Sijunzi San alleviates the negative energy balance in postpartum dairy cows by regulating rumen fermentation capacity

Abstract

Introduction: Postpartum dairy cows are susceptible to negative energy balance caused by decreased feed intake and the initiation of lactation. Sijunzi San, a famous Chinese traditional herbal formulation, can promote gastrointestinal digestion and absorption and improve disorders of intestinal microbiota. Therefore, we hypothesized that Sijunzi San might alleviate negative energy balance in postpartum dairy cows by modulating the structure of the rumen microbiota and enhancing its fermentation capacity.

Methods: Liquid chromatography-mass spectrometry (LC-MS/MS) was utilized in vitro to identify the main active ingredients in the Sijunzi San. Techniques including in vitro ruminal fermentation, gas chromatography, and 16S rRNA high-throughput sequencing were employed to evaluate their effects on the structure of the rumen microbiota. To test their in vivo effects, sixteen postpartum Holstein dairy cows, with similar body condition and parity, were randomly assigned to two groups, with 8 cows per group. The CONT group was fed a basic diet, while the SJZS group received an additional 300 g/d of Sijunzi San along with the basic diet, continuously for 7 days. ELISA and untargeted metabolomics using ultra-high-performance liquid chromatography-tandem mass (UHPLC-MS/MS) were employed to assess the impacts on immunoglobulin levels, fat mobilization, and the blood metabolome in postpartum dairy cows.

Results: Doses of 100 to 500 mg of the Sijunzi San significantly enhanced gas production, microbial protein (MCP), and short-chain fatty acid (SCFA) levels, while notably reducing pH and NH₃-N content (p < 0.05), exhibiting a significant dose-dependent relationship. The results revealed that 500 mg of the prescription significantly increased the abundances of the Succiniclasticum and Prevotella genera and notably decreased the abundances of the Christensenellaceae_R-7_group, Muribaculaceae, UCG-005, Comamonas, and F082 genera (p < 0.05). Succiniclasticum and Prevotella showed a significant positive correlation with ruminal SCFAs, whereas UCG-005 exhibited a significant negative correlation with them (p < 0.05). Additionally, Luteolin and Glycitein were significantly positively correlated with Prevotella, while Licochalcone B and Liquoric acid were significantly negatively correlated with Comamonas (p < 0.05). Subsequently, the prescription significantly increased the concentrations of IgA, IgM, and microsomal triglyceride transfer protein (MTTP) in the blood (p < 0.01), while reducing the levels of ketones (KET) (p < 0.05), non-esterified fatty acids (NEFA), and triglycerides (TG) (p < 0.01). Notable alterations were observed in 21 metabolites in the blood metabolome (p < 0.05). Additionally, metabolic pathways associated with linoleic acid metabolism and steroid hormone biosynthesis were significantly affected.

Discussion: The findings suggest that administering Sijunzi San to dairy cows during the postpartum period can ameliorate negative energy balance by stimulating rumen fermentation and modifying the composition and abundance of the rumen microbiota.

Keywords: Sijunzi San; lipid metabolism; negative energy balance; rumen fermentation; rumen microorganisms.

Figure 1

Base peak chromatograms of positive and negative ion modes of Sijunzi San. (A) Positive ion mode; (B) Negative ion mode.

Figure 2

Effect of different doses of Sijunzi San on rumen gas production in dairy cows (n = 5). CONT represented control group and 100–500 mg represented different doses groups of Sijunzi San.

Figure 3

Effect of Sijunzi San on rumen fermentation parameters in dairy cows (n = 5). CONT represented control group, 100 ~ 500 mg represented different doses of Sijunzi San; (A) pH; (B) NH₃-N; (C) MCP, microbial protein. Different letters indicated significant differences (p < 0.05), while the same letters indicated non-significant differences (p > 0.05).

Figure 4

Effect of Sijunzi San on SCFAs in the rumen of dairy cows (n = 5). CONT represented control group, 100 ~ 500 mg represented different doses of Sijunzi San; (A) SCFAs; (B) Acetate; (C) Propionate; (D) N-butyric acid; (E) Isobutyric acid; (F) N-valeric acid; (G) Isovaleric acid. Different letters indicated significant differences (p < 0.05), while the same letters indicated non-significant differences (p > 0.05).

Figure 5

Effect of Sijunzi San on rumen microbiota diversity of dairy cows. CONT represented the control group and SJZS represented the Sijunzi San group. (A) OTU Venn plots of rumen microorganisms in two groups. (B) Specaccum species cumulative plots, with the sample size as the horizontal coordinate and the number of observed species (ASV/OTU) as the vertical coordinate. The blue shading reflects the confidence intervals for the curves. (C) Abundance Ranking plot, with the horizontal coordinate being the ordinal number of ASVs/OTUs in order of abundance and the vertical coordinate being the log2 value of the abundance of each ASV/OTU in the group. (D) Alpha diversity analysis. The Chao1 index is used to assess the total number of OTUs present in the community. The Simpson index is used to assess community evenness. And the Shannon index is used to combine the assessment of the community’s richness and evenness. (E) Principal Coordinate Analysis (PCoA) of two groups of rumen microbes. (F) Non-Metric Multidimensional Scale Analysis (NMDS) of two groups of rumen microbes.

Figure 6

Differential microbiota analysis of Sijunzi San on rumen microbiota composition in postpartum dairy cows. CONT represented the control group and SJZS represented the Sijunzi San group. (A,B) Histograms of species composition abundance for the TOP20 at phylum level and genus level respectively, with each horizontal bar representing a species. (C,D) Graphs of Stamp species difference analysis based on phylum level and genus level, respectively.

Figure 7

Spearman correlation heatmap. (A) Heatmap of correlation between ruminal differential microbes and SCFAs; (B) Heatmap of correlation between active ingredients in Sijunzi San and ruminal differential microbes. Red indicated positive correlation, blue indicated negative correlation, * indicated p < 0.05, ** indicated p < 0.01 and *** indicated p < 0.001.

Figure 8

Effect of Sijunzi San on immune response of postpartum dairy cows (n = 8). CONT represented control group, SJZS represented Sijunzi San group; (A) IgA; (B) IgG; (C) IgM. Each black dot represented a sample, * indicated p < 0.05 and ** indicated p < 0.01.

Figure 9

Effect of Sijunzi San on blood lipid metabolism of postpartum dairy cows (n = 8). CONT represented control group, SJZS represented Sijunzi San group; (A) KET: ketones; (B) NEFA: non-esterified fatty acids; (C) TG: triglycerides; (D) MTTP: microsomal triglyceride transfer protein; Each black dot represented one sample, * indicated p < 0.05, ** indicated p < 0.01.

Figure 10

Effect of Sijunzi San on blood metabolome of postpartum dairy cows. CONT represented the control group and SJZS represented the Sijunzi San group. (A) Principal Component Analysis (PCA) demonstrating the trend of intra-group aggregation and inter-group separation of the two groups of rumen fluid samples. (B) Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) score plot demonstrating the trend of separation of the two groups of rumen fluid samples. (C) OPLS-DA permutation test plot for seeing whether overfitting occurred in the OPLS-DA model. (D) Volcano plot demonstrating the trend of differential metabolites, with each dot representing a metabolite. Red indicated up-regulation and blue indicated down-regulation, and the size of the dots indicated the Variable importance for the projection (VIP) value. (E) Clustering heatmap of differential metabolites, with the horizontal coordinate indicating the samples and the vertical coordinate indicating the metabolites. Red cooler indicated up-regulation and blue cooler indicated down-regulation.

Figure 11

KEGG pathway enrichment analysis of differential metabolites. Bubble plot of KEGG enrichment analysis, the size of the dots indicated the number of enriched differential metabolites, and the color shade of the dots indicated the significance of the pathway.

Figure 12

Mechanism of Sijunzi San in alleviating negative energy balance in postpartum cows by regulating the structure of rumen microbiota and fermentation capacity of postpartum cows. Created with Figdraw (https://www.figdraw.com).