整合子宫微生物组和代谢组,加深对患子宫炎奶牛子宫环境的了解。

IF 4.9 Q1 MICROBIOLOGY Animal microbiome Pub Date : 2024-05-27 DOI:10.1186/s42523-024-00314-7
S Casaro, J G Prim, T D Gonzalez, F Cunha, R S Bisinotto, R C Chebel, J E P Santos, C D Nelson, S J Jeon, R C Bicalho, J P Driver, Klibs N Galvão
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引用次数: 0

摘要

背景:子宫炎是一种常见的子宫疾病,会影响奶牛的福利、繁殖力和存活率。从产犊到产后 2 天,患子宫炎的奶牛和保持健康的奶牛的子宫微生物群并无不同,产后 2 天后,子宫微生物群出现菌群失调,其特征是转向机会性病原体,如镰刀菌属和类杆菌属。这些机会性病原体是否会增殖并超越子宫共生菌,可能取决于子宫中存在的基质类型。本研究的目的是整合子宫微生物组和代谢组数据,以加深对发生子宫炎的奶牛子宫环境的了解。荷斯坦奶牛(104 头)在产仔时和诊断出元胞炎时采集了子宫液。根据产犊后天数,将患有元气大伤的奶牛(n = 52)与未患元气大伤的奶牛(n = 52)配对。首先对子宫微生物组和代谢组进行单独评估,然后利用网络分析法对其进行整合:结果:子宫微生物组在产犊时没有差异,但在确诊元气大伤当天,有元气大伤的奶牛和没有元气大伤的奶牛的子宫微生物组存在差异。子宫代谢组在产犊时和确诊元气淋巴结炎当天在患元气淋巴结炎和未患元气淋巴结炎的奶牛之间存在差异。在元气大伤确诊当天,对 6 个重要细菌属和 153 个重要代谢物进行了 Omics 整合。由于子宫微生物组没有显著差异,因此没有在产犊时进行整合。共有 3 个菌属(即 Fusobacterium、Porphyromonas 和 Bacteroides)与元气大伤诊断当天的 49 个代谢物密切相关。在产犊时的 49 种代谢物中,有 7 种代谢物与元气大伤确诊当天的机会致病菌密切相关。主要代谢物与减少共生细菌形成生物膜、机会致病菌过度生长、组织损伤和炎症、免疫逃避和免疫失调有关:本文提供的数据整合有助于加深对患子宫炎奶牛子宫环境的了解。鉴定出的代谢物可能为子宫主要病原体镰刀菌、卟啉单胞菌和巴氏杆菌提供了竞争优势,并可能成为未来旨在减少子宫内机会性致病菌生长的干预目标。
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Integrating uterine microbiome and metabolome to advance the understanding of the uterine environment in dairy cows with metritis.

Background: Metritis is a prevalent uterine disease that affects the welfare, fertility, and survival of dairy cows. The uterine microbiome from cows that develop metritis and those that remain healthy do not differ from calving until 2 days postpartum, after which there is a dysbiosis of the uterine microbiome characterized by a shift towards opportunistic pathogens such as Fusobacteriota and Bacteroidota. Whether these opportunistic pathogens proliferate and overtake the uterine commensals could be determined by the type of substrates present in the uterus. The objective of this study was to integrate uterine microbiome and metabolome data to advance the understanding of the uterine environment in dairy cows that develop metritis. Holstein cows (n = 104) had uterine fluid collected at calving and at the day of metritis diagnosis. Cows with metritis (n = 52) were paired with cows without metritis (n = 52) based on days after calving. First, the uterine microbiome and metabolome were evaluated individually, and then integrated using network analyses.

Results: The uterine microbiome did not differ at calving but differed on the day of metritis diagnosis between cows with and without metritis. The uterine metabolome differed both at calving and on the day of metritis diagnosis between cows that did and did not develop metritis. Omics integration was performed between 6 significant bacteria genera and 153 significant metabolites on the day of metritis diagnosis. Integration was not performed at calving because there were no significant differences in the uterine microbiome. A total of 3 bacteria genera (i.e. Fusobacterium, Porphyromonas, and Bacteroides) were strongly correlated with 49 metabolites on the day of metritis diagnosis. Seven of the significant metabolites at calving were among the 49 metabolites strongly correlated with opportunistic pathogenic bacteria on the day of metritis diagnosis. The main metabolites have been associated with attenuation of biofilm formation by commensal bacteria, opportunistic pathogenic bacteria overgrowth, tissue damage and inflammation, immune evasion, and immune dysregulation.

Conclusions: The data integration presented herein helps advance the understanding of the uterine environment in dairy cows with metritis. The identified metabolites may provide a competitive advantage to the main uterine pathogens Fusobacterium, Porphyromonas and Bacteroides, and may be promising targets for future interventions aiming to reduce opportunistic pathogenic bacteria growth in the uterus.

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