Rhubarb is often used to establish chronic diarrhea and spleen (Pi)-deficiency syndrome animal models in China. In this study, we utilized the enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) method to detect changes in bacterial diversity in feces and the bowel mucosa associated with this model. Total microbial genomic DNA from the small bowel (duodenum, jejunum, and ileum), large bowel (proximal colon, distal colon, and rectum), cecum, and feces of normal and rhubarb-exposed rats were used as templates for the ERIC-PCR analysis. We found that the fecal microbial composition did not correspond to the bowel bacteria mix. More bacterial diversity was observed in the ileum of rhubarb-exposed rats (P<0.05). Furthermore, a 380 bp product was found to be increased in rhubarb-exposed rats both in faces and the bowel mucosa. The product was cloned and sequenced and showed high similarity with regions of the Bacteroides genome. AS a result of discriminant analysis with the SPSS software, the Canonical Discriminant Function Formulae for model rats was established.
Rhubarb is often used to establish chronic diarrhea and spleen (Pi)-deficiency syndrome animal models in China. In this study, we utilized the enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) method to detect changes in bacterial diversity in feces and the bowel mucosa associated with this model. Total microbial genomic DNA from the small bowel (duodenum, jejunum, and ileum), large bowel (proximal colon, distal colon, and rectum), cecum, and feces of normal and rhubarb-exposed rats were used as templates for the ERIC-PCR analysis. We found that the fecal microbial composition did not correspond to the bowel bacteria mix. More bacterial diversity was observed in the ileum of rhubarb-exposed rats (P<0.05). Furthermore, a 380 bp product was found to be increased in rhubarb-exposed rats both in faces and the bowel mucosa. The product was cloned and sequenced and showed high similarity with regions of the Bacteroides genome. AS a result of discriminant analysis with the SPSS software, the Canonical Discriminant Function Formulae for model rats was established.
Rhubarb (Rheum rhabarbarum) is a species of plant in the family
Polygonaceae. Its roots and stems are rich in anthraquinones [27], such as emodin and rhein. These substances are
cathartic and laxative. In the Chinese Pharmacopoeia [1], rhubarb is officially prescribed as the dried rhizome and root of R.
palmatum L., R. tanguticum Maxim. ex Balf. and R.
officinale Baill. of the family of Polygonaceae. Rhubarb has
been used as a laxative for several thousand years and classified as “bitter-cold” in terms
of taste and properties in traditional Chinese medicine (TCM). It is also officially listed
in the European and Japanese Pharmacopoeias. Rhubarb exhibits a series of pharmacological
activities and has been widely prescribed to treat gastrointestinal disease, hepatitis,
blood diseases, chronic renal failure, and especially, constipation due to its effective
purgative activity [20]. However, use of rhubarb as a
purgative, when in a chronic state, will result in an imbalance in the intestinal microbiota
and disturb the normal function of the body. As to its adverse effects [9], it is also used to induce chronic diarrhea and spleen
(Pi)-deficiency syndrome in animal models in TCM studies [30]. Understanding the disequilibrium in the microbial diversity may be a key to
understanding these diseases and successful establishment of animal models.Fecal samples are often used to investigate the intestinal microbiota because they are
easily collected and not invasive to the host. However, surface-attached and luminal
microbial populations may be distinct in composition from the fecal population, and fulfill
different roles within the ecosystem [2, 14, 31]. A number
of new bacterial strains have been found in the murine intestinal tract that have not been
detected in feces before [3, 22]. The degree to which the composition and function of the fecal
bacteria differ from those of mucosal bacteria remains unclear. Molecular biological
techniques, which are sensitive and efficient, have been recognized as potential and
valuable tools for systematic and detailed assessment of microbial communities. They are
likely to reveal new and unexpected principles of host biology and microbial ecology.
Enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR)
fingerprinting is a PCR-based technique in which DNA is isolated from a mixed sample and
amplified using conserved ERIC primers [25]. Slight
changes in the composition of the microbial population used could theoretically result in
very different PCR results [28]. Due to its
sensitivity, the ERIC-PCR fingerprinting method may have implications in monitoring the
effects of various known factors on the complex intestinal bacterial community [4, 7, 23, 24, 26].The aim of the present study was thus to reveal the changes in the bacterial composition of
feces and the bowel mucosa associated with a rhubarb-induced rat model by using ERIC-PCR
fingerprinting analysis and therefore gain more information on these animal models and to
propose new routes by which to understand rhubarb-related diseases.
Materials and Methods
Animals
Wistar rats (weighed 200 ± 20 g, aged 7–8 weeks) of either sex were obtained from the
Experimental Animal Centre of Fudan University (Shanghai, China). The rats were housed in
a temperature (25 ± 2◦C) and moisture (55 ± 10%) controlled room, exposed to a
controlled 12-h light/dark cycle, and given ad libitum access to rodent
lab diet and water. All animal experiments were performed in accordance with the
guidelines for use of experimental animals established by Shanghai Jiao Tong
University.The rats acclimated to their environmental conditions for 4 days, and then they were
randomly divided into two groups of eight. Group 1 (control group) received distilled
water only (10 ml/kg, p.o.) during the whole experiment. Group 2 (model group) was
intragastrically given rhubarb (Radix et Rhizoma Rhei extract, 1 g/ml) at 10 ml/kg twice a
day for 10 days.
Sample collection and DNA extraction
Three or four fecal pellets (about 1 g) per rat were directly collected from the anus
into sterile plastic tubes and stored at −20°C immediately. Fecal pellets were collected
before and after inducement. After 10 days of inducement, rats were killed by
decapitation, and samples of bowel (duodenum, D; jejunum, J; ileum, I; cecum, C; proximal
colon, PC; distal colon, DC ; rectum, R) were taken from 16 rats.The intestinal samples were infused and washed with 10 volume of sterile 0.05 M PBS (pH
7.4). The suspension was centrifuged at 300 × g for 6 min, and the supernatant was
transferred to a tube. To form a mixed sample, we mixed the supernatants of different
intestinal parts. The fecal samples (about 0.2 g) were suspended in 1 ml sterile 0.05 M
PBS (pH 7.4) followed by infusion and vortexing twice. After centrifugation at 200 × g to
remove coarse particles, the supernatants were combined. The cells in the supernatant of
feces or intestine were collected and washed twice with PBS by centrifugation at 10,000 ×
g for 6 min, and the total DNA was isolated following the extraction protocol as described
previously [16]. The DNA was checked for integrity
by electrophoretic analysis on 1% agarose gel (Agarose LE, MDBio, Inc., Taipei, Taiwan)
(compared with size-known Hind III digested bacteriophage λ DNA, Tiangen, Inc., Beijing,
China).
ERIC-PCR fingerprint
ERIC-PCR was performed as previously described [16]. ERIC primers (ERIC1R, 5′-ATG TAA GCT CCT GGG GAT TCAC-3′; ERIC2,
5′-AAG TAA GTG ACT GGG GTG AGCG-3′) were used. PCR products were resolved by
electrophoresis in 2% agarose gel containing 0.5 µg/ml ethidium bromide
and visualized under UV light with Tannon GIS2010 Image System Ver. 3.73 (Tanon, Inc.,
Shanghai, China). The size and quantity of the amplified fragments were determined using 1
kb Plus DNA Makers (Tiangen, Inc., Beijing, China).
Cloning procedures
Gel slices containing the individual signature DNA bands were excised and purified using
a commercial gel extraction kit (Qiagen, Valencia, CA). The purified fragments were
ligated with PMD18-T vector (Takara, Dalian, China) and transformed into
E. coli JM109 Cells (Takara, Dalian, China). Cloned
gene fragment was reamplified with M13 forward (5′-CGCCAGGGTTTTCCCAGTCACGAC-3′) and
reverse (5′-AGCGGATAACAATTTCACACAGGA-3′) primers and selected for sequencing (Invitrogen,
Shanghai, China). The sequences were analyzed with the BLAST program at the NCBI website
(http://www.ncbi.nlm.nih.gov/blast).
Data analysis
The bands on the gel were transformed into data sets by the Gel Compare function of
Tannon GIS2010 Image System Ver. 3.73. Furthermore, Sorenson’s pairwise similarity
coefficient (Cs) [8, 11] and the Shannon Index (H’) [8, 11, 21] were employed to measure the similarities of composition or distribution
diversities of microbial ecosystems, although each ERIC-PCR band does not have to stand
for one individual bacterial species. In order to identify the effect of different
parameters on discriminating between normal and rhubarb-exposed rats, discriminant
analysis was performed and evaluated using the SPSS version 11.5 software (Statistical
Package for the Social Sciences, SPSS Inc., Chicago, IL, USA). Results are presented as
means ± SEM. Statistical significance was determined using paired-samples
t-test or ANOVA, where appropriate. Values with
P<0.05 were considered significant.
Results
ERIC-PCR profiles of feces and the intestinal tract in normal rats
The PCR products amplified with ERIC primers yielded 8–13 bands mainly ranging in size
from 250 to 2,000 bp in fecal, large bowel (proximal colon, distal colon, rectum), and
cecum samples, while only 0–5 bands were found in the small bowel (duodenum, jejunum,
ileum) samples (Figs. 1A and B). Comparison of feces and different bowel sections by calculation of the Cs
obtained from ERIC-PCR revealed that there were marked differences in fecal bacterial
composition with the cecum, proximal colon, distal colon, and rectum, as their
similarities ranged from 62% to 67% (Table
1), although the Shannon indexes of these samples were not obviously altered
(Fig. 2c). As few microbes exit in the small bowel, the diversities (H’) of
these microbial communities were low, and the similarity values for feces were lower. To
better understand the differences in bacterial population between feces and the intestinal
tract, a mixture including small bowel, large bowel, and cecum samples was analyzed, and
the bacterial population of the mixture was found to be different from that of feces,
although the similarities in the bacterial populations of the different bowel sections
compared with those of feces paralleled with those of the mixture (Table 1).
Fig. 1.
Electrophoresis profiles of ERIC-PCR fingerprinting for feces and different
intestinal sites of rhubarb-exposed (A) and normal (B) rats. 1, fecal sample; 2,
mixture of intestinal samples; 3, rectum sample; 4, distal colon sample; 5, proximal
colon sample; 6, cecum sample; 7, ileum sample; 8, jejunum sample; 9, duodenum
sample; C, control; M, 1kb Plus ladder
Table 1.
Cs matrix of ERIC-PCR fingerprint obtained from feces and different intestinal
sites in normal rat (n=8)
Sample
Cs% ± SD%
Fecal
Intestinal mixture
Rectum
Distal colon
Proximal colon
Caecum
Ileum
Jejunum
Intestinal mixture
61.98 ± 12.52
Rectum
64.90 ± 8.63
61.03 ± 11.78
Distal colon
63.44 ± 11.66
62.48 ± 7.92
68.46 ± 9.54
Proximal colon
63.04 ± 17.48
70.84 ± 11.29
72.00 ± 10.90
88.40 ± 8.28
Caecum
66.74 ± 10.57
60.55 ± 13.96
64.38 ± 13.99
65.23 ± 10.19
71.43 ± 13.22
Ileum
16.58 ± 18.02
20.09 ± 23.17
22.55 ± 27.69
20.09 ± 23.77
22.23 ± 24.58
23.61 ± 25.33
Jejunum
10.62 ± 15.29
9.26 ± 15.72
7.67 ± 14.52
8.40 ± 11.67
10.28 ± 15.35
9.03 ± 18.29
42.50 ± 49.50
Duodenum
6.25 ± 17.68
0
5.00 ± 14.14
2.50 ± 7.07
2.50 ± 7.07
1.92 ± 5.44
37.50 ± 51.75
62.50 ± 51.75
Fig. 2.
Net integral area (a), abundance of the 380 bp product (b) and Shannon index (c) of
ERIC-PCR fingerprinting of different samples in the control and model groups after
inducement. *P<0.05, **P<0.01, paired
samples t-test, contrasted with the control group. F, fecal sample;
M, mix of intestinal samples; R, rectum sample; DC, distal colon sample; PC,
proximal colon sample; C, cecum sample; I, ileum sample; J, jejunum sample; D,
duodenum sample.
Electrophoresis profiles of ERIC-PCR fingerprinting for feces and different
intestinal sites of rhubarb-exposed (A) and normal (B) rats. 1, fecal sample; 2,
mixture of intestinal samples; 3, rectum sample; 4, distal colon sample; 5, proximal
colon sample; 6, cecum sample; 7, ileum sample; 8, jejunum sample; 9, duodenum
sample; C, control; M, 1kb Plus ladderNet integral area (a), abundance of the 380 bp product (b) and Shannon index (c) of
ERIC-PCR fingerprinting of different samples in the control and model groups after
inducement. *P<0.05, **P<0.01, paired
samples t-test, contrasted with the control group. F, fecal sample;
M, mix of intestinal samples; R, rectum sample; DC, distal colon sample; PC,
proximal colon sample; C, cecum sample; I, ileum sample; J, jejunum sample; D,
duodenum sample.
Alteration of bacterial composition in feces and the intestinal tract of
rhubarb-exposed rats
To monitor the changes in the intestinal microbiota in response to rhubarb, ERIC-PCR
fingerprints obtained from the feces collected before and after inducement were compared.
The diversity (H’) of the rhubarb-exposed rats was significantly
decreased after inducement, and a significant increase in abundance and net integral area
of a 380 bp product was observed (P<0.05), while no obvious changes in
these parameters were shown in normal rats (Fig.
3). Moreover, the similarity before and after inducement of rhubarb-exposed rats was
significantly decreased (45.38 ± 15.52%) compared with the case in normal rats (85.70 ±
5.77%, P<0.01), which suggested that the composition of the microbiota
in the model rats was altered.
Fig. 3.
Net integral area (a), abundance of the 380 bp product (b) and Shannon index (c) in
fecal samples before and after inducement in the control and model groups. *
P<0.05, ** P<0.01, paired Samples
t-test, contrasted with before administration.
Net integral area (a), abundance of the 380 bp product (b) and Shannon index (c) in
fecal samples before and after inducement in the control and model groups. *
P<0.05, ** P<0.01, paired Samples
t-test, contrasted with before administration.In accordance with this, comparative ERIC-PCR profiles obtained from bowel sections also
showed an increase in abundance and net integral area of the 380 bp product in
rhubarb-exposed rats, especially in the ileum section (P<0.05 and
P<0.01, Figs. 2a and b).
The Shannon index (H’) for the ileum in the rhubarb-exposed rats was also
significantly raised, and its similarity with feces, the large bowel, and the cecum was
correspondingly increased, demonstrating that there are more microbes in the proximal
bowel of the model rats.The bowel mixtures of the rhubarb-exposed rats were also analyzed and compared to feces
as in the case of the normal group case. As shown in Table 2, the similarity between mixtures and feces was only 63.65 ± 8.94%,
indicating a difference in bacteria composition between the intestinal tract and
feces.
Table 2.
Cs matrix of ERIC-PCR fingerprints obtained from feces and different intestinal
sites in model rat (n=8)
Sample
Cs% ± SD%
Fecal
Intestinal mix
Rectum
Distal colon
Proximal colon
Caecum
Ileum
Jejunum
Intestinal mixture
63.65 ± 8.94
Rectum
59.66 ± 9.64
69.64 ± 10.70
Distal colon
60.26 ± 9.34
69.90 ± 20.45
73.07 ± 12.40
Proximal colon
52.93 ± 7.58
68.39 ± 21.57
72.16 ± 18.56
77.16 ± 16.57
Caecum
53.36 ± 11.17
67.25 ± 13.99
69.63 ± 12.08
60.56 ± 12.44
63.97 ± 5.37
Ileum
39.43 ± 12.84
45.20 ± 23.67
44.26 ± 20.32
50.24 ± 17.01
49.04 ± 20.00
57.07 ± 20.78
Jejunum
10.93 ± 15.30
26.64 ± 27.69
18.69 ± 18.91
21.54 ± 20.13
25.21 ± 25.40
27.13 ± 28.02
36.78 ± 38.49
Duodenum
7.55 ± 16.63
13.33 ± 25.70
9.63 ± 18.41
13.16 ± 24.36
12.53 ± 23.24
14.18 ± 27.28
17.76 ± 36.35
63.09 ± 43.47
Cloned sequence of the 380 bp product
The fragments of the 380 bp product were purified and ligated into PMD18-T vectors and
transformed into E. coli JM109 Cells. Forty clones
originating from four rhubarb-treated rats were analyzed, and similarity searches of the
GenBank database were performed using BLAST in an attempt to identify known homologous
sequences for the cloned fragments. The results showed that there were 10 different
fragments in these clones, and one was found to share 70–99% homology at the nucleic acid
level with regions of the Bacteroides genome, especially
Bacteroides vulgatus ATCC 8482. Two sequences were found to share 74%
homology with regions of the Salmonella enterica subsp genome, and two
were found to share 80% homology with regions of the Uncultured bacterium clone
LM0ABA36ZH10RM1 sequence and synchronously 70–75% homology with regions of the
Bacteroides genome. For the other fragments, however, no significant
hit was found. This might indicate that they derived either from an unknown bacterium or a
known bacterium that is poorly understood at the genomic level.
Discriminant analysis of normal and rhubarb-exposed rats
To clarify the effect of parameters (Shannon index, net integral area, and abundance of
the 380 bp product) on discriminating between normal and rhubarb-exposed rats, we
conducted discriminant analysis using the SPSS software. The Canonical Discriminant
Function Formulae with three parameters of feces, each parameter of feces, and different
bowel sections were determined respectively. A coefficient of more than zero was
considered to indicate the model animal status; otherwise, the status was considered to be
normal. The validity rates of the formulae were 81.3, 100, 93.8, and 87.5%, respectively
(Table 3). Among the feces and different bowel sections, the ileum was significantly
contributed to discriminating between normal and model rats
(P<0.05).
Table 3.
Canonical Discriminant Function Formulae determined by Discriminant Analysis
using the SPSS software
Parameter
Canonical Discriminant Function Formulae
Validity Rate (%)
Fecal sample
X = −9.345−0.002N+0.245A+4.095H †
81.30%
Net integral area of 380bp
X =
−1.462+0.003F+0.001M+0.003DC−0.005PC+0.004I+0.016J−0.007D ‡
100%
Abundance of 380bp
X =
−1.822+0.129F−0.078M−0.017R+0.061DC−0.073PC+0.055C+0.087I−0.034J+0.175D
‡
93.80%
Shannon’s Index
X =
−19.614+0.416F+4.658M+2.870R−0.370DC+0.630PC+0.453C+1.512I−0.221J+0.205D
‡
87.50%
† N- Net integral area of product 380bp in feces; A- Abundance of product 380bp in
feces; H- Shannon's Index in feces. ‡ F-Fecal sample; M-Mix of intestinal samples;
R-Rectum; DC-Distal colon; PC-Proximal colon; C-Caecum; I-Ileum; J-Jejunum;
D-Duodenum.
† N- Net integral area of product 380bp in feces; A- Abundance of product 380bp in
feces; H- Shannon's Index in feces. ‡ F-Fecal sample; M-Mix of intestinal samples;
R-Rectum; DC-Distal colon; PC-Proximal colon; C-Caecum; I-Ileum; J-Jejunum;
D-Duodenum.
Discussion
Molecular biological techniques have enabled a good assessment of the microbiota
composition and could provide an opportunity to determine the compositions of different
sites of the gut. They are also useful tools for comparing the bacterial composition
associated with the development of intestinal diseases, as they might provide clues to
identity gut residents involved in the pathogenesis of these diseases and clarify the
characteristics of disease models [12, 15]. ERIC-PCR is a rapid and highly discriminating method
and has implications in monitoring the effects of various known factors such as dietary
change, stress, exercise, age, drug treatment, and disease on the complex intestinal
microbiota. It is highly reproducible when it is used to examine the status of the
intestinal microbiota in rats [16, 17]. In our study, the Cs for the PCRs from triplicate
DNA extractions was above 90%, and that for triplicate PCRs from the same DNA extraction was
higher than 95%. However, due to interindividual variation between the rats, there was
considerable variation of ERIC-PCR profiles within groups, in which only approximately 50%
similarity was seen.The inducement with rhubarb appeared to alter the balance of the microbial ecosystem and
ultimately resulted in both increases and decreases in the abundances of various species in
different gastrointestinal locations. These changes may be explained by antibacterial and
purgative activities of rhubarb. Previous studies have demonstrated that a 380 bp product
showed a significant increase in fecal ERIC-PCR fingerprints of spleen (Pi)-deficient rats
induced with rhubarb or Folium Sennae [17]. In the present study, this change was also detected in the intestinal tract.
As the 380 bp product was also found in normal rats, we suggested that it may belong to the
resident gut microbiota and act as an opportunistic pathogen under favorable conditions. The
results of cloning indicated that it had some relationship with
Bacteroides, Salmonella, or an uncultured bacterium.
Bacteroides species largely exist in hosts and are significant with
respect to host health. However, they are also pathogens conditioned to make the host ill
when the microbial balance of the host body is changed [29]. The genus Salmonella belongs to the family
Enterobacteriaceae, and many of its strains are important human and
animal gastrointestinal pathogens [6].Site-specific colonization in the gastrointestinal tract may be contributory to the
etiology of some diseases of the intestine. This may be one of the pathogeneses of the
rhubarb animal model. More bacterial diversity was found in the ileum of rhubarb-exposed
rats, indicating that small intestinal bacterial overgrowth (SIBO) may have been created by
the inclusion of rhubarb. SIBO refers to a condition in which abnormally large numbers of
anaerobic bacteria are present in the small intestine, and patients with SIBO typically
complain of diarrhea, bloating, and some symptoms induced by malabsorption and dysfunction
of the intestinal transit [18]. Anything that
interferes with the normal muscular activity in the small intestine can result in SIBO.
Simply stated, any condition that interferes with muscular activity in the small intestine
allows the bacteria to stay longer and multiply in the small intestine. The lack of muscular
activity also may allow bacteria to spread backwards from the colon and into the small
intestine [10].A large number of studies have been performed to investigate fecal bacterial composition
and changes because of their accessibility. However, its composition and changes have been
demonstrated to differ from those of the intestinal mucosa in humans, pigs, and mice [5, 13, 19, 31]. Our data
indicated that a large variance in bacterial composition existed between feces and different
sections of the intestinal tract in both normal and model rats. Moreover, the fecal
microbial composition did not correspond to that of an intestinal mixture, with the
similarity being 60%.
Authors: R X Wei; F J Ye; F He; Q Song; X P Xiong; W L Yang; X Gang; J W Hu; B Hu; H Y Xu; L Li; H H Liu; X Y Zeng; L Chen; B Kang; C C Han Journal: Poult Sci Date: 2020-12-24 Impact factor: 3.352
Authors: Ana Agustí; Maria P García-Pardo; Inmaculada López-Almela; Isabel Campillo; Michael Maes; Marina Romaní-Pérez; Yolanda Sanz Journal: Front Neurosci Date: 2018-03-16 Impact factor: 4.677