Dietary supplementation of <i>S</i><i>cutellariae radix</i> flavonoid extract improves lactation performance in dairy cows by regulating gastrointestinal microbes, antioxidant capacity and immune function

Dietary supplementation of Scutellariae radix flavonoid extract improves lactation performance in dairy cows by regulating gastrointestinal microbes, antioxidant capacity and immune function

PDF

Dongwen Dai^a^,^b, Chunxiao Dong^a^,^b, Fanlin Kong^a, Shuo Wang^a, Shuxiang Wang^c, Wei Wang^a^,^*, Shengli Li^a^,^b^,^*

Animal Nutrition | 2025, 20(1) : 499 - 508

Less

Animal Nutrition | 2025, 20(1): 499-508

• Original Research Article •

Dietary supplementation of Scutellariae radix flavonoid extract improves lactation performance in dairy cows by regulating gastrointestinal microbes, antioxidant capacity and immune function

Full

Dongwen Dai^a^,^b, Chunxiao Dong^a^,^b, Fanlin Kong^a, Shuo Wang^a, Shuxiang Wang^c, Wei Wang^a^,^*, Shengli Li^a^,^b^,^*

Affiliations

^aState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China

^bCollege of Animal Science and Technology, Ningxia University, Yinchuan 750021, China

^cQinghai University, Xining 810016, China

Published: 2025-03-10 doi: 10.1016/j.aninu.2024.11.019

Outline

Abstract

Less

Scutellariae radix flavonoid extract (SFE) has been acknowledged for its antioxidant, anti-inflammatory and antimicrobial properties in enhancing gastrointestinal microbial communities and improving the host’s immunity. Nevertheless, the impacts of dietary supplementation with SFE on the gastrointestinal microbes and host metabolism in dairy cows remain uncertain. Therefore, the aim of this study was to assess the effects of dietary supplementation with SFE on the lactation performance, gastrointestinal microbes, and plasma biochemical parameters of dairy cows. Six ruminally and duodenally cannulated multiparous dairy cows were used in a crossover design over 28-d periods that included a 21-d adaptation and a 7-d sample collection period. Cows were fed a basal diet (CON group) or a basal diet supplemented with SFE at 25 g/d (SFE group). SFE supplementation tended to increase milk yield (P = 0.067) and milk urea N concentration (P = 0.079), and decreased the milk somatic cell counts (SCC, P = 0.036). Cows in the SFE group had lower plasma aspartate aminotransferase (AST), malondialdehyde (MDA), tumor necrosis factor (TNF-α), and interleukin-1β concentrations compared with the CON (P < 0.05). Meanwhile, SFE supplementation increased butyrate concentration in the rumen (P = 0.044). The microbial structure of rumen and duodenum were affected by SFE supplementation (P = 0.009 and P = 0.031; respectively), resulting in enrichment of Butyrivibrio in both parts of the SFE cows (P = 0.034 and P = 0.029; respectively). However, microbial structure and composition of feces were not affected by SFE supplementation. Overall, our study indicated that dietary supplementation with SFE could enhance lactation performance and milk quality in dairy cows by improving the gastrointestinal inner environment and health status.

Key words

Scutellariae radix flavonoid extract / Milk production / Gastrointestinal microbes / Fermentation profile / Dairy cow

Cite this Article

Dongwen Dai, Chunxiao Dong, Fanlin Kong, Shuo Wang, Shuxiang Wang, Wei Wang, Shengli Li. Dietary supplementation of Scutellariae radix flavonoid extract improves lactation performance in dairy cows by regulating gastrointestinal microbes, antioxidant capacity and immune function[J]. Animal Nutrition, 2025 , 20 (1) : 499 -508 . DOI: 10.1016/j.aninu.2024.11.019

Full Text

Less

1.　Introduction

Less

In recent years, significant advancements in genetic, nutrition and farm management have greatly enhanced productivity and fulfilled the demand for dairy products. However, these strategies often necessitate feeding dairy cows high-concentrate diets and maintaining high stocking densities (Abdela, 2016; Zhou et al., 2023). Previous studies have indicated that dairy cows fed high-concentrate diets are constantly exposed to a greater metabolic load, including oxidative stress, which is associated with increased production diseases and culling rate (Ma et al., 2022; Mcart and Neves, 2020). Furthermore, it is well recognized that the dairy production chain is a potential transmission route of antibiotic residues, which in turn increases the risk of resistant bacteria in susceptible populations (Jank et al., 2015), and antibiotic-resistant genes and bacteria in manure can promote environmental contamination (Oliver et al., 2020). Given the potential risks associated with antibiotic residues, supplementation with plant extracts, which are rich in bioactive compounds such as polyphenols (Barbato et al., 2019) and flavonoids (Tilahun et al., 2022), may offer a safe and reliable approach to improving the lactation performance and health status of dairy cows (Ciampi et al., 2020; Kolling et al., 2018).

Scutellariae radix is a widely used herb in traditional Chinese medicine, known for its antioxidant, anti-inflammatory, and antimicrobial properties (QY Zhao et al., 2018; Gao et al., 1999). Flavonoids are believed to elicit these effects. Baicalin, baicalein, wogonin, and chrysin are four main flavonoids in Scutellariae radix (Li and Chen, 2005). Owing to these beneficial attributes, the application of Scutellariae radix has been extended to livestock farming, with numerous studies demonstrating that dietary supplementation with Scutellari baicalensis extract can enhance growth performance, nutrient digestibility, and the abundance of beneficial intestinal microbes (Zhang et al., 2022; Zhao et al., 2016). In a recent study, Olagaray et al. (2019) reported that adding S. baicalensis extract at a dosage of 60 g/d (containing 33% baicalin) increased milk yield and reduced milk somatic cell counts (SCC). However, most flavonoids exhibit poor aqueous solubility characteristics, extensive metabolism, as well poor systemic absorption, resulting in lower bioavailability and bioactivity (Zhao et al., 2019). In monogastric animals, a series of studies have demonstrated that flavonoids have limited bioavailability after oral administration, with the majority not being absorbed and remain in the colon (Zeng et al., 2020; Song et al., 2020); therefore, it is not clear whether flavonoids are absorbed across the rumen epithelium in ruminants. It was demonstrated that rumen microbes are known to have the capability of partially deglycosylating naringin and hesperidin (Gladine et al., 2007). Hence, a comprehensive determination of the effects of SFE on gastrointestinal (rumen, small intestine, and large intestine) microbes and fermentation profiles can be used to improve lactation performance and the health of dairy cows.

We hypothesized that dietary supplementation with SFE would enhance the fermentation profile and immune status of dairy cows by regulating gastrointestinal microbes, resulting in a positive impact on their lactation performance. Therefore, the current study aimed to evaluate the effects of dietary supplementation with SFE on milk performance, plasma immune indices, gastrointestinal microbes (rumen, duodenum, and feces), and fermentation profiles.

2.　Materials and methods

Less

2.1.　 Animal ethics statement

All animal procedures were approved by the Institutional Animal Care and Use Committee of the China Agricultural University (protocol number: AW42504202-1-2).

2.2.　 Scutellariae radix flavonoid extract (SFE) preparation, animals, and experimental design

The SFE product was purchased from Shanxi Snout Biotechnology Co., Ltd. (Shanxi, Baoji, China). SFE was extracted from the root of scutellaria baicalensis Georgi. In brief, 1 kg scutellaria powder was ultrasonically extracted with 8 L ethanol (80%) for 25–40 min. Then, the mixture underwent reflux extraction to obtain the extract, and the extract was concentrated and adjusted to pH 2 with citric acid, filtered and dried (70 °C) to get the crude SFE. The crude SFE was extracted with 8 times distilled water, adjusted to the pH value of 2 with citric acid, and heated at 80 °C for 30 min. Finally, the precipitate was collected by centrifugation (3500 × g for 10 min at 4 °C) and lyophilized for 24 h to obtain high purity SFE. The total flavonoid content (85.13%) of SFE was determined using the method of Pitz et al. (2016). The concentrations of major flavonoids, including baicalin, chrysin, biochanin A, and apigenin in SFE were determined using a UPLC equipped with a BEH C18 column (2.1 mm × 100 mm, 1.7 μm, Waters, USA) according to the method of De et al. (2016). The chemical composition of SFE is shown in Table S1.

This study was conducted at the Institute of Yuexiu Huishan Dairy Research Farm in Shenyang City, China, from July to September 2023. Six ruminally and duodenally cannulated multiparous Holstein dairy cows (2.5 ± 0.5 parity, 680 ± 36 kg of BW, and 84 ± 7 days in milk) were used in a crossover design with 28-d periods that included a 21-d adaptation and a 7-d sample collection period. Cannulation was performed using a 10-cm internal diameter ruminal cannula (Anscitech Farming Technology Co., Ltd., Wuhan, China) and a gutter-type T cannula placed approximately 10 cm distal to the pylorus (duodenally) (Wang et al., 2023) approximately 40 d postpartum. Cows were randomly assigned to two dietary treatments: basal diet (CON group) or basal diet supplemented with 25 g/d of SFE per cow (SFE group). The dose of SFE used in the current study was determined according to an in vitro test conducted by a team member through a rumen simulation technique. The results showed that 0.1% DM SFE in the TMR had the best effect on rumen fluid incubation performance in dairy cows (unpublished data). Therefore, the dose in the current study was calculated as 0.1% of the average DMI (25 kg/d per cow), resulting in 25 g/d per cow. The SFE product was top-dressed daily and mixed with a small amount of total mixed ration (TMR) during morning feeding according to a previous study (Oh et al., 2015). Each cow was housed separately, and the diets were fed twice daily at 08:00 and 15:00 for ad libitum intake at approximately 110% of actual feed intake. Water was available ad libitum through individual water troughs. All cows were milked at 08:00 and 20:00 daily using a hand-pushed milking machine (Zibo Zhisong Electric Motor Co., China), and milk weights were manually recorded. The experimental diet contained 27.74% starch, 28.59% neutral detergent fiber (NDF), 18.64% acid detergent fiber (ADF), and other nutrients to meet the NRC (2021) nutrient requirements (Table 1).

2.3.　 Sampling and analysis

During the 7-d sample collection period (d 22-28), both orts and TMR were recorded for the determination of DMI. TMR samples were collected on three consecutive days weekly from Friday to Sunday to get a representative sample of the diet fed to the animals, and orts were obtained daily from each cow at 07:30. TMR and orts samples were dried in a forced-air oven (DGG-9240B; Shanghai-ShenXin Inc., Shanghai, China) at 55 °C for 48 h, then ground through a 1-mm screen before analysis. Standard procedures of the Association of Official Analytical Chemists were used to determine dry matter (method 935.29; AOAC, 2006) and crude ash (method 942.05; AOAC, 2006). The organic matter (OM) content of the feeds was calculated by DM subtracting crude ash content. The crude protein (CP) contents of the TMR and orts were analysed according to the Macro-Kjeldahl procedure (method 990.03; AOAC, 2006). The concentration of ether extract (EE) was analysed according to the method 920.39 of AOAC (2006). Neutral detergent fiber and ADF contents were determined according to the method described by Van Soest et al. (1991), using a heat-stable α-amylase and sodium sulphite. Starch content was determined using a total starch assay kit (Megazyme) based on the method 996.11, AOAC (2006).

Milk weight was manually recorded during the 7-d sample collection period. Milk samples were collected in a 50 mL centrifuge tube with a preservative (2-bromo-2-nitropropane-1,3-diol) during the last 3 d (d 26-28) of morning and afternoon milking. Milk samples collected twice a day were mixed at a ratio of 6:4 of morning and afternoon (Shan et al., 2018). The pooled samples were quickly sent to the Beijing Dairy Cow Center for determination of milk composition, including fat, protein, and lactose, using a near-infrared reflectance spectroscopy analyser (Seris300 Combi-FOSS; Foss Electric). Energy-corrected milk (ECM) was calculated as follows: ECM = (12.95 × fat yield) + (7.65 × protein yield) + (0.327 × milk yield), and 3.5% fat-corrected milk (FCM) was calculated as follows: 3.5% FCM = (0.4324 × milk yield) + (16.23 × fat yield) according to a previous study (Liu and Vandehaar, 2020). Blood samples were collected from the coccygeal vein 2 h after morning feeding on d 28 of each period. Blood samples (approximately 10 mL) were collected into vacuumed tubes, incubated at room temperature for about 30 min, and centrifuged at 3000 × g at 4 °C for 15 min to obtain plasma, which was separated into 2.0-mL tubes, frozen, and stored at –20 °C until further analysis. Plasma concentrations of glucose (GLU), insulin (INS), urea nitrogen (UN), aspartate aminotransferase (AST), and alanine transaminase (ALT) were determined using a GF-D200 automatic biochemical analyser (Jiangsu Zecheng Bioengineering Institute, CLS880, Jiangyin, China), as described by Zhang et al. (2023). Plasma beta-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) were measured using commercial kits (Nanjing Jiancheng Bioengineering Institute) following the method described by Sun et al. (2021). Plasma levels of malondialdehyde (MDA), total antioxidant capacity (T-AOC), and glutathione peroxidase (GSH-Px) were determined using commercial kits (Nanjing Jiancheng Bioengineering Institute), according to a previous study (Zou et al., 2012). The concentrations of tumour necrosis factor-α (TNF-α), amyloid-A (SAA), haptoglobin (HPT), and interleukin-1β (IL-1β) in plasma were measured using commercial kits (Nanjing Jiancheng Bioengineering Institute) according to the manufacturers' guidelines. Samples of rumen fluid, duodenal digesta, and faecal samples were collected 2 h after morning feeding on d 28. Approximately 50 mL each of rumen fluid and duodenal digesta, and 50 g of faecal sample were collected from each cow, and ruminal pH was immediately determined using a portable pH meter (Testo206, Schwarzwald, Germany). Then, every sample was divided into three plastic containers and frozen immediately in liquid nitrogen. One was used for microbiota analysis and the other was used to determine the volatile fatty acids (VFA). The VFA concentration in rumen fluid and duodenal digesta samples were determined according to the method described by Dai et al. (2023). Briefly, 0.4 mL of 25% ortho-phosphoric acid and 0.3 mL internal standard 4-methylvaleric acid (internal standard) were added into the 2 mL thawed fluid, and the mixture was centrifuged at 15,000 × g for 15 min at 4 °C. Subsequently, the supernatant was analysed for VFA composition using a gas chromatograph (Agilent 6890N, Agilent Technology, Inc, Beijing, China) equipped with a DB-FFAP capillary column (30 m × 0.32 mm × 0.5 μm). The conditions were as follows: the temperatures of the injector and detector were maintained at 220 and 250 °C, respectively, with a splitting ratio of 30:1 and high-purity nitrogen flow of 40 mL/min. The concentrations of VFA in the faecal samples were measured according to a previous study by Petri et al. (2019) with minor modifications. Briefly, 2 g of thawed faeces from each sample was mixed with 2 mL of distilled water. Then, 0.6 mL of an internal standard (4-methylvaleric acid; Sigma–Aldrich, St. Louis, MO, USA) and 0.4 mL of 25% phosphoric acid were added. The subsequent procedure was consistent with the rumen fluid determination method. Regarding the rumen fluid samples, the ammonia-nitrogen (NH₃–N) concentration was determined according to a phenol hypochlorite assay as described by Broderick and Kang (1980), and ruminal microbial protein (MCP) concentration was determined based on the method of Makkar et al. (1982).

2.4.　 DNA extraction, PCR amplification, and high-throughput sequencing

Total genomic DNA from rumen fluid, duodenal digesta, and faecal samples were extracted using an E.Z.N.A Soil DNA Kit (Omega Bio-Tek, Norcross, GA, USA) (Kong et al., 2022). DNA concentration and purity were determined using a NanoDrop 2000 UV–visible spectrophotometer (Thermo Scientific, Wilmington, DE, USA) and DNA quality was monitored using 1% agarose gel electrophoresis. The V3 and V4 hypervariable regions of the 16S rRNA gene were amplified with a specific primer pair: 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) using ABI GeneAmp 9700 PCR thermal cycler (ABI), as per the method described in a previous study (Liu et al., 2023a). The PCR products were visualised in a 2% agarose gel, purified and quantified by AxyPrep DNA gel extraction kit (Axygen Biosciences, Union City, CA, USA) and QuantiFluor-ST (Promega, USA), respectively. Finally, paired-end sequencing libraries were generated using an Illumina MiSeq PE300 platform (Illumina, San Diego, CA, USA) at Paysono Bioinformatics Technology Co., Ltd. (Shanghai, China). All raw sequencing data have been deposited in the NCBI Sequence Read Archive (SRA) (Accession Number: PRJNA1103999).

2.5.　 Sequence processing and analysis

Paired-end reads were assigned to the samples based on their unique barcodes and truncated by removing the barcodes and primer sequences. The raw read pairs were overlapped and merged using FLASH (v1.2.11) (Magoc and Salzberg, 2011), then imported to QIIME2 (Version 2022.2) for demultiplexing (Bolyen et al., 2019). Quality control, denoising, removal of chimeric sequences, and generation of amplicon sequencing variants (ASV) were performed using the QIIME2 plugin, DADA2 (Callahan et al., 2016). The SILVA database (version 138) was used for ASV classification labelling analysis, and the microbial species composition at different taxonomic levels (phylum, class, order, family, genus, and species) was obtained. Several alpha diversity indices, including Sobs, ACE, Chao1, Simpson, and Shannon indices, were calculated using QIIME 2. The microbial β-diversity was determined using the distance matrices generated from Bray–Curtis analysis, principal coordinate analysis (PCoA), and ANOSIM analysis. LEfSe was used to identify significantly different taxa between the different treatment groups (Segata et al., 2011).

2.6.　 Statistical analysis

The analysis of milk performance, fermentation parameters, inflammatory cytokines, and oxidative stress indices data in plasma were conducted with SAS (version 9.4, SAS Institute Inc., USA) using the PROC MIXED statement and the following model:

where Y_iikl is the observations for dependent variables, μ is the overall mean, T_i is the fixed effect of treatment (i = CON, SFE), P_j is the fixed effect of the period (j = 1-2), B_k is the fixed effect of square (k = 1-2), C_l(_k) is the random effect of cow nested within the square (l = 1-6), and e_ijkl is the residual error. A t-test was used to identify differences in the means of milk performance, fermentation parameters, inflammatory cytokines, and oxidative stress indices data in plasma. Differential microbial composition and α-diversity were compared using a Welch’s t-test between the two groups, and the P-value was corrected by false-discovery rate adjustment. All results were reported as means ± standard error of the mean, and significant differences were declared when P ≤ 0.05, and 0.05 < P < 0.10 was defined as a trend of difference.

3.　Results

Less

3.1.　 Feed intake, milk production and composition

As shown in Table 2, SFE supplementation did not influence the DMI of the cows (P = 0.165). Similarly, no differences were observed between the CON and SFE groups regarding milk composition parameters, including milk fat, protein, and lactose contents (P > 0.10). Milk yield tended to increase (P = 0.067) with SFE supplementation compared to the CON group (35.35 vs. 32.84 kg/d). Cows that received SFE tended to have greater milk MUN concentration (P = 0.079; 10.93 vs. 9.63 mg/dL). Moreover, milk SCC was significantly lower (P = 0.026) in SFE cows than in the CON cows.

3.2.　 Plasma metabolites, liver enzymes, oxidative status, inflammation and acute-phase proteins

Regarding the plasma metabolites, SFE supplementation did not affect the plasma levels of GLU, INS, UN, BHB, or NEFA (P > 0.10; Table 3). Compared to the CON group, SFE supplementation significantly increased the plasma concentrations of T-AOC (P = 0.032), while decreased the plasma AST (P = 0.013) and MDA (P = 0.013) levels. Regarding plasma inflammation and acute-phase proteins, SFE supplementation significantly reduced plasma TNF-α (P = 0.010) and IL-1β (P = 0.001) levels; however, plasma SAA and HPT levels were not affected by SFE supplementation (P > 0.10).

3.3.　 Fermentation profile in the ruminal, duodenal, and fecal contents

Regarding the ruminal fermentation profile, SFE supplementation significantly increased the butyrate concentration (P = 0.044; Table 4), whereas the TVFA, acetate, propionate, isobutyrate, valerate, and isovalerate concentrations were not altered by SFE supplementation (P > 0.10). Moreover, supplementing SFE did not significantly affect the rumen fluid pH and NH₃–N concentration (P > 0.10), while the ruminal MCP concentration was increased (P = 0.037) with SFE supplementation. SFE supplementation did not significantly affect the concentrations of TVFA, acetate, propionate, or butyrate in the duodenum or faeces (P > 0.10), and the pH was unaffected by SFE addition (P > 0.10).

3.4.　 Taxonomic configurations of ruminal, duodenal, and faecal bacteria

The effect of SFE supplementation on gastrointestinal microbes in cows was evaluated using 16S rRNA high-throughput sequencing. Regarding ruminal diversity indices, including the Chao1 (P = 0.427) and Shannon (P = 0.264) indices, no differences were found between the CON and SFE groups (Fig. 1A and B). Furthermore, the beta diversity of rumen bacteria was determined by principal coordinate analysis, explaining 27.0% and 15.5% of the variance, respectively, and a distinct separation was found between the CON and SFE groups (weighted UniFrac, ANOSIM: P = 0.009; Fig. 1C), indicating that feeding SFE modified ruminal microbial structure significantly. Bacteroidetes (49.84%), Firmicutes (42.22%), Actinobacteria (1.18%), Proteobacteria (0.53%), and Tenericutes (1.09%) were the dominant bacterial phyla in the two groups (Fig. 1D), and feeding SFE to dairy cows significantly reduced the relative abundances of Tenericutes (P = 0.005) and Spirochaetes (P = 0.041) in comparison with that of cows fed the CON diet (Table 5). The ruminal microbiome was dominated by Prevotella (23.20%), Ruminococcaceae_Ruminococcus (8.97%), Succiniclasticum (5.22%), Butyrivibrio9 (2.34%), YRC229 (1.16%), and Oscillospira (0.97%) at the genus level (Fig. 1E). Feeding SFE to dairy cows significantly increased the relative abundance of Butyrivibrio (P = 0.034) in the SFE group when compared to that in the CON group, and a tendency of lower abundance of CF231 (P = 0.084) was found in SFE group when compared to that of the CON group (Table 6). We used LEfSe analysis (LDA ≥3, P < 0.05) to identify significantly differential bacterial taxa between the CON and SFE groups. Thirteen biomarkers were identified. Fibrobacteria, Fibrobacteres, Fibrobacteraceae, Fibrobacterales, Bifidobacterium, Fibrobacter, Spirochaetales, Spirochaetaceae, Treponema, Spirochaetes, Spirochaetes, and RFN20 were enriched in the CON group, and Lachnospiraceae was enriched in the SFE group (Fig. 1F).

No differences were found in the alpha diversity indices, including the Chao1(P = 0.348) and Shannon (P = 0.752) indices, between the duodenum in the CON and SFE groups (Fig. S1A, B), whereas PCoA analysis based on weighted UniFrac metrics showed that feeding SFE significantly altered the duodenal microbial structure (weighted UniFrac, ANOSIM: P = 0.031; Fig. S1C). As diagrammed in Fig. S1D, Firmicutes (70.85%), Proteobacteria (11.2%), Actinobacteria (9.69%), and Bacteroidetes (6.53%) were the predominant phyla in both the groups, whereas SFE-supplemented cows had a lower relative abundance of Spirochaetes (P = 0.034; Table S2) compared to the cows in the CON group. The dominant genera were Butyrivibrio (8.85%), Ruminococcaceae_Ruminococcus (5.84%), Prevotella (4.23%), Oscillospira (3.49%), Sharpea (3.23%), Coprococcus (3.20%), and Succiniclasticum (2.75%) in both the groups (Fig. S1E), and the relative abundance of Butyrivibrio was higher in the SFE cows than in the CON cows (P = 0.03). However, the relative abundances of Ruminococcaceae_Ruminococcus (P = 0.010), Coprococcus (P = 0.029), and Clostridiaceae_Clostridium (P = 0.004) were decreased by SFE supplementation compared to the CON group (Table S3). Furthermore, we used LEfSe analysis to discover and elaborate marker microbes between the CON and SFE groups (LDA ≥3.5, P < 0.05). Compared to the CON group, the relative abundances of Coriobacteriales, Christensenellaceae, Pseudobutyrivibrio, Moryella, and Nocardiopsaceae were higher in the SFE group, whereas those of Ruminococcaceae, Erysipelotrichi, Erysipelotrichaceae, Eiysipelotrichales, Sharpea, Ruminococcus, Coprococcus, Ruminobacter, Lactococcus, Neisseriaceae, Clostridiaceae, Clostridium, Moryella, Pseudobutyrivibrio, and Christensenellaceae were higher in the CON group (Fig. S1F).

A remarkable difference was found in the alpha diversity indices of the faeces, including the Chao1 (P = 0.019) and Shannon (P = 0.008) indices, which were higher in the CON group than in the SFE group (Fig. S2A, B), whereas we did not observe a distinct separation between CON and SFE, indicating that feeding did not alter the faecal microbial structure (weighted UniFrac, ANOSIM: P = 0.10; Fig. S2C). As illustrated in Fig. S2D, Firmicutes (63.09%), Bacteroidetes (29.81%), Actinobacteria (2.85%), Spirochaetes (1.99%), and Proteobacteria (1.03%) were the dominant bacterial phyla in both the groups (Fig. S2D), and no significant differences in the phyla were observed between the CON and SFE groups (P > 0.05, Table S4). Clostridiaceae_Clostridium (3.24%), Bifidobacterium (2.57%), 5-7N15 (2.55%), Roseburia (2.45%), and Treponema (1.99%) were the dominant genera in both the groups (Fig. S2E), and no significant differences were found between the CON and SFE groups (P > 0.10; Table S5). We used LEfSe analysis to identify significantly differential bacterial taxa between the CON and SFE groups (LDA ≥3, P < 0.05). Erysipelotrichi, Erysipelotrichaceae, Erysipelotrichales, Fusobacteria, Tenericutes, Fusobacteriaceae, Mollicutes, Oscillospira, Phascolarctobacterium, Cetobacterium, Anaeroplasmataceae, and Anaeroplasmatales were enriched in the SFE group (Fig. S2F).

4.　Discussion

Less

Flavonoid-rich extract has emerged as a promising phytogenic feed additive for improving the performance and health of ruminants (Alhidary and Abdelrahman, 2016; Yu et al., 2023). However, few studies have investigated the effects of dietary SFE supplementation on lactation performance, gastrointestinal microbes, antioxidant capacity, and immune function in ruminants. DMI was not significantly affected by SFE supplementation, indicating that SFE did not affect palatability. This is in accordance with the findings of Aguiar et al. (2014), who found that cows fed diets supplemented with flavonoid-rich extracts of propolis at rates of 3.81, 3.27, or 1.93 mg/kg of ingested dry matter (DM) did not differ among treatments (Aguiar et al., 2014). The tendency for higher milk yield in SFE-fed cows was similar to that reported by Yu et al. (2023), who found that citrus extract supplementation positively affected milk yield in cows. Similar research reported that adding flavonoid extract to dairy cow diets had a positive effect on milk fat (Totakul et al., 2022) or lactose (Olagaray et al., 2019), which was contrary to what was observed in our experiment, therefore, the lack of consistent results could be attributed to the differences in the types of flavonoid extracts, dietary nutrient levels (energy, CP, etc.), and lactation stage between studies. Increased somatic cells in milk reflect poor breast health and milk quality, which are serious issues in modern dairy cow farming that result in considerable financial losses to the dairy husbandry. Nearly 70% of the subclinical breast infections are associated with a temporary or permanent reduction in milk production, mainly due to inflammatory damage to the mammary tissue (Eckersall et al., 2006). In the present study, a reduced milk SCC was observed after each cow received 25 g/d SFE supplementation, which may, in part, be attributed to SFE improving the antioxidant capacity of dairy cows. This is in accordance with similar studies that reported a positive effect on milk SCC in cows that received diets supplemented with flavonoid-rich extracts, such as bamboo leaves (Zhan et al., 2021), citrus (Yu et al., 2023), and quercetin (Burmańczuk et al., 2018). Moreover, a cellular research study reported that baicalin protected cow mammary epithelial cells from lipopolysaccharide (LPS) induced inflammatory injury and apoptosis by attenuating inflammation response (Yang et al., 2016). The milk MUN concentration is generally used to evaluate the balance between carbohydrates and nitrogen sources in the rumen environment (Aguilar et al., 2012); SFE supplementation tended to increase milk MUN concentrations in our study. Increased concentrations of MUN could be attributed to the excessive amount of NH₃ being absorbed from the rumen and converted to urea into the blood system which easily passes through to the milk (Broderick and Clayton, 1997). The greater ruminal NH₃–N concentration in the SFE group observed in this study could confirm this, although it was not statistically significant. In contrast, the results of the present study differ from those of Dschaak et al. (2011), who observed a negative effect of condensed tannin extract supplementation on milk MUN. The lack of consistent results can be attributed to the differences in influencing the DMI. A higher DMI was observed in the SFE cows than in the CON cows, which did not reach statistical significance in the present study. In contrast, Dschaak et al. (2011) observed a negative effect on DMI with a decrease in intakes of 1.75 kg/d, when lactating dairy cows were fed diets supplemented with condensed tannin extract. These results demonstrate the potential benefits of SFE supplementation on milk production in dairy cows.

No effect of SFE supplementation on plasma concentrations of GLU, INS, UN, BHBA, or NEFA was observed. Similar to our study, some previous studies have reported no difference in the plasma concentrations of energy and protein in ruminants receiving diets supplemented with flavonoid-rich extracts from propolis (Varela et al., 2023), quercetin (Gruse et al., 2016), or cabbage (Gao et al., 2022) compared to those fed the CON diets. The liver is a critical organ in the metabolism and adaptation of dairy cows, as well as for coordinating the metabolism of the stomach, intestines, adipose tissue, and mammary glands (Drackley, 1999). AST and gamma-glutamyl transferase (GGT) are important aminotransferases in animals and are considered valuable indicators of hepatic injury. In the present study, the plasma AST concentration in SFE cows decreased compared with those in the CON cows, which is consistent with the result that SFE supplementation had a positive effect on protecting liver injury in chicks (Xu et al., 2021). Thus, the results of our study indicated that SFE supplementation improves liver metabolism in cows. The dynamic balance of free radicals in an organism is primarily achieved by antioxidant enzymes that maintain the normal function and metabolism of the animal body (Khan et al., 2020). In fact, as a comprehensive index for evaluating the antioxidant system, plasma T-AOC reflects the cumulative effect of antioxidants in animals, with a higher concentration indicating greater antioxidant capacity (Kampa et al., 2002). In contrast, plasma MDA is a lipid peroxidation product, and a lower MDA concentration reveals that the organism has low oxidative stress (Zhao et al., 2014). Previous studies confirmed that flavonoid-rich extracts improve the antioxidant capacity of animals. For example, Liu et al. (2023b) observed that supplementation with moringa leaf flavonoids in the diet of dairy cows resulted in an enhanced antioxidant capacity and increased plasma SOD and T-AOC levels paralleled with reduced MDA levels. In addition, a previous study on pre-weaning calves fed mulberry leaf flavonoids showed a positive effect on oxidative stress and increased GSH-PX and SOD levels (Wang et al., 2018). In the present study, increased T-AOC paralleled with reduced MDA concentration in plasma was observed after SFE supplementation, indicating that the antioxidative capacity of dairy cows was enhanced by SFE supplementation, which is in line with the above results, potentially due to flavonoids acting as reducing agents and hydrogen donors to neutralise oxygen radicals and remove hydrogen peroxide and superoxide ions (Kahkonen et al., 1999). TNF-α and IL-1β are mainly proinflammatory cytokines and are released during inflammatory processes (Gabay and Kushner, 1999). Indeed, the increase in pro-inflammatory cytokines is a sign of oxidative stress (Dinda et al., 2017) with alterations of mitochondrial functionality and an increase in free radical production (Musco et al., 2020). Notably, a previous study has reported that supplementing citrus flavonoid extract (CFE) can effectively reduce the serum concentrations of inflammatory cytokines (IL-6, TNF-α) in high-grain fed dairy cows, suggesting that CFE could reduce the inflammatory response. Moreover, a recent study evaluated the effect of CFE on systemic inflammation and showed that these extracts had a positive effect on reducing serum concentrations of LPS proinflammatory cytokines (TNF-α and interleukin-6), acute phase proteins (LPS-binding and HPT protein) in dairy cows (Zhao et al., 2023a,b). In the current study, dietary supplementation with SFE reduced plasma TNF-α and IL-1β concentrations, indicating that SFE supplementation could enhance immune function in dairy cows.

VFA act as the major carbon source for ruminal microbes and provide 60%–80% digestible energy for ruminants (Galyean, 2014). Furthermore, concentration and composition are important indicators of rumen fermentation status and microbial composition (Bergman, 1990). Previous studies have demonstrated that dietary supplementation with flavonoid-rich extracts affects the concentration or composition of rumen VFA (Ma et al., 2017; Yu et al., 2023). We observed that supplementation with SFE increased ruminal butyrate concentration, which might be attributed to the greater abundance of Butyrivibrio, which has been recognised as a producer of butyrate (Wang et al., 2021). Butyrate, a major energy source in the gastrointestinal tract, is important in regulating the gut immune function and inflammatory reactions (Hamer et al., 2008). Hence, the reduced milk SCC and greater immune function with SFE supplementation were likely the result of the higher ruminal butyrate content. Moreover, the results showed that SFE supplementation increased ruminal MCP concentration. The addition of SFE provided an energy substrate which may have reduced the amount of AA used for the energy supply and thus increased MCP synthesis in the rumen. To the best of our knowledge, no previous study has investigated the effects of dietary flavonoid extract supplementation on the duodenal fermentation profiles of dairy cows. We did not observe differences in the duodenal fermentation profiles among treatments, which may be because flavonoids are degraded by rumen microorganisms and act as carbon sources for ruminants (Gessner et al., 2017). Recently, a study reported that feeding CFE to dairy cows significantly increased faecal butyrate concentration (Zhao et al., 2023a,b), which is not consistent with our results, as we observed no difference in the faecal fermentation profile. Hence, further studies are needed to explore the issues associated with the ratio of ruminal degradation of SFE.

Previous studies have demonstrated the antimicrobial activities of flavonoids against some gram-negative and gram-positive bacteria, as well as protozoa (Dong et al., 2021; Karoline Ferreira Leite et al., 2023). In the present study, the β-diversity analysis of the rumen microbes revealed that the SFE supplementation significantly altered ruminal microbial structure. However, there were no significant differences in the alpha-diversity indices between the CON and SFE groups, consistent with that found in a previous study (Zhao et al., 2023a,b). In the present study, cows fed SFE had reduced relative abundances of Tenericutes and Spirochaetes in the rumen. Previous studies have shown that many Treponema spp. are linked to ulcerative mammary dermatitis and bovine digital dermatitis in cattle (Sadet et al., 2007) and contagious ovine digital dermatitis in sheep (Evans et al., 2012), indicating that it has a deleterious impact on host health. Similar responses in reducing the abundance of Spirochaetes were also observed when flavonoids were offered to pigs (T Zhao et al., 2018) or dairy cows (Zhan et al., 2017). It should be noted that various species of Spirochaetes such as Spirochaetes syphilis and Spirochaetes lymeiosis can induce severe infections in animals (Bonhomme and Werts, 2022). This suggests that SFE could limit the growth of harmful bacteria in the rumen, consequently exhibiting a health-promoting effect on dairy cows, which was also evidenced by the decline in milk SCC. To the best of our knowledge, few studies have explored the effects of SFE supplementation on small intestinal (duodenal) microbes in dairy cows. In the current study, duodenal samples were used to reflect small intestinal conditions to a certain extent. SFE supplementation altered the microbial structure in the duodenum, with an increase in the relative abundance of Butyrivibrio and a reduction in the relative abundances of Ruminococcus, Coprococcus, and Clostridium. Butyrivibrio can degrade hemicellulose and pectin to produce butyrate (Palevich et al., 2019), which suppresses the growth of pathogenic bacteria (Brownawell et al., 2012). Wallis et al. (2020) revealed that Ruminococcaceae family microbiota are mainly involved in nitrogen and amino acid metabolism. Therefore, changes in the abundance of these microbiota may affect the microbial amino acid metabolism and may be associated with the host immune system. Coprococcus belongs to the phylum Trichoderma, which actively ferments carbohydrates and is an important producer of butyric acid, which is closely related to the gastrointestinal health (Wang et al., 2022). Huang et al. (2022) showed that adding soybean isoflavones could increase the abundance of Coprococcus and reduce the body weight gain rate, which is inconsistent with our results. Clostridium, belonging to the phylum Firmicutes, prevents inflammation associated with the production of SCFAs, particularly butyrate, through the breakdown of dietary fibre (Guo et al., 2020). Nevertheless, the negative impact of these two beneficial genera remains unclear and requires further investigation. Although some studies have confirmed that dietary supplementation with flavonoids alters the structure and composition of the hindgut microbiota in dairy cows (Zhao et al., 2023a,b), no significant effects were observed when cows were fed SFE in the current study. Consequently, we speculated that the different results on the hindgut microbiota might be attributed to differences in the types of flavonoids, nutrient levels (energy, CP, etc.), and milk production between the studies.

5.　Conclusions

Less

The present study provided new insights into the effects of SFE, such as improved milk yield and reduced milk SCC, increased ruminal butyrate concentration, and reduced plasma AST, MDA, TNF-α and IL-1β concentration in dairy cows. Dietary supplementation with SFE altered the structure and composition of the rumen and duodenum by increasing the relative abundance of Butyrivibrio, and decreasing the relative abundance of Ruminococcus, Coprococcus, and Clostridium in the duodenum. Thus, SFE could be considered as a potential natural supplement for improving the lactation performance and health status of dairy cows.

References

Less

Abdela

. Sub-acute ruminal acidosis (sara) and its consequence in dairy cattle: a review of past and recent research at global prospective. Achieve Life Sci 2016;10(2):187-96. https://doi.org/10.1016/j.als.2016.11.006.

Aguilar

, Hanigan

, Tucker

, Jones

, Garbade

, Mcgilliard

, et al. Cow and herd variation in milk urea nitrogen concentrations in lactating dairy cattle. J Dairy Sci 2012;95(12):7261-8. https://doi.org/10.3168/jds.2012-5582.

Aguiar

, Cottica

, Boeing

, Samensari

, Santos

, Visentainer

, et al. Effect of feeding phenolic compounds from propolis extracts to dairy cows on milk production, milk fatty acid composition, and the antioxidant capacity of milk. Anim Feed Sci Technol 2014;193:148-54. https://doi.org/10.1016/j.anifeedsci.2014.04.006.

Alhidary

, Abdelrahman

. Effects of naringin supplementation on productive performance, antioxidant status and immune response in heat-stressed lambs. Small Rumin Res 2016;138:31-6. https://doi.org/10.1016/j.smallrumres.2016.03.030.

AOAC. Official methods of analysis. 18th ed. Arlington, VA: Association of Official Analytical Chemists; 2006.

Barbato

, Holmes

, Filipescu

, Celi

. Dietary supplementation of yerba mate (ilex paraguariensis) during the dry period improves redox balance in lactating dairy cows. Antioxidants 2019;8(2). https://doi.org/10.3390/antiox8020038.

Bergman

. Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiol Rev 1990;70(2):567-90. https://doi.org/10.1152/physrev.1990.70.2.567.

Bolyen

, Rideout

, Dillon

, Bokulich

, Abnet

, Al-Ghalith

, et al. Reproducible, interactive, scalable and extensible microbiome data science using qiime 2. Nat Biotechnol 2019;37(8):852-7. https://doi.org/10.1038/s41587-019-0209-9.

Bonhomme

, Werts

. Host and species-specificities of pattern recognition receptors upon infection with leptospira interrogans. Front Cell Infect Microbiol 2022;12:932137. https://doi.org/10.3389/fcimb.2022.932137.

Broderick

, Kang

. Automated simultaneous determination of ammonia and total amino acids in ruminal fluid and in vitro media. J Dairy Sci 1980;63(1): 64-75. https://10.3168/jds.S0022-0302(80)82888-8. PMID: 7372898.

Broderick

, Clayton

. A statistical evaluation of animal and nutritional factors influencing concentrations of milk urea nitrogen 1. J Dairy Sci 1997;80(11): 2964-71. https://doi.org/10.3168/jds.S0022-0302(97)76262-3.

Brownawell

, Caers

, Gibson

, Kendall

CWC

, Lewis

, Ringel

, et al. Prebiotics and the health benefits of fiber: current regulatory status, future research, and goals. J Nutr 2012;142(5):962-74. https://doi.org/10.3945/jn.112.158147.

Burmańczuk

, Hola

, Milczak

, Piech

, Kowalski

, Wojciechowska

, et al. Quercetin decrease somatic cells count in mastitis of dairy cows. Res Vet Sci 2018;117:255-9. https://doi.org/10.1016/j.rvsc.2018.01.006.

Callahan

, Mcmurdie

, Rosen

, Han

, Johnson

, Holmes

. Dada2: high-resolution sample inference from illumina amplicon data. Nat Methods 2016;13(7):581-3. https://doi.org/10.1038/nmeth.3869.

Ciampi

, Sordillo

, Gandy

, Caroprese

, Sevi

, Albenzio

, et al. Evaluation of natural plant extracts as antioxidants in a bovine in vitro model of oxidative stress. J Dairy Sci 2020;103(10):8938-47. https://doi.org/10.3168/jds.2020-18182.

Dai

, Wang

, Gao

, Chai

, Xu

. High-grain diet feeding altered blood metabolites, rumen microbiome, and metabolomics of yaks. Fermentation 2023;9(3):215. https://doi.org/10.3390/fermentation9030215.

Dong

, Yu

, Yang

, Zhang

, Su

, Fan

, et al. Berberine, a potential prebiotic to indirectly promote akkermansia growth through stimulating gut mucin secretion. Biomed Pharmacother 2021;139. https://doi.org/10.1016/j.biopha.2021.111595.

, Venter

, Pasch

. Recent advances and trends in the liquidchromatography-mass spectrometry analysis of flavonoids. J Chromatogr A 2016;1430:16-78. https://doi.org/10.1016/j.chroma.2015.11.077. Epub 2015 Nov 28.

Dinda

, Dinda

, Dassharma

, Banik

, Chakraborty

, Dinda

. Therapeutic potentials of baicalin and its aglycone, baicalein against inflammatory disorders. Eur J Med Chem 2017;131:68-80. https://doi.org/10.1016/j.ejmech.2017.03.004.

Drackley

. Adsa foundation scholar award. Biology of dairy cows during the transition period: the final frontier? J Dairy Sci 1999;82(11):2259-73. https://doi.org/10.3168/jds.s0022-0302(99)75474-3.

Dschaak

, Williams

, Holt

, Eun

, Young

, Min

. Effects of supplementing condensed tannin extract on intake, digestion, ruminal fermentation, and milk production of lactating dairy cows. J Dairy Sci 2011;94(5):2508-19. https://doi.org/10.3168/jds.2010-3818.

Eckersall

, Young

, Nolan

, Knight

, Mccomb

, Waterston

, et al. Acute phase proteins in bovine milk in an experimental model of staphylococcus aureus subclinical mastitis. J Dairy Sci 2006;89(5):1488-501. https://doi.org/10.3168/jds.S0022-0302(06)72216-0.

Evans

, Brown

, Hartley

, Smith

, Carter

. Antimicrobial susceptibility testing of bovine digital dermatitis treponemes identifies macrolides for in vivo efficacy testing. Vet Microbiol 2012;160(3-4):496-500. https://doi.org/10.1016/j.vetmic.2012.06.001.

Gabay

, Kushner

. Acute-phase proteins and other systemic responses to inflammation. N Engl J Med 1999;340(6):448-54. https://doi.org/10.1056/NEJM199902113400607.

Galyean

. Invited review: nutrient requirements of ruminants: derivation, validation, and application 1. The Professional animal scientist 2014;30(2):125. https://doi.org/10.15232/S1080-7446(15)30099-1.

Gao

, Huang

, Yang

, Xu

. Free radical scavenging and antioxidant activities of flavonoids extracted from the radix of Scutellari baicalensis Georgi. Biochim Biophys Acta 1999;1472:643-50. https://doi.org/10.1016/S0304-4165(99)00152-X.

Gao

, Cheng

, Liu

, Li

, Zhao

. Effects of red cabbage extract rich in anthocyanins on rumen fermentation, rumen bacterial community, nutrient digestion, and plasma indices in beef bulls. Animal 2022;16(5):100510. https://doi.org/10.1016/j.animal.2022.100510.

Gessner

, Ringseis

, Eder

. Potential of plant polyphenols to combat oxidative stress and inflammatory processes in farm animals. J Anim Physiol Anim Nutr 2017;101(4):605-28. https://doi.org/10.1111/jpn.12579.

Gladine

, Rock

, Morand

, Bauchart

, Durand

. Bioavailability and antioxidant capacity of plant extracts rich in polyphenols, given as a single acute dose, in sheep made highly susceptible to lipoperoxidation. Br J Nutr 2007;98(4): 691-701. https://doi.org/10.1017/S0007114507742666.

Gruse

, Kanitz

, Weitzel

, Tuchscherer

, Stefaniak

, Jawor

, et al. Quercetin feeding in newborn dairy calves cannot compensate colostrum deprivation: study on metabolic, antioxidative and inflammatory traits. PLoS One 2016;11(1):e0146932. https://doi.org/10.1371/journal.pone.0146932.

Guo

, Zhang

, Ma

, He

. Clostridium species as probiotics: potentials and challenges. J Anim Sci Biotechnol 2020;11(1):24. https://doi.org/10.1186/s40104-019-0402-1.

Hamer

, Jonkers

, Venema

, Vanhoutvin

, Troost

, Brummer

. Review article: the role of butyrate on colonic function. Aliment Pharmacol Ther 2008;27(2):104-19. https://doi.org/10.1111/j.1365-2036.2007.03562.x.

Huang

, Zheng

, Hui

, Xie

. Soybean isoflavones modulate gut microbiota to benefit the health weight and metabolism. Front Cell Infect Microbiol 2022;12:1004765. https://doi.org/10.3389/fcimb.2022.1004765.

Jank

, Martins

, Arsand

, Campos Motta

, Hoff

, Barreto

, et al. High-throughput method for macrolides and lincosamides antibiotics residues analysis in milk and muscle using a simple liquid-liquid extraction technique and liquid chromatography-electrospray-tandem mass spectrometry analysis (lc-ms/ms). Talanta 2015;144:686-95. https://doi.org/10.1016/j.talanta.2015.06.078.

Kampa

, Nistikaki

, Tsaousis

, Maliaraki

, Notas

, Castanas

. A new automated method for the determination of the Total Antioxidant Capacity (TAC) of human plasma, based on the crocin bleaching assay. BMC Clin Pathol 2002;2(1):3. https://doi.org/10.1186/1472-6890-2-3.

Kahkonen

, Hopia

, Vuorela

, Rauha

, Pihlaja

, Kujala

, et al. Antioxidant activity of plant extracts containing phenolic compounds. J Agric Food Chem 1999;47(10):3954-62. https://doi.org/10.1021/jf990146l.

Karoline Ferreira Leite

, Vidal Fonteles

, Godoy Alves Filho

, Andrea Da Silva Oliveira F, Rodrigues

. Impact of orange juice containing potentially prebiotic ingredients on human gut microbiota composition and its metabolites. Food Chem 2023;405:134706. https://doi.org/10.1016/j.foodchem.2022.134706.

Khan

, Qiu

, Xu

, Liu

, Cheong

. Physicochemical characterization and antioxidant activity of sulphated polysaccharides derived from porphyra haitanensis. Int J Biol Macromol 2020;145:1155-61. https://doi.org/10.1016/j.ijbiomac.2019.10.040.

Kolling

, Stivanin

, Gabbi

, Machado

, Ferreira

, Campos

, et al. Performance and methane emissions in dairy cows fed oregano and green tea extracts as feed additives. J Dairy Sci 2018;101(5):4221-34. https://doi.org/10.3168/jds.2017-13841.

Kong

, Wang

, Dai

, Cao

, Wang

, Li

, et al. Preliminary investigation of the effects of rosemary extract supplementation on milk production and rumen fermentation in high-producing dairy cows. Antioxidants 2022;11(9):1715. https://doi.org/10.3390/antiox11091715.

, Chen

. Isolation and purification of baicalein, wogonin and oroxylin A from the medicinal plant Scutellaria baicalensis by high-speed counter-current chromatography. J Chromatogr A 2005;13(1074):107-10. https://doi.org/10.1016/j.chroma.2005.03.088.

Liu

, Vandehaar

. Relationship of residual feed intake and protein efficiency in lactating cows fed high- or low-protein diets. J Dairy Sci 2020;103(4):3177-90. https://doi.org/10.3168/jds.2019-17567.

Liu

, Wang

, Liu

, Ma

, Zhang

, Ren

. Effect of moringa leaf flavonoids on the production performance, immune system, and rumen fermentation of dairy cows. Vet Med Sci 2023b;9(2):917-23. https://doi.org/10.1002/vms3.993.

Liu

, Hu

, Li

, Zhao

. Effects of taurine on rumen fermentation, nutrient digestion, rumen bacterial community and metabolomics and nitrogen metabolism in beef steers. J Sci Food Agric 2023a;103(7):3414-26. https://doi.org/10.1002/jsfa.12474.

Makkar

, Sharma

, Dawra

, Negi

. Simple determination of microbial protein in rumen liquor. J Dairy Sci 1982;65(11):2170-3. https://10.3168/jds.S0022-0302(82)82477-6.

, Abaker

, Wei

, Chen

, Shen

, Chang

. A high-concentrate diet induces an inflammatory response and oxidative stress and depresses milk fat synthesis in the mammary gland of dairy cows. J Dairy Sci 2022;105(6):5493-505. https://doi.org/10.3168/jds.2021-21066.

, Chen

, Tu

, Zhang

, Si

, Diao

. Dietary supplementation with mulberry leaf flavonoids inhibits methanogenesis in sheep. Anim Sci J 2017;88(1):72-8. https://doi.org/10.1111/asj.12556.

Magoc

, Salzberg

. Flash: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 2011;27(21):2957-63. https://doi.org/10.1093/bioinformatics/btr507.

Mcart

JAA

, Neves

. Association of transient, persistent, or delayed subclinical hypocalcemia with early lactation disease, removal, and milk yield in holstein cows. J Dairy Sci 2020;103(1):690-701. https://doi.org/10.3168/jds.2019-17191.

Musco

, Tudisco

, Grossi

, Mastellone

, Morittu

, Pero

, et al. Effect of a high forage : concentrate ratio on milk yield, blood parameters and oxidative status in lactating cows. Anim Prod Sci 2020;60(12):1531. https://doi.org/10.1071/AN18041.

, Giallongo

, Frederick

, Pate

, Walusimbi

, Elias

, et al. Effects of dietary capsicum oleoresin on productivity and immune responses in lactating dairy cows. J Dairy Sci 2015;98(9):6327-39. https://doi.org/10.3168/jds.2014-9294.

Olagaray

, Brouk

, Mamedova

, Sivinski

, Liu

, Robert

, et al. Dietary supplementation of scutellaria baicalensis extract during early lactation decreases milk somatic cells and increases whole lactation milk yield in dairy cattle. PLoS One 2019;14(1):e0210744. https://doi.org/10.1371/journal.pone.0210744.

Oliver

, Gooch

, Lansing

, Schueler

, Hurst

, Sassoubre

, et al. Invited review: fate of antibiotic residues, antibiotic-resistant bacteria, and 3antibiotic resistance genes in us dairy manure management systems. J Dairy Sci 2020;103(2): 1051-71. https://doi.org/10.3168/jds.2019-16778.

Palevich

, Kelly

, Leahy

, Denman

, Altermann

, Rakonjac

, et al. Comparative genomics of rumen butyrivibrio spp. Uncovers a continuum of polysaccharide-degrading capabilities. Appl Environ Microbiol 2019;86(1). https://doi.org/10.1128/AEM.01993-19.

Petri

, Münnich

, Zebeli

, Klevenhusen

. Graded replacement of corn grain with molassed sugar beet pulp modulates the fecal microbial community and hindgut fermentation profile in lactating dairy cows. J Dairy Sci 2019;102(6): 5019-30. https://doi.org/10.3168/jds.2018-15704.

Pitz

, Trevisan

ACD

, Cardoso

, Pereira

, Moreira

ELG

, De Pra

, et al. Assessment of in vitro biological activities of anthocyanins-rich plant species based on Plinia cauliflora study model. Pages 65e80. In: Protocols for in vitro cultures and secondary metabolite analysis of aromatic and medicinal plants. 2nd ed. Humana Press; 2016.

Sadet

, Martin

, Meunier

, Morgavi

. Pcr-dgge analysis reveals a distinct diversity in the bacterial population attached to the rumen epithelium. Animal 2007;1(7):939-44. https://doi.org/10.1017/S1751731107000304.

Segata

, Izard

, Waldron

, Gevers

, Miropolsky

, Garrett

, et al. Metagenomic biomarker discovery and explanation. Genome Biol 2011;12(6):R60. https://doi.org/10.1186/gb-2011-12-6-r60.

Shan

, Guo

, Sun

, Li

, Yang

, Gao

, et al. Effects of fermented Chinese herbal medicines on milk performance and immune function in late-lactation cows under heat stress conditions. J Anim Sci 2018;96(10):4444-445710. 29, https://doi.org/1093/jas/sky270.

Sun

, Wang

, Zhang

, Wang

, Zhang

, et al. Effects of saccharomyces cerevisiae culture on ruminal fermentation, blood metabolism, and performance of high-yield dairy cows. Animals (Basel) 2021;11(8):2401. https://doi.org/10.3390/ani11082401.

Song

, Lan

, Wu

, Han

, Wang

, Zheng

, et al. The chemopreventive effect of 5-demethylnobiletin, a unique citrus flavonoid, on colitis-driven colorectal carcinogenesis in mice is associated with its colonic metabolites. Food Funct 2020;11(6):4940-52. https://doi.org/10.1039/d0fo00616e.

Tilahun

, Zhao

, Sun

, Shen

, Ma

, Callaway

, et al. Fresh phyllanthus emblica (amla) fruit supplementation enhances milk fatty acid profiles and the antioxidant capacities of milk and blood in dairy cows. Antioxidants 2022;11(3). https://doi.org/10.3390/antiox11030485.

Totakul

, Viennasay

, Sommai

, Matra

, Infascelli

, Wanapat

. Chaya (cnidoscolus aconitifolius, mill. Johnston) pellet supplementation improved rumen fermentation, milk yield and milk composition of lactating dairy cows. Livest Sci 2022;262:104974. https://doi.org/10.1016/j.livsci.2022.104974.

Varela

, de Lima

, de Araujo

, de Souza

, de Macedo

, Pereira

, et al. The effect of propolis extract on milk production and composition, serum biochemistry, and physiological parameters of heat-stressed dairy cows. Trop Anim Health Prod 2023;55(4):244. https://doi.org/10.1007/s11250-023-03647-8.

Van Soest

, Robertson

, Lewis

. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci 1991;74:3583e97.

Wallis

, Melnyk

, Miousse

. Sex-specific effects of dietary methionine restriction on the intestinal microbiome. Nutrients 2020;12(3). https://doi.org/10.3390/nu12030781.

Wang

, Yang

, Diao

, Tu

. The influence of mulberry leaf flavonoids and candida tropicalis on antioxidant function and gastrointestinal development of preweaning calves challenged with escherichia coli o141:k99. J Dairy Sci 2018;101(7):6098-108. https://doi.org/10.3168/jds.2017-13957.

Wang

, Cha

, Wang

, Li

, et al. Feeding corn silage or grass hay as sole dietary forage sources: overall mechanism of forages regulating healthpromoting fatty acid status in milk of dairy cows. Foods 2023;12(2):303. https://doi.org/10.3390/foods12020303.

Wang

, Nan

, Zhao

, Jiang

, Wang

, Zhang

, et al. Dietary supplementation of inulin ameliorates subclinical mastitis via regulation of rumen microbial community and metabolites in dairy cows. Microbiol Spectr 2021;9(2):e0010521. https://doi.org/10.1128/Spectrum.00105-21.

Wang

, Nan

, Zhao

, Jiang

, Wang

, Zhang

, et al. Discrepancies among healthy, subclinical mastitic, and clinical mastitic cows in fecal microbiome and metabolome and serum metabolome. J Dairy Sci 2022;105(9):7668-88. https://doi.org/10.3168/jds.2021-21654.

, Li

, Jiang

, Gao

, Liu

, Zhu

, et al. Baicalin protects against zearalenone-induced chicks liver and kidney injury by inhibiting expression of oxidative stress, inflammatory cytokines and caspase signaling pathway. Int Immunopharmacol 2021:108097. https://doi.org/10.1016/j.intimp.2021.108097.

Yang

, Li

, Cong

, Wang

, Jiang

, Zhang

, et al. Baicalin attenuates lipopolysaccharide induced inflammation and apoptosis of cow mammary epithelial cells by regulating nf-κb and hsp72. Int Immunopharmacol 2016;40: 139-45. https://doi.org/10.1016/j.intimp.2016.08.032.

, Li

, Zhao

, Zhang

, Tu

, Liu

, et al. Dietary citrus flavonoid extract improves lactational performance through modulating rumen microbiome and metabolites in dairy cows. Food Funct 2023;14(1):94-111. https://doi.org/10.1039/d2fo02751h.

Zeng

, Li

, Xiao

, Cai

, Chu

, Chen

, et al. Citrus polymethoxyflavones attenuate metabolic syndrome by regulating gut microbiome and amino acid metabolism. Sci Adv 2020;6(1):eaax6208. https://doi.org/10.1126/sciadv.aax6208.

Zhan

, Liu

, Wu

, Su

, Zhan

, Zhao

. Effects of alfalfa flavonoids extract on the microbial flora of dairy cow rumen. Asian-Australas J Anim Sci 2017;30(9): 1261-9. https://doi.org/10.5713/ajas.16.0839.

Zhan

, Shen

, Xin

, Hua

, Hui

, Fang

, et al. Microbiome and metabolic changes of milk in response to dietary supplementation with bamboo leaf extract in dairy cows. Front Nutr 2021;8:723446. https://doi.org/10.3389/fnut.2021.723446.

Zhang

, Jin

, Liu

, Ji

, Hu

. Effect of dietary fructus mume and scutellaria baicalensis georgi on the fecal microbiota and its correlation with apparent nutrient digestibility in weaned piglets. Animals (Basel) 2022;12(18). https://doi.org/10.3390/ani12182418.

Zhang

, Cao

, Yang

, Wang

, Li

. Analysis of serum antioxidant capacity and gut microbiota in calves at different growth stages in tibet. Front Microbiol 2023;13. https://doi.org/10.3389/fmicb.2022.1089488.

Zhao

, Li

, Zhao

, Liu

, Suo

, Zhao

, et al. Effect of nrf2 on rat ovarian tissues against atrazine-induced anti-oxidative response. Int J Clin Exp Pathol 2014;7(6):2780-9.

Zhao

, Yang

, Xie

. Improvement strategies for the oral bioavailability of poorly water-soluble flavonoids: an overview. Int J Pharm 2019;570:118642. https://doi.org/10.1016/j.ijpharm.2019.118642.

Zhao

, Li

, Lei

, Li

, Kim

. Effect of fermented medicinal plants on growth performance, nutrient digestibility, fecal noxious gas emissions, and diarrhea score in weanling pigs. J Sci Food Agric 2016;96(4):1269-74. https://doi.org/10.1002/jsfa.7217.

Zhao

, Yuan

, Liang

, Luo

, Jiang

, Qing

, Zhang

. Baicalin inhibits Escherichia coli isolates in bovine mastitic milk and reduces antimicrobial resistance. J Dairy Sci 2018;101(3):2415-22. https://doi.org/10.3168/jds.2017-13349. Epub 2017 Dec 28.

Zhao

, Shen

, Dai

, Cui

. Benefits of procyanidins on gut microbiota in bama minipigs and implications in replacing antibiotics. J Vet Sci 2018;19(6):798. https://doi.org/10.4142/jvs.2018.19.6.798.

Zhao

, Yu

, Li

, Zhao

, Li

, Jiang

, et al. Feeding citrus flavonoid extracts decreases bacterial endotoxin and systemic inflammation and improves immunometabolic status by modulating hindgut microbiome and metabolome in lactating dairy cows. Animal Nutrition 2023a;13:386-400. https://doi.org/10.1016/j.aninu.2023.03.007.

Zhao

, Yu

, Zhao

, Li

, Liu

, et al. Integrated multi-omics analysis reveals the positive leverage of citrus flavonoids on hindgut microbiota and host homeostasis by modulating sphingolipid metabolism in mid-lactation dairy cows consuming a high-starch diet. Microbiome 2023b;11. https://doi.org/10.1186/s40168-023-01661-4.

Zhou

, Liang

, He

, Li

, Tian

, Liu

, et al. Compound enzyme preparation supplementation improves the production performance of goats by regulating rumen microbiota. Appl Microbiol Biotechnol 2023;107(23):7287-99. https://doi.org/10.1007/s00253-023-12804-w.

Zou

, Li

, Chen

, Dong

, Zhang

, Du

. High molecular weight persimmon tannin is a potent hypolipidemic in high-cholesterol diet fed rats. Food Res Int 2012;48(2):970-7. https://doi.org/10.1016/j.foodres.2012.05.024.

Appendix

Less

Year 2025 volume 20 Issue 1

PDF

Cite this Article

BibTeX

Article Info

doi: 10.1016/j.aninu.2024.11.019

Receive Date：2024-05-30
Online Date：2026-01-28
Published：2025-03-10

Article Data

Affiliations

History

Received：2024-05-30
Revised：2024-08-23
Accepted：2024-11-20

Affiliations

^bCollege of Animal Science and Technology, Ningxia University, Yinchuan 750021, China

^cQinghai University, Xining 810016, China

Corresponding:

Corresponding authors. E-mail addresses: Wei.wang@cau.edu.cn (W. Wang)

Lishengli@cau.edu.cn (S. Li).

References

Share

https://castjournals.cast.org.cn/joweb/aninu/EN/10.1016/j.aninu.2024.11.019

Share to

Scan QR to access full text

Cite this article

BibTeX

Citations

表12种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

关闭全屏

BibTeX
EndNote
RefWorks
TxT

Table 1 The ingredients and chemical composition of the experimental diets.

Item	Contents
Ingredients, % of DM
Corn silage	26.63
Alfalfa hay	12.77
Ground corn grain	27.92
Whole cotton seed	4.42
Molasses skins	0.72
Oyogold	0.84
Soybean meal	13.62
Canola meal	3.63
Glucose	1.88
Calcium fatty acid	2.79
CaCO₃	0.65
NaHCO₃	0.52
Nacl	0.49
Premix¹	3.12
Chemical composition, % of DM, unless otherwise stated
DM, % as fed	48.95
OM	91.12
CP	17.73
NDF	28.59
ADF	18.64
EE	4.67
Starch	27.74
NE_L², Mcal/kg of DM	1.69

DM = dry matter; OM = organic matter; CP = crude protein; NDF = neutral detergent fiber; ADF = acid detergent fiber; EE = ether extract; NE_L = Net energy for lactation. ¹ Formulated to provide (per kg of dry matter): 250,000 IU of vitamin A, 50,000 IU of vitamin D₃, 1100 IU of vitamin E, 250 mg of Cu, 500 mg of Mn, 1,000 mg of Zn, 20 mg of Se, 40 mg of I, 24 mg of Co. ² Net energy for lactation was estimated using NRC (2001) model.

Table 2 Effects of dietary with Scutellariae radix flavonoid extracts (SFE) supplementation on feed intake, milk production and composition in dairy cows.

Item	Treatment groups¹		SEM	P-value
Item	CON	SFE	SEM	P-value
DMI, kg/d	23.28	24.09	0.289	0.165
Milk yield, kg/d	32.84	35.35	0.687	0.067
ECM², kg/d	35.81	39.04	2.333	0.515
3.5% FCM³, kg/d	34.98	37.85	2.350	0.566
Milk fat, %	3.85	3.92	0.143	0.824
Milk fat, kg/d	1.28	1.39	0.100	0.613
Milk protein, %	3.37	3.52	0.083	0.384
Milk protein, kg/d	1.11	1.24	0.068	0.374
Milk lactose, %	5.07	5.23	0.084	0.363
Milk lactose, kg/d	1.66	1.85	0.096	0.353
MUN, mg/dL	9.63	10.93	0.373	0.079
SCC, × 10³ cells/mL	159.16^a	82.83^b	18.037	0.026

SEM = standard error of the mean; DMI = dry matter intake; ECM = energy corrected milk; FCM = fat corrected milk; MUN = milk urea nitrogen; SCC = somatic cell count. ^a,b Mean values within a row with different superscripts differed (P < 0.05). ¹ CON = control diet with no SFE supplementation; SFE = control diet with 25 g/d SFE supplementation for per cow. ² ECM = 12.95 × fat yield + 7.65 × protein yield + 0.327 × milk yield. ³ 3.5% FCM = 0.4324 × milk yield + 16.23 × fat yield.

Table 3 Effects of dietary with Scutellariae radix flavonoid extract (SFE) supplementation on plasma metabolites, liver enzymes, oxidative status, inflammation and acute-phase proteins of dairy cows.

Item	Treatment groups¹		SEM	P-value
Item	CON	SFE	SEM	P-value
Metabolites
GLU, mmol/L	3.64	3.68	0.104	0.875
INS, mIU/L	15.10	15.61	1.130	0.833
UN, mmol/L	4.13	4.26	0.317	0.852
BHB, mmol/L	0.34	0.38	0.017	0.249
NEFA, μmol/L	38.93	42.57	1.225	0.144
Liver enzymes
AST, mmol/L	80.75^a	66.9^b	3.032	0.013
GGT, mmol/L	13.50	12.91	0.720	0.706
Oxidative status
GSH-Px activity, U/mL	7.96	8.50	0.324	0.426
T-AOC activity, U/mL	9.09^b	10.03^a	0.227	0.032
MDA activity, nmol/mL	1.75^a	1.52^b	0.055	0.030
Inflammation and acute-phase proteins
TNF-α, ng/L	174.46^a	136.88^b	8.012	0.010
IL-1β, ng/L	64.28^a	51.71^b	2.278	0.001
SAA, μg/L	25.81	25.71	1.244	0.970
HPT, ng/L	42.74	42.29	2.092	0.922

SEM = standard error of the mean; GLU = glucose; INS = insulin; UN = urea nitrogen; BHB = β-hydroxybutyric acid; NEFA = non-esterified fatty acids; AST = aspartate aminotransferase; GG = γ-glutamyl transferase; GSH-Px = glutathione peroxidase; T-AOC = total antioxidant capacity; MDA = malondialdehyde; TNF-α = tumor necrosis factor-α; IL-1β = interleukin-1β; SAA = amyloid-A; HPT = haptoglobin. ^a,b Mean values within a row with different superscripts differed (P < 0.05). ¹ CON = control diet with no SFE supplementation; SFE = control diet with 25 g/d SFE supplementation for per cow.

Table 4 Effects of dietary with Scutellariae radix flavonoid extract (SFE) supplementation on fermentation profile in the rumen, duodenal, and fecal of dairy cows.

Item	Treatment groups¹		SEM	P-value
Item	CON	SFE	SEM	P-value
Rumen
pH	6.31	6.14	0.134	0.548
NH₃–N, mg/dL	8.87	9.43	0.491	0.594
MCP, mg/dL	2.33^b	2.81^a	0.120	0.037
TVFA, mmol/L	100.41	107.21	7.801	0.687
Acetate, mmol/L	60.02	64.97	3.964	0.570
Propionate, mmol/L	25.52	26.84	2.261	0.789
Isobutyrate, mmol/L	0.60	0.83	0.110	0.342
Butyrate, mmol/L	12.78^b	18.08^a	1.360	0.044
Isovalerate, mmol/L	0.48	0.67	0.097	0.323
Valerate, mmol/L	1.01	1.31	0.128	0.267
Duodenal
pH	4.13	4.02	0.119	0.665
TVFA, mmol/L	4.97	4.75	0.526	0.880
Acetate, mmol/L	3.23	3.19	0.344	0.959
Propionate, mmol/L	1.37	1.10	0.179	0.485
Butyrate, mmol/L	0.36	0.50	0.063	0.290
Fecal
pH	6.73	6.68	0.096	0.815
TVFA, mmol/L	75.51	84.79	6.12	0.456
Acetate, mmol/L	63.22	72.22	4.89	0.382
Propionate, mmol/L	7.29	7.98	0.93	0.725
Butyrate, mmol/L	4.60	4.59	0.42	0.988

SEM = standard error of the mean; TVFA = total volatile fatty acids; NH₃–N = ammonia-nitrogen; MCP = ruminal microbial protein. ^a,b Mean values within a row with different superscripts differed (P < 0.05). ¹ CON = control diet with no SFE supplementation; SFE = control diet with 25 g/d SFE supplementation for per cow.

Table 5 Effects of dietary with Scutellariae radix flavonoid extract (SFE) supplementation on bacterial abundance in rumen of dairy cows (phylum level, %).

Item	Treatment groups¹		SEM	P-value
Item	CON	SFE	SEM	P-value
Bacteroidetes	54.46	45.22	3.185	0.158
Firmicutes	37.98	46.46	3.286	0.211
Actinobacteria	0.66	1.70	0.350	0.116
Proteobacteria	0.67	0.39	0.152	0.399
Tenericutes	1.54^a	0.64^b	0.281	0.005
Spirochaetes	0.59^a	0.36^b	0.059	0.041
TM7	0.55	0.20	0.113	0.131
SR1	0.43	0.27	0.118	0.536
Verrucomicrobia	0.41	0.24	0.084	0.355
Fibrobacteres	0.47	0.15	0.096	0.104

SEM = standard error of the mean. ^a,b Mean values within a row with different superscripts differed (P < 0.05). ¹ CON = control diet with no SFE supplementation; SFE = control diet with 25 g/d SFE supplementation for per cow.

Table 6 Effects of dietary with Scutellariae radix flavonoid extract (SFE) supplementation on bacterial abundance in rumen of dairy cows (genus level, %).

Item	Treatment groups¹		SEM	P-value
Item	CON	SFE	SEM	P-value
Prevotella	28.68	17.71	3.697	0.150
Ruminococcaceae_Ruminococcus	7.61	10.34	2.121	0.555
Succiniclasticum	7.11	3.32	1.505	0.223
Butyrivibrio	1.21^b	3.46^a	0.554	0.034
YRC22	1.35	0.97	0.190	0.346
Oscillospira	0.93	1.01	0.252	0.888
CF231	1.12	0.71	0.142	0.084
Coprococcus	0.68	0.85	0.141	0.588
Clostridiaceae_Clostridium	0.65	0.73	0.061	0.491
Sharpea	0.31	0.08	0.108	0.322

Articles: Latest Articles; Most Read; Collections

Updates: Events; News; Multimedia

About: About Us

Contact

No. 86 Xueyuan South Road, Haidian District, Beijing

100081

010-62199257

qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House