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Du et al. Gut Pathog (2015) 7:32
DOI 10.1186/s13099-015-0080-2
RESEARCH
Development of gut inflammation
in mice colonized with mucosa-associated
bacteria from patients with ulcerative colitis
Zhengyu Du1,2, Tomas Hudcovic2, Jakub Mrazek3, Hana Kozakova2, Dagmar Srutkova2, Martin Schwarzer2,
Helena Tlaskalova‑Hogenova1, Martin Kostovcik1 and Miloslav Kverka1,4*
Abstract
Background: Disturbances in the intestinal microbial community (i.e. dysbiosis) or presence of the microbes with
deleterious effects on colonic mucosa has been linked to the pathogenesis of inflammatory bowel diseases. However
the role of microbiota in induction and progression of ulcerative colitis (UC) has not yet been fully elucidated.
Methods: Three lines of human microbiota‑associated (HMA) mice were established by gavage of colon biopsy
from three patients with active UC. The shift in microbial community during its transferring from humans to mice was
analyzed by next‑generation sequencing using Illumina MiSeq sequencer. Spontaneous or dextran sulfate sodium
(DSS)‑induced colitis and microbiota composition profiling in germ‑free mice and HMA mice over 3–4 generations
were assessed to decipher the features of the distinctive and crucial events occurring during microbial colonization
and animal reproduction.
Results: None of the HMA mice developed colitis spontaneously. When treated with DSS, mice in F4 generation
of one line of colonized mice (aHMA) developed colitis. Compared to the DSS‑resistant earlier generations of aHMA
mice, the F4 generation have increased abundance of Clostridium difficile and decrease abundance of C. symbiosum in
their cecum contents measured by denaturing gradient gel electrophoresis and DNA sequencing.
Conclusion: In our study, mucosa‑associated microbes of UC patients were not able to induce spontaneous colitis in
gnotobiotic BALB/c mice but they were able to increase the susceptibility to DSS‑induced colitis, once the potentially
deleterious microbes found a suitable niche.
Keywords: Dysbiosis, Microbiota, Germ‑free mice, Ulcerative colitis
© 2015 Du et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided
you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate
if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/
zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Background
Crohn’s disease (CD) and ulcerative colitis (UC), the two
major types of inflammatory bowel disease (IBD), are
characterized by chronic relapsing inflammation of the
gastrointestinal tract. This inflammation is a result of an
aberrant immune response to antigens of resident gut
microbiota [1, 2]. In spite of intensive research, however,
the underlying mechanisms are still not fully elucidated.
It has been proposed that either imbalances in intestinal
microbiota (dysbiosis) or presence of commensal bacteria with increased virulence could both cause excessive
immune response to microbiota by penetrating through
the mucosal barrier and stimulating local and systemic
immunity [3–5].
The gut microbiota ecology in UC patients is significantly different from the microbiota in healthy subjects,
with typical reduction of diversity among major anaerobic species [6–8]. Transfer of this luminal dysbiotic
microbial community to the germ-free mice renders
them more susceptible to experimentally-induced intestinal inflammation than similar transfer from healthy
subjects [9]. Due to the close contact with gut mucosa,
the adherent microbes may be even more important
Open Access
Gut Pathogens
*Correspondence: kverka@biomed.cas.cz
1 Institute of Microbiology, The Czech Academy of Sciences,
Prague, Czech Republic
Full list of author information is available at the end of the article
Page 2 of 14Du et al. Gut Pathog (2015) 7:32
for disease development. Dominant species of mucosaassociated bacteria are significantly different from those
found in feces [10], and patients with UC have more
bacteria attached to the epithelial surfaces than healthy
individuals [11, 12]. But whether these alterations are
cause or a result of the intestinal inflammation is still not
entirely clear.
To study these mechanisms and to uncover the participation of bacteria in the development of inflammatory
diseases, microbiota analysis is not sufficient and gnotobiology has to be employed. In contrast to established
human disease, host-microbe interactions during early
stages of the disease development can be studied by using
animal models of inflammatory diseases in gnotobiotic conditions (i.e. in germ-free or artificially colonized
animals with known microbes). In our previous experiments, acute intestinal inflammation induced by dextran
sulfate sodium (DSS) was milder in germ-free (GF) mice
compared to normally colonized mice [13], and the mode
and timing of the colonization with microbiota modified
the future immune phenotype of the host [14].
Since the composition and metabolic activities of intestinal microbiota of experimental animals are different
from that of human gut microbiota [15], microbes relevant to the human disease could be missed by using animal models. To overcome this issue, GF animals can be
colonized with human microbiota. These humanized or
human microbiota-associated (HMA) animals are capable of maintaining the bacterial community of the human
gut, thus keeping microbiota composition and its metabolic activities similar to those of the human intestine
[16, 17]. Therefore, gnotobiotic animals can be used to
cultivate bacteria that are uncultivable by most conventional methods [18].
In this study, three lines of HMA mice were created
by colonization of the GF mice with bacteria present in
colonic biopsies from three patients with active UC. Our
aim was to test whether the mucosa-associated bacteria
derived from UC patients could induce spontaneous colitis
or render the mice more sensitive to DSS-induced colitis.
The composition of bacterial community in cecum content of HMA mice was monitored for several generations
to understand its dynamics with respect to colonization
at adult age (parental generation) or neonatal mother-tooffspring (filial generations) mode of colonization.
Results
The inter‑individual variability in biopsy samples
To measure the inter-individual differences among biopsy
lysates, we estimated the beta diversity metrics using
unweighted (qualitative) and weighted (quantitative)
UniFrac. This qualitative analysis showed that biopsy b
is significantly different from biopsy a and biopsy c and
biopsy c was not significantly different from biopsy a.
However, there were no differences among samples in
quantitative analysis of beta diversity (Table 1). This suggests that abundances of major bacterial taxa are similar
among all three biopsy samples and low abundance species contributed to the difference between biopsy b and
biopsy a or biopsy c.
The diversity of microbiota is decreased after the
colonization
GF mice were successfully colonized with bacteria from
biopsies of three patients with active UC (Fig.  1a, c).
Microbial community in samples from human biopsies is
characterized by dominance of one or two bacterial orders,
Lactobacillales and Enterobacteriales, which comprise
more than 80 % of identified reads from each community.
After the transfer of microbiota into the mice, composition
of communities was shifted, with decrease in abundance of
Lactobacillales compensated with an increase in other Firmicutes, namely with Clostridiales. Moreover, in general
abundance distribution of bacterial orders in communities
after the transplant was more evenly distributed but total
species richness decreased during transfer from humans
to mice (Fig.  1b). This decrease may be caused either by
partial unsuitability of recipient niche for the bacterial
community found in the biopsy samples or by dying of
less abundant species during the transfer from human to
mice. The presence and viability of multiple anaerobic and
aerobic bacteria in biopsies and cecum of parental generation of HMA was confirmed by cultivation-based methods
(Table 2) [19–21].
Colonization of GF mice with mucosa‑associated bacteria
from IBD patients does not lead to spontaneous colitis
To test if bacteria from the UC biopsies can induce gut
inflammation, each mouse was evaluated for colitis.
Table 1 Comparison of microbiota composition in biopsies
Biopsies show significant inter-individual differences only in presence of
low abundance taxa as showed by qualitative (unweighted UniFrac) but
not abundance-aware (weighted UniFrac) quantitative analysis. Statistically
significant results are marked with asterisk
Sample 1 Sample 2 P P (Bonferroni
corrected)
Unweighted UniFrac
Biopsy c Biopsy a 0.06 0.90
Biopsy c Biopsy b 0.00* ≤0.01*
Biopsy a Biopsy b 0.00* ≤0.01*
Weighted UniFrac
Biopsy c Biopsy a 0.93 1.00
Biopsy c Biopsy b 0.42 1.00
Biopsy a Biopsy b 0.70 1.00
Page 3 of 14Du et al. Gut Pathog (2015) 7:32
Compared to water-treated GF mice, which remained
completely healthy, the clinical colitis score (CCS) and
myeloperoxidase (MPO) were significantly higher in
water-treated parental and first filial generation (F1) of
mice colonized with biopsy a (aHMA) (Fig. 2). Increase in
MPO was also detected in water-treated parental bHMA
mice, but no histological signs of colitis were observed in
any group of water-treated HMA mice (Fig. 2c). Similar
results were found in parental cHMA mice, which did
not developed colitis either spontaneously or after DSStreatment. The cHMA line of mice did not breed beyond
parental generation and died out. This suggests that the
mucosa-associated microbiota from patients with active
UC cannot induce spontaneous colitis in mice, although
the process of artificial colonization may induces slight
inflammation of colonic mucosa.
aHMA mice exhibited an increase in DSS‑colitis sensitivity
whereas bHMA mice failed to develop colitis
When treated with DSS, GF mice developed milder colitis than conventional (CV) mice, suggesting that the presence of microbiota increased the susceptibility of mice to
colitis. There was a significant increase in CCS and MPO
in GF, CV, F1 aHMA, F4 aHMA and F3 bHMA after DSS
treatment, compared to their littermates treated with
water (Fig.  2a, b). Compared to F1 aHMA mice, CCS
and MPO value were higher in F4 aHMA mice though
the differences in MPO were not statistically significant.
The typical histopathologic picture of DSS-induced colitis was observed only in GF mice (mild to medium), F4
aHMA mice (moderate) and CV mice (very severe) with
a characteristic massive loss of goblet cells and crypts,
ulceration and inflammatory infiltrate in the lamina
Fig. 1 Microbiota composition in colonic biopsies of three patients with active ulcerative colitis and cecum content of parental HMA mice, a
as measured by 16S sequencing. The composition of each sample is based on the RDP taxonomic assignment of the 16S rDNA sequences. The
phylum and the genus level are shown for the most abundant bacterial groups. b The Chao1 diversity index of human biopsy samples (a, b and c)
was compared with the diversity index of cecum contents of relevant mice (healthy aHMA, bHMA and cHMA) by two‑tailed paired Student’s t test.
The black line represent median and the red lines connect the related samples. c DGGE profiles of 16 s rRNA genes amplified from colonic biopsy
lysates and cecum content of biopsy‑colonized mice. Excised and successfully sequenced bands are identified with red numbers (1–9), see Table 1
for identification
Page 4 of 14Du et al. Gut Pathog (2015) 7:32
propria and submucosa (Fig. 2c). The increase in macroand microscopic signs of colitis in aHMA mice shows an
increase in DSS-colitis sensitivity over the generations.
Interestingly both MPO values and CCS in water-treated
aHMA mice showed a steady decline tendency over generations. In contrast to aHMA mice, bHMA mice failed
to develop colitis in all groups of mice throughout the
generations (Fig. 2a–c).
Production of proinflammatory and regulatory cytokines is
increased in colitic F4 aHMA mice
The production of proinflammatory cytokines Tumor
necrosis factor (TNF)-α and Interferon (IFN)-γ in spleen
cell suspension was higher in DSS-treated F4 aHMA
mice than that in their healthy littermates (Fig.  3a, b).
Higher production of TNF-α was also found in DSStreated GF or conventional mice, but the levels of IFN-γ
were not changed. Interleukin (IL)-10, known to regulate immune responses [22], was significantly higher in
DSS-treated F4 aHMA mice when compared to their
water-treated littermates (Fig. 3c). Interestingly, contrary
to F4 mice, production of IL-10 was significantly higher
in water-treated GF mice than in DSS-treated mice. On
the other hand, no significant differences in cytokines
production were determined between DSS-treated and
water-treated bHMA mice. The differences in cytokine
production between DSS-treated and untreated mice are,
therefore, only apparent in mice with clear phenotype of
DSS-induced colitis, such as DSS-treated GF, F4 aHMA
and CV mice. These results suggest that changes in the
cytokine pattern reflect more the presence of colitis in
DSS-treated animals than the differences in microbiota
that colonize the mice.
HMA mice in the later generation exhibited higher
biodiversity in intestinal bacterial community
Shannon-Wiener index was used to compare the diversity
of microbiota in cecum samples from HMA mice. Significantly higher diversity was measured in F4 aHMA mice
and F3 bHMA mice compared to their previous generations (aHMA: F1 = 1.03 ± 0.03 vs F4 = 1.18 ± 0.06,
p < 0.05; bHMA: F1 = 1.12 ± 0.03 vs F3 = 1.35 ± 0.09,
p  <  0.05). Interestingly, there was no significant difference in diversity between water-treated and DSS-treated
HMA mice. Four clusters were roughly generated in
cecum samples in each line of HMA mice and the samples from the same generation and treatment clustered
well together (Figs. 4b, 5b).
A predominance of colitis‑associated Clostridium sp.
was identified in cecum samples of aHMA mice but not
in bHMA mice
Prominent bands from DGGE profiles (Figs.  4, 5) of
PCR amplified DNA from cecum content (Additional
file 1) were identified as Clostridium sp. and Blautia sp.
in both aHMA and bHMA mice (Table  3). Compared
with bHMA mice, in which DSS-induced colitis was not
established, aHMA mice conserved higher richness of
Clostridium species in their cecum samples (Table  1).
Substantial amount of C. difficile and C. aurantibutyricum were identified in F4 aHMA mice, in which DSScolitis was successfully developed. These mice have
substantially lower abundance of C. symbiosum compared to healthy F1 aHMA (Fig. 4a), suggesting that this
microbe has not been successfully transferred to the later
generation of aHMA mice.
Discussion
Inflammation in patients with UC is usually confined to
large intestine, characterized by dysbiosis [23]. When
transferred to GF mice, this dysbiotic microbial community in UC patients increase susceptibility to DSSinduced colitis [9]. Luminal microbes forming feces have
often only indirect contact with inflamed colon mucosa,
so mucosa-associated bacteria are more likely to be
Table 2 Bacteria in  the parental HMA mice and  biopsy
lysates used for  their colonization, as  identified by  enzymatic tests and microscopy
Aerobic bacteria Anaerobic bacteria
Biopsy a Klebsiella oxytoca
Proteus vulgaris
Streptococcus parvulus
Actinomyces naeslundii
Fusobacterium necrogenes/
mortiferum
P aHMA mice Enterococcus faecalis
Enterococcus rafinosus
Enterococcus faecium
Streptococcus parvulus
Klebsiella pneumonie
Escherichia coli
Proteus vulgaris
Veillonella parvula
Bifidobacterium breve
Bifidobaterium sp.
Bacteroides capillosus
Actinomyces israelli
Unidentified G + cocci‑rods
Unidentified G + rods
Biopsy b Escherichia coli
Klebsiella pneumonie
Enterococcus flavescens
Enterococcus casseliflavus
Actinomyces naeslundii
Veillonella parvula
Bifidobacterium sp.
P bHMA mice Enterococcus casseliflavus
Enterococcus faecalis
Enterococcus sp.
Klebsiella pneumonie
Citrobacter amalonaticus
Escherichia coli
Veillonella parvula
Eubacterium lentum
Bifidobacterium sp.
Actinomyces israelli
Lactobacillus sp.
Biopsy c Streptococcus sp.
Enterococcus faecium
Enterococcus raffinossus
Lactobacillus jensenii
P cHMA mice Yeast
Enteococcus faecium
Enterococcus raffinossus
Streptococcus parvulus
Clostridium inocuum
Bifidobacterium sp.
Unidentified G + spore‑
forming rods
Page 5 of 14Du et al. Gut Pathog (2015) 7:32
involved in UC due to their close proximity to the host
epithelium. In healthy individuals, gut bacteria are usually separated from the intestinal mucosa by thick layers
of mucus [24], thus even methods as sensitive as quantitative (q) PCR or Fluorescence in  situ hybridization
(FISH) is not able to detect any bacteria in most biopsies
from healthy subjects [11, 25].
In this study, we found that major bacterial taxa are
similar among all three biopsy samples we used for colonization and only low abundance species differ among
biopsies from UC patients (Table  1). When the microbial community is transferred from human biopsies to
GF mice, the species richness of this community is significantly reduced (Fig. 1b). This may be caused either by
partial unsuitability of recipient niche for the bacterial
community or by dying of less abundant species during the transfer from human to mice. This methodical
difficulty could not be fully excluded even when freshly
collected biopsies were used and their contact with oxygen in the air was minimized.
Colonization of GF mice with mucosa-associated
microbiota from UC patient a (aHMA mice) increased
CCS and MPO activity without damage to colon mucosa.
CCS and MPO gradually decreased in subsequent generations, which support the notion that lack of exposure
to microorganism in the early life could interfere with
the development of immune system and permanently
alter important immune functions [14]. Therefore, the
increase in MPO and presence of pasty stool in parental
aHMA mice appears to be a result of the poorly regulated host-microbe interaction in the ex-GF mice. The
absence of mucosal damage in healthy HMA mice suggests that the mucosa-associated microbes from patients
with active UC do not induce colitis when transferred to
Fig. 2 Macro‑ and microscopic evaluation of DSS induced colitis, as measured by a clinical colitis score, b colonic MPO activity, and c histological
analysis of the mucosal damage of the colon descendens. The values are expressed as mean (bar) value ± standard deviation (whisker). Each bar
represents 4– mice and histology (paraffin‑embedded sections stained with haematoxylin and eosin) is from one mouse showing changes typical
for each group. The numbers represent histological grade and the black bar is 100 µm. *p ≤ 0.05 vs. non‑treated littermates; †p ≤ 0.05, vs. healthy GF
mice; #p ≤ 0.05, vs. DSS‑treated GF mice; ‡p ≤ 0.05, vs. DSS‑treated CV mice; F1/3/4 1st/3rd/4th filial generation, DSS dextran‑sodium sulfate
Page 6 of 14Du et al. Gut Pathog (2015) 7:32
otherwise healthy host. However, this effect cannot be
fully excluded, e.g. if some rare and strongly damaging
microbial communities are transferred, due to the low
number of individual biopsies we tested.
To investigate how the mucosa-associated bacteria increase the sensitivity to colitis, DSS-colitis was
induced in GF, HMA and CV mice. Colitis was successfully induced in GF, F4 aHMA and CV mice with varying severity; mild-moderate in GF mice, moderate in F4
aHMA mice and very severe in CV mice. This is in agreement with our previous study showing that GF mice are
more resistant to acute DSS-induced colitis than CV
mice [13]. The presence of mild colon inflammation in
GF mice suggests that microbiota is not indispensable for colitis development in this model. The absence
of colitis in DSS-treated parental, F1 aHMA, F1 bHMA
and F3 bHMA mice clearly shows that microbiota might
contain certain protective species that actively protected mice from intestinal inflammation. Their presence
would explain the failure to induction of DSS-colitis in
all bHMA mice and in parental and F1 aHMA mice. The
increase in susceptibility to DSS-induced colitis between
F1 and F4 aHMA mice suggests that these protective
bacteria may be lost or that other, potentially harmful
microbes found suitable niche during natural colonization with co-housing. The differences in colitis sensitivity between both lines and different generations also
show, that certain specific microbes, and not the presence of any microbe, is the cause of colitis sensitivity in
F4 aHMA mice. We did not transfer the microbiota from
healthy subjects because we expected that these biopsies
will yield inoculums too low for successful colonization
with complex microbiota [11, 25]. On the other hand, we
cannot exclude that similar effects will be observed also
with mucosa-associated bacteria from healthy subjects.
When we sequenced the bands that were different
between F1 and F4 aHMA, we found disappearance of C.
Symbiosum and appearance of C. difficile. C. symbiosum
Fig. 3 Cytokine production by spleen cells from HMA mice. Each group contained 4–8 mice. a TNF‑α, b IFN‑γ, and c IL‑10 cytokine levels were
measured in supernatant from spleen cells. Cytokine values are expressed as mean ± standard deviation, *p ≤ 0.05 vs. non‑treated littermates;
#p ≤ 0.05, vs. DSS‑treated GF mice
Page 7 of 14Du et al. Gut Pathog (2015) 7:32
(member of the Clostridium cluster XIVa) is the most
abundant bacterium found in human gut mucins, where
it probably protects the mucosa by producing high levels of butyrate [26]. This effect may be responsible for
the resistance of the F1 aHMA mice to the DSS-induced
colitis. Disappearance of C. symbiosum during DSS treatment of F1 aHMA mice could be even partially responsible for the DSS-induced epithelium damage. C. difficile,
on the other hand, may produce toxins that can damage
colon mucosa of infected patients [27]. Indeed, there is
a strong association between UC and colonization with
this bacterium [19, 20], and this association is not limited
only to toxin-producing C. difficile [23]. The close association of C. difficile with colitis may be responsible for the
marked increase in susceptibility to DSS-colitis between
F1 and F4 generations. Since all these microbes could
not be introduced in other way than with the original
biopsy, their appearance on DGGE of F4 aHMA suggests
that they found suitable niche and increased in numbers.
PCR-DGGE can detect only more dominant species,
because its detection limit is between 104 and 108 cfu/ml,
depending on the selected bacterium [28–30]. Reduced
richness of intestinal microbiota is a common feature in
UC patients [7, 31–34]. It is interesting that there is no
significant reduction in biodiversity of microbiota in
cecum samples of DSS-treated HMA mice compared to
their healthy littermates. Taking into account that the
biopsies were taken from patients with active UC, we can
speculate that the bacteria transferred to mice were well
adapted to inflammatory environment.
Intestinal inflammation is associated with impaired
barrier function, which leads to activation of the systemic
immunity and production of pro-inflammatory cytokines
[35, 36]. In fact, this activation is less pronounced in
the mucosal compartment, including mesenteric lymph
nodes, than in systemic one, due to more active inhibitory mechanisms in the gut [37]. This effect is probably
caused by the regulatory mechanisms of the mucosal
immune system [38]. IL-10 is an important anti-inflammatory cytokine that regulate the colonic inflammation
during experimental colitis in the presence of microbiota
[39, 40]. Therefore, an increased IL-10 production in
DSS-treated F4 aHMA mice and DSS-treated CV mice
maybe caused by negative-feedback loop, where immune
a b
Fig. 4 The differences in cecum microbiota of F1 and F4 aHMA mice. a DGGE profiles of 16 s rRNA genes amplified from cecum content of
human biopsy A‑associated mice. Each lane (1–21) represents a DNA sample isolated from cecum content of one mouse. Excised and successfully
sequenced bands are identified with red numbers (8–16), see Table 1 for identification. b Clustering analysis of DGGE banding profiles of cecum
samples. The dendrogram was generated by using the Wards method from a Pearson correlation matrix. The numbers on the nodes indicate the
bootstrap values expressed as percentage from 1000 replications
Page 8 of 14Du et al. Gut Pathog (2015) 7:32
system regulates the inflammation caused by gut barrier breach. The observed decrease in IL-10 production
in DSS-treated GF mice may be caused by the immunological immaturity, indicating that the GF mice do not
have fully developed regulatory mechanisms on a level of
innate and adaptive immunity [41, 42].
Conclusions
In summary, we showed that mucosa-associated bacteria from colonic biopsy of the patients with active UC
can increase sensitivity to DSS-induced colitis, although
not able to induce spontaneous one. The increase in
DSS-induced colitis severity between earlier and later
generations of aHMA, together with the appearance of
C. difficile and disappearance of C symbiosum, suggests
that change in the relationship between these two particular microbes, rather than their presence or absence,
is important for the sensitivity to colitis. Production of
these “humanized” mice using patient’s biopsy and following the fate of bacteria over generations may bring
new insights into host-microbe interaction during intestinal inflammation or in other diseases.
Methods
Patients and biopsy
Biopsy was taken from inflamed sites of colon descendens from three patients during routine endoscopic examination. First patient (a) was 52-year old male, diagnosed
with active UC with shortened colon, caused by a chronic
inflammation. Second patient (b) was a 23-year old male,
diagnosed with very active UC resistant to both mesalasine (5-acetylosalycilic acid) and azathioprine treatment.
Third patient (c) was 28-year old female, diagnosed with
very active UC with numerous ulcers. Immediately after
extraction, the biopsies were transferred to the laboratory in sterile tubes pre-loaded with Schaedler anaerobe
broth (Oxoid Ltd, Cambridge, UK) containing 0.05  %
cysteine-HCl, 10 % glycerol and covered with the layer of
paraffin to preserve anaerobes.
Animals
GF BALB/c mice (8–10  week-old) were maintained in
isolators under sterile conditions, supplied with sterile
water and sterile pellet diet ST-1 (Velaz, Unetice, Czech
Republic) ad  libitum, to keep them free of live bacteria.
a b
Fig. 5 The differences in cecum microbiota of F1 and F3 bHMA mice. a DGGE profiles of 16 s rRNA genes amplified from cecum content of
human biopsy B‑associated mice. Each lane (1–18) represents a DNA sample isolated from cecum content of one mouse. Excised and success‑
fully sequenced bands are identified with numbers (17–24), see Table 1 for identification. b Clustering analysis of DGGE banding profiles of cecum
samples. The dendrogram was generated by using the Wards method from a Pearson correlation matrix. The numbers on the nodes indicate the
bootstrap values expressed as percentage from 1000 replications
Page 9 of 14Du et al. Gut Pathog (2015) 7:32
The conventional (CV) BALB/c mice on the same diet
were regularly checked for the absence of potential pathogens according to an internationally established standard (FELASA).
Human biopsy administration and experimental design
Each human biopsy was homogenized with sterile hand
homogenizer, and 2-month old GF mice were colonized with 0.2 ml of this homogenate in a single gavage,
which were employed as Parental HMA mice. All biopsies were processed immediately after the transport to
the laboratory and under anaerobic conditions until the
gavage. Three months later, parental HMA mice were
divided into three groups; one group was continuing in
breeding for reproduction; one group was used for colitis
induction and the other was used as control against colitis
induced mice. The offsprings of the parental HMA mice
(F1) and the third (F3) and fourth (F4) generations were
again divided into three groups as the parental HMA
mice did. The microbiota composition of the biopsy
homogenate and cecum content of the parental HMA
mice (after 3-month colonization of biopsy homogenate)
Table 3 Phylogenetic affiliation of DNA sequences retrieved from DGGE bands
If the identity of the best match was 97 % or less, two other matches were selected. The sequence number correspond to these in Figs. 1, 4 and 5. (For sequences refer
to Additional file 1)
Sample No GenBank Accession number Best match Identity (%
similarity)
Biopsy a 1 NR121743 Streptococcus lutetiensis 99
P aHMA 2 NR118699 Clostridium innocuum 97
NR044648 Eubacterium tortuosum 91
NR113409 Eubacterium dolichum 90
P aHMA 3 NR119035 Clostridium sphenoides 99
P bHMA 4 NR118729 Clostridium oroticum 98
P bHMA 5 NR041960 Blautia luti 98
P bHMA 6 NR036800 Ruminococcus gnavus 100
Biopsy c 7 NC017960 Enterococcus faecium 98
P cHMA 8 NR119085 Clostridium polysaccharolyticum 97
P cHMA 9 AB971793 Clostridium innocuum 98
F1 aHMA 10 NR044715 Clostridium clostridioforme 96
NR036928 Clostridium hathewayi 96
NR118730 Clostridium symbiosum 96
F1 aHMA 11 NR118730 Clostridium symbiosum 99
F1 aHMA 12 NR119217 Blautia producta 99
F1 aHMA 13 NR041960 Blautia luti 100
F1 aHMA 14 NR118729 Clostridium oroticum 97
NR117142 Eubacterium fissicatena 97
NR104803 Eubacterium contortum 97
F1 aHMA 15 NR118729 Clostridium oroticum 96
NR117147 Eubacterium contortum 96
NR117142 Eubacterium fissicatena 96
F4 aHMA 16 No siginificant similarity found
F4 aHMA 17 NR074454 Clostridium difficile 99
F4 aHMA 18 NR044841 Clostridium aurantibutyricum 98
F1 bHMA 19 NR118729 Clostridium oroticum 98
F1 bHMA 20 NR041960 Blautia luti 98
F1 bHMA 21 NR041960 Blautia luti 100
F1 bHMA 22 NR036800 Ruminococcus gnavus 100
F3 bHMA 23 NR118729 Clostridium oroticum 99
F3 bHMA 24 No siginificant similarity found
F3 bHMA 25 NR118729 Clostridium oroticum 98
F3 bHMA 26 NR118729 Clostridium oroticum 99
Page 10 of 14Du et al. Gut Pathog (2015) 7:32
were analyzed by microscopic and cultivation methods
(see Additional file  1: Table S1) and by next-generation
sequencing (Fig. 1a, b) to analyze the microbiota viability
and changes in microbiota diversity during the transfer
from humans to mice. Colitis was induced in GF, HMA
and CV mice by 7 days lasting exposure to 2.5 % (weight/
volume) dextran sulfate sodium (DSS; Mw = 36–50 kDa;
ICN Biomedicals, Cleveland, OH, USA) in sterile drinking water similarly, as described earlier [13, 43]. Controls
received sterile drinking water. 8-week old mice were
used in all experiments except Parental HMA mice. During the whole duration of these experiments, each line
of HMA mice was kept in separate isolator to avoid any
contamination with other microbes. The cHMA line of
mice did not breed well and it died out shortly after the
experiment with parental generation.
Microbiota analysis by cultivation analysis and microscopy
The presence of live microbes in the biopsy lysate and
in cecum content of the colonized mice was analyzed
by cultivation-dependent methods with subsequent
microscopic and enzymatic tests. Before plating, the
whole cecum of colonized mice was removed and gently vortex in 5  ml of Schaedler broth containing 0.05  %
cysteine-HCl. The samples were cultivated either aerobically using, bovine Blood agar, MRS agar with or without
0.05 % cysteine, Sabouraud agar (all from Oxoid, Hampshire, UK), Endo agar (Merc, Darmstadt, Germany) or
anaerobically on VL blood agar (Imuna-Pharm, Slovak
Republic). Next, the individual colonies were separated,
cultivated and analyzed by microscopy after Gram’s
staining and by detection of their oxidase (PLIVALachema Diagnostika, Brno, Czech Republic) and katalase activity. Subsequently, their enzymatic activity was
determined by oxidative-fermentative test, enterotest,
anaerotest, en-coccustest or PYRtest (all from PLIVALachema Diagnostika, Brno, Czech Republic). The software TNW® (PLIVA-Lachema Diagnostika, Brno, Czech
Republic) was used to identify the individual species of
bacteria (Table 2).
Evaluation of acute colitis
Each mouse was examined on day 8 for stool consistency (solid 0 points, loose stool that do not stick to the
anus 2 points, and 4 points for liquid stools that stick to
the anus) and rectal bleeding (none 0, positive guaiacum
reaction  2 points, and 4 points for gross bleeding), and
the clinical colitis score (CCS) was determined as a mean
of these two parameters.
The colon was removed and its distal third was fixed
in Carnoy’s solution for 30  min, and then transferred
into 96  % ethanol, embedded in paraffin, sectioned at
5 μm transversal sections and stained with haematoxylin
and eosin. Histological grade, ranging from normal (0)
through borderline (0.5) to extreme colitis (3), was calculated by evaluating the degree of epithelium ulceration and infiltration of inflammatory cells in each colon
segment according to a standardized histological scoring
system [43].
Myeloperoxidase (MPO) measurement
The extent of neutrophil infiltration was quantified by
measuring MPO activity in the colon tissue homogenate, as described earlier by Krawisz et  al. [44] with
some modifications. Briefly, 1–2  cm of colon descendens (approximately 50  mg of tissue) was washed in icecold phosphate-buffered saline (PBS) and homogenized
in 1  ml of potassium buffer (0.05  M KH2PO4, 0.05  M
K2HPO4, pH =  6.0). After centrifugation at 12,000g for
30  min 4  °C, the pellet was resuspended in 1  ml 0.5  %
hexadecyltrimethylammoniumbromide (HETAB) in
50 mM potassium buffer (pH = 6.0). Next, samples were
sonificated for 30  s, freeze-thawed three times, sonificated again and centrifuged at 12,000g for 30  min. The
supernatant was used for the measurement of the MPO
activity. All steps of MPO extraction were carried out on
ice.
MPO activity was measured by incubating 100 μl of the
sample with 2.9 ml prewarmed 50 mM phosphate buffer
(pH = 6.0) containing 16.7 % (wt/vol) o-dianisidine and
0.0006 % H2O2 at 37 °C. The reaction kinetics was measured at OD 460 nm for 3 min at 30 s intervals. The MPO
activity is expressed in units (U) per 1 gram of the tissue,
where 1 U equals the change of OD460 of 1 in 1 min.
Measurement of cytokine production
Single-cell suspensions of spleens were prepared by
mashing the tissue and passing the cells through the
70 µm sterile cell strainers (Becton–Dickinson, San Jose,
CA, USA). After the lysis of red blood cells with sterile ACK lysing buffer (0.1  mM EDTA, 150  mM NH4Cl,
10  mM KHCO3), and two washes in complete culture
medium (RPMI 1640 supplemented with 10  % heat
inactivated FCS, 2  mM-glutamine, 100 U/ml penicillin, 100  mg/ml streptomycin), the cells were seeded
at 5 ×  106 cells/500  µl of complete medium per well in
48-well flat bottom plates (Corning; Tewksbury, MA,
USA) and cultivated for 48 h at 37 °C, 5 % CO2 in humidified incubator. The cell supernatant was then used for
determination of IFN-γ, TNF-α and IL-10. The cytokines
were measured by ELISA kit (R&D Systems; Mineapolis,
MN, USA).
DNA isolation
Bacterial DNA was isolated from cecum contents of
HMA mice using ZR fecal Kit™ (Zymo Research, Irvine,
Page 11 of 14Du et al. Gut Pathog (2015) 7:32
CA, USA), according to the manufacturer’s protocol. The
concentration and quality of isolated DNA was assessed
by measuring its absorbance at 260 and 280  nm using
spectrophotometer (NanoDrop Technologies, Inc; Wilmington, DE, USA) and its concentration was adjusted to
10 ng/μl.
Polymerase chain reaction (PCR) and denaturing gradient
gel electrophoresis (DGGE)
The sequences of bacterial 16S rRNA genes were amplified in the DNA isolated from cecum contents of HMA
mice using the universal bacterial primers 338GC and
RP534 in a previously described protocol for PCR
assays (5′-CGC CCG CCG CGC CCC GCG CCC GGC
CCG CCG CCG CCG CCG CAC TCC TAC GGG
AGG CAG CAG-3′) and RP534 (5′-ATT ACC GCG
GCT GCT GG-3′) in a previously described protocol
for PCR assays [45]. Each PCR mixture contained 2 μl
of DNA template, 0.5 μl of each primer (10 μM), 15 μl
of ReadyMix™ Taq PCR Reaction Mix (Sigma-Aldrich,
Steinheim, Germany), and 12 μl of nuclease-free H2O.
Samples were initially denatured at 94 °C for 3 min, followed by 36 cycles of 1 min at 94 °C, 20 s at 61 °C and
40  s at 68  °C with final elongation at 68  °C for 7  min.
Products from PCR were then processed by DGGE
using the DCode™ Universal Mutation Detection System (Bio-Rad Laboratories, Hercules, CA, USA) on 9 %
polyacrylamide gel with 35–60  % denaturing gradient,
as previously described [46]. Gels were stained in 50 ml
of 1× TAE with SYBR Green I dye (0.001 %) for 30 min
and visualized by UV light using the Vilber Lourmat
System (Marne La Vallée, France). Amplicons of interest were cut from the stained polyacrylamide gel by a
sterile scalpel blade. Sterile distilled H2O (100  μl) was
added to the excised gel fragment and subject to centrifugation at 10,000 rpm for 10 min to elute DNA. 1 μl
of this solution was used for amplification with primers FP341 and RP534 under the same PCR program,
as mentioned above. The PCR products were purified
using QIAquick PCR purification kit (Qiagen, Hilden,
Germany) and sequenced using ABI PRISM® BigDye®
Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, Inc, Foster City, CA, USA) with a PCR thermocycler T-personal Combi (Biometra, GmbH, Goettingen,
Germany). Products from sequencing were subsequently purified using BigDye purification kit (Applied
Biosystems Inc) and analyzed on 3100 Avant Genetic
Analyser (Applied Biosystems Inc) in the Institute of
Animal Science sequencing facility (Prague, Czech
Republic). The sequences were compared to those in
the GenBank database using the BLASTn algorithm
[47]. All sequences that did not gave meaningful result
were excluded from this search.
Scoring and analysis of bands
Scanned gels were analyzed with BioNumerics (version 7.1, Applied Maths, Sint-Martens-Latem, Beigium).
Similarity indices of bands was calculated by using Pearson correlation coefficient and displayed graphically as a
dendrogram [48]. The Shannon-Wiener index of diversity was used as a parameter to determine the diversity
of taxa present in microbial communities sampled from
cecum of HMA mice with and without DSS treatment
according to Konstantinov et al. [49].
Next generation sequencing analysis and bioinformatics
For library preparation V3 and V4 region of 16S rRNA
was amplified in triplicate PCR reaction using primer
pair 341F (CCTACGGGNGGCWGCAG) and 806R
(GGACTACHVGGGTWTCTAAT) to utilize to the
maximum read length of employed 2  ×  300 pair-end
sequencing at Illumina MiSeq platform (San Diego, CA,
USA). Double-indexing was applied to allow for demultiplexing of output reads into original samples. Each PCR
reaction was prepared in 25  µl volume using premixed
mastermix (AmpliTaq Gold 360 Master Mix, Thermo
Fisher Scientific, Waltham, MA, USA) and 0.8  µM of
each primer following subsequent cycling conditions: initial denaturation at 95 °C for 3 min following by 35 cycles
of 30 s at 94 °C, 1 min at 55 °C and 75 s at 72 °C with final
extension for 10  min at 72  °C followed by hold at 4  °C.
PCR reactions were checked on agarose gel for presence
of expected product in samples and its absence in negative controls. Next, the triplicates from the same template
reactions were pooled and cleaned using UltraClean htp
96 well PCR clean-up kit (MoBio, Carlsbad, CA, USA).
Concentrations of cleaned samples were measured fluorescently with Quant-iT dsDNA Assay kit (Thermo
Fisher Scientific). Sequencing adapters were ligated to
the PCR amplicons with the help of TruSeq PCR-Free LT
Sample preparation Kit following manufacturer instructions (Illumina, Inc). Next, sample libraries were pooled
in equimolar concentration to produce final library,
which was sequenced on Illumina MiSeq instrument at
Genomics Core Facility, CEITEC (Brno, Czech Republic).
Negative control sample (water) was run through all procedures including DNA extraction, library preparation
and sequencing. Sequencing data were processed using
QIIME 1.8.0 [50]. Forward and reverse reads were joined
to create contigs. Afterwards reads were demultiplexed
in parallel with quality filtering allowing minimal Phred
quality score of Q20 and maximum number of consecutive low quality base calls of 12 due to the nature of lower
quality overlaps of pair-end reads. Resulting reads were
clustered to operational taxonomic units (OTUs) using
UCLUST with 97  % similarity threshold against bacterial 16S reference database Greengenes gg_13_8 release
Page 12 of 14Du et al. Gut Pathog (2015) 7:32
[51, 52]. Singletons were discarded before producing final
dataset. Taxonomic assignment of created OTUs was
performed employing RDP classifier [53]. Finally information about read counts for all OTU clusters from all
samples together with taxonomic information was output
in OTU table. Taxa detected in negative control sample
were screened out based on their relative proportional
abundance. Resampling to the sequencing depth of 8000
reads per sample was performed to allow comparison of
beta diversity measures. The quantitative or qualitative
measures of beta diversity of samples were compared
using weighted or unweighted UniFrac pairwise dissimilarity matrices, respectively [54]. To measure alpha diversity we calculated Chao1 species richness estimators [55].
Raw demultiplexed sequencing data, with sample annotations, were submitted to the Short Read Archive (http://
www.ncbi.nlm.nih.gov/Traces/sra/) under the study
accession number [SRP066136; http://www.ncbi.nlm.nih.
gov/sra/SRP066136].
Statistics
The differences between control group and multiple
experimental groups (GF vs. all other healthy mice,
DSS-treated GF mice vs. all other DSS-treated groups of
mice and DSS-treated CV mice vs. all other DSS-treated
mice) were analyzed with one-way analysis of variance
(ANOVA) with Dunnet’s multiple comparison test. Differences between DSS-treated mice and their healthy
littermates or changes in bacteria biodiversity between
generations were evaluated using an unpaired two-tailed
Student’s t test. Data were expressed as mean ± standard
deviation (SD). Differences were considered statistically
significant at P  <  0.05. GraphPad Prism statistical software (version 5.03, GraphPad Software, Inc. La Jolla, CA,
USA) was used for analyses.
Availability of data and material
The dataset supporting the conclusions of this article is
available in the Short Read Archive repository, [SRP066136;
http://www.ncbi.nlm.nih.gov/sra/SRP066136].
Abbreviations
aHMA: mice associated with human microbiota from biopsy a; bHMA: mice
associated with human microbiota from biopsy b; cHMA: mice associ‑
ated with human microbiota from biopsy c; CCS: clinical colitis score; CD:
Crohn’s disease; CV: conventional (i.e. colonized with normal commensal
microbiota); DGGE: denaturing gradient gel electrophoresis; DSS: dextran
sulfate sodium; F1/3/4: 1st, 3rd and 4th filial generation; FISH: fluorescence
in situ hybridization; GF: germ‑free; HMA: human microbiota‑associated; IBD:
inflammatory bowel diseases; IFN‑γ: interferon‑γ; IL‑10: interleukin‑10; MPO:
Additional file
Additional file 1. The sequences of excised DGGE bands.
myeloperoxidase; OTUs: operational taxonomic units; PCR: polymerase chain
reaction; TNF‑α: tumor necrosis factor‑α; UC: ulcerative colitis.
Authors’ contributions
TH, HK, HTH and MKv conceived the study and designed the experiments. ZD,
DS and MS conducted the experiments. ZD, JM and MKv analyzed and inter‑
pret the data. MKo performed next‑generation sequencing and bioinformatic
analysis. ZD and MKv wrote the manuscript with the input from JM, DS, MS,
HTH and MKo. All authors read and approved the final manuscript.
Author details
1 Institute of Microbiology, The Czech Academy of Sciences, Prague, Czech
Republic. 2 Institute of Microbiology, The Czech Academy of Sciences, Nový
Hrádek, Czech Republic. 3 Institute of Animal Physiology and Genetics, The
Czech Academy of Sciences, Prague, Czech Republic. 4 Institute of Experimen‑
tal Medicine, The Czech Academy of Sciences, Prague, Czech Republic.
Acknowledgements
Patients’ biopsies were kindly provided by Associate professor Pavel Drastich
from Institute of Clinical and Experimental Medicine, Prague, Czech Republic.
We would like to thank Barbora Drabonova and Ivana Grimova, Jarmila Jarko‑
vska and Alena Smolova for their technical assistance.
Competing interests
The authors declare that they have no competing interests.
Ethics approval and consent to participate
The patients enrollment and study procedures were approved by the Local
Research Ethics Committee of the Institute for Clinical and Experimental
Medicine (No. 441/07), and written informed consent was obtained from all
participants.
All animal experiments were approved by both the Animal Care and Use
Committee of the Institute of Microbiology of the CAS and by Committee
for Animal Protection of the Ministry of Health of the Czech Republic. (No.
053/2010 and 050/2011).
Funding
This work was supported by Marie Curie Initial Training Network CROSS‑TALK
(PITN‑GA‑2008‑215553—ZD), by Czech Science Foundation (P304/11/1252—
HTH, P303/12/0535—MKv and 15‑07268S—TH), European Regional Develop‑
ment Fund BIOCEV (CZ.1.05/1.1.00/02.0109—MKo), by Ministry of Health of
the Czech Republic (15‑28064A—MKv) and Institutional Research Concept
(RVO: 61388971). The funders had no role in study design, data collection and
interpretation, or the decision to submit the work for publication.
Received: 15 November 2015 Accepted: 10 December 2015
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