Abstract

   Pre-weaning is the most important period for the growth and development
   of calves. Intestinal morphology, microbial community and immunity are
   initially constructed at this stage, and even have a lifelong impact on
   calves. Early feeding patterns have a significant impact on
   gastrointestinal development and microbial communities. This study
   mainly analyzed the effects of three feeding methods on the
   gastrointestinal development of calves, and provided a theoretical
   basis for further improving the feeding mode of calves. it is very
   important to develop a suitable feeding mode. In this study, we
   selected nine newborn healthy Holstein bull calves were randomly
   selected and divided into three groups (n = 3), which were fed with
   starter + hay + milk (SH group), starter + milk (SF group), total mixed
   ration + milk (TMR group). After 80 days of feeding Feeding to 80 days
   of age after, the ileum contents and blood samples were collected, and
   the differences were compared and analyzed by metagenomic analysis and
   serum metabolomics analysis. Results show that compared with the other
   two groups, the intestinal epithelium of the SH group was more complete
   and the goblet cells developed better. The feeding method of SH group
   was more conducive to the development of calves, with higher daily gain
   and no pathological inflammatory reaction. The intestinal microbial
   community was more conducive to digestion and absorption, and the
   immunity was stronger. These findings are helpful for us to explore
   better calf feeding patterns. In the next step, we will set up more
   biological replicates to study the deep-seated reasons for the
   differences in the development of pre-weaning calves. At the same time,
   the new discoveries of neuro microbiology broaden our horizons and are
   the focus of our future attention.

   Keywords: calves, feeding patterns, metagenomics, metabolomics, neuro
   microbiology

1. Introduction

   Pre-weaning is the most important period for the growth and development
   of calves. Intestinal morphology, microbial community and immunity are
   initially constructed at this stage, and even have a lifelong impact on
   calves ([41]1, [42]2). The living environment of the calf changed from
   a sterile uterus to the outside world, and the nutritional conditions
   changed from maternal provision to the calf’s own feeding of feed and
   milk. Due to the incomplete development of the immune ability and
   digestive system of calves, newborn calves are very sensitive to
   external stimuli, and any external interference will seriously affect
   the growth of calves ([43]3, [44]4). If the appropriate feeding mode is
   not adopted at this time, it will lead to low daily weight gain,
   diarrhea ([45]5). It is reported that 30% of the deaths of pre-weaning
   cows are caused by diarrhea, which highlights the importance of
   intestinal health ([46]6). The development of the digestive tract of
   calves is a unique process. With the development of the
   gastrointestinal tract and the settlement of the microbial community,
   calves gradually change from pseudo-ruminant animals to functional
   ruminants in physiology. The morphology of intestinal epithelial villi,
   the development of intestinal smooth muscle and rumen volume are
   basically completed at this stage which was ac-companied by the
   development of salivary organs and the development of rumination
   behavior. These factors directly affect the feed intake, nutrient
   absorption rate and digestive ability of calves after weaning ([47]7).

   Studies have shown that early feeding patterns have a significant
   impact on gastrointestinal development and microbial communities.
   Differences in dietary composition and feed physical morphology will
   stimulate intestinal structure development and microbial community
   composition ([48]8–10). For example, alfalfa hay can promote the
   development of intestinal epithelial villi; the feeding of high
   carbohydrate and low fiber feeding will be detrimental to the rumen
   development of calves; additives can directly or indirectly increase
   the proportion of probiotics ([49]11–13). Research shows that
   intestinal microbial community can be directed to change, adjusting
   feeding patterns can help animals form beneficial microbial communities
   before weaning ([50]14). This can not only promote the development of
   calf digestive ability, but also is indispensable for the development
   of intestinal immune function. Deng’s research on giant pandas has
   proved that Streptococcus alactolyticus can promote the dietary
   adaptation of giant pandas by participating in protein metabolism
   ([51]15). Recent studies have also found that microbial communities
   also communicate biological information with the nervous system, it
   points to a new field: neuro microbiology, this further illustrates the
   huge impact of gut microbes on the host ([52]16).

   There is no fixed feeding mode for newborn calves. Appropriate feeding
   mode should be comprehensively formulated according to their
   nutritional needs, breed characteristics, feeding plan and other
   factors ([53]17). For calves at this stage, growth is important, but
   more importantly, the healthy development of the digestive system based
   on the gastrointestinal tract. This will have a long-term impact on the
   subsequent growth and production of calves ([54]18, [55]19). Therefore,
   it is very important to develop a suitable feeding mode. In this study,
   three different feeding modes were used to explore the effects of
   different feeding modes on the growth and development of ileum and
   blood metabolism of calves from the perspective of metagenomics and
   metabolomics. The relationship between intestinal development,
   digestive function and microbial community composition was explored to
   provide a theoretical basis for further improving the feeding pattern
   of calves. At the same time, it inspired us to explore the relationship
   between intestinal microorganisms and the nervous system from a new
   perspective of neurobiology.

2. Materials and methods

2.1. Ethics statement

   This study was approved and conducted in accordance with the ethical
   standards of the Institutional Animal Care and Use Committee of the
   College of Animal Science and Technology, Sichuan Agricultural
   University, Sichuan, 611130, China.

2.2. Animals and feeding management

   Nine 7-day-old healthy male Holstein calves with a body weight of about
   41.6 kg (standard deviation = 0.563) and similar physical condition
   were selected. Raised in Sichuan Xuebao Dairy Group HonSFeng cattle
   farm. Nine calves were randomly divided into three groups, SH group:
   starter feed + hay + milk, SF group: starter feed + milk, TMR group:
   total mixed ration + milk. The feed composition and nutrient
   composition of the starter feed are shown in [56]Table 1. The hay in
   the SH group was composed of alfalfa and oat grass in a ratio of 3:2,
   cut into 1.5 cm long, mixed with starter and fed. TMR feed (starter:
   alfalfa: oat grass: water = 0.30: 0.12: 0.08: 0.50), the starter was
   crushed into powder, the hay was cut to about 1 cm, and mixed with
   water to paste. Other feeding and management methods were carried out
   according to the existing methods of cattle farms, and calves were free
   to feed and drink water during the experimental period. Continuous
   feeding to 80 days of age, using electric shock bloodletting method to
   slaughter and record the slaughter weight.

Table 1.

   The feed composition and nutrient composition of the starter feed.
   Component            Proportion (%)
   Corn                     61.16
   Soybean meal             30.05
   Compound vitamins         0.03
   Trace elements            0.4
   CaHCO3                    0.67
   CaCO3                     1.65
   50% choline chloride      0.1
   Soybean oil               4.02
   L-lysine                  0.11
   DL-methionine             0.43
   Mineral additives         1.39
   Nutritional ingredient
   NE,Mcal/kg                8.49
   CP                       17.73
   Ca                        3.10
   Available phosphorus      0.79
   Lys                       0.99
   Met                        0
   [57]Open in a new tab

2.3. Serum sample collection and partial physiological index detection

   After the calves were fasted for 24 h, the external jugular vein blood
   collection method was adopted (June 10, 2022), and 5 mL blood
   collection vessels (EDTAK2, Jiangsu Kangjian Medical Device Co., Ltd.,
   Nanjing, China) were used to collect some calf blood, and heparin
   sodium was used for anticoagulation. Some blood samples were taken to
   determine blood routine indexes such as red blood cell count and white
   blood cell count (Chengdu Li Lai Biotechnology Co., Ltd., Chengdu). The
   blood samples were centrifuged at 4°C, 3000 r / min for 5 min to obtain
   the upper serum. Some serum samples were sent to Novogene
   Bioinformatics Technology Co., Ltd. (Beijing, China) for metabolomics
   analysis, and then some serum samples were selected to determine
   digestive and immune indexes such as α-amylase (C016-1-1), lysozyme
   (A050-1-1) and trypsin (A080-2; the kits were provided by Nanjing
   Jiancheng Bioengineering Institute).

2.4. Ileum morphological section analysis and sample collection

   Slaughter of calves by electric bloodletting. The calves get up in the
   morning, use electric shock anesthesia after fasting blood collection,
   and then slaughter by carotid artery bloodletting. After slaughter, the
   contents of the ileum of the calf were quickly placed in a 2 mL frozen
   tube and stored in liquid nitrogen at −80°C. The unsealed ileum tissue
   was collected and fixed with 10% neutral formaldehyde solution. After
   dehydration, pruning, embedding, slicing, staining with hematoxylin and
   eosin (HE), sealing and other steps, the Pannoramic 250 digital slice
   scanner produced by Hungary 3DHISTECH company was used to collect
   images of the slices.

2.5. Microbial metagenomic sequencing and functional annotation analysis

   According to the Tiangen Magnetic Bead Kit (Tiangen Biotech, Beijing,
   China) instructions, microbial DNA was extracted from ileum content
   samples, and the purity and integrity of DNA were detected by agarose
   gel electrophoresis. The qualified DNA samples were broken into
   fragments of about 350 bp by ultrasonic crushing instrument. After
   repair, purification, PCR amplification and other steps, the
   preliminary database was completed. Qubit2.0 was used for
   quantification, and then NEBNext ® Ultra DNA Library Prep Kit for
   Illumina (NEB, USA) was used to construct a metagenomic library and
   sequenced on the Illumina HiSeq Xten platform. The library construction
   and sequencing work was completed by Novogene Bioinformatics Technology
   Co., Ltd. (Beijing, China). The clean date was obtained by filtering
   the raw date obtained by sequencing, and the clean date of each sample
   was assembled and analyzed by MEGAHIT software ([58]20, [59]21)
   (v1.0.4-beta[60]^1). Then MetaGeneMark software ([61]22) (V2.10[62]^2)
   was used for gene prediction, and the genes predicted by each sample
   were put together to construct gene catalogue. Starting from the gene
   catalogue, the clean data of each sample was synthesized to obtain
   unigenes for subsequent analysis ([63]23).

   The obtained unigenes were compared with the NCBI’s NR database
   ([64]24) (Version 2018-01-02[65]^3) to determine the species annotation
   information of each unigenes. Combined with the gene abundance table,
   the abundance information of each sample in phylum, genus and species
   was obtained. PCA ([66]25) (RADE4 package, version 2.15.3) and LEfSe
   ([67]26) (LDA score default to 3) analysis were used to compare the
   different species between groups. Finally, unigenes were compared with
   KEGG database ([68]27, [69]28) (version 2018-01-01[70]^4), CAZy
   database ([71]29) (version 201,801[72]^5) and eggNOG database ([73]30)
   (version 4.5[74]^6) to obtain the relative abundance and functional
   annotation differences between groups ([75]31).

2.6. Serum metabolomics analysis

   The metabolites in the ileum were studied based on LC–MS technology.
   After preliminary treatment, the supernatant was injected into the
   ultra-performance liquid chromatography–tandem mass spectrometry
   (UHPLC–MS/MS) system for analysis ([76]32). Firstly, the raw data of
   mass spectrometry were imported into Compound discoverer 3.1 software
   for spectral processing and database retrieval, and the qualitative and
   quantitative results of metabolites were obtained. Then, the quality of
   data was controlled to ensure the accuracy and reliability of the data.
   Using high-resolution mass spectrometry (HRMS) technology, we can make
   the non-target metabolic group as much as possible to detect the
   molecular characteristic peaks in the sample. The raw data after
   offline is preprocessed by CD3.1 data processing software. In order to
   make the identification accurate, we extract the peaks according to the
   set of ppm, signal-to-noise ratio (S/N), additive ions, and other
   information and quantify the peak area. Then mzCloud, mzVault, and
   MassList databases were compared to identify metabolites. Finally,
   metabolites with a coefficient of variation of less than 30% in QC
   samples were retained as the final result. The metabolites were
   compared with KEGG, HMDB, and other databases to obtain the annotation
   results. Then, a multivariate statistical analysis of metabolites was
   performed, including principal component analysis (PCA), partial least
   squares discriminant analysis (PLS-DA) to establish the relationship
   between the expression of metabolites and samples ([77]33). According
   to the results of Q2 and R2, the model was judged to reveal the
   differences in metabolic patterns between different groups. KEGG
   enrichment pathway analysis was performed on the differential
   metabolites to obtain clearer and more detailed differential analysis
   results.

3. Results

3.1. HE staining section of ileum tissue

   The results of HE staining are shown in [78]Figure 1. Compared with the
   other two groups, the epithelial villi in the SH group were relatively
   complete, the intestinal epithelial villi were high and well developed,
   the goblet cells were closely arranged, and some inflammatory cells
   were seen in the lamina propria. There were a large number of
   epithelial mucosal shedding in the SF group, and the inflammatory cells
   in the lamina propria were also more than those in the SH group,
   accompanied by congestion; the mucosal integrity of the TMR group was
   the worst, accompanied by inflammatory cells and congestion, and even
   obvious parasitic infection was observed in some sections.

Figure 1.

   [79]Figure 1
   [80]Open in a new tab

   Hematoxylin and eosin (100×) -stained ileal tissue samples of Holstein
   calves fed different diets. (A) SH group; (B) SF group; (C) TMR group.
   Red circle marked mucosal epithelial shedding; the orange circle marked
   congestion; green circle marked as parasitic lesions.

3.2. Daily weight gain and some physiological indexes test results

   In this experiment, 9 newborn, healthy and healthy male calves with no
   significant difference in birth weight were selected. The birth weight
   was about 41 kg. When the calves were slaughtered at 80 days of age,
   there were significant differences in weight among the three groups
   (p = 0.002). The average weight of SH group and SF group TMR group was
   100.62 ± 1.94, 100.07 ± 1.92 and 90.77 ± 2.42. And the daily weight
   gain was 0.745 kg / day, 0.740 kg / day and 0.604 kg / day,
   respectively.

   In [81]Figure 2, some blood routine data. The results showed that the
   number of white blood cells SH was significantly less than that of SF
   group and TMR group, which may be due to the more severe inflammatory
   response in SF group and TMR group. The number of red blood cells in
   the TMR group was the highest. The hemoglobin content in the TMR group
   was also the highest in the three groups. The results of digestive
   enzymes and immunity showed that the contents of amylase, trypsin and
   lysozyme in SH were the highest in the three groups. The IgG content of
   SH group was also the highest in the three groups. These indicators
   show that the digestive ability and immune ability of SH group are
   higher than the other two groups.

Figure 2.

   [82]Figure 2
   [83]Open in a new tab

   Some physiological indexes test results. (A–D) It’s blood routine
   determination results. (E–H) It’s digestive enzyme and immunoassay
   results.

3.3. Ileum microbial metagenomic data processing

   As shown in [84]Table 2, a total of 112,964.83 raw data were measured
   in 9 samples, and 112,791.07 clean data were obtained after Illumina
   pretreatment and filtering, with an average CG content of 45.87% and an
   effective value of more than 99.85%. The average length of scaftigs of
   9 samples was 1434.85.

Table 2.

   Preprocessing of sequencing data.
   Sample ID Raw date Clean date Clean_GC(%) Effective (%) Total Len. Num
   Average Len.
   SH 12,203.11 12,190.28 50.27 99.895 161,322,099 112,565 1,433.15
   12,496.78 12,475.11 47.34 99.827 217,508,616 134,445 1,617.83
   12,651.70 12,609.24 43.09 99.664 153,544,642 102,299 1,500.94
   SF 12,451.10 12,439.42 50.13 99.906 156,100,365 94,575 1,650.55
   12,084.00 12,062.04 47.41 99.818 1,778,426 2,347 757.74
   12,573.19 12,546.90 38.51 99.791 177,806,423 124,453 1,428.70
   TMR 13,345.45 13,323.13 44.12 99.833 344,856,565 217,392 1,586.34
   12,432.55 12,423.68 50.65 99.929 297,219,715 189,565 1,567.90
   12,726.95 12,721.27 41.27 99.955 177,848,979 129,771 1,370.48
   [85]Open in a new tab

3.4. Analysis of correlation between groups and differences in microbial
community

   Based on the number of genes, correlation analysis was performed on 8
   samples. The results are shown in [86]Figure 3. The correlation between
   SF group and SH group was high, but the correlation between TMR group
   and SF group and SH group was low.

Figure 3.

   [87]Figure 3
   [88]Open in a new tab

   Correlation analysis between groups of samples.

   The processed genes were compared with the database to obtain the
   species annotation information of each sequence and compared after
   classification at each level. The results are shown in [89]Figure 4.
   The dominant bacteria in the three groups were Firmicutes under the
   phylum level classification. The subdominant bacteria in group SF were
   Proteobacteria and Chlamydiae. The subdominant flora in SH group was
   Actinobacteria, more than the other two groups. The subdominant flora
   in the TMR group was Proteobacteria. Under the genus level
   classification, the dominant flora of group SF was Clostridium and
   Chlamydia; the dominant flora in SH group was Olsenella, which was more
   than that in TMR group and SF group, and the secondary dominant flora
   was Clostridium. The dominant flora in the TMR group was Clostridium
   secondary dominant flora Sarcina and more than that in the SF and SH
   groups.

Figure 4.

   [90]Figure 4
   [91]Open in a new tab

   Analysis of microbial community differences between groups. (A)
   Relative abundance of species at phylum level TOP10. (B) Relative
   abundance of genus level species TOP10. (C) Phylum level species PCA
   analysis. (D) PCA analysis of genus-level species.

   The results of PCA analysis showed that under the classification of
   phylum level and genus level, the intra-group difference of SH group
   was the smallest, the intra-group difference of SF group was slightly
   larger than that of SH group, and the intra-group difference of TMR
   group was the largest. There were significant differences among the
   three groups, and the intra-group difference of TMR was greater than
   the inter-group difference, which indicate that after feeding the total
   mixture, the ileum microbes of calves were greatly different. In order
   to screen species with significant differences between groups, the
   results of LDA analysis ([92]Figure 5) showed that the main differences
   between SH group and TMR group were p _ Firmicutes and o _
   Mycoplasmatales in SH group and p _ Sarcina in TMR group. The main
   differential flora between SF group and TMR group were o _
   Veillonellaceae, g _ Prevotella in SF group and p _ Sarcina in TMR
   group.

Figure 5.

   [93]Figure 5
   [94]Open in a new tab

   LDA score of LEfSe-PICRUSt. (A) LDA score analysis diagram of different
   species between SH group and TMR group. (B) LDA score analysis diagram
   of different species between SF group and TMR group.

3.5. Functional analysis of differential species

   The relative abundance of KEGG pathway enrichment in the three groups
   was analyzed ([95]Figure 6). It was found that among the 45 pathways
   under the second level classification, the SH group was mainly enriched
   in carbohydrate metabolism, followed by amino acid metabolism,
   translation and membrane transport; the dominant pathways in the TMR
   group were carbohydrate metabolism and amino acid metabolism. It is
   worth noting that the TMR group was enriched in cell growth and death
   and drug resistance: antimicrobial pathway higher than SH group and SF
   group. These genes were further compared in the metabolic pathways of
   the third level, and were enriched in 302 pathways. The three groups
   all enriched more genes in ABC transporters (pathway ID: ko 02010),
   ribosome (pathway ID: ko03010), purine metabolism (pathway ID: ko
   00230) and pyrimidine metabolism (pathway ID: ko00240), but the SF
   group was more and the TMR group was the least. Interestingly, the
   number of genes enriched in Cell cycle-Caulobacter (pathway ID:
   ko04112), necroptosis (pathway ID: ko04217) and other pathways under
   the classification of cell growth and death pathway was the least in SH
   group, and more in TMR group and SF group. The Cationic antimicrobial
   peptide (CAMP) resistance (pathway ID: ko01503) under the Drug
   resistance: Antimicrobial classification was similar.

Figure 6.

   [96]Figure 6
   [97]Open in a new tab

   KEGG pathway enrichment analysis. (A) KEGG level 2 enrichment analysis
   top 10 between groups. (B) KEGG level 3 enrichment analysis top 10
   between groups.

   The results of EggNOG analysis ([98]Figure 7) showed that the most
   abundant genes were enriched in Replication, recombination and repair,
   followed by Amino acid transport and metabolism and Translation,
   ribosomal structure and biogenesis. After comparing the relative
   abundance of genes annotated in eggNOG in the three groups, it was
   found that the main enrichment pathways of the three groups were
   similar, with the most in SF group and the least in TMR group. The
   relative abundance of secondary metabolites biosynthesis, transport and
   catabolism, Cell motility and RNA processing and modification in TMR
   group was higher than that in the other two groups.

Figure 7.

   [99]Figure 7
   [100]Open in a new tab

   EggNOG enrichment analysis.

   After comparing the relative abundance of CAZy genes in the three
   groups ([101]Figure 8), it was found that Glycoside Hydrolases (GH)
   were the main ones, and there were differences in CAZy family under the
   second level classification. The CAZy family of SH group was more
   evenly distributed, and the most enriched families were GT2 family and
   GH1 family, among which GH1, GH3 and GH25 family were higher than the
   other two groups. GH19, GT2 and GH13 family were more enriched in group
   SF than in the other two groups. There were more GH19, GH24 and GT2
   family in TMR group, and GH24 was more than the other two groups. The
   CAZy families that attract our attention are GH1 and GH19. The
   differences between the three groups are also mainly reflected in these
   two families. The enrichment of GH1 in SH group was more than that in
   SF group and TMR group, mainly due to the β-glucosidase (EC 3.2.1.21)
   of GH1 family under level 3 classification. GH19 was more enriched in
   SF group and TMR group than in SH group, mainly chitinase (EC 3.2.1.14)
   of GH19 family under level 3 classification.

Figure 8.

   Figure 8
   [102]Open in a new tab

   CAZy enrichment analysis top 10 between groups.

3.6. Analysis of serum differential metabolites

   After analyzing the blood metabolites of the three groups, a total of
   403 cathode metabolites were found. PLS-DA analysis ([103]Figure 9) of
   these metabolites between groups showed that the separation between
   groups was obvious, the degree of polymerization in the group was high,
   and the model parameters of each group also met the standard,
   indicating that the results were stable and reliable. Further analysis
   and screening of differential metabolites ([104]Table 3) showed that
   there were 87 differential metabolites in the cathode of SF group and
   SH group, 17 were significantly up-regulated and 70 were significantly
   down-regulated. There were 152 differential metabolites in the cathode
   of SF group and TMR group, 27 were significantly up-regulated and 125
   were significantly down-regulated. There were 108 differential
   metabolites in the cathode of SH group and TMR group, 26 were
   significantly up-regulated and 82 were significantly down-regulated.

Figure 9.

   [105]Figure 9
   [106]Open in a new tab

   PLS-DA analysis of serum metabolites between groups. (A) PLS-DA
   analysis of SF group and SH group; (B) PLS-DA analysis of SF group and
   TMR group; (C) PLS-DA analysis of SH group and TMR group.

Table 3.

   Number of differential metabolites in serum.
   Compared samples N total identified N Signif. different N Signif. up N
   Signif. down
   SF vs. SH 403 87 17 90
   SF vs. TMR 403 108 26 82
   SH vs. TMR 403 152 27 125
   [107]Open in a new tab

   N Total Identified, Total number of differential metabolites. N Signif.
   Different, Number of significant differential metabolites. N Signif.
   Up, Number of significantly higher metabolite contents. N Signif. Down,
   Number of significantly lower metabolite.

3.7. KEGG enrichment analysis of differential metabolites

   The selected differential metabolites were subjected to KEGG enrichment
   analysis to determine the effects of differential metabolites on key
   blood metabolic pathways. The results showed that the differential
   metabolites between SF group and SH group were mainly enriched in
   cortisol synthesis and secretion (value of p = 0.032). The differential
   metabolites between SF group and TMR group were mainly enriched in cAMP
   signaling pathway (value of p = 0.043), dopaminergic synapse (value of
   p = 0.043), Taste transduction (value of p = 0.043). The differential
   metabolites between SH group and TMR group were mainly enriched in cAMP
   signaling pathway (value of p = 0.024), dopaminergic synapse (value of
   p = 0.024), taste transduction (value of p = 0.024), tyrosine
   metabolism (value of p = 0.046). The specific pathway information and
   differential metabolites enriched in the pathway are shown in the
   [108]Table 4.

Table 4.

   KEGG enrichment analysis results of differential metabolites.
   Map ID Map title Value of p N Meta IDs
   SF vs. SH map04927 Cortisol synthesis and secretion 0.03241 81
   Pregnenolone^##; Cortodoxone**
   map04934 Cushing’s syndrome 0.03241 81 Pregnenolone^##; Cortodoxone**
   map00140 Steroid hormone biosynthesis 0.04173 81 Pregnenolone^##;
   Androsterone glucuronide*; Cortodoxone**
   SF vs. TMR map04024 cAMP signaling pathway 0.04283 81 Dopamine^##;
   Noradrenaline^##; Adenosine 5′-monophosphate^##
   map04728 Dopaminergic synapse 0.04283 81 Dopamine^##; Levodopa^##;
   3-Methoxytyramine^##
   map04742 Taste transduction 0.04283 81 Noradrenaline^##; Saccharin**;
   Adenosine 5′-monophosphate^#
   SH vs. TMR map04024 cAMP signaling pathway 0.02372 81 Dopamine^##;
   Noradrenaline^##; Adenosine 5′-monophosphate^#
   map04728 Dopaminergic synapse 0.02372 81 Dopamine^##; Levodopa^##;
   3-Methoxytyramine^#
   map04742 Taste transduction 0.02372 81 Noradrenaline^##; Saccharin**;
   Adenosine 5′-monophosphate^#
   map00350 Tyrosine metabolism 0.04598 81 Dopamine^##; Levodopa^##;
   Noradrenaline^##; Tyrosol**; 3-Methoxytyramine^#
   [109]Open in a new tab

   In the Meta IDs annotation, ^# represents a significant
   down-regulation, ^## represents a significant down-regulation, ^*
   represents a significant up-regulation, ^** represents a significant
   up-regulation.

4. Discussion

   The ileum is located in the posterior part of the small intestine and
   is the main place for digestion and absorption of nutrients. Therefore,
   the development of ileal function is essential for the health and
   growth of calves. We observed from the sections after HE staining that
   the intestinal epithelial villi in the SF and SH groups were better
   developed, the villus height was higher, and the goblet cells in the
   villi were more closely arranged. The goblet cells can secrete mucus
   and form a physical barrier on the surface of the intestinal mucosa,
   which is the main component of the intestinal barrier ([110]34). These
   characteristics mean that the ileum of SF group and SH group has a
   larger absorption and digestion area, and the intestinal morphology is
   more conducive to the absorption of nutrients, and has a stronger
   barrier function, which is the characteristic of healthy development of
   calf intestine, which is conducive to the development of digestive
   ability and gastrointestinal health of calves ([111]35, [112]36). The
   research of Ma showed that the intestinal tract of calves must undergo
   development, physical and physiological changes, before they can better
   adapt to the transition from milk to solid feed ([113]37). Studies have
   shown that the healthy development of intestinal epithelial environment
   is conducive to the development of intestinal probiotics and the
   stability of microbial communities ([114]38). We observed a more
   obvious inflammatory response in the TMR group, and the intestinal wall
   in the SH group was relatively complete. After subsequent analysis, we
   believe that it may be due to the digestive ability of calves and
   maturity, which cannot adapt to the inflammatory response caused by TMR
   feed. The parasite phenomenon may be caused by the invasion of
   pathogens. Whether it is related to the total mixed feed needs further
   study.

   Metagenomic analysis compared the microbial community differences among
   the three groups. The results showed that SH group was enriched in
   Actinobacteria and more than the other two groups. In previous studies,
   except for a small number of pathogenic bacteria, Actinobacteria is
   usually a probiotic that is conducive to the digestion and absorption
   of organic matter. In some farms, probiotics are used to selectively
   stimulate the growth of Actinobacteria ([115]39). Moreover,
   Actinobacteria can also produce secondary metabolites such as natural
   drugs, enzymes, and active factors, and is considered to be a potential
   probiotic ([116]40). Bifidobacterium under the classification of
   Actinobacteria plays an important role in regulating the immune system
   and preventing intestinal diseases. It can reduce the inflammatory
   response by producing short-chain fatty acids and regulating
   inflammatory factors. The proliferation of Actinobacteria may be the
   key to regulating immunity and reducing inflammatory response in SH
   group. Some studies have shown that Actinobacteria also plays a role in
   reducing pathogens such as Escherichia-Shigella, indicating that it can
   also have a positive effect on preventing diarrhea ([117]41). Olsenella
   has obvious advantages in SH enrichment. Olsenella belongs to
   probiotics under the classification of lactic acid bacteria. Studies
   have shown that Olsenella is positively correlated with butyrate.
   Butyrate is one of the main volatile fatty acids produced by rumen
   fermentation, and ileum is also the main part of absorbing butyrate.
   Butyrate can provide energy for Olsenella and can strengthen the
   intestinal barrier function, which is conducive to intestinal health
   ([118]42). The study of Zhang also showed that individuals with higher
   relative abundance of Olsenella have a stronger ability to produce
   short-chain fatty acids, which can effectively affect the structure of
   the intestinal epithelial mucus layer, stimulate the development of
   intestinal epithelial tissue, nourish the development of intestinal
   epithelial cells such as goblet cells, and reduce the risk of
   inflammatory bowel disease in individuals ([119]43).

   The dominant bacteria in the SF group were Chlamydiae and
   Proteobacteria. Chlamydiae is a pathogen that may cause enteritis
   ([120]44, [121]45), but no diarrhea symptoms were found in this
   individual, and there may be a case of invisible infection of
   Chlamydiae ([122]46). At the same time, other pathogens with high
   correlation with Chlamydiae, such as Campylobacter, were not found.
   Chlamydiae, as a potential pathogen, may be related to the local
   inflammation observed in the SF group, which may lead to impaired
   intestinal absorption and induce other diseases ([123]47). Timely
   treatment is needed. The study of Xia in weaned piglets showed that the
   addition of plant essential oils containing substances such as
   tributyrin to the feed can resist Chlamydia, regulate microbial
   morphology, and improve intestinal villus morphology ([124]48).

   Proteobacteria in both TMR group and SF group have high abundance.
   Previous studies have shown that many intestinal pathogenic bacteria
   belong to Proteobacteria, and the relative abundance of Proteobacteria
   is too high, which may cause inflammation and cause calf diarrhea
   ([125]49, [126]50). Shin used the enrichment of Proteobacteria as one
   of the important markers of intestinal microflora imbalance in healthy
   individuals. In general, Proteobacteria will not be significantly
   enriched in healthy individuals ([127]51). The study of Han on weaned
   piglets showed that Proteobacteria could activate inflammation-related
   cytokines and cause intestinal inflammation damage. At the same time,
   the daily weight gain of piglets with enrichment of Proteobacteria was
   significantly reduced, which indicated that the intestinal nutrition
   absorption function was also affected ([128]52). The study of Varada on
   newborn buffaloes found that feeding probiotics can regulate the
   composition of intestinal microbial communities by reducing the
   abundance of Proteobacteria ([129]53). Numerous studies have shown that
   the enrichment of Proteobacteria can lead to inflammatory response and
   cause intestinal epithelial cell dysfunction ([130]54, [131]55). This
   may be one of the reasons why the TMR group had a large number of
   inflammatory cell infiltration, intestinal epithelial cell shedding,
   and even diarrhea symptoms. Sarcina enriched in TMR is a pathogen that
   has been reported many times. Katharine found that Sarcina was
   associated with gastric ulcer and fungal infection in calves and goats,
   which may be the cause of gastritis and enteritis ([132]56). The study
   of Simpson also found that Sarcina may cause necrosis of the intestinal
   epithelial surface and may be related to parasitic infection ([133]57).
   Many studies have pointed out that Sarcina is associated with diarrhea,
   inflammation and other symptoms. Sarcina is significantly enriched in
   the intestinal tract of horses parasitized by ascaris, and Sarcina is
   often found in goats, rabbits and other animals with diarrhea symptoms
   or fungal infection ([134]58, [135]59). The study of Zhuo on piglets
   directly pointed out that the enrichment of Sarcina is not conducive to
   the healthy development of the intestinal tract, affects the production
   performance and feed absorption rate, and increases the probability of
   intestinal pathogen infection. They also pointed out that Sarcina has a
   great relationship with the reduction of microorganisms that produce
   short-chain fatty acids and feeding patterns ([136]60). This is similar
   to our findings. Therefore, we believe that the inflammatory response,
   parasitic infection and diarrhea symptoms in the TMR group are closely
   related to Sarcina.

   After comparing the enrichment of KEGG signaling pathway, we found that
   in Cell cycle-Caulobacter (pathway ID: ko04112) and Necroptosis
   (pathway ID: ko04217) signaling pathways, SH group was less, SF group
   and TMR group were more. Cell cycle-Caulobacter is a key pathway that
   can regulate DNA replication, cell cycle and cell topology. Cell cycle
   response regulator is the core of his network. Cell cycle-Caulobacter
   regulates the asymmetric division of bacterial cells, resulting in
   stalked cells and swarmer cells with different fates ([137]61). The
   stalked type of progeny cell type will enter the S phase, while the
   swarmer type will remain in the G1 phase ([138]62). We compared the
   metabolites annotated in the three groups, and found that the unique
   metabolites in the SF group and the TMR group eventually pointed to
   polar morphogenesis and pili biogenesis, while the unique metabolites
   in the SH group pointed to flagellar ejection holdfast biogenesis,
   stalk formation, that is, the cells in the SF group, TMR group and SH
   group went to different divisions, and different daughter cells had
   different cell membrane structures and cell morphology. This leads to
   differences in subsequent functions ([139]63, [140]64). Studies have
   shown that phages with pili and flagella structures are more
   susceptible to the host through CtrA regulation ([141]65). This
   molecular network regulation has a direct relationship with bacterial
   infection. McAdams ‘s study pointed out that the function within the
   Cell cycle-Caulobacter network is conserved, but after asymmetric
   division, due to differences in cell function and protein, downstream
   specific coupling species will be very different ([142]66). Therefore,
   we boldly speculate that the Cell cycle-Caulobacter pathway in the SH
   group is not as active as the other two groups, and the final cell
   division results are different, which may be one of the important
   reasons for the differences in bacterial infection and inflammatory
   response between the SH group and the TMR group and the SF group. The
   difference in Necroptosis is clearer. SH has no unique metabolites,
   while the unique metabolites of SH group and TMR group are the same,
   which are H2AX, VDAC, Drp1, ESCRT-III. These metabolites directly or
   indirectly point to inflammatory response, mitochondrial damage, etc.,
   and their activity may lead to cell damage, and ultimately necroptosis
   ([143]67). Yi’s study found that plasma pathogens such as
   Staphylococcus aureus can lead to cell necroptosis by affecting
   mitochondrial membrane potential and membrane permeability. This
   necroptosis is regulated by calmodulin-dependent protein kinase II
   (CaMKII) and mixed lineage kinase domain-like (MLKL) ([144]68). The
   unique metabolites we found in TMR group and SF group were involved in
   the above reaction process. Huang’s study also pointed out that
   activation of MLKL and CaMKII can lead to mitochondrial dysfunction and
   pro-inflammatory response ([145]69). We also found that the unique
   metabolites of TMR group and SF group were concentrated in cytochrome c
   oxidase \ reductase after comparing the Oxidative phosphorylation
   (pathway ID: ko00190) of the three groups. We believe that this may be
   due to bacterial infection that activates pathways such as MLKL, which
   leads to necroptosis caused by mitochondrial dysfunction and promotes
   inflammatory response, and ultimately leads to damage to intestinal
   epithelial structure ([146]70). In addition, intestinal flora may also
   interact with metabolic intermediates in Oxidative phosphorylation.
   Existing studies have found that NAD (nicotinamide adenine
   dinucleotide) can promote the secretion of intestinal mucin 2 (MUC2),
   enhance the ability of antibacterial infection, and alleviate
   intestinal inflammation by inhibiting NF-kB. Oxidative phosphorylation
   abnormalities and mitochondrial damage are likely to affect the levels
   of metabolites such as NAD, increasing the risk of intestinal
   inflammation and bacterial infection ([147]71).

   In the two signaling pathways of Purine metabolism (pathway ID: ko
   00230) and Pyrimidine metabolism (pathway ID: ko00240), the three
   groups have more enrichment, but their metabolic process is different.
   As shown in [148]Figure 10, some of the reactions in the TMR and SF
   groups were more active than SH in these two pathways, including
   several key enzymes that catalyze one-way reactions, such as apyrase
   (EC: 3.6.1.5) and AMP deaminase (EC: 3.5.4.6), which are unique to the
   SF and TMR groups. Studies have shown that when the body is in an
   inflammatory or stress state, the demand for nucleotides will increase
   to promote intestinal cell proliferation and tissue repair ([149]72,
   [150]73). The activity of apyrase (EC: 3.6.1.5) will lead to excessive
   metabolic intermediates such as GMP and AMP. Their final products all
   point to uric acid, but the enzyme for the next metabolism of uric acid
   is not active. Although nucleotide metabolism in the SF and TMR groups
   may be an autonomous repair of inflammation, it also increases the risk
   of accumulation of substances such as uric acid. In general, purine
   catabolism produces metabolites with potential toxicity ([151]74,
   [152]75). Excessive accumulation of uric acid may lead to the formation
   of sodium salt deposition in shutdown, skin and other parts, causing
   pain. It may also cause kidney damage and lead to the occurrence of
   uric acidemia, which is common in long-term high protein intake of
   livestock and poultry ([153]76, [154]77); in serious cases, it may also
   lead to atherosclerosis ([155]78). Apyrase is involved in the
   dephosphorylation of GTP, ATP, UTP, CTP and other substances, and is a
   one-way reaction. ATP, GTP and ITP were dephosphorylated to produce
   Uric acid. UTP and CTP were also dephosphorylated to produce Uracil,
   which was converted into β-Alanine to participate in the next reaction.
   After dephosphorylation, dTTP is dephosphorylated to generate dTMP,
   which will further generate Thymine, and then generate
   (R)-3-Amino-2-methylpropanoate to participate in Valine, leucine and
   isoleucine degradation pathway. Therefore, we inferred that the
   Nucleotide metabolism of the three groups was more enriched because the
   intestine of the calves was in the developmental stage, and the
   metabolism was vigorous because it responded to stimuli such as feed
   differences and microbial flora changes. However, the SF group and the
   SH group showed uniqueness in some metabolic processes due to the need
   for anti-inflammatory and epithelial cell repair. The activity of
   enzymes such as apyrase (EC: 3.6.1.5), and the enzymes not annotated to
   uric acid catabolism may lead to the risk of uric acid accumulation in
   the SF group and the TMR group.

Figure 10.

   [156]Figure 10
   [157]Open in a new tab

   Differences in purine metabolic pathways between groups. The black box
   is marked as the intermediate product in the purine metabolic pathway.
   The black arrow is marked with enzymes annotated in the kegg enzyme
   database. The red-labeled enzyme is unique in SF and TMR.

   By comparing the analysis results of the three groups of CAZy
   databases. The differences are mainly reflected in the GH1 family and
   the GH19 family. Under level 3 classification, the enrichment of
   β-glucosidase (EC 3.2.1.21) belonging to GH1 family in SH group was
   more than that in the other two groups. β-glucosidase mainly plays a
   role in glycolipid metabolism and is a key enzyme that catalyzes
   cellulose to produce glucose. We believe that the higher β-glucosidase
   activity in the SH group is closely related to its microbial community.
   Studies have shown that adding β-glucosidase to feed or activating
   β-glucosidase through diet can improve the digestive capacity of the
   gastrointestinal tract and benefit animal growth ([158]79).
   β-glucosidase can also increase the activity of intestinal amylase
   ([159]80). This is also consistent with our found, the amylase content
   of SH group was the highest. Zhang ‘s study found that castration
   changed the cecal digestion environment of dairy cows, significantly
   reduced the activity of β-glucosidase, reduced the relative abundance
   of Ruminococcaceae and other bacteria related to β-glucosidase, and
   reduced the daily gain of dairy cows ([160]81). Therefore, the
   enrichment of β-glucosidase has a positive effect on calves. The
   chitinase (EC 3.2.1.14) in GH19 family showed more obvious differences.
   The enrichment of chitinase in SH group was much less than that in SF
   group and TMR group. Chitinase has strong specificity and can cleave
   chitin glycosidic bonds. Chitin is a component of invertebrates,
   arthropods, fungi, etc., but mammals can hardly synthesize chitin
   themselves. Therefore, attention should be paid when excessive
   chitinase is enriched in mammals, and it may be food containing chitin
   or microbial pathogens invade the body ([161]82). Recent studies have
   shown that chitin protein is related to gastrointestinal diseases.
   Chitinase can play an important role in gastrointestinal digestion and
   diseases due to its specificity, and it is likely to become a new idea
   for the treatment of gastrointestinal diseases ([162]83, [163]84). The
   study of Beier found that microorganisms can also produce chitinase,
   including Firmicutes, Actinobacteria, etc. Chitinase can specifically
   hydrolyze chitin and make it lose pathogenicity, which is particularly
   critical for mammals ([164]85). We observed local inflammatory
   reactions in both the SF group and the TMR group. Parasites also
   appeared in the TMR group. It is most likely that foreign pathogens
   produce chitin, which stimulates some of the bacteria in the intestine
   that can release chitinase to respond, causing differences in
   intestinal flora.

   In addition to this, there is a more critical phenomenon, we found that
   in the TMR group, a unique enrichment of many neurotransmitters and
   their precursors: Dopamine, Noradrenaline, Levodopa, etc., which may
   point to a new research field: neuro microbiology. In recent years,
   more and more studies have shown that microorganisms not only have the
   functions of assisting digestion and maintaining barriers, but also
   participate in the regulation of the enteric nervous system and the
   central nervous system by producing neurotransmitters or
   neurotransmitter precursors ([165]86). It is reported that intestinal
   microorganisms can synthesize neurotransmitters such as dopamine,
   norepinephrine, 5-hydroxytryptamine and compounds involved in the
   metabolism of neurotransmitters in the body, which can act on the local
   intestinal nervous system and regulate the intestinal environment
   ([166]87, [167]88). Taking the synthesis mechanism of dopamine
   (phenylalanine-tyrosine-L-dopa-dopamine) as an example, phenylalanine
   hydroxylase converts L-phenylalanine into L-tyrosine, which can cross
   the blood–brain barrier and enter the brain. In the brain, it is
   converted to (s)-3,4-dihydroxyphenylalanine (L-DOPA) by tyrosine
   hydroxylase, and then L-DOPA is converted to dopamine by dopa
   decarboxylase ([168]89, [169]90). Although the pathway by which these
   neurotransmitters are synthesized by the gut microbiome is unclear, it
   is likely that the gut microbiome also has the ability to convert local
   dopamine to norepinephrine, such as dopamine-beta oxidase ([170]91).
   Intestinal microorganisms can also synthesize neurotransmitter
   precursors such as L-tyrosine. Due to the lack of relevant
   transporters, some neurotransmitters circulating in the blood, such as
   dopamine and norepinephrine, cannot cross the blood–brain barrier.
   However, the precursors of these neurotransmitters can cross the
   blood–brain barrier, synthesize related substances in the brain, and
   then regulate, which may be the way that microorganisms connect the
   central nervous system.

   Intestinal flora communicates with the central nervous system,
   sympathetic nerve and vagus nerve through neurotransmitters, regulates
   the level of neurotransmitters such as auxin, and affects the growth
   and development, gastrointestinal digestion and immune function of
   animals ([171]92). For example, slight changes in the vagus nerve will
   lead to dramatic changes in the release of downstream
   neurotransmitters, which will affect digestive level, intestinal
   permeability, intestinal motility and immune response ([172]93,
   [173]94). The central nervous system receives signals from these
   neurotransmitters and regulates the digestive environment and microbial
   community composition in the gastrointestinal tract by producing
   neurochemicals such as 5-hydroxytryptamine, cholecystokinin, and
   dopamine. Microorganisms also stimulate intestinal endocrine cells to
   produce hormones and complete feedback to the central nervous system
   through neural afferent fibers. For example, in the presence of
   dopamine and norepinephrine, Escherichia coli will proliferate faster
   and may also enhance its motility and toxicity ([174]95). Liu ‘s study
   found that abnormal casein synthesis aggravated enteritis, disrupted
   microbial flora and its metabolic function, and led to abnormal immune
   response ([175]96). The intermediate compound of neurotransmitters:
   short-chain fatty acids, also participate in the regulation of
   microorganisms and neurotransmitters. Studies have shown that
   short-chain fatty acids can regulate the metabolism of many
   neurotransmitters by acting on the response element binding proteins in
   the cAMP signaling pathway ([176]97, [177]98). Taking dopamine as an
   example, short-chain fatty acids can regulate the production of
   dopamine and the conversion of dopamine and norepinephrine by
   regulating the expression of tyrosine carboxylase and
   dopamine-β-carboxylase ([178]99). These metabolic pathways are
   reflected in the differential metabolic pathways in the TMR group.
   Especially for ruminant mammals such as calves, the short-chain fatty
   acids in the body will be more abundant, and the regulation mechanism
   of short-chain fatty acids will be more complicated. In some animal
   model experiments, it has also been found that metabolic abnormalities
   caused by intestinal microbial community disorders and the release of
   monoamine substances may lead to depression ([179]100). This proves the
   deep relationship between intestinal microbial changes and host mental
   disorders. In animal husbandry, whether it will affect animal feed
   intake and estrus cycle needs further study.

   In recent years, many studies have shown that intestinal microorganisms
   can communicate and regulate with the gastrointestinal tract and brain
   through neurotransmitters, and interact to maintain the dynamic balance
   of the intestinal environment. One of the difficulties in the field of
   neurobiology is to identify whether the source of various neuroactive
   compounds is host or microorganism. Secondly, the influence between
   intestinal microorganisms and neurotransmitters, and the complex
   communication between intestinal microorganisms and the brain are
   difficult. Combining the analysis results of metabolomics and
   metagenomics will help us understand the operation relationship between
   the microbial-intestinal-brain axis from the perspective of neuro
   microbiology. In the future, specific microbial targeted interventions
   can be performed on the host from the perspective of neuro
   microbiology, which can be used to adjust the intestinal flora and
   improve digestion. It is even possible to regulate specific microbial
   communities by understanding the relationship between gut microbes and
   brain health, and to treat neurological diseases through microbial
   regulation of the central nervous system.

5. Conclusion

   In summary, our study found that the feeding mode of ‘starter + hay +
   milk ‘was more conducive to the development of calves. The calves in
   the SH group had better intestinal development, intestinal microbial
   community was more conducive to digestion and absorption, and immunity
   was stronger. The feeding mode of the SH group was conducive to the
   healthy development of the calves. Therefore, the calves in the SH
   group had higher daily weight gain, stronger digestive ability, and no
   pathological inflammatory reaction was found. For calves, daily weight
   gain is important, and more importantly, there can be a stronger
   digestive system and immune system to ensure that calves can have
   better growth and development after weaning, which is the advantage of
   SH group compared with SF group. The enrichment of neurotransmitters
   found in the TMR group also inspired us to study intestinal
   microorganisms from a new perspective. The research ideas of neuro
   microbiology will be one of our future focuses. Therefore, the results
   of this study provide a basis for improving the feeding mode of calves,
   and inspire us to explore the relationship between microorganisms and
   hosts from the perspective of neural metabolites.

Data availability statement

   The original contributions presented in the study are included in the
   article/supplementary material, further inquiries can be directed to
   the corresponding author.

Ethics statement

   The animal study was approved by the Institutional Animal Care and Use
   Committee of the College of Animal Science and Technology. The study
   was conducted in accordance with the local legislation and
   institutional requirements.

Author contributions

   JW: Data curation, Writing – review & editing, Writing – original
   draft. YC: Data curation, Writing – original draft, Writing – review &
   editing. ML: Data curation, Investigation, Project administration,
   Writing – review & editing. SX: Investigation, Software, Writing –
   review & editing. KZ: Investigation, Software, Writing – review &
   editing. HF: Investigation, Software, Writing – review & editing. JN:
   Investigation, Software, Writing – review & editing. WS:
   Conceptualization, Investigation, Software, Writing – review & editing.
   XJ: Conceptualization, Investigation, Software, Writing – review &
   editing. SL: Methodology, Project administration, Supervision, Writing
   – review & editing.

Funding

   This study was supported by the key research and development project of
   Sichuan beef cattle genome selection technology system (2022YFYZ0006).

Conflict of interest

   The authors declare that the research was conducted in the absence of
   any commercial or financial relationships that could be construed as a
   potential conflict of interest.

Publisher’s note

   All claims expressed in this article are solely those of the authors
   and do not necessarily represent those of their affiliated
   organizations, or those of the publisher, the editors and the
   reviewers. Any product that may be evaluated in this article, or claim
   that may be made by its manufacturer, is not guaranteed or endorsed by
   the publisher.

Footnotes

   ^1 [180]https://github.com/voutcn/megahit

   ^2 [181]http://topaz.gatech.edu/GeneMark/

   ^3 [182]https://www.ncbi.nlm.nih.gov/

   ^4 [183]http://www.kegg.jp/kegg/

   ^5 [184]http://www.cazy.org/

   ^6 [185]http://www.plob.org/tag/eggnog/

References