samples to investigate the complex pathophysiology of SCM. Key hematological and biochemical changes were identified, with biomarkers such as digalacturonic acid and N-methyl-L-lysine emerging as indicators of systemic metabolic and immune disturbances. Metabolomic profiling revealed distinct patterns in metabolite distribution, highlighting the intricate metabolic interactions associated with SCM. Additionally, 16S rRNA gene sequencing revealed significant shifts in microbial communities in both rumen fluid and feces, particularly in genera such as Succinivibrio and Methanobrevibacter, which are involved in carbohydrate fermentation and methanogenesis, respectively. These shifts in microbial composition may reflect alterations in the metabolic activities of the microbiota, potentially contributing to the inflammatory and metabolic processes underlying SCM. Positive correlations were observed between key metabolites, including ropinirole and arachidonic acid, and specific microbial genera such as Succinivibrionaceae_UCG-001, while inverse relationships were found with Alistipes. These findings underscore the complex interactions between metabolites and the microbiome, suggesting the potential of these biomarkers for early detection and targeted interventions in SCM. Our integrative multi-omics approach provides deeper insights into the mechanisms of SCM, laying the groundwork for novel strategies aimed at enhancing dairy cow health and productivity.

奶牛亚临床乳腺炎（Subclinical mastitis, SCM）对牛乳品质与动物整体健康均具有显著负面影响，且在发病早期常难以被察觉。本研究采用多组学（multi-omics）策略，整合血液、乳汁、粪便及瘤胃液样本的代谢组学（metabolomics）与微生物组学（microbiome）分析，以探究亚临床乳腺炎复杂的病理生理机制。研究鉴定出多项关键血液学与生化指标变化，其中半乳糖二酸（digalacturonic acid）和N-甲基-L-赖氨酸（N-methyl-L-lysine）等生物标志物可作为机体系统性代谢与免疫紊乱的指示因子。代谢组学分析揭示了不同样本间代谢物分布的显著特征差异，凸显了与亚临床乳腺炎相关的精细代谢互作关系。此外，16S rRNA基因测序（16S rRNA gene sequencing）结果显示，瘤胃液与粪便中的微生物群落结构发生显著改变，尤其是分别参与碳水化合物发酵与产甲烷作用的琥珀酸弧菌属（Succinivibrio）和甲烷短杆菌属（Methanobrevibacter）等菌属。这类微生物组成的改变可能反映了菌群代谢活性的变化，进而可能参与亚临床乳腺炎相关的炎症与代谢病理进程。研究还观察到，包括罗匹尼罗（ropinirole）与花生四烯酸（arachidonic acid）在内的关键代谢物，与琥珀酸弧菌科_UCG-001（Succinivibrionaceae_UCG-001）等特定微生物菌属呈正相关，而与另枝菌属（Alistipes）则呈负相关。上述研究结果凸显了代谢物与微生物组之间的复杂互作关系，表明这些生物标志物有望用于亚临床乳腺炎的早期检测与靶向干预。本研究的整合多组学策略为深入解析亚临床乳腺炎的发病机制提供了新视角，为提升奶牛健康水平与生产性能的新型干预策略奠定了研究基础。