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Article

Effect of a High-Starch or a High-Fat Diet on the Milk Performance, Apparent Nutrient Digestibility, Hindgut Fermentation Parameters and Microbiota of Lactating Cows

1
Guangdong Laboratory for Lingnan Modern Agriculture, South China Agricultural University, Guangzhou 510642, China
2
College of Animal Science, South China Agricultural University, Guangzhou 510642, China
3
Fuyang Bright Ecological Wisdom Ranch, Bright Dairy & Food Co., Ltd., Fuyang 236328, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Animals 2023, 13(15), 2508; https://doi.org/10.3390/ani13152508
Submission received: 29 May 2023 / Revised: 25 July 2023 / Accepted: 28 July 2023 / Published: 3 August 2023
(This article belongs to the Section Cattle)

Abstract

:

Simple Summary

Fat content is critical to milk quality, health and economic value. Fat content can be affected by diet composition. Diet-induced milk fat depression (MFD) is a specific reduction in milk fat synthesis caused by feeding cows high contents of rapidly fermentable carbohydrates or polyunsaturated fatty acid (PUFA). However, the mechanisms involved in MFD have not been fully elucidated and substantial controversy remains. Therefore, the aim of this study was to provide reference data for exploration of the relationship between milk fat synthesis and nutrient digestion as well as hindgut microbials.

Abstract

In this study, changes in milk performance, nutrient digestibility, hindgut fermentation parameters and microflora were observed by inducing milk fat depression (MFD) in dairy cows fed with a high-starch or a high-fat diet. Eight Holstein cows were paired in a completely randomized cross-over design within two 35 d periods (18 d control period and 17d induction period). During the control period, all cows were fed the low-starch and low-fat diet (CON), and at the induction period, four of the cows were fed a high-starch diet with crushed wheat (IS), and the other cows were fed a high-fat diet with sunflower fat (IO). The results showed that, compared to when the cows were fed the CON diet, when cows were fed the IS or IO diet, they had lower milk fat concentrations, energy corrected milk, 3.5% fat-corrected milk yield, feed efficiency and apparent digestibility of NDF and ADF. However, cows fed the IO diet had a lower apparent digestibility of ether extracts. In addition, we observed that when cows were fed the high-starch (IS) or high-fat (IO) diet, they had a higher fecal concentration of propionate and acetate, and a lower NH3-N. Compared to when the cows were fed the CON diet, cows fed the IS diet had a lower pH, and cows fed the IO diet had a lower concentration of valerate in feces. In the hindgut microbiota, the relative abundance of Oscillospiraceae_UCG-005 was increased, while the Verrucomicrobiota and Lachnospiraceae_AC2044_group were decreased when cows were fed the IO diet. The relative abundance of Prevotellaceae_UCG-003 was increased, while the Alistipes and Verrucomicrobiota decreased, and the Treponema, Spirochaetota and Lachnospiraceae_AC2044_group showed a decreasing trend when cows were fed the IS diet. In summary, this study suggested that high-starch or high-fat feeding could induce MFD in dairy cows, and the high-fat diet had the greatest effect on milk fat; the high-starch or high-fat diet affected hindgut fermentation and apparent fiber digestibility. The changes in hindgut flora suggested that hindgut microbiota may be associated with MFD in cows.

1. Implications

Fat content is critical to milk quality, health and economic value. In addition, fat content can be affected by the components of the diet. Diet-induced milk fat depression (MFD) is a specific reduction in milk fat synthesis caused by feeding with high contents of rapidly fermentable carbohydrates and polyunsaturated fatty acid (PUFA). However, the mechanisms involved in the MFD have not been fully elucidated and substantial controversy remains. Therefore, the aim of this study was to provide data to explore the relationship between milk fat synthesis, nutrient digestion and hindgut microbials.

2. Introduction

The unique nutritional value of milk can be attributed to the presence of short-chain fatty acids and medium-chain fatty acids which are important sources of energy for human internal organs [1]. However, achieving high levels of milk yield and maintaining optimal milk fat synthesis remains a challenge in the current dairy production system [2]. Milk fat depression (MFD) in dairy cows is a reduction in milk fat concentration and yield, with no change in milk yield or other milk components [3]. At present, the nutritional factors causing MFD in dairy cows usually includes two diets, one is a diet rich in rapidly fermenting carbohydrates, low physically available fiber, or both, and the second is a diet supplemented with unsaturated fatty acids (UFA), especially marine lipids containing eicosapentaenoic acid (EPA, 20:5N-3) and docosahexaenoic acid (DHA, 22:6N-3) [4].
Since the discovery of MFD, scholars have continuously explored the mechanism of MFD and have put forward four main theories: acetate and β-hydroxybutyric acid (BHBA) deficiency [5,6], insulin–glucose release theory [7], trans fatty acid inhibition theory [8], and biohydrogenation theory. Among them, the biohydrogenation theory has been widely studied and accepted in recent years, and the reduction in milk fat synthesis is attributed to reduced mammary capacity for lipid synthesis caused by bioactive trans FA intermediates generated during altered rumen biohydrogenation of unsaturated FA by rumen microbes [9]. However, the above views mainly focus on the rumen trans fatty acids or flora, and studies have shown that the hindgut plays a important role in milk production and health [10]. For example, when large amounts of starch are fermented in the hindgut, which could increase the contribution of the concentrate-rich diet to both energy supply and health issues [11].
In addition, studies have shown that changes in diet composition can lead to changes in the microflora of the gastrointestinal tract of cows, resulting in changes in nutrient digestibility and intestinal function [12,13]. We therefore hypothesised that high-starch or high-fat diet induced MFD can alter hindgut fermentation and microbiota in cows, but the effects of these two models differed. In this study, we used traditional animal nutrition research techniques and 16S rRNA high-throughput sequencing to investigate and compare the effects of two dietary patterns on nutrient digestion, hindgut fermentation and microbiota in dairy cows.

3. Materials and Methods

3.1. Management of Cows

The experiment was conducted on the Wenshi dairy farm in Zhaoqing, Guangdong, China. All cows and experimental protocols in this study were reviewed and approved by the Animal Care and Use Committee of the South China Agricultural University, Guangzhou, China (approval number SCAU#2013-10). Eight Holstein dairy cows with an average body weight (BW) of 566 ± 39 kg and days in milk (DIM) of 91 ± 16 days (mean ± SD) were selected. The cows were housed individually in a separate enclosure (2.5 m × 2.5 m) with rubber mattresses throughout the study. All cows had constant ad libitum access to fresh drinking water and were fed twice daily at 0700 and 1800 h with a total mixed ration (TMR), allowing for at least 5–10% residual (as-fed basis) feed. The cows were milked at 0630 and 1730 h. The experimental diets were designed according to feeding standards [14], and details can be seen in Table 1.

3.2. Experimental Design and Treatments

This trial was a completely randomized design with eight Holstein cows divided into Groups A and B having four head per group. The experiment was divided into a pre-experiment period (18 d), two induction periods (34 d) and one washout period (18 d), details are shown in Table 2. There were three dietary treatments, two of which may induce milk fat depression in dairy cows: (1) a basic total mixed ration (CON); (2) a high-starch diet with fine ground wheat (IS, pass through 1.5 mm sieve); and (3) a high-fat diet with sunflower fat (IO). As shown in Table 2, in the pre-experiment, 8 cows were on the CON diet; in period 1, 8 cows were randomly assigned to the IS or IO diet, with 4 cows in each treatment diet. In period 2, the cows that were fed IO or IS in period 1 were switched to the other treatment diet in period 3.

3.3. Feed Intake, Apparent Nutrient Digestibility

The diets and orts amount of each cow were recorded daily and put in 65 °C for 48 h to calculate dry matter intake (DMI). The diets and orts samples were collected from each cow during the last 3 d of the pre-experiment period, and periods 1 and 3. Diets were dried at 65 °C for 48 h, and the samples were ground using a Wiley (A.H.TIOmas, Philadelphia, PA, USA) mill (1 mm sieve). The dry matter (DM), organic matter (OM), crude protein (CP) (Method: 98903), starch (Method: 948.03), ash (Method: 942.05) and ether extract (EE) (Method: 2003.05) were determined based on the Association of Official Analytical Chemists method (AOAC, 1990). Determination of neutral detergent fiber (NDF) and acid detergent fiber (ADF) in diets were performed using the traditional method [15]. Determination of acid insoluble ash (AIA) in diets and feces were performed using a previous method [16].
Fresh fecal samples were collected by rectal palpation on 15 d (04:00, 09:00, 14:00, 19:00), 16 d (05:00, 10:00, 15:00, 20:00) and 17 d (06:00, 11:00, 17:00, 22:00) of pre- experiment period, and periods 1 and 3. The 3 d feces sample from each cow was mixed to 400 g, added to 10% tartaric acid at one-quarter fecal weight, dried at 65 °C for 48 h, ground using a Wiley (A.H.TIOmas, Philadelphia, PA, USA) mill and passed through a 1 mm sieve. Determination of nutrients in fecal samples was similar to the procedure for diets. Apparent nutrient digestibility was calculated using the formula [17]: D = [1 − (Ad × Nf)/(Af × Nd)] × 100, where Ad (g/kg) and Af (g/kg) represent the AIA in the diet and feces, respectively, and Nd (g/kg) and Nf (g/kg) represent the nutrients in the diet and feces, respectively.

3.4. Milk Collection and Analysis

In the last 3 d of the pre-experiment period, and in periods 1 and 3, milk yield and milk samples from each cow were recorded and collected. Milk samples were collected at each milking time and then mixed together based on milk yield. A total of 50 mL of mixed milk samples were collected to determine milk components, and milk urea nitrogen (MUN) was determined. Milk protein, milk non-fat solids, milk lactose and milk fat were determined by the milk analyzers (Lactoscan LAW, Milkotronic Ltd., Nova Zagora, Bulgaria). MUN were determined by a kit purchased from Nanjing Jiancheng Bioengineering Institute (Nanjing, China), according to the manufacturer’s instructions.

3.5. Fecal Samples Collection and Analysis

Before feeding on the last day of the pre-experiment period, and periods 1 and 3, fecal samples were collected by rectal palpation, 10 g fresh feces were mixed 1:2 with distilled water to measure pH with a pH meter (FE28-Standard, Beijing, China). A total of 15 g of fecal samples were preserved at −20 °C to determine the content of volatile fatty acids (VFA) and ammoniacal nitrogen (NH3-N). NH3-N was determined using the colorimetric method [18]. Fecal VFA concentrations were determined using the method by [19] with an Agilent 6890B Gas chromatograph (Agilent, Guangzhou, China) with HP-INNOwax capillary column (30.0 m × 320 μm × 0.5 μm) and FID detector. The parameters of the gas chromatograph were as follows: N2 as carrier gas, 40:1 splitting concentration, 0.4 μL and 220 °C injection volume and temperature, and 120 °C (3 min)–10 °C/min–180 °C (1 min) as the column chamber program. The composition of each sample was obtained using 2-ethylbutyric acid as the internal standard.
Extraction of total DNA from all fecal samples was conducted according to the instructions provided with the Omega Stool (Omega Bio-Tek, Norcross, GA, USA) kit. Selection of the V3-V4 region of the 16SrDNA gene was conducted by PCR amplification. The upstream primer sequence of the amplified region is 5′-CCTAYGGGRBGCASCAG-3′ and the downstream primer is 5′-GGACTACNNGGGTATCTAAT-3′. Gene libraries using kits (Pacific Biosciences, California, USA) was prepared from SMRTbellTM templates, and assessment of generation sequencing libraries quality was conducted using [email protected] fluorometers (Thermo Fisher, Waltham, MA, USA) and FEMTO Pulse systems (Agilent, Guangzhou, China). Sequencing of gene sequencing libraries was conducted using the Illumina NovaSeq platform (BIOTREE, Shanghai, China). PCR-free gene library construction and paired-end sequencing was conducted using the Illumina Nova sequencing platform (BIOTREE, Shanghai, China). A total of 89,879 valid data were obtained by splicing the reads and quality control. The 97% consistent sequences were clustered into OTUs (Operational Taxonomic Units) and the OTUs sequences were species annotated using the Silva138 database. The relative abundance of fecal microbiota at the level of phylum, family and genus were analysed using QIME (Version 1.8.0) software. Analysis of the alpha diversity of fecal microbiota was conducted using MOTHUR (Version 1.30) software; calculation of Unifrac distances was conducted using phyloseq script to measure beta diversity.

4. Statistical Analysis

This study was a completely randomized, cross-over design. Dry matter intake, milk yield and apparent nutrient digestibility were analysed using the MIXED program in SAS 9.4 (SAS Institute Inc, Cary, NC, USA) software, and the specific model is as follows:
Yijk = μ + Tk + Sj +Di+ Eijk
Yijk = value of the dependent variable; μ = overall mean; Tk = diet treatment effect; Sj = random effects of test cattle; Di = random effects of test period; and Eijk = random error. The results for all the data were listed as least square means, and were compared by Tukey’s test and were measured using a Spearman’s correlation rank. When p < 0.05, it was considered statistically significant, and 0.05 < p < 0.1 was considered a significant trend.

5. Results

5.1. DMI, Milk Yield and Milk Components

DMI and milk performance are shown in Table 3. Compared with the cows fed the CON diet, cows fed the IS and IO diet had lower milk fat concentrations, energy corrected milk (ECM), 3.5% fat corrected milk (FCM) yield and feed efficiency (p < 0.05); however, milk yield and DMI were not different among the three dietary treatments. Cows fed the IO diet had lower milk fat concentrations than those in the IS group (p < 0.001). However, there were no significant differences in the milk concentrations of protein, lactose and urea nitrogen among the three dietary treatments. Cows fed the IO diet had a lower milk fat yield than those in the CON group (p = 0.022), and cows fed the IS diet showed a trend for decreasing milk fat yield compared to cows fed the CON diet (p = 0.069). Compared with cows fed the IO diet, the milk protein yield of cows fed the IS diet tended to decrease (p = 0.078), and the yield of other milk components were not different among the three dietary treatments.

5.2. Apparent Nutrient Digestibility

The AOAC standard was used to determine the corresponding nutrients in diets and feces, and the results are shown in Table 4. Compared with the cows fed the CON diet, the cows fed the IS diet had a higher intake of starch (p < 0.001), and a lower intake of ADF (p = 0.004), digestibility of NDF (p = 0.004), ADF (p < 0.001) and EE (p < 0.001); the cows fed the IO diet had a higher intake of EE (p < 0.001), and had a lower intake of NDF (p = 0.014) and ADF (p = 0.004), digestibility of NDF (p = 0.004), ADF (p = 0.001) and EE (p = 0.001). Compared with the cows fed the IS diet, the cows fed the IO diet had a higher intake of EE (p < 0.001) and had a lower intake of starch (p < 0.001) and digestibility of EE (p = 0.001). However, the intake and digestibility of DM, OM and CP were not different among dietary treatments.

5.3. Fecal Fermentation Parameters Effectiveness of Different Diet Treatments

As shown in Table 5, the cows fed the IS diet had a lower fecal pH than cows fed the CON diet and the IO diet (p < 0.05), and the cows fed the IS diet and IO diet had a lower NH3-N concentration than cows fed the CON diet (p < 0.05). Cows fed the IS and IO diet had higher levels of acetate and propionate than cows fed the CON diet (p < 0.05). Cows fed the IS diet had a lower acetate to propionate ratio than cows fed the CON diet (p < 0.05). In addition, compared to the cows fed IO diet, cows fed the IS diet had lower levels of valerate (p < 0.05).

5.4. Feces Bacteria Abundance Effectiveness of Different Diet Treatments

A total of 31 phyla and 419 genera were identified in the feces by taxonomic analysis. and lists the top 10 bacterial phyla and genera (Figure 1A,B). As shown in Figure 2a and Table 6. Firmicutes (56.12% vs. 53.61% vs. 54.89%) and Bacteroidota (33.40% vs. 36.41% vs. 36.29%) were the 2 dominant phyla in the CON, IS and IO groups, respectively. We observed the relative abundance of Verrucomicrobiota was lower in the IS and IO cows than in the CON cows (p < 0.01).
At the genus level, 419 genera were identified. We only listed the 18 bacterial genera whose relative abundance was higher than 1% in at least one group. As shown in Figure 2b, the cows fed the CON, IS and IO diet were dominated by Oscillospiraceae UCG-005 (15.28% vs. 18.54% vs. 18.76%) and Rikenellaceae_RC9_gut_group (9.67% vs. 10.06% vs. 10.56%). According to Table 7 and Figure 2c, we observed that the cows fed the CON diet had a lower Oscillospiraceae_UCG-005 relative abundance, out of the three types of rations, and the cows fed the CON diet had a higher relative abundance of Lachnospiraceae_AC2044_group (1.18% vs. 0.86%) than the IO diet, while the IS cows tended to have less Lachnospiraceae_AC2044_group than those on the CON diet (p = 0.053). In addition, compared with CON cows, the relative abundance of PrevotellaceaeUCG-003 in IS cows was increased by 47.32% (p = 0.004) and the relative abundance of Alistipes in IS cows was 26.33% lower (p = 0.031).

5.5. Diversity of Fecal Microbial Communities

The alpha diversity, species accumulation curves, OTUs Venn and PCA chart of the fecal bacterial community for the different dietary treatments are shown in Figure 3 and Figure 4. In this study (Figure 3A,B), with the increase in sample sizes, the species accumulation curve tended to a plateau, showing that the test sample was sufficient and met the requirements of the test and that the results of further analysis were reliable, and there were no differences in the performance of the Shannon, Simpson, Chao and ACE indices between the different dietary treatments, except for the Simpson and Shonnon indices were higher in the CON cows than in the IS cows. As shown in Figure 4B, 535 OTUs were present in each treatment, and they could be regarded as core microflora; 69, 35 and 42 OTUs were unique to CON, IO and IS groups, respectively.

5.6. Correlation of Feces Bacterial Differentiation with Milk Components and Nutrient Digestibility

The Spearman’s rank correlation analysis was used to explore the correlations between milk components (%), nutrient digestibility and the relative abundances of those bacterial genera that differed significantly between cows fed the CON, IS and IO diet. The results are shown in Figure 5. The milk fat percentage was negatively correlated with the abundances of Prevotellaceae_UCG-003, and Paeniclostridium was correlated positively with milk fat percentage. In addition, the abundances of Prevotella, Succinivibrio, Bifidobacterium and Prevotellaceae_UCG-003 correlated negatively with ADF and NDF digestibility. The relative abundance of Treponema and Prevotella had positive and negative correlations with ADF and starch digestibility, respectively.

6. Discussion

6.1. DMI, Milk Yield and Milk Components

MFD was a syndrome characterized by a reduction in milk fat concentration [3]. In this study, milk fat concentration and yield in cows fed the IS and IO diets were consistent with cows in the MFD condition. In this trial, DMI and milk yield did not differ significantly between different dietary treatments; these results are similar to other studies [21,22]. Milk fat yield and concentration were significantly decreased, while the rest of milk components and yield did not change significantly, similar to what some other researchers have found [23,24]. The reduction of milk fat concentration and yield may be due to lower pH and higher propionate levels in the hindgut [3]. The fermentation pattern of the rumen was altered by the lower pH in cows [25] and may have increased rumen occurrence of biohydrogenation intermediates such as trans-10, cis-12 and trans-9. High levels of propionate can be produced by high-starch diets, which can inhibit the transfer of precursors required for milk fat synthesis to the mammary gland [26]. In addition, propionate decreased all the even-chain FA uniformly, regardless of the length of their carbon chain, and increased the percentage of odd-chain FA [5]. This may be one of the reasons why high-fat diets reduced milk fat yield and concentration in cows. Meanwhile, the rumen bio-hydrogenation (BH) pathway in cows could be directly modified by a high-fat diet through incomplete hydrogenation of polyunsaturated fatty acids and, as a result, the milk fat concentration was reduced in the cows [27]. Moreover, SARA could be induced by low runimal pH [28].

6.2. Apparent Nutrient Digestibility

In this trial, cows fed the IS diet had a lower ADF and NDF digestibility. This result may be due to the higher rumen fermentation rate of finely crushed wheat, as fermentable carbohydrate content was usually negatively correlated with rumen fiber degradation rate [29]. In addition, rumen VFA production was increased by a high-starch diet, which reduced pH when VFA exceeded rumen saturation, and fiber digestibility was reduced [30]. While some researchers have found that the high-starch diet had lower NDF digestibility [31]. Using the in-situ nylon bag technique, the researcher found that when cows were exposed to SARA-induced pH reduction, NDF degradation rates of hay in situ decreased from 31.5% and 51.3% to 24.6% and 36.9% at 24 h and 48 h, respectively [31]. Since the rumen was the main point of nutrient digestion, such as fiber, when rumen digestibility of nutrients was reduced, whole gut digestibility performance was reduced synchronously.
In our study, the digestibility of ether extract was decreased except that the fiber digestibility was decreased by the high-fat diet, which is similar to the results of previous studies [32]. This may be due to the fact that fiber-degrading bacteria were inhibited by unsaturated fatty acids in the high-fat diet [33]. Meanwhile, studies have shown that the hydrophobic and amphiphilic nature of the fat has a negative effect on the digestion and fermentation of nutrients in rumen [34,35].

6.3. Fecal Fermentation Parameters

In Table 5, lower fecal pH in cows fed the IS diet was caused by the higher yield of short-chain fatty acids from high-starch diets [36]. A previous study has shown that fecal pH is not affected by high-fat diets [37], similar to the results of our study. We observed that the two induction groups had lower fecal NH3-N concentrations, because the fecal NH3-N was reduced by a high-starch diet and lower pH [38], and high-fat diets can inhibit microbial protein synthesis pass direct disruption of microbial cell membrane and cellular function by the unsaturated fatty acids, and reduce fecal NH3-N concentrations, altering the microbiota by inhibiting protozoan populations [39].
In our study, the cows fed with IS and IO diets had higher concentrations of acetate. As one of the main precursors of milk fat synthesis, acetate regulated milk fat synthesis and gene expression [40]. One possibility was that shortage of glucose supply may be the limiting factor of milk fat synthesis when acetate concentration is too high [41]. The ratio of acetate to propionate was decreased, which was consistent with the previous study [42]. In this study, cows fed with the IS and IO diets had higher concentrations of propionate; additional starch in the diet can be degraded by starch-degrading bacteria and increased propionate concentrations [43]. Moreover, triacylglycerols in high-fat diets can be hydrolyzed to produce propionate [44]. Meanwhile, in the rumen, increased hydrogen due to inhibition of methanogens by PUFA can cause excess reduced nicotinamide adenine dinucleotide to be transported for propionate production [45], which may further increase whole gut propionate. The cows fed with the IO diet had a higher concentrations of valerate, which was related to their higher starch digestibility [46], and had a higher isobutyrate and butyrate than the other cows, but it was not significant, similar to the results of previous researchers [47,48].

6.4. Fecal Bacteria Abundance

Alpha diversity indicates the diversity and abundance of microflora in a sample, and the changes were inversely proportional to the intestinal pathogen [49]. As can be seen from Figure 3, that the cows fed the IO diet had a lower Simpson and Shannon index compared with the cows fed the CON diet, suggesting that the high-starch diet resulted in an imbalance of hindgut microbiota [50]. The Firmicutes and Bacteroidota were considered by previous researchers to be the majority of the dominant gut microbiota in various mammals and to play an important role in the gut microbial ecology [51]. From Table 6 and the circos map (Figure 2a), Firmicutes and Bacteroidota were not significantly different among CON, IO and IS cows, indicating that the dominant microbial phylum was less affected by the high-fat and high-starch diets. The Spirochaetota acted mainly on the hydrolysis of complex polysaccharides in the plant cell wall, the degradation of proteins and the production of B vitamins in the rumen [52], and this may be one of the reasons for the lower protein and fiber digestibility in the cows fed the IS diet. Verrucomicrobiota was significantly lower in the cows fed the IO and IS diets than in the cows fed the CON diet, which played an important role in animal immune regulation and intestinal health, and its abundance was positively correlated with immunity [53], indicating that high-fat and high-starch diets reduced hindgut immunity.
As shown in Table 7 and Figure 2C, one remarkable alteration in the present study was the increased relative abundance of Oscillospiraceae UCG-005 in the cows fed the IO diet, which can use host glycans as growth stimulants. Some researchers have shown that relative abundance of Oscillospiraceae UCG-005 plays a positive role in the intestinal health of animals [54,55]. Meanwhile, we observed a higher relative abundance of Prevotellaceae_UCG-003 in IS and IO cows, which raised the potential for enteritis [56], and the change may be related to the ruminal BH pathway; but the mechanism of action was unclear [57]. At the same time, the cows fed the IO diet had a lower relative abundance of Alistipes, similar to previous results [58], and was attributed to the reduced fibrous substrate of IS cows feeding. Treponema is a known fiber degrader and was positively correlated with fiber degradation [59], which was also one of the reasons for the lower fiber degradation in the cows fed the IS diet. Similarly, the decrease in Lachnospiraceae_AC2044_group in the cows fed the IO and IS diet may also be associated with the decrease in NH3-N reported in our companion study [60], and it has been reported to be negatively correlated with branched-chain volatile fatty acids in yaks grazing on low-CP (10%) and high-NDF shrubs [61].
In addition, our research showed an interesting result that the abundances of Prevotella, Bifidobacterium, Succinivibrio and Prevotellaceae_UCG-003 negatively correlated with the digestion of ADF and NDF, which explained the lower proportion of ADF and NDF digestibility in the cows fed the IS and IO diet. Paeniclostridium was reportedly one of the two largest genera in heifers of the Holstein-Fresian breed in another study and were correlated to their digestive functions [62], which explained the greater digestibility of ADF and NDF and the milk fat concentration in the cows fed the CON diet. Furthermore, the analysis of PCoA and bacterial abundance confirmed that IO and IS diets play a pronounced role in the correlation analysis. However, the exact mechanism remains unclear, thus requiring further studies.

7. Conclusions

In this trial, both a high-starch and a high-fat diet can result in MFD in dairy cows, resulting in significantly lower milk fat percentage, milk fat yield, 3.5% FCM and ECM yield, as well as reduced digestibility of ADF and NDF. Additionally, the high-fat diet reduced the digestibility of ether extracts in dairy cows. Both a high-starch and a high-fat diet can reduce the concentrations of NH3-N and increase the concentrations of propionate and acetate in feces. A high-fat diet can increase the concentration of valerate, and high-starch diets can decrease pH in feces. In addition, we observed changes in the hindgut flora of cows, suggesting that hindgut flora may also be involved in MFD in cows, but this relationship needs to be further investigated by looking at the relationship between hindgut flora and trans fatty acids in cows.

Author Contributions

Y.G. and B.S. conceived and designed the study; Z.W., S.L. and M.D. performed the experiments; S.L., Z.W. and Z.X. organized the database and performed the statistical analysis; S.L. wrote the manuscript, Y.L., D.L. and G.L. visualized the results; Y.G. and B.S. revised the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by National Nature Science Foundation of China (31872382 and 31501982) and the Natural Science Foundation of Guangdong Province (201981515210020).

Institutional Review Board Statement

All cows and experimental protocols in this study were reviewed and approved by the Animal Care and Use Committee of the South China Agricultural University, Guangzhou, China (approval number SCAU#2013-10).

Informed Consent Statement

Not applicable.

Data Availability Statement

The data analyzed during the current study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors gratefully thank all of the staff of the Dinghu Wens Dairy Farm (Zhaoqing, China) for their assistance in feeding, milking and care of the animals. We also acknowledge the members of the College of Animal Science of South China Agricultural University for their assistance with milk and fecal sampling.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

MFD: milk fat depression; UFA: unsaturated fatty acids; BHBA: β-hydroxybutyric acid; TMR: total mixed ration; DMI: dry matter intake; NDF: neutral detergent fiber; ADF: acid detergent fiber; AIA: acid insoluble ash; MUN: milk urea nitrogen; VFA: volatile fatty acids; NH3-N: ammoniacal nitrogen; ECM: energy corrected milk; FCM: fat corrected milk; BH: rumen bio-hydrogenation; OM: organic matter; CP: crude protein; EE: ethanol extract.

References

  1. Miciński, J.; Zwierzchowski, G.; Kowalski, I.M.; Szarek, J.; Pierożyński, B.; Raistenskis, J. The effects of bovine milk fat on human health. Pol. Ann. Med. 2012, 19, 170–175. [Google Scholar] [CrossRef]
  2. Baldin, M.; Garcia, D.; Zanton, G.I.; Hao, F.; Patterson, A.D.; Harvatine, K.J. Effect of 2-hydroxy-4-(methylthio)butanoate (HMTBa) on milk fat, rumen environment and biohydrogenation, and rumen protozoa in lactating cows fed diets with increased risk for milk fat depression. J. Dairy Sci. 2022, 105, 7446–7461. [Google Scholar] [CrossRef]
  3. Bauman, D.E.; Griinari, J.M. Regulation and nutritional manipulation of milk fat: Low-fat milk syndrome. Livest. Prod. Sci. 2001, 70, 15–29. [Google Scholar] [CrossRef]
  4. Bauman, D.E.; Griinari, J.M. Nutritional regulation of milk fat synthesis. Annu. Rev. Nutr. 2003, 23, 203–227. [Google Scholar] [CrossRef] [Green Version]
  5. Maxin, G.; Glasser, F.; Hurtaud, C.; Peyraud, J.L.; Rulquin, H. Combined effects of trans-10,cis-12 conjugated linoleic acid, propionate, and acetate on milk fat yield and composition in dairy cows. J. Dairy Sci. 2011, 94, 2051–2059. [Google Scholar] [CrossRef]
  6. Bernard, L.; Bonnet, M.; Leroux, C.; Shingfield, K.J.; Chilliard, Y. Effect of sunflower-seed oil and linseed oil on tissue lipid metabolism, gene expression, and milk fatty acid secretion in Alpine goats fed maize silage–based diets. J. Dairy Sci. 2009, 92, 6083–6094. [Google Scholar] [CrossRef] [Green Version]
  7. Zebeli, Q.; Ametaj, B.N. Relationships between rumen lipopolysaccharide and mediators of inflammatory response with milk fat production and efficiency in dairy cows. J. Dairy Sci. 2009, 92, 3800–3809. [Google Scholar] [CrossRef] [Green Version]
  8. Baumgard, L.H.; Matitashvili, E.; Corl, B.A.; Dwyer, D.A.; Bauman, D.E. trans-10, cis-12 Conjugated Linoleic Acid Decreases Lipogenic Rates and Expression of Genes Involved in Milk Lipid Synthesis in Dairy Cows1. J. Dairy Sci. 2002, 85, 2155–2163. [Google Scholar] [CrossRef] [Green Version]
  9. Dewanckele, L.; Toral, P.G.; Vlaeminck, B.; Fievez, V. Invited review: Role of rumen biohydrogenation intermediates and rumen microbes in diet-induced milk fat depression: An update. J. Dairy Sci. 2020, 103, 7655–7681. [Google Scholar] [CrossRef]
  10. van Gastelen, S.; Dijkstra, J.; Alferink, S.J.J.; Binnendijk, G.; Nichols, K.; Zandstra, T.; Bannink, A. Abomasal infusion of corn starch and β-hydroxybutyrate in early-lactation Holstein-Friesian dairy cows to induce hindgut and metabolic acidosis. J. Dairy Sci. 2021, 104, 12520–12539. [Google Scholar] [CrossRef]
  11. Neubauer, V.; Petri, R.M.; Humer, E.; Kröger, I.; Reisinger, N.; Baumgartner, W.; Wagner, M.; Zebeli, Q. Starch-Rich Diet Induced Rumen Acidosis and Hindgut Dysbiosis in Dairy Cows of Different Lactations. Animals 2020, 10, 1727. [Google Scholar] [CrossRef]
  12. Gressley, T.F.; Hall, M.B.; Armentano, L.E. Ruminant Nutrition Symposium: Productivity, digestion, and health responses to hindgut acidosis in ruminants. J. Anim. Sci. 2011, 89, 1120–1130. [Google Scholar] [CrossRef] [Green Version]
  13. Li, S.; Khafipour, E.; Krause, D.O.; Kroeker, A.; Rodriguez-Lecompte, J.C.; Gozho, G.N.; Plaizier, J.C. Effects of subacute ruminal acidosis challenges on fermentation and endotoxins in the rumen and hindgut of dairy cows. J. Dairy Sci. 2012, 95, 294–303. [Google Scholar] [CrossRef] [Green Version]
  14. NRC. Nutrient Requirements of Dairy Cattle: Seventh Revised Edition, 2001; The National Academies Press: Washington, DC, USA, 2001; p. 405. [Google Scholar]
  15. Van Soest, P.J.; Robertson, J.B.; Lewis, B.A. Methods for Dietary Fiber, Neutral Detergent Fiber, and Nonstarch Polysaccharides in Relation to Animal Nutrition. J. Dairy Sci. 1991, 74, 3583–3597. [Google Scholar] [CrossRef]
  16. Van Keulen, J.; Young, B.A. Evaluation of Acid-Insoluble Ash as a Natural Marker in Ruminant Digestibility Studies. J. Anim. Sci. 1977, 44, 282–287. [Google Scholar] [CrossRef]
  17. Guo, Y.; Xu, X.; Zou, Y.; Yang, Z.; Li, S.; Cao, Z. Changes in feed intake, nutrient digestion, plasma metabolites, and oxidative stress parameters in dairy cows with subacute ruminal acidosis and its regulation with pelleted beet pulp. J. Anim. Sci. Biotechnol. 2013, 4, 31. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Broderick, G.A.; Kang, J.H. Automated simultaneous determination of ammonia and total amino acids in ruminal fluid and in vitro media. J. Dairy Sci. 1980, 63, 64–75. [Google Scholar] [CrossRef]
  19. Erwin, E.S.; Marco, G.J.; Emery, E.M. Volatile Fatty Acid Analyses of Blood and Rumen Fluid by Gas Chromatography. J. Dairy Sci. 1961, 44, 1768–1771. [Google Scholar] [CrossRef]
  20. Wu, Z.Z.; Peng, W.C.; Liu, J.X.; Xu, G.Z.; Wang, D.M. Effect of chromium methionine supplementation on lactation performance, hepatic respiratory rate and anti-oxidative capacity in early-lactating dairy cows. Animal 2021, 15, 100326. [Google Scholar] [CrossRef]
  21. Kliem, K.E.; Humphries, D.J.; Kirton, P.; Givens, D.I.; Reynolds, C.K. Differential effects of oilseed supplements on methane production and milk fatty acid concentrations in dairy cows. Animal 2019, 13, 309–317. [Google Scholar] [CrossRef]
  22. Razzaghi, A.; Vakili, A.R.; Khorrami, B.; Ghaffari, M.H.; Rico, D.E. Effect of dietary supplementation or cessation of magnesium-based alkalizers on milk fat output in dairy cows under milk fat depression conditions. J. Dairy Sci. 2022, 105, 2275–2287. [Google Scholar] [CrossRef] [PubMed]
  23. Koch, L.E.; Jenkins, T.C.; Bridges, W.C.; Koch, B.M.; Lascano, G.J. Changes in fermentation and animal performance during recovery from classical diet-induced milk fat depression using corn with differing rates of starch degradability. J. Dairy Sci. 2019, 102, 5079–5093. [Google Scholar] [CrossRef] [PubMed]
  24. He, M.; Perfield, K.L.; Green, H.B.; Armentano, L.E. Effect of dietary fat blend enriched in oleic or linoleic acid and monensin supplementation on dairy cattle performance, milk fatty acid profiles, and milk fat depression. J. Dairy Sci. 2012, 95, 1447–1461. [Google Scholar] [CrossRef] [PubMed]
  25. Mu, Y.Y.; Qi, W.P.; Zhang, T.; Zhang, J.Y.; Mei, S.J.; Mao, S.Y. Changes in rumen fermentation and bacterial community in lactating dairy cows with subacute rumen acidosis following rumen content transplantation. J. Dairy Sci. 2021, 104, 10780–10795. [Google Scholar] [CrossRef] [PubMed]
  26. Shingfield, K.J.; Bernard, L.; Leroux, C.; Chilliard, Y. Role of trans fatty acids in the nutritional regulation of mammary lipogenesis in ruminants. Animal 2010, 4, 1140–1166. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Jenkins, T.C.; Harvatine, K.J. Lipid feeding and milk fat depression. Vet. Clin. N. Am. Food Anim. Pract. 2014, 30, 623–642. [Google Scholar] [CrossRef]
  28. Weimer, P.J.; Stevenson, D.M.; Mertens, D.R. Shifts in bacterial community composition in the rumen of lactating dairy cows under milk fat-depressing conditions. J. Dairy Sci. 2010, 93, 265–278. [Google Scholar] [CrossRef] [Green Version]
  29. Leddin, C.M.; Stockdale, C.R.; Hill, J.; Heard, J.W.; Doyle, P.T. Increasing amounts of crushed wheat fed with pasture hay reduced dietary fiber digestibility in lactating dairy cows. J. Dairy Sci. 2009, 92, 2747–2757. [Google Scholar] [CrossRef] [Green Version]
  30. Zebeli, Q.; Dunn, S.M.; Ametaj, B.N. Perturbations of plasma metabolites correlated with the rise of rumen endotoxin in dairy cows fed diets rich in easily degradable carbohydrates. J. Dairy Sci. 2011, 94, 2374–2382. [Google Scholar] [CrossRef] [Green Version]
  31. Pirondini, M.; Colombini, S.; Mele, M.; Malagutti, L.; Rapetti, L.; Galassi, G.; Crovetto, G.M. Effect of dietary starch concentration and fish oil supplementation on milk yield and composition, diet digestibility, and methane emissions in lactating dairy cows. J. Dairy Sci. 2015, 98, 357–372. [Google Scholar] [CrossRef] [Green Version]
  32. Bayat, A.R.; Ventto, L.; Kairenius, P.; Stefański, T.; Leskinen, H.; Tapio, I.; Negussie, E.; Vilkki, J.; Shingfield, K.J. Dietary forage to concentrate ratio and sunflower oil supplement alter rumen fermentation, ruminal methane emissions, and nutrient utilization in lactating cows. Transl. Anim. Sci. 2017, 1, 277–286. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Weld, K.A.; Armentano, L.E. The effects of adding fat to diets of lactating dairy cows on total-tract neutral detergent fiber digestibility: A meta-analysis. J. Dairy Sci. 2017, 100, 1766–1779. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Onetti, S.G.; Shaver, R.D.; McGuire, M.A.; Grummer, R.R. Effect of Type and Level of Dietary Fat on Rumen Fermentation and Performance of Dairy Cows Fed Corn Silage-Based Diets. J. Dairy Sci. 2001, 84, 2751–2759. [Google Scholar] [CrossRef]
  35. Martin, C.; Rouel, J.; Jouany, J.P.; Doreau, M.; Chilliard, Y. Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil. J. Anim. Sci. 2008, 86, 2642–2650. [Google Scholar] [CrossRef] [Green Version]
  36. Khafipour, E.; Krause, D.O.; Plaizier, J.C. A grain-based subacute ruminal acidosis challenge causes translocation of lipopolysaccharide and triggers inflammation. J. Dairy Sci. 2009, 92, 1060–1070. [Google Scholar] [CrossRef] [Green Version]
  37. Freitas, J.E.; Takiya, C.S.; Del Valle, T.A.; Barletta, R.V.; Venturelli, B.C.; Vendramini, T.H.A.; Mingoti, R.D.; Calomeni, G.D.; Gardinal, R.; Gandra, J.R.; et al. Ruminal biohydrogenation and abomasal flow of fatty acids in lactating cows fed diets supplemented with soybean oil, whole soybeans, or calcium salts of fatty acids. J. Dairy Sci. 2018, 101, 7881–7891. [Google Scholar] [CrossRef] [PubMed]
  38. Aguerre, M.J.; Wattiaux, M.A.; Hunt, T.; Lobos, N.E. Effect of nitrogen content and additional straw on changes in chemical composition, volatile losses, and ammonia emissions from dairy manure during long-term storage. J. Dairy Sci. 2012, 95, 3454–3466. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Yang, S.L.; Bu, D.P.; Wang, J.Q.; Hu, Z.Y.; Li, D.; Wei, H.Y.; Zhou, L.Y.; Loor, J.J. Soybean oil and linseed oil supplementation affect profiles of ruminal microorganisms in dairy cows. Animal 2009, 3, 1562–1569. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Jacobs, A.A.A.; Dijkstra, J.; Liesman, J.S.; VandeHaar, M.J.; Lock, A.L.; van Vuuren, A.M.; Hendriks, W.H.; van Baal, J. Effects of short- and long-chain fatty acids on the expression of stearoyl-CoA desaturase and other lipogenic genes in bovine mammary epithelial cells. Animal 2013, 7, 1508–1516. [Google Scholar] [CrossRef] [Green Version]
  41. Li, B.; Wang, Z.H.; Li, F.C.; Lin, X.Y. Milk fat content was changed by ruminal infusion of mixed VFAs solutions with different acetate/propionate ratios in lactating goats. Small Rumin. Res. 2007, 72, 11–17. [Google Scholar] [CrossRef]
  42. Hassanat, F.; Benchaar, C. Corn silage-based diet supplemented with increasing amounts of linseed oil: Effects on methane production, rumen fermentation, nutrient digestibility, nitrogen utilization, and milk production of dairy cows. J. Dairy Sci. 2021, 104, 5375–5390. [Google Scholar] [CrossRef] [PubMed]
  43. Russell, J.B. The importance of pH in the regulation of ruminal acetate to propionate ratio and methane production in vitro. J. Dairy Sci. 1998, 81, 3222–3230. [Google Scholar] [CrossRef]
  44. Kholif, A.E.; Morsy, T.A.; Abdo, M.M. Crushed flaxseed versus flaxseed oil in the diets of Nubian goats: Effect on feed intake, digestion, ruminal fermentation, blood chemistry, milk production, milk composition and milk fatty acid profile. Anim. Feed Sci. Technol. 2018, 244, 66–75. [Google Scholar] [CrossRef]
  45. Patra, A.K.; Yu, Z. Effects of essential oils on methane production and fermentation by, and abundance and diversity of, rumen microbial populations. Appl. Environ. Microbiol. 2012, 78, 4271–4280. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Lascano, G.J.; Alende, M.; Koch, L.E.; Jenkins, T.C. Changes in fermentation and biohydrogenation intermediates in continuous cultures fed low and high levels of fat with increasing rates of starch degradability. J. Dairy Sci. 2016, 99, 6334–6341. [Google Scholar] [CrossRef] [PubMed]
  47. Côrtes, C.; da Silva-Kazama, D.C.; Kazama, R.; Gagnon, N.; Benchaar, C.; Santos, G.T.D.; Zeoula, L.M.; Petit, H.V. Milk composition, milk fatty acid profile, digestion, and ruminal fermentation in dairy cows fed whole flaxseed and calcium salts of flaxseed oil1. J. Dairy Sci. 2010, 93, 3146–3157. [Google Scholar] [CrossRef] [Green Version]
  48. Mirzaei-Alamouti, H.; Akbari-Pabandi, K.; Mansouryar, M.; Sirjani, M.A.; Cieslak, A.; Szumacher-Strabel, M.; Patra, A.K.; Vazirigohar, M. Effects of feeding frequency and oil supplementation on feeding behavior, ruminal fermentation, digestibility, blood metabolites, and milk performance in late-lactation cows fed a high-forage diet. J. Dairy Sci. 2020, 103, 11424–11438. [Google Scholar] [CrossRef]
  49. Fecteau, M.E.; Pitta, D.W.; Vecchiarelli, B.; Indugu, N.; Kumar, S.; Gallagher, S.C.; Fyock, T.L.; Sweeney, R.W. Dysbiosis of the Fecal Microbiota in Cattle Infected with Mycobacterium avium subsp. paratuberculosis. PLoS ONE 2016, 11, e0160353. [Google Scholar] [CrossRef] [Green Version]
  50. Tao, S.; Tian, P.; Luo, Y.; Tian, J.; Hua, C.; Geng, Y.; Cong, R.; Ni, Y.; Zhao, R. Microbiome-Metabolome Responses to a High-Grain Diet Associated with the Hind-Gut Health of Goats. Front. Microbiol. 2017, 8, 1764. [Google Scholar] [CrossRef]
  51. Ley, R.E.; Hamady, M.; Lozupone, C.; Turnbaugh, P.J.; Ramey, R.R.; Bircher, J.S.; Schlegel, M.L.; Tucker, T.A.; Schrenzel, M.D.; Knight, R.; et al. Evolution of mammals and their gut microbes. Science 2008, 320, 1647–1651. [Google Scholar] [CrossRef] [Green Version]
  52. Hernández, R.; Chaib De Mares, M.; Jimenez, H.; Reyes, A.; Caro-Quintero, A. Functional and Phylogenetic Characterization of Bacteria in Bovine Rumen Using Fractionation of Ruminal Fluid. Front. Microbiol. 2022, 13, 813002. [Google Scholar] [CrossRef] [PubMed]
  53. Derrien, M.; Van Baarlen, P.; Hooiveld, G.; Norin, E.; Müller, M.; de Vos, W.M. Modulation of Mucosal Immune Response, Tolerance, and Proliferation in Mice Colonized by the Mucin-Degrader Akkermansia muciniphila. Front. Microbiol. 2011, 2, 166. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Yan, X.; Zhang, H.; Lin, A.; Su, Y. Antagonization of Ghrelin Suppresses Muscle Protein Deposition by Altering Gut Microbiota and Serum Amino Acid Composition in a Pig Model. Biology 2022, 11, 840. [Google Scholar] [CrossRef]
  55. Konikoff, T.; Gophna, U. Oscillospira: A Central, Enigmatic Component of the Human Gut Microbiota. Trends Microbiol. 2016, 24, 523–524. [Google Scholar] [CrossRef] [PubMed]
  56. Li, Z.; Ding, L.; Zhu, W.; Hang, S. Effects of the increased protein level in small intestine on the colonic microbiota, inflammation and barrier function in growing pigs. BMC Microbiol. 2022, 22, 172. [Google Scholar] [CrossRef]
  57. Huws, S.A.; Kim, E.J.; Lee, M.R.; Scott, M.B.; Tweed, J.K.; Pinloche, E.; Wallace, R.J.; Scollan, N.D. As yet uncultured bacteria phylogenetically classified as Prevotella, Lachnospiraceae incertae sedis and unclassified Bacteroidales, Clostridiales and Ruminococcaceae may play a predominant role in ruminal biohydrogenation. Environ. Microbiol. 2011, 13, 1500–1512. [Google Scholar] [CrossRef]
  58. Mu, Y.Y.; Qi, W.P.; Zhang, T.; Zhang, J.Y.; Mao, S.Y. Gene function adjustment for carbohydrate metabolism and enrichment of rumen microbiota with antibiotic resistance genes during subacute rumen acidosis induced by a high-grain diet in lactating dairy cows. J. Dairy Sci. 2021, 104, 2087–2105. [Google Scholar] [CrossRef]
  59. Wenner, B.A.; Park, T.; Mitchell, K.; Kvidera, S.K.; Griswold, K.E.; Horst, E.A.; Baumgard, L.H. Effect of zinc source (zinc sulfate or zinc hydroxychloride) on relative abundance of fecal Treponema spp. in lactating dairy cows. JDS Commun. 2022, 3, 334–338. [Google Scholar] [CrossRef]
  60. Monteiro, H.F.; Lelis, A.L.J.; Fan, P.; Calvo Agustinho, B.; Lobo, R.R.; Arce-Cordero, J.A.; Dai, X.; Jeong, K.C.; Faciola, A.P. Effects of lactic acid-producing bacteria as direct-fed microbials on the ruminal microbiome. J. Dairy Sci. 2022, 105, 2242–2255. [Google Scholar] [CrossRef]
  61. Yang, C.; Tsedan, G.; Liu, Y.; Hou, F. Shrub coverage alters the rumen bacterial community of yaks (Bos grunniens) grazing in alpine meadows. J. Anim. Sci. Technol. 2020, 62, 504–520. [Google Scholar] [CrossRef]
  62. Cendron, F.; Niero, G.; Carlino, G.; Penasa, M.; Cassandro, M. Characterizing the fecal bacteria and archaea community of heifers and lactating cows through 16S rRNA next-generation sequencing. J. Appl. Genet. 2020, 61, 593–605. [Google Scholar] [CrossRef]
Figure 1. (A). Effect of dietary treatment on accumulation map of feces microflora at the phylum; (B). Effect of dietary treatment on accumulation map of feces microflora at the genus.
Figure 1. (A). Effect of dietary treatment on accumulation map of feces microflora at the phylum; (B). Effect of dietary treatment on accumulation map of feces microflora at the genus.
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Figure 2. Circos map of feces microflora at the phylum (a) and genus (b) levels for test cows; (c) Effects of different dietary treatments on the feces microflora (genus level; relative abundance >1%; * p < 0.05, ** p < 0.01) (CON = fed the control diet; IS = fed the high-starch diet; IO = fed the high-fat diet; and number = cow number).
Figure 2. Circos map of feces microflora at the phylum (a) and genus (b) levels for test cows; (c) Effects of different dietary treatments on the feces microflora (genus level; relative abundance >1%; * p < 0.05, ** p < 0.01) (CON = fed the control diet; IS = fed the high-starch diet; IO = fed the high-fat diet; and number = cow number).
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Figure 3. Effect of different dietary treatments on the feces microflora of dairy cows. (A) Alpha-diversity of the different dietary treatments (* p < 0.05); (B) rarefaction curve of the different dietary treatments; CON = fed the control diet; IS = fed the high-starch diet; IO = fed the high-fat diet; and number = cow number.
Figure 3. Effect of different dietary treatments on the feces microflora of dairy cows. (A) Alpha-diversity of the different dietary treatments (* p < 0.05); (B) rarefaction curve of the different dietary treatments; CON = fed the control diet; IS = fed the high-starch diet; IO = fed the high-fat diet; and number = cow number.
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Figure 4. Effect of different dietary treatments on the feces microflora of dairy cows. (A) Principal coordinates analysis (PCoA) of different diet treatments and (B) Venn diagram of the OTUs of different diet treatments.
Figure 4. Effect of different dietary treatments on the feces microflora of dairy cows. (A) Principal coordinates analysis (PCoA) of different diet treatments and (B) Venn diagram of the OTUs of different diet treatments.
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Figure 5. The correlations between the differential bacteria in different dietary treatments and the milk components and nutrient digestion. Violet color indicates negative correlations and blue color represents positive correlations. Color darkness stands for the value of correlation coefficients, the darker the color, the greater the coefficient. The asterisk indicates the correlation is statistically significant (p < 0.05). (CON = fed the control diet; IS = fed the high-starch diet; and IO = fed the high-fat diet. DM = dry matter; ADF = acid detergent fiber; and NDF = neutral detergent fiber.).
Figure 5. The correlations between the differential bacteria in different dietary treatments and the milk components and nutrient digestion. Violet color indicates negative correlations and blue color represents positive correlations. Color darkness stands for the value of correlation coefficients, the darker the color, the greater the coefficient. The asterisk indicates the correlation is statistically significant (p < 0.05). (CON = fed the control diet; IS = fed the high-starch diet; and IO = fed the high-fat diet. DM = dry matter; ADF = acid detergent fiber; and NDF = neutral detergent fiber.).
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Table 1. Composition and nutritional levels of experimental diets.
Table 1. Composition and nutritional levels of experimental diets.
Ingredients (% of DM 2)Diet 1, %
CONISIO
Whole corn silage25.5517.4225.07
Alfalfa hay15.2610.3814.97
Oat hay6.284.256.18
Ground corn 13.2713.2713.02
Steam-flaked corn6.026.025.91
Fine ground wheat -15.01-
Sunflower oil--5.86
Soybean meal15.4214.0917.01
Sunflower seed meal0.730.730.71
Extruded soybean0.840.840.82
Sugar beet pulp1.681.68-
Soybean hull4.295.65-
Whole cottonseed6.146.146.02
Cane molasses1.551.551.53
Mineral–vitamin premix 30.420.420.42
Dicalcium phosphate0.430.430.42
Limestone0.870.870.85
Sodium bicarbonate0.750.750.73
Magnesium oxide0.220.220.21
Salt0.280.280.27
Nutritional levels 4, % DM
OM93.7194.4393.95
CP16.4716.5216.52
NEL, MJ/kg 56.717.037.70
NDF32.1730.4128.31
ADF15.8413.8413.15
Starch23.5131.9322.97
EE2.602.538.13
Calcium0.870.790.82
Total phosphorus0.400.410.40
1 CON = basic total mixed ration; IS = high-starch diet with crushed wheat; IO = high-fat diet with sunflower fat. 2 DM = dry matter. 3 Premix, per kg (DM basis) contained: Vitamin A, 1,000,000 IU; Vitamin D, 392,000 IU; Vitamin E, 10,080 IU; Iodine, 120 mg; Selenium, 66 mg; Cobalt, 100 mg; Copper, 2000 mg; Zinc, 18,000 mg; and Manganese, 11,000 mg. 4 Nutritional levels: OM = organic matter; CP = crude protein; ADF = acid detergent fiber; NDF = neutral detergent fiber; EE = ether extract. 5 Calculated using NEL values of feedstuffs from Nutrient Requirements of Dairy Cattle (NRC, 2001)
Table 2. Treatment assignment of a cross-over design to study the effect of dietary starch or fat on milk fat depression 1.
Table 2. Treatment assignment of a cross-over design to study the effect of dietary starch or fat on milk fat depression 1.
AssignmentPre-ExperimentPeriod 1Period 2Period 3
1CONISWash periodIO
2CONIOWash periodIS
1 CON/Wash period = basic total mixed ration; IS = high-starch diet; and IO = high-fat diet.
Table 3. Effect of dietary treatment on DMI and milk performance of dairy cows.
Table 3. Effect of dietary treatment on DMI and milk performance of dairy cows.
Items 1Treatments 2SEMp-Value
CONISIOC vs. ISC vs. IOIS vs. IO
DMI, kg/d22.7922.8323.120.2860.999 0.913 0.917
Milk, kg/d29.5228.2630.920.5090.601 0.534 0.065
Milk components, %
Milk fat3.96 a3.26 b2.69 c0.115<0.001<0.001<0.001
Milk protein3.113.163.160.0180.284 0.316 0.997
Milk lactose4.724.844.820.0250.150 0.206 0.979
Yield, kg/d
Milk fat1.17 a0.91 0.82 b 0.0370.069 0.022 0.363
Milk protein0.92 0.89 0.98 0.0160.927 0.642 0.078
Milk lactose1.39 1.37 1.49 0.0260.893 0.213 0.101
3.5%FCM31.68 a26.72 b 26.72 b 0.6330.004 0.004 1.000
ECM31.36 a 27.25 b 27.80 b 0.5260.002 0.006 0.829
Milk urea nitrogen, mg/dL17.06 19.25 20.42 0.8210.419 0.153 0.772
Feed efficiency 31.38 a 1.19 b 1.21 b 0.0250.005 0.007 0.977
1 DMI = DM intake; 3.5% FCM = 3.5% fat corrected milk, calculated with the formula: 16.23 × milk fat production + 0.4318 × milk yield; ECM = energy corrected milk, calculated with the formula: 7.2 × milk protein yield + 0.327 × milk yield + 12.95 × milk fat yield. 2 CON/C = control group; IS = high-starch diet group; IO = high-fat diet group. 3 Feed efficiency = kg of ECM/kg of DMI [20]. a,b,c Different letters indicate significant differences (p < 0.05).
Table 4. Effect of dietary treatment on nutrient digestibility in dairy cows.
Table 4. Effect of dietary treatment on nutrient digestibility in dairy cows.
Items 1Treatments 2SEMp-Value
CONISIOC vs. ISC vs. IOIS vs. IO
Nutrient intake, kg/d
DM22.7922.8323.120.2860.9990.9130.917
OM21.6920.9420.450.2310.2600.0420.543
CP3.743.933.980.0610.4220.2690.941
NDF7.276.946.550.1040.2950.0140.215
ADF3.45 a3.16 b3.04 b0.0460.0340.0040.224
EE0.85 b0.86 b2.01 a0.1150.932<0.001<0.001
Starch4.86 b7.16 a5.18 b0.227<0.0010.473<0.001
Nutrient digestibility, %
DM75.4873.4773.670.4030.108 0.154 0.975
OM74.8372.7272.870.4100.091 0.122 0.984
CP66.8964.4969.561.2520.710 0.658 0.248
NDF55.06 a46.50 b47.93 b1.064<0.0010.004 0.700
ADF60.05 a49.30 b51.15 b1.228<0.0010.001 0.605
EE81.73 a79.43 a70.16 b1.3320.597 0.001 0.001
Starch92.8592.3193.460.5400.917 0.897 0.683
1 DMI = DM intake; OM = organic matter; CP = crude protein; NDF = neutral detergent fibers; ADF = acid detergent fibers; EE = ether extract. 2 CON/C = control group; IS = high-starch diet group; IO = high-fat diet group. a,b Different letters indicate significant differences (p < 0.05).
Table 5. Effect of dietary treatment on hindgut fermentation parameters of dairy cows.
Table 5. Effect of dietary treatment on hindgut fermentation parameters of dairy cows.
Items 1Treatments 2SEMp-Value
CONISIOC vs. ISC vs. IOIS vs. IO
pH6.76 6.59 6.75 0.023 0.025 0.9690.038
NH3-N, mg/100 mL3.53 a2.96 b 3.04 b 0.067 0.011 0.028 0.689
Acetate, mmol/L14.86 b 18.51 a 18.03 a 0.442 0.023 0.049 0.741
Propionate, mmol/L2.93 b 3.86 a 4.23 a 0.131 0.004 0.033 0.061
Valerate, mmol/L0.22 b 0.20 b 0.27 a 0.011 0.613 0.049 0.008
Butyrate, mmol/L2.80 3.18 3.29 0.118 0.260 0.116 0.876
Isobutyrate, mmol/L0.19 0.19 0.25 0.013 1.000 0.128 0.128
Acetate: Propionate5.12 a 4.39 b 4.69 ab 0.105 0.013 0.155 0.369
TVFA21.0025.7225.910.6260.0790.0950.9771
1 pH = potential of hydrogen; NH3-N = ammoniacal nitrogen; TVFA = total volatile fatty acid. 2 CON/C = control group; IS = high-starch diet group; IO = high-fat diet group. a,b Different letters indicate significant differences (p < 0.05).
Table 6. Effect of dietary treatment on feces microflora of dairy cows (phylum levels, %).
Table 6. Effect of dietary treatment on feces microflora of dairy cows (phylum levels, %).
ItemsTreatments 1SEMp-Value
CONISIOC vs. ISC vs. IOIS vs. IO
Firmicutes56.1253.6154.891.258 0.447 0.677 0.712
Bacteroidota33.4036.4136.291.097 0.332 0.249 0.966
Spirochaetota2.841.162.350.354 0.084 0.619 0.050
Actinobacteriota0.442.331.010.479 0.172 0.310 0.363
Proteobacteria1.963.131.840.424 0.355 0.894 0.224
Euryarchaeota1.180.150.200.235 0.143 0.162 0.530
unidentified_Bacteria2.111.641.820.096 0.037 0.262 0.416
Desulfobacterota0.110.080.100.018 0.419 0.935 0.504
Fibrobacterota0.010.010.040.012 0.820 0.447 0.407
Verrucomicrobiota0.17 a0.03 b0.02 b0.018 0.003 <0.001 0.442
1 CON/C = control group; IS = high-starch diet group; IO = high-fat diet group. a,b Different letters indicate significant differences (p < 0.05).
Table 7. Effect of dietary treatment on feces microflora of dairy cows (genus levels, %).
Table 7. Effect of dietary treatment on feces microflora of dairy cows (genus levels, %).
ItemsTreatments 1SEMp-Value
CONISIOC vs. ISC vs. IOIS vs. IO
Oscillospiraceae_UCG-00515.28 b 18.54 18.76 a 0.751 0.104 0.028 0.905
Rikenellaceae_RC9_gut_group9.67 10.06 10.56 0.468 0.783 0.311 0.695
Prevotella1.20 2.44 1.01 0.570 0.486 0.813 0.373
Treponema2.81 1.16 2.31 0.354 0.088 0.612 0.058
Bifidobacterium0.20 2.16 0.90 0.479 0.155 0.218 0.385
Bacteroides5.34 5.07 5.44 0.335 0.744 0.923 0.642
Succinivibrio0.91 2.29 1.03 0.364 0.203 0.770 0.237
Prevotellaceae_UCG-0032.98 b4.39 a 4.52 0.307 0.004 0.069 0.879
Paeniclostridium2.46 1.21 1.50 0.290 0.131 0.256 0.446
Romboutsia2.53 1.60 2.12 0.277 0.213 0.615 0.324
Alistipes3.57 a 2.63 b 3.25 0.190 0.031 0.484 0.201
Clostridium_sensu_stricto_12.23 1.70 2.37 0.252 0.395 0.834 0.270
Agathobacter2.21 2.50 2.20 0.188 0.580 0.997 0.525
Methanobrevibacter1.09 0.14 0.18 0.217 0.142 0.161 0.515
Turicibacter1.29 0.84 1.09 0.141 0.206 0.627 0.397
Christensenellaceae_R-7_group1.92 1.87 1.98 0.075 0.815 0.779 0.544
Monoglobus1.48 1.11 1.46 0.083 0.096 0.919 0.055
Lachnospiraceae_AC2044_group1.18 a 0.90 0.86 b 0.054 0.053 0.027 0.651
Others27.64 28.26 27.46 1.079 0.831 0.954 0.745
1 CON/C = control group; IS = high-starch diet group; IO = high-fat diet group. a,b Different letters indicate significant differences (p < 0.05).
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Liu, S.; Wei, Z.; Deng, M.; Xian, Z.; Liu, D.; Liu, G.; Li, Y.; Sun, B.; Guo, Y. Effect of a High-Starch or a High-Fat Diet on the Milk Performance, Apparent Nutrient Digestibility, Hindgut Fermentation Parameters and Microbiota of Lactating Cows. Animals 2023, 13, 2508. https://doi.org/10.3390/ani13152508

AMA Style

Liu S, Wei Z, Deng M, Xian Z, Liu D, Liu G, Li Y, Sun B, Guo Y. Effect of a High-Starch or a High-Fat Diet on the Milk Performance, Apparent Nutrient Digestibility, Hindgut Fermentation Parameters and Microbiota of Lactating Cows. Animals. 2023; 13(15):2508. https://doi.org/10.3390/ani13152508

Chicago/Turabian Style

Liu, Suran, Ziwei Wei, Ming Deng, Zhenyu Xian, Dewu Liu, Guangbin Liu, Yaokun Li, Baoli Sun, and Yongqing Guo. 2023. "Effect of a High-Starch or a High-Fat Diet on the Milk Performance, Apparent Nutrient Digestibility, Hindgut Fermentation Parameters and Microbiota of Lactating Cows" Animals 13, no. 15: 2508. https://doi.org/10.3390/ani13152508

APA Style

Liu, S., Wei, Z., Deng, M., Xian, Z., Liu, D., Liu, G., Li, Y., Sun, B., & Guo, Y. (2023). Effect of a High-Starch or a High-Fat Diet on the Milk Performance, Apparent Nutrient Digestibility, Hindgut Fermentation Parameters and Microbiota of Lactating Cows. Animals, 13(15), 2508. https://doi.org/10.3390/ani13152508

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