College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, No. 2 Xinyang Road, New Development District, Daqing, Heilongjiang, China 163319; Key Laboratory of Efficient Utilization of Feed Resources and Nutrition Manipulation in Cold Region of Heilongjiang Province, China 163319.
College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, No. 2 Xinyang Road, New Development District, Daqing, Heilongjiang, China 163319.
J Dairy Sci. 2023 Jul;106(7):4906-4917. doi: 10.3168/jds.2022-22282. Epub 2023 Jun 7.
The extent to which a nutrition-related disorder such as ketosis alters the ruminal microbiota or whether microbiota composition is related to ketosis and potential associations with host metabolism is unknown. We aimed to evaluate variations occurring in the ruminal microbiota of ketotic and nonketotic cows in the early postpartum period, and how those changes may affect the risk of developing the disease. Data on milk yield, dry matter intake (DMI), body condition score, and blood β-hydroxybutyrate (BHB) concentrations at 21 d postpartum were used to select 27 cows, which were assigned (n = 9 per group) to a clinical ketotic (CK, 4.10 ± 0.72 mmol BHB/L, DMI 11.61 ± 0.49 kg/d, ruminal pH 7.55 ± 0.07), subclinical ketotic (SK, 1.36 ± 0.12 mmol BHB/L, DMI 15.24 ± 0.34 kg/d, ruminal pH 7.58 ± 0.08), or control (NK, 0.88 ± 0.14 mmol BHB/L, DMI 16.74 ± 0.67/d, ruminal pH 7.61 ± 0.03) group. Cows averaged 3.6 ± 0.5 lactations and a body condition score of 3.11 ± 0.34 at the time of sampling. After blood serum collection for metabolomics analysis (H nuclear magnetic resonance spectra), 150 mL of ruminal digesta was collected from each cow using an esophageal tube, paired-end (2 × 300 bp) sequencing of isolated DNA from ruminal digesta was performed via Illumina MiSeq, and sequencing data were analyzed using QIIME2 (v 2020.6) to measure the ruminal microbiota composition and relative abundance. Spearman correlation coefficients were used to evaluate relationships between relative abundance of bacterial genera and concentrations of serum metabolites. There were more than 200 genera, with approximately 30 being significant between NK and CK cows. Succinivibrionaceae UCG 1 taxa decreased in CK compared with NK cows. Christensenellaceae (Spearman correlation coefficient = 0.6), Ruminococcaceae (Spearman correlation coefficient = 0.6), Lachnospiraceae (Spearman correlation coefficient = 0.5), and Prevotellaceae (Spearman correlation coefficient = 0.6) genera were more abundant in the CK group and were highly positively correlated with plasma BHB. Metagenomic analysis indicated a high abundance of predicted functions related to metabolism (37.7%), genetic information processing (33.4%), and Brite hierarchies (16.3%) in the CK group. The 2 most important metabolic pathways for butyrate and propionate production were enriched in CK cows, suggesting increased production of acetyl coenzyme A and butyrate and decreased production of propionate. Overall, the combined data suggested that microbial populations may be related to ketosis by affecting short-chain fatty acid metabolism and BHB accumulation even in cows with adequate feed intake in the early postpartum period.
在酮病等与营养相关的疾病发生时,瘤胃微生物群会发生怎样的变化,或者微生物群落组成是否与酮病有关,以及与宿主代谢的潜在关联,目前尚不清楚。我们的目的是评估产后早期酮病和非酮病奶牛瘤胃微生物群的变化,并探讨这些变化如何影响疾病的发生风险。我们使用产后第 21 天的产奶量、干物质采食量(DMI)、体况评分和血液β-羟丁酸(BHB)浓度的数据,选择了 27 头奶牛,并将其分为(每组 9 头)临床酮病(CK,4.10 ± 0.72 mmol BHB/L,DMI 11.61 ± 0.49 kg/d,瘤胃 pH 7.55 ± 0.07)、亚临床酮病(SK,1.36 ± 0.12 mmol BHB/L,DMI 15.24 ± 0.34 kg/d,瘤胃 pH 7.58 ± 0.08)或对照组(NK,0.88 ± 0.14 mmol BHB/L,DMI 16.74 ± 0.67/d,瘤胃 pH 7.61 ± 0.03)。奶牛在采样时平均泌乳 3.6 ± 0.5 次,体况评分为 3.11 ± 0.34。在采集血清进行代谢组学分析(H 核磁共振谱)后,使用食管管从每头奶牛中采集 150 毫升瘤胃液,通过 Illumina MiSeq 对瘤胃液中分离的 DNA 进行双端(2 × 300 bp)测序,使用 QIIME2(v 2020.6)分析测序数据,以测量瘤胃微生物群落组成和相对丰度。使用 Spearman 相关系数评估细菌属的相对丰度与血清代谢物浓度之间的关系。有 200 多个属,其中大约 30 个属在 NK 和 CK 奶牛之间存在显著差异。与 NK 奶牛相比,CK 奶牛中 Succinivibrionaceae UCG 1 类群减少。Christensenellaceae(Spearman 相关系数=0.6)、Ruminococcaceae(Spearman 相关系数=0.6)、Lachnospiraceae(Spearman 相关系数=0.5)和 Prevotellaceae(Spearman 相关系数=0.6)属在 CK 组中更为丰富,与血浆 BHB 呈高度正相关。宏基因组分析表明,CK 组中与代谢(37.7%)、遗传信息处理(33.4%)和 Brite 层次结构(16.3%)相关的预测功能丰度较高。丁酸和丙酸产生的 2 个最重要的代谢途径在 CK 奶牛中得到了富集,表明乙酰辅酶 A 和丁酸的产生增加,而丙酸的产生减少。总体而言,这些综合数据表明,微生物群可能通过影响短链脂肪酸代谢和 BHB 积累与酮病有关,即使在产后早期奶牛有足够的饲料摄入时也是如此。