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Article

Effect of Alkaline Mineral Complex Buffer Supplementation on Rumen Fermentation, Rumen Microbiota and Rumen Epithelial Transcriptome of Newborn Calves

by
Xiaowei Wang
1,2,†,
Cheng Guo
1,2,†,
Xiaofeng Xu
2,
Lili Zhang
2,*,
Shengli Li
1,2,*,
Dongwen Dai
2 and
Wen Du
1
1
Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, State Key Laboratory of Animal Nutrition, Department of Animal Nutrition and Feed Science, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing 100094, China
2
College of Animal Science and Technology, Ningxia University, No. 489, Helanshan West Road, Yinchuan 750021, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Fermentation 2023, 9(11), 973; https://doi.org/10.3390/fermentation9110973
Submission received: 6 October 2023 / Revised: 5 November 2023 / Accepted: 9 November 2023 / Published: 14 November 2023
(This article belongs to the Section Industrial Fermentation)
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Abstract

:
Alkaline mineral complex buffer can improve rumen fermentation and affect the rumen microbiota of dairy cows. Here, we studied the effects of alkaline mineral complex buffer on serum immunity indexes, rumen fermentation and the microbiota of newborn calves. We also investigated changes in the rumen epithelial transcriptome expression profile. Compared with the control group, at 15 d, the serum contents of TP and GLB in the treatment group increased significantly (p < 0.05). At 30 d, the serum contents of GLB in the treatment group increased significantly (p < 0.05). At 45 d, the serum contents of IgG in the treatment group increased significantly (p < 0.05). At 60 d, the serum contents of TP and IgG in the treatment group increased significantly (p < 0.05). Rumen pH in the treatment groups was significantly increased at different days of age (p < 0.05). The microbial community composition in the rumen was determined using bacterial and archaeal 16S ribosomal RNA (rRNA) gene amplicon-sequencing. Analysis of bacterial composition in the rumen showed that there was no significant difference in bacterial diversity (p > 0.05). At the phylum level, Firmicutes were significantly decreased and Bacteroidetes were significantly increased in the treatment group at 30 d (p < 0.05). At the genus level, Prevotella_1, Olsenella, Christensenellaceae_R-7_group were significantly increased, and Lachnospiraceae_NK3A20_group, Ruminococcaceae_UCG-014 and Ruminococcus_2 were significantly decreased in the treatment group at 30 d (p < 0.05). Christensenellaceae_R-7_group was significantly increased in the treatment group (p < 0.05) at 45 d. Prevotella_9 was significantly decreased, and Prevotellaceae_UCG_001, Christensenellaceae_R-7_group were significantly increased in the treatment group at 60 d (p < 0.05). RNA sequence analysis of the rumen epithelium showed that 232 differentially expressed genes were screened, of which 158 were upregulated and 74 were downregulated. The main enrichment pathway was related to immune regulation. In conclusion, alkaline mineral complex buffer can enhance the body’s immune response, regulate rumen fermentation by regulating the abundance of rumen microbiota and upregulate immune-related genes in rumen tissues to promote immune regulation. The results of this study provide a reference for the early nutritional regulation of newborn calves with an alkaline mineral complex buffer.

1. Introduction

The rumen is very important to the performance and health of ruminants. Thus, promoting the rumen development of calves is an important goal of the nutritional regulation of calves. In the early rumen development of calves, volatile fatty acids (VFAs) are one of the main influencing factors [1]. The production and absorption of VFAs stimulate the proliferation and apoptosis of rumen epithelial cells [2,3]. The rumen epithelium also plays a key role in the absorption, transport and metabolism of VFAs [4], and maintaining the integrity of the rumen epithelium is particularly relevant to the growth, immunity and health of ruminants [5,6]. Rumen microorganisms also play an important role in the early rumen development of calves. On the one hand, they promote rumen development and participate in nutrient absorption [7,8]; on the other hand, they participate in the body’s immune system regulation [9]. However, with the increase in calf age, the rumen microbiota is easily affected by various factors such as diet and age and gradually forms a microbial community with high resilience [10,11]. An alkaline mineral complex buffer (AMCB) has been shown to improve ruminal fermentation, rumen microbiota and body immunity in transition dairy cows [12]. Therefore, we speculate whether the feeding effect of feeding AMCB to newborn calves is similar to that of adult ruminants.
In the study of the symbiotic interaction between ruminant rumen microorganisms and rumen epithelial development, it was shown that early rumen microorganisms and rumen epithelium jointly participated in rumen development, maintenance of rumen pH homeostasis, rumen immune function expression and regulation, rumen nutrient absorption and metabolism, etc. [13,14,15]. We hypothesize that the AMCB can enhance the body’s immune response, regulate rumen fermentation by regulating the abundance of rumen microbiota and upregulate immune-related genes in rumen tissues to promote immune regulation. Here, we investigated the effects of AMCB supplementation on the immunity of newborn calves, ruminal fermentation and rumen microbiota, and combined them with ruminal epithelial transcriptome sequencing to explore the regulation of related gene expression in the rumen epithelium of newborn calves.

2. Materials and Methods

2.1. Animals, Study Design and Diets

Thirty newborn dairy calves with a similar birth weight (36.63 ± 3.34 kg) and birth time (1–2 d) were randomly divided into two groups: Control group (Con group) and Treatment group (Tre group) with fifteen calves in each group (ten female calves and five male calves). The con group was fed according to normal feeding procedures for newborn calves in the pasture. In the Tre group, 5 mL of AMCB was added to milk from 1 day of age and stopped at 60 days of age. The pre-feeding period lasted 7 days, and the formal experiment lasted 60 days. Given that newborn calves cannot feed on their own, calves 1 to 7 days of age were fed in bottles, and calves 8 to 60 days of age were fed in buckets. Calves were fed at 06:00 and 16:00 h daily in the pasture, and the daily feeding rate during breastfeeding was 4 L/calf at 1–7 days of age, 6 L/calf at 8–14 days of age, 8 L/calf at 15–25 days of age, 10 L/calf at 26–50 days of age and a reduced feeding rate every 2 days at 51–60 d until weaning. Water and pellets were changed daily during breastfeeding to ensure clean and fresh pellets. The nutrient intake of newborn calves is shown in Table 1, Table 2 and Table 3. The AMCB used in this experiment was obtained from the Nail Biotechnology Company, Beijing, China, and its composition is presented in Table 4.

2.2. Blood Sample and Ruminal Sample Collection

The blood samples (10 mL) of all the calves (ten randomly selected in each group) were collected via the jugular vein into evacuated tubes, without any anticoagulant, on days 1, 15, 30, 45 and 60 of the trial period, 3 h after morning feeding. After centrifugation (1500× g; 10 min), the obtained serum was stored at −20 °C. The immunoglobulin A (IgA) ELISA Kits (supplied by Beijing Laibotairui Technology Co. Ltd. Beijing, China) were used for spectrophotometric determination of IgA concentrations at a wavelength of 450 nm (repeated three times). The following biochemical parameters were determined using assay kits supplied by Weifang Zecheng Biotechnology Co. Ltd (Shandong, China).: total protein (TP) concentration at 546 nm and albumin (ALB) concentration at 630 nm using a spectrophotometric method. The concentration of GLB is equal to the concentration of TP minus the concentration of ALB.
On the 30 d, 45 d and 60 d of the trial period, five calves (three female calves and two male calves) were randomly selected in each group. After feeding for 2 h in the morning, a rumen fluid collection tube and 200 mL syringe were used to collect rumen fluid from calves, and the first 100 mL was discarded to reduce saliva contamination. Five male calves from each group were slaughtered at 60 d. The rumen epithelial tissue in the abdominal sac area was rinsed with normal saline and then stored at −80 °C for transcriptomic analysis.

2.3. Rumen Fermentation Parameters

The pH value of rumen fluid (pHS-3E, INESA Scientific Instrument Co., Ltd., Shanghai, China) was determined immediately after the collection of fresh rumen fluid, then the rumen fluid was filtered with four layers of gauze, the filtrate was centrifuged at 4000 rpm/min for 15 min, and the supernatant was stored at −20 °C. The supernatant was used to determine NH3-N, MCP and VFA. NH3-N was determined by the spectrophotometer described by Broderick and Kang [16]. MCP was determined as previously described [17]. VFA concentration was determined by gas chromatography, these methods are described by Wu [18].

2.4. DNA Extraction, 16S rRNA Gene Sequencing and Composition Analysis of Rumen Microbiota

Total genomic DNA samples were extracted using a commercial DNA isolation kit (MoBio Laboratories, Carlsbad, CA, USA), following the manufacturer’s instructions. The quantity and quality of extracted DNAs were measured using a NanoDrop NC2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and agarose gel electrophoresis, respectively.
PCR amplification of the bacterial 16S rRNA genes V3–V4 region was performed using the forward primer 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and the reverse primer 806R (5′-GGACTACNNGGGTATCTAAT-3′) [19]. The DNA extracted from the rumen microbiota samples were sent to Shanghai Bioprofile Technology Company Ltd., Shanghai, China, for sequencing on an Illumina NovaSeq 6000 platform (Illumina, San Diego, CA, USA).
The raw sequence data were processed using QIIME2 (www.qiime2.org) [20]. Raw sequence data were demultiplexed using the demux plugin, followed by primers cutting with the cutadapt plugin. Sequences were then quality filtered, denoised, merged and chimeras removed using the DADA2 plugin [21]. Non-singleton amplicon sequence variants (ASVs) were aligned with mafft [22] and used to construct a phylogeny with fasttree2 [23]. The species structure was analyzed by RDP classifier software (Version 2.14), and the data results were plotted by R software (3.2.0) (R Core Team, Vienna, Austria).

2.5. Rumen Epithelial RNA Extraction and Sequencing and Differential Expression Gene and Function Analysis

According to the manufacturer’s instructions (Invitrogen, Carlsbad, CA, USA), total RNA was extracted from liver tissue using TRIzol® Reagent and genomic DNA was removed using DNase I (TaKara, Kusatsu, Japan). RNA degradation and contamination were monitored on 1% agarose gels. Then RNA quality was determined by 2100 Bioanalyser (Agilent Technologies, Santa Clara, CA, USA) and quantified using the ND-2000 (NanoDrop Technologies). Only high-quality RNA samples (OD260/280 = 1.8~2.2, OD260/230 ≥ 2.0, RIN ≥ 8.0, 28S:18S ≥ 1.0, >1 μg) were used to construct the sequencing library.
RNA purification, reverse transcription, library construction and sequencing were performed at Shanghai Majorbio Bio-pharm Biotechnology Co., Ltd. (Shanghai, China) according to the manufacturer’s instructions (Illumina, San Diego, CA, USA). The transcriptome library was prepared following the TruSeq TM RNA sample preparation Kit from Illumina (San Diego, CA, USA) using 1 μg of total RNA. Messenger RNA was initially isolated according to the polyA selection method by oligo(dT) beads and then fragmented by fragmentation buffer. Double-stranded cDNA was synthesized using a SuperScript double-stranded cDNA synthesis kit (Invitrogen, CA, USA) with random hexamer primers (Illumina). Then the synthesized cDNA was subjected to end-repair, phosphorylation and ‘A’ base addition according to Illumina’s library construction protocol. Libraries were size selected for cDNA target fragments of 300 bp on 2% Low Range Ultra Agarose followed by PCR amplified using Phusion DNA polymerase (NEB) for 15 PCR cycles. After being quantified by TBS380, the paired-end RNA-seq sequencing library was sequenced with the Illumina NovaSeq 6000 sequencer (2 × 150 bp read length).

2.6. Statistical Analysis

Statistical analysis of the data (serum immunity indexes, rumen fermentation parameters) was performed in SAS 9.4 software (SAS Institute Inc., Cary, NC, USA) for one-way ANOVA. The results are represented by the mean value, SEM and the p-value. A p-value less than 0.05 was considered statistically significant. The following model indicates the interaction effects between time and group:
Y = µ + Ti + Gj + TGij + Eijkl
where Y is the dependent variable, µ is the overall mean, Ti is the time effect, Gj is the group effect, TGij is the interaction effect between T and G and Eijkl is the random residual error. Means were considered significantly different at p < 0.05.
The correlation between rumen fermentation parameters and rumen bacteria, and the correlation between rumen bacteria and differentially expressed genes was analyzed by Pearson correlation analysis using SPSS 24 software (IBM Corp., Armonk, NY, USA).
RSEM(Version 1.3.3) [24] was used to quantify gene abundances. Differential expression analysis was performed using the DESeq2 [25], DEGs with |log2 (fold change)| ≥ 1 and p-adjust ≤ 0.05 (DESeq2/edgeR/Limma)/p-adjust ≤ 0.001(DEGseq)/Prob > 0.8(NOIseq) were considered to be significantly differentially expressed genes. In addition, functional-enrichment analyses, including Gene Ontology (GO, http://www.geneontology.org) (accessed on 1 July 2023) and Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/) (accessed on 1 July 2023), were performed to identify which DEGs were significantly enriched in GO terms and metabolic pathways at p-adjust ≤ 0.05 compared with the whole-transcriptome background. GO functional enrichment and KEGG pathway analyses were carried out using Goatools (Version 0.6.5) and KOBAS (Version 2.1.1) [26], respectively.

3. Results

3.1. Serum Immunity Indexes

The effects of AMCB supplementation on the serum immunity indexes of newborn calves are shown in Table 5. At 15 d, the serum contents of TP and GLB in the treatment group increased significantly (p < 0.05). At 30 d, the serum contents of GLB in the treatment group increased significantly (p < 0.05). At 45 d, the serum contents of IgG in the treatment group increased significantly (p < 0.05). At 60 d, the serum contents of TP and IgG in the treatment group increased significantly (p < 0.05).

3.2. Rumen Fermentation Parameters

Effects of AMCB supplementation on rumen fermentation parameters of newborn calves (Table 6). As shown in Table 6, the rumen pH of calves in treatment group at 30, 45, and 60 d was significantly increased compared with the control group (p < 0.05). At 30 d, the treatment group’s NH3-N was significantly increased (p < 0.05). At 45 d, the treatment group’s ratio of acetic to propionic was significantly increased (p < 0.05).

3.3. Rumen Microbiota

Alpha diversity analysis of rumen microbiota shows that (Figure 1A–C), the species richness index (Chao1 and Observed species) and bacterial diversity index (Shannon and Simpson) are not significantly different at different days of age (p > 0.05). Beta diversity analysis of rumen microbiota shows that (Figure 1D) weighted UniFrac distance, Jaccard distance, Bray-Curtis distance, unweighted UniFrac distance and weighted unifrac distance were used for the principal coordinate analysis (PCoA) of the rumen microbiota structure of calves at different days of age. The microbiota structure of the control group and the treatment group showed a clustering trend at different days of age and the control group and the treatment group were gradually separated with an increase in calf age (PERMANOVA, p30 d = 0.061, p45 d = 0.214, p60 d = 0.038).
To study the diversity of sample species composition, OTU cluster analysis was conducted with a similarity greater than 95%, and 5992, 6348 and 6474 OTUs were generated at 30, 45 and 60 d, respectively. Through OTU annotation, 22, 21 and 19 phyla were obtained at 30, 45 and 60 d, respectively, with Firmicutes and Bacteroidetes the two main categories (Figure 2A–C). Firmicutes were significantly decreased and Bacteroidetes were significantly increased in the treatment group at 30 d (p < 0.05). Meanwhile, to better understand the changes in rumen microbial composition, analysis was performed at the genus level (Figure 2D–F). Compared with the control group, the relative abundance of Prevotella_1, Olsenella and Christensenellaceae_R-7_group were significantly increased, and Lachnospiraceae_NK3A20_group, Ruminococcaceae_UCG-014 and Ruminococcus_2 were significantly decreased in the treatment group at 30 d (p < 0.05). Christensenellaceae_R-7_group was significantly increased in the treatment group (p < 0.05) at 45 d. Prevotella_9 was significantly decreased and Prevotellaceae_UCG_001 and Christensenellaceae_R-7_group were significantly increased in the treatment group at 60 d (p < 0.05). To explore the marker bacteria of rumen contents between the two groups, microbiota LEfSe analysis was applied. LEfSe analysis (Figure 2G–I) results indicated that, at 30 d, the labeled species in the treatment group were: the g_Odoribacter, g_[Ruminococcus_gauvreauii] group and g_Elusimicrobium, g_Blautia (p < 0.05). At 45 d, the labeled species in the treatment group were g_Ruminococcus_2, g_Collinsella, g_Faecalicoccus and g_Parabacteroides (p < 0.05). At 60 d, the labeled species in the treatment group were g_Prevotellaceae, g_Ruminococcaceae_UCG_005, g_Ruminococcaceae_NK4A214_group and g_Christensenellaceae_R_7_group (p < 0.05), etc.

3.4. Transcriptome Analysis of Rumen Epithelial Tissue

After the sample passes dimensionality reduction analysis, there are relative coordinate points on the principal component, and the distance of each sample point represents the distance of the sample; a closer distance indicates a higher similarity between samples. Among them, the contribution degrees of PC1, PC2 and PC3 to the differentiated samples were 32.70%, 19.31% and 9.74%, respectively (Figure 3A). In this study, 232 DEGs were screened in the Con group and Tre group (DEG screening conditions: FC ≥ 2 and FC ≤ 0.5, p-value < 0.05), among which 158 upregulated genes and 74 downregulated genes were detected (Figure 3B). GO enrichment analysis of genes in the gene set was performed using the Goatools software (Version 0.6.5)and Fisher’s exact test. When p-adjust < 0.05, it was considered that there was significant enrichment of the GO function. GO enrichment analysis showed that 56 GO terms were significantly enriched, and only the first 20 GO terms are listed here (Figure 3C). As shown in Figure 3C, differentially expressed genes are mainly enriched in biological processes (BP): humoral immune response, immune response, response to external stimuli, defense response, etc.; and cell component (CC): extracellular space, extracellular region. KEGG pathway enrichment analysis was performed on the genes/transcripts in gene sets using the R script (Figure 3D). When p-adjust < 0.05, the KEGG pathway function was considered significantly enriched. KEGG enrichment analysis showed that the significant enrichment pathways were complement and coagulation cascades, drug metabolism–cytochrome P450 and Tyrosine metabolism. The DEGs were screened again with p-adjust < 0.05, the DEGs were MIF, MANF, FGB, ATF3 and AOX1 (Figure 3E).

3.5. Correlation Analysis

To understand whether there was a correlation between rumen fermentation parameters and the level of rumen bacteria, a Pearson correlation analysis was conducted between the two (Figure 4A). Ruminococcaceae_UCG-014 was negatively correlated with rumen pH (r = −0.866, p < 0.05) and Ruminococcaceae_UCG-014 is negatively correlated with NH3-N (r = −0.854, p < 0.05). Prevotellaceae_UCG_001 was positively correlated with acetic acid (r = 0.935, p < 0.01) and Prevotellaceae_UCG_001 was positively correlated with propionate (r = 0.821, p < 0.05). At the same time, we also performed a correlation analysis of rumen bacteria and DEGs (Figure 4B). Prevotellaceae_UCG-001 is positively correlated with ATF3 (r = 0.693, p < 0.05) and Prevotellaceae_UCG-001 is positively correlated with MIF (r = 0.795, p < 0.01).

4. Discussion

4.1. Effects of AMCB on Serum Immunity Indexes and Rumen Fermentation Parameters of Newborn Calves

GLB synthesized and secreted by plasma cells plays a crucial role in the animal immune system, with its content reflecting the level of non-specific immunity and body resistance [27]. The decrease in serum levels of TP and GLB is primarily due to reduced synthesis, which is associated with underdeveloped liver and immune systems in newborn calves. However, this deficiency can be remedied through AMCB supplementation. IgG, which is secreted by effector B cells in the spleen and lymph nodes, constitutes the main component of immunoglobulins. It plays a crucial role in activating complement, neutralizing multiple toxins and binding antigens during immune responses [28,29]. The observed increase in serum IgG content within the treatment group suggests that the addition of AMCB has a positive effect on immune regulation during anti-infection processes.
It has been reported that adult cows with a rumen pH below 5.5 for a long period of time can be considered as having rumen acidosis [30]. However, rumen acidosis is not clearly defined in calves. Previous studies have shown that the rumen pH of calves is usually lower than 5.8, which may be related to calf feeding concentrate and calves producing less saliva [31,32]. In this study, the pH of rumen calves in the control group was 5.41–5.67 and that in the treatment group was 5.53–6.29, indicating that rumen acidosis existed in both the control group and the treatment group [33,34]. Calves are fed concentrates rich in rapidly fermentable carbohydrates that provide energy for their growth but also result in increased VFA production and a low rumen pH [35]. Prolonged low pH results in cell lysis and the release of toxins that disrupt the structural integrity of the rumen epithelium and the barrier function of the rumen mucosa, which are subsequently absorbed into the bloodstream through the damaged rumen mucosa, leading to immunosuppression and inflammatory responses in animals [30]. At 30 and 45 d, the NH3-N content increased significantly in the treatment group, but at 60 d, the difference decreased. NH3-N can provide a nitrogen source for rumen microbial protein synthesis, and the utilization rate of rumen microorganisms to feed protein increases with the increase in microbial activity [36]. In addition, we also observed that, compared with the control group, the ratio of acetic acid to propionic acid increased at different days of age in the treatment group and significantly increased at 45 d in the treatment group. It has been reported that the low acetic acid to propionic acid ratio reflects that rumen microorganisms can effectively utilize nitrogen to synthesize microbial proteins and grow [37]. However, the effects of AMCB dosage and feeding time on blood indexes and rumen fermentation parameters of calves still need to be further investigated.

4.2. Effects of AMCB on Rumen Microbiota of Newborn Calves

Members of the genus Prevotella play an important role in the degradation of proteins, starches and hemicelluloses [38]. Among them, Prevotella_1 can degrade rumen microbial proteins to produce VFA [39], and significantly increase the concentration of ammonia nitrogen in the rumen of dairy cows [40], which also explains the increase in NH3-N concentration in the treatment group, which may be related to the abundance of Prevotella_1. Ruminococcus_2 can degrade cellulose, hemicellulose and lignin in roughage, produce a large amount of cellulase and xylanase and generate acetic acid through enzyme action [41]. At the same time, Ruminococcus_2 can produce carbohydrate enzymes that degrade carbohydrates in feed, and the specific function of Ruminococcaceae_UCG-014 in the rumen is currently unknown. Lachnospiraceae_NK3A20_group is an important fibrodegrading bacteria and the family is a strictly anaerobic Gram-negative bacterium, which is a semi-fibrous degrading bacterium that can ferment glucose, sucrose, pectin, cellodiosaccharide and fructose, etc., and the products are mainly formic acid, acetic acid, lactic acid and butyric acid [42,43,44]. In this study, the abundance of Ruminococcus_2 and Lachnospiraceae_NK3A20_group was significantly reduced in the 30 d treatment group to alleviate the problem of low rumen pH caused by rapid carbohydrate degradation and excessive acid production. Studies have shown that Olsenella can use oligosaccharides, while Olsenella and an immune checkpoint inhibitor are implanted into germ-free mice, showing that Olsenella can enhance cancer immunotherapy [45]. In this study, the abundance of Olsenella increased significantly in the 30-day treatment group, indicating that the addition of AMCB could improve the utilization rate of oligosaccharides and improve immunity in calves. As a probiotic, Christensenellaceae_R-7_group mainly degrades feed protein and fiber, produces butyric acid and promotes nutrient absorption and rumen development [39,46]. It is significantly negatively correlated with some metabolic diseases and plays an important role in maintaining the structure and function of the animal gastrointestinal tract and animal immune regulation, which is conducive to the maintenance of host health [38,47,48,49]. In this study, the abundance of Christensenellaceae_R-7_group in the treatment group at different age stages was significantly increased, indicating that the addition of AMCB could promote rumen development and improve immune regulation in calves.

4.3. Effects of AMCB on Ruminal Epithelium Transcriptome of Newborn Calves

Through the GO functional annotation analysis, we found that the main differentially expressed genes enriched in the BP and CC pathways were FGB, MIF, ATF3 and MANF. FGB is one of the fibrinogen (FG) gene codes, and the β chain encoded by FGB is the limiting step of FG synthesis [50]. FG is a macromolecular glycoprotein derived from the production of liver cells that is involved in the coagulation process to promote thrombosis and is associated with inflammation [51,52]. MIF acts as a movement inhibitor for macrophages. On the one hand, by inhibiting the movement of macrophages, MIF enables macrophages to gather and infiltrate the inflammatory site and participate in the inflammatory response. On the other hand, it promotes the proliferation of macrophages and stimulates macrophages to secrete interleukin, NO and other cytokines, thus mediating the immune response [53,54]. Transcription activator 3 (ATF3) belongs to the ATF/CREB response element-binding protein family and is an early response gene [55]. At present, studies on the biological functions of ATF3 mainly focus on tumorgenesis, apoptosis, energy metabolism and inflammation [56,57]. MANF is a secreted protein induced by endoplasmic reticulum stress [58]. Under inflammatory stimulation, MANF promotes the localization of MANF in the nucleus, interferes with the binding of p65 and its target gene promoter, inhibits the activation of the NF-κB pathway and thus inhibits the proliferation of inflammatory synoviocytes [59]. Therefore, we speculated that the rumen tissue of calves in this experiment might have inflammation or tissue damage, and the treatment group could significantly upregulate the expression of related genes and enhance rumen immune regulation by adding AMCB.
To verify our hypothesis, KEGG functional annotation analysis was performed on differentially expressed genes, and the results showed that differentially expressed genes were significantly enriched through the following pathways: complement and coagulation cascade, drug metabolism-cytochrome P450 and tyrosine metabolism. In addition, differentially expressed genes were also enriched in the Staphylococcus aureus infection pathway, indicating that rumen tissue inflammation of calves in this study may be caused by S. aureus infection. Complement and coagulation cascades are major effectors of the immune response and triggers of many immunomodulatory mechanisms [60,61]. In addition to enhancing the adaptive immune response, it also plays a fundamental role in innate immunity and is a major line of defense against infection [60]. FGB plays a role in blocking blood vessels and preventing excessive bleeding [62]. In this study, FGB was significantly upregulated in the complement and coagulation cascade pathway. Aldehyde oxidase (AOX1) is a class of proteases that can catalyze the oxidation of aldehydes into corresponding carboxylic acids and release reactive oxygen species (ROS) [63,64]. In this experiment, the AOX1 gene in the treatment group was significantly downregulated in the drug metabolism–cytochrome P450 and tyrosine metabolic pathways to reduce the release of reactive oxygen species. A lower ROS concentration induces intracellular ROS-driven oxidative stress, which stimulates the overexpression of specific genes to produce more functional proteins to protect cells and repair damaged cells [65,66]. MIF also acts as a phenylpyruvate isomerase, which can intermutate phenylpyruvate with the enol and ketone forms of (p-hydroxyphenyl) pyruvate [67,68]. A series of reactions would occur in the small space between the ingested bacteria and the phagosome membrane, and hydroxyl radicals, as the products of the secondary reactions, would have effective antibacterial effects [69]. In this study, MIF is significantly upregulated in the tyrosine metabolic pathway, participating in the tautomerization of 4-hydroxy-phenylpyruvate and 2-hydroxy-3-(4-hydroxy-phenyl)propenoate. Studies have shown that some hydroxyl compounds have antibacterial effects on S. aureus [70,71]. These results suggest that MIF, as phenylpyruvate isomerase, is involved in the rumen tissue antibacterial process in the tyrosine metabolism pathway.

4.4. Correlation Analysis

In this study, Prevotella_1 was the dominant bacterium at different days of age, and its abundance was positively correlated with NH3-N, which was consistent with the studies of Chiquette and Fan [40,72]; however, they were negatively correlated with acetic acid, propionic acid and butyric acid, while Prevotella_9 and Prevotellaceae_UCG_001 were directly proportional to acetic acid, propionic acid and butyric acid. Prevotella_1, Prevotella_9 and Prevotellaceae_UCG_001 are all involved in generating VFA [73] and should be positively correlated. Therefore, we speculate whether it is related to the fact that pyruvate is mainly used as the competitive synthetic substrate during the synthesis of acetic acid, propionic acid and butyric acid [74], but further confirmation is needed. The correlation analysis results of rumen bacteria and DEGs showed that Prevotellaceae_UCG_001 was positively correlated with ATF3 and MIF. There was no significant difference in Prevotellaceae_UCG_001 abundance at 30 and 45 d, but at 60 d, the abundance of Prevotellaceae_UCG_001 increased significantly in the treatment group. Studies have shown that reduced Prevotellaceae_UCG_001 abundance is associated with the development of diarrhea and colitis [75,76], but it is unknown how Prevotellaceae_UCG_001 affects the expression of related genes. In addition, some fiber degrading bacteria and some acid-producing bacteria can also promote rumen immunoregulation, but the relationship between specific bacterial species and immune regulation needs further research and exploration.

5. Conclusions

In this study, AMCB can improve the immunity and rumen pH of newborn calves, and regulate rumen bacterial abundance to intervene in the rumen environment to help rumen maintain homeostasis. In addition, by regulating the expression of FGB, MIF, ATF3, MANF, AOX1 and other related genes in rumen epithelial tissue, rumen immune function was enhanced and rumen health was maintained. This study provides a new idea for the early nutritional regulation of newborn calves with AMCB. The trial’s drawback lies in the inability to accurately determine the extent of rumen AMCB absorption, which is influenced by factors such as calf rearing style and age. Consequently, this impedes the accurate assessment of the nutritional value of AMCB.

Author Contributions

X.W.: conceptualization, methodology, data analysis, investigation and writing—original draft; C.G.: investigation, reviewing and editing; S.L.: reviewing, editing, supervision; W.D.: resources and project administration; D.D.: investigations; L.Z.: writing, supervision, reviewing and editing; X.X.: methodology, resources and project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This study was financially supported by the earmarked fund for CARS36.

Institutional Review Board Statement

All experimental designs and protocols were approved by the Experimental Animal Welfare and Ethics Committee of China Agricultural University (Beijing, China) (Approval number: AW01103202-1-32), and followed the recommendations of the academy’s guidelines for animal research.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in the study are deposited in the NCBI Sequence Read Archive (SRA) database repository, accession number PRJNA937435 (rumen tissue transcriptome), PRJNA972886 (rumen fluid 16s rDNA).

Acknowledgments

Thanks to Ningxia Zerui Ecological Breeding and Animal Husbandry Co., Ltd., Yinchuan, China, for providing the test site and test animals.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Fermentation 09 00973 g001
Figure 1. Effects of AMCB supplementation on rumen microbiota diversity analysis of newborn calves. (A–C) Alpha diversity analysis of rumen microbiota at 30, 45 and 60 d. (D) Beta diversity analysis of rumen microbiota.
Figure 1. Effects of AMCB supplementation on rumen microbiota diversity analysis of newborn calves. (A–C) Alpha diversity analysis of rumen microbiota at 30, 45 and 60 d. (D) Beta diversity analysis of rumen microbiota.
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Fermentation 09 00973 g002
Figure 2. Effects of AMCB supplementation on the rumen microbial phylum level and genus level abundance of newborn calves. (A–C) Phylum level. (D–F) Genus level. * Represents a significant increase in abundance (p < 0.05), * Represents a significant decrease in abundance (p < 0.05). (G–I) Plots of LDA values for significantly different species.
Figure 2. Effects of AMCB supplementation on the rumen microbial phylum level and genus level abundance of newborn calves. (A–C) Phylum level. (D–F) Genus level. * Represents a significant increase in abundance (p < 0.05), * Represents a significant decrease in abundance (p < 0.05). (G–I) Plots of LDA values for significantly different species.
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Fermentation 09 00973 g003
Figure 3. Transcriptome analysis of rumen epithelial tissue. (A) PCA analysis. (B) differentially expressed genes. (C) GO enrichment analysis. (D) KEGG enrichment analysis. (E) DEGs filtered using p–adjust.
Figure 3. Transcriptome analysis of rumen epithelial tissue. (A) PCA analysis. (B) differentially expressed genes. (C) GO enrichment analysis. (D) KEGG enrichment analysis. (E) DEGs filtered using p–adjust.
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Fermentation 09 00973 g004
Figure 4. Correlation analysis. (A) rumen fermentation parameters and rumen bacteria, (B) DEGs and rumen bacteria. r < 0: means negative correlation, r > 0: means positive correlation; * indicates p < 0.05, ** indicates p < 0.01.
Figure 4. Correlation analysis. (A) rumen fermentation parameters and rumen bacteria, (B) DEGs and rumen bacteria. r < 0: means negative correlation, r > 0: means positive correlation; * indicates p < 0.05, ** indicates p < 0.01.
Fermentation 09 00973 g004
Table 1. Nutritional composition of granules.
Table 1. Nutritional composition of granules.
Nutrient ComponentDetection Value %
CP18.18
CF9.12
Ash7.70
Ca0.89
Total P0.56
Water12.5
Ingredients: corn, soybean meal, cotton meal, corn dry alcohol grains, corn germ meal, corn husk, vitamin D3, vitamin A acetate, copper sulfate, manganese sulfate, DL-α-tocopherol acetate.
Table 2. Nutritional composition of milk replacer.
Table 2. Nutritional composition of milk replacer.
Nutrient ComponentDetection Value %
CP22.24
EE17.73
CF0.25
Ash6.67
Ca0.61
Total P0.32
Water5.60
Lactose44.03
Ingredients: Whey protein powder, coconut oil, palm oil, wheat hydrolyzed protein, vitamin A.
Table 3. Nutritional composition of normal milk and feeding milk.
Table 3. Nutritional composition of normal milk and feeding milk.
Nutrient ComponentNormal Milk %Feeding Milk %
CP2.903.25
EE3.503.40
Lactose5.205.30
Total Solid13.3013.65
Note: The mixing ratio of feeding milk is: (milk replacer 1: water 7): normal milk = 1:1. Both the control and treatment groups were fed the feeding milk in Table 3.
Table 4. The composition of alkaline mineral complex buffer concentrate.
Table 4. The composition of alkaline mineral complex buffer concentrate.
IngredientContentChemical Formula
Sodium metasilicate pentahydrate200 g/L5H2O·Na2SiO3
Potassium bicarbonate100 g/LKHCO3
Zinc oxide10 mg/LZnO
Bis-(carboxyethyl germanium) sesquioxide1 mg/LGe-132
Table 5. Effects of AMCB supplementation on serum immunity indexes of newborn calves.
Table 5. Effects of AMCB supplementation on serum immunity indexes of newborn calves.
ItemsGroupSEMp-Value
ConTreGroupTimeGroup × Time
TP (g/L)1 d57.0857.660.9660.783
15 d55.7757.890.4190.002
30 d54.8056.920.6190.084
45 d55.7854.220.5230.145
60 d56.4758.410.4170.0080.0770.302
ALB (g/L)1 d24.6622.940.4920.078
15 d26.6925.800.4550.354
30 d29.7929.460.4170.715
45 d29.0130.050.3950.203
60 d30.4431.340.3900.275<0.0010.009
GLB (g/L)1 d32.4234.721.0780.314
15 d29.0732.100.6950.017
30 d25.0227.470.5530.015
45 d26.7724.170.7100.061
60 d26.0227.070.5550.374<0.0010.006
IgG (mg/mL)1 d20.0220.610.4670.563
15 d19.4220.460.4170.231
30 d20.0920.750.4260.473
45 d21.6823.370.2830.001
60 d21.7423.940.4370.002<0.0010.053
Table 6. Effects of AMCB supplementation on rumen fermentation parameters of newborn calves.
Table 6. Effects of AMCB supplementation on rumen fermentation parameters of newborn calves.
ItemsGroupSEMp-Value
ConTreGroupTimeGroup × Time
pH30 d5.676.290.1340.009
45 d5.475.820.0890.037
60 d5.415.530.0300.039<0.0010.052
NH3-N
(mg/dL)		30 d7.5411.681.0840.047
45 d8.0111.270.8940.063
60 d6.416.770.6410.7960.0140.219
MCP
(mg/mL)		30 d3.363.540.4730.591
45 d2.713.570.4240.345
60 d3.053.150.1610.8760.8740.844
Acetic acid
(mmol/L)		30 d40.7841.431.6590.859
45 d47.5745.792.5940.753
60 d47.6161.916.0900.2630.0650.311
Propionic acid
(mmol/L)		30 d19.9117.051.4830.366
45 d28.5518.772.8190.080
60 d27.3134.393.6840.3670.0120.106
Butyric acid
(mmol/L)		30 d5.914.120.5650.117
45 d8.274.680.9540.052
60 d8.4511.371.2630.2730.0020.046
Acetic/
Propionic		30 d2.092.520.1420.140
45 d1.702.610.2070.016
60 d1.771.840.0890.7290.0280.082
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MDPI and ACS Style

Wang, X.; Guo, C.; Xu, X.; Zhang, L.; Li, S.; Dai, D.; Du, W. Effect of Alkaline Mineral Complex Buffer Supplementation on Rumen Fermentation, Rumen Microbiota and Rumen Epithelial Transcriptome of Newborn Calves. Fermentation 2023, 9, 973. https://doi.org/10.3390/fermentation9110973

AMA Style

Wang X, Guo C, Xu X, Zhang L, Li S, Dai D, Du W. Effect of Alkaline Mineral Complex Buffer Supplementation on Rumen Fermentation, Rumen Microbiota and Rumen Epithelial Transcriptome of Newborn Calves. Fermentation. 2023; 9(11):973. https://doi.org/10.3390/fermentation9110973

Chicago/Turabian Style

Wang, Xiaowei, Cheng Guo, Xiaofeng Xu, Lili Zhang, Shengli Li, Dongwen Dai, and Wen Du. 2023. "Effect of Alkaline Mineral Complex Buffer Supplementation on Rumen Fermentation, Rumen Microbiota and Rumen Epithelial Transcriptome of Newborn Calves" Fermentation 9, no. 11: 973. https://doi.org/10.3390/fermentation9110973

APA Style

Wang, X., Guo, C., Xu, X., Zhang, L., Li, S., Dai, D., & Du, W. (2023). Effect of Alkaline Mineral Complex Buffer Supplementation on Rumen Fermentation, Rumen Microbiota and Rumen Epithelial Transcriptome of Newborn Calves. Fermentation, 9(11), 973. https://doi.org/10.3390/fermentation9110973

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