Introduction
Lambs intestinal mucosa is in continual contact with diverse array of microbes.
The intestinal microflora is vital to
physiological functions and homeostatic, and plays important
roles in early-weaned lamb’s defense through colonization resistance by
promoting the development and regulation of the acquired mucosal immune
system (McCoard et al. 2019). Disturbances of intestinal
microflora homeostasis are thought to contribute to severe
gastrointestinal disorders (Kong et al. 2019). The
intestinal microflora comprises potential pathogens and can be a source of
infection under some circumstances (Yang et al. 2019a). Especially for
early-weaned lambs, the immune system and digestive were immature, and they had
to adapt the radical change from digestible watery breast milk to a relatively
indigestible solid feed, and the risks of infection by pathogenic bacteria such
as Escherichia coli and Salmonella were increased (Fan et al.
2019.)
Boulardii yeast wall polysaccharide (BRYP) is one of the main
biologically active components in Boulardii
yeast. Besides, BRYP is a kind of natural prebiotics, which
are compounded from β-glucan (30‒60%), mannosan (20‒30%), and chitin (5‒10%) (Chen et al.
2018a). BRYP almost does not be digested and absorbed by the early-weaned host
digestive system, but could increase the proliferation of kinds of probiotics
selectively (Fortin et al. 2017).
In recent years,
many studies have shown that yeast wall polysaccharides supplementation in
basal diet can regulate the balance of intestinal microbiota, and reduce the
diarrheal diseases, which has caused by an imbalance of intestinal microflora and
bacterial translocation. It has been reported that the yeast cell wall
polysaccharides supplementation could improve the growth performance of cattle
by promoting the fibrotic microbial populations, but decrease aerobic starch-utilizing
bacteria (Peng et al. 2020). Besides, in the cecum of weaned piglets,
feeding diets with yeast cell wall polysaccharides in a short feeding-period
could improve the cecum bacteria structure, and enhance the advantage
bacterium, such as Firmicutes, Ruminococcus (Qin et al. 2017).
Furthermore, the relative abundance of Bacteroidetes
and Firmicutes was significantly improved
in the rate intestine by feeding a diet with yeast cell wall polysaccharides (Radhika
et al. 2019).
However, little study has analyzed the
effects of BRYP on the intestinal microflora of early-weaned lambs according to
a HiSeq of 16S rRNA gene. Differences in intestinal microflora
compositions between jejunum, cecum, and colon in early-weaned lambs after
feeding BRYP are still unknown. Therefore, more pieces of evidence are needed
to specify the roles of BRYP of intestinal microflora and correlation with
immune indices of early-weaned lambs. Therefore, we performed 16S rRNA HiSeq to
specify and compare the intestinal microbial flora composition, diversity,
relative abundance, principle coordination analysis,
and correlations with intestinal immune indices. We hypothesized that a
supplement of 0.5% BRYP with basal milk replacer can modulate the intestinal
microflora compositions. Therefore, this research might provide fundamental
information for a large-scale in lamb industry.
Materials and Methods
All experimental lambs in this research have been
prospectively approved and granted a formal waiver of ethics approval by the Animal
Welfare Committee of Shihezi University (Xinjiang, China) with the ethical
code: A2019-156-01. The experimental period was 40 days from 5th December 2019
to 18th January 2020. The experiment was conducted in Asar farming
cooperatives, Changji, China (43°91’22.01” S, 87°09’93.84” W).
Materials
The Boulardii yeast was obtained from Shihezi University
(Shihezi, China). The pure BRYP was obtained by the procedures of fermentation,
extraction, and purification. The pure BRYP of nutritional compositions were
polysaccharides (≥ 84%), crude protein (≤ 4%), crude fat (≤ 3%),
crude ash (≤ 2%), and moisture (≤ 7%). The main components of BRYP
were BLC-1 and BLC-2, which molecular weight were 22.76 kDa and 9.09 kDa. The
BLC-1 and BLC-2 accounted for 63.12 and 28.70% in BRYP.
The trace mineral
premix was provided by Tianjin Zhengda biological technology Ltd., Tianjin,
China; The Baby Formula Milk Powder was provided by Bright Dairy Co., Ltd,
Shanghai, China; The enzyme-linked immunosorbent assay kit was provided by
Suzhou Eisai Pharmaceutical Co., Ltd, Suzhou, China; DNA isolation kit was
provided by Tiangen Biochemical Technology Co., Ltd, Beijing China.
Experimental animals and experimental design
A total of sixty early-weaned lambs (35-days-old,
Kazak♂*Altay♀*Suffolk♂) were randomly blocked to two groups
with three replicates each and ten lambs (six males and four females per
replicate pen) in each treatment. The feeding trial lasted 40 days. All lambs
were enforcedly weaned at 35 old-days, and housed in thermostatically
controlled livestock pens (3.0×2.5 m) which were equipped with heating facilities
(maintained at 22‒25°C inside) and straw paillasses (thickness 2 cm), and with sufficient
warm water (15‒20°C). The pens were cleaned and sterilize at the beginning of the
experiment day basis to prevent disease outbreaks. Milk replacer and warm water
were available ad libitum in the whole feeding trial. Feeding and vaccination
procedures followed as farm management schedules. The milk replacer was mixed
with warm water (50°C) as the ratio (milk replacer: water = 1:4), and 4 feeding
times a day at 8:00, 13:00, 18:00, and 23:00. The control group was fed the
basal milk replacer with no addiction, a formulation consisting of cottonseed
meal, soybean meal, bran, and corn, which was formulated to meet the nutrient
requirement of 8~25 kg lambs with the daily gain of 300 g/day recommended by
the Chinese Feeding Standard of Lamb (2017) (Table 1). The
experimental group was fed the basal milk replacer with 0.5% BRYP.
Sample collection
and preparation
At the end of the experiment, three lambs in each replicate were randomly
selected and anesthetized by injecting a 5% Nembutal solution. After 25 min of
injection, the lambs were slaughtered by cutting neck vein. After lambs were
dissected, the contents of the jejunum, cecum, and colon were obtained by
manual extrusion, respectively, for the intestinal microflora analysis. After
contents collection, the segments of jejunum, cecum, and colon were cut opened
longitudinally and washed three times by 0.9% sodium chloride to remove
impurities, respectively. All samples were placed immediately into sterile
plastic tubes, separately, for the immune indices
detection (Xu et al. 2016). For reducing variations between individuals,
the contents samples from jejunum, cecum, and colon segment samples of three
lambs were pooled into one biological sample in each treatment (Bukin et al. 2019). Overall, 18 samples (jejunum,
cecum, and colon) were used for 16S rRNA high-throughput sequencing, and 6
samples (colon) were used for immune indices detection. All samples were
fast-frozen in liquid nitrogen and stored at -80°C until the
following analysis.
DNA extraction
Total intestinal microbial genomic DNA were isolated
from each gut segment by using DNA isolation kit and stored at −25°C for the
following analysis.
16S rDNA amplicon pyrosequencing
PCR amplification of the 16S rDNA (V3-V4 region) was
performed using the forward primer 314 F (5′‐ACTCCTACGGGAGGCAGCAG‐3′) and the
reverse primer 806 R (5′‐GGACTACHVGGGTWTCTAAT‐3′). The PCR conditions were as follows: initial denaturation at
92°C for 5 min, 28 cycles of 92°C for 55 s, 50°C for 35 s and 70°C for 2 min,
and then final extension at 70°C for 10 min (Xiao et al. 2017). The
quality and quantity of amplified DNA were showed by agarose gel
electrophoresis, separately.
The 16S rRNA gene,
which has been amplified, was obtained through DNA gel extraction kit, and
analysis with 1% Sepharose, which contains 2% of polyvinylpyrrolidone agarose
gel electrophoresis for the quality and quantity of amplified DNA sequence (Qian
et al. 2018). The total 16S rRNA genes were sent to Shanghai Jingjie
Biomedical Technology Co., Ltd. (Shanghai, China) and to analysis microbiota by
MiSeq PE300 sequencing platform. The raw data were matched by the FLASH
analysis tool (Version 1.2.5, http://ccb.jhu.edu/software/FLASH/), and filtered
to remove the barcode sequences, forward and reverse primers with the QIIME (Version
1.1.6, http://qiime.org/scripts/split_libraries_fastq.html) (Xiao et al.
2018). The read was removed if the quality scores less than 20 at the sliding
window or tags contained ambiguous bases. By using the UCHIME algorithm (http://www.drive5.com/usearch/manual/uchime_algo.html),
the reads were compared with the annotated database of the species, and made
sure that the chimeric sequences were discarded totally (Amato et al.
2013).
Analysis of OTU cluster
The optimized sequences were eliminated and
demultiplexed, after removing the chimeric sequences, barcode, and primers. The
operational taxonomic units (OTUs) were selected (97% similarity) and clustered
by using the Usearch (Version 7.0, http://drive5.
com/uparse/) (Han et al. 2019). The most frequent
sequences in OTUs were selected, and as the representative OTU sequences, which
were analyzed and annotated with the method of SILVA SSU rRNA database and the
mothur (threshold range from 0.6 to 1, http://www.arb-silva.de/).
Sequence analysis
We used the QIIME and R packages to mainly perform the
analyses of the sequence data.
1)
OUT-ranked
abundance curves were conducted to compare the uniformity and richness of OTUs
among samples. Venn diagram was showed to visualize the unique and shared OTUs
among samples. The significance of differentiation of microflora composition
among groups was analyzed by permutational multivariate assessment of variance
and similarities by R package “vegan” (Lozupone and Knight 2005).
2)
Alpha
diversity index revealed the richness and uniformity of the microbial community.
OTU alpha diversity indices, including Abundance‐based Coverage Estimator (ACE),
richness estimator (Chao), Simpson index, and Shannon diversity index, were
calculated by the OTU table in QIIME (Schloss et al. 2009).
3)
The
OTU taxonomic compensation was operated by using BLAST searching the
representative sequences set against the NCBI 16S rRNA database, and then, an
OTU table was clustered to calculate the abundance of each OTU in every sample
and taxonomy of those OTUs (Quast et al. 2012).
4)
Beta
diversity calculation was implemented to analyze the composition variation of
microbial communities in different samples by using Principal component
analysis (PCA). The difference of microbial samples was reflected in a
three-dimensional coordinate diagram, which the more semblable sample
composition was, the nearer the distance in PCA diagram. Linear discriminant
analyses (LDAs) were used to analyze whether it was important microbial
community that contributed to differences (Knights et al. 2011).
The correlation
analysis between intestinal immune indices and intestinal bacteria was
conducted by R package vegan. The heatmap diagrams were generated, according to
the Spearman correlation coefficients between altered intestinal bacteria and
immune indices (Akond et al. 2018).
Determination of immune indices
After the colon segment samples
defrosting, 1 g colon segment was weighed accurately and ground with liquid
nitrogen in sterile mortars for 15 min. The colon segment powder was mixed with
10 mL, 0.9% sodium chloride solution, and centrifuged at 3500 r/min, 6°C for 20
min. After that, the tissue fragments were removed, and the supernatant was
collected. The levels of SIgA, IL-6, IL-10, and TNF-α in the colon segment
were determined according to the instruction of ELISA kits (Wang et al.
2018).
Statistical analysis
The results were shown as mean ± standard deviation, and categorical
variables were shown as proportions and numbers. We used unpaired Student
t-test and ANOVA to statistically evaluate differences among groups,
respectively. It was considered statistically significant when P < 0.05. All analyses were counted
by Excel (version 2017 for Windows, Microsoft Inc., Chicago, IL, USA), and represented
with software SPSS (version 18, SPSS Inc., Chicago, IL, USA).
Results
Assessment of 16S rDNA PCR and sequencing
The 16S rRNA genes in each intestinal segment contents
were amplified by using forward primer 314 F and reverse primer 806 R. As shown
in Fig. 1, the concentrations and sizes of electrophoretic bands in the PCR
electrophoresis graphic were clear and suitable. As shown in Fig. 2, the
Shannon curves and Rarefaction curves have reached the platform, and Good coverage index achieved between 0.992 and 0.997,
according to the analysis of software Mothur. The results represented that the
vast majority of the microbial diversity information has been obtained by the
samples of amplified 16S rRNA genes, and the sequencing depth was adequate in
this study.
Operational taxonomic unit partition and classification
After the quality count, 902,549 high-quality sequences
were acquired. On average, 50,141 ± 3,483 sequences were obtained per sample. A
total of 3,678 OTUs were identified from all samples. On average, 204 OTUs were
obtained per sample of the control group and experimental group, based on 97%
species similarity. All detected OTUs were from 16 phyla, 29 class, 63 order,
108 families, and 287 genera. On average, there were 369, 537 and 885 OTUs in
the jejunum, cecum, and colon from the control group, respectively. There were
378, 552 and 987 OTUs in the jejunum, cecum, and colon from the experimental
group, respectively. Venn figures of unique and common OTUs were shown in Fig. 3.
There were 261, 378 and 657 common OTUs between the control group and experimental
group of jejunum, cecum, and colon, respectively. In the control group, 108,
159 and 198 unique OTUs were detected in the jejunum, cecum, and colon,
respectively; whereas 117, 174 and 330 unique OTUs were detected in the jejunum,
cecum, and colon of the experimental group, respectively.
Analysis of Alpha diversity
Alpha-diversity was analyzed by richness indices (Chao
and ACE), and diversity indices (Shannon and Simpson). According to the results
as shown in Fig. 4, firstly, we found that the richness index of Chao and ACE increased
as digestive tract from top and bottom; whereas the diversity index of Shannon
and Simpson firstly increased, and then decreased as digestive tract from top
and bottom. Besides, the experimental
group of Chao was significantly higher than the control group in the cecum (P < 0.05). Furthermore,
the experimental
group of Chao was extremely significantly higher than the control group in the
colon (P < 0.01). The experimental group of ACE was higher than the control group in the jejunum, cecum and, colon, respectively, but the differences was not significant (P > 0.05). The experimental group of Shannon and Simpson were
significantly lower than the control group in the colon (P < 0.05). These results indicated
that the addition of 0.5% BRYP in basal milk replacer can enhance the richness
of microbial composition in the cecum and colon, but decrease diversity
in the colon.
Analysis of taxonomic composition
The taxonomic
bar represented relative abundance levels of various phyla and genus in two
groups. After the optimized sequences were clustered and annotated, the
top-ranking most abundant microbial at phylum and genus levels were shown in
Fig. 5‒6. Otherwise, the sequences which
could not be clustered into any groups (97% similarity) in the database were
assigned as “other”.
At the level of phyla, based on the average relative
abundance analysis, the results indicated that the proportion of relative
abundance of two major phyla (Firmicutes
and Bacteroidetes) were more than 70%
in all OTUs. Besides, Proteobacteria,
Verrucomicrobia,
Spirochaetes, Fibrobacteres, Tenericutes, Lentisphaerae, and Euryarchaeota were another 8 predominant phyla. In the jejunum, the
experimental group of relative abundance of Bacteroidetes
and Verrucomicrobia was significantly
higher than the control group by 27.70 and 75.75% (P < 0.05), but the experimental group of relative abundance of Proteobacteria was significantly lower
than the control group by 92.15% (P <
0.05). Compared with the control group, and the experimental group of relative
abundance of Bacteroidetes in the
cecum and colon was significantly increased by 30.06 and 45.89% (P < 0.05), but the experimental group
of relative abundance of Firmicutes
and Proteobacteria were significantly
decreased by 7.45, 21.19 49.04 and 48.16% in the cecum and colon, separately (P < 0.05).
At the level
of the genus, the predominant genus was Lactobacillus,
Prevotella, Ruminobacter, Bacteroides,
Blautia, Streptococcus, Faecalibacterium,
Akkermansia, and Bifidobacterium. In the jejunum, the experimental group of relative
abundance of Lactobacillus, Prevotella, and Fibrobacter was significantly higher than the control group by
48.32, 36.87 and 75.42% (P < 0.05),
but the experimental group of relative abundance of Ruminobacter was significantly lower than the control group by
27.83% (P < 0.05). In the cecum,
the experimental group of Table
1: Ingredient compositions
and chemical analysis of milk replacer (%; air-dry basis)
|
Items |
Content |
Nutrient levels |
Content |
|
Ingredients |
|
Nutrition level |
|
|
Expended corn |
41.50 |
Dry matter |
90.67 |
|
Alfalfa hay |
8.00 |
Digestible energy DE/(MJ/kg） |
17.38 |
|
Soybean oil |
2.00 |
Crude protein |
23.75 |
|
Expended soy |
16.00 |
Crude fat |
16.08 |
|
Fermented Soybean |
20.00 |
Neutral detergent fiber |
4.81 |
|
Premix |
1.00 |
Calcium |
0.53 |
|
Baby Formula Milk
Powder |
10.00 |
Phosphorus |
0.41 |
|
NaCl |
0.30 |
Lysine |
0.91 |
|
CaHCO3 |
1.00 |
Methionine + cysteine |
0.61 |
|
NaHCO3 |
0.20 |
Threonine |
0.65 |
|
Total |
100.00 |
Concentrate: roughage |
80:20 |
%20156-168_files/image002.jpg)
Fig. 1: The electrophoresis results of PCR products
%20156-168_files/image004.png)
Fig. 2: Analysis results of Shannon curves and Rarefaction
curves
%20156-168_files/image006.png)
Fig. 3: Veen diagram of common
Operational Taxonomic Units (OTUs). DS,DM and DJ represent samples of
jejunum, cecum and colon in the control group, respectively; SS, SM, SJ represents sample of
jejunum, cecum and colon in the experimental group, respectively
relative abundance of Lactobacillus, Bacteroides,
Oscillospira, and Bifidobacterium were significantly
higher than the control group by 37.65, 32.02, 86.49 and 56.52% (P < 0.05), but the experimental group
of relative abundance of Blautia was
significantly lower than the control group by 68.19% (P < 0.05). In the colon, the experimental group of relative
abundance of Lactobacillus, Faecalibacterium,
Bifidobacterium, and Akkermansia were
significantly higher than the control group by 32.25, 27.72, 72.38 and 73.21% (P < 0.05), but the experimental group
of relative abundance of Escherichia,
Prevotella and Streptococcus were significantly lower than the control group by
42.96, 38.27 and 30.77% (P < 0.05).
Analysis of Beta diversity
The Unweighted UniFrac distances of
samples under the jejunum, cecum, and colon in two groups were calculated based
on the relative abundances of OTUs in the eighteen samples. Besides, Principal
coordinates analysis (PCoA), which based on the Unweighted UniFrac, revealed
that whether there were clear separations of the microflora composition of the
control group from the experimental group. The three-dimensional graph of PCoA
at genus level was shown in Fig. 7. The microbial communities of the control
group and the experimental group were hard %20156-168_files/image008.png)
Fig. 4: Diversities of microflora composition between the control group and the experimental
group in different intestinal segments. Four species richness and diversity
estimators, including (A) Chao, (B) ACE, (C) Shannon’s diversity index and (D) Simpson’s diversity index. Different capital letters indicate
extremely significant difference (P＜0.01), and different small letters indicate
significant difference (P＜0.05)
%20156-168_files/image010.png)
Fig. 5: Relative abundances of microbes in each
intestinal segment at phylum level
to separation
in the jejunum, but there was a clear separation of the microbial communities
of the control group from the experimental group. This result indicated that
BRYP may mainly affect the microbial communities of the bottom of the digestive
tract.
To further identify specific microbial composition with
statistically significant differences among groups, we used linear discriminant
analysis (LDA) to analyze the specific microbial composition, which was altered
by the addition of 0.5% BRYP in the basal milk replacer, as shown in Fig. 8.
When taxa with LDA scores greater than 2, the experimental group of differential OTUs of jejunum, cecum
and colon were 10, 11 and 17, respectively; the control group of differential
OTUs of jejunum, cecum, and colon were 3, 11 and 14, respectively. When taxa
with LDA scores greater than 3, the experimental group of differential OTUs of
jejunum, cecum, and colon were 1, 4, and 9, respectively; the control group of
differential OTUs of jejunum, cecum, and colon were 0, 4 and 3, respectively.
The canonical correlation analysis between immune indices and intestinal
microflora
%20156-168_files/image012.png)
Fig. 6: Relative abundances of microbes in each
intestinal segment at genus level
%20156-168_files/image014.jpg)
Fig. 7: The total Principle Coordination
Analysis scores plot about the microbes in
intestinal segments. DS,DM and DJ represent samples of
jejunum, cecum and colon in the control group, respectively; SS,SM,SJ represents sample of
jejunum, cecum and colon in the experimental group, respectively
The results of the significant differences of immune
indices and intestinal microflora were in two groups. The densities of immunoglobulins and cytokines of intestinal
mucosal were analyzed according to the instruction of ELISA kits. As shown in
Table 2, there was a significant difference in the two groups concerning the
content of IL-6, IL-10, SIgA, and TNF-α. The experimental group of IL-6
was significantly lower than the control group by 15.09% In the colon (P < 0.05); The experimental group of
IL-10 were significantly higher than the control group by 15.80 and 6.60% In
the cecum and colon, respectively (P <
0.05); The experimental group of SIgA was significantly higher than the control
group by 10.98% in the colon (P < 0.05);
The experimental group of TNF-α was significantly lower than the control
group by 7.90% in the colon (P < 0.05).
Besides, according to the analysis of taxonomic composition at the level of genus, the significant
difference of top-ranking most abundant intestinal microflora was listed in
Fig. 9.
The canonical
correlation analysis between immune indices and intestinal
bacteria in the colon as shown in
Fig. 9, the clustering correlations between the compound BRYP-stimulated
significant changes in immune indices (immunoglobulins and cytokines in intestinal mucosa) and intestinal bacteria relative
abundance at the genus levels were analyzed to investigate the interactions
between immune indices and intestinal bacteria during the feeding trial of addition BRYP-treated
early-weaned lambs. The results indicated that robust correlations with
compound BRYP-induced alterations in intestinal microflora and immune indices.
The red bars represented positive correlations, and the blue bars indicated
negative correlations.
To further predict interactions between intestinal
bacteria and immune indices, according to Pearson
correlation coefficients, we constructed a diagram of Canonical Correlation
Analysis (CCA) between intestinal bacteria and immune indices, as shown in Fig. 10.
Combined with the heat map and CCA diagram, we
summarized that there were significant correlations between IL‒6, IL‒10, TNF-α, and intestinal microbial composition
in the colon (P < 0.05). IL‒6 was positively correlated with Butyricicoccus, Clostridiales, Escherichia-Shigella, Achinobacillus, Rikenellaceae_RC9_gut_group,
Norank_f_Erysipelotrichaceae, Clostridium, Prevotella_9, and %20156-168_files/image016.png)
Fig. 8: The comparisons of microflora composition between
the control group and the experimental group in different intestinal segments. (A) Comparison of microbial composition in jejunum; (B) Comparison of microbial composition
in the cecum; (C) Comparison of
microbial composition in the colon
Ruminococcaceae_UCG-014, respectively; but the negative correlations with IL‒6 were Akkermansia,
Lactobacillus, Rombsia, Oscillospira, Prevotella_1, Prevotellaceae_UCG-004,
Lachnospiraceae_136_group, Parabacteroides, Blautia, and Lachnospiraceae
NK4A136. IL-10 was positively correlated with Bifidobacterium,
Akkermansia,
Lactobacillus, Prevotellaceae_UCG-003, Faecalibacterium,
Rombsia, Prevotellaceae_NK3B31_group, Christensenellaceae_R-7group,
Lachnospiraceae_XPB1014_group, Prevotellaceae_UCG-001, and Ruminococcaceae_UCG-005, respectively; but the negative correlations
with IL-10 were Clostridiales, Escherichia-Shigella, Coprococcus_3, clostridium_sensu_stricto_1,
Ruminococcus_1, and Intestinibacter. TNF-α was
positively correlated with Streptococcus,
Erysipelotrichaceae_UCG-003, Norank_f_Erysipelotrichaceae, Escherichia-Shigella, Clostridium_sensu_stricto_1, Prevotella_2, and Eggerthellaceae_unclassified, respectively; but the negative
correlations with TNF-α were Akkermansia,
Romboutsia, Christensenellaceae R-7 group, and Ruminococcaceae_UCG-002.
Discussion
The intestinal microflora
is a vital and complex ecosystem with functions that shape animal health.
Currently, the intestinal microbial ecosystem has been regarded as a virtual
endocrine organ, and it has been proved that the intestinal microbial balance
and the steady-state becomes a requisite for animal maintenance organism health
(Jiao et al. 2019). Generally, high microbial diversity was regarded to
be associated with a healthy intestinal micro-ecosystem, while loss of
diversity seems to be related to the disease (Pradhan et al. 2019). Early
weaning is a common practice in modern sheep farming at present, but the immune
and digestive system of early-weaned lambs were immature. The colonization of
the suckling lamb intestinal microbiome during the first few months of life is
a period of remarkable immaturity and fluctuation. The relatively indigestible solid
food will contribute to the risks of infection by pathogenic bacteria, acute
diarrhea, and gastro-enteritis (Mao et al. 2019). In the early months,
the density and diversity of intestinal microflora are constantly broadening in
response to new environmental exposures until achieving a stable adult-like
intestinal microbial composition (Blasco et al. 2019).
Table 2: Effects of BRYP on immunoglobulins and cytokines
in intestinal mucosa (mg/g)
|
|
The control group |
The experimental group |
|
||||
|
Item |
Jejumum |
Colon |
Cecum |
Jejumum |
Colon |
Cecum |
P-value |
|
IL-1 (pg/g) |
3.86 ± 0.44 |
4.27 ± 0.83 |
4.01 ± 0.51 |
3.25 ± 0.74 |
3.88 ± 0.76 |
3.96 ± 0.25 |
0.739 |
|
IL-6 (pg/g) |
3.05 ± 0.13a |
3.96 ± 0.04b |
3.71 ± 0.06b |
2.98 ± 0.17a |
3.63 ± 0.03b |
3.15 ± 0.04a |
0.038 |
|
IL-10 (pg/g) |
2.05 ± 0.16a |
3.41 ± 0.20b |
3.54 ± 0.22b |
2.78 ± 0.04ab |
4.05 ± 0.39c |
3.79 ± 0.31c |
0.014 |
|
SIgA (mg/g) |
10.28 ± 0.56a |
13.69 ± 0.40b |
14.27 ± 0.59b |
11.44 ± 0.35a |
14.52 ± 0.55b |
16.03 ± 0.39c |
0.036 |
|
IgG (mg/g) |
23.94 ± 6.95 |
27.38 ± 4.67 |
29.55 ± 9.31 |
26.96 ± 7.35 |
28.87 ± 5.67 |
29.30 ± 6.52 |
0.855 |
|
TNF-α (pg/g) |
4.84 ± 0.31b |
4.82 ± 0.31b |
4.81 ± 0.73b |
4.80 ± 0.56b |
4.81 ± 0.18b |
4.43 ± 0.81a |
0.048 |
|
IFN-γ (pg/g) |
3.82 ± 0.02 |
4.05 ± 0.25 |
4.12 ± 0.20 |
3.59 ± 0.11 |
3.52 ± 0.42 |
4.05 ± 0.19 |
0.062 |
%20156-168_files/image018.jpg)
Fig. 9: Correlation Heatmap between BRYP-stimulated
significantly changes in immune indices and intestinal bacteria in two groups
Most polysaccharides, such as yeast wall polysaccharides, have been
proven to exert immunomodulatory, antiulcer, antioxidant, antitumor, and
regulation of microbial composition (Mandal and Sahi 2018). BRYP is one of the main
bioactive constituents in Boulardii
yeast, which has been wildly used to treat diarrhea in babies. The mechanisms that Boulardii
yeast wall polysaccharides could regulate intestinal microbial communities as follows: 1) BRYP is hard to be
digested in the digestive tract, but BRYP could be used by intestinal
probiotics, such as Bifidobacterium
and Lactobacillus, which could
promote the growth of prebiotics, but inhibit the growth of pernicious bacteria
(Dong et al. 2019). 2) There was an interaction between intestinal bacteria
and cytokines. Such interaction could be adjusted by BRYP-induced alteration of
pathogen-associated molecular patterns (Singu et al. 2020). 3) The
harmful and pathogenic bacteria could be absorbed in the large construction of
BRYP (Méabed et al. 2019). It has been reported that the supplementation
of Pichia guilliermondii cell polysaccharides significantly decreased
the level of pH, and the number of pathogenic in the intestinal of chickens (Shanmugasundaram
et al. 2014). The addition of yeast wall polysaccharides significantly
increased the Alpha diversity of intestinal microbial in calf rumen (Jinjin et
al. 2018). After 150 g/t yeast wall polysaccharides as supplementation were
fed to 28 old-days piglets, the results showed that the number of Escherichia, Lactobacillus were significantly increased in ileum and caecum (Murphy
et al. 2013). After 250 g/t yeast wall polysaccharides as
supplementation were fed to piglets, the results indicated that the number of Escherichia was significantly decreased
in the caecum and colon (Sweeney et al. 2012).
%20156-168_files/image020.jpg)
Fig. 10: CCA analysis results of intestinal microflora
composition and immunologic factors
%20156-168_files/image022.jpg)
Fig. 11: A triangle of interdependence and interaction of
MRYP, microflora composition and immune index
Now-a-days, lots of technologies
of high-throughput sequencing technologies, such as 16 Sr RNA, 26Sr RNA, 26Sr
DNA, have been extensively used to analyze the composition of the intestinal
microbial composition in human beings and animals. Besides, analysis of α‐diversity involves a comparison of mean species
richness, uniformity, and diversity found in two or more sets of samples using
analysis of variance (Crist et al. 2003). In this study, the alpha-diversity was analyzed by
using the ACE, Chao, Shannon, and Simpson diversity index. These results showed
that the addition of 0.5% BRYP in milk replacer significantly increased the
richness of intestinal microflora in the cecum and colon by analysis of Chao (P < 0.05). However, we found by
analysis of Shannon and Simpson index that 0.5% BRYP in milk replacer
significantly decreased the diversity of intestinal microflora in the colon (P < 0.05). These results indicated
that 0.5% BRYP as a kind of supplement increased the species of intestinal
microflora in the cecum and colon, but decreased the uniformity of microflora species in the
colon of early-weaned lamb. Besides, the increasing ACE data indicated that the
abundance of microbial taxa increased after 0.5% BRYP as a supplement added
into the basal milk replacer. Besides, it has been reported that fat deposits
were related to the diversity of intestinal microflora, and the diversity of
intestinal microflora of obesity was lower than a normal person with high
probability (Aatsinki et al. 2018). In our feeding trail, we found that
the average lambs’ neck fat of 0.5% BRYP group was higher than the basal milk
replacer group, which speculated that there might be a correlation ship between
fat deposits and diversity of intestinal microflora in lambs.
For the first time, our
study analyzed the addition of 0.5% BRYP in basal milk replacer altered the
taxonomic composition of cecum and ileum microbial communities in early-weaned
lambs. In this study, we found that Firmicutes
and Bacteroidetes were two major
phyla in the early-weaned lamb intestine. Besides, we found that the relative
richness of Bacteroidetes was
significantly increased by 0.5% BRYP, but the addition of 0.5% BRYP
significantly decreased the relative richness of Proteobacteria. These results inferred that the risk of the
infection by pathogenic in intestinal was decreased by BRYP, and increased the
digestion and absorption of carbohydrate and fat in the digestive tract. Danzeisen
has reported that the Firmicutes and Bacteroidetes were the predominant phyla
within the caecum at all time-points (Danzeisen et al. 2011). Jumpertz reported
that the increased Firmicutes and Bacteroidete in the intestine were
related to the nutrient absorption (Jumpertz et al. 2011).
Besides, the growth of
harmful microbes and pathogenic might multiply rapidly when the relative
richness of Proteobacteria increased
in the intestinal, and the increasing of harmful microbes and pathogenic might
could result in dysbacteriosis, diarrhea, and gastro-enteritis in breeding production
(Ramayo-Caldas et al. 2016). Those previous reports agreed to our
results.
Generally, Lactobacillus, Bacteroides, Prevotella, Oscillospira,
Akkermansia, and Bifidobacterium were probiotics in our intestine (Ley et al.
2006). However, most of Escherichia
and Streptococcus were pernicious
microbes (Isaacson and Kim 2012). Lactobacillus
could produce bacteriocin-like substances, which were often active against
related species of bacteria and eradicate neighboring bacteria by attaching
themselves to receptors on their surfaces. Besides, Lactic acids, Acetic, and
Biotin were produced by Lactobacillus
could decrease intestinal pH to inhibit the growth of harmful bacteria (Chen et
al. 2018b). Prevotella was another
advantage microbe composition in the intestine. Prevotella could digest carbohydrates and protein, and it
participated in Polysaccharide degradation, amino acid metabolism in rumen and
intestinal (Fang et al. 2017). The Oscillospira
could decrease in a person with the inflammatory response. Therefore, there is
a negative correlation between the level of inflammatory response and the number
of Oscillospira
(Kovatcheva-Datchary
et al. 2015). The abundance of Akkermansia
was negatively correlated with levels of IL‒6
and free fatty acids in serum. Besides, Akkermansia
have the capacity to ameliorate inflammatory response, guard intestinal
epithelial cells and strengthen mucosal barrier function (Ashrafian et al.
2019). Bifidobacteria could
synthesize antimicrobial compounds such as bacteriocins, and other organic
acids, which could control the growth and reproduction of the harmful microbes
in the intestinal (Modrackova et al. 2020). On the other hand, Escherichia is a kind of common harmful
bacteria in the intestinal, such as pathogenic Escherichia coli (EPEC),
Enterotoxigenic E. coli (ETEC), Enteroinvasive E. coli (EIEC), and Enterohaemorrhagic
E. coli (EHEC) can produce toxins, known as Vero toxins or Shiga toxins,
which damage mucosa cells of the intestine and the kidneys (Sobhy et al.
2020). Besides, Streptococcus could
produce toxins, such as streptolysin, pyrogenic exotoxin, hyaluronidase,
streptodornase, streptokinase, and leipoteichoic acid (LTA), which can cause
the imbalance of intestinal flora, bacterial translocation and decrease
intestinal barrier function (Mabrouk et al. 2019). In this study, 0.5%
BRYP as a supplement added into basal milk replacer significantly enhanced the
relative richness of Lactobacillus, Prevotella, Oscillospira, and Bifidobacteria,
but significantly decreased the Escherichia
and Streptococcus in the lamb
intestine, which indicated that addition of 0.5% BRYP could increase the
proportion of probiotics, but decrease the proportion of harmful bacteria. In a
word, BRYP improved the relative richness of beneficial bacteria, but suppressed
the relative richness of harmful bacteria in the lamb intestine.
Some pieces of evidence have suggested that there are interactions
between immune indices and intestinal bacteria (Ansaldo et al. 2019).
Interleukin-6 (IL‒6) as one of the sensitive indexes of early
diagnosis for acute infection could increase and activate T lymphocyte and B
lymphocyte (Huang et al. 2018). The immune response could be adjusted by
IL-6, which acting an important role in anti-infection immunity, complement
system, and excessive immune response (Ouyang and O'Garra 2019). Interleukin
(IL)-10 is a kind of soluble protein, which exhibits a wide range of both
immunostimulatory and immunosuppressive properties. The excessive immune
response must often have followed in the intestine without or lack of IL‒10 (Fiorentino et al. 2016). TNF-a is a pro-inflammatory cytokine
known to have a crucial cell factor in the initial host response to infections
and the pathogenesis of various chronic immune-mediated diseases (Reinke et
al. 2020). These confirm the pivotal role and features underline of TNF-a
in the immune system and in particular in the area of cell-mediated immune
responses. However, massive TNF-a will occur serious excessive immune response
in the intestine, and will lead to acute gastro-enteritis and acute diarrhea (Yang
et al. 2019b). In this study, we found that there was a correlation
between intestinal bacteria and immune index. For example, Akkermansia had a positive correlation with IL‒10, but had a negative correlation with IL‒10
and TNF-α; In contrast, Escherichia-Shigella
had a negative correlation with IL‒10,
but had a positive correlation with IL-6 and TNF-α.
Therefore, we can speculate there was a triangle of interdependence and
interaction, which was composed of Boulardii yeast wall polysaccharide (BRYP), intestinal microbial composition, and immune
index, as shown in Fig. 11. First of all, BRYP as a supplement altered the
intestinal microbial composition. In this study, the relative abundance of Bifidobacterium, Lactobacillus, Akkermansia were
increased, but the relative abundance of Escherichia-Shigella,
Clostridiales, and Streptococcus were decreased. After that,
the changed intestinal microbial composition enhanced the concentration of IL‒10, but decreased the concentration of IL‒6
and TNF-α. In a word, BRYP not only improved the intestinal microbial composition,
but also indirectly suppressed the level of proinflammatory cytokines and increased
the level of tolerance cytokine.
Conclusion
Compared with the control
group, the richness of OTUs of the experimental group was significantly
increased in the jejunum, cecum, and colon, respectively (P < 0.05). Compared with the control group, the species richness
of the experimental group in the cecum and colon were significantly enhanced,
but the diversity of species of the experimental group was decreased in the
colon (P < 0.05). Bacteroidetes and Firmicutes were the most abundant phyla
in all intestinal segments both in the control group and experimental groups,
and the relative abundance of Bacteroidetes
in the experimental group was significantly enhanced, but the Proteobacteria was significantly decreased in the jejunum, cecum,
and colon (P < 0.05), compared
with the control group. In the jejunum, the relative abundance of Lactobacillus, Prevotella, and Fibrobacter of the experimental group were significantly enhanced than that of the control
group, but the Ruminobacter was significantly decreased (P < 0.05); In the cecum, the relative abundance of Bacteroides, Lactobacillus, Oscillospira and Bifidobacterium
of the experimental group were significantly enhanced than that of the control group,
but the Blautia were significantly
decreased (P < 0.05); In the
colon, the relative abundance of Akkermansia,
Bifidobacterium, Lactobacillus and
Faecalibacterium of the experimental group were significantly enhanced than that of the control group, but the
Prevotella, Streptococcus, and Escherichia
were significantly decreased (P < 0.05). According to the results of Heat maps and Canonical correlation analysis (CCA), there were significant correlations between
intestinal immune indices (IL‒6, IL‒10, TNF-α) and intestinal microbial composition in the colon (P < 0.05). These findings suggested
that BRYP may contribute to the promotion of the proportion of helpful
microbial populations and enhancing the balance of intestinal microflora.
Besides, the changed intestinal microflora composition may indirectly induce
mucosal immune interactions, which may improve local immune function, but
suppress the inflammatory response of the bottom of intestinal mucosa in
early-weaned lambs.
Acknowledgments
This study was supported
by The National Key R&D Program of China (2018YFD0502100).
Author
Contributions
Mengjian Liu: Conceptualization (equal); Methodology (supporting); Data
curation (equal); Formal analysis (equal); Investigation (equal); Methodology
(equal); Writing-original draft (equal); Writing-review & editing (equal); Wenju Zhang: Supervision
(equal); Formal analysis (supporting); Validation (equal); Resources
(supporting); Project administration (equal); Jun Yao: Software
(supporting); Junli Niu: Data curation (supporting); Formal analysis (supporting);
Software (equal); Visualization (equal).
Conflicts
of Interest
No conflict of interest exists in the submission of this
manuscript, and the manuscript is approved by all authors for publication. I
would like to declare on behalf of my co-authors that the work described was
original research that has not been published previously, and not under
consideration for publication elsewhere, in whole or in part. All the authors
listed have approved the manuscript that is enclosed
Data
Availability
The raw/processed data required to reproduce these
findings cannot be shared at this time as the data also forms part of an
ongoing study
Ethical
Approval
This study’s protocols and procedures were ethically reviewed and approved
by the Animal Welfare Committee of Shihezi University with the ethical code: A2019-156-01
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